A survey of leaf phosphorus fractions and leaf economic traits among 12 co-occurring woody species on phosphorus-impoverished soils

Large variations are found in leaf morphology and physiology across species in nature, reflecting diversity in carbon fixation and growth strategies. These variations in leaf traits are not random; rather, they are tightly coordinated with each other. Leaf traits can be expressed per leaf dry mass or per leaf area. A leaf-mass basis reflects leaf economics, i.e., revenues and expenditures per unit investment of biomass, while a leaf-area basis reflects fluxes in relation to surfaces. Leaf N and P concentrations, and photosynthetic and respiration rates – all considered on a mass basis, are negatively correlated with leaf mass per area (LMA) whilst leaf lifespan is positively correlated with LMA. These correlations are summarized into a single major axis called the “leaf economics spectrum” that runs from “quick-return” to “slow-return” species. On the other hand, correlations among area-based traits are less consistent and less understood in relation to leaf economy. LMA was positively correlated with leaf N content but mostly independent from photosynthetic rates per unit leaf area. Given that N is an essential element in photosynthetic proteins and thus photosynthesis, clarifying the mechanisms why the efficiency of photosynthesis (photosynthesis per unit N) decreases with LMA is a major concern in understanding the correlations among area-based traits in relation to leaf economy. Currently available data suggest that greater amounts of cell wall are required for long-lived leaves, which reduces the efficiency of photosynthesis by lowering (1) the fraction of leaf N invested in photosynthetic proteins and (2) CO2 diffusion rates through thicker and denser mesophyll cell walls. These physiological and structural constraints are a fundamental mechanism underpinning the general correlations among leaf economic traits.

Introduction to a <i>Virtual Special Issue</i> on plant ecological strategy axes in leaf and wood traits

Understanding the relationships between species' demography and functional traits is crucial for gaining a mechanistic understanding of community dynamics. While leaf morphology represents a key functional dimension for plants worldwide (i.e., the leaf economics spectrum), its ability to explain variation in trees' life history strategies remains limited. Plant growth is influenced by both leaf morphology and allocation; hence, incorporating both dimensions is essential but rarely done. Additionally, trait–performance relationships have mainly been studied in tropical communities, leaving gaps in our understanding of temperate forests where different seasonality patterns may alter these relationships. We examined whether species' leaf area index (leaf area per crown size, LAI), a measure of leaf allocation, explains the variation of juvenile tree species' potential growth rates in a winter‐deciduous broadleaf forest. LAI has not been characterized as a species‐level trait, but its ability to predict plant productivity at the ecosystem scale highlights its potential for explaining plant growth. We evaluated species' maximum LAI both individually and in conjunction with wood density (WD) and leaf mass per area (LMA). We expected that models would improve when both leaf morphology (LMA) and leaf allocation (LAI) were included and that species with denser crowns would have higher potential growth rates. LAI and LMA were significant predictors of growth but only when both were incorporated, and together explained a high proportion of species' growth variations (R2adj = 0.59). We found evidence of a trade‐off between LAI and LMA, with a negative relationship between them and each having a positive influence on species' growth, suggesting that there are multiple allocation strategies to achieve fast growth. A surprisingly positive LMA–growth relationship contrasts with observations from tropical forests. We did not find significant relationships with WD in this forest. Our results highlight that incorporating leaf allocation improves models of trait–performance relationships. They also suggest, in agreement with the limited literature, that temperate forests may exhibit different trait–performance relationships from those of tropical forests, where LMA is negatively related to growth and WD is often important. Clarifying the details and contexts of trait–performance relationships is crucial for applying the functional trait framework to understanding community structure and dynamics of forests globally.

&amp;lt;p&amp;gt;Leaf construction can be costly to plants with a short leaf lifespan (LLS), with a necessity to pay back the investment in leaf deployment. Costs of leaf construction are often measured as leaf mass per area (LMA) and the deciduousness strategies (deciduous, semideciduous or evergreen) used as proxy to LLS (evergreen species having longest leaf duration compared to semideciduous and deciduous species). According to the leaf economic spectrum theory, a positive correlation between LMA and LLS is expected, with evergreen species having higher LMA than deciduous species. Nonetheless, aridity constraints increase leaf maintenance costs in plants, and the deciduous strategy turns to be the most common leaf exchange behavior in Seasonally Dry Tropical Forests (SDTF). In this study we are testing if the relation of LMA and LLS is influenced by aridity in SDTF, using the length of growing season (LOS) as a proxy of overall response for drought. We expect that LMA: LLS relationship will become stronger towards driest sites. The caatinga vegetation is the largest SDTF in the New World, covering an area of ca. 850,000 km&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; located in North-eastern Brazil. Although the region is characterized by having low amount of rainfall (&amp;lt;1100 mm per year), there is a gradient of aridity that affects plants living across these areas. We applied the near-surface remote method trough the usage of phenocams to simultaneously monitor leaf phenology of 27 tree species from four areas of Caatinga, in a gradient of aridity ranging from 387 mm to 800 mm total annual rainfall. For these species, we used the green chromatic coordinate (Gcc) time series to calculate the phenological transition dates of Start (SOS) and End (EOS) and the Length (LOS) of Growing Season, during two to four growing seasons, from 2017 to 2021. LOS presented high variability among species, ranging from 143 days for &amp;lt;em&amp;gt;Manihot pseudoglaziovii&amp;lt;/em&amp;gt; and 314 days for &amp;lt;em&amp;gt;Aspidosperma pyrifolium&amp;lt;/em&amp;gt;. In general, LOS tend to be shorter for species towards driest sites and analyes of the relation between LMA and LLS are suggesting trade-offs important to understand the acquisitive strategies of plants from semi-arid vegetation with implications for carbon fluxes.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Supported by FAPESP (#2019/11835-2); FAPESP-NERC (FAPESP #2015/50488-5; #2017/17380-1), by CNPq and FACEPE (Caatinga-FLUX, #483223/2011-5 and Caatinga-FLUX Fase 2, #0062-1.07/15); UNESP CAPES-PrInt Program (grant #88887.310463/2018-00; schoolarship ##88887.512218/2020-00) and CNPq productitivity fellowship (#428055/2018-4).&amp;lt;/p&amp;gt;

SummaryThe leaf economics spectrum (LES) has been an organizing framework of plant functional ecology for the past decade. TheLESdescribes a set of trade‐offs among traits related to plant carbon balance. Species with a long leaf life span (LLS) invest additional material for leaf protection and structural support and consequently tend to have a lower leaf photosynthetic rate per unit mass than species with a shorterLLS.While theLESis most apparent in comparing species with extreme differences in their traits, it has nonetheless been adopted as a general explanation of leaf trait variation at all scales and in all plants. It highlights the ‘trait‐based’ approach to plant ecology, which has generally used a small set of traits to predict whole organism and even whole ecosystem attributes. Few studies have investigated the relationships betweenLEStraits and organismal attributes not directly related to carbon economy.We explored theLESin 32 deciduous woody species ofViburnum(Adoxaceae). We found no evidence for any mass‐basedLEStrade‐offs. Rather, on an area basis, photosynthetic rates were positively correlated with leaf mass per area (LMA); higherLMAwas associated with greater investment in photosynthetic tissue, with most of the variation due to changes in the thickness of photosynthetic mesophyll.Species’ meanLLSvaried between 19 and 26 weeks and was not correlated with otherLEStraits. Instead,LLSwas strongly associated with the diverse set of whole‐plant branching patterns inViburnum. In the most common growth pattern,LLSwas significantly correlated with flowering time, because branches end in terminal inflorescences, and all leaves and inflorescences are pre‐formed in overwintering buds.Synthesis. Plants may recover the cost of their leaves early in the growing season, allowingLLSto vary independently of the plant carbon budget. In deciduous species,LLSmay be strongly influenced by whole plant architecture, which, inViburnum, is evolutionarily conserved. In general, positive area‐basedLEStrait relationships will limit the relevance ofLLSto this spectrum and allowLLSto vary for reasons that are not directly related to carbon economy.

