5 papers
Website visits can predict angler presence using machine learning
Julia S. Schmid, Sean Simmons, Mark A. Lewis +2
Understanding and predicting recreational angler effort is important for sustainable fisheries management. However, conventional methods of measuring angler effort, such as surveys…
Analyzing recreational fishing effort -- Gender differences and the impact of Covid-19
Julia S. Schmid, Sean Simmons, Mark S. Poesch +2
Recreational fishing is an important economic driver and provides multiple social benefits. To predict fishing activity, identifying variables related to variation, such as gender…
Can machine learning predict citizen-reported angler behavior?
Julia S. Schmid, Sean Simmons, Mark A. Lewis +2
Prediction of angler behaviors, such as catch rates and angler pressure, is essential to maintaining fish populations and ensuring angler satisfaction. Angler behavior can partly b…
Webpage Views as a Proxy for Angler Pressure and Effort: Insights from Bayesian Networks
Azar Taheri Tayebi, Julia S. Schmid, Sean Simmons +3
Reliable angler activity data inform fisheries management. Traditionally, such data are gathered through surveys, but an innovative cost-effective approach involves utilizing onlin…
Boosting propagule transport models with individual-specific data from mobile apps
Samuel M. Fischer, Pouria Ramazi, Sean Simmons +2
Management of invasive species and pathogens requires information about the traffic of potential vectors. Such information is often taken from vector traffic models fitted to surve…