Unraveling the ecological niche signals of Verticillium dahliae: Insights from Mediterranean landscapes.

Abstract

Verticillium wilt (VW), caused by the soil-borne plant pathogenic fungus Verticillium dahliae, is a major disease impacting olive crops globally. In view of the lack of effective post-infection treatments, exclusion and avoidance strategies are essential in disease management. Assessing the risks posed by this pathogen is essential to prevent the spread and to ensure selection of suitable sites for new plantations. This study aimed to elucidate the environmental factors driving V. dahliae establishment in the Andalusia region, in southern Spain, an emblematic Mediterranean landscape for olive cultivation. To this end, we explored ecological niche signals for this fungal pathogen by analyzing 62 environmental variables across 1.6 million hectares dedicated to olive and cotton cultivation, using a 15-yr survey data on VW incidence on presence-absence from both olive and cotton fields. To ensure robust identification of ecological niche signals, we employed randomization-based, non-parametric univariate tests to compare presence records with the broader sampling universe (including absence records). Our findings identified key environmental variables that are associated significantly with V. dahliae presence, including temperature range seasonality (including mean diurnal and annual ranges), summer temperature (maximum of the warmest month, mean of the warmest quarter), and moisture and water availability (near-surface humidity, potential evapotranspiration, vapor pressure) as core niche variables for V. dahliae. Our results replicated the pathogen's known distribution, identifying the Guadalquivir Valley as a particularly high-risk area in view of its mild winters and distinct rainy seasons, providing new insights into the specific environmental conditions that facilitate the pathogen's survival and spread. Furthermore, this study introduces a novel approach to niche modeling that prioritizes variables with consistent effects and significant impact on the presence and distribution of V. dahliae and identifies potential data artifacts. This approach enhances our understanding of ecological requirements in V. dahliae and informs targeted management strategies.