Multiple abiotic and biotic pathways shape biomass demographic processes in temperate forests

Multiple stressors determine the process of the benthic diatom community assembly and network stability in urban water bodies in Harbin

Human activities have triggered biodiversity loss, often resulting in biotic homogenization, which poses a threat to human well-being. Nevertheless, the overall influence of diverse environmental stressors on intra- and inter-community diversity remains insufficiently elucidated. This study aimed to quantify and reveal the impact of environmental stressors on the alpha and beta diversities of benthic diatom communities in the Harbin urban river network during the summer and autumn of 2022 and spring of 2023. The marked seasonal variations observed in alpha and beta diversity indices highlighted the distinct community compositions. Nonetheless, varying types of urban water pollutants were the primary drivers of biotic homogenization in terms of both taxonomic and functional diversities and played a prominent role in steering diversity shifts. These pollutants indirectly led to biotic homogenization by altering water quality parameters and affecting the ecological dynamics of benthic diatom communities. Furthermore, diverse responses to stressors were identified in taxonomic and functional diversities, providing additional insights for understanding ecological shifts in communities. Taxonomic beta diversity was related to environmental filtering, whereas functional beta diversity resulted from stressor-spatial dimension interactions. Our study emphasises that relying solely on traditional water quality monitoring may not fully reveal the current state of river ecosystem protection, and the need to study the continuous changes in biodiversity across seasons in urban waterbodies from the perspective of various stressors is highlighted.

Multiple anthropogenic stressors influence the taxonomic and functional homogenization of macroinvertebrate communities on the mainstream of an urban-agricultural river in China

Biodiversity loss is caused by intensive human activities and threatens human well-being. However, less is known about how the combined effects of multiple stressors on the diversity of internal (alpha diversity) and multidimensional (beta diversity) communities. Here, we conducted a long-term experiment to quantify the contribution of environmental stressors (including water quality, land use, climate factors, and hydrological regimes) to macroinvertebrate communities alpha and beta diversity in the mainstream of the Songhua River, the third largest river in China, from 2012 to 2019. Our results demonstrated that the alpha and beta diversity indices showed a decline during the study period, with the dissimilarity in community composition between sites decreasing significantly, especially in the impacted river sections (upper and midstream). Despite overall improvement in water quality after management intervention, multiple human-caused stressors still have led to biotic homogenization of macroinvertebrate communities in terms of both taxonomic and functional diversities in the past decade. Our study revealed the increased human land use explained an important portion of the variation of diversities, further indirectly promoting biotic homogenization by changing the physical and chemical factors of water quality, ultimately altering assemblage ecological processes. Furthermore, the facets of diversity have distinct response mechanisms to stressors, providing complementary information from the perspective of taxonomy and function to better reflect the ecological changes of communities. Environmental filtering determined taxonomic beta diversity, and functional beta diversity was driven by the joint efforts of stressors and spatial processes. Finally, we proposed that traditional water quality monitoring alone cannot fully reveal the status of river ecological environment protection, and more importantly, we should explore the continuous changes in biodiversity over the long term. Meanwhile, our results also highlight timely control of nutrient input and unreasonable expansion of land use can better curb the ecological degradation of rivers and promote the healthy and sustainable development of floodplain ecosystems.

Land use intensification alters the relative contributions of plant functional diversity and soil properties on grassland productivity

Understanding the mechanisms of grassland productivity variation is critical for global carbon cycling and climate change mitigation. Heretofore, it is unknown how different environmental factors drive small-scale spatial variation in productivity, and whether land use intensification, one of the most important global changes, can regulate the processes that drive productivity change. Here we performed an 18-year exclosure experiment across six sites with high-intensity mowing/grazing history in northern China to examine the effects of land use intensification on plant functional diversity, soil properties, and their relative contributions to above-ground net primary productivity (ANPP). We found that plant functional diversity and soil properties contributed to the variation in ANPP both independently and equally in enclosed grasslands (plant diversity: 20.6%; soil properties: 19.5%). Intensive land use significantly decreased the Rao's quadratic entropy (RaoQ) and community-weighted mean value (CWM) of plant height, and further suppressed the contributions of plant functional diversity to ANPP. In contrast, intensive land use increased soil available N, P, pH, electrical conductivity, and homogeneity of soil available P, and strengthened their contributions to ANPP (31.5%). Our results indicate that high-intensity land use practices in grasslands decrease the role of plant functional diversity, but strengthen the effects of soil properties on productivity. We, therefore, suggest that plant functional diversity can be used effectively to boost productivity in undisturbed grasslands, while soil properties might be a more critical consideration for grassland management in an areas with increased land use.

