Cropping frequency and area response to climate variability can exceed yield response

2016 ◽  
Vol 6 (6) ◽  
pp. 601-604 ◽  
Author(s):  
Avery S. Cohn ◽  
Leah K. VanWey ◽  
Stephanie A. Spera ◽  
John F. Mustard
2019 ◽  
Vol 7 (2) ◽  
pp. 11
Author(s):  
Ebrima Sonko ◽  
Sampson K. Agodzo ◽  
Philip Antwi-Agyei

Climate change and variability impact on staple food crops present a daunting challenge in the 21st century. The study assesses future climate variability on maize and rice yield over a 30-year period by comparing the outcomes under two GCM models, namely, CSIRO_RCP4.5 and NOAA_RCP4.5 of Australia’s Commonwealth Scientific and National Oceanic and Atmospheric Administration respectively. Historical climate data and yield data were used to establish correlations and then subsequently used to project future yields between 2021 and 2050. Using the average yield data for the period 1987-2016 as baseline yield data, future yield predictions for 2021-2030, 2031-2040 and 2041-2050 were then compared with the baseline data. The results showed that the future maize and rice yield would be vulnerable to climate variability with CSIRO_RCP4.5 showing increase in maize yield whilst CSIRO_RCP4.5 gives a better projection for rice yield. Furthermore, the results estimated the percentage mean yield gain for maize under CSIRO_RCP4.5 and NOAA_ RCP4.5 by about 17 %, 31 % and 48 % for the period 2021-2030, 2031-2040 and 2041-2050 respectively. Mean rice yield lossess of -23 %, -19 % and -23 % were expected for the same period respectively. The study recommended the use of improved rice and maize cultivars to offset the negative effects of climate variability in future.


2021 ◽  
Vol 13 (22) ◽  
pp. 12480
Author(s):  
Fanta F. Jabbi ◽  
Yu’e Li ◽  
Tianyi Zhang ◽  
Wang Bin ◽  
Waseem Hassan ◽  
...  

Variations in the climate constitute a significant threat to the productivity of food crops in the Gambia. A good understanding of the influence of climate variability on crop production is vital for climate resilience and improved food security. This study examined the trends, relationships, and the extent to which growing season temperatures and the SPEI (Standardized Precipitation and Evapotranspiration Index) impacted sorghum, millet, maize, and rice yields in three agro-ecological regions of the Gambia during 1990–2019. Mean temperatures and the SPEI exhibited increasing trends while observed yields showed a decline across all regions. The SPEI had a significant positive relationship with yields, and temperatures were negatively associated with yields. Though yield response to climate variability differs among regions, 20% to 62% of variations in the four crop yields were due to climate trends. The combined effect of the SPEI and temperatures decreased yields from 3.6 kg ha−1 year−1 to 29.4 kg ha−1 year−1, with the most severe decline observed in rice and maize yields in the Sahelian zone. Although uncertainties might arise from not considering related extreme climate events, this study highlights how past climate trends affect cereal yields in the Gambia; thus, any unfavorable change in the local climate could have severe repercussions on the country’s food security. There is a need for concerted efforts to increase investments in adaptation strategies to lessen the effects of the climate for improved crop productivity.


Author(s):  
Motsipiri Calvin Mojapelo ◽  
Johannes Jan Hlongwane ◽  
Abenet Belete

This study aims to estimate sorghum supply elasticity in South Africa. The study used time series data spanning from 1998 to 2016, obtained from the abstracts of agricultural statistics. The Variance Error Correction Model was employed; the study used two dependent variables, these being area and yield response functions. The results have shown that the area response function was found to be a robust model as most of the variables were significant, responsive and elastic. Maize price, as a competing crop for sorghum, negatively influenced the area allocation; however, the remaining variableshad a positive impact on area allocation in the long-run. The yield response function was found not to be robust and hence not adopted. It was therefore concluded that the area response function is more robust than the yield response function, hence sorghum production has shown more response to areaallocation than yield. The findings further indicated that the error correction term for area and for the yield response function was –1.55 and –1.30, respectively. This indicated that the two models were able to revert to equilibrium. Based on the findings, the study recommends that amongst other methods to enhance sorghum output, producers could use improved varieties or hybrids, as this action would result in allocation of more land to sorghum production, following price change.


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