Christopher Richard Cooney

Fine-grained localisation of plumage regions is a prerequisite for computational analyses of avian colouration, patterning and visual traits in ecological and evolutionary research. Progress is limited by the scarcity of image resources with annotations aligned to biologically meaningful anatomical units: existing avian benchmarks provide either landmark points or coarse part categories that do not capture ornithologically defined plumage regions. We present a curated dataset of 4,705 bird images annotated for nine plumage regions: head, throat, breast, belly, vent, back, coverts, remiges and tail. Spanning 39 avian orders and 222 families, the dataset provides a taxonomically broad resource for fine-grained avian image analysis. The dataset was built through an iterative model-assisted annotation workflow, in which model predictions were reviewed and corrected rather than drawn from scratch, improving the efficiency of region-level annotation. We benchmark classical segmentation architectures, SAM-based models and self-supervised foundation-model encoders on this task. A frozen DINOv3 encoder with a lightweight decoder achieved the highest performance on the held-out test set, reaching 84.01% mean Intersection over Union while requiring substantially less memory than end-to-end fine-tuning. The model generalised to external avian benchmarks, including the bird subset of PartImageNet and CUB-200-2011, and achieved competitive performance on the full PartImageNet part-segmentation benchmark, which includes diverse animal taxa. We provide a modular detect-track-segment pipeline as a proof-of-concept extension to video data. Together, these results show that anatomically grounded avian annotations can serve both as a resource for plumage phenotyping and as a benchmark for efficient, transferable biological part segmentation. Author Summary: Birds vary enormously in colour and pattern, but studying this variation at large scales requires more than identifying the bird in a photograph. Researchers often need to know where each colour or pattern occurs on the body, such as on the head, throat, breast, wing or tail. We created PlumageParts to make this kind of region-level analysis easier. The dataset contains 4,705 bird images annotated into nine biologically meaningful plumage regions, covering a wide range of bird families and orders. To build the dataset efficiently, we used a model-assisted workflow in which computer-generated masks were checked and corrected by researchers rather than drawn entirely by hand. We then tested several image-segmentation approaches and found that a frozen self-supervised vision model, combined with a lightweight decoder, provided accurate plumage-region predictions while requiring relatively modest computing resources. The same approach also performed well on a broader animal part-segmentation benchmark, suggesting that it may be useful beyond birds when suitable annotations are available. By releasing the annotations, code and trained model, we aim to support future studies of bird plumage and biologically meaningful image segmentation.

Understanding reproductive isolation (RI) between lineages is a central goal of speciation research. While the strength of RI has been estimated across a broad range of taxa, synthesizing these data remains challenging, partially because we lack a common language for classifying and reporting RI estimates. Here, we present the Reproductive Isolation Ontology (RIO), a structured framework designed to standardize the classification of RI estimates across most sexually reproducing organisms. The RIO comprises 3 interrelated domains, each organized into a nested hierarchy of classification terms. We demonstrate the utility of this approach and call for researchers to adopt and expand the RIO to facilitate the integration of speciation research.

The impact of projected extinctions on global animal colour diversity remains unknown. Combining citizen science with self-supervised deep learning, we built novel representations of bird plumage colour patterning based on >125,000 museum specimen images covering 9,143 species. We demonstrate that losing currently threatened bird species will drive a disproportionate reduction in avian plumage diversity, with the most severe losses occurring in tropical and subtropical regions. Furthermore, while humans generally find non-typical plumage phenotypes more aesthetically attractive, threatened species are unexpectedly deemed less visually appealing despite their comparatively unusual plumages. Overall, our results highlight severe, imminent threats to the existing avian colourscape and raise critical questions about the future of animal colour diversity in a changing world.

Structural colour is widespread in animals, yet we know relatively little about its evolution and development. We shed light on the evolution of structural barbule colour (often referred to as iridescent structural colour) by describing feather nanostructures responsible for plumage colours in the cuckoos (family Cuculidae). The melanosomes found in feathers with structural barbule colour have specialized shapes: hollow rods, thin solid rods, hollow platelets or solid platelets. In contrast, it is often assumed that drably coloured feathers possess thick, rod-shaped melanosomes. We show that this assumption is unfounded in cuckoos. We describe structural barbule colour in the plumages of 126 cuckoo species and map its phylogenetic distribution. This reveals that structural barbule colour is widespread in cuckoos but has probably been lost several times. We then use transmission electron microscopy to describe the feather nanostructures of 21 cuckoo species. Surprisingly, the drab feathers of many cuckoo species contain melanosomes with specialized shapes. Thus, specialized melanosome shapes can be retained in the plumages of drab species, potentially making it easier for structural barbule colour to evolve again in the future. This discovery supports the idea that evolutionary history plays a key role in shaping the evolution of plumage colour diversity.

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.

The digitization of natural history specimens has unlocked opportunities for large-scale phenotypic trait analysis. In recent years, deep learning has shown significant results in accurately predicting annotations on 2D specimen photographs. However, it can be challenging for biologists without extensive related expertise to easily use deep learning. Here, we introduce PhenoLearn, a toolkit developed for biologists to generate annotations on 2D specimen images using deep learning. PhenoLearn integrates graphical user interfaces (GUIs) within its two main modules, PhenoLabel for image annotation and PhenoTrain for model training and prediction. GUIs increase accessibility and reduce the need for computational expertise, allowing biologists to intuitively go through a workflow of labelling training sets, using deep learning, and reviewing predictions in the same tool. We demonstrate PhenoLearn’s capabilities through a case study involving the segmentation of plumage areas on bird images, showcasing prediction accuracy and the running time with and without graphics processing unit, highlighting its potential to generate annotations with minimal computational cost and time. The toolkit’s modular design and flexibility ensure adaptability, allowing for integration with other tools amidst rapidly evolving deep learning approaches. PhenoLearn bridges the gap between specimen digitization and downstream analysis, providing biologists with broader access to deep learning. The source code, installation guides, tutorials with screenshots, and a small demo dataset for PhenoLearn can be found at https://github.com/echanhe/phenolearn.

Sporadically, genetic material that originates from an organelle genome integrates into the nuclear genome. However, it is unclear what processes maintain such integrations over evolutionary time. Recently, it was shown that nuclear DNA of mitochondrial origin (NUMT) may harbor genes with intact mitochondrial reading frames despite the fact that they are highly divergent from the host's mitochondrial genome. Two major hypotheses have been put forward to explain the existence of such mitocoding nuclear genes: (1) recent introgression from another species and (2) long-term selection. To investigate whether these intriguing possibilities play a role, we scanned the genomes of more than 1000 avian and mammalian species for NUMTs. We show that a subclass of divergent NUMTs harboring mitogenes with intact reading frames is widespread across mammals and birds. We also show that some of these NUMTs appear to be similar across species. In addition, we demonstrate that many mitochondrial-coding NUMTs exhibit signs of long-term selection. In a subset of these NUMT genes, we detected evolutionary signals consistent with adaptive evolution, including one human NUMT shared among seven ape species. These findings suggest that NUMT insertions may occasionally be functional.

A central role for sexual isolation in the formation of new species and establishment of species boundaries has been noticed since Darwin and is frequently emphasized in the modern literature on speciation. However, an objective evaluation of when and how sexual isolation plays a role in speciation has been carried out in few taxa. We discuss three approaches for assessing the importance of sexual isolation relative to other reproductive barriers, including the relative evolutionary rate of sexual trait differentiation, the relative strength of sexual isolation in sympatry, and the role of sexual isolation in the long-term persistence of diverging forms. First, we evaluate evidence as to whether sexual isolation evolves faster than other reproductive barriers during the early stages of divergence. Second, we discuss available evidence as to whether sexual isolation is as strong or stronger than other barriers between closely related sympatric species. Finally, we consider the effect of sexual isolation on long-term species persistence, relative to other reproductive barriers. We highlight challenges to our knowledge of and opportunities to improve upon our understanding of sexual isolation from different phases of the speciation process.

Structural coloration is widespread in animals, yet we know relatively little about its evolution and development. While previous studies have explored adaptive functions of structural color, a key gap is our lack of understanding of how historical contingency (path-dependency of biological processes) influences the loss and gain of this complex trait. We shed light on this question by describing feather nanostructures responsible for plumage colors in the cuckoos (family Cuculidae), a group with widespread occurrence of shiny, metallic plumage (metallic luster). The melanosomes found in feathers with metallic luster have specialized shapes: hollow rods, thin solid rods, hollow platelets, or solid platelets. In contrast, it is generally assumed that drably colored feathers possess thick, rod-shaped melanosomes. However, we uncover that this assumption is unfounded in cuckoos. We describe metallic luster in the plumages of 126 cuckoo species and map its phylogenetic distribution. This reveals that metallic luster is widespread in cuckoos but has likely been lost several times. We then use transmission electron microscopy to describe the feather nanostructures of 21 cuckoo species. Surprisingly, the drab feathers of many cuckoo species contain melanosomes with specialized shapes. We propose that historical contingency greatly influences nanostructure diversity in cuckoos. Specialized melanosome shapes can be retained in the plumages of drab species, potentially making it easier for metallic luster to evolve again in the future. This discovery supports the idea that historical contingency plays a key role in shaping the evolution of plumage color diversity.

Both pigmentary and structural colours share many common elements of their feather anatomy, i.e. keratin, air and melanin packed in the melanosomes, despite utilizing different mechanisms of the colour production. This means that evolutionary transitions between pigmentary and structural colours can be achieved through a simple adjustment of these elements. Recently, an evolutionary hypothesis for the transition between pigmentary grey, through slate and finally to structural blue colour has been proposed and confirmed in the clade Tanagers on a macroevolutionary level. Here, we investigate mechanistic basis of this evolutionary pathway. By using SAXS (small-angle X-ray scattering) we have quantified important elements of spongy layer in medullary cells that is crucial for colour production by coherent scattering of light wavelengths. We have quantified five elements of the spongy layer: nanostructure complexity, average hard block thickness, average soft block thickness, filling fraction and I _o value. We report that across different categories of feather colour, i.e. blue, slate and grey, nanostructure complexity, filling fraction and I _o value explained variation in the chromatic component of the colour (between the three colour categories). Chromatic variation within the colour category was explained by filling fraction in the case of slate colour and by nanostructure complexity and average hard block thickness in the case of blue colour. We propose that variation in different elements or combination of elements of the spongy nanostructure has been utilised in feather colour evolution, both within and between colour categories, to overcome developmental constraints imposed by self-assembly processes.