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Species distribution model of invasive macroalgae Citation Ramos, E., Sainz-Villegas, S., de la Hoz, C.F., Puente, A., Juanes, J.A. (2023) Species Distribution Models for invasive macroalgae. Integrated data products created under the European Marine Observation Data Network (EMODnet) Biology project Phase IV (EMFF/2019/1.3.1.9/Lot 6/SI2.837974), funded by the by the European Union under Regulation (EU) No 508/2014 of the European Parliament and of the Council of 15 May 2014 on the European Maritime and Fisheries Fund. https://marineinfo.org/id/dataset/8209 Contact: Availability:  This dataset is licensed under a Creative Commons Attribution 4.0 International License.Description The number of marine seaweeds outside their natural boundaries has increased in the last decades generating impacts on biodiversity and economy. This makes the development of management tools necessary, where species distribution models (SDMs) play a crucial role. SDMs can help in the early detection of invasions and predict the extent of the potential spread. However, modelling non-native marine species distributions is still challenging in terms of model building, evaluation and selection. This product aims to predict the European distribution of four widespread introduced seaweed species (Asparagopsis armata, Caulerpa Taxifolia, Sargassum muticum and Undaria pinnatifida) selecting the best model building process. Scope Themes: Biology > Macroalgae Keywords: Bio-geographical regions, Biota, Data not evaluated, Environment, European, Geoscientific Information, Habitats and biotopes, Invasive species, Metadata not evaluated, NetCDF (Network Common Data Form), No limitations to public access, Oceans, Regional, Sea regions, WGS84 (EPSG:4326), Africa Coasts, ASE, Canary I., Atlantic coast of Europe, Azores Coast, Greenlandic Coast, Icelandic Coast, Madeiran Coast, Mediterranean and Black Sea, Svalbard, Asparagopsis armata Harvey, 1855, Caulerpa taxifolia (M.Vahl) C.Agardh, 1817, Sargassum muticum (Yendo) Fensholt, 1955, Undaria pinnatifida (Harvey) Suringar, 1873 Geographical coverage Africa Coasts [Marine Regions] ASE, Canary I. [Marine Regions] Atlantic coast of Europe [Marine Regions] Azores Coast [Marine Regions] Greenlandic Coast [Marine Regions] Icelandic Coast [Marine Regions] Madeiran Coast [Marine Regions] Mediterranean and Black Sea [Marine Regions] Svalbard [Marine Regions] Taxonomic coverage Contributors University of Cantabria; Environmental Hydraulics Institute (IH Cantabria), more, data owner Project EMODnet Bio IV: European Marine Observation and Data Network- Biology IV, more Publication Used in this dataset Sainz-Villegas, S. et al. (2022). Predicting non-native seaweeds global distributions: The importance of tuning individual algorithms in ensembles to obtain biologically meaningful results. Front. Mar. Sci. 9: 1009808. https://dx.doi.org/10.3389/fmars.2022.1009808, more Cobos, M.E. et al. (2019). kuenm: an R package for detailed development of ecological niche models using Maxent. PeerJ 7: e6281. https://dx.doi.org/10.7717/peerj.6281, more de la Hoz, C.F. et al. (2019). Climate change induced range shifts in seaweeds distributions in Europe. Mar. Environ. Res. 148: 1-11. https://dx.doi.org/10.1016/j.marenvres.2019.04.012, more de la Hoz, C.F. et al. (2019). Temporal transferability of marine distribution models: The role of algorithm selection. Ecol. Indic. 106: 105499. https://dx.doi.org/10.1016/j.ecolind.2019.105499, more URLs Dataset information: Other: Dataset status: Completed Data type: Data products Data origin: Research Release date: 2023-03-14 Metadatarecord created: 2023-02-16 Information last updated: 2024-07-08 | ||||
