Peter G. Jones

The potential impacts of climate change on maize production in Africa and Latin America in 2055

The impacts of climate change on agriculture may add significantly to the development challenges of ensuring food security and reducing poverty. We show the possible impacts on maize production in Africa and Latin America to 2055, using high-resolution methods to generate characteristic daily weather data for driving a detailed simulation model of the maize crop. Although the results indicate an overall reduction of only 10% in maize production to 2055, equivalent to losses of

Agriculture and food systems in sub-Saharan Africa in a 4°C+ world

2 billion per year, the aggregate results hide enormous variability: areas can be identified where maize yields may change substantially. Climate change urgently needs to be assessed at the level of the household, so that poor and vulnerable people dependent on agriculture can be appropriately targetedin research andd evelopment activities whose object is poverty alleviation. r 2003 Elsevier Science Ltd. All rights reserved.

The use of geographical information systems in biodiversity exploration and conservation

Agricultural development in sub-Saharan Africa faces daunting challenges, which climate change and increasing climate variability will compound in vulnerable areas. The impacts of a changing climate on agricultural production in a world that warms by 4°C or more are likely to be severe in places. The livelihoods of many croppers and livestock keepers in Africa are associated with diversity of options. The changes in crop and livestock production that are likely to result in a 4°C+ world will diminish the options available to most smallholders. In such a world, current crop and livestock varieties and agricultural practices will often be inadequate, and food security will be more difficult to achieve because of commodity price increases and local production shortfalls. While adaptation strategies exist, considerable institutional and policy support will be needed to implement them successfully on the scale required. Even in the 2°C+ world that appears inevitable, planning for and implementing successful adaptation strategies are critical if agricultural growth in the region is to occur, food security be achieved and household livelihoods be enhanced. As part of this effort, better understanding of the critical thresholds in global and African food systems requires urgent research.

A rainfall generator for agricultural applications in the tropics

We describe a method for applying geographical information systems (GIS) to exploring biodiversity in the wild relatives of crop species and illustrate its application to the wild common bean (Phaseolus vulgaris L.). We use the latitude, longitude and altitude of the location of origin of each accession in a germplasm collection of wild P. vulgaris, along with long-term monthly mean values of rainfall, temperature and diurnal temperature range for about 10000 stations throughout Latin America to produce maps indicating areas with ‘bean-favouring’ climates. In a test case, these identify a new suitable area in Colombia where wild P. vulgaris has been reported in the literature, and two more areas which are strong candidates on other grounds. Dividing the ‘bean-favouring’ climates into clusters identifies areas that have similar climates but are geographically remote, where we can expect to find wild beans with similar ecological adaptation. We discuss the implications of these results for conserving and improving the common bean, and the application of these methods to other species.

Spatial and temporal variability of rainfall related to a third-order Markov model

Abstract A new rainfall generator, based on a third-order Markov chain, has been developed to simulate the year-to-year variation in rainfall amount that is observed in the tropics. To do this, some of the parameters of the model are themselves sampled randomly. The model has been fitted to over 40 sites in the tropics. The model was tested in detail for three sites in Central and South America and in the African Sahel. Few significant differences were found between the historical and simulated means and variances of yearly and monthly rainfall amount and raindays per month. There were some problems with simulating wet and dry sequences of longer than 9 days. When historical and simulated rainfall records were used to drive a crop simulation model, there was no significant difference in the mean and variance of maize yield response. The results reported suggest that the rainfall model performs adequately for many applications.

Fitting a third-order Markov rainfall model to interpolated climate surfaces

Abstract Many types of analysis require rainfall data, which must often be generated to overcome limitations in the historical record. The ability to model outlying rainfall years satisfactorily is particularly important in risk studies. We describe a rainfall generator with this ability, based on a third-order Markov process, and we show how the fitted parameters of the model vary for an illustrative sample of 18 sites with highly contrasting climates. Some of the parameters of the model show patterns that are characteristic of the climate type. The model should thus be suitable for interpolating rainfall data where they do not exist. We also fitted the model to subsets of some long data records to illustrate the marked changes in rainfall characteristics that have occurred in some locations over the last 70 years, and to help understand the nature of these changes.

A conceptual approach to dynamic agricultural land-use modelling

Abstract We describe a procedure to link a third-order Markov rainfall model to interpolated monthly mean climate surfaces. Such preliminary surfaces have been constructed for Africa and Latin America and these allow a user to generate daily weather data (rainfall, temperatures and solar radiation) that can be used for purposes of system characterisation and to drive a wide variety of crop and livestock production and ecosystem models. For applications with a time resolution of a few weeks or a growing season, the surfaces described already have substantial utility. We present indicators of reliability both spatially, in map form, and as summaries of goodness of fit for the model parameters. We test the surfaces for goodness of fit for three contrasting sites in the tropics and identify refinements to improve the interpolation methodology.

Simulation of the phenology of soybeans

Abstract We describe a dynamic agricultural land-use model based on a Markov process and governed by a few simple decision rules. Currently, the model is purely conceptual, and was designed with one objective: to investigate the possibility of constructing top-down land-use models based on as few processes as possible that might still be useful for statistical analyses of landuse change in a region. The model appears to behave in a plausible fashion in a simulated landscape with respect to cropping patterns and the effects of initial household size on wealth distribution. If this type of simple model could be validated, the information that could be produced might be of considerable value in a wide range of applications, particularly with regard to technology adoption patterns and resultant regional production impacts.

Identifying climatically suitable areas for growing particular trees in Latin America

Abstract Simulation models of three phases of soybean phenology—sowing to primary leaf, primary leaf to flower initiation and flower initiation to flowering—were generated for the soybean cultivar Lee and others. The basic experimental data were obtained from a series of glasshouse experiments under six temperature regimes in natural light. The data for leaf development rates showed a change in the response to temperature at the first trifoliate leaf stage; this was incorporated into the model. The flower initiation model included parameters for the production and decay of a theoretical flower promoter and for the rate of change of daylength. Time to flower initiation showed a complex relationship to photoperiod which could not be described or approximated to by any simple function. The effects of temperature were marked and showed a strong interaction with photoperiod. The flower development model accounted for a strong temperature response which was conditioned by a photoperiod effect. The three models were combined to form a soybean phenology model which was validated against phenological data obtained from date of sowing experiments conducted under field conditions.

Spatial modeling of risk in natural resource management

Abstract Six climatic factors important for tree species selection were calculated from monthly mean values of maximum temperature, minimum temperature and precipitation estimated for 66,688 locations in a 10-min (18.5 km approx.) grid across Latin America. These included measures such as mean annual temperature, mean maximum temperature of the hottest month, mean annual precipitation and rainfall regime. Three microcomputer programs were written to enable the database to be interrogated for Latin America as a whole, and also for the northern and southern regions. The use of the programs is demonstrated with Acacia mearnsii, Eucalyptus camaldulensis (northern provenances) and Pinus radiata. It is concluded that the programs can assist identifying climatically suitable areas for these trees and also assist developing improved descriptions of climatic requirements for other species and provenances.