Unforeseen plant phenotypic diversity in a dry and grazed world.

Earth harbours an extraordinary plant phenotypic diversity1 that is at risk from ongoing global changes2,3. However, it remains unknown how increasing aridity and livestock grazing pressure-two major drivers of global change4-6-shape the trait covariation that underlies plant phenotypic diversity1,7. Here we assessed how covariation among 20 chemical and morphological traits responds to aridity and grazing pressure within global drylands. Our analysis involved 133,769 trait measurements spanning 1,347 observations of 301 perennial plant species surveyed across 326 plots from 6 continents. Crossing an aridity threshold of approximately 0.7 (close to the transition between semi-arid and arid zones) led to an unexpected 88% increase in trait diversity. This threshold appeared in the presence of grazers, and moved toward lower aridity levels with increasing grazing pressure. Moreover, 57% of observed trait diversity occurred only in the most arid and grazed drylands, highlighting the phenotypic uniqueness of these extreme environments. Our work indicates that drylands act as a global reservoir of plant phenotypic diversity and challenge the pervasive view that harsh environmental conditions reduce plant trait diversity8-10. They also highlight that many alternative strategies may enable plants to cope with increases in environmental stress induced by climate change and land-use intensification.

Carboxylation capacity is the main limitation of carbon assimilation in High Arctic shrubs.

Increases in shrub height, biomass and canopy cover are key whole-plant features of warming-induced vegetation change in tundra. We investigated leaf functional traits underlying photosynthetic capacity of Arctic shrub species, particularly its main limiting processes such as mesophyll conductance. In this nutrient-limited ecosystem, we expect leaf nitrogen concentration to be the main limiting factor for photosynthesis. We measured the net photosynthetic rate at saturated light (Asat) in three Salix species throughout a glacial valley in High-Arctic tundra and used a causal approach to test relationships between leaf stomatal and mesophyll conductances (gsc, gm), carboxylation capacity (Vcmax), nitrogen and phosphorus concentration (Narea, Parea) and leaf mass ratio (LMA). Arctic Salix species showed no difference in Asat compared to a global data set, while being characterized by higher Narea, Parea and LMA. Vcmax, gsc and gm independently increased Asat, with Vcmax as its main limitation. We highlighted a nitrogen-influenced pathway for increasing photosynthesis in the two prostrate mesic habitat species. In contrast, the erect wetland habitat Salix richardsonii mainly increased Asat with increasing gsc. Overall, our study revealed high photosynthetic capacities of Arctic Salix species but contrasting regulatory pathways that may influence shrub ability to respond to environmental changes in High Arctic tundra.

Functional rarity and evenness are key facets of biodiversity to boost multifunctionality.

The functional traits of organisms within multispecies assemblages regulate biodiversity effects on ecosystem functioning. Yet how traits should assemble to boost multiple ecosystem functions simultaneously (multifunctionality) remains poorly explored. In a multibiome litter experiment covering most of the global variation in leaf trait spectra, we showed that three dimensions of functional diversity (dispersion, rarity, and evenness) explained up to 66% of variations in multifunctionality, although the dominant species and their traits remained an important predictor. While high dispersion impeded multifunctionality, increasing the evenness among functionally dissimilar species was a key dimension to promote higher multifunctionality and to reduce the abundance of plant pathogens. Because too-dissimilar species could have negative effects on ecosystems, our results highlight the need for not only diverse but also functionally even assemblages to promote multifunctionality. The effect of functionally rare species strongly shifted from positive to negative depending on their trait differences with the dominant species. Simultaneously managing the dispersion, evenness, and rarity in multispecies assemblages could be used to design assemblages aimed at maximizing multifunctionality independently of the biome, the identity of dominant species, or the range of trait values considered. Functional evenness and rarity offer promise to improve the management of terrestrial ecosystems and to limit plant disease risks.

Coordination of photosynthetic traits across soil and climate gradients.

"Least-cost theory" posits that C3 plants should balance rates of photosynthetic water loss and carboxylation in relation to the relative acquisition and maintenance costs of resources required for these activities. Here we investigated the dependency of photosynthetic traits on climate and soil properties using a new Australia-wide trait dataset spanning 528 species from 67 sites. We tested the hypotheses that plants on relatively cold or dry sites, or on relatively more fertile sites, would typically operate at greater CO2 drawdown (lower ratio of leaf internal to ambient CO2 , Ci :Ca ) during light-saturated photosynthesis, and at higher leaf N per area (Narea ) and higher carboxylation capacity (Vcmax 25 ) for a given rate of stomatal conductance to water vapour, gsw . These results would be indicative of plants having relatively higher water costs than nutrient costs. In general, our hypotheses were supported. Soil total phosphorus (P) concentration and (more weakly) soil pH exerted positive effects on the Narea -gsw and Vcmax 25 -gsw slopes, and negative effects on Ci :Ca . The P effect strengthened when the effect of climate was removed via partial regression. We observed similar trends with increasing soil cation exchange capacity and clay content, which affect soil nutrient availability, and found that soil properties explained similar amounts of variation in the focal traits as climate did. Although climate typically explained more trait variation than soil did, together they explained up to 52% of variation in the slope relationships and soil properties explained up to 30% of the variation in individual traits. Soils influenced photosynthetic traits as well as their coordination. In particular, the influence of soil P likely reflects the Australia's geologically ancient low-relief landscapes with highly leached soils. Least-cost theory provides a valuable framework for understanding trade-offs between resource costs and use in plants, including limiting soil nutrients.

When and where soil is important to modify the carbon and water economy of leaves.

Photosynthetic 'least-cost' theory posits that the optimal trait combination for a given environment is that where the summed costs of photosynthetic water and nutrient acquisition/use are minimised. The effects of soil water and nutrient availability on photosynthesis should be stronger as climate-related costs for both resources increase. Two independent datasets of photosynthetic traits, Globamax (1509 species, 288 sites) and Glob13C (3645 species, 594 sites), were used to quantify biophysical and biochemical limitations of photosynthesis and the key variable Ci /Ca (CO2 drawdown during photosynthesis). Climate and soil variables were associated with both datasets. The biochemical photosynthetic capacity was higher on alkaline soils. This effect was strongest at more arid sites, where water unit-costs are presumably higher. Higher values of soil silt and depth increased Ci /Ca , likely by providing greater H2 O supply, alleviating biophysical photosynthetic limitation when soil water is scarce. Climate is important in controlling the optimal balance of H2 O and N costs for photosynthesis, but soil properties change these costs, both directly and indirectly. In total, soil properties modify the climate-demand driven predictions of Ci /Ca by up to 30% at a global scale.

Global photosynthetic capacity is optimized to the environment.

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (Vcmax ), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co-optimization of carboxylation and water costs for photosynthesis, suggests that optimal Vcmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field-measured Vcmax dataset for C3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first-order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.

Dynamics of regulated YNPQ and non-regulated YNO energy dissipation in sunflower leaves exposed to sinusoidal lights.

Better understanding of photosynthetic efficiency under fluctuating light requires a specific approach to characterize the dynamics of energy dissipation in photosystem II. In this study, we characterized the interaction between the regulated YNPQ and non-regulated YNO energy dissipation in outdoor- and indoor-grown sunflower leaves exposed to repetitive cycles of sinusoidal lights of five amplitudes (200, 400, 600, 800, 1000 µmol m-2 s-1) and periods (20, 40, 60, 90, 120 s). The different light cycles induced various patterns of ChlF emission, from which were calculated the complementary quantum yields of photochemical energy conversion YII, light-regulated YNPQ, and non-regulated YNO non-photochemical energy dissipation. During the light cycles, YNO varied in complex but small patterns relative to those of YNPQ, whose variations were mostly mirrored by changes in YII. The YNO patterns could be decomposed by fast Fourier transform into a main (MH) and several upper harmonics (UH). Concerning YNPQ dynamics, they were described by sinusoidal regressions with two components, one constant during the light cycles but increasing with the average light intensity (YNPQc), and one variable (YNPQv). Formation and relaxation of YNPQv followed the intensity of the sinusoidal lights, with lags ranging from 5 to 13 s. These lags decreased with the amplitude of the incident light, and were shorter by 37% in outdoor than indoor leaves. YNPQv and UHs responses to the growth conditions, amplitudes, and the periods of the sinusoidal light were closely correlated (r = 0.939), whereas MH and YNPQc varied similarly (r = 0.803). The analysis of ChlF induced by sinusoidal lights may be a useful tool to better understand the dynamics of energy dissipation in PSII under fluctuating lights.

A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis.

Simulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate (Vcmax ). Estimating this parameter using A-Ci curves (net photosynthesis, A, vs intercellular CO2 concentration, Ci ) is laborious, which limits availability of Vcmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO2 concentration (Asat ) measurements, from which Vcmax can be extracted using a 'one-point method'. We used a global dataset of A-Ci curves (564 species from 46 field sites, covering a range of plant functional types) to test the validity of an alternative approach to estimate Vcmax from Asat via this 'one-point method'. If leaf respiration during the day (Rday ) is known exactly, Vcmax can be estimated with an r(2) value of 0.98 and a root-mean-squared error (RMSE) of 8.19 µmol m(-2) s(-1) . However, Rday typically must be estimated. Estimating Rday as 1.5% of Vcmax, we found that Vcmax could be estimated with an r(2) of 0.95 and an RMSE of 17.1 µmol m(-2) s(-1) . The one-point method provides a robust means to expand current databases of field-measured Vcmax , giving new potential to improve vegetation models and quantify the environmental drivers of Vcmax variation.

Balancing the costs of carbon gain and water transport: testing a new theoretical framework for plant functional ecology.

A novel framework is presented for the analysis of ecophysiological field measurements and modelling. The hypothesis 'leaves minimise the summed unit costs of transpiration and carboxylation' predicts leaf-internal/ambient CO2 ratios (ci /ca ) and slopes of maximum carboxylation rate (Vcmax ) or leaf nitrogen (Narea ) vs. stomatal conductance. Analysis of data on woody species from contrasting climates (cold-hot, dry-wet) yielded steeper slopes and lower mean ci /ca ratios at the dry or cold sites than at the wet or hot sites. High atmospheric vapour pressure deficit implies low ci /ca in dry climates. High water viscosity (more costly transport) and low photorespiration (less costly photosynthesis) imply low ci /ca in cold climates. Observed site-mean ci /ca shifts are predicted quantitatively for temperature contrasts (by photorespiration plus viscosity effects) and approximately for aridity contrasts. The theory explains the dependency of ci /ca ratios on temperature and vapour pressure deficit, and observed relationships of leaf δ(13) C and Narea to aridity.

How tree traits modulate tree methane fluxes: A review.

Trees can play different roles in the regulation of fluxes of methane (CH4), a greenhouse gas with a warming potential 83 times greater than that of carbon dioxide. Forest soils have the greatest potential for methane uptake compared to other land uses. In addition to their influence on soil CH4 fluxes, trees can act directly as a source or sink of CH4, by transporting CH4 produced in the soil and harbouring the key microorganisms involved in CH4 production and consumption (methanogens and methanotrophs). Tree CH4 fluxes can vary between species characterized by different traits that influence transport and modify the availability of CH4 reaction substrates as well as the habitat for methanogens and methanotrophs. Despite their important role in modulating CH4 fluxes from forest ecosystems, the identity and role of tree traits influencing these fluxes are poorly consolidated in the literature. The objectives of this paper are to 1) Review the functional traits of trees associated with their role in the regulation of CH4 emissions; 2) Assess the importance of inter-specific variability in CH4 fluxes via a global analysis of tree methane fluxes in the literature. Our review highlights that differences in CH4 fluxes between tree species and individuals can be explained by a diversity of traits influencing CH4 transport and microbial production of CH4 such as wood density and secondary metabolites. We propose a functional classification for trees based on the key traits associated with a function in CH4 emissions. We identified the fast-growing species with low wood density, species adapted to flood and species vulnerable to rot as functional groups which can be net sources of CH4 in conditions favorable to CH4 production. The global analysis further demonstrated the importance of taxonomy, with other factors such as land type and season in explaining variability in tree CH4 fluxes.

The Arctic Plant Aboveground Biomass Synthesis Dataset.

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m-2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

Species richness drives selection of individuals within wetlands based on traits related to acquisition and utilization of light.

Selection within natural communities has mainly been studied along large abiotic gradients, while the selection of individuals within populations should occur locally in response to biotic filters. To better leverage the role of the latter, we considered the hierarchal nature of environmental selection for the multiple dimensions of the trait space across biological levels, that is, from the species to the community and the ecosystem levels. We replicated a natural species richness gradient where communities included from two to 16 species within four wetlands (bog, fen, meadow, and marsh) contrasting in plant productivity. We sampled functional traits from individuals in each community and used hierarchical distributional modeling in order to analyze the independent variation of the mean and dispersion of functional trait space at ecosystem, community, and species levels. The plant productivity gradient observed between wetlands led to species turnover and selection of traits related to leaf nutrient conservation/acquisition strategy. Within wetlands, plant species richness drove trait variation across both communities and species. Among communities, variation of species richness correlated with the selection of individuals according to their use of vertical space and leaf adaptations to light conditions. Within species, intraspecific light-related trait variation in response to species richness was associated with stable population density for some species, while others reached low population density in more diverse communities. Within ecosystems, variation in biotic conditions selects individuals along functional dimensions that are independent of those selected across ecosystems. Within-species variations of light-related traits are related to demographic responses, linking biotic selection of individuals within communities to eco-evolutionary dynamics of species.

Habitat filtering and niche differentiation jointly explain species relative abundance within grassland communities along fertility and disturbance gradients.

Deterministic niche-based processes have been proposed to explain species relative abundance within communities but lead to different predictions: habitat filtering (HF) predicts dominant species to exhibit similar traits while niche differentiation (ND) requires that species have dissimilar traits to coexist. Using a multiple trait-based approach, we evaluated the relative roles of HF and ND in determining species abundances in productive grasslands. Four dimensions of the functional niche of 12 co-occurring grass species were identified using 28 plant functional traits. Using this description of the species niche, we investigated patterns of functional similarity and dissimilarity and linked them to abundance in randomly assembled six-species communities subjected to fertilization/disturbance treatments. Our results suggest that HF and ND jointly determined species abundance by acting on contrasting niche dimensions. The effect of HF decreased relative to ND with increasing disturbance and decreasing fertilization. Dominant species exhibited similar traits in communities whereas dissimilarity favored the coexistence of rare species with dominants by decreasing inter-specific competition. This stabilizing effect on diversity was suggested by a negative relationship between species over-yielding and relative abundance. We discuss the importance of considering independent dimensions of functional niche to better understand species abundance and coexistence within communities.

Impacts of species interactions on grass community productivity under contrasting management regimes.

Productivity-diversity relationships are routinely described mainly in terms of species richness. However, these relationships can be affected by the functional strategy and physiological plasticity characterizing each species as they respond to environment and management changes. This study, therefore, aimed to analyze species interactions in grass communities presenting the same number of species (n = 6) but different growth strategies, and the impact on community productivity across several forms of field management (two different fertilizer application rates, i.e. 120 and 360 kg N ha(-1) year(-1), and two cutting frequencies, i.e. 3 and 6 cuts per year). For this purpose, we applied the tripartite partitioning method introduced for the analysis of biodiversity effects (BE). Grass species were cultivated on small plots (4.2 m(2)) in both mixtures and monocultures. Different management regimes altered both net BE and its component effects: dominance and potential for complementarity. A higher cutting frequency significantly reduced net BE, via a reduction in dominance effect. We found that increased N supply could either increase or decrease complementary effect according to grass mixture composition, i.e. species strategy. Regardless of management intensity, net BE was in general significantly positive especially when including individual species-specific plasticity effects. We conclude that a combination of different grasses has a positive effect on community biomass. Furthermore, both the functional strategy and the functional plasticity of component species play an important role in the intensity of BE. Therefore, biological mechanisms leading to enhanced biomass in six-grass communities are as effective for productivity as management conditions.

