skip to main content
Idioma:
Primo Search
Clear Search Box
Search in: Busca Geral
Busca Avançada
Busca por Índices

Practical considerations for operationalizing dynamic management tools

Welch, Heather ; Hazen, Elliott L. ; Bograd, Steven J. ; Jacox, Michael G. ; Brodie, Stephanie ; Robinson, Dale ; Scales, Kylie L. ; Dewitt, Lynn ; Lewison, Rebecca ; Smith, Annabel Smith, Annabel

The Journal of applied ecology, 2019-02, Vol.56 (2), p.459-469 [Periódico revisado por pares]

Oxford: Blackwell Publishing Ltd

Texto completo disponível

Citações Citado por
  • Título:
    Practical considerations for operationalizing dynamic management tools
  • Autor: Welch, Heather ; Hazen, Elliott L. ; Bograd, Steven J. ; Jacox, Michael G. ; Brodie, Stephanie ; Robinson, Dale ; Scales, Kylie L. ; Dewitt, Lynn ; Lewison, Rebecca ; Smith, Annabel
  • Smith, Annabel
  • Assuntos: Automation ; Bycatch ; Case studies ; dynamic management ; ecological modelling ; Environmental assessment ; Environmental management ; Fisheries ; fisheries bycatch ; Human motion ; Management tools ; Missing data ; near real‐time ; nowcast ; operationalization ; Protected species ; Remote observing ; Remote sensing ; Resource management ; Sensitivity analysis ; Social conditions ; spatial management ; Variability
  • É parte de: The Journal of applied ecology, 2019-02, Vol.56 (2), p.459-469
  • Notas: The article has been contributed to by US Government employees and their work is in the public domain in the USA
  • Descrição: Dynamic management (DM) is a novel approach to spatial management that aligns scales of environmental variability, animal movement and human uses. While static approaches to spatial management rely on one‐time assessments of biological, environmental, economic, and/or social conditions, dynamic approaches repeatedly assess conditions to produce regularly updated management recommendations. Owing to this complexity, particularly regarding operational challenges, examples of applied DM are rare. To implement DM, scientific methodologies are operationalized into tools, i.e., self‐contained workflows that run automatically at a prescribed temporal frequency (e.g., daily, weekly, monthly). Here we present a start‐to‐finish framework for operationalizing DM tools, consisting of four stages: Acquisition, Prediction, Dissemination, and Automation. We illustrate this operationalization framework using an applied DM tool as a case study. Our DM tool operates in near real‐time and was designed to maximize target catch and minimize bycatch of non‐target and protected species in a US‐based commercial fishery. It is important to quantify the sensitivity of DM tools to missing data, because dissemination streams for observed (i.e., remotely sensed or directly sampled) data can experience delays or gaps. To address this issue, we perform a detailed example sensitivity analysis using our case study tool. Synthesis and applications. Dynamic management (DM) tools are emerging as viable management solutions to accommodate the biological, environmental, economic, and social variability in our fundamentally dynamic world. Our four‐stage operationalization framework and case study can facilitate the implementation of DM tools for a wide array of resource and disturbance management objectives. Dynamic management (DM) tools are emerging as viable management solutions to accommodate the biological, environmental, economic, and social variability in our fundamentally dynamic world. Our four‐stage operationalization framework and case study can facilitate the implementation of DM tools for a wide array of resource and disturbance management objectives.
  • Editor: Oxford: Blackwell Publishing Ltd
  • Idioma: Inglês
Voltar para lista de resultados
Ir para página anteriorAnterior Resultado  7 AvançarIr para próxima página

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

Buscando em bases de dados remotas. Favor aguardar.