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)