This dataset comprises summaries of sight and resight data compiled for the NESP MBH project A13 and derived from data housed in the Australian Right Whale Photo Identification Catalogue (ARWPIC) and associated effort summaries. These summaries have been compiled as part of an analysis of mark recapture information in establishing trends in the population and spatial connectivity of individuals across southern Australia. The summaries are based on original sightings data collected across 1990-2018 by ARWPIC partners. The ARWPIC is housed at the Australian Antarctic Division and managed by the Australian Marine Mammal Centre.

These files contain the data recorded from a mesocosm experiment conducted in Bergen, Norway 2022 which assessed the effect of simualted mineral-based (silicate or calcium) ocean alkalinity enhancement (OAE) on diatom silicification. Ten mesocosms were used in total, divided into two groups either the silicate- or calcium based group and alkalinity was increased by either 0, 150, 300, 450 or 600 µmol L-1 above natrually occuring levels. The PDMPO-fluorescence (an appropriate proxy for silicification) of diatoms was recorded on eight seperate days during the experiment. Accompanying data includes measured; macronutrients (nitrate, nitrite, phophate, silicate), total alkalinity, biogenic silica in the water column and sediment trap.

The effect of ocean alkalinity enhancement on a coastal phytoplankton community was assessed via a microcosm experiment. The effect of alkalinity enhancement in two scenarios (i) when enclosed seawater was in equilibrium with atmospheric CO2 and (ii) when enclosed seawater was not in equilibrium with atmospheric CO2 were explored. Alkalinity was increased by ~497 umol/kg in these two treatments and plankton communities, carbonate chemistry, dissolved inorganic nutrients, particulate matter and chlorophyll a dynamics monitored over a 22 day period where a spring bloom occurred.

Ecosystem data was collected as part of an integrated study of the continental shelf over a 2 and a half year period between November 2015 and January 2018. Data were collected bi-monthly through the spring to autumn (November, January, March, May). Stations were situated perpendicular to shelf bathymetry, ranging in depth from ~50 m to 100 m near the edge of the shelf and were located between 5 km and 15 km from land; encompassing from south Storm Bay, past the southern tip of Bruny Island and into the Southern Ocean (south-east Tasmania, Australia). Data collected focused on each trophic level, characterizing the zooplankton community, fish schools and marine predators. The overarching aim of the study was to investigate the effects of long term warming, and a marine heatwave event on zooplankton dynamics in terms of community response variables and the flow-on effects of changing lower-trophic level dynamics for top predators.

The Seamap Australia National Benthic Habitat Layer (NBHL) is a nationally synthesised database of seafloor habitat data, classified according to the Seamap Australia National Benthic Habitat Classification Scheme (https://vocabs.ardc.edu.au/viewById/129). In generating the Seamap Australia NBHL, datasets from data providers around Australia are collated and centrally hosted by IMAS (UTAS). Through time, some datasets become superseded by newer, more accurate data for the same region (improved data collection or processing methodology). This record aggregates all habitat datasets that have been collated as part of the Seamap Australia project, but are no longer considered the most accurate/up to date habitat for a particular region and have been superseded by another product. The parent record for the Seamap Australia NBHL provides an aggregation point for all "current" habitat datasets: https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/4739e4b0-4dba-4ec5-b658-02c09f27ab9a

The recruitment of mussels and microphytobenthic (MPB) algae to 28 experimental artificial reefs supporting different patch sizes and density of kelp (Ecklonia radiata) off Maria Island, Tasmania. The recruitment of mussels was assessed using rope fibre habitats, and the recruitment of MPB algae was assessed using microscope slides, positioned across the artificial reef and collected in November 2015. These data were collected to examine how the patch size and density of kelp influences the establishment of MPB algae and mussels.

Baited remote underwater stereo-video (stereo-BRUV) were used to sample the fish assemblages of the Hunter Marine Park and adjacent Port Stephens - Great Lakes Marine Park at equivalent depths. Stereo-BRUV were deployed in both autumn and spring from spring 2016 to autumn 2018 and at depth of 32-105m. The videos were analyse to all fish species to the lowest taxonmic level and estimate relative abundance (MaxN) and lengths of all species. This information was used to form a baseline of the benthic fish assemblages of the Hunter Marine Park. This study was done as part of the NESP Marine Biodiversity Hub D3 project (https://www.nespmarine.edu.au/project/project-d3-implementing-monitoring-amps-and-status-marine-biodiversity-assets-continental).

The abundance of macroinvertebrates associated with 28 experimental artificial reefs supporting different patch sizes and density of kelp (Ecklonia radiata) off Maria Island, Tasmania. Macroinvertebrates were assessed by diver-based visual census conducted between November 2015 and December 2016. This data was collected to examine how the patch size and density of kelp influences the establishment of macroinvertebrate assemblages.

This record contains: 1. Thesis 2. The MATLAB codes of the adaptive Canny gradient-based edge detection algorithm and calculating frontal probability/density (for AVHRR data and MODIS data separately). 3. Frontal probability (probability of frontal encounter, PFE) and frontal density (FD) data over Australian hotspot regions (for AVHRR data and MODIS data separately) 4. Results of the Mann-Kendall trend test The purpose of this study is to verify the regional trends of frontal activity within the two marine hotspots near Australia and compare the performance of the two edge detection algorithms.