Environmental factors driving the recovery of bay laurels from Phytophthora ramorum infections: An application of numerical ecology to citizen science

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.