Use of 3-Dimensional Videography as a Non-Lethal Way to Improve Visual Insect Sampling

Abstract

Insects, the most diverse and abundant animal species on the planet, are critical in providing numerous ecosystem services which are significant to the United Nation’s Sustainable Development Goals (UN-SDGs). In addition to the UN-SDGs, the UN has declared the period 2021–2030 as the “Decade on Ecosystem Restoration.” Insects, because of the ecosystem services they provide, are critical indicators of restoration success. While the importance of insects in providing ecosystem services and their role in helping fulfil the UN-SDGs is recognized, traditional techniques to monitor insects may result in observer bias, high rates of type-I and type-II statistical error, and, perhaps most alarmingly, are often lethal. Since insects are critical in maintaining global food security, contribute to biological control and are a key food source for higher trophic levels, lethal sampling techniques which may harm insect populations are undesirable. In this study, we propose a method to visually sample insects which involves non-lethal 3-dimensional video cameras and virtual reality headsets. A total of eight observers viewed video captured insects visiting floral resources in a landscaped area on a university campus. While interobserver variability existed among individuals who partook in this study, the findings are similar to previous visual sampling studies. We demonstrate a combination of 3D video and virtual reality technology with a traditional insect count methodology, report monitoring results, and discuss benefits and future directions to improve insect sampling using these technologies. While improving quantitative monitoring techniques to study insects and other forms of life should always be strived for, it is a fitting time to introduce non-lethal sampling techniques as preservation and restoration of biodiversity are essential components of the UN-SDGs and the “Decade on Ecosystem Restoration”.

Keywords

• 360-degree data capture
• biodiversity
• conservation
• ecological restoration
• environmental monitoring
• pollinators