Search Results (22)

Global warming is accelerating the poleward and upward shifts in climatically suitable ranges of species. Panicum virgatum (switchgrass) is recognized for its dual value in China’s dual-carbon strategy: mitigating food–energy land competition and restoring marginal ecosystems. However, the accuracy of habitat projections is constrained by three limitations: reliance on North American provenance data, uncalibrated model parameters, and insufficient scenario coverage. To address these, 48 switchgrass occurrence records and 22 climatic–topographic variables were integrated. The MaxEnt model was optimized with ENMeval (RM = 4.0, FC = LQH) and coupled with three SSP scenarios (SSP1-2.6, SSP3-7.0, SSP5-8.5) to quantify habitat area changes and centroid shifts across China. The key findings were as follows: (1) The mean temperature of the coldest quarter (Bio11) and elevation were identified as the key limiting factors for the suitable distribution of switchgrass, with their corresponding optimal thresholds determined as −8.79 to 8.11 °C and 0 to 2893 m, respectively. (2) The current suitable habitat covers 583.58 × 10⁴ km², concentrated in the North China Plain. (3) Under SSP5-8.5, the high-suitability habitat is projected to reach 229.44 × 10⁴ km² by the 2090s, with the centroid migrating 305 km northwestward to the Inner Mongolia–Jilin belt. This study highlights the climate–topography coupling that drives northward migration and proposes cold-tolerant cultivar development, priority zoning of marginal lands, and ecological corridor establishment to inform climate-smart biomass energy planning in China. Full article

Climate change poses unprecedented challenges to forest ecosystems. Betula alnoides, a tree species with significant ecological and economic value in southern China, has been the subject of studies on its distribution pattern and response to climate change. However, research on the distribution pattern of B. alnoides and its response to climate change remains relatively limited. In this study, we developed a MaxEnt model incorporating multiple environmental variables, including climate, topography, soil, vegetation, and human activities, to evaluate model performance, identify key factors influencing the distribution of B. alnoides, and project its potential distribution under various future climate scenarios. Species occurrence data and environmental layers were compiled for China, and model parameters were optimized using the ENMeval package. The results showed that the optimized model achieved an AUC value of 0.956, indicating extremely high predictive accuracy. The four key factors affecting the distribution of B. alnoides were standard deviation of temperature seasonality (Bio4), normalized difference vegetation index (NDVI), mean temperature of driest quarter (Bio9), and annual precipitation (Bio12). Among them, the cumulative contribution rate of climatic factors reached 68.9%, but the influence of NDVI was significantly higher than that of precipitation factors. The current suitable habitat of B. alnoides is mainly concentrated in the southwestern region, covering an area of 179.32 × 10⁴ km², which accounts for 18.68% of China’s land area. Under the SSP126 scenario, the suitable habitat area first decreases and then increases in the future, while under the SSP370 and SSP585 scenarios, the suitable habitat area continues to shrink, with significant losses in high-suitability areas. In addition, the centroid of the suitable habitat of B. alnoides shows an overall trend of shifting northwestward. This indicates that B. alnoides is highly sensitive to climate change and its distribution pattern will undergo significant changes in the future. In conclusion, the distribution pattern of B. alnoides shows a significant response to climate change, with particularly prominent losses in high-suitability areas in the future. Therefore, it is recommended to strengthen the protection of high-suitability areas in the southwestern region and consider B. alnoides as an alternative tree species for regions facing warming and drying trends to enhance its climate adaptability. Full article

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. Full article

To ensure food security in Xinjiang, scientifically conducting land suitability evaluation is of significant importance. This paper takes an arid and ecologically fragile region of southern Xinjiang—Qiemu County—as an example. Based on the optimized Maximum Entropy (MaxEnt) model, 14 multi-source environmental variables including climate, soil, hydrology, and topography are integrated. The ENMeval package is used to optimize the model parameters, and Spearman’s rank correlation analysis is employed to screen key variables. The spatial distribution of land suitability and the dominant factors are systematically assessed. The results show that the model AUC values for the mountainous and plain areas are 0.987 and 0.940, respectively, indicating high accuracy. In the plain area, land suitability is primarily influenced by the soil sand content, while in the mountainous region, the annual accumulated temperature plays a leading role. The highly suitable areas are mainly distributed in the northern plains and parts of the southern mountains. This study clarifies the suitable areas for land development and environmental thresholds, providing a scientific basis for the development of land resources in arid regions and the implementation of the “store grain in the land” strategy. Full article

