(Table 2) Comparison of annual mass fluxes measured with shallower and deeper sediment traps off Cape Blanc (CB)

The ocean off NW Africa is the second most important coastal upwelling system with a total annual primary production of 0.33 Gt of carbon per year (Carr in Deep Sea Res II 49:59-80, 2002). Deep ocean organic carbon fluxes measured by sediment traps are also fairly high despite low biogenic opal fluxes. Due to a low supply of dissolved silicate from subsurface waters, the ocean off NW Africa is characterized by predominantly carbonate-secreting primary producers, i.e. coccolithophorids. These algae which are key primary producers since millions of years are found in organic- and chlorophyll-rich zooplankton fecal pellets, which sink rapidly through the water column within a few days. Particle flux studies in the Mauretanian upwelling area (Cape Blanc) confirm the hypothesis of Armstrong et al. (Deep Sea Res II 49:219-236, 2002) who proposed that ballast availability, e.g. of carbonate particles, is essential to predict deep ocean organic carbon fluxes. The role of dust as ballast mineral for organic carbon, however, must be also taken into consideration in the coastal settings off NW Africa. There, high settling rates of larger particles approach 400 m day**-1, which may be due to a particular composition of mineral ballast. An assessment of particle settling rates from opal-production systems in the Southern Ocean of the Atlantic Sector, in contrast, provides lower values, consistent with the assumptions of Francois et al. (Global Biogeochem Cycles 16(4):1087, 2002). Satellite chlorophyll distributions, particle distributions and fluxes in the water column off NW Africa as well as modelling studies suggest a significant lateral flux component and export of particles from coastal shelf waters into the open ocean. These transport processes have implications for paleo-reconstructions from sediment cores retrieved at continental margin settings.

Probability sampling protocol of classification maps from spaceborne/airborne image

To deliver sample estimates provided with the necessary probability foundation to permit generalization from the sample data subset to the whole target population being sampled, probability sampling strategies are required to satisfy three necessary not sufficient conditions: (i) All inclusion probabilities be greater than zero in the target population to be sampled. If some sampling units have an inclusion probability of zero, then a map accuracy assessment does not represent the entire target region depicted in the map to be assessed. (ii) The inclusion probabilities must be: (a) knowable for nonsampled units and (b) known for those units selected in the sample: since the inclusion probability determines the weight attached to each sampling unit in the accuracy estimation formulas, if the inclusion probabilities are unknown, so are the estimation weights. This original work presents a novel (to the best of these authors' knowledge, the first) probability sampling protocol for quality assessment and comparison of thematic maps generated from spaceborne/airborne Very High Resolution (VHR) images, where: (I) an original Categorical Variable Pair Similarity Index (CVPSI, proposed in two different formulations) is estimated as a fuzzy degree of match between a reference and a test semantic vocabulary, which may not coincide, and (II) both symbolic pixel-based thematic quality indicators (TQIs) and sub-symbolic object-based spatial quality indicators (SQIs) are estimated with a degree of uncertainty in measurement in compliance with the well-known Quality Assurance Framework for Earth Observation (QA4EO) guidelines. Like a decision-tree, any protocol (guidelines for best practice) comprises a set of rules, equivalent to structural knowledge, and an order of presentation of the rule set, known as procedural knowledge. The combination of these two levels of knowledge makes an original protocol worth more than the sum of its parts. The several degrees of novelty of the proposed probability sampling protocol are highlighted in this paper, at the levels of understanding of both structural and procedural knowledge, in comparison with related multi-disciplinary works selected from the existing literature. In the experimental session the proposed protocol is tested for accuracy validation of preliminary classification maps automatically generated by the Satellite Image Automatic MapperT (SIAMT) software product from two WorldView-2 images and one QuickBird-2 image provided by DigitalGlobe for testing purposes. In these experiments, collected TQIs and SQIs are statistically valid, statistically significant, consistent across maps and in agreement with theoretical expectations, visual (qualitative) evidence and quantitative quality indexes of operativeness (OQIs) claimed for SIAMT by related papers. As a subsidiary conclusion, the statistically consistent and statistically significant accuracy validation of the SIAMT pre-classification maps proposed in this contribution, together with OQIs claimed for SIAMT by related works, make the operational (automatic, accurate, near real-time, robust, scalable) SIAMT software product eligible for opening up new inter-disciplinary research and market opportunities in accordance with the visionary goal of the Global Earth Observation System of Systems (GEOSS) initiative and the QA4EO international guidelines.

Pollen analysis of modern mangrove systems

Three sediment cores from the Bragança Peninsula located in the coastal region in the north-eastern portion of Pará State have been studied by pollen analysis to reconstruct Holocene environmental changes and dynamics of the mangrove ecosystem. The cores were taken from an Avicennia forest (Bosque de Avicennia (BDA)), a salt marsh area (Campo Salgado (CS)) and a Rhizophora dominated area (Furo do Chato). Pollen traps were installed in five different areas of the peninsula to study modern pollen deposition. Nine accelerator mass spectrometry radiocarbon dates provide time control and show that sediment deposits accumulated relatively undisturbed. Mangrove vegetation started to develop at different times at the three sites: at 5120 14C yr BP at the CS site, at 2170 14C yr BP at the BDA site and at 1440 14C yr BP at the FDC site. Since mid Holocene times, the mangroves covered even the most elevated area on the peninsula, which is today a salt marsh, suggesting somewhat higher relative sea-levels. The pollen concentration in relatively undisturbed deposits seems to be an indicator for the frequency of inundation. The tidal inundation frequency decreased, probably related to lower sea-levels, during the late Holocene around 1770 14C yr BP at BDA, around 910 14C yr BP at FDC and around 750 14C yr BP at CS. The change from a mangrove ecosystem to a salt marsh on the higher elevation, around 420 14C yr BP is probably natural and not due to an anthropogenic impact. Modern pollen rain from different mangrove types show different ratios between Rhizophora and Avicennia pollen, which can be used to reconstruct past composition of the mangrove. In spite of bioturbation and especially tidal inundation, which change the local pollen deposition within the mangrove zone, past mangrove dynamics can be reconstructed. The pollen record for BDA indicates a mixed Rhizophora/Avicennia mangrove vegetation between 2170 and 1770 14C yr BP. Later Rhizophora trees became more frequent and since ca. 200 14C yr BP Avicennia dominated in the forest.

Using ground-penetrating radar, topography and classification of vegetation to model the sediment and active layer thickness in a periglacial lake catchment, Western Greenland, link to shapefiles

The geometries of a catchment constitute the basis for distributed physically based numerical modeling of different geoscientific disciplines. In this paper results from ground-penetrating radar (GPR) measurements, in terms of a 3D model of total sediment thickness and active layer thickness in a periglacial catchment in western Greenland, is presented. Using the topography, thickness and distribution of sediments is calculated. Vegetation classification and GPR measurements are used to scale active layer thickness from local measurements to catchment scale models. Annual maximum active layer thickness varies from 0.3 m in wetlands to 2.0 m in barren areas and areas of exposed bedrock. Maximum sediment thickness is estimated to be 12.3 m in the major valleys of the catchment. A method to correlate surface vegetation with active layer thickness is also presented. By using relatively simple methods, such as probing and vegetation classification, it is possible to upscale local point measurements to catchment scale models, in areas where the upper subsurface is relatively homogenous. The resulting spatial model of active layer thickness can be used in combination with the sediment model as a geometrical input to further studies of subsurface mass-transport and hydrological flow paths in the periglacial catchment through numerical modelling.

Species name, classification (WORMS), abundance and biomass of the megabenthic communities of the Algarve

The present study analysed the megabenthic diversity in subtidal soft bottoms and assessed the main environmental drivers of megabenthic community organisation along the Algarve coast (southern Portugal). We tested the hypothesis that megabenthic communities respond to the same environmental drivers than macrofauna. We found that similar to macrofauna, megafaunal communities were organised in relation to the depth of closure, light reaching the bottom, and the hydrodynamic conditions related with exposure within the shallower areas. The influence of the main river outflow prevailed over other drivers, but only up to 9 m depth. We found that seven different spatial units should be considered, each characterised by different indicator species. Additionally, among a total of 412 taxa collected between 4 and 50 m depth, we provide the characteristics of the 64 commonest species in terms of occurrence, frequency, distribution, abundance, bathymetric and sedimentary preferences, which constitutes most valuable information for ecosystem modelling. Megabenthic alpha diversity decreased with depth, contrary to evenness and was higher in the proximity of the river Guadiana and in highly exposed shores. We conclude that the megafauna, which is significantly quicker to collect and analyse, can provide an accurate alternative to macrofauna sampling, as their communities are shaped by the same drivers.

(Table S1) Diatom abundance in coastal upwelling systems

Coastal upwelling systems account for approximately half of global ocean primary production and contribute disproportionately to biologically driven carbon sequestration. Diatoms, silica-precipitating microalgae, constitute the dominant phytoplankton in these productive regions, and their abundance and assemblage composition in the sedimentary record is considered one of the best proxies for primary production. The study of the sedimentary diatom abundance (SDA) and total organic carbon content (TOC) in the five most important coastal upwelling systems of the modern ocean (Iberia-Canary, Benguela, Peru-Humboldt, California and Somalia-Oman) reveals a global-scale positive relationship between diatom production and organic carbon burial. The analysis of SDA in conjunction with environmental variables of coastal upwelling systems such as upwelling strength, satellite-derived net primary production and surface water nutrient concentrations shows different relations between SDA and primary production on the regional scale. At the global-scale, SDA appears modulated by the capacity of diatoms to take up silicic acid, which ultimately sets an upper limit to global export production in these ocean regions.

Classification of Satellite Images by means of Fuzzy Rules generated by a Genetic Algorithm

The data acquired by Remote Sensing systems allow obtaining thematic maps of the earth's surface, by means of the registered image classification. This implies the identification and categorization of all pixels into land cover classes. Traditionally, methods based on statistical parameters have been widely used, although they show some disadvantages. Nevertheless, some authors indicate that those methods based on artificial intelligence, may be a good alternative. Thus, fuzzy classifiers, which are based on Fuzzy Logic, include additional information in the classification process through based-rule systems. In this work, we propose the use of a genetic algorithm (GA) to select the optimal and minimum set of fuzzy rules to classify remotely sensed images. Input information of GA has been obtained through the training space determined by two uncorrelated spectral bands (2D scatter diagrams), which has been irregularly divided by five linguistic terms defined in each band. The proposed methodology has been applied to Landsat-TM images and it has showed that this set of rules provides a higher accuracy level in the classification process

Evaluation of the influence of toll systems on energy consumption and CO2 emissions: A case study of a Spanish highway

This paper studies the energy consumption and subsequent CO2 emissions of road highway transportation under three toll systems in Spain for four categories of vehicles: cars, vans, buses and articulated trucks. The influence of toll systems is tested for a section of AP-41 highway between Toledo and Madrid. One system is free flow, other is traditional stop and go and the last toll system operates with an electronic toll collection (ETC) technology. Energy consumption and CO2 emissions were found to be closely related to vehicle mass, wind exposure, engine efficiency and acceleration rate. These parameters affect, directly or indirectly, the external forces which determine the energy consumption. Reducing the magnitude of these forces through an appropriate toll management is an important way of improving the energy performance of vehicles. The type of toll system used can have a major influence on the energy efficiency of highway transportation and therefore it is necessary to consider free flow.

Self-reference Scrubber for TMR Systems Based on Xilinx Virtex FPGAs

SRAM-based FPGAs are sensitive to radiation effects. Soft errors can appear and accumulate, potentially defeating mitigation strategies deployed at the Application Layer. Therefore, Configuration Memory scrubbing is required to improve radiation tolerance of such FPGAs in space applications. Virtex FPGAs allow runtime scrubbing by means of dynamic partial reconfiguration. Even with scrubbing, intra-FPGA TMR systems are subjected to common-mode errors affecting more than one design domain. This is solved in inter-FPGA TMR systems at the expense of a higher cost, power and mass. In this context, a self-reference scrubber for device-level TMR system based on Xilinx Virtex FPGAs is presented. This scrubber allows for a fast SEU/MBU detection and correction by peer frame comparison without needing to access a golden configuration memory