Jinxin Zhang

Global climate change is accelerating and human pressures are intensifying, exerting profound impacts on biodiversity and ecosystem service functions. The accurate prediction of species distributions has thus become a critical research direction in ecological conservation and restoration. This study selected Puccinellia tenuiflora, a species distributed across China, as its research subject. Utilizing 169 occurrence records and 10 environmental variables, we applied a parameter-optimized MaxEnt model to simulate the species’ current and future (2050s–2090s) potential suitable habitats under the SSP126, SSP370, and SSP585 scenarios. The results identified the human footprint index (HFI, 43.3%) and temperature seasonality (Bio4, 26.9%) as the dominant factors influencing its distribution. The current suitable area is primarily concentrated in northern China, covering approximately 258.26 × 10⁴ km². Under all future scenarios, a contraction of suitable habitat is projected, with the most significant reduction observed under SSP585 by the 2090s (a decrease of 56.2%). The distribution centroid is projected to shift northeastward by up to 145.36 km. This study elucidates the response mechanism of P. tenuiflora distribution to climate change and human activities. The projected habitat contraction and spatial displacement highlight the potential vulnerability of this species to future climate change. These findings, derived from a rigorously optimized and spatially validated model, provide a scientific basis for the conservation, reintroduction, and adaptive management of P. tenuiflora under climate change.

The distribution of Itea yunnanensis, a shrub species in the genus Itea of the family Iteaceae, is primarily concentrated in the Hengduan Mountains region of China, where it faces severe threats from global climate change. However, systematic research on the species’ distribution patterns, climatic response mechanisms, and future suitable habitat dynamics remains insufficient. This study aims to assess the spatiotemporal evolution and driving mechanisms of I. yunnanensis-suitable habitats under current and future climate change scenarios to reveal the migration patterns of its distribution centroid and ecological thresholds, and to enhance the reliability and interpretability of predictions through model optimization. For MaxEnt modeling, we utilized 142 georeferenced occurrence records of I. yunnanensis alongside environmental data under current conditions and three future Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, SSP5-8.5). Model parameter optimization (Regularization Multiplier, Feature Combination) was performed using the R (v4.2.1) package ‘ENMeval’. The optimized model (RM = 3.0, FC = QHPT) significantly reduced overfitting risk (ΔAICc = 0) and achieved high prediction accuracy (AUC = 0.968). Under current climate conditions, the total area of potential high-suitability habitats for I. yunnanensis is approximately 94.88 × 10⁴ km², accounting for 9.88% of China’s land area, with core areas located around the Hengduan Mountains. Under future climate change, the suitable habitats show significant divergence, area fluctuation and contraction under the SSP1-2.6 scenario, and continuous expansion under the SSP5-8.5 scenario. Meanwhile, the species’ distribution centroid exhibits an overall trend of northwestward migration. This study not only provides key spatial decision-making support for the in situ and ex situ conservation of I. yunnanensis, but also offers an important methodological reference for the adaptive research on other ecologically vulnerable species facing climate change through its optimized modeling framework.

Lysimachia christinae, a regionally endemic medicinal plant in China, is crucial for ecosystems and traditional medicine. This study evaluates climate change impacts on the geographic spread of L. christinae by employing an optimized MaxEnt model based on 625 valid occurrence points and various climatic variables. The model was refined with ENMeval in R, selecting optimal feature combinations (FC) and regularization multipliers (RM). The model's predictive performance was evaluated via the AUC metric, and the distribution changes were analyzed across three Shared Socioeconomic Pathways (SSPs) spanning the 2050s, 2070s, and 2090s. The findings indicated that the refined MaxEnt model exhibited strong predictive performance, achieving an AUC of 0.904. The min temperature of coldest month (Bio6) and the standard deviation of temperature seasonality (Bio4) were identified as the principal climatic variables affecting the geographic range of L. christinae , contributing 68.7% and 20.2%, respectively, under current climatic conditions. Within the SSP1‐2.6 pathway, the viable habitat zone remained relatively stable, with retention rates of 86.78%, 86.13%, and 82.03% during the decades of the 2050s, 2070s, as well as 2090s. However, in the context of the SSP5‐8.5 pathway, the retention rate significantly decreased to 64.77% by the 2090s, indicating greater habitat instability and expansion needs. The research highlights the critical role of thermal variables in shaping L. christinae 's distribution and emphasizes the need for adaptive conservation strategies targeting stable or expanding habitats to ensure its long‐term survival amid climate change.

Identifying ecological distribution responses to climate change is pivotal for preserving biodiversity. Ilex macrocarpa, a deciduous tree of the Aquifoliaceae family, has considerable ecological and medicinal benefits. This study investigated the impact of climate change on the potential distribution of I. macrocarpa using MaxEnt modeling and GIS analysis. We analyzed 562 occurrence records against 19 bioclimatic variables, subsequently refined to 7 key predictors through Pearson correlation analysis (|r| ≤ 0.75). The MaxEnt model demonstrated high predictive accuracy (AUC = 0.902 ± 0.010). Annual precipitation (67.9% contribution) and the minimum temperature of the coldest month (18.4% contribution) emerged as the primary determinants of I. macrocarpa distribution. Currently, suitable habitats occupy 252.97 × 10⁴ km² (26.35%) of the total land area of China, with highly suitable areas (72.82 × 10⁴ km²) predominantly found in southern China. Under future scenarios, substantial distribution shifts are projected: SSP126 shows a 21.7% reduction in suitable area by 2050, followed by a 9.1% recovery by 2090; SSP245 indicates a 13.4% reduction by 2050 with minimal subsequent change; and SSP585 demonstrates the most severe impact, with a 32.0% reduction by 2090. Habitat centroid analysis reveals significant northeastward shifts under SSP126 (116.23 km by 2090), variable movements under SSP245, and southwestern displacement under SSP585 (143.23 km by 2090). These findings suggest differential responses across climate scenarios, with implications for conservation planning and management strategies.