996 resultados para Spectrophotometer
Resumo:
Pack ice in the Bellingshausen Sea contained moderate to high stocks of microalgal biomass (3-10 mg Chl a/m**2) spanning the range of general sea-ice microalgal microhabitats (e.g., bottom, interior and surface) during the International Polar Year (IPY) Sea Ice Mass Balance in the Antarctic (SIMBA) studies. Measurements of irradiance above and beneath the ice as well as optical properties of the microalgae therein demonstrated that absorption of photosynthetically active radiation (PAR) by particulates (microalgae and detritus) had a substantial influence on attenuation of PAR and irradiance transmission in areas with moderate snow covers (0.2-0.3 m) and more moderate effects in areas with low snow cover. Particulates contributed an estimated 25 to 90% of the attenuation coefficients for the first-year sea ice at wavelengths less than 500 nm. Strong ultraviolet radiation (UVR) absorption by particulates was prevalent in the ice habitats where solar radiation was highest - with absorption coefficients by ice algae often being as large as that of the sea ice. Strong UVR-absorption features were associated with an abundance of dinoflagellates and a general lack of diatoms - perhaps suggesting UVR may be influencing the structure of some parts of the sea-ice microbial communities in the pack ice during spring. We also evaluated the time-varying changes in the spectra of under-ice irradiances in the austral spring and showed dynamics associated with changes that could be attributed to coupled changes in the ice thickness (mass balance) and microalgal biomass. All results are indicative of radiation-induced changes in the absorption properties of the pack ice and highlight the non-linear, time-varying, biophysical interactions operating within the Antarctic pack ice ecosystem.
Resumo:
The relationship between phytoplankton assemblages and the associated optical properties of the water body is important for the further development of algorithms for large-scale remote sensing of phytoplankton biomass and the identification of phytoplankton functional types (PFTs), which are often representative for different biogeochemical export scenarios. Optical in-situ measurements aid in the identification of phytoplankton groups with differing pigment compositions and are widely used to validate remote sensing data. In this study we present results from an interdisciplinary cruise aboard the RV Polarstern along a north-to-south transect in the eastern Atlantic Ocean in November 2008. Phytoplankton community composition was identified using a broad set of in-situ measurements. Water samples from the surface and the depth of maximum chlorophyll concentration were analyzed by high performance liquid chromatography (HPLC), flow cytometry, spectrophotometry and microscopy. Simultaneously, the above- and underwater light field was measured by a set of high spectral resolution (hyperspectral) radiometers. An unsupervised cluster algorithm applied to the measured parameters allowed us to define bio-optical provinces, which we compared to ecological provinces proposed elsewhere in the literature. As could be expected, picophytoplankton was responsible for most of the variability of PFTs in the eastern Atlantic Ocean. Our bio-optical clusters agreed well with established provinces and thus can be used to classify areas of similar biogeography. This method has the potential to become an automated approach where satellite data could be used to identify shifting boundaries of established ecological provinces or to track exceptions from the rule to improve our understanding of the biogeochemical cycles in the ocean.
Resumo:
We used piston cores recovered in the western Bering Sea to reconstruct millennial-scale changes in marine productivity and terrigenous matter supply over the past ~180 kyr. Based on a geochemical multi-proxy approach, our results indicate closely interacting processes controlling marine productivity and terrigenous matter supply comparable to the situation in the Okhotsk Sea. Overall, terrigenous inputs were high, whereas export production was low. Minor increases in marine productivity occurred during intervals of Marine Isotope Stage 5 and interstadials, but pronounced maxima were recorded during interglacials and Termination I. The terrigenous material is suggested to be derived from continental sources on the eastern Bering Sea shelf and to be subsequently transported via sea ice, which is likely to drive changes in surface productivity, terrigenous inputs, and upper-ocean stratification. From our results we propose glacial, deglacial, and interglacial scenarios for environmental change in the Bering Sea. These changes seem to be primarily controlled by insolation and sea-level forcing which affect the strength of atmospheric pressure systems and sea-ice growth. The opening history of the Bering Strait is considered to have had an additional impact. High-resolution core logging data (color b*, XRF scans) strongly correspond to the Dansgaard-Oeschger climate variability registered in the NGRIP ice core and support an atmospheric coupling mechanism of Northern Hemisphere climates.
Resumo:
Underwater spectral reflectance was measured for selected biotic and abiotic coral reef features of Heron Reef from June 25-30, 2006. Spectral reflectance's of 105 different benthic types were obtained in-situ. An Ocean Optics USB2000 spectrometer was deployed in an custom made underwater housing with a 0.5 m fiber-optic probe mounted next to an artificial light source. Spectral readings were collected with the probe(bear fibre) about 5 cm from the target to ensure that the target would fill the field of view of the fiber optic (FOV diameter ~4.4 cm), as well as to reduce the attenuating effect of the intermediate water (Roelfsema et al., 2006). Spectral readings included for one target included: 1 reading of the covered spectral fibre to correct for instrument noise, 1 reading of spectralon panel mounted on divers wrist to measure incident ambient light, and 8 readings of the target. Spectral reflectance was calculated for each target by first subtracting the instrument noise reading from each other reading. The corrected target readings were then divided by the corrected spectralon reading resulting in spectral reflectance of each target reading. An average target spectral reflectance was calculated by averaging the eight individual spectral reflectance's of the target. If an individual target spectral reflectance was visual considered an outlier, it was not included in the average spectral reflectance calculation. See Roelfsema at al. (2006) for additional info on the methodology of underwater spectra collection.