Abstract: Climate change impact assessments on agriculture are subject to large uncertainties, as demonstrated in the present review of recent studies for Africa. There are multiple reasons for differences in projections, including uncertainties in greenhouse gas emissions and patterns of climate change; assumptions on future management, aggregation, and spatial extent; and methodological differences. Still, all projections agree that climate change poses a significant risk to African agriculture. Most projections also see the possibility of increasing agricultural production under climate change, especially if suitable adaptation measures are assumed. Climate change is not the only projected pressure on African agriculture, which struggles to meet demand today and may need to feed an additional one billion individuals by 2050. Development strategies are urgently needed, but they will need to consider future climate change and its inherent uncertainties. Science needs to show how existing synergies between climate change adaptation and development can be exploited.

Abstract: Aphid-transmitted viruses frequently cause severe epidemics in lettuce grown under Mediterranean climates. Spatio-temporal dynamics of aphid-transmitted viruses and its vector were studied on lettuce (Lactuca sativa L.) grown under tunnels covered by two types of nets: a commercial UV-absorbing net (Bionet) and a Standard net. A group of plants infected by Cucumber mosaic virus (CMV, family Bromoviridae, genus Cucumovirus) and Lettuce mosaic virus (LMV, family Potyviridae, genus Potyvirus) was transplanted in each plot. The same virus-infected source plants were artificially infested by the aphid Macrosiphum euphorbiae (Thomas). Secondary spread of insects was weekly monitored and plants were sampled for the detection of viruses every two weeks. In 2008, the infection rate of both CMV and LMV were lower under the Bionet than under the Standard cover, probably due to the lower population density and lower dispersal rate achieved by M. euphorbiae. However, during spring of 2009, significant differences in the rate of infection between the two covers were only found for LMV six weeks after transplant. The spatial distribution of the viruses analysed by SADIE methodology was “at random”, and it was not associated to the spatial pattern of the vector. The results obtained are discussed analyzing the wide range of interactions that occurred among UV-radiation, host plant, viruses, insect vector and environmental conditions. Our results show that UV-absorbing nets can be recommended as a component of an integrated disease management program to reduce secondary spread of lettuce viruses, although not as a control measure on its own.

Abstract: A spatial resolution needs to be determined prior to using models to simulate crop yields at a regional scale, but a dilemma exists in compromising between different demands. A fine spatial resolution demands extensive computation load for input data assembly, model runs, and output analysis. A coarse spatial resolution could result in loss of spatial detail in variability. This paper studied the impact of spatial resolution, data aggregation and spatial heterogeneity of weather data on simulations of crop yields, thus providing guidelines for choosing a proper spatial resolution for simulations of crop yields at regional scale. Using a process-based crop model SIMPLACE (LINTUL2) and daily weather data at 1 km resolution we simulated a continuous rainfed winter wheat cropping system at the national scale of Germany. Then we aggregated the weather data to four resolutions from 10 to 100 km, repeated the simulation, compared them with the 1 km results, and correlated the difference with the intra-pixel heterogeneity quantified by an ensemble of four semivariogram models. Aggregation of weather data had small effects over regions with a flat terrain located in northern Germany, but large effects over southern regions with a complex topography. The spatial distribution of yield bias at different spatial resolutions was consistent with the intra-pixel spatial heterogeneity of the terrain and a log-log linear relationship between them was established. By using this relationship we demonstrated the way to optimize the model resolution to minimize both the number of simulation runs and the expected loss of spatial detail in variability due to aggregation effects. We concluded that a high spatial resolution is desired for regions with high spatial environmental heterogeneity, and vice versa. This calls for the development of multi-scale approaches in regional and global crop modeling. The obtained results require substantiation for other production situations, crops, output variables and for different crop models. (C) 2014 Elsevier B.V. All rights reserved.