Shellsim - ECASA website

Transcription

Shellsim - ECASA website
Simulating growth in bivalve shellfish
A J S (Tony) Hawkins
Plymouth Marine Laboratory, U K
Background challenges
¾Aquaculture of suspension-feeding shellfish is among the
fastest-growing of all food-producing sectors, with increasing
pressure to model sustainable practises
¾Shellfish are highly responsive to fluctuations in temperature,
salinity, food availability and food composition, affecting growth
and ecosystem processes
¾To account for the complexity of associated processes and
their consequences in variable environments, dynamic
simulations are needed
¾Only by modelling feedbacks whereby shellfish interact with
ecosystem processes, can one assess environmental impacts
and capacities for culture
¾To identify the key interrelations, towards a common model
structure for calibration according to species and/or location
¾Tools should be cost-effective, meeting above challenges by
simulating dynamic responses using a minimum of drivers
Forcing
Forcing
functions
functions
•• Date
Date
•• Initial
Initialsize
size
•• Temperature
Temperature
•• Salinity
Salinity
•• Aerial
Aerialexposure
exposure
•• Food
Foodavailability
availabilityand
and
composition
composition(TPM,
(TPM,
CHL,
CHL,POM,
POM,POC)
POC)
Simulated
Simulated
responses
responses
•• Particle
Particleclearance
clearance
•• Ammonia
Ammonialosses
losses
•• Oxygen
Oxygenuptake
uptake
•• Faecal
Faecallosses
losses
•• Reproduction
Reproduction
•• Growth
Growth
•• Condition
Condition
http://www.shellsim.com/index.html
Example drivers
Temperature (°C)
Temperature (°C)
Chlorophyll a (µg/L)
Chlorophyll a (µg/L)
25
25
10
10
20
20
Scheldt Oyster
Scheldt Oyster
Scheldt Mussel
Scheldt Mussel
Creran 05-06
Creran 05-06
Clew Oyster
Clew Oyster
Clew Mussel
Clew Mussel
15
15
10
10
5
0
8
6
4
2
5
0
0
0
60 120 180 240 300 360 420 480 540 600 660 720
0
60 120 180 240 300 360 420 480 540 600 660 720
Scheldt Oyster
Scheldt Oyster
Scheldt Mussel
Scheldt Mussel
Creran
Creran
Clew Oyster
Clew Oyster
Clew Mussel
Clew Mussel
8
6
4
2
0
0
0
60 120 180 240 300 360 420 480 540 600 660 720
60 120 180 240 300 360 420 480 540 600 660 720
Julian Day
Julian Day
Julian Day
Julian Day
Particulate organic carbon (µg/L)
Particulate organic carbon (µg/L)
Salinity (‰ )
Salinity (‰ )
35
3435
3334
33
32
3132
3031
2930
2829
28
27
2627
2526
25
0
2000
2000
Scheldt Oyster
Scheldt Oyster
Scheldt Mussel
Scheldt Mussel
Creran
Creran
Clew Oyst
Clew Oyst
Clew Mussel
Clew Mussel
1000
1000
500
500
0
60 120 180 240 300 360 420 480 540 600 660 720
0 60 120 180 240 300 360 420 480 540 600 660 720
Julian Day
Julian Day
Scheldt Oyster
Scheldt Oyster
Scheldt Mussel
Scheldt Mussel
Creran
Creran
Clew Oysters
Clew Oysters
Clew Mussel
Clew Mussel
1500
1500
0
0
0
60 120 180 240 300 360 420 480 540 600 660 720
60 120 180 240 300 360 420 480 540 600 660 720
Julian Day
Julian Day
ShellSIM simulates feeding, metabolism and growth
across full ranges of natural variability
TotalWet
WetWeight
Weight(g)
(g)
Total
Measured
Measured2005
2005
Measured
Measured2006
2006
Predicted
Predicted2005
2005
Predicted
Predicted2006
2006
30
30
20
20
10
10
00
100
100
200
200
300
300
400
400
500
500
600
600
Julian
JulianDay
Day
Caledonian
Oysters
Comparison of measured and predicted growth rates for an
individual oyster Crassostrea gigas in Loch Creran, Scotland
