Search Results (964)

The Qinghai–Tibet Plateau (QTP) is highly sensitive to global climate change, and the stability of its grassland ecosystems is critical for regional ecological security and livestock development. Therefore, investigating future spatial distribution changes of dominant species on the QTP is of great importance for grassland management. In this study, an ensemble model was used to simulate and analyze the potential distribution and centroid migration directions of dominant species in alpine meadow, alpine grassland, desert grassland, and temperate grassland under current and future climate scenarios (SSP2-4.5 and SSP5-8.5). The results show that the ensemble model achieved excellent predictive accuracy for all species (AUC > 0.9, TSS > 0.7, Kappa > 0.6). Elevation is the key factor governing species distribution, while climate drivers differ significantly among species. The distribution of dominant species in alpine meadow and alpine grassland is primarily co-driven by the mean monthly temperature range (MTR), isothermality (ISO), and annual precipitation (AP); desert grassland dominants are mainly influenced by AP and the mean temperature of the driest quarter (MTDQ); and temperate grassland dominants are driven by the precipitation of the coldest quarter (PCQ) and AP. The suitable habitats of dominant species in the future will generally expand towards high-altitude, high-latitude regions in the north and northwest, with centroid migration directions varying markedly among species. Specifically, the centroids of desert grassland dominants and S. bungeana in temperate grassland will migrate northwest under SSP2-4.5 and SSP5-8.5, while N. splendens and S. krylovii in temperate grassland will migrate southwest. For alpine meadow and alpine grassland dominants, the centroids will generally move northwest under SSP2-4.5 but diverge under SSP5-8.5—E. nutans and S. purpurea in alpine grassland will continue to migrate northwest, whereas alpine meadow dominants and P. annua in alpine grassland will migrate east or northeast. This study provides a theoretical basis for grassland conservation, biodiversity conservation, and livestock production in response to climate change on the QTP. Full article

Accurate prediction of the potential habitat distribution of Scomber japonicus, an important target species in China’s distant-water fisheries, is essential for fishing ground forecasting. Using catch data for S. japonicus collected from Chinese large-scale purse-seine and trawl fisheries in the Northwest Pacific Ocean from May to November during 2015–2024, this study applied the maximum entropy model (MaxEnt) and the genetic algorithm for rule-set production (GARP) model to predict the potential habitat distribution of S. japonicus in the Northwest Pacific Ocean. The area under the receiver operating characteristic curve (AUC) and the true skill statistic (TSS) were used to evaluate model performance. The MaxEnt model predicted a relatively concentrated highly suitable habitat, whereas the GARP model identified a broader highly suitable area. To reduce the bias and uncertainty associated with single-model predictions, the outputs of the MaxEnt and GARP models were integrated using a weighted ensemble approach, with the optimal weights for MaxEnt and GARP determined as 0.7:0.3. The ensemble model achieved higher predictive performance, with an AUC of 0.983 and a TSS of 0.840. The highly suitable habitat of S. japonicus was mainly concentrated within 147° E–156° E and 40° N–44° N. Chlorophyll concentration, sea surface temperature (SST), and temperatures at depths of 150 m and 200 m were the main environmental variables affecting the potential habitat distribution of S. japonicus in the MaxEnt model. These findings provide useful information for resource utilization, fishing ground forecasting, and sustainable management of S. japonicus in the high seas of the Northwest Pacific Ocean. Full article

Climate change is increasingly reshaping species habitat suitability worldwide. Primula L., the largest genus in Primulaceae, comprises 404 species in China (including 296 endemic species) and is characterized by high endemism and numerous rare and endangered taxa. However, global warming has intensified habitat fragmentation and loss, while its distribution patterns and key environmental drivers remain insufficiently understood. We compiled 7647 occurrence records of 404 wild Primula species in China and integrated 60 environmental variables (climatic, topographic, and soil factors). Using the MaxEnt model combined with ArcGIS spatial analysis, we assessed current and future habitat suitability, identified dominant environmental drivers, and quantified conservation gaps under multiple climate scenarios. Species richness is highly concentrated in Sichuan (186 species), Yunnan (177 species), and Xizang (165 species), with the Hengduan Mountains and eastern Himalayas representing the core distribution area and showing clear peripheral differentiation. The optimized MaxEnt model performed well (AUC = 0.858), identifying temperature seasonality (bio4, 39.8%) and elevation (27.1%) as the main limiting factors. The total suitable habitat area is 268.52 × 10⁴ km², with high-suitability areas mainly distributed in the Hengduan Mountains, southeastern Qinghai–Xizang Plateau, and the Central Mountain Range of Taiwan. Under three shared socioeconomic pathway (SSP) scenarios (SSP126, SSP245, and SSP585), suitable habitat shows a persistent decline, most pronounced under SSP585 in the 2090s (−20.73%), accompanied by a 25.86% reduction in low-suitability areas. Localized expansion of high-suitability habitats suggests that the Hengduan Mountains and southeastern Qinghai–Xizang Plateau may act as potential climatic refugia. Habitat loss consistently exceeds habitat gain, while the distribution centroid shifts westward and northwestward, with migration distances increasing under higher-emission scenarios. Conservation gap analysis indicates that 90.01% of high-suitability habitats lie outside the current protected area network, revealing a strong mismatch between biodiversity hotspots and conservation coverage. These findings highlight the urgent need to expand protected areas and establish micro-reserves in key gap regions (southwestern Sichuan, northwestern Yunnan, southeastern Xizang, and southern Gansu), and to integrate climate-driven migration corridors into conservation planning to support long-term alpine plant persistence under climate change. Full article

Invasive alien species (IAS) threaten coastal wetland ecosystems, and smooth cordgrass (Spartina alterniflora) is among the most damaging invaders along the coast of China. We compiled occurrence records from the invaded range (China) and native range (United States) and retained 358 and 291 spatially thinned occurrences after quality control and definition of coastal-accessible areas. We assembled climatic, topographic, land use, soil and anthropogenic predictors and fitted species distribution models using the biomod2 ensemble-modeling framework, complemented by an ecospat-based comparison of native and invaded niche spaces. The ensemble model (EM) showed high predictive accuracy (China: AUC = 0.98, TSS = 0.99; USA: AUC = 0.99, TSS = 0.94). Elevation (73.6%) and human influence (6.0%) were the strongest predictors, highlighting the role of intertidal geomorphology and human-mediated propagule pressure. Niche overlap between ranges was low (Schoener’s D = 0.13), and the invaded niche showed substantial unfilling (0.36), indicating additional environmental space at risk of colonization in China. The current suitable habitat forms a continuous coastal belt from the Bohai Rim through the Yellow Sea–East China Sea to the South China Sea. Projections under future climate change suggest predominantly stable suitable areas with localized expansions but potential contractions in some periods. Our results may support the early warning, surveillance prioritization, and adaptive management of S. alterniflora under climate change. Full article

Under global climate change, ungulate distributions are generally shifting poleward. However, the dispersal pathways, dynamics of suitable habitat, and environmental drivers of the expanding Milu population in the intensively used coastal wetlands of Jiangsu Province remain poorly understood. To support conservation and management, this study used field occurrence data and environmental variables to predict potentially suitable habitat for Milu under current and future climate scenarios. The Biomod2 ensemble modeling framework was applied to assess spatial changes in habitat suitability, and Geographical Detector was used to identify key environmental drivers. Current potentially suitable habitat showed a belt-like pattern along the coast, with the high suitability area covering 0.035 × 10⁴ km². Under future climate scenarios, potentially suitable habitat for Milu is projected to expand in the central and northern coastal areas of Jiangsu, with a substantial increase in the predicted total suitable habitat area. Dis_coastline, BIO14, BIO4, and Pop_density were identified as key factors influencing the distribution of potential suitable habitat for Milu, among which BIO4 and BIO14 were the principal climatic drivers affecting the northward shift in future suitable areas. These results suggest that Milu habitat suitability is jointly shaped by coastline proximity, temperature and water-availability conditions, and population density. Conservation should prioritize the protection of highly suitable habitats, improve patch connectivity, reduce human disturbance, and strengthen wetland protection and vegetation restoration. Full article

The White-naped Crane (Antigone vipio), a first-class national protected bird species in China, exhibits a declining global population. To investigate the spatiotemporal patterns and drivers of wintering habitat suitability, data from 71 valid distribution sites were collected from 2015 to 2025 during the wintering period. Using the MaxEnt model, current and future (2050 and 2070) potential suitable habitat distributions were simulated under three climate scenarios: SSP126 (low emissions), SSP245 (medium emissions), and SSP585 (high emissions). The modeling yielded an average AUC value of 0.984, indicating high predictive accuracy. Key environmental variables influencing the wintering distribution of the White-naped Cranes include elevation, distance to major water, precipitation of the driest month, slope, temperature seasonality, and mean temperature of the wettest quarter. The current high-suitable area for the White-naped Cranes spans 5.64 × 10⁴ km² and is primarily distributed in the middle and lower reaches of the Yangtze River and in coastal wetlands along the North China. Among these, Hunan, Hubei, Jiangxi, and Anhui provinces contain relatively concentrated high-suitable areas for the species. Primarily influenced by elevation, distance to major water, precipitation of the driest month, and land-use classification, the suitable wintering habitat of the White-naped Cranes is projected to undergo significant contraction, shifting predominantly to the middle reaches of the Yangtze River. The most severe contraction is projected under the SSP585 scenario by 2070, with a reduction of 4.11 × 10⁵ km². Contraction areas are primarily concentrated along the Bohai and Yellow Sea coasts and in the middle and lower reaches of the Yangtze River, while minimal expansion occurs in Hubei, Anhui, and Zhejiang. The overall southwestward shift in the species’ distribution centroid may be associated with changes in elevation and distance to major water. Finally, habitat conservation strategies for the White-naped Cranes are proposed, providing a scientific basis for population protection and habitat management under future climate change. Full article

