RRC ID 83019
Author Khalaf SMH, Alqahtani MSM, Ali MRM, Abdelalim ITI, Hodhod MS.
Title Using MaxEnt modeling to analyze climate change impacts on Pseudomonas syringae van Hall, 1904 distribution on the global scale.
Journal Heliyon
Abstract Pseudomonas syringae is a pathogenic bacterium that poses a significant threat to global agriculture, necessitating a deeper understanding of its ecological dynamics in the context of global warming. This study investigates the current and projected future distribution of P. syringae, focusing on the climatic factors that influence its spread. To achieve this, we employed Maximum Entropy (MaxEnt) modeling based on Geographic Information Systems (GIS) to analyze species occurrence records alongside relevant climate data. The MaxEnt model was calibrated using 75 % of the occurrence data, with the remaining 25 % reserved for validation. The model's performance was meticulously assessed utilizing the area under the curve (AUC) and true skill statistics (TSS), resulting in an AUC score of 0.92, indicating excellent predictive capability. Our analysis identified key climatic parameters-temperature, precipitation, and humidity-that significantly affect the presence of P. syringae. Notably, our findings project an expansion of the bacterium's geographic range in the coming decades, with optimal conditions shifting toward the poles. This research underscores the significant influence of climate change on the distribution of P. syringae and provides valuable insights for developing targeted disease management strategies. The anticipated increase in bacterial infections in crops highlights the urgent need for proactive measures to mitigate these effects.
Volume 10(24)
Pages e41017
Published 2024-12-7
DOI 10.1016/j.heliyon.2024.e41017
PII S2405-8440(24)17048-X
PMID 39759371
PMC PMC11696772
Resource
GBIF Biological Resource Center, Department of Biotechnology, National Institute of Technology and Evaluation Genebank, National Institute of Agrobiological Sciences