Abstract: Bio-logging is a methodological approach in which miniature data recording devices are temporarily attached to free-ranging animals to monitor their movement, behaviour and physiology, as well as the physical parameters of the environment directly surrounding the animals, turning them into bio-plateformes. Unsurprisingly bio-logging emerged from marine and polar studies where the monitoring of individuals in these harsh and remote places cannot be done using traditional approaches. Miniaturization and technological advances has meant that the range of species that can be instrumented, as well as the diversity of the questions that can be sought through bio-logging, are expanding fast. New sensors are constantly being developed, pushing further the limits of this field. Instrumented animals deliver information not only on their activities but also on the physical characteristics of the environments they go through. For instance, over the last two decades, loggers attached to deep diving seals have supplemented physical oceanographic measurements with hydrographic profiles from CTD loggers but also with new series of biological measurements. For examples, fluorescence and light sensors provided information on the concentration of phytoplankton in the euphotic layer; miniature echo sounders together with high sensitivity and fast responding light sensor to detect bioluminescence, brought considerable progress in detecting small size particles (>1-2 mm) such as marine snow, zooplankton, but also fish and squids and estimate their abundance.

Abstract: IAGA Workshop on on Geomagnetic Observatory Instruments, Data acquisition and Processing, Dourbes, Belgium, September 2016Magnetotellurics (MT) is a passive geophysical exploration technique which uses time series of natural magnetic and electric fields measured at the ground surface. It is based on the induction of electric currents in the ground by large scale geomagnetic waves. A wide collection of waves is used in MT, from lightning strikes emitted waves to magnetic pulsations induced by the interaction of the sun and the magnetosphere. In this work, we have developed a methodology based on the continuous wavelet transform to process MT data in the period range [1-500] seconds based on the time-frequency characteristics of geomagnetic pulsations. In this period range, geomagnetic pulsations are the preponderant signals. To properly detect geomagnetic pulsations in MT time series, we are generating Fourier surrogates of quiet magnetic time series. Then, by comparison between the distribution of wavelets coefficients of these surrogates and the original signal, we are recovering significant wavelet coefficients associated to geomagnetic pulsations. The magnetic observatories are of primary importance in this framework as their data are used as large-scale reference station for the occurrence of geomagnetic events. We are showing several datasets and their consecutive analysis with regards to improvement brought by magnetic observatories data onto the characterization of MT transfer functions.

Abstract: 15th Alpine Glaciology Meeting, Munich, Germany, 24-25 fev. 2011

Abstract: Reliable population estimates are needed for the conservation management of seabird populations. Failing to account for detection probability in surveys often leads to underestimate population size and, if detection probability varies among surveys, to bias the estimated trends. This is particularly relevant for storm petrels, which are widespread small burrow- or cavity-nesting seabirds, which have low detection probabilities on land and at sea and whose population status and trends are the least known among seabirds. Here, we used the distance sampling method to estimate detection probability and breeding population size of the cavity-nesting Wilson’s Storm Petrel (Oceanites oceanicus) in the Pointe Géologie archipelago, East Antarctica. Detection probability was 0.353 ± 0.053 and the average density of active nests was 45.53 ± 15.63 nests/ha. The proportion of nests occupied by breeders was estimated using an endoscope on a sample of nests and was 0.455 ± 0.053. The breeding population was estimated to be 793 (95% CI 344–1359) breeding pairs in January 2016. We advocate the distance sampling method as a robust approach to estimate abundance of breeding Wilson’s Storm Petrels in Antarctica. Comparison with an earlier survey suggests that the population has decreased over the past 30 years, possibly partly due to a reduction in nesting habitat following the extension of the surface area occupied by penguin colonies.