Agricultural productivity is affected by air temperature and CO 2 concentration. The relationships among grain yields of dry season irrigated rice ( <i> Boro </i> ) varieties (BRRI dhan28, BRRI dhan29 and BRRI dhan58) with increased temperatures and CO2 concentrations were investigated for futuristic crop management in six regions of Bangladesh using CERES-Rice model (DSSATv4.6). Maximum and minimum temperature increase rates considered were 0 ° C, +1 ° C, +2 ° C, +3 ° C and +4 ° C and CO2 concentrations were ambient (380), 421, 538, 670 and 936 ppm. At ambient temperature and CO2 concentration, attainable grain yields varied from 6506 to 8076 kg · ha - 1 depending on rice varieties. In general, grain yield reduction would be the highest (13 % - 23%) if temperature rises by 4 ° C and growth duration reduction would be 23 - 33 days. Grain yield reductions with 1 ° C, 2 ° C and 3 ° C rise in temperature are likely to be compensated by increased CO2 levels of 421, 538 and 670 ppm, respectively. In future, the highest reduction in grain yield and growth duration would be in cooler region and the least in warmer saline region of the country. Appropriate adaptive techniques like shifting in planting dates, water and nitrogen fertilizer management would be needed to overcome climate change impacts on rice production.
Bangladesh is a deltaic small country in South Asia with the 13th highest world population density and the population would be 202 million by 2050 [
Throughout the last 150 years, atmospheric CO2 concentration has increased from 280 ppmv to 385 ppmv in 2008 (https://www.esrl.noaa.gov/gmd/ccgg/trends/) due to widespread human activities such as fossil fuel burning, cement production, and modified land-use patterns [
Crop agriculture in Bangladesh is dominated by rice monoculture. Almost 80% of the total cropped area is planted with rice in different seasons, which accounts for more than 90% of total grain production [
Some studies have recently investigated the economic effects of climate change on agricultural production in developing countries [
The study was conducted in six locations across the country of Bangladesh having diverse soil and weather conditions. The study locations were Gazipur (23˚45'N latitude, 90˚22'E longitude, 8.4 m above mean sea level [AMSL]), Rangpur (24˚41'N latitude, 89˚16'E longitude, 33.04 m AMSL), Rajshahi (24˚22'N latitude, 88˚22'E longitude, 17.24 m AMSL), Barisal (22˚41'N latitude, 90˚21'E longitude, 2.54 m AMSL), Comilla (23˚28'N latitude, 91˚09'E longitude, 6.54 m AMSL) and Habiganj (24˚25'N latitude, 91˚25'E longitude, 22.54 m AMSL) districts of Bangladesh.
Selected input data used for CERES-Rice model are shown in
Weather data for the study regions were collected from the Bangladesh Meteorological Department (BMD) for the period of 1981-2015. Base year daily average (to minimize unusual phenomenon) of maximum and minimum temperatures, rainfall and sunshine hours were calculated and created two successive
Agronomic data | Pedological-hydrological data | Daily weather data |
---|---|---|
Sowing and transplanting date | Soil classification | Maximum and minimum air temperature |
Row spacing: seeding depth | Texture | Precipitation |
Number of plants hill−1 | Number of layers in soil profile | Solar radiation |
Number of plants m−2 | Slope | |
Age of seedling (day) | Permeability | |
Base temperature to estimate phenological stages | Drainage | |
Station information: | Soil layer depth | |
Latitude | Soil horizon | |
Longitude | Clay, silt, and sand content | |
Bulk density | ||
Saturated hydraulic conductivity for each soil layer | ||
Total nitrogen for each layer | ||
Soil pH for each layer | ||
Root quantity for each layer |
years’ weather file for DSSAT format, because Boro rice grows from November in one year and ends at April or May in the next year. The seasonal model simulation was run in SIMMETEO mode for 30 years to capture temperature and CO2 effects on yield and growth duration of selected varieties.
Extreme weather parameters like yearly number of cold spell duration indicator by taking annual count of days with at least 6 consecutive days when minimum temperature (<10th percentile) and number of warm spell indicator by taking annual count of days with at least 6 consecutive days when maximum temperature (>90th percentile) was estimated by using RClimDex v1.0 model software [
Location-wise soil parameters used in DSSATv4.6 model is thickness of three layers, layer-wise sand, clay, bulk density, soil organic carbon and soil hydraulic characters. Soil pH, EC and slope also are required as inputs for different locations (
BRRI dhan28, BRRI dhan29 and BRRI dhan58 were used for grain yield and growth duration under varying levels of increased temperatures and CO2 concentrations. In all locations, selected varieties were tested against 15 November sowing, the optimum sowing date for Boro rice cultivation. In sowing date experiment, seeds were sown on 15 October to 30 December at 7 days interval to find out the optimum sowing date and to overcome the climatic effects for Boro rice growing.
