Summary: Ecosystem services have received increasing attention in life sciences, but only a limited amount of quantitative data are available concerning the ability of weeds to provide these services. Following an expert focus group on this topic, a systematic search for articles displaying evidence of weeds providing regulating ecosystem services was performed, resulting in 129 articles. The most common service found was pest control and the prevailing mechanism was that weeds provide a suitable habitat for natural enemies. Other articles showed that weeds improved soil nutrient content, soil physical properties and crop pollinator abundance. Weeds were found to provide some important ecosystem services for agriculture, but only a small number of studies presented data on crop yield. Experimental approaches are proposed that can: (i) disentangle the benefits obtained from ecosystem services provisioning from the costs due to weed competition and (ii) quantify the contribution of diverse weed communities in reducing crop competition and in providing ecosystem services. Existing vegetation databases can be used to select weed species with functional traits facilitating ecosystem service provisioning while having a lower competitive capacity. However, for services such as pest control, there are hardly any specific plant traits that have been identified and more fundamental research is needed.

Questions: Two scientific disciplines, vegetation science and weed science, study arable weed vegetation, which has seen a strong diversity decrease in Europe over the last decades. We compared two collections of plot‐based vegetation records originating from these two disciplines. The aim was to check the suitability of the collections for joint analysis and for addressing research questions from the opposing domains. We asked: are these collections complementary? If so, how can they be used for joint analysis?Location: Europe.Methods: We compared 13 311 phytosociological relevés and 13 328 records from weed science, concerning both data collection properties and the recorded species richness. To deal with bias in the data, we also analysed different subsets (i.e., crops, geographical regions, organic vs conventional fields, center vs edge plots).Results: Records from vegetation science have an average species number of 19.0 ± 10.4. Metadata on survey methodology or agronomic practices are rare in this collection. Records from weed science have an average species number of 8.5 ± 6.4. They are accompanied by extensive methodological information. Vegetation science records and the weed science records taken at field edges or from organic fields have similar species numbers. The collections cover different parts of Europe but the results are consistent in six geographical subsets and the overall data set. The difference in species numbers may be caused by differences in methodology between the disciplines, i.e., plot positioning within fields, plot sizes, or survey timing.Conclusion: This comparison of arable weed data that were originally sampled with a different purpose represents a new effort in connecting research between vegetation scientists and weed scientists. Both collections show different aspects of weed vegetation, which means the joint use of the data is valuable as it can contribute to a more complete picture of weed species diversity in European arable landscapes.

“Arable Weeds and Management in Europe” is a collection of weed vegetation records from arable fields in Europe, initiated within the Working Group Weeds and Biodiversity of the European Weed Research Society (EWRS). Vegetation-plot data from this scientific community was not previously contributed to databases. We aim to prove the usefulness of collection for large scale studies through some first analyses. We hope to assure other weed scientists who have signalled willingness to share data, and plan to construct a full data base, making the data available for easy sharing. Presently, the collection has over 60,000 records, taken between 1996 and 2015. Many more studies for potential inclusion exist. Data originate mostly from studies exploring the effect of agricultural management on weed vegetation. The database is accompanied with extensive meta-data on crop and weed management on the surveyed fields. The criteria for inclusion were a minimum amount of information on the cultivated crop, and a georeference. Most fields were surveyed repeatedly, i.e. transects, multiple random plots, or repeated visits. All surveys aimed to record the complete vegetation on the plots. Sometimes, taxa were identified only to genus level, due to survey dates very early in the vegetation period. Plant taxonomy is standardized to the Euro+Med PlantBase.

Based on a workshop held at the German Weed Science Conference in February 2024, this paper explores strategies for reducing herbicide use in arable cropping systems to enhance weed diversity. Although potentially detrimental to crop yields, weeds play a vital role in supporting ecosystem functions such as pollination, nutrient cycling, and microbial diversity. The reduction of herbicide use is regarded as an important management strategy for preserving weed biodiversity, which has been declining in Europe. Three strategies for reducing herbicide use are discussed: site-specific herbicide application, species-specific herbicide dose rates, and the use of selective herbicides with narrow target spectra. Each strategy is evaluated for its technical feasibility, agronomic risks, and potential benefits for weed diversity. While challenges such as high investment costs, technical limitations, and the need for precise weed distribution data remain, emerging technologies like AI-driven weed detection and autonomous robots offer promising solutions. The paper emphasizes the importance of combining reduced herbicide use with other management practices, such as crop rotation and mechanical weeding, to achieve sustainable and ecologically beneficial weed control. A shift in farmers’ perspectives on “clean fields” and more comprehensive guidance on the ecological value of weeds is essential for the widespread adoption of these strategies.

Purpose: Creating spatial weed distribution maps as the basis for site-specific weed management (SSWM) requires determining the occurrence and densities of weeds at georeferenced grid points. To achieve a field-wide distribution map, the weed distribution between the sampling points needs to be predicted. The aim of this study was to determine the best combination of grid sampling design and spatial interpolation technique to improve prediction accuracy. Gaussian copula as alternative method was tested to overcome challenges associated with interpolating weed densities such as smoothing effects. Methods: The quality of weed distribution maps created using combinations of different sampling grids and interpolation methods was assessed: Inverse Distance Weighting, different geostatistical approaches, and Nearest Neighbor Interpolation. For this comparison, the weed distribution and densities in four fields were assessed using three sampling grids with different resolutions and arrangements: Random vs. regular arrangement of 40 grid points, and a combination of both grid types (fine grid). Results: The best prediction of weed distribution was achieved with the Kriging interpolation models based on weed data sampled on the fine grid. In contrast, the lowest performance was observed using the regular grid and the Nearest Neighbor Interpolation. A patchy distribution of weeds did not affect the prediction quality. Conclusion: Using the Gaussian copula kriging did not result in a reduction of the smoothing effect, which still represents a challenge when employing spatial interpolation methods for SSWM. However, using a randomly distributed raster with a fine resolution could further optimize the precision of weed distribution maps.