Simultaneous estimation of effective and apparent diffusion coefficients in compacted bentonite

Effective diffusion coefficients (D(e)) are usually measured by means of "through-diffusion" experiments in which steady state is reached, and the "time-lag" methods are used to estimate the apparent diffusion coefficient (D(a)). For sorbing radionuclides (as caesium), the time needed to reach steady-state conditions is very large, and the precision in D(a) determinations is not satisfactory. In this paper, a method that allows determining simultaneously effective and apparent diffusion coefficients in compacted bentonite without reaching steady-state conditions is described. Basically, this method consists of an "in-diffusion" experiment in which the concentration profile in the bentonite sample is used to estimate D(a), and the temporal evolution of the solute concentration in the reservoir is used to estimate D(e). This method has several advantages over the typical "through-diffusion" experiments, in particular: (a) experiment duration is significantly shorter, (b) D(a) values are measured with greater precision and (c) it is not necessary to maintain a constant solute concentration in the reservoir. This new method has been used to estimate the effective and apparent diffusion coefficients for caesium in FEBEX bentonite and in order to validate it, the results have been compared with results previously obtained with standard methods. Experimental results have been satisfactorily modelled using a simple model of diffusion in porewater and the measured value of D(e)(Cs) is very similar to D(e)(HTO) in the same bentonite. There is no evidence of "surface diffusion" in FEBEX bentonite for caesium.     

Integrating models to predict regional haze from wildland fire

Visibility impairment from regional haze is a significant problem throughout the continental United States. A substantial portion of regional haze is produced by smoke from prescribed and wildland fires. Here we describe the integration of four simulation models, an array of GIS raster layers, and a set of algorithms for fire-danger calculations into a modeling framework for simulating regional-scale smoke dispersion. We focus on a representative fire season (2003) in the northwestern USA, on a 12 km domain, and track the simulated dispersion and concentration of PM_2.5 over the course of the season. Simulated visibility reductions over national parks and wilderness areas are within the ranges of measured values at selected monitoring sites, although the magnitudes of peak events are underestimated because these include inputs other than fire. By linking the spatial and temporal patterns of haze-producing emissions to climatic variability, particularly synoptic weather patterns, and the stochastic nature of fire occurrence across the region, we can provide a robust method for estimating the quantity and distribution of fire-caused regional haze under climate-warming scenarios.     

Empirical Bayes calculations of concordance between endpoints in environmental toxicity experiments

Hierarchical models are considered for estimating the probability of agreement between two outcomes or endpoints from an environmental toxicity experiment. Emphasis is placed on generalized regression models, under which the prior mean is related to a linear combination of explanatory variables via a monotone function. This function defines the scale over which the systematic effects are modelled as additive. Specific illustration is provided for the logistic link function. The hierarchical model employs a conjugate beta prior that leads to parametric empirical Bayes estimators of the individual agreement parameters. An example from environmental carcinogenesis illustrates the methods, with motivation derived from estimation of the concordance between two species carcinogenicity outcomes. Based on a large database of carcinogenicity studies, the inter-species concordance is seen to be reasonably informative, i.e. in the range 67–84%. Stratification into pertinent potency-related sub-groups via the logistic model is seen to improve concordance estimation: for environmental stimuli at the extremes of the potency spectrum, concordance can reach well above 90%.     

A field test of the Hamilton–Zuk hypothesis in the Trinidadian guppy (<Emphasis Type="Italic">Poecilia reticulata</Emphasis>)

The Hamilton–Zuk hypothesis proposes that females prefer male secondary sexual traits because they are honest indicators of parasite resistance. Despite the attention that this hypothesis has received, its role in sexual selection remains equivocal. This study presents the first field test in guppies of two key predictions of the Hamilton–Zuk hypothesis: (1) that within populations, the most highly ornamented males have the fewest parasites and (2) that among populations, males in high parasite populations have the most conspicuous ornaments. Five hundred male guppies from 19 distinct populations in the Northern Range of Trinidad were inspected for Gyrodactylus parasites and photographed. Eight measures of orange spot ornamentation were used to test the predictions: hue, saturation, lightness, relative area, number, and area-weighted hue, saturation, and lightness. Parasite load had no significant effect on any of these measures. There was also no relationship between orange spot ornamentation and parasite abundance among populations. Guppies from high-predation environments had significantly more parasites, and their orange coloration was lighter and less saturated than that in guppies from low-predation environments. Despite previous lab results, this study found no relationship between parasite load and male orange spot ornamentation.     

火炬松浆材建筑材林经营模型系统的研究

根据火炬松样地资料，建立火炬松林分生长模型、结构模型、商品材产量预估模型、营林措施(含间伐、施肥、整地、抚育等)效应模型及营林效益评估模型，构成火炬松纸浆材与建筑材林经营的模型系统，为火炬松纸浆材与建筑材林定向培育和优化决策提供了系列模型．     

Protected Areas and Prospects for Endangered Species Conservation in Canada

Abstract:  Reserve networks figure prominently in conservation strategies that aim to reduce extinction rates. We tested the effectiveness of the current reserve network at protecting species at risk in Canada, where relatively extensive wilderness areas remain. We compared numbers of terrestrial species at risk included in existing reserves to randomly generated networks with the same total area and number of reserves. Existing reserve networks rarely performed better than randomly selected areas and several included fewer endangered species than expected by chance, particularly in the most biologically imperiled regions. The extent of protected area and density of species at risk were unrelated at either broad (countrywide) or finer spatial scales (50 × 50 km grids), although there was a tendency for the most threatened regions of the country to have few or no protected areas (1.5% of areas with >30 endangered species were in reserves). Although reserves will play a useful role in conserving endangered species that occur within them, reducing extinction rates in a region with much of the world's remaining wilderness will require integrating conservation strategies with agricultural and urban land-use plans outside formally protected areas.     

Use of genetic algorithms to select input variables in decision tree models for the prediction of benthic macroinvertebrates

Predicting freshwater organisms based on machine learning is becoming more and more reliable due to the availability of appropriate datasets, advanced modelling techniques and the continuously increasing capacity of computers. A database consisting of measurements collected at 360 sampling sites in non-navigable watercourses in Flanders was applied to predict the absence/presence of benthic macroinvertebrate taxa by means of decision trees. The measured variables were a combination of physical–chemical (temperature, pH, dissolved oxygen concentration, conductivity, total organic carbon, Kjeldahl nitrogen and total phosphorus), structural (granulometric analysis of the sediment, width, depth and flow velocity of the river) and two ecotoxicological variables. The predictive power of decision trees was assessed on the basis of the number of Correctly Classified Instances (CCI). A genetic algorithm was introduced to compare the predictive power of different sets of input variables for the decision trees. The number of input variables was reduced from 15 to 2–8 variables without affecting the predictive power of the decision trees significantly. Furthermore, reducing the number of input variables allowed to ease the identification of general data trends.     

Impacts of Livestock Grazing and Tree Clearing on Birds of Woodland and Riparian Habitats

Abstract:  We investigated the impact of pastoral management on birds in subtropical grassy eucalypt woodland in southeastern Queensland, Australia, where the patterns of land management have made it possible to disentangle the effects of livestock grazing from those of tree clearing. We recorded changes in bird species composition, density, and relative abundance across two woodland habitat types (riparian and nonriparian) and two levels of clearing (wooded and nonwooded) and three levels of livestock grazing (low, moderate, and high) replicated over space (1000 km²) and time (2001–2002). We predicted that species that depend on understory vegetation would be most negatively affected by livestock grazing. A Bayesian generalized linear model showed that the level of grazing had the greatest effect when trees were present. When trees were absent, the impact of grazing was overshadowed by the effects of a lack of trees. Over 65% of species responded to different levels of grazing, and the abundance of 42% of species varied markedly with habitat and grazing. The most common response to grazing was high species relative abundance under low levels of grazing (28% of species), species absence at high levels of grazing (20%), and an increase in abundance with increasing grazing (18%). Despite having similar bird assemblages, the effect of grazing was stronger in riparian habitat than in adjacent woodland habitat. Our results suggest that any level of commercial livestock grazing is detrimental to some woodland birds, particularly the understory-dependant species, as predicted. Nevertheless, provided trees are not cleared, a rich and abundant bird fauna can coexist with moderate levels of grazing. Habitats with high levels of grazing, on the other hand, resulted in a species-poor bird assemblage dominated by birds that are increasing in abundance nationally .     

Viability Analysis of Reef Fish Populations Based on Limited Demographic Information

Abstract:  Marine protected areas (MPAs) that allow some degree of artisanal fishing have been proposed to control the overexploitation of marine resources while allowing extraction by local communities. Nevertheless, the management of MPAs is often impaired by the absence of data on the status of their resources. We devised a method to estimate population growth rates with the type of data that are usually available for reef fishes. We used 7 years of spatially explicit abundance data on the leopard grouper ( Mycteroperca rosacea ) in an MPA in the Gulf of California, Mexico, to construct a matrix population model that incorporated the effects of El Niño/La Niña Southern Oscillation on population dynamics. An environmental model that estimated different demographic estimates for El Niño and La Niña periods performed better than a single-environment model, and a single-habitat model performed better than a model that considered different depths as different habitats. Our results suggest that the population of the leopard grouper off the main island of the MPA is not viable under present conditions. Although the impact of fishing on leopard grouper populations in the MPA has not yet been established, fishing should be closed as a precautionary measure at this island if a priority of the MPA is to ensure the sustainability of its fish populations.