N
Nadir Alvarez
Researcher at American Museum of Natural History
Publications - 130
Citations - 4786
Nadir Alvarez is an academic researcher from American Museum of Natural History. The author has contributed to research in topics: Population & Biological dispersal. The author has an hindex of 34, co-authored 121 publications receiving 3924 citations. Previous affiliations of Nadir Alvarez include University of Lausanne & Natural History Museum of Geneva.
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Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference
Alicia Mastretta-Yanes,Nils Arrigo,Nadir Alvarez,Tove H. Jorgensen,Daniel Piñero,Brent C. Emerson,Brent C. Emerson +6 more
TL;DR: Individual sample replicates are used, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome and optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci.
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History or ecology? Substrate type as a major driver of spatial genetic structure in Alpine plants
Nadir Alvarez,Conny Thiel-Egenter,Andreas Tribsch,Rolf Holderegger,Stéphanie Manel,Peter Schönswetter,Pierre Taberlet,Sabine Brodbeck,Myriam Gaudeul,Ludovic Gielly,Philippe Küpfer,Guilhem Mansion,Riccardo Negrini,Ovidiu Paun,Marco Pellecchia,Delphine Rioux,Fanny Schüpfer,Marcela van Loo,Manuela Winkler,Felix Gugerli +19 more
TL;DR: The relevance of particular ecological factors in shaping genetic patterns, which should be considered when modelling species projective distributions under climate change scenarios, are demonstrated.
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An evaluation of new parsimony‐based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae
TL;DR: A parametric method, dispersal–extinction–cladogenesis (DEC), is compared against a parsimony‐based method, disperseal–vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes‐DIVA).
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Evaluating the impact of scoring parameters on the structure of intra-specific genetic variation using RawGeno, an R package for automating AFLP scoring
TL;DR: A new scoring algorithm, RawGeno, is used, which appears to perform as well as a commercial program in automating AFLP scoring, at least in the context of population genetics or phylogeographic studies.
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Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation
Stéphanie Manel,Stéphanie Manel,Felix Gugerli,Wilfried Thuiller,Nadir Alvarez,Pierre Legendre,Rolf Holderegger,Ludovic Gielly,Pierre Taberlet +8 more
TL;DR: It is shown, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.