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Particulate matter (PM) has been linked to a range of serious cardiovascular and respiratory health problems, including premature mortality. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regression model for the estimation of the risk of mortality associated with fine PM and its components across all counties in the conterminous United States. We characterize different sources of uncertainty in the data and model the spatial structure of the mortality data and the speciated fine PM. We consider a flexible Bayesian hierarchical model for a space-time series of counts (mortality) by constructing a likelihood-based version of a generalized Poisson regression model that combines methods for point-level misaligned data and change of support regression. Our results seem to suggest an increase by a factor of two in the risk of mortality due to fine particles with respect to coarse particles. Our study also shows that in the Western United States, the nitrate and crustal components of the speciated fine PM seem to have more impact on mortality than the other components. On the other hand, in the Eastern United States, sulfate and ammonium explain most of the fine PM effect. 相似文献
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BackgroundWe investigated the spatial patterns of multiple myeloma (MM) incidence in the United States (US) between 2013 and 2017 to improve understanding of potential environmental risk factors for MM.MethodsWe analyzed the average county-level age-adjusted incidence rates (“ASR”) of MM between 2013 and 2017 in 50 states and the District of Columbia using the U.S. Cancer Statistics Public Use Databases. We firstly divided the ASR into quintiles and described spatial patterns using a choropleth map. To identify global and local clusters of the ASR, we performed the Spatial Autocorrelation (Global Moran’s I) analysis and the Anselin’s Local Indicator of Spatial Autocorrelation (LISA) analysis. We compared the means of selected demographic and socioeconomic factors between the clusters and counties of the whole US using Welch one-sided t-test.ResultsWe identified distinct spatial dichotomy of the ASR across counties. High ASR were observed in counties in the Southeast of the US as well as the Capital District (metropolitan areas surrounding Albany) and New York City in the state of New York, while low ASR were observed in counties in the Southwest and West of the US. The ASR showed a significant positive spatial autocorrelation. We identified two major high-high local clusters of the ASR in Georgia and Southern Carolina and five major low-low local clusters of the ASR in Alabama, Arizona, New Hampshire, Ohio, Oregon, and Tennessee. The racial population distribution may partly explain the spatial distribution of MM incidence in the US.ConclusionFindings from this study showed distinct spatial distribution of MM in the US and two high-high and five low-low local clusters. The non-random distribution of MM suggests that environmental exposures in certain regions may be important for the risk of MM. 相似文献
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保护生物学家和生态学家早就认识到只有准确地辨识保护对象的空间位置、 范围、 及其相邻的关系(例如边缘)和连接度, 以及依存的地形和气候等生境条件, 才能发现生物种群和生境在空间的扩散与收缩、 增长与灭绝的动态, 揭示分布的格局, 从而系统、 全面地了解保护对象和生境的存在状态、 破碎程度和变化趋势, 进行有效的自然保护。 得益于新兴的空间分析技术, 保护生物学自20世纪90年代以来取得了很大的进步。基于空间分析的保护生物学研究是最近10年左右大力发展的新保护生物学的重要基础。 该文结合作者的研究工作,综述了基于空间分析的保护生物学项目, 探讨了保护生物学发展历史、 主要研究方法与应用、 以及今后的可能发展趋势。 在生物多样性的丰度和分布的空间解绎部分,通过综述世界保护监测中心的图解全球生物多样性的工作, 如国家尺度的生物多样性水平、 植物多样性的分布中心和维管束植物科的多样性等的空间分布 ,介绍了 Dobson等图示美国主要濒危植物、 鸟类、 鱼类和软体动物等4个主要类群在县(County) 为基本空间单位上分布的空间格局, 讨论了生物多样性空间解绎的意义。在第二部分用世界资源研究所的全球森林监测(Global forest watch)项目, 美国的国家保护缺失区分析(GAP analysis)项目, 美国林务局的无路自然区域(Roadless area)保护项目和加拿大自然审计(Nature audit)项目, 以及北美和东亚生物多样性空间分布的比较分析和生物入侵的空间分析等具体实例来说明生物多样性空间分布变化比较分析方法的应用。 过去20年来, 面向空间格局的生态学和保护生物学研究得到了快速的发展, 特别是空间格局的描述、 由地统计演变而成的空间统计、 地理信息系统、 基于个体(或栅格)的空间解绎模拟模型、 基于斑块(Patch)的种群理论及其发展(如复合种群理论, 源 汇模型等)等。在第三部分, 以美国森林破碎度空间格局分析和美国太平洋西北演替后期森林的空间格局分析为例, 介绍了空间格局分析在保护生物学中的应用。 同时介绍了澳大利亚保护生态学家Lindenmayer 和美国著名景观生态学家Franklin 2002年提出的模板(Matrix)保护理论,把保护的眼光不局限在面积不多而且分散的保护区中,应注意景观模板和保护区相邻的原生区域的综合保护, 这样将大大扩展保护的范围, 并且平衡保护与发展的关系。最后, 介绍了在保护生物学中已有一定应用的空间模型和模拟, 包括了空间解绎模型(Spatial explicit model)、 基于过程(Process-based)的空间模拟模型、 面向代理(Agent-based)的空间适应模拟模型(SWAM)以及与此有关的动态全球植被模型(DGVM)。 通过上面的讨论和综述, 预测一个新的保护生物学的分支: 空间保护生物学, 已经逐渐成熟问世, 这门基于现代信息技术和空间技术的新学科已经而且还将为全球生物多样性的研究和保育作出重大的贡献。 相似文献
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Constructing maps of dry deposition pollution levels is vital for air quality management, and presents statistical problems typical of many environmental and spatial applications. Ideally, such maps would be based on a dense network of monitoring stations, but this does not exist. Instead, there are two main sources of information for dry deposition levels in the United States: one is pollution measurements at a sparse set of about 50 monitoring stations called CASTNet, and the other is the output of the regional scale air quality models, called Models-3. A related problem is the evaluation of these numerical models for air quality applications, which is crucial for control strategy selection. We develop formal methods for combining sources of information with different spatial resolutions and for the evaluation of numerical models. We specify a simple model for both the Models-3 output and the CASTNet observations in terms of the unobserved ground truth, and we estimate the model in a Bayesian way. This provides improved spatial prediction via the posterior distribution of the ground truth, allows us to validate Models-3 via the posterior predictive distribution of the CASTNet observations, and enables us to remove the bias in the Models-3 output. We apply our methods to data on SO2 concentrations, and we obtain high-resolution SO2 distributions by combining observed data with model output. We also conclude that the numerical models perform worse in areas closer to power plants, where the SO2 values are overestimated by the models. 相似文献
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O'Hara RB Cano JM Ovaskainen O Teplitsky C Alho JS 《Journal of evolutionary biology》2008,21(4):949-957
The study of evolutionary quantitative genetics has been advanced by the use of methods developed in animal and plant breeding. These methods have proved to be very useful, but they have some shortcomings when used in the study of wild populations and evolutionary questions. Problems arise from the small size of data sets typical of evolutionary studies, and the additional complexity of the questions asked by evolutionary biologists. Here, we advocate the use of Bayesian methods to overcome these and related problems. Bayesian methods naturally allow errors in parameter estimates to propagate through a model and can also be written as a graphical model, giving them an inherent flexibility. As packages for fitting Bayesian animal models are developed, we expect the application of Bayesian methods to evolutionary quantitative genetics to grow, particularly as genomic information becomes more and more associated with environmental data. 相似文献
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Yuzi Zhang Howard H. Chang Qu Cheng Philip A. Collender Ting Li Jinge He Justin V. Remais 《Biometrics》2023,79(2):1507-1519
Passive surveillance systems are widely used to monitor diseases occurrence over wide spatial areas due to their cost-effectiveness and integration into broadly distributed healthcare systems. However, such systems are generally associated with imperfect ascertainment of disease cases and with heterogeneous capture probabilities arising from factors such as differential access to care. Augmenting passive surveillance systems with other surveillance efforts provides a way to estimate the true number of incident cases. We develop a hierarchical modeling framework for analyzing data from multiple surveillance systems that allows for individual-level covariate-dependent heterogeneous capture probabilities, and borrows information across surveillance sites to improve estimation of the true number of incident cases. Inference is carried out via a two-stage Bayesian procedure. Simulation studies illustrated superior performance of the proposed approach with respect to bias, root mean square error, and coverage compared to a model that does not borrow information across sites. We applied the proposed model to data from three surveillance systems reporting pulmonary tuberculosis (PTB) cases in a major center of ongoing transmission in China. The analysis yielded bias-corrected estimates of PTB cases from the passive system and led to the identification of risk factors associated with PTB rates, as well as factors influencing the operating characteristics of the implemented surveillance systems. 相似文献
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Raphael Rehms;Nicole Ellenbach;Eva Rehfuess;Jacob Burns;Ulrich Mansmann;Sabine Hoffmann; 《Biometrical journal. Biometrische Zeitschrift》2024,66(1):2200341
Infectious disease models can serve as critical tools to predict the development of cases and associated healthcare demand and to determine the set of nonpharmaceutical interventions (NPIs) that is most effective in slowing the spread of an infectious agent. Current approaches to estimate NPI effects typically focus on relatively short time periods and either on the number of reported cases, deaths, intensive care occupancy, or hospital occupancy as a single indicator of disease transmission. In this work, we propose a Bayesian hierarchical model that integrates multiple outcomes and complementary sources of information in the estimation of the true and unknown number of infections while accounting for time-varying underreporting and weekday-specific delays in reported cases and deaths, allowing us to estimate the number of infections on a daily basis rather than having to smooth the data. To address dynamic changes occurring over long periods of time, we account for the spread of new variants, seasonality, and time-varying differences in host susceptibility. We implement a Markov chain Monte Carlo algorithm to conduct Bayesian inference and illustrate the proposed approach with data on COVID-19 from 20 European countries. The approach shows good performance on simulated data and produces posterior predictions that show a good fit to reported cases, deaths, hospital, and intensive care occupancy. 相似文献
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The stochasticity of molecular motion results in the existence of multiple kinetically relevant pathways in many biomolecular mechanisms. Because it is highly demanding to characterize them for complex systems, mechanisms are often described with a single-pathway perspective. However, kinetic network analysis and sub-ensemble experimental insight are increasingly demonstrating not only the existence of competing pathways but also the importance of kinetic selection in biology. This review focuses on advances in multiscale kinetic analysis of proteins, which connects molecular level information from simulations to macroscopic data to characterize mechanistic reaction networks and the reactive flux through them. We describe a range of methods used and highlight several examples where kinetic modeling has revealed functional importance of pathway heterogeneity. 相似文献
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Philippe Cubry Ivan Scotti Sylvie Oddou‐Muratorio François Lefèvre 《Molecular ecology resources》2017,17(6):e76-e83
QST is a differentiation parameter based on the decomposition of the genetic variance of a trait. In the case of additive inheritance and absence of selection, it is analogous to the genic differentiation measured on individual loci, FST. Thus, QST?FST comparison is used to infer selection: selective divergence when QST > FST, or convergence when QST < FST. The definition of Q‐statistics was extended to two‐level hierarchical population structures with Hardy–Weinberg equilibrium. Here, we generalize the Q‐statistics framework to any hierarchical population structure. First, we developed the analytical definition of hierarchical Q‐statistics for populations not at Hardy–Weinberg equilibrium. We show that the Q‐statistics values obtained with the Hardy–Weinberg definition are lower than their corresponding F‐statistics when FIS > 0 (higher when FIS < 0). Then, we used an island model simulation approach to investigate the impact of inbreeding and dominance on the QST?FST framework in a hierarchical population structure. We show that, while differentiation at the lower hierarchical level (QSR) is a monotonic function of migration, differentiation at the upper level (QRT) is not. In the case of additive inheritance, we show that inbreeding inflates the variance of QRT, which can increase the frequency of QRT > FRT cases. We also show that dominance drastically reduces Q‐statistics below F‐statistics for any level of the hierarchy. Therefore, high values of Q‐statistics are good indicators of selection, but low values are not in the case of dominance. 相似文献
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Managing populations, either for conservation, harvesting, or control, requires a mechanistic or semi-mechanistic understanding of population dynamics. Here, we investigate how time-since-fire affects demographic transitions in an endangered plant, Dicerandra frutescens ssp. frutescens (Lamiaceae), which is specialized to gaps created by fire. We used a hierarchical Bayesian model to estimate transition probabilities (i.e., the elements of population projection matrices) as a function of time-since-fire and random effects, from 13 years of data on marked individuals in five populations. Using a standard Bayesian criterion to compare models, we find that death becomes increasingly probable and progression increasingly improbable with time-since-fire. The magnitude of some of the time-since-fire effects is substantial: death is 3–5 times more likely for flowering plants >6 years versus 3–6 years post-fire, 3-step progression is almost 7 times less likely, and large flowering plants are more than 6 times more likely to stop flowering. These insights inspire new hypotheses about the underlying cause of decline with time-since-fire, and how it can be managed. Our approach can be used by others who wish to model the effect of an exogenous factor on demography, while rigorously accounting for uncertainty and variability. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. 相似文献
