Mechanistic insights into the drivers of soil carbon (C), nitrogen (N), and phosphorus (P) stoichiometry are essential for optimizing forest management strategies. This study investigated the influence of biotic factors (including plant diversity and structural attributes) and abiotic factors (including site and topography) on the spatial variability of soil C, N, and P concentrations and their stoichiometric ratios, utilizing field data from a 25-ha subtropical karst mixed evergreen-deciduous broadleaf forest plot. The results indicated mean soil C, N, and P concentrations of 61.33 +/- 0.83, 7.03 +/- 0.12, and 1.60 +/- 0.03 g kg(-1), respectively, demonstrating moderate spatial variability with coefficients of variation (CV) ranging from 33.87% to 47.50%. The average stoichiometric ratios were 9.40 +/- 0.14 for C:N, 53.70 +/- 1.82 for C:P, and 6.15 +/- 0.22 for N:P, exhibiting more pronounced spatial heterogeneity with CVs between 35.79% and 88.18%. Random forest analysis identified soil depth as the primary driver of soil C, N, and P contents, while elevation emerged as the most significant driver of C:P and N:P ratios. Multiple linear regression and generalized additive models confirmed that rock outcrop ratio and woody plant height diversity positively influenced soil C, whereas soil depth had a negative effect. Variance partitioning analysis revealed that site factors explained 6.8% and 9.9% of the spatial variation in soil C and N, respectively, while topographic factors explained 12.2% of the variation in soil P, as well as 8.3% and 5.4% of the variation in C:P and N:P ratios, respectively. Collectively, our findings reveal strong spatial heterogeneity in soil nutrients and stoichiometry, shaped by interactions among topographic, site, and vegetation factors. This study provides critical insights for forest conservation and restoration strategies in subtropical karst ecosystems.

Understanding the assembly processes of soil microbial communities as secondary succession proceeds offers a critical insight into ecosystem recovery after disturbance. However, a comprehensive understanding of which ecological processes govern the assembly remains elusive. In this study, soil samples were sampled across four seasons (i.e., spring, summer, autumn, and winter) from various forest succession including shrubland, secondary forest, and primary forest, within a karst region in southwestern of China. The assembly of microbial communities was analyzed using the method of the null model, coupled with measurements of environmental variability. The results demonstrate that soil bacterial assembly is primarily dominated by the deterministic processes with their relative influence increases as karst forest proceeds; while soil fungal assembly is dominated by the stochastic processes, and the relative significance of stochasticity peaks in the secondary forest. Moreover, both soil bacterial and fungal communities' co-occurrence networks intensifies as forest succession. The shift in the balance between deterministic and stochastic across successional stages is predicted by factors such as plant DBH and soil nutrient availability. Specially, soil nitrate nitrogen (NO3 --N), along with plant diameter at breast height (DBH), available potassium (AK), available phosphorus (AP), and total phosphorus (TP), emerged as crucial determinants of soil microbial assembly as karst forest succeeds. Overall, our study provides the evidence that the bacterial and fungal communities' assembly vary within and across forest succession, and highlights the importance of plant properties and soil micro-environment for these community assembly in karst soil.

Natural vegetation restoration has emerged as an effective and rapid approach for ecological restoration in fragile areas. However, the response of soil microorganisms to natural succession remains unclear. To address this, we utilized high-throughput sequencing methods to assess the dynamics of soil bacterial and fungal communities during forest succession (shrubland, secondary forest, and primary forest) in a karst region of Southwest China. Our study revealed that bacterial α-diversity was significantly higher in secondary forest compared to both shrubland and primary forest. Intriguingly, the soil bacterial community in primary forest exhibited a closer resemblance to that in shrubland yet diverged from the community in secondary forest. Conversely, the soil fungal community underwent notable variations across the different forest stages. Furthermore, analysis of the microbial co-occurrence network revealed that, within these karst forests, the relationships among soil fungi were characterized by fewer but stronger interactions compared to those among bacteria. Additionally, soil properties (including pH, soil organic carbon, total nitrogen, moisture, and available potassium), soil microbial biomass (specifically phosphorus and nitrogen), and plant diversity were the drivers of soil bacterial community dynamics. Notably, soil pH accounted for the majority of the variations observed in the soil fungal community during karst forest succession. Our findings provide valuable insights that can inform the formulation of strategies for ecological restoration and biodiversity conservation in karst regions, particularly from a microbial perspective.

To elucidate the relationship between productivity and biodiversity and their evolution in the vegetation restoration process of peak-cluster depression region, three representative vegetation types（shrub, secondary forest and primary forest） in southwest karst region, Guangxi were selected. Based on the systematic investigation of dynamic plots of three vegetation types during the period of 2007-2017, the changes of plant community biomass and productivity distribution, the relationship between plant community productivity and biodiversity were analyzed by statistical methods. The results showed that:（1） the biomass and productivity of secondary forest and primary forest continued to increase in 2007-2017, and the increment of secondary forest was higher than that of primary forest; but the biomass of shrub increased firstly and then decreased, resulting in an average productivity at only 0.09 Mg·hm -2 ·a -1 in the whole 10 years.（2） Among the top 10 species with important value（IV）, the productivity of almost all species in the shrub decreased except Ligustrum japonicum and Croton tiglium, and the productivity decrement of Alangium chinense was higher than others; in secondary forest, the productivity of all species increased except Maesa japonica; while in primary forest, the productivity of all species increased and the increment of Callicarpa longifolia was the highest among them.（3）In the shrub, the productivity had positive correlation with structural diversity and had negative correlation with species diversity; in the secondary forest, the productivity had positive correlations with species Shannon-Wiener index, species Simpson index, structural Pielou evenness index and stand density; it had negative correlations with species Pielou evenness index and structural Shannon-Wiener index; and it had no correlation with structural Simple index; in primeval forest, the productivity had negative correlations with species Simpson index, species Pielou evenness index, structural Shannon-Wiener index and Pielou evenness index,and had no correlation with species Shannon-Wiener index, species Simpson index and stand density. This study suggested that shrub biodiversity had the greatest effect on productivity in different vegetation types in the restoration process. So, it is important to increase community structure complexity for improving the forest productivity during forest management.

Gross nitrogen (N) transformations are crucial in determining soil N status, but how gross N transformations change during post-agricultural succession remains poorly understood. Here, gross N transformations were measured using a N-15 isotope dilution technique in a subtropical karst region, southwest China. A stratified random sampling scheme was adopted and the succession sequence included grassland (similar to 4 years), shrubland (similar to 15 years) and secondary forest (similar to 30 years) with cropland as reference. The soil was leptosols (limestone soil). Soil total N concentrations were significantly (P < 0.05 hereafter) elevated in the shrubland and forest relative to the cropland and grassland. No clear pattern was found for NH4+ concentration, but NO3- concentration increased from the grassland to the forest. The gross rates of N mineralization and nitrification (GN) were significantly lower in the grassland than in the cropland, but increased significantly during post-agricultural succession. There were no clear patterns for the rates of dissimilatory NO3- reduction to NH4+ and gross NO3- immobilization. Gross NH4+ immobilization (GAI) in the forest was lowest but there was no significant difference among the cropland, grassland and shrubland. Gross N mineralization rate correlated significantly with protease activity, implying that the depolymerization of N-containing polymers was likely the rate-limiting step of gross N mineralization. Net nitrate production rate and GN:GAI ratio increased significantly from the grassland to the forest, supporting that soil N cycling likely became more open during post-agricultural succession in the karst region of southwest China.

Previous studies on soil organic carbon content or stock mapping mostly use natural environmental covariates and do not consider the soil management practice factor. However, human activities have become an important influencing factor for soil organic carbon, especially for agricultural soils. Crop species/crop rotations and management practices significantly affect the amount and spatial variation of soil organic carbon in croplands, but have not been considered for mapping soil organic carbon. In this study, we used direct crop rotation information and variables generated using Fourier transform on HJ-1A/1B NDVI time series data to capture the periodic effect of crop rotation, and explored the effectiveness of incorporating such information in predicting topsoil organic carbon content in cropland. A case study applied such method in a largely agricultural area in Anhui province, China. Crop rotation information was obtained through field investigation. Various combinations of predictive environmental variables were experimented for mapping soil organic carbon. The results were validated using field samples. Results showed that the combination of natural environment variables with both crop rotation type and variables derived through Fourier transform yielded the highest accuracy. In addition, only using the Fourier decomposed variables and crop rotation information were able to achieve a similar accuracy with using only soil formative natural environmental variables. This indicates that crop rotation information has comparable predictive power of soil organic carbon as natural environment variables. This study demonstrates the effectiveness of including agricultural practice information in digital soil mapping in agricultural landscapes with differences in crop rotation.

Spontaneous vegetation succession after agricultural abandonment is a general phenomenon in many areas of the world. As important indicators of nutrient status and biogeochemical cycling in ecosystems, the stoichiometry of key elements such as carbon (C), nitrogen (N) and phosphorous (P) in soil and microbial biomass, and their responses to vegetation recolonization and succession after agricultural abandonment remain poorly understood. Here, based on a space-for-time substitution approach, surface soil samples (0–15 cm) were collected from four vegetation types, e.g., tussock grassland, shrubland, secondary forest, and primary forest, which represent four successional stages across this region. All samples were examined C, N and P concentrations and their ratios in soil and microbial biomass. The results showed that soil organic C and total N content increased synchronously but total soil P did not remarkably change along a progressive vegetation succession. Consequently, soil C:P and N:P ratios increased while C:N ratio stayed almost unchanged during vegetation succession. Soil microbial biomass C (SMBC) and microbial biomass N (SMBN) concentrations elevated while SMBP did not significantly change during vegetation succession. Unlike the soil C:N:P stoichiometry, however, microbial C:N and C:P ratios were significantly or marginally significantly greater in grassland than in the other three successional stages, while microbial N:P did not significantly vary across the four successional stages. Overall, the present study demonstrated that soil and microbial stoichiometry responded differently to secondary vegetation succession in a karst region of subtropical China.

Soil microorganisms regulate ecosystem function and aboveground community dynamics in terrestrial ecosystems. However, our current understanding of the drivers of soil microbial diversity lags our understanding of macroorganisms. Here, we used Illumina sequencing of 16S and ITS rRNA genes to explore which factor(s) controlled soil microbial (i.e., bacteria and fungi) richness and diversity in a 25-ha karst broadleaf forest in Southwest China. Across the plot, all bacterial and fungal richness (number of OTUs) and diversity indices (Shannon diversity and phylogenetic diversity) showed strong spatial autocorrelations. Soil microbial richness and diversity indices displayed a unimodal pattern from south to north in the karst forest, with peaks in the low and middle areas of the plot. Slope was found to be the best predictor of soil bacterial and fungal richness and diversity indices. Soil pH was negatively related with bacterial richness, and with bacterial and fungal phylogenetic diversity. Tree Shannon diversity and density together explained much of the variations in fungal OTUs and diversity indices. Spatial factors explained much less of the variation in soil microbial richness and diversity indices than the selected environmental variables, which indicated that habitat heterogeneity rather than dispersal limitation played an important role in soil microbial richness and diversity in the karst forest. In conclusion, slope was the major driver of the spatial distribution of soil microbial richness and diversity in the karst forest due to its effects on plant (i.e., tree Shannon diversity and tree density) and soil characteristics (i.e., soil pH and available phosphorus).

Spatial patterns and drivers of soil microbial communities have not yet been well documented. Here, we used geostatistical modeling and Illumina sequencing of 16S rRNA genes to explore how the main microbial taxa at the phyla level are spatially distributed in a 25-ha karst broadleaf forest in southwest China. Proteobacteria, dominated by Alpha- and Deltaproteobacteria, was the most abundant phylum (34.51%) in the karst forest soils. Other dominating phyla were Actinobacteria (30.73%), and Acidobacteria (12.24%). Soil microbial taxa showed spatial dependence with an autocorrelation range of 44.4-883.0 m, most of them within the scope of the study plots (500 m). An increasing trend was observed for Alphaproteobacteria, Deltaproteobacteria, and Chloroflexi from north to south in the study area, but an opposite trend for Actinobacteria, Acidobacteira, and Firmicutes was observed. Thaumarchaeota, Bacteroidetes, Gemmatimonadetes, and Verrucomicrobia had patchy patterns, Nitrospirae had a unimodal pattern, and Latescibacteria had an intermittent pattern with low and high value strips. Location, soil total phosphorus, elevation, and plant density were significantly correlated with main soil bacterial taxa in the karst forest. Moreover, the total variation in soil microbial communities better explained by spatial factors than environmental variables. Furthermore, a large part of variation (76.8%) was unexplained in the study. Therefore, our results suggested that dispersal limitation was the primary driver of spatial pattern of soil microbial taxa in broadleaved forest in karst areas, and other environmental variables (i.e., soil porosity and temperature) should be taken into consideration.

Land-use change can have great influences on soil conditions and microbes are likely respond to these changes. However, such responses are poorly characterized as few studies have examined how changes in soil microbes do, or do not, correlate with environmental factors across land-use types. Soil microbial, conventional, and mineral properties and vegetation were investigated and analyzed under farmland, grassland, brush, plantation forest, secondary forest, and primary forest in the karst region of southwest China. Soil main microbial populations varied among land-use types, total populations were large in the primary forest and farmland, and low in the plantation forest. The three forests had a higher proportion of bacteria, and other types had a higher proportion of actinomycetes, while all the types had a low proportion of fungi. Soil microbial biomass carbon (MBC), nitrogen (MBN), and phosphorus (MBP) were highest in primary forest. Only MBC and microbial populations had a perfect fractal relationship. MBC had closest relationships with Shannon index in tree layer and TN, Fe2O3, and CaO. Soil microbial biomass was high, while microbial status was perfect in the primary forest. Microorganisms were significantly correlated with vegetation, soil nutrients, and minerals following land utilization types in the karst region of China.

This paper introduces Chinese urban forestry research in terms of the concept, forest types, ecosystem services, spatial structure, planning and construction, assessment and management. Modern Chinese urban forest had a close relationship with traditional landscape architecture. Urban forest services had been quantified in some case cities, and determined by urban forest spatial patterns and internal structures. Based on landscape ecology and urban planning, urban forest spatial patterns have been analysed and planned rationally in some cities. However, studies on urban forestry generally lack long-term, continuous and systemic observations, as well as in-depth research on ecological processes and mechanisms. The development trends in urban forestry in China might include extensive application of '3S' technology, research on the relationship between urban forest landscape spatial patterns and their ecological effects, economic assessment, ecological and economic benefits and studies on the negative effects of pollutants.