G.W.J. van de Ven

Farming options for The Netherlands explored by multi-objective modelling

Abstract Intensive agriculture in The Netherlands has a price in the form of environmental degradation and the diminution of nature and landscape values. A reorientation of farming is needed to find a new balance between economic goals and rural employment, and care for clean water and air, animal well-being, safe food, and the preservation of soil, landscape and biodiversity. The search for farm systems that meet such multiple goals requires a systematic combination of (a) agrotechnical, agroecological and agroeconomic knowledge, with (b) the stakeholders’ joint agreement on normative objectives, to arrive at conceptual new designs followed by (c) empirical work to test, adapt and refine these under real commercial farming conditions. In this paper explorative modelling at the whole farm level is presented as a method that effectively integrates component knowledge at crop or animal level, and outlines the consequences of particular choices on scientific grounds. This enables quantitative consideration of a broad spectrum of alternative farming systems, including very innovative and risky ones, before empirical work starts. It thus contributes to a transparent learning and development process needed to arrive at farm concepts acceptable to both entrepreneurs and society. Three case studies are presented to illustrate the method: dairy farming on sandy soils; highly intensified flower bulb industry in sensitive areas in the western Netherlands; and integrated arable farming. Trade-offs between economic and environmental objectives were assessed in all three cases, as well as virtual farm configurations that best satisfy specified priority settings of objectives. In two of the three cases the mutual reinforcement and true integration of modelling and on-farm empirical research appeared difficult, but for obvious reasons. Only in the flower bulb case was the explorative approach utilized to its full potential by involving a broad platform of stakeholders. The other two case studies lacked such formalised platforms and their impact remained limited. Three critical success factors for explorative modelling are identified: to cover a well-differentiated spectrum of possible production technologies; early timing of modelling work relative to empirical farm prototyping; and involvement of stakeholders throughout.

Concepts in production ecology for analysis and design of animal and plant-animal production systems

Abstract The use of a hierarchy in growth factors (defining, limiting and reducing growth factors), as developed for plant production has shown its usefulness in the analysis and design of plant production systems. This hierarchy presents a theoretical framework for the analysis of biophysical conditions in plant production. We hypothesize that analysis and design of agricultural land use systems is facilitated by development of a similar set of production ecological concepts for animal production, as livestock is often part of such systems. In this paper we present such a hierarchy. We identify growth defining (temperature, daylength, animal genetic characteristics), limiting (water and feed quantity and quality) and reducing (diseases, pollutants and other conditions leading to sub-optimal wellbeing) factors, determining the production of an individual animal, in parallel to their definition for crop production, and aggregate this production to herd scale. We discuss how management intervenes with these factors. Application of the production ecological concepts in design of land use systems ensures that all production systems are based on the prevailing biophysical characteristics and that intrinsic system properties are taken into account. This approach also provides a valuable framework for yield-gap analysis, explaining current production levels, and identifying constraining factors, for setting the research agenda by identifying knowledge gaps and for educational purposes. We illustrate application of the concepts in the exploration and design of alternative animal and mixed plant–animal production systems with two examples. The first example relates to potential production in intensive dairy farming in a temperate climate and the second to feed-limited cattle production in the tropics.

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

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 of 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 trajectories of states and farming decisions fulfilling a given set of ecological and productive constraints representing a desired and sustainable future. The three modelling approaches differ in their policy relevance, in the ways that spatial and socio-institutional scales are addressed and in their degree of explicitation of interaction between the various functions of agriculture, 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 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.

Integrated crop management: an approach to sustainable agricultural development.

In developing countries, agriculture is being intensified to produce more food and agricultural products. In most agricultural development strategies, the order of priorities is on: (i) increasing yields, (ii) crop protection, and (iii) human health, environmental and social aspects. This sequential rather than integrated approach contributes to many problems related to sustainability in agriculture. Examples of increased problems with soil erosion, secondary salinization and waterlogging, soil nutrient depletion, increased pest problems, public health hazards and environmental pollution illustrate this phenomenon. To improve the present situation, agricultural development strategies should be based on an integration of factors determining the agricultural production potential of a particular zone: the biophysical environment, the land reclamation level, and external input use. Integrated Crop Management and systems analyses can help to put these factors in the best perspective, and to set the priorities for agricultural research and development accordingly. Techniques aimed at sustainability are listed, and their use is discussed in areas with different production potentials. To assess the impact of cropping techniques on the sustainability of agricultural production systems, suggestions are made for the monitoring of selected physical, chemical and biotic characteristics of agro-ecosystems.

The production-ecological sustainability of cassava, sugarcane and sweet sorghum cultivation for bioethanol in Mozambique

We present an approach for providing quantitative insight into the production‐ecological sustainability of biofuel feedstock production systems. The approach is based on a simple crop‐soil model and was used for assessing feedstock from current and improved production systems of cassava for bioethanol. Assessments were performed for a study area in Mozambique, a country considered promising for biomass production. Our focus is on the potential role of smallholders in the production of feedstock for biofuels. We take cassava as the crop for this purpose and compare it with feedstock production on plantations using sugarcane, sweet sorghum and cassava as benchmarks. Production‐ecological sustainability was defined by seven indicators related to resource‐use efficiency, soil quality, net energy production and greenhouse gas (GHG) emissions. Results indicate that of the assessed systems, sugarcane performed better than cassava, although it requires substantial water for irrigation. Targeted use of nutrient inputs improved sustainability of smallholder cassava. Cassava production systems on more fertile soils were more sustainable than those on less fertile soils; the latter required more external inputs for achieving the same output, affecting most indicators negatively and reducing the feasibility for smallholders. Cassava and sweet sorghum performed similarly. Cassava production requires much more labour per hectare than production of sugarcane or sweet sorghum. Production of bioethanol feedstock on cultivated lands was more sustainable and had potential for carbon sequestration, avoiding GHG emissions from clearing natural vegetation if new land is opened.

Diversity in smallholder farms growing coffee and their use of recommended coffee management practices in Uganda

Many smallholder farm systems in Uganda produce coffee as an important cash crop. Yet coffee yields are poor. To increase farmers’ production, a range of agronomic practices have been recommended by national and international agencies. Yet the adoption potential of recommendations differs between farm systems. To understand the differences in adoption potential of recommended coffee management practices in Uganda, we provide a typology of farm systems with coffee, assess the diversity between the farm types, and evaluate the current use of existing management recommendations for each farm type. Through factor analysis and cluster analysis of farms producing coffee, we identified five farm types: large coffee farms, farms with off-farm activities, coffee-dependent farms, diversified farms, and banana–coffee farms. The farm types were based on differences in size, and on the relative contributions of coffee, banana and off-farm labour to total household income. They also differ in the availability of the resources labour, land and cash, in coffee production and revenue, and in current use of most recommended practices. Qualitative analysis indicates that farm types have different constraints and opportunities to adopt recommendations. Our results highlight that an analysis of different farmsystems with coffee production, a degree of definition beyond the ‘smallholder coffee farmer’ as a homogenous entity, is important in order to understand the scope for success or failure of recommended practices.