Leaf economics fundamentals explained by optimality principles

Contrasting leaf structural, photosynthetic and allocation responses to elevated [CO2] in different-aged leaves of tropical fruit trees Persea americana and Annona muricata

Responses of leaf photosynthetic traits to elevated growth [CO2] vary among species, but there is limited understanding of underlying trait trade-offs, especially for tropical species with continuous leaf formation. Persea americana and Annona muricata with significant investments in defense structures (idioblasts) were used to study the impacts of growth [CO2] (400 vs 800 μmol mol-1) on leaf structural, chemical, and photosynthetic characteristics at different leaf developmental stages. Growth at elevated [CO2] increased whole plant leaf area (ST) and whole plant average leaf dry mass per unit area (MAv) in P. americana, whereas both ST and MAv were reduced in A. muricata. Elevated [CO2] moderately reduced foliage N and P contents per dry mass in P. americana but increased in A. muricata. In P. americana, elevated [CO2] increased anthocyanin content in young leaves and decreased in mature leaves, and increased the share of idioblast tissue fraction (fI) with moderate downregulation of photosynthesis (A). In A. muricata, elevated [CO2] reduced anthocyanin content in young leaves and fI was unaffected, whereas a major downregulation in A was observed. In this species, photosynthetic downregulation was not associated with nutrient starvation, but occurred due to direct inhibition of stomatal conductance by elevated [CO2], ultimately limiting leaf development and growth and curbing Vcmax and Jmax in mature leaves. These results demonstrate a limited impact of primary/secondary metabolism trade-off on photosynthetic response to growth [CO2], underscore major species differences in response to elevated [CO2] and emphasize the impact of leaf age in determining whole plant growth response.

Adaptation in Wood Anatomical Traits to Temperature and Precipitation-A Common Garden Study

Indisputably, temperature and precipitation are key environmental variables driving plant trait variation and shaping plant ecological strategies. However, it is challenging to ascertain their relative influences because site temperature and precipitation are often correlated. Here, using Eucalyptus as a model system representing woody evergreen species more broadly, we sought to disentangle their influence on wood anatomical traits underpinning plant hydraulics. From a common garden we sampled 29 pairs of closely-related Eucalyptus species, each species-pair representing either a contrast in site temperature or precipitation, but never both. Very clearly, and both in phylogenetic and non-phylogenetic analyses, species from lower-rainfall and from colder regions had thicker vessel walls, likely an adaptation to drought and freezing, enabling water transport at more negative water potentials with reduced risk of cavitation or vessel implosion. On average, species from warmer regions had smaller vessels, but theoretical hydraulic conductivity remained stable across site temperatures due to increased vessel density compensating for reduced diameters. These trends being observed for adult plants grown under common conditions suggests that key hydraulic anatomy traits are "hard-wired", and gene × environment interactions are relatively weak. This is a key insight for understanding the trait-basis of plant ecological strategies related to site climate.

Increasing leaf sizes of the vine Epipremnum aureum (Araceae): photosynthesis and respiration

The canopy leaves of allomorphic aroid vines can exceed 2,000 cm2, up to 30 times larger than respective understorey leaves. In the literature, this allomorphic increase in leaf area of aroid vines was hypothesized to improve its light foraging capacity. The viability of these large leaves depends on carbon acquisition obtained from their larger area and on the respective costs of production, maintenance and support. To evaluate and understand how leaf enlargement affects performance, we analyzed the photosynthesis and respiration of Epipremnum aureum leaves of different sizes via photosynthetic response light curves, morpho-physiology and anatomical parameters. Leaf size was increased by varying growth direction (horizontal vs. vertical) and light conditions (low vs. high). Vertical plants in high light produced leaves 9-13 times larger than those under other conditions. Saturated photosynthetic rates per area were similar across leaves of E. aureum, regardless of size, but respiration rates increased while specific leaf area decreased in larger leaves. This may suggests that larger leaves do not offset their costs per unit area in the short term, despite field observations of continuous enlargement with increased plant size. However, the high light levels able to saturate photosynthesis under field conditions are achieved only by larger leaves of E. aureum positioned at canopies (PPFD around 1,000 µmol m-2 s-1), not occurring at understory where smaller leaves are positioned (PPFD around 100 µmol m-2 s-1). This is confirmed by the higher values of the relative growth rate (RGR) and net assimilation rate (NAR) parameters exhibited by the vertical plants in high light. The saturated photosynthetic rates found here under experimental conditions for the smaller leaves of E. aureum could be related to their high invasive capacities as alien species around the world. We propose that the costs of larger aroid leaves might be outweighed by a strategy that optimizes size, morphophysiology, anatomy, photosynthesis and, lifespan to maximize lifetime carbon gain in tropical forests.

A Global Synthesis of How Plants Respond to Climate Warming From Traits to Fitness

Despite intensive research, our understanding of how plants respond to warming by coordinating their full arsenal of traits to adjust fitness is lacking. To fill this gap, we applied a trait-based framework with three clusters (two functional clusters: "carbon-fixation rate" and "carbon-fixation area"; a third cluster: "total carbon fixation") to a global dataset compiled from 572 studies of warming experiments with 677 species and a comprehensive list of traits and fitness components. The pairwise correlation analysis complemented with SEM and PCA showed that plants increased biomass (the core variable in the third cluster) under warming by coordinating satellite traits in two functional clusters to adjust their core traits, net photosynthesis rate and total leaf area, respectively. In particular, the trait coordination was characterised by the maintenance of net photosynthesis rate and the increase of total leaf area, which was robust across ecological contexts although warming responses of the variables per se displayed context-dependences. Moreover, the trade-offs between biomass and reproduction (itself bearing mass vs. number trade-offs) in their warming responses scaled the coordination to enhance fitness except in the contexts where reproduction was reduced. These findings could help explain and predict plant form and function in a warming world.

Plant traits shape global spatiotemporal variations in photosynthetic efficiency

Photosynthetic efficiency (PE) quantifies the fraction of absorbed light used in photochemistry to produce chemical energy during photosynthesis and is essential for understanding ecosystem productivity and the global carbon cycle, particularly under conditions of vegetation stress. However, nearly 60% of the global spatiotemporal variance in terrestrial PE remains unexplained. Here we integrate remote sensing and eco-evolutionary optimality theory to derive key plant traits, alongside explainable machine learning and global eddy covariance observations, to uncover the drivers of daily PE variations. Incorporating plant traits into our model increases the explained daily PE variance from 36% to 80% for C3 vegetation and from 54% to 84% for C4 vegetation compared with using climate data alone. Key plant traits-including chlorophyll content, leaf longevity and leaf mass per area-consistently emerge as important factors across global biomes and temporal scales. Water availability and light conditions are also critical in regulating PE, underscoring the need for an integrative approach that combines plant traits with climatic factors. Overall, our findings demonstrate the potential of remote sensing and eco-evolutionary optimality theory to capture principal PE drivers, offering valuable tools for more accurately predicting ecosystem productivity and improving Earth system models under climate change.

Empirical evidence and theoretical understanding of ecosystem carbon and nitrogen cycle interactions

Interactions between carbon (C) and nitrogen (N) cycles in terrestrial ecosystems are simulated in advanced vegetation models, yet methodologies vary widely, leading to divergent simulations of past land C balance trends. This underscores the need to reassess our understanding of ecosystem processes, given recent theoretical advancements and empirical data. We review current knowledge, emphasising evidence from experiments and trait data compilations for vegetation responses to CO2 and N input, alongside theoretical and ecological principles for modelling. N fertilisation increases leaf N content but inconsistently enhances leaf-level photosynthetic capacity. Whole-plant responses include increased leaf area and biomass, with reduced root allocation and increased aboveground biomass. Elevated atmospheric CO2 also boosts leaf area and biomass but intensifies belowground allocation, depleting soil N and likely reducing N losses. Global leaf traits data confirm these findings, indicating that soil N availability influences leaf N content more than photosynthetic capacity. A demonstration model based on the functional balance hypothesis accurately predicts responses to N and CO2 fertilisation on tissue allocation, growth and biomass, offering a path to reduce uncertainty in global C cycle projections.

Optimising height-growth predicts trait responses to water availability and other environmental drivers

Future changes in climate, together with rising atmosphericCO 2 , may reorganise the functional composition of ecosystems. Without long-term historical data, predicting how traits will respond to environmental conditions-in particular, water availability-remains a challenge. While eco-evolutionary optimality theory (EEO) can provide insight into how plants adapt to their environment, EEO approaches to date have been formulated on the assumption that plants maximise carbon gain, which omits the important role of tissue construction and size in determining growth rates and fitness. Here, we show how an expanded optimisation framework, focussed on individual growth rate, enables us to explain shifts in four key traits: leaf mass per area, sapwood area to leaf area ratio (Huber value), wood density and sapwood-specific conductivity in response to soil moisture, atmospheric aridity,CO 2 and light availability. In particular, we predict that as conditions become increasingly dry, height-growth optimising traits shift from resource-acquisitive strategies to resource-conservative strategies, consistent with empirical responses across current environmental gradients of rainfall. These findings can explain both the shift in traits and turnover of species along existing environmental gradients and changing future conditions and highlight the importance of both carbon assimilation and tissue construction in shaping the functional composition of vegetation across climates.

Contrasting regulation of leaf gas exchange of semi-arid tree species under repeated drought

Predicting how plants respond to drought requires an understanding of how physiological mechanisms and drought response strategies occur, as these strategies underlie rates of gas exchange and productivity. We assessed the response of 11 plant traits to repeated experimental droughts in four co-occurring species of central Australia. The main goals of this study were to: (i) compare the response to drought between species; (ii) evaluate whether plants acclimated to repeated drought; and (iii) examine the degree of recovery in leaf gas exchange after cessation of drought. Our four species of study were two tree species and two shrub species, which field studies have shown to occupy different ecohydrological niches. The two tree species (Eucalyptus camaldulensis Dehnh. and Corymbia opaca (D.J.Carr & S.G.M.Carr) K.D.Hill & L.A.S.Johnson) had large reductions in stomatal conductance (gs) values, declining by 90% in the second drought. By contrast, the shrub species (Acacia aptaneura Maslin & J.E.Reid and Hakea macrocarpa A.Cunn. ex R.Br.) had smaller reductions gs in the second drought of 52 and 65%, respectively. Only A. aptaneura showed a physiological acclimatation to drought due to small declines in gs versus ᴪpd (0.08 slope) during repeated droughts, meaning they maintained higher rates of gs compared with plants that only experienced one final drought (0.19 slope). All species in all treatments rapidly recovered leaf gas exchange and leaf mass per area following drought, displaying physiological plasticity to drought exposure. This research refines our understanding of plant physiological responses to recurrent water stress, which has implications for modelling of vegetation, carbon assimilation and water use in semi-arid environments under drought.

The leaf-scale mass-based photosynthetic optimization model better predicts photosynthetic acclimation than the area-based

Leaf-scale photosynthetic optimization models can quantitatively predict photosynthetic acclimation and have become an important means of improving vegetation and land surface models. Previous models have generally been based on the optimality assumption of maximizing the net photosynthetic assimilation per unit leaf area (i.e. the area-based optimality) while overlooking other optimality assumptions such as maximizing the net photosynthetic assimilation per unit leaf dry mass (i.e. the mass-based optimality). This paper compares the predicted results of photosynthetic acclimation to different environmental conditions between the area-based optimality and the mass-based optimality models. The predictions are then verified using the observational data from the literatures. The mass-based optimality model better predicted photosynthetic acclimation to growth light intensity, air temperature and CO2 concentration, and captured more variability in photosynthetic traits than the area-based optimality models. The findings suggest that the mass-based optimality approach may be a promising strategy for improving the predictive power and accuracy of optimization models, which have been widely used in various studies related to plant carbon issues.

