Introduction A rapidly growing population and ongoing urbanization continue to strain agriculture’s capacity to maintain a stable food supply, both through direct impacts such as land reclamation and indirect effects driven by accelerating climate change. One of the major consequences of climate change is the shifting geographic range of infectious plant pathogens, particularly Ralstonia solanacearum, the causative agent of bacterial wilt. This pathogen poses a significant threat to several economically important crops including tomatoes, bananas, eggplants, and tobacco. Methods To assess the current and future potential distribution of R. solanacearum under various climate scenarios, maximum entropy (MaxEnt) modeling was applied. This method was used to construct predictive maps based on environmental variables influencing the pathogen’s distribution. Results The predictive models demonstrated high accuracy and performance, with an area under the curve (AUC) of 0.89 and a true skill statistic (TSS) of 0.94. Annual mean temperature was identified as the most significant environmental predictor. The present-day distribution map revealed an almost cosmopolitan range, while future climate change scenarios indicated substantial shifts in distribution across all continents. Discussion These findings highlight the urgent need for implementing sustainable agricultural practices and developing novel, environmentally friendly methods to control the spread of R. solanacearum. This is especially critical in developing countries where agriculture is most vulnerable, to ensure food security under changing climate conditions.
Implications for agricultural sustainability: predicting the global distribution of Ralstonia solanacearum under current and future climate scenarios
A.I. Tagyan,Omar Elghoul,Wael N. Hozzein,Walaa Rabie,D. H. Alkhalifah,Noura A. El-Far
Published 2025 in Frontiers in Plant Science
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- Publication year
2025
- Venue
Frontiers in Plant Science
- Publication date
2025-08-04
- Fields of study
Agricultural and Food Sciences, Medicine, Environmental Science
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- Source metadata
Semantic Scholar, PubMed
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