Latest Articles

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  Section: Evolutionary Biology ; Topics: Evolution, Population biology, Genetics/genomics

  The geometry of gametic dispersal in a flying mammal, Rhinolophus hipposideros

  Brazier, Thomas;   Zarzoso-Lacoste, Diane;   Lehnen, Lisa;   Jan, Pierre-Loup;   Puechmaille, Sebastien J.;   Petit, Eric J.  

  10.24072/pcjournal.811 - Peer Community Journal, Volume 6 (2026), article no. e107

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  Dispersal influences population and evolutionary dynamics, in a manner that depends on by which dispersal strategies gene flow occurs. In some species, mating partners move exclusively for mating, dispersing genes but not individuals. This is the case in many bat species, of which the lesser horseshoe bat (Rhinolophus hipposideros) shows a genetic structure at a fine spatial scale suggesting restricted dispersal. We investigated how natal and mating dispersal shape gene flow in this species in two metapopulations using paternity and population assignments. Half of the inferred paternities were intra-colonial and gave an estimate of the mean mating dispersal distance of around 11 km, explaining the observed genetic structure. Complete gametic dispersal distances were further estimated by combining natal with mating dispersal distances. The resulting gametic dispersal kernels showed a mean distance of around 20 km and a fat-tailed distribution typical of an excess of long-distance dispersal movements. It is the first time that natal and mating dispersal distances have been separately estimated and then combined in animals, documenting quantitatively how mating dispersal decorrelates gene and individual flows. It is important to consider this mechanism to explain dispersal evolution.

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  Section: Ecotoxicology & Environmental Chemistry ; Topics: Environmental sciences

  Combination of instrumental and biomonitoring approaches elucidate the contributions of multiple and contrasted sources of atmospheric exposure to polycyclic aromatic hydrocarbons

  Reuillard, Mathilde; Dron, Julien;   Durand, Amandine;   Gandolfo, Adrien;   Wortham, Henri; Wafo, Emmanuel; Austruy, Annabelle

  10.24072/pcjournal.813 - Peer Community Journal, Volume 6 (2026), article no. e106

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  A combined approach was implemented to investigate the origins of elevated PAH concentrations in a complex urban environment where numerous emission sources coexist. This approach integrated one year of atmospheric measurements  PM10 filters and continuous atmospheric monitoring), alongside lichen biomonitoring and soil analyses. Results revealed diffuse multi-source contamination, characterized by high PAH levels in both soils and lichens, with a major contribution from the resuspension of soil particles from contaminated brownfields. Pronounced seasonal variations, particularly in winter, reflected the influence of residential heating, with a minor and local contribution from agricultural stubble-burning. Current industrial and port activities were also identified as significant contributors notably through fine particle. The integration of these complementary spatial and temporal approaches enable the ranking of source as follows: (i) resuspension of contaminated soil particles, (ii) industrial and maritime emissions, (iii) residential heating, and (iv) stubble-burning. Combining biomonitoring with atmospheric monitoring provides a robust methodology for characterizing PAH exposure in complex multi-exposure atmospheric contexts, and for guiding environmental health risk management.

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  Section: Statistics & Machine Learning ; Topics: Statistics

  On Nonparanormal Likelihoods

  Hothorn, Torsten  

  10.24072/pcjournal.814 - Peer Community Journal, Volume 6 (2026), article no. e105

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  Nonparanormal models describe the joint distribution of multivariate responses via latent Gaussian, and thus parametric, copulae while allowing flexible nonparametric marginals. Some aspects of such distributions, for example conditional independence, are formulated parametrically. Other features, such as marginal distributions, can be formulated non- or semiparametrically. Such models are attractive when multivariate normality is questionable but interpretability paramount. Most estimation procedures perform two steps, first estimating the nonparametric part. The copula parameters come second, treating the marginal estimates as known. This is sufficient for some applications. For other applications, e.g. when a semiparametric margin features parameters of interest or when standard errors are important, a simultaneous estimation of all parameters might be more advantageous. We present suitable parameterisations of nonparanormal models, possibly including semiparametric effects, and define four novel nonparanormal log-likelihood functions. In general, the corresponding one-step optimisation problems are shown to be non-convex. In some cases, however, biconvex problems emerge. Several convex approximations are discussed. From a low-level computational point of view, the core contribution is the score function for multivariate normal log-probabilities computed via Genz’ procedure. As a demonstration for the versatility of the theoretical and computational framework, we present a series of nonparanormal models for transformation discriminant analysis when some biomarkers are subject to limit-of-detection problems. Possible empirical gains of full maximum likelihood estimation compared to two-step approaches are illustrated in a simulation study targeting semiparametric efficient polychoric correlation analysis where a theoretical benchmark is available.

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  Section: Evolutionary Biology ; Topics: Evolution, Ecology, Paleontology

  prepR4pcm: An R package for preparing data and trees for phylogenetic comparative methods

  Nakagawa, Shinichi;   Ortega, Santiago;   Mizuno, Ayumi;   Santos, Eduardo S. A.;   Lagisz, Malgorzata;   Jain, Bhavya;   Celeste, Jimuel Jr;   Poo Hernandez, Sergio  

  10.24072/pcjournal.809 - Peer Community Journal, Volume 6 (2026), article no. e104

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  Phylogenetic comparative methods require species names in a trait dataset to match tip labels in a phylogenetic tree. Yet this apparently simple prerequisite is often one of the most fragile steps in a comparative workflow. Names may differ because of, for example, formatting, taxonomic revisions, synonyms, or spelling errors. If these differences are resolved informally, species can be lost from analyses, and the reasons for their loss can be difficult to reconstruct. Here, we present $\texttt{prepR4pcm}$, an R package for preparing data and trees for phylogenetic comparative methods. The package reconciles species names through a staged procedure: exact matching, normalised matching, synonym lookup with local taxonomic databases, and optional fuzzy matching for likely spelling errors. Each decision is stored in a reconciliation object with the original name, matched name, match type, confidence score, and a short explanation. This object turns name matching from a hidden preprocessing step into an auditable part of the analysis. $\texttt{prepR4pcm}$ also supports the points where comparative workflows need human judgement. Users can inspect unresolved names, accept or reject suggested matches, add manual corrections, apply taxonomy crosswalks (which link names across taxonomic systems), compare reconciliation runs, and generate reports. The package then returns a matched data frame and pruned tree with the same species set, ready for phylogenetic generalised least squares, phylogenetic mixed models, phylogenetic meta-analysis, and related workflows. If users do not yet have a tree, $\texttt{prepR4pcm}$ can retrieve trees from several sources, date trees when suitable information is available, and format tree-source citations. We illustrate the workflow using bundled datasets with realistic name mismatches. $\texttt{prepR4pcm}$ is available at the CRAN (Comprehensive R Archive Network) with documentation and vignettes covering data and tree reconciliation, tree retrieval, multi-tree workflows, and phylogenetic meta-analysis.