Quantifying leaf-trait covariation and its controls across climates and biomes

Differential phenotypic plasticity of subalpine trees predicts trait integration under climate warming

Understanding limiting factors of phenotypic plasticity is essential given its critical role in shaping biological adaptation and evolution in changing environments. It has been proposed that the pattern of phenotypic correlation could constrain trait plasticity. However, the interplay between phenotypic plasticity and integration has remained contentious. We experimentally simulated climate warming in juveniles of three subalpine tree species by exposing them to three-year in situ open-top chambers (OTCs), and then measured functional plasticity of 72 eco-physiological traits to evaluate whether phenotypic integration constituted an intrinsic constraint to plasticity. We also tested the relationship between the differences in plasticity and maintenance in trait integration. Phenotypic plasticity was positively associated with integration in deciduous tree species under warming. The difference in the plasticity of two paired traits could predict their integration in different environments, where traits displaying more similar plasticity were more likely to be correlated. Our study showed no indication that phenotypic integration constrained plasticity. More importantly, we demonstrated that differential plasticity between traits might result in a notable reorganization of the trait associations, and that warming commonly induced a tighter phenotype. Our study provides new insights into the interplay between phenotypic plasticity and integration in subalpine trees under climate warming.

Coordination of water use strategies and leaf economic traits in coexisting exotic and native woody species from evergreen and deciduous broadleaf forests

The leaf economics spectrum (LES) describes the covariation of traits relevant for carbon and nutrient economy in different plant species. However, much less is known about the correlation of LES with leaf water economy, not only because some woody species do not follow the rules, but also because they are rarely tested on the widespread, non-native, fast-growing trees. We hypothesized that fast-growing exotic species that spread on the fast side of the LES coordinate their water-use strategies (WUS) to maintain rapid growth, and that the pattern of coordination differs between evergreen and deciduous forests. Using 4 exotic and 4 native species from evergreen and deciduous broadleaf forests in China, we measured 17 traits of LES and WUS and analyzed their functional roles in different species groups. Our results suggest that LES plays a more important role in the coexistence of species within a community, while WUS contributes more to the distribution of species across different regions. The multidimensional coordination of LES and WUS could better explain the growth and distribution of different plant species and shed light on the coexistence of species from different forest types, especially fast-growing woody exotics.

Global patterns of plant functional traits and their relationships to climate

Plant functional traits (FTs) determine growth, reproduction and survival strategies of plants adapted to their growth environment. Exploring global geographic patterns of FTs, their covariation and their relationships to climate are necessary steps towards better-founded predictions of how global environmental change will affect ecosystem composition. We compile an extensive global dataset for 16 FTs and characterise trait-trait and trait-climate relationships separately within non-woody, woody deciduous and woody evergreen plant groups, using multivariate analysis and generalised additive models (GAMs). Among the six major FTs considered, two dominant trait dimensions-representing plant size and the leaf economics spectrum (LES) respectively-are identified within all three groups. Size traits (plant height, diaspore mass) however are generally higher in warmer climates, while LES traits (leaf mass and nitrogen per area) are higher in drier climates. Larger leaves are associated principally with warmer winters in woody evergreens, but with wetter climates in non-woody plants. GAM-simulated global patterns for all 16 FTs explain up to three-quarters of global trait variation. Global maps obtained by upscaling GAMs are broadly in agreement with iNaturalist citizen-science FT data. This analysis contributes to the foundations for global trait-based ecosystem modelling by demonstrating universal relationships between FTs and climate.

Unveiling the transferability of PLSR models for leaf trait estimation: lessons from a comprehensive analysis with a novel global dataset

Leaf traits are essential for understanding many physiological and ecological processes. Partial least squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time, and plant functional types (PFTs) remains unclear. We compiled a novel dataset of paired leaf traits and spectra, with 47 393 records for > 700 species and eight PFTs at 101 globally distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits. While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water, and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reduced R2 (0.12-0.49, 0.15-0.42, and 0.25-0.56) and increased NRMSE (3.58-18.24%, 6.27-11.55%, and 7.0-33.12%) compared with nonspatial random cross-validation. The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability. These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs, and time due to biased validation schemes, and provide guidance for future field sampling strategies and remote sensing applications.

Environmental versus phylogenetic controls on leaf nitrogen and phosphorous concentrations in vascular plants

Global patterns of leaf nitrogen (N) and phosphorus (P) stoichiometry have been interpreted as reflecting phenotypic plasticity in response to the environment, or as an overriding effect of the distribution of species growing in their biogeochemical niches. Here, we balance these contrasting views. We compile a global dataset of 36,413 paired observations of leaf N and P concentrations, taxonomy and 45 environmental covariates, covering 7,549 sites and 3,700 species, to investigate how species identity and environmental variables control variations in mass-based leaf N and P concentrations, and the N:P ratio. We find within-species variation contributes around half of the total variation, with 29%, 31%, and 22% of leaf N, P, and N:P variation, respectively, explained by environmental variables. Within-species plasticity along environmental gradients varies across species and is highest for leaf N:P and lowest for leaf N. We identified effects of environmental variables on within-species variation using random forest models, whereas effects were largely missed by widely used linear mixed-effect models. Our analysis demonstrates a substantial influence of the environment in driving plastic responses of leaf N, P, and N:P within species, which challenges reports of a fixed biogeochemical niche and the overriding importance of species distributions in shaping global patterns of leaf N and P.

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.

Coordination of leaf, root, and seed traits shows the importance of whole plant economics in two semiarid grasslands

Uncertainty persists within trait-based ecology, partly because few studies assess multiple axes of functional variation and their effect on plant performance. For 55 species from two semiarid grasslands, we quantified: (1) covariation between economic traits of leaves and absorptive roots, (2) covariation among economic traits, plant height, leaf size, and seed mass, and (3) relationships between these traits and species' abundance. Pairs of analogous leaf and root traits were at least weakly positively correlated (e.g. specific leaf area (SLA) and specific root length (SRL)). Two pairs of such traits, N content and DMC of leaves and roots, were at least moderately correlated (r > 0.5) whether species were grouped by site, taxonomic group and growth form, or life history. Root diameter was positively correlated with seed mass for all groups of species except annuals and monocots. Species with higher leaf dry matter content (LDMC) tended to be more abundant (r = 0.63). Annuals with larger seeds were more abundant (r = 0.69). Compared with global-scale syntheses with many observations from mesic ecosystems, we observed stronger correlations between analogous leaf and root traits, weaker correlations between SLA and leaf N, and stronger correlations between SRL and root N. In dry grasslands, plant persistence may require coordination of above- and belowground traits, and dense tissues may facilitate dominance.

Impacts of climate timescale on the stability of trait-environment relationships

Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait-environment model predictions if timescale is not accounted for. Here, the timescale dependence of trait-environment relationships is investigated by regressing in situ trait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales. We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub-optimal climate timescales reduces the accuracy of the resulting trait-environment relationships. This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long-term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait-environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system.

Leaf habit and plant architecture integrate whole-plant economics and contextualize trait-climate associations within ecologically diverse genus Rhododendron

Plant resource strategies negotiate a trade-off between fast growth and stress resistance, characterized by specific leaf area (SLA). How SLA relates to leaf structure and function or plant climate associations remains open for debate, and leaf habit and plant architecture may alter the costs versus benefits of individual traits. We used phylogenetic canonical correspondence analysis and phylogenetic least squares to understand the relationship of anatomy and gas exchange to published data on root, wood, architectural and leaf economics traits and climate. Leaf anatomy was structured by leaf habit and carbon to nitrogen ratio was a better predictor of gas exchange than SLA. We found significant correspondence of leaf anatomy with branch architecture and wood traits, gas exchange corresponded with climate, while leaf economics corresponded with climate, architecture, wood and root traits. Species from the most seasonal climates had the highest trait-climate correspondence, and different aspects of economics and anatomy reflected leaf carbon uptake versus water use. Our study using phylogenetic comparative methods including plant architecture and leaf habit provides insight into the mechanism of whole-plant functional coordination and contextualizes individual traits in relation to climate, demonstrating the evolutionary and ecological relevance of trait-trait correlations within a genus with high biodiversity.

Variations and driving factors of leaf functional traits in the dominant desert plant species along an environmental gradient in the drylands of China

Leaf functional traits (LFTs) of desert plants are responsive, adaptable and highly plastic to their environment. However, the macroscale variation in LFTs and driving factors underlying this variation remain unclear, especially for desert plants. Here, we measured eight LFTs, including leaf carbon concentration (LCC), leaf nitrogen concentration (LNC), leaf phosphorus concentration (LPC), specific leaf area (SLA), leaf dry matter content (LDMC), leaf mass per area (LMA), leaf thickness (LTH) and leaf tissue density (LTD) across 114 sites along environmental gradient in the drylands of China and in Guazhou Common Garden and evaluated the effect of environment and phylogeny on the LFTs. We noted that for all species, the mean values of LCC, LNC, LPC, SLA, LDMC, LMA, LTH and LTD were 384.62 mg g-1, 19.91 mg g-1, 1.12 mg g-1, 79.62 cm2 g-1, 0.74 g g-1, 237.39 g m-2, 0.38 mm and 0.91 g cm-3, respectively. LFTs exhibited significant geographical variations and the LNC, LMA and LTH in the plants of Guazhou Common Garden were significantly higher than the field sites in the drylands of China. LDMC and LTD of plants in Guazhou Common Garden were, however, considerably lower than those in the drylands of China. LCC, LPC, LTH and LTD differed significantly among different plant lifeforms, while LNC, SLA, LDMC and LMA didn't show significant variations. We found that the environmental variables explained higher spatial variations (3.6-66.3 %) in LFTs than the phylogeny (1.8-54.2 %). The LCC significantly increased, while LDMC and LTD decreased with increased temperature and reduced precipitation. LPC, LDMC, LMA, and LTD significantly increased, while SLA and LTH decreased with increased aridity. However, leaf elements were not significantly correlated with soil nutrients. The mean annual precipitation was a key factor controlling variations in LFTs at the macroscale in the drylands of China. These findings will provide new insights to better understand the response of LFTs and plants adaptation along environmental gradient in drylands, and will serve as a reference for studying biogeographic patterns of leaf traits.

