Formulating generalised 'goal games' against nature: An illustration from decision-making under uncertainty in agriculture

The games-against-nature approach to the analysis of uncertainty in decision-making relies on the assumption that the behaviour of a decision-maker can be explained by concepts such as maximin, minimax regret, or a similarly defined criterion. In reality, however, these criteria represent a spectrum and, the actual behaviour of a decision-maker is most likely to embody a mixture of such idealisations. This paper proposes that in game-theoretic approach to decision-making under uncertainty, a more realistic representation of a decision-maker's behaviour can be achieved by synthesising games-against-nature with goal programming into a single framework. The proposed formulation is illustrated by using a well-known example from the literature on mathematical programming models for agricultural-decision-making. (c) 2005 Elsevier Inc. All rights reserved.

The 11-yr solar cycle in ERA-40 data: an update to 2008

Multiple linear regression is used to diagnose the signal of the 11-yr solar cycle in zonal-mean zonal wind and temperature in the 40-yr ECMWF Re-Analysis (ERA-40) dataset. The results of previous studies are extended to 2008 using data from ECMWF operational analyses. This analysis confirms that the solar signal found in previous studies is distinct from that of volcanic aerosol forcing resulting from the eruptions of El Chichón and Mount Pinatubo, but it highlights the potential for confusion of the solar signal and lower-stratospheric temperature trends. A correction to an error that is present in previous results of Crooks and Gray, stemming from the use of a single daily analysis field rather than monthly averaged data, is also presented.

Renewable energy in the UK countryside: policy and practice

Of the technologies currently available for producing energy from renewable sources in the British climate all except one depend on a single ingredient, namely land. Therefore other than offshore wind generation, which has been slow and expensive to establish, renewables have had to be derived almost entirely from the land, whether as sites for turbines or areas on which to grow feedstocks for biomass and biofuels. Of these, only wind turbines have been developed in any number while economic conditions have until now been unfavourable for biomass and biofuel. The UK is unlikely to meet its present targets under the Kyoto agreement, due to a mixture of limited funding and problems of policy. Peter Prag examines the present position and the potential outlook.

Considering the normative, systemic and procedural dimensions in indicator-based sustainability assessments in agriculture

This paper develops a framework for evaluating sustainability assessment methods by separately analyzing their normative, systemic and procedural dimensions as suggested by Wiek and Binder [Wiek, A, Binder, C. Solution spaces for decision-making – a sustainability assessment tool for city-regions. Environ Impact Asses Rev 2005, 25: 589-608.]. The framework is then used to characterize indicator-based sustainability assessment methods in agriculture. For a long time, sustainability assessment in agriculture has focused mostly on environmental and technical issues, thus neglecting the economic and, above all, the social aspects of sustainability, the multifunctionality of agriculture and the applicability of the results. In response to these shortcomings, several integrative sustainability assessment methods have been developed for the agricultural sector. This paper reviews seven of these that represent the diversity of tools developed in this area. The reviewed assessment methods can be categorized into three types: (i) top-down farm assessment methods; (ii) top-down regional assessment methods with some stakeholder participation; (iii) bottom-up, integrated participatory or transdisciplinary methods with stakeholder participation throughout the process. The results readily show the trade-offs encountered when selecting an assessment method. A clear, standardized, top-down procedure allows for potentially benchmarking and comparing results across regions and sites. However, this comes at the cost of system specificity. As the top-down methods often have low stakeholder involvement, the application and implementation of the results might be difficult. Our analysis suggests that to include the aspects mentioned above in agricultural sustainability assessment, the bottomup, integrated participatory or transdisciplinary methods are the most suitable ones.

Normative, systemic and procedural aspects: a review of indicator‐based sustainability assessments in agriculture

Several methods for assessing the sustainability of agricultural systems have been developed. These methods do not fully: (i) take into account the multi‐functionality of agriculture; (ii) include multidimensionality; (iii) utilize and implement the assessment knowledge; and (iv) identify conflicting goals and trade‐offs. This paper reviews seven recently developed multidisciplinary indicator‐based assessment methods with respect to their contribution to these shortcomings. All approaches include (1) normative aspects such as goal setting, (2) systemic aspects such as a specification of scale of analysis, (3) a reproducible structure of the approach. The approaches can be categorized into three typologies. The top‐down farm assessments focus on field or farm assessment. They have a clear procedure for measuring the indicators and assessing the sustainability of the system, which allows for benchmarking across farms. The degree of participation is low, potentially affecting the implementation of the results negatively. The top‐down regional assessment assesses the on‐farm and the regional effects. They include some participation to increase acceptance of the results. However, they miss the analysis of potential trade‐offs. The bottom‐up, integrated participatory or transdisciplinary approaches focus on a regional scale. Stakeholders are included throughout the whole process assuring the acceptance of the results and increasing the probability of implementation of developed measures. As they include the interaction between the indicators in their system representation, they allow for performing a trade‐off analysis. The bottom‐up, integrated participatory or transdisciplinary approaches seem to better overcome the four shortcomings mentioned above.

