Sebastian Seibold, Torsten Hothorn, Martin M. Gossner, Nadja K. Siimons, Nico Blüthgen, Jörg Müller, Didem Ambarli, Christian Ammer, Jürgen Bauhus, Markus Fischer

Reports of major losses in biodiversity have stimulated an increasing interest in temporal population changes, particularly in insects, which had received little attention in the past. Existing long-term datasets are often limited to a small number of study sites, few points in time, a narrow range of land-use intensities and only some taxonomic groups, or they lack standardized sampling. While new multi-site monitoring programs have been initiated, most of them still cover rather short time periods. Daskalova et al. 20201 argue that temporal trends of insect populations derived from short time series are biased towards extreme trends, while their own analysis of an assembly of shorter- and longer-term time series does not support an overall insect decline. With respect to the results of Seibold et al.2 based on a 10-year multi-site time series, they claim that the analysis suffers from not accounting for temporal pseudoreplication. In this note, we explain why the criticism of missing statistical rigour in the analysis of Seibold et al.2 is not warranted. Models that include ‘year’ as random effect, as suggested by Daskalova et al. 2020, fail to detect non-linear trends and assume that consecutive years are independent samples which is questionable for insect time-series data. We agree with Daskalova et al. 2020 that the assembly and analysis of larger datasets is urgently needed, but it will take time until such datasets are available. Thus, short-term datasets like ours are highly valuable, should be extended and analysed continually to provide a more detailed understanding of how insect populations are changing under the influence of global change, and to trigger immediate conservation actions.