Rethinking community‐weighted means: why geometric averages matter

Community‐weighted means (CWMs) are central metrics in trait‐based ecology, widely used to link species' traits to community assembly and ecosystem function. Traditionally, CWMs are calculated as community‐weighted arithmetic means (arithmetic CWMs), implicitly assuming normally distributed traits. However, most plant traits follow log‐normal distributions, making arithmetic CWMs potentially misleading and biased toward extreme values. Here, we argue for the adoption of community‐weighted geometric means (geometric CWMs) as a statistically robust alternative that better reflects the central tendency of log‐normal traits. We discuss the conceptual rationale, illustrate differences between arithmetic and geometric CWMs using examples, and outline practical recommendations for applying geometric averaging in trait analyses. By acknowledging trait distributions, geometric CWMs can refine ecological inference, improve cross‐study comparability, and advance our understanding of community structure and function.