This dataset describes the predicted distribution of seagrass communities across the Great Barrier Reef World Heritage Area and adjacent estuaries, based on six multivariate regressions tree models for estuary intertidal, estuary subtidal, coastal intertidal, coastal subtidal, reef intertidal, and reef subtidal. The models are presented as six raster datasets with 30m resolution.
Managing seagrass resources in the GBRWHA requires adequate information on the spatial extent of seagrass communities. The enormous size of the GBRWHA (1000s of kilometres) and the remoteness of many seagrass meadows from human populations means that models are a useful tool to predict where different seagrass communities are likely to be in areas where data is lacking.
James Cook University’s Centre for Tropical Water & Aquatic Ecosystem Research (TropWATER) has been collecting spatial data on GBR seagrass since the early 1980s. This project used TropWATER’s synthesis of seagrass site data (NESP Project 3.1 and 5.4: https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88) to predict seagrass communities.
In making this data publically 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.
Methods:
Seagrass data
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; descriptions and references are available in the metadata for the GBRWHA data composite (https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88).
Environmental data
Environmental predictors used in the models were: depth below mean sea level (Beaman 2017), relative tidal exposure (Bishop-Taylor et al. 2019), water type (Marine Water Bodies definitions version 2_4, Data courtesy of the Great Barrier Reef Marine Park Authority; Dyall et al. 2004), proportion mud in the sediment (coast and reef models, https://research.csiro.au/ereefs/models/model-outputs/access-to-raw-model-output/) (see also Baird et al. 2020; Margvelashvili et al. 2018), dominant sediment (estuary models only; https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88), benthic geomorphology (Heap and Harris 2008), benthic light https://dapds00.nci.org.au/thredds/catalog/fx3/gbr1_bgc_924/catalog.html (see also Baird et al. 2016; Baird et al. 2020), water temperature, mean current speed and salinity https://thredds.ereefs.aims.gov.au/thredds/catalog/ereefs/gbr1_2.0/all-one/catalog.html (Steven et al. 2019), wind speed (https://thredds.ereefs.aims.gov.au/thredds/catalog/ereefs/gbr1_2.0/all-one/catalog.html ) and Australian Bureau of Meteorology’s ACCESS data products (Bureau of Meteorology 2020; Soldatenko et al. 2018; Steven et al. 2019), and latitude. Different models had different combinations of predictors after removing collinear variables and excluding variables that did not extend into an area. For example, estuary models only include depth, relative tidal exposure, dominant sediment, and latitude.
Models
We modelled seagrass communities in six areas: Estuary Intertidal, Estuary Subtidal, Coastal Intertidal, Coastal Subtidal, Reef Intertidal and Reef Subtidal. For each area we used multivariate regression trees to examine changes in seagrass community type within the GBRWHA and adjacent estuaries, using a matrix of seagrass presence/absence site data for 12 seagrass species in the data set. Multivariate regression trees (MRTs) were implemented using the R package mvpart (De’ath 2004) (available in archive form on CRAN at https://cran.r-project.org) in R version 4.0.2 (R Core Team 2020). The map in Figure 1 was created using ArcGIS 10.8.
A detailed description of the modelled communities can be found in the final report for the NESP TWQ Project 5.4 (currently in review).
Spatial limits
Seagrass community types were modelled within potential seagrass habitat. Potential seagrass habitat was modelled by Carter et al. 2020 and is available on eAtlas here: https://eatlas.org.au/data/uuid/108ee868-4fb1-4e5f-ae57-5d65198384cc . The models do not extend north and south of the GBRWHA. The models extend across the continental shelf but exclude waters deeper than ~100m east of the shelf that were not surveyed for seagrass. Data were included when sites extended west of the GBRWHA boundary into coastal and estuarine water immediately adjacent.
Data sets
The site data used in this model is available here: https://eatlas.org.au/data/uuid/5011393e-0db7-46ce-a8ee-f331fcf83a88)
Further information can be found in the upcoming publications of the final report for the NESP TWQ Project 5.4.
Limitations of the data:
The site data used in these models extends back to the mid-1980s. Large parts of the coast have not been mapped for seagrass presence since that time. The seagrass community rasters are at 30m grid resolution, however some environmental variables such as those from eReefs (wind speed, current speed, benthic light, water temperature) are from spatial data at 1km grid resolution, and are likely to vary at much smaller spatial scales that we could not include in these models.
Format:
This dataset consists of six raster datasets with a geographic coordinate system of WGS84. The rasters have been saved as layer packages with symbology representing seagrass communities. These are:
Estuary intertidal communities: GBR_seagrass_communities_estuary_intertidal.lpk
Estuary subtidal communities: GBR_seagrass_communities_estuary_subtidal.lpk
Coastal intertidal communities: GBR_seagrass_communities_coastal_intertidal.lpk
Coastal subtidal communities: GBR_seagrass_communities_coastal_subtidal.lpk
Reef intertidal communities: GBR_seagrass_communities_reef_intertidal.lpk
Reef subtidal communities: GBR_seagrass_communities_reef_subtidal.lpk
References:
TBC
Data Location:
This dataset is filed in the eAtlas enduring data repository at: data\custodian\2019-2022-NESP-TWQ-5\5.4_Seagrass-Burdekin-region
Additional licensing information:
TropWATER gives no warranty in relation to the data (including accuracy, reliability, completeness, currency or suitability) and accepts no liability (including without limitation, liability in negligence) for any loss, damage or costs (including consequential damage) relating to any use of the data. TropWATER reserves the right to update, modify or correct the data at any time. The limitations of some older data included need to be understood and recognised. The TropWATER Seagrass Group would appreciate the opportunity to review documents providing research, management, legislative or compliance advice based on this data.
