Climate change may alter grassland pest distributions, yet province-wide comparisons based on extensive field surveys remain limited in Yunnan, China. We analysed 10,342 census and special-survey records, retaining 4281 species–climate-cell records for nine pests. Five WorldClim predictors entered ten-algorithm ensembles weighted by the true skill statistic (TSS), evaluated using nested spatial cross-validation. Three climate models projected SSP1-2.6, SSP2-4.5, and SSP5-8.5 across four 20-year periods spanning 2021–2100. Predictive performance varied among species: area under the receiver operating characteristic curve (AUC) ranged from 0.591 to 0.778, and TSS from 0.198 to 0.365. Pseudoxya diminuta had the highest AUC (0.778), Patanga japonica the highest TSS (0.365), and the 27-cell Holotrichia parallela model the lowest AUC (0.591). Warm-quarter precipitation ranked first for six species, with mean permutation-induced AUC decreases of 0.054–0.145. Baseline threshold-defined suitable area was largest for Oxya chinensis (235.3 × 10³ km²). By 2081–2100 under SSP5-8.5, consensus suitable area declined by 63.4% for P. japonica and 54.6% for P. diminuta. These species-specific climatic associations and projected changes provide a basis for coordinated provincial surveillance, supported by survey-derived county–township revisit priorities.

Rapid detection of wilt-affected pine crowns in mountainous forests is hindered by occlusion, self-shadowing, and heterogeneous backgrounds in conventional nadir products. We evaluated whether oblique UAV RGB imagery improves crown-level detection relative to nadir imagery under matched site, season, sensor, and workflow conditions. The workflow was designed for rapid post-flight screening of geotagged UAV photographs. Paired nadir orthophotos and 45–70° oblique photographs were acquired over pine stands in Wenshan Prefecture, Yunnan, China, and organized into D1 (nadir), D2 (oblique), and D3 (simple mixed-view concatenation). Three YOLO11 detectors were trained for crown shoot damage ratio (SDR)-derived operational classes: early-stage (SDR < 50%), severely damaged (SDR ≥ 50%), and withered (needle-free dead crowns). A paired crown-level RGB subset (n = 20 crowns observed in both views) was analyzed as supporting evidence for view-dependent appearance differences. The oblique-image model (D2) achieved the highest validation performance, with precision of 0.994, recall of 0.991, F1-score of 0.989, mAP@0.5 of 0.995, and mAP@0.5:0.95 of 0.880. The paired subset showed a significant multivariate RGB profile difference between views (Hotelling’s T2 = 58.91, F = 3.10, p = 0.044), driven mainly by reduced Excess Green and greater dispersion of blue-related traits under oblique viewing. These results indicate that oblique UAV photographs retain additional crown-edge, lateral-structure, and chromatic context for detecting wilt-affected pine crowns. Oblique RGB imagery therefore provides a practical, low-cost input for rapid forest health surveillance and targeted field verification in rugged pine landscapes.