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Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales.

SUMMARYEthiopia is one of the countries most vulnerable to the impacts of climate variability and change on agriculture. The present study aims to understand and characterize agro-climatic variability and changes and associated risks with respect to implications for rainfed crop production in the Central Rift Valley (CRV). Temporal variability and extreme values of selected rainfall and temperature indices were analysed and trends were evaluated using Sen's slope estimator and Mann–Kendall trend test methods. Projected future changes in rainfall and temperature for the 2080s relative to the 1971–90 baseline period were determined based on four General Circulation Models (GCMs) and two emission scenarios (SRES, A2 and B1). The analysis for current climate showed that in the short rainy season (March–May), total mean rainfall varies spatially from 178 to 358 mm with a coefficient of variation (CV) of 32–50%. In the main (long) rainy season (June–September), total mean rainfall ranges between 420 and 680 mm with a CV of 15–40%. During the period 1977–2007, total rainfall decreased but not significantly. Also, there was a decrease in the number of rainy days associated with an increase (statistically not significant) in the intensity per rainfall event for the main rainy season, which can have implications for soil and nutrient losses through erosion and run-off. The reduced number of rainy days increased the length of intermediate dry spells by 0·8 days per decade, leading to crop moisture stress during the growing season. There was also a large inter-annual variability in the length of growing season, ranging from 76 to 239 days. The mean annual temperature exhibited a significant warming trend of 0·12–0·54 °C per decade. Projections from GCMs suggest that future annual rainfall will change by +10 to −40% by 2080. Rainfall will increase during November–December (outside the growing season), but will decline during the growing seasons. Also, the length of the growing season is expected to be reduced by 12–35%. The annual mean temperature is expected to increase in the range of 1·4–4·1 °C by 2080. The past and future climate trends, especially in terms of rainfall and its variability, pose major risks to rainfed agriculture. Specific adaptation strategies are needed for the CRV to cope with the risks, sustain farming and improve food security.

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions-the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers' perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers' perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.