scholarly journals THE IMPACT OF CLIMATIC FACTORS TOWARDS RICE PRODUCTION IN INDONESIA

Agro Ekonomi ◽  
2020 ◽  
Vol 31 (1) ◽  
Author(s):  
Aura Dhamira ◽  
Irham Irham
Keyword(s):  
Climate Change ◽  
Climatic Factors ◽  
Rice Production ◽  
Maximum Temperature ◽  
Function Form ◽  
Policy Makers ◽  
The Difference ◽  
The Impact ◽  
Analytical Frameworks ◽  
Adaptation And Mitigation

Rice production is greatly affected by climatic factors, while those factors keep changing along with time. Therefore, the effects of climate change toward rice production in Indonesia need to be studied. The objective of this study is to: (1) determine the difference of interregional climate in each region and (2) determine the impact of climatic factors on rice production in Indonesia. Just and Pope Production function was used as the analytical frameworks, and Cobb-Douglas function form was used to analyze the data. The analysis was conducted towards rice production in ten provinces in Indonesia from 1985 to 2017. The result shows that there are some differences in climatic condition in each region in Indonesia. The regression analysis shows that maximum temperature and minimum temperature have positive impacts on rice production, meanwhile, El Nino and La Nina impact negatively. The results of this study can be considered by the policy makers in making decisions related to adaptation and mitigation to encounter climate change.

Aridity Changes and Related Climatic Drivers in the Drylands of China during 1960–2019

2021 ◽  
Vol 60 (4) ◽  
pp. 607-617
Author(s):  
Jinqin Xu ◽  
Yan Zeng ◽  
Xinfa Qiu ◽  
Yongjian He ◽  
Guoping Shi ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Land Surface ◽  
Arid Regions ◽  
Climatic Factors ◽  
Sunshine Duration ◽  
Aridity Index ◽  
Maximum Temperature ◽  
The Impact ◽  
Precipitation And Temperature

AbstractDrylands cover about one-half of the land surface in China and are highly sensitive to climate change. Understanding climate change and its impact drivers on dryland is essential for supporting dryland planning and sustainable development. Using meteorological observations for 1960–2019, the aridity changes in drylands of China were evaluated using aridity index (AI), and the impact of various climatic factors [i.e., precipitation P; sunshine duration (SSD); relative humidity (RH); maximum temperature (Tmax); minimum temperature (Tmin); wind speed (WS)] on the aridity changes was decomposed and quantified. Results of trend analysis based on Sen’s slope estimator and Mann–Kendall test indicated that the aridity trends were very weak when averaged over the whole drylands in China during 1960–2019 but exhibited a significant wetting trend in hyperarid and arid regions of drylands. The AI was most sensitive to changes in water factors (i.e., P and RH), followed by SSD, Tmax, and WS, but the sensitivity of AI to Tmin was very small and negligible. Interestingly, the dominant climatic driver to AI change varied in the four dryland subtypes. The significantly increased P dominated the increase in AI in the hyperarid and arid regions. The significantly reduced WS and the significantly increased Tmax contributed more to AI changes than the P in the semiarid and dry subhumid regions of drylands. Previous studies emphasized the impact of precipitation and temperature on the global or regional dry–wet changes; however, the findings of this study suggest that, beyond precipitation and temperature, the impact of wind speed on aridity changes of drylands in China should be given equal attention.

scholarly journals Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 172
Author(s):  
Yuan Xu ◽  
Jieming Chou ◽  
Fan Yang ◽  
Mingyang Sun ◽  
Weixing Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Food Production ◽  
Crop Yields ◽  
Climatic Factors ◽  
Climatic Data ◽  
The South ◽  
The North ◽  
Output Elasticity ◽  
The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

scholarly journals The impact of climate change in wheat and barley yields in the Iberian Peninsula

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Virgílio A. Bento ◽  
Andreia F. S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Rita M. Cardoso ◽  
...  
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Model ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Historical Period ◽  
Early Winter ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Spring Maximum

AbstractThe impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

Simulating the impact of climate change on rice production in Asia and evaluating options for adaptation

1997 ◽  
Vol 54 (3) ◽  
pp. 399-425 ◽  
Author(s):  
R.B. Matthews ◽  
M.J. Kropff ◽  
T. Horie ◽  
D. Bachelet
Keyword(s):  
Climate Change ◽  
Rice Production ◽  
Impact Of Climate Change ◽  
The Impact

scholarly journals Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Negative Impact ◽  
Positive Impact ◽  
Information Criterion ◽  
Growing Season ◽  
Maximum Temperature ◽  
Linear Regression Models ◽  
The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

scholarly journals Impact of Climate Change on Water Availability and Food Security of Nepal

2012 ◽  
pp. 59-63
Author(s):  
Roshan Kumar Mehta ◽  
Shree Chandra Shah
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climatic Factors ◽  
Monsoon Season ◽  
Groundwater Table ◽  
Maximum Temperature ◽  
Aquatic Life ◽  
Temperature And Precipitation ◽  
Average Maximum ◽  
Water Scarce

