10Although functional redundancy has received increased attention in the microbial ecology 11 literature, no quantitative functional redundancy measurement is currently available which 12 compares multiple communities and integrates of 'omics data rather than phenotypic traits. Here, 13 we propose an approach for quantifying functional redundancy that use 'omics data. This 14 approach, termed trait contribution evenness (TCE), is based on traditional measures of 15 community diversity. We measure functional redundancy of a trait within a community as the 16 evenness in relative contribution of that trait among taxa within the community. This definition 17 has several appealing properties including: TCE is an extension of established diversity theory, 18 functional redundancy measurements from communities with different richness and relative trait 19 contribution by taxa are easily comparable, and any quantifiable trait data (genes copies, protein 20 abundance, transcript copies, respiration rates, etc.) is suitable for analysis. Resilience of a trait 21 to taxa extinctions is often viewed as an ecological consequence of traits with high functional 22 redundancy. We demonstrate that TCE functional redundancy is closely and monotonically 23 related to the resilience of a trait to extinctions of trait-bearing taxa. Finally, to illustrate the 24 applicability of TCE, we analyzed the functional redundancy of eight nitrogen-transforming 25 pathways using 2,631 metagenome-assembled genomes from 47 TARA Oceans sites. We found 26 that the NH 4 + assimilation pathway was the most functionally redundant (0.6 to 0.7) while 27 nitrification had the lowest functional redundancy (0 to 0.1). Here, TCE functional redundancy 28 addresses shortfalls of other functional redundancy measurements by providing a generalizable, 29 quantitative, and comparable functional redundancy measurement. 30 Importance 31 The broad application of 'omics technologies in microbiological studies highlights the 32 necessity of integrating traditional ecological theory with omics data when quantifying 33 community functional redundancy. Such an approach should allow for comparisons in functional 34 redundancy between different samples, sites, and studies. Here, we propose measuring functional 35 redundancy based on an expansion of already existing diversity theory. This approach measures 36 how evenly different members in a community contribute to the overall level of a trait within a 37community. The utility in the approach proposed here will allow for broad evaluation of traits.38 42 frequently performed simultaneously by many taxa (5). This is referred to as functional 43 redundancy (6).
44The level of functional redundancy in a microbiome has been shown to affect ecosystem 45 function in diverse environments. For instance, high functional redundancy in freshwater 46 sediments resulted in stabilized porewater redox conditions (7). In surface seawater, a 47 metagenomic analysis of glycosyl hydrolase genes demonstrated a complex successional pa...