Data from: Delineating important killer whale foraging areas using a spatiotemporal logistic model ...

Conservation management planning for highly mobile species requires an understanding of the distribution of areas that are biologically important to the species of concern. Collecting data on the locations of animal behaviors linked to biological characteristics, such as foraging, can be used to spa...

Full description

Bibliographic Details
Main Authors: Stredulinsky, Eva H., Toews, Scott, Watson, Joe, Noren, Dawn P., Holt, Marla M., Thornton, Sheila J.
Format: Dataset
Language:English
Published: Dryad 2024
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.zcrjdfnm9
https://datadryad.org/stash/dataset/doi:10.5061/dryad.zcrjdfnm9
id ftdatacite:10.5061/dryad.zcrjdfnm9
record_format openpolar
spelling ftdatacite:10.5061/dryad.zcrjdfnm9 2024-06-09T07:47:28+00:00 Data from: Delineating important killer whale foraging areas using a spatiotemporal logistic model ... Stredulinsky, Eva H. Toews, Scott Watson, Joe Noren, Dawn P. Holt, Marla M. Thornton, Sheila J. 2024 https://dx.doi.org/10.5061/dryad.zcrjdfnm9 https://datadryad.org/stash/dataset/doi:10.5061/dryad.zcrjdfnm9 en eng Dryad https://dx.doi.org/10.1016/j.gecco.2023.e02726 Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 Nature and Landscape Conservation Ecology FOS Biological sciences Ecology, Evolution, Behavior and Systematics Dataset dataset 2024 ftdatacite https://doi.org/10.5061/dryad.zcrjdfnm910.1016/j.gecco.2023.e02726 2024-05-13T13:23:36Z Conservation management planning for highly mobile species requires an understanding of the distribution of areas that are biologically important to the species of concern. Collecting data on the locations of animal behaviors linked to biological characteristics, such as foraging, can be used to spatially describe biological important areas. However, spatial modeling of free-ranging animal behavior can be challenging, as behavioral observations of animals are often clustered, and sampling is commonly conducted at a higher frequency than changes in behavioral states, resulting in data that are usually highly autocorrelated in space and time. Here, we fit latent Gaussian process models to observational behavioral data to generate spatially-explicit predictions of foraging behavior within the critical habitat of an endangered population of fish-eating killer whales (Orcinus orca) in southern British Columbia, Canada, and northern Washington State, USA. We compare spatial models treating temporal autocorrelation ... : # Delineating important killer whale foraging areas using a spatiotemporal logistic model [https://doi.org/10.5061/dryad.zcrjdfnm9](https://doi.org/10.5061/dryad.zcrjdfnm9) For any questions regarding data and analyses in this publication, please contact the corresponding author, Sheila Thornton[ sheila.thornton@dfo-mpo.gc.ca](mailto:eva.stredulinsky@dfo-mpo.gc.ca). The authors request that should this data (or any subset therein) be used in any analyses, presentations, publications, and/or other data products, it is encouraged that the corresponding author be notified, in order to ensure that the programs and personnel responsible for the collection, assembly, and interpretation of the data are consulted and adequately credited. We recommend citing Stredulinsky et al. (2023) with any use of images or data products in analyses, presentations, publications, and/or other data products. To contact the project lead of a particular study from which data was used in this analysis: (1) Noren_2006: Dawn Noren ... Dataset Killer Whale Orca Orcinus orca Killer whale DataCite Metadata Store (German National Library of Science and Technology) British Columbia ENVELOPE(-125.003,-125.003,54.000,54.000) Canada Sheila ENVELOPE(-44.766,-44.766,-60.716,-60.716) Thornton ENVELOPE(-57.467,-57.467,-63.267,-63.267)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Nature and Landscape Conservation
Ecology
FOS Biological sciences
Ecology, Evolution, Behavior and Systematics
spellingShingle Nature and Landscape Conservation
Ecology
FOS Biological sciences
