Modeling air-mediated dispersal of spores, pollen and seeds in forested areas

Abstract

Dispersal of airborne spores, pollen and seeds is important for various ecological and biological processes, and therefore modeling tools are needed in order to predict the dispersal patterns of these particles. In this study, we use a Lagrangian stochastic (LS) modeling approach to describe airborne particles dispersal in the atmospheric boundary layer. The LS dispersal model is extended to include non-Gaussian turbulence in the upper parts of the atmospheric boundary layer, as well as the reduction of the autocorrelation time in trajectories due to the high terminal velocity of particles. The sensitivity of particle dispersal on biological and atmospheric factors is assessed by simulating dispersal patterns under varying environmental conditions. Similarly, the level of needed model complexity for describing the particle dispersal is examined. Our particle dispersal simulations suggest that the level of model complexity and accuracy needed in the description of biological and atmospheric factors depends on the particle size and the distance and time-scale over which the particle dispersal is monitored. More simplification is justified for light particles, whereas heavy particles require more accuracy in modeling. For example, we found out that the local dispersal of light particles is hardly affected by the atmospheric stability whereas it has a strong effect on the dispersal of heavy particles. Based on our simulations, we developed guidelines for modeling airborne particle dispersal. Together with the detailed description of the LS dispersion model and its parameterization throughout the atmospheric boundary layer, these can serve as basis for various particle dispersal studies and help ecologists and biologists not so familiar with meteorological modeling tools to apply the LS model for spore, pollen and seed dispersal.