Cameroon, Agriculture, Climate change, Policies, Food security,

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 food production. A methodology is applied where transient diagnostics of two atmosphere-ocean general circulation models, the NASA/Goddard Institute GISS and the British HadCM3, are coupled to a cropping system simulation model (CropSyst). This methodology simulates current and future (2020, 2080) crop yields for selected key crops such as bambara nut, groundnut, maize, sorghum, and soybean, in eight agricultural regions of Cameroon. Our results show that for the future, substantial yield increases are estimated for bambara groundnut, soybean and groundnut, while little or no change or even decreases for maize and sorghum yields, varying according to the climate scenario and the agricultural region investigated. Taking the "no regrets" principle into consideration, we also explore the advantages of specific adaptation strategies specifically for three crops, maize, sorghum and bambara groundnut, under GISS A2 and B2 marker scenarios only. Here, changing sowing dates may be ineffective in counteracting adverse climatic effects because of the narrow rainfall band that strictly determines the timing of farm operations in Cameroon. In contrast, the possibility of developing later maturing new cultivars proved to be very effective in offsetting adverse impacts, giving the highest increases in productivity under different scenario projections without management changes. For example, under climate change scenario GISS A2 2080, a 14.6% reduction in maize yield was converted to a 32.1% increase; a 39.9% decrease in sorghum yield was converted to a 17.6% increase, and for bambara groundnut, yields were almost trebled due to increase length of growing period and the positive effects of higher CO 2 concentrations. These results better inform wider studies and development strategies on sustainable agriculture in the area by providing an indication as to the potential direction in shifts in production capabilities. Our approach highlights the benefit of using models as tools to investigate potential climate change impacts, where results can supplement existing knowledge. The findings also provide useful guidance and motivation to public authorities and development agencies interested in food security issues in Cameroon and elsewhere.

The effects of interyear variability of extreme rainfall events on maize yields at locations in Cameroon, in central-west sub-Saharan Africa were investigated through a simulation assessment combining a weather generator with a crop growth model. This study analyzes the potential of using dry/wet year predictions to reduce risk in subsistence agricultural production associated with climate variability at the site level. Weather data sets from eight provincial study localities were classified into three precipitation scenarios -dry (lower threshold), normal and wet (upper threshold) years. According to the modelling results, there is a less than 12 per cent variance in mean maize yields across six out of the eight localities when planting occurs in March, May and August. The variance is equivalent to approximately 100-300 kg per ha, which represents a significant amount of food in the household security of the majority impoverished sectors of rural and urban society, and which could greatly impact the socioeconomic activities of the entire populace. The results lead to the conclusion that all extreme dry and wet years are not equal in terms of their regional manifestation. This calls for precise monthly and sub-seasonal local level forecasts and the effective dissemination of this information to farming communities in Cameroon, thereby facilitating the adaptive management of indigenous cropping practices and reducing their vulnerability to climate related disasters.

This study involves an assessment of the potential effects of greenhouse gas climate change, as well as the direct fertilization effect of CO 2 on crop yields in Cameroon. The methodology involves coupling the transient diagnostics of 2 atmosphere-ocean general circulation models, namely NASA/Goddard Institute GISS and the Hadley Centre's HadCM3, to the CropSyst crop model to simulate current and future (2020, 2080) crop yields (bambara nut, groundnut, maize, sorghum and soybean) in 8 agricultural regions of Cameroon. For the future we estimate substantial yield increases for bambara groundnut, soybean and groundnut, and little or no change and even decreases of maize and sorghum yields, varying according to the climate scenario and the agricultural region. Maize and sorghum (both C4 crops) yields are expected to decrease by 14.6 and 39.9%, respectively, across the whole country under GISS 2080 scenarios. The results also show that the effect of temperature patterns on climate change is much more important than that of precipitation. Findings call for monitoring of climate change/variability and dissemination of information to farmers, to encourage adaptation to climate change.KEY WORDS: Cameroon · Climate change · CO 2 · Crop yields · Adaptation · CropSyst Resale or republication not permitted without written consent of the publisherClim Res 36: [65][66][67][68][69][70][71][72][73][74][75][76][77] 2008 Though a few studies have been conducted to assess the impact of climate change on agriculture in developing countries (Seo et al. 2005, Adejuwon, 2006, Thornton et al. 2006, Kabubo-Mariara & Karanja 2007, there is a dearth of literature on this impact in Cameroon; thus the adaptation and mitigation measures that are available to policy makers are severely limited.The present study aims to partially address this research gap. It uses the coupled climate scenariocrop model method, in which coupled atmosphereocean general circulation models (A-OGCMs), used to generate future climate scenarios, are integrated into crop models in order to simulate future crop yields (Tubiello et al. 2000, Brassard & Singh 2007. The use of this method allows us to gain an insight not only into how future crop yields may change, but also into the nature of the factors responsible for yield changes, and how they may affect crop production. Understanding the impacts of long-term climate change on agriculture is crucial for future agricultural policies and interventions in Cameroon, as well as aiding practical steps to mitigate potentially adverse impacts of climate change, which is likely to have important implications for future food security.The general objective of this study is to examine the effects of long-term climate change on Cameroon crop agriculture and identify the adaptation options of agroecological systems using a simulation analysis. The specific objectives are to simulate and highlight the expected effects of various long-term climate change scenarios on future agricultural productivity and discuss policy ...

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