Robust trend tests with application to toxicology

In most real data situations in the one-way design both the underlying distribution and the shape of the dose-response curve are a priori unknown. The power of a trend test strongly depends on both. However, tests which are routinely used to analyze toxicological assays must be robust. We use nonparametric tests with different scores—powerful for different distributions—and different contrasts—powerful for different shapes—and use the maximum of all test statistics as a new test statistic. Simulation results indicate that this maximum test, which is a nonparametric multiple contrast test, stabilizes the power for various shapes and distributions. The investigated tests are applied to the data of a toxicological assay.     

On the meta-analysis of response ratios for studies with correlated and multi-group designs

A common effect size metric used to quantify the outcome of experiments for ecological meta-analysis is the response ratio (RR): the log proportional change in the means of a treatment and control group. Estimates of the variance of RR are also important for meta-analysis because they serve as weights when effect sizes are averaged and compared. The variance of an effect size is typically a function of sampling error; however, it can also be influenced by study design. Here, I derive new variances and covariances for RR for several often-encountered experimental designs: when the treatment and control means are correlated; when multiple treatments have a common control; when means are based on repeated measures; and when the study has a correlated factorial design, or is multivariate. These developments are useful for improving the quality of data extracted from studies for meta-analysis and help address some of the common challenges meta-analysts face when quantifying a diversity of experimental designs with the response ratio.     

An EM algorithm for capture-recapture estimation

Analysis of capture—recapture data often involves maximizing a complex likelihood function with many unknown parameters. Statistical inference based on selection of a proper model depends on successful attainment of this maximum. An EM algorithm is developed for obtaining maximum likelihood estimates of capture and survival probabilities conditional on first capture from standard capture—recapture data. The algorithm does not require the use of numerical derivatives which may improve precision and stability relative to other estimation schemes. The asymptotic covariance matrix of the estimated parameters can be obtained using the supplemented EM algorithm. The EM algorithm is compared to a more traditional Newton-Raphson algorithm with both a simulated and a real dataset. The two algorithms result in the same parameter estimates, but Newton-Raphson variance estimates depend on a numerically estimated Hessian matrix that is sensitive to step size choice.     

The Optimal Allocation of Conservation Funds

This paper presents a framework to evaluate alternative designs of conservation programs and their implications for the allocation of conservation funds. We show that the efficient allocation of conservation funds must consider two important “pooling” effects—cumulative effects and interrelationships among alternative environmental benefits. Ignoring the cumulative effects of environmental benefits may cause conservation funds to be overly dispersed geographically and, as a result, may result in minimum environmental benefits when the budget is small. Ignoring the interrelationships among alternative environmental benefits may result in not only misallocation of conservation funds among geographical areas, but also incorrect resources being targeted for conservation practices. Implications of these results for the design of conservation programs are discussed.     

Statistical aspects of inhalation toxicokinetics

The statistical analysis of dynamic processes is a useful tool to learn how environmental and ecological systems work and how they respond to disturbances. In the context of human risk assessment of potentially harmful chemicals, many complex dynamic processes in terms of kinetics have to be taken into account. Thorough research of direct influence of chemicals to humans depends on investigations with animalsin vivo andin vitro. However, when animals serve as models of human systems, one critical step is the extrapolation from the risk observed in the experimental animals to the risk associated with the human organism. To extrapolate the observed risk in this case, the detailed knowledge of the relevant kinetic processes as well as their differences between species is fundamental. On the other hand experimental tools for these processes are quite restrictive. Based on simple experimental designs a statistical method is proposed for characterizing such kinetic processes using the well-known compartmental analysis tool and non-linear regression. The methodology is then exemplified by non-invasive toxicokinetic inhalation experiments with rats.     

Maritime oil spills— Environmental lessons and experiences with special reference to low-risk coastlines

Oil spill contingency plans are available for most coastlines but the amount of useful environmental data is variable. The information should be held on a GIS base. High risk areas should be identified and the pre-existing store of environmental knowledge should be commensurately extensive and should be available in considerable spatial detail. Contingency plans still depend on basic lists of coastal types as defined by static, sediment based shoreline characteristics. There is a lack of dynamic, process information. TheBraer oil spill of 1993 provides a case study of the application of sound coastal geomorphological and ecological data to impact assessment. Monitoring of the ecological effects of this massive oil spill reinforces other research which indicates that most coastlines can recover naturally from oil spills, and that oil spill clean up techniques may not necessarily benefit rapid shoreline recovery. Although pre-existing environmental informations is important, the key decisions must be taken quickly and are frequently judgmental and, therefore, place a premium on gathering appropriate scientific expertise to the site of the spill as soon as possible and with sufficient powers to affect both the oil spill response, to initiate early surveys of damage and to facilitate the initial monitoring programme.     

Jobs Versus the Environment: An Industry-Level Perspective

The possibility that workers could be adversely affected by increasingly stringent environmental policies has led to claims of a “jobs versus the environment” trade-off by both business and labor leaders. The present research examines this claim at the industry level for four heavily polluting industries: pulp and paper mills, plastic manufacturers, petroleum refiners, and iron and steel mills. Combining a unique plant-level data set with industry-level demand information, we find that increased environmental spending generally does not cause a significant change in employment. Our average across all four industries is a net gain of 1.5 jobs per $1 million in additional environmental spending, with a standard error of 2.2 jobs—an economically and statistically insignificant effect. There are statistically significant and positive effects in two industries, but total number of affected jobs remains quite small. These small positive effects can be linked to labor-using factor shifts and relatively inelastic estimated demand.     

Bayesian testing for trend in a power model for clustered binary data

Developmental toxicity studies are widely used to investigate the potential risk of environmental hazards. In dose–response experiments, subjects are randomly allocated to groups receiving various dose levels. Tests for trend are then often applied to assess possible dose effects. Recent techniques for risk assessment in this area are based on fitting dose–response models. The complexity of such studies implies a number of non-trivial challenges for model development and the construction of dose-related trend tests, including the hierarchical structure of the data, litter effects inducing extra variation, the functional form of the dose–response curve, the adverse event at dam or at fetus level, the inference paradigm, etc. The purpose of this paper is to propose a Bayesian trend test based on a non-linear power model for the dose effect and using an appropriate model for clustered binary data. Our work is motivated by the analysis of developmental toxicity studies, in which the offspring of exposed and control rodents are examined for defects. Simulations show the performance of the method over a number of samples generated under typical experimental conditions.     

Effects of Recent Environmental Change on Accuracy of Inferences of Extinction Status

Correctly classifying a species as extinct or extant is of critical importance if current rates of biodiversity loss are to be accurately quantified. Observing an extinction event is rare, so in many cases extinction status is inferred using methods based on the analysis of records of historic sighting events. The accuracy of such methods is difficult to test. However, results of recent experiments with microcosm communities suggest that the rate at which a population declines to extinction, potentially driven by varying environmental conditions, may alter one's ability accurately to infer extinction status. We tested how the rate of population decline, driven by historic environmental change, alters the accuracy of 6 commonly applied sighting‐based methods used to infer extinction. We used data from small‐scale experimental communities and recorded wild population extirpations. We assessed how accuracy of the different methods was affected by rate of population decline, search effort, and number of sighting events recorded. Rate of population decline and historic population size of the species affected the accuracy of inferred extinction dates; however, faster declines produced more accurate inferred dates of extinction, but only when population sizes were higher. Optimal linear estimation (OLE) offered the most reliable and robust estimates, though no single method performed best in all situations, and it may be appropriate to use a different method if information regarding historic search efforts is available. OLE provided the most accurate estimates of extinction when the number of sighting events used was >10, and future use of this method should take this into account. Data from experimental populations provide added insight into testing techniques to discern wild extirpation events. Care should be taken designing such experiments so that they mirror closely the abundance dynamics of populations affected by real‐world extirpation events. Efectos del Cambio Ambiental Reciente sobre la Precisión de las Inferencias sobre el Estado de Extinción     

Experimentally elevated plasma levels of testosterone do not increase male reproductive success in blue tits

In temperate passerines, increased testosterone (T) levels during breeding mediate male aggressive and mating behaviour. If individual variability in T levels is reflected in behavioural differences during mating, males with higher T might gain higher reproductive success. This can be tested experimentally by elevating T levels. However, high exogenous T levels are known to have negative effects on male sperm production. This may reduce male fitness, particularly if sperm competition is intense. We experimentally elevated T levels in breeding blue tit males to investigate how T levels above the natural mean influence male reproductive success. Contrary to most—if not all—previous experimental manipulations of T levels in birds, we restricted the treatment with exogenous T to the time when females were fertile and T levels were naturally high in males. In blue tits, extra-pair paternity is an important component of male reproductive success, and its frequency is likely influenced by androgen-mediated behaviours such as mate attraction and aggression towards other males. Here we show that T-males were equally likely to become cuckolded and did not gain more extra-pair paternity than control males. Cuckolded T-males, however, lost more paternity than control males. We discuss the possibility that this is caused by negative effects of T treatment on sperm production.Communicated by M. Webster     

Compartmental systems. An appealing class for kinetic modeling and identification of metabolic processes

Problems which arise in quantitative studies on the kinetics of exogenous and endogenous chemical substances within the organism are examined together with approaches for their resolution. Linear and nonlinear compartmental mathematical models are presented and their relevant role for interpreting stimulus‐response experimental data is outlined. Available approaches are then discussed for the resolution of the system identification problem, including a priori and a posteriori identifiability, parameter estimation from test measurement data and optimum design of kinetic experiments. Finally, approaches to the problem of validation are reviewed.     

A comparison of periodic survey designs employing multi-stage sampling

Sampling designs considered for a national scale environmental monitoring programme are compared. Specifically, design strategies designed to monitor one aspect of this environmental programme, agro-ecosystem health, are assessed. Two types of panel survey designs are evaluated within the framework of two-stage sampling. Comparisons of these designs are discussed with regard to precision, cost, and other issues that need to be considered in planning long-term surveys. To compare precision, the underlying variance of a simple estimator of mean difference is derived for each of the two designs. A variance and cost model accounting for the different rotational sampling schemes across designs are developed. Optimum stage allocation for each design are assessed with the variance-cost models. The best choice of design varied with the conditions underlying the variance model and the degree of other sources of survey error expected in the programme.     

No evidence for female mate choice based on genetic similarity in the túngara frog Physalaemus pustulosus

In most sexually reproducing animals, the behavior of one or both sexes during courtship critically influences the success at mating of the opposite sex. This behavior is often interpreted as “mate choice,” and there is great interest in why such choices are exercised. The explanation for the evolution of mate choice that has received the most attention and generated the most controversy is based on assumed genetic effects. In this study, we investigated whether female túngara frogs, which choose mates based on acoustic cues, have a preference for genetically less related males. Specifically, we determine if there is disassortive mating based on microsatellite markers, if there is information in the advertisement call that could be used to assess genetic similarity, and if females exhibit acoustic-based mating preferences that would promote choice for genetic diversity. Using seven microsatellite markers, we found no correlation of male call similarity and male genetic relatedness. Female choice experiments showed no female preference for calls of less related males, and there was no evidence for inbreeding avoidance in the field. Our results do not support the hypothesis of mate choice based on information about genetic relatedness conveyed by acoustic signals in túngara frogs.     

