Optimizing Management of Invasions in an Uncertain World Using Dynamic Spatial Models

This study synthesizes provides a workflow for applying ecological theory to advancing the science of optimizing the management of invasive species.

View Journal Article


April 9, 2023


Kim M. Pepin, Amy J. Davis, Rebecca Epanchin-Niell, Andrew M. Gormley, Joslin L. Moore, Timothy J. Smyser, H. Bradley Shaffer, William L. Kendall, Katriona Shea, Michael C. Runge, and Sophie McKee


Journal Article in Ecological Applications

Reading time

1 minute


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.


Kim M. Pepin

National Wildlife Research Center

Amy J. Davis

National Wildlife Research Center

Andrew M. Gormley

Landcare Research

Joslin L. Moore

University of Melbourne

Timothy J. Smyser

Purdue University

H. Bradley Shaffer

University of California, Los Angeles

William L. Kendall

United States Geological Survey

Katriona Shea

Pennsylvania State University

Michael C. Runge

United States Geological Survey

Sophie McKee

National Wildlife Research Center

Related Content