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...
Main Authors: | , , , |
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Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2021
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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 |
id | ftunivalberta:oai:era.library.ualberta.ca:6235f4ac-1e78-4a06-8f7d-139f11f43f7a |
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 |
record_format | openpolar |
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 |