Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model

Toward a coordinated understanding of hydro-biogeochemical root functions in tropical forests for application in vegetation models

Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest-climate feedbacks for these carbon-rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics that represent important functional processes in tropical forests. We focus on: (1) fine-root strategies for soil resource exploration, (2) coupling and trade-offs in fine-root water vs nutrient acquisition, and (3) aboveground-belowground linkages in plant resource acquisition and use. We suggest avenues for representing these extremely diverse plant communities in computationally manageable and ecologically meaningful groups in models for linked aboveground-belowground hydro-nutrient functions. Tropical forests are undergoing warming, shifting rainfall regimes, and exacerbation of soil nutrient scarcity caused by elevated atmospheric CO2. The accurate model representation of tropical forest functions is crucial for understanding the interactions of this biome with the climate.

Underlying plant trait strategies for understanding the carbon sequestration in Banj oak Forest of Himalaya

Plant functional attributes are subjected to environmental adjustments, which lead to modulations in forest processes under environmental changes. However, a comprehensive assessment of the relationships between plant traits and carbon stock remains subtle. The present study attempted to accomplish the gap of knowledge by examining the linkages between forest carbon with plant traits within the Banj Oak forest in the Garhwal Himalaya. Twelve individuals from three major species in the Banj Oak forest were randomly selected for trait measurements, and soil samples were collected randomly across the area for evaluation of soil nutrients and carbon. Forest biomass and soil carbon were estimated following standard protocols. A Structural Equation Model (SEM) was applied to establish the relationship between above ground carbon (AGC) and soil organic carbon (SOC) with leaf and stem traits, and soil nutrients. Stem traits were tree height and tree diameter; whereas leaf morphological traits were leaf area, specific leaf area, leaf dry matter content; leaf physiological traits were photosynthesis rate, stomatal conductance, and transpiration rate; and leaf biochemical traits were leaf carbon concentration, leaf nitrogen concentration, and leaf phosphorus concentration. Soil nutrients were available nitrogen, available phosphorus, and exchangeable potassium. Based on SEM results, AGC of the forest was positively correlated with stem traits and leaf physiological traits, while negatively correlated with leaf morphological traits. SOC was positively correlated with soil nutrients and leaf biochemical traits, whereas negatively correlated with stem traits. These findings may support for precise quantification of forest carbon and modeling of forest carbon stocks besides providing inputs to forest managers for devising effective forest management strategies.

'How to adapt forests?'-Exploring the role of leaf trait diversity for long-term forest biomass under new climate normals

Forests, critical components of global ecosystems, face unprecedented challenges due to climate change. This study investigates the influence of functional diversity-as a component of biodiversity-to enhance long-term biomass of European forests in the context of changing climatic conditions. Using the next-generation flexible trait-based vegetation model, LPJmL-FIT, we explored the impact of functional diversity on long-term forest biomass under three different climate change scenarios (video abstract: https://www.pik-potsdam.de/~billing/video/2023/video_abstract_billing_et_al_LPJmLFIT.mp4). Four model set-ups were tested with varying degrees of functional diversity and best-suited functional traits. Our results show that functional diversity positively influences long-term forest biomass, particularly when climate warming is low (RCP2.6). Under these conditions, high-diversity simulations led to an approximately 18.2% increase in biomass compared to low-diversity experiments. However, as climate change intensity increased, the benefits of functional diversity diminished (RCP8.5). A Bayesian multilevel analysis revealed that both full leaf trait diversity and diversity of plant functional types contributed significantly to biomass enhancement under low warming scenarios in our model simulations. Under strong climate change, the presence of a mixture of different functional groups (e.g. summergreen and evergreen broad-leaved trees) was found more beneficial than the diversity of leaf traits within a functional group (e.g. broad-leaved summergreen trees). Ultimately, this research challenges the notion that planting only the most productive and climate-suited trees guarantees the highest future biomass and carbon sequestration. We underscore the importance of high functional diversity and the potential benefits of fostering a mixture of tree functional types to enhance long-term forest biomass in the face of climate change.

Different responses of leaf and root economics spectrum to grazing time at the community level in desert steppe, China

The plant economic spectrum can explain the trade-off strategies of vascular plants between resource acquisition and storage. Grazing can alter the plant functional characteristics of grassland ecosystems, resulting in a shift in plant resource acquisition strategies. Taking fenced grassland as a control, in this study we quantified six leaf traits and four root traits of 14 plant species (those that comprised >85 % of the species community abundance) of different grazing time grasslands in desert grasslands in Ningxia. We examined how grazing time shapes the functional structure of plant communities and the resource acquisition strategy. The results revealed an inverse pattern of the fast-slow economic spectrum of leaf and root traits; that is, as grazing time increased, the leaf traits shifted from an acquisitive type to a conservative type of resource acquisition strategy. In contrast, the root traits showed a shift from a conservative type to an acquisitive type of resource acquisition strategy. Grazing time leads to a whole plant economic spectrum, and plant functional traits may facilitate their response to environmental change, the study of which can hereby deepen our understanding of the plant economics spectrum. Our study provides new evidence that leaf and root resource acquisition and utilization are relatively independent under grazing pressure.

Resource-acquisitive species have greater plasticity in leaf functional traits than resource-conservative species in response to nitrogen addition in subtropical China

The evergreen broad-leaf forest is subtropical zonal vegetation in China, and its species diversity and stability are crucial for maintaining forest ecosystem functions. The region is generally affected by global changes such as high levels of nitrogen deposition. Therefore, it is critical to determine the adaptation strategies of subtropical dominant species under nitrogen addition. Here, we conducted two-year field experiments with nitrogen addition levels as 0 kg N ha-1 yr-1 (CK), 50 kg N ha-1 yr-1 (LN) and 100 kg N ha-1 yr-1 (HN). We investigated the effects of nitrogen addition on leaf functional traits (including nutrition, structural and physiological characteristics) of five dominant species in subtropical evergreen broad-leaf forest. Results suggested that the effect of nitrogen addition on leaf functional traits was species-specific. Contrary to Rhododendron delavayi and Eurya muricata, Quercus glauca, Schima superba and Castanopsis eyrei all responded more to the HN treatment than LN treatment. Compared to other leaf functional traits, leaf anatomical structure traits had the highest average plasticity (0.246), and the relative effect of leaf photosynthetic property was highest (7.785) under N addition. Among the five species, S. superba was highest in terms of the index of plasticity for leaf functional traits under nitrogen addition, followed by Q. glauca, E. muricata, C. eyrei and R. delavayi. The major leaf functional traits representing the economic spectrum of leaves (LES) showed resource acquisitive strategy (high SLA, LNC, LPC, Pn) and conservative strategy (high LTD, LDMC, C/N) clustering on the opposite ends of the PCA axis. The PCA analysis indicated that species with high leaf plasticity adopt resource acquisitive strategy (S. superba and Q. glauca), whereas species with low leaf plasticity adopt resource conservative strategy (E. muricata, C. eyrei and R. delavayi). In aggregate, resource-acquisitive species benefit from nitrogen addition more than resource-conservative species, suggesting that S. superba and Q. glauca will occupy the dominant position in community succession under persistently elevated nitrogen deposition.

The carbon balance of plants: economics, optimization, and trait spectra in a historical perspective

Over fifty years have passed since the publication of Harold Mooney's formative paper, "The Carbon Balance of Plants" on pages 315-346 of Volume 3 (1972) of Annual Review of Ecology and Systematics. Arguably, the conceptual framework presented in that paper, and the work by Mooney and his students leading up to the paper, provided the foundational principles from which core disciplines emerged in plant economic theory, functional trait theory and, more generally, plant physiological ecology. Here, we revisit the primary impacts of those early discoveries to understand how researchers constructed major concepts in our understanding of plant adaptations, and where those concepts are likely to take us in the near future. The discipline of functional trait ecology, which is rooted in the principles of evolutionary and economic optimization, has captured the imagination of the plant physiological ecology research community, though its emphasis has shifted toward predicting species distributions and ecological roles across resource gradients. In the face of 'big-data' research pursuits that are revealing trait expression patterns at the cellular level and mass and energy exchange patterns at the planetary scale, an opportunity exists to reconnect the principles of plant carbon balance and evolutionary optimization with trait origins at the genetic and cellular scales and trait impacts at the global scale.

Predicting the Responses of Functional Leaf Traits to Global Warming: An In Situ Temperature Manipulation Design Using Iris pumila L

Phenotypic plasticity is widely acknowledged as one of the most common solutions for coping with novel environmental conditions following climate change. However, it is less known whether the current amounts of trait plasticity, which is sufficient for matching with the contemporary climate, will be adequate when global temperatures exceed historical levels. We addressed this issue by exploring the responses of functional and structural leaf traits in Iris pumila clonal individuals to experimentally increased temperatures (~1.5 °C) using an open top chamber (OTC) design. We determined the phenotypic values of the specific leaf area, leaf dry matter content, specific leaf water content, and leaf thickness in the leaves sampled from the same clone inside and outside of the OTC deployed on it, over seasons and years within two natural populations. We analyzed the data using a repeated multivariate analysis of variance, which primarily focusses on the profiles (reaction norms (RNs)) of a variable gathered from the same individual at several different time points. We found that the mean RNs of all analyzed traits were parallel regardless of experienced temperatures, but differed in the level and the shape. The populations RNs were similar as well. As the amount of plasticity in the analyzed leaf trait was adequate for coping with elevated temperatures inside the OTCs, we predict that it will be also sufficient for responding to increased temperatures if they exceed the 1.5 °C target.

Drought stress-induced the formation of heteromorphic leaves of Populus euphratica Oliv: evidence from gene transcriptome

Populus euphratica Oliv., a dominant species of arid desert community, grows heteromorphic leaves at different crown positions. Whether heteromorphic leaves are a strategy of plant adaptation to drought stress is rarely reported. This study sequenced the transcriptome of three typical heteromorphic leaves (lanceolate, ovate and broad-ovate leaves) of P. euphratica, and measured their drought stress. We wanted to reveal the molecular mechanisms underlying the formation of heteromorphic leaves. Drought stress was increased significantly from lanceolate to ovate to broad-ovate leaves. Gene ontology (GO) and KEGG enrichment analysis showed that the MADs-box gene regulated the expression of peroxidase (POD) in the phenylpropane biosynthetic pathway. The up-regulated expression of the chalcone synthase (CHS) gene in broad-ovate leaves significantly activated the flavonoid biosynthetic pathway. In the process of leaf shape change, the different expressions of homeodomain leucine zipper (HD-ZIP) among the three heteromorphic leaves had potential interactions on the AUX and ABA pathways. The expression of Sucrose phosphate synthase (SPS) and sucrose synthase (SUS) increased from lanceolate to broad-ovate leaves, resulting in a consistent change in starch and sucrose content. We concluded that these resistance-related pathways are expressed in parallel with leaf formation genes, thereby inducing the formation of heteromorphic leaves. Our work provided a new insights for desert plants to adapt to drought stress.

Evolutionary adaptation of trees and modelled future larch forest extent in Siberia

With changing climate, the boreal forest could potentially migrate north and become threatened by droughts in the south. However, whether larches, the dominant tree species in eastern Siberia, can adapt to novel situations is largely unknown but is crucial for predicting future population dynamics. Exploring variable traits and trait adaptation through inheritance in an individual-based model can improve our understanding and help future projections. We updated the individual-based spatially explicit vegetation model LAVESI (Larix Vegetation Simulator), used for forest predictions in Eastern Siberia, with trait value variation and incorporated inheritance of parental values to their offspring. Forcing the model with both past and future climate projections, we simulated two areas - the expanding northern treeline and a southerly area experiencing drought. While the specific trait of 'seed weight' regulates migration, the abstract 'drought resistance' protects stands. We show that trait variation with inheritance leads to an increase in migration rate (∼ 3% area increase until 2100). The drought resistance simulations show that, under increasing stress, including adaptive traits leads to larger surviving populations (17% of threatened under RCP 4.5 (Representative Concentration Pathway)). We show that with the increase expected under the RCP 8.5 scenario vast areas (80% of the extrapolated area) of larch forest are threatened and could disappear due to drought as adaptation plays only a minor role under strong warming. We conclude that variable traits facilitate the availability of variants under environmental changes. Inheritance allows populations to adapt to environments and promote successful traits, which leads to populations that can spread faster and be more resilient, provided the changes are not too drastic in both time and magnitude. We show that trait variation and inheritance contribute to more accurate models that can improve our understanding of responses of boreal forests to global change.

