@inproceedings{fdi:010078276,
  title = {{C}haracterization of micronektonic spatial structure using ecosystemic acoustics descriptors applied in three {A}tlantic {A}frican {L}arge {M}arine {E}cosystems [r{\'e}sum{\'e} de poster]},
  author = {{M}ouget, {A}nne and {B}ehagle, {N}olwenn and {P}errot, {Y}annick and {T}iedemann, {M}. and {M}igayrou, {C}. and {S}arr{\'e}, {A}. and {U}anivi, {U}. and {R}odriguez, {E}. and {J}eyid, {M}.{A}. and {E}l {A}youbi, {S}. and {K}ouassi, {A}.{M}. and {B}erne, {A}. and {M}bye, {E}.{M}. and {B}rehmer, {P}atrice},
  editor = {},
  language = {{ENG}},
  abstract = {{U}sing the segmentation algorithm within {M}atecho ({P}errot et al., 2018) we are able to deliver 15 descriptors to characterize the acoustic micronektonic layers in the water column. {E}ven if the species composition is not known, these descriptors which are obtained using the same methodology allow for comparison between ecosystems and to study inter-annual variability. {S}ome of these descriptors are new and others are based on the ones usually used to characterize pelagic fish schools using echointegration per shoal ({W}eill et al., 1993). {I}n this work we will focus on the new ones and show some application cases in the three {A}tlantic {A}frican {L}arge {M}arine {E}cosystems, to monitor potential perturbations due to global change. {A}ll layer descriptors are estimated per layer and per elementary sampling unit of 0.1 nautical miles ({ESU}) with an accuracy of 1 meter depth. {I}n this study we present four classes of descriptors: spatial (e.g. altitude, mean depth, minimal depth); morphological (e.g. width, {ESU} number, filling rate of water column); acoustic (e.g. mean volume backscattering strength {S}v (d{B})) and the layer number per {ESU}. {I}n this study we focus on the original descriptors: (i) {F}illing rate of the water column (%): this indicator is based on the calculation of the width of the micronektonic layer vs. the local bottom depth. (ii) {F}illing rate contribution of first layer (%): this indicator shows the contribution of the first layer (the closest layer of surface) in the global filling rate. {I}t is computed by dividing the filling rate of first layer by the filling rate of all layers. (iii) {N}umber of layers: this indicator is calculated for each {ESU}, giving the number of layers in this water column. {T}he descriptors have been computed over more than 1 million of {ESU}s, 992 737 in the {CCLME}, 166 183 in the {GCLME} and 462 807 in the {BCLME}. {S}uch descriptors allow classification of micronekton layers and appear relevant to monitor changes in the ecosystem. {N}ext step will be to use multifrequency or even wide-band data to improve the quality of descriptors. {T}hey were efficiently applied to study diel vertical behaviour as well as the effect of water mass characteristics on the spatial structure of the layers. {I}n future applications it should help in the classification of the layers per functional group as well as to improve our knowledge on ecosystem organization and functioning.},
  keywords = {{AFRIQUE} {DE} {L}'{OUEST} ; {ATLANTIQUE}},
  numero = {},
  pages = {146--147},
  booktitle = {{I}nternational conference {ICAWA} 2017 and 2018 : extended book of abstract : the {AWA} project : ecosystem approach to the management of fisheries and the marine environment in {W}est {A}frican waters},
  year = {2019},
  ISBN = {978-9553602-0-06},
  URL = {https://www.documentation.ird.fr/hor/fdi:010078276},
}