Biotransformation of Chlorpyrifos Shewanella oneidensis MR-1 in the Presence of Goethite: Experimental Optimization and Degradation Products.

In this study, the degradation system of Shewanella oneidensis MR-1 and goethite was constructed with chlorpyrifos as the target contaminant. The effects of initial pH, contaminant concentration, and temperature on the removal rate of chlorpyrifos during the degradation process were investigated. The experimental conditions were optimized by response surface methodology with a Box-Behnken design (BBD). The results show that the removal rate of chlorpyrifos is 75.71% at pH = 6.86, an initial concentration of 19.18 mg·L-1, and a temperature of 30.71 °C. LC-MS/MS analyses showed that the degradation products were C4H11O3PS, C7H7Cl3NO4P, C9H11Cl2NO3PS, C7H7Cl3NO3PS, C9H11Cl3NO4P, C4H11O2PS, and C5H2Cl3NO. Presumably, the degradation pathways involved are: enzymatic degradation, hydrolysis, dealkylation, desulfur hydrolysis, and dechlorination. The findings of this study demonstrate the efficacy of the goethite/S. oneidensis MR-1 complex system in the removal of chlorpyrifos from water. Consequently, this research contributes to the establishment of a theoretical framework for the microbial remediation of organophosphorus pesticides in aqueous environments.

Biothiols-activated near-infrared frequency up-conversion luminescence probe for early evaluation of drug-induced hepatotoxicity.

A novel biothiols-sensitive near-infrared (NIR) fluorescent probe RhDN based on a rhodamine skeleton was developed for early detection of drug-induced hepatotoxicity in living mice. RhDN can be used not only as a conventional large stokes shift fluorescent (FL) probe, but also as a kind of anti-Stokes frequency upconversion luminescence (FUCL) molecular probe, which represents a long wavelength excitation (808 nm) to short wavelength emission (760 nm), and response to Cys/Hcy/GSH with high sensitivity. Compared with traditional FL methods, the FUCL method exhibited a lower detection limit of Cys, Hcy, and GSH in 75.1 nM, 101.8 nM, and 84.9 nM, respectively. We exemplify RhDN for tracking endogenously biothiols distribution in living cells and further realize real-time in vivo bioimaging of biothiols activity in mice with dual-mode luminescence system. Moreover, RhDN has been successfully applied to visualize the detection of drug-induced hepatotoxicity in living mice. Overall, this report presents a unique approach to the development of large stokes shift NIR FUCL molecular probes for in vitro and in vivo biothiols biosensing.

Predicting rice productivity for ground data-sparse regions: A transferable framework and its application to North Korea.

The use of observation-dependent methods for crop productivity and food security assessment is challenging in data-sparse regions. This study presents a transferable framework and applies it to North Korea (NK) to assess rice productivity based on climate similarity, transferable machine-learning techniques, and extendable multi-source data. We initially divided the primary phenological stages of rice in the study region and extracted dynamic rice distributions based on Moderate Resolution Imaging Spectroradiometer products and phenological observations. We compared the performances of four representative environmentally driven models (Linear Regression, back-propagation Neural Network, Support Vector Machine, and Random Forest) in simulating rice productivity using an extensive dataset that included multi-angle vegetation monitoring, climate variables, and planting distribution information. The framework integrated an optimal environmentally driven model with agricultural management practices for transferability to predict rice productivity in NK over multiple years. Additionally, two crop growth scenarios (whole growth period (WGP) and seeding-heading period (SHP)) were compared to assess pre-harvest forecasting capabilities and identify dominant factors. Finally, independent datasets from the Food and Agriculture Organization, World Food Program, and Global Gridded Crop Models were used to validate the magnitude and spatial distribution of the predicted results. The results showed that phenological identification based on remote sensing can accurately capture rice growth characteristics and map rice distribution. Random Forest outperformed other models in simulating rice productivity variation, with r-squares of 0.87 and 0.83 in the WGP and SHP, respectively. The solar-induced chlorophyll fluorescence, maximum temperature, and evapotranspiration collectively determined approximately 40 % of the variation in yield simulated using Random Forest. Conversely, planting areas contributed over 42 % of the variation in rice production. Compared to Food and Agriculture Organization statistics, the environmentally driven framework explained 78.72 % and 76.89 % of the production variation and 69.42 % and 71.15 % of the yield variation in NK under the WGP and SHP, respectively. Moreover, the environmental management-driven framework captured over 90 % of the yield variation. The predicted spatial pattern of rice productivity exhibited significant concordance with the World Food Program and Global Gridded Crop Model reports. In summary, the proposed transferable framework for crop productivity assessment contributes to early warnings of production reduction and has the potential for scalability across various crops and data-sparse regions.

Global nitrous oxide emissions from livestock manure during 1890-2020: An IPCC tier 2 inventory.

Nitrous oxide (N2O) emissions from livestock manure contribute significantly to the growth of atmospheric N2O, a powerful greenhouse gas and dominant ozone-depleting substance. Here, we estimate global N2O emissions from livestock manure during 1890-2020 using the tier 2 approach of the 2019 Refinement to the 2006 IPCC Guidelines. Global N2O emissions from livestock manure increased by ~350% from 451 [368-556] Gg N year-1 in 1890 to 2042 [1677-2514] Gg N year-1 in 2020. These emissions contributed ~30% to the global anthropogenic N2O emissions in the decade 2010-2019. Cattle contributed the most (60%) to the increase, followed by poultry (19%), pigs (15%), and sheep and goats (6%). Regionally, South Asia, Africa, and Latin America dominated the growth in global emissions since the 1990s. Nationally, the largest emissions were found in India (329 Gg N year-1), followed by China (267 Gg N year-1), the United States (163 Gg N year-1), Brazil (129 Gg N year-1) and Pakistan (102 Gg N year-1) in the 2010s. We found a substantial impact of livestock productivity, specifically animal body weight and milk yield, on the emission trends. Furthermore, a large spread existed among different methodologies in estimates of global N2O emission from livestock manure, with our results 20%-25% lower than those based on the 2006 IPCC Guidelines. This study highlights the need for robust time-variant model parameterization and continuous improvement of emissions factors to enhance the precision of emission inventories. Additionally, urgent mitigation is required, as all available inventories indicate a rapid increase in global N2O emissions from livestock manure in recent decades.

Increased nitrous oxide emissions from global lakes and reservoirs since the pre-industrial era.

Lentic systems (lakes and reservoirs) are emission hotpots of nitrous oxide (N2O), a potent greenhouse gas; however, this has not been well quantified yet. Here we examine how multiple environmental forcings have affected N2O emissions from global lentic systems since the pre-industrial period. Our results show that global lentic systems emitted 64.6 ± 12.1 Gg N2O-N yr-1 in the 2010s, increased by 126% since the 1850s. The significance of small lentic systems on mitigating N2O emissions is highlighted due to their substantial emission rates and response to terrestrial environmental changes. Incorporated with riverine emissions, this study indicates that N2O emissions from global inland waters in the 2010s was 319.6 ± 58.2 Gg N yr-1. This suggests a global emission factor of 0.051% for inland water N2O emissions relative to agricultural nitrogen applications and provides the country-level emission factors (ranging from 0 to 0.341%) for improving the methodology for national greenhouse gas emission inventories.

Net greenhouse gas balance in U.S. croplands: How can soils be part of the climate solution?

Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2 ) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2 O) and methane (CH4 ). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2 O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered 13.2 ± 1.16 $$ 13.2\pm 1.16 $$ Tg CO2 -C year-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39 ± 0.02 $$ 0.39\pm 0.02 $$ Tg N2 O-N year-1 and 0.21 ± 0.01 $$ 0.21\pm 0.01 $$ Tg CH4 -C year-1 , respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 ± 11.46 $$ 122.3\pm 11.46 $$ Tg CO2 -eq year-1 , with the largest contribution from N2 O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2 O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.

Soil legacy nutrients contribute to the decreasing stoichiometric ratio of N and P loading from the Mississippi River Basin.

Human-induced nitrogen-phosphorus (N, P) imbalance in terrestrial ecosystems can lead to disproportionate N and P loading to aquatic ecosystems, subsequently shifting the elemental ratio in estuaries and coastal oceans and impacting both the structure and functioning of aquatic ecosystems. The N:P ratio of nutrient loading to the Gulf of Mexico from the Mississippi River Basin increased before the late 1980s driven by the enhanced usage of N fertilizer over P fertilizer, whereafter the N:P loading ratio started to decrease although the N:P ratio of fertilizer application did not exhibit a similar trend. Here, we hypothesize that different release rates of soil legacy nutrients might contribute to the decreasing N:P loading ratio. Our study used a data-model integration framework to evaluate N and P dynamics and the potential for long-term accumulation or release of internal soil nutrient legacy stores to alter the ratio of N and P transported down the rivers. We show that the longer residence time of P in terrestrial ecosystems results in a much slower release of P to coastal oceans than N. If contemporary nutrient sources were reduced or suspended, P loading sustained by soil legacy P would decrease much slower than that of N, causing a decrease in the N and P loading ratio. The longer residence time of P in terrestrial ecosystems and the increasingly important role of soil legacy nutrients as a loading source may explain the decreasing N:P loading ratio in the Mississippi River Basin. Our study underscores a promising prospect for N loading control and the urgency to integrate soil P legacy into sustainable nutrient management strategies for aquatic ecosystem health and water security.

Dynamics and controls of inland water CH4 emissions across the Conterminous United States: 1860-2019.

Inland waters (rivers, lakes, and reservoirs) have been recognized as hotspots of methane (CH4) emissions. However, the magnitude and spatiotemporal pattern of CH4 emissions and their underlying mechanisms remain largely unknown due to a lack of process-based quantification of CH4 production, consumption, and evasion within the aquatic ecosystem. Here we developed a process-based aquatic CH4 module within the framework of the Dynamic Land Ecosystem Model (DLEM) to explicitly simulate inland water carbon fluxes and the associated CH4 processes. We further applied this model to assess the inland-water CH4 emissions across the conterminous United States (CONUS) as affected by the climate variability, land use, fertilizer nitrogen (N) application, atmospheric N deposition, and rising atmospheric CO2 concentration during 1860-2019. The inland water CH4 emissions across the CONUS had doubled from the 1860s (1.65±0.18 Tg CH4-C∙yr-1) to the 2010s (3.73±0.36 Tg CH4-C∙yr-1). In the 2000s, inland water accounts for 8% of the regional CH4 budget that offsets 11∼14% of the terrestrial C uptake across the CONUS. Our study showed that the small headwater streams (1st -3rd order) account for 49% of the diffusive CH4, and reservoirs constitute 50% of the ebullitive CH4 emissions during the 2010s. Climate change and variability played a dominant role in the increased CH4 emissions from rivers and lakes. This study implies that effective mitigation strategies to reduce CH4 emissions should pay much attention to global climate change and headwater stream management.

A 130-year global inventory of methane emissions from livestock: Trends, patterns, and drivers.

Livestock contributes approximately one-third of global anthropogenic methane (CH4 ) emissions. Quantifying the spatial and temporal variations of these emissions is crucial for climate change mitigation. Although country-level information is reported regularly through national inventories and global databases, spatially explicit quantification of century-long dynamics of CH4 emissions from livestock has been poorly investigated. Using the Tier 2 method adopted from the 2019 Refinement to 2006 IPCC guidelines, we estimated CH4 emissions from global livestock at a spatial resolution of 0.083° (~9 km at the equator) during the period 1890-2019. We find that global CH4 emissions from livestock increased from 31.8 [26.5-37.1] (mean [minimum-maximum of 95% confidence interval) Tg CH4 yr-1 in 1890 to 131.7 [109.6-153.7] Tg CH4 yr-1 in 2019, a fourfold increase in the past 130 years. The growth in global CH4 emissions mostly occurred after 1950 and was mainly attributed to the cattle sector. Our estimate shows faster growth in livestock CH4 emissions as compared to the previous Tier 1 estimates and is ~20% higher than the estimate from FAOSTAT for the year 2019. Regionally, South Asia, Brazil, North Africa, China, the United States, Western Europe, and Equatorial Africa shared the majority of the global emissions in the 2010s. South Asia, tropical Africa, and Brazil have dominated the growth in global CH4 emissions from livestock in the recent three decades. Changes in livestock CH4 emissions were primarily associated with changes in population and national income and were also affected by the policy, diet shifts, livestock productivity improvement, and international trade. The new geospatial information on the magnitude and trends of livestock CH4 emissions identifies emission hotspots and spatial-temporal patterns, which will help to guide meaningful CH4 mitigation practices in the livestock sector at both local and global scales.

Grassland productivity response to droughts in northern China monitored by satellite-based solar-induced chlorophyll fluorescence.

Solar-induced chlorophyll fluorescence (SIF) has been applied to a wide range of ecological studies, such as monitoring and assessing drought, vegetation productivity, and crop yield. Previous studies have shown that SIF is highly related to gross primary production (GPP), but its correlation with aboveground biomass (AGB) still needs further exploration. In this study, we explored the potential of SIF for monitoring and assessing the effects of climate change and meteorological drought on grassland AGB changes in the northern grassland of China. By examining the relationship between the Orbiting Carbon Observatory 2 (OCO-2) SIF and drought indices, we assessed the response of northern grassland productivity to meteorological drought conditions. The results show that SIF is very sensitive to meteorological drought and can capture drought events and the dynamics of grassland growth in different grassland types. The correlation between SIF, drought indices, and AGB varied with grassland type. A gradient boosting decision tree (GBDT) was used to explore the relationships between SIF and the impact variables in the grassland ecosystem. We found that climatic factors (e.g., annual mean growing season precipitation, annual mean growing season temperature, and annual mean vapor pressure deficit) and human activity (e.g., grazing intensity) significantly impacted the interannual variability of grassland productivity. Our results indicate that SIF changes can reflect the seasonal dynamics of vegetation growth in the northern grassland of China. Therefore, SIF can be used as benchmark data for evaluating the performance of terrestrial ecosystem models in simulating ecosystem productivity in this region. The high sensitivity of SIF to drought suggests that it is a useful tool for monitoring and assessing drought events.

Building social resilience in North Korea can mitigate the impacts of climate change on food security.

Adaptation based on social resilience is proposed as an effective measure to mitigate hunger and avoid food shocks caused by climate change. But these have not been investigated comprehensively in climate-sensitive regions. North Korea (NK) and its neighbours, South Korea and China, represent three economic levels that provide us with examples for examining climatic risk and quantifying the contribution of social resilience to rice production. Here our data-driven estimates show that climatic factors determined rice biomass changes in NK from 2000 to 2017, and climate extremes triggered reductions in production in 2000 and 2007. If no action is taken, NK will face a higher climatic risk (with continuous high-temperature heatwaves and precipitation extremes) by the 2080s under a high-emissions scenario, when rice biomass and production are expected to decrease by 20.2% and 14.4%, respectively, thereby potentially increasing hunger in NK. Social resilience (agricultural inputs and population development for South Korea; resource use for China) mitigated climate shocks in the past 20 years (2000-2019), even transforming adverse effects into benefits. However, this effect was not significant in NK. Moreover, the contribution of social resilience to food production in the undeveloped region (15.2%) was far below the contribution observed in the developed and developing regions (83.0% and 86.1%, respectively). These findings highlight the importance of social resilience to mitigate the adverse effects of climate change on food security and human hunger and provide necessary quantitative information.

Terrestrial biodiversity threatened by increasing global aridity velocity under high-level warming.

Global aridification is projected to intensify. Yet, our knowledge of its potential impacts on species ranges remains limited. Here, we investigate global aridity velocity and its overlap with three sectors (natural protected areas, agricultural areas, and urban areas) and terrestrial biodiversity in historical (1979 through 2016) and future periods (2050 through 2099), with and without considering vegetation physiological response to rising CO2 Both agricultural and urban areas showed a mean drying velocity in history, although the concurrent global aridity velocity was on average +0.05/+0.20 km/yr-1 (no CO2 effects/with CO2 effects; "+" denoting wetting). Moreover, in drylands, the shifts of vegetation greenness isolines were found to be significantly coupled with the tracks of aridity velocity. In the future, the aridity velocity in natural protected areas is projected to change from wetting to drying across RCP (representative concentration pathway) 2.6, RCP6.0, and RCP8.5 scenarios. When accounting for spatial distribution of terrestrial taxa (including plants, mammals, birds, and amphibians), the global aridity velocity would be -0.15/-0.02 km/yr-1 ("-" denoting drying; historical), -0.12/-0.15 km/yr-1 (RCP2.6), -0.36/-0.10 km/yr-1 (RCP6.0), and -0.75/-0.29 km/yr-1 (RCP8.5), with amphibians particularly negatively impacted. Under all scenarios, aridity velocity shows much higher multidirectionality than temperature velocity, which is mainly poleward. These results suggest that aridification risks may significantly influence the distribution of terrestrial species besides warming impacts and further impact the effectiveness of current protected areas in future, especially under RCP8.5, which best matches historical CO2 emissions [C. R. Schwalm et al., Proc. Natl. Acad. Sci. U.S.A. 117, 19656-19657 (2020)].

A comprehensive quantification of global nitrous oxide sources and sinks.

Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum-maximum estimates: 12.2-23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9-17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2-11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies-particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O-climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.

Increased greenhouse gas emissions intensity of major croplands in China: Implications for food security and climate change mitigation.

Balancing crop production and greenhouse gas (GHG) emissions from agriculture soil requires a better understanding and quantification of crop GHG emissions intensity, a measure of GHG emissions per unit crop production. Here we conduct a state-of-the-art estimate of the spatial-temporal variability of GHG emissions intensities for wheat, maize, and rice in China from 1949 to 2012 using an improved agricultural ecosystem model (Dynamic Land Ecosystem Model-Agriculture Version 2.0) and meta-analysis covering 172 field-GHG emissions experiments. The results show that the GHG emissions intensities of these croplands from 1949 to 2012, on average, were 0.10-1.31 kg CO2 -eq/kg, with a significant increase rate of 1.84-3.58 × 10-3  kg CO2 -eq kg-1  year-1 . Nitrogen fertilizer was the dominant factor contributing to the increase in GHG emissions intensity in northern China and increased its impact in southern China in the 2000s. Increasing GHG emissions intensity implies that excessive fertilizer failed to markedly stimulate crop yield increase in China but still exacerbated soil GHG emissions. This study found that overfertilization of more than 60% was mainly located in the winter wheat-summer maize rotation systems in the North China Plain, the winter wheat-rice rotation systems in the middle and lower reaches of the Yangtze River and southwest China, and most of the double rice systems in the South. Our simulations suggest that roughly a one-third reduction in the current N fertilizer application level over these "overfertilization" regions would not significantly influence crop yield but decrease soil GHG emissions by 29.60%-32.50% and GHG emissions intensity by 0.13-0.25 kg CO2 -eq/kg. This reduction is about 29% and 5% of total agricultural soil GHG emissions in China and the world, respectively. This study suggests that improving nitrogen use efficiency would be an effective strategy to mitigate GHG emissions and sustain China's food security.

A health education model based on knowledge, attitude, and practice used as adjunct therapy for metabolic syndrome complicated with acute pancreatitis: A case report.

Herein, a relatively rare case is reported in which a knowledge, attitude, and practice (KAP) health education model was applied in a young female patient with metabolic syndrome (MS) and acute pancreatitis (AP), with a satisfactory effect. The purpose of this report is to provide a reference for a viable health education program in clinical practice for intervention of MS with concurrent AP in the absence of clinical trials. The patient's unhealthy lifestyle led to obesity, diabetes mellitus, severe fatty liver, hyperlipidemia, and AP. We used a KAP health education model in a nursing intervention and evidence-based multidisciplinary cooperation to develop a personalized diet, exercise plan, education plan, and continuous care of the patient after discharge from the hospital. Within 2 months, the patient achieved weight loss, stable blood lipids, controlled blood sugar levels, and decreased glycated hemoglobin level from 9.0% to 5.4%. This KAP-based health education model has clinical importance as an intervention for lifestyle modification in patients with MS and AP. This approach can be adopted to help other patients to effectively control and prevent the recurrence of diseases.

Global ammonia emissions from synthetic nitrogen fertilizer applications in agricultural systems: Empirical and process-based estimates and uncertainty.

