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Crop production in northern regions is projected to benefit from longer growing seasons brought on by future climate change. However, production also faces multiple challenges due to more frequent and intense extreme weather phenomena, and uncertain future prices of agricultural inputs and outputs. Extensive studies have been conducted to investigate the impacts of climate change on cereals yield change, but integrated assessments that also consider the management and economy of cereal farms have been rare so far. In this study, the effects of climate change-driven crop productivity change on farm level land use dynamics, input use, production management and farm income were considered from the point of view of dynamic decision making of a rational risk-averse farmer. We assessed whether a farmer can gain from improved crop yields when using adapted cultivars and managing the farm accordingly. We incorporated crop yield estimates from a process-based large area crop model (MCWLA) run with two climate scenarios into a dynamic economic model of farm management and crop rotation (DEMCROP) to investigate future input use, land use with crop rotation, economic gross margins and greenhouse gas emissions. A time span of 30 years was considered. The model accounts for the yield responses to fertilisation, crop protection, liming of field parcels, and yield losses due to monoculture. The approach resulted in a novel and necessary analysis of farm management, production and income implications of climate change adaptation under different climate and socio-economic scenarios. We analysed the effects of different climate and price scenarios at a typical cereal farm in the North Savo region, which is currently a marginal area for crop production in Finland due to its harsh climate. Crop modelling results suggest a 19–27% increase of spring cereal yields and 11–19% increase of winter wheat yields from the current level until 2042–2070. According to our economic farm level simulations, these yield increases would incentivise farmers towards more intense input use resulting in additional increase of yields by 3–8% at current prices. More land is allocated to barley and wheat, less to set-aside and oat. The economic gross margin would increase significantly from the current low levels. Greenhouse gas emissions from farms were estimated to increase with increasing production, but emissions per quantity produced (measured as feed energy units) would decrease. There is potential for sustainable intensification (SI) of crop production in the region.

Sunflower is one of the major oilseeds produced in Tanzania, but due to insufficient domestic production more than half of the country's demand is imported. The improvement of the sunflower food value chain (FVC) understanding is important to ensure an increase in the production, availability, and quality of edible oil. In order to analyse causes and propose solutions to increase the production of sunflower oil, a conceptual framework that proposes the combined use of different models to provide insights about the sunflower FVC was developed. This research focus on the identification of agricultural models that can provide a better understanding of the sunflower FVC in Tanzania, especially within the context of food security improvement. A FVC scheme was designed considering the main steps of sunflower production. Thereafter, relevant models were selected and placed along each step of the FVC. As result, the sunflower FVC model in Tanzania is organized in five steps, namely (1) natural resources; (2) crop production; (3) oil processing; (4) trade; and (5) consumption. Step 1 uses environmental indicators to analyse soil parameters on soil-water models (SWAT, LPJmL, APSIM or CroSyst), with outputs providing data for step 2 of the FVC. In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields. Thereafter, outputs from crop models serve as input for bio-economic farm models (FSSIM or MODAM) to estimate production costs and farm income by optimizing resource allocation planning for step 2. In addition, outputs from crop models are used as inputs for macro-economic models (GTAP, MAGNET or MagPie) by adjusting supply functions and environmental impacts within steps 3, 4, and 5. These models simulate supply and demand, including the processing of products to determine prices and trade volumes at market equilibrium. In turn, these data is used by bio-economic farm models to assess sunflower returns for different farm types and agro-environmental conditions. Due to the large variety of models, it is possible to assess significant parts of the FVC, reducing the need to make assumptions, while improving the understanding of the FVC.

CONTEXT The larger scale perspective of Integrated Assessment (IA) and smaller scale perspective of Impacts, Adaptation, and Vulnerability (IAV) need to be bridged to design long-term solutions to agricultural problems that threaten agricultural production, rural economic viability, and global food supplies. FEWCalc (Food-Energy-Water Calculator) is a new freeware, agent-based model with the novel ability to project farm incomes based on crop selection, irrigation practices, groundwater availability, renewable energy investment, and historical and projected environmental conditions. FEWCalc is used to analyze the interrelated food, energy, water, and climate systems of Finney County, Kansas to evaluate consequences of choices currently available to farmers and resource managers. OBJECTIVE This article aims to evaluate local farmer choices of crops and renewable energy investment in the face of water resource limitations and global climate change. Metrics of the analysis include agricultural and renewable-energy production, farm income, and water availability and quality. The intended audience includes farmers, resource managers, and scientists focusing on food, energy, and water systems. METHODS Data derived from publicly available sources are used to support user-specified FEWCalc input values. DSSAT (Decision Support System for Agrotechnology Transfer) with added arid-region dynamics is used to obtain simulated crop production and irrigation water demand for FEWCalc. Here, FEWCalc is used to simulate agricultural and energy production and farm income based on continuation of recent ranges of crop prices, farm expenses, and crop insurance; continuation of recent renewable-energy economics and government incentives; one of four climate scenarios, including General Circulation Model projections for Representative Concentration Pathway 8.5; and groundwater-supported irrigation and its limitations. RESULTS AND CONCLUSIONS A 50-year (2018-2067) climate and groundwater availability projection process indicates possible trends of future crop yield, water utility, and farm income. The simulation during more wet years produces high crop production and slower depletion of groundwater, as expected. However, surprisingly, the simulations suggest that only the Drier Future scenario is commercially profitable, and this is because of reduced expenses for dryland farming. Although simulated income losses due to low crop production are ameliorated by the energy sector income and crop insurance, the simulation under climate change still produces the worst annual total income. SIGNIFICANCE FEWCalc addresses scientific, communication, and educational gaps between global- and local-scale FEW research communities and local stakeholders, affected by food, energy, water systems and their interactions by relating near-term choices to near- and long-term consequences. This analysis is needed to craft a more advantageous future.

