Search Results (740)

Aboveground biomass (AGB) is an important indicator for monitoring ecosystem carbon stocks and vegetation productivity. However, optical-remote-sensing-based AGB estimation is prone to saturation effects. Multi-source remote sensing fusion provides an important means of alleviating optical saturation. Although the optimal estimation result can currently be obtained directly on the basis of overall model accuracy, the contribution mechanisms and effective ranges of different information sources after optical saturation, as well as their dependence on topographic background, remain difficult to explain. Accordingly, this study used Dongzhai National Nature Reserve in Luoshan County, Henan Province, China, as the study area and 90 field-measured AGB values as the target variable; integrated GEDI L2A/L2B, Landsat 9, Sentinel-2, GF-2, GF-5B hyperspectral, Sentinel-1, topographic, and climatic data; constructed four feature sets comprising optical information Sp, structural information St, microwave scattering information Se, and topographic and climatic information En; designed eight ablation experiments using a random forest model; and analyzed the contribution mechanisms and response thresholds of multi-source remote sensing information for AGB estimation under optical saturation. The results showed that: (1) St was the core information source for improving AGB estimation accuracy in the reserve, and adding only structural information to optical information increased the model OOF R² from 0.169 to 0.433, and the high-AGB interval (64.18–129.456 Mg ha⁻¹) was the primary source of model estimation error; (2) under the full-sample sliding-window framework of this study, the predictive response of Sp gradually weakened with increasing AGB and eventually entered a stable saturation state. Thereafter, St provided sustained and stable compensation for RMSE and MAE, whereas the improvements from Se and En were mainly concentrated in the transition stage from weakening optical response to stable saturation, and only when both were simultaneously incorporated in the presence of St; (3) multi-source remote sensing fusion is not necessarily more effective with more information sources. The key lies in whether different information sources can provide effective information under specific ecological backgrounds and observation conditions. Full article

Afforestation assessments in Mediterranean karst regions often focus on vegetation and soil carbon, paying less attention to microbial activity. We examined the surface soil properties of a four-site Cedrus libani chronosequence in southern Turkey. In October 2024, topsoil (0–10 cm deep) was sampled at one degraded reference site and three plantation sites aged approximately 9, 14 and 24 years (15 samples were taken from each site). The afforested sites generally exhibited higher levels of soil organic carbon, total nitrogen, aggregate stability and microbial biomass carbon (MBC). Mean MBC ranged from 288 to 536 mg C kg⁻¹ at afforested sites versus 180 mg C kg⁻¹ at the reference site. Basal respiration was lower (0.30–0.36 versus 0.96 µg CO₂-C g⁻¹ h⁻¹), as was biomass-specific respiration (qCO₂: 0.54–1.39 versus 5.41 mg CO₂-C g⁻¹ MBC h⁻¹). The microbial quotient did not differ significantly. The pooled MBC–respiration association was weak, whereas the site-adjusted association was positive. Multivariate patterns and the non-monotonic ordering of sites highlighted edaphic heterogeneity. As plantation age was completely confounded with site identity, these single-campaign observations cannot establish causal temporal effects. Nevertheless, integrating structural, chemical and microbial indicators provides complementary information for characterizing soil conditions across these karst sites. Full article

Unvegetated tidal flats store sedimentary organic carbon (OC), but their contribution to blue-carbon inventories remains poorly constrained because sparse cores must represent heterogeneous intertidal environments. This study quantified OC stock within the upper 1 m of Hwangdo tidal flat, South Korea, by integrating ten 100-cm cores, 107 surface-sediment samples, and an unmanned-aerial-vehicle-derived digital elevation model covering 4.841 km². The surface survey characterized variations in elevation, sediment texture, and OC, while the cores provided profiles of grain size, dry bulk density, and OC content. Core stocks were integrated over 0–100 cm and evaluated using a spatially grouped, cross-validated adjustment based on surface elevation and uppermost-sediment OC to reduce bias from sparse core distribution. Measured core stocks ranged from 13.61 to 30.20 Mg C ha⁻¹, with an unadjusted mean of 23.04 Mg C ha⁻¹. Mean OC contents were low in surface sediments (0.18%) and core sediments (0.17%). Across the pooled surface and core dataset, TOC correlated positively with mud content (Spearman’s ρ = 0.47) and negatively with sand content (ρ = −0.51), indicating sediment-textural control over OC distribution. The adjustment increased the mean stock by 5.9% to 24.39 Mg C ha⁻¹. Applying this value to 484.108 ha yielded a regional OC storage of 11.81 Gg C, with a conditional bootstrap interval of 9.12–12.90 Gg C. However, the low cross-validated Q² (0.070) shows that the model adjusts the core mean rather than providing a spatially explicit prediction. Overall, Hwangdo’s comparatively low OC pool likely reflects the combined effects of limited inputs of terrestrial organic matter; the absence of vascular vegetation and the associated belowground biomass that would otherwise promote carbon retention; and the frequent reworking, oxygenation, and export of organic matter from its sand-dominated, hydrodynamically energetic sediments. By integrating depth-resolved cores with dense surface observations and UAV-derived topography while explicitly reporting conditional uncertainty, this study establishes a transferable framework for more defensible blue-carbon inventories and strategically targeted sampling in data-limited unvegetated tidal flats. Full article

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

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

To address severe soil erosion and ecological restoration difficulties on abandoned karst sloping farmland, this study proposed and tested an innovative micro-topography modification strategy—film covering of rock outcrops. Field experiments were conducted on typical abandoned karst slopes with 20 standard runoff plots (10 covered, 10 uncovered). Compared with non-covered plots, film covering significantly improved soil properties: bulk density decreased by 6.6%, total porosity increased by 6.0%, non-capillary porosity by 29.6%, macro-aggregates (>2 mm) by 11.6%, soil organic carbon by 14.5%, and volumetric water content by 26.0%. Vegetation also benefited: aboveground biomass increased by 39.9%, root biomass by 45.3%, vegetation coverage by 12.2%, and root vertical pullout resistance by 29.7%. Consequently, surface runoff depth was reduced by 23.9% and sediment concentration by 24.8%. Correlation analysis revealed significant correlations between soil–vegetation indicators and runoff/sediment yield. Specifically, runoff depth was closely linked to bulk density and total porosity, while sediment concentration correlated strongly with total porosity, root pullout resistance, aboveground/root biomass, capillary porosity, and bulk density. This study confirms that film covering of rock outcrops improves soil–vegetation conditions at the microscale and effectively reduces runoff and sediment generation. Full article

Individual-tree-level information on crown distribution and morphology underpins forest inventory, biomass estimation, and carbon accounting. High-resolution Unmanned Aerial Vehicle (UAV) imagery resolves single-tree detail, but automated crown extraction remains difficult: fully supervised segmentation depends on costly pixel-level annotation that generalizes poorly, while the Segment Anything Model (SAM), though training-free, cannot locate trees on its own and existing SAM-based methods restore this ability only by adding task-specific training. We present an end-to-end, annotation-free toolkit for tree crown extraction and ecological analysis. A RetinaNet-based DeepForest detector produces coarse boxes; an adaptive module then removes duplicate boxes and non-vegetation false positives using an intersection-over-union rule and a global greenness index, converting noisy boxes into clean prompts; these prompts drive SAM to decode irregular crown masks without task-specific training; and geometric and texture features are extracted and grouped by principal component analysis and K-means clustering to map ecological patterns. We evaluated the toolkit on multi-biome imagery from the public OAM-TCD dataset. Because pixel-exact metrics are unstable at 10 cm resolution, where wind sway, shadow shift, and small labeling offsets are strongly amplified, we assessed accuracy under an absolute physical-distance tolerance. At a 2.0 m tolerance, consistent with the effective radius of a mature crown, the toolkit reached a precision of 91.25%, a recall of 86.40%, and an F1-score of 88.76%; bootstrap and Monte Carlo resampling confirmed these values are stable. Without manual annotation, it characterized more than 4700 individual crowns and recovered distinct vegetation patterns across geographic settings, offering a highly adaptable, low-cost baseline tool that demonstrates robust performance across the diverse multi-biome scenes within the OAM-TCD dataset. Full article

