Male Mutation Bias and Possible Long‐Term Effects of Human Activities

Abstract: The ability of a population to adapt to changing environments depends critically on the amount and kind of genetic variability it possesses. Mutations are an important source of new genetic variability and may lead to new adaptations, especially if the population size is large. Mutation rates are extremely variable between and within species, and males usually have higher mutation rates as a result of elevated rates of male germ cell division. This male bias affects the overall mutation rate. We examined the factors that influence male mutation bias, and focused on the effects of classical life‐history parameters, such as the average age at reproduction and elevated rates of sperm production in response to sexual selection and sperm competition. We argue that human‐induced changes in age at reproduction or in sexual selection will affect male mutation biases and hence overall mutation rates. Depending on the effective population size, these changes are likely to influence the long‐term persistence of a population.     

Taxonomic Exaggeration and Its Effects on Orchid Conservation

Abstract:  Orchids are the largest family of flowering plants, encompassing several times as many species as birds or mammals. Because of their diversity, charisma, and threats from overcollection and habitat loss, they are a key group in conservation. Nevertheless, preservation of this group is plagued by taxonomic problems, particularly in Europe, where new taxa are actively being described. We used a checklist of orchids to compare the taxonomic treatment of this family between Europe and neighboring areas to search for geographical patterns. Numbers of invalid, infraspecific, and hybrid names are significantly higher in Europe than in surrounding areas. Recognition of numerous and poorly circumscribed orchid taxa is a serious obstacle to their conservation because rare, poorly defined species may be prioritized for conservation over taxonomically "good" species. This phenomenon may be the result of the popularity of orchids in Europe. We believe that more taxonomic effort should be made in other areas of the world (e.g., the tropics) and on less charismatic groups.     

EFFECT OF PRICE ON THE RESIDENTIAL DEMAND FOR WATER WITHIN AN AGENCY1

ABSTRACT: This paper develops a model that can be used to forecast the residential elasticity of demand for water within a district. Long-term water conservation programs and revenue and cost decisions hinge crucially on a determination of this elasticity. This study then pools cross-sectional (census) and time series data to generate elasticity forecasts for the Oakland urban area.     

湖北省60年代以来平均气温变化趋势初探

计算了湖北省７２个气象台年,季,月平均气温在１９６１－１９９５年间的气候倾向率,分析其时空分布特征发现：１）全省大部春季,秋季,年的ｂ值小,夏屯,冬季的ｂ值;２）冬季或１２－２、４月的ｂ值多为正,夏季或３、６－８月的ｂ值为多负,且有一定显著程度;３）夏季变凉冬季变暖,春季前后的变化大,秋季前后变化小;（４）升温中心多在江汉平原和鄂东南,降温中心多在鄂西山区尤其是鄂西北;５）大、中城市的相对热岛效应     

A combination line transect and capture-recapture sampling model for multiple observers in aerial surveys

We present a robust sampling methodology to estimate population size using line transect and capture-recapture procedures for aerial surveys. Aerial surveys usually underestimate population density due to animals being missed. A combination of capture-recapture and line transect sampling methods with multiple observers allows violation of the assumption that all animals on the centreline are sighted from the air. We illustrate our method with an example of inanimate objects which shows evidence of failure of the assumption that all objects on the centreline have probability 1 of being detected. A simulation study is implemented to evaluate the performance of three variations of the Lincoln-Petersen estimator: the overall estimator, the stratified estimator, and the general stratified estimator based on the combined likelihood proposed in this paper. The stratified Lincoln-Petersen estimator based on the combined likelihood is found to be generally superior to the other estimators.     

Kinship and social tolerance among female and juvenile wild house mice: kin bias but not kin discrimination

Kin-biased social tolerance among house mice has been interpreted in terms of kin discrimination. However, several lines of evidence suggest it may instead be an incidental artifact of group member discrimination. This leads to very different predictions about the social consequences of relatedness within and between social groups. Social interactions between wild-stock adult female and juvenile house mice (Mus domesticus) established in neighbouring territorial groups within enclosures reveal relatedness to dominant males within groups as the major factor determining social tolerance of juveniles by females. Relatedness to the female herself had no significant independent effect on responses indicating tolerance. Females were generally more aggressive toward neighbouring-group juveniles (all unrelated to females) compared with those from their own group (all related to females), but were most aggressive toward neighbouring juveniles sired by the neighbouring dominant male. They were also more aggressive toward their own-group juveniles that had been sired by the neighbouring dominant but only when encountered in the neighbouring territory and with a greater bias against female juveniles. Females were least aggressive toward own-group juveniles sired by their own-group dominant male. The sire-bias in tolerance among females is similar to that reported among the dominant males themselves in an earlier study. As a result of the combined sire-bias in tolerance by adult males and females, juveniles sired by their own-group dominant males become less likely to intrude into a neighbouring territory with time. Overall, the results suggest that differences in social tolerance reflect discrimination on the basis of social group membership rather than relatedness between interactants and thus provide strong experimental evidence in support of incidental kin bias rather than kin discrimination.     

