Search Results (697)

The Mayanghe National Nature Reserve, a key habitat for the endangered François’ langur (Trachypithecus francoisi), faces significant anthropogenic disturbances, including extensive distribution of croplands, roads, and settlements. These human-modified features are predominantly concentrated at elevations between 500 and 800 m and on slopes of 10–20°, which notably overlap with the core elevation range utilized by François’ langur. Spatial analysis revealed that langurs primarily occupy areas within the 500–800 m elevation band, which comprises only 33% of the reserve but hosts a high density of human infrastructure—including approximately 4468 residential buildings and the majority of cropland and road networks. Despite slopes >60° representing just 18.52% of the area, langur habitat utilization peaked in these steep regions (exceeding 85.71%), indicating a strong preference for rugged karst terrain, likely due to reduced human interference. Habitat type analysis showed a clear preference for evergreen broadleaf forests (covering 37.19% of utilized areas), followed by shrublands. Landscape pattern metrics revealed high habitat fragmentation, with 457 discrete habitat patches and broadleaf forests displaying the highest edge density and total edge length. Connectivity analyses indicated that distribution areas exhibit a more continuous and aggregated habitat configuration than control areas. These results underscore François’ langur’s reliance on steep, forested karst habitats and highlight the urgent need to mitigate human-induced fragmentation in key elevation and slope zones to ensure the species’ long-term survival. Full article

The unique characteristics of desert vegetation, such as different leaf morphology, discrete canopy structures, sparse and uneven distribution, etc., pose significant challenges for remote sensing-based estimation of fractional vegetation cover (FVC). The Unmanned Aerial Vehicle (UAV) system can accurately distinguish vegetation patches, extract weak vegetation signals, and navigate through complex terrain, making it suitable for applications in small-scale FVC extraction. In this study, we selected the floodplain fan with Caragana korshinskii Kom as the constructive species in Hatengtaohai National Nature Reserve, Bayannur, Inner Mongolia, China, as our study area. We investigated the remote sensing extraction method of desert sparse vegetation cover by placing samples across three gradients: the top, middle, and edge of the fan. We then acquired UAV multispectral images; evaluated the applicability of various vegetation indices (VIs) using methods such as supervised classification, linear regression models, and machine learning; and explored the feasibility and stability of multiple machine learning models in this region. Our results indicate the following: (1) We discovered that the multispectral vegetation index is superior to the visible vegetation index and more suitable for FVC extraction in vegetation-sparse desert regions. (2) By comparing five machine learning regression models, it was found that the XGBoost and KNN models exhibited relatively lower estimation performance in the study area. The spatial distribution of plots appeared to influence the stability of the SVM model when estimating fractional vegetation cover (FVC). In contrast, the RF and LASSO models demonstrated robust stability across both training and testing datasets. Notably, the RF model achieved the best inversion performance (R² = 0.876, RMSE = 0.020, MAE = 0.016), indicating that RF is one of the most suitable models for retrieving FVC in naturally sparse desert vegetation. This study provides a valuable contribution to the limited existing research on remote sensing-based estimation of FVC and characterization of spatial heterogeneity in small-scale desert sparse vegetation ecosystems dominated by a single species. 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

Parrotia subaequalis is a rare and endangered deciduous tree native to China, valued for its vibrant autumn foliage and ornamental appeal. Its leaves exhibit striking coloration, ranging from red to yellow and purple, yet the physiological and molecular mechanisms behind this variation remain poorly understood. Here, we combined transcriptomic, metabolomic, and physiological analyses to investigate pigment changes within the yellow leaf phenotype of P. subaequalis. Our findings revealed significant differences in gene expression and metabolic profiles between yellow and green leaves, particularly in starch and sucrose metabolism, photosynthesis, and carbon metabolism. Yellow leaves exhibited reduced photosynthetic capacity and carotenoid levels, alongside increased D-glucose concentration. These findings suggest that visible color transitions are likely driven by coordinated changes in carbohydrate metabolism, photosynthetic function, and organic compound accumulation. This study provides novel insights into the molecular and physiological mechanisms governing leaf pigmentation in an endangered tree, with useful information relevant to their conservation and sustainable utilization. Full article

