Page 66 - Climate Change and Food Systems

climate change and food systems: global assessments and implications for food security and trade
Many of these events had major agricultural, food security and economic implications, and these can be evaluated using GGCMs in order to test these models under such extreme conditions. This will also result in a standardized, comprehensive multi- model analysis of agricultural drought over the
last 6+ decades, comparable among regions and decades, that will improve both the understanding of drought and its effects on crops and food production and the ability of models to represent the consequences of increased drought and heat in the future.
6.6 Future challenges: Connecting with field-scale assessments
Crop growth models have been applied to multiple purposes for several decades. Given
that models applied to climate change impact assessment do not always employ the most up- to-date formulations, Rötter et al. [2011] called for a general re-assessment of model effectiveness, as a first step towards improving model formulations. This effort has been undertaken by AgMIP [Rosenzweig et al., 2013], focusing first
on the major cereal crops – wheat [Asseng et al., 2013], maize [Bassu et al., 2014] and rice – while building communities and establishing research teams for other crops, pastures and livestock (see http://www.agmip.org). The projects
focus initially on reproducing observations
across different environmental gradients and management systems, followed by exploration
of model sensitivities to changes in temperature, precipitation and atmospheric CO2 concentrations.
As GGCMs are often based on field-scale models to varying degrees, field-scale model improvements can provide the basis for global- scale improvements. Processes that have been identified as important for future crop productivity, such as temperature extremes [Asseng et al., 2011], tropospheric ozone concentrations [Bender and Weigel, 2011; Leisner and Ainsworth, 2012; Pleijel and Uddling, 2012] and pests and diseases [Bebber et al., 2013; Mediene et al., 2011], will
have to be implemented and tested in field-
scale models, before they can be implemented
in global-scale assessments. The high quality of data available at some individual field sites greatly facilitates the development and evaluation of process formulations in crop models. Global-scale models can inform field-scale model development as well – for example, by characterizing expected ranges of growing conditions across large areas, as well as their implications for agricultural productivity and modelled sensitivities.
6.7 Future challenges: Informing economic assessment with biophysical climate change impact studies
Biophysical climate change impact assessments are a central precondition for understanding climate change impacts on future trade patterns in agricultural markets. There are a number of challenges to making these assessments useful to current agricultural economic assessments. The uncertainty with respect to climate change patterns [Christensen et al., 2007] and impact models [Rosenzweig et al., 2014] needs to be accounted for. A broad variety of issues exist
in modelling consistency between economic
and biophysical models. One important aspect
is the difference between market commodities such as sugar, assumed to be homogeneous
by economic models, which can be supplied by very different biophysical crops (here: sugar cane and sugar beet) that differ in their photosynthetic pathways (C4 for sugar cane, C3 for sugar beet), phenology, and plant organs of interest (stalks or beets). The ability to model these different crop types or assumptions about their mixture in the supply of the commodity sugar can greatly affect the assessment of climate change impacts on
the commodity’s market shares and production [Müller and Robertson, 2014; Nelson et al., 2014a; Nelson et al., 2014b].
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