Search Results (347)

Trachypteris picta (Pallas, 1773) is a significant pest that can cause serious damage to poplars and willows. To assess the impact of climate change on the suitable habitats of T. picta, this study conducted a comparative analysis of its global suitable habitats using climatic factors, global land use type, and global vegetation from different periods, in combination with the maximum entropy (MaxEnt) model. The results indicate that the annual mean temperature (Bio01), mean temperature of the coldest quarter (Bio11), precipitation of the coldest quarter (Bio19), and isothermality (Bio03) are the four most important climate variables determining the distribution of T. picta. Under the current climate conditions, the highly suitable areas are primarily located in southern Europe, covering an area of 2.22 × 10⁶ km². Under future climate scenarios, the suitable habitat for T. picta is expected to expand and shift towards higher latitudes. In the 2050s, the SSP5-8.5 scenario has the largest suitable area compared to other scenarios, while the SSP2-4.5 scenario has the largest suitable area in the 2090s. In addition, the centroids of the total suitable areas are expected to shift toward higher latitudes under future climate conditions. The results of this study provide valuable data for the monitoring, control, and management of this pest. Full article

Understanding alpine plants’ survival and reproduction is crucial for their conservation in climate change. Based on 423 valid distribution points, this study utilizes the MaxEnt model to predict the potential habitat and distribution dynamics of Leontopodium nanum under both current and future climate scenarios, while clarifying the key factors that influence its distribution. The primary ecological drivers of distribution are altitude (2886.08 m–5576.14 m) and the mean temperature of the driest quarter (−6.60–1.55 °C). Currently, the suitable habitat area is approximately 520.28 × 10⁴ km², covering about 3.5% of the global land area, concentrated mainly in the Tibetan Plateau, with smaller regions across East and South Asia. Under future climate scenarios, low-emission (SSP126), suitable areas are projected to expand during the 2050s and 2070s. High-emission (SSP585), suitable areas may decrease by 50%, with a 66.07% reduction in highly suitable areas by the 2070s. The greatest losses are expected in the south-eastern Tibetan Plateau. Regarding dynamic habitat changes, by the 2050s, newly suitable areas will account for 51.09% of the current habitat, while 68.26% of existing habitat will become unsuitable. By the 2070s, newly suitable areas will rise to 71.86% of the current total, but the loss of existing areas will exceed these gains, particularly under the high-emission scenario. The centroid of suitable habitats is expected to shift northward, with migration distances ranging from 23.94 km to 342.42 km. The most significant shift is anticipated under the SSP126 scenario by the 2070s. This study offers valuable insights into the distribution dynamics of L. nanum and other alpine species under the context of climate change. From a conservation perspective, it is recommended to prioritize the protection and restoration of vegetation in key habitat patches or potential migration corridors, restrict overgrazing and infrastructure development, and maintain genetic diversity and dispersal capacity through assisted migration and population genetic monitoring when necessary. These measures aim to provide a robust scientific foundation for the comprehensive conservation and sustainable management of the grassland ecosystem on the Qinghai–Tibet Plateau. Full article

Understanding the impacts of climate change on species’ geographic distributions is fundamental for biodiversity conservation and resource management. As a key plant group for ecological restoration and windbreak and sand fixation in arid and semi-arid ares in China’s Three Northern Regions (Northeast, North, and Northwest China), Caragana spp. exhibit distribution patterns whose regulatory mechanisms by environmental factors remain unclear, with a long-term lack of climatic explanations influencing their spatial distribution. This study integrated 2373 occurrence records of 44 Caragana species in China’s Three Northern Regions with four major environmental variable categories. Using the Biomod2 ensemble model, current and future climate scenario-based suitable habitats for Caragana spp. were predicted. This study innovatively combined quantitative analyses with Kira’s thermal indexes (warmth index, coldness index) and Wenduo Xu’s humidity index (HI) to elucidate species-specific relationships between distribution patterns and hydrothermal climatic constraints. The main results showed that (1) compared to other environmental factors, climate is the key factor affecting the distribution of Caragana spp. (2) The current distribution centroid of Caragana spp. is located in Alxa Left Banner, Inner Mongolia. In future scenarios, the majority of centroids will shift toward lower latitudes. (3) The suitable habitats for Caragana spp. will expand overall under future climate scenarios. High-stress scenarios exhibit greater spatial changes than low-stress scenarios. (4) Hydrothermal requirements varied significantly among species in China’s Three Northern Regions, and 44 Caragana species can be classified into five distinct types based on warmth index (WI) and humidity index (HI). The research findings will provide critical practical guidance for ecological initiatives such as the Three-North Shelterbelt Program and the restoration and management of degraded ecosystems in arid and semi-arid regions under global climate change. Full article

