51. Tree effects on coffee leaf rust at field and landscape scales
- Author
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Avelino, Jacques, Gagliardi, Stephanie, Perfecto, Ivette, Isaac, Marney E., Liebig, Theresa, Vandermeer, John, Merle, Isabelle, Hajian-Forooshani, Zachary, Motisi, Natacha, Avelino, Jacques, Gagliardi, Stephanie, Perfecto, Ivette, Isaac, Marney E., Liebig, Theresa, Vandermeer, John, Merle, Isabelle, Hajian-Forooshani, Zachary, and Motisi, Natacha
- Abstract
While integrating trees into agricultural systems (i.e., agroforestry systems) provides many valuable ecosystem services, they can also interact with plant diseases. We demonstrate that a detailed understanding of how plant diseases interact with trees in agroforestry systems is necessary to identify key tree canopy characteristics, leaf traits, spatial arrangements, and management options that can help control plant diseases at different spatial scales. We focus our analysis on how trees affect coffee leaf rust, a major disease impacting one of the world's most significant crop commodities. We show that trees can both promote and discourage the development of coffee leaf rust at the plot scale via microclimate modifications in the understory. Based on our understanding of the role of tree characteristics in shaping the microclimate, we identify several canopy characteristics and leaf traits that can help manage coffee leaf rust at the plot scale: namely, thin canopies with high openness, short base height, horizontal branching, and small, dentate leaves. In contrast, at the edge of coffee farms, having large trees with high canopy volume and small, thick, waxy leaves is more useful to reduce throughflow wind speeds and intercept the airborne dispersal of urediniospores, an important consideration to control disease at the landscape scale. Seasonal pruning can help shape trees into the desired form, and trees can be spatially arranged to optimize desired effects. This case study demonstrates the added value of combining process-based epidemiology studies with functional trait ecology to improve disease management in agroforestry systems.
- Published
- 2023