Environmental Cost Implications of Climate Variability in Arable Crops Farming in Oyo and Ogun States, Nigeria

Emmanuel Olatubosun Sowunmi¹, Luke O. Okojie², Samuel A. Adewuyi³

¹ Lecturer, D. S. Adegbenro ICT Polytechnic, Itori-Ewekoro, Nigeria.

^2,3 Professor, Department of Agricultural Economics and Farm Management, Federal University of Agriculture, Abeokuta [FUNAAB], Nigeria. 

Abstract

This study evaluates the environmental cost implications of climate variability on arable crop farming in Oyo and Ogun States, Nigeria. A multistage sampling procedure was employed to choose 392 participants. The sampled farmers of arable crops in Ogun and Oyo states provided the primary data, and the geo-information pool provided the secondary data on weather patterns, temperature fluctuations, and rainfall. Data obtained was analyzed using descriptive statistics, climate variability indices, Dichotomous-Choice Contingent Valuation Method (DC-CVM) and binary choice logistic regression models. Findings indicate that 57.9%, 42.1% and 71.7% of the respondents were male, married with tertiary education, and the major occupation was farming (78.6%), with a mean age, monthly farm income and household size of 40 years, ₦86,275.51 and 4 persons, respectively. Climate variability was evident in the study area, with Ogun State exhibiting higher levels of climate variability (0.79) with respect to Oyo State (0.29). About 51.3% of the respondents had low awareness of climate variability, while 51.0% and 44.6% reported that reduced crop yields and decreased market value of crop yields, respectively, were the major effects of climate variability on arable crops in the study area.  The DC-CVM model shows that the mean willingness of arable crop farmers to pay for climate adaptation strategies was ₦74.82 per month, and key determinants of environmental cost included farm size (β = 0.241, p<0.05) and education level (β = 0.096, p<0.05). The study concludes that climate variability exacerbates environmental costs, underscoring the need for sustainable farming practices.

Keywords: Environmental cost, climate variability, contingent valuation, adaptation, Nigeria.

References

1. Altieri, M.A., Nicholls, C.I., Henao, A. and Lana, M.A. (2015) ‘Agroecology and the design of climate change-resilient farming systems’, Agronomy for Sustainable Development, 35(3), pp. 869-890.
2. Anderson, R., Bayer, P.E. and Edwards, D. (2020) ‘Climate change and the need for agricultural adaptation’, Current Opinion in Plant Biology, 56, pp. 197-202.
3. Aryal, J.P., Sapkota, T.B., Khurana, R., Khatri-Chhetri, A., Rahut, D.B. and Jat, M.L. (2020) ‘Climate change and agriculture in South Asia: Adaptation options in smallholder production systems’, Environment, Development and Sustainability, 22(6), pp. 5045-5075.
4. Bai, D., Ye, L., Yang, Z. and Wang, G. (2024) ‘Impact of  climate change on agricultural productivity: a combination of spatial Durbin model and entropy approaches’, International Journal of Climate Change Strategies and Management, 16(4), pp. 26–48.
5. Below, T., Schmid, J.C. and Sieber, S. (2015) ‘Farmers’ knowledge and perception of climatic risks and options for climate change adaptation: a case study from two Tanzanian villages’, Regional Environmental Change, 15, pp. 1169–1180.
6. Bodner, G., Nakhforoosh, A. and Kaul, H.P. (2015) ‘Management of crop water under drought: a review’, Agronomy for Sustainable Development, 35, pp. 401–442.
7. Herrington, C.L., Ortega, D.L., Maredia, M.K. and Reyes, B.A. (2023) ‘Does bid quantity matter? Comparing farmer willingness-to-pay for prespecified vs actual quantities of biofortified bean and maize seedin a non-hypothetical field experiment’, In: 2023 Annual Meeting of Agricultural and Applied Economics Association. Washington DC.
8. Cooper, J.C. and Loomis, J. (1992) ‘Sensitivity of willingness-to-pay to bid design in dichotomous choice contingent valuation models’, Land Economics, 68(2), pp. 211-224.
9. Franklin, S.M., Collins, M.M., Milka, N.K., Joseph, M.M., Onesmus, K.N., Chris, A.S., Jeremiah, M.O., Daniel, N.M., Elizabeth, A.O. and Felix, K.N. (2021) ‘Determinants of farmers’ perceptions of climate variability, mitigation, and adaptation strategies in the central highlands of Kenya’, Weather and Climate Extremes, 34, 100374.
10. Godde, C.M., Mason-D’Croz, D., Mayberry, D.E., Thornton, P.K. and Herrero, M. (2021) ‘Impacts of climate change on the livestock food supply chain; a review of the evidence’, Global Food Security, 28, 100488.
11. Gupta, P., Singh, J., Verma, S., Chandel, A. S. and Bhatla, R. (2021) ‘Impact of climate change and water quality degradation on food security and agriculture’. In: Water Conservation in the Era of Global Climate Change; Thokchom, B., et al.  Elsevier.
12. Habib-ur-Rahman, M., Ahmad, A., Raza, A., Hasnain, M.U., Alharby, H.F., Alzahrani, Y.M., Bamagoos, A.A., Hakeem, K.R., Ahmad, S. and Nasim, W. (2022) ‘Impact of climate change on agricultural production; issues, challenges, and opportunities in Asia’, Frontiers in Plant Science, 13, 925548.
13. Hanemann, M. (1984) ‘Welfare evaluation in contingent valuation experiments with discrete responses’, American Journal of Agricultural Economics, 66, pp. 332-341
14. Hanley, N., Shogren, J.F. and White, B. (2016) Environmental Economics: in theory and practice. Macmillan Education, Limited.
15. Ibrahim, S.B., Ayinde, I.A. and Arowolo, A.O. (2015) ‘Analysis of arable crop farmers’ awareness to causes and effects of climate change in southwestern Nigeria’, International Journal of Social Economics, 42(7), pp. 614-628. https://doi.org/10.1108/IJSE-09-2013-0201
16. Jones, J.W., Antle, J.M., Basso, B., Boote, K.J., Conant, R.T., et al. (2017) ‘Brief history of agricultural systems modeling’, Agricultural systems, 155, pp. 240-254.
17. Karimi, V., Karami, E. and Keshavarz, M. (2018) ‘Climate change and agriculture: Impacts and adaptive responses in Iran’, Journal of Integrative Agriculture, 17(1), pp. 1-15.
18. Kadiyala, M.D.M., Nedumaran, S., Singh, P., Chukka, S., Irshad, M. A. and Bantilan, M.C.S. (2015) ‘An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change’, Science of the Total Environment,521, pp. 123-134.
19. Matemilola, S. and Elegbede, I. (2017) ‘The challenges of food security in Nigeria’, Open Access Library Journal, 4(12), pp. 1-22.
20. Michael, A. and Friedrich, S. (2013) ‘Considering household size in contingent valuation studies’, Environmental Economics, 4(1), pp. 112-123.
21. Niles, M.T., Brown, M. and Dynes, R. (2016) ‘Farmer’s intended and actual adoption of climate change mitigation and adaptation strategies’, Climatic Change, 135(2), pp. 277–295.
22. Okojie, L.O. (2007) ‘Socio-economic and environmental attitudinal determinants of rainforest protection: a logit model analysis’, ASSET An International Journal Series C, 2(1), pp. 204-218.
23. Parry, M.L. (2019) ‘Climate change and world agriculture. Routledge.
24. Reed, M.S. and Stringer, L.C. (2016) Land degradation, desertification and climate change: Anticipating, assessing and adapting to future change. Routledge.
25. Turcin, B. and Giraud, K. (2001) ‘Contingent valuation willingness to pay with respect to geographically nested samples: case study of Alaskan Steller Sea Lion’, In: Annual Meeting of Western Regional Project W-133, Miami FL: United States, Department of Agriculture.
26. Udofia, S.K. and Fasona, M.J. (2020) ‘Influence of climate variability on biomass density of South West Nigeria: a case study of Oyo and Ogun States’, Unilag Journal of Medicine, Science and Technology (UJMST) (CEBCEM Special Edition), 8(1), pp. 237-258.