4.6 Article

The relative influence of temperature and size-structure on fish distribution shifts: A case-study on Walleye pollock in the Bering Sea

期刊

FISH AND FISHERIES
卷 18, 期 6, 页码 1073-1084

出版社

WILEY
DOI: 10.1111/faf.12225

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Alaska pollock; distribution shift; size-structure; spatiotemporal model; temperature impacts

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Research has estimated associations between water temperature and the spatial distribution of marine fishes based upon correlations between temperature and the centroid of fish distribution (centre of gravity, COG). Analysts have then projected future water temperatures to forecast shifts in COG, but often neglected to demonstrate that temperature explains a substantial portion of historical distribution shifts. We argue that estimating the proportion of observed distributional shifts that can be attributed to temperature vs. other factors is a critical first step in forecasting future changes. We illustrate this approach using Gadus chalcogrammus (Walleye pollock) in the Eastern Bering Sea, and use a vector-autoregressive spatiotemporal model to attribute variation in COG from 1982 to 2015 to three factors: local or regional changes in surface and bottom temperature (temperature effects), fluctuations in size-structure that cause COG to be skewed towards juvenile or adult habitats (size-structured effects) or otherwise unexplained spatiotemporal variation in distribution (unexplained effects). We find that the majority of variation in COG (including the north-west trend since 1982) is largely unexplained by temperature or size-structured effects. Temperature alone generates a small portion of primarily north-south variation in COG, while size-structured effects generate a small portion of east-west variation. We therefore conclude that projections of future distribution based on temperature alone are likely to miss a substantial portion of both the interannual variation and interdecadal trends in COG for this species. More generally, we suggest that decomposing variation in COG into multiple causal factors is a vital first step for projecting likely impacts of temperature change.

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