As China’s first systematic assessment of high-risk Amaranthaceae invaders, this study addresses a critical knowledge gap identified in the National Invasive Species Inventory, in which four invasive Amaranthaceae species (Dysphania ambrosioides, Celosia argentea, Amaranthus palmeri, and Amaranthus spinosus) are prioritized due to CNY 2.6 billion annual ecosystem damages in China. By coupling multi-species comparative analysis with a parameter-optimized Maximum Entropy (MaxEnt) model integrating climate, soil, and topographical variables in China under Shared Socioeconomic Pathways (SSP) 126/245/585 scenarios, we reveal divergent expansion mechanisms (e.g., 247 km faster northward shift in A. palmeri than D. ambrosioides) that redefine invasion corridors in the North China Plain. Under current conditions, the suitable habitats of these species span from 92° E to 129° E and 18° N to 49° N, with high-risk zones concentrated in central and southern China, including the Yunnan–Guizhou–Sichuan region and the North China Plain. Temperature variables (Bio: Bioclimatic Variables; Bio6, Bio11) were the primary contributors based on permutation importance (e.g., Bio11 explained 56.4% for C. argentea), while altitude (e.g., 27.3% for A. palmeri) and UV-B (e.g., 16.2% for A. palmeri) exerted lower influence. Model validation confirmed high accuracy (mean area under the curve (AUC) > 0.86 and true skill statistic (TSS) > 0.6). By the 2090s, all species showed net habitat expansion overall, although D. ambrosioides exhibited net total contractions during mid-century under the SSP126/245 scenarios, C. argentea experienced reduced total suitability during the 2050s–2070s despite high-suitability growth, and A. palmeri and A. spinosus expanded significantly in both total and highly suitable habitat. All species shifted their distribution centroids northward, aligning with warming trends. Overall, these findings highlight the critical role of temperature in driving range dynamics and underscore the need for latitude-specific monitoring strategies to mitigate invasion risks, providing a scientific basis for adaptive management under global climate change. Full article

The Chinese red panda (Ailurus styani) is a rare and endangered animal in China; the increase in global temperature and the interference of human activities have caused irreversible effects on the suitable habitat of wild red pandas and threatened their survival. Therefore, it is necessary to carry out scientific research and protection for Chinese red pandas. In this study, the MaxEnt model was used to predict and analyze the suitable habitats of Chinese red pandas in the large and small Xiangling Mountains. The results showed that the main ecological factors affecting the suitable habitat distribution of Chinese red pandas in the Daxiangling Mountains are the average slope (45.6%, slope), the distance from the main road (24.2%, road), and the average temperature in the coldest quarter (11%, bio11). The main ecological factors affecting the suitable habitat distribution of Chinese red pandas in the Xiaoxiangling Mountains are bamboo distribution (67.4%, bamboo), annual temperature range (20.7%, bio7), and the average intensity of human activities (8.7%, Human Footprint). The predicted suitable habitat area of the Daxiangling Mountains is 123.835 km², and the predicted suitable habitat area of the Xiaoxiangling Mountains is 341.873 km². The predicted suitable habitat area of the Daxiangling Mountains accounts for 43.45% of the total mountain area, and the predicted suitable habitat area of the Xiaoxiangling Mountains accounts for 71.38%. The suitable habitat area of the Xiaoxiangling Mountains is nearly three times that of the Daxiangling Mountains, and the proportion of suitable habitat area of the Xiaoxiangling Mountains is much higher than that of the Daxiangling Mountains. The suitable habitat of Chinese red pandas in the Daxiangling Mountains is mainly distributed in the southeast, and the habitat is coherent but fragmented. The suitable habitat of Chinese red panda in Xiaoxiangling Mountains is mainly distributed in the east, and the habitat is more coherent. The results of this study can provide a scientific basis for the protection of the population and habitat of Chinese red pandas in Sichuan. 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

