The German insect monitoring scheme: Establishment of a nationwide long-term recording of arthropods

Abstract

A standardised monitoring is indispensable to identify trends of insect populations. However, until recently, a systematic monitoring of insects in Germany was missing. Therefore, the German federal ministry for the environment funded the conceptualisation of an insect monitoring scheme.

Here, we inform about the general concept and structure of the German insect monitoring scheme (GIMS) and the steps taken and still to be taken for the implementation of the scheme. A first step was the development of the objectives, general concept und structure of the GIMS in close collaboration with the nature conservation authorities at the national and federal state levels, as the latter are responsible for the implementation of nature conservation-related monitoring schemes. The GIMS is structured into two sections: section 1 ‘Monitoring of common insects’ and section 2 ‘Monitoring of rare insects’. Both sections contain modules that focus on selected aspects of insect diversity. In section 1, insect communities of the wider countryside will be monitored. Section 2 focuses on insect communities in rare habitats and species of high conservation value (e.g. threatened species). The next step was to develop standardised sampling methods for the modules in collaboration with experts and the nature conservation authorities. Wherever appropriate, synergies with other monitoring schemes were created, e.g. for combined analyses with environmental variables.

Parallel to the development of the concept, several federal states have already implemented selected modules of the GIMS. Furthermore, the module ‘Grasshoppers in grasslands’ was tested during a pilot phase. By using the data from the pilot phase and the High Nature Value Farmland Monitoring scheme the relationship between high nature value farmland and grasshopper diversity was evaluated. This indicated the great potential of using synergies among monitoring schemes for joint data analyses and showed that it is worth exploring such approaches in greater depth.