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Investigating the tipping point of crop productivity induced by changing climatic variables

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Abstract

South Asia is comprised of several countries, including Bangladesh, Pakistan, India, and Sri Lanka, all ranked highly at risk of climatic variability. The region’s susceptibility to climate change can be attributed to both its spatial and inherent characteristics. Considering the countries’ high dependence on agricultural products, to support their economies and growing populations, it is vital to measure the factors impacting crop productivity. This study quantifies the change in temperature and precipitation, coupled with their respective effects on the productivity of three major crops, wheat, rice and cotton, within two of Pakistan’s largest provinces: Punjab and Sindh. Based on the collated data, multivariate regression analysis is conducted. Moreover, highly vulnerable areas to climate change have been identified under RCP scenarios 4.5 and 8.5, until the end of this century. Results reveal that there is a substantial increasing trend in temperature, whereas precipitation has high inter-annual variability. Regression outcomes, based on fixed/random effects models, indicate that temperature above threshold values of 24.3 °C, 33.0 °C and 32.0 °C for wheat, rice and cotton, respectively, negatively impacts productivity (statistically significant). Precipitation is statistically insignificant in explaining its role in crop productivity. Overall, the region is heading towards temperature and threshold exceedances at an alarming rate, which will impact the overall availability of suitable crop-growing areas.

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Notes

  1. The two selected scenarios RCPs 4.5 and 8.5; the former is a stabilization scenario, whereas the latter illustrates rising emissions thorough out the century.

  2. Baseline and projected data were developed by the Numerical Modelling group of Research and Development Division, PMD, Islamabad, Pakistan) using the “Community Climate System Model, version 4” by the National Center for Atmospheric Research (NCAR).

  3. The H0 assumes that the favoured model is random effects (Greene 2008). Prob > chi-square values less than 0.05 indicate that fixed effects model is the correct choice, rejecting the null hypothesis (Torres-Reyna 2007).

  4. Mann Kendall trend test

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Acknowledgements

The authors are grateful to Pakistan Meteorological Department, Islamabad, Pakistan; (especially the Numerical Modelling group of Research and Development Division) for the provision of temperature and precipitation data, along with the Pakistan Bureau of Statistics and Agriculture Department of Punjab, Pakistan, for the provision of district-wise crop yield and area cultivated data. Authors are also grateful to NUST for providing financial support from post-graduate R&D fund to conduct this study. Authors are grateful to the National University of Sciences & Technology (NUST), Pakistan, for providing financial support from post-graduate R&D fund to conduct this study.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the Pakistan Meteorological Department, Islamabad, Pakistan (temperature and precipitation data), and Pakistan Bureau of Statistics/Agriculture Department of Punjab (crop yield and production data) repository.

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Authors and Affiliations

  1. Institute of Environmental Sciences and Engineering, National University of Sciences and Technology, Islamabad, 44000, Pakistan

    Fatimah Mahmood & Muhammad Fahim Khokhar

  2. School of Social Sciences & Humanities, National University of Sciences and Technology, Islamabad, 44000, Pakistan

    Zafar Mahmood

Authors
  1. Fatimah Mahmood
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  2. Muhammad Fahim Khokhar
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  3. Zafar Mahmood
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Contributions

a) FM envisaged the initial idea for the research study and was responsible for undertaking data acquisition, processing and analysis, along with final composition and writing of the main manuscript, including the figures and tables.

b) MFK supervised the research work and oversaw the analysis of temperature, precipitation and crop productivity, along with input into statistical analysis and reviewed the final manuscript.

c) ZM provided technical assistance for selection and analysis of the statistical models used and reviewed the manuscript.

Corresponding author

Correspondence to Muhammad Fahim Khokhar.

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Mahmood, F., Khokhar, M.F. & Mahmood, Z. Investigating the tipping point of crop productivity induced by changing climatic variables. Environ Sci Pollut Res 28, 2923–2933 (2021). https://doi.org/10.1007/s11356-020-10655-w

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  • DOI: https://doi.org/10.1007/s11356-020-10655-w

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