Geology topics

Christopher S. Vandergoot

Publications and source records attributed to Christopher S. Vandergoot.

21 records · Page 2Linked to original sources

USGS2011

Evaluation of two forms of electroanesthesia and carbon dioxide for short-term anesthesia in walleye

Anesthetics immobilize fish, reducing physical damage and stress during aquaculture practices, stock assessment, and experimental procedures. Currently, only tricaine methanesulfonate (MS-222) is approved for use as an anesthetic for food fish in Canada and the United States; however, MS-222 can only be used with certain fish species, and treated fish must be held for a specified period of time before release into the wild. Two forms of electroanesthesia and carbon dioxide (CO 2 ) were evaluated as anesthetics for adult walleye Sander vitreus to determine their suitability for use before intracoelomic implantation of telemetry transmitters. Walleyes were subjected to one of three treatment groups: constant direct current (CDC), pulsed direct current (PDC), and CO 2 . Fish subjected to these treatments were monitored for induction (where appropriate) and recovery time and whether these forms of anesthesia were conducive to implanting telemetry transmitters, that is, whether they fit a surgery threshold range of 250–350 s. Additionally, all fish were monitored for posttrial survival, and radiographs were taken to determine whether any vertebral damage was associated with the electroanesthesia treatments. Although all anesthetic treatments successfully immobilized fish for enough time to implant a transmitter, PDC electroanesthesia is recommended because of its immediate induction time, quick recovery, high immediate and short-term survival, and lack of evidence of vertebral abnormalities.

North American Journal of Fisheries Management↗

USGS2011

Selectivity evaluation for two experimental gill-net configurations used to sample Lake Erie walleyes

We used length frequencies of captured walleyes Sander vitreus to indirectly estimate and compare selectivity between two experimental gill-net configurations used to sample fish in Lake Erie: (1) a multifilament configuration currently used by the Ohio Department of Natural Resources (ODNR) with stretched-measure mesh sizes ranging from 51 to 127 mm and a constant filament diameter (0.37 mm); and (2) a monofilament configuration with mesh sizes ranging from 38 to 178 mm and varying filament diameter (range = 0.20–0.33 mm). Paired sampling with the two configurations revealed that the catch of walleyes smaller than 250 mm and larger than 600 mm was greater in the monofilament configuration than in the multifilament configuration, but the catch of 250–600-mm fish was greater in the multifilament configuration. Binormal selectivity functions yielded the best fit to observed walleye catches for both gill-net configurations based on model deviances. Incorporation of deviation terms in the binormal selectivity functions (i.e., to relax the assumption of geometric similarity) further improved the fit to observed catches. The final fitted selectivity functions produced results similar to those from the length-based catch comparisons: the monofilament configuration had greater selectivity for small and large walleyes and the multifilament configuration had greater selectivity for mid-sized walleyes. Computer simulations that incorporated the fitted binormal selectivity functions indicated that both nets were likely to result in some bias in age composition estimates and that the degree of bias would ultimately be determined by the underlying condition, mortality rate, and growth rate of the Lake Erie walleye population. Before the ODNR switches its survey gear, additional comparisons of the different gill-net configurations, such as fishing the net pairs across a greater range of depths and at more locations in the lake, should be conducted to maintain congruence in the fishery-independent survey time series.

North American Journal of Fisheries Management↗

USGS2009

Evaluating the power to detect temporal trends in fishery independent surveys: A case study based on Gillnets Set in the Ohio waters of Lake Erie for walleye

Fishery-independent (FI) surveys provide critical information used for the sustainable management and conservation of fish populations. Because fisheries management often requires the effects of management actions to be evaluated and detected within a relatively short time frame, it is important that research be directed toward FI survey evaluation, especially with respect to the ability to detect temporal trends. Using annual FI gill-net survey data for Lake Erie walleyes Sander vitreus collected from 1978 to 2006 as a case study, our goals were to (1) highlight the usefulness of hierarchical models for estimating spatial and temporal sources of variation in catch per effort (CPE); (2) demonstrate how the resulting variance estimates can be used to examine the statistical power to detect temporal trends in CPE in relation to sample size, duration of sampling, and decisions regarding what data are most appropriate for analysis; and (3) discuss recommendations for evaluating FI surveys and analyzing the resulting data to support fisheries management. This case study illustrated that the statistical power to detect temporal trends was low over relatively short sampling periods (e.g., 5–10 years) unless the annual decline in CPE reached 10–20%. For example, if 50 sites were sampled each year, a 10% annual decline in CPE would not be detected with more than 0.80 power until 15 years of sampling, and a 5% annual decline would not be detected with more than 0.8 power for approximately 22 years. Because the evaluation of FI surveys is essential for ensuring that trends in fish populations can be detected over management-relevant time periods, we suggest using a meta-analysis–type approach across systems to quantify sources of spatial and temporal variation. This approach can be used to evaluate and identify sampling designs that increase the ability of managers to make inferences about trends in fish stocks.

Ohio↗