Modeling and Predicting Species Occurrence Using Broad-Scale Environmental Variables: an Example with Butterflies of the Great Basin

Abstract: If occurrence of individual species can be modeled as a function of easily quantified environmental variables (e.g., derived from a geographic information system [GIS]) and the predictions of these models are demonstrably successful, then the scientific foundation for management planning will be strengthened. We used Bayesian logistic regression to develop predictive models for resident butterflies in the central Great Basin of western North America. Species inventory data and values for 14 environmental variables from 49 locations (segments of canyons) in the Toquima Range ( Nevada, U.S.A.) were used to build the models. Squares of the environmental variables were also used to accommodate possibly nonmonotonic responses. We obtained statistically significant models for 36 of 56 (64%) resident species of butterflies. The models explained 8–72% of the deviance in occurrence of those species. Each of the independent variables was significant in at least one model, and squared versions of five variables contributed to models. Elevation was included in more than half of the models. Models included one to four variables; only one variable was significant in about half the models. We conducted preliminary tests of two of our models by using an existing set of data on the occurrence of butterflies in the neighboring Toiyabe Range. We compared conventional logistic classification with posterior probability distributions derived from Bayesian modeling. For the latter, we restricted our predictions to locations with a high ( 70%) probability of predicted presence or absence. We will perform further tests after conducting inventories at new locations in the Toquima Range and nearby Shoshone Mountains, for which we have computed environmental variables by using remotely acquired topographic data, digital-terrain and microclimatic models, and GIS computation.     

化学品环境暴露评估模型研究进展

各国政府高度重视化学品生产使用引发的环境问题,研发了一系列环境暴露预测模型,包含了点源暴露到面源暴露各种排放模式,局部暴露、区域暴露及洲际暴露的各种预测尺度,筛选评估到确认水平的不同评估层级,用于评估化学品的潜在风险。本文从模型功能、机理出发,综述了化学品环境暴露评估涉及的排放估计、水/土/气、多介质以及食物链评估模型,以期为推动我国化学品环境暴露模型的研发提供参考。     

化学品环境暴露评估模型研究进展

各国政府高度重视化学品生产使用引发的环境问题,研发了一系列环境暴露预测模型,包含了点源暴露到面源暴露各种排放模式,局部暴露、区域暴露及洲际暴露的各种预测尺度,筛选评估到确认水平的不同评估层级,用于评估化学品的潜在风险。本文从模型功能、机理出发,综述了化学品环境暴露评估涉及的排放估计、水/土/气、多介质以及食物链评估模型,以期为推动我国化学品环境暴露模型的研发提供参考。     

环境归趋模型参数估计方法的比较

大量的研究表明,参数估计方法的可行性和有效性,决定着环境归趋模型的成功与否。在文献检索的基础上,简单介绍了环境归趋模型参数估计方法的类型和最优化原理,分析了各种方法的优点与不足,并初步探讨了环境归趋模型参数估计方法的研究趋势。     

环境污染和生态破坏经济损失的估算模型

应用江苏省1988—2002年时序数据,建立环境污染与生态破坏经济损失的宏观估算模型,对影响环境污染与生态破坏的限制因子进行定量分析评价。     

基于环境逸度模型的化学物质暴露与风险评估研究进展

工业化学品通过各种迁移转化过程后在环境区间中广泛分布,同时新化学品正被大量的生产并进入环境,使得对于化学品管控的需求和压力不断增加。基于这一背景,多国政府颁布了相应的政策法规对化学品进行管控。除了用相应的政策法规进行预先管控之外,使用基于逸度概念的多介质环境模型来表征化学品的行为与归趋是一个相对简单而有效的方法,不仅适用于环境中存在的现有化学品的暴露评估,也成为各国化学品管理中对新化学品的环境暴露进行预测的有力工具。本文综述逸度概念与方法、相关环境模型、建模过程、应用验证等方面的国内外研究进展,希望能够对我国化学品环境暴露评估与风险评估的模型构建、优化与方法应用提供信息和借鉴。     

A Procedure for Making Optimal Selection of Input Variables for Multivariate Environmental Classifications

