Predicting the presence and cover of management relevant invasive plant species on protected areas

Iacona, Gwenllian, Price, Franklin D. and Armsworth, Paul R. (2016) Predicting the presence and cover of management relevant invasive plant species on protected areas. Journal of Environmental Management, 166 537-543. doi:10.1016/j.jenvman.2015.10.052

Author Iacona, Gwenllian
Price, Franklin D.
Armsworth, Paul R.
Title Predicting the presence and cover of management relevant invasive plant species on protected areas
Journal name Journal of Environmental Management   Check publisher's open access policy
ISSN 1095-8630
Publication date 2016-01-15
Year available 2015
Sub-type Article (original research)
DOI 10.1016/j.jenvman.2015.10.052
Open Access Status Not Open Access
Volume 166
Start page 537
End page 543
Total pages 7
Place of publication London, United Kingdom
Publisher Academic Press
Collection year 2016
Language eng
Abstract Invasive species are a management concern on protected areas worldwide. Conservation managers need to predict infestations of invasive plants they aim to treat if they want to plan for long term management. Many studies predict the presence of invasive species, but predictions of cover are more relevant for management. Here we examined how predictors of invasive plant presence and cover differ across species that vary in their management priority. To do so, we used data on management effort and cover of invasive plant species on central Florida protected areas. Using a zero-inflated multiple regression framework, we showed that protected area features can predict the presence and cover of the focal species but the same features rarely explain both. There were several predictors of either presence or cover that were important across multiple species. Protected areas with three days of frost per year or fewer were more likely to have occurrences of four of the six focal species. When invasive plants were present, their proportional cover was greater on small preserves for all species, and varied with surrounding household density for three species. None of the predictive features were clearly related to whether species were prioritized for management or not. Our results suggest that predictors of cover and presence can differ both within and across species but do not covary with management priority. We conclude that conservation managers need to select predictors of invasion with care as species identity can determine the relationship between predictors of presence and the more management relevant predictors of cover.
Keyword Conservation costs
Imperata cylindrica
Ludwigia peruviana
Lygodium microphyllum
Schinus terebinthifolius
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ
Additional Notes Published online 18 November 2015

Document type: Journal Article
Sub-type: Article (original research)
Collections: CEED Publications
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