Trophic amplification: A model intercomparison of climate driven changes in marine food webs
V Guibourd de Luzinais, H Du Pontavice, G Reygondeau, N Barrier, JL Blanchard, V Bornarel, M Büchner, WWL Cheung, TD Eddy, JD Everett, J Guiet, CS Harrison, O Maury, C Novaglio, CM Petrik, J Steenbeek, DP Tittensor, D Gascuel
Marine animal biomass is expected to decrease in the 21st century due to climate driven changes in ocean environmental conditions. Previous studies suggest that the magnitude of the decline in primary production on apex predators could be amplified through the trophodynamics of marine food webs, leading to larger decreases in the biomass of predators relative to the decrease in primary production, a mechanism called trophic amplification. We compared relative changes in producer and consumer biomass or production in the global ocean to assess the extent of trophic amplification. We used simulations from nine marine ecosystem models (MEMs) from the Fisheries and Marine Ecosystem Models Intercomparison Project forced by two Earth System Models under the high greenhouse gas emissions Shared Socioeconomic Pathways (SSP5-8.5) and a scenario of no fishing. Globally, total consumer biomass is projected to decrease by 16.7 ± 9.5% more than net primary production (NPP) by 2090–2099 relative to 1995–2014, with substantial variations among MEMs and regions. Total consumer biomass is projected to decrease almost everywhere in the ocean (80% of the world’s oceans) in the model ensemble. In 40% of the world’s oceans, consumer biomass was projected to decrease more than NPP. Additionally, in another 36% of the world’s oceans consumer biomass is expected to decrease even as projected NPP increases. By analysing the biomass response within food webs in available MEMs, we found that model parameters and structures contributed to more complex responses than a consistent amplification of climate impacts of higher trophic levels. Our study provides additional insights into the ecological mechanisms that will impact marine ecosystems, thereby informing model and scenario development.