RT Journal Article
SR Electronic
T1 Spatially-explicit modeling improves empirical characterization of dispersal: theory and a case study
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 789156
DO 10.1101/789156
A1 Petteri Karisto
A1 Frédéric Suffert
A1 Alexey Mikaberidze
YR 2019
UL http://biorxiv.org/content/early/2019/10/01/789156.abstract
AB Dispersal is a key ecological process. An individual dispersal event has a source and a destination, both are well localized in space and can be seen as points. A probability to move from a source point to a destination point can be described by a dispersal kernel. However, when we measure dispersal, the source of dispersing individuals is usually an area, which distorts the shape of the dispersal gradient compared to the dispersal kernel. Here, we show theoretically how different source geometries affect the gradient shape depending on the type of the kernel. We present an approach for estimating dispersal kernels from measurements of dispersal gradients independently of the source geometry. Further, we use the approach to achieve the first field measurement of dispersal kernel of an important fungal pathogen of wheat, Zymoseptoria tritici. Rain-splash dispersed asexual spores of the pathogen spread on a scale of one meter. Our results demonstrate how analysis of dispersal data can be improved to achieve more rigorous measures of dispersal. Our findings enable a direct comparison between outcomes of different experiments, which will allow to acquire more knowledge from a large number of previous empirical studies of dispersal.