Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

Design and risk assessment tool for vegetative treatment areas receiving agricultural wastewater: Preliminary results

Vegetative treatment areas (VTAs) are commonly being used as an alternative method of agricultural process wastewater treatment. However, it is also apparent that to completely prevent discharge of pollutants to the surrounding environment, settling of particulates and bound constituents from overland flow through VTAs is not sufficient. For effective remediation of dissolved agricultural pollutants, VTAs must infiltrate incoming wastewater. A simple water balance model for predicting VTA soil saturation and surface discharge in landscapes characterized by sloping terrain and a shallow restrictive layer is presented and discussed. The model accounts for the cumulative effect of successive rainfall events and wastewater input on soil moisture status and depth to water table. Nash–Sutcliffe efficiencies ranged from 0.65 to 0.81 for modeled and observed water table elevations after calibration of saturated hydraulic conductivity. Precipitation data from relatively low, average, and high annual rainfall years were used with soil, site, and contributing area data from an example VTA for simulations and comparisons. Model sensitivity to VTA width and contributing area (i.e. barnyard, feedlot, silage bunker, etc.) curve number was also investigated. Results of this analysis indicate that VTAs should be located on steeper slopes with deeper, more-permeable soils, which effectively lowers the shallow water table. In sloping landscapes (>2%), this model provides practitioners an easy-to-use VTA design and/or risk assessment tool that is more hydrological process-based than current methods.     

Growth of northern deciduous trees under increasing atmospheric humidity: possible mechanisms behind the growth retardation

Regional Environmental Change - Increasing atmospheric humidity—a climate trend predicted for northern Europe—will reduce water flux through vegetation. Diminished transpirational water...     

Female reproductive qualities affect male painted turtle (Chrysemys picta marginata) reproductive success

Male reproductive success (RS) in polygamous species with minimal social systems is often determined by the number of mates. However, because male RS is translated through females, the number of offspring sired can also be influenced by female qualities. Empirically sufficient data to document how tradeoffs between mate number and quality influence male RS are seldom available for long-lived, iteroparous species. We combined long-term life history data (1983–2006) on the E. S. George Reserve (ESGR, MI, USA) with parentage data from 155 clutches of 59 female painted turtles (Chrysemys picta marginata) of varying reproductive frequencies (2003–2006) to determine the relative contribution of female numbers and qualities on male RS. One previously documented trait of female painted turtles that can have substantial influences on male RS is repeat paternity through the use of stored sperm to fertilize over 95 % of within-year clutches. In addition, our study found that second-clutch producing female painted turtles on the ESGR have higher among-year reproductive frequencies than do first-clutch only females. Multiple paternity was detected in 14.1 % of clutches (min-max?=?6.1–30.0 % annually), and the number of mates of both sexes was low annually (males 1.0; females 1.2) and over 4 years (males 1.1; females 1.7). Among successful males, RS varied substantially (1–32 offspring) and was strongly influenced by the combination of female reproductive frequency and repeat paternity (>38 % among years), but not mate number. Low mate number for both sexes was unexpected in a species without complex mating behaviors or parental care.     

Integrated assessment of a new Waste-to-Energy facility in Central Greece in the context of regional perspectives

The main aim of this study is the integrated assessment of a proposed Waste-to-Energy facility that could contribute in the Municipal Solid Waste Management system of the Region of Central Greece. In the context of this paper alternative transfer schemes for supplying the candidate facility were assessed considering local conditions and economical criteria. A mixed-integer linear programming model was applied for the determination of optimum locations of Transfer Stations for an efficient supplying chain between the waste producers and the Waste-to-Energy facility. Moreover different Regional Waste Management Scenarios were assessed against multiple criteria, via the Multi Criteria Decision Making method ELECTRE III. The chosen criteria were total cost, Biodegradable Municipal Waste diversion from landfill, energy recovery and Greenhouse Gas emissions and the analysis demonstrated that a Waste Management Scenario based on a Waste-to-Energy plant with an adjacent landfill for disposal of the residues would be the best performing option for the Region, depending however on the priorities of the decision makers. In addition the study demonstrated that efficient planning is necessary and the case of three sanitary landfills operating in parallel with the WtE plant in the study area should be avoided. Moreover alternative cases of energy recovery of the candidate Waste-to-Energy facility were evaluated against the requirements of the new European Commission Directive on waste in order for the facility to be recognized as recovery operation. The latter issue is of high significance and the decision makers in European Union countries should take it into account from now on, in order to plan and implement facilities that recover energy efficiently. Finally a sensitivity check was performed in order to evaluate the effects of increased recycling rate, on the calorific value of treated Municipal Solid Waste and the gate fee of the candidate plant and found that increased recycling efforts would not diminish the potential for incineration with energy recovery from waste and neither would have adverse impacts on the gate fee of the Waste-to-Energy plant. In general, the study highlighted the need for efficient planning in solid waste management, by taking into account multiple criteria and parameters and utilizing relevant tools and methodologies into this context.     

Urinary stones as a novel matrix for human biomonitoring of toxic and essential elements

Monitoring of body burden of toxic elements is usually based on analysis of concentration of particular elements in blood, urine and/or hair. Analysis of these matrices, however, predominantly reflects short- or medium-term exposure to trace elements or pollutants. In this work, urinary stones were investigated as a matrix for monitoring long-term exposure to toxic and essential elements. A total of 431 samples of urinary calculi were subjected to mineralogical and elemental analysis by infrared spectroscopy and inductively coupled plasma mass spectrometry. The effect of mineralogical composition of the stones and other parameters such as sex, age and geographical location on contents of trace and minor elements is presented. Our results demonstrate the applicability of such approach and confirm that the analysis of urinary calculi can be helpful in providing complementary information on human exposure to trace metals and their excretion. Analysis of whewellite stones (calcium oxalate monohydrate) with content of phosphorus <0.6 % has been proved to be a promising tool for biomonitoring of trace and minor elements.

     

Geochemical distribution,bioavailability and potential toxicity of some trace metals in a complex micro-tidal estuary,Southwest India

The spatial and temporal variations of some trace metals in the surface sediments of Cochin Estuary were analyzed along with their geochemical associations to identify the possible sources, bioavailability and the health risks posed by them. The dominance of kaolinite and suggested that clay minerals distribution is influenced by sediment sorting. Total metal analysis revealed enrichment for Cd, Pb and Zn due to anthropogenic activities. The speciation analysis established that notwithstanding the large availability, carbonate as well as organic and sulfides bound fractions showed negligible associations with most of the metals. Hydrous Fe–Mn oxides appeared to play a major role in controlling the fate and transport of these metals in the sediments of Cochin Estuary. Lower contribution of the residual fractions for Cd (21%–26%), Pb (<60%) and Zn (24%–42%) indicated an obvious increase of other geochemical fractions. Risk assessment analysis revealed that regardless of total concentration, none of the analyzed metals were at safe levels in the estuary as appreciable percentages were found to be associated with mobile geochemical forms. The speciation study conspicuously established that the metals originating from non-geogenic sources are largely associated with the labile fractions and hence are more detrimental to the aquatic biota.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.