Identifying Pareto-efficient eradication strategies for invasive populations
October 1, 2024
Invasive species are a major cause of biodiversity loss and are notoriously expensive and challenging to manage.
We developed a decision-analytic framework for evaluating invasive species removal strategies, given objectives of maximizing eradication probability and minimizing costs. The framework uses an existing estimation model for spatially referenced removal data – one of the most accessible types of invasive species data – to obtain estimates of population growth rate, movement probability, and detection probability. We use these estimates in simulations to identify Pareto-efficient strategies – strategies where increases in eradication probability cannot be obtained without increases in cost – from a set of proposed strategies. We applied the framework post hoc to a successful eradication of veiled chameleons (Chamaeleo calyptratus) and identified the potential for substantial improvements in efficiency (Link et al 2018). Our approach provides managers with tools to identify cost-effective strategies for a range of invasive species using only prior knowledge or data from initial physical removals.
Citation Information
Publication Year | 2024 |
---|---|
Title | Identifying Pareto-efficient eradication strategies for invasive populations |
DOI | 10.5066/P13TRXCM |
Authors | Nathan J Hostetter, Amy A Yackel, William A Link, Sarah Converse |
Product Type | Software Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Fort Collins Science Center |
Rights | This work is licensed under CC BY 4.0 |
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Identifying Pareto-efficient eradication strategies for invasive populations
Invasive species are a major cause of biodiversity loss and are notoriously expensive and challenging to manage. We developed a decision-analytic framework for evaluating invasive species removal strategies, given objectives of maximizing eradication probability and minimizing costs. The framework uses an existing estimation model for spatially referenced removal data—one of the most...
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Identifying Pareto-efficient eradication strategies for invasive populations
Invasive species are a major cause of biodiversity loss and are notoriously expensive and challenging to manage. We developed a decision-analytic framework for evaluating invasive species removal strategies, given objectives of maximizing eradication probability and minimizing costs. The framework uses an existing estimation model for spatially referenced removal data—one of the most...
Authors
Amy A. Yackel Adams, Nathan J. Hostetter, William A. Link, Sarah J. Converse
Nathan J Hostetter, PhD
Research Wildlife Biologist
Research Wildlife Biologist
Email
Amy Yackel Adams, PhD
Branch Chief / Supervisory Research Ecologist
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Email
Phone
William Link, Ph.D. (Former Employee)
Research Statistician
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