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Leaf dark respiration (R_d) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models.

We hypothesized thatR_dand Rubisco carboxylation capacity (V_cmax) at 25°C (R_d,25,V_cmax,25) are coordinated so thatR_d,25variations supportV_cmax,25at a level allowing full light use, withV_cmax,25reflecting daytime conditions (for photosynthesis), andR_d,25/V_cmax,25reflecting night‐time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5‐yr warming experiment, and spatially using an extensive field‐measurement data set. We compared the results to three published alternatives:R_d,25declines linearly with daily average prior temperature;R_dat average prior night temperatures tends towards a constant value; andR_d,25/V_cmax,25is constant.

Our hypothesis accounted for more variation in observedR_d,25over time (R² = 0.74) and space (R² = 0.68) than the alternatives. Night‐time temperature dominated the seasonal time‐course ofR_d, with an apparent response time scale ofc.2 wk.V_cmaxdominated the spatial patterns.

Our acclimation hypothesis results in a smaller increase in globalR_din response to rising CO₂and warming than is projected by the two of three alternative hypotheses, and by current models.

 

Abstract. Global fire-vegetation models are widely used to assessimpacts of environmental change on fire regimes and the carbon cycle and toinfer relationships between climate, land use and fire. However,differences in model structure and parameterizations, in both the vegetationand fire components of these models, could influence overall modelperformance, and to date there has been limited evaluation of how welldifferent models represent various aspects of fire regimes. The Fire ModelIntercomparison Project (FireMIP) is coordinating the evaluation ofstate-of-the-art global fire models, in order to improve projections of firecharacteristics and fire impacts on ecosystems and human societies in thecontext of global environmental change. Here we perform a systematicevaluation of historical simulations made by nine FireMIP models to quantifytheir ability to reproduce a range of fire and vegetation benchmarks. TheFireMIP models simulate a wide range in global annual total burnt area(39–536 Mha) and global annual fire carbon emission (0.91–4.75 Pg C yr−1) for modern conditions (2002–2012), but most of the range in burntarea is within observational uncertainty (345–468 Mha). Benchmarking scoresindicate that seven out of nine FireMIP models are able to represent thespatial pattern in burnt area. The models also reproduce the seasonality inburnt area reasonably well but struggle to simulate fire season length andare largely unable to represent interannual variations in burnt area.However, models that represent cropland fires see improved simulation offire seasonality in the Northern Hemisphere. The three FireMIP models whichexplicitly simulate individual fires are able to reproduce the spatialpattern in number of fires, but fire sizes are too small in key regions, andthis results in an underestimation of burnt area. The correct representationof spatial and seasonal patterns in vegetation appears to correlate with abetter representation of burnt area. The two older fire models included inthe FireMIP ensemble (LPJ–GUESS–GlobFIRM, MC2) clearly perform less wellglobally than other models, but it is difficult to distinguish between theremaining ensemble members; some of these models are better at representingcertain aspects of the fire regime; none clearly outperforms all othermodels across the full range of variables assessed. 

Abstract Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.