Climate change significantly impacts species distribution and survival, particularly for habitat specialists with limited dispersal abilities. This study investigates the current and future distribution of Tylonycteris pachypus, one of the world’s smallest bats specialized in bamboo-dwelling, using ensemble modeling approaches. Based on comprehensive occurrence data and seven environmental variables, we developed an ensemble model using the Biomod2 platform, achieving high predictive accuracy (AUC: 0.981, TSS: 0.877). Three environmental variables were identified as crucial determinants: minimum temperature of the coldest month (40.90% contribution), maximum temperature of the warmest month (38.38%), and precipitation of the wettest quarter (11.09%). Currently, highly suitable habitats (291.893 × 10⁴ km²) are concentrated in three main regions: southern China and Indochina Peninsula, Myanmar–Bangladesh–northeastern India, and isolated areas in southwest India and Thailand. Under future climate scenarios, particularly SSP585, suitable habitats are projected to decrease substantially (64.4% reduction by 2090s), with a notable northward shift in distribution. However, the species’ limited dispersal ability, specific habitat requirements, and geographical barriers may constrain its capacity to track these climate-driven changes. Our findings highlight the vulnerability of T. pachypus to climate change and emphasize the need for targeted conservation strategies, including protecting climate-resilient habitats and maintaining bamboo forest corridors. This study provides a comprehensive framework for monitoring and conserving this specialized species under climate change, while considering its unique ecological constraints and dispersal limitations.

Global CO₂ concentrations are gradually increasing, and forests, as the main terrestrial carbon pool, are attracting growing attention in mitigating climate change. However, the impacts of forest types, species diversity, structural diversity, and environmental factors on the carbon sequestration mechanisms of subtropical forests remain unclear. This study established 45 forest plots (20 m × 20 m) in Lishui City, aiming to investigate the relationships between forest diversity, environmental factors, and carbon storage of subtropical forests among different forest types. Results showed that coniferous forests had the lowest species diversity (0.86), which exhibited extremely significant differences from broad-leaved forests (1.47, p < 0.01) and coniferous broad-leaved mixed forests (1.58, p < 0.01). The carbon storage of broad-leaved forests was 97.50 t·ha⁻¹, which was higher than that of coniferous broad-leaved mixed forests (77.08 t·ha⁻¹) and coniferous forests (75.57 t·ha⁻¹). The carbon storage of coniferous forests was significantly positively affected by species diversity (p < 0.05). Tree height was the most significant structural diversity factor affecting forest carbon storage (p < 0.05). The results of the structural equation model (SEM) showed that the proportion of broad-leaved trees in forests and structural diversity had a significant positive effect on carbon storage (p < 0.01). Species diversity had a non-linear relationship with carbon storage. The ecological niche complementarity effect and selection effect interacted with changes in species diversity. When the species diversity was lower than 1.12 (Shannon–Wiener index), the ecological niche complementarity effect dominated and promoted carbon sequestration; when it was above this threshold, the selection effect dominated and weakened carbon sequestration. This study recommends prioritizing the planting of broad-leaved tree species during afforestation and paying attention to the current status of forest diversity.

Greenhouse gases emitted by humans have exacerbated global climate change. Forests can effectively sequester atmospheric carbon dioxide through photosynthesis, and afforestation has been widely adopted worldwide to mitigate climate change. Cunninghamia lanceolata and Pinus massoniana, as major afforestation tree species, are extensively cultivated in southern China. However, the mechanisms by which climate, topography, biodiversity, forest structure, and forest growth status affect the productivity of these two species remain unclear. This study used forest inventory data from Lishui City combining the Biomod2 model with a structural equation model (SEM) to investigate the differential effects of biotic and abiotic factors on the productivity of the two tree species. The results showed that at the same diameter at breast height (DBH), the biomass of P. massoniana reached 384.67 kg, accounting for 188.75% of that of C. lanceolata (211.07 kg). The dominant climatic factors affecting C. lanceolata and P. massoniana were different; the most important climatic factors affecting C. lanceolata were Bio 17, Bio 15, Bio 05, Bio 08, and Bio 02, while those affecting P. massoniana were Bio 18, Bio 04, and Bio 01. Furthermore, the explanatory power of the structural equation model (SEM) optimized by the Biomod2 model was effectively improved. Biodiversity and forest growth factors were the most important biotic factors affecting C. lanceolata (p < 0.01), while structural diversity and forest growth factors were the most important biotic factors affecting P. massoniana (p < 0.05). Biodiversity and structural diversity exerted divergent effects on C. lanceolata and P. massoniana in different growth stages, exerting negative effects in the early growth stage and positive effects in the late growth stage. These outcomes were jointly driven by the selection effect and niche complementarity. This study recommends the forest management practices should select tree species based on local conditions.