Research Project
Full description 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 analytical framework for the analysis of colour patterns in nature through the eyes of non-human observers. However, its large 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 provide a robust and comprehensive batch script that allows users to automate large parts of QCPA workflows. We further provide a set of useful R scripts for downstream data extraction and analysis. We believe these scripts will empower users to exploit the full analytical power of QCPA and facilitate the development of customised semi-automated workflows. Such quantitatively scaled workflows are crucial for the exploration of colour pattern space and the development of ever-richer models of visual perception in animals other than humans. These advances will, in turn, facilitate the testing of hypotheses on the function and evolution of vision and signals, which are otherwise computationally unfeasible.