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Future yields of double-cropping systems in the Southern Amazon, Brazil, under climate change and technological development

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  • Hampf, Anna C.
  • Stella, Tommaso
  • Berg-Mohnicke, Michael
  • Kawohl, Tobias
  • Kilian, Markus
  • Nendel, Claas

Abstract

Climate change is a major threat to agricultural production, particularly in vulnerable ecosystems such as the Southern Amazon, where millions of hectares of tropical forest have been deforested for the purpose of cattle ranching and the expansion of soybean fields. At the same time, genetic progress and improved crop management have led to considerable yield increases in the states of Mato Grosso (MT) and Pará (PA), which are the hotspots of deforestation. The aim of this study is to assess the impact of climate change and technological development on double-cropping systems in the Southern Amazon up to the year 2040. Future crop yields are simulated with the Model for Nitrogen and Carbon in Agro-ecosystems (MONICA). Climate projections are based on the IPCC SRES A1B and were generated with the Weather Research and Forecasting (WRF) model and the Statistical Regional Model (STAR) in a horizontal resolution of 900m×900m. A novel approach of forecasting technology-driven yield increases based on biophysical yield maxima (BYM) was developed to account for gains in breeding and crop management improvements. Results from crop growth simulations indicate that soybean yields will stay nearly unchanged (MG VIII 0%, MG VII+1%), whereas maize and cotton productivity will decrease by 28% and 17%, respectively, between 2015–19 and 2035–40 (average of WRF and STAR scenario). This decline in second season crop productivity is traceable to future lessening of precipitation and higher temperatures. Estimation of technology trends suggests that advances in genetics and crop management are likely to offset the negative effects of climate change by increasing soybean yields by 40% (MG VII+39%, MG VIII+40%) and maize and cotton yields by 68% and 59%, respectively, during the same time period. Estimations of BYM signal a low potential for agricultural exploitation of current rainforest areas. This stands in contrast to the unique ecosystem services (e.g., biodiversity, carbon storage) the Amazonian rainforest provides and calls for more effective control mechanisms to prevent further deforestation.

Suggested Citation

  • Hampf, Anna C. & Stella, Tommaso & Berg-Mohnicke, Michael & Kawohl, Tobias & Kilian, Markus & Nendel, Claas, 2020. "Future yields of double-cropping systems in the Southern Amazon, Brazil, under climate change and technological development," Agricultural Systems, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:agisys:v:177:y:2020:i:c:s0308521x18312617
    DOI: 10.1016/j.agsy.2019.102707
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    5. Massigoge, Ignacio & Carcedo, Ana & de Borja Reis, Andre Froes & Mitchell, Clay & Day, Scott & Oliverio, Joaquin & Truong, Sandra H. & McCormick, Ryan F. & Rotundo, Jose & Lira, Sara & Ciampitti, Igna, 2023. "Exploring avenues for agricultural intensification: A case study for maize-soybean in the Southern US region," Agricultural Systems, Elsevier, vol. 204(C).
    6. Minghui Zhang & Gabriel Abrahao & Sally Thompson, 2021. "Sensitivity of soybean planting date to wet season onset in Mato Grosso, Brazil, and implications under climate change," Climatic Change, Springer, vol. 168(3), pages 1-28, October.
    7. Adeline M. Maciel & Michelle C. A. Picoli & Lubia Vinhas & Gilberto Camara, 2020. "Identifying Land Use Change Trajectories in Brazil’s Agricultural Frontier," Land, MDPI, vol. 9(12), pages 1-16, December.
    8. Tingting Li & Yanfei Wang & Changquan Liu & Shuangshuang Tu, 2021. "Research on Identification of Multiple Cropping Index of Farmland and Regional Optimization Scheme in China Based on NDVI Data," Land, MDPI, vol. 10(8), pages 1-16, August.
    9. Luncheng You & Gerard H. Ros & Yongliang Chen & Qi Shao & Madaline D. Young & Fusuo Zhang & Wim de Vries, 2023. "Global mean nitrogen recovery efficiency in croplands can be enhanced by optimal nutrient, crop and soil management practices," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    10. Guo, Shibo & Zhang, Zhentao & Guo, Erjing & Fu, Zhenzhen & Gong, Jingjin & Yang, Xiaoguang, 2022. "Historical and projected impacts of climate change and technology on soybean yield in China," Agricultural Systems, Elsevier, vol. 203(C).

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