The Huon Commonwealth Marine Reserve (CMR) covers a broad depth range from the inner continental shelf at about 70 m, to abyssal depths of more than 3000 m. The majority of the area is in deep water. The Tasman Seamounts Marine Reserve that was proclaimed in 1999 has been wholly incorporated into the Huon Commonwealth marine reserve. The reserve contains a cluster of seamounts that appear as cone-shaped submerged mountains, which provide a range of depths for a diversity of plants and animals. The peaks of many of the reserve's seamounts are between 750 m and 1000 m below the sea surface and support endemic species, including large erect corals and sponges. Some of the flora and fauna are hundreds and possibly thousands of years old, making them some of the longest-lived animals on Earth. The reserve also provides an important connection between seamounts of the Indian Ocean and the Tasman Sea. This map of the geomorphology of the Huon CMR was prepared for the NESP Marine Biodiversity Hub Theme D (1) project: National data collation, synthesis and visualisation to support sustainable use, management and monitoring of marine assets.

Robust prediction of population responses to changing environments requires the integration of factors controlling population dynamics with processes affecting distribution. This is true everywhere but especially in polar pelagic environments. Biological cycles for many polar species are synchronised to extreme seasonality, while their distributions may be influenced by both the prevailing oceanic circulation and sea-ice distribution. Antarctic krill (krill, Euphausia superba) is one such species exhibiting a complex life history that is finely tuned to the extreme seasonality of the Southern Ocean. Dependencies on the timing of optimal seasonal conditions has led to concerns over the effects of future climate on krill’s population status, particularly given the species’ important role within Southern Ocean ecosystems. Under a changing climate, established correlations between environment and species may breakdown. Developing the capacity for predicting krill responses to climate change therefore requires methods that can explicitly consider the interplay between life history, biological conditions, and transport. The Spatial Ecosystem And Population Dynamics Model (SEAPODYM) is one such framework that integrates population and general circulation modelling to simulate the spatial dynamics of key organisms. Here, we describe a modification to SEAPODYM, creating a novel model – KRILLPODYM – that generates spatially resolved estimates of krill biomass and demographics. This new model consists of three major components: (1) an age-structured population consisting of five key life stages, each with multiple age classes, which undergo age-dependent growth and mortality, (2) six key habitats that mediate the production of larvae and life stage survival, and (3) spatial dynamics driven by both the underlying circulation of ocean currents and advection of sea-ice. Here we present the first results of KRILLPODYM, using published deterministic functions of population processes and habitat suitability rules. Initialising from a non-informative uniform density across the Southern Ocean our model independently develops a circumpolar population distribution of krill that approximates observations. The model framework lends itself to applied experiments aimed at resolving key population parameters, life-stage specific habitat requirements, and dominant transport regimes, ultimately informing sustainable fishery management. ____ This dataset represents KRILLPODYM modelled estimates of Antarctic krill circumpolar biomass distribution for the final year of a 12-year spin up. Biomass distributions are given for each of the five key life stages outlined above. The accompanying background, model framework and initialisation description can be found in the following reference paper: Green, D. B., Titaud, O., Bestley, S., Corney, S. P., Hindell, M. A., Trebilco, R., Conchon, A. and Lehodey, P. in review. KRILLPODYM: a mechanistic, spatially resolved model of Antarctic krill distribution and abundance. - Frontiers in Marine Science

This data set consists of a scored time-series of Autonomous Underwater Vehicle (AUV) images from the Bicheno region on the east coast of Tasmania. Surveys were conducted between 2011 and 2016 within the Governor Island Marine Reserve and nearby sites outside the reserve. Governor Island was surveyed in 2011, 2013, 2014 and 2016. The outside sites of Trap Reef, Cape Lodi and Butlers Point were surveyed in 2011, 2013 and 2016. Imagery across all surveys was scored for the presence of Centrostephanus rodgersii urchin barrens across rocky reef at each site. Prior to analysis the data was subsetted to every fifth image to avoid overlapping images. The data set also contains depth information for each image and a measure of rugosity (Vector Rugosity Measure) computed in ArcGIS software from a one metre resolution bathymetric map covering the survey sites. Analysis was conducted to examine the trend in the presence of barrens through time and to compare the occurrence of barrens inside the Governor Island Marine Reserve with sites outside the reserve. A spatio-temporal model incorporating both spatial and temporal correlation in the time-series of data was used. This data set contains the scored data used in the analysis. Further details of the methods used and results are contained in the following article. Please cite any use of the data or code by citing this article: Perkins NR, Hosack GR, Foster SD, Monk J, Barrett NS (2020) Monitoring the resilience of a no-take marine reserve to a range extending species using benthic imagery. PLOS ONE 15(8): e0237257. https://doi.org/10.1371/journal.pone.0237257

Globally, terrestrially-breeding marine predators have experienced shifts in species distribution, prey availability, breeding phenology, and population dynamics due to climate change. These central-place foragers are restricted within proximity of their breeding colonies during the breeding season, making them highly susceptible to any changes in both marine and terrestrial environments. While ecologists have developed risk assessments to assess likely climate risk in various contexts, these often overlook critical breeding biology data. To address this knowledge gap, we developed a trait-based risk assessment framework, focusing on the breeding season and applying it to marine predators breeding in parts of Australian territory and Antarctica. Our objectives were to quantify climate change risk, identify specific threats, and establish an adaptable framework. The assessment considered 25 criteria related to three risk components: vulnerability, exposure, and hazard, while accounting for uncertainty. We employed a scoring system that integrated a systematic literature review and expert elicitation for the hazard criteria. Monte Carlo sensitivity analysis was conducted to identify key factors contributing to overall risk. Our results identified shy albatross (Thalassarche cauta), southern rockhopper penguins (Eudyptes chrysocome), Australian fur seals (Arctocephalus pusillus doriferus), and Australian sea lions (Neophoca cinerea) with high climate urgency. Species breeding in lower latitudes as well as certain eared seal, albatross, and penguin species were particularly at risk. Hazard and exposure explained the most variation in relative risk, outweighing vulnerability. Key climate hazards affecting most species include extreme weather events, changes in habitat suitability, and prey availability. We emphasise the need for further research, focusing on at-risk species, and filling knowledge gaps (less-studied hazard criteria, and/or species) to provide a more accurate and robust climate change risk assessment. Our findings offer valuable insights for conservation efforts, given monitoring and implementing climate adaptation strategies for land-dependent marine predators is more feasible during their breeding season.