Why can't we predict traits from the environment?

Plant functional traits are powerful ecological tools, but the relationships between plant traits and climate (or environmental variables more broadly) are often remarkably weak. This presents a paradox: Plant traits govern plant interactions with their environment, but the environment does not strongly predict the traits of plants living there. Unpacking this paradox requires differentiating the mechanisms of trait variation and potential confounds of trait-environment relationships at different evolutionary and ecological scales ranging from within species to among communities. It also necessitates a more integrated understanding of physiological and evolutionary equifinality among many traits and plant strategies, and challenges us to understand how supposedly 'functional' traits integrate into a whole-organism phenotype in ways that may be largely orthogonal to environmental tolerances.

Seed Size, Seed Dispersal Traits, and Plant Dispersion Patterns for Native and Introduced Grassland Plants

Most terrestrial plants disperse by seeds, yet the relationship between seed mass, seed dispersal traits, and plant dispersion is poorly understood. We quantified seed traits for 48 species of native and introduced plants from the grasslands of western Montana, USA, to investigate the relationships between seed traits and plant dispersion patterns. Additionally, because the linkage between dispersal traits and dispersion patterns might be stronger for actively dispersing species, we compared these patterns between native and introduced plants. Finally, we evaluated the efficacy of trait databases versus locally collected data for examining these questions. We found that seed mass correlated positively with the presence of dispersal adaptations such as pappi and awns, but only for introduced plants, for which larger-seeded species were four times as likely to exhibit dispersal adaptations as smaller-seeded species. This finding suggests that introduced plants with larger seeds may require dispersal adaptations to overcome seed mass limitations and invasion barriers. Notably, larger-seeded exotics also tended to be more widely distributed than their smaller-seeded counterparts, again a pattern that was not apparent for native taxa. These results suggest that the effects of seed traits on plant distribution patterns for expanding populations may be obscured for long-established species by other ecological filters (e.g., competition). Finally, seed masses from databases differed from locally collected data for 77% of the study species. Yet, database seed masses correlated with local estimates and generated similar results. Nonetheless, average seed masses differed up to 500-fold between data sources, suggesting that local data provides more valid results for community-level questions.

Leaf traits divergence and correlations of woody plants among the three plant functional types on the eastern Qinghai-Tibetan Plateau, China

Leaf traits are important indicators of plant life history and may vary according to plant functional type (PFT) and environmental conditions. In this study, we sampled woody plants from three PFTs (e.g., needle-leaved evergreens, NE; broad-leaved evergreens, BE; broad-leaved deciduous, BD) on the eastern Qinghai-Tibetan Plateau, and 110 species were collected across 50 sites. Here, the divergence and correlations of leaf traits in three PFTs and relationships between leaf traits and environment were studied. The results showed significant differences in leaf traits among three PFTs, with NE plants showed higher values than BE plants and BD plants for leaf thickness (LT), leaf dry matter content (LDMC), leaf dry mass per area (LMA), carbon: nitrogen ratio (C/N), and nitrogen content per unit area (N_area), except for nitrogen content per unit mass (N_mass). Although the correlations between leaf traits were similar across three PFTs, NE plants differed from BE plants and BD plants in the relationship between C/N and N_area. Compared with the mean annual precipitation (MAP), the mean annual temperature (MAT) was the main environmental factor that caused the difference in leaf traits among three PFTs. NE plants had a more conservative approach to survival compared to BE plants and BD plants. This study shed light on the regional-scale variation in leaf traits and the relationships among leaf traits, PFT, and environment. These findings have important implications for the development of regional-scale dynamic vegetation models and for understanding how plants respond and adapt to environmental change.

Citizen science plant observations encode global trait patterns

Global maps of plant functional traits are essential for studying the dynamics of the terrestrial biosphere, yet the spatial distribution of trait measurements remains sparse. With the increasing popularity of species identification apps, citizen scientists contribute to growing vegetation data collections. The question emerges whether such opportunistic citizen science data can help map plant functional traits globally. Here we show that we can map global trait patterns by complementing vascular plant observations from the global citizen science project iNaturalist with measurements from the plant trait database TRY. We evaluate these maps using sPlotOpen, a global collection of vegetation plot data. Our results show high correlations between the iNaturalist- and sPlotOpen-based maps of up to 0.69 (r) and higher correlations than to previously published trait maps. As citizen science data collections continue to grow, we can expect them to play a significant role in further improving maps of plant functional traits.

Future tree survival in European forests depends on understorey tree diversity

Climate change heavily threatens forest ecosystems worldwide and there is urgent need to understand what controls tree survival and forests stability. There is evidence that biodiversity can enhance ecosystem stability (Loreau and de Mazancourt in Ecol Lett 16:106-115, 2013; McCann in Nature 405:228-233, 2000), however it remains largely unclear whether this also holds for climate change and what aspects of biodiversity might be most important. Here we apply machine learning to outputs of a flexible-trait Dynamic Global Vegetation Model to unravel the effects of enhanced functional tree trait diversity and its sub-components on climate-change resistance of temperate forests ( http://www.pik-potsdam.de/~billing/video/Forest_Resistance_LPJmLFIT.mp4 ). We find that functional tree trait diversity enhances forest resistance. We explain this with 1. stronger complementarity effects (~ 25% importance) especially improving the survival of trees in the understorey of up to + 16.8% (± 1.6%) and 2. environmental and competitive filtering of trees better adapted to future climate (40-87% importance). We conclude that forests containing functionally diverse trees better resist and adapt to future conditions. In this context, we especially highlight the role of functionally diverse understorey trees as they provide the fundament for better survival of young trees and filtering of resistant tree individuals in the future.

