Abstract
Use of community trait-based metrics has been increasingly implemented for achieving an integrated view of biodiversity in conservation planning. We examined the extent, to which the use of community metrics based on species traits reflecting plausible sensitivity to change would contribute to our understanding of landscape characteristics of importance to the conservation of farmland birds in a poorly studied region of Northwest Russia. We collected species data on farmland from 230 transects covering a total 215 km for each year of 2008, 2010 and 2011 and analysed them using generalised linear mixed modelling. We derived community indices from species traits of habitat specialisation, trophic position, relative brain size and body mass. By relating these indices to the numbers of all species regarded farmland and Species of European Conservation Concern (SPEC), and by analysing them against the type of field and occurrence in typical non-cropped landscape elements, we showed consistent, albeit weak, congruence among the taxonomic and trait-based community descriptors. All community descriptors had their lowest estimates in arable fields. Community specialisation was the highest in open abandoned fields, which confirms the importance of such fields as refuges for regionally specialised species. Pastures were characterised by the highest community biomass, which indicates a particularly good resource base. Presence of ditches, of all non-cropped elements, had the strongest positive relationship with the community descriptors. The SPEC number strongly correlated with the overall species richness of farmland birds. A relatively weak congruence between taxonomic and trait-based community descriptors highlights their complementarity in understanding the underlying mechanisms of community changes. However, similarity in patterns among field types means that, under the current level of production in the region, accounting for the species richness of farmland birds seems to be sufficient to rapidly assess community sensitivity to agricultural change.
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