PS 29-165 - Evaluating pollen dispersal patterns in the wind-dispersed Amaranthus tuberculatus and the insect-dispersed Solanum lycopersicum in the New York metropolitan area

Tuesday, August 8, 2017
Exhibit Hall, Oregon Convention Center
Chelsea L. Butcher and James D. Lewis, Louis Calder Center - Biological Station and Department of Biological Sciences, Fordham University, Armonk, NY

Although changing landscapes can alter the dispersal patterns of both plants and animals, these changes may have a larger effect on plants, as they can only disperse passively via seeds and pollen. Further, pollen dispersal may be the more important component of gene flow in plants because seed dispersal is often more localized. However, few studies have modelled pollen dispersal patterns in urban landscapes. This relationship between pollen dispersal and distance from pollen source can be modelled using non-linear regression (i.e. curve fitting). Pollen dispersal patterns also have been examined by fitting probability density functions, or kernels, to the probability of pollen dispersal (i.e. kernel fitting). Here, we performed both curve and kernel fitting to evaluate pollen dispersal patterns in a wind-pollinated species (Amaranthus tuberculatus) and an insect-pollinated species (Solanum lycopersicum) at four sites in the New York metropolitan area. We used seed and fruit production as proxies for effective pollen dispersal in A. tuberculatus and S. lycopersicum, respectively. We hypothesized that 1) A. tuberculatus and S. lycopersicum pollen dispersal would show an exponential decay with increasing distance from the pollen source, and 2) the exponential kernel would fit A. tuberculatus and S. lycopersicum probability of pollen dispersal distributions best.


The exponential and power models fit the relationship between pollen dispersal and distance similarly well at all but one site for A. tuberculatus and all sites for S. lycopersicum. The exponential and power models may fit our pollen dispersal data equally well because the exponential model has been shown to provide the best fit at short distances from the pollen source, while the power model generally provides the best fit at longer distances. For the kernel fitting analysis, at all sites Wald was the only candidate kernel for A. tuberculatus probability of pollen dispersal distributions. For the S. lycopersicum distributions, Wald was the only candidate kernel at two sites, and was included as one of three candidate kernels, along with Weibull and exponential, at one site; at the fourth site, Weibull and exponential were the only candidate kernels. The Wald kernel has been shown to fit dispersal patterns of wind-dispersed propagules, which supports our A. tuberculatus kernel results. More generally, our results suggest that pollen dispersal patterns of A. tuberculatus and S. lycopersicum at our study sites are broadly consistent with patterns observed for these species in agricultural and natural settings.