Three sampling methods were used to determine th biomass (chlorophyll ' a' content and algal biovolume) of sediment-associated algae (SAA = epipelon + plocon) at three sites in Delta Marsh, Canada during a two-year period. I hypothesized that the importance of SAA in wetlands has been substantially underestimated due to sampling bias of the standard lens-paper trapping method towards only motile constituents of the assemblage. In addition to the lens paper method, SAA biomass was measured in intact surface sediment cores and in wet slurries aspirated under vacuum from the sediment surface. Sediment slurries yielded the highest Chl 'a' values (15-280 mg/m 2) followed by sediment cores (5-25 mg/m2) whereas estimates using the lens tissue method were consistently <5 mg/m 2. Algal biovolumes followed similar trends. Other determinants of underwater irradiance (macrophyte cover, nutrient concentration, water depth and turbidity) also correlated with SAA chlorophyll. The measured environmental variables could explain 47% of the variation in SAA chlorophyll in 1998 and 54% in 1999. Contrary to my hypotheses, water depth did not affect SAA chlorophyll. Also, SAA chlorophyll did not decrease with increasing macrophyte abundance. I suspect that the species of macrophyte (shape and form) affected the presence of SAA chlorophyll. Furthermore, high sediment and sediment pore-water nutrient concentration did not determine the magnitude of SAA abundance. SAA chlorophyll was negatively related to phytoplankton biomass at the sites. Results of this study have clear implications for food web structure in turbid lacustrine wetlands, where phytoplankton and SAA represent the only food resources for benthic and planktonic herbivores.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:MWU.1993/2501 |
| Date | 01 April 2000 |
| Creators | Bourne, Alexandra L. E. |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | en_US |
| Detected Language | English |
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