Výsledky vyhledávání - "Poesch, Mark"

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Website visits can predict angler presence using machine learning

Autor: Schmid, Julia S., Simmons, Sean, Lewis, Mark A., Poesch, Mark S., Ramazi, Pouria

Understanding and predicting recreational fishing activity is important for sustainable fisheries management. However, traditional methods of measuring fishing pressure, such as surveys, can be costly and limited in both time and spatial extent. Pred

Externí odkaz: http://arxiv.org/abs/2409.17425

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Analyzing fisher effort -- Gender differences and the impact of Covid-19

Autor: Schmid, Julia S., Simmons, Sean, Poesch, Mark S., Ramazi, Pouria, Lewis, Mark A.

Fishing is a valuable recreational activity in our society. To assess future fishing activity, identifying variables related to differences in fishing activity, such as gender or Covid-19, is helpful. We conducted a Canada-wide email survey of users

Externí odkaz: http://arxiv.org/abs/2409.07492

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Can smartphone apps reveal fishing catch rates and durations?

Autor: Tayebi, Azar T., Schmid, Julia S., Simmons, Sean, Poesch, Mark S., Lewis, Mark A., Ramazi, Pouria

Reliable angler behavior data is important for effective fisheries management. Traditionally, such data is gathered through surveys, but an innovative cost-effective approach involves utilizing online platforms and smartphone applications. Previous s

Externí odkaz: http://arxiv.org/abs/2402.07964

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Can machine learning predict citizen-reported angler behavior?

Autor: Schmid, Julia S., Simmons, Sean, Lewis, Mark A., Poesch, Mark S., Ramazi, Pouria

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 be tracked by online platforms and mobile phone applications that provi

Externí odkaz: http://arxiv.org/abs/2402.06678

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Boosting propagule transport models with individual-specific data from mobile apps

Autor: Fischer, Samuel M., Ramazi, Pouria, Simmons, Sean, Poesch, Mark S., Lewis, Mark A.

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 survey data. Here, user-specific data collected via mobile apps offer new o

Externí odkaz: http://arxiv.org/abs/2105.14284

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