Information theory analysis of Australian humpback whale song

Songs produced by migrating whales were recorded off the coast of Queensland, Australia, over six consecutive weeks in 2003. Forty-eight independent song sessions were analyzed using information theory techniques. The average length of the songs estimated by correlation analysis was approximately 100 units, with song sessions lasting from 300 to over 3100 units. Song entropy, a measure of structural constraints, was estimated using three different methodologies: (1) the independently identically distributed model, (2) a first-order Markov model, and (3) the nonparametric sliding window match length (SWML) method, as described by Suzuki et al. [(2006). “Information entropy of humpback whale song,” J. Acoust. Soc. Am. 119, 1849–1866]. The analysis finds that the song sequences of migrating Australian whales are consistent with the hierarchical structure proposed by Payne and McVay [(1971). “Songs of humpback whales,” Science 173, 587–597], and recently supported mathematically by Suzuki et al. (2006) for singers on the Hawaiian breeding grounds. Both the SWML entropy estimates and the song lengths for the Australian singers in 2003 were lower than that reported by Suzuki et al. (2006) for Hawaiian whales in 1976–1978; however, song redundancy did not differ between these two populations separated spatially and temporally. The average total information in the sequence of units in Australian song was approximately 35 bits/song. Aberrant songs (8%) yielded entropies similar to the typical songs

Patterns of Polymorphism and Demographic History in Natural Populations of Arabidopsis lyrata

Many of the processes affecting genetic diversity act on local populations. However, studies of plant nucleotide diversity have largely ignored local sampling, making it difficult to infer the demographic history of populations and to assess the importance of local adaptation. Arabidopsis lyrata, a self-incompatible, perennial species with a circumpolar distribution, is an excellent model system in which to study the roles of demographic history and local adaptation in patterning genetic variation.We studied nucleotide diversity in six natural populations of Arabidopsis lyrata, using 77 loci sampled from 140 chromosomes. The six populations were highly differentiated, with a median FST of 0.52, and structure analysis revealed no evidence of admixed individuals. Average within-population diversity varied among populations, with the highest diversity found in a German population; this population harbors 3-fold higher levels of silent diversity than worldwide samples of A. thaliana. All A. lyrata populations also yielded positive values of Tajima's D. We estimated a demographic model for these populations, finding evidence of population divergence over the past 19,000 to 47,000 years involving non-equilibrium demographic events that reduced the effective size of most populations. Finally, we used the inferred demographic model to perform an initial test for local adaptation and identified several genes, including the flowering time gene FCA and a disease resistance locus, as candidates for local adaptation events.Our results underscore the importance of population-specific, non-equilibrium demographic processes in patterning diversity within A. lyrata. Moreover, our extensive dataset provides an important resource for future molecular population genetic studies of local adaptation in A. lyrata