Publications des scientifiques de l'IRD

Ariza A., Lebourges Dhaussy Anne, Nerini D., Pauthenet E., Roudaut Gildas, Assuncao R., Tosetto E., Bertrand Arnaud. (2023). Acoustic seascape partitioning through functional data analysis. Journal of Biogeography, [Early access], p. [15 p.]. ISSN 0305-0270.

Titre du document
Acoustic seascape partitioning through functional data analysis
Année de publication
Type de document
Article référencé dans le Web of Science WOS:000888936900001
Ariza A., Lebourges Dhaussy Anne, Nerini D., Pauthenet E., Roudaut Gildas, Assuncao R., Tosetto E., Bertrand Arnaud
Journal of Biogeography, 2023, [Early access], p. [15 p.] ISSN 0305-0270
AimWater column acoustic backscatter is regularly registered during oceanographic surveys, providing valuable information on the composition and distribution of pelagic life in the ocean. We propose an objective approach based on functional data analysis to classify these acoustic seascapes into biogeographical regions. LocationTropical South Atlantic Ocean off northeastern Brazil. TaxonSound-scattering pelagic fauna detected with acoustic echosounders, principally small fish, crustaceans, squid and diverse gelatinous life-forms. MethodsWe use acoustic backscatter as a function of depth, simultaneously at three frequencies, to numerically describe the vertical distribution and composition of sound-scattering organisms in the water column. This information is used to classify the acoustic seascape through functional principal component analysis. The analysis routine is tested and illustrated with data collected at 38, 70 and 120 kHz in waters affected by contrasting environmental conditions. ResultsAcoustic seascape partitioning mirrored the distribution of current systems, fronts and taxonomically based regionalization. The study area was divided between slope-boundary and open-ocean waters, and between spring and fall hydrological regimes. Main ConclusionsThe acoustic seascape consistency and the spatiotemporal coherence of the regions classified show that the method is efficient at identifying homogeneous and cohesive sound-scattering communities. Comparisons against hydrological and biological regionalization prove that the method is reliable at delineating distinct pelagic ecosystems in a cost-efficient and non-intrusive way.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Ecologie, systèmes aquatiques [036] ; Etudes, transformation, conservation du milieu naturel [082]
Description Géographique
Fonds IRD [F B010086685]
Identifiant IRD