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Stochastic population dynamic models as probability networksAuthor(s): M.E. and D.C. Lee Borsuk
Source: In: Jorgensen, S.E.; Chon, T.-S.; Recknagel, F.; Billerica, M.A., eds. Handbook of ecological modelling and informatics. WIT Press. 199-220.
Publication Series: Book
Station: Southern Research Station
PDF: View PDF (341.28 KB)
DescriptionThe dynamics of a population and its response to environmental change depend on the balance of birth, death and age-at-maturity, and there have been many attempts to mathematically model populations based on these characteristics. Historically, most of these models were deterministic, meaning that the results were strictly determined by the equations of the model and random variability was ignored. More recently, population modelers have moved away from deterministic models toward stochastic models that explicitly incorporate random variation and uncertainty [1, 2]. Stochastic models have the advantage of both characterizing the central tendencies of a population (similar to deterministic models) and addressing at least three sources of variability and uncertainty: (1) temporal or spatial variation in population structure and environmental conditions, (2) intrapopulation variation among individuals and (3) uncertainty in parameter estimates.
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CitationBorsuk, M.E. and D.C. Lee. 2009. Stochastic population dynamic models as probability networks. Handbook of ecological modelling and informatics. In: Jorgensen, S.E.; Chon, T.-S.; Recknagel, F.; Billerica, M.A., eds. Handbook of ecological modelling and informatics. WIT Press. 199-220.
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