Spatial and Temporal Pattern Analyses of Esca Grapevine Disease in Vineyards in France.

To assess the capacity of esca to spread within vineyards of the Bordeaux region, over 8 years of annual records, containing between 1,200 and 2,300 contiguous Cabernet Sauvignon vines from 15 mature vineyards, were used for spatial statistical analyses. A group of nonparametric tests, based on join count statistics and on permutation methods, was developed to characterize the spatial structure of esca-symptomatic vines in terms of spread in any direction or within-row only. Among vineyards, a large range of spatial patterns, from random to strongly structured, associated with various prevalence rates that increased over time were observed. In four vineyards, the complex esca distribution pattern indicated different levels of clustering. By contrast, in other vineyards, only small clusters of two adjacent symptomatic vines were observed, and they were localized along rows, without enlargement over time, except in one vineyard. An analysis of spatial dependence between previously and newly symptomatic vines within k-order neighborhoods (k = 1 to 5), showed, for 5 of the 15 vineyards, that the newly symptomatic vines were located close to previously infected vines, without a favored orientation or neighbor order. All the results together suggested a limited potential for secondary local spread from neighboring symptomatic vines.

Highlighting features of spatiotemporal spread of powdery mildew epidemics in the vineyard using statistical modeling on field experimental data.

A greater understanding of the development of powdery mildew epidemics on vines would improve disease management by making assessments of the risk of invasion more accurate. We characterized the spatiotemporal spread of epidemics in the vineyard, quantified their variability, and identified the factors responsible for it. We described changes in the probability of infection of a leaf in a plot over time and as a function of distance from a source of disease. Logistic models were fitted to field data from artificially inoculated plots. The velocity of spread decreased along the row and increased in the direction of the prevailing winds. The rate of progression over time was plot dependent, and the velocity was dependent on the vigor of the vine (0.1 to 0.27 m day(-1) in areas of moderate vigor and 1.1 m day(-1) in areas of high vigor). When applied to a larger plot with natural primary foci, the spatiotemporal logistic model showed that the velocity and the slope of the gradient in space depended on the foci; however, the velocity remained in the same range. During the period of highest susceptibility for grape, the probability of a leaf becoming infected increased from 2.5 to 13%. Our logistic model was able to predict changes in disease over time of its extension within the plot; however, the crop heterogeneity prevented prediction of variability of disease at the vine scale.

Accounting for biological variability and sampling scale: a multi-scale approach to building epidemic models.

When one considers the fine-scale spread of an epidemic, one usually knows the sources of biological variability and their qualitative effect on the epidemic process. The force of infection on a susceptible unit depends on the locations and the strengths of the infectious units, and on the environmental and intrinsic factors affecting infectivity and/or susceptibility. The infection probability for the susceptible unit can then be modelled as a function of these factors. Thus, one can build a conceptual model at the fine scale. However, the epidemic is generally observed at a larger scale and one has to build a model adapted to this larger scale. But how can the sources of variation identified at the fine scale be integrated into the model at the larger scale? To answer this question, we present, in the context of plant epidemiology, a multi-scale approach which consists of defining a base model built at the fine scale and upscaling it to match the scale of the sampling and the data. This approach will enable comparing experiments involving different observational processes.

Estimation of abomasum strongyle nematode infections in sheep at necropsy: tentative proposals for a simplified technique.

Several necropsy techniques are available for estimating the abundance of gastro-intestinal nematodes in abomasum of ruminants. Standardization of techniques is needed to allow accurate comparisons between laboratories. Here we propose a standardized technique for estimating the abundance of worms. We intend to compare the worms' number estimations in lambs and ewes based on contents and washings, to determine the uniformity of worm counts in aliquots, and to estimate the total worm number from washings. The digesta (or "contents") and the washings of the abomasum are treated separately. The worms of each subsample are diluted with water and the total number of worms is estimated on a small volume (aliquots) of these subsamples. The use of aliquots assumes that the worms are uniformly distributed in the whole volume of each subsample. We first confirmed that the use of aliquots is appropriate in most cases. We then show that the use of the washings alone allows a faster and a suitable estimation of the total worm burden for all strongyle species of the abomasum in both ewes and lambs. The evaluation of our necropsy procedure is a first step to a standardized technique which should be improved by validation in other laboratories.

[An epidemiological survey of equine anaplasmosis (Anaplasma phagocytophilum) in southern France]. / Enquête epidémiologique sur l'anaplasmose equine (Anaplasma phagocytophilum) dans le Sud de la France.

Anaplasmosis is caused by the bacterium Anaplasma phagocytophilum and transmitted by Ixodes spp. ticks. According to some reports the disease can be introduced into disease-free zones by migrating birds. The purpose of this study was to evaluate the seroprevalence of A. phagocytophilum in horses in the Camargue. Data concerning 424 horses were gathered and the sera were tested for A. phagocytophilum and for piroplasmoses using an enzyme-linked immunosorbent assay and a complement fixation test, respectively. The seroprevalence rates were 11.3 % for A. phagocytophilum, 64.4 % for Theileria equi and 19.7% for Babesia caballi. Stallions were less likely to produce antibodies against A. phagocytophilumthan were females or geldings (odds ratio [OR] = 0.3; p = 0.021). The presence of swallows increased the risk of infections in stables (OR = 5.18; p = 0.011). Spatial analysis showed the existence of groups of infected stables along canals and rivers (p = 0.008). These results suggest an emergence of A. phagocytophilum in the Camargue.

Constraints on adaptive mutations in the codling moth Cydia pomonella (L.): measuring fitness trade-offs and natural selection.

Adaptive changes in populations encountering a new environment are often constrained by deleterious pleiotropic interactions with ancestral physiological functions. Evolutionary responses of populations can thus be limited by natural selection under fluctuating environmental conditions, if the adaptive mutations are associated with pleiotropic fitness costs. In this context, we have followed the evolution of the frequencies of insecticide-resistant mutants of Cydia pomonella when reintroduced into an untreated environment. The novel set of selective forces after removal of insecticide pressure led to the decline of the frequencies of resistant phenotypes over time, suggesting that the insecticide-adapted genetic variants were selected against the absence of insecticide (with a selective coefficient estimated at 0.11). The selective coefficients were also estimated for both the major cytochrome P450-dependent monooxygenase (MFO) and the minor glutathione S-transferase (GST) systems (0.17 and negligible, respectively), which have been previously shown to be involved in resistance. The involvement of metabolic systems acting both through xenobiotic detoxification and biosynthetic pathways of endogenous compounds may be central to explaining the deleterious physiological consequences resulting from pleiotropy of adaptive changes. The estimation of the magnitude of the fitness cost associated with insecticide resistance in C. pomonella suggests that resistance management strategies exclusively based on insecticide alternations would be unlikely to delay such a selection process.

A point pattern model of the spread of foot-and-mouth disease.

The spatial spread of foot-and-mouth disease (FMD) is influenced by several sources of spatial heterogeneity: heterogeneity of the exposure to the virus, heterogeneity of the animal density and heterogeneity of the networks formed by the contacts between farms. A discrete space model assuming that farms can be reduced to points is proposed to handle these different factors. The farm-to-farm process of transmission of the infection is studied using point-pattern methodology. Farm management, commercial exchanges, possible airborne transmission, etc. cannot be explicitly taken into account because of lack of data. These latter factors are introduced via surrogate variables such as herd size and distance between farms. The model is built on the calculation of an infectious potential for each farm. This method has been applied to the study of the 1967-1968 FMD epidemic in UK and allowed us to evaluate the spatial variation of the probability of infection during this epidemic. Maximum likelihood estimation has been conducted conditional on the absence of data concerning the farms which were not infected during the epidemic. Model parameters have then been tested using an approximated conditional-likelihood ratio test. In this case study, results and validation are limited by the lack of data, but this model can easily be extended to include other information such as the effect of wind direction and velocity on airborne spread of the virus or the complex interactions between the locations of farms and the herd size. It can also be applied to other diseases where point approximation is convenient. In the context of an increase of animal density in some areas, the model explicitly incorporates the density and known epidemiological characteristics (e.g. incubation period) in the calculation of the probability of FMD infection. Control measures such as vaccination or slaughter can be simply introduced, respectively, as a reduction of the susceptible population or as a reduction of the source of infection.

A stochastic flowering model describing an asynchronically flowering set of trees.

A general stochastic model is presented that simulates the time course of flowering of individual trees and populations, integrating the synchronization of flowering both between and within trees. Making some hypotheses, a simplified expression of the model, called the 'shoot' model, is proposed, in which the synchronization of flowering both between and within trees is characterized by specific parameters. Two derived models, the 'tree' model and the 'population' model, are presented. They neglect the asynchrony of flowering, respectively, within trees, and between and within trees. Models were fitted and tested using data on flowering of Psidium cattleianum observed at study sites at elevations of 200, 520 and 890 m in Reunion Island. The 'shoot' model fitted the data best and reproduced the strong irregularities in flowering shown by empirical data. The asynchrony of flowering in P. cattleianum was more pronounced within than between trees. Simulations showed that various flowering patterns can be reproduced by the 'shoot' model. The use of different levels of organization of the general model is discussed.

A reference map of Cucumis melo based on two recombinant inbred line populations.

A composite genetic melon map was generated based on two recombinant inbred line (RI) populations. By analyzing the segregation of 346 AFLPs, 113 IMAs and phenotypic characters on a RI population of 163 individuals derived from the cross Védrantais x PI 161375, a first map was constructed. About 20% of the molecular markers were skewed, and the residual heterozygosity was estimated at 4.43% which was not significantly different from the theoretical value of 4.2%. The genome distribution of molecular markers among the 12 linkage groups was not different from a random distribution with the exception of linkage group XII which was found significantly less populated. The genome distributions of IMAs and AFLPs were complementary. AFLPs were found mainly in the middle of each linkage group and sometimes clustered, whereas IMAs were found mainly at the end. A total of 318 molecular markers, mainly AFLP and IMA markers, were mapped on 63 RIs of the second population, Védrantais x PI 414723. Comparison of the maps enables one to conclude that AFLPs and IMAs of like molecular size, amplified with the same primer combination, correspond to the same genetic locus. Both maps were joined through 116 common markers comprising 106 comigrating AFLPs/IMAs, plus five SSRs and five phenotypic markers. The integrated melon map contained 668 loci issuing from the segregation of 1,093 molecular markers in the two RI populations. The composite map spanned 1,654 cM on 12 linkage groups which is the haploid number of chromosomes in melon. Thirty two known-function probes, i.e. known-function genes (9) and morphological traits (23), were included in this map. In addition, the composite map was anchored to previously published maps through SSRs, RFLPs and phenotypic characters.

Testing local independence between two point processes.

Dependencies between two types of points in a spatial point process can be due either to a real dependence between the two types or to the dependence on common underlying variables. We propose a global test for dependence between two point processes that is valid for a wide range of models. In contrast with previously proposed methods, it is based on a number of local test statistics, which makes it possible to map the local association between the two processes. The behavior of the test is evaluated by a simulation study. It is then applied to a vegetation pattern data set from Burkina Faso.

Testing local dependence of spatial structures on images

Associations between two spatial processes can be due to a real dependence between the two processes or to the dependence on common underlying variables. We propose to test the existence of a real dependence by use of local tests, leading to a global test of real dependence and a map of local interactions. We present first how classical interaction tests based on random rotations between completely observed processes such as those developed by Berman (Berman. Appl. Statist. (1986) 35, 54-62), can be integrated in local analyses. For this purpose, tests are first performed locally, and the distribution of their p-values is then compared to the corresponding value under the null hypothesis. A similar approach is proposed to test non-stationarity of a point pattern by using distance statistics popularized by Diggle (Diggle. Statistical Analysis of Spatial Point Patterns. (1983) Academic Press, New York). The problem of testing the interaction between a random field and a censoring area pattern process is discussed and an approach similar to the preceding ones is then proposed. The methods are mainly applied to agricultural examples but they can be applied to any microscopical images for which one wishes to analyse the spatial structure.