Tree Size Inequality Reduces Forest Productivity: An Analysis Combining Inventory Data for Ten European Species and a Light Competition Model

Disentangling linkages between satellite-derived indicators of forest structure and productivity for ecosystem monitoring

The essential biodiversity variables (EBV) framework has been proposed as a monitoring system of standardized, comparable variables that represents a minimum set of biological information to monitor biodiversity change at large spatial extents. Six classes of EBVs (genetic composition, species populations, species traits, community composition, ecosystem structure and ecosystem function) are defined, a number of which are ideally suited to observation and monitoring by remote sensing systems. We used moderate-resolution remotely sensed indicators representing two ecosystem-level EBV classes (ecosystem structure and function) to assess their complementarity and redundancy across a range of ecosystems encompassing significant environmental gradients. Redundancy analyses found that remote sensing indicators of forest structure were not strongly related to indicators of ecosystem productivity (represented by the Dynamic Habitat Indices; DHIs), with the structural information only explaining 15.7% of the variation in the DHIs. Complex metrics of forest structure, such as aboveground biomass, did not contribute additional information over simpler height-based attributes that can be directly estimated with light detection and ranging (LIDAR) observations. With respect to ecosystem conditions, we found that forest types and ecosystems dominated by coniferous trees had less redundancy between the remote sensing indicators when compared to broadleaf or mixed forest types. Likewise, higher productivity environments exhibited the least redundancy between indicators, in contrast to more environmentally stressed regions. We suggest that biodiversity researchers continue to exploit multiple dimensions of remote sensing data given the complementary information they provide on structure and function focused EBVs, which makes them jointly suitable for monitoring forest ecosystems.

Structural diversity is better associated with forest productivity than species or functional diversity

Understanding the relationship between biodiversity and productivity can be advanced by improving metrics used to quantify biodiversity. Structural diversity, that is, variation of size and form of plant organs, is an emerging biodiversity metric. However, compared with the other biodiversity metrics, its relative importance in specific components of forest productivity, for example, recruitment of new individuals, biomass net change after accounting for mortality, is largely unknown, particularly across a large spatial scale with multiple influential gradients. To address the knowledge gap, we used USDA Forest Service Forest Inventory and Analysis (FIA) data across the southcentral USA from 2008 to 2017. We calculated forest biomass increments due to recruitment and growth and net change in biomass. Then, we quantified the effects of a range of abiotic and biotic variables on the biomass increments and net change. Our results showed that (1) Structural diversity was negatively associated with the two biomass increments and net change in biomass. The negative effects were supported by increased occurrences of insects and diseases with greater structural diversity. (2) Compared with species and functional diversity, structural diversity showed a better association with biomass increments and net change, suggested by its larger absolute values of standardized coefficients, and the effects of structural diversity were negative in contrast to species diversity. (3) The effects of structural diversity, stand age, and elevation differed between natural and planted forests that may stem from the differences in stand development and species composition between the two forest types. Together, structural diversity may represent an important dimension of biodiversity impacts on plant productivity, which could be related to the exacerbated disturbances with greater structural diversity.

Species asynchrony stabilizes productivity over 20 years in Northeast China

The stability of forest productivity can reflect the functioning of forest ecosystems. It is a crucial topic to understand the relationship between biodiversity and ecosystem functions in ecology. Although previous studies have made great progress in understanding the effects of diversity, species asynchrony, and other factors on community biomass and productivity, few studies have explored how these factors affect the temporal stability of productivity. In this study, we hypothesized that diversity, species asynchrony, and topography would directly or indirectly impact the temporal stability of productivity. To test this hypothesis, we used a multiple regression model and a piecewise structural equation model based on the inventory data over 20 years (5-year intervals) from 1992 to 2012 at Jingouling Forest Farm in Northeast China. Our results showed that species asynchrony was the main driving factor affecting the temporal stability of productivity. Structural diversity significantly decreased community stability, while species diversity had a nonsignificant effect on it. We found the combination of a multiple regression model and a piecewise structural equation model is an effective method for evaluating the factors that influence community stability. The effect of species asynchrony is crucial for understanding the ecological mechanisms underlying the diversity-stability relationship in mixed forests.