The duckweed family (Lemnaceae) is a group of free‐floating aquatic plants with bodies consisting of single floating fronds that multiply clonally. Although they are known to have the fastest relative growth rate (RGR) among higher plants, their functional trait coordination in relation to within‐family variation of RGR is poorly understood. We tested how duckweed species fit within the trait covariation patterns known as the world‐wide leaf economics spectrum (LES). To this end, several functional traits were evaluated for 15 duckweed species, and their covariation patterns were compared with those in the global database of plant functional traits. As a group, duckweeds exhibited the most acquisitive suite of traits, with extremely small leaf mass per area (LMA), short life span and high mass‐based photosynthetic rate (Amass). These LES traits showed a tight correlation with RGR, corroborating our hypothesis that acquisitive leaf resource economics underpins their extremely high RGR. However, unlike other higher plants, LMA showed weak association with leaf life span and Amass within duckweed family. We also found a unique positive correlation between duckweed LMA and area‐based photosynthetic rates, an indication that their LMA represents different functional significance compared to typical higher plants. Synthesis. Duckweeds, the world's fastest growing plants, mostly follow the world‐wide LES and locate at its extreme end. The slight deviation from the LES highlights that duckweeds experience some physical and chemical constraints not faced by other higher plants.

The leaf economic spectrum (LES) describes a set of universal trade-offs between leaf mass per area (LMA), leaf nitrogen (N), leaf phosphorus (P) and leaf photosynthesis that influence patterns of primary productivity and nutrient cycling. Many questions regarding vegetation-climate feedbacks can be addressed with a better understanding of LES traits and their controls. Remote sensing offers enormous potential for generating large-scale LES trait data. Yet so far, canopy studies have been limited to imaging spectrometers onboard aircraft, which are rare, expensive to deploy and lack fine-scale resolution. In this study, we measured VNIR (visible-near infrared (400–1050 nm)) reflectance of individual sun and shade leaves in 7 one-ha tropical forest plots located along a 1200–2000 mm precipitation gradient in West Africa. We collected hyperspectral imaging data from 3 of the 7 plots, using an octocopter-based unmanned aerial vehicle (UAV), mounted with a hyperspectral mapping system (450–950 nm, 9 nm FWHM). Using partial least squares regression (PLSR), we found that the spectra of individual sun leaves demonstrated significant (p &lt; 0.01) correlations with LMA and leaf chemical traits: r2 = 0.42 (LMA), r2 = 0.43 (N), r2 = 0.21 (P), r2 = 0.20 (leaf potassium (K)), r2 = 0.23 (leaf calcium (Ca)) and r2 = 0.14 (leaf magnesium (Mg)). Shade leaf spectra displayed stronger relationships with all leaf traits. At the airborne level, four of the six leaf traits demonstrated weak (p &lt; 0.10) correlations with the UAV-collected spectra of 58 tree crowns: r2 = 0.25 (LMA), r2 = 0.22 (N), r2 = 0.22 (P), and r2 = 0.25 (Ca). From the airborne imaging data, we used LMA, N and P values to map the LES across the three plots, revealing precipitation and substrate as co-dominant drivers of trait distributions and relationships. Positive N-P correlations and LMA-P anticorrelations followed typical LES theory, but we found no classic trade-offs between LMA and N. Overall, this study demonstrates the application of UAVs to generating LES information and advancing the study and monitoring tropical forest functional diversity.

Summary 1. In this paper we determine whether interspecific variation in entire photosynthetic light–response curves correlates with the leaf traits of the ‘leaf economics spectrum’ (LES) and the degree to which such traits can predict interspecific variation in light–response curves. This question is important because light–response curves are included in many ecosystem models of plant productivity and gas exchange but such models do not take into account interspecific variation in such response curves. 2. We answer this question using original observations from 260 leaves from 130 plants of 65 different species of herbaceous (25) and woody (40) angiosperms. Herbs were grown in growth chambers and gas exchange measurements were taken in the laboratory. Leaf traits and gas exchange measurements for the woody plants were taken in the field. Leaf traits measured were leaf mass per area (LMA), leaf nitrogen concentration (N) and leaf chlorophyll concentration (Chl). We fitted the Mitscherlich and Michaelis–Menten equations of the light–response curve separately for each leaf. This gave (for the Mitscherlich equation) the light compensation point (ϕ), the quantum yield at the light compensation point (q(ϕ)), and maximum net photosynthesis (Amax) and (for the Michaelis–Menten equation), the maximum gross photosynthesis (Gmax), the half saturation coefficient (k) and the dark respiration rate (Rd). 3. Amax and q(ϕ) were highly correlated with the measured leaf traits but ϕ was not. All three parameters of the Michaelis–Menten equations were correlated with the leaf traits. Allometric equations predicting the parameters of the Mitscherlich and Michaelis–Menten equations by N and LMA are presented. Replacing the leaf‐specific parameters by these general allometric equations based on leaf N and LMA gave good predictions of net photosynthetic rates over the entire range of irradiance (r = 0·79–0·98) but with a downward bias for the herbs when the most general allometric equations are used. 4. These results further extend the generality of the LES and may allow available information from large leaf trait data bases to be incorporated into ecosystem models of plant growth and gas exchange.

The leaf economics spectrum (LES) describes multivariate correlations that constrain leaf traits of plant species primarily to a single axis of variation if data are normalized by leaf mass. We show that these traits are approximately distributed proportional to leaf area instead of mass, as expected for a light- and carbon dioxide-collecting organ. Much of the structure in the mass-normalized LES results from normalizing area-proportional traits by mass. Mass normalization induces strong correlations among area-proportional traits because of large variation among species in leaf mass per area (LMA). The high LMA variance likely reflects its functional relationship with leaf life span. A LES that is independent of mass- or area-normalization and LMA reveals physiological relationships that are inconsistent with those in global vegetation models designed to address climate change.

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 (Amass), leaf nitrogen concentration (Nmass), and leaf phosphorus concentration (Pmass). 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); Amass–SLA relationships (from 0.83 to 1.97); Amass–Nmass relationships (from 1.33 to 2.25); Nmass–Pmass 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.

Leaf economics spectrum (LES), characterizing covariation among a suite of leaf traits relevant to carbon and nutrient economics, has been examined largely among species but hardly within species. In addition, very little attempt has been made to examine whether the existence of LES depends on spatial scales. To address these questions, we quantified the variation and covariation of four leaf economic traits (specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus contents) in a cosmopolitan wetland species (Phragmites australis) at three spatial (inter-regional, regional, and site) scales across most of the species range in China. The species expressed large intraspecific variation in the leaf economic traits at all of the three spatial scales. It also showed strong covariation among the four leaf economic traits across the species range. The coordination among leaf economic traits resulted in LES at all three scales and the environmental variables determining variation in leaf economic traits were different among the spatial scales. Our results provide novel evidence for within-species LES at multiple spatial scales, indicating that resource trade-off could also constrain intraspecific trait variation mainly driven by climatic and/or edaphic differences.

Many studies have reported intraspecific variations in leaf functional traits, but their contribution to plant performance and ecosystem function are poorly understood. We studied altitudinal gradients of intraspecific variations in leaf traits, productivity and resource use efficiency in the dominant species of subalpine evergreen coniferous and deciduous broad‐leaved forests in Japan. We addressed three hypotheses, which are exclusive to each other. (1) Leaf traits vary along the leaf economics spectrum (LES). Plants that grow at lower and higher altitudes have fast‐ and slow‐return strategies, respectively, which improve productivity or resource use efficiency in the respective habitat. (2) Leaf trait variations are not consistent with the LES, but they contribute to improving productivity or resource use efficiency in the respective habitat. (3) Leaf trait variations do not contribute to improving productivity or resource use efficiency at higher altitudes. On the studied mountain range, Fagus crenata, a deciduous broad‐leaved tree, and Abies mariesii, an evergreen conifer, are the dominant species at lower and higher altitudes respectively. In F. crenata, leaf mass per area (LMA) and nitrogen concentrations were higher at higher altitudes. The net assimilation rate and light use efficiency during the growing season were greater at higher altitudes, which compensated for the shorter growing season in terms of annual productivity. In A. mariesii, the LMA was lower and the leaf life span was unchanged at higher altitudes. Productivity and resource use efficiency decreased with altitude. Synthesis. We conclude that F. crenata improves its productivity and resource use efficiency at higher altitudes by altering its leaf functional traits (Hypothesis 2), whereas alterations to leaf traits in A. mariesii are not associated with any improvement at higher altitudes (Hypothesis 3), which may result from the negative impact of environmental stress. Hence, the ecological significance of altitudinal variations in leaf traits depends on species and environment.

