Towards robust evolutionary inference with integral projection models
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Integral projection models (IPMs) are extremely flexible tools for ecological and evolutionary inference. IPMs track the distribution of phenotype in populations through time, using functions describing phenotype-dependent development, inheritance, survival and fecundity. For evolutionary inference, two important features of any model are the ability to (i) characterize relationships among traits (including values of the same traits across ages) within individuals, and (ii) characterize similarity between individuals and their descendants. In IPM analyses, the former depends on regressions of observed trait values at each age on values at the previous age (development functions), and the latter on regressions of offspring values at birth on parent values as adults (inheritance functions). We show analytically that development functions, characterized this way, will typically underestimate covariances of trait values across ages, due to compounding of regression to the mean across projection steps. Similarly, we show that inheritance, characterized this way, is inconsistent with a modern understanding of inheritance, and underestimates the degree to which relatives are phenotypically similar. Additionally, we show that the use of a constant biometric inheritance function, particularly with a constant intercept, is incompatible with evolution. Consequently, current implementations of IPMs will predict little or no phenotypic evolution, purely as artifacts of their construction. We present alternative approaches to constructing development and inheritance functions, based on a quantitative genetic approach, and show analytically and through an empirical example on a population of bighorn sheep how they can potentially recover patterns that are critical to evolutionary inference.
Janeiro , M J , Coltman , D W , Festa-Bianchet , M , Pelletier , F & Morrissey , M B 2017 , ' Towards robust evolutionary inference with integral projection models ' Journal of Evolutionary Biology , vol 30 , no. 2 , pp. 270-288 . DOI: 10.1111/jeb.13000
Journal of Evolutionary Biology
© 2016, European Society for Evolutionary Biology. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at onlinelibrary.wiley.com / https://doi.org/10.1111/jeb.13000
M. B. Morrissey is supported by a University Research Fellowship from the Royal Society (London). M. J. Janeiro is supported by a PhD scholarship (SFRH/BD/96078/2013) funded by the Fundação para a Ciência e Tecnologia (FCT).
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