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The Global Carbon Project (GCP) has published global carbon budgets annually since 2007 (Canadell et al. [2007], Proc Natl Acad Sci USA, 104, 18866-18870; Raupach et al. [2007], Proc Natl Acad Sci USA, 104, 10288-10293). There are many scientists involved, but the terrestrial fluxes that appear in the budgets are not well understood by ecologists and biogeochemists outside of that community. The purpose of this paper is to make the terrestrial fluxes of carbon in those budgets more accessible to a broader community. The GCP budget is composed of annual perturbations from pre-industrial conditions, driven by addition of carbon to the system from combustion of fossil fuels and by transfers of carbon from land to the atmosphere as a result of land use. The budget includes a term for each of the major fluxes of carbon (fossil fuels, oceans, land) as well as the rate of carbon accumulation in the atmosphere. Land is represented by two terms: one resulting from direct anthropogenic effects (Land Use, Land-Use Change, and Forestry or land management) and one resulting from indirect anthropogenic (e.g., CO2 , climate change) and natural effects. Each of these two net terrestrial fluxes of carbon, in turn, is composed of opposing gross emissions and removals (e.g., deforestation and forest regrowth). Although the GCP budgets have focused on the two net terrestrial fluxes, they have paid little attention to the gross components, which are important for a number of reasons, including understanding the potential for land management to remove CO2 from the atmosphere and understanding the processes responsible for the sink for carbon on land. In contrast to the net fluxes of carbon, which are constrained by the global carbon budget, the gross fluxes are largely unconstrained, suggesting that there is more uncertainty than commonly believed about how terrestrial carbon emissions will respond to future fossil fuel emissions and a changing climate.

As human activity continues to increase CO2 and O3, broad expanses of north temperate forests will be simultaneously exposed to elevated concentrations of these trace gases. Although both CO2 and O3 are potent modifiers of plant growth, we do not understand the extent to which they alter competition for limiting soil nutrients, like nitrogen (N). We quantified the acquisition of soil N in two 8-year-old communities composed of trembling aspen genotypes (n 55) and trembling aspen‐paper birch which were exposed to factorial combinations of CO2 (ambient and 560lLL � 1 ) and O3 (ambient 530‐40 vs. 50‐60nLL � 1 ). Tracer amount of 15 NH4 1 were applied to soil to determine how these trace gases altered the competitive ability of genotypes and species to acquire soil N. One year after isotope addition, we assessed N acquisition by measuring the amount of 15 N tracer contained in the plant canopy (i.e. recent N acquisition), as well as the total amount of canopy N (i.e. cumulative N acquisition). Exposure to elevated CO2 differentially altered recent and cumulative N acquisition among aspen genotypes, changing the rank order in which they obtained soil N. Elevated O3 also altered the rank order in which aspen genotypes obtained soil N by eliciting increases, decreases and no response among genotypes. If aspen genotypes respond similarly under field conditions, then rising concentrations of CO2 and O3 could alter the structure of aspen populations. In the aspen‐birch community, elevated CO2 increased recent N (i.e. 15 N) acquisition in birch (68%) to a greater extent than aspen (19%), suggesting that, over the course of this experiment, birch had gained a competitive advantage over aspen. The response of genotypes and species to rising CO2 and O3 concentrations, and how these responses are modified by competitive interactions, has the potential to change the future composition and productivity of northern temperate forests.

International audience; This paper examines long-term eddy covariance data from 18 European and 17 North American and Asian forest, wetland, tundra, grassland, and cropland sites under nonwater- stressed conditions with an empirical rectangular hyperbolic light response model and a single layer two light-class carboxylase-based model. Relationships according to ecosystem functional type are demonstrated between empirical and physiological parameters, suggesting linkages between easily estimated parameters and those with greater potential for process interpretation. Relatively sparse documentation of leaf area index dynamics at flux tower sites is found to be a major difficulty in model inversion and flux interpretation. Therefore, a simplification of the physiological model is carried out for a subset of European network sites with extensive ancillary data. The results from these selected sites are used to derive a new parameter and means for comparing empirical and physiologically based methods across all sites, regardless of ancillary data. The results from the European analysis are then compared with results from the other Northern Hemisphere sites and similar relationships for the simplified process-based parameter were found to hold for European, North American, and Asian temperate and boreal climate zones. This parameter is useful for bridging between flux network observations and continental scale spatial simulations of vegetation/atmosphere carbon dioxide exchange

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO2 between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO2 release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO2 fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co‐acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data‐driven approach based on combined neural networks (NNC‐part). NNC‐part incorporates process knowledge by introducing a photosynthetic response based on the light‐use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R 2 > .94) and RECO (R 2 > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NNC‐part performed more realistic than the traditional methods for predicting additional patterns of gross CO2 fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO2 fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NNC‐part is a valid data‐driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods., In this paper, we present an innovative neural network (NNC‐part) for partitioning net ecosystem exchange of CO2, measured by eddy covariance over land ecosystems, into ecosystem respiration (RECO) and gross primary production (GPP). NNC‐part has a hybrid nature for assimilating the light‐use efficiency (LUE) concept. The GPP and RECO produced by NNC‐part resulted consistent with estimates provided in FLUXNET2015 and patterns of fluxes very realistic, being the method able to reproduce: the GPP and RECO response to meteorological forces; hysteresis in the diel cycle of fluxes; effect of diffuse to direct radiation ratio on LUE, respiration pulse.