Search

Menu
Search
in Ecology

Exploring determinants of climate change adaptation by smallholder livestock farmers in coastal West Bengal, India using a double hurdle econometric approach

42 Views


Abstract

Coastal West Bengal, also known as ‘Cyclone capital of India’, is one of the most vulnerable regions due to the impact of cyclone-led climate disasters, disproportionately affecting the smallholder livestock rearers. Therefore, understanding the adaptation strategies available to smallholder livestock rearers and the factors influencing their adoption behaviour would facilitate an understanding of how they cope with the negative impacts of climate change. This study aimed to identify and explore climate adaptation strategies in the livestock sector as adopted by smallholder livestock rearers in coastal West Bengal. It also attempted to analyse the determinants influencing the adoption behaviour of the rearers at both levels of the adoption decision and intensity of adoption. Primary cross-sectional data were collected from 360 smallholder livestock rearers across all districts of coastal West Bengal using a multistage sampling approach. The double hurdle model was employed to assess adoption behaviour. Seven key adaptation strategies were identified, including improved feeding practices, shifting from large ruminants to small ruminants, availing of livestock insurance, well-ventilated housing, relocating animals to a safe place during disasters, preserving fodder, and providing more healthcare practices for livestock. While herd size, availability of climatic information, and community participation had a positive influence on the farmers’ adoption decisions, the availability of non-institutional credit and infrastructure had a negative influence. The intensity of adoption was positively influenced by herd size, access to institutional credit, training received, community participation, and access to livestock extension services. The findings support the need for policy advocacy to provide institutional credit, strengthen institutions to facilitate better extension services, and establish safe places for animals, such as cyclone shelters. Climate policy should consider addressing the heterogeneity responsible for non-adoption among farmers through awareness-building and the provision of incentives. Policy should also be geared towards easy accessibility to better healthcare services for livestock, availability of improved feeds and fodder, a community fodder bank and an organised market for livestock produce.

Similar content being viewed by others

Livestock exposure to future cumulated climate-related stressors in West Africa

Article
Open access
15 February 2023

Multi-week prediction of livestock chill conditions associated with the northwest Queensland floods of February 2019

Article
Open access
08 April 2022

Gridded livestock density database and spatial trends for Kazakhstan

Article
Open access
29 November 2023

Data availability

Data will be made available on reasonable request to the corresponding author.

References

  1. Omerkhil, N. et al. Micro-level adaptation strategies by smallholders to adapt climate change in the least developed countries (LDCs): Insights from Afghanistan. Ecol. Indic. 118, 106781 (2020).

    Google Scholar 

  2. Pandey, R. et al. Agroecology as a climate change adaptation strategy for smallholders of Tehri-Garhwal in the Indian Himalayan Region. Small-Scale For. 16, 53–63 (2017).

    Google Scholar 

  3. Rosenzweig, C. & Parry, M. L. Potential impact of climate change on world food supply. Nature 367, 133–138 (1994).

    Google Scholar 

  4. Wong, P. P. et al. In Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects, 361–409 (Cambridge University Press, 2014). https://www.ipcc.ch/site/assets/uploads/2018/02/WGIIAR5-Chap5_FINAL.pdf.

  5. Ramsay, H. In Oxford Research Encyclopedia of Natural Hazard Science (2017). https://doi.org/10.1093/acrefore/9780199389407.013.79.

  6. Islam, S. M. S., Tanim, A. H. & Mullick, M. R. A. In Water, Flood Management and Water Security Under a Changing Climate Proceedings from the 7th International Conference on Water and Flood Management (eds Haque, A. & Chowdhury, A. I. A.) 301–313 (Springer, 2020). https://doi.org/10.1007/978-3-030-47786-8_21.

    Google Scholar 

  7. Guntukula, R. Assessing the impact of climate change on Indian agriculture: Evidence from major crop yields. J. Public Aff. 20, e2040 (2020).