Seasonal Influence of Biodiversity on Soil Respiration in a Temperate Forest

Soil respiration in forests contributes to significant carbon dioxide emissions from terrestrial ecosystems but it varies both spatially and seasonally. Both abiotic and biotic factors influence soil respiration but their relative contribution to spatial and seasonal variability remains poorly understood, which leads to uncertainty in models of global C cycling and predictions of future climate change. Here, we hypothesize that tree diversity, soil diversity, and soil properties contribute to local-scale variability of soil respiration but their relative importance changes in different seasons. To test our hypothesis, we conducted seasonal soil respiration measurements along a local-scale environmental gradient in a temperate forest in Northeast China, analyzed spatial variability of soil respiration and tested the relationships between soil respiration and a variety of abiotic and biotic factors including topography, soil chemical properties, and plant and soil diversity. We found that soil respiration varied substantially across the study site, with spatial coefficients of variation (CV) of 29.1%, 27.3% and 30.8% in spring, summer, and autumn, respectively. Soil respiration was consistently lower at high soil water content, but the influence of other factors was seasonal. In spring, soil respiration increased with tree diversity and biomass but decreased with soil fungal diversity. In summer, soil respiration increased with soil temperature, whereas in autumn, soil respiration increased with tree diversity but decreased with increasing soil nutrient content. However, soil nutrient content indirectly enhanced soil respiration via its effect on tree diversity across seasons, and forest stand structure indirectly enhanced soil respiration via tree diversity in spring. Our results highlight that substantial differences in soil respiration at local scales was jointly explained by soil properties (soil water content and soil nutrients), tree diversity, and soil fungal diversity but the relative importance of these drivers varied seasonally in our temperate forest.

Topography and Soil Properties Determine Biomass and Productivity Indirectly via Community Structural and Species Diversity in Karst Forest, Southwest China

The forest ecosystem is an important part of the terrestrial ecosystem carbon sink, and its rate of biomass accumulation influences its carbon sink potential. Therefore, it is particularly important to understand the biomass and productivity of forest ecosystems, and their driving factors, especially in karst areas with a fragile ecological environment. We established a 2 ha plot in karst forest in southwest China, and investigated species composition, community structure, topography and soil nutrients in the years 2007 and 2017. In this analysis, the correlations between tree diversity and each factor were evaluated using a Pearson correlation analysis. In addition, the relationships between soil nutrients and topographies and their effects on productivity and biomass were further evaluated, either directly or indirectly, through species and structural diversity by using a structural equation model (SEM). The results showed that the number of individuals in each species decreased, and productivity was 1.76 Mg ha−1 yr−1, from 2007 to 2017. Species diversity was negatively correlated with biomass and positively correlated with productivity; structural diversity was negatively correlated with biomass and productivity, while structural diversity was negatively correlated with biomass and positively correlated with productivity. In addition, the effects of soil factors on biomass and productivity were significantly different: TN had a significant positive effect on productivity, while all soil factors except total nitrogen (TN) had significant positive effects on biomass. The structural equation results also showed that topographic and soil factors can directly affect productivity; structural diversity has a strong direct negative impact on biomass, while species diversity, structural diversity and biomass have similar direct positive impacts on productivity. Structural diversity was better than species diversity when explaining biomass accumulation. In conclusion, biotic and abiotic factors both influence forest productivity in karst forests in southwest China, and improving species diversity and community structure complexity is of great significance for forest management and productivity promotion. The research further improve the understanding of biomass and productivity in karst forest ecosystems, and their driving factors, which will provide relevant theoretical support for sustainable forest development in southwest karst.

