ArticleNature ecology & evolution2021
Environmental resistance predicts the spread of alien species.
Article in Nature ecology & evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Ecological similarities and dissimilarities between donor and recipient regions shape global plant naturalizations.Nature communications · 2025Article
- Genomic Tools in Biological Invasions: Current State and Future Frontiers.Genome biology and evolution · 2024Article
- The poleward naturalization of intracontinental alien plants.Science advances · 2023Article
- Abrupt expansion of climate change risks for species globally.Nature ecology & evolution · 2023Article
- Mechanistic models project bird invasions with accuracy.Nature communications · 2023Article
- Biological invasions as a selective filter driving behavioral divergence.Nature communications · 2022Article
- Potential for invasion of traded birds under climate and land-cover change.Global change biology · 2022Article
- Big data from a popular app reveals that fishing creates superhighways for aquatic invaders.PNAS nexus · 2022Article
- Gene drives for vertebrate pest control: Realistic spatial modelling of eradication probabilities and times for island mouse populations.Molecular ecology · 2022Article
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Authors and funding
4 authors.
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Abstract
The unabating rise in the number of species introduced outside of their native range makes predicting the spread of alien species an urgent challenge. Most predictions use models of the ecological niche of a species to identify suitable areas for invasion, but these predictions may have limited accuracy. Here, using the global alien avifauna, we demonstrate an alternative approach for predicting alien spread based on the environmental resistance of the landscape. This approach does not require any information on the ecological niche of the invading species and, instead, uses gradients of biotic similarity among native communities in the invaded region to predict the most likely routes of spread. We show that environmental resistance predicts patterns of spread better than a null model of random dispersal or a model based on climate matching to the native range of each species. Applying this approach to simulate future spread reveals major regional differences in projected invasion risk, shaped by proximity to existing invasion hotspots as well as gradients in environmental resistance. Our results show how environmental resistance may provide a general and complementary approach for predicting invasion risk that can be rapidly deployed even when information on the niche or the identity of potential invaders is unknown.
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