As shown by Muradian and Kumar , they are a key stage in the process of value creation and a crucial preliminary stage for evaluation. These authors stress the fact that identifying insufficiently developed perceptions increases the legitimacy of policies in situations of uncertainty. They therefore emphasize the need for participatory approaches at this level. This identification stage also determines the structure of the ecosystem data and knowledge bases which precede the evaluation stage. As noted by Villa et al.  these databases are both a collaborative and an educational tool in the recognition of the services and the social acceptation of the relevant conservation measures. Inforestry, Agbenyega et al.  show that if the perceptions of several categories of users are taken into account, tensions can be avoided when measures are implemented.  Over the last decades, field margins and hedgerow habitats have been recognized as being important in maintaining plant and wildlife diversity ; particularly for birds.

With the distinct shift in agricultural practices that has occurred in both Europe and North America, stacking pots away from subsistence farming and towards large-scale industrial farming , adjacent hedgerows and marginal areas have been reduced or eliminated . In Europe where agricultural intensification is marked, hedgerows comprise one of the most important surviving semi-natural habitats for avian species . Managing hedgerow habitats on farmland property is a com-on way to enhance local bird populations, general biodiversity and consequently, ecosystem functioning . In such circumstances, understanding the relative importance of the different hedgerow structural attributes is imperative if we are to implement successful and cost effective mitigation strategies aimed at in-creasing, or at least conserving the wildlife diversity we have left. Another key impact of changing and intensifying farming practices on bird populations in North America has been a reduction in available food resources across the farmed landscape . Decreasing food resources is responsible for the decline of a wide range of species . Consequently, increasing the availability of food is a common mitigation strategy to promote population growth .

An important component of Agri-Environment Schemes , implemented in Europe to en-courage farmers to manage remaining semi-natural habitat in a sustainable fashion, involves conserving and creating invertebrate-rich foraging habitat for birds during the breeding season. Arthropods are especially important for biodiversity. They form an important part of the diet of many birds, especially young nestlings. Un-cropped field margins support high invertebrate populations. As a result,grow lights their creation and maintenance is a key recommendation of AES . Hedgerows and field margins are excellent at providing birds with appropriate nesting, roosting and foraging habitats . Not only do they fulfill these essential functions, but they also provide cover for local movements and can facilitate longer distance travels through different landscapes . However, the value of these hedgerows to different bird species de-pends on a number of different factors such as hedge-row height, width, length, ditch dimensions, number of snags or number of trees .

A number of these factors are species or guild-specific.Therefore, the task becomes daunting when a landowner wishes to manage his hedgerows without prior bird identification knowledge or a strong understanding of avian ecology and habitat requirements. The purpose of our study was to evaluate which hedgerow attribute was best at predicting avian densities in a conventional and organic farming landscape. Furthermore, we wished to investigate if these same hedgerow attributes could explain arthropod family density, richness and diversity, and how these were correlated to avian densities. Our results would then allow us to provide landowners with a simple, stand-alone hedgerow management strategy that could help in-crease avian diversity through improved habitat and food resource management. An information theory-based multi-model inference method was used to identify which factors best explained avian density variance at organic and conventional farming sites.