Disentangling evolutionary, plastic and demographic processes underlying trait dynamics: a review of four frameworks

Abstract

Summary Biologists are increasingly interested in decomposing trait dynamics into underlying processes, such as evolution, plasticity and demography. Four important frameworks that allow for such a decomposition are the quantitative genetic animal model (AM), the ‘Geber’ method (GM), the age‐structured Price equation (APE) and the integral projection model (IPM). However, as these frameworks have largely been developed independently, they differ in the assumptions they make, the data they require, as well as their outcomes and interpretation. Here, we evaluate how each framework decomposes trait dynamics into underlying processes. To do so, we apply them to simulated data for a hypothetical animal population. Individual body size was affected by, among others, genes, maternal effects and food intake. We simulated scenarios with and without selection on body size and with high and low heritability. The APE and IPM provided similar results, as did the AM and GM, with important differences between the former and the latter. All frameworks detected positive contributions of selection in the high but not in the low selection scenarios. However, only the AM and GM distinguished between the high and low heritability scenarios. Furthermore, the AM and GM revealed a high contribution of plasticity. The APE and IPM attributed most of the change in body size to ontogenetic growth and inheritance, where the latter captures the combined effects of plasticity, maternal effects and heritability. We show how these apparent discrepancies are mostly due to differences in aims and definitions. For example, the APE and IPM capture selection, whereas the AM and GM focus on the response to selection. Furthermore, the frameworks differ in the processes that are ascribed to plasticity and in how they take into account demography. We conclude that no single framework provides the ‘true’ contributions of evolution, plasticity and demography. Instead, different research questions require different frameworks. A thorough understanding of the different definitions of their components is necessary for selecting the most appropriate framework for the question at hand and for making biologically meaningful inferences. This work thus supports both future analysis and the careful interpretation of existing work.

Population‐level responses to temperature, density and clonal differences in Daphnia magna as revealed by integral projection modelling

“…The role of evolution in short‐term adaptive trait changes is recently receiving much attention (van Benthem et al., ; Ellner, Geber, & Hairston, ; Pelletier et al., ; Schoener, ), and rapid evolutionary responses have now been shown in many experimental systems (e.g. Becks, Ellner, Jones, & Hairston, ; Cameron, O'Sullivan, Reynolds, Piertney, & Benton, ; Turcotte, Reznick, & Daniel Hare, ).…”

“…To avoid local extinction, populations must appropriately respond to these increasing temperatures, for instance by phenotypic plasticity or by evolution (Gienapp, Teplitsky, Alho, Mills, & Merilä, ; Hoffmann & Sgrò, ). However, disentangling plastic and evolutionary processes is not straightforward, and predicting their relative importance in natural populations is a major challenge (van Benthem et al., ; Chevin, Collins, & Lefèvre, ; Lavergne, Mouquet, Thuiller, & Ronce, ; Pelletier, Garant, & Hendry, ; Schoener, ).…”

Demographic responses underlying eco‐evolutionary dynamics as revealed with inverse modelling

“…These eco‐evolutionary dynamics potentially play an important role in shaping populations, communities and ecosystems (Bassar, Marshall, et al., ; Fussmann, Loreau, & Abrams, ; Matthews, Aebischer, Sullam, Lundsgaard‐Hansen, & Seehausen, ; Strauss, ). Discriminating between ecological and evolutionary processes and quantifying their relative importance are challenging, especially in natural populations, but different frameworks exist that aim to disentangle different processes (Coulson & Tuljapurkar, ; Ellner, Geber, & Hairston, ; Hairston et al., ; van Benthem et al., ). Experiments on eco‐evolutionary dynamics can be very useful in addition to long‐term field observations, as experiments allow for manipulating and tracking ecological and evolutionary processes (Becks, Ellner, Jones, & Hairston, ; Turcotte, Reznick, & Daniel Hare, ; Yoshida, Jones, Ellner, Fussmann, & Hairston, ).…”

Mountain sheep management using data versus opinions: A comment on Boyce and Krausman (2018)

“…They cite van Benthem et al () to claim that “the animal model from quantitative genetics estimates evolution with a negative bias.” Van Benthem et al () report a negative bias only when simulated maternal effects decrease but are not correctly modeled. More relevant to this discussion, van Benthem et al (), like several others (Hedrick et al , Chevin , Janeiro et al ) demonstrate that the Integral Projection Model in Traill et al (), claiming that changes in horn size at Ram Mountain were demographic, cannot detect even strong evolutionary changes. Despite having been refuted by multiple publications, Traill et al () is frequently cited in this Special Section as evidence against evolutionary change in bighorn sheep horn size.…”