Search Results (1,378)

Forest soils play a critical role in carbon sequestration and nutrient cycling by storing large amounts of soil organic matter (SOM). However, the integrated associations linking aboveground resource properties and belowground microbial processes influencing SOM dynamics remain poorly understood. In this observational, cross-sectional study, we analyzed 84 plots across six forest types at Mt. Gariwang, South Korea, to evaluate the relative importance of resource quality and resource quantity in relation to SOM dynamics. Total organic carbon (TOC), total nitrogen (TN), and the C:N ratio were used as indicators of SOM dynamics. Resource quality was represented by species richness (SR) and functional dispersion (FDis) as indirect proxies, whereas resource quantity was represented by aboveground biomass (AGB) and diameter at breast height diversity (DBH diversity). We also evaluated whether fungal and bacterial ASV richness were statistically linked to the relationships between aboveground resource properties and SOM dynamics. Functional dispersion (FDis) was negatively associated with TOC (β = −0.28) and the C:N ratio (β = −0.51), whereas AGB showed no significant relationship with any SOM indicator. In contrast, SR was positively associated with Fungal ASV richness (β = 0.37), which was in turn positively linked to TOC (β = 0.43) and TN (β = 0.56) accumulation, suggesting an indirect statistical pathway consistent with fungi acting as a biological link between aboveground biodiversity and belowground carbon and nitrogen storage. These findings indicate that resource quality indicators showed divergent associations with SOM dynamics: a negative direct pathway via FDis and a positive indirect pathway via SR and fungal ASV richness, and that, overall, resource quality was more consistently associated with SOM dynamics than resource quantity. Our study provides new insights into the associations linking aboveground vegetation and belowground microbial communities and offers a scientific basis for biodiversity-based forest management to enhance long-term soil carbon sequestration. Full article

Accurate historical estimates of forest carbon stocks are essential for greenhouse gas inventories and REDD+ Measurement, Reporting and Verification (MRV) systems, particularly in remote and persistently cloudy regions where field inventories and optical remote sensing are limited. This study presents a retrospective mapping framework with potential relevance for Tier-3 forest carbon estimation of forest volume and carbon stocks in the temperate forests of southern Chile using historical ALOS PALSAR L-band SAR data integrated with Chile’s Continuous National Forest Inventory (CNFI). Three pilot zones in Los Lagos, Aysén, and Magallanes were analysed, covering approximately 42,000 km² of native forests dominated by Lenga, Coihue de Magallanes, Siempreverde, Roble–Raulí–Coihue, Coihue–Raulí–Tepa, and Alerce forest types. Annual 25 m ALOS PALSAR mosaics were processed to derive HH and HV backscatter, HH/HV ratio, and Radar Forest Degradation Index (RFDI) layers, which were used as predictors in k-nearest neighbours (k-NN) models calibrated with inventory plots projected to the 2010 reference year. Model performance varied substantially among forest types and pilot zones, with test r² values ranging from 0.12 to 0.90 and RMSE values between approximately 100 and 300 m³·ha⁻¹; the highest r² values were associated with forest types represented by relatively small samples and should therefore be interpreted cautiously. m³·ha⁻¹ Stratification by altitude and restriction to moderate volume ranges improved predictive performance in several cases, highlighting the influence of ecological gradients and SAR signal saturation at high levels of biomass. Despite substantial pixel-level uncertainty, the methodology reproduced broad regional patterns of forest structure and carbon distribution. Results demonstrate the potential of combining historical ALOS PALSAR archives with national forest inventories to support spatially explicit historical carbon estimation in data-limited forest regions. Full article

Understanding the habitat use by mountain ungulates is essential for conservation planning in mountainous ecosystems. However, it becomes important to know the habitat use pattern for endemic species living in rugged and remote terrain. In this study we examined the habitat-use patterns of endemic Himalayan Tahr (Hemitragus jemlahicus), a mountain ungulate in Govind Pashu Vihar (GPV) landscape of western Himalayan region. We surveyed the study area during pre-monsoon season from April 2025 to June 2025. The study area was divided into equal sized 43 grids of 2.5 × 2.5 km each. Data was collected through direct observations and indirect sign surveys, and analyzed using a single-species, single-season occupancy modelling framework. Occupancy (ψ) and detection probability (p) were modelled using nine site-level covariates (topographic, anthropogenic, and environmental) and two sampling-level covariates. As grid size approximated the species’ home range, occupancy (ψ) is interpreted here as an index of site use. The estimated site use (ψ) of Himalayan Tahr was 0.62 (SE ± 0.08), while detection probability (p) was 0.48 (SE ± 0.06). Site use increased with elevation, terrain ruggedness, and north-facing slopes, and was high in alpine grassland, sub-alpine scrubland, and sub-alpine forest, but declined in temperate and dense forest and in areas with intensive livestock grazing. In contrast, detection probability declined with increasing precipitation and was slightly lower under cooler conditions during the survey period. These results suggest that terrain-based security and forage availability, moderated by livestock presence are key correlates of habitat use by Himalayan Tahr. This study represents the first occupancy-based assessment of Himalayan Tahr habitat use in GPV, and the finding will provide critical baseline data to support future management strategies within ecologically sensitive alpine ecosystems. Full article

Global climate change and human activities have jointly exacerbated habitat fragmentation and expanded ecotones, significantly increasing the frequency and intensity of cross-habitat litter decomposition. The phenomenon whereby litter decomposes faster in its habitat of origin (“home”) than in other habitats (“away”) is known as the home-field advantage (HFA) effect. In-depth exploration of its core mechanisms and key drivers is crucial for revealing the spatial heterogeneity of global carbon and nitrogen cycles and for refining the theory of substance cycling in forest ecosystems. This study integrated 1410 observations from 102 published studies and used meta-analysis to systematically evaluate global patterns, biogeographical differentiation, and key drivers of the HFA effect. The results show that the HFA exhibits significant biogeographical differentiation and is driven by multiple factors. Globally, we found a significant positive HFA (LnRR = 0.0576, p < 0.05), with decomposition-related metrics (e.g., mass loss, decomposition rate) being 5.9% higher at home than away. The strength of the HFA effect shows significant dependence on climate and vegetation types. Regarding vegetation type, significant home-field advantages were observed for coniferous forests (10.15%), deciduous broadleaved forests (8.31%), and evergreen broadleaved forests (6.57%), while no significant differences were detected for shrublands or grasslands. Regarding climate type, subtropical (6.46%), temperate (9.20%), and cold/highland climates (9.53%) exhibited significantly higher home-site effects, whereas tropical and arid/semi-arid climates showed no significant differences. All analyses demonstrated substantial heterogeneity (I² = 65.5–98.3%). This study also systematically analyzed the associations of three core factor categories (environmental factors such as elevation and precipitation, litter chemical composition, and soil chemical properties) with HFA effect. Among these factors, Litter C/P and Litter N/P were verified as significant positive regulatory factors governing the HFA effect. In conclusion, the driving mechanism of the HFA exhibits systemic characteristics that manifest as the interactive and synergistic effects of multiple factors rather than the independent control of a single factor. Specifically, climate and vegetation types jointly dominate the formation of its macro-geographical patterns, while local abiotic factors (e.g., altitude, precipitation) and litter properties (e.g., chemical composition) further and precisely regulate the strength of the HFA effect through complex interactions. Based on a systematic evaluation using meta-analysis, this study provides an important theoretical basis and data support for understanding the driving mechanisms of the HFA effect in cross-habitat litter decomposition across different ecosystems. Full article

Dissolved organic carbon (DOC) is a climate-sensitive component of carbon cycling in inland waters, but consistent regional comparisons of its seasonal and interannual patterns remain limited across China. Here, we conducted a secondary analysis of a published monthly DOC dataset for 60 selected lake and reservoir series (15 per climate region) spanning China’s subtropical monsoon, temperate monsoon, temperate continental, and plateau mountainous regions during 2000–2023. The source dataset was generated using random forest models constrained by 1326 DOC observations from 83 lake and reservoir stations, and with watershed-scale climate, soil, and anthropogenic variables used as predictors. Across the four regions, the long-term mean DOC concentrations were 9.78, 14.10, 16.12, and 15.14 mg L⁻¹, respectively. Seasonal medians showed spring–summer enrichment in the two monsoon regions, nearly equal spring and summer values in the temperate continental region, and an autumn maximum in the plateau mountainous region. Interannual variability was greatest in the subtropical monsoon region (CV = 3.18%), whereas the plateau mountainous region had the lowest variability (CV = 0.95%). Mann–Kendall analysis identified a significant decline only in the temperate continental region (Z = −2.51, p = 0.012). These results provide a climate–region synthesis of model-derived DOC patterns in Chinese inland waters. Because climate variables contributed to the original random forest predictions, the present study interprets regional contrasts descriptively rather than as independent causal evidence of climatic controls. Full article

Nitrogen cycling is a key determinant of ecosystem functioning, productivity, and carbon sequestration during forest development. This review synthesizes ecological evidence on nitrogen cycling in young forest ecosystems established through natural regeneration, afforestation, reforestation, or major disturbance across boreal, temperate, and tropical biomes. The review evaluates how successional stage, plant community composition, soil properties, microbial processes, climate, and disturbance influence nitrogen transformations, retention, and losses during early forest development. The literature indicates that young forests can exhibit rapid nitrogen turnover while maintaining effective nutrient retention, although the balance between conservation and loss varies with biome, site conditions, and disturbance intensity. Boreal forests tend to show more conservative nitrogen cycling, whereas tropical forests generally exhibit faster turnover and greater nitrogen fluxes. The synthesis also highlights important knowledge gaps, particularly the limited availability of long-term studies, insufficient integration of aboveground–belowground interactions, underrepresentation of tropical and Southern Hemisphere forests, and limited assessment of climate-change effects on plant–soil–microbial feedbacks. Addressing these gaps will improve understanding of nitrogen dynamics during forest development and strengthen ecosystem modelling, forest restoration, and climate-change mitigation strategies. Full article

Surface biomass, including litter, organic matter and ground vegetation, plays a very important role in forest ecosystems for regulating water retention and soil erosion. At the global and European temperate forest scale, no bibliometric analysis has previously been conducted, even though the scientific interest has been growing. This bibliometric analysis studied 1189 global and 178 European temperate forest articles retrieved from Scopus from 2005 to 2025 using RStudio (bibliometrix) and VOSviewer. The global output grew at an annual growth rate of almost 20.83%, coinciding with the Paris Agreement 2015 and the European Green Deal 2019 that may have brought scientific attention to climate change, hydrological process, forest ecosystem services and sustainable forest management, leading to the increases, while European research accounted for only 14.9% of global output and was mainly influenced by Mediterranean fire-related research, which limits its direct applicability to central European forest conditions. China and the USA dominated the global research output. Despite being the country with 30% of its area covered with forests, no Polish institution appeared in the top 10 contributors in both the global and European datasets. Thematic analysis showed that infiltration and surface runoff are poorly integrated with forest management and climate change research. Litter and soil organic carbon appeared as an emerging topic in the European Temperate Forest dataset. Three dominant tree species of the central European temperate forest, Scots Pine (Pinus sylvestris L.), Norway Spruce (Picea abies), and European aspen (Populus tremula L.), were each mentioned just once in 178 European publications, indicating the need for species-specific research about water retention and erosion susceptibility and surface runoff. This bibliometric analysis identified the significant species-specific, institutional, and regional knowledge gaps in European temperate forest research, most importantly, for the central European ecosystem and the dominant Polish forest. The study highlighted the limited incorporation of hydrological processes with forest management and climate adaptation strategies. Future research direction should focus on long-term field research analysing biomass changes, water retention and erosion susceptibility in the European temperate forest ecosystem, while promoting stronger international research collaborations. Full article

