We have described biodiversity as a multiple scale character that underpins vital ecosystem processes supporting agricultural land use (see section Definition of Biodiversity) and, as such, the use of simple indicators to monitor the impacts of changes in land management is problematic. There has been a great deal of effort devoted to the search for biodiversity indicators that have broad applicability and can be used internationally (Teder et al. 2007), incorporate plants alone (Gibbons et al. 2008; Gibbons and Freudenberger 2006; Gibbons et al. 2005; Landsberg and Crowley 2004), incorporate a range of taxonomic groups (Kati et al. 2004) or mulit-scale attributes (Smyth and James 2004; Duelli and Obrist 2003; Noss 1990), or which can be used as benchmarks (Oliver et al. (2007); McCarthy et al. 2004). Despite these efforts, and initiatives to provide integrated software packages such as SCaRPA to predict outcomes of land use change (TOOLS2, 2008), biodiversity indicators that are both appropriate and of utility value in agricultural systems are lacking.

(Moonen and Barberi 2008 provide a structured framework that recognises ‘agroecosystem functional groups’ as key indicators relevant to agricultural landscapes and argue that a clear distinction needs to be made between biological indicators that reflect environmental change/status and agro-ecosystem functional groups that reflect interactions and regulation of agro-ecosystem processes. In this way, clusters of biota may provide the same agro-ecosystem service and could be grouped into the one functional group. This recognises that one biota can deliver a number of ecosystem functions. For example, for productive ecosystem services, an agro-ecological functional group may include nutrient cycling, decomposition rates, aggregate stability and organic matter formation.

While ‘agro-ecosystem functional groups’ may be appropriate indicators for agricultural areas, they require considerable technical expertise to measure. The ‘Landscape Function Analysis’ (LFA) tool has been widely adopted (Tongway and Hindley 2004). This method provides a quick but rigorous monitoring procedure using simple indicators of landscape function (soil surface stability, infiltration and nutrient cycling). These indicators are measured by monitoring cryptogam, soil, litter and perennial grass cover; soil surface crusting, erosion type and severity, deposition materials, microtopography, surface resistance to disturbance, slake test and soil texture, and have been broadly applicable across a range of land uses (rangelands, mining, horticultural industries, habitat conservation) and as an indicator of soil carbon. Although this technique requires limited training, it has been widely used as part of regional, state and national resource monitoring and as an adaptive management tool for stewardship schemes (Ampt et al. 2007). The emphasis on using ground cover in the LFA technique and elsewhere highlights the importance of this indicator in landscape function.