Mechanistic invasive species management models and their application in conservation
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Abstract
Management strategies to address the challenges associated with invasive species are critical for effective conservation. An increasing variety of mathematical models offer insight into invasive populations, and can help managers identify cost effective prevention, control, and eradication actions. Despite this, as model complexity grows, so does the inaccessibility of these tools to conservation practitioners making decisions about management. Here, we seek to narrow the science-practice gap by reviewing invasive species management models (ISMMs). We define ISMMs as mechanistic models used to explore invasive species management strategies, and include reaction-advection–diffusion models, integrodifference equations, gravity models, particle transport models, nonspatial and spatial discrete-time population growth models, cellular automata, and individual-based models. For each approach, we describe the model framework and its implementation, discuss strengths and weaknesses, and give examples of conservation applications. We conclude by discussing how ISMMs can be used in concert with adaptive management to address scientific uncertainties impeding action and with multiple objective decision processes to evaluate tradeoffs among management objectives. We undertook this review to support more effective decision-making involving invasive species by providing conservation practitioners with the information they need to identify tools most useful for their applications.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Mechanistic invasive species management models and their application in conservation |
Series title | Conservation Science and Practice |
DOI | 10.1111/csp2.533 |
Volume | 3 |
Issue | 11 |
Year Published | 2021 |
Language | English |
Publisher | Society for Conservation Biology |
Contributing office(s) | Coop Res Unit Seattle |
Description | e533, 18 p. |
Google Analytic Metrics | Metrics page |