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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

The Jurien Bay dune chronosequence in south‐western Australia’s biodiversity hotspot comprises sites differing in nutrient availability, with phosphorus (P) availability declining strongly with increasing soil age. We have explored the exceptionally high photosynthetic P‐use efficiency (PPUE) of Proteaceae in this region, triggering the question what the PPUE of co‐occurring species in other families might be along the Jurien Bay chronosequence. We explored how traits associated with PPUE, photosynthetic nitrogen (N)‐use efficiency (PNUE) and leaf respiration might converge along the chronosequence, and whether Proteaceae and non‐Proteaceae species differ in leaf traits associated with nutrient use. Seven to 10 species were sampled at three sites differing in nutrient availability (ranging from N‐ to P‐limited). Measurements of leaf light‐saturated photosynthesis and dark respiration were integrated with measurements of total N and P concentration in both mature and senesced leaves, and leaf mass per unit area (LMA). Contrary to what is known for other chronosequences, rates of photosynthesis and respiration did not decrease with increasing soil age and LMA along the Jurien Bay chronosequence. However, they increased when expressed per unit leaf P. Both N and P were used much more efficiently for photosynthesis on nutrient‐poor sites, in both Proteaceae and non‐Proteaceae species. Proteaceae had the fastest rate of photosynthesis per unit leaf P, followed by species that preferentially allocate P to mesophyll cells, rather than epidermal cells. Synthesis. Our results show that with declining soil P availability, photosynthetic P‐use efficiency of all investigated species from different families increased. Plants growing on the oldest, most nutrient‐impoverished soils exhibited similar rates of CO₂ exchange as plants growing on more nutrient‐rich younger soils, and extraordinarily high photosynthetic P‐use efficiency. This indicates convergence in leaf traits related to photosynthetic nutrient use on severely P‐impoverished sites.

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V cmax), 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 V cmax 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 V cmax 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.

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.

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 .

Understanding of the extent of acclimation of light-saturated net photosynthesis (An) to temperature (T), and associated underlying mechanisms, remains limited. This is a key knowledge gap given the importance of thermal acclimation for plant functioning, both under current and future higher temperatures, limiting the accuracy and realism of Earth System Model (ESM) predictions. Given this, we analysed and modelled T-dependent changes in photosynthetic capacity in 10 wet-forest tree species; six from temperate forests and four from tropical forests. Temperate and tropical species were each acclimated to three daytime growth temperatures (Tgrowth): temperate - 15, 20 and 25°C; tropical - 25, 30 and 35°C. CO2 response curves of An were used to model maximal rates of RuBP (ribulose-1,5-bisphosphate) carboxylation (Vcmax) and electron transport (Jmax) at each treatment's respective Tgrowth, and at a common measurement T (25°C). SDS-PAGE gels were used to determine abundance of the CO2-fixing enzyme, Rubisco. Leaf chlorophyll, nitrogen (N) and mass per unit leaf area (LMA) were also determined. For all species and Tgrowth, An at current atmospheric CO2 partial pressure was Rubisco-limited. Across all species, LMA decreased with increasing Tgrowth. Similarly, area-based rates of Vcmax at a measurement T of 25°C (Vcmax25) linearly declined with increasing Tgrowth, linked to a concomitant decline in total leaf protein per unit leaf area and Rubisco as a percentage of leaf N. The decline in Rubisco constrained Vcmax and An for leaves developed at higher Tgrowth and resulted in poor predictions of photosynthesis by currently widely used models that do not account for Tgrowth-mediated changes in Rubisco abundance that underpin the thermal acclimation response of photosynthesis in wet-forest tree species. A new model is proposed that accounts for the effect of Tgrowth-mediated declines in Vcmax25 on An, complementing current photosynthetic thermal acclimation models that do not account for T-sensitivity of Vcmax25. This article is protected by copyright. All rights reserved.

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

Temperature is a crucial factor in determining the rates of ecosystem processes, for example, leaf respiration (R) - the flux of plant respired CO2 from leaves to the atmosphere. Generally, R increases exponentially with temperature and formulations such as the Arrhenius equation are widely used in earth system models. However, experimental observations have shown a consequential and consistent departure from an exponential increase in R. What are the principles that underlie these observed patterns? Here, we demonstrate that macromolecular rate theory (MMRT), based on transition state theory (TST) for enzyme-catalyzed kinetics, provides a thermodynamic explanation for the observed departure and the convergent temperature response of R using a global database. Three meaningful parameters emerge from MMRT analysis: the temperature at which the rate of respiration would theoretically reach a maximum (the optimum temperature, Topt ), the temperature at which the respiration rate is most sensitive to changes in temperature (the inflection temperature, Tinf ) and the overall curvature of the log(rate) versus temperature plot (the change in heat capacity for the system, ΔCP‡). On average, the highest potential enzyme-catalyzed rates of respiratory enzymes for R are predicted to occur at 67.0 ± 1.2°C and the maximum temperature sensitivity at 41.4 ± 0.7°C from MMRT. The average curvature (average negative ΔCP‡) was -1.2 ± 0.1 kJ mol-1 K-1 . Interestingly, Topt , Tinf and ΔCP‡ appear insignificantly different across biomes and plant functional types, suggesting that thermal response of respiratory enzymes in leaves could be conserved. The derived parameters from MMRT can serve as thermal traits for plant leaves that represent the collective temperature response of metabolic respiratory enzymes and could be useful to understand regulations of R under a warmer climate. MMRT extends the classic TST to enzyme-catalyzed reactions and provides an accurate and mechanistic model for the short-term temperature response of R around the globe.

Summary This study highlights the dynamic nature of the temperature dependence of leaf respiration in plants experiencing future climate change scenarios, particularly with respect to drought and elevated [CO2]., Climate change is resulting in increasing atmospheric [CO2], rising growth temperature (T), and greater frequency/severity of drought, with each factor having the potential to alter the respiratory metabolism of leaves. Here, the effects of elevated atmospheric [CO2], sustained warming, and drought on leaf dark respiration (R dark), and the short-term T response of R dark were examined in Eucalyptus globulus. Comparisons were made using seedlings grown under different [CO2], T, and drought treatments. Using high resolution T–response curves of R dark measured over the 15–65 °C range, it was found that elevated [CO2], elevated growth T, and drought had little effect on rates of R dark measured at T

We tested whether snow gum (Eucalyptus pauciflora) trees growing in thermally contrasting environments exhibit generalizable temperature (T) response functions of leaf respiration (R) and fluorescence (Fo). Measurements were made on pot-grown saplings and field-grown trees (growing between 1380 and 2110 m a.s.l.). Using a continuous, high-resolution protocol, we quantified T response curves of R and Fo – these data were used to identify an algorithm for modelling R–T curves at subcritical T's and establish variations in heat tolerance. For the latter, we quantified Tmax [T where R is maximal] and Tcrit [T where Fo rises rapidly]. Tmax ranged from 51 to 57 °C, varying with season (e.g. winter > summer). Tcrit ranged from 41 to 49 °C in summer and from 58 to 63 °C in winter. Thus, surprisingly, leaf energy metabolism was more heat-tolerant in trees experiencing ice-encasement in winter than warmer conditions in summer. A polynomial model fitted to log-transformed R data provided the best description of the T-sensitivity of R (between 10 and 45 °C); using these model fits, we found that the negative slope of the Q10–T relationship was greater in winter than in summer. Collectively, our results (1) highlight high-T limits of energy metabolism in E. pauciflora and (2) provide a framework for improving representation of T-responses of leaf R in predictive models.

