Search Results (58)

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

Converting monoculture forests into mixed forests is a widely adopted strategy to enhance forest ecosystem quality. Soil enzyme activities and their stoichiometric ratios are acknowledged as critical indicators of nutrient cycling and ecosystem multifunctionality, with microbial nutrient limitation (particularly C, N, and P) being strongly influenced by forest management practices. However, the effects of this conversion on soil enzyme activities and stoichiometric ratios remain inconclusive, and the impacts of forest conversion on soil C, N, and P dynamics require further clarification. To address these uncertainties, a meta-analysis of 2113 paired observations was conducted to assess the impacts of forest conversion on soil enzyme activities, stoichiometric ratios, and microbial nutrient limitations. The activities of four key enzymes, including β-1,4-glucosidase (BG), β-1,4-N-acetylglucosaminidase (NAG), leucine aminopeptidase (LAP), and phosphatase (ACP) were examined. It was found that mixed forests exhibited significantly higher C-, N-, and P- enzyme activities than monocultures (increases of 36.23%, 9.85%, and 11.07%, respectively). Additionally, soil C, N, and P contents were generally enhanced following the conversion from monocultures to mixed forests. Elevated enzyme C:P and N:P ratios were observed in mixed forests, while C:N ratios were reduced. Microbial C limitation was alleviated, though C&P co-limitation remained prevalent. Notably, greater effects on enzyme activities were observed when conifer monocultures (particularly those introduced with broadleaf species) were converted, compared with conversions of broadleaf monocultures. In contrast, the introduction of additional conifer species into existing conifer stands exacerbated C limitation. These results suggest that conversion of monocultures to mixed-species forests can mitigate microbial C limitation in soils while improving soil nutrient availability. Furthermore, for conifer plantation conversion, selecting functionally complementary broadleaf species yields greater benefits than introducing additional conifer species. Full article

Bare land exposed by glacier retreat provides new opportunities for ecosystem development. Investigating primary vegetation succession in deglaciated regions can provide significant insights for ecological restoration, particularly for future climate change scenarios. Nonetheless, research on this topic in the Qinghai–Tibet Plateau has been exceedingly limited. This study aimed to investigate vegetation succession in the deglaciated area of the Zepu glacier during the Little Ice Age in southeastern Tibet. Quadrat surveys were performed on arboreal communities, and trends in vegetation change were assessed utilizing multi-year (1986–2024) remote sensing data. The findings indicate that vegetation succession in the Zepu glacier deglaciated area typically adheres to a sequence of bare land–shrub–tree, divided into four stages: (1) shrub (species include Larix griffithii Mast., Hippophae rhamnoides subsp. yunnanensis Rousi, Betula utilis D. Don, and Populus pseudoglauca C. Wang & P. Y. Fu); (2) broadleaf forest primarily dominated by Hippophae rhamnoides subsp. yunnanensis Rousi; (3) mixed coniferous–broadleaf forest with Hippophae rhamnoides subsp. yunnanensis Rousi and Populus pseudoglauca C. Wang & P. Y. Fu as the dominant species; and (4) mixed coniferous–broadleaf forest dominated by Picea likiangensis (Franch.) E. Pritz. Soil depth and NDVI both increase with succession. Species diversity is significantly higher in the third stage compared to other successional stages. In addition, soil moisture content is significantly greater in the broadleaf-dominated communities than in the conifer-dominated communities. An analysis of NDVI from 1986 to 2024 reveals an overall positive trend in vegetation recovery in the area, with 93% of the area showing significant vegetation increase. Temperature is the primary controlling factor for this recovery, showing a positive correlation with vegetation cover. The results indicate that Key ecological indicators—including species composition, diversity, NDVI, soil depth, and soil moisture content—exhibit stage-specific patterns, reflecting distinct phases of primary succession. These findings enhance our comprehension of vegetation succession in deglaciated areas and their influencing factors in deglaciated areas, providing theoretical support for vegetation restoration in climate change. Full article

Individual tree crown detection (ITCD) and tree species classification are critical for forest inventory, species-specific monitoring, and ecological studies. However, accurately detecting tree crowns and identifying species in structurally complex forests with overlapping canopies remains challenging. This study was conducted in a complex mixed conifer–broadleaf forest in northern Japan, aiming to improve ITCD and species classification by employing two machine learning models and different combinations of metrics derived from very high-resolution (2.5 cm) UAV red–green–blue (RGB) and multispectral (MS) imagery. We first enhanced ITCD by integrating different combinations of metrics into multiresolution segmentation (MRS) and DeepForest (DF) models. ITCD accuracy was evaluated across dominant forest types and tree density classes. Next, nine tree species were classified using the ITCD outputs from both MRS and DF approaches, applying Random Forest and DF models, respectively. Incorporating structural, textural, and spectral metrics improved MRS-based ITCD, achieving F-scores of 0.44–0.58. The DF model, which used only structural and spectral metrics, achieved higher F-scores of 0.62–0.79. For species classification, the Random Forest model achieved a Kappa value of 0.81, while the DF model attained a higher Kappa value of 0.91. These findings demonstrate the effectiveness of integrating UAV-derived metrics and advanced modeling approaches for accurate ITCD and species classification in heterogeneous forest environments. The proposed methodology offers a scalable and cost-efficient solution for detailed forest monitoring and species-level assessment. Full article

Severe drought events have raised concerns regarding their effects on the phenological cycles of forest species. This study evaluates the correspondence between in situ phenophases and those detected by an unmanned aerial vehicle (UAV) in tree species coexisting within a mixed forest, with particular attention to their relationship with climatic variables. Based on 12 consecutive monthly field observations, we compared phenological developments with UAV-derived normalized difference vegetation index (NDVI) values, which were then correlated with environmental variables. The analysis revealed a convergence of inflection points and seasonal phenological shifts, likely driven by climatic factors, although distinct patterns emerged between coniferous and broadleaf species. Photoperiod (PP), vapor pressure deficit (VPD), maximum temperature (TMAX), and, to a lesser extent, precipitation (P) were the primary environmental variables influencing NDVI results, used here as a proxy for phenology. Photothermal conditions revealed seasonal asynchrony in NDVI responses between coniferous and broadleaf species, exerting a positive influence on conifers during summer, while having a negative impact on broadleaf species in spring. Validation of in situ observations with UAV-derived data demonstrated a biological correlation between canopy dynamics and NDVI values, supporting its use as a proxy for detecting phenophases at the level of individual trees. Full article

Understory vegetation is an important component of forest ecosystems, and the supply of nutrients in the soil is related to the growth and development of soil microorganisms and understory plants. The effects of different tree species composition ratios in the forest on the process of soil microbial community assembly are not clear in the existing studies, and the factors influencing the differences in the abundance of understory plants under different forest canopy compositions and their mechanisms of action have not yet been clearly explained. In this study, two types of pure forests (PFP and PFQ) and two types of mixed forests (MF and MPQ) were selected from the Zhongcun Forestry, and the soil characteristics, soil microbial community assembly process, and understory plant community abundance, composition, and β-diversity were analyzed for the different forest types. The results showed that changes in the proportion of broadleaf and coniferous species in the forest could lead to changes in the community assembly process of soil fungi, and that the fungal assembly process in the mixed forest was mainly related to dispersal limitation. Compared with pure forests that were exclusively coniferous or exclusively broadleaf, mixed coniferous and broadleaf forests had a higher abundance of understory plants and a more stable forest community composition. In mixed forests, forests with a large proportion of broadleaf arbors had more available resources in the soil, soil pH was closer to neutral, and soil C was less likely to be lost compared to forests with a large proportion of conifers. Full article

Numerous studies on biodiversity–ecosystem functioning (BEF) have shown that mixed plantations can improve the ecological benefits of forest ecosystems. However, few studies have employed a multi-dimensional approach to study the integrated ecological benefits of mixed plantations. This study aims to evaluate the stand characteristics and ecological benefits of different forest types by examining various ecological indicators, including trees, shrubs, herbs, and soil properties. Focusing on typical mixed broadleaf–conifer plantations (MBCPs), mixed coniferous plantations (MCPs), and pure Cunninghamia lanceolata (Lamb.) Hook plantations (PCLs) at the Guiyang Plantation Farm, Suichang, we analyzed growth performance, spatial structure, understory vegetation diversity, and soil physicochemical properties across these forest types. For each forest type, one 100 × 100 m plot was established. Within each plot, five 20 × 20 m subplots were selected for investigation. Our results show that the aboveground biomass of MCPs is higher than that of MBCPs and PCLs, with increases of 46.58% and 177.29%, respectively. Furthermore, both mixed plantations offer better stand structure compared to pure plantations. In mixed plantations, the MBCPs exhibited a high degree of niche overlap, indicating that interspecific competition outweighed complementarity, whereas the MCPs demonstrated a more favorable stand structure. MCPs also exhibit significantly greater understory vegetation diversity compared to MBCPs and PCLs, with increases of 4.19%–13.04% and 10.34%–36.99%, respectively. Additionally, mixed plantations enhance soil moisture retention and fertility. With the onset of global warming and the increasing prevalence of extreme weather events, the establishment of artificial mixed plantations is an essential strategy to address climate change and enhance the ecological benefits of plantations. Full article

Individual tree parameters are essential for forestry decision-making, supporting economic valuation, harvesting, and silvicultural operations. While extensive research exists on uniform and simply structured forests, studies addressing complex, dense, and mixed forests with highly overlapping, clustered, and multiple tree crowns remain limited. This study bridges this gap by combining structural, textural, and spectral metrics derived from unmanned aerial vehicle (UAV) Red–Green–Blue (RGB) and multispectral (MS) imagery to estimate individual tree parameters using a random forest regression model in a complex mixed conifer–broadleaf forest. Data from 255 individual trees (115 conifers, 67 Japanese oak, and 73 other broadleaf species (OBL)) were analyzed. High-resolution UAV orthomosaic enabled effective tree crown delineation and canopy height models. Combining structural, textural, and spectral metrics improved the accuracy of tree height, diameter at breast height, stem volume, basal area, and carbon stock estimates. Conifers showed high accuracy (R² = 0.70–0.89) for all individual parameters, with a high estimate of tree height (R² = 0.89, RMSE = 0.85 m). The accuracy of oak (R² = 0.11–0.49) and OBL (R² = 0.38–0.57) was improved, with OBL species achieving relatively high accuracy for basal area (R² = 0.57, RMSE = 0.08 m² tree⁻¹) and volume (R² = 0.51, RMSE = 0.27 m³ tree⁻¹). These findings highlight the potential of UAV metrics in accurately estimating individual tree parameters in a complex mixed conifer–broadleaf forest. Full article

Minor and trace elements in soil play a crucial role in regulating ecological processes that sustain the functionality of forest ecosystems. In this study, we have selected three conifer forests (Pinus sylvestris, Picea asperata, Larix principis-rupprechtii), one broadleaf forest (Betula Platyfilla) and one mixed forest of Betula Platyfilla and Larix principis-rupprechtii in the Winter Olympic core area and determined the pattern of 12 typical elements (B, Fe, V, Cr, Ni, Co, Mn, As, Cu, Zn, Sn and Se) in soils and their main drivers in the three different soil layers (A, B and C horizon) in each soil profile. Our results showed that the concentrations of B, Fe, Cr, Cu, Ni and Sn were mainly enriched in the broadleaf forest and mixed broadleaf–conifer forest zones, and the average concentrations of Co, Mn, V, Zn, As and Se were mainly enriched in coniferous forest zones in contrast. We have observed that the mean concentrations of Fe, Cr, Ni, Zn, As, Sn and Co increase with soil depth in the BP forest. The concentrations of Se and Cu were higher in the A layer than the C layer. The piecewise structural equation modeling (piecewiseSEM) results visualized a direct and negative effect on B, Fe, V, Cr and Ni concentrations due to soil temperature, while the concentrations of Se is mainly influenced by soil temperature and soil properties. Full article

Vegetation restoration has played a significant role in preventing soil erosion and enhancing soil carbon sequestration in the hilly regions of subtropical China. However, under long-term vegetation restoration, it remains unclear how soil organic carbon and nitrogen components synergistically change and whether their dynamics are consistent across different soil depths. This study investigates the soils of four major vegetation types in subtropical hilly regions: enclosed Masson pine forest (EMP), Masson pine forest (MP), slash pine forest (SP), and mixed broadleaf–conifer forest (MBC). Soil organic carbon (SOC) components, nitrogen components, and physicochemical properties were analyzed across different soil depths (0–100 cm) under these vegetation restoration types. Results showed that forest type significantly influenced SOC stability. The MBC exhibited the highest mineral-associated organic carbon (MAOC) content, indicating the highest SOC stability. Both the MBC and SP forests sequestered more iron-aluminum-bound organic carbon (FeOC) and less Ca-associated organic carbon (CaOC) compared to the other forest types. The dominance of FeOC over CaOC in these acidic soils highlights the critical role of iron-aluminum oxides in SOCSOC stabilization. Vegetation restoration significantly influenced the relationship between SOC and nitrogen components in the topsoil (0–20 cm), but this effect diminished in the subsoil (>20 cm). This study confirmed the depth-dependent impacts of long-term vegetation restoration on soil carbon stability and C/N stoichiometry in subtropical plantations. Targeted vegetation restoration strategies can improve SOC stability in subtropical plantations. Full article

The forest musk deer (Moschus berezovskii) and Siberian roe deer (Capreolus pygargus) are browsers with a broad sympatric distribution in North and Southwest China. However, little is known about their spatial utilization of microhabitats and habitats. This study, conducted on Huanglong Mountain in China, analyzed the defecation site distribution, indicating preferences of forest musk deer and Siberian roe deer for their habitat demands. Using generalized linear mixed models (GLMMs), we compared the defecation site preferences of both species and further examined their spatial utilization patterns. The results indicated that the primary factors influencing defecation site preferences for forest musk deer were slope (15.79%), elevation (4.26%), herbaceous cover (19.93%), herb height (33.73%), and tree diversity (15.64%). Conversely, for Siberian roe deer, elevation (54.63%) and herbaceous cover (29.31%) were the key factors. Significant differences were found in elevation (p < 0.001) and herbaceous diversity (p < 0.01) between the defecation sites of the two species, with additional notable differences in slope position, tree diversity, and average tree height (p < 0.05). Furthermore, forest musk deer primarily utilized broadleaf forests, coniferous forests, mixed conifer-broadleaf forests, and sparse woodlands. In contrast, Siberian roe deer utilized broadleaf forests, sparse woodlands, and coniferous forests, showing a significant difference (p = 0.01). These findings suggest distinct spatial ecological segregation between forest musk deer and Siberian roe deer regarding their microhabitat preferences and vegetation type utilization at the habitat scale. Full article

Understanding the relationship between modern pollen assemblages and vegetation/climate for various elevations is essential for accurately interpreting fossil pollen records and conducting quantitative climate reconstructions in mountainous regions. However, these relationships for the Tibetan Plateau, which is the highest and one of the most ecologically sensitive regions globally, are still scarce. We present modern pollen assemblages from 78 topsoil samples collected along altitudinal gradients from 498 to 4046 m above sea level on the eastern Tibetan Plateau. They were distributed in alpine shrub meadows, coniferous forests, and mixed broad-leaved and coniferous forest vegetation types. Multivariate statistical methods, including discriminant analysis, indicator species analysis, logistic regression, and redundancy analysis, were employed to identify relationships among modern pollen assemblages, vegetation types, and climate along an altitudinal gradient. The results revealed that (1) vegetation types along the altitudinal gradient can be effectively differentiated by comparing pollen assemblages, discriminant analysis, and indicator species analysis; (2) the conifer/broadleaf pollen ratio (C/B) efficiently distinguished coniferous forests (C/B > 5) from mixed forests (C/B < 5); and (3) variations in modern pollen assemblages are primarily influenced by temperature, with pollen ratios, such as Artemisia/Cyperaceae (Art/Cy) and Tsuga/(Tsuga + Abies + Picea) (T/TAP), displaying notable altitudinal and temperature differences. These findings demonstrate that variations in modern pollen assemblages on the eastern Tibetan Plateau differentiate between vegetation types and correlate with temperature variations associated with elevation. The results provide insights for future paleovegetation and paleoclimatic reconstructions for similar mountainous regions. Full article