Intraspecific Leaf Trait Variation across and within Five Common Wine Grape Varieties

Variability in traits forming the Leaf Economics Spectrum (LES) among and within crop species plays a key role in governing agroecosystem processes. However, studies evaluating the extent, causes, and consequences of within-species variation in LES traits for some of the world's most common crops remain limited. This study quantified variations in nine leaf traits measured across 90 vines of five common wine grape (Vitis vinifera L.) varieties at two growth stages (post-flowering and veraison). Grape traits in these varieties covary along an intraspecific LES, in patterns similar to those documented in wild plants. Across the five varieties evaluated here, high rates of photosynthesis (A) and leaf nitrogen (N) concentrations were coupled with low leaf mass per area (LMA), whereas the opposite suite of traits defined the "resource-conserving end" of this intraspecific LES in grape. Variety identity was the strongest predictor of leaf physiological (A) and morphological traits (i.e., leaf area and leaf mass), whereas leaf chemical traits and LMA were best explained by growth stage. All five varieties expressed greater resource-conserving trait syndromes (i.e., higher LMA, lower N, and lower A_mass) later in the growing season. Traits related to leaf hydraulics, including instantaneous water-use efficiency (WUE), were unrelated to LES and other resource capture traits, and were better explained by spatial location. These results highlight the relative contributions of genetic, developmental, and phenotypic factors in structuring trait variation in the five wine grape varieties evaluated here, and point to a key role of domestication in governing trait relationships in the world's crops.

Global relationships in tree functional traits

Due to massive energetic investments in woody support structures, trees are subject to unique physiological, mechanical, and ecological pressures not experienced by herbaceous plants. Despite a wealth of studies exploring trait relationships across the entire plant kingdom, the dominant traits underpinning these unique aspects of tree form and function remain unclear. Here, by considering 18 functional traits, encompassing leaf, seed, bark, wood, crown, and root characteristics, we quantify the multidimensional relationships in tree trait expression. We find that nearly half of trait variation is captured by two axes: one reflecting leaf economics, the other reflecting tree size and competition for light. Yet these orthogonal axes reveal strong environmental convergence, exhibiting correlated responses to temperature, moisture, and elevation. By subsequently exploring multidimensional trait relationships, we show that the full dimensionality of trait space is captured by eight distinct clusters, each reflecting a unique aspect of tree form and function. Collectively, this work identifies a core set of traits needed to quantify global patterns in functional biodiversity, and it contributes to our fundamental understanding of the functioning of forests worldwide.

Understanding patterns in woody plant trait relationships and trade-offs is challenging. Here, by applying machine learning and data imputation methods to a global database of georeferenced trait measurements, the authors unravel key relationships in tree functional traits at the global scale.

Global Sensitivity Analysis of the LPJ Model for Larix olgensis Henry Forests NPP in Jilin Province, China

Parameter sensitivity analysis can determine the influence of the input parameters on the model output. Identification and calibration of critical parameters are the crucial points of the process model optimization. Based on the Extended Fourier Amplitude Sensitivity Test (EFAST) and the Morris method, this paper analyzes and compares the parameter sensitivity of the annual mean net primary productivity (NPP) of Larix olgensis Henry forests in Jilin Province simulated by the Lund–Potsdam–Jena dynamic global vegetation model (LPJ model) in 2009–2014 and 2000–2019, and deeply examines the sensitivity and influence of the two methods to each parameter and their respective influence on the model’s output. Moreover, it optimizes some selected parameters and re-simulates the NPP of Larix olgensis forests in Jilin Province from 2010 to 2019. The conclusions are the following: (1) For the LPJ model, the sensitive and non-influential parameters could be identified, which could guide the optimization order of the model and was valuable for model area applications. (2) The results of the two methods were similar but not identical. The sensitivity parameters were significantly correlated (p < 0.05); parameter krp was the most sensitive parameter, followed by parameters αm, αa, and gm. These sensitive parameters were mainly found in the photosynthesis, water balance, and allometric growth modules. (3) The EFAST method had a higher precision than the Morris method, which could calculate quantitatively the contribution rate of each parameter to the variances of the model results; however, the Morris method involved fewer model running times and higher efficiency. (4) The mean relative error (MRE) and mean absolute error (MAE) of the simulated value of LPJ model after parameter optimization decreases. The optimized annual mean value of NPP from 2010 to 2019 was 580 g C m−2 a−1, with a mean annual growth rate of 2.13%, exhibiting a fluctuating growth trend. The MAE of the simulated value of LPJ model after parameter optimization decreases.

Genotypic variation of plant biomass under nitrogen deficiency is positively correlated with conservative economic traits in wheat

Plant functional traits, including leaf and root economic traits, are important for understanding the composition and function of ecosystems. However, plant functional traits of crop species and the relationships between them, and their responses to environmental variations are not fully understood. In the present study, the traits in the leaf and root economics spectrum (LES and RES) and plant biomass were investigated in 14 wheat genotypes grown with sufficient or limited nitrogen (N) supply. We found that N had significant impacts on the LES and RES traits and on the relationships among them. Our results generally supported the hypothesized LES, but did not support the RES or plant economics spectrum concept among wheat plants regardless of N treatment. More importantly, we found that more conservative leaf and root economic traits are beneficial for shoot biomass accumulation in wheat plants grown with limited N supply, and for the improvement in the tolerance of wheat to N stress. The data presented suggest that growth conditions should be accounted for when studying trait-to-trait relationships, and that more conservative resource use strategies could be used as promising targets for wheat breeding programs with limited N input.

Representing plant diversity in land models: An evolutionary approach to make "Functional Types" more functional

Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet, Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere-atmosphere system, simplify the incredible diversity of land plants into a handful of coarse categories of "Plant Functional Types" (PFTs) that often fail to capture ecological dynamics such as biome distributions. The inclusion of more realistic functional diversity is a recognized goal for ESMs, yet there is currently no consistent, widely accepted way to add diversity to models, that is, to determine what new PFTs to add and with what data to constrain their parameters. We review approaches to representing plant diversity in ESMs and draw on recent ecological and evolutionary findings to present an evolution-based functional type approach for further disaggregating functional diversity. Specifically, the prevalence of niche conservatism, or the tendency of closely related taxa to retain similar ecological and functional attributes through evolutionary time, reveals that evolutionary relatedness is a powerful framework for summarizing functional similarities and differences among plant types. We advocate that Plant Functional Types based on dominant evolutionary lineages ("Lineage Functional Types") will provide an ecologically defensible, tractable, and scalable framework for representing plant diversity in next-generation ESMs, with the potential to improve parameterization, process representation, and model benchmarking. We highlight how the importance of evolutionary history for plant function can unify the work of disparate fields to improve predictive modeling of the Earth system.

Fire disturbance effects on plant taxonomic and functional β-diversity mediated by topographic exposure

Although the diversity-disturbance relationship has been extensively studied, the differences in responses of taxonomic vs. functional diversity to natural disturbances (i.e., fire) call for an improved understanding of this relationship. Here, we investigated how fire disturbance influenced plant taxonomic and functional diversity in Golestan National Park, in northeastern Iran. We evaluated the response of α- and β-plant diversity considering both taxonomic and functional diversity and different β-diversity components (i.e., turnover and nestedness) as a function of fire regime, topographic exposure, and their interactive effect. We considered different indices of functional diversity including functional richness, functional evenness, functional divergence, functional dispersion, Rao's quadratic entropy, and community-weighted mean (CWM). Functional diversity indices were computed using four leaf traits related to species growth strategy and fire response including leaf thickness and leaf length, specific leaf area (SLA) and leaf dry matter content (LDMC). Taxonomic and functional diversity had contrasting response to fire disturbance. Fire significantly decreased taxonomic α-diversity similarly in both north and south exposures. β-diversity increased in south exposures but decreased in north exposures. Fire decreased functional richness, increased CWM of SLA, and decreased CWM of LDMC. In contrast, abundance-weighted metrics of functional diversity (functional evenness, functional divergence, functional dispersion, Rao's quadratic entropy) were not impacted by fire disturbance. Finally, the main contributors to heterogeneity were driven by a fire × exposure interaction, suggesting that fire disturbance interacts with topographic exposure. Our results suggest that taxonomic and functional α- and β-diversity have contrasting responses to fire illustrating the need to consider both dimensions to understand how disturbance impacts plant communities. At large spatial scale, species turnover and nestedness appear as essential parameters to maintain species-rich communities in response to fire disturbance.

Nutrient cycling drives plant community trait assembly and ecosystem functioning in a tropical mountain biodiversity hotspot

Community trait assembly in highly diverse tropical rainforests is still poorly understood. Based on more than a decade of field measurements in a biodiversity hotspot of southern Ecuador, we implemented plant trait variation and improved soil organic matter dynamics in a widely used dynamic vegetation model (the Lund-Potsdam-Jena General Ecosystem Simulator, LPJ-GUESS) to explore the main drivers of community assembly along an elevational gradient. In the model used here (LPJ-GUESS-NTD, where NTD stands for nutrient-trait dynamics), each plant individual can possess different trait combinations, and the community trait composition emerges via ecological sorting. Further model developments include plant growth limitation by phosphorous (P) and mycorrhizal nutrient uptake. The new model version reproduced the main observed community trait shift and related vegetation processes along the elevational gradient, but only if nutrient limitations to plant growth were activated. In turn, when traits were fixed, low productivity communities emerged due to reduced nutrient-use efficiency. Mycorrhizal nutrient uptake, when deactivated, reduced net primary production (NPP) by 61-72% along the gradient. Our results strongly suggest that the elevational temperature gradient drives community assembly and ecosystem functioning indirectly through its effect on soil nutrient dynamics and vegetation traits. This illustrates the importance of considering these processes to yield realistic model predictions.

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

Leaf Economics of Early- and Late-Successional Plants

AbstractThe leaf economics spectrum ranges from cheap, short-lived leaves to expensive, long-lived leaves. Species with low leaf mass per area (LMA) and short leaf life span tend to be fast growing and shade intolerant (early successional), whereas species with high LMA and long leaf life span tend to be slow growing and shade tolerant (late successional). However, we have limited understanding of how different leaf mass components (e.g., metabolically active photosynthetic components vs. structural toughness components) contribute to variation in LMA and other leaf economics spectrum traits. Here, we develop a model of plant community dynamics in which species differ in just two traits, photosynthetic and structural LMA components, and we identify optimal values of these traits for early- and late-successional species. Most of the predicted increase in LMA from early- to late-successional species was due to structural LMA. Photosynthetic LMA did not differ consistently between early- and late-successional species, but the photosynthetic LMA to structural LMA ratio declined from early- to late-successional species. Early-successional species had high rates of instantaneous return on leaf mass investment, whereas late-successional species had high lifetime return. Our results provide theoretical support for the primary role of structural (rather than photosynthetic) LMA variation in driving relationships among leaf economics spectrum traits.

Tackling unresolved questions in forest ecology: The past and future role of simulation models

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

Intraspecific trait variation in plants: a renewed focus on its role in ecological processes

BACKGROUND

Investigating the causes and consequences of intraspecific trait variation (ITV) in plants is not novel, as it has long been recognized that such variation shapes biotic and abiotic interactions. While evolutionary and population biology have extensively investigated ITV, only in the last 10 years has interest in ITV surged within community and comparative ecology.

SCOPE

Despite this recent interest, still lacking are thorough descriptions of ITV's extent, the spatial and temporal structure of ITV, and stronger connections between ITV and community and ecosystem properties. Our primary aim in this review is to synthesize the recent literature and ask: (1) How extensive is intraspecific variation in traits across scales, and what underlying mechanisms drive this variation? (2) How does this variation impact higher-order ecological processes (e.g. population dynamics, community assembly, invasion, ecosystem productivity)? (3) What are the consequences of ignoring ITV and how can these be mitigated? and (4) What are the most pressing research questions, and how can current practices be modified to suit our research needs? Our secondary aim is to target diverse and underrepresented traits and plant organs, including anatomy, wood, roots, hydraulics, reproduction and secondary chemistry. In addressing these aims, we showcase papers from the Special Issue.

