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Accounting for interannual variability in agricultural intensification : The potential of crop selection in Sub-Saharan Africa

Bodin, P. LU ; Olin, S. LU ; Pugh, T. A M and Arneth, A. LU (2016) In Agricultural Systems 148. p.159-168
Abstract

Providing sufficient food for a growing global population is one of the fundamental global challenges today. Crop production needs not only to be increased, but also remain stable over the years, in order to limit the vulnerability of producers and consumers to inter-annual weather variability, especially in areas of the world where the food consumed is mainly produced locally (e.g. Sub Saharan Africa (SSA)). For subsistence agriculture, stable yields form a crucial contribution to food security. At a regional to global scale dynamical crop models can be used to study the impact of future changes in climate on food production. However, simulations of future crop production, for instance in response to climate change, often do not take... (More)

Providing sufficient food for a growing global population is one of the fundamental global challenges today. Crop production needs not only to be increased, but also remain stable over the years, in order to limit the vulnerability of producers and consumers to inter-annual weather variability, especially in areas of the world where the food consumed is mainly produced locally (e.g. Sub Saharan Africa (SSA)). For subsistence agriculture, stable yields form a crucial contribution to food security. At a regional to global scale dynamical crop models can be used to study the impact of future changes in climate on food production. However, simulations of future crop production, for instance in response to climate change, often do not take into account either changes in the sown areas of crops or yield interannual variability. Here, we explore the response of simulated crop production to assumptions of crop selection, also taking into account interannual variability in yields and considering the response of agricultural productivity to climate change. We apply the dynamic global vegetation model LPJ-GUESS, which is designed to simulate yield over large regions under a changing environment. Model output provides the basis for selecting the relative fractions of sown areas of a range of crops, either by selecting the highest yielding crop, or by using an optimization approach in which crop production is maximized while the standard deviation in crop production is kept at below current levels. Maximizing simulated crop production for current climate while keeping interannual variability in crop production constant at today's level generates rather similar simulated geographical distributions of crops compared to observations. Even so, the optimization results suggest that it is possible to increase crop production regionally by adjusting crop selection, both for current and future climate, assuming the same cropland cover as today. For future climates modelled production increase is > 25% in more than 15% of the grid cells. For a small number of grid cells it is possible to both increase crop production while at the same time decreasing its interannual variability. Selecting the highest yielding crop for any location will lead to a large potential increase in mean food production, but at the cost of a very large increase in variability.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Climate change, Crop model, LPJ-GUESS, Modern Portfolio Theory, Yield
in
Agricultural Systems
volume
148
pages
10 pages
publisher
Elsevier
external identifiers
  • scopus:84982828974
  • wos:000383525900016
ISSN
0308-521X
DOI
10.1016/j.agsy.2016.07.012
language
English
LU publication?
yes
id
ecbf285a-6565-4e14-904b-2a788a8e8d9e
date added to LUP
2016-10-25 14:11:20
date last changed
2017-06-30 12:30:57
@article{ecbf285a-6565-4e14-904b-2a788a8e8d9e,
  abstract     = {<p>Providing sufficient food for a growing global population is one of the fundamental global challenges today. Crop production needs not only to be increased, but also remain stable over the years, in order to limit the vulnerability of producers and consumers to inter-annual weather variability, especially in areas of the world where the food consumed is mainly produced locally (e.g. Sub Saharan Africa (SSA)). For subsistence agriculture, stable yields form a crucial contribution to food security. At a regional to global scale dynamical crop models can be used to study the impact of future changes in climate on food production. However, simulations of future crop production, for instance in response to climate change, often do not take into account either changes in the sown areas of crops or yield interannual variability. Here, we explore the response of simulated crop production to assumptions of crop selection, also taking into account interannual variability in yields and considering the response of agricultural productivity to climate change. We apply the dynamic global vegetation model LPJ-GUESS, which is designed to simulate yield over large regions under a changing environment. Model output provides the basis for selecting the relative fractions of sown areas of a range of crops, either by selecting the highest yielding crop, or by using an optimization approach in which crop production is maximized while the standard deviation in crop production is kept at below current levels. Maximizing simulated crop production for current climate while keeping interannual variability in crop production constant at today's level generates rather similar simulated geographical distributions of crops compared to observations. Even so, the optimization results suggest that it is possible to increase crop production regionally by adjusting crop selection, both for current and future climate, assuming the same cropland cover as today. For future climates modelled production increase is &gt; 25% in more than 15% of the grid cells. For a small number of grid cells it is possible to both increase crop production while at the same time decreasing its interannual variability. Selecting the highest yielding crop for any location will lead to a large potential increase in mean food production, but at the cost of a very large increase in variability.</p>},
  author       = {Bodin, P. and Olin, S. and Pugh, T. A M and Arneth, A.},
  issn         = {0308-521X},
  keyword      = {Climate change,Crop model,LPJ-GUESS,Modern Portfolio Theory,Yield},
  language     = {eng},
  month        = {10},
  pages        = {159--168},
  publisher    = {Elsevier},
  series       = {Agricultural Systems},
  title        = {Accounting for interannual variability in agricultural intensification : The potential of crop selection in Sub-Saharan Africa},
  url          = {http://dx.doi.org/10.1016/j.agsy.2016.07.012},
  volume       = {148},
  year         = {2016},
}