Potential effects of variation in agriculture sector response to climate change: an integrated assessment

The effects of climate change on agricultural productivity are influenced by a range of factors including changes in temperature, precipitation, humidity, and frost and carbon fertilisation. Recent literature on the sensitivity of the agriculture sector to climate change highlights the need for understanding the way climate change influences the distribution of productivity impacts. These impacts may manifest in the form of changes in food self sufficiency, export availability and import dependency and may vary across different geographic and socioeconomic regions. Such effects will have considerable socio-economic implications, nationally, regionally and globally. In this paper, we examine the potential effects of a 1 0 C warming globally by 2030 (relative to what would otherwise be) on the distribution of agricultural productivity responses in a range of key food exporting and importing countries. To carry out our analysis we use an integrated assessment modelling framework: the Global Integrated Assessment Model (GIAM). GIAM is a coupled model which consists of a global economic module – the Global Trade and Environment Model (GTEM) and a climate module – the Simple Carbon Climate Model (SCCM). The GTEM module provides the greenhouse gas emissions based on economic activities. These emissions are then fed into the SCCM module. The SCCM module converts the emissions into CO2 concentration levels and then into changes in temperature. Changes in temperature are fed into a ‘climate change response function’ in the GIAM framework to assess the potential climate change impacts on agriculture. The main emphasis of this paper is on sensitive regions as defined by the intersection of growing population and income and expanding demand for food. In particular, we assess the impact of climate change on export availability of key food exporting economies such as the US, Canada and Australia. Furthermore, we focus on food self sufficiency and import dependence of key emerging/developing economies such as China and Indonesia. Our results highlight considerable variation in the economic impacts induced by the climate change impacts of magnitudes from the tails of the probability distributions representing the current state of knowledge. We argue that unrestricted global trade could be a useful mediator between regions influenced differently by climate change. We reiterate that reducing the uncertainty in climate change impacts on agriculture should be a high priority for research.