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

Latitudinal variation and driving factors of above-ground carbon proportion of large trees in old-growth forests across China

Large trees play a vital role in forest carbon stocks, dominating the distribution of community biomass. However, climate change and deforestation are reducing large trees globally, resulting in regional differences in their contribution to carbon stocks. Here, we examined the latitudinal change pattern and drivers of large trees' contributions to stand carbon stocks. Above-ground carbon storage was calculated for 530 plots in old-growth forests across China. Linear regression was used to calculate latitudinal variation in the proportion of above-ground carbon in large trees (i.e., AGC proportion). Variance partitioning and multiple linear regression were used to calculate the relative importance of species diversity, stand structure, functional traits, and environmental factors to AGC proportion. The study found that AGC proportion decreased with increasing latitude, averaging at 64.44 %. Stand structure, particularly the coefficient of variation of DBH, was identified as the key drivers of the AGC proportion. The number of common species (Hill's 1D) had no direct effect on the AGC proportion, while wood density, maximum tree height, and leaf nitrogen-to‑phosphorus ratio showed negative effects. The mass-ratio effects on AGC proportion were stronger than diversity effects. Climate variables primarily affected the AGC proportion through stand variables. These results indicate that simultaneously managing high diversity and AGC proportion may pose challenges. Moreover, considering the substantial contribution of large trees to carbon stocks, their storage capacity and sensitivity to environmental changes exert significant control over forest carbon cycles. Therefore, preserving and enhancing the carbon sink function of old-growth forests in the face of climate change and disturbance may depend primarily on protecting existing large trees and soon-to-be large-diameter trees.

Big-sized trees and higher species diversity improve water holding capacities of forests in northeast China

High water-holding forests are essential for adapting to drought climates under global warming, and a central issue is which type of forests could conserve more water in the ecosystem. This paper explores how forest structure, plant diversity, and soil physics impact forest water-holding capacities. We investigated 720 sampling plots by measuring water-holding capacities from 1440 soil and litter samples, 8400 leaves, and 1680 branches and surveying 18,054 trees in total (28 species). Water-holding capacities were measured as four soil indices (Maxwc, maximum water-holding capacity; Fcwc, field water-holding capacity; Cpwc, soil capillary water-holding capacity; Ncpwc, non-capillary water-holding capacity), two litter metrics (Maxwcl, maximum water-holding capacity of litters; Ewcl, effective water-holding capacity of litters), and canopy interception (C, the sum of estimated water interception of all branches and leaves of all tree species in the plot). We found that water-holding capacity in the big-sized tree plots was 4-25 % higher in the litters, 54-64 % in the canopy, and 6-37 % in the soils than in the small-sized plots. The higher species richness increased all soil water-holding capacities compared to the lowest richness plot. Higher Simpson and Shannon-Wiener plots had 10-27 % higher Ewcl and C than the lowest plots. Bulk density had the strongest negative relations with Maxwc, Cpwc, and Fcwc, whereas field soil water content positively affected them. Soil physics, forest structure, and plant diversity explained 90.5 %, 5.9 %, and 0.2 % of the water-holding variation, respectively. Tree sizes increased C, Ncpwc, Ewcl directly (p < 0.05), and richness increased Ewcl directly (p < 0.05). However, the direct effects from the uniform angle index (tree distribution evenness) were balanced by their indirect effect from soil physics. Our findings highlighted that the mixed forests with big-sized trees and rich species could effectively improve the water-holding capacities of the ecosystem.

