Didham, Raphael K., Basset., Yves, Collins, C. Matilda, Leather, Simon R., Littlewood, Nick A., Menz, Myles H.M., Müller, Jörg, Packer, Laurence, Saunders, Manu E., Schönrogge, Karsten, Stewart, Alan J.A., Yanoviak, Stephen P., and Hassall, Christopher (2020) Interpreting insect declines: seven challenges and a way forward. Insect Conservation and Diversity, 13 (2). pp. 103-114.

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Abstract

Many insect species are under threat from the anthropogenic drivers of global change. There have been numerous well-documented examples of insect population declines and extinctions in the scientific literature, but recent weaker studies making extreme claims of a global crisis have drawn widespread media coverage and brought unprecedented public attention. This spotlight might be a double-edged sword if the veracity of alarmist insect decline statements do not stand up to close scrutiny.

We identify seven key challenges in drawing robust inference about insect population declines: establishment of the historical baseline, representativeness of site selection, robustness of time series trend estimation, mitigation of detection bias effects, and ability to account for potential artefacts of density dependence, phenological shifts and scale-dependence in extrapolation from sample abundance to population-level inference.

Insect population fluctuations are complex. Greater care is needed when evaluating evidence for population trends and in identifying drivers of those trends. We present guidelines for best-practise approaches that avoid methodological errors, mitigate potential biases and produce more robust analyses of time series trends.

Despite many existing challenges and pitfalls, we present a forward-looking prospectus for the future of insect population monitoring, highlighting opportunities for more creative exploitation of existing baseline data, technological advances in sampling and novel computational approaches. Entomologists cannot tackle these challenges alone, and it is only through collaboration with citizen scientists, other research scientists in many disciplines, and data analysts that the next generation of researchers will bridge the gap between little bugs and big data.

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