Factors influencing productivity of pine-dominated stands in South Korea

Stand productivity research has mainly focused on increasing yield and has recently begun to examine changes in carbon storage. The Korean government is interested in finding ways to increase forest carbon capture to meet carbon neutrality requirements because approximately 63% of the land is covered by forests. In addition, 69% of these forests are older than 30 years old and their productivity and aboveground carbon storage rates are expected to decline. The purpose of this study was to examine the effect of quadratic mean diameter (QMD), stand basal area, site index, slope, climate (MAT and MAP), stand age, stand structural diversity, and stand composition on the productivity of aging Korean red pine-dominated stands. Based on the effects of these factors, we explored how to manage pine forests with the focus of increasing their productivity. Random forest regression was used for the analysis, and periodic basal area increment (PBAI) was used as the dependent variable of stand productivity. Our results show that the most influential factor on stand productivity was QMD. PBAI dramatically decreased from approximately 0.8 to 0.53 m²/ha·year as QMD increased up to 18 cm. Since diameter (QMD) increment is closely associated with changes in tree competition; increasing tree competition with increasing QMD and stand basal area may lead to decreases in PBAI owing to decreases in growth rate due to space and resource limitations and increases in mortality. PBAI decreased when basal area increased from 22 to 51.5 m²/ha. PBAI increased for site index values between 8 and 12.5 m and decreased for stand age values up to approximately 31 years. For climate factors, PBAI generally increased with increasing MAP and slightly increased as MAT increased up to approximately 11.2 °C and then decreased at higher MAT. PBAI initially increased with increasing slope values, decreased with values lower than 15°, and remained stable at slope values in the range of 16-34°. Stand structural diversity, which ranged from 1.32 to 1.62, exhibited a similar negative influence on PBAI associated with increasing stand density. With regard to pine composition, pine stands with a large proportion of pine basal area, showed higher productivity due to the simple stand structure resulting in better growth of shade intolerant pine. This study found that stand density increases with the development of pine stands and that density increases had negative influences on stand productivity. Collectively, our results suggest that stand density management is essential for increasing stand productivity and carbon sequestration in the Korean red pine-dominated stands of South Korea.

Topography, Diversity, and Forest Structure Attributes Drive Aboveground Carbon Storage in Different Forest Types in Northeast China

Forests regulate air quality and respond to climate change by storing carbon. Assessing the driving factors of forest aboveground carbon (AGC) storage is of great importance for forest management. We assumed that different forest types would affect the relationship between species richness, stand density, individual tree size variation, and AGC. In order to test and verify it, we analyzed the inventory data of 206 fixed plots (20 m × 20 m) of Jingouling Forest Farm, taking advantage of the piecewise structural equation model (pSEM) to explore the effects of species diversity, stand structure attributes, and topography on the AGC storage in the Wangqing Forest in Jilin Province. In addition, in this study, we aimed to investigate whether the fixed factors (species diversity, stand structure attributes, and topography) influenced AGC storage more significantly than the random factor (forest type). According to the results of pSEM, the selected factors jointly explain the impact on 33% of AGC storage. The relationship between stand density and AGC is positive, and the impact of individual tree size variation on AGC storage is negative. Species richness has direct and indirect impacts on AGC storage, and the indirect impact is more significant through individual tree size variation. Both elevation and slope are significantly negatively associated with AGC storage. Forest type explains the impact on 12% of AGC storage, which means the relationship between AGC and predictors varies across forest types. The results provide a scientific basis for the protection and management decision of natural forests in northeastern China.

