APPLICATION OF POPULATION MODELING TECHNIQUES TO WILD TURKEY MANAGEMENT
Abstract: Although population modeling techniques have been available for decades, the advent of the personal computer makes them readily accessible to the biologist. Computerized population models enable us to gain a clearer understanding of ecological relationships and of management alternatives....
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
1990-01-01
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| Series: | Wildlife Society Bulletin |
| Online Access: | https://doi.org/10.1002/j.2328-5540.1990.tb00189.x |
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| Summary: | Abstract: Although population modeling techniques have been available for decades, the advent of the personal computer makes them readily accessible to the biologist. Computerized population models enable us to gain a clearer understanding of ecological relationships and of management alternatives. This paper compares 2 distinct styles of computer modeling: detailed models that incorporate highly specific aspects of life history, and general models that rely on a few parameters to integrate life history processes. Both deterministic and stochastic approaches to modeling populations are reviewed. Selection of the modeling style and approach requires a clear understanding of the objective of the modeling exercise, the data resources, and the environment within which management must operate. Mechanistic models are important where the intent is to gain a deeper understanding of the interaction among various conditions affecting population change. General models are most useful where the objective is to predict future populations. A stochastic approach to modeling is valuable where broad environmental fluctuation affects reproduction or survival, and is especially helpful where turkey (Meleagris gallopavo) populations are small and risk assessment is desired in planning management strategies. General models are shown to be superior to mechanistic models in most management situations. We assert that population modeling will be an essential tool in meeting the management challenges in the next several decades. |
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| ISSN: | 2328-5540 |