Some simple tests for spatial effects around putative sources of health risk

The need for tests dealing with different features of small area health data is less important with the increase in computation speed of computers and the access to MCMC methods. However there are many situations where exploratory testing could be useful and where MCMC methods are not readily usable or available. In this paper, a number of simple tests are derived for the logistic model for case events. This model assumes that a control disease is available and that the events have a binary label relating to case or control state. The tests are derived from likelihood considerations and Monte Carlo critical regions are examined. A simulated evaluation of the tests is presented in terms of Monte Carlo power. A data example is considered.     

Modeling the risk of invasion and spread of Tuta absoluta in Africa

Tuta absoluta is an invasive insect that originated from South America and has spread to Europe Africa and Asia. Since its detection in Spain in 2006, the pest is continuing to expand its geographical range, including the recent detection in several Sub-Saharan African countries. The present study proposed a model based on cellular automata to predict year-to-year the risk of the invasion and spread of T. absoluta across Africa. Using, land vegetation cover, temperature, relative humidity and yield of tomato production as key driving factors, we were able to mimic the spreading behavior of the pest, and to understand the role that each of these factors play in the process of propagation of invasion. Simulations by inferring the pest’s natural ability to fly long distance revealed that T. absoluta could reach South of Africa ten years after being detected in Spain (Europe). Findings also reveal that relative humidity and the presence of T. absoluta host plants are important factors for improving the accuracy of the prediction. The study aims to inform stakeholders in plant health, plant quarantine, and pest management on the risks that T. absoluta may cause at local, regional and event global scales. It is suggested that adequate measures should be put in place to stop, control and contain the process used by this pest to expand its range.     

Comparison of Bayesian methods for flexible modeling of spatial risk surfaces in disease mapping

Bayesian hierarchical models usually model the risk surface on the same arbitrary geographical units for all data sources. Poisson/gamma random field models overcome this restriction as the underlying risk surface can be specified independently to the resolution of the data. Moreover, covariates may be considered as either excess or relative risk factors. We compare the performance of the Poisson/gamma random field model to the Markov random field (MRF)‐based ecologic regression model and the Bayesian Detection of Clusters and Discontinuities (BDCD) model, in both a simulation study and a real data example. We find the BDCD model to have advantages in situations dominated by abruptly changing risk while the Poisson/gamma random field model convinces by its flexibility in the estimation of random field structures and by its flexibility incorporating covariates. The MRF‐based ecologic regression model is inferior. WinBUGS code for Poisson/gamma random field models is provided.     

Bayesian partitioning for estimating disease risk

This paper presents a Bayesian nonlinear approach for the analysis of spatial count data. It extends the Bayesian partition methodology of Holmes, Denison, and Mallick (1999, Bayesian partitioning for classification and regression, Technical Report, Imperial College, London) to handle data that involve counts. A demonstration involving incidence rates of leukemia in New York state is used to highlight the methodology. The model allows us to make probability statements on the incidence rates around point sources without making any parametric assumptions about the nature of the influence between the sources and the surrounding location.     

The scale-dependent impact of wolf predation risk on resource selection by three sympatric ungulates

Resource selection is a fundamental ecological process impacting population dynamics and ecosystem structure. Understanding which factors drive selection is vital for effective species- and landscape-level management. We used resource selection probability functions (RSPFs) to study the influence of two forms of wolf (Canis lupus) predation risk, snow conditions and habitat variables on white-tailed deer (Odocoileus virginianus), elk (Cervus elaphus) and moose (Alces alces) resource selection in central Ontario's mixed forest French River-Burwash ecosystem. Direct predation risk was defined as the frequency of a predator's occurrence across the landscape and indirect predation risk as landscape features associated with a higher risk of predation. Models were developed for two winters, each at two spatial scales, using a combination of GIS-derived and ground-measured data. Ungulate presence was determined from snow track transects in 64 16- and 128 1-km(2) resource units, and direct predation risk from GPS radio collar locations of four adjacent wolf packs. Ungulates did not select resources based on the avoidance of areas of direct predation risk at any scale, and instead exhibited selection patterns that tradeoff predation risk minimization with forage and/or mobility requirements. Elk did not avoid indirect predation risk, while both deer and moose exhibited inconsistent responses to this risk. Direct predation risk was more important to models than indirect predation risk but overall, abiotic topographical factors were most influential. These results indicate that wolf predation risk does not limit ungulate habitat use at the scales investigated and that responses to spatial sources of predation risk are complex, incorporating a variety of anti-predator behaviours. Moose resource selection was influenced less by snow conditions than cover type, particularly selection for dense forest, whereas deer showed the opposite pattern. Temporal and spatial scale influenced resource selection by all ungulate species, underlining the importance of incorporating scale into resource selection studies.     

北疆牧区雪灾预警与风险评估方法

在分析北疆牧区畜牧业生产与雪灾分布特征的基础上,利用RS、GIS和地面监测资料,从草地抗灾力、家畜承灾体和积雪致灾力3个子系统中选择9个因素作为预警参评因子,用家畜死亡率作为风险评估因子,构建了一个在完全放牧状态下的牧区雪灾预警与风险评估体系和模式.采用多层次综合法和目标线性加权函数法,建立了雪灾预警分级模型、判别模型和风险评估模型,据此可对草地和家畜抵御雪灾的强度和雪灾的风险期望损失进行动态预警与评估.北疆牧区雪灾预警与风险评估模型的精度分别达85%和72%.     

基于多源地理数据精细尺度的武汉市人居环境新型冠状病毒肺炎疫情传播风险评估

新型冠状病毒肺炎的迅速传播和扩散警示着疾病风险评估的重要性。但现有的风险评估方法受数据限制,缺少实时性和准确性。此外,多数研究以行政统计单元作为分析尺度,存在可变面元问题。为解决这些问题,耦合精细尺度下武汉市疫情数据及多源地理数据,基于随机森林算法构建社区尺度的市域疫情传播风险评估模型并进行了疫情风险制图。模型测试精度达到0.85,Kappa系数达到0.70。此外,本研究还建立基于随机森林算法的社区及场所尺度的"空间变量-感染风险"模型,评估了不同场所设施疫情传播的风险程度。研究表明,（1）武汉中心区域感染风险最高并呈现出向外围递减的趋势;（2）感染风险排名前五的一级场所类型分别为购物服务、医疗服务、金融服务、交通设施以及公共设施;（3）小学、中学的疫情传播风险较低,而高等院校传播风险较高;（4）社区尺度下的疫情风险程度,预测购物场所与交通场所是疫情传播风险最高的驱动因子。本研究基于精细尺度提出风险评估新方法,可为未来疾病风险评估提供新思路,为疫情防控提供决策支持,人民群众提供安全保障。     

基于空间分析的保护生物学研究

 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。     

The influence of Triticum aestivum density, sowing pattern and nitrogen fertilization on leaf area index and its spatial variation

We investigated leaf area index (LAI) and its spatial variation early in the growing season in Triticum aestivum (spring wheat) sown in two spatial patterns (standard rows and a uniform pattern), at three densities (204, 449 and 721 seeds m⁻²), and two nitrogen fertilization levels (0 and 80 kg nitrogen ha⁻¹). Our main hypothesis was that a more uniform distribution of individual plants does not affect overall LAI but reduces its spatial variation. We used the number of leaves touching a vertical pin (LAI*) as a measure of LAI. LAI* increased with sowing density, nitrogen fertilization and, contrary to our hypothesis, spatial uniformity. The coefficient of variation of LAI* was higher (1) at lower sowing density, (2) without nitrogen fertilizer and (3) in the row pattern. Both the increase in LAI and the decrease in its variation in more spatially uniform crops may contribute to increased weed suppression and increased yield.     

Mice recognize the center of an enclosure

In recent years, it has been shown that animals can localize the geometric center of an area by reference to the shape of the environment. We trained a group of mice (experimental group) to search for a pellet hidden under sand in the center of a square-shaped dry maze. Three weeks later, they were tested in a triangular enclosure half the size of the training area and a circular enclosure double the size of the training area to see transfer to these enclosures. We compared their searching behavior with that of subjects that had received no training. The results show that the experimental group searched the geometric center of each enclosure in both transfer tests, while the untrained control group walked along the walls. This indicates that the experimental group localized the center not by reference to the absolute distance from the corners but by equal distances from all walls (geometric center).     

Spatio-temporal distribution of Ricania shantungensis (Hemiptera: Ricaniidae) in chestnut fields: Implications for site-specific management

Chestnut is one of most important forest products in Korea. However, Ricania shantungensis, an invasive species, has been increasingly causing economic damage to chestnut. To increase management efficiency of R. shantungensis in chestnut fields, its spatio-temporal distributions were analyzed using spatial analysis by distance indices (SADIE) and semivariogram. Experiments were conducted by observing selected, marked, and geo-referenced trees in two commercial chestnut fields for each developmental stage (i.e., spring egg, nymph, adult, and fall egg) of R. shantungensis from 2017 to 2019. Spatial distributions of R. shantungensis were statistically (P < 0.05) aggregated except for its nymphal stage. Spatial associations of its distributions also showed the statistically (P < 0.05) positive associations regardless of years or developmental stages except for the spatial relationship between egg and nymphal stages. These results indicated that site-specific management for R. shantungensis would be applicable. In application of site-specific management for R. shantungensis, the distance of spatial dependence for nymphs, 60 m, should be considered to minimize reoccurrence possibility and additional samplings. Incorporating site-specific management into pest control program of R. shantungensis could increase its control efficiency in chestnut fields.     

Geographical information system-based forest fire risk assessment integrating national forest inventory data and analysis of its spatiotemporal variability

Improvements in forest fire risk estimation and mapping fire risk zones are vital to reduce the negative impacts of fire and to facilitate planning for the protection of forested areas. This is especially important for places with little previous data on fire history. This paper presents an improved conceptual scheme for the assessment and mapping of fire risk using a Forest Resource Inventory Database, based on four aspects of topographical, human activity, climate, and forest characteristics factors. We selected 12 variables based on our defined conceptual scheme to generate a synthetic forest fire risk index (FRI) to quantify potential forest fire risk and map risk zones in the Wuyishan Scenery District (WSD), a world heritage site that located in the northwest of Fujian province, People's Republic of China. Spatial statistics were used to examine the spatio-temporal variation of FRI. The results showed the main fire risk zones in the WSD were in the low or moderate categories (accounting for 76.7% of the total area of the WSD in 1997 and 79.2% in 2009). The spatial heterogeneity of FRI showed anisotropic variability characteristics which changed over time. From 1997 to 2009, there was an increasing influence from both autocorrelation factors and random factors. Moreover, these factors played almost equally important roles in forest fire processes in the WSD. The fire risk map was applied to assess the vulnerability of cultural heritage resources in the WSD. Most were located in low- or moderate-risk areas, and therefore would be at low risk from potential fire damage.     

Dermatoglyphic variation in Europe

We describe the geographic variation patterns of 236 dermatoglyphic variables (118 for each sex) for 74 samples in Europe. Using principal components analysis and rotating to simple structure, we simplified these patterns to the first 20 axes, representing 74.2% of covariation. We then used heterogeneity tests, interpolated surfaces, one-dimensional and directional correlograms, and distances between correlograms to analyze the factor scores of these 20 axes. We also ordinated the 74 localities. The data are remarkable for showing little spatial autocorrelation, despite significant heterogeneity among localities. Only three factor axes exhibit consistently significant correlograms, indicating that there are few spatial patterns in the original variables in Europe. Almost all correlations between pairs of variables occur within serially homologous character sets and are thus developmentally determined. There is some support for demic diffusion from the southeast in finger patterns and ridge counts. We compare these results to those of previous studies and note that Lapps and Icelanders are outliers with respect to both genetics and finger tip variables, whereas Tatars are outliers with respect to craniometrics and dermatoglyphics. © 1996 Wiley-Liss, Inc.     

Seed and microsite limitations of recruitment and the impacts of post-dispersal seed predation at the within population level

Seed predation may cause important seed losses in plant populations, but its impact on the dynamics of populations will depend on the degree of seed or microsite limitations for recruitment. Seed losses will only affect recruitment if it is seed limited. The nature of recruitment limitation (seeds or microsites) is usually ascribed to whole plant populations but it may vary within populations among microhabitats and habitats. Thus, the potential impact of seed predation will also vary within the population, being highest where recruitment is seed limited. The impact to the whole population will depend on the spatial concordance between the intensity of seed predation and that of seed limitation. Recruitment limitations (with seed addition experiments), seed predation (with seed removal experiments), and the dynamics of seed availability in the soil (with soil samples taken both after seed dispersal and before the following dispersal event) of the shrub Corema album (Empetraceae) were investigated in dunes in NW Spain, at microhabitats ‘open ground’, ‘underneath C. album ♀’, and ‘underneath C. album ♂’ at two habitats, sparse and dense scrub. The nature of recruitment limitation (seeds vs. microsites) varied within the population. It was seed limited in the microhabitat ‘open ground’ and microsite limited under shrub cover. The spatial patterns of seedling recruitment were unrelated to seed availability but strongly affected by germination requirements. The spatial discordance between seed availability and recruitment implies a crucial constraint for processes affecting seed availability (seed predation but also e.g., dispersal) to impact recruitment. They will not affect its spatial pattern but only its quantity as long as they act in those sites selected by seeds to germinate. Seed predation was highest underneath mother plants and lowest in open ground. Thus, its potential impact is low, as it is centred where recruitment is not seed limited. This study shows that the analysis of seed predation in relation to recruitment limitations at smaller spatial scales within the population provides more insight to understand its impact.     

Spatial rotations and transpositions in orangutans (<Emphasis Type="Italic">Pongo pygmaeus</Emphasis>) and chimpanzees (<Emphasis Type="Italic">Pan troglodytes</Emphasis>)

This study investigated the ability of three chimpanzees and three orangutans to track the position of a reward after a series of displacements. The reward was placed under one of two opaque containers resting on a platform. Experiment 1 investigated rotational displacements in which the platform was rotated 0°, 180°, or 360°. Experiment 2 investigated transpositional displacements in which the platform remained stationary while the containers either remained stationary, or swapped their positions (in a one- two- or three-step sequence). In both experiments, the initial position of the reward was indicated either by directly showing the reward under the containers, or by placing a landmark, which had been previously associated with the reward, on top of the baited container. Subjects successfully tracked the reward through rotations and transpositions when they had seen it, but their performance substantially deteriorated when the landmark indicated the reward's initial position, even though subjects successfully used the landmark to find the reward in the absence of displacements. This decrease was especially pronounced in rotational displacements. A language-trained orangutan outperformed all the other apes and solved all problems.     

Spatial flow analysis of water pollution in eco-natural systems

The disjunction of ecological and socioeconomic sciences is one of the main obstructions in current human–natural integrated systems research. Therefore, gridded GIS technology is introduced in an attempt to achieve the spatial flow analysis of water pollution in eco-natural systems. With this unified GIS platform, an input–output table and one-dimensional water quality model are chosen to manifest the spatial economic flows and spatial natural flows of water pollution separately. Finally, the comprehensive effect of the spatial circulation of water pollution in eco-natural systems is assessed. A case study of the framework is carried out in the Changzhou District of Taihu Lake, China, and the main results show the following: (1) COD (chemical oxygen demand) direct emissions represent the characteristics of high intensity and clustering in industrial regions; control unit 8 is the largest secondary emissions unit, representing up to 41.79% of the total, whereas the emissions of the primary industry tend to be low intensity and widespread. (2) The gray virtual water flow from the primary industry to other heavy industries (except the chemical industry) is the main flow type; the transfer amount adds up to 2512 t, and the inter-units with the largest occupation of water environment capacity (WEC) upstream to downstream are 8–9, nearly up to 1548 t. (3) Under the interaction of positive and negative functions of economic flows and natural flows, the final effect of pollution transfer may be offset, environmental degradation or environmental improvement. This study could provide a basis for ecological compensation, environmental exteriority and optimization of industrial structure layouts.     

Estimating the environmental Kuznets curve for ecological footprint at the global level: A spatial econometric approach

The national ecological footprint of both consumption and production are significantly spatially autocorrelated at global level. This violates the assumption of independently distributed errors of most conventional estimation techniques. Using a spatial econometric approach, this paper re-examine the relationship between economic growth and environmental impact for indicator of ecological footprint. The results do not show evidence of inverted U-shape Environmental Kuznets Curve. The domestic ecological footprint of consumption (or production) was obviously influenced by the ecological footprint of consumption (or production), income and biocapacity in neighborhood countries. We also found that the consumption footprint is more sensitive to domestic income, while production footprint is more sensitive to domestic biocapacity, which is often unnoticed in EKC hypothesis analyses that focus exclusively on the consumption-based or production-based indictors.     

红松老龄林主要树种的空间异质性特征与比较的定量研究

 空间异质性研究对认识不同尺度上的生态系统结构、功能和过程具有重要的理论意义。采用地统计学理论和方法,通过空间异质性特征和比较研究了我国东北红松老龄林中主要树种,即红松(Pinus koraiensis)、云杉(Picea koraiensis)、冷杉(Abies nephrolepis)、枫桦(Betula costata)和紫椴(Tilia amurensis)的空间异质性程度、空间异质性组成、尺度和格局问题。结果表明：红松老龄林中主要树种虽然生长在同一林分中,但是它们的空间异质性与格局具有明显的差异。红松的空间异质性程度最高,分数维较低,其空间异质性主要由空间自相关部分组成,在450m的尺度内,具有明显的空间格局。枫桦的空间异质性程度最低,分数维最大,空间异质性主要由随机部分组成,在大于100m的尺度上不存在明显的空间格局。云杉和冷杉由于生长的立地相似,因此具有相似的空间异质性特征和格局。紫椴是红松最重要的伴生树种,其空间异质性程度、空间异质性组成、尺度和格局等方面与红松接近。红松老龄林中主要树种空间异质性与格局在一定尺度上的差异,反映这些树种在生态系统中具有不同的生态学功能和过程。