The effects of climate change on agricultural profitability depend not just on changes in production, but also on how farming systems are adapted to suit the new climatic conditions. We investigated the interaction between production changes, adaptation and farm profits for a mixed livestock–cropping farming system in the Western Australian Wheatbelt. Crop and pasture production was simulated for a range of plausible rainfall, temperature and CO2 concentrations for 2030 and 2050. We incorporated the results of these simulations into a whole-farm bio-economic optimisation model. Across a range of climate scenarios, the impact on farm profit varied between − 103% and + 56% of current profitability in 2030, and − 181% and + 76% for 2050. In the majority of scenarios profitability decreased, and the magnitude of impacts in negative scenarios was greater than the upside in positive scenarios. Profit margins were much more sensitive to climate change than production levels (e.g., yields). Adaptive changes to farm production under extreme climate scenarios included reductions in crop inputs and animal numbers and, to a lesser extent, land-use change. The whole-farm benefits of these adaptations were up to $176,000/year, demonstrating that estimating the impact of climate change without allowing for adaptation can substantially inflate costs. However, even with adaptation, profit reductions under the more negative scenarios remained large. Nevertheless, except for the most extreme/adverse circumstances, relatively minor increases in yields or prices would be sufficient to counteract the financial impacts of climate change (although if these price and/or productivity increases would also have occurred without climate change then the actual cost of climate change may still be high).

This study assessed the effects of various low-cost climate-smart agricultural (CSA) technologies on farm productivity, farm income and greenhouse gas (GHG) emissions in smallholder farming systems in southern Ethiopia. On-farm trials were conducted at three study sites/districts (Ziway, Halaba and Loka-Abaya) during the 2015 and 2016 cropping seasons. The experiment compared five climate smart treatments against existing recommended practice. Three farms were selected at each site. Each farm hosted one full experimental repetition, thus functioning as an experimental block. The average data of the two seasons were taken from each farm and means were calculated per site and over the study sites as well. The on-farm trails were established to identify a CSA technology that can improve yields and economic returns, while simultaneously reduce GHG emissions at the farm level. Averaged over the three sites, a combined application of seed priming with micro-dosing (0.5 g of fertilizer per pocket) was identified as the best-fit technology in terms of farm productivity and farm income. Results show that this technology increased maize grain yield by up to 45% (compared to the recommended practice). A model CSA farm was then created using this technology which was compared with the performance of the farmers' current system (conventional farm). It generated surplus production of both grain (more than three times higher) and fodder. The CSA farm produced 84% of dry matter fodder (DM) requirements and 60% of livestock crude protein (CP) needs respectively, while the conventional farm produced 30% DM and 48% of CP needs. Furthermore, the CSA farm demonstrated reduced GHG emissions compared to the conventional farm which grows maize without the use of mineral fertilizers. Our estimates indicate that due to the establishment of multipurpose trees on the CSA farm, the total on-farm C stock was about 29 Mg ha−1, that is 24% higher than the conventional farm. In conclusion, we recommend the combined application of seed priming and micro-dosing as a strategy for improving economic returns and an approach to enhance the sustainability of maize-based mixed systems in southern Ethiopia. Planting multipurpose trees will give additional benefits in terms of fodder and carbon sequestration.

The shock of Coronavirus Disease 2019 (COVID-19) has disrupted food systems worldwide. Such disruption, affecting multiple systems interfaces in smallholder agriculture, is unprecedented and needs to be understood from multi-stakeholder perspectives. The multiple loops of causality in the pathways of impact renders the system outcomes unpredictable. Understanding the nature of such unpredictable pathways is critical to identify present and future systems intervention strategies. Our study aims to explore the multiple pathways of present and future impact created by the pandemic and “Amphan” cyclonic storm on smallholder agricultural systems. Also, we anticipate the behaviour of the systems elements under different realistic scenarios of intervention. We explored the severity and multi-faceted impacts of the pandemic on vulnerable smallholder agricultural production systems through in-depth interactions with key players at the micro-level. It provided contextual information, and revealed critical insights to understand the cascading effect of the pandemic and the cyclone on farm households. We employed thematic analysis of in-depth interviews with multiple stakeholders in Sundarbans areas in eastern India, to identify the present and future systems outcomes caused by the pandemic, and later compounded by “Amphan”. The immediate adaptation strategies of the farmers were engaging family labors, exchanging labors with neighbouring farmers, borrowing money from relatives, accessing free food rations, replacing dead livestock, early harvesting, and reclamation of waterbodies. The thematic analysis identified several systems elements, such as harvesting, marketing, labor accessibility, among others, through which the impacts of the pandemic were expressed. Drawing on these outputs, we employed Mental Modeler, a Fuzzy-Logic Cognitive Mapping tool, to develop multi-stakeholder mental models for the smallholder agricultural systems of the region. Analysis of the mental models indicated the centrality of “Kharif” (monsoon) rice production, current farm income, and investment for the next crop cycle to determine the pathways and degree of the dual impact on farm households. Current household expenditure, livestock, and soil fertility were other central elements in the shared mental model. Scenario analysis with multiple stakeholders suggested enhanced market access and current household income, sustained investment in farming, rapid improvement in affected soil, irrigation water and livestock as the most effective strategies to enhance the resilience of farm families during and after the pandemic. This study may help in formulating short and long-term intervention strategies in the post-pandemic communities, and the methodological approach can be used elsewhere to understand perturbed socioecological systems to formulate anticipatory intervention strategies based on collective wisdom of stakeholders., Graphical abstract Unlabelled Image

Farmers' cultivation choices affect the natural cycles of crops and impact their production. By assessing the farming activities, as influenced by crop types, land suitability and cultivation choices, the effectiveness of agricultural practices in terms of environmental impact can be evaluated. The study of the relationships between agriculture, environment and economic performance should be deepened, by considering the connection between agricultural activities and the use of natural resources beyond the economic issues, which are often taken as the unique or, at least, the main goal of human activities. The aim of this paper is to assess and to analyse in a comparative way the environmental and economic results of a crop production system at farm level. The methodology for the evaluation of environmental performance is based on a modified version of the Ecological Footprint account, used to measure the demand for natural resources linked to the farm's operations, which is compared with the Biocapacity of the crop system itself. The economic performances are assessed by means of crops' analytical budgets. The results provided by the case study analysis show that the considered farm cropping system reports an overall positive ecological balance (+ 2.4 gha) together with an acceptable gross margin (16,200 €). It emerges that crops with negative environmental performances sustain farm income, while the crops with a positive ecological balance bring a very limited contribution to economic profitability. Such results lead to some considerations about the importance of carefully considering the trade-off between economic and environmental consequences of farming activities in order to drive farmers towards a more sustainable behaviour.

