The current digital surface models (DSMs) represent scaled, 3D, representations of benthic communities at EcoRRAP study sites. DSMs are generated from raw imagery collected by divers (see SOP #14, Reef monitoring sampling methods | AIMS) and processed using photogrammetry software Agisoft Metashape. DSMs can be used to extract a range of data describing 3D habitat characterstics at both plot and colony scale, including: rugosity, surface area, and volume. Comparison of DSMS between years can also be used to quantify changes in the above metrics at plot scales and to measure 3D demographic rates of individual colonies (e.g. 3D growth and partial mortality).

This paper analyses the spatial patterns and temporal dynamics of the long-term fish dataset from the LTMP (see LTMP metadata for details on methods). The dataset spand 233 coral reef fish species, recorded from 1995 to 2023 across the entire GBR. We analysed spatial patterns and temporal dynamics at the whole GBR scale and the sector x shelf scale, by year and decade, and by total density and species richness, family level and species level. We used Bayesian glmms, and multivariate techniques such as PCA, Adonis and RDA.

Coral fragment growth for five common species (Acropora hyacinthus, Acropora tenuis, Pocillopora verrucosa, Stylophora pistillata, and Platygyra daedelea) was measured after chronic exposure to temperatures ranging from 19 to 31ºC to quantify thermal-performance curves (TPCs). TPCs are an important tool to make predictions of how future changes in thermal regimes will affect organisms. Coral colonies were collected in March 2021 in Kelso Reef (-18.44°, 146.99°) (Acropora hyacinthus, Acropora tenuis, Pocillopora verrucosa, and Stylophora pistillata) and No Name Reef (-14.64°, 145.64°) (Acropora hyacinthus and Pocillopora verrucosa) and in March 2022 in Heron Island (-23.44°, 151.91°) (Acropora hyacinthus, Acropora tenuis, Pocillopora verrucosa, Platygyra daedelea, and Stylophora pistillata) and Davies Reef (-18.82°, 147.64°) (Acropora hyacinthus and Pocillopora verrucosa). Colonies were transported to the National Sea Simulator (SeaSim) in the Australian Institute of Marine Science. Nine colonies per species were fragmented into ten small nubbins, each of which was randomnly assigned to a temperature (19, 21, 23, 25, 26, 27, 28, 29, 30, or 31ºC ) and a tank. Each tank had three fragments per species, each from a different colony. All tanks were initially held at 28ºC and temperatures were ramped up or down with a maximum daily change of 0.5ºC until all tanks had reach their target temperatures within 19 days. Fragments were buoyant weighted at the beginning of the experiment and then every second week for six weeks. Buoyant weight was converted to dry weight using Archimedes' principle.

Bardi-Jawi Rangers joined forces with the Australian Institute of Marine Science in 2018 to develop a monitoring partnership for looking after Sea Country. The monitoring program was designed to provide scientific data to address the main concerns of Bardi-Jawi Rangers regarding the health and status of their marine resources (increased visitation, recreational fishing, climate change), and to align with management objectives in their existing Healthy Country Plans. Participatory mapping of Sea Country by Bardi-Jawi and Oorany Rangers was used as the basis of the program’s sampling design, to best assess location of monitoring sites and also provide a permanent record of local ecosystem knowledge. Monitoring occurs once a year during August, and targets benthic organisms, fish and year-round in-situ water temperature. Surveys are conducted with remotely operated systems that allow collection of long-term data which can be archived and queried at a number of levels. Fish data are collected using single-camera Baited Remote Underwater Video Systems (BRUVS) at coral reef and mangrove habitats along the east (2 sites) and west (2 sites) of the Dampier Peninsula. Benthos data are collected using DropCam, a still photography tripod system deployed from a small vessel that collects images of benthic organisms along a set transect following GPS track coordinates. There are 3 sites for benthic data collection (1 west, 2 east of Dampier Peninsula), all on solid reef; at one of these sites, benthic data are also collected via photo transects by walking on emergent reef at low tide. Temperature data are collected with HOBO loggers at benthic data collection sites (1 east, 1 west of Dampier Peninsula). All data are collected by the rangers with support from AIMS. Data analysis occurs at AIMS, where video and photos are scored to estimate fish abundance and diversity, as well as the abundance of coral and other benthic organisms of interest. Temperature data contributes to AIMS’ National Temperature Data Program.

The Australian Institute of Marine Science (AIMS) has been running coral reef monitoring programs since the 1980s, including both the Long-Term Monitoring Program (LTMP) and Marine Monitoring Program (MMP). These monitoring programs are designed to detect changes in coral reef communities at a sub-regional scale. Within this context, a subregion consists of inshore, mid-shelf, and outer shelf reefs across the continental shelf within one band of latitude (considered a sector). Data are modelled for presentation on the AIMS Reef Reporting Dashboard https://apps.aims.gov.au/reef-monitoring/reefs. The Reef Monitoring Reporting (MonRep) platform displays modelled data collected by AIMS' Long-Term Monitoring Program and Marine Monitoring Program at reef level, latitudinal Sector or Natural Resource Management (NRM)-region level in the Reef Monitoring Tool. How the data has been modelled for each graph is explained below for each data type. Benthic community cover Reef-level photo transect data. Bayesian hierarchical models (INLA) to model the benthos over time. Specifically, for each major benthic group (live hard coral, algae and soft corals) a model containing the population-level effects of year crossed with major taxonomic groups and the varying effects of transects nested within sites were fit to binomial photo point counts. NRM-region/Sector photo transect data. Bayesian hierarchical models (INLA) to model the benthos over time. Specifically, for each NRM region/Sector and major benthic group (live hard coral, macroalgae and soft corals) a model containing the population-level effects of year and the varying effects of depth and transects nested within sites nested within reefs were fit to binomial photo point counts. Manta tow surveys Reef-level manta-tow data. Bayesian hierarchical models (INLA) to model the benthos over time. Specifically, for each major benthic group (live hard coral and soft corals) a model containing the population-level effects of year and the varying effects of tows were fit against a beta distribution to percentage cover data. For NRM region//Sector level manta-tow data. Bayesian hierarchical models (INLA) to model the benthos over time. Specifically, for each NRM region/Sector major benthic group (live hard coral and soft corals) a model containing the population-level effects of year and the varying effects of tows nested within reef were fit against a beta distribution to percentage cover data. Juvenile hard corals Reef-level data Bayesian hierarchical models (INLA) were used to model the juvenile coral abundances (counts) over time. Specifically, a model containing the population-level effects of year and the varying effects of sites were fit against a zero-inflated negative binomial and also included a (log-transformed) offset for available substrate. NRM region/Sector level data Bayesian hierarchical models (INLA) were used to model the juvenile coral abundances (counts) over time. Specifically, for each NRM region/Sector a model containing the population-level effects of year and the varying effects of sites nested within reefs were fit against a zero-inflated negative binomial and also included a (log-transformed) offset for available substrate. Reef fish Reef-level data Bayesian hierarchical models (INLA) to model the fish abundances (counts) over time. Specifically, for each major fish group (Harvested, Herbivores, Coral Trout, Large fishes and Small fishes) a model containing the population-level effects of year and the varying effects of transects nested within sites were fit against zero-inflated negative binomials. NRM region/Sector level data Bayesian hierarchical models (INLA) to model the fish abundances (counts) over time. Specifically, for each NRM region/Sector and for each major fish group (Harvested, Herbivores, Coral Trout, Large fishes and Small fishes) a model containing the population-level effects of year and the varying effects of transects nested within sites nested within reefs were fit against zero-inflated negative binomials.

Annual Benthic monitoring of six reefs within Southern Inshore Reporting Zone for the Mackay Whitsunday Isaac Regional Report Card Data utilise the same sampling methods as the Marine Monitoring Program: Photopoint intercept for benthic cover, counts of juvenile corals in belt transects and scuba searchs in belt transects for vectors of coral mortality. At each Pine Peak Island, Pine Islets, Connor Island and Henderson Island, five 20m long transects are monitored at each of two sites and at 2m and 5m depth below lowest astronomic tide. At Aquila Island and Temple Island transects are at 1 to 2m depth only. Note: Monitoring of Connor Island ceased in 2021 due to visibility and logistic constraints.

