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Lopes, M. S., El-Basyoni, I., Baenziger, P. S., Singh, S., Royo, C., Ozbek, K., et al. (2015). Exploiting genetic diversity from landraces in wheat breeding for adaptation to climate change. J. Experim. Bot., 66(12), 3477–3486.
Abstract: Climate change has generated unpredictability in the timing and amount of rain, as well as extreme heat and cold spells that have affected grain yields worldwide and threaten food security. Sources of specific adaptation related to drought and heat, as well as associated breeding of genetic traits, will contribute to maintaining grain yields in dry and warm years. Increased crop photosynthesis and biomass have been achieved particularly through disease resistance and healthy leaves. Similarly, sources of drought and heat adaptation through extended photosynthesis and increased biomass would also greatly benefit crop improvement. Wheat landraces have been cultivated for thousands of years under the most extreme environmental conditions. They have also been cultivated in lower input farming systems for which adaptation traits, particularly those that increase the duration of photosynthesis, have been conserved. Landraces are a valuable source of genetic diversity and specific adaptation to local environmental conditions according to their place of origin. Evidence supports the hypothesis that landraces can provide sources of increased biomass and thousand kernel weight, both important traits for adaptation to tolerate drought and heat. Evaluation of wheat landraces stored in gene banks with highly beneficial untapped diversity and sources of stress adaptation, once characterized, should also be used for wheat improvement. Unified development of databases and promotion of data sharing among physiologists, pathologists, wheat quality scientists, national programmes, and breeders will greatly benefit wheat improvement for adaptation to climate change worldwide.
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Biewald, A., Lotze-Campen, H., Otto, I., Brinckmann, N., Bodirsky, B., Weindl, I., et al. (2015). The Impact of Climate Change on Costs of Food and People Exposed to Hunger at Subnational Scale (Vol. 128). Potsdam.
Abstract: Climate change and socioeconomic developments will have a decisive impact on people exposed to hunger. This study analyses climate change impacts on agriculture and potential implications for the occurrence of hunger under different socioeconomic scenarios for 2030, focusing on the world regions most affected by poverty today: the Middle East and North Africa, South Asia, and Sub-Saharan Africa. We use a spatially explicit, agroeconomic land-use model to assess agricultural vulnerability to climate change. The aims of our study are to provide spatially explicit projections of climate change impacts on Costs of Food, and to combine them with spatially explicit hunger projections for the year 2030, both under a poverty, as well as a prosperity scenario. Our model results indicate that while average yields decrease with climate change in all focus regions, the impact on the Costs of Food is very diverse. Costs of Food increase most in the Middle East and North Africa, where available agricultural land is already fully utilized and options to import food are limited. The increase is least in Sub-Saharan Africa, since production there can be shifted to areas which are only marginally affected by climate change and imports from other regions increase. South Asia and Sub-Saharan Africa can partly adapt to climate change, in our model, by modifying trade and expanding agricultural land. In the Middle East and North Africa, almost the entire population is affected by increasing Costs of Food, but the share of people vulnerable to hunger is relatively low, due to relatively strong economic development in these projections. In Sub-Saharan Africa, the Vulnerability to Hunger will persist, but increases in Costs of Food are moderate. While in South Asia a high share of the population suffers from increases in Costs of Food and is exposed to hunger, only a negligible number of people will be exposed at extreme levels. Independent of the region, the impacts of climate change are less severe in a richer and more globalized world. Adverse climate impacts on the Costs of Food could be moderated by promoting technological progress in agriculture. Improving market access would be advantageous for farmers, providing the opportunity to profitably increase production in the Middle East and North Africa as well as in South Asia, but may lead to increasing Costs of Food for consumers. In the long-term perspective until 2080, the consequences of climate change will become even more severe: while in 2030 56% of the global population may face increasing Costs of Food in a poor and fragmented world, in 2080 the proportion will rise to 73%.
