Marine fishes in the Arctic Ocean and adjacent seas (AOAS).

This dataset comprises regional geochemical stream sediment data from West and South Greenland and forms the basis of the Geochemical Atlas of West and South Greenland (Steenfelt, 2001). The Geochemical Atlas of West and South Greenland presents the results of a regional stream sediment geochemical mapping programme conducted between 1979 and 1998. A total of 7,122 stream sediment samples were collected from low-order streams with near-uniform spatial coverage across West and South Greenland. The <0.1 mm grain-size fraction of 500 g samples was analysed for major and trace elements using X-ray fluorescence spectrometry (XRF), instrumental neutron activation analysis (INAA), delayed neutron counting (DNC) and loss on ignition (LOI). After systematic calibration and quality control to eliminate analytical bias between different methods and time periods, a harmonised and internally consistent dataset was established containing up to 43 elements per sample. The atlas provides a regional overview of the geochemical composition of the minerogenic fraction of stream sediments and constitutes a geochemical baseline dataset for geological mapping and mineral exploration in Greenland.

This layer comprises all the available water wells in GIN (Yukon, British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Quebec, Nova Scotia and Newfoundland and Labrador) and published through the open data platforms. This layer is a combination of all individual provincial and territorial layers. The original databases are dynamically converted by an automatic process managed by Natural Resources Canada (Groundwater Information Network).

The dataset comprises spatial polygons (Tracts) representing areas in Greenland assessed as geologically permissive for specific mineral deposit types during mineral resource assessment workshops conducted between 2009 and 2014. Assessments were carried out following the principles of the U.S. Geological Survey “three-part quantitative assessment” method (Singer, 1993), except for the 2010 rare earth elements workshop. For each Tract, probabilistic estimates of the number of undiscovered deposits at different confidence levels are provided, along with statistical results from Monte Carlo simulations based on established grade-tonnage models. The assessments do not include economic, technical, environmental or social considerations.

Appendix 9.8 The thirty moss families of the Canadian Arctic Archipelago with reference number (Ireland et al. 1987) in brackets. Number of species in each family, number of genus in family, and number of species in each genus are given. Species-rich genera and families are highlighted in grey.

DK model 2019 – Water resources assessment comprises derived results from GEUS’ national hydrological model for Denmark for assessing the use and quantitative status of groundwater resources. The dataset contains model-based assessments of groundwater recharge, water abstraction, exploitation rates, water balance, groundwater drawdown and related assessments at groundwater body level. Exploitation rates are calculated as the ratio between abstraction and groundwater recharge and are used together with information on drawdown and streamflow impacts to assess whether groundwater bodies may be at risk with respect to water balance and quantitative status. The dataset is suitable for regional screening, documentation and overall assessment of groundwater resources, but should not be used as the sole basis for local-scale decisions without additional expert evaluation.

This dataset represents a map of ice margin lines and related localities in Scandinavia, illustrating the gradual deglaciation of the Scandinavian Ice Sheet during the last glaciation, the Weichsel Ice Age. The map depicts the ice sheet extent in five main deglaciation phases, as well as the occurrence of recent ice caps, ice-margin localities, De Geer moraines, ice margin lines and hypothetical ice margin lines. The dataset was compiled in 1995 in connection with TemaNord and presents a regional overview of the deglaciation history of Scandinavia. GEUS has provided technical input in producing the ice margin map.

Appendix 9.7 Species list with full names of liverworts of Greenland according to Damsholt (2010, unpublished) including 22 families, 50 genera and 173 species.

DK model 2019 – Model data comprises core model data from GEUS’ national hydrological model for Denmark. The dataset describes the model basis used in DK model 2019, including the hydrogeological model structure, computational grid, groundwater bodies, climate input, water abstraction data, stream network and other thematic input data included in the model setup. DK model 2019 was updated with new groundwater bodies, new hydrogeological mapping information and a new calibration against observed groundwater heads and stream discharge. The model data form the basis for calculations of groundwater recharge, water balance, water abstraction, drawdown, exploitation rates and impacts on streams. The dataset is suitable as documentation of the model basis and as input to regional analyses, screening and further modelling studies, but should not be used directly for local-scale issues without a separate assessment.

DK model 2019 – Calibration statistics comprises spatial and statistical results from the calibration and evaluation of GEUS’ national hydrological model for Denmark. The dataset documents model performance for groundwater heads and stream discharge, including statistical measures such as RMSE and mean error for groundwater heads as well as WBE, summer WBE and KGE for streamflow simulations. The calibration was carried out using dynamic model runs and inverse parameter estimation with PEST based on observed groundwater heads and daily discharge data for the period 2000–2010. The dataset is intended for assessing the suitability of DK model 2019 for regional analyses, screening and further use. The calibration statistics describe model performance at national and regional scales and should not by themselves be used as documentation of local-scale model accuracy.