Nutrient dynamics substantially influences forest productivity, yet the influence of competition on these processes in forests is not well understood. Nitrogen is an important limiting nutrient for tree growth, but how canopy nitrogen dynamics are influenced by tree diversity and competition is unclear. Nitrogen-use efficiency is one mechanism suggested to support niche complementarity, promoting increased productivity as diversity increases, and is influenced by the resorption of foliar nutrients during senescence. We tested how diversity and competition affect canopy nitrogen dynamics by examining nitrogen resorption efficiency (NRE) in over 200 trees from three tree species in a 12-year-old mixed-species hardwood planting that included a full-factorial design of three levels of species diversity, representing intra- and interspecific competition, and two levels of planting density, representing competition intensity. Midseason and senescent foliar samples were collected from black cherry (Prunus serotina), American chestnut (Castanea dentata), and northern red oak (Quercus rubra) and we determined midseason canopy and foliar litter nitrogen concentrations and calculated NRE. Higher midseason canopy nitrogen concentrations were observed in more diverse, low-density plantings, but the response magnitude varied among species. NRE increased as diversity increased; the response, however, varied among species, ranging from a statistically significant increase to no response, but was not influenced by planting density. These findings provide evidence that while the influence of diversity on tree physiological responses depends on the type of competitive interaction (i.e., diversity or intensity), different combinations of species will likely affect processes related with niche complementarity and, ultimately, a positive biodiversity-productivity relationship.

Hyperspectral reflectance can potentially be used to non-destructively estimate a diverse suite of plant physiochemical functional traits by applying chemometric approaches to leverage absorption features related to chemical compounds and physiological processes associated with these traits. This approach has considerable implications in advancing plant physiological and chemical ecology. For complex functional traits, however, there is a lack of well-defined absorption features and features may be unevenly distributed across the reflectance spectrum, suggesting that the influence of wavelength ranges on the performance of chemometric models is potentially important for accurately estimating foliar functional traits. Here, we investigate the influence of spectral ranges on the performance of models estimating six tree functional traits: CO2 assimilation rate, specific leaf area, leaf water content and concentrations of foliar nitrogen, sugars and gallic acid. Using data collected from multiple different experiments, we quantified plant functional trait responses using standard reference measurements and paired them with proximal leaf-level hyperspectral reflectance measurements spanning the wavelength range of 400-2400 nm. A total of 100 different wavelength range combinations were evaluated using partial least squares regression to determine the influence of wavelength range on model performance. We found that the influence of starting or ending wavelength on model performance was trait specific and better model outcomes were achieved when the starting and ending wavelengths encompassed absorption features associated with the specific leaf trait modelled. Interestingly, we found that including shortwave-infrared wavelength ranges (1300-2500 nm) improved performance for all trait models. Collectively, our findings underscore the importance of optimal spectral range selection in enhancing the accuracy of chemometric models for specific foliar trait estimates. An emergent outcome of this work is that the approach can be used to (1) identify the important spectral features of traits that currently lack known absorption features or have multiple or weak absorption features, (2) expand the current suite of plant functional traits that can be estimated using spectroscopy and (3) ultimately advance the integration of a spectral biology approach in ecological research.

Species' traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community reassembly.

AimTo determine the relationships between the functional trait composition of forest communities and environmental gradients across scales and biomes and the role of species relative abundances in these relationships.LocationGlobal.Time periodRecent.Major taxa studiedTrees.MethodsWe integrated species abundance records from worldwide forest inventories and associated functional traits (wood density, specific leaf area and seed mass) to obtain a data set of 99,953 to 149,285 plots (depending on the trait) spanning all forested continents. We computed community-weighted and unweighted means of trait values for each plot and related them to three broad environmental gradients and their interactions (energy availability, precipitation and soil properties) at two scales (global and biomes).ResultsOur models explained up to 60% of the variance in trait distribution. At global scale, the energy gradient had the strongest influence on traits. However, within-biome models revealed different relationships among biomes. Notably, the functional composition of tropical forests was more influenced by precipitation and soil properties than energy availability, whereas temperate forests showed the opposite pattern. Depending on the trait studied, response to gradients was more variable and proportionally weaker in boreal forests. Community unweighted means were better predicted than weighted means for almost all models.Main conclusionsWorldwide, trees require a large amount of energy (following latitude) to produce dense wood and seeds, while leaves with large surface to weight ratios are concentrated in temperate forests. However, patterns of functional composition within-biome differ from global patterns due to biome specificities such as the presence of conifers or unique combinations of climatic and soil properties. We recommend assessing the sensitivity of tree functional traits to environmental changes in their geographic context. Furthermore, at a given site, the distribution of tree functional traits appears to be driven more by species presence than species abundance.

