Effects of summer rainfall manipulations on the abundance and vertical distribution of herbivorous soil macro-invertebrates

Soil invertebrate communities are likely to be highly vulnerable to low soil moisture, caused by a reduction in summer rainfall which is predicted for some regions under current climate change scenarios. However, the effects of changes in summer rainfall on soil invertebrate assemblages have rarely been tested experimentally. In this study, samples were taken in 2003 and 2004 from a long-running field experiment, to investigate the impact of 10 years of experimental summer drought and increased summer rainfall manipulations on the soil fauna of a calcareous grassland. Summer drought altered the soil invertebrate assemblage in the autumn, immediately following treatment application, but by the following spring treatment effects were no longer apparent. The two most common root herbivore species responded differently to the summer rainfall manipulations. Larvae of the dominant root-chewing species, Agriotes lineatus, were more numerous under enhanced rainfall in both the spring and autumn. In contrast, abundance of the Coccoidea Lecanopsis formicarum was unaffected by the rainfall manipulations. The responses of root herbivores to an increased incidence of summer droughts are therefore likely to vary, depending on their feeding strategy and life history. (c) 2007 Elsevier Masson SAS. All rights reserved.

Comparing correlations of continuous observations from two independent populations using a sequential approach

A sequential study design generally makes more efficient use of available information than a fixed sample counterpart of equal power. This feature is gradually being exploited by researchers in genetic and epidemiological investigations that utilize banked biological resources and in studies where time, cost and ethics are prominent considerations. Recent work in this area has focussed on the sequential analysis of matched case-control studies with a dichotomous trait. In this paper, we extend the sequential approach to a comparison of the associations within two independent groups of paired continuous observations. Such a comparison is particularly relevant in familial studies of phenotypic correlation using twins. We develop a sequential twin method based on the intraclass correlation and show that use of sequential methodology can lead to a substantial reduction in the number of observations without compromising the study error rates. Additionally, our approach permits straightforward allowance for other explanatory factors in the analysis. We illustrate our method in a sequential heritability study of dysplasia that allows for the effect of body mass index and compares monozygotes with pairs of singleton sisters. Copyright (c) 2006 John Wiley & Sons, Ltd.

Competition and dispersal in the pea aphid: clonal variation and correlations across traits

1. The presence of an across-species trade-off between dispersal ability and competitive ability has been proposed as a mechanism that facilitates coexistence. It is not clear if a similar trade-off exists within species. Such a trade-off would constrain the evolution of either trait and, given appropriate selection pressures, promote local adaptation in these traits. 2. This study found substantial levels of heritable variation in competitive ability of the pea aphid, Acyrthosiphon pisum Harris (Homoptera: Aphididae), measured in terms of relative survival when reared with a single clone of the vetch aphid, Megoura viciae Buckton (Homoptera: Aphididae). 3. Pea aphids can move to new patches by either flying (longer distance dispersal) or walking (local dispersal) from plant to plant. There was considerable clonal variation in dispersal ability, measured in terms of the proportion of winged offspring produced, and ability to survive away from their host plant. 4. Winged individuals showed longer off-plant survival times than wingless forms of the same pea aphid clone. 5. There was no evidence of a relationship between clonal competitive ability and either measure of dispersal ability, although the power of the test is limited by the number of pea aphid clones used in the trial. 6. However, there was a positive correlation between clonal fecundity and the proportion of winged offspring produced. Although speculative, it is suggested that clones that are more likely to either overwhelm their host plant or attract higher numbers of natural enemies as a result of having higher fecundity are more likely to produce winged morphs.

Analysis of the antigen combining site: Correlations between length and sequence composition of the hypervariable loops and the nature of the antigen

It has long been suggested that the overall shape of the antigen combining site (ACS) of antibodies is correlated with the nature of the antigen. For example, deep pockets are characteristic of antibodies that bind haptens, grooves indicate peptide binders, while antibodies that bind to proteins have relatively flat combining sites. In. 1996, MacCallum, Martin and Thornton used a fractal shape descriptor and showed a strong correlation of the shape of the binding region with the general nature of the antigen. However, the shape of the ACS is determined primarily by the lengths of the six complementarity-determining regions (CDRs). Here, we make a direct correlation between the lengths of the CDRs and the nature of the antigen. In addition, we show significant differences in the residue composition of the CDRs of antibodies that bind to different antigen classes. As well as helping us to understand the process of antigen recognition, autoimmune disease and cross-reactivity these results are of direct application in the design of antibody phage libraries and modification of affinity. (C) 2003 Elsevier Science Ltd. All rights reserved.

Is there a relationship between soil and groundwater toxicity?

Part IIA of the Environmental Protection Act 1990 requires environmental regulators to assess the risk of contaminants leaching from soils into groundwater (DETR, 1999). This newly introduced legislation assumes a link between soil and groundwater chemistry, in which rainwater leaches contaminants from soil into the saturated zone. As the toxicity of both groundwater and overlying soils is dependent upon the chemicals present, their partitioning and their bioavailability, similar patterns of soil, leachates and groundwater toxicity should be observed at contaminated sites. Soil and groundwater samples were collected from different contaminated land sites in an urban area, and used to determine relationships between soil chemistry and toxicity, mobility of contaminants, and groundwater chemistry and toxicity. Soils were leached using water to mimic rainfall, and both the soils and leachates tested using bioassays. Soil bioassays were carried out using Eisenia fetida, whilst groundwater and leachates were tested using the Microtox(TM) test system and Daphnia magna 48 h acute tests. Analysis of the bioassay responses demonstrated that a number of the samples were toxic to test organisms, however, there were no significant statistical relationships between soil, groundwater and leachate toxicity. Nor were there significant correlations between soil, leachates and groundwater chemistry.

Syntheses, structural analyses, and magneto-structural correlations of three polymeric Fe(II) complexes with azide ligand

Three new metal-organic polymeric complexes, [Fe(N-3)(2)(bPP)(2)] (1), [Fe(N-3)(2)(bpe)] (2), and [Fe(N-3)(2)(phen)] (3) [bpp = (1,3-bis(4-pyridyl)-propane), bpe = (1,2-bis(4-pyridyl)-ethane), phen = 1,10-phenanthroline], have been synthesized and characterized by single-crystal X-ray diffraction studies and low-temperature magnetic measurements in the range 300-2 K. Complexes 1 and 2 crystallize in the monoclinic system, space group C2/c, with the following cell parameters: a = 19.355(4) Angstrom, b = 7.076(2) Angstrom, c = 22.549(4) Angstrom, beta = 119.50(3)degrees, Z = 4, and a = 10.007(14) Angstrom, b = 13.789(18) Angstrom, c = 10.377(14) Angstrom, beta = 103.50(1)degrees, Z = 4, respectively. Complex 3 crystallizes in the triclinic system, space group P (1) over bar, with a = 7.155(12) Angstrom, b = 10.066(14) Angstrom, c = 10.508(14) Angstrom, alpha = 109.57(1)degrees, beta = 104.57(1)degrees, gamma = 105.10(1)degrees, and Z = 2. All coordination polymers exhibit octahedral Fe(II) nodes. The structural determination of 1 reveals a parallel interpenetrated structure of 2D layers of (4,4) topology, formed by Fe(II) nodes linked through bpp ligands, while mono-coordinated azide anions are pendant from the corrugated sheet. Complex 2 has a 2D arrangement constructed through 1D double end-to-end azide bridged iron(11) chains interconnected through bpe ligands. Complex 3 shows a polymeric arrangement where the metal ions are interlinked through pairs of end-on and end-to-end azide ligands exhibiting a zigzag arrangement of metals (Fe-Fe-Fe angle of 111.18degrees) and an intermetallic separation of 3.347 Angstrom (through the EO azide) and of 5.229 Angstrom (EE azide). Variable-temperature magnetic susceptibility data suggest that there is no magnetic interaction between the metal centers in 1, whereas in 2 there is an antiferromagnetic interaction through the end-to-end azide bridge. Complex 3 shows ferro- as well as anti-ferromagnetic interactions between the metal centers generated through the alternating end-on and end-to-end azide bridges. Complex I has been modeled using the D parameter (considering distorted octahedral Fe(II) geometry and with any possible J value equal to zero) and complex 2 has been modeled as a one-dimensional system with classical and/or quantum spin where we have used two possible full diagonalization processes: without and with the D parameter, considering the important distortions of the Fe(II) ions. For complex 3, the alternating coupling model impedes a mathematical solution for the modeling as classical spins. With quantum spin, the modeling has been made as in 2.

