To integrate paleoecological data with the “whole fauna” data used in biological monitoring, analyses usually must focus on the subset of taxa that are inherently preservable, for example by virtue of biomineralized hardparts, and those skeletal remains must also be identifiable in fragmentary or otherwise imperfect condition, thus perhaps coarsening analytical resolution to the genus or family level. Here we evaluate the ability of readily preserved bivalves to reflect patterns of compositional variation from the entire infaunal macroinvertebrate fauna as typically sampled by agencies in ocean monitoring, using data from ten long-established subtidal stations in Puget Sound, Washington State. Similarity in compositional variation among these stations was assessed for five taxonomic subsets (the whole fauna, polychaetes, malacostracans, living bivalves, dead bivalves) at four levels of taxonomic resolution (species, genera, families, orders) evaluated under four numerical transformations of the original count data (proportional abundance, square root- and fourth root-transformation, presence-absence). Using the original matrix of species-level proportional abundances of the whole fauna as a benchmark of “compositional variation,” we find that living and dead bivalves had nearly identical potential to serve as surrogates of the whole fauna; they were further offset from the whole fauna than was the polychaete subset (which dominates the whole fauna), but were far superior as surrogates than malacostracans. Genus- and family-level data were consistently strong surrogates of species-level data for most taxonomic subsets, and correlations declined for all subsets with increasing severity of data transformation, although this effect lessened for subsets with high community evenness. The strong congruence of death assemblages with living bivalves, which are themselves effective surrogates of compositional variation in the whole fauna, is encouraging for using bivalve dead-shell assemblages to complement conventional monitoring data, notwithstanding strong natural environmental gradients with potential to bias shell preservation.