1 / 8

Investigating the Effects of Protected Slot Limits on Walleye Populations & Angler Harvest

Investigating the Effects of Protected Slot Limits on Walleye Populations & Angler Harvest. MN Large Lakes. Large Lake Data: Many Types of Data Varying Amounts of Data Large Lake Regulations: Different Regulation Types Different Implementation Dates Combined Data from All Large Lakes

hestia
Download Presentation

Investigating the Effects of Protected Slot Limits on Walleye Populations & Angler Harvest

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Investigating the Effects of Protected Slot Limits on Walleye Populations & Angler Harvest

  2. MN Large Lakes Large Lake Data: Many Types of Data Varying Amounts of Data Large Lake Regulations: Different Regulation Types Different Implementation Dates Combined Data from All Large Lakes - Improved Power to Detect Common Effects - Identify Lake-Specific Differences

  3. I like to focus on question first, and at this stage very important to have input from biologists and managers. After have specific hypotheses about effects, we then determine what analysis is appropriate for the available data. What does PSL do to the population? Creates protected group of spawners, harvest smaller & bigger fish Biological Effects: - Recruitment effects? - Growth rate effects? Fishery Effects: - size-specific catch rates? - harvested biomass?

  4. Creel Data • Many Zeroes • Zero is Lower Limit • High Variation

  5. Zero-Inflated Generalized Poisson Regression • Discrete Response Variable • Response ≥ 0 • Combines Three Models: Regression Zero-Inflation Overdispersion For Poisson-distributed variable: E(X) = Var(X) → Model the extra variance as a function of covariates

  6. Mille Lacs Example Analysis Regression Model: Number of Fish per Party ~ Time Fished + Year ZIP: Number of Fish per Party ~ Time Fished + Year P(Zero Catch) = f(DayType) GP: Number of Fish per Party ~ Time Fished Overdispersion = f(DayType) ZIGP: Number of Fish per Party ~ Time Fished + Year P(Zero Catch) = f(DayType) Overdispersion = f(DayType)

  7. Mille Lacs Example Analysis Regression Model: Number of Fish per Party ~ Time Fished + Year ZIP: Number of Fish per Party ~ Time Fished + Year P(Zero Catch) = f(DayType) GP: Number of Fish per Party ~ Time Fished Overdispersion = f(DayType) ZIGP: Number of Fish per Party ~ Time Fished + Year P(Zero Catch) = f(DayType) Overdispersion = f(DayType)

  8. More Analyses Available for different data & questions LM – LMM GLM – GLMM Multivariate (PCA, CCA, MANCOVA) with LL staff, Need to develop Ho’s about PSL Effects & how to test them with available data

More Related