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CorrectionCC BY V4.0, Open Access
Journal article
Native diversity buffers against severity of non-native tree invasions
Nature, Vol.621, pp.773-781
2023
Abstract
Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies. Here, leveraging global tree databases, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.
Details
- Title
- Native diversity buffers against severity of non-native tree invasions
- Authors
- Camille S. Delavaux (Author) - Swiss Federal Institute of Technology in ZurichThomas W Crowther (Author) - Swiss Federal Institute of Technology in ZurichConstantin M. Zohner (Author) - Swiss Federal Institute of Technology in ZurichNiamh M. Robmann (Author) - Swiss Federal Institute of Technology in ZurichThomas Lauber (Author) - Swiss Federal Institute of Technology in ZurichJohan van den Hoogen (Author) - Swiss Federal Institute of Technology in ZurichSara Kuebbing (Author) - Yale UniversityJingjing Liang (Author) - Purdue UniversitySergio de-Miguel (Author) - Universitat de LleidaSee article full text for complete list of authors (Author)Robin Chazdon (Author) - University of the Sunshine Coast, Queensland, Forest Research InstituteJohn Herbohn (Author) - University of the Sunshine Coast, Queensland, Forest Research InstituteAndrew Marshall (Author) - University of the Sunshine Coast, Queensland, Forest Research InstituteSharif A Mukul (Author) - University of the Sunshine Coast, Queensland, Forest Research Institute
- Publication details
- Nature, Vol.621, pp.773-781
- Publisher
- Nature Publishing Group
- Date published
- 2023
- DOI
- 10.1038/s41586-023-06440-7
- ISSN
- 1476-4687; 0028-0836
- Copyright note
- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Grant note
- Swiss Federal Institute of Technology Zurich
- Organisation Unit
- Australian Centre for Pacific Islands Research; Tropical Forests and People Research Centre; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Forest Research Institute
- Language
- English
- Record Identifier
- 99746795302621
- Output Type
- Journal article
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