CONCLUSIONS

Plant ITV plays a key role in determining individual and population performance, species interactions, community structure and assembly, and ecosystem properties. Its extent varies widely across species, traits and environments, and it remains difficult to develop a predictive model for ITV that is broadly applicable. Systematically characterizing the sources (e.g. ontogeny, population differences) of ITV will be a vital step forward towards identifying generalities and the underlying mechanisms that shape ITV. While the use of species means to link traits to higher-order processes may be appropriate in many cases, such approaches can obscure potentially meaningful variation. We urge the reporting of individual replicates and population means in online data repositories, a greater consideration of the mechanisms that enhance and constrain ITV's extent, and studies that span sub-disciplines.

Does economic optimisation explain LAI and leaf trait distributions across an Amazon soil moisture gradient?

Leaf area index (LAI) underpins terrestrial ecosystem functioning, yet our ability to predict LAI remains limited. Across Amazon forests, mean LAI, LAI seasonal dynamics and leaf traits vary with soil moisture stress. We hypothesise that LAI variation can be predicted via an optimality-based approach, using net canopy C export (NCE, photosynthesis minus the C cost of leaf growth and maintenance) as a fitness proxy. We applied a process-based terrestrial ecosystem model to seven plots across a moisture stress gradient with detailed in situ measurements, to determine nominal plant C budgets. For each plot, we then compared observations and simulations of the nominal (i.e. observed) C budget to simulations of alternative, experimental budgets. Experimental budgets were generated by forcing the model with synthetic LAI timeseries (across a range of mean LAI and LAI seasonality) and different leaf trait combinations (leaf mass per unit area, lifespan, photosynthetic capacity and respiration rate) operating along the leaf economic spectrum. Observed mean LAI and LAI seasonality across the soil moisture stress gradient maximised NCE, and were therefore consistent with optimality-based predictions. Yet, the predictive power of an optimality-based approach was limited due to the asymptotic response of simulated NCE to mean LAI and LAI seasonality. Leaf traits fundamentally shaped the C budget, determining simulated optimal LAI and total NCE. Long-lived leaves with lower maximum photosynthetic capacity maximised simulated NCE under aseasonal high mean LAI, with the reverse found for short-lived leaves and higher maximum photosynthetic capacity. The simulated leaf trait LAI trade-offs were consistent with observed distributions. We suggest that a range of LAI strategies could be equally economically viable at local level, though we note several ecological limitations to this interpretation (e.g. between-plant competition). In addition, we show how leaf trait trade-offs enable divergence in canopy strategies. Our results also allow an assessment of the usefulness of optimality-based approaches in simulating primary tropical forest functioning, evaluated against in situ data.

A research framework for projecting ecosystem change in highly diverse tropical mountain ecosystems

Tropical mountain ecosystems are threatened by climate and land-use changes. Their diversity and complexity make projections how they respond to environmental changes challenging. A suitable way are trait-based approaches, by distinguishing between response traits that determine the resistance of species to environmental changes and effect traits that are relevant for species' interactions, biotic processes, and ecosystem functions. The combination of those approaches with land surface models (LSM) linking the functional community composition to ecosystem functions provides new ways to project the response of ecosystems to environmental changes. With the interdisciplinary project RESPECT, we propose a research framework that uses a trait-based response-effect-framework (REF) to quantify relationships between abiotic conditions, the diversity of functional traits in communities, and associated biotic processes, informing a biodiversity-LSM. We apply the framework to a megadiverse tropical mountain forest. We use a plot design along an elevation and a land-use gradient to collect data on abiotic drivers, functional traits, and biotic processes. We integrate these data to build the biodiversity-LSM and illustrate how to test the model. REF results show that aboveground biomass production is not directly related to changing climatic conditions, but indirectly through associated changes in functional traits. Herbivory is directly related to changing abiotic conditions. The biodiversity-LSM informed by local functional trait and soil data improved the simulation of biomass production substantially. We conclude that local data, also derived from previous projects (platform Ecuador), are key elements of the research framework. We specify essential datasets to apply this framework to other mountain ecosystems.

Components of leaf-trait variation along environmental gradients

Leaf area (LA), mass per area (LMA), nitrogen per unit area (N_area ) and the leaf-internal to ambient CO₂ ratio (χ) are fundamental traits for plant functional ecology and vegetation modelling. Here we aimed to assess how their variation, within and between species, tracks environmental gradients. Measurements were made on 705 species from 116 sites within a broad north-south transect from tropical to temperate Australia. Trait responses to environment were quantified using multiple regression; within- and between-species responses were compared using analysis of covariance and trait-gradient analysis. Leaf area, the leaf economics spectrum (indexed by LMA and N_area ) and χ (from stable carbon isotope ratios) varied almost independently among species. Across sites, however, χ and LA increased with mean growing-season temperature (mGDD₀ ) and decreased with vapour pressure deficit (mVPD₀ ) and soil pH. LMA and N_area showed the reverse pattern. Climate responses agreed with expectations based on optimality principles. Within-species variability contributed < 10% to geographical variation in LA but > 90% for χ, with LMA and N_area intermediate. These findings support the hypothesis that acclimation within individuals, adaptation within species and selection among species combine to create predictable relationships between traits and environment. However, the contribution of acclimation/adaptation vs species selection differs among traits.

Robust leaf trait relationships across species under global environmental changes

Recent studies show coordinated relationships between plant leaf traits and their capacity to predict ecosystem functions. However, how leaf traits will change within species and whether interspecific trait relationships will shift under future environmental changes both remain unclear. Here, we examine the bivariate correlations between leaf economic traits of 515 species in 210 experiments which mimic climate warming, drought, elevated CO₂, and nitrogen deposition. We find divergent directions of changes in trait-pairs between species, and the directions mostly do not follow the interspecific trait relationships. However, the slopes in the logarithmic transformed interspecific trait relationships hold stable under environmental changes, while only their elevations vary. The elevation changes of trait relationship are mainly driven by asymmetrically interspecific responses contrary to the direction of the leaf economic spectrum. These findings suggest robust interspecific trait relationships under global changes, and call for linking within-species responses to interspecific coordination of plant traits.