In this cross-disciplinary investigation, we uncover a suite of previously unexamined factors and their intricate interplay that hold causal relationships with the distribution of Trachurus japonicus in the northern reaches of the South China Sea, thereby extending the existing research paradigms. Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of T. japonicus density. A robust experimental design identified nine key factors significantly influencing this density: mean sea-level pressure (msl-0, msl-4), surface pressure (sp-0, sp-4), Summit ozone concentration (Ozone_sum), F10.7 solar flux index (F10.7_index), nitrate concentration at 20 m depth (N3M20), sonar-detected effective vertical range beneath the surface (Height), and survey month (Month). Crucially, stable causal relationships were identified among Ozone_sum, F10.7_index, Height, and N3M20. Variations in Ozone_sum likely impact surface UV radiation levels, influencing plankton dynamics (a primary food source) and potentially larval/juvenile fish survival. The F10.7_index, reflecting solar activity, may affect geomagnetic fields, potentially influencing the migration and orientation behavior of T. japonicus. N3M20 directly modulates primary productivity by limiting phytoplankton growth, thereby shaping the availability and distribution of prey organisms throughout the food web. Height defines the vertical habitat range acoustically detectable, intrinsically linking directly to the vertical distribution and availability of the fish stock itself. Surface pressures (msl-0/sp-0) and their lagged effects (msl-4/sp-4) significantly influence sea surface temperature profiles, ocean currents, and stratification, all critical determinants of suitable habitats and prey aggregation. The strong influence of Month predominantly reflects seasonal changes in water temperature, reproductive cycles, and associated shifts in nutrient supply and plankton blooms. Rigorous robustness checks (Data Subset and Random Common Cause Refutation) confirmed the reliability and consistency of these causal findings. This elucidation of the distinct biological and physical pathways linking these diverse factors leading to T. japonicus density provides a significantly improved foundation for predicting distribution patterns globally and offers concrete scientific insights for sustainable fishery management strategies. Full article

Ostryopsis davidiana shrubs, widely distributed in northern China, have been significantly affected by global warming. Based on the current geographical distribution data of O. davidiana in China, this study used climate data, soil data, topographic data, human activity data, and the “biomod2” integrated model to conduct an integrated study on the suitable habitat of O. davidiana under the current scenario and three future climate scenarios (SSP126, SSP370, and SSP585). The results showed the following: (1) The suitable habitats of O. davidiana are mainly concentrated in the northwest and north China regions, accounting for about 9.09% of the national area, centered in Shanyin County, Shuozhou City, Shanxi Province. (2) The suitable habitats of O. davidiana are mainly influenced by temperature and precipitation, with precipitation of wettest quarter (Bio16), isothermality (Bio3), and maximum temperature of warmest month (Bio5) being the key driving factors, with contribution rates of 25.69%, 24.31%, and 14.45%, respectively. (3) Under the three future climate scenarios, the suitable habitats of O. davidiana are expected to contract significantly, with only the low suitability areas expanding, while the rest would be contracting, showing a trend of losing most of their original habitat. The centroid of the suitable habitat would be shifting westward, and the suitable habitats would be generally migrating to higher elevation areas. (4) Climate change reduces the aggregation of O. davidiana, leading to gradual habitat fragmentation. This study provides a theoretical basis for the conservation of O. davidiana. Full article

Under the pressures of global climate change, the sustainable management of plant resources in alpine gorge regions faces severe challenges. P. aquilinum var. latiusculum is widely harvested and utilized by residents in the upper reaches of the Dadu River–Min River basin due to its high edible and medicinal value. This study employed ensemble models to simulate the potential distribution of P. aquilinum var. latiusculum in this region, predicting the impacts of future climate change on its distribution, the centroid migration of suitable habitats, and niche dynamics. A production dynamics model was also constructed to identify current and future potential cultivation areas by integrating ecological suitability and nutritional component synergies. The results show that current high-suitability areas and core cultivation zones of P. aquilinum var. latiusculum are predominantly distributed in patchy, fragmented patterns across the Wenchuan, Li, Mao, Luding, and Xiaojin Counties and Kangding City. Under climate change, the “mountain-top trap effect” drives a significant increase in high-suitability areas and core cultivation zones, while moderate-to-low-suitability areas and marginal cultivation zones decrease substantially. Meanwhile, suitable habitats and cultivation areas exhibit a northward migration trend toward higher latitudes. The most significant changes in suitable area and cultivation zone extent, as well as the most pronounced niche shifts, occur under high-emission climate scenarios. This research facilitates the development of suitability-based management strategies for P. aquilinum var. latiusculum in the study region and provides scientific references for the sustainable utilization of montane plant resources in the face of climate change. Full article

