Predicting kill sites of an apex predator from GPS data in different multiprey systems
Kill rates are a central parameter to assess the impact of predation on prey species. An accurate estimation of kill rates requires a correct identification of kill sites, often achieved by field-checking GPS location clusters (GLCs). However, there are potential sources of error included in kill-si...
Published in: | Ecological Applications |
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Language: | English |
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Ecological Society of America, Wiley
2023
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Online Access: | https://repozitorij.uni-lj.si/IzpisGradiva.php?id=145000 https://repozitorij.uni-lj.si/Dokument.php?id=167615&dn= https://repozitorij.uni-lj.si/Dokument.php?id=167614&dn= https://plus.cobiss.net/cobiss/si/sl/bib/130503171 https://hdl.handle.net/20.500.12556/RUL-145000 |
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ftuniljubljanair:oai:repozitorij.uni-lj.si:IzpisGradiva.php-id-145000 2024-09-15T18:41:47+00:00 Predicting kill sites of an apex predator from GPS data in different multiprey systems Oliveira, Teresa Carricondo-Sanchez, David Mattisson, Jenny Vogt, Kristina Corradini, Andrea Linnell, John D. C. Odden, John Heurich, Marco Rodriguez Recio, Mariano Krofel, Miha 2023-03-29 application/pdf text/url https://repozitorij.uni-lj.si/IzpisGradiva.php?id=145000 https://repozitorij.uni-lj.si/Dokument.php?id=167615&dn= https://repozitorij.uni-lj.si/Dokument.php?id=167614&dn= https://plus.cobiss.net/cobiss/si/sl/bib/130503171 https://hdl.handle.net/20.500.12556/RUL-145000 eng eng Ecological Society of America, Wiley info:eu-repo/semantics/altIdentifier/doi/10.1002/eap.2778 https://repozitorij.uni-lj.si/IzpisGradiva.php?id=145000 https://repozitorij.uni-lj.si/Dokument.php?id=167615&dn= https://repozitorij.uni-lj.si/Dokument.php?id=167614&dn= https://plus.cobiss.net/cobiss/si/sl/bib/130503171 http://hdl.handle.net/20.500.12556/RUL-145000 http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Ecological applications, vol. 33, no. 2, e2778, 2023. ISSN: 1939-5582 GPS location clusters GPS-fix schedule kill sites random forest Eurasian lynx domestic prey GLCs multiprey system GPS klastri GPS telemetrije plenjenje evrazijski ris domače živali škoda po divjadi info:eu-repo/classification/udc/630*156 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2023 ftuniljubljanair https://doi.org/20.500.12556/RUL-14500010.1002/eap.2778 2024-08-22T06:53:12Z Kill rates are a central parameter to assess the impact of predation on prey species. An accurate estimation of kill rates requires a correct identification of kill sites, often achieved by field-checking GPS location clusters (GLCs). However, there are potential sources of error included in kill-site identification, such as failing to detect GLCs that are kill sites, and misclassifying the generated GLCs (e.g., kill for nonkill) that were not field checked. Here, we address these two sources of error using a large GPS dataset of collared Eurasian lynx (Lynx lynx), an apex predator of conservation concern in Europe, in three multiprey systems, with different combinations of wild, semidomestic, and domestic prey. We first used a subsampling approach to investigate how different GPS-fix schedules affected the detection of GLC-indicated kill sites. Then, we evaluated the potential of the random forest algorithm to classify GLCs as nonkills, small prey kills, and ungulate kills. We show that the number of fixes can be reduced from seven to three fixes per night without missing more than 5% of the ungulate kills, in a system composed of wild prey. Reducing the number of fixes per 24 h decreased the probability of detecting GLCs connected with kill sites, particularly those of semidomestic or domestic prey, and small prey. Random forest successfully predicted between 73%–90% of ungulate kills, but failed to classify most small prey in all systems, with sensitivity (true positive rate) lower than 65%. Additionally, removing domestic prey improved the algorithm’s overall accuracy. We provide a set of recommendations for studies focusing on kill-site detection that can be considered for other large carnivore species in addition to the Eurasian lynx. We recommend caution when working in systems including domestic prey, as the odds of underestimating kill rates are higher. Article in Journal/Newspaper Lynx Lynx lynx lynx Repository of the University of Ljubljana (RUL) Ecological Applications 33 2 |
institution |
Open Polar |
collection |
Repository of the University of Ljubljana (RUL) |
op_collection_id |
ftuniljubljanair |
language |
English |
topic |
GPS location clusters GPS-fix schedule kill sites random forest Eurasian lynx domestic prey GLCs multiprey system GPS klastri GPS telemetrije plenjenje evrazijski ris domače živali škoda po divjadi info:eu-repo/classification/udc/630*156 |