Intraspecific trait variation (ITV) is an important dimension of plant ecological diversity, particularly in agroecosystems, where phenotypic ITV (within crop genotypes) is an important correlate of key agroecosystem processes including yield. There are few studies that have evaluated whether plants of the same genotype vary along well-defined axes of biological variation, such as the leaf economics spectrum (LES). There is even less information disentangling environmental and ontogenetic determinants of crop ITV along an intraspecific LES, and whether or not a plant's position along an intraspecific LES is correlated with reproductive output. We sought to capture the extent of phenotypic ITV within a single cultivar of soy (Glycine max) - the world's most commonly cultivated legume - using a data set of nine leaf traits measured on 402 leaves, sampled from 134 plants in both agroforestry and monoculture management systems, across three distinct whole-plant ontogenetic stages (while holding leaf age and canopy position stable). Leaf traits covaried strongly along an intraspecific LES, in patterns that were largely statistically indistinguishable from the 'universal LES' observed across non-domesticated plants. Whole-plant ontogenetic stage explained the highest proportion of phenotypic ITV in LES traits, with plants progressively expressing more 'resource-conservative' LES syndromes throughout development. Within ontogenetic stages, leaf traits differed systematically across management systems, with plants growing in monoculture expressing more 'resource-conservative' trait syndromes: trends largely owing to an approximately ≥50% increases in leaf mass per area (LMA) in high-light monoculture vs. shaded agroforestry systems. Certain traits, particularly LMA, leaf area and maximum photosynthetic rates, correlated closely with plant-level reproductive output. Phenotypic ITV in soy is governed by constraints in trait trade-offs along an intraspecific LES, which in turn (1) underpins plant responses to managed environmental gradients, and (2) reflects shifts in plant functional biology and resource allocation that occur throughout whole-plant ontogeny.

Ecologists are increasingly using plant functional traits to predict community assembly, but few studies have linked functional traits to species' responses to fine-scale resource gradients. In this study, it was tested whether saplings of woody species partition fine-scale gradients in light availability based on their leaf mass per area (LMA) in three temperate rain forests and one Mediterranean forest in southern Chile. LMA was measured under field conditions of all woody species contained in approx. 60 plots of 2 m2 in each site, and light availability, computed as the gap light index (GLI), was determined. For each site, species' pairwise differences in mean LMA (Δ LMA) and abundance-weighted mean GLI (Δ light response) of 2 m2 plots were calculated and it was tested whether they were positively related using Mantel tests, i.e. if species with different LMA values differed in their response to light availability. Additionally linear models were fitted to the relationship between plot-level mean LMA and GLI across plots for each site. A positive and significant relationship was found between species' pairwise differences in mean LMA and differences in light response across species for all temperate rain forests, but not for the Mediterranean forest. The results also indicated a significant positive interspecific link between LMA and light availability for all forests. This is in contrast to what is traditionally reported and to expectations from the leaf economics spectrum. In environments subjected to light limitation, interspecific differences in a leaf trait (LMA) can explain the fine-scale partitioning of light availability gradients by woody plant species. This niche partitioning potentially facilitates species coexistence at the within-community level. The high frequency of evergreen shade-intolerant species in these forests may explain the positive correlation between light availability and LMA.

Leaf mass per area (LMA) is a widely used functional trait in both neobotanical and paleobotanical research that provides a window into how plants interact with their environment. Paleobotanists have used site-level measures of LMA as a proxy for climate, biome, deciduousness, and community-scale plant strategy, yet many of these relationships have not been grounded in modern data. In this study, we evaluated LMA from the paleobotanical perspective, seeking to add modern context to paleobotanical interpretations and discover what a combined modern and fossil data set can tell us about how LMA can be best applied toward interpreting plant communities. We built a modern data set by pulling plant trait data from the TRY database, and a fossil data set by compiling data from studies that have used the petiole-width proxy for LMA. We then investigated the relationships of species-mean, site-mean, and site-distribution LMA with different climatic, phylogenetic, and physiognomic variables. We found that LMA distributions are correlated with climate, site taxonomic composition, and deciduousness. However, the relative contributions of these factors are not distinctive, and ultimately, LMA distributions cannot accurately reconstruct the biome or climate of an individual site. The correlations that make up the leaf economics spectrum are stronger than the correlations between LMA and climate, phylogeny, morphospace, or depositional environment. Fossil LMA should be understood as the culmination of the influences of these variables rather than as a predictor.