The what, how, and why of trait‐based analyses in ecology

Functional diversity is increasingly used alongside taxonomic diversity to describe populations and communities in ecology. Indeed, functional diversity metrics allow researchers to summarise complex occupancy patterns in space and/or time across communities and/or populations in response to various stressors. In other words, investigating what, how, and why something is changing in an ecosystem by looking at changes of patterns under a certain process through a specific mechanism. However, as the diversity of functional diversity metrics and methods increases, it is often not directly clear which metric is more readily appropriate for which question. We studied the ability of different functional diversity metrics to recover patterns and signals from different processes linked to common assembly mechanisms in community ecology, such as environmental filtering, competitive exclusion, equalising fitness, and facilitation. Using both simulated data and an empirical dataset affected by more complex and nuanced mechanisms, we tested the effectiveness of different space occupancy metrics to recover the simulated or empirical changes. We show that different metrics perform differently when trying to capture signals from different approximations of common mechanisms relative to no mechanism at all (null). For example, competition was harder to disentangle from the null mechanisms compared to facilitation in our simulations. This emphasises the importance of not using a one‐size‐fits‐all metric. Instead, researchers should carefully consider and test whether a particular metric will be effective in capturing a pattern of interest.