Mapping the macrofauna communities of Portugal's continental shelf north of Nazaré Canyon using Community Distribution Modelling (CDM)

Estuarine, Coastal and Shelf Science(2022)

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摘要
The conservation and sustainable use of marine ecosystems is a worldwide concern, and to achieve it, managers and decision-makers require detailed environmental and biological information, namely supplied as maps of the seafloor. This work was conducted on Portugal's continental shelf located north of Nazaré Canyon. Sediment data was obtained in 226 grab samples, of which 169 were used to study the macroinvertebrate benthic communities. Acoustic transects were run for more than 2500 Km to obtain depth and maps of environmental variables were produced through spatial interpolation of the point data. A multivariate analysis of the biological data identified seven benthic communities, characterized by different species and environmental conditions (i.e., sediment type and depth). The spatial distribution of each biological community was modelled as the response to environmental variables using generalized linear models with a binomial distribution. Depth was the variable more often significantly related to the distribution of the benthic communities, selected in 5 of the 7 Community Distribution Models (CDM). Using the CDM expressions and maps of the environmental variables, probability maps were produced for the distribution of each community. Their combination allowed to obtain a final map of the most probable benthic communities throughout the study area, showing a high agreement (81%) between the observed and the predicted distributions. The maps produced in this study are valuable tools for the decision-making process involved in the management of the marine environment and their resources, for instance to classify these habitats according to the European nature information system (EUNIS) and in the scope of the Marine Strategy Framework Directive.
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关键词
Northeast Atlantic,Marine soft-sediment habitats,Benthic macroinvertebrate,Spatial interpolation,Regression models
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