Dataset: octocoral - sp. abundance and distribution

Name: Octocorals, scleractinia, macroalgae surveys describing species abundance and distribution on St. John and St. Thomas, USVI in 2011 (St. John LTREB project, VI Octocorals project)
Published: 2016-01-06
Keywords: biota, oceans

Cite This Dataset

DOI:10.26008/1912/bco-dmo.630404.1

Spatial Extent: N:18.3833 E:-64.6797 S:18.3023 W:-65.0343

Temporal Extent: 2011 - 2011

Project:

Collaborative research: Ecology and functional biology of octocoral communities (VI Octocorals)

LTREB Long-term coral reef community dynamics in St. John, USVI: 1987-2019 (St. John LTREB)

Principal Investigator:

Peter J. Edmunds (California State University Northridge, CSUN)

Co-Principal Investigator:

Howard Lasker (State University of New York at Buffalo, SUNY Buffalo)

Scientist:

Georgios Tsounis (California State University Northridge, CSUN)

BCO-DMO Data Manager:

Nancy Copley (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version:

Version Date:

2016-01-06

Restricted:

Validated:

Yes

Current State:

Final no updates expected

Octocorals, scleractinia, macroalgae surveys describing species abundance and distribution on St. John and St. Thomas, USVI in 2011 (St. John LTREB project, VI Octocorals project)

Abstract:

Octocorals, scleractinia, macroalgae surveys describing species abundance and distribution on St. John and St. Thomas, USVI in 2011 (St. John LTREB project, VI Octocorals project)

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Archival Copy

Version Date	Archive	Persistent Identifier	Date Assigned
2016-01-06	Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)	10.26008/1912/bco-dmo.630404.1	2023-03-09

Description

Photoquadrats recorded in 2011 on north and south shores of St. John and St. Thomas, USVI, were used to quantify octocoral and scleractinian abundance with generic resolution.

Data used in Edmunds et al., 2015

Original submitted excel file in data file section.

Methods & Sampling

From Edmunds et al (2015) Hydrobiologia:

The study exploited six sites between Cabritte Horn and White Point on the south shore of St. John that have been censused since 1992, and augments data from these sites with 11 new sites sampled in 2011. The six original sites were collapsed to provide a single sampling between Cabritte Horn and White Point, and together with the 11 new sites, an experimental design was created with three sites in each level of a two island x two shore analysis (i.e., with 12 sites). The original sites are at 7-9 m depth on fringing reefs, and since 2000, they have been sampled using ~40 photoquadrats (0.5 x 0.5 m) scattered randomly along a 40 m transect running parallel to the depth contour. To facilitate a comparison among sites on the two islands with similar sampling effort at each site (described below), photoquadrats recorded at the six original sites in 2011 were pooled (n ~ 240 quadrats), and 40 photoquadrats randomly selected for inclusion in the present analysis as representative of the single site between White Point and Cabritte Horn. The advantage of this approach is that it supported a balanced statistical design with ~40 quadrats at each of the 12 sites. Repeated random selections of 40 photoquadrats from the photoquadrats pooled among the original sites did not appreciably alter the mean estimates of coral abundance (data not shown). The 11 new sites were selected haphazardly to sample habitats similar to those evaluated at the original sites, and to sample the north and south shores (i.e., a contrast of exposure) of St. John and St. Thomas at the largest spatial scale that was possible to capture using the small boats available for this project. Sites were not selected with prior knowledge of the benthic communities, and the 40 m transects were placed along the depth contour of the first reef encountered after entering the water. The additional sites are not permanently marked (although the original sites are), but the GPS coordinates are reported in Fig. 1.

Photoquadrats were recorded with a digital camera (Nikon D90, 6.8 megapixels) fitted with an 18-70 mm lens, and two strobes (Nikonos SB 105). The camera was mounted on a framer to hold it perpendicular to the reef, and pictures were taken at random positions along each transect (images archived at http://mcr. lternet.edu/vinp). For scleractinians, images were analyzed for percentage cover by genus using CPCe software (Kohler & Gill, 2006), with 200 dots (10 pixel diameter) randomly placed on each image with the substratum beneath identified and scored. With this technique, ~8000 decisions characterized each site (~96,000 decisions for this study), and here we report analyses including a brief treatment of the cover of scleractinians, macroalgae, and crustose coralline algae, turf, and bare space [combined as CTB (Aronson & Precht, 2000)].

Measurements of planar area is the most widely used means of assessing abundance of benthic organisms on tropical reefs, but the biological interpretation of this metric is equivocal for branching organisms such as arborescent octocorals. Their soft and flexible branches create a canopy whose planar area varies depending on orientation, flow conditions, and height of branches. While percentage cover for such taxa evaluates their impact on the benthos, cover will vary depending on the conditions under which it is recorded, as well as the morphological strategies of the component taxa (e.g., candelabra versus fans), and it is related only loosely to the number of colonies producing the canopy [i.e., substratum occupancy Jackson, 1979)]. To avoid these challenges, we quantified octocoral densities (i.e., colonies 0.25 m-2), with colonies defined by the presence of their holdfast in the photoquadrat (Lenz et al., 2015), or contiguous encrusting colonies (for Erythropodium and encrusting Briareum). Photoquadrats provide an imperfect tool for quantifying arborescent colonies, but we have found densities determined in situ to be correlated with densities determined from photoquadrats, although analyses by photoquadrats are downwardly biased for octocoral density, with this effect intensifying at high densities (Lenz et al., 2015).

Data Processing Description

Preliminary screening of the photoquadrats indicated that 16 scleractinian genera (Orbicella, Montastraea, Agaricia, Colpophyllia, Dendrogyra, Dichocoenia Diploria, Eusmilia, Favia, Madracis, Meandrina, Porites, Stephanocoenia, Siderastrea, Manicina, and Mycetophyllia), 12 octocoral categories consisting of 11 genera (Briareum, Erythropodium, Plexaura, Pseudoplexaura, Eunicea, Plexaurella, Muricea, Muriceopsis, Antillogorgia, Gorgonia,and Pterogorgia), and ‘‘unknown’’ colonies could be identified. Additionally, percentage cover of macroalgae and CTB from Edmunds (2014) was used to provide a more comprehensive analysis of overall community structure on the study reefs.

Site-specific descriptive statistics were calculated from raw data using photoquadrats as replicates (ESM). Overall differences in abundance (pooled genera within the Scleractinia and Octocorallia) between islands, shores, and sites were tested with three-way ANOVA in which islands and shores were fixed effects, and sites were nested in islands and shores. Prior to analyses, percentages were arcsine transformed, abundances transformed to stabilize variances when some of the observations are zero ([x + 3/8]^0.5 [Zar, 2010]), and the statistical assumptions of normality and homoscedasticity tested through graphical analyses of residuals.

Spatial similarity in community structure was visualized using principal coordinates analyses (PCO) and nonmetric multidimensional scaling (MDS). Site-specific means were used to prepare resemblance matrices prepared using Bray-Curtis similarities for three groups of data: (1) overall community structure (scleractinians by genus, octocorals by genus, macroalgae, and CTB), (2) scleractinians by genus, and (3) octocorals by genus. Data were square-root transformed (for scleractinians, macroalgae, and CTB) or fourth-root transformed (octocorals) to adjust for extreme values (the problem was more acute for the octocorals for which many observations were zero). In both cases, the least stringent transformations were applied having verified that the multivariate outcome was broadly robust to the use of more stringent transformations. A PCO was prepared from the resemblance matrix for the overall community structure and was displayed in an ordination plot based on the first two axes. The PCO was combined with vectors with lengths (B 1) revealing the strength of the association between each dependent variable and the PCO axes (defined by Spearman correlation coefficients). The common origin for these vectors was arbitrarily placed on the PCO plot, the terminus of each vectors reveals the form of the relationship with each PCO (either positive or negative relative to the origin of the vector), and together these tools reveal the dependent variables most influential in determining patterns of similarity among sites.

