Optimum growth temperature declines with body size within fish species.

allometry body growth climate change consumption rate metabolic rate metabolic theory of ecology scaling temperature-size rule warming

Journal

Global change biology
ISSN: 1365-2486
Titre abrégé: Glob Chang Biol
Pays: England
ID NLM: 9888746

Informations de publication

Date de publication:
Apr 2022
Historique:
revised: 18 11 2021
received: 05 08 2021
accepted: 12 12 2021
pubmed: 22 1 2022
medline: 14 4 2022
entrez: 21 1 2022
Statut: ppublish

Résumé

According to the temperature-size rule, warming of aquatic ecosystems is generally predicted to increase individual growth rates but reduce asymptotic body sizes of ectotherms. However, we lack a comprehensive understanding of how growth and key processes affecting it, such as consumption and metabolism, depend on both temperature and body mass within species. This limits our ability to inform growth models, link experimental data to observed growth patterns, and advance mechanistic food web models. To examine the combined effects of body size and temperature on individual growth, as well as the link between maximum consumption, metabolism, and body growth, we conducted a systematic review and compiled experimental data on fishes from 52 studies that combined body mass and temperature treatments. By fitting hierarchical models accounting for variation between species, we estimated how maximum consumption and metabolic rate scale jointly with temperature and body mass within species. We found that whole-organism maximum consumption increases more slowly with body mass than metabolism, and is unimodal over the full temperature range, which leads to the prediction that optimum growth temperatures decline with body size. Using an independent dataset, we confirmed this negative relationship between optimum growth temperature and body size. Small individuals of a given population may, therefore, exhibit increased growth with initial warming, whereas larger conspecifics could be the first to experience negative impacts of warming on growth. These findings help advance mechanistic models of individual growth and food web dynamics and improve our understanding of how climate warming affects the growth and size structure of aquatic ectotherms.

Identifiants

pubmed: 35060649
doi: 10.1111/gcb.16067
doi:

Types de publication

Journal Article Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

2259-2271

Subventions

Organisme : Svenska Forskningsrådet Formas
ID : 217-2013-1315
Organisme : Vetenskapsrådet
ID : 2015-03752

