@article{fdi:010040759,
  title = {{A}rtificial neural network analysis of factors controling ecosystem metabolism in coastal systems},
  author = {{R}ochelle {N}ewall, {E}mma and {W}inter, {C}. and {B}arron, {C}. and {B}orges, {A}. {V}. and {D}uarte, {C}. {M}. and {E}lliott, {M}. and {F}rankignoulle, {M}. and {G}azeau, {F}. and {M}iddelburg, {J}.{J}. and {P}izay, {M}.{D}. and {G}attuso, {J}.{P}.},
  editor = {},
  language = {{ENG}},
  abstract = {{K}nowing the metabolic balance of an ecosystem is of utmost importance in determining whether the system is a net source or net sink of carbon dioxide to the atmosphere. {H}owever, obtaining these estimates often demands significant amounts of time and manpower. {H}ere we present a simplified way to obtain an estimation of ecosystem metabolism. {W}e used artificial neural networks ({ANN}s) to develop a mathematical model of the gross primary production to community respiration ratio ({GPP}:{CR}) based on input variables derived from three widely contrasting {E}uropean coastal ecosystems ({S}cheldt {E}stuary, {R}anders {F}jord, and {B}ay of {P}alma). {A}lthough very large gradients of nutrient concentration, light penetration, and organic-matter concentration exist across the sites, the factors that best predict the {GPP}:{CR} ratio are sampling depth, dissolved organic carbon ({DOC}) concentration, and temperature. {W}e propose that, at least in coastal ecosystems, metabolic balance can be predicted relatively easily from these three predictive factors. {A}n important conclusion of this work is that {ANN}s can provide a robust tool for the determination of ecosystem metabolism in coastal ecosystems.},
  keywords = {artificial neural networks ; coastal ecosystems ; metabolic balance ; primary production ; respiration},
  booktitle = {},
  journal = {{E}cological {A}pplications},
  volume = {17},
  numero = {5 {S}uppl.},
  pages = {{S}185--{S}196},
  ISSN = {1051-0761},
  year = {2007},
  DOI = {10.1890/05-1769.1},
  URL = {https://www.documentation.ird.fr/hor/fdi:010040759},
}