Paper No. 13
Presentation Time: 11:20 AM

METHODS USED TO EXAMINE ENCRUSTATION: WHAT WORKS WHEN?


SMRECAK, Trisha A., Michigan State University, East Lansing, MI 48906, smrecakt@msu.edu

Sclerobionts have been integral components of paleontological study, used to understand encrustation patterns in modern and ancient environments (Bordeaux and Brett 1990; Rodland et al., 2004; Mistiaen et al, 2012), ecological relationships with their hosts and each other (Pitrat and Rogers 1978; Liddell and Brett 1982; Schneider 2003; Bose et al., 2010), and to infer the life habits of their hosts (Richards 1972; Key et al., 2000). In most studies, sclerobiont data on host shells are collected for two primary purposes: obtaining abundance information on the varied taxa, and obtaining spatial locations of those taxa on the host. Yet, methodologies used to collect this information vary widely by author, lowering interpretive value among published studies.

Select Paleozoic sclerobiont-bearing brachiopods were examined following a variety of methodologies. Methods used to collect sclerobiont abundance include encrustation frequency, numerical abundance of taxa, and areal abundance (% cover) of taxa. Spatial patterns of encrustation were collected by partitioning regions (6, 9, 13, and 32) on an idealized host shell and counting the occurrence of each taxon within a region, estimating areal % cover of each taxon and sketching the location on an idealized outline of the host, or photographing the host shell and using ArcGIS to map the location of each taxon.

Ranking sclerobionts according to areal % cover of the host allows colonial and solitary encrusters to receive similar weight and was chosen as a baseline. The rank position of ~ 20% of taxa ordered by numerical abundance changed significantly (>4 places), and 30% of taxa ranked by their encrustation frequency on host shells did the same. Colonial and solitary organisms were both impacted in rank order. Spatially, 6 and 9 region partitions fairly reflect the number of sclerobionts observed in the sample but 13 and 32 region partitions significantly over-represent them. 13 and 32 region partitions also significantly under-represent the number of sclerobionts observed along the commissure of hosts, which is particularly interesting as increased partitioning would presumably increase precision. Understanding the biases in the varied methodologies will allow more highly resolved interpretations among previous studies and enhance analysis in future work.