The full potential for using DNA barcodes for profiling functional trait diversity has yet to be determined in plants and animals; thus, we outline a general framework for quantifying functional trait diversity of insect community DNA and propose and assess the accuracy of three methods for achieving this. We built a novel dataset of traits and DNA barcodes for wild bees in China. An informatics framework was developed for phylogeny-based integration of these data and prediction of traits for any subject barcodes, which was compared with two distance-based methods. For Phylogenetic Assignment, we additionally conducted a species-level analysis of publically available bee trait data. Under the specimen-level dataset, the rate of trait assignment was negatively correlated with distance between the query and the nearest trait-known reference, for all methods. Phylogenetic Assignment was found to perform best under several criteria; particularly, it had the lowest false-positive rate (rarely returning a state prediction where success was unlikely; where the distance from query to the nearest reference was high). For a wider range of compiled traits, conservative life-history traits showed the highest rates of assignment; for example, sociality was predicted with confidence at 53%, parasitism at 44% and nest location at 33%. As outlined herein, automated trait assignment might be applied at scale to either barcodes or metabarcodes. With further compilation and databasing of DNA barcode and trait data, the rate and accuracy of trait assignment is expected to increase to the point of being a widely viable and informative approach.
Keywords: DNA barcodes; bees; functional trait; trait assignment.
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