Leaf nitrogen from the perspective of optimal plant function.

Leaf dry mass per unit area (LMA), carboxylation capacity (V cmax) and leaf nitrogen per unit area (Narea) and mass (Nmass) are key traits for plant functional ecology and ecosystem modelling. There is however no consensus about how these traits are regulated, or how they should be modelled. Here we confirm that observed leaf nitrogen across species and sites can be estimated well from observed LMA and V cmax at 25°C (V cmax25). We then test the hypothesis that global variations of both quantities depend on climate variables in specific ways that are predicted by leaf-level optimality theory, thus allowing both Narea to be predicted as functions of the growth environment.A new global compilation of field measurements was used to quantify the empirical relationships of leaf N to V cmax25 and LMA. Relationships of observed V cmax25 and LMA to climate variables were estimated, and compared to independent theoretical predictions of these relationships. Soil effects were assessed by analysing biases in the theoretical predictions.LMA was the most important predictor of Narea (increasing) and Nmass (decreasing). About 60% of global variation across species and sites in observed Narea, and 31% in Nmass, could be explained by observed LMA and V cmax25. These traits, in turn, were quantitatively related to climate variables, with significant partial relationships similar or indistinguishable from those predicted by optimality theory. Predicted trait values explained 21% of global variation in observed site-mean V cmax25, 43% in LMA and 31% in Narea. Predicted V cmax25 was biased low on clay-rich soils but predicted LMA was biased high, with compensating effects on Narea. Narea was overpredicted on organic soils. Synthesis. Global patterns of variation in observed site-mean Narea can be explained by climate-induced variations in optimal V cmax25 and LMA. Leaf nitrogen should accordingly be modelled as a consequence (not a cause) of V cmax25 and LMA, both being optimized to the environment. Nitrogen limitation of plant growth would then be modelled principally via whole-plant carbon allocation, rather than via leaf-level traits. Further research is required to better understand and model the terrestrial nitrogen and carbon cycles and their coupling.

The role of plant traits and their plasticity in the response of pasture grasses to nutrients and cutting frequency.

BACKGROUND AND AIMS: Although plant functional traits (PFTs) appear to be important indicators of species' responses to land use changes, there is no clear understanding of how the variations in traits and their plasticity determine variations in species performance. This study investigated the role of functional shoot traits and their plasticity for variation in above-ground net primary productivity (ANPP) due to changes in N supply and in cutting frequency for 13 native perennial C(3) grass species. METHODS: Monocultures of the grass species were grown in a fully factorial block design combining plant species, cutting frequency and N supply as factors. KEY RESULTS: Four major trait associations were obtained by reducing the dimensions of 14 PFTs with a principal component analysis (PCA).Variations in species' productivity in response to an increase in cutting frequency was mainly explained by traits linked to the first PCA axis, opposing high plant stature from lower shoot cellulose and lignin contents and high leaf N content. Variation in species productivity in response to change in N supply was mainly explained by a set of predictor variables combining traits (average flowering date) and a trait's plasticity (tiller density per unit land area and leaf dry matter content, i.e. mg dry matter g fresh mass(-1)). These traits involved are linked to the second PCA axis ('nutrient acquisition-conservation'), which opposes distinct strategies based on response to nutrient supply. CONCLUSIONS: Variations in ANPP of species in response to an increase in cutting frequency and a decrease in N supply are controlled by a group of traits, rather than by one individual trait. Incorporating plasticity of the individual traits into these trait combinations was the key to explaining species' productivity responses, accounting for up to 89 % of the total variability in response to the changes in N supply.

Both selection and plasticity drive niche differentiation in experimental grasslands.

