Search Results (2,979)

The administrative boundaries of ecosystems do not necessarily align with natural watershed boundaries, which is a significant reason for the current inefficiency and pronounced conflicts in ecological governance. Using the watershed as the fundamental unit, this study assessed the forest ecosystem services (FES) of the Beihai Wetland watershed in Tengchong (As of 2025). Forest vegetation was classified to the formation level, and the functional value method was employed. The results showed the following order of service values: regulating services > provisioning services > supporting services > cultural services. Biodiversity was identified as the most valuable ecosystem function. The study further revealed that factors such as stand type, stand age, and altitude influence the total FES value within the watershed. Analysis of FES per unit stand (1 ha) indicated that Lithocarpus variolosus Franch. Chun (natural forest) exhibited the highest value. Through in-depth analysis of linear correlations and spatial associations of FES per unit stand, a synergy-trade-off visualization was constructed. This revealed that natural forests in the upper watershed may exert systemic effects on nutrient cycling in the lower watershed. The results obtained at the formation level provide support for the development of watershed-based forest tending plans. Moreover, studying FES using the watershed as a unit represents a practical exploration of the “life community of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts” and offers a potential reference for maintaining the ecological security and supporting the ecological protection and restoration of the Beihai watershed. Full article

The unchecked expansion of tea plantations onto steep, forest-adjacent slopes in subtropical mountains engenders a conflict between agricultural productivity and ecosystem integrity, particularly by exacerbating habitat fragmentation and soil erosion. While precise monitoring is essential to navigate this trade-off for sustainable management, accurate inventorying remains a challenge due to the plantations’ strong phenological variability, heterogeneous canopy structures, and high spectral confusion with surrounding vegetation. This study proposes a feature-optimized deep learning framework for mapping and characterizing tea plantations in complex landscapes, using Xinyang City, China, as a study area. The framework integrates multi-temporal Sentinel-1/2 observations with a sequential Jeffries-Matusita (JM)-Pearson feature filtering strategy. This approach effectively condenses a 132-variable high-dimensional pool (including optical spectra, vegetation indices, textures, and SAR polarimetry) into a compact 28-feature subset (a 78.8% reduction), preserving critical phenological and structural cues while minimizing redundancy. These optimized predictors drive a hybrid VGG16–UNet++ segmentation network, which couples transfer-learning-based semantic encoding with detail-preserving dense skip fusion. Extensive experiments across 18 model–feature configurations demonstrate that the optimal setting achieves an Overall Accuracy of 97.82%, an F1-score of 0.9093, and a mean IoU of 0.7968. Notably, the method significantly reduces misclassification in rugged, cloud-prone terrain, yielding a User’s Accuracy of 91.14% for tea. Based on the generated wall-to-wall map, we derived two decision-support indicators: multi-threshold steep-slope exposure and a normalized tea–forest interface density. This framework provides actionable, high-precision spatial products to support slope-based zoning, ecological restoration, and sustainable management in fragile mountain agroforestry systems. Full article

New Guinea, the world’s largest tropical island, supports the planet’s richest insular avifauna. Large areas of New Guinea remain poorly surveyed, however, in part due to the island’s challenging terrain. In hard-to-access areas, like many mountainous parts of New Guinea, automated surveying tools, like camera traps, may be especially helpful to address the survey deficit. Here we present the results of a camera-trap survey of the avifauna of the Cyclops Mountains, a range in New Guinea’s western, Indonesian provinces (Indonesian Papua). To our knowledge, our results represent only the second published survey of birds from Indonesian Papua. We deployed 73 camera traps along an elevation gradient (143–1963 m) of the Cyclops Mountains for 11,869 camera-trap nights, recording 22 bird species from 1696 independent detections. Our species list is, to our knowledge, the first to include observations from the upper northern slopes of the Cyclops Mountains. It documents the first record of Masked Bowerbird (Sericulus aureus) in the range and provides photographic rediscoveries of two ‘lost’ species: Mayr’s Honeyeater (Ptiloprora mayri) and Mayr’s Forest Rail (Rallicula mayri). We also report substantial elevation range extensions for several species, including numerous records of Northern Cassowary (Casuarius unappendiculatus) over 1000 m above its historically known elevation ceiling. These findings provide new insights into species distributions and ecological flexibility in New Guinea’s montane systems, highlighting the potential for previously undocumented biodiversity in under-surveyed regions. Although camera traps detected fewer species than traditional ornithological methods, they were effective in documenting several elusive, ground-dwelling bird species, highlighting their value as a complementary tool for ornithological research in challenging terrain like New Guinea. Finally, we use our data to publish an updated bird species checklist for the Cyclops Mountains. Full article

