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Davidson SC, Cagnacci F, Newman P, Dettki H, Urbano F, Desmet P, Bajona L, Bryant E, Carneiro APB, Dias MP, Fujioka E, Gambin D, Hoenner X, Hunter C, Kato A, Kot CY, Kranstauber B, Lam CH, Lepage D, Naik H, Pye JD, Sequeira AMM, Tsontos VM, van Loon E, Vo D, Rutz C. Establishing bio-logging data collections as dynamic archives of animal life on Earth. Nat Ecol Evol 2025; 9:204-213. [PMID: 39753915 DOI: 10.1038/s41559-024-02585-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 10/15/2024] [Indexed: 01/23/2025]
Abstract
Rapid growth in bio-logging-the use of animal-borne electronic tags to document the movements, behaviour, physiology and environments of wildlife-offers opportunities to mitigate biodiversity threats and expand digital natural history archives. Here we present a vision to achieve such benefits by accounting for the heterogeneity inherent to bio-logging data and the concerns of those who collect and use them. First, we can enable data integration through standard vocabularies, transfer protocols and aggregation protocols, and drive their wide adoption. Second, we need to develop integrated data collections on standardized data platforms that support data preservation through public archiving and strategies that ensure long-term access. We outline pathways to reach these goals, highlighting the need for resources to govern community data standards and guide data mobilization efforts. We propose the launch of a community-led coordinating body and provide recommendations for how stakeholders-including government data centres, museums and those who fund, permit and publish bio-logging work-can support these efforts.
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Affiliation(s)
- Sarah C Davidson
- Department Animal Migration, Max Planck Institute of Animal Behavior, Radolfzell, Germany.
- Department of Biology, University of Konstanz, Konstanz, Germany.
- Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA.
| | - Francesca Cagnacci
- Animal Ecology Unit, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all' Adige, Italy.
- National Biodiversity Future Center (NBFC), Palermo, Italy.
| | - Peggy Newman
- Atlas of Living Australia, CSIRO, Canberra, Australian Capital Territory, Australia
| | - Holger Dettki
- Swedish Species Information Centre, Swedish University of Agricultural Sciences, Uppsala, Sweden
- Wireless Remote Animal Monitoring, Swedish University of Agricultural Sciences, Umeå, Sweden
| | | | - Peter Desmet
- Research Institute for Nature and Forest (INBO), Brussels, Belgium
| | - Lenore Bajona
- Ocean Tracking Network, Dalhousie University, Halifax, Nova Scotia, Canada
- Medical Research Development Office, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Edmund Bryant
- Wildlife Computers, Redmond, WA, USA
- Wildtrack Telemetry Systems Ltd, Skipton, UK
| | | | - Maria P Dias
- CE3C - Centre for Ecology, Evolution and Environmental Changes & CHANGE - Global Change and Sustainability Institute, Department of Animal Biology, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal
| | - Ei Fujioka
- Marine Geospatial Ecology Lab, Nicholas School of the Environment, Duke University, Durham, NC, USA
| | | | - Xavier Hoenner
- Australian Ocean Data Network, Integrated Marine Observing System, University of Tasmania, Hobart, Tasmania, Australia
| | | | - Akiko Kato
- Centre d'Etudes Biologiques de Chizé, CNRS - La Rochelle Université, Villiers-en-Bois, France
| | - Connie Y Kot
- Marine Geospatial Ecology Lab, Nicholas School of the Environment, Duke University, Durham, NC, USA
- U.S. Integrated Ocean Observing System Program Office, National Ocean Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
| | - Bart Kranstauber
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, the Netherlands
| | - Chi Hin Lam
- Large Pelagics Research Center, Gloucester, MA, USA
- Big Fish Intelligence Company Limited, Hong Kong SAR, China
| | | | - Hemal Naik
- Department of Ecology of Animal Societies, Max Planck Institute of Animal Behaviour, Radolfzell, Germany
- Centre of the Advanced Study of Collective Behavior, University of Konstanz, Konstanz, Germany
| | - Jonathan D Pye
- Ocean Tracking Network, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Ana M M Sequeira
- Division of Ecology and Evolution, Research School of Biology, The Australian National University, Canberra, Australian Capital Territory, Australia
- UWA Oceans Institute and School of Biological Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Vardis M Tsontos
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Emiel van Loon
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, the Netherlands
| | - Danny Vo
- Wildlife Computers, Redmond, WA, USA
| | - Christian Rutz
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, UK.