Leaf stomatal traits rather than anatomical traits regulate gross primary productivity of moso bamboo (Phyllostachys edulis) stands

Leaf stomatal and anatomical traits strongly influence plant productivity. Understanding the environmental adaptation mechanisms of leaf stomatal and anatomical traits and their relationship with ecosystem productivity is essential to better understand and predict the long-term adaptation strategies to climate change of moso bamboo forests. Here, we selected 6 sites within the moso bamboo distribution area, measured 3 leaf stomatal traits and 10 leaf anatomical traits of unmanaged moso bamboo stands. We explored the spatial variation characteristics of these traits and their response to environmental changes, assessed the relationships among these traits at regional scales through network analysis, and tested the direct and indirect effects of environmental, leaf stomatal and anatomical traits on gross primary productivity (GPP) of bamboo stands using structural equation modeling (SEM). The results showed that both climate and soil factors significantly affected leaf stomatal and anatomical traits of moso bamboo. Solar radiation (SR) and mean annual precipitation (MAP) out of the climatic factors were the key drivers of variation in leaf stomatal and anatomical traits, respectively. Soil moisture and nutrients out of the soil properties significantly affected both leaf stomatal and anatomical traits of moso bamboo. Network analysis further indicated that there was a significant correlation between leaf stomata and anatomical traits. Stomatal size (SS) showed the highest centrality value at the regional scale, indicating that it plays a key role in adjusting the adaptation of plants to external environmental conditions. SEM analysis showed that environment did not directly but indirectly affect GPP via stomatal performance. The environment explained 53.3% and 39.2% of the variation in leaf stomatal and anatomical traits, respectively, and leaf stomatal traits explained 20.8% of the regional variation in GPP. Our results demonstrate a direct effect of leaf stomatal traits rather than leaf anatomical traits on bamboo ecosystem productivity, which provides new insights into model predictions of bamboo forests under global climate change.

Large plants enhance aboveground biomass in arid natural forest and plantation along differential abiotic and biotic conditions

Big-sized trees, species diversity, and stand density affect aboveground biomass in natural tropical and temperate forests. However, these relationships are unclear in arid natural forests and plantations. Here, we hypothesized that large plants (a latent variable of tall-stature and big-crown, which indicated the effect of big-sized trees on ecosystem function and structure) enhance aboveground biomass in both arid natural forests and plantations along the gradients of climate water availability and soil fertility. To prove it, we used structural equation modeling (SEM) to test the influences of large plants located in 20% of the sequence formed by individual size (a synthetical value calculated from tree height and crown) on aboveground biomass in natural forests and plantations while considering the direct and indirect influences of species diversity as well as climatic and soil conditions, using data from 73 natural forest and 30 plantation plots in the northwest arid region of China. The results showed that large plants, species diversity, and stand density all increased aboveground biomass. Soil fertility declined aboveground biomass in natural forest, whereas it increased biomass in plantation. Although climatic water availability had no direct impact on aboveground biomass in both forests, it indirectly controlled the change of aboveground biomass via species diversity, stand density, and large plants. Stand density negatively affects large plants in both natural forests and plantations. Species diversity positively affects large plants on plantations but not in natural forests. Large plants increased slightly with increasing climatic water availability in the natural forest but decreased in plantation, whereas soil fertility inhibited large plants in plantation only. This study highlights the extended generality of the big-sized trees hypothesis, scaling theory, and the global importance of big-sized tree in arid natural forests and plantations.

Multiple drivers influence tree species diversity and above-ground carbon stock in second-growth Atlantic forests: Implications for passive restoration

