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Lardy, R., Bellocchi, G., & Martin, R. (2015). Vuln-Indices: Software to assess vulnerability to climate change. Computers and Electronics in Agriculture, 114, 53–57.
Abstract: Vuln-Indices Java-based software was developed on concepts of vulnerability to climate change of agro-ecological systems. It implements the calculation of vulnerability indices on series of state variables for assessments at both site and region levels. The tool is useful because synthetic indices help capturing complex processes and prove effective to identify the factors responsible for vulnerability and their relative importance. It is suggested that the tool may be plausible for use with stakeholders to disseminate information of climate change impacts. (C) 2015 Elsevier B.V. All rights reserved.
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Watson, J., Challinor, A. J., Fricker, T. E., & Ferro, C. A. T. (2015). Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model. Clim. Change, 132(1), 93–109.
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.
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Ferrise, R., Toscano, P., Pasqui, M., Moriondo, M., Primicerio, J., Semenov, M. A., et al. (2015). Monthly-to-seasonal predictions of durum wheat yield over the Mediterranean Basin. Clim. Res., 65, 7–21.
Abstract: Uncertainty in weather conditions for the forthcoming growing season influences farmers’ decisions, based on their experience of the past climate, regarding the reduction of agricultural risk. Early within-season predictions of grain yield can represent a great opportunity for farmers to improve their management decisions and potentially increase yield and reduce potential risk. This study assessed 3 methods of within-season predictions of durum wheat yield at 10 sites across the Mediterranean Basin. To assess the value of within-season predictions, the model SiriusQuality2 was used to calculate wheat yields over a 9 yr period. Initially, the model was run with observed daily weather to obtain the reference yields. Then, yield predictions were calculated at a monthly time step, starting from 6 mo before harvest, by feeding the model with observed weather from the beginning of the growing season until a specific date and then with synthetic weather constructed using the 3 methods, historical, analogue or empirical, until the end of the growing season. The results showed that it is possible to predict durum wheat yield over the Mediterranean Basin with an accuracy of normalized root means squared error of <20%, from 5 to 6 mo earlier for the historical and empirical methods and 3 mo earlier for the analogue method. Overall, the historical method performed better than the others. Nonetheless, the analogue and empirical methods provided better estimations for low-yielding and high-yielding years, thus indicating great potential to provide more accurate predictions for years that deviate from average conditions.
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Dáder, B., Plaza, M., Fereres, A., & Moreno, A. (2015). Flight behaviour of vegetable pests and their natural enemies under different ultraviolet-blocking enclosures. Ann. Appl. Biol., 167(1), 116–126.
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.
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Cortignani, R., & Dono, G. (2015). Simulation of the impact of greening measures in an agricultural area of the southern Italy. Land Use Policy, 48, 525–533.
Abstract: Together, sustainable management of natural resources and climate action form one of the three objectives of the 2014-2020 Common Agricultural Policy. This objective is being addressed by replacing the existing direct payments under Pillar 1 with a basic payment, combined with an additional payment conditional on farmers undertaking agricultural practices beneficial for the climate and the environment, a policy referred to as greening. In this study, the impact of greening was assessed using a hybrid model calibrated using positive mathematical programming. The model describes the macro-types of farm production in a Mediterranean agricultural area. The results show that greening was not beneficial throughout the study area and only some farm types have been particularly affected. However, greening appears to have a positive impact on curtailing the use of chemicals, particularly nitrogen, and on crop diversity. (C) 2015 Elsevier Ltd. All rights reserved.
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