Cancer pagurus the Kattegat and the Skagerrak – implications for sustainable management

Transcription

Fisheries biology of the edible crab (Cancer pagurus) in
the Kattegat and the Skagerrak – implications for
sustainable management
Anette Ungfors
Doctoral thesis in Marine Ecology 2008
Faculty of Natural Sciences
Department of Marine Ecology-Tjärnö
452 96 Strömstad
Sweden
Avhandling för filosofie doktorsexamen i marin ekologi vid Göteborgs universitet. Avhandlingen
försvaras offentligt på engelska, enligt beslut av den naturvetenskapliga fakulteten, fredagen den
13 juni 2008 kl. 10.00 i föreläsningssalen på Sven Lovén centrum för marina vetenskaper,
Tjärnö-Strömstad.
Examinator: Professor Per Jonsson
Fakultetsopponent: Dr. Julian Addison, Centre for Environment, Fisheries and Aquaculture
Science (Cefas), Lowestoft Laboratory, United Kingdom
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Published by the Department of Marine Ecology, University of Gothenburg, Sweden
Anette Ungfors, 2008
ISBN: 91-89677-41-2
Cover illustration: The edible crab (Cancer pagurus) by Helena Samuelsson
Cartoons: Copyrighted by Mark Parisi, printed with permission.
Print: Intellecta Docusys AB, Västra Frölunda 2008
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Till mina allra käraste Niclas, Amanda & Malte, Mamma & Pappa
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ABSTRACT: The European edible crab (Cancer pagurus) is exploited to a varying degree in its
area of distribution. Landings in United Kingdom and Ireland may have peaked around year
2000, reaching 25 000 and 13 000 tonnes, respectively but have slightly decreased since. On the
other hand, landings in Norway have quadrupled in a decade, now reaching 8000 tonnes, which is
due to industrial and governmental funding and subsidies, and an increased northward crab
distribution. Official commercial landings in Sweden are approx. 150 tonnes. Compared to
countries such as UK and Norway the Swedish landings are low but the crab fishery plays an
important role for coastal fishermen along the Swedish west coast earning a living from several
alternative fisheries through out the year.
The research covered in this thesis is focused on management prerequisites for sustainable
exploitation of the edible crab in the Kattegat and in the Skagerrak. I have studied if the present
management strategy (escape gaps) is adequate for a sustainable recruitment, and I have also
investigated key knowledge for management of commercial stocks, the stock structure. I have
also estimated to what degree the stock is exploited and I have performed two independent stock
abundance assessments.
I present data (paper I) that describes at what size female and male edible crab reach sexual
maturity, based on characters as sperm presence, gonad development and morphometric analyses
of abdomen or chela. These data indicated that the present indirect minimum landing size
maintained by escape gaps size is not adequate. A minimum landing size for females need to be
set to 132 mm to allow 50 % of the individuals to be physiologically mature before being fished.
Considering indications that even larger sizes are necessary for spawning, 140 mm CW is a more
appropriate MLS to strengthen the spawning stock. Males were shown to mature at smaller sizes
as 50 % of the males were mature at 120 mm CW. Furthermore small males, despite being
physiologically mature, might not have the same chance for copulation as larger males. For
practical purposes, in addition to the copulation advantage of larger males, 140 mm CW is the
recommended MLS also for males. Therefore the escape gap size needs to be increased to 90
mm, from present 75 mm.
Together with colleagues in paper II I have looked at the migration potential, using markrecapture technique of the crab along the Swedish west coast, as an indication of stock structure.
The potential for crabs to move between geographical areas, is one component of the connectivity
between areas, and a high migration potential indicates high connectivity which may lead to wide
stock distributions and no distinct stock structure. Our study showed a high propensity for
migration among females which in many cases moved distances of 100 km, or even as far as 228
km whereas males most often were found within shorter distances from the release point also
after several years. The direction of the long-distance female migrations >20 km was
predominately towards the south. This southward migration of females may compensate for the
northward larval dispersal with the prevailing coastal current. In Paper III I investigated together
with colleagues the genetic population structure of edible crab stock in Swedish waters using
microsatellite DNA. In this study we found a a lack of spatial and temporal genetic differentiation
between crab stocks in Kattegat, Skagerrak and even up to Ålesund, Norway – a waterborne
distance of 1300 km. Local management of the edible crab can be considered and implemented
whereby stakeholders take a precautionary approach such as implementing landing size
restrictions, not fishing below a certain local biomass or above a defined fishing mortality.
In paper IV we present an estimate of the total abundance of crabs on the Swedish west coast,
based on a combination of experimental fisheries to get effective fishing area and catch per unit
effort data, and GIS modelling of available crab habitat. In a mark-recapture experiment in the
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Koster fiord area we estimated the effective fishing area around crab pots targeting edible crabs
i.e. the area from where the crabs are captured if the pot was 100% effective at catching crabs, to
2293 ± 1137 m2 (mean ± 95% confidence interval), corresponding to a circle with a radius of
26.6 ± 6.3 m. In a separate experimental fishery in the Fjällbacka archipelago (35 km south) we
estimated catch per unit effort at two depths strata (15-18 m and 25-30m) at 7 locations during
two seasons. Using the estimated effective fishing areas around the string we calculated an
average density of 0.0038 ± 0.0015 crabs/m2. The area of suitable crab habitat in the Swedish part
of the Skagerrak and Kattegat, 10 and 40 meters water depth, and with a bottom consisting of
bedrock, stone, gravel or sand, was estimated to 4142 km2. This suitable crab habitat combined
with the density estimates from Fjällbacka would indicate that the catchable population of crabs
on the Swedish west coast would be approximately 10-22 million (95 % confidence interval) of
crabs.
In paper V we assessed stock indicators such as fishing mortality, stock abundance and egg
production. The assessments were based on estimations of growth parameters and resampling of
parameter values in a length cohort analysis (LCA). The fishing mortality of females was larger
than for males both in Kattegat and in Skagerrak. This pattern can be explained by the higher
market price for females, so that fishermen choose female dominated grounds and/or land more
females. Another possibility is that the catchablity of females in general seems to be higher
during the main landing autumn period. The fishing mortality in the investigated area seems to
be low. The stock biomass of edible crabs available for the Swedish fishermen in Kattegat and
Skagerrak is estimated to 4-8 million edible crab or 1600-2600 tonnes. This stock estimate is
based on official data on the Swedish commercial landings and estimated recreational landings,
i.e. approx. 400 tonnes in total, and is highly dependent on the total landings and on the input
values of growth parameter and natural mortality.
The status of the edible crab stock in the Kattegat and the Skagerrak appears to be good. The
fishing mortality is low and no trend (decreasing or increasing) in logbook landing per unit effort
(LPUE) can been seen over the last 13 years. Since 2004, using landing and effort data from
logbooks for vessels > 10 m, the LPUE is on average around 2.0-2.5 kg/pot.
This thesis provides new and increased knowledge concerning the sexual maturity, migration
potential, and genetic population structure of the edible crab in Kattegat and Skagerrak and
provides the first estimates on the total stock based on LCA modelling as well as an stock
estimate using crab density and suitable crab habitat.
Keywords: Cancer pagurus, Swedish west coast, sexual maturity, migration, population
genetics, stock structure, fishing mortality, stock abundance, management
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SVENSK POPULÄRVETENSKAPLIG SAMMANFATTNING
Krabbtaskan (Cancer pagurus) är ett tiofotat kräftdjur som fiskas kommersiellt i stora delar i dess
utbredning i Europa längs nordost Atlantiska kusten. Det största fisket sker på Brittiska öarna. På
ett ungefär landas årligen 20 000-25 000 ton i Storbritannien, 10 000 ton på Irland och 6 000 ton i
Frankrike. Norge har fyrdubblat sin landning över en tidsperiod på 10 år och landar nu över 8 000
ton. Sverige kan i dessa sammanhang betraktas som ett utvecklingsland med officiella landningar
kring 150 ton. Om en skattning av fritidsfisket inkluderas ligger den totala landningen kring 400
ton.
Min forskning har varit fokuserad på förvaltning av krabbtaskan i Västerhavet. Jag har dels
studerat om den nuvarande förvaltningsformen (flyktöppningar) är tillräcklig för att säkerställa
rekrytering till beståndet dels har jag undersökt en viktig grundegenskap för hållbar förvaltning
hos kommersiella bestånd, nämligen dess beståndsstruktur. Med beståndsstruktur menar man att
om det finns olika bestånd som är avskilda från varandra, och på vilken geografisk skala som
bestånden kan urskiljas eller om det inte finns någon egentlig gruppering. Jag har även gjort en
skattning på hur hårt beståndet är fiskat och två av varandra oberoende skattningar av
beståndsstorleken samt en genomgång av Fiskeriverkets loggboksdata.
I manuskript I undersökte jag vid vilken storlek krabborna blir könsmogna. För att ta reda på
detta studerade jag krabbornas ägg- och spermie produktion, och om honorna hade parat sig
genom att se om de hade spermier i förvaringsorganet och om nyömsade honor hade en s.k.
kalkplugg i könsöppningarna. Jag mätte även honornas bakkropp som omfångar de yttre
befruktade äggen, och hanarnas klor som används vid försvar och vid parning. Resultaten visar
att vid en skalbredd om 132 mm har 50 % av honorna äggproduktion (fysiologiskt könsmogna)
men parning sker redan i stor utsträckning vid en skalbredd om 107 mm. Hanar är fysiologiskt
mogna (50 % av individerna) vid 101 mm alternativt 122 mm beroende på hur konservativt man
bedömer en hanes spermieproduktion. Men, det finns tecken på att de honor som verkligen är
könsmogna d.v.s. de har yttre befruktade ägg, är ännu större. Äggbärande honor fångas endast i
litet antal varför det är svårt att basera en undersökning på denna karaktär. Skalbredden på de
äggbärande honor som fångas ligger främst kring 150 mm. För att ge 50 % av honorna en chans
att reproducera sig rekommenderar jag ett minimimått på 140 mm. Detta böra gälla både för
honor och hanar då små hanar kan ha en sämre förutsättning till parning (konkurrens med stora
hanar samt att för parning med stor hona krävs en stor hane). I och med detta bör också storleken
på flyktöppningar justeras till 90 mm, från dagens 75 mm i diameter. I manuskript I har jag även
studerat hur många befruktade ägg en hona av varierad storlek bär på, och vilket uppgår till 0.52.5 miljoner ägg.
Beslutfattande inom svensk fiskeriförvaltning sker vanligtvis från ett uppifrånperspektiv, en art
förvaltas ofta över ett stort geografisk område och tillträdet till resursen är ofta öppen för alla
licensierade yrkesfiskare. Ett alternativ till dagens förvaltningssystem kan vara att införa lokal
samförvaltning där en grupp fiskare och andra intressenter får fiskerätten inom ett område eller
till ett fiske. Nyttjarna får då en ökat ansvarskännande och värnar mer om ”sin” resurs. Men
passar en lokal förvaltning alla bestånd, och vad behöver man veta om artens biologi? Det man
främst behöver känna till, och det gäller egentligen all förvaltning, är hur beståndet är fördelat i
rummet. Består resursen av ett sammanhängande bestånd eller finns det mindre grupperingar som
står för sin egen rekrytering och är oberoende av omkringliggande grupper. I manuskript II har
jag och kollegor studerat hur krabbor vandrar längs svenska kusten. Detta gjordes genom märkåterfångst experiment dels i slutet på 1960-talet dels i början av 2000-talet. Totalt märktes ca
3700 krabbor respektive 8000 krabbor i dessa experiment. Det vi kunde visa var att honor
vandrar betydligt oftare och längre än hanar. Honor vandrade distanser om mer än 100 km, och
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även upp till 228 km medan det största avståndet för hanar var 60 km men ofta kortare. De
längsta vandringarna om 20 km och uppåt är huvudsakligen mot syd. Hanarna vandrade inte i
någon specifik riktning. Honorna vandrade med en högre hastighet under hösten i jämförelse med
sommaren men det var inte någon skillnad i vandringsbenägenhet mellan olika storlekar. Orsaken
till honors vandring tros vara att de vandrar mot den förhärskande strömriktningen innan
larvkläckning för att kompensera att larverna förs med strömmen. I svenska vatten stämmer
denna hypotes till viss del men som vi visar i manuskript II så sker en hel del långvandringar
mot norr, med strömmen. Med hjälp av genetiska analyser kan man få reda på hur genetiska lika
eller olika krabbor är från olika områden. I manuskript III visar vi att det inte finns någon
genetisk skillnad mellan krabbor i Kattegat och i Skagerrak, och faktiskt gäller detta hela vägen
upp till Ålesund i Norge, ett avstånd på ca 1300 km. Detta beror då antingen på att det finns ett
stort genflöde (larvspridning och vandring) mellan krabborna från dessa områden. Det kan också
bero på att krabbor från olika områden inte har hunnit att bli olika i sin genetiska sammansättning
efter att krabborna återkoloniserat Kattegat och Skagerrak efter den senaste stora inlandsisens
reträtt för ca 10 000 år sedan.
Baserat på undersökningarna i manuskript III drar jag slutsatsen att krabbor inte har någon
genetisk differentiering i Västerhavet och kan betraktas som ett genetiskt bestånd. Detta leder
också till man kan förvalta krabban på lokal basis då man inte riskerar att genetisk utarma ett helt
bestånd. Man bör dock ha kommunikation mellan samförvaltningsgrupper så att man har en
översikt på hela beståndet och naturligtvis inte fiska för hårt inom det lokala förvaltningsområdet.
I manuskript IV har jag och kollegor undersökt över hur stor area som en bur fiskar d.v.s. över
hur stort område som en bur täcker för att fånga alla krabborna i buren. Detta gjordes genom att
släppa ut märkta krabbor på olika avstånd (10-160 m) i fyra riktningar runt en bur, och se
proportionen varifrån de fångade krabborna kom. Den effektiva fiske area skattades till 2293 ±
1137 m2 (±95 % konfidens intervall) vilket kan omräknas till en cirkulär area med radien 26.6 ±
6.3 m. I ett annat fiskeexperiment undersökte vi hur stor fångst per ansträngning som fås vid
under olika säsonger, djup och dagar, och med hjälp av den effektiva fiske radien skattade vi
tätheten till 0.0038 ±0.0015 krabbor per m2. Den totala area som krabbor i Västerhavet möjligen
befinner sig på (10-40 m djup, hårdbotten såsom berg, sten, grus, sand) skattades med hjälp av
GIS modellering till 4142 km2. Därmed skattas den totala mängden fångstbar krabba till 10-22
miljoner krabbor.
I manuskript V har jag tillsammans med personal på Fiskeriverket gjort en beståndsuppskattning
av krabba i Västerhavet. Vi har använt en metod som kallas längd-cohort analys som bygger på
att man har kännedom om längdfördelning i den totala fångsten och antagandet att en minskande
mängd av allt större storleksklasser beror på dödlighet. Genom att man vet hur stor del av varje
storleksgrupp som blir fiskade och antagande om hur många som dör naturligt (predation,
ålderdom) kan man räkna baklänges för att få reda på hur många det måste ha funnits i början av
tidsperioden. Sedan summerar man ihop medeltalen för alla längdgrupper och får ett totalt antal
som finns i havet, eller en total biomassa då vi vet hur mycket krabbor av olika storlekar väger.
För den skattade totala landningen på 401 ton har vi skattat beståndsstorleken till mellan 4-6
miljoner krabbor eller 1600-2600 ton. Den könsmogna andelen honor producerar årligen mellan
5-7x1011 ägg men hur stor del av dessa som överlever och ger rekrytering till beståndet har vi
ingen uppfattning om. Med ovan metod kan man också skatta fiskeridödligheten, och vi fann att
denna var högre för honor är för hanar. För båda könen är dock dödligheten från fisket låg, om
man jämför med andra områden i Europa.
Min avhandling ökar kunskapen om storlek vid könsmognad, äggproduktion, vandringspotential,
genetisk beståndsstruktur och mängden av krabba i Västerhavet.
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List of papers
This thesis is based on the following papers referred to in the text by their roman numerals. The
papers are appended at the end of the thesis.
I.
II.
III.
IV.
V.
Ungfors, A. 2007. Sexual maturity of the edible crab (Cancer pagurus) in the
Skagerrak and Kattegat, based on reproductive and morphometric characters. ICES
Journal of Marine Science 64:318-327.
Ungfors, A., Hallbäck, H. and Nilsson, P.G. 2007. Movement of adult edible crab
(Cancer pagurus L.) at the Swedish West Coast by mark-recapture and acoustic
tracking. Fisheries Research, 84:345-357.
Ungfors, A., McKeown, N.J., Shaw, P. and André, C. Lack of spatial genetic
variation in the edible crab (Cancer pagurus) in the Kattegat-Skagerrak area.
Submitted manuscript.
Ungfors, A., Nilsson, P.G. and Sundström, H. Effective fishing area, crab density
and stock abundance of the edible crab (Cancer pagurus) in Swedish waters using
mark-recapture experiment and GIS modelling. Manuscript.
Ungfors, A., and Ulmestrand, M. Stock indicators of the edible crab (Cancer
pagurus) in the Kattegat and Skagerrak estimated by length cohort analysis and
resampling of growth parameters. Manuscript.
Already printed papers are reprinted with kind permission of the copyright holders, Oxford
Journals (paper I) and Elsevier (paper II).
A doctoral thesis at a university in Sweden is produced either as a monograph or as a collection
of papers. In the latter case, the introductory part (the summary) constitutes the formal thesis,
which summarises the accompanying papers. These have already been published or are
manuscripts at different stages (in press, accepted, submitted or in preparation).
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Contents
INTRODUCING CONTEXT OF THE THESIS ................................................................... 11
AIM OF THE THESIS ................................................................................................................ 11
FISHERIES DYNAMICS ............................................................................................................. 12
MANAGEMENT....................................................................................................................... 14
Regulations....................................................................................................................... 14
Management of edible crab stocks .................................................................................... 15
LIFE HISTORY OF THE EDIBLE CRAB ........................................................................... 19
LARVAE AND JUVENILES ........................................................................................................ 19
GROWTH ............................................................................................................................... 20
SIZE AT MATURITY AND FECUNDITY – PAPER I ....................................................................... 22
Histological examination of gonads.................................................................................. 24
LONGEVITY AND NATURAL MORTALITY .................................................................................. 26
STOCK STRUCTURE ........................................................................................................... 26
THE GEOGRAPHIC AREA OF THE THESIS ................................................................................... 26
BACKGROUND STOCK STRUCTURE .......................................................................................... 27
MOVEMENTS – PAPER II ........................................................................................................ 28
POPULATION GENETICS – PAPER III ........................................................................................ 31
SPATIAL AND TEMPORAL VARIATION IN PHENOTYPIC TRAITS ................................................... 33
STATUS OF THE SWEDISH EDIBLE CRAB STOCK ...................................................... 36
DENSITY ESTIMATIONS – PAPER IV ........................................................................................ 36
STOCK ASSESSMENT – PAPER V ............................................................................................. 37
LOGBOOKS ............................................................................................................................ 39
CONCLUSIONS ..................................................................................................................... 42
SWOT .................................................................................................................................. 42
LOCAL MANAGEMENT OF EDIBLE CRAB................................................................................... 44
RESEARCH PERSPECTIVE ........................................................................................................ 45
ACKNOWLEDGEMENTS (TACK) ..................................................................................... 46
REFERENCES........................................................................................................................ 48
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Anette Ungfors 2008
Fisheries biology of the edible crab (Cancer pagurus)
Introducing context of the thesis
Aim of the thesis
With few exceptions marine resources in Europe are today managed either on national or on EU
level. The management unit and the biological definition of a stock may not coincide. In the wake
of failures in finfish management recent initiatives such as local co-management of fisheries,
considering a smaller management area with larger co-operation and responsibility of
stakeholders, are under consideration. However, how compatible is this new approach to the
biological stock concept?
Within the MISTRA-programme SUCOZOMA (sustainable coastal zone management) different
species within the Baltic Sea and on the Swedish west coast have been investigated for the
purpose of local management. In this thesis I have investigated life history traits such as
migration potential and genetic variation of edible crab Cancer pagurus in Kattegat and
Skagerrak (ICES area IIIa) to assess connectivity and stock structure. These are important input
data for evaluating which geographic levels are suited for sustainable management. The edible
crab was chosen because of its potential for an increased interest from fishermen and
consequential increase in exploitation and need of management recommendations, and for being
a marine crustacean species with a different life history, inhabiting a more "open" environment
compared to Baltic fish species.
The thesis has also evaluated if the present management strategy using an escape gap of 75 mm
diameter in fishing gears acts to protect the stock from fishing individuals before reaching sexual
maturity. Today, a minimum landing size is not implemented in the area. This technical
regulation is important disregarding the geographical scale of management unit.
Fishery biological characters such as size (carapace width) and sex of the captures and the catch
per unit effort (CPUE) are important for assessment approaches, and have been sampled in
commercial captures of the edible crab in the fishery area Kattegat and Skagerrak. Based on these
data, stock assessment has been carried out with estimates of stock parameters as fishing
mortality and abundance. Also, we have investigated how different input parameters impact
these. In addition to this modelling approach to estimate abundance, a method using our
experimental estimate of density (independent estimate of gear effective fishing area and CPUE)
and extrapolation over suitable crab area using GIS, is presented.
The topics in my thesis were chosen in the spirit of local management to define stock structure
(paper II and III), and by my identification of maturity analyses (paper I) and abundance
estimates (paper IV and V) as being high-priority research areas for sustainable recruitment of
the stock and a sustainable future fishery. In the coming chapters I will present my results in a
fishery biology context. In this chapter I start by giving a general introduction of the fisheries
dynamics i.e. what is changing over time in a new fishery (effort, stock abundance, gears, skills,
area covered), I then give a an overview of management regulations and a detailed picture of the
fisheries and management of edible crab across its geographic distribution. In the chapter about
“Life history of the edible crab”, I present biological traits of importance to management which I
have been working with. In the chapter on “Stock structure” my methods and findings on this
subject are summarized (paper II and III), and in the chapter on “Stock status” I summarize my
(together with colleagues’) assessments (paper IV and V) and an analysis of the logbooks
(Swedish Board of Fisheries). In the final chapter “Conclusions” I have listed the presence and
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Anette Ungfors 2008
absence of essential knowledge, and the pros and cons (SWOT) of the edible crab biology for
sound fisheries. I also give an overall conclusion on the local management issue. In addition I
briefly present my perspective on a continued edible crab research.
Fisheries dynamics
Nellerman et al. (2008) have recently summarised the impact on the oceans by man. All oceans
show traces of impact or even large environmental changes due to a wide range of human
activities such as destructive fishing methods, pollution and invasion of foreign species.
Reducing the overcapacity is top priority in the EU common fishery policy (CFP). On the
Swedish level there have been an unusually large amount of fishery related issues in the media: a
debated and prized book trying to analyse the causes and the different views of depleted fish
stocks (Lövin 2007), newspaper articles and television panel debates have succeeded, mostly
considering fin fishes as the cod, Gadus morhua. However, in contrast to the finfish fishery, an
optimistic view on crustacean fisheries is often expressed. Crustacean fisheries worldwide are
becoming more important and in 2005 accounted for 6 % of the world capture production by
weight but 26 % by trade value (FAO). Many crustacean fisheries are artisanal, but their
importance from a socio-economic perspective should not be neglected.
The dynamics of a fishery over time can broadly be described as going from a pre-developmental
phase where the news of a potential profitable stock is spreading, to a growth phase where the
fishing fleet and effort is rapidly building up the capacity, and then reaching the fully exploited
stage (Hilborn&Walters 1992). At full exploitation, fishing success has normally declined as
more fishermen compete for the resource, and this decline in fishing success, or management,
may set a further limit on fishing pressure. However, overexploitation and collapse may follow,
especially if governmental subsidies are offered, which decrease the exploitation costs for
fishermen. In an unregulated, open access fishery, effort might expand to the level at which total
revenue equals total cost, called the bionomic equilibrium (Clark 1985). At this stage the growth
of the fleet size comes to an end. Low costs make it possible to keep a fishery at low revenue, e.g.
at biologically overfished stocks, and the more valuable a fishery (high price/cost), the more
intensively it will exploited. But from the fishermen’s point of view the optimum effort level
occurs where the difference between revenues and costs is maximised, often called the maximum
economic yield (MEY). However, to stabilise the fishing effort at MEY requires management
restrictions of the fishing effort, as an open access otherwise may lead to bionomic equilibrium
where revenue equals cost.
Many times the biological knowledge about stocks for which commercial exploitation has only
recently started is low, and the reactions from authorities often come after indications of
overexploitation. Life history traits such as longevity of the species, age at first spawning and
migration behaviour can give an early indication of the risk of collapse of the stock (Perry et al.
1999). In the early stage, the distribution of a fishery is often coastal with relatively short
distances to harbour. The fishery may then evolve to occupy a wider area off-shore, while the
fishing fleet and capacity is increasing. Larger fishing vessels and/or more efficient engines are
often the basis for a wider fishing area. Catch per unit effort is decreasing or taking downward
steps during exploitation but records of increased catches especially for schooling fish before a
collapse are well-known, often claimed to be caused by a narrower distribution of the remaining
fish. The effort in a fishery is not homogenous, neither in time nor in space. The fishing area
covered by the gears is not homogenous in terms of available resource as the substrate and
species composition varies. Local knowledge of fishermen includes empirical experience of
bottom substrate, and knowledge of “good and bad” fishing grounds. The definition of an area as
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Anette Ungfors 2008
good or bad may differ with season and year. In addition, the fishing gears are becoming more
efficient, often through a tendency towards larger gear. However, in a crustacean pot fishery
many smaller pots can be advantageous. The invention of the parlour pot, with an extra room or
safety chamber, resulted in increased catch per pot by increasing the days at sea. Thus by
decreasing the number of escapes and increasing the attraction period, it provided to be profitable
to lift the pots more seldom. This gave the possibility for alternate use of a large number of
strings with pots, leading to an increase in catch per pot and extra revenue after the initial cost for
a larger amount of gear. Comparison of the catch per unit effort in a fishery over time needs to
consider these changes in e.g. effort and allocation of the fishery. In other words, the landing data
need to be standardised. Standardisation can be reached by different means: use of time-series of
research surveys with same gear and effort, research fishing on different habitats to be able to
account for different capture potential, time overlapping use of different gear, or by statistical
methods such as generalised linear models to identify the most important factors and the impact
on capture of those. Therefore, knowledge of the fishermen’s behaviour such as increased skills
and movements between fishing grounds, should be considered to the same extent as biological
studies in fisheries science (Hilborn&Walters 1992).
Crustacean fisheries have shown the different stages from unexploited to a depleted stage often
accompanied with an increase in effort capacity. The fishery for Red king crab (RKC)
Paralithodes camtschaticus in the Bering Sea around Alaska increased heavily in landings in the
1970´s but peaked in 1980 and thereafter more or less collapsed. A combination of high
exploitation rate and increased natural mortality in the late 70´s (Zheng et al. 1995) caused the
collapse in the RKC fishery. This fishery has still a high economic value, but comparing the
59000 tonnes of Bering Sea landings in 1980 with 8200 tonnes in 2005 shows the extent of the
stock decrease. An up and down crab fishery in the Bering Sea have also been seen for the snow
crabs Chionoecetes opilio which peaked in 1991 with 149 000 tonnes, declined thereafter and are
now around 10 000 tonnes. In addition to regulations such as minimum landing size, male only
fishery, pot limits and seasonal closures, Individual Fishing Quotas (IFQ) have recently been
introduced in these fisheries. A RKC fishery is now established in the Norwegian Northern fiords
bordering Russia. The crabs have dispersed into the northern part of Norway from the Murmansk
area, Russia, to which it was deliberately introduced in the 60´s (Orlov&Ivanov 1978). Red king
crabs were observed occasionally in the 70´s in Norwegian waters and a research fishery started
in 1992-93 with few vessels with many restrictions (individual quota, specific season, minimum
landing size, male landing) and mandatory co-operation with the researchers. The RKC have
caused problems as by-catch in the demersal trawl and net fisheries for codfishes. Jointed stock
assessments were performed by Russia and Norway during some years but since 2002 Norway
assess their stock and set their Total Allowable Catch (TAC), based on annual research surveys.
TAC in 2007 was 300 000 crabs, for males only > 137 mm carapace length. The RKC stock and
fishery might possibly have reached highest levels as authorities will try to restrict the crab´s
further southward distribution by a open fishing west of longitude 26°E (Anon 2007b).
The blue crab (Callinectes sapidus) is the base for the most important commercial fishery in the
Chesapeake Bay, USA. Commercial landings in 1993 have exceeded 45000 tonnes with more
recent average landings reaching approximately 36000 tonnes. The total impact of the blue crab
fishery to the Chesapeake region exceeds $200 million annually. In 1998 the Bi-state Blue crab
Advisory group stated that the crab population was not in a healthy condition, based on findings
on decreasing abundance of all age groups, low spawning stock, decrease in average size in
combination with high fishing mortality and effort. The new management framework identified
biomass- and exploitation reference points. Rigorous assessments (Miller et al. 2005) now
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indicate that the stock is not experiencing overfishing as it did for a period in the late 1990’s and
early 2000’s. However, the abundance is still not at former levels.
In addition to changes in the resource abundance caused by fishery, natural variation in
recruitment and mortality also has an impact on the abundance. Natural variation has been
studied using deposition of fish scales in anoxic sediment for e.g. herring and anchovy (Patterson
et al. 2005). Caddy and Gulland (1983) classified exploited stocks into four groups; steady state,
cyclical, irregular and spasmodic, based on abundance pattern. The cause behind these patterns
may be a combination of natural and fishing mortality.
Management
The exploitation of marine resources has resulted in a large number of books and papers filled
with theories and models trying to understand the nature of the resource and the exploitation
effect (Beverton&Holt 1957; Ricker 1975; May 1984; Clark 1985). Models are simplifications of
the real world and the major task is to determine how to simplify without losing the ability to
understand the reality and inform management of options. Parameters of interest such as fishing
mortality and stock size can be estimated, and are used to provide management advice. A major
failure of conventional fisheries advice is that it generally does not explicitly incorporate
important sources of uncertainty. Stock or risk assessment aims primarily at evaluating the
consequences of various harvest strategies for future trends in yields, biomass, and dangers to the
stock (Hilborn&Walters 1992). Another key role of stock assessment is to identify if catch and
effort statistics give a false picture of the population dynamics, and if a more extensive sampling
programme is necessary and worthwhile. Data are collected from e.g. logbooks, commercial or
recreational fishermen’s own notes and from research vessel. Incentives is another management
tool used, such as allowed increased catches or access to other periods and areas for fishermen
spending part of their time “fishing for information”. In assessment models using sex-and size
specific parameters of the catch, catch data collected by co-operative fishermen is essential (in
addition to research surveys) as logbooks are often not that detailed. Risk management on the
other hand, involves finding and implementing management policies, strategies, and tactics that
reduce the risk of over-exploiting the stocks (Hilborn et al. 2001).
Different levels of stock assessment occur: from descriptive statistics on catch, to some findings
of population structure and abundance indices, and to fully analytical risk assessments attempting
to understand the stock and fishery dynamics, and estimating population parameters. A less
informative assessment of a stock leads to a reactive management i.e. reaction from authorities
when CPUE is decreasing or a fishery becomes unattractive for fishermen due to low landings.
However, a more comprehensive assessment provides the means for an optimal management
(Smith&Addison 2003). As a response to declining annual catch rates of Tasmanian rock lobster
Jasus edwardsii from 1.6 to 0.9 kg/pot between the years 1980-1995, assessment and
management have improved (Punt&Kennedy 1997). Stock assessment are performed for eight
regions and the stocks are managed by Individual Transferable Quotas (ITQ), limited entry, gear
restrictions, closed seasons, MLS, bans on working gear at night and on taking berried females.
Recreational fishers are allowed to use a single pot. Adaptive management, which is a
combination of quantitative modelling and empirical management “experimentation”, can be seen
as a mixture of reactive and optimal management.
Regulations
Management of marine stocks involves control of exploitation by limitations in effort (e.g. gear
specifications, days of fishing per boat and year, engine capacity, seasonal closures) or
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limitations in landings (e.g. total allowable catch TAC, individual transferable quota ITQ,
maximum landings per week or season). Regulations can also be based on a minimum or
maximum landing size (MLS), sometimes in combination with a selective gear mainly capturing
individuals over respectively below a certain MLS. Limitation of either nature is based on
knowledge or estimations of how the stock responds to different fishing mortality (F), and
reliable processes to translate the fishing mortality into practical legislation expressed as effort or
yield. To avoid growth overfishing i.e. fishing too small juvenile individuals the fishing mortality
(FMSY) where the yield of the stock is maximised (MSY), is a target to be obtained, or rather a
limit not to exceed. Avoidance of recruitment overfishing, i.e. fishing too heavy on mature adult
individuals which give rise to the next generation, is harder to avoid as the relationship of stock
and recruitment is complex. In both categories, for avoidance of overfishing, a precautionary
approach using precautionary targets (amber warning light) and limits (red light) are used as
reference points e.g. for the fishing mortality (Fpa, Flim) or biomass of spawning stock (Bpa, Blim).
Use of property rights in fisheries management is widely discussed (Shotton 2002; Brady&Waldo
2008). A property right can be in the form of an ITQ (New Zealand), an assigned number of Days
at Sea (Faeroe Islands) or exclusive admission to a fishing area (local management). The
advantage of establishing property rights is that the users may take a larger responsibility for the
future of the resource, avoiding the “tragedy of the commons”. Implementing transferable rights
as ITQ can however lead to fewer and larger vessels if no restrictions are defined. For the Irish
crustacean fishermen, life-time licenses with a chance of transferability to a family member, e.g.
on retirement, guided by a public decision-making committee are recommended so as the
licences would not become commodities (Bradshaw&Tully 2004). In Sweden, the national
authorities are presently investigating a possible introduction of ITQs for the pelagic fisheries. In
addition, license requirements have been introduced for e.g. the shrimp fishery and the Nephrops
creel fishery in order to safeguard the resources and enable economic viability for the fishermen
historically involved in the fisheries concerned.
Marine protected areas (MPA) can be used to protect a habitat as well as the exploited fish and
crustacean resources within. The degree of restriction within the area varies from being totally
protected from any kind of use, to zone (Hiddink et al. 2006) where specific fisheries are banned
and others allowed. The process for implementing MPAs has been diverse, ranging from being a
top-down project (governmental) to a local initiative. The effect of an MPA, especially in
temperate regions, on the resources concerned are widely debated, hence several scientific
programmes are looking into this (Protect at www.mpa-eu.net/; EmpaFish at
www.um.es/empafish/).
Management of edible crab stocks
Crab species have become some of the most valuable fisheries within the ICES North Atlantic
area. As fishing effort has been increasing in recent years there is need for proper assessment and
management advice (ICES 2007). The ICES working group on the Biology and Life history of
Crabs (WGCRAB) has participants from most countries with edible crab fisheries, and collects
data on landings, discards, effort and CPUE as well as recommending standardised methods for
sampling of these data at regular workshops. The focus for the WGCRAB is moving towards
defining appropriate management units and evaluating potential assessment methods based on
data availability.
The distribution of the edible crab is the European Atlantic Coast from Tromsø, Norway to
Portugal (Christiansen 1969 and pers. comm. Astrid Woll). In most parts of the edible crab
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distribution area a minimum landing size is implemented, either of national (UK,
Addison&Bennett 1992; Norway, J-102-2004) or international status (Anon., Council regulation
(EC) no. 850/98). However, the crab fishery in the Swedish territory and economic zone of
Skagerrak and Kattegat is not regulated by a MLS but by mandatory 75 mm escape gaps in crab
pots (figure 1) and in fyke-nets (Council regulation (EC)
no. 850/98; FIFS 2004:36). The Swedish escape gaps
allow crabs of carapace width (CW) below 110-115 mm
to escape (Dybern 1983). In the northern part of
Skagerrak, from the Swedish border to the Norwegian
south west coast (Rogaland) commercial landing of crabs
< 110 mm is prohibited (Anon 2004b).
Figure 1. Escape gap of 75 mm diameter mandatory in
edible crab pots in Sweden. Photo: Anette Ungfors.
Below is a summary of landings, available data, stock
status and management regulations per country, mainly
based on ICES WGCRAB report from 2007 (ICES
2007), if no other reference.
United Kingdom – Landings in England and Wales have increased by an average of 400 tonnes
per year since the early 1980s (ICES 2005). The majority of the landings originate from ICES
sub-areas VIID and E (Western English Channel: approx. 5000 tonnes) and from IVB and C
(North Sea: approx. 4500 tonnes) (ICES 2005). Despite the large landings in England and Wales
the data reporting system of the fisheries is limited especially for the effort. However, the system
has improved from consisting of the official Fishing Activity Database since 1983 with
underestimations of landings and poor effort data, added with EU log-books for vessels > 10 m in
2000 but which were limited in the first years by bias in effort recordings, and further improved
in 2006 with mandatory log-books for vessel < 10 m. The 2006 landing in all stock management
units increased sharply as a result of the mandatory logbooks of smaller vessel. Six stock
management units (SMU) have recently been implemented: Western Central North Sea, Southern
North Sea, Eastern Channel, Western Channel, Celtic Sea and Irish Sea. The fishery effort peaks
during the summer months, which reflects the dependency on weather conditions whereas the
landings peak in autumn-early winter. The fisheries are regulated by minimum landing sizes
specified for different areas (115 mm CW in Norfolk area, 160 mm for males and 140 mm for
females in Western Channel and south eastern parts of Celtic Sea, and 140 mm CW for rest of the
area for males and females). Landings of soft-shelled and ovigerous crabs are prohibited.
Landings in Scotland fluctuate between 6600-9400 tonnes since 2000. The main fisheries are
around the Shetlands Isles and Orkney Islands, and off the northwest and west coasts. The
Shetland fisheries (approx. 300 tonnes) are managed locally within 6 nautical miles. All vessels
must obtain a license from the Shetland Shellfish Management organisation, and the fishermen
are required to fill in logbooks for 5-mile squares. In conclusion, landings in the whole UK is
around 20 000-25 000 tonnes per annum.