Plant trait networks reveal adaptation strategies in the drylands of China

BACKGROUND

Plants accomplish multiple functions by the interrelationships between functional traits. Clarifying the complex relationships between plant traits would enable us to better understand how plants employ different strategies to adapt to the environment. Although increasing attention is being paid to plant traits, few studies focused on the adaptation to aridity through the relationship among multiple traits. We established plant trait networks (PTNs) to explore the interdependence of sixteen plant traits across drylands.

RESULTS

Our results revealed significant differences in PTNs among different plant life-forms and different levels of aridity. Trait relationships for woody plants were weaker, but were more modularized than for herbs. Woody plants were more connected in economic traits, whereas herbs were more connected in structural traits to reduce damage caused by drought. Furthermore, the correlations between traits were tighter with higher edge density in semi-arid than in arid regions, suggesting that resource sharing and trait coordination are more advantageous under low drought conditions. Importantly, our results demonstrated that stem phosphorus concentration (SPC) was a hub trait correlated with other traits across drylands.

CONCLUSIONS

The results demonstrate that plants exhibited adaptations to the arid environment by adjusting trait modules through alternative strategies. PTNs provide a new insight into understanding the adaptation strategies of plants to drought stress based on the interdependence among plant functional traits.

Distinct leaf functional traits of Tamarix chinensis at different habitats in the hinterland of the Taklimakan desert

Leaf functional traits reflect plant adaptive strategies towards environmental heterogeneity. However, which factor play the key role of plasticity of leaf functional traits among various variable environmental factors remains unclear in desert hinterland oasis area. Here, we analyzed variations in leaf water content (LWC), δ ¹³C values of leaves (δ ¹³C), specific leaf area (SLA), leaf organic carbon concentration (LOC), leaf total nitrogen concentration (LTN), leaf total phosphorus concentration (LTP), and leaf C: N: P stoichiometry in Tamarix chinensis growing in five habitats at the Daliyabuyi, a natural pristine oasis in northwestern China, that differ abiotically and biotically. The spatial heterogeneity of leaf functional traits was evident. Abiotic factors vitally influence leaf functional traits, of which groundwater depth (GWD) and soil C: N stoichiometry (SOC: STN) are crucial. GWD exhibited close relationships with LWC (P < 0.05) and LOC: LTP (P < 0.01), but not δ ¹³C. Soil water content (SWC) and SOC: STN were negatively related to SLA (P < 0.01; P < 0.05). While, SOC: STN showed positive relationships with LOC: LTN (P < 0.05). As for biological factors, we found T. chinensis in habitat with Sophora alopecuroidies had the highest LTN, possibly as a result of N fixation of leguminous plants (S. alopecuroidies) promotes the N concentration of T. chinensis. Close relationships also existed between leaf functional traits, LWC showed significantly negatively relatd to δ ¹³C, LOC: LTN and LOC: LTP (P < 0.05), whereas δ ¹³C had positively correlated with LOC: LTN (P < 0.01) but negatively correlated with LTN (P < 0.05). T. chinensis had relative higher LWC couple with lower δ ¹³C, and exhibiting lower C, N, P in leaves and their stoichiometric ratios, and also lower SLA which compared with other terrestrial plant. Such coordinations suggesting that T. chinensis develops a suite of trait combinations mainly tends to more conservative to response local habitats in Daliyabuyi, which is contribute to understand desert plant resource acquisition and utilization mechanisms in extremely arid and barren environments.

The China plant trait database version 2

Plant functional traits represent adaptive strategies to the environment, linked to biophysical and biogeochemical processes and ecosystem functioning. Compilations of trait data facilitate research in multiple fields from plant ecology through to land-surface modelling. Here we present version 2 of the China Plant Trait Database, which contains information on morphometric, physical, chemical, photosynthetic and hydraulic traits from 1529 unique species in 140 sites spanning a diversity of vegetation types. Version 2 has five improvements compared to the previous version: (1) new data from a 4-km elevation transect on the edge of Tibetan Plateau, including alpine vegetation types not sampled previously; (2) inclusion of traits related to hydraulic processes, including specific sapwood conductance, the area ratio of sapwood to leaf, wood density and turgor loss point; (3) inclusion of information on soil properties to complement the existing data on climate and vegetation (4) assessments and flagging the reliability of individual trait measurements; and (5) inclusion of standardized templates for systematical field sampling and measurements.

N addition rebalances the carbon and nitrogen metabolisms of Leymus chinensis through leaf N investment

Intensifying nitrogen (N) deposition disturbs the growth of grassland plants due to an imbalance between their carbon (C) and N metabolism. However, it's unclear how plant physiological strategies restore balance. We investigated the effects of multiple N addition levels (0-25 g N m^-2 yr^-1) on the coordination of C and N metabolism in a dominant grass (Leymus chinensis) in a semiarid grassland in northern China. To do so, we evaluated photosynthetic parameters, leaf N allocation, C- and N-based metabolites, and metabolic enzymes. We found that a moderate N level (10 g N m^-2 yr^-1) promoted carboxylation and electron transport by allocating more N to the photosynthetic apparatus and increasing ribulose bisphosphate carboxylase/oxygenase activity, thereby increasing photosynthetic capacity. The highest N level (25 g N m^-2 yr^-1) promoted N investment in nonphotosynthetic pathways and increased the free amino acids in the leaves. N addition stimulated the accumulation of C and N compounds across organs by activating sucrose phosphate synthase, nitrate reductase, and glutamine synthetase. This enhancement triggered a transformation of primary metabolites (nonstructural carbohydrates, proteins, amino acids) to secondary metabolites (flavonoids, phenols, and alkaloids) for temporary storage or as defense compounds. Citric acid, as the C skeleton for enhanced N metabolism, decreased significantly, and malic acid increased by catalysis of phosphoenolpyruvate carboxylase. Our findings show the adaptability of L. chinensis to different N-addition levels by adjusting its allocations of C and N metabolic compounds and confirm the roles of C and N coordination by grassland plants in these adaptations.

Leaf morphological traits as adaptations to multiple climate gradients

Leaf morphological traits vary systematically along climatic gradients. However, recent studies in plant functional ecology have mainly analysed quantitative traits, while numerical models of species distributions and vegetation function have focused on traits associated with resource acquisition; both ignore the wider functional significance of leaf morphology.A dataset comprising 22 leaf morphological traits for 662 woody species from 92 sites, representing all biomes present in China, was subjected to multivariate analysis in order to identify leading dimensions of trait covariation (correspondence analysis), quantify climatic and phylogenetic contributions (canonical correspondence analysis with variation partitioning) and characterise co-occurring trait syndromes (k-means clustering) and their climatic preferences.Three axes accounted for >20% of trait variation in both evergreen and deciduous species. Moisture index, precipitation seasonality and growing-season temperature explained 8%-10% of trait variation; family 15%-32%. Microphyll or larger, mid- to dark green leaves with drip tips in wetter climates contrasted with nanophyll or smaller glaucous leaves without drip tips in drier climates. Thick, entire leaves in less seasonal climates contrasted with thin, marginal dissected, aromatic and involute/revolute leaves in more seasonal climates. Thick, involute, hairy leaves in colder climates contrasted with thin leaves with marked surface structures (surface patterning) in warmer climates. Distinctive trait clusters were linked to the driest and most seasonal climates, for example the clustering of picophyll, fleshy and succulent leaves in the driest climates and leptophyll, linear, dissected, revolute or involute and aromatic leaves in regions with highly seasonal rainfall. Several trait clusters co-occurred in wetter climates, including clusters characterised by microphyll, moderately thick, patent and entire leaves or notophyll, waxy, dark green leaves. Synthesis. The plastic response of size, shape, colour and other leaf morphological traits to climate is muted, thus their apparent shift along climate gradients reflects plant adaptations to environment at a community level as determined by species replacement. Information on leaf morphological traits, widely available in floras, could be used to strengthen predictive models of species distribution and vegetation function.

Phylogenetic independence in the variations in leaf functional traits among different plant life forms in an arid environment

Leaf traits of global plants reveal the fundamental trade-offs in plant resource acquisition to conservation strategies. However, which leaf traits are consistent, converged, or diverged among herbs, shrubs, and subshrubs in an arid environment remains unclear. In the present study, we evaluated the trade-offs in six leaf functional traits (LFTs): leaf fresh mass (LFM), leaf dry mass (LDM), leaf dry matter content (LDMC), leaf area (LA), specific leaf area (SLA), and leaf thickness (LTh) of 37 desert plant species. LFTs differed between different plant life forms; LFM, LDM, and LA were slightly higher in herbs, LDMC and LTh in shrubs, and SLA in subshrubs. Conversely, the correlations among LFTs were inconsistent in different life forms, which may indicate their different adaptation strategies in an arid environment. Legumes and C₃ plants exhibited slightly higher LDMC, LA, and SLA than non-legumes and C₄ plants, whereas non-legumes and C₄ plants showed higher (nonsignificant) LFM, LDM, and LTh than legumes and C₃ plants. A significant phylogenetic signal (PS) and maximum K-value were found for SLA (K = 0.32). LFTs exhibited convergent and divergent variations among different life forms. However, these variations in LFTs were not influenced by phylogeny. Together, these findings increase our understanding of the variations in ecological adaptations of desert plants as well as adaption strategies of different life forms in an arid environment.

Exploring how functional traits modulate species distributions along topographic gradients in Baxian Mountain, North China

The associations between functional traits and species distributions across environments have attracted increasing interest from ecologists and can enhance knowledge about how plants respond to the environments. Here, we applied a hierarchical generalized linear model to quantifying the role of functional traits in plant occurrence across topographic gradients. Functional trait data, including specific leaf area, maximum height, seed mass and stem wood density, together with elevation, aspect and slope, were used in the model. In our results, species responses to elevation and aspect were modulated by maximum height and seed mass. Generally, shorter tree species showed positive responses to incremental elevation, while this trend became negative as the maximum height exceeded 22 m. Most trees with heavy seeds (> 1 mg) preferred more southerly aspects where the soil was drier, and those light-seed trees were opposite. In this study, the roles of maximum height and seed mass in determining species distribution along elevation and aspect gradients were highlighted where plants are confronted with low-temperature and soil moisture deficit conditions. This work contributes to the understanding of how traits may be associated with species occurrence along mesoscale environmental gradients.

Long-term leaf C:N ratio change under elevated CO2 and nitrogen deposition in China: Evidence from observations and process-based modeling

Climate change, elevating atmosphere CO₂ (eCO₂) and increased nitrogen deposition (iNDEP) are altering the biogeochemical interactions between plants, microbes and soils, which further modify plant leaf carbon‑nitrogen (C:N) stoichiometry and their carbon assimilation capability. Many field experiments have observed large sensitivity of leaf C:N ratio to eCO₂ and iNDEP. However, the large-scale pattern of this sensitivity is still unclear, because eCO₂ and iNDEP drive leaf C:N ratio toward opposite directions, which are further compounded by the complex processes of nitrogen acquisition and plant-and-microbial nitrogen competition. Here, we attempt to map the leaf C:N ratio spatial variation in the past 5 decades in China with a combination of data-driven model and process-based modeling. These two approaches showed consistent results. Over different regions, we found that leaf C:N ratio had significant but uneven changes between 2 time periods (1960-1989 and 1990-2015): a 5% ± 8% increase for temperate grasslands in northern China, a 3% ± 6% increase for boreal grasslands in western China, and by contrast, a 7% ± 6% decrease for temperate forests in southern China, and a 3% ± 5% decrease for boreal forests in northeastern China. Additionally, the structural equation models indicated that the leaf C:N change was sensitive to ΔNDEP, ΔCO₂ and ΔMAT rather than ΔMAP and ecosystem types. Process-based modeling suggested that iNDEP was the main source of soil mineral nitrogen change, dominating leaf C:N ratio change in most areas in China, while eCO₂ led to leaf C:N ratio increase in low iNDEP area. This study also indicates that the long-term leaf C:N ratio acclimation was dominated by climate constraint, especially temperature, but was constrained by soil N availability over decade scale.

Distinct Responses of Leaf Traits to Environment and Phylogeny Between Herbaceous and Woody Angiosperm Species in China

Leaf traits play key roles in plant resource acquisition and ecosystem processes; however, whether the effects of environment and phylogeny on leaf traits differ between herbaceous and woody species remains unclear. To address this, in this study, we collected data for five key leaf traits from 1,819 angiosperm species across 530 sites in China. The leaf traits included specific leaf area, leaf dry matter content, leaf area, leaf N concentration, and leaf P concentration, all of which are closely related to trade-offs between resource uptake and leaf construction. We quantified the relative contributions of environment variables and phylogeny to leaf trait variation for all species, as well as for herbaceous and woody species separately. We found that environmental factors explained most of the variation (44.4-65.5%) in leaf traits (compared with 3.9-23.3% for phylogeny). Climate variability and seasonality variables, in particular, mean temperature of the warmest and coldest seasons of a year (MTWM/MTWQ and MTCM/MTCQ) and mean precipitation in the wettest and driest seasons of a year (MPWM/MPWQ and MPDM/MPDQ), were more important drivers of leaf trait variation than mean annual temperature (MAT) and mean annual precipitation (MAP). Furthermore, the responses of leaf traits to environment variables and phylogeny differed between herbaceous and woody species. Our study demonstrated the different effects of environment variables and phylogeny on leaf traits among different plant growth forms, which is expected to advance the understanding of plant adaptive strategies and trait evolution under different environmental conditions.

Detecting the Turning Points of Grassland Autumn Phenology on the Qinghai-Tibetan Plateau: Spatial Heterogeneity and Controls

Autumn phenology, commonly represented by the end of season (EOS), is considered to be the most sensitive and crucial productivity indicator of alpine and cold grassland in the Qinghai-Tibetan Plateau. Previous studies typically assumed that the rates of EOS changes remain unchanged over long time periods. However, pixel-scale analysis indicates the existence of turning points and differing EOS change rates before and after these points. The spatial heterogeneity and controls of these turning points remain unclear. In this study, the EOS turning point changes are extracted and their controls are explored by integrating long time-series remote sensing images and piecewise regression methods. The results indicate that the EOS changed over time with a delay rate of 0.08 days/year during 1982–2015. The rates of change are not consistent over different time periods, which clearly highlights the existence of turning points. The results show that temperature contributed most strongly to the EOS changes, followed by precipitation and insolation. Furthermore, the turning points of climate, human activities (e.g., grazing, economic development), and their intersections are found to jointly control the EOS turning points. This study is the first quantitative investigation into the spatial heterogeneity and controls of the EOS turning points on the Qinghai-Tibetan Plateau, and provides important insight into the growth mechanism of alpine and cold grassland.

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.

Leaf economic strategies of a sclerophyllous plant (Eurya japonica): commonalities and particularities of trait correlation structures in low-moisture and low-phosphorus habitats

Sclerophylly proves an advantageous strategy in a variety of stressful environments. However, it is less clear how multiple phenotypic traits in sclerophyllous plants are integrated to accomplish proper functions under specific stressors. This study measured 10 leaf traits in a sclerophyllous species, Eurya japonica Thunb., in the Zhoushan Archipelago, eastern China, to examine how the structures of trait correlation (i.e. phenotypic integration) vary between two habitats with contrasting moisture and phosphorus (P) availability. Overall, the trait correlation matrices were similar between the two habitats under study (Mantel r > 0.5), reflecting a consistent trade-off between leaf outspreading (i.e. leaf area/mass ratio) and water-use efficiency (measured by δ13C). Stomatal conductance was correlated with leaf area, thickness and area/mass ratio only in the dry, P-rich habitat, whereas it was robustly correlated with leaf P per unit area in the wet, P-poor habitat. Moreover, leaf water-use efficiency was robustly correlated with leaf P and N per unit area in the dry habitat, but not so in the low-P one. These differences in trait correlation structures illustrate that the pathways of strategic compromise under contrasting stressors were locally specialised. This study highlights the importance of phenotypic integration as an emergent 'trait' in sustaining viable strategies.

Predictability of leaf traits with climate and elevation: a case study in Gongga Mountain, China

Leaf mass per area (Ma), nitrogen content per unit leaf area (Narea), maximum carboxylation capacity (Vcmax) and the ratio of leaf-internal to ambient CO2 partial pressure (χ) are important traits related to photosynthetic function, and they show systematic variation along climatic and elevational gradients. Separating the effects of air pressure and climate along elevational gradients is challenging due to the covariation of elevation, pressure and climate. However, recently developed models based on optimality theory offer an independent way to predict leaf traits and thus to separate the contributions of different controls. We apply optimality theory to predict variation in leaf traits across 18 sites in the Gongga Mountain region. We show that the models explain 59% of trait variability on average, without site- or region-specific calibration. Temperature, photosynthetically active radiation, vapor pressure deficit, soil moisture and growing season length are all necessary to explain the observed patterns. The direct effect of air pressure is shown to have a relatively minor impact. These findings contribute to a growing body of research indicating that leaf-level traits vary with the physical environment in predictable ways, suggesting a promising direction for the improvement of terrestrial ecosystem models.

Leaf Traits of Trees in Tropical Dry Evergreen Forests of Peninsular India

A plant functional trait study was conducted to know the existing relationship between important leaf traits namely, specific leaf area (SLA), leaf dry matter content (LDMC), and leaf life span (LL) in tropical dry evergreen forest (TDEFs) of Peninsular India. Widely accepted methodologies were employed to record functional traits. The relationships between SLA and LDMC, LDMC and LL, and SLA and LL were measured. Pearson’s coefficient of correlation showed a significant negative relationship between SLA and LDMC, and SLA and LL, whereas a significant positive relationship was prevailed between LDMC and LL. The mean trait values (SLA, LDMC, and LL) of evergreens varied significantly from deciduous species. SLA had a closer relationship with LDMC than LL. Similarly, LL had a closer relationship with SLA than LDMC. Species with evergreen leaf habits dominated forest sites under study. Evergreen species dominate the study area with a high evergreen-deciduous ratio of 5.34:1. The S strategy score of trees indicated a relatively higher biomass allocation to persistent tissues. TDEFs occur in low elevation, semiarid environment, but with the combination of oligotrophic habitat, high temperature and longer dry season these forests were flourishing as a unique evergreen ecosystem in the drier environment. The relationships found between leaf traits were in concurrence with earlier findings. Trees of TDEFs survive on the poor-nutrient habitat with a low SLA, high LDMC, and LL. This study adds baseline data on key leaf traits to plant functional trait database of India.

