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How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection

1. Uncovering the mechanisms behind animal space use patterns is of vital importance for predictive ecology, thus conservation and management of ecosystems. Movement is a core driver of those patterns so understanding how movement mechanisms give rise to space use patterns has become an increasingly...

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Autores principales: Potts, Jonathan R., Börger, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099581/
https://www.ncbi.nlm.nih.gov/pubmed/36321473
http://dx.doi.org/10.1111/1365-2656.13832
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author Potts, Jonathan R.
Börger, Luca
author_facet Potts, Jonathan R.
Börger, Luca
author_sort Potts, Jonathan R.
collection PubMed
description 1. Uncovering the mechanisms behind animal space use patterns is of vital importance for predictive ecology, thus conservation and management of ecosystems. Movement is a core driver of those patterns so understanding how movement mechanisms give rise to space use patterns has become an increasingly active area of research. 2. This study focuses on a particular strand of research in this area, based around step selection analysis (SSA). SSA is a popular way of inferring drivers of movement decisions, but, perhaps less well appreciated, it also parametrises a model of animal movement. Of key interest is that this model can be propagated forwards in time to predict the space use patterns over broader spatial and temporal scales than those that pertain to the proximate movement decisions of animals. 3. Here, we provide a guide for understanding and using the various existing techniques for scaling up step selection models to predict broad‐scale space use patterns. We give practical guidance on when to use which technique, as well as specific examples together with code in R and Python. 4. By pulling together various disparate techniques into one place, and providing code and instructions in simple examples, we hope to highlight the importance of these techniques and make them accessible to a wider range of ecologists, ultimately helping expand the usefulness of SSA.
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spelling pubmed-100995812023-04-14 How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection Potts, Jonathan R. Börger, Luca J Anim Ecol Research Methods Guide 1. Uncovering the mechanisms behind animal space use patterns is of vital importance for predictive ecology, thus conservation and management of ecosystems. Movement is a core driver of those patterns so understanding how movement mechanisms give rise to space use patterns has become an increasingly active area of research. 2. This study focuses on a particular strand of research in this area, based around step selection analysis (SSA). SSA is a popular way of inferring drivers of movement decisions, but, perhaps less well appreciated, it also parametrises a model of animal movement. Of key interest is that this model can be propagated forwards in time to predict the space use patterns over broader spatial and temporal scales than those that pertain to the proximate movement decisions of animals. 3. Here, we provide a guide for understanding and using the various existing techniques for scaling up step selection models to predict broad‐scale space use patterns. We give practical guidance on when to use which technique, as well as specific examples together with code in R and Python. 4. By pulling together various disparate techniques into one place, and providing code and instructions in simple examples, we hope to highlight the importance of these techniques and make them accessible to a wider range of ecologists, ultimately helping expand the usefulness of SSA. John Wiley and Sons Inc. 2022-11-14 2023-01 /pmc/articles/PMC10099581/ /pubmed/36321473 http://dx.doi.org/10.1111/1365-2656.13832 Text en © 2022 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Methods Guide
Potts, Jonathan R.
Börger, Luca
How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection
title How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection
title_full How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection
title_fullStr How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection
title_full_unstemmed How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection
title_short How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection
title_sort how to scale up from animal movement decisions to spatiotemporal patterns: an approach via step selection
topic Research Methods Guide
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099581/
https://www.ncbi.nlm.nih.gov/pubmed/36321473
http://dx.doi.org/10.1111/1365-2656.13832
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