It is unclear whether rapid global change will lead to unexpected trait combinations. In this global meta-analysis on vascular plants, Cui et al. show that, although within-species responses do not always follow the leaf economic spectrum, the slopes of interspecific trait relationships are robust to rapid environmental change.

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis

The leaf economic spectrum is a widely studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of plant functional types (PFTs). We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (specific leaf area [SLA], N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (dark respiration [R_d ], maximum RuBisCo carboxylation rate [V_c,max ], maximum electron transport rate [J_max ]) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, this covariance was an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.

Climatic and edaphic controls over tropical forest diversity and vegetation carbon storage

Tropical rainforests harbor exceptionally high biodiversity and store large amounts of carbon in vegetation biomass. However, regional variation in plant species richness and vegetation carbon stock can be substantial, and may be related to the heterogeneity of topoedaphic properties. Therefore, aboveground vegetation carbon storage typically differs between geographic forest regions in association with the locally dominant plant functional group. A better understanding of the underlying factors controlling tropical forest diversity and vegetation carbon storage could be critical for predicting tropical carbon sink strength in response to projected climate change. Based on regionally replicated 1-ha forest inventory plots established in a region of high geomorphological heterogeneity we investigated how climatic and edaphic factors affect tropical forest diversity and vegetation carbon storage. Plant species richness (of all living stems >10 cm in diameter) ranged from 69 to 127 ha-1 and vegetation carbon storage ranged from 114 to 200 t ha-1. While plant species richness was controlled by climate and soil water availability, vegetation carbon storage was strongly related to wood density and soil phosphorus availability. Results suggest that local heterogeneity in resource availability and plant functional composition should be considered to improve projections of tropical forest ecosystem functioning under future scenarios.

Functional Trait Variation Among and Within Species and Plant Functional Types in Mountainous Mediterranean Forests

Plant structural and biochemical traits are frequently used to characterise the life history of plants. Although some common patterns of trait covariation have been identified, recent studies suggest these patterns of covariation may differ with growing location and/or plant functional type (PFT). Mediterranean forest tree/shrub species are often divided into three PFTs based on their leaf habit and form, being classified as either needleleaf evergreen (Ne), broadleaf evergreen (Be), or broadleaf deciduous (Bd). Working across 61 mountainous Mediterranean forest sites of contrasting climate and soil type, we sampled and analysed 626 individuals in order to evaluate differences in key foliage trait covariation as modulated by growing conditions both within and between the Ne, Be, and Bd functional types. We found significant differences between PFTs for most traits. When considered across PFTs and by ignoring intraspecific variation, three independent functional dimensions supporting the Leaf-Height-Seed framework were identified. Some traits illustrated a common scaling relationship across and within PFTs, but others scaled differently when considered across PFTs or even within PFTs. For most traits much of the observed variation was attributable to PFT identity and not to growing location, although for some traits there was a strong environmental component and considerable intraspecific and residual variation. Nevertheless, environmental conditions as related to water availability during the dry season and to a smaller extend to soil nutrient status and soil texture, clearly influenced trait values. When compared across species, about half of the trait-environment relationships were species-specific. Our study highlights the importance of the ecological scale within which trait covariation is considered and suggests that at regional to local scales, common trait-by-trait scaling relationships should be treated with caution. PFT definitions by themselves can potentially be an important predictor variable when inferring one trait from another. These findings have important implications for local scale dynamic vegetation models.

Climate and plant community diversity in space and time

Climate strongly shapes plant diversity over large spatial scales, with relatively warm and wet (benign, productive) regions supporting greater numbers of species. Unresolved aspects of this relationship include what causes it, whether it permeates to community diversity at smaller spatial scales, whether it is accompanied by patterns in functional and phylogenetic diversity as some hypotheses predict, and whether it is paralleled by climate-driven changes in diversity over time. Here, studies of Californian plants are reviewed and new analyses are conducted to synthesize climate-diversity relationships in space and time. Across spatial scales and organizational levels, plant diversity is maximized in more productive (wetter) climates, and these consistent spatial relationships are mirrored in losses of taxonomic, functional, and phylogenetic diversity over time during a recent climatic drying trend. These results support the tolerance and climatic niche conservatism hypotheses for climate-diversity relationships, and suggest there is some predictability to future changes in diversity in water-limited climates.

Open Science principles for accelerating trait-based science across the Tree of Life

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Modeling the Effects of Global Change on Ecosystem Processes in a Tropical Rainforest

Research Highlights: Ongoing land-use change and climate change in wet tropical forests can potentially drive shifts in tree species composition, representing a change in individual species within a functional group, tropical evergreen trees. The impacts on the global carbon cycle are potentially large, but unclear. We explored the differential effects of species within this functional group, in comparison with the effects of climate change, using the Century model as a research tool. Simulating effects of individual tree species on biome-level biogeochemical cycles constituted a novel application for Century. Background and Objectives: A unique, long-term, replicated field experiment containing five evergreen tree species in monodominant stands under similar environmental conditions in a Costa Rican wet forest provided data for model evaluation. Our objectives were to gain insights about this forest’s biogeochemical cycles and effects of tree species within this functional group, in comparison with climate change. Materials and Methods: We calibrated Century, using long-term meteorological, soil, and plant data from the field-based experiment. In modeling experiments, we evaluated effects on forest biogeochemistry of eight plant traits that were both observed and modeled. Climate-change simulation experiments represented two climate-change aspects observed in this region. Results: Model calibration revealed that unmodeled soil processes would be required to sustain observed P budgets. In species-traits experiments, three separate plant traits (leaf death rate, leaf C:N, and allocation to fine roots) resulted in modeled biomass C stock changes of >50%, compared with a maximum 21% change in the climate-change experiments. Conclusions: Modeled ecosystem properties and processes in Century were sensitive to changes in plant traits and nutrient limitations to productivity. Realistic model output was attainable for some species, but unusual plant traits thwarted predictions for one species. Including more plant traits and soil processes could increase realism, but less-complex models provide an accessible means for exploring plant-soil-atmosphere interactions.

A Structure Shaped by Fire, but Also Water: Ecological Consequences of the Variability in Bark Properties Across 31 Species From the Brazilian Cerrado

Bark is a structure involved in multiple physiological functions, but which has been traditionally associated with protection against fire. Thus, little is known about how the morpho-anatomical variations of this structure are related to different ecological pressures, especially in tropical savanna species, which are commonly subjected to frequent fire and drought events. Here we evaluated how the structural and functional variations of bark are related to the processes of resilience and resistance to fire, as well as transport and storage of water in 31 native species from the Brazilian Cerrado. Because of their thick bark, none of the trees analyzed were top-killed after a severe fire event. The structural and functional variations of the bark were also associated with water storage and transport, functions related to properties of the inner bark. In fact, species with a thicker and less dense inner bark were the ones that had the highest water contents in the wood, bark, and leaves. Lower bark density was also related to higher stem hydraulic conductivity, carbon assimilation, and growth. Overall, we provide strong evidence that in addition to protection from fire, the relative investment in bark also reflects different strategies of water use and conservation among many Cerrado tree species.

N-P utilization of Acer mono leaves at different life history stages across altitudinal gradients

The relationship between plants and the environment is a core area of research in ecology. Owing to differences in plant sensitivity to the environment at different life history stages, the adaptive strategies of plants are a cumulative result of both their life history and environment. Previous research on plant adaptation strategies has focused on adult plants, neglecting saplings or seedlings, which are more sensitive to the environment and largely affect the growth strategy of subsequent life stages. We compared leaf N and P stoichiometric traits of the seedlings, saplings, and adult trees of Acer mono Maxim and different altitudes and found significant linear trends for both life history stages and altitude. Leaf N and P content by unit mass were greatly affected by environmental change, and the leaf N and P content by unit area varied greatly by life history stage. Acer mono leaf N-P utilization showed a significant allometric growth trend in all life history stages and at low altitudes. The adult stage had higher N-use efficiency than the seedling stage and exhibited an isometric growth trend at high altitudes. The N-P utilization strategies of A. mono leaves are affected by changing environmental conditions, but their response is further dependent upon the life history stage of the plant. Thus, this study provides novel insights into the nutrient use strategies of A. mono and how they respond to the environmental temperature, soil moisture content along altitude and how these changes differ among different life history stages, which further provide the scientific basis for the study of plant nutrient utilization strategy on regional scale.

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.

Towards a New Generation of Trait-Flexible Vegetation Models

Plant trait variability, emerging from eco-evolutionary dynamics that range from alleles to macroecological scales, is one of the most elusive, but possibly most consequential, aspects of biodiversity. Plasticity, epigenetics, and genetic diversity are major determinants of how plants will respond to climate change, yet these processes are rarely represented in current vegetation models. Here, we provide an overview of the challenges associated with understanding the causes and consequences of plant trait variability, and review current developments to include plasticity and evolutionary mechanisms in vegetation models. We also present a roadmap of research priorities to develop a next generation of vegetation models with flexible traits. Including trait variability in vegetation models is necessary to better represent biosphere responses to global change.

Assessment of Risk and Resilience of Terrestrial Ecosystem Productivity under the Influence of Extreme Climatic Conditions over India

Analysing the link between terrestrial ecosystem productivity (i.e., Net Primary Productivity: NPP) and extreme climate conditions is vital in the context of increasing threats due to climate change. To reveal the impact of changing extreme conditions on NPP, a copula-based probabilistic model was developed, and the study was carried out over 25 river basins and 10 vegetation types of India. Further, the resiliency of the terrestrial ecosystems to sustain the extreme disturbances was evaluated at annual scale, monsoon, and non-monsoon seasons. The results showed, 15 out of 25 river basins were at high risks, and terrestrial ecosystems in only 5 river basins were resilient to extreme climatic conditions. Moreover, at least 50% area under 4 out of 10 vegetation cover types was found to be facing high chances of a drastic reduction in NPP, and 8 out of 10 vegetation cover types were non-resilient with the changing extreme climate conditions.

Observed variation in soil properties can drive large variation in modelled forest functioning and composition during tropical forest secondary succession

Censuses of tropical forest plots reveal large variation in biomass and plant composition. This paper evaluates whether such variation can emerge solely from realistic variation in a set of commonly measured soil chemical and physical properties. Controlled simulations were performed using a mechanistic model that includes forest dynamics, microbe-mediated biogeochemistry, and competition for nitrogen and phosphorus. Observations from 18 forest inventory plots in Guanacaste, Costa Rica were used to determine realistic variation in soil properties. In simulations of secondary succession, the across-plot range in plant biomass reached 30% of the mean and was attributable primarily to nutrient limitation and secondarily to soil texture differences that affected water availability. The contributions of different plant functional types to total biomass varied widely across plots and depended on soil nutrient status. In Central America, soil-induced variation in plant biomass increased with mean annual precipitation because of changes in nutrient limitation. In Central America, large variation in plant biomass and ecosystem composition arises mechanistically from realistic variation in soil properties. The degree of biomass and compositional variation is climate sensitive. In general, model predictions can be improved through better representation of soil nutrient processes, including their spatial variation.

Contrasting stomatal sensitivity to temperature and soil drought in mature alpine conifers

Conifers growing at high elevations need to optimize their stomatal conductance (g_s ) for maximizing photosynthetic yield while minimizing water loss under less favourable thermal conditions. Yet the ability of high-elevation conifers to adjust their g_s sensitivity to environmental drivers remains largely unexplored. We used 4 years of sap flow measurements to elucidate intraspecific and interspecific variability of g_s in Larix decidua Mill. and Picea abies (L.) Karst along an elevational gradient and contrasting soil moisture conditions. Site- and species-specific g_s response to main environmental drivers were examined, including vapour pressure deficit, air temperature, solar irradiance, and soil water potential. Our results indicate that maximum g_s of L. decidua is >2 times higher, shows a more plastic response to temperature, and down-regulates g_s stronger during atmospheric drought compared to P. abies. These differences allow L. decidua to exert more efficient water use, adjust to site-specific thermal conditions, and reduce water loss during drought episodes. The stronger plasticity of g_s sensitivity to temperature and higher conductance of L. decidua compared to P. abies provide new insights into species-specific water use strategies, which affect species' performance and should be considered when predicting terrestrial water dynamics under future climatic change.