Sensitivity of marine fish thermal habitat models to fishery data sources

Nazzaro, Laura; Slesinger, Emily; Kohut, Josh; Saba, Grace; Saba, Vincent S.

doi:10.1002/ece3.7817

Cited by 7 publications

(4 citation statements)

References 44 publications

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“…Our findings were consistent with numerous studies which show that restricting the range, and particularly the extremes, of environmental data present in a sample can affect the calculation of species‐climate response curves and can lead to erroneous projections (Hortal et al, 2008; Nazzaro et al, 2021; Støa et al, 2018; Tessarolo et al, 2014; Thuiller et al, 2004). This is likely to occur in systems with strong geographic or temporal gradients in environmental variables when only a portion of the domain or a portion of the habitat or only certain seasons or years are sampled.…”

Section: Discussionsupporting

confidence: 91%

Projecting species distributions using fishery‐dependent data

et al. 2022

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Many marine species are shifting their distributions in response to changing ocean conditions, posing significant challenges and risks for fisheries management. Species distribution models (SDMs) are used to project future species distributions in the face of a changing climate. Information to fit SDMs generally comes from two main sources: fishery‐independent (scientific surveys) and fishery‐dependent (commercial catch) data. A concern with fishery‐dependent data is that fishing locations are not independent of the underlying species abundance, potentially biasing predictions of species distributions. However, resources for fishery‐independent surveys are increasingly limited; therefore, it is critical we understand the strengths and limitations of SDMs developed from fishery‐dependent data. We used a simulation approach to evaluate the potential for fishery‐dependent data to inform SDMs and abundance estimates and quantify the bias resulting from different fishery‐dependent sampling scenarios in the California Current System (CCS). We then evaluated the ability of the SDMs to project changes in the spatial distribution of species over time and compare the time scale over which model performance degrades between the different sampling scenarios and as a function of climate bias and novelty. Our results show that data generated from fishery‐dependent sampling can still result in SDMs with high predictive skill several decades into the future, given specific forms of preferential sampling which result in low climate bias and novelty. Therefore, fishery‐dependent data may be able to supplement information from surveys that are reduced or eliminated for budgetary reasons to project species distributions into the future.

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Section: Discussionsupporting

confidence: 91%

Projecting species distributions using fishery‐dependent data

et al. 2022

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“…Identification of thermal habitat through species distribution models has been assessed before using data from all of these trawl surveys (i.e., [39,43]), and presence/absence data tends to be more robust to potential error in survey differences. These fishery-independent data sources were chosen because they provide standardized fishery distribution data, have been used in prior studies that develop species distribution models for USNES fishes (i.e., [29]), and are used regularly in stock assessments.…”

Section: Plos Climatementioning

confidence: 99%

Climate-induced reduction in metabolically suitable habitat for U.S. northeast shelf marine species

Slesinger,

du Pontavice,

Seibel

et al. 2024

PLOS Clim

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The U.S. northeast shelf (USNES) has been experiencing rapid ocean warming, which is changing the thermal environment that marine species inhabit. To determine the effect of current and future ocean warming on the distribution of five important USNES fish species (Atlantic cod [Gadus morhua], black sea bass [Centropristis striata], cunner [Tautogolabrus adspersus], spiny dogfish [Squalus acanthias], summer flounder [Paralichthys dentatus]), we applied species-specific physiological parameters from laboratory studies to calculate the Metabolic Index (MI). The MI for each species was calculated across a historical (1972–2019) and contemporary (2010–2019) climatology for each season. Broadly, the oceanic conditions in the winter and spring seasons did not limit metabolically suitable habitat for all five species, while portions of the USNES in the summer and fall seasons were metabolically unsuitable for the cold water species (Atlantic cod, cunner, spiny dogfish). The warmer water species (black sea bass, summer flounder) experienced little metabolically suitable habitat loss, which was restricted to the most southern portion of the distribution. Under a doubling of atmospheric CO2, metabolically suitable habitat is projected to decrease substantially for Atlantic cod, restricting them to the Gulf of Maine. Cunner are projected to experience similar habitat loss as Atlantic cod, with some refugia in the New York Bight, and spiny dogfish may experience habitat loss in the Southern Shelf and portions of Georges Bank. In contrast, black sea bass and summer flounder are projected to experience minimal habitat loss restricted to the southern inshore portion of the USNES. The utility of using MI for co-occurring fish species in the USNES differed, likely driven by species-specific physiology and whether the southern edge of a population occurred within the USNES.

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“…The spatial resolution of global climate models can introduce sources of error in the prediction of spatiotemporal responses of species distribution (Stock et al, 2011;Muhling et al, 2015;Nazzaro et al, 2021). Specifically, some climate models are based on numerical ocean circulations that may be biased due to their large spatial resolution (typically 1°) (Bryan et al, 2007;Stock et al, 2011;Saba et al, 2016).…”

Section: Impacts To Hms Due To Changes In Other Oceanographic Processesmentioning

confidence: 99%

Effects of climate change and variability on large pelagic fish in the Northwest Atlantic Ocean: implications for improving climate resilient management for pelagic longline fisheries

Dell’Apa,

Boenish,

Fujita

et al. 2023

Front. Mar. Sci.

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Climate change influences marine environmental conditions and is projected to increase future environmental variability. In the North Atlantic, such changes will affect the behavior and spatiotemporal distributions of large pelagic fish species (i.e., tunas, billfishes, and sharks). Generally, studies on these species have focused on specific climate-induced changes in abiotic factors separately (e.g., water temperature) and on the projection of shifts in species abundance and distribution based on these changes. In this review, we consider the latest research on spatiotemporal effects of climate-induced environmental changes to HMS’ life history, ecology, physiology, distribution, and habitat selection, and describe how the complex interplay between climate-induced changes in biotic and abiotic factors, including fishing, drives changes in species productivity and distribution in the Northwest Atlantic. This information is used to provide a baseline for investigating implications for management of pelagic longline fisheries and to identify knowledge gaps in this region. Warmer, less oxygenated waters may result in higher post-release mortality in bycatch species. Changes in climate variability will likely continue to alter the dynamics of oceanographic processes regulating species behavior and distribution, as well as fishery dynamics, creating challenges for fishery management. Stock assessments need to account for climate-induced changes in species abundance through the integration of species-specific responses to climate variability. Climate-induced changes will likely result in misalignment between current spatial and temporal management measures and the spatiotemporal distribution of these species. Finally, changes in species interactions with fisheries will require focused research to develop best practices for adaptive fisheries management and species recovery.

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Sensitivity of marine fish thermal habitat models to fishery data sources

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 7 publications

References 44 publications

Projecting species distributions using fishery‐dependent data

Projecting species distributions using fishery‐dependent data

Climate-induced reduction in metabolically suitable habitat for U.S. northeast shelf marine species

Effects of climate change and variability on large pelagic fish in the Northwest Atlantic Ocean: implications for improving climate resilient management for pelagic longline fisheries

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