Acoustic seascape partitioning through functional data analysis

• Published in: Journal of Biogeography
• Main Authors: Ariza, Alejandro, Lebourges-dhaussy, Anne, Nerini, David, Pauthenet, Etienne, Roudaut, Gildas, Assunção, Ramilla, Tosetto, Everton, Bertrand, Arnaud
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2023
• Subjects: biogeography; echoregions; Fernando de Noronha; mesopelagic; micronekton; northeastern Brazil; sound-scattering layers; soundscape; South Atlantic Ocean
• Online Access: https://archimer.ifremer.fr/doc/00807/91875/97829.pdf; https://archimer.ifremer.fr/doc/00807/91875/97830.pdf; https://doi.org/10.1111/jbi.14534; https://archimer.ifremer.fr/doc/00807/91875/

Aim Water 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. Location Tropical South Atlantic Ocean off northeastern Brazil. Taxon Sound-scattering pelagic fauna detected with acoustic echosounders, principally small fish, crustaceans, squid and diverse gelatinous life-forms. Methods We 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. Results Acoustic 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 Conclusions The 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.