Search Results (141)

Rapid and effective estimation of soil organic matter (SOM) is crucial for the scientific management of Moso bamboo forests. This study investigated Moso bamboo forest soils in Yongan City, Fujian Province, and systematically evaluated the synergistic adaptation strategies coupling spectral preprocessing methods, feature extraction strategies, and machine learning models based on visible and shortwave near-infrared (Vis-NIR) spectroscopy. The results indicated that: (1) Conventional preprocessing algorithms attenuated the SOM spectral feature signals dominated by soil color within the limited wavelength range of field in situ spectral data, resulting in a general decline in the accuracy of the estimation models. (2) Feature extraction and modeling algorithms exhibited distinct adaptability across different content intervals. Within the low-content interval (<15 g/kg), simple physical indices combined with random forest (RF) achieved effective estimation at a lower computational cost (RPD = 2.18). Within the high-content interval (>25 g/kg), the synergistic strategy of the CARS algorithm combined with support vector regression (SVR) yielded the optimal estimation performance (R² = 0.83, RPD = 2.45) and effectively mitigated the underestimation of high values caused by data imbalance. In conclusion, this study proposed a feature–model synergistic estimation approach, validating its feasibility for estimating SOM in Moso bamboo forests under the specific constraints of the current study area, thereby serving as a valuable reference for forest soil SOM monitoring in specific regions. Full article

Fertilization is widely used in managed Moso bamboo (Phyllostachys edulis (Carrière) J.Houz.) forests in subtropical China, but its short-term effects on soil properties and microbiomes remain uncertain. In this study, we conducted a field experiment with four treatments: no fertilization (NF), compound fertilizer (CF), sheep manure organic fertilizer plus compound fertilizer (SOCF), and a biochar-based sheep manure organic fertilizer combined with compound fertilizer (BSOCF). Surface soils samples were collected approximately one year after the initial application, and soil properties were measured together with bacterial and fungal communities using high-throughput sequencing. Results showed that fertilization mainly affected soil chemical properties rather than overall microbial community structure. Compared with CF, BSOCF significantly increased soil pH (4.56 ± 0.10 vs. 4.30 ± 0.05) and resulted in the highest available phosphorus (AP, 6.38 ± 1.10 mg kg⁻¹) and available potassium (AK, 128.16 ± 17.56 mg kg⁻¹) contents. Microbial responses were comparatively limited. Bacterial richness remained stable, fungal alpha diversity showed only a weak increasing trend, and both beta diversity and phylum-level composition changed little among treatments. Variation in treatment-enriched taxa was associated mainly with soil pH and nutrient availability. Overall, the results indicate that biochar-based sheep manure organic fertilizer can improv soil fertility and partially alleviated soil acidity, while causing only limited short-term shifts in the overall microbial community structure. These findings suggest that BSOCF may be a suitable fertilization strategy for enhancing nutrient availability in Moso bamboo forests with relatively low short-term disturbance to soil microbial assemblages. Full article

The expansion of Moso bamboo (Phyllostachys edulis) significantly alters the spatial configuration of surrounding trees, leading to dynamic shifts in the spatial distribution of coarse woody debris (CWD). Investigating the spatial patterns of CWD during bamboo expansion can reveal the dynamic mechanisms of forest communities in this process, thereby providing scientific insights for forest management and conservation. In this study, conducted within the Yangjifeng Biodiversity Monitoring Large Plot, all trees with a diameter at breast height (DBH) ≥ 1 cm within the plots were tagged and important variables were measured, including DBH, tree height, and spatial attributes. Coarse woody debris (CWD) with a DBH ≥ 10 cm was also measured, including DBH, diameters at both ends, length, and spatial attributes. Based on the importance values of tree species in each 20 m × 20 m plot—where an importance value comprehensively measured a species’ relative abundance, frequency, and dominance in the community—the sample plots were divided into three continuous sample transects: evergreen broad-leaved forest (EBF), bamboo–broadleaf mixed forest (BMF), and Phyllostachys edulis forest (PEF). Ripley’s ‘g’-function was employed to analyze the spatial patterns and associations of CWD across these three forest types. A random sampling approach was used to collect CWD samples for the measurement and calculation of carbon storage. Three key findings emerged. (1) With the expansion of Moso bamboo, the biomass and carbon storage of standing dead trees both decrease. The biomass is highest in EBF, followed by BMF and PEF. However, carbon storage is greatest in BMF and lowest in PEF. (2) With the expansion of Moso bamboo, the distribution of CWD became increasingly uniform in PEF; analysis of the overall spatial pattern of CWD indicated that with increasing spatial scale, CWD changed from an aggregated to a random distribution across all three forest types, with a pattern scale of approximately 10 m. In EBF, the CWD of Moso bamboo exhibited a random distribution at all spatial scales. Additionally, CWD across different diameter classes, decay stages, and types changed from aggregated to random distributions as the spatial scale increased, with a reduction in aggregation intensity correlated with larger diameter classes. (3) Finally, we found an almost exclusively negative spatial association between living trees and CWD across all scales, and this negative correlation may be attributed to the absence of new tree growth following tree mortality. Collectively, our findings demonstrate that during Moso bamboo expansion, the spatial distribution of CWD changes from aggregated to random, while maintaining a significantly negative spatial association with living trees. This reveals the dynamic changes in the spatial patterns of CWD during community development, thereby providing a scientific basis for the forest management of subtropical evergreen broadleaf forests and bamboo management and control. Full article

The eddy covariance technique has become one of the most popular methods for measuring CO₂ exchange between ecosystems and the atmosphere. Flux averaging intervals typically range from 15 to 60 min, with 30 min being the most commonly adopted setting. However, due to variations in site conditions and turbulent regimes, the choice of averaging interval can substantially influence flux calculations. In this study, we applied the eddy covariance method to examine how different averaging intervals affect CO₂ flux measurements in a subtropical Moso bamboo forest during winter in Jinggangshan, Jiangxi Province, China. The results showed that the bamboo forest maintained a relatively high CO₂ uptake rate even in winter. When relative humidity exceeded 80%, the averaging interval had a pronounced effect on CO₂ flux estimates, and in some cases even altered the direction of the flux. Based on a comparative analysis, an average interval of 60 min is recommended. These findings offer practical guidance for eddy covariance observations in subtropical Moso bamboo forests and provide useful insights for flux measurements in humid environments more broadly. Full article

Flame residence time (FRT) is an important indicator of flaming duration and is closely related to local heat release and associated ecological effects. However, the intrinsic mechanisms through which fuel bed structure affects FRT remains insufficiently understood. Clarifying how fuel bed structure affects FRT under flat, wind-free conditions is important for prescribed burning and ecological restoration. This study investigated surface fuels from typical forest types in southwestern China through controlled laboratory experiments conducted under flat, wind-free conditions, with moisture content, loading, thickness, and bulk density systematically varied. The driving mechanisms of fuel bed structural characteristics on FRT were systematically analyzed. Coniferous forests and moso bamboo had significantly lower FRT than broadleaved forests. Moisture content was the most influential factor, followed by thickness and bulk density, whereas loading had a relatively limited effect. Prediction models developed using machine learning methods significantly outperformed traditional regression approaches. Fuel bed structure is a critical factor controlling FRT. The high-accuracy prediction models established in this study enhance the mechanistic understanding of FRT. The findings provide a theoretical basis and practical support for prescribed burning and fire behavior modeling and may contribute to improved forest fire management. Full article

The disorderly expansion of Moso bamboo (Phyllostachys edulis) into adjacent forests has become a serious ecological issue in southern China; however, the response of soil microbial communities remain unclear. This study investigated the succession patterns of bacterial and fungal communities through high-throughput sequencing and soil physicochemical analysis across three expansion stages in subtropical China: mixed coniferous–broadleaf forests, bamboo–forest transition zones, and pure Moso bamboo stands. The results indicate that Moso bamboo expansion altered soil bacterial and fungal beta-diversity without changing alpha-diversity. Random forest and redundancy analyses revealed distinct microbial group drivers. Bacterial communities were driven by available phosphorus (37.1% explained variance), with expansion intensifying soil phosphorus limitation and selecting for groups adapted to low-phosphorus environments (e.g., Acidobacteria). Fungal communities were primarily influenced by bulk density (21.3% explained variance), as the bamboo rhizosphere system altered soil physical structure, resulting in a significant loss of ectomycorrhizal fungi (e.g., Russula) and a corresponding decline in Basidiomycota abundance. This study confirms that Moso bamboo expansion reorganizes the soil microbial ecosystem through two pathways: chemical nutrient limitation and physical space remodeling. By revealing the subterranean ecological consequences of Moso bamboo expansion, this study provides a theoretical foundation for sustainable management of subtropical forests. Full article

To address the limitations regarding poor adaptability to complex forest environments as well as high installation and operational costs in existing mountain transportation equipment, a modular cable-type equipment for moso bamboo transportation was designed based on the terrain characteristics of steep bamboo forests and specific transportation requirements. This study first presents the overall structure and working principle of the transportation equipment. Next, a theoretical analysis and component selection were conducted for critical parts such as the wire rope, supporting components, wire-rope-driven devices, and hydraulic systems. Then, the static characteristics of the supporting components and the vibration characteristics of the wire rope were simulated and analyzed. Finally, performance testing of the equipment was conducted, focusing on transportation productivity and machine utilization. The results showed that the maximum deformation of the supporting components was 1.75 mm, occurring at the lower roller–rail contact region. During unloading, the first-order principal vibration amplitude of the wire rope had the greatest impact at the mid-span position, with a value of 0.27 m. The vibration frequency of the wire rope during operation is influenced by the its initial tension, load mass, and attachment distance, with the first-order frequency range approximately between 0.85 and 3.90 Hz. Within this frequency range, the bouncing excitation caused by moso bamboo does not induce resonance in the wire rope. The transportation productivity of the equipment was 2.61 tons per hour, with the machine utilization rate exceeding 95%. This study indicates that the designed cable-type equipment effectively meets the requirements for moso bamboo transportation in complex forest environments. Full article

The accurate estimation of aboveground biomass (AGB) in Moso bamboo forests is critical for assessing their carbon sequestration potential and supporting sustainable management. Satellite-based approaches are often constrained by signal saturation and mixed-pixel effects, whereas Unmanned Aerial Vehicle (UAV) imagery enables precise individual tree detection, overcoming these limitations. In this study, we propose a stand density (SD)-driven AGB estimation framework using high-resolution UAV RGB imagery. Individual bamboo positions were extracted using the Revised Local Maximum (RLM) algorithm, which achieved an optimal accuracy at a 2.5 m sampling interval (OA = 82.20%). Using 85 ground-truth plots, we developed six SD-AGB models and evaluated them via 10-fold cross-validation and independent UAV validation (10 plots). The Artificial Neural Network (ANN) model outperformed others, with strong calibration (R² = 0.94, RMSE = 3.78 Mg/ha), robust cross-validation (R² = 0.84 ± 0.06, RMSE = 5.24 ± 0.67 Mg/ha), and reliable independent validation (R² = 0.87, RMSE = 4.56 Mg/ha). Spatial mapping revealed a total of 14,190 bamboo plants with an average AGB of 32.80 Mg/ha. This UAV-based SD-AGB framework provides a robust, scalable, and cost-effective tool for precise biomass estimation, supporting sustainable bamboo forest management and carbon sequestration strategies and progress towards SDG 15. Full article

This study investigated the effects of different application rates of spent mushroom substrate (SMS) from Morchella sextelata on soil properties and microbial communities in a moso bamboo (Phyllostachys edulis) plantation. Three SMS rates (2.4, 4.7, and 9.4 kg·m⁻²) were applied, and soil samples were collected at 6 and 12 months from two depths (0–20 cm and 20–40 cm). One year after application, topsoil total phosphorus (TP) increased 12–20 fold, while available phosphorus (AP) and potassium (AK) were significantly elevated. Soil pH initially decreased but partially recovered, whereas electrical conductivity (EC) continued to rise, indicating salt accumulation. Urease (UA) and sucrase (SA) activities increased 10–17 fold and 3–5 fold, respectively, while catalase (CAT) and acid phosphatase (ACP) were temporarily suppressed. SMS application significantly altered microbial community composition, with Acidobacteriota and Basidiomycota becoming more abundant. Correlation analysis identified pH, organic matter, AP, and UA as key factors linked to microbial changes. The medium application rate (4.7 kg·m⁻²) provided the best balance between soil improvement and environmental risk. These findings demonstrate that M. sextelata SMS can effectively enhance soil fertility while modulating microbial communities, but salt accumulation and short-term acidification warrant attention. Full article

As a critical agroforestry crop in Southern China, Moso bamboo, maintains regional timber security and bamboo shoot production, with its net ecosystem productivity (NEP) directly determining dry matter accumulation and economic yield. This study integrates 2024 continuous flux observations with XGBoost and SHAP explanations to characterize the subtropical bamboo forest carbon budget and its nonlinear driving mechanisms. The results show a weak carbon sink in 2024 with an annual cumulative NEP of 120 g C m⁻², as high respiration of 860 g C m⁻² limited organic matter conversion by consuming nearly 88% of the 980 g C m⁻² total primary production. The peak production period during May and June was offset by growth stagnation in August, caused by extreme heat and drought. Net radiation served as the primary driver, with a positive contribution threshold of 75.28 W m⁻², whereas precipitation exceeding 1.85 mm or air temperatures over 17.85 °C hindered carbon accumulation through radiation attenuation and metabolic heat loss. Strong radiation–precipitation interactions confirm that water’s impacts on yield are deeply contingent upon radiation backgrounds. These nonlinear regulatory pathways provide a scientific foundation for stabilizing bamboo forest productivity through synergistic water-radiation management and structural optimization during extreme climate events. Full article

Soil microorganisms are important components of forest ecosystems and play a key role in biogeochemical cycling. Bamboo is invasive due to its strong clonal expansion ability, which often leads to changes in plant communities and soil environments, thus affecting soil microorganisms. However, the existing research focuses on the response of moso bamboo (Phyllostachys edulis) and soil fungi and bacteria, and little attention is paid to other bamboo species and their impact on soil protists. In this study, we examined the effects of Bambusa emeiensis expansion on the soil microbial communities in subtropical evergreen broad-leaved forests. B. emeiensis expansion significantly reduced plant diversity and soil pH (p < 0.05). The expansion of B. emeiensis did not significantly change the relative abundance of dominant bacteria and fungi groups in the soil, but significantly changed the community composition of protists, including a significant increase in the relative abundance of Cercozoa, while the Evosea_X group and Ciliophora decreased significantly (p < 0.05). While α-diversity remained unchanged across all microbial groups, only protist community structure differed significantly (p = 0.026). The main driver of protist variation was identified as plant diversity decline by redundancy analysis (R² = 0.760, p = 0.032). These results can be interpreted within a bottom-up regulatory framework, in which plant diversity is linked to changes in protist community composition. Overall, protists are an important group of organisms that help us understand the impact of bamboo growth on the environment. Their role in nutrient cycling and soil fertility suggests that changes in protist communities may have broader implications for ecosystem sustainability. This study provides a scientific reference for the ecological management of regional B. emeiensis and highlights the potential impact of protist community shifts on soil health and ecosystem resilience. Full article

Moso bamboo (Phyllostachys edulis) harvesting is labor-intensive and inefficient, while strip-cutting enables mechanized, cost-effective management and supports long-term production. Intensive strip-cutting disturbs bamboo ecosystems, altering soil, litter and understory vegetation. This may reduce long-term productivity despite moso bamboo’s rapid growth, especially in the mountainous areas like Anji, Zhejiang. To balance ecological and production goals, we evaluated strip-cutting widths of 3, 5, and 8 m under three slope classes, 5–14° (gentle, SL1), 15–24° (moderate, SL2), and 25–34° (steep, SL3), focusing on bamboo growth recovery and understory vegetation diversity. Compared with uncut control plots, the number of herbaceous and shrub species increased in all treatment plots. In 5 m moderate slope plots, shoot and culm numbers were 27% and 13% higher than those in the 3 m and 8 m plots, and 37% higher than uncut control plots. Herb species diversity, as reflected by the Shannon–Wiener (H′), Simpson (D), and Margalef richness (R) indices, was high in the narrowest clearcut strips under SL1 and SL3. Pielou’s evenness index (J) was high in the 3 and 5 m plots under SL2 and SL3. Shrub species diversity, as indicated by D and R, was high in 5 and 8 m plots under SL2 and SL3. Principal component analysis (PCA) indicated that under SL2, 5 m strip-cutting width with a score of 0.649 outperformed others. These results suggest that 5 m strip-cutting width under SL2 slope optimizes understory vegetation diversity and supports a synergistic outcome of “high shoot emergence–high culm formation” thereby achieving both ecological and production benefits. Full article

Moso bamboo, widely distributed in subtropical regions of China, plays an important role in forest management and carbon cycle research. However, accurate estimation of tree density and aboveground biomass (AGB) remains challenging due to the unique characteristics of Moso bamboo forests in their growth and stand structure. This research aims to develop a new procedure for bamboo tree density and AGB estimation based on UAV-LiDAR and sample plots from multiple sites through comparative analysis of the incorporation of two groups of variables—regular point cloud metrics (e.g., height, point density) and layered texture metrics—and three modeling methods—multiple linear regression (MLR), mixed-effects modeling (MEM), and hierarchical Bayesian modeling (HBM). The results showed that incorporating layered texture metrics with regular variables substantially improved the estimation accuracy of both tree density and AGB. Among these models, HBM achieved the highest predictive performance, yielding coefficient of determination (R²) values of 0.54 for tree density and 0.59 for AGB, with corresponding relative root mean square errors (rRMSE) of 21.46% and 17.97%. This study presents a novel and effective method for estimating Moso bamboo tree density and AGB using multi-site UAV-LiDAR and sample plots, offering a scientific basis for precise management and carbon stock assessment. Full article

Moso bamboo (Phyllostachys heterocyclas) has rapidly expanded in subtropical broadleaf forests of eastern China, raising concerns about biodiversity loss and community restructuring. We investigated how the expansion of this native bamboo influences species diversity and phylogenetic diversity across forest strata (trees, shrubs, herbs) by surveying 16 plots along a gradient from bamboo-free to bamboo-dominated stands. We measured soil properties, calculated multiple α-diversity indices, and constructed a community phylogeny to assess phylogenetic metrics. We also constructed a phylogenetically informed Resistance Index (RI) to evaluate species-specific responses to bamboo expansion. The results showed that overstory tree species richness and Faith’s phylogenetic diversity declined sharply with increasing bamboo cover, accompanied by significant losses of evolutionary lineages. In contrast, understory shrub and herb layers exhibited stable or higher species richness under bamboo expansion, although functional redundancy among new colonists suggests limited gains in ecosystem function. Soil conditions shifted substantially along the expansion gradient: pH increased by approximately 0.5 units, while total organic carbon and total nitrogen each decreased by about 30% (p < 0.01). Redundancy analysis and variance partitioning indicated that bamboo’s impacts on community diversity are mediated primarily through these soil changes. Species-level trends revealed that formerly dominant canopy trees (e.g., Schima superba, Pinus massoniana) were highly susceptible to bamboo, whereas certain shade-tolerant taxa (e.g., Cyclobalanopsis glauca, Rubus buergeri) showed resilience. In conclusion, the aggressive expansion of Moso bamboo drastically alters multi-layer forest diversity and community assembly processes. Our findings point to a need for targeted management (e.g., reducing bamboo density, soil restoration, and enrichment planting of native species) to mitigate biodiversity loss, underscoring the importance of considering phylogenetic diversity in expansion ecology and forest conservation. Full article

Plant roots influence soil infiltration by altering its properties like porosity and bulk density, which are essential for ecohydrological cycles. Moso bamboo (Phyllostachys edulis), using its well-developed underground root system, invades neighbor forest communities, thereby influencing root characteristics and soil properties. Although Moso bamboo invasion may alter soil hydrology, its specific impact on soil infiltration capacity and water flow connectivity remains unclear. This work took a fir forest (Cunninghamia lanceolata), mixed fir and bamboo forest, and a bamboo forest which represent three different degrees of invasion: uninvaded, partially invaded, and completely invaded, respectively, as study objects, using double-ring dyeing infiltration method to measure soil infiltration capacity and calculating water flow connectivity index for the root zone. To assess the effects of soil properties and root characteristics on soil infiltration capacity and water flow connectivity, we employed random forest and structural equation modeling. The analysis revealed that Moso bamboo invasion significantly enhanced soil infiltration capacity. Specifically, in partially invaded forests, the initial infiltration rate, stable infiltration rate, and average infiltration rate increased by 31.5%, 26.1%, and 28.5%, respectively. In completely invaded forests, the corresponding increases were 6.6%, 35.6%, and 28.5%. Also, Moso bamboo invasion increased water flow connectivity of root zone, compared to the uninvaded forest, the water flow connectivity index increased by 29.4% in the completely invaded forest and by 15.6% in the partially invaded forest. The marked increase in fine root biomass density (RBD1), fine root length density (RLD1), soil organic carbon (SOC), and non-capillary pores (NCP) and the decrease in soil bulk density (SBD) followed by Moso bamboo invasion effectively improved water flow connectivity and soil infiltration capacity. The analysis identified that RBD1, RLD1, NCP, and SBD as the key drivers of soil infiltration capacity, whereas the water flow connectivity index was controlled mainly by SOC, NCP, RLD1, and RBD1. These findings help clarify the mechanistic pathways of Moso bamboo’s effects on soil infiltration. Full article