Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Parameters
• Deployments
• Project Information
• Funding

Data supporting Gambrel, B. and Lasker, H.R., 2016

Methodology from Gambrel, B. and Lasker, H.R., 2016

To further examine the spatial distribution of colonies and potential competition among them, nearest neighbor data were collected along the belt transects from each site. Each transect had 20 sampling points arranged at the corners of every 1 m2 quadrat along the first 9 m of each transect. The octocoral colony closest to each sampling point was selected, identified,and the distance between its base and the base of its nearest branching octocoral neighbor was measured to the nearest centimeter (Fig. S1 in the Supplement). The height, width, and length of each colony was measured to the nearest centimeter to calculate cross-sectional area (height × length) and volume (height × width × length), and the proximity of the colony’s branches to nearby octocorals was also noted. Due to the water flow and the resulting oscillation of colony branches, measurements were made when the branches were vertical in the water column to optimize the precision of our measurements.To increase sample sizes, an additional 9 m transect parallel to the other 5 was sampled at each site.

The nature of the spatial distribution of octocorals at each site was determined from the nearest-neighbor data following Clark & Evans (1954). Observed and expected mean distances between the octocoral neighbors were calculated using the total distance between neighbors, sample size (120 pairs of octocorals per site) and the density of octocorals at each site(calculated from the belt transect data). The ratio (R)of the observed and expected (given a randomly distributed octocoral community) mean distances between octocoral neighbors describes the octocoral distribution at each site, where R = 1 denotes a random distribution, R < 1, an aggregated distribution,and R > 1, a uniform distribution (Clark & Evans1954). The significance of R was determined by analyzing the standard variate of the normal curve (c), since the measured distances between neighbors in a randomly dispersed community are expected to follow a normal distribution.

The effects of colony−colony proximity on colony size were assessed by correlating the distance between neighbors at the base with the sum of their sizes (Pielou 1962). If competition affects growth, then the closer the organisms are, the smaller their expected sizes will be (Pielou 1962). Implicit in these analyses is the notion that size is both an indicator of resource use and of success in acquiring resources.

The relationships among the distance between octocoral neighbors at the base (divided into 3 distance groups to make the data categorical: 5−14 cm, 15−24 cm and 25−34 cm), branch proximity and site were analyzed using a hierarchical log-linear test in SPSS. The relationship between the distance between neighbors and branch proximity was further analyzed in a separate log-linear test in SPSS.

BCO-DMO Data Processing Notes:

- filled blank cells with "nd"
- replaced spaces with underscores
- replaced species codes with full names
- added latitudes and longitudes to data

Long Term Research in Environmental Biology (LTREB) in US Virgin Islands:

From the NSF award abstract:
In an era of growing human pressures on natural resources, there is a critical need to understand how major ecosystems will respond, the extent to which resource management can lessen the implications of these responses, and the likely state of these ecosystems in the future. Time-series analyses of community structure provide a vital tool in meeting these needs and promise a profound understanding of community change. This study focuses on coral reef ecosystems; an existing time-series analysis of the coral community structure on the reefs of St. John, US Virgin Islands, will be expanded to 27 years of continuous data in annual increments. Expansion of the core time-series data will be used to address five questions: (1) To what extent is the ecology at a small spatial scale (1-2 km) representative of regional scale events (10's of km)? (2) What are the effects of declining coral cover in modifying the genetic population structure of the coral host and its algal symbionts? (3) What are the roles of pre- versus post-settlement events in determining the population dynamics of small corals? (4) What role do physical forcing agents (other than temperature) play in driving the population dynamics of juvenile corals? and (5) How are populations of other, non-coral invertebrates responding to decadal-scale declines in coral cover? Ecological methods identical to those used over the last two decades will be supplemented by molecular genetic tools to understand the extent to which declining coral cover is affecting the genetic diversity of the corals remaining. An information management program will be implemented to create broad access by the scientific community to the entire data set.

The importance of this study lies in the extreme longevity of the data describing coral reefs in a unique ecological context, and the immense potential that these data possess for understanding both the patterns of comprehensive community change (i.e., involving corals, other invertebrates, and genetic diversity), and the processes driving them. Importantly, as this project is closely integrated with resource management within the VI National Park, as well as larger efforts to study coral reefs in the US through the NSF Moorea Coral Reef LTER, it has a strong potential to have scientific and management implications that extend further than the location of the study.

The recent past has not been good for coral reefs, and journals have been filled with examples of declining coral cover, crashing fish populations, rising cover of macroalgae, and a future potentially filled with slime. However, reefs are more than the corals and fishes for which they are known best, and their biodiversity is affected strongly by other groups of organisms. The non-coral fauna of reefs is being neglected in the rush to evaluate the loss of corals and fishes, and this project will add on to an on-going long term ecological study by studying soft corals. This project will be focused on the ecology of soft corals on reefs in St. John, USVI to understand the Past, Present and the Future community structure of soft corals in a changing world. For the Past, the principal investigators will complete a retrospective analysis of octocoral abundance in St. John between 1992 and the present, as well as Caribbean-wide since the 1960's. For the Present, they will: (i) evaluate spatio-temporal changes between soft corals and corals, (ii) test for the role of competition with macroalgae and between soft corals and corals as processes driving the rising abundance of soft corals, and (iii) explore the role of soft corals as "animal forests" in modifying physical conditions beneath their canopy, thereby modulating recruitment dynamics. For the Future the project will conduct demographic analyses on key soft corals to evaluate annual variation in population processes and project populations into a future impacted by global climate change.

This project was funded to provide and independent "overlay" to the ongoing LTREB award (DEB-1350146, co-funded by OCE, PI Edmunds) focused on the long-term dynamics of coral reefs in St. John.

Note: This project is closely associated with the project "RAPID: Resilience of Caribbean octocorals following Hurricanes Irma and Maria". See: https://www.bco-dmo.org/project/749653.

The following publications and data resulted from this project:
2017 Tsounis, G., and P. J. Edmunds. Three decades of coral reef community dynamics in St. John, USVI: a contrast of scleractinians and octocorals. Ecosphere 8(1):e01646. DOI: 10.1002/ecs2.1646
Rainfall and temperature data
Coral and macroalgae abundance and distribution
Descriptions of hurricanes affecting St. John

2016 Gambrel, B. and Lasker, H.R. Marine Ecology Progress Series 546: 85–95, DOI: 10.3354/meps11670
Colony to colony interactions
Eunicea flexuosa interactions
Gorgonia ventalina asymmetry
Nearest neighbor surveys

2015 Lenz EA, Bramanti L, Lasker HR, Edmunds PJ. Long-term variation of octocoral populations in St. John, US Virgin Islands. Coral Reefs DOI 10.1007/s00338-015-1315-x
octocoral survey - densities
octocoral counts - photoquadrats vs. insitu survey
octocoral literature review
Download complete data for this publication (Excel file)

2015 Privitera-Johnson, K., et al., Density-associated recruitment in octocoral communities in St. John, US Virgin Islands, J.Exp. Mar. Biol. Ecol. DOI: 10.1016/j.jembe.2015.08.006
octocoral density dependence
Download complete data for this publication (Excel file)

Other datasets related to this project:
octocoral transects - adult colony height