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Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multi-model comparisons with data have largely focused on individual processes at sub-annual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO2 at multi-decadal and centennial time scales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO2 in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm growing season temperatures while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO2, but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multi-decadal and multi-centennial time scales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO2 in individual models.

Predicted responses of transpiration to elevated atmospheric CO2 concentration (eCO2 ) are highly variable amongst process-based models. To better understand and constrain this variability amongst models, we conducted an intercomparison of 11 ecosystem models applied to data from two forest free-air CO2 enrichment (FACE) experiments at Duke University and Oak Ridge National Laboratory. We analysed model structures to identify the key underlying assumptions causing differences in model predictions of transpiration and canopy water use efficiency. We then compared the models against data to identify model assumptions that are incorrect or are large sources of uncertainty. We found that model-to-model and model-to-observations differences resulted from four key sets of assumptions, namely (i) the nature of the stomatal response to elevated CO2 (coupling between photosynthesis and stomata was supported by the data); (ii) the roles of the leaf and atmospheric boundary layer (models which assumed multiple conductance terms in series predicted more decoupled fluxes than observed at the broadleaf site); (iii) the treatment of canopy interception (large intermodel variability, 2-15%); and (iv) the impact of soil moisture stress (process uncertainty in how models limit carbon and water fluxes during moisture stress). Overall, model predictions of the CO2 effect on WUE were reasonable (intermodel μ = approximately 28% ± 10%) compared to the observations (μ = approximately 30% ± 13%) at the well-coupled coniferous site (Duke), but poor (intermodel μ = approximately 24% ± 6%; observations μ = approximately 38% ± 7%) at the broadleaf site (Oak Ridge). The study yields a framework for analysing and interpreting model predictions of transpiration responses to eCO2 , and highlights key improvements to these types of models.

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO

Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

in Undetermined Results from free-air CO(2) enrichment (FACE) experiments in temperate climates indicate that the response of forest net primary productivity (NPP) to elevated CO(2) might be highly conserved across a broad range of productivities. In this study, we show that the LPJ-GUESS dynamic vegetation model reproduces the magnitude of the NPP enhancement at temperate forest FACE experiments. A global application of the model suggests that the response found in the experiments might also be representative of the average response of forests globally. However, the predicted NPP enhancement in tropical forests is more than twice as high as in boreal forests, suggesting that currently available FACE results are not applicable to these ecosystems. The modeled geographic pattern is to a large extent driven by the temperature dependence of the relative affinities of the primary assimilation enzyme (Rubisco) for CO(2) and O(2). (Less)

Climate change resulting from the enhanced greenhouse effect together with the direct effect of increased atmospheric CO2 concentrations on vegetation growth are expected to produce changes in the cycling of carbon in terrestrial ecosystems. Impacts will vary across Europe, and regional-scale studies are needed to resolve this variability. In this study, we used the LPJ-GUESS ecosystem model driven by a suite of regional climate model (RCM) scenarios from the European Union (EU) project PRUDENCE to estimate climate impacts on carbon cycling across Europe. We identified similarities and discrepancies in simulated climate impacts across scenarios, particularly analyzing the uncertainties arising from the range of climate models and emissions scenarios considered. Our results suggest that net primary production (NPP) and heterotrophic respiration (Rh) will generally increase throughout Europe, but with considerable variation between European subregions. The smallest NPP increases, and in some cases decreases, occurred in the Mediterranean, where many ecosystems switched from sinks to sources of carbon by 2100, mainly as a result of deteriorating water balance. Over the period 1991-2100, modeled climate change impacts on the European carbon balance ranged from a sink of 11.6 Gt C to a source of 3.3 Gt C, the average annual sink corresponding with 1.85% of the current EU anthropogenic emissions. Projected changes in carbon balance were more dependent on the choice of the general circulation model (GCM) providing boundary conditions to the RCM than the choice of RCM or the level of anthropogenic greenhouse gases emissions. (Less)

Land use has greatly transformed Earth's surface. While spatial reconstructions of how the extent of land cover and land-use types have changed during the last century are available, much less information exists about changes in land-use intensity. In particular, global reconstructions that consistently cover land-use intensity across land-use types and ecosystems are missing. We, therefore, lack understanding of how changes in land-use intensity interfere with the natural processes in land systems. To address this research gap, we map land-cover and land-use intensity changes between 1910 and 2010 for 9 points in time. We rely on the indicator framework of human appropriation of net primary production (HANPP) to quantify and map land-use-induced alterations of the carbon flows in ecosystems. We find that, while at the global aggregate level HANPP growth slowed down during the century, the spatial dynamics of changes in HANPP were increasing, with the highest change rates observed in the most recent past. Across all biomes, the importance of changes in land-use areas has declined, with the exception of the tropical biomes. In contrast, increases in land-use intensity became the most important driver of HANPP across all biomes and settings. We conducted uncertainty analyses by modulating input data and assumptions, which indicate that the spatial patterns of land use and potential net primary production are the most critical factors, while spatial allocation rules and uncertainties in overall harvest values play a smaller role. Highlighting the increasing role of land-use intensity compared to changes in the areal extent of land uses, our study supports calls for better integration of the intensity dimension into global analyses and models. On top of that, we provide important empirical input for further analyses of the sustainability of the global land system.