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Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa, which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

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Adaptation of agricultural and food systems to climate change involves private and public investment decisions in the face of climate and policy uncertainties. The authors present a framework for analysis of adaptation as an investment, based on elements of the economics, finance, and ecological economics literatures. They use this framework to assess critically impact and adaptation studies, and discuss how research could be designed to support public and private investment decisions. They then discuss how climate mitigation policies and other policies may affect adaptive capacity of agricultural and food systems. They conclude with an agenda for public research on climate adaptation.

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Specialty fruit crops represent a substantial portion of the value of agricultural production in the Pacific Northwest. Climate change may threaten water sources, lengthen the dry season, raise temperatures during both the winter chilling period and the growing season, and facilitate the spread of fungal diseases and insects. Such changes have the potential to substantially reduce net returns due to increased input costs and altered yields and product quality. Many management strategies that are already being used to prolong growing seasons in marginal production areas and to improve production and quality in established production regions may also be useful as adaptation strategies under a changing climate. These strategies mostly involve moderating temperatures and controlling or compensating for mismatches between phenology and seasonal weather conditions.

This article develops the conceptual and empirical basis for a class of empirical economic production models that can be linked to site-specific biophysical models for use in integrated assessment research. Site-specific data are used to estimate econometric production models, and these data and models are then incorporated into a simulation model that represents the decision-making process of the farmer as a sequence of discrete and continuous land-use and input-use decisions. An econometric-process model of the dryland grain production system of the Northern Plains demonstrates the capabilities of this type of model to simulate decision making both within and outside the range of observed data. Copyright 2001, Oxford University Press.

The purpose of this paper is to develop and apply a new method to assess economic potential for agricultural greenhouse gas mitigation. This method uses secondary economic data and conventional econometric production models, combined with estimates of soil carbon stocks derived from biophysical simulation models such as Century, to construct economic simulation models that estimate economic potential for carbon sequestration. Using this method, simulations for the central United States show that reduction in fallow and conservation tillage adoption in the wheat-pasture system could generate up to about 1.7 million MgC/yr, whereas increased adoption of conservation tillage in the corn-soy-feed system could generate up to about 6.2 million MgC/yr at a price of $200/MgC. About half of this potential could be achieved at relatively low carbon prices (in the range of $50 per ton). The model used in this analysis produced estimates of economic potential for soil carbon sequestration potential similar to results produced by much more data-intensive, field-scale models, suggesting that this simpler, aggregate modeling approach can produce credible estimates of soil carbon sequestration potential. Carbon rates were found to vary substantially over the region. Using average carbon rates for the region, the model produced carbon sequestration estimates within about 10% of those based on county-specific carbon rates, suggesting that effects of spatial heterogeneity