Search Results (77)

Sustainable forest management requires inventory workflows that provide spatially explicit structural information while retaining field-based calibration and uncertainty control. This case study evaluated a field-calibrated UAV LiDAR workflow for individual-tree inventory in middle-aged and near-mature larch plantations in Chuanying District, Jilin City, China. UAV laser scanning point-clouds were integrated with six 30 m × 30 m field plots to assess three individual-tree extraction algorithms: point-cloud segmentation (PCS), marker-controlled region growing (MCRG), and region-based hierarchical cross-section analysis (RHCSA). Algorithm performance was evaluated using plot-level recall, precision, F-score, localization RMSE, tree-height and crown-width accuracy, bootstrap confidence intervals, exploratory Wilcoxon signed-rank comparisons, and leave-one-plot-out stability checks. MCRG provided the most balanced numerical performance under the tested configuration, with a mean F-score of 0.845, compared with 0.808 for PCS and 0.827 for RHCSA. However, the MCRG-RHCSA paired difference was not robust across the six plots, and the analysis should be interpreted as a dataset-specific workflow comparison rather than a universal algorithm ranking. Tree height was estimated with comparatively high accuracy, whereas crown-width estimation remained weak, indicating that vertical canopy structure was more reliable than lateral crown delineation. After calibration assessment, the workflow was applied to 157.47 ha of UAV LiDAR survey areas and generated 219,996 algorithm-based detections. These outputs are best interpreted as a spatial decision-support layer for compartment updating, density screening, and field-inspection prioritization, not as an independently verified wall-to-wall stem census. Full article

This study conducts a multi-objective optimization of an impact pruner for coniferous plantation trees, using Prince Rupprecht’s larch (Larix principis-rupprechtii Mayr) in North China as a case study. The objective is to establish an impact cutting mechanics model and to construct an impact cutting platform. This study utilizes the Box–Behnken principle, with the cutting speed (v), cutter wedge angle (β), and cutting clearance (L) as influencing factors and the cutting energy consumption (Y₁), total equipment energy consumption (Y₂), and specific cutting area (S) as evaluation indexes. The cutting parameters were optimized using a mathematical model for multi-objective optimization. The experimental results indicate that the factors influencing target Y₁ were ranked as β, L, and v, while the factors influencing target Y₂ were ranked as β, v, and L, and the factors influencing target S were ranked as L, β, and v. Field tests demonstrated that the optimization reduced the cutting energy consumption by up to 16.90% and improved the cutting quality by up to 19.28%. These gains directly translate to improved operational efficiency and economic value in forestry management. The optimal parameters corresponding to these improvements are v = 2.15 m·s⁻¹, β = 20°, and L = 5 mm, resulting in Y₁ = 36.10 J, Y₂ = 3351.01 J, and S = 3.45. These results demonstrate the feasibility and efficiency of the impact pruning method for Larix principis-rupprechtii in coniferous plantation forests. By combing mechanism analysis with multi-objective optimization, this study proposes a solution that can improve the pruning quality of coniferous plantation trees, reduce the energy consumption of impact pruning machines, enhance tree health, and serve as a measure to prevent pests and diseases, contributing to the advancement of artificial forest plant protection technology. Full article

Grain for Green, as an important ecological restoration method, profoundly affects soil nitrogen (N) cycling by altering the soil physicochemical properties and microbial community. Soil nitrogen mineralization is a key process in the terrestrial N cycle. However, the dynamics and underlying driving mechanisms of soil N mineralization rate (Rmin) that respond to afforestation remain unclear. In this study, we selected a typical afforestation sequence in Northeast China, including farmland (F), 21-year-old larch plantation (L21), 42-year-old larch plantation (L42), and natural larch forest (NL). The soil Rmin, associated soil physicochemical properties, and microbial community characteristics were determined to explore the effects of afforestation on soil Rmin and its potential mechanisms of action. The results suggested that soil Rmin was ranked in the order of L42 (0.41 mg kg⁻¹ d⁻¹) > F (0.39 mg kg⁻¹ d⁻¹) > L21 (0.23 mg kg⁻¹ d⁻¹) (p < 0.05) along the afforestation sequence, with no significant difference between L42 and F. Compared to the L42, the NL exhibited significantly lower soil Rmin (0.23 mg kg⁻¹ d⁻¹) (p < 0.05). The changes in soil Rmin during the afforestation were significantly positively related to soil total N (TN) and organic carbon (SOC) concentrations, but significantly negatively related to pH (p < 0.05). Furthermore, the abundances of Proteobacteria and Acidobacteria (bacteria) and Ascomycota (fungi) were also closely correlated with soil Rmin. Structural equation modeling (SEM) analysis further indicated that the afforestation mainly regulated soil Rmin by altering soil temperature (ST) and NH₄⁺-N content. Meanwhile, soil NH₄⁺-N content could also exert a significantly positive effect on soil Rmin by influencing the microbial community. In conclusion, afforestation effectively altered soil Rmin, which was even higher in the plantation than in natural forests. This finding further enhances our understanding of forest restoration and land management practices on soil N cycling in temperate regions. Full article

Climate change is intensifying drought stress in temperate forests, yet the mechanisms governing gradual versus threshold responses remain unclear, limiting adaptive management. This study tested whether tree morphological traits can help detect these response patterns and whether they vary with species identity, drought timescale, and stand structure. Using 2026 plot records (1022 larch, Larix principis-rupprechtii Mayr; 1004 Chinese pine, Pinus tabuliformis Carrière) from plantations across northern China, we combined random forest and generalized additive models to evaluate the height-to-diameter (H/D) ratio as a drought indicator. The H/D ratio outperforms height or diameter alone in detecting drought responses. Two distinct nonlinear strategies were identified: larch exhibited high sensitivity to spring drought with a threshold near SPEI ≈ −0.47, while Chinese pine showed resilience to short-term stress but nonlinear responses to cumulative drought (thresholds 0.07–0.12). These differences align with biomass allocation patterns, with Chinese pine maintaining lower H/D ratios. Stand structure significantly influenced responses, with strong Age × Density × Drought interactions (p < 0.001) highlighting vulnerability in young, dense stands. Overall, the H/D ratio provides a candidate early-warning indicator of drought vulnerability and may support species-specific monitoring and risk screening in young, high-density stands, although experimental validation is still needed. Full article

Soil preferential flow plays a crucial role in governing hydrological cycles and soil moisture distribution in mountain forests. This makes it essential for understanding subsurface water movement and for guiding hillslope hydrological management. In this study, soil preferential flow, soil properties, and root characteristics across three slope positions on a Larix gmelinii var. principis-rupprechtii (Mayr) Pilger (larch) plantation hillslope in the Liupan Mountains were systematically observed to reveal the spatial patterns and formation mechanisms of hillslope soil preferential flow. The results showed that soil preferential flow development followed a distinct spatial pattern across the slope positions, with the mid-slope exhibiting the most developed preferential flow characteristics. The comprehensive preferential flow index further quantified this spatial variation, ranking the slope positions as mid-slope > upper slope > lower slope. Different soil structural properties exerted varying influences on preferential flow. Macropore-related properties (low bulk density and high porosity and saturated conductivity) promoted most preferential flow, whereas aggregate-related properties (high organic matter and water-stable aggregates) suppressed it. The influence of root characteristics on preferential flow was also dual. Root length density generally promoted preferential flow (e.g., DC, LI, and UniFr), whereas root surface area density primarily exerted an inhibitory effect (e.g., LI, UniFr, and total stained area TotStAr). This study clarifies how slope position modulates preferential flow through soil and root characteristics, offering insights for slope-specific hydrological understanding and targeted soil and water conservation practices. Full article

Increasing the carbon sink function of forests is critical for achieving carbon (C) neutrality in the context of global climate change. Past studies have focused on the estimation of forest biomass or C storage, while those on forest C sink potential remain limited. In particular, there remain few systematic investigations to define the forest C sink, to characterize the synergistic influencing factors, and to develop related quantitative analysis methods. The development of scientific C enhancement strategies requires the construction of C density-age models integrating multiple stand factors. These models allow accurate quantification of the gap (∆C) between actual and maximum C sequestration capacity. This study used permanent sample plot data to develop and validate a novel multi-model assessment approach for quantifying the C sink potential of Larix olgensis plantations in Heilongjiang Province, China, and to translate the results into precise management tools. An Average-Level Model (ALM) was established to define baseline C sequestration. Three innovative potential assessment models were then proposed: (1) the Empirical Upper Boundary Model (PLM1); (2) the Dummy Variable Model (PLM2); and (3) the Quantile Regression Model (PLM3). These models define the maximum C sequestration capacity from distinct perspectives. PLM1 (R² = 0.7910) characterized the theoretical upper limit of C sink potential (79.86 Mg·ha⁻¹), making it suitable for macro-strategic goal setting, though it is somewhat dependent on extreme data points. PLM2 (R² = 0.7943) achieved the best fit, and when combined with measurable stand conditions (site class index [SCI] > 16 m, stand density index [SDI] > 800 trees·ha⁻¹), it provides clear guidance for management practices. Although PLM3 showed a lower goodness-of-fit (R² = 0.1056), it provided reasonable parameter estimates and robust predictions, offering a reliable upper-bound reference for C sink project planning and risk control. At a stand age of 60 years (yr), the C sink enhancement potentials (“∆” C) corresponding to the three models were 15.73, 14.48, and 13.26 Mg·ha⁻¹, representing increases of 24.53%, 22.58%, and 20.68%, respectively, over the average level (64.13 Mg·ha⁻¹); the peak C sequestration rates of the models were 104.3%, 82.7%, and 60.5% higher than that of the ALM, with peak times occurring earlier at 9, 7, and 11 yr, respectively, underscoring the importance of the early management. The multi-model assessment approach developed here facilitates “precision carbon enhancement” by quantifying C sink potential across its theoretical, achievable, and robust upper-bound dimensions. This quantification provides both mechanistic insights into C sequestration processes and a critical link between theoretical understanding and practical forest management. This work holds significant value for advancing forestry C sinks in service of national strategies. Full article

Woody debris decomposition is a key process in forest ecosystem material cycles, with invertebrate communities playing a vital role. Distinct physicochemical properties of woody debris types lead to varying effects on these communities. Taking woody debris in Saihanba’s Larix principis-rupprechtii plantations, Betula platyphylla natural secondary forests, and larch–birch mixed forests (northern China) as objects, we collected woody debris-inhabiting invertebrates via hand-sorting. We studied how tree species (larch/birch), forest types (pure/mixed), and decay stages (I–V) collectively regulate invertebrate community assembly. Results showed significant differences in woody debris physicochemical properties across these factors. Phytophagous groups dominated early decay stages (I–III) and decreased significantly (p < 0.05) with reduced wood density. In contrast, saprophagous and predatory groups increased with decay, correlated with higher TN and were more abundant in mixed than pure forests. NMDS indicated significant community differences among tree species/forest types in early decay, converging later. PLS-PM further confirmed functional groups’ response pathways to woody debris characteristics. Thus, preserving woody debris integrity and diversity in plantations is crucial for maintaining invertebrate diversity, promoting nutrient cycling, and enhancing forest ecosystem functions. Full article

Accurate estimation of individual tree aboveground biomass (AGB) is essential for understanding forest carbon dynamics, optimizing resource management, and addressing climate change. Conventional methods rely on destructive sampling, whereas unmanned aerial vehicle (UAV) remote sensing provides a non-destructive alternative. In this study, spectral indices, textural features, and canopy height attributes were extracted from high-resolution UAV optical imagery and Light Detection And Ranging (LiDAR) point clouds. We developed an improved YOLOv8 model (NB-YOLOv8), incorporating Neural Architecture Manipulation (NAM) attention and a Bidirectional Feature Pyramid Network (BiFPN), for individual tree detection. Combined with a random forest algorithm, this hybrid framework enabled accurate biomass estimation of Chinese fir, Chinese pine, and larch plantations. NB-YOLOv8 achieved superior detection performance, with 92.3% precision and 90.6% recall, outperforming the original YOLOv8 by 4.8% and 4.2%, and the watershed algorithm by 12.4% and 11.7%, respectively. The integrated model produced reliable tree-level AGB predictions (R² = 0.65–0.76). SHapley Additive exPlanation (SHAP) analysis further revealed that local feature contributions often diverged from global rankings, underscoring the importance of interpretable modeling. These results demonstrate the effectiveness of combining deep learning and machine learning for tree-level AGB estimation, and highlight the potential of multi-source UAV remote sensing to support large-scale, fine-resolution forest carbon monitoring and management. Full article

The ecological restoration process of larch plantations to mixed forests contributes to enhancing the stability and functionality of forest ecosystems, with soil microbes playing a crucial role in this process. To elucidate the changes in soil microbial communities during this transition and their relationships with soil and litter properties, the study used 16S/ITS rRNA high-throughput sequencing to investigate the diversity and composition of soil bacterial and fungal communities at two soil depths across four restoration stages, and further quantified the relative contributions of soil and litter properties to variations in microbial community structure. The results indicated that bacterial and fungal $\mathsf{\alpha }$-diversity remained relatively stable in the topsoil but varied significantly across restoration stages in the subsoil ($p<0.05$), with the highest levels observed during the broadleaf species invasion stage. Fungal community structure demonstrated greater sensitivity to the restoration process, whereas bacterial communities showed stronger spatial dependency. Variance partitioning analysis revealed that soil properties were the main contributors to the variations of bacterial and fungal communities, accounting for 41% and 28% of the total variance, respectively. Fungal communities were more closely associated with litter properties than bacterial communities. Redundancy analysis combined with hierarchical partitioning further revealed that soil available phosphorus (AP) and total nitrogen (TN) were key factors explaining the variation in both bacterial and fungal communities. Additionally, litter total nitrogen (LTN) also emerged as an important factor affecting soil fungal communities. These findings provide critical microbiological evidence for accelerating the forest restoration in Northeast China through soil fertility management and regulation of litter inputs. Full article

Differences in environmental conditions due to slope topography result in differences in evapotranspiration along slopes, but it is unclear how changes in environmental conditions affect the variations in evapotranspiration along slopes. Therefore, we monitored dry-day evapotranspiration (ET_d), solar radiation, vapor pressure deficit (VPD), and soil moisture downslope and upslope on a larch plantation hillslope from July to September 2023 to reveal the mechanisms driving ET_d variations. The results revealed that the difference in ET_d values between the downslope and upslope positions varied by month, with comparable ET_d values at both positions in July and higher ET_d values at the downslope position than at the upslope position in August and September. An ET_d model combining the effects of solar radiation, VPD, and soil water content was developed, which explained 68% of the variation in ET_d. The contributions of solar radiation, VPD, soil moisture, and their interactions to ET_d varied across slope positions, and ET_d was limited mainly by solar radiation downslope and by soil moisture upslope. Our study improves the understanding of the mechanisms governing the variations in evapotranspiration along slopes, and provides a new methodology for quantifying the effects of environmental differences between slope positions on evapotranspiration. Full article

Clarifying spatiotemporal variations in transpiration and their influencing mechanisms is highly valuable for the accurate assessment of hillslope-scale transpiration and for the effective management of forest–water coordination. Here, the sap flow density, meteorological conditions, and soil moisture downslope and upslope of a Larix gmelinii var. principis-rupprechtii plantation hillslope were observed during the growing season (June to September) in 2023, China. The results revealed that transpiration per unit leaf area (T_L) was significantly lower at the upslope position than at the downslope position, with mean values of 0.21 and 0.31 mm·d⁻¹, respectively; these data were associated with the lower canopy conductance per unit leaf area induced by the higher vapor pressure deficit (VPD) and lower soil water content at the 40–60 cm soil depth at the upslope position. The temporal variations in the T_L were controlled by solar radiation, VPD, air temperature, and soil moisture at both slope positions, and the quantitative relationships established from these factors explained 89% of the variation in the T_L. The slope position did not affect the response functions between the T_L and the controlling factors but changed the contribution to the T_L. Compared with those at the downslope position, the contributions from solar radiation and VPD (air temperature) decreased (increased) at the upslope position, and the contribution of soil moisture was essentially similar at both slope positions. Transpiration mainly utilized water from the 20–60 cm soil depth; these results indicated that the soil water content at the 20–40 and 40–60 cm soil depths contributed more to the T_L than did that at the 0–20 cm soil depth. Based on our findings, changes in the environmental conditions caused by slope position have a critical impact on transpiration and can contribute to the development of hillslope-scale transpiration estimates and precise integrated forest and water management. Full article

Among numerous global problems, one of the most significant is air pollution. In this paper, unwashed (U) and water-washed (W) needles of two conifers—European larch and Douglas fir—were used to assess their capacity for the retention and accumulation of heavy metals. The needle samples were used to represent the atmospheric deposition of heavy metals located on the surface of the needles. The sampled European larch and Douglas fir plantations were situated at three locations in Serbia: a least polluted (Kučevo), a moderately polluted (Avala), and a very polluted (Lazarevac) site. The content of five heavy metals (Ni, Cu, Co, Cd, Pb) was investigated in the study. The concentration of cadmium (Cd) was higher in the European larch needles compared to Douglas fir, while the differences in the content of the other heavy metals between the species studied were insignificant. For both species, the following trend applied with respect to the heavy metal content in their needles: Ni ˃ Cu ˃ Co ˃ Pb ˃ Cd. Based on the results obtained, we deduced that the concentrations of all investigated heavy metals at all three locations for both species were within the allowed limits, except for nickel (Ni) content, which was over the predicted limit values for both species in the highly polluted area (Lazarevac). A PCA (principal component analysis) undertaken suggests that European larch has a greater ability to accumulate Co than Douglas fir on sites contaminated with heavy metals. The predictive foliar metal accumulation index (MAI) value was slightly higher in Douglas fir (4.14) than in European larch (3.76); therefore, the results suggest that this species would be a good planting choice, particularly in urban and industrial environments. Full article

This study aimed to understand the difference in forest transpiration (T) between slope positions and to separate the contributions of main influencing factors to improve the accuracy of forest transpiration estimation at the slope scale by up-scaling the results measured at the plot scale, especially in semiarid regions with significant soil moisture differences along slope positions. Two plots of larch plantation were established, one at the lower position and another at the upper position of a northwest-facing slope in the semiarid area of the Liupan Mountains in northwest China. The sap flow velocity ($J_S$, mL·cm⁻²·min⁻¹) of sample trees, meteorological parameters in the open field, and soil water potential in the main root zone (0–60 cm) were monitored simultaneously in the growing season (from July to September) of 2015. However, only the transpiration data of 59 selected effective days were used, after excluding the days with rainfall and missing data. Based on the relative sap flow velocity (the ratio of instantaneous sap flow velocity to its daily peak value), the impacts of terrain shading and soil water potential on sap flow velocity at varying slope positions were quantitatively disentangled. The reduction in $J_S$ at the lower slope plot, attributed to terrain shading, exhibited a positive linear correlation with solar radiation intensity. Conversely, the $J_S$ reduction at the upper slope plot demonstrated a quadratic functional relationship with the differential in soil water potential between the two plots. Subsequently, employing the relationship whereby transpiration is equivalent to the product of sap flow velocity and sapwood area, we conducted a quantitative analysis of the contributions of soil water potential, sapwood area, terrain shading, and their interaction to the disparity in transpiration between the two slope positions. The total transpiration of the 59 effective days was 41.91 mm at the lower slope plot, slightly higher than that at the upper slope plot (37.38 mm), indicating a small difference (4.53 mm) due to the offsetting effects of multiple factors. When taking the upper slope plot as a reference, the plot difference in soil water potential increased the total transpiration for the 59 days at the lower slope plot by 16.40 mm, while the differences in sapwood area and terrain shading and the interaction of the three factors decreased the total transpiration at the lower slope plot by 6.61, 2.86, and 2.40 mm, respectively, making a net increase of 4.53 mm. Based on the pilot study under given conditions of location, soil, climate, and vegetation, the contributions of the influencing factors to the stand transpiration differences between the upper and lower slopes are as follows: soil moisture (soil water potential) > stand structure (sapwood area) > solar radiation (terrain shading) > interaction of all factors. All these impacts should be considered for the accurate prediction of forest transpiration at the slope scale through up-scaling from measurement at the plot scale, especially in semiarid regions. Full article

The natural regeneration of Larix gmelinii plantations plays a pivotal role in rehabilitating ecosystem services in Northeast China’s degraded forests. However, mechanistic linkages between soil aggregate nutrient fluxes and fungal community assembly remain poorly constrained. Combining space-for-time substitution with particle-size fractionation and high-throughput sequencing, this study examined successional trajectories across regeneration in Langxiang National Nature Reserve to resolve nutrient–fungal interplay during long-term forest restructuring. The results demonstrated that microaggregates (<0.25 mm) functioned as nutrient protection reservoirs, exhibiting significantly higher total carbon (TC) and nitrogen (TN) contents and greater fungal diversity (p < 0.05). Both stand regeneration stage and aggregate size significantly influenced fungal community composition and structural organization (p < 0.05). Aggregate-mediated effects predominated in upper soil horizons, where fungal dominance progressively transitioned from Mortierellomycota to Ascomycota with increasing particle size. In contrast, lower soil layers exhibited regeneration-dependent dynamics: Basidiomycota abundance declined with L. gmelinii reduction, followed by partial recovery through mycorrhizal reestablishment in Pinus koraiensis broadleaf communities. Fungal co-occurrence networks displayed peak complexity during Juglans mandshurica germination (Node 50, Edge 345), with 64.6%positive correlations, indicating the critical period for functional synergy. Basidiomycota showed significant negative correlations with nutrients and major fungal phyla (R² = 0.89). This study confirms that natural vegetation regeneration reshapes belowground processes through litter inputs and mycorrhizal symbiosis, while microaggregate management enhances soil carbon sequestration. Near-natural plantation management should incorporate broadleaf species to preserve mycorrhizal diversity and amplify ecosystem services. These findings provide an essential soil ecological theoretical basis for sustainable plantation management in Northeast China. Full article

Mycorrhizal symbiosis has been the focus of research for more than a century due to the positive effect of fungi on the growth of the majority of woody plants. The extramatrical mycelium (EMM) of ectomycorrhiza (EMR) accounts for up to one-third of the total soil microbial biomass, whereas litter from this short-living pool accounts for 60% of the total litterfall mass in forest ecosystems. The functioning of EMR improves the nitrogen (N) nutrition of trees and thus contributes to the carbon (C) balance of forest soils. The model presented here is an attempt to describe these EMR functions quantitatively. It calculates the growth of EMM and the subsequent “mining” of additional nitrogen from recalcitrant soil organic matter (SOM) for EMR growth, with the associated formation of “dissolved soil carbon”. The decomposition of EMM litter is carried out by all organisms in the soil food webs, forming available ${\mathrm{N}\mathrm{H}}_4^{+}$ in the first phase and then solid-phase by-products (excretes) as a new labile SOM pool. These substances are the feedback that determines the positive role of EMR symbiosis for forest vegetation. A sensitivity analysis revealed a leading role of the C:N ratio of biotic components in the dynamics of EMM. The model validation showed a satisfactory agreement between simulated and observed data in relation to EMM respiration in larch forest plantations of different ages. Model testing within the EFIMOD3 model system allowed a quantitative assessment of the contribution of different components to forest soil and ecosystem respiration. The validation and testing of this model demonstrated the adequacy of the theoretical background used in this model, with a fast EMM decomposition cycle by all soil biota of the food webs and without direct resource exchange between plants and fungi. Full article