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  • 1
    Publication Date: 2017-07-07
    Description: Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions Scientific Reports, Published online: 6 July 2017; doi:10.1038/s41598-017-03818-2
    Electronic ISSN: 2045-2322
    Topics: Natural Sciences in General
    Published by Springer Nature
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  • 2
    Publication Date: 2016-03-11
    Description: The terrestrial biosphere can release or absorb the greenhouse gases, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), and therefore has an important role in regulating atmospheric composition and climate. Anthropogenic activities such as land-use change, agriculture and waste management have altered terrestrial biogenic greenhouse gas fluxes, and the resulting increases in methane and nitrous oxide emissions in particular can contribute to climate change. The terrestrial biogenic fluxes of individual greenhouse gases have been studied extensively, but the net biogenic greenhouse gas balance resulting from anthropogenic activities and its effect on the climate system remains uncertain. Here we use bottom-up (inventory, statistical extrapolation of local flux measurements, and process-based modelling) and top-down (atmospheric inversions) approaches to quantify the global net biogenic greenhouse gas balance between 1981 and 2010 resulting from anthropogenic activities and its effect on the climate system. We find that the cumulative warming capacity of concurrent biogenic methane and nitrous oxide emissions is a factor of about two larger than the cooling effect resulting from the global land carbon dioxide uptake from 2001 to 2010. This results in a net positive cumulative impact of the three greenhouse gases on the planetary energy budget, with a best estimate (in petagrams of CO2 equivalent per year) of 3.9 +/- 3.8 (top down) and 5.4 +/- 4.8 (bottom up) based on the GWP100 metric (global warming potential on a 100-year time horizon). Our findings suggest that a reduction in agricultural methane and nitrous oxide emissions, particularly in Southern Asia, may help mitigate climate change.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Tian, Hanqin -- Lu, Chaoqun -- Ciais, Philippe -- Michalak, Anna M -- Canadell, Josep G -- Saikawa, Eri -- Huntzinger, Deborah N -- Gurney, Kevin R -- Sitch, Stephen -- Zhang, Bowen -- Yang, Jia -- Bousquet, Philippe -- Bruhwiler, Lori -- Chen, Guangsheng -- Dlugokencky, Edward -- Friedlingstein, Pierre -- Melillo, Jerry -- Pan, Shufen -- Poulter, Benjamin -- Prinn, Ronald -- Saunois, Marielle -- Schwalm, Christopher R -- Wofsy, Steven C -- England -- Nature. 2016 Mar 10;531(7593):225-8. doi: 10.1038/nature16946.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, Alabama 36849, USA. ; Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Iowa 50011, USA. ; Laboratoire des Sciences du Climat et de l'Environnement, 91191 Gif sur Yvette, France. ; Department of Global Ecology, Carnegie Institution for Science, Stanford, California 94305, USA. ; Global Carbon Project, CSIRO Oceans and Atmosphere Research, GPO Box 3023, Canberra, Australian Capital Territory 2601, Australia. ; Department of Environmental Sciences, Emory University, Atlanta, Georgia 30322, USA. ; School of Earth Sciences and Environmental Sustainability, Northern Arizona University, Flagstaff, Arizona 86011, USA. ; School of Life Sciences, Arizona State University, Tempe, Arizona 85287, USA. ; College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK. ; NOAA Earth System Research Laboratory, Global Monitoring Division, Boulder, Colorado 80305, USA. ; Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA. ; College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK. ; The Ecosystems Center, Marine Biological Laboratory, Woods Hole, Massachusetts 02543, USA. ; Institute of Ecosystems and Department of Ecology, Montana State University, Bozeman, Montana 59717, USA. ; Center for Global Change Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. ; Woods Hole Research Center, Falmouth, Massachusetts 02540, USA. ; Department of Earth and Planetary Science, Harvard University, 29 Oxford Street, Cambridge, Massachusetts 02138, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26961656" target="_blank"〉PubMed〈/a〉
    Keywords: Agriculture/statistics & numerical data ; Asia ; Atmosphere/*chemistry ; Carbon Dioxide/analysis/*metabolism ; *Ecosystem ; Global Warming/prevention & control/*statistics & numerical data ; Greenhouse Effect/prevention & control/*statistics & numerical data ; Human Activities/statistics & numerical data ; Methane/analysis/*metabolism ; Nitrous Oxide/analysis/*metabolism
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 2018-07-12
    Description: The contemporary Arctic carbon balance is uncertain, and the potential for a permafrost carbon feedback of anywhere from 50 to 200 petagrams of carbon (Schuur et al ., 2015) compromises accurate 21st-century global climate system projections. The 42-year record of atmospheric CO 2 measurements at Barrow, Alaska (71.29 N, 156.79 W), reveals significant trends in regional land-surface CO 2 anomalies (CO 2 ), indicating long-term changes in seasonal carbon uptake and respiration. Using a carbon balance model constrained by CO 2 , we find a 13.4% decrease in mean carbon residence time (50% confidence range = 9.2 to 17.6%) in North Slope tundra ecosystems during the past four decades, suggesting a transition toward a boreal carbon cycling regime. Temperature dependencies of respiration and carbon uptake suggest that increases in cold season Arctic labile carbon release will likely continue to exceed increases in net growing season carbon uptake under continued warming trends.
    Electronic ISSN: 2375-2548
    Topics: Natural Sciences in General
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  • 4
  • 5
    Publication Date: 2013-12-17
    Description: Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding of land–atmosphere carbon exchange to larger regions. The North American Carbon Program (NACP) Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal model intercomparison and evaluation effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. MsTMIP builds upon current and past synthesis activities, and has a unique framework designed to isolate, interpret, and inform understanding of how model structural differences impact estimates of carbon uptake and release. Here we provide an overview of the MsTMIP effort and describe how the MsTMIP experimental design enables the assessment and quantification of TBM structural uncertainty. Model structure refers to the types of processes considered (e.g., nutrient cycling, disturbance, lateral transport of carbon), and how these processes are represented (e.g., photosynthetic formulation, temperature sensitivity, respiration) in the models. By prescribing a common experimental protocol with standard spin-up procedures and driver data sets, we isolate any biases and variability in TBM estimates of regional and global carbon budgets resulting from differences in the models themselves (i.e., model structure) and model-specific parameter values. An initial intercomparison of model structural differences is represented using hierarchical cluster diagrams (a.k.a. dendrograms), which highlight similarities and differences in how models account for carbon cycle, vegetation, energy, and nitrogen cycle dynamics. We show that, despite the standardized protocol used to derive initial conditions, models show a high degree of variation for GPP, total living biomass, and total soil carbon, underscoring the influence of differences in model structure and parameterization on model estimates.
    Print ISSN: 1991-959X
    Electronic ISSN: 1991-9603
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 6
    Publication Date: 2010-10-29
    Description: Given the large differences between biospheric model estimates of regional carbon exchange, there is a need to understand and reconcile the predicted spatial variability of fluxes across models. This paper presents a set of quantitative tools that can be applied for comparing flux estimates in light of the inherent differences in model formulation. The presented methods include variogram analysis, variable selection, and geostatistical regression. These methods are evaluated in terms of their ability to assess and identify differences in spatial variability in flux estimates across North America among a small subset of models, as well as differences in the environmental drivers that appear to have the greatest control over the spatial variability of predicted fluxes. The examined models are the Simple Biosphere (SiB 3.0), Carnegie Ames Stanford Approach (CASA), and CASA coupled with the Global Fire Emissions Database (CASA GFEDv2), and the analyses are performed on model-predicted net ecosystem exchange, gross primary production, and ecosystem respiration. Variogram analysis reveals consistent seasonal differences in spatial variability among modeled fluxes at a 1°×1° spatial resolution. However, significant differences are observed in the overall magnitude of the carbon flux spatial variability across models, in both net ecosystem exchange and component fluxes. Results of the variable selection and geostatistical regression analyses suggest fundamental differences between the models in terms of the factors that control the spatial variability of predicted flux. For example, carbon flux is more strongly correlated with percent land cover in CASA GFEDv2 than in SiB or CASA. Some of these factors can be linked back to model formulation, and would have been difficult to identify simply by comparing net fluxes between models. Overall, the quantitative approach presented here provides a set of tools for comparing predicted grid-scale fluxes across models, a task that has historically been difficult unless standardized forcing data were prescribed or a detailed sensitivity analysis was performed.
    Print ISSN: 1810-6277
    Electronic ISSN: 1810-6285
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 7
    Publication Date: 2014-07-17
    Description: Scientific understanding of the global carbon cycle is required for developing national and international policy to mitigate fossil-fuel CO2 emissions by managing terrestrial carbon uptake. Toward that understanding and as a contribution to the REgional Carbon Cycle Assessment and Processes (RECCAP) project, this paper provides a synthesis of net land–atmosphere CO2 exchange for North America over the period (1990–2009). This synthesis is based on results from three different methods: atmospheric inversion, inventory-based methods and terrestrial biosphere modeling. All methods indicate that the North America land surface was a sink for atmospheric CO2, with a net transfer from atmosphere to land. Estimates ranged from −890 to −280 Tg C yr−1, where the atmospheric inversion estimate forms the lower bound of that range (a larger land-sink) and the inventory-based estimate the upper (a smaller land sink). Integrating across estimates, "best" estimates (i.e., measures of central tendency) are −472 ± 281 Tg C yr−1 based on the mean and standard deviation of the distribution and −360 Tg C yr−1 (with an interquartile range of −496 to −337) based on the median. Considering both the fossil-fuel emissions source and the land sink, our analysis shows that North America was, however, a net contributor to the growth of CO2 in the atmosphere in the late 20th and early 21st century. The continent's CO2 source to sink ratio for this time period was likely in the range of 4 : 1 to 3 : 1.