Ireland –The crab landings have increased by approx. 650 tonnes annually from 1990 to 2004
from less than 4000 tonnes to over 13 000 tonnes. During this period the annual effort for the area
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has increased from about 28000 to 1 396 800 pot hauls. Excluding the exceptional 2004 landing,
the landings seem to be stabilised around 10 000 tonnes since 2001. Detailed capture records
exist for the offshore segment consisting of 3-5 index vessels from 1990 and onwards. In addition
of precise landing and effort the position is given which mean that changes in catch rate can be
associated with moves in the geographic location of fishing, rather than changes in stock
abundance. The short but intensive periods in a given area have also been used in stock
assessments by depletion methods (ICES 2003). In the offshore area the LPUE has decreased
stepwise from 2.6-2.8 kg/pot in 1990-1992 to 1.3 kg/pot in 2006. This decrease is robust to
changes between years in seasonal and spatial allocation of the fishery (Bell et al. 2005) using
GLM. The inshore data are not of the same accuracy as the offshore data but LPUE have been
falling to a similar extent. Fahy (2002) points at an extended under-estimation in official statistics
of the landings in the south-eastern Ireland. The MLS in Ireland is 130 mm CW (ICES 2004).
France –The annual landings have decreased over the period since 1984, from 7292 to 5423
tonnes, coinciding with a decrease in number of coastal potters. Potters provide 75 % of the
landings and the rest is taken by gillnets and trawlers. The offshore potters land 40% of the total
landings. Since 1985 there exists a relatively good database of fishing activity of this limited
offshore fleet consisting of 15-25 vessels. Over this period the number of offshore potters
decreased but the number of pots/vessel increased from 700 to 1000. The CPUE shows no longterm trend for any area. The French edible crab fishery is regulated by licenses and pot
limitations (maximum 250 pots per fisherman and 1000 pots per boat), which have been in use
for more than 10 years. Parlour pots are banned.
Norway – There has been a fourfold increase in landings of the edible crab during the last 10
years, from 2000 to over 8000 tonnes in 2007, which is a result of directed effort from the
industry to exploit and process this resource but also from an increase in the distribution and
exploitation of the crab towards northern areas. Research projects financed by the government,
community and industry are focusing on market issues such as quality grading by a developed
light penetrating device, quality improvement by artificial feeding and live-storage (Woll&Berge
2007), on resource investigations (Woll et al. 2006) and how to use by-product from processing
(Østvik et al. 2006). From 2001, on research basis and from 2004 and onwards on permanent
basis, contracted fishermen have filled out detailed capture protocols for 4 standard pots during a
10-week period. The pots must be deployed twice a week, and are spread among the rest of the
gear. The fisheries are divided into 5 districts and from where the main landings are taken
between 62° to 67° (area 06 and 07; county Møre og Romsdal, S and N Trondelag and
Helgeland). No obvious trend in LPUE or DPUE (discards) has been found for any of the
southern areas but higher LPUE for the most northern area (area 00 Lofoten and 05 Vesterålen).
The fishery is regulated by minimum landings size of 130 mm CW north of 60° and by 110 mm
south of this latitude. Landings of soft-shelled and ovigerous individuals are banned. Landings in
Skagerrak are under-estimated, as fishermen are not obliged to report the landings to the fish sale
organisation.
Sweden - The edible crab in Sweden is distributed in the Kattegat and the Skagerrak, and is
commercially fished in these areas. The fishery of edible crab in Sweden is small-scale.
Recordings of annual landings based on the trade by first-hand dealers exist from 1914 onwards
(figure 2) and vary between 50-233 tonnes. The high reported landing in 1994 is probably due to
a new license system: for a renewed license the fishermen had to report landings. Many types of
gear capture the edible crab but gears targeting crab and lobster are most important. Gear such as
pots, gillnets or fyke-nets targeting crabs or lobster took 82% of the landings in 2006.
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Figure 2. Swedish edible crab landings in 1914-2007 based on first-hand sales. Source: the
National Statistics Office of Sweden.
Records of annual landings, based on data from logbooks and first-hand dealers over the last
twelve years from 1994-2007 (figure 3), show some cyclic variation between years. Reports from
first-hand dealers (white triangles) are on average 33 tonnes lower than logbook data targeting
crab or lobster (dotted line white squares), and total landings (thick line filled diamonds) on
average 21 tonnes higher than those based solely on logbook data from vessels targeting crab and
lobster. The first-hand value of the 134 tonnes landed in 2006 was 280,000. The fishery is
allowed all year around but most professional crab fishermen fish during July-November.
However, a large unreported amount is taken by recreational fishermen and tourists in summer
months. A recent report on the Swedish recreational fisheries has estimated the crab fishery to
269 tonnes (Anon 2007a). Both sexes are harvested, but as the price for females are higher than
for males, fishermen tend to choose areas where females dominate (higher female frequency in
captures, Ungfors pers. observations). There are few regulations of the Swedish crab fishery. Pots
deployed shallower than 30 m must have one, and crab fyke-nets two, circular escape gaps with a
diameter of 75 mm (FIFS 2004:36, Anon 2004a). Recreational fishermen are allowed to use six
pots, 180 metres of net or six fyke-nets. No gear number restriction exists for commercial
fishermen except a maximum of 600 fyke-nets. The European Union has declared a minimum
landing size of 130 mm CW but excluded the Kattegat and Skagerrak (Council regulation (EC)
no. 850/98).
Figure 3. Swedish edible crab
landings in 1994-2007, based
on logbook data from the Swedish
Board of Fisheries and trade
statistics from The National
Statistics Office of Sweden.
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Life history of the edible crab
Bennett (1995) reviews factors in the life history of the edible crab that influence modelling and
management. He focuses on the 1) reproductive cycle including findings on maturity and the
larvae and the juvenile stage, 2) growth where he discusses sex-specific and regional moult
increment (MI) and frequency, 3) movements, 4) catchability changes based on LPUE over the
year, 5) population structure mainly indicated by size frequency and 6) stock density in the light
of productivity (growth differences), larval occurrence and water currents and adult movements.
Below I present my analysis as well as literature data of life history traits that Bennett (1995)
identified to be important, and which I also have prioritized. However, I have worked with these
traits to a varying degree: most effort has been put into the reproductive trait sexual maturity
(paper I) whereas the effort put into other traits e.g. the larvae dispersal simulation is lower but
presented as it is an explaining factor for genetic population structure (paper III). Earlier
unpublished Swedish data on growth have been analysed in stock assessment paper V. My
findings on migration are presented together with the genetic population structure in a chapter of
its own (Stock structure). Information on catchability is given in the chapter Stock assessment
(paper IV). Literature findings on the longevity, and own calculations, is presented as this is an
important factor in life history, which can indicate the vulnerability of the stock to fisheryinduced mortality (Perry et al. 1999). Stock assessment often uses estimates on natural mortality,
and in paper V I have, together with a colleague, estimated the natural mortality by general life
history based models and presented below.
Larvae and juveniles
The egg development takes about seven to eight months, and during this period the female lies in
the sand, partly buried (Edwards 1979; Howard 1982; Woll 2003). The development of eggs and
larvae is temperature-dependent, and the critical minimum temperature is 8-9°C (Lindley 1987).
The hatching starts at different times during the year for different regions, and closely follows the
pattern of seabed warming above this level. Thorson (1946) found edible crab larvae in the
Kattegat during April to October but in general the eggs hatch during summer months June to
September (Lindley et al. 1993). During the larval development the planktotrophic, pelagic larvae
go through seven development stages; one proto-zoea, five zoeal and finally the megalopa
settling stage (Lebour 1927; Ingle 1981). The larval period is a dispersal phase, but different
opinions exists about the length of the developmental period; lasting for about four weeks
(Edwards 1979), approximately 40 days (Eaton 2005), 60 days as used in a dispersal simulation
(Thompson et al. 1995) or even up to 51-78 days including zoea stage IV for laboratory reared
crabs in temperatures of 15-20°C (Nichols et al. 1982). The developmental period in 10°C are
considerably longer, in total it may take 144 days before reaching zoea stage V (Nichols et al.
1982). Particularly the late zoea stages perform diurnal vertical migration as these are found at
deeper depths during daytime compared to dusk and dawn (Irish studies, ICES 2003) which is
also found for other Cancer species (Park&Shirley 2005).
Simulation of larval dispersal from a release position near Grove Bank in the Kattegat showed an
average dispersal distance of 63 km towards northeast (figure 4) (Jonsson and Ungfors,
unpublished). The simulation of larval trajectories was done using the Lagrangian tracking
software TRACMAS (Döös et al. 2004) using current velocity fields for the years 1980-2005
modeled with the Rossby regional ocean-atmosphere model (RCAO, Döscher et al. 2002).
Dispersal distribution is only based on trajectories ending in areas shallower than 12 metres.
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Anette Ungfors 2008
Simulated larvae were allowed to disperse for 21 days in April-May, at a constant depth of 0.5-3
m. Of 120 000 released larvae 16.7 % settled within grids shallower than 12 m. Studies of larval
distribution have been undertaken around UK and Ireland (Nichols et al. 1982; Lindley et al.
1993; Thompson et al. 1995; Eaton et al. 2003; ICES 2003). Recently, edible crab larvae have
been captured in light attracting traps in Skagerrak (pers. comm. Vidar Öresland, IMR, Sweden),
which is promising for the future research on the ecology of crab larvae.
Figure 4. Distribution of settled larvae in a
simulation of larval dispersal for 21 days from a
release point close to Grove Bank in Kattegat,
based on current velocity fields from the RCAO
model. Only trajectories ending in areas with a
depth shallower than 12 metres were used. The
mean dispersed distance is 63 km, and the main
direction towards NE, to the Swedish coast. Darker
colour means higher density of settled larvae.
Simulation made by Jonsson, P and Ungfors, A.
(unpublished).
Knowledge of the habitat or depth prevalence of Swedish edible crab juveniles is poor but there
are occasional observations of juveniles in shallow coastal areas. Four juveniles of carapace
width 15-61 mm were caught by bottom-trawl in November 2007 at 6-13 m depth among the
brown algae Laminaria digitata and red algae Delesseria sanguinea, Furcellaria lumbricalis
Phycodrys rubens and Corallina officinalis (pers. comm. Anneli Lindgren, TMBL). Monthly dive
collections of Laminaria hyperborea hapterons (holdfasts) in 1991/1992 at an exposed area in the
archipelago in the Norwegian Sea, showed an occurrence of 40 % of crabs in the range of 8-73
mm CW, under the investigated 400 hapterons (Eriksen&Moen 1993). Robinson and Tully
(2000) state that shallow water (8-10 m) cobble habitats represent a major source of recruitment
to offshore fisheries. In these cobble habitats the authors showed settlement of edible crab 2.5
mm in CW in July to September, but larger sized specimen up to 8.8 mm CW were present in the
monthly suction samples taken over one year. In the investigated habitat, the algal cover of
Laminaria species varied between 50-70%. In conclusion, further studies of juvenile crab
occurrence or abundance in Swedish waters should focus on shallow algal habitat, particular
covered by Laminaria species.
Growth
The moulting process determines growth in crustaceans, and the growth rate depends on the
moult increment (MI, increase in size per moult) and the frequency of the moults. Data on growth
increment from Swedish edible crab are based on recaptured moulted individuals in a tagging
experiment (Hallbäck, unpublished) and on moults in pots (own measurements) (figure 5). The
absolute increment of carapace width (mm) increases with crab size as presented in figure 5, up
to sizes around maturity. The decrease in proportional moult (increment to pre-moult carapace
width) are shown for females in figure 6 (right graph).
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Figure 5. Moult increment for females and males. For females, and possibly also for males, the
increment seem to decrease (lesser proportional increment) around 100-125 mm CW. The
increment is around 25 mm per moult for sizes >110 mm. Data come from recaptures in tagging
experiment (Paper II, 1968-73 experiment, increment not presented in the paper) and my
observations on moults in pots.
The inter-moult period i.e. the period between moults, which set the frames for moult frequency,
is more difficult to estimate. Estimation can be based on intensive mark-recapture studies,
observations on moulted proportion per size, observations of laboratory reared juvenile
individuals or size frequency data. Estimates on the inter-moult period by isotopes 228Th/228Ra
in the pre-moulted carapace (Latrouite et al. 1991; Verdoit et al. 1999) have also been tried.
Edwards (1979, and references within) summarise moult frequency based on field and laboratory
studies as: following 3-4 moults during the first year a CW of 25-30 mm are reached, during the
second year and 2-3 moults 50 mm CW are reached. In the third year the crab may reach 70 mm
but further two years are necessary to reach 115 mm. Moult frequency decrease around maturity,
possibly more frequently for females than for males. Females may moult every second year to
allow sufficient condition and energy demands for gonad development and growth.
In paper V we also plotted a discrete growth curve, for a comparison to the continuous growth
based on our estimated von Bertalanffy growth parameters. In this discrete growth curve carapace
width is plotted against age (figure 6) based on the findings on moult increment per pre-moult
CW, and moult per year discussed above. From the MI data we assumed a 25 % increment
increase up to approx. 100 mm CW, thereafter 20 % up to 140 mm, 15 % from 162 mm and 10 %
at ca. 180 and 200 mm. From a carapace width of 140 mm (5.5 years old) we onwards assumed a
moult every second year. Figure 6 also illustrates continuous Bertalanffy growth curve with L
217 and K 0.160 given, which approximately follow the discrete growth curve.
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Figure 6. Left graph show female discrete growth curve based on findings of the moult increment
(MI) with size for Skagerrak and Kattegat (seen in right graph), and of the estimate of moult
interval from Edwards (1979). Right graph show the proportional change (%) in increment to
pre-moult CW for females (same data as in figure 6a). MI data originates from tagging
experiment in 1968-73 (Hallbäck unpublished) and from my moult observations in commercial
pots. Dashed line show the Bertalanffy growth curve for L 217 and K 0.160 (Paper V).
Growth rates have been estimated for the Dungeness crab Cancer magister from size frequency
data: 6-9 moults during the first year after settlement, another 2-5 moults during the second year
and 1-2 moults during the third year (Wainwright&Armstrong 1993). Tagging of C. magister
indicates that older ages moult annually. The probability for annual moult is near one for recently
matured females but this probability sharply decreases above 135 mm CW, and approach zero at
155 mm CW (Hankin et al. 1989). This low probability for annual moults occurs at similar sizes
for males (Wainwright&Armstrong 1993). Growth of C. magister also shows a marked decrease
in moult increment at female maturity size and a less distinct change for males
(Wainwright&Armstrong 1993).
Size at maturity and Fecundity – Paper I
The reproduction cycle of crustaceans is fairly complex. Copulation of the edible crab occurs
when the female recently has moulted, as her shell has to be soft for successful mating. Males and
females are attracted to each other before the female casts her shell, probably controlled by a
chemical substance similar to a pheromone (Edwards 1966). The male is close to the female
during her moult (ecdysis phase) and may even assist the female to escape from the old shell. As
the moult is completed the male will gently turn her onto her back and copulation takes place as
his spermatophores are transferred to both of the spermathecas of the female, located in her
oviducts (Edwards 1966).
After copulation a sperm plug may be produced in each genital opening of the female, seen as
white structures visible with the naked eye. The main purpose of the sperm plugs is presumed to
be to prevent sperm loss and entry of seawater after copulation, and/or to prevent other males
from copulating with the female (Edwards 1979). Fertilisation of the oocytes occurs at the time of
spawning, when the mature oocytes are passing the spermathecas (Charniaux-Cotton&Payen
1988). Sperm from a single copulation may fertilise oocytes in several consecutive spawnings
(Edward 1979). For the spawn to succeed properly, the female needs a soft bottom substrate
while spawning where the eggs are able to adhere to each other and attach to her pleopodal setae.
Probably, females do not spawn every year (Swiney et al. 2003).
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Size at onset of sexual maturity (SOM) needs to be considered in the implementing process of
MLS, and signs of mating activities, gonad development or allometric changes in growth of body
parts in relation to body size have been used to discriminate between juveniles and adults in
Cancridae (Weymouth&MacKay 1936; Edwards 1979; Brown&Bennett 1980; Campbell&Eagles
1983; Orensanz&Gallucci 1988; Orensanz et al. 1995; Hankin et al. 1997; Pinho et al. 2001;
Tallack 2002b).
In my study of sexual maturity (paper I), females were defined as mature if the ovary was in a
developing or mature stage during the autumn season, or if there were indications of mating
activities (presence of sperm in spermatheca or sperm plug of early post-moulted females). For
males, two alternative scenarios for the gonad classification were used: gonads classified as
developing were defined either as immature (scenario 1) or as mature (scenario 2) as there were
definition difficulties with this stage. Morphometric analyses of female abdomen width (AW) and
male chela were also used to define SOM. The proportion of mature females based on the
reproductive characters, ovary development, spermatheca and sperm plug increased with CW.
The CW50, the carapace width where the proportion of maturity is 50%, is 132, 107 and 118 mm,
for each character respectively (figure 7). CW50 based on abdomen width is 104 mm, with
indications of a change in growth pattern at 95-104 and 125-139 mm CW. The proportion of
mature males increases with CW, and the CW50 is 117 mm if the developing gonad is considered
immature (scenario 1) and 101 mm if considered mature (scenario 2). CW50 based on chela
morphometrics is 122 mm.
Figure 7. Size at maturity ogives (proportion of mature at different carapace widths) for female
edible crab in the Kattegat and the Skagerrak (Paper I).
Size at sexual maturity of female edible crabs in Skagerrak and Kattegat is concordant with
results from maturity studies in other European areas. A report from the ICES study group on the
crab biology and life history points at 130 mm CW as the size of maturity for female edible crab
in the North Sea (ICES 2003). Findings on size at sexual maturity (CW50) based on gonad
development from different regions are given in table 1. CW50 of females based on gonad
development is around 130 mm (as I found for Kattegat and Skagerrak) in Ireland and Shetland
whereas smaller maturity size is estimated for e.g. UK and Norway. However, the size
distribution of ovigerous females (Hallbäck, H unpublished data, inter-quartiles q25=142,
q50=152, q75162 mm, min=109 mm) in Skagerrak and Kattegat, and other European areas
(Pearson 1908; Brown&Bennett 1980; Woll 2003), indicate that most females do not spawn until
yet another moult. The smallest observed ovigerous female on the English East Coast is 129 mm
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Anette Ungfors 2008
CW, but out of 200 the main part of ovigerous females was larger than 152 mm (Edwards 1979).
It seems that copulation is established at around 110 mm CW, physiological maturation one
moult later (at around 130 mm CW), but that fertilisation needs yet another moult, and occurs
around 150 mm. This means that physiologically mature females are vulnerable to the fishery
another 1-2 years before becoming functional mature.
To avoid recruitment overfishing, a minimum landings size needs to take into account that we do
not have enough data on the size frequency and CW50 of ovigerous functional mature females.
Therefore, a precautionary approach setting the MLS above the CW50 of gonad physiological
maturity indices, is recommended. Males are functionally mature at smaller sizes but possible
limitations for these small males to copulate successfully with larger females may occur why the
same carapace width for both sexes can be used. This is most practical when escape gap on the
pots should be optimized for the MLS.
Table 1. Size at Maturity – CW50 in different areas within the edible crab distribution.
Area
Males
Females
Comment
Reference
UK
Vas deferens/Ovary (Lawler&Addison
North Sea
88.9
108.5
2005)
Western Channel
94.9
113.7
Eastern Channel
104.9
125.9
Shetland
110-114 130-134
Vas deferens/ Ovary (Tallack 2002a)
Ireland
Vas deferens/Ovary (ICES 2004)
North
112.5
132.6
SW
109.7
138.4
SE
116.8
135.7
Ireland, SW
110
127-139
Vas deferens/Ovary (Edwards 1979)
Norway
113.9-117.8 Ovary (macroscopic) (Woll&Emblem
111.8
Ovary (microscopic) 2005)
France, Bay of
102
111
Vas deferens ovary/ (Le Foll 1986)
Biscay
(microscopic)
Fecundity analysis was performed for 39 females sampled in Kattegat and Skagerrak (paper I).
The fecundity, calculated as number of fertilized eggs, increases with female carapace size in the
size range of 113-190 mm CW (figure 8). In this size range the fecundity is between 0.5-2.5
million eggs. Dry weight of egg mass to body mass ranged between 5 and 28 % (average 13 %,
SD ± 5). The egg diameter (m) was independent of the number of eggs per batch or female
carapace width.
Figure 8. Fecundity of female edible crab in
the Kattegat and the Skagerrak (n=39)
(Paper I). A larger female carry more
fertilised eggs.
Histological examination of gonads
Macroscopic gonad classes can be, especially the juvenile and adult undeveloped classes,
classes
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Anette Ungfors 2008
difficult to discriminate. In addition, the classification can be dependent on the observer. For this
reason, histological analyses of the gonads in relation to the macroscopic classification were
tested (Sjöström 2003). This study was the Master thesis of Elisabeth Sjöström, under
supervision of Lillemor Svärdh and me. The objective of this study was to use histology, to
classify the development of the gonads in female edible crab into maturity indices. In addition,
we analysed if the macroscopic visual judgement of the gonad maturity reflected the
physiological maturity of the ovaries. The gametogenesis (gonad development) of the females is
divided into three main phases: the previtellogenesis and primary vitellogenesis which are
continuing processes during the reproduction life of the female; and the secondary vitellogenesis
which takes place during the reproduction season (Charniaux-Cotton&Payen 1988; Krol et al.
1992). By studying these phases six histological maturity indices were created (A, B, C, D, E and
F). The histological indices A to E indicate a gradual development from the previtellogenesis to
the late secondary vitellogenesis stage whereas F is a resting stage. Male crabs in the
macroscopic group “developing” were histologically analysed, searching for sperm production of
the testes, and sperm storage in the collecting tube and vas deferens. This group is critical,
because it is difficult to macroscopically determine the maturity stage of the gonad (scenario 1
and 2 in paper I). In total, six macroscopic classes of the female gonad (n=13, in totally 78
samples), and 20 replicates of developing male gonads (three organs per individual, in totally 60
samples), were analysed. The samples were paraffin-embedded and stained by haemotoxylineosin, and analysed under light microscope. In addition to maturity indices, the mean oocyte area
(n=5) was calculated for the female samples.
An increasing oocyte area in maturity indices C-E was observed indicating a change in
physiology. The distribution of maturity indices differed statistically between groups
macroscopically determined as primary (class 1/5) and secondary vitellogenesis (classes 2, 3, 3+,
respectively) (figure 9). The figure 9 is a modified classification of Sjöström (2003), where I have
re-classified some individuals e.g. to the resting stage F. However, macroscopic determined
groups close in maturity stage did not differ in distribution of maturity indices, but they did differ
in oocyte area. All males were physiologically mature.
Figure 9. Distribution of histological
maturity indices A to F of the
macroscopic female gonad classes 1
to +3. The classification is a modified
version of Sjöström (2003).
The most important result from this study was that the histological analyses gave insight into the
gonad development at the cellular level of both females and males. Therefore, I had better
confidence in the forthcoming macroscopic classification, on which most of paper I rest. The
macroscopic classes 1, 1/5 and 2 are regarded as undeveloped immature stages whereas classes 3,
3+ and 5 are regarded as mature. For males, the macroscopic three grade scales (immature,
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Anette Ungfors 2008
developing, mature) were still used despite the fact that I now knew that the mid class was
physiologically mature.
Longevity and natural mortality
Sheehy and Prior (2005) estimated chronological age and corrected for thermal differences on the
basis of cohorts modes of neurolipofuscin concentration frequency distributions (NCFD) for
different areas with different mean temperatures, and not by use of individuals of known age
reared in laboratory (Belchier et al. 1998). They showed that longevity varied inversely with sea
temperature: longer life at the cooler East coast of UK compared to the warmer English Channel
but the average maximum life span is around 10 years for edible crab within UK (Sheehy&Prior
2005). 95% confidence interval for age determinations of 1, 7 and 15 years are: 0.6-2, 5.2-9.7 and
11.8-19.7. In paper V we estimated the age of a large sized edible crab of 200 mm CW, using the
L 217 and K 0.160 as in figure 6, to 19.2 years.
The importance of an accurate estimate of natural mortality is well known in fisheries
assessment, and well known is the difficulty estimating it. A review of six common methods for
estimating natural mortality (M) is given in Quinn and Deriso (1999): 1) catch curve analysis, 2)
length frequency analysis, 3) mark-recapture experiments (Siddeek et al. 2002; Frusher&Hoenig
2003), 4) collection of dead organisms, 5) fitting population models and 6) meta analysis of life
history. An alternative to estimations of natural mortality especially in data-poor populations is to
use estimations for the same species but in other regions, or from other species with similar life
history (alternative 6 above). This value is of course dependent on the accuracy of that estimation
and how similar the taxa life histories are. General formulas, relying on parameters such as age at
maturity, longevity, body size, L and K, often measured in biological studies, have been
established (reviewed in Hewitt et al. 2007). We estimated (paper V) natural mortality from
Pauly (1980) formula using L, K and mean habitat temperature, to 0.26 and using Rikther and
Efanov formula (1976) based on age at maturation, to 0.18-0.34. Sheehy and Prior (2005)
estimated natural mortality to 0.45 for males and 0.39 for females in UK East coast, based on
Hoenig (1983) general formula using the oldest 5% for the average longevity.
The natural mortality is caused by predation on juveniles and sub-adults by codfishes and wolf
fishes and by sea birds such as herring gull (own shell observations at skerries during summer).
Hallbäck (1998) analysed the stomach content of fishes, and from this study it was shown that
almost 50 % of the wolf-fishes Anarhichas lupus had pieces of edible crab <100 mm CW in their
stomachs. Pieces of edible crab were also found in stomachs of cod Gadus morhua. Larger crabs
are more safe to predators but on the other hand mortality caused by moult, inter-actions in
mating activities and age senescence may increase with age.
Stock structure
The geographic area of the thesis
The climate of the studied geographic area has changed over time as the Northern Europe have
repeatedly been covered by ice to varying degree during Pleistocene era (1.8 Mya-10 kyr) of the
Quaternary period: the British and Scandinavian ice sheets, respectively, covered land and shelf
edges (~200-400 m depths) during glacial periods 500 000 years ago to that the last ice age
melted around 9000 years ago. The ice sheets were possible confluent during last glacial
maximum (LGM) approx. 20 000 ago i.e. ice covered central and northern North Sea region
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Anette Ungfors 2008
which otherwise seem to have been ice free (Sejrup et al. 2005). The South Western ice limit of
the British ice sheet is not fully agreed on but the northern parts of the Celtic Sea was covered.
This knowledge is good to have in mind reading the about the population genetic structure
(paper III) in this chapter.
The postglacial oceanography of Skagerrak, i.e. from 14 kyr to 8 kyr, is described by
Gyllencreutz et al (Gyllencreutz et al. 2006). The ice margin, drainage and the circulation in
Skagerrak and adjacent basins are presented in four time-slice maps covering the basal changes
during this time period. During this time the present anti-clockwise circulation and the marine
conditions has been strengthened mainly due to an increased impact from Atlantic marine water
inflow and the North Jutland Current. A calving ice front was present in the northern and eastern
flanks of Skagerrak while the ice was retreating 14.0 kyr ago; a northward freshwater current
from the Baltic Sea existed already 14.0 kyr ago but thereafter changed in strength. At 11.2 kyr
glacial meltwater from Närke strait reached Skagerrak trough outlets on the Swedish west coast
(Otteid-Stenselva, Uddevalla and Göta Älv outlet). The modern circulation system was
essentially established at 8 kyr when the eastern North Sea coastlines had attained present
appearance. In the presentation of paper IV below and in the logbook part, the effect of the
calving ice fronts and the moraine deposits upon the edible crab density can be seen in the
geographical landing distribution.
Even on a shorter time-frame it is obvious that the climate in northern Europe and particularly in
the North Sea is related to the warm and saline Atlantic waters to the region. This can be seen in
“The Medieval Warm Period”(MWP) (AD 700-1350) during strong Atlantic water advection and
“The Little Ice Age” (AD 1350-1900) probably caused by weaker Atlantic water advection. The
oceanography of Skagerrak during the last 2000 years, has been analysed by sediment cores from
different locations within and outside Skagerrak (Hebbeln et al. 2006). At AD 900 during the
MWP an increase in the to Skagerrak inflowing bottom current occurred (and which is still
persistent), explaining the seen lowered surface salinity as an increase of regional North Sea
evaporation and a consequential continental precipitation (Hebbeln et al. 2006).
Today the prevailing surface current along the Swedish west coast is northward (Rodhe 1996).
The baroclinic northward coastal current (the Baltic current) is more pronounced in Skagerrak
than in Kattegat due to 1) the Kattegat-Skagerrak front forcing this low-saline water to contract
along the Swedish coast, 2) as a result of the basic cyclonic current around the Skagerrak and 3)
the often strong westerly currents towards the Swedish coast from north Jutland
(Gustafsson&Stigebrandt 1996). The surface salinity is gradually decreasing in Kattegat possibly
limiting crab larvae survival, and the reduction in salinity also penetrates deeper down negatively
impacting adult edible crab.
Background stock structure
A prerequisite for resource management of commercially exploited fish and shellfish species is to
define how the resource is partitioned, spatially (geographically) and temporally, i.e. to identify
stock units. As for species and population concepts there is no universally accepted definition of
what constitutes a stock and there has been a shift towards an adaptive holistic approach
admitting the use and need for several purposes (Begg&Waldman 1999; Carvalho&Hauser 1999;
Waples&Gaggiotti 2006; Abaunza et al. 2008). All attempts of stock definitions struggle with
optimizing a balance on precision and generality, and common words in the definitions are “selfsustaining”, “integrity/sharing”, “spatial/area” and “temporal/time” (Cadrin et al. 2005). In
contrast to the species or population concept, there is an underlying meaning of management in
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Anette Ungfors 2008
the stock definition. Different methods to investigate the stock unit have been suggested, which
all have their strengths and weaknesses and often reflect the definition chosen by the investigator.
The advantage of using a holistic approach is that one of the techniques may detect stock
structure where others fail to do so. For example, morphologic or phenotypic traits for stock
identification can be biased by environmental modulation so that separate stocks may be
indistinguishable due to similar selection effects while at the other end of the spectrum
directional selection may lead to false estimates of stock heterogeneity.
Genetic markers are powerful tools for describing population/stock structure (Utter 1991 ;
Carvalho&Pitcher 1995). A major benefit of population genetics to fisheries management has
been to define the concept of ‘stock’ in an evolutionary meaningful way, and to promote the use
of this concept in management (Ihssen et al. 1981; Allendorf et al. 1987; Carvahlo&Hauser
1994). While gene flow is expected to promote genetic homogeneity, populations that are not
exchanging genes are expected to acquire differences in frequencies of genetic variants over time
by genetic drift. Therefore, by characterising the distribution of genetic variation, population
substructuring can be detected and the degree of connectivity among populations estimated
(Nesbo et al. 2000; Ruzzante et al. 2000; Hutchinson et al. 2001).
Movements – Paper II
The dispersal ability of a species is related to that species’ population structure (Bohonak 1999),
so that higher dispersal ability in general is associated with decreased differentiation, e.g. as
measured by genetic distances, among populations. Consequently, knowledge of the dispersal
processes during the entire life cycle of a species i.e. larval dispersal and the juvenile/adult life
style may give an estimate on the geographic distribution of a population and the connectivity
among populations (Jennings 2001; Hellberg et al. 2002).
The dispersal potential of larvae depends on the biology of the species (e.g. larval type, larval
development time, hatching season and vertical migrations), and on the regional oceanography
(e.g. directional currents, topographic gyres and cross shelf currents) and hydrological parameters
(temperature, salinity). The distance of dispersal as an adult differs according to the life-style:
benthic and sessile, benthic and non-sessile, or pelagic. A non-sessile species has the potential to
disperse over geographic areas, also as an adult. At the extreme, larval dispersal and adult
movement can interact and result in a high dispersal, or counter-interact and result in a relative
low gene flow despite high dispersal potential for both larvae and adult.
To be able to manage exploited resources such as crabs it is important to have knowledge of how
e.g. fishery in neighbouring or even distant areas impact the area in question. A limited larval
dispersal and/or limited adult movement decrease the connectivity between areas, which opens
for self-sustaining and in the long-term genetically heterogeneous stocks. In this case recruitment
comes from within the area i.e. the area are vulnerable to the exploitation within the area and to
less extent from outside. This situation, if exploitation is too severe, can lead to collapse of the
resource and extinction of this genetic stock. However if exploitation is optimised yield can be
high. Larger larval and adult dispersal make the stock structure less distinct and areas can work as
recruitment sinks or sources, or both, complicating the management strategy. On the other hand,
this stock structure is spreading the risks of collapse and extinction i.e. not all eggs are put in one
basket.
In paper II we report the movement pattern of sub-adult and adult edible crabs on the Swedish
west coast. We present previously unpublished data from a tagging experiment in the late 1960s
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Anette Ungfors 2008
and movement data from a recent tagging experiment in 2003. The recent experiment use other
areas for release compared to the initial but also one area in common. Acoustic tracking of males
was also performed in 2005 to gather information on short-term movements. We specially
investigate sex-specific differences in distance, direction and rate of movement, and analyse
whether migration occurs seasonally, and whether it is size-dependent. Also we investigate the
movement pattern of repeatedly recaptured individuals. The movement pattern is compared
between areas and between studies i.e. 1968-73 and 2003.
Three marking methods were used in the mark-release experiments: The crabs in the initial
experiment were marked with numbered plastic discs posteriorly attached by a braided terylene
thread through two pierced holes in the carapace epidermal suture. In the recent experiment t-tags
were inserted through a 2 mm drilled hole in the epidermal suture, and eight cm numbered plastic
bands hung out and could be externally observed (figure 10, left). This type was used at the
offshore and inshore Kattegat area. Black cable ties with yellow numbered discs tightened around
the merus segment of the 1st periopod (claw) were used as a mark in the Skagerrak (area
Strömstad and Fjällbacka) and the northern Kattegat (area Tistlarna) (figure 10, mid). The
tagging procedure took mainly place aboard the fishing boats directly after capture and the crabs
were released within two hours, in close vicinity to the place of capture. In total 3749 crabs were
released in the initial experiment, from three Skagerrak locations, and of these 33 % were
recaptured. In the recent experiment 8110 crabs from five locations were released, and 8 % of
these were recaptured. In addition, nine males were tracked by the use of acoustic tags in 2005
(figure 10 right). Distance and direction of movement of recaptured crabs were calculated in the
GIS programme ArcView 3.2.
Figure 10. Tagged crabs with floy t-tags, cable ties and acoustic tags. The tags were used in the
mark-recapture experiment in 2003 and acoustic tracking in 2005 (Paper II).
Photo: Anette Ungfors.
Females moved on average 6.4-21.7 km and males 1.5-8.8 km (averages within different areas,
table 2). Female long-range movements > 5 km were predominately towards north and south
from Strömstad, Fjällbacka and inshore Kattegat; towards south from the Brofjorden, Lysekil and
Tistlarna and towards east from the offshore Kattegat release area. For males the direction pattern
was uniform in most cases: e.g. the location Strömstad, Brofjorden, Tistlarna and inshore
Kattegat did not differ from a uniform distribution in long-ranged movements. 78 % and 62 % of
the female movements longer than 20 km from coastal areas were towards south, whereas 22 and
33 % were toward north and less than 5 % in eastward or westward direction (initial (ntotal=162)
and recent (ntotal=58) study respectively). In the initial experiment females moved longer
distances in October and November compared to July and August, and in the recent experiment
the crabs moved longer distances in August compared to June. There was no difference in
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Anette Ungfors 2008
movement distance between different sized females or males in either of the experiments. The
rate of movement within six months was significantly higher than rates of crabs recaptured after a
longer time period and females moved faster than males in both the initial (1968-73) and the
recent (2003) experiment.
Table 2. Migration distance per area for a) the1968-73 study and b) the 2003 study (paper II).
a) 1968-73 study
Fjällbacka
Brofjorden
Lysekil
b) 2003 study
Strömstad
Fjällbacka
Tistlarna
Katt Insh
Katt Offsh
Females
Mean±SD
Median
12.6±23.1
13.4±20.7
13.3±24.2
2.5
5.9
2.8
0.8-10.6
2.2-11.5
1.2-10.1
137
117
228
32
12
0
38
9
1.5±4.1
3.4±5.9
2.1±5.0
12.6±21.2
11.6±17.7
21.7±22.7
16.2±17.1
6.4
5.2
3.5
7.7
12.1
3.5
2.3-10.8
0.9-17.2
6.0-43.3
3.9-18.1
1.5-5.6
130
121
71
72
44
11
1
12
35
38
15
6
3.2±4.4
4.9±11.4
3.2±1.9
8.8±11.1
3.9±6.0
q25-q75
max
n
Males
Mean±SD
Median
q25-q75
max
n
0.6
1.4
1.1
0.1-1.7
1.0-2.7
0.3-2.4
36
28
60
197
22
193
1.7
0.6
3.5
2.6
2.5
1.0-3.1
0.2-3.3
1.1-4.7
1.21.5-3.8
18
59
6
32
40
38
77
13
13
80
Several hypothesis to explain migration patterns for Cancer spp. have been presented: inshore
migration for moulting, mating and spawning, and offshore hatching migration
(Diamond&Hankin 1985), migrations toward exposed area for spawning (Smith&Jamieson
1991), mating migration or pre-hatching emigration to avoid osmotic stress (Orensanz&Gallucci
1988) of C. magister, feeding migration in C. novaezelandiae (Chatterton&Williams 1994) and
female migrations related to moulting and mating in C. pagurus at the north east coast of
Scotland and England (Mason 1962; Edwards 1979). The extensive westerly or south-westerly
migrations in the English channel (Bennett&Brown 1983; Latrouite&Le Foll 1989) are against
the prevailing eastern-directed Channel current (Dahlgaard 1995; Guegueniat et al. 1995).