Measurement of parental investment and sex allocation in the European beewolf Philanthus triangulum F. (Hymenoptera: Sphecidae)

Fisher’s 1930 theory of sex allocation predicts a population-wide 1:1 ratio of parental investment. We tested this prediction in the European beewolf, a sphecid wasp that hunts for honeybees as larval food. Because the method to quantify parental investment is of crucial importance, we compared the suitability of several different investment measures. Female/male cost ratios were determined from a sample and the total investment in sons and daughters was calculated. In addition, the actual number of prey items for sons and daughters was directly determined by excavating nests and counting the cuticle remains of the prey. Though mortality was high (70%), it had only a weak effect on the estimate of the investment ratio. Based on commonly used measures like fresh and dry weight of emerged adults, the investment ratio did not deviate from Fisher’s prediction of equal investment. However, progeny weight considerably underestimates investment in males and investment in large progeny. Measures that reflect the allocation of resources more directly (amount of provisions, brood cell volume) revealed a significant male bias and thus contradicted Fisher’s theory. Three kinds of explanation are discussed. First, non-adaptive explanations are unlikely. Second, from the spectrum of alternative adaptive theories, only models that assume a non-linear relationship between amount of investment and progeny fitness seem to be relevant for the study species. Third, though the number of prey in a brood cell seems to be a rather good measure of parental investment in European beewolves, some problems in measuring parental investment remain. These problems are of broad significance. Received: 17 June 1999 / Received in revised form: 6 July 1999 / Accepted: 11 July 1999     

Performance of a Bayesian state-space model of semelparous species for stock-recruitment data subject to measurement error

Measurement errors in spawner abundance create problems for fish stock assessment scientists. To deal with measurement error, we develop a Bayesian state-space model for stock-recruitment data that contain measurement error in spawner abundance, process error in recruitment, and time series bias. Through extensive simulations across numerous scenarios, we compare the statistical performance of the Bayesian state-space model with that of standard regression for a traditional stock-recruitment model that only considers process error. Performance varies depending on the information content in data, as determined by stock productivity, types of harvest situations, and amount of measurement error. Overall, in terms of estimating optimal spawner abundance S_MSY, the Ricker density-dependence parameter β, and optimal harvest rate h_MSY, the Bayesian state-space model works best for informative data from low and variable harvest rate situations for high-productivity salmon stocks. The traditional stock-recruitment model (TSR) may be used for estimating α and h_MSY for low-productivity stocks from variable and high harvest rate situations. However, TSR can severely overestimate S_MSY when spawner abundance is measured with large error in low and variable harvest rate situations. We also found that there is substantial merit in using h_MSY (or benchmarks derived from it) instead of S_MSY as a management target.     

脉冲放电脱硫产物的收集

实验结果表明利用给反应器加直流基压收集脱硫产物是可行的．产物收集效率随直流基压和停留时间的增加而增加,在本实验条件下,最高收集效率达到９５．１％ ．加直流基压后,脉冲电压、电流波形基本不变,放电增强,脱硫效果提高．加直流基压可使反应器在脱硫的同时有效收集产物．     

Misspecification of within-area exposure distribution in ecological Poisson models

Ecological studies enable investigation of geographic variations in exposure to environmental variables, across groups, in relation to health outcomes measured on a geographic scale. Such studies are subject to ecological biases, including pure specification bias which arises when a nonlinear individual exposure-risk model is assumed to apply at the area level. Introduction of the within-area variance of exposure should induce a marked reduction in this source of ecological bias. Assuming several measurements per area of exposure and no confounding risk factors, we study the model including the within-area exposure variability when Gaussian within-area exposure distribution is assumed. The robustness is assessed when the within-area exposure distribution is misspecified. Two underlying exposure distributions are studied: the Gamma distribution and an unimodal mixture of two Gaussian distributions. In case of strong ecological association, this model can reduce the bias and improve the precision of the individual parameter estimates when the within-area exposure means and variances are correlated. These different models are applied to analyze the ecological association between radon concentration and childhood acute leukemia in France.