[en] Climate change is a serious concern for the agricultural sector given that this sector is highly dependent on climate conditions. Moreover, farmersʼ adaptation process under changing climate can be explained by the psychological factors and the incorporation of socio-environmental background. Therefore, the current study aimed at socio-cognitive perceptions and extended protection motivation theory (PMT) as the basis. This paper estimated the influence of cognitive factors on individualsʼ views and decisions regarding climate change adaptation. Data from this study came from a survey with 245 rural farmers in temperate mount areas of Fars province, Iran. Structural equation modeling (SEM) was used to estimate the different factors. Results showed that three core elements of the theory, namely, risk evaluation, adaptation evaluation, and maladaptation, were the statistically significant factors that could directly explain farmersʼ adaptation decisions to adopt appropriate coping strategies under changing climate. Findings also suggested that another structural factor, adaptation incentives, had a statistically significant influence on adaptation decision-making among farmers. The study proposed valuable insights on social discourse to promote adaptation. Findings strongly offered that social discourse should focus more strongly on confirming the truth and timeliness of information that individuals gained. Eventually, further investigations are necessary to conduct the measurement model in other cultures and geographical areas and see how socio-environmental components can influence risk evaluation and adaptation evaluation.
Disciplines :
Agriculture & agronomy
Author, co-author :
Ghazali, Samane; Department of Agricultural Economics, Shiraz University, Shiraz, Iran
Azadi, Hossein ; Université de Liège - ULiège > TERRA Research Centre > Modélisation et développement ; Department of Geography, Ghent University, Ghent, Belgium ; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic
Kurban, Alishir; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, China ; University of Chinese Academy of Sciences, Beijing, China ; Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, China
Ajtai, Nicolae; Faculty of Environmental Science and Engineering, Babeş-Bolyai University, Cluj-Napoca, Romania
Pietrzykowski, Marcin; Department of Forest Ecology and Silviculture, University of Agriculture in Krakow, Krakow, Poland
Witlox, Frank; Department of Geography, Ghent University, Ghent, Belgium ; Department of Geography, University of Tartu, Tartu, Estonia ; College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Language :
English
Title :
Determinants of farmers’ adaptation decisions under changing climate: the case of Fars province in Iran
This research paper was partly funded by the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA20060303) and the Chinese Academy of Sciences President’s International Fellowship Initiative (PIFI grant no. 2021VCA0004).
Alcon F, Tapsuwan S, Brouwer R, de Miguel MD (2014) Adstrategy of irrigation water policies to guarantee water supply: a choice experiment. Environ Sci Pol 44:226–236
Arbuckle JG, Morton LW, Hobbs J (2015) Understanding farmer perspectives on climate change adaptation and mitigation: the roles of trust in sources of climate information, climate change beliefs, and perceived risk. Environ Behav 47:205–234
Arunrat N, Wang C, Pumijumnong N, Sereenonchai S, Cai W (2017) Farmersʼ intention and decision to adapt to climate change: a case study in the Yom and Nan basins, Phichit province of Thailand. J Clean Prod 143:672–685
Azadi Y, Yazdanpanah M, Mahmoudi H (2019a) Understanding smallholder farmersʼ adaptation behaviors through climate change beliefs, risk perception, trust, and psychological distance: evidence from wheat growers in Iran. J Environ Manag 250:109–456
Azadi Y, Yazdanpanah M, Forouzani M, Mahmoudi H (2019b) Farmersʼ adaptation choices to climate change: a case study of wheat growers in Western Iran. J Water Climate Change 10(1):102–116
Bocchiola A, Brunetti L, Soncini A, Polinelli F, Gianinetto M (2019) Impact of climate change on agricultural productivity and food security in the Himalayas: a case study in Nepal. Agric Syst 171:113–125
Bowen NK, Guo S (2011) Structural equation modeling. Oxford University Press
Burnham M, Ma Z (2017) Climate change adaptation: factors influencing Chinese smallholder farmersʼ perceived self-efficacy and adaptation intent. Reg Environ Chang 17(1):171–186
Byrne BM (2013) Structural equation modeling with AMOS: basic concepts, applications, and programming. Routledge
Call M, Gray C, Jagger P (2019) Smallholder responses to climate anomalies in rural Uganda. World Dev 115:132–144
Chen S, Chen X, Xu J (2016) Impacts of climate change on agriculture: evidence from China. J Environ Econ Manag 76:105–124
Chen M, Chow S-M, Hammal Z, Messinger DS, Cohn JF (2020) A person- and time-varying vector autoregressive model to capture interactive infant-mother head movement dynamics. Multivar Behav Res:1–29
Dang LH, Li E, Bruwer J (2012) Understanding climate change adaptive behaviour of farmers: an integrated conceptual framework. Int J Climate Change: Impact Respon 3(2):255–272
Dang HL, Li E, Nuberg I, Bruwer J (2014) Understanding farmersʼ adaptation intention to climate change: a structural equation modelling study in the Mekong Delta, Vietnam. Environ Sci Pol 41:11–22
Delfiyan F, Yazdanpanah M, Forouzani M, Yaghobi J (2020) Farmersʼ adaptation to drought risk through farm–level decisions: the case of farmers in Dehloran county. S Iran Climate Develop. 10.1080/17565529.2020.1737797
Dowling GR (1986) Perceived risk: the concept and its measurement. Psychol Mark 3(3):193–210
Eakin H, York A, Aggarwal R, Waters S, Welch J, Rubinos C, Smith-Heisters S, Bausch C, Anderies JM (2016) Cognitive and institutional influences on farmersʼ adaptive capacity: insights into barriers and opportunities for transformative change in Central Arizona. Reg Environ Chang 16:801–814
Esteve P, Varela-Ortega C, Blanco-Gutierrez I, Downing TE (2015) A hydro-economic model for the assessment of climate change impacts and adaptation in irrigated agriculture. Ecol Econ 120:49–58
Flórez Bossio C, Ford J, Labbé D (2019) Adaptive capacity in urban areas of developing countries. Clim Chang 157:279–297
Floyd DL, Prentice-Dunn S, Rogers RW (2000) A meta-analysis of research on protection motivation theory. J Appl Soc Psychol 30:407–429
Gao H, Yan C, Liu Q, Ding W, Chen B, Li Z (2018) Effects of plastic mulching and plastic residue on agricultural production: a meta-analysis. Sci Total Environ 651:484–492
Ghanian M, Ghoochani OM, Dehghanpour M, Taqipour M, Taheri F, Cotton M (2020) Understanding farmersʼ climate adaptation intention in Iran: a protection-motivation extended model. Land Use Policy:94 In progress
Grace JB (2006) Structural equation modeling and natural systems. Cambridge University Press
Grace JB, Schoolmaster DR Jr, Guntenspergen GR, Little AM, Mitchell BR, Miller KM, Schweiger EW (2012) Guidelines for a graph-theoretic implementation of structural equation modeling. Ecosphere 3(8):art73
Grothmann T, Patt A (2005) Adaptive capacity and human cognition: the process of individual adaptation to climate change. Glob Environ Chang 15(3):199–213
Grothmann T, Reusswig F (2006) People at risk of flooding: why some residents take precautionary action while others do not. Nat Hazards 38(1):101–120
Hair JFJ, Black WC, Babin BJ, Anderson RE (2010) Multivariate Data Analysis, seventh ed. Prentice Hall, Upper Saddle River
Hamilton-Webb A, Naylor R, Manning L, Conway J (2019) “Living on the edge”: using cognitive filters to appraise experience of environmental risk. J Risk Res 22(3):303–319
Hasegawa T, Fujimori S, Havlík P, Valin H, Bodirsky BL, Doelman, J.C. … Witzke, P. (2018) Risk of increased food insecurity under stringent global climate change mitigation policy. Nat Clim Chang 8(8):699–703
Kabir MJ, Alauddin M, Crimp S (2017) Farm-level adaptation to climate change in Western Bangladesh: an analysis of adaptation dynamics, profitability and risks. Land Use Policy 64:212–224
Karimi V, Karami E, Keshavarz M (2018) Climate change and agriculture: impacts and adaptive responses in Iran. J Integr Agric 17(1):1–15
Kastanakis MN, Voyer BG (2014) The effect of culture on perception and cognition: a conceptual framework. J Bus Res 67:425–433
Keshavarz M, Karami E (2016) Farmersʼ pro-environmental behavior under drought: application of protection motivation theory. J Arid Environ 127:128–136
Kaplan-Hallam M, Bennett NJ (2017) Adaptive social impact management for conservation and environmental management. Conserv Biol 32(2):304–314
Kuruppu N, Liverman D (2011) Mental preparation for climate adaptation: the role of cognition and culture in enhancing adaptive capacity of water management in Kiribati. Glob Environ Chang 21:657–669
Luu TA, Nguyen AT, Trinh QA, Pham VT, Le BB, Nguyen DT, Hoang QN, Pham HTT, Nguyen TK, Luu VN, Hens L (2019) Farmersʼ intention to climate change adaptation in agriculture in the red River Delta biosphere reserve (Vietnam): a combination of structural equation modeling (SEM) and protection motivation theory (PMT). Sustainability 11(10):1–17
Markus KA (2012) Principles and practice of structural equation modeling by rex B. Kline Struct Eq Model 19(3):509–512
McClaran MP, Butler GJ, Wei H, Ruyle GD (2015) Increased preparation for drought among livestock producers reliant on rainfed forage. Nat Hazards 79:151–170
Milne S, Sheeran P, Orbell S (2000) Prediction and intervention in health related behavior: a meta analytic review of protection motivation theory. J Appl Soc Psychol 30(1):106–143
Mitter H, Schonhart M, Larcher M, Schmid E (2018) The stimuli-actions-effects-responses (SAER)-framework for exploring perceived relationships between private and public climate change adaptation in agriculture. J Environ Manag 209:286–300
Mitter H, Larcher M, Schonhart M, Stottinger M, Schmid E (2019) Exploring farmersʼ climate change perceptions and adaptation intentions: empirical evidence from Austria. Environ Manag 63:804–821
Mo F, Wang J-Y, Zhou H, Luo C-L, Zhang X-F, Li X-Y et al (2017) Ridge-furrow plastic-mulching with balanced fertilization in rainfed maize (Zea mays L.): an adaptive management in east African Plateau. Agric For Meteorol 236:100–112
Mulenga BP, Wineman A, Sitko NJ (2017) Climate trends and farmersʼ perceptions of climate change in Zambia. Environ Manag 59:291–306
Neisi M, Bijani M, Abbasi E, Mahmoudi H, Azadi H (2020) Analyzing farmersʼ drought risk management behavior: evidence from Iran. J Hydrol 590:125243
Niles MT, Brown M, Dynes R (2016) Farmerʼs intended and actual adstrategy of climate change mitigation and adaptation strategies. Clim Chang 135:277–295
Pakmehr S, Yazdanpanah M, Baradaran M (2020a) How collective efficacy makes a difference in responses to water shortage due to climate change in southwest Iran. Land Use Policy 99:104798
Pakmehr S, Yazdanpanah M, Baradaran M (2020b) Explaining farmersʼ response to climate change-induced water stress through cognitive theory of stress: an Iranian perspective. Environ Dev Sustain. 10.1007/s10668-020-00846-3
Pearl J (2009) Causality, second ed. Cambridge University Press, Cambridge
Pietrzykowski M, Woś B, Likus-Cieślik L, Świątek B, Pająk M (2020) Forest and climate change – a global view and local cases, in the role of agriculture in climate change mitigation, 1st edn. Ed. by Lucjan Pawłowski, Zygmunt Litwińczuk, pp 29–39
Probstl-Haider U, Mostegl NM, Kelemen-Finan J, Haider W, Formayer H, Kantelhardt J, Moser T, Kapfer M, Trenholm R (2016) Farmersʼ preferences for future agricultural land use under the consideration of climate change. Environ Manag 58:446–464
Robert M, Thomas A, Bergez J-E (2016) Processes of adaptation in farm decision-making models. A review. Agron Sustain Dev 36(4):64
Roesch-McNally GE, Arbuckle JG, Tyndall JC (2017) What would farmers do? Adaptation intentions under a Corn Belt climate change scenario. Agric Hum Values 34:333–346
Rogers RW, Prentice-Dunn S (1997) Protection motivation theory. In: Gochman DS (ed) Handbook of health behaviour research, I: personal and social determinants. Plenum Press, New York, pp 113–132
Sanderson MR, Curtis AL (2016) Culture, climate change and farm-level groundwater management: an Australian case study. J Hydrol 536:284–292
Scheaffer RL, Mendenhall W, Ott L (1979) Elementary survey sampling. Duxbuy Press
Sousa K, Casanoves F, Sellare J, Ospina A, Suchini JG, Aguilar A, Mercado L (2018) How climate awareness influences farmersʼ adaptation decisions in Central America? J Rural Stud 64:11–19
Truelove HB, Carrico AR, Thabrew L (2015) A socio-psychological model for analyzing climate change adaptation: a case study of Sri Lankan paddy farmers. Glob Environ Chang 31:85–97
Vulturius G, André K, Swartling AG, Brown C, Rounsevell MDA, Blanco V (2018) The relative importance of subjective and structural factors for individual adaptation to climate change by forest owners in Sweden. Reg Environ Chang 18:511–520
Warnatzsch EA, Reay DS (2020) Assessing climate change projections and impacts on central Malawiʼs maize yield: the risk of maladaptation. Sci Total Environ 711
Woods BA, Nielsen HQ, Pedersen AB, Kristofersson D (2017) Farmersʼ perceptions of climate change and their likely responses in Danish agriculture. Land Use Policy 65:109–120
Yu Y, Tao H, Yao H, Zhao C (2018) Assessment of the effect of plastic mulching on soil respiration in the arid agricultural region of China under future climate scenarios. Agric For Meteorol 256-257:1–9
Zobeidi T, Yazdanpanah M, Forouzani M, Khosravipour B (2016) Climate change discourse among Iranian farmers. Clim Chang 138(3–4):521–535
