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Abstract Previous work has proposed various mechanisms by which the environment may affect the emergence of linguistic features. For example, dry air may cause careful control of pitch to be more effortful, and so affect the emergence of linguistic distinctions that rely on pitch such as lexical tone or vowel inventories. Criticisms of these proposals point out that there are both historical and geographic confounds that need to be controlled for. We take a causal inference approach to this problem to design the most detailed test of the theory to date. We analyse languages from the Bantu language family, using a prior geographic–phylogenetic tree of relationships to establish where and when languages were spoken. This is combined with estimates of humidity for those times and places, taken from historical climate models. We then estimate the strength of causal relationships in a causal path model, controlling for various influences of inheritance and borrowing. We find no evidence to support the previous claims that humidity affects the emergence of lexical tone. This study shows how using causal inference approaches lets us test complex causal claims about the cultural evolution of language. 

Witchcraft beliefs are historically and geographically widespread, but little is known about the cultural inheritance processes that may explain their variation between populations. A core component of witchcraft belief is that certain people (‘witches’) are thought to harm others using supernatural means. Various traits, which we refer to as the ‘witchcraft phenotype’ accompany these beliefs. Some can be classified as ‘symbolic culture’, including ideas about the typical behaviour of witches and concepts such as familiars (witches’ magical helpers), and demographic traits such as the age and sex of those likely to be accused. We conducted an exploratory study of the cultural evolution of 31 witchcraft traits to examine their inferred ancestry and associations with historic population movements. We coded a dataset from ethnographic accounts of Bantu and Bantoid-speaking societies in sub-Saharan Africa (N = 84) and analysed it using phylogenetic comparative methods (PCMs). Our results estimate that while some traits, such as an ordeal to test for witchcraft, have deep history, others, such as accusations of children, may have evolved more recently, or are limited to specific clusters of societies. Demographic and symbolic cultural traits do not typically co-evolve. Our findings suggest traits have different transmission patterns, and these may result from benefits they provide or from universal psychological mechanisms that produce their recurrent evolution. 

Abstract Spatially resolved transcriptomics technologies enable the measurement of transcriptome information while retaining the spatial context at the regional, cellular or sub-cellular level. While previous computational methods have relied on gene expression information alone for clustering single-cell populations, more recent methods have begun to leverage spatial location and histology information to improve cell clustering and cell-type identification. In this study, using seven semi-synthetic datasets with real spatial locations, simulated gene expression and histology images as well as ground truth cell-type labels, we evaluate 15 clustering methods based on clustering accuracy, robustness to data variation and input parameters, computational efficiency, and software usability. Our analysis demonstrates that even though incorporating the additional spatial and histology information leads to increased accuracy in some datasets, it does not consistently improve clustering compared with using only gene expression data. Our results indicate that for the clustering of spatial transcriptomics data, there are still opportunities to enhance the overall accuracy and robustness by improving information extraction and feature selection from spatial and histology data.