In the face of Climate Change: Part 2

Whilst completing my weekly reading I strolled upon a paper which stopped me in my tracks. A crop model? My favorite!

 Lobell and Burke (2008) ‘On the use of statistical models to predict crop yield response to climate change’. Within the Paper Lobell and Burke discussed the potential effects of climate change on crop yields for 198 sites in Sub Saharan Africa. The paper adopts the hypothesis, that a 2 degree temperature rise and 20% precipitation reduction will be the prominent implications of climate change. As always there will be uncertainty associated with climate change predictions but this argument lies beyond the scope of this blog post. The results, of the study, indicated (based on median emissions predictions) a 2 degree warming would result in a 14.4% loss in crop yields, whereas the effect of reducing precipitation (by 20%) would only produce a 5.8% yield reduction. This seems counter intuitive when considering the importance of rainfall in agricultural production. However temperature trends are large in relation to historical yield variability, thus becoming more prominent than precipitation trends when using the model CERES to analyse crop responses to climate change.

Methods:

The paper adopted the following methodology. A CERES-Maize model was used to simulate historical measurements of maize yield variability. The model was run under the climate change conditions to simulate the impact of a 2 degree temperature increase and 20% reduction of precipitation in maize yield variability. A statistical model was run alongside to provide a comparison of results.

Thoughts and reflections:

In relation to the adopted methods of the study, evidence suggests there are areas which contain increased levels of uncertainty. Firstly results do not consider any form of socio-economic response, all parameters are purely physical. An integrated assessment aims to tie together crop yield and socio- economic factors and can increase relevance (to a specific region) by incorporating issues such as how yield may differ in repose to adaptive measures.(Challinor et al., 2007). Fischer et al. (2002) use an integrated assessment to combine the use of climate change scenarios and resulting price trends in the global crop market.

Secondly, historical measurements of crop yield variability (within the Lobell and Burke study) were simulated within a CERES model (based on climate parameters and soil moisture conditions). In general modelling terms, a historic data set of observed variability (in this case I would expect historically observed crop yields), is initially inputted into the model. Observed data is also used to calibrate models to reduce uncertainty and ensure results are realistic. The use of observed historical data does not seem to be present in this study as either an input or for calibration purposes. This leads to the question, how accurate is this model.

In a future post I aim to explore a series of different crop modelling studies to investigate whether or not a lack of historical observations is common throughout this field of research.

As always, feel free to respond to what I have covered in today’s post by leaving a comment below.