Linking soil moisture balance and source-responsive models to estimate diffuse and preferential components of groundwater recharge

Results are presented of a detailed study into the vadose zone and shallow water table hydrodynamics of a field site in Shropshire, UK. A conceptual model is developed and tested using a range of numerical models, including a modified soil moisture balance model (SMBM) for estimating groundwater recharge in the presence of both diffuse and preferential flow components. Tensiometry reveals that the loamy sand topsoil wets up via macropore flow and subsequent redistribution of moisture into the soil matrix. Recharge does not occur until near-positive pressures are achieved at the top of the sandy glaciofluvial outwash material that underlies the topsoil, about 1 m above the water table. Once this occurs, very rapid water table rises follow. This threshold behaviour is attributed to the vertical discontinuity in the macropore system due to seasonal ploughing of the topsoil, and a lower permeability plough/iron pan restricting matrix flow between the topsoil and the lower outwash deposits. Although the wetting process in the topsoil is complex, a SMBM is shown to be effective in predicting the initiation of preferential flow from the base of the topsoil into the lower outwash horizon. The rapidity of the response at the water table and a water table rise during the summer period while flow gradients in the unsaturated profile were upward suggest that preferential flow is also occurring within the outwash deposits below the topsoil. A variation of the source-responsive model proposed by Nimmo (2010) is shown to reproduce the observed water table dynamics well in the lower outwash horizon when linked to a SMBM that quantifies the potential recharge from the topsoil. The results reveal new insights into preferential flow processes in cultivated soils and provide a useful and practical approach to accounting for preferential flow in studies of groundwater recharge estimation

Human imprinted chromosomal regions are historical hot-spots of recombination.

Human recombination rates vary along the chromosomes as well as between the two sexes. There is growing evidence that epigenetic factors may have an important influence on recombination rates, as well as on crossover position. Using both public database analysis and wet-bench approaches, we revisited the relationship between increased rates of meiotic recombination and genome imprinting. We constructed metric linkage disequilibrium (LD) maps for all human chromosomal regions known to contain one or more imprinted genes. We show that imprinted regions contain significantly more LD units (LDU) and have significantly more haplotype blocks of smaller sizes than flanking nonimprinted regions. There is also an excess of hot-spots of recombination at imprinted regions, and this is likely to do with the presence of imprinted genes, per se. These findings indicate that imprinted chromosomal regions are historical "hot-spots" of recombination. We also demonstrate, by direct segregation analysis at the 11p15.5 imprinted region, that there is remarkable agreement between sites of meiotic recombination and steps in LD maps. Although the increase in LDU/Megabase at imprinted regions is not associated with any significant enrichment for any particular sequence class, major sequence determinants of recombination rates seem to differ between imprinted and control regions. Interestingly, fine-mapping of recombination events within the most male meiosis-specific recombination hot-spot of Chromosome 11p15.5 indicates that many events may occur within or directly adjacent to regions that are differentially methylated in somatic cells. Taken together, these findings support the involvement of a combination of specific DNA sequences and epigenetic factors as major determinants of hot-spots of recombination at imprinted chromosomal regions

Elucidating the impact of micro-scale heterogeneous bacterial distribution on biodegradation

Groundwater microorganisms hardly ever cover the solid matrix uniformly–instead they form micro-scale colonies. To which extent such colony formation limits the bioavailability and biodegradation of a substrate is poorly understood. We used a high-resolution numerical model of a single pore channel inhabited by bacterial colonies to simulate the transport and biodegradation of organic substrates. These high-resolution 2D simulation results were compared to 1D simulations that were based on effective rate laws for bioavailability-limited biodegradation. We (i) quantified the observed bioavailability limitations and (ii) evaluated the applicability of previously established effective rate concepts if microorganisms are heterogeneously distributed. Effective bioavailability reductions of up to more than one order of magnitude were observed, showing that the micro-scale aggregation of bacterial cells into colonies can severely restrict the bioavailability of a substrate and reduce in situ degradation rates. Effective rate laws proved applicable for upscaling when using the introduced effective colony sizes

Analysis of Ratios in Multivariate Morphometry

The analysis of ratios of body measurements is deeply ingrained in the taxonomic literature. Whether for plants or animals, certain ratios are commonly indicated in identification keys, diagnoses, and descriptions. They often provide the only means for separation of cryptic species that mostly lack distinguishing qualitative characters. Additionally, they provide an obvious way to study differences in body proportions, as ratios reflect geometric shape differences. However, when it comes to multivariate analysis of body measurements, for instance, with linear discriminant analysis (LDA) or principal component analysis (PCA), interpretation using body ratios is difficult. Both techniques are commonly applied for separating similar taxa or for exploring the structure of variation, respectively, and require standardized raw or log-transformed variables as input. Here, we develop statistical procedures for the analysis of body ratios in a consistent multivariate statistical framework. In particular, we present algorithms adapted to LDA and PCA that allow the interpretation of numerical results in terms of body proportions. We first introduce a method called the “LDA ratio extractor,” which reveals the best ratios for separation of two or more groups with the help of discriminant analysis. We also provide measures for deciding how much of the total differences between individuals or groups of individuals is due to size and how much is due to shape. The second method, a graphical tool called the “PCA ratio spectrum,” aims at the interpretation of principal components in terms of body ratios. Based on a similar idea, the “allometry ratio spectrum” is developed which can be used for studying the allometric behavior of ratios. Because size can be defined in different ways, we discuss several concepts of size. Central to this discussion is Jolicoeur's multivariate generalization of the allometry equation, a concept that was derived only with a heuristic argument. Here we present a statistical derivation of the allometric size vector using the method of least squares. The application of the above methods is extensively demonstrated using published data sets from parasitic wasps and rock crabs