Spatial distribution patterns of ascidians (Ascidiacea: Tunicata) in combination with information on bathymetry, oceanography, chlorophyll-a, and sea-ice on the continental shelves off the northern Antarctic Peninsula during POLARSTERN cruise ANT-XXIX/3

Ascidians (Ascidiacea: Tunicata) are sessile suspension feeders that represent dominant epifaunal components of the Southern Ocean shelf benthos and play a significant role in the pelagic-benthic coupling. Here, we report the results of a first study on the relationship between the distribution patterns of eight common and/or abundant (putative) ascidian species, and environmental drivers in the waters off the northern Antarctic Peninsula. During RV Polarstern cruise XXIX/3 (PS81) in January-March 2013, we used seabed imaging surveys along 28 photographic transects of 2 km length each at water depths from 70 to 770 m in three regions (northwestern Weddell Sea, southern Bransfield Strait and southern Drake Passage), differing in their general environmental setting, primarily oceanographic characteristics and sea-ice dynamics, to comparatively analyze the spatial patterns in the abundance of the selected ascidians, reliably to be identified in the photographs, at three nested spatial scales. At a regional (100-km) scale, the ascidian assemblages of the Weddell Sea differed significantly from those of the other two regions, whereas at an intermediate 10-km scale no such differences were detected among habitat types (bank, upper slope, slope, deep/canyon) on the shelf and at the shelf break within each region. These spatial patterns were superimposed by a marked small-scale (10-m) patchiness of ascidian distribution within the 2-km-long transects. Among the environmental variables considered in our study, a combination of water-mass characteristics, sea-ice dynamics (approximated by 5-year averages in sea-ice cover in the region of or surrounding the photographic stations), as well as the seabed ruggedness, was identified as explaining best the distribution patterns of the ascidians.

Homogeneous Spatial Units (HSU) - a Pan-European geographical basis for environmental and socio-economic modelling

The spatial data set delineates areas with similar environmental properties regarding soil, terrain morphology, climate and affiliation to the same administrative unit (NUTS3 or comparable units in size) at a minimum pixel size of 1km2. The scope of developing this data set is to provide a link between spatial environmental information (e.g. soil properties) and statistical data (e.g. crop distribution) available at administrative level. Impact assessment of agricultural management on emissions of pollutants or radiative active gases, or analysis regarding the influence of agricultural management on the supply of ecosystem services, require the proper spatial coincidence of the driving factors. The HSU data set provides e.g. the link between the agro-economic model CAPRI and biophysical assessment of environmental impacts (updating previously spatial units, Leip et al. 2008), for the analysis of policy scenarios. Recently, a statistical model to disaggregate crop information available from regional statistics to the HSU has been developed (Lamboni et al. 2016). The HSU data set consists of the spatial layers provided in vector and raster format as well as attribute tables with information on the properties of the HSU. All input data for the delineation the HSU is publicly available. For some parameters the attribute tables provide the link between the HSU data set and e.g. the soil map(s) rather than the data itself. The HSU data set is closely linked the USCIE data set.

Spatial distribution of key zooplankton species using continuous plankton recorder (CPR) data from the North Atlantic (2000-2009)

The continuous plankton recorder (CPR) survey is an upper layer plankton monitoring program that has regularly collected samples, at monthly intervals, in the North Atlantic and adjacent seas since 1946. Water from approximately 6 m depth enters the CPR through a small aperture at the front of the sampler and travels down a tunnel where it passes through a silk filtering mesh of 270 µm before exiting at the back of the CPR. The plankton filtered on the silk is analyzed in sections corresponding to 10 nautical miles (approx. 3 m**3 of seawater filtered) and the plankton microscopically identified (Richardson et al., 2006 and reference therein). In the present study we used the CPR data to investigate the current basin scale distribution of C. finmarchicus (C5-C6), C. helgolandicus (C5-C6), C. hyperboreus (C5-C6), Pseudocalanus spp. (C6), Oithona spp. (C1-C6), total Euphausiida, total Thecosomata and the presence/absence of Cnidaria and the Phytoplankton Colour Index (PCI). The PCI, which is a visual assessment of the greenness of the silk, is used as an indicator of the distribution of total phytoplankton biomass across the Atlantic basin (Batten et al., 2003). Monthly data collected between 2000 and 2009 were gridded using the inverse-distance interpolation method, in which the interpolated values were the nodes of a 2 degree by 2 degree grid. The resulting twelve monthly matrices were then averaged within the year and in the case of the zooplankton the data were log-transformed (i.e. log10 (x+1).

Modelled spatial and seasonal distribution of Blue Whiting (Micromesistius poutassou) larvae in the North-East Atlantic (1951 to 2005)

Blue whiting (Micromesistius poutassou, http://www.marinespecies.org/aphia.php?p=taxdetails&id=126439) is a small mesopelagic planktivorous gadoid found throughout the North-East Atlantic. This data contains the results of a model-based analysis of larvae captured by the Continuous Plankton Recorder (CPR) during the period 1951-2005. The observations are analysed using Generalised Additive Models (GAMs) of the the spatial, seasonal and interannual variation in the occurrence of larvae. The best fitting model is chosen using the Aikaike Information Criteria (AIC). The probability of occurrence in the continous plankton recorder is then normalised and converted to a probability distribution function in space (UTM projection Zone 28) and season (day of year). The best fitting model splits the distribution into two separate spawning grounds north and south of a dividing line at 53 N. The probability distribution is therefore normalised in these two regions (ie the space-time integral over each of the two regions is 1). The modelled outputs are on a UTM Zone 28 grid: however, for convenience, the latitude ("lat") and longitude ("lon") of each of these grid points are also included as a variable in the NetCDF file. The assignment of each grid point to either the Northern or Southern component (defined here as north/south of 53 N), is also included as a further variable ("component"). Finally, the day of year ("doy") is stored as the number of days elapsed from and included January 1 (ie doy=1 on January 1) - the year is thereafter divided into 180 grid points.

Short-term temporal and spatial variations in physical, optical and biogeochemical parameters in June of 2013 in Alfacs Bay (NW Mediterranean)

With the aim of analyzing the complex physical and biogeochemical interactions at high temporal and spatial resolution in the complex estuarine waters of Alfacs Bay, a beam attenuation-based approach was used as optical proxy of different biogeochemical variables. Thus, the dataset contains the attenuation proxies as well as laboratory results from the analysis of water samples, which were used to validate our approach. In addition, the major physical forcing in the Bay was also measured.

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling, links to files in GeoTIFF format

Topographic variation, the spatial variation in elevation and terrain features, underpins a myriad of patterns and processes in geography and ecology and is key to understanding the variation of life on the planet. The characterization of this variation is scale-dependent, i.e. it varies with the distance over which features are assessed and with the spatial grain (grid cell resolution) of analysis. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale basic research and analytical applications, however to date, such technique is unavailable. Here we used the digital elevation model products of global 250 m GMTED and near-global 90 m SRTM to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile and tangential curvature, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches (median, average, minimum, maximum, standard deviation, percent cover, count, majority, Shannon Index, entropy, uniformity). While a global cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at http://www.earthenv.org and can serve as a basis for standardized hydrological, environmental and biodiversity modeling at a global extent.