A hierarchical distance sampling model to estimate spatially explicit sea otter density

Abstract Wildlife managers often rely on analyses conducted prior to the widespread adoption of hierarchical models which can lead to questions about the accuracy of previous inferences. Hierarchical models allow observed data to be partitioned into factors that influenced the collection of the data...

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Published in:Ecosphere
Main Authors: Wilson, Ryan R., St. Martin, Michelle, Beatty, William S.
Other Authors: U.S. Fish and Wildlife Service
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2021
Subjects:
Online Access:http://dx.doi.org/10.1002/ecs2.3666
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.3666
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.3666
https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.3666
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spelling crwiley:10.1002/ecs2.3666 2024-06-02T08:15:56+00:00 A hierarchical distance sampling model to estimate spatially explicit sea otter density Wilson, Ryan R. St. Martin, Michelle Beatty, William S. U.S. Fish and Wildlife Service 2021 http://dx.doi.org/10.1002/ecs2.3666 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.3666 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.3666 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.3666 en eng Wiley http://creativecommons.org/licenses/by/4.0/ Ecosphere volume 12, issue 9 ISSN 2150-8925 2150-8925 journal-article 2021 crwiley https://doi.org/10.1002/ecs2.3666 2024-05-03T11:19:16Z Abstract Wildlife managers often rely on analyses conducted prior to the widespread adoption of hierarchical models which can lead to questions about the accuracy of previous inferences. Hierarchical models allow observed data to be partitioned into factors that influenced the collection of the data such as detectability of animals (i.e., observation processes) and factors that influence the ecology of a population such as features that affect the distribution of animals (i.e., ecological processes). Population surveys for sea otters in the Aleutian Islands, Alaska, have historically been conducted by conflating the observation and ecological processes potentially leading to inaccurate population estimates. Based on boat and plane‐based sea otter survey data collected in 2017, we sought to overcome many problems of previous sea otter surveys in southwestern Alaska. We developed a spatially explicit hierarchical distance sampling model to estimate the abundance of sea otters in the Eastern Aleutians Management Unit while explicitly accounting for factors that affect the ability to detect sea otters during surveys (i.e., group size, ocean conditions). We also sought to account for the environmental factors leading to the non‐uniform distribution of sea otter groups by identifying relationships between otter group abundance and environmental attributes (i.e., ocean depth, presence of kelp, underwater substrate). Detection of sea otter groups was related to group size, and ocean conditions (e.g., ocean swell size). After accounting for detection, we estimated a mean population size of 8593 individual sea otters (95% CI: 7450–9984) which is considerably higher than previous estimates, although comparisons are difficult given divergent methodologies. Sea otter group density was negatively related to ocean depth and the presence of rock and gravel as underwater substrates. Conversely, sea otter group density was positively related to the presence of kelp and mud as an underwater substrate. Our hierarchical distance ... Article in Journal/Newspaper Alaska Aleutian Islands Wiley Online Library Ecosphere 12 9
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description Abstract Wildlife managers often rely on analyses conducted prior to the widespread adoption of hierarchical models which can lead to questions about the accuracy of previous inferences. Hierarchical models allow observed data to be partitioned into factors that influenced the collection of the data such as detectability of animals (i.e., observation processes) and factors that influence the ecology of a population such as features that affect the distribution of animals (i.e., ecological processes). Population surveys for sea otters in the Aleutian Islands, Alaska, have historically been conducted by conflating the observation and ecological processes potentially leading to inaccurate population estimates. Based on boat and plane‐based sea otter survey data collected in 2017, we sought to overcome many problems of previous sea otter surveys in southwestern Alaska. We developed a spatially explicit hierarchical distance sampling model to estimate the abundance of sea otters in the Eastern Aleutians Management Unit while explicitly accounting for factors that affect the ability to detect sea otters during surveys (i.e., group size, ocean conditions). We also sought to account for the environmental factors leading to the non‐uniform distribution of sea otter groups by identifying relationships between otter group abundance and environmental attributes (i.e., ocean depth, presence of kelp, underwater substrate). Detection of sea otter groups was related to group size, and ocean conditions (e.g., ocean swell size). After accounting for detection, we estimated a mean population size of 8593 individual sea otters (95% CI: 7450–9984) which is considerably higher than previous estimates, although comparisons are difficult given divergent methodologies. Sea otter group density was negatively related to ocean depth and the presence of rock and gravel as underwater substrates. Conversely, sea otter group density was positively related to the presence of kelp and mud as an underwater substrate. Our hierarchical distance ...
author2 U.S. Fish and Wildlife Service
format Article in Journal/Newspaper
author Wilson, Ryan R.
St. Martin, Michelle
Beatty, William S.
spellingShingle Wilson, Ryan R.
St. Martin, Michelle
Beatty, William S.
A hierarchical distance sampling model to estimate spatially explicit sea otter density
author_facet Wilson, Ryan R.
St. Martin, Michelle
Beatty, William S.
author_sort Wilson, Ryan R.
title A hierarchical distance sampling model to estimate spatially explicit sea otter density
title_short A hierarchical distance sampling model to estimate spatially explicit sea otter density
title_full A hierarchical distance sampling model to estimate spatially explicit sea otter density
title_fullStr A hierarchical distance sampling model to estimate spatially explicit sea otter density
title_full_unstemmed A hierarchical distance sampling model to estimate spatially explicit sea otter density
title_sort hierarchical distance sampling model to estimate spatially explicit sea otter density
publisher Wiley
publishDate 2021
url http://dx.doi.org/10.1002/ecs2.3666
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.3666
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.3666
https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.3666
genre Alaska
Aleutian Islands
genre_facet Alaska
Aleutian Islands
op_source Ecosphere
volume 12, issue 9
ISSN 2150-8925 2150-8925
op_rights http://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1002/ecs2.3666
container_title Ecosphere
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