Flightless brown kiwis of New Zealand possess extremely subdivided population structure and cryptic species like small mammals.

Using allozymes and mtDNA sequences from the cytochrome b gene, we report that the brown kiwi has the highest levels of genetic structuring observed in birds. Moreover, the mtDNA sequences are, with two minor exceptions, diagnostic genetic markers for each population investigated, even though they are among the more slowly evolving coding regions in this genome. A major unexpected finding was the concordant split in molecular phylogenies between brown kiwis in the southern South Island and elsewhere in New Zealand. This basic phylogeographic boundary halfway down the South Island coincides with a fixed allele difference in the Hb nuclear locus and strongly suggests that two morphologically cryptic species are currently merged under one polytypic species. This is another striking example of how molecular genetic assays can detect phylogenetic discontinuities that are not reflected in traditional morphologically based taxonomies. However, reanalysis of the morphological characters by using phylogenetic methods revealed that the reason for this discordance is that most are primitive and thus are phylogenetically uninformative. Shared-derived morphological characters support the same relationships evident in the molecular phylogenies and, in concert with the molecular data, suggest that as brown kiwis colonized northward from the southern South Island, they retained many primitive characters that confounded earlier systematists. Strong subdivided population structure and cryptic species in brown kiwis seem to have evolved relatively recently as a consequence of Pleistocene range disjunctions, low dispersal power, and genetic drift in small populations.

Measurement of genetic structure within populations using Moran's spatial autocorrelation statistics.

Spatial structure of genetic variation within populations, an important interacting influence on evolutionary and ecological processes, can be analyzed in detail by using spatial autocorrelation statistics. This paper characterizes the statistical properties of spatial autocorrelation statistics in this context and develops estimators of gene dispersal based on data on standing patterns of genetic variation. Large numbers of Monte Carlo simulations and a wide variety of sampling strategies are utilized. The results show that spatial autocorrelation statistics are highly predictable and informative. Thus, strong hypothesis tests for neutral theory can be formulated. Most strikingly, robust estimators of gene dispersal can be obtained with practical sample sizes. Details about optimal sampling strategies are also described.

Geographical structuring in the mtDNA of Italians.

Geographical patterns of mtDNA variation were studied in 12 Italian samples (1072 individuals) by two different spatial autocorrelation methods. Separate analyses of the frequencies of 12 restriction morphs show North-South clines, differences between Sardinia and the mainland populations, and the effects of isolation by distance. A recently developed autocorrelation statistic summarizing molecular similarity at all sites (AIDA; autocorrelation index for DNA analysis) confirms the presence of a clinical pattern; differences between random pairs of haplotypes tend to increase with their geographical distance. The partition of gene diversity, however, reveals that most variability occurs within populations, whereas differences between populations are minor (GST = 0.057). When the data from the 12 samples are pooled, two descriptors of genetic variability (number of polymorphic sites and average sequence difference between pairs of individuals) do not behave as expected under neutrality. The presence of clinal patterns, Tajima's tests, and a simulation experiment agree in suggesting that population sizes increased rapidly in Italy and Sicily but not necessarily so in Sardinia. The distribution of pairwise sequence differences in the Italian peninsula (excluding Sardinia) permits a tentative location of the demographic increase between 8000 and 20,500 years ago. These dates are consistent with archaeological estimates of two distinct expansion processes, occurring, respectively, in the Neolithic and after the last glacial maximum in the Paleolithic. Conversely, there is no genetic evidence that such processes have had a major impact on the Sardinian population.