Denitrifying bioreactors are increasingly being used for nitrate removal from agricultural drainage water. Filled with carbon substrates, often woodchips, denitrifying bioreactors provide a favorable anaerobic environment for denitrification. Despite performing well in loess soils in the Midwestern United States, field bioreactors have not yet been evaluated in shallow soils over glacial till that are characteristic for the Northeastern United States. This study, therefore, investigates the performance of bioreactors and provides design criteria for shallow soil with flashy discharges. Paired bioreactors, one filled with woodchips and one with a mixture of woodchip and biochar, were installed in tile drained fields in three landscapes in New York State. The bioreactors were monitored for a three-year period during which, the flow rate, temperature, nitrate (NO-N), sulfate (SO-S) and dissolved organic carbon (DOC) were measured. Results showed that the average NO-N removal efficiency during the three years of observations was about 50%. The NO-N removal rate ranged from 0 in winter to 72 g d m in summer. We found that biochar was only effective during the first year in enhancing denitrification, due to the ageing. An index for carbon availability related to NO-N removal was developed. During winter, availability of the DOC was a limiting factor in bioreactor performance. Finally, to aid in the design of bioreactors, we developed generalizable relationships between the removal efficiency and hydraulic retention time and temperature.

Ash plays an important role in controlling runoff and erosion processes after wildfire and has frequently been hypothesised to clog soil pores and reduce infiltration. Yet evidence for clogging is incomplete, as research has focussed on identifying the presence of ash in soil; the actual flow processes remain unknown. We conducted laboratory infiltration experiments coupled with microscope observations in pure sands, saturated hydraulic conductivity analysis, and interaction energy calculations, to test whether ash can clog pores (i.e. block pores such that infiltration is hampered and ponding occurs). Although results confirmed previous observations of ash washing into pores, clogging was not observed in the pure sands tested, nor were conditions found for which this does occur. Clogging by means of strong attachment of ash to sand was deemed unlikely given the negative surface charge of the two materials. Ponding due to washing in of ash was also considered improbable given the high saturated conductivity of pure ash and ash–sand mixtures. This first mechanistic step towards analysing ash transport and attachment processes in field soils therefore suggests that pore clogging by ash is unlikely to occur in sands. Discussion is provided on other mechanisms by which ash can affect post-fire hydrology.

Soil microbial metabolism is critical to carbon cycling, but direct annotation of metabolic activities is challenging. Here, we present an exometabolomics approach coupled with 13C profiling for in situ probing of metabolic activities following a 13C-glucose pulse in oxic or anoxic soil incubations. In the soil water extracts, we monitored both abundance and isotopic enrichment of short-chain carboxylic acids (SCCAs) involved in different metabolic pathways: peripheral sugar oxidation, glycolysis, fermentation, and the tricarboxylic acid cycle. The water-extractable SCCAs captured redox-dependent metabolic dynamics. First, under both redox conditions, increased concentration (up to 50 μM) along with near-complete 13C-labeled fractions for both gluconate and 2-ketogluconate revealed activation of the peripheral sugar oxidation pathway. Second, greater citrate depletion during the oxic condition than during the anoxic condition (6.2 versus 2.3 μM) was consistent with an expected decrease in carbon usage in the anoxic incubations. Third, accumulation of 13C-labeled succinate and malate only in the anoxic incubations demonstrated metabolic overflow typical of anaerobic metabolism. Fourth, production of 13C-labeled lactate under the anoxic conditions highlighted glucose fermentation but, under the oxic conditions, lactate depletion implied its role as a carbon source. Such 13C-assisted exometabolomics data offer insights to interpret gene-based predictions of metabolic potentials.

The computer simulation hydrologic model, DRAINMOD and modified DRAINMOD (Luo et al., 2000) for cold condition, was used to predict the performance of surface drainage and yield of canola as post-rice cultivation during the wet growing season of [2004][2005] in Rasht, Iran.Performance of surface drainage system treatments with 2 m spacing and 15 cm drain depth as compared with plots having no drainage (4 Â 10 m 2 ), were used to evaluate the models. Evaluation of predicted daily groundwater table depths as compared with measured values shows that the root mean square error (RMSE) was about 10.2 and 9.9 cm for DRAINMOD versus 11.0 and 11.5 for modified DRAINMOD in 2 m drain spacing and no drainage treatment respectively. Original DRAINMOD and modified DRAINMOD predictions for groundwater table depth was on average about 4 and 7% less than measured values for the surface drainage treatment and 22 and 14% greater for the no drainage treatment, whereas the standard error of original DRAINMOD was 1.4 and 1.51 (cm), respectively. The average absolute deviations were 8.67 and 9.22 (cm). However, by using the modified DRAINMOD these values were decreased to 1.34, 1.

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While genome sequencing has expanded our knowledge of symbiosis, role assignment within multi-species microbiomes remains challenging due to genomic redundancy and the uncertainties of in vivo impacts. We address such questions, here, for a specialized nitrogen (N) recycling microbiome of turtle ants, describing a new genus and species of gut symbiont—Ischyrobacter davidsoniae (Betaproteobacteria: Burkholderiales: Alcaligenaceae)—and its in vivo physiological context. A re-analysis of amplicon sequencing data, with precisely assigned Ischyrobacter reads, revealed a seemingly ubiquitous distribution across the turtle ant genus Cephalotes, suggesting ≥50 million years since domestication. Through new genome sequencing, we also show that divergent I. davidsoniae lineages are conserved in their uricolytic and urea-generating capacities. With phylogenetically refined definitions of Ischyrobacter and separately domesticated Burkholderiales symbionts, our FISH microscopy revealed a distinct niche for I. davidsoniae, with dense populations at the anterior ileum. Being positioned at the site of host N-waste delivery, in vivo metatranscriptomics and metabolomics further implicate I. davidsoniae within a symbiont-autonomous N-recycling pathway. While encoding much of this pathway, I. davidsoniae expressed only a subset of the requisite steps in mature adult workers, including the penultimate step deriving urea from allantoate. The remaining steps were expressed by other specialized gut symbionts. Collectively, this assemblage converts inosine, made from midgut symbionts, into urea and ammonia in the hindgut. With urea supporting host amino acid budgets and cuticle synthesis, and with the ancient nature of other active N-recyclers discovered here, I. davidsoniae emerges as a central player in a conserved and impactful, multipartite symbiosis.

A hydrological simulation model, DRAINMOD, was used to predict the performance of surface drainage and yield of canola as post-rice cultivation during wet growing season of 2004-2005 in Rasht-Iran. The DRAINMOD model was evaluated on performance of surface drainage with 2 m spacings and 15 cm drain depth as compared with 4×10 m 2 plots having no drainage. The results showed that DRAINMOD model was well able to predict water table fluctuations. Evaluation of predicted daily water table depths as compared with measured values shows that the root mean square error (RMSE) was about 8 cm for both treatments. Predicted water table depth was, on average about 4% less than the measured water table depths for the surface drainage treatment and 17% less for the no drainage treatment. Accurate measurement of deep seepage is required to improve performance of the model. Results also showed DRAINMOD was capable of predicting relative yield of canola for both treatments. Poor aeration as a result of excess soil moisture could be related as the main reason for yield reduction.

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