Species distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data‐limited ecosystem
Abstract Species distribution models (SDMs) are used to map and predict the geographic distributions of animals based on environmental covariates. Typically, SDMs require high‐resolution habitat data and time series information on animal locations. For data‐limited regions, defined as having scarce...
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ftdoajarticles:oai:doaj.org/article:8f0d69ffa7a443d586cc969c7d36a29f 2024-09-15T18:15:45+00:00 Species distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data‐limited ecosystem Elizabeth L. Hasan Kristen B. Gorman Heather A. Coletti Brenda Konar 2024-03-01T00:00:00Z https://doi.org/10.1002/ece3.11118 https://doaj.org/article/8f0d69ffa7a443d586cc969c7d36a29f EN eng Wiley https://doi.org/10.1002/ece3.11118 https://doaj.org/toc/2045-7758 2045-7758 doi:10.1002/ece3.11118 https://doaj.org/article/8f0d69ffa7a443d586cc969c7d36a29f Ecology and Evolution, Vol 14, Iss 3, Pp n/a-n/a (2024) data‐limited Enhydra lutris kenyoni habitat mapping MaxEnt sea otter species distribution modeling Ecology QH540-549.5 article 2024 ftdoajarticles https://doi.org/10.1002/ece3.11118 2024-08-05T17:49:46Z Abstract Species distribution models (SDMs) are used to map and predict the geographic distributions of animals based on environmental covariates. Typically, SDMs require high‐resolution habitat data and time series information on animal locations. For data‐limited regions, defined as having scarce habitat or animal survey data, modeling is more challenging, often failing to incorporate important environmental attributes. For example, for sea otters (Enhydra lutris), a federally protected keystone species with variable population trends across the species' range, predictive modeling of distributions has been successfully conducted in areas with robust sea otter population and habitat data. We used open‐access data and employed a presence‐only model, maximum entropy (MaxEnt), to investigate subtidal habitat associations (substrate and algal cover, bathymetry, and rugosity) of northern sea otters (E. lutris kenyoni) for a data‐limited ecosystem, represented by Kachemak Bay, Alaska. Habitat association results corroborated previous findings regarding the importance of bathymetry and understory kelp as predictors of sea otter presence. Novel associations were detected as filamentous algae and shell litter were positively and negatively associated with northern sea otter presence, respectively, advancing existing knowledge of sea otter benthic habitat associations useful for predicting habitat suitability. This study provides a quantitative framework for conducting species distribution modeling with limited temporal and spatial animal distribution and abundance data. Utilizing drop camera information, our novel approach allowed for a better understanding of habitat requirements for a stable northern sea otter population, including bathymetry, understory kelp, and filamentous algae as positive predictors of sea otter presence in Kachemak Bay, Alaska. Article in Journal/Newspaper Kachemak Alaska Directory of Open Access Journals: DOAJ Articles Ecology and Evolution 14 3 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
data‐limited Enhydra lutris kenyoni habitat mapping MaxEnt sea otter species distribution modeling Ecology QH540-549.5 |
spellingShingle |
data‐limited Enhydra lutris kenyoni habitat mapping MaxEnt sea otter species distribution modeling Ecology QH540-549.5 Elizabeth L. Hasan Kristen B. Gorman Heather A. Coletti Brenda Konar Species distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data‐limited ecosystem |
topic_facet |
data‐limited Enhydra lutris kenyoni habitat mapping MaxEnt sea otter species distribution modeling Ecology QH540-549.5 |
description |
Abstract Species distribution models (SDMs) are used to map and predict the geographic distributions of animals based on environmental covariates. Typically, SDMs require high‐resolution habitat data and time series information on animal locations. For data‐limited regions, defined as having scarce habitat or animal survey data, modeling is more challenging, often failing to incorporate important environmental attributes. For example, for sea otters (Enhydra lutris), a federally protected keystone species with variable population trends across the species' range, predictive modeling of distributions has been successfully conducted in areas with robust sea otter population and habitat data. We used open‐access data and employed a presence‐only model, maximum entropy (MaxEnt), to investigate subtidal habitat associations (substrate and algal cover, bathymetry, and rugosity) of northern sea otters (E. lutris kenyoni) for a data‐limited ecosystem, represented by Kachemak Bay, Alaska. Habitat association results corroborated previous findings regarding the importance of bathymetry and understory kelp as predictors of sea otter presence. Novel associations were detected as filamentous algae and shell litter were positively and negatively associated with northern sea otter presence, respectively, advancing existing knowledge of sea otter benthic habitat associations useful for predicting habitat suitability. This study provides a quantitative framework for conducting species distribution modeling with limited temporal and spatial animal distribution and abundance data. Utilizing drop camera information, our novel approach allowed for a better understanding of habitat requirements for a stable northern sea otter population, including bathymetry, understory kelp, and filamentous algae as positive predictors of sea otter presence in Kachemak Bay, Alaska. |
format |
Article in Journal/Newspaper |
author |
Elizabeth L. Hasan Kristen B. Gorman Heather A. Coletti Brenda Konar |
author_facet |
Elizabeth L. Hasan Kristen B. Gorman Heather A. Coletti Brenda Konar |
author_sort |
Elizabeth L. Hasan |
title |
Species distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data‐limited ecosystem |
title_short |
Species distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data‐limited ecosystem |
title_full |
Species distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data‐limited ecosystem |
title_fullStr |
Species distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data‐limited ecosystem |
title_full_unstemmed |
Species distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data‐limited ecosystem |
title_sort |
species distribution modeling of northern sea otters (enhydra lutris kenyoni) in a data‐limited ecosystem |
publisher |
Wiley |
publishDate |
2024 |
url |
https://doi.org/10.1002/ece3.11118 https://doaj.org/article/8f0d69ffa7a443d586cc969c7d36a29f |
genre |
Kachemak Alaska |
genre_facet |
Kachemak Alaska |
op_source |
Ecology and Evolution, Vol 14, Iss 3, Pp n/a-n/a (2024) |
op_relation |
https://doi.org/10.1002/ece3.11118 https://doaj.org/toc/2045-7758 2045-7758 doi:10.1002/ece3.11118 https://doaj.org/article/8f0d69ffa7a443d586cc969c7d36a29f |
op_doi |
https://doi.org/10.1002/ece3.11118 |
container_title |
Ecology and Evolution |
container_volume |
14 |
container_issue |
3 |
_version_ |
1810453693616619520 |