Time‐series analysis reveals genetic responses to intensive management of razorback sucker (Xyrauchen texanus)

Evolutionary Applications

Thomas E. Dowling²  Thomas F. Turner¹  Evan W. Carson¹  Melody J. Saltzgiver²  Deborah Adams²  Brian Kesner³ 

[1] Department of Biology and Museum of Southwestern Biology, University of New Mexico, Albuquerque, NM, USA;School of Life Sciences, Arizona State University, Tempe, AZ, USA;Marsh & Associates, Tempe, AZ, USA

关键词: age structure;    census size;    effective number of breeders;    genetic diversity;    genetic monitoring;   

DOI  :  10.1111/eva.12125

来源: Wiley

【 摘 要 】

Abstract

Time-series analysis is used widely in ecology to study complex phenomena and may have considerable potential to clarify relationships of genetic and demographic processes in natural and exploited populations. We explored the utility of this approach to evaluate population responses to management in razorback sucker, a long-lived and fecund, but declining freshwater fish species. A core population in Lake Mohave (Arizona-Nevada, USA) has experienced no natural recruitment for decades and is maintained by harvesting naturally produced larvae from the lake, rearing them in protective custody, and repatriating them at sizes less vulnerable to predation. Analyses of mtDNA and 15 microsatellites characterized for sequential larval cohorts collected over a 15-year time series revealed no changes in geographic structuring but indicated significant increase in mtDNA diversity for the entire population over time. Likewise, ratios of annual effective breeders to annual census size (N_b/N_a) increased significantly despite sevenfold reduction of N_a. These results indicated that conservation actions diminished near-term extinction risk due to genetic factors and should now focus on increasing numbers of fish in Lake Mohave to ameliorate longer-term risks. More generally, time-series analysis permitted robust testing of trends in genetic diversity, despite low precision of some metrics.

【 授权许可】

CC BY   
© 2013 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.

Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.