Analysis of Productive Performance of Crop and Animal Production Systems: An Integrated Analytical Framework

This article presents a two-stage analytical framework that integrates ecological crop (animal) growth and economic frontier production models to analyse the productive efficiency of crop (animal) production systems. The ecological crop (animal) growth model estimates "potential" output levels given the genetic characteristics of crops (animals) and the physical conditions of locations where the crops (animals) are grown (reared). The economic frontier production model estimates "best practice" production levels, taking into account economic, institutional and social factors that cause farm and spatial heterogeneity. In the first stage, both ecological crop growth and economic frontier production models are estimated to calculate three measures of productive efficiency: (1) technical efficiency, as the ratio of actual to "best practice" output levels; (2) agronomic efficiency, as the ratio of actual to "potential" output levels; and (3) agro-economic efficiency, as the ratio of "best practice" to "potential" output levels. Also in the first stage, the economic frontier production model identifies factors that determine technical efficiency. In the second stage, agro-economic efficiency is analysed econometrically in relation to economic, institutional and social factors that cause farm and spatial heterogeneity. The proposed framework has several important advantages in comparison with existing proposals. Firstly, it allows the systematic incorporation of all physical, economic, institutional and social factors that cause farm and spatial heterogeneity in analysing the productive performance of crop and animal production systems. Secondly, the location-specific physical factors are not modelled symmetrically as other economic inputs of production. Thirdly, climate change and technological advancements in crop and animal sciences can be modelled in a "forward-looking" manner. Fourthly, knowledge in agronomy and data from experimental studies can be utilised for socio-economic policy analysis. The proposed framework can be easily applied in empirical studies due to the current availability of ecological crop (animal) growth models, farm or secondary data, and econometric software packages. The article highlights several directions of empirical studies that researchers may pursue in the future.agro-economic efficiency, agronomic efficiency, crop growth model, frontier production model, farm heterogeneity, spatial heterogeneity

A Modelling Framework for Addressing the Synergies between Global Conventions through Land Use Changes: Carbon Sequestration, Biodiversity Conservation, Prevention of Land Degradation and Food Security in Agricultural and Forested Lands in Developing Countries

This paper proposed a methodological framework for the assessment of carbon stocks and the development and identification of land use, land use change and land management scenarios, whereby enhancing carbon sequestration synergistically increases biodiversity, the prevention of land degradation and food security through the increases in crop yields. The framework integrates satellite image interpretation, computer modelling tools (i.e. software customization of off-the-shelf soil organic matter turnover simulation models) and Geographical Information Systems (GIS). The framework addresses directly and indirectly the cross-cutting ecological concerns foci of major global conventions: climate change, biodiversity, the combat of desertification and food security. Their synergies are targeted by providing procedures for assessing and identifying simultaneously carbon sinks, potential increases in plant diversity, measures to prevent land degradation and enhancements in food security through crop yields, implicit in each land use change and land management scenario. The scenarios aim at providing “win-win” options to decision makers through the framework’s decision support tools. Issues concerning complex model parameterization and spatial representation were tackled through tight coupling soil carbon models to GIS via software customization. Results of applying the framework in the field in two developing countries indicate that reasonably accurate estimates of carbon sequestration can be obtained through modeling; and that alternative best soil organic matter management practices that arrest shifting “slash-and-burn” cultivation and prevent burning and emissions, can be identified. Such options also result in increased crop yields and food security for an average family size in the area, while enhancing biodiversity and preventing land degradation. These options demonstrate that the judicious management of organic matter is central to greenhouse gas mitigation and the attainment of synergistic ecological benefits, which is the concern of global conventions. The framework is to be further developed through successive approximations and refinement in future, extending its applicability to other landscapes.Climate Change, Greenhouse Gas Mitigation, Carbon Sequestration, Soil Organic Matter, Modeling, Land-Use Change, Land Management, Ecological Synergies, Agriculture

A framework for a European network for a systematic environmental impact assessment of genetically modified organisms (GMO)

The assessment of the impacts of growing genetically modified (GM) crops remains a major political and scientific challenge in Europe. Concerns have been raised by the evidence of adverse and unexpected environmental effects and differing opinions on the outcomes of environmental risk assessments (ERA). The current regulatory system is hampered by insufficiently developed methods for GM crop safety testing and introduction studies. Improvement to the regulatory system needs to address the lack of well designed GM crop monitoring frameworks, professional and financial conflicts of interest within the ERA research and testing community, weaknesses in consideration of stakeholder interests and specific regional conditions, and the lack of comprehensive assessments that address the environmental and socio economic risk assessment interface. To address these challenges, we propose a European Network for systematic GMO impact assessment (ENSyGMO) with the aim directly to enhance ERA and post-market environmental monitoring (PMEM) of GM crops, to harmonize and ultimately secure the long-term socio-political impact of the ERA process and the PMEM in the EU. These goals would be achieved with a multi-dimensional and multi-sector approach to GM crop impact assessment, targeting the variability and complexity of the EU agro-environment and the relationship with relevant socio-economic factors. Specifically, we propose to develop and apply methodologies for both indicator and field site selection for GM crop ERA and PMEM, embedded in an EU-wide typology of agro-environments. These methodologies should be applied in a pan-European field testing network using GM crops. The design of the field experiments and the sampling methodology at these field sites should follow specific hypotheses on GM crop effects and use state-of-the art sampling, statistics and modelling approaches. To address public concerns and create confidence in the ENSyGMO results, actors with relevant specialist knowledge from various sectors should be involved

Training materials for different categories of users

Agricultural and Food Policy, Environmental Economics and Policy, Farm Management, Land Economics/Use, Production Economics, Teaching/Communication/Extension/Profession,