Attributes | Gazipur | Rangpur | Rajshahi | Barisal | Comilla | Habiganj | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Soil depth (cm) | 20 | 40 | 60 | 20 | 40 | 60 | 20 | 40 | 60 | 20 | 40 | 60 | 20 | 40 | 60 | 20 | 40 | 60 |
WP (vol., frac.) | 0.29 | 0.29 | 0.28 | 0.09 | 0.08 | 0.06 | 0.23 | 0.17 | 0.15 | 0.24 | 0.24 | 0.22 | 0.26 | 0.25 | 0.24 | 0.26 | 0.25 | 0.24 |
FC (vol., frac.) | 0.45 | 0.43 | 0.40 | 0.28 | 0.22 | 0.26 | 0.41 | 0.35 | 0.35 | 0.44 | 0.44 | 0.44 | 0.41 | 0.39 | 0.38 | 0.41 | 0.39 | 0.39 |
Porosity (vol., frac.) | 0.50 | 0.50 | 0.49 | 0.48 | 0.46 | 0.40 | 0.48 | 0.49 | 0.44 | 0.49 | 0.48 | 0.48 | 0.46 | 0.47 | 0.47 | 0.46 | 0.47 | 0.47 |
Ks (cm/hr) | 0.32 | 0.35 | 0.32 | 1.10 | 0.89 | 0.81 | 0.15 | 0.48 | 0.48 | 0.15 | 0.14 | 0.14 | 0.17 | 0.19 | 0.19 | 0.29 | 0.21 | 0.19 |
BD (g/cc) | 1.35 | 1.34 | 1.35 | 1.39 | 1.41 | 1.52 | 1.29 | 1.42 | 1.42 | 1.26 | 1.30 | 1.31 | 1.36 | 1.35 | 1.35 | 1.34 | 1.35 | 1.35 |
OC (%) | 0.72 | 0.60 | 0.38 | 0.45 | 0.37 | 0.20 | 1.18 | 1.10 | 0.90 | 0.90 | 0.70 | 0.40 | 0.54 | 0.31 | 0.29 | 0.74 | 0.31 | 0.21 |
Clay (%) | 48.0 | 48.0 | 47.0 | 17.0 | 8.0 | 5.0 | 60.0 | 35.0 | 37.0 | 34.0 | 36.0 | 34.0 | 46.0 | 44.0 | 42.0 | 45.0 | 44.0 | 42.0 |
Silt (%) | 47.0 | 46.0 | 47.0 | 51.0 | 37.0 | 15.0 | 27.0 | 30.0 | 30.0 | 59.0 | 58.0 | 56.0 | 42.0 | 41.0 | 40.0 | 43.0 | 41.0 | 40.0 |
Total N (%) | 0.07 | 0.06 | 0.04 | 0.04 | 0.03 | 0.02 | 0.15 | 0.12 | 0.10 | 0.09 | 0.07 | 0.04 | 0.05 | 0.03 | 0.03 | 0.07 | 0.03 | 0.02 |
pH | 6.4 | 6.3 | 6.2 | 5.5 | 5.9 | 6.1 | 5.6 | 6.0 | 6.2 | 7.5 | 7.0 | 6.8 | 6.7 | 7.0 | 7.3 | 6.6 | 7.0 | 7.2 |
*WP-Wilting point, FC-field capacity, Ks-Saturated hydraulic conductivity, BD-Bulk density, OC-Organic carbon.
Potential yield is defined as the maximum yield of a variety restricted only by season-specific climatic conditions. This assumes that other inputs (nutrient, water, etc.) are non-limiting and cultural practices are optimal. Thus, the potential yield of a crop depends on the temporal variation in CO2 level in the atmosphere, solar radiation, maximum and minimum temperatures during the crop growing season and physiological characteristics of the variety. Mechanistic crop growth models are routinely used to estimate potential yield and assess the effects of climate change [
To simulate potential rice yield CERES-Rice v4.6 was used. This mechanistic model simulates crop growth and development processes, net photosynthesis based on radiation use efficiency, leaf area index, extinction coefficient and light absorption by the canopy [
Potential yields of BRRI dhan28, BRRI dhan29 and BRRI dhan58, the most popular varieties in dry season of Bangladesh, were simulated. Genetic coefficients used for those varieties are provided in
In future, the rise in temperature is likely to be 2˚C to 4˚C by 2100 in South Asia including Bangladesh [
Genetic coefficient parameters | Values | |||
---|---|---|---|---|
BRRI dhan28 | BRRI dhan29 | BRRI dhan58 | ||
Juvenile phase coefficient (P1), GDDa | 825 | 950 | 850 | |
Photoperiodism coefficient (P2R), GDD h−1 | 150 | 150 | 150 | |
Grain filling duration coefficient (P5), GDD | 425 | 550 | 470 | |
Critical photoperiod (P20), h | 12.6 | 12.8 | 12.7 | |
Spikelet number coefficient (G1) | 50 | 60 | 55 | |
Single grain weight (G2), g | 0.022 | 0.021 | 0.021 | |
Tillering coefficient (G3) | 1.0 | 1.0 | 1.0 | |
Temperature tolerance coefficient (G4) | 1.0 | 1.0 | 1.0 | |
aGDD, growing degree days (˚C).
During initial growth stage, Boro rice plants grow under cool and dry conditions but exposed to hot environment in flowering and harvesting stages. Although Boro rice growing season is generally uneventful, few localized thunder showers take place sometimes. It is found that temperature stress and resultant crop damage is a significant reason for reductions in Boro rice yield, especially with delayed established crop. According to CMIP5 and Earth System Model, predicted CO2 concentrations will be reaching 421 ppm (RCP2.6), 538 ppm (RCP4.5), 670 ppm (RCP6.0), and 936 ppm (RCP 8.5) by the year 2100 [
Grain yields of selected rice varieties varied among regions mainly due to climatic variability and soil properties. In general, the highest potential grain yield was found in Rangpur and the lowest in Barisal region irrespective of varieties. Grain yield varied from 6.50 to 7.36, 7.29 to 8.08 and 6.84 to 7.80 t・ha−1 for BRRI dhan28, BRRI dhan29 and BRRI dhan58, respectively based on long-term (1981-2015) weather parameters (
Long-term (1981-2015) monthly mean weather data showed that mean maximum temperature varied from 23.0˚C to 36.1˚C for all the study regions. The
lowest mean maximum temperature was found in January and the highest mean maximum temperature in April (
Climatic extreme events like five years’ total number of cold spell duration were in decreasing trends in most of the regions, except a slight deviation in Rangpur and Rajshahi areas (
Year | Gazipur | Rangpur | Rajshahi | Barisal | Comilla | Habiganj | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Cold spell (d) | Warm spell (d) | Cold spell (d) | Warm spell (d) | Cold spell (d) | Warm spell (d) | Cold spell (d) | Warm spell (d) | Cold spell (d) | Warm spell (d) | Cold spell (d) | Warm spell (d) | |
1981-85 | 0 | 19 | 0 | 6 | 17 | 21 | 27 | 27 | 23 | 13 | 21 | 0 |
1986-90 | 7 | 60 | 19 | 18 | 31 | 60 | 8 | 14 | 12 | 13 | 40 | 12 |
1991-95 | 7 | 31 | 43 | 8 | 23 | 40 | 25 | 7 | 58 | 7 | 41 | 13 |
1996-00 | 7 | 44 | 8 | 32 | 6 | 38 | 32 | 29 | 26 | 27 | 7 | 75 |
2001-05 | 0 | 20 | 12 | 7 | 12 | 42 | 0 | 6 | 0 | 28 | 0 | 51 |
2006-10 | 6 | 32 | 15 | 0 | 30 | 50 | 20 | 27 | 6 | 26 | 12 | 96 |
2011-15 | 0 | 44 | 40 | 7 | 22 | 71 | 7 | 38 | 0 | 18 | 0 | 79 |
duration caused by increased temperature and the sharp decline after 30˚C was because of spikelet sterility from high temperature damage.
Grain yields decreased with increase in temperatures at 380, 421, 538, 670 and 936 ppm CO2 levels; although it improved with increasing CO2 levels for a specific temperature rise (Figures 3-5). Increase in grain yields were 2.6% - 2.8% for RCPs 2.6, 10.8% - 11.8% for RCPs 4.5 and 19.4% - 21.2% for RCPs 6.0 and 32.7% - 37.1% for RCPs 8.5 with varied CO2 levels. The highest yield increase was 40.3% with BRRI dhan28, 33.6% with BRRI dhan29 and 40.3% with BRRI dhan58 rice varieties at 936 ppm CO2. In all regions of Bangladesh, predicted mean yield reduction was 4.77%, 3.44% and 5.03% per degree rise in temperature for BRRI dhan28, BRRI dhan29 and BRRI dhan58, respectively at 380 ppm CO2 level. Mahmood [
was minimum (0.4% - 3%) because of temperature rise up to 2˚C. This part of the country generally enjoys cooler environment for a longer period in winter season and thus predicted temperature increase by 2˚C might not be hazardous for Boro rice production in future.
Grain yield reduction as predicted through the use of ORYZA1 and INFOCROP rice models with 1˚C increase in temperature was 7.20% and 6.66%, respectively at 380 ppm CO2 level [
An increase in air CO2 level generally increased crop yield because of stimulated photosynthetic processes and improved water use efficiency [
All the study regions had lower minimum average temperature at sowing (middle of November) and transplanting (January) time and it increased during tillering, panicle initiation and flowering stages. After nineties, cold spell at Rangpur and Rajshahi areas was is increasing trend that might have inflicted cold injury of Boro rice seedlings (
regions, warm spells were in increasing trend resulting in reduced rice production in those areas (
In all studied regions, growth duration of rice varieties was not significantly influenced by CO2 levels but it was reduced by 7.45, 7.49 and 7.88 days for BRRI dhan28, BRRI dhan29 and BRRI dhan58, respectively with every degree increase in temperature compared to ambient temperature (
Locations | BRRI dhan28 | BRRI dhan29 | BRRI dhan58 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Increase in temperature | ||||||||||||
+1 | +2 | +3 | +4 | +1 | +2 | +3 | +4 | +1 | +2 | +3 | +4 | |
Gazipur | 8 | 15 | 21 | 26 | 9 | 18 | 24 | 29 | 10 | 17 | 22 | 28 |
Rangpur | 10 | 18 | 26 | 33 | 9 | 15 | 25 | 33 | 9 | 17 | 26 | 33 |
Rajshahi | 7 | 14 | 20 | 26 | 7 | 10 | 14 | 26 | 9 | 17 | 23 | 29 |
Barisal | 6 | 13 | 17 | 23 | 8 | 15 | 21 | 25 | 7 | 12 | 18 | 23 |
Comilla | 10 | 16 | 22 | 27 | 7 | 15 | 22 | 28 | 10 | 17 | 24 | 29 |
Habiganj | 7 | 17 | 24 | 29 | 9 | 16 | 24 | 30 | 7 | 17 | 24 | 29 |
At the ambient CO2 concentration, grain yield of rice is likely to be reduced by 16.4% - 21.3% for BRRI dhan28 (
CO2 level (ppm) | Temperature rise (˚C) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Gazipur | Rangpur | |||||||||
0 | +1 | +2 | +3 | +4 | 0 | +1 | +2 | +3 | +4 | |
380 | 0.0 | −4.2 | −9.7 | −11.9 | −17.5 | 0.0 | −5.1 | −8.7 | −18.3 | −21.3 |
421 | 2.8 | −1.5 | −7.2 | −9.6 | −15.2 | 2.9 | −2.3 | −6.1 | −16.0 | −19.3 |
538 | 11.7 | 7.1 | 0.8 | −1.8 | −8.1 | 11.7 | 6.6 | 1.8 | −8.7 | −12.5 |
670 | 20.6 | 15.7 | 8.7 | 6.1 | −0.4 | 22.6 | 16.3 | 10.5 | −1.0 | −4.9 |
936 | 36.6 | 31.3 | 21.4 | 18.8 | 11.7 | 40.6 | 32.6 | 26.6 | 10.8 | 6.5 |
Rajshahi | Barisal | |||||||||
380 | 0.0 | −2.4 | −10.3 | −17.2 | −19.6 | 0.0 | −4.0 | −8.5 | −10.3 | −16.4 |
421 | 2.9 | 0.3 | −7.6 | −14.9 | −17.4 | 2.7 | −1.3 | −6.0 | −7.9 | −14.3 |
538 | 11.8 | 9.2 | 0.5 | −7.6 | −10.4 | 11.3 | 7.2 | 2.1 | 0.1 | −7.0 |
670 | 22.0 | 17.7 | 8.6 | 0.2 | −2.9 | 20.9 | 15.6 | 10.2 | 8.4 | 0.9 |
936 | 40.0 | 34.8 | 23.1 | 12.8 | 8.6 | 37.3 | 29.5 | 23.0 | 21.4 | 13.0 |
Comilla | Habiganj | |||||||||
380 | 0.0 | −3.6 | −8.5 | −12.3 | −16.4 | 0.0 | −5.2 | −11.7 | −18.1 | −19.5 |
421 | 2.8 | −0.9 | −6.0 | −9.8 | −14.2 | 2.8 | −2.3 | −9.1 | −15.7 | −17.1 |
538 | 11.3 | 7.5 | 2.3 | −1.8 | −6.7 | 12.5 | 6.9 | −0.2 | −8.0 | −9.7 |
670 | 20.4 | 16.2 | 10.4 | 6.5 | 1.1 | 22.8 | 17.1 | 8.3 | 0.5 | −1.7 |
936 | 36.7 | 32.5 | 24.3 | 18.6 | 12.8 | 41.1 | 33.4 | 23.7 | 15.0 | 12.1 |
CO2 level (ppm) | Temperature increase level | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Gazipur | Rangpur | |||||||||
0 | +1 | +2 | +3 | +4 | 0 | +1 | +2 | +3 | +4 | |
380 | 0.0 | −5.0 | −6.3 | −10.3 | −15.4 | 0.0 | −0.2 | −3.0 | −9.8 | −14.6 |
421 | 2.7 | −2.4 | −3.8 | −8.2 | −13.5 | 2.7 | 2.5 | −0.4 | −7.4 | −12.3 |
538 | 11.0 | 5.5 | 4.1 | −0.8 | −6.9 | 11.0 | 10.9 | 7.7 | 0.1 | −5.2 |
670 | 19.5 | 13.6 | 12.1 | 6.9 | 0.3 | 19.6 | 19.5 | 16.0 | 7.8 | 2.1 |
936 | 32.9 | 26.1 | 24.5 | 18.7 | 11.5 | 32.9 | 33.0 | 28.8 | 19.7 | 13.5 |
Rajshahi | Barisal | |||||||||
380 | 0.0 | −4.0 | −7.4 | −12.5 | −14.7 | 0.0 | −0.7 | −7.8 | −9.0 | −12.2 |
421 | 2.7 | −1.4 | −5.0 | −10.3 | −12.8 | 2.5 | 1.9 | −5.7 | −6.9 | −10.4 |
538 | 11.1 | 6.6 | 2.5 | −3.2 | −5.6 | 10.7 | 10.2 | 1.6 | 0.1 | −4.0 |
670 | 19.6 | 14.8 | 10.3 | 4.3 | 1.9 | 19.1 | 18.7 | 9.4 | 7.9 | 3.4 |
936 | 33.0 | 27.5 | 22.6 | 15.9 | 13.1 | 32.3 | 31.8 | 21.4 | 19.8 | 14.8 |
Comilla | Habiganj | |||||||||
380 | 0.0 | −2.7 | −7.3 | −10.4 | −15.4 | 0.0 | −6.5 | −9.2 | −9.9 | −15.4 |
421 | 2.6 | −0.2 | −4.9 | −8.2 | −13.4 | 2.7 | −4.0 | −6.8 | −7.5 | −13.0 |
538 | 10.9 | 7.9 | 2.8 | −0.8 | −6.6 | 11.1 | 3.9 | 0.9 | 0.3 | −5.4 |
670 | 19.4 | 16.2 | 10.7 | 6.9 | 0.7 | 19.7 | 11.9 | 8.7 | 8.1 | 2.3 |
936 | 32.5 | 29.0 | 22.9 | 18.6 | 11.9 | 33.6 | 24.5 | 20.8 | 20.6 | 13.8 |
CO2 level (ppm) | Temperature increase level | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Gazipur | Rangpur | |||||||||
0 | +1 | +2 | +3 | +4 | 0 | +1 | +2 | +3 | +4 | |
380 | 0.0 | −5.7 | −12.0 | −15.1 | −19.7 | 0.0 | −5.0 | −11.5 | −17.5 | −22.3 |
421 | 2.7 | −3.0 | −9.7 | −12.8 | −17.7 | 2.7 | −2.5 | −9.0 | −15.2 | −20.2 |
538 | 11.2 | 5.1 | −2.0 | −5.2 | −11.1 | 11.3 | 5.6 | −1.3 | −7.9 | −13.8 |
670 | 19.9 | 13.7 | 5.7 | 2.5 | −3.8 | 21.0 | 14.7 | 6.5 | −0.4 | −6.9 |
936 | 34.5 | 27.3 | 18.1 | 14.2 | 7.2 | 37.3 | 29.9 | 20.4 | 11.8 | 3.7 |
