Woody plants are crucial components of forest ecosystems and play critical roles in regulating community succession and ecosystem function. Studying woody plant diversity and its influencing factors is thus important for understanding and protecting forest ecosystems. Quercus aliena var. acutiserrata is an important deciduous broadleaf species in the warm–temperate forest of central China. Multiple regression and structural equation modelling were used to discuss the effect of biotic and soil factors on tree species diversity across seven relative density gradients of Q. aliena var. acutiserrata trees in this zone. Our results showed that the following: (1) Species diversity showed significant decreasing trends with increasing relative density of Q. aliena var. acutiserrata. (2) As the relative density of the oak tree increased, some biotic factors (canopy density, and mean DBH) and soil factors (Soil SOC, AP, and AK) all showed significantly increasing trends, whereas the DBH variation (CVD) and soil pH displayed decreasing trends. (3) Biotic factor (e.g., mean DBH, CVD, and competition interaction) had strong direct effect on species diversity, and soil factors exerted indirect roles on tree diversity via biotic factors. Our results provide insight into biodiversity protection and scientific management in this warm–temperate natural oak forest.

Estimates of tree species diversity via traditional optical remote sensing are based only on the spectral variation hypothesis (SVH); however, this approach does not account for the vertical structure of a forest. The relative height (RH) indices derived from GEDI spaceborne LiDAR provide vertical vegetation structure information through waveform decomposition. Although RH indices have been widely studied, the optimal RH index for tree species diversity estimation remains unclear. This study integrated GF-1 optical imagery and GEDI LiDAR data to estimate tree species diversity in a warm temperate forest. First, random forest plus residual kriging (RFRK) was employed to achieve wall-to-wall mapping of the GEDI-derived indices. Second, recursive feature elimination (RFE) was applied to select relevant spectral and LiDAR features. The random forest (RF), support vector machine (SVM), and k-nearest neighbor (kNN) methods were subsequently applied to estimate tree species diversity through remote sensing data. The results indicated that multisource data achieved greater accuracy in tree species diversity estimation (average R² = 0.675, average RMSE = 0.750) than single-source data (average R² = 0.636, average RMSE = 0.754). Among the three machine learning methods, the RF model (R² = 0.760, RMSE = 2.090, MAE = 1.624) was significantly more accurate than the SVM (R² = 0.571, RMSE = 2.556, MAE = 1.995) and kNN (R² = 0.715, RMSE = 2.084, MAE = 1.555) models. Moreover, mean_mNDVI, mean_RDVI, and mean_Blue were identified as the most important spectral features, whereas RH30 and RH98 were crucial features derived from LiDAR for establishing models of tree species diversity. Spatially, tree species diversity was high in the west and low in the east in the study area. This study highlights the potential of integrating optical imagery and spaceborne LiDAR for tree species diversity modeling and emphasizes that low RH indices are most indicative of middle- to lower-canopy tree species diversity.

Active soil substances, which can indicate environmental changes sensitively, have the fastest turnover rate. Vegetation diversity and soil bio-physicochemical properties according to five elevations classes (800 m, 1000 m, 1100 m, 1200 m, and 1500 m a.s.l.) in the Southern Taihang Mountain were investigated. Soil ammonium-N (NH₄⁺—N), nitrate-N (NO₃⁻—N), microbial biomass carbon (MBC), and nitrogen (MBN), as well as soil urease (URE) and sucrose (SUC) activities were determined. The results showed that elevation gradients, soil layers, and their interaction had significant effects on most of the active soil substances. With the rise of elevation, soil NO₃⁻—N, inorganic N, MBC, and MBN contents, as well as SUC activity and SUC/MBC ratio basically showed an inverted V-shaped distribution trend and reached the peak value at 1100 m (p < 0.05). Soil URE showed a fluctuating upward trend and reached the peak value at 1500 m (p < 0.05), and the URE/MBC ratio showed a straight upward trend. With the depth of soil layer, the contents of active soil substances tended to decrease, showing a phenomenon of surface aggregation. Active soil substances were correlated with plant community diversity indexes, soil water content, pH, available N, and available phosphorus contents, and available N was the main factor affecting active soil substances, which could explain 34.4% of the variation. In summary, at the intermediate slope of 1100 m, soil moisture and tightness were suitable for soil microbial activity and plant growth, the highest contents of active soil substances, indicating a fast turnover of soil carbon and nitrogen. The present study enriched our understanding of soil carbon and nitrogen turnover mechanisms in the mountain ecosystem.

Ecosystem service value (ESV) is a critical indicator of regional ecological well-being. Assessing and forecasting ESV are essential for achieving the coordinated development of environmental and economic systems. This study employs the SD-PLUS model, integrating Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to assess the spatiotemporal dynamics of land use and land cover change (LUCC), as well as ESV in Zhengzhou from 2030 to 2040. It analyses the impact of various driving factors on ESV and examines the spatial correlations among ecosystem services across different regions. The results indicate that the total ESV is expected to decrease by 73.53 × 10⁷ yuan, primarily due to significant reductions in cropland and water areas. By 2040, ESV is projected to increase by 14.51 × 10⁷ yuan under the SSP126 scenario, decrease by 73.18 × 10⁷ yuan under the SSP585 scenario, and show a moderate decline under the SSP245 scenario. Climate factors, transportation location, and topographical features have a significantly positive impact on ESV, while environmental and socioeconomic factors exert a negative influence. The analysis of interrelationships among ecosystem services shows that synergies dominate, especially between supporting and cultural services, with only localised trade-offs observed. These findings contribute valuable insights for the development of scientifically sound, well-reasoned, and efficient strategies for ecological conservation and sustainable development.

Soil fungi play vital roles in the forest soil ecosystems through the nutrient cycle and organic substance decomposition, so the distribution of fungi at different altitudes has attracted increasing attention. However, their abundance, diversity, and community structure at different altitudes in temperate deciduous forests have rarely been studied. In this study, the fungal communities around two dominant trees (Quercus aliena var. acutiserrata and Carpinus turczaninowii Hance) in temperate deciduous forests at different altitudes (low altitude, medium altitude, high altitude) in the Taihang Mountains were identified via Illumina high-throughput sequencing according to the UNITE database. The soil chemical properties (soil pH value, soil available potassium, alkaline hydrolyzed nitrogen, soil available phosphorus contents, soil total nitrogen, and carbon contents) were also measured. The results revealed that the dominant genera around the tree species were Russula, Tylopilus, Sebacina, Saitozyma, Mortierella, Amanita, and Descolea. The highest relative abundance of fungi occurred at the lowest altitude. The species richness index and diversity index of fungi around Carpinus turczaninowii at low altitudes were the highest. The soil pH, available potassium content, and alkaline hydrolyzed nitrogen content played a crucial role in the composition and diversity of the fungal communities at different altitudes. Therefore, soil physicochemical properties were the important factors in forming fungi composition and diversity at different altitudes in the temperate forest.

Ectomycorrhizal (EcM) tree species often dominate temperate and warm-temperate forests, yet how variation in their relative abundance is associated with sp