326
Views
7
CrossRef citations to date
0
Altmetric
ARTICLE

Matching Watershed and Otolith Chemistry to Establish Natal Origin of an Endangered Desert Lake Sucker

, &
Pages 732-743 | Received 27 Aug 2016, Accepted 28 Feb 2017, Published online: 22 May 2017
 

Abstract

Stream habitat restoration and supplemental stocking of hatchery-reared fish have increasingly become key components of recovery plans for imperiled freshwater fish; however, determining when to discontinue stocking efforts, prioritizing restoration areas, and evaluating restoration success present a conservation challenge. In this study, we demonstrate that otolith microchemistry is an effective tool for establishing natal origin of the June Sucker Chasmistes liorus, an imperiled potamodromous fish. This approach allows us to determine whether a fish is of wild or hatchery origin in order to assess whether habitat restoration enhances recruitment and to further identify areas of critical habitat. Our specific objectives were to (1) quantify and characterize chemical variation among three main spawning tributaries; (2) understand the relationship between otolith microchemistry and tributary chemistry; and (3) develop and validate a classification model to identify stream origin using otolith microchemistry data. We quantified molar ratios of Sr:Ca, Ba:Ca, and Mg:Ca for water and otolith chemistry from three main tributaries to Utah Lake, Utah, during the summer of 2013. Water chemistry (loge transformed Sr:Ca, Ba:Ca, and Mg:Ca ratios) differed significantly across all three spawning tributaries. We determined that Ba:Ca and Sr:Ca ratios were the most important variables driving our classification models, and we observed a strong linear relationship between water and otolith values for Sr:Ca and Ba:Ca but not for Mg:Ca. Classification models derived from otolith element : Ca signatures accurately sorted individuals to their experimental tributary of origin (classification tree: 89% accuracy; random forest model: 91% accuracy) and determined wild versus hatchery origin with 100% accuracy. Overall, this study aids in evaluating the effectiveness of restoration, tracking progress toward recovery, and prioritizing future restoration plans for fishes of conservation concern. Our results have further application, such as identifying subpopulations that provide the greatest reproductive contribution to a metapopulation or finding the reproductive area and origin of invasive fishes.

Received August 27, 2016; accepted February 28, 2017 Published online May 22, 2017

ACKNOWLEDGMENTS

Our research was funded by the June Sucker Recovery Implementation Program. Additional support was provided by the U.S. Geological Survey, Utah Cooperative Fish and Wildlife Research Unit (in-kind); the Department of Watershed Sciences, Utah State University; and the Ecology Center, Utah State University. D. A. Pluth, K. Landom, and D. W. Tinsley provided extensive logistical support in the field and laboratory. S. Birdwhistle (Plasma Mass Spectrometry Facility, Woods Hole Oceanographic Institution) provided support with the LA-ICP-MS analysis, and T. Guy (Water Research Laboratory, Utah State University) analyzed the water samples. M. Conner and D. Newell reviewed previous drafts of the manuscript and provided helpful constructive criticism. S. Klobucar provided guidance and support throughout the study. M. Meier (Utah State University) contributed the map of Utah Lake. J. Gaeta provided enthusiasm, support, and statistical advice. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. This research was conducted under Certificate of Registration Number 4COLL6474 (Utah Division of Wildlife Resources) and Protocol Number 2259 (Institutional Animal Care and Use Committee).

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.