Population history and the selective landscape shape patterns of osmoregulatory trait divergence in tidal marsh Savannah sparrows (Passerculus sandwichensis)

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12 Scopus citations

Abstract

A persistent challenge in making associations between phenotypic and environmental variation is understanding how ecological factors and demographic history interact to shape adaptive outcomes. Evaluating the degree to which conspecific populations exposed to similar environmental pressures respond in parallel provides a powerful framework for addressing this challenge. We took this comparative approach with multiple populations of Savannah sparrows (Passerculus sandwichensis) found in tidal marshes along the Pacific coast of North America. The high salinities characterizing tidal marshes select for increased osmoregulatory performance and salinity tolerance. We collected data on physiological traits associated with osmoregulatory performance from 10 tidal marsh and three freshwater-adapted interior populations to evaluate the degree of parallel divergence across populations. All traits showed differences in the magnitude of divergence, but only total evaporative water loss (TEWL) showed differences in the direction of divergence. The drivers of these differences in both the magnitude and direction of divergence varied among traits. For kidney morphology and TEWL, patterns of divergence were best explained by variation in immigration rate from interior populations. Maximum temperature was the best predictor of variation in urine excretion ability, and both gene flow and temperature contributed to variation in plasma osmolality. Finally, analysis of multitrait divergence patterns indicated that differences in the direction of divergence were best explained by population genetic structure, whereas differences in the magnitude of divergence were explained by environmental differences. Together these results show that the influences of demography and the selective landscape can manifest themselves differently across functionally integrated traits.

Original languageEnglish
Pages (from-to)57-72
Number of pages16
JournalEvolution
Volume74
Issue number1
DOIs
StatePublished - Jan 1 2020

Funding

PMB and ZAC designed the study. PMB collected and analyzed all the data. PMB and ZAC wrote the paper. We thank the following museums and individuals for providing tissue samples for this study: J. Cracraft, P. Sweet, and T. Trombone (AMNH); J. Rising, R. Zink, and M. Westberg (ROM and BELL); P. Unitt and K. Burns (SDNHM & SDSU Museum of Biodiversity); S. Birks (UWBM). Adolfo Navarro-Siqüenza was instrumental in providing necessary permits and assistance with field logistics for work in Mexico. We also thank J. Bates, S. Hackett, B. Marks, J. Maley, J. McCormack, and A. Gordillo Martínez for their assistance with permits and field logistics. S. M. Robles Bello, A. Hernández Cardona, D. Levey, and D. Senner provided excellent field assistance in collecting samples. J. Jones and A. Hernandez helped with sequencing and lab work. L. Herritt, G. Carlson, and K. Booi for assistance with all hisotological procedures. C. Cheng for providing access to the osmometer in her laboratory. Personnel at CDFW and USFWS assisted with access to federal and state lands. Finally, we thank N. Sly, M. Stager, C. Wolf, R. Schweizer, J. Velotta, N. Senner, E. Beckman, Andrew Crawford, and three anonymous reviewers for valuable comments on the manuscript. Funding for field work and sequencing was provided by AMNH Frank M. Chapman Memorial Fund, SSE Rosemary Grant Award, SICB GIAR, Sigma-XI GIAR, UIUC Animal Biology departmental grants, Illinois Ornithological Society, Systematics Research Fund, AOU research award, Center for Latin America & Caribbean Studies Tinker Fellowship, and startup funds to ZAC from UM and UIUC. Short-read Illumina data have been submitted to the NCBI sequence read archive (SRA accession: PRJNA521441). All code and data used in analyses for this paper can be found on github at: https://github.com/phbenham/BenhamCheviron_evolution2019_DataCode

FundersFunder number
University of Illinois at Urbana-Champaign
American Museum of Natural History
American Ornithologists' Union
PRJNA521441

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 10 - Reduced Inequalities
      SDG 10 Reduced Inequalities

    Keywords

    • Adaptation
    • demography
    • geographic variation
    • nonparallelism
    • osmoregulation
    • tidal marshes

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