This study explores the influences of agricultural systems on a social aspect of farming, namely work satisfaction. We use an individual activity choice model and hypothesize that different systems yield different levels of satisfaction with farming. Farmers of northeast (NE) Germany and Switzerland were surveyed with a joint questionnaire, as these study regions differ widely in terms of farm size and thus in economies of scale. Regression analysis was done in two separate models including different proxies for farm income, namely farm size (n = 1137) and perceived financial situation of the farm (n = 1158). The results show that in the large-scale industrialized agricultural system of NE Germany, farmers' work satisfaction is positively affected by both farm income proxies. Both of these elements have a significantly different effect on the work satisfaction of Swiss farmers. Their work satisfaction is not affected by farm size and the positive effect of the perceived financial situation of the farm is significantly less strong for Swiss farmers than for German ones. Thus, monetary return seems to play a major role in utility of farming for NE German farmers, whereas it is less important for Swiss ones. Additionally, the Swiss agricultural system seems to offer qualities besides economic returns for its farmers as they are generally more satisfied with their work despite the lower economic return compared with NE German farmers.

Agricultural water interventions (AWI), e.g. in-situ soil and water conservation strategies, irrigation, and damming of rivers to increase groundwater recharge, have been suggested as important strategies to improve yields in tropical agriculture. Although the biophysical implications of AWIs have been well investigated, the coupling between the biophysical changes and the economic implications thereof is less well understood. In this study we translate the results from a hydrological model, SWAT, on crop yields for different cropping systems with and without agricultural water interventions, to hypothetical farm incomes for a watershed, Kothapally, located in Andhra Pradesh, India. It was found that on average, AWI significantly improved farm incomes by enabling the cultivation of a high value crop during the monsoon season (cotton), supplementary irrigated to bridge dry spells and replacing a traditional crop (sorghum), and also by enhancing the capacity to produce dry season, fully irrigated vegetable crops, in this case exemplified by onion. AWI combined with cotton resulted in more than a doubling of farm incomes compared to traditional sorghum-based systems without AWI during normal and wet years (i.e. for 75% of the years). Interestingly, we observed that the difference between the AWI system and the no intervention system was larger during years of high average rainfall compared to dry years. It was also found that access to irrigation was more important for farm income than crop choice and AWI per se, and thus farms with access irrigation benefitted more from AWI compared to farmers lacking access to irrigation. In conclusion, we suggest that in order to assess equity aspects in terms of farm income generation following the implementation of an AWI project, there is a need for income analyses at the farm level, since income estimates at the watershed level may mask important differences in economic benefits between farms.

Over 22 million hectares (ha) of U.S. croplands are irrigated. Irrigation is an intensified agricultural land use that increases crop yields and the practice affects water and energy cycles at, above, and below the land surface. Until recently, there has been a scarcity of geospatially detailed information about irrigation that is comprehensive, consistent, and timely to support studies tying agricultural land use change to aquifer water use and other factors. This study shows evidence for a recent overall net expansion of 522 thousand ha across the U.S. (2.33%) and 519 thousand ha (8.7%) in irrigated cropped area across the High Plains Aquifer (HPA) from 2002 to 2007. In fact, over 97% of the net national expansion in irrigated agriculture overlays the HPA. We employed a modeling approach implemented at two time intervals (2002 and 2007) for mapping irrigated agriculture across the conterminous U.S. (CONUS). We utilized U.S. Department of Agriculture (USDA) county statistics, satellite imagery, and a national land cover map in the model. The model output, called the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the U.S. (MIrAD-US), was then used to reveal relatively detailed spatial patterns of irrigation change across the nation and the HPA. Causes for the irrigation increase in the HPA are complex, but factors include crop commodity price increases, the corn ethanol industry, and government policies related to water use. Impacts of more irrigation may include shifts in local and regional climate, further groundwater depletion, and increasing crop yields and farm income.

A Swiss popular initiative reflecting large public concerns about the negative environmental impacts of agricultural production launched a proposal to rigorously tighten environmental cross-compliance standards. The so-called drinking water initiative (DWI) proposes restricting direct payments to farms that (1) preserve biodiversity, (2) do not use any pesticides, (3) adapt their livestock to their on-farm feed capacity and (4) do not use antibiotics regularly or prophylactically. Based on the recursive-dynamic, agent-based agricultural sector model SWISSland, we assessed, ex-ante, the impacts of the initiative on environmental and economic indicators at the farm- and sector-level. Stakeholders from both groups, supporters and opponents of the initiative, were involved in the assessment. We found that the incorporation of far more stringent environmental standards into the cross-compliance system caused a larger number of farms to opt-out: For 33–63% of the pork and poultry farms and 51–93% of the vegetable/orchards/winery farms, it was more profitable to forego direct payments. However, the majority of the ruminant farms (87%) were expected to comply with the standards. Although the non-complying farm types were associated with the most severe environmental impacts, we found that the initiative nonetheless had positive effects on water quality at the sectoral level in Switzerland: e.g., the share of pesticide-free arable land increased to 70–92%, those of the permanent cropland to 11–52%, and the nitrogen surplus decreased. However, the total agricultural production measured in calories decreased (12–21%), and therefore agricultural imports would increase. If the current direct payment budget goes completely to the complying farms, and if these farms receive a price premium, then we predict an average farm income increase of 2–34% for the complying farms; otherwise, a decrease of 6–22% will be found depending on the scenario. A sensitivity analysis showed that price uncertainties had the highest impact on farm income.

A local chicken farming is an integral part of Tanzania's rural economy. However, despite its contributions to household economy and food security, local chicken productivity remains low because of low genetic potential, diseases and poor feeding. One of the options to increase local chicken productivity is the adoption of the chicken strains with high genetic potential. With that respect, Africa Genetic Gain project introduced Sasso and Kuroiler chicken strains for on-farm test purposes. Developmental design involved provision of 25 six weeks old chicks to 20 farmers in 12 sites making a total of 240 farmers in three regions. The study was carried out in Dodoma, Morogoro and Njombe regions to assess the effects of agro-ecological differences in the performance of these strains. The chicks were vaccinated against Mareks and Newcastle diseases at the hatchery; then against Infectious Bronchitis (IB) at 0, 7 10, 16 and 21 days. The Newcastle Disease vaccine was repeated after 10 and 21 days using LaSota vaccine. After 6 weeks, the chicks were again vaccinated against fowl pox ready for supply to farmers. A farm Simulation Model (FARMSIM) and Stochastic Efficiency with Respect to Function (SERF) were applied to access economic viability of these strains relative to local chickens. FARMSIM is a Monte Carlo Simulation Model that simultaneously evaluates a baseline and an alternative farming technology. To simulate using FARMSIM, Simulation and Econometrics to Analyse Risk (Simetar©), an excel add-in is needed as a simulating engine. Data were obtained through survey, farmers' records and simulation exercises. The results indicate that keeping Sasso strain was the most economically viable with the highest Net Present Value, Net Cash Farm Income and the highest probability of attaining economic return. Kuroiler was the second, followed by keeping local chickens without supplement and local chicken with supplement was the least economically viable enterprise. However, inclusion of risk behaviour revealed that extremely risk-averse farmers preferred mostly keeping local chickens without supplement whereas extremely risk loving farmers preferred the most Sasso strain. It is recommended that the introduced chicken strains should be promoted to increase household income and improve people's livelihoods. However, scaling up of the introduced chicken strains must be integrated with education on technical know-how for good farming practices, feed formulations, medication and shelter for improved productivity and reduced variability.

This study aims at assessing the determinants of the agricultural productivity through the partial productivities of the main production factors (land, labor and capital), using primary data collected from a sample of 210 farmers randomly selected in two villages belonging to the municipality of Banikoara in Northern Benin (West Africa). The partial land, labor and capital productivities are 163643.90 francs CFA/ha, 1716.92 francs CFA/Man.Day, and 2.48 respectively, implying that land is the most productive factor. The seemingly unrelated regression model is highly significant at 1% and revealed factors such as the household head gender, experience in agriculture, off – farm income employment; the household size; the sizes of land under maize, sorghum, and cotton cultivation; the household’s capital; and the maize fertilisation as determinants of the partial land productivity. The partial labor productivity is influenced by the household head gender, his experience in agriculture, an off – farm income employment, the household size, the sizes of land under rice and cotton cultivation, the household’s capital, and the access to credit whereas the household size, the land size under cotton cultivation, and the household’s capital affect the partial capital productivity. These factors need to be taken into account by policy to design agricultural projects that aim to improve agricultural productivity. The land size to be allocated to different crops has to be at the centre of agricultural policy as it has influenced all partial agricultural productivities.

Eastern Germany is often hit by drought causing income risk for crop farmers. Index-based risk management instruments could help crop farmers to reduce their farm income risk. Such instruments have some important advantages over damage-based insurance, like e.g. less moral hazard and adverse selection. At the same time they typically have a high level of basis risk. Up to now, mainly precipitation-based weather derivatives have been discussed as an appropriate risk management instrument for farmers in Germany. As a potentially more effective alternative, we propose water capacity-based index insurance. In order to show the benefits of a precipitation-based and water capacity-based index insurance, several contract designs are compared. Using a whole farm risk program planning approach, we show that for an average agricultural producer in Eastern Germany water capacity-based index insurance offers greater benefits than precipitation-based index insurance.

We present an integrated spatially explicit land use modeling framework, which integrates two key components of agricultural systems, the bio-physical production system and the management system, by coupling the bio-economic farm optimization model FAMOS[space], the crop rotation model CropRota, and the bio-physical process model EPIC (Environmental Policy Integrated Climate). The integrated modeling framework has been developed to analyze the cost-effectiveness of selected agri-environmental program (AEP) measures. We also focus on the landscape development and therefore include a detailed representation of landscape elements such as fields or orchard meadows in our analysis. An indicator set represents all main environmental AEP objectives, i.e. preservation of water and soil resources, mitigation of climate change, protection of biodiversity, maintenance of cultural landscapes as well as farm income support. The integrated modeling framework is applied to 20 farms in the Austrian ‘Mostviertel’ region, which are selected from the Integrated Administration and Control System (IACS) of the European Union. The cost-effectiveness of AEP measures is assessed under different premium levels. The implementation of the AEP clearly affects environmental quality in a positive way. Nitrogen rates are reduced, landscape elements can be sustained, and the landscape becomes more diverse. The program also increases farm gross margins on average. However, the cost-effectiveness ratios (CER) are declining with increasing premium levels. The results indicate that the cost-effectiveness of AEP measures can be improved by spatial targeting.

In a WTO battle and the press the argument is often made that eliminating US cotton subsidies would have a large effect on the incomes and competitive position of farmers in developing countries. In Francophone West Africa cotton productivity has stagnated after rapid gains in the first two decades following independence (1960–1980). A farm model was constructed based on farmers’ definition of their decisionmaking framework which they use to respond to income and weather risks. With this model the effects on farmers of eliminating US subsidies are compared with various productivity increasing measures for cotton and sorghum in Dioila, Mali. Dioila is located in a representative cotton region producing 16% of the cotton in Mali. We include sorghum due to its importance for consumption and the observation of Malian farmers substituting cereals (sorghum and maize) for cotton as the returns to cotton have fallen in the 21st Century. In the farm model, the elasticity of transmission of a change in the world cotton price to the farm gate price is taken into account. The gains from eliminating US subsides are small. In contrast, the various technological alternatives including Bt cotton introduction, the use of higher fertilization levels for cotton, and the introduction of improved sorghum cultivars and moderate fertilization along with a marketing package all have substantially higher returns Even with substantial improvement in the mechanisms enabling farmers to benefit from the higher prices resulting from elimination of US subsidies, there are still much higher returns resulting from the various types of productivity increases. Published by Elsevier Ltd.

Technological interventions to address the problem of poor productivity of smallholder agricultural systems must be designed to target socially diverse and spatially heterogeneous farms and farming systems. This paper proposes a categorisation of household diversity based on a functional typology of livelihood strategies, and analyses the influence of such diversity on current soil fertility status and spatial variability on a sample of 250 randomly selected farms from six districts of Kenya and Uganda. In spite of the agro-ecological and socio-economic diversity observed across the region (e.g. 4 months year_1 of food self-sufficiency in Vihiga, Kenya vs. 10 in Tororo, Uganda) consistent patterns of variability were also observed. For example, all the households with less than 3 months year_1 of food self-sufficiency had a land:labour ratio (LLR) < 1, and all those with LLR > 1 produced enough food to cover their diet for at least 5 months. Households with LLR < 1 were also those who generated more than 50% of their total income outside the farm. Dependence on off/non-farm income was one of the main factors associated with household diversity. Based on indicators of resource endowment and income strategies and using principal component analysis, farmers' rankings and cluster analysis the 250 households surveyed were grouped into five farm types: (1) Farms that rely mainly on permanent off-farm employment (from 10 to 28% of the farmers interviewed, according to site); (2) larger, wealthier farms growing cash crops (8-20%); (3) medium resource endowment, food self-sufficient farms (20-38%); (4) medium to low resource endowment relying partly on non-farm activities (18-30%); and (5) poor households with family members employed locally as agricultural labourers by wealthier farmers (13-25%). Due to differential soil management over long periods of time, and to ample diversity in resource endowments (land, livestock, labour) and access to cash, the five farm types exhibited different soil carbon and nutrient stocks (e.g. Type 2 farms had average C, N, P and K stocks that were 2-3 times larger than for Types 4 or 5). In general, soil spatial variability was larger in farms (and sites) with poorer soils and smaller in farms owning livestock. The five farm types identified may be seen as domains to target technological innovations and/or development efforts.

We model the contractual arrangements between smallholder pepper (Piper nigrum L.) producers and a single processor in Costa Rica. Producers in the El Roble settlement sell their pepper to only one processing firm, which exerts its monopsonistic bargaining power by setting the purchase price of fresh pepper. It also sets quality norms that result in the rejection of considerable amounts of the pepper produced by individual farmers. Because the firm is not able to produce its own raw pepper and requires a sufficiently stable flow of the fresh product to be processed into high quality white pepper, it usually relies on contracts with individual smallholders. Nevertheless, the latter considered collective marketing and took the initiative to propose a group contract with the firm. Such a contract increases the producers’ bargaining power vis-à-vis the processing firm and reduces rejection rates as more care is taken when transporting the pepper to be processed. Although a group contract causes the firm to lose part of its monopsonistic rents, it also reduces transaction costs as only one contract must be negotiated instead of many. Both the firm and the producers benefit, yet from the very beginning of the association, the producers breached the group contract. We have used a mixed integer linear model which, given a set of constraints, maximises the weighted sum of the expected incomes of the firm and producers. We modelled the contract chosen by the firm and the producers according to the conditions included, such as minimum income requirements and risk considerations of both processor and farmers. We calibrated the model with data from pepper producers and the firm in El Roble. The results show that at different fresh pepper prices, the contract preferred changes with the bargaining power attributed to the firm and smallholders. However, in general, it can be concluded that fresh pepper prices high enough to cover the costs, for the farmers, of a group contract lead to lower rejection rates, and thus to more pepper of an acceptable quality, increasing the incomes of both the processor and the farmers. This is also of interest in agricultural policymaking. Modelamos los arreglos contractuales entre pequeños productores de pimiento (Piper nigrum L.) y un procesador único en Costa Rica. Los productores del asentamiento El Roble venden su pimiento a una sola empresa procesadora, la cual ejerce su poder de negociación monopsónico al fijar el precio de compra del pimiento fresco. También establece normas de calidad que resultan en el rechazo de cantidades considerables de la pimienta producida por agricultores individuales. Debido a que la empresa no puede producir su propia pimienta cruda y requiere una cantidad suficiente flujo estable del producto fresco para ser procesado en pimienta blanca de alta calidad, por lo general se basa en contratos con pequeños agricultores individuales. Sin embargo, este último consideró el marketing colectivo y tomó la iniciativa para proponer un contrato de grupo con la firma. Tal contrato aumenta la negociación de los productores. poder frente a la empresa de procesamiento y reduce las tasas de rechazo ya que se tiene más cuidado al transportar el pimiento a procesar. Aunque un contrato de grupo hace que la empresa pierda parte de su capacidad monopsónica rentas, también reduce los costos de transacción ya que solo se debe negociar un contrato en lugar de muchos. Ambos empresa y los productores se benefician, sin embargo, desde el comienzo mismo de la asociación, los productores incumplieron el contrato de grupo. Hemos utilizado un modelo lineal entero mixto que, dado un conjunto de restricciones, maximiza la suma ponderada de los ingresos esperados de la empresa y los productores. Modelamos el contrato elegido por la empresa y los productores de acuerdo con las condiciones incluidas, como ingresos mínimos requisitos y consideraciones de riesgo tanto del procesador como de los agricultores. Calibramos el modelo con datos de productores de pimiento y la firma de El Roble. Los resultados muestran que a diferentes precios de pimiento fresco, la cambios preferidos en el contrato con el poder de negociación atribuido a la empresa y a los pequeños propietarios. Sin embargo, En general, se puede concluir que los precios de la pimienta fresca son lo suficientemente altos para cubrir los costos, para los agricultores, de un contrato de grupo conduce a tasas de rechazo más bajas y, por lo tanto, a más pimienta de una calidad aceptable, lo que aumenta los ingresos tanto del procesador como de los agricultores. Esto también es de interés en la formulación de políticas agrícolas. Universidad Nacional, Costa Rica Centro Internacional de Política Económica para el Desarrollo Sostenible

International audience; The environmental and economic performance of five Charolais beef production systems (three specialized beef producer test cases in grassland areas and two mixed crop-livestock test cases with a more intensive production system) were assessed by coupling an economic optimization model ("Opt'INRA") with a model assessing non-renewable energy (NRE) consumption and greenhouse gas emissions ("PLANETE"). The test cases studied covered a relatively diverse range of raised and sold animals: calf-to-weanling or calf-to-beef systems (animals sold: from 10-month-old weaners to 36-month-old beef steers). In 2006, NRE consumption ranged from 26,440 to 31,863 MJ/ton of live weight produced over I year. Fuels and lubricants were the main factors of NRE consumption, followed by fertilizers and farm equipment. Livestock was the main driver of global warming potential. GHG emissions, at 14.3-18.3 tCO(2)eq/t LW, were mainly determined by the proportion of cows in the total herd livestock units, according to the farming system deployed, i.e. calf-to-weanling vs. calf-to-beef. Against a background of rising energy costs, farms running mixed crop-livestock systems enjoy greater flexibility to adjust their farming systems than grassland-based farms, enabling them to minimize the drop in income over the timeframe to 2012 (-3%). In this same setting, specialist beef producers face a 15-25% drop in income. In all the scenarios run, system adjustments designed to minimize the drop in income have only a very limited impact on NRE consumption and GHG emissions. (C) 2009 Elsevier Ltd. All rights reserved.

