@incollection{fdi:010079230,
  title = {{S}eychelles {VMS}/logbook comparison for tuna fisheries ({FAO} {A}rea 51)},
  author = {{N}ieblas, {A}.{E}. and {B}arde, {J}ulien and {L}ouys, {J}. and {L}ucas, {J}. and {A}ssan, {C}. and {I}mzilen, {T}aha and {D}alleau, {C}. and {G}erry, {C}. and {C}hassot, {E}mmanuel},
  editor = {},
  language = {{ENG}},
  abstract = {{S}eychelles high seas tuna fleets have a high {AIS} use with a transmission frequency considerably higher than that of {VMS}. {H}owever, {AIS} has far fewer transmissions than {VMS} and many more gaps in transmission longer than a few hours. {T}he spatial coverage of the {AIS} data is good for {S}eychelles longline vessels, with acceptable coverage over the core fishing grounds. {B}y contrast, {AIS} data are deficient for purse seiners and supply vessels with most data only present around ports due to the switch-off behavior linked to the piracy threat.{C}onsistent with data coverage, {AIS} seems to be very useful in describing the spatiotemporal patterns of the longline fishery and for identifying fishing hotspots. {T}he {GFW} neural net algorithm predicts well the fishing operations for longliners but predictions for purse seiners are not informative. {M}etrics for effort at the scale of 5° x 5° squares, such as those typically used by tuna regional fisheries management organizations ({RFMO}s) for longline fisheries, are well correlated between logbooks and {GFW} algorithms. {T}hus, {GFW} is able to accurately distinguish fishing from non-fishing activities for longliners. {H}owever, the frequent breaks in transmission, perhaps due to issues with {AIS} reception, lead to consistent underprediction by {AIS} and {GFW} algorithms of the "true" patterns shown using {VMS} and logbook data. {T}he increased satellite coverage observed between 2016 and 2017 resulted in improved {GFW} algorithm performance in deriving estimations of longline fishing effort.{T}he relationships between {GFW} predictions of longline fishing and effort could be useful in data-poor fisheries where poor collection and management systems may prevent the reporting of spatial effort to the {RFMO}. {I}n such cases, the availability of {AIS} or {VMS} data combined with information on the number of hooks deployed per operation may enable predictions of gridded effort, which would improve compliance with the {C}onservation and {M}anagement {M}easures.},
  keywords = {{SEYCHELLES} ; {OCEAN} {INDIEN}},
  booktitle = {{G}lobal atlas of {AIS}-based fishing activity : challenges and opportunities},
  numero = {},
  pages = {79--108},
  address = {{R}ome},
  publisher = {{FAO}},
  series = {},
  year = {2019},
  ISBN = {978-92-5-131964-2},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079230},
}