BIDS’ researchers Alex de Siqueira and Stéfan van der Walt have been working with a team of researchers from London’s Natural History Museum and the University of Southampton to analyze over 180,000 photographed specimens from the Natural History Museum’s digitized butterfly collections in order to evaluate the impacts of climate change.
To analyze this expansive collection of images, de Siqueira and Van der Walt developed Mothra, a computer vision pipeline that automatically detects a specimen’s orientation, scale, wing measurements, and other biological features. Computer vision is a rapidly evolving field in which computers are programmed to identify and measure information from digital images or video. The new Mothra pipeline significantly minimized the time and effort needed to conduct research and analysis that would otherwise require researchers to physically measure and record the data manually. The results from this study indicate that there was a near-perfect relationship between Mothra and manual measurements.
Collected measurements and meta-data are paired with temperature records to test how various traits vary with environmental factors during different stages of development. To date, the most common findings suggest that adult butterfly body size increases with temperature during the late larval stages of development. The study highlights the value of digitizing natural history specimens in order to improve our understanding of how different species respond to changing climate and other environmental factors.
Alongside museums’ digitization efforts, and the increased availability of open access datasets, technological advancements in computer vision are enabling researchers to work more effectively and collaboratively, and to conduct research more efficiently and rapidly – and these aspects are contributing significantly to collective efforts to conserve species and mitigate the impacts of climate change both on local and global scales.
According to Van der Walt, “The open source scientific Python ecosystem made it possible to rapidly develop software which accurately and automatically analyses digital specimens, an otherwise laborious manual process. The international collaboration also benefited from being a small, cross-disciplinary team--having both field and software expertise. We are delighted that the research is based around open data and software, allowing others to verify and build upon our work.”
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Rebecca J. Wilson, Stephen J. Brooks, Benjamin W. Price, Lea M. Simon, Phillip B. Fenberg, Alexandre Fioravante de Siqueira, Stéfan J. van der Walt