Farming Systems Simulation Research Articles

Integrated Assessment of the EU’s Greening Reform and Feed Self-Sufficiency Scenarios on Dairy Farms in Piemonte, Italy

Specialised dairy farms are challenged to be competitive and yet respect environmental constrains. A tighter integration of cropping and livestock systems, both in terms of feed and manure flows, can be beneficial for the farm economy and the environment. The greening of the direct payments, which was introduced in the European Union’s greening reform in 2013, is assumed to stimulate the transition towards more sustainable systems. The aim of this study was to quantitatively assess the impacts of greening policies on important economic and environmental indicators of sustainability, and explore potential further improvements in policies. The Farm System SIMulator (FSSIM) bioeconomic farm model was used to simulate the consequences of scenarios of policy change on three representative dairy farms in Piedmont, Italy, i.e., an ‘intensive’, an ‘extensive’, and an ‘organic’ dairy farm. Results showed that in general, there is a large potential to increase the current economic performance of all of the farms. The most profitable activity is milk production, resulting in the allocation of all of the available farm land to feed production. Imposing feed self-sufficiency targets results in a larger adaptation of current managerial practice than the adaptations that are required due to the greening policy scenario. It was shown that the cropping system is not always able to sustain the actual herd composition when 90% feed self-sufficiency is imposed. Regarding the greening policies, it is shown that extensive and organic farms already largely comply with the greening constrains, and the extra subsidy is therefore a bonus, while the intensive farm is likely to sacrifice the subsidy, as adapting the farm plan will substantially reduce profit. The introduction of nitrogen (N)-fixing crops in ecological focus areas was the easiest greening strategy to adopt, and led to an increase in the protein feed self-sufficiency. In conclusion, it is important to note that the greening policy in its current form does not lead to reduced environmental impacts. This implies that in order to improve environmental performance, regulations are needed rather than voluntary economic incentives.

The impact of changes in the AgriStability program on crop activities: A farm modeling approach

AbstractTo analyze the production impacts of changes made in 2013 to Canada's AgriStability risk management program, we calibrate a crop allocation model using positive mathematical programming (PMP). Because PMP is not straightforward if farmers are assumed to maximize expected utility (as a risk parameter also needs to be calibrated), we consider possible ways to address this issue but settle on a traditional approach used in the EU's Farm System Simulator. We calibrate farm management models for six different Alberta regions and use it to determine how changes in the AgriStability's payment trigger affect production incentives. Results indicate that, although the initial introduction of the AgriStability program in 2008 might have tilted farmers’ planting decisions toward crops with higher returns and greater risk, changes to this program reduce indemnities and farmers’ expected profits, but do not further alter land‐use decisions. Rather, it is increases in farmers’ aversion to risk that lead to the greatest changes in crop allocation. [EconLit citations: Q14, Q18, C61].

Promoting resilience in Cambodian lowland rice ecosystems—Farming system research to support flexible climate response strategies for smallholder farmers

With high levels of seasonal climatic variability impacting on the consistency of rice production in Cambodian rainfed, lowland systems, there is a need to identify strategies that improve farmer food security and better meet national domestic and export demands. While there is a substantial gap between actual and potential rice yield, little research has been undertaken in Cambodia to improve rainfed rice agronomy or the efficiency of use of natural resources which, in a climate constrained environment can hold the key to better productivity and food security.On-station and on-farm research, in combination with farming systems simulation and social research provide the capacity to evaluate cropping options through the lens of climate variability. The testing of technologies and strategies, including the use of modern, short and medium duration varieties, opportunistic timing of crop establishment, mechanisation, supplementary irrigation and improved agronomic practice has shown that there is potential to mitigate the effects of variable climate on farm productivity and household income. However, this requires an increased level of farmer/systems flexibility to allow for near to real-time changes in cropping response to observed seasonal conditions. These factors differentiate this research and provide the opportunities to improve the individuals’ livelihood and in meeting national rice production targets.

Modelling the manager: Representing rule-based management in farming systems simulation models

We trace the evolution of the representation of management in cropping and grazing systems models, from fixed annual schedules of identical actions in single paddocks toward flexible scripts of rules. Attempts to define higher-level organizing concepts in management policies, and to analyse them to identify optimal plans, have focussed on questions relating to grazing management owing to its inherent complexity. “Rule templates” assist the re-use of complex management scripts by bundling commonly-used collections of rules with an interface through which key parameters can be input by a simulation builder. Standard issues relating to parameter estimation and uncertainty apply to management sub-models and need to be addressed. Techniques for embodying farmers' expectations and plans for the future within modelling analyses need to be further developed, especially better linking planning- and rule-based approaches to farm management and analysing the ways that managers can learn.

Predicting nitrogen dynamics in a dairy farming catchment using systems synthesis modelling

The intensity of milk production from pasture based dairy farming systems is often related to nitrogen (N) losses. This paper investigates dairy farming systems in the Scotts Creek catchment, an intensive farming region in south-eastern Australia, to assess aspects of productive potential and environmental footprint as a result of nutrient loss. A detailed survey of farming systems was coupled with regional data and a dairy farming systems simulation model (DairyMod) to better understand the N flows in farming systems over a range of different input and production intensities. Simulations of representative farming systems – farming system typologies – were run for 100years to provide information on the consistency and proportion of N loss in various pathways over a range of different weather and soil moisture conditions. The typologies covered a very wide range in intensity of stocking rate, inputs (e.g. concentrates, fertiliser). In general N transformations, plant and animal production and the efficiency of conversion of N into animal and plant products were related to the level of N inputs of the farming systems and milk production, or intensity. The long-term average total predicted N loss (via leaching, denitrification and volatilisation) ranged from 24(±6) to 227(±73)kgN/ha/yr and increased relative to the intensity of milk production (L/ha). Over the long term, annual average N losses by leaching ranged from 4 to 143kgN/ha/yr, volatilisation from 17 to 66kgN/ha/yr and denitrification from 2 to 18kgN/ha/yr. In an average system there were similar amounts of N exported from the farming system by leaching (44% of total N), as lost through volatilisation (47%), whereas losses by denitrification were comparatively minor (9%). The inputs were principally related to a potential milk production capacity of the farming system which was not wholly related to stocking rate. The efficiency of N utilisation for milk synthesis (L milk/kgN-consumed) increased with system intensity, however the relative loss (gN loss/kg milk N) also increased. With the current farming system typologies, improvements in animal efficiency due to intensification appear to be offset by the capacity of the system to retain surplus N. In order to meet regional production targets, there are various potential ways to further intensify the current farming systems. However the implications of achieving such targets on N losses (via leaching, denitrification and volatilisation) are important when considering the environmental implications of further intensification.

Food insecurity of smallholder farming systems in B72A catchment in the Olifants River Basin, South Africa

Traditional smallholder farming systems are characterized by low yields and high risks of crop failure and food insecurity. Through a biophysical model, PARCHED-THIRST and a socio-economic farming systems simulation model, OLYMPE, we evaluated the performance of farming practices based on maize yield, gross margin and total family balance over a 10-year period in semi-arid Olifants River Basin of South Africa. Farm profitability under scenarios of different maize productions, maize grain and fertiliser price variations were explored for the identified farming systems. Farm types (A to E) were identified from farm surveys, and validated with farmers and extension officers. The order of vulnerability to severe droughts and food insecurity, starting with the most vulnerable is farm Type B, C, D, A and E. Severe drought or flood shock resulted in highest farm gross margin and total family balance reductions, partly due to loss of production for family consumption. Labour returns ranged from US$ 62/capita.year for crop-based farm types to US$ 363/capita.year for livestock-based farm Type E. Results revealed that livestock and crop diversification are most proficient strategies to ensure stable income and food security for smallholder farmers. Thus, smallholder farming technology innovations and policies should engage in solutions to poor yields and livestock farming.

SWIM3: Model Use, Calibration, and Validation

SWIM3 is the latest release in the family of SWIM (Soil Water Infiltration and Movement) models that provides efficient solutions to the Richards and advection-dispersion equations for use in studies of soil water and solute dynamics. This version of the model has been designed specifically for use in farming systems simulation. Development within the APSIM (Agricultural Production Systems Simulator) framework enables SWIM3 to be combined with a wide range of soil and crop models to simulate a variety of agricultural systems. Other improvements in this release provide a new approach for specifying soil hydraulic properties from simple measures of soil water behavior. The simplicity of this new approach makes such a mechanistic numerical model more accessible to farming systems researchers. The effectiveness of this approach and the utility of SWIM3 for use in farming systems analysis is demonstrated using data from two long-term trials with different soils, climates, and cropping systems. These examples show how the design of SWIM3 allows model parameterization from consistent and well understood emergent soil properties in a simple but meaningful way. Access to the model and involvement in its ongoing development is welcomed via the APSIM Community Source Framework.

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.

How farming systems simulation can aid the development of more sustainable smallholder farming systems in southern Africa

Over the past 20 years, farming systems modelling has become an accessible tool for developing intervention strategies targeted at smallholder farmers in southern Africa. Applying the Agricultural Productions Systems sIMulator (APSIM) to credibly simulate key soil and crop processes in highly constrained, low yielding maize/legume systems has led to four distinct modes of use: (i) to add value to field experimentation and demonstration; (ii) in direct engagement with farmers; (iii) to explore key system constraints and opportunities with researchers and extension agencies; and (iv) in the generation of information for policy makers, bankers and insurance institutions. Examples of application in each of these modes are presented. Despite being demonstrated as an excellent tool for developing intervention strategies and extension material, the use of simulation is limited by a lack of competent local users. Better co-operation within the simulation community, sharing of climate, soil and crop parameterisation and validation datasets, and focussing of efforts on using models to benefit smallholder farmers are suggested as ways of increasing the use and relevance of simulation. Substantial investment in the training of agriculturalists and the further science development of systems simulation is required to tackle the enormous challenges facing agricultural development in the region.

An overview of APSIM, a model designed for farming systems simulation

The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIM's structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided.