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1.
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2.
植物病害时空流行动态模拟模型的构建   总被引：4，自引：0，他引：4  
 一个描述在二维空间中单一种植或混合种植的植物群体内病害时、空流行动态的计算机随机模拟模型构建完成。模型由寄主、病原2个组分和病斑产孢、孢子传播、孢子着落、孢子侵染、病斑潜育、寄主生长、病害控制等一系列代表病害流行生物学过程的子模型构成。模型采用了面向对象的程序设计方法,用C++语言编写,能以病害流行曲线图、空间分布图、数据列表等方式显示模拟结果。测试结果表明:模型能反映植物病害流行过程的本质规律,既可作为植物病害流行学教学工具,帮助学生理解病害流行的时、空动态规律和不同因子对病害流行的影响,也可以作为研究工具,对流行学的某些理论问题进行模拟研究  相似文献   

3.
We propose and illustrate a likelihood-based method for fitting spatio-temporal stochastic models for the spread of a plant disease to experimental observations. The models considered are individual-based, with members of the population occupying discrete sites on a two-dimensional lattice. The disease is assumed to be characterized by presence/absence, and infection of susceptible individuals by infected individuals is represented as a stochastic process. The method described can be applied to estimate parameters in models of this kind when observations consisting of temporal sequences of disease maps are available. The use of measures of spatial aggregation as measured from simulated and real epidemics is proposed as a means of assessing the relative merits of alternative models for the spread of a disease. To illustrate the technique we fit and compare two models, which differ in the relationship between infective pressure and distance, to observations of an epidemic of citrus tristeza virus (CTV). It is demonstrated that a model in which this relationship is a power-law is superior to one which uses a negative exponential and the importance of model choice for the design of control strategies is discussed briefly.  相似文献   

4.
Coffee wilt disease (CWD) caused by Fusarium xylarioides, considered to be a soil-inhabiting fungus, is endemic in several African countries, affecting commercially important coffee species and causing serious economic losses. Coffee wilt disease development in naturally infected Coffea canephora fields at the Coffee Research Institute in Uganda was assessed from April 2001 to March 2006 to generate information about temporal and spatial spread of the disease. Maps of diseased trees were also generated from the data. Semi-variance analysis was performed on the data to show the spatio-temporal structure of disease. Host influence on the spatio-temporal structure was deduced from the distribution pattern of diseased and healthy trees and analysis of variance. Results show that the temporal disease epidemic progress was slow. The disease was found to spread from initial infections to healthy neighbouring trees, resulting in an aggregated pattern. An infected tree could infect up to three healthy trees away, in any direction. Disease foci formed and expanded with time, coalescing but punctuated in spots planted with resistant hosts. There were varying levels of susceptibility among host genotypes, affecting the rates and levels of epidemic development. The implications of the findings to the control of CWD are discussed.  相似文献   

5.
The spatial and temporal distribution of dicarboximide-resistant strains of Monilinia fructicola were investigated in six peach and nectarine orchard blocks in 1987–89 using a dispersion index (Lloyd's Patchiness Index, LPI), and spatial, temporal and spatio-temporal autocorrelation analyses (Moran's Coefficient, I ). The LPI values indicated that resistant strains were aggregated in all blocks in all years. Spatial correlations were not significant beyond one quadrat for any spatial proximity pattern in five of six blocks. Thus the spread of resistant strains was mostly restricted to the vicinity of the original focus. An absence of significant temporal correlation between years in five of the six blocks indicated poor persistence of resistant strains at specific locations. Only one significant temporal correlation was detected at one block and this could have arisen by chance. Significant spatio-temporal correlation was not detected, suggesting that there was no focus expansion or carry-over of resistant strain inoculum from the previous sampling date. Spatial, temporal and spatio-temporal autocorrelation analyses were consistent with previously reported laboratory results that resistant strains had not acquired all the necessary characteristics to remain in, or dominate, field populations. The spatial pattern of brown rot incidence was investigated at one block in a separate study in 1988 and 1989. There were no significant spatial correlations for brown rot incidence in 1988 for any of the spatial proximity patterns analysed. In 1989, however, significant correlations indicated ellipsoid aggregates of brown rot orientated along the orchard rows.  相似文献   

