اثر پذیرش راهبرد‌های مقابله با تغییر اقلیم بر کارایی فنی گندمکاران منطقه سیستان

نوع مقاله : مقالات پژوهشی به زبان انگلیسی

نویسندگان

• هما ناروئی ¹
• محمود احمدپور برازجانی ¹
• ماشاءالله سالارپور ¹
• علیرضا کیخا ¹
• رضا اسفنجاری کناری ²

¹ گروه اقتصاد کشاورزی، دانشکده کشاورزی، دانشگاه زابل، زابل، ایران

² دانشکده علوم کشاورزی‬، دانشگاه گیلان، گیلان، ایران

10.22067/jead.2024.87331.1259

چکیده

تأثیر منفی و مخرب پدیده تغییر اقلیم بر عملکرد و بهره‌وری عوامل تولید کشاورزی در بسیاری از مناطق جهان به‌خصوص در مناطق خشک و نیمه­خشک به اثبات رسیده است. در این راستا، اتخاذ راهبرد‌های نوآورانه برای افزایش انعطاف‌پذیری و سازگاری کشاورزان به منظور تطبیق با تغییرات اقلیمی گسترش یافته است. بنابراین، آگاهی از میزان اثرگذاری راهبردهای تطبیق با اقلیم بر میزان کارایی و عملکرد زراعین حائز اهمیت است. بر این اساس، در پژوهش حاضر، تأثیر راهبردهای تطبیق با تغییر اقلیم همراه با مصرف نهاده‌ها و عوامل خارج از کنترل کشاورز برکارایی فنی با استفاده از مدل مرزی تصادفی اصلاح­شده درونزا (EMSF) ارزیابی شد. داده­ها ازطریق تکمیل 265 پرسشنامه درسال زراعی 1401-1400 و به روش نمونه­گیری تصادفی چندمرحله‌ای برای تولیدکنندگان گندم در منطقه سیستان جمع­آوری شد. به‌ منظور ساختن شاخص تطبیق از روش تجزیه و تحلیل مؤلفه اصلی (PCA) استفاده شد. نتایج PCA نشان داد تغییر اندازه زمین (812/0) خاکورزی حفاظتی (797/0) و تغییر تاریخ کشت (619/0) بیشترین بار عاملی و استفاده از آب باران (219/0) و استفاده از کودهای زیستی (327/0) کمترین بار عاملی راهبردهای تطبیق در بین کشاورزان را دارند. دراین مطالعه، میانگین کارایی فنی گندمکاران 82 درصد محاسبه شد. نتایج برآورد مدل نشان داد که مساعدت نهاده‌های نیروی کار، سموم شیمیایی، کود شیمیایی، آب و ماشین‌آلات به کارایی تولید گندم از نظر آماری مثبت و معنی‌دار است و با اجرای راهبردهای تطبیق با اقلیم توسط کشاورزان، میزان ناکارایی فنی کاهش می‌یابد. همچنین، متغیرهای سطح تحصیلات، تجربه کشاورزی، دسترسی به اطلاعات اقلیمی و دسترسی به اعتبارات در کاهش ناکارایی فنی مؤثرند.

کلیدواژه‌ها

• تحلیل مؤلفه‌های اصلی
• رگرسیون لاجیت
• مدل مرزی تصادفی
• ویژگی‌های اجتماعی-اقتصادی

موضوعات

• اقتصاد کشاورزی

©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

مراجع

1. Ackerberg, D., Caves, K., & Frazer, G. (2006). Structural estimation of production functions. University Library of Munich, Germany. https://mpra.ub.uni-muenchen.de/38349/1/MPRA_paper_38349.pdf.
2. Ado, A.M., Leshan, J., Savadogo, P., Bo, L. & Shah, A.A. (2018) Farmers' awareness and perception of climate change impacts: case study of Aguie district in Niger. Environment, Development and Sustainability 21, 2963-2977. https://doi.org/10.1007/s10668-018-0173-4
3. Agriculture Jihad Ministry. (2020). Agricultural Statistics of Crops for the Crop Year 1399-1400, Agriculture Organization of Sistan and Baluchestan. (In Persian)
4. Anser, M. K., Hina, T., Hameed, S., Nasir, M. H., Ahmad, I., & Naseer, M. A. u. R. (2020). Modeling adaptation strategies against climate change impacts in integrated rice-wheat agricultural production system of Pakistan. International Journal of Environmental Research and Public Health, 17(7), 2522. https://doi.org/10.3390/ijerph17072522
5. Azadi, Y., Yazdanpanah, M., & Mahmoudi, H. (2019). Understanding smallholder farmers’ adaptation behaviors through climate change beliefs, risk perception, trust, and psychological distance: Evidence from wheat growers in Iran. Journal of environmental management, 250, 109456. https://doi.org/10.1016/j.jenvman.2019.109456
6. Baiyegunhi, L., Hassan, M., Danso-Abbeam, G., & Ortmann, G. (2019). Diffusion and adoption of Integrated Striga Management (ISM) technologies among smallholder maize farmers in rural northern Nigeria. Technology in Society, 56, 109-115. https://doi.org/10.1016/j.techsoc.2018.09.009
7. Binam, J. N., Tonye, J., Nyambi, G., & Akoa, M. (2004). Factors affecting the technical efficiency among smallholder farmers in the slash and burn agriculture zone of Cameroon. Food policy, 29(5), 531-545. https://doi.org/10.1016/j.foodpol.2004.07.013
8. Bonzanigo, L., Bojovic, D., Maziotis, A., & Giupponi, C. (2016). Agricultural policy informed by farmers’ adaptation experience to climate change in Veneto, Italy. Regional Environmental Change, 16, 245-258. https://doi.org/10.1007/s10113-014-0750-5
9. Bozorgparvar, E., Yazdanpanah, M., Forouzani, M., & Khosravipour, B. (2018). Cleaner and greener livestock production: Appraising producers' perceptions regarding renewable energy in Iran. Journal of Cleaner Production, 203, 769-776. https://doi.org/10.1016/j.jclepro.2018.08.280
10. Camarotto, C., Dal Ferro, N., Piccoli, I., Polese, R., Furlan, L., Chiarini, F., & Morari, F. (2018). Conservation agriculture and cover crop practices to regulate water, carbon and nitrogen cycles in the low-lying Venetian plain. Catena, 167, 236-249. https://doi.org/10.1016/j.catena.2018.05.006
11. Chandio, A. A., Magsi, H., Rehman, A., & Sahito, J. G. M. (2017). Types, sources and importance of agricultural credits in Pakistan. Journal of Applied Environmental and Biological Sciences, 7(3), 144-149.
12. Danso-Abbeam, G., Bosiako, J. A., Ehiakpor, D. S., & Mabe, F. N. (2017). Adoption of improved maize variety among farm households in the northern region of Ghana. Cogent Economics & Finance, 5(1), 1416896. https://doi.org/10.1080/23322039.2017.1416896
13. Deng, J., Sun, P., Zhao, F., Han, X., Yang, G., & Feng, Y. (2016). Analysis of the ecological conservation behavior of farmers in payment for ecosystem service programs in eco-environmentally fragile areas using social psychology models. Science of the Total Environment, 550, 382-390. https://doi.org/10.1016/j.scitotenv.2016.01.152
14. FAO. (2015). FAOSTAT. Retrieved 03.12.15 from http://www.fao.org/worldfoodsituation/csdb/en/
15. Giri, N. C. (1974). Introduction to Probability and Statistics: Statistics (Vol. 7). M. Dekker.
16. Hotelling, H. (1933). Analysis of a complex of statistical variables into principal components. Journal of educational psychology, 24(6), 417. https://doi.org/10.1037/h0071325
17. IPCC. (2017). Scoping of the IPCC sixth assessment report (AR6) background, cross cutting issues and the AR6 synthesis report. IPCC-XLVI/Doc. 6. (4.VIII.2017). Agenda Item: 7.4. IPCC Secretariat, Geneva.
18. Karimi, V., Karami, E., & Keshavarz, M. (2018). Climate change and agriculture: Impacts and adaptive responses in Iran. Journal of Integrative Agriculture, 17(1), 1-15. https://doi.org/10.1016/S2095-3119(17)61794-5
19. Khadka, C., Aryal, K. P., Edwards-Jonášová, M., Upadhyaya, A., Dhungana, N., Cudlin, P., & Vacik, H. (2018). Evaluating participatory techniques for adaptation to climate change: Nepal case study. Forest Policy and Economics, 97, 73-82. https://doi.org/10.1016/j.forpol.2018.08.017
20. Khakifirouz, Z., Niknami, M., Keshavarz, M. & Sabouri, M. S. (2022). Drivers of Farmers’ Resilience to Drought: A Case of Sistan Plain. Iranian Agricultural Extension and Education Journal, 18, 161-179. http://www.iaeej.ir/article_156443.html?lang=en (In Persian)
21. Khanal, U., Wilson, C., Lee, B. L., & Hoang, V. N. (2018). Climate Change Adaptation Strategies and Food Productivity in Nepal: A Counterfactual Analysis. Climatic Change, 148(4), 575-590. https://doi.org/10.1007/s10584-018-2214-2
22. Kitole, F. A., Tibamanya, F. Y., & Sesabo, J. K. (2024). Exploring the nexus between health status, technical efficiency, and welfare of small-scale cereal farmers in Tanzania: A stochastic frontier analysis. Journal of Agriculture and Food Research, 15, 100996. https://doi.org/10.1016/j.jafr.2024.100996
