Residue Management and Nutrient Stoichiometry Control Greenhouse Gas and Global Warming Potential Responses in Alfisols

Dharmendra Singh, Sangeeta Lenka (), Narendra Kumar Lenka, Dinesh Kumar Yadav, Shashi S. Yadav, Rameshwar S. Kanwar (), Abhijit Sarkar and Jitendra Kushwaha
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Dharmendra Singh: Department of Soil Science and Agriculture Chemistry, College of Agriculture, Gwalior 474011, India
Sangeeta Lenka: ICAR—Indian Institute of Soil Science, Navi Bagh, Bhopal 462038, India
Narendra Kumar Lenka: ICAR—Indian Institute of Soil Science, Navi Bagh, Bhopal 462038, India
Dinesh Kumar Yadav: ICAR—Indian Institute of Soil Science, Navi Bagh, Bhopal 462038, India
Shashi S. Yadav: Department of Soil Science and Agriculture Chemistry, College of Agriculture, Gwalior 474011, India
Rameshwar S. Kanwar: Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USA
Abhijit Sarkar: ICAR—Indian Institute of Soil Science, Navi Bagh, Bhopal 462038, India
Jitendra Kushwaha: ICAR—Indian Institute of Soil Science, Navi Bagh, Bhopal 462038, India

Sustainability, 2024, vol. 16, issue 10, 1-16

Abstract: Although crop residue returns are extensively practiced in agriculture, large uncertainties remain about greenhouse gas (GHG) emissions and global warming potential (GWP) responses to residue return (RR) rates under different residue placements and nutrient supplements. We conducted a laboratory mesocosm experiment in Alfisol in central India to investigate the responses of soil GHG emissions (CO 2 , N 2 O, and CH 4 ) and the global warming potential to four wheat RR rates (R0: no residue; R5: 5 Mg/ha; R10: 10 Mg/ha; R15: 15 Mg/ha) and two placements (surface [Rsur] and incorporated [Rinc]) under three nutrient supplement levels (NSLs) (NS0: no nutrients, NS1: nutrients (N and P) added to balance the stoichiometry of C:N:P to achieve 30% humification in RR at 5 t/ha, NS2: 3 × NS1). The results demonstrated a significant ( p < 0.05) interaction effect of RR × NSL × residue placement on N 2 O emission. However, CH 4 and GWP responses to the RR rate were independent of NSL. N 2 O fluxes ranged from −2.3 µg N 2 O-N kg −1 soil (R5 NS0 Rsur) to 43.8 µg N 2 O-N kg −1 soil (R10 NS2 Rinc). A non-linear quadratic model yielded the best fit for N 2 O emissions with RR rate (R 2 ranging from 0.55 to 0.99) in all NSLs and residue placements. Co-applying wheat residue at 10 and 15 Mg/ha at NS1 reduced CH 4 and N 2 O emissions (cf. R0 at NS1). However, increasing NSLs in NS2 reduced the nutrient stoichiometry to < 12:1 (C:N) and < 50:1 (C:P), which increased N 2 O emissions in all RR rates (cf. R0) across all residue placements. Averaged across nutrient levels and residue placements, the order of the effects of RR rates on CH 4 emissions (µg C kg −1 soil) was R10 (5.5) > R5 (3.8) > R15 (2.6) > R0 (1.6). Our results demonstrated a significant linear response of total GWP to RR rates R15 > R10 > R5 > R0, ranging from 201.4 to 1563.6 mg CO 2 eq kg −1 soil. In conclusion, quadratic/linear responses of GHGs to RR rates underscore the need to optimize RR rates with nutrient supplements and residue placement to reduce GHG emissions and GWP while ensuring optimal soil health and crop productivity.

Keywords: residue quantity; residue placement; nutrient stoichiometry; GWP; GHG (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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