Work

Rethinking community‐weighted means: why geometric averages matter

Year: 2026

Type: article

Abstract: 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.

Source: Oikos

DOI: 10.1002/oik.12190

Authors: Congcong Liu, Xiaowen Yang, Ying Li, Nianpeng He

Institutions: Minzu University of China, Beijing Forestry University, Chinese Academy of Sciences, Northeast Forestry University

Language: English

Topic: Ecology and Vegetation Dynamics Studies

Subfield: Nature and Landscape Conservation

Field: Environmental Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,640

Funders: National Natural Science Foundation of China, Minzu University of China, National Key Research and Development Program of China