The increase in the concentration of greenhouse gases (GHGs) in the atmosphere is widely believed to be causing climate change. It affects agriculture, forestry, human health, biodiversity, and snow cover and aquatic life. Changes in climatic factors like temperature, solar radiation and precipitation have potential to influence agrobiodiversity and its production. An average of 0.04°C/ year and 0.82 mm/year rise in annual average maximum temperature and precipitation respectively from 1975 to 2006 has been recorded in Nepal. Frequent droughts, rise in temperature, shortening of the monsoon season with high intensity rainfall, severe floods, landslides and mixed effects on agricultural biodiversity have been experienced in Nepal due to climatic changes. A survey done in the Chitwan District reveals that lowering of the groundwater table decreases production and that farmers are attracted to grow less water consuming crops during water scarce season. The groundwater table in the study area has lowered nearly one meter from that of 15 years ago as experienced by the farmers. Traditional varieties of rice have been replaced in the last 10 years by modern varieties, and by agricultural crops which demand more water for cultivation. The application of groundwater for irrigation has increased the cost of production and caused severe negative impacts on marginal crop production and agro-biodiversity. It is timely that suitable adaptive measures are identified in order to make Nepalese agriculture more resistant to the adverse impacts of climate change, especially those caused by erratic weather patterns such as the ones experienced recently.DOI: http://dx.doi.org/10.3126/hn.v11i1.7206 Hydro Nepal Special Issue: Conference Proceedings 2012 pp.59-63

scholarly journals Spatial-temporal changes in river runoff and terrestrial ecosystem water retention under 1.5 °C and 2 °C warming scenarios across China

2017 ◽  
Author(s):  
Ran Zhai ◽  
Fulu Tao ◽  
Zhihui Xu
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
River Runoff ◽  
Water Retention ◽  
Terrestrial Ecosystem ◽  
Maximum Temperature ◽  
Climate Scenarios ◽  
Warming Scenario ◽  
Basin Scale ◽  
The Impact

Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ℃ above pre-industrial levels, and pursuing efforts to limit this to 1.5 ℃, it is therefore important to understand the impacts of climate change under 1.5 ℃ and 2.0 ℃ warming scenarios for climate adaptation and mitigation. Here, climate scenarios by four Global Circulation Models (GCMs) for the baseline (2006–2015), 1.5 ℃ and 2.0 ℃ warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on river runoff and Terrestrial Ecosystem Water Retention (TEWR) in China. The trends in annual mean temperature, precipitation, river runoff and TEWR were analysed at the grid and basin scale. Results showed that there were large uncertainties in climate scenarios from the different GCMs, which led to large uncertainties in the impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. The interannual variability of river runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from 1.5 ℃ warming scenario to 2.0 ℃ warming scenario. By contrast, TEWR would remain relatively stable. Both extreme low and high river runoff would increase under the two warming scenarios in most areas in China, with high river runoff increasing more. And the risk of extreme river runoff events would be higher under 2.0 ℃ warming scenario than under 1.5 ℃ warming scenario in term of both extent and intensity. River runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause river runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our findings highlight climate change mitigation and adaptation should be taken to reduce the risks of hydrological extreme events.

The impact of drought on tree growth in Mediterranean sites

2021 ◽  
Author(s):  
Giovanna Battipaglia ◽  
Francesco Niccoli ◽  
Arturo Pacheco-Solana
Keyword(s):  
Climate Change ◽  
Tree Growth ◽  
Sustainable Forest Management ◽  
Climatic Factors ◽  
Management Strategies ◽  
Ring Width ◽  
Limiting Factor ◽  
Individual Tree ◽  
Annual Growth Rings ◽  
The Impact

<p>Climate-induced forest mortality is a critical issue in the Mediterranean basin, with major consequences for the functioning of these key ecosystems. Indeed, in Mediterranean ecosystems, where water stress is already the most limiting factor for tree performance, climatic changes are expected to entail an increase in water deficit. In this context, annual growth rings can provide short- (e.g., years) and long-term (e.g., decades) information on how trees respond to drought events. With climate change, <em>Pinus pinaster</em> and <em>Pinus pinea</em> L. are expected to reduce their distribution range in the region, being displaced at low altitudes by more drought tolerant taxa such as sub Mediterranean <em>Quercus</em> spp.</p><p>This study aims was to assess the physiological response of <em>Pinus</em> and <em>Quercus</em> species growing in the Vesuvio National park, located in Southern Italy and where an increase of temperature and drought events has been recorded in the recent years. Our preliminary results underlined the importance of temperature on the tree ring width of all the analyses species. The high temperatures can cause a change in the constant kinetics of the RuBisCo, leading to a consequent decrease in carboxylation rate and thus to a reduction in tree growth. On the other hand, also precipitation seemed to affect the growth of the sampled trees: indeed, in all the chronologies a reduction in growth was found after particular dry years: for example, the low rainfall in 1999 (455 mm/year) determined a drastic decline in growth in 2000 in all the species. In addition to the climatic factors, competition can also play an important role in the growth rate: dendrochronological analyzes have highlighted how stand specific properties (i.e. density, structure and composition) can influence individual tree responses to drought events. The knowledge of those researches should be integrated into sustainable forest management strategies to minimize the potential impacts of climate change on forest ecosystems.</p>

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