Growing-Season Precipitation Is a Key Driver of Plant Leaf Area to Sapwood Area Ratio at the Global Scale

Leaf area to sapwood area ratio (AL/AS) influences carbon sequestration, community composition, and ecosystem functioning in terrestrial vegetation and is closely related to leaf economics and hydraulics. However, critical predictors of AL/AS are not well understood. We compiled an AL/AS data set with 1612 species-site combinations (1137 species from 285 sites worldwide) from our field experiments and published literature. We found the global mean AL/AS to be 0.63 m2 cm-2, with its variation largely driven by growing-season precipitation (Pgs), which accounted for 18% of the variation in AL/AS. Species in tropical rainforests exhibited the highest AL/AS (0.82 m2 cm-2), whereas desert species showed the lowest AL/AS (0.16 m2 cm-2). Soil factors such as soil nitrogen and soil organic carbon exhibited positive effects on AL/AS, whereas soil pH was negatively correlated with AL/AS. Tree density accounted for 7% of the variation in AL/AS. All biotic and abiotic predictors collectively explained up to 45% of the variation in AL/AS. Additionally, AL/AS was positively correlated to the net primary productivity (NPP) of the ecosystem. Our study provides insights into the driving factors of AL/AS at the global scale and highlights the importance of AL/AS in ecosystem productivity. Given that Pgs is the most critical driver of AL/AS, alterations in global precipitation belts, particularly seasonal precipitation, may induce changes in plant leaf area on the branches.

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.

Developing a predictive science of the biosphere requires the integration of scientific cultures

Increasing the speed of scientific progress is urgently needed to address the many challenges associated with the biosphere in the Anthropocene. Consequently, the critical question becomes: How can science most rapidly progress to address large, complex global problems? We suggest that the lag in the development of a more predictive science of the biosphere is not only because the biosphere is so much more complex, or because we do not have enough data, or are not doing enough experiments, but, in large part, because of unresolved tension between the three dominant scientific cultures that pervade the research community. We introduce and explain the concept of the three scientific cultures and present a novel analysis of their characteristics, supported by examples and a formal mathematical definition/representation of what this means and implies. The three cultures operate, to varying degrees, across all of science. However, within the biosciences, and in contrast to some of the other sciences, they remain relatively more separated, and their lack of integration has hindered their potential power and insight. Our solution to accelerating a broader, predictive science of the biosphere is to enhance integration of scientific cultures. The process of integration-Scientific Transculturalism-recognizes that the push for interdisciplinary research, in general, is just not enough. Unless these cultures of science are formally appreciated and their thinking iteratively integrated into scientific discovery and advancement, there will continue to be numerous significant challenges that will increasingly limit forecasting and prediction efforts.

Genetically correlated leaf tensile and morphological traits are driven by growing season length in a widespread perennial grass

PREMISE

Leaf tensile resistance, a leaf's ability to withstand pulling forces, is an important determinant of plant ecological strategies. One potential driver of leaf tensile resistance is growing season length. When growing seasons are long, strong leaves, which often require more time and resources to construct than weak leaves, may be more advantageous than when growing seasons are short. Growing season length and other ecological conditions may also impact the morphological traits that underlie leaf tensile resistance.

METHODS

To understand variation in leaf tensile resistance, we measured size-dependent leaf strength and size-independent leaf toughness in diverse genotypes of the widespread perennial grass Panicum virgatum (switchgrass) in a common garden. We then used quantitative genetic approaches to estimate the heritability of leaf tensile resistance and whether there were genetic correlations between leaf tensile resistance and other morphological traits.