A key challenge is how to effectively conserve habitats and biodiversity amid widespread habitat fragmentation and loss caused by global urbanization. Despite growing attention to this issue, knowledge of the seasonal dynamics of habitats remains limited, and conservation gaps are still inadequately identified. This study proposes a novel integrated framework, “Habitat Suitability–Risk–Quality”, to improve the assessment of the seasonal bird habitat quality and to identify priority conservation habitats in urban landscapes. The framework was implemented in Wuhan, China, a critical stopover site along the East Asian–Australasian Flyway. It combines the Maximum Entropy (MaxEnt) model to predict the seasonal habitat suitability, the Habitat Risk Assessment (HRA) model to quantify habitat sensitivity to multiple anthropogenic threats, and a refined Habitat Quality (HQ) model to evaluate the seasonal habitat quality. K-means clustering was then applied to group habitats based on seasonal quality dynamics, enabling the identification of priority areas and the development of differentiated conservation strategies. The results show significant seasonal variation in habitat suitability and quality. Wetlands provided the highest-quality habitats in autumn and winter, grasslands exhibited moderate seasonal quality, and forests showed the least seasonal fluctuation. The spatial analysis revealed that high-quality wetland habitats form an ecological belt along the urban–suburban fringe. Four habitat clusters with distinct seasonal characteristics were then identified. However, spatial mismatches were found between existing protected areas and habitats of high ecological value. Notably, Cluster 1 maintained high habitat quality year round, spanning 99.38 km², yet only 46.51% of its area is currently protected. The remaining 53.16 km², mostly situated in urban–suburban transitional zones, remain unprotected. This study provides valuable insights for identifying priority habitats and developing season-specific conservation strategies in rapidly urbanizing regions, thereby supporting the sustainable management of urban biodiversity and the development of resilient ecological systems. Full article

Phytophthora cinnamomi is a globally distributed plant-pathogenic oomycete that threatens economically important crops, including Lauraceae, Bromeliaceae, Fabaceae, and Solanaceae. Utilizing species occurrence records and 35 environmental variables (|R| < 0.8), we employed the MaxEnt model and ArcGIS spatial analysis to systematically predict the potential geographical distribution of P. cinnamomi under current (1970–2000) and future (2030S, 2050S, 2070S, 2090S) climate scenarios across three Shared Socioeconomic Pathways (SSPs). The results indicate that currently suitable habitats cover the majority of China’s provinces (>50% of their areas), with only sporadic low-suitability zones in Qinghai, Tibet, and Xinjiang. The most influential environmental variables were the mean diurnal temperature range, mean temperature of the warmest quarter, annual precipitation, precipitation of the driest month, and elevation. Under future climate scenarios, new suitable habitats emerged in high-latitude regions, while the highly suitable area expanded significantly, with the distribution centroid shifting northeastward. This study employs predictive modeling to elucidate the future distribution patterns of P. cinnamomi in China, providing a theoretical foundation for establishing a regional-scale disease early warning system and formulating ecological management strategies. Full article

Solanum aculeatissimum is a herbaceous to semi-woody perennial plant native to the Brazilian ecosystem. It has naturalized extensively in southwestern China, posing significant threats to local biodiversity. This study systematically screened and integrated 100 distribution records from authoritative databases, including the Chinese Virtual Plant Specimen Database, the Global Biodiversity Information Facility, and Chinese Natural Museums. Additionally, 23 environmental variables were incorporated, comprising 19 bioclimatic factors from the World Climate Dataset, 3 topographic indicators, and the Human Footprint Index. The objectives of this research are as follows: (1) to simulate the plant’s current and future distribution (2050s/2070s) under CMIP6 scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5); (2) to quantify changes in the distribution range; and (3) to determine the migration trajectory using MaxEnt 3.4.4 software. The findings reveal that human pressure (contributing 79.7%) and isothermality (bioclimatic factor 3: 10.1%) are the primary driving forces shaping its distribution. The core suitable habitats are predominantly concentrated in the provinces of Yunnan, Guizhou, and Sichuan. By 2070, the distribution center shifts northeastward to Qujing City. Under the SSP5-8.5 scenario, the invasion front extends into southern Tibet, while retreat occurs in the lowlands of Honghe Prefecture. This study underscores the synergistic effects of socioeconomic development pathways and bioclimatic thresholds on invasive species’ biogeographical patterns, providing a robust predictive framework for adaptive management strategies. Full article