23. Luo, L., Qin, L., Wang, Y., & Wang, Q. (2016). Environmentally-friendly agricultural practices and their acceptance by smallholder farmers in China—A case study in Xinxiang County, Henan Province. Science of the Total Environment, 571, 737-743. https://doi.org/10.1016/j.scitotenv.2016.07.045
24. Ma, W., Renwick, A., Yuan, P., & Ratna, N. (2018). Agricultural cooperative membership and technical efficiency of apple farmers in China: An analysis accounting for selectivity bias. Food policy, 81, 122-132. https://doi.org/10.1016/j.foodpol.2018.10.009
25. Mardani Najafabadi, M., Mirzaei, A., Azarm, H., & Nikmehr, S. (2022). Managing Water Supply and Demand to Achieve Economic and Environmental Objectives: Application of Mathematical Programming and ANFIS Models. Water Resources Management, 36(9), 3007-3027. https://doi.org/10.1007/s11269-022-03178-1
26. Mensah, A., & Brummer, B. (2016). Drivers of technical efficiency and technology gaps in Ghana’s mango production sector: A stochastic metafrontier approach Amos. African Journal of Agricultural and Resource Economics, 11(2), 101-117. 22004/ag.econ.241854
27. Mirzaei, A., & Zibaei, M. (2021). Water conflict management between agriculture and wetland under climate change: Application of economic-hydrological-behavioral modelling. Water Resources Management, 35, 1-21. https://doi.org/10.1007/s11269-020-02703-4
28. Mirzaei, A., Azarm, H., Yazdanpanah, M., & Najafabadi, M.M. (2022). Socio-economic, social-capital, and psychological characteristics and climate change adaptive behavior of farmers in Iran. Climate Research, 87, 1-12. https://doi.org/10.3354/cr01683
29. Ogundari, K., & Bolarinwa, O.D. (2018). Impact of agricultural innovation adoption: a meta‐ Australian Journal of Agricultural and Resource Economics, 62(2), 217-236. https://doi.org/10.1111/1467-8489.12247
30. Ojo, T., & Baiyegunhi, L. (2020). Determinants of climate change adaptation strategies and its impact on the net farm income of rice farmers in south-west Nigeria. Land Use Policy, 95, 103946. https://doi.org/10.1016/j.landusepol.2019.04.007
31. Ojo, T., Baiyegunhi, L., & Salami, A. (2019). Impact of credit demand on the productivity of rice farmers in South West Nigeria. Journal of Economics and Behavioral Studies, 11(1 (J)), 166-180. https://doi.org/10.22610/jebs.v11i1(J).2757
32. Okonya, J. S., Syndikus, K., & Kroschel, J. (2013). Farmers' perception of and coping strategies to climate change: Evidence from six agro-ecological zones of Uganda. Journal of Agricultural Science, 5(8), 252. https://doi.org/10.5539/jas.v5n8p252
33. Otitoju, M.A., & Enete, A.A. (2014). Climate change adaptation strategies and farm-level efficiency in food crop production in southwestern, Nigeria. Tropicultura, (32), 3.
34. Page, G., & Bellotti, B. (2015). Farmers value on-farm ecosystem services as important, but what are the impediments to participation in PES schemes? Science of the Total Environment, 515, 12-19. https://doi.org/10.1016/j.scitotenv.2015.02.029
35. Pagliacci, F., Defrancesco, E., Mozzato, D., Bortolini, L., Pezzuolo, A., Pirotti, F., Pisani, E., & Gatto, P. (2020). Drivers of farmers' adoption and continuation of climate-smart agricultural practices. A study from northeastern Italy. Science of the Total Environment, 710, 136345. https://doi.org/10.1016/j.scitotenv.2019.136345
36. Pearson, K. (1971). LIII. On lines and planes of closest fit to systems of points in space. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 2(11), 559-572. https://doi.org/10.1080/14786440109462720
37. Roco, L., Bravo-Ureta, B., Engler, A., & Jara-Rojas, R. (2017). The impact of climatic change adaptation on agricultural productivity in Central Chile: A stochastic production frontier approach. Sustainability, 9(9), 1648. https://doi.org/10.3390/su9091648
38. Sardar Shahraki, A., & Ghaffari Moghdam, Z. (2023). Analysis of types of efficiency with risk of wheat production in Sistan region. Iranian Journal of Agricultural Sciences, 54, 201-220. 22059/ijaedr.2022.341903.669143 (In Persian)
39. Shaffril, H. A. M., Krauss, S. E., & Samsuddin, S. F. (2018). A systematic review on Asian's farmers' adaptation practices towards climate change. Science of the Total Environment, 644, 683-695. https://doi.org/10.1016/j.scitotenv.2018.06.349
40. Wahid, U., Ali, S., & Hadi, N. A. (2017). On the estimation of technical efficiency of tomato growers in Malakand, Pakistan. Sarhad Journal of Agriculture, 33(3), 357-365.
41. Yazdanpanah, M., Forouzani, M., Abdeshahi, A., & Jafari, A. (2016). Investigating the effect of moral norm and self-identity on the intention toward water conservation among Iranian young adults. Water Policy, 18(1), 73-90. https://doi.org/10.2166/wp.2015.031
42. Zaveri, E., Russ, J., & Damania, R. (2020). Rainfall anomalies are a significant driver of cropland expansion. Proceedings of the National Academy of Sciences, 117(19), 10225-10233. https://doi.org/10.1073/pnas.1910719117
43. Zhang, B., Fu, Z., Wang, J., & Zhang, L. (2019). Farmers’ adoption of water-saving irrigation technology alleviates water scarcity in metropolis suburbs: A case study of Beijing, China. Agricultural Water Management, 212, 349-357. https://doi.org/10.1016/j.agwat.2018.09.021