Sea urchin size and biomass with respect to Clathromorphum bioerosion at central and western Aleutian Islands, Alaska from visual surveys, July 2014 (NCEI Accession 0278876)

This dataset contains biological data collected on R/V Point Sur during cruise PS1409 in the Bering Sea from 2014-07-04 to 2014-07-21. These data include biomass and depth. These data were collected by Douglas B. Rasher of Bigelow Laboratory for Ocean Sciences, James Estes of University of California-Santa Cruz, and Robert S. Steneck of University of Maine as part of the "Ocean Acidification: Century Scale Impacts to Ecosystem Structure and Function of Aleutian Kelp Forests (OA Kelp Forest Function)" project and "Science, Engineering and Education for Sustainability NSF-Wide Investment (SEES): Ocean Acidification (formerly CRI-OA) (SEES-OA)" program. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) submitted these data to NCEI on 2019-02-25.

The following is the text of the dataset description provided by BCO-DMO:

Target site benthic survey urchin size and biomass - 2014

Dataset Description:
Acquisition Description:
Prior to examining Clathromorphum bioerosion at each focal study site, we characterized sea urchin community structure at each site by quantifying the density, size frequency distribution, and biomass of the sea urchin community (primarily Strongylocentrotus polyacanthus ), using the same methods that have been employed by us and others over the past 30 years (Estes et al. 2010). We characterized two types of sites: (1) those that have long persisted as urchin barrens (“habitat.type” = “Barren”) and (2) urchin barrens that are situated immediately adjacent to shallow, remnant kelp stands, and thereby receive urchin food subsidies (“habitat.type” = “Barren + kelp subsidy”). At these latter sites, we also surveyed the adjacent kelp stand (“habitat.type” = “Shallow kelp”).

At each site, a diver placed a 0.25-m^2 quadrat at the target depth and counted all urchins within the quadrat, then collected the urchins in a bag. The diver then took a random number of kicks along the same depth contour and repeated this process until 20 quadrats were sampled or 200 urchins collected, whichever occurred first. If 200 urchins were collected quickly, additional density counts were made to yield a better density estimate (n = 4 minimum). Shipside, we measured the size (test diameter; mm) of each collected urchin with calipers. We then calculated its biomass using a known size-weight relationship (Estes et al. 2010). To estimate total urchin biomass for a site (grams per 0.25-m^2), we summed the biomass of all urchins collected at the site and divided that sum by the number of quadrats deployed.