In four communities in the Peruvian Andes, 56 farmers were interviewed every three months over a period of one year. Information linked to milk and cattle production such as activities, inputs (labour, means of production, capital) and outputs (milk, cheese, animals) were recorded using a closed-ended questionnaire. The communities were divided into two groups with low (LC) and high (HC) level of dependence on income from milk and animal sales. The survey results showed that cattle production on the LC farms was based on less land and a smaller herd (3.32 ha/farm, 1.06 lactating cows) than on HC farms (10.28 ha/farm, 4.19 lactating cows). The data from the survey and the results of the nutritional analyses of 74 feed samples were introduced into a model that applied linear programming techniques in order to estimate the farm household income under the current production systems and evaluate the economic impact of improved forage varieties for hay production. Furthermore, the economic viability of other changes in fodder and herd management was tested. Both groups were characterised by a dual-purpose system generating a gross income from the sale of both, milk and live animals in the amount of -21 (LC) and +1057 US$/farm and year (HC). Due to higher production costs for forages and better access to markets, LC communities were characterised by an integrated crop–livestock system whereas in the HC group income was mainly based on livestock. Introduction of improved and fertilized barley for hay production, was estimated to increase the annual farm income to 127 and 1257 US$ for LC and HC, respectively. This increase was accompanied by an increment of the animal number. Maintaining the animal number but increasing the milk production/cow by feeding additional forage was a less profitable option generating 50 and 1221 US$ of income per farm and year for LC and HC, respectively. The production of hay was limited by high costs (external labour) in LC communities and the restricted availability of family labour in the HC group. A scenario based on the use of improved cow genotypes led to the highest estimated annual farm income for HC communities (1280 US$) but was less favourable for LC. The modelling results showed that the best development strategy depends on various factors such as production costs, access to the markets and to irrigation and availability of different feed resources.

In most parts of the world, pastoral societies are governed by internal rules or legal bodies and legal rules (institutions) at the regional and national scale. In the Large Scale Grazing Systems (LSGS) of the European Union (EU), institutional management is also dependent on EU regulations, which underpin a considerable part of total policy support. In this research we argue that the effectiveness of policy intervention should be determined “on the ground” and taking into account the structural and social features of particular LSGS. Under a community-based research approach, the main stakeholders (arable farmers and landless pastoralists) and organisations governing the cereal–sheep farming system in Castilla-La Mancha (South-Central Spain) were consulted with the aim of assessing the sustainability of the mixed cereal and sheep system. In this area, sheep farming is a secondary land use relying on the agricultural residues from arable farming, but representing some 35% of the total value of production farming per land unit. Our results showed that regional and EU regulations are uncoordinated and uncongenial for the continuity of the mixed cereal and sheep operation. They are supported by separate policy schemes, while operating on the same land units. Arable farming is more affected by EU regulations and corresponding policy support schemes, while sheep farming is more regulated by regional institutions. EU support was 32% and 13% of total farm income for cereal and sheep farmers, respectively. Arable farmers received a regulated non-market grazing fee. They abide by the law, but have no incentive to facilitate the sheep subsystem. The farming practices of sheep farmers are more market-driven as the value of production makes up the bulk of their total income. However, they are squeezed by strict regional regulations when implementing pastoral surviving strategies (mobility, accessibility, and diversity of land based resources). Both subsystems are following disconnected trends, with increasing cultivation intensity in arable farming and the abandonment of shepherding and a consequent consolidation of sheep flocks and an increase in indoor feeding. This research suggests that sensible institutional management should be derived from a proper knowledge of the social and structural features of particular grazing systems and the disentangling of their main constraints.

In African smallholder agriculture, improved farm-scale understanding of the interaction between the household, crops, soils and livestock is required to develop appropriate strategies for improving productivity. A combination of models was used to analyse land use and labour allocation strategies for optimizing income for wealthy (2.5 ha with eight cattle) and poor (0.9 ha without cattle) farms in Murewa, Zimbabwe. Trade-offs between profitability, labour use and partial nutrient balances were also evaluated for alternative resource management strategies. Farm data were captured using the Integrated Modelling Platform for Mixed Animal-Crop Systems (IMPACT), which was directly linked to the Household Resource use Optimization Model (HROM). HROM was applied to optimize net cash income within the constraints specific to the households. Effects of alternative nutrient resource management strategies in crop and milk production were simulated using the Agricultural Production Systems Simulator (APSIM) and RUMINANT models, respectively, and the output evaluated using HROM. The poor farm had a net income of US$ 1 yr−1 and the farmer relied on selling unskilled labour to supplement her income. The poor farm’s income was marginally increased by US$18 yr−1 and the soil nitrogen (N) balance was increased from 6 to 9 kg ha−1 yr−1 by expanding groundnut production from the previous 5–25% of the land area. Further increases in area allocated to groundnut production were constrained by lack of labour. On the poor farm, maize production was most profitable when cultivated on a reduced land area with optimal weeding. The wealthy farm had a maize-dominated cropping system that yielded a net cash balance of US$290 yr−1, mainly from the sale of crop produce. Net income could be increased to US$1175 yr−1, by re-allocating the 240 hired labour-days more efficiently, although this reallocation substantially reduced partial soil N and phosphorus (P) balances by 74 kg N ha−1 and 11 kg P ha−1, respectively, resulting in negative nutrient balances. Few opportunities existed to increase productivity and income of the smallholder farms without inducing negative nutrient balances. On the wealthy farm, groundnut was the least profitable crop; shifting its production to the most fertile field did not improve income unless the groundnut residues were fed to lactating cows. The analysis carried out in this paper highlights the need to develop practical technological recommendations and development interventions that consider farm resource endowment (land, fertilizers, manure and labour), variability in soil fertility within farms and competing resource use options.