The resemblance matrices for scleractinians and octocorals (separately) were used to prepare MDS plots with similarity contours (70, 80, and 90% levels) determined through clustering by means of group averages, and sites displayed as bubbles scaled to the combined cover of scleractinians or the combined abundance of octocorals. For octocorals, an additional MDS was prepared without Erythropodium in order to evaluate the impact of this taxon on the similaritybased analyses. Erythropodium was treated this way because estimation of its abundance based on number of colonies was made difficult by the challenges of using photographs to discern the boundaries of small encrusting colonies on topographically complex substrata. The resemblance matrices also were used to prepare PCO plots for scleractinians and octocorals in which the first two axes captured the multivariate structure of the resemblance matrices. When combined with vectors displaying the association between dependent variables and PCOs (as described above), this tool was used to reveal the taxa most influential in determining patterns of similarity among sites, shores, and islands.

Resemblance matrices were also prepared using photoquadrats as replicates, in these cases with the addition of a dummy value (=1) to accommodate paired observations of zero abundance. Transformations and similarities were applied as above, and the resemblance matrices used for three analyses. These resemblance matrices were used in three way PERMANOVAs (one for each of the overall community structure, octocorals, and scleractinians) testing the effect of islands, shores, and sites on multivariate community structure. Site was nested in islands and shores, and the results (Pseudo-F) displayed following 1000 permutations with a probability of occurrence by chance alone (Pperm). The photoquadrat-based resemblance matrices for octocorals, and scleractinians were statistically compared using a Mantel-type test (‘‘RELATE’’ in PRIMER 6 software) in a permutational format (1000 permutations). This test evaluated the extent to which the two resemblance matrices described similar multivariate variation among shores, sites, and islands. Inferential tests involving octocorals were repeated using a resemblance matrix in which Erythropodium was excluded as described above. Univariate statistics were completed using Systat 11, and multivariate analyses were completed using PRIMER 6 (Clark & Gorley, 2006) with PERMANOVA + (Anderson et al., 2008).

BCO-DMO Processing Notes:

- original file: 'All Data_Gorgonians_Scleract.xlsx'
- added conventional header with dataset name, PI name, version date, reference
- renamed parameters to BCO-DMO standard
- reformatted data from columns to rows to conform with database practices
- added lat/lon and photo columns

Data Files

File
hydrobio_2015.csv (Comma Separated Values (.csv), 787.20 KB) MD5:3160f2f375dde5e9ffc8bf4e352fcdca Primary data file for dataset ID 630404
octocoral - sp. abundance and distribution filename: All_Data_Gorgonians_Scleract_Hydrobiol_2015.xlsx (ZIP Archive (ZIP), 90.92 KB) MD5:d1832e54a421c7d33d6661dbd5712de2 Original excel file for dataset 630404. This file has been reworked and put into the BCO-DMO system for improved interoperability.

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-1332915
NSF Division of Ocean Sciences	OCE-1334052
NSF Division of Environmental Biology	DEB-1350146

Deployments

Deployment	Synonyms	Start Date	Platform	Investigator
Edmunds_StThomas		2011-01-01	Virgin Islands	Peter J. Edmunds (Principal Investigator)	data info
Edmunds_VINP		1987-01-01	Virgin Islands National Park	Peter J. Edmunds (Principal Investigator)	data info

Instruments

Camera

Supplied Name: camera

Supplied Description:

Nikon D90 - 6.8 megapixel digital camera

Instrument Type

Generic Name: Camera

Acronym: camera

Community Identifier: http://vocab.nerc.ac.uk/collection/L05/current/311/

Generic Description:

All types of photographic equipment including stills, video, film and digital systems.

Parameters

Date and time formats are described in python strftime() syntax.

Supplied Name	Supplied description	Supplied Units	Standard Name
site	sampling location	unitless	site
lat	latitude; north is positive	decimal degrees	lat
lon	longitude; east is positive	decimal degrees	lon
year	year of survey	yyyy	year
island	island of survey	unitless	site
shore	north or south shore of island	unitless	site
station_code	ST=St. Thomas; SJ=St. John; N=north; S=south	unitless	site
photo	randomly assigned number for photoquadrat	unitless	sample
taxon	genus of organism; CTB=crustose coralline algae/algal turf/bare space combined	unitless	taxon
abund_or_pcent_cover	abundance of octocorals or percent cover of scleractinia and macroalgae	specimens/0.25 m^2 or percent	abundance

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Database

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Dataset: octocoral - sp. abundance and distribution