@article{fdi:010070316,
  title = {{C}omparison of different genetic distances to test isolation by distance between populations},
  author = {{S}{\'e}r{\'e}, {M}. and {T}h{\'e}venon, {S}. and {B}elem, {A}. {M}. {G}. and {D}e {M}eeûs, {T}hierry},
  editor = {},
  language = {{ENG}},
  abstract = {{S}tudying isolation by distance can provide useful demographic information. {T}o analyze isolation by distance from molecular data, one can use some kind of genetic distance or coalescent simulations. {M}olecular markers can often display technical caveats, such as {PCR}-based amplification failures (null alleles, allelic dropouts). {T}hese problems can alter population parameter inferences that can be extracted from molecular data. {I}n this simulation study, we analyze the behavior of different genetic distances in {I}sland (null hypothesis) and stepping stone models displaying varying neighborhood sizes. {I}mpact of null alleles of increasing frequency is also studied. {I}n stepping stone models without null alleles, the best statistic to detect isolation by distance in most situations is the chord distance {DCSE}. {N}evertheless, for markers with genetic diversities {H}-{S}<o0.4-0.5, all statistics tend to display the same statistical power. {M}arginal sub-populations behave as smaller neighborhoods. {M}etapopulations composed of small sub-population numbers thus display smaller neighborhood sizes. {W}hen null alleles are introduced, the power of detection of isolation by distance is significantly reduced and {DCSE} remains the most powerful genetic distance. {W}e also show that the proportion of null allelic states interact with the slope of the regression of {F}-{ST}/(1 - {FST}) as a function of geographic distance. {T}his can have important consequences on inferences that can be made from such data. {N}evertheless, {C}hapuis and {E}stoup's {F}ree{NA} correction for null alleles provides very good results in most situations. {W}e finally use our conclusions for reanalyzing and reinterpreting some published data sets.},
  keywords = {},
  booktitle = {},
  journal = {{H}eredity},
  volume = {119},
  numero = {2},
  pages = {55--63},
  ISSN = {0018-067{X}},
  year = {2017},
  DOI = {10.1038/hdy.2017.26},
  URL = {https://www.documentation.ird.fr/hor/fdi:010070316},
}