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1. Contrasting effects of CO2 fertilization, land-use change and warming on seasonal amplitude of Northern Hemisphere CO2 exchange

Author: A. Bastos, P. Ciais, F. Chevallier, C. Rödenbeck, A. P. Ballantyne, F. Maignan, Y. Yin, M. Fernández-Martínez, P. Friedlingstein, J. Peñuelas, S. L. Piao, S. Sitch, W. K. Smith, X. Wang, Z. Zhu, V. Haverd, E. Kato, A. K. Jain, S. Lienert, D. Lombardozzi, J. E. M. S. Nabel, P. Peylin, B. Poulter, and D. Zhu
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Continuous atmospheric CO2 monitoring data indicate an increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) in northern high latitudes. The major drivers of enhanced SCANBP remain unclear and intensely debated, with land-use change, CO2 fertilization and warming being identified as likely contributors. We integrated CO2-flux data from two atmospheric inversions (consistent with atmospheric records) and from 11 state-of-the-art land-surface models (LSMs) to evaluate the relative importance of individual contributors to trends and drivers of the SCANBP of CO2 fluxes for 1980–2015. The LSMs generally reproduce the latitudinal increase in SCANBP trends within the inversions range. Inversions and LSMs attribute SCANBP increase to boreal Asia and Europe due to enhanced vegetation productivity (in LSMs) and point to contrasting effects of CO2 fertilization (positive) and warming (negative) on SCANBP. Our results do not support land-use change as a key contributor to the increase in SCANBP. The sensitivity of simulated microbial respiration to temperature in LSMs explained biases in SCANBP trends, which suggests that SCANBP could help to constrain model turnover times.
Published: 2019
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2. Improvement of the Irrigation Scheme in the ORCHIDEE Land Surface Model and Impacts of Irrigation on Regional Water Budgets Over China

Author: Z. Yin, X. H. Wang, C. Ottlé, F. Zhou, M. Guimberteau, J. Polcher, S. S. Peng, S. L. Piao, L. Li, Y. Bo, X. L. Chen, X. D. Zhou, H. Kim, and P. Ciais
Subjects: irrigation model, paddy irrigation, irrigation water withdrawal, crops, local climate, total water storage, Physical geography, GB3-5030, Oceanography, GC1-1581
Abstract: Abstract In China, irrigation is widespread in 40.7% cropland to sustain crop yields. By its action on water cycle, irrigation affects water resources and local climate. In this study, a new irrigation module, including flood and paddy irrigation technologies, was developed in the ORCHIDEE‐CROP land surface model which describes crop phenology and growth in order to estimate irrigation demands over China from 1982 to 2014. Three simulations were performed including NI (no irrigation), IR (with irrigation limited by local water resources), and FI (with irrigation demand fulfilled). Observations and census data were used to validate the simulations. Results showed that the estimated irrigation water withdrawal ( W) based on IR and FI scenarios bracket statistical W with fair spatial agreements ( r=0.68±0.07; p
Published: 2020
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3. How have past fire disturbances contributed to the current carbon balance of boreal ecosystems?

Author: C. Yue, P. Ciais, D. Zhu, T. Wang, S. S. Peng, and S. L. Piao
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Boreal fires have immediate effects on regional carbon budgets by emitting CO2 into the atmosphere at the time of burning, but they also have legacy effects by initiating a long-term carbon sink during post-fire vegetation recovery. Quantifying these different effects on the current-day pan-boreal (44–84° N) carbon balance and quantifying relative contributions of legacy sinks by past fires is important for understanding and predicting the carbon dynamics in this region. Here we used the global dynamic vegetation model ORCHIDEE–SPITFIRE (Organising Carbon and Hydrology In Dynamic Ecosystems – SPread and InTensity of FIRE) to attribute the contributions by fires in different decades between 1850 and 2009 to the carbon balance of 2000–2009, taking into account the atmospheric CO2 change and climate change since 1850. The fire module of ORCHIDEE–SPITFIRE was turned off for each decade in turn and was also turned off before and after the decade in question in order to model the legacy carbon trajectory by fires in each past decade. We found that, unsurprisingly, fires that occurred in 2000–2009 are a carbon source (−0.17 Pg C yr−1) for the carbon balance of 2000–2009, whereas fires in all decades before 2000 contribute carbon sinks with a collective contribution of 0.23 Pg C yr−1. This leaves a net fire sink effect of 0.06 Pg C yr−1, or 6.3 % of the simulated regional carbon sink (0.95 Pg C yr−1). Further, fires with an age of 10–40 years (i.e., those that occurred during 1960–1999) contribute more than half of the total sink effect of fires. The small net sink effect of fires indicates that current-day fire emissions are roughly balanced out by legacy sinks. The future role of fires in the regional carbon balance remains uncertain and will depend on whether changes in fires and associated carbon emissions will exceed the enhanced sink effects of previous fires, both being strongly affected by global change.
Published: 2016
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4. Wet deposition of atmospheric inorganic nitrogen at five remote sites in the Tibetan Plateau

Author: Y. W. Liu, Xu-Ri, Y. S. Wang, Y. P. Pan, and S. L. Piao
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: Since the mid-20th century, nitrogen (N) deposition has shown an increasing trend in the Tibetan Plateau (TP), where alpine ecosystems are sensitive to elevated N deposition. However, the quantitative characterization of N deposition in the TP remains unclear, due in most part to the lack of in situ measurement. Using the Tibetan Observation and Research Platform network, we conducted short-term in situ measurements of major ions (NO3−, Cl−, SO42−, NH4+, Na+, K+, Ca2+, and Mg2+) wet deposition at five remote sites in the TP during 2011–2013. At Southeast Tibet Station, Nam Co Station, Qomolangma Station, Ngari Station, and Muztagh Ata Station, the NH4+–N wet deposition was 0.63, 0.68, 0.92, 0.36, and 1.25 kg N ha−1 yr−1, respectively; the NO3−–N wet deposition was 0.28, 0.24, 0.03, 0.08, and 0.30 kg N ha−1 yr−1, respectively; and the inorganic N wet deposition was 0.91, 0.92, 0.94, 0.44, and 1.55 kg N ha−1 yr−1, respectively. The inorganic N wet deposition mainly occurred in the form of NH4+–N during summer at all sites. Results of enrichment factor analysis and principal component analysis demonstrated that both NH4+–N and NO3−–N wet deposition in the TP were mainly influenced by anthropogenic activities. Backward trajectory analysis showed that the inorganic N deposition at Muztagh Ata Station was mainly transported from central Asia and the Middle East through westerlies. At Southeast Tibet Station, Nam Co Station, Qomolangma Station, and Ngari Station, the inorganic N deposition was mainly contributed by anthropogenic sources in south Asia, and was mainly transported by the Indian monsoon. Combining site-scale in situ measurements of inorganic N wet deposition in this and previous studies, the average wet deposition of atmospheric NH4+–N, NO3−–N, and inorganic N in the TP was estimated to be 1.06, 0.51, and 1.58 kg N ha−1 yr−1, respectively. The average NH4+–N : NO3−–N ratio in precipitation in the TP was approximately 2 : 1. Results from the present study suggest that earlier estimations based on chemical transport model simulations and/or limited field measurements likely overestimated substantially the regional inorganic N wet deposition in the TP. To clarify the total N deposition in the TP more clearly, it is essential to conduct long-term monitoring of both wet and dry deposition of atmospheric N in various climate zones in the TP in the future.
Published: 2015
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5. Improving the dynamics of Northern Hemisphere high-latitude vegetation in the ORCHIDEE ecosystem model

Author: D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko
Subjects: Geology, QE1-996.5
Abstract: Processes that describe the distribution of vegetation and ecosystem succession after disturbance are an important component of dynamic global vegetation models (DGVMs). The vegetation dynamics module (ORC-VD) within the process-based ecosystem model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) has not been updated and evaluated since many years and is known to produce unrealistic results. This study presents a new parameterization of ORC-VD for mid- to high-latitude regions in the Northern Hemisphere, including processes that influence the existence, mortality and competition between tree functional types. A new set of metrics is also proposed to quantify the performance of ORC-VD, using up to five different data sets of satellite land cover, forest biomass from remote sensing and inventories, a data-driven estimate of gross primary productivity (GPP) and two gridded data sets of soil organic carbon content. The scoring of ORC-VD derived from these metrics integrates uncertainties in the observational data sets. This multi-data set evaluation framework is a generic method that could be applied to the evaluation of other DGVM models. The results of the original ORC-VD published in 2005 for mid- to high-latitudes and of the new parameterization are evaluated against the above-described data sets. Significant improvements were found in the modeling of the distribution of tree functional types north of 40° N. Three additional sensitivity runs were carried out to separate the impact of different processes or drivers on simulated vegetation distribution, including soil freezing which limits net primary production through soil moisture availability in the root zone, elevated CO2 concentration since 1850, and the effects of frequency and severity of extreme cold events during the spin-up phase of the model.
Published: 2015
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6. Recent trends and drivers of regional sources and sinks of carbon dioxide

Author: S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: The land and ocean absorb on average just over half of the anthropogenic emissions of carbon dioxide (CO2) every year. These CO2 "sinks" are modulated by climate change and variability. Here we use a suite of nine dynamic global vegetation models (DGVMs) and four ocean biogeochemical general circulation models (OBGCMs) to estimate trends driven by global and regional climate and atmospheric CO2 in land and oceanic CO2 exchanges with the atmosphere over the period 1990–2009, to attribute these trends to underlying processes in the models, and to quantify the uncertainty and level of inter-model agreement. The models were forced with reconstructed climate fields and observed global atmospheric CO2; land use and land cover changes are not included for the DGVMs. Over the period 1990–2009, the DGVMs simulate a mean global land carbon sink of −2.4 ± 0.7 Pg C yr−1 with a small significant trend of −0.06 ± 0.03 Pg C yr−2 (increasing sink). Over the more limited period 1990–2004, the ocean models simulate a mean ocean sink of −2.2 ± 0.2 Pg C yr−1 with a trend in the net C uptake that is indistinguishable from zero (−0.01 ± 0.02 Pg C yr−2). The two ocean models that extended the simulations until 2009 suggest a slightly stronger, but still small, trend of −0.02 ± 0.01 Pg C yr−2. Trends from land and ocean models compare favourably to the land greenness trends from remote sensing, atmospheric inversion results, and the residual land sink required to close the global carbon budget. Trends in the land sink are driven by increasing net primary production (NPP), whose statistically significant trend of 0.22 ± 0.08 Pg C yr−2 exceeds a significant trend in heterotrophic respiration of 0.16 ± 0.05 Pg C yr−2 – primarily as a consequence of widespread CO2 fertilisation of plant production. Most of the land-based trend in simulated net carbon uptake originates from natural ecosystems in the tropics (−0.04 ± 0.01 Pg C yr−2), with almost no trend over the northern land region, where recent warming and reduced rainfall offsets the positive impact of elevated atmospheric CO2 and changes in growing season length on carbon storage. The small uptake trend in the ocean models emerges because climate variability and change, and in particular increasing sea surface temperatures, tend to counter\-act the trend in ocean uptake driven by the increase in atmospheric CO2. Large uncertainty remains in the magnitude and sign of modelled carbon trends in several regions, as well as regarding the influence of land use and land cover changes on regional trends.
Published: 2015
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7. Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system

Author: P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.
Published: 2014
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8. Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model

Author: C. Yue, P. Ciais, S. Luyssaert, P. Cadule, J. Harden, J. Randerson, V. Bellassen, T. Wang, S. L. Piao, B. Poulter, and N. Viovy
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Stand-replacing fires are the dominant fire type in North American boreal forests. They leave a historical legacy of a mosaic landscape of different aged forest cohorts. This forest age dynamics must be included in vegetation models to accurately quantify the role of fire in the historical and current regional forest carbon balance. The present study adapted the global process-based vegetation model ORCHIDEE to simulate the CO2 emissions from boreal forest fire and the subsequent recovery after a stand-replacing fire; the model represents postfire new cohort establishment, forest stand structure and the self-thinning process. Simulation results are evaluated against observations of three clusters of postfire forest chronosequences in Canada and Alaska. The variables evaluated include: fire carbon emissions, CO2 fluxes (gross primary production, total ecosystem respiration and net ecosystem exchange), leaf area index, and biometric measurements (aboveground biomass carbon, forest floor carbon, woody debris carbon, stand individual density, stand basal area, and mean diameter at breast height). When forced by local climate and the atmospheric CO2 history at each chronosequence site, the model simulations generally match the observed CO2 fluxes and carbon stock data well, with model-measurement mean square root of deviation comparable with the measurement accuracy (for CO2 flux ~100 g C m−2 yr−1, for biomass carbon ~1000 g C m−2 and for soil carbon ~2000 g C m−2). We find that the current postfire forest carbon sink at the evaluation sites, as observed by chronosequence methods, is mainly due to a combination of historical CO2 increase and forest succession. Climate change and variability during this period offsets some of these expected carbon gains. The negative impacts of climate were a likely consequence of increasing water stress caused by significant temperature increases that were not matched by concurrent increases in precipitation. Our simulation results demonstrate that a global vegetation model such as ORCHIDEE is able to capture the essential ecosystem processes in fire-disturbed boreal forests and produces satisfactory results in terms of both carbon fluxes and carbon-stock evolution after fire. This makes the model suitable for regional simulations in boreal regions where fire regimes play a key role in the ecosystem carbon balance.
Published: 2013
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9. High-resolution mapping of combustion processes and implications for CO2 emissions

Author: R. Wang, S. Tao, P. Ciais, H. Z. Shen, Y. Huang, H. Chen, G. F. Shen, B. Wang, W. Li, Y. Y. Zhang, Y. Lu, D. Zhu, Y. C. Chen, X. P. Liu, W. T. Wang, X. L. Wang, W. X. Liu, B. G. Li, and S. L. Piao
Subjects: Physics, QC1-999, Chemistry, QD1-999
Abstract: High-resolution mapping of fuel combustion and CO2 emission provides valuable information for modeling pollutant transport, developing mitigation policy, and for inverse modeling of CO2 fluxes. Previous global emission maps included only few fuel types, and emissions were estimated on a grid by distributing national fuel data on an equal per capita basis, using population density maps. This process distorts the geographical distribution of emissions within countries. In this study, a sub-national disaggregation method (SDM) of fuel data is applied to establish a global 0.1° × 0.1° geo-referenced inventory of fuel combustion (PKU-FUEL) and corresponding CO2 emissions (PKU-CO2) based upon 64 fuel sub-types for the year 2007. Uncertainties of the emission maps are evaluated using a Monte Carlo method. It is estimated that CO2 emission from combustion sources including fossil fuel, biomass, and solid wastes in 2007 was 11.2 Pg C yr−1 (9.1 Pg C yr−1 and 13.3 Pg C yr−1 as 5th and 95th percentiles). Of this, emission from fossil fuel combustion is 7.83 Pg C yr−1, which is very close to the estimate of the International Energy Agency (7.87 Pg C yr−1). By replacing national data disaggregation with sub-national data in this study, the average 95th minus 5th percentile ranges of CO2 emission for all grid points can be reduced from 417 to 68.2 Mg km−2 yr−1. The spread is reduced because the uneven distribution of per capita fuel consumptions within countries is better taken into account by using sub-national fuel consumption data directly. Significant difference in per capita CO2 emissions between urban and rural areas was found in developing countries (2.08 vs. 0.598 Mg C/(cap. × yr)), but not in developed countries (3.55 vs. 3.41 Mg C/(cap. × yr)). This implies that rapid urbanization of developing countries is very likely to drive up their emissions in the future.
Published: 2013
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10. The carbon budget of South Asia

Author: P. K. Patra, J. G. Canadell, R. A. Houghton, S. L. Piao, N.-H. Oh, P. Ciais, K. R. Manjunath, A. Chhabra, T. Wang, T. Bhattacharya, P. Bousquet, J. Hartman, A. Ito, E. Mayorga, Y. Niwa, P. A. Raymond, V. V. S. S. Sarma, and R. Lasco
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: The source and sinks of carbon dioxide (CO2) and methane (CH4) due to anthropogenic and natural biospheric activities were estimated for the South Asian region (Bangladesh, Bhutan, India, Nepal, Pakistan and Sri Lanka). Flux estimates were based on top-down methods that use inversions of atmospheric data, and bottom-up methods that use field observations, satellite data, and terrestrial ecosystem models. Based on atmospheric CO2 inversions, the net biospheric CO2 flux in South Asia (equivalent to the Net Biome Productivity, NBP) was a sink, estimated at −104 ± 150 Tg C yr−1 during 2007–2008. Based on the bottom-up approach, the net biospheric CO2 flux is estimated to be −191 ± 193 Tg C yr−1 during the period of 2000–2009. This last net flux results from the following flux components: (1) the Net Ecosystem Productivity, NEP (net primary production minus heterotrophic respiration) of −220 ± 186 Tg C yr−1 (2) the annual net carbon flux from land-use change of −14 ± 50 Tg C yr−1, which resulted from a sink of −16 Tg C yr−1 due to the establishment of tree plantations and wood harvest, and a source of 2 Tg C yr−1 due to the expansion of croplands; (3) the riverine export flux from terrestrial ecosystems to the coastal oceans of +42.9 Tg C yr−1; and (4) the net CO2 emission due to biomass burning of +44.1 ± 13.7 Tg C yr−1. Including the emissions from the combustion of fossil fuels of 444 Tg C yr−1 for the 2000s, we estimate a net CO2 land–atmosphere flux of 297 Tg C yr−1. In addition to CO2, a fraction of the sequestered carbon in terrestrial ecosystems is released to the atmosphere as CH4. Based on bottom-up and top-down estimates, and chemistry-transport modeling, we estimate that 37 ± 3.7 Tg C yr−1 were released to atmosphere from South Asia during the 2000s. Taking all CO2 and CH4 fluxes together, our best estimate of the net land–atmosphere CO2-equivalent flux is a net source of 334 Tg C yr−1 for the South Asian region during the 2000s. If CH4 emissions are weighted by radiative forcing of molecular CH4, the total CO2-equivalent flux increases to 1148 Tg C yr−1 suggesting there is great potential of reducing CH4 emissions for stabilizing greenhouse gases concentrations.
Published: 2013
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11. A framework for benchmarking land models

Author: Y. Q. Luo, J. T. Randerson, G. Abramowitz, C. Bacour, E. Blyth, N. Carvalhais, P. Ciais, D. Dalmonech, J. B. Fisher, R. Fisher, P. Friedlingstein, K. Hibbard, F. Hoffman, D. Huntzinger, C. D. Jones, C. Koven, D. Lawrence, D. J. Li, M. Mahecha, S. L. Niu, R. Norby, S. L. Piao, X. Qi, P. Peylin, I. C. Prentice, W. Riley, M. Reichstein, C. Schwalm, Y. P. Wang, J. Y. Xia, S. Zaehle, and X. H. Zhou
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills.
Published: 2012
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12. The carbon budget of terrestrial ecosystems in East Asia over the last two decades

Author: S. L. Piao, A. Ito, S. G. Li, Y. Huang, P. Ciais, X. H. Wang, S. S. Peng, H. J. Nan, C. Zhao, A. Ahlström, R. J. Andres, F. Chevallier, J. Y. Fang, J. Hartmann, C. Huntingford, S. Jeong, S. Levis, P. E. Levy, J. S. Li, M. R. Lomas, J. F. Mao, E. Mayorga, A. Mohammat, H. Muraoka, C. H. Peng, P. Peylin, B. Poulter, Z. H. Shen, X. Shi, S. Sitch, S. Tao, H. Q. Tian, X. P. Wu, M. Xu, G. R. Yu, N. Viovy, S. Zaehle, N. Zeng, and B. Zhu
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: This REgional Carbon Cycle Assessment and Processes regional study provides a synthesis of the carbon balance of terrestrial ecosystems in East Asia, a region comprised of China, Japan, North and South Korea, and Mongolia. We estimate the current terrestrial carbon balance of East Asia and its driving mechanisms during 1990–2009 using three different approaches: inventories combined with satellite greenness measurements, terrestrial ecosystem carbon cycle models and atmospheric inversion models. The magnitudes of East Asia's terrestrial carbon sink from these three approaches are comparable: −0.293±0.033 PgC yr−1 from inventory–remote sensing model–data fusion approach, −0.413±0.141 PgC yr−1 (not considering biofuel emissions) or −0.224±0.141 PgC yr−1 (considering biofuel emissions) for carbon cycle models, and −0.270±0.507 PgC yr−1 for atmospheric inverse models. Here and in the following, the numbers behind ± signs are standard deviations. The ensemble of ecosystem modeling based analyses further suggests that at the regional scale, climate change and rising atmospheric CO2 together resulted in a carbon sink of −0.289±0.135 PgC yr−1, while land-use change and nitrogen deposition had a contribution of −0.013±0.029 PgC yr−1 and −0.107±0.025 PgC yr−1, respectively. Although the magnitude of climate change effects on the carbon balance varies among different models, all models agree that in response to climate change alone, southern China experienced an increase in carbon storage from 1990 to 2009, while northern East Asia including Mongolia and north China showed a decrease in carbon storage. Overall, our results suggest that about 13–27% of East Asia's CO2 emissions from fossil fuel burning have been offset by carbon accumulation in its terrestrial territory over the period from 1990 to 2009. The underlying mechanisms of carbon sink over East Asia still remain largely uncertain, given the diversity and intensity of land management processes, and the regional conjunction of many drivers such as nutrient deposition, climate, atmospheric pollution and CO2 changes, which cannot be considered as independent for their effects on carbon storage.
Published: 2012
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13. Modelling sub-grid wetland in the ORCHIDEE global land surface model: evaluation against river discharges and remotely sensed data

Author: B. Ringeval, B. Decharme, S. L. Piao, P. Ciais, F. Papa, N. de Noblet-Ducoudré, C. Prigent, P. Friedlingstein, I. Gouttevin, C. Koven, and A. Ducharne
Subjects: Geology, QE1-996.5
Abstract: The quality of the global hydrological simulations performed by land surface models (LSMs) strongly depends on processes that occur at unresolved spatial scales. Approaches such as TOPMODEL have been developed, which allow soil moisture redistribution within each grid-cell, based upon sub-grid scale topography. Moreover, the coupling between TOPMODEL and a LSM appears as a potential way to simulate wetland extent dynamic and its sensitivity to climate, a recently identified research problem for biogeochemical modelling, including methane emissions. Global evaluation of the coupling between TOPMODEL and an LSM is difficult, and prior attempts have been indirect, based on the evaluation of the simulated river flow. This study presents a new way to evaluate this coupling, within the ORCHIDEE LSM, using remote sensing data of inundated areas. Because of differences in nature between the satellite derived information – inundation extent – and the variable diagnosed by TOPMODEL/ORCHIDEE – area at maximum soil water content, the evaluation focuses on the spatial distribution of these two quantities as well as on their temporal variation. Despite some difficulties in exactly matching observed localized inundated events, we obtain a rather good agreement in the distribution of these two quantities at a global scale. Floodplains are not accounted for in the model, and this is a major limitation. The difficulty of reproducing the year-to-year variability of the observed inundated area (for instance, the decreasing trend by the end of 90s) is also underlined. Classical indirect evaluation based on comparison between simulated and observed river flow is also performed and underlines difficulties to simulate river flow after coupling with TOPMODEL. The relationship between inundation and river flow at the basin scale in the model is analyzed, using both methods (evaluation against remote sensing data and river flow). Finally, we discuss the potential of the TOPMODEL/LSM coupling to simulate wetland areas. A major limitation of the coupling for this purpose is linked to its ability to simulate a global wetland coverage consistent with the commonly used datasets. However, it seems to be a good opportunity to account for the wetland areas sensitivity to the climate and thus to simulate its temporal variability.
Published: 2012
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14. A global analysis of soil moisture derived from satellite observations and a land surface model

Author: K. T. Rebel, R. A. M. de Jeu, P. Ciais, N. Viovy, S. L. Piao, G. Kiely, and A. J. Dolman
Subjects: Technology, Environmental technology. Sanitary engineering, TD1-1066, Geography. Anthropology. Recreation, Environmental sciences, GE1-350
Abstract: Soil moisture availability is important in regulating photosynthesis and controlling land surface-climate feedbacks at both the local and global scale. Recently, global remote-sensing datasets for soil moisture have become available. In this paper we assess the possibility of using remotely sensed soil moisture – AMSR-E (LPRM) – to similate soil moisture dynamics of the process-based vegetation model ORCHIDEE by evaluating the correspondence between these two products using both correlation and autocorrelation analyses. We find that the soil moisture product of AMSR-E (LPRM) and the simulated soil moisture in ORCHIDEE correlate well in space and time, in particular when considering the root zone soil moisture of ORCHIDEE. However, the root zone soil moisture in ORCHIDEE has on average a higher temporal autocorrelation relative to AMSR-E (LPRM) and in situ measurements. This may be due to the different vertical depth of the two products – AMSR-E (LPRM) at the 2–5 cm surface depth and ORCHIDEE at the root zone (max. 2 m) depth – to uncertainty in precipitation forcing in ORCHIDEE, and to the fact that the structure of ORCHIDEE consists of a single-layer deep soil, which does not allow simulation of the proper cascade of time scales that characterize soil drying after each rain event. We conclude that assimilating soil moisture, using AMSR-E (LPRM) in a land surface model like ORCHIDEE with an improved hydrological model of more than one soil layer, may significantly improve the soil moisture dynamics, which could lead to improved CO2 and energy flux predictions.
Published: 2012
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15. Controls on winter ecosystem respiration in temperate and boreal ecosystems

Author: T. Wang, P. Ciais, S. L. Piao, C. Ottlé, P. Brender, F. Maignan, A. Arain, A. Cescatti, D. Gianelle, C. Gough, L. Gu, P. Lafleur, T. Laurila, B. Marcolla, H. Margolis, L. Montagnani, E. Moors, N. Saigusa, T. Vesala, G. Wohlfahrt, C. Koven, A. Black, E. Dellwik, A. Don, D. Hollinger, A. Knohl, R. Monson, J. Munger, A. Suyker, A. Varlagin, and S. Verma
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Winter CO2 fluxes represent an important component of the annual carbon budget in northern ecosystems. Understanding winter respiration processes and their responses to climate change is also central to our ability to assess terrestrial carbon cycle and climate feedbacks in the future. However, the factors influencing the spatial and temporal patterns of winter ecosystem respiration (Reco) of northern ecosystems are poorly understood. For this reason, we analyzed eddy covariance flux data from 57 ecosystem sites ranging from ~35° N to ~70° N. Deciduous forests were characterized by the highest winter Reco rates (0.90 &pm; 0.39 g C m−2 d−1), when winter is defined as the period during which daily air temperature remains below 0 °C. By contrast, arctic wetlands had the lowest winter Reco rates (0.02 &pm; 0.02 g C m−2 d−1). Mixed forests, evergreen needle-leaved forests, grasslands, croplands and boreal wetlands were characterized by intermediate winter Reco rates (g C m−2 d−1) of 0.70(±0.33), 0.60(±0.38), 0.62(±0.43), 0.49(±0.22) and 0.27(±0.08), respectively. Our cross site analysis showed that winter air (Tair) and soil (Tsoil) temperature played a dominating role in determining the spatial patterns of winter Reco in both forest and managed ecosystems (grasslands and croplands). Besides temperature, the seasonal amplitude of the leaf area index (LAI), inferred from satellite observation, or growing season gross primary productivity, which we use here as a proxy for the amount of recent carbon available for Reco in the subsequent winter, played a marginal role in winter CO2 emissions from forest ecosystems. We found that winter Reco sensitivity to temperature variation across space (QS) was higher than the one over time (interannual, QT). This can be expected because QS not only accounts for climate gradients across sites but also for (positively correlated) the spatial variability of substrate quantity. Thus, if the models estimate future warming impacts on Reco based on QS rather than QT, this could overestimate the impact of temperature changes.
Published: 2011
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16. The African contribution to the global climate-carbon cycle feedback of the 21st century

Author: P. Friedlingstein, P. Cadule, S. L. Piao, P. Ciais, and S. Sitch
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Future climate change will have impact on global and regional terrestrial carbon balances. The fate of African tropical forests over the 21st century has been investigated through global coupled climate carbon cycle model simulations. Under the SRES-A2 socio-economic CO2 emission scenario of the IPCC, and using the Institut Pierre Simon Laplace coupled ocean-terrestrial carbon cycle and climate model, IPSL-CM4-LOOP, we found that the warming over African ecosystems induces a reduction of net ecosystem productivity, making a 38% contribution to the global climate-carbon cycle positive feedback. Most of this contribution comes from African grasslands, followed by African savannahs, African tropical forest contributing little to the global climate-carbon feedback. However, the vulnerability of the African rainforest ecosystem is quite large. In contrast, the Amazon forest, despite its lower vulnerability, has a much larger overall contribution due to its 6 times larger extent.
Published: 2010

17. Autumn temperature and carbon balance of a boreal Scots pine forest in Southern Finland

Author: T. Vesala, S. Launiainen, P. Kolari, J. Pumpanen, S. Sevanto, P. Hari, E. Nikinmaa, P. Kaski, H. Mannila, E. Ukkonen, S. L. Piao, and P. Ciais
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: We analyzed the dynamics of carbon balance components: gross primary production (GPP) and total ecosystem respiration (TER), of a boreal Scots pine forest in Southern Finland. The main focus is on investigations of environmental drivers of GPP and TER and how they affect the inter-annual variation in the carbon balance in autumn (September–December). We used standard climate data and CO2 exchange measurements collected by the eddy covariance (EC) technique over 11 years. EC data revealed that increasing autumn temperature significantly enhances TER: the temperature sensitivity was 9.5 gC m−2 °C−1 for the period September–October (early autumn when high radiation levels still occur) and 3.8 gC m−2 °C−1 for November–December (late autumn with suppressed radiation level). The cumulative GPP was practically independent of the temperature in early autumn. In late autumn, air temperature could explain part of the variation in GPP but the temperature sensitivity was very weak, less than 1 gC m−2 °C−1. Two models, a stand photosynthesis model (COCA) and a global vegetation model (ORCHIDEE), were used for estimating stand GPP and its sensitivity to the temperature. The ORCHIDEE model was tested against the observations of GPP derived from EC data. The stand photosynthesis model COCA predicted that under a predescribed 3–6 °C temperature increase, the temperature sensitivity of 4–5 gC m−2 °C−1 in GPP may appear in early autumn. The analysis by the ORCHIDEE model revealed the model sensitivity to the temporal treatment of meteorological forcing. The model predictions were similar to observed ones when the site level 1/2-hourly time step was applied, but the results calculated by using daily meteorological forcing, interpolated to 1/2-hourly time step, were biased. This is due to the nonlinear relationship between the processes and the environmental factors.
Published: 2010
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18. METER: MEasuring TExt Reuse.

Author: Paul D. Clough, Robert J. Gaizauskas, Scott S. L. Piao, and Yorick Wilks
Published: 2002
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19. Evaluating Lexical Resources for a Semantic Tagger.

Author: Scott S. L. Piao, Paul Rayson, Dawn Archer, and Tony McEnery
Published: 2004

20. Building and annotating a corpus for the study of journalistic text reuse.

Author: Paul D. Clough, Robert J. Gaizauskas, and Scott S. L. Piao
Published: 2002

21. A global map of root biomass across the world’s forests

Author: R. Z. Abramoff, Hui Yang, Wei Wei, Daniel S. Goll, S. L. Piao, P. Ciais, Jérôme Chave, Maurizio Santoro, Ye Chen, Dmitry Schepaschenko, Yuanyuan Huang, and David Makowski
Subjects: 0106 biological sciences, Biomass (ecology), Plant growth, Root (linguistics), 010504 meteorology & atmospheric sciences, Taiga, Land management, Global Map, 15. Life on land, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Temperate climate, Environmental science, Allometry, 0105 earth and related environmental sciences
Abstract: (150 words limits)Root plays a key role in plant growth and functioning. Here we combine 10307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially-explicit global high-resolution (~ 1km) root biomass dataset, including fine and coarse roots. In total, 142 ± 32 Pg of live dry matter biomass is stored below-ground, that is a global average root:shoot biomass ratio of 0.25 ± 0.10. Our estimations of total root biomass in tropical, temperate and boreal forests are 44-226% smaller than earlier studies1–3. The smaller estimation is attributable to the updated forest area, spatially explicit above-ground biomass density used to predict the patterns of root biomass, new root measurements and upscaling methodology. We show specifically that the root shoot allometry is one underlying driver that leads to methodological overestimation of root biomass in previous estimations.
Published: 2020
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22. Soil thawing regulates the spring growth onset in tundra and alpine biomes

Author: Adrià Descals, Josep Peñuelas, Marc Peaucelle, Philippe Ciais, Aleixandre Verger, Yongshuo H. Fu, Ivan A. Janssens, Iolanda Filella, S. L. Piao, Dennis D. Baldocchi, ICOS-ATC (ICOS-ATC), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), H2020 Marie Skłodowska-Curie Actions, MSCA: 891369 European Research Council, ERC: ERC-SyG-2013-610028 IMBALANCE-P SGR 2017-1005 Fonds Wetenschappelijk Onderzoek, FWO: G018319N PID2019-110521GB-I00, The authors would like to acknowledge the financial support from the European Research Council Synergy grant ERC-SyG-2013-610028 IMBALANCE-P, the Spanish Government grant PID2019-110521GB-I00 and the Catalan Government grant SGR 2017-1005 . M.P. acknowledges the financial support from the Fonds Wetenschappelijk Onderzoek (FWO, grant no. G018319N ) and the H2020 Marie Skłodowska-Curie Actions (LEAF-2-TBM grant no. 891369 )., and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: Environmental Engineering, 010504 meteorology & atmospheric sciences, Climate Change, Plant phenology, Growing season, 010501 environmental sciences, Forests, Thawing, 01 natural sciences, complex mixtures, Soil, Environmental Chemistry, Biology, Waste Management and Disposal, Tundra, Ecosystem, 0105 earth and related environmental sciences, Phenology, Taiga, Temperature, Deciduous forests, Vegetation, 15. Life on land, Pollution, Chemistry, Deciduous, Agronomy, Boreal forests, 13. Climate action, Spring onset, Soil water, [SDE]Environmental Sciences, Environmental science, Seasons, Temperate rainforest
Abstract: Soil temperature remains isothermal at 0 degrees C and water shifts to a liquid phase during soil thawing. Vegetation may receive this process as a signal and a key to restore physiological activity. We aimed to show the relationship between the timing of soil thawing and the spring growth onset. We estimated the delay between the soil thawing and the spring growth onset in 78 sites of the FLUXNET network. We built a soil thawing map derived from modeling for the northern hemisphere and related it to the greenness onset estimated with satellite imagery. Spring onset estimated with GPP time series occurred shortly after soil surface thawing in tundra (1.1 +/- 3.5 days) and alpine grasslands (16.6 +/- 5.8 days). The association was weaker for deciduous forests (40.3 +/- 4.2 days), especially where soils freeze infrequently. Needleleaved forests tended to start the growing season before the end of thawing (-17.4 +/- 3.6 days), although observations from remote sensing (MODIS Land Cover Dynamics) indicated that the onset of greenness started after the thawing period (26.8 +/- 32 days). This study highlights the role of soil temperature at the spring growth onset at high latitudes. Soil thawing becomes less relevant in temperate forests, where soil is occasionally frozen and other climate factors become more important. (C) 2020 Elsevier B.V. All rights reserved.
Published: 2020
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23. Short-lived climate forcers have long-term climate impacts via the carbon–climate feedback

