Evaluating the impacts of reduced sampling density in a systematic fisheries-independent survey design

Fisheries-independent surveys provide critical data products used to estimate stock status and inform management decisions. While it can be possible to redistribute sampling effort to improve survey efficiency and address changing monitoring needs in the face of unforeseen challenges, it is importan...

Full description

Bibliographic Details
Main Authors: Lukas DeFilippo, Stan Kotwicki, Lewis Barnett, Jon Richar, Michael A. Litzow, William T. Stockhausen, Katie Palof
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Marine Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2023.1219283/full
_version_ 1797737007803269120
author Lukas DeFilippo
Stan Kotwicki
Lewis Barnett
Jon Richar
Michael A. Litzow
William T. Stockhausen
Katie Palof
author_facet Lukas DeFilippo
Stan Kotwicki
Lewis Barnett
Jon Richar
Michael A. Litzow
William T. Stockhausen
Katie Palof
author_sort Lukas DeFilippo
collection DOAJ
description Fisheries-independent surveys provide critical data products used to estimate stock status and inform management decisions. While it can be possible to redistribute sampling effort to improve survey efficiency and address changing monitoring needs in the face of unforeseen challenges, it is important to assess the consequences of such changes. Here, we present an approach that relies on existing survey data and simulations to evaluate the impacts of strategic reductions in survey sampling effort. We apply this approach to assess the potential effects of reducing high density sampling near St. Matthew Island and the Pribilof Islands in the NOAA eastern Bering Sea (EBS) bottom trawl survey. These areas contain high density “corner stations” that were implemented for finer-scale monitoring of associated blue king crab stocks (Paralithodes platypus) which historically supported commercial fisheries but have since declined and are seldom eligible for harvest. We investigate the effects of removing these corner stations on survey data quality for focal P. platypus stocks and other crab and groundfish species monitored by the EBS survey. We find that removing the St. Matthew and Pribilof Islands corner stations has negligible effects on data quality for most stocks, except for those whose distributions are concentrated in these areas. However, the data quality for such stocks was relatively low even with higher density sampling, and corner station removal had only minor effects on stock assessment outcomes. The analysis we present here provides a generic approach for evaluating strategic reductions in sampling effort for systematic survey designs and can be applied by scientists and managers facing similar decisions elsewhere.
first_indexed 2024-03-12T13:22:10Z
format Article
id doaj.art-3fb52aa2badf4900bac8a512385997a2
institution Directory Open Access Journal
issn 2296-7745
language English
last_indexed 2024-03-12T13:22:10Z
publishDate 2023-08-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Marine Science
spelling doaj.art-3fb52aa2badf4900bac8a512385997a22023-08-25T17:21:05ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452023-08-011010.3389/fmars.2023.12192831219283Evaluating the impacts of reduced sampling density in a systematic fisheries-independent survey designLukas DeFilippo0Stan Kotwicki1Lewis Barnett2Jon Richar3Michael A. Litzow4William T. Stockhausen5Katie Palof6Resource Assessment and Conservation Engineering Division, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), Seattle, WA, United StatesResource Assessment and Conservation Engineering Division, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), Seattle, WA, United StatesResource Assessment and Conservation Engineering Division, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), Seattle, WA, United StatesResource Assessment and Conservation Engineering Division, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), Kodiak, AK, United StatesResource Assessment and Conservation Engineering Division, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), Kodiak, AK, United StatesResource Ecology and Fisheries Management Division, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), Seattle, WA, United StatesAlaska Department of Fish and Game, Division of Commercial Fisheries, Juneau, AK, United StatesFisheries-independent surveys provide critical data products used to estimate stock status and inform management decisions. While it can be possible to redistribute sampling effort to improve survey efficiency and address changing monitoring needs in the face of unforeseen challenges, it is important to assess the consequences of such changes. Here, we present an approach that relies on existing survey data and simulations to evaluate the impacts of strategic reductions in survey sampling effort. We apply this approach to assess the potential effects of reducing high density sampling near St. Matthew Island and the Pribilof Islands in the NOAA eastern Bering Sea (EBS) bottom trawl survey. These areas contain high density “corner stations” that were implemented for finer-scale monitoring of associated blue king crab stocks (Paralithodes platypus) which historically supported commercial fisheries but have since declined and are seldom eligible for harvest. We investigate the effects of removing these corner stations on survey data quality for focal P. platypus stocks and other crab and groundfish species monitored by the EBS survey. We find that removing the St. Matthew and Pribilof Islands corner stations has negligible effects on data quality for most stocks, except for those whose distributions are concentrated in these areas. However, the data quality for such stocks was relatively low even with higher density sampling, and corner station removal had only minor effects on stock assessment outcomes. The analysis we present here provides a generic approach for evaluating strategic reductions in sampling effort for systematic survey designs and can be applied by scientists and managers facing similar decisions elsewhere.https://www.frontiersin.org/articles/10.3389/fmars.2023.1219283/fullsurvey designstock assessmentgroundfishcrabspatiotemporal model
spellingShingle Lukas DeFilippo
Stan Kotwicki
Lewis Barnett
Jon Richar
Michael A. Litzow
William T. Stockhausen
Katie Palof
Evaluating the impacts of reduced sampling density in a systematic fisheries-independent survey design
Frontiers in Marine Science
survey design
stock assessment
groundfish
crab
spatiotemporal model
title Evaluating the impacts of reduced sampling density in a systematic fisheries-independent survey design
title_full Evaluating the impacts of reduced sampling density in a systematic fisheries-independent survey design
title_fullStr Evaluating the impacts of reduced sampling density in a systematic fisheries-independent survey design
title_full_unstemmed Evaluating the impacts of reduced sampling density in a systematic fisheries-independent survey design
title_short Evaluating the impacts of reduced sampling density in a systematic fisheries-independent survey design
title_sort evaluating the impacts of reduced sampling density in a systematic fisheries independent survey design
topic survey design
stock assessment
groundfish
crab
spatiotemporal model
url https://www.frontiersin.org/articles/10.3389/fmars.2023.1219283/full
work_keys_str_mv AT lukasdefilippo evaluatingtheimpactsofreducedsamplingdensityinasystematicfisheriesindependentsurveydesign
AT stankotwicki evaluatingtheimpactsofreducedsamplingdensityinasystematicfisheriesindependentsurveydesign
AT lewisbarnett evaluatingtheimpactsofreducedsamplingdensityinasystematicfisheriesindependentsurveydesign
AT jonrichar evaluatingtheimpactsofreducedsamplingdensityinasystematicfisheriesindependentsurveydesign
AT michaelalitzow evaluatingtheimpactsofreducedsamplingdensityinasystematicfisheriesindependentsurveydesign
AT williamtstockhausen evaluatingtheimpactsofreducedsamplingdensityinasystematicfisheriesindependentsurveydesign
AT katiepalof evaluatingtheimpactsofreducedsamplingdensityinasystematicfisheriesindependentsurveydesign