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Changing agricultural practices have dramatically altered the arable flora of Europe since the Second World War. We conducted a meta-analysis of the available literature to assess the dynamics of species richness and species traits in the arable flora across Europe during this time period. We found a total of 32 publications, yielding 53 data sets with an average number of 252 studied plots per data set. Average species number per plot of arable plants across all data sets declined by about 20%. However, twelve data sets showed an increase in average species number per plot, including all studies starting after 1980. Plant species preferring nutrient-rich sites, neophytes and monocotyledons generally increased since 1980, while character-istic or threatened species of arable weed communities further declined. This temporal development of the European arable flora suggests that the changes happening in agricultural management since the 1980s, such as organic farming and reduced pesticide input, may have helped slow the decline of the arable flora in terms of species number, but not in terms of characteristic or threatened arable weeds. Hence, more specific measures are necessary to stop decline of the latter, making sure that these measures are advantageous for rare and characteristic arable species, but not for harmful weeds.

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Abstract. Farmland is a major land cover type in Europe and Africa and provides habitat for numerous species. The severe decline in farmland biodiversity of the last decades has been attributed to changes in farming practices, and organic and low-input farming are assumed to mitigate detrimental effects of agricultural intensification on biodiversity. Since the farm enterprise is the primary unit of agricultural decision making, management-related effects at the field scale need to be assessed at the farm level. Therefore, in this study, data were collected on habitat characteristics, vascular plant, earthworm, spider, and bee communities and on the corresponding agricultural management in 237 farms in 13 European and two African regions. In 15 environmental and agricultural homogeneous regions, 6-20 farms with the same farm type (e.g., arable crops, grassland, or specific permanent crops) were selected. If available, an equal number of organic and non-organic farms were randomly selected. Alternatively, farms were sampled along a gradient of management intensity. For all selected farms, the entire farmed area was mapped, which resulted in total in the mapping of 11 338 units attributed to 194 standardized habitat types, provided together with additional descriptors. On each farm, one site per available habitat type was randomly selected for species diversity investigations. Species were sampled on 2115 sites and identified to the species level by expert taxonomists. Species lists and abundance estimates are provided for each site and sampling date (one date for plants and earthworms, three dates for spiders and bees). In addition, farmers provided information about their management practices in face-to-face interviews following a standardized questionnaire. Farm management indicators for each farm are available (e.g., nitrogen input, pesticide applications, or energy input). Analyses revealed a positive effect of unproductive areas and a negative effect of intensive management on biodiversity. Communities of the four taxonomic groups strongly differed in their response to habitat characteristics, agricultural management, and regional circumstances. The data has potential for further insights into interactions of farmland biodiversity and agricultural management at site, farm, and regional scale.

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Farmers are key players in actions to halt biodiversity loss from farmland. However, if farmers are to sustain biodiversity, they must first be adequately informed about biodiversity and understand its drivers. Measuring biodiversity at the farm scale is difficult because of the structural complexity of many farms, and because different aspects of diversity can be considered desirable, e.g. species richness or rarity. In this study we examined 19 grassland farms in Central Switzerland, and sampled plants, earthworms, spiders and bees using a stratified sampling design. We considered several metrics of species diversity, but found two particularly useful at farm scale: average richness (area-weighted) and farm uniqueness in terms of species identity. Average richness reflects the expected species richness in a random sample taken on the farm, and farm uniqueness is the contribution of a farm to the total species richness of all farms under study. Average richness and farm uniqueness are complementary and reflect different aspects of biodiversity. We demonstrate how combining these metrics enables tailored recommendations for enhancing species diversity on the farm. AbstractFarmers are key players in actions to halt biodiversity loss from farmland. However, if farmers are to sustain biodiversity, they must first be adequately informed about biodiversity and understand its drivers. Measuring biodiversity at the farm scale is difficult because of the structural complexity of many farms, and because different aspects of diversity can be considered desirable, e.g. species richness or rarity. In this study we examined 19 grassland farms in Central Switzerland, and sampled plants, earthworms, spiders and bees using a stratified sampling design. We considered several metrics of species diversity, but found two particularly useful at farm scale: average richness (area-weighted) and farm uniqueness in terms of species identity. Average richness reflects the expected species richness in a random sample taken on the farm, and farm uniqueness is the contribution of a farm to the total 2 species richness of all farms under study. Average richness and farm uniqueness are complementary and reflect different aspects of biodiversity. We demonstrate how combining these metrics enables tailored recommendations for enhancing species diversity on the farm.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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