ArticleEcology and evolution2023
Constructing indicator species distribution models to study the potential invasion risk of invasive plants: A case of the invasion of
Article in Ecology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Predicting the Potential Distribution of the Invasive PlantEcology and evolution · 2026Article
- Predictive Framework Based on GBIF and WorldClim Data for Identifying Drought- and Cold-TolerantPlants (Basel, Switzerland) · 2025Article
- Reconstructing the biological invasion of noxious invasive weedFrontiers in plant science · 2024Article
- Constructing indicator species distribution models to study the potential invasion risk of invasive plants: A case of the invasion ofEcology and evolution · 2023Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: As invasive plants are often in a non-equilibrium expansion state, traditional species distribution models (SDMs) are likely underestimating their suitable habitat. New methods are necessary to identify potential invasion risk areas. Location: Tropical monsoon rainforest and subtropical evergreen broad-leaved forest regions in China. Methods: We took Results: The optimized indicator SDMs prediction showed an expanded range beyond the current geographic range compared to EM and the thresholds for predicting key environmental variables were wider. It also reinforced the human activities' influence on the potential distribution of Main Conclusions: For invasive plants with expanding ranges, information about indicator species distribution can be borrowed as a barometer for areas not currently invaded. The optimized indicator SDMs allow for more efficient potential invasion risk prediction. On this basis, invasive plants can be prevented earlier.
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