A new study suggests that human induced climate change is not only increasing ocean temperatures but is also decreasing the amount of oxygen. The decrease in oxygen will likely shrink the average size of fish.
From the Journal Nature:
Shrinking of fishes exacerbates impacts of global ocean changes on marine ecosystems
by William W. L. Cheung, Jorge L. Sarmiento, John Dunne, Thomas L. Frölicher, Vicky W. Y. Lam, M. L. Deng Palomares, Reg Watson and Daniel Pauly
Changes in temperature, oxygen content and other ocean biogeochemical properties directly affect the ecophysiology of marine water-breathing organisms1, 2, 3. Previous studies suggest that the most prominent biological responses are changes in distribution4, 5, 6, phenology7, 8 and productivity9. Both theory and empirical observations also support the hypothesis that warming and reduced oxygen will reduce body size of marine fishes10, 11, 12. However, the extent to which such changes would exacerbate the impacts of climate and ocean changes on global marine ecosystems remains unexplored. Here, we employ a model to examine the integrated biological responses of over 600 species of marine fishes due to changes in distribution, abundance and body size. The model has an explicit representation of ecophysiology, dispersal, distribution, and population dynamics3. We show that assemblage-averaged maximum body weight is expected to shrink by 14–24% globally from 2000 to 2050 under a high-emission scenario. About half of this shrinkage is due to change in distribution and abundance, the remainder to changes in physiology. The tropical and intermediate latitudinal areas will be heavily impacted, with an average reduction of more than 20%. Our results provide a new dimension to understanding the integrated impacts of climate change on marine ecosystems.
Global climate and ocean changes resulting from anthropogenic greenhouse-gas emissions are currently affecting and expected to continue to affect marine organisms1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11. These impacts are fundamentally linked to the close relationship between ocean conditions and the ecophysiology of marine organisms, notably water-breathing ectotherms1, 2, 13. However, previous studies focus largely on the implication of thermal tolerance and limitations of other environmental factors for the distribution range of these organisms4, 5, 6. Few studies have assessed the integrated responses of changes in ecophysiology, distribution and their effects on key characteristics of marine biota such as body size.
The size of aquatic water-breathers is strongly affected by temperature, oxygen level and other factors such as resource availability2, 14. Specifically, the maximum body weight ( ) of marine fishes and invertebrates is fundamentally limited by the balance between energy demand and supply, where is reached when energy demand?=?energy supply (thus net growth?=?0). This can be expressed by the function that is commonly used to describe growth of fishes 15:
where dW/dt is growth in body weight, H and k are the coefficients for anabolism and catabolism, respectively, and a describes the allometric scaling of energy input. A growth function is obtained by integrating equation (1):
where Wt and are weight at age t and asymptotic weight, respectively; K is the growth parameter that represents the rate of approaching through growth.
Oxygen is one of the key ingredients for body growth. Ample theoretical and empirical evidence suggests that the capacity for growth is limited by oxygen in aquatic water-breathing ectotherms and oxygen-limitation is one of the fundamental mechanisms determining biological responses of fish to environmental changes, from cellular to organismal levels1, 2. Assuming that other resources for growth are constant, the anabolic term can be expressed as a function of oxygen supply. The catabolic term represents only the pre-oxidative phase of the breakdown of body materials. This phase mainly involves structural loss and hydrolization of protein without coupling with energy-providing exergonic reactions (see ref. 2 for details). The subsequent oxidative phase, which is included in the first term of equation (1), involves break-down of amino acids, is exergonic and requires oxygen. Applying equation (1) and previously estimated growth parameters, ocean conditions and published metabolic parameters of fishes, we calculated and K of marine fishes under scenarios of future water temperature and oxygen level (see Methods and Supplementary Information). We also examine the sensitivity of the calculated values to the key parameters on the model (Supplementary Information).
We accounted for the effects of species distribution shifts in mediating the ecophysiological responses of individual marine fishes to environmental changes and their linkages to community-level changes (Fig. 1). Marine fishes are observed and projected to shift their distributions and abundance as temperature, primary productivity and other ocean conditions change3, 4, 5, 6, 9, 16. These will mediate the effects of such changes on the metabolism and body weight of the organisms. Here, we modelled the integrated changes in ecophysiology and distribution of 610 species of exploited marine demersal fishes around the world using the Dynamic Bioclimate Envelope model (DBEM; see Supplementary Information and ref. 3). DBEM simulates changes in the relative abundance and spatial distribution of the marine population on a global grid by accounting for the organisms’ ecophysiology, preferences and tolerances to environmental conditions, adult movement and larval dispersal, and population dynamics. Applying the model to simulate historical (1959–2004) changes in species distributions and comparing the results with available observations on range and abundance shifts (in the Bering Sea and around the UK) show that results from DBEM agree significantly (P<0.01) with these observations (Supplementary Fig. S3). This provides empirical support that the DBEM has skill in predicting shifts in distribution range and changes in community structure under changes in oceanographic conditions.