Bennett and Brown (1983) point out that this may be an offshore migration towards grounds
suitable for spawning and/or counteracting larval drift, and therefore having consequences for the
replenishment of eastern stocks in the Channel. Robinson et. al. (2003) found strong indications
of return movements of tagged edible crabs from the North west of Ireland. A large bulk of the
recaptures (recovery rate approx. 37 %) moved north and westward to the continental slope but
later south and eastward, back towards the release area. The crab movements from the south east
of Ireland did not follow the hypothesised pattern of a against current movement but rather the
opposite (Robinson et al. 2003). Northward movements of female crabs along the English east
coast have been concluded by many investigators (reviewed in Edwards 1979), and a southward
larval drift impacting recruitment further south have been assumed until recently. Eaton et.al.
(2003) review larval investigations in the area and point at an aggregation of zoea I larvae
offshore, south east of a front system separating areas to the north and south of a circulation gyre.
This finding challenge the belief in that crab fishery in the south is dependent upon northerly
spawning areas, and state that the offshore Dogger Bank may be a separate self-sustaining stock.
The prevailing surface current along the Swedish west coast is northward (Rodhe 1996). A
northward dispersal of pelagic larvae could be the underlying reason for the observation that
adult females predominantly migrate toward the south when distances over 20 km are considered.
Dispersal of crab larvae for two months by a one-directional current of 0.20 m s-1 mean velocity
(Rodhe 1996) move the larvae more than 1000 km downstream of hatching location. This
distance is certainly a substantial overestimation of the true dispersal as the direction of currents
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Anette Ungfors 2008
may change on daily basis and larval swimming behaviour, not least vertical migration
(Harding&Nichols 1987; Park&Shirley 2005), will impact the realised dispersal distance. In our
larvae simulation for 21 days (see Life History Chapter) the mean larval dispersal was 63 km, and
most of the larval dispersal was to northeast, towards the Swedish coast from the offshore release
spot in Kattegat (figure 4). Female adult migrations from offshore Kattegat were commonly
towards E or NW. However, the calculation and dispersal simulation may indicate the need for a
evolved behaviour, such as the upstream migration of females prior hatching or larval swimming
behaviour (Shanks&Brink 2005), to guarantee continued recruitment along the Swedish coast.
Several mark-recapture experiments in Norway have been undertaken. Gundersen (1977)
conducted experiments around Bergen and concluded that females moved more frequently than
males, the major part of the movement were in southerly direction against the residual water
movement and the longest distance moved was 37 km but most of the recaptures were taken
within one year. Woll (1981; 1995) marked crabs offshore and in the fiord system around
Midsund (N63°), mid Norway. The recaptures in these studies showed that females moved longer
distances whereas males were more stationary. The offshore recapture rate was low but a single
female, which moved longer than 1 km from the release area, moved towards southwest against
the prevailing current. However, recaptures in the fiord system, with deep depths (200-299 m) to
the south, were towards east or north east. Karlsson and Christiansen (1996) observed and tagged
edible crabs in shallow areas below 5 m depth on a rocky islet on the southern Norwegian coast
in Skagerrak. Edible crabs were not observed before May in this shallow habitat but then the
authors clearly showed that the crab had a diurnal vertical movement as they observed many
more crabs on their night dives compared to the day. The size of the crabs ranged from 50-190
mm CW, with an average of around 120-130 mm. Besides interesting findings on short term
vertical feeding movement, Karlsson and Christiansen (1996) also found that males were more
prone to stay in the area whereas females moved away to a larger extent. None of the males
moved more than 3.5 km away but females were recaptured up to 28 km from release point. 61 %
of the female movements were towards northeast (towards the Oslo fiord, against the prevailing
current) and 39 % towards southwest.
Population genetics – Paper III
The basic methodology for population genetic analyses is that individuals are sampled from
different potential stocks, and the larger the genetic variance between samples the more distant
their genetic origin. To diminish the risk that the marker is under selection or that the alleles are
inherited in a non-Mendelian manner, several loci of the same marker or several marker types
need to be used.
In general, marine species are expected to show weak population structure over large geographic
areas due to fewer physical barriers, compared to land, and high dispersal ability via larval drift
and/or adult movements (Ward et al. 1994). However, intra-specific genetic analyses of
commercial decapods have revealed complex patterns of genetic differentiation at various
geographical scales. Thus, the genetic structure of marine species is determined by the complex
interaction of several factors including adult mating and pre-spawning behaviour, larval
development time and behaviour, oceanography and its seasonal and annual variation, and must
be empirically examined to inform management.
Sampling of individuals for genetic analysis (paper III) was performed at two different
geographic locations within the study area and during different years in order to study the genetic
allele variation on a geographic and temporal scale. In addition, a Norwegian sample from
outside the area was analysed. 70 individuals were sampled at each occasion. The sampling of
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crabs in Kattegat was performed in 2001 and 2007 at Groves bank (N57°06, E11°31), and
samples from Skagerrak were obtained in 2002 and 2006 at Lunneviken (N59°03, E11°10). The
third “outside area” location, a coastal location in the Norwegian Sea Norway called Midsund
(N62°40, E06°40), was sampled in 2004. Eight microsatellite DNA loci were amplified with
PCR. Screening and statistical analyses were by common methods, described in detail in Paper
III.
The spatial and temporal genetic differentiation of edible crab is low within 1300 kilometres of
waterway distance in the investigated area. This conclusion is supported by i) low global
multilocus FST of 0.002 and non-significant single locus FSTs using allele frequencies, ii) nonsignificant global FST, single locus FST and pair-wise comparisons using genotype frequencies,
(iii) no genetic differentiation among groups in AMOVA and (iv) that statistical power analysis
suggested > 93 % power for our sampling design to detect an overall genetic differentiation of
FST 0.002. Altogether, these results suggest that the genetic variation over a 1300 km water
distance, from the basin of Kattegat at 57°N to the Norwgian Sea 62°N is very low. The cause of
this low genetic variation, between groups of individuals over 1300 of kilometres, can be by a
high gene flow or caused by large and young stock in the areas under low genetic drift, further
discussed below.
Firstly, the lack of spatial genetic differentiation can be explained by a high gene flow over large
areas. Female edible crabs are capable to move 100´s of kilometres and the pelagic larvae can
disperse over long distances. A hypothesis explaining the pattern and cause of migration of
females states that migration is directed towards the prevailing surface current to compensate for
larval dispersal (Bennett&Brown 1983). This migration pattern opposite to current direction is
valid for some areas, but not for all. Mark-recapture experiments in Kattegat and Skagerrak
(paper II) demonstrated a large fraction of long southerly directed migrations of females from
some coastal locations, thus against the coastal northward surface current, but also long
migrations both northward and southward from other locations. There is a lack of knowledge
concerning return movement or natal homing behaviour for the edible crab, which is described
for other species in connection with spawning. But there are some observations indicating return
movements for the edible crab (Robinson et al. 2003 and paper II), which could explain the
northward migrations according to the hypothesis. If the above hypothesis is true, this could
result in local genetic populations as the larval dispersal is compensating for the adult migration.
Though, the results in this study indicate that adult migratory behaviour vs. oceanographic
currents does not genetically structure the population in this area, undermining the above
compensating hypothesis. Adult and larval drifts seem to cause high gene flow, diminishing
genetic variation over a large area.
Secondly, the low genetic differentiation among the individuals within the studied geographic
area may reflect historical gene flow persisting among recently founded large populations. The
edible crab distributed in Kattegat, Skagerrak and mid Norway at present could have been recolonised from an area south of British ice sheet e.g. English channel – Bay of Biscay or possible
from a refuge in the North Sea. In this case, the time that has past is likely insufficient for genetic
differentiation based on genetic drift. This especially applies for a large population typical of the
edible crab (high density, high fecundity), as opposed to a small population where bottlenecks
and stochasticity can change the allele frequencies over time to a larger extent.
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Spatial and temporal variation in phenotypic traits
Phenotypic traits can be used as an indication of stock structure. A variation in a phenotypic trait
between crabs from different fishing grounds may indicate a reduced stock interaction between
different grounds. However, the variation in the trait can be caused of differences in the
environment such as temperature, food and predator availability, or by differences in the density
of edible crab. I was interested to investigate if the traits size distribution and moult cycle of
edible crab differed at geographic locations. The moulting of adult edible crab takes place during
summer-autumn but anecdotal evidence suggests that there are spatial differences in the timing of
moult. The size data are also used in stock assessment (paper V), in addition to the purpose of
using size frequency for stock identification. To sample this detailed fishery biological data,
which is not acquired by the logbook system I involved fishermen for data sampling in 20022004. In order to investigate a wider size frequency, three pots without escape gaps were given to
each of 15 commercial crab fishermen. In addition to the standard pot, the fishermen would use
three pots of their own design normally used in the commercial fishery. The reason to use the two
gear types was to study the impact of the escape gap on the capture. The fishermen were told to
record sex, carapace width measured to nearest mm and the moult status of the crab would be
classified to a four-grade scale separating Newly moulted, New-moulted some time ago, Intermoult of good quality and Degrading carapace. The fishermen were informed to use the standard
pots within a normal string at their common fishing grounds and that they would measure the
capture every time or a minimum 1-2 times per months. Except for the possibility to sell the
capture in the additional pots each fisherman was given about 100-150 per year if a minimum
of measurements was met.
The number of occasions that the capture in the pots were recorded as well as the data quality,
varied between fishermen. A few fishermen filled out the protocols a sufficient number of times
for both standard and commercial pot design, and a few more were filling out for one or the other
of the two. The period for sampling was from within a short time period of a month or two, or
was stretched across the season from May to December. Measurements to the closest cm were
used in some cases, not to mm as told. Presentations of size frequency for different areas are
given in figures 11-12. For comparison of size frequency between standard and own commercial
pot design (with escape gaps) examples are given in figure 13-14. The size frequencies in some
of the geographic locations may be questioned, especially where data are poor. There is a risk
that not all crabs caught in the pots were measured e.g. to decrease labour. Unfortunately the data
on the moult status are difficult to interpret. Most fishermen have filled out this column, but the
variation of shell status is low. This can be caused by that the sampling process did not cover the
main moult period or by uncertainties in the classification. New-moulted occurred during all
season with a weak increase in September-October, no matter location.
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Figure 11. Size frequency in the catch of edible crab inshore and offshore Kattegatt for females
and males, using standard pots without escape gaps. The data are from 2002, 2003 and 2004.
Figure 12. Size frequency at different fishing
locations in Skagerrak, using standard pots
pots in 2002 and 2003. Lunneviken (n=980, 18occasions, July/May to October), Pater Noster
(n=572, 20 occasions, in July and August),
Smögen (n=180, 11 occasions, 10th of July-19th
of October).
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Figure 13. Size frequency of edible crab inshore Kattegatt for females and males, using
commercial pots with escape gaps. More distinct increase in the capture frequency for crabs >
120 mm CW compared to standard pots without gaps.
Figure 14. Size frequency in standard and commercial pots in 2003 at two Skagerrak locations:
Pater Noster (nstandard=446 at 18 occasions and ncommercial=379 at 19 occasions between 17 July
to 19th of December) and Smögen (nstandard=182 at 16 occasions June-October and ncommercial=72,
6 occasions, September-October).
It is less common for voluntary logbook sampling programmes to gather size data. Cooperation
requires liaison and information to fishermen as fishermen suspect that the information can be
used against their interests such as implementing quota or other enforcements. In addition, Starr
and Vignaux (1997) compared size frequency of New Zealand rock lobster from logbooks and
research sampling and found that there was a tendency for higher frequency modes (possibly
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Anette Ungfors 2008
excluding smallest lobsters) in voluntary logbooks and larger frequency modes in research
sampling. The designing and evaluation of length-frequency surveys for pot fisheries are
discussed by McGarvey and Pennington (2001). They show that it was more efficient to sample
one pot from all trips instead of several pots from a few trips. The variance between fishermen
accounted for a relatively large part, and the least efficient sampling strategy was by research
sampling measuring all pots on selected trips. Similar findings came from a Norwegian research
project with detailed log book data (fishermen partly refunded) collected over 4 years by a
reference fleet of professional fishers reporting the edible crab catch from four standardized trial
pots set among their ordinary pots (Woll et al. 2006). Catch rate, catch composition, discards and
size distribution was recorded, and the most efficient survey design is a collection of relatively
small samples from many boats to reduce the between-vessel component of variation.
My conclusion is that it would be inappropriate to use the above sampled data on size and moult
timing as phenotypic traits to distinguish a possible stock structure in Swedish waters. Possibly
the size frequency difference between inshore and offshore Kattegat indicates some stock
structuring but this difference can also be caused by larger mature crabs of the same stock
inhabiting offshore areas. The size frequency between gears with and without escape gaps can
possibly be seen as some higher proportion of crabs smaller than 120 mm in the standard gears.
To improve the edible crab data sampling strategy in Sweden there is 1) a need to increase the
refund per fisherman or call for an alternative incentive for co-operation, 2) possibly shorten or
restrict the sampling period, 3) possibly decrease the pot number, 4) use only standardized pot,
possibly with escape gaps, 5) increase the effort for information and instructions of each
fisherman taking advantage of organization meetings etc as fishermen in general are not fond of
written instructions, and 6) change to weekly reporting rather than annual.
Status of the Swedish edible crab stock
Density estimations – Paper IV
In paper IV we present an estimate of the total abundance of adult crabs on the Swedish west
coast, based on a combination of experimental fisheries to get catch per unit effort data and
effective fishing area, and GIS modelling of available crab habitat. Fishery-related data, e.g.
catch per unit effort (CPUE), is often used as a substitute for direct density assessments for
estimating trends in stock size. In order to translate CPUE data from static gear e.g. baited crab
pots to stock biomass or number, it is necessary to know the catchability coefficient q also
defined as effective fishing area, i.e. the area from which all individuals of the target species are
caught in one pot if the pot was 100% effective at catching crabs. In a mark-recapture experiment
we estimated the effective fishing area around crab pots targeting edible crabs. Crabs were caught
and marked at 5 locations in the Kosterfjord, Swedish Skagerrak coast in September 2003. Crabs
were then released at 5 distances (10-160 m) in four directions from a baited pot. The number of
marked crabs caught in the baited pot was then followed daily for 5 consecutive days. The current
speed and direction close to bottom during the experimental period was measured daily with a
drift buoy. In total, 1635 crabs were marked, and 45 crabs were recaptured (2.8%). The effective
fishing area q was estimated to 2293 ± 1137 m2 (mean ± 95% confidence interval), corresponding
to a circle with a radius of 26.6 ± 6.3 m.
In a separate experimental fishery during June and August 2003in the Fjällbacka archipelago
located approximately 35 km south of the Kosterfjord, we estimated catch per unit effort at two
depths strata (15-18 m and 25-30m) at 7 locations. CPUE did not differ significantly between
seasons or depths, but differed significantly among locations. Using the effective fishing areas
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Anette Ungfors 2008
estimated as described above, we calculated an average density of 0.0038 ± 0.0015 crabs/m2.
Using GIS data on depth and sediment characteristics of Skagerrak and Kattegatt we calculated
the area of suitable crab habitats along the Swedish West coast. We defined a suitable crab
habitat to be between 10 and 40 meters water depth, and with a bottom consisting of bedrock,
stone, gravel or sand. The area of suitable crab habitat was estimated to 4142 km2 (figure 15),
which combined with density estimates from Fjällbacka would indicate that the catchable
population of crabs on the Swedish west coast would be approximately 16 ± 6.3x106 crabs.
Figure 15. The suitable crab habitat (10-40 m
depth and bedrock, stone, gravel or sand) is
estimated to 4142 km2 (grey in sea). Landing
positions for crab pots, net and fyke-nets in 20042007 are also given.
Stock assessment – Paper V
Crustaceans repeatedly shed their shell for growing
and the lack of a structure showing annual growth
marks makes it difficult to age individuals.
However, age determination by lipufuscin pigment
is promising (Tully 1993; Sheehy&Prior 2005).
Still, the age determination of crustaceans must be
considered expensive and time-consuming but agelength keys have recently been used in parameter
estimation and stock assessment (Sheehy&Prior
2005; Fonseca&Sheehy 2007). Below I present
short descriptions of some available and used stock
assessment methods for crustaceans, mainly based
on Smith and Addison (2003).
General production models or Biomass dynamics models, assume CPUE to be proportional to
stock abundance. Input data is a time-series of catch and effort data, and the data are more
informative if data cover a wide range of biomass and effort levels. These models provide
estimates of reference points such as the maximum sustainable yield (MSY), fishing mortality at
MSY (fMSY), and biomass at MSY (BMSY). Available free computer programmes are e.g. ASPIC
(http://www.sefsc.noaa.gov/mprager/aspic.html) and
COLERAINE (http://fish.washington.edu/research/coleraine/).
Depletion models are based on how the removal (catch) influences the remaining abundance.
CPUE are often used, and are assumed to be proportional to population size. The classical
models assumes a closed population with no immigration or emigration, and predicts how large
cumulative removal should be to reduce the abundance to zero, which is then an estimate of the
current population abundance. If used on unexploited or early in a fishery developmental phase,
the reference point unexploited biomass is estimated. Variability in catchability (q) is of
particular concern when the methods are applied to crustaceans (Miller 1990). Frusher et. al.
(1998) recommend that the method should be restricted to fisheries with high exploitation rate
and relatively uniform size composition over the area. Stock assessment of the Irish edible crab
have been performed by an open population depletion model considering soak-time, using a
tagging experiment with an intense effort of recovery (ICES 2003). Soak-time is the time that the
hauled gears were deployed at sea.
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Length-based population analyses are sex and size-structured abundance estimating models
using the probability of moult and increment for different size cohorts, gradual increased
recruitment potential (egg production) over length and if possible are spawning-recruitment
relationship are included so that recruitment can be calculated. Fishing and natural and
handling/discard mortality are often the factors decreasing the cohort abundance (Zheng et al.
1995; Punt&Kennedy 1997; Zheng et al. 1997; Siddeek et al. 2004). These models offer a high
degree of biological realism but are computationally complex, and need supporting input data on
biological processes e.g. as growth, maturity, natural mortality and of fishing processes as
catchability and selection.
Length cohort analysis (LCA) produces fishing mortality and abundance estimate per length
class. Input data are length frequency of the catch from a population assumed to be in equilibrium
(i.e. no trends in recruitment or mortality/exploitation), growth parameters K and L and natural
mortality. In LCA the parameters of growth rate is important as von Bertalanffy growth curve
(VBGC, relation of size with age) is used for estimation of the taken time (t) it takes to grow
between cohorts (Jones 1990), instead of using 1 year as in virtual population analysis (VPA) or
age cohort analysis (ACA). The model works from the largest to the smallest cohort to calculate
the cohort abundances that must have been at start of the time period accounting for the assumed
natural mortality and the estimated fishing mortality from landing data. The reliability of length
cohort analyses and the shortcomings of the model have been discussed (Hilborn&Walters 1992).
Efforts on minimizing the model limitations i.e. the discrepancy between size and age have been
made by excluding the largest cohorts with too large variation in size-at-age, and by including
sensitivity analyses of growth parameters and natural mortality (Jones 1979; Addison&Bennett
1992). Still, LCA is used for relative comparison of yield per effort with different growth
parameters (Ulmestrand&Eggert 2001) or used for its simplicity and lack of alternatives
(Wolff&Soto 1992; Kirchner 2001).
In paper V we assessed the stock of edible crab in Skagerrak and Kattegat with length cohort
analysis, using von Bertalanffy growth parameters L and K estimated from length frequency
data and mark-recapture experiment. Input data length frequency of the catch removal (landing
and discard) is shown in figure 16. The calculation steps of LCA were describe in Jones (1984)
and a recent user-friendly description of length cohort analyses was presented by Jennings et al
(2001, p. 143-144). The impact of different parameters on stock indicators i) fishing mortality, ii)
current stock abundance (numbers and weight) and iii) and egg production of the spawning stock
have been analysed. Monte Carlo resamplings of L, K, weight-at-size and fecundity-at-size were
used to estimate the sensitivity on stock indicators of input parameter. The analyses were made in
Matlab 7.5 (MathWork Inc.). In addition to the commonly used value of natural mortality of 0.2,
we ran the LCA for natural mortalities of 0.1 to 0.3 to cover a likely range of this parameter.
Figure 16. Raised landing frequency for females
males in the Kattegat and the Skagerrak. Used in
stock assessment in Paper V.
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The fishing mortality was higher for females than for males (figure 17), and the fishery in
Kattegat exploits larger individuals whereas the fishery in Skagerrak seems to have a wider
exploitation pattern. The mean fishing mortality Fall and the Fp are around 0.3 for females and 0.2
for males. Overall, the fishing mortality seems low. Based on total commercial and estimated
recreational landing of 403 tonnes in Kattegat and Skagerrak, the estimates on the current stock
ranged between 1600-2600 tonnes or 4-8 million of edible crabs, and the egg production was
around 5-7x10^11 eggs. These ranges of stock estimates are based on different values on growth
parameters, weight-size, fecundity and natural mortality. A lower natural mortality generated a
lower stock abundance and egg production whereas a higher natural mortality generated higher
stock indicators. Natural mortality had an impact on the estimated fishing mortality, such as a
lower natural mortality resulted in higher fishing mortality.
Figure 17. Skagerrak. Fishing mortality (mean ± 95 % confidence interval) of a) females using
L 217±12.2 and of b) males using L 217±8.6. 1000 runs (paper V).
Logbooks
Licensed Swedish fishermen fill out mandatory logbooks. In 1994 when Sweden became a
member of the EU, a logbook of a common type was introduced in the Swedish fishery. Skippers
on fishing vessels over 10 m length have to report fishing activities on daily operational basis
whereas skippers on vessels below 10 m fill out journals on a monthly basis. The daily logbook
type is more detailed and useful for assessment as the number of gears and effort hours are given.
Gear effort is not given in the monthly journals but the number of fishing days for that month as
well as landing per day. The data quality in the logbooks has improved over the years but still e.g.
the number of gears could be reported in a more accurate way.
To give a picture of the edible crab fishery in Sweden, logbook data from 2007 are presented in
more detail: The total landing is 148 540 kg, and of this 80 966 kg (55%) is taken by crab pots.
Nine fishing vessels over 10 m are targeting crab with pots with a total landing of 27703 kg and
12704 pot hauls i.e. a rough estimate on LPUE is 2.18 kg/pot. Using this landing rate an
estimation of the pot hauls for vessels under 10 m are estimated to 24432 pot hauls. The total
effort of fishermen targeting crabs is then 37136 pot hauls in a year. The LPUE for 1995-2007 is
given in figure 18 (left graph) based on daily logbook reporting, and since 1999 onwards there is
no trend in LPUE using data for Kattegat and Skagerrak. LPUE since 1999 is on average 2.22
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Anette Ungfors 2008
kg/pot excluding 2000. However, the LPUE per area is more variable but since 2004 the LPUE in
both areas seem to be stabilised around 2.0-2.5 kg/pot. I have not been able to get effort data from
2004-2005.
Figure 18. Left graph show annual LPUE in 1995-2007 based on daily log-book reports of vessel
>10 m. Right graph show LPUE (kg/pot) in 2007 for vessels >10m for soak-times up to one
week.
Catch or landing per unit effort can be used as an indicator of the stock abundance. However,
several factors in addition of stock abundance can affect the LPUE. The abundance of crabs is
higher on certain grounds, and the search behaviour of fishermen to optimize yield may provide
trends in CPUE that do not reflect real changes in abundance. Generalized linear models can be
used to quantify the variation in LPUE by e.g. year, month, area, soak-time and vessel/vessel type
e.g. Bell et. al. (2005). GIS information can elucidate variation in LPUE in logbooks due to
differences in depth and substrate. Based on capture position given in the Swedish logbooks, the
geographical positions of the landings plotted on depth and substrate type, respectively (figure
19) indicate that landings mainly occur in shallow areas composed of mixed substrate. Other
factors are trap saturation and soak time. Many traps within an area may decrease the catch rate,
or as trap saturation commonly means: that the capture in a trap impacts the further catch (Miller
1990). Catch rate is increasing with prolonged soak-time at least up to some asymptotic level
defined by the gear design. Logbook data in 2007 for vessels over 10 m length showed how soaktime affected the catch rate (figure 18, right graph). The soak-time (days) shows a positive
correlation with catch rate. Soak-time up to 7 days are included, catch rates after approximately
10 days of soak time decreased probably due to crab escapes or misreporting. In this data both
one and two chamber pots are used (no discrimination in logbooks, which further could improve
the data set). A two-chamber pot fish differently compared to one-chamber: escapes by time are
prohibited or at least decreased in the two-chamber pot by a soft entrance into the extra room.
This means that high capture rates in two chamber pots can camouflage decreases in stock
abundance.
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Figure 19. Fishing positions in the commercial edible crab fishery in 2004-2007. Left graph
show depth strata and right graph substrate strata in the Kattegat and in the Skagerrak.
To improve stock assessment the compilation of fishery data is most important. Logbooks can be
used to assess the stock by e.g. surplus biomass models or by analyses of trends in LPUE. A
time-series of logbook data over an approximately 10-20 years might be needed, and the input
data should mirror the absolute abundance. The existing logbook system is fully comparable to
other EU countries, and in some cases even better as even the small vessel tonnage (< 10 m) are
reporting on monthly basis. However, there is need for better guidance in how to properly report,
in particular the effort columns. The exact numbers of hauled pots, not an approximation or a
rounded off number, should be given. To be able to standardise the LPUE for soak-time,
information on effort hours must be reliable. For more detailed knowledge of the capture such as
sex ratio and size frequency, a new license system for the coastal segment can build on agreement
of co-operation of the licensed fishermen to sample necessary data. Earlier research on how to
efficiently sample a reliable length frequency clearly recommends to sample few pots from
several to all fishing vessels instead of sampling a larger amount of pots from a few vessels or by
occasional observer sampling (McGarvey&Pennington 2001; Woll et al. 2006). The pot type
should be of similar standard design to exclude different catch rate caused by dissimilarities, and
as two-chambered pots may camouflage stock decrease one-chambered standard pots might
preferable be used.
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Conclusions
SWOT
In this section I combine old and recent (this thesis) knowledge in a somewhat subjective SWOT
(Strengths-Weaknesses-Opportunities-Threats, table 3) analysis of the fisheries and biology
characteristics of the Swedish edible crab stock. By this operation I wish to illustrate and
summarize the advantages or drawbacks of the stock status, potential management strategies as
well as the gaps in our knowledge.
Today we know the life history of the Swedish edible crab to varying degree: relatively much is
known of its adult migration potential (paper II) but less is known about larval dispersal and
natural mortality, the latter most important for stock assessment (paper V). The stock might
extend over large geographic areas in the range of 1000 km (paper III) but the possibility for
some local smaller stocks cannot be excluded. Genetic population analyses on crabs in UK
showed that close locations could be significantly different (pair-wise comparison) despite no
genetic isolation-by-distance (no diversification with distance) (McKeown&Shaw 2007).
Significantly different close locations always included an inshore area, and complex
oceanographic features promoting local retention that could affect larvae from these areas. The
fecundity is high (paper I) but on the other hand the larval development period is long (months),
so a large proportion of the hatched larvae does not to settle. Maturity occurs relatively late, at an
age of 5-8 years. The escape gap size needs to be increased to 90 mm to be consistent with the
recommended MLS of 140 mm (paper I).
The two independent estimations of stock abundance (paper IV and V) came up with estimates
not so far from each other: in the range of 10-22 million crabs (95 % CI) in paper IV and 4-8
million crabs (95 % CI, different parameter values) in paper V. However, the confidence intervals
are not overlapping. Both estimates are impacted by several factors such as catchability,
parameter values (e.g. natural mortality) and assumptions (e.g. about suitable habitat, or that
length can be used as a cohort). As the total landing of edible crab most probably is underreported the abundance estimate in paper V is too low which mean that most confidence should
be put on the higher estimate.
Stock status is judge to be in a sustainable condition, and even to have the potential to be
exploited to a higher degree. For now, before e.g. age-based or length-based models have further
improved the assessment level, stock assessment can be based on indicative LPUE assessment.
This means that in case the LPUE declines this needs to be followed by management restrictions.
For this option, logbook data need to be reliable, as stated before, to be able to explain changes in
LPUE due to changes in abundance or due to e.g. changes in fishery distribution or other change
in exploitation pattern.
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Table 3. A SWOT-analysis of the exploitation and management of the Swedish edible crab stock.
STRENGTHS WEAKNESSES OPPORTUNITIES
THREATS
Fisheries
• Selective gear
• Low benthic
impact
• Local trap
saturation;
Competition of
fishing grounds
Life history
•High gene flow
• Low
catchability of
berried females
• High fecundity
• One
homogenous
stock in longterm evolutionary
perspective
• Low fishery
mortality
• 15-30 % harvest
rate (F110-160)
• Stable LPUE
•Natural
mortality?
•Larval dispersal?
• Catchability?
Stock structure
Stock
assessment
Management
• Escape gaps
Stock status
•Under-exploited
•Increasing stock
(fishermens
observations)
•Low predation
due to low
abundance of e.g.
codfishes
• Marketing of
Swedish edible crab,
also males
•Product development
(diversification)
•Potential increased
landings
•Promotion of high
quality crabs by light
sorting device
• Fishing on
female soon to
spawn
• By-catches of
berried females
in nets
• Used as bait
• Claw market
• Mortality on
soft crab e.g. for
claws or poor
handling
• Relatively late
sexual
maturation
• Longevity
•Reliable stock
assessment?
• Length frequency
vs. age frequency?
•Logbook
misreporting
• Age determination
by lipofuscin used for
assessment
• ICES WGCRAB
Assessments
• No minimum
landings size
• No monitoring
except logbooks
• Poor effort
reporting in
logbooks, better
guidance needed
• Pot type?
• Co-operative
management
•Protection of
spawning areas
• MLS 140 mm CW
•Prohibit handling
mortality of soft and
berried females
• Unreported
catches (e.g. in
crab pots,
lobster pots, fish
nets and
recreational
fishery)
• Present escape
gaps too small
• Different stocks
in short term
ecological
perspective?
• Area not fully
exploited
•Un-reported
mortality and
removals
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Local management of edible crab
One of the aims of this thesis is to evaluate on what geographic level the Swedish edible crabs
should be managed. This implicitly means to estimate the geographic distribution of the stock and
equal this with the management unit. Of the many available stock definitions I base the
conclusion of stock distribution on population genetics where low genetic variation is considered
to occur within one stock. With the information we now have, Kattegat and Skagerrak can be
looked upon as one homogenous stock, and therefore should be treated as one management unit.
However, does this argument exclude local management such as local co-management of
fisheries, implementing smaller management areas than the stock unit?
Laikre et al (2005) discuss three types of genetic population structures in relation to fishes in the
Baltic Sea, namely distinct, continuous and no differentiation. They conclude that local overexploitation, or even extinction of populations with no differentiation, may not have a serious
effect on total genetic variation in comparison with the two other genetic population structures, as
long as the effective population size is large enough to counter the effect of genetic drift.
However, the ecological effect could be serious. Therefore, local management of the edible crab
can be considered and implemented if stakeholders take a precautionary approach such as
implementing size restrictions and not fishing below a certain local biomass. However, local over
harvest does not severely impact the total genetic pool, as long as no extensive fishery exists on
all local management areas and as long as corridors for genetic connectivity between them
prevail.
Co-management initiatives limiting fishermen entrance, can the decrease the open access of the
resource and by this can build an increased responsibility of the participating fishermen (Shotton
2002; Piriz 2004; Brady&Waldo 2008). Symes (2007) put the light onto different questions that
need to be considered in establishing co-operative organisations. However, increased yields or
revenues can repay sound resource exploitation of the participating stakeholders. As the stock
status of the edible crabs within the co-management area also depends on recruitment and
mortality in other areas, as well as immigration and emigration, the stock may not recover from
depleted conditions in spite of a sound local fishery. However, as long as this is understood and
that fishermen are monitoring the resource and react (adaptive management) if negative trends
occur or if limits of negotiated reference indicators such as fishing mortality or stock biomass are
reached, smaller management units than stock distribution is practical. Communication between
co-management areas needs to be established to tune the overall exploitation. Also, marine
protected areas in the Kattegat and Skagerrak, working as a recruitment source or as a
precautionary strategy, can be one way to safeguard against failures.
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Research perspective
To use an alternative modelling strategy such as dynamic length-based method (Punt&Kennedy
1997), we need to evaluate the available data. Biomass surplus modelling (Hilborn 2001) using
LPUE data and landings from logbooks can be worthwhile and can be tested with data from
1995-2007. The LPUE in the logbooks can be improved by detailed review of the reported effort
through e.g. interviews with skippers to get information on the amount of used gears over the
years, and possibly to get private landing records. Generalized linear models can be used to
quantify the variation in LPUE by e.g. year, month, area or vessel/vessel type. Variation in LPUE
in the logbook due to differences in substrate or habitat can be elucidated by available position of
fisheries and GIS information.
Establishing age-length keys for the Swedish edible crab is a tempting prospect. The calibration
to chronological age and the thermal correction of age estimates for edible crab were made on the
basis of cohorts modes of neurolipofuscin concentration frequency distributions (NCFD) for
different areas with different mean temperatures (Sheehy&Prior 2005), and not by use of
individuals of known age reared in the laboratory (Belchier et al. 1998). If pronounced
temperature differences between Kattegat and Skagerrak fishery locations, keys need to be
established for both areas as Sheehy and Prior (2005) found a strong relationship between sea
temperature and neurolipofuscin accumulation rate.
As the knowledge of the juvenile crab distribution in Sweden is scarce it would be interesting to
investigate if the Laminaria habitat also is a nursery area for the edible crabs in Sweden.
Within the thesis I tried to evaluate the fishery-dependent estimates of the crab densities by use of
remotely operated vehicle (ROV). This ROV study can be worth re-evaluation with an increased
filming effort or by use of divers or underwater cameras (UWTV) on sledge.
The genetic analysis can be extended to include more locations, such as samples from the inner
fiords.
Estimates on natural mortality need to be reliable for the use in assessment models. Research
fishing in marine protected areas with no commercial fishery or in formerly un-fished areas, gives
information on the natural mortality by length frequency analysis or catch curves (age) i.e. the
total mortality = the natural mortality.
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Acknowledgements (Tack)
First I have to express the joy of having spend all these years at Tjärnö Marine Biological
Laboratory since coming here as a student in 1997, then working as an marine biologist in
Fishery Technology Centre (FTC), and later on as a PhD student and in projects for fisheries
development. Many thanks to the TMBL first lady Kerstin Johannesson, my Idol when it comes
to marine biology, speaking talent and combining-career-with-family-issues, and to her co-driver
Lars Hagström and all the TA staff.
Then, folk responsible for that I came into the crab business is my supervisor Per Nilsson, a very
busy man damn good at statistics, who could not possible has guessed that not one but two
children later he got rid of me :=D. Colin Wheatley who put effort into crab development and
me. Eva-Marie Rödström for being my mentor (now you know) and support in a lot of issues.
Hans Hallbäck, IMR/H-lab, has most kindly shared a lot of his earlier findings and data on the
edible crab. I spend my first half a year as a PhD student plotting all the mark and recapture
location in GIS, which meant I had to identify and find a lot of small local-named Islands along
the Swedish west coast. After that I was pretty good at the name of all Islands. Later on I repeated
this process with own data...Mats Ulmestrand, a fishery biologist knowing everything about
lobsters, has been my direct channel to the Swedish Board of Fisheries (data bases), a colleague
in SUCOZOMA and LCA mate. The meetings within the ICES Crab Working group where I
have got the possibility to find out about ongoing crab research, have been invaluable. Many
thanks to e.g. Julian Addison, Derek Eaton, Oliver Tully, Martin Robinson, Daniel Latrouite,
Suzanne Henderson, Beth Leslie, Astrid Woll, Jan Sundet, Knut Sunnanå and many more. Astrid
Woll at Möreforskning, Norway examplary in the co-operation with fishermen, thanks for all
communication during the years about crab biology, meat yield, management and the comments
on the thesis summary. Hope we can come up with a project together! In 2001 I attended the
annual research expedition on the Red King Crabs in the Northern Norwegian Fiords, where Jan
Sundet och Ann Merete Hjelset learned how to measure and mark big crabs 24 h per day for
two weeks. Thanks for that experience!
Many thanks to my two master students Elizabeth Sjöström and Helena Sundström, and the
colleagues Christin Appelqvist and Lillemor Svärdh not only for making me feel as a group
member, but also for assistance during mark-recapture and reporting, experimental fishing and
histological work! To all the VOF-group members and particular its shellfish- and wine loving
chairwoman Susanne Lindegarth - soon I will have the best home-site ever! Later on I had use of
my assistant supervisor Carl André, the DNA lab boss, thanks for your contribution. This last
year, having the privilege to work in the DNA lab with all the EGG hang arounds was worth
waiting for: Benno Jönsson learned me how to use the still functional ALF-machines and AnnaKarin, Marina, Rick, “Pia”, Tuuli, Johanna G and Petri all shared their knowledge about useful
PCR programmes, pipetting etc. Marina also gave professional advices when working with the
statistical analyses and commented the manuscript. Many thanks also to Niall McKeown and
Paul Shaw for primer sharing and collaboration.
It is fantastic how many people that really have been involved in a thesis, this must be a true
altruistic behaviour (ok some money has been transferred): Thank you Tomas Lundälv for ROV
filming at shallow depths around crab pots with dangerous ropes :=), Jon Havenhand for
language improvements (and other comments) in paper II, Roger Johansson and Sven-Gunnar
Lunneryd for all help with the heavy acoustic buoys, Magnus Wahlberg for the acoustic tags,
assistants in crab tracking Benno, Linus, Malin K. Many thanks also to Annika L, a new fast-
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Anette Ungfors 2008
working friend, and Frank S which I have pushed hard in Nephrops projects. Hans-G for
corridor chatting.
