Temporal variability of phytoplankton community structure based on pigment analysis
Temporal variability of phytoplankton community structure based on pigment analysis
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DOI:
10.4319/lo.1993.38.7.1420
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发表时间:
1993-11
影响因子:
4.5
通讯作者:
Ricardo M Letelier;R. Bidigare;Dale V. Hebel;M. Ondrusek;C. D. Winn;D. Karl
中科院分区:
文献类型:
--
作者:
Ricardo M Letelier;R. Bidigare;Dale V. Hebel;M. Ondrusek;C. D. Winn;D. Karl
Algal chlorophyll and carotenoid distributions were measured periodically in the euphotic zone of Sta. ALOHA (22”45’N, 158”OO’W) between February 1989 and October 1991 to document the variability in phytoplankton abundance and composition. The annual mean depth-integrated (O-200 db) concentration of Chl a displayed significant interannual variability. Seasonal patterns in Chl a concentration were found to be depth-dependent. Elevated Chl a in the mixed layer is the result of photoadaptation as the mixed layer deepens in winter. Increases in Chl a at the deep chlorophyll maximum layer (DCML) in spring are explained by increased nutrient availability caused by a deepening of the DCML relative to the bg = 24.25 density surface. An algorithm based on the ratios of Chl a to diagnostic pigments present in specific algal taxa was used to estimate the contribution to total Chl a by the major algal groups represented within the DCML. Results indicate the presence of a phytoplankton community at the DCML with the following mean composition: Prochlorococcus spp. (39%), cyanobacteria (24%), prymnesiophytes (22%),and chrysophytes (13%). No single taxon is responsible for the springtime increase in Chl a observed in this habitat. Results from size fractionation and normal-phase high performance liquid chromatography confirm that Prochforococcus spp. are the principal contributors of Chl a to the DCML. The amplitude of the seasonal cycle in phytoplankton production and biomass is thought to be latitude-dependent with the smallest variations at low latitudes (Cushing 1959; Heinrich 1962; Sournia 1969). Consequently, mid- and low-latitude oceanic regions require robust sampling schedules and precise analyses to discern seasonal fluctuations in phytoplankton biomass and production from variability produced by stochastic events.