Modelling Impacts of Climate Change on Maize (<i>Zea mays</i> L.) Growth and Productivity: A Review of Models, Outputs and Limitations

Abstract

The use of crop modelling in various cropping systems and environments to project and upscale agronomic decision-making under the facets of climate change has gained currency in recent years. This paper provides an evaluation of crop models that have been used by researchers to simulate maize growth and productivity. Through a systematic review approach, a comprehensive assessment of 186 published articles was carried out to establish the models and parameterization features, simulated impacts on maize yields and adaptation strategies in the last three decades. Of the 23 models identified, CERES-maize and APSIM models were the most dominant, representing 49.7% of the studies undertaken between 1990 and 2018. Current research shows projected decline in maize yields of between 8%-38% under RCP4.5 and RCP8.5 scenarios by the end of the 21 st century, and that adaptation is essential in alleviating the impacts of climate change. Major agro-adaptation options considered in most papers are changes in planting dates, cultivars and crop water management practices. The use of multiple crop models and multi-model ensembles from general circulation models (GCMs) is recommended. As interest in crop modelling grows, future work should focus more on suitability of agricultural lands for maize production under climate scenarios.

Response to climate change in a rain-fed crop production system: insights from maize farmers of western Kenya

“…3 that the key adaptation strategy by the farmers in the western region of Kenya was a change of planting decision by either planting early or delaying planting date. This supports the findings of a review study by Kogo et al (2019c) which established that change of planting dates was one of the major agro-adaption options towards mitigating the impacts of climate change on crop production. According to Lv et al (2020), adjusting of planting date is one of the strategies used by farmers to maintain or increase crop yields under climate change.…”

Impact of Climate Change in West Africa on Cereal Production Per Capita in 2050

“…In this study, we use daily climate projections from GCMs which have been previously bias-corrected [15]. The cumulative distribution function transfer (CDFt) method [16,17], using a univariate quantile-quantile method, reducing the bias in daily data.…”

“…The cumulative distribution function transfer (CDFt) method [16,17], using a univariate quantile-quantile method, reducing the bias in daily data. By computing various climatic indices such as seasonal rainfall, dry spells and onset of the rains, that is demonstrated that this technique strongly reduces the errors in the present-day simulations of the CMIP5 models compared to observed data [15](WFDEI, [18] over the 1979-2013 period), and reduces the spread between the models for the different RCPs. Climate model outputs have been bi-linearly interpolated onto a 0.5 • linear grid before bias correction.…”

“…Climate model outputs have been bi-linearly interpolated onto a 0.5 • linear grid before bias correction. This unbiased set of daily output (precipitation and temperature) from 16 CMIP5 Global Climate Models (GCM) (see Table S1 for the list in Supplementary Materials) is used under two RCPs (RCP2.6 and RCP8.5) over the period 2006-2100 with this resolution of 0.5 • × 0.5 • [15]. The scenario RCP2.6 corresponds to a CO 2 atmospheric concentration of, already questioned, 442 ppm in 2050 stabilization and leads to an elevation of the global surface temperature of about 1.5 + 2 • C with respect to pre-industrial temperature.…”

Bioprospecting Soil Bacteria from Arid Zones to Increase Plant Tolerance to Drought: Growth and Biochemical Status of Maize Inoculated with Plant Growth-Promoting Bacteria Isolated from Sal Island, Cape Verde

“…Climate change has caused inter-seasonal yield variability and negative impact on crop growth, development and production. The major challenges to agriculture are related to climate change severity and occurrence of extreme weather events, such as floods, drought and heat haves but also to agricultural management (application of fertilizers, tillage, agrochemicals) [ 5 , 7 , 8 ].…”