Second-growth forests (SGF) are critical components for limiting biodiversity loss and climate change mitigation. However, these forests were established after anthropic disturbances such as land use for planting, and in highly human-modified landscapes. These interventions can decrease the ability of biological communities to recover naturally, and it is necessary to understand how multiple drivers, from local scale to landscape scale influence the diversity and carbon stock of these forests in natural regeneration. For this, we used data from 37 SGF growing on areas previously used for eucalyptus plantations in the Brazilian Atlantic Forest, after the last cut cycle. For each SGF, the forest tree species diversity was calculated based on the Hills number, and we also calculated the above-ground carbon stock. Then, we evaluated the influence of multiple environmental factors on these indexes: soil properties, past-management intensity, patch configuration, and landscape composition. Little influence of soil properties was found, only soil fertility negatively influenced above-ground carbon stock. However, past-management intensity negatively influenced tree species diversity and carbon stock. The isolation of other forests and tree species propagules source distance (>500 ha) also negatively influenced the diversity of species. This is probably due to the favoring of tree pioneer species in highly human-modified landscapes because they are more tolerant of environmental changes, less dependent on animal dispersal, and have low carbon stock capacity. Thus, areas with higher past-management intensity and more isolated areas are less effective for passive restoration and may require intervention to recover tree diversity and carbon stock in the Atlantic Forest. The approach, which had not yet been applied in the Atlantic Forest, brought similar results to that found in other forests, and serves as a theoretical basis for choosing priority areas for passive restoration in the biome.

Tropical forest strata shifts in plant structural diversity-aboveground carbon relationships along altitudinal gradients

Aboveground carbon storage in forests can be influenced by both structural and compositional diversity of plant communities. However, the relative and interactive effects of structural and compositional diversity on multilevel aboveground carbon storage across forest strata and how these relationships vary with altitude and soil nutrients remain unclear. Using data obtained from 34 tropical forest plots (total area 8.5 ha) in Hainan Island, China, we analyzed the relationships between aboveground carbon at four levels (litter, understory, overstory, and whole-community) with structural diversity (diameter and height diversity) and compositional diversity (species diversity and evenness) in the understory and overstory. The direct and indirect effects of altitude, soil nutrients (total N and total P and N/P ratio), structural diversity, and compositional diversity on aboveground carbon were explored via Bayesian structural equation modeling. The results showed that structural diversity, rather than compositional diversity, in overstory stratum determined aboveground carbon. Specifically, overstory structural diversity was negatively associated with understory carbon, while positively associated with overstory and whole-community carbon. Furthermore, diversity‑carbon relationships were slightly affected by soil nutrients but strongly by altitude. Specifically, the relationship between overstory and whole-community carbon content with overstory tree height diversity weakened with altitude, while their relationship with overstory diameter diversity strengthened. Altitude directly and indirectly affected overstory tree height and diameter diversity through overstory species diversity, thereby reducing understory and increasing overstory and whole-community carbon. Altitude directly promoted litter carbon. We provide evidence that the effects of plant diversity on aboveground carbon storage are forest strata- and altitude-dependent. As overstory structural diversity plays a crucial role in storing aboveground carbon at all altitudes, we proposed that focusing on overstory structural diversity would be promising for predicting trends in how plant diversity affects aboveground carbon in response to climate change.

Big-sized trees and species-functional diversity pathways mediate divergent impacts of environmental factors on individual biomass variability in Sri Lankan tropical forests

In tropical forests, several studies have explored the effects of environmental factors and tree species diversity as well as functional trait diversity and trait composition on aboveground biomass (AGB) stock. However, these abiotic and biotic effects on individual biomass variability (BioVar) are still largely unexplored, which limits our understanding of the plant-plant interactions for species coexistence. Here, we used the Partial Least Squares Structural Equation Models (PLS-SEMs), and other complementary analyses, on data from 189 tropical forest plots in Sri Lanka, to test the linkages amongst climate (a latent variable of solar radiation and potential evapotranspiration), soil (pH and cation exchange capacity), plot (plot size and stand density) conditions, big-sized trees, species-functional diversity, and BioVar. The PLS-SEMs showed that climate conditions decreased BioVar directly but increased indirectly via integrative promoting direct effects on soil conditions, species-functional diversity and big-sized trees. In contrast, soil conditions increased BioVar directly but decreased indirectly via integrative suppressing direct effects on species-functional diversity and big-sized trees. Interestingly, we found that the divergent indirect effects of climate and soil conditions on BioVar via big-sized trees mattered when the direct effect of big-sized trees on species-functional diversity was considered as compared to the reverse effect in PLS-SEMs. Also, the indirect positive effect of plot properties on BioVar was nearly equal to the direct effect because plot properties affected big-sized trees as similar as or lower than species-functional diversity. The positive effect of species-functional diversity on BioVar was mediated by the structural attributes of big-sized trees, indicating increased plant species co-existence. This study suggests that individual tree biomass variability (i.e., BioVar) should be considered for managing natural tropical forests in the context of the plant-plant interactions for species coexistence.

