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611.
Andrew C. Parnell Donald L. Phillips Stuart Bearhop Brice X. Semmens Eric J. Ward Jonathan W. Moore Andrew L. Jackson Jonathan Grey David J. Kelly Richard Inger 《Environmetrics》2013,24(6):387-399
In this paper, we review recent advances in stable isotope mixing models (SIMMs) and place them into an overarching Bayesian statistical framework, which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixture. The most widely used application is quantifying the diet of organisms based on the food sources they have been observed to consume. At the centre of the multivariate statistical model we propose is a compositional mixture of the food sources corrected for various metabolic factors. The compositional component of our model is based on the isometric log‐ratio transform. Through this transform, we can apply a range of time series and non‐parametric smoothing relationships. We illustrate our models with three case studies based on real animal dietary behaviour. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
612.
Kathryn M. Irvine Jamie Thornton Vickie M. Backus Matthew G. Hohmann Erik A. Lehnhoff Bruce D. Maxwell Kurt Michels Lisa J. Rew 《Environmetrics》2013,24(6):407-417
Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non‐adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un‐sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
613.
Environmental researchers often face the problem of assessing which potiential stressors in an environment actually are stressors. In making these assessments they often have data sets that have missing values for many of the stressors. Techniques such as Multiple Imputation, Data Augmentation via the EM algorithm have been proposed to deal with the missing value problem. Then standard deterministic model search methods such as forward, backward, stepwise, Mallows Cp, etc. are then applied to these imputed datasets to determine the single “best” model. Using this “best” model all inferences concerning which potential stressors actually induce stress are determined. This work proposes a probabilistic model search to determine the stressors in an environment while taking into account the problem of missing values. This method is applied to an ecological data set concerning benthic health collected by the Ohio Environmental Protection Agency. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
614.
We compare ground rainfall with purely deterministic Regional Climate Model (RCM) simulations within a Bayesian framework. A truncated normal model is fitted to the observed ground data to represent spatial variability. The predictive posterior distribution of the spatially aggregated rainfall is obtained by using a Markov chain Monte Carlo method and compared to the RCM simulations. Also, the predictive posterior distribution of the RCM output is downscaled using the truncated normal model and obtaining pointwise rainfall estimates from aerial observations which are compared to the ground observations. These two procedures allow us to determine if the differences between the two sources of information are compatible with the variability predicted by the spatial model. Also, point rainfall estimates at locations without rainfall measurements conditioned on RCM observations can be obtained. We considered a set of data from an area in Nebraska for which time is considered fixed and rainfall is accumulated monthly. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
615.
We present a novel method for analysing spatial data when response data is given at a finite number of locations and the aim is to predict the response at a new location, where only a short run of data is available. This is the type of dataset that is typically available when attempting to analyse wind velocity data. We demonstrate our method, and compare it to that introduced by Haslett and Raftery on a set of data collected from the island of Crete in Greece. Typically the distance between locations is used to define the correlation matrix between responses at distinct locations even though this cannot always be justified. The peculiarity presented in our data is that the sites are in a complex topography so differences in the local characteristics of the wind station the direction of the prevailing winds, and other unobserved covariates can all lead to unsuitable model fitting. We use a nonlinear model to avoid these problems and demonstrate its predictive power in relation to the dataset under study. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
616.
An increasingly important concern in epidemiological and toxicological studies of environmental exposures is the need to combine information from diverse sources that relate to a common endpoint. This is clearly a statistical activity, but statistical techniques for data combination are still only developmental. Herein, we illustrate some current applications of combining information in environmental epidemiology and toxicology, with emphasis on the burgeoning use of meta-analyses for environmental settings. Our goal is to inform readers about modern statistical techniques useful for combining environmental information, with emphasis on more recently developed approaches. 相似文献
617.
618.
In this paper, a simple model for analysing variability in radon concentrations in homes is tested. The approach used here involves two error components, representing additive and multiplicative errors, together with variation between-houses. We use a Bayesian approach for our analysis and apply this model to two datasets of repeat radon measurements in homes; one based on 3-month long measurements for which the original measurements were close to the current UK Radon Action Level (200 Bq m−3), and the other based on 6-month measurement data (from regional and national surveys), for which the original measurements cover a wide range of radon concentrations, down to very low levels. The model with two error components provides a better fit to these datasets than does a model based on solely multiplicative errors. 相似文献
619.
农田温室气体净排放研究进展 总被引：3，自引：0，他引：3
农业是温室气体排放的主要排放源之一,农业温室气体减排对全球温室气体排放具有重要贡献,研究农田温室气体净排放潜力亦具有重要现实意义.本文阐述了农田温室气体净排放的涵义,并归纳总结了耕作方式、施肥、水分管理、间套作等农业措施对农田土壤有机碳(SOC)含量、农田土壤N2O和CH4、农田生产物资的使用所造成的温室气体(主要为CO2、N2O和CH4)排放的影响,结果表明:保护性耕作总体能提高表层SOC含量,减少CH4排放,但减少农田土壤N2O排放的研究尚存在一定的争议,耕作方式亦影响投入,从而影响温室气体的排放;施肥(特别是配施)能提高SOC含量.施氮肥越多,N2O排放量越大,而CH4主要受有机物料的影响较大;水分对减少N2O和CH4排放有相反作用,需综合进行平衡管理;不同的作物品种、间套作模式或促进或减少温室气体排放.此外,本文指出了国外在该领域的研究注重从系统角度考虑农田温室气体排放,而国内的研究则非常少,提出我国农田温室气体净排放可作为未来研究的一个重点,并对未来研究内容进行了初步归纳总结. 相似文献
620.
新型农村社会养老保险收入再分配效应研究 总被引：1，自引：0，他引：1
通过政策分析发现,新农保制度的收入再分配效应主要体现在政府补贴方面,在本质上是财政的再分配,其中个人账户部分体现为代内再分配,基础养老金部分体现为代际再分配。新农保制度几乎对所有制度内人群都具有正的收入再分配效应。以净转移额来度量新农保收入再分配效应的程度,通过建立模型进行测算发现:在现行财政补贴政策下,新农保的收入再分配偏向于选择较高档次缴费的人群、缴费困难群体、寿命长的人群、女性农民、长期缴费的人群以及农村计划生育家庭;政府缴费补贴越多,个人账户投资收益率越高,基础养老金调整系数越大,参保人养老金的净转入额就越多;"捆绑式缴费"政策产生了逆向的收入再分配效应。 相似文献