Assessment of deep-water habitat for crown-of-thorns starfish (COTS) in the Great Barrier Reef (NESP TWQ 3.1.1, JCU)

This project integrated all the available source bathymetry data currently used within the latest gbr100 grid and generated a much higher-resolution gbr30 bathymetry grid (~30 m pixel spacing) over the GBR shelf area. The gbr30 grid is recommended for use as a spatial dataset to feed into the Local and Regional Decision Support Tool (DST) being developed by CSIRO for Integrated Pest Management. Other uses of the grid may extend beyond COTS control efforts to include hydrodynamic modelling, natural hazard assessment, to plan and build offshore infrastructure, and to benefit tourism and fishing.The gbr30 grid was then used to generate spatial datasets and descriptive statistics of 22 selected 'super spreader' and tourism reefs, to better understand the extent of deep-water habitat at these sites. An assessment was conducted on whether submerged banks or deeper reefs may provide deep-water coral habitat for COTS, and the implications for the design of the control program.Methods:* Development of gbr30 bathymetry gridThe project used the following bathymetry datasets to develop the gbr30 grid:- MBES source dataThe Australian Hydrographic Office (AHO)-supplied the majority of multibeam echo sounder (MBES) data on the GBR shelf. Geoscience Australia (GA) provided other MBES data, acquired mostly offshore by Australia’s Marine National Facility vessels and also foreign research vessels transiting through the area. Extensive editing on the source data were conducted using QPS Fledermaus and Caris HIPS&SIPS software, and by applying sound velocity and mean sea level (MSL) tide corrections where necessary.- SBES source dataThe AHO have conducted extensive singlebeam echo sounder (SBES) surveys across the GBR shelf for safety of navigation purposes. Other SBES data were from Maritime Safety Queensland (MSQ), various Queensland Port Authorities and from older National Mapping Division surveys. Data editing were conducted on 3D point clouds generated with Fledermaus software, and lowest astronomical tide (LAT) to MSL tide corrections applied using the Australian Vertical Datum Transformation Tool (AusCoastVDT).- ENC source dataElectronic Navigational Chart (ENC) spot depths were generated from S-57 files provided by the AHO and broadly cover the entire GBR shelf and the upper slope. These spot depths were extracted from S-57 files using an ESRI file geodatabase and the xyz data imported to Fledermaus software for examining as 3D point clouds. The accepted bathymetry data were then exported from Fledermaus and LAT-MSL adjustment conducted with AusCoastVDT prior to interpolation of the depth model.- ALB source dataAirborne lidar bathymetry (ALB) data were from extensive, AHO-supplied Laser Airborne Depth Sounder (LADS) surveys conducted over the GBR since 1993. Other ALB data were from the Sunshine Coast for the CRC for Spatial Information, and from the Torres Strait using the Fugro SHOALS-1000T system. ALB depths are typically limited to ~40 m. Bathymetry data were imported to Fledermaus software for editing and then LAT-MSL adjustment conducted with AusCoastVDT.- ITEM source dataThe ITEM DEM data were derived from the Intertidal Extents Model (ITEM v1.0), a nationalscale gridded dataset characterising the spatial extents of the exposed intertidal zone, based upon a full 28 year time series of Landsat observations. ITEM DEM data have 25 m point spacing and have a MSL vertical datum. This version of the gbr30 grid only has ITEM DEM data southwards from latitude 23° South. Future versions of the grid will include ITEM DEM along the remaining intertidal zone.