Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat
Aim The increasing availability of animal tracking datasets collected across many sites provides new opportunities to move beyond local assessments to enable detailed and consistent habitat mapping at biogeographical scales. However, integrating wildlife datasets across large areas and study sites i...
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ftslunivuppsala:oai:pub.epsilon.slu.se:32178 2023-12-17T10:51:42+01:00 Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat Andren, Henrik Persson, Jens 2023 application/pdf https://pub.epsilon.slu.se/32178/ https://pub.epsilon.slu.se/32178/1/oeser-j-et-al-20231116.pdf en eng eng https://pub.epsilon.slu.se/32178/1/oeser-j-et-al-20231116.pdf Andren, Henrik and Persson, Jens (2023). Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat. Diversity and Distributions. 29 :12 , 1546-1560 [Research article] Ecology Research article NonPeerReviewed info:eu-repo/semantics/article 2023 ftslunivuppsala 2023-11-23T17:13:59Z Aim The increasing availability of animal tracking datasets collected across many sites provides new opportunities to move beyond local assessments to enable detailed and consistent habitat mapping at biogeographical scales. However, integrating wildlife datasets across large areas and study sites is challenging, as species' varying responses to different environmental contexts must be reconciled. Here, we compare approaches for large-area habitat mapping and assess available habitat for a recolonizing large carnivore, the Eurasian lynx (Lynx lynx).LocationEurope.Methods We use a continental-scale animal tracking database (450 individuals from 14 study sites) to systematically assess modelling approaches, comparing (1) global strategies that pool all data for training versus building local, site-specific models and combining them, (2) different approaches for incorporating regional variation in habitat selection and (3) different modelling algorithms, testing nonlinear mixed effects models as well as machine-learning algorithms.Results Testing models on training sites and simulating model transfers, global and local modelling strategies achieved overall similar predictive performance. Model performance was the highest using flexible machine-learning algorithms and when incorporating variation in habitat selection as a function of environmental variation. Our best-performing model used a weighted combination of local, site-specific habitat models. Our habitat maps identified large areas of suitable, but currently unoccupied lynx habitat, with many of the most suitable unoccupied areas located in regions that could foster connectivity between currently isolated populations.Main Conclusions We demonstrate that global and local modelling strategies can achieve robust habitat models at the continental scale and that considering regional variation in habitat selection improves broad-scale habitat mapping. More generally, we highlight the promise of large wildlife tracking databases for large-area habitat mapping. Our ... Article in Journal/Newspaper Lynx Lynx lynx lynx Swedish University of Agricultural Sciences (SLU): Epsilon Open Archive |
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Swedish University of Agricultural Sciences (SLU): Epsilon Open Archive |
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English |
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Ecology |
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Ecology Andren, Henrik Persson, Jens Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat |
topic_facet |
Ecology |
description |
Aim The increasing availability of animal tracking datasets collected across many sites provides new opportunities to move beyond local assessments to enable detailed and consistent habitat mapping at biogeographical scales. However, integrating wildlife datasets across large areas and study sites is challenging, as species' varying responses to different environmental contexts must be reconciled. Here, we compare approaches for large-area habitat mapping and assess available habitat for a recolonizing large carnivore, the Eurasian lynx (Lynx lynx).LocationEurope.Methods We use a continental-scale animal tracking database (450 individuals from 14 study sites) to systematically assess modelling approaches, comparing (1) global strategies that pool all data for training versus building local, site-specific models and combining them, (2) different approaches for incorporating regional variation in habitat selection and (3) different modelling algorithms, testing nonlinear mixed effects models as well as machine-learning algorithms.Results Testing models on training sites and simulating model transfers, global and local modelling strategies achieved overall similar predictive performance. Model performance was the highest using flexible machine-learning algorithms and when incorporating variation in habitat selection as a function of environmental variation. Our best-performing model used a weighted combination of local, site-specific habitat models. Our habitat maps identified large areas of suitable, but currently unoccupied lynx habitat, with many of the most suitable unoccupied areas located in regions that could foster connectivity between currently isolated populations.Main Conclusions We demonstrate that global and local modelling strategies can achieve robust habitat models at the continental scale and that considering regional variation in habitat selection improves broad-scale habitat mapping. More generally, we highlight the promise of large wildlife tracking databases for large-area habitat mapping. Our ... |
format |
Article in Journal/Newspaper |
author |
Andren, Henrik Persson, Jens |
author_facet |
Andren, Henrik Persson, Jens |
author_sort |
Andren, Henrik |
title |
Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat |
title_short |
Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat |
title_full |
Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat |
title_fullStr |
Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat |
title_full_unstemmed |
Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat |
title_sort |
integrating animal tracking datasets at a continental scale for mapping eurasian lynx habitat |
publishDate |
2023 |
url |
https://pub.epsilon.slu.se/32178/ https://pub.epsilon.slu.se/32178/1/oeser-j-et-al-20231116.pdf |
genre |
Lynx Lynx lynx lynx |
genre_facet |
Lynx Lynx lynx lynx |
op_relation |
https://pub.epsilon.slu.se/32178/1/oeser-j-et-al-20231116.pdf Andren, Henrik and Persson, Jens (2023). Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat. Diversity and Distributions. 29 :12 , 1546-1560 [Research article] |
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1785577020150775808 |