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Additional file 10: Appendix 10. Influence of the abundance-weighted mean (AWM) of grazing on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in grasslands. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 1: Supplementary Figure 1. Ordinary least squares regression between forest structural parameters of 124 forest plots from the Biodiversity Exploratories (calibration sites). Supplementary Figure 2. Comparison between observed and predicted data based on subsets of the Biodiversity Exploratories plots. Supplementary Figure 3. Procedure of forest inventory plot selection for the extrapolation of ecosystem service indicators. Supplementary Figure 4. Averages and 95% confidence intervals for the initial set of predictors (forest structural and abiotic parameters) calculated for the final set of 53 forest types. Supplementary Figure 5. Principal components space based on the forest structural and compositional parameters and abiotic parameters. Supplementary Figure 6.: Predicted levels of ecosystem service indicators for the 53 most dominant forest types in Germany. Supplementary Table 1. List of ecosystem service indicators with corresponding categories and unit of measurement. Supplementary Table 2. Coefficients of ecosystem service models based on forest structural and compositional parameters and abiotic parameters. Supplementary Table 3. Number of forest inventory plots used to predict potential ecosystem service supply across Germany.

Additional file 3: Appendix 3. Influence of the abundance-weighted mean (AWM) of the proportion of non-native trees on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in forests. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 7: Appendix 7. Influence of the abundance-weighted mean (AWM) of soil moisture on the maximum shell, size number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in forests. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 6: Appendix 6. Influence of the abundance-weighted mean (AWM) of soil pH on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in forests. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 5: Appendix 5. Influence of the abundance-weighted mean (AWM) of the proportion of wood harvested on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in forests. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 4: Appendix 4. Influence of the abundance-weighted mean (AWM) of the proportion of deadwood with saw cuts on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in forests. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 1: Appendix 1. Summary of significant effects of land-use parameters and abiotic factors in forests (forest management index Formi, proportion of non-native tress, proportion of dead wood with saw cuts, proportion of wood harvested, pH and soil moisture) and grasslands (land-use index LUI, mowing, grazing, fertilization, pH and soil moisture) on the community weighted mean of the maximum shell size, the number of offspring, light preference, humidity preference, drought resistance and inundation tolerance. * p

Additional file 11: Appendix 11. Influence of the abundance-weighted mean (AWM) of fertilization on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in grasslands. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 9: Appendix 9. Influence of the abundance-weighted mean (AWM) of mowing on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in grasslands. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 15: Appendix 15. Relation of the abundance-weighted means (AWM) of the land-use intensity, mowing, grazing, fertilization, pH and soil moisture and the proportional occurrence of a certain species in forests.

Additional file 2: Appendix 2. Influence of the abundance-weighted mean (AWM) of the forest management index on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in forests. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 14: Appendix 14. Relation of the abundance-weighted means (AWM) of the forest management index, proportion of non-native trees, proportion of dead wood with saw cuts, proportion of wood harvested, pH and soil moisture and the proportional occurrence of a certain species in forests.

Additional file 13: Appendix 13. Influence of the abundance-weighted mean (AWM) of soil moisture on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in grasslands. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 8: Appendix 8. Influence of the abundance-weighted mean (AWM) of land-use intensity (LUI) on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in grasslands. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Additional file 12: Appendix 12. Influence of the abundance-weighted mean (AWM) of soil pH on the maximum shell size, number of offspring, light preference, humidity preference, drought resistance and inundation tolerance in grasslands. Species in italics are land-use “winners”, species in bold are land-use “losers”.

Reports of major losses in insect biodiversity have stimulated an increasing interest in temporal population changes. Existing 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 standardised sampling. While new monitoring programs have been initiated, they still cover rather short time periods. Daskalova et al. 2021 (Insect Conservation and Diversity, 14, 1-18) 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. 2019 (Nature, 574, 671-674) based on a 10-year multi-site time series, they claim that the analysis suffers from not accounting for temporal pseudoreplication. Here, we explain why the criticism of missing statistical rigour in the analysis of Seibold et al. (2019) is not warranted. Models that include 'year' as random effect, as suggested by Daskalova et al. (2021), 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. (2021) 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 are highly valuable, should be extended and analysed continually to provide a more detailed understanding of insect population changes under the influence of global change, and to trigger immediate conservation actions.

Background Forests perform various important ecosystem functions that contribute to ecosystem services. In many parts of the world, forest management has shifted from a focus on timber production to multi-purpose forestry, combining timber production with the supply of other forest ecosystem services. However, it is unclear which forest types provide which ecosystem services and to what extent forests primarily managed for timber already supply multiple ecosystem services. Based on a comprehensive dataset collected across 150 forest plots in three regions differing in management intensity and species composition, we develop models to predict the potential supply of 13 ecosystem services. We use those models to assess the level of multifunctionality of managed forests at the national level using national forest inventory data. Results Looking at the potential supply of ecosystem services, we found trade-offs (e.g. between both bark beetle control or dung decomposition and both productivity or soil carbon stocks) as well as synergies (e.g. for temperature regulation, carbon storage and culturally interesting plants) across the 53 most dominant forest types in Germany. No single forest type provided all ecosystem services equally. Some ecosystem services showed comparable levels across forest types (e.g. decomposition or richness of saprotrophs), while others varied strongly, depending on forest structural attributes (e.g. phosphorous availability or cover of edible plants) or tree species composition (e.g. potential nitrification activity). Variability in potential supply of ecosystem services was only to a lesser extent driven by environmental conditions. However, the geographic variation in ecosystem function supply across Germany was closely linked with the distribution of main tree species. Conclusions Our results show that forest multifunctionality is limited to subsets of ecosystem services. The importance of tree species composition highlights that a lack of multifunctionality at the stand level can be compensated by managing forests at the landscape level, when stands of complementary forest types are combined. These results imply that multi-purpose forestry should be based on a variety of forest types requiring coordinated planning across larger spatial scales.

Land-use intensification poses major threats to biodiversity, such as to insect herbivore communities. The stability of these communities depends on interactions linking herbivores and host plants. How interaction network structure begets robustness, and thus stability, in different ecosystems and how network structure and robustness are altered along land-use intensity gradients are unclear. We analyzed plant-herbivore networks based on literature-derived interactions and long-term sampling from 289 grasslands and forests in three regions of Germany. Network size and nestedness were the most important determinants of network robustness in both ecosystems. Along land-use intensity gradients, networks in moderately grazed grasslands were more robust than in those managed by frequent mowing or fertilization. In forests, changes of network robustness along land-use intensity gradients relied on changes in plant species richness. Our results expand our knowledge of the stability of plant-herbivore networks and indicate options for management aimed at stabilizing herbivore communities.