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A multitaxa assessment of the effectiveness of agri-environmental schemes for biodiversity management
Friday, 2021/03/19 | 08:16:40

Fabian A. Boetzl, Jochen Krauss, Jonathan Heinze, Hannes Hoffmann, Jan Juffa, Sebastian König, Elena Krimmer, Maren Prante, Emily A. Martin, Andrea Holzschuh, and Ingolf Steffan-Dewenter

PNAS March 9, 2021 118 (10) e2016038118

Significance

The loss of biodiversity challenges agriculture as crop yields depend on biodiversity-mediated ecosystem services. Targeted agri-environmental schemes (AES), like sown flowering fields, provide additional food resources and shelter for wild plants and animals. Such AES have been implemented to restore biodiversity in agricultural landscapes and ensure ecosystem services provision. However, little is known about the comparative benefits of different AES for functional biodiversity and whether temporal continuity, covered area, or perennial source habitats in the surrounding landscape limit the success of an AES. Here, we systematically evaluate within one study design how temporal continuity, size, and seminatural habitat cover in the surrounding landscape affect multitaxa diversity in different AES types and assess their potential for biodiversity conservation in agricultural landscapes.

Abstract

Agri-environmental schemes (AES) aim to restore biodiversity and biodiversity-mediated ecosystem services in landscapes impoverished by modern agriculture. However, a systematic, empirical evaluation of different AES types across multiple taxa and functional groups is missing. Within one orthogonal design, we studied sown flowering AES types with different temporal continuity, size, and landscape context and used calcareous grasslands as seminatural reference habitat. We measured species richness of 12 taxonomic groups (vascular plants, cicadas, orthopterans, bees, butterflies, moths, hoverflies, flower visiting beetles, parasitoid wasps, carabid beetles, staphylinid beetles, and birds) representing 5 trophic levels. A total of 54,955 specimens were identified using traditional taxonomic methods, and bulk arthropod samples were identified through DNA metabarcoding, resulting in a total of 1,077 and 2,110 taxa, respectively. Species richness of most taxonomic groups, as well as multidiversity and richness of pollinators, increased with temporal continuity of AES types. Some groups responded to size and landscape context, but multidiversity and richness of pollinators and natural enemies were not affected. AES flowering fields supported different species assemblages than calcareous grasslands, but assemblages became more similar to those in seminatural grasslands with increasing temporal continuity. Our results indicate that AES flowering fields and seminatural grasslands function synergistically. Flowering fields support biodiversity even when they are relatively small and in landscapes with few remaining seminatural habitats. We therefore recommend a network of smaller, temporally continuous AES flowering fields of different ages, combined with permanent seminatural grasslands, to maximize benefits for biodiversity conservation and ecosystem service delivery in agricultural landscapes.

 

See https://www.pnas.org/content/118/10/e2016038118

Figure 2:

(A) Overall multidiversity, (B) diversity of pollinators, and (C) diversity of natural enemies in the different AES types along a gradient of temporal continuity (increasing from left to right; percentages of species in each site of the total species pool ± 95% confidence interval; blue dashed lines indicate means across all sites). Proportion of species present in each AES type (mean) for (D) all taxa, (E) pollinators, and (F) natural enemies. In radar charts, one interval equals 10% starting from the center of the chart. Taxonomic groups were 1) vascular plants 2) orthopterans, 3) cicadas, 4) hoverflies, 5) bees, 6) butterflies, 7) moths, 8) flower visiting beetles, 9) parasitoid wasps, 10) carabid beetles, 11) staphylinid beetles, and 12) birds. Different letters in AC indicate significant differences (P < 0.05), brackets indicate marginally significant differences (P < 0.1). For statistics, see SI Appendix, Table S4.

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