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Multiscale ordination is a technique for examining spatial patterns of several species at several scales. We present a paired-quadrat method (paired quadrat covariance; PQC) to be used in multiscale ordination and test it with artificial data. Multiscale ordination with PQC successfully extracted the salient features of the data set. The method appears to be more sensitive than blocked-quadrat techniques for extracting small-scale patterns. We suggest that PQC will be useful as a complement to existing procedures or as a tool for analysing data from scattered quadrat arrangements.Abbreviations PQC =
Paired Quadrat Covariance
- PQV =
Paired Quadrat Variance
- TTLC =
Two-Term Local Covariance
- TTLQV =
Two-Term Local Quadrat Variance 相似文献
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Kathie Y Sun Daniel Oreper Sarah A Schoenrock Rachel McMullan Paola Giusti-Rodríguez Vasyl Zhabotynsky Darla R Miller Lisa M Tarantino Fernando Pardo-Manuel de Villena William Valdar 《Genetics》2021,218(1)
Female mammals are functional mosaics of their parental X-linked gene expression due to X chromosome inactivation (XCI). This process inactivates one copy of the X chromosome in each cell during embryogenesis and that state is maintained clonally through mitosis. In mice, the choice of which parental X chromosome remains active is determined by the X chromosome controlling element (Xce), which has been mapped to a 176-kb candidate interval. A series of functional Xce alleles has been characterized or inferred for classical inbred strains based on biased, or skewed, inactivation of the parental X chromosomes in crosses between strains. To further explore the function structure basis and location of the Xce, we measured allele-specific expression of X-linked genes in a large population of F1 females generated from Collaborative Cross (CC) strains. Using published sequence data and applying a Bayesian “Pólya urn” model of XCI skew, we report two major findings. First, inter-individual variability in XCI suggests mouse epiblasts contain on average 20–30 cells contributing to brain. Second, CC founder strain NOD/ShiLtJ has a novel and unique functional allele, Xceg, that is the weakest in the Xce allelic series. Despite phylogenetic analysis confirming that NOD/ShiLtJ carries a haplotype almost identical to the well-characterized C57BL/6J (Xceb), we observed unexpected patterns of XCI skewing in females carrying the NOD/ShiLtJ haplotype within the Xce. Copy number variation is common at the Xce locus and we conclude that the observed allelic series is a product of independent and recurring duplications shared between weak Xce alleles. 相似文献
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GLM versus CCA spatial modeling of plant species distribution 总被引：16，自引：0，他引：16
Despite the variety of statistical methods available for static modeling of plant distribution, few studies directly compare methods on a common data set. In this paper, the predictive power of Generalized Linear Models (GLM) versus Canonical Correspondence Analysis (CCA) models of plant distribution in the Spring Mountains of Nevada, USA, are compared. Results show that GLM models give better predictions than CCA models because a species-specific subset of explanatory variables can be selected in GLM, while in CCA, all species are modeled using the same set of composite environmental variables (axes). Although both techniques can be readily ported to a Geographical Information System (GIS), CCA models are more readily implemented for many species at once. Predictions from both techniques rank the species models in the same order of quality; i.e. a species whose distribution is well modeled by GLM is also well modeled by CCA and vice-versa. In both cases, species for which model predictions have the poorest accuracy are either disturbance or fire related, or species for which too few observations were available to calibrate and evaluate the model. Each technique has its advantages and drawbacks. In general GLM will provide better species specific-models, but CCA will provide a broader overview of multiple species, diversity, and plant communities. 相似文献
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