Contrasting carbon cycle along tropical forest aridity gradients in West Africa and Amazonia.

Tropical forests cover large areas of equatorial Africa and play a substantial role in the global carbon cycle. However, there has been a lack of biometric measurements to understand the forests' gross and net primary productivity (GPP, NPP) and their allocation. Here we present a detailed field assessment of the carbon budget of multiple forest sites in Africa, by monitoring 14 one-hectare plots along an aridity gradient in Ghana, West Africa. When compared with an equivalent aridity gradient in Amazonia, the studied West African forests generally had higher productivity and lower carbon use efficiency (CUE). The West African aridity gradient consistently shows the highest NPP, CUE, GPP, and autotrophic respiration at a medium-aridity site, Bobiri. Notably, NPP and GPP of the site are the highest yet reported anywhere for intact forests. Widely used data products substantially underestimate productivity when compared to biometric measurements in Amazonia and Africa. Our analysis suggests that the high productivity of the African forests is linked to their large GPP allocation to canopy and semi-deciduous characteristics.

Incorporating photosynthetic acclimation improves stomatal optimisation models.

Stomatal opening in plant leaves is regulated through a balance of carbon and water exchange under different environmental conditions. Accurate estimation of stomatal regulation is crucial for understanding how plants respond to changing environmental conditions, particularly under climate change. A new generation of optimality-based modelling schemes determines instantaneous stomatal responses from a balance of trade-offs between carbon gains and hydraulic costs, but most such schemes do not account for biochemical acclimation in response to drought. Here, we compare the performance of six instantaneous stomatal optimisation models with and without accounting for photosynthetic acclimation. Using experimental data from 37 plant species, we found that accounting for photosynthetic acclimation improves the prediction of carbon assimilation in a majority of the tested models. Photosynthetic acclimation contributed significantly to the reduction of photosynthesis under drought conditions in all tested models. Drought effects on photosynthesis could not accurately be explained by the hydraulic impairment functions embedded in the stomatal models alone, indicating that photosynthetic acclimation must be considered to improve estimates of carbon assimilation during drought.

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.

Optimality principles explaining divergent responses of alpine vegetation to environmental change.

Recent increases in vegetation greenness over much of the world reflect increasing CO2 globally and warming in cold areas. However, the strength of the response to both CO2 and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (Fmax ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year-1 in drier regions and a browning of 0.12 ± 0.08% year-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in Fmax with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year-1 ) and browning (0.07 ± 0.06% year-1 ). We also predicted the observed reduced sensitivities of Fmax to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces Fmax in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO2 stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.

Towards a unified theory of plant photosynthesis and hydraulics.

The global carbon and water cycles are governed by the coupling of CO2 and water vapour exchanges through the leaves of terrestrial plants, controlled by plant adaptations to balance carbon gains and hydraulic risks. We introduce a trait-based optimality theory that unifies the treatment of stomatal responses and biochemical acclimation of plants to environments changing on multiple timescales. Tested with experimental data from 18 species, our model successfully predicts the simultaneous decline in carbon assimilation rate, stomatal conductance and photosynthetic capacity during progressive soil drought. It also correctly predicts the dependencies of gas exchange on atmospheric vapour pressure deficit, temperature and CO2. Model predictions are also consistent with widely observed empirical patterns, such as the distribution of hydraulic strategies. Our unified theory opens new avenues for reliably modelling the interactive effects of drying soil and rising atmospheric CO2 on global photosynthesis and transpiration.

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.

Rising CO2 and warming reduce global canopy demand for nitrogen.

Nitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO2 and climate change. By extension, it has been suggested that declining carboxylation capacity (Vcmax ) and leaf N content in enhanced-CO2 experiments and satellite records signify increasing N limitation of primary production. We predicted Vcmax using the coordination hypothesis and estimated changes in leaf-level photosynthetic N for 1982-2016 assuming proportionality with leaf-level Vcmax at 25°C. The whole-canopy photosynthetic N was derived using satellite-based leaf area index (LAI) data and an empirical extinction coefficient for Vcmax , and converted to annual N demand using estimated leaf turnover times. The predicted spatial pattern of Vcmax shares key features with an independent reconstruction from remotely sensed leaf chlorophyll content. Predicted leaf photosynthetic N declined by 0.27% yr-1 , while observed leaf (total) N declined by 0.2-0.25% yr-1 . Predicted global canopy N (and N demand) declined from 1996 onwards, despite increasing LAI. Leaf-level responses to rising CO2 , and to a lesser extent temperature, may have reduced the canopy requirement for N by more than rising LAI has increased it. This finding provides an alternative explanation for declining leaf N that does not depend on increasing N limitation.

