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Incorporating pyrodiversity into wildlife habitat assessments for rapid post-fire management: A woodpecker case study.
Stillman, Andrew N; Wilkerson, Robert L; Kaschube, Danielle R; Siegel, Rodney B; Sawyer, Sarah C; Tingley, Morgan W.
Afiliación
  • Stillman AN; Cornell Lab of Ornithology, Cornell University, Ithaca, New York, USA.
  • Wilkerson RL; Cornell Atkinson Center for Sustainability, Cornell University, Ithaca, New York, USA.
  • Kaschube DR; The Institute for Bird Populations, Petaluma, California, USA.
  • Siegel RB; The Institute for Bird Populations, Petaluma, California, USA.
  • Sawyer SC; The Institute for Bird Populations, Petaluma, California, USA.
  • Tingley MW; USDA Forest Service, Vallejo, California, USA.
Ecol Appl ; 33(4): e2853, 2023 06.
Article en En | MEDLINE | ID: mdl-36995347
ABSTRACT
Spatial and temporal variation in fire characteristics-termed pyrodiversity-are increasingly recognized as important factors that structure wildlife communities in fire-prone ecosystems, yet there have been few attempts to incorporate pyrodiversity or post-fire habitat dynamics into predictive models of animal distributions and abundance to support post-fire management. We use the black-backed woodpecker-a species associated with burned forests-as a case study to demonstrate a pathway for incorporating pyrodiversity into wildlife habitat assessments for adaptive management. Employing monitoring data (2009-2019) from post-fire forests in California, we developed three competing occupancy models describing different hypotheses for habitat associations (1) a static model representing an existing management tool, (2) a temporal model accounting for years since fire, and (3) a temporal-landscape model which additionally incorporates emerging evidence from field studies about the influence of pyrodiversity. Evaluating predictive ability, we found superior support for the temporal-landscape model, which showed a positive relationship between occupancy and pyrodiversity and interactions between habitat associations and years since fire. We incorporated the new temporal-landscape model into an RShiny application to make this decision-support tool accessible to decision-makers.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ecosistema / Incendios Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Ecol Appl Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Ecosistema / Incendios Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Ecol Appl Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos