Abstract

Title:  A Population Model and Decision-making Framework for Managing Deer Hunter Populations
Author(s): Jennifer L. Price - School of Forestry and Wildlife Sciences, Auburn University; Stephen S. Ditchkoff - School of Forestry and Wildlife Sciences, Auburn University; Conor P. McGowan - USGS, Alabama Cooperative Fish and Wildlife Research Unit, School of Forestry and Wildlife Sciences, Auburn University
Year: 2016
Abstract: In recent decades U.S. hunter populations have been on the decline, which reduces funds available to state wildlife agencies and limits agency capacity to manage wild populations. As long as financial support for the North American Model of Wildlife Conservation relies on the hunter-generated funds, declines in hunter participation are a threat to the conservation of both game and non-game species. To sustain funding, wildlife management agencies might benefit by setting objectives for and managing hunter populations. In order to address options to bolster hunter participation and evaluate the potential to sustain or increase hunter populations, we developed a stage-based, stochastic population model of a hunter population in order to predict trends over the next 50 years. The model included the stages "youth", "potential hunter", "annual hunter", and "life time hunter" and allowed for transitions between stages. We then evaluated the effect of hypothetical management actions to demonstrate the utility of the model to inform state agencies interested in boosting recruitment and retention rates of hunters. Finally, we parameterized the model using expert opinion and license sale data obtained from the Alabama Department of Conservation and Natural Resources. Using our model as the core of a decision analysis, state agencies can set hunter population or license revenue targets and evaluate management actions to achieve those objectives. Our model could be directly linked to a game species population model to account for the effects of hunters on games species and the effect of game species abundance on hunter populations. Results from our model demonstrate the utility of using population models to inform management of hunters and hunting-generated conservation funds.

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