Inferring dispersal and migrations from incomplete geochemical baselines: analysis of population structure using Bayesian infinite mixture models

Abstract

Summary1. Geochemical and stable isotope tags are often used to attribute individual animals in a sample of mixed origins to distinct sources, be it spawning, overwintering or foraging habitats. In order for individuals to be uniquely classified to one source, modelling approaches generally assume that all potential sources have been characterized in terms of their geochemical signature. This assumption is rarely met in applications of geochemistry in environments where species distributions and spawning grounds are poorly known; statistical methods that can accommodate this problem are therefore essential. 2. We develop nonparametric Bayesian mixture models for geochemical signatures that estimate the most likely number of sources represented in a mixed sample, both in the absence and presence of baseline data. We then use a marginal clustering framework to evaluate the probability that a fish comes from a particular source. 3. Using both simulations and a previously analysed data set, we illustrate the method and highlight the potential merits and difficulties. These examples reveal how our interpretations of geochemistry data sets can change when potentially un-sampled sources are taken into account.

Lagoon nurseries make a major contribution to adult populations of a highly prized coastal fish

“…Therefore, the estimations of the relative contributions of each habitat may be slightly overestimated (Chittaro et al ). Advances in nonparametric Bayesian mixture models for geochemical signatures may be able to account for unsampled habitats (Neubauer et al ), and this is an active area of research. In this study, the analysis of sequential spots in the adults permitted them to be assigned to an unknown nursery if the sequence of predictions was random, thereby at least partially correcting for the potential bias of unsampled habitats.…”

Spatial analysis of hydrogen and oxygen stable isotopes (“isoscapes”) in ground water and tap water across South Africa

“…West et al, 2008), hair (Ehleringer et al, 2008a) and feathers (Cherel et al, 2000). Such isoscapes allow a statistical approach to determining the origin of materials (Neubauer and Shima, 2013). Spatial variation in stable isotopes has been used successfully in revealing patterns of animal migration (Rubenstein and Hobson, 2004) and forensic identification of a wide variety of materials (Ehleringer et al, 2008b).…”

Space, time and complexity in plant dispersal ecology

“…In the case of non-clinal (patchy) spatial genetic structure, allele frequency smoothing techniques may allow genetic assignment of propagules to a set of sampled and unsampled sources across the species range [ 125 , 126 ], although the accuracy of this method under contrasting sampling, dispersal, and genetic structure scenarios remains to be tested. If the number of migrant propagules is large (unfortunately an unlikely case for LDD), it may also be possible to use the genotypic composition of the propagule sample to help infer propagule migration rates from a known [ 127 ] or unknown [ 128 ] number of unsampled locations.…”