Non-point source pollution caused by surface runoff has been a popular hydrological and environmental safety issue and has attracted extensive attention from global scholars. To identify the optimal vegetation coverage of Festuca arundinacea grassland for controlling soil erosion and purifying surface runoff, bare land was chosen as the control in this experiment. Simulated rainfall experiments were carried out with three levels of coverage (low coverage, moderate coverage and full coverage) under four slope conditions (flat slope, gentle slope, medium slope, and steep slope) and at four rainfall intensities (moderate rainfall, heavy rainfall, rainstorm and heavy rainstorm). The comprehensive evaluation results suggested that the capacity of Festuca arundinacea grassland for reducing the surface runoff, sediment yield, suspended solids (SS), total nitrogen (TN), total phosphorus (TP) and chemical oxygen demand (COD) decreased with increasing rainfall intensity and slope but increased with increasing vegetation coverage. Structural equation model (SEM) results suggested that there were positive relationships between the vegetation coverage and purification capacity index and negative correlations between the rainfall intensity and slope and the purification capacity index. The response surface analysis results suggested that the optimal vegetation coverage should be higher than 84% and that the slope should be smaller than 10° for controlling soil erosion and avoiding pollution via diffusion with surface runoff in Festuca arundinacea grassland. This study proposes recommendations for the vegetation configuration pattern in the development and management of runoff purification systems.

The accurate estimation of forest biomass is important to evaluate the structure and function of forest ecosystems, estimate carbon sinks in forests, and study matter cycle, energy flow, and the effects of climate change on forest ecosystems. Biomass additivity is a desirable characteristic to predict each component and the total biomass since it ensures consistency between the sum of the predicted values of components such as roots, stems, leaves, pods, and branches and the prediction for the total tree. In this study, 45 Robinia pseudoacacia L. trees were harvested to determine each component and the total biomass in the Loess Plateau of western Shanxi Province, China. Three additive systems of biomass equations of R. pseudoacacia L., based on the diameter at breast height (D) only and on the combination of D and tree height (H) with D²H and D^bH^c, were established. To ensure biomass model additivity, the additive system of biomass equations considers the correlation among different components using simultaneous equations and establishes constraints on the parameters of the equation. Seemingly uncorrelated regression (SUR) was used to estimate the parameters of the additive system of biomass equations, and the jackknifing technique was used to verify the accuracy of prediction of the additive system of biomass equations. The results showed that (1) the stem biomass contributed the most to the total biomass, comprising 51.82% of the total biomass, followed by the root biomass (24.63%) and by the pod and leaf biomass, which accounted for the smallest share, comprising 1.82% and 2.22%, respectively; (2) the three additive systems of biomass equations of R. pseudoacacia L. fit well with the models and were effective at making predictions, particularly for the root, stem, above-ground, and total biomass (R²_adj > 0.812; root mean square error (RMSE) < 0.151). The mean absolute error (MAE) was less than 0.124, and the mean prediction error (MPE) was less than 0.037. (3) When the biomass model added the tree height predictor, the goodness of fit R²_adj increased, RMSE decreased, and the accuracy of prediction was much improved. In particular, the additive system, which was developed based on D^bH^c combination prediction factors, was the most accurate. The additive system of biomass equations established in this study can provide a reliable and accurate estimation of the individual biomass of R. pseudoacacia L. in the Loess region of western Shanxi Province, China.

The mechanisms by which the soil physical structure, nutrient conditions, understory vegetation diversity and forest meteorological factors influence fine root (<2 mm diameter) characteristics mediated by soil moisture content (SMC) and soil heat flux (SHF) remain uncertain under climate change. Therefore, in this research, continuous observations were made of the fine root growth, death and turnover of cypress plantations, as well as the SMC and SHF under the management of four thinning intensities in hilly areas in central Sichuan from 2021 to 2023. The fine root data were obtained using the microroot canals (minirhizotron) in the study, and the soil hydrothermal data were obtained using the ECH2O soil parameter sensor and the PC-2R SHF data logger. In the time series, the fine root growth, death and turnover of the cypress plantations with different thinning intensities first increased and then decreased throughout the year; the vertical center of the gravity of the fine roots of cypress was concentrated in the 30–50 cm range. This research also revealed that the variability in the SMC decreased with increasing soil depth. Additionally, the SHF was transmitted from greater soil depths to the surface in unthinned cypress plantation at a rate of 0.036 per year, which decreased the heat in the fine root region. However, SHF was transmitted from the soil surface to greater depths at rates of 0.012 per year, 0.08 per year and 0.002 per year, which increased the heat in the fine root area. The redundancy analysis (RDA) and structural equation model (SEM) results indicated that the SMC and soil heat energy distribution pattern obviously affected fine root growth, death and turnover in the cypress plantation. However, the climate conditions in the forest, the characteristics of vegetation in the understory and the physical and chemical characteristics of the soil directly or indirectly affect the characteristics of the fine roots of cypress plantations with changes in thinning intensity. This research provides a basis for understanding ecosystem structure, nutrient cycling and carbon balance and may guide artificial plantation development and management.

Southwestern China has a large area of artificial forests and has experienced massive environmental and social losses due to forest fires. Evaluating the flammability of fuels from dominated forests in this region can help assess the fire risk and predict potential fire behaviors in these forests, thus guiding forest fire management. However, such studies have been scarcely reported in this region. In this study, the flammability of litter from nine forest types, which are common in southwestern China, was evaluated by measuring organic matter content, ignition point, and calorific value. All these flammability characteristics of fuels varied significantly across forest types. By using principal component analysis and K-means clustering, litters were classified into three groups: highly susceptible to ignition with low fire intensity (Pinus densata, Pinus densata-Populus simonii, Pinus yunnanensis, Larix gmelini, Pinus armandii), less susceptible to ignition with high fire intensity (Abies fabri-Populus simonii), and median ignitibility and fire intensity (Abies fabri, Abies fabri-Picea asperata, Platycladus orientalis). Our study can help predict the risk and intensity of fires in the studied forests and serve as a source of information for fire management in southwestern China.

Pleioblastus amarus (bitter bamboo) shoots are a traditional forest vegetable in China, renowned for its nutritional composition and associated health benefits. This study aimed to investigate the dynamic changes in nutritional quality and bitterness-related metabolites, as well as corresponding gene expression in P. amarus shoots at three distinct growth stages, specifically at heights of 10 cm (BT1), 20 cm (BT2), and 40 cm (BT3). The results showed that the content of soluble sugars decreased while the content of total phenols and flavonoids, which contribute to bitterness, increased during the growth of P. amarus shoots. In addition, comparative analysis of BT2 vs. BT1, BT3 vs. BT1, and BT3 vs. BT2 revealed 14, 43, and 36, respectively, differentially accumulated metabolites (DAMs). Notably, BT2 exhibited upregulation of flavonoids, such as apigenin, while bitter amino acids, including phenylalanine and arginine, showed a marked increase in BT3. Moreover, differential gene expression analysis revealed 3161, 13268, and 3742 differentially expressed genes (DEGs) in the BT2 vs. BT1, BT3 vs. BT1, and BT3 vs. BT2 comparisons, respectively. An integrated analysis of metabolomic and transcriptomic data indicated that the metabolites and genes associated with the biosynthesis pathways of phenylalanine, tyrosine, tryptophan, arginine, and the branched-chain amino acids valine, leucine, and isoleucine were significantly enriched during the growth of P. amarus shoots. The study indicates that early-stage (≤20 cm) P. amarus shoots are mainly bitter due to flavonoids like apigenin, while the bitterness in later-stage (around 40 cm) shoots is largely due to bitter amino acids such as phenylalanine, arginine, valine, and isoleucine. This research highlights key compounds and genes related to bitterness, providing a basis for future research on enhancing the nutritional value and flavor of P. amarus shoots.

Topography is an important factor that impacts the hydrological processes on sloping farmlands. Yet, few studies have reported the combined influences of slope gradient and slope position on infiltration characteristics and hydrodynamic parameters on sloping croplands in purple soil regions, an important area for agricultural productivity in Southwest China. Here, laboratory-simulated rainfall experiments were conducted in a steel trough (5 m long, 2 m wide, and 0.45 m deep), and rainfall lasted for 1 h at a rate of 90 mm h⁻¹ to examine the variations in the infiltration rates and hydrodynamic parameters under varying slope gradients (i.e., 3°, 6°, 10°, 15°, 21°, and 27°) and slope positions (i.e., upper, middle, and lower), and explore the relationships between the infiltration rate and the soil detachment rate. The results showed that the infiltration rate decreased gradually with duration rainfall and ultimately approached a steady state in the six slope treatments. Cumulative infiltration ranged from 15.54 to 39.32 mm during rainfall, and gradually reduced with the increase of slope gradient. The Horton’s model outperforms other models for predicting the infiltration rate with an R² value of 0.86. Factors such as Darcy–Weisbach friction, flow shear force, Manning friction coefficient, unit energy, and runoff depth varied in the following order: upper slope > middle slope > lower slope, whilst the Reynolds number and Froude number gradually increased along the slope transect from the upper to lower slope positions. A significant linear function was fitted between the soil detachment rate and the infiltration rate at the gentle slopes (3°, 6°, 10°), whereas an exponential relationship was observed at the steep slopes (15°, 21°, and 27°). Observation also suggested that 15° was the critical slope gradient of sediment detachment, infiltration characteristics, and hydrodynamic parameters. Our results provide theoretical insight for developing models that predict the impacts of topographic factors on hydrological characteristic and soil erosion in hilly agricultural landscapes of purple soil fields.