Tamarix boveana Bunge demonstrates strong drought and salinity tolerance, exhibiting significant economic potential and ecological functions. With global warming profoundly altering plant distribution patterns, this study aims to identify key factors influencing its distribution and predict shifts in habitat suitability under future climate scenarios. This study employed the maximum entropy (MaxEnt) model with 186 presences and 36 environmental variables. Results reveal that the current suitable habitat of Tamarix boveana is primarily concentrated along the southern Mediterranean coast and partial western coastal areas, with highly suitable zones comprising 14% of the total suitable range. Dominant environmental factors governing its distribution include isothermality (bio3), annual mean temperature (bio1), soil pH (t_pH_h₂o), and precipitation of the warmest quarter (bio18). Projections under varying carbon emission scenarios indicate a contraction in suitable habitat area, accompanied by pronounced poleward range shifts and habitat fragmentation, particularly under high-emission pathways. This study provides a scientific foundation for the conservation and management of Tamarix boveana, while contributing to climate change impact assessments and biodiversity preservation. Full article

Under global climate change, sustainable management of plant resources in alpine canyon regions faces severe challenges. M. esculenta, highly valued for its edible and medicinal properties, is widely harvested for consumption by residents in the upper Dadu River–Minjiang River region. This study employs ensemble models to simulate the potential distribution of M. esculenta in this region, predicting the impacts of future climate change on its distribution, centroid migration of suitable habitats, and niche dynamics. Additionally, a production dynamics model integrating ecological suitability and nutritional components was developed to delineate current and future potential cultivation zones for M. esculenta. The results indicate that current high-suitability areas and core cultivation zones of M. esculenta are predominantly distributed in a patchy and fragmented pattern. The high-suitability habitats in the upper Dadu River–Minjiang River region have three distribution centers: the largest spans southern Danba County, southern Jinchuan County, and northeastern Kangding City, while the other two are located in northeastern Li County, southwestern Aba County, and northwestern Ma’erkang City, with sporadic distributions in Heishui County, Maoxian County, and Wenchuan County. First-level cultivation areas are primarily concentrated in Kangding City, Danba County, Ma’erkang City, Li County, and surrounding regions. Under climate change, low-suitability areas and third-level cultivation zones for M. esculenta in the region have increased significantly, while high- and medium-suitability areas, along with first- and second-level cultivation zones, have decreased notably. Concurrently, suitable habitats and cultivation zones exhibit a migration trend toward higher northern latitudes. The most pronounced changes in suitable areas and cultivation zones, as well as the largest niche migration, occur under the high-emission climate scenario. This study facilitates the formulation of suitability-based management strategies for M. esculenta in the upper Dadu River–Minjiang River region and provides a scientific reference for the sustainable utilization of mountain plant resources under climate change. Full article

Global warming has caused the change of the geographical distribution of many species and threatened the living of species on earth. It is important to describe and predict the response of these species to current and future climate changes to conserve and utilize the endemic forest species. Acer pubinerve of the Sapindaceae is an important forest tree species endemic to China, our recent fieldwork recorded A. pubinerve in the Jiangsu province for the first time, representing the northernmost known occurrence of the species. In this study, we compiled an occurrence dataset of A. pubinerve based on field investigation, herbarium specimen data and literature, and mapped the resource distribution of this endemic forest species in China. Then, we used the optimized MaxEnt model to predict the potential suitable areas of the species under current climate conditions and future climate change scenarios and studied the impacts of environmental variables on the suitable areas of the species. The MaxEnt model, optimized with a regularization multiplier of 0.5 and a feature combination of linear and quadratic terms, exhibited the best predictive performance. The prediction accuracy of the model was extremely high and the AUC values of training and test data were 0.995 and 0.998, respectively. We found that the leading environmental variables affecting the potential distribution of A. pubinerve include the mean temperature of warmest quarter, the mean temperature of driest quarter, and the annual precipitation. Under the current climatic condition, the suitable distribution area of A. pubinerve is 165.68 × 10⁴ km², mainly located in the provinces of Zhejiang, Fujian, Jiangxi, Hunan, Guangdong, and Guangxi. Compared with the suitable area under the current climate, the total suitable areas of A. pubinerve is projected to expand toward the north under the future climate change scenarios SSP126, SSP370, and SSP585, while its center shows a general trend of westward migration. Our study lays the foundation for conservation and resource utilization of this endemic tree species in China. Full article