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Integrated modeling to evaluate climate change impacts on coupled social-ecological systems in Alaska

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Hollowed, AB and Holsman, KK and Haynie, AC and Hermann, AJ and Punt, AE and Aydin, K and Ianelli, JN and Kasperski, S and Cheng, W and Faig, A and Kearney, KA and Reum, JCP and Spencer, P and Spies, I and Stockhausen, W and Szuwalski, CS and Whitehouse, GA and Wilderbuer, TK, Integrated modeling to evaluate climate change impacts on coupled social-ecological systems in Alaska, Frontiers in Marine Science, 6 Article 775. ISSN 2296-7745 (2020) [Refereed Article]


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Copyright Statement

Copyright 2020 Hollowed, Holsman, Haynie, Hermann, Punt, Aydin, Ianelli, Kasperski, Cheng, Faig, Kearney, Reum, Spencer, Spies, Stockhausen, Szuwalski, Whitehouse and Wilderbuer. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License (https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

DOI: 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 (EBS) 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 outreaches with managers and fishery-dependent communities that have 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 (MSE) 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 of 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 inform risk assessments under different future scenarios. The first phase of projections of climate conditions to the end of the 21st century is complete, including projections of catch for core species under baseline (status quo) fishing conditions and two alternative fishing scenarios are discussed. The ACLIM modeling framework serves as a guide for multidisciplinary integrated climate impact and adaptation decision making in other large marine ecosystems.

Item Details

Item Type:Refereed Article
Keywords:climate change, fishery management strategy, Bering Sea, walleye pollock, Pacific cod, climate projections
Research Division:Environmental Sciences
Research Group:Climate change impacts and adaptation
Research Field:Ecological impacts of climate change and ecological adaptation
Objective Division:Environmental Policy, Climate Change and Natural Hazards
Objective Group:Mitigation of climate change
Objective Field:Climate change mitigation strategies
UTAS Author:Reum, JCP (Dr Jonathan Reum)
ID Code:151406
Year Published:2020
Web of Science® Times Cited:36
Deposited By:Ecology and Biodiversity
Deposited On:2022-07-28
Last Modified:2022-08-12
Downloads:0

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