The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design

Species-distribution shifts are becoming commonplace due to climate-driven change. Difficult decisions to modify survey extent and frequency are often made due to this change and constraining survey budgets. This often leads to spatially and temporally unbalanced survey coverage. Spatio-temporal mod...

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Published in:Frontiers in Marine Science
Main Authors: Bryan, Meaghan D., Thorson, James T.
Format: Article in Journal/Newspaper
Language:unknown
Published: Frontiers Media SA 2023
Subjects:
Online Access:http://dx.doi.org/10.3389/fmars.2023.1198260
https://www.frontiersin.org/articles/10.3389/fmars.2023.1198260/full
id crfrontiers:10.3389/fmars.2023.1198260
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spelling crfrontiers:10.3389/fmars.2023.1198260 2024-02-11T10:02:32+01:00 The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design Bryan, Meaghan D. Thorson, James T. 2023 http://dx.doi.org/10.3389/fmars.2023.1198260 https://www.frontiersin.org/articles/10.3389/fmars.2023.1198260/full unknown Frontiers Media SA https://creativecommons.org/licenses/by/4.0/ Frontiers in Marine Science volume 10 ISSN 2296-7745 Ocean Engineering Water Science and Technology Aquatic Science Global and Planetary Change Oceanography journal-article 2023 crfrontiers https://doi.org/10.3389/fmars.2023.1198260 2024-01-26T10:03:49Z Species-distribution shifts are becoming commonplace due to climate-driven change. Difficult decisions to modify survey extent and frequency are often made due to this change and constraining survey budgets. This often leads to spatially and temporally unbalanced survey coverage. Spatio-temporal models are increasingly used to account for spatially unbalanced sampling data when estimating abundance indices used for stock assessment, but their performance in these contexts has received little research attention. We therefore seek to answer two questions: (1) how well can a spatio-temporal model estimate the proportion of abundance in a new “climate-adaptive” spatial stratum? and (2) when sampling must be reduced, does annual sampling at reduced density or biennial sampling result in better model-based abundance indices? We develop a spatially varying coefficient model in the R package VAST using the eastern Bering Sea (EBS) bottom trawl survey and its northern Bering Sea (NBS) extension to address these questions. We first reduce the spatial extent of survey data for 30 out of 38 years of a real survey in the EBS and fit a spatio-temporal model to four commercially important species using these “data-reduction” scenarios. This shows that a spatio-temporal model generally produces similar trends and density estimates over time when large portions of the sampling domain are not sampled. However, when the central distribution of a population is not sampled the estimates are inaccurate and have higher uncertainty. We also conducted a simulation experiment conditioned upon estimates for walleye pollock ( Gadus chalcogrammus ) in the EBS and NBS. Many species in this region are experiencing distributional shifts attributable to climate change with species historically centered in the southeastern portion of the survey being increasingly encountered in the NBS. The NBS was occasionally surveyed in the past, but has been surveyed more regularly in recent years to document distributional shifts. Expanding the survey to ... Article in Journal/Newspaper Bering Sea Frontiers (Publisher) Bering Sea Frontiers in Marine Science 10
institution Open Polar
collection Frontiers (Publisher)
op_collection_id crfrontiers
language unknown
topic Ocean Engineering
Water Science and Technology
Aquatic Science
Global and Planetary Change
Oceanography
spellingShingle Ocean Engineering
Water Science and Technology
Aquatic Science
Global and Planetary Change
Oceanography
Bryan, Meaghan D.
Thorson, James T.
The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design
topic_facet Ocean Engineering
Water Science and Technology
Aquatic Science
Global and Planetary Change
Oceanography
description Species-distribution shifts are becoming commonplace due to climate-driven change. Difficult decisions to modify survey extent and frequency are often made due to this change and constraining survey budgets. This often leads to spatially and temporally unbalanced survey coverage. Spatio-temporal models are increasingly used to account for spatially unbalanced sampling data when estimating abundance indices used for stock assessment, but their performance in these contexts has received little research attention. We therefore seek to answer two questions: (1) how well can a spatio-temporal model estimate the proportion of abundance in a new “climate-adaptive” spatial stratum? and (2) when sampling must be reduced, does annual sampling at reduced density or biennial sampling result in better model-based abundance indices? We develop a spatially varying coefficient model in the R package VAST using the eastern Bering Sea (EBS) bottom trawl survey and its northern Bering Sea (NBS) extension to address these questions. We first reduce the spatial extent of survey data for 30 out of 38 years of a real survey in the EBS and fit a spatio-temporal model to four commercially important species using these “data-reduction” scenarios. This shows that a spatio-temporal model generally produces similar trends and density estimates over time when large portions of the sampling domain are not sampled. However, when the central distribution of a population is not sampled the estimates are inaccurate and have higher uncertainty. We also conducted a simulation experiment conditioned upon estimates for walleye pollock ( Gadus chalcogrammus ) in the EBS and NBS. Many species in this region are experiencing distributional shifts attributable to climate change with species historically centered in the southeastern portion of the survey being increasingly encountered in the NBS. The NBS was occasionally surveyed in the past, but has been surveyed more regularly in recent years to document distributional shifts. Expanding the survey to ...
format Article in Journal/Newspaper
author Bryan, Meaghan D.
Thorson, James T.
author_facet Bryan, Meaghan D.
Thorson, James T.
author_sort Bryan, Meaghan D.
title The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design
title_short The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design
title_full The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design
title_fullStr The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design
title_full_unstemmed The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design
title_sort performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design
publisher Frontiers Media SA
publishDate 2023
url http://dx.doi.org/10.3389/fmars.2023.1198260
https://www.frontiersin.org/articles/10.3389/fmars.2023.1198260/full
geographic Bering Sea
geographic_facet Bering Sea
genre Bering Sea
genre_facet Bering Sea
op_source Frontiers in Marine Science
volume 10
ISSN 2296-7745
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3389/fmars.2023.1198260
container_title Frontiers in Marine Science
container_volume 10
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