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Lexun Wang,1 Lei Xiang,1,2 Shenghua Piao,1 Xiao Gong,3 Wanxing Zhou,4 Weixun Feng,5 Huilin Li,6 Leyu Li,7 Aisheng Wei,8 Qing Zhu,1 Xianglu Rong,1 Jiao Guo1,2 1Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine; Key Laboratory of Glucolipid Metabolic Disorder, Ministry of Education of China; Institute of Chinese Medicine, Guangdong Pharmaceutical University; Guangdong TCM Key Laboratory for Metabolic Diseases, Guangzhou, People’s Republic of China; 2The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, People’s Republic of China; 3School of Public Health, Guangdong Pharmaceutical University, Guangzhou, People’s Republic of China; 4Department of Internal Cardiology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, People’s Republic of China; 5Famous Doctor’s Studio, Qingyuan Hospital of Traditional Chinese Medicine, Qingyuan, People’s Republic of China; 6Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, People’s Republic of China; 7Department of Endocrinology, Zhongshan Hospital of Traditional Chinese Medicine, Zhongshan, People’s Republic of China; 8Department of Endocrinology, Foshan Hospital of Traditional Chinese Medicine, Foshan, People’s Republic of ChinaCorrespondence: Jiao GuoGuangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine; Key Laboratory of Glucolipid Metabolic Disorder, Ministry of Education of China; Institute of Chinese Medicine, Guangdong Pharmaceutical University; Guangdong TCM Key Laboratory for Metabolic Diseases, Guangzhou, People’s Republic of ChinaTel +86-02-39352818Fax +86-02-39352607Email gyguoyz@163.comBackground: Diabetic coronary heart disease (DCHD), the main macrovascular complication of type 2 diabetes mellitus (T2DM), is greatly harmful to T2DM patients. Traditional Chinese medicine (TCM) is an alternative and effective therapy to delay the development of macrovascular diseases, but the existing evidence of its efficacy and safety is insufficient. The aim of this multicenter, randomized, double-blind, placebo-controlled trial is to evaluate the efficacy and safety of Chinese Medicine Fufang Zhenzhu Tiaozhi capsule (FTZ) in treating DCHD.Patients and Methods: This study includes a 2-week run-in, 52-week treatment, and 52-week post-treatment follow-up. A total of 160 participants will be recruited and randomized into two groups. The treatment group will receive FTZ and basic treatment, while the control group will receive the placebo and basic treatment. The primary outcome is the combined outcome including the major adverse cardiovascular events, coronary restenosis, and unplanned revascularization. The combined secondary outcomes include all-cause mortality, acute coronary syndrome, ischemic stroke, heart failure, unplanned re-hospitalization mainly caused by acute complications of diabetes, other thromboembolic events, and TCM symptom indicators. The safety outcomes and adverse events will also be evaluated in this trial.Discussion: This trial evaluates the clinical effectiveness and safety of FTZ in patients with DCHD. The results are important to further explore the effectiveness of the comprehensive strategy “Tiao Gan Qi Shu Hua Zhuo” (modulating Gan, trigging key metabolic system to resolve pathogenic factors such as phlegm retention and dampness) in the prevention and control of glucolipid metabolic disorders (GLMD) including DCHD and T2DM. On the other hand, this study is the first trial of FTZ to observe cardiovascular outcomes through long-term follow-up after treatment of DCHD, which is of great value.Trial Registration: This trial was registered in the Chinese Clinical Trial Registry on April 07, 2019 (No. ChiCTR1900022345).Keywords: type 2 diabetes mellitus, traditional Chinese medicine, clinical study

© 2018 John Wiley & Sons Ltd Whether and how the timing of extreme events affects the direction and magnitude of legacy effects on tree growth is poorly understood. In this study, we use a global database of Ring-Width Index (RWI) from 2,500 sites to examine the impact and legacy effects (the departure of observed RWI from expected RWI) of extreme drought events during 1948–2008, with a particular focus on the influence of drought timing. We assessed the recovery of stem radial growth in the years following severe drought events with separate groupings designed to characterize the timing of the drought. We found that legacies from extreme droughts during the dry season (DS droughts) lasted longer and had larger impacts in each of the 3 years post drought than those from extreme droughts during the wet season (WS droughts). At the global scale, the average integrated legacy from DS droughts (0.18) was about nine times that from WS droughts (0.02). Site-level comparisons also suggest stronger negative impacts or weaker positive impacts of DS droughts on tree growth than WS droughts. Our results, therefore, highlight that the timing of drought is a crucial factor determining drought impacts on tree recovery. Further increases in baseline aridity could therefore exacerbate the impact of punctuated droughts on terrestrial ecosystems.

© 2018 John Wiley & Sons Ltd Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.

International audience; The terrestrial biosphere shows substantial inertia in its response to environmental change. Hence, assessments of transient changes in ecosystem properties to 2100 do not capture the full magnitude of the response realized once ecosystems reach an effective equilibrium with the changed environmental boundary conditions. This equilibrium state can be termed the committed state, in contrast to a transient state in which the ecosystem is in disequilibrium. The difference in ecosystem properties between the transient and committed states represents the committed change yet to be realized. Here an ensemble of dynamic global vegetation model simulations was used to assess the changes in tree cover and carbon storage for a variety of committed states, relative to a preindustrial baseline, and to attribute the drivers of uncertainty. Using a subset of simulations, the committed changes in these variables post-2100, assuming climate stabilization, were calculated. The results show large committed changes in tree cover and carbon storage, with model disparities driven by residence time in the tropics, and residence time and productivity in the boreal. Large changes remain ongoing well beyond the end of the 21st century. In boreal ecosystems, the simulated increase in vegetation carbon storage above preindustrial levels was 20-95 Pg C at 2 K of warming, and 45-201 Pg C at 5 K, of which 38-155 Pg C was due to expansion in tree cover. Reducing the large uncertainties in long-term commitment and rate-of-change of terrestrial carbon uptake will be crucial for assessments of emissions budgets consistent with limiting climate change.

International audience; Large-scale atmospheric circulation patterns (i.e., teleconnections) influence global climate variability patterns and can be studied to provide a simple framework for relating the complex response of ecosystems to climate. This study analyzes the effects of 15 major teleconnections on terrestrial ecosystem carbon fluxes during 1951-2012 using an ensemble of nine dynamic global vegetation models. We map the global pattern of the dominant teleconnections and find that these teleconnections significantly affect gross primary productivity variations over more than 82.1% of the global vegetated area, through mediating the global temperature and regional precipitation and cloud cover. The El Niño-Southern Oscillation, the Pacific Decadal Oscillation, and the Atlantic Multidecadal Oscillation are strongly correlated with global, hemispherical, and continental carbon fluxes and climatic variables, while the Northern Hemisphere teleconnections have only regional influences. Further research regarding the interactions among the teleconnections and the nonstationarity of the relationship between teleconnections and carbon fluxes is needed.

The year 2015 was, at the time, the warmest since 1880, and many regions in the Northern Hemisphere (NH) registered record breaking annual temperatures. Simultaneously, a remarkable and widespread growing season greening was observed over most of the NH in the record from the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). While the response of vegetation to climate change (i.e. the long term trend) is assumed to be predictable, it is still unclear whether it is also possible to predict the interannual variability in vegetation activity. Here, we evaluate whether the unprecedented magnitude and extent of the greening observed in 2015 corresponds to an expected response to the 2015 climate anomaly, or to a change in the sensitivity of NH vegetation to climate. We decompose NDVI into the long-term and interannual variability components, and find that the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) explain about half of NDVI interannual variability. This response is in addition to the long-term temperature and human-induced greening trend. We use a simple statistical approach to predict the NDVI anomaly in 2015, using the PDO and AMO states as predictors for interannual variability, and temperature and precipitation trends for the long-term component. We show that the 2015 anomaly can be predicted as an expected vegetation response to temperature and water-availability associated with the very strong state of the PDO in 2015. The link found between climate variability patterns and vegetation activity should contribute to increase the predictability of carbon-cycle processes at interannual time-scales, which may be relevant, for instance, for optimizing land-management strategies. ISSN:1748-9326 ISSN:1748-9318

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.

International audience; 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 $\pm$ 3% (mean $\pm$ SE; 17 forests) of their photosynthates for plant biomass production (BP), while forests with low-nutrient availability only convert 42 $\pm$ 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 $\pm$ 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.

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.

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.

A large number of silicon (Si) patterns consisting of nanopillars of varying diameter and pitch have been fabricated and further coated with diamond-like carbon (DLC) and perfluoropolyether (Z-DOL) films. The wetting behavior and nano-adhesion/friction of the patterns are investigated experimentally in relation to the nanostructures and the hydrophobicity of the materials. Measurements of water contact angle illustrate that the patterning-enhanced wettability of the Si flat surface, along with two distinct wettings which are in good agreement with the Wenzel and hemi-wicking states, depended on the value of the pitch-over-diameter ratio. In the case of the coated patterns, three wetting states are observed: the Cassie-Baxter, the Wenzel, and a transition from the Cassie-Baxter into the Wenzel, which varies with regard to the hydrophobic properties of the DLC and Z-DOL. In terms of tribological properties, it is demonstrated that a combination of the nanopatterns and the films is effective in reducing adhesive and frictional forces. In addition, the pitch and diameter of the patterns are found to significantly influence their adhesion/friction behaviors.

International audience; We model the carbon balance of European croplands between 1901 and 2000 in response to land use and management changes. The process-based ORCHIDEE-STICS model is applied here in a spatially explicit framework. We reconstructed land cover changes, together with an idealized history of agro-technology. These management parameters include the treatment of straw and stubble residues, application of mineral fertilizers, improvement of cultivar species and tillage. The model is integrated for wheat and maize during the period 1901-2000 forced by climate each 1/2-hour, and by atmospheric CO2, land cover change and agro-technology each year. Several tests are performed to identify the most sensitive agro-technological parameters that control the net biome productivity (NBP) in the 1990s, with NBP equaling for croplands the soil C balance. The current NBP is a small sink of 0.16 t C ha-1 yr-1. The value of NBP per unit area reflects past and current management, and to a minor extent the shrinking areas of arable land consecutive to abandonment during the 20th Century. The uncertainty associated with NBP is large, with a 1-sigma error of 0.18 t C ha-1 yr-1 obtained from a qualitative, but comprehensive budget of various error terms. The NBP uncertainty is dominated by unknown historical agro-technology changes (47%) and model structure (27%), with error in climate forcing playing a minor role. A major improvement to the framework would consist in using a larger number of representative crops. The uncertainty of historical land-use change derived from three different reconstructions, has a surprisingly small effect on NBP (0.01 t C ha-1 yr-1) because cropland area remained stable during the past 20 years in all the tested land use forcing datasets. Regional cross-validation of modeled NBP against soil C inventory measurements shows that our results are consistent with observations, within the uncertainties of both inventories and model. Our estimation of cropland NBP is however likely to be biased towards a sink, given that inventory data from different regions consistently indicate a small source whereas we model a small sink.

International audience; [1] We evaluated three global models of the coupled carbon-climate system against atmospheric CO 2 concentration measured at a network of stations. These three models, HadCM3LC, IPSL-CM2-C, and IPSL-CM4-LOOP, participated in the C 4 MIP experiment and in various other simulations of the future climate impacts on the land and ocean carbon cycle. A new set of performance metrics is defined and applied to quantify each model's ability to reproduce the global growth rate, the seasonal cycle, the El Niño-Southern Oscillation (ENSO)-forced interannual variability of atmospheric CO 2 , and the sensitivity to climatic variations. Knowing that the uncertainty on the amplitude, in 2100, of the climate-carbon feedback is mainly due to the uncertainty of the response of the terrestrial biosphere to the climate change, our new metrics primarily target the evaluation of the land parameterization of the carbon cycle. The modeled fluxes are prescribed to the same global atmospheric transport model LMDZ4, and the simulated concentrations are compared to available observations. We found that the IPSL-CM4-LOOP model is best able to reproduce the phase and amplitude of the atmospheric CO 2 seasonal cycle in the Northern Hemisphere, while the other two models generally underestimate the seasonal amplitude. This points to some shortcomings in describing the vegetation phenology and heterotropic respiration response to climate. We also found that IPSL-CM2-C produces a climate-driven abnormal source of CO 2 to the atmosphere in response to El Niño anomalies. Here a good model performance rests upon a realistic simulation of ENSO-type climate variability and the subsequent tropical carbon cycle response. The three climate models underestimate the sea surface temperature warm anomaly during an El Niño, but HadCM3LC does best in reproducing the interannual CO 2 variability. More efforts are needed to further develop metrics for assessing the sensitivity of the carbon cycle to climate change, and this work should now be extended to assess ocean carbon models against observations.

We estimated the long-term carbon balance [net biome production (NBP)] of European (EU-25) croplands and its component fluxes, over the last two decades. Net primary production (NPP) estimates, from different data sources ranged between 490 and 846 gC m−2 yr−1, and mostly reflect uncertainties in allocation, and in cropland area when using yield statistics. Inventories of soil C change over arable lands may be the most reliable source of information on NBP, but inventories lack full and harmonized coverage of EU-25. From a compilation of inventories we infer a mean loss of soil C amounting to 17 g m−2 yr−1. In addition, three process-based models, driven by historical climate and evolving agricultural technology, estimate a small sink of 15 g C m−2 yr−1 or a small source of 7.6 g C m−2 yr−1. Neither the soil C inventory data, nor the process model results support the previous European-scale NBP estimate by Janssens and colleagues of a large soil C loss of 90 ± 50 gC m−2 yr−1. Discrepancy between measured and modeled NBP is caused by erosion which is not inventoried, and the burning of harvest residues which is not modeled. When correcting the inventory NBP for the erosion flux, and the modeled NBP for agricultural fire losses, the discrepancy is reduced, and cropland NBP ranges between −8.3 ± 13 and −13 ± 33 g C m−2 yr−1 from the mean of the models and inventories, respectively. The mean nitrous oxide (N2O) flux estimates ranges between 32 and 37 g C Eq m−2 yr−1, which nearly doubles the CO2 losses. European croplands act as small CH4 sink of 3.3 g C Eq m−2 yr−1. Considering ecosystem CO2, N2O and CH4 fluxes provides for the net greenhouse gas balance a net source of 4247 g C Eq m−2 yr−1. Intensifying agriculture in Eastern Europe to the same level Western Europe amounts is expected to result in a near doubling of the N2O emissions in Eastern Europe. N2O emissions will then become the main source of concern for the impact of European agriculture on climate.

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Semantic lexical resources play an important part in both linguistic study and natural language engineering. In Lancaster, a large semantic lexical resource has been built over the past 14 years, which provides a knowledge base for the USAS semantic tagger. Capturing semantic lexicological theory and empirical lexical usage information extracted from corpora, the Lancaster semantic lexicon provides a valuable resource for the corpus research and NLP community. In this paper, we evaluate the lexical coverage of the semantic lexicon both in terms of genres and time periods. We conducted the evaluation on test corpora including the BNC sampler, the METER Corpus of law/court journalism reports and some corpora of Newsbooks, prose and fictional works published between 17th and 19th centuries. In the evaluation, the semantic lexicon achieved a lexical coverage of 98.49% on the BNC sampler, 95.38% on the METER Corpus and 92.76% -- 97.29% on the historical data. Our evaluation reveals that the Lancaster semantic lexicon has a remarkably high lexical coverage on modern English lexicon, but needs expansion with domain-specific terms and historical words. Our evaluation also shows that, in order to make claims about the lexical coverage of annotation systems as well as to render them ‘future proof’, we need to evaluate their potential both synchronically and diachronically across genres.

Annotation schemes for semantic field analysis use abstract concepts to classify words and phrases in a given text. The use of such schemes within lexicography is increasing. Indeed, our own UCREL semantic annotation system (USAS) is to form part of a web-based ‘intelligent’ dictionary (Herpiö 2002). As USAS was originally designed to enable automatic content analysis (Wilson and Rayson 1993), we have been assessing its usefulness in a lexicographical setting, and also comparing its taxonomy with schemes developed by lexicographers. This paper initially reports the comparisons we have undertaken with two dictionary taxonomies: the first was designed by Tom McArthur for use in the Longman Lexicon of Contemporary English, and the second by Collins Dictionaries for use in their Collins English Dictionary. We then assess the feasibility of mapping USAS to the CED tagset, before reporting our intentions to also map to WordNet (a reasonably comprehensive machine-useable database of the meanings of English words) via WordNet Domains (which augments WordNet 1.6 with 200+ domains). We argue that this type of research can provide a practical guide for tagset mapping and, by so doing, bring lexicographers one-step closer to using the semantic field as the organising principle for their general-purpose dictionaries.

