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Ecology of bottom ice algae: II. Dynamics, distributions and productivity
In: Journal of Marine Systems. Elsevier: Tokyo; Oxford; New York; Amsterdam. ISSN 0924-7963; e-ISSN 1879-1573
Ook verschenen in:Nihoul, J.C.J.; Djenidi, S. (1991). Ice covered seas and ice edges: Physical, chemical and biological processes and interactions - Proceedings of the 22th International Liège Colloquium on Ocean Hydrodynamics. Journal of Marine Systems, 2. Elsevier Science Publishers: Amsterdam. 520 pp., meer
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| Abstract |
Spring blooms of bottom ice algae are a common feature of landfast congelation ice in polar regions. Because ice algae are usually associated with a substrate, their population dynamics can be followed with considerable confidence. Although ice algal dynamics are closely related to irradiance, their dynamics and distributions are influenced by other abiotic and biotic factors. Ice algal abundance varies horizontally over all scales examined. Factors such as grazing and nutrient availability may contribute to local and geographic differences. Loss terms for most sea ice assemblages are largely unquantified. Ice algal biomass is most concentrated near the ice-water interface in spring.Environmental factors affecting ice algal abundance and productivity are considered here, emphasizing recent results from several well-studied sites. Biomass accumulation, growth rates and productivity have been documented for spring blooms of bottom interstitial and sub-ice assemblages. On an areal basis biomass accumulation in bottom ice assemblages can be comparable with planktonic systems. At low ambient temperatures and irradiances average specific growth rates (≤ 0.25 d−1) and production rates (≤ 1.0 mg C mg Chl−1 h−1) for ice algae are low. Current methods of measuring productivity are compared. Results are consistently low but variable with little systematic difference among them. At present, apparent differences in productivity between bottom ice assemblages in the Arctic and Antarctic, or among different antarctic assemblages, are so confounded by methodological and other sources of variability that no firm differences can be detected. |
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