Using MaxEnt modeling to analyze climate change impacts on Pseudomonas syringae van Hall, 1904 distribution on the global scale.

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

SUBMITTER: Khalaf SMH 

PROVIDER: S-EPMC11696772 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature