Plant genetic resources display patterns resulting from ecological and co-evolutionary processes. Such patterns are instrumental in tracing the origin and diversity of crops and locating adaptive traits. With climate change and the anticipated increase in demand for food, new crop varieties will be needed to perform under unprecedented climatic conditions. In the present study, we explored genetic resources patterns to locate traits of adaptation to drought and to maximize the utilization of plant genetic resources lacking ex ante evaluation for emerging climate conditions. This approach is based on the use of mathematical models to predict traits as response variables driven by stochastic ecological and co-evolutionary processes. The high congruence of metrics between model predictions and empirical trait evaluations confirms in silico evaluation as an effective tool to manage large numbers of crop accessions lacking ex ante evaluation. This outcome will assist in developing cultivars adaptable to various climatic conditions and in the ultimate use of genetic resources to sustain agricultural productivity under conditions of climate change.
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The authors express their gratitude to CIMO (the Centre for International Mobility) and the Emil Aaltonen Foundation for their financial support to H.K.; to the University of Helsinki, the Niemi Foundation and the FP7 project Legume Futures (245216 CP-FP ‘Legume Futures: Legume supported cropping systems for Europe’) for support to H.K., M.J.S. and F.L.S.; and to NSERC Canada for partial funding of this research through Discovery Grants for support to Y.P.C. and S.D. We thank the many colleagues who helped in this research directly or indirectly and those who developed and compiled climate databases. This study was further supported by the Climate Change, Agriculture and Food Security (CCAFS) Program of the CGIAR, Concordia University, and the Australian Grains Research & Development Cooperation (GRDC).
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Bari, A., Khazaei, H., Stoddard, F.L. et al. In silico evaluation of plant genetic resources to search for traits for adaptation to climate change. Climatic Change 134, 667–680 (2016). https://doi.org/10.1007/s10584-015-1541-9
- Faba Bean
- Accuracy Metrics
- Genetic Resource Collection
- Correct Classification Average Rate
- Faba Bean Accession