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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Format: | Article in Journal/Newspaper |
Language: | English |
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Blackwell Science.
2023
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ftuniljubljanair:oai:repozitorij.uni-lj.si:IzpisGradiva.php-id-151701 2024-09-15T18:41:46+00:00 Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat Oeser, Julian Heurich, Marco Kramer-Schadt, Stephanie Mattisson, Jenny Krofel, Miha Krojerová-Prokešová, Jarmila Zimmermann, Fridolin Anders, Ole Andrén, Henrik Bagrade, Guna Černe, Rok Oliveira, Teresa Pagon, Nives 2023-01-01 text/url application/pdf https://repozitorij.uni-lj.si/IzpisGradiva.php?id=151701 https://repozitorij.uni-lj.si/Dokument.php?id=176735&dn= https://repozitorij.uni-lj.si/Dokument.php?id=177702&dn= https://plus.cobiss.net/cobiss/si/sl/bib/168776195 https://hdl.handle.net/20.500.12556/RUL-151701 eng eng Blackwell Science. info:eu-repo/semantics/altIdentifier/doi/10.1111/ddi.13784 https://repozitorij.uni-lj.si/IzpisGradiva.php?id=151701 https://repozitorij.uni-lj.si/Dokument.php?id=176735&dn= https://repozitorij.uni-lj.si/Dokument.php?id=177702&dn= https://plus.cobiss.net/cobiss/si/sl/bib/168776195 http://hdl.handle.net/20.500.12556/RUL-151701 http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Diversity and distributions, vol. 29, no. 12, pp. 1546-1560, 2023. ISSN: 1472-4642 nimal tracking Eurasian lynx habitat suitability large carnivore large-area mapping Lynx lynx sledenje živalim evrazijski ris primernost habitata velike zveri kartiranje info:eu-repo/classification/udc/630*15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2023 ftuniljubljanair https://doi.org/20.500.12556/RUL-15170110.1111/ddi.13784 2024-08-22T06:53:13Z 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). Location Europe. 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. ... Article in Journal/Newspaper Lynx Lynx lynx lynx Repository of the University of Ljubljana (RUL) Diversity and Distributions 29 12 1546 1560 |
institution |
Open Polar |
collection |
Repository of the University of Ljubljana (RUL) |
op_collection_id |
ftuniljubljanair |
language |
English |
topic |
nimal tracking Eurasian lynx habitat suitability large carnivore large-area mapping Lynx lynx sledenje živalim evrazijski ris primernost habitata velike zveri kartiranje info:eu-repo/classification/udc/630*15 |
spellingShingle |
nimal tracking Eurasian lynx habitat suitability large carnivore large-area mapping Lynx lynx sledenje živalim evrazijski ris primernost habitata velike zveri kartiranje info:eu-repo/classification/udc/630*15 Oeser, Julian Heurich, Marco Kramer-Schadt, Stephanie Mattisson, Jenny Krofel, Miha Krojerová-Prokešová, Jarmila Zimmermann, Fridolin Anders, Ole Andrén, Henrik Bagrade, Guna Černe, Rok Oliveira, Teresa Pagon, Nives Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat |
topic_facet |
nimal tracking Eurasian lynx habitat suitability large carnivore large-area mapping Lynx lynx sledenje živalim evrazijski ris primernost habitata velike zveri kartiranje info:eu-repo/classification/udc/630*15 |
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). Location Europe. 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. ... |
format |
Article in Journal/Newspaper |
author |
Oeser, Julian Heurich, Marco Kramer-Schadt, Stephanie Mattisson, Jenny Krofel, Miha Krojerová-Prokešová, Jarmila Zimmermann, Fridolin Anders, Ole Andrén, Henrik Bagrade, Guna Černe, Rok Oliveira, Teresa Pagon, Nives |
author_facet |
Oeser, Julian Heurich, Marco Kramer-Schadt, Stephanie Mattisson, Jenny Krofel, Miha Krojerová-Prokešová, Jarmila Zimmermann, Fridolin Anders, Ole Andrén, Henrik Bagrade, Guna Černe, Rok Oliveira, Teresa Pagon, Nives |
author_sort |
Oeser, Julian |
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 |
publisher |
Blackwell Science. |
publishDate |
2023 |
url |
https://repozitorij.uni-lj.si/IzpisGradiva.php?id=151701 https://repozitorij.uni-lj.si/Dokument.php?id=176735&dn= https://repozitorij.uni-lj.si/Dokument.php?id=177702&dn= https://plus.cobiss.net/cobiss/si/sl/bib/168776195 https://hdl.handle.net/20.500.12556/RUL-151701 |
genre |
Lynx Lynx lynx lynx |
genre_facet |
Lynx Lynx lynx lynx |
op_source |
Diversity and distributions, vol. 29, no. 12, pp. 1546-1560, 2023. ISSN: 1472-4642 |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1111/ddi.13784 https://repozitorij.uni-lj.si/IzpisGradiva.php?id=151701 https://repozitorij.uni-lj.si/Dokument.php?id=176735&dn= https://repozitorij.uni-lj.si/Dokument.php?id=177702&dn= https://plus.cobiss.net/cobiss/si/sl/bib/168776195 http://hdl.handle.net/20.500.12556/RUL-151701 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/20.500.12556/RUL-15170110.1111/ddi.13784 |
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Diversity and Distributions |
container_volume |
29 |
container_issue |
12 |
container_start_page |
1546 |
op_container_end_page |
1560 |
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