Recent advances of quantitative modeling to support invasive species eradication on islands
|
Published Version
(PDF 2MB)
112563128. Available under License Creative Commons Attribution 4.0. |
Open access copy at publisher website
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.
Impact and interest:
Citation counts are sourced monthly from Scopus and Web of Science® citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads:
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
ID Code: | 233344 | ||
---|---|---|---|
Item Type: | Contribution to Journal (Review article) | ||
Refereed: | Yes | ||
ORCID iD: |
|
||
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 | ||
Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||
Deposited On: | 06 Jul 2022 02:15 | ||
Last Modified: | 10 Apr 2024 21:46 |
Export: EndNote | Dublin Core | BibTeX
Repository Staff Only: item control page