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SummaryLeaf dark respiration (R dark ) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of R dark 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 R dark .Area-based R dark 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, R dark at a standard T (25°C, R dark 25 ) 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 R dark 25 at a given photosynthetic capacity (V cmax 25 ) or leaf nitrogen concentration ([N]) than species at warmer sites. R dark 25 values at any given V cmax 25 or [N] were higher in herbs than in woody plants.The results highlight variation in R dark 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 R dark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs).

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Summary• Gas exchange, fluorescence, western blot and chemical composition analyses were combined to assess if three functional groups (forbs, grasses and evergreen trees/ shrubs) differed in acclimation of leaf respiration ( R ) and photosynthesis ( A ) to a range of growth temperatures (7, 14, 21 and 28 ° C).• When measured at a common temperature, acclimation was greater for R than for A and differed between leaves experiencing a 10-d change in growth temperature (PE) and leaves newly developed at each temperature (ND). As a result, the R : A ratio was temperature dependent, increasing in cold-acclimated plants. The balance was largely restored in ND leaves. Acclimation responses were similar among functional groups.• Across the functional groups, cold acclimation was associated with increases in nonstructural carbohydrates and nitrogen. Cold acclimation of R was associated with an increase in abundance of alternative and/or cytochrome oxidases in a speciesdependent manner. Cold acclimation of A was consistent with an initial decrease and subsequent recovery of thylakoid membrane proteins and increased abundance of proteins involved in the Calvin cycle.• Overall, the results point to striking similarities in the extent and the biochemical underpinning of acclimation of R and A among contrasting functional groups differing in overall rates of metabolism, chemical composition and leaf structure.

The response of plant respiration (R) to temperature is an important component of the biosphere's response to climate change. At present, most global models assume that R increases exponentially with temperature and does not thermally acclimate. Although we now know that acclimation does occur, quantitative incorporation of acclimation into models has been lacking. Using a dataset for 19 species grown at four temperatures (7, 14, 21, and 28 1C), we have assessed whether sustained differences in growth temperature systematically alter the slope and/or intercepts of the generalized log-log plots of leaf R vs. leaf mass per unit leaf area (LMA) and vs. leaf nitrogen (N) concentration. The extent to which variations in growth temperature account for the scatter observed in log-log R-LMA-N scaling relationships was also assessed. We show that thermal history accounts for up to 20% of the scatter in scaling relationships used to predict R, with the impact of thermal history on R-LMA-N generalized scaling relationships being highly predictable. This finding enabled us to quantitatively incorporate acclimation of R into a coupled global climate-vegetation model. We show that accounting for acclimation of R has negligible impact on predicted annual rates of global R, net primary productivity (NPP) or future atmospheric CO 2 concentrations. However, our analysis suggests that accounting for acclimation is important when considering carbon fluxes among thermally contrasting biomes (e.g. accounting for acclimation decreases predicted rates of R by up to 20% in high-temperature biomes). We conclude that acclimation of R needs to be accounted for when predicting potential responses of terrestrial carbon exchange to climatic change at a regional level.

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One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale.