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Plant biomass production (BP), nitrogen uptake (Nup) and their ratio, nitrogen use efficiency (NUE), must be quantified to understand how nitrogen (N) cycling constrains terrestrial carbon (C) uptake. But the controls of key plant processes determiningNupand NUE, including BP, C and N allocation, tissue C:N ratios and N resorption efficiency (NRE), remain poorly known. We compiled measurements from 804 forest and grassland sites and derived regression models for each of these processes with growth temperature, vapour pressure deficit, stand age, soil C:N ratio, fAPAR (remotely sensed fraction of photosynthetically active radiation absorbed by green vegetation) and growing-season average daily incident photosynthetic photon flux density (gPPFD) (effectively the seasonal concentration of light availability, which increases polewards) as predictors. An empirical model for leaf N was based on optimal photosynthetic capacity (a function of gPPFD and climate) and observed leaf mass-per-area. The models were used to produce global maps ofNupand NUE. Global BP was estimated as 72 Pg C/yr;Nupas 950 Tg N/yr; and NUE as 76 gC/gN. Forest BP was found to increase with growth temperature and fAPAR and to decrease with stand age, soil C:N ratio and gPPFD. Forest NUE is controlled primarily by climate through its effect on C allocation – especially to leaves, being richer in N than other tissues. NUE is greater in colder climates, where N is less readily available, because belowground allocation is increased. NUE is also greater in drier climates because leaf allocation is reduced. NRE is enhanced (further promoting NUE) in both cold and dry climates. These findings can provide observationally based benchmarks for model representations of C–N cycle coupling. State-of-the-art vegetation models in the TRENDY ensemble showed variable performance against these benchmarks, and models including coupled C–N cycling produced relatively poor simulations ofNupand NUE.

Fire modifies vegetation spectral reflectances in the optical, thermal and microwave domains due to the changes it induces in vegetation canopy components (leaves, needles, branches) and in soil properties. Freely available satellite-derived (Landsat) Vegetation Indices (VIs) and PALSAR Mosaic backscatter measurements (known to be sensitive to vegetation structure) were used to help understand vegetation properties (species richness, basal area) in relation to fire return time (FRT) across a range of tropical biomes (open savanna, savanna forest, evergreen forest, peat-swamp forest) in Mato Grosso (Brazil), Kruger National Park (South Africa) and Central Kalimantan (Indonesia).For each site, we combined: (i) post-fire Landsat imagery (30 m) to derive VIs sensitive to vegetation diversity with (ii) PALSAR (25 m) backscatter that employes a longer wavelength (21 cm) and dual polarisation (Horizontal-Horizontal, Horizontal-Vertical) enabling the capture of strong backscattering of signal by branches and trunks.Most of the Landsat VI values showed greater variability in forests compared to open savanna, reflecting the greater diversity in species’ composition and growth form. A strong positive relationship was found between VIs and FRT across biomes and especially in forests. The amount of vegetation burned per fire as recorded by the magnitude of changes in these VIs, was highest in annual burn regimes (FRT = 1 year). Green and red-edge bands provided better discrimination of vegetation species richness and basal area. A significant positive relationship to basal area in response to fire return time was also found using PALSAR data due to its deeper canopy penetration level and strong backscattering from woody components. The observed responses of VI- and PALSAR-inferred species’ richness and basal area in response to FRT in different tropical biomes suggest that the green and red-edge channels from optical and longer wavelength HV-backscatter are useful metrics to quantify post-fire tropical vegetation dynamics.

"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.

© 2021 The Author(s)., Recent extreme wildfire seasons in several regions have been associated with exceptionally hot, dry conditions, made more probable by climate change. Much research has focused on extreme fire weather and its drivers, but natural wildfire regimes—and their interactions with human activities—are far from being comprehensively understood. There is a lack of clarity about the 'causes' of wildfire, and about how ecosystems could be managed for the co-existence of wildfire and people. We present evidence supporting an ecosystem-centred framework for improved understanding and modelling of wildfire. Wildfire has a long geological history and is a pervasive natural process in contemporary plant communities. In some biomes, wildfire would be more frequent without human settlement; in others they would be unchanged or less frequent. A world without fire would have greater forest cover, especially in present-day savannas. Many species would be missing, because fire regimes have co-evolved with plant traits that resist, adapt to or promote wildfire. Certain plant traits are favoured by different fire frequencies, and may be missing in ecosystems that are normally fire-free. For example, post-fire resprouting is more common among woody plants in high-frequency fire regimes than where fire is infrequent. The impact of habitat fragmentation on wildfire crucially depends on whether the ecosystem is fire-adapted. In normally fire-free ecosystems, fragmentation facilitates wildfire starts and is detrimental to biodiversity. In fire-adapted ecosystems, fragmentation inhibits fires from spreading and fire suppression is detrimental to biodiversity. This interpretation explains observed, counterintuitive patterns of spatial correlation between wildfire and potential ignition sources. Lightning correlates positively with burnt area only in open ecosystems with frequent fire. Human population correlates positively with burnt area only in densely forested regions. Models for vegetation-fire interactions must be informed by insights from fire ecology to make credible future projections in a changing climate., We gratefully acknowledge support from the Leverhulme Centre for Wildfires, Environment and Society, who organized the virtual mini-workshop which initiated the writing of this paper. RKN is supported by the Leverhulme Centre. SPH and YS acknowledge support from the ERC-funded project GC2.0 (Global Change 2.0: Unlocking the past for a clearer future, Grant Number 694481). ICP, KJB and ND acknowledge support from the ERC-funded project REALM (Re-inventing Ecosystem And Land-surface Models, Grant Number 787203). JCH acknowledges funding from the ERC project SCATAPNUT (Grant Number 681885). This work is a contribution to the LEMONTREE (Land Ecosystem Models based On New Theory, obseRvations and ExperimEnts) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures program (SPH, YS and ICP).

