60
which is beyond what most farmers can afford (FAO 2006; Vanlauwe and Giller
2006). However, in our current study both models simulate yield plateau at 60 kg N/
ha for better soils and at around 70 kg N/ha for poor soils. The biophysical and
socio-economic situation needs to be considered for establishing recommendations
and these should be location-specific and dynamic because soil changes depending
on how it is managed.
5.4.2 Combined Effects of Climate Factors on Maize
and Groundnuts
Temperatures are projected to increase in Nkayi district, however, rainfall is likely
to change by −15% to +10%. Average annual rainfall for Nkayi is about 650 mm
per year and the projected reductions and increases can lead to 552 and 715 mm per
year, respectively. Variability will be high especially under hot/dry conditions as
shown by the variations in yields reductions (Figs. 5.4 and 5.5). Yield variability is
higher for maize grain than stover while for groundnuts high variability is only
simulated by the DSSAT model for both grain and stover. Increased temperature
effects supersede the other factors and will be mostly detrimental to maize while
high response to CO 2 exhibited by groundnuts negate the negative effects of
increased temperature. Increased temperature reduces crop yields by accelerating
crop phonological stages, hence, reducing the time for biomass accumulation.
Another adverse effect of high temperature is heat and/or water stress, which at the
critical crop growth stages, such as anthesis or grain filling, also reduces crop yields.
It will be important to assess which effect will be more prominent and this information could be used when developing adaptation strategies. Important is also to assess
the particular times when crops are water stressed so that farmers can adjust water
and nutrient management, planting and sowing dates, plant densities and cultivar
choice. Climate-smart agricultural practices such as agroforestry that make use of
water more efficiently and have the potential to induce microclimatic conditions can
be recommended in areas affected by heat stress (Mbow et al. 2014).
5.5 Implications for Development
Crop models are important tools that can be used to understand disaggregated
effects of climate elements on crop production. However, models do differ in the
way they are constructed and in their responses to different effects of climatic factors on crop production. We used two crop models DSSAT and APSIM and both
models generally agreed on the effects of different climatic factors on maize and
groundnuts. It is only the magnitude of the effects that vary, for example, reductions
on maize grain yields are more pronounced in the APSIM model while the DSSAT
P. Masikati et al.
which is beyond what most farmers can afford (FAO 2006; Vanlauwe and Giller
2006). However, in our current study both models simulate yield plateau at 60 kg N/
ha for better soils and at around 70 kg N/ha for poor soils. The biophysical and
socio-economic situation needs to be considered for establishing recommendations
and these should be location-specific and dynamic because soil changes depending
on how it is managed.
5.4.2 Combined Effects of Climate Factors on Maize
and Groundnuts
Temperatures are projected to increase in Nkayi district, however, rainfall is likely
to change by −15% to +10%. Average annual rainfall for Nkayi is about 650 mm
per year and the projected reductions and increases can lead to 552 and 715 mm per
year, respectively. Variability will be high especially under hot/dry conditions as
shown by the variations in yields reductions (Figs. 5.4 and 5.5). Yield variability is
higher for maize grain than stover while for groundnuts high variability is only
simulated by the DSSAT model for both grain and stover. Increased temperature
effects supersede the other factors and will be mostly detrimental to maize while
high response to CO 2 exhibited by groundnuts negate the negative effects of
increased temperature. Increased temperature reduces crop yields by accelerating
crop phonological stages, hence, reducing the time for biomass accumulation.
Another adverse effect of high temperature is heat and/or water stress, which at the
critical crop growth stages, such as anthesis or grain filling, also reduces crop yields.
It will be important to assess which effect will be more prominent and this information could be used when developing adaptation strategies. Important is also to assess
the particular times when crops are water stressed so that farmers can adjust water
and nutrient management, planting and sowing dates, plant densities and cultivar
choice. Climate-smart agricultural practices such as agroforestry that make use of
water more efficiently and have the potential to induce microclimatic conditions can
be recommended in areas affected by heat stress (Mbow et al. 2014).
5.5 Implications for Development
Crop models are important tools that can be used to understand disaggregated
effects of climate elements on crop production. However, models do differ in the
way they are constructed and in their responses to different effects of climatic factors on crop production. We used two crop models DSSAT and APSIM and both
models generally agreed on the effects of different climatic factors on maize and
groundnuts. It is only the magnitude of the effects that vary, for example, reductions
on maize grain yields are more pronounced in the APSIM model while the DSSAT
P. Masikati et al.