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It is widely known that the subsurface will play a crucial role in the transition towards a carbon-neutral society, with the aid of technologies like geothermal energy, CO2-storage, .... Nevertheless, still a lot of aspects concerning the subsurface, its structure and characteristics remain to be investigated to facilitate the use of underground space in an efficient and safe way. In-depth investigation of the subsurface with conventional techniques such as seismic campaigns or drillings requires high investments, and it is not always straightforward to determine the success-rate upfront. This leads to geodata collections typically displaying a large variety and scatter, both concerning data (type) availability and in spatial distribution. Additionally, incorporating subsurface knowledge from neighboring countries often is challenging, but at the same time indispensable to increase understanding of the own subsurface, not least because some projects may display cross-border influences. It is clear that subsurface exploration benefits from a cross-border and cross-thematic data collection and interpretation approach. One way to organize such data centralization was explored in the framework of the European Horizon2020-project GeoConnect³d, by means of constructing a Structural Framework (SF) and a database of Geomanifestations (GM) for several pilot study areas. The Structural Framework defines geological units by its limits (e.g., faults, terrane boundaries, ...). All known limits and associated parameters are structured in a uniform and inter-connected way. Furthermore, the SF is designed on multiple zoom-levels, hence it can serve as a real backbone to integrate multiple other subsurface models of various scale and resolution together. Geomanifestations are anomalous observations covering a wide range of geo-disciplines, including —but not limited to— temperature, geochemistry, mineralogy and even geophysics data. Such irregularities are too often excluded or ignored in view of the larger cloud of ‘normal’ datapoints. Nevertheless, precisely these anomalies can be of great value for identifying subsurface processes and serve as an excellent pathway for communication to non-experts, and also as guideline for further research. In addition to GIS- and attribute-information, Factsheets summarize the relations between individual geomanifestations, and, if applicable, their connection to the Structural Framework. Especially the latter, the combination of the (independent) elements SF and GM, gives a powerful tool that allows exploring the subsurface in an original and cost-efficient way. The newly gained insights can be directly linked and are extremely relevant to the use of the subsurface, either as storage space or as renewable/green energy-source. But it goes further than that. The overall usability of the SF and GM database is far more fundamental, as it gives innovative clues about characteristics and processes at play in the subsurface, such as fault permeability and connectivity, the presence of advection cells in the upper crust, or gas origin and migration pathways. To quote just one example; in the area of Spa, Belgium, elevated 3He/4He-ratios were analyzed (Griesshaber et al., 1992), a parameter that can highlight mantle gas contribution in gas seeps (White, 2013). This observation was unexpected given the far distance from any volcanic activity, but suggests the presence of deep-seated, transcrustal faults and/or a large-distance connectivity till the Eifel area where mantle-derived magma was involved in recent volcanism. When indirect indications like this are not considered further, such valuable subsurface knowledge is easily overlooked and not at all taken into account for investigating in more detail in the future. Even when limited resources or funding is available, the above-illustrated SF+GM approach can shed new light on properties and processes of the subsurface, given its novel and multidisciplinary approach. An inherent drawback, however, is that such a database is never complete and includes information from a variety of sources. Not only does this demands careful consideration on which data is included (or not), it also has to be taken into account for future database expansion as well as for data interpretation. Simple visualizations on a map without further (geological) background, e.g., combining both surface and at depth data as is the case for Wiesbaden, Germany (Mittelbach & Siebert, 2014), may lead to false conclusions. However, the provided Factsheets and metadata can help in this. Furthermore, at this moment, a large proportion of the entries depends on the availability of literature data, which implies some data source bias is unavoidable. For example, CO2-data typically is measured for springs and streams, while dry CO2-seeps easier remain unnoticed and therefore are reported less consistently. New data collection campaigns, possibly including bio-indicators like plants or ants (e.g., Berberich & Schreiber, 2013), can provide a good starting point for this. The uniform and well-designed structure of the database allows very easy expansion, be it for newly discovered faults, additional geomanifestation types, or parameter updates of either part. In addition, as demonstrated in the GeoConnect³d project, the SF+GM approach is fully transferable to other study areas. This clears the way for a cost-efficient cross-border exploration of the subsurface with wins for both the academic world and common public (geoheritage, education, ...), and significantly contributes to a more data-supported outline for subsurface management. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 731166. References Berberich, G., & Schreiber, U., 2013. GeoBioScience: Red Wood Ants as Bioindicators for Active Tectonic Fault Systems in the West Eifel (Germany). Animals, 3, 475-498. Griesshaber, E., O'Nions, R.K. & Oxburg, E.R., 1992. Helium and carbon isotope systematics in crustal fluids from the Eifel, the Rhine Graben and Black Forest, F.R.G. Chemical Geology, 99, 213-235. Mittelbach, G. & Siebert, S., 2014. Gutachten zur Festsetzung eines Heilquellenschutzgebietes für die Heilquellen (Große und Kleine Adlerquelle, Schützenhofquelle, Kochbrunnen, Salmquelle und Faulbrunnen) von Wiesbaden, Stadt Wiesbaden (WSG-ID 414-005), Wiesbaden, pp. 1-52. White, W.M., 2013. Chapter 12: Noble Gas Isotope Geochemistry, Isotope Geochemistry course notes. Cornell University.

Leponce, M.1, Pascal, O.2, Novotny, V.3,4 & Y. Basset5 (1) Royal Belgian Institute of Natural Sciences, Belgium (Maurice.Leponce@naturalsciences.be); (2) Pro-Natura International, France; (3) University of South Bohemia, Czech Rep.; (4) Czech Academy of Sciences; (5) Smithsonian Tropical Research Institute, Republic of Panama. Background: IBISCA is an international and informal network of biodiversity experts conducting large-scale biotic inventories in various regions of the World (www.ibisca.net). Each IBISCA project is a collective effort addressing a global ecological question. IBISCA-Panama (2003-2004) aimed at estimating the overall arthropod diversity of a lowland rainforest while the Papua New Guinea survey (2012-2014), conducted in the framework of the “Our Planet Reviewed” programme, aimed at assessing the diversity generated by the elevational factor, from sea level up to the tree line. Methods: All projects are multi-taxa (with an emphasis on plants and arthropods), multi-strata and multi-methods. A central database (DB) is at the heart of each project. Results: The data flow follows a 10 step standard process: (1) sampling design which is often a trade-off between sampling effort and representativeness; (2) pre-printing of permanent labels with unique codes for samples and specimens; (3) collection of specimens with standardized mass collection methods; (4) on-site pre-sorting of material by helpers (para-taxonomists, students) to Order level; (5) further sorting to Family level by Taxonomic Working Group (TWIG) leaders and dispatching of specimens to experts; (6) identification of the material to (morpho-)species level by taxonomic experts who send afterwards the results to their TWIG leader; (7) control of the quality of data by TWIG leaders who fill a data entry template and send it to the database administrator; (8) import and cleaning of the data by the database administrator; (9) analysis and publication of the data by participants, either collectively or individually; (10) export of the DB to a public repository of data. Assisted data entry with high tech equipment (barcode scanner, PDA) reduces the risk of errors. Discussion/conclusion: Our experience shows that the main bottleneck in the data flow is the processing of the huge quantity of specimens collected. Solutions include securing enough funds for this critical step, training research technicians (para-taxonomists/ecologists) to assist main investigators and focusing on a limited number of informative yet tractable taxa. An additional benefit is that providing employment to local research assistants supports initiatives of local communities to conserve their forests.

This study describes physical processes (mainly the turbulence and re-suspension of particles due to turbulence) which control the micro scale variability of the bio-optical properties in highly turbid coastal waters. Time series analyses of different bio-optical and physical properties (temperature, salinity) have been performed from a boat in coastal waters. The data base gathers high frequency (1 Hz) simultaneous measurements performed during about 12 hours at four different days and locations in the highly turbid coastal environments of North Sea. We mainly focus on the concentrations of Chlorophyll and coloured detrital matter, back-scattering, and attenuation. For each parameter we consider the statistics (mean values, coefficients of variance and probability density functions) and the dynamics (Fourier power spectra). We found that these optical parameters (bbp, bpslope g, Refractive index-n and cp) are influenced by turbulence and inherit some of turbulence characteristics; high frequency noise, scales of variability at lower frequencies.