Using compositional and functional indicators for biodiversity conservation monitoring of semi-natural grasslands in Scotland

Compositional indicators (i.e. indices that focus on the identity of species, genes or phylogeny) have been widely used to estimate and monitor biodiversity, however, their use in combination with species and/or community functional characteristics remains limited. Using large-scale, spatio-temporal data, we use both compositional and functional indices to investigate land-use change impacts on the vegetation of a semi-natural grassland ecosystem (Machair) for fourteen regions in Scotland, UK. Our study aimed to identify national- and regional-scale temporal vegetation patterns, and through use of simple compositional and functional indices (e.g. Competitor, Stress, Ruderal and Ellenberg scores) link observed changes to agricultural intensification and/or land-use abandonment. Using linear-mixed modelling and non-metric multi-dimensional scaling, we showed significant national and regional-scale changes in species composition over time. Increases in diversity, particularly gains in Machair grassland, identified several regions that may have benefited from past government incentivised schemes to protect the Machair, but which may also be suffering from an extinction lag. Shifts in plant functional signatures (CSR & Ellenberg values) identified varying degrees of internal (competition) and external (land-use) factors, highlighting several regions where biodiversity change could be linked to reduced disturbance (i.e. lower grazing intensity) or greater disturbance (i.e. land-use intensification). Our results demonstrate the utility of simple compositional and functional indices for monitoring biodiversity of semi-natural grasslands and identifying land-use drivers of change across different spatial scales.