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Springer, Climatic Change, 8(176), 2023

DOI: 10.1007/s10584-023-03577-2

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Multi-criteria analysis for rapid vulnerability assessment of marine species to climate change

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

AbstractThe accelerating pace of climate-induced stress to global ecosystems threatens the sustainable management and conservation of biodiversity. To effectively respond, researchers and managers require rapid vulnerability assessment tools that can be readily implemented using diverse and existing knowledge sources. Here we demonstrate the application of multi-criteria analysis (MCA) for this purpose using a group of coastal-pelagic fishes from south-eastern Australia as a case-study. We show that MCA has the capacity to formally structure diverse knowledge sources, ranging from peer-reviewed information (which informed 29.2% of criteria among models) to expert knowledge (which informed 22.6% of criteria among models), to quantify the sensitivity of species to biophysical conditions. By integrating MCA models with spatial climate data over historical and future periods, we demonstrate the application of MCA for rapidly assessing the vulnerability of marine species to climate change. Spatial analyses revealed an apparent trend among case-study species towards increasing or stable vulnerability to projected climate change throughout the northern (i.e. equatorward) extent of the study domain and the emergence of climate refugia throughout southern (i.e. poleward) regions. Results from projections using the MCA method were consistent with past analyses of the redistribution of suitable habitat for coastal-pelagic fishes off eastern Australia under climate change. By demonstrating the value of MCA for rapidly assessing the vulnerability of marine species to climate change, we highlight the opportunity to develop user-friendly software infrastructures integrated with marine climate projection data to support the interdisciplinary application of this method.