In South Patagonia, Argentina, sweet cherry is the main fruit-tree crop grown for export, resulting in a highly seasonal labour demand. Managers of deciduous perennial fruit orchards must consider both biological and economic relationships in selecting crop species and orchard design. This makes decisions at the farm-level extremely complex, as especially in such perennial crops, strategic (`what to plant¿, `with which technology¿ and `how much area of each activity¿, i.e. the final design) and tactical (`when, what and how to plant in time¿, the pathway to the planned farm) decisions have a long-term effect. The objective of this study was to explore the consequences of different strategic and tactical decisions at farm scale in fruit production systems of South Patagonia, considering the variation in interests and aims of different stakeholders, and using a sensitivity analysis to evaluate the consequences of possible changes in external conditions. A dynamic farm-scale optimization model called OPTIFROP was developed to generate alternative farm development plans, by allocating, in the course of the time horizon of the run, production activities to different land units, while optimising different objective functions, subject to several constraints. Although time-dependent, dynamic, mathematical programming models for analysing farming systems have been described in literature, the dynamic aspects of long-term decision-making in orchard design and their impact on the sequential (annual) nature of orchards in different growth phases (i.e. medium-term decision-making), need a higher time-staged dynamic approach with a staircase matrix structure. The model includes two objective functions at farm level: (1) maximization of the present value of cumulative financial result, which is the main objective for growers, and (2) maximization of cumulative farm labour, which is an objective often mentioned by policy makers. The inter-months deviation for labour demand (during the period of high labour demand, November¿April) was included as an upper-bound. Input and output coefficients for the land use options considered in OPTIFROP were quantified using the Technical Coefficient Generator FRUPAT. Model results indicated that the present value of cumulative financial result and the cumulative farm labour are conflicting to a very limited extent. Timing and feasibility of implementing certain combinations of production technologies are affected by resource endowments and initial conditions, but these factors do not influence land use selection in the long term. Land use selection is driven by the objectives of the stakeholders. OPTIFROP showed that, through introduction of alternative crops, substantial reductions in labour peaks in the period November¿April could be achieved with a relatively small reduction in farm income. The sensitivity of the model solution to the cherry price suggests that the fruit production sector of South Patagonia should pay more attention to the robustness of their land use plans and take preventive measures to avoid being caught by a possible crisis due to changes in the context.

Reducing fallow periods with sown leguminous plants (i.e., Callopogonium mucunoides) was found to be a technically feasible, low-input method of improving soil nutrient levels for rice cropping in the Guinea and Sudan savannah regions of northern Ghana. However, farmers and policy makers are particularly interested in understanding whether the new rice production technology can be substituted for the traditional rice cropping systems within a whole-farm plan context and, if so, what are the likely resource allocation and financial implications to farmers. An optimal whole-farm plan that incorporates traditional (bush fallow) cropping of rice, jointly with livestock production was generated using a linear programming model, and then used to assess the economic implications of introducing the improved fallow (i.e., incorporating Callopogonium mucunoides) rice cropping system. The alternative combinations of enterprises investigated needed to be economically viable household farm units, as well as meet household food security requirements of such resource poor farmers. Introducing the new rice production technology into a base whole-farm model (i.e., under traditional rice cropping) increased rice area by 45%, and farm income above variable costs by 34%. In addition, the representative farm raises six beef cows and 72 poultry birds. In sensitivity analyses of alternative model scenarios, farm incomes were higher and more stable for farming systems using the new rice cropping technology than with the traditional whole-farm model. More widespread adoption of the new rice-based production technology will help transform existing traditional subsistence farming systems to more profitable commercial production systems. This transformation will have implications for farm structure (in terms of consolidation of highly fragmented holdings), agricultural resource management, and property rights (such as recognition of individualized rights to cropland, livestock grazing land and agricultural water resources).

Family composition and its changes over time are believed to have a major impact on the welfare and sustainability of small-scale, limited resource farm households. In order to understand and test the effects of household composition on overall farm household well-being, a simulation model was developed based on information from 60 small farms from the Coastal Canete Valley, Peru. The model accounts dynamically for the birth, age and death of household members and for crop, livestock, and economic activities. A representative farm with ten scenarios representing the range of household composition was simulated. Results in 10, 20 and 40-year runs showed that family composition has a large influence on economic stress. Families with fewer members were economically better off after 10, 20, and even 40 years. With more young or very old members, the expenses and consumption requirements exceeded the benefits from the additional labor, and debt was greater and of longer duration. Changing prices and yields across their observed ranged of variability influenced simulated financial position, but not the ranking of results among household composition scenarios.

Soil nutrient depletion in Uganda is one of the leading environmental degradation problems threatening the livelihoods of most farmers in the region. In order to identify policy options that may be used to address the problem, this study was conducted with an objective of analyzing the determinants of flow and balances of nitrogen (N), Phosphorus (P), and Potassium (K) in Uganda. Data for this study were collected from 58 randomly selected farmers who participated in on-farm fertilizer trials and household surveys conducted in 2000 to 2001. Econometric models were used to analyze the determinants of soil nutrient flows and balances. Only 5% of the sample households had positive total NPK balances implying 95% of the farmers likely used unsustainable land management practices in the 2000/2001 season. If inorganic fertilizer were used to restore the mined nutrients, it would cost an equivalent of a fifth of the farm income. The results confirm the heavy reliance of smallholder farmers to soil fertility mining for their livelihoods. Agricultural potential, size of livestock herd, crop diversity, education, and having non-farm activities improve soil nutrient balances. This implies farmers need to be encouraged to grow crops and keep livestock in order to utilize the crop-livestock synergies. Education and non-farm activities in rural areas also need to be promoted as they contribute to more sustainable land management practices. Contact with extension agents initially accelerates soil nutrient depletion probably due to tendency of farmers to first adopt improved crop varieties without using fertilizer. Hence there is need for extension messages to emphasize adoption of both soil fertility and seed technologies. Farmers in high market access appear to deplete their soils more rapidly, pointing to the need to design policy mechanisms that would reduce soil nutrient depletion in high market access areas.

Rapid changes in the social and economic environment in which agriculture is developing, together with the deterioration of the natural resource base threatens sustainability of farm systems in many areas of the world. For vegetable farms in South Uruguay, survival in the long term depends upon the development of production systems able to reduce soil erosion, maintain or improve physical and biological soil fertility, and increase farmer's income to socially acceptable levels. We propose a model-based explorative land use study to support the re-orientation of vegetable production systems in South Uruguay. In this paper we present a new method to quantitatively integrate agricultural, environmental and socio-economic aspects of agricultural land use based on explicit design objectives. We describe the method followed to design and evaluate a wide variety of land use activities for Canelon Grande (South Uruguay) and we illustrate the usefulness of this approach in an ex-ante evaluation of new farming systems using data from 25 farms in this region. Land use activities resulted from systematic combination of crops and inter-crop activities into crop rotations, different crop management techniques (i.e., mechanisation, irrigation and crop protection) and animal production. We identified and quantified all possible rotations and estimated inputs and outputs at crop rotation scale, explicitly considering interactions among crops. Relevant inputs and outputs (i.e., soil erosion, balance of soil organic matter and nutrients, environmental impact of pesticides, labour and machinery requirements, and economic performance) of each land use activity were quantified using different quantitative methods and following the target-oriented approach. By applying the methodology presented in this paper we were able to design and evaluate 336,128 land use activities suitable for the different soil types in Canelon Grande and for farms with different availability of resources, i.e., land, labour, soil quality, capital and water for irrigation. After theoretical evaluation, a large subset of these land use activities showed promise for reducing soil erosion, maintaining soil organic matter content of the soil and increasing farmer's income, allowing improvement of current farming systems in the region and providing a widely diverse set of strategic options for farmers in the region to choose from. This method can be used as a stand-alone tool to explore options at the field and farm scale or to generate input for optimisation models to explore options at the farm or regional scale. (C) 2003 Elsevier Ltd. All rights reserved.

This paper locates impact assessment research within the disciplinary constructs of agricultural economics, the institutions (rules of the game) and organizations (structures governed by these rules/norms) of agricultural innovation. The paper analyses the disciplinary limitations in impact assessment research. In the hard science culture of agricultural research the social sciences, closer to the reality of complex technological contexts, are less prestigious. Agricultural economics, the disciplinary root of impact assessment, imposes a major constraint by making institutional contexts and variations intractable and analysed at best as disturbances. Sophisticated econometric methodologies substitute for information on institutions, systems components and relationships. The paper presents an analytical framework to distinguish between the institutional and organizational variables in the agricultural innovation system. The case study of institutional and organizational change in Indian agricultural research and extension is used to demonstrate the role of institutions in determining the impact of agricultural science and technology. Impact assessment research is institutionally conditioned to look for end point consequences of research, such as yield increase, cost reduction, or farm income. This body of knowledge ignores crucial requirements such as the institutional framework (hierarchy for instance) and actors that facilitate these end point impacts. Mainstream impact assessment literature is not concerned about the important relationships among these institutions and actors, or about the impact of knowledge on these institutions and organizations. In the quest for end point consequences, estimated often as rates of return to investment, impact assessment has overlooked important requirements and relationships within agricultural innovation systems. An analysis of institutional learning using the key elements of an evaluation culture as proposed by program evaluators is used to demonstrate the need for impact assessment to engage with institutional questions and build the capacity for institutional learning. There is a felt need to move from impact assessment to a larger evaluation culture. Agricultural research evaluation has much to learn from regular program evaluation. This calls for more social science research besides neoclassical agricultural economics, and active interaction among the natural and social scientists, extensionists, farming communities, policy makers and other actors. Effective evaluation in general and impact assessment in particular depends on the institutional learning capacity of the actors, especially scientists and policy makers.

In the search for Integrated Nutrient Management practices in response to the widely observed soil fertility decline in Sub-Saharan Africa, the potential of low-external-input and organic farming remains to be systematically examined. The nutrient monitoring concept was used to assess the impact of technologies on nutrient flows and economic performance at activity and farm household level in Machakos district, Kenya. The nutrient flows and balances and economic performance indicators of farms practising low-external input agriculture (LEIA) technologies for a number of years were compared with a group of farms practising conventional farm management. Based upon monitoring two farming seasons, it was concluded that both subsistence-oriented farm management systems result in serious N-depletion and that 60–80% of farm income is based upon nutrient mining. No significant differences could be found between the LEIA and conventional farm management group. Only if LEIA farm management reduces nutrient losses through leaching and gaseous losses can a positive impact on nutrient balance be expected. Off-farm income plays a crucial role, especially in the conventional management group, in keeping farm household income levels above the poverty line. High-level compost application treatments in maize are attractive if labour and organic inputs are available.

In the Savannah region of West Africa, the highly variable rainfall and poor soils have been shown to differentially affect the yield potential of various crops. The paper applies a simple risk programming model to assess the effects of price and yield risk on the incomes of smallholder farmers in northern region of Cote d'Ivoire. The analysis showed that by considering price and yield risks, it would be possible for farmers to improve their incomes. Considerable evidence has been gathered to show that smallholder allocative inefficiency is a common place in Cote d'Ivoire. This study also found that farmers were operating at sub-optimal levels. This could be due to several factors, including multiple market failures, lack of information on prices, price and yield risks, labor market search costs or high transaction costs. The results from this paper suggests that when such price series information on the risks of different crops are considered, farmers would be better off re-allocating their cropping to a more optimal cropping plan. In evaluating cropping systems in the Savanna zone it is important to consider not only the yield of alternative crops, but also the yield risk, price risk, and income risk that farmers face in adjusting their cropping patterns. Second, to reduce production risks faced by farmers, emphasis should be placed on yield-stability of technology interventions intended for farmers in this zone. Lastly, policy makers should focus efforts on achieving farm income stabilization for farmers in this zone by: (1) developing effective market price information transmission system; (2) providing low-cost but high-resolution climatic information; and (3) developing risk-management institutions. Unless policy makers improve the availability of information that allows farmers to improve their managerial capacity for making more risk-efficient cropping decisions, it is unlikely that farmers in the zone will be able to cope with the pervasive risks that affect their welfare and livelihoods.

Irrigated agriculture has been analysed in Spain in recent years because of its high water consumption and its apparent ineAciency. Several possibilities for water policy have been debated, in particular the pricing of irrigation water. This paper aims to contribute to this discussion by simulating the impact that a policy based upon the price of water could have on agricultural production, analysing the economic, social and environmental implications of such a water policy. This research introduces a methodology for deriving water-demand functions in contexts in which farmers’ behaviour is not explained by the maximisation of gross margin but by a utility function with several conflicting criteria. This methodology utilises a weighted-goal programming approach to estimate a surrogate utility function for the farmer’s decision process; this in turn is used to estimate the value of water demand in irrigated crop production using utility-derived demand functions. The empirical results of this study stress that water pricing as a single instrument for controlling water use is not a satisfactory tool for significantly reducing water consumption in agriculture. The reason for this is that consumption is not reduced significantly until prices reach such a level that farm income and agricultural employment are negatively aAected. The results also show that the estimated water-demand curve is diAerent when a multicriteria utility function rather than the classical profit maximisation hypothesis is employed. # 2000 Elsevier Science Ltd. All rights reserved.