Maize farmers’ adaptation to drought: Do risk attitudes and perceived risk probability matter?

References

• Adejoro, S. O. (2000). Handbook for poultry practitioners and consultants. Jilog Nigeria Company.
   Google Scholar
• Adu-Boahen, K., Dadson, I. Y., & Halidu, M. A. (2019). Climatic variability and food crop production in the bawku west district of the upper east region of Ghana. Ghana Journal of Geography, 11(1), 103–27.
   Google Scholar
• Agyemang-Bonsu, W. K., Minia, Z., Dontwi, J., Dontwi, I. K., Buabeng, S. N., Baffoe-Bonnie, B., & Frimpong, E. B. (2008). Ghana climate change impacts, vulnerability and adaptation assessments. Environmental Protection Agency.
   Google Scholar
• Akponikpè, P. I., Johnston, P., & Agbossou, E. K. (2010). Farmers’ perception of climate change and adaptation strategies in Sub-Saharan West-Africa. Proceedings of the 2nd International Conference: Climate, Sustainability and Development in Semi-arid Regions, 1620, 134147).
   Google Scholar
• Akudugu, M. A., Guo, E., & Dadzie, S. K. (2012). Adoption of modern agricultural production technologies by farm households in Ghana: What factors influence their decisions? Journal of Biology, Agriculture and Healthcare, 2(3), 1–13. www.iiste.org.
   Google Scholar
• Alabi, O. O., Lawal, A. F., Coker, A. A., & Awoyinka, Y. A. (2014). Probit model analysis of Smallholder’s farmers decision to use Agrochemical Inputs in Gwagwalada and kuje area councils of federal capital TERRITORY, ABUJA, NIGERIA. International Journal of Food and Agricultural Economics, 2(1), 85–94.
   Google Scholar
• Altieri, M. A., Nicholls, C. I., Henao, A., & Lana, M. A. (2015). Agroecology and the design of climate change-resilient farming systems. Agronomy for Sustainable Development, 35(3), 869–890.
   Web of Science ®Google Scholar
• Apata, T. G., Samuel, K. D., &Adeola, A. O. (2009).“Analysis of climate change perception and adaptation among arable food crop farmers in South Western Nigeria”. In Contributed paper prepared for presentation at the international association of agricultural economists’ 2009 conference, Beijing, China, 16, Vol. 22.
   Google Scholar
• Arbis, D., Dixit, V. V., & Rashidi, T. H. (2016). Impact of risk attitudes and perception on game theoretic driving interactions and safety. Accident Analysis & Prevention, 94, 135–142. https://doi.org/10.1016/j.aap.2016.05.027
   PubMed Web of Science ®Google Scholar
• Asfaw, S., DiBattista, F., & Lipper, L. (2016). Agricultural technology adoption under climate change in the Sahel: Micro-evidence from Niger. Journal of African Economies, 25(5), 637–669. https://doi.org/10.1093/jae/ejw005
   Web of Science ®Google Scholar
• Baffoe-Asare, R., Danquah, J. A., & Annor-Frempong, F. (2013). Socioeconomic factors influencing adoption of Codapec and cocoa high-tech technologies among small holder farmers in Central Region of Ghana. American Journal of Experimental Agriculture, 3(2), 277–292. https://doi.org/10.9734/AJEA/2013/1969
   Google Scholar
• Balcombe, K., Bardsley, N., Dadzie, S., & Fraser, I. (2019). Estimating parametric loss aversion with prospect theory: Recognising and dealing with size dependence. Journal of Economic Behavior and Organization, 162, 106–119. ISSN 0167-2681. https://doi.org/10.1016/j.jebo.2019.04.017
   Web of Science ®Google Scholar
• Cascetta, E. (2009). Random utility theory. In Transportation systems analysis (pp. 89–167). Springer US. https://doi.org/10.1007/978-0-387-75857-2_3
   Google Scholar
• Clarkson, G., Dorward, P., Poskitt, S., Stern, R. D., Nyirongo, D., Fara, K., & Giraldo, D. (2022). Stimulating small-scale farmer innovation and adaptation with Participatory Integrated Climate Services for Agriculture (PICSA): Lessons from successful implementation in Africa, Latin America, the Caribbean and South Asia. Climate Services, 26, 100298.
   Google Scholar
• Comoe, H., & Siegrist, M. (2013). Relevant drivers of farmers’ decision behaviour regarding their adaptation to climate change: Case study of regions in cote d’Viour. In Mitigation adaptation strategy global change. Springer Science 2013. https://doi.org/10.1007/511027-013
   Google Scholar
• Czaja, R., & Blair, J. (2005). Designing surveys: A guide to decisions and procedures. Sage Publications. https://doi.org/10.4135/9781412983877
   Google Scholar
• Dadzie, S. K. N. (2016). Decision Behaviour Under Risk and Climate Change Adaptation Among Food Crop Farmers in Ghana Doctoral dissertation, University of Reading, School of Agriculture, Policy and Development.
   Google Scholar
• Dadzie S. K. N. (2019). Implication of subjective probabilities of extreme weather events associated with climate change (SPEWEACCs) for climate risk assessment and farm adaptation choices: A study of Ghanaian farmers. In Kokoye, S. E. H., Yegbemey, R. N.& Awoye, O. H. R. (Eds.), Advancing climate change research in Africa (pp. 159–208). Nova Science Publishers, New York.
   Google Scholar
• Dadzie, S. K. N., & Acquah, H. D. (2012). Attitudes toward risk and coping responses: The case of food crop farmers at Agona Duakwa in Agona East district of Ghana. International Journal of Agriculture and Forestry, 2(2), 29–37. https://doi.org/10.5923/j.ijaf.20120202.06
   Google Scholar
• Dadzie, S. K. N., Orkorley, E. A., Bosompem, M. and Okwei, T. (2011). “Effect of climate change outcomes on food production and implication for food security: A Ghanaian case study”. Presented and accepted for publication, edited conference proceedings of 2nd Joint international conference of University of Irolline and University of cape coast, May 1-4, 2011.
   Google Scholar
• Darlington, J. P. E. C. (1990). Populations in nests of the termite macrotermes subhyalinus in Kenya. Insectes Sociaux, 37(2), 158–168.
   Web of Science ®Google Scholar
• Deressa, T. T., Hassan, R. M., Ringler, C., Alemu, T., & Yesuf, M. (2009). Determinants of farmers’ choice of adaptation methods to climate change in the Nile Basin of Ethiopia. Global Environmental Change, 19(2), 248–255. https://doi.org/10.1016/j.gloenvcha.2009.01.002
   Web of Science ®Google Scholar
• Deressa, T. T., Ringler, C., & Hassan, R. M. (2010). Factors affecting the choices of coping strategies for climate extremes. The case of farmers in the Nile Basin of Ethiopia IFPRI Discussion Paper, 1032.
   Google Scholar
• DiFalco, S., & Veronesi, M. (2013). How can African Agriculture adapt to climate change? A counterfactual analysis from Ethiopia. Land Economics, 89(4), 761–784. https://doi.org/10.3368/le.89.4.743
   Web of Science ®Google Scholar
• DiFalco, S., Veronesi, M., & Yesuf, M. (2011). Does adaptation to climate change provide food security? A micro-perspective from Ethiopia. American Journal of Agricultural Economics, 93(3), 829–846. https://doi.org/10.1093/ajae/aar006
   Web of Science ®Google Scholar
• Dovers, S. (2009). Normalizing adaptation. Global Environmental Change: Human and Policy Dimensions, 19(1), 4–6. https://doi.org/10.1016/j.gloenvcha.2008.06.006
   Web of Science ®Google Scholar
• Ekstrom, J. A., Moser, S. C., Torn, M. (2010). Barriers to adaptation: A diagnostic framework. Final project report. California Energy Commission.
   Google Scholar
• Enete, A. A., Madu, I. I., Mojekwu, J. C., Onyekuru, A. N., Onwubuya, E. A., & Eze, F. (2011). Indigenous agricultural adaptation to climate change: Study of Southeast Nigeria.
   Google Scholar
• Engle-Warnick, J., Escobal, J., and Laszlo, S. (2006). “Ambiguity aversion as a predictor of technology choice: Experimental evidence from Peru”. Departmental Working Paper, McGrill University, Department of Economics.
   Google Scholar
• Environmental Protection Agency. (2003). National action programme to combat drought and desertification. Accra, Ghana. PreventionWeb, the Knowledge Platform for Disaster Risk Reduction, available at www.preventionweb.net Retrieved August 15, 2020.
   Google Scholar
• Etoundi, S. M. N., and Dia, B. K. (2008). Determinants of the adoption of improved varieties of Maize in Cameroon: case of cms 8704 (No. 37783). University Library of Munich,
   Google Scholar
• Fadare, O. A., Akerele, D., & Toritseju, B. (2014). Factors influencing adoption decisions of maize farmers in Nigeria. International Journal of Food and Agricultural Economics (IJFAEC), 2(3), 45–54.
   Google Scholar
• Fatuase, A. I., & Ajibefun, A. I. (2013). Adaptation to climate change: A case study of rural farming households in Ekiti state, Nigeria. Impacts world 2013. Proceedings of the International Conference on Climate change Effects, Potsdam.
   Google Scholar
• Food and Agriculture Organization of the United Nations (FAO). (2016). FAOSTAT Database, FAO. www.fao.org/faostat
   Google Scholar
• Fosu-Mensah, B. Y., Vlek, P. L., & MacCarthy, D. S. (2012). Farmers’ perception and adaptation to climate change: A case study of Sekyedumase district in Ghana. Environment Development and Sustainability, 14(4), 495–505. https://doi.org/10.1007/s10668-012-9339-7
   Google Scholar
• Fosu-Mensah, B. Y., Vlek, P. L. G., & Manschadi, A. M. (2010). Farmers’ perceptions and adaption to climate change: A case study of Sekyedumase district in Ghana. Centre for Development Research, University of Bonn.
   Google Scholar
• Fox, N., Hunn, A., & Mathers, N. (2009). Sampling and sample size calculation. East Midlands/Yorkshire: The National Institutes for Health Research. Research Design Service for the East Midlands/Yorkshire & the Humber.
   Google Scholar
• Gbetibouo, G. A. (2009). Understanding farmers’ perceptions and adaptations to climate change and variability: The case of the Limpopo basin, South Africa. IFPRI discussion paper 00849, February 2009.
   Google Scholar
• Greene, W. H. (2008). Econometric analysis (6th ed.). New York University.
   Google Scholar
• Hassan, R., & Nhemachena, C. (2008). Determinants of African farmers’ strategies for adapting to climate change: Multinomial choice analysis. African Journal of Agricultural and Resource Economics, 2(1), 83–104.
   Google Scholar
• Hazell, P., Anderson, J., Balzer, N., Hastrup, C. A., Hess, U., & Rispoli, F. (2010). Potential for scale and sustainability in weather index insurance for Agriculture and rural livelihoods. International Fund for Agricultural Development and Rural Food Programme.
   Google Scholar
• Hill, R. C., Griffiths, W. E., & Lim, G. C. (2011). Principles of econometrics (4th ed.). ISBN 978-0471-72360-8. John Wiley and Sons, Inc.
   Google Scholar
• Hill, L., & Kau, P. (1973). Application of multivariate probit to a threshold model of grain dryer purchasing decision. American Journal of Agricultural Economics, 55(1), 19–27. https://doi.org/10.2307/1238657
   Web of Science ®Google Scholar
• Hillson, D. A. (2005). Describing probability: The limitations of natural language. Proceedings of PMI Global Congress 2005 EMEA, Edinburgh, UK
   Google Scholar
• Hyland, M., & Russ, J. (2019). Water as destiny–the long-term impacts of drought in sub-Saharan Africa. World Development, 115, 30–45. https://doi.org/10.1016/j.worlddev.2018.11.002
   Web of Science ®Google Scholar
• IPCC. (2007a). Climate change 2007: Synthesis report. In Pachauri, R. K. and Reisinger, A. (Eds.), A contribution of working groups I, II, and III to the fourth assessment report of the intergovernmental panel on climate change [core writing team (p. 398).
   Google Scholar
• IPCC. (2007b). Summary for policymakers. In: Climate change 2007: Impacts, adaptation and vulnerability. In Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J. and Hanson, C. E. (Eds.), Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change (pp. 7–22). Cambridge University Press.
   Google Scholar
• Ishaya, S., & Abaje, I. B. (2008). Indigenous people’s perception on climate change and adaptation strategies in Jema’a local government area of Kaduna state, Nigeria. Journal of Geography and Regional Planning, 1(8), 138–143.
