Systematic Biology

Phylogenetic network inference methods are increasingly used to detect hybridization and gene flow from genomic data, but their robustness to common sources of model violation remains poorly characterized. We conducted a simulation study to evaluate the effects of hidden paralogy and substitution rate variation on two widely used network inference methods: find_graphs from ADMIXTOOLS 2 and SNaQ. Using an eight-taxon species tree calibrated from an empirical reptile phylogeny, we simulated data under various levels of hidden paralogy (from none to strong) and three levels of rate variation (none, gene-specific, and lineage-specific). We found that hidden paralogy had limited impact on network inference under the conditions examined: both network methods correctly favored a tree without reticulation, and ASTRAL recovered the correct species tree every time. In contrast, lineage-specific rates severely biased find_graphs, inflating worst f-statistic residuals well beyond the standard acceptance threshold. SNaQ correctly selected a tree model almost always across all conditions, though its network with h = 1 reticulation displayed the true species tree with a lower probability under lineage-specific rates. We also show that the standard worst residuals threshold of 3 for find_graphs produces inflated type I error even without rate variation, and we recommend empirical calibration of this threshold within each study system.

Forest trees pose numerous potential challenges to phylogenomic inference. Their large effective population sizes and relatively long generation times lead to deep allele coalescence and consequently incomplete lineage sorting (ILS), which biases inferences of divergence times toward older ages and introduces gene tree discordance. Deep phylogenetic divergences, reaching back into the Paleocene, introduce reference-mapping biases. Introgression--the movement of genes between lineages--may result in different phylogenies being inferred depending on which individuals are included in analysis, even if the plurality of the genome favors the divergence history unaffected by introgression. These factors influence phylogenetic inference across the Tree of Life but are particularly prevalent in forest trees. Oaks (Quercus) are notable for all three influences. In addition, our knowledge of the oak phylogeny is currently based strongly on restriction site associated DNA sequencing (RADseq) datasets published over the past decade, which may introduce additional sources of uncertainty. In this chapter, we analyze a 322-species RADseq dataset and genome resequencing data from across the genus to address sources of uncertainty in our understanding of the global oak phylogeny, which we hope will serve as a model for other research groups working on comparable woody plant groups.

The order Atheriniformes (silversides, rainbowfishes, and blue-eyes) is a globally distributed group of fishes with frequent evolutionary transitions between marine and freshwater ecosystems. However, understanding the tempo and mode of these transitions has been hampered by poor phylogenetic resolution and limited taxonomic sampling, particularly within the suborder Atherinoidei. We generated a phylogenomic dataset of 1,100 exon loci for 150 species to resolve interfamilial relationships and reconstruct the groups biogeographic history. We were also able to incorporate a large number of existing GenBank sequences, producing a phylogeny with 265 species sampled for at least some genetic data (67% of known species diversity). While the New World suborder Atherinopsidae is well-resolved, we found that the family Atherinidae is polyphyletic across all analyses. We propose a revised classification that restricts Atherinidae to the genus Atherina and recognizes Atherinomoridae and Craterocephalidae as separate families. Our biogeographic inferences using explicit geographic areas suggests more frequent marine-to-freshwater transitions than previously inferred with simplified binary (marine vs. freshwater) coding, and uncover habitat transitions where marine ancestors may have gone extinct. These results highlight how explicit geographic modeling can uncover marine ancestry erased by extinction, providing a robust phylogenetic framework for future evolutionary studies of Atheriniformes.

Models of genome evolution often account for different evolutionary rates at different genome positions due to, e.g., varying selective pressures or mutation rates. Recent evidence from millions of publicly shared SARS-CoV-2 genomes has revealed a more complex mutational landscape than can be modeled with existing approaches. Here, mutation rates are in fact not only highly position-specific, as currently modeled, but also nucleotide-specific; for example, specific mutations can occur very often at certain determined genome positions, while at the same positions other mutations might not be highly recurrent. Here, we propose and investigate a general model of genome evolution where each genome position is allowed to evolve under an independent, non-normalized substitution rate matrix describing site-specific rates of all mutation types ("Site-Specific Matrix" model, or SSM). We implement SSM in the efficient pandemic-scale phylogenetic inference software CMAPLE. Large-scale genomic epidemiological simulations suggest that, given enough data, SSM can accurately infer position- and nucleotide-specific substitution rates for more frequently observed nucleotides (typically the reference nucleotide), while other rates require higher levels of divergence. Simulations also show that SSM has a modest impact on the accuracy of phylogenetic tree estimation. We use SSM to analyze the evolution of millions of SARS-CoV-2 genomes and observe substantial mismatches between the substitution rates of classical rate variation models and our SSM estimates. These results suggest that classical models of rate variation are inadequate for modeling site-specific mutation patterns and that SSM is a useful alternative for large-scale genome analyses.

Computational workshops are common in evolutionary biology and are used to share discipline-specific tools and skills with researchers. Despite the perceived importance of these workshops, there is no common set of criteria for workshop success, and there are few peer-reviewed studies investigating the efficacy of workshops or assessing the value of particular instructional techniques in this context. Here, we focused on one key element of a successful workshop: its ability to increase participants motivation to use the methods and tools presented during the workshop. We analyzed the goals, perceptions, and future plans of research practitioners engaging in a workshop on phylogenetic methods of historical biogeography using pre- and post-workshop surveys. Overall, the workshop was successful at motivating participants, and survey responses provided insights into participants perceptions of different activities, including "participatory live coding". Apart from this case study, we aim to highlight the importance of developing a common set of workshop goals in collaboration with other workshop stakeholders and the need for specialized, validated tools for assessing the efficacy of computational workshops for researchers.

Understanding how global biodiversity patterns arise is a central theme of biogeography, with contemporary theory recognising the roles of both dispersal and vicariance. Genera that are broadly distributed can provide important systems for disentangling the relative influence of these processes across evolutionary timescales. However, many lesser-studied groups, particularly those in the tropics, lack a densely sampled phylogeny which hinders robust inference of their evolutionary and biogeographic history. This study investigates the global diversification and systematics of the putative pantropical moth genus Parasa Moore (Lepidoptera: Limacodidae), with the aim of assessing the relative importance of dispersal and vicariance in shaping its distribution. Medium-coverage whole genome sequencing of specimens predominantly from museum collections were used to generate a globally sampled time-calibrated phylogeny of Parasa and associated genera (the Parasa-complex). Ancestral range estimation analyses were employed to infer geographical origins and possible dispersal times between bioregions. The Parasa-complex originated in Africa in the late Oligocene ([~]24 Ma) and, through a series of long-distance dispersal events during the early-mid Miocene, expanded into Asia ([~]23 Ma) and the Americas ([~]21 Ma). Across all regions, dispersal was the dominant process shaping present-day distributions, with a limited role of vicariance in some subregions. Phylogenetic analyses further demonstrated that Parasa is not monophyletic, with multiple independent lineages contributing to its apparent pantropical distribution. These findings highlight a central role of long-distance dispersal in generating certain global distributions. The results support a dynamic model of range evolution involving rapid Miocene dispersal and subsequent regional diversification. In addition, the non-monophyly of Parasa requires substantial taxonomic revision, underscoring the importance of robust phylogenetic frameworks for interpreting global biodiversity patterns.

Hybridisation between species was once considered a relatively uncommon occurrence but is now recognised to occur frequently across many different taxa. It can result in homogenisation of previously distinct forms, a potential conservation issue, but can also act as a catalyst for diversification through introgression and sharing of favourable genes. Repeated rounds of island colonisation followed by speciation result in secondary sympatry, with the potential for hybridisation between early and late arrivers. In the southwest Pacific, this situation has arisen in the avian family Zosteropidae (the white-eyes). Here we use whole genome sequencing of live birds and historical specimens to characterise hybridisation between three white-eye species on Norfolk Island: two island endemics, Zosterops tenuirostris and the now-extinct Zosterops albogularis, and Zosterops lateralis, which colonised the island in 1904. Despite over two million years of divergence between Z. lateralis and the two endemics, we provide genomic evidence of their hybridisation. First, we confirm the identities of three Z. lateralis x Z. tenuirostris hybrids and additionally identify one Z. lateralis x Z. albogularis hybrid. We also report asymmetric, genome-wide introgression from both endemics into Z. lateralis, with introgressed regions enriched for a range of potential functions. However, despite this introgression, species boundaries have been maintained, and the extant endemic Z. tenuirostris does not appear to be at risk of genetic extinction. Our work additionally demonstrates an unusual case of recent ghost introgression from the extinct Z. albogularis into Z. lateralis. This study sheds light on the genomic outcomes of secondary sympatry and its potential consequences for single-island endemics.

