The Subantarctic Rayadito (Aphrastura subantarctica), a new bird species on the southernmost islands of the Americas Page: 5
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Geographic group n K Kr S H 7T D Fu
CNS 20 2 1.45 1 0.10 0.10 - 1.16 -0.88
PATAG 68 11 2.92 11 0.43 0.57 - 2.08 - 10.02
NAVHOR 23 4 2.67 3 0.39 0.42 -1.24 -1.84
DIERAM 9 1 1 0 0.00 0.00 0 0
Total 120 14 - 14 0.45 0.56 - 2.10 - 3.30
Table 1. Measures of genetic diversity based on mtDNA in different Aphrastura geographic groups. CNS
Center, north and south, PATAG Patagonia (Chilo6 to Tierra del Fuego), NAVHOR Navarino and Horn
islands, DIERAM Diego Ramirez, N sample size, K number of haplotypes, Kr number of haplotypes based on
rarefaction curves to compare diversity in geographic groups with different sample sizes (see "Methods" for
details), S number of polymorphic sites, H heterozygosity, n average number of nucleotide differences between
pairs of sequences, D Fu and Li's D neutrality test, Fu Fu's neutrality test. Statistically significant values are
indicated in bold.Locality Latitude/longitude n Na Na (rarefied)* Np Ho He F s
Manquehue 33.35 S/70.57 W 40 8.42 (1.01) 6.23 (0.64) 0.42 (0.15) 0.72 (0.06) 0.73 (0.06) 0.009
Bariloche 41.15 S/71.38 W 40 12.08 (1.76) 7.19 (0.84) 2.08 (0.72) 0.75 (0.06) 0.76 (0.05) 0.013
Tierra del Fuego 54.11 S/69.36 W 24 9.66 (1.40) 6.51 (0.78) 0.58 (0.26) 0.74 (0.06) 0.74 (0.05) - 0.008
Navarino Island 54.94 S/67.64 W 40 9.66 (1.26) 6.12 (0.65) 0.58 (0.26) 0.75 (0.04) 0.74 (0.04) - 0.028
Diego Ramirez 56.52 S/68.71 W 9 2.25 (0.45) 2.25 (0.45) 0.08 (0.08) 0.22 (0.08) 0.25 (0.09) 0.026
Table 2. Localities, sample sizes and measures of genetic diversity based on 12 microsatellite loci in five
Aphrastura populations. N sample size, Na number of alleles, Np number of private alleles, Ho observed
heterozygosity, He expected heterozygosity, F1s within-population inbreeding coefficient. Mean values and
standard errors over 12 microsatellite loci are reported. *The allelic richness for the minimum number of
individuals genotyped in any population (times 2).
Phylogeographic analysis. We used Arlequin 3.5.1.232 to estimate the number of haplotypes and polymorphic
sites, gene diversity, differences between pairs of sequences (T) and nucleotide diversity (T per nucleotide site).
For comparison of the four geographic groups (Fig. 1; Table 1), we used a rarefaction analysis with PAST33 to
adjust for unequal sample sizes. We generated a haplotype network using the median-joining approach method34
implemented in Network 4.6. Using Arlequin 3.5.1.232, we estimated indices of genetic differentiation among
geographic units based on both allele frequencies and pairwise nucleotide differences (pairwise FST and OsT,
respectively). We tested for phylogeographic structure by comparing GST and NST coefficients using permutation
tests implemented in PERMUT35. To infer the spatial genetic structure of Aphrastura populations, we used an
analysis of molecular variance (AMOVA)36, defining groups of populations that are geographically homogene-
ous and maximally differentiated from each other.
Population genetic analysis. We performed further genetic analyses based on nuclear microsatellite markers to
check the conclusions from the mitochondrial phylogeographic approach. We analyzed an additional sub-sam-
ple of 153 individuals from Central Chile, Southern Chile and Argentina, and Diego Ramirez (Fig. 1; Table 2).
These individuals were originally genotyped for another study led by EB-D10, using 12 autosomal polymorphic
loci37. The marker panel consisted of seven species-specific markers and five cross-species amplifying markers
(seei0,38). None of the loci showed evidence for deviations from Hardy-Weinberg equilibrium (all p >0.1) and all
had null allele frequencies<0.05. We calculated measures of genetic diversity per population using the hierfstat
package39 in R. To summarize overall genetic variability among individuals and to preliminarily assess genetic
structure, we used a PCA as implemented in the R package adegenet40. To estimate the optimal (most likely)
number of genetic clusters that were present in our sample, we used the 'snapclust' method in adegenet. This
method relies on maximizing the likelihood of a number of panmictic populations by combining model-based
and geometric approaches41. The best-supported number of groups was determined using the Akaike Informa-
tion Criterion (AIC).
The resulting genetic clusters were subsequently used for population structure analyses. First, we used
GenAlex 6.542 to calculate pairwise G-statistics for the genetic clusters identified, implementing both the Nei's
standardized index (G'ST(Nei)) and the Hedrick's standardized index corrected for small samples (G "sT). Second,
we calculated the posterior membership probabilities of all sampled individuals for the newly identified genetic
clusters, using the probability of assignment obtained from the 'snapclust' method (see41). Finally, we performed
a complementary analysis for inferring individual membership to each genetic group using GeneClass243 to
identify first-generation migrants. Detection of migrants was carried out using Paetkau et ails44 criterion for
likelihood computation (Lh) and Paetkau et al's45 resampling method for probability calculation, setting the
default frequency for missing alleles at 0.01 and using 10 replicates with 100 simulated individuals each (a= 0.01).https://doi.org/10.1038/s41598-022-17985-4
Scientific Reports (2022) -12:13957
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Rozzi, Ricardo, 1960-; Quilodrán, Claudio S.; Botero-Delgadillo, Esteban; Napolitano, Constanza; Torres-Mura, Juan C.; Barroso, Omar et al. The Subantarctic Rayadito (Aphrastura subantarctica), a new bird species on the southernmost islands of the Americas, article, August 26, 2022; (https://digital.library.unt.edu/ark:/67531/metadc2178792/m1/5/: accessed July 17, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Science.