Food Security

, Volume 4, Issue 2, pp 163–179

The socioeconomics of food crop production and climate change vulnerability: a global scale quantitative analysis of how grain crops are sensitive to drought

  • Elisabeth Simelton
  • Evan D. G. Fraser
  • Mette Termansen
  • Tim G. Benton
  • Simon N. Gosling
  • Andrew South
  • Nigel W. Arnell
  • Andrew J. Challinor
  • Andrew J. Dougill
  • Piers M. Forster
Original Paper

DOI: 10.1007/s12571-012-0173-4

Cite this article as:
Simelton, E., Fraser, E.D.G., Termansen, M. et al. Food Sec. (2012) 4: 163. doi:10.1007/s12571-012-0173-4

Abstract

Many studies warn that climate change may undermine global food security. Much work on this topic focuses on modelling crop-weather interactions but these models do not generally account for the ways in which socio-economic factors influence how harvests are affected by weather. To address this gap, this paper uses a quantitative harvest vulnerability index based on annual soil moisture and grain production data as the dependent variable in a Linear Mixed Effects model with national scale socio-economic data as independent variables for the period 1990–2005. Results show that rice, wheat and maize production in middle income countries were especially vulnerable to droughts. By contrast, harvests in countries with higher investments in agriculture (e.g. higher amounts of fertilizer use) were less vulnerable to drought. In terms of differences between the world’s major grain crops, factors that made rice and wheat crops vulnerable to drought were quite consistent, while those of maize crops varied considerably depending on the type of region. This is likely due to the fact that maize is produced under very different conditions worldwide. One recommendation for reducing drought vulnerability risks is coordinated development and adaptation policies, including institutional support that enables farmers to take proactive action.

Keywords

Drought vulnerability index Crop failure Soil moisture Food security Transition economies Linear model Adaptive capacity 

Supplementary material

12571_2012_173_MOESM1_ESM.doc (62 kb)
ESM 1(DOC 61 kb)
12571_2012_173_MOESM2_ESM.doc (50 kb)
ESM 2 (DOC 50 kb)

Copyright information

© Springer Science + Business Media B.V. & International Society for Plant Pathology 2012

Authors and Affiliations

  • Elisabeth Simelton
    • 1
    • 2
  • Evan D. G. Fraser
    • 1
    • 3
  • Mette Termansen
    • 1
    • 4
  • Tim G. Benton
    • 5
  • Simon N. Gosling
    • 6
  • Andrew South
    • 7
  • Nigel W. Arnell
    • 8
  • Andrew J. Challinor
    • 9
  • Andrew J. Dougill
    • 1
  • Piers M. Forster
    • 9
  1. 1.School of Earth and EnvironmentUniversity of LeedsLeedsUK
  2. 2.World Agroforestry Centre (ICRAF)Ha NoiViet Nam
  3. 3.Department of Geography, College of Human and Applied Social SciencesUniversity of GuelphGuelphCanada
  4. 4.Department of Environmental ScienceUniversity of AarhusRoskildeDenmark
  5. 5.Faculty of Biological SciencesUniversity of LeedsLeedsUK
  6. 6.School of GeographyUniversity of NottinghamNottinghamUK
  7. 7.Centre for EnvironmentFisheries & Aquaculture ScienceDorsetUK
  8. 8.Walker Institute, Department of MeteorologyUniversity of ReadingReadingUK
  9. 9.Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK

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