In national park sections adjacent to large cities, protected wildlife habitats often intersect with roads, tourism, agriculture, forestry, and other community-use spaces. This overlap complicates the joint prioritization of multi-species conservation and potential human-wildlife conflict governance. Using species trace-point data from the Fourth National Giant Panda Survey, we developed 30 m MaxEnt distribution models for 12 mammal species in the Chengdu section of the Giant Panda National Park and integrated protected-species’ conservation priority with potential wild-boar-related conflict pressure. Test AUC values ranged from 0.702 to 0.897, and elevation was the dominant predictor for 11 species. The Top 15% weighted conservation priority area, based on protection status and rarity, covered 350.1 km². Potential wild boar conflict pressure was defined as wild boar suitability multiplied by human exposure, and the Top 15% risk area covered 348.3 km². Overlaying the two layers identified 61.6 km² of high-conservation-high-conflict areas. Functional-zone statistics showed that the core conservation zone concentrated higher multi-species conservation value, whereas the general control zone carried stronger potential wild boar conflict pressure. This framework provides a spatial basis for coordinating protected mammal monitoring, crop-damage warning, and community co-management. Full article

This study aims to predict the global distribution and future potential distribution trends of Phytopythium litorale to support its prevention and control. The current suitable habitat area is estimated at 3702.85 × 10⁴ km², mainly in North America, Europe, Asia, and Oceania. Using 150 global occurrence records and 36 environmental variables, we applied the MaxEnt model (FC = LQHPT, RM = 4) to identify dominant environmental factors and project suitable habitats and centroid shifts under three future climate scenarios. The model performed well (AUC > 0.95). The main influencing factors were Mean Temperature of the Coldest Quarter, Isothermality, and Precipitation of the Coldest Quarter. Under future scenarios, the total suitable area is projected to increase, while some currently suitable regions will shrink and shift toward higher latitudes. The habitat centroid is predicted to migrate northeastward from Tamanrasset Province, Algeria, with a maximum displacement of 960 km (SSP3-7.0, 2081–2100). By predicting these distributional shifts, this study enhances our understanding of P. litorale biogeography and provides a scientific basis for managing this pathogen under climate change. Full article

The Iranian Ground Jay (Podoces pleskei) is the endemic bird species inhabiting the deserts and steppes of Iran, a region experiencing severe ecological disturbances like habitat loss and fragmentation of preferred habitat. Despite its remarkable adaptation to arid environments, Iranian Ground Jay exhibits strong habitat specialization, making it both ecologically resilient and vulnerable—an intriguing case for evaluating how the species responds to climate-driven habitat shifts. The present study aims to assess the current and future distribution of Iranian Ground Jay under climatic change using MaxEnt incorporating presence records and bioclimatic variables. We modeled the species’ potential distribution under two climate models (HadGEM3-GC31-LL and MIROC6) for 2070. Then, using the predicted habitats, we estimated the coverage of protected areas in Iran. Among climatic variables, we predicted that the annual precipitation (bio12), precipitation of driest quarter (bio17), and temperature seasonality (bio4) significantly influenced the distribution of Iranian Ground Jays. The highly suitable distributions of the species are concentrated in Eastern, Southeastern, and Central Iran. Our results indicated that a vast range of potential distribution is located outside protected areas, emphasizing the importance of conservation efforts. Our investigation shed lighted the consequences of global warming, where the highly suitable habitat is expected to shift under predicted climatic changes, resulting in a reduction in suitable habitat extent projected for the future. Based on these insights, it becomes imperative to reassess current conservation policy and devise an action plan specifically tailored for the Iranian Ground Jay, particularly emphasizing the protection of its core habitats within anthropogenically altered landscapes and non-protected regions. Full article