6.
Analysing epidemics in time and space   总被引：3，自引：2，他引：1  
Simple models of disease increase in time and space are developed by considering the rate of isopath movement (change in distance of a given level of disease in unit time) from a focal centre. Linear equations for simultaneously estimating parameters of temporal progress and spatial spread are derived for different types of epidemics. The uses of the models in estimation and interpretation are demonstrated by reference to published epidemic data.  相似文献   

7.
Xu XM  Ridout MS 《Phytopathology》1998,88(10):1000-1012
ABSTRACT A stochastic model that simulates the spread of disease over space and time was developed to study the effects of initial epidemic conditions (number of initial inocula and their spatial pattern), sporulation rate, and spore dispersal gradient on the spatio-temporal dynamics of plant disease epidemics. The spatial spread of disease was simulated using a half-Cauchy distribution with median dispersal distance mu (units of distance). The rate of temporal increase in disease incidence (beta(I), per day) was influenced jointly by mu and by the sporulation rate lambda (spores per lesion per day). The relationship between beta(I) and mu was nonlinear: the increase in beta(I) with increasing mu was greatest when mu was small (i.e., when the dispersal gradient was steep). The rate of temporal increase in disease severity of diseased plants (beta(S)) was affected mainly by lambda: beta(S) increased directly with increasing lambda. Intraclass correlation (kappa(t)), the correlation of disease status of plants within quadrats, increased initially with disease incidence, reached a peak, and then declined as disease incidence approached 1.0. This relationship was well described by a power-law model that is consistent with the binary form of the variance power law. The amplitude of the model relating kappa(t) to disease incidence was affected mainly by mu: kappa(t) decreased with increasing mu. The shape of the curve was affected mainly by initial conditions, especially the spatial pattern of the initial inocula. Generally, the relationship of spatial autocorrelation (rho(t,k)), the correlation of disease status of plants at various distances apart, to disease incidence and distance was well described by a four-parameter power-law model. rho(t,k) increased with disease incidence to a maximum and then declined at higher values of disease incidence, in agreement with a power-law relationship. The amplitude of rho(t,k) was determined mainly by initial conditions and by mu: rho(t,k) decreased with increasing mu and was lower for regular patterns of initial inocula. The shape of the rho(t,k) curve was affected mainly by initial conditions, especially the spatial pattern of the initial inocula. At any level of disease incidence, autocorrelation declined exponentially with spatial lag; the degree of this decline was determined mainly by mu: it was steeper with decreasing mu.  相似文献   

8.

Knowing the patterns of Black Sigatoka development is essential to propose adequate disease management practices and evaluate their effects, which can be achieved through temporal analysis by integrating the evolving interactions of the pathosystem components, expressed by data on cumulative incidence and severity, and summarizing these data in a disease progress curve. Airborne spores are essential components for the progression of an epidemic in the context of a specific pathosystem. In this perspective, the spore count is an essential approach to assess and model an epidemic. This study evaluated the temporal dynamics of Black Sigatoka in a banana plantation in the Ribeira Valley, state of São Paulo, Brazil, while simultaneously performing a year-long evaluation of fungal spore aerobiology. The disease was intense during the rainy season, but the leaf emergence rate was high enough for quickly inverting the severity peak (between 169 and 197 days of evaluation). After that, the disease severity raised until reach the higher rates (around the score 7 out of 8). The disease progress curve of Black Sigatoka showed peaks of extreme severity, one in the rainy and another in the dry season, with high levels of ascospores in the air. The ascospore concentration and the severity of the disease correlated significantly on the same day of sampling and 15 days after ascospore sampling, corresponding to the average latency period of the disease in the region. The patterns of the disease progress curve in both peaks fitted the monomolecular model, with higher rates of disease increase in the rainy season.

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9.
The Linum marginale–Melampsora lini plant–pathogen interaction has been studied extensively with regard to its epidemiology and population genetic structure (host resistance and pathogen virulence) in a natural metapopulation. In this study, this system was used in an experimental metapopulation approach to investigate explicitly how the distance (degree of isolation) between local population patches influences disease dynamics within a growing season, as well as the genetic structure of pathogen populations through stochastic colonization and extinction processes. The experimental design centred on four replicate sets of populations, within which patches were spaced at increasingly greater distances apart. Each patch consisted of an identical set of host and pathogen genotypes, with each pathogen genotype having the ability to attack only one of four host-resistance types. Over the 2 years of the experiment, the results showed clear 'boom-and-bust' epidemic patterns, with the strongest determinant of disease dynamics within a growing season being the identity of particular host–pathogen genotypic combinations. However, there were also significant effects of spatial structure, in that more isolated patches tended to exhibit lower levels of disease during epidemic peaks than patches that were close together. Extinction of pathogen genotypes from individual populations was positively related to the severity of disease during preceding epidemic peaks, but negatively related to the level of disease present at the final census prior to overwintering. The probability of recolonization of pathotypes into populations during the second growing season was most strongly related to the distance to the nearest neighbouring source population in which a given pathotype was present. Overall, these results highlight the importance of spatial scale in influencing the numerical and genetical dynamics of pathogen populations.  相似文献   

10.
Tree canopies are architecturally complex and pose several challenges for measuring and characterizing spatial patterns of disease. Recently developed methods for fine-scale canopy mapping and three-dimensional spatial pattern analysis were applied in a 3-year study to characterize spatio-temporal development of pre-harvest brown rot of peach, caused by Monilinia fructicola, in 13 trees of different maturity classes. We observed a negative correlation between an index of disease aggregation and disease incidence in the same tree (r?=??0.653, P?<?0.0001), showing that trees with higher brown rot incidence had lower aggregation of affected fruit in their canopies. Significant (P?≤?0.05) within-canopy aggregation among symptomatic fruit was most pronounced for early-maturing cultivars and/or early in the epidemic. This is consistent with the notion of a greater importance of localized, within-tree sources of inoculum at the beginning of the epidemic. Four of five trees having >10 blossom blight symptoms per tree showed a significant positive spatial association of pre-harvest fruit rot to blossom blight within the same canopy. Spatial association analyses further revealed one of two outcomes for the association of new fruit rot symptoms with previous fruit rot symptoms in the same tree, whereby the relationship was either not significant or exhibited a significant negative association. In the latter scenario, the newly diseased fruit were farther apart from previously symptomatic fruit than expected by random chance. This unexpected result could have been due to uneven fruit ripening in different sectors of the canopy, which could have affected the timing of symptom development and thus led to negative spatial associations among symptoms developing over time in a tree.  相似文献   

11.
ABSTRACT The general Kermack and McKendrick epidemic model (K&M) is derived with an appropriate terminology for plant diseases. The epidemic dynamics and patterns of special cases of the K&M model, such as the Vanderplank differential-delay equation; the compartmental healthy (H), latent (L), infectious (S), and postinfectious (R) model; and the K&M model with a delay-gamma-distributed sporulation curve were compared. The characteristics of the disease cycle are summarized by the basic reproductive number, R(0), and the normalized sporulation curve, i(tau). We show how R(0) and the normalized sporulation curve can be calculated from data in the literature. There are equivalences in the values of the basic reproductive number, R(0), the epidemic threshold, and the final disease level across the different models.However, they differ in expressions for the initial disease rate, r, and the initial infection, Q, because the values depend on the sporulation curve. Expressions for r and Q were obtained for each model and can be used to approximate the epidemic curve by the logistic equation.  相似文献   

12.
Citrus postbloom fruit drop (PFD) is caused by Colletotrichum acutatum and C. gloeosporioides. These pathogens attack the flowers and cause premature fruit drop and the retention of fruit calyces. This study was designed to characterize the spatial and temporal dynamics of PFD in commercial citrus‐growing areas to better understand the disease spread. Experiments were carried out in three young orchards (500 trees each) in two municipalities in Sao Paulo State, Brazil. Symptoms of PFD on the flowers and presence of persistent calyces were assessed in each of three orchards for three years. Logistic, Gompertz and monomolecular models were fitted to the incidence data over time from the trees with symptoms. The spatial pattern of diseased trees was characterized by a dispersion index and by Taylor′s power law. An autologistic model was used for the spatiotemporal analysis. The logistic model provided the best fit to the disease incidence data, which had a fast progress rate of 0·53 per day. During the early epidemic of PFD, the spatial pattern of diseased trees was random, which suggested that inoculum spread was due to mechanisms other than rain splash. As the disease incidence increased (up to 12·6%), the spatial pattern of diseased trees became aggregated. The rapid rate of disease progress and the distribution of PFD suggest that dispersal of the pathogen is possibly related to a mechanism other than splash dispersal, which is more typical of other fruit diseases caused by Colletotrichum spp.  相似文献   

13.
 本文引入模糊(Fuzzy)集论中基于模糊等价关系的模糊聚类分析方法,将发病数量(病害强度)、空间和时间动态的相互关系联系起来作为统一整体,研究了稻纹枯病田间流行动态。以平均发病株数(X)、聚集度指标(Ṁ/M)和发病丛率(P)作为群体动态的特征测度。从整体水平上,将对病害流行系统的考察,化成对若干亚系统(若干阶段)来研究,使复杂的系统得以简化,为深入定量研究和刻划纹枯病流行动态进行了初步尝试。作为一种新的研究方法,文中给出了具体的应用过程。  相似文献   

14.
Spread patterns of a Grapevine leafroll-associated virus 1 (GLRaV-1) epidemic and a mealybug infestation survey over 10 year were recorded in two Burgundy French vineyards to investigate the relation between them. The temporal evolution of leafroll spread at both study sites was compared on disease incidence data with logistic regression models. We first tested if the spatial distribution of the disease and the mealybug were aggregated using permutation methods, then we tested the independence between the two spatial patterns by randomly shifting one pattern. In Bonzon, an increase from 5 % to 86 % of leafroll prevalence was observed over an 8-year time span, whereas leafroll prevalence remained stable around 5 % in Marsannay-la-Côte during the same period. In Bonzon, the disease spread rapidly from older neighbouring vineyards in four main patches while no spread of the disease was recorded from infected vines in Marsannay-la-Côte. The mealybug Phenacoccus aceris was recorded on 74 % of vines in Bonzon throughout the study and only 6 % of vines in Marsannay-la-Côte. In the latter location, the disease was not associated with the presence of the mealybug, so that it may have arisen from infected plant material escaping the sanitary inspection. In Bonzon, the significant statistical correlation between the mealybug distribution and diseased plants suggests that P. aceris was responsible for the rapid spread of GLRaV-1 in the vineyard. This is the first report of GLRaV-1 natural spread in Europe.  相似文献   

15.
The optimization of management strategies for plant diseases is a difficult task because of the complexity and variability of epidemic dynamics. Thanks to their ability to numerically simulate many scenarios, models can be used to estimate epidemiological parameters, assess the effectiveness of different management strategies and optimize them. This article presents the PESO (parameter estimation–simulation–optimization) modelling framework to help improve plant disease management strategies. This framework is based on (i) the characterization of the epidemic dynamics to estimate key epidemiological parameters, (ii) the use of spatially explicit models to simulate epidemic dynamics and disease management, and (iii) the use of numerical optimization methods to identify better management strategies. This approach is generic and can be applied to many diseases. The work presented here focuses on sharka (caused by Plum pox virus), which has a worldwide impact on the Prunus industry, and is associated with huge disease management costs in many countries, especially in France.  相似文献   

16.
In this paper, we attempted to determine the most stable or unstable regions of vegetation cover in Mongolia and their spatio-temporal dynamics using Terra/MODIS Normalized Difference Vegetation Index(NDVI) dataset, which had a 250-m spatial resolution and comprised 6 periods of 16-day composited temporal resolution data(from 10 June to 13 September) for summer seasons from 2000 to 2012. We also used precipitation data as well as biomass data from 12 meteorological stations located in 4 largest natural zones of Mongolia. Our study showed that taiga and forest steppe zones had relatively stable vegetation cover because of forest characteristics and relatively high precipitation. The highest coefficient of variation(CV) of vegetation cover occurred frequently in the steppe and desert steppe zones, mainly depending on variation of precipitation. Our results showed that spatial and temporal variability in vegetation cover(NDVI or plant biomass) of Mongolia was highly dependent on the amount, distribution and CV of precipitation. This suggests that the lowest inter-annual CV of NDVI can occur during wet periods of growing season or in high precipitation regions, while the highest inter-annual CV of NDVI can occur during dry periods and in low precipitation regions. Although the desert zone received less precipitation than other natural zones of the country, it had relatively low variation compared to the steppe and desert steppe, which could be attributed to the very sparse vegetation in the desert.  相似文献   