Informations de copyright

© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

Références

Andersen, K. H., Beyer, J. E., & Lundberg, P. (2009). Trophic and individual efficiencies of size-structured communities. Proceedings of the Royal Society B: Biological Sciences, 276(1654), 109-114. https://doi.org/10.1098/rspb.2008.0951
Angilletta, M. J., & Dunham, A. E. (2003). The temperature-size rule in ectotherms: Simple evolutionary explanations may not be general. The American Naturalist, 162, 332-342. https://doi.org/10.1086/377187
Armstrong, J. D., & Hawkins, L. A. (2008). Standard metabolic rate of pike, Esox lucius: Variation among studies and implications for energy flow modelling. Hydrobiologia, 601(1), 83-90. https://doi.org/10.1007/s10750-007-9268-x
Atkinson, D. (1994). Temperature and organism size-A biological law for ectotherms? Advances in Ecological Research, 25, 1-58. https://doi.org/10.1016/S0065-2504(08)60212-3
Audzijonyte, A., Barneche, D. R., Baudron, A. R., Belmaker, J., Clark, T. D., Marshall, C. T., Morrongiello, J. R., & van Rijn, I. (2019). Is oxygen limitation in warming waters a valid mechanism to explain decreased body sizes in aquatic ectotherms? Global Ecology and Biogeography, 28(2), 64-77. https://doi.org/10.1111/geb.12847
Audzijonyte, A., & Pecl, G. T. (2018). Deep impact of fisheries. Nature Ecology & Evolution, 2(9), 1348-1349. https://doi.org/10.1038/s41559-018-0653-9
Audzijonyte, A., Richards, S. A., Stuart-Smith, R. D., Pecl, G., Edgar, G. J., Barrett, N. S., Payne, N., & Blanchard, J. L. (2020). Fish body sizes change with temperature but not all species shrink with warming. Nature Ecology & Evolution, 4, 809-814. https://doi.org/10.1038/s41559-020-1171-0
Barneche, D. R., & Allen, A. P. (2018). The energetics of fish growth and how it constrains food-web trophic structure. Ecology Letters, 21(6), 836-844. https://doi.org/10.1111/ele.12947
Barneche, D. R., Jahn, M., & Seebacher, F. (2019). Warming increases the cost of growth in a model vertebrate. Functional Ecology, 33(7), 1256-1266. https://doi.org/10.1111/1365-2435.13348
Barneche, D. R., Robertson, D. R., White, C. R., & Marshall, D. J. (2018). Fish reproductive-energy output increases disproportionately with body size. Science, 360(6389), 642-645. https://doi.org/10.1126/science.aao6868
Baudron, A. R., Needle, C. L., Rijnsdorp, A. D., & Marshall, C. T. (2014). Warming temperatures and smaller body sizes: Synchronous changes in growth of North Sea fishes. Global Change Biology, 20(4), 1023-1031. https://doi.org/10.1111/gcb.12514
Beamish, F. W. H. (1964). Respiration of fishes with special emphasis on standard oxygen consumption II. Influence of weight and temperature on respiration of several species’. Canadian Journal of Zoology/Revue Canadienne De Zoologie, 42(2), 177-188. https://doi.org/10.1139/z64-016
Björnsson, B., Steinarsson, A., & Árnason, T. (2007). Growth model for Atlantic cod (Gadus morhua): Effects of temperature and body weight on growth rate. Aquaculture, 271(1-4), 216-226. https://doi.org/10.1016/j.aquaculture.2007.06.026
Blanchard, J. L., Heneghan, R. F., Everett, J. D., Trebilco, R., & Richardson, A. J. (2017). From bacteria to whales: Using functional size spectra to model marine ecosystems. Trends in Ecology & Evolution, 32(3), 174-186. https://doi.org/10.1016/j.tree.2016.12.003
Bokma, F. (2004). Evidence against universal metabolic allometry. Functional Ecology, 18(2), 184-187. https://doi.org/10.1111/j.0269-8463.2004.00817.x