    Google Scholar 

  8. Pachauri, R. K. et al. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. EPIC3Geneva Switz., pp 151. ISBN 978-92-9169-143-2 (IPCC, 2014). https://epic.awi.de/id/eprint/37530/.

  9. Praveen, B. & Sharma, P. Climate change and its impacts on Indian agriculture: An econometric analysis. J. Public Aff. 20, e1972 (2020).

    Google Scholar 

  10. Patra, J. & Kantariya, K. Science–policy interface for disaster risk management in India: toward an enabling environment. Curr. Sci. 107, 39–45 (2014).

    Google Scholar 

  11. Dorward, P., Osbahr, H., Sutcliffe, C. & Mbeche, R. Supporting climate change adaptation using historical climate analysis. Clim. Dev. 12, 469–480 (2020).

    Google Scholar 

  12. Huang, K. & Sim, N. Adaptation may reduce climate damage in agriculture by two thirds. J. Agric. Econ. 72, 47–71 (2021).

    Google Scholar 

  13. Turner-Walker, S., Anantasari, E. & Retnowati, A. In Climate Change Research, Policy and Actions in Indonesia. Science, Adaptation and Mitigation (eds Djalante, R. et al.) 53–77 (Springer, 2021). https://doi.org/10.1007/978-3-030-55536-8_4.

    Google Scholar 

  14. Needham, H. F., Keim, B. D. & Sathiaraj, D. A review of tropical cyclone-generated storm surges: Global data sources, observations, and impacts. Rev. Geophys. 53, 545–591 (2015).

    Google Scholar 

  15. Mohapatra, M. Cyclone hazard proneness of districts of India. J. Earth Syst. Sci. 124, 515–526 (2015).

    Google Scholar 

  16. Basu, J. Sundarbans is cyclone capital of India: IMD report. Earth (2022). https://www.downtoearth.org.in/natural-disasters/sundarbans-is-cyclone-capital-of-india-imd-report-81244.

  17. IMD. Hazard Atlas of India. Clim. Hazards Vulnerability India (n.d.). https://imdpune.gov.in/hazardatlas/index.html.

  18. National Centre for Coastal Research. National Assessment of Shoreline Changes along Indian Coastal (National Centre for Coastal Research, 2022). https://nccr.gov.in/sites/default/files/NSASEast%20Coast_optimize.pdf.

  19. Bandyopadhyay, S. Sundarban: A Review of Evolution and Geomorphology (World Bank Group, 2019). http://documents.worldbank.org/curated/en/119121562735959426/Sundarban-A-Review-of-Evolution-and-Geomorphology.

  20. Brown, S. & Nicholls, R. J. Subsidence and human influences in mega deltas: The case of the Ganges–Brahmaputra–Meghna. Sci. Total Environ. 527–528, 362–374 (2015).

    Google Scholar 

  21. Mandal, U. K. et al. Delineation of saline soils in coastal India using satellite remote sensing. Curr. Sci. 125, 1339–1353 (2023).

    Google Scholar 

  22. Department of Animal Husbandry and Dairying. 20th Livestock Census (Government of India, 2019). https://dahd.nic.in/schemes/programmes/animal-husbandry-statistics.

  23. Islam, A. S., Bala, S. K., Hussain, M. A., Hossain, M. A. & Rahman, M. M. Performance of coastal structures during cyclone Sidr. Nat. Hazards Rev. 12, 111–116 (2011).

    Google Scholar 

  24. Naim, Z., Asaduzzaman, M., Akter, M. & Islam, M. S. Impact of climate change on livestock production in Bangladesh—A review. Bangladesh J. Anim. Sci. 52, 1–14 (2023).

    Google Scholar 

  25. Goswami, R. et al. Multi-faceted impact and outcome of COVID-19 on smallholder agricultural systems: Integrating qualitative research and fuzzy cognitive mapping to explore resilient strategies. Agric. Syst. 189, 103051 (2021).