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

Wepresent a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia usingmultiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food andAgriculture Organization-Forest Resource Assessment (FAO-FRA2015; country-level inventory estimates), the Emission Database forGlobalAtmospheric Research (EDGARv4.3), the ‘Houghton’ bookkeepingmodel that incorporates FAO-FRA data, an ensemble of 8 state-of-the-artDynamic Global Vegetation Models (DGVM), and2 recently published independent studies using primarily remote sensing techniques.The estimates are aggregated spatially to Southeast, East, and SouthAsia and temporally for three decades, 1980–1989, 1990–1999 and 2000–2009. Since 1980, net carbon emissions from LULCCin Asia were responsible for 20%–40%of global LULCCemissions, with emissions from Southeast Asia alone accounting for15%–25%of global LULCCemissions during the same period. In the 2000s and for allAsia, three estimates (FAO-FRA,DGVM,Houghton) were in agreement of a net source of carbon to the atmosphere,with meanestimates rangingbetween0.24 to0.41PgCyr$^{-1}$,whereasEDGARv4.3 suggested a net carbon sink of−0.17 Pg C yr$^{-1}$. Three of 4 estimates suggest that LULCCcarbon emissions declined by at least 34%in the preceding decade (1990–2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to includeemissions fromcarbon rich peatlands and land management, such as shifting cultivation andwood harvesting, which appear to be consistently underreported.

Year-to-year variability in CO2 fluxes can yield insight into climate-carbon cycle relationships, a fundamental yet uncertain aspect of the terrestrial carbon cycle. In this study, we use global observations from NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite for years 2015���2019 and a geostatistical inverse model to evaluate 5 years of interannual variability (IAV) in CO2 fluxes and its relationships with environmental drivers. OCO-2 launched in late 2014, and we specifically evaluate IAV during the time period when OCO-2 observations are available. We then compare inferences from OCO-2 with state-of-the-art process-based models (terrestrial biosphere model, TBMs). Results from OCO-2 suggest that the tropical grasslands biome (including grasslands, savanna, and agricultural lands within the tropics) makes contributions to global IAV during the 5 year study period that are comparable to tropical forests, a result that differs from a majority of TBMs. Furthermore, existing studies disagree on the environmental variables that drive IAV during this time period, and the analysis using OCO-2 suggests that both temperature and precipitation make comparable contributions. TBMs, by contrast, tend to estimate larger IAV during this time and usually estimate larger relative contributions from the extra-tropics. With that said, TBMs show little consensus on both the magnitude and the contributions of different regions to IAV. We further find that TBMs show a wide range of responses on the relationships of CO2 fluxes with annual anomalies in temperature and precipitation, and these relationships across most of the TBMs have a larger magnitude than inferred from OCO-2. Overall, the findings of this study highlight large uncertainties in process-based estimates of IAV during recent years and provide an avenue for evaluating these processes against inferences from OCO-2.

We present a new synthesis, based on a suite of complementary approaches, of the primary production and carbon sink in forests of the 25 member states of the European Union (EU-25) during 1990-2005. Upscaled terrestrial observations and model-based approaches agree within 25% on the mean net primary production (NPP) of forests, i.e. 520 +/- 75 g C m-2 yr-1 over a forest area of 1.32 x 106 km2 to 1.55 x 106 km2 (EU-25). New estimates of the mean long-term carbon forest sink (net biome production, NBP) of EU-25 forests amounts 75 +/- 20 g C m-2 yr-1. The ratio of NBP to NPP is 0.15 +/- 0.05. Estimates of the fate of the carbon inputs via NPP in wood harvests, forest fires, losses to lakes and rivers and heterotrophic respiration remain uncertain, which explains the considerable uncertainty of NBP. Inventory-based assessments and assumptions suggest that 29 +/- 15% of the NBP (i.e., 22 g C m-2 yr-1) is sequestered in the forest soil, but large uncertainty remains concerning the drivers and future of the soil organic carbon. The remaining 71 +/- 15% of the NBP (i.e., 53 g C m-2 yr-1) is realized as woody biomass increments. In the EU-25, the relatively large forest NBP is thought to be the result of a sustained difference between NPP, which increased during the past decades, and carbon losses primarily by harvest and heterotrophic respiration, which increased less over the same period.