Search

Modern agriculture has been focused on optimizing production, neglecting supporting and regulating ecosystem services. Meta-analyses have demonstrated the potential of intercropping to deliver multiple ecosystem services. However, guidelines for the design and management of such systems remain unclear, especially for the understudied vegetable-based intercropping systems. Given the diversity of vegetable crops, we propose a ‘relay’ of classical crop-specific meta-analyses to capitalize on vegetable intercropping research. Each ‘leg’ in the relay analyzes the effects of companion crops on a focal crop, and over the course of subsequent legs, the network of interactions among the different crops is built. In this study we start what we aspire to be the meta-analysis relay, focusing on cabbage (Brassica oleracea ssp.) and the delivery of the provisioning services Productivity, Product Quality (grade and pest injury in cabbage products), and Yield Stability across different companion species, spatio-temporal configurations, and management practices. We identified 76 studies from all inhabited continents across 81 field sites, comprising 892 data records, of which 689 remained after cleaning. We show that intercropping reduced cabbage productivity (−7% on average, P < 0.05) but also pest injury (−48%, P < 0.001) relative to sole cabbage systems. Cabbage grade on the contrary was not significantly improved by intercropping (+1%, P = 0.71). Effects on yield stability varied widely as only few data records were available from trials conducted over more than two years, pointing to the need for longer-term experimentation. Greater productivity was associated with companion species with a low growth habit or types sown at or after planting of the cabbage crop thus limiting competition with cabbage at early development stages. The decrease in pest injuries was associated with intercropping patterns involving strong inter-plant interactions (i.e., mixed, row, and additive) and companion species that supported biodiversity such as living mulches. Overall, beneficial effects of intercropping tended to be more evident in organic production systems, possibly because synthetic inputs may have hidden regulating effects. Cabbage growers and agricultural advisors can use these guidelines when designing intercrop systems specific to their needs. Applying the approach to other crops and agro-ecosystem services as part of the proposed meta-analysis relay will foster comprehensive understanding of vegetable intercropping systems interactions.

Context: Crop diversification has been proposed as a promising strategy for transitioning towards sustainable agricultural systems by leveraging biological processes and controls present in naturally biodiverse ecosystems. Strip cropping, a form of intercropping where two or more crops are grown adjacent to one another in long and narrow multi-row strips, has been shown to deliver a greater range of ecosystem services compared to sole crop references due to increased interspecific crop interactions, spatio-temporal niche differentiation, and higher in-field habitat diversity. The possibility to adjust the strip width to the working width of farmers' existing machines gives strip cropping of cash crops an important implementation advantage over other intercropping practices. Systematic exploration and evaluation of spatial plans for strip cropping systems, however, is constrained by the lack of spatially-explicit design approaches.Objective: Here we present a framework to support systematic exploration of spatio-temporal strip cropping configurations for a given farm context and set of objectives.Methods: The framework comprises six steps: 1) Diagnosis of the current farm situation; 2) Specification of strip cropping system attributes; 3) Temporal strip cropping planning; 4) Spatio-temporal strip cropping planning; 5) Spatio-temporal strip cropping configuration assessment; 6) Strip cropping configuration selection and visualization. We combine two software applications: ROTAT to generate crop rotations and the novel RotaStrip to systematically explore spatio-temporal configurations based on the rotations generated by ROTAT. We illustrate the framework with a case study from the Netherlands using gross margin, habitat score, and spatial crop compatibility score as indicators.Results and conclusions: 150 crop rotations were generated. When 6 additional crops were included this was increased to 51,371, and the maximum values of the three indicator scores were also improved. Using the thirteen candidate crops to generate spatio-temporal configurations, we identified 16 Pareto-optimal and 78 anti-optimal configurations, from which the highest and lowest performing configurations were selected. The two contrasting configurations scored 7254 and 6658 €.ha−1.yr−1 for gross margin, 0.88 and 0.75 for habitat score, and 98 and− 58 for crop compatibility score, respectively, illustrating the value of consideration of the spatial aspects. Bridging the current knowledge gaps regarding what constitute good crop combinations, and strengthening the evidence underpinning the evaluation of ecosystem service delivery on the basis of spatial configuration, would further improve the quality of the generated strip cropping plans.Significance: The framework presented and illustrated in this study provides a basis for systematic spatio-temporal strip cropping systems design and implementation.

To operate within the safe and just operating space captured by the doughnut metaphor, sustainability transitions are needed in the food system. Niche food systems with highly distinct practices and organization constitute a treasure chest of alternatives from which society can build new futures. Policy has little awareness of niche food systems and their potential contributions to sustainability transitions. Importantly, this limits society’s ability to adapt. Here, we review findings from an ongoing scientific project into different components of the vegetable food systems in Chile and Uruguay. The aim of the project is to investigate options for transitioning to low- or no-pesticide vegetable food systems. The results show: 1. the presence of promising alternative vegetable food systems in Chile, which are, however, highly marginalized and disempowered; 2. a diversity of vertical and horizontal producer arrangements in Uruguay and the need for value-driven as well as market-driven engagement; and 3. major possibilities for improving production systems to arrive within the doughnut by taking a systems perspective at the farm scale that includes the farm families and their networks. Consequences of these findings for alternative vegetable food systems are discussed.

Legume crops hold promise to diversify the currently simplified rotations that dominate Europe and to increase the sustainability of European farming systems. Nevertheless, most legumes have been ignored by farmers, advisors, and value chain agents in the EU, where legumes are estimated to occupy only ~2% of arable land. Recent surveys find that farmers see a lack of knowledge on the agroecological impacts of (re)introducing legumes as a key barrier to legume adoption. A review of current research on the agroecological potential of legume-inclusive cropping systems would help in assessing whether research targeting sufficiently supports farmers in overcoming this barrier. We have systematically reviewed and synthesized published literature reporting on agricultural ecosystem service delivery in European cropping systems with legumes included compared to those without legumes. Our analysis of 163 published articles revealed: (1) the bulk of published research addresses production-related services delivered by few legume species (pea, clover, faba bean, and vetch, 70% of reviewed studies) comparatively assessed in cereal-based rotations; (2) substantial knowledge gaps also exist, encompassing ecosystem services with less direct relevance to economic outcomes (e.g., biodiversity) and with potential for high variability (e.g., pest and disease suppression); (3) studies at plot-level and within-season scales dominate (92% and 75% of reviewed studies, respectively). Assessed in the context of recent complementary studies, we find that a limited research focus is both counter to knowledge demands from farmers and likely the result of self-reinforcing socio-technical regimes which prioritize production over non- or indirectly-marketable ecosystem services. We conclude that scientists in Europe should diversify research to include legume species, ecosystem services, contexts, and scales not yet well studied, in order to provide the agroecological knowledge base farmers need to amplify the potential benefits of crop diversity.

Around 30% of global food is produced by smallholder farmers, yet they constitute the most food-insecure group. In Mexico, food self-sufficiency is declining. Rural policies in the country have stimulated the production of cash crops to the detriment of the traditional intercropping system, themilpa. Such a decline may have negative consequences for the food security of subsistence farmers. This study aimed to assess changes in nutritional self-sufficiency over the last 30 years and the role ofmilpasystems in food security for two communities in the highlands of Oaxaca, Mexico. The study used satellite images, censuses, and field data to estimate food production. Three cropping systems, monoculture of maize, monoculture of common bean, and themilpawere compared in terms of nutrients and vitamins produced. Furthermore, a household typology was developed for each community to contrast nutritional self-sufficiency levels between the different household types. Results showed that themilpaproduced more volume of food per area compared to the other systems. Themilpaalso produced all the nutrients and vitamins (except for B12) required to feed at least 2 persons ha-1. Monocultures of maize lacked vitamins A, B9, B12, and C, and the common bean lacked vitamins A, B12, and C. While farmers recognized the importance of themilpa, they preferred monocultures due to the reduced labor demands of this system. Households that obtained most of their income from off-farm activities had the lowest nutritional self-sufficiency. Enhancing nutritional self-sufficiency through crop diversification has the potential to not only improve the nutrition of subsistence farmers, but also to enhance ecosystem service provision, promote biodiversity conservation and restoration, and improve resilience to climate change.

