No. 1102

Title:

Spatially explicit neutral models for population genetics and community ecology: extensions of the Neyman-Scott clustering process

Author(s):

Shimatani, Ichiro (Institute of Statistical Mathematics)

Key words:

effective population density; kinship; point process; reproductive success; seed dispersal

Abstract:

    Spatially explicit models for populations in which limited seed dispersal causes clustering of individuals have developed little since Felsenstein (1975) pointed out that such models cannot reach an equilibrium. Developing the Neyman-Scott cluster point process, this paper models a system with clustered regeneration and demonstrates that including random movements resolves the problem, so that the continued increase in the clustering of individuals stops at some level. Therefore, the improved version of the Neyman-Scott process provides a new individual-based spatially explicit neutral coalescent model. By fitting the spatial structure at equilibrium to individual spatial distribution data, we can indirectly estimate seed dispersal and effective population density. These estimates are improved when genetic data are available, and become even more sophisticated if spatial distribution and genetic data pertaining to the offspring are also available.