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In eight European study sites (in Spain, Ireland, Netherlands, Germany, Poland, Estonia and Sweden), abundance of breeding farmland bird territories was obtained from 500 × 500 m survey plots (30 per area, N = 240) using the mapping method. Two analyses were performed: (I) a Canonical Correspondence Analysis of species abundance in relation to geographical location and variables measuring agricultural intensification at field and farm level to identify significant intensification variables and to estimate the fractions of total variance in bird abundance explained by geography and agricultural intensification; (II) several taxonomic and functional community indices were built and analysed using GLM in relation to the intensification variables found significant in the CCA. The geographical location of study sites alone explains nearly one fifth (19.5%) of total variation in species abundance. The fraction of variance explained by agricultural intensification alone is much smaller (4.3%), although significant. The intersection explains nearly two fifths (37.8%) of variance in species abundance. Community indices are negatively affected by correlates of intensification like farm size and yield, whereas correlates of habitat availability and quality have positive effects on taxonomic and functional diversity of assemblages. Most of the purely geographical variation in farmland bird assemblage composition is associated to Mediterranean steppe species, reflecting the bio-geographical singularity of that assemblage and reinforcing the need to preserve this community. Taxonomic and functional diversity of farmland bird communities are negatively affected by agricultural intensification and positively affected by increasing farmland habitat availability and quality. [ABSTRACT FROM AUTHOR]

The article focuses on the effects of agricultural intensification (AI) on biodiversity in Europe. It investigates the diversity of vascular plants, carabid beetles, and birds in agricultural landscapes in cereal crop field at the field, farm, and European-region scale. The study suggests that a more detailed understanding of AI effects on diversity patterns of various plants and animals in multiple spatial scales would contribute to more efficient agri-environmental schemes in agroecosystems.

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