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File: 'EMODnet-Biology-invasive-macroalgae-sdm.zip'
IMIS metadata and citations
Species distribution model of invasive macroalgae [dasid=8209] show more
File properties
Filename EMODnet-Biology-invasive-macroalgae-sdm.zip
Direct link https://mda.vliz.be/directlink.php?fid=VLIZ_00000727_640b3123f30b0243339169
Datatype Geographic data
MIMEtype application/x-zip-compressed
Authors EMODnet-Biology
Dataprovider EMODnet-Biology
Email Dataprovider bio@emodnet.eu
Conditions of use CC-BY
Creationdate 2023-03-10
Submitter Fernandez Salvador
Submit date 2023-03-10 13:31:16
Archived by Fernandez Salvador
Archive date 2023-03-10 13:33:25
Path EMODnet - Public/Data products/2023/
Start year 2022
End year 2100
Summary
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.
Changes
Metadata
Content
Geographic file type
Numeric
Data origin
derived/modelled/interpolated
Version
Temporal scope
First date
2022
Last date
2100
Geographic scope
Sea area(s)
- North Atlantic Ocean (MRGID1912)
- Mediterranean Sea (MRGID1905)
Location
Coordinate reference
Z Reference
Additional information
Other info
Webservice
Link file
| Species distribution model of invasive macroalgae [dasid=8209] show more |
File properties
| Filename | EMODnet-Biology-invasive-macroalgae-sdm.zip |
|---|---|
| Direct link | https://mda.vliz.be/directlink.php?fid=VLIZ_00000727_640b3123f30b0243339169 |
| Datatype | Geographic data |
| MIMEtype | application/x-zip-compressed |
| Authors | EMODnet-Biology |
| Dataprovider | EMODnet-Biology |
| Email Dataprovider | bio@emodnet.eu |
| Conditions of use | CC-BY |
| Creationdate | 2023-03-10 |
| Submitter | Fernandez Salvador |
| Submit date | 2023-03-10 13:31:16 |
| Archived by | Fernandez Salvador |
| Archive date | 2023-03-10 13:33:25 |
| Path | EMODnet - Public/Data products/2023/ |
| Start year | 2022 |
| End year | 2100 |
| Summary | |
| 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. |
| Changes |
Metadata
| Content | |
| Geographic file type | Numeric |
|---|---|
| Data origin | derived/modelled/interpolated |
| Version | |
| Temporal scope | |
| First date | 2022 |
| Last date | 2100 |
| Geographic scope | |
| Sea area(s) |
|
| Location | |
| Coordinate reference | |
| Z Reference | |
| Additional information | |
| Other info | |
| Webservice | |
| Link file |