Climate trends and soybean production since 1970 in Mississippi: Empirical evidence from ARDL model

Ramandeep Kumar Sharma; Jagmandeep Dhillon; Pushp Kumar; Michael J Mulvaney; Vaughn Reed; Raju Bheemanahalli; Michael S Cox; Meetpal S Kukal; Krishna N Reddy

doi:10.1016/j.scitotenv.2023.167046

Climate trends and soybean production since 1970 in Mississippi: Empirical evidence from ARDL model

Sci Total Environ. 2023 Dec 20:905:167046. doi: 10.1016/j.scitotenv.2023.167046. Epub 2023 Sep 13.

Authors

Ramandeep Kumar Sharma¹, Jagmandeep Dhillon², Pushp Kumar³, Michael J Mulvaney¹, Vaughn Reed¹, Raju Bheemanahalli¹, Michael S Cox¹, Meetpal S Kukal⁴, Krishna N Reddy⁵

Affiliations

¹ Department of Plant and Soil Sciences, Mississippi State University, MS, USA.
² Department of Plant and Soil Sciences, Mississippi State University, MS, USA. Electronic address: jagman.dhillon@msstate.edu.
³ School of Humanities, Social Sciences, and Management, Indian Institute of Technology, Odisha, India.
⁴ Department of Agricultural and Biological Engineering, The Pennsylvania State University, State College, PA, USA.
⁵ Crop Production Systems Research Unit, USDA-ARS, Stoneville, MS, USA.

PMID: 37714355
DOI: 10.1016/j.scitotenv.2023.167046

Abstract

Studying historical response of crops to weather conditions at a finer scale is essential for devising agricultural strategies tailored to expected climate changes. However, determining the relationship between crop and climate in Mississippi (MS) remains elusive. Therefore, this research attempted to i) estimate climate trends between 1970 and 2020 in MS during the soybean growing season (SGS) using the Mann-Kendall and Sen slope method, ii) calculate the impact of climate change on soybean yield using an auto-regressive distributive lag (ARDL) econometric model, and iii) identify the most critical months from a crop-climate perspective by generating a correlation between the detrended yield and the monthly average for each climatic variable. Specific variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), carbon dioxide emissions (CO₂), and relative humidity (RH). All required diagnostic-tests i.e., pre-analysis, post-analysis, model-sensitivity, and assessing the models' goodness-of-fit were performed and statistical standards were met. A positive trend in Tmin (+0.25 °C/decade), and a negative trend in DTR (-0.18 °C/decade) was found. Although Tmax, PT, and RH showed non-significant trends, numerical changes were noted as +0.11 °C/decade, +3.03 mm/decade, and -0.06 %/decade, respectively. Furthermore, soybean yield was positively correlated with Tmin (in June and September), PT (in July and August), and RH (in July), but negatively correlated with Tmax (in July and August) and DTR (in June, July, and August). Soybean yield was observed to be significantly reduced by 18.11 % over the long-term and by 5.51 % over the short-term for every 1 °C increase in Tmax. With every unit increase in Tmin and CO₂ emissions, the yield of soybeans increased significantly by 7.76 % and 3.04 %, respectively. Altogether, soybeans in MS exhibited variable sensitivity to short- and long-terms climatic changes. The results highlight the importance of testing climate-resilient agronomic practices and cultivars that encompass asymmetric sensitivities in response to climatic conditions of MS.

Keywords: ARDL model; Abiotic stresses; Climate change; Crop modeling; Crop yield; Food security.

Published by Elsevier B.V.

MeSH terms

Carbon Dioxide*
Climate Change
Crops, Agricultural
Glycine max*
Mississippi
Temperature
Weather

Substances

Carbon Dioxide