The spread of agriculture in Iberia through Approximate Bayesian Computation and Neolithic projectile tools

In the present article we use geometric microliths (a specific type of arrowhead) and Approximate Bayesian Computation (ABC) in order to evaluate possible origin points and expansion routes for the Neolithic in the Iberian Peninsula. In order to do so, we divide the Iberian Peninsula in four areas (Ebro river, Catalan shores, Xúquer river and Guadalquivir river) and we sample the geometric microliths existing in the sites with the oldest radiocarbon dates for each zone. On this data, we perform a partial Mantel test with three matrices: geographic distance matrix, cultural distance matrix and chronological distance matrix. After this is done, we simulate a series of partial Mantel tests where we alter the chronological matrix by using an expansion model with randomised origin points, and using the distribution of the observed partial Mantel test’s results as a summary statistic within an Approximate Bayesian Computation-Sequential Monte-Carlo (ABC-SMC) algorithm framework. Our results point clearly to a Neolithic expansion route following the Northern Mediterranean, whilst the Southern Mediterranean route could also find support and should be further discussed. The most probable origin points focus on the Xúquer river area.

The PAU survey: measurement of narrow-band galaxy properties with approximate bayesian computation

Narrow-band imaging surveys allow the study of the spectral characteristics of galaxies without the need of performing their spectroscopic follow-up. In this work, we forward-model the Physics of the Accelerating Universe Survey (PAUS) narrow-band data. The aim is to improve the constraints on the spectral coefficients used to create the galaxy spectral energy distributions (SED) of the galaxy population model in Tortorelli et al. 2020. In that work, the model parameters were inferred from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) data using Approximate Bayesian Computation (ABC). This led to stringent constraints on the B-band galaxy luminosity function parameters, but left the spectral coefficients only broadly constrained. To address that, we perform an ABC inference using CFHTLS and PAUS data. This is the first time our approach combining forward-modelling and ABC is applied simultaneously to multiple datasets. We test the results of the ABC inference by comparing the narrow-band magnitudes of the observed and simulated galaxies using Principal Component Analysis, finding a very good agreement. Furthermore, we prove the scientific potential of the constrained galaxy population model to provide realistic stellar population properties by measuring them with the SED fitting code CIGALE. We use CFHTLS broad-band and PAUS narrow-band photometry for a flux-limited (i < 22.5) sample of galaxies up to redshift z ∼ 0.8. We find that properties like stellar masses, star-formation rates, mass-weighted stellar ages and metallicities are in agreement within errors between observations and simulations. Overall, this work shows the ability of our galaxy population model to correctly forward-model a complex dataset such as PAUS and the ability to reproduce the diversity of galaxy properties at the redshift range spanned by CFHTLS and PAUS.

Parapatric speciation with recurrent gene flow of two sexual dichromatic pheasants

Background: Understanding speciation has long been a fundamental goal of evolutionary biology. It is widely accepted that speciation requires an interruption of gene flow to generate strong reproductive isolation between species, in which sexual selection may play an important role by generating and maintaining sexual dimorphism. The mechanism of how sexual selection operated in speciation with gene flow remains an open question and the subject of many research. Two species in genus Chrysolophus, Golden pheasant (C. pictus) and Lady Amherst's pheasant (C. amherstiae), which both exhibit significant plumage dichromatism, are currently parapatric in the southwest China with several hybrid recordings in field. Methods: In this research, we estimated the pattern of gene flow during the speciation of two pheasants using the Approximate Bayesian Computation (ABC) method based on the multiple genes data. With a new assembled de novo genome of Lady Amherst's pheasant and resequencing of widely distributed individuals, we reconstructed the demographic history of the two pheasants by pairwise sequentially Markovian coalescent (PSMC). Results: The results provide clear evidence that the gene flow between the two pheasants were consistent with the prediction of isolation with migration model for allopatric populations, indicating that there was long-term gene flow after the initially divergence (ca. 2.2 million years ago), and further support the secondary contact when included the parapatric populations since around 30 ka ongoing gene flow to now, which might be induced by the population expansion of the Golden pheasant in late Pleistocene. Conclusions: The results of the study support the scenario of speciation between Golden pheasant (C. pictus) and Lady Amherst's pheasant (C. amherstiae) with cycles of mixing-isolation-mixing due to the dynamics of natural selection and sexual selection in late Pleistocene that provide a good research system as evolutionary model to test reinforcement selection in speciation. Keywords: Golden pheasant (Chrysolophus pictus), Lady Amherst's pheasant (Chrysolophus amherstiae), speciation, gene flow, Approximate Bayesian Computation (ABC), Pairwise Sequentially Markovian coalescent (PSMC).