RAMI4PILPS: An intercomparison of formulations for the partitioning of solar radiation in land surface models

[1] Remotely sensed, multiannual data sets of shortwave radiative surface fluxes are now available for assimilation into land surface schemes (LSSs) of climate and/or numerical weather prediction models. The RAMI4PILPS suite of virtual experiments assesses the accuracy and consistency of the radiative transfer formulations that provide the magnitudes of absorbed, reflected, and transmitted shortwave radiative fluxes in LSSs. RAMI4PILPS evaluates models under perfectly controlled experimental conditions in order to eliminate uncertainties arising from an incomplete or erroneous knowledge of the structural, spectral and illumination related canopy characteristics typical for model comparison with in situ observations. More specifically, the shortwave radiation is separated into a visible and near-infrared spectral region, and the quality of the simulated radiative fluxes is evaluated by direct comparison with a 3-D Monte Carlo reference model identified during the third phase of the Radiation transfer Model Intercomparison (RAMI) exercise. The RAMI4PILPS setup thus allows to focus in particular on the numerical accuracy of shortwave radiative transfer formulations and to pinpoint to areas where future model improvements should concentrate. The impact of increasing degrees of structural and spectral subgrid variability on the simulated fluxes is documented and the relevance of any thus emerging biases with respect to gross primary production estimates and shortwave radiative forcings due to snow and fire events are investigated.

Normative, systemic and procedural aspects: a review of indicator-based sustainability assessments in agriculture

Methods for assessing the sustainability of agricultural systems do often not fully (i) take into account the multifunctionality of agriculture, (ii) include multidimensionality, (iii) utilize and implement the assessment knowledge and (iv) identify conflicting goals and trade-offs. This chapter reviews seven recently developed multidisciplinary indicator-based assessment methods with respect to their contribution to these shortcomings. All approaches include (1) normative aspects such as goal setting, (2) systemic aspects such as a specification of scale of analysis and (3) a reproducible structure of the approach. The approaches can be categorized into three typologies: first, top-down farm assessments, which focus on field or farm assessment; second, top-down regional assessments, which assess the on-farm and the regional effects; and third, bottom-up, integrated participatory or transdisciplinary approaches, which focus on a regional scale. Our analysis shows that the bottom-up, integrated participatory or transdisciplinary approaches seem to better overcome the four shortcomings mentioned above.

How large is congressional dependence in agriculture. Bayesian inference about ‘scale’ and ‘scope’ in measuring a spatial externality

The political economy literature on agriculture emphasizes influence over political outcomes via lobbying conduits in general, political action committee contributions in particular and the pervasive view that political preferences with respect to agricultural issues are inherently geographic. In this context, ‘interdependence’ in Congressional vote behaviour manifests itself in two dimensions. One dimension is the intensity by which neighboring vote propensities influence one another and the second is the geographic extent of voter influence. We estimate these facets of dependence using data on a Congressional vote on the 2001 Farm Bill using routine Markov chain Monte Carlo procedures and Bayesian model averaging, in particular. In so doing, we develop a novel procedure to examine both the reliability and the consequences of different model representations for measuring both the ‘scale’ and the ‘scope’ of spatial (geographic) co-relations in voting behaviour.

A lagged response to the 11 year solar cycle in observed winter Atlantic/European weather patterns

The surface response to 11 year solar cycle variations is investigated by analyzing the long-term mean sea level pressure and sea surface temperature observations for the period 1870–2010. The analysis reveals a statistically significant 11 year solar signal over Europe, and the North Atlantic provided that the data are lagged by a few years. The delayed signal resembles the positive phase of the North Atlantic Oscillation (NAO) following a solar maximum. The corresponding sea surface temperature response is consistent with this. A similar analysis is performed on long-term climate simulations from a coupled ocean-atmosphere version of the Hadley Centre model that has an extended upper lid so that influences of solar variability via the stratosphere are well resolved. The model reproduces the positive NAO signal over the Atlantic/European sector, but the lag of the surface response is not well reproduced. Possible mechanisms for the lagged nature of the observed response are discussed.

Electronic commerce in agriculture and agribusiness: the case of Emilia-Romagna (Italy )

Despite the expectations of the benefits of this tool, the adoption of Electronic Commerce (EC) by small and medium firms of the agro-food sector in Italy is still not frequent, however, the understanding of opportunities it could create and how they can be exploited remains a relevant issue. This study, carried out in the Emilia -Romagna region during 2002, illustrates the results of a survey of 208 firms at all stages of the agro-food chain aimed at understanding the use of the Internet and the strategies adopted for EC implementation. The results show a low level of implementation of the instrument and a limited variety of adoption strategies. Agro-food firms actually invest very little in EC focusing their efforts on the Internet as promotion tool, while web-based direct selling is confined to market niches. The view that the Internet would reverse the disadvantages of small firms appears by now non realistic, even if interesting opportunities for further development are still present.

Organic contaminant content and physico-chemical characteristics of waste materials recycled in agriculture

A range of wastes representative of materials currently applied, or with future potential to be applied, to agricultural land in the UK as fertilisers and soil improvers or used as animal bedding in livestock production, were investigated. In addition to full physico-chemical characterization, the materials were analysed for a suite of priority organic contaminants. In general, contaminants were present at relatively low concentrations. For example, polychlorinated dibenzo-p-dioxins/dibenzofurans and polychlorinated biphenyls in biosolids and compost-like-outputs (CLOs) were, in most cases, between 5-50 times lower than proposed and implemented European limit values for biosolids or composts applied to agricultural land. However, the technical basis for these limits may need to be re-evaluated. Polybrominated, and mixed halogenated, dibenzo-p-dioxins/dibenzofurans are not currently considered in risk assessments of dioxins and dioxin-like chemicals, but were detected in the biosolids and compost-like-outputs and their potential contribution to the overall toxic equivalency will be assessed. Other, ‘emerging’ contaminants such as perfluoralkyl compounds (PFCs) and organophosphate flame retardants were detected in several of the waste materials, and their potential significance is discussed. The study is part of a wider research programme that will provide evidence to improve confidence in the use of waste-derived materials in agriculture and establish guidelines to protect the food chain where necessary.