Author: Philippe Ciais, Xinyue Li, Yunman Han, Bengang Li, Yves Balkanski, Bo Fu, S. L. Piao, Thomas Gasser, Shu Tao, S. Peng, Luchao Han, Wei Li, Tianya Yin, Jie An, Jing Xu, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), National Natural Science Foundation of China, NSFC: 41988101, 2019QZKK0208, 41830641, 41771495, This study is supported by the National Natural Science Foundation of China grant nos. 41771495, 41830641 and 41988101 and the Second Tibetan Plateau Scientific Expedition and Research Program grant no. 2019QZKK0208., and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 0303 health sciences, 010504 meteorology & atmospheric sciences, Climate system, chemistry.chemical_element, Climate change, Carbon sink, 15. Life on land, Environmental Science (miscellaneous), Radiative forcing, Atmospheric sciences, 01 natural sciences, Term (time), 03 medical and health sciences, chemistry, 13. Climate action, Climate impact, Environmental science, Earth system model, Carbon, Social Sciences (miscellaneous), 030304 developmental biology, 0105 earth and related environmental sciences
Abstract: Short-lived climate forcers (SLCFs) like methane, ozone and aerosols have a shorter atmospheric lifetime than CO2 and are often assumed to have a short-term effect on the climate system: should their emissions cease, so would their radiative forcing (RF). However, via their climate impact, SLCFs can affect carbon sinks and atmospheric CO2, causing additional climate change. Here, we use a compact Earth system model to attribute CO2 RF to direct CO2 emissions and to climate–carbon feedbacks since the pre-industrial era. We estimate the climate–carbon feedback contributed 93 ± 50 mW m−2 (~5%) to total RF of CO2 in 2010. Of this, SLCF impacts were −13 ± 50 mW m−2, made up of cooling (−115 ± 43 mW m−2) and warming (102 ± 26 mW m−2) terms that largely cancel. This study illustrates the long-term impact that short-lived species have on climate and indicates that past (and future) change in atmospheric CO2 cannot be attributed only to CO2 emissions. Short-lived climate forcers (SLCFs) are thought to have short-term impacts relative to CO2. A compact Earth system model estimates SLCFs have caused substantial, long-term impacts via carbon–climate feedbacks since the pre-industrial era but species-dependent impacts of opposite sign largely cancel.
Published: 2020
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24. Emergent constraint on crop yield response to warmer temperature from field experiments

Author: Joshua Elliott, Chuang Zhao, Christoph Müller, S. L. Piao, Senthold Asseng, Ivan A. Janssens, Xuhui Wang, Philippe Ciais, Laurent Li, Yao Huang, Josep Peñuelas, Tao Li, Chenzhi Wang, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], Potsdam Institute for Climate Impact Research (PIK), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), UNIVERSITY OF ANTWERP DEPARTMENT OF BIOLOGY WILRIJK BEL, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Centre de Recerca Ecològica i Aplicacions Forestals, Univ. Autònoma de Barcelona (CREAF), université de Barcelone, Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona (UAB), University of Florida [Gainesville] (UF), University of Chicago Computation Institute, University of Chicago, Institute of Botany of the Chinese Academy of Sciences (IBCAS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Institute of Tibetan Plateau Research Chinese Academy of Sciences P.O. Box 2871, 18 Shuang Qing Road Beijing 100085, China (J.L.-Z.) (INSTITUTE OF TIBETAN PLATEAU RESEARCH), Institute of Tibetan Plateau Research, 2019YFA0607300 Chinese Academy of Sciences, CAS, This study was supported by the National Key Research & Development Program of China (2019YFA0607300) and Strategic Priority Research Program (A) of the Chinese Academy of Sciences (grant no. XDA20050101)., Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL)
Subjects: 010504 meteorology & atmospheric sciences, Yield (finance), Geography, Planning and Development, Climate change, Management, Monitoring, Policy and Law, 01 natural sciences, Crop, 03 medical and health sciences, Still face, Constraint (mathematics), Biology, 030304 developmental biology, 0105 earth and related environmental sciences, Nature and Landscape Conservation, 2. Zero hunger, 0303 health sciences, Global and Planetary Change, Ecology, Renewable Energy, Sustainability and the Environment, Impact assessment, Crop yield, Global warming, food and beverages, 15. Life on land, Urban Studies, Chemistry, Agronomy, 13. Climate action, [SDU]Sciences of the Universe [physics], Environmental science, Engineering sciences. Technology, Food Science
Abstract: Responses of global crop yields to warmer temperatures are fundamental to sustainable development under climate change but remain uncertain. Here, we combined a global dataset of field warming experiments (48 sites) for wheat, maize, rice and soybean with gridded global crop models to produce field-data-constrained estimates on responses of crop yield to changes in temperature (S-T) with the emergent-constraint approach. Our constrained estimates show with >95% probability that warmer temperatures would reduce yields for maize (-7.1 +/- 2.8% K-1), rice (-5.6 +/- 2.0% K-1) and soybean (-10.6 +/- 5.8% K-1). For wheat,S(T)was 89% likely to be negative (-2.9 +/- 2.3% K-1). Uncertainties associated with modelledS(T)were reduced by 12-54% for the four crops but data constraints do not allow for further disentanglingS(T)of different crop types. A key implication for impact assessments after the Paris Agreement is that direct warming impacts alone will reduce major crop yields by 3-13% under 2 K global warming without considering CO(2)fertilization effects and adaptations. Even if warming was limited to 1.5 K, all major producing countries would still face notable warming-induced yield reduction. This yield loss could be partially offset by projected benefits from elevated CO2, whose magnitude remains uncertain, and highlights the challenge to compensate it by autonomous adaptation. Global responses of crops to warmer temperatures will affect agricultural sustainability. This study of maize, rice, soybean and wheat projects yield reductions of 3-13% under 2 degrees C warming.
Published: 2020
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25. Global trends in carbon sinks and their relationships with CO2 and temperature

Author: S. L. Piao, Michael Obersteiner, Josep G. Canadell, Pierre Friedlingstein, Jordi Sardans, Ivan A. Janssens, Ana Bastos, Marcos Fernández-Martínez, Stephen Sitch, Sara Vicca, Frédéric Chevallier, Josep Peñuelas, P. Ciais, University of Antwerp (UA), Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Global Carbon Project (GCP), CSIRO Marine and Atmospheric Research (CSIRO-MAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Exeter, Potsdam Institute for Climate Impact Research (PIK), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, Environmental Science (miscellaneous), Photosynthesis, Atmospheric sciences, 01 natural sciences, 03 medical and health sciences, Nutrient, Negatively associated, Ecosystem, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Biology, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 0303 health sciences, Physics, fungi, Global warming, Carbon sink, Vegetation, 15. Life on land, Chemistry, Boreal, 13. Climate action, Environmental science, Social Sciences (miscellaneous)
Abstract: Elevated CO2 concentrations increase photosynthesis and, potentially, net ecosystem production (NEP), meaning a greater CO2 uptake. Climate, nutrients and ecosystem structure, however, influence the effect of increasing CO2. Here we analysed global NEP from MACC-II and Jena CarboScope atmospheric inversions and ten dynamic global vegetation models (TRENDY), using statistical models to attribute the trends in NEP to its potential drivers: CO2, climatic variables and land-use change. We found that an increased CO2 was consistently associated with an increased NEP (1995–2014). Conversely, increased temperatures were negatively associated with NEP. Using the two atmospheric inversions and TRENDY, the estimated global sensitivities for CO2 were 6.0 ± 0.1, 8.1 ± 0.3 and 3.1 ± 0.1 PgC per 100 ppm (~1 °C increase), and −0.5 ± 0.2, −0.9 ± 0.4 and −1.1 ± 0.1 PgC °C−1 for temperature. These results indicate a positive CO2 effect on terrestrial C sinks that is constrained by climate warming. Global net ecosystem production (NEP) from a number of atmospheric inversions and dynamic global vegetation models is analysed to attribute trends to potential drivers. CO2 is found to have a positive effect on NEP that is constrained by climate warming.
Published: 2018
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26. Five decades of northern land carbon uptake revealed by the interhemispheric CO2 gradient

Author: Benjamin Poulter, R. Moriarty, Grégoire Broquet, Philippe Ciais, J. G. Canadell, S. Peng, Xuhui Wang, Frédéric Chevallier, Pieter P. Tans, S. L. Piao, C. Le Quéré, Zhu Liu, Jianguang Tan, Christian Roedenbeck, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Peking University [Beijing], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Tyndall Ctr Climate Change Res, Southampton, Hants, England, affiliation inconnue, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), NASA, Tsinghua University [Beijing] (THU), Harvard University, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Harvard University [Cambridge]
Subjects: Carbon dioxide in Earth's atmosphere, geography, Multidisciplinary, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Northern Hemisphere, Carbon sink, Land cover, 15. Life on land, 010501 environmental sciences, Carbon sequestration, Atmospheric sciences, 01 natural sciences, Sink (geography), Carbon cycle, chemistry.chemical_compound, [SPI]Engineering Sciences [physics], chemistry, 13. Climate action, Carbon dioxide, Environmental science, 0105 earth and related environmental sciences
Abstract: The global land and ocean carbon sinks have increased proportionally with increasing carbon dioxide emissions during the past decades1. It is thought that Northern Hemisphere lands make a dominant contribution to the global land carbon sink2–7; however, the long-term trend of the northern land sink remains uncertain. Here, using measurements of the interhemispheric gradient of atmospheric carbon dioxide from 1958 to 2016, we show that the northern land sink remained stable between the 1960s and the late 1980s, then increased by 0.5 ± 0.4 petagrams of carbon per year during the 1990s and by 0.6 ± 0.5 petagrams of carbon per year during the 2000s. The increase of the northern land sink in the 1990s accounts for 65% of the increase in the global land carbon flux during that period. The subsequent increase in the 2000s is larger than the increase in the global land carbon flux, suggesting a coincident decrease of carbon uptake in the Southern Hemisphere. Comparison of our findings with the simulations of an ensemble of terrestrial carbon models5,8 over the same period suggests that the decadal change in the northern land sink between the 1960s and the 1990s can be explained by a combination of increasing concentrations of atmospheric carbon dioxide, climate variability and changes in land cover. However, the increase during the 2000s is underestimated by all models, which suggests the need for improved consideration of changes in drivers such as nitrogen deposition, diffuse light and land-use change. Overall, our findings underscore the importance of Northern Hemispheric land as a carbon sink. Measurements of the interhemispheric gradient of atmospheric carbon dioxide show that the Northern Hemisphere carbon land sink remained stable between the 1960s and the late 1980s, then increased during the 1990s and 2000s.
Published: 2019
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27. The carbon budget of South Asia

Author: Rodel D. Lasco, J. Hartman, Peter A. Raymond, S. L. Piao, Josep G. Canadell, Richard A. Houghton, Yosuke Niwa, P. Ciais, Abha Chhabra, Philippe Bousquet, Prabir K. Patra, Akihiko Ito, Emilio Mayorga, T. Bhattacharya, V. V. S. S. Sarma, Neung-Hwan Oh, Tao Wang, K. R. Manjunath, Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Global Carbon Project (GCP), CSIRO Marine and Atmospheric Research (CSIRO-MAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Woods Hole Research Center, Partenaires INRAE, College of Urban and Environmental Sciences [Beijing], Peking University [Beijing], Seoul National University [Seoul] (SNU), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Space Applications Centre [Ahmedabad] (SAC), Indian Space Research Organisation (ISRO), Indian Council of Agricultural Research (ICAR), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institute for Biogeochemistry and Marine Chemistry, University of Hamburg, National Institute for Environmental Studies (NIES), Applied Physics Laboratory [Seattle] (APL-UW), University of Washington [Seattle], Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Yale University [New Haven], CSIR National Institute of Oceanography [India] (NIO), World Agroforestry Centre, Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Subjects: 010504 meteorology & atmospheric sciences, lcsh:Life, 010501 environmental sciences, Atmospheric sciences, 7. Clean energy, 01 natural sciences, Atmosphere, chemistry.chemical_compound, Flux (metallurgy), lcsh:QH540-549.5, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, Earth-Surface Processes, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, lcsh:QE1-996.5, Primary production, 15. Life on land, Radiative forcing, lcsh:Geology, lcsh:QH501-531, chemistry, 13. Climate action, Greenhouse gas, Climatology, Carbon dioxide, Environmental science, Terrestrial ecosystem, lcsh:Ecology, Sink (computing)
Abstract: The source and sinks of carbon dioxide (CO2) and methane (CH4) due to anthropogenic and natural biospheric activities were estimated for the South Asian region (Bangladesh, Bhutan, India, Nepal, Pakistan and Sri Lanka). Flux estimates were based on top-down methods that use inversions of atmospheric data, and bottom-up methods that use field observations, satellite data, and terrestrial ecosystem models. Based on atmospheric CO2 inversions, the net biospheric CO2 flux in South Asia (equivalent to the Net Biome Productivity, NBP) was a sink, estimated at −104 ± 150 Tg C yr−1 during 2007–2008. Based on the bottom-up approach, the net biospheric CO2 flux is estimated to be −191 ± 193 Tg C yr−1 during the period of 2000–2009. This last net flux results from the following flux components: (1) the Net Ecosystem Productivity, NEP (net primary production minus heterotrophic respiration) of −220 ± 186 Tg C yr−1 (2) the annual net carbon flux from land-use change of −14 ± 50 Tg C yr−1, which resulted from a sink of −16 Tg C yr−1 due to the establishment of tree plantations and wood harvest, and a source of 2 Tg C yr−1 due to the expansion of croplands; (3) the riverine export flux from terrestrial ecosystems to the coastal oceans of +42.9 Tg C yr−1; and (4) the net CO2 emission due to biomass burning of +44.1 ± 13.7 Tg C yr−1. Including the emissions from the combustion of fossil fuels of 444 Tg C yr−1 for the 2000s, we estimate a net CO2 land–atmosphere flux of 297 Tg C yr−1. In addition to CO2, a fraction of the sequestered carbon in terrestrial ecosystems is released to the atmosphere as CH4. Based on bottom-up and top-down estimates, and chemistry-transport modeling, we estimate that 37 ± 3.7 Tg C yr−1 were released to atmosphere from South Asia during the 2000s. Taking all CO2 and CH4 fluxes together, our best estimate of the net land–atmosphere CO2-equivalent flux is a net source of 334 Tg C yr−1 for the South Asian region during the 2000s. If CH4 emissions are weighted by radiative forcing of molecular CH4, the total CO2-equivalent flux increases to 1148 Tg C yr−1 suggesting there is great potential of reducing CH4 emissions for stabilizing greenhouse gases concentrations.
Published: 2018
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28. The greenhouse gas balance of European grasslands

Author: Martin Wattenbach, Philippe Ciais, Rene Dechow, Pete Smith, Sebastiaan Luyssaert, S. L. Piao, E.-D. Schulze, Fabienne Maignan, Jean-François Soussana, Christof Ammann, Ivan A. Janssens, J. Lathière, Annette Freibauer, A. Don, and Nicolas Vuichard
Subjects: geography, geography.geographical_feature_category, Agronomy, Ecosystem model, Grazing, Eddy covariance, Environmental science, Carbon sink, Primary production, Ecosystem, Carbon sequestration, Atmospheric sciences, Grassland
Abstract: The long-term carbon balance (NBP) of grasslands is estimated by combining scarce multi-year eddy-covariance observations at ecosystem observation sites where information on carbon inputs and harvesting removals is available. Following accounting for carbon leached to rivers, we estimated grasslands to be net carbon sinks of 74±10 g C m−2 yr−1. Uncertainties arise from the small number of sites and the short measurement period. Only 11 sites, out of a total of 20 grassland sites in Europe where eddy covariance systems are installed, were set-up for estimating NBP. These 11 selected sites are representative of intensive management practice and we lack information on disturbance history, such as plowing. This suggests that the grassland NBP estimate is likely biased towards overestimating the sink, compared to the European average. Direct measurements of Net Primary Productivity (NPP) are not possible in grasslands given permanent biomass removal by grazing and mowing, uncertainties in rhizodeposition and production of volatile organic carbon compounds lost to the atmosphere. Therefore, the grassland process-based ecosystem model PASIM was used to estimate the spatial-temporal distribution of NPP, providing a European average value of 750±150 g C across extensively grazed, intensively grazed pastures, and forage production systems. In Europe the NPP of grasslands seems higher than that of croplands and forests. The carbon sequestration efficiency of grasslands, defined as the ratio of NBP to NPP, amounts to 0.09±0.10. Therefore, per unit of carbon input, grasslands sequester 3–4 times more carbon in the soil than forests do, making them a good candidate for managing onsite carbon sinks. When using the 100 yr greenhouse warming potential for CH4 and N2O, their emissions due to management of grasslands together offset roughly 70–80% of the carbon sink. Uncertainties on the European grassland greenhouse gas balance, including CO2, CH4 and N2O fluxes are likely to be reduced in the near future, with data being collected from more sites, and improved up-scaling methods.
Published: 2018

29. Atmospheric deposition, CO

Author: M, Fernández-Martínez, S, Vicca, I A, Janssens, P, Ciais, M, Obersteiner, M, Bartrons, J, Sardans, A, Verger, J G, Canadell, F, Chevallier, X, Wang, C, Bernhofer, P S, Curtis, D, Gianelle, T, Grünwald, B, Heinesch, A, Ibrom, A, Knohl, T, Laurila, B E, Law, J M, Limousin, B, Longdoz, D, Loustau, I, Mammarella, G, Matteucci, R K, Monson, L, Montagnani, E J, Moors, J W, Munger, D, Papale, S L, Piao, and J, Peñuelas
Subjects: Article
Abstract: Concentrations of atmospheric carbon dioxide (CO2) have continued to increase whereas atmospheric deposition of sulphur and nitrogen has declined in Europe and the USA during recent decades. Using time series of flux observations from 23 forests distributed throughout Europe and the USA, and generalised mixed models, we found that forest-level net ecosystem production and gross primary production have increased by 1% annually from 1995 to 2011. Statistical models indicated that increasing atmospheric CO2 was the most important factor driving the increasing strength of carbon sinks in these forests. We also found that the reduction of sulphur deposition in Europe and the USA lead to higher recovery in ecosystem respiration than in gross primary production, thus limiting the increase of carbon sequestration. By contrast, trends in climate and nitrogen deposition did not significantly contribute to changing carbon fluxes during the studied period. Our findings support the hypothesis of a general CO2-fertilization effect on vegetation growth and suggest that, so far unknown, sulphur deposition plays a significant role in the carbon balance of forests in industrialized regions. Our results show the need to include the effects of changing atmospheric composition, beyond CO2, to assess future dynamics of carbon-climate feedbacks not currently considered in earth system/climate modelling.
Published: 2017

30. Current systematic carbon cycle observations and needs for implementing a policy-relevant carbon observing system

Author: P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, G. van der Werf, D. Wickland, M. Williams, C. Zehner, Earth and Climate, Petrology, and Amsterdam Global Change Institute
Abstract: A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The goal of this study is to identify the current state of carbon observations and needs for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion (by several orders of magnitude) of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over remote areas such as the southern oceans, tropical forests and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in-situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases inter-operable, and on the calibration of each component of the system to agreed-upon international scales., JRC.H.7-Climate Risk Management
Published: 2013
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31. Five decades of northern land carbon uptake revealed by the interhemispheric CO

Author: P, Ciais, J, Tan, X, Wang, C, Roedenbeck, F, Chevallier, S-L, Piao, R, Moriarty, G, Broquet, C, Le Quéré, J G, Canadell, S, Peng, B, Poulter, Z, Liu, and P, Tans
Subjects: Carbon Sequestration, China, Fossil Fuels, Geologic Sediments, Atmosphere, Construction Materials, Nitrogen, Uncertainty, Geographic Mapping, Carbon Dioxide, Forests, History, 20th Century, Models, Theoretical, History, 21st Century, Carbon, Siberia, Linear Models
Abstract: The global land and ocean carbon sinks have increased proportionally with increasing carbon dioxide emissions during the past decades
Published: 2016

32. Supplementary material to 'Inventory of anthropogenic methane emissions in Mainland China from 1980 to 2010'

Author: S. S. Peng, S. L. Piao, P. Bousquet, P. Ciais, B. G. Li, X. Lin, S. Tao, Z. P. Wang, Y. Zhang, and F. Zhou
Published: 2016
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33. How have past fire disturbances contributed to the current carbon balance of boreal ecosystems?

Author: Philippe Ciais, Chao Yue, Dan Zhu, S. L. Piao, S. S. Peng, Tao Wang, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institute of Tibetan Plateau Research Chinese Academy of Sciences P.O. Box 2871, 18 Shuang Qing Road Beijing 100085, China (J.L.-Z.) (INSTITUTE OF TIBETAN PLATEAU RESEARCH), Institute of Tibetan Plateau Research, Peking University [Beijing], Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), and Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, lcsh:Life, Climate change, 010603 evolutionary biology, 01 natural sciences, Sink (geography), lcsh:QH540-549.5, Carbon source, Ecosystem, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, Earth-Surface Processes, geography, geography.geographical_feature_category, lcsh:QE1-996.5, Carbon sink, Global change, 15. Life on land, lcsh:Geology, lcsh:QH501-531, Boreal, 13. Climate action, Climatology, Greenhouse gas, [SDE]Environmental Sciences, Environmental science, lcsh:Ecology
Abstract: Boreal fires have immediate effects on regional carbon budgets by emitting CO2 into the atmosphere at the time of burning, but they also have legacy effects by initiating a long-term carbon sink during post-fire vegetation recovery. Quantifying these different effects on the current-day pan-boreal (44–84° N) carbon balance and quantifying relative contributions of legacy sinks by past fires is important for understanding and predicting the carbon dynamics in this region. Here we used the global dynamic vegetation model ORCHIDEE–SPITFIRE (Organising Carbon and Hydrology In Dynamic Ecosystems – SPread and InTensity of FIRE) to attribute the contributions by fires in different decades between 1850 and 2009 to the carbon balance of 2000–2009, taking into account the atmospheric CO2 change and climate change since 1850. The fire module of ORCHIDEE–SPITFIRE was turned off for each decade in turn and was also turned off before and after the decade in question in order to model the legacy carbon trajectory by fires in each past decade. We found that, unsurprisingly, fires that occurred in 2000–2009 are a carbon source (−0.17 Pg C yr−1) for the carbon balance of 2000–2009, whereas fires in all decades before 2000 contribute carbon sinks with a collective contribution of 0.23 Pg C yr−1. This leaves a net fire sink effect of 0.06 Pg C yr−1, or 6.3 % of the simulated regional carbon sink (0.95 Pg C yr−1). Further, fires with an age of 10–40 years (i.e., those that occurred during 1960–1999) contribute more than half of the total sink effect of fires. The small net sink effect of fires indicates that current-day fire emissions are roughly balanced out by legacy sinks. The future role of fires in the regional carbon balance remains uncertain and will depend on whether changes in fires and associated carbon emissions will exceed the enhanced sink effects of previous fires, both being strongly affected by global change.
Published: 2016
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34. The carbon balance of Africa: synthesis of recent research studies

Author: Riccardo Valentini, Jérôme Chave, Antonio Bombelli, Casey M. Ryan, Mathew Williams, P. Ciais, P. Brender, Matieu Henry, S. L. Piao, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Euro-Mediterranean Center on Climate Change (CMCC), University of Edinburgh, College of Urban and Environmental Sciences [Beijing], Peking University [Beijing], Evolution et Diversité Biologique (EDB), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), AgroParisTech, Division on Impacts on Agriculture, Forests and Ecosystem Services (IAFES), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées
Subjects: Time Factors, 010504 meteorology & atmospheric sciences, Climate Change, General Mathematics, Population, General Physics and Astronomy, Climate change, 01 natural sciences, Sink (geography), Carbon Cycle, Trees, Carbon cycle, Soil, Environmental protection, Ecosystem, Biomass, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, education, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, education.field_of_study, geography, geography.geographical_feature_category, Land use, General Engineering, 04 agricultural and veterinary sciences, Soil carbon, 15. Life on land, 13. Climate action, Africa, 040103 agronomy & agriculture, Research studies, 0401 agriculture, forestry, and fisheries, Environmental science
Abstract: The African continent contributes one of the largest uncertainties to the global CO 2 budget, because very few long-term measurements are carried out in this region. The contribution of Africa to the global carbon cycle is characterized by its low fossil fuel emissions, a rapidly increasing population causing cropland expansion, and degradation and deforestation risk to extensive dryland and savannah ecosystems and to tropical forests in Central Africa. A synthesis of the carbon balance of African ecosystems is provided at different scales, including observations of land–atmosphere CO 2 flux and soil carbon and biomass carbon stocks. A review of the most recent estimates of the net long-term carbon balance of African ecosystems is provided, including losses from fire disturbance, based upon observations, giving a sink of the order of 0.2 Pg C yr −1 with a large uncertainty around this number. By comparison, fossil fuel emissions are only of the order of 0.2 Pg C yr −1 and land-use emissions are of the order of 0.24 Pg C yr −1 . The sources of year-to-year variations in the ecosystem carbon-balance are also discussed. Recommendations for the deployment of a coordinated carbon-monitoring system for African ecosystems are given.
Published: 2011
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35. How past fire disturbances have contributed to the current carbon balance of boreal ecosystems?

