993 resultados para OH- groups


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Past years have seen the development of different approaches to detect phytoplankton groups from space. One of these methods, the PHYSAT one, is empirically based on reflectance anomalies. Despite observations in good agreement with in situ measurements, the underlying theoretical explanation of the method is still missing and needed by the ocean color community as it prevents improvements of the methods and characterization of uncertainties on the inversed products. In this study, radiative transfer simulations are used in addition to in situ measurements to understand the organization of the signals used in PHYSAT. Sensitivity analyses are performed to assess the impact of the variability of the following three parameters on the reflectance anomalies: specific phytoplankton absorption, colored dissolved organic matter absorption, and particles backscattering. While the later parameter explains the largest part of the anomalies variability, results show that each group is generally associated with a specific bio-optical environment which should be considered to improve methods of phytoplankton groups detection.

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Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.

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35S-Methionine and 3H-leucine bioassay tracer experiments were conducted on two meridional transatlantic cruises to assess whether dominant planktonic microorganisms use visible sunlight to enhance uptake of these organic molecules at ambient concentrations. The two numerically dominant groups of oceanic bacterioplankton were Prochlorococcus cyanobacteria and bacteria with low nucleic acid (LNA) content, comprising 60% SAR11-related cells. The results of flow cytometric sorting of labelled bacterioplankton cells showed that when incubated in the light, Prochlorococcus and LNA bacteria increased their uptake of amino acids on average by 50% and 23%, respectively, compared with those incubated in the dark. Amino acid uptake of Synechococcus cyanobacteria was also enhanced by visible light, but bacteria with high nucleic acid content showed no light stimulation. Additionally, differential uptake of the two amino acids by the Prochlorococcus and LNA cells was observed. The populations of these two types of cells on average completely accounted for the determined 22% light enhancement of amino acid uptake by the total bacterioplankton community, suggesting a plausible way of harnessing light energy for selectively transporting scarce nutrients that could explain the numerical dominance of these groups in situ.