Improved Object-Based Estimation of Forest Aboveground Biomass by Integrating LiDAR Data from GEDI and ICESat-2 with Multi-Sensor Images in a Heterogeneous Mountainous Region

Accurate and effective mapping of forest aboveground biomass (AGB) in heterogeneous mountainous regions is a huge challenge but an urgent demand for resource managements and carbon storage monitoring. Conventional studies have related the plot-measured or LiDAR-based biomass to remote sensing data using pixel-based approaches. The object-based relationship between AGB and multi-source data from LiDAR, multi-frequency radar, and optical sensors were insufficiently studied. It deserves the further exploration that maps forest AGB using the object-based approach and combines LiDAR data with multi-sensor images, which has the smaller uncertainty of positional discrepancy and local heterogeneity, in heterogeneous mountainous regions. To address the improvement of mapping accuracy, satellite LiDAR data from GEDI and ICEsat-2, and images of ALOS-2 yearly mosaic L band SAR (Synthetic Aperture Radar), Sentinel-1 C band SAR, Sentinel-2 MSI, and ALOS-1 DSM were combined for pixel- and object-based forest AGB mapping in a vital heterogeneous mountainous forest. For the object-based approach, optimized objects during a multiresolution segmentation were acquired by the ESP (Estimation of the Scale Parameter) tool, and suitable predictors were selected using an algorithm named VSURF (Variable Selection Using Random Forests). The LiDAR variables at the footprint-level were extracted to connect field plots to the multi-sensor objects as a linear bridge. It was shown that forests’ AGB values varied by elevations with a mean value of 142.58 Mg/ha, ranging from 12.61 to 514.28 Mg/ha. The north slope with the lowest elevation (<1100 m) had the largest mean AGB, while the smallest mean AGB was located in the south slope with the altitude above 2000 m. Using independent validation samples, it was indicated by the accuracy comparison that the object-based approach performed better on the precision with relative improvement based on root-mean-square errors (RIRMSE) of 4.46%. The object-based approach also selected more optimized predictors and markedly decreased the prediction time than the pixel-based analysis. Canopy cover and height explained forest AGB with their effects on biomass varying according to the elevation. The elevation from DSM and variables involved in red-edge bands from MSI were the most contributive predictors in heterogeneous temperate forests. This study is a pioneering exploration of object-based AGB mapping by combining satellite data from LiDAR, MSI, and SAR, which offers an improved methodology for regional carbon mapping in the heterogeneous mountainous forests.

Quantifying the Effects of Stand and Climate Variables on Biomass of Larch Plantations Using Random Forests and National Forest Inventory Data in North and Northeast China

The accurate estimation of forest biomass is crucial for supporting climate change mitigation efforts such as sustainable forest management. Although traditional regression models have been widely used to link stand biomass with biotic and abiotic predictors, this approach has several disadvantages, including the difficulty in dealing with data autocorrelation, model selection, and convergence. While machine learning can overcome these challenges, the application remains limited, particularly at a large scale with consideration of climate variables. This study used the random forests (RF) algorithm to estimate stand aboveground biomass (AGB) and total biomass (TB) of larch (Larix spp.) plantations in north and northeast China and quantified the contributions of different predictors. The data for modelling biomass were collected from 445 sample plots of the National Forest Inventory (NFI). A total of 22 independent variables (6 stand and 16 climate variables) were used to develop and train climate-sensitive stand biomass models. Optimization of hyper parameters was implemented using grid search and 10-fold cross-validation. The coefficient of determination (R2) and root mean square error (RMSE) of the RF models were 0.9845 and 3.8008 t ha−1 for AGB, and 0.9836 and 5.1963 t ha−1 for TB. The cumulative contributions of stand and climate factors to stand biomass were >98% and <2%, respectively. The most crucial stand and climate variables were stand volume and annual heat-moisture index (AHM), with relative importance values of >60% and ~0.25%, respectively. The partial dependence plots illustrated the complicated relationships between climate factors and stand biomass. This study illustrated the power of RF for estimating stand biomass and understanding the effects of stand and climate factors on forest biomass. The application of RF can be useful for mapping of large-scale carbon stock.

Temporal and Spatial Variation of Aboveground Biomass of Pinus densata and Its Drivers in Shangri-La, CHINA

