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Detecting strong spatial and temporal variation in macrobenthic composition on an urban shelf using taxonomic surrogates

Broc S. Kokesh*, Susan M. Kidwell, Adam Tomašových, Shelly M. Walther

*Corresponding author:

ABSTRACT: Surrogates of macrobenthic assemblages, intended to alleviate the effort and taxonomic expertise required for monitoring, can take many forms, such as using coarser taxonomic levels (‘sufficiency’) or only a subset of the whole fauna (‘subsetting’). Here, the power of both approaches to retain community-level patterns of spatial and temporal variation were evaluated using an exceptionally long (47-year) infaunal dataset generated from monitoring wastewater impacts on an urban shelf in southern California. Four taxonomic sets (whole infauna, polychaetes, bivalves, malacostracans) were evaluated at five resolutions (species, genus, family, order, functional guild) along a pollution gradient subdivided into two spatial bins based on proximity to the wastewater outfall (near-field vs far-field) and three temporal bins based on wastewater treatment phases. All taxonomic sets detected weakening of the spatial gradient with improved wastewater treatment − communities became more similar in richness, evenness, and composition through time − and patterns were robust when coarsened to families or guilds. Polychaetes mirrored (‘proxied’) whole-fauna patterns most accurately, as expected since they constitute most of individuals and species. However, bivalves outperformed all other sets in detecting (‘indicating’) the pollution gradient itself, owing to their breath of feeding strategies. These results strengthen the consistently positive results from taxonomic coarsening emerging from tests elsewhere and the caveats for taxonomic subsetting: clade strengths serve different objectives. Comparable datasets should exist in environmental agency archives elsewhere, promoting the general surrogacy model. For monitoring programs still in their planning stage, regional insights could be acquired via analogous nested analyses of a single survey.