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Tidal freshwater forested wetlands (TFFW) provide critical ecosystem services including an essential habitat for a variety of wildlife species and significant carbon sinks for atmospheric carbon dioxide. However, large uncertainties remain concerning the impacts of climate change on the magnitude and variability of carbon fluxes and storage across a range of TFFW. In this study, we developed a process-driven Tidal Freshwater Wetlands DeNitrification-DeComposition model (TFW-DNDC) that has integrated new features, such as soil salinity effects on plant productivity and soil organic matter decomposition to explore carbon dynamics in the TFFW in response to drought-induced saltwater intrusion. Eight sites along the floodplains of the Waccamaw River (USA) and the Savannah River (USA) were selected to represent the TFFW transition from healthy to moderately and highly salt-impacted forests, and eventually to oligohaline marshes. The TFW-DNDC was calibrated and validated using field observed annual litterfall, stem growth, root growth, soil heterotrophic respiration, and soil organic carbon storage. Analyses indicate that plant productivity and soil carbon sequestration in TFFW could change substantially in response to increased soil pore water salinity and reduced soil water table due to drought, but in interactive ways dependent on the river simulated. These responses are variable due to nonlinear relationships between carbon cycling processes and environmental drivers. Plant productivity, plant respiration, soil organic carbon sequestration rate, and storage in the highly salt-impacted forest sites decreased significantly under drought conditions compared with normal conditions. Considering the high likelihood of healthy and moderately salt-impacted forests becoming highly salt-impacted forests under future climate change and sea-level rise, it is very likely that the TFFW will lose their capacity as carbon sinks without up-slope migration.

Progress on reducing nutrient loss from annual croplands has been hampered by perceived conflicts between short‐term profitability and long‐term stewardship, but these may be overcome through strategic integration of perennial crops. Perennial biomass crops like switchgrass can mitigate nitrate‐nitrogen (NO3‐N) leaching, address bioenergy feedstock targets, and – as a lower‐cost management alternative to annual crops (i.e., corn, soybeans) – may also improve farm profitability. We analyzed publicly available environmental, agronomic, and economic data with two integrated models: a subfield agroecosystem management model, Landscape Environmental Assessment Framework (LEAF), and a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC). We constructed a factorial combination of profitability and NO3‐N leaching thresholds and simulated targeted switchgrass integration into corn/soybean cropland in the agricultural state of Iowa, USA. For each combination, we modeled (i) area converted to switchgrass, (ii) switchgrass biomass production, and (iii) NO3‐N leaching reduction. We spatially analyzed two scenarios: converting to switchgrass corn/soybean cropland losing >US $ 100 ha−1 and leaching >50 kg ha−1 (‘conservative’ scenario) or losing >US$0 ha−1 and leaching >20 kg ha−1 (‘nutrient reduction’ scenario). Compared to baseline, the ‘conservative’ scenario resulted in 12% of cropland converted to switchgrass, which produced 11 million Mg of biomass and reduced leached NO3‐N 18% statewide. The ‘nutrient reduction’ scenario converted 37% of cropland to switchgrass, producing 34 million Mg biomass and reducing leached NO3‐N 38% statewide. The opportunity to meet joint goals was greatest within watersheds with undulating topography and lower corn/soybean productivity. Our approach bridges the scales at which NO3‐N loss and profitability are usually considered, and is informed by both mechanistic and empirical understanding. Though approximated, our analysis supports development of farm‐level tools that can identify locations where both farm profitability and water quality improvement can be achieved through the strategic integration of perennial vegetation. We modelled the effects of strategic subfield integration of switchgrass into corn/soybean cropland on Nitrate‐Nitrogen (NO3‐N) leaching reduction, using two decision making scenarios. In an exemplary impaired watershed in Iowa, in which 80 % of land is in corn/soybeans, the ‘conservative’ scenario would result in 14.3 % of considered cropland converted to switchgrass with a concomitant NO3‐N leaching reduction of 11.3 %. The ‘nutrient reduction’ scenario would result in 39.7 % of considered cropland converted to switchgrass and reduce NO3‐N leached by 31.4 %.

Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well as limited data availability. We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long‐term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C‐cycle processes. Bayesian calibration was conducted using quality‐controlled C flux data sets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern US rangelands to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass‐shrub mixture, and grass‐tree mixture). The resulting RCTM system produced higher model accuracy for estimating annual cumulative gross primary productivity (GPP) (R2 > 0.6, RMSE <390 g C m−2) relative to net ecosystem exchange of CO2 (NEE) (R2 > 0.4, RMSE <180 g C m−2). Model performance in estimating rangeland C fluxes varied by season and vegetation type. The RCTM captured the spatial variability of SOC stocks with R2 = 0.6 when validated against SOC measurements across 13 NEON sites. Model simulations indicated slightly enhanced SOC stocks for the flux tower sites during the past decade, which is mainly driven by an increase in precipitation. Future efforts to refine the RCTM system will benefit from long‐term network‐based monitoring of vegetation biomass, C fluxes, and SOC stocks. Plain Language Summary Rangelands play a crucial role in providing various ecosystem services, including potential climate change mitigation through increased soil organic carbon (SOC) storage. Accurate estimates of changes in carbon (C) storage are challenging due to the heterogeneous nature of rangelands and the limited availability of field observations. In this work, we leveraged remote sensing observations, tower‐based C flux measurements from over 60 rangeland sites in the Western and Midwestern US, and other environmental data sets to build the process‐based Rangeland Carbon Tracking and Management (RCTM) modeling system. The RCTM system is designed to simulate the past 20 years of rangeland C dynamics and is regionally calibrated. The RCTM system performs well in estimating spatial and temporal rangeland C fluxes as well as spatial SOC storage. Model simulation results revealed increased SOC storage and rangeland productivity driven by annual precipitation patterns. The RCTM system developed by this work can be used to generate accurate spatial and temporal estimates of SOC storage and C fluxes at fine spatial (30 m) and temporal (every 5 days) resolutions, and is well‐suited for informing rangeland C management strategies and improving broad‐scale policy making. Key Points The Rangeland Carbon Tracking and Monitoring System was calibrated to simulate vegetation type‐specific rangeland C dynamics Regional variability in carbon fluxes and soil organic carbon is well represented by a remote sensing‐driven process modeling approach Soil organic carbon stocks in Western and Midwestern US rangelands increased over the past 20 years due to increased precipitation

Aims Process-based biogeochemical models can be used to simulate soil nitrous oxide (N 2 O) fluxes and maize yields and draw insights on yields improvement and climate change mitigation options. We compared both observed and DeNitrification-DeComposition (DNDC) simulated soil N 2 O fluxes and maize yields. Methods We used DNDC model to simulate soil N 2 O fluxes and maize yields under four soil fertility treatments (inorganic fertiliser, animal manure, animal manure + inorganic fertiliser and control,) replicated thrice for 1 year in Central Highlands of Kenya. We sampled soil N 2 O fluxes using static chambers installed in each plot. We analysed soil N 2 O using gas chromatography and calculated cumulative fluxes using trapezoidal rule linear interpolation between sampling dates. Results DNDC showed poor results in simulating daily N 2 O fluxes (157.16% ≤ normalised root mean square error (nRMSE) ≤ 324.01% and 0.90 ≤ modelling efficiency (NSE) ≤ 0.96), good to excellent performance in simulating cumulative annual soil N 2 O fluxes (6.16 ≤ nRMSE ≤12.86 and 0.63 ≤ NSE ≤ 0.86) and good to excellent performance in simulating maize yields (1.15% ≤ nRMSE ≤13.86% and 0.51 ≤ NSE ≤ 0.88) across all soil fertility treatments. Conclusion The DNDC model had good to excellent performance in simulating cumulative soil N 2 O fluxes and crop yields across treatments. Though the model captured yield-scaled N 2 O fluxes and N 2 O emission factors across treatments, they were underestimated under manure treatment. There is a need to continue calibrating the DNDC model for improved capture of daily N 2 O fluxes and uptakes on Kenyan soils.

Soil organic carbon (SOC) conservation in agricultural soils is vital for sustainable agricultural production and climate change mitigation. To project changes of SOC and rice yield under different water and carbon management in future climates, based on a two-year (2015 and 2016) field test in Kunshan, China, the Denitrification Decomposition (DNDC) model was modified and validated and the soil moisture module of DNDC was improved to realize the simulation under conditions of water-saving irrigation. Four climate models under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5), which were integrated from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), were ensembled by the Bayesian Model Averaging (BMA) method. The results showed that the modified DNDC model can effectively simulate changes in SOC, dissolved organic carbon (DOC), and rice yield under different irrigation and fertilizer management systems. The normalized root mean squared errors of the SOC and DOC were 3.45–17.59% and 8.79–13.93%, respectively. The model efficiency coefficients of SOC and DOC were close to 1. The climate scenarios had a great impact on rice yield, whereas the impact on SOC was less than that of agricultural management measures on SOC. The average rice yields of all the RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 scenarios in the 2090s decreased by 18.41%, 38.59%, 65.11%, and 65.62%, respectively, compared with those in the 2020s. The long-term effect of irrigation on the SOC content of paddy fields was minimal. The SOC of the paddy fields treated with conventional fertilizer decreased initially and then remained unchanged, while the other treatments increased obviously with time. The rice yields of all the treatments decreased with time. Compared with traditional management, controlled irrigation with straw returning clearly increased the SOC and rice yields of paddy fields. Thus, this water and carbon management system is recommended for paddy fields.

Carbon fluxes in tidal brackish marshes play a critical role in determining coastal wetland carbon sequestration and storage, thus affecting carbon crediting of coastal wetland restoration. In this study, a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool DeNitrification-DeComposition was applied to nine brackish marsh sites in Mississippi River (MR) Deltaic Plain to examine the responses of gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem exchange (NEE), and emissions of methane (CH 4 ) and nitrous oxide (N 2 O) to climate change. Simulations of a normal hydrologic year (2013), dry year (2011) and wet year (2021), and a hypothetical sea level rise (SLR) case were conducted as climate change scenarios. These climate change scenarios were determined by the Palmer Drought Severity Index (PDSI) for the Northeast Division of Coastal Louisiana during 2001–2021. Model results showed that GPP, ER, NEE, CH 4 , and N 2 O vary with site, and these brackish marshes lost carbon (net CO 2 emission) due to large reduction in primary productivity under the climate scenarios, as well as even during the normal hydrologic year. Average cross-site NEE were 148, 140 and 132 g C m −2  yr −1 in the dry, wet, and normal years (all net loss of wetland C). Under the hypothetical SLR, NEE were reduced by -25% compared to the normal year, but GPP and NPP were declined by -40% and -70%, respectively. These results suggest that climate change induced changes in soil salinity and water table depth will exacerbate carbon loss from tidal brackish marshes.

A comprehensive understanding of the potential effects of conservation practices on soil health, crop productivity, and greenhouse gas (GHG) emissions remains elusive, despite extensive research. Thus, the DeNitrification–DeComposition (DNDC) model was employed to evaluate the impact of eleven commonly practiced management scenarios on ecosystem services in the Western Lake Erie Basin, USA, from 1998–2020. Out of eleven scenarios, eight were focused on corn–soybean rotations with varied nitrogen application timing (50% before planting and 50% at either fall or spring during or after planting), or nitrogen source (dairy slurry or synthetic fertilizer (SF)), or tillage practices (conventional, no-till), or cereal rye (CR) in rotation. Remaining scenarios involved rotations with silage corn (SC), winter crops (CR or winter wheat), and alfalfa. The silage corn with winter crop and four years of alfalfa rotation demonstrated enhanced ecosystem services compared to equivalent scenario with three years of alfalfa. Applying half the total nitrogen to corn through SF during or after spring-planted corn increased yield and soil organic carbon (SOC) sequestration while raising global warming potential (GWP) than fall-applied nitrogen. The no-till practice offered environmental benefits with lower GWP and higher SOC sequestration, while resulting in lower yield than conventional tillage. The incorporation of CR into corn–soybean rotations enhanced carbon sequestration, increased GHG emissions, improved corn yield, and lowered soybean yield. Substituting SF with manure for corn production improved corn yield under conventional tillage and increased SOC while increasing GWP under both tillage conditions. While the role of conservation practices varies by site, this study’s findings aid in prioritizing practices by evaluating tradeoffs among a range of ecosystem services.

The impact of climate change on methane (CH4) emissions from rice production systems in the Coimbatore region (Tamil Nadu, India) was studied by leveraging field experiments across two main treatments and four sub-treatments in a split-plot design. Utilizing the closed-chamber method for gas collection and gas chromatography analysis, this study identified significant differences in CH4 emissions between conventional cultivation methods and the system of rice intensification (henceforth SRI). Over two growing seasons, conventional cultivation methods reported higher CH4 emissions (range: from 36.9 to 59.3 kg CH4 ha−1 season−1) compared with SRI (range: from 2.2 to 12.8 kg CH4 ha−1 season−1). Experimental data were subsequently used to guide parametrization and validation of the DeNitrification–DeComposition (DNDC) model. The validation of the model showed good agreement between the measured and modeled data, as denoted by the statistical tests performed, which included CRM (0.09), D-index (0.99), RMSE (7.16), EF (0.96), and R2 (0.92). The validated model was then used to develop future CH4 emissions projections under various shared socio-economic pathways (henceforth SSPs) for the mid- (2021–2050) and late (2051–2080) century. The analysis revealed a potential increase in CH4 emissions for the simulated scenarios, which was dependent on specific soil and irrigation management practices. Conventional cultivation produced the highest CH4 emissions, but it was shown that they could be reduced if the current practice was replaced by minimal flooding or through irrigation with alternating wetting and drying cycles. Emissions were predicted to rise until SSP 370, with a marginal increase in SSP 585 thereafter. The findings of this work underscored an urgency to develop climate-smart location-specific mitigation strategies focused on simultaneously improving current water and nutrient management practices. The use of methanotrophs to reduce CH4 production from rice systems should be considered in future work. This research also highlighted the critical interaction that exists between agricultural practices and climate change, and emphasized the need to implement adaptive crop management strategies that can sustain productivity and mitigate the environmental impacts of rice-based systems in southern India.

Background: Traditional polyethylene film mulching is widely used in the Loess Plateau region of China to improve crop yields. However, whether long-term polyethylene film mulching can continue to ensure crop yield under future climate change conditions is questionable. First, we conducted a four-year field experiment to calibrate and validate the biogeochemical DeNitrification–DeComposition (DNDC) model. Then, based on the calibrated and validated model, we evaluated the spring maize yield and water use efficiency under different film mulching methods (no mulching, traditional polyethylene film mulching, and biodegradable film mulching) in the Loess Plateau region. Results: The temperature and rainfall in the Loess Plateau region are predicted to increase in the future (2021–2100) under four scenarios due to higher CO2 concentrations. Through 252 simulation results, we found that future climate change will have positive impacts under no mulching, traditional polyethylene film mulching, and degradable film mulching conditions. The yield increase will be greater with no mulching, but in the future, film mulching will continue to reduce crop yields. Additionally, the crop yield reduction under traditional polyethylene film mulching is greater. A sensitivity analysis indicated that rainfall will have a major effect on yield, and polyethylene film mulching will reduce the sensitivity of the yield to rainfall. As the rainfall increases, the differences between the yield and water use efficiency under ordinary plastic film and degradable film will become smaller. In the later period with a warmer and wetter climate under the SSP585 scenario, the water use efficiency will be higher under degradable film than traditional polyethylene film mulching. Conclusion: It can be seen that degradable film is more adaptable to the warmer and wetter climate in the future.

Aim We test the hypothesis that land use and climate are important controls of nitrous oxide (N2O) emissions from savanna ecosystems, and that these emissions can be represented by a mechanistic model of carbon (C) and nitrogen (N) transformations. Location Miombo woodlands in Zimbabwe are part of widespread woody savanna formations in southern and central Africa that cover more than 2.7 million km2. The rainfall in this region is around 800 mm and is concentrated in the period between November and March. Methods Losses of N2O were measured along transects in two field areas using static chambers over a period of 1 year. The vegetation in both areas was dominated by Julbernardia globiflora and Brachystegia spiciformis, but had differing management systems (burned and unburned), soil properties and site characteristics (slope and drainage). The effects of simulated rainfall and fertilizer additions were studied in laboratory incubations. Results Patterns of N2O emissions were strongly linked to rainfall. The highest fluxes at both sites were measured within 18 days of the onset of the first rains in November, with fluxes of up to 42 μ g N m-2h-1. During the dry season, fluxes were lower, but a large proportion (R2values between 0.8 and 0.95, P < 0.001) of the N2O flux could be predicted by variations in soil moisture. Soil columns were set up in the laboratory to which simulated rainwater was added, and the amounts and timing of rainwater addition were varied. Losses of N2O were highest within the first week of the laboratory study. Altering the amount of rainwater addition did not significantly affect N2O loss; however, a continuous addition of water resulted in higher losses of N2O (up to 79 μ g N m-2h-1) than periodic addition of the same amount. A model (denitrification-decomposition) was used to simulate N2O release over a 12 month period, using meteorological data recorded in the vicinity of the field site. The simulations and field data suggest that nitrification was the main process responsible for N2O release during the dry season but that denitrification was more important during the wet season. Main conclusions The release of N2O from dryland savannas was shown to constitute an important nutrient flux, and emissions were strongly linked to patterns of rainfall; however, there was evidence to suggest that the magnitude of fluxes is also influenced locally by differences in soil organic matter concentration and drainage.