All best friends and colleagues who I have shared years as “single” or as “married-wanna-be”,
preparing fancy or simple dinners, in SPAs, drinking wine and chatting: Solveig van Nes for our
friendship, for commenting on manuscript and summary, you are an excellent godmother to
Amanda; Karin and Hasse for shared interests in a lot and for comments on the summary;
Susanne and Mats L for hospitality among many other good characters; Malin and Jerry –
looking forwards to more grill parties; Eva-Marie and Per for being you, and Per - thanks;
Gunilla –sailing? Henrik you are doing a great “prefekt” job; Marina and Anita – garden
planning evening?; Mia and Martin for lively discussions.
Och min allra bästa kojbyggarkompis Anna Nilsson för all tid vi har spenderat tillsammans, på
cyklar, vid kiosken, på discon, tja vad har vi inte hittat på! Ditt telenummer används fortfarande
“flitigt” när jag bara vill prata lite eller behöver peppas upp. Och alla grannar och andra
barnfamiljer som lyser upp tillvaron under kvällar och helger: Ronny och Charlotta för att ni
försöker få lika fin gräsmatta som oss; Håkan och Camilla som flaggar för oss; Malin och P-O
som har våra barn hos sig; Roger och Helene som drar ut oss på minst en skogs-eller båttur varje
helg; Anna och Gunnar för grillkalas.
Och tänk alla fiskare som jag tagit över rodret hos: Bröderna Patrik och Joakim och pappa
Ingemar i Lejet, Martin och Folke i Bua, Per-Arne i Ringhals, Gilbert i Kullavik, Lennart i
Marstrand, Henning och Lars-Erik på Tjörn, Bo på Orust, Björn i Fiskebäckskil, Henrik i Norra
Grundsund, Martin på Smögen, Lars-Åke i Långasjö, Janne och Nisse på Resö, Morgan och PerGösta i Strömstad. Hallands Skaldjursutveckling EF med vildbasingen Viking Bengtsson. Tack
alla ni och alla andra som lämnat in återfångstrapporter & andra observationer!
Och min Sturköfamilj då? Pappa John-Erik som bara måste ut på ”sjön” varje dag, och varifrån
jag troligen har snappat upp intresset för havet, det är Dig jag ser framför mig när jag tänker på
hållbart småskaligt kustfiske. Mamma Inga-Lill som är en viktig grundbult i familjen Ungfors,
som har haft en viktig roll i fisket och som nu intagit en annan viktig roll – rollen som
supermormor! Äldsta broder Anders med sin Kristina, mellanbroder John & Marie och
Jessika, och så minstingen Martin med sin Caroline, finfina bröder och svägerskor som håller
mig kvar i Ungfors-klanen trots långt avstånd oss emellan – tur att det finns telefon och datorer.
Fast på sistone är det väl busungarna som ni helst vill prata med?
Min Strömstadfamilj då? Ja, dom har fått ta på sig rollen som min extrafamilj. Men om dom fattat
vad jag håller på med – nej, det tror jag inte! I alla fall, tack till Majsan, Freddan & Ginny,
Victoria & Robert och Putte & Mona för alla familjesammankomster, barnvakter och
promenader. Men hur ska jag tacka min allra närmaste underbara familj? Niclas, den bästa
pappan och livskamrat, som varit så förstående i alla fall de sista månaderna – du ska få spela
bridge och åka på husvagnssemestrar så att du storknar under kommande år! Amanda och Malte,
ni är alldeles för bra för att vara sant. Älskar Er!
My PhD study was supported by the Swedish research programme on Sustainable Coastal Zone Management,
SUCOZOMA, funded by the Foundation for Strategic Environmental Research, MISTRA; The Department of
Marine Ecology, University of Gothenburg; and Project Västkustkrabban, funded by The EU Economic Fond for
Fishery. In addition, economic support for chemicals, field equipment and for participation in conferences have been
given by Orvar and Gertrud Nybelin Fishery Fund, Helge Ax:son Johnson Foundation, Iris foundation, Kurt Belfrage
Fund, Adlerbertska Research Fund, Wilhelm and Martina Lundgren Scientific Fund, Clara Lachmanns Foundation,
KVVS, Colliander and Birgit och Birger Wåhlströms Foundation.
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Anette Ungfors 2008
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318
Sexual maturity of the edible crab (Cancer pagurus) in
the Skagerrak and the Kattegat, based on reproductive
and morphometric characters
Anette Ungfors
Ungfors, A. 2007. Sexual maturity of the edible crab (Cancer pagurus) in the Skagerrak and the Kattegat, based on reproductive and
morphometric characters. – ICES Journal of Marine Science, 64: 318–327.
The size at the onset of sexual maturity of female and male edible crab (Cancer pagurus) from the Skagerrak and the Kattegat and
the fecundity of females were estimated. Physiological maturity of females, i.e. ovary development, was at a larger size than
behavioural maturity (indications of successful copulation). The carapace width (CW) at which 50% of females were mature (CW50),
based on development of the gonads, was 132 mm, sperm presence gave a CW50 of 107 mm, and the presence of sperm plugs a
CW50 of 118 mm. Changes in relative abdominal width were found at approximately 100 and 130 mm, and CW50 was 104 mm. A
smaller fraction (25%) of the females is functionally mature at sizes ,140 mm. However, male physiological and functional maturity
was more synchronized: CW50s based on advanced sperm production and allometric changes in the chelae were within 5 mm (117 –
122 mm). Size-specific fecundity increases with CW (0.5– 2.5 million eggs). Recommendations for a minimum landing size (MLS) of
140 mm and a change of escape gap size to 90 mm are given. Legislation of a MLS of 140 mm CW for females and males will reduce
future potential landings more in the Skagerrak than in the Kattegat.
Keywords: allometry, Cancridae, fecundity, gonad development, management, minimum landing size, size at maturity.
Received 23 May 2005; accepted 24 November 2006; advance access publication 16 January 2007.
A. Ungfors: Tjärnö Marine Biological Laboratory, Department of Marine Ecology, Göteborg University, S–452 96 Strömstad, Sweden; tel: þ46 526
686 88; fax: þ46 526 686 07; e-mail: anette.ungfors@tmbl.gu.se
Introduction
To avoid recruitment-overfishing of brachyurans, recruits to the
fishery should be able to reproduce at least once. To meet this
requirement, management actions can restrict the size of landed
crabs by minimum landing size (MLS), by restrictions on the gear
deployed, or by a one-sex harvesting strategy. Additional regulations can protect the pre-recruits and recruits at vulnerable
stages of their life, e.g. by decreasing handling mortality during
moulting periods by seasonal closures (Hankin et al., 1997;
Siddeek et al., 2004). The size at the onset of sexual maturity
(SOM) needs to be considered in the implementing process of a
MLS, and signs of mating activities, gonad development, or allometric changes in growth of the body parts have been used to discriminate between juveniles and adult Brachyura, e.g. Cancridae
(Weymouth and MacKay, 1936; Edwards, 1979; Brown and
Bennett, 1980; Campbell and Eagles, 1983; Orensanz and Gallucci,
1988; Orensanz et al., 1995; Hankin et al., 1997; Pinho et al.,
2001), Portunidae (González-Gurriarán and Freire, 1994; Muino
et al., 1999; de Lestang et al., 2003; Hall et al., 2006), Majidae
(Alunno-Bruscia and Sainte-Marie, 1998; Sampedro et al., 1999),
and Xanthidae (Flores and Paula, 2002). Stock assessment can use
egg production (S) of mature individuals and stock-recruitment
relationships of commercial species (Addison and Bennett, 1992),
so for management purposes the relationship between size and
egg production (fecundity) is important.
The edible crab (Cancer pagurus) is distributed along the
Northeast Atlantic coast (Christiansen, 1969): in Swedish waters,
it is limited to the Skagerrak and the Kattegat, where there is a
small commercial fishery. The total landings in 2005 in Europe
were 46 280 t, most in the UK, Ireland, and France. In 2002, the
Swedish landings in fisheries targeting crabs were 105 t, 57% of
the total taken by crab pots, and of this, 68% (57 t) was caught by
boats ,10 m (ICES, 2003). In Sweden, the main landing season is
July–November. In most parts of its distribution a MLS is
implemented, either of national (UK, Addison and Bennett, 1992;
Norway, J-102-2004) or international status (Anon., 1998).
However, the crab fishery in Swedish waters in the Skagerrak and
Kattegat is not regulated by implementation of a MLS, but by
obligatory 75 mm escape gaps in pots fished shallower than 30 m
and in fykenets fished deeper than 10 m (Anon., 1998, 2004a).
These escape gaps allow crabs of carapace width (CW) ,110–
120 mm to escape (Dybern, 1983). In the northern part of
Skagerrak, from the Swedish border to the Norwegian southwest
coast (Rogaland), the commercial landing of crabs ,110 mm is
prohibited (Anon., 2004b).
The aim of this study is to investigate whether the current
management actions in the Skagerrak and the Kattegat preclude
recruitment-overfishing. The SOM is defined as the CW at which
50% of the population is mature, and both physiological and
functional sexual maturity are considered by evaluating the
gonad development in both sexes, the presence of sperm plugs
and filled spermathecae in females, and by measuring male chelae
and female abdomens. I did not sample ovigerous females for
maturity because of their low catchability (Howard, 1982).
# 2007 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved.
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319
Sexual maturity of Cancer pagurus in the Skagerrak and the Kattegat
However, I did conduct fecundity analyses, so that they can be
considered in the process of MLS recommendation and in stock
modelling. In addition, I experimentally evaluated the potential
for crabs to escape from creels with gaps of different diameter and
forecast the potential commercial landings under an MLS based
on the SOM.
Material and methods
Sampling and classification
From July to December of 2001 and 2002, edible crabs of both sex
were collected from fishing vessels (potters) operating in the
archipelagos along the Swedish Skagerrak coast and on coastal
and offshore banks in the Kattegat (Figure 1). Subsamples of the
catch were brought to the laboratory. As reproduction of Cancer
spp. has a temporal component (Charniaux-Cotton and Payen,
1988; Shields, 1991) females for ovary classification were sampled
from September to December, when a large proportion of Cancer
pagurus females have ripe or ripening ovaries (Edwards, 1979).
Ovaries were classified as immature (previtellogenesis), undeveloped (primary vitellogenesis), developing (early secondary
vitellogenesis), ripe/mature (late secondary vitellogenesis), or
resting (primary vitellogenesis, loose appearance), and testes were
classified as immature (no visual indication of, or just tiny 5 mm
coiled, testes), developing (production of spermatozoa has
started, testes and vas deferens are thin but partly filled), or
mature (vas deferens is extended and filled by a white mass
of spermatophores). Observations were made on the presence of
spermatophores in the spermathecae and the presence of sperm
Figure 2. Claw of the edible crab (Cancer pagurus) and
morphometric measurements. RPL is the right propodus length, and
RPH is the right propodus height. The right propodus width (RPW)
is not shown but is measured at the widest part of propodus.
Modified from an illustration by H. Samuelsson, Göteborg
University, Sweden.
plugs in the oviducts of early post-moult females. CW, female
fifth abdominal segment at the broadest part (AW), and the
length, height, and width of the male right propodus (RPL, RPH,
and RPW, respectively) (Figure 2) were measured to the nearest
millimetre. If the right chela was missing or regenerating, the left
propodus was used (a pairwise t-test showed no significant
difference between right and left measurements of RPL, RPH, or
RPW; p ¼ 0.07–0.41, n ¼ 34). Moult stage was determined
according to four classes: (i) crabs at early post-moult, having a
soft carapace, a whitish appearance and sharp toe tips; (ii) crabs
with indications of recent moulting, i.e. a clean appearance but
not fully hardened shell (late post-moult); (iii) inter-moult crabs
had some fouling organisms, worn toe tips, and a presumed high
meat yield; (iv) crabs with shell necrosis and many fouling organisms were classified as degrading. This classification is not based
on Drach’s (1939) setal definition of moult stage (A–D4), but
rather on a modification of macroscopic characters, e.g. as used by
Edwards (1979).
Analysis of size at sexual maturity
Figure 1. Sampling areas for the edible crab Cancer pagurus for
analyses of SOM (black circles) and for ovigerous females for
fecundity analyses (crosses).
SOM was estimated by fitting the percentage of mature crabs
per 5 mm size interval to the logistic equation Proportion
mature ¼ 1(1 þ Ae(BCW))21 by non-linear least squares regression
(Somerton, 1980). The CW at which 50% of crabs are mature
(CW50), i.e. the mature proportion P ¼ 0.5, is calculated as
CW50 ¼ 2log A B 21. Females were defined as mature if the ovary
was in a developing or mature stage during autumn, or if there
were indications of mating (e.g. the presence of sperm in spermathecae or a sperm plug in early post-moult females). For males,
two alternative scenarios for gonad classification were applied in
the calculations: gonads classified as developing were defined
either as immature (scenario 1) or as mature (scenario 2), because
there were definition difficulties with this stage. Chi-squared tests
were used to analyse differences in the mature proportion of
inter-moult and post-moult females and males and the mature
proportion of females in autumn and summer. The allometric
relationship between size (CW) and organ dimension (AW, RPL,
RPH, and RPW) was analysed in three ways: (i) a one- or twophase model (Gaertner and Laloé, 1986), (ii) minimum sum of
squared residuals (SSR) in the transition zone (Lovett and Felder,
1989), and (iii) iterative assignment of adolescent individuals
(Somerton, 1980). Data were divided into two data sets, juveniles
or adults, on an a priori basis. For (i), the lower a priori limit for
320
female adults (LA) was set to 150 mm because 75% of large
females have developed or resting ovaries (this study). Further,
three limits for juveniles (LJ) were used, namely ,104 mm (100%
immature), ,109 mm (75% immature), and 124 mm (75%
undeveloped). Most males .110 mm CW are mature in the UK
(Edwards, 1979), so an a priori higher LJ males was set at 109 mm,
and for adults at 110 mm. A priori limits for (ii) and (iii) are
provided graphically.
Ovigerous females for fecundity analyses were collected in
April and May 2002. Samples (n ¼ 29) were collected as bycatch
in nets deployed for lumpfish (Cyclopterus lumpus) west of
Måseskär (588040 N 118180 E) at depths of 40–50 m, or in crab
creels at Kummel Bank (578280 N 118230 E) (n ¼ 10) in the
Kattegat (Figure 1). After fixation for 1 month in Davidson
solution (Lightner, 1996)), the egg mass was washed in water,
separated from pleopods, and dried to constant weight at 608C. A
sample (n ¼ 10 per crab) of fixed but not dried eggs was measured
for oocyte diameter (mm). Three subsamples of 2–10 mg (0.1 mg
accuracy) of approximately 200–650 eggs were chosen randomly
for exact enumeration and calculating egg weight per subsample.
The whole crab was dried to constant weight in four main pieces,
and the total body weight was recorded. The weight of the missing
claw (or claws) was calculated from the regression equation
y ¼ 0.342x – 31.23 (n ¼ 39, r 2 ¼ 0.86, p , 0.0001; model with
best fit of data), where y is the dry weight per claw and x the CW.
Losses of walking legs were considered by additions of a mean
walking leg weight or by the regression equation y ¼ 0.4886x –
43.5 (n ¼ 35, r 2 ¼ 0.91, p , 0.0001), where y is the dry weight of
four pairs of walking legs and x is again the CW. Fecundity (the
number of fertilized eggs per crab) was calculated by dividing the
total dry weight of the egg by the mean weight of each egg
(the standard deviation was calculated by triplicates of egg
weight). Relative fecundity was calculated as a proportion of the
dry weight of eggs and body. Fecundity and relative fecundity
were analysed statistically by linear regression (untransformed and
logged data) and by testing the curve fit to logarithmic, quadratic,
power, exponential, and logistic relationships, respectively (using
the computer program SPSS), with CW used as a measure of body
size. The relationship between oocyte diameter and the number of
eggs per batch and with CW was tested by linear regression.
A manipulative laboratory experiment was set up in October
2005 to determine how the diameter of the escape gap in creels
A. Ungfors
affects the size of potential escapements. Four escape gap sizes
(75, 80, 85, and 90 mm) were tested against six different size
classes of crabs (115–119, 120– 124, 125–129, 130–134, 135–
139, and 140–144 mm CW). Four females and four males per
size class were arranged within a creel placed in a tank
(9 1 0.7 m) with circulating water (11 –138C, salinity 33).
Three creels per tank were used (in separate compartments), and
bait (fish) was hung on the outside of the creel. Over 10 d, all
possible combinations were tested twice, in random order and
with eight creels per night. The proportion of escapes per size
class and escape gap was calculated.
The future Swedish edible crab landing potential if a MLS is
implemented from the SOM results of this study was estimated.
Five alternative values of MLS were simulated for females (the
four calculated CW50s plus one precautionary), and five alternative values of MLS for males (the three CW50s plus two precautionary). The percentage of the landing potential compared with
recent capture (%, numbers of crabs) without implementation of
a MLS but an escape gap of 75 mm was calculated for females and
males, respectively, on the assumption of MLS being knife-edged,
and from data on the sex-specific size frequency in commercial
catches. The data on crab size composition in commercial catches
were gathered at different sites along the Swedish coast between
1999 and 2003: (i) females in the Skagerrak (Strömstad, n ¼ 4112;
Fjällbacka, n ¼ 1842; Lysekil, n ¼ 363) and the Kattegat (offshore
Groves Bank, n ¼ 2259; inshore Varberg, n ¼ 465) and (ii) males
in the Skagerrak (Strömstad, n ¼ 1743; Fjällbacka, n ¼ 1642;
Lysekil, n ¼ 705) and the Kattegat (offshore Groves Bank,
n ¼ 710) (Figure 1).
Results
The proportion of females with a developed ovary (developing or
mature) was 41% during summer and 64% during autumn
(x2 ¼ 47.1, p 0.001, n ¼ 920) (Figure 3). The ovaries of
30–50% of females of intermediate size (124 –149 mm CW) were
in a resting stage in summer, compared with ,25% in autumn. In
autumn, most females of intermediate size were in an undeveloped stage, but irrespective of season, larger females (150 mm
CW) were generally classified as mature. Most crabs in CW classes
124 mm were immature and undeveloped. During autumn, the
proportion of females with developing or mature ovaries was
Figure 3. Ovary stages during (a) the summer months June– August (n ¼ 521), and (b) the gonad development period September–
December (n ¼ 399) of crabs in 5 mm CW intervals (endpoint of interval shown). The data are based on inter- and post-moult crabs.
321
Figure 4. The proportion of mature female edible crabs based on (a) developing and ripe ovaries during autumn (n ¼ 399), (b) the
presence of sperm in the paired spermathecae (n ¼ 1128), and (c) presence of a sperm plug in the oviduct of early post-moult (n ¼ 446).
Logistic growth curves are drawn (parameters presented in Table 1). The CW50 is 132, 107, and 118 mm, respectively.
higher for inter-moult (80%) than for post-moult females (51%)
(x2 ¼ 35.1, p 0.001, n ¼ 399).
The proportion of mature females based on the reproductive
characters, ovary development, spermathecae, and sperm plug
presence increased with CW (Figure 4). CW50 is 132, 107, and
118 mm, respectively (logistic regression, Table 1). The general
patterns of gonad development for inter-moult and post-moult
males were similar (Figure 5a, b), but post-moult males were
more often classified as immature or developing (52%) than
inter-moult males (26%) (x2 ¼ 44.4, p 0.001, n ¼ 631). The
proportion of mature males based on gonad development per
5 mm CW size class increased with CW (Figure 5c). CW50 was
117 mm if a developing gonad was considered immature, and
101 mm if it was considered mature (Figure 5c, Table 1).
A two-phase regression model fitted the allometric data better
than a one-phase model for both sexes: the SSR for linear
regression of the two-phase model was lower than for a one-phase
regression of juveniles and adult data combined (Table 2). The
total SSR on allometric data of female AW showed a minimum at
95–104 mm CW and a second minimum at 125–139 mm CW
(Figure 6a). Minimum total SSR was at 125–129 mm CW for
male length propodus (RPL), and at 119–124 mm CW for male
height propodus (RPH) (Figure 7, inset).
The CW50 based on morphometric data was 104 mm for
females (Figure 6b, Table 1) and 122, 122, and 120 mm for male
RPL, RPH, and RPW, respectively (Figure 7, Table 1). Dividing
data into juvenile and adult groups based on an iterative process
fitted the linear regression better than the pooled data set (AW
F ¼ 529.9 p 0.05; RPL F ¼ 306, p 0.05; RPH F ¼ 515.8,
p 0.05; RPW F ¼ 464.8, p 0.05). The growth coefficient of
adult female AW decreased, whereas the juvenile and the male
chela (RPL, RPH, and RPW) showed greater positive allometry
during adult growth (Table 1, coefficient B). The 95% confidence
interval did not overlap between juvenile and adult phases for
either variable (Table 3).
Fecundity, measured as the number of fertilized eggs, increased
with female CW (linear regression r 2 ¼ 0.68, and log-log linear
regression r 2 ¼ 0.71, p , 0.000, n ¼ 39; Figure 8a) in the size
Table 1. Regression (log Y ¼ log A þ B log CW) summary of the iterative assignment of morphometric data, where Y is abdomen width
(AW), RPL, RPH, or RPL (log A1 and B1 ¼ juvenile phase; log A2 and B2 ¼ adult phase) of edible crab.
Sex and morphometry
Log A1 constant
B1 coefficient
Log A2 constant
B2 coefficient
Log A constant
B coefficient
CW50
Females
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
Abdomen
21.8864
1.5986
21.4619
1.4152
224.2413
0.2337
103.7
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
Spermatheca
–
–
–
–
219.034
0.1785
106.6
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
Sperm plug
–
–
–
–
23.0957
0.0261
118.5
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
Ovary
–
–
–
–
217.002
0.1289
131.8
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
Males
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
RPL
21.280
1.276
21.9649
1.6033
28.0619
0.0666
122.5
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
RPH
21.306
1.304
21.577
1.454
27.7268
0.0632
122.3
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
RPW
21.245
1.185
21.588
1.357
27.1330
0.0597
119.5
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
Scenario (i)
–
–
–
–
27.6669
0.0655
117.0
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .
Scenario (ii)
–
–
–
–
214.809
0.1468
100.9
The adult proportion of morphometric and reproductive data is fitted by non-linear least squares to the logistic equation: Proportion mature ¼ 1(1 þ Ae(B*CW))21
and the coefficients log A and B are given. CW50 is calculated from these coefficients (–log A/B). Two scenarios of maturity stage of male gonad are considered:
(i) developing gonad treated as immature and (ii) developing gonad treated as mature. The iterative process fitted data in the CW range 100–149 mm for females
and 94–149 mm for males to the juvenile or the adult phase. The method is based on that of Somerton (1980).
322
A. Ungfors
Table 2. Comparison of a one- and a two-phase relationship
between AW and CW of females, and of RPL, RPH, and RPW and
CW of males.
Sex, size, and
SSR1 SSR2 F
p
d.f.
morphometry
Females
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .
LJ ,104 mm
0.186 0.177
9.076 ,0.05 2 and 361
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .
LJ ,109 mm
0.199 0.187 11.904 ,0.05 2 and 375
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .
LJ ,124 mm
0.317 0.305 10.052 ,0.05 2 and 515
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .
Males
LJ ,110 mm
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .
RPL
0.079 0.075
3.22
,0.05 2 and 125
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .
RPH
0.070 0.065
4.65
,0.05 2 and 125
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . .
RPW
0.095 0.092
1.97
ns
2 and 125
SSR1 is the sum of squared residuals when combining juveniles and adults
to one phase, and SSR2 the same when splitting into two phases. Data of
intermediate sizes (LJ–LA) are not included in the one-phase regression.
The data fit a two-phase linear regression better (F-statistic) than a
one-phase regression (except for the data on RPW). The method is based
on that of Gaertner and Laloe (1986).
Figure 5. Gonad stages of (a) inter-moult (n ¼ 360) and (b)
post-moult males (n ¼ 271) per 5 mm CW interval. Gonads were
classified as immature, developing, or mature on the basis of visual
inspection of the testes and the vas deferens. (c) The proportion of
mature males per 5 mm CW interval. Treating the developing male
gonad as immature or mature gives a CW50 of 117 or 101 mm
(n ¼ 631). Logistic growth curves are drawn (parameters presented
in Table 1).
range 113–190 mm CW. At that size range, fecundity was between
0.5 and 2.5 million eggs. Relative fecundity, calculated as the
relationship between number of eggs and body weight, was independent of CW (linear regression, p ¼ 0.39) and fitted poorly to
other models (r 2 ¼ 0.02–0.07, p . 0.07) (Figure 8b). The
relationship between dry weight of the egg mass and body weight
ranged between 5 and 28% (average 13%, s.d. +5%). Egg
diameter (mm) was independent of the number of eggs per batch
(linear regression, p ¼ 0.197, r 2 ¼ 0.044, n ¼ 39) (Figure 8c) or
female CW (linear regression, p ¼ 0.278, r 2 ¼ 0.032, n ¼ 39). The
mean oocyte diameter averaged over subsamples and crabs was
383 mm (s.d. +20). The ovaries of all ovigerous females were
macroscopically classified as resting: a greyish loose appearance of
small ovaries in primary vitellogenesis. Only one ovigerous female
showed signs on the carapace of recent moulting, i.e. it was relatively soft and whitish; the rest had a hard carapace with fouling
organisms. The smallest ovigerous female (113 mm) had no
sperm in the spermathecae, as did all other ovigerous females.
Escapements from creels with different gap sizes are shown in
Table 4. The proportion of escapement of different size classes
indicate that a 90 mm gap is required to allow escapement of the
larger crabs in the experiment (135 –144 mm CW).
The CW50 determined from the different biological characters
may be used as background for implementation of a MLS in the
Skagerrak and the Kattegat. The effect of different potential MLS
(CW50) on the Swedish catch potential is shown in Figure 9. The
simulated impact on the capture potential of females subjected to
implementation of a 104, 107, 118, 132, or 140 mm CW as MLS
led to a decrease in the number captured with increasing MLS in
the Skagerrak and the Kattegat. The decrease was more severe in
the Skagerrak (Koster, Fjällbacka, and Lysekil) than in the
Kattegat (Varberg inshore, Groves Bank offshore). A MLS of
140 mm in the Skagerrak resulted in an estimated local specific
capture potential of 33–57% of the present catch, but in the
Kattegat the result was a 80–87% decline. In Figure 9b, the simulated impact of 101, 122, 130, or 140 mm MLS on male capture
potential is shown. A MLS of 140 mm CW in the Skagerrak
reduced the capture potential to 32– 51%, and in the Kattegat to
80% of the present catch by number.
Discussion
Size at onset of sexual maturity
SOM of female edible crab in the Skagerrak and the Kattegat is in
accord with the results of maturity studies on the species in other
European areas. Sperm plugs are observed in the gonadopore
from 100 mm CW (this study) and larger in several areas
(105–211 mm CW in the English Channel, Brown and Bennett,
1980; .107 mm Yorkshire data, Edwards, 1979), and CW50 based
on sperm plug presence is close to our 118 mm (116 mm CW East
Coast England, Edwards, 1979; 115–119 mm CW Shetland,
Tallack, 2002a). A CW50 derived from observations of sperm in
the spermathecae has not been calculated before. However, our
results indicate that mating takes place at smaller crab sizes than
expected from sperm plug indices: the CW50 based on sperm
plugs is also likely overestimated, as shown in Figure 4c. The ovary
develops at a similar body size in different areas of Europe. The
CW50 of 132 mm in Swedish waters (this study) are comparable
with the 130– 134 mm CW at the Shetland Islands (Tallack,
2002a), the 127–139 mm off southwest Ireland (Edwards, 1979),
and the 132–138 mm around Ireland (ICES, 2004). However, Le
Foll (1986) reported a CW50 in the Bay of Biscay based on ovary
323
Figure 6. AW in relation to body size (CW) of female edible crabs. (a) Minimum of SSR in the transition zone of females is observed at
99– 104 mm and 129– 139 mm. (b) Relationship between the logarithm of AW and the logarithm of CW for juveniles and adults (n ¼ 689).
The division into mature adult females was based on Somerton’s (1980) iterative assignment and a priori LJ .104 mm and LA . 150 mm.
The CW50 is 104 mm (Table 1).
development to be as low as 111 mm (i.e. 73 mm CL). This may
be an effect of living in southern parts of the species distribution,
where the water is warmer, and temperature does impact the size
at sexual maturity in other crab species (Fisher, 1999; de Lestang
et al., 2003; Defeo and Cardoso, 2004). In this study, the CW50
assessed from ovary development during autumn included both
post- and inter-moult females: excluding post-moult crabs might
move the logistic curve to the left (significant differences in gonad
development between post- and inter-moults in autumn), resulting in a lower CW50, possibly explaining the geographical differences in ovary maturation. No CW50 has been reported for large
female crabs in the English Channel (Brown and Bennett, 1980),
which borders the Bay of Biscay, but 85% of females .115 mm
(all size categories lumped together) had developed gonads in
autumn (Brown and Bennett, 1980).
A report from an ICES study group on crab biology and life
history point to 130 mm CW as the SOM of maturity of female C.
pagurus in the North Sea (ICES, 2003). However, the size distribution of ovigerous females (H. Hallbäck, unpublished data,
q25 ¼ 142, q50 ¼ 152, q75 ¼ 162 mm, min ¼ 109 mm) in the
Skagerrak and the Kattegat indicates that most females do not
spawn until yet another moult. The size range of ovigerous
females in the Skagerrak and the Kattegat is of the same magnitude as elsewhere in Europe: in the English Channel, ovigerous
females range from 133 to 205 mm (mean 166 mm) (Brown and
Bennett, 1980). The smallest observed ovigerous female from the
English east coast was 129 mm CW, but out of 200 females examined, most that were ovigerous were .152 mm (Edwards, 1979).
Pearson (1908) measured the smallest ovigerous female in northern parts of the North Sea at 115 mm. In situ CW measurements
Table 3. 95% confidence intervals of coefficient B in the linear
regression log Y ¼ log A þ B log CW coefficient, where Y refers to
measures of abdomen, right propodus length, right propodus
height, and right propodus width, and CW is the carapace width.
Figure 7. Logarithm of the RPL plotted against logarithm CW for
juvenile male and adult male edible crabs (n ¼ 509). The
classification into mature males was based on Somerton’s (1980)
iterative assignment and a priori LJ .94 mm and LA . 150 mm.
The CW50 was calculated as 122 mm (Table 1). The left corner of
the graph shows a minimum total SSR at 124– 129 mm and 119–
124 mm for RPL and RPH, respectively.
Dependent variable Y
Juvenile B
Adult B
Abdomen
1.565 –1.633
1.390 –1.439
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .
RPL
1.236 –1.316
1.560 –1.647
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .
RPH
1.270 –1.337
1.419 –1.490
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .
RPW
1.147 –1.223
1.315 –1.399
The confidence interval does not overlap between juveniles and adults of
either variable.
324
A. Ungfors
Figure 8. (a) Absolute fecundity (number of eggs) plotted against CW, (b) relative fecundity (number of eggs per dry body weight) plotted
against CW (mm), and (c) oocyte diameter of female edible crabs (n ¼ 39) in Swedish waters. Oocyte diameter (mm) is similar for large and
small batches (linear regression, p . 0.05). Mean oocyte diameter is 383 mm (s.d. +20), the s.d. being based on three subsamples.
of 16 ovigerous females of 122– 159 mm at a site off northwest
Norway (Woll, 2003) gave an indication of the size of ovigerous
females in Norwegian waters. Statistical analyses (minimum of
SSR) and graphical observations (Figure 6) of female allometric
data indicate three cohorts: one with relatively steep allometric
growth of the abdomen ,105 mm CW, one with relatively less
growth of crabs 105–133 mm CW, and one for larger crabs with
faster growth. Interestingly, Tallack (2002b) found a change in
relative AW in females .100 mm, consistent with the present
findings of first minima at 95–104 mm and a CW50 of 104 mm.
Tallack (2002b) also noted that female pleopod capacity had an
inflection point at 138 mm CW. This phenomenon is also
observed in snow crab (Chionoecetes opilio; Alunno-Bruscia and
Sainte-Marie, 1998), those authors suggesting a downscaling in
the allometry of intermediate-sized crabs brought about by later
structural limits on abdomen size. The size at which sexual maturity of females is attained covers a wide range. It seems that copulation takes place once the females reach 110 mm CW, and
physiological maturity one moult later at around 130 mm CW,
but that fertilization needs yet another moult, at around 150 mm.
Findings on the size of mature male in the Skagerrak and the
Kattegat (Figure 5, Table 1) reveal a similar size range as reported
from other areas. Edwards (1979) observed male crab gonads
from Yorkshire and southwest Ireland, and based on the presence
of a ripe vas deferens, suggested that most males .110 mm were
mature. Similar studies around the Shetland Islands suggest
maturity (CW50) at 110–114 mm CW (Tallack, 2002a). The
CW50 in the Bay of Biscay is at about 102 mm (67 mm CL), on
the basis of histological analysis of gonad development (Le Foll,
1986). In the current work, classification of the gonads of interand post-moult males suggests that shell condition does have an
impact on gonad development (Figure 5). This finding is contrary
to that of other authors, who suggest that gonad maturation is not
affected by moulting (e.g. Edwards, 1979; Pinho et al., 2001), but
a change during the year in male Cancer magister sperm content
has been shown by Swiney and Shirley (2001). Enlargement of the
male chela at 110 mm CW (the onset of maturity) is reported by
Edwards (1979), some 9–12 mm less than the CW50 of Swedish
male crabs assessed on the basis of morphometry. However, the
intersection point discriminating Shetland juvenile male crabs
from adults is calculated to be 102– 105 mm CW (Tallack, 2002b),
a value conspicuously lower. Differences in methodology (intersection vs. 50% mature) can explain some of the differences, but
geographical differences in size at attainment of maturity cannot
Table 4. Summary of the edible crab escapement experiment of creels equipped with traps with gaps of different
diameters (75 – 90 mm).
CW (mm)
75 mm
80 mm
85 mm
90 mm
Total (%)
F
M
Total (%)
F
M
Total (%)
F
M
Total (%)
F
M
115–119
0
0
0
93.8
7
8
44.0
3
4
63.0
5
5
. . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . .
120–124
0
0
0
37.5
3
3
44.0
4
3
63.0
5
5
. . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . .
125–129
0
0
0
0
0
0
13.0
0
2
38.0
3
3
. . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . .
130–134
0
0
0
0
0
0
6.0
0
2
44.0
1
6
. . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . .
135–139
0
0
0
0
0
0
0
0
0
6.0
0
1
. . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . .. . . .
140–144
0
0
0
0
0
0
0
0
0
6.0
0
1
Four females (F) and four males (M) of each range of CW class were located within a creel, and each combination was run overnight
on two occasions. The total proportion of escapes (%) are given per gap and CW class (n ¼ 16), as is the sex-specific number of
escapes.
325
Figure 9. Different hypothesized MLS and the resulting catch potential in the Skagerrak (Strömstad, Fjällbacka, and Lysekil) and Kattegat
(Varberg and Groves Bank) for (a) female and (b) male edible crabs. The number of crabs per area is given in the section Material and
methods.
be excluded. Application of morphometric and reproductive data
that considers the developing male gonad to be immature results
in a CW50 at the higher end of these findings (117–122 mm CW).
However, interpreting developing gonads as mature yield a value
of CW50 at the lower end, close to a CW50 based on histological
analyses in the Bay of Biscay. Campbell and Eagles (1983) considered male gonads that were slightly developed to be immature,
because of their low numbers and the small developing spermatophores. In summary, the onset of sexual maturity for males is at
size ranges between 100 and 120 mm CW, if based on the findings
herein and in earlier literature.
Fecundity of the edible crab (0.5–2.6 million eggs, Figure 8a)
is in accord with findings in the UK (0.8 –2.9 Million eggs;
145 –183 mm CW, Edwards, 1979) that show that fecundity
increases with female size. Larger females not only have larger
gonads, but their pleopod capacity, sperm content in spermathecae, and AW increases with size (Tallack, 2002b). Any variation in
the fecundity between crabs caused by differences in the moulting
stage (Hankin et al., 1989) or egg development (O’Clair and
Freese, 1988; Shields, 1991) is probably small in this study because
all females (except one) were of similar inter-moult stage, there
was no visible eye-pigment formation of the eggs, and the eggs
were of similar colour. In addition, the eggs were of similar size,
despite differences in absolute numbers per batch. However,
fecundity standardized for body weight is similar for the females
in the size range seen here (Figure 8b) and the egg mass to body
weight ration was of similar magnitude to that of other species
of the genus Cancer (11 –19 %, Hines, 1991). The eggs of cancrid
crabs are of similar size, and because of the large body size of the
animals, the fecundity of cancrid crabs is among the highest
reported (Hines, 1982), especially that of larger females.
Management recommendations and their effects
on catch potential
Hartnoll (1969) suggested that female crabs are mature when they
are capable of extruding eggs, and males when they can mate/
copulate successfully. This means that the crabs must be both
physiologically and functionally mature before they can be treated
as fully mature. To reduce the risk of recruitment-overfishing,
landing restrictions on females could be introduced if based on
observations on the size-specific proportion of ovigerous crabs in
the population. However, few egg-carrying female edible crabs are
captured by the fishing gear (Edwards, 1979; Howard, 1982), and
female crabs in cold, temperate waters may not spawn annually
(Swiney et al., 2003), all of which results in sampling problems
and biases. Other characters can be used as indicators for female
maturity analysis to overcome sampling problems and biases.
Physiological and functional maturity are not synchronized for
females, but span wide ranges, and for this reason caution in
instituting management action is needed. Further, fecundity is
magnitudes higher for large females than for first-spawners, and
ovigerous females are likely to have a higher CW50 than assessed
through physiological maturity analysis. For male crabs, physiological and functional maturity are more synchronized, and take
place at smaller size. However, small physiologically and functionally mature male Chionoecetes opilio and Cancer gracilis rarely take
part in reproduction because of competition with larger males
(Alunno-Bruscia and Sainte-Marie, 1998; Orensanz et al., 1995).
