Search Results (7,777)

Soil health is critical for the sustainability of tropical plantation ecosystems, However, the ecological factors driving productivity gradients remain inadequately understood. This study investigated rubber plantations on Hainan Island with varying yield levels to assess soil health and its underlying ecological mechanisms using a minimum data set (MDS) approach. Twenty-seven soil physical, chemical, and biological indicators were analyzed at two depths (0–20 cm and 20–40 cm). Principal component analysis identified seven key indicators for the MDS: soil organic matter (OM), alkaline-hydrolyzable nitrogen (AN), cation exchange capacity (CEC), dissolved organic carbon (DOC), microbial biomass phosphorus (MBP), acid phosphatase activity (ACP), and microbial diversity (Shannon-Wiener index, SHDI). The soil health indices derived from the MDS showed strong correlations with those generated from the total data set (TDS) (p < 0.001), confirming the reliability of the MDS framework. Overall, soil health levels were rated low to moderate with no significant differences across low-yield plantations (≤900 kg·ha⁻¹), medium-yield plantations (900–1200 kg·ha⁻¹), and high-yield plantations (≥1200 kg·ha⁻¹)., suggesting a decoupling of soil health and rubber productivity under uniform management practices. Random forest analysis identified microbial-driven phosphorus cycling, particularly MBP and ACP, as the primary determinant of soil health across soil layers, with DOC and SHDI also contributing significantly. These findings highlight the critical role of microbial-mediated nutrient cycling in maintaining soil health in rubber plantations and suggest that current management practices prioritize short-term yields over long-term soil ecological stability. Enhancing microbial activity and increasing organic matter inputs may be essential for improving soil health and ensuring the sustainability of rubber production in tropical agroecosystems. Full article

Riparian ecosystems are being increasingly threatened by hydrological alteration and biological invasions, yet the role of local environmental heterogeneity in shaping invasion dynamics remains poorly understood. To address this, we tested the hypothesis that invasion patterns are spatially structured and therefore cannot be fully captured by global statistical models. We evaluated this hypothesis by analysing the relationship between soil sand content and the abundance of Gleditsia triacanthos in a riparian forest of the Esteros de Farrapos and Islands of the Uruguay River National Park, Uruguay. Generalized Linear Mixed Model revealed no significant relationship between soil sand content and G. triacanthos abundance (χ² = 1.93, p = 0.17). In contrast, spatially explicit analyses showed that relationships between sand content and abundance were spatially contingent. Positive linear relationships predominated in areas with low sand content (mean 24.5%, n = 12), while negative relationships were restricted to the highest sand levels (mean 87.6%, n = 3). Intermediate sand-content zones (mean 47%, n = 16) showed no consistent patterns. These results suggest that invasion patterns vary across spatial contexts and may reflect the influence of different processes operating locally, indicating that relying solely on global analyses risks misinterpreting drivers and overlooking fine-scale variation. Our findings emphasize that understanding invasive species in heterogeneous systems requires considering whether mechanisms operate at local or broad scales, and that explicitly analyzing spatial structure can guide both hypothesis formulation and field study design. Full article

Urban trees are increasingly deployed as nature-based infrastructure to mitigate heat and manage stormwater, yet quantitative guidance on how species traits and site context shape transpiration remains fragmented. We conducted a systematic metadata analysis of seven field studies that measured daily transpiration rate in urban settings using heat-pulse methods. The units and spatial scales reported were harmonized with the sap flow density across active sapwood (J_s, g H₂O/${\mathrm{cm}}^2$/day) by converting reported stand transpiration and the outer 2 cm of sapwood sap flux using established Gaussian radial distribution functions for angiosperms and gymnosperms, which account for the non-linear decline in sap flux from the vascular cambium to the heartwood boundary. We then summarized distributions and tested group differences with Kruskal–Wallis and Dunn post hoc comparisons across wood anatomy, climate, soil texture, and planting configuration. Conifers exhibited significantly lower median $J_s$ (39.76 g/${\mathrm{cm}}^2$/day) than angiosperms, while the ring-porous group (median $J_s$ = 92.25 g/${\mathrm{cm}}^2$/day) and diffuse-porous groups (median $J_s$ = 96.70 g/${\mathrm{cm}}^2$/day) had similar distributions overall. Climate-modulated responses within wood anatomy groups differed, with diffuse-porous species exhibiting the highest median $J_s$ (152.59 g/${\mathrm{cm}}^2$/day) in semi-arid regions, ring-porous species maintaining comparatively stable median $J_s$ across climates (varying slightly between 80.72 and 99.32 g/${\mathrm{cm}}^2$/day), and conifers reaching their highest median $J_s$ (69.90 g/${\mathrm{cm}}^2$/day) in humid continental sites. Soil texture effects were consistent with moisture availability: sandy loam generally reduced $J_s$ relative to loam or silt loam for conifers and diffuse-porous species. Across anatomies, single trees transpired more than clustered trees or closed canopies. For example, planting as single trees increased median $J_s$ by 86% in conifers (from 33.01 to 61.37 g/${\mathrm{cm}}^2$/day) and by 45% in diffuse-porous species (from 81.31 to 118.25 g/${\mathrm{cm}}^2$/day). These results provide actionable ranges and contrasts to inform species selection and planting design for urban greening and runoff reduction, while highlighting data gaps for future research. Ultimately, by matching specific wood anatomies and planting configurations to local soil and climatic conditions, urban planners and ecohydrologists can strategically optimize urban forests to maximize targeted ecosystem services. Full article

Ledum palustre (L. palustre) is widely used in drug development because of its antibacterial and analgesic effects. However, wild L. palustre is often affected by wildfires, resulting in unstable yields. Forest fires represent a major disturbance in northern forest ecosystems and profoundly affect shrub vegetation and its associated rhizosphere microbial communities. In this study, we investigated a fire chronosequence (1991, 2004, 2012, 2017, and 2020) to systematically examine the morphological traits of L. palustre, rhizosphere soil physicochemical properties, and microbial community characteristics and to identify the key drivers underlying these patterns. The results revealed that postfire recovery time significantly influenced the morphological traits of L. palustre. The biomass, branch number, basal diameter, and plant height of the shrubs at the 1991 burned site increased by 270.49%, 36.11%, 79.32%, and 191.36%, respectively (p < 0.05). From unburned soils, 29 bacterial and 29 fungal isolates were obtained, with Bacillus sp. and Oidiodendron sp. being the dominant culturable bacterial and fungal taxa, respectively. With increasing postfire recovery time, soil moisture, total nitrogen, ammonium, nitrate, soil organic carbon, acid phosphatase (AP) and N-acetyl-β-D-glucosaminidase (NAG) activity significantly decreased. Early fire disturbance markedly altered soil microbial abundance and community composition, leading to an overall decrease in bacterial α diversity. The bacterial community structure at the 2020 burn site and the fungal community structure at the 2012 burn site significantly differed. Mantel tests revealed significant positive correlations between branch number and basal diameter (p < 0.01) and significant negative correlations between plant height and stem density (p < 0.001). Soil carbon and hydrolysable nitrogen were significantly positively correlated with AP and NAG activities (p < 0.001). Moreover, soil physicochemical properties significantly shaped soil microbial community structures, with bacterial communities in early postfire sites driven by total carbon and nitrogen (p < 0.05), whereas fungal communities in the 2012 burned site were influenced primarily by β-N-acetylglucosaminidase (BG) activity (p < 0.05). Fire disturbance drives successional changes in the rhizosphere microbial community structure and function by altering the soil nutrient status and enzyme activity, which in turn influences the morphological traits of L. palustre. This study provides a theoretical basis for improving the yield of L. palustre by exploring the variation in rhizosphere microorganisms. Full article