The Chinese Caterpillar Fungus (CCF) is a precious and rare traditional Chinese medicinal material that is extremely sensitive to environmental changes, making wild resources scarce. Therefore, studying the impact of climate change on the potential distribution and changes of the CCF is of great significance. Employing an enhanced MaxEnt approach (optimized with ENMeval), this study determined the primary ecological constraints on CCF and mapped its potential present and future ranges. The results indicated that elevation, bio05, bio04, bio12, bio11, slope, d1_ph_water, and hf were the driving environmental factors influencing the survival of the CCF. The ideal habitat zones for the CCF were mainly distributed in the plateau and alpine climate zones of northwestern and southwestern China, covering an area of 7.42 × 10⁴ km². Compared with the current climate scenario, the area of suitable habitats for the CCF was expected to increase in the future. In the 2090s, under the SSP1–2.6 scenario, the highly suitable areas for the CCF will have increased the most, by 67.54%, while the low–suitability areas will have decreased by 6.87%. Overall, the highly suitable areas for the CCF will shift towards higher latitudes. The outcomes of this study can inform subsequent conservation strategies for CCF resources and facilitate research on other ecological variables affecting CCF distribution patterns. Full article

Chinese Caterpillar Fungus (CCF) is a fungal–insect complex formed by the underground larvae of certain species in the family Hepialidae parasitized by Ophiocordyceps sinensis (Berk.) (G.H.Sung, J.M.Sung, Hywel-Jones & Spatafora). It is a precious Chinese herbal medicine with significant medicinal value. This study aimed to identify the key environmental factors influencing the distribution of CCFs using the MaxEnt model. First, in the MaxEnt model optimized using the ENMeval package, the most suitable combinations of feature classes and regularization parameters were selected. Second, 22 environmental variables were used to construct distribution models for O. sinensis, host insects, and CCFs. Then, the distribution areas of O. sinensis and host insects were overlapped to identify highly suitable habitats where both coexist. Finally, these highly suitable habitats were compared to analyze the differences in the distribution areas of O. sinensis and host insects and their contributions to the formation of the CCF distribution area. The results showed that elevation, bio18, and bio09 were the primary environmental factors influencing the distributions of O. sinensis, host insects, and CCFs. Considering the present, 2050s, and 2070s, the highly suitable areas for all three entities overlapped to a large extent. When we superimposed the high-suitability zones of O. sinensis and host insects, the overlapping area was found to be 56.87 × 10⁴ km², which accounted for 5.92% of China’s total land area. The high-suitability area for CCFs was 64.06 × 10⁴ km², accounting for 6.67% of China’s total land area. The findings of this study provide valuable insights into the mechanisms behind the combination of O. sinensis and host insects in forming CCFs. Full article

Acorus calamus, a perennial emergent herb, is highly valued for its ornamental appeal, water purification ability, and medicinal properties. However, there is a significant contradiction between the rapidly increasing demand for A. calamus and the diminishing wild resources. Understanding its geographical distribution and the influence of global climate change on its geographical distribution is imperative for establishing a theoretical framework for the conservation of natural resources and the expansion of its cultivation. In this study, 266 distribution records of A. calamus and 18 selected key environmental factors were utilized to construct an optimal MaxEnt model via the ENMeval package. We simulated the potential geographical distributions under current conditions and under three different climate scenarios (SSP126, SSP370, and SSP585) in the 2050s, 2070s, and 2090s. Additionally, we employed the jackknife method and response curves to identify the environmental factors with the greatest influence on the distribution of A. calamus, and their response intervals. The results indicate that the regularization multiplier (RM) of 3.5 and the feature combinations (FC) of linear (L), quadratic (Q), hinge (H), and product (P) are the optimal model parameter combinations. With these parameters, the model predictions are highly accurate, and the consistency of the results is significant. The dominant environmental factors and their thresholds affecting the distribution of A. calamus are the precipitation of the wettest month (≥109.87 mm), human footprint (≥5.39), annual precipitation (≥388.56 mm), and mean diurnal range (≤12.83 °C). The primary land use types include rivers and channels, reservoirs and ponds, lakes, urban areas, marshes, other constructed lands, rice fields, forested areas, and shrublands. Under current climate conditions, the suitable geographical distribution of A. calamus in China is clearly located east of the 400 mm precipitation line, with high- and low-suitability areas covering 121.12 × 10⁴ km², and 164.20 × 10⁴ km², respectively. Under future climate conditions, both high- and low- suitability areas are projected to increase significantly, whereas unsuitable areas are expected to decrease, with the centroid of each suitability zone shifting northward. This study provides a theoretical foundation for sustainable utilization, future production planning, and the development of conservation strategies for wild germplasm resources of A. calamus. Full article

The Northeastern China Salamander (Hynobius leechii) is classified as a rare, nationally protected Class II wild animal in China. Its population is declining, and its habitat is deteriorating. This study aimed to predict the distribution of suitable habitats for the Northeastern China Salamander under both current and future climate scenarios, utilizing the MaxEnt model optimized through ENMeval parameters. Species distribution data were collected from field surveys, existing literature, amphibian records in China, and the Global Biodiversity Information Network. A total of 97 records were compiled, with duplicate records within the ENMTools grid unit removed, ensuring that only one record existed within every 5 km. Ultimately, 58 distinct distribution points for the Northeastern China Salamander were identified. The R software package ‘ENMeval 2.0’ was employed to optimize the feature complexity (FC) and regularization multiplier (RM), and the optimized model was applied to assess the suitable distribution regions for the Northeastern China Salamander under present and future climate conditions. The findings indicated that rainfall and temperature are the primary environmental factors influencing Hynobius. Currently, the suitable habitat for the Northeastern China Salamander constitutes 6.6% of the total area of Northeastern China. Projections for the periods of 2050 and 2070 suggest that suitable habitats for the Northeastern China Salamander will continue to expand towards higher latitudes across three climate scenarios. While this study focuses solely on climate change factors and acknowledges certain limitations, it serves as a reliable reference and provides essential information for the distribution and conservation of the Northeastern China Salamander. Full article

The widespread and complex formation of saline soils in China significantly affects the sustainable development of regional ecosystems. Intense climate changes and regional land use further exacerbate the uncertainties faced by ecosystems in saline areas. Therefore, studying the distribution characteristics of typical halophytic vegetation under the influence of climate change and human activities, and exploring their potential distribution areas, is crucial for maintaining ecological security in saline regions. This study focuses on Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya, integrating geographic information systems, remote sensing, species distribution models, and landscape ecological risk (LER) theories and technologies. An optimized MaxEnt model was established using the ENMeval package, incorporating 143, 173, and 213 distribution records and 13 selected environmental variables to simulate the potential suitable habitats of these three Tamarix species. A quantitative assessment of the spatial characteristics and the area of their potential geographical distribution was conducted. Additionally, a landscape ecological risk assessment (LERA) of the highly suitable habitats of these three Tamarix species was performed using land use data from 1980 to 2020, and the results of the LERA were quantified using the Landscape Risk Index (LERI). The results showed that the suitable areas of Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya were 9.09 × 10⁵ km², 6.03 × 10⁵ km², and 5.20 × 10⁵ km², respectively, and that the highly suitable habitats for the three species were concentrated in flat areas such as plains and basins. Tamarix austromongolica faced increasing ecological risk in 27.22% of its highly suitable habitat, concentrated in the northern region, followed by Tamarix chinensis in 16.70% of its area with increasing ecological risk, concentrated in the western and northern highly suitable habitats; Tamarix chinensis was the least affected, with an increase in ecological risk in only 1.38% of its area. This study provides valuable insights for the protection of halophytic vegetation, represented by Tamarix, in the context of China’s national land development. Full article

Betula luminifera H. Winkler, a fast-growing broad-leaved tree species native to China’s subtropical regions, possesses significant ecological and economic value. The species’ adaptability and ornamental characteristics make it a crucial component of forest ecosystems. However, the impacts of global climate change on its geographical distribution are not well understood, necessitating research to predict its potential distribution shifts under future climate scenarios. Our aims were to forecast the impact of climate change on the potential suitable distribution of B. luminifera across China using the MaxEnt model, which is recognized for its high predictive accuracy and low sample data requirement. Geographical coordinate data of B. luminifera distribution points were collected from various databases and verified for redundancy. Nineteen bioclimatic variables were selected and screened for correlation to avoid overfitting in the model. The MaxEnt model was optimized using the ENMeval package, and the model accuracy was evaluated using the Akaike Information Criterion Correction (delta.AICc), Training Omission Rate (OR10), and Area Under the Curve (AUC). The potential distribution of B. luminifera was predicted under current and future climate scenarios based on the Shared Socio-economic Pathways (SSPs). The optimized MaxEnt model demonstrated high predictive accuracy with an AUC value of 0.9. The dominant environmental variables influencing the distribution of B. luminifera were annual precipitation, minimum temperature of the coldest month, and standard deviation of temperature seasonality. The potential suitable habitat area and its geographical location were predicted to change significantly under different future climate scenarios, with complex dynamics of habitat expansion and contraction. The distribution centroid of B. luminifera was also predicted to migrate, indicating a response to changing climatic conditions. Our findings underscore the importance of model optimization in enhancing predictive accuracy and provide valuable insights for the development of conservation strategies and forest management plans to address the challenges posed by climate change. Full article

Global climate changes are expected to profoundly shape species distribution. Quercus oxyphylla, a valuable evergreen broad-leaved tree species, is rigorously conserved and managed in China owing to its substantial scientific, economic, and ecological value. However, the impact of projected climate change on its future distribution and potential climatic drivers remains unclear. Here, a maximum entropy model (MaxEnt) was used to explore the distribution of Q. oxyphylla in China under current conditions and three future scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the 2050s and 2070s. We optimized the model using the ‘ENMeval’ package to obtain the best parameter combination (RM = 1, FC = LQHPT), and multiple evaluation metrics (AUC ≥ 0.9; TSS ≥ 0.6; Kappa ≥ 0.75) verified the high accuracy of the model and the reliability of the prediction results. We found the following: (1) The potential distribution of Q. oxyphylla spans across 28 provinces in China under current climatic conditions, predominantly in southern regions, with Sichuan exhibiting the largest suitable area for survival. The total suitable habitat covers 244.98 × 10⁴ km², comprising highly, moderately, and poorly suitable habitats of 51.66 × 10⁴ km², 65.98 × 10⁴ km², and 127.34 × 10⁴ km², respectively. (2) Under future climate conditions, the overall geographical boundaries of Q. oxyphylla are predicted to remain similar to the present one, with an increase of 10.29% in the 2050s and 11.31% in the 2070s. In the 2050s, the total suitable habitats for Q. oxyphylla under the three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) might increase by 8.83%, 9.62%, and 12.42%, while in the 2070s they might increase by 10.39%, 17.21%, and 6.33%, respectively. (3) Moreover, the centroid of the suitable area is expected to migrate southwestward under the three scenarios in the future. (4) Annual precipitation, isothermality, and temperature annual range emerged as the main factors influencing the distribution of Q. oxyphylla, with contributions of 55.9%, 25.7%, and 13.5%, respectively. Our findings refined the spatial arrangement of Q. oxyphylla growth and revealed its climate resilience. This suggested that under climate change, Sichuan and Shaanxi are the optimal regions for cultivation and management, while appropriate conservation strategies should be formulated in Tibet and Hubei. Full article

Liriodendron chinense (Hemsl.) Sarg. (Magnoliales: Magnoliaceae), valued for its medicinal properties and timber and as an ornamental plant, is now classified as an endangered species. Investigating how future climate-change scenarios might affect the potential geographic distribution of L. chinense will provide a crucial scientific basis for its protection and management strategies. The MaxEnt model was calibrated using the ENMeval optimization package, and then it was coupled with ArcGIS 10.8 to forecast the possible distribution areas of L. chinense in China, utilizing elevation data, bioclimatic factors, and human footprint as environmental variables. The results indicate: (1) The optimal model parameters were set as follows: FC = LQ, RM = 0.5, the MaxEnt model demonstrated high predictive accuracy and minimal overfitting; (2) The total suitable habitat area for the potential geographical distribution of L. chinense during the current period is estimated at 151.55 × 10⁴ km², predominantly located in central, eastern, and southwestern regions of China; (3) The minimum temperature of the coldest month (bio6), precipitation of the driest month (bio14), precipitation of the driest quarter (bio17), precipitation of the warmest quarter (bio18), elevation (alt), and human footprint (hf) are the main environmental variables determining the suitable habitat distribution of L. chinense; (4) During the period from 2041 to 2060, under the carbon emission scenarios of SSP126, SSP245, and SSP370, the suitable habitat for L. chinense shows varying degrees of increase compared to the current period. However, under the highest concentration scenario of SSP585, the suitable habitat area decreases to some extent; (5) The distribution of L. chinense is likely to move towards higher latitudes and elevations in the future due to changes in the climate. This research provides a comprehensive analysis of the potential impacts of climate change on L. chinense, offering valuable information for its protection and management under future climatic conditions. Full article

The invasive pest, Bactrocera tsuneonis (Miyake), has become a significant threat to China’s citrus industry. Predicting the area of potentially suitable habitats for B. tsuneonis is essential for optimizing pest control strategies that mitigate its impact on the citrus industry. Here, existing distribution data for B. tsuneonis, as well as current climate data and projections for four future periods (2021–2040, 2041–2060, 2061–2080, and 2081–2100) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were obtained. The distribution of B. tsuneonis under current and different climate change scenarios in China was predicted using the optimized MaxEnt model, ArcGIS, and the ENMeval data package. Model accuracy was assessed using ROC curves, and the primary environmental factors influencing the distribution of the pest were identified based on the percent contribution. When the regularization multiplier (RM) was set to 1.5 and the feature combination (FC) was set to LQH, a model with lower complexity was obtained. Under these parameter settings, the mean training AUC was 0.9916, and the mean testing AUC was 0.9854, indicating high predictive performance. The most influential environmental variables limiting the distribution of B. tsuneonis were the Precipitation of Warmest Quarter (Bio18) and Temperature Seasonality (standard deviation ×100) (Bio4). Under current climatic conditions, potentially suitable habitat for B. tsuneonis in China covered an area of 215.9 × 10⁴ km², accounting for 22.49% of the country’s land area. Potentially suitable habitat was primarily concentrated in Central China, South China, and East China. However, under future climatic projections, the area of suitable habitat for B. tsuneonis exhibited varying degrees of expansion. Furthermore, the centroid of the total suitable habitat for this pest gradually shifted westward and northward. These findings suggest that B. tsuneonis will spread to northern and western regions of China under future climate changes. The results of our study indicate that climate change will have a major effect on the invasion of B. tsuneonis and have implications for the development of strategies to control the spread of B. tsuneonis in China. Full article

Climate change has been considered to pose critical threats for wildlife. During the past decade, species distribution models were widely used to assess the effects of climate change on the distribution of species’ suitable habitats. Among all the vertebrates, amphibians are most vulnerable to climate change. This is especially true for salamanders, which possess some specific traits such as cutaneous respiration and low vagility. The Wushan salamander (Liua shihi) is a threatened and protected salamander in China, with its wild population decreasing continuously. The main objective of this study was to predict the distribution of suitable habitat for L. shihi using the ENMeval parameter-optimized MaxEnt model under current and future climate conditions. Our results showed that precipitation, cloud density, vegetation type, and ultraviolet radiation were the main environmental factors affecting the distribution of L. shihi. Currently, the suitable habitats for L. shihi are mainly concentrated in the Daba Mountains, including northeastern Chongqing and western Hubei Provinces. Under the future climate conditions, the area of suitable habitats increased, which mainly occurred in central Guizhou Province. This study provided important information for the conservation of L. shihi. Future studies can incorporate more species distribution models to better understand the effects of climate change on the distribution of L. shihi. Full article

Climate change affects the geographical distribution of plant species. Rare Trachycarpus nanus with a narrow distribution range, high medicinal value and extremely small population is facing increasing extinction risks under global climate change. In this study, 96 recorded occurrences and 23 environmental factors are used to predict the potential suitable area of T. nanus based on the optimized MaxEnt (3.4.4) model and ArcGIS (10.7) software. The results show that when the parameters are FC = LQ and RM = 1, the MaxEnt model is optimal and AUC = 0.946. The distribution patterns were predicted in the past, present, and four future phases, i.e., 2021–2040 (2030), 2041–2060 (2050), 2061–2080 (2070), and 2081–2100 (2090). The main factors are the annual precipitation (bio12), mean temperature of the coldest quarter (bio11), temperature seasonality (bio4), precipitation of the wettest quarter (bio16), and isothermality (bio3). The potential distribution of T. nanus is primarily concentrated in central Chuxiong, encompassing a total potential suitable area of 5.65 × 10⁴ km². In historical periods, the total habitat area is smaller than that in the present. In the future, the potential suitable area is generally increased. The centroid analysis shows that T. nanus will move to a high-altitude area and to the southeast. But its dispersal capacity may not keep up with the climate change rate. Therefore, additional protection sites for this species should be appropriately established and the habitat connectivity should be enhanced. Full article