We calculated changes in individual- and community-level average (geometric mean) maximum body weight of fishes in the global ocean driven by predicted physical and chemical conditions from two IPCC-class earth system models: NOAA’s GFDL ESM 2.1 and IPSL-CM4-LOOP under the SRES A2 scenario (Fig. 1, see Supplementary Information). We then calculated the changes in average maximum body weight for individual fish in a population and for fish assemblage from year 2000 (average from 1991 to 2010) to 2050 (average from 2041 to 2060; see Methods).
Overall, the ocean is projected to become warmer and less oxygenated under the SRES A2 scenario17. Because demersal fishes spend most of their time near the bottom layers of the ocean, sea bottom temperature and oxygen content are more representative of the environmental conditions that demersal fishes experience. Averaged across the two earth system models, sea bottom temperature in the large marine ecosystems in the Pacific, Atlantic, Indian, Southern and Arctic oceans are projected to increase at average rates of 0.029, 0.012, 0.017, 0.038 and 0.037?°C?decade?1 respectively between 2000 and 2050, whereas oxygen content is predicted to decrease at average rates of 0.8, 1.1, 0.9, 0.9 and 0.1?mmol?m?3?decade?1 (Fig. 1 and Supplementary Fig. S5).
Although the projected rate of change in environmental temperature and oxygen content seems to be small, the resulting changes in maximum body size are unexpectedly large (Fig. 2). This study predicts that the current (1991–2010) assemblage-averaged is smallest in the tropics and approximately five and two times larger in the northern and southern temperate regions, respectively (Fig. 2a). Overall, assemblage-averaged is projected to decrease by 14–24% from 2001 to 2050 (20-year average) or 2.8–4.8%?decade?1 (Fig. 2b). The projected decrease is largest in the Indian Ocean (24%), followed by the Atlantic Ocean (20%) and Pacific Ocean (14%; see Supplementary Fig. S4 for the delineation of ocean basins). Across latitudinal zones, changes in assemblage-averaged in the tropics are predicted to be large, with an average reduction of around 20% from 2001 to 2050 (20-year average; Fig. 2b). The magnitude of change is similar in the temperate regions (~30°–60°?N/S). In areas where the model projected a decrease in assemblage-averaged , there is a generally high level of agreement (coefficient of variation <20%) in the projections generated from using the two different earth system models (Fig. 2c).
Focusing on individual within each fish population, our study shows that most (>75%) of the studied populations are expected to experience a reduction of their of 5–39%, with a median of 10% in all ocean basins (Fig. 3). As a result of the higher rates of warming and reduction in oxygen content, the magnitude of decrease in individual is larger for fishes in the Pacific and Southern oceans, followed by those in the Atlantic, Indian and Arctic oceans (Fig. 3).
Overall, each of the two factors—changes in individual and species composition—contributes around half of the projected body weight shrinkage at the assemblage-level. Out of the 20% average assemblage-level shrinkages by 2050, around 10% is explained by the individual-level shrinkages from increased oxygen demand and reduced oxygen supply, because of the projected warming and reduced oxygen content (Fig. 1). Also, our model projects that distributions of most fish populations are expected to shift poleward at a median rate of around 27.5–36.4?km?decade?1 by 2050 relative to 2000 under the SRES A2 scenario (Supplementary Fig. S6 and Methods). As assemblage-averaged maximum body weight in the lower latitude region is smaller than that in the higher latitude regions (Fig. 2a), the model shows that a poleward shift of the fish community explains another half of the projected shrinkage of assemblage-level maximum body weight by 2050.
This study requires a number of assumptions and simplifications to represent and project long-term changes in the complex biological and earth systems, and is thus subject to several sources of uncertainty. First, there are uncertainties associated with projections of climate and ocean conditions. We attempted to address this by using outputs from two earth system models and identifying area of agreement between models. Our projected global trends are robust to outputs from the two earth system models. However, future studies should include outputs from more earth system models to investigate how different models affect the projected patterns of body size changes. Second, in modelling the ecophysiology, relative abundance and distribution of the fish species, the DBEM does not address factors such as an organism’s capacity to adapt to environmental changes through phenotypic and evolutionary changes3, 6. Although consideration of such factors may reduce species’ sensitivity to environmental changes, there is currently little evidence that fishes would adapt to compensate completely for warming. In contrast, increasing empirical evidence supports that warming has led to reduction in body size across foodwebs10, 11, 12; there is also ample evidence for climate-induced shifts in distribution4, 5. Moreover, comparing the observed relationship between intra-specific differences in maximum body size at different locations or different time-periods, we show that the predictions from our model are within the range of reported values and are more conservative in projecting shrinking of fishes under warming (Fig. 4). Examples of observed decreases in community-level body size under warming are also available from freshwater fishes in lakes18.
Sensitivity analysis of key parameters in the growth and metabolic scaling models suggest moderate sensitivity of the results to extreme parameter values, but particularly high sensitivity to an extremely high value (0.95) of the scaling coefficient (a in equation (3)), which may result in a considerably larger reduction in maximum body size (Supplementary Fig. S7). On the other hand, the use of alternative parameter values does not alter the direction of change. Also, our comparisons with empirical data and sensitivity analysis suggest that the rate of shrinking of maximum body size projected here is likely to be conservative. Our analysis did not explicitly account for trophic interactions, which may affect both the growth and distribution of marine biota19. Specifically, the widespread changes in assemblage-level body size structure suggest that climate and ocean changes are expected to cause considerable modification of foodweb dynamics. In particular, predator and prey relationship across marine ecosystems are strongly dependent on mass20. For example, the prey size of Atlantic cod (Gadus morhua) in the North Sea is significantly related to the size of this predator21. Moreover, maximum body weight, with temperature being a covariate, is significantly and positively related to size at maturity22, but negatively correlated with natural mortality rate23 and food consumption rate24. These are key factors determining trophic interactions25. Furthermore, food availability, which is assumed here to remain unlimited as fish’s maximum body size decreases and distribution shifts, will change as ocean productivity or abundance of prey changes. We did not investigate the potential effects of interactions between climate change and other human stressors, such as overfishing, habitat destruction and pollution, on species’ biological responses.
Despite these uncertainties, this study is the first-ever attempt to use models to examine the integrated effects of changes in species distribution, population abundance, and individual- and assemblage-level induced by climate and ocean changes on marine ecosystems. Assumptions and simplifications of the complex biological system underlying this study are inevitable if we are to make steps toward a better understanding of the effects of global change on marine biota. Such a study, however, provides the foundation for future work, incorporating other mechanisms and factors, and ultimately improving our ability to assess the effects of climate change on biological systems.
This study indicates that the consequences of failing to curtail greenhouse-gas emissions on marine ecosystems are likely to be larger than previously expected. It has been recognized that warming will increase the metabolic rate of terrestrial ectotherms globally across taxonomic groups26. Here, we demonstrate that the effects of warming on metabolic rate extend to fishes in the ocean. Furthermore, the results suggest that oxygen-limited growth in aquatic water-breathing animals and species’ range shift will translate, given their physiological responses to warming and changes in oxygen level, into a reduction in individual- and assemblage-level body size. We demonstrate that such a widespread decrease in exacerbates the impacts of distribution and abundance change on marine ecosystems. Previous studies identified that the tropics will suffer most from a high rate of local extinction and reduction in maximum catch potential, whereas higher latitude regions, such as the northern temperate regions, may gain9. This study shows that both the tropics and temperate regions will also be impacted by reduction in body size. Other human impacts, such as overfishing and pollution, are likely to further exacerbate such impacts27. Consequently, these changes are expected to have large implications for trophic interactions, ecosystem functions, fisheries and global protein supply.
Predicting changes in individual-level maximum body weight.
For simplification, the study assumes a?=?0.7 (equation (2)), although it varies from 0.5 to 0.95 between fish species2. Solving for dW/dt?=?0 in equation (1), we obtain:
H and k can be expressed as a function of temperature through the Arrhenius equation. To represent the limitation of capacity for growth by oxygen in fishes, H is also expressed as a function of dissolved oxygen in water (see Methods in Supplementary Information). Thus, H is directly proportional to O2, whereas both H and k are proportional to e?j/T and e?i/T, respectively, with the exponential term representing the Boltzmann factor. The growth parameter K (equation (2)) can be expressed as k(1?a); therefore and log(K) should be negatively and linearly related, and log(K) is negatively related to the inverse of temperature (1/T; see Supplementary Fig. S1).
