Automated workflows using Quantitative Colour Pattern Analysis (QCPA): a guide to batch processing and downstream data analysis.

Animal and plant colouration presents a striking dimension of phenotypic variation, the study of which has driven general advances in ecology, evolution, and animal behaviour. Quantitative Colour Pattern Analysis (QCPA) is a dynamic framework for analysing colour patterns through the eyes of non-human observers. However, its extensive array of user-defined image processing and analysis tools means image analysis is often time-consuming. This hinders the full use of analytical power provided by QCPA and its application to large datasets. Here, we offer a robust and comprehensive batch script, allowing users to automate many QCPA workflows. We also provide a complimentary set of useful R scripts for downstream data extraction and analysis. The presented batch processing extension will empower users to further utilise the analytical power of QCPA and facilitate the development of customised semi-automated workflows. Such quantitatively scaled workflows are crucial for exploring colour pattern spaces and developing ever-richer frameworks for analysing organismal colouration accounting for visual perception in animals other than humans. These advances will, in turn, facilitate testing hypotheses on the function and evolution of vision and signals at quantitative and qualitative scales, which are otherwise computationally unfeasible. Supplementary Information: The online version contains supplementary material available at 10.1007/s10682-024-10291-7.

Causes of variability in estimates of mutational variance from mutation accumulation experiments.

Characteristics of the new phenotypic variation introduced via mutation have broad implications in evolutionary and medical genetics. Standardized estimates of this mutational variance, VM, span 2 orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogeneity using 2 approaches. First, meta-analyses of ∼150 estimates of standardized VM from 37 mutation accumulation studies did not support a difference among taxa (which differ in mutation rate) but provided equivocal support for differences among trait types (life history vs morphology, predicted to differ in mutation rate). Notably, several experimental factors were confounded with taxon and trait, and further empirical data are required to resolve their influences. Second, we analyzed morphological data from an experiment in Drosophila serrata to determine the potential for unintentional heterogeneity among environments in which phenotypes were measured (i.e. among laboratories or time points) or transient segregation of mutations within mutation accumulation lines to affect standardized VM. Approximating the size of an average mutation accumulation experiment, variability among repeated estimates of (accumulated) mutational variance was comparable to variation among published estimates of standardized VM. This heterogeneity was (partially) attributable to unintended environmental variation or within line segregation of mutations only for wing size, not wing shape traits. We conclude that sampling error contributed substantial variation within this experiment, and infer that it will also contribute substantially to differences among published estimates. We suggest a logistically permissive approach to improve the precision of estimates, and consequently our understanding of the dynamics of mutational variance of quantitative traits.

Digest: More than just a pretty fin: The evolution of sexual ornaments in killifish.

What conditions favor the evolution of elaborate sexual ornaments? In freshwater killifishes, Sowersby et al. found that larger sexual ornaments were negatively associated with locomotive performance. Although selection clearly favored large ornamental fins in environments with fewer predators, there was no clear association between large ornamental fins and differences in life-history strategy. This finding illustrates that habitat differences in predation risk have the potential to influence the evolution of secondary sexual traits such as ornaments through natural selection.

Repeatability of locomotor performance and morphology-locomotor performance relationships.

There is good evidence that natural selection drives the evolution of locomotor performance, but the processes that generate the among-individual variation for selection to act on are relatively poorly understood. We measured prolonged swimming performance, Ucrit, and morphology in a large cohort (n=461) of wild-type zebrafish (Danio rerio) at ∼6 months and again at ∼9 months. Using mixed-model analyses to estimate repeatability as the intraclass correlation coefficient, we determined that Ucrit was significantly repeatable (r=0.55; 95% CI: 0.45-0.64). Performance differences between the sexes (males 12% faster than females) and changes with age (decreasing 0.07% per day) both contributed to variation in Ucrit and, therefore, the repeatability estimate. Accounting for mean differences between sexes within the model decreased the estimate of Ucrit repeatability to 21% below the naïve estimate, while fitting age in the models increased the estimate to 14% above the naïve estimate. Greater consideration of factors such as age and sex is therefore necessary for the interpretation of performance repeatability in wild populations. Body shape significantly predicted Ucrit in both sexes in both assays, with the morphology-performance relationship significantly repeatable at the population level. However, morphology was more strongly predicative of performance in older fish, suggesting a change in the contribution of morphology relative to other factors such as physiology and behaviour. The morphology-performance relationship changed with age to a greater extent in males than females.