Estuaries and Coasts

, Volume 42, Issue 1, pp 157–172 | Cite as

Recovery of Benthic Microalgal Biomass and Community Structure Following Beach Renourishment at Folly Beach, South Carolina

  • Kristina M. Hill-SpanikEmail author
  • Aubrey S. Smith
  • Craig J. Plante


One method of preserving beaches against the effects of erosion and sea level rise is beach renourishment. While there have been many studies assessing the impact of renourishment on macrofauna, few studies have looked at its effects on microbes. Benthic microalgae (BMA) are important primary producers, representing the basis of nearshore food webs. BMA also secrete extracellular polymeric substances (EPS), which bind sediment and thus help prevent erosion. The objective of this study was to monitor recovery of BMA in terms of relative biomass (estimated as sediment chlorophyll a) and community structure (characterized using high-throughput DNA sequencing) following renourishment of Folly Beach, SC in 2014. We also examined the relationships among biomass, EPS, and erosion. Sediment samples were collected intermittently (n = 9) from two renourished and two control sites within three intertidal zones (high, mid, low) from June 2014 to January 2015. Biomass recovered in sequence from low to high intertidal, corresponding to when the artificially-raised beach once again experienced regular tidal inundation (between 93 and 169 days post-renourishment). Alpha diversity metrics misleadingly indicated recovery around this same time within the high intertidal, but compositional changes through time were unlike those seen in control samples, and these communities had yet to recover at ~ 7 months post-renourishment. Renourishment therefore appears to impact BMA communities via artificial elevation of the beach face. While there were relationships between chl a, EPS, and erosion, BMA most likely play a minimal role in sediment stabilization in high-energy environments like Folly Beach.


Benthic microalgae Microphytobenthos Beach nourishment High-throughput sequencing South Carolina Erosion Extracellular polymeric substances 



We thank the Great Lakes Dredge and Dock Company and the US Army Corps of Engineers for providing access to field sites. We also thank Jennifer Ness at the National Institute of Standards and Technology’s Material Measurement Laboratory for providing training on the Malvern Mastersizer 3000 for particle size analyses and the Hollings Marine Laboratory for access to the facility. Morgan Larimer and Caroline Cooper provided both laboratory and field assistance. Kevin Spanik, Stacy Krueger-Hadfield, Meredith Smylie, Nathan Butcher, and Paige Bippus also provided field assistance. This is Grice Marine Laboratory publication 511.

Funding Information

This work was funded by a Summer Research with Faculty (SURF) grant at The College of Charleston, Charleston, SC. We would also like to acknowledge the Proteogenomics Facility supported by the National Institutes of Health Grants (P30GM103342, P20GM103499) and MUSC’s Office of the Vice President for Research.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Supplementary material

12237_2018_456_MOESM1_ESM.docx (21 kb)
ESM 1 (DOCX 21 kb)
12237_2018_456_MOESM2_ESM.pdf (38 kb)
Supplementary Fig. 1 Median grain size (μm) of sediment collected from control and renourished sites from the a high and b low intertidal zones from June 2014 to January 2015. Samples were sieved (< 1 mm) before analysis to remove shell hash. Error bars represent standard error (PDF 38 kb)
12237_2018_456_MOESM3_ESM.pdf (41 kb)
Supplementary Fig. 2 Mean percent silt-clay in sediment collected from control and renourished sites from a both the high and low intertidal zones, b the high, and c low intertidal zones from June 2014 to January 2015. Error bars represent standard error (PDF 40 kb)
12237_2018_456_MOESM4_ESM.pdf (41 kb)
Supplementary Fig. 3 Mean percent shell hash by volume in sediment collected from control and renourished sites from a both the high and low intertidal zones, b the high, and c low intertidal zones from June 2014 to January 2015. Error bars represent standard error (PDF 40 kb)
12237_2018_456_MOESM5_ESM.pdf (153 kb)
Supplementary Fig. 4 Mean inclusive graphic standard deviation (σ1), a measurement of particle sorting, of sediment samples collected from control and renourished sites from a both the high and low intertidal zones, b the high, and c low intertidal zones from June 2014 to January 2015. All control (C1 and C2) and renourished (R1 and R2) sites are represented for the high intertidal zone because there was a significant difference between the two control replicates. Data from replicate sites were otherwise averaged. σ1 < 0.350, Φ = very well sorted, and > 4.00Φ = extremely poorly sorted (Folk and Ward 1957). Error bars represent standard error (PDF 153 kb)
12237_2018_456_MOESM6_ESM.png (88 kb)
Supplementary Fig. 5 Principal coordinate analysis plot of unweighted UniFrac distances of samples collected from the control and renourished sites from the low intertidal zone from five sampling dates. Groupings are defined based on analysis of similarity results (Supplementary Table 3). t = days post-renourishment (PNG 88 kb)
12237_2018_456_MOESM7_ESM.pdf (102 kb)
Supplementary Fig. 6 Mean maximum erosion measurements taken 24 h after erosion pin deployment at the a high intertidal, b mid intertidal, and c low intertidal zones renourished (R1, R2) and control (C1) sites and mean wind speed by sampling date. Wind data were collected at NOAA Buoy Station FBIS1 (32° 41′ 6″ N 79° 53′ 18″ W) operated by the National Data Buoy Center ( Note the difference in scale for the high intertidal zone. Error bars represent standard error (PDF 102 kb)


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Copyright information

© Coastal and Estuarine Research Federation 2018

Authors and Affiliations

  1. 1.Department of Biology, Grice Marine LaboratoryCollege of CharlestonCharlestonUSA
  2. 2.Medical University of South CarolinaCharlestonUSA

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