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Population connectivity: combining methods for estimating avian dispersal and migratory linkages

Ibarguen, Siri B
http://rave.ohiolink.edu/etdc/view?acc_num=osu1079979416

Abstract Details

2004, Doctor of Philosophy, Ohio State University, Evolution, Ecology, and Organismal Biology.
We use a variety of methods to study population connectivity. In Chapter 1, we use stable isotope ratios in feathers to make Bayesian inferences about the migratory connectivity between breeding and wintering grounds of Henslow’s sparrows. We use hydrogen and carbon stable isotope ratios (deltaH and deltaC). We compare the deltaH and deltaC of feathers from wintering sparrows to five breeding region deltaH and deltaC to estimate the probability that each individual wintering sparrow originated from each of the five regions. Breeding bird abundances are used as prior probabilities of breeding region origin. We conclude that there are no clear linkages between specific breeding regions and wintering sites. In Chapter 2, we use three methods to estimate dispersal in Henslow’s sparrows. 1)deltaH in feathers are used to determine whether an individual breeding bird has a deltaH signature characteristic of the breeding site. 2) Song structure is used as the signature of an individual’s previous breeding-ground origin. 3) Genetic markers are used to evaluate population structure. Genetic structure is evaluated using three estimates. Fst estimates and private alleles are used to calculate the number of migrants per generation (Nm) between sites. Private alleles are evaluated to determine if they are truly private. A Bayesian clustering method is used to infer the number of populations. All methods revealed high rates of dispersal. In Chapter 3, three methods for estimating dispersal are compared: deltaH in feathers, genetic population structure, and spatial autocorrelation (SAC). We compare the dispersal estimates of five migratory species. With the SAC analysis, we find no clear evidence for dispersal as a major synchronizing agent. However, new statistical methods may allow for the parsing out the effect of dispersal. One species had historically high dispersal (limited genetic structure) but currently low dispersal (high deltaH correlations). Another species had a deltaH correlation value indicating low current dispersal. Three other species are all found to have high dispersal, both historically and currently. Comparing dispersal estimates may allow researchers to evaluate how dispersal rates have changed over time, as well as how well estimation methods agree.
Thomas Waite (Advisor)
143 p.
Biology, Ecology
Population connectivity; Migratory linkages; Dispersal; Henslow's sparrow; Ammodramus henslowii; Spatial autocorrelation; Gene flow; Meme flow; Geographic variation in song; Private alleles; Bayesian analysis; Stable isotope ratios

Recommended Citations

Citations

  • Ibarguen, S. B. (2004). Population connectivity: combining methods for estimating avian dispersal and migratory linkages [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1079979416

    APA Style (7th edition)

  • Ibarguen, Siri. Population connectivity: combining methods for estimating avian dispersal and migratory linkages. 2004. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1079979416.

    MLA Style (8th edition)

  • Ibarguen, Siri. "Population connectivity: combining methods for estimating avian dispersal and migratory linkages." Doctoral dissertation, Ohio State University, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=osu1079979416

    Chicago Manual of Style (17th edition)

osu1079979416
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This open access ETD is published by The Ohio State University and OhioLINK.