Towards a toolkit for global insect biodiversity monitoring

Abstract

Insects are the most diverse group of animals on Earth, yet our knowledge of their diversity, ecology and population trends remains abysmally poor. Four major technological approaches are coming to fruition for use in insect monitoring and ecological research—molecular methods, computer vision, autonomous acoustic monitoring and radar-based remote sensing—each of which has seen major advances over the past years. Together, they have the potential to revolutionize insect ecology, and to make all-taxa, fine-grained insect monitoring feasible across the globe. So far, advances within and among technologies have largely taken place in isolation, and parallel efforts among projects have led to redundancy and a methodological sprawl; yet, given the commonalities in their goals and approaches, increased collaboration among projects and integration across technologies could provide unprecedented improvements in taxonomic and spatio-temporal resolution and coverage. This theme issue showcases recent developments and state-of-the-art applications of these technologies, and outlines the way forward regarding data processing, cost-effectiveness, meaningful trend analysis, technological integration and open data requirements. Together, these papers set the stage for the future of automated insect monitoring. This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’.

Monitoring aerial insect biodiversity: a radar perspective

“…Radar-based approaches are increasingly considered for monitoring aerial insect biodiversity and EBVs. The greatest advantages and unique selling points of radars are that they run autonomously, over medium to large spatial and temporal scales and are a non-invasive, non-destructive observation method, providing information on all aerial organisms [ 90 ]. Furthermore, the radar infrastructure is—at least for weather radars—already existing, and using their data for applications beyond meteorology would provide added societal value [ 91 ].…”

“…Their technology makes it inherently hard to identify species—a feature that has long precluded radars from the traditional biodiversity monitoring toolbox. However, ecological research increasingly depends on using disparate data sources (with unique strengths in spatial extent, taxonomic resolution and biases), providing an opportunity to integrate radar-based approaches with other monitoring approaches [ 90 ]. Radars can deliver unique information on insect EBVs that complements other approaches, and their use is expanding with promising current developments—from developments in radar technology that measure more features of aerial objects, machine learning and neural network algorithms that use these novel features to improve taxonomic classification, harmonization of data across radar systems and integration with other data sources, to efforts in providing data infrastructure for improved availability and access.…”

Sharing insect data through GBIF: novel monitoring methods, opportunities and standards

“…Incomplete reference databases are an issue for other novel insect monitoring methods as well [ 24 ]. Reference databases for computer vision are incomplete [ 25 ], and reference databases for acoustic monitoring of insects are less complete than vertebrate reference databases [ 26 ].…”

Invertebrate responses to rewilding: a monitoring framework for practitioners

“…The use of new technologies could revolutionize and upscale monitoring of invertebrates for rewilding practitioners, increasing the adaptability of the framework and allowing coverage of taxonomic groups currently absent from or challenging to cover in monitoring schemes, despite their acknowledged importance for ecosystem functioning (van Klink et al 2024). Examples of relevant technology include the use of computer vision and deep learning to identify individuals (Blair et al 2020;Bjerge et al 2021), applications on smartphones to facilitate widespread and robust data capture by citizen scientists, robots to sort and identify samples (Ärje et al 2020), and remote cameras to assess species interaction networks and ecosystem services (Alison et al 2022).…”