AbstractAlthough functional redundancy has received increased attention in the microbial ecology literature, no quantitative functional redundancy measurement is currently available which compares multiple communities and integrates of ‘omics data rather than phenotypic traits. Here, we propose an approach for quantifying functional redundancy that use ‘omics data. This approach, termed trait contribution evenness (TCE), is based on traditional measures of community diversity. We measure functional redundancy of a trait within a community as the evenness in relative contribution of that trait among taxa within the community. This definition has several appealing properties including: TCE is an extension of established diversity theory, functional redundancy measurements from communities with different richness and relative trait contribution by taxa are easily comparable, and any quantifiable trait data (genes copies, protein abundance, transcript copies, respiration rates, etc.) is suitable for analysis. Resilience of a trait to taxa extinctions is often viewed as an ecological consequence of traits with high functional redundancy. We demonstrate that TCE functional redundancy is closely and monotonically related to the resilience of a trait to extinctions of trait-bearing taxa. Finally, to illustrate the applicability of TCE, we analyzed the functional redundancy of eight nitrogen-transforming pathways using 2,631 metagenome-assembled genomes from 47 TARA Oceans sites. We found that the NH4+ assimilation pathway was the most functionally redundant (0.6 to 0.7) while nitrification had the lowest functional redundancy (0 to 0.1). Here, TCE functional redundancy addresses shortfalls of other functional redundancy measurements by providing a generalizable, quantitative, and comparable functional redundancy measurement.ImportanceThe broad application of ‘omics technologies in microbiological studies highlights the necessity of integrating traditional ecological theory with omics data when quantifying community functional redundancy. Such an approach should allow for comparisons in functional redundancy between different samples, sites, and studies. Here, we propose measuring functional redundancy based on an expansion of already existing diversity theory. This approach measures how evenly different members in a community contribute to the overall level of a trait within a community. The utility in the approach proposed here will allow for broad evaluation of traits.