Designing sustainable agricultural production systems for a changing world: Methods and applications. Over the next 40 years agriculture will have to increase ...
Agricultural Systems 126 (2014) 1–2
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Preface
Designing sustainable agricultural production systems for a changing world: Methods and applications Over the next 40 years agriculture will have to increase food production by an estimated 70% at least, on nearly the same area of land, under increasing costs of energy and other inputs, and under evident climate change (Lobell et al., 2009; State of Food Insecurity in the World, 2013). Ecological intensification of agricultural production has been proposed as a way forward for agriculture to meet these challenges (Cassman, 1999; Doré et al., 2011). The required practices, technologies, tactics and strategies are likely to differ between low and high income countries, across agro-ecologies, farming systems, and households having access to contrasting levels of resources and markets. It is clear that no single solution will be able to achieve sustainable economic development across this diversity of more or less rural-based economies around the globe. Despite the complexity of the problem, opportunities are urgently needed to increase agricultural production and feed a growing population while reducing the negative environmental impacts of agriculture, and increasing its contribution to natural capital and environmental services. A conference in Catania in 2007 brought together for the first time a community of scientists with an interest in farming systems design and the use of systems modelling as the common method. Studies presented at the conference aimed at bringing together knowledge, exploring options for development and proposing redesigns, by focusing on quantitative understanding of the farm components crops, soils, animals and manure, and their interactions. The contributions revealed a flurry of new and exciting approaches in modelling of farming systems. They also showed that in many cases traditional field-level agronomic studies prevailed and the change in level of the research object was a transition for the agricultural sciences involved. The success of the conference signaled the unexpectedly large interest of researchers to develop approaches and tools to support sustainable development of farming systems worldwide. Since the Catania conference, a conference in 2009 in Monterey, USA, reconfirmed the interest of the community to inform the dialog of science with practice, policy and business, and to foster co-learning processes. In this special issue, developed after the 3rd Farming Systems Design Conference held from 26–29 September 2011 in Brisbane, we present examples that illustrate the state of the art in characterization, assessment and re-design to improve the sustainability of farming systems around the world. The first paper of this Special Issue examines fundamental properties of complex systems dynamics and their relation with the mechanisms that govern resilience and transformability in African smallholder agriculture, with the aim of translating resilience thinking theory into farming systems design practice (Tittonell, http://dx.doi.org/10.1016/j.agsy.2014.02.003 0308-521X/Ó 2014 Published by Elsevier Ltd.
2014). The second and third papers present examples of applications of quantitative modelling to assess farm sustainability gaps with the aim of identifying strategies to improve farm performance (Cortez-Arriola et al., 2014; Alvarez et al., 2014). The fourth paper presents the development and application of a spatially explicit dynamic model to assess the extent to which biodiversity can be enhanced by altering landscape structure without reducing agricultural production (Sabatier et al., 2014). The fifth paper presents the use of a whole farm model in a participatory modelling research approach to examine the sensitivity of four contrasting case study farms to a likely climate change scenario (Rodríguez et al., 2014). The sixth paper introduces gaming methodology developed to actively involve farmers in the process of agro-ecosystem design at landscape level (Speelman et al., 2014). The last paper presents the main outcomes of a multiyear co-innovation process that involved farmers, technical advisers and scientists in a systemic diagnosis and redesign of the farm systems (Dogliotti et al., 2014). These examples show how the field has expanded since the first Farming Systems Design conference in 2007. Both static (Alvarez et al., 2014; Cortez-Arriola et al., 2014) and dynamic farm modelling approaches (Rodríguez et al., 2014) have found their place in the literature. Their distinctive data demand and opportunities for exploring alternatives allow them to cater to specific aims. While process-based, dynamic approaches enable understanding system dynamics that include farmer feedbacks in the long