991 resultados para Accumulation rate, marine organic carbon
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Composition and concentration of colored dissolved organic matter (CDOM) have been determined in Hudson Bay and Hudson Strait by excitation emission matrix spectroscopy (EEM) and parallel factor analysis (PARAFAC). Based on 63 surface samples, PARAFAC identified three fluorescent components, which were attributed to two humic- and one protein-like components. One humic-like component was identified as representing terrestrial organic matter and showed a conservative behaviour in Hudson Bay estuaries. The second humic-like component, traditionally identified as peak M, originated both from land and produced in the marine environment. Component 3 had spectra resembling protein-like material and thought to be plankton-derived. The distribution and composition of CDOM were largely controlled by water mass mixing with protein-like component being the least affected. Distinctive fluorescence patterns were also found between Hudson Bay and Hudson Strait, suggesting different sources of CDOM. The optically active fraction of DOC (both absorbing and fluorescing) was very high in the Hudson Bay (up to 89%) suggesting that fluorescence and absorbance can be used as proxies of the DOC concentration.
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Background: Anthropogenic disturbance of old-growth tropical forests increases the abundance of early successional tree species at the cost of late successional ones. Quantifying differences in terms of carbon allocation and the proportion of recently fixed carbon in soil CO2 efflux is crucial for addressing the carbon footprint of creeping degradation. Methodology: We compared the carbon allocation pattern of the late successional gymnosperm Podocarpus falcatus (Thunb.) Mirb. and the early successional (gap filling) angiosperm Croton macrostachyus Hochst. es Del. in an Ethiopian Afromontane forest by whole tree (CO2)-C-13 pulse labeling. Over a one-year period we monitored the temporal resolution of the label in the foliage, the phloem sap, the arbuscular mycorrhiza, and in soil-derived CO2. Further, we quantified the overall losses of assimilated C-13 with soil CO2 efflux. Principal Findings: C-13 in leaves of C. macrostachyus declined more rapidly with a larger size of a fast pool (64% vs. 50% of the assimilated carbon), having a shorter mean residence time (14 h vs. 55 h) as in leaves of P. falcatus. Phloem sap velocity was about 4 times higher for C. macrostachyus. Likewise, the label appeared earlier in the arbuscular mycorrhiza of C. macrostachyus and in the soil CO2 efflux as in case of P. falcatus (24 h vs. 72 h). Within one year soil CO2 efflux amounted to a loss of 32% of assimilated carbon for the gap filling tree and to 15% for the late successional one. Conclusions: Our results showed clear differences in carbon allocation patterns between tree species, although we caution that this experiment was unreplicated. A shift in tree species composition of tropical montane forests (e. g., by degradation) accelerates carbon allocation belowground and increases respiratory carbon losses by the autotrophic community. If ongoing disturbance keeps early successional species in dominance, the larger allocation to fast cycling compartments may deplete soil organic carbon in the long run.
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ABSTRACT: The study of labile carbon fractions (LCF) provides an understanding of the behavior of soil organic matter (SOM) under different soil management systems and cover crops. The aim of this study was to assess the effect of different soil management systems with respect to tillage, cover crop and phosphate fertilization on the amount of the LCF of SOM. Treatments consisted of conventional tillage (CT) and no-tillage (NT) with millet as the cover crop and a no-tillage system with velvet bean at two phosphorus dosages. Soil samples were collected and analyzed for organic carbon (OC), C oxidizable by KMnO4 (C-KMnO4), particulate OC (POC), microbial biomass carbon and light SOM in the 0.0-0.05, 0.05-0.10 and 0.10-0.20 m soil layers. The Carbon Management Index (CMI) was calculated to evaluate the impacts of soil management treatments on the quality of the SOM. The different LCFs are sensitive to different soil management systems, and there are significant correlations between them. C-KMnO4 is considered the best indicator of OC carbon lability. In the soil surface layers, the CT reduced the carbon content in all of the labile fractions of the SOM. The use of phosphorus led to the accumulation of OC and carbon in the different soil fractions regardless of the tillage system or cover crop. The application of phosphate fertilizer improved the ability of the NTsystem to promote soil quality, as assessed by the CMI.
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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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Agricultural management affects soil organic matter, which is important for sustainable crop production and as a greenhouse gas sink. Our objective was to determine how tillage, residue management and N fertilization affect organic C in unprotected, and physically, chemically and biochemically protected soil C pools. Samples from Breton, Alberta were fractionated and analysed for organic C content. As in previous report, N fertilization had a positive effect, tillage had a minimal effect, and straw management had no effect on whole-soil organic C. Tillage and straw management did not alter organic C concentrations in the isolated C pools, while N fertilization increased C concentrations in all pools. Compared with a woodlot soil, the cultivated plots had lower total organic C, and the C was redistributed among isolated pools. The free light fraction and coarse particulate organic matter responded positively to C inputs, suggesting that much of the accumulated organic C occurred in an unprotected pool. The easily dispersed silt-sized fraction was the mineral-associated pool most responsive to changes in C inputs, whereas the microaggregate-derived silt-sized fraction best preserved C upon cultivation. These findings suggest that the silt-sized fraction is important for the long-term stabilization of organic matter through both physical occlusion in microaggregates and chemical protection by mineral association.
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The literature was reviewed and analyzed to determine the feasibility of using a combination of acid hydrolysis and CO2-C release during long-term incubation to determine soil organic carbon (SOC) pool sizes and mean residence times (MRTs). Analysis of 1100 data points showed the SOC remaining after hydrolysis with 6 M HCI ranged from 30 to 80% of the total SOC depending on soil type, depth, texture, and management. Nonhydrolyzable carbon (NHC) in conventional till soils represented 48% of SOC; no-till averaged 56%, forest 55%, and grassland 56%. Carbon dates showed an average of 1200 yr greater MRT for the NHC fraction than total SOC. Longterm incubation, involving measurement of CO2 evolution and curve fitting, measured active and slow pools. Active-pool C comprised 2 to 8% of the SOC with MRTs of days to months; the slow pool comprised 45 to 65% of the SOC and had MRTs of 10 to 80 yr. Comparison of field C-14 and (13) C data with hydrolysis-incubation data showed a high correlation between independent techniques across soil types and experiments. There were large differences in MRTs depending on the length of the experiment. Insertion of hydrolysis-incubation derived estimates of active (C-a), slow (C-s), and resistant Pools (C-r) into the DAYCENT model provided estimates of daily field CO2 evolution rates. These were well correlated with field CO2 measurements. Although not without some interpretation problems, acid hydrolysis-laboratory incubation is useful for determining SOC pools and fluxes especially when used in combination with associated measurements.
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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