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Integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement

BACKGROUND: Agricultural and pastoral landscapes can provide important habitat for wildlife conservation, but sharing these landscapes with wildlife can create conflict that is costly and requires managing. Livestock predation is a good example of the challenges involving coexistence with wildlife a...

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Autores principales: Breck, Stewart W., Schultz, Jeffrey T., Prause, David, Krebs, Cameron, Giordano, Anthony J., Boots, Byron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239614/
https://www.ncbi.nlm.nih.gov/pubmed/37283902
http://dx.doi.org/10.7717/peerj.15491
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author Breck, Stewart W.
Schultz, Jeffrey T.
Prause, David
Krebs, Cameron
Giordano, Anthony J.
Boots, Byron
author_facet Breck, Stewart W.
Schultz, Jeffrey T.
Prause, David
Krebs, Cameron
Giordano, Anthony J.
Boots, Byron
author_sort Breck, Stewart W.
collection PubMed
description BACKGROUND: Agricultural and pastoral landscapes can provide important habitat for wildlife conservation, but sharing these landscapes with wildlife can create conflict that is costly and requires managing. Livestock predation is a good example of the challenges involving coexistence with wildlife across shared landscapes. Integrating new technology into agricultural practices could help minimize human-wildlife conflict. In this study, we used concepts from the fields of robotics (i.e., automated movement and adaptiveness) and agricultural practices (i.e., managing livestock risk to predation) to explore how integration of these concepts could aid the development of more effective predator deterrents. METHODS: We used a colony of captive coyotes as a model system, and simulated predation events with meat baits inside and outside of protected zones. Inside the protected zones we used a remote-controlled vehicle with a state-of-the art, commercially available predator deterrent (i.e., Foxlight) mounted on the top and used this to test three treatments: (1) light only (i.e., without movement or adaptiveness), (2) predetermined movement (i.e., with movement and without adaptiveness), and (3) adaptive movement (i.e., with both movement and adaptiveness). We measured the time it took for coyotes to eat the baits and analyzed the data with a time-to-event survival strategy. RESULTS: Survival of baits was consistently higher inside the protected zone, and the three movement treatments incrementally increased survival time over baseline except for the light only treatment in the nonprotected zone. Incorporating predetermined movement essentially doubled the efficacy of the light only treatment both inside and outside the protected zone. Incorporating adaptive movement exponentially increased survival time both inside and outside the protected zone. Our findings provide compelling evidence that incorporating existing robotics capabilities (predetermined and adaptive movement) could greatly enhance protection of agricultural resources and aid in the development of nonlethal tools for managing wildlife. Our findings also demonstrate the importance of marrying agricultural practices (e.g., spatial management of livestock at night) with new technology to improve the efficacy of wildlife deterrents.
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spelling pubmed-102396142023-06-05 Integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement Breck, Stewart W. Schultz, Jeffrey T. Prause, David Krebs, Cameron Giordano, Anthony J. Boots, Byron PeerJ Agricultural Science BACKGROUND: Agricultural and pastoral landscapes can provide important habitat for wildlife conservation, but sharing these landscapes with wildlife can create conflict that is costly and requires managing. Livestock predation is a good example of the challenges involving coexistence with wildlife across shared landscapes. Integrating new technology into agricultural practices could help minimize human-wildlife conflict. In this study, we used concepts from the fields of robotics (i.e., automated movement and adaptiveness) and agricultural practices (i.e., managing livestock risk to predation) to explore how integration of these concepts could aid the development of more effective predator deterrents. METHODS: We used a colony of captive coyotes as a model system, and simulated predation events with meat baits inside and outside of protected zones. Inside the protected zones we used a remote-controlled vehicle with a state-of-the art, commercially available predator deterrent (i.e., Foxlight) mounted on the top and used this to test three treatments: (1) light only (i.e., without movement or adaptiveness), (2) predetermined movement (i.e., with movement and without adaptiveness), and (3) adaptive movement (i.e., with both movement and adaptiveness). We measured the time it took for coyotes to eat the baits and analyzed the data with a time-to-event survival strategy. RESULTS: Survival of baits was consistently higher inside the protected zone, and the three movement treatments incrementally increased survival time over baseline except for the light only treatment in the nonprotected zone. Incorporating predetermined movement essentially doubled the efficacy of the light only treatment both inside and outside the protected zone. Incorporating adaptive movement exponentially increased survival time both inside and outside the protected zone. Our findings provide compelling evidence that incorporating existing robotics capabilities (predetermined and adaptive movement) could greatly enhance protection of agricultural resources and aid in the development of nonlethal tools for managing wildlife. Our findings also demonstrate the importance of marrying agricultural practices (e.g., spatial management of livestock at night) with new technology to improve the efficacy of wildlife deterrents. PeerJ Inc. 2023-06-01 /pmc/articles/PMC10239614/ /pubmed/37283902 http://dx.doi.org/10.7717/peerj.15491 Text en © 2023 Breck et al. https://creativecommons.org/publicdomain/zero/1.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/publicdomain/zero/1.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Agricultural Science
Breck, Stewart W.
Schultz, Jeffrey T.
Prause, David
Krebs, Cameron
Giordano, Anthony J.
Boots, Byron
Integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement
title Integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement
title_full Integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement
title_fullStr Integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement
title_full_unstemmed Integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement
title_short Integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement
title_sort integrating robotics into wildlife conservation: testing improvements to predator deterrents through movement
topic Agricultural Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239614/
https://www.ncbi.nlm.nih.gov/pubmed/37283902
http://dx.doi.org/10.7717/peerj.15491
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