997 resultados para Soil layer
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Report of Conservation Program Summary produced by Iowa Departmment of Agriculture and Land Stewardship
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Report produced by Iowa Departmment of Agriculture and Land Stewardship
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Report produced by Iowa Departmment of Agriculture and Land Stewardship
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In recent research, both soil (root-zone) and air temperature have been used as predictors for the treeline position worldwide. In this study, we intended to (a) test the proposed temperature limitation at the treeline, and (b) investigate effects of season length for both heat sum and mean temperature variables in the Swiss Alps. As soil temperature data are available for a limited number of sites only, we developed an air-to-soil transfer model (ASTRAMO). The air-to-soil transfer model predicts daily mean root-zone temperatures (10cm below the surface) at the treeline exclusively from daily mean air temperatures. The model using calibrated air and root-zone temperature measurements at nine treeline sites in the Swiss Alps incorporates time lags to account for the damping effect between air and soil temperatures as well as the temporal autocorrelations typical for such chronological data sets. Based on the measured and modeled root-zone temperatures we analyzed. the suitability of the thermal treeline indicators seasonal mean and degree-days to describe the Alpine treeline position. The root-zone indicators were then compared to the respective indicators based on measured air temperatures, with all indicators calculated for two different indicator period lengths. For both temperature types (root-zone and air) and both indicator periods, seasonal mean temperature was the indicator with the lowest variation across all treeline sites. The resulting indicator values were 7.0 degrees C +/- 0.4 SD (short indicator period), respectively 7.1 degrees C +/- 0.5 SD (long indicator period) for root-zone temperature, and 8.0 degrees C +/- 0.6 SD (short indicator period), respectively 8.8 degrees C +/- 0.8 SD (long indicator period) for air temperature. Generally, a higher variation was found for all air based treeline indicators when compared to the root-zone temperature indicators. Despite this, we showed that treeline indicators calculated from both air and root-zone temperatures can be used to describe the Alpine treeline position.
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Oxalate catabolism, which can have both medical and environmental implications, is performed by phylogenetically diverse bacteria. The formyl-CoA-transferase gene was chosen as a molecular marker of the oxalotrophic function. Degenerated primers were deduced from an alignment of frc gene sequences available in databases. The specificity of primers was tested on a variety of frc-containing and frc-lacking bacteria. The frc-primers were then used to develop PCR-DGGE and real-time SybrGreen PCR assays in soils containing various amounts of oxalate. Some PCR products from pure cultures and from soil samples were cloned and sequenced. Data were used to generate a phylogenetic tree showing that environmental PCR products belonged to the target physiological group. The extent of diversity visualised on DGGE pattern was higher for soil samples containing carbonate resulting from oxalate catabolism. Moreover, the amount of frc gene copies in the investigated soils was detected in the range of 1.64x10(7) to 1.75x10(8)/g of dry soil under oxalogenic tree (representing 0.5 to 1.2% of total 16S rRNA gene copies), whereas the number of frc gene copies in the reference soil was 6.4x10(6) (or 0.2% of 16S rRNA gene copies). This indicates that oxalotrophic bacteria are numerous and widespread in soils and that a relationship exists between the presence of the oxalogenic trees Milicia excelsa and Afzelia africana and the relative abundance of oxalotrophic guilds in the total bacterial communities. This is obviously related to the accomplishment of the oxalate-carbonate pathway, which explains the alkalinization and calcium carbonate accumulation occurring below these trees in an otherwise acidic soil. The molecular tools developed in this study will allow in-depth understanding of the functional implication of these bacteria on carbonate accumulation as a way of atmospheric CO(2) sequestration.
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This article originates from a panel with the above title, held at IEEE VTC Spring 2009, in which the authors took part. The enthusiastic response it received prompted us to discuss for a wider audience whether research at the physical layer (PHY) is still relevant to the field of wireless communications. Using cellular systems as the axis of our exposition, we exemplify areas where PHY research has indeed hit a performance wall and where any improvements are expected to be marginal. We then discuss whether the research directions taken in the past have always been the right choice and how lessons learned could influence future policy decisions. Several of the raised issues are subsequently discussed in greater details, e.g., the growing divergence between academia and industry. With this argumentation at hand, we identify areas that are either under-developed or likely to be of impact in coming years - hence corroborating the relevance and importance of PHY research.