CONTEXT: Family-run cow-calf farms based on native grasslands exhibit low economic and social sustainability, as reflected in low family incomes and high workloads. Experimental results have shown that pasture–herd interaction management could improve native grasslands and animal productivity OBJECTIVE: This paper analyzes the extent to which the sustainability of family-run livestock farms based on native grasslands could be enhanced by a systemic redesign informed by ecological intensification practices. The research questions address the initial state of farm sustainability, key bottlenecks to improving farm sustainability, and changes in sustainability criteria achieved over three years of farm redesign. METHODS: The study was executed as part of a multi-level co-innovation project in Uruguay in which a team of scientist-practitioners and seven farm families participated in farm characterization, diagnosis, and redesign. The farm characterization took the form of indicators to describe the farms’ management and bio-physical subsystems. Redesign plans were negotiated between the research team and the farmers. Frequent monitoring and evaluation cycles enabled finetuning across the years of implementation. RESULTS AND CONCLUSION: Improvements were observed in the economic indicators gross margin (+55%), return to labor (+71%), and family income (+53%) and in the social indicator workload ( 22%), and the environmental indicators bird diversity and ecosystem integrity index were maintained or increased slightly. These changes were explained by the uptake of coherent sets of ecological intensification practices causing changes in forage height (+30%), forage allowance (+69%), pregnancy (+22), weight of weaning calf per mating cow (+32%), and presence of tussocks (+65%). Ecological intensification principles resulted in synergistic positive effects between productivity–biodiversity tradeoffs and the scope for enhanced farm resilience and stability. SIGNIFICANCE: Cow-calf family-run farms can be transformed to produce positive environmental and social effects and viable economic results. The implementation of projects in a co-innovation context may be taken as a guide to scaling up and scaling out the ecological intensification of livestock production on native grasslands, contributing to an extension system at the national level with the aim of improving cow-calf systems sustainability. Estación Experimental Agropecuaria Bariloche Fil: Ruggia, Andrea. Instituto Nacional de Investigacion Agropecuaria (INIA). Programa Nacional de Investigacion en Produccion Familiar. Estacion Experimental INIA Las Brujas; Uruguay Fil: Dogliotti, Santiago. Universidad de la República. Facultad de Agronomía. Departamento de Produccion Vegetal; Uruguay Fil: Aguerre, Maria Veronica. Instituto Nacional de Investigacion Agropecuaria (INIA). Programa Nacional de Investigacion en Produccion Familiar. Estacion Experimental INIA Las Brujas; Uruguay Fil: Albicette, Maria Marta. Instituto Nacional de Investigacion Agropecuaria (INIA). Programa Nacional de Investigacion en Produccion Familiar. Estacion Experimental INIA Las Brujas; Uruguay Fil: Blumetto, Oscar. Instituto Nacional de Investigacion Agropecuaria (INIA). Programa Nacional de Investigacion en Produccion Familiar. Estacion Experimental INIA Las Brujas; Uruguay Fil: Cardozo, Geronimo. Instituto Nacional de Investigacion Agropecuaria (INIA). Programa Nacional de Investigacion en Pasturas y Forrajes. Estacion Experimental INIA Treinta y Tres; Uruguay Fil: Leoni, Carolina. Instituto Nacional de Investigacion Agropecuaria (INIA). Programa Nacional de Investigacion en Produccion Familiar. Estacion Experimental INIA Las Brujas; Uruguay Fil: Quintans, Graciela. Instituto Nacional de Investigacion Agropecuaria (INIA). Programa Nacional de Investigacion en Carne y Lana. Estacion Experimental INIA Treinta y Tres; Uruguay Fil: Scarlato, Santiago. nstituto Nacional de Investigacion Agropecuaria (INIA). Programa Nacional de Investigacion en Produccion Familiar. Estacion Experimental INIA Las Brujas; Uruguay Fil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina Fil: Tittonell, Pablo Adrian. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina Fil: Rossing, Walter A.H. Wageningen University and Research. Farming Systems Ecology, Plant Sciences Group; Holanda

Context: Despite a wealth of analytical knowledge on factors and processes that operate to slow down orimpedesustainabilitytransitions in various sectors of society, design-oriented researchers face a lack of guidance on the ‘how to’questionfor developing knowledge to support sustainability changes. From 2007, we crafted co-innovation as an approachforgovernance and management of change-oriented projects, combining three domains; a complex adaptive systems perspective, asocial learning setting, and dynamic monitoring and evaluation. Objective: This paper sets out to describe the co-innovation approach and draw lessons from its application in projects on ecological intensification in Uruguay and the European Union. Methods: We used an analytical framework for evaluating sustainability transition experiments, which considers project features that provide insights into the contribution to sustainability transformations by project outputs, outcomes, processes and inputs, and their interactions. Empirical information on 6 cases from 3 projects was collected through in-depth interviews with former project staff, group discussion, and project documentation. This enabled a reflexive evaluation of co-innovation. Results and conclusions: Outputs showed substantial variation among the cases despite a similar approach to project governance and management. More significant contributions to sustainability transitions were associated with in-depth project preparation, a focus at the farm-level instead of the crop or field level, connections during the project’s lifetime with regional innovation system actors, and frequent facilitated interactions among project actors to reflect on results, wider system implications, and project direction. We discuss the results in relation to the three domains of co-innovation. To enhance the role of projects in destabilizing currently unsustainable systems we highlight: reconsidering the role of projects as a business model; stimulating institutional learning from previous change-oriented projects; and making funding more adaptive to evolving project needs. Significance: With most of the budget for agricultural research-for-change spent through projects, how projects are conducted is a critical determinant of the rate of sustainability transitions. Effective disruption of unsustainable practices through project interventions requires rethinking linear cause-effect relations to include project governance and management approaches based on complex adaptive systems thinking, social learning settings, and monitoring geared to adaptation and learning.

International audience; Grazing plays a key role in reducing the external inputs required for ruminant production and in alleviating feed-food competition. Beyond the production of meat and milk, grassland-based systems provide a wide range of ecosystem services. Agroecology and organic farming aim to reconcile natural resource management and food production, in the long term, based on the management of ecological processes. In this perspective paper, we report what we have learned from case studies with beef cattle, sheep, and dairy cattle across Uruguay and western Europe, in which we have been involved. Multicriteria methods, such as Pareto frontiers and positive deviances, were used to analyze trade-offs and identify win-wins from farm surveys. Long-term farm networks coupled with bioeconomic optimization models revealed fluctuations in farm income and allowed estimating system resilience. Extensive farmlet experiments made it possible to integrate knowledge on animal physiology and grassland ecology in the system redesign process and to test for innovative and risky management options that could lead to unacceptable learning costs in commercial farms. Finally, learning from farmers' local knowledge in teams with researchers and technical advisers can provide positive changes in grazing systems. In Uruguayan family farms, for example, the scientific knowledge gained from farmlet experiments led to advice on management options based on farm-specific diagnosis. Farmers adapted the proposals, with researchers supporting the processes by providing quantitative information on consequences and spaces for reflection. In a French cheese production area, the focus was on farmers' own experience. Games facilitated interactions as participants could challenge each other's reasoning and conclusions in a safe environment. These two case studies illustrate the diversity of co-innovation approaches, but in both cases knowledge sharing between researchers, farmers, and other stakeholders appeared more efficient to help farmers understand and adapt their own system properties than researching "best practice" solutions for large-scale transfer.

Carabid beetles are common predators of pest insects and weed seeds in agricultural systems. Understanding their dispersal across farmland is important for designing farms and landscapes that support pest and weed biological control. Little is known, however, about the effect of farmland habitat discontinuities on dispersal behaviour and the resulting redistribution of these beetles. We released 1,985 well-fed and 1,680 food-deprived individuals of the predatory carabid beetle Pterostichus melanarius (Illiger) (Coleoptera: Carabidae) on a farm in Wageningen, The Netherlands. We recaptured 23.6% of those beetles over a period of 23 days in 2010. The farmland comprised agricultural fields with various crop species and tillage, separated by strips of perennial vegetation. We developed discrete Fokker-Planck diffusion models to describe dispersal based on motility (m2 day−1) and preferential behaviour at habitat interfaces. We used model selection and Akaike’s information criterion to determine whether movement patterns were driven by variation in motility between habitats, preferential behaviour at habitat interfaces, or both. Model selection revealed differences in motility among habitats and gave strong support for preferential behaviour at habitat interfaces. Behaviour at interfaces between crop and perennial vegetation was asymmetric, with beetles preferentially moving towards the crop. Furthermore, beetles had lower motility in perennial strips than in arable fields. Also between arable habitats movement was asymmetric, with beetles preferentially moving towards the habitat in which motility was lowest. Neither crop type nor tillage explained differences in motility between crop habitats. Recapture data representing dispersal patterns of beetles were best described by a model that accounted for differences in motility between farmland habitats and preferential behaviour at habitat interfaces. Motility in farmland and behaviour at interfaces can also be estimated for other organisms and farmland habitats to support design of farmland conducive to natural pest suppression. Landscape design for early recruitment of carabids into arable fields should take into account the quantity and quality of resource habitats in the landscape, their proximity to crop fields, movement rates, and the possibility of movement responses at interfaces between landscape elements.

Droughts in southern South America affect grazing systems in many ways. They reduce biomass productivity; decrease livestock feed intake, weight and reproductive performance; increase farmers' costs; and reduce farm income. It was hypothesized that simple grazing management variables affect the resilience of grazing systems to droughts at the paddock and farm scales. The effects of grazing management on herbage and animal production were assessed at paddock level, and how technological and structural variables relate to the production and economic performances at farm level. Results of a grazing experiment controlling herbage allowance at paddock level showed that resistance of herbage accumulation and animal live weight to drought was significantly higher for paddocks with higher pre-drought herbage allowance than for those managed to low herbage allowance treatments. A strong positive linear relationship was found between pre-drought herbage height and resistance of herbage accumulation rate (p < .01). In a longitudinal study of nine farms in Uruguay, resistance of cow pregnancy rate to drought was positively correlated with cow pregnancy rate (r = .72, p = .02) and farm net income (r = .78, p = .02), and negatively correlated with sheep-to-cattle ratio (r = −.80, p = .01). These correlations suggest that farms with higher incomes and low proportions of sheep in the herd withstand drought better (in terms of pregnancy rate). Four common regional production strategies were identified that react differently when farmers face drought, and these results can aid farmers in those regions to design more resilient mixed livestock farming systems and can inform policymakers about effective strategies for mitigating drought impacts in the region.

In this paper, we present the LandscapeIMAGES modeling framework for multi-scale spatially explicit analysis of tradeoffs and synergies among ecosystem services provisioning across agricultural landscapes. The framework generates large sets of spatially explicit land-use and management scenarios to inform discussions among stakeholders involved in landscape planning processes. The generated plans are evaluated and optimized for multiple indicators of ecosystem services provisioning. The framework has been developed with an object-oriented programming approach to allow rapid implementation of new indicators and application to new case study landscapes. The modeling system includes (i) a generic framework for Pareto-based multi-objective optimization to generate a set of land-use and management plans, (ii) an easily expandable collection of modules to quantify indicators of ecosystem services provisioning, which can be used as objectives or constraints in optimization, and (iii) a graphical user interface that allows parameterization of the model and inspection of the original and generated land-use and management plans. This allows visualization of trade-offs and synergies among ecosystem services as a consequence of land-use and management planning choices. LandscapeIMAGES is currently used in projects aiming to improve the provision of multiple ecosystem services within landscapes in Asia, Africa, Latin America and Europe.

International audience; Invertebrates perform many vital functions in agricultural production, but many taxa are in decline, including pest natural enemies. Action is needed to increase their abundance if more sustainable agricultural systems are to be achieved. Conservation biological control (CBC) is a key component of integrated pest management yet has failed to be widely adopted in mainstream agriculture. Approaches to improving conservation biological control have been largely ad hoc. Two approaches are described to improve this process, one based upon pest natural enemy ecology and resource provision while the other focusses on the ecosystem service delivery using the QuESSA (Quantification of Ecological Services for Sustainable Agriculture) project as an example. In this project, a predictive scoring system was developed to show the potential of five seminatural habitat categories to provide biological control, from which predictive maps were generated for Europe. Actual biological control was measured in a series of case studies using sentinel systems (insect or seed prey), trade-offs between ecosystem services were explored, and heatmaps of biological control were generated. The overall conclusion from the QuESSA project was that results were context specific, indicating that more targeted approaches to CBC are needed. This may include designing new habitats or modifying existing habitats to support the types of natural enemies required for specific crops or pests.

The allocation of feedstuff to intensively managed dairy cows to achieve different objectives is challenging due to the inherent complexity of the system and the combinatorial problem that has to be solved. Pareto-based multi-objective optimization approaches using evolutionary algorithms can help to address these challenges and show the trade-offs and synergies among various objectives. Here we present a framework for multi-objective optimization with the Differential Evolution (DE) algorithm applied to dairy feeding systems with grazing and concentrate supply to generate an approximation of the Pareto front. The available feed resources are located in different feeding areas, and the number of animals and groups of animals with similar feeding requirements are distributed across these areas for feeding purposes. To evaluate the DE algorithm, we performed two in-silico experiments to: (1) compare the solutions quality of single-objective DE with exact Linear Programming (LP) solutions, and (2) assess the influence of different stocking rates (number of cows/ha) on milk production, feed allocation and economic performance indicators. The DE solutions that minimize the feeding costs for different stocking rates (1.1–2.6 cows/ha) closely approached the solutions derived with LP, confirming the quality of the heuristic algorithm. The multi-objective model scenarios demonstrated that increasing stocking density would enhance milk production and gross margin per unit of area at largely unchanged productivity per animal by shifting the feed ration from roughage to a large proportion of supplementary concentrate feed. At low stocking rates solutions with high productivity and gross margin and a large proportion of roughage in the ration and limited supplementary feeding were identified. We conclude that the multi-objective optimization with a Pareto-based DE algorithm is highly effective to explore the interrelations among conflicting objectives and to find suitable solutions.

Regional impact studies are needed to explore possible adaptation options to climate change. We estimated impacts and adaptation options for future scenarios that feature different assumptions regarding climate, cropping pattern and access to irrigation with two bio-economic farm models. Farm profit, soil organic matter balance and labor input are used as indicators of farm performance. The difference between the baseline and the alternative configurations computed by models is referred as adaptation potential, indicative of the adaptation options including the corresponding changes in cropping patterns. Our results show that as long as there is sufficient access to irrigation water, there is little incentive to change current practices, as farming is at the economic optimum, has a positive soil organic matter balance and labor requirements can be met. Conversely, if irrigation is no longer possible, drastic impacts occur, causing a need to sustainably adjust on-going farm practices. Adaptation through changed crop selection reduced losses to some extent. We conclude that the use of bio-economic models can assist in evaluating the qualitative findings of participatory studies by quantitatively assessing possible climate change impacts and adaptation measures. Strong impacts of climate change, however, cannot be offset by changes in cropping patterns and need further adaptation measures.

Ecological intensification has been proposed as a promising lever for a transition towards more sustainable food systems. Various food systems exist that are based on ecological intensification and may have potential for a sustainability transition. Little is known, however, about their diversity and about how they perform against dominant systems in terms of the multiple societal goals. The aim of this study is to contribute to knowledge about sustainability transitions in food systems through an empirical analysis of vegetable food systems in Chile. The study (i) characterizes the diversity of vegetable food systems in Chile (ii) evaluates the food systems in terms of multiple societal goals, and (iii) assesses their potential for supporting sustainability transition pathways from the perspective of ecological intensification. Results indicate that among the five vegetable food system types, the agroecological and the small organic have potential to foster a sustainability transition. Nevertheless, these systems are small and localized, and scaling them requires actions to remove barriers in the relations with the agri-food regime and among themselves. The broader relevance of this analysis is that there needs to be awareness in research on transitions about the diversity of food systems present in countries and how they interact.

Reduced tillage and mulching may bring about new production systems that combine better soil structure with greater water use efficiency for vegetable crops grown in raised bed systems. These are especially relevant under conditions of high rainfall variability, limited access to irrigation and high soil erosion risk. Here we evaluate a novel combination of empirical models on water interception and infiltration, with a soil-water balance model to evaluate water dynamics in raised bed systems on fine Uruguayan soils to analyze the effect of reduced tillage, cover crops and organic matter addition on soil physical properties and water balance. In the experiment mulching increased water capture by 9.5% and reduced runoff by 37%, on average, leading to less erosion risk and greater plant available water over four years of trial. Using these data we calibrated and evaluated different models that predicted interception + infiltration efficiently (EF = 0.93 to 0.95), with a root mean squared error (RMSE) from 0.32 to 0.40 mm, for an average observed interception + infiltration of 28.8 mm per day per rainfall event. Combining the best model with a soil water balance resulted in predictions of total soil water content to 1 m depth (SWC T ) with RMSE ranging from 4.5 to 10.3 mm for observed SWC T ranging from 180.4 to 380.6 mm. Running the model for a four-year crop sequence under 10 years of Uruguayan historical weather revealed that reduced tillage required on average 141 mm yr −1 less irrigation water than conventional tillage combined with organic matter application, thus enabling a potential increase in irrigated area of vegetable crops and crop yields. Results also showed the importance of inter-annual rainfall variability, which caused up to 3-fold differences in irrigation requirements. The model is easily adaptable to other soil and weather conditions.

International audience; AbstractDominant food systems are configured from the productivist paradigm, which focuses on producing large amounts of inexpensive and standardized foods. Although these food systems continue being supported worldwide, they are no longer considered fit-for-purpose as they have been proven unsustainable in environmental and social terms. A large body of scientific literature argues that a transition from the dominant food systems to alternative ones built around the wider principles of sustainable production and rural development is needed. Promoting such a sustainability transition would benefit from a diagnosis of food system types to identify those systems that may harbor promising characteristics for a transition to sustainable food systems. While research on food system transitions abounds, an operational approach to characterize the diversity of food systems taking a system perspective is still lacking. In this paper we review the literature on how transitions to sustainable food systems may play out and present a framework based on the Multi-Level Perspective on Socio-Technical Transitions, which builds upon conceptual developments from social and natural science disciplines. The objectives of the framework are to (i) characterize the diversity of existing food systems at a certain geographical scale based on a set of structural characteristics and (ii) classify the food systems in terms of their support by mainstream practices, i.e., dominant food systems connected to regimes; deviate radically from them, niche food systems such as those based on grassroots innovation; or share elements of dominant and niche food systems, i.e., hybrid food systems. An example is given of application of our framework to vegetable food systems with a focus on production, distribution, and consumption of low-or-no pesticide vegetables in Chile. Drawing on this illustrative example we reflect on usefulness, shortcomings, and further development and use of the diagnostic framework.

Improvements in agricultural land and labour productivity are needed to meet the growing food demand and reduce farmer poverty in sub-Saharan Africa. The objectives of this study were to (i) quantify variation in labour inputs, yield and labour productivity among rice fields; (ii) elicit factors associated with this variation; and (iii) identify opportunities for improving yield and labour productivity. The study was carried out in two contrasting Beninese villages: Zonmon in the south and Pelebina in the north-west. In Zonmon 82 irrigated rice fields were surveyed during the 2013 and 2014 dry seasons. In Pelebina 50 rainfed lowland rice fields were surveyed over three rainy seasons (2012–2014). Data on farmer field management practices and field conditions were recorded through interviews with farmers, on-farm observations and measurements. Stepwise regression analyses were used to identify variables associated with variation in yield, labour inputs and labour productivity. Average yields were 4.8 ± 2.0 t ha−1 in Zonmon and 2.3 ± 1.2 t ha−1 in Pelebina. Average labour productivity, however, was larger in Pelebina (17 kg of paddy rice person-day−1) than in Zonmon (8 kg of paddy rice person-day−1). Relative yield gaps (43–48%) and labour productivity gaps (59–63%) were similar in the villages. There was no trade-off between yield and labour or labour productivity within the villages, suggesting that in many cases rice yields can be increased without additional labour inputs. The major labour-demanding farming operations were bird scaring in Zonmon and harvesting and threshing in Pelebina. We identified opportunities to improve rice yield and labour productivity, given current farmer knowledge and resource endowment. Based on the statistical models fitted per village, increasing the average hill density would result in up to 1.2 t ha−1 more yield, and up to 4 kg person-day−1 greater labour productivity for Zonmon. Increasing the average field size and avoiding rice shading would result in up to 0.8 t ha−1 more yield, and up to 17.1 kg person-day−1 greater labour productivity for Pelebina. Further enhancing yield and labour productivity will require (i) introducing small-scale mechanisation and other labour-saving innovations, in particular for labour-demanding farming operations such as bird scaring in Zonmon and harvesting and threshing in Pelebina; and (ii) combining analyses of yields and labour productivities at field level with detailed analyses of labour use and labour productivity at farm level. We found that, on average, one hectare in Zonmon contributed twice as much to Beninese rice production than one hectare in Pelebina but with a two times smaller reward for farmer labour. This paradox of higher yields but lower labour productivity in such different rice growing environments and farming systems should be addressed in elaborating development policies.

In sub-Saharan Africa, unexploited land and water resources in wetlands represent an important potential for intensified, sustainable and food-secure farms through rice production and market gardening. The lack of uptake of cropping in wetlands may be related to the ways in which resources are divided between family fields and individual fields. The management system on sub-Saharan African farms comprises a family management unit or a combination of a family management unit and one or more individual management units. The family management unit or the farm head controls production in family fields to satisfy family needs while the individual management units control production in individual fields to satisfy individual needs. Our objective was to investigate the diversity in farm management systems and the resulting uptake of cropping in wetlands for different farm types, as the first step towards suggestions for enhancing rice production and market gardening in wetlands. We studied farms in two case-study villages in Benin: Zonmon in the southern part and Pelebina in the north-western part. Farm typologies were developed based on random samples of 51 out of 134 farms (38%) from Zonmon and 50 out of 146 farms (34%) from Pelebina by combining principal component analysis and Ward's minimum variance clustering. Variables included in the PCA were related to levels of resource endowment (e.g., amounts of land, family labour, cash for purchasing chemical inputs and hiring labour) and to resource-use strategies including resource division between family fields and individual fields, and between uplands and wetlands. We identified 3 farm types in Zonmon and 5 farm types in Pelebina based on differences in resource-use strategies and in resource endowment. We found no trade-off between the existence of individual fields and the area under rice and market garden crops in wetlands. Labour abundance was the main factor driving both the occurrence of individual fields and the expansion of cropping in wetlands. Differences in labour division strategies between family and individual fields among farm types reflected differences in food and cash division strategies. Land use appeared strongly motivated by food self-sufficiency objectives and labour productivity, leading to prioritisation of upland over wetland areas. In wetlands, most farm types opted for cultivating market garden crops during the dry season when labour demand for upland fields was low. Our results indicate that increasing labour productivity in food crops and in rice and market garden crops would enhance the uptake of rice and market garden crops in wetlands. Creating credit facilities would increase the labour resource and allow farmers to hire labour, further contributing to wetland use. We discuss the relevance of a systemic farm analysis that enables distinguishing family and individual fields for understanding farm uptake of rice and market garden crops in wetlands.

Knowledge on farm diversity provides insight into differences among farms, enables scaling from individual farm to farm population level and vice versa, and has been used in the definition of recommendation domains for introduction of novel technologies. Farm diversity can be broadly described in terms of resource endowment and resource use strategy, or in other words, in terms of scale and intensity of production. Measuring intensity of production requires much greater monitoring effort than measuring scale of production, and often only proxies of production intensity are used. Using data from a regional farm survey and from intensive on-farm monitoring the question addressed in this paper is to which extent results of farm surveys that measure primarily scale of production can inform on-farm interventions aimed at improving farm performance. The survey included a random sample of 97 out of 664 smallholder dairy farmers in a community in north-west Michoacan, Mexico. Farm types were identified by a combination of Principal Component Analysis to reduce the dimensionality of the dataset, followed by Cluster Analysis. The survey was complemented with detailed analyses of costs, revenues and productivity on 6 farms over the course of one year. Survey results revealed considerable variation among the dairy farms in land area, livestock units, amount of hired labour, and infrastructure and equipment, which led to the distinction of 4 farm types. Indicators for animal health management and feeding strategies were uniform across the 4 types. The farm types matched the distinction of family-based and semi-intensive farm types used in Mexico. The detailed analyses of the individual farms belonging to the different types, however, revealed differences in resource use strategies reflected in differences in animal productivity, labour productivity and return to labour. Differences in animal productivity and labour productivity were explained by stocking rate, albeit in different ways. Return to labour was strongly related to cost of feed. Profitability was negative for all farms and was on most farms related to high external feedstuff costs, which constituted 59–89% of the feed cost of the animal ration. The results indicate that in addition to variables reflecting resource endowment or scale of production, typologies that aim to inform on-farm interventions need to consider farm characteristics that reflect intensity of production. Which variables should be selected will need to be determined in a preliminary assessment. To enhance internal resource use efficiency as was the purpose in the current study, candidate variables expressing intensity could include the share of external feed in the ration and proxies of internal resource use, e.g. reflected in crop and milk yields. Opportunities for on-farm innovation arising from the analyses are discussed from the perspective of labour flexibility, low costs and use of internal resources.

Yield variability in space and time is a well-known phenomenon in the highland coffee production systems of Costa Rica. Our objective was to systematically unravel variations and gaps in yields due to the combined effects of farm resources and major production variables in a region of premium quality highland coffee. We surveyed 40 coffee producing farms varying in size from small to large in Llano Bonito, Costa Rica to examine their diversity based on their resources. We further conducted an agronomic diagnosis and yield estimates in 97 individual measuring plots in 63 coffee fields over two cropping years (2013–2014 and 2014–2015). We categorized farm diversity through a resource endowment typology built by combining direct observation with the use of multivariate analysis and clustering techniques. This resulted in four farm types: large farms depending on external labour (Type 1, 25%), large farms with livestock (Type 2, 20%), small farms dedicated to coffee (Type 3, 38%), and small farms with an off-farm income (Type 4, 17%). We then analysed coffee yield variability and yield gaps through a boundary line approach. The mean yields for two cropping years fluctuated between 2.5 ± 0.18 and 1.6 ± 0.12 t ha−1 on farm types 1 and 2 respectively. Though the yields did not differ strongly across farm types, there was a weak tendency (p = 0.10) towards yield variability between study years. The combined use of farm typology and yield gap analysis revealed multiple farm‐specific production variables that were significantly related to gaps in attainable yields. For any intervention to improve and stabilize yields in the future, the heterogeneity of farm orientation, management practices, production geographical context and soil properties must be given proper attention and integrated into crop, shade tree and soil management practices.

Loss of ecological functions due to soil degradation impacts viability of crop production systems world-wide, particularly in vegetable cropping systems commonly located in the most productive areas and characterized by intensive soil cultivation. This paper reports soil degradation caused by intensive vegetable farming, and its reversibility after two to five years of drastic changes in soil management on 16 commercial vegetable farms in south Uruguay. Changes in soil management included addition of green manures and pastures in rotations of vegetable crops, use of animal manure, and erosion control support measures (terracing, reducing slope length, re-orientation of ridges). Soil degradation caused by vegetable farming was assessed by comparing soil properties in 69 vegetable fields with values at reference sites located close to the cropped fields. Effects of the changes in soil management in the 69 fields were assessed by comparing soil properties at the start and to those at the end of the project. Compared to the on-farm reference sites, the vegetable fields contained 36% less SOC, 19% less exchangeable potassium, water stable aggregates with an 18% smaller geometric mean diameter, and 11% lower plant-available soil water capacity. Phosphorus availability was 5 times higher under vegetable cropping compared to the on-farm reference. Phaeozems (Abruptic) revealed greater degradation (44% less soil organic carbon (SOC)) than Vertisols (24% less SOC) and Phaeozems (Pachic) (21% less SOC). After two to five years of improved soil management, SOC concentration in the upper 20 cm increased by on average 1.53 g kg −1 (12%) in the Phaeozems (Abruptic) and 1.42 g kg −1 (9%) in the Phaeozems (Pachic). SOC in Vertisols increased only by 0.87 g kg −1 , most likely due to their greater initial SOC concentration. Topsoil carbon sequestration was on average 3.4 Mg ha −1 in the Phaeozems. Multiple linear regression showed the quantity of incorporated amendments, the initial amount of SOC and the clay content to explain 77% of the variability in yearly changes of SOC. Available water capacity increased significantly with SOC particularly due to more water retention at field capacity, resulting in an increase in available water capacity in the first 20 cm of soil of 8.4 mm for every 10 g kg −1 of SOC increase. Results are discussed in relation to perspectives of soil degradation reversal in the long term.

An integrated methodological framework for ex-ante evaluation and planning of public policies for sustainable agriculture at agro-landscape level is proposed. The components of the framework are to: (1) determine the private, i.e. farmers’, and public benefits associated to agro-landscapes, consisting of an agricultural land-use system, according to its performance for several market and non-market functions. Market forces determine the market benefits and preferences of society the non-market benefits; (2) explore and select potential sustainable agro-landscapes based on the private and public benefits associated with possible land-use alternatives; (3) define efficient public policy mechanisms for improving social net benefit of agro-landscapes. The framework is illustrated with a case study in a small dairy farming dominated agro-landscape in The Netherlands, with gross margin, landscape quality, nature value and environmental health as the analysed ecosystem functions. Alternative landscapes consisting of hedgerow configurations and grassland management practices were explored, yielding a set of alternatives representing the solution space in terms of change in private and public benefits. Policy mechanisms were defined to move from the current to a desired landscape based on changes in social net benefits. Moreover, the necessity of a modification in the current agri-environmental support was analysed for each landscape. The analysis considered all farmers in the agro-landscape jointly. The results for the case study showed potential prototypes of landscapes and their performance compared to the current landscape. Extension was the most efficient policy mechanism to promote the change to the socially optimum landscape alternative.

Opportunities exist to improve decision support systems through the use of dispersal information gained from epidemiological research. However, dispersal and demographic information is often fragmentary in plant pathology, and this uncertainty creates a risk of inappropriate action whenever such information is used as a basis for decision making. In this article, a scenario-based simulation approach is used to evaluate crop and economic risks and benefits in the use of dispersal information for decision making using the potato late blight pathosystem (Phytophthora infestans–Solanum tuberosum) as a case study. A recently validated spatiotemporal potato late blight model was coupled to submodels for crop growth, tuber dry matter production, and fungicide efficacy. The yield response of a range of management scenarios to a single influx of primary inoculum (the initial spore load) was calculated. Damage curves (relative yield loss versus initial spore load) from a range of combinations of varietal susceptibility and fungicide treatments were used to classify the various management scenarios as either sensitive to initial spore load or tolerant to initial spore load, thus identifying where a high degree of accuracy would be required in dispersal information for appropriate decision making, and where a greater degree of uncertainty could be tolerated. General epidemics, resulting from spatially homogeneous initial spore loads, responded more strongly to the size of the initial spore load than focal epidemics, resulting from an initial spot infection. Susceptible cultivars responded with sizeable yield losses even at low levels of initial spore load, regardless of the fungicide management regime used. These results indicated that, for susceptible cultivars (late cultivars in particular), the degree of accuracy that would be required in dispersal information for appropriate decision making is unlikely to be practically attainable. The results also indicated that, contrary to “folk wisdom,” spore loads of a few hundred spores per square meter do not lead to appreciable crop loss in resistant cultivars and are therefore acceptable. We conclude that scope exists for including dispersal information in decision making for potato late blight with resistant potato cultivars but not for susceptible cultivars. The modeling framework used in this study can be extended to investigate the scope for inclusion of dispersal information in decision support for other aerially transmitted pathogens.

Landscape character can be defined as the presence, variety and arrangement of landscape features, which give a landscape a specific identity and make it stand out from surrounding landscapes. Landscape character contributes to the esthetical and perceptional value of an area, which is important for the development of non-production functions in the countryside as demanded by society. In this paper we present a new methodology for landscape character assessment using the pattern of landscape features as stored in a GIS to delineate, characterize and evaluate landscapes using a region growing algorithm. We have applied this methodology in a case study area in the north of The Netherlands and compared the results with a series of expert classifications of the study area. The results of the region growing algorithms were good and interpretable in relation to the underlying data. The resemblance between the expert classification and the classification based on the region growing results varied between 34% and 100% for the different landscape types. The differences between the two data sets can be explained in terms of input data and knowledge about the study area. The classification of the region growing algorithm was more consistent than the expert classification throughout the study area. The presented methodology for landscape character assessment is proposed as support for spatial planning processes and policy development for landscape conservation by providing a quantitative tool to analyze landscape patterns, to discriminate between the various landscapes in a study area and by elucidating features that are important for the identity of a region.

In recent years, interest in the policy-informing role of research organisations has grown considerably. It has been argued from within the science domain that the management of land, whether at the field, farm or regional scale, can benefit from computer-based systems analysis. This proposition was examined through 26 semi-structured interviews, by conducting a workshop on modelling support in policy decision-making and investigating 11 European-based cases of policy-oriented modelling research. On basis of these materials, we assess approaches towards policy-oriented modelling within the domain of agricultural production and other environmental services of land. First, we define the boundary arrangements for our field of interest, i.e. computer-based systems analysis of agricultural production and ecosystems services. Such ideotypical classification of boundary arrangements makes explicit the institutional space in which system scientists function. This space enables certain activities, and at the same time constrains other initiatives, dependent on who is perceived to initiate and/or control research activities and to formulate objectives, and whether it is considered appropriate to integrate scientific knowledge development with policy work. Five ideotypical boundary arrangements are proposed: ‘Civil mandate’; ‘Trickle out’; ‘Janus face’; ‘Critical participant’; and ‘Knowledge broker’. In a second step, a number of critical leverage points are identified based on the 11 cases and these are addressed in relation to the five boundary arrangements. The term ‘leverage point’ covers means, conditions and methods that foster use of modelling work that can be changed, and thus may be part of a strategy to increase the chances that a model is used. The leverage points were: reputation of research institute and/or scientists; raising and balancing expectations; communication about and investment in the scientific basis of the modelling work; participation in model development; heterogeneous and extensive social network in policy domain; institute mandate that secures availability of ‘stepping stones’. We conceive of two applications of our research for modellers who are interested in the use of their work in the policy sphere. First, the boundary arrangement classification helps to interpret the experiences of others and to assess the relevance of lessons and suggestions for their own context. Secondly, the combination of the boundary arrangement perspective and critical leverage points presents a basis to design an institutional pathway for enhancing impact of modelling research in the policy sphere. For those researchers functioning in a science-domain-oriented environment, the analysis in this paper suggests that there are more options than the frequently proposed ‘more participation’ for increasing the likelihood that their policy-oriented work is used. These include establishing contacts with research groups or institutes that are in a position to function as ‘stepping stones’, or engaging with others to develop a social network in the policy sphere.

There is a growing concern about food security and sustainability of agricultural production in developing countries. However, there are limited attempts to quantify agro-biodiversity losses and relate these losses to soil degradation and crop productivity, particularly in Tigray, Ethiopia. In this study, spatial variation in agro-biodiversity and soil degradation was assessed in 2000 and 2005 at 151 farms in relation to farm, productivity, wealth, social, developmental and topographic characteristics in Tigray, northern Ethiopia. A significant decrease in agro-biodiversity was documented between 2000 and 2005, mainly associated with inorganic fertilizer use, number of credit sources and proximity to towns and major roads. Agro-biodiversity was higher at farms with higher soil fertility (available P and total N) and higher productivity (total caloric crop yield). Low soil organic matter, few crop selection criteria and steep slopes contributed to soil erosion. Sparsely and intensively cultivated land use types, as determined from satellite images, were associated with high and low agro-biodiversity classes, respectively, as determined during on-farm surveys in 2005. This study gives insight into the recent changes in and current status of agro-biodiversity and soil degradation at different spatial scales, which can help to improve food security through the maintenance of agro-biodiversity resources.

Although Mexico aims to be self-sufficient in milk, domestic prices for milk are low due to trade liberalization, which resulted in imports of large amounts of milk powder, mainly from the United States. This situation threatens the livelihoods of smallholder dairy farmers. With varying success, farmers have tried to increase revenues by intensifying production through increased purchase of concentrates and production per cow, but this also resulted in substantial environmental problems. In this paper we combine a whole-farm model with data from representative pilot farms to explore alternative intensification options that more adequately can support the multi-objective setting of smallholders. Pilot dairy farms were defined in two categories: family-based (FB) and semi-specialized (SS), each at three levels of intensification: extensive (E, − 1 ), medium-intensive (M, > 0.8 and − 1 ), and intensive (I, > 1.2 LU ha − 1 ). We aimed to explore management alternatives that enhance farm economic performance, while improving resource use efficiency and reducing negative environmental impacts. For each of the six pilot farms a large set of Pareto-optimal farm configurations was generated using the whole farm model in combination with an evolutionary algorithm. Applying a multivariate analysis, the sets of alternatives were classified in three functional groups that respectively aimed to: a) maximize profitability (‘economic’), b) maximize organic matter (OM) balance (‘environmental’), and c) minimize labor used, N balance and feeding costs (‘integrated’). Intensive (FBI, SSI) and large (SSM) farms had the widest ranges of opportunities for change, mainly to maximize profitability and/or OM balance, and to minimize N balance. Synergies were found between maximizing profitability and minimizing feed costs, and for minimizing both feed costs and N balance; trade-offs occurred for OM balance with feed costs and N balance. When comparing the current farm performance with the sets of alternatives, farms performed already well in terms of N and labor balances, whereas the largest scope for improvement was found for increasing OM balances. The results showed that just re-allocating the current resources might by itself lead to economic, social and/or environmental improvements for smallholder dairy farms.

Management of potato late blight could benefit from prediction of the risk posed to potato fields from external inoculum sources of Phytophthora infestans. Influx of inoculum depends on a complex interplay of population biological, atmospheric and spore survival processes, and is difficult to predict. This research aims at building tools for such prediction. BLIGHTSPACE is a spatio-temporal model (parameterized for potato late blight) that has been developed and utilized to study the progress of epidemics in individual fields and networks of fields. A quasi-Gaussian plume model was developed to provide long-range transport of spores within BLIGHTSPACE. Numerical results compared favorably with experimental data. A further submodel for the survival of spores during long-range transportation has been added. Integration of these three submodels will create an experimental arena for comparing control options for potato late blight.

The implementation of the statutory Mineral Accounting System (MINAS) in the Netherlands in the period 1998–2003 required large reductions in nutrient inputs of dairy farms. Patterns in farm management adjustments throughout 6 years and their effectiveness in terms of nitrogen use efficiency (NUE) and economic performance were evaluated for 45 commercial farms participating in a regional nutrient management project. Six groups of farms were identified that differed in initial NUE and the change therein. Three groups of farms that were able to rapidly reduce fertilizer N input and establish a consistent farm management strategy were most successful in improving NUE. These farms had a higher gross margin per 100 kg milk than farms without a consistent strategy. The three effective strategies were primarily characterized by (i) continuous, gradual adjustment of the integrated farm management combined with a slight reduction in milk production per ha (re-balancing) versus increasing productivity per animal, thereby reducing maintenance N requirements, while (ii) maintaining or (iii) increasing the production intensity per ha. It was concluded that different approaches to improve NUE can be successful, also in economic terms, although a direct relationship between NUE and gross margin was not observed. The probably implicit choice for adoption of a strategy may be governed by farm endowment and the farmer's skills and objectives.

To ensure the productivity of smallholder maize production systems in Central America, increased attention must be paid to conserving soil and water resources. Various stakeholders from national agricultural research services (NARS), networks, non-governmental organizations (NGO's) and research institutes seek to develop and target productivity enhancing resource conserving management practices such as crop residue retention systems. To support this process, a methodology with explicit spatial and temporal dimensions using the DSSAT crop simulation models was developed and applied to the case study of residue retention in maize production systems of Jalisco, Mexico. Systems where crop residues were partially or totally retained were compared with systems with no residue retention. Variables considered included crop production, soil surface runoff water, soil organic carbon and soil organic nitrogen content. Gridded climate surfaces and a range of soil profile scenarios formed the basis of the regional input. Three levels of nitrogen application (0, 150 and 235 kg ha(-1)) were selected to represent current agronomic practices. Simulation models for maize and fallow were run in sequence for 12 consecutive years. Results demonstrated that soil water holding capacity and topography affected benefits of residue retention much more than nitrogen management. Benefits to maize production from residue retention were found mainly in areas in the northeast of Jalisco and surrounding regions, where low precipitation limits maize production. Reductions in soil surface runoff due to residue retention were most evident in high rainfall areas in the central-east of Jalisco and surrounding regions. Although the effect of soil loss is not accounted for in DSSAT, areas of pronounced soil surface runoff reduction are hypothesized to be areas of productivity gain in the longer term. The assessment provided insight in the regional potential for and the soil and climate conditions under which successful introduction of residue retention in maize cropping systems in Jalisco may be achieved. In combination with socio-economic assessment studies and experimental work, the approach and its results contribute to targeted introduction of new production technologies. (C) 2004 Published by Elsevier Ltd.

Quantification of the movement of insects at field and landscape levels helps us to understand their ecology and ecological functions. We conducted a meta-analysis on movement of carabid beetles (Coleoptera: Carabidae), to identify key factors affecting movement and population redistribution. We characterize the rate of redistribution using motility μ (L2 T−1), which is a measure for diffusion of a population in space and time that is consistent with ecological diffusion theory and which can be used for upscaling short-term data to longer time frames. Formulas are provided to calculate motility from literature data on movement distances. A field experiment was conducted to measure the redistribution of mass-released carabid, Pterostichus melanarius in a crop field, and derive motility by fitting a Fokker–Planck diffusion model using inverse modelling. Bias in estimates of motility from literature data is elucidated using the data from the field experiment as a case study. The meta-analysis showed that motility is 5.6 times as high in farmland as in woody habitat. Species associated with forested habitats had greater motility than species associated with open field habitats, both in arable land and woody habitat. The meta-analysis did not identify consistent differences in motility at the species level, or between clusters of larger and smaller beetles. The results presented here provide a basis for calculating time-varying distribution patterns of carabids in farmland and woody habitat. The formulas for calculating motility can be used for other taxa.

Farming systems in the Costa Chica region in Mexico face limitations linked to low yields and soil fertility degradation. Several alternative maize-based cropping systems have been proposed to improve current limitations. These field-level options need to be evaluated at farm level in order to assess their feasibility, taking into account input requirements, contributions to self-sufficiency in food and long-term soil fertility, and the availability of labor. In this study, we defined four scenarios to explore consequences of changes in current farming systems for eight typical farms in the region; the first two scenarios comprised redressing current imbalances in crop nutrition and organic matter (OM) supply, respectively, and the last two scenarios explored high fertilizer input and animal husbandry. Farms responded in different ways to the various options depending on available land, current soil quality, current cropping systems and presence of livestock. Improvements in crop nutrition based on mineral fertilizers increased family income but only had substantial effects on soil OM (SOM) balances when fertilizer rates were double the amount currently subsidized. Addition of organic fertilizers resulted in positive effects on SOM balance, but with often strong trade-offs with family income due to costs of acquisition, transport and application. Animals played an important role in increasing SOM balances, but had relatively little effect on improving family income. The results demonstrated that improvements in family income and SOM balance at farm scale were feasible but that without more fundamental system changes trade-offs between short-term yield increases and longer-term soil fertility increases should be expected. The results highlight the need for policies that take into account farm-specific differences in crop and livestock intensification opportunities.

In complex decision problems, some objectives are not well quantified or are not introduced explicitly in optimization models. In view of this inherent limitation of models, solutions that are nearly optimal, i.e. deviating less than a predefined percentage from the optimal value of the quantified objective functions, can constitute interesting alternatives for stakeholders. The aim of this paper is to extend the analysis of nearly optimal solutions to mixed-integer linear programming (MILP) models. Two branch-and-bound algorithms are described to generate nearly optimal solutions, and methods are discussed to summarise and to present nearly optimal solutions. A case study is introduced with an MILP model developed to design farming systems in the Netherlands. This case study shows that the presentation of nearly optimal solutions provides relevant information to resolve complex decision problems.

Crop rotation has been used for the management of soilborne diseases for centuries, but has not often been planned based on scientific knowledge. Our objective was to generate information on Sclerotium rolfsii dynamics under different crop or intercrop activities, and design and test a research approach where simple experiments and the use of models are combined to explore crop sequences that minimize Southern blight incidence. The effect of seventeen green manure (GM) amendments on sclerotia dynamics was analyzed in greenhouse and field plot experiments during two years. The relative densities of viable sclerotia 90 days after winter GM (WGM) incorporation were generally lower than after summer GM (SGM) incorporation, with average recovery values of 60% and 61% for WGM in the field, 66% and 43% for WGM in the greenhouse, and 162% to 91% for SGM in the greenhouse, in 2009 and 2010, respectively. Sclerotia survival on day d after GM amendment was described by the model Sf = Si × exp(−b × d), relating initial (Si) and final (Sf) sclerotia densities. Relative decay rates of the sclerotia (b) in SGM amended soil were largest for alfalfa (0.0077 ± 0.0031 day−1) and sudangrass (0.0072 ± 0.0030 day−1). In WGM amended soil, the largest b values were for oat (0.0096 ± 0.0024 day−1), wheat (0.0090 ± 0.0024 day−1) and alfalfa (0.0087 ± 0.0023 day−1). The effect of three cropping sequences (sweet pepper–fallow, sweet pepper–black oat and sweet pepper–onion) on sclerotia dynamics was analyzed in microplot experiments, and the data were used to calibrate the model Pf = Pi/(α + βPi), relating initial (Pi) and final (Pf) sclerotia densities. Median values for the relative rate of population increase at low Pi (1/α, dimension less) and the asymptote (1/β, number of viable sclerotia in 100 g of dry soil) were 8.22 and 4.17 for black oat (BO), 1.13 and 8.64 for onion (O), and 6.26 and 17.93 for sweet pepper (SwP). By concatenating the two models, sclerotia population dynamics under several crop sequences were simulated. At steady state, the sequence SwP–O–Fallow–BO resulted in the lowest long-term sclerotia density (7.09 sclerotia/100 g soil), and SwP–Fallow in the highest (17.89 sclerotia/100 g soil). The developed methodology facilitates the selection of a limited number of rotation options to be tested in farmers’ fields.

Smallholder dairy farms that intensify production risk resource degradation and increased dependence on external feeds and fertilizers due to lack of knowledge and appropriate technology, which undermines farm productivity and profitability. Here we analyze underlying causes at farm level of such process through an integrated analysis at the farm scale by assessing current resource use efficiency for grazing-based dairy farming systems representative of NW Michoacan, Mexico. Whole-farm yield gaps were quantified by comparing current farms to virtual reference farms that have the same farm surface area but improved farm management. Productivity of reference farms was calculated by assuming best crop production practices (as observed within the set of case study farms) and improved herd management. Three family-based (FB) and three semi-specialized (SS) dairy systems spanning three levels of intensification in terms of density of livestock units (LU): extensive (E, 1.2 LU ha−1) were monitored during one year (rainy and dry seasons) to assess productivity and resource use efficiencies. Milk production was generally low and variable (2.2–4.3 Mg milk cow−1 lactation−1, and 0.6–5.8 Mg ha−1) due to high incidence of mastitis, a large fraction of non-productive animals in the herd and inefficient reproduction management. During the dry season, grazing areas provided insufficient metabolizable energy, and milk production was sustained through increased use of concentrates (from 310 g kg−1 DMI in rainy season to 454 g kg−1 DMI−1 in dry season of the herd) and conserved forage. All farms had positive nitrogen, phosphorus and potassium balances, averaging 75 ± 16, 15 ± 6, and 19 ± 6 kg ha−1, respectively. Nutrients in animal excreta were mostly not recycled on the farms but lost to the environment, and nutrient surpluses increased with livestock density. The reference farms exhibited an attainable milk yield of 2.7 Mg ha−1 on the basis of full feed self-supply, and 4.2 Mg ha−1 when the crude protein limitation in the ration was lifted. Compared to the reference farm actual milk yields were on average 78.4% lower on FB farms and 57.9% lower on SS farms. The underlying causes of the farm yield gap differed between farms and were due to sub-optimal areas of forage maize, low forage and forage maize productivity and deficient herd management. We conclude that the farm yield gap analysis was effective in identifying the major shortcomings in management of the dairy farming systems and enabled formulation of change avenues for farm reconfiguration focusing on combined improvements in crop, feed and herd management and recycling of nutrients through manure management.

In European grassland landscapes, grazing and mowing play a key role for the maintenance of high-quality habitats that host important bird populations. As grasslands are also key resources for cattle feeding, there is a need to develop management strategies that achieve the double objective of production and biodiversity conservation. The objective of this study was to use a modelling approach to generate recognisable patterns of bird dynamics in farms composed of different land use proportions, and to compare their production and ecological dimensions. We developed a dynamic model, which linked grassland management to bird population dynamics at the field and farm levels. The model was parameterised for two types of suckling farms corresponding to contrasting levels of grassland intensification and for two bird species of high conservation value. A viability algorithm was used to define and assess viable management strategies for production and ecological performance so as to draw the shape of the relationship between both types of performances for the two types of farms. Our results indicated that, at the farm level, there was a farming system effect with a negative and non-linear relationship linking performance. Improving bird population maintenance was less costly in extensive farms compared with intensive farms. At the field level, the model predicted the timing and intensity of land use, maximising either production or ecological performance. The results suggested that multi-objective grassland management would benefit from public policies that consider levels of organisation higher than the field level, such as the farm or the landscape.

International audience

To reduce Fusarium Basal Rot caused by Fusarium oxysporum f.sp. cepae (Foc) through crop rotation, plant species should be selected based on Foc multiplication in their roots. Foc multiplication rates in 13 plant species were tested in a greenhouse. All plant species enabled Foc multiplication. The lowest Foc levels (cfu g−1 dry root) were found for wheat, sunflower, cowpea and millet, the highest for black bean. The highest Foc levels per plant were calculated for sudan grass. These data were used to calibrate the model Pf = Pi/(α + βPi) relating final (Pf) and initial (Pi) Foc levels in the soil. The rate of population increase at low Pi (1/α) was highest for onion and black oat and smallest for sunflower. The pathogen carrying capacity (1/β) was highest for black oat and black bean, and lowest for wheat, cowpea and foxtail millet. Foc soil population dynamics was simulated for crop sequences by concatenating Pi-Pf values, considering instantaneous or gradual pathogen release after harvest. Different soil Foc populations were attained after reaching steady states. Foc populations in the sequence onion –foxtail millet - wheat – cowpea were 67 % lower than in the sequence onion – sudan grass - black oat - black beans. In this work, by combining detailed greenhouse experiments with modelling, we were able to screen crops for their ability to increase Foc population and to explore potential crop sequences that may limit pathogen build-up.

Maize yields in continuous maize production systems of smallholders in the Costa Chica, a region in Southwest Mexico, are low despite consistent inputs of fertilizers and herbicides. This study was aimed at investigating the prospects of intercropping maize (Zea mays L.) and maize-roselle (Hibiscus sabdariffa L.) mixtures with the legumes canavalia (Canavalia brasiliensis Mart. ex Benth) and mucuna (Mucuna pruriens var. utilis) for improving nutrient uptake and weed suppression. Farmer-managed experiments were established in two communities in the region during 2006 and 2007 using randomized split-plot designs. Maize monocrops and maize-roselle intercrops grown with different sources of nutrients were intercropped with both legume species, sown 4–6 weeks after maize. Neither the legumes decreased yields of maize nor roselle, whereas they caused a reduction of the weed biomass by 24–55%. Total aboveground biomass returned to the soil increased up to 36% and total N, P, and K uptake was increased on average by 52%, 24%, and 30%, respectively. Legumes acted not only as a N-fixing crop, but also as a “catch” crop, preventing N and K leaching. With its prostrate growth habit and adaptation to poor soil conditions, canavalia demonstrated agronomic advantages in comparison to mucuna.

Experimental design theory provides tools to estimate parameters of nematode dynamics and yield loss functions with the highest accuracy given the available budget for the experiment. Variables in models, which take the role of predictors, are given values and a weight so that the best result is obtained. As a side result the prediction of the response will have a minimal variance. We introduce the concept of D-optimum design and consider in our models two response variables: the nematode density at the end of the season and the crop yield. Both variables depend on the same predictor, the initial nematode density. D-optimum design applies to linear regression models. For models that are nonlinear in the parameters, as is the case in this study, a linearisation at a given point in a parameter plane is used. When the initial nematode density at the experimental units is known prior to experimentation, one may optimally allocate the treatments to the units by selecting the combination that has the highest efficiency.

An approach is presented for supporting decision making on chemical pest control in an uncertain environment. Timing of chemical control is considered as a decision problem, which is analysed in terms of objectives, strategies, selection criteria, and a model of the system dynamics. Return on expenditure and insurance are considered to be two generally applicable objectives in pest control. These objectives are made operational by defining the profitability of strategy A compared with strategy B as the probability that A results in lower costs than B, and the risk associated with a strategy as the 0.90 quantile of the probability distribution of costs associated with that strategy, respectively. The authors propose to express the performance of relevant strategies in terms of profitability and risk. Risk-neutral damage thresholds where expected costs of no chemical control at any time just exceed those of immediate application of a pesticide, constitute a yardstick for assessing a strategy's performance. The approach is illustrated using a deterministic model of the pathosystem aphid-brown rust-winter wheat. Uncertainty is modelled as random inputs. No control and immediate pesticide application represent the only relevant strategies, as postponing chemical control decreases profitability and increases risk. The decline in risk attributable to pesticide application is larger for brown rust than for aphids. At risk-neutral damage thresholds the probability of positive returns on pesticide application amounts to only 30%. The causes of this bias to chemical control in recommendations for risk-neutral decision makers are discussed. Current recommendations for both aphids and brown rust appear to presume that farmers become more risk-averse as crop development advances.

The components of an existing model for supervised control of aphids (especially Sitobion avenae) and brown rust (Puccinia recondita) in winter wheat contain uncertainty. Their contribution to uncertainty about model output is assessed. The model simulates financial loss associated with a time sequence of decisions on chemical control as a function of crop development, population growth, and damage. Four sources of uncertainty were quantified: model parameters, incidence sample estimates, future average daily temperature, and white noise. Uncertainty about the first two sources is controllable because it decreases when more information is collected. Uncertainty about the last two sources is uncontrollable, given the structure of the model. Uncertainty about model output, characterized by its variance, is calculated by repeatedly drawing realizations of the various sources of uncertainty, and calculating financial loss after each draw. By processing new realizations of these sources one by one, the contribution of each component to total variance can be assessed using an adapted Monte Carlo procedure. For most relevant initial conditions and decision strategies the sources of uncontrollable uncertainty cause more than half of the uncertainty about model output. White noise in the relative growth rates of aphids and brown rust is the most important source of uncertainty. Resources for improvement of the model are most effectively allocated to studies of the population dynamics of aphids and brown rust.

The design of efficient public policies that aim to improve the provision of ecosystem services faces the problem that many ecosystem services are only apparent at spatial levels beyond the level at which they are managed. This makes it impossible to measure the contribution of individual resource managers to the provision of these services, as is the case in landscapes managed by private landowners such as farmers. As a consequence, the magnitude of the public support associated with the implementation of a policy cannot be specified down to the level of the individual manager/land owner. In this situation, institutional arrangements among resource managers are needed to determine how the public support defined at the higher level can be fairly distributed. This paper proposes a financial compensation arrangement among resource managers in a landscape, based on the Kaldor–Hicks criterion leading to a Pareto-optimal improvement, and explores the institutional requirements for the effective implementation of this arrangement. The proposed arrangement is illustrated with a case study in a woodland landscape in The Netherlands. The results show that private benefits among farms differed considerably due to biophysical, ecological and geographic differences among the farms. The financial compensation arrangement could contribute to improved equity among natural resource managers, which has been proposed as a key requirement for implementation of effective governance of environmental changes. The discussion addresses the institutional requirements of the proposed arrangement for governance structures that effectively deal with biophysical and socio-economic scale mismatches in sustainable use of natural resources.

Strategic spatial patterning of crop species and cultivars could make agricultural landscapes less vulnerable to plant disease epidemics, but experimentation to explore effective disease-suppressive landscape designs is problematic. Here, we present a realistic, multiscale, spatiotemporal, integrodifference equation model of potato late blight epidemics to determine the relationship between spatial heterogeneity and disease spread, and determine the effectiveness of mixing resistant and susceptible cultivars at different spatial scales under the influence of weather. The model framework comprised a landscape generator, a potato late blight model that includes host and pathogen life cycles and fungicide management at the field scale, and an atmospheric dispersion model that calculates spore dispersal at the landscape scale. Landscapes consisted of one or two distinct potato-growing regions (6.4-by-6.4-km) embedded within a nonhost matrix. The characteristics of fields and growing regions and the separation distance between two growing regions were investigated for their effects on disease incidence, measured as the proportion of fields with ≥1% severity, after inoculation of a single potato grid cell with a low initial level of disease. The most effective spatial strategies for suppressing disease spread in a region were those that reduced the acreage of potato or increased the proportion of a resistant potato cultivar. Clustering potato cultivation in some parts of a region, either by planting in large fields or clustering small fields, enhanced the spread within such a cluster while it delayed spread from one cluster to another; however, the net effect of clustering was an increase in disease at the landscape scale. The planting of mixtures of a resistant and susceptible cultivar was a consistently effective option for creating potato-growing regions that suppressed disease spread. It was more effective to mix susceptible and resistant cultivars within fields than plant some fields entirely with a susceptible cultivar and other fields with a resistant cultivar, at the same ratio of susceptible to resistant potato plants at the landscape level. Separation distances of at least 16 km were needed to completely prevent epidemic spread from one potato-growing region to another. Effects of spatial placement of resistant and susceptible potato cultivars depended strongly on meteorological conditions, indicating that landscape connectivity for the spread of plant disease depends on the particular coincidence between direction of spread, location of fields, distance between the fields, and survival of the spores depending on the weather. Therefore, in the simulation of (airborne) pathogen invasions, it is important to consider the large variability of atmospheric dispersion conditions.

Implications of changes in traditional Faidherbia albida based land use systems on productivity were investigated in Tigray, northern Ethiopia. The relation between F. albida based-land use systems and crop productivity was explored in 77 fields and 81 farms at field and regional scales, respectively. Barley yield and soil fertility increased when field locations were closer to a F. albida trunk in the F. albida alone (AA) and F. albida + livestock (AL) land use systems. However, the F. albida + Eucalyptus camaldulensis (AE) land use system showed a decreasing trend in barley yield and soil fertility as distance from a F. albida trunk decreased. At regional scales, higher F. albida tree density per farm and sparsely cultivated land use types were associated with increased potential ecosystem services (barley yield). This study suggests that local biodiversity components (e.g. F. albida trees) can increase crop yield and soil fertility significantly when grown within and around farm lands. This study contributes to the knowledge on agricultural productivity enhancement by developing an approach to scaling up from farm to regional level.

The contribution of agriculture to the welfare of society is determined by its economic, social and environmental performance. Although theoretical discussions can be found in the literature, few reports exist that integrate the social demand for multifunctional agriculture in the evaluation of the sustainability and the global welfare of society. This paper presents a methodology that combines economic valuation, integrated modelling, stakeholder analysis, and multi-criteria evaluation. It consists of three steps to determine: (1) social demands for multifunctional agriculture; (2) feasible technical alternatives available from the supply part of the market; (3) the net utility of alternatives for society measured as the change in social net benefit, i.e. the sum of changes compared to the current situation expressed in utility of market and non-market net benefits. Market net benefits are represented by their monetary value. Quality Function Deployment combined with Analytic Network Process (QFD/ANP) were used to estimate the non-market net benefits. The methodology is applied to the case study of a dairy-farming based agricultural landscape in the Northern Friesian Woodlands, The Netherlands. Social net benefit depended on land use, i.e. pasture management regimes on each of the agricultural fields and on presence or absence of hedgerows around the fields. Changes in market net utility were expressed in terms of changes for farmers, consumers and government. Changes in non-market net utility were expressed in terms of changes in landscape quality, nature value and environmental health for Dutch society as a whole, as estimated from European public surveys (Eurobarometer). The complete solution space defined by the market and non-market net benefits of landscapes with alternative patterns of land use was estimated to offer insight in the trade-off between market and non-market performance and enable selection of ‘icon’ landscapes to target or avoid. Improvement of the current landscape towards the social optimum would involve changes in pasture management resulting in higher gross margin for farmers, slightly relaxing current environmental restrictions, which could be reached at lower levels of subsidies in agri-environmental programs. In addition to such overall optimum the results demonstrate the trade-off between market and non-market benefits and the characteristics of current, utopian and dystopian landscapes. The approach provides an alternative to current economic valuation methods which focus on assessment of economic value as an input to analysis. Here, economic value emerges as the trade-off between market and non-market functions which is an output of the analysis.

[Departement_IRSTEA]GT [TR1_IRSTEA]RURAMEN / CERES [TR2_IRSTEA]RURAMEN / AMANDE; International audience; Multifunctionality of Agriculture (MFA) is a concept that supports the recognition of complex interdependencies between different resources, production processes and outputs of agricultural land use. Political decision making within a sustainable development frame requires extensive information about these interrelationships in order to analyse the impact of implemented policies and to assess future policy effects. This paper presents selected results of the EU FP6 supported MultAgri project, such as a comparative overview of models, techniques and tools that have been applied to the assessment of various agricultural outputs. In detail, multidimensional modelling tools and economic valuation instruments have been inspected and valuated. Examples from France, Germany, The Netherlands and Portugal - the countries reviewed within the MultAgri workpackage 3 - are used to highlight specific instrumental strengths and weaknesses. Conclusions are drawn with respect to further methodological research needs on multifunctionality of agriculture.

In different parts of the world, there is an urgent need for redesigning and innovating farming systems. Such a process may be supported by model-based explorations that enable ex-ante evaluation of a broad range of alternatives. Since a variety of viable patterns of farm development exists related to farm resource endowment and farmer's strategy, model-based explorations should be able to capture the existing variation in resource endowment and strategies in order to have impact on strategic farm management. In this paper, we present an overview of the model-based explorative method based on the MILP model Farm Images, applied to explore options for sustainable development of vegetable farms in Canelón Grande, Uruguay. The method is used to gain insight into the impact of current farm resource endowment on the possibilities for sustainable development and on the resource use efficiency at farm scale. We maximized farm income for 128 different farm types in an environment-oriented scenario and in an income-oriented scenario. Farm types were defined by combining 4 farm sizes, 2 labor endowments, 4 irrigation endowments, 2 soil quality combinations and 2 mechanization levels. The results demonstrate a strong impact of farm resource endowment on possibilities for sustainable development, as well as synergy between labor, land and irrigated area on resource-use efficiency at farm scale. Farms with 10 ha of land or less, representing 47% of the farms in the Canelón Grande region, could only achieve a family income higher than the average income of Uruguayan families when the irrigated area was ca. 40% of the farm area. The achievement of environmental targets was less costly in terms of income on farms with a low rather than high labor availability per unit area and on farms with irrigation facilities.