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Abstract This study investigated seasonal patterns in stoichiometric ratios, nutrient resorption characteristics, and nutrient use strategies of dominant tree species at three successional stages in subtropical China, which have not been fully understood. Fresh leaf and leaf litterfall samples were collected in growing and nongrowing seasons for determining the concentrations of carbon (C), nitrogen (N), and phosphorus (P). Then, stoichiometric ratios (i.e., C:N, C:P, N:P, and C:N:P) and resorption parameters were calculated. Our results found that there was no consistent variation in leaf C:N and C:P ratios among different species. However, leaf N:P ratios in late‐successional species became significantly higher, indicating that P limitation increases during successional development. Due to the P limitation in this study area, P resorption efficiency and proficiency were higher than corresponding N resorption parameters. Dominant tree species at early‐successional stage adopted “conservative consumption” nutrient use strategy, whereas the species at late‐successional stage inclined to adopt “resource spending” strategy.

The study was to investigate the change patterns of soil organic carbon (SOC), total nitrogen (TN), and soil C/N (C/N) in each soil sublayer along vegetation restoration in subtropical China. We collected soil samples in four typical plant communities along a restoration chronosequence. The soil physicochemical properties, fine root, and litter biomass were measured. Our results showed the proportion of SOC stocks (Cs) and TN stocks (Ns) in 20–30 and 30–40 cm soil layers increased, whereas that in 0–10 and 10–20 cm soil layers decreased. Different but well-constrained C/N was found among four restoration stages in each soil sublayer. The effect of soil factors was greater on the deep soil than the surface soil, while the effect of vegetation factors was just the opposite. Our study indicated that vegetation restoration promoted the uniform distribution of SOC and TN on the soil profile. The C/N was relatively stable along vegetation restoration in each soil layer. The accumulation of SOC and TN in the surface soil layer was controlled more by vegetation factors, while that in the lower layer was controlled by both vegetation factors and soil factors.

Abstract Ecosystem-level effects of increasing atmospheric nitrogen (N) deposition on the phosphorus (P) cycle and P use strategy are poorly understood. Here, we conducted a seven year N-addition experiment to comprehensively evaluate the effects of N deposition on P limitation, cycling, and use strategy in a subtropical Moso bamboo forest. N addition significantly increased foliar litterfall by 4.7%–21.7% and subsequent P return to the soil by 49.0%–70.1%. It also increased soil acidity, acid phosphatase activity, and soil microbial biomass P, which substantially contributed to a significantly increased soil P availability and largely alleviated the P limitation. This resulted in a significant decrease in the foliar P-resorption efficiency and the abundance and colonization of arbuscular mycorrhizal fungi. Our results indicate that N deposition can reduce plant internal cycling while enhancing ecosystem-scale cycling of P in Moso bamboo forests. This suggests a shift in P use from a ‘conservative consumption’ strategy to a ‘resource spending’ strategy. Our findings shed new light on N deposition effects on P cycle processes and P use strategy at the ecosystem scale under increasing atmospheric N deposition.

Evergreen broadleaved forests in subtropical China contain a complicated structure of diverse species. The impact of topographic and soil factors on the assembly of woody species in the forest has been poorly understood. We used Ripley’s K(t) function to analyze the spatial patterns and associations of dominant species and residual analysis (RDA) to quantify the contribution of topography and soil to species assembly. The 1 ha plot investigated had 4797 stems with a diameter at breast height (dbh) larger than 1 cm that belong to 73 species, 55 genera, and 38 families. All stems of the entire forest and four late successional species exhibited a reversed J shape for dbh distribution, while two early successional species showed a unimodal shape. Aggregation was the major spatial pattern for entire forests and dominant species across vertical layers. Spatial associations between inter- and intra-species were mostly independent. Topographic and soil factors explained 28.1% of species assembly. The forest was close to late succession and showed the characteristics of diverse woody species, high regeneration capacity, and aggregated spatial patterns. Topographic and soil factors affected species assembly, but together they could only explain a small part of total variance.

Abstract Applying allometric equations in combination with forest inventory data is an effective approach to use when qualifying forest biomass and carbon storage on a regional scale. The objectives of this study were to (1) develop general allometric tree component biomass equations and (2) investigate tree biomass allocation patterns for Pinus massoniana , a principal tree species native to southern China, by applying 197 samples across 20 site locations. The additive allometric equations utilized to compute stem, branch, needle, root, aboveground, and total tree biomass were developed by nonlinear seemingly unrelated regression. Results show that the relative proportion of stem biomass to tree biomass increased while the contribution of canopy biomass to tree biomass decreased as trees continued to grow through time. Total root biomass was a large biomass pool in itself, and its relative proportion to tree biomass exhibited a slight increase with tree growth. Although equations employing stem diameter at breast height (dbh) alone as a predictor could accurately predict stem, aboveground, root, and total tree biomass, they were poorly fitted to predict the canopy biomass component. The inclusion of the tree height ( H ) variable either slightly improved or did not in any way increase model fitness. Validation results demonstrate that these equations are suitable to estimate stem, aboveground, and total tree biomass across a broad range of P . massoniana stands on a regional scale.

Moso bamboo forests have greater net carbon uptake benefits with increasing nitrogen deposition in the coming decades. , Atmospheric nitrogen (N) deposition affects the greenhouse gas (GHG) balance of ecosystems through the net atmospheric CO 2 exchange and the emission of non-CO 2 GHGs (CH 4 and N 2 O). We quantified the effects of N deposition on biomass increment, soil organic carbon (SOC), and N 2 O and CH 4 fluxes and, ultimately, the net GHG budget at ecosystem level of a Moso bamboo forest in China. Nitrogen addition significantly increased woody biomass increment and SOC decomposition, increased N 2 O emission, and reduced soil CH 4 uptake. Despite higher N 2 O and CH 4 fluxes, the ecosystem remained a net GHG sink of 26.8 to 29.4 megagrams of CO 2 equivalent hectare −1 year −1 after 4 years of N addition against 22.7 hectare −1 year −1 without N addition. The total net carbon benefits induced by atmospheric N deposition at current rates of 30 kilograms of N hectare −1 year −1 over Moso bamboo forests across China were estimated to be of 23.8 teragrams of CO 2 equivalent year −1 .

Abstract. Leaf area index (LAI) is an important parameter related to carbon, water, and energy exchange between canopy and atmosphere and is widely applied in process models that simulate production and hydrological cycles in forest ecosystems. However, fine-scale spatial heterogeneity of LAI and its controlling factors have yet to be fully understood in Chinese subtropical forests. We used hemispherical photography to measure LAI values in three subtropical forests (Pinus massoniana–Lithocarpus glaber coniferous and evergreen broadleaved mixed forests, Choerospondias axillaris deciduous broadleaved forests, and L. glaber–Cyclobalanopsis glauca evergreen broadleaved forests) from April 2014 to January 2015. Spatial heterogeneity of LAI and its controlling factors were analysed using geostatistical methods and the generalised additive models (GAMs) respectively. Our results showed that LAI values differed greatly in the three forests and their seasonal variations were consistent with plant phenology. LAI values exhibited strong spatial autocorrelation for the three forests measured in January and for the L. glaber–C. glauca forest in April, July, and October. Obvious patch distribution pattern of LAI values occurred in three forests during the non-growing period and this pattern gradually dwindled in the growing season. Stem number, crown coverage, proportion of evergreen conifer species on basal area basis, proportion of deciduous species on basal area basis, and forest types affected the spatial variations in LAI values in January, while stem number and proportion of deciduous species on basal area basis affected the spatial variations in LAI values in July. Floristic composition, spatial heterogeneity, and seasonal variations should be considered for sampling strategy in indirect LAI measurement and application of LAI to simulate functional processes in subtropical forests.