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            <gco:CharacterString>The HABMAP project used a multi-parameter predictive modelling tool to develop seabed biotope maps for the Southern Irish Sea. Existing biological and physical datasets across the whole study area were collated within a Geographical Information System (GIS) and used to construct a rule-based biotope prediction model. Data were collated for the following physical parameters: bathymetry, sediment type, temperature, wave stress, tide stress, salinity and light attenuation. (NB Bedform data was not included in the extension project modelling work as it was found to be unreliable during the original project). These data were combined in GIS to produce a single map with many cells, each with a value for each of the physical parameters. Data was also collated for seabed biotopes and these points were overlain onto the physical data layer, allowing the relationships between each biotope and the physical environment to be determined. Preference ranges of each physical parameter were then identified for each biotope, leading to the development of predictive rules that could identify other cells with the same physical data ranges. This meant that maps could be produced showing the recorded and predicted distributions for each biotope. A final map was produced which listed all recorded and predicted biotopes in each cell, in order of confidence.</gco:CharacterString>
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                <gmd:LocalisedCharacterString locale="#EN">The HABMAP project used a multi-parameter predictive modelling tool to develop seabed biotope maps for the Southern Irish Sea. Existing biological and physical datasets across the whole study area were collated within a Geographical Information System (GIS) and used to construct a rule-based biotope prediction model. Data were collated for the following physical parameters: bathymetry, sediment type, temperature, wave stress, tide stress, salinity and light attenuation. (NB Bedform data was not included in the extension project modelling work as it was found to be unreliable during the original project). These data were combined in GIS to produce a single map with many cells, each with a value for each of the physical parameters. Data was also collated for seabed biotopes and these points were overlain onto the physical data layer, allowing the relationships between each biotope and the physical environment to be determined. Preference ranges of each physical parameter were then identified for each biotope, leading to the development of predictive rules that could identify other cells with the same physical data ranges. This meant that maps could be produced showing the recorded and predicted distributions for each biotope. A final map was produced which listed all recorded and predicted biotopes in each cell, in order of confidence.</gmd:LocalisedCharacterString>
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            </gmd:PT_FreeText>
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