(Table 1) Summary of sampling points described and main petrographic, morphological and geochemical characteristics

Targeted sampling on the Dolgovskoy Mound (northern Shatsky Ridge) revealed the presence of spectacular laterally extensive and differently shaped authigenic carbonates. The sampling stations were selected based on sidescan sonar and profiler images that show patchy backscatter and irregular and discontinuous reflections in the near subsurface. The interpretation of acoustic data from the top part of the mound supports the seafloor observations and the sampling that revealed the presence of a complex subsurface plumbing system characterized by carbonates and gas. The crusts sampled consist of carbonate cemented layered hemipelagic sedimentary Unit 1 associated with several centimetres thick microbial mats. Three different carbonate morphologies were observed: (a) tabular slabs, (b) subsurface cavernous carbonates consisting of void chambers up to 20 cm**3 in size and (c) chimney and tubular conduits vertically oriented or forming a subhorizontal network in the subsurface. The methanogenic origin of the carbonates is established based on visual observations of fluids seepage structures, 13C depletion of the carbonates (d13C varying between -36.7 per mil and -27.4 per mil), and by thin carbonate layers present within the thick microbial mats. Laboratory experiments with a Hele-Shaw cell were conducted in order to simulate the gas seepage through contrasting grain size media present on the seafloor. Combined petrography, visual observations and sandbox simulations allowed a characterization of the dynamics and the structures of the plumbing system in the near subsurface. Based on sample observations and the experiments, three observed morphologies of authigenic carbonates are interpreted, respectively, as (a) Darcian porous flow through the finely laminated clayey/coccolith-rich layers, (b) gas accumulation chambers at sites where significant fluid escape was impeded by thicker clayey layers forming the laminated Unit1 and (c) focussed vertical fluid venting and subhorizontal migration of overpressured fluids released from (b). The Hele-Shaw cell experiments represent a promising tool for investigating shallow fluid flow pathways in marine systems.

Description of sampling sites in Northern Russia

The youngest ice marginal zone between the White Sea and the Ural mountains is the W-E trending belt of moraines called the Varsh-Indiga-Markhida-Harbei-Halmer-Sopkay, here called the Markhida line. Glacial elements show that it was deposited by the Kara Ice Sheet, and in the west, by the Barents Ice Sheet. The Markhida moraine overlies Eemian marine sediments, and is therefore of Weichselian age. Distal to the moraine are Eemian marine sediments and three Palaeolithic sites with many C-14 dates in the range 16-37 ka not covered by till, proving that it represents the maximum ice sheet extension during the Weichselian. The Late Weichselian ice limit of M. G. Grosswald is about 400 km (near the Urals more than 700 km) too far south. Shorelines of ice dammed Lake Komi, probably dammed by the ice sheet ending at the Markhida line, predate 37 ka. We conclude that the Markhida line is of Middle/Early Weichselian age, implying that no ice sheet reached this part of Northern Russia during the Late Weichselian. This age is supported by a series of C-14 and OSL dates inside the Markhida line all of >45 ka. Two moraine loops protrude south of the Markhida line; the Laya-Adzva and Rogavaya moraines. These moraines are covered by Lake Komi sediments, and many C-14 dates on mammoth bones inside the moraines are 26-37 ka. The morphology indicates that the moraines are of Weichselian age, but a Saalian age cannot be excluded. No post-glacial emerged marine shorelines are found along the Barents Sea coast north of the Markhida line.

IBAMar DATABASE: 4 decades of oceanographic sampling on the Western Mediterranean Sea

IBAMar (http://www.ba.ieo.es/ibamar) is a regional database that puts together all physical and biochemical data obtained by multiparametric probes (CTDs equipped with different sensors), during the cruises managed by the Balearic Center of the Spanish Institute of Oceanography (COB-IEO). It has been recently extended to include data obtained with classical hydro casts using oceanographic Niskin or Nansen bottles. The result is a database that includes a main core of hydrographic data: temperature (T), salinity (S), dissolved oxygen (DO), fluorescence and turbidity; complemented by bio-chemical data: dissolved inorganic nutrients (phosphate, nitrate, nitrite and silicate) and chlorophyll-a. In IBAMar Database, different technologies and methodologies were used by different teams along the four decades of data sampling in the COB-IEO. Despite of this fact, data have been reprocessed using the same protocols, and a standard QC has been applied to each variable. Therefore it provides a regional database of homogeneous, good quality data. Data acquisition and quality control (QC): 94% of the data are CTDs Sbe911 and Sbe25. S and DO were calibrated on board using water samples, whenever a Rossetta was available (70% of the cases). All CTD data from Seabird CTDs were reviewed and post processed with the software provided by Sea-Bird Electronics. Data were averaged to get 1 dbar vertical resolution. General sampling methodology and pre processing are described in https://ibamardatabase.wordpress.com/home/). Manual QC include visual checks of metadata, duplicate data and outliers. Automatic QC include range check of variables by area (north of Balearic Islands, south of BI and Alboran Sea) and depth (27 standard levels), check for spikes and check for density inversions. Nutrients QC includes a preliminary control and a range check on the observed level of the data to detect outliers around objectively analyzed data fields. A quality flag is assigned as an integer number, depending on the result of the QC check.

Bird observation and sampling in tropical agroforestry landscapes of the Napu Valley in Central Sulawesi, Indonesia

We investigated the local bird community in Central Sulawesi (Indonesia), with focus on insectivorous species in the agroforestry landscapes adjacent to the Lore Lindu National Park. All study sites were situated at the northern tip of Napu Valley in Central Sulawesi, Indonesia. After an initial mapping of the study area, we selected 15 smallholder cacao plantations as sites for our study in March 2010. These sides were mainly used for bird and bat exclosure experiments. All sited were situated along a local gradient (shade availability on each plantation) and a landscape gradient (distance to primary forest), which were independent from each other. In September 2010 and from February until June 2011, we assessed the bird community on our 15 study sites using monthly point count and mist netting sampling. Point count (20 minutes between 07 am and 10 am and in between the net checking hours) and mist netting surveys (12 hours, between 05:30 am and 17:30 pm) were conducted simultaneously but only once per month on each study site, to avoid habituation of the local bird community to our surveys. Further, point counts were conducted at least 100 m apart from the mist netting sites, to avoid potential disturbance between the two methods. We discarded all observations beyond 50 m (including those individuals that flew over the canopy) from the statistical analysis, as well as recaptures of individuals within identical mist netting rounds.

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.