Geology topics

Michael J. Wilberg

Publications and source records attributed to Michael J. Wilberg.

4 recordsLinked to original sources

USGS2025

Participatory modelling to support evaluation of management actions for recreational fisheries

Participatory modelling (PM) is a collaborative problem-solving approach that involves shared learning through the development of a model or multiple models with a group of participants and a modelling team. PM has the potential to be used more frequently to address recreational fisheries problems. We focus on our experience working with small groups (usually <40 people) to address natural resource issues. This chapter focuses on building a PM team and the communications that occur before, during, and after a PM process. The participants usually include people like recreational and commercial fishers, members of environmental non-governmental organizations, and fishery managers or other decision makers. Ground rules, expectations, and end goals should be established early in the PM process. We emphasize that benefits arise from including the participants in the development and validation of the models in a process that includes feedback between the modellers and participants. Although participants are ideally involved in all stages, their inclusion during model development and testing can be critical for buy-in within the group. When the modellers listen carefully to participant concerns and respond to those concerns during model development, we have experienced favourable process outcomes such as improved participant engagement and building of trust.

Book chapter↗

USGS2016

Tradeoff between assessment and control of aquatic invasive species: A case study of sea lamprey management in the St. Marys River

Allocating resources between the gathering of information to guide management actions and implementing those actions presents an inherent tradeoff. This tradeoff is evident for control of the Sea Lamprey Petromyzon marinus in the St. Marys River, connecting Lakes Huron and Superior and a major source of parasitic Sea Lampreys to Lake Huron and northern Lake Michigan. Larval Sea Lampreys in the St. Marys River are controlled through the application of Bayluscide, which is applied to areas of high larval density. Bayluscide applications are guided with an annual deepwater electrofishing survey to estimate larval Sea Lamprey density at relatively fine spatial scales. We took a resampling approach to describe the effect of sampling intensity on the success of the larval Sea Lamprey management program and explicitly incorporated the economic tradeoff between assessment and control efforts to maximize numbers of larvae killed in the St. Marys River. When no tradeoff between assessment and control was incorporated, increasing assessment always led to more larvae killed for the same treatment budget. When the tradeoff was incorporated, the sampling intensity that maximized the number of larvae killed depended on the overall budget available. Increased sampling intensities maximized effectiveness under medium to large budgets (US \$0.4 to \$2.0 million), and intermediate sampling intensities maximized effectiveness under low budgets. Sea Lamprey control actions based on assessment information outperformed those that were implemented with no assessment under all budget scenarios.

St. Marys River↗

USGS2015

Comparing methods for estimating larval sea lamprey ( Petromyzon marinus ) density in the St. Marys River for the purposes of control

The St. Marys River is a major producer of parasitic sea lampreys ( Petromyzon marinus ) to Lake Huron making it an important area for larval control. Bayluscide treatments are conducted in areas of high larval density requiring density estimation at fine spatial scales to inform treatment decisions. We evaluated six methods of estimating spatially specific density including the currently used sampling-based estimates, a generalized linear model (GLM) based on mean larval density per plot, a GLM based on larval density per sample, a generalized additive model based on mean larval density per plot, a spatial age-structured population model, and a hybrid approach, which averaged the best performing sampling- and model-based methods. Methods were evaluated based on accuracy in matching independent validation data. Specifically, the methods were evaluated based on their ability to project plot-level larval density, identify high density plots for treatment, and rank plots in order based on density resulting in high numbers of sea lampreys killed per hectare treated. Performance was variable, and no single method outperformed the others for all metrics. Although the sampling-based estimation method and the GLM based on catch data performed adequately for estimating density and identifying high density plots, the hybrid approach was identified as the best method to inform sea lamprey control decisions in the St. Marys River due to its consistent performance. Incorporating model-based approaches should lead to a more efficient and effective treatment program in the St. Marys River and aid in making decisions about the allocation of control resources.

St. Marys River↗

USGS2013

A spatial age-structured model for describing sea lamprey ( Petromyzon marinus ) population dynamics

The control of invasive sea lampreys ( Petromyzon marinus ) presents large scale management challenges in the Laurentian Great Lakes. No modeling approach has been developed that describes spatial dynamics of lamprey populations. We developed and validated a spatial and age-structured model and applied it to a sea lamprey population in a large river in the Great Lakes basin. We considered 75 discrete spatial areas, included a stock-recruitment function, spatial recruitment patterns, natural mortality, chemical treatment mortality, and larval metamorphosis. Recruitment was variable, and an upstream shift in recruitment location was observed over time. From 1993–2011 recruitment, larval abundance, and the abundance of metamorphosing individuals decreased by 80, 84, and 86%, respectively. The model successfully identified areas of high larval abundance and showed that areas of low larval density contribute significantly to the population. Estimated treatment mortality was less than expected but had a large population-level impact. The results and general approach of this work have applications for sea lamprey control throughout the Great Lakes and for the restoration and conservation of native lamprey species globally.

Great Lakes↗