The influence of thematic resolution on metric selection for biodiversity monitoring in agricultural landscapes

The objective of this paper is to investigate the relationship between landscape pattern metrics and agricultural biodiversity at the Temperate European scale, exploring the role of thematic resolution and a suite of biological and functional groups. Factor analyses to select landscape-level metrics were undertaken on 25 landscapes classified at four levels of thematic resolution. The landscapes were located within seven countries. The different resolutions were considered appropriate to taxonomic and functional group diversity. As class-level metrics are often better correlated to ecological response, the landscape-level metric subsets gained through exploratory analysis were additionally used to guide the selection of class-level metric subsets. Linear mixed models were then used to detect correlations between landscape- and class-level metrics and species richness values. Taxonomic groups with differing requirements (plants, birds, different arthropod groups) and also functional arthropod groups were examined. At the coarse scale of thematic resolution grain metrics (patch density, largest patch index) emerged as rough indicators for the different biological groups whilst at the fine scale a diversity metric (e.g. Simpson's diversity index) was appropriate. The intermediate thematic resolution offered most promise for biodiversity monitoring. Metrics included largest patch index, edge density, nearest neighbour, the proximity index, circle and Simpson's diversity index. We suggest two possible applications of these metrics in the context of biodiversity monitoring and the identification of biodiversity hot spots in European agricultural landscapes.