Spatially explicit ecological modeling improves empirical characterization of dispersal

Abstract

16 Main text Appendices A, B, C, and D. 18 6700 words in the main text.Abstract 20 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 22 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 24 an area, which distorts the shape of the dispersal gradient compared to the dispersal kernel. Here, we show theoretically how dierent source geometries aect the gradient 26 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 28 geometry. Further, we use the approach to achieve the rst eld measurement of dispersal kernel of an important fungal pathogen of wheat, Zymoseptoria tritici. Rain-splash 30 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 32 measures of dispersal. Our ndings enable a direct comparison between outcomes of dierent experiments, which will allow to acquire more knowledge from a large number 34 of previous empirical studies of dispersal. 1979; Ferrandino, 1996; Cousens and Rawlinson, 2001). Flattening of gradients due 58 to extended sources is noted qualitatively in previous studies (Zadoks and Schein, 1979; Ferrandino, 1996), but how exactly and how much does the source geometry aect the 60 dispersal gradient? 3 A more rigorous mathematical description of dispersal is achieved with a dispersal 62 kernel that represents a probability distribution of dispersal to a certain location relative to the source (dispersal location kernel, Nathan et al., 2012). It is convenient to have 64 a point source for an empirical characterization of dispersal kernels, because a dispersal gradient from a point source will have the same shape as the kernel. Zadoks and Schein 66 (1979) proposed a rule of thumb, stating that a point source should have a diameter smaller than 1% of the gradient length; but in many experiments, it is up to 5 or 68 10%. However, to determine whether the source is small enough so that the dispersal gradient captures the shape of the dispersal kernel, the size of the source should be 70 compared with the characteristic distance of dispersal (i.e., the distance over which the dispersal kernel changes substantially), rather than the gradient length. This represents a 72 challenge for the design of dispersal experiments that aim to achieve a point-like source, because whether or not the chosen source size is suciently small can be established 74 with certainty only when the measurements are already conducted. As a result, point sources of various sizes are found in literature: an adult tree (Werth et al. (2006); cf. 76 Cousens and Rawlinson (2001) presenting eect of tree canopy morphology on the shape of the gradient), circles ...

Improved control of septoria tritici blotch in durum wheat using cultivar mixtures

“…nodorum are still largely lacking, although recently Karisto et al . (2019b) estimated dispersal kernels of Z . tritici in the field.…”

Measuring splash-dispersal of a major wheat pathogen in the field

“…First reason is that the modeling approaches did not consider the spatial extent of the source area as we did here but assumed a unique point source (Karisto et al, 2019b).…”

“…CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 23, 2021. ; https://doi.org/10.1101/2021.03.23.436423 doi: bioRxiv preprint ematical model that took into account the spatial extent of the source area (Karisto et al, 2019b), we achieved the rst estimates of dispersal kernel parameters associated with splash dispersal of Z. tritici pycnidiospores in eld conditions.…”

“…In addition, we genotyped the re-isolated strains using strain-specific primers to differentiate the inoculated pathogen populations from the background natural population. Using a spatially-explicit mathematical model that took into account the spatial extent of the source area (Karisto et al, 2019 b ), we achieved the first estimates of dispersal kernel parameters associated with splash dispersal of Z. tritici pycnidiospores in field conditions.…”

“…CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprint this version posted March 23, 2021. ; https://doi.org/10.1101/2021.03.23.436423 doi: bioRxiv preprint estimates of the dispersal kernel (Karisto et al, 2019b). However, to enable comparisons between our outcomes and the earlier estimates in controlled conditions, and to highlight the distorting eect of this "standard" simplication, we constructed the one-dimensional function describing the dispersal process that follows an exponential kernel:…”