Invasion of Phytophthora infestans at the Landscape Level: How Do Spatial Scale and Weather Modulate the Consequences of Spatial Heterogeneity in Host Resistance?

Abstract

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.

Spatial diversification of agroecosystems to enhance biological control and other regulating services: An agroecological perspective

“…inter or cover cropping) allows limiting the dispersion of the fungi Puccinia striiformis responsible for the strip rust on wheat. At the landscape scale, the importance of mixed cropping for limiting disease spread was suggested through modelling (Skelsey et al, 2010). Moreover mixed cropping, by limiting the abundance of insect pests on crops, could be mobilised to control viruses hosted by insects (e.g.…”

Impacts of climate change on plant diseases—opinions and trends

“…Nonetheless, their direct test in reality will have to wait. There is an increased appreciation that understanding of the interactions among weather and the spatial distribution of susceptible/resistant host patches are keys to managing plant diseases across entire landscapes (Seem 2004;Skelsey et al 2010). The integration of multi-scale epidemic simulations with climate change scenarios is indeed one of the outstanding challenges in landscape epidemiology (Holdenrieder et al 2004;Pinkard et al 2010).…”

Scale-Dependent Assessment of Relative Disease Resistance to Plant Pathogens

“…Landscapes were modelled as a 128 × 128-cell torus and were thus -wrapped‖ such that any spore dispersing outside of the borders of the grid -reappeared‖ on the opposite edge, equalizing immigration and emigration rates. This is a commonly used approach to approximate an infinite spatial extent [8][9][10][22][23][24][25][26]. Thus, whilst the grain size of landscapes varied across a range of 30 values, spatial extent was effectively infinite.…”

“…Some practices, such as adjusting plot size and spacing, are commonly used to reduce inoculum interference, although this is often done in an ad-hoc manner based on expert opinion (or limited space), as there are no hard and fast quantitative guidelines. Furthermore, in agricultural landscapes, host crop abundance and heterogeneity can affect the magnitude of inoculum dispersal among crops [5,[7][8][9][10]. Thus, an agricultural landscape may have epidemic suppressive or enhancing effects that confound projections for QDR based on pot experiments or field trials.…”