The potential global distribution of an emerging forest pathogen, Lecanosticta acicola, under a changing climate

Brown spot needle blight (BSNB), caused by Lecanosticta acicola (Thüm.) Syd., is an emerging forest disease of Pinus species originating from North America and introduced to Europe Asia. Severity spread the has increased in last two decades as a response climate change. No modeling work on spread, severity, climatic suitability, or potential distribution been done for this important pathogen. This study utilizes global dataset 2,970 independent observations L. presence absence geodatabase, together with spp. data 44 environmental variables. The objectives were (1) identify which bioclimatic variables are most influential ; (2) compare four approaches determine method best fits data; (3) examine realized pathogen under conditions reference period (1971–2000); (4) predict future various change scenarios. These achieved using modeling. Four tested: regression-based model, individual classification trees, bagging three different base learners, random forest. Altogether, eight models developed. An ensemble was used make predictions : tree, logistic model Performance very good, high precision (0.87) AUC (0.94). computed five (GCM) combined pathways Shared Socioeconomic Pathway (SSP) Representative Concentration (SSP-RCP): SSP1-RCP2.6, SSP2-RCP4.5, SSP5-RCP8.5. results GCMs averaged SSP-RCP (median) per 30-year period. Eight studied factors determined explaining included models: mean diurnal temperature range, wettest quarter, precipitation warmest seasonality, moisture upper portion soil column surface downwelling longwave radiation driest shortwave quarter elevation. actual 1971–2000 covered 5.9% area globally. However, predicted cover average 58.2% Different scenarios (five GCMs, SSP-RCPs) showed positive trend possible range expansion 1971–2100. toward end century rising 62.2, 61.9, 60.3% SSP5-RCP8.5, respectively. 95% confidence interval encompassed 35.7–82.3% 33.6–85.8% 2071–2100. It found that SSP-RCPs had little effect variability BSNB (60.3–62.2% 2071–2100 medium prediction). In contrast, vast impact (33.6–85.8% pines area). maps will assist managers considering risk BSNB. allow practitioners policymakers focus surveillance methods implement appropriate management plans.