Spatio-temporal mosaic of the phytoplankton spring bloom in the open Baltic Sea in 1986

Abstract

The spatio-temporal variability of the phytoplankton spring bloom in the open Baltic Sea during an international joint study (PEX'86) is described in relation to the physical and chemical environment. Simultaneous participation of 14 research vessels enabled highly synoptic sampling of the study area of 20 X 40 n mile. Onset of the bloom was controlled by mesoscale hydrodynamic features -a pair of cyclonic and anticyclonic eddies; water masses with different salinities. The eddies supported an exceptionally high amount of chlorophyll (> 700 mg m-' in the cyclonic eddy). The temporal development of the bloom was different in each of the mesoscale features. Chlorophyll levels in the eddies started to decrease due to se&mentation before formation of the thermocline and the depletion of inorganic nutrients. Variability of the chlorophyll distribution was highest just before the peak in the spatially averaged concentrahon was attained.

Spatial and temporal variability of a dinoflagellate-cyanobacterium community under a complex hydrodynamical influence:a case study at the entrance to the Gulf of Finland

“…Satellite irnages and several ship-borne investigations have shown that meso-scale patchiness of the surface layer of the Baltic Sea is pronounced both in physical (Kahru et al 1995) and in biological , Moisander et al 1997 fields. Several studies carried out during phytoplankton blooms have revealed a typical patch size of phytoplankton ca 10 to 40 km (Kahru et al 1991, Moisander et al 1997, a size that corresponds well with meso-scale hydrophysical structures. In these studies, a good correlation was observed between the spatial distnbution of microphytoplankton species and water masses.…”

“…We conclude that, before the study penod, grazing by copepods and tintinnids was insufficient to suppress the bloorn development of H. tnquetra. Earlier studies carned out in the Baltic Sea during the phytoplankton spnng bloom (Kahru et al 1991) and late summer bloom , Moisander et al 1997 have revealed a good correlation between species abundance and water masses. The results were based on measurements at sparse Stations on the transects so that the horizontal patchiness was poorly resolved.…”

Methods of sampling and analysis and our concepts of ocean dynamics

“…In order to make intercomparisons between the sampling and analysis systems as a whole, we would require that the research vessels involved in the intercomparisons draw samples simultaneously from a homogeneous body of water. It is difficult to imagine where one would find a body of water large enough and homogeneous enough for such an exercise, given any reasonably large international program; certainly much recent work has suggested that patchiness in many attributes and at many scales extends throughout the water column (Lehman and Scavia, 1982;Atkinson et al, 1987;Owen, 1989;Kahru et al, 1990;Nero et al, 1990;Duarte and Vaqué, 1992;Taylor and Howes, 1994). At least at this time it does not seem likely that we will be able to separate variability due to the sampling method from that inherent in the universe sampled, as long as we are limited to taking samples at discrete intervals in time and space.…”

“…The PEX86 expedition, involving fourteen ships, attempted to determine the dimensions of patchiness in the Baltic spring bloom. This turned out to be below the resolution of a 2-mile grid (Kahru et al, 1990). In the long run, the decision on the fineness of the sampling grid will probably come from a compromise between heart's desire, computer capability for data handling, and economics.…”

Effect of sampling frequency on detection of natural variability in phytoplankton: unattended high-frequency measurements on board ferries in the Baltic Sea

“…The problems in obtaining representative phytoplankton data sets have been known for decades (e.g., Hardy, 1955;Harris, 1980). In phytoplankton dynamics there is a hierarchy of processes operating at different temporal and spatial scales, which results in patchiness, in both time and space, in respect of biomass and species composition (e.g., Harris, 1980;Kahru et al, 1986Kahru et al, , 1990Leppänen et al, 1994a, b). In the Baltic Sea, the main factors affecting the scales of primary production are strong seasonality, specific overall hydrophysical features (water exchange, topographical characteristics), and local hydrodynamic variability (upwelling, eddy formation;Nõ mmann, 1990;.…”