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Supported by IEEE 802.15.4 standardization activities, embedded networks have been gaining popularity in recent years. The focus of this paper is to quantify the behavior of key networking metrics of IEEE 802.15.4 beacon-enabled nodes under typical operating conditions, with the inclusion of packet retransmissions. We corrected and extended previous analyses by scrutinizing the assumptions on which the prevalent Markovian modeling is generally based. By means of a comparative study, we singled out which of the assumptions impact each of the performance metrics (throughput, delay, power consumption, collision probability, and packet-discard probability). In particular, we showed that - unlike what is usually assumed - the probability that a node senses the channel busy is not constant for all the stages of the backoff procedure and that these differences have a noticeable impact on backoff delay, packet-discard probability, and power consumption. Similarly, we showed that - again contrary to common assumption - the probability of obtaining transmission access to the channel depends on the number of nodes that is simultaneously sensing it. We evidenced that ignoring this dependence has a significant impact on the calculated values of throughput and collision probability. Circumventing these and other assumptions, we rigorously characterize, through a semianalytical approach, the key metrics in a beacon-enabled IEEE 802.15.4 system with retransmissions.
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Tillage systems play a significant role in agricultural production throughout Iowa and the Midwest. It has been well documented that increased tillage intensities can reduce soil organic matter in the topsoil due to increased microbial activity and carbon (C ) oxidation. The potential loss of soil organic matter due to tillage operations is much higher for high organic matter soils than low organic matter soils. Tillage effects on soil organic matter can be magnified through soil erosion and loss of soil productivity. Soil organic matter is a natural reservoir for nutrients, buffers against soil erosion, and improves the soil environment to sustain soil productivity. Maintaining soil productivity requires an agriculture management system that maintains or improves soil organic matter content. Combining cropping systems and conservation tillage practices, such as no-tillage, strip-tillage, or ridge-tillage, are proven to be very effective in improving soil organic matter and soil quality.
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This paper describes a maximum likelihood method using historical weather data to estimate a parametric model of daily precipitation and maximum and minimum air temperatures. Parameter estimates are reported for Brookings, SD, and Boone, IA, to illustrate the procedure. The use of this parametric model to generate stochastic time series of daily weather is then summarized. A soil temperature model is described that determines daily average, maximum, and minimum soil temperatures based on air temperatures and precipitation, following a lagged process due to soil heat storage and other factors.
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Zeta potential is a physico-chemical parameter of particular importance to describe sorption of contaminants at the surface of gas bubbles. Nevertheless, the interpretation of electrophoretic mobilities of gas bubbles is complex. This is due to the specific behavior of the gas at interface and to the excess of electrical charge at interface, which is responsible for surface conductivity. We developed a surface complexation model based on the presence of negative surface sites because the balance of accepting and donating hydrogen bonds is broken at interface. By considering protons adsorbed on these sites followed by a diffuse layer, the electrical potential at the head-end of the diffuse layer is computed and considered to be equal to the zeta potential. The predicted zeta potential values are in very good agreement with the experimental data of H-2 bubbles for a broad range of pH and NaCl concentrations. This implies that the shear plane is located at the head-end of the diffuse layer, contradicting the assumption of the presence of a stagnant diffuse layer at the gas/water interface. Our model also successfully predicts the surface tension of air bubbles in a KCl solution. (c) 2012 Elsevier Inc. All rights reserved.
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Report of Conservation Program Summary produced by Iowa Departmment of Agriculture and Land Stewardship
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Rifampin-resistant Pseudomonas fluorescens CHA0-Rif and mutants in which the regulatory gene algU (encoding sigma factor sigma(E)) or gacA (encoding a global regulator of secondary metabolism) was inactivated were compared for persistence in three nonsterile soils. Functional algU and (particularly) gacA were needed for CHA0-Rif to maintain cell culturability in soil.
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The general soil map, which is a color map, shows the survey area divided into groups of associated soils called general soil map units. This map is useful in planning the use and management of large areas. To find information about your area of interest, locate that area on the map, identify the name of the map unit in the area on the color-coded map legend, then refer to the section General Soil Map Units for a general description of the soils in your area.