Esker, P.D., A.H. Sparks, G. Antony, M. Bates, W. Dall' Acqua, E.E. Frank, L. Huebel, V. Segovia, and K.A. Garrett, 2007. Ecology and Epidemiology in R: Modeling dispersal gradients. The Plant Health Instructor. DOI:10.1094/PHI-A-2007-1226-03.
Ecology and Epidemiology in R: Modeling dispersal gradients
Suggested Quiz and Study Questions
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There are two general types of dispersal models. What are they? Also, describe the differences between these two models.
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Dispersal models are similar to models for disease progress over time. With that being said, what is the significant difference between these two modeling approaches?
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Under what situation will an Exponential model be more appropriate? A Power model?
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For a polycyclic pathogen, dispersal (or disease) gradients may be made over the course of a growing season. What typically happens to the gradient over time? Which model has a link to the Exponential model for these situations? The Power model?
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What are some of the statistics that may be used for determining a model's goodness-of-fit? What R function enables an examination of these statistics?
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What are the three steps involved for fungal dispersal?
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Why is modeling dispersal important for studying plant pathogens and plant diseases? What are the two most important mechanisms for fungal dispersal?
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What would be the difference in the disease gradient between data modeled by y=19*exp(-0.1x) and y= 19*exp((-0.5x)? Would it be reasonable to compare the disease gradients associated with these 2 equations?
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What are the five primary mechanisms for nematode dispersal? Describe for one of the mechanisms a method to reduce the likelihood of nematode dispersal.
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Would you expect a random distribution of infected plants if the source of inoculum was infected seeds? Aerially dispersed propagules? Inoculum from adjacent fields? Explain your reasoning.