Assessing habitat specific fish assemblages in estuaries along the Portuguese coast

Estuaries consist of a complex mosaic of many distinctive habitat types. Each one may perform several vital functions in the functioning of the whole system and although its value is often based on species density patterns, functional relationships between them also need to be examined. Spatial patterns of estuarine habitat use by fish assemblages were determined within and among nine estuarine systems along the Portuguese coast. Fish sampling surveys were conducted in May and July 2006, covering the full estuarine gradient. All the different habitat types were sampled in each estuarine system with a beam trawl. Estuarine habitats were mapped with GIS and habitat specific associated fish assemblages were described based on several community descriptors, namely richness (S), evenness (J′), and diversity (H′) and on an ecological and feeding guilds classification. A canonical correspondence analysis was performed to evaluate the relationship between estuarine habitats and fish assemblages in this set of estuaries. The intertidal and subtidal soft substratum habitats corresponded to the largest areas in all the estuaries and presented higher number of species. Nevertheless the highest mean density of fish was registered at the salt marsh habitat, which occupies smaller areas within each estuary. The fact that small vegetated habitats like salt marsh and seagrass supported high densities of fish may be an indication of the important role these habitats play in the whole system functioning. Differences in fish assemblage structure were found with latitude and between habitats amongst and within estuaries. Some of the fish species were found to be particularly associated with certain habitat types, which might indicate that each estuarine habitat may be related with specific fish assemblages regardless the estuary. The present work provides valuable information for management by identifying the most important habitats for species conservation and predicting the possible effects of habitat disturbance or destruction, namely by climate change and anthropogenic pressures.