Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

Responses of the Emiliania huxleyi Proteome to Ocean Acidification

Ocean acidification due to rising atmospheric CO2 is expected to affect the physiology of important calcifying marine organisms, but the nature and magnitude of change is yet to be established. In coccolithophores, different species and strains display varying calcification responses to ocean acidification, but the underlying biochemical properties remain unknown. We employed an approach combining tandem mass-spectrometry with isobaric tagging (iTRAQ) and multiple database searching to identify proteins that were differentially expressed in cells of the marine coccolithophore species Emiliania huxleyi (strain NZEH) between two CO2 conditions: 395 (~current day) and ~1340 p.p.m.v. CO2. Cells exposed to the higher CO2 condition contained more cellular particulate inorganic carbon (CaCO3) and particulate organic nitrogen and carbon than those maintained in present-day conditions. These results are linked with the observation that cells grew slower under elevated CO2, indicating cell cycle disruption. Under high CO2 conditions, coccospheres were larger and cells possessed bigger coccoliths that did not show any signs of malformation compared to those from cells grown under present-day CO2 levels. No differences in calcification rate, particulate organic carbon production or cellular organic carbon: nitrogen ratios were observed. Results were not related to nutrient limitation or acclimation status of cells. At least 46 homologous protein groups from a variety of functional processes were quantified in these experiments, of which four (histones H2A, H3, H4 and a chloroplastic 30S ribosomal protein S7) showed down-regulation in all replicates exposed to high CO2, perhaps reflecting the decrease in growth rate. We present evidence of cellular stress responses but proteins associated with many key metabolic processes remained unaltered. Our results therefore suggest that this E. huxleyi strain possesses some acclimation mechanisms to tolerate future CO2 scenarios, although the observed decline in growth rate may be an overriding factor affecting the success of this ecotype in future oceans.

Distribution of desmoscolecida (Nematoda) in surface sediments of the Iberian Deep-Sea, North Atlantic (Table 1)

1. Desmoscolecida from the continental slope and the deep-sea bottom (59-4354 m) off the Portuguese and Moroccan coasts are described. 18 species were identified: Desmoscolex bathyalis sp. nov., D. chaetalatus sp. nov., D. eftus sp. nov., D. galeatus sp. nov., D. lapilliferus sp. nov., D. longisetosus Timm, 1970, D. lorenzeni sp. nov., D. perspicuus sp. nov., D. pustulatus sp. nov., Quadricoma angulocephala sp. nov., Q. brevichaeta sp. nov., Q. iberica sp. nov., Q. loricatoides sp. nov., Tricoma atlantica sp. nov., T. bathycola sp. nov., T. beata sp. nov., T. incomposita sp. nov., T. meteora sp. nov., T. mauretania sp. nov. 2. The following new terms are proposed: "Desmos" (ring-shaped concretions consisting of secretion and concretion particles), "desmoscolecoid" and "tricomoid" arrangement of the somatic setae, "regelmaessige" (regular), "unregelmaessige" (irregular), "vollstaendige" (complete) and "unvollstaendige" (incomplete) arrangement of somatic seta (variations in the desmoscolecoid arrangement of the somatic setae). The length of the somatic setae is given in the setal pattern. 3. Desmoscolecida identical as to genus and species exhibit no morphological differences even if forthcoming from different bathymetrical zones (deep sea, sublitoral, litoral) or different environments (marin, freshwater, coastal subsoil water, terrestrial environment). 4. Lorenzen's (1969) contention that thearrangement of the somatic setae is more significant for the natural relationships between the different genera of Desmoscolecida than other characteristics is further confirmed. Species with tricomoid arrangement of somatic setae are regarded as primitive, species with desmoscolecoid arrangement of somatic setae are regarded as more advanced. 5. Three new genus are established: Desmogerlachia gen. nov., Desmolorenzenia gen. nov. and Desmofimmia gen. nov. - Protricoma Timm, 1970 is synonymized with Paratricoma Gerlach, 1964 and Protodesmoscolex Timm, 1970 is synonymized with Desmoscolex Claparede,1863. 6. Checklists of all species of the order Desmoscolecida and keys to species of the subfamilies Tricominae and Desmoscolecinae are provided. 7. The following nomenclatorial changes are suggested: Desmogerlachia papillifer (Gerlach, 1956) comb. nov., D .pratensis (Lorenz, 1969) comb. nov., Desmotimmia mirabilis (Timm, 1970) comb. nov., Paratricoma squamosa (Timm, 1970) comb. nov., Desmolorenzenia crassicauda (Timm, 1970) comb. nov., D. desmoscolecoides (Timm, 1970) comb. nov., D. eurycricus (Filipjev, 1922) comb. nov., D. frontalis (Gerlach, 1952) comb. nov., D. hupferi (Steiner, 1916) comb. nov., D. longicauda (Timm, 1970) comb. nov., D. parva (Timm, 1970) comb. nov., D. platycricus (Steiner, 1916) comb. nov., D. viffata (Lorenzen, 1969) comb. nov., Desmoscolex anfarcficos (Timm, 1970) comb. nov.