    Print ISSN: 1810-6277
    Electronic ISSN: 1810-6285
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 8
    Publication Date: 2014-02-20
    Description: Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for Alaska, we provide a baseline of terrestrial carbon cycle structural and parametric uncertainty, defined as the multi-model standard deviation (σ) against the mean (x) for each quantity. Mean annual uncertainty (σ/x) was largest for net ecosystem exchange (NEE) (−0.01± 0.19 kg C m−2 yr−1), then net primary production (NPP) (0.14 ± 0.33 kg C m−2 yr−1), autotrophic respiration (Ra) (0.09 ± 0.20 kg C m−2 yr−1), gross primary production (GPP) (0.22 ± 0.50 kg C m−2 yr−1), ecosystem respiration (Re) (0.23 ± 0.38 kg C m−2 yr−1), CH4 flux (2.52 ± 4.02 g CH4 m−2 yr−1), heterotrophic respiration (Rh) (0.14 ± 0.20 kg C m−2 yr−1), and soil carbon (14.0± 9.2 kg C m−2). The spatial patterns in regional carbon stocks and fluxes varied widely with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as carbon neutral. Additionally, a feedback (i.e., sensitivity) analysis was conducted of 20th century NEE to CO2 fertilization (β) and climate (γ), which showed that uncertainty in γ was 2x larger than that of β, with neither indicating that the Alaskan Arctic is shifting towards a certain net carbon sink or source. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic.
    Print ISSN: 1810-6277
    Electronic ISSN: 1810-6285
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 9
    Publication Date: 2011-07-11
    Description: Robust estimates of regional-scale terrestrial CO2 exchange are needed to support carbon management policies and to improve the predictive ability of models representing carbon-climate feedbacks. Large discrepancies remain, however, both among and between CO2 flux estimates from atmospheric inverse models and terrestrial biosphere models. Improved atmospheric inverse models that provide robust estimates at sufficiently fine spatial scales could prove especially useful for monitoring efforts, while also serving as a validation tool for process-based assumptions in terrestrial biosphere models. A growing network of continental sites collecting continuous CO2 measurements provides the information needed to drive such models. This study presents results from a regional geostatistical inversion over North America for 2004, taking advantage of continuous data from the nine sites operational in that year, as well as available flask and aircraft observations. The approach does not require explicit prior flux estimates, resolves fluxes at finer spatiotemporal scales than previous North American inversion studies, and uses a Lagrangian transport model coupled with high-resolution winds (i.e. WRF-STILT) to resolve near-field influences around measurement locations. The estimated fluxes are used in an inter-comparison with other inversion studies and a suite of terrestrial biosphere model estimates collected through the North American Carbon Program Regional and Continental Interim Synthesis. Differences among inversions are found to be smallest in areas of the continent best-constrained by the atmospheric data, pointing to the value of an expanded measurement network. Aggregation errors in previous coarser-scale inversion studies are likely to explain a portion of the remaining spread. The spatial patterns from a geostatistical inversion that includes auxiliary environmental variables from the North American Regional Reanalysis were similar to those from the median of the biospheric model estimates during the growing season, but diverged more strongly in the dormant season. This could be due to a lack of sensitivity in the inversion during the dormant season, but may also point to a lack of skill in the biospheric models outside of the growing season, particularly in agricultural areas. For the annual continental budget, the boundary conditions used as an input into the inversions were seen to have a substantial impact on the estimated net flux, with a difference of ~0.8 PgC yr−1 associated with results using two different plausible sets of boundary conditions.
    Print ISSN: 1810-6277
    Electronic ISSN: 1810-6285
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 10
    Publication Date: 2011-06-21
    Description: Given the large differences between biospheric model estimates of regional carbon exchange, there is a need to understand and reconcile the predicted spatial variability of fluxes across models. This paper presents a set of quantitative tools that can be applied to systematically compare flux estimates despite the inherent differences in model formulation. The presented methods include variogram analysis, variable selection, and geostatistical regression. These methods are evaluated in terms of their ability to assess and identify differences in spatial variability in flux estimates across North America among a small subset of models, as well as differences in the environmental drivers that best explain the spatial variability of predicted fluxes. The examined models are the Simple Biosphere (SiB 3.0), Carnegie Ames Stanford Approach (CASA), and CASA coupled with the Global Fire Emissions Database (CASA GFEDv2), and the analyses are performed on model-predicted net ecosystem exchange, gross primary production, and ecosystem respiration. Variogram analysis reveals consistent seasonal differences in spatial variability among modeled fluxes at a 1° × 1° spatial resolution. However, significant differences are observed in the overall magnitude of the carbon flux spatial variability across models, in both net ecosystem exchange and component fluxes. Results of the variable selection and geostatistical regression analyses suggest fundamental differences between the models in terms of the factors that explain the spatial variability of predicted flux. For example, carbon flux is more strongly correlated with percent land cover in CASA GFEDv2 than in SiB or CASA. Some of the differences in spatial patterns of estimated flux can be linked back to differences in model formulation, and would have been difficult to identify simply by comparing net fluxes between models. Overall, the systematic approach presented here provides a set of tools for comparing predicted grid-scale fluxes across models, a task that has historically been difficult unless standardized forcing data were prescribed, or a detailed sensitivity analysis performed.
    Print ISSN: 1726-4170
    Electronic ISSN: 1726-4189
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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