Cecere, J. G. | bioRxiv Science

bioRxiv2026

The BEAC, an epigenetic clock for birds

Epigenetic clocks are powerful tools for estimating both chronological and biological age, enabling the integration of age information into population monitoring, demographic modelling, and research on the ecophysiology and evolution of ageing. Most epigenetic clocks so far have been developed for mammals: here, we present the Bird Epigenetic Ageing Clock (BEAC) for estimating chronological age in avian species. BEAC was established based on genome-wide enzymatic methylation sequencing data of known-age king penguins (Aptenodytes patagonicus), and validated in nine other bird species. The BEAC collects age-informative signals into a bisulfite amplicon sequencing panel of 24 primer pairs, providing a highly accurate and cost-effective alternative to sequencing-intensive approaches. It achieved strong predictive performance in independent king penguin training (R{superscript 2}=0.88; MAE=1.7 years, n=78) and testing data (R{superscript 2}=0.79; MAE=2.3 years, n=41), with negligible batch effects, high longitudinal consistency, and resilience to reduced sample size or missing loci. Importantly, cross-species validation across 180 samples showed that BEAC reliably captures age-associated methylation signals in nine additional bird species across seven clades, demonstrating that a single set of loci can be predictive of ageing across multiple different bird species. BEAC offers a flexible, empirically validated tool and a transferable framework for developing epigenetic clocks in avian species, providing a highly valuable resource for eco-evolutionary studies of ageing in wild species.

molecular biology↗

bioRxiv2019

A data-driven method to locate nest sites and estimate reproductive outcome from avian telemetry data

Recursive movement patterns have been used to detect behavioral structure within individual movement trajectories in the context of foraging ecology, home-ranging behavior, and predator avoidance. Some animals exhibit movement recursions to locations that are tied to reproductive functions, including nests and dens; while existing literature recognizes that, no method is currently available to explicitly target different types of revisited locations. Moreover, the temporal persistence of recursive movements to a breeding location can carry information regarding the fate of breeding attempts, but it has never been used as a metric to quantify recursive movement patterns. Here, we introduce a method to locate breeding attempts and estimate their fate from GPS-tracking data of central place foragers. We tested the performance of our method in three bird species differing in breeding ecology (wood stork (Mycteria americana), lesser kestrel (Falco naumanni), Mediterranean gull (Ichthyaetus melanocephalus)) and implemented it in the R package nestR. We identified breeding sites based on the analysis of recursive movements within individual tracks. Using trajectories with known breeding attempts, we estimated a set of species-specific criteria for the identification of nest sites, which we further validated using non-reproductive individuals as controls. We then estimated individual nest survival as a binary measure of reproductive fate (success, corresponding to fledging of at least one chick, or failure) from nest-site revisitation histories during breeding attempts, using a Bayesian hierarchical modeling approach that accounted for temporally variable revisitation patterns, probability of visit detection, and missing data. Across the three species, positive predictive value of the nest-site detection algorithm varied between 87-100% and sensitivity between 88-92%, and we correctly estimated the fate of 86-100% breeding attempts. By providing a method to formally distinguish among revisited locations that serve different ecological functions and introducing a probabilistic framework to quantify temporal persistence of movement recursions, we demonstrated how the analysis of recursive movement patterns can be applied to estimate reproduction in central place foragers. Beyond avian species, the principles of our method can be applied to other central place foraging breeders such as denning mammals. Our method estimates a component of individual fitness from movement data and will help bridge the gap between movement behavior, environmental factors, and their fitness consequences.

ecology↗