Vulnerability of barley yields in Québec.

Climate projections across Québec indicate increased water stress and recurrent vulnerability of cropping systems. In recent years, reports of droughts and water stress have been recorded across the province. Many parts of Québec have experienced droughts in the past few years, which have had uninvestigated impacts on crops. These droughts have been described as some of the most significant in the last 80 years. On the positive side, climate change is likely to trigger shorter winters and therefore longer growing seasons for several crops. However, for crops like maple syrup, the regions suitable for their cultivation will shift northwards. Despite these projections, studies monitoring the susceptibility of barley to environmental changes, climate variability, and adaptive capacity across Québec are still limited. This study aims to provide a provincial-scale portrait of vulnerability of barley in Québec based on historical growing season precipitation, barley yield, and socioeconomic data (literacy and poverty rates) using a composite statistical model. Growing season precipitation data were downloaded from Ouranos. Barley yield data were collected from the Institut de la Statistique du Québec, and the socio-demographic data were collected from the Advisory Council of Poverty and the Institut de la Statistique du Québec. A vulnerability index with sub-indices (sensitivity, exposure, and adaptive capacity) is deployed. It is hypothesised that (1) vulnerability is inversely associated with adaptive capacity, and (2) the peripheral regions of Québec are more vulnerable and less adaptive to climate stressors. Initial results show that when the vulnerability index for barley is more prominent, the associated index of adaptive capacity is relatively lower. A significant gradient between the peripheral and southern regions of Québec is observed, with vulnerability lowest around Montreal/Laval and gradually increasing towards the peripheral regions. A better understanding of vulnerability warrants a change in approach from focusing solely on climate-related variables to integrating socioeconomic proxies. The challenge, however, has been how to introduce these socioeconomic proxies into empirical and process-based crop models.

Comparing standardised precipitation and barley yield across Quebec.

Climate change and variability continue to affect crop production across the world in general and in Quebec in particular. Therefore, it is important to better understand this climate-yield nexus. Unfortunately, in Quebec, there are currently no studies that analyse both precipitation and barley yield. This study aims at filling this research gap by comparing standardised precipitation (SPI) against barley yield gaps across Quebec for three peripheral and three southern/central regions of Quebec. The study uses growing season precipitation data from Ouranos and barley yield data from Institut de la Statistique du Québec. This work deploys the use of standardised index (SPI) index and a machine learning yield gap algorithm (actual barley yield minus projected barley yield) to provide a provincial portrait of the relationships between SPI and barley yield. The results show that the peripheral regions record below zero SPIs (Abitibi-Temiscamingue - 0.48, Saguenay-Lac-Saint-Jean - 0.14 and Outaouais - 0.10) and more yield gap years, while the southern/central regions record positive SPIs (Estrie 1.17, Centre du Quebec 0.86 and Monteregie: 0.33) and fewer years with yield gaps. This shows that there is a south-north gradient in the variations of SPI and yield gaps. The SPI and yield patterns can be explained by prolonged winters further north of Quebec and recently winters with insufficient snow cover which triggers rapid snow melt and thus shortening the growing season for barley. Policy actions around drought-resistant varieties within a co-creation context and more research that explores daily and monthly liquid precipitation totals during the growing season of the crop need to be explored. There is also a need to better understand the economic costs and benefits of the associated yield gaps as well as the impacts of temperature.

Fire effects on soil CH4 and N2O fluxes across terrestrial ecosystems.

Fire, as a natural disturbance, significantly shapes and influences the functions and services of terrestrial ecosystems via biotic and abiotic processes. Comprehending the influence of fire on soil greenhouse gas dynamics is crucial for understanding the feedback mechanisms between fire disturbances and climate change. Despite work on CO2 fluxes, there is a large uncertainty as to whether and how soil CH4 and N2O fluxes change in response to fire disturbance in terrestrial ecosystems. To narrow this knowledge gap, we performed a meta-analysis synthesizing 3615 paired observations from 116 global studies. Our findings revealed that fire increased global soil CH4 uptake in uplands by 23.2 %, soil CH4 emissions from peatlands by 74.7 %, and soil N2O emissions in terrestrial ecosystems (including upland and peatland) by 18.8 %. Fire increased soil CH4 uptake in boreal, temperate, and subtropical forests by 20.1 %, 38.8 %, and 30.2 %, respectively, and soil CH4 emissions in tropical forests by 193.3 %. Additionally, fire negatively affected soil total carbon (TC; -10.3 %), soil organic carbon (SOC; -15.6 %), microbial biomass carbon (MBC; -44.8 %), dissolved organic carbon (DOC; -27 %), microbial biomass nitrogen (MBN; -24.7 %), soil water content (SWC; -9.2 %), and water table depth (WTD; -68.2 %). Conversely, the fire increased soil bulk density (BD; +10.8 %), ammonium nitrogen (NH4+-N; +46 %), nitrate nitrogen (NO3--N; +54 %), pH (+4.4 %), and soil temperature (+15.4 %). Our meta-regression analysis showed that the positive effects of fire on soil CH4 and N2O emissions were significantly positively correlated with mean annual temperature (MAT) and mean annual precipitation (MAP), indicating that climate warming will amplify the positive effects of fire disturbance on soil CH4 and N2O emissions. Taken together, since higher future temperatures are likely to prolong the fire season and increase the potential of fires, this could lead to positive feedback between warming, fire events, CH4 and N2O emissions, and future climate change.

Global net climate effects of anthropogenic reactive nitrogen.

Anthropogenic activities have substantially enhanced the loadings of reactive nitrogen (Nr) in the Earth system since pre-industrial times1,2, contributing to widespread eutrophication and air pollution3-6. Increased Nr can also influence global climate through a variety of effects on atmospheric and land processes but the cumulative net climate effect is yet to be unravelled. Here we show that anthropogenic Nr causes a net negative direct radiative forcing of -0.34 [-0.20, -0.50] W m-2 in the year 2019 relative to the year 1850. This net cooling effect is the result of increased aerosol loading, reduced methane lifetime and increased terrestrial carbon sequestration associated with increases in anthropogenic Nr, which are not offset by the warming effects of enhanced atmospheric nitrous oxide and ozone. Future predictions using three representative scenarios show that this cooling effect may be weakened primarily as a result of reduced aerosol loading and increased lifetime of methane, whereas in particular N2O-induced warming will probably continue to increase under all scenarios. Our results indicate that future reductions in anthropogenic Nr to achieve environmental protection goals need to be accompanied by enhanced efforts to reduce anthropogenic greenhouse gas emissions to achieve climate change mitigation in line with the Paris Agreement.

Soil methane emissions from plain poplar (Populus spp.) plantations with contrasting soil textures.

The forest soil methane (CH4) flux exhibits high spatiotemporal variability. Understanding these variations and their driving factors is crucial for accurately assessing the forest CH4 budget. In this study, we monitored the diurnal and seasonal variations in soil CH4 fluxes in two poplar (Populus spp.) plantations (Sihong and Dongtai) with different soil textures using the static chamber-based method. The results showed that the annual average soil CH4 flux in the Sihong and Dongtai poplar plantations was 4.27 ± 1.37 kg CH4-C ha-1 yr-1 and 1.92 ± 1.07 kg CH4-C ha-1 yr-1, respectively. Both plantations exhibited net CH4 emissions during the growing season, with only weak CH4 absorption (-0.01 to -0.007 mg m-2 h-1) during the non-growing season. Notably, there was a significant difference in soil CH4 flux between the clay loam of the Sihong poplar plantation and the sandy loam of the Dongtai poplar plantation. From August to December 2019 and from July to August and November 2020, the soil CH4 flux in the Sihong poplar plantation was significantly higher than in the Dongtai poplar plantation. Moreover, the soil CH4 flux significantly increased with rising soil temperature and soil water content. Diurnally, the soil CH4 flux followed a unimodal variation pattern at different growing stages of poplars, with peaks occurring at noon and in the afternoon. However, the soil CH4 flux did not exhibit a consistent seasonal pattern across different years, likely due to substantial variations in precipitation and soil water content. Overall, our study emphasizes the need for a comprehensive understanding of the spatiotemporal variations in forest soil CH4 flux with different soil textures. This understanding is vital for developing reasonable forest management strategies and reducing uncertainties in the global CH4 budget.

Climate warming accelerates carbon release from foliar litter-A global synthesis.

With over one-third of terrestrial net primary productivity transferring to the litter layer annually, the carbon release from litter serves as a crucial valve in atmospheric carbon dioxide concentrations. However, few quantitative global projections of litter carbon release rate in response to climate change exist. Here, we combined a global foliar litter carbon release dataset (8973 samples) to generate spatially explicitly estimates of the response of their residence time (τ) to climate change. Results show a global mean litter carbon release rate ( k $$ k $$ ) of 0.69 year-1 (ranging from 0.09-5.6 year-1). Under future climate scenarios, global mean τ is projected to decrease by a mean of 2.7% (SSP 1-2.6) and 5.9% (SSP 5-8.5) during 2071-2100 period. Locally, the alleviation of temperature and moisture restrictions corresponded to obvious decreases in τ in cold and arid regions, respectively. In contract, τ in tropical humid broadleaf forests increased by 4.6% under SSP 5-8.5. Our findings highlight the vegetation type as a powerful proxy for explaining global patterns in foliar litter carbon release rates and the role of climate conditions in predicting responses of carbon release to climate change. Our observation-based estimates could refine carbon cycle parameterization, improving projections of carbon cycle-climate feedbacks.

Global responses of wetland methane emissions to extreme temperature and precipitation.

As global warming continues, events of extreme heat or heavy precipitation will become more frequent, while events of extreme cold will become less so. How wetlands around the globe will react to these extreme events is unclear yet critical, because they are among the greatest natural sources of methane(CH4). Here we use seven indices of extreme climate and the rate of methane emission from global wetlands(WME) during 2000-2019 simulated by 12 published models as input data. Our analyses suggest that extreme cold (particularly extreme low temperatures) inhibits WME, whereas extreme heat (particularly extreme high temperatures) accelerates WME. Our results also suggest that daily precipitation >10 mm accelerates WME, while much higher daily precipitation levels can slow WME. The correlation of extreme high temperature and precipitation with rate of WME became stronger during the study period, while the correlation between extreme low temperature and WME rate became weaker.

Phenolic compounds weaken the impact of drought on soil enzyme activity in global wetlands.

Soil enzymes play a central role in carbon and nutrient cycling, and their activities can be affected by drought-induced oxygen exposure. However, a systematic global estimate of enzyme sensitivity to drought in wetlands is still lacking. Through a meta-analysis of 55 studies comprising 761 paired observations, this study found that phosphorus-related enzyme activity increased by 38% as result of drought in wetlands, while the majority of other soil enzyme activities remained stable. The expansion of vascular plants under long-term drought significantly promoted the accumulation of phenolic compounds. Using a 2-week incubation experiment with phenol supplementation, we found that phosphorus-related enzyme could tolerate higher biotoxicity of phenolic compounds than other enzymes. Moreover, a long-term (35 years) drainage experiment in a northern peatland in China confirmed that the increased phenolic concentration in surface layer resulting from a shift in vegetation composition inhibited the increase in enzyme activities caused by rising oxygen availability, except for phosphorus-related enzyme. Overall, these results demonstrate the complex and resilient nature of wetland ecosystems, with soil enzymes showing a high degree of adaptation to drought conditions. These new insights could help evaluate the impact of drought on future wetland ecosystem services and provide a theoretical foundation for the remediation of degraded wetlands.

An optimized water table depth detected for mitigating global warming potential of greenhouse gas emissions in wetland of Qinghai-Tibetan Plateau.

Climate change and human activities have intensified variations of water table depth (WTD) in wetlands around the world, which may strongly affect greenhouse gas emissions. Here, we analyzed how emissions of CO2, CH4, and N2O from the Zoige wetland on the Qinghai-Tibetan Plateau (QTP) vary with the WTD. Our data indicate that the wetland shows net positive global warming potential (11.72 tCO2-e ha-1 yr-1), and its emissions of greenhouse gases are driven primarily by WTD. Our analysis suggests that an optimal WTD exists, which at our study site was approximately 18 cm, for mitigating increases in global warming potential from the wetland. Our study provides insights into how climate change and human acitivies affect greenhouse gas emissions from alpine wetlands, and they suggest that water table management may be effective at mitigating future increases in emissions.

Vegetation types and flood water level are dominant factors controlling the carbon sequestration potential in Dongting Lake floodplain, China.

Wetlands are important carbon sinks. However, the carbon sequestration potential of flooded wetlands may be weakened owing to water regime changes induced by anthropogenic disturbances. Using the eddy covariance technique, this study quantified the effects of the water level and vegetation types on the net ecosystem CO2 exchange (NEE), gross primary production (GPP), and ecosystem respiration (Reco) from a reed marsh (Miscanthus sacchariflorus) and a sedge meadow (Carex spp.) in the Dongting Lake floodplain from 2014 to 2016. Our results indicated that the sedge meadow (-89.49 to -186.47 g C m-2 y-1) and reed marsh (-246.12 to -513.94 g C m-2 y-1) were carbon sinks on the interannual timescale. However, the sedge meadow changed from a carbon sink to a carbon source during the flooding season. The effect of flooding on the carbon sink function in the reed marsh was dependent on the water level. The carbon sink function of the reed marsh was enhanced by moderate flooding (water level under 30.5 m in Chenglingji) owing to the inhibition of Reco, but was weakened by extremely high-water levels (over 33 m in Chenglingji) during the flooding season. Seasonal variations in NEE, GPP, and Reco were closely related to photosynthetic photon flux density, soil water content, water level, soil temperature, and air temperature. We can conclude that the increase in reed area combined with the decrease in flooding days in the sedge meadow can potentially enhance the carbon sink function of the Dongting Lake floodplain.

Potential future changes in soil carbon dynamics in the Ziwuling Forest, China under different climate change scenarios.

Soil carbon (C) cycling processes in terrestrial ecosystems are significantly influenced by global changes, and soil microorganisms play a crucial role in soil organic carbon (SOC) and its feedbacks to climate change. To investigate the potential future changes in soil C dynamics under different scenarios in the Ziwuling Forest region, China, we conducted a soil observation and sampling experiment from April 2021 to July 2022. By utilizing a microbial ecological model (MEND), we aimed to predict the future dynamics of soil C under different scenarios in the area. Our results demonstrate that under the RCP2.6 (Representative Concentration Pathway) scenario, SOC showed a rapid increase, SOC under the RCP2.6 scenario will be significantly higher than those under the RCP4.5 scenario and RCP8.5 scenario in the topsoil and whole soil. Furthermore, the positive correlation between total litter carbon (LC) and SOC under the RCP2.6 scenario highlights the potential role of total litter carbon in driving SOC dynamics. Our study also revealed that the low greenhouse gas (GHG) emission scenario favors the accumulation of SOC in the study area, while the high GHG emission scenario leads to greater soil carbon loss. Overall, these results underscore the importance of considering the impact of climate change, especially global warming, on soil ecosystems in the future. Protecting the soil ecosystem of the Loess Plateau is critical for maintaining soil carbon sinks, preventing soil erosion, and improving and regulating the surrounding environmental climate.

Responses of C:N:P stoichiometric correlations among plants, soils and microorganisms to warming: A meta-analysis.

Plants, soils and microorganisms play important roles in maintaining stable terrestrial stoichiometry. Studying how nutrient balances of these biotic and abiotic players vary across temperature gradients is important when predicting ecosystem changes on a warming planet. The respective responses of plant, soil and microbial stoichiometric ratios to warming have been observed, however, whether and how the stoichiometric correlations among the three components shift under warming has not been clearly understood and identified. In the present study, we have performed a meta-analysis based on 600 case studies from 74 sites or locations to clarify whether and how warming affects plant, soil and microbial stoichiometry, respectively, and their correlations. Our results indicated that: (1) globally, plants had higher C:N and C:P values compared to soil and microbial pools, but their N:P distributions were similar; (2) warming did not significantly alter plant, soil and microbial C:N and C:P values, but had a noticeable effect on plant N:P ratios. When ecosystem types, duration and magnitude of warming were taken into account, there was an inconsistent and even inverse warming response in terms of the direction and magnitude of changes in the C:N:P ratios occurring among plants, soils and microorganisms; (3) despite various warming responses of the stoichiometric ratios detected separately for plants, soils and microorganisms, the stoichiometric correlations among all three parts remained constant even under different warming scenarios. Our study highlighted the complexity of the effect of warming on the C:N:P stoichiometry, as well as the absence and importance of simultaneous measurements of stoichiometric ratios across different components of terrestrial ecosystems, which should be urgently strengthened in future studies.

C:N:P stoichiometry of plants, soils, and microorganisms: Response to altered precipitation.

Precipitation changes modify C, N, and P cycles, which regulate the functions and structure of terrestrial ecosystems. Although altered precipitation affects above- and belowground C:N:P stoichiometry, considerable uncertainties remain regarding plant-microbial nutrient allocation strategies under increased (IPPT) and decreased (DPPT) precipitation. We meta-analyzed 827 observations from 235 field studies to investigate the effects of IPPT and DPPT on the C:N:P stoichiometry of plants, soils, and microorganisms. DPPT reduced leaf C:N ratio, but increased the leaf and root N:P ratios reflecting stronger decrease of P compared with N mobility in soil under drought. IPPT increased microbial biomass C (+13%), N (+15%), P (26%), and the C:N ratio, whereas DPPT decreased microbial biomass N (-12%) and the N:P ratio. The C:N and N:P ratios of plant leaves were more sensitive to medium DPPT than to IPPT because drought increased plant N content, particularly in humid areas. The responses of plant and soil C:N:P stoichiometry to altered precipitation did not fit the double asymmetry model with a positive asymmetry under IPPT and a negative asymmetry under extreme DPPT. Soil microorganisms were more sensitive to IPPT than to DPPT, but they were more sensitive to extreme DPPT than extreme IPPT, consistent with the double asymmetry model. Soil microorganisms maintained stoichiometric homeostasis, whereas N:P ratios of plants follow that of the soils under altered precipitation. In conclusion, specific N allocation strategies of plants and microbial communities as well as N and P availability in soil critically mediate C:N:P stoichiometry by altered precipitation that need to be considered by prediction of ecosystem functions and C cycling under future climate change scenarios.

Satellite monitoring reveals short-term cumulative and time-lag effect of drought and heat on autumn photosynthetic phenology in subtropical vegetation.

Comparing with the effect of the average climate change on vegetation phenology, the impacts of extreme climate events remain unclear, especially considering their characteristic cumulative and time-lag effects. Using solar-induced chlorophyll fluorescence (SIF) satellite records, we investigated the cumulative and time-lag effects of drought and heat events on photosynthesis, particularly for the end date of autumn photosynthesis (EOP), in subtropical vegetation in China. Our results showed a negative effect of drought on the delay of EOP, with the cumulative effect on 30.12% (maximum continuous dry days, CDD), 34.82% (dry days, DRD), and 26.14% (dry period, DSDI) of the study area and the general time-lag effect on 50.73% (maximum continuous dry days), 56.61% (dry days), and 47.55% (dry period) of the study area. The cumulative and lagged time were 1-3 months and 2-3 months, respectively. In contrast, the cumulative effect of heat on EOP was observed in 16.27% (warm nights, TN90P), 23.66% (moderate heat days, TX50P), and 19.19% (heavy heat days, TX90P) of the study area, with cumulative time of 1-3 months. The lagged time was 3-4 months, detected in 31.02% (warm nights), 45.86% (moderate heat days), and 36.52% (heavy heat days) of the study area. At the vegetation community level, drought and heat had relatively rapid impacts on EOP in the deciduous broadleaved forest, whereas evergreen forests and bushes responded to heat slowly and took a longer time. Our results revealed that drought and heat have short-term cumulative and time-lag effects on the EOP of subtropical vegetation in China, with varying effects among different vegetation types. These findings provide new insights into the effect of drought and heat on subtropical vegetation and confirm the need to consider these effects in the development of prediction models of autumn phenology for subtropical vegetation.

An early warning signal for grassland degradation on the Qinghai-Tibetan Plateau.

Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

The microbial mechanisms by which long-term heavy metal contamination affects soil organic carbon levels.

Globally, reducing carbon emissions and mitigating soil heavy metal pollution pose pressing challenges. We evaluated the effects of lead (Pb) and cadmium (Cd) contamination in the field over 20 years. The five treatment groups featured Pb concentrations of 40 and 250 mg/kg, Cd concentrations of 10 and 60 mg/kg, and a combination of Pb and Cd (60 and 20 mg/kg, respectively); we also included a pollution-free control group. After 20 years, soil pH decreased notably in all treatments, particularly by 1.02 in Cd10-treated soil. In addition to the increase of SOC in Cd10 and unchanged in Pb40 treatment, the SOC was reduced by 9.62%-12.98% under the other treatments. The α diversities of bacteria and fungi were significantly changed by Cd10 pollution (both p < 0.05) and the microbial community structure changed significantly. However, there were no significant changes in bacterial and fungal communities under other treatments. Cd10 pollution reduced the numbers of Ascomycota and Basidiomycota fungi, and enhanced SOC accumulation. Compared to the control, long-term heavy Cd, Pb, and Pb-Cd composite pollution caused SOC loss by increasing Basidiomycota which promoting carbon degradation, and decreasing Proteobacteria which promoting carbon fixation via the Krebs cycle. Our findings demonstrate that heavy metal pollution mediates Carbon-cycling microorganisms and genes, impacting SOC storage.

