Choice of climate data influences current and future global invasion risks for two Phelsuma geckos

Abstract

Invasion risks may be influenced either negatively or positively by climate change, depending on the species. These can be predicted with species distribution models, but projections can be strongly affected by input environmental data (climate data source, Global Circulation Models and Shared Socio-economic Pathways SSP). We modelled the distribution of Phelsuma grandis and P. laticauda , two Malagasy reptiles that are spreading globally. We accounted for drivers of spread and establishment using socio-economic factors (e.g., distance from ports) and two climate data sources, i.e., Climatologies at High Resolution for the Earth’s and Land Surface Areas (CHELSA) and Worldclim. We further quantified the degree of agreement in invasion risk models that utilised CHELSA and Worldclim data for current and future conditions. Most areas identified as highly exposed to invasion risks were consistently identified (e.g. in Caribbean and Pacific Islands). However, projected risks differed locally. We also found notable differences in quantitative invasion risk (3% difference in suitability scores for P. laticauda and up to 14% for P. grandis ) under current conditions. Despite both species native distributions overlap substantially, climate change will drive opposite responses on invasion risks by 2070 (decrease for P. grandis, increase for P. laticauda ). Overall, projections of future invasion risks were the most affected by climate data source, followed by SSP. Our results highlight that assessments of current and future invasion risks are sensitive to the climate data source, especially in Islands. We stress the need to account for multiple climatologies when assessing invasion risks.

A bird’s-eye view: Evaluating drone imagery for the detection and monitoring of endangered and invasive day gecko species

“…This area and its surroundings were predicted as hosting the most suitable climate in the future for the endemic P. inexpectata (Dubos et al, 2022b). On the other hand, climate change is predicted to benefit P. laticauda (Dubos et al, 2022a), which emphasizes the need to pursue the sampling effort at this site in order to better understand the impact of the invasive P. laticauda on the Critically Endangered P. inexpectata and plan efficient intervention if needed.…”

“…Phelsuma grandis also raises concerns due to its larger size, imposing high predation risk on smaller species (Buckland et al, 2014). Both invasive species successfully established throughout the world (Dubos et al, 2014; Fieldsend and Krysko, 2019; Fieldsend, Borgia, and Krysko, 2020; Fieldsend et al, 2021; Dubos et al, 2022a), with strong invasion potential on tropical islands (Dubos et al, 2022a). The two invasive Phelsuma spp.…”

High-resolution climate data reveals increased risk of Pierce’s Disease for grapevines worldwide

“…Likewise, the choice of climate data affects the predictions of species distribution models (SDMs) [17]. In particular, the spatial resolution of the data can influence the predictions of invasion risk for some species [18]. It is therefore clear that the resolution of climate data will have a significant impact on predicting the risk of plant diseases and pests.…”

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“…Species distribution models (SDMs) can be used to identify the most suitable conditions for a given species, and forecast potential future geographical shifts in these conditions. SDMs are commonly used for testing ecological hypotheses (Anderson et al, 2009;Dubos, Augros, et al, 2022), assessing alien species invasion risks (Bellard et al, 2013;Dubos, Fieldsend, et al, 2022;Lanner et al, 2022), forecasting the potential effect of environmental change (Araújo et al, 2005), and supporting conservation and management efforts (Schwartz, 2012;Leroy et al, 2014;. In conservation application, SDMs can provide maps of projected future environmental suitability at the resolution of environmental data.…”