Effects of waterlogging on the solubility and redox state of Sb in a shooting range soil and its uptake by grasses: a tank experiment

Aims

The effects of waterlogging on redox state and solubility of antimony (Sb) in a calcareous shooting range soil and its uptake by forage grass Lolium perenne L. and pasture weed Holcus lanatus L. were investigated.

Methods

Grasses were grown on semi-waterlogged or waterlogged shooting range soil in a laboratory tank. The soil solution was sampled at various depths over time and analyzed for the concentrations of Sb(III), Sb(V) and total Sb, as well as other trace elements.

Results

Although the reduction of Sb(V) to Sb(III) under increased waterlogging time decreased Sb solubility, it increased Sb uptake by L. perenne from 1.1 to 1.7 mg?kg^?1 (and to a lesser extent H. lanatus), implying preferential uptake of Sb(III) by this grass. The tank showed considerable variation in redox conditions with depth and plant treatment. The soil root zone (30 cm for L. perenne and 15 cm for H. lanatus) instead of the water saturated bottom, showed the highest manganese (Mn) and iron (Fe) concentrations in solution, accompanied by a higher proportion of Sb(III) in solution than the bottom zone of the tank.

Conclusions

Waterlogging can increase the risk of Sb entering the food chain from shooting range soil.     

The use of DGT for prediction of plant available copper, zinc and phosphorus in agricultural soils

Soil chemical extractions are widely used to predict the nutritional status of soils. However, the correlation between extracted elements and plant uptake is often poor, especially if compared over a range of soil types. The aim of this study was to examine a new method called Diffusive Gradients in Thin films (DGT), which measures the diffusive supply of elements, thereby mimicking a plant root. The ability of DGT to assess plant-available P, Zn and Cu was tested in a wide range of typical Scandinavian agricultural soils along with conventional methods (EDTA and DTPA for Cu and Zn; NaHCO₃ for P and soil solution concentrations). Extracted soil concentrations were compared to that of the element in the youngest fully developed leaf of barley (Hordeum vulgare L.) grown in pots. For Zn and P, only DGT could predict plant uptake while conventional extraction methods and soil solution analyses performed poorly. All soil tests could predict Cu concentration in leaves, but the DGT technique proved to be most accurate followed by the soil solution concentration of Cu. We conclude that DGT is much more accurate at predicting plant-available P, Zn and Cu than commonly used methods for analysing plant-available nutrients in soil.     

Treelength optimization for phylogeny estimation

The standard approach to phylogeny estimation uses two phases, in which the first phase produces an alignment on a set of homologous sequences, and the second phase estimates a tree on the multiple sequence alignment. POY, a method which seeks a tree/alignment pair minimizing the total treelength, is the most widely used alternative to this two-phase approach. The topological accuracy of trees computed under treelength optimization is, however, controversial. In particular, one study showed that treelength optimization using simple gap penalties produced poor trees and alignments, and suggested the possibility that if POY were used with an affine gap penalty, it might be able to be competitive with the best two-phase methods. In this paper we report on a study addressing this possibility. We present a new heuristic for treelength, called BeeTLe (Better Treelength), that is guaranteed to produce trees at least as short as POY. We then use this heuristic to analyze a large number of simulated and biological datasets, and compare the resultant trees and alignments to those produced using POY and also maximum likelihood (ML) and maximum parsimony (MP) trees computed on a number of alignments. In general, we find that trees produced by BeeTLe are shorter and more topologically accurate than POY trees, but that neither POY nor BeeTLe produces trees as topologically accurate as ML trees produced on standard alignments. These findings, taken as a whole, suggest that treelength optimization is not as good an approach to phylogenetic tree estimation as maximum likelihood based upon good alignment methods.     

Short quartet puzzling: a new quartet-based phylogeny reconstruction algorithm.

Quartet-based phylogeny reconstruction methods, such as Quartet Puzzling, were introduced in the hope that they might be competitive with maximum likelihood methods, without being as computationally intensive. However, despite the numerous quartet-based methods that have been developed, their performance in simulation has been disappointing. In particular, Ranwez and Gascuel, the developers of one of the best quartet methods, conjecture that quartet-based methods have inherent limitations that make them unable to produce trees as accurate as neighbor joining or maximum parsimony. In this paper, we present Short Quartet Puzzling, a new quartet-based phylogeny reconstruction algorithm, and we demonstrate the improved topological accuracy of the new method over maximum parsimony and neighbor joining, disproving the conjecture of Ranwez and Gascuel. We also show a dramatic improvement over Quartet Puzzling. Thus, while our new method is not compared to any ML method (as it is not expected to be as accurate as the best of these), this study shows that quartet methods are not as limited in performance as was previously conjectured, and opens the possibility to further improvements through new algorithmic designs.     

