Forest In Eastern China Research Articles

Quantification of the Influencing Factors of Stand Productivity of Subtropical Natural Broadleaved Forests in Eastern China Using an Explainable Machine Learning Framework

Natural broadleaf forests (NBFs) are the most abundant zonal vegetation type in subtropical regions. Understanding the mechanisms influencing stand productivity in NBFs is important for developing “nature-based” solutions for climate change mitigation. However, minimal research has captured the effects of nonlinearities and feature interactions that often have nonlinear impacts on stand productivity and influencing factors. To address this research gap, we used continuous forest inventory data, and a machine learning model for stand productivity of NBFs was constructed. Subsequently, through leveraging the interpretable machine learning framework of the SHapley Additive explanation (SHAP) and partial dependence plot, we determined global and local explanations of the influencing factors of stand productivity. Our findings indicate the following: (1) The Autogluon model performed the strongest based on R2, RMSE, and rRMSE metrics. (2) The basal area (BA), neighborhood comparison of diameter at breast height (NC), and stand age (AGE) were the key influencing factors. Stand productivity increased with increasing BA and decreased with increasing NC and AGE. BA was maintained above 15 m2ha−1 and NC was maintained below 0.45, which represent favorable conditions for NBFs to maintain optimal growth. (3) SHAP interaction values were calculated to determine the effects of the five major interactions on stand productivity. Our study provides a reference for the sustainable management of NBFs, thereby highlighting the important role of forests in mitigating climate change.

Application of Bayesian Causal Inference in the Study of the Relationship Between Biodiversity and Aboveground Biomass of Subtropical Forest in Eastern China

The relationship between biodiversity and ecosystem function is crucial for understanding the structure and processes of subtropical forest ecosystems. However, the extent to which biodiversity influences subtropical forest biomass remains unclear. This study applies Bayesian causal inference to explore causal relationships between forest Aboveground Biomass (AGB) and its potential driving factors (biodiversity factors, biotic factors and abiotic factors) based on Huangshan Forest Dynamics Plots. Furthermore, hypothetical interventions are introduced to these driving factors within the causal network to estimate their potential impact on AGB. The causal relationship network reveals that species diversity and functional diversity are the most direct factors influencing AGB, whereas phylogenetic diversity exerts only an indirect effect. Biotic and abiotic factors also contribute indirect effects on AGB, potentially by influencing other mediating indexes. Intervention analysis shows that with low-level interventions on direct influencing factors, the probability of low AGB is as high as 84%. As the intervention level increases to high, the probability of low AGB decreases by 36%. Moreover, AGB demonstrates a particularly sensitive response to changes in Rao’s quadratic entropy (RaoQ) intervention levels, more so than to other factors, highlighting its critical role in maintaining forest biomass. Therefore, we contend that functional diversity, due to its direct reflection of species’ roles in ecosystem processes, is a more accurate measure of the impact of biodiversity on biomass compared to species or phylogenetic diversity and the interplay between abiotic and biotic factors and biodiversity should not be overlooked. This approach offers a powerful tool for exploring causal relationships, thereby providing a more nuanced and accurate understanding of the relationship between biodiversity and forest ecosystem function.

Distinct features of topsoil carbon fractions across urban forests in eastern China

AbstractRapid urbanization has increased the areas of urban forests that store considerable soil carbon (C). Different soil C fractions may show distinctive contents and spatial patterns in view of their contrasting sensitivities to various drivers. However, current studies on soil C fractions are mostly limited to natural ecosystems and little is known about the large‐scale patterns and drivers of soil C fractions in urban forests. Based on a field survey of urban forests across a north–south transect in eastern China, we analysed the spatial variations and main drivers of topsoil (surface layer, 0–10 cm; subsurface layer, 10–20 cm) C fractions (i.e., soil organic C, SOC; soil inorganic C, SIC; particulate organic C, POC; mineral‐associated organic C, MAOC). Our results showed that topsoil contents of POC, MAOC and SOC changed non‐linearly with latitude, with lowest values occurring in the cities in the warm temperate region. In contrast, SIC content showed the highest values in the warm temperate region. POC instead of MAOC was found to be a major fraction of SOC in urban forests. The spatial variation in topsoil POC content was mainly explained by mean annual temperature, soil clay and silt content, and park age. The spatial variation in MAOC content was mainly explained by soil clay and silt content, mean annual precipitation, mean annual temperature and park age. In contrast, the spatial variation in SIC content was mainly explained by mean annual precipitation and soil pH. These findings demonstrate distinct features of different soil C fractions in urban forests and provide useful implications for urban soil carbon management.

Effect of species-independent conspecific and heterospecific density dependence is contingent on seedling growth stage, season, and climate conditions

Conspecific negative density dependence (CNDD) and its extension heterospecific positive density dependence (HPDD) are the two most prominent mechanisms used to explain the maintenance of species diversity in forest communities. However, the impact of species identity, growth stage, seasonal and inter-annual variation in precipitation and temperature on conspecific and heterospecific density dependence remains poorly understood. Based on a decade of seedling (dbh < 1 cm) and tree (dbh ≥ 1 cm) census data from a 5-ha subtropical evergreen broad-leaved forest in eastern China, we used generalized linear mixed models with crossed random effects to test whether seedling survival was density dependent and varied by growth stage, species identity, season or interacted with inter-annual variation in seasonal precipitation and temperature. In addition to conspecific and heterospecific seedling and tree density, the height (or age) of the seedlings, habitat variables, seasonal precipitation and temperature and the interactions between conspecific and heterospecific seedling and tree density and seasonal precipitation and temperature were also used as predictors. The results of our long-term, spatially, and temporally explicit study showed that the strength of CNDD and enemy induced HPDD was stronger in summer and at early seedling stages, whereas interspecific facilitation induced HPDD mainly in winter for early and late seedling stages. Additionally, the effects of seasonal temperature and precipitation, and the soil PC1 axis (which correlated positively with soil nutrients and negatively with soil moisture) on seedling survival varied with season, seedling stage, and focal species identity, indicating the potential for niche partitioning among species in this community. However, neither conspecific nor heterospecific neighbor effects varied among focal seedling species, which resulted in a community compensatory trend in young seedlings. Variation in the effect of CNDD and HPDD across seedling stages, seasons, and inter-annual fluctuations of climate conditions highlights the necessity of long-term monitoring of the dynamics of CNDD in tree communities.

Latitudinal patterns and drivers of plant lignin and microbial necromass accumulation in forest soils: Disentangling microbial and abiotic controls

Plant- and microbial-derived compounds are the two primary sources of the soil organic carbon (SOC) pool. However, whether and how biotic and abiotic factors regulate the means through which microbes and plants contribute to SOC accumulation at a regional scale remains unclear. This study investigated the distribution patterns of plant lignin components and microbial necromass in soils, as indicated by lignin phenols and amino sugars across five latitudinal forests in eastern China. The contents of plant lignin and microbial necromass in the soil increased with increasing latitude. However, their contributions to SOC followed quadratic patterns with increasing latitude. Given its positive relationship with SOC content in all examined forests, microbial necromass seemed to play a more critical role in SOC accumulation than lignin phenols. Moreover, plant lignin and microbial necromass accumulation and their contributions to SOC were mainly influenced by the joint effects of climatic variables, microbial traits, and soil properties, but their importance was divergent. Specifically, the mean annual temperature (MAT) and soil phosphorus content were central to plant lignin accumulation, whereas MAT and the microbial richness: biomass ratio mainly controlled microbial necromass accumulation. These findings demonstrate that microbial necromass plays a more critical role than plant lignin in forest SOC accumulation and further highlight the importance of microbial traits in microbial necromass accumulation.

Distinct latitudinal patterns and drivers of topsoil nitrogen and phosphorus across urban forests in eastern China.

Nitrogen (N) and phosphorus (P) are the two most important macronutrients supporting forest growth. Unprecedented urbanization has created growing areas of urban forests that provide key ecosystem services for city dwellers. However, the large-scale patterns of soil N and P content remain poorly understood in urban forests. Based on a systematic soil survey in urban forests from nine large cities across eastern China, we examined the spatial patterns and key drivers of topsoil (0-20 cm) total N content, total P content, and N:P ratio. Topsoil total N content was found to change significantly with latitude in the form of an inverted parabolic curve, while total P content showed an opposite latitudinal pattern. Variance partition analysis indicated that regional-scale patterns of topsoil total N and P contents were dominated by climatic drivers and partially regulated by time and pedogenic drivers. Conditional regression analyses showed a significant increase in topsoil total N content with lower mean annual temperature (MAT) and higher mean annual precipitation (MAP), while topsoil total P content decreased significantly with higher MAP. Topsoil total N content also increased significantly with the age of urban park and varied with pre-urban soil type, while no such effects were found for topsoil total P content. Moreover, topsoil N:P ratio showed a latitudinal pattern similar to that of topsoil total N content and also increased significantly with lower MAT and higher MAP. Our findings demonstrate distinct latitudinal trends of topsoil N and P contents and highlight a dominant role of climatic drivers in shaping the large-scale patterns of topsoil nutrients in urban forests.

Constructing a non-linear additive crown-width model system for moso bamboo forests in eastern China

ABSTRACT Tree crown can be described by various crown dimension variables, including crown width (CW), an important predictor variable in forest growth-and-yield models. Because CW is quantified as the arithmetic mean of north–south and east–west CW measurements (crown components), issues of additivity and inherent correlation between crown components exist. Using two versatile estimation algorithms (non-linear seemingly unrelated regression − NSUR – and non-linear error-in-variable models − NEIVM), we employed three methods of constructing simultaneous model systems (non-linear summation − NSE, one-step proportional weighting system − OPWS, and two-step proportional weighting system − TPWS) to effectively address those issues. The performance of the three methods was evaluated using CW measurements of moso bamboo (Phyllostachys edulis) in China. Results showed that the OPWS outperformed the NSE and the TPWS for each algorithm. NEIVM-OPWS was more accurate than TPWS, and NEIVM outperformed NSUR. Diameter at breast height, total height and mean diameter at breast height (a variable describing stand density and competition) significantly contributed to CW and its component equations. Each CW model system included additivity of the crown component equations and accounted for the inherent correlations between equations. Overall, NEIVM-OPWS provided a closer estimate of CW to the measured CW than other model systems and methods employed. An effective CW model system will help understand light capture by the bamboo canopy and contribute to the effective management of bamboo forests in China and elsewhere.

Multiple dimensions of phylogenetic diversity are needed to explain the complex aboveground–belowground diversity relationships

The complex relationship between aboveground and belowground diversity and whether they act as surrogates for one another remains unresolved. Increasing evidence suggests that investigating phylogenetic diversity could provide valuable insights into the interplay between plants and soil microbes, but the proliferation of phylogenetic diversity metrics has hindered comparative studies and the identification of general patterns. To overcome this challenge, we implemented a multi‐dimensional framework that classifies phylogenetic diversity metrics into three dimensions: richness, divergence, and regularity, each of which captures different ecological aspects of species differences. Then we applied this framework to investigate the relationship between above and belowground diversity in a subtropical forest in eastern China. We found that phylogenetic diversity of plant and soil microbes, including bacteria and fungi, were more strongly correlated at the richness and regularity dimensions compared with divergence dimension. Further analyses revealed that these observed correlation patterns align with variations in soil total phosphorus content, a key factor influencing both plant and microbial phylogenetic diversity at richness and regularity dimensions. Together, our study demonstrated the necessity of using a multi‐dimensional approach to advance our understanding of the complex relationships between plant and soil microbial biodiversity.

VGGish-based detection of biological sound components and their spatio-temporal variations in a subtropical forest in eastern China.

Passive acoustic monitoring technology is widely used to monitor the diversity of vocal animals, but the question of how to quickly extract effective sound patterns remains a challenge due to the difficulty of distinguishing biological sounds within multiple sound sources in a soundscape. In this study, we address the potential application of the VGGish model, pre-trained on Google's AudioSet dataset, for the extraction of acoustic features, together with an unsupervised clustering method based on the Gaussian mixture model, to identify various sound sources from a soundscape of a subtropical forest in China. The results show that different biotic and abiotic components can be distinguished from various confounding sound sources. Birds and insects were the two primary biophony sound sources, and their sounds displayed distinct temporal patterns across both diurnal and monthly time frames and distinct spatial patterns in the landscape. Using the clustering and modeling method of the general sound feature set, we quickly depicted the soundscape in a subtropical forest ecosystem, which could be used to track dynamic changes in the acoustic environment and provide help for biodiversity and ecological environment monitoring.

PH is the major predictor of soil microbial network complexity in Chinese forests along a latitudinal gradient

Patterns in the network structure of microbial communities may give indications of their degree of interaction and interdependence, and their resilience to environmental disturbance. Geographical differences in network patterns of forest communities may reflect broad-scale differences in ecosystem structure and responses to environmental change. We analyzed a large dataset of 144 samples of soil bacterial and fungal communities characterized by 16S and ITS amplicon sequencing from forests in eastern China, along a 4,100 km latitudinal transect. This showed that fungal-bacterial network complexity was most closely related to soil pH. Results showed that pH was the strongest predictor of variation in community network structure across the forest soils of eastern China. Lower network complexity and stability were found around neutral pH, which was the strongest environmental predictor. This may be due to the optimal conditions that neutral soils provide for microorganism survival, reducing the necessity for physiological interdependence, consequently leading to fewer positive connections. Additionally, neutral soils provide more generalized niches, resulting in less specific niche exclusion, showing up as fewer negative connections. Unlike the trend for overall connectivity, the richness and relative abundances of keystone taxa were significantly and negatively correlated with pH. Overall, both connectivity and numbers of keystones were consistent in suggesting that network complexity was greatest overall at acidic pH. It appears that at the broad scale studied here, pH plays a more significant role in shaping microbial community integration than such factors as ecosystem productivity or climate.

Enhanced precipitation has driven the evolution of subtropical evergreen broad‐leaved forests in eastern China since the early Miocene: Evidence from ring‐cupped oaks

AbstractSubtropical evergreen broad‐leaved forest (EBLF) is the predominant vegetation type in eastern China. However, the majority of the region it covers in eastern China was an arid area during the Paleogene. The temporal history and essential factors involved in the evolution of subtropical EBLFs in eastern China remain enigmatic. Here we report on the niche evolution of Quercus section Cyclobalanopsis, which appeared in south China and Japan during the Eocene and became a dominant component of subtropical EBLFs since the Miocene in eastern Asia, using integrative analysis of occurrences, climate data and a dated phylogeny of 35 species in Cyclobalanopsis. Species within clades Cyclobalanoides, Lamellosa, and Helferiana mainly exist in the Himalaya–Hengduan region, adapting to a plateau climate, while species within the other clades mainly live in eastern China under the control of the East Asian monsoon. Reconstructed history showed that significant divergence of climatic tolerance in Cyclobalanopsis began around 19 million years ago (Ma) in the early Miocene. Simultaneously, disparities in precipitation of wettest/warmest quarter and annual precipitation were markedly enhanced in Cyclobalanopsis, especially in the recent eastern clades. During the Miocene, the marked radiation of Cyclobalanopsis and many other dominant taxa of subtropical EBLFs strongly suggest the rapid formation and expansion of subtropical EBLFs in eastern China. Our research highlights that the intensification of the East Asian monsoon and subsequent occupation of new niches by the ancient clades already present in the south may have jointly promoted the formation of subtropical EBLFs in eastern China since the early Miocene.

A distinctive latitudinal trend of nitrogen isotope signature across urban forests in eastern China.

Rapid urbanization has greatly altered nitrogen (N) cycling from regional to global scales. Compared to natural forests, urban forests receive much more external N inputs with distinctive abundances of stable N isotope (δ15 N). However, the large-scale pattern of soil δ15 N and its imprint on plant δ15 N remain less well understood in urban forests. By collecting topsoil (0-20 cm) and leaf samples from urban forest patches in nine large cities across a north-south transect in eastern China, we analyzed the latitudinal trends of topsoil C:N ratio and δ15 N as well as the correlations between tree leaf δ15 N and topsoil δ15 N. We further explored the spatial variation of topsoil δ15 N explained by corresponding climatic, edaphic, vegetation-associated, and anthropogenic drivers. Our results showed a significant increase of topsoil C:N ratio towards higher latitudes, suggesting lower N availability at higher latitudes. Topsoil δ15 N also increased significantly at higher latitudes, being opposite to the latitudinal trend of soil N availability. The latitudinal trend of topsoil δ15 N was mainly explained by mean annual temperature, mean annual precipitation, and atmospheric deposition of both ammonium and nitrate. Consequently, tree leaf δ15 N showed significant positive correlations with topsoil δ15 N across all sampled plant species and functional types. Our findings reveal a distinctive latitudinal trend of δ15 N in urban forests and highlight an important role of anthropogenic N sources in shaping the large-scale pattern of urban forest 15 N signature.

Earthworms neutralize the influence of components of particulate pollutants on soil extracellular enzymatic functions in subtropical forests.

Human activities are increasing the input of atmospheric particulate pollutants to forests. The components of particulate pollutants include inorganic anions, base cations and hydrocarbons. Continuous input of particulate pollutants may affect soil functioning in forests, but their effects may be modified by soil fauna. However, studies investigating how soil fauna affects the effects of particulate pollutants on soil functioning are lacking. Here, we investigated how earthworms and the particulate components interact in affecting soil enzymatic functions in a deciduous (Quercus variabilis) and a coniferous (Pinus massoniana) forest in southeast China. We manipulated the addition of nitrogen (N, ammonium nitrate), sodium (Na, sodium chloride) and polycyclic aromatic hydrocarbons (PAHs, five mixed PAHs) in field mesocosms with and without Eisenia fetida, an earthworm species colonizing forests in eastern China. After one year, N and Na addition increased, whereas PAHs decreased soil enzymatic functions, based on average Z scores of extracellular enzyme activities. Earthworms generally stabilized soil enzymatic functions via neutralizing the effects of N, Na and PAHs addition in the deciduous but not in the coniferous forest. Specifically, earthworms neutralized the effects of N and Na addition on soil pH and the effects of the addition of PAHs on soil microbial biomass. Further, both particulate components and earthworms changed the correlations among soil enzymatic and other ecosystem functions in the deciduous forest, but the effects depended on the type of particulate components. Generally, the effects of particulate components and earthworms on soil enzymatic functions were weaker in the coniferous than the deciduous forest. Overall, the results indicate that earthworms stabilize soil enzymatic functions in the deciduous but not the coniferous forest irrespective of the type of particulate components. This suggests that earthworms may neutralize the influence of atmospheric particulate pollutants on ecosystem functions, but the neutralization may be restricted to deciduous forests.

Modeling stand biomass for Moso bamboo forests in Eastern China.

Stand biomass models can be used as basic decision-making tools in forest management planning. The Moso bamboo (Phyllostachys pubescens) forest, a major forest system in tropical and subtropical regions, represents a substantial carbon sink, slowing down the rise of greenhouse gas concentrations in the earth's atmosphere. Bamboo stand biomass models are important for the assessment of the contribution of carbon to the terrestrial ecosystem. We constructed a stand biomass model for Moso bamboo using destructively sampled data from 45 sample plots that were located across the Yixing state-owned farm in Jiangsu Province, China. Among several bamboo stand variables used as predictors in the stand biomass models, mean diameter at breast height (MDBH), mean height (MH), and canopy density (CD) of bamboo contributed significantly to the model. To increase the model's accuracy, we introduced the effects of bamboo forest block as a random effect into the model through mixed-effects modeling. The mixed-effects model described a large part of stand biomass variation (R2=0.6987), significantly higher than that of the ordinary least squares regression model (R2=0.5748). Our results show an increased bamboo stand biomass with increasing MH and CD, confirming our model's biological logic. The proposed stand biomass model may have important management implications; for example, it can be combined with other bamboo models to estimate bamboo canopy biomass, carbon sequestration, and bamboo biomass at different growth stages.

Acoustic niche partitioning among seven cuckoo species in a forest in eastern China

Acoustic communication among birds plays an important role in attracting mates and defending territories. For the successful transmission of songs, individuals of different species often avoid singing at the same time to reduce acoustic interference from background noise and overlapping signals from heterospecifics. Such behavioural acoustic niche partitioning may occur especially among closely related species due to their ecological similarities. In this study, we recorded bird sounds in a subtropical forest in China in May–June 2019 and detected seven cuckoo species. Extracting characteristics of the cuckoo calls, we found that only four of the 21 pairs of species overlapped in frequency range, and 19 pairs were classified accurately using a linear discriminant analysis classifier based on their features. The remaining two species pairs could be separated based on temporal or spatial distribution patterns. We also analysed the temporal distribution patterns and overlap time of the calls, finding that the seven species exhibit partitioning in at least one of three acoustic dimensions (site, frequency, activity time). We conclude that the seven sympatric cuckoo species were strongly partitioned in acoustic signal space and minimally masked each other's signals.

Spatial patterns and determinants of nitrogen composition in the trunk xylem sap of tree species from tropical to temperate forests

Trunk xylem sap nitrogen (N) composition can provide key information for interpreting tree N transport strategies in a changing environment. However, there remains poorly explored to properly depict the spatial patterns and determinants of the xylem sap N composition in different tree species across climate zones. Here, we analyzed the trunk xylem sap N of dominant tree species from tropical to temperate forests in eastern China. The random forest (RF) approach was used to quantify the relative importance of biotic and abiotic variables in driving the spatial patterns of the trunk xylem sap N composition. The concentration ranges of total N (TN), ammonium (NH4+) and nitrate (NO3−) in the trunk xylem sap were 0.37–37.23, 0.01–2.60 and 0.01–0.49 mM, respectively. Dissolved organic nitrogen (DON) was the main component of TN in the xylem sap of forest trees, accounting for 83.4 ± 3.6%, followed by NH4+ (11.8 ± 3.2%) and NO3− (4.8 ± 1.3%). In addition, the TN and NH4+ concentrations increased from the tropical rainforest and then decreased to the northern temperate forest, with a peak in the subtropical deciduous forest in the middle-latitude climatic transition zone. The NO3− concentration in the temperate forest was higher than that in other forests, regardless of coniferous and broad-leaf forests. Tree species was the key factor affecting the spatial TN patterns, whereas soil pH primarily and conversely determined the spatial NH4+ and NO3− patterns. Together, tree characteristics and soil properties were the most important factors affecting the spatial patterns of xylem sap N composition. These findings provide new insights into N cycling within forest trees and have implications for better understanding the adaptation to global changes in forest ecosystems.

Does Forest Soil Fungal Community Respond to Short-Term Simulated Nitrogen Deposition in Different Forests in Eastern China?

Nitrogen (N) deposition has changed plants and soil microbes remarkably, which deeply alters the structures and functions of terrestrial ecosystems. However, how forest fungal diversity, community compositions, and their potential functions respond to N deposition is still lacking in exploration at a large scale. In this study, we conducted a short-term (4-5 years) experiment of artificial N addition to simulated N deposition in five typical forest ecosystems across eastern China, which includes tropical montane rainforest, subtropical evergreen broadleaved forest, temperate deciduous broadleaved forest, temperate broadleaved and conifer mixed forest, and boreal forest along a latitudinal gradient from tropical to cold temperature zones. Fungal compositions were identified using high-throughput sequencing at the topsoil layer. The results showed that fungal diversity and fungal community compositions among forests varied apparently for both unfertilized and fertilized soils. Generally, soil fungal diversity, communities, and their potential functions responded sluggishly to short-term N addition, whereas the fungal Shannon index was increased in the tropical forest. In addition, environmental heterogeneity explained most of the variation among fungal communities along the latitudinal gradient. Specifically, soil C: N ratio and soil water content were the most important factors driving fungal diversity, whereas mean annual temperature and microbial nutrient limitation mainly shaped fungal community structure and functional compositions. Topsoil fungal communities in eastern forest ecosystems in China were more sensitive to environmental heterogeneity rather than short-term N addition. Our study further emphasized the importance of simultaneously evaluating soil fungal communities in different forest types in response to atmospheric N deposition.

Plant and fungal species interactions differ between aboveground and belowground habitats in mountain forests of eastern China.

Plant and fungal species interactions drive many essential ecosystem properties and processes; however, how these interactions differ between aboveground and belowground habitats remains unclear at large spatial scales. Here, we surveyed 494 pairwise fungal communities in leaves and soils by Illumina sequencing, which were associated with 55 woody plant species across more than 2,000-km span of mountain forests in eastern China. The relative contributions of plant, climate, soil and space to the variation of fungal communities were assessed, and the plant-fungus network topologies were inferred. Plant phylogeny was the strongest predictor for fungal community composition in leaves, accounting for 19.1% of the variation. In soils, plant phylogeny, climatic factors and soil properties explained 9.2%, 9.0% and 8.7% of the variation in soil fungal community, respectively. The plant-fungus networks in leaves exhibited significantly higher specialization, modularity and robustness (resistance to node loss), but less complicated topology (e.g., significantly lower linkage density and mean number of links) than those in soils. In addition, host/fungus preference combinations and key species, such as hubs and connectors, in bipartite networks differed strikingly between aboveground and belowground samples. The findings provide novel insights into cross-kingdom (plant-fungus) species co-occurrence at large spatial scales. The data further suggest that community shifts of trees due to climate change or human activities will impair aboveground and belowground forest fungal diversity in different ways.

Responses of tree seedlings to understory filtering by the recalcitrant fern layer in a subtropical forest.

The recalcitrant understory fern layer is an important ecological filter for seedling regeneration, yet how the fern layer influences seedling regeneration dynamics remains unclear. Here we transplanted 576 seedlings of four dominant tree species, Castanopsis fargesii, Lithocarpus glaber, Schima superba and Hovenia acerba, to the treatments of Diplopterygium glaucum retention and removal under an evergreen broad-leaved forest in eastern China. We monitored the survival, growth and biomass data of these seedlings for 28 months, and then used generalized linear mixed models to evaluate the treatment effects on seedling survival, growth, biomass and root-shoot ratio. Our results showed that fern retention significantly inhibited the seedling establishment of all four species. During the seedling development stage, the seedling relative growth rate of L. glaber decreased under fern retention, which was not the case for the other three species. Root-shootratio of C. fargesii and L. glaber increased significantly under fern retention. Our findings provide new evidence of the filtering effect of a recalcitrant fern understory. Notably, we observed that the response of tree seedlings to the recalcitrant fern understory was more sensitive in the establishment stage. Finally, our work highlights that the filtering effect of the recalcitrant fern understory changes depending on the regeneration stages, and that shade-tolerant species, C. fargesii and L. glaber were even more affected by fern disturbed habitats, suggesting that effective management should attempt to curb forest fern outbreaks, thus unblocking forest recruitment.

Mean annual temperature and carbon availability respectively controlled the contributions of bacterial and fungal residues to organic carbon accumulation in topsoil across China's forests

AbstractAimSoil organic carbon (SOC) stabilization has become an important topic in recent years in the context of global climate change. Microbial residues represent a significant component of stabilized SOC pools. However, spatial variations in the contributions of bacterial and fungal residues to SOC and their determinants at a continental scale remain poorly understood. We aimed to evaluate the spatial variations and controls of the contributions of microbial residues to SOC in forest topsoil.LocationNorth–south transect in eastern China.Time period2014.Major taxa studiedForest ecosystems.MethodsA total of 195 surface (0–10 cm) soils were sampled from 28 forest sites across tropical and boreal forests in eastern China from July to August to assess how biotic and abiotic factors govern the geographic patterns of the contributions of soil microbial residues (indicated by amino sugars) to SOC.ResultsFungal residues (30.0%) had a greater average contribution to SOC than bacterial residues (15.5%). The contributions of bacterial (CBR) and total microbial residues (CMR) to SOC showed negative latitudinal patterns and were positively correlated with mean annual temperature (MAT). In contrast, the contribution of fungal residues to SOC (CFR) showed no clear geographic or climatic patterns. On average, the CBR (9.7%), CFR (21.1%) and CMR (30.8%) were lower in boreal forests than in other biome forests. SOC concentration negatively mediated CBR, CFR and CMR. The piecewise structural equation model results showed that MAT was the primary driver of the geographic pattern of CBR, whereas SOC and soil carbon : nitrogen ratio were more directly associated with the CFR. Additionally, plant factors and microbial properties (i.e., microbial biomass and composition) played relatively little roles in regulating CBR, CFR and CMR.Main conclusionsThese findings advance the current knowledge of the different geographic patterns of CBR and CFR regulated by different potential mechanisms in forest ecosystems. This highlights that the dynamics of microbial residues could potentially have unexpected consequences for topsoil SOC stocks under climate change.