Understanding the drivers of forest aboveground biomass (AGB) is essential to further understanding the forest carbon cycle. In the upper Yangtze River region, where ecosystems are incredibly fragile, the driving factors that make AGB changes differ from other regions. This study aims to investigate AGB's spatial and temporal variation of Pinus densata in Shangri-La and decompose the direct and indirect effects of spatial attribute, climate, stand structure, and agricultural activity on AGB in Shangri-La to evaluate the degree of influence of each factor on AGB change. The continuous sample plots from National Forest Inventory (NFI) and Landsat time series were used to estimate the AGB in 1987, 1992, 1997, 2002, 2007, 2012, and 2017. The structural equation model (SEM) was used to analyze the different effects of the four factors on AGB based on five scales: entire, 1987-2002, 2007-2017, low population density, and high population density. The results are as follows: (1) The AGB of Pinus densata in Shangri-La decreased from 1987 to 2017, with the total amount falling from 9.52 million tons to 7.41 million tons, and the average AGB falling from 55.49 t/ha to 40.10 t/ha. (2) At different scales, stand structure and climate were the drivers that directly affect the AGB change. In contrast, the agricultural activity had a negative direct effect on the AGB change, and spatial attribute had a relatively small indirect effect on the AGB change. (3) Analyzing the SEM results at different scales, the change of the contribution of the agricultural activity indicates that human activity is the main negative driver of AGB change in Shangri-La, especially at the high population density region. In contrast, the change of the contribution of the stand structure and climate indicates that the loss of old trees has an important influence on the AGB change. Forest resources here and other ecologically fragile areas should be gradually restored by adhering to policies, such as strengthening forest protection, improving forest stand quality, and limiting agricultural production activities.

Mass-ratio and complementarity effects simultaneously drive aboveground biomass in temperate Quercus forests through stand structure

Forests play a key role in regulating the global carbon cycle, a substantial portion of which is stored in aboveground biomass (AGB). It is well understood that biodiversity can increase the biomass through complementarity and mass-ratio effects, and the contribution of environmental factors and stand structure attributes to AGB was also observed. However, the relative influence of these factors in determining the AGB of Quercus forests remains poorly understood. Using a large dataset retrieved from 523 permanent forest inventory plots across Northeast China, we examined the effects of integrated multiple tree species diversity components (i.e., species richness, functional, and phylogenetic diversity), functional traits composition, environmental factors (climate and soil), stand age, and structure attributes (stand density, tree size diversity) on AGB based on structural equation models. We found that species richness and phylogenetic diversity both were not correlated with AGB. However, functional diversity positively affected AGB via an indirect effect in line with the complementarity effect. Moreover, the community-weighted mean of specific leaf area and height increased AGB directly and indirectly, respectively; demonstrating the mass-ratio effect. Furthermore, stand age, density, and tree size diversity were more important modulators of AGB than biodiversity. Our study highlights that biodiversity-AGB interaction is dependent on the regulation of stand structure that can be even more important for maintaining high biomass than biodiversity in temperate Quercus forests.

Linking functional traits with tree growth and forest productivity in Quercus ilex forests along a climatic gradient

Plant functional traits are highly plastic to changes in climatic factors and nutrient availability. However, the intraspecific plant response to abiotic factors and the overall effect on tree growth and productivity is still under debate. We studied forest productivity for 30 Quercus ilex subsp. ballota forests in Spain along a broad climatic gradient of aridity (mean annual precipitation from 321 to 858 mm). We used linear mixed models to quantify the effect of climatic and edaphic (soil nutrients, topography, and texture) factors on tree functional traits (leaf and branch traits), and subsequently, the effect of such functional traits and abiotic factors on the relative growth rate (RGR) of adult trees. We used piecewise structural equation models (SEMs) to determine the causal effect of intrinsic and extrinsic factors on forest productivity. Our results showed that tree functional traits were mainly explained by climatic and edaphic factors. Functional traits and tree biomass explained forest biomass and RGR, respectively, which ultimately explained forest productivity. In conclusion, intraspecific variability of functional traits has a significant effect on plant biomass and growth, which ultimately may explain forest productivity in Quercus ilex forests.

Divergent above- and below-ground biodiversity pathways mediate disturbance impacts on temperate forest multifunctionality

Biodiversity plays a fundamental role in provisioning and regulating forest ecosystem functions and services. Above-ground (plants) and below-ground (soil microbes) biodiversity could have asynchronous change paces to human-driven land-use impacts. Yet, we know very little how they affect the provision of multiple forest functions related to carbon accumulation, water retention capacity and nutrient cycling simultaneously (i.e. ecosystem multifunctionality; EMF). We used a dataset of 22,000 temperate forest trees from 260 plots within 11 permanent forest sites in Northeastern China, which are recovering from three post-logging disturbances. We assessed the direct and mediating effects of multiple attributes of plant biodiversity (taxonomic, phylogenetic, functional and stand structure) and soil biodiversity (bacteria and fungi) on EMF under the three disturbance levels. We found the highest EMF in highly disturbed rather than undisturbed mature forests. Plant taxonomic, phylogenetic, functional and stand structural diversity had both positive and negative effects on EMF, depending on how the EMF index was quantified, whereas soil microbial diversity exhibited a consistent positive impact. Biodiversity indices explained on average 45% (26%-58%) of the variation in EMF, whereas climate and disturbance together explained on average 7% (0.4%-15%). Our result highlighted that the tremendous effect of biodiversity on EMF, largely overpassing those of both climate and disturbance. While above- (β = 0.02-0.19) and below-ground (β = 0.16-0.26) biodiversity had direct positive effects on EMF, their opposite mediating effects (β = -0.22 vs. β = 0.35 respectively) played as divergent pathways to human disturbance impacts on EMF. Our study sheds light on the need for integrative frameworks simultaneously considering above- and below-ground attributes to grasp the global picture of biodiversity effects on ecosystem functioning and services. Suitable management interventions could maintain both plant and soil microbial biodiversity, and thus guarantee a long-term functioning and provisioning of ecosystem services in an increasing disturbance frequency world.