Soil salinization is one of the primary forms of land degradation in arid and semi-arid regions, severely constraining agricultural production in Xinjiang’s oases. Unmanned aerial vehicle (UAV) imagery provides an effective means for precise monitoring of soil salinization, with image spatial resolution being a key factor affecting assessment accuracy. However, traditional single-scale remote sensing monitoring methods rely solely on spectral and textural features at the leaf scale (0.1 m resolution captures leaf-scale characteristics), neglecting the contribution of multi-scale features (single-row canopy scale and single-membrane-covered area scale (6-row crop canopy)) to soil salinity. For instance, 0.5–1 m reflects single-row canopy scale, while 2 m reflects single-membrane-covered area scale. Therefore, this study developed a multi-scale UAV imagery and machine learning framework to enhance soil electrical conductivity prediction accuracy. This study focuses on oasis cotton fields in Shaya County, Xinjiang. Based on UAV multispectral imagery, we resampled data to generate eight datasets at different spatial resolutions: 0.1, 0.5, 1, 1.5, 2, 2.5, 5, and 10 m. For each resolution, we calculated 21 spectral indices and 48 texture features to construct a feature set. At both single and multispatial scales, spectral indices, texture features, and their spectral-texture fusion features were constructed. Combining these with Backpropagation Neural Network (BPNN), Random Forest Regression (RFR), and Extreme Gradient Boosting (XGBoost) models, a soil EC estimation framework was developed. The impact of three feature combination schemes on cotton field soil conductivity estimation using single-scale UAV imagery was compared. The accuracy of soil EC estimation for cotton fields was compared between multi-spatial scale and single-scale UAV image features. The optimal combination strategy for a multi-spatial scale and multiple features was determined. Results indicate that combining spectral and texture features yields the highest estimation accuracy for cotton field soil electrical conductivity in single-scale analysis. Multi-spatial scale image features outperform single-scale image features in estimating cotton field soil electrical conductivity accuracy. By comparing different feature combinations, when integrating 0.5 m spatial-scale spectra (S1, EVI, DVI, NDVI, Int1, SI) with 0.1 m texture features (RE1_ent, R_cor, RE1_cor, G_hom, B_mea, R_con, NIR_con), the XGBoost model achieved the optimal prediction accuracy ($R^2$ = 0.693, RMSE = 0.515 dS/m), outperforming the methods using multiple features at a single scale. This study developed a novel multi-scale image feature fusion technique to construct a machine learning model. This method describes the image characteristics of soil electrical conductivity at different geographical scales, providing a reference approach for the rapid and accurate prediction of soil electrical conductivity in arid regions. Full article

Biomass pyrolysis has emerged as a flexible platform for converting low-value residues into higher-value energy carriers (bio-oil, biochar and gas) and carbon-rich materials, with realistic potential for negative emissions when biochar is deployed in long-lived sinks. Over the last decade, three developments have driven the field forward: first, a finer mechanistic understanding of devolatilization and secondary reactions; second, major improvements in analytical techniques for characterising feedstocks and products; and third, more rigorous techno-economic and life-cycle assessments that place pyrolysis in a broader energy-system context. Recent experimental work on forestry and agro-industrial residues has clarified how biomass composition, ash chemistry and operating conditions jointly govern product yields, energy content and stability. Parallel advances in GC×GC–MS, high-resolution mass spectrometry, NMR and thermogravimetric methods have shifted the discussion from bulk “bio-oil” and “char” to families of molecules and well-defined structural domains, which can be deliberately targeted by reactor and catalyst design. Data-driven models, ranging from support vector machines applied to TGA curves to ANFIS and random forests for yield prediction, are now accurate enough to support process screening and multi-objective optimisation. At the system level, commercial fast pyrolysis biorefineries report overall useful energy efficiencies on the order of 80–86%, while slow pyrolysis configurations centred on biochar can be economically viable when carbon storage and co-products are appropriately valued. Thermodynamic analyses confirm that indirect gasification via fast-pyrolysis oil sacrifices some energy and exergy efficiency relative to direct solid-biomass gasification but may offer logistical and integration advantages. This review synthesises recent work on (i) feedstock and process characterisation; (ii) state-of-the-art analytical methods for bio-oil, biochar and gas; (iii) modelling and machine-learning tools; and (iv) energy-system deployment of pyrolysis products. Throughout, the emphasis is on how characterisation and modelling inform concrete design choices and on the trade-offs that arise when pyrolysis is considered as part of a wider decarbonisation portfolio. By integrating laboratory-scale characterisation with system-level modelling, this review aligns biomass pyrolysis with several United Nations Sustainable Development Goals (SDGs). The optimisation of thermochemical conversion pathways for forestry and agro-industrial residues directly supports SDG 7 (Affordable and Clean Energy) by enhancing the efficiency of bio-oil and syngas production. Furthermore, the deployment of biochar as a stable carbon sink for negative emissions and soil amendment addresses SDG 13 (Climate Action) and SDG 15 (Life on Land). By converting low-value waste streams into high-value energy carriers and chemicals within a circular bioeconomy framework, the research further contributes to SDG 12 (Responsible Consumption and Production) and SDG 9 (Industry, Innovation and Infrastructure). Full article

