ctSpyderFields: A Python package for visual field reconstruction in spiders

1The measurement of visual fields in arachnology has a long-standing history. Given the wide variety of eye positions, orientation and structure, the topic is fundamental for studies of taxonomy, evolution, ecology and behavior. The existing methods for measuring visual fields deploy ophthalmoscopic measurements, which require custom microscopes, anatomical structures like the reflective tapetum, which may not always be present, or the capacity to detect photoreceptor autofluorescence. Here we present the ctSpyderFields python package: a tool for geometrically predicting the visual fields of arachnids from digital images of the lens and retina. The tool uses images coming from computed tomography (CT) scans of specimens, but could be applied to other 3D microscopy techniques, to virtually project the boundaries of the retina through the geometrically predicted nodal point of the lens, deriving a rough per-eye visual field both in cartesian and spherical coordinates. The extracted data can then be used to calculate likely visual field overlap between eyes and angular spans, which can be compared within or between species. We also provide a use case, reporting the visual field data extracted from a museum specimen of Philaeus crysops. We propose that the tool will allow a wider comparative analysis of visual fields across spider species, unlocking the potential for a deeper understanding of visual ecology and evolution.