@article{fdi:010068332,
  title = {{E}xploring the spatial distribution patterns of {S}outh {A}frican {C}ape hakes using generalised additive models},
  author = {{G}russ, {A}rnaud and {Y}emane, {D}. and {F}airweather, {T}. {P}.},
  editor = {},
  language = {{ENG}},
  abstract = {{W}e developed delta generalised additive models ({GAM}s) to predict the spatial distribution of different size classes of {S}outh {A}frican hakes, {M}erluccius capensis and {M}. paradoxus, using demersal trawl survey data and geographical (latitude and longitude) and environmental features (depth, temperature, bottom dissolved oxygen and sediment type). {O}ur approach consists of fitting, for each hake size class, two independent models, a binomial {GAM} and a quasi-{P}oisson {GAM}, whose predictions are then combined using the delta method. {D}elta {GAM}s were validated using an iterative cross-validation procedure, and their predictions were then employed to produce distribution maps for the southern {B}enguela. {D}elta {GAM} predictions confirmed existing knowledge about the spatial distribution patterns of {S}outh {A}frican hakes, and brought new insights into the factors influencing the presence/absence and abundance of these species. {O}ur {GAM} approach can be used to produce distribution maps for spatially explicit ecosystem models of the southern {B}enguela in a rigorous and objective way. {E}cosystem models are critical features of the ecosystem approach to fisheries, and distribution maps constructed using our {GAM} approach will enable a reliable allocation of species biomasses in spatially explicit ecosystem models, which will increase trust in the spatial overlaps and, therefore, the trophic interactions predicted by these models.},
  keywords = {distribution maps ; {M}erluccius capensis ; {M}erluccius paradoxus ; {S}outh {A}frica ; spatial distributions ; {AFRIQUE} {DU} {SUD}},
  booktitle = {},
  journal = {{A}frican {J}ournal of {M}arine {S}cience},
  volume = {38},
  numero = {3},
  pages = {395--409},
  ISSN = {1814-232{X}},
  year = {2016},
  DOI = {10.2989/1814232x.2016.1218367},
  URL = {https://www.documentation.ird.fr/hor/fdi:010068332},
}