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dc.contributor.authorJesús, N. (Nair) de
dc.contributor.authorMatos-Pita, S.S. (Susana Soto) de 
dc.contributor.authorRamil, F. (Francisco)
dc.contributor.authorRamos, A. (Ana)
dc.coverage.temporal2011-2012es_ES
dc.date.accessioned2016-10-13T11:04:18Z
dc.date.issued2016-10-13
dc.identifier.urihttp://hdl.handle.net/10508/10670
dc.description.abstractTwo multidisciplinary surveys aimed to evaluate demersal and pelagic resources were conducted in the framework of the CCLME-FAO project in Northwest African region between October to December 2011 and from May to July 2012 on-board Norwegian R/V Dr. Fridtjof Nansen. A total of 580 stations were sampled with commercial trawl gear in the area spreading between the Gibraltar Strait and the Sierra Leone border. Fifty of these hauls were carried out in Guinea-Bissau waters between 48 and 983 meters depth. In both surveys, the research team of EcoAfrik project, belonging to the Spanish Institute of Oceanography and the University of Vigo, was responsible for the benthos sampling. At all stations the megabentic species, including decapod crustaceans, were sorted at morphospecies level and data of numerical abundance and biomass (wet weight) were collected. When the large volume of material did not allow the sampling of total catch, a subsample was worked, being after estimated the abundances and total biomass by a weighting factor. At every station living specimens of each species were protographed and a representative collection was preserved in 70% ethanol for further taxonomic study. The decapods collection taken in Guinea Bissau, composed by about 400 specimens, has been identified at the University of Vigo, and quantitative data have been analysed to stablish the distribution, composition and structure of the decapod communities. Abundance data (number of individuals) and weight (in kg) per station were standardized to a swept area of 0.1 km2 and matrices of numerical abundance and biomass by species and station were constructed to serve as basis for statistical analysis. Ecological descriptors, such as occurrence (O, presence of the species in the hauls), abundance (N), biomass (B), species richness (S), Shannon-Wiener diversity index (H') and Pielou equitability index (J') were estimated for each station. For the characterization of the assemblages, multivariate analysis (cluster and MDS) were applied to similarity matrix after to transform abundance data by double square root and Bray-Curtis index. Species with low frequency (<10% of the stations) and low abundance (<50 individuals), as well as stations with a single species, were removed to reduce the proportion of zeros in the matrix. The uni- and multivariate analyses were performed using DIVERSE, CLUSTER, MDS, ANOSIM and SIMPER routines of the PRIMER software package v 6 (Plymouth Routines in Multivariate Ecological Research) (Clarke and Gorley 2006). A total of 195,635 individuals with a biomass of 676 kg, belonging to 107 species and 40 families, were collected. Brachyura was the most diverse taxa (37 species), followed by Caridea and Anomura (25 and 21 species). The richest families were Pandalidae (10 spp.), Diogenidae and Paguridae (7 spp.). At specific level, Macropipus rugosus and Dardanus arrosor have been the most frequent species, appearing in 42% and 38% of the stations, respectively. The African spider shrimp, Nematocarcinus africanus, showed the highest abundance (64% of the total) and biomass (37%), followed in both cases by M. rugosus and Munida speciosa. Both plots, dendrogram and MDS (stress value = 0.09), joined the 50 stations in five communities, which distribution seems strongly influenced by the depth: 1) coastal shelf north (<50 m, only 2 stations); 2) shelf (<100 m, 15 st.); 3) deep shelf (100-200 m, 10 st.); 4) upper slope (200-400 m, 7 st. ), 5) middle slope (400-1000 m, 8 st.). In addition to depth, the factor that appear to have greater influence on the assemblages’ segregation was the sediment grain size, especially the high mud proportion and organic matter content (OM). The overall (R = 0.744) and the pairwise value of the ANOSIM test, which oscillated from 0.46 (among the deep shelf and upper slope assemblages) and 1.00 (among the coastal shelf north and the two deepest groups) proved that these five assemblages are statistically different. The SIMPER analysis showed that the five assemblages are quite homogeneous with average similarity inner each group higher than 29%, while dissimilarity between them ranged from 77% to 100%. Holthuispenaeopsis atlantica was the discriminating species of the coastal shelf assemblage (>58.8%), while three species, Macropipus rugosus, Scyllarus caparti and Sternodromia spinirostris were responsible together of the 62% of the similarity inner the shelf group; in the deep shelf assemblage, only two decapods, Pagurus cuanensis and Dardanus arrosor account for the 73% of the similarity. Parapenaeus longirostris typified the upper slope group (53%) and Nematocarcinus africanus, Stereomastis talismani, Aristeus varidens and Sergia robusta contributed to 69% of the similarity in the deepest assemblage. Our results are according to previous studies on decapods biodiversity carried out by Muñoz et al. (2012) in Guinea-Bissau.es_ES
dc.description.sponsorshipMAVA (Contract 12/87 AO C4/2012)es_ES
dc.language.isoenges_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceBenthic database from Norwegian Surveys in Northwest Africaes_ES
dc.subjectBiodiversityes_ES
dc.subjectassemblageses_ES
dc.subjectDecapodaes_ES
dc.subjectGuinea-Bissaues_ES
dc.subjectNorthwest Africaes_ES
dc.titleBiodiversity of Decapoda in Guinea-Bissau waterses_ES
dc.typeconference posteres_ES
dc.identifier.bibliographicCitationXIX Simposio Ibérico de Estudios de Biología Marina. (05/09/2016 - 09/09/2016. Oporto (Portugal)). today. conferenceObject. En: , . today: -*
dc.publisher.centreCentro Oceanográfico de Vigoes_ES
dc.relation.projectIDEcoAfrikes_ES
dc.rights.accessRightsopen accesses_ES
dc.coverage.spatialStudyAtlantic Oceanen_US
dc.coverage.spatialStudyCentral Atlanticen_US
dc.coverage.spatialStudyEastern Central Atlanticen_US
dc.coverage.spatialStudyGuinea watersen_US
dc.coverage.spatialStudyes_ES


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    Atribución-NoComercial-SinDerivadas 3.0 España
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