Leaf trait variation in species-rich tropical Andean forests

Screening species-rich communities for the variation in functional traits along environmental gradients may help understanding the abiotic drivers of plant performance in a mechanistic way. We investigated tree leaf trait variation along an elevation gradient (1000-3000 m) in highly diverse neotropical montane forests to test the hypothesis that elevational trait change reflects a trend toward more conservative resource use strategies at higher elevations, with interspecific trait variation decreasing and trait integration increasing due to environmental filtering. Analysis of trait variance partitioning across the 52 tree species revealed for most traits a dominant influence of phylogeny, except for SLA, leaf thickness and foliar Ca, where elevation was most influential. The community-level means of SLA, foliar N and Ca, and foliar N/P ratio decreased with elevation, while leaf thickness and toughness increased. The contribution of intraspecific variation was substantial at the community level in most traits, yet smaller than the interspecific component. Both within-species and between-species trait variation did not change systematically with elevation. High phylogenetic diversity, together with small-scale edaphic heterogeneity, cause large interspecific leaf trait variation in these hyper-diverse Andean forests. Trait network analysis revealed increasing leaf trait integration with elevation, suggesting stronger environmental filtering at colder and nutrient-poorer sites.

Mechanisms driving plant functional trait variation in a tropical forest

Plant functional trait variation in tropical forests results from taxonomic differences in phylogeny and associated genetic differences, as well as, phenotypic plastic responses to the environment. Accounting for the underlying mechanisms driving plant functional trait variation is important for understanding the potential rate of change of ecosystems since trait acclimation via phenotypic plasticity is very fast compared to shifts in community composition and genetic adaptation. We here applied a statistical technique to decompose the relative roles of phenotypic plasticity, genetic adaptation, and phylogenetic constraints. We examined typically obtained plant functional traits, such as wood density, plant height, specific leaf area, leaf area, leaf thickness, leaf dry mass content, leaf nitrogen content, and leaf phosphorus content. We assumed that genetic differences in plant functional traits between species and genotypes increase with environmental heterogeneity and geographic distance, whereas trait variation due to plastic acclimation to the local environment is independent of spatial distance between sampling sites. Results suggest that most of the observed trait variation could not be explained by the measured environmental variables, thus indicating a limited potential to predict individual plant traits from commonly assessed parameters. However, we found a difference in the response of plant functional traits, such that leaf traits varied in response to canopy-light regime and nutrient availability, whereas wood traits were related to topoedaphic factors and water availability. Our analysis furthermore revealed differences in the functional response of coexisting neotropical tree species, which suggests that endemic species with conservative ecological strategies might be especially prone to competitive exclusion under projected climate change.

Spatial variation and mechanisms of leaf water content in grassland plants at the biome scale: evidence from three comparative transects

Leaf water content (LWC) has important physiological and ecological significance for plant growth. However, it is still unclear how LWC varies over large spatial scale and with plant adaptation strategies. Here, we measured the LWC of 1365 grassland plants, along three comparative precipitation transects from meadow to desert on the Mongolia Plateau (MP), Loess Plateau, and Tibetan Plateau, respectively, to explore its spatial variation and the underlying mechanisms that determine this variation. The LWC data were normally distributed with an average value of 0.66 g g⁻¹. LWC was not significantly different among the three plateaus, but it differed significantly among different plant life forms. Spatially, LWC in the three plateaus all decreased and then increased from meadow to desert grassland along a precipitation gradient. Unexpectedly, climate and genetic evolution only explained a small proportion of the spatial variation of LWC in all plateaus, and LWC was only weakly correlated with precipitation in the water-limited MP. Overall, the lasso variation in LWC with precipitation in all plateaus represented an underlying trade-off between structural investment and water income in plants, for better survival in various environments. In brief, plants should invest less to thrive in a humid environment (meadow), increase more investment to keep a relatively stable LWC in a drying environment, and have high investment to hold higher LWC in a dry environment (desert). Combined, these results indicate that LWC should be an important variable in future studies of large-scale trait variations.

Response of Leaf Traits of Eastern Qinghai-Tibetan Broad-Leaved Woody Plants to Climatic Factors

Plant ecologists have long been interested in quantifying how leaf traits vary with climate factors, but there is a paucity of knowledge on these relationships given a large number of the relevant leaf traits and climate factors to be considered. We examined the responses of 11 leaf traits (including leaf morphology, stomatal structure and chemical properties) to eight common climate factors for 340 eastern Qinghai-Tibetan woody species. We showed temperature as the strongest predictor of leaf size and shape, stomatal size and form, and leaf nitrogen and phosphorus concentrations, implying the important role of local heat quantity in determining the variation in the cell- or organ-level leaf morphology and leaf biochemical properties. The effects of moisture-related climate factors (including precipitation and humidity) on leaf growth were mainly through variability in leaf traits (e.g., specific leaf area and stomatal density) related to plant water-use physiological processes. In contrast, sunshine hours affected mainly cell- and organ-level leaf size and shape, with plants developing small/narrow leaves and stomata to decrease leaf damage and water loss under prolonged solar radiation. Moreover, two sets of significant leaf trait-climate relationships, i.e., the leaf/stomata size traits co-varying with temperature, and the water use-related leaf traits co-varying with precipitation, were obtained when analyzing multi-trait relationships, suggesting these traits as good indicators of climate gradients. Our findings contributed evidence to enhance understanding of the regional patterns in leaf trait variation and its environmental determinants.