   Google Scholar
• Juana, J. S., Kahaka, Z., & Okurut, F. N. (2013). Farmers’ perception and adaptations to climate change in sub-Saharan Africa: A synthesis of empirical studies and implications for public Policy in African Agriculture. Journal of Agricultural Science, 5(4), 121–135. https://doi.org/10.5539/jas.v5n4p121
   Google Scholar
• Juma, M., Nyangena, W., and Yesuf, M. (2009). “Production risk and farm technology adoption in rain-fed semi-arid lands of Kenya”. Environment for Development Discussion paper series, EfD DP, 09–22.
   Google Scholar
• Kass, R. E., Carlin, B. P., Gelman, A., & Neal, R. M. (1998). Markov Chain Monte Carlo in practice: A roundtable Discussion. International Journal of Offshore and Polar Engineering, 52(2), 93–100. https://doi.org/10.1080/00031305.1998.10480547
   Google Scholar
• Kenyon, S. J., Bromley, B. C., O’Brien, D. P., & Davis, D. R. (2008). The solar System beyond Neptune. (M. A. Barucci, H. Boehnhardt, D. P. Cruikshank & A. Morbidelli, Eds.). University of Arizona Press.
   Google Scholar
• Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.
   Web of Science ®Google Scholar
• Kurukulasuriya, P. and Mendelsohn, R. (2006). “Crop selection: Adaptation to climate change in Africa”. CEEPA Discussion Paper, No. 26, Centre for Environmental Economics and Policy in Africa, University of Pretoria.
   Google Scholar
• Leedy, P. D., & Ormrod, J. E. (2001). Practical Research: Planning and design (7th ed.). Merrill Prentice Hall.
   Google Scholar
• Lemi, T., & Hailu, F. (2019). Effects of climate change variability on agricultural productivity. International Journal of Environmental Sciences & Natural Resources, 17, 14–20.
   Google Scholar
• Limantol, A. M., Keith, B. E., Azabre, B. A., & Lennartz, B. (2016). Farmers’ perception and adaptation practice to climate variability and change: A case study of the vea catchment in Ghana. SpringerPlus, 5, 1–38.
   PubMedGoogle Scholar
• Liu, E. M. (2008). “Time to change what to sow: Risk preferences and technology adoption decisions of cotton farmers in China”. Working Paper No. 526, Princeton University, Industrial Relations Section,
   Google Scholar
• Liu, E. M. (2013). Time to change what to sow: Risk preferences and technology adoption decisions of cotton farmers in china. The Review of Economics and Statistics, 95(4), 1386–1403. https://doi.org/10.1162/REST_a_00295
   Web of Science ®Google Scholar
• Lolemtum, J. T., Mugalavai, E. M., & Obiri, J. A. (2017). Impact of drought on food security in West Pokot County, Kenya. International Journal of Scientific and Research Publications, 7(6), 742–750.
   Google Scholar
• Lybbert, T., and Sumner, D. (2010). “Agricultural technologies for climate change mitigation and adaptation in developing countries: Policy options for innovation and technology diffusion”. Issue Brief No.6.
   Google Scholar
• Maddison, D. (2006). “The perception of and adaptation to climate change in Africa”. CEEPA Discussion Paper No.10. Centre for Environmental Economics and Policy in Africa.
   Google Scholar
• Mahmood, R., Pielke, R. A., Sr., Hubbard, K. G., Niyogi, D., Dirmeyer, P. A., McAlpine, C., & Fall, S. (2014). Land cover changes and their biogeophysical effects on climate. International Journal of Climatology, 34(4), 929–953.
   Web of Science ®Google Scholar
• Masters, G., Baker, P., and Flood, J. (2010). “Climate change and agricultural commodities”. CABI Working Paper 2, No. 38, www.cabi.org
   Google Scholar
• Maxwell, S. L., Butt, N., Maron, M., McAlpine, C. A., Chapman, S., Ullmann, A., Watson, J. E. (2019). Conservation implications of ecological responses to extreme weather and climate events. Diversity and Distributions, 25(4), 613–625. https://doi.org/10.1111/ddi.12878
   Web of Science ®Google Scholar
• Minia, Z. (2004). Climate scenarios developed for climate change impacts assessment in Ghana. The Netherlands climate change studies assistance programme (NCCSAP). hase2—Part, 1.
   Google Scholar
• Mistiaen, J., & Strand, I. E. (2000). Location choice of commercial fishermen with heterogeneous risk preferences. American Journal of Agricultural Economics, 82(5), 1184–1190. https://doi.org/10.1111/0002-9092.00118
   Web of Science ®Google Scholar
• Moser, S. C., & Ekstrom, J. A. (2010). A framework to diagnose barriers to climate change adaptation. (Roger E. Kasperson, Edited by). Clark University.
   Google Scholar
• Mudzonga, E. (2011). “Farmers’ adaptation to climate change in Chivi district of Zimbabwe”. Trade and Development Studies Centre. Trapca Working Papers, Trade Policy Training Centre in Africa, www.trapca.org/working-papers
   Google Scholar
• Neuman, W. L. (2007). Social Research: Qualitative and quantitative approaches (2nd ed.). Pearson Education, Inc.
   Google Scholar
• Newcomer, K. E., Hatry, H. P., & Wholey, J. S. (Eds.). (2015). Handbook of practical program evaluation. Jossey-Bass & Pfeiffer Imprints, Wiley.
   Google Scholar
• Nutsukpo, D. K., Jalloh, A., & Zougmore, R. (2012). West African agriculture and climate change: A comprehensive analysis-ghana.
   Google Scholar
• Osbahr, H., Dorward, P., Stern, R., & Cooper, S. (2011). Supporting agricultural innovation in Uganda to respond to climate risk: Linking climate change and variability with farmer perceptions. Experimental Agriculture, 47(2), 293–316.
   Web of Science ®Google Scholar
• Osberghaus, D. (2013). “Prospect theory, mitigation and adaptation to climate change”. Discussion Paper No. 13-091, Centre for European Economic Research (ZEW). Retrieved http://ftp.zew.de/pub/zew-docs/dp/dp13091.pdf
   Google Scholar
• Osberghaus, D., Finkel, E., and Pohl, M. (2010). “Individual adaptation to climate change: The role of information and perceived risk”. Discussion Paper No. 10-061, Centre for European Economic Research (ZEW). Retrieved ftp://ftp.zew.de/pub/zew-docs/dp/dp10061.pdf
   Google Scholar
• Pennings, J. M. E., & Wansink, B. (2004). Channel contract behaviour: The role of risk attitudes, risk perceptions, and channel members’ market structures. Journal of Business, 77(4), 697–723. https://doi.org/10.1086/422633
   Google Scholar
• Picazo‐Tadeo, A. J., & Wall, A. (2011). Production risk, risk aversion and the determination of risk attitudes among Spanish rice producers. Agricultural Economics, 42(4), 451–464. https://doi.org/10.1111/j.1574-0862.2011.00537.x
   Web of Science ®Google Scholar
• Pindyck, R., & Rubinfeld, D. (1998). Econometric models and Econometric forecasts (4th ed.). McGraw-Hill.
   Google Scholar
• Quartey, J. D. (2010). “The demand for climate change mitigation in Ghana’s forested regions” presented at 18th Commonwealth Forestry Conference, theme: Restoring the Commonwealth’s Forests: Tackling Climate Change. Edinburgh International Conference Centre, Scotland, 28th June – 2 July 2010. www.cfc2010.org
   Google Scholar
• Ragier, D. A., Ryan, M., Phimister, & Marra, C. A. (2009). Bayesian and classical estimation of mixed logit: An application to genetic testing. Journal of Health Economics, 28(3), 598–610. https://doi.org/10.1016/j.jhealeco.2008.11.003
   PubMed Web of Science ®Google Scholar
• Reilly, J. M., & Schimmelpfennig, D. (1999). Weeds, insects, and diseases. Climatic Change, 43(4), 711–727.
   Web of Science ®Google Scholar
• Roberts, C. (2007). Mixing modes of data collection in surveys: A methodological review. NCRM methods review papers. ESRC National Centre for Research Methods, NCRM/008, City University.