3
2
0 100 200 300 400
DAY
400
300
200
100
0
0 100 200 300 400
DAY
20
15
10
5
0
0 100 200 300 400
DAY
4
3
2
1
Filtration (l/anim/d)
4
25
N loss (mg/anim/d)
5
Total fresh wt (g)
6
Oxygen uptake (ml/anim/d)
Faeces (dry mg/anim/d)
Shell length (cm)
ShellSIM simulates feeding, metabolism and growth
across full ranges of natural variability
0
0 100 200 300 400
DAY
60
50
40
30
20
10
0 100 200 300 400
DAY
0.25
0.20
0.15
0.10
0.05
0.00
0 100 200 300 400
DAY
For an individual Crasssostrea gigas during typical culture cycle
in Carlingford Lough, Ireland over 365 d: approximately 15 m3 cleared,
80 g dry biodeposits, 37 mg N excreted and 0.7 l O2 consumed
Species
Type
Site
Error in
Project or
predicted collaboration
growth
(%)
Single standard set of ShellSIM parameters, optimised per
species across sites
Mytilus
Mytilus
Mytilus
Mytilus
Mytilus
Mytilus
Mytilus
edulis
edulis
edulis
edulis
edulis
edulis
edulis
Crassostrea gigas
Crassostrea gigas
Crassostrea gigas
Crassostrea gigas
Crassostrea gigas
Crassostrea gigas
Mussel
Mussel
Mussel
Mussel
Mussel
Mussel
Mussel
Sanggou Bay, China
Oosterscheldt, Netherlands
Strangford Lough, N. Ireland
Carlingford Lough, N Ireland
Lough Foyle, N. Ireland
Belfast Lough, N. Ireland
Clew Bay, Ireland
3
11
11
7
5
7
9
SPEAR
KEYZONES
SMILE
SMILE
SMILE
SMILE
KEYZONES
Oyster
Oyster
Oyster
Oyster
Oyster
Oyster
Sanggou Bay China
Oosterscheldt, Netherlands
Strangford Lough, N. Ireland
Carlingford Lough, N Ireland
Clew Bay, Ireland
Loch Creran, Scotland
12
18
5
1
15
12
SPEAR
KEYZONES
SMILE
SMILE
KEYZONES
ECASA
2
2
3
6
3
5
6
SPEAR
ECASA
ECASA
SPEAR
SPEAR
SPEAR
SPEAR
Summary of species
and sites for which
ShellSIM has been
calibrated using
standardized protocols,
with accuracies of
simulated growth
ShellSIM calibrated per site
Chlamys farreri
M. galloprovincialis
Tapes philippinarum
Tapes philippinarum
Tegillarca granosa
Ostrea plicatula
Sinonvacula constricta
Scallop
Mussel
Clam
Clam
Cockle
Oyster
Clam
Sanggou Bay, China
Fangar Bay, Spain
Venice Lagoon, Italy
Huangdun Bay, China
Huangdun Bay, China
Huangdun Bay, China
Huangdun Bay, China
ShellSIM calibrated per site, with validation underway
Perna canaliculus
Perna viridis
Crassostrea belcheri
Crassostrea iradelei
Saccostrea cucculata
Pinctada margarifera
Mussel
Mussel
Oyster
Oyster
Oyster
Oyster
Marlborough, New Zealand
Merbok, Malaysia
Merbok, Malaysia
Merbok, Malaysia
Merbok, Malaysia
Merbok, Malaysia
-
NIWA
DARWIN
DARWIN
DARWIN
DARWIN
DARWIN
Calibration effected from:
¾1 to 29 oC
¾7 to 35 ppt
¾0.25 to 150 µg chlorophyll a l-1
¾0.5 to 500 mg TPM l-1
¾0 to 25% aerial exposure
*
current work
Using a single parameter
set, ShellSIM successfully
predicts growth measured as
shell length (mm) during
normal culture of Mytilus
edulis over between 8 and
24 months at all sites to date
Measured mm length
Mytilus edulis
60
r 2 = 0.87
a = 6.5 ± 4.6
b = 0.81 ± 0.11
50
40
30
20
20
30
40
50
60
Predicted mm length
Measured mm length
60
LOCATION
50
40
30
20
20
30
40
50
60
Predicted mm length
Belfast
Carlingford
Clew
Foyle
Pertuis
Scheldt
Strangford
x column 3 vs y column 3
Medulispredicted vs Medulismeasured
95% Confidence Band
95% Prediction Band
Measured g TFW
Using a single parameter
set, ShellSIM successfully
predicts growth measured
as total fresh weight (TFW,
g) during normal culture of
Crassostrea gigas over
between 8 and 24 months at