The Effects of Biotic and Abiotic Factors on the Community Dynamics in a Mountain Subtropical Forest

From supporting wood production to mitigating climate change, forest ecosystem services are crucial to the well-being of humans. Understanding the mechanisms that drive forest dynamics can help us infer how to maintain forest ecosystem services and how to improve predictions of forest dynamics under climate change. Despite the growing number of studies exploring above ground biomass (AGB) dynamics, questions of dynamics in biodiversity and in number of individuals still remain unclear. Here, we first explored the patterns of community dynamics in different aspects (i.e., AGB, density and biodiversity) based on short-term (five years) data from a 25-ha permanent plot in a subtropical forest in central China. Second, we examined the relationships between community dynamics and biodiversity and functional traits. Third, we identified the key factors affecting different aspects of community dynamics and quantified their relative contributions. We found that in the short term (five years), net above ground biomass change (ΔAGB) and biodiversity increased, while the number of individuals decreased. Resource-conservation traits enhanced the ΔAGB and reduced the loss in individuals, while the resource-acquisition traits had the opposite effect. Furthermore, the community structure contributed the most to ΔAGB; topographic variables and soil nutrients contributed the most to the number of individuals; demographic process contributed the most to biodiversity. Our results indicate that biotic factors mostly affected the community dynamics of ΔAGB and biodiversity, while the number of individuals was mainly shaped by abiotic factors. Our work highlighted that the factors influencing different aspects of community dynamics vary. Therefore, forest management practices should be formulated according to a specific protective purpose.

Climate regulates the functional traits - aboveground biomass relationships at a community-level in forests: A global meta-analysis

The relationships between plant functional traits and aboveground biomass (AGB) stock have been explored across forest biomes. Yet, meta-analyses synthesizing our understanding regarding the influences of climate and soil on the functional traits - AGB relationships at a community-level in global forests are still unavailable. Here, we evaluated the latitudinal gradient in the functional traits -AGB relationships in forests, including functional trait diversity (FTD) - AGB (FTD-AGB), community-weighted mean (CWM) of conservative traits (CWMCT-AGB), CWM of acquisitive traits (CWMAT-AGB), and CWM of plant maximum height or diameter (FunDom-AGB), and then answer the question whether climate and soil conditions modulate the functional traits - AGB relationships in global forests. To do so, we selected those studies which reported the relationships of FTD and CWM with AGB stock (i.e. in Mg ha^-1) rather with AGB productivity or growth (i.e. Mg ha^-1 yr^-1) at a community-level (i.e. forest plot). By using piecewise structural equation meta-modeling, we found that: (1) functional traits - AGB relationships at a community-level were driven by mean annual temperature (MAT), aridity and soil fertility. (2) Higher MAT and low aridity promoted FTD-AGB relationships but the opposite trend was true for CWMCT-AGB, whereas higher MAT promoted CWMAT-AGB and FunDom-AGB at high aridity levels. (3) The FunDom-AGB relationship increased with increasing the number of forest plots but other relationships declined. (4) The negligible or negative FTD-AGB relationships but the positive AGB-FunDom relationships were conspicuous across global forests, indicating the mass ratio effect in terms of functional dominance. Our meta-analysis suggests that functional dominance and conservative species' strategy in relation to favorable abiotic conditions should be promoted to increase AGB stock under global environmental changes.

