934 resultados para soil carbon
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Peer reviewed
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© 2016 John Wiley & Sons Ltd. Funded by DEVIL project. Grant Number: NE/M021327/1 Global Carbon Project MaGNET programme EU FP7 SmartSoil project. Grant Number: 289694
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The influence water levels have on CO2 and CH4 efflux were investigated at the Loxahatchee Impoundment Landscape Assessment (LILA) research facility, located in Boynton Beach, FL, USA. Measurements of CO2 efflux were taken for 24 h periods four times for one year from study plots. Laboratory incubations of intact soil cores were sampled for CO2, CH4, and redox potential. Additionally, soil cores from wet and dry condition were incubated for determination of enzyme activity and macronutrient limitation on decomposition of organic matter from study soils. Water levels had a significant negative influence on CO2 efflux and redox, but did not significantly influence CH4 efflux. Study plots were significantly different in CH4 efflux and redox potential. Labile carbon was more limiting to potential CO2 and CH4 production than phosphorus, with the effect significantly greater from dry conditions soils. Enzyme activity results were variable with greater macronutrient responses from dry condition soils.
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Beef production can be environmentally detrimental due in large part to associated enteric methane (CH4) production, which contributes to climate change. However, beef production in well-managed grazing systems can aid in soil carbon sequestration (SCS), which is often ignored when assessing beef production impacts on climate change. To estimate the carbon footprint and climate change mitigation potential of upper Midwest grass-finished beef production systems, we conducted a partial life cycle assessment (LCA) comparing two grazing management strategies: 1) a non-irrigated, lightly-stocked (1.0 AU/ha), high-density (100,000 kg LW/ha) system (MOB) and 2) an irrigated, heavily-stocked (2.5 AU/ha), low-density (30,000 kg LW/ha) system (IRG). In each system, April-born steers were weaned in November, winter-backgrounded for 6 months and grazed until their endpoint the following November, with average slaughter age of 19 months and a 295 kg hot carcass weight. As the basis for the LCA, we used two years of data from Lake City Research Center, Lake City, MI. We included greenhouse gas (GHG) emissions associated with enteric CH4, soil N2O and CH4 fluxes, alfalfa and mineral supplementation, and farm energy use. We also generated results from the LCA using the enteric emissions equations of the Intergovernmental Panel on Climate Change (IPCC). We evaluated a range of potential rates of soil carbon (C) loss or gain of up to 3 Mg C ha-1 yr-1. Enteric CH4 had the largest impact on total emissions, but this varied by grazing system. Enteric CH4 composed 62 and 66% of emissions for IRG and MOB, respectively, on a land basis. Both MOB and IRG were net GHG sources when SCS was not considered. Our partial LCA indicated that when SCS potential was included, each grazing strategy could be an overall sink. Sensitivity analyses indicated that soil in the MOB and IRG systems would need to sequester 1 and 2 Mg C ha-1 yr-1 for a net zero GHG footprint, respectively. IPCC model estimates for enteric CH4 were similar to field estimates for the MOB system, but were higher for the IRG system, suggesting that 0.62 Mg C ha-1 yr-1 greater SCS would be needed to offset the animal emissions in this case.
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2016
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2008
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Apesar de os teores de matéria orgânica serem normalmente baixos em solos arenosos, ela é responsável por quase a totalidade da CTC, armazenamento de água e disponibilidade de nutrientes desses solos. A avaliação de sistemas de exploração florestais alternativos, com vistas em incrementar a acumulação de C e N, devem ser incentivados. Este estudo compara plantios puros e mistos de Eucalyptus grandis e Pseudosamanea guachapele, leguminosa fixadora de N2, em relação os estoques de C e N do solo. Os plantios foram realizados em áreas anteriormente manejadas com Panicum maximum num Planossolo, que, por pelo menos dez anos, não recebeu qualquer fertilizante. Para estimar o C e o N estocado, foram retiradas amostras das camadas de 0-2,5; 2,5-5,0; 5,0-7,5; 7,5-10,0; 10,0-20,0 e 20,0-40,0 cm tanto nos plantios puros e mistos, quanto na área de pasto. A técnica da abundância natural do 13C foi utilizada na estimativa do C originado das árvores nos 10 cm superficiais. Os estoques de C e N, no plantio misto atingiu valores de 23,83 e 1,74 Mg ha-1, respectivamente. Nos puros, de guachapele e eucalipto, e no pasto os estoques de C estimados foram de 14,20; 17,19 e 24,24 Mg ha-1, respectivamente. Para os mesmos tratamentos, os estoques de N foram estimados em 0,83; 0,99 e 1,71 Mg ha-1, respectivamente. Mais de 40 % do C do solo sob o plantio misto foram estimados como sendo derivados das árvores, enquanto nos plantios puros de eucalipto e guachapele, a contribuição do C das árvores ficou em 19 e 27 %, respectivamente. Esses resultados evidenciam que a presença da leguminosa no plantio consorciado aumenta os estoques de C e N do solo.
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Land use change from native forests to pastures in the tropics have impact on global carbon (C) cycle through increased rates of C emissions to the atmosphere and the loss of above- and belowground C accumulation and storage capacity (SILVER et al., 2000). This study was conducted to determine the carbon stock in a Ultisol under a pure Brachiaria humidicola (Rendle) Scheick pasture and a mixed pasture of B. humidicola and Arachis pintoi Krapov. & W. C. Greg cv. BRS Mandobi, both without fertilization.
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Potential impacts of plantation forestry practices on soil organic carbon and Fe available to microorganisms were investigated in a subtropical coastal catchment. The impacts of harvesting or replanting were largely limited to the soil top layer (0–10 cm depth). The thirty-year-old Pinus plantation showed low soil moisture content (Wc) and relatively high levels of soil total organic carbon (TOC). Harvesting and replanting increased soil Wc but reduced TOC levels. Mean dissolved organic carbon (DOC) and microbial biomass carbon (MBC) increased in harvested or replanted soils, but such changes were not statistically significant (P > 0.05). Total dithionite-citrate and aqua regia-extractable Fe did not respond to forestry practices, but acid ammonium oxalate and pyrophosphate-extractable, bioavailable Fe decreased markedly after harvesting or replanting. Numbers of heterotrophic bacteria were significantly correlated with DOC levels (P < 0.05), whereas Fe-reducing bacteria and S-bacteria detected using laboratory cultivation techniques did not show strong correlation with either soil DOC or Fe content.
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Extensive data used to quantify broad soil C changes (without information about causation), coupled with intensive data used for attribution of changes to specific management practices, could form the basis of an efficient national grassland soil C monitoring network. Based on variability of extensive (USDA/NRCS pedon database) and intensive field-level soil C data, we evaluated the efficacy of future sample collection to detect changes in soil C in grasslands. Potential soil C changes at a range of spatial scales related to changes in grassland management can be verified (alpha=0.1) after 5 years with collection of 34, 224, 501 samples at the county, state, or national scales, respectively. Farm-level analysis indicates that equivalent numbers of cores and distinct groups of cores (microplots) results in lowest soil C coefficients of variation for a variety of ecosystems. Our results suggest that grassland soil C changes can be precisely quantified using current technology at scales ranging from farms to the entire nation. (C) 2001 Elsevier Science Ltd. All rights reserved.
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Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design
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The effect of liming on the flow of recently photosynthesized carbon to rhizosphere soil was studied using (CO2)-C-13 pulse labelling, in an upland grassland ecosystem in Scotland. The use of C-13 enabled detection, in the field, of the effect of a 4-year liming period of selected soil plots on C allocation from plant biomass to soil, in comparison with unlimed plots. Photosynthetic rates and carbon turnover were higher in plants grown in limed soils than in those from unlimed plots. Higher delta(13)C% values were detected in shoots from limed plants than in those from unlimed plants in samples clipped within 15 days of the end of pulse labelling. Analysis of the aboveground plant production corresponding to the 4-year period of liming indicated that the standing biomass was higher in plots that received lime. Lower delta(13)C% values in limed roots compared with unlimed roots were found, whereas no significant difference was detected between soil samples. Extrapolation of our results indicated that more C has been lost through the soil than has been gained via photosynthetic assimilation because of pasture liming in Scotland during the period 1990-1998. However, the uncertainty associated with such extrapolation based on this single study is high and these estimates are provided only to set our findings in the broader context of national soil carbon emissions.
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The Irish and UK governments, along with other countries, have made a commitment to limit the concentrations of greenhouse gases in the atmosphere by reducing emissions from the burning of fossil fuels. This can be achieved (in part) through increasing the sequestration of CO2 from the atmosphere including monitoring the amount stored in vegetation and soils. A large proportion of soil carbon is held within peat due to the relatively high carbon density of peat and organic-rich soils. This is particularly important for a country such as Ireland, where some 16% of the land surface is covered by peat. For Northern Ireland, it has been estimated that the total amount of carbon stored in vegetation is 4.4Mt compared to 386Mt stored within peat and soils. As a result it has become increasingly important to measure and monitor changes in stores of carbon in soils. The conservation and restoration of peat covered areas, although ongoing for many years, has become increasingly important. This is summed up in current EU policy outlined by the European Commission (2012) which seeks to assess the relative contributions of the different inputs and outputs of organic carbon and organic matter to and from soil. Results are presented from the EU-funded Tellus Border Soil Carbon Project (2011 to 2013) which aimed to improve current estimates of carbon in soil and peat across Northern Ireland and the bordering counties of the Republic of Ireland.
Historical reports and previous surveys provide baseline data. To monitor change in peat depth and soil organic carbon, these historical data are integrated with more recently acquired airborne geophysical (radiometric) data and ground-based geochemical data generated by two surveys, the Tellus Project (2004-2007: covering Northern Ireland) and the EU-funded Tellus Border project (2011-2013) covering the six bordering counties of the Republic of Ireland, Donegal, Sligo, Leitrim, Cavan, Monaghan and Louth. The concept being applied is that saturated organic-rich soil and peat attenuate gamma-radiation from underlying soils and rocks. This research uses the degree of spatial correlation (coregionalization) between peat depth, soil organic carbon (SOC) and the attenuation of the radiometric signal to update a limited sampling regime of ground-based measurements with remotely acquired data. To comply with the compositional nature of the SOC data (perturbations of loss on ignition [LOI] data), a compositional data analysis approach is investigated. Contemporaneous ground-based measurements allow corroboration for the updated mapped outputs. This provides a methodology that can be used to improve estimates of soil carbon with minimal impact to sensitive habitats (like peat bogs), but with maximum output of data and knowledge.