Sampling related individuals within ponds biases estimates of population structure in a pond‐breeding amphibian

Authors

Kyle A. O'Connell, Smithsonian Institution & The University of Texas at ArlingtonFollow
Kevin P. Mulder, Smithsonian Institution & Centro de Investigação em Biodiversidade e Recursos Genéticos
Jose Maldonado, The University of Texas at Arlington
Kathleen L. Currie, The University of Texas at Arlington
Dennis M. Ferraro, University of Nebraska-LincolnFollow

ORCID IDs

https://orcid.org/0000-0002-0464-9259

https://orcid.org/0000-0001-6688-8848

Document Type

Article

Date of this Version

1-28-2019

Citation

www.ecolevol.org Ecology and Evolution. 2019;9:3620–3636

Comments

2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Abstract

Effective conservation and management of pond‐breeding amphibians depends on the accurate estimation of population structure, demographic parameters, and the influence of landscape features on breeding‐site connectivity. Population‐level studies of pond‐breeding amphibians typically sample larval life stages because they are easily captured and can be sampled nondestructively. These studies often identify high levels of relatedness between individuals from the same pond, which can be exacerbated by sampling the larval stage. Yet, the effect of these related individuals on population genetic studies using genomic data is not yet fully understood. Here, we assess the effect of within‐pond relatedness on population and landscape genetic analyses by focusing on the barred tiger salamanders (Ambystoma mavortium) from the Nebraska Sandhills. Utilizing genome‐wide SNPs generated using a double‐digest RADseq approach, we conducted standard population and landscape genetic analyses using datasets with and without siblings. We found that reduced sample sizes influenced parameter estimates more than the inclusion of siblings, but that withinpond relatedness led to the inference of spurious population structure when analyses depended on allele frequencies. Our landscape genetic analyses also supported different models across datasets depending on the spatial resolution analyzed. We recommend that future studies not only test for relatedness among larval samples but also remove siblings before conducting population or landscape genetic analyses. We also recommend alternative sampling strategies to reduce sampling siblings before sequencing takes place. Biases introduced by unknowingly including siblings can have significant implications for population and landscape genetic analyses, and in turn, for species conservation strategies and outcomes.