Computer vision enables short- and long-term analysis of Lophelia pertusa polyp behaviour and colour from an underwater observatory.

An array of sensors, including an HD camera mounted on a Fixed Underwater Observatory (FUO) were used to monitor a cold-water coral (Lophelia pertusa) reef in the Lofoten-Vesterålen area from April to November 2015. Image processing and deep learning enabled extraction of time series describing changes in coral colour and polyp activity (feeding). The image data was analysed together with data from the other sensors from the same period, to provide new insights into the short- and long-term dynamics in polyp features. The results indicate that diurnal variations and tidal current influenced polyp activity, by controlling the food supply. On a longer time-scale, the coral's tissue colour changed from white in the spring to slightly red during the summer months, which can be explained by a seasonal change in food supply. Our work shows, that using an effective integrative computational approach, the image time series is a new and rich source of information to understand and monitor the dynamics in underwater environments due to the high temporal resolution and coverage enabled with FUOs.

Comparison of gas chromatography/isotope ratio mass spectrometry and liquid chromatography/isotope ratio mass spectrometry for carbon stable-isotope analysis of carbohydrates.

RATIONALE: We compared gas chromatography/isotope ratio mass spectrometry (GC/IRMS) and liquid chromatography/isotope ratio mass spectrometry (LC/IRMS) for the measurement of δ(13)C values in carbohydrates. Contrary to GC/IRMS, no derivatisation is needed for LC/IRMS analysis of carbohydrates. Hence, although LC/IRMS is expected to be more accurate and precise, no direct comparison has been reported. METHODS: GC/IRMS with the aldonitrile penta-acetate (ANPA) derivatisation method was compared with LC/IRMS without derivatisation. A large number of glucose standards and a variety of natural samples were analysed for five neutral carbohydrates at natural abundance as well as at (13)C-enriched levels. Gas chromatography/chemical ionisation mass spectrometry (GC/CIMS) was applied to check for incomplete derivatisation of the carbohydrate, which would impair the accuracy of the GC/IRMS method. RESULTS: The LC/IRMS technique provided excellent precision (±0.08‰ and ±3.1‰ at natural abundance and enrichment levels, respectively) for the glucose standards and this technique proved to be superior to GC/IRMS (±0.62‰ and ±19.8‰ at natural abundance and enrichment levels, respectively). For GC/IRMS measurements the derivatisation correction and the conversion of carbohydrates into CO2 had a considerable effect on the measured δ(13)C values. However, we did not find any significant differences in the accuracy of the two techniques over the full range of natural δ(13)C abundances and (13)C-labelled glucose. The difference in the performance of GC/IRMS and LC/IRMS diminished when the δ(13)C values were measured in natural samples, because the chromatographic performance and background correction became critical factors, particularly for LC/IRMS. The derivatisation of carbohydrates for the GC/IRMS method was complete. CONCLUSIONS: Although both LC/IRMS and GC/IRMS are reliable techniques for compound-specific stable carbon isotope analysis of carbohydrates (provided that derivatisation is complete and the calibration requirements are met), LC/IRMS is the technique of choice. The reasons for this are the improved precision, simpler sample preparation, and straightforward isotopic calibration.