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Massive spread of invasive plant species predicted from spatio-temporal modelling on Reunion Island

L'Horset R., Castets M., Cazaux E., Fenouillas P., Ajaguin Soleyen C., Lo Seen D., Rouget M.. 2025. Global Ecology and Conservation, 62 : 16 p..

DOI: 10.1016/j.gecco.2025.e03680

Despite their high species diversity and endemism, island ecosystems are extremely vulnerable to invasive plant species (IPS). Reunion Island, located in the Indian Ocean, represents the largest area of intact vegetation in the Mascarene archipelago. However, the flora of Reunion Island is mostly threatened by IPS. Ecological modelling is crucial for studying IPS dynamics and for guiding management decisions on islands. To improve the capacity of IPS management in Reunion Island, this study aimed: (1) to predict the future spatio-temporal dynamics of IPS at island scale, (2) to better understand IPS spread factors. This work was conducted through an active “research-action” partnership. We designed a hybrid model to simulate the spatial spread over time of IPS on Reunion Island. We selected three species to be modelled: Anthoxanthum odoratum, Hiptage benghalensis and Solanum mauritianum. The hybrid model predicted an increase of 30¿% of the current invaded surface by A. odoratum in Key Biodiversity Areas (KBAs); an increase of 20¿% for S. mauritianum; and a spread outside of KBAs for H. benghalensis. The framework of the model, based on generic life-cycle mechanisms and species distribution models, can be adapted to other IPS of different plant types (such as lianas, shrubs and trees). The model framework is also adaptable and can be used with different climate change scenarios. With the implementation of IPS control actions also planned, the model could be used as a support tool by managers for analysing IPS trends spreading into KBAs and for taking appropriate actions.

Mots-clés : espèce envahissante; modèle de simulation; anthoxanthum; adaptation aux changements climatiques; ips; changement climatique; biodiversité; france; la réunion

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