@article{fdi:010078196,
  title = {{M}achine learning for characterizing tropical tuna aggregations under {D}rifting {F}ish {A}ggregating {D}evices ({DFAD}s) from commercial echosounder buoys data},
  author = {{B}aidai, {Y}. and {D}agorn, {L}aurent and {A}mande, {M}. {J}. and {G}aertner, {D}aniel and {C}apello, {M}anuela},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he use of echosounder buoys deployed in conjunction with {D}rifting {F}ish {A}ggregating {D}evices ({DFAD}s) has progressively increased in the tropical tuna purse seine fishery since 2010 as a means of improving fishing efficiency. {G}iven the broad distribution of {DFAD}s, the acoustic data provided by echosounder buoys can provide an alternative to the conventional {CPUE} index for deriving trends on tropical tuna stocks. {T}his study aims to derive reliable indices of presence of tunas (and abundance) using echosounder buoy data. {A} novel methodology is presented which utilizes random forest classification to translate the acoustic backscatter from the buoys into metrics of tuna presence and abundance. {T}raining datasets were constructed by cross-referencing acoustic data with logbook and observer data which reported activities on {DFAD}s (tuna catches, new deployments and visits of {DFAD}s) in the {A}tlantic and {I}ndian {O}ceans from 2013 to 2018. {T}he analysis showed accuracies of 75 and 85 % for the recognition of the presence/absence of tuna aggregations under {DFAD}s in the {A}tlantic and {I}ndian {O}ceans, respectively. {T}he acoustic data recorded at ocean-specific depths (6-45m in the {A}tlantic and 30-150m in the {I}ndian {O}cean) and periods (4 a.m.-4 p.m.) were identified by the algorithm as the most important explanatory variables for detecting the presence of tuna. {T}he classification of size categories of tuna aggregations showed a global accuracy of nearly 50 % for both oceans. {T}his study constitutes a milestone towards the use of echosounder buoys data for scientific purposes, including the development of promising fisheries-independent indices of abundance for tropical tunas.},
  keywords = {{T}ropical tunas ; {D}irect abundance indicator ; {E}chosounder buoys ; {F}ish aggregating devices ; {P}urse seiner ; {ATLANTIQUE} ; {OCEAN} {INDIEN}},
  booktitle = {},
  journal = {{F}isheries {R}esearch},
  volume = {229},
  numero = {},
  pages = {art. 105613 [9 p.]},
  ISSN = {0165-7836},
  year = {2020},
  DOI = {10.1016/j.fishres.2020.105613},
  URL = {https://www.documentation.ird.fr/hor/fdi:010078196},
}