AimEcological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species?LocationGlobal.Time period1990-2017.Major taxa studiedTrees.MethodsWe used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated.ResultsCommunity dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large-scale land degradation.Main conclusionsBy linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large-scale management and conservation practices.

To achieve carbon neutrality in the face of climate change, accurately estimating forest carbon uptake is crucial. Environmental changes, such as temperature increases or precipitation fluctuations caused by climate change, can alter the growth responses of each species and act as a driver for changes in forest productivity. In particular, using a single-species growth model increases uncertainty in predicting stand growth, given the high species diversity in temperate forests in East Asia. Therefore, in this study, we identified the growth curve of 17 speciesspecific distributed in Korean temperate forest as well as the growth trend over the last 30 years (1976 -2005). For this purpose, the species distribution and growth characteristics of 17 major Korean species of trees were analyzed using 13,808 tree-ring series from the 5th National Forest Inventory, which was conducted between 2006 and 2010. The growth characteristics of each species were analyzed using the average growth curve specific to each species, and the yearly growth trend was examined through residual analysis of the average growth curve. The distribution range of the 17 major tree species varied by species, as did the growth rate, ranging from 7 cm 2 center dot year- 1 to 17 cm 2 center dot year- 1 for the 30-year-old average basal area increment (BAI). Over time, fast-growing tree species exhibited initially high BAI, followed by a sharp decline from the 2000s. In contrast, broadleaf trees showed a continuous increase. Furthermore, a comparison of the total volume of individual trees and the volume of the yield table revealed that accurately estimating the actual forest volume was challenging. This study contributes to improving the accuracy of productivity predictions for temperate forests, underscoring the necessity to investigate the interaction between climate and forest succession in the future.

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.

The density of wood is a key indicator of trees’ carbon investment strategies, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here, we analyze information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially-explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical dry forests being up to twice as dense as that in boreal forests. In both angiosperms and gymnosperms, temperature and water availability emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.

1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale.2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness-productivity relationship.3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive.4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity-ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions.

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17–34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling.

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system 1 . Remote-sensing estimates to quantify carbon losses from global forests 2 – 5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced 6 and satellite-derived approaches 2 , 7 , 8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea 2 , 3 , 9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

Significance Tree diversity is fundamental for forest ecosystem stability and services. However, because of limited available data, estimates of tree diversity at large geographic domains still rely heavily on published lists of species descriptions that are geographically uneven in coverage. These limitations have precluded efforts to generate a global perspective. Here, based on a ground-sourced global database, we estimate the number of tree species at biome, continental, and global scales. We estimated a global tree richness (≈73,300) that is ≈14% higher than numbers known today, with most undiscovered species being rare, continentally endemic, and tropical or subtropical. These results highlight the vulnerability of global tree species diversity to anthropogenic changes.

Correction for "The number of tree species on Earth," by Roberto Cazzolla Gatti, Pramod Kumar Khare, Timothy J. Kileen, Hyun Seok Kim, Henn Korjus, Amit Lewis, Natalia Lukina, Brian S. Maitner, Yadvinder Malhi, Andrew R. Marshall, Olga V. Martynenko, Abel L. Monteagudo Mendoza, Petr V. Ontikov, Edgar OrtizMalavasi, Nadir C. Pallqui Camacho, Alain Paquette, Minjee Park, Narayanaswamy Phillips, Nicolas Picard, Daniel Piotto, Lourens Poorter, John R. Poulsen, Hans

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers. Examining drivers of the latitudinal biodiversity gradient in a global database of local tree species richness, the authors show that co-limitation by multiple environmental and anthropogenic factors causes steeper increases in richness with latitude in tropical versus temperate and boreal zones.