In this study, we assume that food availability remains constant and in optimal supply so that it is not limiting maximum body size across space now and in the future. On the other hand, the consumption rate of fishes increases with temperature and correlates strongly with and K (Supplementary Fig. S1). Also, oxygen is required to convert food into metabolically available energy. Thus, we expect that fishes’ response to any climate change-related changes in food availability through alteration of maximum body size would be similar to those through oxygen-limitation.
The theoretical relationship between temperature, K and is clearly demonstrated from empirical analysis of fish’s growth parameters. Such analysis show significant intra-specific relationships between and log(K) (see ref. 2), and between log (K) and water temperature (for example, refs 28, 29, 30). These provide the empirical basis for applying this model to predict changes in and K under changing temperature.
We obtained averaged values of i and j for marine fishes based on published estimates of Q10 of basal metabolic rate of fishes with respect to temperature, and von Bertalanffy growth parameter K (see Supplementary Information and ref. 3). Thus, given known estimates of , sea water temperature and oxygen content of the habitat and their changes over time, we applied equation (3) to predict changes in as a result of changes in ocean conditions for fish populations. Moreover, changes in fish distributions were modelled by the Dynamic Bioclimate Envelope Model (see Supplementary Information). We initialized the models using predicted current (average of 1970–2000) species distribution6, and published parameter values for the growth and metabolic models (ref. 3 and see Supplementary Information). This model predicted changes in life-history characteristics that are consistent with empirically estimated growth parameters (that is, and K; see ref. 3 and Supplementary Fig. S2). We also examine the sensitivity of the results to the key parameters in equation (3) on the simulation (Supplementary Information).
Calculation of mean assemblage-level body weight.
We calculated the mean (geometric) assemblage-level body weight from the predicted distribution and maximum body weight of the modelled fish species. We identified species that were predicted to occur in each 30??latitude×30??longitude cell. We then calculated the mean (geometric) predicted maximum body weight in each cell weighted by the predicted relative abundance of each species, the area of the grid cells, and their historically observed maximum catch. Fish body weights range over several orders of magnitude, thus the geometric mean provides a better representation of the relative changes in body weight across the size spectrum of the assemblage. The historical maximum catch (C) was used as a proxy of the current level biomass of each species in the ocean, which was calculated from time-series catch data (1950 to the present) obtained from the United Nations Food and Agriculture Organization (FAO) and processed by the Sea Around Us project (www.seaaroundus.org). For each species, we calculated the average maximum annual catch from the mean of the five highest annual catches across the time-series. The mean assemblage-level body weight (W?) at cell i was then calculated from:
where is the maximum body weight of species j. The projected future level of biomass was calculated by multiplying C by the predicted relative abundance (Abd) from the DBEM under climate and ocean changes. The values of W?i are calculated for each year from 1971 to 2060.
Calculation of latitudinal centroid shift.
The latitudinal centroid (LC) of each species was calculated from:
where Lati is the latitude of the centre of the spatial cell (i), Abd is the predicted relative abundance in the cell (corrected by area of the grid cells), and n is the total number of cells. The range shift was then calculated from the difference between the latitudinal centroid of the projected and reference years. Shift in distance (kilometre) was then calculated from:
- Pörtner, H-O. Oxygen- and capacity-limitation of thermal tolerance: A matrix for integrating climate-related stressor effects in marine ecosystems. J. Exp. Biol. 213, 881–893 (2010).
- Pauly, D. Gasping Fish and Panting Squids: Oxygen, Temperature and the Growth of Water-Breathing Animals(International Ecology Institute, 2010).
- Cheung, W. W. L., Dunne, J., Sarmiento, J. L. & Pauly, D. Integrating ecophysiology and plankton dynamics into projected maximum fisheries catch potential under climate change in the Northeast Atlantic. ICES J. Mar. Sci. 68, 1008–1018 (2011).
- Perry, A. L., Low, P. J., Ellis, J. R. & Reynolds, J. D. Climate change and distribution shifts in marine fishes. Science 308, 1912–1915 (2005).
- Dulvy, N. K. et al. Climate change and deepening of the North Sea fish assemblage: A biotic indicator of warming seas. J. Appl. Ecol. 45, 1029–1039 (2008).
- Cheung, W. W. L. et al. Projecting global marine biodiversity impacts under climate change scenarios. Fish Fisheries 10, 235–251 (2009).
- Edwards, M. & Richardson, A. J. Impact of climate change on marine pelagic phenology and trophic mismatch. Nature 430, 881–884 (2004).
