Drought heightens severity of diseases caused by Botryosphaeria dothidea and Cryptostroma corticale and needs to be factored in to properly assess pathogenicity or fulfill Koch’s postulates

Author:

Garbelotto MatteoORCID

Abstract

AbstractClimate change is driving the emergence of novel tree diseases at the global scale, requiring new approaches for the formal confirmation of the pathogenicity of novel pathogens on novel hosts. At the same time, predictive models need to account for the possible effect of environmental changes and of abiotic stressors on disease severity for all diseases. By wound-inoculating Botryosphaeria dothidea on potted California coast live oaks and Cryptostroma corticale on potted silver maples, simultaneously in well-watered and in water-deprived conditions, I show that drought conditions increase the severity of disease symptoms. I also show that, by including a water-stressed treatment, I can formally prove pathogenicity and fulfill Koch’s postulates for putative pathogens that could not be confirmed in the absence of the stressor. Additionally, I show that the inclusion of data obtained in water stress conditions increases the differentiation between symptoms caused by fungal infection vs. symptoms caused by wound trauma, thus reducing the possible effect of outliers, a significant problem affecting many trials for fulfilling Koch’s postulates conducted with a limited number of replicates. The availability of comparable datasets in the presence and the absence of an abiotic stressor allows for the calculation of an Environmental Disease Component Index. Positive values of the index indicate a significant role of environmental change in disease progression and identify those pathogens that must be modeled factoring in climatic stressors. I suggest that this index may be extremely valuable for identifying pathogens likely to become emergent as climate changes.

Funder

San Francisco Public Utilities Commission

East Bay Regional Parks

Publisher

Springer Science and Business Media LLC

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