Robust leaf trait relationships across species under global environmental changes

Contrasting range changes and drivers of four forest foundation species under future climate change in China

Forest foundation species, vital for shaping community structure and dynamics through non-trophic level interactions, are key to forest succession and sustainability. Despite their ecological importance, the habitat ranges of these species in China and their responses to future climate change remain unclear. Our study employed the optimal MaxEnt model to assess the range shifts and their essential drivers of four typical forest foundation species from three climatic zones in China under climate scenarios, including Acer tegmentosum, Acer pseudo-sieboldianum (temperate zone), Quercus glandulifera (subtropical zone), and Ficus hispida (tropical zone). The optimal MaxEnt model exhibited high evaluation indices (AUC values > 0.90) for the four foundation species, indicating excellent predictive performance. Currently, we observed that A. tegmentosum and A. pseudo-sieboldianum are predominantly inhabited temperate forest areas in northeastern China, Q. glandulifera is primarily concentrated in subtropical forests in southeastern China, and F. hispida is mainly distributed across the tropical forests in southern China. Climate factors, particularly temperature, emerged as the primary environmental factors influencing the potential range of forest foundation species. Moreover, precipitation strongly influenced the potential range of A. tegmentosum and A. pseudo-sieboldianum, while elevation exhibited a greater impact on the range of Q. glandulifera and F. hispida. Under future climate scenarios, suitable areas for A. tegmentosum and A. pseudo-sieboldianum tend to expand southward, F. hispida tends to expand northward, while Q. glandulifera exhibited a tendency to contract towards the center. This study advances our understanding of the spatial and temporal dynamics of forest foundation species in China under climate change, providing critical insights for conservation efforts and sustainable forest management practices.

Using leaf economic spectrum and photosynthetic acclimation to evaluate the potential performance of wintersweet under future climate conditions

The function of landscape plants on the ecosystem can alleviate environmental issues of urbanization and global change. Global changes due to elevated CO2 affect plant growth and survival, but there is a lack of quantitative methods to evaluate the adaptability of landscape plants to future climate conditions. Leaf traits characterized by leaf economic spectrum (LES) are the universal currency for predicting the impact on plant ecosystem functions. Elevated CO2 usually leads to photosynthetic acclimation (PC), characterised by decreased photosynthetic capacity. Here, we proposed a theoretical and practical framework for the use of LES and PC to project the potential performance of landscape plants under future climatic conditions through principal component analysis, structural equation modelling, photosynthetic restriction analysis and nitrogen allocation analysis. We used wintersweet (an important landscaping species) to test the feasibility of this framework under elevated CO2 and different nitrogen (N) supplies. We found that elevated CO2 decreased the specific leaf area but increased leaf N concentration. The results suggest wintersweet may be characterized by an LES with high leaf construction costs, low photosynthetic return, and robust stress resistance. Elevated CO2 reduced photosynthetic capacity and stomatal conductance but increased photosynthetic rate and leaf area. These positive physio-ecological traits, e.g., larger leaf area (canopy), higher water use efficiency and stress resistance, may lead to improved performance of wintersweet under the predicted future climatic conditions. The results suggest planting more wintersweet in urban landscaping may be an effective adaptive strategy to climate change.

Changes in mass allocation play a more prominent role than morphology in resource acquisition of the rhizomatous Leymus chinensis under drought stress

BACKGROUND AND AIMS

Plants can respond to drought by changing their relative investments in the biomass and morphology of each organ. The aims of this study were to quantify the relative contribution of changes in morphology vs. allocation and determine how they affect each other. These results should help us understand the mechanisms that plants use to respond to drought events.

METHODS

In a glasshouse experiment, we applied a drought treatment (well-watered vs. drought) at early and late stages of plant growth, leading to four treatment combinations (well-watered in both early and late periods, WW; drought in the early period and well-watered in the late period, DW; well-watered in the early period and drought in the late period, WD; drought in both early and late periods, DD). We used the variance partitioning method to compare the contribution of organ (leaf and root) biomass allocation and morphology to the leaf area ratio, root length ratio and root area ratio, for the rhizomatous grass Leymus chinensis (Trin.) Tzvelev.

KEY RESULTS

Compared with the continuously well-watered treatment, the leaf area ratio, root length ratio and root area ratio showed increasing trends under various drought treatments. The contribution of leaf mass allocation to leaf area ratio differed among the drought treatments and was 2.1- to 5.3-fold greater than leaf morphology, and the contribution of root mass allocation to root length ratio was ~2-fold greater than that of root morphology. In contrast, root morphology contributed more to the root area ratio than biomass allocation under drought in both the early and late periods. There was a negative correlation between the ratio of leaf mass fraction to root mass fraction and the ratio of specific leaf area to specific root length (or specific root area).

CONCLUSIONS

This study suggested that organ biomass allocation drove a larger proportion of variation than morphological traits for the absorption of resources in this rhizomatous grass. These findings should help us understand the adaptive mechanisms of plants when they are confronted with drought stress.

Timely estimation of leaf chlorophyll fluorescence parameters under varying light regimes by coupling light drivers to leaf traits

Unveiling informative chlorophyll a fluorescence (ChlF) parameters and leaf morphological/biochemical traits under varying light conditions is important in ecological studies but has less been investigated. In this study, the trait-ChlF relationship and regressive estimation of ChlF parameters from leaf traits under varying light conditions were investigated using a dataset of synchronous measurements of ChlF parameters and leaf morphological/biochemical traits in Mangifera indica L. The results showed that the relationships between ChlF parameters and leaf traits varied across light intensities, as indicated by different slopes and intercepts, highlighting the limitations of using leaf traits alone to capture the dynamics of ChlF parameters. Light drivers, on the other hand, showed a better predictive ability for light-dependent ChlF parameters compared to leaf traits, with light intensity having a large effect on light-dependent ChlF parameters. Furthermore, the responses of ФF and NPQ to light drivers differed between leaf types, with light intensity having an effect on ФF in shaded leaves, whereas it had a primary effect on NPQ in sunlit leaves. These results facilitate and deepen our understanding of how the light environment affects leaf structure and function and, therefore, provide the theoretical basis for understanding plant ecological strategies in response to the light environment.

Leaf phenotypic plasticity coupled with integration facilitates the adaptation of plants to enhanced N deposition

The response of leaf functional traits can provide vital insight into the adaptive strategies of plants under global change. However, empirical knowledge on the acclimation of functional coordination between phenotypic plasticity and integration to increased nitrogen (N) deposition is still scarce. The variation of leaf functional traits of two dominant seedling species, Machilus gamblei and Neolitsea polycarpa, across four N deposition rates (0, 3, 6, and 12 kg N ha^-1yr^-1), along with the relationship between leaf phenotypic plasticity and integration were investigated in a subtropical montane forest. We found that enhanced N deposition promoted the development of seedling traits toward the direction of resource acquisition, including improved leaf N content, specific leaf area and photosynthetic performance. Appropriate N deposition (≤6 kg N ha^-1 yr^-1) might induce the optimization of leaf functional traits to promote the capability and efficiency of nutrient use and photosynthesis in seedlings. However, excessive N deposition (12 kg N ha^-1 yr^-1) would result in detrimental effects on leaf morphological and physiological traits, thus inhibiting the efficiency in resource acquisition. A positive relationship occurred between leaf phenotypic plasticity and integration in both seedling species, implied that higher plasticity of leaf functional traits likely led to better integration with other traits under N deposition. Overall, our study emphasized that leaf functional traits could rapidly respond to changes in N resource, while the coordination between leaf phenotypic plasticity and integration can facilitate the adaptation of tree seedlings in coping with enhanced N deposition. Further studies are still needed on the role of leaf phenotypic plasticity and integration in plant fitness for predicting ecosystem functioning and forest dynamics, especially in the context of future high N deposition.

How woody plants adjust above- and below-ground traits in response to sustained drought

Future increases in drought severity and frequency are predicted to have substantial impacts on plant function and survival. However, there is considerable uncertainty concerning what drought adjustment is and whether plants can adjust to sustained drought. This review focuses on woody plants and synthesises the evidence for drought adjustment in a selection of key above-ground and below-ground plant traits. We assess whether evaluating the drought adjustment of single traits, or selections of traits that operate on the same plant functional axis (e.g. photosynthetic traits) is sufficient, or whether a multi-trait approach, integrating across multiple axes, is required. We conclude that studies on drought adjustments in woody plants might overestimate the capacity for adjustment to drier environments if spatial studies along gradients are used, without complementary experimental approaches. We provide evidence that drought adjustment is common in above-ground and below-ground traits; however, whether this is adaptive and sufficient to respond to future droughts remains uncertain for most species. To address this uncertainty, we must move towards studying trait integration within and across multiple axes of plant function (e.g. above-ground and below-ground) to gain a holistic view of drought adjustments at the whole-plant scale and how these influence plant survival.

Leaf economics fundamentals explained by optimality principles

The life span of leaves increases with their mass per unit area (LMA). It is unclear why. Here, we show that this empirical generalization (the foundation of the worldwide leaf economics spectrum) is a consequence of natural selection, maximizing average net carbon gain over the leaf life cycle. Analyzing two large leaf trait datasets, we show that evergreen and deciduous species with diverse construction costs (assumed proportional to LMA) are selected by light, temperature, and growing-season length in different, but predictable, ways. We quantitatively explain the observed divergent latitudinal trends in evergreen and deciduous LMA and show how local distributions of LMA arise by selection under different environmental conditions acting on the species pool. These results illustrate how optimality principles can underpin a new theory for plant geography and terrestrial carbon dynamics.

Global patterns of plant and microbial biomass in response to CO2 fumigation

Introduction

The stimulation of plant and microbial growth has been widely observed as a result of elevated CO₂ concentrations (eCO₂), however, this stimulation could be influenced by various factors and their relative importance remains unclear.

Methods

A global meta-analysis was performed using 884 lines of observations collected from published papers, which analyzed the eCO₂ impact on plant and microbial biomass.

Results

A significant positive impact of eCO₂ was observed on various biomass measures, including aboveground biomass (20.5%), belowground biomass (42.6%), soil microbial biomass (10.4%), fungal biomass (11.0%), and bacterial biomass (9.2%). It was found that eCO₂ levels above 200 ppm had a greater impact on plant biomass compared to concentrations at or below 200 ppm. On the other hand, studies showed that positive effects on microbial biomass were more prominent at lower eCO₂ levels (≤200 ppm) than at higher levels (>200 ppm), which could be explained by soil nitrogen limitations. Importantly, our results indicated that aboveground biomass was controlled more by climatic and experimental conditions, while soil properties strongly impacted the stimulation of belowground and microbial biomass.

Discussion

Our results provided evidence of the eCO₂ fertilization effect across various ecosystem types, experimental methods, and climates, and provided a quantitative estimate of plant and soil microbial biomass sensitivity to eCO₂. The results obtained in this study suggest that ecosystem models should consider climatic and edaphic factors to more accurately predict the effects of global climate change and their impact on ecosystem functions.

The trade-offs between resistance and resilience of forage stay robust with varied growth potentials under different soil water and salt stress

Water shortage and soil salinization are important factors restricting crop production worldwide. To conduct accurate yield prediction and reasonable crop layout, more attention should be paid to the performances of crop resistance and resilience under water and salt stress and their trade-off relationships. Here, we set different water (full irrigation, W0; moderate deficit irrigation, W1; and severe deficit irrigation, W2) and salt (S0, S1, S2, S3, S4, S5, and S6, representing 0 ‰, 1 ‰, 2 ‰, 3 ‰, 4 ‰, 5 ‰, and 6 ‰ salt in soil) treatments. Together with relevant studies, we analyzed the performances of forage resistance (Rt) and resilience (Rs) and their relationships under varied water and salt stress. The results indicated that logarithmic Rt (lg(Rt), the same as lg(Rs)) and the distribution of lg(Rs) were affected by water and salt stress, however, the relationships of lg(Rs)-lg(Rt) stayed stable with the constant slopes (k) and declined intercepts (m) as stress intensified. The physiological mechanisms and trade-offs for fixed species remained robust while the growth potentials varied under stress, which were closely related to stomatal regulations. Forage with larger |k| was suitable for fully irrigated regions to achieve higher yields, while regions with detrimental water and salt conditions should select cultivars with smaller |k| to ensure production. This study laid the groundwork for the estimation of the perennial forage adaptation and stability, and the method of long-term yield prediction and cultivar management under soil water and salt stress.

Variation of photosynthesis during plant evolution and domestication: implications for improving crop photosynthesis

Studies investigating the mechanisms underlying the variation of photosynthesis along plant phylogeny and especially during domestication are of great importance, and may provide new insights to further improve crop photosynthesis. In the present study, we compiled a database including 542 sets of data of leaf gas exchange parameters and leaf structural and chemical traits in ferns and fern allies, gymnosperms, non-crop angiosperms, and crops. We found that photosynthesis was dramatically improved from ferns and fern allies to non-crop angiosperms, and further increased in crops. The improvement of photosynthesis during phylogeny and domestication was related to increases in carbon dioxide diffusional capacities and, to a lesser extent, biochemical capacity. Cell wall thickness rather than chloroplast surface area facing intercellular airspaces drives the variation of mesophyll conductance. The variation of the maximum carboxylation rate was not related to leaf nitrogen content. The slope of the relationship between mass-based photosynthesis and nitrogen was lower in crops than in non-crop angiosperms. These findings suggest that the manipulation of cell wall thickness is the most promising approach to further improve crop photosynthesis, and that an increase of leaf nitrogen will be less efficient in improving photosynthesis in crops than in non-crop angiosperms.

Can evolutionary history predict plant plastic responses to climate change?

Plant plastic responses are critical to the adaptation and survival of species under climate change, but whether they are constrained by evolutionary history (phylogeny) is largely unclear. Plant leaf traits are key in determining plants' performance in different environments, and if these traits and their variation are phylogenetically dependent, predictions could be made to identify species vulnerable to climate change. We compiled data on three leaf traits (photosynthetic rate, specific leaf area, and leaf nitrogen content) and their variation under four environmental change scenarios (warming, drought, elevated CO₂ , or nitrogen addition) for 434 species, from 210 manipulation experiments. We found phylogenetic signal in the three traits but not in their variation under the four scenarios. This indicates that closely related species show similar traits but that their plastic responses could not be predicted from species relatedness under environmental change. Meanwhile, phylogeny weakened the slopes but did not change the directions of conventional pairwise trait relationships, suggesting that co-evolved leaf trait pairs have consistent responses under contrasting environmental conditions. Phylogeny can identify lineages rich in species showing similar traits and predict their relationships under climate change, but the degree of plant phenotypic variation does not vary consistently across evolutionary clades.

Leaf trait association in relation to herbivore defense, drought resistance, and economics in a tropical invasive plant

PREMISE

Exploring how functional traits vary and covary is important to understand plant responses to environmental change. However, we have limited understanding of the ways multiple functional traits vary and covary within invasive species.

METHODS

We measured 12 leaf traits of an invasive plant Chromolaena odorata, associated with plant or leaf economics, herbivore defense, and drought resistance on 10 introduced populations from Asia and 12 native populations from South and Central America, selected across a broad range of climatic conditions, and grown in a common garden.

RESULTS

Species' range and climatic conditions influenced leaf traits, but trait variation across climate space differed between the introduced and native ranges. Traits that confer defense against herbivores and drought resistance were associated with economic strategy, but the patterns differed by range. Plants from introduced populations that were at the fast-return end of the spectrum (high photosynthetic capacity) had high physical defense traits (high trichome density), whereas plants from native populations that were at the fast-return end of the spectrum had high drought escape traits (early leaf senescence and high percentage of withered shoots).

CONCLUSIONS

Our results indicate that invasive plants can rapidly adapt to novel environmental conditions. Chromolaena odorata showed multiple different functional trait covariation patterns and clines in the native and introduced ranges. Our results emphasize that interaction between multiple traits or functions should be considered when investigating the adaptive evolution of invasive plants.

Soil phosphorus drives plant trait variations in a mature subtropical forest

Earth system models are implementing soil phosphorus dynamic and plant functional traits to predict functional changes in global forests. However, the linkage between soil phosphorus and plant traits lacks empirical evidence, especially in mature forests. Here, we examined the soil phosphorus constraint on plant functional traits in a mature subtropical forest based on observations of 9943 individuals from 90 species in a 5-ha forest dynamic plot and 405 individuals from 15 species in an adjacent 10-year nutrient-addition experiment. We first confirmed a pervasive phosphorus limitation on subtropical tree growth based on leaf N:P ratios. Then, we found that soil phosphorus dominated multidimensional trait variations in the 5-ha forest dynamic plot. Soil phosphorus content explained 44% and 53% of the variance in the traits defining the main functional space across species and communities, respectively. Lastly, we found much stronger phosphorus effects on most plant functional traits than nitrogen at both species and community levels in the 10-year nutrient-addition experiment. This study provides evidence for the consistent pattern of soil phosphorus constraint on plant trait variations between the species and community levels in a mature evergreen broadleaf forest in the East Asian monsoon region. These findings shed light on the predominant role of soil phosphorus on plant functional trait variations in mature subtropical forests, providing new insights for models to incorporate soil phosphorus constraint in predicting future vegetation dynamics.

Varying Relationship Between Vascular Plant Leaf Area and Leaf Biomass Along an Elevational Gradient on the Eastern Qinghai-Tibet Plateau

The altitudinal gradient is one of the driving factors leading to leaf trait variation. It is crucial to understand the response and adaptation strategies of plants to explore the variation of leaf traits and their scaling relationship along the altitudinal gradient. We measured six main leaf traits of 257 woody species at 26 altitudes ranging from 1,050 to 3,500 m within the eastern Qinghai-Tibet Plateau and analyzed the scaling relationships among leaf fresh weight, leaf dry weight, and leaf area. The results showed that leaf dry weight increased significantly with elevation, while leaf fresh weight and leaf area showed a unimodal change. Leaf dry weight and fresh weight showed an allometric relationship, and leaf fresh weight increased faster than leaf dry weight. The scaling exponent of leaf area and leaf fresh weight (or dry weight) was significantly greater than 1, indicating that there have increasing returns for pooled data. For α and normalization constants (β), only β of leaf area vs. leaf fresh weight (or dry weight) had significantly increased with altitude. All three paired traits had positive linear relationships between α and β. Our findings suggest that plants adapt to altitudinal gradient by changing leaf area and biomass investment and coordinating scaling relationships among traits. But leaf traits variation had a minor effect on scaling exponent.

