Comparability between box-corer and epibenthic-sledge data on higher taxon level: A case study based on deep-sea samples from the NW Pacific

摘要

The vastness and difficult accessibility of the deep sea, together with the previous thought that it harboured no life, has hampered research in this environment until the nineteenth century, when the exponential discovery of new species was rapidly combined with the development of new gears to explore the deep-sea fauna. Nevertheless, apparatuses developed in the twentieth century are still used to sample benthic organisms nowadays. Among them, box corers (BC) and epibenthic sledges (EBS) are the most common ones applied in macrofaunal studies. In this study, the comparability between these two gears from samples collected at the deep NW Pacific was tested by means of non-permutational ANOVA. Using uni- and multivariate analyses, we tested whether significant differences could be found between gears using the univariate indices: high taxa richness, total abundance, evenness, estimated number of taxa, and Shannon diversity; and the multivariate indices: total abundance, presence|absence, and relative abundance. Results indicate that both gears can be comparable when evenness, estimated number of taxa, and Shannon diversity (univariate indices) are used, as well as relative abundances based on the multivariate data matrix. This means that data derived from the EBS can be used in a quantitative way, for e.g. in an ecological context, up to a certain extent. On the other hand, significant differences between BC and EBS were found for total abundance and species richness. This could be a result of the bigger amount of sediment the EBS collects together with a larger sampled area by this gear, consequently leading to a higher amount of organisms and taxa sampled. Moreover, despite the interchangeability between these two gears was possible for some indices at higher taxa level, caution should be taken into account when comparing data for other deep-sea areas and at species level.