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Agriculture in the semi-arid regions of West Africa is mainly rain-fed with a large number of smallholder farmers dependent on it for their livelihoods. Farming systems are dominated by cereals and legumes with livestock playing a significant role in the functioning of the systems. In this paper, we use the AgMIP Regional Integrated Assessment methods, which include a set of mid-century climate projections, biophysical (Decision Support Systems for Agro-technological Transfer; DSSAT and Agricultural Production Systems sIMulator; APSIM) and economic (trade-off analysis model: TOA-MD) models, representative agricultural pathways and global economic model projections to explore the impacts of climate change on the economic vulnerability of farm households in Nioro, Senegal. Our results indicate that most climate scenarios -except the hot-dry had positive impacts on peanuts which is one of the main crops in this production system. The effect of climate change on maize was negative and the impacts on millet were variable but changes are small. In tomorrow's production systems and socio-economic conditions, climate change would have positive impact on Nioro farmers livelihoods in almost all cases simulated. However, with low prices, climate change would have a negative impact of Nioro farmers' livelihoods in most cases. For Senegal, these results have significant policy implications, in particular on international trade and regional prices as peanut is one of the major export commodities.

Difference between 2.0 °C and 1.5 °C on rainfed maize with (left) and without (right) CO2 effects for three global gridded crop models (pDSSAT, GEPIC, LPJmL).

The production of cereals in West Africa is constraint by several yield limiting factors such as poor soil fertility and erratic rainfall distributions and is largely dominated by smallholder farmers. Projected changes in climate thus poses a threat since crop production is mainly rainfed. In this study, two crop models; Decision Support System for Agro-technological Transfer (DSSAT) and Agricultural Production Systems sIMulator (APSIM) were calibrated, evaluated and used to quantify climate change impact on the yield of maize, sorghum and millet under future production systems in Nioro, Senegal and Navrongo, Ghana. Data on management practices (sowing dates, time and amount of fertilizer) obtained from household surveys, soil data, weather data (historical; 1980-2009 and 5 Global Circulation Models (GCMs); Mid Century time slice 2040 – 2069 for two representative concentration Pathway (RCP); 4.5 and 8.5) were used for the impact assessment. Temperatures were projected to increase in both study areas with higher temperatures for Nioro. Change in total rainfall amounts varied in Nioro with rains in Navrongo to remain same or increase slightly. Ensembled maize yield changes under RAP 4 were between -22 to -1% in Nioro, and -19 to 0 in Navrongo for DSSAT and APSIM respectively. The impact of climate change on sorghum and millet were lower than those of maize. Yield reductions under RAP 5 were generally higher than under RAP 4. The extent of yield loss varied among households due to differences in management practices and soils. There is need to explore potential adaptations to reduce yield loses.

In the semi-arid region of the Sahel, climate change is already affecting the farming systems and these impacts are expected to heighten in the near to mid-century. Given the complexities and conflicting drivers at play and the foreseeable negative consequences on the livelihoods of the majority of farmers, it is worthwhile designing relevant adaptation packages that will alleviate these effects. In this study, we envision to assess the implications of implementing two adaptation packages within the context of three West African farming systems specifically located in Ghana (Navrongo), Mali (Koutiala) and Senegal (Nioro). The first adaptation package is composed of heat and drought tolerant species along with an economic and policy level intervention through the delivery of subsidies to acquire improved varieties. The second pack builds on the first but adds a fertilizer component (splitting and timing to account for extreme events) and a policy variable in the form of index-based insurance adoption. The design process included interactions with a diverse set of stakeholders. The outcomes of these adaptation options on current and future agricultural systems will shed light on the projected adoption rates of climate adapted-systems and show how these various adaptations affect the impacts of climate change, keeping congruence with the relevant representative agricultural pathways. (Texte intégral)

An integrated modelling framework is used to simulate crop productivity for current and future climate scenarios. Two crop models, Decision Support Systems for Agro-Technological Transfer (DSSAT) and the Agricultural Productions Systems sIMulator (APSIM), were calibrated and evaluated for the study site in Koutiala, Mali, simulating yields of maize, millet, and peanut for 123 households. These crop models are fed by weather data from baseline climate (1980-2009) from observed weather and future climate (2040-2069) from 5 Global Circulation Models (GCMs) were used as inputs to crop models. The models' results differ according to the crop considered. For maize, there is a decrease of grain yield across all GCMs and crop models. For sorghum, there is a slight decrease across GCMs with DSSAT, but the grain yield remains constant on average with APSIM. For peanut and millet, the results are more optimistic and grain yield increases across all cases. These outputs will then be linked to the economical the Trade-Off Analysis-Minimum Data model (TOA-MD) to assess impacts on farmer livelihoods. Further, adaptation strategies (e.g. drought and heat tolerant cultivars) will be simulated to assess their potential impact for the future. (Texte intégral)

An important component of the farming system in Ghana is livestock production. Livestock, especially cattle production is heavily dependent on rainfall for the production of forages to feed them. Projected increase in temperature and shifts in rainfall patterns due to climate change is expected to affect the level of livestock production and livelihood of the resource poor animal herders in Ghana. To gain insight into the livestock-climate nexus, we conducted a study in Tamale in the Northern region of Ghana to parameterize the LivSim (Livestock Simulator) model for the simulation of growth of the Ghana Shorthorn cattle. The main objective was to quantify milk and calf production by the various smallholder farmers in the community. A survey of 261 households out of which 96 owned livestock was conducted to obtain observed data on milk yield, calving frequencies, among others. Other data required by LivSIM such as the minimum and maximum bodyweights of both male and female Ghana Shorthorn were obtained from the literature. The number of cattle owned by the households interviewed ranged from 2-47 with majority having a herd size less than twelve. The herd composition was estimated to be 72% female and 28% male. Preliminary simulation results showed that the herd dynamics could be well captured for an initial period of 5 years, after which there was divergence between the simulated and the observed. Further current efforts are directed to the improvement in parameter values especially those relating to the potential growth rates and the compensatory growth rate.