Design Of Farming Systems Research Articles

Agroecology and the design of climate change-resilient farming systems

Diverse, severe, and location-specific impacts on agricultural production are anticipated with climate change. The last IPCC report indicates that the rise of CO2 and associated “greenhouse” gases could lead to a 1.4 to 5.8 °C increase in global surface temperatures, with subsequent consequences on precipitation frequency and amounts. Temperature and water availability remain key factors in determining crop growth and productivity; predicted changes in these factors will lead to reduced crop yields. Climate-induced changes in insect pest, pathogen and weed population dynamics and invasiveness could compound such effects. Undoubtedly, climate- and weather-induced instability will affect levels of and access to food supply, altering social and economic stability and regional competiveness. Adaptation is considered a key factor that will shape the future severity of climate change impacts on food production. Changes that will not radically modify the monoculture nature of dominant agroecosystems may moderate negative impacts temporarily. The biggest and most durable benefits will likely result from more radical agroecological measures that will strengthen the resilience of farmers and rural communities, such as diversification of agroecosytems in the form of polycultures, agroforestry systems, and crop-livestock mixed systems accompanied by organic soil management, water conservation and harvesting, and general enhancement of agrobiodiversity. Traditional farming systems are repositories of a wealth of principles and measures that can help modern agricultural systems become more resilient to climatic extremes. Many of these agroecological strategies that reduce vulnerabilities to climate variability include crop diversification, maintaining local genetic diversity, animal integration, soil organic management, water conservation and harvesting, etc. Understanding the agroecological features that underlie the resilience of traditional agroecosystems is an urgent matter, as they can serve as the foundation for the design of adapted agricultural systems. Observations of agricultural performance after extreme climatic events (hurricanes and droughts) in the last two decades have revealed that resiliency to climate disasters is closely linked to farms with increased levels of biodiversity. Field surveys and results reported in the literature suggest that agroecosystems are more resilient when inserted in a complex landscape matrix, featuring adapted local germplasm deployed in diversified cropping systems managed with organic matter rich soils and water conservation-harvesting techniques. The identification of systems that have withstood climatic events recently or in the past and understanding the agroecological features of such systems that allowed them to resist and/or recover from extreme events is of increased urgency, as the derived resiliency principles and practices that underlie successful farms can be disseminated to thousands of farmers via Campesino a Campesino networks to scale up agroecological practices that enhance the resiliency of agroecosystems. The effective diffusion of agroecological technologies will largely determine how well and how fast farmers adapt to climate change.

Soil improvement and mitigation of greenhouse gas emissions for integrated crop–livestock systems: Case study assessment in the Pantanal savanna highland, Brazil

Greenhouse gas emissions and climate change has been partially attributed to agricultural expansion by deforestation, while the pressure to assure food, fiber and energy for the future generations leads to the intensification of agricultural systems. The transition to more efficient systems is actually considered an important strategy to reduce deforestation and to spare land for other uses, including the recovery of environmental services and ecohydrological processes in the drainage basin such as carbon sink and water regulation. The Brazilian Federal Program for Low Carbon Agriculture (ABC Program) intends to reduce carbon emissions by stimulating technological processes that neutralize emissions or enhance the sinking of greenhouse gases. A pilot farm has been established to assess an intensive animal-plant farming system that incorporates anaerobic digestion for biogas, power generation and organic fertilizer production. Emergy Synthesis was chosen as a methodological tool to assess and to diagnosis the farm system design. The modified emergy assessment including externalities (greenhouse gas emissions) improves the understanding of integrated crop–livestock systems efficiency in internal recycling of nutrients and power conversion. The adoption of manure treatment in intensified agricultural systems can effectively contribute to enhance environmental and economic performances.

ANÁLISIS MULTICRITERIO DEL ESTADO DE LAS PASTURAS DE LA HACIENDA GANADERA GARCÍA ABAJO EN CORINTO (CAUCA, COLOMBIA)

Evaluation of pasture, based on a multicriteria approach, is an important issue for decision making in the design of sustainable farming systems. The aim was to build a state index, based on production and biological indicators of pasture in 50 paddocks of a farm estate Garcia Abajo, located on department of Cauca, Colombia. Nine variables describing

Is low-input management system a good selection environment to screen winter wheat genotypes adapted to organic farming?

The move toward resilient and productive agriculture requires, among other innovations, the design of new sustainable farming systems in which the variety plays a main role. Plant breeding strategies adapted to organic farming conditions have to deal with limiting factors. Whereas in north-west France, it is known that trials carried out under high-input management do not give a good prediction of genotype performance in organic conditions, less is known about the relative stability of wheat genotypes between low-input (LI) and organic cropping systems. A retrospective analysis of 34 winter wheat trials conducted from 2004 to 2011 was performed to determine whether data obtained on genotypes grown under LI conditions can be used to predict genotype performance in organic (ORG) target conditions. Every year, ORG and LI (no fungicide or growth regulators, N balance sheet-60 kgN/ha, weed control with herbicides) trials including 25–30 genotypes describing a large range of genetic diversity were sown in three different agro-climatic regions across north-west France. Genotype performance in ORG management system was reduced from 25 to 40 % for yield and from 10 to 22 % for grain protein content. Estimates of genotypic values appeared to be more precise under LI than ORG conditions. Because of high genetic correlations between LI and ORG conditions, the relative efficiency of indirect selection from LI to ORG conditions was approximately 1. Spearman’s rank correlations were high (Rs = 0.54–0.92) and genotype rank inversions generally had a minor extent. However, in 2005 and 2010, almost 50 % of the lines had to be retained in LI to keep 80 % of the top 20 % of genotypes in organic conditions. Compared with previous results from high-input conditions, LI management provided a better prediction of genotype performance under ORG conditions but crossover genotype × management interactions could be observed between both systems. Overall, combining information provided from both LI and ORG crop management systems appears to be a good process for building efficient and adapted breeding schemes for ORG farming conditions.

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion of square root of mean square prediction error (RMSPE) due to random error of 97.5%. Predicted monthly herbage growth rates had a line bias of 2%, a proportion of RMSPE due to random error of 96%, and a concordance correlation coefficient of 0.87. Annual herbage production was predicted with an RMSPE of 531 (kg of herbage dry matter/ha per year), a line bias of 11%, a proportion of RMSPE due to random error of 80%, and relative prediction errors of 2%. Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively. These results indicate that predictions of the new WFM are relatively accurate and precise, with a conclusion that incorporating a plant-animal relationship model into the WFM allows for dynamic predictions of residuals and more realistic simulations of the effect of grazing pressure on herbage production and intake at the farm level without the intervention from the user.

How does the suppression of energy supplementation affect herbage intake, performance and parasitism in lactating saddle mares?

Agroecology opens up new perspectives for the design of sustainable farming systems by using the stimulation of natural processes to reduce the inputs needed for production. In horse farming systems, the challenge is to maximize the proportion of forages in the diet, and to develop alternatives to synthetic chemical drugs for controlling gastrointestinal nematodes. Lactating saddle mares, with high nutritional requirements, are commonly supplemented with concentrates at pasture, although the influence of energy supplementation on voluntary intake, performance and immune response against parasites has not yet been quantified. In a 4-month study, 16 lactating mares experimentally infected with cyathostome larvae either received a daily supplement of barley (60% of energy requirements for lactation) or were non-supplemented. The mares were rotationally grazed on permanent pastures over three vegetation cycles. All the mares met their energy requirements and maintained their body condition score higher than 3. In both treatments, they produced foals with a satisfying growth rate (cycle 1: 1293 g/day; cycle 2: 1029 g/day; cycle 3: 559 g/day) and conformation (according to measurements of height at withers and cannon bone width at 11 months). Parasite egg excretion by mares increased in both groups during the grazing season (from 150 to 2011 epg), independently of whether they were supplemented or not. This suggests that energy supplementation did not improve mare ability to regulate parasite burden. Under unlimited herbage conditions, grass dry matter intake by supplemented mares remained stable around 22.6 g DM/kg LW per day (i.e. 13.5 kg DM/al per day), whereas non-supplemented mares increased voluntary intake from 22.6 to 28.0 g DM/kg LW per day (13.5 to 17.2 kg DM/al per day) between mid-June and the end of August. Hence total digestible dry matter intake and net energy intake did not significantly differ between supplemented and non-supplemented mares during the second and third cycles. In conclusion, supplementing lactating mares at pasture should not be systematic because their adaptive capacities enable to increase herbage intake and ensure foal growth. Further research is needed to determine the herbage allowance threshold below which supplementation is required.

