Monitoring European farmland biodiversity: a cost and information optimisation exercise

Authors and Affiliations: 

I.R. Geijzendorffer 1,2,  F. Herzog3, P. Jeanneret3, Y. Ammari4, S. Angelova5, M. Arndorfer6, D. Bailey3, K. Balázs7, A. Báldi8, M. Bogers9, D. Brus9, R.G.H. Bunce9,10, J.-P. Choisis11, P. Dennis12, T. Dyman13, S. Eiter14, W. Fjellstad14, M.D. Fraser12, T. Frank6, J.K. Friedel6, S. Garchi4, T. Gomiero15, A. Griffioen9 G. Jerkovich12, R.H.G. Jongman9, M. Kainz16, E. Kakudidi17, E. Kelemen7, M. Knotters9, R. Kölliker3, N. Kwikiriza17, A. Kovács-Hostyánszki8, L. Last3, G. Lüscher3, G. Moreno18, C. Nkwiine17, J. Opio17, M.-L. Oschatz6, M.G. Paoletti15, P. Pointereau19, J.- P. Sarthou20, 21, M.K. Schneider3, N. Siebrecht16, D. Sommaggio15, I. Staritsky9, S. Stoyanova5, S. Targetti22, D. Viaggi22, S. Wolfrum16 , S. Yashchenko13




1 Institut de Recherche en Sciences et Technologie pour l'Environnement et l'Agriculture (IRSTEA), Aix-en-Provence 13182 , France,

2 Institut Méditerranéen de Biodiversité et d’Ecologie marine et continentale (IMBE), Aix-Marseille Université, UMR CNRS IRD Avignon Université, Technopôle Arbois-Méditerranée, Bât. Villemin – BP 80, F-13545 Aix-en-Provence cedex 04, France

3 Agroscope Reckenholz-Tänikon Research Station ART, Reckenholzstrasse 191, Zurich 8046, Switzerland. 

4 Institut National de Recherches in Génie Rural, Eaux et Forêt, BP N°10, Ariana 2080, Tunisia.

5 Institute of Plant Genetic Resources K. Malkov, Sadovo 4122, Bulgaria.  

6 University of Natural Resources & Life Sciences, Gregor Mendel Strasse 33, Vienna 1180, Austria. 

7 Institute of Environmental & Landscape Management, Szent Istvan University, Páter Károly u. 1, Gödöllö 2100, Hungary. 

8 MTA Centre for Ecological Research, Alkotmány u. 2-4, Vácrátót 2163, Hungary 

9 Alterra, Wageningen UR, Droevedaalsesteeg 3, Wageningen 6700 AA, The Netherlands. 

10 Estonian University of Life Sciences, Kreuzwaldi 5, Tartu 51041, Estonia 

10 INRA, UMR 1201 Dynafor, Chemin de Borde-Rouge, Castanet-Tolosan 31326, France. 

11Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais Campus, Aberystwyth SY23 3FG, United Kingdom. 

12 Bila Tserkva National Agrarian University, Soborna sq. 8/1, Bila Tserkva 09117, Ukraine.  

13 Norwegian Forest and Landscape Institute, Raveien 9, Ås 1431, Norway. 

14 Department of Biology, Padova University, via U. Bassi 58/b, Padova 35121, Italy. 

15 Centre of Life and Food Science, Technical University of Munich, Alte Akademie 12, Freising  85354, Germany. 

16 School of Agriculture, Makarere University, P.O. Box 7062, Kampala, Uganda. 

17 Forestry School, University of Extremadura, Av. Virgen del Puerto 2, Plasencia 10600, Spain. 

18 SOLAGRO, Initiatives and Innovations for Energy, Agriculture and Environment, 75 Voie du TOEC, Toulouse 31076, France. 

19 Toulouse University; ENSAT; UMR 1248 Agir, Castanet Tolosan 31326, France. 

20 INRA, UMR 1248 Agir, Chemin de Borde-Rouge, Castanet Tolosan 31326, France. 

21 Department of Agricultural Science, University of Bologna, viale Fanin, 50, Bologna 40127, Italy.



With the greening of the Common Agricultural Policy, the ambition to contribute to halting of biodiversity loss outside protected conservation areas and the current financial situation of the European Union, there is a need for (i) a cost efficient monitoring scheme of agricultural biodiversity while simultaneously (ii) maximizing the information gained. Those two requirements result in an optimization exercise.

In the European FP7 project BioBio (, we collected biodiversity data on farm types throughout Europe and consulted stakeholders. We identified 1. A set of biodiversity indicators which is informative for non-scientists and does not include redundant information (Dennis et al. 2010); 2. The costs of collecting these indicators in a routine monitoring scheme (Geijzendorffer et al. 2012). 3. A proposition of a sampling design for the monitoring of agro-biodiversity on farming systems within Europe.

Based on these results, statistical and modeling exercises were undertaken to determine whehter agro-biodiversity monitoring could already be possible using 0.25 % of the total CAP budget. This assumed budget percentage of 0.25 is relatively modest compared with recommended percentages for monitoring activities in literature (e.g. Rieder (2011) proposes 0.5 -10 %) and is lower than that recommended by the European commission (i.e. 0.5 % in EC (2004)).

To answer these questions, explicit effort was undertaken to ensure that changes in biodiversity over space and time can be detected. This aspect is usually not covered by research projects that propose monitoring systems.

The sampling design was developed based on a probability sampling of farms within regions (NUTS2) combined with environmental zones (Metzger et al., 2005) over main farm types, using the current regional distribution of farm types (Jongman et al., 2012) taking into account farm and biodiversity dynamics (type and size).

BioBio focused on monitoring biodiversity at farm scale and it uses farm types within zones as the smallest reporting unit for biodiversity indicators. Whilst this biodiversity monitoring scheme allows the detection of trends in biodiversity, it would not be able to pick up changes at a landscape scale. Therefore it would need to be complemented by a landscape monitoring effort.



Results from the modeling exercise show that with 0.25 % of the CAP budget, 50.000 farms can be monitored which equals 1.7% of the total number of European farms in a rolling 5 years’ survey. Estimations of the farm numbers to be sampled based on data variability included three scenarios with respectively 12.7%, 4.3% and 1.9% of total farm population to be sampled. The 1,7% that can be monitored by the 0.25% of the CAP is less than the percentage in the lowest monitoring scenario computed in this paper based on the data variability, but it is not far off indicating a true potential for monitoring for a realistic budget allocation. 

Keywords: monitoring, sampling design, agro-biodiversity, cost-effectiveness


We would like to thank all stakeholders for their input and all farmers that allowed us access to their lands on multiple occasions and all the field teams that took up the challenge to collect data for the BioBio protocol.

Part of the BioBio project was funded under the 7th framework program of the European Union (Grant KBBE 227161). This presentation was made possible by the EU BON project ( which is funded under the 7th framework program of the European Union (Grant no 308454).



Dennis, P., Herzog, F. and Jeanneret, P., (Editors), 2010. Selection and field validation of candidate biodiversity indicators, including field manual. Aberystwyth, Deliverable 2.1 of the EU FP7 Project BioBio.

Geijzendorffer, I., S. Targetti, R. Jongman and D. Viaggi , 2012. Implementing a biodiversity monitoring scheme for European farms. Book chapter in Biodiversity Indicators for European Farming systems, editors: Herzog, F., K.Balázs, P. Dennis, J. Friedel, I. Geijzendorffer, P. Jeanneret, M.Kainz and P. Pointereau, ART-Schriftenreihe 17, 79-89p.

Jongman, R.H.G., I. Staritsky, I. Geijzendorffer, F. Herzog, D. Viaggi and S. Targetti, 2012. Report on suitability of continental scale indicators for reflecting biodiversity of organic/low input farming systems, proposition of a monitoring system at the continental scale. Deliverable 4.2 of the EU FP7 Project BioBio.

Metzger, M., R.G.H. Bunce, R.H.G. Jongman, C. A. Mücher and J.W. Watkins, 2005. A climatic stratification of the environment of Europe. Global Ecol. Biogeogr. 1-15.

Rieder, S., 2011, Kosten von Evuationen. Leges 1, 73-88.