A high resolution study of the chlorophyll and bacteriochlorophyll pigment distributions in a calcite/gypsum microbial mat

Application of a high resolution high performance liquid chromatography-mass spectrometry method to the study of a microbial mat system has permitted the identification of a greater number of pigments derived from green bacteria than reported in a previous study. Although the green bacteria found in the mat were identified as Chloroflexus-like, bacteriochlorophylls and bacteriophaeophytins c that can be attributed to Chloroflexaceae on the basis of literature reports account for less than 10% of the pigments derived from green bacteria in the mat. Analysis of the bacteriochlorophylls and bacteriophaeophytins c and d using atmospheric pressure chemical ionisation-liquid chromatography-tandem mass spectrometry reveals complex depth profiles, signalling inputs from a number of organisms. The pigment compositions provide evidence for green bacteria living in close proximity to the living cyanobacterial mat. Depth profiles of pigments derived from green, purple and cyanobacteria indicate that the remnants of mats present in the deeper part of the section contain a record dominated by signatures from anoxygenic photoautotrophs.

A novel sedimentary chlorin: structural evidence for a chlorophyll origin for aetioporphyrins

A novel sedimentary transformation product of chlorophyll, purpurin-7 phytyl ester, has been identified by atmo- spheric pressure chemical ionisation liquid chromatography mass-spectrometry in sediments from Lake Baikal, Russia, Loch Ness and Priest Pot, UK. This product of oxidative transformation is an intermediate on the transformation pathway leading to sedimentary aetioporphyrins and its occurrence lends strong support to the view that aetiopor- phyrins derive mainly from precursor chlorophylls.

Estimating Oceanic Primary Production Using Vertical Irradiance and Chlorophyll Profiles from Ocean Gliders in the North Atlantic

An autonomous underwater vehicle (Seaglider) has been used to estimate marine primary production (PP) using a combination of irradiance and fluorescence vertical profiles. This method provides estimates for depth-resolved and temporally evolving PP on fine spatial scales in the absence of ship-based calibrations. We describe techniques to correct for known issues associated with long autonomous deployments such as sensor calibration drift and fluorescence quenching. Comparisons were made between the Seaglider, stable isotope (13C), and satellite estimates of PP. The Seaglider-based PP estimates were comparable to both satellite estimates and stable isotope measurements.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-abased models

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.