Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Soil organic carbon is a key determinant of CH4 sink in global forest soils

Soil organic carbon (SOC) is a primary regulator of the forest-climate feedback. However, its indicative capability for the soil CH₄ sink is poorly understood due to the incomplete knowledge of the underlying mechanisms. Therefore, SOC is not explicitly included in the current model estimation of the global forest CH₄ sink. Here, using in-situ observations, global meta-analysis, and process-based modeling, we provide evidence that SOC constitutes an important variable that governs the forest CH₄ sink. We find that a CH₄ sink is enhanced with increasing SOC content on regional and global scales. The revised model with SOC function better reproduces the field observation and estimates a 39% larger global forest CH₄ sink (24.27 Tg CH₄ yr^-1) than the model without considering SOC effects (17.46 Tg CH₄ yr^-1). This study highlights the role of SOC in the forest CH₄ sink, which shall be factored into future global CH₄ budget quantification.

China's terrestrial ecosystem carbon balance during the 20th century: an analysis with a process-based biogeochemistry model

BACKGROUND

China's terrestrial ecosystems play a pronounced role in the global carbon cycle. Here we combine spatially-explicit information on vegetation, soil, topography, climate and land use change with a process-based biogeochemistry model to quantify the responses of terrestrial carbon cycle in China during the 20th century.

RESULTS

At a century scale, China's terrestrial ecosystems have acted as a carbon sink averaging at 96 Tg C yr^- 1, with large inter-annual and decadal variabilities. The regional sink has been enhanced due to the rising temperature and CO₂ concentration, with a slight increase trend in carbon sink strength along with the enhanced net primary production in the century. The areas characterized by C source are simulated to extend in the west and north of the Hu Huanyong line, while the eastern and southern regions increase their area and intensity of C sink, particularly in the late 20th century. Forest ecosystems dominate the C sink in China and are responsible for about 64% of the total sink. On the century scale, the increase in carbon sinks in China's terrestrial ecosystems is mainly contributed by rising CO₂. Afforestation and reforestation promote an increase in terrestrial carbon uptake in China from 1950s. Although climate change has generally contributed to the increase of carbon sinks in terrestrial ecosystems in China, the positive effect of climate change has been diminishing in the last decades of the 20th century.

CONCLUSION

This study focuses on the impacts of climate, CO₂ and land use change on the carbon cycle, and presents the potential trends of terrestrial ecosystem carbon balance in China at a century scale. While a slight increase in carbon sink strength benefits from the enhanced vegetation carbon uptake in China's terrestrial ecosystems during the 20th century, the increase trend may diminish or even change to a decrease trend under future climate change.

Regional trends and drivers of the global methane budget

The ongoing development of the Global Carbon Project (GCP) global methane (CH₄ ) budget shows a continuation of increasing CH₄ emissions and CH₄ accumulation in the atmosphere during 2000-2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH₄ emission estimates demonstrates robust temporal trends with CH₄ emissions increasing in 16 of the 19 regions. Five regions-China, Southeast Asia, USA, South Asia, and Brazil-account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270 Tg CH₄  yr^-1 in 2008-2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH₄ emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH₄ burden and the greatest opportunities for greenhouse gas abatement.

Spatial state distribution and phase transition of non-uniform water in soils: Implications for engineering and environmental sciences

The physical behaviors of water in the interface are the fundamental to discovering the engineering properties and environmental effects of aqueous porous media (e.g., soils). The pore water pressure (PWP) is a key parameter to characterize the pore water state (PWS) and its phase transition in the micro interface. Traditionally, the water in the interface is frequently believed to be uniform, negative in pressure and tensile based on macroscopic tests and Gibbs interface model. However, the water in the interface is a non-uniform and compressible fluid (part of tensile and part of compressed), forming a spatial profile of density and PWP depending on its distance from the substrate interface. Herein, we introduced the static and dynamic theory methods of non-uniform water based on diffuse interface model to analyze non-uniform water state dynamics and water density and PWP. Based on the theory of non-uniform water, we gave a clear stress analysis on soil water and developed the concepts of PWS, PWP and matric potential in classical soil mechanics. In addition, the phase transition theory of non-uniform water is also examined. In nature, the generalized Clausius-Clapeyron equation (GCCE) is consistent with Clapeyron equation. Therefore, a unified interpretation is proposed to justify the use of GCCE to represent frozen soil water dynamics. Furthermore, the PWP description of non-uniform water can be well verified by some experiments focusing on property variations in the interface area, including the spatial water density profile and unfrozen water content variations with decreasing temperature and other factors. In turn, PWP spatial distribution of non-uniform water and its states can well explain some key phenomena on phase transition during ice or hydrate formation, including the discrepancies of phase transition under a wide range of conditions.

An improved nightlight threshold method for revealing the spatiotemporal dynamics and driving forces of urban expansion in China

An accurate and efficient extraction of urban extent is important for understanding the dynamics of urban expansion process and for sustainable planning and management of cities. We proposed an improved dynamic nightlight threshold method to model urban extent and to reveal the spatiotemporal dynamics and driving forces of urban expansion. Differing from previous studies, we correct the blooming and over-saturation problems of nighttime light (NTL), and highlight a combination of NTL with urban population data for determining a yearly-continued and city-class-wide threshold for urban mapping. China is selected as a case study area to test the improved method and to gain insights to its urban expansion process. Through the validation, our method has been proven to be more accurate than the traditional NTL threshold method. Accordingly, the yearly-continued NTL data can better describe the changing patterns and driving forces of urban expansion than the yearly-discontinued land use and land cover data do. It is found that the total urban area in China has more than quadrupled from 25.2 in 1992 to 108.2 thousand km² in 2013. Some significant pulses of urban expansion have been detected in our study, which may be attributed to the policy and socioeconomic impacts. Moreover, the panel regression based on annual NTL data indicates that GDP is a more important driver of urban expansion than urban population.

Improved Constraints on Global Methane Emissions and Sinks Using δ 13C-CH4

We study the drivers behind the global atmospheric methane (CH4) increase observed after 2006. Candidate emission and sink scenarios are constructed based on proposed hypotheses in the literature. These scenarios are simulated in the TM5 tracer transport model for 1984-2016 to produce three-dimensional fields of CH4 and δ 13C-CH4, which are compared with observations to test the competing hypotheses in the literature in one common model framework. We find that the fossil fuel (FF) CH4 emission trend from the Emissions Database for Global Atmospheric Research 4.3.2 inventory does not agree with observed δ 13C-CH4. Increased FF CH4 emissions are unlikely to be the dominant driver for the post-2006 global CH4 increase despite the possibility for a small FF emission increase. We also find that a significant decrease in the abundance of hydroxyl radicals (OH) cannot explain the post-2006 global CH4 increase since it does not track the observed decrease in global mean δ 13C-CH4. Different CH4 sinks have different fractionation factors for δ 13C-CH4, thus we can investigate the uncertainty introduced by the reaction of CH4 with tropospheric chlorine (Cl), a CH4 sink whose abundance, spatial distribution, and temporal changes remain uncertain. Our results show that including or excluding tropospheric Cl as a 13 Tg/year CH4 sink in our model changes the magnitude of estimated fossil emissions by ∼20%. We also found that by using different wetland emissions based on a static versus a dynamic wetland area map, the partitioning between FF and microbial sources differs by 20 Tg/year, ∼12% of estimated fossil emissions.

Investigating the spatio-temporal variability of soil organic carbon stocks in different ecosystems of China

Soil organic carbon (SOC) significantly influences soil fertility, soil water holding capacity, and plant productivity. In this study, we applied two boosted regression tree (BRT) models to map SOC stocks across China in the 1980s and the 2010s. The models incorporated nine environmental variables (climate, topography, and biology) and 8897 (in the 1980s) and 4534 (in the 2010s) topsoil (0-20 cm) samples. During the two study periods, 20% of the soil samples were randomly selected for model testing, and the remaining samples were used as a training set to construct the models. The verification results showed that incorporating climate environment variables significantly improved the model prediction in both study periods. Mean annual temperature, mean annual precipitation, elevation, and the normalized difference vegetation index were the dominant environmental factors affecting the spatial distribution of SOC stocks. The full-variable model predicted similar spatial distributions of SOC stocks for the 1980s and the 2010s. SOC stocks in China showed an increasing trend over the past 30 years, from 3.9 kg m^-2 in the 1980s to 4.6 kg m^-2 in the 2010s. In both periods, topsoil SOC stocks were mainly stored in agroecosystems, forests, and grasslands in the 1980s, with values of 9.5, 12.0, and 11.4 Pg C, respectively. Our study provides reliable information on Chain's carbon distribution, which can be used by land managers and the national government to formulate relevant land use and carbon sequestration policies.

Genetic investigation of nodal melanocytic nevi in cases of giant congenital melanocytic nevus

Nodal melanocytic nevi are common incidental findings in lymph nodes that have been removed during sentinel lymph node biopsy for melanoma. They can also occur in the local lymph nodes of the giant congenital nevus (GCN), but very little is known regarding nodal melanocytic nevi in the giant congenital nevus, especially at the genetic level. There are two theories that explain the possible pathogenesis of nodal melanocytic nevi, mechanical transport and arrested migration during embryogenesis. However, there have been few tests of these two theories at the molecular biology level until now. We used whole-exon sequencing to test these two theories at the gene level for the first time. In clonal evolution analysis of patient 1, whose tumor mutation burden (TMB) value was relatively stable, showed that the GCN and nodal nevus had the same initial origin and then diverged into two branches as a result of gene mutations. In contrast, analysis indicated that in the other patient, whose TMB value declined from 68.02/Mb in a GCN to 17.55/Mb in associated nodal nevi, these two samples were from different origins at the beginning, each with its own gene mutation. These results are consistent with the two respective theories at the molecular biological level. We provided the first tests of the two theories of pathogenesis of nodal melanocytic nevi at the gene level, and these findings may provide some clues for further study. In addition, not all nodal nevi should be treated as lymph node metastasis in clinical diagnosis, and we should make a comprehensive assessment and judgment of nodal melanocytic nevi based on morphology, immunological characteristics and fluorescence in situ hybridization (FISH) tests.

[Genetic changes and biological potential of proliferative nodule in congenital pigmented nevus]

Objective: To study the genetic changes and biological potential of proliferative nodule in congenital melanocytic nevus. Methods: Whole-exome sequencing was carried out using the technique of next-generation sequencing (NGS) in order to detect the genomic alterations of two cases of proliferative nodules (PN) in congenital melanocytic nevi (CMN). Twelve cases of CMN and ten cases of malignant melanoma were used as benign and malignant controls, respectively. Mutated genes that possessed statistically significant difference between benign and malignant controls were listed, according to what benign and malignant statuses were classified and clustered. The heatmaps of clustering analyses were depicted using heatmap package. Fluorescence in situ hybridization (FISH) was also used to validate the above results. Results: Eighty-six common somatic gene mutations were detected in two samples of PN. Compared with CMN, PN had 52 more mutated genes. Furthermore, 22 of these 52 mutated genes were also detected in malignant melanoma samples. Two cases of PN fell between benign CMN and malignant melanoma in germline mutation clustering. Both cases of PN were positive in the FISH tests. Conclusions: The genetic changes of PN partially overlap with those of CMN and malignant melanoma. Therefore, although most of the PN manifest as a benign lesion clinically, it may have certain malignant potential at the genetic level, and warrant long-term monitoring and follow-up.

Impacts of urbanization on soil organic carbon stocks in the northeast coastal agricultural areas of China

Dynamic changes in soil organic carbon pools have significant impacts on regional and global carbon balance. Due to rapid development in urbanized areas, the land use changes dramatically, impacting soil organic carbon (SOC) stocks in topsoil. This study aimed to document the impacts of urbanization on SOC stocks in a rapidly urbanized area from northeastern China. A total of 12 auxiliary variables were as SOC predictors including elevation, slope aspect, slope gradient, topographic wetness index, Landsat TM band3, Landsat TM band4, Landsat TM5, and normalized difference vegetation index. Urban-specific variables including population (POP), gross domestic product (GDP), distance to the socio-economic center, and distance to the roads are also considered. A set of 523 (in 1990) and 847 (in 2015) top soil samples with SOC measurement were collected. Two random forest (RF) models, one with all auxiliary variables except urban-specific variable (MA) and the other with all auxiliary variables (MB) were used to map the spatial distribution of SOC stocks in the two periods. Ten-fold cross-validation was conducted to evaluate the performance of RF models. We find that the full auxiliary variables model had a better performance for the both periods. POP and GDP were key auxiliary variables affecting spatial variability of SOC stocks in 2015. Over a 25-year period, SOC stocks decreased from 2.77 ± 1.09 kg m^-2 to 2.16 ± 0.93 kg m^-2, resulting in 3.78 Tg SOC loss in this region. Rapid urbanization led to drastic land- use change, which was the main reason for the decrease of SOC stocks. Additionally, urban-specific variables should be used as the main auxiliary variables when predicting SOC stocks in the areas that experience rapid urbanization. We believe that accurate prediction and mapping of SOC stocks will help manage land use and facilitate soil quality assessment so as to increase soil carbon sequestration in the region.

An improved similarity-based approach to predicting and mapping soil organic carbon and soil total nitrogen in a coastal region of northeastern China

Soil organic carbon (SOC) and soil total nitrogen (STN) are major soil indicators for soil quality and fertility. Accurate mapping SOC and STN in soils would help both managed and natural soils and ecosystem management. This study developed an improved similarity-based approach (ISA) to predicting and mapping topsoil (0-20 cm soil depth) SOC and STN in a coastal region of northeastern China. Six environmental variables including elevation, slope gradient, topographic wetness index, the mean annual temperature, the mean annual temperature, and normalized difference vegetation index were used as predictors. Soil survey data in 2012 was designed based on the clustering of the study area into six climatic vegetation landscape units. In each landscape unit, 20-25 sampling points were determined at different landform positions considering local climate, soil type, elevation and other environmental factors, and finally 126 sampling points were obtained. Soil sampling from the depth of 0-20 cm were used for model prediction and validation. The ISA model performance was compared with the geographically weighted regression (GWR), regression kriging (RK), boosted regression trees (BRT) considering mean absolute prediction error (MAE), root mean square error (RMSE), coefficient of determination (R ²), and maximum relative difference (RD) indices. We found that the ISA method performed best with the highest R² and lowest MAE, RMSE compared to GWR, RK, and BRT methods. The ISA method could explain 76% and 83% of the total SOC and STN variability, respectively, 12-40% higher than other models in the study area. Elevation had the largest influence on SOC and STN distribution. We conclude that the developed ISA model is robust and effective in mapping SOC and STN, particularly in the areas with complex vegetation-landscape when limited samples are available. The method needs to be tested for other regions in our future research.

Large loss of CO2 in winter observed across the northern permafrost region

Recent warming in the Arctic, which has been amplified during the winter^1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO₂)⁴. However, the amount of CO₂ released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates^5,6. Here we synthesize regional in situ observations of CO₂ flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr^-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr^-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO₂ emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO₂ emissions from northern terrestrial regions and indicate that enhanced soil CO₂ loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration

Evidence suggests that global maize yield declines with a warming climate, particularly with extreme heat events. However, the degree to which important maize processes such as biomass growth rate, growing season length (GSL) and grain formation are impacted by an increase in temperature is uncertain. Such knowledge is necessary to understand yield responses and develop crop adaptation strategies under warmer climate. Here crop models, satellite observations, survey, and field data were integrated to investigate how high temperature stress influences maize yield in the U.S. Midwest. We showed that both observational evidence and crop model ensemble mean (MEM) suggests the nonlinear sensitivity in yield was driven by the intensified sensitivity of harvest index (HI), but MEM underestimated the warming effects through HI and overstated the effects through GSL. Further analysis showed that the intensified sensitivity in HI mainly results from a greater sensitivity of yield to high temperature stress during the grain filling period, which explained more than half of the yield reduction. When warming effects were decomposed into direct heat stress and indirect water stress (WS), observational data suggest that yield is more reduced by direct heat stress (-4.6 ± 1.0%/°C) than by WS (-1.7 ± 0.65%/°C), whereas MEM gives opposite results. This discrepancy implies that yield reduction by heat stress is underestimated, whereas the yield benefit of increasing atmospheric CO₂ might be overestimated in crop models, because elevated CO₂ brings yield benefit through water conservation effect but produces limited benefit over heat stress. Our analysis through integrating data and crop models suggests that future adaptation strategies should be targeted at the heat stress during grain formation and changes in agricultural management need to be better accounted for to adequately estimate the effects of heat stress.

Potential shift from a carbon sink to a source in Amazonian peatlands under a changing climate

Amazonian peatlands store a large amount of soil organic carbon (SOC), and its fate under a future changing climate is unknown. Here, we use a process-based peatland biogeochemistry model to quantify the carbon accumulation for peatland and nonpeatland ecosystems in the Pastaza-Marañon foreland basin (PMFB) in the Peruvian Amazon from 12,000 y before present to AD 2100. Model simulations indicate that warming accelerates peat SOC loss, while increasing precipitation accelerates peat SOC accumulation at millennial time scales. The uncertain parameters and spatial variation of climate are significant sources of uncertainty to modeled peat carbon accumulation. Under warmer and presumably wetter conditions over the 21st century, SOC accumulation rate in the PMFB slows down to 7.9 (4.3-12.2) g⋅C⋅m-2⋅y-1 from the current rate of 16.1 (9.1-23.7) g⋅C⋅m-2⋅y-1, and the region may turn into a carbon source to the atmosphere at -53.3 (-66.8 to -41.2) g⋅C⋅m-2⋅y-1 (negative indicates source), depending on the level of warming. Peatland ecosystems show a higher vulnerability than nonpeatland ecosystems, as indicated by the ratio of their soil carbon density changes (ranging from 3.9 to 5.8). This is primarily due to larger peatlands carbon stocks and more dramatic responses of their aerobic and anaerobic decompositions in comparison with nonpeatland ecosystems under future climate conditions. Peatland and nonpeatland soils in the PMFB may lose up to 0.4 (0.32-0.52) Pg⋅C by AD 2100 with the largest loss from palm swamp. The carbon-dense Amazonian peatland may switch from a current carbon sink into a source in the 21st century.

Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic

Across the Arctic, the net ecosystem carbon (C) balance of tundra ecosystems is highly uncertain due to substantial temporal variability of C fluxes and to landscape heterogeneity. We modeled both carbon dioxide (CO₂ ) and methane (CH₄ ) fluxes for the dominant land cover types in a ~100-km² sub-Arctic tundra region in northeast European Russia for the period of 2006-2015 using process-based biogeochemical models. Modeled net annual CO₂ fluxes ranged from -300 g C m^-2  year^-1 [net uptake] in a willow fen to 3 g C m^-2  year^-1 [net source] in dry lichen tundra. Modeled annual CH₄ emissions ranged from -0.2 to 22.3 g C m^-2  year^-1 at a peat plateau site and a willow fen site, respectively. Interannual variability over the decade was relatively small (20%-25%) in comparison with variability among the land cover types (150%). Using high-resolution land cover classification, the region was a net sink of atmospheric CO₂ across most land cover types but a net source of CH₄ to the atmosphere due to high emissions from permafrost-free fens. Using a lower resolution for land cover classification resulted in a 20%-65% underestimation of regional CH₄ flux relative to high-resolution classification and smaller (10%) overestimation of regional CO₂ uptake due to the underestimation of wetland area by 60%. The relative fraction of uplands versus wetlands was key to determining the net regional C balance at this and other Arctic tundra sites because wetlands were hot spots for C cycling in Arctic tundra ecosystems.

