Anil Graves

Who's in and why? A typology of stakeholder analysis methods for natural resource management

Stakeholder analysis means many things to different people. Various methods and approaches have been developed in different fields for different purposes, leading to confusion over the concept and practice of stakeholder analysis. This paper asks how and why stakeholder analysis should be conducted for participatory natural resource management research. This is achieved by reviewing the development of stakeholder analysis in business management, development and natural resource management. The normative and instrumental theoretical basis for stakeholder analysis is discussed, and a stakeholder analysis typology is proposed. This consists of methods for: i) identifying stakeholders; ii) differentiating between and categorising stakeholders; and iii) investigating relationships between stakeholders. The range of methods that can be used to carry out each type of analysis is reviewed. These methods and approaches are then illustrated through a series of case studies funded through the Rural Economy and Land Use (RELU) programme. These case studies show the wide range of participatory and non-participatory methods that can be used, and discuss some of the challenges and limitations of existing methods for stakeholder analysis. The case studies also propose new tools and combinations of methods that can more effectively identify and categorise stakeholders and help understand their inter-relationships.

Applications of crop/soil simulation models in tropical agricultural systems☆

Abstract Crop simulation models have been used widely to describe systems and processes at the level of the genotype, the crop, the farming system, the region, and the global environment, but examples of how the use of such models has benefited poor people in developing countries are limited. There is, therefore, an urgent need to make the use of models in research more relevant to problems in the real world and to find effective means of disseminating the results from work using models to the potential beneficiaries. To achieve this, we believe that there must be a shift in the thinking of crop/soil modelers toward making people more center stage and toward a more problem-solving approach. This means researchers must think of the real problems faced by ordinary people in developing countries and construct and apply their models to contribute to solving these problems. For this to be effective, modelers need to define clearly who are the end users of their models and to enter into dialogue with these people so that the final product is tailored to their needs. There appear to be two opposite directions in which further crop modeling research can develop. On the one hand, in response to the rapidly expanding field of genomics, links between information at the gene level and performance at the phenotype level need to be established, and methodologies to do this must be developed. Such models will have the potential to contribute to enhancing the efficiency of crop improvement programs worldwide by providing more efficient ways of identifying and evaluating desirable characteristics for specific plant breeding goals. On the other hand, crop models need to be incorporated into higher order systems such as the whole farm, catchment, or region. Some progress has already been made in linking crop growth models with other physical process models to improve our understanding of how changes in agricultural systems influence overall environmental impacts. However, the role of people in these systems also needs to be made explicit so that the day-to-day decisions that they make to sustain and improve their livelihoods and the influence these decisions have on their environment and natural resource base can be taken into account.

Low External Input Technologies for Livelihood Improvement in Subsistence Agriculture

Publisher Summary Technologies using low levels of external inputs readily available either on-farm or from nearby off-farm sources are seen by some experts as more appropriate and sustainable to address the demand for food in the next 50 years by improving the productivity of subsistence farmers. This approach, often referred to as low external input agriculture (LEIA), emphasizes the use of techniques that integrate natural processes such as nutrient cycling, biological nitrogen fixation (BNF), soil regeneration, and natural enemies of pests into food production processes. Efforts are also made to minimize losses from the system, such as by leaching or removal of crop residues. The use of non-renewable inputs, such as pesticides and fertilizers that can damage the environment or harm the health of farmers and consumers is also minimized, and more emphasis is placed on the use of such techniques as, for example, intercropping, agroforestry, cover crops, or animal manure. This chapter analyzes the biophysical and socioeconomic characteristics of a number of LEIA techniques that have been evaluated as potential improvements to subsistence agricultural systems. These techniques include intercropping, alley cropping, cover crops and green manures, biomass transfer, compost, use of animal manure, and improved and enriched fallows.

Classifications and Functions of Agroforestry Systems in Europe

Agroforestry systems have often been neglected in Europe because administrative structures within many national governments have considered that only agriculture or forestry are legitimate within their remit. This has resulted in the loss of agroforestry systems in European countries and an impoverishment of the benefits that they provide. This paper argues that agroforestry systems are a complex interaction of agricultural and forestry elements which can be classified according to their components, spatial and temporal arrangement, agro-ecological zone, and socio-economic aspects. A further breakdown can be made on the basis of ecosystem functions, and their associated goods and services. The ecosystem functions of agroforestry systems can be grouped under production (the creation of biomass), habitat (the delivery of biodiversity), regulation (maintenance of essential processes and life support systems) and culture (cultural heritage, landscape enhancement and recreation). The importance of the multi-functionality of agroforestry systems in terms of their management input and the range of their outputs is stressed and it is proposed that land use decisions should be made within the broader ecosystems perspective so that greater social well-being can be derived from rural areas in Europe.

Environmental Impact Assessment, ecosystems services and the case of energy crops in England

A consequence of the increased requirements for renewable energy is likely to be allocation of more land to bio-energy crop production. Recent regulatory changes in England, as in other parts of the UK, mean that changes in land-use are increasingly subject to screening through Environmental Impact Assessment (EIA). This paper reviews these regulatory changes and explores the potential benefits of incorporating a fuller examination of ecosystem services within EIA procedures. The authors argue that such an approach could help achieve sustainability by identifying the best options within an area, rather than concentrating on the negative effects of selected proposed projects. It could also help highlight the benefits provided by existing and proposed agricultural, forestry, peri-urban and urban systems. However, successful implementation of an ecosystem services approach would also require a greater understanding of the societal preferences for the full range of ecosystem services at a landscape scale, aswell as the trade-offs and synergies between uses of specific services.

