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The Western Highlands of Guatemala are dominated by small-scale farming in indigenous communities. Mountain conditions and overpopulation have led to expansion of the agricultural frontier with con...

Context The COVID-19 pandemic has been affecting health and economies across the world, although the nature of direct and indirect effects on Asian agrifood systems and food security has not yet been well understood. Objectives This paper assesses the initial responses of major farming and food systems to COVID-19 in 25 Asian countries, and considers the implications for resilience, food and nutrition security and recovery policies by the governments. Methods A conceptual systems model was specified including key pathways linking the direct and indirect effects of COVID-19 to the resilience and performance of the four principal Asian farming and food systems, viz, lowland rice based; irrigated wheat based; hill mixed; and dryland mixed systems. Based on this framework, a systematic survey of 2504 key informants (4% policy makers, 6% researchers or University staff, 6% extension workers, 65% farmers, and 19% others) in 20 Asian countries was conducted and the results assessed and analysed. Results and conclusion The principal Asian farming and food systems were moderately resilient to COVID-19, reinforced by government policies in many countries that prioritized food availability and affordability. Rural livelihoods and food security were affected primarily because of disruptions to local labour markets (especially for off-farm work), farm produce markets (notably for perishable foods) and input supply chains (i.e., seeds and fertilisers). The overall effects on system performance were most severe in the irrigated wheat based system and least severe in the hill mixed system, associated in the latter case with greater resilience and diversification and less dependence on external inputs and long market chains. Farming and food systems' resilience and sustainability are critical considerations for recovery policies and programmes, especially in relation to economic performance that initially recovered more slowly than productivity, natural resources status and social capital. Overall, the resilience of Asian farming and food systems was strong because of inherent systems characteristics reinforced by public policies that prioritized staple food production and distribution as well as complementary welfare programmes. With the substantial risks to plant- and animal-sourced food supplies from future zoonoses and the institutional vulnerabilities revealed by COVID-19, efforts to improve resilience should be central to recovery programmes. Significance This study was the first Asia-wide systems assessment of the effects of COVID-19 on agriculture and food systems, differentiating the effects of the pandemic across the four principal regional farming and food systems in the region.

Land use change results from top-down drivers, such as policies, trade, and migration. Land use change may also result from community-based responses. In Mexico, rural communities govern most of the country's forests. This study aimed to assess how socio-economic and biophysical factors affected the landscape trajectories of rural communities in southern Mexico. It also aimed at evaluating the role of communities in landscape change. Land use change of 63 rural communities was analyzed for the years 1987 and 2017. Four land uses were distinguished: forest, shrubland, agriculture, and bare soil. Five groups of communities were identified according to their socio-economic and biophysical factors. Two groups located in areas with high slopes and elevated marginalization index values showed deforestation patterns. Two other groups, consisting of more than half of the municipalities assessed, showed reforestation trends. The final group did not reveal major changes in land use. Two municipalities with reforestation trends were selected for an in-depth analysis of how community-based responses impacted natural resource management and conservation. Through local assemblies, the population voted for regulations that increased the forest area and reduced the bare soil. There was no evidence that these regulations affected croplands. These results show how a combination of socio-economic and biophysical factors can affect landscape change, but it also shows the often overlooked role of communities as a relevant bottom-up driver of change.

Highlights • Stakeholders’ engagement in the assessment process helps build capacity. • Stakeholders help define local sustainability goals, opportunities, and indicators. • Local champions, coordination, and sustained support are key to success. • Timely monitoring and continual improvement are part of the iterative approach. • Trust, engagement, communication, and capacity are required for improvement., A systematic process for assessing progress toward landscape sustainability goals is developed and tested. Application of the approach builds capacity and promotes continual improvements in management practices, thus enabling timely action to address changing conditions while progressing toward locally defined goals. We consider how the approach applies to agricultural landscapes, that is farm ecosystem interactions with the environment and human well-being. We present lessons learned from applying the assessment approach in two contrasting situations: large, high-input, commercial agriculture in northwestern Mexico and small, low-input family farms in the Western Highlands of Guatemala. Applying the approach reveals five attributes required for success and the means to achieve those conditions. (1) Having a capable local champion for the project is critical. (2) Implementation of the approach must be in concert with local people and organizations as well as with regional and national policies and programs. (3) Identification and engagement of key stakeholders is essential. (4) Application of the approach is not meant to be a one-time effort but rather an ongoing and systematic process. (5) Engagement and buy-in from stakeholders including multiple agency levels is essential for allocation of necessary resources and logistic support in the continuing implementation of the approach.

