Virginia Tech
Non-Linear Density Dependence in a Stochastic Wild Turkey Harvest Model
Abstract
dc:description.abstractCurrent eastern wild turkey (<I>Meleagris gallopavo silvestris</I>) harvest models assume density-independent population dynamics despite indications that populations are subject to a form of density dependence. I suggest that both density-dependent and independent factors operate simultaneously on wild turkey populations, where the relative strength of each is governed by population density. I attempt to estimate the form of the density dependence relationship in wild turkey population growth using the theta-Ricker model. Density-independent relationships are explored between production and rainfall and temperature correlates for possible inclusion in the harvest model. Density-dependent and independent effects are then combined in the model to compare multiple harvest strategies. To estimate a functional relationship between population growth and density, I fit the theta-Ricker model to harvest index time-series from 11 state wildlife agencies. To model density-independent effects on population growth, I explored the ability of rainfall, temperature, and mast during the nesting and brooding season to predict observed production indices for 7 states. I then built a harvest model incorporating estimates to determine their influence on the mean and variability of the fall and spring harvest. Estimated density-dependent growth rates produced a left-skewed yield curve maximized at ~40% of carrying capacity, with large residuals. Density-independent models of production varied widely and were characterized by high model uncertainty. Results indicate a non-linear density dependence effect strongest at low population densities. High residuals from the model fit indicate that extrinsic factors will overshadow density-dependent factors at most population densities. However, environmental models were weak, requiring more data with higher precision. This indicates that density-independence can be correctly and more easily modeled as random error. The constructed model uses both density dependence and density-independent stochastic error as a tool to explore harvest strategies for biologists. The inclusion of weak density dependence changes expected harvest rates little from density-independent models. However, it does lower the probability of overharvest at low densities. Alternatives to proportional harvesting are explored to reduce the uncertainty in annual harvests.
Degree
thesis:*- Name thesis:degree_name
- Ph. D.
- Level thesis:degree_level
- doctoral
- Discipline thesis:degree_discipline
- Fisheries and Wildlife Sciences
- Department dc:contributor.department
- Fisheries and Wildlife Sciences
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 2006
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- McGhee, Jay D.
- Chair dc:contributor.committeechair
-
- Berkson, James M.
- Committee members dc:contributor.committeemember
-
- Vaughan, Michael R.
- Stauffer, Dean F.
- Brewster, Carlyle C.
- Kelly, Marcella J.
Subjects
dc:subject × 6Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Dc Identifier Other
- etd-02102006-161134
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/26164