Gas-phase rate coefficients for reactions of NO3, OH, O-3 and O(P-3) with unsaturated alcohols and ethers: correlations and structure-activity relations (SARs)

Experimental difficulties sometimes force modellers to use predicted rate coefficients for reactions of oxygenated volatile organic compounds (oVOCs). We examine here methods for making the predictions for reactions of atmospheric initiators of oxidation, NO3, OH, O-3 and O(P-3), with unsaturated alcohols and ethers. Logarithmic correlations are found between measured rate coefficients and calculated orbital energies, and these correlations may be used directly to estimate rate coefficients for compounds where measurements have not been performed. To provide a shortcut that obviates the need to calculate orbital energies, structure-activity relations (SARs) are developed. Our SARs are tested for predictive power against compounds for which experimental rate coefficients exist, and their accuracy is discussed. Estimated atmospheric lifetimes for oVOCs are presented. The SARs for alkenols successfully predict key rate coefficients, and thus can be used to enhance the scope of atmospheric models incorporating detailed chemistry. SARs for the ethers have more limited applicability, but can still be useful in improving tropospheric models. (C) 2008 Elsevier Ltd. All rights reserved.

Link between DOC in near surface peat and stream water in an upland catchment

Hydrologic transport of dissolved organic carbon (DOC) from peat soils may differ to organo-mineral soils in how they responded to changes in flow, because of differences in soil profile and hydrology. In well-drained organo-mineral soils, low flow is through the lower mineral layer where DOC is absorbed and high flow is through the upper organic layer where DOC is produced. DOC concentrations in streams draining organo-mineral soils typically increase with flow. In saturated peat soils, both high and low flows are through an organic layer where DOC is produced. Therefore, DOC in stream water draining peat may not increase in response to changes in flow as there is no switch in flow path between a mineral and organic layer. To verify this, we conducted a high-resolution monitoring study of soil and stream water at an upland peat catchment in northern England. Our data showed a strong positive correlation between DOC concentrations at − 1 and − 5 cm depth and stream water, and weaker correlations between concentrations at − 20 to − 50 cm depth and stream water. Although near surface organic material appears to be the key source of stream water DOC in both peat and organo-mineral soils, we observed a negative correlation between stream flow and DOC concentrations instead of a positive correlation as DOC released from organic layers during low and high flow was diluted by rainfall. The differences in DOC transport processes between peat and organo-mineral soils have different implications for our understanding of long-term changes in DOC exports. While increased rainfall may cause an increase in DOC flux from peat due to an increase in water volume, it may cause a decrease in concentrations. This response is contrary to expected changes in DOC exports from organo-mineral soils, where increase rainfall is likely to result in an increase in flux and concentration.

Geostatistical analysis of rainfall

Rainfall can be modeled as a spatially correlated random field superimposed on a background mean value; therefore, geostatistical methods are appropriate for the analysis of rain gauge data. Nevertheless, there are certain typical features of these data that must be taken into account to produce useful results, including the generally non-Gaussian mixed distribution, the inhomogeneity and low density of observations, and the temporal and spatial variability of spatial correlation patterns. Many studies show that rigorous geostatistical analysis performs better than other available interpolation techniques for rain gauge data. Important elements are the use of climatological variograms and the appropriate treatment of rainy and nonrainy areas. Benefits of geostatistical analysis for rainfall include ease of estimating areal averages, estimation of uncertainties, and the possibility of using secondary information (e.g., topography). Geostatistical analysis also facilitates the generation of ensembles of rainfall fields that are consistent with a given set of observations, allowing for a more realistic exploration of errors and their propagation in downstream models, such as those used for agricultural or hydrological forecasting. This article provides a review of geostatistical methods used for kriging, exemplified where appropriate by daily rain gauge data from Ethiopia.

Correlations for gas-phase reactions of NO3, OH and O3 with alkenes: an update

Methods are developed for predicting rate coefficients for reactions of initiators of tropospheric oxidation with unsaturated compounds that are abundant in the atmosphere; prognostic tools of this kind are essential for atmospheric chemists and modellers. To pursue the aim of exploring such tools, the kinetics of reactions of NO3, OH and O-3 with a series of alkenes are examined for correlations relating the logarithms of the rate coefficients to the energies of the highest occupied molecular orbitals (HOMOs) of the alkenes. A comparison of the values predicted by the correlations with experimental data (where the latter exist) allowed us to assess the reliability of our method. We used a series of theoretical methods to calculate the HOMO energies, and found that higher computational effort improves the agreement of the predicted rate coefficients with experimental values, especially for reactions of NO3 with alkenes that possess vinyllic halogen substituents. As a consequence, it is expedient to suggest new correlations to replace those presented by us and others that were based on the lower level of theory. We propose the following correlations for the reactions of NO3, OH and O-3 with alkenes: ln(k(NO3)/cm(3) molecule(-1) s(-1)) = 6.40(E-HOMO/eV) + 31.69, ln(k(OH)/cm(3) molecule(-1) s(-1)) = 1.21 (E-HOMO/eV)-12.34 and ln(k(O3)/cm(3) molecule(-1) s(-1)) = 3.28(E-HOMO/eV)-6.78. These new correlations have been developed using the larger experimental data sets now available, and the impact of the extended data on the quality of the correlations is examined in the paper. Atmospheric lifetimes have been calculated from both experimental and estimated rate coefficients to provide an overview of removal efficiencies for different classes of alkenes with respect to oxidative processes initiated by NO3, OH and O-3. A figure is presented to show the spatial scales over which alkenes may survive transport in competition with attack by NO3, OH and O-3. Removal by NO3 or OH is always more important than removal by O-3, and reactions with NO3 dominate for scales up to a few hundred metres.

Gas-phase rate coefficients for the reactions of O(3P), S(3P), Se(3P), and Te(3P) with alkenes: application of perturbation frontier molecular orbital theory, correlations, and structure-activity relations (SARs)

The kinetics of the reactions of the atoms O(P-3), S(P-3), Se(P-3), and Te((3)p) with a series of alkenes are examined for correlations relating the logarithms of the rate coefficients to the energies of the highest occupied molecular orbitals (HOMOs) of the alkenes. These correlations may be employed to predict rate coefficients from the calculated HOMO energy of any other alkene of interest. The rate coefficients obtained from the correlations were used to formulate structure-activity relations (SARs) for reactions of O((3)p), S(P-3), Se (P-3), and Te((3)p) with alkenes. A comparison of the values predicted by both the correlations and the SARs with experimental data where they exist allowed us to assess the reliability of our method. We demonstrate the applicability of perturbation frontier molecular orbital theory to gas-phase reactions of these atoms with alkenes. The correlations are apparently not applicable to reactions of C(P-3), Si(P-3), N(S-4), and Al(P-2) atoms with alkenes, a conclusion that could be explained in terms of a different mechanism for reaction of these atoms.

The TAMORA algorithm: satellite rainfall estimates over West Africa using multi-spectral SEVIRI data

A multi-spectral rainfall estimation algorithm has been developed for the Sahel region of West Africa with the purpose of producing accumulated rainfall estimates for drought monitoring and food security. Radar data were used to calibrate multi-channel SEVIRI data from MSG, and a probability of rainfall at several different rain-rates was established for each combination of SEVIRI radiances. Radar calibrations from both Europe (the SatPrecip algorithm) and Niger (TAMORA algorithm) were used. 10 day estimates were accumulated from SatPrecip and TAMORA and compared with kriged gauge data and TAMSAT satellite rainfall estimates over West Africa. SatPrecip was found to produce large overestimates for the region, probably because of its non-local calibration. TAMORA was negatively biased for areas of West Africa with relatively high rainfall, but its skill was comparable to TAMSAT for the low-rainfall region climatologically similar to its calibration area around Niamey. These results confirm the high importance of local calibration for satellite-derived rainfall estimates. As TAMORA shows no improvement in skill over TAMSAT for dekadal estimates, the extra cloud-microphysical information provided by multi-spectral data may not be useful in determining rainfall accumulations at a ten day timescale. Work is ongoing to determine whether it shows improved accuracy at shorter timescales.

Climatic and oceanic associations with daily rainfall extremes over southern Africa

Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based daily rainfall historical data set, this paper describes the main patterns of rainfall variability over southern Africa, identifies the dates when extreme rainfall occurs within these patterns, and shows the effect of resolution in trying to identify the location and intensity of SST anomalies associated with these extremes in the Atlantic and southwest Indian Ocean. Derived from a Principal Component Analysis (PCA), the results also suggest that, for the spatial pattern accounting for the highest amount of variability, extremes extracted at a higher spatial resolution do give a clearer indication regarding the location and intensity of anomalous SST regions. As the amount of variability explained by each spatial pattern defined by the PCA decreases, it would appear that extremes extracted at a lower resolution give a clearer indication of anomalous SST regions.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa.