Stanley Wood

Drivers of change in global agriculture

As a result of agricultural intensification, more food is produced today than needed to feed the entire world population and at prices that have never been so low. Yet despite this success and the impact of globalization and increasing world trade in agriculture, there remain large, persistent and, in some cases, worsening spatial differences in the ability of societies to both feed themselves and protect the long-term productive capacity of their natural resources. This paper explores these differences and develops a country×farming systems typology for exploring the linkages between human needs, agriculture and the environment, and for assessing options for addressing future food security, land use and ecosystem service challenges facing different societies around the world.

Generating Plausible Crop Distribution Maps for Sub-Saharan Africa Using a Spatial Allocation Model

Agricultural production statistics are fundamental parameters for agriculture policy research. Information on acreage and yields of important crops is critical for understanding trends within what is the most important economic sector of many developing countries. Sub-national data — i.e. data organized by administrative units such as regions or districts — enable the analysis of patterns within countries that may highlight important policy issues, such as the need to allocate resources to underproductive areas. However, collecting sub-national data is difficult for developing countries with limited resources. Even with great effort, and often only on broad regional scales, enormous data gaps exist and are unlikely to be filled. As a result, information is often only available at national or very broad sub-national levels (such as provinces). Such geographically coarse data are unable to reflect important variations within countries and are insufficient for the spatial analysis of production patterns and trends. To fill these spatial data gaps we developed a model to disaggregate production data from coarser to finer spatial units. Using a cross-entropy approach, our spatial allocation model attempts to make plausible allocations of crop production from large reporting units such as a country or state, into smaller spatial units organized as cells of a regularly-spaced grid. In addition to more detailed information, the organization of production information in geographic grids allows for greater analytical possibilities through geographic information systems. The allocation model works on the basis of available evidence of mapped indicators of agricultural production, which include farming systems, land cover, crop biophysical suitability surfaces, commodity prices and local market access. This article describes the generation of crop distribution maps for Sub-Saharan Africa for the year 2000 using the spatial allocation model and discusses the importance of such maps for development analysis and planning.

Reanalysis of a global soil database for crop and environmental modeling

There is an increased need for detailed soil information that can be used for applications of crop and environmental modeling. The goal of this project was to conduct a reanalysis of the ISRIC-WISE 1.1 Soil Profile Dataset. As part of the procedures, the soil reanalysis database was fitted to the standard formats of the International Consortium for Agricultural Systems Application (ICASA). Thus, the soil reanalysis database tailors dynamic crop models such as the Cropping System Model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT). During the reanalysis, the physical and chemical parameters of the soil profiles were revised and estimated, where necessary and possible, using pre-established ranges given by the literature and correlations among other more stable variable. To evaluate each of the 3404 reanalyzed soil profiles, the CSM-CERES-Maize model was run for a standard crop management scenario using both the original and the new improved soil databases. Nine hundred seventy-eight soil profiles were considered to be not useful during the reanalysis due to missing values for one or more critical variables and were, therefore, not considered for quality control procedures. A pre-diagnostic for only nitrogen and soil organic carbon in the original dataset showed 70% and 5% of missing values respectively. A sensitivity analysis based on crop simulations comparing the original and the reanalyzed soil databases, showed that 1294 soil profiles yielded different results due to improvement of either the original data or improved conversion procedures. The details and considerations for detecting missing and erroneous values and for estimating soil variable values are presented in this paper for further use. The final soil reanalysis global database contains 3404 soil profiles and is available at https://harvestchoice.wufoo.com/forms/download-wisol.

A Comparative Analysis of Global Cropping Systems Models and Maps

This study aims to explore and quantify systematic similarities and differences between four major global cropping systems products: the dataset of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000), the spatial production allocation model (SPAM), the global agroecological zone (GAEZ) dataset, and the M3 dataset developed by Monfreda, Ramankutty, and Foley. The analysis explores not only the final cropping systems maps but also the interdependencies of each product, methodological differences, and modeling assumptions, which will provide users with information vital for discerning between datasets in selecting a product appropriate for each intended application.

Agroecological aspects of evaluating agricultural R&D

Abstract In this paper we describe how biophysical data can be used, in conjunction with agroecological concepts and multimarket economic models, to systematically evaluate the effects of agricultural R&D in ways that inform research priority setting and resource-allocation decisions. Agroecological zones can be devised to help estimate the varying, site-specific responses to new agricultural technologies and to evaluate the potential for research to spill over from one agroecological zone to another. The application of agroecological zonation procedures in an international, agricultural-research context is given special attention, and we propose tailoring the zones to the R&D being evaluated.

SPATIAL PATTERNS OF CROP YIELDS IN LATIN AMERICA AND THE CARIBBEAN

Because of the apparent slowdown in the growth of crop yield potential, the increasing share of farmers already using modern crop varieties, and the accelerating flow of knowledge on agricultural technology, one would expect to find gradual convergence in

From science to technology adoption: the role of policy research in improving natural resource management

Abstract GCTE3 science seeks to predict the effects of global change on agriculture, forestry and soils. Better understanding the response of these ecological systems, it is argued, will enable society to better ameliorate, adapt to, and even benefit from, the forces of global change. The argument presented in this paper, however, is that the response of managed ecosystems can only be understood by treating likely human response to global change as an integral part of the research agenda. Linking science and policy research matters because the adoption of technologies for improved natural resource management, or of other interventions that scientific research may help design, is conditioned by socio-economic factors that policy research is better equipped to articulate. The paper first discusses how natural resource management and technology adoption are influenced by policy factors. It then explores why science — including GCTE — research needs to be linked to policy research. The reasons include: (a) that understanding biophysical processes is necessary but insufficient to understanding the socio-economic consequences of global change; (b) that the design of interventions to ameliorate negative and foster positive change at a global scale depends on gauging the likely human behavioral responses to change; (c) that although global impacts arise from an accumulation of local changes, interventions are often best coordinated in an international forum where the interests of potential “winners” and “losers” can best be matched. Different (winner and loser) nations have different policy stances on the underlying promoters of change, e.g., population growth, carbon emissions, biodiversity loss, etc. Failure to understand the (often economic) incentives underlying the “business-as-usual” position of many countries can hamper progress, even if the scientific arguments are compelling. The paper also assesses how best to link GCTE science research and policy research. Researchers need to be: (a) concerned at many scales, from local to global; (b) able to predict and allow for the influences of technical change; (c) able to model biophysical processes and behavioral norms and responses in an integrated way. Interactive models in which biophysical processes impact on human behavioral response and vice versa are increasingly required. Even where land use and socio-economic models are not formally linked, significant gains may be made from multidisciplinary approaches and information exchange that develop common scenarios under which biophysical and economic analyses are made separately, but at least in complementary ways.