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Rapid photogrammetry of morphological traits of free‐ranging moths
Author(s) -
Mungee Mansi,
Athreya Ramana
Publication year - 2020
Publication title -
ecological entomology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.865
H-Index - 81
eISSN - 1365-2311
pISSN - 0307-6946
DOI - 10.1111/een.12907
Subject(s) - ranging , photogrammetry , biology , computer vision , remote sensing , artificial intelligence , computer science , ecology , geography , telecommunications
Photogrammetric studies of free‐ranging animals are limited to mammals and birds. Recent advances in insect photogrammetry, including 3D imaging, are entirely associated with museum specimens. We present a rapid, simple, accurate, and inexpensive morphometric method targeting thousands of free‐ranging insects attracted to light screens using images taken without collecting a specimen or even constraining the individual in any manner. A reference grid printed on the screen is used to calibrate the images for shape and size without prior knowledge of the camera‐subject configuration. The method requires only inexpensive, off‐the‐shelf, consumer equipment, and freely available programming ( R statistical language) and image processing ( ImageMagick ) tools. We demonstrate the efficacy of the method using a dataset of 3675 images of free‐ranging hawkmoths (Lepidoptera:Sphingidae) imaged in natural repose on a screen. We show that this method introduces no bias and has a high degree of correspondence with traditional morphometry using collected specimens. We also propose error metrics, which quantify the calibration quality and identify images with poor data. Although this method is particularly suited for the hyperdiverse moth community, which dominates the dynamics of many terrestrial ecosystems, it can be used for other phototropic taxa identifiable on an image to (morpho)‐species. It will help in accumulating reliable trait data from hundreds of thousands of individual insects without any expenditure on specimen collection. It is particularly suited for studies which require multi‐epoch, multi‐locate sampling like investigations into ecosystem stability, climate change, and community assembly.