    Google Scholar 

  26. Chauhan, D. S. & Ghosh, N. Impact of climate change on livestock production: A review. J. Anim. Res. 4, 223 (2014).

    Google Scholar 

  27. Sreenivasaiah, K. In Climate Change Challenge (3C) and Social-Economic-Ecological Interface-Building—Exploring Potential Adaptation Strategies for Bio-resource Conservation Livelihood Development (eds Nautiyal, S. et al.) 531–547 (Springer, 2016). https://doi.org/10.1007/978-3-319-31014-5_32.

    Google Scholar 

  28. Choudhary, B. B. & Sirohi, S. Understanding vulnerability of agricultural production system to climatic stressors in North Indian Plains: a meso-analysis. Environ. Dev. Sustain. 24, 13522–13541 (2022).

    Google Scholar 

  29. Geethalakshmi, V. et al. Impact of climate change on coastal agriculture. Int. J. Econ. Plants 3, 093–097 (2016).

    Google Scholar 

  30. IPCC In Climate Change 2021: The Physical Science Basis contribution Working Group Sixth Assessment Report by the Intergovernmental Panel on Climate Change (eds Matthews, J. B. R. et al.) 2215–2256 (Cambridge University Press, 2021). https://doi.org/10.1017/9781009157896.

    Google Scholar 

  31. 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 7, e06231 (2021).

    Google Scholar 

  32. Belay, A., Recha, J. W., Woldeamanuel, T. & Morton, J. F. Smallholder farmers’ adaptation to climate change and determinants of their adaptation decisions in the Central Rift Valley of Ethiopia. Agric. Food Secur. 6, 24 (2017).

    Google Scholar 

  33. Suresh, K. et al. An economic analysis of agricultural adaptation to climate change impacts in Sri Lanka: An endogenous switching regression analysis. Land Use Policy 109, 105601 (2021).

    Google Scholar 

  34. IPCC. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, Cambridge, UK, 2007).

  35. Rakshit, S., Padaria, R. N. & Bandyopadhyay, S. Farmers’ adaptation strategies, coping behaviour and barriers to effective adaptation to current climatic risks: A study on Sundarban Region. Indian J. Ext. Educ. 52, 17–20 (2016).

    Google Scholar 

  36. Reddy, K. V. et al. Farmers’ perception and efficacy of adaptation decisions to climate change. Agronomy 12, 1023 (2022).

    Google Scholar 

  37. Dhanya, P., Ramachandran, A. & Palanivelu, K. Understanding the local perception, adaptation to climate change and resilience planning among the farmers of semi-arid tracks of South India. Agric. Res. 11, 291–308 (2022).

    Google Scholar 

  38. Ghosh, S. & Mistri, B. Coastal agriculture and its challenges: A case study in Gosaba Island, Sundarban, India. Space Cult. India 8, 140–154 (2020).

    Google Scholar 

  39. Mondal, T. K. Assessing the scope for promoting climate resilient agriculture in the Indian Sundarban Delta: A SWOT-AHP analysis. J. Coast. Conserv. 26, 62 (2022).

    Google Scholar 

  40. Jena, P. R., Tanti, P. C. & Maharjan, K. L. Determinants of adoption of climate resilient practices and their impact on yield and household income. J. Agric. Food Res. 14, 100659 (2023).

    Google Scholar 

  41. Padhan, N. & Madheswaran, S. Determinants of farm-level adaptation strategies to flood: Insights from a farm household-level survey in coastal districts of Odisha. Water Policy 24, 450–469 (2022).

    Google Scholar 

  42. Das, U., Ansari, M. A. & Ghosh, S. Effectiveness and upscaling potential of climate smart agriculture interventions: Farmers’ participatory prioritization and livelihood indicators as its determinants. Agric. Syst. 203, 103515 (2022).

    Google Scholar 

  43. Panja, A. et al. Climate adaptation in agricultural sector of coastal India: A comprehensive exploration of adaptation strategies. Mitig. Adapt. Strateg. Glob. Change 29, 92 (2024).

    Google Scholar 

  44. Maiti, S. et al. Adaptation strategies followed by the livestock rearers of Coastal Odisha and West Bengal to cope up with climate change. Indian J. Anim. Sci. 84, 652–659 (2014).