Ecology, Evolution, Behavior and Systematics
Stredulinsky, Eva H.
Toews, Scott
Watson, Joe
Noren, Dawn P.
Holt, Marla M.
Thornton, Sheila J.
Data from: Delineating important killer whale foraging areas using a spatiotemporal logistic model ...
topic_facet Nature and Landscape Conservation
Ecology
FOS Biological sciences
Ecology, Evolution, Behavior and Systematics
description Conservation management planning for highly mobile species requires an understanding of the distribution of areas that are biologically important to the species of concern. Collecting data on the locations of animal behaviors linked to biological characteristics, such as foraging, can be used to spatially describe biological important areas. However, spatial modeling of free-ranging animal behavior can be challenging, as behavioral observations of animals are often clustered, and sampling is commonly conducted at a higher frequency than changes in behavioral states, resulting in data that are usually highly autocorrelated in space and time. Here, we fit latent Gaussian process models to observational behavioral data to generate spatially-explicit predictions of foraging behavior within the critical habitat of an endangered population of fish-eating killer whales (Orcinus orca) in southern British Columbia, Canada, and northern Washington State, USA. We compare spatial models treating temporal autocorrelation ... : # Delineating important killer whale foraging areas using a spatiotemporal logistic model [https://doi.org/10.5061/dryad.zcrjdfnm9](https://doi.org/10.5061/dryad.zcrjdfnm9) For any questions regarding data and analyses in this publication, please contact the corresponding author, Sheila Thornton[ sheila.thornton@dfo-mpo.gc.ca](mailto:eva.stredulinsky@dfo-mpo.gc.ca). The authors request that should this data (or any subset therein) be used in any analyses, presentations, publications, and/or other data products, it is encouraged that the corresponding author be notified, in order to ensure that the programs and personnel responsible for the collection, assembly, and interpretation of the data are consulted and adequately credited. We recommend citing Stredulinsky et al. (2023) with any use of images or data products in analyses, presentations, publications, and/or other data products. To contact the project lead of a particular study from which data was used in this analysis: (1) Noren_2006: Dawn Noren ...
format Dataset
author Stredulinsky, Eva H.
Toews, Scott
Watson, Joe
Noren, Dawn P.
Holt, Marla M.
Thornton, Sheila J.
author_facet Stredulinsky, Eva H.
Toews, Scott
Watson, Joe
Noren, Dawn P.
Holt, Marla M.
Thornton, Sheila J.
author_sort Stredulinsky, Eva H.
title Data from: Delineating important killer whale foraging areas using a spatiotemporal logistic model ...
title_short Data from: Delineating important killer whale foraging areas using a spatiotemporal logistic model ...
title_full Data from: Delineating important killer whale foraging areas using a spatiotemporal logistic model ...
title_fullStr Data from: Delineating important killer whale foraging areas using a spatiotemporal logistic model ...
title_full_unstemmed Data from: Delineating important killer whale foraging areas using a spatiotemporal logistic model ...
title_sort data from: delineating important killer whale foraging areas using a spatiotemporal logistic model ...
publisher Dryad
publishDate 2024
url https://dx.doi.org/10.5061/dryad.zcrjdfnm9
https://datadryad.org/stash/dataset/doi:10.5061/dryad.zcrjdfnm9
long_lat ENVELOPE(-125.003,-125.003,54.000,54.000)
ENVELOPE(-44.766,-44.766,-60.716,-60.716)
ENVELOPE(-57.467,-57.467,-63.267,-63.267)
geographic British Columbia
Canada
Sheila
Thornton
geographic_facet British Columbia
Canada
Sheila
Thornton
genre Killer Whale
Orca
Orcinus orca
Killer whale
genre_facet Killer Whale
Orca
Orcinus orca
Killer whale
op_relation https://dx.doi.org/10.1016/j.gecco.2023.e02726
op_rights Creative Commons Zero v1.0 Universal
https://creativecommons.org/publicdomain/zero/1.0/legalcode
cc0-1.0
op_doi https://doi.org/10.5061/dryad.zcrjdfnm910.1016/j.gecco.2023.e02726
_version_ 1801378565557583872