Phytophthora and vascular plant species distributions along a steep elevation gradient

Epidemiology of boxwood blight in western North Carolina and Virginia and evaluation of the boxwood blight infection risk model

Boxwood blight, caused by Calonectria pseudonaviculata, is a highly invasive emerging disease. Since the first US report in North Carolina and Connecticut in 2011, boxwood blight has spread to over 30 US states, risking more than 90% of boxwood production. Our study investigated the disease field epidemiology and evaluated the boxwood blight infection risk model's prediction by analysing weekly blight monitoring data collected on detector plants exposed to the prevailing environmental conditions at two different locations (western Virginia and North Carolina) from spring through fall of 2014 to 2017. Boxwood blight was recorded in 61 of 86 weeks, with the highest infected leaf counts recorded in late summer or early fall. Rainfall, high relative humidity outside rainy periods and optimal temperatures (13.6-22.7 °C) during prolonged leaf wetness (> 65 h per week) had a significant positive effect on boxwood blight development. Classification analyses showed that disease predictions from the model using leaf wetness estimated by leaf wetness sensor were more closely aligned with observations from the field than predictions based on algorithms. This study improved our understanding of disease field epidemiology, provided leads to improve the existing model, and generated essential knowledge for formulating effective strategies for blight mitigation.

Comparison of Primers for the Detection of Phytophthora (and Other Oomycetes) from Environmental Samples

Many oomycetes are important plant pathogens that cause devastating diseases in agricultural fields, orchards, urban areas, and natural ecosystems. Limitations and difficulties associated with isolating these pathogens have led to a strong uptake of DNA metabarcoding and mass parallel sequencing. At least 21 primer combinations have been designed to amplify oomycetes, or more specifically, Phytophthora species, from environmental samples. We used the Illumina sequencing platform to compare 13 primer combinations on mock communities and environmental samples. The primer combinations tested varied significantly in their ability to amplify Phytophthora species in a mock community and from environmental samples; this was due to either low sensitivity (unable to detect species present in low concentrations) or a lack of specificity (an inability to amplify some species even if they were present in high concentrations). Primers designed for oomycetes underestimated the Phytophthora community compared to Phytophthora-specific primers. We recommend using technical replicates, primer combinations, internal controls, and a phylogenetic approach for assigning a species identity to OTUs or ASVs. Particular care must be taken if sampling substrates where hybrid species could be expected. Overall, the choice of primers should depend upon the hypothesis being tested.