Keywords: ftnotmacsur
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Tao, F., Roetter, R. P., Palosuo, T., Diaz-Ambrona, C. G. H., Ines Minguez, M., Semenov, M. A., et al. (2017). Designing future barley ideotypes using a crop model ensemble. Europ. J. Agron., 82, 144–162.
Abstract: Climate change and its associated higher frequency and severity of adverse weather events require genotypic adaptation. Process-based ecophysiological modelling offers a powerful means to better target and accelerate development of new crop cultivars. Barley (Hordeum vulgare L) is an important crop throughout the world, and a good model for study of the genetics of stress adaptation because many quantitative trait loci and candidate genes for biotic and abiotic stress tolerance have been identified in it. Here, we developed a new approach to design future crop ideotypes using an ensemble of eight barley simulation models (i.e. APSIM, CropSyst, HERMES, MCWLA, MONICA, SIMPLACE, Sirius Quality, and WOFOST), and applied it to design climate-resilient barley ideotypes for Boreal and Mediterranean climatic zones in Europe. The results showed that specific barley genotypes, represented by sets of cultivar parameters in the crop models, could be promising under future climate change conditions, resulting in increased yields and low inter-annual yield variability. In contrast, other genotypes could result in substantial yield declines. The most favorable climate-zone-specific barley ideotypes were further proposed, having combinations of several key genetic traits in terms of phenology, leaf growth, photosynthesis, drought tolerance, and grain formation. For both Boreal and Mediterranean climatic zones, barley ideotypes under future climatic conditions should have a longer reproductive growing period, lower leaf senescence rate, larger radiation use efficiency or maximum assimilation rate, and higher drought tolerance. Such characteristics can produce substantial positive impacts on yields under contrasting conditions. Moreover, barley ideotypes should have a low photoperiod and high vernalization sensitivity for the Boreal climatic zone; for the Mediterranean, in contrast, it should have a low photoperiod and low vernalization sensitivity. The drought-tolerance trait is more beneficial for the Mediterranean than for the Boreal climatic zone. Our study demonstrates a sound approach to design future barley ideotypes based on an ensemble of well-tested, diverse crop models and on integration of knowledge from multiple disciplines. The robustness of model-aided ideotypes design can be further enhanced by continuously improving crop models and enhancing information exchange between modellers, agro-meteorologists, geneticists, physiologists, and plant breeders. (C) 2016 Elsevier B.V. All rights reserved.
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Holman, I. P., Brown, C., Carter, T. R., Harrison, P. A., & Rounsevell, M. (2019). Improving the representation of adaptation in climate change impact models. Reg. Environ. Change, 19(3), 711–721.
Abstract: Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.
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Mitter, H., Schmid, E., & Sinabell, F. (2015). Integrated modelling of protein crop production responses to climate change and agricultural policy scenarios in Austria. Clim. Res., 65, 205–220.
Abstract: Climate and policy changes are likely to affect protein crop production and thus trade balances in Europe, which is highly dependent on imports. Exemplified for Austrian cropland, we developed an integrated modelling framework to analyze climate change and policy scenario impacts on protein crop production and environmental outcomes. The integrated modelling framework consists of a statistical climate change model, a crop rotation model, the bio-physical process model EPIC, and the economic bottom-up land use optimization model BiomAT. EPIC is applied to simulate annual dry matter crop yields for different crop management practices including crop rotations, fertilization intensities, and irrigation, as well as for 3 regional climate change scenarios until 2040 at a 1 km grid resolution. BiomAT maximizes total gross margins by optimizing land use choices and crop management practices subject to spatially explicit cropland endowments. The model results indicate that changes in agricultural policy conditions, cropland use, and higher flexibility in crop management practices may reduce protein import dependence under changing climatic conditions. Expanding protein crop production is most attractive in south-eastern Austria with its Central European continental climate where maize is most often replaced in crop rotations. However, the acreage of protein crops is limited by agronomically suitable cropland. An intended side effect is the reduction of nitrogen fertilizer inputs by about 0.1% if total protein crop production increases by 1%.
Keywords: Climate change impact; Adaptation; Soybean; EPIC; Common Agricultural Policy; Land use
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