Forest inventory compartments provide extensive and management-relevant reference information for satellite-based tree species mapping, but their dominant-species attributes are defined at the stand level rather than for individual image pixels. Existing applications commonly derive training samples from compartment centres or assign polygon labels to enclosed pixels, which may introduce boundary effects, uneven class representation, and disproportionate contributions from individual compartments. However, the intermediate step of converting inventory polygons into spatially controlled pixel-level reference samples has received comparatively limited attention. Here, we developed a geometry-constrained reference sample construction framework that integrates interior-position screening, class balancing, source compartment contribution control, and spatial-spacing constraints. The framework was evaluated for mapping Korean pine, larch, white birch, and spruce in a temperate mixed forest in northeastern China using Sentinel-1/2 time series and ancillary predictors. Predictor–classifier combinations were selected using compartment-grouped out-of-fold evaluation, sampling workflows were compared on 60 independently withheld compartments, and the final map was further assessed using 306 independent reference points. Relative to centroid sampling, the geometry-constrained workflow increased compartment-level macro-F1 from 0.612 to 0.709. XGBoost with optical time series and ancillary predictors achieved the best development-set performance, while inclusion of the complete Sentinel-1 time series provided no further gain. The final model achieved an overall accuracy of 0.827 and a macro-F1 of 0.820 on the independent reference points. Aggregation of 10 m predictions further enabled compartment-level characterization of mapped dominant species, dominance strength, and mixing intensity. These results demonstrate that reference sample construction is a consequential step in tree species mapping from polygon-based forest inventories and provide a practical approach for linking pixel-level remote sensing classification with forest management units. Full article

Soil organic carbon (SOC) in mountain forest ecosystems exerts critical controls over regional carbon balance and climate feedback loops. This study collected 209 stratified topsoil (0–30 cm) samples across temperate mountain forests of Northeast China, conducted a boosted regression tree (BRT) modeling framework integrated with space-for-time substitution, and established 15 combined thermopluviometric sensitivity scenarios to simulate SOC shifts under diversified climate disturbances. Tenfold cross-validation yielded a model mean R² of 0.62, revealing mean annual temperature (MAT, RI = 35.31%) as the most influential predictor of SOC spatial variation, followed by elevation (ELE, RI = 19.11%), while single-season NDVI and soil particle fractions showed weak predictive capacity. Multi-scenario spatial simulation outputs demonstrated that simultaneous warming and aridification drastically reduce the coverage of high SOC zones, whereas increased precipitation can partially offset temperature-induced carbon mineralization losses. Terrain-mediated SOC spatial stratification remained stable across all climate backgrounds. This study quantifies the layered environmental association hierarchy of mountain SOC and generates spatially explicit modeled carbon sink projections under climate change. The terrain-dependent SOC response patterns provide operable differentiated carbon regulation guidance: humid low-lying convergence zones require long-term soil moisture conservation, while arid steep ridges need native mixed forest restoration to lift baseline carbon storage capacity, supporting precise watershed climate adaptation and targeted forest carbon sink management for temperate mountain regions. Full article

Understanding how trees coordinate carbon acquisition and allocation under warming is essential for predicting forest–carbon dynamics; however, whether warming induces common or species-specific source–sink regulation strategies remains unresolved. We conducted a field warming experiment (+2 °C and +4 °C above ambient) to investigate photosynthetic responses, organ-specific non-structural carbohydrate (NSC) dynamics, and carbon allocation strategies in two temperate tree species, Fraxinus mandschurica and Juglans mandshurica. Moderate warming (+2 °C) initially enhanced carbon assimilation in both species, whereas severe warming (+4 °C) progressively inhibited photosynthetic performance during the later growing season. In F. mandschurica, +2 °C warming promoted carbon storage by increasing starch accumulation across leaves, stems, and roots, with starch concentrations 2.5–38.0% higher than those in control plants from July to September. These enhanced NSC reserves were positively associated with photosynthetic performance and survival, indicating an effective source-driven carbon storage strategy. In contrast, J. mandshurica exhibited a distinct carbon allocation pattern under warming, characterized by preferential soluble sugar accumulation in leaves and reduced carbon investment in storage tissues. Specifically, leaf soluble sugar-to-starch ratios increased by 6.0–162.3%, whereas root soluble sugar content decreased by up to 55.7% under warming, suggesting a shift toward short-term carbon regulation rather than long-term storage. Structural equation modeling further demonstrated that photosynthetic performance and leaf NSC pools were central regulators of warming responses, but their effects on downstream carbon allocation differed between species. Our results reveal that warming does not induce a uniform carbon response among temperate trees; instead, species-specific source–sink regulation strategies determine carbon resilience under elevated temperatures. These findings improve understanding of how coexisting tree species may diverge in their adaptive capacity under future climate warming. Full article

