Delivering on a promise: futureproofing automated insect monitoring methods

Abstract

Due to rapid technological innovations, the automated monitoring of insect assemblages comes within reach. However, this continuous innovation endangers the methodological continuity needed for calculating reliable biodiversity trends in the future. Maintaining methodological continuity over prolonged periods of time is not trivial, since technology improves, reference libraries grow and both the hard- and software used now may no longer be available in the future. Moreover, because data on many species are collected at the same time, there will be no simple way of calibrating the outputs of old and new devices. To ensure that reliable long-term biodiversity trends can be calculated using the collected data, I make four recommendations: (1) Construct devices to last for decades, and have a five-year overlap period when devices are replaced. (2) Construct new devices to resemble the old ones, especially when some kind of attractant (e.g. light) is used. Keep extremely detailed metadata on collection, detection and identification methods, including attractants, to enable this. (3) Store the raw data (sounds, images, DNA extracts, radar/lidar detections) for future reprocessing with updated classification systems. (4) Enable forward and backward compatibility of the processed data, for example by in-silico data ‘degradation’ to match the older data quality. This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.

Towards a toolkit for global insect biodiversity monitoring

“…As a first step towards achieving this goal, Roy et al [ 42 ] discuss metadata standards for hardware and image analysis. With the continued development of hardware and analytical algorithms, rigorous metadata recording will be fundamental for future trend analyses and, possibly, reprocessing of (historic) images [ 43 ].…”

“…Still, even when methodological standards have been agreed upon, the continued development of each of the technologies poses a real challenge for the standardized quantification of EBV's, especially over long time periods. Van Klink [ 43 ] proposes strategies to ensure the usefulness of the collected data for future trend calculations.…”