On the contribution of modelling to multifunctional agriculture: learning from comparisons

Groot, Jeroen C.J. and Rossing, Walter a.H. and Tichit, Muriel and Turpin, Nadine and Jellema, André and Baudry, Jacques and Verburg, Peter and Doyen, Luc and van de Ven, Gerrie (2009): On the contribution of modelling to multifunctional agriculture: learning from comparisons. Published in: Journal of Environmental Management , Vol. 90, (May 2009): pp. 147-160.

Abstract

In this paper a set of criteria is proposed for the evaluation of the potential contribution of modelling tools to strengthening the multifunctionality of agriculture. The four main areas of evaluation are (1) policy relevance, (2) the temporal resolution and scope, (3) the degree to which spatial and socio institutional scales and heterogeneity are addressed and (4) the level of integration in the assessment of scientific dimensions and of the multiple functions of agriculture. The evaluative criteria are applied to the portfolio of modelling approaches developed and applied in a joint project of the French research institute INRA and the Dutch Wageningen University & Research Centre. The CLUE-S model focuses on prediction of changes in multifunctional land-use at regional scale, given a set of predetermined scenarios or policy variants, e.g. for ex-ante policy assessment and initiation discussions on regional development. The two other modelling approaches are complementary and aim to address multifunctional farming activities. The Landscape IMAGES framework generates a range of static images of possible but sometimes distant futures for multifunctional farming activities in a small region or landscape. It supports the exploration of trade-offs between financial returns from agriculture, landscape quality, nature conservation and restoration, and environmental quality. Co-Viability Analysis generates viable trajectories of changes in farming activities within a given set of constraints, to reach a desired future. In the application implemented in the project, co-viability analysis focuses on grassland grazed by cattle which is also the breeding habitat of two wader species at field level. The three modelling approaches differ in their policy relevance, in the ways that spatial and socio institutional scales are addressed and in their levels of integration, but jointly cover most of the desired capabilities for assessment of multifunctionality. Caveats were particularly identified in the integration of the socio-institutional dimension and the related heterogeneity. Although the model portfolio did not completely satisfy the demands of the of the set of evaluative criteria, it is concluded that, due to their complementarities, in combination the three models could significantly contribute to further development and strengthening of multifunctionality.

• Item Type: MPRA Paper
• Language: English
• Keywords: multifunctionality, modelling, exploration, solution space, scales, policy
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis; C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C88 - Other Computer Software; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q18 - Agricultural Policy ; Food Policy; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q57 - Ecological Economics: Ecosystem Services ; Biodiversity Conservation ; Bioeconomics ; Industrial Ecology; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q58 - Government Policy

References

Annets, J.E., Audsley, E., 2002. Multiple objective linear programming for environmental planning. J. Oper. Res. Soc. 53, 933–943.

Arheimer, B., Torstensson, G., Wittgren, H.B., 2004. Landscape planning to reduce coastal eutrophication: agricultural practices and constructed wetlands. Landsc. Urban Plann. 67, 205–215.

Aubin, J.P., 1991. Viability Theory. Birkha¨user, Boston. Barkaoui, A., Butault, J.-P., 2004. Impacts sur l’offre des régions françaises de la réforme de la PAC de 2003. INRA Sciences Sociales 4–5, 6.

Beintema, A.J., Mu¨ skens, G.J.D.M., 1987. Nesting success of birds breeding in Dutch agricultural grasslands. J. Appl. Ecol. 24, 743–758.

Béné , C., Doyen, L., Gabay, D., 2001. A viability analysis for a bio-economic model. Ecol. Econ. 36, 385–396.

Berger, P.A., Bolte, J.P., 2004. Evaluating the impact of policy options on agricultural landscapes: an alternative-futures approach. Ecol. Applic. 14, 342–354.

Bergey, P.K., Ragsdale, C., 2005. Modified differential evolution: a greedy random strategy for genetic recombination. Omega-Int. J. Manage. Sci. 33, 255–265.

Beissinger, S.R., Westphal, M.I., 1998. On the use of demographic models of population viability in endangered species management. J. Wildl. Manag. 62, 821–841.

Bohnet, I., Smith, D.M., 2007. Planning future landscapes in the Wet Tropics of Australia: a social–ecological framework. Landsc. Urban Plann. 80, 137–152.

Bouma, J., Stoorvogel, J.J., Quiroz, R., Staal, S., Herrero, M., Immerzeel, W., Roetter, R.P., Van den Bosch, H., Sterk, G., Rabbinge, R., Chater, S., 2007. Ecoregional research for development. Adv. Agron. 93, 257–311.

Clark, J., 2006. The institutional limits to multifunctional agriculture: subnational governance and regional systems of innovation. Environ. Plann. C 24, 331–349.

Crossman, N.D., Bryan, B.A., 2006. Systematic landscape restoration using integer programming. Biol. Conserv. 128, 369–383.

Cury, P.M., Mullon, C., Garcia, S.M., Shannon, L.J., 2005. Viability theory for an ecosystem approach to fisheries. ICES J. Mar. Sci. 62, 577–584.

DATAR, 2003. Quelle France rurale pour 2020? Contribution a` une nouvelle politique du développement durable. DATAR, Paris, 59 pp.

De Lara, M., Doyen, L., Gilbaud, T., Rochet, M.J., 2007. Is a management framework based on spawning-stock biomass indicators sustainable? A viability approach. ICES J. Mar. Sci. 64, 761–767.

DeVoil, P., Rossing, W.A.H., Hammer, G.L., 2006. Exploring profit – sustainability trade-offs in cropping systems using evolutionary algorithms. Environ. Model. Softw. 21, 1368–1374.

De Wit, C.T., Van Keulen, H., Seligman, N.G., Spharim, I., 1988. Application of interactive multiple goal programming techniques for analysis and planning of regional agricultural development. Agric. Syst. 26, 211–230.

Doyen, L., Be´ne´ , C., 2003. Sustainability of fisheries through marine reserves: a robust modelling analysis. J. Environ. Manag. 69 (1), 1–13.

Durand, G., Van Huylenbroeck, G., 2003. Multifunctionality and rural development: a general framework. In: Van Huylenbroeck, G., Durand, G. (Eds.), Multifunctional Agriculture: A New Paradigm for European Agriculture and Rural Development. Ashgate Publishing Limited, Hampshire, England, pp. 1–16.

Eisenack, K., Scheffran, J., Kropp, J.P., 2006. Viability analysis of management frameworks for fisheries. Environ. Model. Assess. 11, 69–79.

Ferrière, R., Sarrazin, F., Legendre, S., Baron, J.-P., 1996. Matrix population models applied to viability analysis and conservation: theory and practice using the ULM software. Acta. Oecol. 17, 629–656.

Geertsema, W., 2002. Plant survival in dynamic habitat networks in agricultural landscapes. PhD thesis, Wageningen University, Wageningen.

Goldberg, D.E., 1989. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, MA, 412 pp.

Green, R.E., Cornell, S.J., Scharlemann, J.P.W., Balmford, A., 2005. Farming and the fate of wild nature. Science 207, 550–555.

Groot, J.C.J., Rossing, W.A.H., Jellema, A., Stobbelaar, D.J., Renting, H., Van Ittersum, M.K., 2007. Exploring multi-scale trade-offs between nature conservation, agricultural profits and landscape quality – a methodology to support discussions on land-use perspectives. Agric. Ecosyst. Environ. 120, 58–69.

Gude, P.H., Hansen, A.J., Rasker, R., Maxwell, B., 2006. Rates and drivers of rural residential development in the Greater Yellowstone. Landsc. Urban Plann. 77, 131–151.

Hajkowicz, S., Perraud, J.M., Dawes, W., DeRose, R., 2005. The strategic landscape investment model: a tool for mapping optimal environmental expenditure. Environ. Model. Softw. 20, 1251–1262.

Hisschemo¨ ller, M., Tol, R.S.J., Vellinga, P., 2001. The relevance of participatory approaches in integrated assessment. Integr. Assess. 2, 57–72.

Holman, I.P., Rounsevell, M.D.A., Shackley, S., Harrison, P.A., Nicholls, R.J., Berry, P.M., Audsley, E., 2005. A regional, multi-sectoral and integrated assessment of the impacts of climate and socio-economic change in the UK. Clim. Change 71, 9–41.

Irwin, E.G., Geoghegan, J., 2001. Theory, data, methods: developing spatially explicit economic models of land use change. Agric. Ecosyst. Environ. 85, 7–23.

Kleijn, D., Berendse, F., Smit, R., Gilissen, N., 2001. Agri-environment schemes do not effectively protect biodiversity in Dutch agricultural landscapes. Nature 413, 723–725.

Knickel, K.H., Renting, H., 2000. Methodological and conceptual issues in the study of multifunctionality and rural development. Sociol. Ruralis 40, 512–528.

Lankoski, J., Ollikainen, M., 2003. Agri-environmental externalities: a framework for designing targeted policies. Eur. Rev. Agric. Econ. 30, 51–75.

Losch, B., 2004. Debating the multifunctionality of agriculture: from trade negotiations to development policies by the South. J. Agrar. Change 4, 336–360.

Makowski, D., Hendrix, E.M.T., Van Ittersum, M.K., Rossing, W.A.H., 2000. A framework to study nearly optimal solutions of linear programming models developed for agricultural land use exploration. Ecol. Model. 131, 65–77.

Marshall, E.P., Homans, F.R., 2006. Juggling land retirement objectives on an agricultural landscape: coordination, conflict, or compromise? Environ. Manag. 38, 37–47.

Martinet, V., Doyen, L., 2007. Sustainability of an economy with an exhaustible resource: a viable control approach. Resour. Energy Econ. 29, 17–39.

Matthews, K.B., Buchan, K., Sibbald, A.R., Craw, S., 2005. Combining deliberative and computer-based methods for multi-objective land-use planning. Agric. Syst. 87, 18–37.

McIntosh, B.S., Jeffrey, P., Lemon, M., Winder, N., 2005. On the design of computer based models for integrated environmental science. Environ.Manag. 35, 741–752.

Mimouni, M., Zekri, S., Flichman, G., 2000. Modelling the trade-offs between farm income and the reduction of erosion and nitrate pollution. Ann. Oper. Res. 94, 91–103.

Moffett, A., Garson, J., Sarkar, S., 2005. MultCSync: a software package for incorporating multiple criteria in conservation planning. Environ. Model. Softw. 20, 1315–1322.

Mu¨ nier, B., Birr-Pedersen, K., Schou, J.S., 2004. Combined ecological and economic modelling in agricultural land use scenarios. Ecol. Model 174, 5–18.

Newburn, D.A., Berck, P., Merenlender, A.M., 2006. Habitat and open space at risk of land-use conversion: targeting strategies for land conservation. Am. J. Agric. Econ. 88, 28–42.

OECD, 2001. Multifunctionality – Towards an Analytical Framework. Organisation for Economic Co-operation and Development, Paris, 27 pp.

Oomes, M.J.M., 1992. Yield and species density of grassland during restoration management. J. Veg. Sci. 3, 271–274.

Overmars, K.P., Verburg, P.H., Veldkamp, T., 2007. Comparison of a deductive and an inductive approach to specify land suitability in a spatially explicit land use model. Land Use Pol., in Press.

J.C.J. Groot et al. / Journal of Environmental Management 90 (2009) S147–S160 S159 Renting, H., Rossing, W.A.H., Groot, J.C.J., Van der Ploeg, J.D., Laurent, C., Perraud, D., Stobbelaar, D.J., Van Ittersum, M.K., 2009. Exploring multifunctional agriculture. A review of conceptual approaches and prospects for an integrative transitional framework. J. Environ. Manage. 90 (S2), S112–S123.

Roetter, R.P., Hoanh, C.T., Laborthe, A.G., Van Keulen, H., Van Ittersum, M.K., Dreiser, C., Van Diepen, C.A., De Ridder, N., Van Laar, H.H., 2005. Integration of Systems Network (SysNet) tools for regional land use scenario analysis in Asia. Environ. Model. Softw. 20, 291–307.

Rossing, W.A.H., Zander, P., Josien, E., Groot, J.C.J., Meyer, B., Knierim, A., 2007. Integrative modeling approaches for analysis of impact of multifunctional agriculture: a review for France, Germany and The Netherlands. Agric. Ecosyst. Environ. 120, 41–57.

Rothley, K.D., 1999. Designing bioreserve networks to satisfy multiple, conflicting demands. Ecol. Applic. 9, 741–750.

Rothley, K.D., 2006. Finding the tradeoffs between the reserve design and representation. Environ. Manag. 38, 327–337.

Sarkar, S., Garson, J., 2004. Multiple criterion synchronisation for conservation area network design: the use of non-dominated alternative sets. Conserv. Soc. 2, 433–448.

Sattler, C., Schuler, J., Zander, P., 2006. Determination of trade-off-functions to analyse the provision of agricultural non-commodities. Int. J. Agric. Res. Govern. Ecol. 5, 309–325.

Strange, N., Thorsen, B.J., Bladt, J., 2006. Optimal reserve selection in a dynamic world. Biol. Conserv. 131, 33–41.

Storn, R., Price, K., 1995. Differential evolution – a simple and efficient adaptive scheme for global optimization over continuous spaces. International Computer Science Institute, Berkeley, USA, 12 pp. Technical Report TR-95–012.

Swagemakers, P., Wiskerke, J.C.S., 2004. Integrating nature conservation and landscape management in farming systems in the Friesian Woodlands. In: Tress, B., Tres, G., Fry, G., Opdam, P. (Eds.), From Landscape Research to Landscape Planning Aspects of Integration, Education and Application. Wageningen UR Frontis Series, vol. 12. Springer, Dordrecht, The Netherlands, pp. 321–334.

Tichit, M., Doyen, L., Lemel, J.Y., Renault, O., Durant, D., 2007. A co-viability model of grazing and bird communitymanagement in farmland. Ecol.Model. 206, 277–293.

Tichit, M., Durant, D., Kerne´ ı¨s, E., 2005a. The role of grazing in creating suitable sward structures for breeding waders in agricultural landscapes. Livest. Prod. Sci. 96, 119–128.

Tichit, M., Hubert, B., Doyen, L., Genin, D., 2004. A viability model to assess the sustainability of mixed herds under climatic uncertainty. Anim. Res. 53, 405–417.

Tichit, M., Renault, O., Potter, T., 2005b. Grazing regime as a tool to assess positive side effects of livestock farming systems on wading birds. Livest. Prod. Sci. 96, 109–117.

Tscharntke, T., Klein, A.M., Kruess, A., Steffan-Dewenter, I., Thies, C., 2005. Landscape perspectives on agricultural intensification and biodiversity – ecosystem service management. Ecol. Lett. 8, 857–874.

Turnhout, E., Hisschemoller, M., Eijsackers, H., 2007. Ecological indicators: between the two fires of science and policy. Ecol. Indic. 7, 215–228.

Turpin, N., Dupraz, P., Thenail, C., Joannon, A., Baudry, J. et al., 2006. Landscape organisation and multifunctionality in the Beauce plain at local and regional scales: a scenario analysis with the CLUE-S model. First Workshop on Landscape Economics, Angers, Institut National d’Horticulture, 9–10 juin 2006, p. 21.

Van Der Ploeg, J.D., Bouma, J., Rip, A., Rijkenberg, F.H.J., Ventura, F., Wiskerke, J.S.C., 2004. On regimes, novelties, niches and co-production. In: Wiskerke, J.S.C., van der Ploeg, J.D. (Eds.), Seeds of Transition. Essays on Novelty Production, Niches and Regimes in Agriculture. Van Gorcum, Assen, pp. 1–27.

Van de Ven, G.W.J., Van Keulen, H., 2007. A mathematical approach to comparing environmental and economic goals in dairy farming: identifying strategic development options. Agric. Syst. 94, 231–246.

Van Ittersum, M.K., Rabbinge, R., 1997. Concepts in production ecology for analysis and quantification of agricultural input–output combinations. Field Crops Res. 52, 197–208.

Van Langevelde, F., Claassen, F., Schotman, A., 2002. Two strategies for conservation planning in human-dominated landscapes. Landsc. Urban Plann. 58, 281–295.

Verburg, P.H., Soepboer,W., Veldkamp, A., Limpiada, R., Espaldon, V., Mastura, S.S.A., 2002. Modeling the spatial dynamics of regional land use: the CLUE-S model. Environ. Manag. 30, 391–405.

Verburg, P.H., Eickhout, B., van Meijl, H., 2008. A multi-scale, multi-model approach for analyzing the future dynamics of European land use. Ann. Reg. Sci., doi:10.1007/s00168-007-0136-4.

Wossink, A., Van Wenum, J., Jurgens, C., De Snoo, G., 1999. Co-ordinating economic, behavioural and spatial aspects of wildlife preservation in agriculture. Eur. Rev. Agric. Econ. 26, 443–460.

Young, O.R., Lambin, E.F., Alcock, F., Haberl, H., Karlsson, S.I., McConnell, W.J., Myint, T., Pahl-Wostl, C., Polsky, C., Ramakrishnan, P.S., Schroeder, H., Scouvart, M., Verburg, P.H., 2006. A portfolio approach to analyzing complex human-environment interactions: institutions and land change. Ecol. Soc. 11 (2), 31.

Zander, P., Groot, J.C.J., Josien, E., Karpinski, I., Knierim, A., Meyer, B.C., Madureira, L., Rambonilaza, M., Rossing, W.A.H., 2008. Farm models and economic valuation in the context of multifunctionality: a review of approaches from France, Germany, The Netherlands and Portugal. Int. J. Agric. Res. Govern. Ecol. 7 (4/5), 339–360.

Zander, P., Ka¨chele, H., 1999. Modelling multiple objectives of land use for sustainable development. Agric. Syst. 59, 311–325.