globalchange  > 气候变化事实与影响
DOI: doi:10.1038/nclimate2119
论文题名:
Impacts of climate change on marine ecosystem production in societies dependent on fisheries
作者: M. Barange
刊名: Nature Climate Change
ISSN: 1758-1416X
EISSN: 1758-7536
出版年: 2014-02-23
卷: Volume:4, 页码:Pages:211;216 (2014)
语种: 英语
英文关键词: Projection and prediction ; Ecological modelling ; Developing world ; Ecosystem services
英文摘要:

Growing human populations and changing dietary preferences are increasing global demands for fish1, adding pressure to concerns over fisheries sustainability2. Here we develop and link models of physical, biological and human responses to climate change in 67 marine national exclusive economic zones, which yield approximately 60% of global fish catches, to project climate change yield impacts in countries with different dependencies on marine fisheries3. Predicted changes in fish production indicate increased productivity at high latitudes and decreased productivity at low/mid latitudes, with considerable regional variations. With few exceptions, increases and decreases in fish production potential by 2050 are estimated to be <10% (mean +3.4%) from present yields. Among the nations showing a high dependency on fisheries3, climate change is predicted to increase productive potential in West Africa and decrease it in South and Southeast Asia. Despite projected human population increases and assuming that per capita fish consumption rates will be maintained1, ongoing technological development in the aquaculture industry suggests that projected global fish demands in 2050 could be met, thus challenging existing predictions of inevitable shortfalls in fish supply by the mid-twenty-first century4. This conclusion, however, is contingent on successful implementation of strategies for sustainable harvesting and effective distribution of wild fish products from nations and regions with a surplus to those with a deficit. Changes in management effectiveness2 and trade practices5 will remain the main influence on realized gains or losses in global fish production.

Marine fisheries provide 80Mt of protein and micronutrient-rich food for human consumption per year and contribute US$230 billion to the global economy, offering livelihood support to 8% of the world’s population5. With demand for fish products predicted to increase, efforts to support food and livelihood security need to be informed by predictions of changes in fish production and their societal and economic consequences. Biological predictions based on ocean–atmosphere general circulation models (OA-GCMs) have demonstrated that climate change will modify the physical and chemical properties of the oceans, affecting the productivity, distribution, seasonality and efficiency of food webs, from primary producers6 to fish7, 8. However, using GCMs to predict fish production has several uncertainties, in addition to their structural and natural variability uncertainties9. First, the resolution of GCMs is too coarse (typically 1°–2°) to capture the processes that dominate the dynamics of the world’s coastal and shelf regions, such as coastal upwelling and tidal mixing10, which exhibit significantly different responses to climate than the open ocean. Directly addressing the effects of these processes is an important challenge because coastal and shelf regions contribute a quarter of the global primary production and most global fish production11. Second, predicting the impacts of climate change on the ecosystem and fish production remains a challenge, as it depends on the transfer of energy through complex and often compensatory food chain processes12. Approaches at present either make strong habitat or energy transfer assumptions8, 13, or focus on predicting impacts on individual species14.

Here we directly address these challenges by developing and applying a highly resolved coupled physical–biological shelf-seas model to 67 marine national exclusive economic zones (EEZs). The model was forced using a single GCM (Institute Pierre Simon Laplace Global Climate Model; IPSL-CM4) under the Intergovernmental Panel on Climate Change (IPCC) SRES (Special Report on Emissions Scenarios) A1B scenario, providing ten-year mean outputs for the present day and 2050. These were used to drive a dynamic size-based food web model to estimate the ecological consequences of climate change on fish production capacity. Finally, we evaluate the societal relevance of these results by looking at the dependency of individual countries on their fisheries sectors in terms of food and livelihood security, as well as at the expected global demand for fish products for an increasing human population.

Our results show that in all the shelf regions considered the mixed layer depth temperature (MLDT, the depth to which the density difference from the surface is less than 0.03kg m−3) is expected to increase when referenced to the present day. By 2050, predicted warming of the mixed layer of shelf seas will range from a moderate 0.2°C in the Irish EEZ to 2.9°C off Korea and East China (Figs 1a and 2a).

Figure 1: Results of the modelling runs for the shelf seas of 20 large marine ecosystems.
Results of the modelling runs for the shelf seas of 20 large marine ecosystems.

a, Change in temperature (in °C) of the mixed layer in 2050 referenced to the present day control scenario. b, Change in total primary production in 2050 (in percentage) referenced to the present day control scenario. Each map reflects ten years of model outputs (modified from ref. 4 with permission from Elsevier).

Physical–biological models

. We simulated coastal and shelf-sea processes, and primary and secondary production, by means of a three-dimensional, high-resolution (0.1° × 0.1°) hydrodynamic model (POLCOMS; ref.26), coupled with a generic, functional type ecosystem model (ERSEM; ref.27). The coupled model was run under three particular experiments: a present day control experiment; a near-future climate experiment (for 2050) using data taken from IPCC SRES A1B emissions scenario (business-as-usual, using the IPSL-SM4 OA-GCM); and re-analysis simulation using data from a global ocean assimilation and re-analysis simulation17. Differences in ten-year means were considered as indicative of climate change, although recognizing that climate variability may contribute to these differences. The outputs of these models were used to drive a size-structured ecosystem model28 that explicitly accounts for food web interactions, linking primary production to fish production through predation, to project climate-driven changes in potential fish production. This modelling framework was applied to 11 coastal and shelf sea regions, covering 30 large marine ecosystems and including 67 marine national EEZs. With this modelling structure, we obtained fine-scale temperature, primary production and size-based estimates of biological production change by 2050, referenced to the present day, for an area at present yielding 60% of the global landings recorded from EEZs (Supplementary Section 1, www.seaaroundus.org). The use of size-based models recognizes that in marine environments predation is strongly driven by body size rather than taxonomic identity, and that direct climate change impacts are likely to be on ecological and physiological relationships that are size- and temperature-dependent, but overlooks processes linked to species identity. For each EEZ and scenario, the model was first run to equilibrium using time-averaged input before applying the model to time-varying environmental conditions for the duration of a ten-year time slice under each of the scenarios. The results used in this paper are time-averaged across a ten-year time slice during which the size spectrum model has been dynamically forced using daily time-varying inputs of temperature (near sea floor and mixed layer depth), detritus and the intercept of the plankton. The intercept of the size spectrum is determined by the temporal changes in phytoplankton and microzooplankton biomass density, with the consequences that higher primary production leads to size spectra with higher intercepts. Phytoplankton and microzooplankton functional groups (outputs of the POLCOMS–ERSEM model) are assumed to occupy size ranges. Assuming invariant biomass in body mass log bins and a −1 numerical density slope across a size range of 10−14 to 10−4 g size margin, we estimated the intercept. Recent work has shown that size spectrum dynamics can be influenced by the variation in intercepts, slopes and the size range of phytoplankton, and our results may therefore be sensitive to these simplifying assumptions.

Fisheries dependency

. Vulnerability to climate change depends on three key elements: exposure to the physical effects of climate change; economic and social dependency on the changing variable(s); and adaptive capacity to the changes. To investigate the potential societal impact of climate-induced changes in fish production potential, we developed an index of fisheries dependency for 58 nations, defined as ‘The Importance of Fish and Fisheries to the National Economy and Food Security’3. A country’s dependence score was determined from global fisheries statistics29 using three indicators measuring the contribution that fisheries make to the national diet, to employment and to gross domestic product. The national-scale indicators were standardized on a scale of 0 to 1 and averaged to generate an overall dependency score. The dependency analysis builds on data obtained from UN FAO statistics (dietary contributions) and the Sea Around Us project (economic contributions, www.searoundus.org); contributions in terms of employment were obtained from published literature29, 30.

Modelling climate assumptions

. We conducted a single, but dynamically consistent, future climate projection based around the sensitivity of the system to this imposed change, but without an assessment of its likelihood. The forcing scenario (A1B) was chosen, as it sits near the middle of the envelope of projected CO2 emissions. The IPSL-CM4 model sits close to the centre of spread of the CMIP3 models in terms of global temperature, and for the 2050 forecast horizon model uncertainty would be expected to dominate over scenario uncertainty. We recognize that a different combination of OA-GCM and regional model would have resulted in some quantitative differences in the results, and where there are competing processes in the models these may lead to qualitative differences.

  1. Delgado, C. L., Wada, N., Rosegrant, M. W., Meijer, S. & Ahmed, M. Fish to 2020: Supply and demand in changing global markets. International Food Policy Research Institute and Worldfish Center, 2003.
  2. Worm, B. et al. Rebuilding global fisheries. Science 325, 578585 (2009).
  3. Allison, E. H. et al. Vulnerability of national economies to the impacts of climate change on fisheries. Fish Fish. 10, 173196 (2009).
  4. Merino, G. et al. Can marine fisheries and aquaculture meet fish demand from a growing human population in a changing climate?. Glob. Environ. Change 22, 795806 (2012).
  5. Sumaila, R. U., Cheung, W. W. L., Lam, V. W. Y., Pauly, D. & Herrick, S. Climate change impacts on the biophysics and economics of world fisheries. Nature Clim. Change 1, 449456 (2011).
  6. Steinacher, M. et al. Projected 21st century decrease in marine productivity: A multi-model analysis. Biogeosciences 7, 9791005 (2010).
  7. Cheung, W. W. L., Dunne, J. & Sarmiento, J. L. P. D. Integrating ecophysiology and plankton dynamics into projected maximum fisheries catch potential under climate change in the Northeast Atlantic. ICES J. Mar. Sci. 68, 10081018 (2011).
  8. 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, 2435 (2009).
  9. Hawkins, E. & Sutton, R. The potential to narrow uncertainties in regional climate predictions. B. Am. Meteorol. Soc. 90, 10951107 (2009).
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URL: http://www.nature.com/nclimate/journal/v4/n3/full/nclimate2119.html
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/5236
Appears in Collections:气候变化事实与影响
科学计划与规划
气候变化与战略

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M. Barange. Impacts of climate change on marine ecosystem production in societies dependent on fisheries[J]. Nature Climate Change,2014-02-23,Volume:4:Pages:211;216 (2014).
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