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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Bayesian Models of Development
Judy A Stamps1, Willem E Frankenhuis2
1Section of Evolution and Ecology, Division of Biological Sciences, University of California at Davis, Davis, CA 95616, USA.
Abstract:
Until recently, biology lacked a framework for studying how information from genes, parental effects, and different personal experiences is combined across the lifetime to affect phenotypic development. Over the past few years, researchers have begun to build such a framework, using models that incorporate Bayesian updating to study the evolution of developmental plasticity and developmental trajectories. Here, we describe the merits of a Bayesian approach to development, review the main findings and implications of the current set of models, and describe predictions that can be tested using protocols already used by empiricists. We suggest that a Bayesian perspective affords a simple and tractable way to conceptualize, explain, and predict how information combines across the lifetime to affect development.
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