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

One of the major challenges in ecology is to understand how ecosystems respond to changes inenvironmental conditions, and how taxonomic and functional diversity mediate these changes. Inthis study, we use a trait-spectra and individual-based model, to analyse variation in forest primaryproductivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accuratelypredicted the magnitude and trends in forest productivity with elevation, with solar radiation andplant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, andwood density) collectively accounting for productivity variation. Remarkably, explicit representationof temperature variation with elevation was not required to achieve accurate predictions offorest productivity, as trait variation driven by species turnover appears to capture the effect oftemperature. Our semi-mechanistic model suggests that spatial variation in traits can potentiallybe used to estimate spatial variation in productivity at the landscape scale. Fil: Fyllas, Nikolaos M.. University of Oxford; Reino Unido Fil: Patrick Bentley, Lisa. University of Oxford; Reino Unido Fil: Shenkin, Alexander. University of Oxford; Reino Unido Fil: Asner, Gregory P.. Carnegie Institution for Science. Department of Global Ecology; Reino Unido Fil: Atkin, Owen K.. The Australian National University. ARC Centre of Excellence in Plant Energy Biology. Research School of Biology; Australia Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Enquist, Brian J.. Arizona State University; Estados Unidos Fil: Farfan Rios, William. University Wake Forest; Estados Unidos Fil: Gloor, Emanuel. University of Leeds; Reino Unido Fil: Guerrieri, Rossella. Universitat Autònoma de Barcelona; España. University of Edinburgh; Reino Unido Fil: Huaraca Huasco, Walter. Universidad Nacional de San Antonio Abad del Cusco; Perú Fil: Ishida, Yoko. James Cook University; Australia Fil: Martin, Roberta E.. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Meir, Patrick. University of Edinburgh; Reino Unido. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia Fil: Phillips, Oliver. University of Leeds; Reino Unido Fil: Salinas, Norma. University of Oxford; Reino Unido. Pontificia Universidad Católica de Perú; Perú Fil: Silman, Miles. University Wake Forest; Estados Unidos Fil: Weerasinghe, Lasantha K.. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia Fil: Zaragoza Castells, Joana. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia. University of Exeter; Reino Unido Fil: Malhi, Yadvinder. University of Oxford; Reino Unido

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.

[EN] Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g(-1) for soluble sugars, 6-533 (mean = 94) mg g-1 for starch and 53-649 (mean = 153) mg g-1 for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R-2 = 0.05-0.12 for soluble sugars, 0.10-0.33 for starch and 0.01-0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g-1 for total NSC, compared with the range of laboratory estimates of 596 mg g-1. Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41-0.91), but less so for total NSC (r = 0.45-0.84) and soluble sugars (r = 0.11-0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods., M.G.R. was funded by McMaster fellowship (1158.C). S.P. was funded by Juan de la Cierva contract (MCI project) and project ARBALMONT/786-2012 (OPAN, MAAMA, Spain). F.P. was funded by Fondecyt 11121175. U.N. and M.T. were funded by the Estonian Ministry of Education and Science, grant IUT-8-3. N.G.M. and L.T.D. were funded by DOE-BER. H.D.A. was funded by LANL-LDRD. J.M.-V. was funded by the Spanish Government (CGL 2010-16376). S.H. was funded by the Montana Institute on Ecosystems' Graduate Enhancement Award from NSF EPSCoR Track-1 NSF-IIA-1443108. Valuable comments from Dr Mauricio Mencuccini (University of Edinburgh), Dan Binkley (Colorado State University) and two anonymous reviewers were also greatly appreciated.

We explored the impact of canopy position on leaf respiration (R) and associated traits in tree and shrub species growing in a lowland tropical rainforest in Far North Queensland, Australia. The range of traits quantified included: leaf R in darkness (R-D) and in the light (R-L; estimated using the Kok method); the temperature (T)-sensitivity of R-D; light-saturated photosynthesis (A(sat)); leaf dry mass per unit area (LMA); and concentrations of leaf nitrogen (N), phosphorus (P), soluble sugars and starch. We found that LMA, and area-based N, P, sugars and starch concentrations were all higher in sun-exposed/upper canopy leaves, compared with their shaded/lower canopy and deep-shade/understory counterparts; similarly, area-based rates of R-D, R-L and A(sat) (at 28aEuro...A degrees C) were all higher in the upper canopy leaves, indicating higher metabolic capacity in the upper canopy. The extent to which light inhibited R did not differ significantly between upper and lower canopy leaves, with the overall average inhibition being 32% across both canopy levels. Log-log R-D-A(sat) relationships differed between upper and lower canopy leaves, with upper canopy leaves exhibiting higher rates of R-D for a given A(sat) (both on an area and mass basis), as well as higher mass-based rates of R-D for a given [N] and [P]. Over the 25-45aEuro...A degrees C range, the T-sensitivity of R-D was similar in upper and lower canopy leaves, with both canopy positions exhibiting Q(10) values near 2.0 (i.e., doubling for every 10aEuro...A degrees C rise in T) and T-max values near 60aEuro...A degrees C (i.e., T where R-D reached maximal values). Thus, while rates of R-D at 28aEuro...A degrees C decreased with increasing depth in the canopy, the T-dependence of R-D remained constant; these findings have important implications for vegetation-climate models that seek to predict carbon fluxes between tropical lowland rainforests and the atmosphere.

We tested whether snow gum (Eucalyptus pauciflora) trees growing in thermally contrasting environments exhibit generalizable temperature (T) response functions of leaf respiration (R) and fluorescence (Fo). Measurements were made on pot-grown saplings and field-grown trees (growing between 1380 and 2110 m a.s.l.). Using a continuous, high-resolution protocol, we quantified T response curves of R and Fo--these data were used to identify an algorithm for modelling R-T curves at subcritical T's and establish variations in heat tolerance. For the latter, we quantified Tmax [T where R is maximal] and Tcrit [T where Fo rises rapidly]. Tmax ranged from 51 to 57 °C, varying with season (e.g. winter summer). Tcrit ranged from 41 to 49 °C in summer and from 58 to 63 °C in winter. Thus, surprisingly, leaf energy metabolism was more heat-tolerant in trees experiencing ice-encasement in winter than warmer conditions in summer. A polynomial model fitted to log-transformed R data provided the best description of the T-sensitivity of R (between 10 and 45 °C); using these model fits, we found that the negative slope of the Q10 -T relationship was greater in winter than in summer. Collectively, our results (1) highlight high-T limits of energy metabolism in E. pauciflora and (2) provide a framework for improving representation of T-responses of leaf R in predictive models.

The conventional representation of Plant Functional Types (PFTs) in Dynamic Global Vegetation Models (DGVMs) is increasingly recognized as simplistic and lacking in predictive power. Key ecophysiological traits, including photosynthetic parameters, are typically assigned single values for each PFT while the substantial trait variation within PFTs is neglected. This includes continuous variation in response to environmental factors, and differences linked to spatial and temporal niche differentiation within communities. A much stronger empirical basis is required for the treatment of continuous plant functional trait variation in DGVMs. We analyse 431 sets of measurements of leaf and plant traits, including photosynthetic measurements, on evergreen angiosperm trees in tropical moist forests of Australia and China. Confining attention to tropical moist forests, our analysis identifies trait differences that are linked to vegetation dynamic roles. Coordination theory predicts that Rubisco- and electron-transport limited rates of photosynthesis are co-limiting under field conditions. The least-cost hypothesis predicts that air-to-leaf CO2 drawdown minimizes the combined costs per unit carbon assimilation of maintaining carboxylation and transpiration capacities. Aspects of these predictions are supported for within-community trait variation linked to canopy position, just as they are for variation along spatial environmental gradients. Trait differences among plant species occupying different structural and temporal niches may provide a basis for the ecophysiological representation of vegetation dynamics in next-generation DGVMs.

Owen K. Atkin [et al.].- Received: 8 July 2014, Accepted: 29 November 2014, Leaf dark respiration (Rdark) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of Rdark and associated leaf traits., Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in Rdark., Area-based Rdark at the prevailing average daily growth temperature (T) of each site increased only twofold from the Arctic to the tropics, despite a 20°C increase in growing T (8–28°C). By contrast, Rdark at a standard T (25°C, Rdark25) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher Rdark25 at a given photosynthetic capacity (Vcmax25) or leaf nitrogen concentration ([N]) than species at warmer sites. Rdark25 values at any given Vcmax25 or [N] were higher in herbs than in woody plants., The results highlight variation in Rdark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of Rdark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs).