Acoustic multi-frequency indicator of four major groups on a spatial grid in the Bay of Biscay

The first data set contains the mean and cofficient of variation (standard deviation divided by mean) of a multi-frequency indicator I derived from ER60 acoustic information collected at five frequencies (18, 38, 70, 120, and 200 kHz) in the Bay of Biscay in May of the years 2006, 2008, 2009 and 2010 (Pelgas surveys). The multi-frequency indicator was first calculated per voxel (20 m long × 5 m deep sampling unit) and then averaged on a spatial grid (approx. 20 nm × 20 nm) for five 5-m depth layers in the surface waters (10-15m, 15-20m, 20-25m, 25-30m below sea surface); there are missing values in particular in the shallowest layer. The second data set provides for each grid cell and depth layer the proportion of voxels for which the multi-frequency indicator I was indicative of a certain group of organisms. For this the following interpretation was used: I < 0.39 swim bladder fish or large gas bubbles, I = 0.39-0.58 small resonant bubbles present in gas bearing organisms such as larval fish and phytoplankton, I = 0.7-0.8 fluidlike zooplankton such as copepods and euphausiids, and I > 0.8 mackerel. These proportions can be interpreted as a relative abundance index for each of the four organism groups.

Rare-earth elements and isotope ratios at DSDP Leg 82 Holes

We report 48 analyses of rare-earth elements (REE) and 15 143Nd/144Nd and 87Sr/86Sr analyses for basalts from the eight holes drilled during Leg 82. Discrete and distinct REE patterns and 143Nd/144Nd ratios characterize the eight holes, with little variation observed downhole except in Holes 561 and 558, thus suggesting dominantly long-term temporal and large-scale spatial variations in the mantle source of these basalts beneath the Mid-Atlantic Ridge over the last 35 Ma of its spreading activity. There is a good inverse correlation between 143Nd/144Nd and (La/Sm)EF with one exception in Hole 558 (approximately 35 Ma), the latter suggesting a recent (35 Ma) light REE depletion event, perhaps caused by dynamic or fractional melting. Short-term temporal and small-scale spatial mantle source variability is also evident in Hole 561 (approximately 18 Ma), which has rapid fluctuations in REE patterns and 143Nd/144Nd ratios (suggesting rapid transfer of magma from the time of melting) and is evidence contrary to the presence of a well-mixed magma chamber at this particular site and time. The mantle source variations noted can be interpreted within two extreme models. The first model invokes a convecting mantle depleted in large ion lithophile elements (LILE) and containing lumps (or veins) of LILE-enriched material of various shapes and sizes, passively and randomly distributed throughout. A second more restrictive model considers the interaction of fixed mantle plumes and the LILE-depleted asthenosphere flowing towards a migrating Mid- Atlantic Ridge (MAR) axis. With the exception of Hole 558 and the uncertainties of reconstructions of absolute plate movements in the region, the observed variations can be explained by two hot spots; the nearly ridge-centered Azores hot spot (plume) and another hot spot located beneath the African plate that may be affecting the source of basalts currently erupting at the MAR axis at 35°N and which, in the past, would have produced the New England chain of seamounts on the North American plate and (later) the Atlantis-Great Meteor chain on the African plate. Basalts erupted south of the Hayes Fracture Zone have not been affected by either of these two hot spots over the last 35 Ma and appear to have been continuously derived from the LILE-depleted source. Subaxial flow downridge from the Azores plume appears to have started 9 Ma, on the basis of the southward converging V-shaped time-transgressive ridges branching from the Pico and Corves Island, or not earlier than 16 Ma, on the basis of the geochemical results. Variations within Hole 558 remains unexplained by the latter model, unless we hypothesize a third hot spot.

Probability inundation map for a scenario combining storm surge and sea-level rise

Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.

SADA and DESYRE DSSs descriptive classification criteria (main issues related to DSS's)

Brownfield rehabilitation is an essential step for sustainable land-use planning and management in the European Union. In brownfield regeneration processes, the legacy contamination plays a significant role, firstly because of the persistent contaminants in soil or groundwater which extends the existing hazards and risks well into the future; and secondly, problems from historical contamination are often more difficult to manage than contamination caused by new activities. Due to the complexity associated with the management of brownfield site rehabilitation, Decision Support Systems (DSSs) have been developed to support problem holders and stakeholders in the decision-making process encompassing all phases of the rehabilitation. This paper presents a comparative study between two DSSs, namely SADA (Spatial Analysis and Decision Assistance) and DESYRE (Decision Support System for the Requalification of Contaminated Sites), with the main objective of showing the benefits of using DSSs to introduce and process data and then to disseminate results to different stakeholders involved in the decision-making process. For this purpose, a former car manufacturing plant located in the Brasov area, Central Romania, contaminated chiefly by heavy metals and total petroleum hydrocarbons, has been selected as a case study to apply the two examined DSSs. Major results presented here concern the analysis of the functionalities of the two DSSs in order to identify similarities, differences and complementarities and, thus, to provide an indication of the most suitable integration options.

Crustaceans and fish abundances and species at and around artificially introduced tetrapod fields in the southern North Sea, 2009

The micro-scale spatial distribution patterns of a demersal fish and decapod crustacean assemblage were assessed in a hard-bottom kelp environment in the southern North Sea. Using quadrats along line transects, we assessed the in situ fish and crustacean abundance in relation to substratum types (rock, cobbles and large pebbles) and the density of algae. Six fish and four crustacean species were abundant, with Ctenolabrus rupestris clearly dominating the fish community and Galathea squamifera dominating the crustacean community. Differences in the substratum types had an even stronger effect on the micro-scale distribution than the density of the dominating algae species. Kelp had a negative effect on the fish abundances, with significantly lower average densities in kelp beds compared with adjacent open areas. Averaged over all of the substrata, the most attractive substratum for the fish was large pebbles. In contrast, crustaceans did not show a specific substratum affinity. The results clearly indicate that, similar to other complex systems, significant micro-scale species-habitat associations occur in northern hard-bottom environments. However, because of the frequently harsh environmental conditions, these habitats are mainly sampled from ships with sampling gear, and the resulting data cannot be used to resolve small-scale species-habitat associations. A detailed substratum classification and community assessment, often only possible using SCUBA diving, is therefore important to reach a better understanding of the functional relationships between species and their environment in northern temperate waters, knowledge that is very important with respect to the increasing environmental pressure caused by global climate change.

(Table 1) Snow and sea ice thickness, solar heat input and solar heat used for melting at seven ice mass-balance buoys in the Arctic in 2008

There has been a marked decline in the summer extent of Arctic sea ice over the past few decades. Data from autonomous ice mass-balance buoys can enhance our understanding of this decline. These buoys monitor changes in snow deposition and ablation, ice growth, and ice surface and bottom melt. Results from the summer of 2008 showed considerable large-scale spatial variability in the amount of surface and bottom melt. Small amounts of melting were observed north of Greenland, while melting in the southern Beaufort Sea was quite large. Comparison of net solar heat input to the ice and heat required for surface ablation showed only modest correlation. However, there was a strong correlation between solar heat input to the ocean and bottom melting. As the ice concentration in the Beaufort Sea region decreased, there was an increase in solar heat to the ocean and an increase in bottom melting.

The Lena River Delta - inventory of lakes and geomorphological terraces

This data set provides a detailed inventory of lakes in the Lena Delta, northern Siberia, with respect to the lakes' association with one of the three geomorphological main terraces of the Lena Delta. The inventory is based on Landsat-7 ETM+ image data and spatial analysis in a Geographical Information System (GIS). Several morphometric lake attributes were determined from the resulting dataset and statistically analyzed. Significant differences in the morphometric lake characteristics allowed the distinction of a mean lake type for each main terrace. The lake types reflect the special lithological and cryolithological conditions and geomorphological processes prevailing on each terrace. In Morgenstern et al. (2008), special focus was laid on the investigation of lake orientation and the discussion of possible mechanisms for the evolution of the second terrace's oriented lakes.

Mosaic image of the artificial light produced by Berlin on the night of September 11, 2010 observed from an altitude of 10,000 ft

Aerial observations of light pollution can fill an important gap between ground based surveys and nighttime satellite data. Terrestrially bound surveys are labor intensive and are generally limited to a small spatial extent, and while existing satellite data cover the whole world, they are limited to coarse resolution. This paper describes the production of a high resolution (1 m) mosaic image of the city of Berlin, Germany at night. The dataset is spatially analyzed to identify themajor sources of light pollution in the city based on urban land use data. An area-independent 'brightness factor' is introduced that allows direct comparison of the light emission from differently sized land use classes, and the percentage area with values above average brightness is calculated for each class. Using this methodology, lighting associated with streets has been found to be the dominant source of zenith directed light pollution (31.6%), although other land use classes have much higher average brightness. These results are compared with other urban light pollution quantification studies. The minimum resolution required for an analysis of this type is found to be near 10 m. Future applications of high resolution datasets such as this one could include: studies of the efficacy of light pollution mitigation measures, improved light pollution simulations, economic and energy use, the relationship between artificial light and ecological parameters (e.g. circadian rhythm, fitness, mate selection, species distributions, migration barriers and seasonal behavior), or the management of nightscapes. To encourage further scientific inquiry, the mosaic data is freely available at Pangaea.

Corel Geological Drafting Kit (CGDK) - an extensible CorelDRAW VBA program for geological drafting

Corel Geological Drafting Kit (CGDK), a program written in VBA, has been designed to assist geologists and geochemists with their drafting work. It obtains geological data from a running Excel application directly, and uses the data to plot geochemical diagrams and to construct stratigraphic columns. The software also contains functions for creating stereographic projections and rose diagrams, which can be used for spatial analysis, on a calibrated geological map. The user-friendly program has been tested to work with CorelDRAW 13 - 14 - 15 and Excel 2003 - 2007.

Benthic cover map of Heron Reef derived from a high-spatial-resolution multi-spectral satellite image using object based image analysis

Providing accurate maps of coral reefs where the spatial scale and labels of the mapped features correspond to map units appropriate for examining biological and geomorphic structures and processes is a major challenge for remote sensing. The objective of this work is to assess the accuracy and relevance of the process used to derive geomorphic zone and benthic community zone maps for three western Pacific coral reefs produced from multi-scale, object-based image analysis (OBIA) of high-spatial-resolution multi-spectral images, guided by field survey data. Three Quickbird-2 multi-spectral data sets from reefs in Australia, Palau and Fiji and georeferenced field photographs were used in a multi-scale segmentation and object-based image classification to map geomorphic zones and benthic community zones. A per-pixel approach was also tested for mapping benthic community zones. Validation of the maps and comparison to past approaches indicated the multi-scale OBIA process enabled field data, operator field experience and a conceptual hierarchical model of the coral reef environment to be linked to provide output maps at geomorphic zone and benthic community scales on coral reefs. The OBIA mapping accuracies were comparable with previously published work using other methods; however, the classes mapped were matched to a predetermined set of features on the reef.

An individual based model spatial distribution, production and biomass for Calanus finmarchicus in the Norwegian Sea

The copepod Calanus finmarchicus is the dominant species of the meso-zooplankton in the Norwegian Sea, and constitutes an important link between the phytoplankton and the higher trophic levels in the Norwegian Sea food chain. An individualbased model for C. finmarchicus, based on super-individuals and evolving traits for behaviour, stages, etc., is two-way coupled to the NORWegian ECOlogical Model system (NORWECOM). One year of modelled C. finmarchicus spatial distribution, production and biomass are found to represent observations reasonably well. High C. finmarchicus abundance is found along the Norwegian shelf-break in the early summer, while the overwintering population is found along the slope and in the deeper Norwegian Sea basins. The timing of the spring bloom is generally later than in the observations. Annual Norwegian Sea production is found to be 29 million tonnes of carbon and a production to biomass (P/B) ratio of 4.3 emerges. Sensitivity tests show that the modelling system is robust to initial values of behavioural traits and with regards to the number of super-individuals simulated given that this is above about 50,000 individuals. Experiments with the model system indicate that it provides a valuable tool for studies of ecosystem responses to causative forces such as prey density or overwintering population size. For example, introducing C. finmarchicus food limitations reduces the stock dramatically, but on the other hand, a reduced stock may rebuild in one year under normal conditions. The NetCDF file contains model grid coordinates and bottom topography.

Results of bulk sediment X-ray diffraction analysis and quantification of mineral phases based on the RockJock and on the QUAX quantitative analysis

We have performed quantitative X-ray diffraction (qXRD) analysis of 157 grab or core-top samples from the western Nordic Seas between (WNS) ~57°-75°N and 5° to 45° W. The RockJock Vs6 analysis includes non-clay (20) and clay (10) mineral species in the <2 mm size fraction that sum to 100 weight %. The data matrix was reduced to 9 and 6 variables respectively by excluding minerals with low weight% and by grouping into larger groups, such as the alkali and plagioclase feldspars. Because of its potential dual origins calcite was placed outside of the sum. We initially hypothesized that a combination of regional bedrock outcrops and transport associated with drift-ice, meltwater plumes, and bottom currents would result in 6 clusters defined by "similar" mineral compositions. The hypothesis was tested by use of a fuzzy k-mean clustering algorithm and key minerals were identified by step-wise Discriminant Function Analysis. Key minerals in defining the clusters include quartz, pyroxene, muscovite, and amphibole. With 5 clusters, 87.5% of the observations are correctly classified. The geographic distributions of the five k-mean clusters compares reasonably well with the original hypothesis. The close spatial relationship between bedrock geology and discrete cluster membership stresses the importance of this variable at both the WNS-scale and at a more local scale in NE Greenland.

Seagrass time-series analysis products, in Moreton Bay, Australia, with links to GeoTIFFs

The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (~200 km**2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.