- SDB source dataSatellite derived bathymetry (SDB) data utilise optical imagery and rely on physics- or empirical-based techniques to extract depth data. The Queensland Government-supplied SDB data were created by Earth Observation and Environmental Services (EOMAP) using physicsbased Landsat8 for the Gladstone area. EOMAP supplied SDB data using physics-based Landsat8 for offshore Coral Sea reefs. Other SDB data used empirical-based Landsat7/8 data to supplement those reefs on the GBR lacking ALB data. SDB data are limited to ~20 m depth.- Coastline source dataCoastline source data are used to ‘pin’ the bathymetry grid at the coast in order to prevent ‘bleeding’ of land into the water during the grid development phase. Coastline data were only used where the higher priority ITEM DEM data were absent, e.g. the coast northwards of latitude 23° South. The Queensland Government-supplied coastline data were rasterised and converted to 25 m point spacing files, then AusCoastVDT used to apply a mean high water springs elevation value to the data.- SRTM Source dataThe 1 arcsec (~27 m) Shuttle Radar Topographic Mission (SRTM) digital surface model (DSM) data were used as land elevation data for the gbr30 model. The DSM data best represents the topography of the mainland and islands, but also includes vegetation features. The 27 m data were resampled to 30 m to match the interpolated bathymetry grid pixel size. During the grid development phase, the SRTM-DSM data were merged onto the interpolated bathymetry grid to complete the gbr30 grid.* Grid developmentThe final grid development phase was conducted using Generic Mapping Tools (GMT) software (Wessel & Smith, 1991), following the methodology used in Becker et al. (2009). The xyz source data were first decimated using GMT blockmedian into individual xyz data files representing single node points at 15 m-resolution. The decimated data files were then concatenated into one large xyz file. Next, GMT blockmedian was conducted on the single large file to decimate the combined data to 30 m-resolution in order to produce one valid depth point for each pixel location to be used in the interpolated bathymetry grid at that same 30 mresolution. The 30 m xyz data were then compared with co-located depths from an underlying base grid, in this case the 250 m-resolution AusBathyTopo grid (Whiteway, 2009). The purpose of using a base grid was to flag any new data that may be greatly in error and thus be rejected, and also to provide underlying bathymetry data for pixels that lack coverage by the new source data. The 'repair and replace' method repairs the AusBathyTopo grid, replacing pixels with newer, higher-resolution data.A grid was made with GMT surface using the difference values between the co-located new data and the underlying base data. GMT surface was used to resample the AusBathyTopo grid to 30 m-resolution. The difference grid and the resampled base grid were then added together with GMT grdmath. This resulting netCDF file was converted into an Environmental Systems Research Institute (ESRI) grid. The SRTM-DSM data were then merged with the interpolated bathymetry grid and clipped to produce the final gbr30 bathymetry grid.Format:This dataset consists of spreadsheets and various geospatial files for each of the 22 'super spreader' reefs, and a shapefile identifying the reefs.Data Location:This dataset is filed in the eAtlas enduring data repository at: data\NESP3\AU_NESP-TWQ-3.1.1_CSIRO_COTS-control-strategies\本项目整合了当前最新GBR100网格（gbr100 grid）中所使用的全部可用水深源数据，在大堡礁（Great Barrier Reef, GBR）陆架区域生成了分辨率更高的GBR30水深网格（约30米像素间距）。推荐将该GBR30网格作为空间数据集，输入至澳大利亚联邦科学与工业研究组织（Commonwealth Scientific and Industrial Research Organisation, CSIRO）为有害生物综合管理开发的本地与区域决策支持工具（Decision Support Tool, DST）中。该网格的应用场景可超越长棘海星（Crown-of-Thorns Starfish, COTS）防控工作范畴，涵盖水动力模拟、自然灾害评估、近海基础设施规划与建设，以及助力旅游业与渔业发展。 随后，研究团队利用GBR30网格生成了22处选定的“超级传播点”珊瑚礁与旅游型珊瑚礁的空间数据集与描述性统计量，以更好地厘清这些区域的深水栖息地范围。此外，研究还评估了水下沙洲与更深的珊瑚礁是否可为长棘海星提供深水珊瑚栖息地，以及该评估结果对防控方案设计的启示。 * GBR30水深网格构建 本项目使用以下水深数据集开发GBR30网格： - 多波束测深系统（Multibeam Echo Sounder, MBES）源数据：澳大利亚水文局（Australian Hydrographic Office, AHO）提供了大堡礁陆架上的大部分多波束测深数据。澳大利亚地球科学局（Geoscience Australia, GA）提供了其余多波束测深数据，这些数据大多由澳大利亚海洋国家设施船队以及途经该区域的外国科研船队在近海采集。研究团队使用QPS Fledermaus与Caris HIPS&SIPS软件对源数据进行了全面编辑，并在必要时应用声速与平均海平面（Mean Sea Level, MSL）潮汐校正。 - 单波束测深系统（Singlebeam Echo Sounder, SBES）源数据：澳大利亚水文局为保障航行安全，已在大堡礁陆架开展了大量单波束测深调查。其余单波束测深数据来自昆士兰州海事安全局（Maritime Safety Queensland, MSQ）、多个昆士兰州港务局以及早期的国家测绘局调查项目。研究团队使用Fledermaus软件对生成的三维点云进行数据编辑，并通过澳大利亚垂直基准转换工具（Australian Vertical Datum Transformation Tool, AusCoastVDT）应用最低天文潮（Lowest Astronomical Tide, LAT）至平均海平面的潮汐校正。 - 电子海图（Electronic Navigational Chart, ENC）源数据：电子海图点测深数据源自澳大利亚水文局提供的S-57格式文件，基本覆盖整个大堡礁陆架与上部斜坡。研究团队使用ESRI文件地理数据库从S-57文件中提取这些点测深数据，并将xyz数据导入Fledermaus软件以三维点云形式进行检视。经确认的水深数据随后从Fledermaus导出，并在插值生成水深模型前通过AusCoastVDT完成最低天文潮至平均海平面的校正。 - 机载激光测深（Airborne Lidar Bathymetry, ALB）源数据：机载激光测深数据源自澳大利亚水文局自1993年起在大堡礁区域开展的大量激光航空测深（Laser Airborne Depth Sounder, LADS）调查。其余机载激光测深数据包括空间信息合作研究中心（CRC for Spatial Information）在阳光海岸采集的数据，以及使用Fugro SHOALS-1000T系统在托雷斯海峡采集的数据。机载激光测深水深数据的有效范围通常约为40米。研究团队将水深数据导入Fledermaus软件进行编辑，随后通过AusCoastVDT完成最低天文潮至平均海平面的校正。 - 潮间带范围模型（Intertidal Extents Model, ITEM）源数据：ITEM DEM数据源自潮间带范围模型v1.0（ITEM v1.0），这是一套全国范围的网格数据集，基于28年完整的陆地卫星（Landsat）观测时间序列，刻画了裸露潮间带的空间分布范围。ITEM DEM数据的点间距为25米，采用平均海平面垂直基准。本版本的GBR30网格仅在南纬23°以南区域纳入了ITEM DEM数据，未来版本的网格将在剩余潮间带区域补充该数据。 - 卫星反演水深（Satellite Derived Bathymetry, SDB）源数据：卫星反演水深数据利用光学影像，基于物理或经验方法提取水深信息。昆士兰州政府提供的卫星反演水深数据由地球观测与环境服务公司（Earth Observation and Environmental Services, EOMAP）使用基于物理模型的陆地卫星8号（Landsat8）数据在格拉德斯通区域生成。EOMAP还使用基于物理模型的陆地卫星8号数据为珊瑚海近海珊瑚礁生成了卫星反演水深数据。其余卫星反演水深数据采用基于经验模型的陆地卫星7/8数据，用于补充大堡礁区域缺乏机载激光测深数据的珊瑚礁。卫星反演水深数据的有效范围通常约为20米。 - 海岸线源数据：海岸线源数据用于在网格构建阶段将水深网格“锚定”至海岸，以防止陆地在插值过程中渗入侵入水域。该数据仅在高优先级的ITEM DEM数据缺失的区域使用，例如南纬23°以北的海岸。昆士兰州政府提供的海岸线数据被栅格化并转换为25米点间距的文件，随后通过AusCoastVDT为数据赋予平均高潮面高程值。 - 航天飞机雷达地形测绘任务（Shuttle Radar Topographic Mission, SRTM）源数据：本研究使用1角秒（约27米）分辨率的航天飞机雷达地形测绘任务数字表面模型（Shuttle Radar Topographic Mission Digital Surface Model, SRTM DSM）数据作为GBR30模型的陆地高程数据。该数字表面模型数据可较好地反映大陆与岛屿的地形，但同时也包含植被特征。研究团队将27米分辨率的数据重采样至30米，以匹配插值生成的水深网格的像素尺寸。在网格构建阶段，研究团队将SRTM DSM数据合并至插值生成的水深网格，以完成GBR30网格的构建。 * 网格开发流程 最终的网格构建阶段使用通用制图工具（Generic Mapping Tools, GMT）软件（Wessel & Smith, 1991）完成，遵循了Becker等人（2009）的方法。首先，使用GMT blockmedian工具将xyz源数据抽稀为代表15米分辨率单个节点的xyz数据文件。随后将抽稀后的文件合并为一个大型xyz文件。接下来，对该大型文件再次使用GMT blockmedian工具进行抽稀，将合并后的数据降至30米分辨率，为该分辨率下的每个像素位置生成一个有效的水深点，用于插值生成水深网格。随后，将30米分辨率的xyz数据与来自基础参考网格的同位置水深数据进行比对，本研究中的基础参考网格为250米分辨率的AusBathyTopo网格（Whiteway, 2009）。使用基础参考网格的目的是标记并剔除存在显著误差的新数据，同时为缺乏新源数据覆盖的像素提供基础水深数据。本研究采用“修复替换法”对AusBathyTopo网格进行修复，使用更新的高分辨率数据替换原有像素。 研究团队使用GMT surface工具基于新数据与基础参考网格的差值生成差值网格。随后使用GMT surface工具将AusBathyTopo网格重采样至30米分辨率。将差值网格与重采样后的基础网格通过GMT grdmath工具相加，得到最终的水深网格。将生成的netCDF文件转换为环境系统研究协会（Environmental Systems Research Institute, ESRI）网格格式。随后将SRTM DSM数据与插值生成的水深网格合并并进行裁剪，得到最终的GBR30水深网格。 * 数据集格式 本数据集包含22处“超级传播点”珊瑚礁对应的电子表格与各类地理空间文件，以及一个用于标识这些珊瑚礁的形状文件。 * 数据存储位置 本数据集存储于eAtlas永久数据仓库中，路径为：dataNESP3AU_NESP-TWQ-3.1.1_CSIRO_COTS-control-strategies\