Species distribution model of invasive macroalgae
<p>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.</p>
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Date | 2023-03-14 |
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Date type | Publication: Date identifies when the resource was issued |
Unique resource identifier |
Point of contact
Organisation name | Environmental Hydraulics Institute |
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Electronic mail address | elvira.ramos@unican.es |
Role | Owner: Party that owns the resource |
Point of contact
Organisation name | Environmental Hydraulics Institute |
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Role | Owner: Party that owns the resource |
Point of contact
Organisation name | Environmental Hydraulics Institute |
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Role | Owner: Party that owns the resource |
Point of contact
Organisation name | Environmental Hydraulics Institute |
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Role | Owner: Party that owns the resource |
Point of contact
Organisation name | Environmental Hydraulics Institute |
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Role | Owner: Party that owns the resource |
Descriptive keywords
GEMET - INSPIRE themes, version 1.0 | |
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European
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Regional
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Language | zxx: zxx |
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Topic category code |
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Reference System Information
Anchor | EPSG:4326 |
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Hierarchy level | Dataset: Information applies to the dataset |
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Statement | Methodology is available via https://github.com/EMODnet/EMODnet-Biology-invasive-macroalgae-sdm |
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File identifier | 6d617269-6e65-696e-666f-000000008209 |
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Metadata language | English |
Character set | UTF8: 8-bit variable size UCS Transfer Format, based on ISO/IEC 10646 |
Hierarchy level | Dataset: Information applies to the dataset |
Date stamp | 2024-07-08T00:00:00+02:00 |
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