Probabilistic Models for Collecting Genetic Diversity: Comparisons, Caveats, and Limitations
- Dale R. Lockwoodac,
- Christopher M. Richards *b and
- Gayle M. Volkb
- a Program for Interdisciplinary Mathematics, Ecology and Statistics; Dep. of Mathematics, Colorado State Univ., Fort Collins, CO 80523
c The research of D.R.L. is partially supported by the National Science Foundation through grant DGE-0221595
b USDA, National Center for Genetic Resources Preservation, 1111 South Mason St., Fort Collins, CO 80521
Methods for collecting genetic diversity from in situ populations are important tools for plant conservation. Many quantitative collection strategies for sampling populations without a priori information regarding the ecology, reproductive biology, or population genetic structure of the taxa have been proposed, but their different assumptions regarding the collection scale and the basis for diversity often make them difficult to compare. Understanding the limitations of the different strategies enables collectors to make more informed choices when implementing conservation and restoration projects or collecting for germplasm improvement. We compare two genetically based strategies under a common set of assumptions and extend the probabilistic arguments of the strategies to accommodate rare alleles, multiple loci, and multiple populations. The recommendations of many models are based on a single locus, but larger numbers of individuals must be collected to assure with a high probability (>0.95) the acquisition of alleles at multiple independent loci within a population. Sampling from multiple populations linked by gene flow may offset this increase. Additionally, the likelihood of capturing rare alleles remains high when sampling for multiple loci or across multiple populations. Comparison of the models provides germplasm collectors with a basis to evaluate risks of over- and undersampling to capture genetic diversity within a species.Please view the pdf by using the Full Text (PDF) link under 'View' to the left.
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