International audience; In the mountainous areas of South-East Asia, family farms have shifted from subsistence to input-intensified and market-oriented maize-based farming systems, resulting in a substantial increase in farm income, but also in new environmental threats: deforestation, biodiversity loss, soil erosion, herbicide leaching and soil fertility degradation. In this typical case study of cash-strapped farms, where the balance between socio-economic and environmental dimensions of sustainability is complex, we used participatory methods (serious games and Q-methodology), combined with agronomic field monitoring, to identify relevant farm and field-level criteria for sustainability assessment.Serious games at farm level showed that short-term socio-economic dimensions prevailed over environmental dimensions in farmers' objectives. However, farmers also greatly valued their capacity to transfer a viable farm to the next generation and avoid herbicide use. Serious games at field level showed that some farmers were willing to preserve soil fertility for future generations. The agronomic field monitoring showed that maize yield deviations from potential water-limited yield were primarily due to weed infestation favoured by low sowing density, due to uncontrolled moto-mechanized crop establishment. This technical failure at the beginning of the maize cycle led to herbicide overuse, poor returns on investment for fertilizer, and increased exposure to soil erosion.Combining the perspectives of scientists and farmers led to the following set of locally-relevant criteria: i) at farm level: farm income, diversity of activities, farmer autonomy, farmer health, workload peaks, soil fertility transfer between agroecological zones in the landscape, rice and forage self-sufficiency; ii) at field level: resource use efficiency, soil fertility, erosion and herbicide risks, susceptibility to pests, weeds and climate variability, biodiversity, land productivity, economic performance, labour productivity and work drudgery. Our approach helped to identify key relevant sustainability criteria and could be useful for designing alternatives to current maize-based cropping systems, and contributed to informing priority-setting for institutional development and agricultural policies in the region.

Methods to construct farm household typologies may differ in their approach but they share a common feature: they rely mostly on structural farm data. Methods to build functional typologies are far less abundant. Households or communities are complex social-ecological systems that often exhibit patterns in their response to disturbances (e.g., droughts, floods, price shocks, policy change). We propose building functional typologies – classifiable ´behaviours´ of rural actors – using archetype analysis to categorise such responses and identify salient behaviours. We illustrate this approach by examining the response of rural households to recurrent droughts in northern Patagonia, Argentina, as revealed by 23 in-depth interviews about perceptions and strategies concerning droughts. Using the algorithm from Mørup and Hansen (2012), and the corrected Akaike decision rule, we identified three archetypes (A–C) that represented three distinct aggregated responses of households to droughts. Archetype A presented variable degrees of resistance to droughts (production losses < 40%), avoidance and diversification, whereas archetype B exhibited tolerance (higher losses) and some degree of transformability (off-farm income). Archetype C farms exhibited high levels of vulnerability, if some degree of tolerance to high losses, but no real adaptive strategy to speak of. Such pattern could not have been identified through the more commonly used typology building methods such as using multivariate and clustering techniques. By allowing to combine qualitative and quantitative information, and to deal with a relatively small number of observations, archetype analysis appears as highly suitable to delineate functional farm household typologies. Fil: Tittonell, Pablo. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina Fil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina Fil: Solano Hernández, Ainhoa. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina Fil: López Ridaura, Santiago. Centro Internacional de Mejoramiento de Maíz y Trigo; México Fil: Easdale, Marcos Horacio. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina

Improving farming systems in resource-poor contexts is often difficult as farmers face multiple challenges to implement the innovations developed by researchers. Viable solutions may however be present within local communities by positive deviant farmers, i.e. farmers that outperform positively compared to others. This study develops a positive deviance informed methodology to support redesign of farming systems, with the aim to improve farm productive, economic and environmental performances. We tested the methodology in Bihar, India, using survey data from 43 farms and the indicators of operating profit, soil organic matter balance, water use and dietary energy production. Positive deviant farms and practices were first identified and then recombined into a redesigned farm in consultation with farmers. The FarmDESIGN model was used to calculate current farm performance and to explore potential alternative farm configurations in the redesign. We found that outstanding performance on all indicators could only be reached by integrating high livestock density with an optimal combination of crop practices, which confirms the key role of interactions among components in mixed crop-livestock systems to improve all dimensions of farm sustainability. The redesigns outperformed all real farms on the indicators assessed. Farmers confirmed the viability of the redesigns in focus group discussions and their suggestions can serve as useful input for a next cycle of farm redesign. Since all suggestions are locally practiced and have proven to be accessible, affordable and recognizable, we conclude that our methodology based on positive deviant farms and practices yields promising results with a large potential to boost agricultural development for resource-scarce smallholder farmers.

Research and development agencies, as well as policy makers and agri-food enterprises, need reliable data to support informed decisions that can improve the sustainability of agricultural landscapes. We present a review of agricultural sustainability assessment frameworks (ASAF) that identifies the features most relevant to monitoring progress towards sustainability goals for agricultural landscapes. This qualitative review considers a variety of approaches for defining goals and for selecting stakeholders, spatial and temporal boundaries, indicators, and analytical approaches. We focused on assessment frameworks that (i) include environmental, social, and economic implications of agriculture; (ii) are applicable to multiple, non-specified farm system types; (iii) are described in an English language, peer-reviewed publication; (iv) have been developed for use at a farm system to regional spatial scale; (v) engage stakeholders; (vi) provide case studies; and (vii) could be used in a variety of contexts across the globe. Based on the review, we provide recommendations for further development and use of assessment frameworks to better address the needs of agricultural research, extension, and development organizations. We recommend an agro-ecosystem approach to help stakeholders identify appropriate indicators for their situation. Assessment methods need to be flexible enough for adaptation to a spectrum of agricultural landscapes and changing environmental conditions, and remain relevant as farmers and other stakeholders acquire new information, resources, and different management techniques. We find that to address information gaps across different scales from farm to region will require creativity and some reliance on local knowledge systems to support adaptive management. Assessment results should communicate relationships among ecosystem services and socio-economic activities affected by agricultural landscapes. Visualization tools can facilitate understanding of trade-offs and synergies among sustainability goals as reflected by individual indicators.

The increasingly complex challenges facing agricultural systems require problem-solving processes and systems analysis (SA) tools that engage multiple actors across disciplines. In this article, we employ the theory of affordances to unravel what tools may furnish users, and how those affordances contribute to a tool's usefulness in co-design and co-innovation processes. Affordance is defined as a function provided by an object through an interaction with a user. We first present a conceptual framework to assess the affordances of SA tools. This framework is then applied in a literature review of three SA tools used in agricultural systems research (fuzzy cognitive mapping, bio-economic whole-farm models, and role play and serious games). Through this exercise, we extend the SA tool design and implementation dialogue by illuminating (i) links between lower-level affordances, tool design, and heuristic functioning, and (ii) the central role of use setting and facilitation in mobilizing higher-level, productive affordances. Based on our findings, we make five propositions for how SA tool design and implementation in participatory problem-solving settings can be improved.

The western highlands of Guatemala lie within the area where maize was first domesticated, and maize remains central to farmers' livelihood security. Over 50% of the population in the region are in poverty, and over 48% suffer from chronic malnutrition. Development efforts have focused on improved land management, crop diversification, and improved access to markets, especially for high-value vegetable crops such as snow peas. As a result of successful initiatives worldwide, more attention is being directed at the extent to which farmers can benefit from market opportunities for indigenous crops by receiving a price premium for providing the environmental service of conserving agricultural biodiversity. Such an approach bridges the gap between poverty alleviation and in situ conservation. We explored this potential development pathway through both qualitative and quantitative research. Focus groups were conducted in 5 communities in the maize-growing highlands of Guatemala, followed by a survey of 989 farm households in 59 locations. Our results show that most farmers in the western highlands of Guatemala are severely maize deficient; on average, farm households produce enough maize for only 6.9 months of consumption a year and are forced to purchase maize to meet basic consumption needs. The results are in sharp contrast to research conducted in highland communities in neighboring Mexico, where many farmers are able to sell their maize in relatively lucrative specialty maize markets. In the context of renewed interest in reducing poverty in Central America, our research suggests that rather than focus on market development for local maize varieties, development efforts should target other types of interventions.

Despite considerable development investment, food insecurity remains prevalent throughout East and West Africa. The concept of ‘sustainable intensification’ of agricultural production has been promoted as a means to meet growing food needs in these regions. However, inadequate attention has been given to assessing whether benefits from intensification would be realized by farm households considering highly diverse resource endowments, household and farm characteristics, and agroecological contexts. In this study, we apply a simple energy-based index of food availability to 1800 households from research sites in 7 countries in East and West Africa to assess the food availability status of each of these households and to quantify the contribution of different on- and off-farm activities to food availability. We estimate the effects of two production intensification strategies on food availability: increased cereal crop production from crop-based options, and increased production of key livestock products from livestock-based options. These two options are contrasted with a third strategy: increased off-farm income for each household from broader socioeconomic-based options. Using sensitivity analysis, each strategy is tested against baseline values via incremental production increases. Baseline results exhibit considerable diversity within and across sites in household food availability status and livelihood strategies. Interventions represented in the crop and livestock options may primarily benefit food-adequate and marginally food-inadequate households, and have little impact on the most food-inadequate households. The analysis questions what production intensification can realistically achieve for East and West African smallholders, and how intensification strategies must be augmented with transformational strategies to reach the poorest households.

Climate model projections coupled with process-based crop models are advocated for assessing impacts of climate change on crop yields and for informing crop-level adaptations. However, most reported studies are vague on the choice of the global circulation models (GCMs) for climate projections, and on the corresponding uncertainty with this type of model simulations. Here we investigated whether climate-crop modelling can be used for identifying crop management-level adaptation options. We focused our analyses on a case study for maize in southern Africa using the APSIM crop growth model and projections from 17 individual climate models for the period 2017–2060 for the contrasting representative concentration pathways 2.6 and 8.5. Intensification of nitrogen fertiliser use (from 30 to 90 kg N ha−1) was simulated as an example of a crop management-level adaptation to climate change. Uncertainties in crop yield predictions were about 30 to 60%, i.e. larger than expected crop responses to most management-level interventions or adaptations. Variation in simulated yields was caused by inter-seasonal rainfall variability and uncertainty with climate models. Some GCMs resulted in significantly different maize yield predictions, without any clear pattern across sites. Given these high uncertainties, we argue that crop modellers should be cautious when informing future crop management adaptation strategies based on climate-crop model ensembles. A better use of crop models is the simulation of crop responses to current weather variability aiming at the identification of crop management practices for coping with climate variability. Promising practices can then be evaluated with farmers on their feasibility over a range of plausible future biophysical and socio-economic farming conditions.

Wheat is one of the most important staple foods as it provides 55% of the carbohydrates and 20% of the food calories and protein consumed worldwide. Demand for wheat is projected to continue to grow over the coming decades, particularly in the developing world, to feed an increasing population. More than 22% of global area under wheat is located in South Asia which is home to about 25% of the world's population. The Intergovernmental Panel on Climate Change has projected that in the 21st century South Asia is going to be hit hard by climate change. Changes in mean annual temperature will exceed 2°C above the late-20th-century baseline and there can be declines in the absolute amount of precipitation during December to February, when wheat is grown in the region. Temperature, precipitation, and enhanced CO2 level in the atmosphere, the three climate change drivers can affect wheat cropping both directly at plant level and indirectly through changes in properties and processes in the soil, shifts in nutrient cycling, insect pest occurrence, and plant diseases. Studies pertaining to the effects of climate change on soil processes and properties are now becoming available and it is becoming increasingly clear that climate change will impact soil organic matter dynamics, including soil organisms and the multiple soil properties that are tied to organic matter, soil water, and soil erosion. Warmer conditions will stimulate soil N availability through higher rates of mineralization so that fertilizer management in wheat is also going to be governed by emerging climate change scenarios. Similarly, higher temperatures and altered precipitation regimes will determine the net irrigation water requirements of wheat. Several simulation models have projected reduced wheat yields in the emerging climate change scenarios, but occurrence of an extreme heat event around senescence can lead to crop models to underestimate the effects of heat on senescence by as much as 50% for late sowing dates for 2°C rise in mean temperature. So as to project productivity of wheat in South Asia in the emerging climate change scenarios with increased certainty, integrated holistic modeling studies will be needed which also take into account effect of extreme heat events as well as the contribution of altered soil processes and properties.

In this paper, we present a framework and a methodology to identify the long-term strategies of small-scale farmers dealing with uncertainties. To do so, we link the Activity System framework to the concept of perceived vulnerability and analyse the small-scale farmers' trajectories. Based on a sample of 34 small-scale coffee producers in Guatemala and through the analysis of case studies and classification methods, we identify some trends in long-term decisionmaking. These trends are mainly built on responsiveness, autonomy, vulnerability shifts and collective means of action. We finally discuss these findings in the light of previous studies carried out in different contexts.

International audience; European farmers are facing challenges that call for important transformations on their agricultural production systems, including an increasing number of regulations aimed at reducing environmental impacts from farming practices. Climate change is also expected to affect agricultural production in most European regions, and in Southern Europe this effect is expected to negatively impact yields. In this study, we present the application of an innovative participatory approach to assess the potential of innovative agricultural systems to reconcile environmental sustainability with economic viability while contributing to local and global food security. Our approach consisted of combining (1) the participation of local stakeholders in the design of narrative scenarios, and (2) an integrated assessment of scenarios through the calculation of indicators at different scale with a bio-economic model. We tested our approach with a case study situated in the Camargue region of Southern France. Rice is currently the main crop in this region, but farmers there face adverse economic conditions linked to the recent reform of European Common Agriculture Policy. After identifying the main drivers of change, local stakeholders developed narrative scenarios and described how farmers would adapt within the context of those changes. These elements were then translated into model inputs. At the regional level, the four scenarios led to variations in farmland acreage (28,000–33,000 ha), as well as the proportion of rice crops (19–75%) and areas cultivated under organic farming standards (8–43%). The four scenarios also led to different values for indicators of agricultural economic welfare, food production, and environmental impacts. Trade-offs between these indicators and the associated objectives assigned to agriculture were identified and discussed with the stakeholders. We end with a discussion of the limitations and advantages of our approach to the participatory development and assessment of locally developed narrative scenarios.

Small-scale coffee producers are particularly exposed to a very fluctuant market. The present work aims at characterising the adaptation of small-scale coffee and honey producers to the 1999–2003 coffee crisis in the Guatemalan Highlands from a systemic and agronomical perspective. Working with a homogeneous sample of 34 families we identify up to 27 different flexibility mechanisms. A qualitative analysis of families' life histories was combined with classification methods. Besides confirming the importance of the availability resources and some well known adaptive responses, such as workload intensification, expenses reduction or the importance of social networks, the classification of households reveals a sequence in the implementation of flexibility mechanisms. The focus on the combination of coffee and honey productions also suggests changing the traditional approaches to agricultural processes toward the adoption of a more systemic perspective. The possible impacts of these findings on technical extension and construction of public policies are then discussed.

Alternative agricultural systems, such as organic farming (OF), are promising options to sustain both agriculture productivity and environmental health. However, the adoption of OF by farmers is occurring more slowly than is advocated. A key factor limiting farmers is an inability to predict socio-economic consequences of converting to OF. To overcome this, we developed a novel method of integrated assessment of agricultural systems (IAAS) and applied it to scenarios of development of OF in the Camargue region, South of France. In collaboration with the local stakeholders, we characterized the agricultural systems at different spatial scales and defined scenario related to the future of agriculture and to OF. We then used agent-based modeling with farmers and bio-economic modeling with local stakeholders for scenario assessment. We examined the effects on the development of OF systems of key factors such as the ongoing reform in the European Common Agricultural Policy and the effects of regulations for decreased use of pesticides. The policy reform implied trends towards a diversification of crops and greater possibility for conversion to OF. Development of OF at the regional level led to improved environmental performance, but caused a decrease in profitability of the rice supply chains. In light of the observed trade-off between rice production and OF development, objectives and options towards more sustainable agricultural systems were discussed with farmers and local stakeholders. Stakeholders' assessment of the framework provided insights on the positive and specific aspects of the IAAS methodology requiring improvement. The complementarities of agent-based and bio-economic modeling provide stakeholders with a better-informed assessment of diverse scenarios, for the development of more sustainable agricultural systems.

Part III; International audience; Is the regional conversion to Organic Farming (OF) possible? What could be the consequences at different scales in terms of social and economic development as well as nature conservation? Taking the heterogeneity of farms and farming systems in the region into account, are there farmers more prone to conversion and others that face greater obstacles? The objective of this paper is to shed light on some of these question by presenting the results of a scenario assessment carried out with regard to the extension of OF in the Camargue region in southern France. The application of different modelling approaches with great potential for the multi-scale and multi-criteria evaluation of the extension of OF is presented: bio-economic models, agent-based models and land-use/cover change models. According to our results, the most probable conversion in the near future in the Camargue would take place in fields with low salt pressure that belong to livestock breeders and diversified cereal producers. However, the regional conversion to OF is plausible since the region could maintain its economic productivity while decreasing potential harmful impacts on the environment. Finally, the possible conversion trajectories suggest that certain farmers (specialised in rice production) might need greater assistance to ensure such conversion to OF since their economic performance would be hampered during that period. The application of these three approaches to explore the same scenario in one region revealed their complementarity for tackling the complex issue of regional conversion to OF from different angles.

Evaluating the impacts of the development of alternative agricultural systems, such as organic or low-input cropping systems, in the context of an agricultural region requires the use of specific tools and methodologies. They should allow a prospective (using scenarios), multi-scale (taking into account the field, farm and regional level), integrated (notably multicriteria) and participatory assessment, abbreviated PIAAS (for Participatory Integrated Assessment of Agricultural System). In this paper, we compare the possible contribution to PIAAS of three modeling approaches i.e. Bio-Economic Modeling (BEM), Agent-Based Modeling (ABM) and statistical Land-Use/Land Cover Change (LUCC) models. After a presentation of each approach, we analyze their advantages and drawbacks, and identify their possible complementarities for PIAAS. Statistical LUCC modeling is a suitable approach for multi-scale analysis of past changes and can be used to start discussion about the futures with stakeholders. BEM and ABM approaches have complementary features for scenarios assessment at different scales. While ABM has been widely used for participatory assessment, BEM has been rarely used satisfactorily in a participatory manner. On the basis of these results, we propose to combine these three approaches in a framework targeted to PIAAS.

International audience; In view of the urgent need to improve agroecosystem sustainability, several efforts have been made to evaluate the effect of alternative strategies on key environmental and socioeconomic variables at the farm, community and regional levels. Most peasant farmers manage complex and diverse agroecosystems, and constantly adapt management strategies with multiple aims. A sustainability evaluation framework for peasant systems has been applied in over 40 case studies in Latin America, from which 15 were analysed, focusing on the choice of indicators, the effect of alternative strategies on agroecosystem sustainability and the trade-offs involved. Common indicators include yields, income, agrodiversity and external input dependence. Alternative strategies include crop/product diversification and soil conservation practices. Yields, income and agrodiversity improved in most cases, but in some cases the establishment costs increased external input use. Trade-offs observed include improved performance of a subsystem (i.e. crops) vs. decreased one in others (livestock, forestry) and increases in productivity vs. decreases in stability, resilience and reliability. The difficulty of assessing systems in transition towards alternative management was acknowledged by some evaluation teams. Applying the framework to such a variety of cases allowed making the sustainability concept operational, promoted alternative strategies and generated knowledge on agroecosystem processes among stakeholders.

SAD CT1 ridaura@supagro.inra.fr Nutrient Cycling in Agroecosystems: formerly Fertilizer Research ; FI 2008 1.282; International audience; Smallholder farming systems in sub-Saharan Africa are often nutrient-limited, and therefore imports must be increased to compensate exports and losses. To explore whether the properties of nutrient cycling networks relate to the systems'capability to sustain rural families, we investigated N flows within contrasting crop-livestock systems in Ethiopia, Kenya and Zimbabwe applying concepts from ecological network analysis. Farm households were conceptualised as networks, the compartments were the household and their farming activities which were connected by the N flows. Indicators assessing network size, activity and cycling, and the organisation and diversity of the N flows were compared with system productivity and food self-sufficiency. Results showed that organisation and diversity of N flows to, from and within the farm households differed more between farms of different resource endowments than across sites. The amount of N cycled per household was small and comparable across sites: less than 25 kg N year-1, and for the poor households less than 5 kg N year-1. Poor households with soil N stocks that were 50-60% smaller than wealthier households depended more on external inputs (e.g. a dependence of 65% vs. 45% in Zimbabwe). Productivity was positively related to network size, its organisation and N cycling, but utilisation efficiencies were different across sites in relation to soil N stock and the importance of livestock for N flows. Greater size of the N flow network and its organisation led to increased productivity and food self-sufficiency, reducing dependence, which may increase the adaptability and reliability of smallholder crop-livestock systems.

SAD CT1 ridaura@supagro.inra.fr; Slurry management is a central topic in the agronomic and environmental analysis of intensive livestock production systems. The objective of this study is to compare the environmental performance of two scenarios of collective slurry management for the disposal of excess nitrogen from animal manure. The scenarios are the transfer of slurry and its injection to crop land, and the treatment of slurry in a collective biological treatment station. The study is based on a real case in the West of France, where a group of farmers is developing a collective plan for the disposal of almost 7000 m(3) of excess pig slurry. The evaluation is carried out by Life Cycle Assessment, where emissions and resource consumption are quantified and aggregated into four environmental impact categories: eutrophication, acidification, climate change, and non-renewable energy use. Ammonia emitted is the most important contributor to acidification and eutrophication, while methane contributes most to climate change. Both ammonia and methane are mostly emitted during the storage of slurry and, in the case of the treatment scenario, also during composting the solid fraction of the slurry. The two management strategies are similar with respect to climate change, whereas eutrophication and acidification are twice as large for treatment relative to transfer. Electricity needed for the treatment process is the main contributor to non-renewable energy use for the treatment scenario, while the transfer scenario represents a net energy saving, as energy saved by the reduction of mineral fertiliser use more than compensates for the energy needed for transport and injection of slurry. The overall environmental performance of transfer is better than that of treatment, as it involves less acidification, eutrophication and non-renewable energy use. The method employed and the results obtained in this study can provide elements for a transparent discussion of the advantages and disadvantages of contrasting excess slurry management scenarios as well as the identification of the main aspects determining their environmental performance. (c) 2008 Elsevier Ltd. All rights reserved.