RESULTS

Leaf tensile resistance was positively associated with aboveground biomass (a proxy for fitness). Moreover, both measures of leaf tensile resistance exhibited high heritability and were positively genetically correlated with leaf lamina thickness and leaf mass per area (LMA). Leaf tensile resistance also increased with the growing season length in the habitat of origin, and this effect was mediated by both LMA and leaf thickness.

CONCLUSIONS

Differences in growing season length may promote selection for different leaf lifespans and may explain existing variation in leaf tensile resistance in P. virgatum. In addition, the high heritability of leaf tensile resistance suggests that P. virgatum will be able to respond to climate change as growing seasons lengthen.

Variation in leaf carbon economics, energy balance, and heat tolerance traits highlights differing timescales of adaptation and acclimation

Multivariate leaf trait correlations are hypothesized to originate from natural selection on carbon economics traits that control lifetime leaf carbon gain, and energy balance traits governing leaf temperatures, physiological rates, and heat injury. However, it is unclear whether macroevolution of leaf traits primarily reflects selection for lifetime carbon gain or energy balance, and whether photosynthetic heat tolerance is coordinated along these axes. To evaluate these hypotheses, we measured carbon economics, energy balance, and photosynthetic heat tolerance traits for 177 species (157 families) in a common garden that minimizes co-variation of taxa and climate. We observed wide variation in carbon economics, energy balance, and heat tolerance traits. Carbon economics and energy balance (but not heat tolerance) traits were phylogenetically structured, suggesting macroevolution of leaf mass per area and leaf dry matter content reflects selection on carbon gain rather than energy balance. Carbon economics and energy balance traits varied along a common axis orthogonal to heat tolerance traits. Our results highlight a fundamental mismatch in the timescales over which morphological and heat tolerance traits respond to environmental variation. Whereas carbon economics and energy balance traits are constrained by species' evolutionary histories, photosynthetic heat tolerance traits are not and can acclimate readily to leaf microclimates.

Plant economic strategies in two contrasting forests

BACKGROUND

Predicting relationships between plant functional traits and environmental effects in their habitats is a central issue in terms of classic ecological theories. Yet, only weak correlation with functional trait composition of local plant communities may occur, implying that some essential information might be ignored. In this study, to address this uncertainty, the objective of the study is to test whether and how the consistency of trait relationships occurs by analyzing broad variation in eight traits related to leaf morphological structure, nutrition status and physiological activity, within a large number of plant species in two distinctive but comparable harsh habitats (high-cold alpine fir forest vs. north-cold boreal coniferous forest).

RESULTS

The contrasting and/or consistent relationships between leaf functional traits in the two distinctive climate regions were observed. Higher specific leaf area, photosynthetic rate, and photosynthetic nitrogen use efficiency (PNUE) with lower N concentration occurred in north-cold boreal forest rather than in high-cold alpine forest, indicating the acquisitive vs. conservative resource utilizing strategies in both habitats. The principal component analysis illuminated the divergent distributions of herb and xylophyta groups at both sites. Herbs tend to have a resource acquisition strategy, particularly in boreal forest. The structural equation modeling revealed that leaf density had an indirect effect on PNUE, primarily mediated by leaf structure and photosynthesis. Most of the traits were strongly correlated with each other, highlighting the coordination and/or trade-offs.

CONCLUSIONS

We can conclude that the variations in leaf functional traits in north-cold boreal forest were largely distributed in the resource-acquisitive strategy spectrum, a quick investment-return behavior; while those in the high-cold alpine forest tended to be mainly placed at the resource-conservative strategy end. The habitat specificity for the relationships between key functional traits could be a critical determinant of local plant communities. Therefore, elucidating plant economic spectrum derived from variation in major functional traits can provide a fundamental insight into how plants cope with ecological adaptation and evolutionary strategies under environmental changes, particularly in these specific habitats.