Brett, J. R. (1971). Energetic responses of salmon to temperature. A study of some thermal relations in the physiology and freshwater ecology of sockeye salmon (Oncorhynchus nerka). Integrative and Comparative Biology, 11(1), 99-113. https://doi.org/10.1093/icb/11.1.99
Brett, J. R., Shelbourn, J. E., & Shoop, C. T. (1969). Growth rate and body composition of fingerling sockeye salmon, Oncorhynchus nerka, in relation to temperature and ration size. Journal of the Fisheries Research Board of Canada, 26(9), 2363-2394. https://doi.org/10.1139/f69-230
Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M., & West, G. B. (2004). Toward a metabolic theory of ecology. Ecology, 85(7), 1771-1789. https://doi.org/10.1890/03-9000
Cheung, W. W. L., Sarmiento, J. L., Dunne, J., Frölicher, T. L., Lam, V. W. Y., Deng Palomares, M. L., Watson, R., & Pauly, D. (2013). Shrinking of fishes exacerbates impacts of global ocean changes on marine ecosystems. Nature Climate Change, 3(3), 254-258. https://doi.org/10.1038/nclimate1691
Clarke, A., & Johnston, N. M. (1999). Scaling of metabolic rate with body mass and temperature in teleost fish. Journal of Animal Ecology, 68, 893-905. https://doi.org/10.1046/j.1365-2656.1999.00337.x
Cuenco, M. L., Stickney, R. R., & Grant, W. E. (1985). Fish bioenergetics and growth in aquaculture ponds: I. Individual fish model development. Ecological Modelling, 27(3), 169-190. https://doi.org/10.1016/0304-3800(85)90001-8
Daufresne, M., Lengfellner, K., & Sommer, U. (2009). Global warming benefits the small in aquatic ecosystems. Proceedings of the National Academy of Sciences of the United States of America, 106(31), 12788-12793. https://doi.org/10.1073/pnas.0902080106
de Roos, A. M., & Persson, L. (2001). Physiologically structured models - from versatile technique to ecological theory. Oikos, 94(1), 51-71. https://doi.org/10.1034/j.1600-0706.2001.11313.x
Dell, A. I., Pawar, S., & Savage, V. M. (2011). Systematic variation in the temperature dependence of physiological and ecological traits. Proceedings of the National Academy of Sciences of the United States of America, 108(26), 10591-10596. https://doi.org/10.1073/pnas.1015178108
Downs, C. J., Hayes, J. P., & Tracy, C. R. (2008). Scaling metabolic rate with body mass and inverse body temperature: A test of the Arrhenius fractal supply model. Functional Ecology, 22(2), 239-244. https://doi.org/10.1111/j.1365-2435.2007.01371.x
Elliott, J. M., & Hurley, M. A. (1995). The functional relationship between body size and growth rate in fish. Functional Ecology, 9(4), 625. https://doi.org/10.2307/2390153
Englund, G., Öhlund, G., Hein, C. L., & Diehl, S. (2011). Temperature dependence of the functional response. Ecology Letters, 14(9), 914-921. https://doi.org/10.1111/j.1461-0248.2011.01661.x
Essington, T. E., Kitchell, J. F., & Walters, C. J. (2001). The von Bertalanffy growth function, bioenergetics, and the consumption rates of fish. Canadian Journal of Fisheries and Aquatic Sciences, 58(11), 2129-2138. https://doi.org/10.1139/cjfas-58-11-2129
Fernández-i-Marín, X. (2016). ggmcmc: Analysis of MCMC samples and Bayesian inference. Journal of Statistical Software, 70(1), 1-20. https://doi.org/10.18637/jss.v070.i09
Forster, J., Hirst, A. G., & Atkinson, D. (2012). Warming-induced reductions in body size are greater in aquatic than terrestrial species. Proceedings of the National Academy of Sciences of the United States of America, 109(47), 19310-19314. https://doi.org/10.1073/pnas.1210460109
Froese, R., & Pauly, D. (Eds.). (2019). FishBase. World Wide Web Electronic Publication. Retrieved from www.fishbase.org
Fussmann, K. E., Schwarzmüller, F., Brose, U., Jousset, A., & Rall, B. C. (2014). Ecological stability in response to warming. Nature Climate Change, 4(3), 206-210. https://doi.org/10.1038/nclimate2134
Gabry, J., Simpson, D., Vehtari, A., Betancourt, M., & Gelman, A. (2019). Visualization in Bayesian workflow. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(2), 389-402. https://doi.org/10.1111/rssa.12378
García García, B., Cerezo Valverde, J., Aguado-Giménez, F., García García, J., & Hernández, M. D. (2011). Effect of the interaction between body weight and temperature on growth and maximum daily food intake in sharpsnout sea bream (Diplodus puntazzo). Aquaculture International, 19(1), 131-141. https://doi.org/10.1007/s10499-010-9347-2
Gardner, J. L., Peters, A., Kearney, M. R., Joseph, L., & Heinsohn, R. (2011). Declining body size: A third universal response to warming? Trends in Ecology & Evolution, 26(6), 285-291. https://doi.org/10.1016/j.tree.2011.03.005
Gelman, A., Carlin, J., Stern, H., & Rubin, D. (2003). Bayesian data analysis (2nd ed). Chapman and Hall/CRC.
Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.
Gilbert, B., Tunney, T. D., McCann, K. S., DeLong, J. P., Vasseur, D. A., Savage, V. M., Shurin, J. B., Dell, A. I., Barton, B. T., Harley, C. D., Kharouba, H. M., Kratina, P., Blanchard, J. L., Clements, C., Winder, M., Greig, H. S., & O’Connor, M. I. (2014). A bioenergetic framework for the temperature dependence of trophic interactions. Ecology Letters, 17(8), 902-914. https://doi.org/10.1111/ele.12307
Gillooly, J. F., Brown, J. H., West, G. B., Savage, V. M., & Charnov, E. L. (2001). Effects of size and temperature on metabolic rate. Science, 293(5538), 2248-2251. https://doi.org/10.1126/science.1061967
Glazier, D. S. (2005). Beyond the “3/4-power law”: Variation in the intra- and interspecific scaling of metabolic rate in animals. Biological Reviews of the Cambridge Philosophical Society, 80(4), 611-662. https://doi.org/10.1017/S1464793105006834
Handeland, S. O., Imsland, A. K., & Stefansson, S. O. (2008). The effect of temperature and fish size on growth, feed intake, food conversion efficiency and stomach evacuation rate of Atlantic salmon post-smolts. Aquaculture, 283(1), 36-42. https://doi.org/10.1016/j.aquaculture.2008.06.042
Harrison, X. A., Donaldson, L., Correa-Cano, M. E., Evans, J., Fisher, D. N., Goodwin, C. E. D., Robinson, B. S., Hodgson, D. J., & Inger, R. (2018). A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ, 6, e4794. https://doi.org/10.7717/peerj.4794
Hartvig, M., Andersen, K. H., & Beyer, J. E. (2011). Food web framework for size-structured populations. Journal of Theoretical Biology, 272(1), 113-122. https://doi.org/10.1016/j.jtbi.2010.12.006
Heincke, F. (1913). Rapports et procès-verbaux des reunions. Conseil International pour l'Exploration de la Mer, 16, 1-70.
Hepher, B. (1988). Nutrition of pond fishes. Cambridge University Press.
Horne, C. R., Hirst, A. G., & Atkinson, D. (2015). Temperature-size responses match latitudinal-size clines in arthropods, revealing critical differences between aquatic and terrestrial species. Ecology Letters, 18(4), 327-335. https://doi.org/10.1111/ele.12413
Huey, R. B., & Kingsolver, J. G. (2019). Climate warming, resource availability, and the metabolic meltdown of ectotherms. The American Naturalist, 194(6), E140-E150. https://doi.org/10.1086/705679
Huss, M., Lindmark, M., Jacobson, P., van Dorst, R. M., & Gårdmark, A. (2019). Experimental evidence of gradual size-dependent shifts in body size and growth of fish in response to warming. Global Change Biology, 25(7), 2285-2295. https://doi.org/10.1111/gcb.14637
Ikpewe, I. E., Baudron, A. R., Ponchon, A., & Fernandes, P. G. (2020). Bigger juveniles and smaller adults: Changes in fish size correlate with warming seas. Journal of Applied Ecology, 58(4), 847-856. https://doi.org/10.1111/1365-2664.13807
Jerde, C. L., Kraskura, K., Eliason, E. J., Csik, S. R., Stier, A. C., & Taper, M. L. (2019). Strong evidence for an intraspecific metabolic scaling coefficient near 0.89 in fish. Frontiers in Physiology, 10, 1166. https://doi.org/10.3389/fphys.2019.01166
Jobling, M. (1997). Temperature and growth: Modulation of growth rate via temperature change. In C. M. Wood, & D. G. McDonald (Eds.), Global warming: Implications for freshwater and marine fish, Vol. 61 (pp. 225-254). Cambridge University Press.
Kitchell, J. F., Stewart, D. J., & Weininger, D. (1977). Applications of a bioenergetics model to yellow perch (Perca flavescens) and walleye (Stizostedion vitreum vitreum). Journal of the Fisheries Board of Canada, 34(10), 1922-1935.
Kooijman, S. A. L. M. (1993). Dynamic energy budgets in biological systems. Cambridge University Press.
Lefevre, S., McKenzie, D. J., & Nilsson, G. E. (2018). In modelling effects of global warming, invalid assumptions lead to unrealistic projections. Global Change Biology, 24(2), 553-556. https://doi.org/10.1111/gcb.13978
Lemoine, N. P., & Burkepile, D. E. (2012). Temperature-induced mismatches between consumption and metabolism reduce consumer fitness. Ecology, 93(11), 2483-2489. https://doi.org/10.1890/12-0375.1
Lindmark, M., Huss, M., Ohlberger, J., & Gårdmark, A. (2018). Temperature-dependent body size effects determine population responses to climate warming. Ecology Letters, 21(2), 181-189. https://doi.org/10.1111/ele.12880
Lindmark, M., Ohlberger, J., Huss, M., & Gårdmark, A. (2019). Size-based ecological interactions drive food web responses to climate warming. Ecology Letters, 22(5), 778-786. https://doi.org/10.1111/ele.13235
Lloret-Lloret, E., Navarro, J., Giménez, J., López, N., Albo-Puigserver, M., Pennino, M. G., & Coll, M. (2020). The seasonal distribution of a highly commercial fish is related to ontogenetic changes in its feeding strategy. Frontiers in Marine Science, 7. https://doi.org/10.3389/fmars.2020.566686
Lorenzen, K. (1996). The relationship between body weight and natural mortality in juvenile and adult fish: A comparison of natural ecosystems and aquaculture. Journal of Fish Biology, 49(4), 627-642. https://doi.org/10.1111/j.1095-8649.1996.tb00060.x
Marshall, D. J., & White, C. R. (2019). Have we outgrown the existing models of growth? Trends in Ecology & Evolution, 34(2), 102-111. https://doi.org/10.1016/j.tree.2018.10.005
Maury, O., & Poggiale, J.-C. (2013). From individuals to populations to communities: A dynamic energy budget model of marine ecosystem size-spectrum including life history diversity. Journal of Theoretical Biology, 324, 52-71. https://doi.org/10.1016/j.jtbi.2013.01.018
Messmer, V., Pratchett, M. S., Hoey, A. S., Tobin, A. J., Coker, D. J., Cooke, S. J., & Clark, T. D. (2017). Global warming may disproportionately affect larger adults in a predatory coral reef fish. Global Change Biology, 23(6), 2230-2240. https://doi.org/10.1111/gcb.13552
Morita, K., Fukuwaka, M., Tanimata, N., & Yamamura, O. (2010). Size-dependent thermal preferences in a pelagic fish. Oikos, 119(8), 1265-1272. https://doi.org/10.1111/j.1600-0706.2009.18125.x
Nelson, J. A. (2016). Oxygen consumption rate v. rate of energy utilization of fishes: A comparison and brief history of the two measurements. Journal of Fish Biology, 88(1), 10-25. https://doi.org/10.1111/jfb.12824