Author: S. L. Piao, Shushi Peng, Chao Yue, Philippe Ciais, Tao Wang, and Dan Zhu
Subjects: Balance (accounting), Boreal, chemistry, 13. Climate action, Climatology, Environmental science, chemistry.chemical_element, Ecosystem, 15. Life on land, Current (fluid), Carbon
Abstract: Boreal fires have immediate effects on regional carbon budgets by emitting CO2 into the atmosphere at the time of burning, but also have legacy effects by initiating a long-term carbon sink during post-fire vegetation recovery. Quantifying these different effects on the current-day pan-boreal (44–84° N) carbon balance and relative contributions of legacy sinks by past fires is important for understanding and predicting the carbon dynamics in this region. Here we used the global dynamic vegetation model ORCHIDEE-SPITFIRE to attribute the contributions by fires in different decades of 1850–2009 to the carbon balance of 2000–2009, taking into account the atmospheric CO2 change and climate change since 1850. The fire module of ORCHIDEE-SPITFIRE was turned off in each decade sequentially, and turned on before and after, to model the legacy carbon trajectory by fires in each past decade. We found that, unsurprisingly, fires that occured in 2000–2009 are a carbon source (−0.17 Pg C yr−1) for the 2000s-decade carbon balance, whereas fires in all decades before 2000 contribute carbon sinks with a collective contribution of 0.23 Pg C yr−1. This leaves a net fire sink effect of 0.06 Pg C yr−1, or 6.3 % of the simulated regional carbon sink (0.95 Pg C yr−1). Further, fires with an age of 10–40 years (i.e. those occurred during 1960–1999) contribute more than half of the total sink effect of fires. The small net sink effect of fires indicates that current-day fire emissions are roughly in balance with legacy sinks. The future role of fires in the regional carbon balance remains uncertain and will depend on whether changes in fires and associated carbon emissions will exceed the enhanced sink effects of previous fires, both being strongly affected by global change.
Published: 2015
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36. Improving the dynamics of northern vegetation in the ORCHIDEE ecosystem model

Author: Dmitry Schepaschenko, Gerhard Krinner, B. Poulter, Anatoly Shvidenko, S. L. Piao, Philippe Peylin, Masa Kageyama, Arsène Druel, Catherine Ottlé, P. Ciais, Nicolas Viovy, Shushi Peng, and D. Zhu
Subjects: Ecosystem model, medicine, Environmental science, medicine.symptom, Atmospheric sciences, Vegetation (pathology)
Abstract: Processes that describe the distribution of vegetation and ecosystem succession after disturbance are an important component of dynamic global vegetation models (DGVMs). The vegetation dynamics module (ORC-VD) within the process-based ecosystem model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) has not been updated and evaluated since many years and does not match the progress in modeling the rest of the physical and biogeochemical processes. Therefore, ORC-VD is known to produce unrealistic results. This study presents a new parameterization of ORC-VD for mid-to-high latitude regions in the Northern Hemisphere, including processes that influence the existence, mortality and competition between tree functional types. A new set of metrics is also proposed to quantify the performance of ORC-VD, using up to five different datasets of satellite land cover, forest biomass from remote sensing and inventories, a data-driven estimate of gross primary productivity (GPP) and two gridded datasets of soil organic carbon content. The scoring of ORC-VD derived from these metrics integrates uncertainties in the observational datasets. This multi-dataset evaluation framework is a generic method that could be applied to the evaluation of other DGVM models. The results of the original ORC-VD published in 2005 for mid-to-high latitudes and of the new parameterization are evaluated against the above-described datasets. Significant improvements were found in the modeling of the distribution of tree functional types north of 40° N. Three additional sensitivity runs were carried out to separate the impact of different processes or drivers on simulated vegetation distribution, including soil freezing which limits net primary production through soil moisture availability in the root zone, elevated CO2 concentration since 1850, and the return frequency of cold climate extremes causing tree mortality during the spin-up phase of the model.
Published: 2015
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37. Supplementary material to 'Improving the dynamics of northern vegetation in the ORCHIDEE ecosystem model'

Author: D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko
Published: 2015
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38. Recent trends and drivers of regional sources and sinks of carbon dioxide

Author: Peter Levy, Pierre Friedlingstein, Manuel Gloor, Benjamin Poulter, S. L. Piao, Mark R. Lomas, Benjamin Smith, Steve D Jones, Scott C. Doney, Sönke Zaehle, Nicolas Viovy, Philippe Ciais, Ranga B. Myneni, Laurent Bopp, C. Le Quéré, Almut Arneth, Stephen Sitch, Zaichun Zhu, Frédéric Chevallier, Samuel Levis, Gordon B. Bonan, Nicolas Gruber, Josep G. Canadell, Guillermo N. Murray-Tortarolo, Christoph Heinze, Chris Huntingford, Philippe Peylin, Ning Zeng, Richard J. Ellis, Anders Ahlström, Heather Graven, College of Life and Environmental Sciences [Exeter], University of Exeter, Exeter Climate Systems, College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter, United Kingdom, Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), University of Bergen (UiB), Centre for Ecology and Hydrology (CEH), Natural Environment Research Council (NERC), National Center for Atmospheric Research [Boulder] (NCAR), Georgia Institute of Technology [Lorraine, France], Centre for Terrestrial Carbon Dynamics: National Centre for Earth Observation (CTCD), University of Sheffield [Sheffield], Montana State University (MSU), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Department of Atmospheric and Oceanic Science [College Park] (AOSC), University of Maryland [College Park], University of Maryland System-University of Maryland System, Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), ICOS-ATC (ICOS-ATC), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], Tyndall Centre for Climate Change Research and School of Environmental Sciences, University of East Anglia [Norwich] (UEA), Beihang University (BUAA), Department of Earth and Environment [Boston], Boston University [Boston] (BU), College of Life and Environmental Sciences, Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, University of Bergen, Geophysical Institute & Bjerkness Centre for Climate Research, Centre for Ecology and Hydrology ( CEH ), Natural Environment Research Council ( NERC ), National Center for Atmospheric Research [Boulder] ( NCAR ), Georgia Tech Lorraine, Centre for Terrestrial Carbon Dynamics: National Centre for Earth Observation, Montana State University ( MSU ), Laboratoire Science Climat & Environnement, Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ), Max Planck Institute for Biogeochemistry, Department of Atmospheric and Oceanic Science [College Park] ( AOSC ), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung ( IMK-IFU ), Karlsruher Institut für Technologie ( KIT ), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] ( LSCE ), Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ), Chimie et Photonique Moléculaires ( CPM ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China, affiliation inconnue, University of East Anglia [Norwich] ( UEA ), Beihang University, Department of Earth and Environment, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: [ SDU.OCEAN ] Sciences of the Universe [physics]/Ocean, Atmosphere, Biogeochemical cycle, lcsh:Life, Climate change, Land cover, Sink (geography), chemistry.chemical_compound, Meteorology and Climatology, lcsh:QH540-549.5, [ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces, environment, ddc:550, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Ecology, Evolution, Behavior and Systematics, ComputingMilieux_MISCELLANEOUS, Earth-Surface Processes, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, geography, geography.geographical_feature_category, Land use, lcsh:QE1-996.5, Primary production, Carbon sink, 15. Life on land, lcsh:Geology, lcsh:QH501-531, Earth sciences, chemistry, 13. Climate action, Climatology, Carbon dioxide, Environmental science, lcsh:Ecology
Abstract: International audience; Published by Copernicus Publications on behalf of the European Geosciences Union. 654 S. Sitch et al.: Recent trends and drivers of regional sources Abstract. The land and ocean absorb on average just over half of the anthropogenic emissions of carbon dioxide (CO 2) every year. These CO 2 "sinks" are modulated by climate change and variability. Here we use a suite of nine dynamic global vegetation models (DGVMs) and four ocean biogeo-chemical general circulation models (OBGCMs) to estimate trends driven by global and regional climate and atmospheric CO 2 in land and oceanic CO 2 exchanges with the atmosphere over the period 1990-2009, to attribute these trends to underlying processes in the models, and to quantify the uncertainty and level of inter-model agreement. The models were forced with reconstructed climate fields and observed global atmospheric CO 2 ; land use and land cover changes are not included for the DGVMs. Over the period 1990-2009, the DGVMs simulate a mean global land carbon sink of −2.4 ± 0.7 Pg C yr −1 with a small significant trend of −0.06 ± 0.03 Pg C yr −2 (increasing sink). Over the more limited period 1990-2004, the ocean models simulate a mean ocean sink of −2.2 ± 0.2 Pg C yr −1 with a trend in the net C uptake that is indistinguishable from zero (−0.01 ± 0.02 Pg C yr −2). The two ocean models that extended the simulations until 2009 suggest a slightly stronger, but still small, trend of −0.02 ± 0.01 Pg C yr −2. Trends from land and ocean models compare favourably to the land green-ness trends from remote sensing, atmospheric inversion results , and the residual land sink required to close the global carbon budget. Trends in the land sink are driven by increasing net primary production (NPP), whose statistically significant trend of 0.22 ± 0.08 Pg C yr −2 exceeds a significant trend in heterotrophic respiration of 0.16 ± 0.05 Pg C yr −2-primarily as a consequence of widespread CO 2 fertilisation of plant production. Most of the land-based trend in simulated net carbon uptake originates from natural ecosystems in the tropics (−0.04 ± 0.01 Pg C yr −2), with almost no trend over the northern land region, where recent warming and reduced rainfall offsets the positive impact of elevated atmospheric CO 2 and changes in growing season length on carbon storage. The small uptake trend in the ocean models emerges because climate variability and change, and in particular increasing sea surface temperatures, tend to counteract the trend in ocean uptake driven by the increase in atmospheric CO 2. Large uncertainty remains in the magnitude and sign of modelled carbon trends in several regions, as well as regarding the influence of land use and land cover changes on regional trends.
Published: 2015
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39. Improving the dynamics of Northern Hemisphere high-latitude vegetation in the ORCHIDEE ecosystem model