Accurate quantification of aboveground biomass (AGB) for sparse desert vegetation is fundamental for assessing regional carbon sink potential, yet large-scale data retrieval remains constrained by high spatial heterogeneity and severe background noise. Focusing on Haloxylon ammodendron communities in the Gurbantunggut Desert, this study integrated plot-level ground truth derived from Unmanned Aerial Vehicle Light Detection and Ranging (UAV-LiDAR) with multi-source satellite imagery (Sentinel-2 and Jilin-1) to evaluate AGB estimation accuracy and spatial distribution patterns across various feature combinations and employed four machine learning algorithms at a 10 m pixel scale. The Difference Vegetation Index (DVI) exhibited the strongest explanatory power for AGB spatial variance, whereas downsampled high-resolution textures induced feature redundancy. Among the evaluated algorithms, the Random Forest (RF) model driven solely by multispectral parameters achieved the optimal cross-scale mapping accuracy (R² = 0.72, RMSE = 1.32 t ha⁻¹). The total regional AGB storage was estimated to be approximately 6.99 × 10⁴ t, with low-density habitats (0.2–2.0 t ha⁻¹) occupying 90.39% of the area. This study confirms the feasibility of integrating UAV point clouds with multi-source satellite imagery for the large-scale retrieval of sparse shrub biomass, providing a quantitative basis for desert carbon management. Full article

Reliable forest biomass and carbon-stock assessment is essential for climate-change mitigation and sustainable forest management, particularly in semi-arid Mediterranean mountain forests affected by drought, wildfire and tree decline. Here, we estimated above-ground biomass (AGB), total biomass, carbon stock and CO₂-equivalent storage in the Ouled Yagoub Forest, northeastern Algeria, by combining field inventory data, species-specific allometric equations, Sentinel-2 vegetation indices and elevation. We established 60 circular plots of 0.1 ha in April 2026 and retained 54 stocked plots for biomass modelling. The field inventory included 661 trees: 467 Pinus halepensis and 194 Cedrus atlantica, including 122 healthy and 72 declining cedar individuals. Field estimates indicated an AGB of 338.07 Mg, equivalent to 62.61 Mg ha⁻¹ for stocked plots. Total biomass reached 436.11 Mg, while carbon stock and CO₂-equivalent storage reached 238.56 Mg C and 874.78 Mg CO₂eq, respectively. The NDVI-based model explained 78.3% of AGB variability, with Pearson’s r = 0.885, RMSE = 48.77 Mg ha⁻¹ and MAE = 39.14 Mg ha⁻¹. Cross-validation confirmed acceptable model stability, with LOOCV R² = 0.755 and RMSE = 51.86 Mg ha⁻¹, and 5-fold CV R² = 0.762 and RMSE = 51.07 Mg ha⁻¹. SAVI produced identical predictive performance because it was perfectly collinear with NDVI. Therefore, we selected the NDVI-only model as the most parsimonious model for spatial prediction. Declining Cedrus atlantica individuals showed lower estimated biomass and carbon storage than healthy cedar individuals, although this difference represents an observed pattern rather than a direct causal quantification of carbon loss due to dieback. The resulting maps provide field-calibrated exploratory spatial estimates rather than independently validated carbon maps. The research directly aligns with the principles of Sustainability, contributing to climate change mitigation and resilient forest management in semi-arid Mediterranean ecosystems. In addition, this work provides a stocked-plot carbon baseline and supports forest carbon monitoring, cedar conservation and restoration planning in the Aurès Mountains. Full article

As the unique edible nut species in China, Chinese hickory (Carya cathayensis Sarg.) is vulnerable to anthropogenic disturbances that reduce vegetation residue inputs and soil organic matter accumulation. To investigate the effects of net-harvesting-associated understory management on the soil carbon pool management index (CPMI), soil samples were collected from C. cathayensis plantations subjected to net harvesting for 2, 3, 6, and 7 years, with traditional beating as the control. Long-term net harvesting significantly increased particulate and dissolved organic carbon, microbial biomass carbon, and labile organic carbon (p < 0.05). It also altered soil enzyme activities, microbial community composition, and microbial co-occurrence network complexity. Soil physical and chemical properties and carbon pools were key drivers of enzyme activities and microbial complexity. Partial least squares path modeling (PLS-PM) revealed that understory vegetation positively influenced the CPMI (total effect = 0.57), while soil biological processes also contributed to CPMI variation. Overall, net harvesting reduced anthropogenic disturbance, enhanced litter-derived carbon inputs, and promoted soil biological functions, thereby improving the CPMI. These findings provide insights into sustainable soil management and carbon sequestration in C. cathayensis plantations. Full article

Cultivated grasslands provide an important strategy for reducing pressure on degraded natural grasslands and increasing high-quality forage supply. However, how stand-age-related variation affects belowground–aboveground coordination and forage production in cultivated Leymus chinensis remains unclear. Here, we compared a natural L. chinensis stand (NL) with 3-, 4-, and 5-year-old cultivated ‘Zhongke No. 1’ stands by integrating plant trait measurements, biomass assessment, nutrient analysis, forage quality evaluation, correlation analysis, and structural equation modeling. (1) Compared with NL, cultivated stands generally showed greater vegetative growth and aboveground biomass, lower fiber concentrations, and higher soluble sugar concentration and relative feed value. (2) Root and aboveground traits exhibited distinct stand-age-related patterns, with the 3Y stand showing greater root exploration traits, the 4Y stand achieving the highest aboveground biomass (4.61 t/hm²), and the 5Y stand exhibiting greater root thickening and ramet density. (3) Carbon, nitrogen, and phosphorus concentrations varied among stand ages, indicating shifts in nutrient status during stand development. (4) Correlation analysis and PLS-SEM revealed that root architecture, nutrient status, and aboveground morphology were closely associated with forage yield and quality variation. These findings highlight the importance of stand-age-dependent belowground–aboveground coordination for optimizing the management and utilization of cultivated L. chinensis grasslands. Full article

Cibotium barometz (L.) J.Sm., a medicinal fern, relies on three interconnected processes for in vitro propagation: spore germination, ordered gametophyte development, and successful initiation and early establishment of the sporophyte generation. However, during aseptic subculture, gametophytes frequently deviate from this developmental trajectory. The predominant abnormalities include filamentous arrest, thick fan-shaped blades, and irregular spatulate blades, all of which were associated with reduced archegonial maturation and subsequent sporophyte establishment. In this study, developmental time-course observation, paraffin-section histology, and medium-regulation experiments were integrated to establish a diagnosis–recovery–initiation framework for Cibotium barometz gametophytes. Spore germination and gametophyte development were divided into eight practical checkpoints: spore imbibition, spore-wall rupture, rhizoid emergence, rhizoid elongation, filamentous prothallus, lamellar prothallus, cordate gametophyte, and sporophyte formation. The ontogeny of archegonia was delineated into six histological stages, ranging from the initial-cell stage to the pre-fertilization stage. Based on an integrative assessment of population appearance, individual morphology, and anatomical sections, abnormal gametophytes were classified into three diagnostic categories. Filamentous arrest manifested as wool-like or thread-like growth patterns, featuring persistent chain-like cellular organization and failure to develop a two-dimensional blade. Thick fan-shaped blades showed pronounced enlargement and thickening; section images revealed narrow, densely packed cells, accumulation of storage compounds, and localized wall thickening, a pattern consistent with, but not sufficient to demonstrate, a preferential shift toward vegetative proliferation. Irregular spatulate blades were narrow and asymmetric and showed morphological and histological features suggestive of disrupted tissue polarity. Although archegonial initial cells or primordium-like structures were intermittently detected, they infrequently advanced to mature archegonia. Medium treatment significantly affected arrest rate, hypertrophy rate, sporophyte initiation, and mean young-sporophyte height (p < 0.001). Murashige and Skoog (MS) medium supplemented with IAA, 6-BA, and activated carbon was associated with the highest arrest rate, whereas full-strength MS medium was associated with the most pronounced hypertrophy. Among hormone-free subculture treatments, 1/2 MS + activated carbon gave the highest sporophyte initiation rate (71.45% ± 9.16%); the same formula also performed well in primary hormone-free cultures (70.54% ± 9.07%). Correlation analysis showed a strong positive association between sporophyte initiation rate and mean young-sporophyte height (r = 0.935, p < 0.001), while arrest and hypertrophy were negatively associated with sporophyte initiation. These results support evaluating in vitro propagation using quantified developmental outcomes—arrest rate, hypertrophy rate, sporophyte initiation rate, and mean young-sporophyte height—rather than biomass alone. Under the tested conditions, hormone-free 1/2 MS + activated carbon was associated with the most favorable recovery outcomes; the underlying mechanisms require validation by quantitative histology, gene-expression analysis, endogenous-hormone profiling, and direct measurement of compounds adsorbed by activated carbon. 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

Post-fire plantations play a crucial role in recovering carbon stocks, yet how carbon is partitioned among vegetation, litter, and soil pools during stand growth dynamics remains insufficiently resolved for Quercus acutissima plantations. Forest ecosystems play a crucial role in the global carbon cycle. This study quantified carbon-storage allocation and identified stand characteristics and soil factors associated with carbon recovery in fire-affected Q. acutissima plantations. Using a chronosequence design, we compared five stand-age classes (4, 10, 25, 45, and 50 years) on Huangfu Mountain, China, and measured carbon stocks in tree organs, understory vegetation, litter, and the 0–30 cm soil layer. Ecosystem carbon stock increased from 31.64 t ha⁻¹ in 4-year-old stands to 230.66 t ha⁻¹ in 50-year-old stands, representing a 629% increase. Soil was the dominant carbon pool, with 0–30 cm soil carbon rising from 25.32 to 126.56 t ha⁻¹ (a 400% increase). The contribution of soil carbon to total ecosystem storage declined from approximately 80% in 4-year-old stands to 55% in 50-year-old stands, indicating a shift in allocation toward vegetation biomass over time. Carbon accumulation was primarily concentrated in the 0–10 cm layer. Tree basal area was significantly associated with ecosystem carbon stocks, identified as a key structural factor linked to carbon accumulation through potential direct and indirect pathways involving light availability and soil carbon. Soil organic matter and nitrogen were also positively correlated with carbon accumulation. These findings suggest that stand development and topsoil carbon formation are closely linked to post-fire carbon recovery processes. Future management measures should optimize stand density, maintain soil fertility, and protect surface carbon to enhance long-term carbon sequestration. Full article

Urban green open spaces play a critical role in mitigating greenhouse gas emissions and enhancing biodiversity in rapidly urbanizing tropical megacities. This study aims to characterize vegetation structure and species diversity, as well as quantify above-ground carbon stocks in Taman Bendera Pusaka, South Jakarta, Indonesia. The results are expected to inform evaluations of urban parks’ contribution as nature-based solutions. A complete tree census was conducted between August and September 2025, recording diameter at breast height, height, and species identity for all individuals. Above-ground biomass (AGB) for woody trees was estimated using a widely applied pantropical allometric model developed for humid tropical forests, while separate generalized equations were applied respectively to the palms and bamboos groups to account for their distinct morphological characteristics. The estimated biomass values were subsequently converted into carbon stocks and CO₂ equivalents. Biodiversity was evaluated using Margalef richness, Shannon–Wiener diversity, and Pielou’s evenness indices. A total of 2459 individuals were recorded. Langsat Park had the highest species richness (S = 79) with diversity (H′ = 3.38; E = 0.77), and Leuser (S = 78) with highest diversity (H′ = 3.44; E = 0.79), whereas Ayodya Parks showed the lowest structures and diversity values (S = 33; H′ = 2.18; E = 0.68). Total AGB reached 5873.63 Mg, with a mean carbon density of 444.64 Mg C ha⁻¹ or 1631.82 Mg CO₂ ha⁻¹. Carbon storage was largely driven by a few dominant ornamental palms, particularly Roystonea regia, although native canopy trees contributed to structural stability. These findings show that even relatively small tropical urban parks can serve as significant localized carbon storage while sustaining urban biodiversity, underscoring the value of structurally diverse, native-enriched planting strategies for resilient urban forest management. Full article