Neubauer, P., & Andersen, K. H. (2019). Thermal performance of fish is explained by an interplay between physiology, behaviour and ecology. Conservation. Physiology, 7(1). https://doi.org/10.1093/conphys/coz025
Neuenfeldt, S., Bartolino, V., Orio, A., Andersen, K. H., Andersen, N. G., Niiranen, S., Bergström, U., Ustups, D., Kulatska, N., & Casini, M. (2020). Feeding and growth of Atlantic cod (Gadus morhua L.) in the eastern Baltic Sea under environmental change. ICES Journal of Marine Science, 77(2), 624-632. https://doi.org/10.1093/icesjms/fsz224
Neuheimer, A. B., Thresher, R. E., Lyle, J. M., & Semmens, J. M. (2011). Tolerance limit for fish growth exceeded by warming waters. Nature Climate Change, 1(2), 110-113. https://doi.org/10.1038/nclimate1084
Ohlberger, J. (2013). Climate warming and ectotherm body size - from individual physiology to community ecology. Functional Ecology, 27(4), 991-1001. https://doi.org/10.1111/1365-2435.12098
Ohlberger, J., Edeline, E., Vollestad, L. A., Stenseth, N. C., & Claessen, D. (2011). Temperature-driven regime shifts in the dynamics of size-structured populations. The American Naturalist, 177(2), 211-223. https://doi.org/10.1086/657925
Ohlberger, J., Mehner, T., Staaks, G., & Hölker, F. (2012). Intraspecific temperature dependence of the scaling of metabolic rate with body mass in fishes and its ecological implications. Oikos, 121(2), 245-251. https://doi.org/10.1111/j.1600-0706.2011.19882.x
Ohlberger, J., Staaks, G., & Hölker, F. (2007). Effects of temperature, swimming speed and body mass on standard and active metabolic rate in vendace (Coregonus albula). Journal of Comparative Physiology, B, 177(8), 905-916. https://doi.org/10.1007/s00360-007-0189-9
Olmos, M., Payne, M. R., Nevoux, M., Prévost, E., Chaput, G., Pontavice, H. D., Guitton, J., Sheehan, T., Mills, K., & Rivot, E. (2019). Spatial synchrony in the response of a long range migratory species (Salmo salar) to climate change in the North Atlantic Ocean. Global Change Biology, 26(3), 1319-1337. https://doi.org/10.1111/gcb.14913
Padfield, D., Castledine, M., & Buckling, A. (2020). Temperature-dependent changes to host-parasite interactions alter the thermal performance of a bacterial host. The ISME Journal, 14(2), 389-398. https://doi.org/10.1038/s41396-019-0526-5
Padfield, D., Lowe, C., Buckling, A., Ffrench-Constant, R., Jennings, S., Shelley, F., Ólafsson, J. S., & Yvon-Durocher, G. (2017). Metabolic compensation constrains the temperature dependence of gross primary production. Ecology Letters, 20(10), 1250-1260. https://doi.org/10.1111/ele.12820
Padfield, D., & Matheson, G. (2020). nls.multstart: Robust non-linear regression using AIC scores (R package version 1.2.0.) [Computer software]. https://CRAN.R-project.org/package=nls.multstart
Padfield, D., & O’Sullivan, H. (2020). RTPC: Functions for fitting thermal performance curves (R package version 1.0.0.) [Computer software]. https://github.com/padpadpadpad/rTPC
Panov, V. E., & McQueen, D. J. (1998). Effects of temperature on individual growth rate and body size of a freshwater amphipod. Canadian Journal of Zoology, 76(6), 1107-1116. https://doi.org/10.1139/z98-025
Pauly, D. (2021). The gill-oxygen limitation theory (GOLT) and its critics. Science Advances, 7(2). eabc6050. https://doi.org/10.1126/sciadv.abc6050
Pauly, D., & Cheung, W. W. L. (2018a). Sound physiological knowledge and principles in modeling shrinking of fishes under climate change. Global Change Biology, 24(1), e15-e26. https://doi.org/10.1111/gcb.13831
Pauly, D., & Cheung, W. W. L. (2018b). On confusing cause and effect in the oxygen limitation of fish. Global Change Biology, 24(11), e743-e744. https://doi.org/10.1111/gcb.14383
Pawar, S., Dell, A. I., & Savage, V. M. (2012). Dimensionality of consumer search space drives trophic interaction strengths. Nature, 486(7404), 485-489. https://doi.org/10.1038/nature11131
Pawar, S., Dell, A. I., Savage, V. M., & Knies, J. L. (2016). Real versus artificial variation in the thermal sensitivity of biological traits. The American Naturalist, 187(2), E41-E52. https://doi.org/10.1086/684590
Peralta-Maraver, I., & Rezende, E. L. (2021). Heat tolerance in ectotherms scales predictably with body size. Nature Climate Change, 11(1), 58-63. https://doi.org/10.1038/s41558-020-00938-y
Perrin, N. (1995). About Berrigan and Charnov’s life-history puzzle. Oikos, 73(1), 137-139. https://doi.org/10.2307/3545737
Plummer, M. (2003). JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. Working Papers, 8.
Plummer, M. (2019). Rjags (R package version 4-10) [Computer software]. https://CRAN.R-project.org/package=rjags
Pörtner, H. O., & Knust, R. (2007). Climate change affects marine fishes through the oxygen limitation of thermal tolerance. Science, 315(5808), 95-97.
Pütter, A. (1920). Studien über physiologische Ähnlichkeit VI. Wachstumsähnlichkeiten. Pflügers Archiv Für Die Gesamte Physiologie Des Menschen Und Der Tiere, 180(1), 298-340. https://doi.org/10.1007/BF01755094
R Core Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Rall, B. C., Brose, U., Hartvig, M., Kalinkat, G., Schwarzmuller, F., Vucic-Pestic, O., & Petchey, O. L. (2012). Universal temperature and body-mass scaling of feeding rates. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 367(1605), 2923-2934. https://doi.org/10.1098/rstb.2012.0242
Rall, B. C., Vucic-Pestic, O., Ehnes, R. B., Emmerson, M., & Brose, U. (2010). Temperature, predator-prey interaction strength and population stability. Global Change Biology, 16(8), 2145-2157. https://doi.org/10.1111/j.1365-2486.2009.02124.x
Rijnsdorp, A. D., & Ibelings, B. (1989). Sexual dimorphism in the energetics of reproduction and growth of North Sea plaice, Pleuronectes platessa L. Journal of Fish Biology, 35(3), 401-415. https://doi.org/10.1111/j.1095-8649.1989.tb02992.x
Rohatgi, A. (2012). WebPlotDigitalizer: HTML5 based online tool to extract numerical data from plot images. Version 4.1. [WWW document]. https://automeris.io/WebPlotDigitizer
Savage, V. M., Gillooly, J. F., Brown, J. H., West, G. B., & Charnov, E. L. (2004). Effects of body size and temperature on population growth. The American Naturalist, 163(3), 429-441. https://doi.org/10.1086/381872
Schielzeth, H. (2010). Simple means to improve the interpretability of regression coefficients: Interpretation of regression coefficients. Methods in Ecology and Evolution, 1(2), 103-113. https://doi.org/10.1111/j.2041-210X.2010.00012.x
Schoolfield, R. M., Sharpe, P. J. H., & Magnuson, C. E. (1981). Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory. Journal of Theoretical Biology, 88(4), 719-731. https://doi.org/10.1016/0022-5193(81)90246-0
Steinarsson, A., & Imsland, A. K. (2003). Size dependent variation in optimum growth temperature of red abalone (Haliotis rufescens). Aquaculture, 224(1-4), 353-362. https://doi.org/10.1016/S0044-8486(03)00241-2
Thresher, R. E., Koslow, J. A., Morison, A. K., & Smith, D. C. (2007). Depth-mediated reversal of the effects of climate change on long-term growth rates of exploited marine fish. Proceedings of the National Academy of Sciences of the United States of America, 104(18), 7461-7465. https://doi.org/10.1073/pnas.0610546104
Uiterwaal, S. F., & DeLong, J. P. (2020). Functional responses are maximized at intermediate temperatures. Ecology, 101(4), e02975. https://doi.org/10.1002/ecy.2975
