Abstract: Ultraviolet (UV) radiation, particularly in the UV-A + B range (280-400 nm) is a fraction of the solar spectrum that regulates almost every aspect of insect behaviour, including orientation towards hosts, alighting, arrestment and feeding behaviour. To study the role of UV radiation on the flight activity of five insect species of agricultural importance (pests Myzus persicae, Bemisia tabaci and Tuta absoluta, and natural enemies Aphidius colemani and Sphaerophoria rueppellii), one-chamber tunnels were covered with six cladding materials with different light transmittance properties ranging from 2% to 83% UV and 54% to 85% photosynthetically active radiation (PAR). Inside each tunnel, insects were released from tubes placed in a platform suspended from the ceiling. Specific targets varying with insect species were placed at different distances from the platform. Evaluation parameters were designed for each insect and tested separately. The ability of insects to leave the platform was assessed, as well as the number of captures, eggs or mummies in each target, either sticky traps or plants. Our results suggest differences in flight activity among insect species and UV-blocking nets. The UV-opaque film drastically prevented aphids, and whiteflies from flying outside the tubes whereas T. absoluta, syrphids and parasitoids were not affected. Aphid flight behaviour was affected by the UV-opaque film compared to the other nets, especially in the furthest target of the tunnel. Fewer aphids reached distant traps under UV-absorbing nets, and significantly more aphids could fly to the end of tunnels covered with non-UV-blocking materials. Orientation of B. tabaci and T. absoluta was also negatively affected by the UV-opaque film although in a different trend. Unlike aphids, differences in B. tabaci captures were mainly found in the closest targets. UV transmittance did not have any effects on parasitoids, and S. rueppellii, implying cues other than visual for these insects under our experimental conditions. Further effects of photoselective enclosures on greenhouse pests and their natural enemies are discussed.

Abstract: Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

Abstract: Land-use change, mainly the conversion of tropical forests to agricultural land, is a massive source of carbon emissions and contributes substantially to global warming(1-3). Therefore, mechanisms that aim to reduce carbon emissions from deforestation are widely discussed, A central challenge is the avoidance of international carbon leakage if forest conservation is not implemented globally’’, Here, We show that forest conservation schemes, even if implemented globally, could lead to another type of carbon leakage by driving cropland expansion in non-forested areas that are not subject to forest conservation schemes (non-forest leakage). These areas have a smaller. but still considerable potential to store carbon(5,6). We show that a global forest policy could reduce carbon emissions by 77 Gt CO2, but would still allow for decreases in carbon stocks of non-forest land by 96 Gt CO2, until 2100 due to non-forest leakage effects. Furthermore; abandonment of agricultural hand and associated carbon uptake through vegetation regrowth is hampered. Effective mitigation measures thus require financing structures and conservation investments that cover the full range of carbon-rich ecosystems. However, our analysis indicates that greater agricultural productivity increases would be needed to compensate for such restrictions on agricultural expansion.