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physics.soc-ph2024
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…
physics.soc-ph2024
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…
physics.soc-ph2024
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…