Knowledge Platform


Landscape policies can take different spatial effect, covering horizontal policies which are not site specific at all, like certain regulation and good management practices to more site-specific policy and planning measures either based on European and national legislation, such as the Flora-Fauna Habitat (FFH) and the Water Framework Directive (WFD) or based on regional/local site designations (planning zones, environmental compensation areas, etc.). Through the overall European (FFH and WFD) directives, national (such as ecological and habitat networks), regional (greenways, etc.) specific (ecologically important) sites are predefined to set legal regulations and economic incentives for environmental and landscape management schemes.

The farm location represents an important driver for landscape policy implementation. Organic farming as extensive production, particularly in livestock farming, tends to prevail in locations of less productive and low fertile conditions, such as mountainous areas or areas with low soil fertility.

The ability of how the managed landscape is valorised for regional competitiveness and welfare strongly depends on the regional bio-physical framework conditions. For instance, regions which are characterised by a high degree of natural amenities (theoretically without agricultural landscape management), i.e. through relief energy (mountains) or water courses or forests will therewith attract more visitors than comparable regions without those natural amenities.

Empirical Case Study Evidence

Targeting / Area designation

In several ad-hoc studies (AT, BG, DE) it has been shown that extensive parts of the agricultural landscape are under some form of area designation (e.g. landscape, nature or water protection), having an effect on landscape management. Also agri-environmental measures (AEM, measure 214) are partly targeted at the management for specific geographic settings (mountain area, less favoured areas).

Cost-effectiveness / Heterogeneous natural conditions

Very different natural framework conditions are found within each region, representing very different requirements for AES. Axis 2 measures are effective only in some areas of the region, i.e. by management of low productivity land, preservation of biodiversity and recreation of degraded land (BG). In other cases (FR), AEM are designed in a way that they focus on specific types of land use (e.g. grasslands), which occur in part of the regions, but neglecting others (e.g. mis-targeting for chestnut forests or rangelands).

Temporal and scale mismatch

The implementation of measure 213 (Natura 2000 areas) is in temporal mismatch with AEM. There is a need for flexibilisation of AEM contracting (binding contracting over years: intermission of specific top up measures like late mowing, extensive grazing practices etc. in years of draught). CAP measures are taking effect at farm level, but not at landscape level (NL), creating unwanted effects (e.g., dichotomisation of the landscape (ES)).

Evidence landscape valorisation

Natural amenities

Both, mountain geography and seaside locations represent advantageous basic conditions for socio-economic valorisation of landscape. In the Austrian case, the presence of mountainous landscape has been found more influential on local employment than managed landscape characteristics in particular. On the other hand the absence of natural amenities can lead to a clear underutilisation of the managed agricultural landscape. As observed in the regions of Ferrara (IT) and Corsica (FR), tourism concentrates mainly at the seaside, leaving aside the agricultural hinterland. In those cases the landscape management of these agricultural areas can hardly be adequately valorised in the sense of rural tourism.

Demand-Supply Mismatch

It has been found in different ad-hoc studies that a serious degree of spatial and temporal mismatches between the provision of landscape amenities (through landscape management) and their demand (potential for socio-economic valorisation). Farmers as main providers are rather "production-oriented" and have often little potential to make locally use of the natural capital (e.g. through agri-tourism or diversification). As tourism is mainly driven by natural assets (e.g. mountains, wetlands), cultural heritage (UNESCO site) and or seaside location (FR, IT), potential consumers are concentrated elsewhere or visit only for a limited time (TR).

Conclusions & recommendations

The ad-hoc studies at hand show, that the natural and landscape framework conditions influence the process of landscape policy implementation or the valorisation for regional socio-economic development and competitiveness (e.g. through natural amenities, less-favoured conditions).

Natural amenities

The presence of natural amenities, such as mountains (relief energy) or water courses (coastline) are important pre-conditions to define the potential of landscape management to be further valorised for regional competitiveness and welfare.


The results of the ad-hoc studies at hand call for a more targeted approach to landscape management, which take the specific regional framework conditions into consideration or which understands and incorporates scale-dependency of landscape measures (farm, sub-landscapes, and landscape).


To address the requirements for landscape management in heterogeneous regions and to deal with the shortcoming of the scale issue (policy intervention on farm level, effect on landscape level), stronger coordination of landscape management measures is suggested.

Further reading

Lange, A., Piorr, A., Siebert, R., Zasada, I. (2013). Spatial differentiation of new target groups for farm diversification: How vicinity to cities and rural attractiveness determine farm households strategies for future CAP options. Land Use Policy 13: 136-144.

Matzdorf,B. & Lorenz,J. (2010). How cost-effective are result-oriented agri-environmental measures? An empirical analysis in Germany. Land Use Policy 27: 535-544.

Pfeifer, C., Jongeneel, R.A., Sonneveld, M.P.W., Stoorvogel, J.J. (2009). Landscape properties as drivers for farm diversification: A Dutch case study. Land Use Policy 26(4): 1106-1115.

Piorr, A., Ungaro, F., Ciancaglini, A., Happe, K., Sahrbacher, A., Sattler, C., Uthes, S., Zander, P. (2009). Integrated assessment of future CAP policies: land use changes, spatial patterns and targeting. Environmental Science & Policy 12, 1122-1136.