Using Field Experiments to Inform Biodiversity Monitoring in Agricultural Landscapes

Abstract

Fueled by debates on the causes and consequences of biodiversity decline worldwide, many countries are now employing biodiversity monitoring programs of various scope, intensity and scale. While these programs will be important to set a baseline for managing a country´s biological diversity, the availability of detailed data may take too long for the urgently needed implementation of biodiversity-friendly action. Intensification of local agricultural land use and the high dynamics of landscape change are major reasons for current biodiversity losses. Hence, better use of published and unpublished data to inform predictive biodiversity monitoring under global change is needed. Here, we exemplarily show how existing experiments manipulating land-use drivers can be used to predict species responses to land-use change. In an experimental manipulation of temperate grassland plots, fertilizer addition and low mowing frequency increased the species richness of aboveground arthropods, while herbicide addition and frequent mowing reduced it. In a crop rotation experiment, temporal crop diversity slightly increased arthropod abundances, but crop identity had the strongest effect on arthropod abundance, showing that the type of crop grown may superimpose crop diversity effects on arthropod communities. Finally, in a wheat-bean intercropping experiment, we found that the legume-based farming systems under low-input management had higher diversity of flower-visiting insect taxa. In an upscaling exercise, we show how current crop distribution data from the pan-European LUCAS survey can be combined with insect biodiversity data to suggest an approach for predictive mapping of insect biodiversity. These can form the basis for scenario modeling that is based on experimental evidence.