Farming system design for innovative crop-livestock integration in Europe

The development of integrated crop–livestock systems (ICLS) is a major challenge for the ecological modernisation of agriculture but appears difficult to implement at a large scale. A participatory method for ICLS design has been developed and implemented in 15 case studies across Europe, representing a range of production systems, challenges, constraints and resources for innovation. Local stakeholders, primarily farmers, but also cooperatives, environmental-association representatives and natural-resource managers, were involved in the identification of challenges and existing initiatives of crop-livestock integration; in the design of new options at field, farm and territory levels; and then in qualitative multicriteria assessment of these options. A conceptual framework based on a conceptual model (crops, grasslands, animals) was developed to act as a boundary object in the design step and invite innovative thinking in ‘metabolic’ and ‘ecosystemic’ approaches. A diversity of crops and grasslands interacting with animals appeared central for designing sustainable farming systems at the territory level, providing and benefitting from ecosystem services. Within this diversity, we define three types of integrated systems according to their degrees of spatial and temporal coordination: complementarity, local synergy, territorial synergy. Moreover, the options for cooperation and collective organisation between farmers and other stakeholders in territories to organise and manage this diversity of land use revealed opportunities for smart social innovation. The qualitative multicriteria assessment identified farmer workload as the main issue of concern while demonstrating expected benefits of ICLS simultaneously for economic, agronomic, environmental and social criteria. This study concludes that participatory design of ICLS based on a generic multi-level and multi-domain framework and a methodology to deal with a local context can identify new systems to be tested. Further assessment and redesign work will be performed in later stages of the European FP7 CANTOGETHER project.

Livelihood strategies, resilience and transformability in African agroecosystems

Aiming to translate resilience thinking theory into farming systems design practice, this paper examines fundamental properties of complex systems dynamics and their relation with the mechanisms that govern resilience and transformability in African smallholder agriculture. Agroecosystems dynamics emerge from the aggregation of diverse livelihood strategies in response to changes in the agroecosystem context, and are characterised by non-linearity, irreversibility, convergence/divergence and hysteresis. I examine a number of case studies from Africa to verify three guiding hypotheses in connection to the diversity of rural livelihood strategies: (1) diversity as alternative system regimes; (2) diversity as the result of transformability; (3) diversity determined by changing agricultural contexts. The hierarchy of constraints that determine the space for manoeuvring in agroecosystems is described through the analogy of the Matryoshka nesting dolls: each system level confines and is confined by their immediate sub- and supra-systems. Agricultural contexts, as defined by agro-ecological potential, demography and market connectivity are also dynamic and their trajectory can be described as shifts across stability domains. An example from Kenya shows that household diversity can be described as alternative system regimes, through hysteretic rather than continuous, reversible models. In some particular cases diversity emerges from divergent pathways that may have implied radical transformations in the past, as shown here for rural livelihoods in northern Cameroun. A comparative analysis of East African agroecosystems shows that thresholds in specific variables that may point to the existence of possible tipping points are rather elusive and largely site specific, requiring systematic categorisation of agricultural contexts. While agroecology needs to provide the knowledge base for the ecological intensification of smallholder landscapes, policy and market developments are needed to deal with the Matryoshka effect – or with interactions that are presumably panarchical in certain cases. Desirable shifts in farming systems can only be stimulated by working on both ends simultaneously.

Farming systems designing landscapes: land management units at the interface between agronomy and geography

Agriculture faces big challenges, such as feeding a growing population and providing an increasing amount of biomass for energy production. Land is, however, a limited resource and intensification of agricultural practices is deprecated because of the negative impacts on natural resources. Effective answers should therefore be fostered by the development of smarter spatial configurations of agricultural activities. The improvement of farming systems therefore requires agronomy to interact with geography and other disciplines that deal with spatially-explicit aspects of agricultural land management. Different research approaches have supported agronomy in the development of a landscape approach and in this paper we focus on the interactions with geography fostering the enhancement of a common language about the way farming practices are observed and understood by the two disciplines. For this purpose, we compare land management units, identified in recent agronomic literature, with the aim to facilitate future synergies of landscape-oriented research about farming system design. We conclude by arguing for the enhancement of the interface between agronomy and geography and discussing some perspectives on the use of the various land management units in the design of future farming systems with a landscape approach.

CASIMOD’N: An agro-hydrological distributed model of catchment-scale nitrogen dynamics integrating farming system decisions

This work presents the new integrative model CASIMOD’N (Catchment and Agricultural Systems Integrated MODel for Nitrogen), which assesses effects of farming systems on nitrogen (N) dynamics at the catchment level. Its main innovation is the consideration of the level of the farming system through production strategies, farmer decisions and the expression of decisions as management practices, along with the link between these farming systems, their practices and water pollution. CASIMOD’N integrates farming systems at the farm level and N transfers and transformations at the field, farm and catchment levels. It was built by adapting and combining three models: the catchment-scale biophysical model TNT2 and two farm-scale models, TOURNESOL and FUMIGENE, for the allocation of land use and manure, respectively. The intrinsic logic behind farming system design and function was represented by ensuring agreement between livestock-feeding and manure-management strategies under specific farm constraints (land fragmentation, distance between fields and farmyards) and agronomic rules. The model is able to simulate management practices (crop, manure and mineral fertiliser allocation).An assessment of the farming system modelling was performed by comparing the management practices simulated with CASIMOD’N with (i) observed data from a livestock-oriented catchment and (ii) a reference dataset of management practices reconstructed with a Markov chain and Knapsack-based algorithm. Then, the spatial distributions of the main N fluxes at the sub-catchment scale simulated with CASIMOD’N and based on the reconstructed management practices are discussed.Simulations of the two options had few differences in spatial distribution of the main N compartments, organic and mineral fertilisation and N flux at the outlets both at catchment and sub-catchment levels. However, CASIMOD’N was more accurate for simulating farming systems than the reconstructed reference dataset of management practices. This suggests that CASIMOD’N can be used to conceive, implement and assess prospective scenarios involving farming system redesign.

An open platform to build, evaluate and simulate integrated models of farming and agro-ecosystems

Due to significant changes in agro-ecological contexts, farmers need new solutions to produce goods. Modelling complements field experiments in the design of new farming systems. French researchers...

Optimising farm resource allocation to maximise profit using a new generation integrated whole farm planning model

A new generation integrated whole farm planning model ("the model") is introduced. In a departure from the use of whole farm and average data for decision making, this model integrates data from multiple land management units (LMUs) within a farm business and uses optimisation to identify farm system design to maximise profit under variable production and market conditions. The user supplies pasture growth rates, minimum and maximum acceptable pasture covers for each LMU, animal performance, farm costs and market prices. Additions or constraints can be placed on individual LMUs. The optimisation routine uses this information to identify the mix of production enterprises and management regimes that maximises profit for the business. A case study is presented based on a commercial sheep and beef farm with five distinct LMUs. Comparisons are made between: treating the farm as a single LMU and as five LMUs; with current and optimal farm system. Keywords: Farm System modelling, linear programming, optimisation, land management units, investment

Animal welfare: A result of animal background and perception of its environment

Animal welfare is a growing issue in modern farming systems due to a perceived mismatch between animals’ actual environments and their natural habitats, acknowledgement that animals are sentient beings, and societal awareness not only that animal production matters but also that the production methods matter.[br/] Welfare implies that the biological needs of animals are fulfilled and, more importantly, that the animals feel “well.” What emotions animals can feel is now documented, and methods have been developed to assess how well an animal feels. The welfare of an individual depends on its living environment, genetics, and past experiences, with the result that each individual may perceive a triggering situation differently. Farming system design needs to evolve to encompass the welfare provided to animals based on actual living conditions and the animals’ background. Improvements have been proposed so that it is now possible to integrate animal welfare into farming conditions that meet both animal requirements and societal concerns.

Multi-objective optimization and design of farming systems

Reconfiguration of farming systems to reach various productive and environmental objectives while meeting farm and policy constraints is complicated by the large array of farm components involved, and the multitude of interrelations among these components. This hampers the evaluation of relations between various farm performance indicators and of consequences of adjustments in farm management. Here we present the FarmDESIGN model, which has been developed to overcome these limitations by coupling a bio-economical farm model that evaluates the productive, economic and environmental farm performance, to a multi-objective optimization algorithm that generates a large set of Pareto-optimal alternative farm configurations. The model was implemented for a 96ha mixed organic farm in the Netherlands that represents an example with relevant complexity, comprising various crop rotations, permanent grasslands and dairy cattle. Inputs were derived from a number of talks with the farmers and from literature. After design-, output- and end-user validation the optimization module of the model was used to explore consequences of reconfiguration. The optimization aimed to maximize the operating profit and organic matter balance, and to minimize the labor requirement and soil nitrogen losses. The model outcomes showed that trade-offs existed among various objectives, and at the same time identified a collection of alternative farm configurations that performed better for all four objectives when compared to the original farm. Relatively small modifications in the farm configuration resulted in considerable improvement of farm performance. This modeling study demonstrated the usefulness of multi-objective optimization in the design of mixed farming systems; the potential of the model to support the learning and decision-making processes of farmers and advisers is discussed.

An open platform to build, evaluate and simulate integrated models of farming and agro-ecosystems

Due to significant changes in agro-ecological contexts, farmers need new solutions to produce goods. Modelling complements field experiments in the design of new farming systems. French researchers involved in such design issues developed a specific modelling platform to help model, simulate and evaluate cropping systems. After testing several existing environments, the RECORD platform was developed under the VLE environment, allowing the design of atomic and coupled models. It integrates different time steps and spatial scales and proposes some standard formalisms used to model agro-ecosystems (e.g. difference equations, differential equations, state charts…). A graphic user interface was designed to simplify coding tasks. A variety of research projects already use this platform. Examples are given showing the ability to recode simple models, encapsulate more complex models, link with GIS and databases, and use the R statistical package to run models and analyse simulation outputs. The option to use web interfaces enables application by non-scientist end-users. As the models follow a given standard, they can be placed in a repository and used by other researchers. Linking RECORD to other international platforms is now a compelling issue.

Selecting the sharpest tools to explore the food-feed-fuel debate: Sustainability assessment of family farmers producing food, feed and fuel in Brazil

Continuing interest in sustainable biofuel production is linked with sustainable farming and begs for insights from farming systems research on sustainability assessment and the role of family farms. The aims of this work were two-fold. First, to present a tools and methods selection framework supporting indicator-based sustainability assessment. Second, to apply the framework to the case of castor beans (Ricinus communis L.), family farmers and the biodiesel industry in the southeast of Brazil. The framework synthesizes existing work on sustainability assessment within the agricultural domain. Transparent selection of tools and methods is supported by sequentially accounting for the context of sustainability, dealing with space, classifying the ‘nature of research’ and the degree of integration of different facets of sustainability. The framework is demonstrated with an exploratory assessment of the potential for castor bean cultivation within the current farm type of extensive pasture and fodder crops for dairy cattle. The study accounted for the range of productivity levels within the current farm type and for different management decisions when including castor beans. Assessment was made against economic development, livelihood stability and soil fertility criteria. Selected tools and methods included farm surveys, alternative farming system design and input–output calculations. The results demonstrate the greatest opportunity for castor bean cultivation by currently low productive farms. There is a trade-off of income derived from milk production that is supported by fodder production, and income from castor beans. Decisions regarding areal extent of castor beans and supplementing animal feed, are shown to be farm-specific, and depend upon the interactions between current farm productivity and prioritisation of sustainability criteria. However, generally it is shown that castor bean cultivation should be linked to animal production so that current risk management and income levels can be supported and improved. Further, to maintain soil fertility, castor bean cultivation with nitrogen inputs is necessary. The cyclic nature of the framework supports the next contextualisation of the sustainability question. For our application, constructive future work in a next cycle could include extending to regional level and accounting for temporal variability.

Farming system design to feed the changing world. A review

Agricultural production is unstable as a result of complex, dynamic and interrelated factors such as climate, markets and public policy that are beyond farmers’ control. Farmers must therefore develop new farming systems incorporating innovations in objectives, organization and practices adapted to changing production contexts. As a consequence, agronomists have expanded the “farming system design” field of research. A variety of quantitative and qualitative design approaches have been developed to support the analysis of current farming systems and the design and evaluation of alternatives. A comprehensive literature assessment is lacking for this emerging field of agricultural science. Here we review 41 farming system design approaches using computer models. Our main findings are the following: (1) the reviewed literature do not make reference to the theoretical approaches from the field of design science. (2) Two categories of farming system approaches can be distinguished: optimisation approaches, and participatory and simulation-based approaches. These two categories are connected to two of the main design science theories. (3) For optimisation approaches, farming system design is mainly seen as a problem-solving process. Emphasis is placed on the computational exploration of the solution space by a problem-solving algorithm. (4) For participatory and simulation-based approaches, conceptualization of the design problem is central to the farming system design process. The subsequent exploration of the solution space relies on the creativity of humans. (5) Optimisation approaches, and participatory and simulation-based approaches are oriented towards the development of exploitative rather than exploratory innovations. Exploitative innovations involve the exploitation of available knowledge while exploration innovations build on knowledge created in the course of the design process.

Forage rummy: A game to support the participatory design of adapted livestock systems

The context of agricultural production, climate change in particular, is increasingly requiring adaptations in the structure and management of farming systems. As explorers, implementers, testers and promoters of such adaptations, farmers and extension services have to be involved in the design process of adapted farming systems. However, the complexity of most design approaches produced by research (e.g. computer-model-based) keeps them outside the core of this process. Here we present a game called “forage rummy” developed to engage farmers and extension services in being the main players in livestock system design and evaluation. It relies on a number of “boundary objects” developed upon the conversion of scientific knowledge into more usable forms of support. These are a player-friendly game board based on a conceptual model of a livestock system on which flattened wooden sticks marked with year-round forage production and animal feeding requirements have to be assembled with the support of a computerized support system. Playing the game thus consists of repeated cycles of design of livestock systems adapted to scenarios of the agricultural production context and evaluation of their biophysical and organizational feasibility. An application to designing dairy systems adapted to climate change by 2050 is presented. As the first example of a game-based approach for farming system design, forage rummy proves to be useful in stimulating discussion, reflective and interactive analysis and learning about farming systems, their management and the scope for their adaptation. This is attributed to the researchers’ effort to offer transparent and easily-usable forms of support to the design process. We conclude that the learning stimulated by the game could potentially lead to more consistent and concerted action between researchers, extension services and farmers.

Diagnosis and simulation: a suitable combination to support farming systems design

Designing or improving farming systems requires understanding their dynamics so as to predict their behaviour in response to management. Simulation tools can potentially support the process by which farmers and scientists might obtain such an encompassing understanding. The usability of these tools is, however, partially inhibited by the inherent complexity of the interactions at work in farm-scale models. Whereas such models are generally used in isolation, here we present an approach in which a field-scale diagnosis method complements a farm-scale simulation model. This diagnosis method lends itself easily to an intelligible presentation of field-specific knowledge that can be fed to the simulation tool for more encompassing considerations. Our approach is used to support the design of novel management strategies in grassland-based beef systems and proved to be effective when applied to two farms in the French Pyrenees. Thanks to the integrative representation of the various processes, including the management ones, simulation contributed to deeper learning of both scientists and farmers about room for manoeuvre for increasing self-sufficiency for forage. The diagnosis phase enhanced the learning process by providing a simpler framework in which elementary problems at field scale could be considered separately before being examined concurrently at farm scale in the simulation phase.

Organic agriculture and climate change

AbstractThis article discusses the mitigation and adaptation potential of organic agricultural systems along three main features: farming system design, cropland management and grassland and livestock management. An important potential contribution of organically managed systems to climate change mitigation is identified in the careful management of nutrients and, hence, the reduction of N2O emissions from soils. Another high mitigation potential of organic agriculture lies in carbon sequestration in soils. In a first estimate, the emission reduction potential by abstention from mineral fertilizers is calculated to be about 20% and the compensation potential by carbon sequestration to be about 40–72% of the world's current annual agricultural greenhouse gas (GHG) emissions, but further research is needed to consolidate these numbers. On the adaptation side, organic agriculture systems have a strong potential for building resilient food systems in the face of uncertainties, through farm diversification and building soil fertility with organic matter. Additionally, organic agriculture offers alternatives to energy-intensive production inputs such as synthetic fertilizers which are likely to be further limited for poor rural populations by rising energy prices. In developing countries, organic agricultural systems achieve equal or even higher yields, as compared to the current conventional practices, which translate into a potentially important option for food security and sustainable livelihoods for the rural poor in times of climate change. Certified organic products cater for higher income options for farmers and, therefore, can serve as promoters for climate-friendly farming practices worldwide.