Widespread poverty is the most serious threat and social problem that Bangladesh faces. Regional vulnerability to climate change threatens to escalate the magnitude of poverty. It is essential that poverty projections be estimated while bearing in mind the effects of climate change. The main purpose of this paper is to perform an agrarian sub-national regional analysis of climate change vulnerability in Bangladesh under various climate change scenarios and evaluate its potential impact on poverty. This study is relevant to socio-economic research on climate change vulnerability and agriculture risk management and has the potential to contribute new insights to the complex interactions between household income and climate change risks to agricultural communities in Bangladesh and South Asia. This study uses analysis of variance, cluster analysis, decomposition of variance and log-normal distribution to estimate the parameters of income variability that can be used to ascertain vulnerability levels and help us to understand the poverty levels that climate change could potentially generate. It is found that the levels and sources of income vary greatly among regions of Bangladesh. The variance decomposition of income showed that agricultural income in Mymensingh and Rangpur is the main cause of the total income difference among all sources of income. Moreover, a large variance in agricultural income among regions is induced by the gross income from rice production. Additionally, even in the long run the gradual, constant reduction of rice yield due to climate change in Bangladesh is not a severe problem for farmers. However, extreme events such as floods, flash floods, droughts, sea level rise and greenhouse gas emissions, based on Representative concentration pathways (RCPs), could increase the poverty rates in Mymensingh, Rajshahi, Barisal and Khulna—regions that would be greatly affected by unexpected yield losses due to extreme climatic events. Therefore, research into and development of adaptation measures to climate change in regions where farmers are largely dependent on agricultural income are important.

The food items, such as pulses and oil crops, are influential means of nutritional security for the people in Bangladesh. Pulses are widely called here as an alternative to meat for poor households. The study aimed to predict productivity and national demand of pulses and oil crops in Bangladesh by 2030 and 2050, minimizing the supply and demand gaps of these crops. Using the ARIMA model developed by Box and Jenkins, the current study projected Bangladesh’s pulse and oil crop demand and supply for the years 2030 and 2050. The projections showed that the total demand for pulses in 2030 will be 17.9 lakh MT and further increased to 19.5 lakh MT in 2050. The deficit in the supply of pulses will be 12.36 lakh MT in 2030 and 9.26 lakh MT in 2050 although the shortage of pulses will disappear as a result of productivity improvements and innovations. Per capita consumption of edible oil in Bangladesh is 20–22 g per day. The majority of domestically produced soybean (5% of total demand) is used in the feed industries, while edible oil from soybean depends on import. The supply of mustard oil is predicted to be in deficit by 0.30 lakh MT in 2030 and 1.68 lakh MT in 2050. Nevertheless, the estimates also warn that supply of these food items could be threatened due to climate changes. In facing future challenges, supportive government policy and substantial investment in research and extension should be given priority for technological innovation and productivity improvement. Government also needs to develop a strategic import substitution policy for higher production of these crop and storage facilities.

Heat stress is a major concern for lactating dairy cows. This study evaluated the effects of heat stress on six Holstein-Friesian crossbred dairy cows exposed to three thermal conditions represented by the Temperature-Humidity Index (THI). These conditions included a baseline pre-treatment phase at THI-72, a heat stress treatment phase at THI-75 and THI-80, and a post-treatment recovery phase at THI-72. The duration of the heat stress treatment phase was 24 h. A total of four trials, each involving three cows, were conducted in an IoT-based climatic chamber to assess various physiological, hematological, biochemical, and production parameters across these phases. Compared to the baseline (THI-72), cows showed significant increases (p < 0.05) in rectal temperature (RT), heart rate (HR), respiration rate (RR), and water intake (WI) at both THI-75 and THI-80, with the highest elevations observed at THI-80 (RT: 5.1%, HR: 8.6%, RR: 23.5%, and WI: 19.1%). Feed intake declined significantly (p < 0.05) by 6.5% and 14.0%, and milk yield dropped by 5.3% and 14.7% at THI-75 and THI-80, respectively; milk fat and protein percentages decreased by 1.1-fold and 1.2-fold. Hemoglobin, platelet, and lymphocyte counts, along with biochemical parameters (excluding serum creatinine) also decreased significantly (p < 0.05). The different levels of THI influenced pairwise correlation patterns, with THI-75 showing intense interactions and THI-80 exhibiting greater variability. The findings highlight that Holstein-Friesian crossbred dairy cows are particularly vulnerable to heat stress, even with short-term exposure. This vulnerability can lead to economic losses for Bangladeshi dairy farmers rearing Holstein-Friesian crossbred cows.

Global warming has been increasing heat stress threat in animals, which can be monitored via the Temperature Humidity Index (THI). The present study describes the THI pattern and the relationship between THI and the production performances of dairy cows in a selected area of Bangladesh. The THI value was calculated using weather station data gathered over 35 years. Based on the THI pattern, January and June were identified as the coolest and hottest months, respectively. Consequently, the production performances of 10 crossbred cows with homogenous characteristics were monitored every January and June for a 5-year period. The average THI^MEAN was found to be 17% higher in June when compared to January; with this increment of THI^MEAN, average milk production was decreased by 24.4% (p < 0.05). The milk fat and protein content were also reduced (p < 0.05) by 14.5 and 15.2%, respectively, suggesting a negative correlation. However, ash content increased by 15.3%, which indicates a positive correlation. In addition, multiple regression analysis revealed that, with each point increase in THI^MEAN and rectal temperature, there was a decrease in milk yield of 0.04 and 1.17 kg ECM, respectively. In contrary, each point increase in THI^MEAN resulted in 0.059 °C increase of rectal temperature. Taken together, THI^MEAN calculated using meteorological station data has a distinct relationship with the production performances of lactating crossbred dairy cows.

Widespread poverty is the most serious threat and social problem that Bangladesh faces. Regional vulnerability to climate change threatens to escalate the magnitude of this poverty. It is essential that projections of poverty be made while bearing in mind the effects of climate change. The main purpose of this paper is to investigate the agrarian sub-national regional analysis of climate change vulnerability in Bangladesh under various climate change scenarios and its potential impact on poverty. This study is relevant to socio-economic research on climate change vulnerability and agriculture risk management and has the potential to contribute new insights to the complex interactions in household income and climate change risks to agricultural communities in Bangladesh and South Asia. The current study uses analysis of variance, cluster analysis, decomposition of variance and log-normal distribution to estimate the parameters of income variability that ascertain vulnerability levels and help us to understand the poverty levels that climate change could potentially incur. It is found that the income share in income sources revealed that income category shares across the various regions of Bangladesh are far from uniform. The variance decomposition of income showed that agricultural income in Mymensingh and Rangpur is the main cause of income difference. Moreover, large variance of agricultural income in the regions is induced by gross income from rice production. Additionally, constant reduction of rice yield due to climate change in Bangladesh is not such a severe problem for farmers, however, the extreme events like flood, flash flood, drought, sea level rise, and greenhouse gas emission based on RCPs could increase the poverty rates in Mymensingh, Rajshahi, Barisal, and Khulna regions that would be highly affected by unexpected yield loss due to extreme climatic events. Therefore, research and development of adaptation measures to climate change for regions where farmers are largely dependent on agricultural income is important.