Time‐series analysis reveals genetic responses to intensive management of razorback sucker (Xyrauchen texanus). (15th November 2013)

• Record Type: Journal Article
• Authors: Dowling, Thomas E.; Turner, Thomas F.; Carson, Evan W.; Saltzgiver, Melody J.; Adams, Deborah; Kesner, Brian; Marsh, Paul C.
• Is Part Of: Evolutionary applications. Volume 7:Number 3(2014)
• Page Start: 339
• Page End: 354
• Publication Date: 2013-11-15
• Subjects: Evolution (Biology) -- Periodicals; Genetics -- Periodicals; Natural selection -- Periodicals; Ecology -- Periodicals; 576.8
• DOI: 10.1111/eva.12125
• Languages: English
• ISSNs: 1752-4571

Abstract

<abstract abstract-type="main" id="eva12125-abs-0001"> <title>Abstract</title> <p>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 (<italic>N</italic><sub>b</sub><italic>/N</italic><sub>a</sub>) increased significantly despite sevenfold reduction of <italic>N</italic><sub>a</sub>. 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.</p> </abstract>