Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat

  1. Oeser, Julian ORCID logo
  2. Heurich, Marco
  3. Kramer‐Schadt, Stephanie
  4. Mattisson, Jenny
  5. Krofel, Miha ORCID logo
  6. Krojerová‐Prokešová, Jarmila
  7. Zimmermann, Fridolin
  8. Anders, Ole
  9. Andrén, Henrik
  10. Bagrade, Guna
  11. Belotti, Elisa
  12. Breitenmoser‐Würsten, Christine
  13. Bufka, Luděk
  14. Černe, Rok
  15. Drouet‐Hoguet, Nolwenn
  16. Duľa, Martin
  17. Fuxjäger, Christian
  18. Gomerčić, Tomislav
  19. Jędrzejewski, Włodzimierz
  20. Kont, Raido
  21. Koubek, Petr
  22. Kowalczyk, Rafał
  23. Kusak, Josip
  24. Kubala, Jakub
  25. Kutal, Miroslav
  26. Linnell, John D. C.
  27. Molinari‐Jobin, Anja
  28. Männil, Peep
  29. Middelhoff, Tomma Lilli
  30. Odden, John
  31. Okarma, Henryk
  32. Oliveira, Teresa
  33. Pagon, Nives
  34. Persson, Jens
  35. Remm, Jaanus
  36. Schmidt, Krzysztof
  37. Signer, Sven
  38. Tám, Branislav
  39. Vogt, Kristina
  40. Kuemmerle, Tobias

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WeightNameValue
1000 Titel
  • Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat
1000 Autor/in
  1. Oeser, Julian |
  2. Heurich, Marco |
  3. Kramer‐Schadt, Stephanie |
  4. Mattisson, Jenny |
  5. Krofel, Miha |
  6. Krojerová‐Prokešová, Jarmila |
  7. Zimmermann, Fridolin |
  8. Anders, Ole |
  9. Andrén, Henrik |
  10. Bagrade, Guna |
  11. Belotti, Elisa |
  12. Breitenmoser‐Würsten, Christine |
  13. Bufka, Luděk |
  14. Černe, Rok |
  15. Drouet‐Hoguet, Nolwenn |
  16. Duľa, Martin |
  17. Fuxjäger, Christian |
  18. Gomerčić, Tomislav |
  19. Jędrzejewski, Włodzimierz |
  20. Kont, Raido |
  21. Koubek, Petr |
  22. Kowalczyk, Rafał |
  23. Kusak, Josip |
  24. Kubala, Jakub |
  25. Kutal, Miroslav |
  26. Linnell, John D. C. |
  27. Molinari‐Jobin, Anja |
  28. Männil, Peep |
  29. Middelhoff, Tomma Lilli |
  30. Odden, John |
  31. Okarma, Henryk |
  32. Oliveira, Teresa |
  33. Pagon, Nives |
  34. Persson, Jens |
  35. Remm, Jaanus |
  36. Schmidt, Krzysztof |
  37. Signer, Sven |
  38. Tám, Branislav |
  39. Vogt, Kristina |
  40. Kuemmerle, Tobias |
1000 Erscheinungsjahr 2023
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2023-10-16
1000 Erschienen in
1000 Quellenangabe
  • 29(12):1546-1560
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2023
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1111/ddi.13784 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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. Our maps provide the first high-resolution, yet continental assessment of lynx habitat across Europe, providing a consistent basis for conservation planning for restoring the species within its former range.
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
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1000 Label
1000 Förderer
  1. Projekt DEAL |
  2. Federal State of Berlin |
1000 Fördernummer
  1. -
  2. -
1000 Förderprogramm
  1. Open Access funding
  2. Elsa-Neumann scholarship
1000 Dateien
  1. Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat
    Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Projekt DEAL |
    1000 Förderprogramm Open Access funding
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Federal State of Berlin |
    1000 Förderprogramm Elsa-Neumann scholarship
    1000 Fördernummer -
1000 Objektart article
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1000 @id frl:6482787.rdf
1000 Erstellt am 2024-05-28T16:07:18.094+0200
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1000 Bearbeitet von 317
1000 Zuletzt bearbeitet Wed Jun 19 09:42:14 CEST 2024
1000 Objekt bearb. Wed Jun 19 09:00:32 CEST 2024
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