Faecal pellet production of copepoda collected at different water depth in the eastern Mediterranean Sea during SES_GR2

The SES_GR2-Mesozooplankton faecal pellet production rates dataset is based on samples taken during August and September 2008 in the Northern Libyan Sea, Southern Aegean Sea and the North-Eastern Aegean Sea. Mesozooplankton is collected by vertical tows within the 0-100 m layer or within the Black sea water body mass layer in the case of the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).

Faecal pellet production of copepoda collected in water depth up to 20 meters in the eastern Mediterranean Sea in March and April 2008 during SES_GR1

The SES_GR1-Mesozooplankton faecal pellet production rates dataset is based on samples taken during April 2008 in the North-Eastern Aegean Sea. Mesozooplankton is collected by vertical tows within the Black sea water body mass layer in the NE Aegean, using a WP-2 200 µm net equipped with a large non-filtering cod-end (10 l). Macrozooplankton organisms are removed using a 2000 µm net. A few unsorted animals (approximately 100) are placed inside several glass beaker of 250 ml filled with GF/F or 0.2 µm Nucleopore filtered seawater and with a 100 µm net placed 1 cm above the beaker bottom. Beakers are then placed in an incubator at natural light and maintaining the in situ temperature. After 1 hour pellets are separated from animals and placed in separated flasks and preserved with formalin. Pellets are counted and measured using an inverted microscope. Animals are scanned and counted using an image analysis system. Carbon- Specific faecal pellet production is calculated from a) faecal pellet production, b) individual carbon: Animals are scanned and their body area is measured using an image analysis system. Body volume is then calculated as an ellipsoid using the major and minor axis of an ellipse of same area as the body. Individual carbon is calculated from a carbon- total body volume of organisms (relationship obtained for the Mediterranean Sea by Alcaraz et al. (2003) divided by the total number of individuals scanned and c) faecal pellet carbon: Faecal pellet length and width is measured using an inverted microscope. Faecal pellet volume is calculated from length and width assuming cylindrical shape. Conversion of faecal pellet volume to carbon is done using values obtained in the Mediterranean from: a) faecal pellet density 1,29 g cm**3 (or pg µm**3) from Komar et al. (1981); b) faecal pellet DW/WW=0,23 from Elder and Fowler (1977) and c) faecal pellet C%DW=25,5 Marty et al. (1994).

Corals, substrate and physical oceanography during the expedition Comau2012, Northern Chilean Patagonia

Cold-water corals provide an important habitat for a rich fauna along the continental margins and slopes. Although these azooxanthellate corals are considered particularly sensitive to ocean acidification, their responses to natural variations in pH and aragonite saturation are largely unknown due to the difficulty of studying their ecology in deep waters. Previous SCUBA investigations have shown an exceptionally shallow population of the cold-water coral Desmophyllum dianthus in near-surface waters of Comau Fjord, a stratified 480 m deep basin in northern Chilean Patagonia with suboxic deep waters. Here, we use a remotely operated vehicle to quantitatively investigate the distribution of D. dianthus and its physico-chemical drivers in so far uncharted naturally acidified waters. Remarkably, D. dianthus was ubiquitous throughout the fjord, but particularly abundant between 20 and 280 m depth in a pH range of 8.4 to 7.4. The persistence of individuals in aragonite-undersaturated waters suggests that present-day D. dianthus in Comau Fjord may show pre-acclimation or pre-adaptation to conditions of ocean acidification predicted to reach over 70% of the known deep-sea coral locations by the end of the century.

Time series of ZOOSCAN images and results of zooplankton samples at Villefranche from 1966 to 2003

ZooScan with ZooProcess and Plankton Identifier (PkID) software is an integrated analysis system for acquisition and classification of digital zooplankton images from preserved zooplankton samples. Zooplankton samples are digitized by the ZooScan and processed by ZooProcess and PkID in order to detect, enumerate, measure and classify the digitized objects. Here we present a semi-automatic approach that entails automated classification of images followed by manual validation, which allows rapid and accurate classification of zooplankton and abiotic objects. We demonstrate this approach with a biweekly zooplankton time series from the Bay of Villefranche-sur-mer, France. The classification approach proposed here provides a practical compromise between a fully automatic method with varying degrees of bias and a manual but accurate classification of zooplankton. We also evaluate the appropriate number of images to include in digital learning sets and compare the accuracy of six classification algorithms. We evaluate the accuracy of the ZooScan for automated measurements of body size and present relationships between machine measures of size and C and N content of selected zooplankton taxa. We demonstrate that the ZooScan system can produce useful measures of zooplankton abundance, biomass and size spectra, for a variety of ecological studies.