An AI‐based platform to investigate African large carnivore dispersal and demography across broad landscapes: A case study and future directions using African wild dogs

Understanding dispersal patterns and demographic processes is crucial for the development of evidence‐based conservation practices. Obtaining such information relies on the ability to identify and track individuals across spatial and temporal scales relevant to the life‐history events under investig...

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Published inAfrican journal of ecology Vol. 62; no. 1
Main Authors Cozzi, Gabriele, Reilly, Maureen, Abegg, Daniela, Behr, Dominik M., Brack, Peter, Claase, Megan J., Holmberg, Jason, Hofmann, David D., Kalil, Paul, Ndlovu, Sichelesile, Neelo, John, McNutt, John Weldon
Format Journal Article
LanguageEnglish
Published Nairobi Blackwell Publishing Ltd 01.01.2024
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Online AccessGet full text
ISSN0141-6707
1365-2028
DOI10.1111/aje.13227

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Abstract Understanding dispersal patterns and demographic processes is crucial for the development of evidence‐based conservation practices. Obtaining such information relies on the ability to identify and track individuals across spatial and temporal scales relevant to the life‐history events under investigation. This knowledge can be achieved by combining photographic and sighting data collected by various sources with a high accuracy automated individual identification platform. Here, we present the African Carnivore Wildbook (ACW), an AI‐based graphical user interface tool capable of identifying individuals of several African carnivore species and specifically developed to accommodate the above outlined needs. We showcase the ACW functionality using the endangered African wild dog as an example. Pictures collected over an area >56,000 km2 and submitted to ACW allowed inferences on movement patterns and dispersal at regional and international scales; for instance, transboundary dispersal events >200 km were documented. ACW furthermore enabled monitoring some individuals for >4 years; such information is invaluable for reliable survival analyses. We discuss how the ACW can contribute to data collection at appropriate spatial and temporal scales to support population monitoring, scientific research and management of African wild dogs and other apex carnivores and to the conservation of these charismatic species. Résumé Le développement de pratiques de conservation fondées sur des données probantes passe par la compréhension des schémas de dispersion et des processus démographiques. L'obtention de ces informations repose sur la capacité d'identifier et de suivre les individus sur des échelles spatiales et temporelles correspondant aux événements de l'histoire de la vie étudiés. Ces connaissances peuvent être acquises en combinant les données photographiques et d'observation recueillies par diverses sources avec une plate‐forme d'identification individuelle automatisée de haute précision. Le présent document présente l'African Carnivore Wildbook (ACW), un outil d'interface utilisateur graphique basé sur l'IA, capable d'identifier les individus de plusieurs espèces de carnivores africains et spécifiquement développé pour répondre aux besoins décrits ci‐dessus. La fonctionnalité de l'ACW est illustrée par l'exemple du dingo africain, une espèce en voie de disparition. Grâce aux images collectées sur une zone de plus de 56 000 km2 et soumises à l'ACW, il a été possible de déduire des schémas de déplacement et de dispersion à l'échelle régionale et internationale; par exemple, des événements de dispersion transfrontalière de plus de 200 km ont été documentés. En outre, l’ACW a permis de suivre certains individus pendant plus de 4 ans; ces informations sont inestimables pour des analyses de survie fiables. Nous examinons les possibilités de contribution de l'ACW à la collecte de données à des échelles spatiales et temporelles appropriées pour soutenir le suivi des populations, la recherche scientifique et la gestion des dingos africains et d'autres carnivores de premier plan, ainsi que la conservation de ces espèces charismatiques.
