@inproceedings{fdi:010089466,
  title = {{A} bi-frequency discrimination method of copepods in the {S}enegalese coast [r{\'e}sum{\'e}]},
  author = {{D}iogoul, {N}. and {B}rehmer, {P}atrice and {P}errot, {Y}annick and {R}odrigues, {E}.{R}. and {T}hiam, {A}. and {E}l {A}youbi, {S}. and {M}ouget, {A}. and {S}arr{\'e}, {A}. and {L}ebourges {D}haussy, {A}nne},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he {C}anary {C}urrent {L}arge {M}arine {E}cosystem ({CCLME}) is one of the most productive marine ecosystem worldwide and is key for food security for numerous {A}frican countries. {N}evertheless, its function remains poorly described and ecosystemic data collection are rare. {C}opepods are the key macrozooplankton group in the {CCLME} but their dynamic, their distribution and even their abundance remain poorly documented. {M}ultinet net data allowed identifying large {C}opepod in {CCLME}. {A}s small pelagic fish assessment acoustics survey were routinely done using 38 and 120 k{H}z frequencies, we used the same frequencies to propose a bi-frequencies inversion method to discriminate {C}opepod. {W}e identified copepod backscatter using differences in volume backscat-tering strength ({S}v). {A} close significant relationship were found between the size values of {C}ope-pod from multinet samples with those calculated by the acoustic highpass model. {T}he correlation between copepod abundance and corresponding {S}v were positive. {T}his work showed that 38-120 k{H}z frequency can be used on {C}opepod and thus open the way to retrospective analysis in the {CCLME}. {T}hese results were important to better understand marine ecosystem, and constitute a first step for {C}opepod biomass estimation in the context of ecosystemic approach of small pelagic fish management and climate change.},
  keywords = {{ATLANTIQUE} ; {SENEGAL} ; {CANARIES} {COURANT} {MARIN} ; {AFRIQUE} {DU} {NORD} {OUEST}},
  volume = {4},
  numero = {54},
  pages = {41},
  booktitle = {{W}orking group of fisheries acoustics, science and technology ({WGFAST})},
  year = {2022},
  ISSN = {2618-1371},
  URL = {https://www.documentation.ird.fr/hor/fdi:010089466},
}