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-hum...

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Veröffentlicht in:Evolutionary ecology Jg. 38; H. 3; S. 387 - 397
Hauptverfasser: van den Berg, Cedric P., Condon, Nicholas D., Conradsen, Cara, White, Thomas E., Cheney, Karen L.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 01.06.2024
Springer
Springer Nature B.V
Schlagworte:
animal behavior
Animal Ecology
animals
Automation
Batch processing
Biomedical and Life Sciences
Color
Coloration
Data analysis
data collection
Ecology
Equipment and supplies
Evolution
Evolutionary Biology
Image analysis
Image processing
Information processing
Life Sciences
Mechanization
Methodology
Pattern analysis
phenotypic variation
Phenotypic variations
Plant Sciences
Technology application
vision
Visual perception
ImageJ
Visual ecology
Java
R software
Automation
Animal colouration
ISSN:0269-7653, 1573-8477
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Zusammenfassung: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.
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ISSN:0269-7653
1573-8477
DOI:10.1007/s10682-024-10291-7