Intra-specific leaf trait variability of F. sylvatica, Q. petraea and P. abies in response to inter-specific competition and implications for forest functioning

Variability in functional traits (FT) is increasingly used to understand the mechanisms behind tree species interactions and ecosystem functioning. In order to explore how FT differ due to interactions between tree species and its influence on stand productivity and other ecological processes, we examined the effects of tree species composition on the intra-specific variability of four widely measured FT: specific leaf area, leaf nitrogen content, leaf angle and stomatal conductance response to vapor pressure deficit. This study focused on three major central European tree species: European beech (Fagus sylvatica L.), Sessile oak (Quercus petraea Liebl.) and Norway spruce (Picea abies [L.] H. Karst.). Each species was examined in monoculture and two-species mixtures in the 13-year-old tree biodiversity experiment BIOTREE-Kaltenborn. Trait distributions and linear mixed models were used to analyze the effect of species mixing, tree size and stand variables on the intra-specific FT variability. A significant effect of branch height on most traits and species indicated a vertical gradient of foliar trait frequently related to light availability. Beech and oak showed a high overall trait variability and sensitivity to species mixing and stand basal area, while the trait variability of spruce was limited. Greater shifts in trait distributions due to mixing were found in specific leaf area for oak and leaf nitrogen content for beech. Thus intra-specific variability of key leaf traits was already influenced at this young development stage by inter-specific interactions. Finally, we used the 3-PG (Physiological Processes Predicting Growth) process-based forest growth model to show that the measured intra-specific variability on single FT values could influence stand productivity, light absorption and transpiration, although the net effect depends on the considered trait and the species composition of the mixture. The results of this study will aid better understanding of the effects of inter-specific competition on intra-specific FT variability, which has implications for the parameterization of process-based forest growth models and our understanding of ecosystem functioning.

Individual Tree Detection and Qualitative Inventory of a Eucalyptus sp. Stand Using UAV Photogrammetry Data

Digital aerial photogrammetry (DAP) data acquired by unmanned aerial vehicles (UAV) have been increasingly used for forest inventory and monitoring. In this study, we evaluated the potential of UAV photogrammetry data to detect individual trees, estimate their heights (ht), and monitor the initial silvicultural quality of a 1.5-year-old Eucalyptus sp. stand in northeastern Brazil. DAP estimates were compared with accurate tree locations obtained with real time kinematic (RTK) positioning and direct height measurements obtained in the field. In addition, we assessed the quality of a DAP-UAV digital terrain model (DTM) derived using an alternative ground classification approach and investigated its performance in the retrieval of individual tree attributes. The DTM built for the stand presented an RMSE of 0.099 m relative to the RTK measurements, showing no bias. The normalized 3D point cloud enabled the identification of over 95% of the stand trees and the estimation of their heights with an RMSE of 0.36 m (11%). However, ht was systematically underestimated, with a bias of 0.22 m (6.7%). A linear regression model, was fitted to estimate tree height from a maximum height metric derived from the point cloud reduced the RMSE by 20%. An assessment of uniformity indices calculated from both field and DAP heights showed no statistical difference. The results suggest that products derived from DAP-UAV may be used to generate accurate DTMs in young Eucalyptus sp. stands, detect individual trees, estimate ht, and determine stand uniformity with the same level of accuracy obtained in traditional forest inventories.

Seeing the wood despite the trees: Exploring human disturbance impact on plant diversity, community structure, and standing biomass in fragmented high Andean forests

High Andean forests harbor a remarkably high biodiversity and play a key role in providing vital ecosystem services for neighboring cities and settlements. However, they are among the most fragmented and threatened ecosystems in the neotropics. To preserve their unique biodiversity, a deeper understanding of the effects of anthropogenic perturbations on them is urgently needed. Here, we characterized the plant communities of high Andean forest remnants in the hinterland of Bogotá in 32 0.04 ha plots. We assessed the woody vegetation and sampled the understory and epiphytic cover. We gathered data on compositional and structural parameters and compiled a broad array of variables related to anthropogenic disturbance, ranging from local to landscape-wide metrics. We also assessed phylogenetic diversity and functional diversity. We employed nonmetric multidimensional scaling (NMDS) to select meaningful variables in a first step of the analysis. Then, we performed partial redundancy analysis (pRDA) and generalized linear models (GLMs) in order to test how selected environmental and anthropogenic variables are affecting the composition, diversity, and aboveground biomass of these forests. Identified woody vegetation and understory layer communities were characterized by differences in elevation, temperature, and relative humidity, but were also related to different levels of human influence. We found that the increase of human-related disturbance resulted in less phylogenetic diversity and in the phylogenetic clustering of the woody vegetation and in lower aboveground biomass (AGB) values. As to the understory, disturbance was associated with a higher diversity, jointly with a higher phylogenetic dispersion. The most relevant disturbance predictors identified here were as follows: edge effect, proximity of cattle, minimum fragment age, and median patch size. Interestingly, AGB was efficiently predicted by the proportion of late successional species. We therefore recommend the use of AGB and abundance of late successional species as indicators of human disturbance on high Andean forests.