Forests store carbon in downed logs, whose decomposition is driven by bacterial and fungal communities. Yet most studies treat individual logs as homogeneous units, obscuring internal–external gradients in wood chemistry as fine-scale habitat filters. To address this gap, we combined ALDEx2, SpiecEasi networks, Mantel tests and PLS-SEM on 24 samples from Larix principis-rupprechtii logs spanning three decay stages (I, III, and V) and two radial positions. Chemical heterogeneity between positions peaked at Stage III (5.9-fold difference in total nitrogen), with severe internal nitrogen and phosphorus depletion. Bacterial alpha diversity converged between positions by Stage V, whereas fungal communities maintained persistent divergence, and differentially abundant taxa showed stage- and position-associated enrichment patterns. Network topology did not differ detectably between internal and external wood. Path modelling showed contrasting associations: fungal composition tracked primarily the decay-stage axis, whereas bacterial composition was associated more weakly and mainly through an indirect nutrient channel. These results provide a fine-scale, descriptive account of divergent bacterial and fungal responses to within-log heterogeneity during downed-log decomposition in a temperate coniferous forest. Full article

Fine-scale mapping of forest types is a prerequisite for accurately assessing forest biomass, biodiversity, ecosystem service values, and carbon budgets. Shihe County, located within an ecotone transitioning from subtropical to temperate monsoon climates in China, was selected as the case study area. By integrating Sentinel-1 SAR and Sentinel-2 multispectral imagery, along with derived vegetation indices, texture features, and backscattering coefficients, as well as statistical features extracted from the 2022 NDVI time-series, we employed a hierarchical classification framework and a random forest algorithm to generate the forest type map. The results indicated the following: (1) With a single-date multi-feature dataset, late winter (3 March) was determined to be the optimal period for forest type classification in Shihe County. (2) Shortwave infrared bands, red-edge bands, the modified vegetation index, the normalized difference red-edge index, mean texture features, and VH-polarization data were the most influential variables. (3) Incorporating yearly NDVI time-series statistical features into the single-date winter subset significantly improved classification performance, yielding an overall accuracy of 86.39% and a Kappa of 0.781, which represents a 10.83% improvement over the baseline. Persistent misclassification between bamboo forests and tea plantations remained a primary constraint on further accuracy enhancement, while the classification accuracy for evergreen broadleaf forest and deciduous coniferous forest exhibited considerable uncertainty, likely attributable to limited reference sample sizes. (4) Deciduous broadleaf forests constituted the dominant land cover type in Shihe County, whereas evergreen coniferous forests, bamboo, and tea plantations were also widely distributed, collectively reflecting the region’s transitional ecological characteristics. Full article

Climate change drives shifts in forest vegetation zones, and the major tree species of warm–temperate evergreen broad-leaved forests in South Korea are also expected to undergo changes in their potential distributions under future climate conditions. This study applied a Committee Averaging (CA) ensemble species distribution model to Quercus acuta, Machilus thunbergii, Quercus glauca, and Castanopsis sieboldii to project changes in their potential distributions under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) across two future periods (2050s and 2090s). To compare interspecific differences in response more clearly, we applied a two-tier threshold scheme that distinguished potential habitat (agreement ≥0.6) from highly suitable habitat (>0.8), and we concurrently conducted a Multivariate Environmental Similarity Surface (MESS) analysis to assess predictive uncertainty arising from extrapolation into future climates. The CA ensemble models showed excellent predictive performance (AUC 0.947–0.989; TSS 0.837–0.943). For Q. acuta, M. thunbergii, and Q. glauca, potential habitat expanded consistently across all SSP scenarios, and highly suitable habitat shifted northward into parts of the central and Gangwon regions. In contrast, both the potential habitat and the highly suitable habitat of C. sieboldii contracted under most future scenarios. These results demonstrate that even species belonging to the same warm–temperate evergreen broad-leaved forest community can respond differently to future climate. The two-tier threshold scheme applied in this study was effective not only for assessing whether distributions expand but also for delineating and evaluating climatically stable core habitats. Although our findings need to be interpreted in light of the uncertainty associated with extrapolation into future climates, they can serve as useful baseline data for establishing climate-change-adaptive forest conservation and species-specific management strategies. Full article

