4.5 Article

Functional responses of plant communities to management, landscape and historical factors in semi-natural grasslands

Journal

JOURNAL OF VEGETATION SCIENCE
Volume 25, Issue 3, Pages 750-759

Publisher

WILEY
DOI: 10.1111/jvs.12126

Keywords

Land use; Grazing management; Functional trait diversity; Species pool; Biodiversity loss; Community-weighted mean; Landscape history

Funding

  1. Swedish Research Council (VR)
  2. Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS)
  3. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
  4. German Research Foundation [FZT 118]

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Question To what extent do historical and present-day management regimes and landscape characteristics affect the functional structure of semi-natural grassland communities? Location Semi-natural grasslands, the Baltic island of oland, Sweden. Methods We assessed community functional structure within 475 (50cmx50cm) semi-natural grassland vegetation plots using two indices: community-weighted mean trait values (CWM) and functional divergence (FD), calculated using the Rao quadratic entropy index. Spatially explicit regressions were used to assess the extent to which the CWM and FD for different plant traits are explained by past and present levels of local grazing management, and the present and historical characteristics of the surrounding landscape. Results Across traits, the CWM and FD of individual grasslands were strongly associated with current grazing intensity, but also with local management history and past landscape structure. Conclusions Our results indicate that grassland functional structure in the fragmented present-day landscape reflects not only present conditions, but also the historical context of the grassland fragments - where the presence of extensive grassland habitat in the surroundings provided a diverse pool of grazing-tolerant species. The study also suggests that information on landscape history, and its effects on the local species pool, may improve predictions of future plant community structure.

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