1 research outputs found
Climate, host ontogeny and pathogen structural specificity determine forest disease distribution at a regional scale
Predicting forest health at a regional level is challenging as forests are simultaneously attacked by multiple pathogens. Usually, the impacts of each pathogen are studied separately, however, interactions between them can affect disease dynamics. Pathogens can interact directly by competing for the same niche, but also facilitate or suppress each other via indirect effects through the host. We studied 66 native Mediterranean Pinus nigra stands located in the Pyrenees which were affected by two pathogens with different structural specificity: Dothistroma pini causing Dothistroma needle blight and Diplodia sapinea causing Diplodia shoot blight. We explored the ecology of both pathogens and whether the diseases they caused had an impact on trees and recruits. No signs of competition were found on adult trees. Diplodia shoot blight was restricted to the warmest and driest areas, while no climatic restrictions were identified for Dothistroma needle blight. Both diseases caused additive effects on crown defoliation and defoliated trees showed stagnated growth. In the regeneration layer, signs of disease suppression were found. In the warmest and driest areas, seedling mortality was mainly associated with Diplodia shoot blight, even though both pathogens were detected. Clear signs of D. pini spillover from canopy trees to recruits were found. However, seedling mortality caused by Dothistroma needle blight was only restricted to the coldest and wettest sites where D. sapinea could not survive. Large crowns in adult trees probably allow both pathogens to co-exist and cause additive impacts. The smaller size of recruits and a higher susceptibility to environmental stress compared to adult trees probably facilitates the effects of Diplodia shoot blight which masked those caused by Dothistroma needle blight. By considering climatic constraints, host ontogeny and structural specificity, we could dissect the disease impacts of two different pathogens and successfully explain forest health at a regional scale