A general trait‐based modelling framework for revealing patterns of airborne fungal dispersal threats to agriculture and native flora

Abstract

Fungal plant pathogens are of economic and ecological importance to global agriculture and natural ecosystems. Long-distance atmospheric dispersal of fungal spores (LAD) can pose threats to agricultural and native vegetation lands. An understanding of such patterns of fungal spore dispersal and invasion pathways can provide valuable insights into plant protection.Spore traits affect their dispersal abilities. We propose a general trait-based framework for modelling LAD to reveal dispersal patterns and pathways, and assess subsequent threats of arrival (TOA) quantitatively in the context of biosecurity. To illustrate the framework, we present a study of Australia and its surrounding land masses.The overall dispersal pattern covered almost the entire continent of Australia. Fungal spores in the size class of 10 and 20 µm (aerodynamic diameter) posed the greatest TOA. Our study shows the effects of morphological traits on these potential TOA, and how they varied between source regions, size classes, and seasons.Our framework revealed spore dispersal patterns and pathways. It also facilitates comparisons of spatio-temporal dispersal dynamics among fungal classes, gaining insights into atmospheric long-distance dispersal of fungi as a whole, and provides a basis for assessing fungal pest threats in potential source regions based on easily measured spore characteristics.

Early-detection surveillance for stem rust of wheat: insights from a global epidemic network based on airborne connectivity and host phenology

“…South America, South Africa, Ethiopia and Australia are thousands of kilometers away from each other. Furthermore, our prediction of possible longdistance connections from North America to Europe, and from Europe towards Central Asia and Russia, are in accordance with previous theoretical and empirical findings [17,19,20,56]. On the other hand, due to the time lag in the respective susceptibility seasons, no connection between the Northern and Southern Hemispheres is predicted by our epidemic network.…”

“…Its aerobiology has been largely studied in the last century [9][10][11][12] and experimental procedures have been recently developed for studying three-dimensional transport and detection of spores [13,14]. However, the use of mathematical models to simulate spore transport by wind at the continental scale is very recent [15][16][17][18][19][20]. In fact, the use of such models would allow researchers, policy makers and farmers to design surveillance strategies [21][22][23] capable of detecting outbreaks and take timely countermeasures (e.g.…”

Spore production monitoring reveals contrasting seasonal strategies and a trade‐off between spore size and number in wood‐inhabiting fungi

“…For fungal spores, an empirical demonstration of this effect is difficult to achieve due to the poor detectability of spores and the large spatial scale of their dispersal caused by their small size (Wilkinson et al, 2012). However, recent work based on atmospheric model simulations has highlighted the effect of both diurnal (Lagomarsino Oneto et al, 2020) and seasonal timing (Wang et al, 2021) on fungal dispersal. Lagomarsino Oneto et al (2020) showed that diurnal timing can be critical for species whose spores are vulnerable to atmospheric conditions such as sunlight, including many wood‐inhabiting fungi (Norros et al, 2015).…”

Computing Geographical Networks Generated by Air‐Mass Movement

“…For further developing tropolink we may, (a) complement the options consisting of specifying a circular or geographic buffer around network nodes by considering flexible polygons provided by the user (Choufany, Martinetti, Senoussi, et al, 2021). We may also (b) combine variables associated to the computation of air mass trajectories (e.g., the altitude of the air mass along its trajectory, its temperature, its humidity, the level of solar radiation…), land-use maps, and properties/ behaviors of particles/insects (e.g., their shapes, their mass, their behavior with respect to the air mass conditions, their host preferences; Aylor, 2017;Isard & Gage, 2001) for weighting the trajectory contributions to connectivities and especially evaluating the likelihood of particle/insects release and deposition (Choufany, Martinetti, Senoussi, et al, 2021;Radici et al, 2022;M. Wang et al, 2021).…”