Jornal de Filogenética e Biologia Evolutiva

Evolutionary patterns of languages and organisms have surprising similarity, as Darwin famously captured by what he termed as “Curious Parallelism.” While traditional comparative and historical linguistic methods such as detailed analysis of cognate correspondences reveal similarities between languages and group them into linguistic families like how Carl Linnaeus grouped organisms into taxonomical hierarchies based on overall similarity-an approach known as phenetic clustering, this will not help to answer such as “when did Proto-Dravidian split to Proto-South Dravidian and Proto-South-Central Dravidian?” and so on. Conventional methods for dating linguistic trees such as glottochronology are severely flawed such that these have now been largely discredited. Proposed in this invited editorial is the direct extension of the molecular clock hypothesis and time-calibration techniques of molecular phylogenetics to the field of phylolinguistics. For ‘calibration checkpoints’, ancient dated texts, as well as dated and reliable historical information (such as Cro-Magnon migration to Europe, etc.), can be employed. Also deliberated here is a call to make use of Maximum Parsimony-based approaches for the ancient character-state reconstruction, for reconstructing long-lost languages.

Background: Species with planktonic larvae are more likely to show temporal genetic variation, due to differences in larval mortality and dispersal ability. The shanny Lipophrys pholis is a typical benthic rocky intertidal fish with its dispersion limited to a long larval stage. In contrast, the sand smelt Atherina presbyter has a very short planktonic life, small size and weak swimming capabilities, which translates into reduced dispersion potential.

Methods: A total of 226 shanny specimens (collected in 2003, 2013 and 2014) and 281 sand smelts (collected in 2005, 2012, 2013 and 2014) were screened for genetic variation using the mitochondrial control region. Genealogies, genetic diversities, temporal structures and contemporary effective population sizes were assessed.

Results: Haplotype networks showed deep genealogies with multiple levels of diversification and no temporal structure. Genetic diversity indices showed little variation among sampling periods and were generally high. For L. pholis significant genetic differentiation was detected between 2013 and 2014, while no significant differences were detected between sampling periods in A. presbyter. The shanny showed lower effective population size per generation when compared to the sand smelt (which yielded lack of evidence for genetic drift for the first two periods of the study).

Conclusion: These results highlight the fact that temporal changes in the gene pool composition need to be considered when evaluating population structure, especially for species with long pelagic larval dispersion, more vulnerable to fluctuations in the recruitment.