Strategic spatial patterning of crop species and cultivars could make agricultural landscapes less vulnerable to plant disease epidemics, but experimentation to explore effective disease-suppressive landscape designs is problematic. Here, we present a realistic, multiscale, spatiotemporal, integrodifference equation model of potato late blight epidemics to determine the relationship between spatial heterogeneity and disease spread, and determine the effectiveness of mixing resistant and susceptible cultivars at different spatial scales under the influence of weather. The model framework comprised a landscape generator, a potato late blight model that includes host and pathogen life cycles and fungicide management at the field scale, and an atmospheric dispersion model that calculates spore dispersal at the landscape scale. Landscapes consisted of one or two distinct potato-growing regions (6.4-by-6.4-km) embedded within a nonhost matrix. The characteristics of fields and growing regions and the separation distance between two growing regions were investigated for their effects on disease incidence, measured as the proportion of fields with ≥1% severity, after inoculation of a single potato grid cell with a low initial level of disease. The most effective spatial strategies for suppressing disease spread in a region were those that reduced the acreage of potato or increased the proportion of a resistant potato cultivar. Clustering potato cultivation in some parts of a region, either by planting in large fields or clustering small fields, enhanced the spread within such a cluster while it delayed spread from one cluster to another; however, the net effect of clustering was an increase in disease at the landscape scale. The planting of mixtures of a resistant and susceptible cultivar was a consistently effective option for creating potato-growing regions that suppressed disease spread. It was more effective to mix susceptible and resistant cultivars within fields than plant some fields entirely with a susceptible cultivar and other fields with a resistant cultivar, at the same ratio of susceptible to resistant potato plants at the landscape level. Separation distances of at least 16 km were needed to completely prevent epidemic spread from one potato-growing region to another. Effects of spatial placement of resistant and susceptible potato cultivars depended strongly on meteorological conditions, indicating that landscape connectivity for the spread of plant disease depends on the particular coincidence between direction of spread, location of fields, distance between the fields, and survival of the spores depending on the weather. Therefore, in the simulation of (airborne) pathogen invasions, it is important to consider the large variability of atmospheric dispersion conditions.

The impacts of climate change on ecosystem services are complex in the sense that effective prediction requires consideration of a wide range of factors. Useful analysis of climate-change impacts on crops and native plant systems will often require consideration of the wide array of other biota that interact with plants, including plant diseases, animal herbivores, and weeds. We present a framework for analysis of complexity in climate-change effects mediated by plant disease. This framework can support evaluation of the level of model complexity likely to be required for analysing climate-change impacts mediated by disease. Our analysis incorporates consideration of the following set of questions for a particular host, pathogen, host-pathogen combination, or geographic region. 1. Are multiple biological interactions important? 2. Are there environmental thresholds for population responses? 3. Are there indirect effects of global change factors on disease development? 4. Are spatial components of epidemic processes affected by climate? 5. Are there feedback loops for management? 6. Are networks for intervention technologies slower than epidemic networks? 7. Are there effects of plant disease on multiple ecosystem services? 8. Are there feedback loops from plant disease to climate change? Evaluation of these questions will help in gauging system complexity, as illustrated for fusarium head blight and potato late blight. In practice, it may be necessary to expand models to include more components, identify those components that are the most important, and synthesize such models to include the optimal level of complexity for planning and research prioritization.

Skelsey, P., Rossing, W. A. H., Kessel, G. J. T., Powell, J., and van der Werf, W. 2005. Influence of host diversity on development of epidemics: An evaluation and elaboration of mixture theory. Phytopathology 95:328-338.A spatiotemporal/integro-difference equation model was developed and utilized to study the progress of epidemics in spatially heterogeneous mixtures of susceptible and resistant host plants. The effects of different scales and patterns of host genotypes on the development of focal and general epidemics were investigated using potato late blight as a case study. Two different radial Laplace kernels and a two-dimensional Gaussian kernel were used for modeling the dispersal of spores. An analytical expression for the apparent infection rate, r, in general epidemics was tested by comparison with dynamic simulations. A genotype connectivity parameter, q, was introduced into the formula for r. This parameter quantifies the probability of pathogen inoculum produced on a certain host genotype unit reaching the same or another unit of the same genotype. The analytical expression for the apparent infection rate provided accurate predictions of realized r in the simulations of general epidemics. The relationship between r and the radial velocity of focus expansion, c, in focal epidemics, was linear in accordance with theory for homogeneous genotype mixtures. The findings suggest that genotype mixtures that are effective in reducing general epidemics of Phytophthora infestans will likewise curtail focal epidemics and vice versa.

In China, the incidence of phoma stem canker observed in pre-harvest surveys from 2005 to 2012 was greater on winter oilseed rape in provinces in central China (in May) than on spring oilseed rape in north China (in August). In all 742 cases when the causal pathogen was isolated from stem cankers, it was identified as Leptosphaeria biglobosa by morphology in culture and/or by species-specific polymerase chain reaction. Both L. biglobosa and Leptosphaeria maculans were detected on crop debris and seed in shipments of oilseed rape seed imported into China through Shanghai or Wuhan ports in 2009-2011. Descriptions of the observed spread of L. maculans into areas previously colonized by L. biglobosa across a spring oilseed rape growing region (Alberta, Canada, westwards, 1984-1998 and across a winter oilseed rape growing region (Poland, eastwards, 1984(Poland, eastwards, -2004 were used to estimate the potential westward spread of L. maculans in China across spring oilseed rape growing regions (north China) and winter oilseed rape growing regions (central China, generally provinces along the Yangtze River), respectively. The rates of spread were estimated as 47 km per year across spring oilseed rape in north China and 70 km per year across winter oilseed rape in central China. Dispersal modelling suggested that the rate of spread of L. maculans across Alberta, Canada (c. 17 km per year) could be explained by windborne dispersal of ascospores.

SUMMARYThis study develops and tests novel approaches that significantly reduce the fungicide input necessary for potato late blight control while maintaining the required high level of disease control. The central premise is that fungicide inputs can be reduced by reducing dose rates on more resistant cultivars, by omitting applications on days when conditions are unsuitable for atmospheric transport of viable sporangia and by adapting the dose rate to the length of the predicted critical period. These concepts were implemented and tested in field experiments in 2007 and 2008 in the North Eastern potato growing region in the Netherlands which is known for its high potato late blight disease pressure. Field experiments contained three starch potato cultivars, representing a range in resistance to potato late blight from susceptible to highly resistant, and a series of decision rules determining spray timing and incorporating an increasing number of variables such as: remaining fungicide protection level, critical weather, atmospheric capacity for viable transport of sporangia and the length of the predicted critical period. The level of cultivar resistance was used to reduce the dose rate of the preventive fungicide Shirlan (a.i. fluazinam) by default. A 50% -75% reduction of the fungicide input proved possible in both years without adverse consequences to the crop or yield. The principles can be used in many decision contexts, but further work is needed to test and refine the methods before it can be used in practice.

Dispersal is a fundamental biological process that results in the redistribution of organisms due to the interplay between the mode of dispersal, the range of scales over which movement occurs, and the scale of spatial heterogeneity, in which patchiness may occur across a broad range of scales. Despite the diversity of dispersal mechanisms and dispersal length scales in nature, we posit that a fundamental scaling relationship should exist between dispersal and spatial heterogeneity. We present both a conceptual model and mathematical formalization of this expected relationship between the scale of dispersal and the scale of patchiness, which predicts that the magnitude of dispersal (number of individuals) among patches should be maximized when the scale of spatial heterogeneity (defined in terms of patch size and isolation) is neither too fine nor too coarse relative to the gap-crossing abilities of a species. We call this the “dispersal scaling hypothesis” (DSH). We demonstrate congruence in the functional form of this relationship under fundamentally different dispersal assumptions, using well-documented isotropic dispersal kernels and empirically derived dispersal parameters from diverse species, in order to explore the generality of this finding. The DSH generates testable hypotheses as to when and under what landscape scenarios dispersal is most likely to be successful. This provides insights into what management scenarios might be necessary to either restore landscape connectivity, as in certain conservation applications, or disrupt connectivity, as when attempting to manage landscapes to impede the spread of an invasive species, pest, or pathogen.

Opportunities exist to improve decision support systems through the use of dispersal information gained from epidemiological research. However, dispersal and demographic information is often fragmentary in plant pathology, and this uncertainty creates a risk of inappropriate action whenever such information is used as a basis for decision making. In this article, a scenario-based simulation approach is used to evaluate crop and economic risks and benefits in the use of dispersal information for decision making using the potato late blight pathosystem (Phytophthora infestans-Solanum tuberosum) as a case study. A recently validated spatiotemporal potato late blight model was coupled to submodels for crop growth, tuber dry matter production, and fungicide efficacy. The yield response of a range of management scenarios to a single influx of primary inoculum (the initial spore load) was calculated. Damage curves (relative yield loss versus initial spore load) from a range of combinations of varietal susceptibility and fungicide treatments were used to classify the various management scenarios as either sensitive to initial spore load or tolerant to initial spore load, thus identifying where a high degree of accuracy would be required in dispersal information for appropriate decision making, and where a greater degree of uncertainty could be tolerated. General epidemics, resulting from spatially homogeneous initial spore loads, responded more strongly to the size of the initial spore load than focal epidemics, resulting from an initial spot infection. Susceptible cultivars responded with sizeable yield losses even at low levels of initial spore load, regardless of the fungicide management regime used. These results indicated that, for susceptible cultivars (late cultivars in particular), the degree of accuracy that would be required in dispersal information for appropriate decision making is unlikely to be practically attainable. The results also indicated that, contrary to "folk wisdom," spore loads of a few hundred spores per square meter do not lead to appreciable crop loss in resistant cultivars and are therefore acceptable. We conclude that scope exists for including dispersal information in decision making for potato late blight with resistant potato cultivars but not for susceptible cultivars. The modeling framework used in this study can be extended to investigate the scope for inclusion of dispersal information in decision support for other aerially transmitted pathogens.

A spatiotemporal, integrodifference equation model of the potato late blight pathosystem is described. Formerly, the model was used in a theoretical context to analyze and predict epidemic dynamics in spatially heterogeneous mixtures of host genotypes. The model has now been modified to reflect a research interest in interactions between genotype, environment, landscape, and management. New parameter values describing host-pathogen interactions were determined and new environment-pathogen relationships included. A new analytical equation describing lesion expansion and associated necrosis has also been developed. These changes prompted a need to assess the quality of model predictions. Cultivar-isolate-specific interactions were characterized in the model using three quantitative components of resistance: infection efficiency, lesion growth rate, and sporulation intensity. These were measured on detached potato leaflets in the laboratory. Results of a sensitivity analysis illuminate the effect of different quantitative components of resistance and initial conditions on the shape of disease progress curves. Using the resistance components, the epidemic process of lesion expansion was separated from the epidemic process of lesion propagation providing two reference curves for diagnosing observed epidemics. The spatial component of the model was evaluated graphically in order to determine if realistic rates of focal expansion for potato late blight are produced. In accordance with theory, the radius of a predicted focus increased linearly with time and a constant focal velocity was reached that compared well with published experimental data. Validation data for the temporal model came from 20 late blight epidemics observed in field trials conducted in the Netherlands in 2002 and 2004. The field data and model were compared visually using disease progress curves, and numerically through a comparison of predicted and observed t(5) and t(50) points (time in days until 5 and 50% disease severity is reached, respectively) and relative areas under the disease progress curve values. Temporal model predictions were in close agreement with observational data and the ability of the model to translate measured resistance components, weather data, and initial conditions into realistic disease progress curves without the need for calibration confirms its utility as a tool in the analysis and diagnosis of epidemics.