Pattersons D statistic, also known as the ABBA-BABA statistic, is widely used to detect the presence of archaic genome-wide introgression between two non-sister taxa. Requiring only a single lineage from each of four taxa where one taxon acts as an outgroup to determine the ancestral allele, Pattersons D, counts the imbalance between the number of biallelic sites where either the second and third taxa (ABAB site) or the first and third taxa (BABA site). When there is no introgression, these counts are expected to be equal, and a discordance between counts suggests introgression from the third taxon into either the first or second. Pattersons D is limited to the detection of genome-wide introgression and exhibits a high false-positive rate when applied to smaller genomic segments. Here, we present a new method, D STatistic with Allelic Rarefaction (D*), to address these limitations. D* uses multiple lineages and does not require an outgroup to calculate the imbalance between the number of alleles found exclusively in the second and third taxa and the number of alleles found exclusively in the first and third taxa. D* employs a rarefaction technique to correct for unequal sample-size and allows multiallelic sites. We use simulations to show that D* has better precision and recall for detecting introgressed segments of DNA when compared to similar methods under a wide variety of model parameters and in the presence of technical artifacts common to ancient DNA analyses. We conclude with an analysis of Denisovan DNA introgression in modern day Papuans. Precompiled executables, the manual, and source code can be found at https://github.com/TQ-Smith/DSTAR

The TKF92 model of molecular evolution--a linear birth-death process for indels, with finite-state continuous-time Markov chain substitutions--is exchangeable in residue identity at every site: the generative process treats amino acids symmetrically, conditional on a single substitution rate matrix. To introduce local heterogeneity, evolutionary models are often equipped with site-class mixtures, preserving this symmetry in the sense of de Finetti: conditional on the latent class, residues are still exchangeable. In a four-step theoretical ladder, we show how long-range structure such as couplings between distant sites can also be introduced exchangeably by using a Dirichlet process to partition sites into co-evolving classes. Our first step is a thorough analysis of TKF92 to establish sufficient statistics, limiting behavior, and inferential tools. We then lift the pairwise TKF92 hidden Markov model, in the limit of small time, to a time-indexed gravestone-augmented pair stochastic context-free grammar, and from there to its phylogenetic generalisation. This framing allows trajectories to be sampled exactly by Inside-Outside recursion. The third step places a Dirichlet process over the alive sites and asks co-keyed sites to evolve under a sparse Potts interaction -- an exchangeably-partitioned hidden direct-coupling model whose marginal alignment likelihood is unchanged from plain TKF92. The fourth rung of the ladder develops inference machinery: a Gibbs-Metropolis sampler that alternates alignment resamples, key-partition resamples, and stochastic parameter updates. We close several gaps along the way -- exact closed-form sufficient statistics for the linear birth-death-immigration component, the resolvable LHopital limit at{lambda} =, and a closed-form M-step for a recursive generalisation of TKF92 -- and we report a 1,000-family Pfam fit with K=4 site classes whose Potts atoms carry [~]0.54 nats of covariation per class-pair on top of a substantial single-site substitution model. Supplementary material, including full source code for inference, may be found at https://tkfdp.net/.

This investigation aimed at compiling all phylogenetic lineages within and around genus Cyanoboletus. The evolutionary inference obtained from the nuclear ribosomal genes internal transcribed spacer region (ITS) suggests that part of the species currently classified in Cyanoboletus belong in lineages separate from the genus, thus suggesting a narrower boundary that includes only the species that develop a strong staining reaction to touch and to air exposure of the context. The separate lineages are the monotypic Cupreoboletus genus and a few species that do not develop such reaction, which are part of a clade together with genera Cacaoporus and Acyanoboletus, thus broadening the concept of Cacaoporus to encompass all of them. The emerging 3C perspective of Cupreoboletus, Cacaoporus and Cyanoboletus offers a remarkably consistent morphological diagnosis, overcoming the problems of a too broad concept for Cyanoboletus. This work reveals that Boletus neotropicus, B. novae-zelandiae and B. sensibilis belong respectively in Cyanoboletus, Cacaoporus and Lanmaoa, and by studying multigene alignment concatenates it identifies lineages that probably represent undescribed species: at least four in Cacaoporus and at least five in Cyanoboletus. Diagnostic tables and dichotomic keys are presented by geographic region. The present work also includes a study of the phylogenetic position of Neoboletus flavosanguineus, a species once classified in Cyanoboletus. The complexity of assigning species epithets in some lineages is addressed, namely for the boundaries between Cacaoporus instabilis and Ca. fagaceophilus as well as the diversity under the names Cyanoboletus sinopulverulentus and Cy. pulverulentus. The overall picture of evolutionary lineages sets a framework for the choice of reference data that can provide, in future phylogenetic studies that involve the 3C, a balanced and efficient coverage. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/724631v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@7f618corg.highwire.dtl.DTLVardef@dd6a14org.highwire.dtl.DTLVardef@5f7399org.highwire.dtl.DTLVardef@9e7443_HPS_FORMAT_FIGEXP M_FIG C_FIG

Mosquitoes are classified into two subfamilies, each monophyletic, and typically considered to both be ancient, having diverged more than 100 million years ago based on previous divergence analyses. A recent publication challenged this view with phylogenomic results primarily from the third codon position and UCEs. Utilizing alternative fossil placement and these phylogenomic data, these authors find that the Culicidae and Chaoboridae diverged in the lower Cretaceous, and that one mosquito subfamily, the Anophelinae, is nested within the Culicinae. These results are in stark contrast to previous results from diverse data sources, ranging from other genomic data, to morphology, to fossils. Here, we briefly detail the substantial evidence that supports two monophyletic subfamilies of extant mosquitoes, along with fossil evidence that supports the ancient divergence of these lineages.

Arthropods exhibit an exceptional diversity of life histories, where developmental modes involve moulting stage progressions with changes ranging from the bare minimal to the dramatically transformative. While this variability drives many research questions aiming to understand evolutionary and developmental underpinnings of life history differences, it can complicate comparative analyses across taxa. However, this can be approached by applying a framework that defines metamorphosis as a post-embryonic stage progression characterised by substantial changes in morphology and adaptive landscape. Employing this framework with a phylogenomic dataset spanning 26 orders and encompassing four independently arising metamorphic lineages, we explore gene repertoire evolutionary dynamics potentially associated with metamorphosis in Pancrustacea. The approach contrasts gene family evolutionary dynamics inferred to have occurred in the last common ancestors of the metamorphic Insecta, Copepoda, Eucarida, and Thecostraca, with those of their sister lineages, as well as of descendent and ancestral nodes. The results reveal that the metamorphosis ancestors are characterised by an elevated number of gene family births and expansions. Expanded gene families share a set of commonly enriched biological processes across all metamorphosis ancestors, suggesting functional convergence by independent evolution of distinct gene families involved in embryonic and post-embryonic development and nervous system differentiation. Evolutionary modelling further highlights a subset of these families exhibiting signatures of adaptive, lineage-specific gene family size increases associated with metamorphic development. These families include genes implicated in neural and sensory development, segmentation, and moulting. These findings support a model of the evolution of pancrustacean metamorphosis where distinct gene families from a common functional toolkit expand and are co-opted into facilitating transitions to multi-phasic life cycles. This reframes the role of moulting in arthropod diversification to be recognised as an important reservoir of genetic change that can potentiate truly remarkable life history transitions.

Animal weapons are ecologically important traits that mediate contests over limiting resources and can strongly influence survival and reproduction. Weapon traits often exhibit substantial intraspecific morphological diversity, raising questions about the ecological drivers of this variation. Acrorhagi are weapons produced by sea anemones that are used in intraspecific territorial encounters. Although acrorhagial morphology varies widely within species, patterns of intraspecific variation remain poorly characterized, and the extent to which such variation reflects differences in local intraspecific competition is unclear. Here, we conduct morphometric analyses to characterize within-population variation and allometry in acrorhagial traits of the solitary anemone Anthopleura sola. We show that these traits covary with habitats differing in conspecific density. The number of acrorhagi scaled positively with body size, and individuals occupying a high-density habitat tended to possess more acrorhagi than did similar sized individuals from a low-density habitat. In addition, anemones from high-density habitats exhibited longer acrorhagial cnidae, a pattern that was not explained by differences in body size or acrorhagial density. Together, these results suggest that competitive context influences weapon-related traits at multiple levels of biological organization, potentially via phenotypic plasticity or selective processes. More broadly, our findings highlight how fine-scale ecological variation may contribute to the maintenance of trait diversity within and across species.

Immunoglobulin genes are a central component of jawed-vertebrate adaptive immunity. A previous study showed that the blunt-snouted clingfish Gouania willdenowi lacks immunoglobulin genes and T-cell receptor gamma/delta loci, while retaining T-cell receptor alpha/beta genes, MHC genes, and RAG1 /RAG2. Here I extend that observation to the family Gobiesocidae using all seven chromosome-level Gobiesocidae genome assemblies currently available. Manual tblastn and synteny-guided searches found no convincing immunoglobulin heavy-chain or light-chain loci in G. willdenowi, Gouania pigra, Gobiesox punctulatus, Apletodon dentatus, Lepadogaster candolii, Lepadogaster purpurea, or Diplecogaster bimaculata. Thus, the absence of antibody genes is best interpreted as a root-level character of clingfishes. The latest seven-species screen of 40 additional immune-associated genes shifts the broader interpretation in the same direction: the B-cell/adaptive core genes CD79A, CD79B, CIITA, TNFRSF13B, and TNFSF13B lack strong tblastn support in all sampled Gobiesocidae, and 37 of the 40 tested targets show an all-zero binary pattern at the presence threshold. Only IL21R.1, TYROBP, and TNFRSF11A show strong hits in one or more species. I therefore interpret the principal immune-gene erosion as occurring at or near the Gobiesocidae root rather than as a recent Gouania-specific process, while keeping weak, paralog-sensitive, and patchy loci provisional. RAG2 comparisons show a shared Gobiesocidae PHD-domain C-to-S replacement in the zinc-binding motif, with apparently intact RAG2 coding sequence. A family-wide TRG/TRD screen did not recover TRGV V segments or accepted TRDC constant-region exons, but it did detect TRGC-like constant exons in several genomes. These TRGC-like sequences are probably not canonical TRG constant exons without further validation, so I treat the gamma/delta system as eroded or rearranged rather than as a complete root-level loss equivalent to the Ig loss. The RAG2 variant provides a plausible molecular context for antigen-receptor remodeling, but it is not evidence that RAG genes are pseudogenized, because TCR alpha/beta, MHC genes, and RAG1 /RAG2 are retained. Gobiesocidae are therefore best described as a vertebrate family with ancestral loss of canonical immunoglobulin genes and associated root-level erosion of B-cell and immune-related genes, not as a lineage lacking adaptive immunity in its entirety. HighlightsO_LISeven chromosome-level Gobiesocidae genomes lack convincing canonical IgH and IgL loci. C_LIO_LIThe strongest non-Ig losses map to the B-cell/adaptive core: CD79A, CD79B, CIITA, TNFRSF13B, and TNFSF13B. C_LIO_LITCR alpha/beta, MHC genes, and RAG1 /RAG2 are retained, so Gobiesocidae should not be described as lacking adaptive immunity in full. C_LIO_LIA shared Gobiesocidae RAG2 PHD-domain C-to-S variant provides candidate molecular context for antigen-receptor remodeling. C_LI