Context-dependency of tree species diversity, trait composition and stand structural attributes regulate temperate forest multifunctionality

High species diversity is generally thought to be a requirement for sustaining forest multifunctionality. However, the degree to which the relationship between species-, structural-, and trait-diversity of forests and multifunctionality depend on the context (such as stand age or abiotic conditions) is not well studied. Here, we hypothesized that context-dependency of tree species diversity, functional trait composition and stand structural attributes promote temperate forest multifunctionality including above- and below-ground multiple and single functions. To do so, we used repeated forest inventory data, from temperate mixed forests of northeast China, to quantify two above-ground (i.e. coarse woody productivity and wild edible plant biomass), five below-ground (i.e. soil organic carbon, total soil nitrogen, potassium, phosphorus and sulfur) functions, tree species diversity, individual tree size variation (CV_DBH) and functional trait composition of specific leaf area (CWM_SLA) as well as stand age and abiotic conditions. We found that tree species diversity increased forest multifunctionality and most of the single functions. Below-ground single and multifunctionality were better explained by tree species diversity. In contrast, above-ground single and multifunctionality were better explained by CV_DBH. However, CWM_SLA was also an additional important driver for maintaining above- and below-ground forest multifunctionality through opposing plant functional strategies. Stand age markedly reduced forest multifunctionality, tree species diversity and CWM_SLA but substantially increased CV_DBH. Below-ground forest multifunctionality and tree species diversity decreased while above-ground forest multifunctionality increased on steep slopes. These results highlight that context-dependency of forest diversity attributes might regulate forest multifunctionality but may not have a consistent effect on above-ground and below-ground forest multifunctionality due to the fact that those functions were driven by varied functional strategies of different plant species. We argue that maximizing forest complexity could act as a viable strategy to maximizing forest multifunctionality, while also promoting biodiversity conservation to mitigate climate change effects.

Topography and forest diversity facets regulate overstory and understory aboveground biomass in a temperate forest of South Korea

Diversity-biomass studies across (sub-)tropical forest strata have been explored, but our understanding on how multiple facets of forest diversity and abiotic factors regulate aboveground biomass across forest strata in temperate forests remains somehow unclear. Here, we conducted a comprehensive analysis of the effects and relative importance of taxonomic, phylogenetic and functional diversity, community-weighted mean (CWM) of trait values, coefficient of variation in individual tree diameter at breast height (CV DBH), and soil and topographic factors on aboveground biomass to select the diversity facets that could have the strongest response to abiotic factors across over- and understory and whole community in a temperate forest of South Korea. We used forest inventory, functional traits and environmental factors data from 259 plots to select the most important diversity facets with abiotic factors through multi-model inference tests, and we then used structural equation models. In the overstory, the most important regulators of aboveground biomass were topographic factor, species evenness, functional richness, and CV DBH. In the understory, the significant drivers of aboveground biomass were topographic factor, species evenness, phylogenetic species richness and CWM of height. In addition, diversity facets of overstory such as functional richness and CV DBH also had significant direct and/or indirect effects on understory aboveground biomass. Moreover, the diversity facets influencing aboveground biomass at the whole community were the combination of the multiple facets of forest diversity influencing aboveground biomass at each forest stratum. The role of functional dominance (CWM of height) seems to be negligible in the overstory but significant in the understory, indicating different diversity drivers as shown previously for a subtropical forest. Hence, our study suggests the urgent need of exploring diversity-biomass studies across forest strata in different forest ecosystems and types in order to provide more specific guidelines for the management of a specific natural forest.

Assessing biotic and abiotic effects on forest productivity in three temperate forests

It is well understood that biotic and abiotic variables influence forest productivity. However, in regard to temperate forests, the relative contributions of the aforementioned drivers to biomass demographic processes (i.e., the growth rates of the survivors and recruits) have not received a great deal of attention. Thus, this study focused on the identification of the relative influencing effects of biotic and abiotic variables in the demographic biomass processes of temperate forests.This study was conducted in the Changbai Mountain Nature Reserve, in northeastern China. Based on the observational data collected from three 5.2-hectare forest plots, the annual above-ground biomass (AGB) increment (productivity) of the surviving trees, recruits, and the total tree community (survivors + recruits) were estimated. Then, the changes in the forest productivity in response to biotic variables (including species diversity, structural diversity, and density variables) along with abiotic variables (including topographic and soil variables) were evaluated using linear mixed-effect models.This study determined that the biotic variables regulated the variabilities in productivity. Density variables were the most critical drivers of the annual AGB increments of the surviving trees and total tree community. Structural diversity enhanced the annual AGB increments of the recruits, but diminished the annual AGB increments of the surviving trees and the total tree community. Species diversity and abiotic variables did not have impacts on the productivity in the examined forest plots.The results highlighted the important roles of forest density and structural diversity in the biomass demographic processes of temperate forests. The surviving and recruit trees were found to respond differently to the biotic variables, which suggested that the asymmetric competition had shaped the productivity dynamics in forests. Therefore, the findings emphasized the need to consider the demographic processes of forest productivity to better understand the functions of forests.

