Eddy covariance measurements of net ecosystem carbon dioxide (CO2) exchange (NEE) were taken at an ombrotrophic bog near Ottawa, Canada from 1 June 1998 to 31 May 2002. Temperatures during this ...period were above normal except for 2000 and precipitation was near normal in 1998 and 1999, above normal in 2000, and well below normal in 2001. Growing period maximum daytime uptake (−0.45 mg CO2 m−2 s−1) was similar in all years and nighttime maximum respiration was typically near 0.20 mg CO2 m−2 s−1, however, larger values were recorded during very dry conditions in the fourth year of study. Winter CO2 flux was considerably smaller than in summer, but persistent, resulting in significant accumulated losses (119–132 g CO2 m−2 period−1). This loss was equivalent to between 30 and 70% of the net CO2 uptake during the growing season. During the first 3 years of study, the bog was an annual sink for CO2 (∼−260 g CO2 m−2 yr−1). In the fourth year, with the dry summer, however, annual NEE was only −34 g CO2 m−2 yr−1, which is not significantly different from zero. We examined the performance of a peatland carbon simulator (PCARS) model against the tower measurements of NEE and derived ecosystem respiration (ER) and photosynthesis (PSN). PCARS ER and PSN were highly correlated with tower‐derived fluxes, but the model consistently overestimated both ER and PSN, with slightly poorer comparisons in the dry year. As a result of both component fluxes being overestimated, PCARS simulated the tower NEE reasonably well. Simulated decomposition and autotrophic respiration contributed about equal proportions to ER. Shrubs accounted for the greatest proportion of PSN (85%); moss PSN declined to near zero during the summer period due to surface drying.
Large‐scale assessments of the potential for food production and its impact on biogeochemical cycling require the best possible information on the distribution of cropland. This information can come ...from ground‐based agricultural census data sets and/or spaceborne remote sensing products, both with strengths and weaknesses. Official cropland statistics for China contain much information on the distribution of crop types, but are known to significantly underestimate total cropland areas and are generally at coarse spatial resolution. Remote sensing products can provide moderate to fine spatial resolution estimates of cropland location and extent, but supply little information on crop type or management. We combined county‐scale agricultural census statistics on total cropland area and sown area of 17 major crops in 1990 with a fine‐resolution land‐cover map derived from 1995–1996 optical remote sensing (Landsat) data to generate 0.5° resolution maps of the distribution of rice agriculture in mainland China. Agricultural census data were used to determine the fraction of crop area in each 0.5° grid cell that was in single rice and each of 10 different multicrop paddy rice rotations (e.g., winter wheat/rice), while the remote sensing land‐cover product was used to determine the spatial distribution and extent of total cropland in China. We estimate that there were 0.30 million km2 of paddy rice cropland; 75% of this paddy land was multicropped, and 56% had two rice plantings per year. Total sown area for paddy rice was 0.47 million km2. Paddy rice agriculture occurred on 23% of all cultivated land in China.
Since the early 1980s, water management of rice paddies in China has changed substantially, with midseason drainage gradually replacing continuous flooding. This has provided an opportunity to ...estimate how a management alternative impacts greenhouse gas emissions at a large regional scale. We integrated a process‐based model, DNDC, with a GIS database of paddy area, soil properties, and management factors. We simulated soil carbon sequestration (or net CO2 emission) and CH4 and N2O emissions from China's rice paddies (30 million ha), based on 1990 climate and management conditions, with two water management scenarios: continuous flooding and midseason drainage. The results indicated that this change in water management has reduced aggregate CH4 emissions about 40%, or 5 Tg CH4 yr−1, roughly 5–10% of total global methane emissions from rice paddies. The mitigating effect of midseason drainage on CH4 flux was highly uneven across the country; the highest flux reductions (>200 kg CH4‐C ha−1 yr−1) were in Hainan, Sichuan, Hubei, and Guangdong provinces, with warmer weather and multiple‐cropping rice systems. The smallest flux reductions (<25 kg CH4‐C ha−1 yr−1) occurred in Tianjin, Hebei, Ningxia, Liaoning, and Gansu Provinces, with relatively cool weather and single cropping systems. Shifting water management from continuous flooding to midseason drainage increased N2O emissions from Chinese rice paddies by 0.15 Tg N yr−1 (∼50% increase). This offset a large fraction of the greenhouse gas radiative forcing benefit gained by the decrease in CH4 emissions. Midseason drainage‐induced N2O fluxes were high (>8.0 kg N/ha) in Jilin, Liaoning, Heilongjiang, and Xinjiang provinces, where the paddy soils contained relatively high organic matter. Shifting water management from continuous flooding to midseason drainage reduced total net CO2 emissions by 0.65 Tg CO2‐C yr−1, which made a relatively small contribution to the net climate impact due to the low radiative potential of CO2. The change in water management had very different effects on net greenhouse gas mitigation when implemented across climatic zones, soil types, or cropping systems. Maximum CH4 reductions and minimum N2O increases were obtained when the mid‐season draining was applied to rice paddies with warm weather, high soil clay content, and low soil organic matter content, for example, Sichuan, Hubei, Hunan, Guangdong, Guangxi, Anhui, and Jiangsu provinces, which have 60% of China's rice paddies and produce 65% of China's rice harvest.
Soil carbon dioxide efflux (soil respiration, SR) was measured with eight autochambers at two locations along a wetland to upland slope at Harvard Forest over a 4 year period, 2003–2007. SR was ...consistently higher in the upland plots than at the wetland margin during the late summer/early fall. Seasonal and diel hystereses with respect to soil temperatures were of sufficient magnitude to prevent quantification of the influence of soil moisture, although apparent short‐term responses of SR to precipitation occurred. Calculations of annual cumulative SR illustrated a decreasing trend in SR over the 5 year period, which were correlated with decreasing springtime mean soil temperatures. Spring soil temperatures decreased despite rising air temperatures over the same period, possibly as an effect of earlier leaf expansion and shading. The synchronous decrease in spring soil temperatures and SR during regional warming of air temperatures may represent a negative feedback on a warming climate by reducing CO2 production from soils. SR reached a maximum later in the year than total ecosystem respiration (ER) measured at a nearby eddy covariance flux tower, and the seasonality of their temperature response patterns were roughly opposite. SR, particularly in the upland, exceeded ER in the late summer/early fall in each year, suggesting that areas of lower efflux such as the wetland may be significant in the flux tower footprint or that long‐term bias in either estimate may create a mismatch. Annual estimates of ER decreased over the same period and were highly correlated with SR.
During early July 2002, wildfires burned ∼1 × 106 ha of forest in Quebec, Canada. The resultant smoke plume was seen in satellite images blanketing the U.S. east coast. Concurrently, extremely high ...CO mixing ratios were observed at the Atmospheric Investigation, Regional Modeling, Analysis and Prediction (AIRMAP) network sites in New Hampshire and at the Harvard Forest Environmental Measurement Site (HFEMS) in Massachusetts. The CO enhancements were on the order of 525–1025 ppbv above low mixing ratio conditions on surrounding days. A biomass burning source for the event was confirmed by concomitant enhancements in aerosol K+, NH4+, NO3−, and C2O42− mixing ratios at the AIRMAP sites. Additional data for aerosol K, organic carbon, and elemental carbon from the Interagency Monitoring of Protected Visual Environments network and CO data from Environmental Protection Agency sites indicated that the smoke plume impacted much of the U.S. east coast, from Maine to Virginia. CO mixing ratios and K concentrations at stations with 10‐year or longer records suggested that this was the largest biomass burning plume to impact the U.S. east coast in over a decade. Furthermore, CO mixing ratios and aerosol particles with diameters <2.5 μm (PM2.5) mass and scattering coefficients from the AIRMAP network and HFEMS indicated that this event was comparable to the large anthropogenic combustion and haze events which intermittently impact rural New England. The degree of enhancement of O3, NOy, NO3−, NH4+, and SO42− in the biomass plume showed significant variation with elevation and latitude that is attributed to variations in transport and surface depositional processes.
