Processing Argo oxygen data at the DAC level cookbook

This document does NOT address the issue of oxygen data quality control (either real-time or delayed mode). As a preliminary step towards that goal, this document seeks to ensure that all countries deploying floats equipped with oxygen sensors document the data and metadata related to these floats properly. We produced this document in response to action item 14 from the AST-10 meeting in Hangzhou (March 22-23, 2009). Action item 14: Denis Gilbert to work with Taiyo Kobayashi and Virginie Thierry to ensure DACs are processing oxygen data according to recommendations. If the recommendations contained herein are followed, we will end up with a more uniform set of oxygen data within the Argo data system, allowing users to begin analysing not only their own oxygen data, but also those of others, in the true spirit of Argo data sharing. Indications provided in this document are valid as of the date of writing this document. It is very likely that changes in sensors, calibrations and conversions equations will occur in the future. Please contact V. Thierry (vthierry@ifremer.fr) for any inconsistencies or missing information. A dedicated webpage on the Argo Data Management website (www) contains all information regarding Argo oxygen data management : current and previous version of this cookbook, oxygen sensor manuals, calibration sheet examples, examples of matlab code to process oxygen data, test data, etc..

First insight into personality traits in Northern pike (Esox lucius) larvae: a basis for behavioural studies of early life stages

Personality traits have been studied for some decades in fish species. Yet, most often, studies focused on juveniles or adults. Thus, very few studies tried to demonstrate that traits could also be found in fish larvae. In this study, we aimed at identifying personality traits in Northern pike (Exos lucius) larvae. Twenty first-feeding larvae aged 21 days post hatch (16.1 +/− 0.4 mm in total length, mean +/− SD) were used to establish personality traits with two tests: a maze and a novel object. These tests are generally used for evaluating the activity and exploration of specimens as well as their activity and boldness, respectively. The same Northern pike twenty larvae were challenged in the two tests. Their performances were measured by their activity, their exploratory behaviour and the time spent in the different arms of the maze or near the novel object. Then, we used principal component analysis (PCA) and a hierarchical ascendant classification (HAC) for analysis of each data set separately. Finally, we used PCA reduction for the maze test data to analyse the relationship between a synthetic behavioural index (PCA1) and morphometric variables. Within each test, larvae could be divided in two sub groups, which exhibited different behavioural traits, qualified as bold (n = 7 for the maze test and n = 13 for the novel object test) or shy (n = 9 for the maze test and n = 11 for the novel object test). Nevertheless, in both tests, there was a continuum of boldness/shyness. Besides, some larvae were classified differently between the two tests but 40 % of the larvae showed cross context consistency and could be qualified as bold and/or proactive individuals. This study showed that it is possible to identify personality traits of very young fish larvae of a freshwater fish species.