The shape of selection: using alternative fitness functions to test predictions for selection on flowering time

Abstract

Selection gradient analysis examines the strength and direction of phenotypic selection as well as the curvature of fitness functions, allowing predictions on and insights into the process of evolution in natural populations. However, traditional linear and quadratic selection analyses are not capable of detecting other features of fitness functions, such as asymmetry or thresholds, which may be relevant for understanding key aspects of selection on many traits. In these cases, additional analyses are needed to test specific hypotheses about fitness functions. In this study we used several approaches to analyze selection on a major life-history trait—flowering time—in the annual plant Brassica rapa subjected to experimentally abbreviated and lengthened growing seasons. We used a model that incorporated a tradeoff between the time allocated to growth versus the time allocated to reproduction in order to predict fitness function shape. The model predicted that optimal flowering time shifts to earlier and later dates as the growing season contracts and expands. It also showed the flowering time fitness function to be asymmetrical: reproductive output increases modestly between the earliest and the optimal flowering date, but then falls sharply with later dates, truncating in a ‘tail of zeros’. Our experimental results strongly supported selection for early flowering in short season and selection for late flowering in long season conditions. We also found support for the predicted asymmetry of the flowering time fitness function, including a ‘tail of zeros’ at later flowering dates. The form of the fitness function revealed here has implications for interpreting estimates of selection on flowering time in natural populations and for refining predictions on evolutionary response to climate change. More generally, this study illustrates the value of diverse statistical approaches to understanding mechanisms of natural selection.