Ursin, E. (1967). A mathematical model of some aspects of fish growth, respiration, and mortality. Journal of the Fisheries Research Board of Canada, 24(11), 2355-2453. https://doi.org/10.1139/f67-190
van Denderen, D., Gislason, H., van den Heuvel, J., & Andersen, K. H. (2020). Global analysis of fish growth rates shows weaker responses to temperature than metabolic predictions. Global Ecology and Biogeography, 29(12), 2203-2213. https://doi.org/10.1111/geb.13189
van Dorst, R. M., Gårdmark, A., Svanbäck, R., Beier, U., Weyhenmeyer, G. A., & Huss, M. (2019). Warmer and browner waters decrease fish biomass production. Global Change Biology, 25(4), 1395-1408. https://doi.org/10.1111/gcb.14551
van Rijn, I., Buba, Y., DeLong, J., Kiflawi, M., & Belmaker, J. (2017). Large but uneven reduction in fish size across species in relation to changing sea temperatures. Global Change Biology, 23(9), 3667-3674. https://doi.org/10.1111/gcb.13688
Vasseur, D. A., & McCann, K. S. (2005). A mechanistic approach for modelling temperature-dependent consumer-resource dynamics. The American Naturalist, 166(2), 184-198.
Vehtari, A., Gelman, A., & Gabry, J. (2017). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Statistics and Computing, 27(5), 1413-1432. https://doi.org/10.1007/s11222-016-9696-4
von Bertalanffy, L. (1957). Laws in metabolism and growth. The Quarterly Review of Biology, 32(3), 217-231.
Wang, H.-Y., Shen, S.-F., Chen, Y.-S., Kiang, Y.-K., & Heino, M. (2020). Life histories determine divergent population trends for fishes under climate warming. Nature Communications, 11(1), 4088. https://doi.org/10.1038/s41467-020-17937-4
Watanabe, S. (2013). A widely applicable Bayesian information criterion. Journal of Machine Learning Research, 14, 867-897.
Werner, E. E., & Hall, D. J. (1988). Ontogenetic habitat shifts in bluegill: The foraging rate-predation risk trade-off. Ecology, 69(5), 1352-1366. https://doi.org/10.2307/1941633
Wickham, H., Averick, M., Bryan, J., Chang, W., D’Agostino McGowan, L., François, R., Grolemund, G., & Alex, H. (2019). Welcome to the Tidyverse. Journal of Open Source Software, 4(43), 1686-https://doi.org/10.21105/joss.01686
Wyban, J., Walsh, W. A., & Godin, D. M. (1995). Temperature effects on growth, feeding rate and feed conversion of the Pacific white shrimp (Penaeus vannamei). Aquaculture, 138(1), 267-279. https://doi.org/10.1016/0044-8486(95)00032-1
Xie, X., & Sun, R. (1990). The bioenergetics of the southern catfish (Silurus meridionalis Chen). I. Resting metabolic rate as a function of body weight and temperature. Physiological Zoology, 63(6), 1181-1195.
Youngflesh, C. (2018). MCMCvis: Tools to visualize, manipulate, and summarize MCMC output. Journal of Open Source Software, 3(24), 640. https://doi.org/10.21105/joss.00640

Auteurs

Max Lindmark (M)

Department of Aquatic Resources, Institute of Coastal Research, Swedish University of Agricultural Sciences, Öregrund, Sweden.

Jan Ohlberger (J)

School of Aquatic and Fishery Sciences (SAFS), University of Washington, Seattle, Washington, USA.

Anna Gårdmark (A)

Department of Aquatic Resources, Swedish University of Agricultural Sciences, Öregrund, Sweden.

Articles similaires

Robotic Surgical Procedures Animals Humans Telemedicine Models, Animal

Odour generalisation and detection dog training.

Lyn Caldicott, Thomas W Pike, Helen E Zulch et al.
1.00
Animals Odorants Dogs Generalization, Psychological Smell
Animals TOR Serine-Threonine Kinases Colorectal Neoplasms Colitis Mice
Animals Tail Swine Behavior, Animal Animal Husbandry

Classifications MeSH