@article{fdi:010085210,
  title = {{C}ombining passive acoustics and environmental data for scaling up ecosystem monitoring : a test on coral reef fishes},
  author = {{E}lise, {S}. and {G}uilhaumon, {F}ran{\c{c}}ois and {M}ou-{T}ham, {G}{\'e}rard and {U}rbina-{B}arreto, {I}. and {V}igliola, {L}aurent and {K}ulbicki, {M}ichel and {B}ruggemann, {J}. {H}.},
  editor = {},
  language = {{ENG}},
  abstract = {{E}cological surveys of coral reefs mostly rely on visual data collected by human observers. {A}lthough new monitoring tools are emerging, their specific advantages should be identified to optimise their simultaneous use. {B}ased on the goodness-of-fit of linear models, we compared the potential of passive acoustics and environmental data for predicting the structure of coral reef fish assemblages in different environmental and biogeographic settings. {B}oth data types complemented each other. {G}lobally, the acoustic data showed relatively low added value in predicting fish assemblage structures. {T}he predictions were best for the distribution of fish abundance among functional entities (i.e., proxies for fish functional groups, grouping species that share similar eco-morphological traits), for the simplest functional entities (i.e., combining two eco-morphological traits), and when considering diet and the level in the water column of the species. {O}ur study demonstrates that {P}assive {A}coustic {M}onitoring ({PAM}) improves fish assemblage assessment when used in tandem with environmental data compared to using environmental data alone. {S}uch combinations can help with responding to the current conservation challenge by improving our surveying capacities at increased spatial and temporal scales, facilitating the identification and monitoring of priority management areas.},
  keywords = {coral reefs ; fish assemblages ; remote sensing ; {P}assive {A}coustic {M}onitoring ({PAM}) ; ecoacoustic indices ; conservation ; {PACIFIQUE} ; {OCEAN} {INDIEN} ; {REUNION} ; {NOUVELLE} {CALEDONIE} ; {EUROPA}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {14},
  numero = {10},
  pages = {2394 [18 p.]},
  year = {2022},
  DOI = {10.3390/rs14102394},
  URL = {https://www.documentation.ird.fr/hor/fdi:010085210},
}