Tubakia species are fungi causing leaf spots and blights and are reported worldwide, mainly in Asia, Europe and North America. These diseases often occur on Quercus (oak) trees, which constitute one of the dominant broad-leaved tree genera in the world, so forest structure, function and dynamics could be affected by Tubakia infection. However, few data about the negative impacts of Tubakia on key leaf functional traits are available. This study was conducted to investigate the changes in photosynthetic capacity, morphological, and chemical traits of sawtooth oak (Quercus acutissima Carruth.) leaves infected with Tubakia koreana causing Quercus leaf blight. Two control and four treatment seedlings were used for this study. It was found that maximum photosynthetic rate and maximum rates of carboxylation and electron transport showed exponential reductions with increasing disease severity (p < .001). However, leaf mass per area (LMA) showed no noticeable changes, while leaf nitrogen concentration (N-mass) increased linearly with increasing disease severity (p < .001), suggesting that Tubakia disease may underlay the inconsistent patterns of LMA and N-mass. These findings contribute to the understanding of fundamental effects of disease development on physiological traits of oak leaves.

Down-regulation of leaf N and Rubisco under elevated CO2 (eCO(2)) are accompanied by increased non-structural carbohydrates (NSC) due to the sink-source imbalance. Here, to investigate whether the canopy position affects the down-regulation of Rubisco, we measured leaf N, NSC and N allocation in two species with different heights at maturity [Fraxinus rhynchophylla (6.8 +/- 0.3 m) and Sorbus alnifolia (3.6 +/- 0.2 m)] from 2017 to 2019. Since 2009, both species were grown at three different CO2 concentrations in open-top chambers: ambient CO2 (400 ppm; aCO(2)); ambient CO2 x 1.4 (560 ppm; eCO(2)1.4); and ambient CO2 x 1.8 (720 ppm; eCO(2)1.8). Leaf N per unit mass (Nmass) decreased under eCO(2), except under eCO(2)1.8 in S. alnifolia and coincided with increased NSC. NSC increased under eCO(2) in F. rhynchophylla, but the increment of NSC was greater in the upper canopy of S. alnifolia. Conversely, Rubisco content per unit area was reduced under eCO(2) in S. alnifolia and there was no interaction between CO2 and canopy position. In contrast, the reduction of Rubisco content per unit area was greater in the upper canopy of F. rhynchophylla, with a significant interaction between CO2 and canopy position. Rubisco was negatively correlated with NSC only in the upper canopy of F. rhynchophylla, and at the same NSC, Rubisco was lower under eCO(2) than under aCO(2). Contrary to Rubisco, chlorophyll increased under eCO(2) in both species, although there was no interaction between CO2 and canopy position. Finally, photosynthetic N content (Rubisco + chlorophyll + PSII) was reduced and consistent with down-regulation of Rubisco. Therefore, the observed Nmass reduction under eCO(2) was associated with dilution due to NSC accumulation. Moreover, down regulation of Rubisco under eCO(2) was more sensitive to NSC accumulation in the upper canopy. Our findings emphasize the need for the modification of the canopy level model in the context of climate change.

Down-regulation of photosynthesis under elevated CO2 (eCO2) concentrations could be attributed to the depletion of nitrogen (N) availability after long-term exposure to eCO2 (progressive nitrogen limitation, PNL) or leaf N dilutions due to excessive accumulation of nonstructural carbohydrates. To determine the mechanism underlying this down-regulation, we investigated N availability, photosynthetic characteristics, and N allocation in leaves of Pinus densiflora (shade-intolerant species, evergreen tree), Fraxinus rhynchophylla (intermediate shade-tolerant species, deciduous tree), and Sorbus alnifolia (shade-tolerant species, deciduous tree). The three species were grown under three different CO2 concentrations in open-top chambers, i.e., ambient 400 ppm (aCO2); ambient × 1.4, 560 ppm (eCO21.4); and ambient × 1.8, 720 ppm (eCO21.8), for 11 years. Unlike previous studies that addressed PNL, after 11 years of eCO2 exposure, N availability remained higher under eCO21.8, and chlorophyll and photosynthetic N use efficiency increased under eCO2. In the case of nonstructural carbohydrates, starch and soluble sugar showed significant increases under eCO2. The maximum carboxylation rate, leaf N per mass (Nmass), and ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) were low under eCO21.8. The ratio of RuBP regeneration to the carboxylation rate as well as that of chlorophyll N to Rubisco N increased with CO2 concentrations. Based on the reduction in Nmass (not in Narea) that was diluted by increase in nonstructural carbohydrate, down-regulation of photosynthesis was found to be caused by the dilution rather than PNL. The greatest increases in chlorophyll under eCO2 were observed in S. alnifolia, which was the most shade-tolerant species. This study could help provide more detailed, mechanistically based processes to explain the down-regulation of photosynthesis by considering two hypotheses together and showed N allocation seems to be flexible against changes in CO2 concentration.