Understanding the activity patterns of a species is essential for developing sound conservation and management plans. In this study, we used a camera-trapping technique to determine the activity patterns of bharal (Pseudois nayaur) in a marginal population in Wolong National Nature Reserve, Sichuan, China. Our results showed that these animals preferred to be active in the daytime from 08:00 to 20:00, with an activity peak between 10:00 and 14:00. In addition, we found that the species had a seasonal activity pattern with higher activity frequency in summer than in winter and that bharal were most active in a temperature range of 3–11 °C and at night with a waxing crescent moon, implying that the activity rhythm of the species is an adaptation to a subtropical high-altitude alpine area with vertical zonation in temperature. The pattern of movement and activity was also correlated with the moon phase. Full article

Highway accessibility plays a vital role in supporting local economic development, particularly in regions lacking access to sea or river ports. Recognizing the functional transformation of road infrastructure, the Chinese government has made substantial investments in its expansion. Nevertheless, a theoretical gap remains in justifying whether such investments yield significant economic returns. Drawing on the theory of economic externalities, this study investigates the causal relationship between highway development and regional economic growth, and assesses whether highway construction leads to an acceleration in growth rates. Utilizing panel data from 14 Chinese cities spanning 2000 to 2014, the synthetic control method (SCM) is employed to evaluate the economic externalities of highway investment. The results indicate a positive impact on surrounding industries. Furthermore, a growth rate forecasting analysis based on Back-Propagation Neural Networks (BPNNs) is conducted using industrial enterprise data from 2005 to 2014. The growth rate in the treated city is 1.144%, which is close to the real number 1.117%, higher than the number for the weighted control group, which is 1.000%. The findings suggest that the growth rate of total industrial output improved significantly, confirming the existence of positive spillover effects. This not only enriches the empirical literature on transport infrastructure but also provides targeted enlightenment for the sustainable development of urban economy in terms of policy guidance. Full article

Economically, all countries seek sustained growth driven by domestic demand, investment, and exports; however, COVID-19 revealed the vulnerability of interconnected economic systems and a sharp contraction in global trade. The objective of this research is to analyze through an econometric model the effect of traditional exports on Peru’s economic growth during the 2012–2023 period. The study employed a quantitative approach with a non-experimental, longitudinal design, using quarterly data from the Central Reserve Bank of Peru and the National Bureau of Statistics of China, which were transformed into natural logarithms. Unit root tests, the ordinary least squares (OLS) method and a two-stage least squares (2SLS) model were applied to correct for endogeneity. The results show that mining accounts for 81.7% of total traditional exports from Peru. The model indicated that a 1% increase in traditional exports leads to a 0.29% increase in GDP, confirming a positive impact. However, the high dependence of the mining sector exposes the economy to external risks. Therefore, a productive diversification strategy, alongside the modernization of the mining sector, is recommended to strengthen Peru’s economic resilience in the face of global crises and external fluctuations. Full article

AM fungi play a pivotal role in regulating ecosystem functioning and processes. However, the assembly of soil AM fungal communities and its drivers across Populus euphratica forests in extremely arid regions remain largely unclear. Here, we explored the composition and assembly processes of AM fungal communities in the soil of P. euphratica forests in northwest China. The results showed that soil salinity affected the composition, assembly processes, and network stability and complexity of AM fungal communities. Stochastic processes rather than deterministic processes dominated the community assembly of AM fungi. Habitat generalists were more susceptible to deterministic processes than specialists. In addition, the network analysis showed that fungal network complexity had a hump-shaped relationship with increasing soil salinity, while network stability had a U-shaped relationship. This research suggests that soil salinity plays an essential role in determining AM fungal community composition and assembly processes in P. euphratica forests of arid regions. Full article

Strategic petroleum reserves are critical for energy security. In Japan, 0.5 million kiloliters of crude oil (12% of the state-owned reserves) is stored using underground rock-cavern tanks, which comprise unlined horizontal tunnels bored into bedrock. Crude oil is held within the tank by water inside the tank, the pressure of which is kept higher than that of the crude oil by natural groundwater and irrigation water. This study applied microbial DNA-based monitoring to assess the water environments in and around national petroleum-stockpiling bases (the Kuji, Kikuma, and Kushikino bases) using the rock-cavern tanks. Forty-five water samples were collected from the rock-cavern tanks, water-supply tunnels, and observation wells. Principal-component analysis and hierarchical clustering indicated that microbial profiles of the water samples reflect the local environments of their origins. Particularly, the microbial profiles of water inside the rock-cavern tanks were distinct from other samples, revealing biological conditions and hence environmental characteristics within the tanks. Moreover, the clustering analysis indicated distinct features of water samples that have not been detected by other monitoring methods. Thus, microbial DNA-based monitoring provides valuable information on the in situ environments of rock-cavern tanks and can serve as an extremely sensitive measurement to monitor the underground oil storage. Full article

(1) Background: Phoridae is a relatively large and understudied family of Diptera. Species within this family occupy diverse ecological niches across a wide range of habitats. (2) Methods: The dataset is based on Phoridae specimens collected in the Republic of Mordovia (European Russia). Sampling was conducted from 2019 to 2024 using six collection methods: hand-held sweep nets, pitfall traps, beer traps, pan traps, Malaise traps, and window traps. (3) Results: The dataset includes 4713 occurrence records from the Republic of Mordovia, comprising a total of 15,701 Phoridae specimens. It provides data on 271 species. The highest species richness was recorded in the Mordovia State Nature Reserve (226 species, 83.4%). Fewer species were documented in the fauna of the National Park “Smolny” (177 species, 65.3%), with comparable diversity observed in other parts of the region. Ten species were dominant in the dataset (Megaselia pusilla, Triphleba opaca, Megaselia angusta agg., Diplonevra funebris, Megaselia brevicostalis, Megaselia plurispinulosa, Megaselia minuta, Megaselia lutea, Megaselia lactipennis, and Megaselia flavicans). A total of 139 species were represented by fewer than ten specimens each. Seasonal dynamics varied across habitats: in the Mordovia State Nature Reserve, both species richness and specimen abundance were already high in April, peaking in June. In contrast, in the National Park “Smolny”, peak values were observed in August. (4) Conclusions: We have listed 151 new recorded species from Russia in this list. Currently, the Phoridae fauna of the Republic of Mordovia is among the best-studied in Russia. The distribution of many species has become clearer, with the Mordovia State Nature Reserve demonstrating the highest biodiversity compared to other areas of the region. Full article

Cobboldia elephantis (Oestridae: Gasterophilinae) is an obligate parasite of the alimentary tract of the Asian elephant, causing gastric myiasis. Current knowledge of its first instar larval morphology has been limited to observations under light microscopy, significantly constraining our understanding of morphological evolution within the genus Cobboldia and the broader subfamily Gasterophilinae. In this study, we provided ultrastructural and three-dimensional characterizations of C. elephantis using scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) based on newly hatched first instar larvae. Features of the first instar larva of C. elephantis, which are either unique or shared with C. loxodontis Brauer, 1896, include (i) three pairs of mouthhooks, (ii) posterior spiracles bearing peristigmatic tufts, (iii) anal division with two spine-clusters and a row of elongated spines, and (iv) a planed, button-like sensilla and a sensillum placodeum. We also compared the first instar larval morphology of C. elephantis with that of Cobboldia loxodontis, Gyrostigma rhinocerontis (Owen, 1830), Gasterophilus pecorum (Fabricius, 1794), Portschinskia magnifica Pleske, 1926, and Oestrus ovis Linnaeus, 1758. Species of Gasterophilinae share several unique features of the first instar larva, including (i) an anal division composed of three subdivisions, (ii) spiracular slits on the posterior spiracles, and (iii) conserved positioning of thoracic sensilla. These findings fill a key gap in our knowledge of C. elephantis larval morphology and suggest that these distinctive structures play a role in adaptation to its parasitic lifestyle. Full article

Aquatic fungi serve as core ecological engines in freshwater ecosystems, driving organic matter decomposition and energy flow to sustain environmental balance. Wetlands, with their distinct hydrological dynamics and nutrient-rich matrices, serve as critical habitats for these microorganisms. As an internationally designated Ramsar Site, Yunnan Dashanbao Black-Necked Crane National Nature Reserve in China not only sustains endangered black-necked cranes but also harbors a cryptic reservoir of aquatic fungi within its peat marshes and alpine lakes. This study employed high-throughput sequencing to characterize fungal diversity and community structure across 12 understudied wetland sites in the reserve, while analyzing key environmental parameters (dissolved oxygen, pH, total nitrogen, and total phosphorus). A total of 5829 fungal operational taxonomic units (OTUs) spanning 649 genera and 15 phyla were identified, with Tausonia (4.17%) and Cladosporium (1.89%) as dominant genera. Environmental correlations revealed 19 genera significantly linked to abiotic factors. FUNGuild functional profiling highlighted saprotrophs (organic decomposers) and pathogens as predominant trophic guilds. Saprotrophs exhibited strong associations with pH, total nitrogen, and phosphorus, whereas pathogens correlated primarily with pH. These findings unveil the hidden diversity and ecological roles of aquatic fungi in alpine wetlands, emphasizing their sensitivity to environmental gradients. By establishing baseline data on fungal community dynamics, this work advances the understanding of wetland microbial ecology and informs conservation strategies for Ramsar sites. Full article

Castor fiber birulai is a subspecies of the Eurasian beaver that has a relatively small population size compared to other Castor subspecies. There is limited genetic research on this subspecies. In this study, mitochondrial cytochrome b (Cytb) and D-loop sequences were analysed in genetic samples obtained from 19 individuals residing in the Buergen River Basin, Xinjiang, China. The Cytb region presented a single haplotype, whereas three haplotypes were identified in the D-loop region. The genetic diversity within the Chinese population was low (D-loop Hd = 0.444; Pi = 0.0043), markedly lower than that observed in other geographical populations of C. fiber. Phylogenetic reconstructions and haplotype network analyses revealed substantial genetic differentiation between C. f. birulai and other Eurasian lineages (Fst > 0.95), supporting the status of C. f. birulai as a distinct evolutionary lineage. Although the genetic distance between the Chinese and Mongolian populations was relatively small (distance = 0.00269), significant genetic differentiation was detected (Fst = 0.67055), indicating that anthropogenic disturbances—such as hydraulic infrastructure and fencing along the cross-border Bulgan River—may have impeded gene flow and dispersal. Demographic analyses provided no evidence of recent population expansion (Fu’s Fs = 0.19152), suggesting a demographically stable population. In subsequent studies, we recommend increasing nuclear gene data to verify whether the C. f. birulai population meets the criteria for Evolutionarily Significant Unit classification, and strengthening cross-border protection and cooperation between China and Mongolia. Full article

Stand structural configuration dictates ecosystem functional performance. Mangrove ecosystems, located in ecologically sensitive coastal ecotones, require efficient acquisition of stand structure parameters and health assessments based on these parameters for practical applications. Effective assessment of mangrove ecosystem health, crucial for their functional performance in ecologically sensitive coastal ecotones, relies on efficient acquisition of stand structure parameters. This study developed a UAV (Unmanned Aerial Vehicle)-based framework for mangrove health evaluation integrating stand structure parameters, utilizing UAV visible-light imagery, field plot surveys, and computer vision techniques, and applied it to the assessment of a national nature reserve. We obtained the following results: (1) A deep neural network, combining UAV visible-light data with tree height constraints, achieved 88.29% overall accuracy in simultaneously identifying six dominant mangrove species; (2) Stand structure parameters were derived based on individual tree extraction results in seedling zones along forest edges (with canopy individual tree segmentation accuracy ≥ 78.57%), and a stand health evaluation model was constructed; (3) Health assessment revealed that the core zone exhibited significantly superior stand health compared to non-core zones. This method demonstrates high efficiency, significantly reducing the time and effort for monitoring, and offers robust support for future mangrove forest health assessments and adaptive conservation strategies. Full article

The blue-eared pheasant (Crossoptilon auritum), a Near Threatened (NT) species endemic to China, is primarily distributed across the northeastern region of the Qinghai–Tibetan Plateau. To bridge the fine-scale spatiotemporal gap in blue-eared pheasant behavioral ecology, this study combines satellite telemetry, movement modeling, and field-based habitat assessments (vegetation, topography, human disturbance). This multidisciplinary approach reveals detailed patterns of their behavior throughout the breeding season. Using satellite-tracking data from six individuals (five males tracked at 4 h intervals; one female tracked hourly) in Wanglang National Nature Reserve (WLNNR), Sichuan Province during breeding seasons 2018–2019, we quantified their home ranges via Kernel Density Estimation (KDE) and examined the female movement patterns using a Hidden Markov Model (HMM). The results indicated male core (50% KDE: 21.93 ± 16.54 ha) and total (95% KDE: 158.30 ± 109.30 ha) home ranges, with spatial overlap among individuals but no significant temporal variation in home range size. Habitat selection analysis indicated that the blue-eared pheasants favored shrub-dominated areas at higher elevations (steep southeast-facing slopes), regions distant from human disturbance, and with abundant animal trails. We found that their movement patterns differed between sexes: the males exhibited higher daytime activity yet slower movement speeds, while the female remained predominantly near nests, making brief excursions before returning promptly. These results enhance our understanding of the movement ecology of blue-eared pheasants by revealing fine-scale breeding-season behaviors and habitat preferences through satellite-tracking. Such detailed insights provide an essential foundation for developing targeted conservation strategies, particularly regarding effective habitat management and zoning of human activities within the species’ range. Full article