Castanea seguinii Dode is ecologically and economically significant in China, and its potential as a carbon sink and ability to adapt to varying climates have garnered considerable interest. In light of global warming, the geographical distribution of Castanea seguinii is experiencing notable changes. This study employs the Maximum Entropy (MaxEnt) model to forecast both present and future potential habitats conducive to the survival of Castanea seguinii across four emission scenarios (SSP126, SSP245, SSP370, and SSP585) and utilizes Fragstats 4.2 to analyze fragmentation in its most suitable regions. Findings reveal that current habitats that support adaptation are chiefly located in southern China, covering around 12.7% of the total land area of the country. Key factors affecting this distribution are precipitation levels during the driest month, average temperatures recorded in the driest quarter, precipitation rates in the wettest quarter, isothermality, and elevation, with climate-related variables exerting the greatest influence. As carbon emissions vary, a general trend of habitat contraction is observed for Castanea seguinii, especially in regions that are highly adaptive. The populations of Castanea seguinii are shifting northwestward into areas at higher latitudes and altitudes. This upward movement reflects pronounced nonlinear traits as the intensity of carbon emissions changes. An increase in carbon emissions leads to greater fragmentation in regions that are most adaptable, with the lowest and low fragmentation levels falling to a minimum by 2090 under the SSP585 scenario. The reduction in highly adaptive habitats will contribute to increasing fragmentation. These results offer vital scientific insights for the conservation and management of Castanea seguinii forest resources amid climate change and the pursuit of carbon neutrality. Full article

Soils are critical microbial habitats that support terrestrial ecosystem functioning and harbor numerous uncultured and functionally uncharacterized microbial groups. The black soil region in northeast China is a key agricultural ecosystem globally, yet the classification and functional understanding of its crucial microbial groups remain underexplored. In this study, we identified three high-completeness metagenome-assembled genomes (MAGs) from the Global Mollisols Genomic Atlas (GMGA). Phylogenetic and comparative genomic analyses identified these genomes as representing a novel evolutionary branch within the genus Flavobacterium, classified under the phylum Bacteroidota. Their novel taxonomic position is further supported by average nucleotide identity (ANI) and average amino acid identity (AAI) thresholds, demonstrating significant divergence from all known reference genomes. Functional annotation indicated that this species possesses strong plant polysaccharide degradation potential and a chemoheterotrophic lifestyle, together with environmental stress tolerance and a specialized nitrogen metabolic network adapted to agricultural inputs, thereby conferring a metabolic advantage in black soil environments characterized by high organic matter input and marked seasonal fluctuations. In addition, global distribution analysis showed that this lineage is widely distributed across diverse ecosystems and is significantly enriched in soil habitats, particularly in environments with fluctuating carbon sources and high organic matter inputs. The new species is most abundant in temperate soils, with the northeast black soil region of China emerging as a key hotspot. Based on these findings, and because no pure culture is currently available, we propose Candidatus Flavobacterium genomatis based on genome-resolved metagenomic evidence and in alignment with the International Code of Nomenclature of Prokaryotes rules for uncultivated prokaryotes. Our results expand the known species diversity of the genus Flavobacterium and suggest potential ecological roles of uncultured black-soil microbes in carbon and nitrogen cycling, including possible involvement in N₂O reduction under suitable environmental conditions. Full article

Phytolacca americana L. is an invasive perennial plant that has become increasingly widespread in China, but its current climatic suitability and future redistribution under climate change remain insufficiently quantified. This study aimed to identify the major environmental drivers of P. americana distribution and to project its potential habitat suitability under future climate scenarios. We compiled a national occurrence dataset and retained 683 quality-controlled presence records after taxonomic verification, coordinate checking, and 5 km spatial thinning. A BIOMOD2 ensemble modelling framework was used to integrate nine algorithms, and future projections were generated using CMIP6 climate data under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 across four time periods from 2021 to 2100. The ensemble model showed strong predictive performance, with TSS = 0.804 and ROC = 0.967. May shortwave radiation, January mean temperature, and annual temperature range were identified as the dominant predictors of habitat suitability. Under current climate conditions, highly suitable habitats were mainly concentrated in warm and humid regions of eastern and southern China. Future projections indicated that suitable habitats may expand toward northern, northwestern, and higher-elevation regions, whereas highly suitable habitats may become redistributed or fragmented under stronger climate forcing. Centroid analyses further suggested non-linear, scenario-dependent shifts rather than a simple poleward expansion. These findings provide a spatial basis for early warning, targeted monitoring, and pathway-focused management of P. americana in China. Full article

(1) Background: The rapid spatial expansion of the ruderal weed Chenopodium hybridum L. poses a potential challenge to agricultural production and regional ecosystems in China. However, the spatial evolution characteristics of its potential geographic distribution remain unclear under the compound scenarios of global warming and intensified human activities. (2) Methods: Utilizing an optimized MaxEnt model (regularization multiplier (RM) = 0.5, feature combination (FC) = LQ), this study integrated bioclimatic, topographic, soil, and Human Footprint (Hfp) data to predict the potential suitable habitats of C. hybridum in China under current conditions and four future Shared Socioeconomic Pathways (SSPs) emission scenarios (SSP126, SSP245, SSP370, and SSP585) for the 2050s and 2070s. Additionally, spatial turnover rate and centroid migration analyses were incorporated to elucidate its spatiotemporal dynamics. (3) Results: The results indicate that the optimized model exhibited robust predictive performance (Area Under the Curve (AUC) = 0.928). The Human Footprint (Hfp) was the environmental factor most prominently associated with the macro-spatial distribution of C. hybridum, with a relative contribution of 58.4%—significantly higher than any single natural geographic factor. Currently, potential suitable habitats are primarily concentrated in North, Central, and Southwest China, totaling approximately 205.59 × 10⁴ km². Under future climate scenarios, the highly suitable core habitats exhibit a consistent contraction trend, whereas the marginal suitable habitats shift spatially toward the arid inland regions of the northwest and the high-altitude areas of the southwest. By the 2070s under the higher-emission scenario (SSP585), the spatial turnover rate reaches a peak value (16.23%), and the distributional centroids of the potential suitable habitats exhibit localized directional shifts. (4) Conclusions: The spatial expansion trajectory of C. hybridum exhibits a high degree of spatial congruence with human activity corridors, reflecting a distinct macro-ecological niche spatial response characterized by shifts toward higher latitudes and elevations. It must be emphasized that the projections of this study reflect potential habitat suitability rather than definitive future actual distributions. The three-tier spatial management framework proposed herein—encompassing transport regulation, ecological management in core areas, and early warning in marginal zones—can serve as a scientific basis for the early monitoring and spatial management of this species under climate change. Full article

Given the ongoing global decline in biodiversity, species reintroduction has become an important strategy for the conservation of endangered wildlife. Père David’s deer (Elaphurus davidianus), a historically extinct-in-the-wild species successfully reintroduced in China, represents a useful model for evaluating ecological responses following reintroduction into different habitats. Increasing evidence suggests that fecal microbiota can serve as a non-invasive indicator of host-associated microbial communities and their variation under different conditions. In this study, we investigated the fecal microbiota of a reintroduced population in the Daqingshan National Nature Reserve (Inner Mongolia). A total of 90 fresh fecal samples were collected between December 2021 and October 2023 across different seasonal periods. High-throughput 16S rRNA gene sequencing was used to characterize microbial community structure, and comparative analyses were conducted alongside published datasets from populations in Beijing and Shishou. The results revealed significant seasonal variation in microbial community composition and diversity, with distinct clustering of rainy, dry, and transitional (October) samples. Several taxa exhibited differential enrichment between seasons, suggesting temporal shifts in microbial community structure. A comparative analysis with other populations (Beijing and Shishou) revealed differences in microbial composition at broad taxonomic levels, suggesting potential variations related to regional environmental conditions, diet, and management practices. Overall, the observed patterns are consistent with seasonal variation in plant resource availability and highlight the potential influence of geographic context on microbial community structure. This study provides baseline data on the fecal microbiota of Père David’s deer in a semi-arid steppe environment and the potential indication of host suitability from the perspective of the microbiome. Full article

Taxus baccata is a rare conifer species that occurs as isolated individuals or in small patches in Morocco and is listed in the National List of Protected Flora. To predict its current and future distribution areas, based on 41 occurrence records and 11 bioclimatic variables, the Maxent model was applied using cross-validation (1000 replicates) with logistic outputs under current climate conditions and the SSP1-2.6, SSP2-4.5, and SSP5-8.5 future climate scenarios. Our results indicate high-performing models (AUC > 0.966, TSS > 0.862). The bioclimatic factors that most influence the current potential geographic distribution of yew are the Mean Temperature of Driest Quarter (Bio9) and Isothermality (Bio3). The spatial distribution indicates that the current potential range of yew is discontinuous, with a current suitable area not exceeding 4602 km². Predictive modeling identifies a decline of the predicted suitable habitat under the SSP1-2.6 and SSP2-4.5 scenarios, fueled by both climate change and human activities. Given the species’ limited dispersal and the ongoing fragmentation of its habitat, immediate conservation actions, both in situ and ex situ, are urgently needed. This study demonstrates the vital role of predictive modeling in identifying these vulnerabilities to guide long-term sustainability efforts. Full article