Target enrichment methods have provided unprecedented advances in phylogenomics. Targeting hundreds of conserved regions has proven to be a good tradeoff between cost and efficiency, while being useful for museomics and diversified non-model clades. Unfortunately, current methods used for identifying such regions involve high degrees of conservation within targeted elements, usually pushing researchers to rely on flanking data with little guarantee for homology. With a growing number of high quality genomes available throughout the Tree of Life emerges new opportunities to improve marker selection. In this study, we introduce GABBI, a new method for designing target capture probes by taking advantage of genome alignments, avoiding the selection of a single reference genome that can cause notable biases. We compare GABBI-derived markers to the most commonly used probe design method, PHYLUCE, at two taxonomic scales, the weevil superfamily Curculionoidea and the tribe Pachyrhynchini. At both taxonomic scales, results show that our new method allows identifying more variable loci that prove to be more phylogenetically resolutive than the PHYLUCE-derived ones. Doing so, we provide the first probe set specifically designed for weevils, targeting a wide set of 4,255 shared homologous regions, encouraging future research on systematics and macroevolution of one of the most diverse and economically important groups of insects. By providing GABBI as an automated and open-access pipeline, we hope to open new probe design opportunities to other taxonomic groups that face similar phylogenetic obstacles.

Eye loss has long fascinated evolutionary biologists and occurs across the animal kingdom. Spiders have two parallel visual systems -- two primary and six secondary eyes -- but eye losses, leaving six, four, two, or no eyes, have occurred in multiple lineages. Despite their significance, reports of eye loss are scattered, limiting broader analysis. Here we present the first comprehensive analysis of eye loss across all known spider lineages. We show that eye loss occurs in [~]12% of extant species, mainly within the clade Synspermiata. Six-eyed spiders are most common (>5,300 species), while four-eyed, two-eyed, and eyeless forms are rarer and often linked to troglobitic lifestyles. Principal eye loss is widespread, occurring in 49 families across nearly all major lineages. Using a recent phylogeny of the order Araneae, we demonstrate a strong correlation between eye loss and occupancy of low-light environments, but this is complicated by differential effects across eye types and phylogenetic groups through geological time. These findings reveal striking lability in eye number and lay groundwork for future research into ecological, developmental, and neurological drivers of eye loss. [hidden Markov models, ancestral state reconstruction, Araneae, discrete character evolution, principal eyes, secondary eyes, low light environments].

Sexual selection is a major evolutionary force, yet its demographic consequences remain unclear. While experimental studies often report positive effects of sexual selection on traits linked to population performance, comparative studies often find null or negative associations with population persistence. One explanation for this discrepancy is that the demographic consequences of sexual selection depend on ecological context, particularly variation in mortality and fecundity. Here, we used six decades of abundance data and test whether sexual selection predicts population trends across 738 bird species from Europe and North America. We quantify sexual selection using complementary proxies capturing different components of sexual selection: mating system, sexual dichromatism, sexual size dimorphism and relative testes mass. We further assess whether the effect of sexual selection in population trends is mediated by mortality and fecundity. Across all proxies, we found no evidence that sexual selection is associated with population trends. This result is consistent across continents and robust to variation in mortality and fecundity. Our findings suggest that, despite its central role in shaping phenotypic evolution, sexual selection does not translate into consistent effects on long-term population trends at macroecological scales. More broadly, these results highlight a potential disconnect between evolutionary processes and population dynamics.

AO_SCPLOWBSTRACTC_SCPLOWThe stochastic simulation algorithm (SSA) is widely used to perform exact forward simulation of discrete stochastic processes in biology. However, the computational cost, driven by sequential event-by-event sampling across large ensembles, remains a computational barrier. We investigate whether reduced-precision floating-point arithmetic can accelerate SSA without degrading statistical fidelity, drawing on the success of reduced-precision methods in weather and climate modelling. We evaluate two strategies across five canonical models (birth-death, Schlogl, Telegraph, dimerisation, repressilator): (i) mixed precision, computing propensities in 16-bit while maintaining accumulators in 32-bit; and (ii) uniform precision, performing all arithmetic in 16-bit. Mixed-precision SSA produces ensemble statistics that closely match the 64-bit reference for all models, as measured by Kolmogorov-Smirnov tests and Wasserstein distances. Under uniform precision, deterministic rounding introduces systematic biases across several models, with catastrophic failures in some cases. Stochastic rounding (SR) and propensity normalisation eliminate these biases, restoring distributional fidelity across all models tested (KS p > 0.05). Our results establish mixed-precision SSA with SR as a viable acceleration strategy for mathematical biology: 16-bit formats shrink per-variable data size by 2-4x relative to fp32/fp64, yielding comparable reductions in memory footprint and up to ~ 1.5x wall-clock speedup on CPU hardware that lacks native 16-bit arithmetic. As a hardware-level acceleration, mixed-precision SSA complements algorithmic methods such as tau-leaping and maps naturally onto modern GPU and TPU architectures with native 16-bit arithmetic.

Innovation of the avian beak has facilitated a grand radiation of >11,000 species, with vast morphological disparity suggesting limited developmental constraints on beak diversification. We assess four macroevolutionary currencies - integration, disparity, phenotypic evolutionary rates, and ecological specialization - using 3D beak landmarks for 8,627 species mapped to a complete avian supertree with a resolved genomic backbone. We introduce a Gini coefficient-based metric of ecological specialization, measuring evolutionary time spent across trophic niches. Phylogenetic regressions show that lineages with faster phenotypic rates exhibit stronger beak integration (landmark covariation) and more generalised diets, while beak disparity declines with greater trophic specialization. These results suggest that integration facilitates, rather than constrains, phenotypic evolution, by channeling variation along lines of least resistance. Future work should explore modular structure of the bird beak, which arises from multiple genetic and developmental factors.

AO_SCPLOWBSTRACTC_SCPLOWSerological assays remain the standard experimental approach for estimating the cumulative incidence of a pathogen and monitoring population immunity. The predominant approach for analysing serum titration data from virus neutralisation assays uses a nearly century-old interpolation-based method which neglects inherent imperfections in the assay and produces estimates with no measure of uncertainty. We introduce a two-part Bayesian modelling framework to estimate the underlying antibody concentrations in the raw serum samples taken from serosurveyed individuals, to improve the interpretation of serological data over age. First, we develop a mechanistic Bayesian model for serum antibody titration data that estimates latent antibody concentrations while accounting for assay variability and quantifying uncertainty. Second, we propagate this uncertainty into an age-structured serocatalytic model by integrating over posterior draws of individual antibody concentrations, allowing joint inference on latent serostate membership, force of infection, and serological waning rate. We use this framework to explore the dynamics of infection and immunity for three enterovirus serotypes: enteroviruses A71 (EV-A71) and D68 (EV-D68) and coxsackievirus A6 (CVA6). These serotypes are leading causes of outbreaks of severe respiratory illness and hand, foot, and mouth disease. Applying these approaches to three cross-sectional serosurveys, we estimated consistently higher and more persistent antibody concentrations throughout life for EV-D68 compared to EV-A71 and CVA6. Our analysis suggests that the proportion of recently infected individuals (i.e. individuals with high estimated antibody concentration levels given their age) peaks around 25% by age 7 years for both EV-A71 and CVA6 before gradually declining with age. In contrast, for EV-D68 the inferred proportion of the population in the infected state exceeds 50% by age 9 years and continues to grow with age. We also estimate that EV-D68 antibody concentration levels are higher than those of the other two serotypes, with the force of infection estimated to be highest in early childhood and declining more gradually with age than for EV-A71 and CVA6. These estimates are different to previous estimates found in the literature. Our inferential framework uncovers the wide-ranging variation in antibody levels that are often obscured by conventional endpoint titre estimation methods. We demonstrate that our framework can infer infection rates without relying on predetermined seropositivity cut-offs and without making explicit assumptions of virus-specific infection mechanisms. Author summarySerological tests measure antibody levels in blood to show how widely a virus has spread and how well populations are protected. Titre-based tests dilute blood samples in steps, mix these dilutions with virus, and add the mixture to living cells; the titre is the highest dilution where antibodies still protect cells from infection. Traditional analyses overlook test imperfections. We present a new two-part Bayesian framework to estimate antibody levels and track age-related exposure to infection. First, we estimate underlying antibody concentrations while accounting for uncertainty, then use these estimates in another model to infer age-specific transmission of three common viruses - EV-A71, EV-D68, and CVA6. Our results show that EV-D68 infections may be more common, especially in children, compared to the other viruses. This new approach provides a clearer picture of the dynamics of seroconversion, without relying on arbitrary thresholds, helping to improve public health monitoring and responses.