AbstractList Understanding dispersal patterns and demographic processes is crucial for the development of evidence‐based conservation practices. Obtaining such information relies on the ability to identify and track individuals across spatial and temporal scales relevant to the life‐history events under investigation. This knowledge can be achieved by combining photographic and sighting data collected by various sources with a high accuracy automated individual identification platform. Here, we present the African Carnivore Wildbook (ACW), an AI‐based graphical user interface tool capable of identifying individuals of several African carnivore species and specifically developed to accommodate the above outlined needs. We showcase the ACW functionality using the endangered African wild dog as an example. Pictures collected over an area >56,000 km 2 and submitted to ACW allowed inferences on movement patterns and dispersal at regional and international scales; for instance, transboundary dispersal events >200 km were documented. ACW furthermore enabled monitoring some individuals for >4 years; such information is invaluable for reliable survival analyses. We discuss how the ACW can contribute to data collection at appropriate spatial and temporal scales to support population monitoring, scientific research and management of African wild dogs and other apex carnivores and to the conservation of these charismatic species. Le développement de pratiques de conservation fondées sur des données probantes passe par la compréhension des schémas de dispersion et des processus démographiques. L'obtention de ces informations repose sur la capacité d'identifier et de suivre les individus sur des échelles spatiales et temporelles correspondant aux événements de l'histoire de la vie étudiés. Ces connaissances peuvent être acquises en combinant les données photographiques et d'observation recueillies par diverses sources avec une plate‐forme d'identification individuelle automatisée de haute précision. Le présent document présente l' African Carnivore Wildbook (ACW), un outil d'interface utilisateur graphique basé sur l'IA, capable d'identifier les individus de plusieurs espèces de carnivores africains et spécifiquement développé pour répondre aux besoins décrits ci‐dessus. La fonctionnalité de l'ACW est illustrée par l'exemple du dingo africain, une espèce en voie de disparition. Grâce aux images collectées sur une zone de plus de 56 000 km2 et soumises à l'ACW, il a été possible de déduire des schémas de déplacement et de dispersion à l'échelle régionale et internationale; par exemple, des événements de dispersion transfrontalière de plus de 200 km ont été documentés. En outre, l’ACW a permis de suivre certains individus pendant plus de 4 ans; ces informations sont inestimables pour des analyses de survie fiables. Nous examinons les possibilités de contribution de l'ACW à la collecte de données à des échelles spatiales et temporelles appropriées pour soutenir le suivi des populations, la recherche scientifique et la gestion des dingos africains et d'autres carnivores de premier plan, ainsi que la conservation de ces espèces charismatiques.
Understanding dispersal patterns and demographic processes is crucial for the development of evidence‐based conservation practices. Obtaining such information relies on the ability to identify and track individuals across spatial and temporal scales relevant to the life‐history events under investigation. This knowledge can be achieved by combining photographic and sighting data collected by various sources with a high accuracy automated individual identification platform. Here, we present the African Carnivore Wildbook (ACW), an AI‐based graphical user interface tool capable of identifying individuals of several African carnivore species and specifically developed to accommodate the above outlined needs. We showcase the ACW functionality using the endangered African wild dog as an example. Pictures collected over an area >56,000 km2 and submitted to ACW allowed inferences on movement patterns and dispersal at regional and international scales; for instance, transboundary dispersal events >200 km were documented. ACW furthermore enabled monitoring some individuals for >4 years; such information is invaluable for reliable survival analyses. We discuss how the ACW can contribute to data collection at appropriate spatial and temporal scales to support population monitoring, scientific research and management of African wild dogs and other apex carnivores and to the conservation of these charismatic species. Résumé Le développement de pratiques de conservation fondées sur des données probantes passe par la compréhension des schémas de dispersion et des processus démographiques. L'obtention de ces informations repose sur la capacité d'identifier et de suivre les individus sur des échelles spatiales et temporelles correspondant aux événements de l'histoire de la vie étudiés. Ces connaissances peuvent être acquises en combinant les données photographiques et d'observation recueillies par diverses sources avec une plate‐forme d'identification individuelle automatisée de haute précision. Le présent document présente l'African Carnivore Wildbook (ACW), un outil d'interface utilisateur graphique basé sur l'IA, capable d'identifier les individus de plusieurs espèces de carnivores africains et spécifiquement développé pour répondre aux besoins décrits ci‐dessus. La fonctionnalité de l'ACW est illustrée par l'exemple du dingo africain, une espèce en voie de disparition. Grâce aux images collectées sur une zone de plus de 56 000 km2 et soumises à l'ACW, il a été possible de déduire des schémas de déplacement et de dispersion à l'échelle régionale et internationale; par exemple, des événements de dispersion transfrontalière de plus de 200 km ont été documentés. En outre, l’ACW a permis de suivre certains individus pendant plus de 4 ans; ces informations sont inestimables pour des analyses de survie fiables. Nous examinons les possibilités de contribution de l'ACW à la collecte de données à des échelles spatiales et temporelles appropriées pour soutenir le suivi des populations, la recherche scientifique et la gestion des dingos africains et d'autres carnivores de premier plan, ainsi que la conservation de ces espèces charismatiques.
