Integrated Modeling to Evaluate Climate Change Impacts on Coupled Social-Ecological Systems in Alaska

Anne Babcock Hollowed,James N Ianelli,Kerim Aydin,Thomas K Wilderbuer,Albert J Hermann,Jonathan C P Reum,William Stockhausen,George A Whitehouse,Amanda Faig,Wei Cheng,Kirstin Kari Holsman,Andre E Punt,Paul Spencer,Kelly A Kearney,Stephen Kasperski,Cody S Szuwalski,Ingrid Spies,Alan C Haynie

doi:10.3389/fmars.2019.00775

Abstract

The Alaska CLimate Integrated Modeling (ACLIM) project represents a comprehensive, multi-year, interdisciplinary effort to characterize and project climate-driven changes to the Eastern Bering Sea ecosystem, from physics to fishing communities. Results from the ACLIM project are being used to understand how different regional fisheries management approaches can help promote adaptation to climate-driven changes to sustain fish and shellfish populations and to inform managers and fishery dependent communities of the risks associated with different future climate scenarios. The project relies on iterative communications and outreach with managers and fishery dependent communities that has informed the selection of fishing scenarios. This iterative approach ensures that the research team focuses on policy relevant scenarios that explore realistic adaptation options for managers and communities. Within each iterative cycle, the interdisciplinary research team continues to improve: methods for downscaling climate models, climate-enhanced biological models, socio-economic modeling, and management strategy evaluation within a common analytical framework. The evolving nature of the ACLIM framework ensures improved understanding of system responses and feedbacks are considered within the projections and that the fishing scenarios continue to reflect the management objectives of the regional fisheries management bodies. The multi-model approach used for projection of biological responses facilitates the quantification the relative contributions of climate forcing scenario, fishing scenario, parameter, and structural uncertainty with and between models. Ensemble means and variance within and between models informs risk assessments under different future scenarios. The first phase of projections of climate conditions to the end of 21st century are complete, and projections of catch for core species under baseline (status quo) fishing conditions and two alternative fishing scenarios. The ACLIM modeling framework serves as a guide for multidisciplinary integrated climate impact and adaptation decision making in other large marine ecosystems.

Highlights

Significant increases in sea surface temperature (SST) over the century are projected for most ocean systems (IPCC, 2014, 2018)
Under representative concentration pathways (RCPs) 8.5, Bering Sea shelf average mean bottom temperatures may warm by as much as 5◦C by 2100, with associated loss of large zooplankton (Figure 4), whereas, under the lower emission scenario, bottom temperatures will warm by approximately 2.5◦C (Figure 4)
Alaska Climate Integrated Modeling is a novel multidisciplinary modeling study designed to quantify the impacts of climate change on Bering Sea species and fisheries

Summary

INTRODUCTION

Significant increases in sea surface temperature (SST) over the century are projected for most ocean systems (IPCC, 2014, 2018). Bering Sea ecosystems are threatened by the effects of ocean acidification on valuable crab stocks and important pelagic prey species (Comeau et al, 2010; Long et al, in press) In anticipation of these changes, the US National Marine Fisheries Service (NMFS) established a Climate Science Strategy (NCSS) that called for scientists from each management region to conduct research to understand, prepare for, and respond to, climate impacts on the distribution and abundance of managed species and the ecosystems in which they reside (Buser et al, 2016). The Climate-Enhanced Age-based model with Temperature-specific Trophic Linkages and Energetics (CEATTLE, Holsman et al, 2016) was funded directly by NMFS research initiatives focused on the development of integrated ecosystem assessments and stock assessment improvement This legacy of collaborative research led to a mechanistic understanding of key biophysical linkages governing fish production (Sigler et al, 2016a) and completed model performance verification studies that served as the foundation for the ACLIM project. ACLIM GCM or ESM Emission Spatial–temporal resolution phase scenario for atmosphere

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INITIAL RESULTS

SUMMARY