H. Hengsdijk

Long-Term Effects of Manure and Inorganic Fertilizers on Yield and Soil Fertility for a Winter Wheat-Maize System in Jiangsu, China*'

ABSTRACT Winter wheat-maize rotations are dominant cropping systems on the North China Plain, where recently the use of organic manure with grain crops has almost disappeared. This could reduce soil fertility and crop productivity in the long run. A 20-year field experiment was conducted to 1) assess the effect of inorganic and organic nutrient sources on yield and yield trends of both winter wheat and maize, 2) monitor the changes in soil organic matter content under continuous wheat-maize cropping with different soil fertility management schemes, and 3) identify reasons for yield trends observed in Xuzhou City, Jiangsu Province, over a 20-year period. There were eight treatments applied to both wheat and maize seasons: a control treatment (C); three inorganic fertilizers, that is, nitrogen (N), nitrogen and phosphorus (NP), and nitrogen, phosphorus and potassium (NPK); and addition of farmyard manure (FYM) to these four treatments, that is, M, MN, MNP, and MNPK. At the end of the experiment the MN, MNP, and MNPK treatments had the highest yields, about 7 t wheat ha−1 and 7.5 t maize ha−1, with each about 1 t ha−1 more than the NPK treatments. Over 20 years with FYM soil organic matter increased by 80% compared to only 10% with NPK, which explained yield increases. However, from an environmental and agronomic perspective, manure application was not a superior strategy to NPK fertilizers. If manure was to be applied, though, it would be best applied to the wheat crop, which showed a better response than maize.

A framework for integrated biophysical and economic land use analysis at different scales

There is a general need for quantitative tools that can be used to support policy makers in regional rural development. Here, a framework for (sub-) regional land use analysis is presented that quantifies biophysical and economic sustainability trade-offs. The framework, called sustainable options for land use (SOLUS), was developed over a 10-year period of investigation in the Northern Atlantic Zone of Costa Rica and encompasses scale levels that range from field to region. SOLUS consists of technical coefficient generators to quantify inputs and outputs of production systems, a linear programming model that selects production systems by optimizing regional economic surplus, and a geographic information system. Biophysical and economic disciplines are integrated and various types of knowledge, ranging from empirical expert judgement to deterministic process models are synthesized in a systems-analytical manner. Economic sustainability indicators include economic surplus and labor employment, and biophysical ones include soil N, P and K balances, biocide use and its environmental impact, greenhouse gas emission and nitrogen leaching loss and volatilization. Land use scenarios can be implemented by varying properties of production inputs (e.g., prices), imposing sustainability restrictions in the optimization, and incorporating alternative production systems based on different technologies. Examples of application of SOLUS in the Northern Atlantic Zone of Costa Rica show that introduction of alternative technologies may result in situations that satisfy both economic as well as biophysical sustainability. On the other hand, negative trade-offs were found among different dimensions of biophysical sustainability themselves.

A goal-oriented approach to identify and engineer land use systems

This paper describes a formalized approach to identify and engineer future-oriented land use systems. Such land use systems can be used to explore options for strategic decision making with respect to land use policy and to do ex-ante assessment of land use alternatives to be further tested or developed in experimental settings. The so-called goal-oriented approach consists of three steps: (1) goal-oriented identification and design of land use systems; (2) quantification of biophysical production possibilities; and (3) defining the optimal mix of inputs, i.e. the production technique, required to realize production possibilities. The goal-oriented identification and design depends on the land-related objectives of a system under study, whereas plant, animal and environmental characteristics determine biophysical production possibilities. Characteristics of the production technique determine the realization of production possibilities. General guidelines are given to structure the specification and number of alternatives to be explored and to apply agro-ecological principles required for quantification of future-oriented land use systems. Concepts of the approach are illustrated with data from the northern Atlantic zone of Costa Rica and the Sudano–Sahelian zone of Mali. Finally, suggestions are given for the application of the approach at spatial and temporal scales exceeding the field level and time horizon of 1 year.

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.

Quantifying economic and biophysical sustainability trade-offs in land use exploration at the regional level: a case study for the Northern Atlantic Zone of Costa Rica

A generic methodology is presented for exploration of sustainable land use options at the regional level by quantifying trade-offs between socio-economic and biophysical sustainability objectives. The methodology is called SOLUS (Sustainable Options for Land USe), and was developed over a ten year period of investigation in the Northern Atlantic Zone of Costa Rica. SOLUS includes a linear programming model, technical coefficient generators for livestock and cropping activities and a geographic information system. The linear programming model maximizes regional economic surplus subject to a flexible number of resource and sustainability constraints. Economic sustainability indicators are economic surplus and labor employment, and biophysical ones include soil N, P and K balances, pesticide use and its environmental impact, nutrient losses and a proxy for trace gas emissions. The capabilities of the methodology are illustrated for the Northern Atlantic Zone of Costa Rica. Though ample scope exists for reducing environmental effects and introducing sustainable production systems separately, pursuing both objectives simultaneously, considerably reduces economic surplus and agricultural employment. Agricultural area can be decreased and forested area increased without severely affecting the regional economic surplus.

Formalizing agro-ecological engineering for future-oriented land use studies

Agriculture faces an array of interrelated problems that call for development of new and revision of existing cropping systems towards the multiple needs of the 21st century. Agro-ecological engineering approaches aimed at design and exploration of alternative land use systems at various scales may support the identification of appropriate land use options. Engineering approaches are based on mathematical representations of well-founded agro-ecological principles while taking into account available resources and prevailing land-related objectives. The goal of this paper is to contribute to the development of a formalized approach to engineer cropping systems at the land unit level that can be used as building blocks for systematic explorations of land use options at farm or regional scale. The approach for engineering cropping systems at the land unit level consists of three steps: (i) goal-driven design of cropping systems, (ii) quantification of biophysical production targets and (iii) definition of the optimal mix of inputs required to realize production targets. This paper describes the approach and illustrates it with examples from the Sudano-Sahelian zone of Mali. Explicit attention is paid to the required numerical tools and their application to analyze consequences of uncertainty in the performance of engineered cropping systems. Using numerical tools, uncertainty is made explicit with the aim to better manage or reduce it. Identification of uncertainty at the designers desk allows taking uncertainty into account before applying engineered land use systems in regional model studies or testing such systems in practice. Problems related to the application of numerical tools are discussed, including the future role of agro-ecological engineering as independent discipline within agricultural science.

Analytical framework for disentangling the concept of sustainable land use

Definitions of sustainability have till now failed to suit both conceptual and operational purposes for lack of an appropriate analytical framework that can be used by biophysical and socio-economic sciences with equal ease. A framework for analysing sustainable land use is proposed which distinguishes between agro-ecological and socio-economic components and between different hierarchical system levels. In some detail the agro-ecological component is discussed in terms of changes in the stock of natural resources. Two decision-making levels with regard to land use, the farm level and the policy level are discussed in terms of the trade-offs between agro-ecological sustainability and socio-economic objectives.

Quantification of land use systems using technical coefficient generators: a case study for the Northern Atlantic zone of Costa Rica

Abstract This paper describes two generic so-called technical coefficient generators, PASTOR (Pasture and Animal System Technical coefficient generatOR) and LUCTOR (Land Use Crop Technical coefficient generatOR), that quantify land use systems in terms of inputs and outputs based on the integration of systems-analytical knowledge, standard agronomic and animal husbandry data and expert knowledge. PASTOR quantifies livestock systems while LUCTOR is geared towards cropping systems. Main inputs quantified include costs, labour requirements, fertiliser use and application of crop protection agents. Outputs are production and a number of associated environmental indicators. Although both PASTOR and LUCTOR were developed to generate input data for land use models, they are also useful as stand-alone tools to explore the technical efficiency of land use systems, to perform cost-benefit analyses and to quantify the trade-off among socio-economic, agronomic and environmental indicators at the field level. PASTOR and LUCTOR are illustrated with data from the Northern Atlantic zone in Costa Rica. Tools such as PASTOR and LUCTOR integrate different types of knowledge, including non-documented knowledge from field experts and make that knowledge transparent and open to critical review and discussion by others.

Combining farm and regional level modelling for Integrated Resource Management in East and South-east Asia

Abstract Currently, in many of the highly productive lowland areas of East and South-east Asia a trend to further intensification and diversification of agricultural land use can be observed. Growing economies and urbanization also increase the claims on land and water by non-agricultural uses. As a result, decisions related to the management and planning of scarce resources become increasingly complex. Technological innovations at the field/farm level are necessary but not sufficient – changes in resource use at regional scale will also be essential. To support decision-making in such situations, we advocate a multi-scale modelling approach embedded in a sound participatory process. To this end, the Integrated Resource Management and Land use Analysis (IRMLA) Project is developing an analytical framework and methods for resource use analysis and planning, for four sites in Asia. In the envisaged multi-scale approach, integration of results from field, farm, district and provincial level analysis is based on interactive multiple goal linear programming (IMGLP), farm household modelling (FHM), production ecological concepts and participatory techniques. The approach comprises the following steps: (i) inventory/quantification of current land use systems, resource availability, management practices and policy views, (ii) analysis of alternative, innovative land use systems/technologies, (iii) exploration of the opportunities and limitations to change resource use at regional scale under alternative future scenarios, (iv) modelling decision behaviour of farmers and identification of feasible policy interventions, and (v) synthesis of results from farm to regional level for negotiation of the most promising options by a stakeholder platform. In the current paper, the operationalisation of dual-scale analysis is illustrated by the outputs (development scenarios, promising policy measures and innovative production systems) from various component models for the case study Ilocos Norte, Philippines. An approach is discussed for the integration of results from the different model components at two different decision making levels (farm and province).

The effect of temporal variation on inputs and outputs of future-oriented land use systems in West Africa

Abstract The (semi-) arid area of West Africa is characterized by erratic rainfall that causes highly variable performances of cropping systems. This creates difficulties in strategic decision-making based on future-oriented production systems. In this paper, the degree of variation in inputs and outputs of future-oriented millet ( Pennisetum glaucum L.) systems is quantified using a dynamic crop growth simulation model and a static technical coefficient generator. To determine inputs and outputs of future-oriented millet systems under (semi-) arid conditions, the target-oriented approach was operationalized for low-yielding conditions. Economic yield, N-loss and labor requirement were used as benchmarks for outputs and inputs of future-oriented land use systems. Weather data for 31 year characterize two sites in the (semi-) arid zone of Mali, while for each site two soil types with distinct properties were considered. In all four physical environments, inputs and outputs of millet systems have coefficients of variation (CV) exceeding 50%. Consequences of the variable performances of these systems are discussed for both policy-makers and designers of future-oriented systems. Engineering tools exist which help policy-makers to quantify consequences of variability at different scale levels so that variability can be reduced or better managed. Examples are given of future-oriented cropping systems aimed at less variable yield. At one site, fine tuning of the sowing date to seasonal water availability reduced CVs yield to 20–30% while long-term average yields increased with 40 to more than 130%. Water conservation measures increased yields by 40–230% and reduced their CVs by 28–50% in all four physical environments. Effects of various cultivation methods on the variability in inputs and outputs of future-oriented cropping systems can be rapidly explored using these tools. In addition, systematic analysis using such tools allows explicit analysis of gains and costs of various alternatives simultaneously.