Search Results (982)

Understanding the environmental drivers of radial growth in the Pinus massoniana (lamb.) is essential for improving forest productivity and carbon sequestration in subtropical ecosystems. This study used the basal area increment (BAI) as an indicator of radial growth to investigate the main factors affecting the radial growth rate of P. massoniana and the changes in BAI with these factors. A total of 58 high quality tree ring series were analyzed. Six common methods were used to comprehensively analyze the importance of nine factor variables on the BAI, including tree age, competition index, average temperature, and so on. Generalized additive models (GAMs) were developed to explore the nonlinear relationships between each selected variable and the BAI. The results revealed the following: (1) Age and Competition Index was identified as the primary driving force; (2) BAI increased with Age when tree age was below 69 years; (3) from the overall trend, the BAI of P. massoniana decreased with the increase in the Competition Index. These findings provide a scientific basis for developing management plans for P. massoniana forests. Full article

Accurate above-ground biomass (AGB) quantification is confounded by signal saturation and data fusion challenges, particularly in structurally complex ecosystems like bamboo forests. To address these gaps, this study developed a two-stage framework to map the AGB of Dendrocalamus giganteus in a subtropical mountain environment. This study first employed Empirical Bayesian Kriging Regression Prediction (EBKRP) to spatialize sparse GEDI and ICESat-2 LiDAR metrics using Sentinel-2 and topographic covariates. Subsequently, a stacked ensemble model, integrating four machine learning algorithms, predicted AGB from the full suite of continuous variables. The stacking model achieved high predictive accuracy (R² = 0.84, RMSE = 11.07 Mg ha⁻¹) and substantially mitigated the common bias of underestimating high AGB, improving the predicted observed regression slope from a base model average of 0.63 to 0.81. Furthermore, SHAP analysis provided mechanistic insights, identifying the canopy photon rate as the dominant predictor and quantifying the ecological thresholds governing AGB distribution. The mean AGB density was 71.8 ± 21.9 Mg ha⁻¹, with its spatial pattern influenced by elevation and human settlements. This research provides a robust framework for synergizing multi-source remote sensing data to improve AGB estimation, offering a refined methodological pathway for large-scale carbon stock assessments. Full article

To explore the characteristics of species diversity and phylogenetic diversity, as well as the dominant processes of community construction, in different forest types (deciduous broad-leaved forest, mixed coniferous and broad-leaved forest, and Chinese fir plantation) in subtropical regions, analyze the specific driving patterns of soil nutrients and other environmental factors on the formation of forest diversity in different forest types, and clarify the differences in response to environmental heterogeneity between natural forests and plantation forests. Based on 48 fixed monitoring plots of 50 m × 50 m in Shouchang Forest Farm, Jiande City, Zhejiang Province, woody plants with a diameter at breast height ≥5 cm were investigated. Species diversity indices (Margalef index, Shannon–Wiener index, Simpson index, and Pielou index), phylogenetic structure index (PD), and environmental factors were used to analyze the relationship between diversity characteristics and environmental factors through variance analysis, correlation analysis, and generalized linear models. Phylogenetic structural indices (NRI and NTI) were used, combined with a random zero model, to explore the mechanisms of community construction in different forest types. Research has found that (1) the deciduous broad-leaved forest had the highest species diversity (Margalef index of 4.121 ± 1.425) and phylogenetic diversity (PD index of 21.265 ± 7.796), significantly higher than the mixed coniferous and broad-leaved forest and the Chinese fir plantation (p < 0.05); (2) there is a significant positive correlation between species richness and phylogenetic diversity, with the best fit being AIC = 70.5636 and R² = 0.9419 in broad-leaved forests; however, the contribution of evenness is limited; (3) the specific effects of soil factors on different forest types: available phosphorus (AP) is negatively correlated with the diversity of deciduous broad-leaved forests (p < 0.05), total phosphorus (TP) promotes the diversity of coniferous and broad-leaved mixed forests, while the diversity of Chinese fir plantations is significantly negatively correlated with total nitrogen (TN); (4) the phylogenetic structure of three different forest types shows a divergent pattern in deciduous broad-leaved forests, indicating that competition and exclusion dominate the construction of deciduous broad-leaved forests; the aggregation mode of Chinese fir plantation indicates that environmental filtering dominates the construction of Chinese fir plantation; the mixed coniferous and broad-leaved forest is a transitional model, indicating that the mixed coniferous and broad-leaved forest is influenced by both stochastic processes and ecological niche processes. In different forest types in subtropical regions, the species and phylogenetic diversity of broad-leaved forests is significantly higher than in other forest types. The impact of soil nutrients on the diversity of different forest types varies, and the characteristics of community construction in different forest types are also different. This indicates the importance of protecting the original vegetation and provides a scientific basis for improving the ecological function of artificial forest ecosystems through structural adjustment. The research results have important practical guidance value for sustainable forest management and biodiversity conservation in the region. Full article

Soil organic carbon (SOC) pool plays an extremely important role in regulating the global carbon (C) cycle and climate change. Atmospheric nitrogen (N) and phosphorus (P) deposition caused by human activities has significant impacts on soil C sequestration potential of terrestrial ecosystem. To investigate the effects of N and P deposition on soil C sequestration and C-N coupling relationship in broad-leaved evergreen forests, a 6-year field nutrient regulation experiment was implemented in subtropical Castanopsis sclerophylla forests with four different N and P additions: N addition (100 kg N·hm⁻²·year⁻¹), N + P (100 kg N·hm⁻²·year⁻¹ + 50 kg P·hm⁻²·year⁻¹), P addition (50 kg P·hm⁻²·year⁻¹), and CK (0 kg N·hm⁻²·year⁻¹). The changes in the C and N contents and stable isotope distributions (δ¹³C and δ¹⁵N) of different soil organic fractions were examined. The results showed that the SOC and total nitrogen (STN) (p > 0.05) increased with N addition, while SOC significantly decreased with P addition (p < 0.05), and N + P treatment has low effect on SOC, STN (p > 0.05). By density grouping, it was found that N addition significantly increased light fraction C and N (LFOC, LFN), significantly decreased the light fraction C to N ratio (LFOC/N) (p < 0.05), and increased heavy fraction C and N (HFOC, HFN) accumulation and light fraction to total organic C ratio (LFOC/SOC, p > 0.05). Contrary to N addition, P addition was detrimental to the accumulation of LFOC, LFN and reduced LFOC/SOC. It was found that different reactive oxidized carbon (ROC) increased under N addition but ROC/SOC did not change, while N + P and P treatments increased ROC/SOC, resulting in a decrease in SOC chemical stability. Stable isotope analysis showed that N addition promoted the accumulation of new soil organic matter, whereas P addition enhanced the transformation and utilization of C and N from pre-existing organic matter. Additionally, N addition indirectly increased LFOC by significantly decreasing pH; significantly contributed to LFOC and ROC by increasing STN accumulation promoted by NO₃⁻-N and NH₄⁺-N; and decreased light fraction δ¹³C by significantly increasing dissolved organic C (p < 0.05). P addition had directly significant negative effect on LFOC and SOC (p < 0.05). In conclusion, six-year N deposition enhances soil C and N sequestration while the P enrichment reduces the content of soil C, N fractions and stability in Castanopsis sclerophylla forests. The results provide a scientific basis for predicting the soil C sink function of evergreen broad-leaved forest ecosystem under the background of future climate change. Full article

Understanding species composition and forest dynamics is essential for predicting biomass productivity and informing conservation in tropical montane ecosystems. We evaluated floristic, demographic, and biomass changes in eighteen 0.1 ha permanent plots in the Colombian Sub-Andean forest, including both primary (ca. 60 y old) and secondary forests (ca. 30 years old). Two censuses of individuals (DBH ≥ 2.5 cm) were conducted over 7–13 years. We recorded 516 species across 202 genera and 89 families. Floristic composition differed significantly between forest types (PERMANOVA, p = 0.001), and black oak (Trigonobalanus excelsa Lozano, Hern. Cam. & Henao) forests formed distinct assemblages. Demographic rates were higher in secondary forests, with mortality (4.17% yr), recruitment (4.51% yr), and relative growth rate (0.02% yr) exceeding those of primary forests. The mean aboveground biomass accumulation and the rate of annual change were higher in primary forests (447.5 Mg ha⁻¹ and 466.8 Mg ha⁻¹ yr⁻¹, respectively) than in secondary forests (217.2 Mg ha⁻¹ and 217.2 Mg ha⁻¹ yr⁻¹, respectively). Notably, black oak forests showed the greatest biomass accumulation and rate of change in biomass. Annual net biomass production was higher in secondary forests (8.72 Mg ha⁻¹ yr⁻¹) than in primary forests (5.66 Mg ha⁻¹ yr⁻¹). These findings highlight the ecological distinctiveness and recovery potential of secondary Sub-Andean forests and underscore the value of multitemporal monitoring to understand forest resilience and assess vulnerability to environmental change. Full article

Plant functional traits serve as vital tools for understanding vegetation adaptation mechanisms in changing environments. As the primary organs for nutrient acquisition from soil, fine roots are highly sensitive to environmental variations. However, current research on fine-root adaptation strategies predominantly focuses on tropical, subtropical, and temperate forests, leaving a significant gap in comprehensive knowledge regarding fine-root responses in rocky-desertification habitats. This study investigates the fine roots of Pseudotsuga sinensis across varying degrees of rocky desertification (mild, moderate, severe, and extremely severe). By analyzing fine-root morphological and nutrient traits, we aim to elucidate the trait differences and correlations under different desertification intensities. The results indicate that root dry matter content increases significantly with escalating desertification severity. Fine roots in mild and extremely severe desertification exhibit notably higher root C, K, and Mg concentrations compared to those in moderate and severe desertification, while root Ca concentration shows an inverse trend. Our correlation analyses reveal a highly significant positive relationship between specific root length and specific root area, whereas root dry matter content demonstrates a significant negative correlation with elemental concentrations. The principal component analysis (PCA) further indicates that the trait associations adopted by the forest in mild- and extremely severe-desertification environments are different from those in moderate- and severe-desertification environments. This study did not account for soil nutrient dynamics, microbial diversity, or enzymatic activity—key factors influencing fine-root adaptation. Future research should integrate root traits with soil properties to holistically assess resource strategies in rocky-desertification ecosystems. This study can serve as a theoretical reference for research on root characteristics and adaptation strategies of plants in rocky-desertification habitats. Full article

Understanding the activity patterns of a species is essential for developing sound conservation and management plans. In this study, we used a camera-trapping technique to determine the activity patterns of bharal (Pseudois nayaur) in a marginal population in Wolong National Nature Reserve, Sichuan, China. Our results showed that these animals preferred to be active in the daytime from 08:00 to 20:00, with an activity peak between 10:00 and 14:00. In addition, we found that the species had a seasonal activity pattern with higher activity frequency in summer than in winter and that bharal were most active in a temperature range of 3–11 °C and at night with a waxing crescent moon, implying that the activity rhythm of the species is an adaptation to a subtropical high-altitude alpine area with vertical zonation in temperature. The pattern of movement and activity was also correlated with the moon phase. Full article

Phosphorus (P) availability is a major constraint on plant growth in many forest ecosystems, yet the strategies by which different tree species acquire and utilize various forms of soil phosphorus remain poorly understood. This study investigated how coexisting tree species with contrasting mycorrhizal types, specifically arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) associations, respond to different phosphorus forms under field conditions. An in situ root bag experiment was conducted using four phosphorus treatments (control, inorganic, organic, and mixed phosphorus) across four subtropical tree species. A comprehensive set of fine root traits, including morphological, physiological, and mycorrhizal characteristics, was measured to evaluate species-specific phosphorus foraging strategies. The results showed that AM species were more responsive to phosphorus form variation than ECM species, particularly under inorganic and mixed phosphorus treatments. Significant changes in root diameter (RD), root tissue density (RTD), and acid phosphatase activity (RAP) were observed in AM species, often accompanied by higher phosphorus accumulation in fine roots. For example, RD in AM species significantly decreased under the Na₃PO₄ treatment (0.94 mm) compared to the control (1.18 mm), while ECM species showed no significant changes in RD across treatments (1.12–1.18 mm, p > 0.05). RTD in AM species significantly increased under Na₃PO₄ (0.030 g/cm³) and Mixture (0.021 g/cm³) compared to the control (0.012 g/cm³, p < 0.05), whereas ECM species exhibited consistently low RTD values across treatments (0.017–0.020 g/cm³, p > 0.05). RAP in AM species increased significantly under Na₃PO₄ (1812 nmol/g/h) and Mixture (1596 nmol/g/h) relative to the control (1348 nmol/g/h), while ECM species showed limited variation (1286–1550 nmol/g/h, p > 0.05). In contrast, ECM species displayed limited trait variation across treatments, reflecting a more conservative acquisition strategy. In addition, trait correlation analysis revealed stronger coordination among root traits in AM species. And AM species exhibited high variability across treatments, while ECM species maintained consistent trait distributions with limited plasticity. These findings suggest that AM and ECM species adopt fundamentally different phosphorus acquisition strategies. AM species rely on integrated morphological and physiological responses to variable phosphorus conditions, while ECM species maintain stable trait configurations, potentially supported by fungal symbiosis. Such divergence may contribute to functional complementarity and species coexistence in phosphorus-limited subtropical forests. Full article

The Millard’s rat (Dacnomys millardi), a threatened murid endemic to Southeast Asian montane rainforests and the sole member of its monotypic genus, faces escalating endangered risks as a Near Threatened species in China’s Biodiversity Red List. This ecologically specialized rodent exhibits diagnostic morphological adaptations—hypertrophied upper molars and cryptic pelage—that underpin niche differentiation in undisturbed tropical/subtropical forests. Despite its evolutionary distinctiveness, the conservation prioritization given to Dacnomys is hindered due to a deficiency of data and unresolved phylogenetic relationships. Here, we integrated morphological analyses with the first complete mitogenome (16,289 bp in size; no structural rearrangements) of D. millardi to validate its phylogenetic placement within the subfamily Murinae and provide novel insights into genetic diversity erosion. Bayesian and maximum likelihood phylogenies robustly supported Dacnomys as sister to Leopoldamys (PP = 1.0; BS = 100%), with an early Pliocene divergence (~4.8 Mya, 95% HPD: 3.65–5.47 Mya). Additionally, based on its basal phylogenetic position within Murinae, we propose reclassifying Micromys from Rattini to the tribe Micromyini. Codon usage bias analyses revealed pervasive purifying selection (Ka/Ks < 1), constraining mitogenome evolution. Genetic diversity analyses showed low genetic variation (CYTB: π = 0.0135 ± 0.0023; COX1: π = 0.0101 ± 0.0025) in fragmented populations. We propose three new insights into this genetic diversity erosion. (1) Evolutionary constraints: genome-wide evolutionary conservation and shallow evolutionary history (~4.8 Mya) limited mutation accumulation. (2) Anthropogenic pressures: deforestation-driven fragmentation of habitats (>20,000 km²/year loss since 2000) has reduced effective population size, exacerbating genetic drift. (3) Ecological specialization: long-term adaptation to stable niches favored genomic optimization over adaptive flexibility. These findings necessitate suitable conservation action by enforcing protection of core habitats to prevent deforestation-driven population collapses and advocating IUCN reclassification of D. millardi from Data Deficient to Near Threatened. Full article

The distribution of forest aboveground biomass density (AGBD) is a key indicator of carbon stock and ecosystem health in the Eastern Himalayas, which represents a global biodiversity hotspot that sustains diverse forest types across an elevation gradient from lowland rainforests to alpine meadows and contributes to the livelihoods of more than 200 distinct indigenous communities. This study aimed to identify the key factors influencing forest AGBD across this region by analyzing the underlying biophysical and anthropogenic drivers through machine learning (random forest). We processed AGBD data from the Global Ecosystem Dynamics Investigation (GEDI) spaceborne LiDAR and applied filtering to retain 30,257 high-quality footprints across ten ecoregions. We then analyzed the relationship between AGBD and 17 climatic, topographic, soil, and anthropogenic variables using random forest regression models. The results revealed significant spatial variability in AGBD (149.6 ± 79.5 Mg ha⁻¹) across the region. State-wise, Sikkim recorded the highest mean AGBD (218 Mg ha⁻¹) and Manipur the lowest (102.8 Mg ha⁻¹). Within individual ecoregions, the Himalayan subtropical pine forests exhibited the highest mean AGBD (245.5 Mg ha⁻¹). Topographic factors, particularly elevation and latitude, were strong determinants of biomass distribution, with AGBD increasing up to elevations of 2000 m before declining. Protected areas (PAs) consistently showed higher AGBD than unprotected forests for all ecoregions, while proximity to urban and agricultural areas resulted in lower AGBD, pointing towards negative anthropogenic impacts. Our full model explained 41% of AGBD variance across the Eastern Himalayas, with better performance in individual ecoregions like the Northeast India-Myanmar pine forests (R² = 0.59). While limited by the absence of regionally explicit stand-level forest structure data (age, stand density, species composition), our results provide valuable evidence for conservation policy development, including expansion of PAs, compensating avoided deforestation and modifications in shifting cultivation. Future research should integrate field measurements with remote sensing and use high-resolution LiDAR with locally derived allometric models to enhance biomass estimation and GEDI data validation. Full article

Plant microbiomes are vital for the growth and health of their host. Tree-associated microbiomes are shaped by multiple factors, of which the host is one of the key determinants. Whether different host genotypes affect the structure and diversity of the tissue-associated microbiome and how specific taxa enriched in different tree tissues are not yet well illustrated. Chinese fir (Cunninghamia lanceolata) is an important tree species for both economy and ecosystem in the subtropical regions of Asia. In this study, we investigated the tissue-specific fungal community structure and diversity of nine different Chinese fir genotypes (39 years) grown in the same field. With non-metric multidimensional scaling (NMDS) analysis, we revealed the divergence of the fungal community from rhizosphere soil (RS), fine roots (FRs), and thick roots (TRs). Through analysis with α-diversity metrics (Chao1, Shannon, Pielou, ACE, Good‘s coverage, PD-tree, Simpson, Sob), we confirmed the significant difference of the fungal community in RS, FR, and TR samples. Yet, the overall fungal community difference was not observed among nine genotypes for the same tissues (RS, FR, TR). The most abundant fungal genera were Russula in RS, Scytinostroma in FR, and Subulicystidium in TR. Functional prediction with FUNGuild analysis suggested that ectomycorrhizal fungi were commonly enriched in rhizosphere soil, while saprotroph–parasite and potentially pathogenic fungi were more abundant in root samples. Specifically, genotype N104 holds less ectomycorrhizal and pathogenic fungi in all tissues (RS, FR, TR) compared to other genotypes. Additionally, significant correlations of several endophytic fungal taxa (Scytinostroma, Neonothopanus, Lachnum) with the growth traits (tree height, diameter, stand volume) were observed. This addresses that the interaction between tree roots and the fungal community is a reflection of tree growth, supporting the “trade-off” hypothesis between growth and defense in forest trees. In summary, we revealed tissue-specific, as well as host genotype-specific and genotype-common characters of the structure and functions of their fungal communities. Full article

Climatic oscillations in the Quaternary are altering the performance of angiosperms, while the species’ distribution is regarded as a macroscopic view of these spatial and temporal changes. Oaks (Quercus L.) are important tree models for estimating the abiotic impacts on the distribution of forest tree species. In this study, we modeled the past, present, and future suitable habitat for two varieties of deciduous oaks (Quercus serrata and Quercus serrata var. brevipetiolata), which are widely distributed in China and play dominant roles in the local forest ecosystem. We evaluated the importance of environmental factors in shaping the species’ distribution and identified the “wealthy” habitats in harsh conditions for the two varieties. The ecological niche models showed that the suitable areas for these two varieties are mainly concentrated in mountain ranges in central China, while Q. serrata var. brevipetiolata is also widely distributed in the middle-east mountain range. The mean temperature of the coldest quarter was identified as the critical factor in shaping the habitat availability for these two varieties. From the last glacial maximum (LGM) to the present, the potential distribution range of these two sibling species has obviously shifted northward and expanded from the inferred refugia. Under the optimistic (RCP2.6), moderate (RCP 4.5)-, and higher (RCP 6.0)-concentration greenhouse gas emissions scenarios, our simulations suggested that the total area of suitable habitats in the 2050s and 2070s will be wider than it is now for these two varieties of deciduous oaks, as the distribution range is shifting to higher latitudes; thus, low latitudes are more likely to face the risk of habitat losses. This study provides a case study on the response of forest tree species to climate changes in the north temperate and subtropical zones of East Asia and offers a basis for tree species’ protection and management in China. Full article

Soil microbes play a crucial role in driving biogeochemical cycles and are closely linked with aboveground plants during forest succession. Moso bamboo (Phyllostachys edulis) encroachment into adjacent forests of varying composition is known to alter plant diversity in subtropical and tropical regions. However, how soil microbial communities respond to this vegetation type transformation has not fully explored. To address this knowledge gap, a time-alternative spatial method was employed in the present study, and we investigated the effect of Moso bamboo expansion into subtropical broad-leaved forest and coniferous forest on soil microbial phospholipid fatty acids (PLFAs). We also measured the dynamics of key soil properties during the Moso bamboo expansion processes. Our results showed that Moso bamboo encroachment into subtropical broad-leaved forest induced an elevation in soil bacterial PLFAs (24.78%) and total microbial PLFAs (22.70%), while decreasing the fungal-to-bacterial (F:B) ratio. This trend was attributed to declines in soil NO₃⁻-N (18.63%) and soil organic carbon (SOC) concentrations (28.83%). Conversely, expansion into coniferous forests promoted soil fungal PLFAs (40.41%) and F:B ratio, primarily driven by increases in soil pH (4.83%) and decreases in SOC (36.18%). These results provide mechanistic insights into how contrasting expansion trajectories of Moso bamboo restructure soil microbial communities and highlight the need to consider vegetation context-dependency when evaluating the ecological consequences of Moso bamboo expansion. Full article

Forest biomass is closely related to carbon sequestration capacity and can reflect the level of forest management. This study utilizes four machine learning algorithms, namely Multivariate Stepwise Regression (MSR), K-Nearest Neighbors (k-NN), Artificial Neural Network (ANN), and Random Forest (RF), to estimate forest aboveground biomass (AGB) in Chenzhou City, Hunan Province, China. In addition, a canopy height model, constructed from a digital surface model (DSM) derived from Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) and an ICESat-2-corrected SRTM DEM, is incorporated to quantify its impact on the accuracy of AGB estimation. The results indicate the following: (1) The incorporation of multi-source remote sensing data significantly improves the accuracy of AGB estimation, among which the RF model performs the best (R² = 0.69, RMSE = 24.26 t·ha⁻¹) compared with the single-source model. (2) The canopy height model (CHM) obtained from InSAR-LiDAR effectively alleviates the signal saturation effect of optical and SAR data in high-biomass areas (>200 t·ha⁻¹). When FCH is added to the RF model combined with multi-source remote sensing data, the R² of the AGB estimation model is improved to 0.74. (3) In 2018, AGB in Chenzhou City shows clear spatial heterogeneity, with a mean of 51.87 t·ha⁻¹. Biomass increases from the western hilly part (32.15–68.43 t·ha⁻¹) to the eastern mountainous area (89.72–256.41 t·ha⁻¹), peaking in Dongjiang Lake National Forest Park (256.41 t·ha⁻¹). This study proposes a comprehensive feature integration framework that combines red-edge spectral indices for capturing vegetation physiological status, SAR-derived texture metrics for assessing canopy structural heterogeneity, and canopy height metrics to characterize forest three-dimensional structure. This integrated approach enables the robust and accurate monitoring of carbon storage in subtropical forests. Full article