The important but weakening maize yield benefit of grain filling prolongation in the US Midwest

A better understanding of recent crop yield trends is necessary for improving the yield and maintaining food security. Several possible mechanisms have been investigated recently in order to explain the steady growth in maize yield over the US Corn-Belt, but a substantial fraction of the increasing trend remains elusive. In this study, trends in grain filling period (GFP) were identified and their relations with maize yield increase were further analyzed. Using satellite data from 2000 to 2015, an average lengthening of GFP of 0.37 days per year was found over the region, which probably results from variety renewal. Statistical analysis suggests that longer GFP accounted for roughly one-quarter (23%) of the yield increase trend by promoting kernel dry matter accumulation, yet had less yield benefit in hotter counties. Both official survey data and crop model simulations estimated a similar contribution of GFP trend to yield. If growing degree days that determines the GFP continues to prolong at the current rate for the next 50 years, yield reduction will be lessened with 25% and 18% longer GFP under Representative Concentration Pathway 2.6 (RCP 2.6) and RCP 6.0, respectively. However, this level of progress is insufficient to offset yield losses in future climates, because drought and heat stress during the GFP will become more prevalent and severe. This study highlights the need to devise multiple effective adaptation strategies to withstand the upcoming challenges in food security.

Assessing historical and projected carbon balance of Alaska: A synthesis of results and policy/management implications

We summarize the results of a recent interagency assessment of land carbon dynamics in Alaska, in which carbon dynamics were estimated for all major terrestrial and aquatic ecosystems for the historical period (1950-2009) and a projection period (2010-2099). Between 1950 and 2009, upland and wetland (i.e., terrestrial) ecosystems of the state gained 0.4 Tg C/yr (0.1% of net primary production, NPP), resulting in a cumulative greenhouse gas radiative forcing of 1.68 × 10^-3  W/m² . The change in carbon storage is spatially variable with the region of the Northwest Boreal Landscape Conservation Cooperative (LCC) losing carbon because of fire disturbance. The combined carbon transport via various pathways through inland aquatic ecosystems of Alaska was estimated to be 41.3 Tg C/yr (17% of terrestrial NPP). During the projection period (2010-2099), carbon storage of terrestrial ecosystems of Alaska was projected to increase (22.5-70.0 Tg C/yr), primarily because of NPP increases of 10-30% associated with responses to rising atmospheric CO₂ , increased nitrogen cycling, and longer growing seasons. Although carbon emissions to the atmosphere from wildfire and wetland CH₄ were projected to increase for all of the climate projections, the increases in NPP more than compensated for those losses at the statewide level. Carbon dynamics of terrestrial ecosystems continue to warm the climate for four of the six future projections and cool the climate for only one of the projections. The attribution analyses we conducted indicated that the response of NPP in terrestrial ecosystems to rising atmospheric CO₂ (~5% per 100 ppmv CO₂ ) saturates as CO₂ increases (between approximately +150 and +450 ppmv among projections). This response, along with the expectation that permafrost thaw would be much greater and release large quantities of permafrost carbon after 2100, suggests that projected carbon gains in terrestrial ecosystems of Alaska may not be sustained. From a national perspective, inclusion of all of Alaska in greenhouse gas inventory reports would ensure better accounting of the overall greenhouse gas balance of the nation and provide a foundation for considering mitigation activities in areas that are accessible enough to support substantive deployment.

The role of environmental driving factors in historical and projected carbon dynamics of wetland ecosystems in Alaska

Wetlands are critical terrestrial ecosystems in Alaska, covering ~177,000 km² , an area greater than all the wetlands in the remainder of the United States. To assess the relative influence of changing climate, atmospheric carbon dioxide (CO₂ ) concentration, and fire regime on carbon balance in wetland ecosystems of Alaska, a modeling framework that incorporates a fire disturbance model and two biogeochemical models was used. Spatially explicit simulations were conducted at 1-km resolution for the historical period (1950-2009) and future projection period (2010-2099). Simulations estimated that wetland ecosystems of Alaska lost 175 Tg carbon (C) in the historical period. Ecosystem C storage in 2009 was 5,556 Tg, with 89% of the C stored in soils. The estimated loss of C as CO₂ and biogenic methane (CH₄ ) emissions resulted in wetlands of Alaska increasing the greenhouse gas forcing of climate warming. Simulations for the projection period were conducted for six climate change scenarios constructed from two climate models forced under three CO₂ emission scenarios. Ecosystem C storage averaged among climate scenarios increased 3.94 Tg C/yr by 2099, with variability among the simulations ranging from 2.02 to 4.42 Tg C/yr. These increases were driven primarily by increases in net primary production (NPP) that were greater than losses from increased decomposition and fire. The NPP increase was driven by CO₂ fertilization (~5% per 100 parts per million by volume increase) and by increases in air temperature (~1% per °C increase). Increases in air temperature were estimated to be the primary cause for a projected 47.7% mean increase in biogenic CH₄ emissions among the simulations (~15% per °C increase). Ecosystem CO₂ sequestration offset the increase in CH₄ emissions during the 21st century to decrease the greenhouse gas forcing of climate warming. However, beyond 2100, we expect that this forcing will ultimately increase as wetland ecosystems transition from being a sink to a source of atmospheric CO₂ because of (1) decreasing sensitivity of NPP to increasing atmospheric CO₂ , (2) increasing availability of soil C for decomposition as permafrost thaws, and (3) continued positive sensitivity of biogenic CH₄ emissions to increases in soil temperature.

The role of driving factors in historical and projected carbon dynamics of upland ecosystems in Alaska

It is important to understand how upland ecosystems of Alaska, which are estimated to occupy 84% of the state (i.e., 1,237,774 km² ), are influencing and will influence state-wide carbon (C) dynamics in the face of ongoing climate change. We coupled fire disturbance and biogeochemical models to assess the relative effects of changing atmospheric carbon dioxide (CO₂ ), climate, logging and fire regimes on the historical and future C balance of upland ecosystems for the four main Landscape Conservation Cooperatives (LCCs) of Alaska. At the end of the historical period (1950-2009) of our analysis, we estimate that upland ecosystems of Alaska store ~50 Pg C (with ~90% of the C in soils), and gained 3.26 Tg C/yr. Three of the LCCs had gains in total ecosystem C storage, while the Northwest Boreal LCC lost C (-6.01 Tg C/yr) because of increases in fire activity. Carbon exports from logging affected only the North Pacific LCC and represented less than 1% of the state's net primary production (NPP). The analysis for the future time period (2010-2099) consisted of six simulations driven by climate outputs from two climate models for three emission scenarios. Across the climate scenarios, total ecosystem C storage increased between 19.5 and 66.3 Tg C/yr, which represents 3.4% to 11.7% increase in Alaska upland's storage. We conducted additional simulations to attribute these responses to environmental changes. This analysis showed that atmospheric CO₂ fertilization was the main driver of ecosystem C balance. By comparing future simulations with constant and with increasing atmospheric CO₂ , we estimated that the sensitivity of NPP was 4.8% per 100 ppmv, but NPP becomes less sensitive to CO₂ increase throughout the 21st century. Overall, our analyses suggest that the decreasing CO₂ sensitivity of NPP and the increasing sensitivity of heterotrophic respiration to air temperature, in addition to the increase in C loss from wildfires weakens the C sink from upland ecosystems of Alaska and will ultimately lead to a source of CO₂ to the atmosphere beyond 2100. Therefore, we conclude that the increasing regional C sink we estimate for the 21st century will most likely be transitional.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2

Heat and drought are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO2 concentrations. This study quantifies the combined and separate impacts of high temperature, heat and drought stresses on the current and future US rainfed maize and soybean production and for the first time characterizes spatial shifts in the relative importance of individual stress. Crop yields are simulated using the Agricultural Production Systems Simulator (APSIM), driven by high-resolution (12 km) dynamically downscaled climate projections for 1995-2004 and 2085-2094. Results show that maize and soybean yield losses are prominent in the US Midwest by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of loss highly depends on the current vulnerability and changes in climate extremes. Elevated atmospheric CO2 partially but not completely offsets the yield gaps caused by climate extremes, and the effect is greater in soybean than in maize. Our simulations suggest that drought will continue to be the largest threat to US rainfed maize production under RCP4.5 and soybean production under both RCP scenarios, whereas high temperature and heat stress take over the dominant stress of drought on maize under RCP8.5. We also reveal that shifts in the geographic distributions of dominant stresses are characterized by the increase in concurrent stresses, especially for the US Midwest. These findings imply the importance of considering heat and drought stresses simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management. The modeling framework of partitioning the total effects of climate change into individual stress impacts can be applied to the study of other crops and agriculture systems.

The further exploration of hidden blood loss in posterior lumbar fusion surgery

PURPOSE

Hidden blood loss (HBL) plays an important role in lumbar fusion surgery. However, there was huge computation error when calculating hidden loss in previous studies because they regarded the volume of drainage as postoperative blood loss. We should not ignore the fact that the composition of drainage varies from person to person and also with time-lapse after operation. The purpose of this study was to demonstrate a more accurate HBL calculation formula by comparing it with previous formula and to address the importance of HBL in patients undergoing posterior lumbar fusion surgeries.

METHODS

For each patient, the HBL was calculated by previous formula and our recommendable formula. We compared the result of HBL calculated by two different methods. At the same time, we explored the HBL in patients undergoing posterior lumbar fusion surgeries with various levels.

RESULTS

In our study, the average total blood loss was 771ml. The mean intraoperative blood loss was 268ml, and the total volume of post-operative drainage is 276ml. The mean hidden loss of 90 patients calculated with previous method was 227ml and 29.4% of total loss. When taking change of drainage HCT into account, the mean hidden loss calculated with our recommendable method was 362.8ml and 47% of total loss. The results were significantly different (P<0.01). There was no significant difference in the percentage of the HBL between patients with single or multiple surgical levels.

CONCLUSIONS

There is often a substantial unmeasured blood loss in lumbar fusion surgeries. However, the component of drainage changed radically with time, we should take the true blood contained in drainage into considerations when calculating the HBL.

LEVEL OF EVIDENCE

Our research is a case-control study and the level of proof is III.

Modeling long-term changes in tundra carbon balance following wildfire, climate change, and potential nutrient addition

To investigate the underlying mechanisms that control long-term recovery of tundra carbon (C) and nutrients after fire, we employed the Multiple Element Limitation (MEL) model to simulate 200-yr post-fire changes in the biogeochemistry of three sites along a burn severity gradient in response to increases in air temperature, CO₂ concentration, nitrogen (N) deposition, and phosphorus (P) weathering rates. The simulations were conducted for severely burned, moderately burned, and unburned arctic tundra. Our simulations indicated that recovery of C balance after fire was mainly determined by the internal redistribution of nutrients among ecosystem components (controlled by air temperature), rather than the supply of nutrients from external sources (e.g., nitrogen deposition and fixation, phosphorus weathering). Increases in air temperature and atmospheric CO₂ concentration resulted in (1) a net transfer of nutrient from soil organic matter to vegetation and (2) higher C : nutrient ratios in vegetation and soil organic matter. These changes led to gains in vegetation biomass C but net losses in soil organic C stocks. Under a warming climate, nutrients lost in wildfire were difficult to recover because the warming-induced acceleration in nutrient cycles caused further net nutrient loss from the system through leaching. In both burned and unburned tundra, the warming-caused acceleration in nutrient cycles and increases in ecosystem C stocks were eventually constrained by increases in soil C : nutrient ratios, which increased microbial retention of plant-available nutrients in the soil. Accelerated nutrient turnover, loss of C, and increasing soil temperatures will likely result in vegetation changes, which further regulate the long-term biogeochemical succession. Our analysis should help in the assessment of tundra C budgets and of the recovery of biogeochemical function following fire, which is in turn necessary for the maintenance of wildlife habitat and tundra vegetation.

Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches

Stresses from heat and drought are expected to increasingly suppress crop yields, but the degree to which current models can represent these effects is uncertain. Here we evaluate the algorithms that determine impacts of heat and drought stress on maize in 16 major maize models by incorporating these algorithms into a standard model, the Agricultural Production Systems sIMulator (APSIM), and running an ensemble of simulations. Although both daily mean temperature and daylight temperature are common choice of forcing heat stress algorithms, current parameterizations in most models favor the use of daylight temperature even though the algorithm was designed for daily mean temperature. Different drought algorithms (i.e., a function of soil water content, of soil water supply to demand ratio, and of actual to potential transpiration ratio) simulated considerably different patterns of water shortage over the growing season, but nonetheless predicted similar decreases in annual yield. Using the selected combination of algorithms, our simulations show that maize yield reduction was more sensitive to drought stress than to heat stress for the US Midwest since the 1980s, and this pattern will continue under future scenarios; the influence of excessive heat will become increasingly prominent by the late 21st century. Our review of algorithms in 16 crop models suggests that the impacts of heat and drought stress on plant yield can be best described by crop models that: (i) incorporate event-based descriptions of heat and drought stress, (ii) consider the effects of nighttime warming, and (iii) coordinate the interactions among multiple stresses. Our study identifies the proficiency with which different model formulations capture the impacts of heat and drought stress on maize biomass and yield production. The framework presented here can be applied to other modeled processes and used to improve yield predictions of other crops with a wide variety of crop models.

Endoplasmic reticulum stress eIF2α-ATF4 pathway-mediated cyclooxygenase-2 induction regulates cadmium-induced autophagy in kidney

The heavy metal cadmium (Cd) is nephrotoxic. Recent studies show that autophagy plays an essential role in Cd-induced kidney injury. However, the mechanisms of Cd-induced kidney injury accompanied by autophagy are still obscure. In the present study, we first confirmed that Cd induced kidney damage and dysfunction, along with autophagy, both in vivo and in vitro. Then, we observed that cyclooxygenase-2 (COX-2) and the eIF2α-ATF4 pathway of endoplasmic reticulum (ER) stress were induced by Cd in both kidney tissues and cultured cells. Further studies showed that inhibition of COX-2 with celecoxib or RNA interference (RNAi) inhibited the Cd-induced autophagy in kidney cells. In addition, blocking ER stress with 4-phenylbutyrate or RNAi partially counteracted COX-2 overexpression and autophagy induced by Cd, which suggested that ER stress was required for Cd-induced kidney autophagy. Significantly, our results showed that Cd activated ATF4 and induced its translocation to the nucleus. Knockdown of ATF4 inhibited Cd-induced COX-2 overexpression. While COX-2 overexpression is involved in renal dysfunction, there is no prior report on the role of COX-2 in autophagy regulation. The results of the current study suggest a novel molecular mechanism that the ER stress eIF2α-ATF4 pathway-mediated COX-2 overexpression contributes to Cd-induced kidney autophagy and injury. The present study implies that COX-2 may be a potential target for therapy against Cd-induced nephrotoxicity.

