Forest fires threaten global ecosystems, socio-economic structures, and public safety. Accurately assessing forest fire susceptibility is critical for effective environmental management. Supervised learning methods dominate this assessment, relying on a substantial dataset of forest fire occurrences for model training. However, obtaining precise forest fire location data remains challenging. To address this issue, semi-supervised learning emerges as a viable solution, leveraging both a limited set of collected samples and unlabeled data containing environmental factors for training. Our study employed the transductive support vector machine (TSVM), a key semi-supervised learning method, to assess forest fire susceptibility in scenarios with limited samples. We conducted a comparative analysis, evaluating its performance against widely used supervised learning methods. The assessment area for forest fire susceptibility lies in Dayu County, Jiangxi Province, China, renowned for its vast forest cover and frequent fire incidents. We analyzed and generated maps depicting forest fire susceptibility, evaluating prediction accuracies for both supervised and semi-supervised learning methods across various small sample scenarios (e.g., 4, 8, 12, 16, 20, 24, 28, and 32 samples). Our findings indicate that TSVM exhibits superior prediction accuracy compared to supervised learning with limited samples, yielding more plausible forest fire susceptibility maps. For instance, at sample sizes of 4, 16, and 28, TSVM achieves prediction accuracies of approximately 0.8037, 0.9257, and 0.9583, respectively. In contrast, random forests, the top performers in supervised learning, demonstrate accuracies of approximately 0.7424, 0.8916, and 0.9431, respectively, for the same small sample sizes. Additionally, we discussed three key aspects: TSVM parameter configuration, the impact of unlabeled sample size, and performance within typical sample sizes. Our findings support semi-supervised learning as a promising approach compared to supervised learning for forest fire susceptibility assessment and mapping, particularly in scenarios with small sample sizes.

Increasing nitrogen (N) deposition alters the availability of soil nutrients and is likely to intensify phosphorus (P) limitations, especially in P-limited tropical and subtropical forests. Soil microorganisms play vital roles in carbon (C) and nutrient cycling, but it is unclear whether and how much N and P imbalances affect the soil’s microbial metabolism and mechanisms of nutrient limitations. In this study, a 3-year field experiment of N and P addition (control (CK), 100 kg N ha−1 yr−1 (N), 50 kg P ha−1 yr−1 (P), and NP) was set up to analyze the extracellular enzyme activities and stoichiometry characteristics of the top mineral soils in Chinese fir plantations with different stand ages (7, 20, and 33 years old). The results showed that the enzyme activities associated with the acquisition of C (β-1,4-glucosidase (BG) and β-d-cellobiohydrolase (CBH)) and P (acid phosphatases (APs)) in the N treatment were significantly higher than those in the CK treatment. Moreover, vector analysis revealed that both the vector’s length and angle increased in stands of all ages, which indicated that N addition aggravated microbial C and P limitations. The P and NP treatments both significantly decreased the activity of AP and the enzymes’ N:P ratio, thereby alleviating microbial P limitations, as revealed by the reduction in the vector’s angle. Stand age was found to promote all enzymatic activities but had no obvious effects on the limitation of microbial metabolism with or without added nutrients in the soils under Chinese fir. Available N, Olsen-P, and pH were the main drivers of microbial metabolic limitations related to C nutrients. These results provide useful data for understanding the change in soil microbial activity in response to environmental changes, and suggest that P fertilization should be considered for management to improve productivity and C sequestration in Chinese fir plantation in the context of increased deposition of N.

Reforestation after forest clearcutting is an effective measure to increase soil organic carbon (SOC) sequestration. However, the soil C balance and functions of microbial communities under reforestation remain to be determined. Samples of organic (0-2 cm) and mineral (2-10 cm) horizons were collected from the 7-, 15-, 20-, 29-, and 36-year-old forest stands of Chinese fir developed after plantation clearcutting in subtropical climate zone under the condition of phosphorus limitation. Particulate organic carbon (POC), mineral-associated organic carbon (MAOC), microbial phospholipid fatty acids (PLFAs), and enzymatic activities for C, nitrogen (N), and phosphorus (P) acquisition were analyzed. The lowest contents of POC (10 %) and MAOC (13 %) in the organic horizon were found in 7-year-old stands due to the slow tree regrowth and extensive decomposition of SOC in the first years of forest regrowth. POC (2.0x) and MAOC (0.8x) increases in the organic horizon with forest age were attributed to the stand development and accumulation of above and belowground litter. The organic horizon had a higher POC: MAOC ratio than the mineral (0.7-1.1 vs. 0.2-0.5), indicating lower SOC stability in the first one. A positive correlation of the Gram-positive to Gram-negative bacteria (G+:G-) ratio with the POC: MAOC ratio may point to developing specific substrate utilization strategies for microbial communities. Microorganisms were limited by C and P; however, the C limitation was alleviated in the 36-year-old plots in the organic horizon due to increased litter input. Microbial C and P limitations increased with total PLFAs and the G+:G- ratio, indicating the strong influence of community structure on nutrient acquisition from SOC. Thus, soil C sequestration under reforestation of Chinese fir can be controlled by microbial community structure and metabolic limitation, which both shifted with the stand age.

Soil pH stands as a decisive factor in shaping bacterial diversity and community composition, yet predicting the pH preferences and traits of individual bacterial taxa is still incomplete. We surveyed 942 samples from seven biomes worldwide to unravel the responses of individual bacterial genus to soil pH. Our findings indicate that soil pH surpasses the influences of spatial and climatic factors (biomes) in affecting bacterial composition and diversity. We observed that a comparable proportion of genera had low pH optima (21%), high pH optima (18%), and neutral pH optima (18%). However, apart from genera with optima groups, only a small percentage of genera were low pH tolerant (0.8%) compared to those that were high pH tolerant (21%). This suggests that a greater number of non-extremophiles genera can tolerate alkaline conditions compared to acidic conditions. Bacterial richness forms unimodal relationship with soil pH, consistently increasing from acidic levels to neutral across all biomes. However, the decline in richness when pH rises beyond neutral was less pronounced. This can be attributed to the higher number of alkaline-tolerant genera compared to acidic-tolerant genera. As expected, genera with acidic optima are more prevalent in humid climates, such as tropical forests, arctic tundra, and boreal forests, whereas genera with alkaline optima are generally dominant in arid grasslands and drylands. Collectively, our results indicate that the probability of existence of at least 75% of genera in specific soil pH conditions can be predicted, irrespective of biome. The identification of the actual niche spaces occupied by individual soil bacterial genera forms the foundation for developing comprehensive hypotheses regarding the response of soil communities to changing soil conditions worldwide.

Transpiration is a key process that couples the land-atmosphere exchange of water and carbon, and its maximum water transport ability affects plant productivity. Functional traits significantly influence the maximum transpiration rate; however, which factor plays the dominant role remains unknown. SAPFLUXNET dataset, which includes sap flux density of diverse species worldwide, provides fundamental data to test the importance of photosynthetic and hydraulic traits on maximum tree-level sap flux density (Js_max). Here, we investigated variations in Js_max of 2194 trees across 129 species using data from the SAPFLUXNET dataset, and analysed the relationship of Js_max with photosynthetic and hydraulic traits. Our results indicated that Js_max was positively correlated with photosynthetic traits at both leaf and tree level. Regarding hydraulic traits, Js_max was positively related to xylem hydraulic conductivity (Ks), leaf-specific hydraulic conductivity (Kl), xylem pressure inducing 50 % loss of hydraulic conductivity (P50), xylem vessel diameter (Vdia), and leaf-to-sapwood area ratio (AlAs). Random forest model showed that 87 % of the variability in Js_max can be explained by functional traits, and hydraulic traits (e.g., P50 and sapwood area, As) exerted larger effects on Js_max than photosynthetic traits. Moreover, trees with a lower sapwood area or depth could increase their sap flux density to compensate for the reduced whole-tree transpiration. Js_max of the angiosperms was significantly higher than that of the gymnosperms. Mean annual total precipitation (MAP) were positively related to Js_max with a weak correlation coefficient. Furthermore, Js_max showed a significant phylogenetic signal with Blomberg's K below 0.2. Overall, tree species with acquisitive resource economics or more efficient hydraulic systems show higher water transport capacity, and the efficiency of xylem hydraulic system rather than the demand for carbon uptake predominantly determines water transport capacity.

Forests are increasingly exposed to extreme global warming-induced climatic events. However, the immediate and carry-over effects of extreme events on forests are still poorly understood. Gross primary productivity (GPP) capacity is regarded as a good proxy of the ecosystem's functional stability, reflecting its physiological response to its surroundings. Using eddy covariance data from 34 forest sites in the Northern Hemisphere, we analyzed the immediate and carry-over effects of late-spring frost (LSF) and growing season drought on needle-leaf and broadleaf forests. Path analysis was applied to reveal the plausible reasons behind the varied responses of forests to extreme events. The results show that LSF had clear immediate effects on the GPP capacity of both needle-leaf and broadleaf forests. However, GPP capacity in needle-leaf forests was more sensitive to drought than in broadleaf forests. There was no interaction between LSF and drought in either needle-leaf or broadleaf forests. Drought effects were still visible when LSF and drought coexisted in needle-leaf forests. Path analysis further showed that the response of GPP capacity to drought differed between needle-leaf and broadleaf forests, mainly due to the difference in the sensitivity of canopy conductance. Moreover, LSF had a more severe and long-lasting carry-over effect on forests than drought. These results enrich our understanding of the mechanisms of forest response to extreme events across forest types.

Although many studies have focused on the roles of soil microbes in phosphorus (P) cycling, little is known about the distribution of microbial P cycling genes across soil depths. In this study, metagenomic sequencing was adopted to examine the differences in the abundance of genes and microbial taxa associated with soil P cycling between organic and mineral soil in subtropical forests. The total relative abundance of inorganic P solubilizing genes was the highest, that of P starvation response regulating genes was second, and organic P mineralizing genes was the lowest. The soil organic carbon concentration, N:P ratio, and available P concentration were higher in the organic soil than the mineral soil, resulting in abundances of organic P mineralizing genes (appA and 3-phytase), and inorganic P cycling genes (ppa), whereas those of the inorganic P cycling genes (gcd and pqqC) and the P starvation response regulating gene (phoR) were higher in mineral soil. The four bacteria phyla that related to P cycling, Proteobacteria, Actinobacteria, Bacteroidetes, and Candidatus_Eremiobacteraeota were higher in organic soil; conversely, the three bacteria phyla (Acidobacteria, Verrucomicrobia, and Chloroflexi) and archaea taxa were more abundant in mineral soil. Therefore, we concluded that the distribution of genes and microbial taxa involved in soil P cycling differed among soil depths, providing a depth-resolved scale insight into the underlying mechanisms of P cycling by soil microorganisms in subtropical forests.

1. Accurate information about age dynamics of timber production and carbon storage in forest ecosystems is frequently required by scientists, stakeholders, and policymakers. However, we lack standardized tools to calculate tree growth dynamics, even though this could be obtained by combining typical tree inventory, allometry and stem analysis data.2. Here we present an integrated R package, StemAnalysis, designed to reconstruct stem growth profiles, construct height-diameter relationships, and consequently to compute growth trends in terms of diameter at breast height (DBH), tree height, stem volume, tree biomass and carbon for an individual tree.3. StemAnalysis performs a number of standard tasks on input stem analysis data: (i) age class determination; (ii) the cumulative growth, mean annual increment, and current annual increment of outside-bark DBH, tree height, and stem volume are estimated; (iii) height-diameter relationship is fitted with nonlinear models; and (iv) tree biomass and carbon storage estimation from allometric and volume models are calculated. These tasks can be performed optionally.4. StemAnalysis provides investigators with a set of procedures for exploring tree growth patterns, thereby contributing to the ongoing development of forest multifunctional management sciences.

Tree species diversity is assumed to be an important component in managing forest ecosystems because of effects on multiple functions or ecosystem multifunctionality. However, the importance of tree diversity in determining multifunctionality in structurally complex subtropical forests relative to other regulators (e.g., soil microbial diversity, stand structure, and environmental conditions) remains uncertain. In this study, effects of aboveground (species richness and functional and structural diversity) and belowground (bacterial and fungal diversity) biodiversity, functional composition (community-weighted means of species traits), stand structure (diameter at breast height and stand density), and soil factors (pH and bulk density) on multifunctionality (including biomass production, carbon stock, and nutrient cycling) were examined along a tree diversity gradient in subtropical forests. The community-weighted mean of tree maximum height was the best predictor of ecosystem multifunctionality. Functional diversity explained a higher proportion of the variation in multifunctionality than that of species richness and fungal diversity. Stand structure -played an important role in modulating the effects of tree diversity on multifunctionality. The work highlights that species composition and maximizing forest structural complexity are effective strategies to increase forest multifunctionality while also conserving biodiversity in the management of multifunctional forests under global environmental changes.

Leaf carbon isotope composition (δ13C) provides an integrative record on the carbon and water balance of plants over long periods. Photosynthetic ability and hydraulic traits which are highly associated with stomatal behavior could affect leaf δ13C. Association between photosynthetic ability and leaf δ13C has been examined, however, how hydraulic traits influence leaf δ13C has not been fully understood. To fill this gap, we investigated the variations in leaf δ13C among 2591 woody species (547 shrub and 2044 tree species), and analyzed the link of leaf δ13C with leaf photosynthetic and xylem hydraulic traits. Our result showed that leaf δ13C was positively correlated to leaf photosynthetic ability and capacity. For hydraulic traits, leaf δ13C was negatively related to hydraulic conductivity (Ks), xylem pressure inducing 50 % loss of hydraulic conductivity (P50) and vessel diameter (Vdia). Associations of leaf δ13C with xylem hydraulic traits indicate woody species with stronger hydraulic safety discriminated less against 13C, while woody species with higher hydraulic efficiency had more negative leaf δ13C. Shrub species, which showed a lower Vdia and P50, had a significant less negative leaf δ13C than tree species. Furthermore, woody species inhabiting in dry regions discriminated less against 13C than those growing in humid regions. Moreover, leaf δ13C displayed a low phylogenetic signal based on Blomberg's K statistic. Overall, woody species with a higher leaf photosynthetic ability or stronger hydraulic safety system discriminated less against 13C and adopt the provident water use strategy.

Carbon and water cycles in forest ecosystems are tightly coupled, but global warming-induced soil and atmospheric droughts alter the coupling, thereby greatly increasing uncertainty in predicting carbon and water cycles. Therefore, a carbon–water coupled model (TRIPLEX-CW-Flux) was developed, and an R package (rTRIPLEXCWFlux) was created to facilitate model application. TRIPLEX-CW-Flux integrates vapor pressure deficit and soil moisture into a stomatal conductance submodule to estimate forest carbon and water fluxes. Prediction accuracy of TRIPLEX-CW-Flux and rTRIPLEXCWFlux application were evaluated in a Chinese fir (Cunninghamia lanceolata) plantation. Simulated net ecosystem production (NEP) and evapotranspiration (ET) were in good agreement with flux observations (R2: 0.76 for NEP; 0.71 for ET). Thus, the TRIPLEX-CW-Flux model can be used to predict and quantify effects of global warming-induced droughts on forest carbon and water cycles. The open-access rTRIPLEXCWFlux package facilitates estimations of carbon sequestration and water consumption in forest ecosystems using the observed flux data.

Understanding stomatal regulatory mechanisms across various woody species is helpful for explaining their adaptations to diverse environmental conditions. Stomatal opening and closing are driven by the requirements for maintaining water transport integrity and carbon uptake; however, distinguishing which factor plays a dominant role in the regulation of tree-level stomatal behavior has seldom been explored. To address this knowledge gap, we investigated differences in tree-level iso/anisohydric stomatal regulation among various tree species (61 and 59 species, at daily and hourly timescales, respectively) across diverse biomes, and analyzed the association of tree-level stomatal regulation with xylem hydraulic and leaf photosynthetic traits. Xylem hydraulic traits were closely related to tree-level stomatal regulation, whereas leaf photosynthetic traits showed non-significant correlations. Reduction in tree-level stomatal conductance with the same vapor pressure deficit increment (ranging from 0.6 to 2 kPa; Lcond), representing the degree of iso/anisohydry, was positively correlated to xylem pressure inducing 50% loss of hydraulic conductivity and vessel diameter, but negatively correlated to the hydraulic safety margin. The associations between xylem hydraulic traits and Lcond revealed that tree species with greater xylem hydraulic efficiency were more likely to adopt an avoidance strategy for tree-level stomatal regulation, whereas tolerance strategy occurred in species with a stronger hydraulic safety system. Furthermore, Lcond was positively correlated to mean annual precipitation and temperature, suggesting that species inhabiting humid and warm regions rely upon isohydric stomatal regulation. Moreover, Lcond displayed a phylogenetic signal, suggesting that variation in Lcond has been influenced by evolutionary history. Overall, tree-level stomatal regulation is more closely related to xylem hydraulic traits than to leaf photosynthetic traits, and maintaining water transport integrity rather than fulfilling requirements for carbon uptake is the major factor impacting tree-level stomatal regulation.

The process of rapid urbanization in China has led to various impacts on the urban ecological environment and one of these significant effects is the urban heat island (UHI). Pursuing the construction of a ecological city is recognized as an important direction to relieve the contradictions between environmental protection and city development. Yet how the landcape configuation and composition in such city development influences the UHI has not been well understood. This paper attempted to evaluate the spatial patterning of land surface temperature (LST) and to discuss the effects of source and sink landscape patterns upon LST in a smart city demonstrated at the local level in China. The results revealed that the UHI was spatially associated with the land use changes driven by rapid urbanization and gradually declines along the urban–rural gradient. When the urban–rural gradient reached the range of 7.5 to 8.75 km from the city center, there exhibited a tipping point where the combinative effects of source and sink landscapes on UHI significantly decreased. Through exploring the impact of source-sink landscape area ratio on UHI, we also found a tipping point that when source-sink area ratio in a patch was smaller than the golden separation value (1.30), UHI effect was almost mitigated because the warming effect of source area would be weaker than the cooling effect of sink area. Overall, this study highlights that controlling the optimal area ratio of source-sink landscape are very important strategy for mitigating the UHI effect during urban development and planning.

Aim Spatial patterns of root : shoot ratios (R:S) are critical to better estimate biomass turnover time (tau). Given the difficulty of measuring belowground biomass directly, we still lack an understanding of high-resolution spatial patterns of R:S in China's forests. Here, we explored patterns of R:S and their association with stand age, tree height, elevation, land cover, and climatic and edaphic variables, and estimated tau for China's forests. Location China. Time period 2004 and 2010. Major taxa studied Forests. Methods We used a machine learning algorithm trained with an R:S dataset of 1,907 observations covering five forest types to upscale the spatial distribution of R:S in China as a function of stand age, tree height, elevation, land cover, and climatic and edaphic variables. We calculated tau using the estimated R:S together with satellite-based aboveground biomass and net primary productivity data at 1 km x 1 km resolution. Results The estimated mean tau for total biomass in China's forests was 10.8-2.0+3.2years. The longest tau (tau > 20 years) was observed in central China, whereas southern China exhibited the shortest tau (tau < 10 years). Large differences in partial correlations between tau and climatic variables (mean annual precipitation, climatological water deficit, and mean annual temperature) were observed among forest types. Main conclusions Our data-driven gridded maps of estimated R:S and tau provide valuable baseline information for assessing model performance and improving future carbon-cycle assessments.

Forest farms are the main body of forest management at the landscape-scale in China, and have long sought ways to jointly maximize timber production and other ecosystem services. Carbon sequestration is of particular interest because China has established the goal of becoming carbon neutral by 2060. However, optimizing the balance between timber production and carbon sequestration is a challenge due to a lack of methods that account for the spatial arrangement of forest management activities within a landscape. This study developed a multi-objective planning model for forest management approaches to promote natural forest regeneration, adjusting the stand age structure of plantation forests to an even distribution across a landscape, and quantified the effects of social preferences and market prices on optimal management. The results show that depending on the dominant ecosystem services provided by the forests, forest management could promote an increased timber volume and stand carbon stock that is sustainable in the long-term. Social preferences have a relatively small influence on optimal management plans after forests are restructured to a normal forest age class distribution. In addition, forest management dynamics are more sensitive to carbon prices than timber prices. Hence, the spatial allocation of different management practices and forest restructuring, rather than protecting forests or managing them less intensively, is more effective for improving forest carbon stocks. More importantly, an urgent need also exists to increase the carbon price to guide and strengthen the attention of forest managers to forest carbon sequestration, with the goal of achieving a win–win strategy.

Canopy interception loss is an important hydrological process that affects rainfall redistribution, nutrient cycling, and soil and water conservation in forest ecosystems. However, the manner in which interception loss is affected in forests that are in restoration stages dominated by different tree species has not been fully understood. In this study, interception loss, throughfall, and stemflow were measured consecutively for 2 years (May 2017 through April 2019) in three secondary forests in subtropical China: a coniferous and broadleaved mixed forest ( Pinus massoniana , Lithocarpus glaber , PM) in early restoration stage, a deciduous broadleaved forest ( Choerospondias axillaris , CA) in middle restoration stage, and an evergreen broadleaved forest ( L. glaber – Cyclobalanopsis glauca , LG) in late restoration stage. For a given amount of rainfall, the relative interception loss in the CA was significantly lower than that in the evergreen forests in summer, spring, or winter. The amount of interception loss during light rain, moderate rain, or heavy storms was also significantly lower in CA as compared to that in evergreen forests, owing to the lesser leaf area and phenology of deciduous tree species as well as a higher leaf area index (LAI) and stand density in PM and LG. Meanwhile, the highest relative interception loss, interception loss amount, canopy storage capacity, canopy cover fraction, and mean evaporation rate was observed in the climax forest (LG), which has a higher LAI and stand density. Further, the revised Gash's analytical model (RGAM) and the sparse Rutter models were successfully applied to simulate interception loss in these forests, with the RGAM performing better as compared to the sparse Rutter model. The results of the field measurements and model simulations depict that the climax community at the late restoration stage can effectively reduce the amount of rainwater reaching the soil surface, thus weakening the effect of flood peaks.

Afforestation is an effective method to increase carbon (C) sinks and address climate change. It is crucial to understand how the stand growth affects C sequestration capacity, especially when the trade-offs with timber production from plantations have not been fully examined. We used a chronosequence approach to estimate C storage in Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantations (including the trees, understory, litter, and soils) at seven stand ages (3, 8-11, 16, 21, 25, 29, and 32 years). Ecosystem C storage increased nonlinearly from 76.4 to 282.2 t ha(-1) with stand age and was fitted with a logistic model that had a maximum C storage and age of 271.9 t ha(-1) and 33 years, respectively, to reach 95% of the maximum stored C. The C increment was mainly contributed by an increase in tree biomass, which ranged from 2.8 to 177.7 t ha(-1) and comprised 4-64% of the total ecosystem C. Live root C (sum of the stump, coarse, and fine root C) showed a logistic increase from 2.0 to 26.3 t ha(-1) with stand age and constituted 2.5-9.3% of ecosystem C. Understory plants and litter represented a small pool (< 2% of ecosystem C). The C storage in shrubs and litter slightly increased, while that in herbs decreased as the stands aged. Soil C storage was an important and relatively stable pool, ranging from 69.6 to 130.1 t ha(-1). Stand volume was also best fitted with a logistic model with a maximum value of 552.6 m(3 )ha(-1). Additionally, the time needed to reach 95% of the maximum volume was 25 years. Hence, extending the rotation age to over 30 years for Chinese fir plantations could potentially maximize the synergistic benefits of C storage to mitigate climate change and obtain timber products for economic profit.

Soil fungi are a diverse group of organisms extremely crucial to forest nutrient cycling and carbon (C) storage. The elevational pattern of soil microbial diversity has been widely studied, but how soil properties, elevation, and their association affect fungal community in subalpine forests remain to be explored. Here, soil fungal community diversity was investigated using high-throughput sequencing along an elevation gradient (3500–4300 m a.s.l.) in the Abies georgei var. smithii forests, a typical subalpine forest type in the Segila Mountains of Southeast Tibet. Elevation significantly affected the soil properties. Available phosphorus (P), total nitrogen (N), and soil organic C (SOC) increased whereas pH decreased with elevation. A U-shaped pattern for fungal diversity was found in topsoil while a slight monotonically decreasing pattern in subsoil layer across the elevation gradient. Basidiomycota, Ascomycota, and Mortierellomycota were the top three dominant phyla, and ectomycorrhizal fungi were the dominant functional fungi group in the A. georgei forest soils. Significant negative correlations were observed between fungal OTUs richness and NO3- (r = −0.431, p < 0.01), indicating that soil N availability is an important factor for fungal diversity. Based on redundancy analysis, soil factors explained 32.1% of the total variations in composition structure of fungal community. Soil pH, moisture, and fertilities (i.e., SOC, TN, TP, NO3-) were independent factors affecting the fungal community composition. Collectively, the alterations in soil environmental factor across elevations are essential in shaping the soil fungal diversity and community composition in the A. georgei forests in Segila Mountains, Southeast Tibet.

Background Forest ecosystems play an important role in carbon sequestration, climate change mitigation, and achieving China's target to become carbon (C) neutral by 2060. However, changes in C storage and net primary production (NPP) in natural secondary forests stemming from tree growth and future climate change have not yet been investigated in subtropical areas in China. Here, we used data from 290 inventory plots in four secondary forests [evergreen broad-leaved forest (EBF), deciduous and evergreen broad-leaved mixed forest (DEF), deciduous broad-leaved forest (DBF), and coniferous and broad-leaved mixed forest (CDF)] at different restoration stages and run a hybrid model (TRIPLEX 1.6) to predict changes in stand carbon storage and NPP under two future climate change scenarios (RCP4.5 and RCP8.5). Results The runs of the hybrid model calibrated and validated by using the data from the inventory plots suggest significant increase in the carbon storage by 2060 under the current climate conditions, and even higher increase under the RCP4.5 and RCP8.5 climate change scenarios. In contrast to the carbon storage, the simulated EBF and DEF NPP declines slightly over the period from 2014 to 2060. Conclusions The obtained results lead to conclusion that proper management of China’s subtropical secondary forests could be considered as one of the steps towards achieving China’s target to become carbon neutral by 2060.

Drought events lead to depressions in gross primary productivity (GPP) of forest ecosystems. Photosynthetic and hydraulic traits are important factors governing GPP variation. However, how these functional traits affect GPP responses to drought has not been well understood. We quantified the capacity of GPP to withstand changes during droughts (GPP_resistance) and its post-drought responses (GPP_resilience) using eddy covariance data from the FLUXNET2015 dataset, and investigated how functional traits of dominant tree species that comprised >80% of the biomass (or composition) influenced GPP_resistance or GPP_resilience. Light-saturated photosynthetic rate of dominant tree species was negatively related to GPP_resistance, and was positively correlated with GPP_resilience. Forests dominated by species with higher hydraulic safety margins (HSM), smaller vessel diameter (Vdia) and lower sensitivity of canopy stomatal conductance per unit land area (Gs) to droughts had a higher GPP_resistance, while those dominated by species with lower HSM, larger Vdia and higher sensitivity of Gs to droughts exhibited a higher GPP_resilience. Differences in functional traits of forests located in diverse climate regions led to distinct GPP sensitivities to droughts. Forests located in humid regions had a higher GPP_resilience while those in arid regions exhibited a higher GPP_resistance. Forest GPP_resistance was negatively related to drought intensity, and GPP_resilience was negatively related to drought duration. Our findings highlight the significant role of functional traits in governing forest resistance and resilience to droughts. Overall, forests dominated by species with higher hydraulic safety were more resistant to droughts, while forests containing species with higher photosynthetic and hydraulic efficiency recovered better from drought stress.