17 resultados para Detrital organic matter


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Understanding the response of humid mid-latitude forests to changes in precipitation, temperature, nutrient cycling, and disturbance is critical to improving our predictive understanding of changes in the surface-subsurface energy balance due to climate change. Mechanistic understanding of the effects of long-term and transient moisture conditions are needed to quantify
linkages between changing redox conditions, microbial activity, and soil mineral and nutrient interactions on C cycling and greenhouse gas releases. To illuminate relationships between the soil chemistry, microbial communities and organic C we established transects across hydraulic and topographic gradients in a small watershed with transient moisture conditions. Valley bottoms tend to be more frequently saturated than ridge tops and side slopes which generally are only saturated when shallow storm flow zones are active. Fifty shallow (~36”) soil cores were collected during timeframes representative of low CO2, soil winter conditions and high CO2, soil summer conditions. Cores were subdivided into 240 samples based on pedology and analyses of the geochemical (moisture content, metals, pH, Fe species, N, C, CEC, AEC) and microbial (16S rRNA gene
amplification with Illumina MiSeq sequencing) characteristics were conducted and correlated to watershed terrain and hydrology. To associate microbial metabolic activity with greenhouse gas emissions we installed 17 soil gas probes, collected gas samples for 16 months and analyzed them for CO2 and other fixed and greenhouse gasses. Parallel to the experimental efforts our data is being used to support hydrobiogeochemical process modeling by coupling the Community Land Model (CLM) with a subsurface process model (PFLOTRAN) to simulate processes and interactions from the molecular to watershed scales. Including above ground processes (biogeophysics, hydrology, and vegetation dynamics), CLM provides mechanistic water, energy, and organic matter inputs to the surface/subsurface models, in which coupled biogeochemical reaction
networks are used to improve the representation of below-ground processes. Preliminary results suggest that inclusion of above ground processes from CLM greatly improves the prediction of moisture response and water cycle at the watershed scale.

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Organic soils are widespread in Ireland and vulnerable to degradation via drainage for agriculture. The soil-landuse combination of pasture on organic soils may play a disproportionate role in regional C dynamics but is yet to receive study. Fluvial C fluxes and labile organic fractions were determined for two such sites at nested field (c.4 ha) and subcatchment scales (>40 ha); one relatively dry and nutrient rich, the other wetter and nutrient poor. Field scale flux from the nutrient poor site over 2 years was 38.9 ± 6.6 g C m−2 yr−1 with DIC > DOC > POC at 57, 32 and 11 % respectively, and 72 % DIC was comprised of above equilibrium CO2. At the nutrient rich site, which overlies limestone geology, field scale export over an individual year was 90.4 g C m−2 with DIC > DOC > POC at 49, 42 and 9 %, but with 90 % DIC as bicarbonate. By comparison with the nutrient poor site, the magnitude and composition of inorganic C exports from the nutrient rich site implied considerable export of soil-respiratory C as bicarbonate, and lower evasion losses due to carbonate system buffering. Labile DOC determined using dark incubations indicated small fractions (5–10 %) available for remineralisation over typical downstream transit times of days to weeks. These fractions are probably conservative as photolysis in the environment can increase the proportion of labile compounds via photocleavage and directly remineralise organic matter. This study demonstrates that monitoring at soil–water interfaces can aid capture of total landscape fluvial fluxes by precluding the need to incorporate prior C evasion, although rapid runoff responses at field scales can necessitate high resolution flow proportional, and hydrograph sampling to constrain uncertainty of flux estimates.