A novel meta-analytical approach to improve systematic review of rates and patterns of microevolution

Ecol Evol. 2017 Jun 20;7(15):5821-5832. doi: 10.1002/ece3.3116. eCollection 2017 Aug.

Abstract

A classic topic in ecology and evolution, phenotypic microevolution of quantitative traits has received renewed attention in the face of rapid global environmental change. However, for plants, synthesis has been hampered by the limited use of standard metrics, which makes it difficult to systematize empirical information. Here we demonstrate the advantages of incorporating meta-analysis tools to the review of microevolutionary rates. We perform a systematic survey of the plant literature on microevolution of quantitative traits over known periods of time, based on the scopus database. We quantify the amount of change by standard mean difference and develop a set of effect sizes to analyze such data. We show that applying meta-analysis tools to a systematic literature review allows the extraction of a much larger volume of information than directly calculating microevolutionary rates. We also propose derived meta-analysis effect sizes (h, LG and LR) which are appropriate for the study of evolutionary patterns, the first being similar to haldanes, the second and third allowing the application of a preexisting analytical framework for the inference of evolutionary mechanisms. This novel methodological development is applicable to the study of microevolution in any taxa. To pilot test it, we built an open-access database of 1,711 microevolutionary rates of 152 angiosperm species from 128 studies documenting population changes in quantitative traits following an environmental novelty with a known elapsed time (<260 years). The performance of the metrics proposed (h, LG and LR) is similar to that of preexisting ones, and at the same time they bring the advantages of lower estimation bias and higher number of usable observations typical of meta-analysis.

Keywords: LRI‐framework; contemporary evolution; haldanes; phenotypic evolution; plant microevolution; quantitative traits.