Also, the size of copulating males exceeds that of post-moult
females (Hankin et al., 1997), indicating copulation size limits for
smaller males. However, Edwards (1966) found that a 110 mm
male Cancer pagurus copulated with a 151 mm post-moult female
and that the sperm contribution of small male edible crabs was
less than expected from gonad and morphometric studies alone.
Maturity characteristics tend to be sampled by traps that may
have underestimated the real CW50, because the proportion
mature may well be higher in active than in passive fishing gear
(Smith et al., 2004). Precautionary management based on a possibly underestimated CW50, along with the diverse maturation
process of the exploited edible crab stock in Swedish waters,
results in a suggested MLS for females and males of 140 mm CW,
particularly if the crab industry develops and fishing effort burgeons. A legislated MLS of 140 mm CW would ensure that almost
all of Swedish landings of male edible crabs are physiologically
and functionally mature, that 75% of female crabs are physiologically mature, and that approximately 25% of female crabs are
326
functionally mature. In other words, spawning is relatively intense
and fecundity fairly high, so even the larger female crabs may have
accessibility to suitable mating partners. I assume that the MLS in
force in the English Channel (.140 mm CW) exceeds the size at
which 50% are mature (Bennett, 1995). The MLS in neighbouring
Norwegian water is just 110 mm CW south of 608N, and for that
reason alone there seems to be reason for Norwegian authorities
to reconsider it or to find other ways of improving management
of their edible crab resource. The MLS of male Cancer magister is
155–165 mm, a value that allows most male crabs to mate at least
once before capture, and capture of female crabs is prohibited
(Siddeek et al., 2004). As an alternative for the Skagerrak and the
Kattegat, or in combination with a MLS, there could be a legislated change in the size of the present mandatory escape gap to
avoid capturing undersized crabs. The diameter of the circular
gap would need to be increased from its present 75 mm to
90–92 mm. Such a gap size can be estimated from a length–CW
regression (Brown, 1982), assuming that length is a discriminating
character. Additionally, the manipulative experiment with different escape gaps conducted here showed that a 90 mm gap is
needed for crabs 135–139 mm CW to escape (Table 4). The catchability of ovigerous females in creel fisheries (for crab and lobster)
is so low that restriction on landing probably does not need to be
considered. However, the bycatch of ovigerous female crabs in, for
example, gillnet fishing for lumpfish or flatfish, which causes high
levels of crab mortality, does need to be assessed. Seasonal closure
of the crab fishery during peaks in moulting may be necessary to
decrease handling mortality of crab pre-recruits and recruits,
particularly if fishing effort burgeons.
The catch potential will be affected along the Skagerrak coast
but to a lesser extent in the Kattegat (Figure 9). Stock assessment
of crustacean fisheries (Smith and Addison, 2003) estimates both
short- and long-term yield benefits from instituting an appropriate MLS, and it also yield other advantages that make the management action acceptable to stakeholders (the professional fishers).
Length cohort analyses of edible crab on the east coast of England
have shown long-term gains in yield per recruit and biomass per
recruit attributable to increases in the MLS (Addison and Bennett,
1992). In addition, increasing fishing effort to overcome shortterm losses did not counterbalance the long-term gain to the
population. Considering stock –recruit relationships and the
higher economic value of larger crabs may even result in greater
gains than are immediately obvious, but density-dependent effects
may limit those benefits. Assessments of the effects of an increase
in the minimum size at first capture of Dungeness crab Cancer
magister in the USA and Canada indicate increases in future
harvest rate (Siddeek et al., 2004), i.e. increases in yield. Similar
modelling of yield per recruit for the crab length cohorts present
in the Skagerrak and the Kattegat may indicate both short- and
long-term beneficial effects of increasing the MLS to 140 mm.
Acknowledgements
I thank all the fishers of the professional crab fishing boats
involved in sampling, Hans Hallbäck (IMR), who provided data
on the size composition of ovigerous females for comparison with
other maturity characters, and two anonymous referees whose
comments helped improve the manuscript. The study could
not have been performed without support from the
SUCOZOMA programme and the development project Swedish
West Coast Crab.
A. Ungfors
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doi:10.1093/icesjms/fsl039
II
Fisheries Research 84 (2007) 345–357
Movement of adult edible crab (Cancer pagurus L.) at the
Swedish West Coast by mark-recapture and acoustic tracking
Anette Ungfors a,∗ , Hans Hallbäck b , Per G. Nilsson a
a
Department of Marine Ecology, Tjärnö Marine Biological Laboratory, Göteborg University, S-452 96 Strömstad, Sweden
b Institute of Marine Research, National Board of Fisheries, S-453 30 Lysekil, Sweden
Received 6 March 2006; received in revised form 10 November 2006; accepted 12 November 2006
Abstract
Movements of the edible crab Cancer pagurus were investigated from mark-recaptures in the Skagerrak and Kattegat. Crabs were released in
1968–1973 and in 2003 from six main areas along the Swedish west coast, and from one offshore bank in the Kattegat. Recaptures were reported
for up to 7 years after the release. Sex-specific differences in migration were found: females migrated significantly longer distances than males,
and higher proportions of males stayed within the area of release (60 and 48% of males versus 28 and 19% of females) were recaptured within
1 km of the release site: initial and recent mark-recapture studies, respectively. The movement direction varied with sampling location, however
females tended to move in a net southerly direction. The range of mean rates of movement within the first month were 325–345 m d−1 for females
and 202–299 m d−1 for males. Over longer time periods mean rates of movement were significantly lower. There was no significant impact of
size class on the distance migrated. Short-term (2 months) movements of nine male edible crabs were studied with acoustic transmitters and
active tracking. The movement pattern varied among individuals: some stayed in the same area for weeks whereas some made regular movements
every day during the tracking period. The difference in migration pattern of females and males, and the largely southward migration of females is
consistent with the hypothesis that the migration is related to reproduction. By moving to the south to release their larvae, females may compensate
for larval dispersion in the northbound current along the Swedish west coast. The observed migration pattern indicates advisable management
options in Sweden for this commercially fished species: protection of areas with high proportion of egg-bearing females from fishing, especially
in the Kattegat. Significantly, local management only on a small spatial scale is not recommended as the resource is seasonally shared, if not the
effect on the crab population is monitored.
© 2006 Elsevier B.V. All rights reserved.
Keywords: Edible crab; Cancer pagurus; Mark-recapture; Acoustic tracking; Migration; Management
1. Introduction
The dispersal ability of a species is related to that species’
population structure (Bohonak, 1999), so that higher dispersal
ability in general is associated with decreased differentiation
(e.g. measured by genetic distances) among populations. Consequently, knowledge of the dispersal processes during the entire
life cycle of a species i.e. larval dispersal and the juvenile/adult
life style may give an estimate on the geographic distribution of
a population and the connectivity among populations (Jennings,
2001; Hellberg et al., 2002). The larval distance of dispersal
depends not only on the biology of the species (e.g. larval development time, hatching season and larval swimming behaviour),
∗
Corresponding author. Tel.: +46 526 686 88; fax: +46 526 686 07.
E-mail address: Anette.Ungfors@tmbl.gu.se (A. Ungfors).
0165-7836/$ – see front matter © 2006 Elsevier B.V. All rights reserved.
doi:10.1016/j.fishres.2006.11.031
but also on the regional oceanography (e.g. directional currents,
topographic gyres and cross shelf currents) and hydrological
parameters (temperature, salinity). The distance of dispersal differs among adults according to the life-style: benthic and sessile,
benthic and non-sessile, or pelagic. A non-sessile species has the
potential to disperse over geographic areas, also as an adult. At
the extreme, larval dispersal and adult movement can interact
and result in high dispersal, or counteract and result in relatively low realised dispersal despite high dispersal potential for
both larvae and adult. For commercial species knowledge of the
population structure is important for management reasons. For
example, Begg et al. (1999) discuss the importance of identifying the stock structure of a species in order to manage a fishery
effectively.
Here we describe a study on the migration of a commercial crustacean species with a hypothesised moderate dispersal
potential. The edible crab Cancer pagurus (L.) has plank-
346
A. Ungfors et al. / Fisheries Research 84 (2007) 345–357
totrophic larvae that are pelagic at least for 60 days at
temperatures of 15–20 ◦ C (Nichols et al., 1982; Thompson et
al., 1995). Adults are characterised as mobile and benthic.
The distribution of the edible crab on the European Atlantic
Coast stretches from the Lofoten Islands, Norway to Portugal (Christiansen, 1969). In Sweden edible crab occurs on the
west coast in the Skagerrak and Kattegat. The fishery of edible crab in Sweden is small (registered landings in 2004 were
164 tonnes) but has potential to increase as fishermen switch
from declining fish stocks. The fishery is open year-round but
most professional crab fishermen fish during July–November.
A large but un-quantified amount of edible crab is taken by
amateur fishermen during the summer months. Both sexes are
harvested, but as the price for females is higher, fishermen tend
to choose areas were females dominate (higher female frequency
in captures, Ungfors, pers. observations). There is no regulated
minimum landing size (MLS) but obligatory Ø75 mm gaps in
traps and fyke-nets allow the escape of individuals smaller than
110–115 mm CW. The carapace width at size of maturity (CW50 )
based on gonad development in Swedish waters is 132 mm for
females and 117 mm for males (Ungfors, submitted).
In this paper we report the study of movement patterns of subadult and adult edible crabs on the Swedish west coast. Long and
short-range movements of adult edible crab have been studied
with different mark-recapture techniques and in different European areas; claw-tagging lost during moulting on the North Sea
coast of UK (Mistakidis, 1960; Mason, 1962), persistent suturetagging in the English Channel (Bennett and Brown, 1983), the
Bay of Biscay (Latrouite and Le Foll, 1989) and east coast of
England (Edwards, 1979) and ultrasonic transmitters in Scotland
(Hall et al., 1991) and Norway (Skajaa et al., 1998). We present
previously unpublished data from a tagging study undertaken in
the late 1960s and movement data from a recent tagging study
in 2003. The recent study used different mark-recapture areas
to the initial study but also used one area in common. Acoustic
tracking of males was also performed in 2005 to gather information on short-term movements. We specifically investigate
sex-specific differences in distance, direction and rate of movement, and analyse whether migration occurs seasonally, whether
it is size-dependent. We also investigate the movement pattern of
repeatedly recaptured individuals. Movement patterns are compared between areas and between studies (i.e. 1968–1973 and
2003). The causes of movement, their effect on stock structure,
and their management consequences are discussed.
Fig. 1. On the map are the seven release areas on the Swedish west coast and
offshore Kattegat shown. Circles show release areas in the 1968–1973 study and
squares show release areas in the 2003 study. The arrow points at the area of
Acoustic tracking.
crabs and 3135 crabs in Skagerrak and Kattegat, respectively
(Table 1). During the tagging exercise crabs were released on the
fishing grounds or occasionally on crab grounds in close vicinity. The bathymetry of the two basins differs substantially: the
Skagerrak deepens steadily offshore (maximum depth 700 m,
mean depth 210 m (Rodhe, 1996)), while the shallow Kattegat basin has a maximum depth of 124 m (mean depth 23 m)
interspersed with shallower 20–30 m offshore Banks (Fonselius,
1995). In the acoustic tracking study crabs were fished and
released in a small shallow coastal bay (maximum depth 20 m,
58◦ 51 N, 11◦ 08 E, Fig. 1) within 1 month (4, 5, 16 and 29 June
2005). In this study distances between collection and release
locations were less than few hundred meters.
2. Materials and methods
2.2. Tagging and recapture
2.1. Study area
Between 1968 and 1973 a total of 3749 crabs were tagged
and released in three areas along the Swedish Skagerrak coast
(Fig. 1, Table 1). Seventy-eight percent of the females and 74%
of the males were released between September and December,
the remainder between January and August. The recent markrelease study in 2003 took place at two coastal areas in Skagerrak
and two coastal areas in Kattegat, and at an offshore fishing bank
in Kattegat (Fig. 1). The total number of marked crabs was 4975
Crabs were mainly caught by professional fishermen
although some crabs used in the initial study were sampled
by Scuba diving. Three marking methods were used in the
mark-release studies: in the initial study crabs were marked by
a modification of the suture-tagging technique first described
by Mistakidis (1959). Numbered plastic discs were posterior
attached by a braided Terylene thread through two holes pierced
in the carapace epidermal suture. The recent study used two tagging methods: (i) T-bar tags were inserted through a 2 mm hole
347
Table 1
The release and recapture number, and average carapace width of edible crabs Cancer pagurus marked in different areas in (a) the 1968–1973 and (b) the 2003 study
for females and males, respectively
Release location
Releases
Number of females
(a) 1968–1973 mark-recapture study
Fjällbacka
712
Brofjorden
337
Lysekil
1058
Sum
Total
2107
3749
(b) 2003 mark-recapture study
Strömstad
1420
Fjällbacka
1708
Tistlarna
274
Katt. Inshore
794
Katt. Offsore
1144
Sum
Total
5340
8110
Recaptures
Number of males
Carapace width (mm)
Number of females
Number of males
Mean ± S.D. (females)
Mean ± S.D. (males)
155 ± 17
155 ± 15
152 ± 16
147 ± 15
147 ± 16
143 ± 15
732
140
770
326 (46%)
121 (36%)
389 (37%)
199 (27%)
22 (16%)
193 (25%)
1642
836 (40%)
1250
414 (25%)
764
1083
119
365
439
111 (7.8%)
127 (7.4%)
35 (12.8%)
38 (4.8%)
156 (13.6%)
2770
467 (8.7%)
688
38 (5.0%)
77 (7.1%)
13 (10.9%)
13 (3.6%)
80 (18.2%)
139
140
152
151
168
±
±
±
±
±
17
17
15
51
63
134
138
143
140
158
±
±
±
±
±
22
20
17
18
18
221 (8.0%)
Edible crabs in the range of 95–209 mm carapace width were marked. Releases in 1968–1973 study generally occurred in September–December, while release
periods in 2003 were: Strömstad 1–9 September, Fjällbacka 23–28 June and 26–29 August, Tistlarna October–December, Offshore Kattegat 18–19 August, inshore
Kattegat 1–2 December.
drilled in the epidermal suture. Eight cm long numbered plastic
ID-bands hung from these tags and could be readily observed.
This type was used at the offshore and inshore Kattegat area.
(ii) In the Skagerrak (area Strömstad and Fjällbacka) and the
northern Kattegat (area Tistlarna) black cable ties with yellow
numbered discs tightened around the merus segment of the first
periopod (claw) were used as a mark. The tagging procedure
took mainly place aboard the fishing boats direct after capture
and crabs were released within 2 h in close vicinity to the capture
location. Information about the mark-and recapture project was
spread to Nordic fishermen and authorities.
For acoustic tracking, nine male edible crabs were marked
(dorsally secured with glue on the carapace) with ultrasonic
transmitters (Sonotronics IBT-96-1; 25 mm × 8 mm, 1.5 g; 21
Day Life-Time; range 500 m+; 69–77 kHz). During a 2-month
period (or until the transmitter expired) the crabs were actively
tracked using a directional Vemco VR 60 and the GPS position
was taken every, or every second day. The technique allowed for
individual identification.
2.3. Analysis
Distance and direction of movement of recaptured crabs were
calculated in the GIS programme ArcView 3.2 (ESRI inc.) using
the extensions Animal movement (USGS-BRD, Alaska Biological Science Center) or Path, with distances and Bearings
3.2 (Jenness Enterprises, USA). Factorial Analysis of Variance (two-factor ANOVA) was used to compare movements
(total individual distances) between areas and sexes. For statistical analyses, data sets were repeatedly balanced by randomly
sampling an equal number of crabs from each group. For calculating means and associated measures of uncertainty shown
in figures and tables, the entire data set was used. Homogene-
ity of variances was tested using Leveneı̌s test and the data
were log-transformed when necessary. For some data sets, variances could not be made homogenous by transformation. For
these analyses (mentioned in the text) we show the resulting
p-values, although these should be interpreted with caution.
Fisher’s LSD were used as post hoc test. The impact of size
on total movement distance was statistically analysed with
one-factor ANOVA (four levels, ≤120, 121–140, 141–160 and
≥161 mm CW). For illustration of direction of movements, bearing data were grouped into eight directions using 45◦ intervals
(0◦ ± 22.5, etc.) and the pattern shown in spider diagrams. Due
to uncertainties of exact location of some recaptures (e.g. missing details as on which side of a small skerry the recapture
occurred or in situ estimation of distance to shore, etc.), we
include movements of more than 1 km in the directional analyses. In order to assess whether this arbitrary 1 km limit is
too strict and introduces bias we also present direction analyses with shorter movements from the recent study. Statistical
analyses of movement direction involved a Goodness of fit test
against an expected 1:1:1:1 ratio using the G-statistic (Sokal and
Rohlf, 1995) of directions grouped into four 90◦ interval (North
316–45◦ , East 46–135◦ , South 136–225◦ , West 226–315◦ ). To
compare movement distance between seasons tagging month
and recaptures within 30 days were considered. Seasonal movements and differences in rate of movements based on elapsed
time before recapture (four levels) were analysed with onefactor ANOVAs and Fisher’s LSD post hoc test. Recaptures
less than 1 km and rates considered unrealistic (>3000 m d−1 )
were excluded in the rate analysis. A test of independence using
the G-statistic (Box 17.8 Sokal and Rohlf, 1995) were used to
compare the distribution of directions towards N:E:S:W from
Fjällbacka release area between the periods for comparing recapture rates.
348
recaptured once (Table 1), and of these 206, 63 and 5 individuals were recaptured two, three and four times, respectively. The
recapture frequency of females (40%) was significantly higher
than the recapture frequency of males (25%) (G-test of independence, G = 5.2, p = 0.023). The last reported recapture from
the 1968–1973 study occurred in 1977, 7 years after the crab
was marked. In the 2003 study 50% of recaptures were within 1
month, 89% within a year and 10% in the second year (Fig. 2).
The recapture rate of females (8.7%) was similar to the recapture rate of males (8.0%) (G-test of independence, G = 0.03,
p = 0.86). Repeated recaptures occurred: of the 688 recaptured
individuals (Table 1), 48 were recaptured twice and 1 three times.
3.2. Pattern of movement
Fig. 2. The number of recaptures by days after release. The time after release is
divided into twenty-seven 30-day periods, and the number of recaptured crabs
per interval are shown for (a) the 1968–1973 and (b) 2003 mark-recapture study.
The number given at the x-axis is the last day in each interval. The regular annual
increases in recapture rate indicate the Autumn periods.
3. Results
3.1. Pattern of recapture
Most recaptures came within 2 years of release, and the
temporal pattern of recoveries showed marked annual peaks of
recaptures in autumn (Fig. 2). In the 1968–1973 study 28% of
all recaptures was recaptured within 1 month, 87% during the
first year and 12% in the second year. 1250 individuals were
3.2.1. Distance and direction
Females migrated longer distances than males, and in some
areas were the frequency of longer movements larger than in
others (Table 2, Fig. 3). Females moved on average 6.4–21.7 km
and males 1.5–8.8 km (range of area specific means) (Table 3).
The frequency of longer movements increased with time before
recapture, especially for females (Fig. 4).
Female long-range movements (>5 km) were predominately
towards north and south from Strömstad, Fjällbacka and inshore
Kattegat, towards south from the Brofjorden, Lysekil and Tistlarna and towards east from offshore Kattegat release area
(Fig. 5). Movements >20 km were towards south in 78 and
62% of the female migrations from coastal areas, 22 and 33%
were toward north and less than 5% in eastward or westward direction in the initial (ntotal = 162) and recent (ntotal = 58)
study, respectively. Statistical analyses of direction pattern confirmed differences between areas and preferred directions within
areas: The frequency of movements toward the four compass
points (N:E:S:W ± 45◦ ) differed among release areas in the
initial and recent study, for both sexes and movement-ranges
(Goodness of fit test; GHeterogeneity , p = 0.0001–0.03). The
only exception to this pattern was for long-range movements
of males in the initial study. The female direction pattern was
not uniform toward the four cardinal directions (Goodness of fit
test; preplicates < 0.001–0.042) except for short-range data from
Fjällbacka in the recent study (Table 4). In most cases statisti-
Table 2
Distance calculations and statistical analyses (individual total distance) for the 1968–1973 and 2003 mark-release studies
1968–1973 study
Females
Proportion > 1 km
Mean ± S.D., median,
q25 –q75 , max, n
ANOVA log-transformed
factors: sex and area;
dependent variable:
total distance (m)
2003 study
Males
72%
40%
13.0 km ± 23.2, 2.9 km,
1.9 km ± 4.6, 0.7 km,
1.2–10.3 km, 228 km,
0.3–2.1 km, 60 km,
n = 836
n = 414
Significant interaction (pinteract = 0.01) in unbalanced but not
in balanced (8 of 10 random samplings of data
pinteract = 0.065–0.74, n = 22). Sex and area significant
(psex < 0.0001 and parea ≤ 0.043). Heterogenous variance.
Fisherı̌s LSD: longer distances for females, Fjällbacka
differ from Brofjorden & Lysekil
Females
Males
81%
52%
11.2 km ± 17.4, 4.0 km,
4.4 km ± 8.3, 1.8 km,
1.8–10.8 km, 130 km,
0.7–3.8 km, 59 km,
n = 467
n = 221
Significant interaction (pinteract = 0.003) in unbalanced but
not in balanced (10 of 10 random samplings of data pinteract
0.081–0.623, n = 13). Sex and area significant (psex < 0.0001
and parea > 0.0001–0.031, except parea = 0.109 in 1/10 of
samplings). Heterogenous variance of 8/10 samplings.
Fisherı̌s LSD females longer distances, especially
Fjällbacka differ from other locations
349
Fig. 3. Individual total distance presented as Boxplots (percentiles, median). (a) Females and (b) males in the 1968–1973 study and (c) females and (d) males the
2003 study. Sample size (n) is given. In (a) is the extreme distance value (*) at 228,147 m excluded.
cal analyses (Goodness of fit test, preplicates ) were not calculated
for males due to few replicates (Table 4). An overview of the
movements, based on Arcview layouts of all female movements from all the release locations in the 2003 study, is given
in Fig. 6.
3.2.2. Season
In the 1968–1973 study females moved longer distances
in autumn months than in summer months (Fig. 7, one-factor
ANOVA pfemales < 0.0001, Fisherı̌s LSD October and November
longer distances compared to July, August and September). Males did not show a similar pattern (pmales = 0.249).
In the 2003 study crabs of both sexes moved longer distances in August compared to June (Fig. 7, one-factor
ANOVA pFemUnbalanced = 0.004, pFemBalanced = 0.063, n = 8 and
pMaleUnbalanced = 0.005, pMaleBalanced = 0.002, n = 4).
3.2.3. Size
There was no significant difference in total distance between
four tested size classes (≤120, 121–140, 141–160 and ≥161 mm
Table 3
Distance calculations per area for (a) the1968–1973 study and (b) the 2003 study
Females
Mean ± S.D.
(a) 1968–1973 study
Fjällbacka
12.6 ± 23.1
Brofjorden
13.4 ± 20.7
Lysekil
13.3 ± 24.2
(b) 2003 study
Strömstad
Fjällbacka
Tistlarna
Katt Insh
Katt Offsh
12.6 ± 21.2
11.6 ± 17.7
21.7 ± 22.7
16.2 ± 17.1
6.4
Males
q25 –q75
Max
n
Mean ± S.D.
Median
q25 –q75
Max
n
2.5
5.9
2.8
0.8–10.6
2.2–11.5
1.2–10.1
137
117
228
327
120
389
1.5 ± 4.1
3.4 ± 5.9
2.1 ± 5.0
0.6
1.4
1.1
0.1–1.7
1.0–2.7
0.3–2.4
36
28
60
197
22
193
5.2
3.5
7.7
12.1
3.5
2.3–10.8
0.9–17.2
6.0–43.3
3.9–18.1
1.5–5.6
130
121
71
72
44
111
127
35
38
156
3.2
4.9
3.2
8.8
3.9
±
±
±
±
±
1.7
0.6
3.5
2.6
2.5
1.0–3.1
0.2–3.3
1.1–4.7
1.2–14.2
1.5–3.8
18
59
6
32
40
38
77
13
13
80
Median
4.4
11.4
1.9
11.1
6.0
350
Fig. 4. The histograms show the distance distribution at different times before recapture. The total number of recaptures per time interval is distributed among five
different distance classes: 0–5, 5–10, 10–50, 50–100 and >100 km. The time intervals are grouped on basis of lapsed months before recapture, from within 1 month
to more than 24 months. Female frequency is shown in (a) for the 1968–1973 and (c) for the 2003 mark-recapture study. Male frequency is given in (b) for the
1968–1973 and (d) for the 2003 mark-recapture study. Sample size per time interval (n) is shown on top of each bar.
CW), neither females nor males in the two studies (one-factor
ANOVA, p > 0.24).
3.2.4. Rate of movement
The rate of movement for females and males was grouped
according to elapsed time before recapture. The rate of move-
ment females and for males within 1 month was significantly
higher than movement rates of crabs recaptured after a longer
time period (Table 5, one-factor ANOVA log-transformed data,
pfemales < 0.0001 and pmales < 0.0001, Fisherı̌s LSD: females
1 month > 2–6 months > 7–12 months ≥ 12 months, males
1 month > 2–6 months = 7–12 months = >12 months) in the
Table 4
Comparison of direction pattern between areas and statistical analyses of direction within an area in the (a) 1968–1973 and (b) 2003 mark-release study
(a) 1968–1973 mark-release study
Females
1–5 km
>5 km
Males
1–5 km
>5 km
Fjällbacka
Brofjorden
Lysekil
45:30:56:14, p < 0.001
71:1:55:0, p < 0.001
11:5:25:19, p < 0.001
3:4:55:2, p < 0.001
57:96:17:41, p < 0.001
32:15:85:7, p < 0.001
16:17:27:9, p = 0.02
1:0:3:0
4:3:4:4
0:0:2:1
30:25:9:22, p = 0.012
7:2:6:0
Strömstad
(b) 2003 mark-release study
Females
0–5 km
24:4:24:3, p 0.001
1–5 km
21:3:23:2, p <0.001
>5 km
27:0:29:0, p 0.001
Males
0–5 km
1–5 km
>5 km
7:8:14:3, p = 0.047
5:3:13:1, p = 0.002
4:0:2:0
Fjällbacka
Tistlarna
Katt. Inshore
Katt. Offshore
25:17:23:14, p = 0.25 ns
18:9:11:5, p = 0.042
24:2:22:0, p 0.001
1:5:0:0
1:5:0:0
4:0:24:1, p 0.001
5:0:7:0
5:0:4:0
13:3:7:3, p = 0.02
7:81:15:17, p 0.001
6:61:14:16, p 0.001
3:25:3:5, p 0.001
17:19:14:15, p = 0.83 ns
6:4:7:5, p = 0.82 ns
4:2:6:0
6:2:2:0
3:2:2:0
2:2:0:1
3:2:2:0
0:2:2:0
1:1:2:2
5:29:23:7, p = 0.000
5:25:16:7, p = 0.000
0:11:1:4
The data is summarised as the number of edible crabs toward each of four directions: North (316–45◦ ), East (46–135◦ ), South (136–225◦ ) and West (226–315◦ ). Data
is statistically analysed with Goodness of fit test: p < 0.05 means a significant difference of the observed distribution compared to an even (25% in each direction)
distribution. Analyse not performed if n ≤ 20. ns = non-significant.
351
Fig. 5. The movement frequency toward eight different directions for female and male crabs in the 1968–1973 and 2003 mark-recapture study. In (a) are female
movements longer than 5 km and in (b) are male movements longer than 5 km summarised. The direction interval is 0◦ ± 22.5◦ , 45◦ ± 22.5◦ , 90◦ ± 22.5◦ , 135◦ ± 22.5◦ ,
180◦ ± 22.5◦ , 225◦ ± 22.5◦ , 270◦ ± 22.5◦ , 315◦ ± 22.5◦ . Sample size (n) is given for each release area. The scales on the axes differ between 50, 80 and 100%.
1968–1973 and the 2003 study. The maximum rate of movement of all recaptures were 8377 and 3965 m d−1 for females,
and 841 and 1968 m d−1 for males (initial and recent studies,
respectively).
3.3. Comparison of movements in time
The Fjällbacka release area was used in both studies, and
therefore we were able to compare statistically the distance and
352
Fig. 6. The graph shows the individual female movements from the release areas in the 2003 mark-release study. The central map framed with intervening sections,
shows Skagerrak and Kattegat in whole and the four other are magnifications of coastal segments. Unfilled circles indicate points of release.
direction data. For females, the mean distance (km, ±S.D.) for
the two periods was 9.5 km ± 19.9 (n = 433) and 10.6 km ± 17.1
(n = 139) and for males 1.2 km ± 3.7 (n = 244) and 4.6 km ± 11.1
(n = 82). Statistical analyses showed that females moved longer
distances independent of investigational period (two-factor
ANOVA, psex < 0.0005, n = 82). The distribution of directions
(N:E:S:W) was similar between the investigational periods for
females and males, both for all movement data combined,
Fig. 7. The average distance (km) in different months of the year from (a) the 1968–1973 and (b) 2003 mark-recapture study for females and males, respectively.
Calculations are based on crabs recaptured within 1 month of release. The sample size (n) is shown on top of each bar. Standard error bars are shown.
353
Table 5
The mean (±standard deviation and sample size) rate of movement (m d−1 ) within a specified time interval from the 1968–1973 and 2003 study, for females and
males, respectively
1968–1973 study
One month
2–6 months
7–12 months
>12 months
2003 study
Females
Males
Females
Males
325 (±469, n = 139)
137 (±175, n = 145)
48 (±69, n = 335)
49 (±52, n = 124)
202 (±184, n = 35)
46 (±31, n = 16)
14 (±23, n = 90)
9 (±21, n = 51)
345 (±302, n = 193)
166 (±175, n = 109)
97 (±107, n = 65)
53 (±49, n = 55)
299 (±304, n = 81)
71 (±75, n = 37)
38 (±47, n = 21)
27 (±30, n = 18)
as well as for only considering movements longer than 1 km
(G-test of independence, pfemales all = 0.59, pfemales>1 km = 0.91,
pmales all = 0.61 and pmales>1 km = 0.88).
Crab 8, released in northern part of the bay stayed there but
moved between two near-lying stone areas.
4. Discussion
3.4. Repeated recaptures in the 1968–1973 study
For 63 females that were recaptured a second time (movements > 1 km), we analysed whether movement continued in the
same direction or not. Of these, 16 females were recaptured a
third time. Most of the repeated recoveries were made within
the same year but some showed movements extending more
than 1 year. We classified the difference in direction of consecutive movements into four 90◦ (±45◦ ) intervals between first and
second recapture: 43% of the females moved in the opposite
direction (difference ± 136–180◦ ), 32% made further movements in same (difference < ±45◦ ) direction, and the remainder
moved perpendicularly (difference ± 45–135◦ ) in relation the
first recapture direction. This was significantly different from
an expected random 1:2:1 (same: intermediate: opposite) ratio
(Goodness of fit test, G = 26.7, p < 0.001, n = 63). Of the 12
repeated recaptures (between first and second recapture) involving movements >5 km, 4 continued in a same direction and 7 in
the opposite direction (G = 81.9, p ≤ 0.001, n = 12).
3.5. Acoustic tracking
The total movements (total distance per individual) over the
tracked period ranged between 689 and 5440 m (Table 6). The
movement behaviour of male crabs varied such that two of the
crabs (1 and 3) were more prone to move over the actively tracked
period of 27–45 days (Table 6). Crab 1 moved back and forth
within an area (close to the coastline of a small island) while
crab 3 moved consistently south. In fact, a professional fisherman captured one crab 146 days after the last recorded tracking
position, during which time the crab had moved approximately
26 km (179 m d−1 ) south. The individual mean rate of movement over the tracked period was between 28 and 147 m d−1 but
the movement could be as high as 922 m from 1 day to another.
Crabs 4, 5 and 9 moved SSW from the release area (which had
a relatively soft substratum) to an area with stones and coarser
bottom substrate, and stayed then within these. Crab 2 moved
from its release area central in the bay towards west and stayed
at a shallow depth close to the coastline of a small island. Crab 5
moved from the northern part of the bay towards the southwest.
After a short period of moving from location to location crab 6
stayed in a small stone area before heading towards southwest.
We found that females moved longer distances more frequently than males, in all the seven locations and in both
investigational periods. On average females moved 1.8–8.4
times farther than males. Movement patterns at the location that
was common to both studies (Fjällbacka) showed consistency in
distance and direction. However, the majority of recaptures of
both females (89% in 1968–1973 and 92% in 2003) and males
(>99% in 1968–1973 and 98% in 2003) moved less than 36 km
(20 miles). This result is similar to others from inshore in the
English Channel (Bennett and Brown, 1983). Our acoustic tracking of males showed both directed and irregular movements
over thousands of meters indicating that males, like females,
can show directional movement behaviour. In general however,
the shorter average distances and more uniform direction pattern indicate that males were more prone to stay in an area
than were females, and their rather short movements were more
like exploratory routes in all directions, probably searching for
females, new habitats, preys or a response to seasonal temperature changes. Females on the other hand carried out long-range
migrations southwards or northwards along the Skagerrak and
Kattegat coast, and eastwards and northwards offshore Kattegat. Mark-recapture studies in other regions have shown that
females move more frequently than males (e.g. English Channel (Bennett and Brown, 1983), Bay of Biscay (Latrouite and Le
Foll, 1989) and east coast of UK (Edwards, 1979)). However the
frequency of long migrations from the eastern and French side
of the English Channel was higher than we found (Bennett and
Brown, 1983; Latrouite and Le Foll, 1989). This indicates similar
but regionally influenced movement patterns of C. pagurus over
its geographical distribution. Movement studies of Cancer magister (Pacific Coast of North America (Jensen and Armstrong,
1987)) showed that females were more migratory than males
in southern British Columbia (Smith and Jamieson, 1991). On
the other hand, the limited migrations of C. magister in an
Alaskan deep fiord-type estuary showed that males had larger
home ranges than females, 3.75 and 0.4 km2 , respectively (Stone
and O’Clair, 2001). Home ranges (the largest area covered by all
individual positions of recapture or tracking) in our study was
many magnitudes larger, particularly for females but was not
calculated due to lack of data points in our mark-recapture data
and the short (acoustic) tracking duration for the males. In north-
The crabs were released in a Swedish coastal bay (58◦ 51 N, 11◦ 08 E) within 1 month starting the 4 June 2005. The crabs were tracked for 33–45 days every 1–2 days. Movement data including recaptures of crab 1
and 3 in the commercial fishery, 1 and 5 months, respectively, after tracking, is shown in parentheses. Gross movement (m month−1 ) is calculated from the individual mean rate over the tracking period.
689
28 ± 22
178
153
33
21
170
2340
46 ± 68
353
694
41
31
197
1706
50 ± 37
553
566
41
31
168
2537
67 ± 96
467
400
45
33
169
1698
76 ± 71
228
419
29
14
135
1681
77 ± 97
772
760
27
24
146
3909 (30,078)
92 ± 79 (106 ± 111)
447
787 (26,169)
45 (191)
30 (31)
153
1360
53 ± 47
357
304
33
20
169
5440 (6108)
147 ± 218 (143 ± 216)
922
956
44 (77)
29 (30)
129
Total movement (m)
Mean rate (m d−1 )
Max rate (m d−1 )
Max distance (m)
Total days
Tracking occasions
CW (mm)
Mean ± S.D.
9
8
7
6
5
4
3
2
1
Crab
Table 6
Data summary from acoustic tracking of nine male edible crabs
38 ± 7
26 ± 6
160 ± 21
2373 ± 1376
72 ± 124 (82 ± 124)
354
ern California 46% of female C. magister moved < 2 km, and the
stocks were considered to be “extremely localized” (Diamond
and Hankin, 1985). We found 41% of recaptures after 12–24
months, and 27% of recaptures after 2 years, were within 5 km of
the release point (initial study, equivalent figures for recent study
are 27 and 50% but these are based on few recaptures). Consequently female C. pagurus could be regarded as highly localized
on the Swedish west coast. The male population was even more
localized (89 and 64% of recaptures after 12–24 months; 86
and 50% after 2 years, within 5 km, initial and recent studies,
respectively).
There is a risk of misinterpreting a stock as being “localized”
with the mark-release method as the crabs may have moved
extensive distances and back during the period until recapture.
Mark-recapture studies that use conventional tagging methods to
study movement patterns of marine species have been shown to
“tell the truth, but not the whole truth” (Bolle et al., 2005). On the
Swedish west coast, trawling has been allowed closer and closer
to the coastline during the 20th Century but the trawling boundary was moved out to 3–4 nautical miles in 2004 (Anon., 2006).
From the mid-1980s Norway lobster (Nephrops norvegicus) has
been captured in creels, mainly inshore of the trawling boundary and in the northern area of Swedish Skagerrak coast (Anon.,
2006). Static gears (pots) for lobster (Homarus gammarus) and
edible crab have been used commercially since beginning of
20th Century and are extensively in use, generally aggregated
closer to the shore but also offshore on the banks in Kattegat.
These fisheries are all capable of fishing crabs and for that reason no serious limitations or spatial differences in fishing effort
exist on the Swedish west coast. However, the temporal pattern
of recoveries is most probably influenced by fishing practices as
the frequency of recaptures peaks at approximately 30, 300 and
690 days, in both investigational periods. The Swedish monthly
landings of edible crab are highest in August to November (2005
log-book data, National Board of Fisheries) due to high meat
yields (Ungfors et al., 1999) and high catchability (Bennett,
1995). In addition, the annual opening of the Swedish fishery
for lobster (with by-catches of edible crab) in late September
results in large numbers of lobster traps and a corresponding
increase in the chance of reports from recaptured crabs during
this period.
Several hypothesis to explain migration patterns for Cancer spp. have been presented: inshore migration for moulting,
mating (females and males) and spawning and offshore hatching migration (Diamond and Hankin, 1985), migrations toward
exposed area for spawning (Smith and Jamieson, 1991), mating
migration or pre-hatching emigration to avoid osmotic stress
(Orensanz and Gallucci, 1988) of C. magister, feeding migration in C. novaezelandiae (Chatterton and Williams, 1994) and
female migrations related to moulting and mating in C. pagurus at the north east coast of Scotland and England (Mason,
1962; Edwards, 1979). The extensive westerly or south-westerly
migrations in the English channel (Bennett and Brown, 1983;
Latrouite and Le Foll, 1989) are against the prevailing easterndirected Channel current (Dahlgaard, 1995; Guegueniat et al.,
1995). Bennett and Brown (1983) point out that this may be an
offshore migration towards grounds suitable for spawning and/or
counteracting larval drift, and therefore having consequences for
the replenishment of eastern stocks in the Channel. They could
not find evidence for return movements of the adults, but did find
some easterly movements from the inshore (westerly located)
release areas. Stress of repeated capture and handling may
impact crab behaviour, and technical mistakes (e.g. incorrect
reporting from fishermen, or wrong recording of crab number by
the fishery biologists) are possible. However, in our study, over
40% of the repeated recaptures were towards opposite direction
between first and second recapture, which could be interpreted as
return movements. This is an important finding as understanding
of biology and implementation of proper management need not
only to be aware of the one-way migration but also of possible
returns, which theoretically re-establish the stock state.
The prevailing surface current along the Swedish west coast
is northward (Rodhe, 1996). A northward dispersal of pelagic
larvae could be the underlying reason for the observation that
adult females predominantly migrate toward the south when
distances over 20 km are considered. Dispersal of crab larvae
for 2 months by a one-directional current of 0.20 m s−1 mean
velocity (Rodhe, 1996) move the larvae more than 1000 km
downstream of hatching location. This distance is certainly a
substantial overestimation of the true dispersal as the direction
of currents may change on daily basis and larval swimming
behaviour (not least vertical migration (Harding and Nichols,
1987; Park and Shirley, 2005)) will impact the realised dispersal distance. However, this simple calculation may indicate
the need for a evolved behaviour, such as the upstream migration of females prior hatching or larval swimming behaviour
(Shanks and Brink, 2005), to guarantee continued recruitment
along the Swedish coast. Eaton et al. (2003) challenge the formerly accepted wisdom of a northward movement of females
along the east coast of England and Scotland that results in southward transport of crab larvae i.e. recruitment to the main fishery
from the north. Instead the main fishery seem to be on a separate,
self-sustaining population, which may provide adult recruitment
to the north of adult crabs. The relatively high percentage of
migrations towards north in release areas Strömstad, Fjällbacka
and inshore Kattegat could be explained either as return movements of females not spawning that year, adult recruitment to
the north or regional differences in environment e.g. the water
current. The baroclinic northward coastal current (the Baltic current) is more pronounced in Skagerrak than in Kattegat due to
(1) the Kattegat-Skagerrak front forcing this low-saline water
to contract along the Swedish coast, (2) as a result of the basic
cyclonic current around the Skagerrak and (3) the often strong
westerly currents towards the Swedish coast from north Jutland
(Gustafsson and Stigebrandt, 1996). This stronger northward
current around the border between Skagerrak and Kattegat could
explain the higher frequency of southward movement in the mid
Skagerrak and northern Kattegat compared to more southern or
northern coastal release areas.
The relative high share of female recaptures that do not show
signs of long migrations may be explained by their natural life
cycle: females are not ovigerous every year after sexual maturity
in Swedish waters (about 10–20% of large-sized 134–170 mm
CW females have their gonads in a “resting” stage in the spawn-
355
ing period, Ungfors, 2006) and for that reason there is no need
for a compensatory migration every year. Ovigerous females are
rarely captured in baited creels and are observed to congregate in
deep water (Howard, 1982) indicating that females are inactive
during embryogenesis. The spawning period in Swedish waters
is in late November to January (Ungfors, pers. observations)
and larvae can be found from April to October (Thorson, 1946).
The most probable period for migration related to reproduction
in Swedish waters is therefore the autumn, before the winter
spawning and inactive period, after the hatching and regaining
feeding summer period. This is also what we found: for females
the average distance of movement was higher during autumn
than summer months. However, none of our long-range migrating females were in the ovigerous state at recapture (or release).
This controversy between theory of migration and the evidence
is probable more due to the fact that collection and recapture
were by pots, and that ovigerous females are captured in low
frequency in these gears. In addition to the use of pots and low
catchability of ovigerous females, the time for recapture and
ovigerous state was not synchronised: most of the recoveries
were in autumns but crabs are ovigerous state in winter-spring.
Our data suggest that there were no impact of crab size and
distance of movement, which is not what we would expect if the
hypothesis that female movements are of reproductive origin.
Size-independency in migration pattern has also been found in
C. magister (Diamond and Hankin, 1985). In our study the proportion of small marked females and males was low: only 2%
of the females and males were smaller than 120 mm and none
was smaller than 100 mm carapace width. Based on gonad studies (Ungfors, 2006) the main part of the studied crabs could
be regarded as sexual mature and the risk of an immediate
large-scale loss of externally secured tags was therefore not overwhelming. While externally secured tags have a lifetime of a
couple of years at most, persistent tags may last for longer periods and recaptures after longer periods are possible. A higher
frequency of sub-adults may result in a difference in distance
with size.
The average rate of movement in our study decreased with
increasing time elapsed since release, indicating either that crabs
had periods of resting during the migrations, or that some individuals were migrating back to the release areas. Another cause
for the low rate of movement after longer periods may be that
the individuals have fulfilled their movement in a shorter time
and were no longer moving. Depending on the time of tagging
and release, rates of movement could be higher with time as the
probability for migratory behaviour is increasing. For example
if the releases occurred in early spring the rate of movement
would be small the first month but increasing after longer periods (autumn movement). In both studies most releases were
in the autumn or late summer and consequently longer periods
increased “the risk” of including the coldwater inactive winterspring season. The average rate of movement within 1 month
was around 300 m d−1 for females and 200 m d−1 for males,
which is consistent with rates from offshore release points in the
English Channel (Bennett and Brown, 1983) and for C. magister
in British Columbia (Smith and Jamieson, 1991). For recaptures
between 7 and 12 months migration rates were around 50 m d−1
356
(females) and 14 m d−1 (males) comparable with slow inshore
migrations in the English Channel and with C. magister weekly
migrations in an Alaskan estuary (Stone and O’Clair, 2001).
Some recaptures show extraordinarily high rates of over 8377 m
in 1 day. The validity of these data can be questioned but these
high rates have been reported for the English Channel (Bennett
and Brown, 1983; Latrouite and Le Foll, 1989). The mean rate of
acoustically tracked males was 28–147 m d−1 (72 m d−1 in average), which indicates sizeable variation in migration behaviour
even within a short time period.
4.1. Management consequences
Movement patterns of populations obtained from markrecapture studies are limited in space and time, which make it
difficult to draw conclusions about population structure. In our
study we have movement data from seven different locations
within a limited area (Skagerrak and Kattegat) spanning more
than 30 years. Within a restricted area of kilometres there is no
doubt that the shown migration pattern improve the mating possibilities and mating success. Harder to speculate about is the
effect of this migration on the population structure. Waples and
Gaggiotti (2006) found population differentiation at migration
rates up to 0.1–0.2 (the fraction of immigrants in a population). In Sweden captures of new-moulted soft crabs occurs in
July–October, which allows moulting, mating and subsequent
sperm delivery to occur either before or after movement. As
the moulting period starts during the summer period when as
shown in our study, movement rates were lower, sperm delivery may take place before movement, and the mixing of genes
between crabs from different locations is reduced compared to
if the mating occurs after movement. This speculation assumes
that females are the migratory sex, return movements are a rule
and males are stationary i.e. “immigrants” in an area are of low
frequency.
The genetic population structure studied by genetic markers is the result of long-term mixing processes so studies on
differentiation in genetic markers indirectly may indicate the
dispersal (gene flow) of larvae and adults among geographical
areas (Bohonak, 1999). However, we are not aware of any published data on the genetic structure of C. pagurus in any of its
distribution area. Despite the prevailing paradigm that pelagic
larvae confer dispersal (e.g. Hellberg, 1996; Todd et al., 1998;
Uthicke et al., 2001) there is evidence for genetic differentiation in species with pelagic larvae (e.g. for American lobster
Homarus americanus (Tracey et al., 1975), spider crabs (Weber
et al., 2000) and sea urchins (Moberg and Burton, 2000)). An
analysis of the genetic variation along the Swedish west coast is
therefore necessary to complement the results from this markrecapture study, to draw conclusions on mixing processes at the
population level.
The connectivity of populations has profound implications
for the management of these populations. In our study there is
evidence that some individuals are highly mobile (females) but
also that a high portion may be resident. Crabs in this investigation dispersed over distances up to 228 km. This can be compared
with the 450 km range of the Kattegat and Skagerrak west coast.
The proportion of individuals that migrated between Skagerrak and Kattegat (in either direction) was low but nonetheless
present, and this probably represents an important component
of gene flow between the two basins. Fisheries targeting ovigerous adult females during autumn in the Kattegat (Ungfors, pers.
observations) can have seriously negative effects on the fishery resource along the whole coast if these females function as
a source population. In order to combine a fishery on females
with developed ovaries (the preferred crab product in Sweden),
while still maintaining a sufficient larval supply to the north,
different management actions can aid in preventing recruitment
over-fishing (Hilborn and Walters, 1992). One among the many
options for management would be to implement seasonal closures or a marine protected area (MPA) on the spawning grounds
in the Kattegat (to protect spawning females) or the implementation of protected spawning areas regularly distributed along the
Kattegat and Skagerrak coast in combination with catch quotas
in the basins to guarantee a sufficient migratory proportion of
females. Local management only a small spatial scale (hundreds
of km) is not recommended as the resource is seasonally shared
i.e. Skagerrak and Kattegat should most probably be considered
as one management unit unless genetic markers show the opposite. However, as it is difficult to say how the movements found in
our study (some long-range movements of females but also evidence of highly localized stocks) would affect connectivity and
population independency learning by doing i.e. adaptive management (Walters and Green, 1997; Sainsbury et al., 2000) using
different suitable management actions on relatively small spatial
scale in combination with population monitoring and assessment might be the best management option, and would lead to
an increased knowledge of the population dynamics of the crabs.
Acknowledgements
The data underlying this manuscript could not have been
compiled without all the fishermen along the Swedish coast
who have been cooperating and reporting recaptures, or without
field assistance of Christin Appelqvist and Helena Sundström.
Many thanks for practical help during the acoustic study to SvenGunnar Lunneryd, Magnus Wahlberg, and all course participants
of the Marine Bioacoustics course (June 2005) at TMBL and to
Marie-Laure Bégout Anras and Marie-Laure Acolas for acoustic
instruments and instructions. We are grateful to Jon Havenhand for grammar improvement of the manuscript. We thank the
SUCOZOMA programme, the project Swedish west coast crab,
the Institute of Marine Research, Orvar and Gertrud Nybelin
Fund for Fishery Biology Research, and Sonotronics for funding of these studies. Methodologies undertaken in the studies
comply with the current laws of Sweden.
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III
Lack of spatial genetic variation in the edible crab (Cancer pagurus) in the
Kattegat-Skagerrak area
1
1
Ungfors, A., 2McKeown, N.J., 2Shaw, P. and 1Andre, C.
Department of Marine Ecology-Tjärnö, University of Gothenburg,
SE-452 96 Strömstad, Sweden
2
School of Biological Sciences, Royal Holloway University of London, United Kingdom
Corresponding author: Anette Ungfors, Anette.Ungfors@marecol.gu.se, +46 526 686 88
1
1
Abstract
The stock structure of the edible crab Cancer pagurus in Kattegat and Skagerrak was
investigated using eight microsatellite DNA loci. Samples were collected twice at Grove Bank
(N57°) in Kattegat and at Lunneviken (N59°) in Skagerrak, 4-6 years in between. In addition,
one sample collected at Midsund (N62°) in the Norwegian Sea was included as an outgroup.
The genetic differentiation among samples, estimated as global FST=0.002, is significant
(p=0.03) when the statistical test was based on allele frequencies but not when based on
genotype frequencies. Moreover, all single-locus and pair-wise FST values were nonsignificant using both allelic and genotypic tests. Analysis of molecular variance, AMOVA,
did not reveal any differentiation between spatial (Kattegat vs. Skagerrak) or temporal groups
of samples (2001-2002 vs. 2006-2007). A statistical power analysis suggests that using the
same number of loci, sample sizes, and allele frequencies as in this study, we would have a
power of >90 % to detect stock differences of the same magnitude as recorded in the present
study. The processes behind the low spatial and temporal genetic structure might be a high
gene flow in the area due to adult migration and larval dispersal or alternatively, historical
gene flow persisting among recently founded large populations. Local management of the
edible crab fishery can be considered and implemented whereby stakeholders take a
precautionary approach such as implementing size restrictions and not fishing below a certain
local biomass.
Keywords: Genetic stock structure, microsatellite DNA, genetic differentiation, FST, gene
flow, edible crab
2
2
Introduction
A prerequisite for resource management of commercially exploited fish and shellfish species
is to define how the resource is partitioned, spatially (geographically) and temporally, i.e. to
identify stock units. As for species and population concepts there is no universally accepted
definition of what constitutes a stock and there has been a shift towards an adaptive holistic
approach admitting the use and need for several purposes (Begg&Waldman 1999;
Carvalho&Hauser 1999; Waples&Gaggiotti 2006; Abaunza et al. 2008). All attempts of stock
definitions struggle in optimizing a balance on precision and generality, and common words
in the definitions are “self-sustaining”, “integrity/sharing”, “spatial/area” and “temporal/time”
(Cadrin et al. 2005). In contrary to the species or population concept, there is an underlying
meaning of management in the stock definition. The need of conservation of biodiversity or
genetic variation within endangered species has resulted in another debated concept of similar
nature: evolutionary significant unit (ESU) (reviewed in Fraser&Bernatchez 2001). However,
a fundamental difference between stock management and ESU is the aim of maximizing yield
of the former unit versus a more life-sustaining aim in an evolutionary perspective of the
latter. Different methods to investigate the stock unit have been suggested , which all have
their strengths and weaknesses and often reflects the definition chosen by the investigator.
The advantage of using a holistic approach is that one of the techniques may detect stock
structure where others fail to do so. For example, morphologic or phenotypic characters for
stock identification can be biased by environmental modulation so that separate stocks may be
indistinguishable due to similar selection effects (Chaceon quinquedens in Gulf of Mexico vs.
New England Weinberg et al. 2003) while at the other end of the spectrum directional
selection may lead to false estimates of stock heterogeneity (Clupea harengus e.g. in Kinsey
et al. 1994).
Genetic markers are powerful tools for describing population/stock structure (Utter 1991 ;
Carvalho&Pitcher 1995). A major of population genetics to fisheries management has been to
define the concept of ‘stock’ in an evolutionary meaningful way, and to promote the use of
this concept in management (Ihssen et al. 1981; Allendorf et al. 1987; Carvahlo&Hauser
1994). The extent of gene flow among populations, mediated by the forces of genetic drift and
mutation, determine patterns of variation at selectively neutral genetic loci. Over short time
scales the effect of mutation is expected to be negligible with genetic population structure
being the product of opposing forces of gene flow and genetic drift. While gene flow is
expected to promote genetic homogeneity, populations that are not exchanging genes are
expected to acquire differences in frequencies of genetic variants over time by genetic drift.
Therefore, by characterising the distribution of genetic variation, population substructuring
can be detected and the degree of connectivity among populations estimated (Nesbo et al.
2000; Ruzzante et al. 2000; Hutchinson et al. 2001). From a management point of view this
connectivity is often interpreted as a proxy for likelihood of replenishment, or more
specifically, if individuals are removed to what extent will replenishment occur by migration
(Waples 1998). In this way the ‘genetic’ stock concept focuses on the degree of isolation
among stocks.
In general, marine species are expected to show weak population structure over large
geographic areas due to fewer barriers, compared to land, and high dispersal ability via larval
drift and/or adult movements (Ward et al. 1994). However, intra-specific genetic analyses of
commercial decapods have revealed complex patterns of genetic differentiation at various
geographical scales. For example, mtDNA restriction fragment length polymorphism (RFLP)
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3
analysis of European lobster Homarus gammarus revealed distinct genetic clusters and an
overall FST estimate of 0.078 among 44 samples from its European distribution range
(Triantafyllidis et al. 2005). Similarly, Norway lobster, Nephrops norvegicus, revealed
significant differentiation (FST 0.013-0.018) among samples from the North Sea, Irish Sea,
Portugal and the Mediterranean, but with no isolation by distance effect or partitioning
associated with the Atlantic-Mediterranean division (Stamatis et al. 2004 (allozymes);
Stamatis et al. 2006 (mtDNA RFLP)). Studies of decapod species have found genetic
variation over relatively short distances like 40, 142, and 225 km (Weber et al. 2000;
Weber&Levy 2000; Jorstad et al. 2004). Also, enhanced settling of larvae within 0-6 m of
parents, despite a 1-2 week larval dispersal period, have been reported indicating that
dispersal potential may not be realised (Knowlton&Keller 1986). Thus, the genetic structure
of marine species is determined by the complex interaction of several factors including adult
mating and pre-spawning behaviour, larval development time and behaviour, oceanography
and its seasonal and annual variation, and must be empirically examined to inform
management.
The edible crab Cancer pagurus is distributed in the eastern Atlantic Ocean from the northern
part of Norway to north-western part of Africa (Christiansen 1969). The total landings in 2004
were 46 280 tonnes and mainly originate from around the British Isles including UK, Ireland
and France. Though, northern areas like Norway have had an increase in landings lately (FAO
2004). Tagging studies from the English Channel (Bennett&Brown 1983), Bay of Biscay
(Latrouite&Le Foll 1989), North Sea Coast of United Kingdom (Edwards 1979), and
Skagerrak and Kattegat (Ungfors et al. 2007) reveal that female edible crabs have the ability
to move long distances over 100´s of kilometres. Laboratory rearing of larvae shows
developmental times of at least 50-80 days in 15-20°C (total days in zoea stage I-IV, Nichols
et al. 1982), and field surveys indicates that the larvae are pelagic for 2-3 months as this is the
time between density peaks of zoea I and megalopae, respectively (Eaton et al. 2003). The
fecundity is high, ranging from 0.5 to 2.9 million of eggs female-1 in the mature size range of
a female, the larger female the more eggs (Edwards 1979; Ungfors 2007). The size at sexual
maturation has been studied in different areas (Edwards 1979; Brown&Bennett 1980; Tallack
2002; Ungfors 2007). In general, females start mating at relatively small sizes at carapace
width (CW) ~110 mm but their gonads are not maturing until after one more moult at ~130
mm CW. Contradictory, gonadal development and allometric growth of chela in males show
higher consistency between physiological and functional maturity, at 110-120 mm CW.
The aim of this study was to investigate the spatial genetic stock structure of the edible crab in
Kattegat and Skagerrak and to examine the temporal consistency of this structure; a sample
from the Norwegian Sea was included as an outgroup. This is the first study of genetic
population structure of edible crab in this area. The edible crab has a high potential for
dispersal during the pelagic larval stage and a mobile benthic life-style during its adult stage.
Genetic variation was analysed in 348 individuals captured at three different locations and
two occasions using eight microsatellite DNA loci. The outcome of the study is discussed in a
management perspective.
Materials and methods
Sampling of individuals was performed at three different geographic locations and during
different years in order to study the genetic variation on both a geographic and temporal scale.
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4
Seventy individuals were sampled on each occasion (table 1). The sampling of crabs in
Kattegat was performed in August 2001 and June 2007 at an offshore bank, Groves bank
(N57°06, E11°31). Samples from Skagerrak were obtained in September 2002 and September
2006 at Lunneviken, a coastal location close to the Swedish-Norwegian border (N59°03,
E11°10) (table 1, figure 1). A third location, a coastal location in the Norwegian Sea of mid
Norway called Midsund (N62°40, E06°40), was sampled in December 2004. This third
location was used as an outgroup.
Genomic DNA was isolated from the claw or the periopod muscle cells using the VIOGENE
DNA EXTRACTION KIT (protocol Blood and Tissue Genomic Mini). Eight microsatellite
DNA loci (table 2) were amplified with PCR (Eppendorf Mastercycler Gradient) using
primers described in McKeown and Shaw (2008) with modified primer annealing
temperatures (TA) (Cpag-5D8 TA = 54ºC, Cpag-6C4 TA = 55ºC, Cpag-3A2 TA = 55/52ºC,
Cpag-3D7 TA = 54C, Cpag-1B9 TA = 51ºC, Cpag-2A5-2 TA = 58ºC, Cpag-4 TA = 55°C and
Cpag-15 TA = 55°C; 30-33 cycles of 1 min 95ºC, 1 min TA and 1 min 72ºC except for Cpag3A2 where 10 cycles of 55ºC and 25 cycles of 52ºC was used). Individual locus PCRs
incorporated a forward primer labelled with a CY5 tag permitting visualisation on an ALF II
express automatic sequencer (Amersham Pharmacia Biotech). Identification of alleles was
performed by the use of software ALFwin Fragment Analyser 1.02. To ensure accurate sizing
of alleles a suite of size markers specific to each locus (two sizemarkers (ALF expressTM
SizerTM 50-500, Amersham Bioscience) external to the allele spread and two size markers
within the allele size range (van Oppen et al. 1997)) were run simultaneously (within the
same lane) at each amplification. Two control individuals were run across all gels to ensure
consistency among runs. Six of the loci (Cpag-5D8 to Cpag-2A5-2) were analysed at TMBL
but loci Capg-4 and Cpag-15 genotyped at the School of Biological Sciences, Royal
Holloway University of London following similar protocols.
Overall amplification success was 97.7 %. The allele sizes were checked for typing errors
with Microsatellite toolkit (Excel add-in, Park 2001) and for potential null alleles using
Micro-checker (Van Oosterhout et al. 2004). Genepop on the Web (Raymond&Rousset 1995)
was used to calculate for each locus/sample combination the expected heterozygosity (He, Nei
1987) and FIS, and to test for deviations from Hardy-Weinberg equilibrium (HWE).
Population structure was quantified using FST (Weir&Cockerham 1984) calculated in
GENEPOP. The null hypotheses of FST=0 was tested using both allelic (genic) and genotypic
data in GENEPOP. Significance levels were adjusted for multiple tests using Bonferroni
correction (Rice 1989). Analyses of molecular variance (AMOVA) (ARLEQUIN, Excoffier
et al. 2005) was used to analyse the genetic differentiation due to temporal and spatial
groupings: the two samples in Kattegat (GR01, GR07) and the two samples in Skagerrak
(LU01, LU06) were grouped either by location (Kattegat vs. Skagerrak) or by time (20012002 vs. 2006-2007).
The statistical power of the markers and sample sizes employed in this study to detect a userinferred level of population structure (FST) was assessed using the simulation approach in
POW-SIM (Ryman&Palm 2006). Five populations with effective population size Ne is
allowed to drift for t generations. The expected genetic differentiation FST is calculated by the
Nei (1987) formula FST=1-(1-1/2Ne)t, and we simulated a range of FST values. We used Ne of
1000 and 10000 based on earlier estimates of Ne in marine species being three to four
magnitudes smaller (Turner et al. 2002; Turner et al. 2006) than census size (Ungfors et al. in
5
5
prep). After t generations a subsample of 70 individuals was taken from each of the five
samples, whereafter a FST was calculated. This was repeated for 1000 or 10000 runs. The
proportion of statistically significant overall FST outcomes (p<0.05) estimates the power.
Results
Micro-checker indicated possible null allele frequencies in the sample from Grove Bank 2001
at locus Cpag-4, and in the sample from Lunneviken 2006 at loci Cpag-5D8 and Cpag-3A2, at
7, 5 and 7-11 % respectively. Allele and genotype frequencies for those loci were adjusted,
and original as well as adjusted genotypes were used for calculations of FST for population
comparisons. Locus Cpag-4 showed indications of null alleles of low frequency 2.5-5 % in
the samples from Lunneviken 2006 and Norway but frequencies were not adjusted.
Out of the 40 comparisons of locus-specific FIS-value, six indicated significant deviation from
HWE, and of these two remained significant after Bonferroni correction for multiple
comparisons, p=0.05/40=0.00125 (table 3, ***).
The overall genetic differentiation among the samples, global FST = 0.0019. Using genotypic
data this estimate was not different from zero (p=0.27), whereas an analysis based on allele
frequencies (genic data) indicated an overall structure (p=0.03). This pattern was consistent
for all eight individual microsatellite DNA loci, with individual locus FST values ranging
between -0.0049 and 0.0088 (table 4). The pair-wise population comparisons revealed no
difference in allele frequencies between the five samples; pair-wise FST’s ranged from -0.0008
and 0.0038 (table 5, figure 2). Analyses based on genotype frequencies adjusted for null
alleles were similar for overall FST (FST 0.0020, p=0.25), locus-specific population
comparisons (FST ranged between -0.0048 and 0.0088, p>0.05) and pair-wise comparisons
(FST ranged between -0.0008-0.0040, p>0.05).
The results from the AMOVA indicated neither spatial (Kattegat vs. Skagerrak) (table 6a) nor
temporal structure (years 2001-2002 vs. years 2006-2007) (table 6b). However, the AMOVA
indicated some difference between samples within the different groupings, in accordance with
the genic analysis above (tables 5a,b).
The statistical power, the probability of rejecting the null hypothesis (H0) when it is false,
with our sampling design, is > 93 % for a FST of 0.002 (table 7). An expected FST of zero
estimates to 0.04-0.05, indicating expected levels of type I error.
Discussion
The spatial and temporal genetic differentiation of edible crab is low within 1300 kilometres
of waterway distance in the investigated area. This conclusion is supported by i) low global
multilocus FST of 0.002 and non-significant single locus FSTs using allele frequencies, ii) nonsignificant global FST, single locus FST and pair-wise comparisons using genotype
frequencyies, (iii) no genetic differentiation among groups in AMOVA and (iv) that statistical
power analysis suggested > 93 % power for our sampling design to detect an overall genetic
6
6
differentiation of FST 0.002. Altogether, these results suggest that the genetic variation over a
1300 km water distance, from the basin of Kattegat at 57°N to the Norwegian Sea 62°N is
very weak. The reason for this weak structure is discussed below.
Firstly, the lack of spatial genetic differentiation can be explained by a high gene flow over
large areas. Female edible crabs are capable to move 100´s of kilometres and the pelagic
larvae can disperse over long distances. A hypothesis explaining the pattern and cause of
migration of females states that migration is directed towards the prevailing surface current to
compensate for larval dispersal (Bennett&Brown 1983). This migration pattern opposite to
current direction is valid for some areas, but not for all. Mark-recapture experiments in
Kattegat and Skagerrak (Ungfors et al. 2007) demonstrated a large fraction of long southerly
directed migrations of females from some coastal locations, thus against the coastal northward
surface current, but also long migrations both northward and southward from other locations.
There is a lack of knowledge concerning return movement or natal homing behaviour for the
edible crab, which is described for other species in connection with spawning
(Vannini&Cannicci 1995; Thorrold et al. 2001; Hauser et al. 2006). But there are some
observations indicating return movements the edible crab (Robinson et al. 2003; Ungfors et
al. 2007), which could explain the northward migrations according to the hypothesis. If the
above hypothesis is true, this could result in local genetic populations as the larval dispersal is
compensating for the adult migration. Though, the results in this study indicate that adult
migratory behaviour vs. oceanographic currents does not genetically structure the population
in this area, undermining the above compensating hypothesis. Adult and larval drift seem to
cause high gene flow, diminishing genetic variation over a large area.
Secondly, the low genetic differentiation among the individuals within the studied geographic
area may reflect historical gene flow persisting among recently founded large populations.
The Pleistocene ice ages (1.8 Mya-10 kyr years ago) and particular the last glacial maximum
(LGM) 21 kyr years ago have shown to impact the spatial pattern of genetic differentiation of
invertebrate species (Macoma balthica Atlantic assemblages, Luttikhuizen et al. 2003) and
marine algae (Fucus serratus, Coyer et al. 2003). Northern Europe has repeatedly been
covered by ice to a varyingly degree during Pleistocene: the British and the Scandinavian ice
sheets, respectively, covered land and extended out to the shelf edge (~200-400 m) during
glacial periods from at least 0.5 Mya to LGM. The ice sheets were possible confluent 28-22
14
C ka BP (LGM) and ice covered central and northern North Sea regions which otherwise
seem to be ice free (Sejrup et al. 2005). The south-western ice limit of the British ice sheet is
not fully agreed upon, but the Celtic Sea was partially covered. The modern marine
circulation system in Skagerrak was essentially established at about 8 kyr ago when the
eastern North Sea coastlines had attained present appearance (Gyllencreutz et al. 2006). The
edible crab distributed in Kattegat, Skagerrak and mid Norway at present could, rather than
from these areas formerly covered by ice, have been re-colonised from area(s) south of British
ice sheet e.g. English channel – Bay of Biscay or possible from a refuge in the North Sea. In
this case, the time that has past is likely un-sufficient for genetic differentiation based on
genetic drift. This especially counts for a large population which edible crab has had the
potential to be (high density, high fecundity), as opposed to a small population where
bottlenecks and stochasticity can change the allele frequencies over time to a larger extent. As
for the edible crab, lack of migration-drift equilibrium due to recent re-colonisation is also
hypothesized to explain the the low genetic differentiation and and absence of geographical
pattern of genetic variation in the the European lobster (Triantafyllidis et al. 2005) and the
genetic structure of Norway lobster (Stamatis et al. 2004). Areas of possible survival for cod,
7
7
Gadus morhua, populations during LGM have been analysed by environmental modelling.
This revealed potential suitable habitats off Atlantic Europe down to at least northern Spain
and off eastern North America and Iceland, but only scattered potential habitats around
Greenland (Bigg et al. 2007). This is consistent with analysis of genetic data for this species,
indicating a long time of population divergence between Europe-Iceland-North America but
shorter for Greenland populations in relation to Iceland-Europe (Bigg et al. 2007 and
references there in).
A third alternative that may explain the lack of significant genetic differentiation is Type II
error: that we have missed the genetic signal for a genetic differentiation due to too few
sampled individuals, too few loci or not so variable loci. The sample size of 70 individuals
and the use of 8 microsatellite loci is fully comparable with other recent population genetic
studies (Jorstad et al. 2004; Laikre et al. 2005a). The allele numbers per locus are variable to
hypervariable, varying from 4 to 34 alleles (table 2). Also, the frequencies of alleles within a
locus was a mixture of relatively uniform to skewed frequencies (figure 2). Differences in
power to detect genetic differentiation, particular at low FST values, have been shown between
statistical methods, number of samples and populations, and allele frequency distribution
(Ryman et al. 2006). The power analysis performed in this study showed that the analysis had
a high power, > 90%, to detect differences between stocks at FST 0.002 (global value in this
study), using the same number of loci and sample size, and the allele frequencies as in this
study. This strengthens our findings of lack of significant genetic differentiation among the
sampled groups.
An assumption of the statistical FST analysis is random sampling so that every individual in
the population should have an equal chance of being sampled. However, sampling biological
populations is as Waples (1998) underlines typically constrained in time and space. In our
study we sampled location Grove Bank and Lunneviken twice with 4-6 years in between (1
generation) to be able to exclude that some e.g. seasonal biological behaviour impacted the
outcome. No genetic differentiation was seen between temporal or spatial groups, or in pairwise FST analyses. However, as the AMOVAs among samples within locations/occasions
indicate, there was some differentiation between the samples. This can possibly be explained
by temporal instability signalling sweepstakes (Hedgecock 1994) i.e. a temporal change in
genetic composition because of small effective population size and random genetic drift. The
edible crab is highly fecund and randomly a few of the females may succeed in reproduction
whereas other not which cause temporal instability in population allele frequencies.
In general, marine genetic population studies show a relatively low level of genetic
differentiation. Studies of decapod species with similar biology as edible crab show upon the
complex situation where biology, but also marker, geographical scale, environment and
historical events play a role for the conclusions on stock structure. A genetic population study
of the hairy edible crab C. setosus, distributed along the 2500 km Chilean coast, found nonsignificant differentiation by the use of AFLP analysis (Gomez-Uchida et al. 2003). This
could possibly be caused by the lack of barriers and effective mixing by northward Peru
currents and southward Peru-Chile counter-currents. However, a genetic differentiation (FST
0.026) was shown in the C. setosus based on allozymes. Though this result was not
considered reliable since only two allozyme loci were polymorphic and environmental
selection could impact the allele frequencies. Despite high genetic diversity within samples,
the northern shrimp Pandalus borealis in North-eastern Atlantic group into three main
8
8
clusters partly explained by the retention of larvae within coastal fjords (allozymes, Drengstig
et al. 2000; RAPD, Martinez et al. 2006). In a large-scale study the coastal shrimp Crangon
crangon groups into three geographical regions with some differentiation within a region
(Weetman et al. 2007). Also, a genetic study on a smaller scale within United Kingdom
revealed a distinct population of C. crangon from north-eastern UK (Beaumont&Croucher
2006). Clustering of H. gammarus throughout its distribution from Greece to Norway (FST =
0.078) have been shown, but this was explained by regional reduced diversity rather than
unique haplotypes (mtDNA) (Triantafyllidis et al. 2005). The genetic pattern of the blue crab
Callinectes sapidus on the eastern United States indicate a overall structure, FST (0.04), but
with no apparent geographic pattern except for a decrease in haplotype diversity with
increasing latitude indicating a historic period of sudden expansion (McMillen-Jackson&Bert
2004). Populations of swimming crab C. danae in southern Brazil differentiate between
estuaries only 250 km apart and the investigated populations cluster into two groups separated
with at least 550 km. The sampling strategy has a large impact on the study of stock structure,
as distinct populations may be extensively mixed during e.g. feeding migrations and thus not
identifiable as samples may comprise individuals from multiple populations (Ruzzante et al.
2006). Nesbo et al. (2000) reported elevate populations structure for the Atlantic mackerel
(Scomber scombrus) when sampling at spawning periods compared to at other times. In
conclusion, unique genetic structures exist for decapod species all around the world and the
cause (s) of the pattern differs.
On an evolutionary time frame of thousands or millions of years the investigated area in this
study can be looked upon as one genetically based stock unit. However, as only a few
effective migrants between sampled locations generation-1 are needed to overcome the effects
of genetic drift establishing homogenous allele frequencies (Wright 1931), this stock unit can
be questioned on an ecologically time frame of decades. Many studies of marine species have
shown significant genetic differences, which could lead the author to recommend the use of
multi-stock management. Waples (1998) high-light three other possible outcomes that can
occur if H0 (no differences) is rejected, in addition to a correct conclusion. The most important
possible outcome to emphasise is that given enough data, significant differences can be
expected to occur routinely when comparing geographic samples due to some departures from
panmixia. This difference between samples might not be biological meaningful (Hedrick
1999). Therefore the management recommendation of a commercial species after 1) nonsignificant FST, as in this study, of one single stock unit, or after 2) significant FST of fewseveral stock units, is not straightforward.
Management
In Sweden and internationally, suggestions are raised and research programs are financed for
investigations on the potential for local management e.g. the Swedish programme
SUCOZOMA Sustainable Coastal Zone Management. Laikre et al (2005b) discuss three types
of genetic population structures in relation to fishes in the Baltic Sea, namely distinct,
continuous and no differentiation. They conclude that local over harvest, or even extinction of
populations with no differentiation, may not have a serious effect on total genetic variation in
comparison with the two other genetic population structures, as long as the effective
population size is large enough to resist the effect of genetic drift. However, ecological
impacts could be serious. Therefore, local management of the edible crab can be considered
and implemented whereby stakeholders take a precautionary approach such as implementing
size restrictions and not fishing below a certain local biomass. However, local over harvest
9
9
does not severely impact the total genetic pool, as long as no extensive fishery exists on all
local management areas and as long as corridors for genetic connectivity between them
prevails. Kattegat and Skagerrak landings of edible crab are taken by Swedish, Danish and
Norwegian fishermen, and today different regulations are used within these areas; different
MLS are legislated along the Norwegian coast (Anon 2004b) but no MLS is in use in Swedish
(Anon 2004a) or Danish waters within these areas (Anon. 1998). If exploitation rate increases
in the basins, international negotiations on catch or effort limits can be necessary.
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14
14
TABLES
Table 1. Site and date of sampling, sex (no. of females:males) and size distribution (sex-specific
carapace width (CW); mean, standard deviation and interval) in the five samples of edible crab Cancer
pagurus.
Locality
Grove Bank
Grove Bank
Lunneviken
Lunneviken
West Norway
GR01
GR07
LU02
LU06
NO04
Major
sampling area
Sampling site
(mm.dd.ss)
Date of
Sampling
Sample size
Female:Male
CW (mm)
F
M
Kattegat
Kattegat
Skagerrak
N57.06.21 E11.30.73
th
Skagerrak
N59.03.50 E11.10.00
2001, 26 of
September
th
2007, 4 of July
2002, 27th of
August
70
66:4
70
52:18
70
51:19
2006,
SeptemberOctober
70
63:7
162±11, 138-186
154±17, 131-172
168±14, 131-193
172±12, 160-207
152±16,122-183
168±16,126-187
154±17,78-185
146±13,127-167
Northern
North Sea
N62.40.33
E06.39.77
2004, 4th of
December
69
34:35
152±11,131-180
154±18,122-197
Table 2. Number of alleles, frequencies of most common allele (average for 5 samples) and allele size
ranges (bp) per loci.
