Recent advances of quantitative modeling to support invasive species eradication on islands

Baker, Christopher M. & (2021) Recent advances of quantitative modeling to support invasive species eradication on islands. Conservation Science and Practice, 3(2), Article number: e246.

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Description

The eradication of invasive species from islands is an important part of managing these ecologically unique and at-risk regions. Island eradications are complex projects and mathematical models play an important role in supporting efficient and transparent decision-making. In this review, we cover the past applications of modeling to island eradications, which range from large-scale prioritizations across groups of islands, to project-level decision-making tools. While quantitative models have been formulated and parameterized for a range of important problems, there are also critical research gaps. Many applications of quantitative modeling lack uncertainty analyses, and are therefore overconfident. Forecasting the ecosystem-wide impacts of species eradications is still extremely challenging, despite recent progress in the field. Overall, the field of quantitative modeling is well-developed for island eradication planning. Multiple practical modeling tools are available for, and are being applied to, a diverse suite of important decisions, and quantitative modeling is well placed to address pressing issues in the field.

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26 citations in Scopus
19 citations in Web of Science®
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ID Code: 233344
Item Type: Contribution to Journal (Review article)
Refereed: Yes
ORCID iD:
Bode, Michaelorcid.org/0000-0002-5886-4421
Additional Information: Funding information: Australian Research Council, Grant/Award Number: FT170100274.
Measurements or Duration: 19 pages
DOI: 10.1111/csp2.246
ISSN: 2578-4854
Pure ID: 112563128
Divisions: Current > Research Centres > Centre for the Environment
Current > QUT Faculties and Divisions > Faculty of Science
Current > Schools > School of Mathematical Sciences
Funding Information: M. B. was funded by ARC Grant FT170100274.
Funding:
Copyright Owner: 2020 The Authors
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Deposited On: 06 Jul 2022 02:15
Last Modified: 10 Apr 2024 21:46