Climate mitigation and the future of tropical landscapes Thomson, Allison M.; Calvin, Katherine V.; Chini, Louise P. ...
Proceedings of the National Academy of Sciences - PNAS,
11/2010, Letnik:
107, Številka:
46
Journal Article
Recenzirano
Odprti dostop
Land-use change to meet 21st-century demands for food, fuel, and fiber will depend on many interactive factors, including global policies limiting anthropogenic climate change and realized ...improvements in agricultural productivity. Climate-change mitigation policies will alter the decision-making environment for land management, and changes in agricultural productivity will influence cultivated land expansion. We explore to what extent future increases in agricultural productivity might offset conversion of tropical forest lands to crop lands under a climate mitigation policy and a contrasting no-policy scenario in a global integrated assessment model. The Global Change Assessment Model is applied here to simulate a mitigation policy that stabilizes radiative forcing at 4.5 W m⁻² (approximately 526 ppm CO₂) in the year 2100 by introducing a price for all greenhouse gas emissions, including those from land use. These scenarios are simulated with several cases of future agricultural productivity growth rates and the results downscaled to produce gridded maps of potential land-use change. We find that tropical forests are preserved near their present-day extent, and bioenergy crops emerge as an effective mitigation option, only in cases in which a climate mitigation policy that includes an economic price for land-use emissions is in place, and in which agricultural productivity growth continues throughout the century. We find that idealized land-use emissions price assumptions are most effective at limiting deforestation, even when cropland area must increase to meet future food demand. These findings emphasize the importance of accounting for feedbacks from land-use change emissions in global climate change mitigation strategies.
Soil microbes drive decomposition of soil organic matter (SOM) and regulate soil carbon (C) dynamics. Process‐based models have been developed to quantify changes in soil organic carbon (SOC) and ...carbon dioxide (CO2) fluxes in agricultural ecosystems. However, microbial processes related to SOM decomposition have not been, or are inadequately, represented in these models, limiting predictions of SOC responses to changes in microbial activities. In this study, we developed a microbial‐mediated decomposition model based on a widely used biogeochemical model, DeNitrification‐DeComposition (DNDC), to simulate C dynamics in agricultural ecosystems. The model simulates organic matter decomposition, soil respiration, and SOC formation by simulating microbial and enzyme dynamics and their controls on decomposition, and considering impacts of climate, soil, crop, and farming management practices (FMPs) on C dynamics. When evaluated against field observations of net ecosystem CO2 exchange (NEE) and SOC change in two winter wheat systems, the model successfully captured both NEE and SOC changes under different FMPs. Inclusion of microbial processes improved the model's performance in simulating peak CO2 fluxes induced by residue return, primarily by capturing priming effects of residue inputs. We also investigated impacts of microbial physiology, SOM, and FMPs on soil C dynamics. Our results demonstrated that residue or manure input drove microbial activity and predominantly regulated the CO2 fluxes, and manure amendment largely regulated long‐term SOC change. The microbial physiology had considerable impacts on the microbial activities and soil C dynamics, emphasizing the necessity of considering microbial physiology and activities when assessing soil C dynamics in agricultural ecosystems.
Plain Language Summary
Soil microbes drive decomposition of soil organic matter (SOM) and regulate soil carbon (C) dynamics. Process‐based models are useful tools for quantifying changes in soil organic carbon (SOC) and carbon dioxide (CO2) fluxes in agricultural ecosystems. However, microbial processes related to SOM decomposition have not been, or are inadequately, represented in these models, limiting predictions of SOC responses to changes in microbial activities. We developed a microbial‐mediated decomposition model based on a widely used biogeochemical model, DeNitrification‐DeComposition (DNDC), to simulate C dynamics in agricultural ecosystems. The model simulates organic matter decomposition, soil respiration, and SOC formation by simulating microbial dynamics and controls on decomposition, and considering impacts of climate, soil, crop, and farming management practices (FMPs) on C dynamics. We also investigated impacts of microbial physiology, SOM, and FMPs on soil C dynamics. Our results demonstrated that residue or manure input drove microbial activity and predominantly regulated CO2 fluxes, and manure amendment largely regulated long‐term SOC change. The microbial physiology had considerable impacts on microbial activities and soil C dynamics, emphasizing the necessity of considering microbial physiology and activities when assessing soil C dynamics in agricultural ecosystems. These results provide insights in simulating microbial‐mediated soil C dynamics in agricultural ecosystems.
Key Points
A biogeochemical model was improved to simulate microbe‐driven soil organic matter (SOM) decomposition and carbon dynamics in agricultural ecosystems
The model simulates carbon dynamics by simulating both microbial controls and impacts of soil, crop, and farming management practices
Carbon input drives microbial activity and exerts large impacts on carbon dynamics while microbes play a central role in decomposing SOM
Net ecosystem CO2 exchange (NEE) was measured from June 2000 through October 2001 by 10 automatic chambers at a peatland in southeastern New Hampshire. The high temporal frequency of this sampling ...method permitted detailed examination of NEE as it varied daily and seasonally. Summer of 2001 was significantly drier than the 30‐year average, while summer of 2000 was wetter than normal. Although NEE varied spatially across the peatland with differences in plant species composition and biomass, maximum CO2 uptake was 30–40% larger in the drier summer in evergreen and deciduous shrub communities but the same or lower in sedge sites. Ecosystem respiration rates were 13–84% larger in the drier summer depending on plant growth form with water table and temperature as strong predictors. Ecosystem respiration was also correlated with maximum ecosystem productivity and foliar biomass suggesting that plant processes, water table, and temperature are tightly linked in their control of respiratory losses. The ratio between maximum productivity and respiration declined for evergreen shrub and sedge sites between the wet and dry summer, but increased in deciduous shrub sites. A drier climate may reduce the CO2 sink function of peatlands for some growth forms and increase it for others, suggesting that ecosystem carbon and climate models should account for differences in growth form responses to climate change. It also implies that plant functional types respond on short timescales to changes in moisture, and that the transition from sedges to shrubs could occur rapidly in peatlands under a drier and warmer climate.
This paper describes a rain‐event driven, process‐oriented simulation model, DNDC, for the evolution of nitrous oxide (N2O), carbon dioxide (CO2), and dinitrogen (N2) from agricultural soils. The ...model consists of three submodels: thermal‐hydraulic, decomposition, and denitrification. Basic climate data drive the model to produce dynamic soil temperature and moisture profiles and shifts of aerobic‐anaerobic conditions. Additional input data include soil texture and biochemical properties as well as agricultural practices. Between rainfall events the decomposition of organic matter and other oxidation reactions (including nitrification) dominate, and the levels of total organic carbon, soluble carbon, and nitrate change continuously. During rainfall events, denitrification dominates and produces N2O and N2. Daily emissions of N2O and N2 are computed during each rainfall event and cumulative emissions of the gases are determined by including nitrification N2O emissions as well. Sensitivity analyses reveal that rainfall patterns strongly influence N2O emissions from soils but that soluble carbon and nitrate can be limiting factors for N2O evolution during denitrification. During a year sensitivity simulation, variations in temperature, precipitation, organic C, clay content, and pH had significant effects on denitrification rates and N2O emissions. The responses of DNDC to changes of external parameters are consistent with field and experimental results reported in the literature.
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