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Abstract:
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Stage structured matrix models provide an effective tool for modeling long-term population dynamics. However it can be difficult to capture short term transient behavior, particularly if there is heterogeneity within the stages observed in data. We present a method for introducing unobserved latent population stages as a method for increasing model richness, and accounting for unobserved heterogeneity. Latent stages may have their own dynamics, and are related to data by requiring them to sum to the mean of observed stages. This allows for the creation of flexible models for complex population dynamics that fit within the stage structured matrix model structure, and are therefore simple to implement and interpret. The method is applied to data on spore development in the common fungus Colletotricum acutatum under laboratory settings. While simple models based on observed stages fail to reflect short term trends, the latent stage model successfully captures the short and long term dynamics of spore development.
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