How to describe and measure phenology? An investigation of the diversity of metrics using phenology of births in large herbivores as a case study

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Lucie Thel and Christophe Bonenfant, Laboratoire de Biométrie et Biologie Evolutive, CNRS - Université Lyon 1, Villeurbanne, France, Simon Chamaillé-Jammes, Centre d'Ecologie Fonctionnelle et Evolutive, CNRS - EPHE - IRD, Montpellier, France

Background/Question/Methods
Proposed in 1849 by Charles Morren to depict periodical phenomena governed by seasons, the term “phenology” has spread in many fields, from evolutionary to molecular biology. The adoption of the concept of phenology in such diverse fields has been associated with the creation of a wide diversity of metrics, and we believe, some confusion about what they measure. Here, as an example and to offer some perspective, we studied phenology of births in large herbivores and we identified 52 metrics that were previously used to quantify phenology. We conducted a quantitative analysis of these metrics based on simulations. We compared and classified the metrics using a correlation matrix, and we evaluated the ability of each metric to capture the variation of a set of phenological characteristics via a sensitivity analysis. We finally scored each metric according to eight criteria we thought were important to describe phenology well.
Results/Conclusions
We highlight that four characteristics of phenology are important and can be clearly defined: timing, synchrony, rhythmicity and regularity. We also report on the high correlations that can usually be observed among the metrics corresponding to each of the four characteristics of phenology, suggesting that such diversity of metrics is not useful. Additionally, we show that the best metrics are not necessarily the most commonly used and that simpler is often better: easy to implement metrics often got the best scores. We give some guidelines and advice, in order to facilitate repeatability and comparison of phenologies between studies. We also discuss some pitfalls to avoid when choosing a metric. We trust our study can facilitate the use of well defined and robust concepts and metrics in studies of phenology, for instance in the context of global change effects on populations.