Accounting for phenology in the analysis of animal movement

The analysis of animal tracking data provides an important source of scientific understanding and discovery in ecology. Observations of animal trajectories using telemetry devices provide researchers with information about the way animals interact with their environment and each other. For many spec...

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Main Authors: Scharf, Henry R., Hooten, Mevin B., Wilson, Ryan R., Durner, George M., Atwood, Todd C.
Format: Report
Language:unknown
Published: arXiv 2018
Subjects:
Online Access:https://dx.doi.org/10.48550/arxiv.1806.09473
https://arxiv.org/abs/1806.09473
id ftdatacite:10.48550/arxiv.1806.09473
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spelling ftdatacite:10.48550/arxiv.1806.09473 2023-05-15T15:54:37+02:00 Accounting for phenology in the analysis of animal movement Scharf, Henry R. Hooten, Mevin B. Wilson, Ryan R. Durner, George M. Atwood, Todd C. 2018 https://dx.doi.org/10.48550/arxiv.1806.09473 https://arxiv.org/abs/1806.09473 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Methodology stat.ME Applications stat.AP FOS Computer and information sciences Preprint Article article CreativeWork 2018 ftdatacite https://doi.org/10.48550/arxiv.1806.09473 2022-04-01T09:40:06Z The analysis of animal tracking data provides an important source of scientific understanding and discovery in ecology. Observations of animal trajectories using telemetry devices provide researchers with information about the way animals interact with their environment and each other. For many species, specific geographical features in the landscape can have a strong effect on behavior. Such features may correspond to a single point (e.g., dens or kill sites), or to higher-dimensional subspaces (e.g., rivers or lakes). Features may be relatively static in time (e.g., coastlines or home-range centers), or may be dynamic (e.g., sea ice extent or areas of high-quality forage for herbivores). We introduce a novel model for animal movement that incorporates active selection for dynamic features in a landscape. Our approach is motivated by the study of polar bear (Ursus maritimus) movement. During the sea ice melt season, polar bears spend much of their time on sea ice above shallow, biologically productive water where they hunt seals. The changing distribution and characteristics of sea ice throughout the late spring through early fall means that the location of valuable habitat is constantly shifting. We develop a model for the movement of polar bears that accounts for the effect of this important landscape feature. We introduce a two-stage procedure for approximate Bayesian inference that allows us to analyze over 300,000 observed locations of 186 polar bears from 2012--2016. We use our proposed model to answer a particular question posed by wildlife managers who seek to cluster polar bears from the Beaufort and Chukchi seas into sub-populations. : Correction to caption of Figure 4 Report Chukchi polar bear Sea ice Ursus maritimus DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Methodology stat.ME
Applications stat.AP
FOS Computer and information sciences
spellingShingle Methodology stat.ME
Applications stat.AP
FOS Computer and information sciences
Scharf, Henry R.
Hooten, Mevin B.
Wilson, Ryan R.
Durner, George M.
Atwood, Todd C.
Accounting for phenology in the analysis of animal movement
topic_facet Methodology stat.ME
Applications stat.AP
FOS Computer and information sciences
description The analysis of animal tracking data provides an important source of scientific understanding and discovery in ecology. Observations of animal trajectories using telemetry devices provide researchers with information about the way animals interact with their environment and each other. For many species, specific geographical features in the landscape can have a strong effect on behavior. Such features may correspond to a single point (e.g., dens or kill sites), or to higher-dimensional subspaces (e.g., rivers or lakes). Features may be relatively static in time (e.g., coastlines or home-range centers), or may be dynamic (e.g., sea ice extent or areas of high-quality forage for herbivores). We introduce a novel model for animal movement that incorporates active selection for dynamic features in a landscape. Our approach is motivated by the study of polar bear (Ursus maritimus) movement. During the sea ice melt season, polar bears spend much of their time on sea ice above shallow, biologically productive water where they hunt seals. The changing distribution and characteristics of sea ice throughout the late spring through early fall means that the location of valuable habitat is constantly shifting. We develop a model for the movement of polar bears that accounts for the effect of this important landscape feature. We introduce a two-stage procedure for approximate Bayesian inference that allows us to analyze over 300,000 observed locations of 186 polar bears from 2012--2016. We use our proposed model to answer a particular question posed by wildlife managers who seek to cluster polar bears from the Beaufort and Chukchi seas into sub-populations. : Correction to caption of Figure 4
format Report
author Scharf, Henry R.
Hooten, Mevin B.
Wilson, Ryan R.
Durner, George M.
Atwood, Todd C.
author_facet Scharf, Henry R.
Hooten, Mevin B.
Wilson, Ryan R.
Durner, George M.
Atwood, Todd C.
author_sort Scharf, Henry R.
title Accounting for phenology in the analysis of animal movement
title_short Accounting for phenology in the analysis of animal movement
title_full Accounting for phenology in the analysis of animal movement
title_fullStr Accounting for phenology in the analysis of animal movement
title_full_unstemmed Accounting for phenology in the analysis of animal movement
title_sort accounting for phenology in the analysis of animal movement
publisher arXiv
publishDate 2018
url https://dx.doi.org/10.48550/arxiv.1806.09473
https://arxiv.org/abs/1806.09473
genre Chukchi
polar bear
Sea ice
Ursus maritimus
genre_facet Chukchi
polar bear
Sea ice
Ursus maritimus
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.1806.09473
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