Le Quéré C., Andrew R.M., Friedlingstein P., Sitch S., Pongratz J., Manning A.C., Ivar Korsbakken J., Peters G.P., Canadell J.G., Jackson R.B., Boden T.A., Tans P.P., Andrews O.D., Arora V.K., Bakker D.C.E., Barbero L., Becker M., Betts R.A., Bopp L., Chevallier F., Chini L.P., Ciais P., Cosca C.E., Cross J., Currie K., Gasser T., Harris I., Hauck J., Haverd V., Houghton R.A., Hunt C.W., Hurtt G., Ilyina T., Jain A.K., Kato E., Kautz M., Keeling R.F., Klein Goldewijk K., Körtzinger A., Landschützer P., Lefèvre N., Lenton A., Lienert S., Lima I., Lombardozzi D., Metzl N., Millero F., Monteiro P.M.S., Munro D.R., Nabel J.E.M.S., Nakaoka S.-I., Nojiri Y., Antonio Padin X., Peregon A., Pfeil B., Pierrot D., Poulter B., Rehder G., Reimer J., Rödenbeck C., Schwinger J., Séférian R., Skjelvan I., Stocker B.D., Tian H., Tilbrook B., Tubiello F.N., Laan-Luijkx I.T.V., Werf G.R.V., Van Heuven S., Viovy N., Vuichard N., Walker A.P., Watson A.J., Wiltshire A.J., Zaehle S., Zhu D. (2018) Global Carbon Budget 2017. Earth System Science Data. 10: 405-448.LinkDoi: 10.5194/essd-10-405-2018
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere-the "global carbon budget"-is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1δ. For the last decade available (2007-2016), EFF was 9.4±0.5 GtC yr-1, ELUC 1.3±0.7 GtC yr-1, GATM 4.7±0.1 GtC yr-1, SOCEAN 2.4±0.5 GtC yr-1, and SLAND 3.0±0.8 GtC yr-1, with a budget imbalance BIM of 0.6 GtC yr-1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9±0.5 GtC yr-1. Also for 2016, ELUC was 1.3±0.7 GtC yr-1, GATM was 6.1±0.2 GtC yr-1, SOCEAN was 2.6±0.5 GtC yr-1, and SLAND was 2.7±1.0 GtC yr-1, with a small BIM of-0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007-2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ninõ conditions. The global atmospheric CO2 concentration reached 402.8±0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6-9 months indicate a renewed growth in EFF of C2.0% (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017). © 2018 Author(s).
Stocker B.D., Zscheischler J., Keenan T.F., Prentice I.C., Peñuelas J., Seneviratne S.I. (2018) Quantifying soil moisture impacts on light use efficiency across biomes. New Phytologist. 218: 1430-1449.LinkDoi: 10.1111/nph.15123
Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust
Terrer, C., Vicca, S., Stocker, B.D., Hungate, B.A., Phillips, R.P., Reich, P.B., Finzi, A.C., Prentice, I.C. (2018) Ecosystem responses to elevated CO2governed by plant–soil interactions and the cost of nitrogen acquisition. New Phytologist. 217: 507-522.LinkDoi: 10.1111/nph.14872
Vicca S., Stocker B.D., Reed S., Wieder W.R., Bahn M., Fay P.A., Janssens I.A., Lambers H., Peñuelas J., Piao S., Rebel K.T., Sardans J., Sigurdsson B.D., Van Sundert K., Wang Y.-P., Zaehle S., Ciais P. (2018) Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling. Environmental Research Letters. 13: 0-0.LinkDoi: 10.1088/1748-9326/aaeae7
A wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities. © 2018 The Author(s). Published by IOP Publishing Ltd.
Wang Y., Ciais P., Goll D., Huang Y., Luo Y., Wang Y.-P., Bloom A.A., Broquet G., Hartmann J., Peng S., Penuelas J., Piao S., Sardans J., Stocker B.D., Wang R., Zaehle S., Zechmeister-Boltenstern S. (2018) GOLUM-CNP v1.0: A data-driven modeling of carbon, nitrogen and phosphorus cycles in major terrestrial biomes. Geoscientific Model Development. 11: 3903-3928.LinkDoi: 10.5194/gmd-11-3903-2018
Global terrestrial nitrogen (N) and phosphorus (P) cycles are coupled to the global carbon (C) cycle for net primary production (NPP), plant C allocation, and decomposition of soil organic matter, but N and P have distinct pathways of inputs and losses. Current C-nutrient models exhibit large uncertainties in their estimates of pool sizes, fluxes, and turnover rates of nutrients, due to a lack of consistent global data for evaluating the models. In this study, we present a new model-data fusion framework called the Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines the CARbon DAta MOdel fraMework (CARDAMOM) data-constrained C-cycle analysis with spatially explicit data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. We calculated the steady-state N- and P-pool sizes and fluxes globally for large biomes. Our study showed that new N inputs from biological fixation and deposition supplied > 20 % of total plant uptake in most forest ecosystems but accounted for smaller fractions in boreal forests and grasslands. New P inputs from atmospheric deposition and rock weathering supplied a much smaller fraction of total plant uptake than new N inputs, indicating the importance of internal P recycling within ecosystems to support plant growth. Nutrient-use efficiency, defined as the ratio of gross primary production (GPP) to plant nutrient uptake, were diagnosed from our model results and compared between biomes. Tropical forests had the lowest N-use efficiency and the highest P-use efficiency of the forest biomes. An analysis of sensitivity and uncertainty indicated that the NPP-allocation fractions to leaves, roots, and wood contributed the most to the uncertainties in the estimates of nutrient-use efficiencies. Correcting for biases in NPP-allocation fractions produced more plausible gradients of N- and P-use efficiencies from tropical to boreal ecosystems and highlighted the critical role of accurate measurements of C allocation for understanding the N and P cycles. © Author(s) 2018.
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