Atmospheric Dispersion of Wheat Rust Spores: A New Theoretical Framework to Interpret Field Data and Estimate Downwind Dispersion (original) (raw)
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Turbulent dispersion of spores was studied near a source located inside a wheat canopy. Two colors of Lycopodium spores were released simultaneously at a steady rate from line sources at two heights (0.4-0.5 m and 0.7-0.8 m) in a 0.8 to 1.0 m tall crop. The number of spores of each color released was estimated by weighing the sources before and after each release. Aerial spore concentrations were measured at 2 and 4 m downwind of the sources using rotorods placed at four heights above the canopy and small suction traps at two heights inside the canopy. Concentrations near the ground were estimated from deposits on sticky glass microscope slides placed on the ground. Experiments were conducted on six different days. Friction velocities ranged from about 0.3 to 015 m s-i. The average horizontal fluxes of spores were calculated as the product of the observed concentrations and average wind speeds. At a distance of 2 m downwind from the sources, more than 16 to 44% of the flux of spores released from the lower source and more than 41 to 50% of the flux of spores released from the upper source were estimated to be above the canopy. These fluxes were compared with fluxes calculated using both a K-theory model and a random-flight-fluid-parceltrajectory simulation model. The fluxes predicted by the models were generally considerably less than the values determined experimentally. 252 DONALD E. AYLOR AND FRANCIS J. FERRANDINO DONALD E. AYLOR AND FRANCIS I. FERRANDINO
Phytopathology®, 2017
In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa’s largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from E...
Ability of the Gaussian plume model to predict and describe spore dispersal over a potato crop
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The Gaussian plume model (GPM) is considered as a valuable tool in predictions of the atmospheric transport of fungal spores and plant pollen in risk assessments. The validity of the model in this important area of application has not been extensively evaluated. A field experiment was set up to test and-if necessary-adapt the GPM, as applied to the dispersal of spores. Spores of the fern Lycopodium cla6atum were released artificially over a period of 10 min from a source placed 70 cm above the surface in a potato crop. Spore catches were made with a network of Rotorod and Burkhard samplers, placed up to 100 m downwind from the source and at several heights and crosswind distances from the anticipated plume axis. The width and height of Gaussian plumes depend on atmospheric mixing, as affected by weather. Mixing parameters in risk assessments are commonly predicted on the basis of weather conditions. We found a low correlation (R= 0.4) between measured spore concentrations and predicted spore concentrations, using a widely used prediction method (GPM Pasquill Atmospheric Diffusion, 2nd ed., Wiley, New York, 1974), based on cloud cover, wind speed, season and time of day. More precise methods for predicting the width and height of Gaussian plumes require detailed site-specific information (measurements of wind speed and temperature at two heights above the vegetation), and are therefore not readily applicable in risk assessments. An alternative that is often adequate is to use a worst case approach, in which the dispersal parameters are used that give the highest spore concentration at the location of interest. Predictability could be improved by measuring atmospheric stability during and just after weather conditions conducive to release of the pollen or spores of interest. We calibrated the model with a weighted least-squares method. Calibrating the model led to a more than 100-fold decrease in the sum of weighted squares. A comparison of estimated concentrations with the measurements confirmed that spore clouds originating from a point source take the form of a Gaussian plume: the coefficient of correlation between measured spore concentrations and fitted concentrations was 0.8. The fraction of spores that escaped the canopy and was available
PLoS ONE, 2014
Given its biological significance, determining the dispersal kernel (i.e., the distribution of dispersal distances) of sporeproducing pathogens is essential. Here, we report two field experiments designed to measure disease gradients caused by sexually-and asexually-produced spores of the wind-dispersed banana plant fungus Mycosphaerella fijiensis. Gradients were measured during a single generation and over 272 traps installed up to 1000 m along eight directions radiating from a traceable source of inoculum composed of fungicide-resistant strains. We adjusted several kernels differing in the shape of their tail and tested for two types of anisotropy. Contrasting dispersal kernels were observed between the two types of spores. For sexual spores (ascospores), we characterized both a steep gradient in the first few metres in all directions and rare long-distance dispersal (LDD) events up to 1000 m from the source in two directions. A heavy-tailed kernel best fitted the disease gradient. Although ascospores distributed evenly in all directions, average dispersal distance was greater in two different directions without obvious correlation with wind patterns. For asexual spores (conidia), few dispersal events occurred outside of the source plot. A gradient up to 12.5 m from the source was observed in one direction only. Accordingly, a thin-tailed kernel best fitted the disease gradient, and anisotropy in both density and distance was correlated with averaged daily wind gust. We discuss the validity of our results as well as their implications in terms of disease diffusion and management strategy.
Microbial Ecology, 2012
Many of the fungal pathogens that threaten agricultural and natural systems undergo wind-assisted dispersal. During turbulent wind conditions, long-distance dispersal can occur, and airborne spores are carried over distances greater than the mean. The occurrence of longdistance dispersal is an important ecological process, as it can drastically increase the extent to which pathogen epidemics spread across a landscape, result in rapid transmission of disease to previously uninfected areas, and influence the spatial structure of pathogen populations in fragmented landscapes. Since the timing of spore release determines the wind conditions that prevail over a dispersal event, this timing is likely to affect the probability of longdistance dispersal occurring. Using a Lagrangian stochastic model, we test the effect of seasonal and diurnal variation in the release of spores on wind-assisted dispersal. Spores released during the hottest part of the day are shown to be more likely to undergo long-distance dispersal than those released at other times. Furthermore, interactions are shown to occur between seasonal and diurnal patterns of release. These results have important consequences for further modelling of wind-assisted dispersal and the use of models to predict the spread of fungal pathogens and resulting population and epidemic dynamics.
Do small spores disperse further than large spores?
Ecology, 2014
In species that disperse by airborne propagules an inverse relationship is often assumed between propagule size and dispersal distance. However, for microscopic spores the evidence for the relationship remains ambiguous. Lagrangian stochastic dispersion models that have been successful in predicting seed dispersal appear to predict similar dispersal for all spore sizes up to ;40 lm diameter. However, these models have assumed that spore size affects only the downwards drift of particles due to gravitation and have largely omitted the highly size-sensitive deposition process to surfaces such as forest canopy. On the other hand, they have assumed that spores are certain to deposit when the air parcel carrying them touches the ground. Here, we supplement a Lagrangian stochastic dispersion model with a mechanistic deposition model parameterized by empirical deposition data for 1-10 lm spores. The inclusion of realistic deposition improved the ability of the model to predict empirical data on the dispersal of a wood-decay fungus (aerodynamic spore size 3.8 lm). Our model predicts that the dispersal of 1-10 lm spores is in fact highly sensitive to spore size, with 97-98% of 1 lm spores but only 12-58% of 10-lm spores dispersing beyond 2 km in the simulated range of wind and canopy conditions. Further, excluding the assumption of certain deposition at the ground greatly increased the expected dispersal distances throughout the studied spore size range. Our results suggest that by evolutionary adjustment of spore size, release height and timing of release, fungi and other organisms with microscopic spores can change the expected distribution of dispersal locations markedly. The complex interplay of wind and canopy conditions in determining deposition resulted in some counterintuitive predictions, such as that spores disperse furthest under intermediate wind, providing intriguing hypotheses to be tested empirically in future studies.
A model of the escape of Sclerotinia sclerotiorum ascospores from pasture
Ecological Modelling, 2002
A multi-layer physical model, SPORESIM-1D, based on the gradient transfer theory (K-theory) of turbulent dispersal (analogous with the molecular diffusion of gasses) is described for the transport of Sclerotinia sclerotiorum ascospores within and above a grass canopy following their release from apothecia at ground level. The 'steady-state' diffusion equation is solved numerically and the spore escape fraction is estimated. SPORESIM-1D's context is the risk analysis of S. sclerotiorum used as a mycoherbicide to control Cirsium ar6ense in pasture. In validation tests SPORESIM-1D was internally consistent and produced a vertical wind speed profile similar to that measured in a grassland. In further validation tests, measured vertical profiles of atmospheric concentrations of Lycopodium cla6atum spores in a wheat crop, and Venturia inaequalis spores in an apple orchard and in a grassland, were closely approximated by the model, as was measured data on the concentration of S. sclerotiorum ascospores deposited downwind of a small area source in a grassland. Escape fractions for grassland predicted by SPORESIM-1D, were 50% lower than predicted by both a Lagrangian model (Plant Disease 82 (1998) 838) and a one-layer version of SPORESIM-1D, SPORESIM-1L, indicating that the vertical compartmentalisation in SPORESIM-1D, allowing wind speed and pasture leaf area index (LAI) to vary with height, results in a more realistic estimate of the escape fraction. Simulations using SPORESIM-1D revealed an increase in the escape fraction with increasing wind speed, and an order-of-magnitude fall with increases in LAI from values typical of a closely grazed sheep pasture (ca. 2) to those of more laxly grazed cattle pastures and intact grassland (ca. 7). This result implies that any additional risk of disease in a susceptible crop growing downwind of a pasture treated with a S. sclerotiorum mycoherbicide may be reduced by grazing management. Reduction in the risk of sclerotinia rot in kiwifruit (Actinidia deliciosa) vines, and in apple scab disease in apple trees, caused by V. inaequalis, appears possible by maintaining a dense grass under-storey. A simple empirical model for spore escape with one parameter and two variables (LAI and wind speed) derived from the mechanistic model provided a good description (r 2 =0.998) of simulated escape fraction. Combined with information on release rates of S. sclerotiorum spores at a biocontrol site, this model will enable a times-series analysis of spore emission, and coupled with a : S 0 3 0 4 -3 8 0 0 ( 0 1 ) 0 0 4 6 2 -8 M. D. de Jong et al. / Ecological Modelling 150 (2002) 83-105 84 Gaussian plume model, prediction of minimum isolation distances between a biocontrol site and a susceptible crop.
Quantifying airborne dispersal routes of pathogens over continents to safeguard global wheat supply
Nature Plants, 2017
Infectious crop diseases spreading over large agricultural areas pose a threat to food security. Aggressive strains of the obligate pathogenic fungus Puccinia graminis f.sp. tritici (Pgt), causing the crop disease wheat stem rust, have been detected in East Africa and the Middle East, where they lead to substantial economic losses and threaten livelihoods of farmers. The majority of commercially grown wheat cultivars worldwide are susceptible to these emerging strains, which pose a risk to global wheat production, because the fungal spores transmitting the disease can be wind-dispersed over regions and even continents 1-11. Targeted surveillance and control requires knowledge about airborne dispersal of pathogens, but the complex nature of long-distance dispersal poses significant challenges for quantitative research 12-14. We combine international field surveys, global meteorological data, a Lagrangian dispersion model and high-performance computational resources to simulate a set of disease outbreak scenarios, tracing billions of stochastic trajectories of fungal spores over dynamically changing host and environmental landscapes for more than a decade. This provides the first quantitative assessment of spore transmission frequencies and amounts amongst all wheat producing countries in Southern/East Africa, the Middle East and Central/South Asia. We identify zones of high airborne connectivity that geographically correspond with previously postulated wheat rust epidemiological zones (characterized by endemic disease and free movement of inoculum) 10,15 , and regions with genetic similarities in related pathogen populations 16,17. We quantify the circumstances (routes, timing, outbreak sizes) under which virulent pathogen strains such as 'Ug99' 5,6 pose a threat from long-distance dispersal out of East Africa to the large wheat producing areas in Pakistan and India. Long-term mean spore dispersal trends (predominant direction, frequencies, amounts) are summarized for all countries in the domain (Supplementary Data). Our mechanistic modelling framework can be applied to other geographic areas, adapted for other pathogens and used to provide risk assessments in real-time 3. The aim of the study described here was threefold: to develop a flexible data-driven simulation framework to analyse spore dispersal on regional and continental scales; to identify key airborne dispersal routes of Pgt-spores threatening wheat production; and to obtain estimates of typical airborne pathogen transmission quantities amongst donor and recipient countries to inform surveillance
Authorea (Authorea), 2023
Cereal rust diseases are caused by Puccinia spp. urediniospores that travel by air currents to cause losses in wheat, oat, barley, and rye. In western Canada, inoculum can arrive from the USA through the Great Plains or via a Pacific corridor west of the Rocky Mountains. Moreover, climate and land use are known factors in Puccinia dissemination, but their relative effects remain poorly understood. We investigated aeromycobiota in western Canada by weekly air-sampling over four growing seasons (2015-2018) three mixed-crop sites in British Columbia (BC) and one season (2018) at five sites in southern Alberta (AB). ITS2-based metabarcoding and novel bioinformatic comparative analyses to known, especially curated cereal rust fungal sequences, was used for species identification. The overall aeromycobiota and rust fungal community diversity was higher west than east of the Canadian Rockies. This mountain range delineates climate and land use and also creates a barrier to wind flow to prevent the spread of rusts and other plant pathogens (e.g., Bipolaris, Blumeria). We recovered seven major cereal rusts and revealed their geographic and seasonal dynamics at the eight sampling sites. Forward and reverse trajectory HYSPLIT model simulations predicted the potential sources of rust urediniospores and their pathways of movement modulated by air currents, through which some pronounced changes in the abundance of wheat rust pathogens were explained. This study paves the way for a potential application for pathogen monitoring and disease risk forecasting as part of the design and development of an early-warning system for enhanced biovigilance against crop diseases.