Abstract:
:While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.
journal_name
Proc Natl Acad Sci U S Aauthors
Lotze HK,Tittensor DP,Bryndum-Buchholz A,Eddy TD,Cheung WWL,Galbraith ED,Barange M,Barrier N,Bianchi D,Blanchard JL,Bopp L,Büchner M,Bulman CM,Carozza DA,Christensen V,Coll M,Dunne JP,Fulton EA,Jennings S,Jones MC,doi
10.1073/pnas.1900194116subject
Has Abstractpub_date
2019-06-25 00:00:00pages
12907-12912issue
26eissn
0027-8424issn
1091-6490pii
1900194116journal_volume
116pub_type
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