Maximum Likelihood Inference for Seed and Pollen Dispersal Distributions

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Abstract
Seed and pollen dispersal are both important factors in the demography and population genetic structure of plant populations. How does one model and infer dispersal patterns? One approach is to map the locations of individuals in a population and use genetic information to suggest which parents generated which offspring. This article develops models and a maximum likelihood inference framework for data of this type. The procedure will be illustrated on data from a population of Chamaelirium luteum, an herbacious plant of the forest floor. This article shows how the proposed method avoids some of the problems found in the original analysis of these data. The approach also allows us to uncover some additional patterns in the data: differencesin the seed dispersal distributions between years.

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