When is a male not a male? Sex recognition and choice in two sex-changing species

For dioecious species, choosing a mate of the same sex can have reproductive costs. For sex-changing animals, however, a lack of sex recognition may not carry a reproductive cost, as pairs that were initially same-sex can become opposite-sex pairs as one partner changes sex. The strength of sex discrimination in sex changers, then, should depend on the duration of mating associations and whether the time of sex change is influenced by social situation (“flexible” sex change). We studied two species of marine snails that change sex from male to female, one with flexible sex change and long-term or permanent mating associations (Crepidula fornicata) and one with short-term pairings and relatively fixed time of sex change (Crepidula convexa), to determine whether either species exhibits sex recognition and whether members of C. convexa show stronger sex discrimination. In laboratory experiments, small males, the choosing animals, were placed with either a male or a female conspecific (no-choice experiments) or given a choice of a male or female (choice experiments). We controlled for shell length in all experiments, as relative size may influence sex change or choice. Males of both species paired more often with females than males, but, as predicted, males of C. convexa showed stronger discrimination: When given a choice, no C. convexa male paired with another male. In contrast, some C. fornicata males always chose other males even when given the choice of a female. These results suggest that sex recognition can be adaptive even for sex changers but demonstrate that the level of sex recognition will depend on other aspects of reproductive behavior.     

Leaching of aluminium from cookwares -- a review

Concern over the possible relation between environmental aluminium exposure and Alzheimer's disease has prompted studies of all forms of human intake of this element including that from foods. Aluminium cookware, apart from other sources of dietary aluminium, is considered to be a potential source of this metal to human beings. Various research groups have carried out aluminium leaching experiments with food, beverages and water under different experimental conditions modified by varying the level of pH, chloride, fluoride, citrate, acetate etc. The results reported by different workers show marked discrepancies in levels of leached aluminum. The apparent reason for such discrepancy in levels of aluminum leached can be attributed to factors such as non-systematic and non-uniform experimental designs, non-standard conditions maintained during the experiments and choice of method for aluminium analysis. In order to assess accurately the contribution of aluminium ingestion by human beings through aluminium cookware, the present review emphasises the need of i) standard size aluminium plates obtained from the same lot for one set of experimentations; ii) real life cooking conditions to highlight the role of various complexing species present in food e.g. citrate, oxalate, acetate, tartrate etc.; iii) role of chemistry of aluminium in presence of acidic, basic and neutral cooking medium and iv) strict analytical control in the estimation of aluminium. Results of a systematic study by the authors conducted on the abovementioned lines are also described.     

Variation in composition of predator-attracting allelochemicals emitted by herbivore-infested plants: Relative influence of plant and herbivore

Summary During foraging, natural enemies of herbivores may employ volatile allelochemicals that originate from an interaction of the herbivore and its host plant. The composition of allelochemical blends emitted by herbivore-infested plants is known to be affected by both the herbivore and the plant. Our chemical data add new evidence to the recent notion that the plants are more important than the herbivore in affecting the composition of the volatile blends. Blends emitted by apple leaves infested with spider mites of 2 different species,T. urticae andP. ulmi, differed less in composition (principally quantitative differences for some compounds) than blends emitted by leaves of two apple cultivars infested by the same spider-mite species,T. urticae (many quantitative and a few qualitative differences). Comparison between three plant species — apple, cucumber and Lima bean — reveals even larger differences between volatile blends emitted upon spider-mite damage (many quantitative differences and several qualitative differences).     

Species distribution modelling—Effect of design and sample size of pseudo-absence observations

We explored the effect of varying pseudo-absence data in species distribution modelling using empirical data for four real species and simulated data for two imaginary species. In all analyses we used a fixed study area, a fixed set of environmental predictors and a fixed set of presence observations. Next, we added pseudo-absence data generated by different sampling designs and in different numbers to assess their relative importance for the output from the species distribution model. The sampling design strongly influenced the predictive performance of the models while the number of pseudo-absences had minimal effect on the predictive performance. We attribute much of these results to the relationship between the environmental range of the pseudo-absences (i.e. the extent of the environmental space being considered) and the environmental range of the presence observations (i.e. under which environmental conditions the species occurs). The number of generated pseudo-absences had a direct effect on the predicted probability, which translated to different distribution areas. Pseudo-absence observations that fell within grid cells with presence observations were purposely included in our analyses. We discourage the practice of excluding certain pseudo-absence data because it involves arbitrary assumptions about what are (un)suitable environments for the species being modelled.     

Prior encounters with the opposite sex affect male and female mating behavior in a wolf spider (Araneae,Lycosidae)

Mate availability can vary widely in nature depending upon population density and sex ratio and can affect the ability of individuals to be selective in mate choice. We tested the effects of prior encounters with the opposite sex (i.e., exposure to the opposite sex either with or without mating) on subsequent mating behavior in two experiments that manipulated mate availability for both males and females in the wolf spider, Hogna helluo. The probability of mating in the experimental trial depended upon whether the prior encounter involved mating or not, and males and females responded in opposite directions. Exposure without mating resulted in a higher subsequent frequency of mating for females and a lower subsequent frequency of mating for males, while prior mating experience resulted in a lower frequency of female remating and a higher frequency of male remating. Prior exposure without mating did not affect female aggression. However, mated females engaged in precopulatory cannibalism more frequently than virgins. Mated males escaped postcopulatory cannibalism more frequently than virgins. Our results show that males respond to exposure without mating in the expected manner. However, prior mating (1 week earlier) had unexpected effects on males, which may be due to mated males being of higher quality. There were little or no effects of the size of the prior exposure individual or mate on subsequent mating behaviors. Further research is needed to determine why different species use different degrees of prior information in mate choice.     

Sampling designs on stream networks using the pseudo-Bayesian approach

Monitoring stream networks through time provides important ecological information. The sampling design problem is to choose locations where measurements are taken so as to maximise information gathered about physicochemical and biological variables on the stream network. This paper uses a pseudo-Bayesian approach, averaging a utility function over a prior distribution, in finding a design which maximizes the average utility. We use models for correlations of observations on the stream network that are based on stream network distances and described by moving average error models. Utility functions used reflect the needs of the experimenter, such as prediction of location values or estimation of parameters. We propose an algorithmic approach to design with the mean utility of a design estimated using Monte Carlo techniques and an exchange algorithm to search for optimal sampling designs. In particular we focus on the problem of finding an optimal design from a set of fixed designs and finding an optimal subset of a given set of sampling locations. As there are many different variables to measure, such as chemical, physical and biological measurements at each location, designs are derived from models based on different types of response variables: continuous, counts and proportions. We apply the methodology to a synthetic example and the Lake Eacham stream network on the Atherton Tablelands in Queensland, Australia. We show that the optimal designs depend very much on the choice of utility function, varying from space filling to clustered designs and mixtures of these, but given the utility function, designs are relatively robust to the type of response variable.     

Orientation ofRhizophagus grandis (Coleoptera: Rhizophagidae) to oxygenated monoterpenes in a species-specific predator-prey relationship

Summary The predator,Rhizophagus grandis, is linked to its specific prey,Dendroctonus micans, by semiochemical signals regulating oviposition and long range orientation. A mixture of simple oxygenated monoterpenes [(–)—fenchone, (–)—pinocamphone, rac. camphor, terpinene-4-ol, borneol, fenchol and verbenone], identified from the frass ofD. micans has been found to be extremely active in a flight windtunnel as a long—range attractant for the predator. The mixture elicited 84 % of the response to larval frass of the prey. Excluding pinocamphone from the mixture did not influence its activity. Also, changing the absolute configurations of some of the components (fenchol, terpinene-4-ol and borneol) did not influence the predators' response. However, the addition of (–)—-terpineol increased the attractivity of the synthetic blend to almost that of larval frass of the prey. Ecological implications of the identified semiochemicals and their use in pest management are discussed.