Multi-scale modeling of potato late blight epidemics

P. Skelsey

Research output: Thesisinternal PhD, WU

Abstract

Keywords: Solanum, invasion, Gaussian plume model, functional connectivity, landscape design

Proper landscape-scale deployment of disease resistant genotypes of agricultural crop species could
make those crops less vulnerable to invasion by resistance breaking genotypes. Here we develop a
multi-scale, spatio-temporal model of the potato late blight pathosystem (Phytophthora infestans -
Solanum tuberosum) to investigate spatial strategies for the deployment of host resistance. The
model comprises a landscape generator, a potato late blight model, and a suite of aerobiological
models, including an atmospheric dispersion model. Spatial phenomena are solved using Fast Fourier
transforms.
Increasing the number of host genotypes caused the greatest reduction in epidemic extent,
followed by reduction of the proportion of potato in the landscape, lowering the clustering of host
fields, and reducing the size of host fields. Simulation results showed that spatial spread through
short-distance “island hopping” is not a prerequisite for P. infestans invasions, and it appeared not
possible to generate host free zones at the landscape level that were large enough to provide
worthwhile levels of resilience against disease invasion from one host area to another. Deployment
of host resistance in genotype mixtures had a large effect on disease invasion. A new functional
connectivity parameter, characterizing the probability of successful infection following spore
dispersal, proved to be useful in interpreting these results.
Variation in simulation results revealed the importance of using an atmospheric dispersion
model for dispersal, with large weather data sets, and many random landscape iterations. The
specific coincidence in time and space between weather conditions and the geographic locations of
source and target sites defined true landscape connectivity and determined model results regarding
inoculum exchange between fields.
Given the apparent capacity of P. infestans for long distance transport of viable inoculum, it can
be concluded that spatial resistance deployment strategies that center on the creation of spatial
barriers to disease at scales up to several kilometers may not be effective in mitigating invasions of
virulent pathogen strains. Strategies that induce finer-grained spatial and genotypic heterogeneities
in host populations are more limiting to epidemic spread. Genotype mixing was an effective option
for generating agricultural landscapes that are comparatively resilient to disease invasion.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • Holtslag, Bert, Promotor
  • van der Werf, Wopke, Co-promotor
  • Kessel, Geert Jan, Co-promotor
  • Rossing, Walter, Co-promotor
Award date2 Sep 2008
Place of PublicationS.l.
Publisher
Print ISBNs9789085049418
Publication statusPublished - 2008

Fingerprint

Phytophthora infestans
genotype
inoculum
genotype mixtures
spore dispersal
landscaping
Solanum
crops
meteorological data
Solanum tuberosum
space and time
weather
potatoes
pathogens
infection

Keywords

  • phytophthora infestans
  • solanum tuberosum
  • epidemics
  • disease models
  • spore dispersal
  • virulence
  • epidemiology
  • integrated pest management
  • host pathogen interactions

Cite this

Skelsey, P.. / Multi-scale modeling of potato late blight epidemics. S.l. : S.n., 2008. 257 p.
@phdthesis{fd81b26e843a472a8c017b6dcf2d3691,
title = "Multi-scale modeling of potato late blight epidemics",
abstract = "Keywords: Solanum, invasion, Gaussian plume model, functional connectivity, landscape design Proper landscape-scale deployment of disease resistant genotypes of agricultural crop species could make those crops less vulnerable to invasion by resistance breaking genotypes. Here we develop a multi-scale, spatio-temporal model of the potato late blight pathosystem (Phytophthora infestans - Solanum tuberosum) to investigate spatial strategies for the deployment of host resistance. The model comprises a landscape generator, a potato late blight model, and a suite of aerobiological models, including an atmospheric dispersion model. Spatial phenomena are solved using Fast Fourier transforms. Increasing the number of host genotypes caused the greatest reduction in epidemic extent, followed by reduction of the proportion of potato in the landscape, lowering the clustering of host fields, and reducing the size of host fields. Simulation results showed that spatial spread through short-distance “island hopping” is not a prerequisite for P. infestans invasions, and it appeared not possible to generate host free zones at the landscape level that were large enough to provide worthwhile levels of resilience against disease invasion from one host area to another. Deployment of host resistance in genotype mixtures had a large effect on disease invasion. A new functional connectivity parameter, characterizing the probability of successful infection following spore dispersal, proved to be useful in interpreting these results. Variation in simulation results revealed the importance of using an atmospheric dispersion model for dispersal, with large weather data sets, and many random landscape iterations. The specific coincidence in time and space between weather conditions and the geographic locations of source and target sites defined true landscape connectivity and determined model results regarding inoculum exchange between fields. Given the apparent capacity of P. infestans for long distance transport of viable inoculum, it can be concluded that spatial resistance deployment strategies that center on the creation of spatial barriers to disease at scales up to several kilometers may not be effective in mitigating invasions of virulent pathogen strains. Strategies that induce finer-grained spatial and genotypic heterogeneities in host populations are more limiting to epidemic spread. Genotype mixing was an effective option for generating agricultural landscapes that are comparatively resilient to disease invasion.",
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language = "English",
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}

Skelsey, P 2008, 'Multi-scale modeling of potato late blight epidemics', Doctor of Philosophy, Wageningen University, S.l..

Multi-scale modeling of potato late blight epidemics. / Skelsey, P.

S.l. : S.n., 2008. 257 p.

Research output: Thesisinternal PhD, WU

TY - THES

T1 - Multi-scale modeling of potato late blight epidemics

AU - Skelsey, P.

N1 - WU thesis 4479

PY - 2008

Y1 - 2008

N2 - Keywords: Solanum, invasion, Gaussian plume model, functional connectivity, landscape design Proper landscape-scale deployment of disease resistant genotypes of agricultural crop species could make those crops less vulnerable to invasion by resistance breaking genotypes. Here we develop a multi-scale, spatio-temporal model of the potato late blight pathosystem (Phytophthora infestans - Solanum tuberosum) to investigate spatial strategies for the deployment of host resistance. The model comprises a landscape generator, a potato late blight model, and a suite of aerobiological models, including an atmospheric dispersion model. Spatial phenomena are solved using Fast Fourier transforms. Increasing the number of host genotypes caused the greatest reduction in epidemic extent, followed by reduction of the proportion of potato in the landscape, lowering the clustering of host fields, and reducing the size of host fields. Simulation results showed that spatial spread through short-distance “island hopping” is not a prerequisite for P. infestans invasions, and it appeared not possible to generate host free zones at the landscape level that were large enough to provide worthwhile levels of resilience against disease invasion from one host area to another. Deployment of host resistance in genotype mixtures had a large effect on disease invasion. A new functional connectivity parameter, characterizing the probability of successful infection following spore dispersal, proved to be useful in interpreting these results. Variation in simulation results revealed the importance of using an atmospheric dispersion model for dispersal, with large weather data sets, and many random landscape iterations. The specific coincidence in time and space between weather conditions and the geographic locations of source and target sites defined true landscape connectivity and determined model results regarding inoculum exchange between fields. Given the apparent capacity of P. infestans for long distance transport of viable inoculum, it can be concluded that spatial resistance deployment strategies that center on the creation of spatial barriers to disease at scales up to several kilometers may not be effective in mitigating invasions of virulent pathogen strains. Strategies that induce finer-grained spatial and genotypic heterogeneities in host populations are more limiting to epidemic spread. Genotype mixing was an effective option for generating agricultural landscapes that are comparatively resilient to disease invasion.

AB - Keywords: Solanum, invasion, Gaussian plume model, functional connectivity, landscape design Proper landscape-scale deployment of disease resistant genotypes of agricultural crop species could make those crops less vulnerable to invasion by resistance breaking genotypes. Here we develop a multi-scale, spatio-temporal model of the potato late blight pathosystem (Phytophthora infestans - Solanum tuberosum) to investigate spatial strategies for the deployment of host resistance. The model comprises a landscape generator, a potato late blight model, and a suite of aerobiological models, including an atmospheric dispersion model. Spatial phenomena are solved using Fast Fourier transforms. Increasing the number of host genotypes caused the greatest reduction in epidemic extent, followed by reduction of the proportion of potato in the landscape, lowering the clustering of host fields, and reducing the size of host fields. Simulation results showed that spatial spread through short-distance “island hopping” is not a prerequisite for P. infestans invasions, and it appeared not possible to generate host free zones at the landscape level that were large enough to provide worthwhile levels of resilience against disease invasion from one host area to another. Deployment of host resistance in genotype mixtures had a large effect on disease invasion. A new functional connectivity parameter, characterizing the probability of successful infection following spore dispersal, proved to be useful in interpreting these results. Variation in simulation results revealed the importance of using an atmospheric dispersion model for dispersal, with large weather data sets, and many random landscape iterations. The specific coincidence in time and space between weather conditions and the geographic locations of source and target sites defined true landscape connectivity and determined model results regarding inoculum exchange between fields. Given the apparent capacity of P. infestans for long distance transport of viable inoculum, it can be concluded that spatial resistance deployment strategies that center on the creation of spatial barriers to disease at scales up to several kilometers may not be effective in mitigating invasions of virulent pathogen strains. Strategies that induce finer-grained spatial and genotypic heterogeneities in host populations are more limiting to epidemic spread. Genotype mixing was an effective option for generating agricultural landscapes that are comparatively resilient to disease invasion.

KW - phytophthora infestans

KW - solanum tuberosum

KW - epidemieën

KW - ziektemodellen

KW - sporenverspreiding

KW - virulentie

KW - epidemiologie

KW - geïntegreerde plagenbestrijding

KW - gastheer-pathogeen interacties

KW - phytophthora infestans

KW - solanum tuberosum

KW - epidemics

KW - disease models

KW - spore dispersal

KW - virulence

KW - epidemiology

KW - integrated pest management

KW - host pathogen interactions

M3 - internal PhD, WU

SN - 9789085049418

PB - S.n.

CY - S.l.

ER -

Skelsey P. Multi-scale modeling of potato late blight epidemics. S.l.: S.n., 2008. 257 p.