- Genner, M. J. et al. Temperature-driven phenological changes within a marine larval fish assemblage. J. Plankton Res. 32, 699–708 (2010).
- Cheung, W. W. L. et al. Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Glob. Change Biol. 16, 24–35 (2010).
- Daufresne, M., Lengfellner, K. & Sommer, U. Global warming benefits the small in aquatic ecosystems. Proc. Natl Acad. Sci. USA 106, 12788–12793 (2009).
- Baudron, A. R., Needle, C. L. & Marshall, C. T. Implications of a warming North Sea for the growth of haddock Melanogrammus aeglefinus. J. Fish Biol. 78, 1874–1889 (2011).
- Sheridan, J. A. & Bickford, D. Shrinking body size as an ecological response to climate change. Nature Clim. Change 1, 401–406 (2011).
- Sunday, J. M., Bates, A. E. & Dulvy, N. K. Global analysis of thermal tolerance and latitude in ectotherms. Proc. R. Soc. B 278, 1823–1830 (2011).
- Verberk, W. C. E. P. & Bilton, D. T. Can oxygen set thermal limits in an insect and drive gigantism? PLoS ONE 6, e22610 (2011).
- Von Bertalanffy, L. Theoretische Biologie—Zweiter Band: Stoffwechsel, Wachstum(A. Francke, 1951).
- Cheung, W. W. L., Close, C., Lam, V., Watson, R. & Pauly, D. Application of macroecological theory to predict effects of climate change on global fisheries potential. Mar. Ecol. Prog. Ser. 365, 187–197 (2008).
- Frölicher, T. L., Joos, F., Plattner, G. K., Steinacher, M. & Doney, S. C. Natural variability and anthropogenic trends in oceanic oxygen in a coupled carbon cycle in a coupled carbon cycle–climate model ensemble. Glob. Biogeochem. Cycles 23, GB1003 (2009).
- Jeppesen, E. et al. Impacts of climate warming on lake fish community structure and potential effects on ecosystem function. Hydrobiologia 646, 73–90 (2010).
- Harley, C. D. G. Climate change, keystone predation, and biodiversity loss. Science 334, 1124–1127 (2011).
- Barnes, C., Maxwell, D., Reuman, D. C. & Jennings, S. Global patterns in predator–prey size relationships reveal size dependency of trophic transfer efficiency. Ecology 91, 222–232 (2010).
- Floeter, J. & Temming, A. Explaining diet composition of North Sea cod (Gadus morhua): Prey size preference vs. prey availability. Can. J. Fish. Aquat. Sci. 60, 140–150 (2003).
- Pauly, D. A mechanism for the juvenile-to-adult transition in fishes. ICES J. Mar. Sci. 41, 280–284 (1984).
- Pauly, D. On the interrelationships between natural mortality, growth parameters and mean environmental temperature in 175 fish stocks. ICES J. Mar. Sci. 39, 175–192 (1980).
- Palomares, M. L. D. & Pauly, D. Predicting food consumption of fish populations as functions of mortality, food type, morphometrics, temperature and salinity. Mar. Freshwat. Res. 49, 447–453 (1998).
- Jennings, S., Kaiser, M. J. & Reynold, J. D. Marine Fisheries Ecology(Blackwell, 2001).
- Dillon, M. E., Wang, G. & Huey, R. B. Global metabolic impacts of recent climate warming. Nature 467, 704–706 (2010).
- Crain, C. M., Kroeker, K. & Halpern, B. S. Interactive and cumulative effects of multiple human stressors in marine systems. Ecol. Lett. 11, 1304–1315 (2008).
- Taylor, C. C. Cod growth and temperature. ICES J. Mar. Sci. 23, 366–370 (1958).
- Wohlschlag, D. E. in Biology of the Antarctic Seas(ed. Lee, M. O.) 33–62 (Anatarctic Research Series 1, American Geophysics Union, 1964).
- Henry, K. A. Atlantic Menhaden (Brevoortia tyrannus). Resource and Fishery–Analysis of Decline. Technical Report NMFS SSRF-642 (NOAA, 1971).
The contribution by W.W.L.C. is supported by the National Geographic Society and the Centre for Environment, Fisheries and Aquaculture Sciences (CEFAS). D.P. and R.W. are supported by the Pew Charitable Trust through the Sea Around Us project. J.L.S. and T.L.F. are supported by the Carbon Mitigation Initiative (CMI) project at Princeton University, sponsored by BP. We thank L. Bopp for providing outputs from the IPSL-CM4-LOOP model.
Competing financial interests
The authors declare no competing financial interests.