@article{fdi:010079306,
  title = {"{T}oo {B}ig to {I}gnore" : a feasibility analysis of detecting fishing events in {G}abonese small-scale fisheries},
  author = {{C}ardiec, {F}. and {B}ertrand, {S}ophie and {W}itt, {M}. {J}. and {M}etcalfe, {K}. and {G}odley, {B}. {J}. and {M}c{C}lellan, {C}. and {V}ilela, {R}. and {P}arnell, {R}. {J}. and {L}e {L}oc'h, {F}ran{\c{c}}ois},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n many developing countries, small-scale fisheries provide employment and important food security for local populations. {T}o support resource management, the description of the spatiotemporal extent of fisheries is necessary, but often poorly understood due to the diffuse nature of effort, operated from numerous small wooden vessels. {H}ere, in {G}abon, {C}entral {A}frica, we applied {H}idden {M}arkov {M}odels to detect fishing patterns in seven different fisheries (with different gears) from {GPS} data. {M}odels were compared to information collected by on-board observers (7 trips) and, at a larger scale, to a visual interpretation method (99 trips). {M}odels utilizing different sampling resolutions of {GPS} acquisition were also tested. {M}odel prediction accuracy was high with {GPS} data sampling rates up to three minutes apart. {T}he minor loss of accuracy linked to model classification is largely compensated by the savings in time required for analysis, especially in a context of nations or organizations with limited resources. {T}his method could be applied to larger datasets at a national or international scale to identify and more adequately manage fishing effort.},
  keywords = {{GABON}},
  booktitle = {},
  journal = {{PL}o{S} {O}ne},
  volume = {15},
  numero = {6},
  pages = {e0234091 [19 p.]},
  ISSN = {1932-6203},
  year = {2020},
  DOI = {10.1371/journal.pone.0234091},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079306},
}