@article{fdi:010091209,
  title = {{O}ptimising occurrence data in species distribution models : sample size, positional uncertainty, and sampling bias matter},
  author = {{M}oudry, {V}. and {B}azzichetto, {M}. and {R}emelgado, {R}. and {D}evillers, {R}odolphe and {L}enoir, {J}. and {M}ateo, {R}. {G}. and {L}embrechts, {J}. {J}. and {S}illero, {N}. and {L}ecours, {V}. and {C}ord, {A}. {F}. and {B}arták, {V}. and {B}alej, {P}. and {R}occhini, {D}. and {T}orresani, {M}. and {A}renas-{C}astro, {S}. and {M}an, {M}. {T}. and {P}rajzlerová, {D}. and {G}dulová, {K}. and {P}rosek, {J}. and {M}archetto, {E}. and {Z}arzo-{A}rias, {A}. and {G}ábor, {L}. and {L}eroy, {F}. and {M}artini, {M}. and {M}alavasi, {M}. and {G}atti, {R}. {C}. and {W}ild, {J}. and {S}ímová, {P}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}pecies distribution models ({SDM}s) have proven valuable in filling gaps in our knowledge of species occurrences. {H}owever, despite their broad applicability, {SDM}s exhibit critical shortcomings due to limitations in species occurrence data. {T}hese limitations include, in particular, issues related to sample size, positional uncertainty, and sampling bias. {I}n addition, it is widely recognised that the quality of {SDM}s as well as the approaches used to mitigate the impact of the aforementioned data limitations depend on species ecology. {W}hile numerous studies have evaluated the effects of these data limitations on {SDM} performance, a synthesis of their results is lacking. {H}owever, without a comprehensive understanding of their individual and combined effects, our ability to predict the influence of these issues on the quality of modelled species-environment associations remains largely uncertain, limiting the value of model outputs. {I}n this paper, we review studies that have evaluated the effects of sample size, positional uncertainty, sampling bias, and species ecology on {SDM}s outputs. {W}e build upon their findings to provide recommendations for the critical assessment of species data intended for use in {SDM}s.},
  keywords = {data quality ; ecological niche modelling ; filtering ; sampling ; spatial ; scale ; validation},
  booktitle = {},
  journal = {{E}cography},
  volume = {[{E}arly access]},
  numero = {},
  pages = {[20 p.]},
  ISSN = {0906-7590},
  year = {2024},
  DOI = {10.1111/ecog.07294},
  URL = {https://www.documentation.ird.fr/hor/fdi:010091209},
}