Spatial database of canopy plant densities created from satellite images over Galapagos in 2011, with intent to manage invasive species

Mapping is an important tool for the management of plant invasions. If landscapes are mapped in an appropriate way, results can help managers decide when and where to prioritize their efforts. We mapped vegetation with the aim of providing key information for managers on the extent, density and rates of spread of multiple invasive species across the landscape. Our case study focused on an area of Galapagos National Park that is faced with the challenge of managing multiple plant invasions. We used satellite imagery to produce a spatially-explicit database of plant species densities in the canopy, finding that 92% of the humid highlands had some degree of invasion and 41% of the canopy was comprised of invasive plants. We also calculated the rate of spread of eight invasive species using known introduction dates, finding that species with the most limited dispersal ability had the slowest spread rates while those able to disperse long distances had a range of spread rates. Our results on spread rate fall at the lower end of the range of published spread rates of invasive plants. This is probably because most studies are based on the entire geographic extent, whereas our estimates took plant density into account. A spatial database of plant species densities, such as the one developed in our case study, can be used by managers to decide where to apply management actions and thereby help curtail the spread of current plant invasions. For example, it can be used to identify sites containing several invasive plant species, to find the density of a particular species across the landscape or to locate where native species make up the majority of the canopy. Similar databases could be developed elsewhere to help inform the management of multiple plant invasions over the landscape.

Global Lithological Map Database v1.0 (gridded to 0.5° spatial resolution)

Lithology describes the geochemical, mineralogical, and physical properties of rocks. It plays a key role in many processes at the Earth surface, especially the fluxes of matter to soils, ecosystems, rivers, and oceans. Understanding these processes at the global scale requires a high resolution description of lithology. A new high resolution global lithological map (GLiM) was assembled from existing regional geological maps translated into lithological information with the help of regional literature. The GLiM represents the rock types of the Earth surface using 1,235,400 polygons. The lithological classification consists of three levels. The first level contains 16 lithological classes comparable to previously applied definitions in global lithological maps. The additional two levels contain 12 and 14 subclasses, respectively, which describe more specific rock attributes. According to the GLiM, the Earth is covered by 64 % sediments (a third of which is carbonates), 13 % metamorphics, 7 % plutonics, and 6 % volcanics, and 10% are covered by water or ice. The high resolution of the GLiM allows observation of regional lithological distributions which often vary from the global average. The GLiM enables regional analysis of Earth surface processes at global scales.

Time series of zooplankton abundance at station L4 in the English Channel from 1988 to 2011

Ongoing zooplankton research at the Plymouth Marine Laboratory has established a time series of zooplankton species since 1988 at L4, a coastal station off Plymouth. Samples were collected by vertical net hauls (WP2 net, mesh 200 µm; UNESCO 1968) from the sea floor (approximately 50 m) to the surface and stored in 4% formalin. Much of the zooplankton analysis has been to the level of "major taxonomic groups" only, and a number of different analysts have participated over the years. The level of expertise has generally been consistent, but the user should be aware that levels of taxonomic discrimination may vary during the course of the dataset. The dominant calanoid copepods are generally well discriminated to species throughout. Calanus has not been routinely examined for species determination, the assumption being that the local population is entirely composed of Calanus helgolandicus. In certain years there has been a particular interest in Temora stylifera, Centropages cherchiae and other species reflected in the dataset. The lack of records in other previous years does not necessarily reflect species absence. We view it as essential for all users of L4 plankton data to establish and maintain contact with the nominated current data originators as well as fully consulting the metadata. While not impinging on free data access, this ensures that this large, species-rich but slightly complex species database is being used in the correct way, and any potential issues with the data are clarified. Furthermore, a proper dialogue with these local experts on the time series will enable where appropriate the most recent sampling timepoints to be used. The data can be downloaded from BODC or from doi:10.1594/PANGAEA.778092 as files for each year by searching for "L4 zooplankton". The most comprehensive dataset is the version downloadable directly from this page. The entire set of zooplankton samples is stored at the Plymouth Marine Laboratory in buffered formalin, and may be available for further taxonomic analysis on request.

Integrated topographic database for King George Island, South Shetland Islands, with links to shapefiles

SCAR KGIS (SCAR King George Island GIS Project) was an integrated topographic database for King George Island, South Shetland Islands, including the SCAR Feature Catalogue to semantically integrate the data sets. The project, operated by the University of Freiburg, was available at http://portal.uni-freiburg.de/AntSDI as "The Antarctic Spatial Data Infrastructure (AntSDI)". Operation ended in 2007. The remaining data files were archived in shape format (zipped) in projections as recommended by SCAR. The source data was provided by a variety of institutions which were not referenced in the original product.

The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.