   Google Scholar
• Rogers, R. W. (1983). A Protection motivation theory of fear, appeals and attitude change. Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803
   Google Scholar
• Russano, M. B., Narchet, F. M., Kleinman, S. M., & Meissner, C. A. (2014). Structured interviews of experienced HUMINT interrogators. Applied Cognitive Psychology, 28(6), 847–859. https://doi.org/10.1002/acp.3069
   Web of Science ®Google Scholar
• Senapati, A. K. (2020). Evaluation of risk preferences and coping strategies to manage with various agricultural risks: Evidence from India. Heliyon, 6(3), e03503. https://doi.org/10.1016/j.heliyon.2020.e03503
   PubMed Web of Science ®Google Scholar
• Shahabuddn, Q., Mestelman, S., & Feeny, D. (1986). Peasant behaviour towards risk and socio-Economic and structural characteristics of farm households in Bangladesh. Oxford Economic Papers, 38(1), 122–130. https://doi.org/10.1093/oxfordjournals.oep.a041724
   Web of Science ®Google Scholar
• Shiferaw, B., Tesfaye, K., Kassie, M., Abate, T., Prasanna, B. M., & Menkir, A. (2014). Managing vulnerability to drought and enhancing livelihood resilience in sub-Saharan Africa: Technological, institutional and policy options. Weather and Climate Extremes, 3, 67–79. https://doi.org/10.1016/j.wace.2014.04.004
   Google Scholar
• Smit, B., Burton, I., Klein, R., & Wandel, J. (2000). An anatomy of adaptation to climate change and variability. Climatic Change, 45(1), 223–251. https://doi.org/10.1023/A:1005661622966
   Web of Science ®Google Scholar
• Smit, B., & Skinner, M. W. (2002). Adaptation options in agriculture to climate change: A typology. Mitigation and Adaptation Strategies for Global Change, 7(1), 85–114.
   Google Scholar
• Taherdoost, H. (2016). Sampling methods in research methodology; how to choose a sampling technique for research. How to Choose a Sampling Technique for Research (April 10, 2016).
   Google Scholar
• Tambang, Y. G. (2009). Technology adoption in small-scale Agriculture: The case of Cameroon and Ghana. Science, Technology and Innovation Studies, 5(2), 111–131.
   Google Scholar
• Tambo, J. A., & Abdoulaye, T. (2013). Smallholder farmers’ perceptions of and adaptations to climate change in the Nigerian savannah. Regional Environmental Change, 13(2), 375–388. https://doi.org/10.1007/s10113-012-0351-0
   Web of Science ®Google Scholar
• Tiffin, R., & Balcombe, K. (2011). The determinants of technology adoption by UK farmers using Bayesian model averaging: The cases of organic production and computer usage. The Australian Journal of Agricultural and Resource Economics, 55(4), 579–598. https://doi.org/10.1111/j.1467-8489.2011.00549.x
   Web of Science ®Google Scholar
• Tizale, C. Y. (2007). The dynamics of soil degradation and incentives for optimal management in the Central Highlands of Ethiopia Doctoral dissertation, University of Pretoria. Available online atwww.dspace.up.ac.za
   Google Scholar
• Tombu, M., & Mandel, D. R. (2015). When does framing influence preferences, risk perceptions, and risk attitudes? The explicated valence account. Journal of Behavioral Decision Making, 28(5), 464–476. https://doi.org/10.1002/bdm.1863
   Web of Science ®Google Scholar
• Train, K. (2003). Discrete choice methods with simulation. Cambridge University Press.
   Google Scholar
• van Winsen, F., de Mey, Y., Lauwers, L., Van Passel, S., Vancauteren, M., & Wauters, E. (2016). Determinants of risk behaviour: Effects of perceived risks and risk attitude on farmer’s adoption of risk management strategies. Journal of Risk Research, 19(1), 56–78. https://doi.org/10.1080/13669877.2014.940597
   Web of Science ®Google Scholar
• Williams, C. (2007). Research methods. Journal of Business & Economic Research, 5(3), 65–72.
   Google Scholar
• World Bank. (2020) . Poverty and shared prosperity 2020: Reversals of fortune. The World Bank.
   Google Scholar
• Yaro, J. A. (2013). The perception of and adaptation to climate variability/change in Ghana by small-scale and commercial farmers. Regional Environmental Change, 13(6), 1259–1272. https://doi.org/10.1007/s10113-013-0443-5
   Web of Science ®Google Scholar