all sites to date
Crassostrea gigas
120
100
80
60
40
20
0
Measured g TFW
125
0
20
40
60
80
100
120
Predicted g TFW
x column vs y column
Cgigaspredicted vs Cgigasmeasured
95% Confidence Band
95% Prediction Band
100
LOCATION
75
50
25
0
0
r 2 = 0.97
a = -5.2 ± 4.2
b = 1.13 ± 0.08
25 50 75 100 125
Predicted g TFW
Carlingford
Clew
Creran
Sanggou
Scheldt
Strangford
Measured g TFW
Using a single parameter
set, ShellSIM successfully
predicts growth measured
as total fresh weight (TFW,
g) during normal culture of
Crassostrea gigas over
between 8 and 24 months at
all sites to date
Crassostrea gigas
120
100
80
60
40
20
0
Measured g TFW
125
0
20
40
60
80
100
120
Predicted g TFW
x column vs y column
Cgigaspredicted vs Cgigasmeasured
95% Confidence Band
95% Prediction Band
100
LOCATION
75
50
25
0
0
r 2 = 0.97
a = -5.2 ± 4.2
b = 1.13 ± 0.08
25 50 75 100 125
Predicted g TFW
Carlingford
Clew
Creran
Sanggou
Scheldt
Strangford
And
Andthis,
this,despite
despitevarying
varying
protocols
protocolsininthe
the
measurement
of
drivers
measurement of drivers
and
andgrowth
growth
Dynamic simulation of each physiological
component of net energy balance
F = Energy lost
C = Energy as faeces
E = Energy
ingested
excreted
(feeding rate)
R = Energy
expenditure
(heat loss)
NEB = Net energy
balance (deposited
as tissue)
Net energy balance = (Energy gains) - (Energy losses)
NEB = C - ( F + R + E)
Advantages of ShellSIM
¾Entirely functional common structure, based upon shared responses
that are similar within species at different sites
¾Easily calibrated using standardized procedures and minimal drivers
Adding relevant
ingredients
Standardised
measures
Standard protocols
Seston availability and composition
•TPM, PIM, POM, Chl a, POC (ECASA Book)
Feeding responses
•retention efficiency
•filtration rate
•rejection rate
•ingestion rate
•absorption efficiency
•absorption rate
Physiological measures for calibration within
ECASA according to species and/or site
Responses have been measured across full
natural ranges of food availability in:
¾Mytilus edulis and
Crassostrea gigas reared
in Loch Creran, Scotland
(Caledonian Oyster
Company, SAMSPartner 1) May 2006
¾Mytilus galloprovincialis
and Tapes decussatus in
Venice Lagoon (Veneto
Agricultura, ICRAMPartner 11, Univ VenicePartner 14) July 2006
Loch Creran May 2006
Venice Lagoon July 2006
ECASA, SMILE & KEYZONES feeding conditions
1.000
0.100
0.010
1
10
100
Total particulate matter (mg/l)
200
PHYORG
DETORG
150
0
1
10
100
Total particulate matter (mg/l)
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
0
100 200 300 400
Total particulate matter (mg/l)
LOCATION
100
50
Organic content (fraction)
10.000
Chlorophyll a (ug/l)
Organic matter (mg/l)
(10 individual M. edulis and C. gigas per condition = approx. 1500 measures per species)
EXPTCOND
MIXTURE
SILT
Carlingford
Clew
Creran
Foyle
Lynher
Scheldt
Strangford
Advantages of ShellSIM
¾Entirely functional common structure, based upon shared responses
that are similar within species at different sites
¾Easily calibrated using standardized procedures and minimal drivers
¾Differentiates the relative abundances, selection and energy
contents of phytoplankton and detrital organics
Mytilus edulis - Sanggou Bay, China
6
6
5
5
Shell length (cm)
Shell length (cm)
Mytilus edulis - Kijkuit, Netherlands
4
3
2
1
0
300
500
600
700
Shell length
2
1
800
100
Fraction of energy absorbed
Fraction of energy absorbed
3
0
400
1
0.75
0.5
0.25
0
300
4
200
300
400
500
600
1
0.75
0.5
Phyto
organics
0.25
Detrital
organics
0
400
500
600
Days
700
800
Phytoplankton
100
200
300
400
Days
500
600
Detritus
Advantages of ShellSIM
Particulateorganic
organicmatter
matter(mg/l)
(mg/l)
Particulate
¾Entirely functional common structure, based upon shared responses
that are similar within species at different sites
¾Easily calibrated using standardized procedures and minimal drivers
¾Differentiates the relative abundances, selection and energy
contents of phytoplankton and detrital organics
¾Corrects for historic errors in the measurement of food availability
16.0000
16.0000
14.0000
14.0000
Uncorrected
Uncorrected
12.0000
12.0000
10.0000
10.0000
Corrected
Correctedfor
forbound
bound
wwater
ater
8.0000
8.0000
6.0000
6.0000
Linear
Linear
(Uncorrected)
(Uncorrected)
4.0000
4.0000
2.0000
2.0000
0.0000
0.0000
0.0000
0.0000
Linear
Linear(Corrected
(Corrected
for
bound
for boundwwater)
ater)
50.0000
50.0000
100.0000
100.0000
Particulate
Particulateinorganic
inorganicmmatter
atter
(m
g/l)
(m g/l)
9Practicable
- requiring a minimum of drivers
9Robust and adaptable
- validated across seven species to date
- when optimised for given species across a range of
environments and culture practices, applying a single
standard set of parameters, simulates to < 20% error
- potential for (i) greater precision through site-specific
calibration, and (ii) calibration in further species
Validated from:
•1 to 29 oC
•7 to 35 ppt
•0.25 to 150 µg chlorophyll µ l-1
•0.5 to 500 mg TPM l-1
•0 to 25% aerial exposure
Validated for culture on/in:
•ropes
•trestles
•bottom
•posts
•lantern nets
ShellSIM delivery
i. WinShell workbench to run SHellSIM on Windows
desktop or Internet ExplorerTM
ShellSIM delivery
i. WinShell workbench to run SHellSIM on Windows
Farm-scale conceptual diagram
desktop or Internet ExplorerTM
Farm length
ii. Dynamic link library (DLL) called
by FORTRAN, C++ etc for
integration with other models
e.g. FARMTM, EcoWIN2000
Width
Current
Current
Shellfish
Chl a
Chl a
Depth 1
2
3
n-1
n
POM
POM
Sections
SHELLSIM Integration in EcoWin2000
Individual length and weight
BOX
4.7
Mussels
38
36
5.0
35
5.0
34
5.1
4.5
32
8.4
6.9
9.1
8.7
Length (cm)
11.0
35
0
Mussels
Length = 5 cm
Weight = 9.2 g
10.2
5
0
Oysters
9.9
5.2
5
24
9.7
4.7
33
31
8.4
10
(cm)
(g)
70
(cm)
(g)
67.2
57.6
Weight (g)
Oysters
Length = 9 cm
Weight = 62.4 g
ShellSIM applications
Up-scaling to the population, for integration with
other model components to assess animalenvironment relations at scales from farms to
systems, with typical applications that include
studying:
¾effects of environment on population dynamics
¾influences of shellfish upon ecological processes
and environmental status (i.e. water quality)
¾environmental carrying capacities for aquaculture
¾optimal practises in terms of species composition,
seeding times, densities, spatial distributions etc
100
20
30
40
10
6 0 10
90
70
40
80
60
10
30 20
50
80
70
40
900
8
20
50
40
70
20
20
20
30
50
30
10
70
40
10
7600
40
60
60
50
30
30
Integrations to date:
Bacher, C., Grant, J., Hawkins, A.J.S., Fang, J., Zhu, M., Besnard, M. (2003) Modelling the effect of food
depletion on scallop growth in Sungo Bay (China). Aquatic Living Resources, 16: 10-24.
Duarte, P., Meneses, R., Hawkins, A.J.S., Zhu, M., Fang, J., Grant, J. (2003) Mathematical modelling to
assess the carrying capacity for multi-species culture within coastal waters. Ecological Modelling,
168: 109-143.
Duarte, P., Hawkins, A. J. S., Pereira, A. (2005) How does estimation of environmental carrying
capacity for bivalve culture depend upon spatial and temporal scales? In: Dame, R. F. and Olenin, S.
(Editors), The comparative roles of suspension-feeders in aquatic systems. Springer, The
Netherlands. pp. 121-135.
Ferreira, J. G., Hawkins, A. J. S., Bricker, S. B. (In press) Management of productivity, environmental
effects and profitability of shellfish aquaculture - the Farm Aquaculture Resource Management
(FARM) model. Aquaculture
10
40
20
60
30
20
10
Current ShellSIM integrations
ShellSIM is currently being integrated with other physical,
biogeochemical and socio-economic components to help model
sustainable aquaculture within the following projects:
“ECASA” - EU STREP "Ecosystem Approach for Sustainable
Aquaculture"; 01/12/2004 to 30/10/2007; http://www.ecasa.org.uk
“SMILE” - AFBI "Sustainable mariculture in Northern Irish lough
ecosystems"; 01/10/2004 to 31/01/2007; http://www.ecowin.org/smile
“KEYZONES” - EU CRAFT "To investigate sustainable biological
carrying capacities of key European coastal zones"; 01/02/2005 to
01/02/2007; http://www.keyzones.com
“SPEAR” - EU INCO-DEV "Sustainable options for people,
catchment and aquatic resources"; 01/12/2004 to 31/11/2007;
http://www.biaoqiang.org
“UISCE” – IRISH SEA FISHERIES BOARD “Shellfish carrying
capacity”; 1/02/07 to 31/12/08;
http://www.bim.ie/uploads/reports/AquaCulture%20NewsLetter%20No%2058.pdf
ECASA collaborations
SAMS-Partner 1
Napier Univ.-Partner 3
PML-Partner 9
IMAR-Partner 10
Univ. Algarve-Partner 10
ICRAM-Partner 11
Univ. Venice-Partner 14
Caledonian Oyster Company
Veneto Agricultura
Dr A. J. S. (Tony) Hawkins,
Plymouth Marine Laboratory,
Prospect Place,
Plymouth PL13DH,
Devon,
United Kingdom.
Website: http://www.shellsim.com/index.html
Email: ajsh@pml.ac.uk
Phone: 00 44 (0)1752 633100
Ingestion rate (mg phyto-org/h/g)
Crassostrea gigas
Common responses in different environments
10.0000
LOCATION
Carlingford
Clew
Creran
Foyle
Lynher
Scheldt
Strangford
1.0000
0.1000
0.0100
0.0010
0
0
1
.0
0
0
0
.1
1
0
0
.0
Phytoplankton organics (mg/l)