Towards an understanding of shallow water marine hydroids on Cape Breton coastlines

Abstract

Distributions of North Atlantic marine animals can be expected to shift in response to climate change. Tracking distributions temporally requires an understanding of what species are currently present. Hydroids (Cnidaria, Hydrozoa, Hydroidolina) are conspicuous taxa in the fouling community of shallow water marine environments in Cape Breton, yet surveys of them specific to Cape Breton are sparse and outdated. Consequently, the identity and diversity of local species needs to be clarified. For this study, hydroids were sampled from shallow water environments around Cape Breton and preserved for morphological and molecular analysis. Key morphological features including tentacle anatomy and arrangement, gonophore anatomy, colony structure, and the presence of hydrothecae were examined for family and genus level designations. Sequences were generated for the 16S rRNA barcoding gene and used in BLAST searches to find strong genetic matches on GenBank. Molecular phylogenetic analyses were then performed to refine identifications and determine genetic relationships to other populations. The use of both molecular and morphological analyses has enabled the identification of thirteen taxa to at least genus level and eleven to species level. In total, 14 out of 18 sequences strongly matched GenBank sequences, with similarities ranging from 98%-100%. Two taxa, Podocorynoides minima and Pachycordyle michaeli, do not appear to have been recorded previously in the region. Phylogenetic analysis of genetic connectivity indicated strong genetic relationships with conspecifics in the United States and more distant relationships to conspecifics in Europe. Additionally, it revealed potential cryptic species in Obelia dichotoma. Two genera, Hydractinia and Sarsia, have yet to be identified to species level. Having reliable morphological and molecular databases to identify species, especially for Hydrozoa, is important for monitoring changing distributions over time. This study represents the first stage in the development of a useful dataset for identifying local hydroids using 16S sequence data and accompanying morphological descriptions.