@article{fdi:010088270,
  title = {{A} quantitative theory for genomic offset statistics},
  author = {{G}ain, {C}. and {R}hone, {B}. and {C}ubry, {P}hilippe and {S}alazar, {I}. and {F}orbes, {F}. and {V}igouroux, {Y}ves and {J}ay, {F}. and {F}rancois, {O}.},
  editor = {},
  language = {{ENG}},
  abstract = {{G}enomic offset statistics predict the maladaptation of populations to rapid habitat alteration based on association of genotypes with environmental variation. {D}espite substantial evidence for empirical validity, genomic offset statistics have well-identified limitations, and lack a theory that would facilitate interpretations of predicted values. {H}ere, we clarified the theoretical relationships between genomic offset statistics and unobserved fitness traits controlled by environmentally selected loci and proposed a geometric measure to predict fitness after rapid change in local environment. {T}he predictions of our theory were verified in computer simulations and in empirical data on {A}frican pearl millet ({C}enchrus americanus) obtained from a common garden experiment. {O}ur results proposed a unified perspective on genomic offset statistics and provided a theoretical foundation necessary when considering their potential application in conservation management in the face of environmental change.},
  keywords = {predictive ecological genomics ; genomic offset ; climate change ; local adaptation ; pearl millet ; {AFRIQUE} {SUBSAHARIENNE}},
  booktitle = {},
  journal = {{M}olecular {B}iology and {E}volution},
  volume = {40},
  numero = {6},
  pages = {msad140 [10 ]},
  ISSN = {0737-4038},
  year = {2023},
  DOI = {10.1093/molbev/msad140},
  URL = {https://www.documentation.ird.fr/hor/fdi:010088270},
}