Synergistic interactions among growing stressors increase risk to an Arctic ecosystem

被引:37
作者
Arrigo, K. R. [1 ]
van Dijken, Gert L. [1 ]
Cameron, M. A. [2 ]
van der Grient, J. [3 ]
Wedding, L. M. [2 ,3 ]
Hazen, L. [2 ]
Leape, J. [2 ]
Leonard, G. [4 ]
Merkl, A. [4 ]
Micheli, F. [2 ,5 ]
Mills, M. M. [1 ]
Monismith, S. [6 ]
Ouellette, N. T. [6 ]
Zivian, A. [4 ]
Levi, M. [7 ]
Bailey, R. M. [3 ]
机构
[1] Stanford Univ, Sch Earth Energy & Environm Sci, Stanford, CA 94305 USA
[2] Stanford Univ, Stanford Ctr Ocean Solut, Stanford, CA USA
[3] Univ Oxford, Sch Geog & Environm, Oxford, England
[4] Ocean Conservancy, Santa Cruz, CA USA
[5] Stanford Univ, Hopkins Marine Stn, Pacific Grove, CA USA
[6] Stanford Univ, Dept Civil & Environm Engn, Stanford, CA USA
[7] Stanford Univ, Ctr Adv Study Behav Sci, Stanford, CA USA
关键词
CLIMATE-CHANGE IMPACTS; AMBIENT NOISE; FOOD-WEB; OCEAN ACIDIFICATION; MARINE; SEA; MECHANISMS; INSIGHTS; QUALITY; WHALES;
D O I
10.1038/s41467-020-19899-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Oceans provide critical ecosystem services, but are subject to a growing number of external pressures, including overfishing, pollution, habitat destruction, and climate change. Current models typically treat stressors on species and ecosystems independently, though in reality, stressors often interact in ways that are not well understood. Here, we use a network interaction model (OSIRIS) to explicitly study stressor interactions in the Chukchi Sea (Arctic Ocean) due to its extensive climate-driven loss of sea ice and accelerated growth of other stressors, including shipping and oil exploration. The model includes numerous trophic levels ranging from phytoplankton to polar bears. We find that climate-related stressors have a larger impact on animal populations than do acute stressors like increased shipping and subsistence harvesting. In particular, organisms with a strong temperature-growth rate relationship show the greatest changes in biomass as interaction strength increased, but also exhibit the greatest variability. Neglecting interactions between stressors vastly underestimates the risk of population crashes. Our results indicate that models must account for stressor interactions to enable responsible management and decision-making. Multiple co-occurring stressors may affect food webs in ways that are not predictable by studying individual stressors. Here the authors apply a network interaction model to a marine food web in the Arctic, finding that nonlinear interactions between stressors can more than double the risk of population collapse compared to simpler simulations.
引用
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页数:8
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