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Updated: Jun 28, 2025

A Method for Quantifying Foliage-Dwelling Arthropods
Published on: October 20, 2019
Adaptive monitoring in action-what drives arthropod diversity and composition in central European beech forests?
Constanze Keye1, Marcus Schmidt2, Christian Roschak2,3
1Department for Forest Nature Conservation, Northwest German Forest Research Institute, Prof.-Oelkers-Str. 6, 34346, Hann. Münden, Germany. constanze_keye@icloud.com.
Abstract:
Recent studies suggest that arthropod diversity in German forests is declining. Currently, different national programs are being developed to monitor arthropod trends and to unravel the effects of forest management on biodiversity in forests. To establish effective long-term monitoring programs, a set of drivers of arthropod diversity and composition as well as suitable species groups have to be identified. To aid in answering these questions, we investigated arthropod data collected in four Hessian forest reserves (FR) in the 1990s. To fully utilize this data set, we combined it with results from a retrospective structural sampling design applied at the original trap locations in central European beech (Fagus sylvatica) forests. As expected, the importance of the different forest structural, vegetation, and site attributes differed largely between the investigated arthropod groups: beetles, spiders, Aculeata, and true bugs. Measures related to light availability and temperature such as canopy cover or potential radiation were important to all groups affecting either richness, composition, or both. Spiders and true bugs were affected by the broadest range of explanatory variables, which makes them a good choice for monitoring general trends. For targeted monitoring focused on forestry-related effects on biodiversity, rove and ground beetles seem more suitable. Both groups were driven by a narrower, more management-related set of variables. Most importantly, our study approach shows that it is possible to utilize older biodiversity survey data. Although, in our case, there are strong restrictions due to the long time between species and structural attribute sampling.
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