Granulometry and Bulk Geochemistry of Nearshore Sediments, Herschel Island, Yukon Territory, Canada

This dataset contains the results of granulometric and bulk geochemical analyses of Van Veen surface samples obtained by the Alfred Wegener Institute (AWI) in the course of the 2012 and 2013 summer field seasons. The sampling was performed along transects in depths generally <13 m, to a distance of about <5 km off Herschel Island. In 2012, 75 samples in Pauline Cove and in the vicinity of Simpson Point were obtained. Sample collection was expanded in 2013, on transects established the previous year, with additional locations in Tetris Bay and Workboat Passage. Samples consisted of approximately 100 g of the top 3-6 cm of sediment, and were frozen in the field and freeze dried at the AWI before undergoing analytical procedures. Sample locations were recorded with the onboard global positioning system (GPS) unit. Grain size distributions in our study were obtained using laser diffractometry at the AWI (Beckman Coulter LS200) on the <1 mm fraction of samples oxidized with 30% H2O2 until effervescence ceased to remove organics. Some samples were also sieved using a sieve stack with 1 phi intervals. GRADISTAT (Blott and Pye, 2001) was used to calculate graphical grain size statistics (Folk and Ward, 1957). Grain diameters were logarithmically transformed to phi values, calculated as phi=-log2d, where d is the grain diameter in millimeters (Blott and Pye, 2001; Krumbein, 1934). Freeze dried samples were ground and ground using an Elemetar Vario EL III carbon-nitrogen-sulphur analyzer at the AWI to measure total carbon (TC) and total nitrogen (TN). Tungsten oxide was added to the samples as a catalyst to the pyrolysis. Following this analysis, total organic carbon (TOC) was determined using an Elementar VarioMax. Stable carbon isotope ratios of 13C/12C of 118 samples were determined on a DELTAplusXL mass spectrometer (ThermoFisher Scientific, Bremen) at the German Research Centre for Geosciences (GFZ) in Potsdam, Germany . An additional analysis on 69 samples was carried out at the University of Hamburg with an isotope ratio mass spectrometer (Delta V, Thermo Scientific, Germany) coupled to an elemental analyzer (Flash 2000, Thermo Scientific, Germany). Prior to analysis, soil samples were treated with phosphoric acid (43%) to release inorganic carbon. Values are expressed relative to Vienna Peedee belemnite (VPDB) using external standards (USGS40, -26.4 per mil VPDB and IVA soil 33802153, -27.5 per mil VPDB).

Ensemble prediction distribution maps of macroalgae for current conditions and four climate change scenarios and high resultion bathymetry for Potter Cove, WAP, Antarctica

Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.

Results of wave modelling for Moreton Bay, Southeast Queensland, and a reef lagoon off Lizard Island, Great Barrier Reef, Australia

The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.