Detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling

1. Spatial memory plays a role in the way animals perceive their environments, re-sulting in memory-informed movement patterns that are observable to ecologists. Developing mathematical techniques to understand how animals use memory in their environments allows for an increased understanding of ani...

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Main Authors: Peter R. Thompson, Andrew E. Derocher, Mark A. Edwards, Mark A. Lewis
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
Online Access:https://era.library.ualberta.ca/items/6235f4ac-1e78-4a06-8f7d-139f11f43f7a
https://doi.org/10.7939/r3-pcy8-2825
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author Peter R. Thompson
Andrew E. Derocher
Mark A. Edwards
Mark A. Lewis
author_facet Peter R. Thompson
Andrew E. Derocher
Mark A. Edwards
Mark A. Lewis
author_sort Peter R. Thompson
collection University of Alberta: Era - Education and Research Archive
description 1. Spatial memory plays a role in the way animals perceive their environments, re-sulting in memory-informed movement patterns that are observable to ecologists. Developing mathematical techniques to understand how animals use memory in their environments allows for an increased understanding of animal cognition. 2. Here we describe a model that accounts for the memory of seasonal or ephem-eral qualities of an animal's environment. The model captures multiple behaviours at once by allowing for resource selection in the present time as well as long- distance navigations to previously visited locations within an animal's home range. 3. We performed a set of analyses on simulated data to test our model, determin-ing that it can provide informative results from as little as 1 year of discrete-time location data. We also show that the accuracy of model selection and parameter estimation increases with more location data. 4. This model has potential to identify a specific mechanism in which animals use memory to optimize their foraging, by revisiting temporally and predictably vari-able resources at consistent time- lags.
format Article in Journal/Newspaper
genre Ursus arctos
genre_facet Ursus arctos
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institution Open Polar
language English
op_collection_id ftunivalberta
op_doi https://doi.org/10.7939/r3-pcy8-2825
op_relation https://era.library.ualberta.ca/items/6235f4ac-1e78-4a06-8f7d-139f11f43f7a
doi:10.7939/r3-pcy8-2825
op_rights http://creativecommons.org/licenses/by-nc/4.0/
publishDate 2021
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spelling ftunivalberta:oai:era.library.ualberta.ca:6235f4ac-1e78-4a06-8f7d-139f11f43f7a 2025-01-17T01:14:46+00:00 Detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling Peter R. Thompson Andrew E. Derocher Mark A. Edwards Mark A. Lewis 2021-01-01 https://era.library.ualberta.ca/items/6235f4ac-1e78-4a06-8f7d-139f11f43f7a https://doi.org/10.7939/r3-pcy8-2825 English eng https://era.library.ualberta.ca/items/6235f4ac-1e78-4a06-8f7d-139f11f43f7a doi:10.7939/r3-pcy8-2825 http://creativecommons.org/licenses/by-nc/4.0/ animal movement cognitive map grizzly bear hidden Markov model spatial memory step- selection function Ursus arctos Article (Published) 2021 ftunivalberta https://doi.org/10.7939/r3-pcy8-2825 2023-05-13T23:00:02Z 1. Spatial memory plays a role in the way animals perceive their environments, re-sulting in memory-informed movement patterns that are observable to ecologists. Developing mathematical techniques to understand how animals use memory in their environments allows for an increased understanding of animal cognition. 2. Here we describe a model that accounts for the memory of seasonal or ephem-eral qualities of an animal's environment. The model captures multiple behaviours at once by allowing for resource selection in the present time as well as long- distance navigations to previously visited locations within an animal's home range. 3. We performed a set of analyses on simulated data to test our model, determin-ing that it can provide informative results from as little as 1 year of discrete-time location data. We also show that the accuracy of model selection and parameter estimation increases with more location data. 4. This model has potential to identify a specific mechanism in which animals use memory to optimize their foraging, by revisiting temporally and predictably vari-able resources at consistent time- lags. Article in Journal/Newspaper Ursus arctos University of Alberta: Era - Education and Research Archive
spellingShingle animal movement
cognitive map
grizzly bear
hidden Markov model
spatial memory
step- selection function
Ursus arctos
Peter R. Thompson
Andrew E. Derocher
Mark A. Edwards
Mark A. Lewis
Detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling
title Detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling
title_full Detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling
title_fullStr Detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling
title_full_unstemmed Detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling
title_short Detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling
title_sort detecting seasonal episodic-like spatio-temporal memory patterns using animal movement modelling
topic animal movement
cognitive map
grizzly bear
hidden Markov model
spatial memory
step- selection function
Ursus arctos
topic_facet animal movement
cognitive map
grizzly bear
hidden Markov model
spatial memory
step- selection function
Ursus arctos
url https://era.library.ualberta.ca/items/6235f4ac-1e78-4a06-8f7d-139f11f43f7a
https://doi.org/10.7939/r3-pcy8-2825