Understanding the dynamics of carbon (C), nitrogen (N), and phosphorus (P) stoichiometry and C stocks along a stand development chronosequence has been extensively studied in forest ecosystems. However, despite the global economic and ecological importance of apple orchards, such knowledge remains limited for these intensively managed perennial agroecosystems. We examined C, N, and P concentrations and stoichiometric ratios in tree tissues (root, stem, branch, foliage) and soils (0–100 cm depth), as well as ecosystem C stocks, across a chronosequence of 4, 8, 12, and 16 yr old Malus pumila orchards in the eastern Yan Mountains, Hebei Province, North China. The results showed that C concentrations exhibited no consistent age-dependent trend in tree tissues. In contrast, N and P concentrations in all tree tissues decreased significantly with stand age, while their C:N and C:P ratios increased. The leaf N:P ratios suggested progressive P limitation as orchards aged. In soil, C, N, and P concentrations first decreased and then increased along the chronosequence, with the highest values observed in the 16 yr stands. This U-shaped trajectory reflected the dynamic interplay between stand development and anthropogenic management. Intercropping and intensive fertilization in the 4 yr orchards initially elevated soil nutrient levels, while the cessation of intercropping and nutrient removal via fruit harvesting in the 8 yr stands led to a decline. Thereafter, accumulation of litter decomposition and root turnover, combined with continued organic matter inputs, progressively replenished soil nutrient pools in the 12 and 16 yr stands. The total ecosystem C stocks ranged from 70.80 to 136.13 Mg ha⁻¹, initially declining from 4 to 8 years and then increasing at 12 and 16 years, with soil contributing 84.7–99.7% of the total. Plant and soil nutrient concentrations showed predominantly negative correlations, indicating weak coupling between tree and soil nutrient pools. Our findings demonstrated that stand age profoundly influenced C:N:P stoichiometry and C stocks in apple orchard ecosystems and that prolonged orchard development enhanced both tree biomass C and soil C stocks. These results provide a scientific basis for nutrient optimization and sustainable management of apple orchards in temperate regions. Full article

Soil fungi play a key role in nutrient cycling and soil organic matter turnover, yet the influence of pedological context on fungal communities across forest types remains insufficiently understood. Here, we combined soil chemical analyses, Fourier-transform infrared spectroscopy (FTIR), and ITS2 metabarcoding to investigate soil properties and fungal communities in temperate mountain beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) H. Karst) forests in Italy developed on contrasting geological substrates. Soil horizons were sampled across seasons to characterize the main associations between fungal community structure, inferred functional diversity, and environmental context. Soil chemistry revealed site- and horizon-dependent patterns, particularly in pH, Ca, and P availability, whereas differences related to dominant tree species were comparatively limited. FTIR spectra showed clear variation in organic matter composition among sites, consistent with site- and stand-associated differences in organic matter composition. Fungal community composition was primarily associated with site and soil horizon. Functional guild patterns suggested ectomycorrhizal dominance in Ca-rich soils and greater prevalence of saprotrophs in more acidic soils. Overall, this multi-proxy approach suggests that pedological context was more closely associated with fungal community structure and ecological strategies than with vegetation type or season within the studied stands. These patterns should be interpreted as site-specific and hypothesis-generating because substrate types were not replicated across independent locations. Full article