    Google Scholar 

  45. Kc, V. K., Dhungana, A. R., Khand, P. B., Upadhayaya, R. P. & Baral, M. P. Determinants of livestock farmers’ adaptation strategies to climate change in Gandaki province, Nepal. Indian J. Anim. Sci. 95, 348–353 (2025).

    Google Scholar 

  46. Maiti, S. et al. Determinants to climate change adaptation among the livestock-rearers of eastern coastal Region of India. J. Indian Soc. Coast. Agric. Res. 32, 80–86 (2014).

    Google Scholar 

  47. Parameswaranaik, J., Kumar, R. S., Bhawar, R. S., Darshan, N. P. & Patel, D. Factors influencing adaptation strategies by livestock owners to combat climate variability in Karnataka state: Application of ordered logistic regression model. Indian J. Anim. Sci. 86, 1046–1050 (2016).

    Google Scholar 

  48. Thinda, K. T., Ogundeji, A. A., Belle, J. A. & Ojo, T. O. Understanding the adoption of climate change adaptation strategies among smallholder farmers: Evidence from land reform beneficiaries in South Africa. Land Use Policy 99, 104858 (2020).

    Google Scholar 

  49. Derso, D., Tolossa, D. & Seyoum, A. A double hurdle estimation of crop diversification decisions by smallholder wheat farmers in Sinana District, Bale Zone, Ethiopia. CABI Agric. Biosci. 3, 25 (2022).

    Google Scholar 

  50. Workie, D. M. & Tasew, W. Adoption and intensity use of malt barley technology package by smallholder farmers in Ethiopia: A double hurdle model approach. Heliyon 9, e18477 (2023).

    Google Scholar 

  51. Carman, J. P. & Zint, M. T. Defining and classifying personal and household climate change adaptation behaviors. Glob. Environ. Change 61, 102062 (2020).

    Google Scholar 

  52. Choudhary, B. B. et al. Determinants of adoption of multiple natural resource management practices: A case study from semi-arid tropics of Central India. Environ. Dev. Sustain. 2024, 1–16 (2024).

    Google Scholar 

  53. Paul, S. & Das, C. S. Delineating the coastal vulnerability using coastal hazard wheel: A study of West Bengal coast, India. Reg. Stud. Mar. Sci. 44, 101794 (2021).

    Google Scholar 

  54. Directorate of Economics and Statistics. Area under crops—Report. https://data.desagri.gov.in/weblus/classification-of-area-report-web.

  55. NABARD. PLP 2021–22 North 24 Parganas (NABARD, 2022). https://www.nabard.org/auth/writereaddata/tender/2411200152WB_24_Parganas_North.pdf.

  56. Department of Animal Husbandry and Dairying. 20th Livestock Census (Ministry of Fisheries, Animal Husbandry and Dairying, Government of India, 2019). https://dahd.nic.in/sites/default/filess/20thLivestockcensus-2019AllIndiaReport_0.pdf.

  57. Sahana, M., Rehman, S., Paul, A. K. & Sajjad, H. Assessing socio-economic vulnerability to climate change-induced disasters: Evidence from Sundarban Biosphere Reserve, India. Geol. Ecol. Landsc. 5, 40–52 (2021).

    Google Scholar 

  58. Department of Animal Husbandry and Dairying. Annual Report 2019–20. (Government of India, 2020). https://dahd.nic.in/sites/default/filess/Annual2019-20.pdf.

  59. Dutta, S. et al. Analyzing adaptation strategies to climate change followed by the farming community of the Indian Sunderbans using Analytical Hierarchy Process. J. Coast. Conserv. 24, 61 (2020).

    Google Scholar 

  60. Ahmed, S. K. How to choose a sampling technique and determine sample size for research: A simplified guide for researchers. Oral Oncol. Rep. 12, 100662 (2024).

    Google Scholar 

  61. Jabbar, A. et al. Contract farming as a catalyst for sustainable agriculture: The case of maize growers in Punjab, Pakistan. Environ. Dev. Sustain. https://doi.org/10.1007/s10668-024-05896-5 (2025).

    Google Scholar 

  62. Nandi, S., Patel, P. & Swain, S. IMDLIB: An open-source library for retrieval, processing and spatiotemporal exploratory assessments of gridded meteorological observation datasets over India. Environ. Model. Softw. 171, 105869 (2024).

    Google Scholar 

  63. Rogers, E. M. Diffusion of Innovations (Free Press, 2003).

    Google Scholar 

  64. Noltze, M., Schwarze, S. & Qaim, M. Understanding the adoption of system technologies in smallholder agriculture: The system of rice intensification (SRI) in Timor Leste. Agric. Syst. 108, 64–73 (2012).

    Google Scholar 

  65. Cragg, J. G. Some statistical models for limited dependent variables with application to the demand for durable goods. Econometrica 39, 829–844 (1971).

    Google Scholar 

  66. García, B. Implementation of a double-hurdle model. Stata J. 13, 776–794 (2013).

    Google Scholar 

  67. Ojo, T. O. & Baiyegunhi, L. J. S. Climate change perception and its impact on net farm income of smallholder rice farmers in South-West, Nigeria. J. Clean. Prod. 310, 127373 (2021).

    Google Scholar 

  68. Burke, W. J. Fitting and interpreting Cragg’s tobit alternative using stata. Stata J. 9, 584–592 (2009).

    Google Scholar 

  69. Sahoo, B. et al. Role of mineral mixture supplementation in enhancing productivity and profitability of peri-urban dairy farming. Indian J. Anim. Nutr. 38, 41–47 (2021).

    Google Scholar 

  70. National Bureau of Animal Genetic Resources. Animal Genetic Resources of India. http://14.139.252.116:8080/appangr/openagr.htm.

  71. Biglari, T., Maleksaeidi, H., Eskandari, F. & Jalali, M. Livestock insurance as a mechanism for household resilience of livestock herders to climate change: Evidence from Iran. Land Use Policy 87, 104043 (2019).

    Google Scholar 

  72. Karimi, V., Karami, E. & Keshavarz, M. Vulnerability and adaptation of livestock producers to climate variability and change. Rangel. Ecol. Manag. 71, 175–184 (2018).

    Google Scholar 

  73. Zeren, G., Tan, J., Zheng, Z., Li, M. & Yang, F. Use of subsidized insurance policy in climate adaptation strategies: The case of pastoral regions in China. Clim. Policy 24, 332–345 (2024).

    Google Scholar 

  74. Chand, S., Kumar, A., Bhattarai, M. & Saroj, S. Status and determinants of livestock insurance in India: A micro level evidence from Haryana and Rajasthan. Indian J. Agric. Econ. 71, 335–346 (2016).

    Google Scholar 

  75. Das, S. Impact of climate change on livestock, various adaptive and mitigative measures for sustainable livestock production. Approaches Poult. Dairy Vet. Sci. 1, 64–70 (2017).

    Google Scholar 

  76. Behera, J., Jha, S. K., Maiti, S. & Garai, S. A study on housing management strategies adopted by livestock-rearers in flood-prone districts of Odisha. J. Commun. Mobil. Sustain. Dev. 16, 223–228 (2021).

    Google Scholar 

  77. Lal, K. et al. Livestock and fodder production: A potential source of livelihood for Bihar region. Int. J. Chem. Stud. 8, 211–214 (2020).

    Google Scholar 

  78. Singh, P. K., Papageorgiou, K., Chudasama, H. & Papageorgiou, E. I. Evaluating the effectiveness of climate change adaptations in the world’s largest mangrove ecosystem. Sustainability 11, 6655 (2019).

    Google Scholar 

  79. Idrissou, Y., Assani, A. S., Baco, M. N., Yabi, A. J. & Alkoiret Traoré, I. Adaptation strategies of cattle farmers in the dry and sub-humid tropical zones of Benin in the context of climate change. Heliyon 6, e04373 (2020).

