Climate-Driven Changes in Potential Suitability and Spatial Co-Occurrence Across the Pine Wilt Disease Complex.

Climate change may redistribute forest pests, pathogens, natural enemies, and host trees, yet these components are still often projected independently. We used ensemble species distribution models (SDMs) to map potential climatic suitability for Monochamus alternatus, Dastarcus helophoroides, Scleroderma guani, Bursaphelenchus xylophilus, and a genus-level Pinus host layer, and then summarized niche overlap, range overlap, and multispecies co-suitability under SSP1-2.6, SSP3-7.0, and SSP5-8.5 for the 2050s and 2090s. A structural equation model (SEM) fitted to thresholded binary layers was retained only as an exploratory description of conditional spatial associations. Because its inputs were suitability classifications rather than abundance, infection, parasitism, nematode load, or transmission data, neither arrow direction nor coefficient sign is interpreted causally. The strongest joint modeled suitability for the vector, pathogen, host, and at least one natural enemy occurred in East Asia, whereas B. xylophilus alone also showed potential climatic suitability in parts of the Americas and Africa. Importantly, the current model underpredicted the established occurrence of B. xylophilus in Portugal and western Spain, demonstrating that mapped unsuitable cells cannot be interpreted as confirmed absence. The genus-level Pinus layer similarly represents broad host availability rather than species-specific susceptibility. Because the future maps are based on averages across three general circulation models and the archived outputs do not permit retrospective estimation of inter-model variability, these projections should be treated as screening-level, scenario-conditioned summaries rather than uncertainty-bounded forecasts. The results identify priorities for surveillance and field validation, but they do not quantify disease incidence, interaction strength, or biological-control efficacy.