SEASONAL PATTERNS IN THE BELOWGROUND BIOMASS OF SPARTINA ALTERNIFLORA (GRAMINEAE) ACROSS A TIDAL GRADIENT

Belowground biomass of two ht forms of the salt marsh cordgrass, Spartina alterniflora, in a New England salt marsh exhibited a seasonal cycle. Biomass was highest in midsummer with no secondary peak in biomass corresponding with the autumn dieback of aboveground parts. Total annual biomass production and the maximum depth that living tissue penetrated into the substrate decreased with increasing tidal ht. Substrate characteristics (soil aeration, pH, nutrient levels) known to affect aboveground biomass of S. alterniflora also decreased with increasing tidal ht and may similarly affect belowground biomass across the same tidal gradient.     

Challenges and frustrations in the separation and analysis of chiral agrochemicals

The development of chiral HPLC methods and isolation techniques within Zeneca Agrochemicals (formerly ICI Agrochemicals) is reviewed. The use of low temperature to improve chiral separations has been successfully applied to production analysis, but although useful for some compounds it is regrettably not a universal panacea for all poor separations. The need to isolate small quantities of individual enantiomers from new compounds for research evaluation has led us to devise a more universal and cheap chiral stationary phase (CSP) for Preparative-LC. Joint academic research produced a CSP based on tartaric acid which was made commercially available and it was gratifying to find it was the only phase able to resolve a novel insecticide. However, as new CSPs emerged almost every month, our attention turned to using a universal chiral detector for analysis, rather than via separation of individual enantiomers. Diode laser-based polarimeters offered the opportunity of cheap, sensitive chiroptical detectors for HPLC and the ability to move away from chiral columns in both research and production analysis. Jointly sponsored research with a university has successfully explored the versatility of chiroptical detectors in agrochemical and food analysis. Comparison of chiral SFC with chiral HPLC and an extensive evaluation of established and research agrochemicals on a wide range of commercial CSPs have led to a revised method development strategy. Current work with high load displacement chiral chromatography will be described as a potential means of isolating pure enantiomers from racemates. © 1994 Wiley-Liss, Inc.     

Heavy metal fractionation during the co-composting of biosolids,deinking paper fibre and green waste

Due to the introduction of the European Union Landfill Directive, composting has become a potentially viable disposal route for some organic wastes. As waste-derived compost is frequently added to soil to improve soil quality, it is important to quantify the environmental risk posed by potentially toxic elements contained within it. Here we used a sequential chemical extraction procedure to investigate the temporal dynamics of heavy metals (Cu, Zn, Pb and Ni) during the co-composting of biosolids, deinking paper fibre and green waste. Overall, composting over 26 weeks reduced the availability of Ni, had no effect on Pb and slightly increased the availability of Cu and Zn. We conclude that although the total Cu and Ni concentrations in the compost exceed legislative guidelines for land application, due to their recalcitrant nature within the compost, this compost posed very little threat to soil or plant quality if used in agriculture or land restoration.     

The impact of multiple protein sequence alignment on phylogenetic estimation

Multiple sequence alignment is typically the first step in estimating phylogenetic trees, with the assumption being that as alignments improve, so will phylogenetic reconstructions. Over the last decade or so, new multiple sequence alignment methods have been developed to improve comparative analyses of protein structure, but these new methods have not been typically used in phylogenetic analyses. In this paper, we report on a simulation study that we performed to evaluate the consequences of using these new multiple sequence alignment methods in terms of the resultant phylogenetic reconstruction. We find that while alignment accuracy is positively correlated with phylogenetic accuracy, the amount of improvement in phylogenetic estimation that results from an improved alignment can range from quite small to substantial. We observe that phylogenetic accuracy is most highly correlated with alignment accuracy when sequences are most difficult to align, and that variation in alignment accuracy can have little impact on phylogenetic accuracy when alignment error rates are generally low. We discuss these observations and implications for future work.     

SuperFine: fast and accurate supertree estimation

Many research groups are estimating trees containing anywhere from a few thousands to hundreds of thousands of species, toward the eventual goal of the estimation of a Tree of Life, containing perhaps as many as several million leaves. These phylogenetic estimations present enormous computational challenges, and current computational methods are likely to fail to run even on data sets in the low end of this range. One approach to estimate a large species tree is to use phylogenetic estimation methods (such as maximum likelihood) on a supermatrix produced by concatenating multiple sequence alignments for a collection of markers; however, the most accurate of these phylogenetic estimation methods are extremely computationally intensive for data sets with more than a few thousand sequences. Supertree methods, which assemble phylogenetic trees from a collection of trees on subsets of the taxa, are important tools for phylogeny estimation where phylogenetic analyses based upon maximum likelihood (ML) are infeasible. In this paper, we introduce SuperFine, a meta-method that utilizes a novel two-step procedure in order to improve the accuracy and scalability of supertree methods. Our study, using both simulated and empirical data, shows that SuperFine-boosted supertree methods produce more accurate trees than standard supertree methods, and run quickly on very large data sets with thousands of sequences. Furthermore, SuperFine-boosted matrix representation with parsimony (MRP, the most well-known supertree method) approaches the accuracy of ML methods on supermatrix data sets under realistic conditions.