Predicting Plant Communities in the Vicinity of Wheat Crops and Vineyards in Europe using Participatory Modeling

Abstract

The risk assessment of pesticide use on non-target terrestrial plants is currently based on standardized greenhouse tests with a limited number of mostly crop plant species. Higher tier tests or assessments of any kind (e.g., field, semi-field, landscape studies) are not standardized. In this study we explored an approach to inform such a higher level by collecting datasets and information at European scale to characterize the vegetation communities that are likely to grow in the off-field areas of wheat and vine crops. The EUNIS (European Nature Information System) habitat classification was used to identify eight man-made habitats considered characteristic of the off-field areas in the European agricultural landscape. These habitats are spatially identified on the bases of a modelling process where vegetation plots, taken from the European Vegetation Archive, were used as observations and climate, soil, topographic, population density parameters and Remote Sensed Essential Biodiversity Variables as predictors. This modelling results in habitat suitability maps. The habitats are also described in terms of species frequencies and abundances, and to plant traits underlying possible vulnerability to pesticide exposure requested from the TRY plant trait database. Wheat and vine crop spatial data were derived from EUROSTAT and the QUICKScan methodology was used to combine all these data. We conclude that this method is helpful in reaching the objective as described in this paper. Its potential is that it can be extended probabilistically or linked to plant effect models.