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Broekman MJE, Hilbers JP, Tucker MA, Huijbregts MAJ, Schipper AM. Impacts of existing and planned roads on terrestrial mammal habitat in New Guinea. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024; 38:e14152. [PMID: 37551763 DOI: 10.1111/cobi.14152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 04/26/2023] [Accepted: 07/03/2023] [Indexed: 08/09/2023]
Abstract
New Guinea is one of the last regions in the world with vast pristine areas and is home to many endemic species. However, extensive road development plans threaten the island's biodiversity. We quantified habitat fragmentation due to existing and planned roads for 139 terrestrial mammal species in New Guinea. For each species, we calculated the equivalent connected area (ECA) of habitat, a metric that takes into account the area and connectivity of habitat patches in 3 situations: no roads (baseline situation), existing roads (current), and existing and planned roads combined (future). We assessed the effect of roads as the proportion of the ECA remaining in the current and future situations relative to the baseline. To examine whether there were patterns in these relative ECA values, we fitted beta-regression models relating these values to 4 species characteristics: taxonomic order, body mass, diet, and International Union for the Conservation of Nature Red List status. On average across species, current ECA was 89% (SD 12) of baseline ECA. Shawmayer's coccymys (Coccymys shawmayeri) had the lowest amount of current ECA relative to the baseline (53%). In the future situation, the average remaining ECA was 71% (SD 20) of baseline ECA. Future remaining ECA was below 50% of the baseline for 28 species. The montane soft-furred paramelomys (Paramelomys mollis) had the lowest future ECA relative to the baseline (36%). In general, currently nonthreatened carnivorous species with a large body mass had the greatest reductions of ECA in the future situation. In conclusion, future road development plans imply extensive additional habitat fragmentation for a large number of terrestrial mammal species in New Guinea. It is therefore important to limit the impact of planned roads, for example, by reconsidering the location of planned roads that intersect habitat of the most threatened species, or by the implementation of mitigation measures such as underpasses.
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Affiliation(s)
- Maarten J E Broekman
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences, Radboud University, Nijmegen, The Netherlands
| | - Jelle P Hilbers
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences, Radboud University, Nijmegen, The Netherlands
| | - Marlee A Tucker
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences, Radboud University, Nijmegen, The Netherlands
| | - Mark A J Huijbregts
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences, Radboud University, Nijmegen, The Netherlands
| | - Aafke M Schipper
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences, Radboud University, Nijmegen, The Netherlands
- PBL Netherlands Environmental Assessment Agency, The Hague, The Netherlands
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Hurtado C, Hemming V, Burton C. Comparing wildlife habitat suitability models based on expert opinion with camera trap detections. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2023; 37:e14113. [PMID: 37204011 DOI: 10.1111/cobi.14113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 03/21/2023] [Accepted: 05/11/2023] [Indexed: 05/20/2023]
Abstract
Expert knowledge is used in the development of wildlife habitat suitability models (HSMs) for management and conservation decisions. However, the consistency of such models has been questioned. Focusing on 1 method for elicitation, the analytic hierarchy process, we generated expert-based HSMs for 4 felid species: 2 forest specialists (ocelot [Leopardus pardalis] and margay [Leopardus wiedii]) and 2 habitat generalist species (Pampas cat [Leopardus colocola] and puma [Puma concolor]). Using these HSMs, species detections from camera-trap surveys, and generalized linear models, we assessed the effect of study species and expert attributes on the correspondence between expert models and camera-trap detections. We also examined whether aggregation of participant responses and iterative feedback improved model performance. We ran 160 HSMs and found that models for specialist species showed higher correspondence with camera-trap detections (AUC [area under the receiver operating characteristic curve] >0.7) than those for generalists (AUC < 0.7). Model correspondence increased as participant years of experience in the study area increased, but only for the understudied generalist species, Pampas cat (β = 0.024 [SE 0.007]). No other participant attribute was associated with model correspondence. Feedback and revision of models improved model correspondence, and aggregating judgments across multiple participants improved correspondence only for specialist species. The average correspondence of aggregated judgments increased as group size increased but leveled off after 5 experts for all species. Our results suggest that correspondence between expert models and empirical surveys increases as habitat specialization increases. We encourage inclusion of participants knowledgeable of the study area and model validation for expert-based modeling of understudied and generalist species.
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Affiliation(s)
- Cindy Hurtado
- Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada
- Centro de Investigación Biodiversidad Sostenible-BioS, Piura, Peru
| | - Victoria Hemming
- Department of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cole Burton
- Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada
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