Shahrier Rafee, Hasan Mohammad Nazmol, Ankita Sadia Yesmin, Tasnim Ismat, Rahman Kazi Tamim
Faculty of Agricultural Economics and Rural Development, Gazipur Agricultural University, Gazipur, Bangladesh.
Department of Agricultural and Applied Statistics, Bangladesh Agricultural University, Mymensingh, Bangladesh.
PLoS One. 2025 Jul 23;20(7):e0328699. doi: 10.1371/journal.pone.0328699. eCollection 2025.
Bangladesh has three distinct rice-growing seasons: Aus, Aman, and Boro, each with its distinct climatic state. Climatic factors interacting with non-climatic factors impact seasonal rice yield. However, research hasn't yet examined how climatic and non-climatic factors (CNCFs) affect the yield of rice production during the Boro season (YBR). Therefore, this study attempted to assess the impact of CNCFs on YBR using time series modeling. Accordingly, the modeling approaches used stationarity testing and pairwise correlation analysis to verify the suitability of the CNCFs for further analysis. After that, the autoregressive distributed lag (ARDL) model, the Granger causality test, and the principal component analysis (PCA) were used to predict how the CNCFs affect YBR. The ARDL model predicted that area and temperature had a substantial positive effect on YBR in both the long- and short-run, but humidity adversely influenced YBR in the long-run and positively in the short-run. The Granger causality test revealed a unidirectional causal relationship between YBR and CNCFs, except for the climatic factor rainfall. On the other hand, the non-climatic factors area, population, energy consumption, and fertilizer consumption were positively associated with YBR and substantially contributed to PC1's (71.7%) variation. Aligning these results, this study concluded that the area, temperature, population, fertilizer consumption, and energy consumption positively impacted the YBR, while humidity negatively impacted it. These findings are crucial for ensuring Bangladesh's rice security amid climate change, guiding policymaking, and addressing future rice demand. Therefore, policymakers and stakeholders should focus on controlling greenhouse gas emissions to keep temperatures and humidity consistent, developing climate-tolerant rice cultivars, encouraging farmers to use organic fertilizer, and adapting eco-friendly technologies for sustainable rice production.
奥什、阿曼和boro,每个季节都有其独特的气候状况。与非气候因素相互作用的气候因素会影响季节性水稻产量。然而,研究尚未考察气候和非气候因素(CNCFs)如何影响boro季节(YBR)的水稻产量。因此,本研究试图使用时间序列模型评估CNCFs对YBR的影响。相应地,建模方法使用平稳性检验和成对相关性分析来验证CNCFs是否适合进一步分析。之后,使用自回归分布滞后(ARDL)模型、格兰杰因果检验和主成分分析(PCA)来预测CNCFs如何影响YBR。ARDL模型预测,面积和温度在长期和短期内对YBR都有显著的正向影响,但湿度在长期内对YBR有不利影响,在短期内有正向影响。格兰杰因果检验揭示了YBR与CNCFs之间存在单向因果关系,但气候因素降雨除外。另一方面,非气候因素面积、人口、能源消耗和化肥消耗与YBR呈正相关,并对PC1的变化(71.7%)有显著贡献。综合这些结果,本研究得出结论,面积、温度、人口、化肥消耗和能源消耗对YBR有正向影响,而湿度对其有负向影响。这些发现对于在气候变化背景下确保孟加拉国的水稻安全、指导政策制定以及满足未来水稻需求至关重要。因此,政策制定者和利益相关者应专注于控制温室气体排放以保持温度和湿度稳定,培育耐气候水稻品种,鼓励农民使用有机肥料,并采用环保技术实现可持续水稻生产。