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chapter 6: global climate change, food supply and livestock production systems: a bioeconomic analysis
of livestock between the different production systems based on their relative profitability. The model has been implemented for climate change impact assessments in the past, both individually (Mosnier et al., 2014) and as part of the AgMIP/ISI- MIP model intercomparison, but it is in this chapter that climate change impacts on grasslands are included for the first time.
Future climate development is highly uncertain and the large differences in impact assessments provided by crop or vegetation models add to this uncertainty (Asseng et al., 2013; Ramirez- Villegas et al., 2013; Challinor et al., 2014; Rosenzweig et al., 2014). The ISI-MIP project results (www.isi-mip.org) that were made available to impact modellers downscaled
and bias-corrected climate change scenarios, based on the results of the Coupled Model Intercomparison Project (CMIP). Subsequently,
a database of global, spatially explicit, modelled climate change impacts across different sectors has been created (Warszawski et al., 2013). These datasets make it possible, in principle, to account for the uncertainties inherent in climate change impact assessments. We have identified the most important sources of uncertainty to be: use of a particular crop/grass growth model; and assumptions about the strength of the carbon dioxide (CO2) fertilization effect. These two aspects will be systematically treated throughout our study.
2. Methodology
The assessment provided in this chapter follows
a sequential approach. First, climate change scenarios quantified by general circulation
models (GCMs) are selected, then results of
these scenarios are used as input to biophysical process-based models to assess the impacts on crop and grass yields, and finally these models are used as input for the economic model to project the effects of climate change on the agricultural sector as a whole. In the next sections, we will present these three steps in detail.
2.1 Climate scenarios3
The most recent generation of climate change scenarios available at the time of this study corresponds to the fifth phase of the Coupled Model Intercomparison Project (CMIP5)
(Taylor et al., 2011). In this project, more than
50 climate models were used to simulate four emission scenarios (Representative Concentration Pathways, or RCPs). The four RCPs cover a range of “radiative forcing”4 in the year 2100, going from 2.6 to 8.5 W/m2 (Vuuren et al., 2011). Depending on the climate model, these levels of radiative forcing would spread the global temperature increase above pre-industrial levels, from below
1 °C for RCP2.6 to about 7 °C for RCP8.5, the median across the models for the latter RCP being just below 5 °C (Rogelj et al., 2012). For
this analysis, we will focus on RCP8.5 for three reasons: first, because this scenario shows best what the future challenges of climate change could be; second, because together with the “present climate” scenario, it allows for judgment about the intermediate emission pathways; and finally, because the recent emission developments exceed even the RCP8.5 emission levels for the relevant years (Peters et al., 2013).
The ISI-MIP provided impact modellers
with spatially interpolated and bias-corrected climate datasets for all four RCPs and for five GCMs (GFDL-ESM2M, HadGEM2-ES, IPSL- CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) selected to span the CMIP5 range of global mean temperature changes and relative precipitation changes (Warszawski et al., 2013). Of the five GCMs, ISI-MIP retained HadGEM2-ES as the
3
4
The scenarios reported in this study were developed as part of a European Union-funded FP7 project called “An integration of mitigation and adaptation options for sustainable livestock production under climate change” (ANIMALCHANGE) (Grant 266018)
“radiative forcing” is linked to the CO2 concentration measured in part per million value or ppmv. The higher the CO2 concentration, the higher the radiative forcing which in turn raises the radiative energy reaching the earth’s surface and causes the average earth temperature to increase
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