We analyzed wildfire hazard profiles across the Hyrcanian temperate forests of northern Iran (Guilan Province) by simulating a large set of wildfires with FlamMap MTT. We first derived geospatial data on terrain, fuel models, weather conditions, and historical wildfire occurrence (1992–2022) for the study area. We stratified fire weather conditions and fuel moisture based on the bioclimatic classification of the study area, considering observed extreme fire weather, as well as observed and random fire ignition locations for the simulations. The wildfire simulations were used to estimate burn probability (BP), conditional flame length (CFL), fire size (FS), and crown fire probability (CFP). BP ranged from 0 to 5.0 × 10⁻², with mean values of 1.3 × 10⁻³ and 1.1 × 10⁻³ for observed and random scenarios, respectively. The mean value of CFL from random ignition simulations (0.78 m) was substantially higher than that obtained in the observed ignition simulations (0.54 m), ranging from 0 to 6.75 m. We evidenced significant differences between observed and random ignition simulations for all wildfire hazard metrics. The highest wildfire hazard profiles were observed in the Cold-Mountainous bioclimatic zone under the random ignition simulations. On average, the annual number of anthropic structures threatened by wildfires ranged from 97 (observed scenario) to 123 (random scenario). This research provides detailed and spatially explicit fire hazard and exposure maps to inform fire modeling, land management, and policy actions. Full article

Alpine treeline and shrubline ecotones are climatically sensitive transition zones where vegetation shifts strongly influence belowground microbial processes. Soil bacteria and fungi, as core component of the soil microbiome, play vital roles in nutrient cycling and plant–soil interactions within these fragile ecosystems. However, the structure and diversity of soil microbial communities across the treeline–shrubline transition remain poorly understood. Here, we investigated soil bacterial and fungal communities across treeline and shrubline ecotones in two mountain on the eastern Tibetan Plateau. We further examined how soil physicochemical properties shaped microbial community assembly. Our results demonstrated that the community composition of both bacteria and fungi differed significantly between the treeline and shrubline ecotones, while the Shannon index showed no significant variation. At the phylum level, Proteobacteria, Actinobacteriota, and Acidobacteriota dominated bacterial communities, while Ascomycota and Basidiomycota were the predominant fungal phyla. Both the network complexity of soil bacterial and fungal communities changed significantly across ecotones. Specifically, bacterial network complexity increased significantly toward the shrubline, whereas fungal network complexity declined. Bacterial community compositions were co-regulated by both environmental and vegetation factors, while fungal community compositions were only regulated by soil pH. Redundancy analysis revealed that soil organic carbon, pH, and moisture were the primary drivers of bacterial community (38.17%), whereas vegetation cover, soil organic carbon, and moisture explained the largest proportion of fungal community (44.79%). Our findings reveal the distribution patterns and underlying shift mechanisms of microbial communities between the treeline and shrubline ecotone. These insights are crucial for mountain biodiversity conservation and for improving predictions of forest responses to climate change. Full article

Aiming to clarify the spatial distribution characteristics of soil microbial assemblages and the environmental factors shaping them across a narrow altitudinal transect, this investigation concentrated on the surface soil layer within naturally occurring mixed forests of Picea crassifolia and Betula platyphylla, situated in the elevation band from 2400 to 2800 m along the southern flank of the Qilian Mountains. Leveraging the Illumina NextSeq 2000 high-throughput sequencing platform, integrated with α- and β-diversity analyses and redundancy analysis (RDA), we systematically characterized the composition and diversity traits of soil bacterial and fungal communities, as well as their associations with environmental factors. Notably, the bacterial communities were dominated by Pseudomonadota, Actinomycetota, and Acidobacteria with the abundance of Pseudomonadota decreasing with increasing altitude and that of Acidobacteria increasing with increasing altitude. Furthermore, Ascomycota and Basidiomycota were the dominant phyla in the fungal community. In contrast, bacterial α-diversity—as estimated by the Ace index—showed no significant variation across altitudes. Yet, the fungal alpha diversity metrics—namely Ace and Chao1—were markedly elevated at the 2800 m elevation relative to those observed at both intermediate and lower-altitude locations. Importantly, fungal diversity and community composition showed stronger altitudinal differentiation than bacterial communities in this dataset. Moreover, soil pH, total phosphorus, organic carbon, litter C:N:P stoichiometric ratios, and microbial biomass C:N:P stoichiometric ratios were strongly associated with soil microbial community variation along the altitude gradient, suggesting that they may act as important environmental filters. In conclusion, altitude-driven variations in litter characteristics and soil physicochemical properties jointly shape the assembly processes and spatial distribution patterns of soil microbial communities in this region. Full article

We investigated bryophyte communities in mature beech forests (Fagus sylvatica L.) and Austrian pine plantations (Pinus nigra J.F. Arnold) on Fruška Gora Mountain (northern Serbia) to examine how stand structure and edaphic conditions influence trait composition and functional diversity. Environmental predictors included soil pH, soil temperature, herbaceous cover, and shrub density, while collinear structural variables were summarized using principal component analysis into a composite structural–moisture gradient. Community–environment relationships were analyzed using redundancy analysis (RDA) with restricted permutations, trait–environment coupling using RLQ and fourth-corner analysis, and functional diversity using Rao’s quadratic entropy (RaoQ). The RDA indicated significant effects of all predictors. RLQ revealed a structured multivariate coupling between bryophyte traits and environmental gradients. Functional diversity was higher in beech forests than in pine plantations, increasing with shrub density and decreasing along the structural–moisture gradient. Overall, plantation stands supported functionally more homogeneous bryophyte assemblages, highlighting the importance of stand structural complexity for maintaining forest-floor bryophytes’ functional diversity. Full article

Despite recent advances in polycyclic aromatic hydrocarbon (PAH) research on the Tibetan Plateau (TP), studies investigating the transport potential and accumulation dynamics of these contaminants in the Hengduan Mountains, especially in forest soils which are important sinks for atmospheric PAHs, remain scarce. In the present study, soil and lichen samples (partially located under the forest canopy) were concurrently collected from 62 sampling sites across the Hengduan Mountains to characterize the occurrence, spatial distribution patterns, and underlying controlling factors of PAHs. The total concentrations of the 16 US EPA priority PAHs (∑₁₆PAHs) in soils and lichens ranged from 59.8 to 1163 ng/g and 174 to 3362 ng/g, respectively—values consistently higher than those reported in corresponding matrices from the northern and northwestern TP. Further, concentrations of PAHs in both soil and lichen under the forest canopy are significantly higher than those on the leeward slope without forest. Compositional fractionation of PAHs along the longitudinal and latitudinal gradients of sampling locations indicates significant modulation of PAH distribution by both the Indian monsoon and East Asian monsoon, a pattern further corroborated by air mass backward trajectory analysis. Our results confirm that PAHs can be transported to the southeastern TP slope via long-range atmospheric transport (LRAT). Notably, the combined effects of mountain cold-trapping and forest filtering jointly govern the deposition and spatial distribution of PAHs in this region. Full article

As a crucial national ecological barrier, China’s Southern Collective Forest Region (SCFR) plays an essential role in maintaining regional ecological security and promoting sustainable development. Understanding the mechanisms driving the evolution of its ecosystem service value (ESV) is of great significance. Based on county-level data from 2000 to 2023, this study integrated the equivalent factor method, spatial autocorrelation analysis, the XGBoost-SHAP model, geographically and temporally weighted regression (GTWR), and partial least squares structural equation modeling (PLS-SEM) to examine the spatio-temporal evolution patterns and driving mechanisms of ESV in the SCFR. The results showed that ESV in the SCFR exhibited an overall downward trend, with a cumulative loss of 1973.77 × 10⁸ CNY. This was primarily due to marked reductions in hydrological and climate regulation services. The spatial distribution of ESV exhibited a significant heterogeneity—higher in the southwestern and southeastern mountainous regions, and lower in the northern plains and coastal zones, with the center of gravity shifting first to the northeast and then to the southwest. Local spatial autocorrelation revealed relatively stable “High–High” and “Low–Low” clustering characteristics, where high-value clusters were consistently distributed in core forest zones, while low-value clusters overlapped highly with urban agglomerations. Socio-economic factors exerted a significantly stronger influence on ESV than natural factors. Population density (POP), land use intensity (LUI), and gross domestic product (GDP) were identified as the dominant drivers, exhibiting distinct non-linear threshold effects and significant spatio-temporal heterogeneity. PLS-SEM analysis further quantified LUI as the dominant direct inhibitory pathway on ESV, highlighting urbanization’s indirect negative effect mediated through intensified LUI. Meanwhile, terrain effects were confirmed to positively influence ESV indirectly by constraining LUI and modulating local climate. The analytical framework of “threshold identification–spatio-temporal heterogeneity–causal pathway analysis” proposed in this study elucidated the complex driving mechanisms of ESV evolution, providing valuable guidance for ecological restoration evaluation and differentiated environmental governance. Full article

Forest structural complexity underpins habitat quality, microclimate buffering, and resilience, yet it remains poorly characterized across the Hindu Kush Himalaya (HKH) where field inventories and airborne LiDAR are difficult to scale across rugged terrain. Conservation planning and protected-area evaluation in the HKH therefore often rely on canopy height or cover proxies that do not directly represent vertical structural organization. Here we develop a repeatable, uncertainty-aware indicator of forest structural complexity from GEDI waveform LiDAR using the Waveform Structural Complexity Index (WSCI) and its prediction intervals. We first define a conservative analysis footprint (“trustable pixels”) by combining a woody-vegetation screen with minimum GEDI sampling support and canopy-stature plausibility, and by excluding the highest-uncertainty tail using a relative prediction-interval criterion. To separate complexity from canopy height, we model the HKH-wide expected WSCI–RH98 relationship and map height-normalized excess complexity (observed minus expected), identifying structural complexity hotspots and coldspots as the upper and lower tails of the excess distribution. Anomaly patterns are strongly organized along elevation and treeline-relevant belts and show coherent departures among ecoregions that persist after stratified adjustment for elevation and mean annual precipitation, indicating additional controls beyond broad environmental gradients. Protected areas exhibit systematically lower hotspot prevalence than surrounding landscapes, and within-elevation comparisons suggest this association is not explained by elevation alone, highlighting the need to interpret protected-area signals in the context of placement and land-use pressure. Overall, the anomaly atlas provides an operational indicator framework to stratify monitoring, prioritize field validation, and support the landscape-scale assessment of structural conditions beyond canopy height across one of the world’s most critical mountain forest systems. Full article

Urban sprawl constantly reconfigures the land use pattern, and such transformations may significantly modify regional carbon stocks. Utilizing Tai’an City as the study site, this research established a comprehensive integrated Patch-generating Land Use Simulation (PLUS), Integrated Valuation of Ecosystem Services and Trade-offs (InVEST), and Optimal Parameters-based Geographical Detector (OPGD) system to reconstruct carbon storage shifts from 2000 to 2020, project its reaction to four diverse development trajectories in 2030, and investigate the drivers underlying spatial disparities. The results indicate a persistent decline in carbon storage throughout the past two decades, with peak concentrations primarily gathered in mountain regions dominated by forest and grassland, whereas lesser amounts were grouped in urban and suburban areas defined by built-up land. Compared to 2020, the projected carbon stock in 2030 drops by 1,803,966 t under the natural growth trajectory and by 2,417,778 t under the high-quality economic growth pathway, whereas it rises by 47,326 t under cultivated land conservation and by 7679 t under ecological conservation. Elevation represents the most crucial driver among the selected variables in clarifying the spatial fluctuation of carbon storage (q = 0.3985), followed by slope (0.3323), mean annual temperature (0.2382), and the Normalized Difference Vegetation Index (NDVI) (0.1219). The synergy between elevation and NDVI produces the highest integrated explanatory power (q = 0.4906). These outcomes imply that constraining construction land growth while protecting agricultural and ecological land is vital for preserving and enhancing regional carbon sink potential. Full article

Spaceborne LiDAR systems, such as ICESat-2, provide critical data for global land cover and topography; however, their performance in rugged, vegetated landscapes requires rigorous local validation. This study evaluates the vertical accuracy of ICESat-2 ATL08 terrain height metrics in the complex Turkish Western Black Sea region, utilizing a reference dataset of high-precision terrestrial GNSS measurements. Following strict IQR-based outlier detection and photon density filtering, 1637 spatially matched segments were analyzed. The h_te_best_fit terrain height metric showed the best agreement with the terrestrial GNSS reference data, yielding an RMSE of 3.37 m and a mean bias of −0.42 m, indicating a slight underestimation of the terrain surface. The univariate analysis revealed a strong positive correlation between terrain slope and vertical error, indicating that slope is the prominent degradation factor contributing to pulse broadening. Additionally, dense forest cover was found to limit ground photon retrieval, leading to increased error margins, whereas nighttime acquisitions offered slightly improved precision. These findings suggest that while ATL08 is a valuable topographic source, slope-dependent corrections are essential for applications in mountainous environments. Full article

The Changbai Mountain Forest Region contains one of the best-preserved mountain forest ecosystems in eastern Asia and serves as a critical ecological barrier in China. Using the Baihe Forestry Bureau as the study area, this research quantified forest surface fire behavior, and based on the historical wildfire occurrence data and the forest fire spread trends, proposed targeted strategies for fire prevention and emergency resource allocation. Forest fires in the coniferous and broad-leaved mixed near-mature forest pose the greatest threat to the region. The establishment of five supply storages in five strategic locations and the construction of new firebreak roads are essential for effective fire management in the Baihe Forestry Bureau. Full article

This study investigates plant species diversity, regeneration patterns, and the ecological drivers influencing endangered plant species in the Than Sa–Phuong Hoang Nature Reserve, Thai Nguyen Province, Vietnam. Although tropical forest ecosystems in Southeast Asia are known for their high biodiversity, there is still a lack of site-specific studies that integrate species diversity, regeneration dynamics, and environmental drivers at the reserve scale. A total of 15 standard plots (20 × 50 m) were established across three main forest types (limestone forests, soil mountain forests, and transitional forests) to assess species composition, community structure, and regeneration patterns. Multivariate analyses, including principal component analysis (PCA) and cluster analysis, were applied to identify key ecological factors shaping species distribution and regeneration. The results recorded 1234 plant species belonging to 171 families, confirming the high biodiversity of the study area. Regeneration capacity differed significantly among forest types and was strongly influenced by environmental variables such as canopy cover, soil moisture, topography, and human disturbance. Multivariate results revealed clear ecological differentiation among forest types, highlighting the role of environmental filtering in structuring plant communities. The three target species (Curculigo orchioides Gaertn, Parashorea chinensis, and Paphiopedilum hirsutissimum Stein) exhibited strong dependence on stable microhabitat conditions and showed limited regeneration under disturbed environments, indicating high sensitivity to ecological changes and anthropogenic pressure. This study provides new insights into species–environment relationships at a local scale and highlights key ecological drivers of endangered plant distribution and regeneration, contributing to more effective conservation planning and biodiversity management in tropical forest ecosystems. Full article

Grazing is a widespread land use practice with significant implications for biodiversity and ecosystem functioning. Wild ungulates, as key components of terrestrial ecosystems, play a vital role in maintaining ecosystem health. Dietary overlap exposes wild ungulates to intense competition with livestock, yet the effects of grazing on them remain underexplored. Using camera-trapping data from Xinglong County in the mountains of Southeast China, we investigated the spatiotemporal responses of eight wild ungulates to livestock (cattle and horses). Our results showed the following: (1) The potential distribution of suitable habitats for ungulates was primarily shaped by elevation (ELE), distance to temple (DTT), precipitation of the coldest quarter (bio19), and distance to water (DTW). Among the species, blue sheep (Pseudois nayaur) showed the strongest response to livestock presence. (2) Spatially, most ungulates appeared to avoid livestock; forest musk deer (Moschus berezovskii) showed spatial avoidance of horses. (3) Temporally, the daily activity patterns of most ungulates generally showed low to moderate overlap with those of cattle. These findings suggest that livestock grazing may be associated with negative effects on wild ungulates in Xinlong County. Given the ecological importance of ungulates, the need to maintain wildlife community integrity, and the long history of grazing in the region, further research is warranted to understand the role of livestock in shaping wildlife communities. Full article