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.

Will the climate of plant origins influence the chemical profiles of cuticular waxes on leaves of Leymus chinensis in a common garden experiment?

Cuticular wax covering the leaf surface plays important roles in protecting plants from biotic and abiotic stresses. Understanding the way in which plant leaf cuticles reflect their growing environment could give an insight into plant resilience to future climate change. Here, we analyzed the variations of cuticular waxes among 59 populations of Leymus chinensis in a common garden experiment, aiming to verify how environmental conditions influence the chemical profiles of cuticular waxes. In total, eight cuticular wax classes were identified, including fatty acids, aldehydes, primary alcohols, alkanes, secondary alcohols, ketones, β-diketones, and alkylresorcinols, with β-diketones the predominant compounds in all populations (averaged 67.36% across all populations). Great intraspecific trait variations (ITV) were observed for total wax coverage, wax compositions, and the relative abundance of homologues within each wax class. Cluster analysis based on wax characteristics could separate 59 populations into different clades. However, the populations could not be separated according to their original longitudes, latitudes, annual temperature, or annual precipitation. Redundancy analysis showed that latitude, arid index, and the precipitation from June to August were the most important parameters contributing to the variations of the amount of total wax coverage and wax composition and the relative abundance of wax classes. Pearson's correlation analysis further indicated that the relative abundance of wax classes, homologues in each wax class, and even isomers of certain compound differed in their responses to environmental factors. These results suggested that wax deposition patterns of L. chinensis populations formed during adaptations to their long-term growing environments could inherit in their progenies and exhibit such inheritance even these progenies were exported to new environments.

Climate, Life Form and Family Jointly Control Variation of Leaf Traits

Variation in leaf traits may represent differences in physiological processes and environmental adaptative strategies. Using multivariate analyses, we investigated 13 leaf traits to quantify the trade-off in these traits and the trait-climate/biome relationships based on the China Plant Trait Database, which contains morphometric and physiological character information on 1215 species for 122 sites, ranging from the north to the tropics, and from deserts and grasslands to woodlands and forests. Leaf traits across the dataset of Chinese plants showed different spatial patterns along longitudinal and latitudinal gradients and high variation. There were significant positive or negative correlations among traits; however, with the exception of the leaf 13C:12C stable isotope ratio, there were no significant correlations between leaf area and other traits. Climate, life form, and family jointly accounted for 68.4% to 95.7% of trait variance. Amongst these forms of variation partitioning, the most important partitioning feature was the family independence of climate and life form (35.6% to 57.2%), while the joint effect of family and climate was 4.5% to 26.2%, and the joint effect of family and life form was 2.4% to 21.6%. The findings of this study will enhance our understanding of the variation in leaf traits in Chinese flora and the environmental adaptative strategies of plants against a background of global climate change, and also may enrich and improve the leaf economics spectrum of China.

Trait-Based Climate Change Predictions of Vegetation Sensitivity and Distribution in China

Dynamic global vegetation models (DGVMs) suffer insufficiencies in tracking biochemical cycles and ecosystem fluxes. One important reason for these insufficiencies is that DGVMs use fixed parameters (mostly traits) to distinguish attributes and functions of plant functional types (PFTs); however, these traits vary under different climatic conditions. Therefore, it is urgent to quantify trait covariations, including those among specific leaf area (SLA), area-based leaf nitrogen (N _area), and leaf area index (LAI) (in 580 species across 218 sites in this study), and explore new classification methods that can be applied to model vegetation dynamics under future climate change scenarios. We use a redundancy analysis (RDA) to derive trait-climate relationships and employ a Gaussian mixture model (GMM) to project vegetation distributions under different climate scenarios. The results show that (1) the three climatic variables, mean annual temperature (MAT), mean annual precipitation (MAP), and monthly photosynthetically active radiation (mPAR) could capture 65% of the covariations of three functional traits; (2) tropical, subtropical and temperate forest complexes expand while boreal forest, temperate steppe, temperate scrub and tundra shrink under future climate change scenarios; and (3) the GMM classification based on trait covariations should be a powerful candidate for building new generation of DGVM, especially predicting the response of vegetation to future climate changes. This study provides a promising route toward developing reliable, robust and realistic vegetation models and can address a series of limitations in current models.