Subtropical Forests In China Research Articles

Strip clear-cutting transformations increase soil N2O emissions in abandoned Moso bamboo forests

Forest transformation can markedly impact soil greenhouse gas emissions and soil environmental factors. Due to increasing labor costs and declining bamboo prices, the abandonment of Moso bamboo forests is sharply escalating in recent years, which weakens the carbon sequestration capacity and decreases the ecological function of forests. To improve the ecological quality of abandoned Moso bamboo forests, transformations of abandoned bamboo forests have occurred. However, the impact of such transformations on N2O emissions remains elusive. To bridge the knowledge gap, we conducted a 23-month field experiment to compare the effects of various forest management practices on soil N2O emissions and soil environmental factors in abandoned Moso bamboo forests in subtropical China. These practices included uncut abandonment as a control, intensive management, three intensities (light, moderate, and heavy) of strip clear-cutting with replanting local tree species, and clear-cutting with replanting transformation. During the experimental period, the mean soil N2O flux in abandoned Moso bamboo forests was 13.2 ± 0.1 μg m-2 h-1, representing a 44% reduction compared to intensive management forests. In comparison to the uncut control, light, moderate, and heavy strip clear-cutting and clear-cutting transformations increased soil N2O emission rates by 20%, 43%, 64%, and 94%, respectively. Soil temperature (69-71%), labile C (2-6%) and N (3-8%) were the main factors that explain N2O emissions following the transformation of abandoned Moso bamboo forests. Additionally, replanting could decrease soil N2O emissions by increasing the contribution of soil moisture. Overall, the light strip clear-cutting transformation is suggested to convert abandoned Moso bamboo forests to mitigate N2O emissions.

Constant isometric scaling of soil carbon to nitrogen in Moso bamboo-invaded evergreen broadleaf forests in subtropical China

Constant isometric scaling of soil carbon to nitrogen in Moso bamboo-invaded evergreen broadleaf forests in subtropical China

Phylogeographic patterns match the floristic subdivisions: The diversification history of a widespread herb in subtropical China.

Subtropical China is dominated by evergreen broad-leaved forests (EBLFs) and is acknowledged as a critical region for its high floristic richness and endemism. Understanding of evolutionary mechanisms of such global biodiversity hotspots comes almost exclusively from long-lived tree species. Herbaceous plants represent critical biodiversity components in forests, however, the diversification history of understory herbs in subtropical EBLFs remain poorly understood. Here, we investigated the phylogeographic patterns and demographic history of Oreocharis auricula, a widespread perennial herb endemic to the EBLFs of subtropical China. Both cpDNA sequences and single-copy nuclear genes were used to investigate the genetic variation among 657 individuals from 68 populations. Evidences from molecular dating, demographic history construction, and species distribution modeling were also combined to infer the phylogeography and evolutionary history of O. auricula. Strong phylogeographic signals have been congruently observed using nuclear and plastid DNA markers, with the diversification patterns generally consistent with the recognized floristic subdivisions of subtropical China. Notably, we revealed an important phylogeographic barrier along the Nanling mountain range, which is also around a climatic transition at 24-26°N latitude in subtropical China, separating the south monsoon subtropical EBLFs from the mid-subtropical EBLFs. Demographic expansion and significant niche divergence were detected among the extant lineages, which may have diverged during the early Pleistocene. The inherent characteristics of understory herbs with limited dispersal and short generation time intensify the genetic divergence response of O. auricula to abiotic forces, contributing to the profound phylogeographic imprints of mountains and climate in such herbaceous flora. To further substantiate the generality of the identified patterns, it is paramount to extend phylogeographic investigations to other understory herbaceous taxa in subtropical China. These results have expanded our understanding of the diversification processes of subtropical forests in China.

Autumn phenology consistently delays in subtropical forests in China based on a new process-based model integrating temperature, photoperiod and precipitation

Abstract Climate warming has delayed vegetation autumn phenology, which in turn influences terrestrial carbon and water cycles and their feedback to the climate. However, the performance of autumn phenology models, especially for subtropical forests, remains poor. In this study, we extracted the end-of-photosynthetic-growing-season (EOPS) dates in subtropical China over the period 2001-2018 based on high-resolution solar-induced chlorophyll fluorescence (SIF) dataset using three fitting methods. We developed a new autumn phenology model (DMP model) that integrates precipitation and photoperiod into the classic cold-degree days model, and the new model outperformed the classic model reducing the RMSE by approximately 2 days. We found that the EOPS date was delayed by an average of 4.1 days per decade in the subtropical forests of China from 2001 to 2018, and the precipitation (partial correlation coefficient, r = 0.45), rather temperature (r = 0.29) determined the EOPS processes. We further studied future EOPS using the DMP model and found the EOPS will delay by 1.0 days per decade under the SSP2-4.5 scenario and 2.7 days per decade under the SSP5-8.5 scenario from 2030 to 2100. Our study highlighted the role of precipitation in regulating EOPS in the subtropical forests of China and provided valuable insight for integrating multiple climatic determinants into autumn phenology models.

Thinning alters nitrogen transformation processes in subtropical forest soil: Key roles of physicochemical properties

Thinning—a widely used forest management practice—can significantly influence soil nitrogen (N) cycling processes in subtropical forests. However, the effects of different thinning intensities on nitrification, denitrification, and their relationships with soil properties and microbial communities remain poorly understood. Here, we conducted a study in a subtropical forest in China and applied three thinning treatments, i.e., no thinning (0 %), intermediate thinning (10–15 %), and heavy thinning (20–25 %), and investigated the effects of thinning intensity on the potential nitrification rate (PNR), potential denitrification rate (PDR), and microbial communities. Moreover, we explored the relationships among soil physicochemical properties, microbial community structure, and nitrogen transformation rates under different thinning intensities. Our results showed that intermediate and heavy thinning significantly increased the PNR by 87 % and 61 % and decreased the PDR by 31 % and 50 % compared to that of the control, respectively. Although the bacterial community structure was markedly influenced by thinning, the fungal community structure remained stable. Importantly, changes in microbial community composition and diversity had minimal impacts on the nitrogen transformation processes, whereas soil physicochemical properties, such as pH, organic carbon content, and nitrogen forms, were identified as the primary drivers. These findings highlight the critical role of managing soil physicochemical properties to regulate nitrogen transformations in forest soils. Effective forest management should focus on precisely adjusting the thinning intensity to enhance the soil physicochemical conditions, thereby promoting more efficient nitrogen cycling and improving forest ecosystem health in subtropical regions.

Forest Structure Regulates Response of Erosion-Induced Carbon Loss to Rainfall Characteristics

Forestation is a common measure to control erosion-induced soil and carbon (C) loss, but the effect can vary substantially between different types of forest. Here, we measured event-based runoff, soil, dissolved organic carbon (DOC), particulate organic carbon (POC) and total C loss with runoff plots (20 m × 5 m) in a broad-leaved and a coniferous forest in subtropical China and explored their relationships with rainfall amount, average intensity, maximum 5-min intensity and rainfall erosivity. The broad-leaved forest had a denser canopy but sparse understory vegetation while the coniferous forest had a relatively open canopy but dense understory vegetation. The results showed that runoff, soil, DOC, POC and total C losses were all significantly higher in the broad-leaved forest than the coniferous forest despite the potentially higher canopy interception associated with the greater leaf area index of the broad-leaved forest. The mean runoff in the broad-leaved forest was 3.03 ± 0.20 m3 ha−1 event−1 (mean ± standard error) and 12.49 ± 0.18 m3 ha−1 event−1 in the coniferous forest. The mean soil, DOC, POC and total C loss (kg ha−1 event−1) was 1.12 ± 0.16, 0.045 ± 0.003, 0.118 ± 0.016 and 0.163 ± 0.017, respectively, in the broad-leaved forest and 0.66 ± 0.09, 0.020 ± 0.002, 0.060 ± 0.009 and 0.081 ± 0.010, respectively, in the coniferous forest. Runoff and DOC losses were driven by rainfall in two forests, but the key rainfall characteristic driving soil, POC and total C losses was different in the broad-leaved forest from that in the coniferous forest due to their different understory patterns. Soil, POC and total C losses were mostly driven by rainfall amount in the broad-leaved forest but by EI30 in the conifer forest. Our findings highlight that the response of erosion-induced carbon loss to rainfall characteristics differs between different forest types of the same age but contrasting overstory and understory vegetation covers. Moreover, our study underscores the overlooked significance of understory vegetation in regulating these effects. Thus, we call for the inclusion of understory vegetation in the modeling of soil and carbon erosion in forest ecosystems.

Influence of Slope Aspect and Position on Xylem Formation Dynamics in Subtropical Chinese Fir Plantations

Recent studies on the intra-annual dynamics of trees were mainly focused on mature trees in natural forests; however, less is known about how topography (e.g., slope’s position and aspect) shape the intra-annual xylem formation dynamics of young trees in plantation forests. We monitored intra-annual xylem formation dynamics of 6-year-old Chinese fir (Cunninghamia lanceolata (Lamb.)) trees across two different aspects (northeast and southwest) and three different positions (upper, middle, and lower) of the slope in a planted forest in subtropical China. We found that the intra-annual xylem formation of trees on the northeast slope aspect (176.98 ± 34.52 cells) was significantly higher than that on the southwest slope aspect (140.19 ± 36.07 cells) due to the higher growth rate (0.67 ± 0.11 cells/day vs. 0.53 ± 0.10 cells/day). In the middle slope position, xylem formation (187.89 ± 19.81 cells) was also significantly higher than that of the upper (147.35 ± 29.08 cells) and lower slope positions (140.51 ± 48.36 cells), resulting from higher growth rate rather than longer growing season length. Our study demonstrated that intra-annual xylem formation dynamics of Chinese fir were altered by different topographic features and therefore encourage the implementation of management strategies that consider different slope aspects and positions to maximize forest productivity.

Genetic Differentiation and Relationship among Castanopsis chinensis, C. qiongbeiensis, and C. glabrifolia (Fagaceae) as Revealed by Nuclear SSR Markers.

Castanopsis chinensis (Spreng.) Hance is widespread in the subtropical forests of China. Castanopsis qiongbeiensis G.A. Fu and Castanopsis glabrifolia J. Q. Li & Li Chen are limited to the coastal beaches of Wenchang county in the northeast of Hainan Island, and have similar morphological characteristics to C. chinensis. It is supposed that C. qiongbeiensis and C. glabrifolia are closely related to C. chinensis. In the present study, the genetic differentiation, gene flow, and genetic relationship of C. chinensis, C. qiongbeiensis, and C. glabrifolia were investigated by using 15 nuclear microsatellite markers; a total of 308 individuals from 17 populations were sampled in the three species. The allelic variation of nuclear microsatellites revealed moderate but significant genetic differentiation (FCT = 0.076) among C. chinensis, C. qiongbeiensis, and C. glabrifolia, and genetic differentiation between C. chinensis and C. glabrifolia was larger than that between C. chinensis and C. qiongbeiensis. Demographic simulations revealed unidirectional gene flow from C. chinensis to C. glabrifolia and C. qiongbeiensis, which highlight dispersal from mainland to island. The isolation effect of Qiongzhou Strait increased the genetic differentiation of species on both sides of the strait; however, the differentiation was diminished by gene flow that occurred during the historical period when Hainan Island was connected to mainland China. Our results supported the argument that C. glabrifolia should be considered an independent species and argued that C. qiongbeiensis should be regarded as an incipient species and independent conservation unit.

Comparative Analysis of Machine Learning-Based Predictive Models for Fine Dead Fuel Moisture of Subtropical Forest in China

The moisture content of fine dead surface fuel in forests is a crucial metric for assessing its combustibility and plays a pivotal role in the early warning, occurrence, and spread of forest fires. Accurate prediction of the moisture content of fine dead fuel on the forest surface is a critical challenge in forest fire management. Previous research on fine surface fuel moisture content has been mainly focused on coniferous forests in cold temperate zones, but there has been less attention given to understanding the fuel moisture dynamics in subtropical forests, which limits the development of regional forest fire warning models. Here, we consider the coupled influence of multiple meteorological, terrain, forest stand, and other characteristic factors on the fine dead fuel moisture content within the subtropical evergreen broadleaved forest region of southern China. The ability of five machine learning algorithms to predict the moisture content of fine dead fuel on the forest surface is assessed, and the key factors affecting the model accuracy are identified. Results show that when a single meteorological factor is used as a forecasting model, its forecasting accuracy is less than that of the combined model with multiple characteristic factors. However, the prediction accuracy of the model is improved after the addition of forest stand factors and terrain factors. The model prediction ability is the best for the combination of all feature factors including meteorology, forest stand, and terrain. The overall prediction accuracy of the model is ordered as follows: random forest > extreme gradient boosting > support vector machine > stepwise linear regression > k-nearest neighbor. Canopy density in forest stand factors, slope position and altitude in terrain factors, and average relative air humidity and light intensity in the previous 15 days are the key meteorological factors affecting the prediction accuracy of fuel moisture content. Our results provide scientific guidance and support for understanding the variability of forest surface fuel moisture content and improved regional forest fire warnings.

Species-specific and generalized allometric biomass models for eight Fagaceae species in the understory of evergreen broadleaved forests in subtropical China

Species-specific and generalized allometric biomass models for eight Fagaceae species in the understory of evergreen broadleaved forests in subtropical China

2010–2014年哀牢山亚热带常绿阔叶林土壤呼吸数据集

Subtropical forests, as the largest forest type in China, play an important role in regulating global climate change and maintaining atmospheric carbon balance. The carbon emitted by soil through respiration is the main contributor of atmospheric CO2 levels, so even slight changes in soil carbon pool can significantly affect the concentration of atmospheric CO2. Therefore, at present, the magnitude and dynamic change characteristics of soil carbon storage in subtropical forests are attached great importance to. Ailao Mountain in Yunan Province stands as a crucial region for the distribution of subtropical forests in China. This study used a multichannel automated chamber system to estimate soil respiration in a subtropical evergreen broad-leaved forest ecosystem of Ailao Mountain. Ailao Mountain Station for Subtropical Forest Ecosystem Studies is a national field station and a basic observation station of the Chinese Ecosystem Research Network. We gathered soil respiration data from the subtropical evergreen broad-leaved forest in Ailao Mountain from 2011 to 2014, including soil temperature 5cm (TS), soil moisture content 10cm (SWC) and soil respiration data (RS), organized at daily, monthly and annual scales. This dataset is of great significance in revealing the effects of climate change on soil ecological processes in subtropical evergreen broad-leaved forests. It can facilitate precise evaluation of soil organic carbon emissions and forest ecosystem management, and provide both empirical and theoretical basis for further research on the effects of global changes (e.g. climate warming) on soil respiration components, especially with a focus on soil organic carbon emissions.

Model Exploration and Application of Near-Infrared Spectroscopy for Species Separation and Quantification during Mixed Litter Decomposition in Subtropical Forests of China

Litter of different species coexists in the natural ecosystem and may induce non-additive effects during decomposition. Identifying and quantifying the origins of species in litter mixtures is essential for evaluating the responses of each component species when mixed with co-occurring species and then unraveling the underlying mechanism of the mixing effects of litter decomposition. Here, we used near-infrared spectroscopy (NIRS) to predict the species composition and proportions of four-tree species foliage mixtures in association with litter crude ash and litter decomposition time. To simulate the whole mixed litter decomposition process in situ, a controlled mixture of four tree species litter leaves consisting of 15 tree species combinations and 193 artificial mixed-species samples were created for model development and verification using undecomposed pure tree species and decomposed litter of single tree species over one year. Two series of NIRS models were developed with the original mass and ash-free weight as reference values. The results showed that these NIRS models could provide an accurate prediction for the percentage of the component species from in the litter leaf mixture’s composition. The predictive ability of the near-infrared spectroscopy model declined marginally with the prolonged litter decomposition time. Furthermore, the model with ash-free litter mass as a reference exhibited a higher coefficient of determination (R2) and a lower standard error of prediction (RMSECV). Thus, our results demonstrate that NIRS presents great potential for not only predicting the organic composition and proportion in multi-species mixed samples in static conditions, but also for samples in dynamic conditions (i.e., during the litter decomposition process), which could facilitate evaluation of the species-specific responses and impacts on the interspecific interactions of co-occurring species in high-biodiversity communities.

How does position affect the decomposition of fine woody debris in subtropical forest?

Fine woody debris (FWD: 1 cm ≤ diameter ≤ 10 cm) may be intercepted by understory vegetation (including the branches of canopy trees). However, the decay dynamics of aerial FWD are often overlooked. In this study, we collected wood from four different tree species (Platycarya strobilacea, Lithocarpus glaber, Pinus massoniana, and Cryptomeria japonica) from four forests in subtropical China, and the mesh bag method was used to measure the remaining mass and microbial respiration by reciprocally transplanting mesh bags filled with different species among the four forests. The main objectives of this study were to reveal the influence of position (the ground and the air) on the decay rates of FWD and the home-field advantage (HFA) effect during a two-year experimental period. Irrespective of the experimental periods and decay fields, the mass loss of FWD was significantly higher on the ground (58.05%) than in the air (45.74%), and the microbial respiration of wood was significantly higher on the ground (18.87 μg CO2 h−1 g−1) than in the air (7.79 μg CO2 h−1 g−1). Microbial respiration was negatively correlated with wood remaining mass on the ground during the entire decay period and in the air only during the late decay period. The HFA effect was observed only on the ground (5.03–23.86%). Our study highlights that soil contact predominantly regulated the decomposition patterns and the HFA effect of fine woody debris and suggests that we should not neglect the decay of fine woody debris in the air due to the interception of understory vegetation in subtropical Chinese forests.

Enhanced home-field advantage in deep soil organic carbon decomposition: Insights from soil transplantation in subtropical forests

Climate change affects microbial community physiological strategies and thus regulates global soil organic carbon (SOC) decomposition. However, SOC decomposition by microorganisms, depending on home-field advantage (HFA, indicating a faster decomposition rate in ‘Home’ than ‘Away’ conditions) or environmental advantage (EA, indicating a faster decomposition rate in warmer-wetter environments than in colder-drier environments) remains unknown. Here, a soil transplantation experiment was conducted between warmer-wetter and colder-drier evergreen broadleaved forests in subtropical China. Specifically, soil samples were collected along a 60 cm soil profile, including 0–15, 15–30, 30–45, and 45–60 cm layers after one year of transplantation. SOC fractions, soil chemical properties, and microbial communities were evaluated to assess where there was an HFA of EA in SOC decomposition, along with an exploration of internal linkages. Significant HFAs were observed, particularly in the deep soils (30–60 cm) (P < 0.05), despite the lack of a significant EA along a soil profile, which was attributed to environmental changes affecting soil fungal communities and constraining SOC decomposition in ‘Away’ conditions. The soils transplanted from warmer-wetter to colder-drier environments changed the proportions of Mortiereltomycota or Basidiomycota fungal taxa in deep soils. Furthermore, the shift from colder-drier to warmer-wetter environments decreased fungal α-diversity and the proportion of fungal necromass carbon, ultimately inhibiting SOC decomposition in ‘Away’ conditions. However, neither HFAs nor EAs were significantly present in the topsoil (0–30 cm), possibly due to the broader adaptability of bacterial communities in these layers. These results suggest that the HFA of SOC decomposition in deep soils may mostly depend on the plasticity of fungal communities. Moreover, these results highlight the key roles of microbial communities in the SOC decomposition of subtropical forests, especially in deep soils that are easily ignored.

Nitrogen deposition-induced stimulation of soil heterotrophic respiration is counteracted by biochar in a subtropical forest

Both atmospheric nitrogen (N) deposition and biochar application can markedly impact soil heterotrophic respiration (RH), an important component of the global carbon cycle. However, the interactive effects of N deposition and biochar application on soil RH in subtropical forest ecosystems remain unclear. Here, we conducted a three-year (2019–2022) field trial within a bamboo forest in subtropical China to examine the responses of soil physicochemical and microbial properties to N deposition and biochar application, and to elucidate how biochar regulates N deposition-induced change in soil RH. Nitrogen deposition stimulated soil RH by 8.1–9.8 % annually over three years compared to the control, and this stimulation was mitigated (by 8.1–8.9 % annually) with biochar addition. In the context of N deposition, the decrease of soil RH by biochar application was not through changing soil temperature, moisture or labile organic carbon content. Biochar treatment reduced the abundances of bacterial glycoside hydrolase family 48 gene (GH48) and fungal glycoside hydrolase family 7 cellobiohydrolase I gene (cbhI) and the activities of β-glucosidase and cellobiohydrolase (CBH), but increased the abundance of cbbL gene and activity of RubisCO enzyme. Furthermore, the RH was correlated positively (P < 0.01) with β-glucosidase and CBH activities and negatively (P < 0.01) with RubisCO enzyme activity. Structural equation modeling revealed that the biochar-induced reduction of soil RH under N deposition was associated with decreases in the abundance of cbhI gene and the activity of CBH in soils. We highlight that management practices can mitigate soil carbon loss in forests through modulating soil microbial functions under atmospheric N deposition, and that biochar application in Moso bamboo forests has the potential to reduce RH by approximately 7.6 × 106 t CO2 yr−1 under atmospheric N deposition.

Diurnal, Seasonal, and Vertical Changes in Photosynthetic Rates in Cinamomum camphora Forests in Subtropical China

The increase in the global atmospheric CO2 concentration is expected to increase the productivity of forests, but the dynamic processes of such increased productivity in the forest canopy remain unclear. In this study, diurnal and seasonal variations and vertical changes in photosynthetic rates were investigated in Camphor tree (Cinnamomum camphora) forests in subtropical China. The effect of photosynthetically active radiation (PAR) and CO2 concentrations on photosynthetic rates were also examined in the studied forests. Results showed the diurnal patterns of photosynthesis exhibited two peaks on sunny days, but only one peak on cloudy days. The daily average photosynthetic rate on cloudy days was approximately 74% of that on sunny days. The photosynthetic rate decreased along the vertical forest canopy profile. If the photosynthetic rate in the upper canopy layer was 100%, the corresponding rates were 83% and 25% in the middle and lower canopy layers, respectively. The rates of dark respiration derived from the PAR response curve were 1.73, 1.25, and 1.0 µmol m−2 s−1 for the upper, middle, and lower canopy layers, respectively. The apparent quantum yield of photosynthesis was 0.0183, 0.0186, and 0.0327 µmol CO2 µmol−1 PAR for the upper, middle, and lower canopy, respectively. The initial slope of the photosynthetic response curve to CO2 was highest in the upper canopy and lowest in the lower canopy. The seasonal variation in photosynthetic rates exhibited a two-peaked pattern at all canopy positions, with the two peaks occurring in June and September. The stand biomass and biomass carbon storage were 144.7 t ha−1 and 71.6 t C ha−1 in the examined forests, respectively. The study provides a scientific reference for future research on accessing carbon sequestration and designing forest management practices, specifically in regulating canopy structure in subtropical regions.

Revealing Three-Dimensional Variations in Fuel Structures in Subtropical Forests through Backpack Laser Scanning

Wildfire hazard is a prominent issue in subtropical forests as climate change and extreme drought events increase in frequency. Stand-level fuel load and forest structure are determinants of forest fire occurrence and spread. However, current fuel management often lacks detailed vertical fuel distribution, limiting accurate fire risk assessment and effective fuel policy implementation. In this study, backpack laser scanning (BLS) is used to estimate several 3D structural parameters, including canopy height, crown base height, canopy volume, stand density, vegetation area index (VAI), and vegetation coverage, to characterize the fuel structure characteristics and vertical density distribution variation in different stands of subtropical forests in China. Through standard measurement using BLS point cloud data, we found that canopy height, crown base height, stand density, and VAI in the lower and middle-height strata differed significantly among stand types. Compared to vegetation coverage, the LiDAR-derived VAI can better show significant stratified changes in fuel density in the vertical direction among stand types. Among stand types, conifer-broadleaf mixed forest and C. lanceolata had a higher VAI in surface strata than other stand types, while P. massoniana and conifer-broadleaf mixed forests were particularly unique in having a higher VAI in the lower and middle-height strata, corresponding to the higher surface fuel and ladder fuel in the stand, respectively. To provide more informative support for forest fuel management, BLS LiDAR data combined with other remote sensing data were advocated to facilitate the visualization of fuel density distribution and the development of fire risk assessment.

Spatiotemporal patterns of net primary productivity of subtropical forests in China and its response to drought

Net primary productivity (NPP) is an important indicator used to evaluate the carbon sequestration capacity of forest ecosystems. Subtropical forest ecosystems play an indispensable role in maintaining the global carbon balance, while frequently occurring drought events in recent years have seriously damaged their productivity. However, the spatiotemporal patterns of NPP, as well as its response to drought, remain uncertain. In this study, the multiscale drought characteristics in subtropical China during 1981–2015 were analyzed based on the standardized precipitation evapotranspiration index. Then, simulated and analyzed the spatiotemporal NPP of subtropical forests by the boreal ecosystem productivity simulator model. Finally, the response of NPP to drought was analyzed based on multiple statistical indices. The results show that most regions in subtropical China experienced mild and moderate drought during 1981–2015. In particular, the extent of drought severity has shown a noticeable increasing trend after 2000. The forest NPP ranged from 622.64 to 1323.82 gC·m−2·a−1, with an overall increase rate of 16.15 gC·m−2·a−1; in particular, the contribution of the western forest NPP became increasingly important. Drought stress has limited the growth of subtropical forest NPP in China, with summer and wet season time scales of drought having the greatest impact on forest NPP anomalies, followed by autumn time scales. The limitation is mostly because the drought duration continually increased, leading to differences in the impact of drought on forest NPP before and after 2000, with declines of 59.55 % and 82.45 %, respectively, mainly concentrated in southwestern regions, such as Yunnan, Guangxi, and Sichuan provinces. This study quantitatively analyzed the impact of drought on subtropical forest NPP, and provides scientific basis for subtropical forest response and adaptation to climate change.

Tight relationships between leaf and topsoil stoichiometries after 42 years of forest conversion from old-growth forests to Chinese fir plantations

Soil C:N:P stoichiometry can regulate plant survival and reflect soil fertility and nutrient utilization. Despite the widespread conversion of old-growth forests to plantations or secondary forests, there is little knowledge about how these conversions affect the relation between leaf and soil stoichiometries. We examined the topography, leaf, and soil stoichiometries of 75 plots (20 m × 20 m) across Chinese fir plantations, secondary forests, and old-growth forests in subtropical China. We found that: (1) There were significant differences in leaf carbon, nitrogen, phosphorus, and their stoichiometry ratios among different stand types (2) stand type significantly affected soil SOC, TP, C:N, C:P, and N:P, except TN and (3) the explanation percentage of leaf stoichiometry on soil stoichiometry doubled with the conversion of old-growth forest to Chinese fir plantation, whereas it was twofold decreased with the conversion of old-growth forest to secondary forest. The explanation percentage of topography on soil stoichiometry decreased onefold at a minimum with the conversion of the old-growth forest to the Chinese fir plantation or the secondary forest. Our results show the shortages of soil nutrients from transforming old-growth forests into plantations or secondary forests and indicate the urgent need to preserve the remaining old-growth forests and increase stand ages by reducing forest disturbances. Therefore, determining the optimal stand type and slope location can effectively promote the accumulation of carbon, nitrogen, and phosphorus nutrients in the topsoil, which is essential for improving the planning and implementation of appropriate forest restoration and ecosystem management strategies.

Soil bacterial and fungal communities resilience to long-term nitrogen addition in subtropical forests in China

Atmospheric nitrogen (N) deposition is predicted to increase, especially in the subtropics. However, the responses of soil microorganisms to long-term N addition at the molecular level in N-rich subtropical forests have not been clarified. A long-term nutrient addition experiment was conducted in a subtropical evergreen old-growth forest in China. The four treatments were: control, low N (50 kg N ha−1 a−1), high N (100 kg N ha−1 a−1), and combined N and phosphorus (P) (100 kg N ha−1 a−1 + 50 kg P ha−1 a−1). Metagenomic sequencing characterized diversity and composition of soil microbial communities and used to construct bacterial/fungal co-occurrence networks. Nutrient-treated soils were more acidic and had higher levels of dissolved organic carbon than controls. There were no significant differences in microbial diversity and community composition across treatments. The addition of nutrients increased the abundance of copiotrophic bacteria and potentially beneficial microorganisms (e.g., Gemmatimonadetes, Chaetomium, and Aureobasidium). Low N addition increased microbiome network connectivity. Three rare fungi were identified as module hubs under nutrient addition, indicating that low abundance fungi were more sensitive to increased nutrients. The results indicate that the overall composition of microbial communities was stable but not static to long-term N addition. Our findings provide new insights that can aid predictions of the response of soil microbial communities to long-term N addition.