Locus
Cpag-5D8
Cpag-6C4
Cpag-3A2
Cpag-1B9
Cpag-3D7
Cpag-2A5-2
Cpag-4
Cpag-15
total
Number
of alleles
34
8
4
16
8
8
31
8
117
Freq. of
most
common
allele
0.20
0.38
0.52
0.66
0.45
0.54
0.76
0.12
0.45
Allele size
range
154-265
166-194
255-264
222-286
169-217
153-174
202-295
124-145
124-295
15
15
Table 3. Expected heterozygosity, He, and deviation and exact test from Hardy-Weinberg expectancy
(HWE), FIS, for single loci, in the five samples of edible crab. The number of private alleles per
sample are also given.
Locus
Sample
GR01
GR07
LU02
LU06
NO05
He
FIS
He
FIS
He
FIS
He
FIS
He
FIS
Cpag5D8
0.91
-0.02
0.91
-0.00
0.88
0.08
0.90
0.11
0.90
0.04
Cpag6C4
0.69
0.03
0.72
-0.03
0.73
0.02
0.70
-0.17
0.69 -0.00
Cpag3A2
0.57
-0.04
0.57
-0.11
0.58
-0.20
0.58
0.21
0.59 -0.04
Cpag1B9
0.48
-0.02
0.56
0.06
0.59
0.05
0.45
0.07
0.50 -0.03
Cpag3D7
0.64
-0.11
0.68
-0.10
0.66
0.03
0.69
0.15
0.65
0.10
Cpag2A5-2
0.52
0.12
0.49
-0.05
0.51
-0.04
0.53
-0.20
0.57
-0.19
0.03
0.94
-0.01
0.94
0.08*** 0.95
0.10
Cpag-4
0.95
0.14*** 0.94
Cpag-15
0.44
0.07
0.46
0.01
0.44
-0.01
0.35
0.06
0.33
-0.04
No. of private
3
2
1
3
6
alleles
Bold FIS values differ significantly from zero (p<0.05; no correction). Two of the six significant FIS remained
significant after the Bonferroni correction (p=0.05/40=0.00125) (***locus Cpag-4 in GR01 and LU06).
Table 4. Overall genetic differentiation among edible crab samples, FST, for single loci and all eight
loci combined. Statistical significance is calculated using both genotypic and genic data.
Locus
FST
P genotypic
P genic
Cpag-5D8
0.0021
0.220
0.061
Cpag-6C4
0.0023
0.151
0.117
Cpag-3A2
-0.0049
0.994
0.994
Cpag-1B9
0.0088
0.164
0.0498
Cpag-3D7
0.0057
0.459
0.347
Cpag-2A5-2
-0.0018
0.700
0.668
Cpag-4
0.0005
0.290
0.215
Cpag-15
0.0031
0.153
0.042
All loci
0.0019
0.272
0.0297*
Significance level P<0.05, and adjusted for Bonferroni correction =0.05/8=0.00625.
16
16
Table 5. Pair-wise FST. a) FST (below diagonal) and p-value (above diagonal, genotype
frequencies=genotypic test) for pair-wise comparison between the five samples for all eight loci.
b) FST (below diagonal) and p-value (above diagonal, allele frequencies=genic test) for pair-wise
comparison between the five samples for all eight loci.
Table 5a.
GR01
GR01
GR07
LU02
LU06
NO
0.0033
0.0019
0.0012
0.0010
GR07
0.43
-0.0008
0.0031
0.0026
LU02
0.64
0.76
0.0038
0.0035
LU06
0.08
0.36
0.13
0.0005
NO
0.49
0.13
0.31
0.82
-
LU02
0.38
0.57
0.0038
0.0035
LU06
0.063
0.13
0.016
0.0005
NO
0.25
0.051
0.16
0.50
-
No significant pair-wise comparisons.
Table 5b.
GR01
GR01
GR07
LU02
LU06
NO
0.0033
0.0019
0.0012
0.0010
GR07
0.28
-0.0008
0.0031
0.0026
Significant level after Bonferroni correction =0.05/10=0.005. No significant pair-wise comparisons after
adjusted significance level.
17
17
Table 6. AMOVA result. a. Grouping according to location i.e. Kattegat (GR01 and GR07) vs.
Skagerrak (LU02 and LU06). b. Grouping according to occasion i.e. in 2001-2002 (GR01 and LU02)
vs. 2006-2007 (GR07 and LU06). The Norwegian sample is not included in theses analyses.
Table 6a.
Source of variation
d.f.
Among locations
Among samples
within locations
Within populations
Total
Table 6b.
Source of variation
Among occasions
Among samples
within occasions
Within populations
Total
1
2
Sum of
squares
1.770
6.607
Variance
components
-0.0054
0.0084
Percentage of
variation
-0.26
0.40
556
559
1176.021
1184.398
2.115
2.118
99.86
100
0.051
d.f.
Variance
components
-0.0023
0.0064
Percentage of
variation
-0.11
0.30
p-value
1
2
Sum of
squares
2.359
6.018
556
559
1176.021
1184.398
2.1151
2.1192
99.81
100
18
p-value
1.000
0.024*
0.686
0.021*
0.068
18
Table 7. Analysis of statistical power of rejecting the null hypothesis H0 of no differentiation when
false. The simulations of different expected FST below, at and above the observed overall FST, from
effective population size and generations (FST=1-(1-1/2Ne)t (Nei 1987), and the resulting proportion of
significant Chi and Fisher tests after 1000 or 10000 runs, namely the power. The proportion of
significant test with no simulated genetic drift (t=0) estimates , indicating (expected) type I error.
Expected
FST
0.0010
0.0010
0.0020
0.0020
0.0020
0.0020
0.0050
0.0050
0.0000
0.0000
Average
FST
0.0010
0.0010
0.0020
0.0020
0.0020
0.0020
0.0050
0.0050
0.0000
0.0000
Chi-test
0.57
0.54
0.96
0.95
0.96
0.96
1.00
1.00
0.040
0.040
Fisher´s
test
0.54
0.52
0.94
0.93
0.94
0.94
1.00
1.00
0.050
0.048
Ne
Generations (t)
runs
1000
10000
1000
10000
1000
10000
1000
10000
1000
10000
2
20
4
40
4
40
10
100
0
0
1000
1000
1000
1000
10000
10000
1000
1000
1000
1000
FIGURES
Figure 1. Genetic population study of edible crab Cancer pagurus. The map show the geographical
distribution of the three sampling locations: Grove bank (GR) in Kattegat, Lunneviken (LU) in
Skagerrak and Midsund (NO) in the Northern North Sea. Grove bank and Lunneviken were sampled
twice in 2001 and 2007, and in 2002 and 2006, respectively.
19
19
Figure 2. Allele frequencies of all eight loci and five samples (GR01, GR07, LU02, LU06, and NO).
20
20
IV
Effective fishing area, crab density and stock abundance of the edible
crab (Cancer pagurus) in Swedish waters using mark-recapture
experiment and GIS modelling
1
Ungfors, A., 1Nilsson, P.G. and 2Sundström, H
1
Department of Marine Ecology-Tjärnö, University of Gothenburg, 452 96, Strömstad,
Sweden
2
Department of Systems Ecology, Stockholm University, Sweden
Correspondence author: +46 526 686 88, Anette.Ungfors@marecol.gu.se
Keywords: mark-recapture, bait attraction, effective fishing area, edible crab density, stock
abundance, suitable habitat
1
1
Abstract
Here we present an estimate of the total abundance of adult crabs (Cancer pagurus) on the
Swedish west coast, based on a combination of experimental fisheries to get catch per unit
effort data and effective fishing area, and GIS modelling of available habitat.
Fishery-related data, e.g. catch per unit effort (CPUE), is often used as a substitute for direct
density assessments for estimating trends in stock size. In order to translate CPUE data from
static gear (e.g. baited crab pots) to stock biomass or number, it is necessary to know the
catchability coefficient q also defined as effective fishing area, i.e. the area over which all
individuals of the target species are caught in one pot assuming that the pot is capturing 100%
of the crabs within this area.
In a mark-recapture experiment we estimated the effective fishing area around crab pots
targeting edible crabs (Cancer pagurus). Crabs were caught and marked at 5 locations in the
Kosterfjord, Swedish Skagerrak coast in September 2003. Crabs were then released at 5
distances (10-160 m) in four directions from a baited pot. The number of marked crabs
caught in the baited pot was then followed daily for 5 consecutive days. The current speed
and direction close to bottom during the experimental period was measured daily with a drift
buoy. In total, 1635 crabs were marked, and 45 crabs were recaptured (2.8%). The effective
fishing area q was estimated to 2293 ± 1137 m2 (mean ± 95% confidence interval),
corresponding to a circle with a radius of 26.6 ± 6.3 m.
In a separate experimental fishery in the Fjällbacka archipelago located approximately 35 km
south of the Kosterfjord during June and August 2003, we estimated catch per unit effort at
two depths strata (15-18 m and 25-30m) at 7 locations. CPUE did not differ significantly
between seasons or depths, but differed significantly among locations. Using the effective
fishing areas estimated around a string of seven pots, we calculated an average density of
0.0038 ± 0.0015 crabs/m2.
Using GIS data on depth and sediment characteristics of Skagerrak and Kattegatt we
calculated the area of suitable crab habitats along the Swedish West coast. We defined a
suitable crab habitat to be between 10 and 40 meters water depth, and with a bottom
consisting of bedrock, stone, gravel or sand. The area of suitable crab habitat was estimated
to 4142 km2, which combined with density estimates from Fjällbacka would indicate that the
catchable population of crabs on the Swedish west coast would be approximately 1.6x107 ±
6.3x106 crabs.
2
2
Introduction
Knowing the abundance or density of a commercial species of fish or crustaceans is important
for management, e.g. for estimating the potential of a fishery in the early stages of
development, for modelling the effect of different management regimes, and for evaluating
the efficiency of existing management. Direct visual observation on abundance in marine
habitat is often more effort demanding compared to observations of terrestrial species because
of the 3D and low transparency of the oceans. However, diver observations (Miller 1989;
Wolff&Soto 1992; Karlsson&Christiansen 1996), underwater filming using remotely
operated vehicles (ROV) (Stevens 2003; Busby et al. 2005) or cameras (UWTV)
(Hughes&Atkinson 1997; Tuck et al. 1997; Morello et al. 2007) on sledges are in use. Markrecapture methods are indirect alternative for stock estimation where the recapture of marked
individuals and e.g. the Jolly-Seber method have allowed for stock size estimation in an open
population of e.g. Cancer pagurus (Bell et al. 2003) and Carcinus maenas (Munch-Petersen
et al. 1982).
For many fisheries, data from the commercial fishery, commonly catch per unit effort
(CPUE), is the only means available to estimate density. However, CPUE data must be used
with caution, as many factors besides the abundance of the target species may influence
CPUE, e.g. soak-time, gear saturation, changes in gear efficiency, changes in fishing grounds,
the skills of the fishermen, and many other causes (Bennett&Brown 1979; Miller 1990;
Hilborn&Walters 1992; Miller&Addison 1995; Shelton 2001). If these factors are taken into
account, CPUE may be used as an index to assess if changes in the abundance of the targets
species occur. However, if CPUE is also to be used as an index of absolute abundance (e.g.
number of individuals per m2), then some kind of translation of CPUE data must be applied.
The general conversion factor is the catchability coefficient q such as
CPUE=qN
where N is the stock size, and q defined as the fraction of the stock captured by a unit of
fishing effort (Ricker 1975). The catchability coefficient has also been termed as the effective
fishing area (reviewed in Miller 1990). The effective area is the area from where the captured
crab came from assuming that 100 % of the individuals are captured, and should not be
confused with the wider attraction area (Himmelman 1988; McQuinn et al. 1988) i.e. the
maximum area from where individuals could be attracted.
The area of effective fishing or attraction can be estimated by several methods, e.g. by direct
behavioural studies (Sainte-Marie&Hargrave 1987; Skajaa et al. 1998), using traps in a string
investigating overlapping areas or not (Bell et al. 2001; Aedo&Arancibia 2003) or use of
independent estimation of abundance (diving) and CPUE (Miller 1989). An alternative
approach is to use mark-recapture methods (Bell et al. 2003). A way of using mark-recapture
to estimate effective fishing and attraction area, is to release marked animals at different
distances from a trap, and then recording the number of recaptured animals during a certain
time period, or using one release point and many traps at several distances around this point
(Acosta&Perry 2000).
In this study we estimate the catchability coefficient q for edible crab (Cancer pagurus) in
Skagerrak as the effective fishing area using the mark-recapture strategy (release at different
distances and directions from a central crab pot) and using a model previously used to
extimate insect densities using baited traps (Byers et al. 1989; Turchin&Odendaal 1996;
Östrand&Anderbrant 2003). A graph of the distance (r) from the trap on the x-axis and the
3
3
proportion of recaptured individuals (P(r)) on the y-axis can then be used to estimate the
maximum distance that an animal can reach the trap in the time interval, which is obtained by
the intercept with the x-axis. This measure is called the attraction range (rs), and it is
dependent on the time that the trap is employed. The effective fishing area q is the area
around the trap from which all animals originate if the trap catches all the animals within the
area and no animals outside this area. The effective fishing area q can be obtained from the
formula
where rs and P(r) is obtained from the graph described above. This is in a sense an artificial
concept, as no trap probably works this way, but it is a convenient way of calculating density
from the trap catch, by the formula
Density= Catch/q
where the catch can be taken e.g. from logbook or research survey CPUE data.
Estimation of effective fishing area
The experimental fishery was made during September 2003 on 5 locations in the Kosterfjord
on the Swedish Skagerrak coast (table 1). Crabs were initially caught on each location with
60 pots of the type used in the commercial crab fishery in Sweden. The crabs caught were
measured and marked with a numbered plastic band on each claw (figure 1). Two baited pots
(figure 1) were then placed on each location, and crabs from that location were released at 5
different distances from these two pots (10, 20, 40, 80 and 160 m) in the four cardinal
directions (north, west, south and east). On each location, the number of crabs released was
increased with distance from the central pots (figure 2). The total number of crabs released
differed slightly among localities and was dependent on the number of crabs caught during
the initial fishery (table 1). The central pots were first checked for crabs caught after 24 hours,
and then every 24 hours for 4 consecutive days. The number marked and unmarked crabs of
each sex were recorded.
The attraction range and effective fishing area were calculated as described by
(Östrand&Anderbrant 2003). In short, if the distance of release from the central collecting
pots is plotted on the x-axis against the proportion of crabs caught on the y-axis, the intercept
of a fitted line with the x-axis is a measure of the sampling range rs (the maximum distance
from where a crab can reach the pot during the fishing period) i.e. attraction range.
The effective fishing area q (the area from where the crabs are attracted if the pot was 100%
effective at catching crabs) is calculated from the probability function of recapture from
distances 0-rs from the central collecting pots.
4
4
Figure 1. Cable-ties were used as marks (left), central pot (mid) and drift buoy (right).
To test if the current direction would influence the area of attraction, the current close to the
seafloor was measured with a drift bouy (figure 1), first when the crabs were released and
later each time the pots were checked for marked crabs. The drift bouy was allowed to drift
for 30 minutes on each occasion, and the position at the start and end of the period was
recorded. The average speed and direction was then calculated in the GIS software ArcGIS
9.0 (Esri Inc.).
Figure 2. Experimental design. Marked
edible crabs were released at five different
distances from two central pots (black dots).
The number of released crabs increased
from the short distance to the maximum: 10
m 4-6 crabs, 20 m 5-15 crabs, 40 m 10-35
crabs, 80 m 10-35 and 160 m 15-63 crabs.
This was repeated on 5 locations.
Estimate of CPUE
CPUE was estimated in a trial fishery during 6 days in June (23d – 28th) and 5 days in August
(25th – 29th) 2003, in the Fjällbacka- Väderöarna area on the Swedish west coast (11°03 N
58°36 E; 11°10`N 58°36E: 11°05 N 58°33 E, 11°12 N 58°35 E) in a chartered 9 m (29.5 feet)
commercial crab fishing vessel. The experimental fishing was designed to resemble methods,
seasons and locations used by commercial fishermen. Fishing gear were common pots
(70x45x45 cm) with metal skeleton and nylon mesh, with 75 mm escape gaps. Seven traps, 15
m apart, were tied together with rope, forming so-called strings .14 strings were distributed at
seven locations: three locations in the inner part of archipelago (Småsvinningarna,
Kyrkogårdsön and Skottarna), three locations in the outer part (Knappen, Hamnerö and
Ärholmen), and one location on the ground Stora Ryggen in the fjord separating the inner and
outer archipelago. At each location two strings were used, one at shallow depth (15-18 m) and
one deeper (25-30 m), since these are depths commonly used by commercial fishermen during
these seasons. Traps were hauled and put back on the same place every day during the
5
5
experiment, except the first day in each session when traps only were set. Weather conditions
also forced us to cancel the fishery during one day in each fishing session: 24th June and 27th
August. Thus we got both 24 and 48 hours soak-times. The catch in 48 hours soak-times were
converted to 24 h by the conversion factor 1.1, estimated from a data set (Hallbäck, H
unpublished). Data was taken on sex, size (carapace width (mm)), shell condition (indicating
time since moulting, on a scale from one to five, where one is newly moulted and five is long
time since moulting), lost claws, location, depth, position of trap in string, soak time and
recaptures. All crabs were returned to water at the site of capture.
Extrapolating density estimates to the Swedish west coast.
We estimated the available crab habitat by a modelling approach in the GIS software ArcGIS
9.0 (Esri Inc.). Data on depth and sediment characteristics with a spatial resolution of 600 m-7
km (depending on the actual area) for the entire Kattegat and the eastern part of the Skagerrak
was obtained from the BALANCE project (BALANCE 2007). From this, areas with suitable
depths (10-40 m and sediment characteristics bedrock and other hard substrates, gravel and
sand) were plotted, and their area was calculated. The area included in the analysis was based
on sites reported in logbooks from crab fishermen during the years 2004-2007 (data obtained
from the Swedish National Board of Fisheries). The area of suitable crab habitats was
calculated in the GIS, and this was then combined with the estimates of effective fishing area
per pot and CPUE (described above) to form an estimate of the available abundance of crabs.
Results
Effective fishing area
In total, 1635 crabs were marked on the five locations, and 45 crabs were recaptured (2.8%).
The number of marked and recaptured crabs on each location is given in table 1.
Table 1: Number of crabs measured and recaptured on the 5 locations.
Location
Position
Arsklåvet
58°50,090;
11°07,42
58°51,054;
11°07,293
58°50,30;
N Rossöflaket
Kalvörännan
11°01 40
N Grötholmen 58°53,609;
11°06,057
58°50,500;
Ramsöflaket
11°04,30
Crabs
marked
296
Crabs
recaptured
7
197
5
350
9
557
18
234
6
The proportion of recaptures decreased with distance for all 5 locations (an example from one
locality is given in figure 3), although the pattern is less clear on some localities beacause of
the low number of recaptures.
6
6
Figure 3. The proportion of recaptured edible crab from increasing distance from the central
pots. Data from location N Grötholmen.
We could not find that the current pattern significantly affected the attraction of pots. The
proportion of recaptured crabs did not differ significantly among the four directions for any of
the locations (2 goodness of fit-test against a null hypothesis of equal number recaptures in
all directions ), except for Ramsöflaket where more than expected recaptures came from the
east. However, as the prominent current direction was toward the south or towards the north,
the relatively high capture rate on crabs released east of the pots in not easily explained by the
currents.
The attraction range rs varied between 159 and 343 meters for the five locations (table 2).
Table 2. Attraction range rs, effective fishing area, and radius of effective fishing area, and
estimated density on the 5 locations. Mean± 95% confidence interval, n=5.
Location
Arsklåvet
Sampling
range rs (m)
214
Effective fishing area q
(m2)
2077
Radius of q
(m)
26
N Rossöflaket
159
1426
21
Kalvörännan
343
3828
35
N Grötholmen
171
1846
24
Ramsöflaket
250
2290
27
2293 ± 1137
26 ± 6.5
Average estimate 227 ± 92
7
7
Despite the variation among locations in estimates shown in table 2, the regression lines of
proportion recaptured vs. distance were not significantly different among locations (Analysis
of Covariance, Interaction F4,94=1.23, P=0.305, Location F4,89=0.77, P=0.548). Therefore, we
may average the results from all 5 locations to get an overall estimate of the attraction range
of 227± 92.
The effective sampling area varied between 1426 and 3828 m2, corresponding to radii of
between 21 and 35 m. The average estimate of radius of attraction was 26 ± 6.5 m.
Catch per unit effort
The catch per unit effort varied between 2 and 119 crabs caught per string and 24 hours. The
catches at different depths or seasons did not differ significantly (factorial ANOVA), but there
were significant differences both among Fishing days and Locations (p=0.0001 and p=0.0006
respectively), and in the interaction among them (Season*Location p=0.0009;
Location*Fishing day p=0.03; Depth*Fishing day*Locations p=0.001). The other interactions
were not significant, and are hence less important in explaining the variations in catches.
Fishing success does hence depend on location and day, but also on season. There are better
catches at shallow water in June than in August and conversely higher catches at deep than
shallow water in August. Catches are also significantly higher (p=0.0047) at the inner
locations (Småsvinningarna, Skottarna and Kyrkogårdsön) in June than in August.
Additionally there are daily differences on each location on what depth gives highest catches
(Table 3).
Table 3. CPUE per string averaged over all fishing occasions at different locations, seasons
and depths (mean ± 95% confidence interval, n= 4 for June, n= 5 for August).
Hamnerö
Kyrkog/
Lyngö
Skottarna
Småsvinn St.
.
Ryggen
St. & L.
Knappen
Ärholme
n
9.5±9.4
54.0±15.5
53.5±20.9
30.5±15.5
41.7±15.5
24.0±11.8
14.9± 9.1
16.7±7.2
46.1±24.7
46.9±15.5
8.6± 7.1
53.6±35.5
22.3±12.4
17.7± 7.5
12.4±9.5
7.8±3.3
12.2±9.5
26.7± 4.6
21.4±19.6
16.4±17.3
8.6± 4.9
23.1±4.5
22.9±16.7
28.9 ±17.0
13.1± 7.7
27.6±15.4
40.5±25.5
20.4±15.3
June
15-18 m
25-30 m
August
15-18 m
25-30 m
The overall average of all fishing days, depths and occasions and taking the 7 localities as
replicates is then 26.6 ± 9.4 (mean ± 95% confidence interval) crabs caught per string and 24
hours. As each string consisted of 7 pots, with partly overlapping effective fishing areas, we
calculate a combined effective fishing area for a string to 7022 ± 1366 m2 (using the average
8
8
effective fishing radius of 26 ± 6.3 m from table 2 above). The average density of crabs at the
7 locations is then CPUE/effective fishing area = 26.6/7022 =0.0038 ± 0.0015 crabs/m2.
Extrapolating density estimates to the Swedish west coast.
The area of suitable crab habitat (as defined by hard and sandy substrates between 10 and 40
meters) along the Swedish west coast is calculated to 4142 km2 (figure 4). Using the density
value of 0.0038 ± 0.0015 crabs/m2 obtained from the experimental fishery in Fjällbacka, we
get an overall density estimate of crabs in the parts of the Skagerrak-Kattegat area visited by
Swedish fishermen of 1.6x107 ± 6.3x106 crabs.
Figure 4. Suitable crab habitat (greyish) defined as 10-40 m depth with sediment
characteristics bedrock, gravel and sand. The landing positions in 2004-2007 of crab gears are
shown.
Discussion
Miller (1990) reviewed findings on effective fishing area and concluded that catchability
coefficients on shallow bottoms have been in tens and hundreds of square metres whereas
values from deep flat habitats have been in thousands of square metres. Our finding on
effective fishing area do more closely resemble those of deep-water species such as the snow
crab Chionoecetes opilio with a q of 2470-5290 m2 (Miller 1975), and the red crab Geryon
maritae with q of 2160 m2 (Melville-Smith 1986). However, Bell et. al. (2003) estimated the
effective area fished per trap of Cancer pagurus to 5851-10301 m2 (95% confidence
interval) comparable or even larger than our estimate 1426-3828 m2. Earlier finding for the
shallow-living species C. irroratus is 276 m2 (80 mm CW, average q for kelp and barren
habitat), whereas q was smaller for smaller individuals (Miller 1989). Aedo and Arancibia
(2003) estimated q to 577 m2 for the Chilean lemon crab C. porteri. Miller (1989) also
estimated the catchability coefficient for American lobster Homarus americanus to 373 m2
(70-89 mm CL), where q also was smaller for smaller individuals. The q estimates for edible
9
9
crab in our study is for crabs larger > 75 mm CW similar to the size range in Bell et.al. (2003,
> 70 mm CW).
Bell et. al. (2003) found a density of 0.0021 crab m-2 for edible crab on the East coast of UK,
comparable to our density estimation of 0.0038±0.0015 crab m-2. The density of deep-water
stone crab Paralomis formosa (Lithodidae) was in average 0.008 individuals m-2 using
photographs and prediction on effective area of bait odour plume (Collins et al. 2002). Cancer
polydon in the Northern Chile is more dense, 0.15 individuals m-2 estimated from night dives
(Wolff&Soto 1992).
Previous experiments in Norway by Skajaa et. al. (1998) based on behavioural data collected
by telemetric tracking of crabs estimated an attraction distance of 28 m, significantly lower
than the pooled value of 198 m (rs) we found in our mark-recapture experiment. Our
estimation of attraction area is dependent of time, so time difference (we used five days for
estimation and Skajaa (1998) used one night and instant attraction) may have cause the
difference. However, our effective fishing radius is close to Skajaa (1998) attraction distance.
We used two pots for attraction to avoid gear saturation effects (Miller 1990) e.g. to avoid that
attracted crabs did not enter because of inter-specific avoidance of aggressive large males.
This might have impacted the effective fishing area most probably overestimated the area
resulting in an underestimation of the density.
Our estimate of q is based on a recapture rate of 2.8 % as 45 of the 1635 marked crabs were
recaptured. This low recaptured rate could have had an impact on the results.
Many biological characters of the edible crab may impact the catchablity in fishing gear e.g.
feeding intention, moulting, spawning, hatching and migration (Bennett 1995). As these
characters are time-dependent the time of the season is an important driver for catchability.
We estimated the catchability coefficient in September i.e. during the main fishing period.
Three components contribute to the overall uncertainty in the estimate of total stock size:
effective fishing area (q), CPUE (from the experimental fishery in Fjällbacka), and the GIS
analysis of habitat area. To reduce the combined uncertainty and thus improve the estimate of
total abundance, trial fisheries should ideally be repeated in other areas along the coast, to
assess the geographical variation. A more detailed analysis of fishermens logbooks may help,
but the current varying level of detail in the logbooks makes this complicated. The uncertainty
of the GIS estimate of habitats is more complex: this is dependent on a number of different
datasets, each with its own uncertainty. However, as detailed mapping of marine habitats
progresses, these types of data sets will become more reliable. A last important part is of
course to make investigations of the actual habitats preferences of crabs. More directed
investigations using fishery-independent data (e.g. divers, video or ROV) of the habitat
preferences of different size-categories of crabs will be necessary to make estimates of total
abundance more reliable.
Acknowledgements
We are grateful towards the fishermen Lars-Åke Olsson, Långasjö and Morgan Axelsson,
Strömstad for all collaboration during the experimental fishings. Many thanks to Christin
Appelqvist for assistance during the fishing experiments, markings and for being an
exemplary skipper on Doris. And to Hans Hallbäck for the crab capture data used for soaktime conversion.
10
10
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V
Stock indicators of the edible crab (Cancer pagurus) in the Kattegat
and Skagerrak estimated by length cohort analysis and
resampling of growth parameters
1
Ungfors, A*. and 2Ulmestrand, M
1
Department of Marine Ecology - Tjärnö, University of Gothenburg, 452 96 Strömstad,
Sweden +46 526 686 88, Anette.Ungfors@marecol.gu.se
2
Institute of Marine Research, National Board of Fisheries, 453 21 Lysekil, Sweden
Corresponding author: Anette Ungfors, Anette.Ungfors@marecol.gu.se, +46 526 686 88
1
1
Abstract
In this study we estimate the von Bertalanffy growth parameter L using length frequency in
catches (Power-Wetherall approach) and the K by the use of growth data from a markrecapture experiment (a forced Gulland-Holt plot, Munro, Fabens, Appledoorn in FISTAT II,
and a Ford-Walford plot) for females and males in Skagerrak and Kattegat, respectively. The
stock indicators fishing mortality, current stock biomass and abundance are calculated for the
female and male stock in Skagerrak and Kattegat by Monte Carlo resampling of growth
parameters and weight-at-length and length cohort analysis (LCA) (Matlab 7.5). In addition,
the egg production is estimated, based on knowledge of fecundity (resampling procedure
within regression distribution), female stock abundance and an estimate of the spawning
proportion. The fishing mortality was higher for females than for males, and the fishery in
Kattegat exploits larger individuals whereas the fishery in Skagerrak seem to have a wider
exploitation pattern. The mean fishing mortality Fall and the Fp is around 0.3 for females and
0.2 for males. Overall, the fishing mortality seems to be low. Based on total commercial and
estimated recreational landing of 401 tonnes in Kattegat and Skagerrak, the estimates on the
current stock was ranging between 1600-2600 tonnes or 4-8 million of edible crabs, and the
egg production was around 5-7x10^11. These ranges of stock indicators consider different
values on growth parameters and natural mortality (M). A lower M generated a lower stock
abundance and egg production whereas a higher M generated higher stock indicators. Natural
mortality had also an impact on the estimated fishing mortality. We discuss the advantages
and disadvantages of the used stock assessment approach.
Keywords: von Bertalanffy growth parameters, Monte Carlo resampling, length cohort
analysis, fishing mortality, stock biomass, egg production
2
2
Introduction
Sustainable resource exploitation needs information indicating the stock´s ability to withstand
fishing and natural mortality to grow and recruit fulfillingly in the long term. An important
indicator is the fishing mortality coefficient (F), which is an estimate on the proportion of the
stock dying due to the fishery. Other indicators are e.g. stock abundance, spawning biomass,
juvenile biomass and egg production, which are estimates of stock status or recruitment
potential. For these indicators target and limit reference points, are empirically and
scientifically established for valuable exploited stocks. To avoid growth overfishing i.e.
fishing too small juvenile individuals the fishing mortality FMSY where the yield of the stock
is maximised (MSY), is a target to be obtained, or rather a limit not to exceed. Avoidance of
recruitment overfishing i.e. fishing to hard on mature individuals who give rise to next
generation is harder to avoid as the relationship of the spawning stock and consequential
recruitment is complex.
Direct visual observation on abundance in marine habitat is often more effort demanding
compared to observations of terrestrial species because of the 3D and low transparency of the
oceans. The recent development and availability of new techniques such as echo-sounder,
cameras on trawls and remotely operated vehicles (ROV), make visual methods possible
below the water surface. However, estimation of the abundance of marine species is often
based on calculations (assessment) of the population, restricted to underlying assumptions of
recruitment, natural mortality, immigration and emigration. Today there exist several models
for crustacean stock assessment all with their pros and cons (Smith&Addison 2003), and the
usefulness is dependent on the existing data and the fishing history. A fishing history of a
large decrease in abundance are informative for stock assessment, and the quotation of John
G. Pope ’the more fish you catch, the better you know how many there were‘ summaries the
findings of informative data for abundance and reference points in a recent paper of
Magnusson and Hilborn (2007). Contrast in harvest rate seemed to be of secondary
importance. Schnute et al. (2007) enlighten the problem with many models and different
computer languages resulting in difficulties not only to compare stock status but as it involves
a decreased availability to management. General production models (logistic growth of
biomass) using time-series of abundance indices of the stock and total effort or total landing,
have now evolved into more dynamic age or size-structured models. For example the
assessment models of Blue crabs Callinectes sapidus (Kahn&Helser 2005; Miller et al. 2005)
use catch-surveys for recruits and adults to add recruitment information and stochastic growth
i.e. using probabilities for growth into another length class have also been considered
(Siddeek et al. 2004; Bunnell&Miller 2005). In these models it is possible to solve different
involved parameters as recruitment, natural, handling and fishing mortality, and risk
assessment have been included (Zheng et al. 1995; Punt&Kennedy 1997; Zheng et al. 1997).
Models as delay-difference, depletion and virtual population models are shown to be special
cases of a generalized age-structured model (references within Magnusson&Hilborn 2007).
Virtual population analysis (VPA) is the procedure for determining the amount of individuals
there must have been in the sea to account for the known catch and the natural losses as
mortality. Age-based population analysis (APA) (Pope 1972) is an approximation to, and
computationally simpler than VPA. The main difference between VPA and age cohort
analysis is that the exponential decline in numbers within any age class in VPA, is changed to
a step-wise decline in cohort analysis meaning that the catch is caught half-ways through the
age interval. Natural losses decline exponentially in VPA and APA. For species with
3
3
difficulties in age determination caused by homogenous climate with no annular striation in
otoliths or scales such as in tropic fishes, or by the lack of calcified structures and repeated
moults such as in crustaceans, length cohort analysis (LCA) (Jones 1984) have been used
(Addison&Bennett 1992; Wolff&Soto 1992; Kirchner 2001; Ulmestrand&Eggert 2001).
However, over the last decade aging technique using lipofuscin age-pigment accumulation
rate in the brain or eye-stalks has been established. Ageing have been performed for several
marine and fresh waters decapods including the edible crab Cancer pagurus (Sheehy&Prior
2005) but also e.g. Callinectes sapidus (Ju et al. 2001), Homarus gammarus
(O'Donovan&Tully 1996; Sheehy&Bannister 2002), Homarus americanus (Wahle et al.
1996), Nephrops norvegicus (Tully 1993), Pacifastacus leniusculus (Belchier et al. 1998;
Fonseca&Sheehy 2007), Panulirus argus (Maxwell et al. 2007) and Cherax quadricarinatus
(Sheehy 1992). Also, aging initiatives using estimations on the inter-moult period by isotopes
228Th/228Ra in the pre-moulted carapace (Latrouite et al. 1991; Verdoit et al. 1999) have been
tried.
In this study we assess the edible crab Cancer pagurus stock in Skagerrak and Kattegat with
length cohort analysis, using von Bertalanffy growth parameters L and K estimated from
length frequency data and mark-recapture experiment. The impact on estimates of i) fishing
mortality measured as the average fishing mortality Fall, mean fishing mortality over the interquartile F110-160, fishing mortality of the three most exploited cohorts F3max, coefficient of
variance, Fp and Fc (fishing mortality standardised for population and catch numbers,
respectively see equation 11), ii) current stock biomass and abundances, and iii) the
recruitment potential measured as egg production of the spawning stock, are estimated using
Monte Carlo resamplings of L using different mean and standard deviation. Resampling is
also allowed in the weight-at-carapace width relationship for biomass calculations from stock
numbers, and in the fecundity-at-carapace width for egg production calculations. The analyses
are performed in Matlab 7.5 (MathWork Inc.). In addition, of the commonly used value of
natural mortality of 0.2 the LCA is run for M 0.1 and 0.3. No calculation on long term
changes on biomass or yield-per recruit based on simulated effort changes is presented.
In length-cohort analyses the parameters of growth rate is important as von Bertalanffy
growth curve (VBGC, relation of size to age) is used for estimation of the time (t) to grow
between length cohorts (Jones 1990). The reliability of length cohort analysis is discussed and
drawbacks of the model have been stated (Rosenberg&Beddington 1988; Hilborn&Walters
1992; Sheehy&Prior 2005). Efforts on minimizing the model limitations i.e. the discrepancy
between size and age have been made by excluding the largest pseudo cohorts with too large
variation in size-at-age, and by sensitivity analyses of growth parameters and natural
mortality (Jones 1979; Addison&Bennett 1992). Still, LCA is used for relative comparison of
yield per effort with different growth parameters (Ulmestrand&Eggert 2001) or used for its
simplicity and shortage of alternatives (Wolff&Soto 1992; Kirchner 2001).
4
4
Parameter estimation and input data
Growth rate is assumed to follow the von Bertalanffy growth curve i.e. a linear decline in
growth rate with age,
Lt= L(1-e-K(t-t0))
(equation 1)
where Lt is the length at age t, L the asymptote length where growth rate theoretically is zero
and is the mean length an individual would reach if it grew for an infinite number of years, K
(yr-1) is the Brody growth coefficient, indicating the rate of growth towards asymptote and t0
is the time at zero length.
Pauly (1984) presented a modified formula of Wetherall (1986) method based on Powell
(1979) and Beverton and Holt (1956), to estimate L and Z/K from length-converted catch
frequency. Wetherall estimated Z in a steady state population with constant exponential
mortality from a mean length sample (L) above a selected cut-off point (L´) as Z=K[(L-L)/LL´)]. For a series of arbitrary cut-off lengths (Li´) above size of full recruitment to the fishery
and corresponding mean lengths of all individual above Li, there is a linear relationship shown
below according to Pauly (1984),
Li-Li´=+Li
(equation 2)
Y-values of the difference between mean length and cut-off point is plotted against cut-off
points to judge linear relationship. and is then estimated by linear regression of the
selected length class range, and L = -/ and Z/K=(1+)/-. Estimations on L are also
performed by the method of Munro (Munro 1982), Faben (Fabens 1965) and Appeldoorn
(Appeldoorn 1987) respectively (FISAT II).
For individuals larger than length at onset of sexual maturity von Bertalanffy growth curve
assume that the growth rate (dL/dt) declines linearly with length, and Gulland and Holt (1959)
showed that K and L can be estimated using the relationship
L/t= a + bL
(equation 3)
where L=L2-L1, t=t2-t1 and L=L1+(L/2), and K and L is estimated as K=-b and L= a/b. The estimation of L from the Powell-Wetherall method is used to fix (“force”) the line
to the x-axis through the data points of L/t, to be able to calculate the linear regression
coefficients and K. The growth data comes from mark-recapture experiments where edible
crabs in Skagerrak and Kattegat have been marked with suture tags and Floy (Ungfors et al.
2007) tags allowing for recapture of tagged individual after carapace shedding and growth .
Data on moult increment and time between tagging and recapture exists from the 1968-1973
marking period in Skagerrak where in total 3749 edible crabs were tagged and released (moult
increment Hallbäck, unpublished). Of these, 1250 individuals (33 %) were recaptured and 126
individuals indicated growth. In order to decrease the risk of over-estimation of growth due to
short time since release, only recoveries longer than one year ( 365 days) were considered.
Underestimation of growth is considered by not including the recaptured individuals with
5
5
zero growth, and < 5 mm due to measurement errors. Thus, 54 females and 12 males are used
in the growth analyses of L/t (nfemales=54, nmales=12). K are also estimated by the iterative
Munro (Munro 1982), Fabens (Fabens 1965) and Appledoorn (Appeldoorn 1987) method in
FISAT II, and by the Ford-Walford plot where L is set to 210, 200 and 190 mm and the sexspecific average of L/t is used to calculate K (Jones 1984).
The parameters a and b in equation W=aCWb, where W=weight (g) and CW=carapace width
(mm) were solved by linear regression of log transformed weight and carapace data. Weightat-carapace width is used in the calculation of biomass from number of individuals. Weight
data are restricted to include only landed crabs of good meat yield.
Estimations on natural mortality rate (M) are performed by the aid of two general life-history
formulas: 1) Rikhter&Effanov formula where M=(1.52/tmass)0.72-0.16, where tmass is the age
(year) at which 50% of the stock reaches the age of “massive spawning”. M is estimated for
massive maturation age between 4 and 8 years. 2) Pauly (1980) ln(M)= -0.0152-0.279 log(L)
+ 0.6543 log(K) + 0.4634ln(T) and -0.4852-0.0824ln(W) + 0.6757 ln(K) + 0.4627ln(T)
where W is the weight (g) at L and T is the mean annual habitat temperature. Temperature
data from monthly samplings at 30 m depth from 15 locations along the Skagerrak coast
(www.bvvf.se), annual average 9.2 °C for 2007.
A discrete growth curve based on measurement on moult increment (MI) per pre-moult CW
(tagging experiment, laboratory moultings and creel captures of moulted individuals within
creels) and moult frequency based on literature on C.pagurus (Edwards 1979) and C.
magister (Wainwright&Armstrong 1993) are given to show carapace width with age. 25 to 10
% of MI per premoult carapace width is used (25% < 130 mm, 20% 130-150 mm, 15 % 150170 and 10 % > 170 mm). The combination of growth parameter, which makes the
continuous Bertalanffy growth curve performance similar to this guess of discrete growth, is
given.
Length frequency data
Length frequency is sampled from commercial landing and discards in Kattegat and
Skagerrak (figure 1). Samplings have covered the fishery distribution at coastal and more offshore ground in Kattegat and at coastal locations in Skagerrak. During the years 1999 to 2004
some locations have been resampled up to five times and other have been visited only
occasionally. In addition to the capture data sampled by an observer on selected trips a few
fishermen have been filled out capture log books for three pots on a regular basis during
2002-2004. The sampling months are from May to December. In total, 19322 edible crabs
have been measured in samplings considering both landing and discard frequency for females
and males, respectively (table 1).
The total landing of edible crab in Kattegatt and Skagerrak (table 1) is used to raise the
sampled length frequency of landings and discards (figure 2). A mortality of 1 % of the
discards was used to calculate removal frequency from raised landings and discards (table 2).
The total commercial landing in 2006 was 134 tonnes (log book data, National Board of
Fisheries) and the recreational fishery in 2006 was estimated to 269 tonnes (Anon 2007).
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Commercial landing was similar for the Kattegat and the Skagerrak but recreational landings
were 53 and 216 tonnes, respectively (Anon 2007). In addition to fishing area, the landings
were divided into a female and male part: 1:1 of females to males are assumed in Skagerrak
and 2:1 in Kattegat, which is based on sex ratio in the samplings. The fishery in Skagerrak is
coastal but in Kattegat it occurs also further offshore with a different capture composition
(larger individuals) why half of the commercial landing are assumed to be of inshore length
frequency and half of offshore (sex-specific). All recreational fishery in Kattegat was
assumed to be coastal (table 1).
Length cohort analysis (LCA)
The calculation steps of LCA are describe in Jones (1984) and a recent user-friendly
description of length cohort analyses is presented by Jennings et al (2001, p. 143-144). Length
cohort population analysis is based on the formulas of age cohort population analyses (Pope
1972) but instead of using the frequency of different age cohorts (often 1 year in between) of
catch or landings and discards, the frequency of length groups with constant class interval are
sampled. The underlying assumptions are that the majority of the decline in the length class is
due to the catch (fishing mortality), and that the length composition of the catch is in a steadystate condition caused by constant (i.e. no time trends in) recruitment and mortality.
The age (t) of the length groups are then calculated with aid of growth parameters L and K,
and von Bertalanffy growth equation (von Bertalanffy 1938; Beverton&Holt 1957) solved for
t,
t1= -(1/K)*ln(1-(L1/L))
(equation 4)
where t1 is the age of the smallest cohort, t2 the age of next cohort etc. The time for growth to
next cohort, t, is calculated as the difference in ages or as
t=(1/K) ln((L-L1)/( L-L2))
(equation 5)
where L1 is shortest width of cohort 1 and L2 shortest width at cohort 2. Age cohort and
length cohort analyses use Pope´s approximation (Pope 1972) of the catch equation of virtual
population analyses (VPA), assuming that the catch is taken halfway through the age of the
cohort instead of continuously. Jones (1984) modified Pope formulas for LPA, and both
formulas are given below. The number of individuals per cohort is calculated by
Nt= (Nt+teMt/2 + Ct) eMt/2
(Pope, equation 6)
or as Jones (1984) noted that Mt/2= (M/2K)*ln((L-L1)/( L-L2)) and eMt/2= (L-L1)/( LL2)M/2K= XL2L1, then a simpler numerical formula for the step-wise backward calculation of
number attaining each size class, if considering catch and natural mortality, is
NL1=(NL2XL2L1+C1,2)XL2L1
(Jones, equation 7)
However, first is the number attaining the largest cohort calculated by the use of an initial
guess of the terminal F/Z in the catch equation, and solving for NL
CL = F/Z *NL(1-e-Zt)
(equation 8)
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keeping e-Zt =0 as the age of the largest size class after the t is infinite. After being able to
calculate the stock size attaining each length class, the fishing mortality rates for each cohort
can be calculated by
F=M*((F/Z)/(1-F/Z))
(equation 9)
where F/Z per cohort is calculated as the quota from catches and the total decrease in stock
numbers
F/Z = C1,2/(NL1-NL2)
(equation 10)
The fishing mortality is also presented as the weighted for population (Fp) and catch weight
(Fc) as suggested by Bannister and Addison (1984),
Fp=(Pi Fi ti)/( Pi ti) and Fc=(Ci Fi ti)/( Ci ti)
(equation 11)
To calculate the actual numbers in the stock at Sea from the numbers of individuals that attain
each cohort, the average number per length class and year is calculated as
NL1L2 = (NL1-NL2)/Z
(equation 12)
where Z is calculated as
Z=M/(1-F/Z)
(equation 13)
Monte Carlo simulations of LCA
The LCA is accomplished in MAT LAB computer programme. Indata for L is drawn
randomly with replacement by Monte Carlo simulation from a normal distribution with a
defined mean and standard deviation. The mean and standard deviation, 202.2 ±12.2 females
and 197.4±8.6 males, is estimated from the calculated values of L but other means and
standard deviations are controlled for. A minimum L was set to 191 mm to allow LCA
calculations with the plus group of 190 mm. As the L and K are linked (covariates) the K is
drawn from the linear relationship, based on the simulated L and the slope (-0.006349),
standard deviation (0.0004) of the slope and intercept (1.589) (figure 4). A minimum of K
was set to 0.150. 1000 runs of the LCA with different values within the L distribution and
dependent K combinations are performed to estimate fishing mortality with uncertainty (SD
or 95% confidence interval) for females and males in Skagerrak and Kattegat respectively.
The same L and K is used for all eleven cohorts (plus group excluded) in a run.
The biomass of the stock is calculated by using the linear log-log relationship between crab
weight (g) and carapace width (mm) log(W)=log(a) +log(CW)*b to estimate weight at mid
cohort length, and multiplication by the cohort-specific average number of edible crab. The
parameter value log(a) and b is estimated in each LCA run (1000) by Monte Carlo simulation
using the distribution of mean and standard deviation given in table 3 (specific parameter
values for females and males in Kattegat and Skagerrak, respectively). The stock biomass
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(tonnes) is given per cohort class or as a mean, with standard deviation or 95% confidence
interval calculated from the 1000 runs.
Estimation of egg production of the spawning stock biomass build on: 1) data of the egg
production (fecundity) for female edible crab in Skagerrak and Kattegat, fecundity
(no.)=24180*CW-2229266 (standard deviation slope 2739; standard deviation intercept
417142) (Ungfors 2007). The mid carapace width per cohort is used to draw a value of
fecundity given the regression characters above; 2) on the assumption of a knife-edged start of
spawning at the 110 mm CW cohort (113 mm CW smallest ovigerous female) (Ungfors
2007), and 3) estimations of the annual proportion of spawning females of the female
population. Observations of the ovigerous proportion (Hallbäck, H unpublished) show that at
most females are egg-bearing every second year as the proportion mature based on this
character reach 50%: P115=0.01, P125=0.05, P135=0.15, P145=32, P155=44, P165=0.48, P175=0.50,
P185=0.50. The total egg production is estimated through the product of the number of females
per cohort (estimated in the LCA runs), and the cohort-specific fecundity randomly simulated
from the regression times the proportion ovigerous females.
Standard deviation or 95 % confidence interval is presented for the different averaged and
standardised F, stock estimates and egg production. The coefficient of variation (CV), which
is the standard deviation divided with its mean, is also used in presentations of fishing
mortality.
Results
Growth parameters
The estimations of L and K from different approaches are given in table 3. A mean and
standard deviation of L is estimated from these values of L; for females 202.2± 12.2, and
for males 197.4±8.6. For graphical presentation on the length at age for the different growth
parameters a selection of the estimated combinations of growth parameters (7 of 11
combinations for females and 7 of 9 combinations for males) from table 3 are inserted in
Bertalanffy growth curve (VBGC) (figure 3a and b respectively). In figure 3c) is a guessimate
for the discrete growth curve based on measurements on Swedish edible crab moult
increments per pre-moult CW, and from moult frequency based on literature on C.pagurus
(Edwards 1979) and C. magister (Wainwright&Armstrong 1993). A continuous VBGC with
L of 217 and K of 0.160 fit relatively well to this discrete growth curve. The growth
parameters are not independent but co-vary in such that a higher L generates a lower K for
the used approaches. The linear regression between K as a dependent variable and L as the
independent (figure 4, K= L*-0.0063+1.5895 with SD ±0.0004 of the slope, R2=0.37) was
used to calculate K from L in further simulations on LCA in MATLAB.
Fishing mortality (F)
The overall fishing mortality, the average for the three most exploited cohorts F3max, F110-160,
and F weighted to population (Fp) and to catch (Fc) is given in table 4. Females are more
exploited than males, which is a consistent pattern for Kattegat and Skagerrak (table 4, and
figures 5 and 6).
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The cohort-specific fishing mortality has a different pattern in Kattegat in comparison with
Skagerrak. In Kattegat F is relatively low for the cohorts up to 140 mm CW and rise sharply
for cohorts 160-170 mm CW (figure 5). In Skagerrak the increase in F with size is smoother
including a wider range of cohorts i.e. 140-170 mm CW being most exploited (figure 6).
Changes in input mean and standard deviation of L impacts the coefficient of variance (CV)
of fishing mortality more than it impacts actual changes in fishing mortality (figure 7). A low
mean (202 mm CW) results in a relative high CV of the larger cohorts (approx. 60%) and
lesser CV in the smaller cohorts. A high mean of 217 mm CW increase the CV on the smaller
cohorts (50 % CV of the smaller and 40% CV of the larger cohorts) (figure 7a and b). Ten
times lower standard deviation of the low input L decrease the CV for the large cohorts
(figure 7a and c). Narrowing the distribution around the large mean of 217 mm CW does not
impact the relative standard deviation much in comparison with a wider distribution (figure
7b and d) except for a small increase in the smaller cohorts.
Values of natural mortality within 0.1-0.3 have no dramatic effect on mean fishing mortality
(M0.1 0.32±0.14, M0.2 0.30±0.11 and M0.3 0.28±0.12) but an overall increase in CV is noted
with higher M especially for the smaller cohorts (figure 8, Kattegat females as an example).
The three most exploited cohorts i.e. 150-170 mm CW has mean F3max of 0.78±0.25,
0.71±0.26 and 0.65±28 with increasing M.
Stock abundance and egg production
The total stock biomass in Kattegat and Skagerrak estimated with LCA is 2495±613 tonnes
and a stock abundance 6.03±1.1 million of edible crabs (table 5a). Using higher mean L in
the resampling procedure resulted in 20 % lower biomass and 4 % lower abundance (table
5b). The egg production is five magnitudes higher than the stock abundance. The total egg
production of the spawning stock is 6.79±2.38 x10^11 but 14 % lower if using a higher value
on L (table 5). An example (Females Skagerrak) of the cohort specific outcome of stock and
egg estimates for the 1000 runs are shown in figure 9, and averaged in table 6.
Assuming a natural mortality of 0.1 results in lower estimates of stock size and egg
production and using a higher (0.3) result in higher estimates (table 6), compared to the
general used M of 0.2 (table 5). The stock is 1599±221 tonnes or 4.32±0.38 x10^6 crabs, and
the estimated egg production is 5.04±1.33 x10^11 when M=0.1, and 2619±467 tonnes or
8.29±1.25 x10^6 crabs and 6.90±2.63 x10^11 eggs when M=0.3 (compare with table 5b for
M=0.2).
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Discussion
We have estimated von Bertalanffy growth parameter L and K for the edible crab in Kattegat
and Skagerrak. These parameters were used in LCA for the estimation of stock indicators
fishing mortality, stock biomass and abundance and egg production of spawning stock. Below
we compared our result with findings in crustacean literature. In addition we discuss the
importance of natural mortality and strategies for length frequency sampling. The context of
the discussion considers the advantages and disadvantages of using LCA. The advantages are
that the model use length frequency data available for crustaceans for which aging methods
are in its infancy. Species for which aging is a problem this model still is an assessment
option for rough estimates of e.g. stock abundance. Also the model can be compiled in
common and user friendly programmes as Excel. However, we performed the LCA in
MATLAB as we included uncertainty of growth parameters, weight-at-length and fecundity
by Monte Carlo resampling. The drawback of the model is that length is used as an indicator
of age, but that the individual growth has been shown to be variable. Furthermore, the
parameter natural mortality has a large impact in the model.
Growth parameters and LCA
Our analyses of length frequencies pointed at L of 179-212 mm but as the maximum
observed edible crab in Swedish waters is 207 mm CW, the lower estimated L might be
biased by few captures of large individuals. Our estimate of L 217 mm, 5 % over maximum
carapace width, is considerably lower than the chosen L of 240 mm at the east coast of
England (Addison&Bennett 1992). However, Addison and Bennett (1992) considered values
of 220 and as low as 180 mm for the UK stock assessment. The Addison and Bennett (1992)
best estimate of the growth parameter K is 0.191 and 0.196 for females and males
respectively. These estimates originating from tagging data and using Jones modification of a
Ford-Walford plot, is close to our estimate of K for the same approach, especially for females.
However, our estimations of growth parameters by Ford-Walford gave lower value for K in
comparison with approaches in FISAT II (forced Gulland-Holt plot, Munro, Fabens,
Appledoorn). Haddon (2001, p. 212) point at discrepancies of growth parameter from
different approaches: L from tagging data e.g. Fabens method are shown to be biased high,
but low for the K parameter in comparison with fitting VBGC by length at age data where
both parameter were slightly lower than the overall averages. Sheehy and Prior (2005)
estimated growth parameters with fitting Bertalanffy growth curve to weight at age data for
edible crab, and the parameters were within the range of most previously stock assessment
options: L 176-245 and K 0.41-0.66. The K parameters from that study are at the higher end
of the interval we found, 0.193-0.586. A continuous Bertalanffy growth curve with L of 217
and a K of 0.160 graphically seem to fit relatively well with a empirical discrete growth curve
based on estimates on the proportional MI (Swedish data; Hallbäck, unpublished) and moult
frequency (Edwards 1979; Wainwright&Armstrong 1993). By lipofuscin aging technique
Sheehy and Prior (2005) estimated the average maximum edible crab life-span to around 10
years around UK and oldest crabs were around 14.6 (95 % CI 11.5-19.1). Interestingly, a 207
mm CW crab have an estimated age of 19.2 years based on the length-based VBGF as in
LCA, using L 217 and K 0.160. Sheehy and Prior (2005) showed that the longevity varied
inversely with sea temperature i.e. a longer life at the cooler E. coast than in the warmer
Channel. We can only speculate on longer longevity further north such as in in Kattegat and
Skagerrak.
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The fishing mortality in Kattegat and Skagerrak is higher for females (average F110-160=0.33,
Fp=0.26 and Fc=0.53) than for males (average F110-160=0.22, Fp=0.21 and Fc=0.35). From
these values of F the annual fishing mortality rate i.e. proportion of the stock dying from
fishing, is estimated to 23-41 % (F 0.26-0.53) of females and 19-30% (F 0.21-035) for males.
In general, are females the preferred target for Swedish fishermen as the price for females is
higher than for males, which may explain this exploitation pattern. Possible, catchability is
higher for females e.g. as females are highly attracted to baited pots after winter diet and
hatching period (Brown&Bennett 1980). In contrary, fishing mortality on the UK East coast,
from LCA, has been found to be lower for females (average Fp and Fc=1.30) than for males
(average Fp and Fc=1.62) (Addison&Bennett 1992). If excluding the Norfolk data (one of
three analysed regions) these estimates are 0.83 and 0.50 respectively. The Fp value for
Kattegat and Skagerrak ranged between 0.17-0.27 and the Fc between 0.22-0.61 whereas
similar estimates for the East coast of England is 0.34-3.02 and 0.66-3.36, respectively.
Recent findings on the UK East Coast, using age-length key, linearized catch curves (Z) and
estimations on natural mortality (M), show that fishing mortality (F=Z-M) on female were
higher than that for males (Sheehy&Prior 2005). For the Western English Channel, Sheehy
and Prior (2005) found that mortality induced by the fishery is higher (1.02) for males than
for females (0.21), whereas Bennett (1979) found more consistency in fishing mortality
between sexes (0.44-0.46) using length frequency data converted to age data and exploitation
estimates from tagging. An impact of the growth parameters on the coefficient of variance of
fishing mortality is observed e.g. a low L in combination with a relative wide SD generates
higher CV for the larger cohorts. However, the fishing mortality in Kattegat and Skagerrak is
low despite consideration (resampling) of different potential parameter values. Addison and
Bennett (1992) found that the fishing mortality Fc varied between 0.57-0.78 for females and
0.83-1.54 for males, for six different growth parameter combinations. The fishery mortality in
Kattegat and Skagerrak seem to be in the lower range of estimates from other areas.
Uncertainty in growth parameters K and L is judged to be the major cause of poor length
based assessment for Nephrop norvegicus Skagerrak-Kattegat stock (ICES 1999). Sensitivity
analyses for different combinations of growth parameters were performed in Addison and
Bennett (1992) LCA for yield and biomass per recruit, respectively. In our estimation of stock
biomass and abundance a wide range of growth parameters were considered using Monte
Carlo resampling of L around a mean with a given standard deviation. In addition the K was
resampled from the regression of K and L with uncertainty in the slope. Given the total
commercial and recreational landing of 401 tonnes, the stock biomass is 1600-2600 tonnes in
Kattegat and Skagerrak, and the abundance about 4-8 million crabs. This stock estimation
must be considered minimum as the actual commercial landing is probably higher than
reported. Critizism on using size bins as pseudo age cohorts in LCA base its arguments on
that the majority of size variation is not explained by age and that the descending slope of the
CW-frequency distribution used in LCA is primarily a reflection of individual growth
variation rather than age (Sheehy&Prior 2005). The individual variation of growth is large but
we believe that the right-hand slope indicate a decreasing abundance of older individuals. A
high variation in individual growth is to some extent regarded for in the average results, by
repeating the LCA several times (1000) using different growth combinations per repeat. The
precision of age estimates of 1, 7 and 15 years old edible crabs, using 95% confidence
interval, is 0.6-2, 5.2-9.7 and 11.8-19.7 (Sheehy&Prior 2005). So, using lipofuscin aging in
stock assessment still incorporates bias, similar to the drawback of using length frequency as
estimates of age bins.
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The approaches of the age determination of crustaceans are still expensive and timeconsuming but age-length keys have recently been used in parameter estimation and stock
assessment (Ju et al. 2003; Sheehy&Prior 2005; Fonseca&Sheehy 2007). Crustacean
assessment based on both age and length-cohort approaches for the same regional area have
been used to evaluate the traditional length-cohort method (Sheehy&Prior 2005;
Fonseca&Sheehy 2007). The ability to use lipofuscin frequency distribution more accurately
estimates (lower prediction errors, higher regression r2) the age distribution in the population
in comparison with the size distribution, which generally is considered a poor proxy for age
because of individual variations in growth due to numerous environmental, densitydependent, and fishery-related factors. However, for some environment, size can be a
predictor of age (Uglem et al. 2005) and even for a long-lived species as the freshwater signal
crayfish Pacifastacus leniusculus with longevity of 12-16 years the r2 of size and age is 84.1
% (Belchier et al. 1998). Lipofuscin aging technique has shown that there is large individual
variation in size-at-age but importantly the mean age is increasing with larger sizes.
Recommendations to define the plus group to less than 70 % of L (Addison&Bennett 1992)
were not considered. We suspect that exclusion of larger individuals negatively bias the stock
estimation as including does.
A larger total egg production was seen with a smaller L (mean 202). A smaller mean L
generates larger K parameter values i.e. individuals grow faster, mature earlier and therefore
produce more eggs during their life-time.
Natural mortality
The importance of an accurate estimate of natural mortality is well-known in fisheries
assessment, and as well is the difficulty estimating it. Our assessment is no exception, the
natural mortality impacted the stock estimates and the average fishing mortality i.e. the stock
abundance and egg production increased with higher value on M but the fishery mortality
decreased. Evaluation of long-term harvest strategy for red king crab Paralithodes
camtschaticus using length-structured model found that the result was highly sensitive to
changes in M of 0.2-0.3 (Zheng et al. 2003). The fishing mortality is estimated for the blue
crab in Cheasapeak Bay given presumed levels of M (Miller et al. 2005). The levels of M
produced varying estimates of F with the lowest values being associated with an M of 0.375
and the highest F with an M of 1.2. Natural mortality can usually be estimated by relative
abundance of different ages (or size, if aging difficulties) on an unfished virgin population
before fishing is impacting age or size structure and where total mortality Z is allocated to M.
A review of six common methods for the estimating of natural mortality is given in Quinn
and Deriso (1999): 1) catch curve analyses, 2) length-frequency analysis, 3) mark-recapture
experiments (Siddeek et al. 2002; Frusher&Hoenig 2003), 4) collection of dead organisms, 5)
fitting population models (Zheng et al. 1997) and 6) meta analysis of life history. An
alternative to the complex estimations for finding M especially of data poor populations is to
use estimations for same species but in other regions, or from other species with similar lifehistory (alternative 6 above). This value is of course dependent of the accuracy of that
estimation and how similar the taxa life-history. General indirect methods, relying on
parameters such as age at maturity, longevity, body size, L and K often measured in
biological studies, have been established (Hewitt et al. 2007). We estimated M by Pauly
(1980) formula using L, K and mean habitat temperature to 0.26, and by Rikther&Efanov
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formula (1976) using age at massive maturation to 0.18-0.34. Based on Hoenig (1983)
general formula ln(M)=1.44-0.982Ln (Amax) and using the oldest 5% for the average
longevity, Sheehy and Prior (2005) estimated natural mortality to 0.45 for males and 0.39 for
females in region E. coast.
Previous edible crab assessment values of M have been in the range 0.1-0.69 (Hancock 1975;
Bennett 1979; Addison&Bennett 1992; Sheehy&Prior 2005) but 0.2 are often regarded as a
good estimate. Our indirect life-history estimates of M point at M in the mid of this range, or
just above the holy 0.2 value. Natural mortality can formerly have been underestimated
because of a belief on low predation in the armoured species and a belief in relatively low
mortality during moulting. On the other hand, by the use of the general formulas empirically
based on several species the edible crab must be considered a rigid species. Not only because
of an armoured shelter from predation but from less-active winter (both sexes) and spawned
(females) behaviour. Overestimation of M in rigid species by these general life-history
formulas might therefore occur.
Sampling strategy of length frequency
Internal cycles as moulting and spawning impact the catchability of edible crabs in the fishery
why the length frequency during the year may change at a fishing location (Brown&Bennett
1980). Immigration into and emigration out from a location of adult individuals, especially
females, may also impact size frequency (and age frequency). Juveniles and pre-recruits may
also change habitat during growth. To get a rigid estimation on length frequency in landings it
is more efficient to sample one or few pot from all trips from several fishermen instead of
several pots from a few trips (McGarvey&Pennington 2001; Woll et al. 2006). The least
efficient sampling strategy was by research sampling measuring all pots on selected trips
(McGarvey&Pennington 2001). The length frequencies in our study come from a mixture of
selected trips with onboard observer measuring whole catch, and from a few fishermen using
standardised and/or selected pots for regular measurements. For collection of reliable capture
and length data, a sampling strategy must be emphasized from the Swedish National Board of
Fisheries allowing observers for edible crab. Or alternatively, fishermen within the pilot
projects for local co-operative management of fisheries (Anon 2008) can, if the co-operative
initiative become permanent, be encouraged to sample detailed data of one to three pots per
fishing trip.
Future assessment
To use an alternative modelling strategy such as dynamic length-structured method
(Punt&Kennedy 1997), we need to evaluate the available data. Biomass surplus modelling
(Hilborn 2001) using LPUE data and landings from log-books can be worthwhile testing with
data from 1995-2007. The LPUE in the logbooks can be improved by detailed review of the
effort reporting by e.g. interviews with skippers to get information on amount of used gears
over the years, and possible to get private landing records. Generalized linear models can be
used to quantify the variation in LPUE by e.g. year, month, area or vessel/vessel type.
Variation in LPUE in the log book due to differences in substrate or depth, can be elucidated
by available position of fisheries and GIS information (BALANCE 2007).
Establishing age-length keys for the Swedish edible crab are tempting. The calibration to
chronological age and the thermal correction of age estimates for edible crab were made on
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the basis of cohorts modes of neurolipofuscin concentration frequency distributions (NCFD)
for different areas with different mean temperatures (Sheehy&Prior 2005), and not by use of
individuals of known age reared in laboratory (Belchier et al. 1998). If pronounced
temperature differences between Kattegat and Skagerrak fishery locations, keys need to be
established for both areas as Sheehy and Prior (2005) found a strong relationship (r2=0.78,
p<0.001) between sea temperature and neurolipofuscin accumulation rate.
Acknowledgement
We are grateful to Per Jonsson and Mats Lindegarth for invaluable guidance in MATLAB
scipt writing and programme instructions. Thanks also to all involved fishermen firstly
allowing a female marine biologist onboard and secondly for the measurement support
despite delaying working tempo. Hans Hallbäck for scuba diving sampling of ovigerous
females used to estimate spawning population proportion.
Reference
Addison JT, Bennett DB. 1992. Assessment of minimum landing sizes of the edible crab,
Cancer pagurus L, on the East Coast of England. Fisheries Research 13, 67-88.
Anon. 2007. Fritidsfiske och frittidsfiskebaserad verksamhet. Titel in English: Recreational
fishery and co-existing business. Report from the Swedish National Board of
Fisheries. 182 pp.
Anon. 2008. Uthålligt yrkesfiske i norra Bohuslän - en samförvaltningsplan med fokus på
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20
TABLES
Table 1. Length frequencies of edible crab originate from
sampling aboard commercial fishing vessels in 1999 to 2004
where both the landed (L) and the discarded (D) individuals
were measured. Total landing=commercial landing from
logbooks and estimated recreational landing.
Stock
No. of sampled
individuals in
landing; discard
Linsh 1164, Loff 1908;
Dinsh 717, Doff 1299
Total Landings
(tonnes)
Kattegat M
Linsh 404, Loff 698;
Dinsh 282, Doff 565
Inshore 28.54;
Offshore 11.055=39.60
Skagerrak F
Skagerrak M
Sum
n= 5270; 1874
n=4353; 788
19322
140.5
140.5
Kattegat F
Inshore 57.96;
Offshore 22.45=80.41
401
Table 2. Raised removals (no) .per length frequency based
on total landing of commercial and recreational per sex and
per area, and sampled landing and discard length frequencies.
1 % mortality of the discards was assumed.
Total landing
frequency
(no.)
Female
Male
Kattegat Skagerrak Kattegat Skagerrak
80
2 361
942
2 977
1 267
510
353
507
90
425
3 572
990
5 773
100
6 592
9 837
2 257
13 184
110
4 165
26 174
3 692
25 147
120
8 121
53 009
6 752
44 807
130
18 177
76 374
10 191
45 541
140
28 808
76 121
11 660
46 674
150
40 797
49 783
11 640
37 374
160
35 552
27 403
9 901
29 847
170
16 087
180
8 289
3 604
15 236
3 984
2 608
724
8 346
190
1 015
Sum
164 990
336 041
62 706
275 413
*The sampled length frequencies are scaled to reach the total landings
(tonnes) by a multiplying factor using weight-at-carapace width parameters.
21
Table 3. The estimated growth parameters L and K by different approaches, natural
mortality M by empirically developed formulas, and weight-at-carapace width.
MR=Mark-recapture.
Sex
Location
L Capture data
Power-Wetherall
Z/K
Empirical L
K MR data
Forced GullandHolt
L; K MR data
Munro`s
Fabens
Appeldoorn`s
K MR data
Ford-Walford
M
Pauly (1980)
Rikther/Effanov
(1976)
Weight –width*
a
b
log a
Female
Male
Kattegat
Skagerrak
Kattegat
Skagerrak
193; 212
182; 197,
193; 202
179; 195
(n>140=3713) (n>140=1574)
(n>140=2649)
(n>140=4308)
0.92; 2.00
3.28; 5.30
0.82; 1.63
2.12; 2.77
217 (5% over max 207 mm CW)
0.586 (179);
0.403 (193);
0.386 (195);
0.283 (212)
0.263 (217)
0.263 (217)
n=54
201; 0.450
212; 0.253
210 ± se 16.7; K 0.260±se 0.08)
0.193 (L 210)
0.214 (L 200)
0.241 (L 190)
0.391 (182);
0.289 (197);
0.214 (217)
n=12
190; 0.603
0.21-0.25 (9.2°C) (W-L)
0.34-0.32-0.26- 0.21- 0.18 (age
of 4-8 years at maturation,
resp.)
n=656
n=716
0.000194
0.000284
2.9297±0.038
2.8620± 0.052
-3.71±0.084
-3.55±0.112
0.21-0.25 (9.2°C) (W-L)
0.34-0.32
(age of 4-5 years at maturation,
resp.)
n=139
n=348
0.00004133
0.00004890
3.2758±0.088
3.2419±0.061
-4.38±0.190
-4.31±0.130
*Landings, intact individuals.
22
0.310 (193);
0.266 (202)
0.214 (217)
0.241 (L 210)
0.269 (L 200)
0.304 (L 190)
Table 4. Mean and standard deviation of fishery mortality measured for all edible
crab cohorts (Fall), for the inter-quartile 110-160 mm CW (F110-160), for the three most
exploited cohorts (F3max) (females and male Skg 150-170 mm cohorts, male Kgt 160180 mm cohorts) and the fishery mortality weighted for population, Fp, or catch, Fc,
for females and males in Kattegat and Skagerrak. The values of L are simulated by
Monte Carlo resampling and the incident value of K is drawn from the regression of
K and L (n= 1000 per cohort). Table a) and in b) differ in mean ± SD of the growth
parameter L.
a)
L 202.2±12.2 for females and 197.4±8.6 for males
Area
Fall
F110-160
F3max
FEMALE
MALE
b)
Kattegat
Skagerrak
Kattegat
Skagerrak
0.26±0.11
0.27±0.12
0.19±0.09
0.15±0.07
0.31±0.12
0.35±0.13
0.22±0.09
0.21±0.09
0.62±0.26
0.57±0.25
0.40±0.16
0.27±0.12
Fp
Fc
0.26±0.11
0.26±0.12
0.22±0.10
0.17±0.09
0.52±0.23
0.47±0.21
0.35±0.18
0.22±0.12
L 217±12.2 for females and 217±8.6
FEMALE
MALE
Area
Fall
F110-160
F3max
Fp
Fc
Kattegat
Skagerrak
Kattegat
Skagerrak
0.30±0.11
0.30±0.12
0.25±0.10
0.19±0.08
0.33±0.13
0.35±0.14
0.23±0.10
0.24±0.10
0.71±0.26
0.64±0.25
0.58±0.22
0.36±0.15
0.26±0.11
0.27±0.12
0.24±0.11
0.20±0.09
0.61±0.22
0.54±0.21
0.50±0.19
0.32±0.13
23
Table 5. Stock abundance, biomass and egg production of edible crab based on
Length cohort analyses. Mean and standard deviation are given (n=1000). Table a)
and in b) differ in mean ± SD of the growth parameter L.
a) Mean L 202.2 ±12.2 for females and 197.4±8.6 for males.
KATTEGAT
SKAGERRAK
b)
Females
Males
Females
Males
Sum of means
Stock abundance
(no.) 10^6
1.05±0.55
0.49±0.38
2.00±1.05
2.49±2.44
6.03±1.1
Stock biomass
mean (tonnes)
329±192
258±303
670±419
1238±1538
2495±613
Current Egg
production (10^11)
2.44±1.78
4.35 ±2.97
6.79±2.38
L 217±12.2 for females and 217±8.6 for males.
KATTEGAT
SKAGERRAK
Females
Males
Females
Males
Sum of means
Stock abundance
(no.) 10^6
1.08±0.64
0.47±0.22
2.07±0.91
2.15±1.0
5.77±0.69
Stock biomass
mean (tonnes)
317±205
209±175
617±344
840±522
1983±311
Current Egg
production (10^11)
2.05±1.57
3.82 ±2.22
5.87±1.89
Table 6. Stock abundance, biomass and egg production of edible crab based on
Length cohort analysis. Mean and standard deviation are given (n=1000). L
217±12.2 for females and 217±8.6 for males (as in table 5b). Table a) and in b) differ
in used value of natural mortality M.
a) M=0.1
Area
Sex
KATTEGAT
Females
Males
Females
Males
Sum of means
SKAGERRAK
Stock abundance
(no.) 10^6
0.82±0.29
0.34±0.12
1.60±0.55
1.56±0.57
4.32±0.38
Stock biomass
mean (tonnes)
254±112
151±112
517±269
677±390
1599±221
Current Egg
production (10^11)
1.82±0.98
Stock
abundance
(no.) 10^6
1.48±0.84
0.70±0.40
2.95±1.91
3.16±1.84
8.29±1.25
Stock biomass
mean (tonnes)
Current Egg
production
(10^11)
2.40±1.54
3.22±1.68
5.04±1.33
b) M=0.3
Area
Sex
Kattegat
Females
Males
Females
Males
Sum of means
Skagerrak
24
408±245
279±250
845±626
1087±746
2619±467
4.50±3.72
6.90±2.63
FIGURES
Figure 1. Map over sampling locations for length
frequency of landings and discards (n=sampled
individuals) in commercial edible crab captures.
Figure 2. Raised landing (left) and raised discard (right) size frequency for females
and males in Kattegat and Skagerrak.
25
a)
b)
c)
Figure 3. Carapace width-at-age based on a selection of our estimated growth
parameters (L and K) for a) females and b) males (see table 3). In c) is shown a
simulated discrete growth rate based on moult increment (MI) of 25-10 % (decreasing
with size) of pre-moult CW and moult frequency. MI is based on observations on
moult of Swedish crabs (tagging experiment and individuals moulted in creels), and
estimation of frequency is based on literature of C. pagurus (Edwards 1979) and C.
magister (Wainwright and Armstrong 1993) (basically decreasing with size). The
dotted line in c) is the von Bertalanffy growth curve with L 217 and K 0.160.
26
Figure 4. Linear regression of K and L. The
standard deviation of the slope is 0.0004. This
relationship with including slope uncertainty is
used to repeatedly sample K, after that the
resampled L is given.
Figure 5. Kattegat. Fishing mortality of a) females using L 217±12.2, and of b)
males using L 217±8.6. Cohort 1=80 mm CW and cohort 11=180 mm; 10 mm
cohorts. Runs=1000.
Figure 6. Skagerrak. Fishing mortality of a) females using L 217±12.2 and of b)
males using L 217±8.6. Cohort 1=80 mm CW and cohort 11=180 mm; 10 mm
cohorts. Runs=1000.
27
a) 202±12.2
c) 202±1.2
b) 217±12.2
d) 217±1.2
Figure 7. Skagerrak females. Fishing mortality and 95 % confidence interval error
bars (above), and coefficient of variation (below) for different input mean and
standard deviation values of L. In a) L 202 ±12.2, b) L 217±12.2, c) L 202 ±1.2
and d) L 217±1.2. (M=0.2, n=1000).
28
a)
b)
c)
Figure 8. Kattegat females. Fishing mortality and 95 % confidence interval error bars
(above), and coefficient of variation (below) for different parameter value of natural
mortality: a) M=0.1, b) M=0.2 and c) M=0.3. The mean±SD of Fall is 0.32±0.14,
0.30±0.11 and 0.28±0.12 for increasing M. L 217±12.2.
Figure 9. Skagerrak females. Mean and 95% confidence interval of stock biomass
and abundance, and egg production using L 217±12.2. n=1000.
29

Cancer pagurus the Kattegat and the Skagerrak – implications for sustainable management

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