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.

Vegetation responses to climate extremes recorded by remotely sensed atmospheric formaldehyde.

Accurate monitoring of vegetation stress is required for better modelling and forecasting of primary production, in a world where heatwaves and droughts are expected to become increasingly prevalent. Variability in formaldehyde (HCHO) concentrations in the troposphere is dominated by local emissions of short-lived biogenic (BVOC) and pyrogenic volatile organic compounds. BVOCs are emitted by plants in a rapid protective response to abiotic stress, mediated by the energetic status of leaves (the excess of reducing power when photosynthetic light and dark reactions are decoupled, as occurs when stomata close in response to water stress). Emissions also increase exponentially with leaf temperature. New analytical methods for the detection of spatiotemporally contiguous extremes in remote-sensing data are applied here to satellite-derived atmospheric HCHO columns. BVOC emissions are shown to play a central role in the formation of the largest positive HCHO anomalies. Although vegetation stress can be captured by various remotely sensed quantities, spaceborne HCHO emerges as the most consistent recorder of vegetation responses to the largest climate extremes, especially in forested regions.

Global decadal variability of plant carbon isotope discrimination and its link to gross primary production.

Carbon isotope discrimination (Δ13 C) in C3 woody plants is a key variable for the study of photosynthesis. Yet how Δ13 C varies at decadal scales, and across regions, and how it is related to gross primary production (GPP), are still incompletely understood. Here we address these questions by implementing a new Δ13 C modelling capability in the land-surface model JULES incorporating both photorespiratory and mesophyll-conductance fractionations. We test the ability of four leaf-internal CO2 concentration models embedded in JULES to reproduce leaf and tree-ring (TR) carbon isotopic data. We show that all the tested models tend to overestimate average Δ13 C values, and to underestimate interannual variability in Δ13 C. This is likely because they ignore the effects of soil water stress on stomatal behavior. Variations in post-photosynthetic isotopic fractionations across species, sites and years, may also partly explain the discrepancies between predicted and TR-derived Δ13 C values. Nonetheless, the "least-cost" (Prentice) model shows the lowest biases with the isotopic measurements, and lead to improved predictions of canopy-level carbon and water fluxes. Overall, modelled Δ13 C trends vary strongly between regions during the recent (1979-2016) historical period but stay nearly constant when averaged over the globe. Photorespiratory and mesophyll effects modulate the simulated global Δ13 C trend by 0.0015 ± 0.005‰ and -0.0006 ± 0.001‰ ppm-1 , respectively. These predictions contrast with previous findings based on atmospheric carbon isotope measurements. Predicted Δ13 C and GPP tend to be negatively correlated in wet-humid and cold regions, and in tropical African forests, but positively related elsewhere. The negative correlation between Δ13 C and GPP is partly due to the strong dominant influences of temperature on GPP and vapor pressure deficit on Δ13 C in those forests. Our results demonstrate that the combined analysis of Δ13 C and GPP can help understand the drivers of photosynthesis changes in different climatic regions.

Eco-evolutionary optimality as a means to improve vegetation and land-surface models.

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

An improved statistical approach for reconstructing past climates from biotic assemblages.

Quantitative reconstructions of past climates are an important resource for evaluating how well climate models reproduce climate changes. One widely used statistical approach for making such reconstructions from fossil biotic assemblages is weighted averaging partial least-squares regression (WA-PLS). There is however a known tendency for WA-PLS to yield reconstructions compressed towards the centre of the climate range used for calibration, potentially biasing the reconstructed past climates. We present an improvement of WA-PLS by assuming that: (i) the theoretical abundance of each taxon is unimodal with respect to the climate variable considered; (ii) observed taxon abundances follow a multinomial distribution in which the total abundance of a sample is climatically uninformative; and (iii) the estimate of the climate value at a given site and time makes the observation most probable, i.e. it maximizes the log-likelihood function. This climate estimate is approximated by weighting taxon abundances in WA-PLS by the inverse square of their climate tolerances. We further improve the approach by considering the frequency ( fx) of the climate variable in the training dataset. Tolerance-weighted WA-PLS with fx correction greatly reduces the compression bias, compared with WA-PLS, and improves model performance in reconstructions based on an extensive modern pollen dataset.

Impacts of soil water stress on the acclimated stomatal limitation of photosynthesis: Insights from stable carbon isotope data.

Atmospheric aridity and drought both influence physiological function in plant leaves, but their relative contributions to changes in the ratio of leaf internal to ambient partial pressure of CO2 (χ) - an index of adjustments in both stomatal conductance and photosynthetic rate to environmental conditions - are difficult to disentangle. Many stomatal models predicting χ include the influence of only one of these drivers. In particular, the least-cost optimality hypothesis considers the effect of atmospheric demand for water on χ but does not predict how soils with reduced water further influence χ, potentially leading to an overestimation of χ under dry conditions. Here, we use a large network of stable carbon isotope measurements in C3 woody plants to examine the acclimated response of χ to soil water stress. We estimate the ratio of cost factors for carboxylation and transpiration (ß) expected from the theory to explain the variance in the data, and investigate the responses of ß (and thus χ) to soil water content and suction across seed plant groups, leaf phenological types and regions. Overall, ß decreases linearly with soil drying, implying that the cost of water transport along the soil-plant-atmosphere continuum increases as water available in the soil decreases. However, despite contrasting hydraulic strategies, the stomatal responses of angiosperms and gymnosperms to soil water tend to converge, consistent with the optimality theory. The prediction of ß as a simple, empirical function of soil water significantly improves χ predictions by up to 6.3 ± 2.3% (mean ± SD of adjusted-R2 ) over 1980-2018 and results in a reduction of around 2% of mean χ values across the globe. Our results highlight the importance of soil water status on stomatal functions and plant water-use efficiency, and suggest the implementation of trait-based hydraulic functions into the model to account for soil water stress.

Components of leaf-trait variation along environmental gradients.

Leaf area (LA), mass per area (LMA), nitrogen per unit area (Narea ) 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 Narea ) 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 Narea 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 Narea 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.

A theory of plant function helps to explain leaf-trait and productivity responses to elevation.

Several publications have examined leaf-trait and carbon-cycling shifts along an Amazon-Andes transect spanning 3.5 km in elevation and 16°C in mean annual temperature. Photosynthetic capacity was previously shown to increase as temperature declines with increasing elevation, counteracting enzyme-kinetic effects. Primary production declines, nonetheless, due to decreasing light availability. We aimed to predict leaf-trait and production gradients from first principles, using published data to test an emerging theory whereby photosynthetic traits and primary production depend on optimal acclimation and/or adaptation to environment. We re-analysed published data for 210 species at 25 sites, fitting linear relationships to elevation for both predicted and observed photosynthetic traits and primary production. Declining leaf-internal/ambient CO2 ratio (χ) and increasing carboxylation (Vcmax ) and electron-transport (Jmax ) capacities with increasing elevation were predicted. Increases in leaf nitrogen content with elevation were explained by increasing Vcmax and leaf mass-per-area. Leaf and soil phosphorus covaried, but after controlling for elevation, no nutrient metric accounted for any additional variance in photosynthetic traits. Primary production was predicted to decline with elevation. This analysis unifies leaf and ecosystem observations in a common theoretical framework. The insensitivity of primary production to temperature is shown to emerge as a consequence of the optimisation of photosynthetic traits.

TRY plant trait database - enhanced coverage and open access.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Plant respiration: Controlled by photosynthesis or biomass?

Two simplifying hypotheses have been proposed for whole-plant respiration. One links respiration to photosynthesis; the other to biomass. Using a first-principles carbon balance model with a prescribed live woody biomass turnover, applied at a forest research site where multidecadal measurements are available for comparison, we show that if turnover is fast the accumulation of respiring biomass is low and respiration depends primarily on photosynthesis; while if turnover is slow the accumulation of respiring biomass is high and respiration depends primarily on biomass. But the first scenario is inconsistent with evidence for substantial carry-over of fixed carbon between years, while the second implies far too great an increase in respiration during stand development-leading to depleted carbohydrate reserves and an unrealistically high mortality risk. These two mutually incompatible hypotheses are thus both incorrect. Respiration is not linearly related either to photosynthesis or to biomass, but it is more strongly controlled by recent photosynthates (and reserve availability) than by total biomass.

Observed and modelled historical trends in the water-use efficiency of plants and ecosystems.

Plant water-use efficiency (WUE, the carbon gained through photosynthesis per unit of water lost through transpiration) is a tracer of the plant physiological controls on the exchange of water and carbon dioxide between terrestrial ecosystems and the atmosphere. At the leaf level, rising CO2 concentrations tend to increase carbon uptake (in the absence of other limitations) and to reduce stomatal conductance, both effects leading to an increase in leaf WUE. At the ecosystem level, indirect effects (e.g. increased leaf area index, soil water savings) may amplify or dampen the direct effect of CO2 . Thus, the extent to which changes in leaf WUE translate to changes at the ecosystem scale remains unclear. The differences in the magnitude of increase in leaf versus ecosystem WUE as reported by several studies are much larger than would be expected with current understanding of tree physiology and scaling, indicating unresolved issues. Moreover, current vegetation models produce inconsistent and often unrealistic magnitudes and patterns of variability in leaf and ecosystem WUE, calling for a better assessment of the underlying approaches. Here, we review the causes of variations in observed and modelled historical trends in WUE over the continuum of scales from leaf to ecosystem, including methodological issues, with the aim of elucidating the reasons for discrepancies observed within and across spatial scales. We emphasize that even though physiological responses to changing environmental drivers should be interpreted differently depending on the observational scale, there are large uncertainties in each data set which are often underestimated. Assumptions made by the vegetation models about the main processes influencing WUE strongly impact the modelled historical trends. We provide recommendations for improving long-term observation-based estimates of WUE that will better inform the representation of WUE in vegetation models.

Frost and leaf-size gradients in forests: global patterns and experimental evidence.

Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede convective exchange with the surrounding air. Seedlings of 15 New Zealand evergreens spanning 12-fold variation in leaf width were exposed to clear night skies, and leaf temperatures were measured with thermocouples. We then used a global dataset to assess several climate variables as predictors of leaf size in forest assemblages. Leaf minus air temperature was strongly correlated with leaf width, ranging from -0.9 to -3.2°C in the smallest- and largest-leaved species, respectively. Mean annual temperature and frost-free period were good predictors of evergreen angiosperm leaf size in forest assemblages, but no climate variable predicted deciduous leaf size. Although winter deciduousness makes large leaves possible in strongly seasonal climates, large-leaved evergreens are largely confined to frost-free climates because of their susceptibility to radiative cooling. Evergreen leaf size data can therefore be used to enhance vegetation models, and to infer palaeotemperatures from fossil leaf assemblages.

Long-term water stress leads to acclimation of drought sensitivity of photosynthetic capacity in xeric but not riparian Eucalyptus species.

BACKGROUND AND AIMS: Experimental drought is well documented to induce a decline in photosynthetic capacity. However, if given time to acclimate to low water availability, the photosynthetic responses of plants to low soil moisture content may differ from those found in short-term experiments. This study aims to test whether plants acclimate to long-term water stress by modifying the functional relationships between photosynthetic traits and water stress, and whether species of contrasting habitat differ in their degree of acclimation. METHODS: Three Eucalyptus taxa from xeric and riparian habitats were compared with regard to their gas exchange responses under short- and long-term drought. Photosynthetic parameters were measured after 2 and 4 months of watering treatments, namely field capacity or partial drought. At 4 months, all plants were watered to field capacity, then watering was stopped. Further measurements were made during the subsequent 'drying-down', continuing until stomata were closed. KEY RESULTS: Two months of partial drought consistently reduced assimilation rate, stomatal sensitivity parameters (g1), apparent maximum Rubisco activity (V'(cmax)) and maximum electron transport rate (J'(max)). Eucalyptus occidentalis from the xeric habitat showed the smallest decline in V'(cmax) and J'(max); however, after 4 months, V'(cmax) and J'(max) had recovered. Species differed in their degree of V'(cmax) acclimation. Eucalyptus occidentalis showed significant acclimation of the pre-dawn leaf water potential at which the V'(cmax) and 'true' V(cmax) (accounting for mesophyll conductance) declined most steeply during drying-down. CONCLUSIONS: The findings indicate carbon loss under prolonged drought could be over-estimated without accounting for acclimation. In particular, (1) species from contrasting habitats differed in the magnitude of V'(cmax) reduction in short-term drought; (2) long-term drought allowed the possibility of acclimation, such that V'(cmax) reduction was mitigated; (3) xeric species showed a greater degree of V'(cmax) acclimation; and (4) photosynthetic acclimation involves hydraulic adjustments to reduce water loss while maintaining photosynthesis.