Estimating Spore Release Rates Using a Lagrangian Stochastic Simulation ModelSource: Journal of Applied Meteorology:;2001:;volume( 040 ):;issue: 007::page 1196DOI: 10.1175/1520-0450(2001)040<1196:ESRRUA>2.0.CO;2Publisher: American Meteorological Society
Abstract: Practical problems in predicting the spread of plant diseases within and between fields require knowledge of the rate of release Q of pathogenic spores into the air. Many plant pathogenic fungus spores are released into the air from plant surfaces inside plant canopies, where they are produced, or from diseased plant debris on the ground below plant canopies, where they have survived from one growing season to the next. There is no direct way to specify Q for naturally released microscopic fungus spores. It is relatively easy to measure average concentrations of spores above a source, however. A two-dimensional Lagrangian stochastic (LS) simulation model for the motion of spores driven by atmospheric turbulence in and above a plant canopy is presented. The model was compared 1) with measured concentration profiles of Lycopodium spores released from line sources at two heights inside a wheat canopy and 2) with concentration profiles of V. inaequalis ascospores measured above ground-level area sources in a grass canopy. In both cases, there was generally good agreement between the shapes of the modeled and measured concentration profiles. Modeled and measured concentrations were compared to yield estimates of spore release rates. These, in turn, were compared to release rates estimated independently from direct measurements. The two estimates of spore release rate were in good agreement both for 1) the 30-min artificial releases of Lycopodium spores [significance level P = 0.02 (upper source) and P = 0.02 (lower source)] and for 2) the daily total release of V. inaequalis ascospores (P < 0.002). These results indicate that the LS model can yield accurate values of Q (or, conversely, of concentration). Thus, LS models allow a means of attacking a nearly intractable problem and can play an important role in predicting disease spread and in helping to reduce pesticide use in disease-management decisions.
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contributor author | Aylor, Donald E. | |
contributor author | Flesch, Thomas K. | |
date accessioned | 2017-06-09T14:07:56Z | |
date available | 2017-06-09T14:07:56Z | |
date copyright | 2001/07/01 | |
date issued | 2001 | |
identifier issn | 0894-8763 | |
identifier other | ams-13014.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4148418 | |
description abstract | Practical problems in predicting the spread of plant diseases within and between fields require knowledge of the rate of release Q of pathogenic spores into the air. Many plant pathogenic fungus spores are released into the air from plant surfaces inside plant canopies, where they are produced, or from diseased plant debris on the ground below plant canopies, where they have survived from one growing season to the next. There is no direct way to specify Q for naturally released microscopic fungus spores. It is relatively easy to measure average concentrations of spores above a source, however. A two-dimensional Lagrangian stochastic (LS) simulation model for the motion of spores driven by atmospheric turbulence in and above a plant canopy is presented. The model was compared 1) with measured concentration profiles of Lycopodium spores released from line sources at two heights inside a wheat canopy and 2) with concentration profiles of V. inaequalis ascospores measured above ground-level area sources in a grass canopy. In both cases, there was generally good agreement between the shapes of the modeled and measured concentration profiles. Modeled and measured concentrations were compared to yield estimates of spore release rates. These, in turn, were compared to release rates estimated independently from direct measurements. The two estimates of spore release rate were in good agreement both for 1) the 30-min artificial releases of Lycopodium spores [significance level P = 0.02 (upper source) and P = 0.02 (lower source)] and for 2) the daily total release of V. inaequalis ascospores (P < 0.002). These results indicate that the LS model can yield accurate values of Q (or, conversely, of concentration). Thus, LS models allow a means of attacking a nearly intractable problem and can play an important role in predicting disease spread and in helping to reduce pesticide use in disease-management decisions. | |
publisher | American Meteorological Society | |
title | Estimating Spore Release Rates Using a Lagrangian Stochastic Simulation Model | |
type | Journal Paper | |
journal volume | 40 | |
journal issue | 7 | |
journal title | Journal of Applied Meteorology | |
identifier doi | 10.1175/1520-0450(2001)040<1196:ESRRUA>2.0.CO;2 | |
journal fristpage | 1196 | |
journal lastpage | 1208 | |
tree | Journal of Applied Meteorology:;2001:;volume( 040 ):;issue: 007 | |
contenttype | Fulltext |