Data from the ReefScan image survey system for reef flats along the Great Barrier Reef for the ecoRRAP project. The ReefScan survey system consists of a series of GoPro cameras mounted on an underwater boom either side of a small Tender which then undertakes surveys of reef flat areas of reefs. The surveys are typically 0.5Ha in area (100m x 50m) located over the top of the shallow ecoRRAP sites with the intent to include all of the area of the ecoRAPP DSRL camera surveys and to include the reef edge and reef flat. The images are geo-located and so can be stitched using the Metashape software (www.agisoft.com) into Ortho-mosaics, the data is also processed into 2.5D DEM's and object clouds which can be used to get structural information. As the data is colelcted at the surface it has some depth information and so best represents 2.5D over true 3D. The images can also be analysed using Machine Learning to give percent cover of the major benthic forms. One compoent of the work is to develop and validate a set of classificaiton labels suitable for the data collected. Surveys were done over 2021 and 2022 as part of the Technology Development work with the techniques evolving as the work progressed. The first survey was incomplete and some of the ecoRAPP trips were not surveyed using this system. The following trips have been completed: Orpheus / Pelorus Island and Davies Reef I [Jan 2021] (partial survey) Torres Strait (Dunganess / Masig / Aukane) [Feb 2021] Moore Reef / Lizard Island [Oct 2021] Orpheus / Pelorus Island / Davies Reef / Chicken Reef / Little Boardhurst Reef II [Jan 2022] Davies post-bleaching and Southern Reefs (Heron, Lady Muscgrave) [March 2022] The core data are sets of geo-located GoPro images of shallow reef areas with a high degree of overlap. The data products derived from these include: Orth-mosaic images either a GeoTIFFs or as GeoServer layers Digital Elevation Models (DEM's) showing elevation / bathymetry as GeoTIFFs Point Clouds or 3D/2.5D models (as obj files) Percent cover estimates from the images via Machine Learning models Each survey will have a child metadata record to this parent record.

The Gladstone Healthy Harbour Partnership (GHHP) Data and Information Management System (DIMS) is a web based system that helps coordinate the submission and processing of monitoring data associated with the annual GHHP environmental report card for the Gladstone region. This system allows groups performing the monitoring to upload their data into the system. The system performs a range of checks on the minoring data to ensure consistent data. The algorithms that implement the logic of the report card are implemented as a range of R scripts. The DIMS system allows the GHHP science team to run these scripts on the monitoring data to produce a range of products (trend plots, preview of the report card scores and prepopulated report card templates) that are used produce the final report card. This year’s project focused primarily on maintenance of the system, such upgrading software components to include the latest security patches, high priority bugs that were detected during this period and high priority adjustments to the report card logic. Key activities during this report card year were: Replacing the web based file management system (Pydio) with KeyCloak (user management) and NextCloud (file sharing). Adjusting the aggregation hierarchy for the mud crab’s indicator. The source code for the DIMS system software and the scripts are stored on in private repositories on GitHub at the address: https://github.com/ghhp-dims. The server associated with the DIMS is hosted on the Amazon cloud and managed by the Knowledge System team at AIMS. This server also hosts the GHHP website (http://ghhp.org.au). Data uploaded to the GHHP DIMS is owned by GHHP or made available to GHHP under license for the purpose of the creation of the GHHP report card. The results of the analysis from the data are made available through the report card which is available publicly from http://ghhp.org.au.

Genetic data measureing Acanthaster cf. solaris (CoTS) larvae densities in the field, based on a quantitative PCR methods.

EcoRRAP oceanographic logger data. Data collected to provide explanatory information for ecological datasets, and for model parameterisation. At the main reef per cluster (e.g. Masig Island, Lizard Island, Moore Reef, Pelorus Island, Davies Reef, Keppel Islands, Heron Island) an array of loggers were deployed at one of the front deep sites. These loggers measured salinity, temperature, depth, light and currents (current profiles and surface waves) and were deployed for 12 months at a time. A wave buoy was also deployed adjacent to the instrument array. Temperature sensors and current meters were further deployed at many other monitoring sites. Deployment details are described in the logger deployment database.