Abstract:  Multivariate classifications of environmental factors are used as frameworks for conservation management. Although classification performance is likely to be sensitive to choice of input variables, these choices have been subjective in most previous studies. We used the Mantel test on a limited set of sites for which biological data were available to iteratively seek a definition of environmental space (i.e., intersite distances calculated with a set of appropriately transformed and weighted environmental variables) that had maximal correlation with the same sites described in a biological space. The procedure was used to select input variables for a classification of New Zealand's rivers that discriminates variation in fish communities for biodiversity management. The classification performed (i.e., discriminated biological variation) better than classifications with subjectively chosen variables. The inherently linear measures of environmental distance that underlie multivariate environmental classifications mean that they will perform best if they are defined based on variables for which there is a linear variation in the biological community throughout the entire range of the variable. Classification performance will therefore be improved when variables that have nonlinear relationships with biological variation are transformed to make their relationship with biological turnover more linear and when the contributions of environmental factors that have particularly strong relationships with biological variation are increased by weighting. Our results indicate that attention to the manner in which environmental space is defined improves the efficacy of multivariate classification and other techniques in which the environment is used as a surrogate for biological variation.     

持久性有机污染物环境多介质空间分异模型研究进展

环境多介质空间分异模型能够对持久性有机污染物(POPs)在环境多个介质中空间尺度上的迁移转化和分配过程进行准确、细致和接近真实的描述,是进行POPs的环境多介质归趋模拟和环境风险评价的重要工具.将环境多介质空间分异模型分为环境多介质质量平衡空间区划模型和大气化学传输模型,对目前几种常用的环境多介质空间分异模型GLOBO...     

A Successful Predictive Model of Species Richness Based on Indicator Species

Abstract:  Because complete species inventories are expensive and time-consuming, scientists and land managers seek techniques to alleviate logistic constraints on measuring species richness, especially over large spatial scales. We developed a method to identify indicators of species richness that is applicable to any taxonomic group or ecosystem. In an initial case study, we found that a model based on the occurrence of five indicator species explained 88% of the deviance of species richness of 56 butterflies in a mountain range in western North America. We validated model predictions and spatial transferability of the model using independent, newly collected data from another, nearby mountain range. Predicted and observed values of butterfly species richness were highly correlated with 93% of the observed values falling within the 95% credible intervals of the predictions. We used a Bayesian approach to update the initial model with both the model-building and model-validation data sets. In the updated model, the effectiveness of three of the five indicator species was similar, whereas the effectiveness of two species was reduced. The latter species had more erratic distributions in the validation data set than in the original model-building data set. This objective method for identifying indicators of species richness could substantially enhance our ability to conduct large-scale ecological assessments of any group of animals or plants in any geographic region and to make effective conservation decisions.     

基于环境雌激素评估的卵黄蛋白原研究进展

卵黄蛋白原(Vitellogenin,Vtg)是卵黄蛋白(Vitellins,Vn)的前体.无脊椎动物的Vtg主要在肝胰腺、卵巢或脂肪体合成,脊椎动物主要在肝脏合成.在总结国内外相关研究基础上,对基于环境雌激素评估的Vtg研究进展进行了综述.目前的研究已经证明,Vtg的N末端氨基酸序列在动物进化中既具有高度的保守性,又具有一定的特异性.Vtg作为检测环境雌激素效应的生物标志物之一,在环境雌激素类化合物污染的评价中被广泛采用.Vtg的检测方法包括蛋白直接定量检测和mRNA定量分析,选择检测技术要依据实验设计,对于长时间的暴露实验,可通过检测蛋白来完成,短时间的暴露实验则适合半定量RT-PCR检测VtgmRNA的表达.在Vtg的检测中应考虑动物种属的特异性.     

Imputing Unmeasured Explanatory Variables in Environmental Epidemiology With Application to Health Impact Analysis of Air Pollution

This paper presents the results of a reconsideration of earlier work that finds an association between daily hospital admissions for respiratory distress and daily concentrations of sulphate (lag 1) as well as daily maximum concentrations of ozone (lags 1 and 3). These associations are found even after clustering the data by hospital of admission and accounting for the effects of temperature. We use an adaptation of their generalized estimating equation technique for clustered data, that daily data being for southern Ontario summers from 1983 to 1988. Like them, we adjust for daily maximum temperatures. However, unlike the earlier work returned to ours includes daily average humidity as a potential explanatory variable in our model. Our analysis also differs from theirs in that we cluster the data by census subdivision to reduce the risk of confounding pollutant levels with population size within regions. Moreover, we log-transform the explanatory variables and then high-pass filter the resulting data. We also deviate from the earlier analysis by taking account of measurement error incurred in using surrogate measures of the explanatory variables. To do so we use new methodology designed for our study but of potential value in other applications. That methodology requires a spatial predictive distribution for the unmeasured explanatory variables. Each day about 700 missing measurements for each of these variables can then be imputed over the geographical domain of the study. With these imputations we get a measure of imputation error through the covariance of the predictive distribution. Along with the predictive distribution we require an impact model to link-up with the predictive distribution. We describe that model and show how it uses the imputed measurements of the missing values of the explanatory variables. We also show how through that model, uncertainty about these values is reflected in our analysis and in commensurate uncertainties in the inferences made. Apart from its substantive objectives, our analysis serves to test the new methods with the earlier results serving as a foil. The reassuring qualitative agreement between our findings and the earlier results seems encouraging.     

共存阳离子对砷、硒和钒毒性效应的影响及预测模型研究

为探明并量化共存阳离子存在下含氧阴离子型金属在生物体中的毒性效应,以模式植物小麦(Triticum aestivumL.)为研究对象,通过单一变量控制实验,探究了4种阳离子(Ca⁽²⁺⁾、Mg(2+)、Mg⁽²⁺⁾、Na(2+)、Na⁺和K+和K⁺)对3种典型含氧阴离子型金属(AsO_4+)对3种典型含氧阴离子型金属(AsO_4^(3-)、SeO_3(3-)、SeO_3^(2-)和VO_4(2-)和VO_4^(3-))毒性的影响,并构建了静电作用模型来预测和评估As、Se和V的生态毒性效应与风险。结果表明,Ca(3-))毒性的影响,并构建了静电作用模型来预测和评估As、Se和V的生态毒性效应与风险。结果表明,Ca⁽²⁺⁾对As、Se和V毒性的影响呈现出3种不同的趋势：在相同设计浓度范围内Ca(2+)对As、Se和V毒性的影响呈现出3种不同的趋势：在相同设计浓度范围内Ca⁽²⁺⁾的增加显著引起了As毒性的减弱(Adj.R(2+)的增加显著引起了As毒性的减弱(Adj.R²=0.76,P<0.05)、V毒性的加剧(Adj.R2=0.76,P<0.05)、V毒性的加剧(Adj.R²=0.81,P<0.05),而对Se毒性却没有显著影响。当Mg2=0.81,P<0.05),而对Se毒性却没有显著影响。当Mg⁽²⁺⁾从0.20 mmol·L(2+)从0.20 mmol·L^(-1)增加到2.73 mmol·L(-1)增加到2.73 mmol·L^(-1)时,Se主导形态的半数有效活度值(EC_(50){HSeO+3(-1)时,Se主导形态的半数有效活度值(EC_(50){HSeO+3^-})从40.40 μmol·L-})从40.40 μmol·L^(-1)显著下降为27.98 μmol·L(-1)显著下降为27.98 μmol·L^(-1),即Se毒性增强到原来的1.44倍(Adj.R(-1),即Se毒性增强到原来的1.44倍(Adj.R²=0.79,P<0.05)。静电作用理论能够很好地解释Ca2=0.79,P<0.05)。静电作用理论能够很好地解释Ca⁽²⁺⁾(或Mg(2+)(或Mg⁽²⁺⁾)在显著增强V(或Se)毒性中发挥的作用,将这种静电作用影响纳入考虑成功构建了可以定量预测V(Adj.R(2+))在显著增强V(或Se)毒性中发挥的作用,将这种静电作用影响纳入考虑成功构建了可以定量预测V(Adj.R²=0.88)和Se(Adj.R2=0.88)和Se(Adj.R²=0.95)毒性的静电作用模型。研究结果弥补了目前含氧阴离子型金属生态毒性研究的不足,为含氧阴离子型金属的土壤污染生态风险评估提供了指导与参考。     

Reliability of Conservation Actions Based on Elasticity Analysis of Matrix Models

Abstract: Matrix population models have entered the mainstream of conservation biology, with analysis of proportional sensitivities (elasticity analysis) of demographic rates becoming important components of conservation decision making. We identify areas where management applications using elasticity analysis potentially conflict with the mathematical basis of the technique, and we use a hypothetical example and three real data sets (Prairie Chicken [   Tympanuchus cupido ], desert tortoise [ Gopherus agassizii ], and killer whale [ Orcinus orca ]) to evaluate the extent to which conservation recommendations based on elasticities might be misleading. First, changes in one demographic rate can change the qualitative ranking of the elasticity values calculated from a population matrix, a result that dampens enthusiasm for ranking conservation actions based solely on which rates have the highest elasticity values. Second, although elasticities often provide accurate predictions of future changes in population growth rate under management perturbations that are large or that affect more than one rate concurrently, concordance frequently fails when different rates vary by different amounts. In particular, when vital rates change to their high or low values observed in nature, predictions of future growth rate based on elasticities of a mean matrix can be misleading, even predicting population increase when the population growth rate actually declines following a perturbation. Elasticity measures will continue to be useful tools for applied ecologists, but they should be interpreted with considerable care. We suggest that studies using analytical elasticity analysis explicitly consider the range of variation possible for different rates and that simulation methods are a useful tool to this end.     

Combined Effects of Levels of Protection and Environmental Variables at Different Spatial Resolutions on Fish Assemblages in a Marine Protected Area

Abstract: The links between species–environment relations and species’ responses to protection are unclear, but the objectives of marine protected areas (MPAs) are most likely to be achieved when those relations are known and inform MPA design. The components of a species’ habitat vary with the spatial resolution of the area considered. We characterized areas at two resolutions: 250 m² (transect) and approximately 30,000 m² (seascape). We considered three categories of environmental variables: substrate type, bottom complexity, and depth. We sought to determine at which resolution habitat characteristics were a better predictor of abundance and species composition of fishes and whether the relations with environmental variables at either resolution affected species’ responses to protection. Habitat features accounted for a larger proportion of spatial variation in species composition and abundances than differences in protection status. This spatial variation was explained best by habitat characteristics at the seascape level than at the transect level. Species’ responses to protected areas were specific to particular seascape characteristics, primarily depth, and bottom complexity. Our method may be useful for prioritizing marine areas for protection, designing MPAs, and monitoring their effectiveness. It identified areas that provided natural shelter, areas acting as buffer zones, and areas where fish species were most responsive to protection. The identification of such areas is necessary for cost‐effective establishment and monitoring of MPAs.     

基于生命周期评价理论的建筑物环境影响评价系统

建筑物对环境有着巨大的影响。基于生命周期评价(LCA)理论,从材料的开采生产,建筑物的建造、运行直至建筑物被拆除来研究建筑物的环境影响。在一个涉及建筑材料、建筑设备以及建设场地的环境影响数据库的基础上,开发了一个建筑物的环境影响的评价模型BEPAS(BuildingEnvironmentalPerformanceAnalysisSystem)。模型从3个方面:建筑设备运行、建筑材料和建筑场地来研究建筑的环境影响。最后,测算了一个案例,分析了其环境影响水平。     

基于有机污染物生物有效性的土壤环境质量基准的探讨

我国的土壤污染日益严重,由于污染物对土壤生物产生的毒性效应与其生物有效态含量相关,以污染物总量为指标的土壤环境质量标准已无法满足当前土壤管理的需求,亟需开展以生物有效性为基础的土壤环境质量基准的研究工作。目前对土壤中重金属的生物有效性的研究较为深入,但是针对有机污染物的土壤生物有效性研究相对匮乏。本研究综述了有机污染物在土壤中的结构形态、吸附吸收和迁移转化,以及影响土壤中有机污染物生物有效性的关键因素。从我国有机污染物的污染现状、土壤类型分布情况,以及物种选择3个方面对基于生物有效性的土壤环境质量标准/基准的制定进行探讨,以期为我国根据国情制定适合本土特征的生态安全土壤质量标准提供借鉴。