High frequency mesozooplankton monitoring: Can imaging systems and automated sample analysis help us describe and interpret changes in zooplankton community composition and size structure — An example from a coastal site
|Author(s)||Romagnan Jean-Baptiste1, 5, Aldamman Lama2, Gasparini Stephane1, 2, Nival Paul1, 2, Aubert Anais4, Jamet Jean Louis3, Stemmann Lars1, 2|
|Affiliation(s)||1 : Univ Paris 06, Univ Paris 04, UMR 7093, LOV,Observ Oceanol, F-06230 Villefranche Sur Mer, France.
2 : CNRS, UMR 7093, Observ Oceanol, LOV, F-06230 Villefranche Sur Mer, France.
3 : Univ Toulon & Var, Lab EBMA PROTEE EA 3819, BP 20132, F-83957 La Garde, France.
4 : Aix Marseille Univ, UM110, CNRS INSU, IRD,Mediterranean Inst Oceanog, F-13288 Marseille 09, France.
5 : IFREMER, Unite Ecol & Modele Halieut, BP 21105, F-44311 Nantes 03, France.
|Source||Journal Of Marine Systems (0924-7963) (Elsevier Science Bv), 2016-10 , Vol. 162 , P. 18-28|
|WOS© Times Cited||4|
|Note||SI : Progress in marine science supported by European joint coastal observation systems: The JERICO-RI research infrastructure|
|Keyword(s)||Mesozooplankton, Copepod, Size distributions, High frequency, Automatic classification, Zooscan, MSFD|
|Abstract||The present work aims to show that high throughput imaging systems can be useful to estimate mesozooplankton community size and taxonomic descriptors that can be the base for consistent large scale monitoring of plankton communities. Such monitoring is required by the European Marine Strategy Framework Directive (MSFD) in order to ensure the Good Environmental Status (GES) of European coastal and offshore marine ecosystems. Time and cost-effective, automatic, techniques are of high interest in this context. An imaging-based protocol has been applied to a high frequency time series (every second day between April 2003 to April 2004 on average) of zooplankton obtained in a coastal site of the NW Mediterranean Sea, Villefranche Bay. One hundred eighty four mesozooplankton net collected samples were analysed with a Zooscan and an associated semi-automatic classification technique. The constitution of a learning set designed to maximize copepod identification with more than 10,000 objects enabled the automatic sorting of copepods with an accuracy of 91% (true positives) and a contamination of 14% (false positives). Twenty seven samples were then chosen from the total copepod time series for detailed visual sorting of copepods after automatic identification. This method enabled the description of the dynamics of two well-known copepod species, Centropages typicus and Temora stylifera, and 7 other taxonomically broader copepod groups, in terms of size, biovolume and abundance–size distributions (size spectra). Also, total copepod size spectra underwent significant changes during the sampling period. These changes could be partially related to changes in the copepod assemblage taxonomic composition and size distributions. This study shows that the use of high throughput imaging systems is of great interest to extract relevant coarse (i.e. total abundance, size structure) and detailed (i.e. selected species dynamics) descriptors of zooplankton dynamics. Innovative zooplankton analyses are therefore proposed and open the way for further development of zooplankton community indicators of changes.|