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Optimizing management of invasions in an uncertain world using dynamic spatial models. | LitMetric

AI Article Synopsis

  • Dispersal plays a key role in the invasion dynamics of nonnative species and pathogens, and understanding this can greatly enhance the effectiveness of management control programs.
  • Optimizing dynamic spatial models to manage invasions is complex due to the interactions of time, space, and uncertainty, necessitating a multidisciplinary approach that combines ecology, decision analysis, and optimization techniques.
  • A major gap identified in current management frameworks is the lack of consideration for dispersal uncertainty, which can significantly impact invasion outcomes, highlighting the need for improved strategies to integrate various uncertainties into management decisions.

Article Abstract

Dispersal drives invasion dynamics of nonnative species and pathogens. Applying knowledge of dispersal to optimize the management of invasions can mean the difference between a failed and a successful control program and dramatically improve the return on investment of control efforts. A common approach to identifying optimal management solutions for invasions is to optimize dynamic spatial models that incorporate dispersal. Optimizing these spatial models can be very challenging because the interaction of time, space, and uncertainty rapidly amplifies the number of dimensions being considered. Addressing such problems requires advances in and the integration of techniques from multiple fields, including ecology, decision analysis, bioeconomics, natural resource management, and optimization. By synthesizing recent advances from these diverse fields, we provide a workflow for applying ecological theory to advance optimal management science and highlight priorities for optimizing the control of invasions. One of the striking gaps we identify is the extremely limited consideration of dispersal uncertainty in optimal management frameworks, even though dispersal estimates are highly uncertain and greatly influence invasion outcomes. In addition, optimization frameworks rarely consider multiple types of uncertainty (we describe five major types) and their interrelationships. Thus, feedbacks from management or other sources that could magnify uncertainty in dispersal are rarely considered. Incorporating uncertainty is crucial for improving transparency in decision risks and identifying optimal management strategies. We discuss gaps and solutions to the challenges of optimization using dynamic spatial models to increase the practical application of these important tools and improve the consistency and robustness of management recommendations for invasions.

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Source
http://dx.doi.org/10.1002/eap.2628DOI Listing

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