run, static approaches may in many data-limited conditions be superior for assessment of key system properties and their development opportunities. Agent-based modelling and gaming as a way to inform both societal stakeholders and modelling on consequences of human decision making for resource utilization has become an important community in itself. The contribution of Speelman et al. (2014) shows that also with farmers, rather than commonly with land users, relevant insights can be gleaned. The contribution of Sabatier et al. (2014) shows that linkages between the farming systems design community and ecology need to be accompanied by approaches that take into account the spatially explicit nature of dispersal processes in ecology. Moreover, depending on the sizes of farms, ecological questions may take us at supra-farm spatial and temporal scales. Resilience thinking may allow new insights into macro-level processes affecting farming systems. The contribution from Tittonell (2014) builds on a body of concepts that have as yet not been applied to farming systems evolution, and are suffering from a chronic lack of data. Monitoring farms over time has received little attention in agronomic research. From this contribution it is clear that insights in farm trajectories can inform strategic
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decisions on types of useful interventions, as well as create insight in farmer rationalities that enable better targeting of research. The contribution by Dogliotti et al. (2014) demonstrates how farming systems approaches result in improvement of farmer livelihoods. Modelling has its place in such innovation processes, but the example suggests that we need to think beyond ‘kitchen table’ use of models with farmers and see the models as learning tools for researchers that can engage with farmers based on clearer ideas about critical blockages in systems and their resolution. The contribution begs the question about the design of larger-scale innovation processes and how to optimally position farming systems research to support these. With these examples we expect to contribute to a better understanding on the types of constraints, gaps and opportunities for improvement across the spectrum of resource availabilities/constraints, risk attitudes, and socio-economic environments we find in our interactions with farmers and their communities. References Alvarez, S., Rufino, M.C., Vayssières, J., Salgado, P., Tittonell, P., Tillard, E., Bocquier, F., 2014. Whole-farm nitrogen cycling and intensification of crop-livestock systems in the highlands of Madagascar: an application of network analysis. Agric. Syst. 126, 24–36. Cassman, K.G., 1999. Ecological intensification of cereal production systems: yield potential, soil quality, and precision agriculture. Proc. Natl. Acad. Sci. U.S.A. 96, 5952–5959. Cortez-Arriola, J., Groot, J.C., Améndola, R.D., Scholberg, J.M.S., Mariscal Aguayo, V., Tittonell, P., Rossing, W.A.H., 2014. Resource use efficiency and farm productivity gaps of smallholder dairy farming in North-west Michoacan, Mexico. Agric. Syst. 126, 14–23. Dogliotti, S., García, M.C., Peluffo, S., Dieste, J.P., Pedemonte, A.J., Bacigalupe, G.F., Scarlato, M., Alliaume, F., Alvarez, J., Chiape, M., Rossing, W.A.H., 2014. Co-innovation of family farm systems: a systems approach to sustainable agriculture. Agric. Syst. 126, 75–85.
Doré, T., Makowski, D., Malézieux, E., Munier-Jolaind, N., Tchamitchian, M., Tittonell, P., 2011. Facing up to the paradigm of ecological intensification in agronomy: revisiting methods, concepts and knowledge. Eur. J. Agronomy 34, 197–210. Lobell, D.B., Cassman, K.G., Field, C.B., 2009. Crop yield gaps: their importance, magnitudes, and causes. Annu. Rev. Environ. Resour. 34, 179–204. Rodríguez, D., Cox, H., deVoil, P., 2014. A participatory whole farm modelling approach to understand impacts and increase preparedness to climate change in Australia. Agric. Syst. 126, 49–60. Sabatier, R., Doyen, L., Tichit, M., 2014. Heterogeneity and the trade-off between ecological and productive functions of agro-landscapes: a model of cattle-bird interactions in a grassland agroecosystems. Agric. Syst. 126, 37–48. Speelman, E.N., García-Barrios, L.E., Groot, J.C.J., Tittonell, P., 2014. Gaming for smallholder participation in the design of more sustainable agricultural landscapes. Agric. Syst. 126, 61–74. Tittonell, P., 2014. Livelihood strategies, resilience and transformability in African agroecosystems. Agric. Syst. 126, 2–13.
S. Dogliotti Universidad de la República, Facultad de Agronomía, Uruguay D. Rodríguez University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Toowoomba, Australia S. López-Ridaura Climate Change and Food Security – Global Conservation Agriculture Program, CIMMYT, Mexico INRA, UMR Innovation, Montpellier, France P. Tittonell W.A.H. Rossing Wageningen University, Farming Systems Ecology, Wageningen, The Netherlands
