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Snapshot Wisconsin: networking community scientists and remote sensing to improve ecological monitoring and management.
Townsend, Philip A; Clare, John D J; Liu, Nanfeng; Stenglein, Jennifer L; Anhalt-Depies, Christine; Van Deelen, Timothy R; Gilbert, Neil A; Singh, Aditya; Martin, Karl J; Zuckerberg, Benjamin.
Afiliação
  • Townsend PA; Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.
  • Clare JDJ; Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.
  • Liu N; Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.
  • Stenglein JL; Wisconsin Department of Natural Resources, Madison, Wisconsin, 53707, USA.
  • Anhalt-Depies C; Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.
  • Van Deelen TR; Wisconsin Department of Natural Resources, Madison, Wisconsin, 53707, USA.
  • Gilbert NA; Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.
  • Singh A; Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.
  • Martin KJ; Department of Agricultural and Biological Engineering, University of Florida, Gainesville, Florida, 32603, USA.
  • Zuckerberg B; Division of Extension, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.
Ecol Appl ; 31(8): e02436, 2021 12.
Article em En | MEDLINE | ID: mdl-34374154
Biological data collection is entering a new era. Community science, satellite remote sensing (SRS), and local forms of remote sensing (e.g., camera traps and acoustic recordings) have enabled biological data to be collected at unprecedented spatial and temporal scales and resolution. There is growing interest in developing observation networks to collect and synthesize data to improve broad-scale ecological monitoring, but no examples of such networks have emerged to inform decision-making by agencies. Here, we present the implementation of one such jurisdictional observation network (JON), Snapshot Wisconsin, which links synoptic environmental data derived from SRS to biodiversity observations collected continuously from a trail camera network to support management decision-making. We use several examples to illustrate that Snapshot Wisconsin improves the spatial, temporal, and biological resolution and extent of information available to support management, filling gaps associated with traditional monitoring and enabling consideration of new management strategies. JONs like Snapshot Wisconsin further strengthen monitoring inference by contributing novel lines of evidence useful for corroboration or integration. SRS provides environmental context that facilitates inference, prediction, and forecasting, and ultimately helps managers formulate, test, and refine conceptual models for the monitored systems. Although these approaches pose challenges, Snapshot Wisconsin demonstrates that expansive observation networks can be tractably managed by agencies to support decision making, providing a powerful new tool for agencies to better achieve their missions and reshape the nature of environmental decision-making.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biodiversidade / Tecnologia de Sensoriamento Remoto Tipo de estudo: Prognostic_studies País/Região como assunto: America do norte Idioma: En Revista: Ecol Appl Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biodiversidade / Tecnologia de Sensoriamento Remoto Tipo de estudo: Prognostic_studies País/Região como assunto: America do norte Idioma: En Revista: Ecol Appl Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos