Evergreen Broad-leaved Forest Research Articles

Effects of seasonal precipitation regimes on microbial biomass and extracellular enzyme activity during shrub foliar litter decomposition in a subtropical forest

Elucidating the mechanisms underlying microbial biomass and extracellular enzyme activity responses to the seasonal precipitation regime during foliar litter decomposition is highly important for understanding the material cycle of forest ecosystems in the context of global climate change; however, the specific underlying mechanisms remain unclear. Hence, a precipitation manipulation experiment involving a control (CK) and treatments with decreased precipitation in the dry season and extremely increased precipitation in the wet season (IE) and decreased precipitation in the dry season and proportionally increased precipitation in the wet season (IP) was conducted in a subtropical evergreen broad-leaved forest in China from October 2020 to October 2021. The moisture, microbial biomass, and extracellular enzyme activities of foliar litter from two dominant shrub species, Phyllostachys violascens and Alangium chinense, were measured at six stages during the dry and wet seasons. The results showed that (1) both IE and IP significantly decreased the microbial biomass carbon and microbial biomass nitrogen content and the activities of β-1,4-glucosidase, β-1,4-N-acetylglucosaminidase, acid phosphatase and cellulase in the dry season, while the opposite effects were observed in the wet season. (2) Compared with those of IE, the effects of IP on foliar litter microbial biomass and extracellular enzyme activity were more significant. (3) The results from the partial least squares model indicated that extracellular enzyme activity during foliar litter decomposition was strongly controlled by the foliar litter water content, microbial biomass nitrogen, the ratio of total carbon to total phosphorus, foliar litter total carbon, and foliar litter total nitrogen. These results provide an important theoretical basis for elucidating the microbial mechanisms driving litter decomposition in a subtropical forest under global climate change scenarios.

Elevated atmospheric CO2 concentration and vegetation structural changes contributed to gross primary productivity increase more than climate and forest cover changes in subtropical forests of China

Abstract. The subtropical forests of China play a pivotal role in the global carbon cycle and in regulating the global climate. Quantifying the individual and combined effects of forest cover change (FCC), vegetation structural change (e.g. leaf area index (LAI)), CO2 fertilisation, and climate change (CC) on the annual gross primary productivity (GPP) dynamics of different subtropical forest types are essential for mitigating carbon emissions and predicting future climate changes, but these impacts remain unclear. In this study, we used a processed-based model to comprehensively investigate the impacts of these factors on GPP variations with a series of model experiments in China's subtropical forests from 2001 to 2018. Simulated GPP showed a significant increasing trend (20.67 gCm-2yr-1, p<0.001) under the interaction effects of FCC, LAI change, rising CO2, and CC. The CO2 fertilisation (6.84 gCm-2yr-1, p<0.001) and LAI change (3.79 gCm-2yr-1, p=0.004) were the two dominant drivers of total subtropical forest GPP increase, followed by the effects of FCC (0.52 gCm-2yr-1, p<0.001) and CC (0.92 gCm-2yr-1, p=0.080). We observed different responses to drivers depending on forest types. The evergreen broad-leaved forests showed the maximum carbon sequestration rate due to the positive effects of all drivers. Both the FCC (0.19 gCm-2yr-1, p<0.05) and CC (1.22 gCm-2yr-1, p<0.05) significantly decreased evergreen needle-leaved forest GPP, while their negative effects were almost offset by the positive impact of LAI changes. Our results indicated that LAI outweighed FCC in promoting GPP, which is an essential driver that needs to be accounted for in studies and ecological and management programmes. Overall, our study offers a novel perspective on different drivers of subtropical forest GPP changes and provides valuable information for policy makers to better manage subtropical forests to mitigate climate change risks.

Analysis of spatio-temporal changes in net primary productivity and their driving factors in ecological functional areas of the Yellow River Basin

The Yellow River Basin (YRB) is an important region for both ecological and economic growth in China, and a healthy and stable ecological environment is fundamental to achieving high-quality development. Investigating the spatio-temporal changs of vegetation carbon sinks in the YRB is necessary to improve understanding of the regional carbon cycle. This study analyzed the YRB using the Google Earth Engine (GEE) platform. The basin was divided into sections based on ecological function regionalization schemes. We applied Theil-Sen median trend analysis and Spearman correlation analysis, along with the lasso regression model, to examine the NPP's temporal and spatial patterns and its driving factors in these regions. The objective was to examine the NPP’ s temporal and spatial patterns and its driving factors in these regions, identifying commonalities within regions and differences between regions, while analyzing in a targeted manner the lack of vegetation carbon sequestration in ecological areas. This study highlighted the importance of ecological engineering in ecological civilization and carbon neutrality, providing scientific theoretical support and a decision-making basis for the realization of carbon neutrality. The research results indicate significant upward trends (p<0.001) in both the average annual NPP (AANPP) growth rate (57.98%) and the total annual NPP (TANPP) growth rate (41.9%) in the YRB from 2001 to 2020. The multi-year average NPP (MYANPP) exhibit a spatial distribution with high values in the south and low values in the north. The spatial distribution of NPP exhibits notable spatial aggregation and heterogeneity, where regions demonstrating improvement trends constitute 93.01% of the area, and approximately 79.73% of this region displays low volatility. A high-value area is concentrated in the Agroecological Zone of the Fenwei Basin (I-11), the Loess Plateau Agriculture and Grassland Ecological Zone (I-12), and the Qinba Mountains Deciduous and Evergreen Broad-leaved Forest Ecological Zone (I-15), with significant spatial differences. Temperature, precipitation, and forests are the foremost elements affecting NPP in the YRB, exhibiting positive correlations. Conversely, farmland displays negative correlations. Overall, NPP shows an increasing trend in all ecological function areas, and the NPP of the YRB shows a trend of improvement as a whole, as the ecological environment of the YRB has improved significantly.

Alpha and beta diversity of functional traits in subtropical evergreen broad-leaved secondary forest communities.

Intra-speciic variation is the main source of functional trait diversity and has similar ecological effects as inter-speciic variation. We studied 79 species and 3546 individuals from 50 ixed monitoring plots in subtropical evergreen broad - leaved secondary forests in Zhejiang Province, China. Using trait gradient analysis, we examined nine traits (speciic leaf area, leaf dry matter content, wood density, leaf area, chlorophyll content, leaf nitrogen content, leaf phosphorus content, leaf potassium content, and nitrogen-phosphorus ratio) by decomposing species functional traits into alpha (within-community) and beta (among-communities) measure the impact of environmental gradients and the presence of other species on the variation of traits. All nine functional traits showed some degree of differentiation in the forest communities, with a greater range of variation in alpha values than in beta values . Correlations were signiicantly different between the trait differences in the communities. The alpha values of each trait showed a higher correlation with other components than the beta values. The factors affecting intra-speciic trait variation were relatively complex. The alpha component had a more signiicant and stronger effect on intra-speciic trait variation compared to the beta component. Abiotic factors, such as soil nutrient content, soil nitrogen-phosphorus content, directly affected the beta component. In contrast, biotic factors, such as tree height variation, had a direct and stronger effect on the alpha component. Our results demonstrate that alpha and beta components, as independent differentiation axes among coexisting species, have different sensitivities to different environmental factors and traits in different ecological strategies and spatial scales. Trait gradient analysis can more clearly reveal the variation patterns of species traits in communities, which will help to understand the scale effects and potential mechanisms of trait relationships.

The Origin of Evergreen Broad-Leaved Forests in East Asia from the Evidence of Floristic Elements.

Arguments about the origin and evolution of the evergreen broad-leaved forests in East Asia exist generally, and are even contradictory in some cases. The origin and evolution of the flora of East Asia, especially in the evolutionary process, the formation time of the Asian monsoon, the implications of phylogenetic and biogeographic studies on some important taxa, and the implications of palaeobotanical evidence are debatable. Most research from different disciplines suggests that the monsoon in the Miocene was key to the diversification of East Asian flora and its evergreen broad-leaved forests. The common view is that the evergreen broad-leaved forests of East Asia are closely related to the monsoon's intensity and developments, which were caused by the uplift of Himalaya-Tibet during or after the mid-Miocene. Analysis of the floristic elements show that the present subtropical evergreen broad-leaved forests in East Asia could have an early or ancient tropical origin and a tropical Asian affinity, but that their species are dominated by endemic Chinese or East Asian ones, many of which have tropical Asian affinity or are tropical sister species. The time of Himalayan uplift and the intensity of the monsoon climate are believed to be key to the formation of the evergreen broad-leaved forests in East Asia. Combined with existing paleobotanical findings, the uplift of the Himalayas and the formation of the monsoon climate, as well as floristic elements of the subtropical evergreen broad-leaved forests, we believe that they evolved from an Asian tropical rainforest after the mid-Miocene in the southeastern region of East Asia, while the ancient subtropical evergreen broad-leaved forests in the southwestern region continuously evolved into the present subtropical ones.

The complete chloroplast genome assembly of Castanopsis orthacantha Franch. 1899 (Fagaceae) in Southwestern China

Castanopsis orthacantha Franch. 1899 is one representative tree species distributed in the evergreen broad-leaved forests of southwestern China. This species is an important source of timber for manufacturing furniture, floors, and paper. It also plays a significant role in maintaining ecological balance and stability. To help with the genetic diversity assessment of C. orthacantha, we sequenced and assembled the first complete chloroplast genome. The length of the chloroplast genome was 160,588 bp, with a typical quadripartite structure (GenBank accession no. OR900101). The large single-copy (LSC), small single-copy (SSC), and two inverted repeats (IRs) were 90,237 bp, 18,953 bp, and 25,699 bp in length, respectively. We annotated one hundred and thirty genes across the chloroplast genome, including 86 protein-coding genes (79 are unique), 37 tRNA genes (29 are unique), and eight rRNA genes (four are unique). Seventeen genes had one intron, and four were detected with two introns. The maximum likelihood phylogeny suggested that C. orthacantha, C. lamontii, C. sclerophylla, and C. hainanensis formed a clade with a high bootstrap value. This newly sequenced chloroplast genome assembly will aid in the population genetic and phylogenetic studies of Castanopsis species in the future.

2021–2022年广东南岭站日尺度气象数据集

The mountainous forest and biodiversity ecological functional area of the Nanling Mountain forest ecosystem is one of the 25 key ecological functional areas in China, covering a variety of forest vegetation types, including tropical and subtropical moist broadleaf forests, coniferous broad-leaved evergreen mixed forest, and mountain top evergreen broad-leaved dwarf forest. The tropical and subtropical moist broadleaf forests are the most typical vegetation type in the Nanling Mountains. Monitoring the meteorological elements in the community can help understand the response mechanism of the tropical and subtropical moist broadleaf forests in the Nanling Mountains to climate change. Based on the Nanling Forest Ecosystem National Field Scientific Observation Research station ("Nanling Station" for short) in the Nanling Mountains, Guangdong, we carried out positioning research in Nanling National Nature Reserve. In this paper, we disclosed the raw data of 10 min average wind speed, precipitation, air temperature, air pressure, solar radiation (i.e. total radiation, reflected radiation, ultraviolet radiation, net radiation, photosynthetically active radiation) as well as relative humidity continuously collected in the subtropical evergreen broad-leaved forest area of the Nanling Station from 2021-2022 on a daily scale after data processing, quality control and evaluation. The dataset accessible to the public can serve as a valuable resource for further insights into the Nanling Mountain Forest Ecosystem, and provide foundation for efforts related to the restoration and protection of forest ecosystems.

2018年浙江古田山24公顷亚热带常绿阔叶林动态监测样地林冠结构和地形数据集

The canopy structure and topographic variables jointly influence the spatiotemporal variation of habitats for important species. However, there remains a considerable scarcity of precise forest canopy structure and topographic data obtained from large-scale forest dynamic plots. LiDAR data, acquired via near-surface remote sensing platforms, facilitates precise computation of both canopy structure and topographic variables. This study selected a 24-hectare dynamic plot in the subtropical evergreen broadleaf forest, located in the core conservation area of Qianjiangyuan National Park, as its focal point for survey. We conducted an analysis and quality control process on the point cloud data in 2018 using a near-surface remote sensing platform for this area, aiming to acquire corresponding canopy structure and topography data. Ground data collected through Real-Time Kinematic (RTK) surveying were used to verify and validate the accuracy of the digital elevation model (DEM). The analysis revealed a mean square error of elevation of 0.07 meters, suggesting a high level of accuracy of the dataset. The 24-hectare subtropical evergreen broad-leaved forest dynamic plot represents a typical low-altitude evergreen broad-leaved forest in the central subtropical region. This dataset can provide essential data support for the monitoring and research of biodiversity in subtropical broadleaved evergreen forests.

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.

Interactions between leaf traits and environmental factors help explain the growth of evergreen and deciduous species in a subtropical forest

It is well known that evergreen and deciduous species possess different functional traits and utilize different strategies in growth and adaptation to environments. However, little work has been done to elucidate whether leaf habits mediate the effect of trait-environment interactions on plant performance. In this study, our subjective was to illuminate whether relative growth rate of deciduous and evergreen species is influenced by multiple trait-environment interactions. We conducted measurements on eight leaf traits of 1230 individuals belonging to 25 species in a subtropical evergreen and deciduous broad-leaved mixed forest. Additionally, we collected data on topographic factors, edaphic variables and competition index. Subsequently, we employed generalized linear mixed model to analyze plant relative growth rate, considering high-order trait-environment interactions for both evergreen and deciduous species. We also visualized the effects of these interactions on growth patterns. Our results showed that leaf habits were divided by trait PC1 (41.8%) which was related to leaf lifespan and resource acquisition. Evergreen species tended to have greater interspecific variation compared to deciduous species. Notably, the inclusion of trait-environment interactions significantly improved growth predictions for both leaf habits, although explanatory power of deciduous models was always higher than that of evergreen species. Furthermore, we observed variability in the effects of trait-environment interactions on plant performance varied between leaf habits, leading to different optimal models for each leaf habit, even when they shared similar trait-environment context. These results indicated that difference of life history strategies between leaf habits could be reflected by trait-environment interactions. We emphasized the importance of leaf habits in explaining forest productivity and functions, and future research should focus on the effects of leaf habits on other demographic metrics to understand species coexistence in mixed forests.

Reconstruction of zonal vegetation of East Asia in the early Eocene

For the fi rst time, unifi ed types of zonal vegetation are established for the early Eocene in east of Asia and their changes in space are traced. The reconstruction is based on the analysis of 48 palynofl oras from the early Eocene localities situated from 75 to 19° N using Integrated Plant Record (IPR) vegetation analysis. In the results, quantitative parameters of the relative proportions of vegetation components are obtained. According to our data, along the latitudinal gradient from north to south, there is an increase in evergreen plants and herbs, but a decrease in conifers and deciduous plants, and no changes in the proportions of xerophytic plants. Mixed mesophytic forest is a widespread and dominant type of zonal vegetation. In general, the main changes in plant biomes show a very shallow and weakly pronounced diff erentiation into two plant zones: mixed mesophytic forest, north of ~50° paleolatitude, and warmer types of zonal vegetation (broadleaved evergreen forest and an ecotone between mixed mesophytic and broadleaved evergreen forests), in addition to mixed mesophytic forest, south of ~50° paleolatitude. The resulting spatial patterns of vegetation are consistent with climatic inferences.

New records of Harpiolaisodon (Chiroptera, Vespertilionidae) from the Chinese mainland.

The new species, Harpiolaisodon Kuo et al., 2006, was described from Taiwan, China. So far, no distribution of this species outside Taiwan has been reported. During two field investigations of small mammals in Guanyin Mountains Provincial Nature Reserve, Yuanyang, Yunnan, China, in April 2022 and May 2023, five individuals of Harpiola were collected in the mid-montane evergreen broad-leaved forest. Our morphological and molecular results reveal that these individuals from the Chinese mainland belong to Harpiolaisodon, extending the occurrence of this species well beyond its known distributions in Taiwan, China and Vietnam.

Nitrogen Deposition Modulates Litter Decomposition and Enhances Water Retention in Subtropical Forests

Nitrogen (N) deposition influences litter decomposition and its water-holding capacity in forest ecosystems. Water conservation remains a priority, so understanding these interactions is vital for managing forests, especially in the Yunnan Plateau region. This study aimed to investigate the effects of simulated N deposition on litter decomposition and water-holding capacity in the Evergreen broad-leaf and Quercus aquifolioides forest in the central Yunnan Plateau. Indoor flooding experiments were performed alongside varied nitrogen deposition treatments. Litter decomposition rates under these treatments were evaluated using the Olson model. In the decomposition study, the N treatments in the Evergreen broad-leaved forest increased the remaining mass by 4.75%–17.50% and 2.09%–16.36% compared with the control (20.97 ± 0.44% and 42.43 ± 0.47%), while in the Quercus aquifolioides forest, the remaining mass of leaves and twigs decreased by 5.00% and 0.70% in the LN treatment compared with the control (35.47 ± 0.39% and 44.10 ± 1.18%) and the MN and HN treatments increased by 2.55%–8.13% and 5.61%–11.28%, respectively. Effects of increased N deposition on litter decomposition changed from promoting to inhibiting, as low N sped up decomposition but higher levels inhibited it. Additionally, N boosted the water-holding capacity of litter, especially in leaves. The litter from both forests displayed a notable ability to absorb water. Nitrogen deposition modulates litter decomposition and water retention properties. Specifically, high nitrogen deposition increases litter water-holding capacity by inhibiting the rate of litter decomposition, which in turn alters its mass remaining rate, lignin, and cellulose remaining rates. Efficient management of the studied forests leveraging nitrogen deposition can boost their water conservation potential, aiding in atmospheric precipitation absorption and surface runoff regulation.

Decomposition and Carbon and Nitrogen Releases of Twig and Leaf Litter Were Inhibited by Increased Level of Nitrogen Deposition in a Subtropical Evergreen Broad-Leaved Forest in Southwest China

Decomposition and Carbon and Nitrogen Releases of Twig and Leaf Litter Were Inhibited by Increased Level of Nitrogen Deposition in a Subtropical Evergreen Broad-Leaved Forest in Southwest China

Growth-climate relationships of four tree species in the subtropical evergreen broad-leaved forests in Southwest China

Subtropical forests are an important carbon sink, yet our understanding on tree growth response to inter-annual climate variability remains limited. This study investigated the growth-climate relationships of four evergreen broad-leaved tree species (Stewartia pteropetiolata W. C. Cheng, Schima noronhae Reinw. ex Bl. Bijdr, Machilus gamblei King ex J. D. Hooker, and Machilus yunnanensis Lec) in the subtropical evergreen broad-leaved forests (EBFs) in the Ailao Mountains of Yunnan province, southwest China. We constructed tree ring-width residual chronologies for each species and correlated them with daily and monthly climate data. Ring-width chronologies of S. pteropetiolata and S. noronhae were positively correlated with precipitation, relative humidity, and self-calibrated Palmer drought index (scPDSI) during autumn of the previous year and spring-to-early summer of the current year, indicating that these two Theaceae species were sensitive to moisture availability. Tree radial growth of two Machilus species was primarily limited by excessive precipitation and dense cloud cover during the rainy season in this middle montane cloud forest. Moving correlations between climate variables and radial growth of all species were temporally unstable, with a weakening response to climate variability in recent decades. We highlight the dendroclimatic potential of evergreen broad-leaved tree species in moist subtropical forests. The findings offer a pertinent perspective, emphasizing the necessity of separately considering distinct ecological indicators for trees in order to obtain a comprehensive understanding of climate-growth responses within highly diverse subtropical forests.

Differences in Response of Tree Species at Different Succession Stages to Neighborhood Competition

Neighborhood competition influences tree growth, which can affect species composition and community succession. However, there is a lack of understanding regarding how dominant tree species at different successional stages of forest communities respond in terms of crown architecture and functional traits during their growth process to neighborhood competition. In this study, we analyzed the responses of average annual basal area increment (BAI), crown architecture, and leaf functional traits of early-successional species (Cunninghamia lanceolata and Pinus massoniana), transitional species (Alniphyllum fortunei and Choerospondias axillaris), and late-successional species (Elaeocarpus duclouxii and Castanopsis carlesii) to neighbor competition in a secondary evergreen broad-leaved forest. We found that the BAI of all species is negatively correlated with competition intensity. Notably, early-successional and transitional species exhibited a more rapid decline in growth rates compared to late-successional species in response to increased competition. Among these tree species, the response of crown structure to neighbor competition exhibited variation. Early-successional and transitional species displayed a negative correlation between the competition index and crown area (CA)/diameter, while a positive correlation emerged between the lowest branch height (LBH)/height. Conversely, late-successional species followed the opposite trend. In terms of leaf functional traits, specific leaf area (SLA) showed heightened sensitivity to neighborhood competition, with a positive correlation between SLA of all tree species and the competition index. Furthermore, water use efficiency (WUE) demonstrated negative correlations with the competition index in early-successional and transitional trees, while a positive correlation emerged with late-successional trees. These findings suggest that early-successional and transitional trees prioritize vertical canopy growth, whereas late-successional trees tend to favor horizontal canopy expansion in response to neighboring competition. Additionally, early-successional and transitional trees experience more significant suppression of radial growth rate. Our research contributes to a deeper understanding of the underlying mechanisms driving changes in species composition and community succession.

Quantitative Holocene climate reconstruction and anthropogenic impact analysis based on the pollen records in peat sediment in Southern China

The quantitative reconstruction of Holocene paleoclimate is pivotal for unraveling the evolution of East Asian Monsoon (EAM). Some recent studies have highlighted the escalating human activities in the late Holocene, which could potentially pose significant challenges to the precise quantitative reconstruction of paleoclimate. In this study, we undertake a quantitative reconstruction of Holocene climate and human influence index (HII) based on pollen data from the Shiwangutian (SWGT) in Southern China. This is achieved by developing and applying a pollen-based calibration model utilizing Locally Weighted Average-Partial Least Squares Regression (LWWA-PLS) and the Modern Analogue Technique (MAT). Our findings reveal that evergreen forests experienced expansion between 11.6 and 9.0 cal ka BP, coinciding with elevated Mean Annual Precipitation (Map) and Mean Annual Temperature (Mat) levels. These patterns signify a progressively warm and wet climate during this period. Subsequently, evergreen forests achieved their maximum abundance between 9.0 and 4.0 cal ka BP, aligning with a notable increase in vegetation richness, indicating a warmer and wetter climate during the mid-Holocene. Notably, during the interval of 6.0–4.0 cal ka BP, the Map, Mat, and Precipitation of Warmest Month (Mpwa) reached the Holocene optimum, approximately 14% higher than modern. Consequently, we deduce that in the early and middle Holocene, when the monsoon was particularly strong, synchronous changes in precipitation fostered the regional expansion of evergreen broad-leaved forests. Furthermore, the record demonstrates a substantial reduction in forest cover and a noteworthy increase in the HII value since 4.0 cal ka BP, likely attributable to anthropogenic impacts. Our analysis suggests that the influence of anthropogenic activities surpassed that of natural climate factors in shaping regional vegetation cover. These findings offer insights into potential drivers of climate change. As a preliminary conclusion, we propose that the summer insolation, ice sheets, and meltwater fluxes were the primary controlling factors for climate variations during the early to mid-Holocene in Southern China.

AGB estimation using Sentinel-2 and Sentinel-1 datasets.

Climate change is one of the greatest threats recently, of which developing countries are facing most of the brunt. In the fight against climate change, forests can play an important role, since they hold a substantial amount of terrestrial carbon and can therefore affect the global carbon cycle. Deforestation, however, is a significant challenge. There are financial incentives that can help in halting deforestation by compensating developing countries for their efforts. They require however assessments which makes it essential for developing countries to regularly monitor their stocking. Based on the aforementioned, forest carbon stock assessment was conducted in Margalla Hills National Park i.e., Sub-tropical Chir Pine Forest (SCPF) and Sub-tropical Broadleaved Evergreen Forest (SBEF), in Pakistan combining field inventory with a remote-sensing-based approach using machine learning algorithms. Circular plots of a 20m radius were used for recording the data and Sentinel-2 (S2) and Sentinel-1 (S1) satellite data were used for estimating the Aboveground Biomass (AGB). The performances of Random Forests (RF) and Support Vector Machine (SVM) were explored. The AGB was higher for the SCPF. The RF performed better for SCPF, but SVM was better for SBEF. The free available satellite data in the form of S2 and S1 data offers an advantage for AGB estimations. The combination of S2 and S1 for future AGB studies in Pakistan is also recommended.

Patterns and Dominant Driving Factors of Carbon Storage Changes in the Qinghai–Tibet Plateau under Multiple Land Use Change Scenarios

Revealing the spatial–temporal evolution of carbon storage and its driving mechanisms in the Qinghai–Tibet Plateau could provide support for decision making in the protection of regional ecosystems and the achievement of regional dual-carbon goals. In this study, the spatial–temporal evolution of carbon storage in the Qinghai–Tibet Plateau was analyzed under various scenarios using PLUS-InVEST and a gravity center model, and the driving mechanisms of carbon storage were clarified with Geodetector. The results are as follows: (1) During 2000–2020, the areas of coniferous forest, evergreen broad-leaved forest, closed shrub, temperate shrub desert, multi-tree grassland, and grassland showed an increasing trend, while the areas of deciduous broad-leaved forest and mixed forest showed a decreasing trend. (2) During 2030–2060, there was a decreasing trend in the total carbon storage of the Qinghai–Tibet Plateau under three different scenarios. (3) During 2030–2060, the area of the Qinghai–Tibet Plateau was mostly represented by carbon balance (56%), while the areas of carbon sources and carbon sinks showed a scattered distribution. (4) The precipitation and topographic factors with a q value of 0.888 played a dominant role in affecting the spatio-temporal variations in carbon storage in the Qinghai–Tibet Plateau. (5) In future ecological protection and restoration efforts, more high-quality farmlands should be protected and constructed, which could contribute to the achievement of dual-carbon goals. In addition, the hydrothermal conditions should be improved to aid the carbon cycle process in the Qinghai–Tibet Plateau.

The Changes in Soil Microbial Communities and Assembly Processes along Vegetation Succession in a Subtropical Forest

Soil microbes are the primary drivers of the material cycling of the forest ecosystem, and understanding how microbial structure and composition change across succession assists in clarifying the mechanisms behind succession dynamics. However, the response of soil microbial communities and assembly processes to succession is poorly understood in subtropical forests. Thus, through the “space instead of time” and high throughput sequencing method, the dynamics of the soil bacterial and fungal communities and assembly process along the succession were studied, where five succession stages, including Abandoned lands (AL), Deciduous broad-leaved forests (DB), Coniferous forests (CF), Coniferous broad-leaved mixed forests (CB), and Evergreen broad-leaved forests (EB), were selected in a subtropical forest on the western slope of Wuyi Mountain, southern China. The results demonstrated that succession significantly decreased soil bacterial α-diversity but had little effect on fungal α-diversity. The composition of soil bacterial and fungal communities shifted along with the succession stages. LEfSe analysis showed the transition from initial succession microbial communities dominated by Firmicutes, Bacteroidota, Ascomycota, and Chytridiomycota to terminal succession communities dominated by Actinobacteriota and Basidiomycota. Distance-based redundancy analysis (db-RDA) revealed that soil total organic carbon (TOC) was the main factor explaining variability in the structure of soil bacterial communities, and multiple soil environmental factors such as the TOC, soil total nitrogen (TN), C:N ratio, and pH co-regulated the structure of fungi. The null models illustrated that deterministic processes were dominant in the soil bacterial communities, while the stochastic processes contributed significantly to the soil fungal communities during succession. Collectively, our results suggest that different patterns are displayed by the soil bacterial and fungal communities during the succession. These findings enhance our comprehension of the processes that drive the formation and maintenance of soil microbial diversity throughout forest succession.