Book Description

In a study of foraminiferal distribution in southeast Baffin Bay and the associated environmental parameters, 44 grab samples and 4 cores were analysed for their foraminiferal and sediment contents. Environmental parameters studied were bathymetry, sediment distribution and calcium carbonate content of the sediments. Of the environmental factors considered depth and substrate were found to be most closely associated with foraminiferal distribution, with the sediment type related to the source of sedimentary particles and the prevailing currents. A foraminiferal depth zonation based on the grouping of stations with like faunas was worked out and showed: a shallow water (40-250 metres) diverse calcareous fauna dominated by Cibicides lobatulus and Astrononion gallowayi; an intermediate depth (150-400 metres) arenaceous fauna with Adercotryma glomeratum, Textularia torquata, Trochammina nana and Spiroplectammina biformis dominant; a deep water (300-750 metres), very sparse mixed fauna with calcareous specimens in the majority and Melonis zaandami a common species. In the core samples arenaceous Foraminifera virtually disappear at distances greater than 5-10 cm below the top, probably as a result of mechanical or chemical disintegration soon after burial, caused by compaction of the sediments or the action of annelids or both. Accordingly only calcareous assemblages could be considered for further paleoenvironmental reconstructions. Planktonic foraminiferal tests were rare in the sediments despite being present in the water column in the area. Tests were almost all Globigerina pachyderma and were found in the more calcareous benthonic populations. The inorganic calcium carbonate content of the sediments was found to be closely associated with the calcareous foraminiferal content, indicating a negligible carbonate contribution to the sediments from terrestrial sources. The application of Similarity Analysis and Group Average Sorting techniques gives a grouping of stations with like faunal assemblages similar to that obtained from a visual inspection of the raw data, but these techniques also extract some finer distinctions not otherwise obvious. This indicates that Similarity and Cluster Analyses, and statistical techniques are valuable for studies using larger amounts of more complex data.