Seasonal Distributions of Satellite-Measured Phytoplankton Pigment Concentration Along the Chilean Coast

Five years (1979-1983) of Coastal Zone Color Scanner satellite ocean color data are used to examine seasonal patterns of phytoplankton pigment concentration along the Chilean coast from 20 degrees S to 45 degrees S. Four kilometer resolution, 2-4 day composites document the presence of filaments of elevated pigment concentration extending offshore throughout the study area, with maximum offshore extension at higher latitudes. In three years, 1979, 1981, and 1983, sufficient data exist in monthly composites to allow recreation of portions of the seasonal cycle. Data in 1979 are the most complete. Near-shore concentrations and cross-shelf extension of pigment concentrations in 1979 are maximum in austral winter throughout the study area and minimum in summer. Available data from 1981 and 1983 are consistent with this temporal pattern but with concentrations approximately double those of 1979. Seasonal, spatial patterns within 10 km of shore and 50 km offshore indicate a latitudinal discontinuity both in absolute concentration and in the magnitude of the seasonal cycle at approximately 33 degrees S in both 1979 and in the climatological time series. The discontinuity is strongest ill fall-winter and weakest in summer. South of this latitude, concentrations are relatively high (2-3 mg m(-3) in 1979), a strong seasonal cycle is present, and patterns 50 km offshore are correlated with those within 10 km of shore. North of 33 degrees S, concentrations are < 1.5 mg m(-3) (in 1979), and the seasonal cycle within 10 km of shore is present but much weaker and less obviously correlated with that 50 km offshore. The seasonal cycle of pigment concentrations is 180 degrees out of phase with monthly averaged upwelling favorable winds. Noncoincident Pathfinder sea surface temperature data show that over most latitudes, coastal low surface temperatures lag wind forcing by 1-2 months, but these too are out of phase with the pigment seasonal cycle. These data point to control of pigment patterns along the Chilean coast by the interaction of upwelling with circulation patterns unconnected to local wind forcing.

Satellite-Detected Fluorescence Reveals Global Physiology of Ocean Phytoplankton

Phytoplankton photosynthesis links global ocean biology and climate-driven fluctuations in the physical environment. These interactions are largely expressed through changes in phytoplankton physiology, but physiological status has proven extremely challenging to characterize globally. Phytoplankton fluorescence does provide a rich source of physiological information long exploited in laboratory and field studies, and is now observed from space. Here we evaluate the physiological underpinnings of global variations in satellite-based phytoplankton chlorophyll fluorescence. The three dominant factors influencing fluorescence distributions are chlorophyll concentration, pigment packaging effects on light absorption, and light-dependent energy-quenching processes. After accounting for these three factors, resultant global distributions of quenching-corrected fluorescence quantum yields reveal a striking consistency with anticipated patterns of iron availability. High fluorescence quantum yields are typically found in low iron waters, while low quantum yields dominate regions where other environmental factors are most limiting to phytoplankton growth. Specific properties of photosynthetic membranes are discussed that provide a mechanistic view linking iron stress to satellite-detected fluorescence. Our results present satellite-based fluorescence as a valuable tool for evaluating nutrient stress predictions in ocean ecosystem models and give the first synoptic observational evidence that iron plays an important role in seasonal phytoplankton dynamics of the Indian Ocean. Satellite fluorescence may also provide a path for monitoring climate-phytoplankton physiology interactions and improving descriptions of phytoplankton light use efficiencies in ocean productivity models.