Introduction
The structure and composition of land uses and land cover determines the flow of landscape services provided by agricultural landscapes. Often, ecological or landscape indicators are employed to estimate the relation between services and land use/land cover-based metrics. These indicators often consist of simple mathematical equations to describe (often in reality more complex) causal relations between land use/cover and flows of landscape services. They are frequently used to enable the spatial extrapolation of the potential supply of ecosystem services in a landscape. Alternatively, expert-based approaches are available, such as the landscape services assessment matrix to estimate the landscape services associated with different land cover types. These matrices, however, do not identify effects of landscape structure, composition or management in relation to the functions of these landscapes, but often rely solely on land cover, whereas for several types of landscape services it is important to account for landscape structure. Cultural services and pollination, for instance, are related to landscape structure characteristics such as landscape patchiness or openness as a result of the abundance of green landscape elements. Given the complexity of relations between services and landscape, recently other methods, such as Bayesian Belief Networks (BBN) and Analytic Hierarchy or Network Process (AHP/ANP) analyses (which often also rely on expert knowledge) are also applied to quantify associations between landscape characteristics and landscape services.
One should consider that landscape service flows can be measured at different spatial scales and the type of landscape services delivered can vary with the scale of measurement accordingly. At farm or field level, landscape elements such as hedgerows, tree lines or historic buildings potentially delivers a benefit (e.g. via recreational or climate regulating services). At landscape level, spatial structure and composition of landscape elements could benefit society in a different way; the spatial structure can for instance determine the landscapes capacity to deliver pollination services, since landscape structure determines spatial organization of pollinator habitats.
Empirical Case Study Evidence
Below, we discuss case study evidence on relations between landscape structure & composition and flows of landscape services.
Provisioning services
Several ad-hoc studies applied modelling approaches to estimate changes in agricultural output as a result of changing landscape structure and composition. We observe rather different outcomes. In the case study Märkische Schweiz (DE) more agricultural output is expected if green landscape elements removed, whereas in the Polish case study agricultural production, of especially sugar beets and rapeseed, seems to depend on the presence of shelterbelts in the landscape. In the Ferrara case study (IT), a resident survey was used to measure the perceived value of landscape elements for the agricultural sector. Here, all landscape elements were perceived as beneficial to the agricultural sector, except for rice paddies.
Regulating services
We can distinguish between regulating services that benefit the local or global society as a whole or services that are beneficial only to agricultural production. An example of an ad-hoc study looking at services that support agricultural production is the General Chlapowski Landscape Park case study (PL). This study assessed the effect of shelterbelts that surround agricultural fields on the prevention of wind erosion. It was found that yields from several crops, such as rapeseed, sugar beet and potatoes would decrease if shelterbelt were removed. The French and German case study focused on regulating services that benefit society as a whole. An ad-hoc study in the German case study area found that the presence of ponds in agricultural fields contributes to water supply and water regulation. In Corsica, the ad-hoc study assessed the effect of different vegetation pattern on wildfire regulation and found a clear relation between an increase of overall vegetation and the increased occurrence of larger wild fires.
Cultural services
Most ad-hoc studies in the project addressed relations between landscape characteristics and cultural services, such as rural tourism or the visual appreciation of landscapes. We can distinguish between stated preference methods and expert-based approaches. In several ad-hoc studies image-based choice experiments are applied to measure preferences of residents and visitors different landscape scenarios (DE, NL) and also to estimate the influence of landscape characteristics on the probability of visit, such in the Montoro case (ES). In a more descriptive way, a tourists survey (IT) indicated that landscape diversity in the landscape as a results of the presence of woods, hedges and water bodies are to some extent a reason to visit the area. However, the tourists indicated that the presence of beaches outweighed the importance of these landscape characteristics.
Trade-offs and synergies between landscape services
Finally, a number of ad-hoc studies addressed trade-offs and synergies between landscape services. In Polish and Italian case study areas a BBN was developed to assess trade-offs between regulating, cultural and provisioning services in relation to changing management practices and characteristics. In the German case study, trade-offs between services were explicitly addressed using joint probability maps.
Conclusions & recommendations
The ad-hoc studies have mostly addressed the most pressing knowledge gaps: trade-offs and synergies between services and relations between cultural services and landscape structure and composition. Several innovative stated preference approaches were developed which provide useful insights for future landscape scale assessment of cultural services.