spellingShingle |
GPS location clusters GPS-fix schedule kill sites random forest Eurasian lynx domestic prey GLCs multiprey system GPS klastri GPS telemetrije plenjenje evrazijski ris domače živali škoda po divjadi info:eu-repo/classification/udc/630*156 Oliveira, Teresa Carricondo-Sanchez, David Mattisson, Jenny Vogt, Kristina Corradini, Andrea Linnell, John D. C. Odden, John Heurich, Marco Rodriguez Recio, Mariano Krofel, Miha Predicting kill sites of an apex predator from GPS data in different multiprey systems |
topic_facet |
GPS location clusters GPS-fix schedule kill sites random forest Eurasian lynx domestic prey GLCs multiprey system GPS klastri GPS telemetrije plenjenje evrazijski ris domače živali škoda po divjadi info:eu-repo/classification/udc/630*156 |
description |
Kill rates are a central parameter to assess the impact of predation on prey species. An accurate estimation of kill rates requires a correct identification of kill sites, often achieved by field-checking GPS location clusters (GLCs). However, there are potential sources of error included in kill-site identification, such as failing to detect GLCs that are kill sites, and misclassifying the generated GLCs (e.g., kill for nonkill) that were not field checked. Here, we address these two sources of error using a large GPS dataset of collared Eurasian lynx (Lynx lynx), an apex predator of conservation concern in Europe, in three multiprey systems, with different combinations of wild, semidomestic, and domestic prey. We first used a subsampling approach to investigate how different GPS-fix schedules affected the detection of GLC-indicated kill sites. Then, we evaluated the potential of the random forest algorithm to classify GLCs as nonkills, small prey kills, and ungulate kills. We show that the number of fixes can be reduced from seven to three fixes per night without missing more than 5% of the ungulate kills, in a system composed of wild prey. Reducing the number of fixes per 24 h decreased the probability of detecting GLCs connected with kill sites, particularly those of semidomestic or domestic prey, and small prey. Random forest successfully predicted between 73%–90% of ungulate kills, but failed to classify most small prey in all systems, with sensitivity (true positive rate) lower than 65%. Additionally, removing domestic prey improved the algorithm’s overall accuracy. We provide a set of recommendations for studies focusing on kill-site detection that can be considered for other large carnivore species in addition to the Eurasian lynx. We recommend caution when working in systems including domestic prey, as the odds of underestimating kill rates are higher. |
format |
Article in Journal/Newspaper |
author |
Oliveira, Teresa Carricondo-Sanchez, David Mattisson, Jenny Vogt, Kristina Corradini, Andrea Linnell, John D. C. Odden, John Heurich, Marco Rodriguez Recio, Mariano Krofel, Miha |
author_facet |
Oliveira, Teresa Carricondo-Sanchez, David Mattisson, Jenny Vogt, Kristina Corradini, Andrea Linnell, John D. C. Odden, John Heurich, Marco Rodriguez Recio, Mariano Krofel, Miha |
author_sort |
Oliveira, Teresa |
title |
Predicting kill sites of an apex predator from GPS data in different multiprey systems |
title_short |
Predicting kill sites of an apex predator from GPS data in different multiprey systems |
title_full |
Predicting kill sites of an apex predator from GPS data in different multiprey systems |
title_fullStr |
Predicting kill sites of an apex predator from GPS data in different multiprey systems |
title_full_unstemmed |
Predicting kill sites of an apex predator from GPS data in different multiprey systems |
title_sort |
predicting kill sites of an apex predator from gps data in different multiprey systems |
publisher |
Ecological Society of America, Wiley |
publishDate |
2023 |
url |
https://repozitorij.uni-lj.si/IzpisGradiva.php?id=145000 https://repozitorij.uni-lj.si/Dokument.php?id=167615&dn= https://repozitorij.uni-lj.si/Dokument.php?id=167614&dn= https://plus.cobiss.net/cobiss/si/sl/bib/130503171 https://hdl.handle.net/20.500.12556/RUL-145000 |
genre |
Lynx Lynx lynx lynx |
genre_facet |
Lynx Lynx lynx lynx |
op_source |
Ecological applications, vol. 33, no. 2, e2778, 2023. ISSN: 1939-5582 |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1002/eap.2778 https://repozitorij.uni-lj.si/IzpisGradiva.php?id=145000 https://repozitorij.uni-lj.si/Dokument.php?id=167615&dn= https://repozitorij.uni-lj.si/Dokument.php?id=167614&dn= https://plus.cobiss.net/cobiss/si/sl/bib/130503171 http://hdl.handle.net/20.500.12556/RUL-145000 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/20.500.12556/RUL-14500010.1002/eap.2778 |
container_title |
Ecological Applications |
container_volume |
33 |
container_issue |
2 |
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1810486159074131968 |