Ecological risk assessment of ecosystem services in the Taihu Lake Basin of China from 1985 to 2020

There are tremendous theoretical, methodological and policy challenges in evaluating the impact of land-use change on the degradation of ecosystem services (ES) at the regional scale. This study addresses these challenges by developing an interdisciplinary methodology based on the Procedure for Ecological Tiered Assessment of Risk (PETAR). This novel methodology integrates ecological models with a land-use change model. This study quantifies the multi-dimensional degradation risks of ES in the Taihu Lake Basin (TLB) of China from 1985 to 2020. Four key ES related to water purification, water quantity adjustment, carbon sequestration and grain production are selected. The study employs models of Denitrification-Decomposition (DNDC), Soil-Water-Atmosphere-Plant (SWAP), Biome-BGC and Agro-ecological Zoning (AEZ) for assimilations. Land-use changes by 2020 were projected using a geographically weighted multinomial logit-cellular automata (GWML-CA) model. The results show that rapid land-use change has posed a great degradation risk of ES in the region in 1985-2020. Slightly less than two-thirds of the basin experienced degradation of ES over the 1985-2010 period, and about 12% of the basin will continue to experience degradation until 2020. Hot spots with severe deterioration in 2010-2020 are projected to be centered around some small and less developed cities in the region. Regulating accelerated urban sprawl and population growth, reinforcing current environmental programs, and establishing monitoring systems for observing dynamics of regional ES are suggested as practical counter-measures.

Global patterns and predictors of stem CO2 efflux in forest ecosystems

Stem CO2 efflux (ES) plays an important role in the carbon balance of forest ecosystems. However, its primary controls at the global scale are poorly understood and observation-based global estimates are lacking. We synthesized data from 121 published studies across global forest ecosystems and examined the relationships between annual ES and biotic and abiotic factors at individual, biome, and global scales, and developed a global gridded estimate of annual ES . We tested the following hypotheses: (1) Leaf area index (LAI) will be highly correlated with annual ES at biome and global scales; (2) there will be parallel patterns in stem and root CO2 effluxes (RA) in all forests; (3) annual ES will decline with forest age; and (4) LAI coupled with mean annual temperature (MAT) and mean annual precipitation (MAP) will be sufficient to predict annual ES across forests in different regions. Positive linear relationships were found between ES and LAI, as well as gross primary production (GPP), net primary production (NPP), wood NPP, soil CO2 efflux (RS), and RA . Annual ES was correlated with RA in temperate forests after controlling for GPP and MAT, suggesting other additional factors contributed to the relationship. Annual ES tended to decrease with stand age. Leaf area index, MAT and MAP, predicted 74% of variation in ES at global scales. Our statistical model estimated a global annual ES of 6.7 ± 1.1 Pg C yr(-1) over the period of 2000-2012 with little interannual variability. Modeled mean annual ES was 71 ± 43, 270 ± 103, and 420 ± 134 g C m(2) yr(-1) for boreal, temperate, and tropical forests, respectively. We recommend that future studies report ES at a standardized constant temperature, incorporate more manipulative treatments, such as fertilization and drought, and whenever possible, simultaneously measure both aboveground and belowground CO2 fluxes.

Rising methane emissions from northern wetlands associated with sea ice decline

The Arctic is rapidly transitioning toward a seasonal sea ice-free state, perhaps one of the most apparent examples of climate change in the world. This dramatic change has numerous consequences, including a large increase in air temperatures, which in turn may affect terrestrial methane emissions. Nonetheless, terrestrial and marine environments are seldom jointly analyzed. By comparing satellite observations of Arctic sea ice concentrations to methane emissions simulated by three process-based biogeochemical models, this study shows that rising wetland methane emissions are associated with sea ice retreat. Our analyses indicate that simulated high-latitude emissions for 2005-2010 were, on average, 1.7 Tg CH₄ yr^-1 higher compared to 1981-1990 due to a sea ice-induced, autumn-focused, warming. Since these results suggest a continued rise in methane emissions with future sea ice decline, observation programs need to include measurements during the autumn to further investigate the impact of this spatial connection on terrestrial methane emissions.

Realization of Vertically Aligned, Ultrahigh Aspect Ratio InAsSb Nanowires on Graphite

The monolithic integration of InAs(1-x)Sb(x) semiconductor nanowires on graphitic substrates holds enormous promise for cost-effective, high-performance, and flexible devices in optoelectronics and high-speed electronics. However, the growth of InAs(1-x)Sb(x) nanowires with high aspect ratio essential for device applications is extremely challenging due to Sb-induced suppression of axial growth and enhancement in radial growth. We report the realization of high quality, vertically aligned, nontapered and ultrahigh aspect ratio InAs(1-x)Sb(x) nanowires with Sb composition (xSb(%)) up to ∼12% grown by indium-droplet assisted molecular beam epitaxy on graphite substrate. Low temperature photoluminescence measurements show that the InAs(1-x)Sb(x) nanowires exhibit bright band-to-band related emission with a distinct redshift as a function of Sb composition providing further confirmation of successful Sb incorporation in as-grown nanowires. This study reveals that the graphite substrate is a more favorable platform for InAs(1-x)Sb(x) nanowires that could lead to hybrid heterostructures possessing potential device applications in optoelectronics.