M. Rivington

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This paper argues that an integrated assessment (IA) approach, combining simulation modelling with deliberative processes involving decision makers and other stakeholders, has the potential to generate credible and relevant assessments of climate change impacts on farming systems. The justification for the approach proposed is that while simulation(More)
The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop(More)
The potential of mathematical models is widely acknowledged for examining components and interactions of natural systems, estimating the changes and uncertainties on outcomes, and fostering communication between scientists with different backgrounds and between scientists, managers and the community. For favourable reception of models, a systematic accrual(More)
Meteorological station records often consist only of precipitation and air temperature data. There is therefore a need for appropriate methods to estimate solar radiation data to enable complete data set creation, by combining observed and estimated data. It is important to know the quality and characteristics of the estimates made in order to understand(More)
The Cameroonian agricultural sector, a critical part of the local ecosystem, is potentially vulnerable to climate change, thus raising concerns about food security in the country’s future. Adaptations policies may be able to mitigate some of this vulnerability. This article addresses the issue of selected adaptation options within the context of Cameroonian(More)
This paper continues a series of reflections on the challenges of developing and deploying decision and information systems (DIST) for environmental management. Our focus is on the additional challenges being posed by funders to evaluate the outcomes (changes in the world beyond the research institute). This is a significant raising of the bar for DIST,(More)
Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan 2 Department of Geosciences, Idaho State University, USA 3 Grassland Ecosystem Research Unit, French National Institute for Agricultural Research, Clermont-Ferrand, France UCD Centre for Water Resources Research, University College Dublin, Ireland(More)
Agricultural decision support systems (DSS) may be argued to have passed sequentially through phases of unbelief, euphoria and disappointment and to be passing into either a phase of maturity with realistic expectations of the technology or to abandonment. This paper proposes that agricultural DSS in their widest sense still have a significant role to play(More)
The use of biophysical models in agroecology has increased in the last few decades for two main reasons: the need to formalize empirical knowledge and the need to disseminate model-based decision support for decision makers (such as farmers, advisors, and policy makers). The first has encouraged the development and use of mathematical models to enhance the(More)