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Cited by 235

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

A new framework for predicting invasive plant species

Moles, Angela T., Gruber, Monica A. M., Bonser, Stephen P.·2008·Journal of Ecology

Abstract

1 Many studies have searched for traits that characterize successful invaders. Unfortunately, very few generalizations have emerged from this work. It seems that the traits of successful invaders are idiosyncratic and context-dependent. Unless we are to study each potential invader in each possible target community individually, we will need a new approach. 2 We introduce a framework for predicting traits that are likely to confer success in a given ecosystem. Our approach considers the prevailing environmental conditions, the traits of resident species, and the traits of potentially invading species. 3 Our approach can be applied to ecosystems where the environmental conditions and/or disturbance regime have recently changed, to predict the range of trait space occupied by (i) native species at risk of local extinction, (ii) native species that can persist under the present conditions, and (iii) successful invaders. Our approach can also be used to identify unoccupied viable trait space (i.e. vacant niches) that might be at risk of invasion. 4 Synthesis. Understanding invasions resulting from rapid changes in environmental conditions and invasions resulting from the colonization of vacant niches would be a major step forward for invasion biology. The conceptual framework described here is not limited to plant invasions: the same approach can be used for any taxa (e.g. insects, fish, mammals and marine invertebrates) and could also be used to predict species responses to environmental change.

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Metadata

Authors
Moles, A. T., Gruber, M. A. M., & Bonser, S. P.
Venue
Journal of Ecology
Publisher
Wiley
Published
2007-11-16
Volume
96
Issue
1
Pages
13-17
ISSN
  • 0022-0477 (ISSN-L)
  • 1365-2745
OpenAlex
W2004961626
Cited by
235
References
2
FWCI
12.91
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A new framework for predicting invasive plant species. https://app.cochat.ai/papers/10.1111/j.1365-2745.2007.01332.x
The paper
Moles, A. T., Gruber, M. A. M., & Bonser, S. P. (2008). A new framework for predicting invasive plant species. Journal of Ecology. https://doi.org/10.1111/j.1365-2745.2007.01332.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.