Search Results (69)

Vegetation dynamics are key indicators of climate change and ecological risk in cold regions. This study investigated vegetation–climate interactions in Heilongjiang Province, China, using an integrated analytical framework that combined the Mann–Kendall test, Pettitt test, Hurst exponent, Continuous Wavelet Transform, and Wavelet Transform Coherence with the Normalized Difference Vegetation Index and meteorological data from 1990 to 2024. The dominant vegetation comprises cold–temperate coniferous forests, mixed broadleaf–conifer forests, meadow steppes, and croplands. Results showed that (1) the climate system experienced asynchronous abrupt changes, with potential evapotranspiration, precipitation, and temperature changing in 2008, 2011, and 2013, respectively. Accordingly, the Normalized Difference Vegetation Index reversed in 2011, with greening rates in the range of 0.009–0.022 yr⁻¹ in the northwestern and central regions and browning rates in the range of −0.010 to −0.025 yr⁻¹ in the southwestern and eastern regions. (2) The Hurst exponent ranged from 0.23 to 0.48 for temperature and potential evapotranspiration, indicating strong anti-persistence and high future ecological vulnerability. (3) Wavelet coherence analysis identified precipitation as the dominant climatic driver at 6–9-year scales, whereas temperature shifted from a short-term positive driver to a long-term stressor, and potential evapotranspiration mainly regulated vegetation at 5–8-year scales. These findings provide scientific support for ecological risk assessment and climate-resilient cold regions engineering. Full article

Chinese fir (Cunninghamia lanceolata) is one of the most important fast-growing timber species in southern China and plays a critical role in regional carbon sequestration and timber production. Soil organic carbon (SOC) is a key component of the terrestrial ecosystem carbon pool, and its content, composition, and stability directly affect soil fertility, ecosystem service functions, and the ability to cope with climate change. This review summarizes the mechanisms by which density regulation and conifer–broadleaf mixed forest management affect the content, fractions and stability of SOC in Chinese fir plantations. Density regulation changes stand structure, litterfall, and roots, which can impact soil microbial activity, litter decomposition, and mineralization of soil organic matter. Conifer–broadleaf mixed planting and broader mixed-forest reconstruction, through introducing functionally distinct tree species, can optimize stand microenvironments, increase species diversity, improve litter quantity and quality, and diversify root exudates. These changes further regulate soil organic carbon (SOC) accumulation and its physicochemical stability. Based on the latest literature reports, we demonstrate that mixed-species stands with a moderate broadleaf proportion significantly enhance SOC sequestration relative to pure stands, driven by improved litter quality and soil pH neutralization that promote microbial necromass formation and aggregate-associated carbon stabilization. Optimal density regulation complements these benefits by facilitating understory development and root carbon input. Current research indicates that both density reduction and species mixing, as two independent silvicultural measures, can individually enhance soil organic carbon (SOC) stability in Chinese fir plantations. This review identifies key research gaps and provides theoretical foundations for carbon-oriented sustainable management of Chinese fir plantations. Full article

