Adaptation to Climate Change and Impact on Smallholder Farmers’ Food Security in South Africa
Abstract
:1. Introduction
2. Methodology
2.1. Conceptual Framework
2.2. Food Security Measurement
2.3. Empirical Specification
Average Treatments: ATE and ATT
2.4. The Study Areas, Sampling and Data Collection Techniques
3. Results and Discussion
3.1. Descriptive Statistics
3.2. Determinants of Climate Change Adaptation
3.3. Determinants of Household Food Insecurity
3.4. Impact of Climate Change Adaptation on Food Security
4. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Bhuiyan, C.; Saha, A.K.; Bandyopadhyay, N.; Kogan, F.N. Analyzing the impact of thermal stress on vegetation health and agricultural drought–a case study from Gujarat, India. GIScience Remote Sens. 2017, 54, 678–699. [Google Scholar] [CrossRef]
- Masipa, T. The impact of climate change on food security in South Africa: Current realities and challenges ahead. Jàmbá J. Disaster Risk Stud. 2017, 9, 1–7. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bakht, S.; Safdar, K.; Khair, K.U.; Fatima, A.; Fayyaz, A.; Ali, S.M.; Munir, H.; Farid, M. The Response of Major Food Crops to Drought Stress: Physiological and Biochemical Responses. In Agronomic Crops; Springer: Singapore, 2020; pp. 93–115. [Google Scholar]
- Food and Agriculture Organization of the United Nations. The Impact of Natural Hazards and Disasters on Agriculture and Food Security and Nutrition: A Call for Action to Build Resilient Livelihoods; Food and Agriculture Organization of the United Nations: Rome, Italy, 2015. [Google Scholar]
- Bwalya, M. Comprehensive Africa Agriculture Development Programme (CAADP) to Reduce Food Security Emergencies in Africa; NEPAD Planning and Coordinating Agency: Johannesburg, South Africa, 2013. [Google Scholar]
- Nangombe, S.; Zhou, T.; Zhang, W.; Wu, B.; Hu, S.; Zou, L.; Li, D. Record-breaking climate extremes in Africa under stabilized 1.5 C and 2 C global warming scenarios. Nat. Clim. Change 2018, 8, 375–380. [Google Scholar] [CrossRef]
- Sousa, P.M.; Blamey, R.C.; Reason, C.J.; Ramos, A.M.; Trigo, R.M. The ‘Day Zero’Cape Town drought and the poleward migration of moisture corridors. Environ. Res. Lett. 2018, 13, 124025. [Google Scholar] [CrossRef] [Green Version]
- Mugambiwa, S.S.; Tirivangasi, H.M. Climate change: A threat towards achieving ‘Sustainable Development Goal number two’ (end hunger, achieve food security and improved nutrition and promote sustainable agriculture) in South Africa. Jàmbá J. Disaster Risk Stud. 2017, 9, 1–6. [Google Scholar] [CrossRef] [Green Version]
- Cammarano, D.; Valdivia, R.O.; Beletse, Y.G.; Durand, W.; Crespo, O.; Tesfuhuney, W.A.; Antle, J. Integrated assessment of climate change impacts on crop productivity and income of commercial maize farms in northeast South Africa. Food Secur. 2020, 12, 659–678. [Google Scholar] [CrossRef]
- Shisanya, S.; Mafongoya, P. Adaptation to climate change and the impacts on household food security among rural farmers in uMzinyathi District of Kwazulu-Natal, South Africa. Food Secur. 2016, 8, 597–608. [Google Scholar] [CrossRef]
- Adetoro, A.A.; Abraham, S.; Paraskevopoulos, A.L.; Owusu-Sekyere, E.; Jordaan, H.; Orimoloye, I.R. Alleviating water shortages by decreasing water footprint in sugarcane production: The impacts of different soil mulching and irrigation systems in South Africa. Groundw. Sustain. Dev. 2020, 11, 100464. [Google Scholar] [CrossRef]
- Morton, J.F. The impact of climate change on smallholder and subsistence agriculture. Proc. Natl. Acad. Sci. USA 2007, 104, 19680–19685. [Google Scholar] [CrossRef] [Green Version]
- Harvey, C.A.; Viguera, B.; Vignola, R.; Viguera, B.; Chain-Guadarrama, A.; Vignola, R.; Alpizar, F. Climate change impacts and adaptation among smallholder farmers in Central America. Agric. Food Security 2018, 7, 1–20. [Google Scholar] [CrossRef]
- Wiebe, K.; Robinson, S.; Cattaneo, A. Climate change, agriculture and food security: Impacts and the potential for adaptation and mitigation. Sustain. Food Agric. 2019, 55–74. [Google Scholar] [CrossRef]
- Ojo, T.O.; Adetoro, A.A.; Ogundeji, A.A.; Belle, J.A. Quantifying the determinants of climate change adaptation strategies and farmers’ access to credit in South Africa. Sci. Total Environ. 2021, 792, 148499. [Google Scholar] [CrossRef] [PubMed]
- Owen, G. What makes climate change adaptation effective? A systematic review of the literature. Glob. Environ. Change 2020, 62, 102071. [Google Scholar] [CrossRef]
- Adeagbo, O.A.; Ojo, T.O.; Adetoro, A.A. Understanding the determinants of climate change adaptation strategies among smallholder maize farmers in South-west, Nigeria. Heliyon 2021, 7, e06231. [Google Scholar] [CrossRef]
- Akanbi, R.T.; Davis, N.; Ndarana, T. Climate change and maize production in the Vaal catchment of South Africa: Assessment of farmers’ awareness, perceptions and adaptation strategies. Clim. Res. 2021, 82, 191–209. [Google Scholar] [CrossRef]
- Fadina, A.M.R.; Barjolle, D. Farmers’ adaptation strategies to climate change and their implications in the Zou department of South Benin. Environments 2018, 5, 15. [Google Scholar] [CrossRef] [Green Version]
- Kogo, B.K.; Kumar, L.; Koech, R. Climate change and variability in Kenya: A review of impacts on agriculture and food security. Environ. Dev. Sustain. 2021, 23, 23–43. [Google Scholar] [CrossRef]
- Asare-Nuamah, P.; Mandaza, M.S. Climate change adaptation strategies and food security of smallholder farmers in the rural Adansi North District of Ghana. In Handbook of Climate Change Management: Research, Leadership, Transformation; Springer International Publishing: Berlin/Heidelberg, Germany, 2020; pp. 1–20. [Google Scholar]
- Ojo, T.O.; Baiyegunhi, L.J.S. Determinants of climate change adaptation strategies and its impact on the net farm income of rice farmers in south-west Nigeria. Land Use Policy 2020, 95, 103946. [Google Scholar] [CrossRef]
- Oluwatayo, I.B. Towards assuring food security in South Africa: Smallholder farmers as drivers. AIMS Agric. Food 2019, 4, 485–500. [Google Scholar] [CrossRef]
- Di Falco, S.; Veronesi, M.; Yesuf, M. Does adaptation to climate change provide food security? A micro-perspective from Ethiopia. Am. J. Agric. Econ. 2011, 93, 829–846. [Google Scholar] [CrossRef] [Green Version]
- Webber, H.; Gaiser, T.; Ewert, F. What role can crop models play in supporting climate change adaptation decisions to enhance food security in Sub-Saharan Africa? Agric. Syst. 2014, 127, 161–177. [Google Scholar] [CrossRef]
- Below, T.B.; Schmid, J.C.; Sieber, S. Farmers’ knowledge and perception of climatic risks and options for climate change adaptation: A case study from two Tanzanian villages. Reg. Environ. Change 2015, 15, 1169–1180. [Google Scholar] [CrossRef]
- Douxchamps, S.; Van Wijk, M.T.; Silvestri, S.; Moussa, A.S.; Quiros, C.; Ndour, N.Y.B.; Buah, S.; Somé, L.; Herrero, M.; Kristjanson, P.; et al. Linking agricultural adaptation strategies, food security and vulnerability: Evidence from West Africa. Reg. Environ. Change 2016, 16, 1305–1317. [Google Scholar] [CrossRef] [Green Version]
- Donkor, E.; Owusu, V.; Owusu-Sekyere, E.; Ogundeji, A.A. The adoption of farm innovations among rice producers in Northern Ghana: Implications for sustainable rice supply. Agriculture 2018, 8, 121. [Google Scholar] [CrossRef] [Green Version]
- Asfaw, A.; Simane, B.; Bantider, A.; Hassen, A. Determinants in the adoption of climate change adaptation strategies: Evidence from rainfed-dependent smallholder farmers in north-central Ethiopia (Woleka sub-basin). Environ. Dev. Sustain. 2019, 21, 2535–2565. [Google Scholar] [CrossRef]
- Soglo, Y.Y.; Nonvide, G.M.A. Climate change perceptions and responsive strategies in Benin: The case of maize farmers. Clim. Change 2019, 155, 245–256. [Google Scholar] [CrossRef]
- Montana, E.; Diaz, H.P.; Hurlbert, M. Development, local livelihoods, and vulnerabilities to global environmental change in the South American Dry Andes. Reg. Environ. Chang. 2016, 16, 2215–2228. [Google Scholar] [CrossRef]
- Reddy, A.A.; Bhattacharya, A.; Reddy, S.V.; Ricart, S. Farmers’ Distress Index: An Approach for an Action Plan to Reduce Vulnerability in the Drylands of India. Land 2021, 10, 1236. [Google Scholar] [CrossRef]
- Guerrero Lara, L.; Pereira, L.M.; Ravera, F.; Jiménez-Aceituno, A. Flipping the Tortilla: Social-ecological innovations and traditional ecological knowledge for more sustainable agri-food systems in Spain. Sustainability 2019, 11, 1222. [Google Scholar] [CrossRef] [Green Version]
- Cafiero, C.; Viviani, S.; Nord, M. Food security measurement in a global context: The food insecurity experience scale. Measurement 2018, 116, 146–152. [Google Scholar] [CrossRef]
- Maxwell, D.; Coates, J. Reaching for the Stars? Identifying Universal Measures of Food Insecurity; Paper presented at the Presentation at the FAO International Scientific Symposium; Food and Agriculture Organization: Rome, Italy, 2012. [Google Scholar]
- Maxwell, D.; Coates, J.; Vaitla, B. How Do Different Indicators of Household Food Security Compare? Empirical Evidence from Tigray; Feinstein International Center, Tufts University: Medford, MA, USA, 2013; p. 26. [Google Scholar]
- Ballard, T.J.; Kepple, A.W.; Carfielo, C. Food Insecurity Experience Scale: Development of Global Standard for Monitoring Hunger Worldwide; FAO Technical Paper Version 1.1; Food and Agriculture Organization: Rome, Italy, 2013. [Google Scholar]
- Mohammadi, F.; Omidvar, N.; Houshiar-Red, A.; Mohammad-Reza, K.; Abdollahi, M.; Mehrabi, Y. Validity of an adapted household food insecurity experience access scale in urban households in Iran. Public Health Nutr. 2012, 15, 149–157. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Coates, J.; Swindale, A.; Bilinsky, P. Household Food Insecurity Access Scale (HFIAS) for Measurement of Food Access: Indicator Guide (Version 3); Food and Nutrition Technical Assistance Project (FANTA); Academy for Educational Development: Washington, DC, USA, 2007. [Google Scholar]
- Heckman, J.J. Sample Selection Bias as a Specification Error. Econometrica 1979, 47, 153–161. [Google Scholar] [CrossRef]
- Fang, H.; Ali, M.M.; Rizzo, J.A. Does smoking affect body weight and obesity in China? Econ. Hum. Biol. 2009, 7, 334–350. [Google Scholar] [CrossRef] [PubMed]
- Wooldridge, J.M. Econometric Analysis of Cross Section and Panel Data, 2nd ed.; MIT Press: Cambridge, MA, USA, 2010. [Google Scholar]
- Copeland, A.L.; McVay, M.A.; Martin, P.D.; Rash, C.J.; Kendzor, D.E.; Baillie, L.E.; Spearsg, C.A.; Geiselmanab, P.J. Smoking relapse and weight gain prevention program for postmenopausal weight-concerned women: A pilot study. Eat. Behav. 2015, 18, 107–114. [Google Scholar] [CrossRef] [Green Version]
- Asfaw, S.; Di Battistab, F.; Lipper, L. Agricultural Technology Adoption under Climate Change in the Sahel: Micro-evidence from Niger. J. Afr. Econ. 2016, 25, 1–33. [Google Scholar] [CrossRef]
- Gregory, C.A. Estimating treatment effects for ordered outcomes using maximum simulated likelihood. Stata J. 2015, 15, 756–774. [Google Scholar] [CrossRef] [Green Version]
- Mabe, F.N.; Mumuni, E.; Sulemana, N. Does smallholder farmers’ awareness of sustainable development goal 2 improve household food security in the Northern Region of Ghana? Agric. Food Secur. 2021, 10, 9. [Google Scholar] [CrossRef]
- Jaworowska, A.; Blackham, T.; Davies, I.G.; Stevenson, L. Nutritional challenges and health implications of takeaway and fast food. Nutr. Rev. 2013, 71, 310–318. [Google Scholar] [CrossRef]
- Drukker, D.M.; Gates, R. Generating Halton sequences using Mata. Stata J. 2006, 6, 214–228. [Google Scholar] [CrossRef] [Green Version]
- Deb, P.; Trivedi, P.K. Maximum simulated likelihood estimation of a negative binomial regression model with multinomial endogenous treatment. Stata J. 2006, 6, 246–255. [Google Scholar] [CrossRef] [Green Version]
- Department of Rural Development and Land Reform (DRDLR). Land Reform News. 2015. Available online: http://www.ruraldevelopment.gov.za/ (accessed on 20 March 2015).
- Cochran, W.G. Sampling Techniques, 3rd ed.; John Wiley & Sons: New York, NY, USA, 1977. [Google Scholar]
- Abid, M.; Ali, A.; Rahut, D.B.; Raza, M. Ex-ante and Ex-post coping strategies for climatic shocks and adaptation determinants in rural Malawi. Clim. Risk Manag. 2020, 27, 100200. [Google Scholar] [CrossRef]
- Asfaw, E.; Suryabhagavan, K.V.; Argaw, M. Soil salinity modeling and mapping using remote sensing and GIS: The case of Wonji sugar cane irrigation farm, Ethiopia. J. Saudi Soc. Agric. Sci. 2018, 17, 250–258. [Google Scholar] [CrossRef] [Green Version]
- Danso-Abbeam, G.; Ojo, T.O.; Baiyegunhi, L.J.S.; Ogundeji, A.A. Climate change adaptation strategies by smallholder farmers in Nigeria: Does non-farm employment play any role? Heliyon 2021, 7, e07162. [Google Scholar] [CrossRef] [PubMed]
- Islam, A.R.M.T.; Shill, B.K.; Salam, R.; Siddik, M.N.A.; Patwary, M.A. Insight into farmers’ agricultural adaptive strategy to climate change in northern Bangladesh. Environ. Dev. Sustain. 2021, 23, 2439–2464. [Google Scholar] [CrossRef]
- Fosu-Mensah, B.Y.; Vlek, P.L.; MacCarthy, D.S. Farmers’ perception and adaptation to climate change: A case study of Sekyedumase district in Ghana. Environ. Dev. Sustain. 2012, 14, 495–505. [Google Scholar] [CrossRef]
- Jianjun, J.; Yiwei, G.; Xiaomin, W.; Nam, P.K. Farmers’ risk preferences and their climate change adaptation strategies in the Yongqiao District, China. Land Use Policy 2015, 47, 365–372. [Google Scholar] [CrossRef]
- Jin, J.; Wang, X.; Gao, Y. Gender differences in farmers’ responses to climate change adaptation in Yongqiao District, China. Sci. Total Environ. 2015, 538, 942–948. [Google Scholar] [CrossRef]
- Getachew, S.; Tilahun, T.; Teshager, M. Determinants of agro-pastoralist climate change adaptation strategies: Case of Rayitu Woredas, Oromiya Region, Ethiopia. Res. J. Environ. Sci. 2014, 8, 300–317. [Google Scholar] [CrossRef] [Green Version]
- Ndiritu, S.W.; Muricho, G. Impact of climate change adaptation on food security: Evidence from semi-arid lands, Kenya. Clim. Change 2021, 167, 1–20. [Google Scholar] [CrossRef]
- Danso-Abbeam, G.; Baiyegunhi, L.J.S.; Laing, M.D.; Hussein, S. Understanding the determinants of food security among rural households in Rwanda. Ecol. Food Nutr. 2022, 61, 1–19. [Google Scholar] [CrossRef]
- Tefera, T.; Tefera, F. Determinants of households food security and coping strategies for food shortfall in mareko district, guraghe zone southern ethiopia. J. Food Secur. 2014, 2, 92–99. [Google Scholar]
- Asghar, N.; Salman, A. Impact of agriculture credit on food production and food security in Pakistan. Parkistan J. Commer. Social Sci. 2018, 12, 851–864. [Google Scholar]
Variables | Pooled Sample | Adopters | Non-Adopters | t-Values | |
---|---|---|---|---|---|
Description | Mean (SD) | Mean (SD) | Mean (SD) | ||
Food insecurity severity | |||||
Food secure | Yes = 1; otherwise 0 | 0.1038 | 0.1398 | 0.0666 | 1.62 |
Mild food insecurity | Yes = 1; otherwise 0 | 0.459 | 0.4888 | 0.4301 | 0.79 |
Moderate food insecurity | Yes = 1; otherwise 0 | 0.23 | 0.20 | 0.258 | 0.93 |
Severe food insecurity | Yes = 1; otherwise 0 | 0.208 | 0.172 | 0.244 | 1.21 |
Independent variables | |||||
Age | Age of respondent in years | 43.83 (12.68) | 42.19 (12.50) | 45.52 (12.60) | 1.72 *** |
Gender | Male = 1; otherwise 0 | 0.61 (0.49) | 0.55 (0.49) | 0.66 (0.47) | 1.41 |
Education | Years in formal education | 3.95 (1.54) | 4.08 (1.58) | 3.83 (1.49) | 1.17 |
Experience | Years in crop production | 10.54 (4.75) | 10.15 (4.49) | 10.94 (4.91) | 1.14 |
Non-farm income | Yes = 1; otherwise 0 | 0.38 (0.49) | 0.51 (0.50) | 0.24 (0.43) | 3.93 * |
Own Television | Yes = 1; otherwise 0 | 0.65 (0.43) | 0.63 (0.42) | 0.62 (0.48) | 0.42 |
Own Radio | Yes = 1; otherwise 0 | 0.48 (0.50) | 0.56 (0.49) | 0.55 (0.49) | 0.19 |
Own mobile phone | Yes = 1; otherwise 0 | 0.36 (0.48) | 0.79 (0.40) | 0.30 (0.49) | 7.71 * |
Received training | Yes = 1; otherwise 0 | 0.48 (0.50) | 0.47(0.58) | 0.47 (0.50) | 0.06 |
Membership of FBO | Yes = 1; otherwise 0 | 0.64 (0.42) | 0.69 (0.41) | 0.58 (0.38) | 1.67 *** |
Access to extension | Yes = 1; otherwise 0 | 0.33 (0.47) | 0.31 (0.46) | 0.35 (0.48) | 0.62 |
Access to credit | Yes = 1; otherwise 0 | 0.45 (0.50) | 0.44 (0.49) | 0.46 (0.50) | 0.34 |
KwaZulu-Natal | Yes = 1; otherwise 0 | 0.20 | |||
Free State | Yes = 1; otherwise 0 | 0.19 | |||
Limpopo | Yes = 1; otherwise 0 | 0.39 | |||
North West | Yes = 1; otherwise 0 | 0.22 |
Variables | Coef. | Std. Err. | p-Value |
---|---|---|---|
Age of the respondent | −0.0187 | 0.0092 | 0.042 ** |
Gender of the respondent | −0.4111 | 0.2228 | 0.065 * |
Educational attainment | 0.0428 | 0.0744 | 0.565 |
Experience | −0.0173 | 0.0229 | 0.451 |
Owned television | 0.05007 | 0.1313 | 0.703 |
Owned radio | 0.0427 | 0.2475 | 0.598 |
Tropical livestock unit (TLU) | 0.1121 | 0.0586 | 0.056 * |
Accessed extension services | 0.1120 | 0.1128 | 0.321 |
Accessed agricultural credit | 0.0836 | 0.2675 | 0.753 |
Access to climatic information | 1.4333 | 0.2180 | 0.000 *** |
KwaZulu-Natal | 0.2549 | 0.3664 | 0.474 |
Free State | 0.0737 | 0.3308 | 0.824 |
Limpopo | 0.1529 | 0.2792 | 0.689 |
Constant | 0.1179 | 0.6244 | 0.850 |
Variables | Coef. | Std. Err. | p-Value |
---|---|---|---|
Age of the respondent | 0.0089 | 0.0073 | 0.222 |
Gender of the respondent | −0.0062 | 0.1781 | 0.972 |
Educational attainment | −0.0711 | 0.0560 | 0.204 |
Experience | −0.0081 | 0.0181 | 0.654 |
Owned television | 0.2686 | 0.1360 | 0.048 ** |
Owned radio | 0.4094 | 0.2058 | 0.047 ** |
Tropical livestock unit (TLU) | 0.1413 | 0.0440 | 0.000 *** |
Accessed extension services | −0.2141 | 0.1419 | 0.131 |
Accessed agricultural credit | 0.8291 | 0.2308 | 0.000 *** |
KwaZulu-Natal | −0.1617 | 0.2448 | 0.509 |
Free State | −0.1751 | 0.2351 | 0.456 |
Limpopo | −0.2313 | 0.2248 | 0.304 |
Adoption of Adaptation strategies | 0.6093 | 0.3101 | 0.049 ** |
Cut 1 | −0.805 | 0.256 | 0.001 |
Cut 2 | 0.487 | 0.142 | 0.001 |
Cut 3 | 1.111 | 0.182 | 0.000 |
Atanh_rho | −1.751 | 0.591 | 0.003 |
rho | −0.941 | 0.067 | 0.000 |
Wald chi2(13) | 63.06 | ||
Prob > chi2 | 0.0000 |
Food Security Status | ATE | ATT | ||
---|---|---|---|---|
Mean | SD | Mean | SD | |
Food secure | 0.109 | 0.046 | 0.125 | 0.089 |
Mild food insecurity | 0.129 | 0.066 | 0.239 | 0.12 |
Moderate food insecurity | −0.065 | 0.035 | −0.075 | 0.072 |
Severe food insecurity | −0.172 | 0.047 | −0.289 | 0.112 |
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Ogundeji, A.A. Adaptation to Climate Change and Impact on Smallholder Farmers’ Food Security in South Africa. Agriculture 2022, 12, 589. https://doi.org/10.3390/agriculture12050589
Ogundeji AA. Adaptation to Climate Change and Impact on Smallholder Farmers’ Food Security in South Africa. Agriculture. 2022; 12(5):589. https://doi.org/10.3390/agriculture12050589
Chicago/Turabian StyleOgundeji, Abiodun A. 2022. "Adaptation to Climate Change and Impact on Smallholder Farmers’ Food Security in South Africa" Agriculture 12, no. 5: 589. https://doi.org/10.3390/agriculture12050589
APA StyleOgundeji, A. A. (2022). Adaptation to Climate Change and Impact on Smallholder Farmers’ Food Security in South Africa. Agriculture, 12(5), 589. https://doi.org/10.3390/agriculture12050589