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SCALETOOL IntroductionDriversBiodiversityPolicies and managementConnectivity and protected areas

The Importance of Connectivity for Agri-Environment Schemes

The effectiveness of Agri-Environment Schemes could be improved with use of spatial prioritization tools. The key challenge is in developing voluntary based mechanism so that the chances of inclusion of the most valuable areas are increased without compromising the legitimacy of conservation in the eyes of the land owners.


Agricultural intensification and land abandonment are two major drivers of biodiversity decline throughout Europe. Together they have led to a dramatic decline of semi-natural grasslands, resulting in severe habitat loss and fragmentation across Europe. Agri-environment schemes (AES), regulated and funded by both the EU and national government in Finland, provide a potentially important multi-scale tool to mitigate the harmful impacts of agriculture on biodiversity. However, despite high expenditures, experiences of the effectiveness of AES have been mixed.

One possible reason for the mixed performance of the AES is that the ecological effects arising from the landscape structure on the success of conservation have been neglected. Despite abundant evidence of the importance of connectivity to species persistence, the subsidies are allocated at the local farm scale independently of any landscape context or subsidies given to other farms in the region. This suggests that the use of subsidies could be much more effective if spatially coordinated to enhance ecological processes, such as dispersal. This module provides an example how the use of spatial prioritization tools may help with more effective allocation of agri-environment schemes. The case study area is situated in South-Western Finland, where high-resolution GIS data on the occurrence of semi-natural grasslands is available.

Methods: Spatial conservation prioritization with Zonation software

In this study, the grassland cells for management were prioritized with the Zonation software v3.1. The Zonation prioritization outputs can be used to identify well-connected networks of high quality habitats. The analyses were replicated with and without connectivity. Connectivity was implemented by using a 2km-wide "distribution smoothing" kernel in the Zonation cell value calculations: the value of each cell increases the value of its surrounding cells following the shape of the smoothing kernel so that cells located close to each other are highlighted in the solution as compared with isolated cells. This ensured that the connectivity among grassland patches reflected adequately the commonly used value for the mean dispersal range of grassland species. Three different datasets were used in the analyses: (I) Grasslands of conservation concern, (II) Other grasslands, and semi-natural pasture areas, (III) Areas that have (or have had) AES management contracts of semi-natural habitats recently. Datasets I-II were combined as the "habitat layer", whereas the management contracts (III) were handled as a separate layer (Figure 1). The cells were given weights from 0.5 to 4 in the Zonation analyses on the basis of their conservation value.

Figure 1: Descriptions of the input data. The upper part describes the raw data (I–III) used to derive two input layers to Zonation, described in the lower part. In the input layers the large numbers indicate weights given to those cells based on their assumed conservation value. The flower symbols indicate open sites, and the trees indicate wooded sites that were considered of lower conservation value currently, but were included with lower weights because they have potential for restoration and importance for improving connectivity of the network.


When connectivity is not included, the priorities are scattered and closely follow the locations of most valuable traditional biotope sites. Inclusion of connectivity helps to identify more ecologically coherent networks where species persistence is facilitated by easier dispersal between grassland patches (Figure 2). These networks may also contain some grassland areas or partly wooded sites of lower current conservation value, but which could be improved by securing management through the AES.

Figure 2: Management status of ranked cells. The cells are divided into different Zonation priority rank categories from best 5% (top) to worst 10% (bottom). Each bar shows the distribution of cells into the two types of management contract sites and sites outside agri-environment schemes.

The highest priorities identified by Zonation partially coincided with the areas that were under agri-environment scheme management contracts (Figure 3). However, ca. 25-30% of the sites with highest conservation value were unmanaged, and therefore are likely to eventually be suffocated by succession and lost. Some areas under management contracts fell into the lowest priority categories according to Zonation: altogether 12% of area that ranks lower than top 20% in Zonation is under management contracts. These are mostly very small and isolated sites that may have a history as traditional biotopes that are required from the AES contract sites, but which are unlikely to maintain viable populations of valuable species into the future.

Figure 3: Land cover (a) and priority rank maps (b-c). The land cover map shows the locations of open and wooded traditional biotope (TBT) sites, and broad land cover categories for the surrounding landscape (b). The colors in (b-c) indicate high (red tones) and low (black) conservation priority: e.g. the best 2% of the landscape are in bright red. The maps are shown only for a small subsection or our study region because the grassland sites are very small and scattered, and would show poorly on a full map of the region. (b) is the solution without connectivity, and in (c) we have used the distribution smoothing feature in Zonation, where a 2km kernel was used for calculating a smoothed conservation value of the raster cells to ensure connectivity between valuable sites.

Further, the study indicated that the conservation value of the currently managed network was 85% of that of an optimal network. To achieve the same conservation benefits as with an optimal network of sites selected by Zonation, the current network of managed sites should be expanded by 50%, or by 1700 ha. While this expansion seems realistically achievable, our results also show that reallocation of management contracts from scratch would be a more cost-effective strategy than expansion of present-day network of AES sites.


In order to improve the effectiveness of voluntary agri-environment schemes, decision-makers should include landscape scale criteria among the other criteria that are used in the planning process for granting subsidies. Spatial conservation prioritization tools, like Zonation, have the potential to provide useful information helping to target locations that should receive high priority for conservation management.

The success of the agri-environment schemes depends on their ability to motivate and involve the right people to take management action on the right sites. Potential means to achieve this include:
  • Increased financial compensation. Currently only expenses are covered, which offers no true incentive for the farmers to participate.
  • Differentiating payments according to the conservation value of the site. This could encourage the owners with the most valuable sites to enroll.
  • Agglomeration bonuses to enhance spatial connectivity. This could encourage the farmers to establish regional collaborations, ensuring the management of large enough habitat networks.
  • Improved dialogue between authorities and the land owners, to enhance landowners' awareness of the possibilities to use agri-environment schemes in safeguarding biodiversity as well as to share various knowledge about the conservation values and management demands of habitats and species that the schemes target.


Arponen A, Heikkinen RK, Paloniemi R, Pöyry J, Similä J, Kuussaari M (2013) Improving conservation planning for semi-natural grasslands: Integrating connectivity into agri-environment schemes. Biological Conservation 160: 234-241. http://dx.doi.org/10.1016/j.biocon.2013.01.018

Kleijn D, Rundlöf M, Scheper J, Smith HG, Tscharntke T (2011) Does conservation on farmland contribute to halting the biodiversity decline? Trends in Ecology & Evolution 26: 474-481. http://dx.doi.org/10.1016/j.tree.2011.05.009

Moilanen A, Leppänen J, Meller L, Montesino Pouzols F, Arponen A, Kujala H (2012) Spatial conservation planning framework and software Zonation v. 3.1: User manual. http://cbig.it.helsinki.fi/software/zonation/
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