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Generic response functions to simulate climate-based processes in models for the development of airborne fungal crop pathogens

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  • Caubel, J.
  • Launay, M.
  • Lannou, C.
  • Brisson, N.

Abstract

Climate variability influences the development of crop diseases, including through an effect on crop structure and hence on the microclimate. In a context of climate change, emerging and/or more aggressive plant diseases are thus expected. It is therefore critical to understand, anticipate and quantify the effects of climate variability and climate change on numerous host plant/pathogen systems. For this purpose, an homogeneous and integrative approach to the disease dynamics of all airborne fungal pathogens affecting crops is necessary. It enables to identify when plant–climate–pathogen interactions lead to the onset or development of one or more pathosystem(s) at a local or regional scale. We therefore describe here the conceptual design of a mechanistic model of foliar disease dynamics coupled with a process-based crop model. This conceptual design proposes generic response functions based on existing response functions in published models to simulate climate-based epidemiological processes. The dispersal and deposition, infection, latency and secondary inoculum production processes are the modules in this generic model. Input variables are either climate-related (rain, wind, air temperature, and air relative humidity) or plant-related (canopy relative humidity, canopy temperature, host surface wetness, plant phenological stage, plant and tissue age, organ surfaces, plant nitrogen content and varietal resistance). We evaluated the general applicability of the conceptual design using a number of airborne fungal plant pathogens with contrasted biological behaviours. We successfully completed proof-of-concept tests, during which disease models for two airborne fungal pathogens, Plasmopara viticola and Puccinia triticina, were coupled with the grapevine and wheat versions of the generic crop model STICS. This revealed the ability of our conceptual design to be transposed into functional models and then coupled with a classical crop model. This conceptual design could be a valuable tool for agronomists who might now be wanting to consider biotic stresses as additional constraints in their crop models.

Suggested Citation

  • Caubel, J. & Launay, M. & Lannou, C. & Brisson, N., 2012. "Generic response functions to simulate climate-based processes in models for the development of airborne fungal crop pathogens," Ecological Modelling, Elsevier, vol. 242(C), pages 92-104.
    • Handle: RePEc:eee:ecomod:v:242:y:2012:i:c:p:92-104
    DOI: 10.1016/j.ecolmodel.2012.05.012
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    References listed on IDEAS

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    1. Kleijnen, Jack P. C. & Sargent, Robert G., 2000. "A methodology for fitting and validating metamodels in simulation," European Journal of Operational Research, Elsevier, vol. 120(1), pages 14-29, January.
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    1. Landry, C. & Bonnot, F. & Ravigné, V. & Carlier, J. & Rengifo, D. & Vaillant, J. & Abadie, C., 2017. "A foliar disease simulation model to assist the design of new control methods against black leaf streak disease of banana," Ecological Modelling, Elsevier, vol. 359(C), pages 383-397.
    2. Silvia Traversari & Sonia Cacini & Angelica Galieni & Beatrice Nesi & Nicola Nicastro & Catello Pane, 2021. "Precision Agriculture Digital Technologies for Sustainable Fungal Disease Management of Ornamental Plants," Sustainability, MDPI, vol. 13(7), pages 1-22, March.
    3. Majid Galoie & Fouad Kilanehei & Artemis Motamedi & Mohammad Nazari-Sharabian, 2021. "Converting Daily Rainfall Data to Sub-daily—Introducing the MIMD Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3861-3871, September.

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