Large-scale patterns of understory biomass and its allocation across China's forests

Plant biomass storage and its allocation reflect the ecosystem productivity and adaptation to different environments. Understory vegetation is a significant component of any forest ecosystem and plays a vital role in biodiversity maintenance and the ecosystem's carbon cycle. Although many studies have addressed the relationships of climate, stand structure and resource availability with understory biomass and its allocation at local scales, the large-scale variation of understory biomass and allocation and their underlying mechanisms remain unclear. We compiled a large database of understory biomass at the community level across China's forests to explore the large-scale patterns of understory biomass and R/S ratio, and to quantify the relative importance of drivers. Understory biomass and R/S ratio varied largely with forest types, and decreased with increasing longitude, but increased with elevation. Understory biomass increased with increasing latitude, mean annual temperature (MAT), and mean annual precipitation (MAP), while the R/S ratio decreased with latitude, MAT, and MAP. Stand structure had a strong effect on the variations in understory biomass. MAP was the most important driver in determining R/S ratio. This synthesis provides a first assessment of the large-scale patterns of understory biomass and allocation and sheds new light on the mechanisms underlying the variations in understory biomass and its allocation over a broad geographic scale. These findings will improve predictions of understory community dynamics in response to climate change and aid in further optimizing ecosystem process models.

Land use intensity determines soil properties and biomass recovery after abandonment of agricultural land in an Amazonian biodiversity hotspot

There has been widespread clearance of tropical forests for agriculture, but in many cases the cultivation phase is only transient. The secondary forests recovering on these abandoned sites may contribute to mitigation of greenhouse gas emissions and protection of biodiversity, but the rates of recovery may be dependent on land-use intensity and changes in soil properties during cultivation. However fine-scale details on these changes are poorly known for many tropical forest locations. We quantified soil properties and recovery of woody biomass in 42 tropical forest fragments representing a chronosequence following two types of agricultural land-uses, and in 15 comparable reference old growth forests, between the Andes and the Amazon in Peru. Soil fertility, particularly base cation concentrations, responded negatively to increasing intensity of agricultural land-use, and either decreased or increased with time after abandonment dependent on prior land-use. The predicted mean recovery rate of woody biomass over the first 20 years following abandonment matched that predicted by a general model for the Neotropics, but recovery was three-fold higher on sites abandoned following traditional agriculture than on sites recovering from intensive agriculture. Estimated total biomass recovered to just above half that of reference old growth forests within 71 years. The inclusion of the biomass of lianas and smaller tree stems did not modify the apparent rate of ecosystem biomass recovery, however the proportion of the total biomass stored in small stems was greater following intensive than traditional agriculture, which suggests that patterns of stand structural development are sensitive to land-use history. We conclude that effects of historic land use on soil nutrient concentrations and their changes through time are required for a more complete interpretation of variation in biomass recovery rates at local scales. These results also highlight the critical importance of contemporary agricultural intensification for carbon storage in tropical forests.

The Contribution of Trees Outside of Forests to Landscape Carbon and Climate Change Mitigation in West Africa

While closed canopy forests have been an important focal point for land cover change monitoring and climate change mitigation, less consideration has been given to methods for large scale measurements of trees outside of forests. Trees outside of forests are an important but often overlooked natural resource throughout sub-Saharan Africa, providing benefits for livelihoods as well as climate change mitigation and adaptation. In this study, the development of an individual tree cover map using very high-resolution remote sensing and a comparison with a new automated machine learning mapping product revealed an important contribution of trees outside of forests to landscape tree cover and carbon stocks in a region where trees outside of forests are important components of livelihood systems. Here, we test and demonstrate the use of allometric scaling from remote sensing crown area to provide estimates of landscape-scale carbon stocks. Prominent biomass and carbon maps from global-scale remote sensing greatly underestimate the “invisible” carbon in these sparse tree-based systems. The measurement of tree cover and carbon in these landscapes has important application in climate change mitigation and adaptation policies.

Structural diversity and tree density drives variation in the biodiversity-ecosystem function relationship of woodlands and savannas

Positive biodiversity-ecosystem function relationships (BEFRs) have been widely documented, but it is unclear if BEFRs should be expected in disturbance-driven systems. Disturbance may limit competition and niche differentiation, which are frequently posited to underlie BEFRs. We provide the first exploration of the relationship between tree species diversity and biomass, one measure of ecosystem function, across southern African woodlands and savannas, an ecological system rife with disturbance from fire, herbivores and humans. We used > 1000 vegetation plots distributed across 10 southern African countries and structural equation modelling to determine the relationship between tree species diversity and above-ground woody biomass, accounting for interacting effects of resource availability, disturbance by fire, tree stem density and vegetation type. We found positive effects of tree species diversity on above-ground biomass, operating via increased structural diversity. The observed BEFR was highly dependent on organismal density, with a minimum threshold of c. 180 mature stems ha^-1 . We found that water availability mainly affects biomass indirectly, via increasing species diversity. The study underlines the close association between tree diversity, ecosystem structure, environment and function in highly disturbed savannas and woodlands. We suggest that tree diversity is an under-appreciated determinant of wooded ecosystem structure and function.

Species Identity of Large Trees Affects the Composition and the Spatial Structure of Adjacent Trees

Large trees are keystone structures for the functioning and maintenance of the biological diversity of wooded landscapes. Thus, we need a better understanding of large-tree–other-tree interactions and their effects on the diversity and spatial structure of the surrounding trees. We studied these interactions in the core of the Białowieża Primeval Forest—Europe’s best-preserved temperate forest ecosystem, characterized by high abundance of ancient trees. We measured diameter and bark thickness of the monumental trees of Acer platanoides L., Carpinus betulus L., Picea abies L. H. Karst, Quercus robur L., and Tilia cordata Mill., as well as the diameter and distance to the monumental tree of five nearest neighbor trees. The effects of the monumental tree on arrangements of the surrounding trees were studied with the help of linear models. We revealed that the species identity of a large tree had, in the case of C. betulus and T. cordata, a significant impact on the diversity of adjacent tree groupings, their distance to the central tree, and frequency of the neighboring trees. The distance between the neighbor and the large trees increased with the increasing diameter of the central tree. Our findings reinforce the call for the protection of large old trees, regardless of their species and where they grow from the geographical or ecosystem point of view.

Estimating Primary Forest Attributes and Rare Community Characteristics Using Unmanned Aerial Systems (UAS): An Enrichment of Conventional Forest Inventories

The techniques for conducting forest inventories have been established over centuries of land management and conservation. In recent decades, however, compelling new tools and methodologies in remote sensing, computer vision, and data science have offered innovative pathways for enhancing the effectiveness and comprehension of these sampling designs. Now with the aid of Unmanned Aerial Systems (UAS) and advanced image processing techniques, we have never been closer to mapping forests at field-based inventory scales. Our research, conducted in New Hampshire on complex mixed-species forests, used natural color UAS imagery for estimating individual tree diameters (diameter at breast height (dbh)) as well as stand level estimates of Basal Area per Hectare (BA/ha), Quadratic Mean Diameter (QMD), Trees per Hectare (TPH), and a Stand Density Index (SDI) using digital photogrammetry. To strengthen our understanding of these forests, we also assessed the proficiency of the UAS to map the presence of large trees (i.e., >40 cm in diameter). We assessed the proficiency of UAS digital photogrammetry for identifying large trees in two ways: (1) using the UAS estimated dbh and the 40 cm size threshold and (2) using a random forest supervised classification and a combination of spectral, textural, and geometric features. Our UAS-based estimates of tree diameter reported an average error of 19.7% to 33.7%. At the stand level, BA/ha and QMD were overestimated by 42.18% and 62.09%, respectively, while TPH and SDI were underestimated by 45.58% and 3.34%. When considering only stands larger than 9 ha however, the overestimation of BA/ha at the stand level dropped to 14.629%. The overall classification of large trees, using the random forest supervised classification achieved an overall accuracy of 85%. The efficiency and effectiveness of these methods offer local land managers the opportunity to better understand their forested ecosystems. Future research into individual tree crown detection and delineation, especially for co-dominant or suppressed trees, will further support these efforts.

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.

Tree Height Measurements in Degraded Tropical Forests Based on UAV-LiDAR Data of Different Point Cloud Densities: A Case Study on Dacrydium pierrei in China

Tropical forest degradation is a major contributor to greenhouse gas emissions. Tree height can be used as an important predictor of forest growth, and yield models can provide basic data for forest degradation assessments. As an important parameter of unmanned aerial vehicle-light detection and ranging (UAV-LiDAR), it is not clear how the point cloud density affects the extraction accuracy of tree height in degraded tropical rain forests. To solve this problem, we collected UAV-LiDAR data at a flight altitude of 150 m, and then resampled the UAV-LiDAR data obtained according to the point cloud density percentage resampling method and obtained UAV-LiDAR data for five different point cloud densities, namely, 12, 17, 28, 64, and 108 points/m2. On the basis of the resampled LiDAR data, we generated a canopy height model (CHM) to extract the height of Dacrydium pierrei (D. pierrei). The results show that (1) With the increase in the point cloud density, the accuracy of tree height extraction gradually increased, with a maximum accuracy at 108 points/m2 (root mean squared error (RMSE)% = 22.78%, bias% = 14.86%). The accuracy (RMSE%) increased by 6.92% as the point cloud density increased from 12 points/m2 to 17 points/m2, but only increased by 0.99% as the point cloud density increased from 17 points/m2 to 108 points/m2, indicating that 17 points/m2 is a critical point for tree height extraction of D. pierrei. (2) Compared with the results from broad-leaved forests, the accuracy of D. pierrei height extraction from coniferous forest was higher. With the increase in point cloud density, the difference in the accuracy of D. pierrei height between two stands gradually increased. When the point cloud density was 108 points/m2, the differences in RMSE% and bas% were 3.55% and 6.22%, respectively. When the point cloud density was 12 points/m2, the differences in RMSE% and bias% were 2.71% and 4.69%, respectively. Our research identified the lowest LiDAR data point cloud density required to ensure a certain accuracy in tree height extraction, which will help scholars formulate UAV-LiDAR forest resource survey plans.

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.

Ecosystem-level carbon storage and its links to diversity, structural and environmental drivers in tropical forests of Western Ghats, India

Tropical forests are rich in biodiversity with great potential for carbon (C) storage. We estimated ecosystem-level C stock using data from 70 forest plots in three major forest types: tropical dry deciduous (TDD I and TDD II), tropical semi-evergreen (TSE I and TSE II) and tropical evergreen forests (TEF I, TEF II and TEF III) of Kanyakumari Wildlife Sanctuary, Western Ghats, India. The average C stock in these forests was 336.8 Mg C/ha, of which 231.3, 3.0, 2.4, 15.2 and 84.9 Mg C/ha were stored in woody vegetation, understorey, litter, deadwood and soil respectively. The live vegetation, detritus and soil contributed 65.5%, 5.5% and 29% respectively to the total ecosystem-level C stock and distributed in forest types in the order: TEF III > TEF II > TEF I > TSE I > TDD II > TSE II > TDD I. The plant diversity, structural attributes and environmental factors showed significant positive correlations with C stocks and accounted for 6.7, 77.2 and 16% of variance. These findings indicate that the tropical forests in the Western Ghats store large amount of C, and resulting data are invaluable for planning and monitoring forest conservation and management programs to enhance C storage in tropical forests.