Development and Use of a Framework for Characterising Computer Models of Silvoarable Economics

A review of existing computer models of silvoarable 1 economics was undertaken for a project, entitled Silvoarable Agroforestry for Europe (SAFE), which aims to reduce uncertainty regarding the introduction and management of silvoarable systems in Europe. Because the published literature describing and comparing such models is sparse, a framework was developed and then used to characterise five computer models: POPMOD, ARBUSTRA, the Agroforestry Estate Model, WaNuLCAS, and the Agroforestry Calculator. Key characteristics described for each model were the background, systems modelled, objective of the economic analysis, economic viewpoint, spatial and temporal scales, generation and use of biophysical data, model platform and interface, and input requirements and outputs. Each of the models could produce a partial budget of the profitability of a silvoarable, arable, or forestry system at a one-hectare level using discounted cost–benefit analysis. Whilst the research models undertook the analysis from a viewpoint of a generic farmer, models developed for decision-support also included appraisals from the perspectives of tenants, share-croppers, and participants in a joint-venture. The two farm-scale models, ARBUSTRA and the Agroforestry Estate Model, could also be used to examine the feasibility of silvoarable systems on an existing business, and to determine the effects of heterogeneous land types and phased planting. The framework allows users to identify the pertinent issues for selecting or developing a particular model.

Farm-SAFE: the process of developing a plot- and farm-scale model of arable, forestry, and silvoarable economics

Financial feasibility and financial return are two key issues that farmers and land owners consider when deciding between alternative land uses such as arable farming, forestry and agroforestry. Moreover regional variations in yields, prices and government grants mean that the relative revenue and cost of such systems can vary substantially within Europe. To aid our understanding of these variations, the European Commission sponsored a research project called “Silvoarable Agroforestry For Europe” (SAFE). This paper describes the process of developing a new economic model within that project. The initial stages included establishing criteria for the model with end-users and reviewing the literature and existing models. This indicated that the economic model needed to allow comparison of arable farming, forestry and agroforestry systems at a plot- and a farm-scale. The form of comparisons included net margins, net present values, infinite net present values, equivalent annual values, and labour requirements. It was decided that the model would operate in a spreadsheet format, and the effect of phased planting patterns would be included at a farm-scale. Following initial development, additional user feedback led to a final choice on a model name, a final method of collating input data, and the inclusion of field-based operations such as varying the cropped area, replacing dead trees, and pruning. In addition options in terms of improved graphical outputs and the ability to undertake sensitivity analysis were developed. Some of the key lessons learnt include the need to establish clear model criteria and the benefits of developing a working prototype at an early stage to gain user-feedback.

Swiss farmers don’t adopt agroforestry because they fear for their reputation

Abstract Agricultural policy in Europe is moving towards greater support of multifunctional agriculture, such as agroforestry systems. However, modern farmers appear to be resisting this change. Trees in agricultural landscapes have been declining, despite increasing direct payments for their ecosystem services. To understand the drivers of farmer behaviour in Switzerland with regard to practicing agroforestry, we interviewed 50 farmers using a semi-quantitative and open ended questionnaire. In terms of potential motivations for adoption of agroforestry, most farmers gave highest scores to habitat ecosystem services, both for livestock and wildlife. Low scores were given to productivity, profitability and ecological direct payments. Farmers resisting adoption concluded that practising agroforestry would not have a positive impact on their reputation. They also attributed significantly lower scores to perceived behavioural control. We conclude that payments for ecosystem services will be unlikely to change farmers’ behaviour, as long as their expectations and knowledge are not appropriately addressed. Transdisciplinary co-production of agro-ecological knowledge could help to change their attitude.

A system identification approach for developing and parameterising an agroforestry system model under constrained availability of data

This paper introduces a system identification approach to overcome the problem of insufficient data when developing and parameterising an agroforestry system model. Typically, for these complex systems the number of available data points from actual systems is less than the number of parameters in a (process-based) model. In this paper, we follow a constrained parameter optimization approach, in which the constraints are found from literature or are given by experts. Given the limited a priori systems knowledge and very limited data sets, after decomposition of the parameter estimation problem and after model adaptation, we were able to produce an acceptable correspondence with validation data from a real-world agroforestry experiment.

How is agroforestry perceived in Europe? An assessment of positive and negative aspects by stakeholders

Whilst the benefits of agroforestry are widely recognised in tropical latitudes few studies have assessed how agroforestry is perceived in temperate latitudes. This study evaluates how stakeholders and key actors including farmers, landowners, agricultural advisors, researchers and environmentalists perceive the implementation and expansion of agroforestry in Europe. Meetings were held with 30 stakeholder groups covering different agroforestry systems in 2014 in eleven EU countries (Denmark, France, Germany, Greece, Hungary, Italy, Netherlands, Portugal, Spain, Sweden and the United Kingdom). In total 344 valid responses were received to a questionnaire where stakeholders were asked to rank the positive and negative aspects of implementing agroforestry in their region. Improved biodiversity and wildlife habitats, animal health and welfare, and landscape aesthetics were seen as the main positive aspects of agroforestry. By contrast, increased labour, complexity of work, management costs and administrative burden were seen as the most important negative aspects. Overall, improving the environmental value of agriculture was seen as the main benefit of agroforestry, whilst management and socio-economic issues were seen as the greatest barriers. The great variability in the opportunities and barriers of the systems suggests enhanced adoption of agroforestry across Europe will be most likely to occur with specific initiatives for each type of system.