    Google Scholar 

  80. Ayal, D. Y. & Mamo, B. Farmer’s climate smart livestock production adoption and determinant factors in Hidebu Abote District, Central Ethiopia. Sci. Rep. 14, 10027 (2024).

    Google Scholar 

  81. Kandlikar, M. & Risbey, J. Agricultural impacts of climate change: If adaptation is the answer, what is the question?. Clim. Change 45, 529–539 (2000).

    Google Scholar 

  82. Jha, C. K. & Gupta, V. Do better agricultural extension and climate information sources enhance adaptive capacity? A micro-level assessment of farm households in rural India. Ecofeminism Clim. Change 2, 83–102 (2021).

    Google Scholar 

  83. Matere, S. et al. Do farmers use climate information in adaptation decisions? Case of smallholders in semi-arid Kenya. Inf. Dev. https://doi.org/10.1177/02666669231152568 (2023).

    Google Scholar 

  84. Obsi Gemeda, D., Korecha, D. & Garedew, W. Determinants of climate change adaptation strategies and existing barriers in Southwestern parts of Ethiopia. Clim. Serv. 30, 100376 (2023).

    Google Scholar 

  85. Manjunath, K. V. et al. Impact of climate services on the operational decision and economic outcome of wheat (Triticum aestivum) and rice (Oryza sativa) cultivation in Haryana. Indian J. Agric. Sci. 94, 116–123 (2024).

    Google Scholar 

  86. Manjunath, K. V. et al. Impact of climate services on the operational decision of Murrah buffalo farmers in Haryana. Indian J. Dairy Sci. 77, 179–187 (2024).

    Google Scholar 

  87. Aguirre-López, J. M., Díaz-José, J., Chaloupková, P. & Guevara-Hernández, F. In Challenges in Social Network Research Methods and Applications: Methods and Applications (eds Ragozini, G. & Vitale, M. P.) 133–148 (Springer, 2020). https://doi.org/10.1007/978-3-030-31463-7_9.

    Google Scholar 

  88. Nikam, V., Kumar, S. & Kingsly, M. I. Social network factors affecting adoption of Mobile app by farmers. Indian J. Agric. Sci. 91, 193–797 (2021).

    Google Scholar 

  89. Jia, R. et al. Impact of participation in collective action on farmers’ decisions and waiting time to adopt soil and water conservation measures. Int. J. Clim. Change Strateg. Manag. 16, 201–227 (2024).

    Google Scholar 

  90. Feleke, F. B., Berhe, M., Gebru, G. & Hoag, D. Determinants of adaptation choices to climate change by sheep and goat farmers in Northern Ethiopia: The case of Southern and Central Tigray, Ethiopia. Springerplus 5, 1692 (2016).

    Google Scholar 

  91. Majumdar, C. Institutional and non-institutional credit delivery in Hooghly, West Bengal: Who are the recipients?. J. Land Rural Stud. 1, 199–211 (2013).

    Google Scholar 

  92. Rajeev, M. & Deb, S. Institutional and non-institutional credit in agriculture: Case study of Hugli district of West Bengal. Econ. Polit. Wkly. 33, 2997–3002 (1998).

    Google Scholar 

  93. Mihiretu, A., Okoyo, E. N. & Lemma, T. Determinants of adaptation choices to climate change in agro-pastoral dry lands of Northeastern Amhara, Ethiopia. Cogent. Environ. Sci. 5, 1636548 (2019).

    Google Scholar 

  94. Singh, S. Farmers’ perception of climate change and adaptation decisions: A micro-level evidence from Bundelkhand Region, India. Ecol. Indic. 116, 106475 (2020).

    Google Scholar 

  95. Atube, F. et al. Determinants of smallholder farmers’ adaptation strategies to the effects of climate change: Evidence from northern Uganda. Agric. Food Secur. 10, 6 (2021).

    Google Scholar 

  96. Aroyehun, A. R., Ugwuja, V. C. & Onoja, A. O. Determinants of melon farmers’ adaptation strategies to climate change hazards in South–South Nigeria. Sci. Rep. 14, 17395 (2024).

    Google Scholar 

  97. Waaswa, A., Oywaya Nkurumwa, A., Mwangi Kibe, A. & Ng’eno Kipkemoi, J. Adapting agriculture to climate change: Institutional determinants of adoption of climate-smart agriculture among smallholder farmers in Kenya. Cogent. Food Agric. 10, 22945471 (2024).

    Google Scholar 

  98. Olutumise, A. I. Impact of credit on the climate adaptation utilization among food crop farmers in Southwest, Nigeria: Application of endogenous treatment Poisson regression model. Agric. Food Econ. 11, 7 (2023).

    Google Scholar 

  99. Ojo, T. O., Kassem, H. S., Ismail, H. & Adebayo, D. S. Level of adoption of climate smart agriculture among smallholder rice farmers in Osun State: Does financing matter?. Sci. Afr. 21, e01859 (2023).

    Google Scholar 

  100. Mahmood, N. et al. Fatalism, climate resiliency training and farmers’ adaptation responses: Implications for sustainable rainfed-wheat production in Pakistan. Sustainability 12, 1650 (2020).

    Google Scholar 

  101. Belay, A. et al. Knowledge of climate change and adaptation by smallholder farmers: evidence from southern Ethiopia. Heliyon 8, e12089 (2022).

    Google Scholar 

  102. Upendram, S., Regmi, H. P., Cho, S.-H., Mingie, J. C. & Clark, C. D. Factors affecting adoption intensity of climate change adaptation practices: A case of smallholder rice producers in Chitwan, Nepal. Front. Sustain. Food Syst. 6, 1016404 (2023).

    Google Scholar 

  103. Sahoo, D. & Moharaj, P. Determinants of climate-smart adaptation strategies: Farm-level evidence from India. J. Asian Afr. Stud. 59, 876–894 (2024).

    Google Scholar 

  104. Singh, H. K., Prakash, N., Singh, R. & Christopher, K. Training impact analysis of farmers knowledge and adoption behavior on climate smart village. Int. J. Stat. Appl. Math. 8, 763–766 (2023).

    Google Scholar 

  105. Argade, S. et al. Impact of skill development trainings on fish farmers’ knowledge and attitude: A case study from Bihar, India. Indian J. Fish. 70, 119–125 (2023).

    Google Scholar 

  106. Lenka, S., Patnaik, B. R. & Dash, S. R. Impact of NICRA project on knowledge, skill and attitude (KSA)of farmers on climate-resilient agrotechnology’s in the NICRA operated district of Odisha. Int. J. Bio-Resour. Stress Manag. 14, 132–137 (2023).

    Google Scholar 

  107. Zakaria, A., Azumah, S. B., Appiah-Twumasi, M. & Dagunga, G. Adoption of climate-smart agricultural practices among farm households in Ghana: The role of farmer participation in training programmes. Technol. Soc. 63, 101338 (2020).

    Google Scholar 

  108. Jabbar, A. et al. Enhancing adaptation to climate change by fostering collective action groups among smallholders in Punjab, Pakistan. Front. Sustain. Food Syst. 7, 1235726 (2023).

    Google Scholar 

  109. Xu, Z., Li, J. & Ma, J. Impacts of extension contact on the adoption of formulated fertilizers and farm performance among large-scale farms in rural China. Land 11, 1974 (2022).

    Google Scholar 

  110. Ansari, M. A. Farmers’ knowledge of adaptation strategies to mitigate climate change and factors influencing their adoption. Int. J. Environ. Clim. Change 13, 926–938 (2023).

    Google Scholar 

  111. Deressa, T. T., Hassan, R. M. & Ringler, C. Perception of and adaptation to climate change by farmers in the Nile basin of Ethiopia. J. Agric. Sci. 149, 23–31 (2011).

    Google Scholar 

  112. Aryal, J. P. et al. Adoption of multiple climate-smart agricultural practices in the Gangetic plains of Bihar, India. Int. J. Clim. Change Strateg. Manag. 10, 407–427 (2018).

    Google Scholar 

  113. Devi, M. V. et al. Farmers’ climate change adaptation intention in North Eastern Hill Region of India. Curr. J. Appl. Sci. Technol. 39, 9–16 (2020).

    Google Scholar 

  114. Anang, B. T. Interceding role of agricultural extension services in adoption of climate-smart agricultural technologies in northern Ghana. Asia Pac. J. Sustain. Agric. Food Energy 10, 69–76 (2022).

    Google Scholar 

  115. Jabbar, A. et al. Synergies and determinants of sustainable intensification practices in Pakistani agriculture. Land 9, 110 (2020).

    Google Scholar 

Download references

Acknowledgements

We have a sincere gratitude to the Director, ICAR-National Dairy Research Institute, Karnal and ADG (NASF), ICAR, New Delhi for providing all the facilities for this study. We are also thankful to our esteemed dairy farmers for sharing their views and giving time for the research work.

Author information

Authors and Affiliations

  1. National Dairy Research Institute, Karnal, Haryana, 132001, India

    Amitava Panja, Sanchita Garai, Sanjit Maiti, Siddhesh Zade, Apoorva Veldandi & Gopal Sankhala

  2. ICAR-Indian Grassland and Fodder Research Institute, Jhansi, 284003, India

    Bishwa Bhaskar Choudhary

Authors

  1. Amitava Panja
    View author publications

    Search author on:PubMed Google Scholar

  2. Sanchita Garai
    View author publications

    Search author on:PubMed Google Scholar

  3. Sanjit Maiti
    View author publications

    Search author on:PubMed Google Scholar

  4. Bishwa Bhaskar Choudhary
    View author publications

    Search author on:PubMed Google Scholar

  5. Siddhesh Zade
    View author publications

    Search author on:PubMed Google Scholar

  6. Apoorva Veldandi
    View author publications

    Search author on:PubMed Google Scholar

  7. Gopal Sankhala
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Conception of the study and design of the study was done by Amitava Panja, Sanchita Garai and Sanjit Maiti. Data collection and first draft writing was done by Amitava Panja. Data analysis and data curation was done by Amitava Panja, Sanchita Garai and Sanjit Maiti. Correction of methodology was done by Bishwa Bhaskar Choudhary. Software support was done by Siddhesh Zade and Apoorva Veldandi. Study was supervised by Gopal Sankhala. All authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to
Sanchita Garai.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical declarations

The study was conducted using ethical standards for carrying out survey-based research. Procedure of the study along with the methods used were approved both at departmental level and institutional level by Dairy Extension Division, ICAR-National Dairy Research Institute, Karnal, India. Before data collection, verbal consent was obtained from all the respondents regarding their participation. Simultaneously, they were also informed regarding the voluntariness for being a respondent, information confidentiality and identification anonymity.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Panja, A., Garai, S., Maiti, S. et al. Exploring determinants of climate change adaptation by smallholder livestock farmers in coastal West Bengal, India using a double hurdle econometric approach.
Sci Rep (2026). https://doi.org/10.1038/s41598-025-32890-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-025-32890-2

Keywords

  • Adaptation strategies
  • Livestock
  • Climate change
  • Smallholder livestock rearers
  • Doubled hurdle model

Source: Ecology - nature.com

Exploring the impact of urban vitality on carbon emission mechanisms using multi-source data

Arctic driftwood proposal for durable carbon removal

This portal is not a newspaper as it is updated without periodicity. It cannot be considered an editorial product pursuant to law n. 62 of 7.03.2001. The author of the portal is not responsible for the content of comments to posts, the content of the linked sites. Some texts or images included in this portal are taken from the internet and, therefore, considered to be in the public domain; if their publication is violated, the copyright will be promptly communicated via e-mail. They will be immediately removed.

Back to Top
Close