Future ocean biomass losses may widen socioeconomic equity gaps

Daniel G Boyce,David A Carozza,Heike K Lotze,Boris Worm,Derek P Tittensor

doi:10.1038/s41467-020-15708-9

Daniel G Boyce, David A Carozza + Show 3 more

Open Access

https://doi.org/10.1038/s41467-020-15708-9

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Abstract

Future climate impacts and their consequences are increasingly being explored using multi-model ensembles that average across individual model projections. Here we develop a statistical framework that integrates projections from coupled ecosystem and earth-system models to evaluate significance and uncertainty in marine animal biomass changes over the 21st century in relation to socioeconomic indicators at national to global scales. Significant biomass changes are projected in 40%–57% of the global ocean, with 68%–84% of these areas exhibiting declining trends under low and high emission scenarios, respectively. Given unabated emissions, maritime nations with poor socioeconomic statuses such as low nutrition, wealth, and ocean health will experience the greatest projected losses. These findings suggest that climate-driven biomass changes will widen existing equity gaps and disproportionally affect populations that contributed least to global CO2 emissions. However, our analysis also suggests that such deleterious outcomes are largely preventable by achieving negative emissions (RCP 2.6).

Highlights

Future climate impacts and their consequences are increasingly being explored using multimodel ensembles that average across individual model projections
Average biomass was positively related to latitudinal gradients in average net primary production (NPP) and negatively related to gradients in sea surface temperature (SST), especially between ~50°N and °S, but less so at higher latitudes (Fig. 2a)
The prevalence of diatoms was often elevated, potentially increasing the fraction of NPP transferred to consumers rather than to the microbial loop, leading to higher animal biomass than would be expected from NPP or SST alone[4]

Summary

Introduction

Future climate impacts and their consequences are increasingly being explored using multimodel ensembles that average across individual model projections. Projections of marine ecosystem responses to climate change could be used to explore feasibility pathways towards meeting several of the sustainable development goals (SDGs), including those aimed at reducing hunger (SDG2), improving health, well-being (SDG3), and economic inequalities (SDG10), and avoiding adverse ecosystem effects due to climate change (SDG14) We address these knowledge gaps by estimating the rates of climate-driven ensemble-averaged animal biomass changes and their statistical significance over the 21st century and relating these future biomass changes to present-day indicators of fisheries productivity, human stressors, and socioeconomic status (SES). Despite their widespread application in other disciplines, longitudinal models remain far unused in ensemble climate forecasting

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