17.
The use of cultivar mixtures is increasingly practical in wheat stripe rust management. Field experiments with wheat cultivar mixtures were conducted to determine their effects on temporal and spatial patterns of stripe rust epidemics in three regions. In the Beijing and Gangu fields, where the epidemics were caused by artificial inoculation, disease incidence and the area under the disease progress curve (AUDPC) of the cultivar mixtures were significantly lower (P < 0.05) than those of the susceptible pure stands. We defined the relative effectiveness of cultivar mixture on disease development related to that in pure stands (REM). The results demonstrated that in many treatments of mixtures of susceptible cultivar with resistant cultivars at various ratios in different locations, their effects on disease reduction were positive (REM < 1). The reduction of epidemic rate in cultivar mixtures expressed in either early season or late season depended on the initial pattern of disease and cultivar mixture treatments. Semivariograms were used to determine the spatiotemporal patterns of disease in the Gangu field. The spatial analysis showed clear spatial patterns of the disease in all four directions of the fields on susceptible pure stands but not on cultivar mixtures. The results implied that the mechanisms of cultivar mixture on disease management might include the interruption of disease spatial expansion and a physical barrier to pathogen inoculum by resistant cultivars.  相似文献   

18.
Ferrandino FJ 《Phytopathology》2004,94(11):1215-1227
ABSTRACT The incomplete sampling of a binary epidemic is nothing more than the overlap of two spatial patterns: the pattern of diseased plants and the pattern of sampled points. Thus, the information on the spatial arrangement of diseased plants obtained from such a sampling explicitly depends on the geometric locations of the sampled points. A number of procedures for sampling disease incidence are examined. These include samples placed on a regular grid, spatially clustered samples, randomly selected samples, and samples specified by a nested fractal design. The performance of these various sampling schemes was examined using simulated binary epidemics with varying degrees of spatial aggregation over different length scales, generated using a Neyman-Scott cluster process. A modification of spatial correlation analysis specifically geared to binary epidemics is derived and shown to be equivalent to a X(2) test comparing the number of infected plant pairs to that expected from a spatially random epidemic. This analysis was applied to the data obtained using the various sampling schemes and the results are compared and contrasted. For the same number of sampling points, the fractal design is most efficient in the detection of contagion and provides spatial information over a larger range of distance scales than other sampling schemes. However, the regular grid sampling scheme consistently yielded an estimate of average disease incidence that had the smallest variance. Sampling patterns consisting of randomly selected points were intermediate in behavior between the two extremes.  相似文献   

19.
 在国内已发表的两个小麦条锈病流行电算模拟模型的基础上,将研究的病害传播范围等分成一定大小的正方形小区,并以其为空间传播的计量单元,确定各小区的方位和间距。利用Mackenzie的病害直线传播梯度模型,通过试验建立回归预测式求得b值。并根据子代病叶总数与子代发病中心病情的定量关系,求出中心点病情a。再经过随机数转换和重叠侵染转换,与已有的日传染率、潜育期模型相结合,组建了"XRZD-1"电子计算机模拟模型。通过多次循环可以推算和打印出逐日的各小区病害数量及形象化图形。实现了病害时间动态和空间动态的协同模拟。  相似文献   

20.
ABSTRACT Rhizomania disease of sugar beet represents a major economic threat to the sugar industry in the United Kingdom. Here we use the UK rhizomania epidemic as an exemplar of a range of highly infectious spatially heterogeneous diseases. Using a spatially explicit stochastic model, we investigated the efficacy of a spectrum of possible control strategies, both locally reactive and national in character. These include the use of novel cultivars of beet with different responses to infection, changes in cultivation practice, and reactive containment policies at the farm scale. We show that strictly local responses, including a containment policy similar to that initially implemented in the United Kingdom in response to the disease, are largely ineffective in slowing the spread because they fail to match the natural scale of the epidemic. Larger spatial-scale processes are considerably more successful. We conclude that epidemics have intrinsic temporal and spatial scales that must be matched by any control strategy if it is to be both effective and efficient. We have generated probability distributions for the proportion of farms symptomatic. Over the course of the epidemic, such distributions develop a bimodality that we hypothesize to correspond to the matching of spatial heterogeneity in the susceptible population to the intrinsic scales of the epidemic.  相似文献   

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