This dataset contains environmental layers used to model the predicted distribution of demersal fish bioregions for the paper: Hill et al. (2020) Determining Marine Bioregions: A comparison of quantitative approaches, Methods in Ecology and Evolution. It contains climatological variables from satellite and modelled data that represent sea floor and sea surface conditions likely to affect the distribution of demersal fish including: depth, slope, seafloor temperatures, seafloor current, seafloor nitrate, sea surface temperature, chlorophyll-a standard deviation and sea surface height standard deviation. Layers are presented at 0.1 degree resolution. "prediction_space" is a Rda file for R that consists of two objects: env_raster: a raster stack of the environmental layers pred_sp: a data.frame version of the env_raster where some variables have been transformed for statistical analysis and bioregion prediction. "Env_data_sources.xlsx" contains a description of each environmental variable and it's source.

Metadata record for data from ASAC Project 1229 See the link below for public details on this project. ---- Public Summary from Project ---- This project will develop a method to monitor human impacts in the shallow marine environment of Antarctica. Artificial substratum units, placed at polluted and unpolluted sites, will be recovered after a specific time interval and resident animal communities will be compared to identify the type and magnitude of impacts. Data are community abundance data from artificial substrate units comprised of three nylon mesh pot scourers. Taxa are identified to morphospecies. Substrates were deployed in nearshore waters of Casey Station. Standard deployment was 1 year at 14m depth. Four main sites were used - Brown Bay, Newcombe Bay, O'Brien Bay and Browning Peninsula. Brown Bay is a known contaminated site. Experiments were designed to investigate natural variation on spatial and temporal scales, habitat area and potential impacts of a contaminated site, Brown Bay.