This dataset summarises 30 years of seagrass data collection (1984-2014) within the Great Barrier Reef World Heritage Area
into a GIS shapefile which describes seagrass at 1,169 individual or composite meadows. The data includes information on
species, meadow type and age and reliability of the data. Data is current as of
The data described by this record is current as of 01/12/2016 for use in the Seamap Australia project. Newer versions of
the data, additional 'point' site data, and alternative download formats are available from eAtlas. http://eatlas.org.au/geonetwork/srv/eng/metadata.show?uuid=77998615-bbab-4270-bcb1-96c46f56f85a
In making this data publicly available for management, the authors from the TropWATER Seagrass Group request being contacted
and involved in decision making processes that incorporate this data, to ensure its limitations are fully understood.
Birch, W. R. and Birch, M. 1984. Succession and pattern of tropical intertidal seagrasses in Cockle Bay, Queensland, Australia:
a decade of observations. Aquatic Botany, 19: 343-367
Coles, R., McKenzie, L., De'ath, G., Roelofs, A. and Long, W. L. 2009. Spatial distribution of deepwater seagrass in the
inter-reef lagoon of the Great Barrier Reef World Heritage Area. Marine Ecology Progress Series, 392: 57-68
Coles, R. G., Lee Long, W. J., Watson, R. A. and Derbyshire, K. J. 1993. Distribution of seagrasses, and their fish and penaeid
prawn communities, in Cairns Harbour, a tropical estuary, Northern Queensland, Australia. Marine and Freshwater Research,
Coles, R. G., McKenzie, L. J., Rasheed, M. A., Mellors, J. E., Taylor, H., Dew, K., McKenna, S., L., S. T., B., C. A. and
A., G. 2007. Status and Trends of Seagrass Habitats in the Great Barrier Reef World Heritage Area. Report to the Marine
and Tropical Sciences Research Facility. Reef and Rainforest Research Centre Limited, Cairns, pp.
Fourqurean, J. W., Duarte, C. M., Kennedy, H., Marba, N., Holmer, M., Mateo, M. A., Apostolaki, E. T., Kendrick, G. A., Krause-Jensen,
D., McGlathery, K. J. and Serrano, O. 2012. Seagrass ecosystems as a globally significant carbon stock. Nature Geoscience,
Grech, A., Chartrand-Miller, K., Erftemeijer, P., Fonseca, M., McKenzie, L., Rasheed, M., Taylor, H. and Coles, R. 2012. A
comparison of threats, vulnerabilities and management approaches in global seagrass bioregions. Environmental Research Letters,
Grech, A. and Coles, R. G. 2011. Interactions between a Trawl Fishery and Spatial Closures for Biodiversity Conservation in
the Great Barrier Reef World Heritage Area, Australia. PLoS ONE, 6.6: e21094
Kenworthy, W. J., Wyllie-Echeverria, S., Coles, R. G., Pergent, G. and Pergent-Martini, C. 2006. Seagrass conservation biology:
an interdisciplinary science for protection of the seagrass biome. Page 595-623. In A. W. D. Larkum, R. J. Orth and C.
M. Duarte (eds), Seagrasses: Biology, Ecology and Conservation. Springer, The Netherlands
Kuo, J. and McComb, A. J. 1989. Seagrass taxonomy, structure and development. Page 6-73. In A. W. D. Larkum, A. J. McComb
and S. A. Shepherd (eds), Biology of seagrasses: a treatise on the biology of seagrasses with special reference to the Australian
Region. Elsevier, New York
Lavery, P. S., Mateo, M. A., Serrano, O. and Rozaimi, M. 2013. Variability in the carbon storage of seagrass habitats and
its implications for global estimates of blue carbon ecosystem service. PLoS ONE, 8: e73748
Marsh, H., O'Shea, T. J. and Reynolds III, J. E. 2011. Ecology and conservation of the sirenia: dugongs and manatees. Cambridge
McKenzie, L., Collier, C. and Waycott, M. 2014a. Reef Rescue Marine Monitoring Program: Inshore seagrass, annual report for
the sampling period 1st July 2011 – 31st May 2012. TropWATER, James Cook University, pp.
McKenzie, L. J., Yoshida, R. L., Grech, A. and Coles, R. G. 2014b. Composite of coastal seagrass meadows in Queensland,
Australia - November 1984 to June 2010. PANGAEA.
Mellors, J. E. 1991. An evaluation of a rapid visual technique for estimating seagrass biomass. Aquatic Botany, 42: 67-73
Pendleton, L., Donato, D. C., Murray, B. C., Crooks, S., Jenkins, W. A., Sifleet, S., Craft, C., Fourqurean, J. W., Kauffman,
J. B., Marba, N., Megonigal, P., Pidgeon, E., Herr, D., Gordon, D. and Baldera, A. 2012. Estimating Global "Blue Carbon"
Emissions from Conversion and Degradation of Vegetated Coastal Ecosystems. PLoS One, 7:
Pitcher, C. R., Doherty, P., Arnold, P., Hooper, J., Gribble, N., Bartlett, C., Browne, M., Campbell, N., Cannard, T.,
Cappo, M., Carini, G., Chalmers, S., Cheers, S., Chetwynd, D., Colefax, A., Coles, R., Cook, S., Davie, P., De'ath, G.,
Devereux, D., Done, B., Donovan, T., Ehrke, B., Ellis, N., Ericson, G., Fellegara, I., Forcey, K., Furey, M., Gledhill,
D., Good, N., Gordon, S., Haywood, M., Hendriks, P., Jacobsen, I., Johnson, J., Jones, M., Kinninmoth, S., Kistle, S., Last,
P., Leite, A., Marks, S., McLeod, I., Oczkowicz, S., Robinson, M., Rose, C., Seabright, D., Sheils, J., Sherlock, M., Skelton,
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T., Welna, A. and Yearsley, G. 2007. Seabed Biodiversity on the Continental Shelf of the Great Barrier Reef World Heritage
Area. AIMS/CSIRO/QM/QDPI CRC Reef Research Task Final
Report. 320 pp.
Rasheed, M. A., McKenna, S. A., Carter, A. B. and Coles, R. G. 2014. Contrasting recovery of shallow and deep water seagrass
communities following climate associated losses in tropical north Queensland, Australia. Marine pollution bulletin, 83:
Watson, R. A., Coles, R. G. and Lee Long, W. J. 1993. Simulation estimates of annual yield and landed value for commercial
penaeid prawns from a tropical seagrass habitat, northern Queensland, Australia. Marine and Freshwater Research, 44: 211-220
The sampling methods used to study, describe and monitors seagrass meadows were developed by the TropWATER Seagrass Group
and tailored to the location and habitat surveyed; these are described in detail in the relevant publications (https://research.jcu.edu.au/tropwater).
Methods for data sets collected by CSIRO are reported in Pitcher et al (2007).
1. Location – Latitudes and longitudes are from converted RADAR fix or GPS. Depth is depth below mean sea level (dbMSL) in
2. Seagrass metrics – Visual estimation methods prior to 1990 were mostly percent cover estimates matched to standard photographs.
Data limitations for these early surveys are specific to each survey and advice from the TropWATER data custodians should
be sought for assistance with interpretation. For recent surveys (post-1990) above-ground biomass was determined using a
“visual estimates of biomass” technique (Mellors 1991) using trained observers. A linear regression was calculated for the
relationship between the observer ranks and the harvested values. This regression was used to calculate above-ground biomass
for all estimated ranks made from the survey sites. Biomass ranks were converted into above-ground biomass estimates in
grams dry weight per square metre (g DW m-2) for each site. Observers estimated biomass data using video transects, grabs,
free diving, helicopter and walking:
* Video transect: Commonly used for subtidal meadows at each transect site. A CCTV camera was lowered to the bottom and towed
at drift speed (less than one knot). Footage was observed on a TV monitor and digitally recorded. The recording was paused
at random times and frames selected. From this frame, an observer estimated a rank of seagrass biomass and a species composition.
On completion of the video analysis, the video observer ranked five additional quadrats that had been previously videoed
for calibration. The camera sled included a small collecting net to obtain a specimen for identification.
* van Veen grab: Commonly used for subtidal meadows. A sample of seagrass was collected using a van Veen grab (grab area
0.0625 m2) to identify species present at each site. Species identified from the grab sample were used to inform species
composition assessments made from the recorded video transects (Kuo and McComb 1989), or to record presence/absence where
visibility was too poor for video transects.
* Free diving, helicopter and walking: At each site seagrass above-ground biomass and species composition were estimated
from 0.25 m2 quadrats placed randomly. Seagrass percent cover was recorded at each site. The “visual estimates of biomass”
technique when applied to free diving/helicopter/walking surveys involves ranking while referring to a series of quadrat
photographs of similar seagrass habitats for which the above-ground biomass has been previously measured. The relative proportion
of the above-ground biomass (percentage) of each seagrass species within each survey quadrat was also recorded. Field biomass
ranks were converted into above-ground biomass estimates in grams dry weight per square metre (g DW m-2).
All survey data were entered into a Geographic Information System (GIS) using MapInfo (generally pre-2005) then ArcMap®
software. MapInfo spatial data was converted to ArcMap shapefiles. Rectified colour satellite imagery of the region (Source:
ESRI), field notes and aerial photographs taken from helicopter surveys were used to identify geographical features such
as reef platforms, channels and deep-water drop-offs to assist in determining seagrass meadow boundaries.
- Stable: enduring meadow form; seagrass presence, biomass and area expected to be stable over time and seagrass meadow
expected to be a permanent feature apart from extreme events or sustained long term impacts;
- Variable: meadow presence, biomass and area expected to fluctuate within and among years, but generally some seagrass expected
to be present apart from extreme events or sustained long term impacts;
- Highly variable ephemeral: meadow not persistent over time; at some time periods seagrass will be present and at other
times absent. Ephemeral meadows that have a naturally extreme level of variation in area and biomass within and among years;
- Unknown: undetermined persistence as meadow sampled only once.
- Intertidal - all sites surveyed by helicopter or walking within a meadow and/or comments in field books identified an
- Shallow subtidal - meadows where free divers SCUBA, sled collection, or cameras were used to sample and water depth was
generally <10 m;
- Deep subtidal - for this project meadows >10 m deep were included as deep subtidal.