Recent losses in the abundance and diversity of arthropods have been documented in many regions and ecosystems. In grasslands, such insect declines are largely attributed to land use, including modern machinery and mowing regimes. However, the effects of different mowing techniques on arthropods remain poorly understood. Using 11 years of data from 111 agricultural grassland plots across Germany, we analyzed the influence of various grassland management variables on the abundance and abundance‐accounted species richness of four arthropod orders: Araneae, Coleoptera, Hemiptera, and Orthoptera. The analysis focused on detailed mowing information, for example, days after mowing and mower type, and compared their effect with other aspects of grassland management, that is, rolling, leveling, fertilization, and grazing. We found strong negative effects of mowing on all four arthropod orders, with arthropod abundance being lowest directly after mowing and steadily increasing to three to seven times the abundance after 100 days post‐mowing. Likewise, Hemiptera and Coleoptera species richness was 30% higher 100 days after mowing. Mower width showed a positive effect on Orthoptera abundance, but not on the other arthropods. Arthropod abundance and Coleoptera species richness were lowest when a mulcher was used compared to rotary or bar mowers. In addition to mowing, intensive grazing negatively affected Orthoptera abundance but not the other orders. Mowing represents a highly disturbing and iterative stressor with negative effects on arthropod abundance and diversity, likely contributed by mowing‐induced mortality and habitat alteration. While modifications of mowing techniques such as mower type or mowing height and width may help to reduce the negative impact of mowing on arthropods, our results show that mowing itself has the most substantial negative effect. Based on our results, we suggest that reduced mowing frequency, omission of mowing in parts of the grassland (refuges), or extensive grazing instead of mowing have the greatest potential to promote arthropod populations.

Urban areas have profound impacts on local species diversity and composition through a set of intertwined changes in the environment. As the world is rapidly urbanising while simultaneously facing a biodiversity crisis, a better understanding of how urbanisation influences biodiversity is necessary. To test if and how urbanisation influences moth diversity and whether urbanisation is acting directly or indirectly via urbanisation‐induced increased habitat isolation, smaller habitat area, higher light pollution and increased mowing intensity, we sampled moths with light trapping in 20 grasslands in the urban core of the city of Darmstadt (southwestern Germany) and 20 grasslands in the surrounding area. Moth abundance and diversity decreased with increasing urbanisation. Smaller habitat area and high mowing intensity reduced moth abundance, while other environmental variables including isolation and light pollution had only indirect effects. High levels of urbanisation were associated with reduced moth abundance, which in turn drove declines in diversity. Urbanised sites favoured generalist species and differed in species composition compared to sites in the surrounding. The results show that urbanisation is directly reducing moth abundance and diversity in cities. The negative effect of urbanisation is further attenuated by habitat fragmentation and high mowing intensity, which are both known drivers of biodiversity decline in urban areas and beyond. While urbanisation itself is often irreversible, reducing mowing intensity and preserving larger grassland areas could facilitate moths and other taxa in and around cities.

Background: Only a few decades ago, colorful, small‐scale, heterogeneous, and species‐rich hay meadows or extensive pastures were common, but have often been replaced by species‐poor, uniform, large‐scale multicut meadows. Technological advancements and improved efficiency in grassland management have come at the cost of biodiversity.Methods: In Germany, 150 grassland plots have been investigated since 2006. Using these extensive data, we propose a new compound index for estimating the site‐specific mowing intensity in order to facilitate assessment of the impact of mowing intensity on biodiversity and ecosystem processes. Our index integrates the various qualitative components of mowing machine type, mowing height and use of a conditioner, with the annual number of cuts.Results: The newly proposed index achieves a much finer gradation of mowing intensity compared to the previous quantification based on the number of cuts only. Furthermore, a decrease in plant and arthropod species was observed at higher mowing intensity.Conclusions: The proposed mowing intensity index offers enhanced precision in calculations and can easily be integrated into assessments of land‐use intensity in grasslands. Further, it could serve as a basis for providing subsidies to farmers, who adopt low‐impact mowing practices.

Grassland biomass yield reflects a complex interaction of management intensity and environmental factors, yet quantifying the relative role of practices such as mowing and fertilization remains challenging. In this study, we introduce a multi-class machine learning framework to predict above-ground biomass on 150 permanent grassland plots across eight years (2009–2016) in Germany’s Biodiversity Exploratories and to evaluate the influence of key management variables. Following rigorous data cleaning, imputation of missing nitrogen values, feature standardization, and encoding of categorical practices, we trained CatBoost classifiers optimized via Bayesian hyperparameter search and mitigated class imbalance with ADASYN oversampling. We assessed model performance under binary, three-class, four-class, and five-class quantile-based categorizations, achieving test accuracies of 0.76, 0.57, 0.42, and 0.38, respectively. Across all schemes, mowing frequency and mineral nitrogen input emerged as the dominant predictors, while secondary variables such as drainage and conditioner use contributed as well. These results demonstrate that broad biomass categories can be forecast reliably from standardized management records, whereas finer distinctions necessitate additional environmental information or automated sensing to capture nonlinear effects and reduce reporting bias. This work shows both the potential and the limits of machine learning for informing sustainable grassland management and explainability thereof. Frequent mowing and higher mineral nitrogen inputs explained most of the predictable variation, enabling a 76% accurate separation of low and high biomass categories. Predictive accuracy fell below 60% for finer class resolutions, indicating that management records alone are insufficient for detailed yield forecasts without complementary environmental data.

Intensified land‐use in grasslands reduces biodiversity, particularly affecting arthropod populations. However, responses of individual species vary depending on their ecological traits and habitat requirements. Some species may tolerate or even benefit from intensive land‐use, while others, particularly specialists or those with narrow niches, are likely to be negatively affected. We used a quantitative niche model to evaluate species‐specific responses to land‐use intensity in four arthropod orders common in grasslands: Araneae, Coleoptera, Hemiptera and Orthoptera. From 2008 to 2018, a total of 214 416 individuals across 1352 species were collected on 150 grassland plots across three regions of Germany. The effects of mowing, fertilizing, and grazing on species occurrence and abundance were evaluated by their niche optima to identify winners, losers, and neutrals. Fertilizing showed the fewest winners (6%) as well as the most losers (29%) with all orders having the highest proportion being negatively affected, whereas grazing showed the most winners (10%) and fewest losers (10%). Nevertheless, most species showed neutral responses (71%). The niche optimum of grazing favored smaller species, whereas mowing and fertilizing favored larger species. Herbivores were particularly sensitive to fertilizing. Comparison with the Red List revealed that species under mowing exhibited lower niche optima with higher‐risk categories, which was also reflected in declining population trends. This study highlights the high variation in species‐specific responses of arthropods to the different components of land‐use, showing overall three times as many loser species as winner species. This emphasizes the need for conservation strategies tailored to vulnerable species. Balancing land‐use strategies with biodiversity conservation in land‐use policies is essential to preserve arthropod diversity and enhance ecosystem resilience in grasslands.