Wildfires are among the key drivers of transformation in boreal ecosystems; however, the mechanisms of postfire recovery in the arid regions of Eurasia remain insufficiently understood. The aim of this study was to identify the role of burn severity and associated edaphic and hydrological factors in shaping the natural regeneration trajectories of Scots pine forests in the Kostanay region of northern Kazakhstan. This study is based on the integration of field data on seedling regeneration and soil conditions with the analysis of long-term satellite-derived indices (NDVI, NDMI, and NBR). Sample plots were grouped according to fixed burn severity classes, which enabled a consistent statistical comparison and reduced the interpretative ambiguity that has characterized previous studies in the region. The results indicate that pine forest regeneration is most successful under low and moderate burn severity, where seed sources are preserved and favourable moisture conditions are maintained. In contrast, high burn severity leads to a reduction in regenerative potential and a shift in recovery trajectories toward deciduous or sparsely vegetated communities. The spectral indices derived from the remote sensing data strongly agreed with the field-based indicators, confirming their suitability for assessing postfire vegetation dynamics. Soil properties act as important modifying factors of recovery processes, particularly under conditions of limited water availability. These findings enhance the current understanding of postfire recovery mechanisms in the arid part of the boreal zone and highlight the need for differentiated management of postfire landscapes. The integration of field observations with remote sensing data provides a robust framework for monitoring and forecasting recovery processes under an increasingly intensified fire regime. Full article

Availability of phosphorus (P) is thought to limit bole growth in wet tropical forests, raising concern that removing P through repeated logging in P-limited stands may be unsustainable. Motivated by a study in Indonesia, we analyzed Olsen extractable and total soil P in the upper 10 cm in paired samples we collected under vs. near decaying boles of two contrasting species in a wet tropical forest in Puerto Rico. Guarea guidonia had higher wood and leaf P concentrations than Dacryodes excelsa. G. guidonia colonized valleys with higher soil P concentrations than ridge sites dominated by D. excelsa. We used two age cohorts of trees > 30 cm diameter, felled by hurricanes Hugo in 1989 (11 years old) and Georges in 1998 (1.5 years old), but soil P did not differ with age. Soil Olsen P concentrations were significantly higher under versus away from boles of both species. Paradoxically, augmentation of soil P was greater under boles of D. excelsa than G. guidonia despite having lower wood P. Soil % C and Olsen P were strongly positively correlated in D. excelsa but not in G. guidonia, suggesting that regulation of soil P-availability differs between ridges and valleys. Both soil C and P may be critical for maintaining soil fertility on ridges in a wet tropical forest. Our results are discussed in the context of prior experiments at our site, including two where bole growth increased with wood addition and/or decreased after removal of woody debris. These studies in Puerto Rico, together with others elsewhere, suggest that reduced forest productivity could potentially result from repeated logging of forest stands on ridges with low P-availability in humid tropical areas since decaying wood could directly and indirectly maintain P-availability in sites with low soil P-availability. We suggest several hypotheses on P-cycling in montane humid tropical forests that need further research to elucidate mechanisms controlling soil P-availability and identify sites where repeated logging is likely to be unsustainable. 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

Sustainable forest management is increasingly recognized as an important climate change mitigation strategy because forests capture and store large amounts of carbon. This study presents a regional framework that integrates LiDAR data, forest cartography, and Life Cycle Assessment (LCA) to quantify biomass-related carbon dynamics and greenhouse gas emissions associated with forest management operations. The methodology was applied to the Autonomous Community of La Rioja (Spain) for the period 2010–2016 using public LiDAR campaigns, the Forest Map of Spain, and inventory data for reforestation and logging operations. Results show that above-ground biomass increased from 4,537,956 t in 2010 to 7,092,890 t in 2016, which corresponds to an increase of 1,200,819 t C in above-ground carbon stock. A complementary first-order estimate based on IPCC default root/shoot ratios suggests that total living biomass carbon (above- plus below-ground) increased by approximately 1,495,269 t C during the same period. In parallel, LCA results indicate that logging has substantially higher operational impacts than reforestation, particularly in terms of global warming potential. Even under a conservative scenario in which part of the carbon removed through logging is returned to the atmosphere, the regional balance remains net negative in CO₂-equivalent terms, indicating a net sink over the analyzed period. However, the approach has important limitations, including the absence of independent field validation, stand-age stratification, and explicit soil-carbon accounting. 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

The uptake and accumulation of mercury (Hg) in rice poses a serious threat to food safety. Pot experiments are widely used to screen for low-Hg-accumulating cultivars, yet their reliability in predicting field performance remains uncertain. This study evaluated pot-based screening by (1) comparing Hg uptake in rice grown in freshly processed versus aged soil; (2) contrasting Hg accumulation in the same cultivars grown in pots versus at two field sites; and (3) isolating micro-environmental effects by burying pots in situ. A total of 22 rice cultivars were used during 2021–2023 in this study. Pot systems, regardless of soil treatment, failed to replicate field accumulation patterns, yielding significantly greater Hg concentrations in brown rice (up to 59.24 ng g⁻¹) than field conditions (maximum 32.33 ng g⁻¹). Cultivar rankings derived from pot experiments showed little or no correlation with field rankings, indicating that performance is not transferable across environments. Random forest analysis identified elevated soil temperature and reduced light intensity as key artificial factors driving overestimation in pots, explaining 15.68% (total Hg) and 21.65% (methylmercury) of the variation. We conclude that pot experiments—due to soil disturbance and altered microclimates—overestimate Hg accumulation potential and show limited predictive capacity under the tested conditions. Therefore, field validation across multiple sites and seasons is essential for accurate mercury risk assessment and region-specific cultivar recommendation. Full article

The neotropical genus Inga (Fabaceae) is a fast-growing tree component of tropical forests which plays crucial ecological and functional roles. However, its diversity patterns and the specific environmental drivers that structure its distribution in Andean landscapes remain insufficiently documented. This study aimed to quantify the diversity and distribution of Inga species in the province of Imbabura (4785 km²), northern Ecuador, while evaluating the influence of key environmental determinants. By integrating 52 field records along 321 km of exploration and 22 herbarium records (QCNE, MO, AAU, F, HUTN), the study analyzes the role of topographic variables (12.5 m resolution) and climate data (1 km² resolution). Seventeen species were recorded, almost tripling previous regional findings. The results demonstrate that species richness and occurrence are strongly structured by altitude, temperature, and soil properties as primary environmental drivers. Ten species showed narrow altitudinal ranges and limited thermal tolerance (<2 °C), indicating high habitat specialization, while I. densiflora and I. insignis exhibited broader niches. Edaphically, most species were associated with sandy loam soils, particularly Mollisols and Inceptisols developed from volcanic material. These findings indicate that climatic gradients and edaphic conditions act as the main environmental filters shaping Inga assemblages in heterogeneous montane landscapes. The observed high level of specialization suggests significant vulnerability to land-use change and highlights the need for habitat-specific conservation strategies in Andean forests. 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

Nitrogen addition significantly affects soil aggregate stability by altering the aggregate microenvironment. Although the ecological effects of nitrogen addition on soil aggregates have been extensively investigated, studies specifically focusing on the responses of soil aggregate stability in Larix olgensis forest understories remain scarce. The effects of different forms of nitrogen addition (urea (CO(NH₂)₂), ammonium chloride (NH₄Cl), and sodium nitrate (NaNO₃)) were investigated at 20 kg N·ha⁻¹·yr⁻¹ across all treatments, and the physicochemical properties, stability, and microbial community composition of soil aggregates were determined to analyze soil aggregate stability. NaNO₃ significantly increased soil nutrient contents, promoted the formation of macroaggregates, and significantly enhanced soil aggregate stability. NH₄Cl significantly decreased bacterial diversity in microaggregates, while NaNO₃ significantly elevated fungal diversity in macroaggregates. CO(NH₂)₂ and NH₄Cl increased the relative abundances of Ascomycota and Proteobacteria in microaggregates, whereas NaNO₃ elevated the relative abundances of Mortierellomycota and Gemmatimonadetes in soil aggregates of all particle sizes. These results indicated that NaNO₃ was more effective in improving soil aggregate stability and exerted regulatory effects on microbial community structure compared to the other nitrogen forms. These findings can provide a theoretical basis for an in-depth understanding of the microecological processes of forest soil aggregates under the context of nitrogen deposition. Full article