Understanding dispersal patterns and demographic processes is crucial for the development of evidence‐based conservation practices. Obtaining such information relies on the ability to identify and track individuals across spatial and temporal scales relevant to the life‐history events under investigation. This knowledge can be achieved by combining photographic and sighting data collected by various sources with a high accuracy automated individual identification platform. Here, we present the African Carnivore Wildbook (ACW), an AI‐based graphical user interface tool capable of identifying individuals of several African carnivore species and specifically developed to accommodate the above outlined needs. We showcase the ACW functionality using the endangered African wild dog as an example. Pictures collected over an area >56,000 km² and submitted to ACW allowed inferences on movement patterns and dispersal at regional and international scales; for instance, transboundary dispersal events >200 km were documented. ACW furthermore enabled monitoring some individuals for >4 years; such information is invaluable for reliable survival analyses. We discuss how the ACW can contribute to data collection at appropriate spatial and temporal scales to support population monitoring, scientific research and management of African wild dogs and other apex carnivores and to the conservation of these charismatic species.
Understanding dispersal patterns and demographic processes is crucial for the development of evidence‐based conservation practices. Obtaining such information relies on the ability to identify and track individuals across spatial and temporal scales relevant to the life‐history events under investigation. This knowledge can be achieved by combining photographic and sighting data collected by various sources with a high accuracy automated individual identification platform. Here, we present the African Carnivore Wildbook (ACW), an AI‐based graphical user interface tool capable of identifying individuals of several African carnivore species and specifically developed to accommodate the above outlined needs. We showcase the ACW functionality using the endangered African wild dog as an example. Pictures collected over an area >56,000 km2 and submitted to ACW allowed inferences on movement patterns and dispersal at regional and international scales; for instance, transboundary dispersal events >200 km were documented. ACW furthermore enabled monitoring some individuals for >4 years; such information is invaluable for reliable survival analyses. We discuss how the ACW can contribute to data collection at appropriate spatial and temporal scales to support population monitoring, scientific research and management of African wild dogs and other apex carnivores and to the conservation of these charismatic species.
Author Behr, Dominik M.
Ndlovu, Sichelesile
Neelo, John
McNutt, John Weldon
Hofmann, David D.
Holmberg, Jason
Reilly, Maureen
Kalil, Paul
Claase, Megan J.
Cozzi, Gabriele
Brack, Peter
Abegg, Daniela
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Snippet Understanding dispersal patterns and demographic processes is crucial for the development of evidence‐based conservation practices. Obtaining such information...
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SubjectTerms African Carnivore Wildbook
Carnivores
case studies
citizen science
Conservation
Conservation practices
Data collection
Demography
Dispersal
Dispersion
Dogs
Graphical user interface
HotSpotter
inter‐institutional collaboration
Kavango‐Zambesi Transfrontier Conservation Area
life history
long‐distance dispersal
Lycaon pictus
Monitoring
open source
pattern identification algorithm
transboundary
user interface
wildlife
Title An AI‐based platform to investigate African large carnivore dispersal and demography across broad landscapes: A case study and future directions using African wild dogs
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Faje.13227
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