Environmental filtering, predominance of strong competitor trees and exclusion of moderate-weak competitor trees shape species richness and biomass

Strong competitor (i.e. big-sized) trees are globally crucial for promoting aboveground biomass. Still, we do not fully understand the simultaneous influences of different levels of competitor (i.e. strong, moderate, medium and weak) trees at stand level in shaping forest diversity and biomass along a climatic gradient. We hypothesized that few strong competitor trees shape the positive relationship between tree species richness and aboveground biomass better than moderate, medium and weak competitor trees along a climatic gradient. Using the forest inventory data (i.e. tree diameter, height and crown diameter), we quantified strong (i.e. 99th percentile; top 1%), moderate (i.e. 75th percentile; top 25%), medium (i.e. 50th percentile) and weak (i.e. 25th percentile) competitor trees as well as species richness and aboveground biomass of 248 plots (moist temperate, semi-humid, and semi-arid forests) across 12 sites in Iran. The main results from three piecewise structural equation models (i.e. tree diameter, height and crown based models) showed that, after considering the simultaneous fixed effects of climate and random effects of sites or forest types variation, strong competitor trees possessed strong positive effects on tree species richness and biomass whereas moderate, medium and weak competitor trees possessed negligible positive to negative effects. Also, different levels of competitor trees promoted each other in a top-down way but the effects of strong competitor trees on moderate, medium and weak competitor trees were relatively weak. This study suggests that the simultaneous interactions of different tree sizes at stand level across forest sites should be included in the integrative ecological modeling for better understanding the role of different levels of competitor trees in shaping positive forest diversity - functioning relationship in a changing environment.

Impacts of climatic and edaphic factors on the diversity, structure and biomass of species-poor and structurally-complex forests

Understanding the impacts of multiple climatic and edaphic factors on forest diversity, structure and biomass is crucial to predicting how forests will react to global environmental change. Here, we addressed how do forest structural attributes (i.e. top 1% big, top 25% big medium and small trees; in terms of tree height, diameter, and crown), species richness, and aboveground biomass respond to temperature-related and water-related climatic factors as well as to edaphic factors. By assuming disturbance as a constant factor in the study forests, we hypothesize that water-related and temperature-related climatic factors play contrasting roles whereas edaphic factors play an additional role in shaping forest diversity, structure and aboveground biomass in species-poor and structurally-complex forests. We used forest inventory and environmental factors data from 248 forest plots (moist temperate, semi-humid, and semi-arid) across 12 sites in Iran. We developed multiple linear mixed-effect models for each response variable by using multiple climatic and edaphic factors as fixed effects whereas sites as a random effect. Top 1% big, top 25% big, medium, and small trees enhanced with mean annual temperature but declined with water-related climatic (i.e. mean annual precipitation, cloud cover, potential evapotranspiration, and wet day frequency) factors, whereas soil texture (i.e. sand content) and pH were of additional importance. Species richness increased with precipitation and cloud cover but decreased with temperature, potential evapotranspiration, soil fertility and sand content. Aboveground biomass increased along temperature gradient but decreased with potential evapotranspiration, clay and sand contents. Temperature seemed to be the main driver underlying the increase in forest structure (i.e. diameter-related attributes) and biomass whereas precipitation did so for species richness. We argue that the impacts of multiple climatic factors on forest structural attributes, diversity and biomass should be properly evaluated in order to better understand the responses of species-poor forests to climate change.

Soil nutrients, forest structure and species traits drive aboveground carbon dynamics in an old-growth temperate forest

Forests store a substantial amount of terrestrial carbon (C), but the drivers of forest C dynamics remain poorly understood, especially in old-growth forests. Here, we evaluate how aboveground C dynamics (i.e., net C change and its demographic processes: C gain from the growth of surviving trees (∆C-surv), C gain from the growth of recruited trees (∆C-recr) and C loss by tree mortality (∆C-mort)) are driven by vegetation attributes (diversity, trait composition and forest structure) and habitat conditions (soil properties and light environment), as well as how ∆C-surv, ∆C-recr and ∆C-mort contribute to net C change. Using 10-year interval demographic data from a 9-ha permanent plot in an old-growth temperate forest in northeastern China, we performed structural equation model to relate the C dynamics to the vegetation attributes and habitat conditions. The net C change is most strongly determined by ∆C-mort. High soil phosphorus concentrations increased ∆C-surv, soil moisture increased ∆C-recr, and leaf area index increased both ∆C-surv and ∆C-recr. Diversity (i.e., structural diversity) had a positive relationship with ∆C-surv but was not related to ∆C-recr or ∆C-mort. Trait composition was significantly related to all three demographic processes. Forest structure was the best predictor of ∆C-surv and ∆C-recr. The net C change increased with higher soil phosphorus concentrations and basal area and in communities dominated by conservative traits (i.e., high wood density). This study highlights that soil nutrients, forest structure and trait composition are important drivers of net C change in old-growth temperate forests. Better insights into C storage and productivity can be gained by simultaneously evaluating the vegetation attributes and habitat conditions of C dynamics in natural ecosystems.

Big-sized trees overrule remaining trees' attributes and species richness as determinants of aboveground biomass in tropical forests

Large-diameter, tall-stature, and big-crown trees are the main stand structures of forests, generally contributing a large fraction of aboveground biomass, and hence play an important role in climate change mitigation strategies. Here, we hypothesized that the effects of large-diameter, tall-stature, and big-crown trees overrule the effects of species richness and remaining trees attributes on aboveground biomass in tropical forests (i.e., we term the "big-sized trees hypothesis"). Specifically, we assessed the importance of: (a) the "top 1% big-sized trees effect" relative to species richness; (b) the "99% remaining trees effect" relative to species richness; and (c) the "top 1% big-sized trees effect" relative to the "99% remaining trees effect" and species richness on aboveground biomass. Using environmental factor and forest inventory datasets from 712 tropical forest plots in Hainan Island of southern China, we tested several structural equation models for disentangling the relative effects of big-sized trees, remaining trees attributes, and species richness on aboveground biomass, while considering for the full (indirect effects only) and partial (direct and indirect effects) mediation effects of climatic and soil conditions, as well as interactions between species richness and trees attributes. We found that top 1% big-sized trees attributes strongly increased aboveground biomass (i.e., explained 55%-70% of the accounted variation) compared to species richness (2%-18%) and 99% remaining trees attributes (6%-10%). In addition, species richness increased aboveground biomass indirectly via increasing big-sized trees but via decreasing remaining trees. Hence, we show that the "big-sized trees effect" overrides the effects of remaining trees attributes and species richness on aboveground biomass in tropical forests. This study also indicates that big-sized trees may be more susceptible to atmospheric drought. We argue that the effects of big-sized trees on species richness and aboveground biomass should be tested for better understanding of the ecological mechanisms underlying forest functioning.

Multiple abiotic and biotic pathways shape biomass demographic processes in temperate forests

Forests play a key role in regulating the global carbon cycle, and yet the abiotic and biotic conditions that drive the demographic processes that underpin forest carbon dynamics remain poorly understood in natural ecosystems. To address this knowledge gap, we used repeat forest inventory data from 92,285 trees across four large permanent plots (4–25 ha in size) in temperate mixed forests in northeast China to ask the following questions: (1) How do soil conditions and stand age drive biomass demographic processes? (2) How do vegetation quality (i.e., functional trait diversity and composition) and quantity (i.e., initial biomass stocks) influence biomass demographic processes independently from soil conditions and stand age? (3) What is the relative contribution of growth, recruitment, and mortality to net biomass change? Using structural equation modeling, we showed that all three demographic processes were jointly constrained by multiple abiotic and biotic factors and that mortality was the strongest determinant on net biomass change over time. Growth and mortality, as well as functional trait diversity and the community‐weighted mean of specific leaf area (CWM_SLA), declined with stand age. By contrast, high soil phosphorous concentrations were associated with greater functional diversity and faster dynamics (i.e., high growth and mortality rates), but associated with lower CWM_SLA and initial biomass stock. More functionally diverse communities also had higher recruitment rates, but did not exhibit faster growth and mortality. Instead, initial biomass stocks and CWM_SLA were stronger predictors of biomass growth and mortality, respectively. By integrating the full spectrum of abiotic and biotic drivers of forest biomass dynamics, our study provides critical system‐level insights needed to predict the possible consequences of regional changes in forest diversity, composition, structure and function in the context of global change.