Abstract
Phytophthora ramorum is an alien and invasive plant pathogen threatening forest ecosystems in Western North America, where it can cause both lethal and non-lethal diseases. While the mechanisms underlying the establishment and spread of P. ramorum have been elucidated, this is the first attempt to investigate the environmental factors driving the recovery of bay laurel, the main transmissive host of the pathogen. Based on a large dataset gathered from a citizen science program, an algorithm was designed, tested, and run to detect and geolocate recovered trees. Approximately 32% of infected bay laurels recovered in the time period between 2005 and 2015. Monte Carlo simulations pointed out the robustness of such estimates, and the algorithm achieved an 85% average rate of correct classification. The association between recovery and climatic, topographic, and ecological factors was assessed through a numerical ecology approach mostly based on binary logistic regressions. Significant (p < 0.05) coefficients and the information criteria of the models showed that the probability of bay laurel recovery increases in association with high temperatures and low precipitation levels, mostly in flat areas. Results suggest that aridity might be a key driver boosting the recovery of bay laurels from P. ramorum infections.
Highlights
The “disease triangle” model [1,2] frames pathogenesis as a process relying on the trophic interconnection between susceptible hosts and pathogens, provided that the environmental conditions are conducive to infection by the pathogen and to disease progression
The interest of forest pathologists in unraveling environmental factors driving plant diseases has been amplified in the last decades by the onset of relevant epidemics caused by emerging pathogens such as Phytophthora ramorum Werres, De Cock and Man in’t Veld in Western North America, Heterobasidion irregulare Garbelotto and Otrosina, Hymenoscyphus fraxineus
By combining the results gathered from a large citizen science disease survey program with an innovative numerical ecology approach based on a newly designed classification algorithm, we were able to determine the location of trees resampled over time, detecting the ones which had recovered from P. ramorum
Summary
The “disease triangle” model [1,2] frames pathogenesis as a process relying on the trophic interconnection between susceptible hosts and pathogens, provided that the environmental conditions are conducive to infection by the pathogen and to disease progression. The interest of forest pathologists in unraveling environmental factors driving plant diseases has been amplified in the last decades by the onset of relevant epidemics caused by emerging pathogens such as Phytophthora ramorum Werres, De Cock and Man in’t Veld in Western North America, Heterobasidion irregulare Garbelotto and Otrosina, Hymenoscyphus fraxineus Environmental factors play a key role in boosting plant diseases, they may unbalance the interaction between pathogen and host, favoring the latter and promoting recovery of the host. Recovery is a theoretical possibility, since it has been extensively documented for a Forests 2017, 8, 293; doi:10.3390/f8080293 www.mdpi.com/journal/forests
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