Accounting for year effects and sampling error  in temporal analyses of population and biodiversity change - Response to Seibold et al. 2019 “Arthropod decline in grasslands and forests is associated with landscape-level drivers”

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Authors

Gergana N. Daskalova, Isla H. Myers-Smith , Albert Phillimore 

Abstract

An accumulating number of studies are reporting severe biomass, abundance and/or species richness declines of insects (Hallmann et al., 2017; Lister & Garcia, 2018; Seibold et al., 2019; Sánchez-Bayo & Wyckhuys, 2019). Collectively these studies aim to quantify the net change in invertebrate populations and/or community composition over time and to establish whether such changes can be attributed to anthropogenic drivers (Macgregor, Williams, Bell, & Thomas, 2019; Saunders, Janes, & O’Hanlon, 2019; Thomas, Jones, & Hartley, 2019; Montgomery et al., 2020; van Klink et al., 2020). Seibold et al. 2019 analysed a dataset of arthropod biomass, abundance and species richness from forest and grassland plots in a region of Germany and report significant declines of up to 78% over the time period of 2008 to 2018 (Seibold et al., 2019). However, their analysis did not account for the confounding effects of temporal pseudoreplication of observations from the same years. We show that simply by including a year random effect in the statistical models and thereby accounting for the common conditions experienced by observations from proximal sites in the same years, four of the five reported declines become non-significant out of six tests overall. To place their estimated effect sizes and those of other recent studies of insect declines in a broader geographic context, we analysed invertebrate biomass, abundance and species richness over time from 640 time series from 1167 sites around the world. We found that the average trend across the terrestrial and freshwater realms was not significantly distinguishable from no net change. Shorter time series that are likely to be most affected by sampling error variance – such as those reported in Seibold et al. 2019 – yielded the most extreme estimates of decline or increase. We suggest that the uncritical media uptake of extreme negative trends from short time series may be serving to exaggerate the speed of "insect Armageddon" and could eventually undermine public confidence in biodiversity research. We advocate that future research include all available data and use model structures that account for uncertainties to build a more robust understanding of biodiversity change during the Anthropocene and its variation among regions and taxa (Kunin, 2019; Saunders et al., 2019; Thomas et al., 2019; Didham et al., 2020; Dornelas & Daskalova, 2020).

DOI

https://doi.org/10.32942/osf.io/cg3zs

Subjects

Biodiversity, Biology, Ecology and Evolutionary Biology, Life Sciences, Population Biology

Keywords

biodiversity change, ecology, global change ecology, population change, Statistical models, temporal analyses, time series analysis, year effect

Dates

Published: 2020-10-11 02:07

Last Updated: 2020-10-16 07:03

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License

CC-By Attribution-ShareAlike 4.0 International