Individual tree crown (ITC) segmentation in structurally complex mixed forests remains challenging under limited annotation, uneven effective height-structure support, and severe inter-crown adhesion. Existing end-to-end instance segmentation methods often require substantial instance-level annotation, and their cross-domain transferability can degrade when applied to plots with different forest structures. This study proposes a probabilistic prior-constrained instance reconstruction framework that treats semantic segmentation output as an interpretable canopy prior and reconstructs object-level crowns through a structured post-processing pipeline. A height-aware canopy support mask (HCSM) converts the probability field into a credible operational domain through hysteresis thresholding, morphological reconstruction, and a height constraint. Constrained recovery within the support domain (E2GROW) repairs coverage deficiency through spatially bounded boundary adjustment with guard rails on area ratio and buffer distance. Selective splitting then addresses residual merge errors through branch-specific seed-guided partitioning, including an aggressive Voronoi reference branch and a more conservative LOCAL/marker-controlled watershed branch with explicit trigger and child-object filtering criteria. An instance-level evaluation loop based on Gate-3 Recall, a precision proxy, and threshold-crossing audits is used during module development as an iterative safeguard. On a single 500 × 500 m mixed conifer–broadleaf plot with 306 reference crowns retained for evaluation, the high-Recall VORv1 branch improves Recall from 0.369 to 0.673 over the internal R2 baseline produced by the semantic-prior-to-instance initialization procedure, whereas the balanced E2GROW configuration achieves the highest F1_proxy with fewer predicted objects; the overall gain originates from two distinct mechanisms: threshold-crossing boundary recovery for coverage-deficient crowns and local structural decomposition for merged crown groups. Sensitivity analysis indicates that the support-domain construction is stable across the explored parameter ranges, and that the two splitting branches realize a structural Recall–precision trade-off with no evidence of simple additive gains. The framework is modular and auditable, and its demonstrated applicability is strongest for annotation-scarce closed-canopy plots where a usable semantic canopy prior and height information are available. The reported evidence represents a single-site, within-plot methodological demonstration. Full article

Forest soils serve as critical terrestrial carbon sinks. While broad hydrothermal controls on soil respiration (R_s) are established, uncertainties persist regarding high-frequency temporal dynamics and moisture-dependent variations in temperature sensitivity (Q₁₀). Specifically, conventional reliance on discrete, clear-day sampling obscures how precipitation disrupts diurnal patterns. To address this, we continuously monitored R_s and environmental factors in two Northeast Chinese mixed forests (Korean pine, Pinus koraiensis (KP), and Dahurian larch, Larix gmelinii (DL)) to quantify weather-driven daily dynamics and carbon fluxes. Precipitation primarily drove daily variability, but more importantly, it reshaped day–night asymmetry. Under clear-day conditions, R_s exhibited a consistent daytime-dominant pattern, with daytime fluxes being significantly higher than nighttime fluxes (p < 0.05). However, precipitation events fundamentally neutralized this asymmetry, resulting in no significant day–night differences across most phenological stages. Annual R_s effluxes (759 and 965 g C m⁻² yr⁻¹ for KP and DL, respectively) lacked significant inter-stand or temporal variations. Seasonal emissions peaked unimodally in July, with the non-growing season contributing merely 5%–8%. Notably, spring freeze–thaw R_s in the KP stand surged interannually by 143%. While R_s correlated positively with temperature (p < 0.001), Q₁₀ was co-regulated by forest stand and moisture. Under moderate moisture, the KP stand’s Q₁₀ (2.72) was significantly lower than the DL stand’s (3.81); however, this divergence neutralized under low moisture. Consequently, soil moisture acts as both a direct R_s driver and a fundamental regulator of its temperature sensitivity. These empirical findings provide critical data to calibrate forest carbon models, improving predictions of soil carbon feedbacks under future climate scenarios. Full article

Accurate estimation of forest aboveground biomass (AGB) is pivotal for assessing forest carbon sequestration and informing global change studies. Conventional LiDAR-based AGB estimation approaches primarily rely on height and density metrics, which inadequately characterize the complex three-dimensional (3D) structure of forest canopies. This study developed and evaluated a novel method utilizing voxel-based 3D canopy structural metrics derived from airborne LiDAR (ALS) to improve AGB estimation accuracy across diverse forest types. First, voxel-based metrics (Voxel Canopy Height Model (VCHM), canopy volume, and canopy surface area) were extracted from voxelized point clouds. Their distribution patterns across five forest types (Pinus massoniana, Cunninghamia lanceolata, coniferous, broadleaf, and mixed conifer–broadleaf forests) and their correlations with AGB were systematically examined. The results revealed distinct 3D canopy architectures among forest types, with all three voxel metrics showing highly significant positive correlations with AGB; VCHM demonstrated the strongest association. We then constructed two Random Forest models: a baseline model using traditional metrics only, and an enhanced model integrating both traditional and voxel-based metrics. The 10-fold cross-validation indicated that the model incorporating voxel metrics achieved markedly higher accuracy (R² in 0.490–0.684) than the traditional model (R² in 0.480–0.607), representing a relative improvement of 2.1% to 32.7%. The most substantial gain occurred in structurally complex broadleaf forests. The enhanced model was subsequently applied to generate a wall-to-wall AGB map of the study region, yielding a total estimated AGB stock of 8.36 × 10⁶ t, which exhibited a patchy spatial distribution. Pinus massoniana forests accounted for the largest proportion (57.8%) of the total stock. This study demonstrates that voxel-based 3D canopy metrics can more effectively capture forest structural heterogeneity and substantially improve the accuracy of AGB estimation models, particularly for complex forest stands. The findings provide a significant advancement toward precise, stand-scale forest biomass monitoring founded on detailed 3D structural information. Full article

Plant diversity plays a fundamental role in ecosystem functioning and is essential for sustaining ecosystem services. National forest inventories are key instruments for assessing floristic diversity. However, their measurement protocols may introduce bias by omitting smaller individuals because of the stem diameter criterion used or the minimum plant size threshold applied. Such bias is exacerbated in dryland ecosystems where small-statured plants with low-branching stems are particularly abundant. In this study, we evaluated the effects of using basal diameter (BD) instead of diameter at breast height, and of sampling small individuals (BD ≥ 2.5 cm), on the estimation of abundance, alpha and gamma diversity and community composition in different vegetation types in NW Mexico. We found substantial underestimation due to the omission of smaller individuals in xeric shrubland and tropical dry forest, where gamma diversity may be underestimated by up to 209% and 139%, respectively. Broadleaf forest also showed strong underestimation (133%), whereas mixed conifer–broadleaf forests were unaffected. We discuss these differential effects and propose a methodology to attenuate this underestimation and achieve more accurate floristic diversity estimates from national forest inventories in dryland vegetation, which encompasses roughly one-third of the Earth’s surface and more than half of Mexico’s territory. Full article

In this study, pristine biochar (BC1) and magnesium-modified biochar (BC2) were prepared from corn straw. Different nitrogen deposition intensities (0, 8, 30, and 50 kg N/(ha·yr)) were simulated by adding NH₄NO₃ solution. A laboratory incubation experiment was conducted to investigate the effects of biochar addition and N deposition on CO₂ emissions, CH₄ uptake, and microbial community structure in soils from a temperate mixed conifer–broadleaf forest. The results showed that BC1 significantly increased cumulative CO₂ emissions (p < 0.05), while no significant difference was observed between BC2 and the control. N deposition had no significant effect on CO₂ emissions. Biochar addition significantly promoted cumulative CH₄ uptake (p < 0.05), with BC2 exhibiting a stronger promoting effect than BC1. In contrast, N deposition significantly inhibited CH₄ uptake (p < 0.05) in a dose-dependent manner. Spearman’s correlation analysis revealed that cumulative CO₂ emissions were significantly or highly significantly negatively correlated with the relative abundances of Elusimicrobiota, Actinomycetota, Chloroflexota, Planctomycetota, Acidibacter, Bacillus, Paenibacillus, Acidothermus, and Mycobacterium, and significantly positively correlated with Bacteroidota, Bdellovibrionota, Pseudomonadota, Devosia, and Mesorhizobium. Cumulative CH₄ uptake was highly significantly positively correlated with the relative abundance of Bacteroidota and significantly negatively correlated with Chloroflexota, Candidatus_Eremiobacterota, and Mycobacterium. These findings demonstrate that N deposition has no significant impact on soil CO₂ emissions but significantly inhibits CH₄ uptake, while magnesium-modified corn straw biochar promotes CH₄ uptake without substantially increasing CO₂ emissions, highlighting its promising application potential. Full article

Establishing mixed conifer–broadleaf forests enhances soil multi-nutrient cycling (SMC), yet the underlying mechanisms, particularly the role of rhizosphere microbial communities, remain poorly understood. This study investigated how bacterial and fungal communities in the rhizosphere soil of Larix olgensis drive SMC in both pure and mixed plantations with Fraxinus mandshurica, elucidating the microbial pathways for nutrient supply in mixed stands. Our results indicated that SMC in the L. olgensis rhizosphere soil was significantly greater in mixed stands (0.43) than in pure stands (−0.51). Tree species mixing significantly enhanced microbial diversity, increased the stochasticity of community assembly, and reduced dispersal limitation. Cross-kingdom (bacteria–fungi) co-occurrence networks in mixed stands showed a 19.7% increase in positive correlations, indicating stronger microbial cooperation. Random forest analysis identified microbial diversity, network complexity, and bacterial assembly processes as the main predictors of SMC. Structural equation modeling indicated that microbial diversity indirectly promoted SMC via increased network complexity, while bacterial assembly processes directly influenced SMC. These findings demonstrate that mixed conifer–broadleaf plantations improve soil microbial functioning and nutrient cycling by modifying microbial diversity, assembly processes, and interaction networks. Full article

Alpine forests are key regulators of soil biogeochemical cycles, yet the extent to which forest type constrains soil microbial diversity and soil quality in high-elevation regions remains insufficiently resolved. Here, we assessed how contrasting alpine forest types influence the taxonomic composition and diversity of soil microbial communities, identified the dominant environmental drivers, and evaluated soil quality along the southern slope of the Qilian Mountains. Six forest types were examined, including four monospecific stands (Picea crassifolia, QQ; Betula spp., HS; Juniperus przewalskii, YB; and Pinus tabuliformis, YS) and two mixed formations (mixed conifer–broadleaf, ZKHJ; and mixed broadleaved, KKHJ). Bacterial and fungal communities were characterized using Illumina high-throughput sequencing, while structural equation modeling (SEM) was used to identify primary drivers of diversity and principal component analysis (PCA) was applied to construct the minimum data set (MDS) for soil quality evaluation. Mixed forests consistently exhibited higher bacterial and fungal alpha diversity than pure stands. Environmental gradients were the strongest positive drivers of microbial diversity, whereas soil chemical properties and vegetation-related biotic factors exerted partially negative effects. Soil quality index (SQI) values ranked as follows: KKHJ (0.55) > ZKHJ (0.49) > YB (0.48) > HS (0.46) > YS (0.44) > QQ (0.43). The mixed broadleaved forest reached Grade IV (upper-intermediate level) soil quality, whereas the other forest types were classified as Grade III (intermediate). Mixed forests showed stronger capacities for organic matter accumulation and nutrient retention. These findings indicate that promoting mixed forest stands is critical for improving soil structure, nutrient retention, and microbial diversity in this alpine region. Accordingly, forest management should prioritize the development of mixed forests to enhance overall soil quality. Full article

Broad-scale assessments often track forest productivity, yet they rarely quantify how soil conditions determine whether these gains persist as long-lived carbon and generate measurable economic value. This study focused on Northeast China, where forests include boreal coniferous stands dominated by Dahurian larch, temperate conifer–broadleaf mixed forests with Korean pine, and temperate deciduous broadleaf forests dominated by Mongolian oak. We combined GLASS net primary productivity and ESA CCI Land Cover to delineate forest pixels, used 2000 to 2005 as the baseline, and converted productivity anomalies into pixel level carbon economic value using a consistent pricing rule. Forest NPP increased significantly during 2000 to 2018 (slope = 1.57, p = 0.019), and carbon economic value also increased over time during 2006 to 2018 (slope = 2.24, p = 0.002), with the highest values in core mountain forests and lower values in the western forest–grassland transition zone. Correlation analysis, explainable random forests, and variance partitioning characterized spatial and temporal dynamics from 2000 to 2018 and identified environmental controls. Carbon value increased over time and showed marked spatial heterogeneity that mirrored productivity patterns in core mountain forests. Climate was the dominant predictor of value, while higher soil pH and clay content were negatively associated with value. The random forest model explained about 70% of the variance in carbon value (R² = 0.695), and variance partitioning indicated substantial unique and joint contributions from climate and soil alongside secondary topographic effects. The automatable framework enables periodic updates with new satellite composites, supports ecological compensation zoning, and informs soil-oriented interventions that enhance the monetized value of forest carbon sinks in data-limited regions. Full article

Northeast British Columbia (54–60° N latitude, 120–123° W longitude) has 10+ M ha of complex conifer–broadleaf forest, which is a unique forest type in the province. Current management practice is to remove competing broadleaf species to promote the growth of more commercially valued conifers. This approach ignores the species silvics and results in forest simplification, thus reducing species and structural diversity, habitat value, and overall stand resilience to future events such as climate change and wildfires. These practices also negatively impact traditional First Nation treaty rights. Three trials were established across the region in 5-to-18-year-old post-logging mixed species stands where broadleaves had not been removed. Competition-free radii of 0, 1, 2, and 4 m were established around white spruce (Picea glauca (Moench) Voss) crop trees. The objective was to investigate the impact of broadleaf (aspen Populus tremuloides Michx. or paper birch Betula papyrifera Marsh.) competition on crop tree growth with respect to the free-to-grow (FTG) standard. Except at extreme broadleaf densities (>10,000 SPH), crop tree DBH growth was not impacted when trials were established. After at least 11 growing seasons, except at the competition-free 4 m radius, DBH was not impacted by competition. Spruce DBH in the mixed stand at all radii was greater than the expected BC model projections for a pure spruce stand on these sites. Our findings suggest that the current FTG management approach in northeast BC only has a positive result if taken to an extreme. It has a low return on investment and reduces stand resilience and total productivity. An alternative forest management approach for the region is presented. Full article

Semi-humid subtropical montane regions face the dual pressures of climate change and water scarcity, making it essential to understand how soil carbon–water coupling varies among forest types. Focusing on seven representative forest types in the central Yunnan Plateau, this study analyzes the spatial distribution, trade-offs, and drivers of soil organic carbon storage (SOCS) and soil water storage (SWS) within the 0–60 cm soil layer, using sloping rainfed farmland (SRF) as a reference. We hypothesize that, relative to SRF, both SOCS and SWS increase across forest types; however, the direction and strength of the SOCS–SWS trade-off differ among plant communities and are regulated by litter traits and soil structural properties. The results show that SOCS in all forest types exceeded that in SRF, whereas a significant increase in SWS occurred only in ACF. Broadleaf stands were particularly prominent: SOCS rose most in the 23 yr SF and the 20 yr ACF (274.44% and 256.48%, respectively), far exceeding the 9–60 yr P. yunnanensis stands (44.01%–105.32%). Carbon–water trade-offs varied by forest type and depth. In conifer stands, SWS gains outweighed SOCS and trade-off intensity increased with stand age (RMSD from 0.48 to 0.53). In broadleaf stands, SOCS gains were larger, with RMSD ranging from 0.21 to 0.45 and the weakest trade-off in SF. Across depths, SOCS gains exceeded SWS in 0–20 cm, whereas SWS gains dominated in 40–60 cm. Regression analyses indicated a significant negative SOCS–SWS relationship in conifer stands and a significant positive relationship in 0–20 cm soils (both p < 0.05), with no significant correlations in other forest types or depths (p > 0.05). Correlation results further suggest that organic matter inputs, N availability, and soil physical structure jointly regulate carbon–water trade-off intensity across forest types and soil depths. We therefore recommend prioritizing native zonal broadleaf species, as well as protecting SF and establishing mixed conifer–broadleaf stands, to achieve synergistic improvements in SOCS and SWS. Full article