Author: Benjamin Poulter, Gerhard Krinner, Philippe Peylin, Catherine Ottlé, Arsène Druel, Dan Zhu, Masa Kageyama, Philippe Ciais, Anatoly Shvidenko, S. L. Piao, Shushi Peng, Dmitry Schepaschenko, Nicolas Viovy, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Écologie et santé des écosystèmes (ESE), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Department of Ecology, College of Urban and Environmental Science, Peking University [Beijing], International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Modélisation du climat (CLIM), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, Biomass (ecology), 010504 meteorology & atmospheric sciences, lcsh:QE1-996.5, Northern Hemisphere, Primary production, Soil carbon, Vegetation, Land cover, 15. Life on land, 010603 evolutionary biology, 01 natural sciences, lcsh:Geology, 13. Climate action, Ecosystem model, Climatology, [SDE]Environmental Sciences, Environmental science, Ecosystem, 0105 earth and related environmental sciences
Abstract: Processes that describe the distribution of vegetation and ecosystem succession after disturbance are an important component of dynamic global vegetation models (DGVMs). The vegetation dynamics module (ORC-VD) within the process-based ecosystem model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) has not been updated and evaluated since many years and does not match the progress in modeling the rest of the physical and biogeochemical prcesses. Therefore, ORC-VD is known to produce unrealistic results. This study presents a new parameterization of ORC-VD for mid-to high latitude regions in the Northern Hemisphere, including processes that influence the existence, mortality and competition between tree functional types. A new set of metrics is also proposed to quantify the performance of ORC-VD, using up to five different datsets of satellite land cover, forest biomass from remote sensing and inventories, a data-driven estimate of gross primary productivity (GP) and two gridded datasets of soil organic carbon content. The scoring of ORC-VD derived from these metrics integrates uncertainties in the observational datasets. This multi-dataset evaluation framework is a generic method that could be applied to the evaluation of other DGVM models. The results of the original ORC-VD published in 2005 for mid-to-high latitudes and of the new parameterization are evaluated against the above- described datasets. Significant improvements were found in the modeling of the distribution of tree fnctional types north of 40 degrees N. Three additional sensitivity runs were carried out to separate the impact of different processes or drivers on simulated vegetation distribution, including soil freezing which limits net primary production through soil moisture availability in the root zone, elevated CO2 concentration since 1850, and the return frequency of cold climate extremes causing tree mortality during the spin-up phase of the model.
Published: 2015
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40. Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system

Author: Robert B. Cook, P. Ciais, Grégoire Broquet, Antonio Bombelli, Robert J. Andres, Riley M. Duren, Alberto Borges, G. R. van der Werf, Yude Pan, Anna Peregon, Josep G. Canadell, J. Butler, Christopher L. Sabine, Jean-Daniel Paris, Roger Dargaville, Benjamin Poulter, Peter Rayner, Oksana Tarasova, L. Rivier, Nadine Gobron, Ranga B. Myneni, S. Plummer, Shaun Quegan, Beverly E. Law, G. Kinderman, T. Moriyama, John B. Miller, Markus Reichstein, Frédéric Chevallier, Michael Obersteiner, Richard Engelen, R. DeFries, Diane Wickland, Heinrich Bovensmann, Matieu Henry, Rong Wang, Peter A. Raymond, S. L. Piao, Nicolas Gruber, Michael Buchwitz, Tom J. Battin, F. M. Bréon, Dennis S. Ojima, David S. Schimel, Kevin R. Gurney, Sebastiaan Luyssaert, C. Nussli, Claus Zehner, Laurent Bopp, Mathew Williams, Christoph Heinze, Gregg Marland, Gianpaolo Balsamo, Charles E. Miller, Riccardo Valentini, Alex Held, A. J. Dolman, C. Moulin, Martin Heimann, Earth and Climate, Systems Ecology, Petrology, Language, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Euro-Mediterranean Center on Climate Change (CMCC), Jet Propulsion Laboratory (JPL), California Institute of Technology (CALTECH)-NASA, School of Earth Sciences [Melbourne], Faculty of Science [Melbourne], University of Melbourne-University of Melbourne, JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Appalachian State University, University of North Carolina System (UNC), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, European Centre for Medium-Range Weather Forecasts (ECMWF), University of Vienna [Vienna], Université de Liège, Institute of Environmental Physics [Bremen] (IUP), University of Bremen, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), CSIRO Marine and Atmospheric Research (CSIRO-MAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Boston University [Boston] (BU), Arizona State University [Tempe] (ASU), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Oregon State University (OSU), Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), Japan Aerospace Exploration Agency [Tokyo] (JAXA), Thales Alenia Space, Natural Resource Ecology Laboratory [Fort Collins] (NREL), Colorado State University [Fort Collins] (CSU), Newtown, PA 19073, ICOS-RAMCES (ICOS-RAMCES), Peking University [Beijing], University of Sheffield [Sheffield], Yale School of Forestry and Environmental Studies, National ecological observatory network, World Meteorological Organization (WMO), National Aeronautics and Space Administration, Partenaires INRAE, University of Edinburgh, ESA Centre for Earth Observation (ESRIN), European Space Agency (ESA), VU University Amsterdam, NASA-California Institute of Technology (CALTECH), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Vrije Universiteit Amsterdam [Amsterdam] (VU), Thales Alenia Space [Toulouse] (TAS), THALES [France], National Aeronautics and Space Administration (NASA), and Agence Spatiale Européenne = European Space Agency (ESA)
Subjects: Mathematics and natural scienses: 400::Geosciences: 450::Meteorology: 453 [VDP], lcsh:Life, Carbon sequestration, 7. Clean energy, 12. Responsible consumption, Carbon cycle, Matematikk og naturvitenskap: 400::Geofag: 450::Meteorologi: 453 [VDP], lcsh:QH540-549.5, 11. Sustainability, Land use, land-use change and forestry, SDG 14 - Life Below Water, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Temporal scales, Ecology, Evolution, Behavior and Systematics, Earth-Surface Processes, Remote sensing, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, business.industry, lcsh:QE1-996.5, Fossil fuel, Environmental resource management, Biosphere, lcsh:Geology, lcsh:QH501-531, 13. Climate action, Software deployment, Greenhouse gas, lcsh:Ecology, business
Abstract: A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales., JRC.H.7-Climate Risk Management
Published: 2014
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41. Nutrient availability as the key regulator of global forest carbon balance

Author: M. Fern�ez-Mart�z, S. Vicca, I. A. Janssens, J. Sardans, S. Luyssaert, M. Campioli, F.�S. Chapin III, P. Ciais, Y. Malhi, M. Obersteiner, D. Papale, S. L. Piao, M. Reichstein, and F. Rod� J. Pe�as
Published: 2014

42. Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model: Simulating boreal forest carbon dynamics after stand-replacing fire disturbance

Author: Chao Yue, Sebastiaan Luyssaert, Nicolas Viovy, James T. Randerson, Tao Wang, Benjamin Poulter, Valentin Bellassen, S. L. Piao, Patricia Cadule, J. L. Harden, P. Ciais, Systems Ecology, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), United States Geological Survey [Reston] (USGS), Department of Earth System Science [Irvine] (ESS), University of California [Irvine] (UCI), University of California-University of California, Centre d'Economie et de Sociologie Rurales Appliquées à l'Agriculture et aux Espaces Ruraux (CESAER), Institut National de la Recherche Agronomique (INRA)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Department of Ecology, College of Urban and Environmental Science, Peking University [Beijing], Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of California [Irvine] (UC Irvine), and University of California (UC)-University of California (UC)
Subjects: 0106 biological sciences, Canada, self thinning, 010504 meteorology & atmospheric sciences, Chronosequence, [SDV]Life Sciences [q-bio], lcsh:Life, Soil science, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, lcsh:QH540-549.5, Forest ecology, carbon cycle, Physical Sciences and Mathematics, SDG 13 - Climate Action, boreal forest, stand structure, Ecology, Evolution, Behavior and Systematics, global change, Earth-Surface Processes, 0105 earth and related environmental sciences, Forest floor, geography, geography.geographical_feature_category, vegetation dynamics, lcsh:QE1-996.5, Carbon sink, carbon dioxide, Soil carbon, 15. Life on land, Old-growth forest, United States, lcsh:Geology, lcsh:QH501-531, 13. Climate action, Environmental science, Secondary forest, lcsh:Ecology, Ecosystem respiration, Alaska, forest fire
Abstract: Stand-replacing fires are the dominant fire type in North American boreal forests. They leave a historical legacy of a mosaic landscape of different aged forest cohorts. This forest age dynamics must be included in vegetation models to accurately quantify the role of fire in the historical and current regional forest carbon balance. The present study adapted the global process-based vegetation model ORCHIDEE to simulate the CO2 emissions from boreal forest fire and the subsequent recovery after a stand-replacing fire; the model represents postfire new cohort establishment, forest stand structure and the self-thinning process. Simulation results are evaluated against observations of three clusters of postfire forest chronosequences in Canada and Alaska. The variables evaluated include: fire carbon emissions, CO2 fluxes (gross primary production, total ecosystem respiration and net ecosystem exchange), leaf area index, and biometric measurements (aboveground biomass carbon, forest floor carbon, woody debris carbon, stand individual density, stand basal area, and mean diameter at breast height). When forced by local climate and the atmospheric CO2 history at each chronosequence site, the model simulations generally match the observed CO2 fluxes and carbon stock data well, with model-measurement mean square root of deviation comparable with the measurement accuracy (for CO2 flux ~100 g C m−2 yr−1, for biomass carbon ~1000 g C m−2 and for soil carbon ~2000 g C m−2). We find that the current postfire forest carbon sink at the evaluation sites, as observed by chronosequence methods, is mainly due to a combination of historical CO2 increase and forest succession. Climate change and variability during this period offsets some of these expected carbon gains. The negative impacts of climate were a likely consequence of increasing water stress caused by significant temperature increases that were not matched by concurrent increases in precipitation. Our simulation results demonstrate that a global vegetation model such as ORCHIDEE is able to capture the essential ecosystem processes in fire-disturbed boreal forests and produces satisfactory results in terms of both carbon fluxes and carbon-stock evolution after fire. This makes the model suitable for regional simulations in boreal regions where fire regimes play a key role in the ecosystem carbon balance.
Published: 2013
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43. Does the integration of the dynamic nitrogen cycle in a terrestrial biosphere model improve the long-term trend of the leaf area index?

Author: Sönke Zaehle, Pierre Friedlingstein, Fabienne Maignan, P. Ciais, Bertrand Guenet, Patricia Cadule, S. L. Piao, Philippe Peylin, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Chinese Academy of Sciences [Beijing] (CAS), ICOS-ATC (ICOS-ATC), University of Exeter, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: Biosphere model, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Atmospheric Science, 010504 meteorology & atmospheric sciences, Climate change, Biosphere, Global change, 04 agricultural and veterinary sciences, 15. Life on land, 01 natural sciences, Normalized Difference Vegetation Index, Carbon cycle, 13. Climate action, Climatology, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Leaf area index, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Nitrogen cycle, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: The carbon cycle strongly interacts with the nitrogen cycle. Several observations show that the effects of global change on primary production and carbon storage in plant biomass and soils are partially controlled by N availability. Nevertheless, only a small number of terres- trial biosphere models represent explicitly the nitrogen cycle, despite its importance on the carbon cycle and on climate. These models are difficult to evaluate at large spatiotemporal scales because of the scarcity of data at the global scale over a long time period. In this study, we benchmark the capacity of the O-CN global terrestrial biosphere model to reproduce temporal changes in leaf area index (LAI) at the global scale observed by NOAA_AV- HRR satellites over the period 1982-2002. Using a satellite LAI product based on the normalized difference vegetation index of global inventory monitoring and modelling studies dataset, we estimate the long-term trend of LAI and we compare it with the results from the terrestrial biosphere models, either with (O-CN) or without (O-C) a dynamic nitrogen cycle coupled to the carbon-water-energy cycles. In boreal and temperate regions, including a dynamic N cycle (O-CN) improved the fit between observed and modeled temporal changes in LAI. In contrast, in the tro- pics, simulated LAI from the model without the dynamic N cycle (O-C) better matched observed changes in LAI over time. Despite differential regional trends, the satellite estimate suggests an increase in the global average LAI during 1982-2002 by 0.0020 m 2 m -2 y -1 . Both versions of the model substantially overestimated the rate of change in LAI over time (0.0065 m 2 m -2 y -1 for O-C and 0.0057 m 2 m -2 y -1 for O-CN), suggesting that some additional limitation mechanisms are missing in the model. We also estimated the relative importance of climate, CO2 and N deposition as potential drivers of the temporal changes in LAI. We found that recent climate change better explained temporal changes in LAI when the dynamic N cycle was included in the model (higher ranked fit for O-CN vs. O-C). Using the O-C configuration to estimate the direct effect of climate on LAI, we quantified the importance of climate-N cycle feedbacks in explaining the LAI response. We found that the warming-induced release of N from soil organic matter decomposition explains 17.5 % of the global trend in LAI over time, however, reaching up to 40.9 % explained variance in the boreal zone, which is a more important contribution than increasing anthropogenic nitrogen deposition. Our analysis supports a strong connection between warming, N cycling, and vegetation productivity. These findings underscore the importance of including N cycling in global-scale models of vegetation response to environmental change.
Published: 2013
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44. Supplementary material to 'Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model'

Author: C. Yue, P. Ciais, S. Luyssaert, P. Cadule, J. Harden, J. Randerson, V. Bellassen, T. Wang, S. L. Piao, B. Poulter, and N. Viovy
Published: 2013
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45. Attributing the increase in atmospheric CO2 to emitters and absorbers

Author: S. L. Piao, Jean-Daniel Paris, Vincent Gitz, Philippe Ciais, Michael R. Raupach, Ken Caldeira, Pierre Friedlingstein, Thomas Gasser, Anand Patwardhan, Josep G. Canadell, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), centre international de recherche sur l'environnement et le développement (CIRED), Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École des hautes études en sciences sociales (EHESS)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), ICOS-RAMCES (ICOS-RAMCES), Department of Global Ecology [Carnegie] (DGE), Carnegie Institution for Science [Washington], Australian National University (ANU), Global Carbon Project, CSIRO Marine and Atmospheric Research, University of Exeter, Department of Ecology, College of Urban and Environmental Science, Peking University [Beijing], Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École des hautes études en sciences sociales (EHESS)-AgroParisTech-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS), and Carnegie Institution for Science
Subjects: 010504 meteorology & atmospheric sciences, Climate-Change, Ecology, Carbon sink, 15. Life on land, 010501 environmental sciences, Environmental Science (miscellaneous), Atmospheric sciences, 01 natural sciences, Carbon-Cycle, 13. Climate action, Kyoto-Protocol, [SDE]Environmental Sciences, Greenhouse gas removal, Environmental science, Dependant, Land-Use, ComputingMilieux_MISCELLANEOUS, Social Sciences (miscellaneous), 0105 earth and related environmental sciences, Model
Abstract: Climate change policies need to consider the contribution of each emitting region to the increase in atmospheric carbon dioxide. We calculate regional attributions of increased atmospheric CO2 using two different assumptions about land sinks. In the first approach, each absorber region is attributed 'domestic sinks' that occur within its boundaries. In the second, alternative approach, each emitter region is attributed 'foreign sinks' that it created indirectly through its contribution to increasing CO2. We unambiguously attribute the largest share of the historical increase in CO2 between pre-industrial times and the present-day period to developed countries. However, the excess CO2 in the atmosphere since pre-industrial times attributed to developing countries is greater than their share of cumulative CO2 emissions. This is because a greater fraction of their emissions occurred more recently. If emissions remain high over the coming decades, the share of excess CO2 attributable to developing countries will grow, and the sink service provided by forested regions-in particular those with tropical forest-to other regions will depend critically on future tropical land-use change.
Published: 2013
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46. Carbon and Other Biogeochemical Cycles

Author: Philippe Ciais, Ranga B. Myneni, James N. Galloway, Josep G. Canadell, Peter E. Thornton, Christopher L. Sabine, Laurent Bopp, Abha Chhabra, Ruth DeFries, S. L. Piao, Martin Heimann, Chris D. Jones, C. Le Quéré, Victor Brovkin, and Govindasamy Bala
Subjects: Meteorologie en Luchtkwaliteit, Biogeochemical cycle, Denitrification, WIMEK, Reactive nitrogen, Meteorology and Air Quality, chemistry.chemical_element, Atmospheric sciences, Nitrogen, Oceanography, chemistry, Atmospheric chemistry, Environmental science, Life Science, Carbon, Deposition (chemistry), NOx
Abstract: For base year 2010, anthropogenic activities created ~210 (190 to 230) TgN of reactive nitrogen Nr from N2. This human-caused creation of reactive nitrogen in 2010 is at least 2 times larger than the rate of natural terrestrial creation of ~58 TgN (50 to 100 TgN yr−1) (Table 6.9, Section 1a). Note that the estimate of natural terrestrial biological fixation (58 TgN yr−1) is lower than former estimates (100 TgN yr−1, Galloway et al., 2004), but the ranges overlap, 50 to 100 TgN yr−1 vs. 90 to 120 TgN yr−1, respectively). Of this created reactive nitrogen, NOx and NH3 emissions from anthropogenic sources are about fourfold greater than natural emissions (Table 6.9, Section 1b). A greater portion of the NH3 emissions is deposited to the continents rather than to the oceans, relative to the deposition of NOy, due to the longer atmospheric residence time of the latter. These deposition estimates are lower limits, as they do not include organic nitrogen species. New model and measurement information (Kanakidou et al., 2012) suggests that incomplete inclusion of emissions and atmospheric chemistry of reduced and oxidized organic nitrogen components in current models may lead to systematic underestimates of total global reactive nitrogen deposition by up to 35% (Table 6.9, Section 1c). Discharge of reactive nitrogen to the coastal oceans is ~45 TgN yr−1 (Table 6.9, Section 1d). Denitrification converts Nr back to atmospheric N2. The current estimate for the production of atmospheric N2 is 110 TgN yr−1 (Bouwman et al., 2013).
Published: 2013
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47. Supplementary material to 'High resolution mapping of combustion processes and implications for CO2 emissions'

Author: R. Wang, S. Tao, P. Ciais, H. Z. Shen, Y. Huang, H. Chen, G. F. Shen, B. Wang, W. Li, Y. Y. Zhang, Y. Lu, D. Zhu, Y. C. Chen, X. P. Liu, W. T. Wang, X. L. Wang, W. X. Liu, B. G. Li, and S. L. Piao
Published: 2012
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48. High resolution mapping of combustion processes and implications for CO2 emissions

Author: R. Wang, S. Tao, P. Ciais, H. Z. Shen, Y. Huang, H. Chen, G. F. Shen, B. Wang, W. Li, Y. Y. Zhang, Y. Lu, D. Zhu, Y. C. Chen, X. P. Liu, W. T. Wang, X. L. Wang, W. X. Liu, B. G. Li, and S. L. Piao
Abstract: High-resolution mapping of fuel combustion and CO2 emission provides valuable information for inferring terrestrial carbon balance, modeling pollutant transport, and developing mitigation strategies. Previous inventories included only a limited number of fuel types and anthropogenic emissions were mapped using national population proxies which may distort the geographical distribution within countries. In this study, a sub-national disaggregation method (SDM) was applied to establish a global 0.1°×0.1° geo-referenced inventory of fuel combustion (PKU-FUEL) and a corresponding CO2 emission inventory (PKU-CO2) based upon 64 fuel sub-types for the year 2007. Uncertainties of the new inventories were evaluated using a Monte Carlo method. The total combustion CO2 emission in 2007 was 11.2 (9.11 and 13.3 as 5th and 95th percentiles) Pg C yr−1. By replacing national disaggregation with sub-national disaggregation in this study, the average 95th minus 5th percentile ranges of CO2 emission for all grids can be reduced from 417 to 68.2 Mg km−2 yr−1, indicating a significant reduction in uncertainty, because the uneven distribution of per-capita fuel consumptions within countries has been taken into account by using the sub-national fuel consumption data directly. Significant difference in per-capita CO2 emissions between urban and rural areas was found in developing nations (2.09 vs. 0.600 Mg C cap−1 yr−1), but not in developed ones (3.57 vs. 3.42 Mg C cap−1 yr−1), suggesting strong influence of the rapid urbanization of these countries on the carbon emission. By using the CO2 emission product, a new spatial pattern of terrestrial carbon sink was derived and the impact of sub-national disaggregation is discussed.
Published: 2012
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49. Modelling sub-grid wetland in the ORCHIDEE global land surface model: evaluation against river discharges and remotely sensed data

Author: Fabrice Papa, N. de Noblet-Ducoudré, S. L. Piao, P. Ciais, Pierre Friedlingstein, Agnès Ducharne, Charles D. Koven, C. Prigent, Isabelle Gouttevin, Bertrand Decharme, Bruno Ringeval, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University [Beijing], Institute of Tibetan Plateau Research, Chinese Academy of Sciences [Beijing] (CAS), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA), École normale supérieure - Paris (ENS Paris)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Centre National de la Recherche Scientifique (CNRS), University of Exeter, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Structure et fonctionnement des systèmes hydriques continentaux (SISYPHE), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE)-MINES ParisTech - École nationale supérieure des mines de Paris-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université de Cergy Pontoise (UCP), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Météo France, Peking University, Centre National de la Recherche Scientifique (CNRS), Université Grenoble Alpes (COMUE) (UGA), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-MINES ParisTech - École nationale supérieure des mines de Paris, Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS Paris), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), and Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Hydrology, geography, geography.geographical_feature_category, Floodplain, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], lcsh:QE1-996.5, 0207 environmental engineering, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Wetland, 02 engineering and technology, 15. Life on land, Spatial distribution, 01 natural sciences, lcsh:Geology, Coupling (computer programming), 13. Climate action, Streamflow, Soil water, Environmental science, Satellite, Scale (map), 020701 environmental engineering, 0105 earth and related environmental sciences
Abstract: The quality of the global hydrological simulations performed by Land Surface Models (LSMs) strongly depends on processes that occur at unresolved spatial scales. Approaches such as TOPMODEL have been developed, which allow soil moisture redistribution within each grid-cell, based upon sub-grid scale topography. Moreover, the coupling between TOPMODEL and a LSM appears as a potential way to simulate wetland extent dynamic and its sensitivity to climate, a recently identified research problem for biogeochemical modelling, including methane emissions. Global evaluation of the coupling between TOPMODEL and an LSM is difficult, and prior attempts have been indirect, based on the evaluation of the simulated river flow. This study presents a new way to evaluate this coupling, within the ORCHIDEE LSM, using remote sensing data of inundated areas. Because of differences in nature between the satellite derived information – inundation extent – and the variable diagnosed by TOPMODEL/ORCHIDEE – area at maximum soil water content –, the evaluation focuses on the spatial distribution of these two quantities as well as on their temporal variation. Despite some difficulties in exactly matching observed localized inundated events, we obtain a rather good agreement in the distribution of these two quantities at a global scale. Floodplains are not accounted for in the model, and this is a major limitation. The difficulty of reproducing the year-to-year variability of the observed inundated area (for instance, the decreasing trend by the end of 90s) is also underlined. Classical indirect evaluation based on comparison between simulated and observed riverflow is also performed and underlines difficulties to simulate riverflow after coupling with TOPMODEL. The relationship between inundation and river flow at the basin scale in the model is analyzed, using both methods (evaluation against remote sensing data and riverflow). Finally, we discuss the potential of the TOPMODEL/LSM coupling to simulate wetland areas. A major limitation of the coupling for this purpose is linked to its ability to simulate a global wetland coverage consistent with the commonly used datasets. However, it seems to be a good opportunity to account for the wetland areas sensitivity to the climate and thus to simulate its temporal variability.
Published: 2012
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50. Fertile forests produce biomass more efficiently

Author: S, Vicca, S, Luyssaert, J, Peñuelas, M, Campioli, F S, Chapin, P, Ciais, A, Heinemeyer, P, Högberg, W L, Kutsch, B E, Law, Y, Malhi, D, Papale, S L, Piao, M, Reichstein, E D, Schulze, and I A, Janssens
Subjects: Autotrophic Processes, Climate, Cell Respiration, Forestry, Biomass, Photosynthesis, Plant Roots, Carbon, Carbon Cycle, Trees
Abstract: Trees with sufficient nutrition are known to allocate carbon preferentially to aboveground plant parts. Our global study of 49 forests revealed an even more fundamental carbon allocation response to nutrient availability: forests with high-nutrient availability use 58 ± 3% (mean ± SE; 17 forests) of their photosynthates for plant biomass production (BP), while forests with low-nutrient availability only convert 42 ± 2% (mean ± SE; 19 forests) of annual photosynthates to biomass. This nutrient effect largely overshadows previously observed differences in carbon allocation patterns among climate zones, forest types and age classes. If forests with low-nutrient availability use 16 ± 4% less of their photosynthates for plant growth, what are these used for? Current knowledge suggests that lower BP per unit photosynthesis in forests with low- versus forests with high-nutrient availability reflects not merely an increase in plant respiration, but likely results from reduced carbon allocation to unaccounted components of net primary production, particularly root symbionts.
Published: 2012

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