Phosphate d18O pore-water profiles of sediment core GeoB11807-2 and GeoB11804-4

Phosphorus cycling in the ocean is influenced by biological and geochemical processes that are reflected in the oxygen isotope signature of dissolved inorganic phosphate (Pi). Extending the Pi oxygen isotope record from the water column into the seabed is difficult due to low Pi concentrations and small amounts of marine porewaters available for analysis. We obtained porewater profiles of Pi oxygen isotopes using a refined protocol based on the original micro-extraction designed by Colman (2002). This refined and customized method allows the conversion of ultra-low quantities (0.5 - 1 µmol) of porewater Pi to silver phosphate (Ag3PO4) for routine analysis by mass spectrometry. A combination of magnesium hydroxide co-precipitation with ion exchange resin treatment steps is used to remove dissolved organic matter, anions, and cations from the sample before precipitating Ag3PO4. Samples as low as 200 µg were analyzed in a continuous flow isotope ratio mass spectrometer setup. Tests with external and laboratory internal standards validated the preservation of the original phosphate oxygen isotope signature (d18OP) during micro extraction. Porewater data on d18OP has been obtained from two sediment cores of the Moroccan margin. The d18OP values are in a range of +19.49 to +27.30 per mill. We apply a simple isotope mass balance model to disentangle processes contributing to benthic P cycling and find evidence for Pi regeneration outbalancing microbial demand in the upper sediment layers. This highlights the great potential of using d18OP to study microbial processes in the subseafloor and at the sediment water interface.

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.