Clarifying the role of density regulation in different stand types of Chinese fir (Cunninghamia lanceolata) is beneficial for sustainable management. Stand density management diagrams (SDMDs) can help in simulating thinning, regulating stand structure, and balancing timber yield. This study, conducted in Ganzhou City, a mid-subtropical region of China, used second-class forest resource survey plots dominated by Chinese fir, including 541 Chinese fir pure stands, 232 Chinese fir-conifer mixed stands, and 351 Chinese fir-broadleaf mixed stands. Equations for self-thinning, dominant height, and stand volume were constructed, and the SDMDs were subsequently developed to simulate two management scenarios: self-thinning and thinning. The results indicate that self-thinning relationships differ among Chinese fir stand types and that appropriate thinning can improve stand growth. Mixed stands, particularly Chinese fir–broadleaf mixed stands, showed greater growth potential at later stages, highlighting the role of species mixing in reducing competition and enhancing resource-use efficiency. The SDMDs developed in this study provide a practical tool for density regulation and silvicultural planning in Chinese fir plantations. However, being based on regional-scale growth models, the results mainly reflect regional conditions and should be further validated with long-term experiments. Full article

Global climate change is driving profound transformations in forest ecosystems, particularly in monsoon-influenced regions of the Pacific coast of Asia, such as the Sikhote-Alin Mountains. Long-lived conifer species, notably Korean pine (Pinus koraiensis Siebold & Zucc.), play a central ecological role in mixed broadleaf–coniferous forests of the region. We examined how the radial growth response of Korean pine to climatic variability changes with tree age and ontogenetic stage, using 191 increment cores from trees ranging from early virginile to old generative stages. We employed two approaches: (i) a stage-based analysis, constructing tree-ring chronologies for each ontogenetic stage; (ii) an individual-tree analysis, applying correlation and regression directly to individual ring-width series. Climate–growth relationships were assessed using monthly temperature, precipitation, and drought indices (PDSI, SPEI). For the stage-based approach, radial growth was positively correlated with the mean August temperature of the previous year (up to r = 0.61), minimum November temperature (up to r = 0.50), and summer drought indices (up to r = 0.57). Age-related trends in climate sensitivity, assessed from regression models under both approaches, were significant for 9 of the 18 monthly climate variables examined. For stage-specific chronologies, simple regressions across six ontogenetic stages described up to 98% of the variance, whereas cambial-age-based relationships were much weaker (R² = 0.03–0.14). These findings highlight the importance of accounting for ontogenetic structure in dendroclimatic analyses and climate reconstructions. Such insights are critical for understanding long-term forest dynamics and informing climate adaptation strategies in Korean pine-dominated ecosystems. Full article

Urban trees play a crucial role in regulating hydrological processes within urban ecosystems by intercepting rainfall to effectively reduce surface runoff and mitigate urban flooding. Current research lacks a systematic quantification of rainfall interception capacity and its community-level impacts at the urban scale. This study adopts a city-scale perspective, integrating field survey data with the i-Tree Eco model to systematically explore the contributions of 20 factors to the average annual rainfall interception of tree species and the average annual rainfall interception efficiency of communities. The study revealed that Deciduous broadleaf trees (1.28 m³ year⁻¹) and Pure coniferous forests (90.7 mm year⁻¹) exhibited substantial rainfall interception capacity. Relative Height, Average Tree Height, Average Crown Width, and Planting Density of trees significantly influence interception capacity. Urban planning can optimize the selection of tree species (e.g., Paulownia, Populus tomentosa, etc.) and community structure (e.g., mixed planting of conifers and deciduous broadleaf trees) to improve rainfall interception capacity, thereby effectively reducing stormwater runoff, mitigating the risk of urban flooding. These findings provide a scientific basis for designing urban vegetation to mitigate flooding, support water management, and advance sponge city development. Full article