Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring
| Autor: | Mikael Åkesson, Joseph Chipperfield, Olivier Gimenez, Daniel Turek, Linn Svensson, J. Andrew Royle, Richard Bischof, Pierre Dupont, Perry de Valpine, Jonas Kindberg, Henrik Brøseth, Andrés Ordiz, Cyril Milleret, Mahdieh Tourani, Øystein Flagstad |
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| Přispěvatelé: | Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) |
| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
Zoology and botany: 480 [VDP] Population Dynamics Population Wildlife imperfect detection Animals Wild 010603 evolutionary biology 01 natural sciences Predation density surface vital rates Animals Carnivore Ursus education Zoologiske og botaniske fag: 480 [VDP] Apex predator Spatial Analysis education.field_of_study Multidisciplinary Ecology Geography biology 010604 marine biology & hydrobiology Statistics Biological Sciences Models Theoretical 15. Life on land biology.organism_classification Genetics Population 13. Climate action Predatory Behavior Physical Sciences [SDE]Environmental Sciences spatial capture–recapture noninvasive monitoring of large carnivores Vital rates Algorithms Genetic monitoring |
| Zdroj: | Proceedings of the National Academy of Sciences of the United States of America Proceedings of the National Academy of Sciences of the United States of America, 2020, 117 (48), pp.30531-30538. ⟨10.1073/pnas.2011383117⟩ Proceedings of the National Academy of Sciences of the United States of America, National Academy of Sciences, 2020, 117 (48), pp.30531-30538. ⟨10.1073/pnas.2011383117⟩ |
| ISSN: | 1091-6490 0027-8424 |
| DOI: | 10.1073/pnas.2011383117 |
| Popis: | Significance We are experiencing the accelerated loss and reconfiguration of biological diversity. Meanwhile, those charged with natural resource management are struggling to meet the challenges of monitoring and managing wildlife populations across vast areas crisscrossed by political borders. What if, akin to weather maps, we could track and forecast the dynamics of wildlife populations across space and time? Using the world’s most extensive large carnivore monitoring program, we showcase the application of an effective tool for spatially explicit quantification of wildlife population dynamics at scales that are relevant to management and conservation. The ongoing recovery of terrestrial large carnivores in North America and Europe is accompanied by intense controversy. On the one hand, reestablishment of large carnivores entails a recovery of their most important ecological role, predation. On the other hand, societies are struggling to relearn how to live with apex predators that kill livestock, compete for game species, and occasionally injure or kill people. Those responsible for managing these species and mitigating conflict often lack fundamental information due to a long-standing challenge in ecology: How do we draw robust population-level inferences for elusive animals spread over immense areas? Here we showcase the application of an effective tool for spatially explicit tracking and forecasting of wildlife population dynamics at scales that are relevant to management and conservation. We analyzed the world’s largest dataset on carnivores comprising more than 35,000 noninvasively obtained DNA samples from over 6,000 individual brown bears (Ursus arctos), gray wolves (Canis lupus), and wolverines (Gulo gulo). Our analyses took into account that not all individuals are detected and, even if detected, their fates are not always known. We show unequivocal quantitative evidence of large carnivore recovery in northern Europe, juxtaposed with the finding that humans are the single-most important factor driving the dynamics of these apex predators. We present maps and forecasts of the spatiotemporal dynamics of large carnivore populations, transcending national boundaries and management regimes. |
| Databáze: | OpenAIRE |
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