Leaf trait responses to global change factors in terrestrial ecosystems.

Global change influences plant growth by affecting plant morphology and physiology. However, the effects of global change factors vary based on the climate gradient. Here, we established a global database of leaf traits from 192 experiments on elevated CO2 concentrations (eCO2), drought, N deposition, and warming. The results showed that the leaf mass per area (LMA) significantly increased under eCO2 and drought conditions but decreased with N deposition, whereas eCO2 levels and drought conditions reduced stomatal conductance and increased and decreased photosynthetic rates, respectively. Leaf dark respiration (Rd) increased in response to global change, excluding N deposition. Leaf N concentrations declined with eCO2 but increased with N deposition. Leaf area increased with eCO2, N deposition, and warming but decreased with drought. Leaf thickness increased with eCO2 but decreased with warming. eCO2 and N deposition enhanced plant water-use efficiency (WUE), eCO2 and warming increased photosynthetic N-use efficiency (PNUE), while N fertilization reduced PNUE significantly. eCO2 produced a positive relationship between WUE and PNUE, which were limited under drought but increased in areas with high humidity and high temperature. Trade-offs were observed between WUE and PNUE under drought, N deposition, and warming. These findings suggest that the effects of global change factors on plants can be altered by complex environmental changes; moreover, diverse plant water and nutrient strategy responses can be interpreted against the background of their functional traits.

Climatic drivers and ecological implications of variation in the time interval between leaf-out and flowering.

Leaf-out and flowering in any given species have evolved to occur in a predetermined sequence, with the inter-stage time interval optimized to maximize plant fitness. Although warming-induced advances of both leaf-out and flowering are well documented, it remains unclear whether shifts in these phenological phases differ in magnitudes and whether changes have occurred in the length of the inter-stage intervals. Here, we present an extensive synthesis of warming effects on flower-leaf time intervals, using long-term (1963-2014) and in situ data consisting of 11,858 leaf-out and flowering records for 183 species across China. We found that the timing of both spring phenological events was generally advanced, indicating a dominant impact of forcing conditions compared with chilling. Stable time intervals between leaf-out and flowering prevailed for most of the time series despite increasing temperatures; however, some of the investigated cases featured significant changes in the time intervals. The latter could be explained by differences in the temperature sensitivity (ST) between leaf and flower phenology. Greater ST for flowering than for leaf-out caused flowering times to advance faster than leaf emergence. This shortened the inter-stage intervals in leaf-first species and lengthened them in flower-first species. Variation in the time intervals between leaf-out and flowering events may have far-reaching ecological and evolutionary consequences, with implications for species fitness, intra/inter-species interactions, and ecosystem structure, function, and stability.

Climate change mitigation potential of kitchen waste utilization in China for combined heat and power production.

Given the concerns about climate change, energy sustainability, and public health, the reuse of kitchen wastes (KW) is attracting increasing interest. In China, the municipal solid waste sorting scheme has increased the available KW. To assess the available KW and the climate change mitigation potential of KW utilization for bioenergy in China, three scenarios (base, conservative, and ambitious) were defined. A new framework was implemented to assess the climate change impacts of bioenergy. The annual available KW ranged from 11.450 million dry tons (in metric) under the conservative scenario to 22.898 million dry tons in the ambitious scenario, and had the potential to produce 12.37 × 106-24.74 × 106 MWh heat and 9.62 × 106-19.24 × 106 MWh power. The total potential climate change impacts of KW for combined heat and power were 3.339-6.717 million tons CO2 eq in China. The highest eight provinces and municipalities contributed over half of the national total. Among the three components of the new framework, fossil fuel-derived greenhouse gas emissions and biogenic CO2 emissions were positive. The difference in carbon sequestration was negative and ensured a lower integrated life-cycle climate change impacts than that of natural gas-derived combined heat and power. The mitigation effects of using KW as a substitute for natural gas and synthetic fertilizers were 2.477-8.080 million tons CO2 eq. These outcomes can inform relevant policymaking and benchmark climate change mitigation in China. The conceptual framework of this study can also be adapted for applications in other countries or regions worldwide.

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.