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge., Measurement(s)plant traitTechnology Type(s)digital curationSample Characteristic - OrganismViridiplantaeSample Characteristic - LocationAustralia Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14545755

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.

Accurate simulations of gross primary production (GPP) are vital for Earth System Models that must inform public policy decisions. The instantaneous controls of leaf-level photosynthesis, which can be measured in manipulative experiments, are well established. At the canopy scale, however, there is no consensus on how GPP depends on (a) light or (b) other aspects of the physical environment such as temperature and CO2. Models of GPP make a variety of different assumptions when ‘scaling-up’ the standard model of photosynthesis. As a troublesome consequence, they make a variety of different predictions about how GPP responds to projected environmental change.This problem can be tackled by theoretical modelling and by empirical analysis of GPP as reconstructed from eddy-covariance flux measurements. Theoretical modelling has provided an explanation for why ‘light-use efficiency’ (LUE) models work well at time scales of a week or longer. The same logic provides a justification for the use of LUE as a key metric in an empirical analysis. By focusing on LUE, we can isolate the drivers of GPP independent of its over-riding control by absorbed light. We have used open-access eddy covariance data from over 100 sites, collated over 20 years (the number of sites has grown with time). These sites, located in a wide range of biomes and climate zones, form part of the FLUXNET network. We have combined the flux data with a satellite product (EVI from MODIS) that allows spatial estimates of the fraction of incident light absorbed by green vegetation. Matching soil moisture data were estimated using the SPLASH model, with appropriate meteorological inputs, and soil water-holding capacity derived using SoilGrids. LUE was then calculated as the amount of carbon fixed per unit of absorbed light. We then explored additive models (incorporating multiple explanatory factors) that support non-linear responses. Recognising that our longitudinal data lack independence, we controlled for the hierarchical nature of the dataset through a variance structure that nests measurement year within site location.In arriving at a preferred parsimonious model, we show that daytime air temperature and vapour pressure deficit, and soil moisture content are all salient predictors of LUE. The same explanatory terms are retained in iterations of this analysis run at timescales from weeks to months. As a model-comparison exercise, we used that portion of our dataset which overlaps the North American Carbon Program to apply our empirical model structure to site-based estimates of GPP generated by 19 discrete Terrestrial Biosphere Models (TBMs). The comparative analysis reveals wide variation between the TBMs in the shape, strength and even sign of the environmental effects on modelled GPP.This empirical analysis suggests it is feasible to predict GPP using a single model structure, common across vegetation categories. And the appeal of such universal approaches is highlighted by inconsistent relationships with key environmental drivers within extant terrestrial models.

Plants not only acquire carbon to sustain biomass production, autotrophic respiration, and the production of non-structural compounds, but also require nitrogen to support carboxylation and growth. However, available observations have not fully been integrated and used for modelling growth, carbon allocation to different compartments, and how different compartments’ nitrogen-to-carbon ratio vary across large climatic and soil gradients. This leaves substantial uncertainty in estimates of the global distribution of growth and nitrogen uptake by plants. Here, we used the P-model, a first principles-derived and remote sensing-driven model for terrestrial gross primary production (GPP) to simulate the global distribution of GPP. Using comprehensive datasets with locally measured covariates for climatic and edaphic conditions and vegetation structure, we modelled the fractional allocation of GPP to biomass production (BP), aboveground net primary production (ANPP), and leaf NPP based on linear mixed-effects regression models. We defined BP as the sum of NPP in leaves, wood and roots. It thus does not include additional components such as exudates and labile carbon to mycorrhizae. Leaf nitrogen-to-carbon was modelled based on the maximum rate of carboxylation at 25 degrees Celsius (Vcmax25) and leaf mass per area (LMA). We then used global gridded data for the covariates that entered as predictors in site-level empirical models to simulate global C and N allocated to each component. We finally validated our global simulation results with an extended set of globally distributed GPP, BP and nitrogen-to-carbon ratio observations. GPP was well predicted (R2 = 0.61). In forests, ratios of BP/GPP and ANPP/GPP decreased with soil C/N and stand-age but increased with humidity and with the fraction of absorbed photosynthetically active radiation (fAPAR). The ratio of leaf NPP to ANPP, increased with light availability and growth temperature, but decreased with vapor pressure deficit. Leaf nitrogen-to-carbon ratio was positively related to the ratio of Vcmax25 to LMA. Leaf nitrogen resorption efficiency (NRE) was increased in drier and colder environments. Through our data validation at the end, we have shown a prediction for NPP (R2 = 0.26), ANPP (R2 = 0.28), leaf NPP (R2 = 0.39), NRE (R2 = 0.30), leaf N/C (R2 = 0.26) and leaf N flux (R2 = 0.35). Simulated global total GPP is 125 Pg C yr-1. Based on these statistical models, global mean carbon-use-efficiency (BP/GPP) was estimated to be 40%. The ratio of ANPP/BP was 72%, and ANPP was further split with 46% to leaf NPP and 54% to wood NPP. Simulated global total nitrogen acquisition (total of uptake from the soil and symbiotic N fixation) was 860 Tg N yr-1. Growth in the leaf, wood and root compartment accounted for 39%, 23% and 38% of global N acquisition, respectively. We suggest that plant adaptations result in higher ANPP, leaf NPP and finally leaf N flux under warmer, wetter, more abundant light and N-rich soil conditions, which aims to support higher rate of photosynthesis with greater nitrogen investment in the leaf.

International audience; Short-term temperature response curves of leaf dark respiration (R-T) provide insights into a critical process that influences plant net carbon exchange. This includes how respiratory traits acclimate to sustained changes in the environment. Our study analysed 860 high-resolutionR-T(10-70 degrees C range) curves for: (a) 62 evergreen species measured in two contrasting seasons across several field sites/biomes; and (b) 21 species (subset of those sampled in the field) grown in glasshouses at 20 degrees C : 15 degrees C, 25 degrees C : 20 degrees C and 30 degrees C : 25 degrees C, day : night. In the field, across all sites/seasons, variations inR(25)(measured at 25 degrees C) and the leafTwhereRreached its maximum (T-max) were explained by growthT(mean air-Tof 30-d before measurement), solar irradiance and vapour pressure deficit, with growthThaving the strongest influence.R(25)decreased andT(max)increased with rising growthTacross all sites and seasons with the single exception of winter at the cool-temperate rainforest site where irradiance was low. The glasshouse study confirmed thatR(25)andT(max)thermally acclimated. Collectively, the results suggest: (1) thermal acclimation of leafRis common in most biomes; and (2) the highTthreshold of respiration dynamically adjusts upward when plants are challenged with warmer and hotter climates.

There remains large uncertainty about the global exchanges of carbon between the atmosphere and the terrestrial biosphere under different environmental change scenarios. Ecosystem and Earth system models rely on photosynthetic capacity (maximum rates of carboxylation (Vcmax) and electron transport (Jmax)) to simulate carbon assimilation. Photosynthetic capacity has been related to environmental and climatic constraints, but also to leaf and soil nutrients. Views differ on which are more important.We assembled and analysed a large dataset of global observations of photosynthetic and other leaf traits. Photosynthetic capacity was best predicted based on optimality hypotheses. Vcmax standardized to 25°C (Vcmax25) was proportional to light availability, and increased towards colder and drier environments – as expected due to the greater biochemical investment required at lower temperatures, or when stomata are more closed. The ratio Jmax25/ Vcmax25 declined with growth temperature (also predicted). However, theoretical predictions slightly underestimated Vcmax at high growth temperatures, and overestimated it at low growth temperatures. This bias might be due to the difference between leaf and air temperatures.Statistical models for photosynthetic capacity (all species, and site means) overestimated Vcmax in low-P leaves. Analysis of a subset of the data showed that leaf P tends to increase with measured soil P. A relationship of model bias to leaf N appears in the all-species analysis – perhaps reflecting a correlation of Vcmax, leaf N and light levels within communities. But site-mean analysis showed no such bias, and leaf N showed no relationship to the soil C:N ratio. These results support a previously noted dependency of Vcmax on P availability; but not the control of Vcmax by N availability that has been assumed in many models.

© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust The ratio of leaf intercellular to ambient CO 2 (χ) is modulated by stomatal conductance (g s ). These quantities link carbon (C) assimilation with transpiration, and along with photosynthetic capacities (V cmax and J max ) are required to model terrestrial C uptake. We use optimization criteria based on the growth environment to generate predicted values of photosynthetic and water-use efficiency traits and test these against a unique dataset. Leaf gas-exchange parameters and carbon isotope discrimination were analysed in relation to local climate across a continental network of study sites. Sun-exposed leaves of 50 species at seven sites were measured in contrasting seasons. Values of χ predicted from growth temperature and vapour pressure deficit were closely correlated to ratios derived from C isotope (δ 13 C) measurements. Correlations were stronger in the growing season. Predicted values of photosynthetic traits, including carboxylation capacity (V cmax ), derived from δ 13 C, growth temperature and solar radiation, showed meaningful agreement with inferred values derived from gas-exchange measurements. Between-site differences in water-use efficiency were, however, only weakly linked to the plant's growth environment and did not show seasonal variation. These results support the general hypothesis that many key parameters required by Earth system models are adaptive and predictable from plants’ growth environments.

In many biomes, plants are subject to heatwaves, potentially causing irreversible damage to the photosynthetic apparatus. Field surveys have documented global, temperature-dependent patterns in photosynthetic heat tolerance (PHT ); however, it remains unclear if these patterns reflect acclimation in PHT or inherent differences among species adapted to contrasting habitats. To address these unknowns, we quantified seasonal variations in Tcrit (high temperature where minimal chlorophyll-a fluorescence rises rapidly, reflecting disruption to photosystem II) in 62 species native to 6 sites from 5 thermally contrasting biomes across Australia. Tcrit and leaf fatty acid (FA) composition (important for membrane stability) were quantified in three temperature-controlled glasshouses in 20 of those species. Tcrit was greatest at hot field sites and acclimated seasonally (summer > winter, increasing on average 0.34 °C per °C increase in growth temperature). The glasshouse study showed that Tcrit was inherently higher in species from warmer habitats (increasing 0.16 °C per °C increase in origin annual mean maximum temperature) and acclimated to increasing growth temperature (0.24 °C °C-1 ). Variations in Tcrit were positively correlated with the relative abundance of saturated FAs, with FAs accounting for 40% of Tcrit variation. These results highlight the importance of both plastic adjustments and inherent differences determining contemporary continent-wide patterns in PHT .

Large spatial and temporal gradients in rainfall and temperature occur across Australia. This heterogeneity drives ecological differentiation in vegetation structure and ecophysiology. We examined multiple leaf-scale traits, including foliar 13 C isotope discrimination (Δ13 C), rates of photosynthesis and foliar N concentration and their relationships with multiple climate variables. Fifty-five species across 27 families were examined across eight sites spanning contrasting biomes. Key questions addressed include: (i) Does Δ13 C and intrinsic water-use efficiency (WUEi ) vary with climate at a continental scale? (ii) What are the seasonal and spatial patterns in Δ13 C/WUEi across biomes and species? (iii) To what extent does Δ13 C reflect variation in leaf structural, functional and nutrient traits across climate gradients? and (iv) Does the relative importance of assimilation and stomatal conductance in driving variation in Δ13 C differ across seasons? We found that MAP, temperature seasonality, isothermality and annual temperature range exerted independent effects on foliar Δ13 C/WUEi . Temperature-related variables exerted larger effects than rainfall-related variables. The relative importance of photosynthesis and stomatal conductance (gs ) in determining Δ13 C differed across seasons: Δ13 C was more strongly regulated by gs during the dry-season and by photosynthetic capacity during the wet-season. Δ13 C was most strongly correlated, inversely, with leaf mass area ratio among all leaf attributes considered. Leaf Nmass was significantly and positively correlated with MAP during dry- and wet-seasons and with moisture index (MI) during the wet-season but was not correlated with Δ13 C. Leaf Pmass showed significant positive relationship with MAP and Δ13 C only during the dry-season. For all leaf nutrient-related traits, the relationships obtained for Δ13 C with MAP or MI indicated that Δ13 C at the species level reliably reflects the water status at the site level. Temperature and water availability, not foliar nutrient content, are the principal factors influencing Δ13 C across Australia.

Nitrogen (N) and phosphorus (P) have key roles in leaf metabolism, resulting in a strong coupling of chemical composition traits to metabolic rates in field-based studies. However, in such studies, it is difficult to disentangle the effects of nutrient supply per se on trait–trait relationships.Our study assessed how high and low N (5 mM and 0.4 mM, respectively) and P (1 mM and 2 μM, respectively) supply in 37 species from six plant functional types (PTFs) affected photosynthesis (A) and respiration (R) (in darkness and light) in a controlled environment.Low P supply increased scaling exponents (slopes) of area-based log–log A–N or R–N relationships when N supply was not limiting, whereas there was no P effect under low N supply. By contrast, scaling exponents of A–P and R–P relationships were altered by P and N supply. Neither R : A nor light inhibition of leaf R was affected by nutrient supply. Light inhibition was 26% across nutrient treatments; herbaceous species exhibited a lower degree of light inhibition than woody species.Because N and P supply modulates leaf trait−trait relationships, the next generation of terrestrial biosphere models may need to consider how limitations in N and P availability affect trait−trait relationships when predicting carbon exchange.

Plant respiration is an important contributor to the proposed positive global carbon-cycle feedback to climate change. However, as a major component, leaf mitochondrial ('dark') respiration (Rd ) differs among species adapted to contrasting environments and is known to acclimate to sustained changes in temperature. No accepted theory explains these phenomena or predicts its magnitude. Here we propose that the acclimation of Rd follows an optimal behaviour related to the need to maintain long-term average photosynthetic capacity (Vcmax ) so that available environmental resources can be most efficiently used for photosynthesis. To test this hypothesis, we extend photosynthetic co-ordination theory to predict the acclimation of Rd to growth temperature via a link to Vcmax , and compare predictions to a global set of measurements from 112 sites spanning all terrestrial biomes. This extended co-ordination theory predicts that field-measured Rd and Vcmax accessed at growth temperature (Rd,tg and Vcmax,tg ) should increase by 3.7% and 5.5% per degree increase in growth temperature. These acclimated responses to growth temperature are less steep than the corresponding instantaneous responses, which increase 8.1% and 9.9% per degree of measurement temperature for Rd and Vcmax respectively. Data-fitted responses proof indistinguishable from the values predicted by our theory, and smaller than the instantaneous responses. Theory and data are also shown to agree that the basal rates of both Rd and Vcmax assessed at 25°C (Rd,25 and Vcmax,25 ) decline by ~4.4% per degree increase in growth temperature. These results provide a parsimonious general theory for Rd acclimation to temperature that is simpler-and potentially more reliable-than the plant functional type-based leaf respiration schemes currently employed in most ecosystem and land-surface models.

The ratio of leaf internal (ci ) to ambient (ca ) partial pressure of CO2 , defined here as χ, is an index of adjustments in both leaf stomatal conductance and photosynthetic rate to environmental conditions. Measurements and proxies of this ratio can be used to constrain vegetation model uncertainties for predicting terrestrial carbon uptake and water use. We test a theory based on the least-cost optimality hypothesis for modelling historical changes in χ over the 1951-2014 period, across different tree species and environmental conditions, as reconstructed from stable carbon isotopic measurements across a global network of 103 absolutely dated tree-ring chronologies. The theory predicts optimal χ as a function of air temperature, vapour pressure deficit, ca and atmospheric pressure. The theoretical model predicts 39% of the variance in χ values across sites and years, but underestimates the intersite variability in the reconstructed χ trends, resulting in only 8% of the variance in χ trends across years explained by the model. Overall, our results support theoretical predictions that variations in χ are tightly regulated by the four environmental drivers. They also suggest that explicitly accounting for the effects of plant-available soil water and other site-specific characteristics might improve the predictions.

We examined whether variations in photosynthetic capacity are linked to variations in the environment and/or associated leaf traits for tropical moist forests (TMFs) in the Andes/western Amazon regions of Peru. We compared photosynthetic capacity (maximal rate of carboxylation of Rubisco (Vcmax), and the maximum rate of electron transport (Jmax)), leaf mass, nitrogen (N) and phosphorus (P) per unit leaf area (Ma, Na and Pa, respectively), and chlorophyll from 210 species at 18 field sites along a 3300-m elevation gradient. Western blots were used to quantify the abundance of the CO2-fixing enzyme Rubisco. Area- and N-based rates of photosynthetic capacity at 25°C were higher in upland than lowland TMFs, underpinned by greater investment of N in photosynthesis in high-elevation trees. Soil [P] and leaf Pa were key explanatory factors for models of area-based Vcmax and Jmax but did not account for variations in photosynthetic N-use efficiency. At any given Na and Pa, the fraction of N allocated to photosynthesis was higher in upland than lowland species. For a small subset of lowland TMF trees examined, a substantial fraction of Rubisco was inactive. These results highlight the importance of soil- and leaf-P in defining the photosynthetic capacity of TMFs, with variations in N allocation and Rubisco activation state further influencing photosynthetic rates and N-use efficiency of these critically important forests. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust

© 2018 The Authors. Functional Ecology © 2018 British Ecological Society Plant species show considerable leaf trait variability that should be accounted for in dynamic global vegetation models (DGVMs). In particular, differences in the acclimation of leaf traits during periods more and less favourable to growth have rarely been examined. We conducted a field study of leaf trait variation at seven sites spanning a range of climates and latitudes across the Australian continent; 80 native plant species were included. We measured key traits associated with leaf structure, chemistry and metabolism during the favourable and unfavourable growing seasons. Leaf traits differed widely in the degree of seasonal variation displayed. Leaf mass per unit area (Ma) showed none. At the other extreme, seasonal variation accounted for nearly a third of total variability in dark respiration (Rdark). At the non-tropical sites, carboxylation capacity (Vcmax) at the prevailing growth temperature was typically higher in summer than in winter. When Vcmax was normalized to a common reference temperature (25°C), however, the opposite pattern was observed for about 30% of the species. This suggests that metabolic acclimation is possible, but far from universal. Intraspecific variation—combining measurements of individual plants repeated at contrasting seasons, different leaves from the same individual, and multiple conspecific plants at a given site—dominated total variation for leaf metabolic traits Vcmax and Rdark. By contrast, site location was the major source of variation (53%) for Ma. Interspecific trait variation ranged from only 13% of total variation for Vcmax up to 43% for nitrogen content per unit leaf area. These findings do not support a common practice in DGVMs of assigning fixed leaf trait values to plant functional types. Trait-based models should allow for interspecific differences, together with spatial and temporal plasticity in leaf structural, chemical and metabolic traits. A plain language summary is available for this article.

Recent compilations of experimental and observational data have documented global temperature-dependent patterns of variation in leaf dark respiration (R), but it remains unclear whether local adjustments in respiration over time (through thermal acclimation) are consistent with the patterns in R found across geographical temperature gradients. We integrated results from two global empirical syntheses into a simple temperature-dependent respiration framework to compare the measured effects of respiration acclimation-over-time and variation-across-space to one another, and to a null model in which acclimation is ignored. Using these models, we projected the influence of thermal acclimation on: seasonal variation in R; spatial variation in mean annual R across a global temperature gradient; and future increases in R under climate change. The measured strength of acclimation-over-time produces differences in annual R across spatial temperature gradients that agree well with global variation-across-space. Our models further project that acclimation effects could potentially halve increases in R (compared with the null model) as the climate warms over the 21st Century. Convergence in global temperature-dependent patterns of R indicates that physiological adjustments arising from thermal acclimation are capable of explaining observed variation in leaf respiration at ambient growth temperatures across the globe.

Large spatial and temporal gradients in rainfall and temperature occur across Australia. This heterogeneity drives ecological differentiation in vegetation structure and ecophysiology. We examined multiple leaf-scale traits, including foliar

Aims our study quantified the combined effects of fertilization and inoculation with arbuscular mycorrhizal fungi (amF) on grain yield and allocation of biomass and nutrients in field-grown rice (Oryza sativa l.). Methods a two-factor experiment was conducted at a field site in northeast of China (in shuangcheng, Heilongjiang Province, songhua river basin): six nitrogen–phosphorus–potassium fertilizer levels were provided (0, 20, 40, 60, 80 and 100% of the local norm of fertilizer supply), with or without inoculation with Glomus mosseae. at maturity, we quantified the percentage of root length colonization by amF, grain yield, shoot:root ratios, shoot N and P contents and nutrients allocated to panicles, leaves and stems. Important Findings as expected, inoculation resulted in greatly increased amF colonization, which in turn led to higher shoot:root ratios and greater shoot N contents. shoot:root ratios of inoculated rice increased with increasing fertilization while there was a significant interaction between fertilization and inoculation on shoot:root ratio. additionally, amF inoculation increased panicle:shoot ratios, panicle N:shoot N ratios and panicle P:shoot P ratios, especially in plants grown at low fertilizer levels. Importantly, inoculated rice exhibited higher grain yield, with the maximum improvement (near 62%) at the lower fertilizer end. our results showed that (i) amFinoculated plants conform to the functional equilibrium theory, albeit to a reduced extent compared to non-inoculated plants and (ii) amF inoculation resulted in greater allocation of shoot biomass to panicles and increased grain yield by stimulating N and P redistribution to panicles.

How leaf respiration (Rd) is represented in leading terrestrial biosphere models (TBMs ) is reviewed, followed by an overview of how emerging global datasets provide opportunities to improve parameterization of leaf Rd in large-scale models. We first outline how TBMs have historically accounted for variations in respiratory CO2 release in mature leaves, using assumed relationships between leaf nitrogen, photosynthetic capacity and Rd. The need for TBMs to account for light inhibition of Rd in mature leaves is highlighted, followed by a discussion on how Rd of upper canopy leaves is used to predict maintenance respiration in whole plants. We then outline how respiratory energy requirements of growth are accounted for in TBMs, pointing out that current assumptions on the costs of biosynthesis are based on theoretical calculations that may not be valid for all plant species and environments. The chapter then considers how improvements might be made to TBMs with respect to the parameterization of leaf Rd. We show how recently compiled datasets provide improved capacity to predict global variations in baseline Rd measured at a standard temperature, and how baseline Rd likely acclimates to sustained changes in growth temperature. Application of this dataset reveals markedly higher rates of leaf Rd than currently predicted by TBMs , suggesting that TBMs may be underestimating global plant respiratory CO2 release. The availability of a new, global dataset on short-term temperature responses of leaf Rd is highlighted. Analysis of this dataset reveals that leaf Rd does not exhibit the exponential response assumed by most TBMs; rather, the temperature-sensitivity declines as leaves warm, with convergence in the temperature-response across biomes and plant functional types . We show how equations derived from these datasets may provide the TBM community with a new framework to improve representation of mature leaf respiration in TBMs.

Reply to Adams et al. : Empirical versus process-based approaches to modeling temperature responses of leaf respiration

Plant respiration constitutes a massive carbon flux to the atmosphere, and a major control on the evolution of the global carbon cycle. It therefore has the potential to modulate levels of climate change due to the human burning of fossil fuels. Neither current physiological nor terrestrial biosphere models adequately describe its short-term temperature response, and even minor differences in the shape of the response curve can significantly impact estimates of ecosystem carbon release and/or storage. Given this, it is critical to establish whether there are predictable patterns in the shape of the respiration-temperature response curve, and thus in the intrinsic temperature sensitivity of respiration across the globe. Analyzing measurements in a comprehensive database for 231 species spanning 7 biomes, we demonstrate that temperature-dependent increases in leaf respiration do not follow a commonly used exponential function. Instead, we find a decelerating function as leaves warm, reflecting a declining sensitivity to higher temperatures that is remarkably uniform across all biomes and plant functional types. Such convergence in the temperature sensitivity of leaf respiration suggests that there are universally applicable controls on the temperature response of plant energy metabolism, such that a single new function can predict the temperature dependence of leaf respiration for global vegetation. This simple function enables straightforward description of plant respiration in the land-surface components of coupled earth system models. Our cross-biome analyses shows significant implications for such fluxes in cold climates, generally projecting lower values compared with previous estimates.

High-temperature tolerance in plants is important in a warming world, with extreme heat-waves predicted to increase in frequency and duration, potentially leading to lethal heating of leaves. Global patterns of high-temperature tolerance are documented in animals, but generally not plants, limiting our ability to assess risks associated with climate warming. To assess whether there are global patterns in high-temperature tolerance of leaf metabolism, we quantified Tcrit (high temperature where minimal chlorophyll a fluorescence rises rapidly, and thus where photosystem II is disrupted) and Tmax (temperature where leaf respiration in darkness is maximal, beyond which respiratory function rapidly declines) in upper-canopy leaves of 218 plant species spanning seven biomes. Mean site-based Tcrit values ranged from 41.5 °C in the Alaskan arctic to 50.8 °C in lowland tropical rainforests of Peruvian Amazon. For Tmax, the equivalent values were 51.0 and 60.6 °C in the Arctic and Amazon, respectively. Tcrit and Tmax followed similar biogeographic patterns, increasing linearly (~8 °C) from polar to equatorial regions. Such increases in high temperature tolerance are much less than expected based on the 20 °C span in high temperature extremes across the globe. Moreover, with only modest high-temperature tolerance despite high summer temperature extremes, species in mid-latitude (~20°-50°) regions have the narrowest thermal safety margins in upper-canopy leaves; these regions are at the greatest risk of damage due to extreme heat-wave events, especially under conditions when leaf temperatures are further elevated by a lack of transpirational cooling. Using predicted heat-wave events for 2050 and accounting for possible thermal acclimation of Tcrit and Tmax, we also found that these safety margins could shrink in a warmer world, as rising temperatures are likely to exceed thermal tolerance limits. Thus, increasing numbers of species in many biomes may be at risk as heat-wave events become more severe with climate change.

Through interpretations of remote-sensing data and/or theoretical propositions, the idea that forest and savanna represent "alternative stable states" is gaining increasing acceptance. Filling an observational gap, we present detailed stratified floristic and structural analyses for forest and savanna stands located mostly within zones of transition (where both vegetation types occur in close proximity) in Africa, South America and Australia. Woody plant leaf area index variation was related to tree canopy cover in a similar way for both savanna and forest with substantial overlap between the two vegetation types. As total woody plant canopy cover increased, so did the relative contribution of middle and lower strata of woody vegetation. Herbaceous layer cover declined as woody cover increased. This pattern of understorey grasses and herbs progressively replaced by shrubs as the canopy closes over was found for both savanna and forests and on all continents. Thus, once subordinate woody canopy layers are taken into account, a less marked transition in woody plant cover across the savanna–forest-species discontinuum is observed compared to that inferred when trees of a basal diameter > 0.1 m are considered in isolation. This is especially the case for shrub-dominated savannas and in taller savannas approaching canopy closure. An increased contribution of forest species to the total subordinate cover is also observed as savanna stand canopy closure occurs. Despite similarities in canopy-cover characteristics, woody vegetation in Africa and Australia attained greater heights and stored a greater amount of above-ground biomass than in South America. Up to three times as much above-ground biomass is stored in forests compared to savannas under equivalent climatic conditions. Savanna–forest transition zones were also found to typically occur at higher precipitation regimes for South America than for Africa. Nevertheless, consistent across all three continents coexistence was found to be confined to a well-defined edaphic–climate envelope with soil and climate the key determinants of the relative location of forest and savanna stands. Moreover, when considered in conjunction with the appropriate water availability metrics, it emerges that soil exchangeable cations exert considerable control on woody canopy-cover extent as measured in our pan-continental (forest + savanna) data set. Taken together these observations do not lend support to the notion of alternate stable states mediated through fire feedbacks as the prime force shaping the distribution of the two dominant vegetation types of the tropical lands.

Forest and savanna are the two dominant vegetation types of the tropical regions with very few tree species common to both. At a broad scale, it has long been recognised that the distributions of these two biomes are principally governed by precipitation and its seasonality, but with soil physical and chemical properties also potentially important. For tree species drawn from a range of forest and savanna sites in tropical Far North Queensland, Australia, we compared leaf traits of photosynthetic capacity, structure and nutrient concentrations. Area-based photosynthetic capacity was higher for the savanna species with a steeper slope to the photosynthesis ↔ nitrogen (N) relationship compared with the forest group. Higher leaf mass per unit leaf area for the savanna trees derived from denser rather than thicker leaves and did not appear to restrict rates of light-saturated photosynthesis when expressed on either an area or mass basis. Median ratios of foliar N to phosphorus (P) were relatively high (>20) at all sites, but we found no evidence for a dominant P limitation of photosynthesis for either forest or savanna trees. A parsimonious mixed-effects model of area-based photosynthetic capacity retained vegetation type and both N and P as explanatory terms. Resulting model-fitted predictions suggested a good fit to the observed data (R2 = 0.82). The model's random component found variation in area-based photosynthetic response to be much greater among species (71% of response variance) than across sites (9%). These results suggest that, on a leaf-area basis, savanna trees of Far North Queensland, Australia, are capable of photosynthetically outperforming forest species at their common boundaries.

Plant biologists have long had a choice of the dimensions in which to express their studied traits and/or processes. For example, a plant physiologist working at the leaf level might typically measure and report photosynthetic rates as a flux per unit leaf area (e.g. μmol CO₂ m⁻² s⁻¹) whereas a biochemist might typically express the same process per unit chlorophyll. An agronomist or forester would usually be more interested in dry matter accumulation rate per unit ground area (Mg ha⁻¹ yr⁻¹) or sometimes even as a relative growth rate (g DW g⁻¹ DW d⁻¹). Although expressing leaf-level photosynthesis on an area basis seems intuitive and was for decades the standard practice, starting with Field & Mooney (1986) and then Reich & Walters (1994), there has been an increasing tendency to express the photosynthetic characteristics of leaves on a dry-weight basis (typically nmol CO₂ g⁻¹ s⁻¹). This trend has been due, at least in part, to stronger correlations for mass-based photosynthetic rates with foliar properties thought to be important in their modulation (Reich et al., 1998). Weaker associations between foliar properties when expressed on an area-basis have also provided one rationale for the inclusion of mass-based measures of photosynthesis, nitrogen and phosphorus into a so-called 'leaf economics spectrum' (Wright et al., 2004) and with mass-based measures of photosynthetic carbon exchange subsequently underlying further analyses (Shipley et al., 2006). Some modelling studies investigating the relative importance of nitrogen vs phosphorus as modulators of leaf photosynthetic capacity have likewise been parameterized on a mass rather than an area-basis because of the apparently superior model fit of the former (Domingues et al., 2010).

Tropical soils are often characterised by low phosphorus availability and tropical forest trees typically exhibit lower area-based rates of photosynthesis (Aa) for a given area-based leaf nitrogen concentration ([N]a) compared with plants growing in higher-latitude, N-limited ecosystems. Nevertheless, to date, very few studies have assessed the effects of P deprivation per se on Aa ↔ [N]a relationships in tropical trees. Our study investigated the effect of reduced soil P availability on light-saturated Aa and related leaf traits of seven Australian tropical tree species. We addressed the following questions: (1) Do contrasting species exhibit inherent differences in nutrient partitioning and morphology? (2) Does P deprivation lead to a change in the nature of the Aa ↔ [N]a relationship? (3) Does P deprivation lead to an alteration in leaf nitrogen levels or N allocation within the leaf? Applying a mixed effects model, we found that for these Australian tropical tree species, removal of P from the nutrient solution decreased area-based photosynthetic capacity (Amax,a) by 18% and reduced the slope of the Amax,a ↔ [N]a relationship and differences among species accounted for around 30% of response variation. Despite greater N allocation to chlorophyll, photosynthetic N use efficiency was significantly reduced in low-P plants. Collectively, our results support the view that low soil P availability can alter photosynthesis–nitrogen relationships in tropical trees.