@article{fdi:010079038,
  title = {{M}icronekton distribution in the southwest {P}acific ({N}ew {C}aledonia) inferred from shipboard-{ADCP} backscatter data},
  author = {{R}eceveur, {A}. and {K}estenare, {E}lodie and {A}llain, {V}. and {M}{\'e}nard, {F}r{\'e}d{\'e}ric and {C}ravatte, {S}ophie and {L}ebourges {D}haussy, {A}nne and {L}ehodey, {P}. and {M}angeas, {M}organ and {S}mith, {N}. and {R}adenac, {M}arie-{H}{\'e}l{\`e}ne and {M}enk{\`e}s, {C}hristophe},
  editor = {},
  language = {{ENG}},
  abstract = {{A}coustic data are invaluable information sources for characterizing the distribution and abundance of mid-trophic-level organisms (micronekton). {T}hese organisms play a pivotal role in the ecosystem as prey of top predators and as predators of low-trophic-level organisms. {A}lthough shipboard-{ADCP} (acoustic {D}oppler current profiler) acoustic backscatter signal intensity cannot provide an absolute biomass estimate, it may be a useful proxy to investigate variability in the distribution and relative density of micro-nekton. {T}his study used acoustic recordings data spread across 19 years (1999-2017) from 54 {ADCP} cruises in {N}ew {C}aledonia's subtropical {EEZ} (exclusive economic zone) to assess seasonal and interannual variabilities and spatial distribution of micro-nekton. {T}he dataset was composed of two different {ADCP}s: 150 k{H}z for the first period, followed by 75 k{H}z for more recent years. {W}e examined the 20-120 m averaged scattering layer. {U}sing the few cruises with concurrent {EK}60 measurements, we proposed that the backscatter from the {ADCP}s and 70 k{H}z {EK}60 were sufficiently closely linked to allow the use of the backscatter signal from the {ADCP}s in a combined dataset over the full time series. {W}e then designed a {GAMM} (generalized additive mixed model) model that takes into account the two {ADCP} devices as well as temporal variability. {A}fter accounting for the effect of the devices, we showed that the acoustic signal was mainly driven by diel vertical migration, season, year, and {ENSO} ({E}l {N}ino-{S}outhern {O}scillation). {I}n a second step, a consensus model between two statistical approaches ({GAMM} and {SVM}) (support vector machine) was constructed, linking the nighttime 20-120 m backscatter to the oceanographic and geographic environment. {T}his model showed that sea surface temperature was the main factor driving backscatter variability in the {EEZ}, with intensified backscatter during the austral summer ({D}ecember to {M}ay) in the northern part of the {EEZ}. {W}e showed that acoustic density differed significantly, spatially and temporally from micronekton biomass predicted for the same period by the {SEAPODYM}-{MTL} (mid-trophic level) ecosystem model. {T}he seasonal cycle given by {ADCP} data lagged behind the {SEAPODYM}-{MTL} seasonal cycle by around three months. {R}easons to explain these differences and further needs in observation and modeling were explored in the discussion. {I}n addition to providing new insights for micronekton dynamics in this {EEZ} (i.e., the science needed for ecosystem-based fisheries management), the data should help improve our ability to model this key trophic component.},
  keywords = {{M}icronekton ; {S}outhwest {P}acific ocean ; {SEAPODYM} ; {A}coustic ; {E}cosystem ; {NOUVELLE} {CALEDONIE} ; {PACIFIQUE}},
  booktitle = {},
  journal = {{D}eep-{S}ea {R}esearch {P}art {I} : {O}ceanographic {R}esearch {P}apers},
  volume = {159},
  numero = {},
  pages = {art. 103237 [17 p.]},
  ISSN = {0967-0637},
  year = {2020},
  DOI = {10.1016/j.dsr.2020.103237},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079038},
}