Rajshahi | Barisal | |||||||||
380 | 0.0 | −4.2 | −14.0 | −16.8 | −20.7 | 0.0 | −4.5 | −6.3 | −13.1 | −14.8 |
421 | 2.7 | −1.6 | −11.6 | −14.4 | −18.6 | 2.7 | −1.9 | −3.7 | −10.8 | −12.8 |
538 | 11.1 | 6.8 | −4.1 | −7.0 | −11.6 | 11.2 | 6.2 | 4.3 | −3.0 | −5.5 |
670 | 19.9 | 15.3 | 3.8 | 0.4 | −4.3 | 19.8 | 14.4 | 12.5 | 4.9 | 2.3 |
936 | 36.6 | 29.3 | 15.9 | 12.6 | 6.5 | 34.3 | 27.0 | 25.3 | 16.9 | 14.1 |
Comilla | Habiganj | |||||||||
380 | 0.0 | −4.4 | −8.8 | −16.8 | −20.1 | 0.0 | −5.2 | −11.7 | −18.1 | −19.5 |
421 | 1.3 | −1.7 | −6.2 | −14.5 | −18.1 | 2.8 | −2.3 | −9.1 | −15.7 | −17.1 |
538 | 9.7 | 6.6 | 1.9 | −7.1 | −11.3 | 12.5 | 6.9 | −0.2 | −8.0 | −9.7 |
670 | 18.2 | 14.9 | 10.0 | 0.4 | −4.1 | 22.8 | 17.1 | 8.3 | 0.5 | −1.7 |
936 | 33.1 | 28.9 | 22.9 | 12.0 | 7.0 | 41.1 | 33.4 | 23.7 | 15.0 | 12.1 |
This study was conducted to determine the effect of increased daily maximum and minimum temperatures and elevated CO2 levels using CERES-Rice model on grain yield and growth duration of dry season rice (Boro) at six representative locations across Bangladesh. Long-term normalized weather data were used to predict grain yields of those varieties under variable increased temperature and CO2 levels. Temperature increase rate considered was 0, +1˚C, +2˚C, +3˚C and +4˚C with the elevated CO2 concentrations of 380, 421, 538, 670 and 936 ppm based on different RCPs. Rice grain yield was reduced by 256 - 403 kg・ha−1 for BRRI dhan28, 172 - 370 kg・ha−1 for BRRI dhan29 and 268 - 432 kg・ha−1 for BRRI dhan58 per 1˚C temperature rise. On the contrary, CO2 concentration compensated yield by 225 - 275 kg・ha−1 for BRRI dhan28, 230 - 267 kg・ha−1 for BRRI dhan29 and 198 - 275 kg・ha−1 for BRRI dhan58 per 50 ppm CO2 rise. In general, grain yield reduction and compensation rate were lower in warmer region and higher in cooler region. Growth duration was reduced by about 9 days irrespective of locations and varieties with an exception for BRRI dhan58, which has comparatively less growth duration reduction per degree temperature rise. In the projected climate change scenarios, maximum temperature at flowering stage of rice might cross the critical limit and thus reduction in rice yield is expected. To avoid this situation, shifting of sowing window for Boro rice and to develop cold and heat tolerant rice varieties would be the options for sustaining food security in Bangladesh and similar environments in other parts of the world.
The authors acknowledge the Modeling Climate Change on Agriculture Project (CRP-II, KGF) for funding this study. This finding is the outcome of the collaborative research of BRRI, BARI and BSMRAU.
Maniruzzaman, M., Biswas, J.C., Hossain, M.B., Haque, M.M., Naher, U.A., Choudhury, A.K., Akhter, S., Ahmed, F., Sen, R., Ishtiaque, S., Rahman, M.M. and Kalra, N. (2018) Effect of Elevated Air Temperature and Carbon Dioxide Levels on Dry Season Irrigated Rice Productivity in Bangladesh. American Journal of Plant Sciences, 9, 1557-1576. https://doi.org/10.4236/ajps.2018.97114