Biology subjects

Blasi, D. E.

Publications and source records attributed to Blasi, D. E..

5 recordsLinked to original sources

bioRxiv2026

Repertoire-wide contextual mapping reveals signal functions in cooperatively breeding crows

Communication structures society, and is likewise shaped by relationships and shared tasks; yet, for most socially complex species, we know little of their full vocal repertoire and its functions. We investigated how communication structures the who, what, and when of social interactions in cooperative carrion crows - group-living birds who rely on coordinated behaviors, as in chick care. Leveraging machine learning to integrate large-scale data from crow-borne audio-loggers and nest cameras, we charted the vocal repertoire across 24 cooperative groups and mapped all discovered call types to behaviors and social context. We found that crows used a rich repertoire across three domains of joint behavior - flocking, chick care, and territorial display. Relatively quiet call types were abundant and included close-range calls that may coordinate chick care by announcing nest visits. Our study demonstrates how combining continuous-capture data and machine learning can reveal a holistic understanding of how vocalizations function across contexts.

animal behavior and cognition↗

bioRxiv2024

Global patterns of genetic admixture reveal effects of language contact

When speakers of different languages are in contact, they often borrow features like sounds, words, or syntactic patterns from one language to the other, but the lack of historical data has hampered estimation of this effect at a global scale. We break out of this impasse by using genetic admixture as a proxy for population contact. We find that language pairs whose speaker populations underwent genetic admixture or that are located in the same geo-historical area share more features than others, suggesting borrowing. The effect varies strongly across features, partly following expectations from differences in lifelong learnability, partly responding to differences in social imbalances during contact. Additionally, we find that for some features, admixture decreases sharing. This likely reflects signals of divergence (schismogenesis) under contact.

evolutionary biology↗

bioRxiv2021

Reconstructing hunter-gatherer planet Earthusing machine-learning

Estimating the total human population size (i.e., abundance) of the preagricultural planet is important for setting the baseline expectations for human-environment interactions if all energy and material requirements to support growth, maintenance, and well-being were foraged from local environments. However, demographic parameters and biogeographic distributions do not preserve directly in the archaeological record. Rather than attempting to estimate human abundance at some specific time in the past, a principled approach to making inferences at this scale is to ask what the human demography and biogeography of a hypothetical planet Earth would look like if populated by ethnographic hunter-gatherer societies. Given ethnographic hunter-gatherer societies likely include the largest, densest, and most complex foraging societies to have existed, we suggest population inferences drawn from this sample provide an upper bound to demographic estimates in prehistory. Our goal in this paper is to produce principled estimates of hunter-gatherer abundance, diversity, and biogeography. To do this we trained an extreme gradient boosting algorithm (XGBoost) to learn ethnographic hunter-gatherer population densities from a large matrix of climatic, environmental, and geographic data. We used the predictions generated by this model to reconstruct the hunter-gatherer biogeography of the rest of the planet. We find the human abundance of this world to be 6.1{+/-}2 million with an ethnolinguistic diversity of 8,330{+/-}2,770 populations, most of whom would have lived near coasts and in the tropics. Significance StatementUnderstanding the abundance of humans on planet Earth prior to the development of agriculture and the industrialized world is essential to understanding human population growth. However, the problem is that these features of human populations in the past are unknown and so must be estimated from data. We developed a machine learning approach that uses ethnographic and environmental data to reconstruct the demography and biogeography of planet Earth if populated by hunter-gatherers. Such a world would house about 6 million people divided into about 8,330 populations with a particular concentration in the tropics and along coasts.

ecology↗

bioRxiv2020

Languages, evolution and statistics: human sound systems were shaped by changes in bite configuration. Response to Tarasov & Uyeda (2020)

In Blasi et al. (2019) we have shown, through a series of statistical analyses and models, that human sound systems have been affected by a transition in bite configuration starting from the Neolithic. Tarasov and Uyeda (2020) (henceforth T&U) raise a number of observations in relation to our article. We appreciate T&Us engagement with our work and their sharing of the code and data of the analyses reported. In brief, their technical comment involves five analyses: O_LIBinomial Causal Models (BCM) C_LIO_LILinear Regression of across-area variation in labiodentals and subsistence C_LIO_LIPredictive Posterior Simulations (PPS) C_LIO_LIPoisson Linear Regression (PLR): model comparison C_LIO_LIPhylogenetic Analyses C_LI In what follows, we show that the discrepancies they report between our findings and theirs are due mostly to ill-specified models, weak (or missing) statistical evidence, and a misinterpretation of our results. After these issues are addressed, we conclude that T&Us claims do not hold.

evolutionary biology↗

bioRxiv2019

Exploring deep-time relationships between cultural and genetic evolution in Northeast Asia

Culture evolves in ways that are analogous to, but distinct from, genomes. Previous studies examined similarities between cultural variation and genetic variation (population history) at small scales within language families, but few studies empirically investigated such parallels across language families using diverse cultural data. We report an analysis comparing culture and genomes from in and around Northeast Asia spanning 11 language families. We extract and summarize the variation in language (grammar, phonology, lexicon), music (song structure, performance style), and genomes (genome-wide SNPs) and test for correlations. We find that grammatical structure correlates with population history. Recent contact and shared descent fail to explain the signal, suggesting relationships that arose before the formation of current families. Our results suggest that grammar might be a cultural indicator of population history, while also demonstrating differences among cultural and genetic relationships that highlight the complex nature of human history.

evolutionary biology↗