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Using stochastic models to incorporate spatial and temporal variability [Exercise 14]Author(s): Carolyn Hull Sieg; Rudy M. King; Fred Van Dyke
Source: In: Van Dyke, Fred, ed. A Workbook In Conservation: Solving Practical Problems in Conservation. New York, NY: McGraw-Hill. p. 109-113.
Publication Series: Book Chapter
Station: Rocky Mountain Research Station
PDF: Download Publication (401.38 KB)
DescriptionTo this point, our analysis of population processes and viability in the western prairie fringed orchid has used only deterministic models. In this exercise, we conduct a similar analysis, using a stochastic model instead. This distinction is of great importance to population biology in general and to conservation biology in particular. In deterministic models, transition probabilities are held constant throughout the projected time period, and populations are allowed to increase without bound (Beissinger and Westphal 1998). Deterministic models are mathematically convenient, but biologically unrealistic. As population biologist Robert Lacy has noted, "With the exception of aging, almost all events in the life of an organism are stochastic." (Lacy 1993).
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CitationSieg, Carolyn Hull; King, Rudy M.; Van Dyke, Fred. 2003. Using stochastic models to incorporate spatial and temporal variability [Exercise 14]. In: Van Dyke, Fred, ed. A Workbook In Conservation: Solving Practical Problems in Conservation. New York, NY: McGraw-Hill. p. 109-113.
Keywordsstochastic model, spatial and temporal variability, western prairie fringed orchid
- The western prairie fringed orchid (Platanthera praeclara): monitoring and research
- The concept and use of elasticity in population viability models [Exercise 13]
- Spatial and temporal optimization in habitat placement for a threatened plant: the case of the western prairie fringed orchid
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