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.

Sustainability of High-Value Timber Species in Mixed Conifer–Broadleaf Forest Managed under Selection System in Northern Japan

Understanding the sustainability of high-value timber species in managed forests provides useful information for the management of these species in the long-run. Using nearly 50 years of census data in long-term permanent plots, we investigated the sustainability of three high-value timber species—monarch birch (Betula maximowicziana Regel), castor aralia (Kalopanax septemlobus (Thunb.) Koidz), and Japanese oak (Quercus crispula Blume)—in cool-temperate mixed forest under a selection system in northern Japan. We used stocking, demographic parameters, and species proportions of these species as measures of sustainability. Results showed that the tree density and basal area of the three high-value timber species increased during the study period. Moreover, the basal area increment of these species showed an increasing trend across census periods. However, while no significant differences in the tree mortality of these species were observed, the numbers of in-growth fluctuated across census periods. Increasing trends in species proportions of monarch birch and Japanese oak were observed. Even though there were some fluctuations across census periods, especially in smaller diameter classes, diameter distribution curves of high-value timber species followed a reversed J-shaped pattern. The results revealed that the sustainability measures of high-value timber species can be achieved in forest stands managed under single-tree selection system. In addition, the results also indicated the changing structure and composition of the forest stand. The stocking and basal area increment of conifers decreased while those of broadleaves increased. The proportion of conifers decreased to 33.01% in 2008–2016 from 48.35% in 1968–1978. The results of this study would be useful for adapting silvicultural practices and harvesting practices as well as for simulating various silvicultural and management options for high-value timber species.

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.

Comparing Individual Tree Height Information Derived from Field Surveys, LiDAR and UAV-DAP for High-Value Timber Species in Northern Japan

High-value timber species such as monarch birch (Betula maximowicziana Regel), castor aralia (Kalopanax septemlobus (Thunb.) Koidz), and Japanese oak (Quercus crispula Blume) play important ecological and economic roles in forest management in the cool temperate mixed forests in northern Japan. The accurate measurement of their tree height is necessary for both practical management and scientific reasons such as estimation of biomass and site index. In this study, we investigated the similarity of individual tree heights derived from conventional field survey, digital aerial photographs derived from unmanned aerial vehicle (UAV-DAP) data and light detection and ranging (LiDAR) data. We aimed to assess the applicability of UAV-DAP in obtaining individual tree height information for large-sized high-value broadleaf species. The spatial position, tree height, and diameter at breast height (DBH) were measured in the field for 178 trees of high-value broadleaf species. In addition, we manually derived individual tree height information from UAV-DAP and LiDAR data with the aid of spatial position data and high resolution orthophotographs. Tree heights from three different sources were cross-compared statistically through paired sample t-test, correlation coefficient, and height-diameter model. We found that UAV-DAP derived tree heights were highly correlated with LiDAR tree height and field measured tree height. The performance of individual tree height measurement using traditional field survey is likely to be influenced by individual species. Overall mean height difference between LiDAR and UAV-DAP derived tree height indicates that UAV-DAP could underestimate individual tree height for target high-value timber species. The height-diameter models revealed that tree height derived from LiDAR and UAV-DAP could be better explained by DBH with lower prediction errors than field measured tree height. We confirmed the applicability of UAV-DAP data for obtaining the individual tree height of large-size high-value broadleaf species with comparable accuracy to LiDAR and field survey. The result of this study will be useful for the species-specific forest management of economically high-value timber species.

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.