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Crop Science Abstract - Beyond the Yield Curves: Exerting the Power of Genetics, Genomics, and Synthetic Biology

Climate Risk Management for Adaptation to Climate Variability and Change


This article in CS

  1. Vol. 50 No. Supplement_1, p. S-70-S-76
    unlockOPEN ACCESS
    Received: Sept 23, 2009

    * Corresponding author(s): baethgen@iri.columbia.edu
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  1. Walter E. Baethgen *
  1. International Research Institute for Climate and Society (IRI), Columbia Univ., 61 Route 9W, Palisades, NY 10964


The warming of the climate system is evident from observations of air and ocean temperatures as well as in melting of snow and ice and rising sea level. Measures are needed to reverse the trends of increased accumulation of greenhouse gases (GHG) in the atmosphere. The two main paths to reverse this trend are: (i) reducing GHG emissions through cleaner energy generation and (ii) removing CO2 through carbon sequestration. The agricultural and forestry sectors can play a key role in both paths. Carbon markets will likely encourage increased carbon sequestration. However, the implementation of carbon-market projects for small farmers in least developed countries is still a major challenge. Even under the most optimistic scenarios of future GHG emissions adaptive measures are needed to address impacts of the warming due to past and current emissions. Integrating climate change into decision making is complicated by the uncertainty levels of climate scenarios. It is also challenged by a “double conflict of scales”: (i) climate scenarios are available for periods much farther in the future than the ones typically needed for decision making and (ii) spatial scales of the climate scenarios (global to regional) are coarser than the ones often needed for actual decision making (i.e., local level). Introducing the issue of climate change into policy and development agendas can be facilitated by considering the longer-term variations as part of the continuum of total climate variability (seasons to decades to centuries) and generating information at the temporal scales that are relevant and applicable for particular decisions.

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