Exploring the Influence of Biological Traits and Environmental Drivers on Water Use Variations across Contrasting Forests

Understanding species-specific water use patterns across contrasting sites and how sensitivity of responses to environmental variables changes for different species is critical for evaluating potential forest dynamics and land use changes under global change. To quantify water use patterns and the sensitivity of tree transpiration to environmental drivers among sites and species, sap flow and meteorological data sets from three contrasting climatic zones were combined and compared in this analysis. Agathis australis from NZHP site, Schima wallichii Choisy (native) and Acacia mangium Willd (exotic) from CHS site, Liquidamber formosana Hance, Quercus variabilis Blume and Quercus acutissima Carruth from CJGS site were the dominant trees chosen as our study species. Biological traits were collected to explain the underlying physiological mechanisms for water use variation. Results showed that the strongest environmental drivers of sap flow were photosynthetically active radiation (PAR), vapor pressure deficit (VPD) and temperature across sites, indicating that the response of water use to abiotic drivers converged across sites. Water use magnitude was site specific, which was controlled by site characteristics, species composition and local weather conditions. The species with higher sap flow density (Fd) generally had greater stomatal conductance. Native deciduous broadleaved species had a higher Fd and faster response to stomatal regulation than that of native evergreen broadleaved species (S. wallichii) and conifer species A. australis. The analysis also showed that exotic species (A. mangium) consumed more water than native species (S. wallichii). Trees with diffuse porous and lower wood density had relatively higher Fd for angiosperms, suggesting that water use was regulated by physiological differences. Water use characteristics across sites are controlled by both external factors such as site-specific characteristics (local environmental conditions and species composition) and internal factors such as biological traits (xylem anatomy, root biomass and leaf area), which highlights the complexity of quantifying land water budgets for areas covered by different species.

Agents Affecting the Productivity of Pine Plantations on the Loess Plateau in China: A Study Based on Structural Equation Modeling

Stability and productivity are important indicators used to measure the state of forest ecosystems. Artificial forests populations with reasonable structures and strong stability are critical for ecosystem productivity. Previous studies have focused on individual factors, while the mechanisms of how multiple factors affect population productivity remain unknown. We used 57 plots in a Chinese pine (Pinus tabuliformis) plantation to investigate 23 stand factors and analyzed the relationships among site factors, population structure, population stability, and population productivity using partial least square-structural equation modeling (PLS-SEM). The results showed that the population productivity of the plantation was directly affected by the population stability latent variable but indirectly affected by the site conditions latent variables (indirect effect path coefficient = 0.249) and forest structure (indirect effect path coefficient = 0.222). However, the site conditions latent variable was the main factor directly affecting the population stability latent variables; the total effect was 0.511 (direct effect path coefficient = 0.307, indirect effect path coefficient = 0.204), and the influence of forest structure on population stability was lower than that of the site conditions latent variable (direct effect path coefficient = 0.454). The factor with the greatest weight among the site conditions latent variable was slope (0.747), indicating that slope contributes the most to latent variables related to forest population stability. Among all variables affecting the forest stability latent variables, forest density had the highest weight value (0.803), and the weight value of forest mortality was lower than that of forest density. The weights of the latent variables associated with population structure from high to low were canopy density, the uniform angle index, and the spatial competition index, indicating that competition for space had the lowest influence on the population stability latent variables. The results provide new insights and ideas for quantifying relationships among different driving factors and a basis for scientific and rational plantation management.

Individual Tree Attribute Estimation and Uniformity Assessment in Fast-Growing Eucalyptus spp. Forest Plantations Using Lidar and Linear Mixed-Effects Models

Fast-growing Eucalyptus spp. forest plantations and their resultant wood products are economically important and may provide a low-cost means to sequester carbon for greenhouse gas reduction. The development of advanced and optimized frameworks for estimating forest plantation attributes from lidar remote sensing data combined with statistical modeling approaches is a step towards forest inventory operationalization and might improve industry efficiency in monitoring and managing forest resources. In this study, we first developed and tested a framework for modeling individual tree attributes in fast-growing Eucalyptus forest plantation using airborne lidar data and linear mixed-effect models (LME) and assessed the gain in accuracy compared to a conventional linear fixed-effects model (LFE). Second, we evaluated the potential of using the tree-level estimates for determining tree attribute uniformity across different stand ages. In the field, tree measurements, such as tree geolocation, species, genotype, age, height (Ht), and diameter at breast height (dbh) were collected through conventional forest inventory practices, and tree-level aboveground carbon (AGC) was estimated using allometric equations. Individual trees were detected and delineated from lidar-derived canopy height models (CHM), and crown-level metrics (e.g., crown volume and crown projected area) were computed from the lidar 3-D point cloud. Field and lidar-derived crown metrics were combined for ht, dbh, and AGC modeling using an LME. We fitted a varying intercept and slope model, setting species, genotype, and stand (alone and nested) as random effects. For comparison, we also modeled the same attributes using a conventional LFE model. The tree attribute estimates derived from the best LME model were used for assessing forest uniformity at the tree level using the Lorenz curves and Gini coefficient (GC). We successfully detected 96.6% of the trees from the lidar-derived CHM. The best LME model for estimating the tree attributes was composed of the stand as a random effect variable, and canopy height, crown volume, and crown projected area as fixed effects. The %RMSE values for tree-level height, dbh, and AGC were 8.9%, 12.1%, and 23.7% for the LFE model and improved to 7.3%, 7.1%, and 13.6%, respectively, for the LME model. Tree attributes uniformity was assessed with the Lorenz curves and tree-level estimations, especially for the older stands. All stands showed a high level of tree uniformity with GC values approximately 0.2. This study demonstrates that accurate detection of individual trees and their associated crown metrics can be used to estimate Ht, dbh, and AGC stocks as well as forest uniformity in fast-growing Eucalyptus plantations forests using lidar data as inputs to LME models. This further underscores the high potential of our proposed approach to monitor standing stock and growth in Eucalyptus—and similar forest plantations for carbon dynamics and forest product planning.

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.

Forest structure, diversity, and primary production in relation to disturbance severity

Differential disturbance severity effects on forest vegetation structure, species diversity, and net primary production (NPP) have been long theorized and observed. Here, we examined these factors concurrently to explore the potential for a mechanistic pathway linking disturbance severity, changes in light environment, leaf functional response, and wood NPP in a temperate hardwood forest.Using a suite of measurements spanning an experimental gradient of tree mortality, we evaluated the direction and magnitude of change in vegetation structural and diversity indexes in relation to wood NPP. Informed by prior observations, we hypothesized that forest structural and species diversity changes and wood NPP would exhibit either a linear, unimodal, or threshold response in relation to disturbance severity. We expected increasing disturbance severity would progressively shift subcanopy light availability and leaf traits, thereby coupling structural and species diversity changes with primary production.Linear or unimodal changes in three of four vegetation structural indexes were observed across the gradient in disturbance severity. However, disturbance-related changes in vegetation structure were not consistently correlated with shifts in light environment, leaf traits, and wood NPP. Species diversity indexes did not change in response to rising disturbance severity.We conclude that, in our study system, the sensitivity of wood NPP to rising disturbance severity is generally tied to changing vegetation structure but not species diversity. Changes in vegetation structure are inconsistently coupled with light environment and leaf traits, resulting in mixed support for our hypothesized cascade linking disturbance severity to wood NPP.

Ectomycorrhizal fungus-associated determinants jointly reflect ecological processes in a temperature broad-leaved mixed forest

Ectomycorrhizal (ECM) fungi are closely related to vegetation compositions, edaphic properties, and site-specific processes. However, the coevolutionary mechanisms underlying the spatial distributions in floristic and ECM fungal composition in the context of biotic adaptations and abiotic variances remain unclear. We combine a total of 25 ECM fungus-associated environmental variables to impose three types of composite scores and then quantify the environmental gradients of geographical site, soil chemical property and vegetation functional trait across 122 grids of 20 m × 20 m in a 25-hm² forest plot. Significant dissimilarities in vegetational and ECM fungal abundance and composition existed along the above environmental gradients. Specifically, a contrasting floristic distribution (e.g., Betula platyphylla vs. Tilia mandshurica) existed between the northeastern and southwestern areas and was closely related to the nutrient and moisture gradients (with high levels in the west and low levels in the east). Furthermore, the ECM fungal communities were more abundant in the nutrient-poor and low-moisture environments than in the nutrient-rich and high-moisture environments, and the mixed-forest in the middle-gradient sites between the northeastern and southwestern areas harbored the highest ECM fungal diversity. These findings suggest that predictable within-site vegetation succession is closely related to ECM-associated determinants and the natural spatial heterogeneity of edaphic properties at a local scale.

Asymmetric competition, ontogenetic growth and size inequality drive the difference in productivity between two-strata and one-stratum forest stands

Size inequality has been considered a key feature of plant population structure with impacts on ecosystem functions. In forest ecosystems, studies examining the relationship between tree size inequality and stand productivity have produced mixed outcomes. These studies found positive, neutral or negative relationships and discussed how this could be influenced by competition for light between trees (e.g. light interception efficiency), but far less attention has been paid to the role played by tree ontogenetic growth. In this article, we present a simple mathematical model that predicts the basal area growth of a two-strata stand as a function of tree basal areas and asymmetric competition. Comparing the growth of this stand to the growth of a spatially homogeneous one-stratum stand and a spatially heterogeneous one-stratum stand, we show that higher growth of the two-strata stand is achieved for concave shape, increasing functions of ontogenetic growth and for low intensities of absolute size-asymmetric competition. We also demonstrate that the difference in growth between the two-strata stand and the one-stratum stands depends on tree size inequality, mean tree basal area and total basal area in the two-strata stand. We finally found that the relationships between tree size inequality and productivity can vary from positive to negative and even non-monotonous. However, we highlight that negative relationships may be more frequent. As a conclusion, our results indicate that ontogenetic growth can have a major impact on the form and the magnitude of the size inequality-productivity relationship.

Development of a Mixed-Effects Individual-Tree Basal Area Increment Model for Oaks (Quercus spp.) Considering Forest Structural Diversity

In the context of uneven-aged mixed-species forest management, an individual-tree basal area increment model considering forest structural diversity was developed for oaks (Quercus spp.) using data collected from 11,860 observations in 845 sample plots from the 7th (2004), 8th (2009), and 9th (2014) Chinese National Forest Inventory in Hunan Province, south-central China. Since the data was longitudinal and had a nested structure, we used a linear mixed-effects approach to construct the model. We also used the variance function and an autocorrelation structure to describe within-plot heteroscedasticity and autocorrelation. Finally, the optimal mixed-effects model was determined based on the Akaike information criterion (AIC), Bayesian information criterion (BIC), log-likelihood (Loglik) and the likelihood ratio test (LRT). The results indicate that the reciprocal transformation of initial diameter at breast height (1/DBH), relative density index (RD), number of trees per hectare (NT), elevation (EL) and Gini coefficient (GC) had a significant impact on the individual-tree basal area increment. In comparison to the basic model developed using least absolute shrinkage and selection operator (LASSO) regression, the mixed-effects model performance was greatly improved. In addition, we observed that the heteroscedasticity was successfully removed by the exponent function and autocorrelation was significantly corrected by AR(1). Our final model also indicated that forest structural diversity significantly affected tree growth and hence should not be neglected. We hope that our final model will contribute to the scientific management of oak-dominated forests.

A standardization method to disentangle environmental information from axial trends of xylem anatomical traits

Anatomical traits such as xylem conduit diameter and vessel connectivity are fundamental characteristics of the hydraulic architecture of vascular plants. Stem xylem conduits are narrow at the stem apex, and this confers resistance to embolisms that might otherwise be induced by large, negative water potentials at the top of tall trees. Below the apex, conduits progressively widen and this characteristic minimizes effects of path length on total hydraulic resistance. While interconnections among xylem vessels have been noted for decades, their role(s) are not fully clarified. For example, we do not know if they allow water to bypass embolized vessels, or increase the risk of spread of embolisms, or how their arrangement varies within a tree. Here we demonstrate the benefit of removing the independent effect of stem length on assessment of effects of external (e.g., climatic) factors on such xylem traits. We measured the hydraulic diameter (Dh) and vessel conductivity index (VCI) along the stem of 21 shrubs/trees of similar height (1.19 < H < 5.45 m) belonging to seven Acacia species, across a wide aridity gradient in Australia. All trees showed similar scaling exponents of Dh (b = 0.33) and VCI (b = 0.53) vs axial distance from the apex (L), thus conforming with general patterns in woody plants. After de-trending for L, neither Dh (P = 0.21) nor VCI (P = 0.109) differed across the aridity gradient. We found that across a wide gradient of aridity, climate had no effect on xylem anatomy of Acacia spp, which was instead dictated by axial distances from stem apices. We argue that the use of standardization procedures to filter out intrinsic patterns of vascular traits is an essential step in assessing climate-driven modifications of xylem architecture.

Size-growth asymmetry is not consistently related to productivity across an eastern US temperate forest network

Modeling and forecasting forests as carbon sinks require that we understand the primary factors affecting productivity. One factor thought to be positively related to stand productivity is the degree of asymmetry, or the slope of the relationship between tree size and biomass growth. Steeper slopes indicate disproportionate productivity of big trees relative to small trees. Theoretically, big trees outcompete smaller trees during favorable growth conditions because they maintain better access to light. For this reason, high productivity forests are expected to have asymmetric growth. However, empirical studies do not consistently support this expectation, and those that do are limited in spatial or temporal scope. Here, we analyze size-growth relationships from 1970 to 2011 across a diverse network of forest sites in the eastern United States (n = 16) to test whether asymmetry is consistently related to productivity. To investigate this relationship, we analyze asymmetry-productivity relationships between our 16 forests at non-overlapping annual, 2-, 5-, 10-, and 20-year sampling intervals and find that asymmetry is negatively related to productivity, but the strength depends on the specific interval considered. Within-site temporal variability in asymmetry and productivity are generally positively correlated over time, except at the 5-year remeasurement interval. Rather than confirming or failing to support a positive relationship between asymmetry and productivity, our findings suggest caution interpreting these metrics since the relationship varies across forest types and temporal scales.

How to map forest structure from aircraft, one tree at a time

Forest structure is strongly related to forest ecology, and it is a key parameter to understand ecosystem processes and services. Airborne laser scanning (ALS) is becoming an important tool in environmental mapping. It is increasingly common to collect ALS data at high enough point density to recognize individual tree crowns (ITCs) allowing analyses to move beyond classical stand-level approaches. In this study, an effective and simple method to map ITCs, and their stem diameter and aboveground biomass (AGB) is presented. ALS data were used to delineate ITCs and to extract ITCs' height and crown diameter; then, using newly developed allometries, the ITCs' diameter at breast height (DBH) and AGB were predicted. Gini coefficient of DBHs was also predicted and mapped aggregating ITCs predictions. Two datasets from spruce dominated temperate forests were considered: one was used to develop the allometric models, while the second was used to validate the methodology. The proposed approach provides accurate predictions of individual DBH and AGB (R2 = .85 and .78, respectively) and of tree size distributions. The proposed method had a higher generalization ability compared to a standard area-based method, in particular for the prediction of the Gini coefficient of DBHs. The delineation method used detected more than 50% of the trees with DBH >10 cm. The detection rate was particularly low for trees with DBH below 10 cm, but they represent a small amount of the total biomass. The Gini coefficient of the DBH distribution was predicted at plot level with R2 = .46. The approach described in this work, easy applicable in different forested areas, is an important development of the traditional area-based remote sensing tools and can be applied for more detailed analysis of forest ecology and dynamics.

Persistence of Coffea arabica and its relationship with the structure, species diversity and composition of a secondary forest in Brazil

Understanding the relationships between Coffea arabica L. and the native tree community of secondary forests regrowing after the abandonment of coffee plantations is important because, as a non-native species in the Neotropics, coffee can outcompete native species, reducing diversity and forests ecosystem services. We aimed to answer three questions: 1) Does coffee regeneration in secondary forests differ between shaded and unshaded abandoned plantations?; 2) How is coffee basal area related to structural attributes, species diversity and composition of the native community?; and 3) Do the relationships between coffee and native community differ between tree and sapling components? We sampled the tree and sapling components in a seasonal tropical dry forest that were previously used as shaded and unshaded coffee plantations. Coffee was the most important species in the sapling component of shaded systems, but was almost absent in unshaded ones. Coffee basal area was negatively related with the native density and absolute species richness of the sapling component; and was negatively related with tree density, and positively related with the percentage of pioneer individuals of the native tree component. Our results indicate that coffee persists in secondary forest communities even after more than 70 years of shaded-coffee plantations were abandoned, potentially reducing density and diversity of native species. Despite limitations, which hinder more general conclusions on coffee invasiveness in Brazilian secondary tropical forests, our results indicate that coffee is a strong competitor in the studied secondary forests and provide important insights for future research on this topic.

The importance of forest structure to biodiversity-productivity relationships

While various relationships between productivity and biodiversity are found in forests, the processes underlying these relationships remain unclear and theory struggles to coherently explain them. In this work, we analyse diversity-productivity relationships through an examination of forest structure (described by basal area and tree height heterogeneity). We use a new modelling approach, called 'forest factory', which generates various forest stands and calculates their annual productivity (above-ground wood increment). Analysing approximately 300 000 forest stands, we find that mean forest productivity does not increase with species diversity. Instead forest structure emerges as the key variable. Similar patterns can be observed by analysing 5054 forest plots of the German National Forest Inventory. Furthermore, we group the forest stands into nine forest structure classes, in which we find increasing, decreasing, invariant and even bell-shaped relationships between productivity and diversity. In addition, we introduce a new index, called optimal species distribution, which describes the ratio of realized to the maximal possible productivity (by shuffling species identities). The optimal species distribution and forest structure indices explain the obtained productivity values quite well (R² between 0.7 and 0.95), whereby the influence of these attributes varies within the nine forest structure classes.

Complementarity effects on tree growth are contingent on tree size and climatic conditions across Europe

Neglecting tree size and stand structure dynamics might bias the interpretation of the diversity-productivity relationship in forests. Here we show evidence that complementarity is contingent on tree size across large-scale climatic gradients in Europe. We compiled growth data of the 14 most dominant tree species in 32,628 permanent plots covering boreal, temperate and Mediterranean forest biomes. Niche complementarity is expected to result in significant growth increments of trees surrounded by a larger proportion of functionally dissimilar neighbours. Functional dissimilarity at the tree level was assessed using four functional types: i.e. broad-leaved deciduous, broad-leaved evergreen, needle-leaved deciduous and needle-leaved evergreen. Using Linear Mixed Models we show that, complementarity effects depend on tree size along an energy availability gradient across Europe. Specifically: (i) complementarity effects at low and intermediate positions of the gradient (coldest-temperate areas) were stronger for small than for large trees; (ii) in contrast, at the upper end of the gradient (warmer regions), complementarity is more widespread in larger than smaller trees, which in turn showed negative growth responses to increased functional dissimilarity. Our findings suggest that the outcome of species mixing on stand productivity might critically depend on individual size distribution structure along gradients of environmental variation.