Agriculture plays a large role in the economy across Africa
and is one of the most vulnerable sectors to climate change, research needs to
be conducted into this area in order to protect this livelihood. Crop models
are an essential part of this climate change research (Roudier et al., 2011;
Challinor 2007). Predicting how changes to temperature and rainfall patterns
will influence crop yields in Africa provides essential data for agriculture
mitigation strategies.
Consistency of literature.
One of the main conclusions drawn from the literature surrounds
the relative importance of alterations to temperature vs rainfall patterns. A general
consensus shows temperature change (predictions of approximately 1.4-1.6
degrees warming by 2050, approximately 0.2 degrees per decade (IPCC, 2013))
dominates over rainfall, having the largest negative influence on crop yields
(Lobell et al., 2008; Roudier et al., 2011; Thorton et al., 2009). A warmer and
drier climate is anticipated to reduce crop yields across Africa by 10-20%
(Thorton et al., 2009).
Temperature patterns dominate, if rainfall remained the
same, temperature would still decrease yields in West Africa by 15% (Schlenker and Lobell, 2010). Rainfall has the potential
to either exaggerate or alleviate the influence of warming. This is not enough,
however to overcome the issues of temperature change. Slack (2006) states
demonstrates changes to rainfall compensate a 1.5 degree C temperature change for
millet crop by -59% and -26% for a decrease or increasing in rainfall, retrospectively.
This was supported by Gaun et al (2015).
Please note. These are generalised conclusions for Africa,
these results will value for different locations and crop types. For example trends
generally show a decrease in crop yield, yet rainfall can also mitigate climate
change impacts. Some will witness an increase in crop yield. Within the
Ethiopian highlands, surrounding Addis Ababa, Jones and Thorton (2003) predicted
a “substantial localised yield increase” of up to 100% in places. Despite this
the overall conclusions of the study showed a reduction in yield (maize across Africa)
and in some cases too drastically (it is predicted) to prevent mitigate
changes. This highlights the fact the sensitivity of crops across Africa are
not uniform this fact should be notified when implementing mitigation schemes
as a single policy may not be successful for a whole region.
Final words
Policy is something which has risen throughout a lot of the literature
addressed. Crop models are proving very effective within the academic world but
outside much work still needs to be done in order to use modelling results to implement
successful policies (Bouman
et al., 1996). One factor which will improve the application of agricultural
policy is to involve knowledge of local farmers. The incorporation of such
ideas will help reduce the gap between the needs of farmers and the academic
hypothesis Stephens
and Middleton (2000).