Browsing by Author "Phelps, Nicholas B. D."
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Item Data and code in support of: Release of live baitfish by recreational anglers drives fish pathogen introduction risk(2022-06-06) McEachran, Margaret C.; Phelps, Nicholas B. D.; Drake, D. Andrew R.; Mladonicky, Janice M.; Picasso, Catalina; thom4412@umn.edu; McEachran, Margaret; University of Minnesota Department of Fisheries, Wildlife and Conservation Biology; University of Minnesota Department of Veterinary Population Medicine; University of Minnesota Gabbert Raptor Center; Fisheries and Oceans Canada Great Lakes Research LaboratoryThis repository contains supplementary information, simulation data, and R computer code to accompany the manuscript titled "Release of live baitfish by recreaional anglers drives fish pathogen introduction risk." The purpose of this project was to quantify the risk of fish pathogen introduction, conceptualized as the number of fish infected with a priority pathogen released in a given year of fishing, under a range of conditions.Item Data for refining copper concentrations using the Biotic Ligand Model to maximize zebra mussel control while minimizing non-target effects(2023-10-12) Dahlberg, Angelique D.; Waller, Diane L.; Severson, Todd J.; Barbour, Matthew T.; Meulemans, Matthew; Wise, Jeremy K.; Bajcz, Alex W.; Jankowski, Mark; Phelps, Nicholas B. D.; edge0023@umn.edu; Dahlberg, Angelique D.Copper in various forms can be toxic to aquatic organisms at high concentrations and has been used as a pesticide in lake management since the early 1900s. Managers have recently extended this use to control aquatic invasive species, including zebra mussels (Dreissena polymorpha). Because copper toxicity changes with changing concentrations of water chemistry parameters (e.g., pH, temperature, and other cations such as Ca2+ and Mg2+), using the same copper concentration to target the same species in two different waterbodies could have different outcomes. However, past zebra mussel control projects have selected copper concentrations irrespective of water chemistry differences. We demonstrate, in a two-part study, how measuring water chemistry parameters and using the Biotic Ligand Model (BLM) can help predict a site-specific copper concentration that will kill zebra mussels while minimizing effects on non-target species. We first tested the application of the BLM for predicting the effects of a copper concentration on non-target species. We found that Daphnia magna (daphnia) had a 50% chance of survival at 9.50 µg Cu/L (i.e., the 50% lethal concentration, LC50), within our BLM-predicted range of 3.38-16.95 µg Cu/L LC50 values. Given the accuracy of our prediction, in the future, managers could make similar predictions and tailor copper concentrations to their management goals. Secondly, we measured zebra mussel larvae (veliger) mortality at added copper concentrations ranging from 0-191 µg Cu/L and assessed exposure–response using a logistic regression model that also included water chemistry parameters. This model can be applied to future projects; using it, managers can predict the amount of copper in a particular waterbody that will kill a predetermined proportion of zebra mussels and simultaneously predict what non-target effects to monitor or expect.Item Data in support of: AIS Explorer: Intervention Impact - An application for planning cost-effective AIS prevention programs(2024-01-22) Angell, Nichole R; Bajcz, Alex; Kinsley, Amy; Keller, Reuben; Phelps, Nicholas B. D.; nangell@glc.org; Angell, Nichole R.; Minnesota Aquatic Invasive Species Research Center (MAISRC)The movement of aquatic invasive species (AIS) between waterbodies is often facilitated by overland transport on recreational boats. Once established, AIS can have detrimental ecological effects that are difficult or impossible to manage. Prevention is the most cost-effective AIS intervention strategy, with many management agencies focused on implementing spread prevention techniques such as boater education, watercraft inspection, and hot water decontamination. Given resource constraints, deciding which spread prevention techniques to implement and where to place them is a decision fraught with uncertainty. In this study, we collected data for, developed, and tested a new application entitled “Intervention Impact” for the AIS Explorer, an online AIS program-planning dashboard (www.aisexplorer.umn.edu). The application assists AIS managers by simulating scenarios derived from user-defined lake-level budgets, effort, and effectiveness of interventions, enabling them to make comparisons. The outputs provide estimates for risk reduction and infestations averted for both zebra mussel and starry stonewort in Minnesota lakes. We demonstrate the utility of this application using the conditions of Cass County, Minnesota, USA as a case study. Our simulation outputs highlight the tradeoffs of each prevention strategy applied given budget constraints and demonstrate that value of a data-driven approach to guide the implementation of cost-effective prevention plans.Item Supplementary files for an expert-based risk ranking framework for assessing potential pathogens in the live baitfish trade(2022-05-06) McEachran, Margaret C.; Travis, Dominic A.; Phelps, Nicholas B. D.; Sampedro, Fernando; thom4412@umn.edu; McEachran, Margaret C.; Minnesota Aquatic Invasive Species Research CenterThe purpose of this study was to develop a “hazard identification” and ranking tool to identify the pathogens that pose the highest risk to wild fish from the release of live baitfish by recreational anglers in freshwater systems. We developed a screening protocol and semi-quantitative stochastic risk ranking framework by combining published data with expert elicitation (n=25) and applied the framework to identify high-priority pathogens for the bait supply in Minnesota, USA. Normalized scores were developed for seven risk criteria (likelihood of transfer, prevalence in bait supply, likelihood of colonization, current distribution, economic impact if established, ecological impact if established, and host species) to characterize a pathogen’s ability to persist in the bait supply and cause impacts to wild fish species of concern. Of an initial list of 33, 15 potential pathogens met the criteria for inclusion and were evaluated using the semi-quantitative framework. The generalist macroparasite Schizocotyle acheilognathi was identified as presenting highest overall threat to wild Minnesota fish, followed by the microsporidian Ovipleistophora ovariae, and viral hemorrhagic septicemia virus. Our findings contribute to the development of risk-based prevention and surveillance methods in support of front-line managers charged with maintaining both the aquatic sporting industry and sustainable, healthy natural resources in Minnesota. In addition, the ranking framework provides a standardized conceptual framework for prioritizing management as novel disease needs emerge.