The way species avoid each other in a community by using resources differently across space and time is one of the main drivers of species coexistence in nature1,2. This mechanism, known as niche differentiation, has been widely examined theoretically but still lacks thorough experimental validation in plants. To shape niche differences over time, species within communities can reduce the overlap between their niches or find unexploited environmental space3. Selection and phenotypic plasticity have been advanced as two candidate processes driving niche differentiation4,5, but their respective role remains to be quantified6. Here, we tracked changes in plant height, as a candidate trait for light capture7, in 5-year multispecies sown grasslands. We found increasing among-species height differences over time. Phenotypic plasticity promotes this change, which explains the rapid setting of differentiation in our system. Through the inspection of changes in genetic structure, we also highlighted the contribution of selection. Altogether, we experimentally demonstrated the occurrence of species niche differentiation within artificial grassland communities over a short time scale through the joined action of both plasticity and selection.

Global ecosystem thresholds driven by aridity.

Aridity, which is increasing worldwide because of climate change, affects the structure and functioning of dryland ecosystems. Whether aridification leads to gradual (versus abrupt) and systemic (versus specific) ecosystem changes is largely unknown. We investigated how 20 structural and functional ecosystem attributes respond to aridity in global drylands. Aridification led to systemic and abrupt changes in multiple ecosystem attributes. These changes occurred sequentially in three phases characterized by abrupt decays in plant productivity, soil fertility, and plant cover and richness at aridity values of 0.54, 0.7, and 0.8, respectively. More than 20% of the terrestrial surface will cross one or several of these thresholds by 2100, which calls for immediate actions to minimize the negative impacts of aridification on essential ecosystem services for the more than 2 billion people living in drylands.

Testing the environmental filtering concept in global drylands.

1. The environmental filtering hypothesis predicts that the abiotic environment selects species with similar trait values within communities. Testing this hypothesis along multiple - and interacting - gradients of climate and soil variables constitutes a great opportunity to better understand and predict the responses of plant communities to ongoing environmental changes. 2. Based on two key plant traits, maximum plant height and specific leaf area (SLA), we assessed the filtering effects of climate (mean annual temperature and precipitation, precipitation seasonality), soil characteristics (soil pH, sand content and total phosphorus) and all potential interactions on the functional structure and diversity of 124 dryland communities spread over the globe. The functional structure and diversity of dryland communities were quantified using the mean, variance, skewness and kurtosis of plant trait distributions. 3. The models accurately explained the observed variations in functional trait diversity across the 124 communities studied. All models included interactions among factors, i.e. climate - climate (9% of explanatory power), climate - soil (24% of explanatory power) and soil - soil interactions (5% of explanatory power). Precipitation seasonality was the main driver of maximum plant height, and interacted with mean annual temperature and precipitation. Soil pH mediated the filtering effects of climate and sand content on SLA. Our results also revealed that communities characterized by a low variance can also exhibit low kurtosis values, indicating that functionally contrasting species can co-occur even in communities with narrow ranges of trait values. 4. Synthesis We identified the particular set of conditions under which the environmental filtering hypothesis operates in drylands worldwide. Our findings also indicate that species with functionally contrasting strategies can still co-occur locally, even under prevailing environmental filtering. Interactions between sources of environmental stress should be therefore included in global trait-based studies, as this will help to further anticipate where the effects of environmental filtering will impact plant trait diversity under climate change.

Global climatic drivers of leaf size.

Leaf size varies by over a 100,000-fold among species worldwide. Although 19th-century plant geographers noted that the wet tropics harbor plants with exceptionally large leaves, the latitudinal gradient of leaf size has not been well quantified nor the key climatic drivers convincingly identified. Here, we characterize worldwide patterns in leaf size. Large-leaved species predominate in wet, hot, sunny environments; small-leaved species typify hot, sunny environments only in arid conditions; small leaves are also found in high latitudes and elevations. By modeling the balance of leaf energy inputs and outputs, we show that daytime and nighttime leaf-to-air temperature differences are key to geographic gradients in leaf size. This knowledge can enrich "next-generation" vegetation models in which leaf temperature and water use during photosynthesis play key roles.