Sulfur and strontium isotope composition of the Llobregat River (NE Spain): Tracers of natural and anthropogenic chemicals in stream waters

The use of sulfur and strontium isotopes as tracers for the source/s of water contaminants have been applied to the water of the Llobregat River system (NE Spain). Surface water samples from June 1997 were collected from the Llobregat River and its main tributaries and creeks. The chemistry of most stream waters are controlled mainly by the weathering of Tertiary chemical sediments within the drainage basin. The largest variation in delta(34)S values were found in the small creeks with values ranging from -9.9 to 15parts per thousand, whilst in the main river channels values ranged from 6.3 to 12.4parts per thousand. The Sr-87/Sr-86 ratio for dissolved strontium ranged from 0.70795 for a non-polluted site to 0.70882 for a polluted one. Most of the waters with high NO3 and low Ca/Na ratio converge to the same Sr-87/Sr-86 value, pointing to dominant pollutant end member contribution or a mixing of pollutants with an isotopic composition around 0.7083-0.7085. Although the concentration of the natural inputs in the river for sulfate and strontium are high, as a result of the sulfate outcrops within the geology of the basin, their isotopic characteristics suggest that they can be used as a discriminating device in water pollution problems. However to establish the detailed characteristics of the isotopes as geochemical tools, specific high-resolution case studies are necessary in small areas, where the inputs are well known.

Examining the information content of time-lapse crosshole GPR data collected under different infiltration conditions to estimate unsaturated soil hydraulic properties

Time-lapse geophysical data acquired during transient hydrological experiments are being increasingly employed to estimate subsurface hydraulic properties at the field scale. In particular, crosshole ground-penetrating radar (GPR) data, collected while water infiltrates into the subsurface either by natural or artificial means, have been demonstrated in a number of studies to contain valuable information concerning the hydraulic properties of the unsaturated zone. Previous work in this domain has considered a variety of infiltration conditions and different amounts of time-lapse GPR data in the estimation procedure. However, the particular benefits and drawbacks of these different strategies as well as the impact of a variety of key and common assumptions remain unclear. Using a Bayesian Markov-chain-Monte-Carlo stochastic inversion methodology, we examine in this paper the information content of time-lapse zero-offset-profile (ZOP) GPR traveltime data, collected under three different infiltration conditions, for the estimation of van Genuchten-Mualem (VGM) parameters in a layered subsurface medium. Specifically, we systematically analyze synthetic and field GPR data acquired under natural loading and two rates of forced infiltration, and we consider the value of incorporating different amounts of time-lapse measurements into the estimation procedure. Our results confirm that, for all infiltration scenarios considered, the ZOP GPR traveltime data contain important information about subsurface hydraulic properties as a function of depth, with forced infiltration offering the greatest potential for VGM parameter refinement because of the higher stressing of the hydrological system. Considering greater amounts of time-lapse data in the inversion procedure is also found to help refine VGM parameter estimates. Quite importantly, however, inconsistencies observed in the field results point to the strong possibility that posterior uncertainties are being influenced by model structural errors, which in turn underlines the fundamental importance of a systematic analysis of such errors in future related studies.

Statistical Analysis of Eco-Toxicologic Data of Mammals from a Polluted Area

Several eco-toxicological studies have shown that insectivorous mammals, due to theirfeeding habits, easily accumulate high amounts of pollutants in relation to other mammal species. To assess the bio-accumulation levels of toxic metals and their in°uenceon essential metals, we quantified the concentration of 19 elements (Ca, K, Fe, B, P,S, Na, Al, Zn, Ba, Rb, Sr, Cu, Mn, Hg, Cd, Mo, Cr and Pb) in bones of 105 greaterwhite-toothed shrews (Crocidura russula) from a polluted (Ebro Delta) and a control(Medas Islands) area. Since chemical contents of a bio-indicator are mainly compositional data, conventional statistical analyses currently used in eco-toxicology can givemisleading results. Therefore, to improve the interpretation of the data obtained, weused statistical techniques for compositional data analysis to define groups of metalsand to evaluate the relationships between them, from an inter-population viewpoint.Hypothesis testing on the adequate balance-coordinates allow us to confirm intuitionbased hypothesis and some previous results. The main statistical goal was to test equalmeans of balance-coordinates for the two defined populations. After checking normality,one-way ANOVA or Mann-Whitney tests were carried out for the inter-group balances

A search for the origin of cadmium in the soil of the Swiss Jura

The top soil of a 14.5 km(2) region at la Chaux-de-Fonds in the Swiss Jura is exceptionally rich in cadmium. It contains an average of 1.3 mg per kg of soil. The spatial distribution of the metal has no simple pattern that could be explained by atmospheric deposition or agricultural practices. Thin soil contained most of its Cd at the surface; in thicker soil Cd is mainly concentrated between 60 and 80 cm depth. No specific minerals or soil fractions could account for these accumulation, and the vertical distribution of Cd is best explained by leaching from the topsoil and further adsorption within layers of nearly neutral pH. The local Jurassic sedimentary rocks contained too little Cd to account for the Cd concentrations in the soil. Alpine gravels from glacial till were too sparse in soils to explain such a spreading of Cd. Moreover this origin is contradictory with the fact that Cd is concentrated in the sand fraction of soils. The respective distributions of Fe and Cd in soils, and soil fractions, suggested that the spreading of iron nodules accumulated during the siderolithic period (Eocene) was not the main source of Cd. Atmospheric deposition, and spreading of fertiliser or waste from septic tanks seem the only plausible explanation for the Cd concentrations, but at present few factors allow us to differentiate between them.

Ecology and evolution of soil nematode chemotaxis.

Plants influence the behavior of and modify community composition of soil-dwelling organisms through the exudation of organic molecules. Given the chemical complexity of the soil matrix, soil-dwelling organisms have evolved the ability to detect and respond to these cues for successful foraging. A key question is how specific these responses are and how they may evolve. Here, we review and discuss the ecology and evolution of chemotaxis of soil nematodes. Soil nematodes are a group of diverse functional and taxonomic types, which may reveal a variety of responses. We predicted that nematodes of different feeding guilds use host-specific cues for chemotaxis. However, the examination of a comprehensive nematode phylogeny revealed that distantly related nematodes, and nematodes from different feeding guilds, can exploit the same signals for positive orientation. Carbon dioxide (CO(2)), which is ubiquitous in soil and indicates biological activity, is widely used as such a cue. The use of the same signals by a variety of species and species groups suggests that parts of the chemo-sensory machinery have remained highly conserved during the radiation of nematodes. However, besides CO(2), many other chemical compounds, belonging to different chemical classes, have been shown to induce chemotaxis in nematodes. Plants surrounded by a complex nematode community, including beneficial entomopathogenic nematodes, plant-parasitic nematodes, as well as microbial feeders, are thus under diffuse selection for producing specific molecules in the rhizosphere that maximize their fitness. However, it is largely unknown how selection may operate and how belowground signaling may evolve. Given the paucity of data for certain groups of nematodes, future work is needed to better understand the evolutionary mechanisms of communication between plant roots and soil biota.

Diversity of the bacterial community in the surface soil of a pear orchard based on 16S rRNA gene analysis

A cultivation-independent approach based on polymerase chain reaction (PCR)-amplified partial small subunit rRNA genes was used to characterize bacterial populations in the surface soil of a commercial pear orchard consisting of different pear cultivars during two consecutive growing seasons. Pyrus communis L. cvs Blanquilla, Conference, and Williams are among the most widely cultivated cultivars in Europe and account for the majority of pear production in Northeastern Spain. To assess the heterogeneity of the community structure in response to environmental variables and tree phenology, bacterial populations were examined using PCR-denaturing gradient gel electrophoresis (DGGE) followed by cluster analysis of the 16S ribosomal DNA profiles by means of the unweighted pair group method with arithmetic means. Similarity analysis of the band patterns failed to identify characteristic fingerprints associated with the pear cultivars. Both environmentally and biologically based principal-component analyses showed that the microbial communities changed significantly throughout the year depending on temperature and, to a lesser extent, on tree phenology and rainfall. Prominent DGGE bands were excised and sequenced to gain insight into the identities of the predominant bacterial populations. Most DGGE band sequences were related to bacterial phyla, such as Bacteroidetes, Cyanobacteria, Acidobacteria, Proteobacteria, Nitrospirae, and Gemmatimonadetes, previously associated with typical agronomic crop environments

Soil Nitrogen and Carbon Management Project, 2002

Report produced by Iowa Departmment of Agriculture and Land Stewardship

Soil and Water Conservation; Conservation Program Summary, 2003

Report of Conservation Program Summary produced by Iowa Departmment of Agriculture and Land Stewardship

Strip Tillage Effects on Crop Production and Soil Erosion, 2002

Report produced by Iowa Departmment of Agriculture and Land Stewardship

Iowa Soil Properties and Interpretation Database, 2002

Report produced by Iowa Departmment of Agriculture and Land Stewardship

Evaluating thermal treeline indicators based on air and soil temperature using an air-to-soil temperature transfer model

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.

Use of the frc gene as a molecular marker to characterize oxalate-oxidizing bacterial abundance and diversity structure in soil.

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.

Tillage Management and Soil Organic Matter, 2005

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.

Generation of Simulated Daily Precipitation and Air and Soil Temperatures, January 2000

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.