Influence of Leaf Age on the Scaling Relationships of Lamina Mass vs. Area

Leaf lamina mass and area are closely correlated with the photosynthetic capacity and competitive ability of plants, whereas leaf age has been demonstrated to affect physiological processes such as photosynthesis. However, it remains unknown whether the lamina mass vs. area scaling relationship is influenced by leaf age, which is important for understanding plant adaptive strategies and, more broadly, resource utilization and growth. We measured the leaf functional traits of five leaf-age groups of Photinia × fraseri for a total of 1,736 leaves. ANOVA followed by Tukey's honestly significant difference test was used to compare the functional traits among the five leaf-age groups. Reduced major axis regression protocols were used to fit the scaling relationship between lamina mass and area, and the bootstrap percentile method was used to compare the lamina mass vs. area scaling relationships among the leaf-age groups. Lamina area, and the ratio of lamina dry mass to lamina fresh mass increased with increasing leaf age. Lamina fresh mass per unit area, and lamina dry mass per unit area both exhibited a parabolic-like trend as leaf age increased, i.e., at the leaf maturation stage, it showed a slight but significant decline. The phenomenon called diminishing returns were confirmed by each of the five leaf-age groups, i.e., all of the numerical values of the scaling exponents of lamina mass vs. area were significantly greater than 1. There were significant differences in the scaling exponents of lamina mass vs. area for the leaves across different sampling times. The scaling exponents were lower at the early rapid growth stage, indicating a lower cost for increasing leaf area compared to the leaf maturation stage. These data are consistent with leaves undergoing a transition from resource acquisition to resource conservation in the process of their development and growth.

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.

Differential Investment Strategies in Leaf Economic Traits Across Climate Regions Worldwide

The leaf economics spectrum (LES) is the leading theory of plant ecological strategies based on functional traits, which explains the trade-off between dry matter investment in leaf structure and the potential rate of resource return, revealing general patterns of leaf economic traits investment for different plant growth types, functional types, or biomes. Prior work has revealed the moderating role of different environmental factors on the LES, but whether the leaf trait bivariate relationships are shifted across climate regions or across continental scales requires further verification. Here we use the Köppen-Geiger climate classification, a very widely used and robust criterion, as a basis for classifying climate regions to explore climatic differences in leaf trait relationships. We compiled five leaf economic traits from a global dataset, including leaf dry matter content (LDMC), specific leaf area (SLA), photosynthesis per unit of leaf dry mass (A_mass), leaf nitrogen concentration (N_mass), and leaf phosphorus concentration (P_mass). Moreover, we primarily used the standardized major axis (SMA) analysis to establish leaf trait bivariate relationships and to explore differences in trait relationships across climate regions as well as intercontinental differences within the same climate type. Leaf trait relationships were significantly correlated across almost all subgroups (P < 0.001). However, there was no common slope among different climate zones or climate types and the slopes of the groups fluctuated sharply up and down from the global estimates. The range of variation in the SMA slope of each leaf relationship was as follows: LDMC-SLA relationships (from -0.84 to -0.41); A_mass-SLA relationships (from 0.83 to 1.97); A_mass-N_mass relationships (from 1.33 to 2.25); N_mass-P_mass relationships (from 0.57 to 1.02). In addition, there was significant slope heterogeneity among continents within the Steppe climate (BS) or the Temperate humid climate (Cf). The shifts of leaf trait relationships in different climate regions provide evidence for environmentally driven differential plant investment in leaf economic traits. Understanding these differences helps to better calibrate various plant-climate models and reminds us that smaller-scale studies may need to be carefully compared with global studies.

Quantifying Leaf Trait Covariations and Their Relationships with Plant Adaptation Strategies along an Aridity Gradient

Simple Summary

Plants usually adopt different strategies to adapt to their surrounding environments. Accurately quantifying plant strategies is of great interest in trait-based ecology, in particular to understand the responses of ecological structures and processes. In the last two decades, these strategies have been described qualitatively; however, the use of quantitative methods is still lacking. In this study, we used a plant functional trait approach to discuss plant strategies along an aridity gradient. We found that eight functional traits divided into four dimensions represent four adaptation strategies: energy balance, resource acquisition, resource investment and water use efficiency. We also concluded that climate and soil together with family (vegetation succession) were the main driving forces of trait covariations. Our study provided a new perspective to understand plant functional responses to aridity gradients, which is helpful for ecological management and vegetation restoration programs in arid regions.

Abstract

A trait-based approach is an effective way to quantify plant adaptation strategies in response to changing environments. Single trait variations have been well depicted before; however, multi-trait covariations and their roles in shaping plant adaptation strategies along aridity gradients remain unclear. The purpose of this study was to reveal multi-trait covariation characteristics, their controls and their relevance to plant adaptation strategies. Using eight relevant plant functional traits and multivariate statistical approaches, we found the following: (1) the eight studied traits show evident covariation characteristics and could be grouped into four functional dimensions linked to plant strategies, namely energy balance, resource acquisition, resource investment and water use efficiency; (2) leaf area (LA) together with traits related to the leaf economic spectrum, including leaf nitrogen content per area (N_area), leaf nitrogen per mass (N_mass) and leaf dry mass per area (LMA), covaried along the aridity gradient (represented by the moisture index, MI) and dominated the trait–environmental change axis; (3) together, climate, soil and family can explain 50.4% of trait covariations; thus, vegetation succession along the aridity gradient cannot be neglected in trait covariations. Our findings provide novel perspectives toward a better understanding of plant adaptations to arid conditions and serve as a reference for vegetation restoration and management programs in arid regions.

Spatial variations in stomatal traits and their coordination with leaf traits in Quercus variabilis across Eastern Asia

The stomatal traits influence ecosystem carbon-water fluxes and play essential roles that enable plants to adapt to changing environmental conditions. However, how stomatal traits vary along a large climate gradient and whether stomatal traits coordinated with other leaf functional traits in response to environmental changes remain unclear. We investigated the stomatal density (SD), stomatal size (SS), and leaf traits (leaf area (LA), leaf mass per area (LMA), and vein density (VD)) of 44 in situ Quercus variabilis populations across Eastern Asia (24 to 51.8°N, 99 to 137°E) and 15 populations grown in a common garden, and evaluated their relationships with environmental factors. Stepwise multiple regression showed that the SD was significantly associated with mean annual precipitation (MAP), LMA, and VD, and the SS with latitude, mean annual temperature (MAT), mean monthly solar radiation (MMSR), and VD. The SD was positively correlated with the LMA, while the SS was negatively correlated with the VD. The SD and LMA increased with decreasing precipitation, which indicated that they may coordinate to commonly enhance plant resistance against drought. The SS decreased; however, the VD increased with temperature. This implied that plants might further reduce their SS by increasing VD limitations under global warming. In the common garden, plants exhibited a higher SD and VD and lower SS and LA compared to those in the field; however, no relation between the stomatal and leaf traits was observed. Our results suggested that stomatal traits have high environmental plasticity and are highly coordinated with other leaf functional traits in response to environmental changes. Nevertheless, this coordination may have been formed through long-term adaptations, rather than over short time spans.

Research challenges and opportunities for using big data in global change biology

Global change biology has been entering a big data era due to the vast increase in availability of both environmental and biological data. Big data refers to large data volume, complex data sets, and multiple data sources. The recent use of such big data is improving our understanding of interactions between biological systems and global environmental changes. In this review, we first explore how big data has been analyzed to identify the general patterns of biological responses to global changes at scales from gene to ecosystem. After that, we investigate how observational networks and space-based big data have facilitated the discovery of emergent mechanisms and phenomena on the regional and global scales. Then, we evaluate the predictions of terrestrial biosphere under global changes by big modeling data. Finally, we introduce some methods to extract knowledge from big data, such as meta-analysis, machine learning, traceability analysis, and data assimilation. The big data has opened new research opportunities, especially for developing new data-driven theories for improving biological predictions in Earth system models, tracing global change impacts across different organismic levels, and constructing cyberinfrastructure tools to accelerate the pace of model-data integrations. These efforts will uncork the bottleneck of using big data to understand biological responses and adaptations to future global changes.