Comparison of convective and diffusive absorption of nutrients by growing roots

With the roots assumed growing at an exponential rate the effects of the diffusive and convective components of flux and nutrient uptake are examined in a non-dimensional setting. Two cases considered are root-root on no root-root competition. Several examples are presented to illustrate the general effects of interroot competition.Contribution from the Purdue Agric. Exp. Stn., West Lafayette, IN, 47907. Journal Paper Number7656.     

Effect of viscoelastic relaxation on moisture transport in foods. Part I: Solution of general transport equation

Within the framework of continuum mechanics, Singh et al. [1] developed an integro-differential equation, which applies to both Darcian (Fickian) and non-Darcian (non-Fickian) modes of fluid transport in swelling biological systems. A dimensionless form of the equation was obtained and transformed from moving Eulerian to the stationary Lagrangian coordinates. Here a solution scheme for the transport equation is developed to predict moisture transport and viscoelastic stresses in spheroidal biopolymeric materials. The equation was solved numerically and results used for predicting drying and sorption curves, moisture profiles, and viscoelastic stresses in soybeans. The Lagrangian solution was obtained by assembling together several schemes: the finite element method was used to discretize the equation in space; non-linearity was addressed using the Newton-Raphson method; the Volterra term was handled via a time integration scheme of Patlashenko et al. [2] and the Galerkin rule was used to solve the time-differential term. The solution obtained in Lagrangian coordinates was transformed back to the Eulerian coordinates. In part II of this sequence we present the numerical results.Revised version: 5 October 2003     

A comparison of individual‐based genetic distance metrics for landscape genetics

A major aim of landscape genetics is to understand how landscapes resist gene flow and thereby influence population genetic structure. An empirical understanding of this process provides a wealth of information that can be used to guide conservation and management of species in fragmented landscapes and also to predict how landscape change may affect population viability. Statistical approaches to infer the true model among competing alternatives are based on the strength of the relationship between pairwise genetic distances and landscape distances among sampled individuals in a population. A variety of methods have been devised to quantify individual genetic distances, but no study has yet compared their relative performance when used for model selection in landscape genetics. In this study, we used population genetic simulations to assess the accuracy of 16 individual‐based genetic distance metrics under varying sample sizes and degree of population genetic structure. We found most metrics performed well when sample size and genetic structure was high. However, it was much more challenging to infer the true model when sample size and genetic structure was low. Under these conditions, we found genetic distance metrics based on principal components analysis were the most accurate (although several other metrics performed similarly), but only when they were derived from multiple principal components axes (the optimal number varied depending on the degree of population genetic structure). Our results provide guidance for which genetic distance metrics maximize model selection accuracy and thereby better inform conservation and management decisions based upon landscape genetic analysis.     

Qualitative and quantitative comparison of glucose transport activity and glucose transporter concentration in plasma membranes from basal and insulin-stimulated rat adipose cells.

Conditions are described which allow the isolation of rat adipose-cell plasma membranes retaining a large part of the stimulatory effect of insulin in intact cells. In these membranes, the magnitude of glucose-transport stimulation in response to insulin was compared with the concentration of transporters as measured with the cytochalasin-B-binding assay or by immunoblotting with an antiserum against the human erythrocyte glucose transporter. Further, the substrate- and temperature-dependencies of the basal and insulin-stimulated states were compared. Under carefully controlled homogenization conditions, insulin-treated adipose cells yielded plasma membranes with a glucose transport activity 10-15-fold higher than that in membranes from basal cells. Insulin increased the transport Vmax. (from 1,400 +/- 300 to 15,300 +/- 3,400 pmol/s per mg of protein; means +/- S.E.M.; assayed at 22 degrees C) without any significant change in Km (from 17.8 +/- 4.4 to 18.9 +/- 1.4 nM). Arrhenius plots of plasma-membrane transport exhibited a break at 21 degrees C, with a higher activation energy over the lower temperature range. The activation energy over the higher temperature range was significantly lower in membranes from basal than from insulin-stimulated cells [27.7 +/- 5.0 kJ/mol (6.6 +/- 1.2 kcal/mol) and 45.3 +/- 2.1 kJ/mol (10.8 +/- 0.5 kcal/mol) respectively], giving rise to a larger relative response to insulin when transport was assayed at 37 degrees C as compared with 22 degrees C. The stimulation of transport activity at 22 degrees C was fully accounted for by an increase in the concentration of transporters measured by cytochalasin B binding, if a 5% contamination of plasma membranes with low-density microsomes was assumed. However, this 10-fold stimulation of transport activity contrasted with an only 2-fold increase in transporter immunoreactivity in membranes from insulin-stimulated cells. These data suggest that, in addition to stimulating the translocation of glucose transporters to the plasma membrane, insulin appears to induce a structural or conformational change in the transporter, manifested in an altered activation energy for plasma-membrane transport and possibly in an altered immunoreactivity as assessed by Western blotting.     

Assessing multi-taxa sensitivity to the human footprint,habitat fragmentation and loss by exploring alternative scenarios of dispersal ability and population size: a simulation approach

Quantifying the effects of landscape change on population connectivity is compounded by uncertainties about population size and distribution and a limited understanding of dispersal ability for most species. In addition, the effects of anthropogenic landscape change and sensitivity to regional climatic conditions interact to strongly affect habitat fragmentation and loss. To further develop conservation theory and to understand the interplay between all of these factors, we simulated habitat fragmentation and loss across the Western United States for several hypothetical species associated with four biome types, and a range of habitat requirements and dispersal abilities. We found dispersal ability and population size of the focal species to be equally sensitive to habitat extent, while dispersal ability is more sensitive to habitat fragmentation. There were also strong critical threshold effects where habitat connectivity decreased disproportionately to decreases in life-history traits making these species near these thresholds more sensitive to changes in habitat loss and fragmentation. Overall, grassland and forest associated species are also most at risk from habitat loss and fragmentation driven by human related land-use. These two largest biome types were most sensitive at large contiguous patch sizes which is often considered most important for metapopulation viability and biodiversity conservation. Hypothetical simulation studies such as this can be of great value to scientists in further conceptualizing and developing conservation theory, and evaluating spatially-explicit scenarios of habitat connectivity. Our results are available for download in a web-based interactive mapping prototype useful for accessing the results of this study.     

Population connectivity and genetic diversity of American marten (Martes americana) in the United States northern Rocky Mountains in a climate change context

Climate change is likely to alter population connectivity, particularly for species associated with higher elevation environments. The goal of this study is to predict the potential effects of future climate change on population connectivity and genetic diversity of American marten populations across a 30.2 million hectare region of the in the US northern Rocky Mountains. We use a landscape resistance model validated from empirical landscape genetics modeling to predict the current and expected future extent and fragmentation of American marten dispersal habitat under five climate change scenarios, corresponding to climatic warming of between 0.7 and 3.3 °C, consistent with expected climate change by year 2080. We predict the regions of the current and future landscapes where gene flow is expected to be governed by isolation by distance and the regions where population fragmentation is expected to limit gene flow. Finally, we predict changes in the strength and location of predicted movement corridors, fracture zones and the location of dispersal barriers across the study area in each scenario. We found that under the current climate, gene flow is predicted to be limited primarily by distance (isolation), and landscape structure does not significantly limit gene flow, resulting in very high genetic diversity over most of the study area. Projected climatic warming substantially reduces the extent and increases the fragmentation of marten populations in the western and northwestern parts of the study area. In contrast, climate change is not predicted to fragment the extensive higher elevation mountain massifs in central Idaho, the northern U.S. continental divide, and Greater Yellowstone Ecosystem. In addition, we show locations in the study area that are important corridors in the current landscape that remain intact across the climate change scenarios.     

Variability of serum levels of tumor necrosis factor-alpha, interleukin 6, and soluble interleukin 6 receptor over 2 years in young women

Serum levels of tumor necrosis factor-alpha (TNF-alpha), interleukin 6 (IL-6), and soluble interleukin 6 receptor (sIL-6R) have been studied as risk factors of cardiovascular disease in longitudinal studies. However, it is unknown about their long-term intra-individual variations and whether single measurements of these cytokines and receptor are reliable biomarkers in epidemiological studies. In this study, serum levels of TNF-alpha, IL-6, and sIL-6R were assayed by ELISAs in 36 young, healthy women from whom three blood samples were collected at 12-month intervals over 2 years, and the intraclass correlation coefficients (ICC) were estimated. The ICC of 0.73 (95% CI=0.49-0.79) for TNF-alpha was comparable to those of other commonly used biomarkers, justifying its use in epidemiological studies. The ICC of 0.48 (95% CI=0.25-0.58) for IL-6 was not optimal. However, IL-6 has been demonstrated as a consistent risk factor for cardiovascular disease, suggesting it could still be a useful biomarker if its disease association is substantial. The ICC of 0.36 (95% CI=0.10-0.47) for sIL-6R was relatively low, and multiple samples would need to be collected in prospective studies for this receptor.