Qualitative and quantitative studies of benthic infaunal communities in British Columbia coastal waters
Date
2018-06-28
Authors
Burd, Brenda Jean
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Abstract
In this study, I examine and compare benthic infaunal and
environmental factors from the British Columbia coastline on a broader
geographic and temporal scale than has been attempted in this area. The
hypothesis that large and small macrofauna are distributed differently
under different environmental conditions was examined by comparing
results based on numerical abundance and biomass-weighted abundance
data. Both data methods have drawbacks, but their combined use
nullified the primary bias of each. I concluded that the combined
results from numerical and biomass-weighted data provided a clearer
picture of faunal and environmental interactions than either result
alone.
The faunal data were analysed using cluster analysis in
conjunction with an inferential bootstrap method called Sigtree, which
places significance values on the cluster groupings. The multivariate
results from both faunal data formats were compared to each other using
a second non-parametric bootstrap method, Comtre2. Finally the two
faunal dendrograms were inferentially compared with a dendrogram derived
from environmental data, using the method Comtre1. The above analyses
were conducted independently on the two faunal datasets from each survey
area, then for data from all survey areas combined. I have included a
discussion of the potential effects of sampling parameters on the
results of inferential analyses, power and overall significance of the
tests, and suggested an optimum approach for future studies.
The Sigtree analyses of significant cluster groups was the most
valuable of the three inferential methods used, and was least affected
by the multiple comparisons problem. The major drawback of this and other bootstrap methods is their dependence on the raw data being
manipulated. Despite the limitations of the method, the results of
Sigtree analyses were believable and readily interpretable. The Sigtree
analyses of the combined data for all survey areas indicated that most
stations within a given survey area remained grouped together.
Exceptions illustrated the consistency in faunal composition (including
impoverishment) which may be expected for areas with similar
environmental conditions, regardless of the geographic distance between
stations. Results often revealed very different patterns in the
distribution of small versus large fauna, particularly in disturbed
areas such as Alice Arm and Vancouver Harbour, and in cases where only
the small fauna or only the large fauna were impoverished. However, the
Comtre2 comparison of results for the two data management approaches
lacked sufficient discrimination to distinguish between the distribution
patterns of large and small fauna for any survey area except Alice Arm.
As well, the multiple comparisons problem was serious for Comtre2 for
sets of data with many stations.
The Comtre1 results suggested that the distribution patterns of
large fauna were more closely predicted than the distribution of small
fauna, by the environmental factors measured. I concluded that Comtre1
was of limited use for the environmental data available (sediment
particle size, depth and location) for all survey areas, but was of
considerable value for interpreting relationships between complex
sediment chemistry factors and the distribution of large fauna. The
Comtre1 results were considered unreliable for analyses with many
stations, because of the multiple comparisons problem.
Using the methods outlined in this study, comparisons of mactofaune structure from different habitat types and geographic locations were feasible
and informative even though sampling conditions were variable. The data
management approach used to examine patterns in different size components of
the assemblage could be expanded to focus in greater detail on size-related structural complexities within benthic communities.
Description
Keywords
Benthos, British Columbia, Marine animals, Ecology, British Columbia