This report describes the methodology used to refine the validation scenarios and the compilation of required data inputs, accounting for the different potential use cases

IREMARE (Marine Renewable Energie Resource Information) is a project funded by ADEME (Agency for the Environment and Energy Control, French Public Institution), convention n°1505C0027. It is dedicated to the production and dissemination of high level information about Marine Renewable Energy (MRE) resource. The information produced during IREMARE project covers the western coast of France (Atlantic, English Channel and North Sea) and can be used for national down to local scale studies. IREMARE-MED (Informations sur la Ressource pour les Energies MArines REnouvelables en MEDiterranée/Marine Renewable Energie Resource Information in the Mediterranean) is a project funded by ADEME (Agence de l'Environnement et de la Maitrise de l'Energie/Agency for the Environment and Energy Control, French Public Institution), convention n°1705C0016. It is dedicated to the production and dissemination of high level information about Marine Renewable Energy (MRE) resource. The data comes from the HOMERE database (Boudiere et al. 2013) for the zone Atlantic, Channel and North Sea and from the ANEMOC-2 dataset (Tiberi-Wadier et al. 2016) for the Mediterranean Sea.

Auteur(s): Sanderre Alain, Desmoulins Christian , Projet thérapeutique étudié en fonction de l'architecture

The “French sub-rectangles of the ICES fishery statistical rectangles” product contains 2D areas vector objects representing a sub-rectangle division of ICES statistical rectangles. Each product polygon belongs to an unique ICES rectangle. This subdivision enables distinction between overlapping areas in two or more EEZs, areas of functional interest and areas of regulatory interest.

Water column sonar data, the acoustic back-scatter from the near-surface to the seafloor, are used to assess physical and biological characteristics of the ocean including the spatial distribution of plankton, fish, methane seeps, and underwater oil plumes. In collaboration with NOAA's National Marine Fisheries Service (NMFS) and the University of Colorado Boulder, NOAA’s National Centers for Environmental Information (NCEI) established a national archive for water column sonar data. This project entails ensuring the long-term stewardship of well-documented water column sonar data, and enabling discovery and access to researchers and the public around the world. Data providers include NOAA National Marine Fisheries Service (NMFS), NOAA Office of Ocean Exploration and Research (OER), NOAA National Ocean Service (NOS), Rolling Deck to Repository (R2R), U.S. academic and private institutions, and international groups. This data set comprises the water-column sonar data archived at NCEI in a more readily accessible media. Data provided to NCEI are in their raw format. Processing routines are being applied to a subset of the archive, specifically focusing on Simrad EK60 single and multiple frequency datasets. Ping alignment, noise removal algorithms (De Robertis & Higgenbottom, 2007; Ryan et al., 2015), and bottom detection algorithms are applied to the raw data binned into one hour intervals using Echoview (Myriax, v.10). The processed data are exported as a CSV for each interval and each frequency.

The "EMODnet Digital Bathymetry (DTM) - 2016" is a multilayer bathymetric product for Europe’s sea basins covering:: • the Greater North Sea, including the Kattegat and stretches of water such as Fair Isle, Cromarty, Forth, Forties, Dover, Wight, and Portland • the English Channel and Celtic Seas • Western and Central Mediterranean Sea and Ionian Sea • Bay of Biscay, Iberian coast and North-East Atlantic • Adriatic Sea • Aegean - Levantine Sea (Eastern Mediterranean) • Azores - Madeira EEZ • Canary Islands • Baltic Sea • Black Sea • Norwegian – Icelandic seas The DTM is based upon more than 7700 bathymetric survey data sets and Composite DTMs that have been gathered from 27 data providers from 18 European countries and involving 169 data originators. The gathered survey data sets can be discovered and requested for access through the Common Data Index (CDI) data discovery and access service that also contains additional European survey data sets for global waters. This discovery service makes use of SeaDataNet standards and services and have been integrated in the EMODnet portal (https://emodnet.ec.europa.eu/en/bathymetry#bathymetry-services ). The Composite DTMs are described using the Sextant Catalogue Service that makes also use of SeaDataNet standards and services. Their metadata can retrieved through interrogating the Source Reference map in the Central Map Viewing service (https://emodnet.ec.europa.eu/geoviewer/ ). In addition, the EMODnet Map Viewer gives users wide functionality for viewing and downloading the EMODnet digital bathymetry such as: • water depth (refering to the Lowest Astronomical Tide Datum - LAT) in gridded form on a DTM grid of 1/8 * 1/8 arc minute of longitude and latitude (ca 230 * 230 meters) • option to view depth parameters of individual DTM cells and references to source data • option to download DTM in 16 tiles in different formats: EMO, EMO (without GEBCO data), ESRI ASCII, ESRI ASCII Mean Sea Level, XYZ, NetCDF (CF), RGB GeoTiff and SD • layer with a number of high resolution DTMs for coastal regions • layer with wrecks from the UKHO Wrecks database. The NetCDF (CF) DTM files are fit for use in a special 3D Viewer software package which is based on the existing open source NASA World Wind JSK application. It has been developed in the frame of the EU FP7 Geo-Seas project (another sibling of SeaDataNet for marine geological and geophysical data) and is freely available. The 3D viewer also supports the ingestion of WMS overlay maps. The SD files can also be used for 3D viewing by means of the freely available iView4De(Fledermaus) software. The original datasets themselves are not distributed but described in the metadata services, giving clear information about the background survey data used for the DTM, their access restrictions, originators and distributors and facilitating requests by users to originator.

GAM-NICHE is a new tool developed by AZTI (Valle et al. 2023) to build Species Distribution Models (SDMs) under the ecological niche theory (Citores et al. 2020). It provides a GitHub tutorial in R language with an application to marine fish. Species Distribution Models (SDMs) are numerical tools that combine observations of species occurrence or abundance at known locations with information on the environmental and/or spatial characteristics of those locations (Elith and Leathwick 2009). SDMs are widely used as a tool for understanding species spatial ecology and are also known as ecological niche models (ENM) or habitat suitability models. According to ecological niche theory, species response curves are unimodal with respect to environmental gradients (Hutchinson 1957). While a variety of statistical methods have been developed for species distribution modelling, a general problem with most of these habitat modelling approaches is that the estimated response curves can display biologically implausible shapes which do not respect ecological niche theory. This is because species response curves are fit statistically with any assumption or restriction, which sometimes do not respect the ecological niche theory. To better understand species response to environmental changes, SDMs should consider theoretical background such as the ecological niche theory and pursue the unimodality of the response curves with respect to environmental gradients. This book provides a tutorial on how to use Shape-Constrained Generalized Additive Models (SC-GAMs) to build SDMs under the ecological niche theory framework (Citores et al. 2020). SC-GAMs impose monotonicity and concavity constraints in the linear predictor of the GAMs and avoid overfitting. SC-GAM is an effective alternative to fitting nonsymmetric parametric response curves, while retaining the unimodality constraint, required by ecological niche theory, for direct variables and limiting factors. The book is organised following the key steps in good modelling practice of SDMs (Elith and Leathwick 2009). First, presence data of a selected species are downloaded from GBIF/OBIS global public datasets and pseudo-absence data are created. Then, environmental data are downloaded from public repositories and extracted at each of the presence/pseudo-absence data points. Based on this dataset, an exploratory analysis is conducted to help deciding on the best modelling approach. The model is fitted to the dataset and the quality of the fit and the realism of the fitted response function are evaluated. After selecting a threshold to transform the continuous probability predictions into binary responses, the model is validated using a k-fold approach. Finally, the predicted maps are generated for visualization. The code is available in AZTI’s github repository and the book is readily available. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0) To cite the book, please use: Valle, M., Citores, L., Ibaibarriaga, L., Chust, C. (2023) GAM-NICHE: Shape-Constrained GAMs to build Species Distribution Models under the ecological niche theory. AZTI. https://doi.org/10.57762/fzpy-6w51 References Citores, L, L Ibaibarriaga, DJ Lee, MJ Brewer, M Santos, and G Chust. 2020. “Modelling Species Presence–Absence in the Ecological Niche Theory Framework Using Shape-Constrained Generalized Additive Models.” Ecological Modelling 418: 108926. https://doi.org/10.1016/j.ecolmodel.2019.108926.

The objective of the DTOceanPlus project was to develop a software suite of open source advanced tools for the selection, development and deployment of ocean energy systems. DTOceanPlus project made it to develop and demonstrate an open source sotftware suite of second generation design tools for ocean energy technologies including sub-systems, energy capture devices and arrays. These tools support the entire technology innovation process, from concept, through development, to deployment. More broadly, the project also provided an industry standard for communicating technology descriptions throughout the sector. To complement the numerical work, an extensive market analysis of the ocean energy sector is publicly available.