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Bressan, R. A., Park, H. C., Orsini, F., Oh, D. -ha, Dassanayake, M., Inan, G., et al. (2013). Biotechnology for mechanisms that counteract salt stress in extremophile species: a genome-based view. Plant Biotechnol. Rep., 7(1), 27–37.
Abstract: Molecular genetics has confirmed older research and generated new insights into the ways how plants deal with adverse conditions. This body of research is now being used to interpret stress behavior of plants in new ways, and to add results from most recent genomics-based studies. The new knowledge now includes genome sequences of species that show extreme abiotic stress tolerances, which enables new strategies for applications through either molecular breeding or transgenic engineering. We will highlight some physiological features of the extremophile lifestyle, outline emerging features about halophytism based on genomics, and discuss conclusions about underlying mechanisms.
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Paas, W. (2013). Impacts of climate change and socio-economic drivers on dairy farms in ‘the Baakse Beek’, the Netherlands. M.Sc., M.Sc.. Master's thesis, Wageningen UR, .
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Zhou, Z. (2013). Improving a grass yield model to assess impacts of climate change on grass yields around 2050 at plot level in the Dutch region Baakse Beek. M.Sc., M.Sc.. Master's thesis, Wageningen University, Wageningen.
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Semenov, M. A., Pilkington-Bennett, S., & Calanca, P. (2013). Validation of ELPIS 1980-2010 baseline scenarios using the observed European Climate Assessment data set. Clim. Res., 57(1), 1–9.
Abstract: Local-scale daily climate scenarios are required for assessment of climate change impacts. ELPIS is a repository of local-scale climate scenarios for Europe, which are based on the LARS-WG weather generator and future projections from 2 multi-model ensembles, CMIP3 and EU-ENSEMBLES. In ELPIS, the site parameters for the 1980-2010 baseline scenarios were estimated by LARS-WG using daily weather from the European Crop Growth Monitoring System (CGMS) used in many European agricultural assessment studies. The objective of this paper was to compare ELPIS baseline scenarios with observed daily weather obtained independently from the European Climate Assessment (ECA) data set. Several statistical tests were used to compare distributions of climatic variables derived from ECA-observed daily weather and ELPIS-generated baseline scenarios. About 30% of selected sites have a difference in altitude of > 50 m compared with the CGMS grid-cell altitude that was selected to represent agricultural land within a grid-cell. Differences in altitude can explain significant Kolmogorov-Smirnov test (KS-test) results for distribution of daily temperature and in t-tests for temperature monthly means, because of the well-known negative correlation between temperature and elevation. For daily precipitation, the KS-test showed little difference between generated and observed data; however, the more sensitive t-test showed significant results for the sites where altitude differences were large. Approximately 11% of sites showed small positive or negative bias in monthly solar radiation, although 86% sites showed > 3 significant t-test results for monthly means. These results can be explained by differences in conversion of sunshine hours to solar radiation used in CGMS and LARS-WG. We conclude that, considering the limitations above, ELPIS baseline scenarios are suitable for agricultural impact assessments in Europe.
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Porter, J. R., & Christensen, S. (2013). Deconstructing crop processes and models via identities. Plant Cell and Environment, 36(11), 1919–1925.
Abstract: This paper is part review and part opinion piece; it has three parts of increasing novelty and speculation in approach. The first presents an overview of how some of the major crop simulation models approach the issue of simulating the responses of crops to changing climatic and weather variables, mainly atmospheric CO2 concentration and increased and/or varying temperatures. It illustrates an important principle in models of a single cause having alternative effects and vice versa. The second part suggests some features, mostly missing in current crop models, that need to be included in the future, focussing on extreme events such as high temperature or extreme drought. The final opinion part is speculative but novel. It describes an approach to deconstruct resource use efficiencies into their constituent identities or elements based on the Kaya-Porter identity, each of which can be examined for responses to climate and climatic change. We give no promise that the final part is correct’, but we hope it can be a stimulation to thought, hypothesis and experiment, and perhaps a new modelling approach.
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