Excessive ammonia (NH3 ) emitted from nitrogen (N) fertilizer applications in global croplands plays an important role in atmospheric aerosol production, resulting in visibility reduction and regional haze. However, large uncertainty exists in the estimates of NH3 emissions from global and regional croplands, which utilize different data and methods. In this study, we have coupled a process-based Dynamic Land Ecosystem Model (DLEM) with the bidirectional NH3 exchange module in the Community Multiscale Air-Quality (CMAQ) model (DLEM-Bi-NH3 ) to quantify NH3 emissions at the global and regional scale, and crop-specific NH3 emissions globally at a spatial resolution of 0.5° × 0.5° during 1961-2010. Results indicate that global NH3 emissions from N fertilizer use have increased from 1.9 ± 0.03 to 16.7 ± 0.5 Tg N/year between 1961 and 2010. The annual increase of NH3 emissions shows large spatial variations across the global land surface. Southern Asia, including China and India, has accounted for more than 50% of total global NH3 emissions since the 1980s, followed by North America and Europe. Rice cultivation has been the largest contributor to total global NH3 emissions since the 1990s, followed by corn and wheat. In addition, results show that empirical methods without considering environmental factors (constant emission factor in the IPCC Tier 1 guideline) could underestimate NH3 emissions in context of climate change, with the highest difference (i.e., 6.9 Tg N/year) occurring in 2010. This study provides a robust estimate on global and regional NH3 emissions over the past 50 years, which offers a reference for assessing air quality consequences of future nitrogen enrichment as well as nitrogen use efficiency improvement.

Global soil nitrous oxide emissions since the preindustrial era estimated by an ensemble of terrestrial biosphere models: Magnitude, attribution, and uncertainty.

Our understanding and quantification of global soil nitrous oxide (N2 O) emissions and the underlying processes remain largely uncertain. Here, we assessed the effects of multiple anthropogenic and natural factors, including nitrogen fertilizer (N) application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO2 concentration, on global soil N2 O emissions for the period 1861-2016 using a standard simulation protocol with seven process-based terrestrial biosphere models. Results suggest global soil N2 O emissions have increased from 6.3 ± 1.1 Tg N2 O-N/year in the preindustrial period (the 1860s) to 10.0 ± 2.0 Tg N2 O-N/year in the recent decade (2007-2016). Cropland soil emissions increased from 0.3 Tg N2 O-N/year to 3.3 Tg N2 O-N/year over the same period, accounting for 82% of the total increase. Regionally, China, South Asia, and Southeast Asia underwent rapid increases in cropland N2 O emissions since the 1970s. However, US cropland N2 O emissions had been relatively flat in magnitude since the 1980s, and EU cropland N2 O emissions appear to have decreased by 14%. Soil N2 O emissions from predominantly natural ecosystems accounted for 67% of the global soil emissions in the recent decade but showed only a relatively small increase of 0.7 ± 0.5 Tg N2 O-N/year (11%) since the 1860s. In the recent decade, N fertilizer application, N deposition, manure N application, and climate change contributed 54%, 26%, 15%, and 24%, respectively, to the total increase. Rising atmospheric CO2 concentration reduced soil N2 O emissions by 10% through the enhanced plant N uptake, while land cover change played a minor role. Our estimation here does not account for indirect emissions from soils and the directed emissions from excreta of grazing livestock. To address uncertainties in estimating regional and global soil N2 O emissions, this study recommends several critical strategies for improving the process-based simulations.

Amazon drought and forest response: Largely reduced forest photosynthesis but slightly increased canopy greenness during the extreme drought of 2015/2016.

Amazon droughts have impacted regional ecosystem functioning as well as global carbon cycling. The severe dry-season droughts in 2005 and 2010, driven by Atlantic sea surface temperature (SST) anomaly, have been widely investigated in terms of drought severity and impacts on ecosystems. Although the influence of Pacific SST anomaly on wet-season precipitation has been well recognized, it remains uncertain to what extent the droughts driven by Pacific SST anomaly could affect forest greenness and photosynthesis in the Amazon. Here, we examined the monthly and annual dynamics of forest greenness and photosynthetic capacity when Amazon ecosystems experienced an extreme drought in 2015/2016 driven by a strong El Niño event. We found that the drought during August 2015-July 2016 was one of the two most severe meteorological droughts since 1901. Due to the enhanced solar radiation during this drought, overall forest greenness showed a small increase, and 21.6% of forests even greened up (greenness index anomaly ≥1 standard deviation). In contrast, solar-induced chlorophyll fluorescence (SIF), an indicator of vegetation photosynthetic capacity, showed a significant decrease. Responses of forest greenness and photosynthesis decoupled during this drought, indicating that forest photosynthesis could still be suppressed regardless of the variation in canopy greenness. If future El Niño frequency increases as projected by earth system models, droughts would result in persistent reduction in Amazon forest productivity, substantial changes in tree composition, and considerable carbon emissions from Amazon.

Tea consumption and the risk of ovarian cancer: A meta-analysis of epidemiological studies.

A large number of epidemiological studies have provided conflicting results about the relationship between tea consumption and ovarian cancer. This study aimed to clarify the association between tea consumption and ovarian cancer. A literature search of the MEDICINE, Scopus, PubMed, and Web of Science databases was performed in April 2016. A total of 18 (11 case-control and 7 cohort) studies, representing data for 701,857 female subjects including 8,683 ovarian cancer cases, were included in the meta-analysis. A random-effects meta-analysis was used to compute the pooled relative risks (RR), meta regression, and publication bias, and heterogeneity analyses were performed for the included trials. We found that tea consumption had a significant protective effect against ovarian cancer (relative risk [RR] = 0.86; 95% confidence interval [CI]: 0.76, 0.96). The relationship was confirmed particularly after adjusting for family history of cancer (RR = 0.85; 95% CI: 0.72, 0.97), menopause status (RR = 0.85; 95% CI: 0.72, 0.98), education (RR = 0.82; 95% CI: 0.68, 0.96), BMI (RR = 0.85; 95% CI: 0.70, 1.00) , smoking (RR = 0.83; 95% CI: 0.72, 0.93) and Jadad score of 3 (RR = 0.76; 95% CI: 0.56, 0.95) and 5 (RR = 0.74; 95% CI: 0.59, 0.89). The Begg's and Egger's tests (all P > 0.01) showed no evidence of publication bias. In conclusion, our meta-analysis showed an inverse association between tea consumption and ovarian cancer risk. High quality cohort-clinical trials should be conducted on different tea types and their relationship with ovarian cancer.

Methane emission from global livestock sector during 1890-2014: Magnitude, trends and spatiotemporal patterns.

Human demand for livestock products has increased rapidly during the past few decades largely due to dietary transition and population growth, with significant impact on climate and the environment. The contribution of ruminant livestock to greenhouse gas (GHG) emissions has been investigated extensively at various scales from regional to global, but the long-term trend, regional variation and drivers of methane (CH4 ) emission remain unclear. In this study, we use Intergovernmental Panel on Climate Change (IPCC) Tier II guidelines to quantify the evolution of CH4 emissions from ruminant livestock during 1890-2014. We estimate that total CH4 emissions in 2014 was 97.1 million tonnes (MT) CH4 or 2.72 Gigatonnes (Gt) CO2 -eq (1 MT = 1012 g, 1 Gt = 1015 g) from ruminant livestock, which accounted for 47%-54% of all non-CO2 GHG emissions from the agricultural sector. Our estimate shows that CH4 emissions from the ruminant livestock had increased by 332% (73.6 MT CH4 or 2.06 Gt CO2 -eq) since the 1890s. Our results further indicate that livestock sector in drylands had 36% higher emission intensity (CH4 emissions/km2 ) compared to that in nondrylands in 2014, due to the combined effect of higher rate of increase in livestock population and low feed quality. We also find that the contribution of developing regions (Africa, Asia and Latin America) to the total CH4 emissions had increased from 51.7% in the 1890s to 72.5% in the 2010s. These changes were driven by increases in livestock numbers (LU units) by up to 121% in developing regions, but decreases in livestock numbers and emission intensity (emission/km2 ) by up to 47% and 32%, respectively, in developed regions. Our results indicate that future increases in livestock production would likely contribute to higher CH4 emissions, unless effective strategies to mitigate GHG emissions in livestock system are implemented.