scholarly journals Factor Influencing Adaptation Choices Employed by Farmers Against Climate Change to Improve Rice Yield in Bugarama Wetland in Rwanda

2020 ◽  
Vol 2 (1) ◽  
pp. 12-22
Author(s):  
Esther Nyirandorimana ◽  
Ezekiel Ndunda ◽  
John Muriuki
Keyword(s):  
Climate Change ◽  
Rice Yield ◽  
New Technology ◽  
Climatic Conditions ◽  
Descriptive Research ◽  
Changing Climate ◽  
Step Model ◽  
Rice Yields ◽  
Market Distance ◽  
Adaptation Method

The changing climate poses a great challenge to many wetlands productivity worldwide. Rice production in wetlands is a major source of livelihood in developing countries such as Rwanda. This study aimed at determining the factors influencing adaptation methods when farmers perceive the changing climate at Bugarama Wetland Rice Scheme in Rwanda. A descriptive research design was used by this study, whereby quantitative and qualitative data was collected. The analysis was based on data collected from 300 selected farmers using systematic random sampling method. We employed descriptive statistics to assess how farmers perceive the effects of climate change and descriptively measured the new adaptation methods used by farmers in Bugarama to increase their yields. The study adopted Heckman two-step model to determine factors that influence adaptation choices, this analysis procedurally required farmers’ knowledge of perception that makes them respond to the effects of changes in climatic conditions by the use of new adaptation methods. The results deduced that level of education (p =0.019), extension access (p=0.001), market distance (p=0.002) and rice income (p < 0.001) had a probability of influencing farmers perceptions about climate change thus need to adapt. Based on the outcome model, results showed that extension access (p < 0.001), household size (p= 0.098), market distance (p= 0.047), rice income (p =0.032), farmers-to-farmers contact (p < 0.001) and effects of climate change on rice (p=0.038) had a greater probability of influencing farmers choice of adaptation method used to improve rice yields. To conclude, the study found that access to informational facilities and rice income, influenced farmers’ perceptions while extension access, rice income, market distance, farmers-to-farmers contact and effects of climate change on rice yield strongly had a probability of determining farmers’ choice of adaptation. This study recommends that the Rwandan government and local administrators need to develop a strategy that would allow farmers to access information facilities about new technology so as to adapt to the effects of climate change thus improve their rice yields.

scholarly journals Evaluating the Tourist Climate Comfortable Period of China in a Changing Climate

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Dan-Dan Yu ◽  
Shan Li ◽  
Zhong-Yang Guo
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Scientific Evidence ◽  
Climatic Conditions ◽  
Climate Index ◽  
Climate Indices ◽  
Climate Data ◽  
Climate Conditions ◽  
Positive Effects ◽  
Changing Climate

The evaluation of climate comfort for tourism can provide information for tourists selecting destinations and tourism operators. Understanding how climate conditions for tourism evolve is increasingly important for strategic tourism planning, particularly in rapidly developing tourism markets like China in a changing climate. Multidimensional climate indices are needed to evaluate climate for tourism, and previous studies in China have used the much criticized “climate index” with low resolution climate data. This study uses the Holiday Climate Index (HCI) and daily data from 775 weather stations to examine interregional differences in the tourist climate comfortable period (TCCP) across China and summarizes the spatiotemporal evolution of TCCP from 1981 to 2010 in a changing climate. Overall, most areas in China have an “excellent” climate for tourism, such that tourists may visit anytime with many choices available. The TCCP in most regions shows an increasing trend, and China benefits more from positive effects of climate change in climatic conditions for tourism, especially in spring and autumn. These results can provide some scientific evidence for understanding human settlement environmental constructions and further contribute in improving local or regional resilience responding to global climate change.

CERES-Rice model-based simulations of climate change impacts on rice yields and efficacy of adaptive options in Northeast China

2014 ◽  
Vol 65 (12) ◽  
pp. 1267 ◽  
Author(s):  
Wenxiang Wu ◽  
Qian Fang ◽  
Quansheng Ge ◽  
Mengzi Zhou ◽  
Yumei Lin
Keyword(s):  
Climate Change ◽  
Northeast China ◽  
Rice Yield ◽  
Adaptive Strategies ◽  
Future Climate ◽  
Future Climate Change ◽  
Rice Cultivars ◽  
Rice Yields ◽  
The Impact ◽  
Impacts Of Climate Change

Global temperatures are rising, and concerns about the response of agricultural production to climate change are increasing. Adaptation is a key factor that will shape the severity of impacts of future climate change on food production. Based on actual meteorological, soil and agricultural management data at site scale, the CERES-Rice model, combined with the Regional Climate Model (RCM)-PRECIS, was used to simulate both the effects of climate change on rice yields and the efficacy of adaptive options in Northeast China. The impact simulation showed that rice yield changes ranged from +0.1% to –44.9% (A2 scenario) and from –0.3% to –40.1% (B2 scenario) without considering CO2 fertilisation effects. When considering CO2 fertilisation effects, rice yield reductions induced by temperature increases were decreased at all sites. The CO2 fertilisation effects may partly offset the negative impacts of climate change on rice yields. Adaptive option results revealed that the adverse impacts of climate change on rice yields could be mitigated by advancing the planting dates, transplanting mid–late-maturing rice cultivars to replace early-maturing ones, and breeding new rice cultivars with high thermal requirements. Our findings provide insight into the possible impacts of climate change on rice production, and we suggest which adaptive strategies could be used to cope with future climate change, thus providing evidence-based suggestions for government policy on adaptive strategies.

scholarly journals Integrating Statistical and System Dynamics Modelling to Analyse the Impacts of Climate Change on Rice Production in West Nusa Tenggara, Indonesia

2021 ◽  
Author(s):  
◽  
Muhamad Bahri
Keyword(s):  
Climate Change ◽  
System Dynamics ◽  
Statistical Models ◽  
Rice Yield ◽  
Rice Production ◽  
Maximum Temperature ◽  
Dynamics Model ◽  
Rice Varieties ◽  
Changing Climate ◽  
Impacts Of Climate Change

<p>Climate change, manifested as temperature rise and rainfall change, will pose significant challenges to rice farmers, leading to a possible rice shortage under a changing climate. This research aims to understand the impacts of climate variability and change on rice production through the rest of this century using Representative Concentration Pathway (RCP) scenarios, and combination of statistical and system dynamic modelling. The area of study is West Nusa Tenggara, Indonesia. Wetland and dryland farming types are assessed separately because they have different rice varieties and different agricultural practices.  Overall, the research seeks to answer the question: How will climate change and climate variability affect rice production? Additional questions investigated are (1) What are the most significant supply uncertainties associated with a changing climate? and (2) What are possible solutions for reducing the impacts of climate change on rice production?. To answer these research questions, this study deals with three main research areas. First, based on observed data (1976-2011), this study developed regression-based statistical models in understanding the impacts of climate change on rice yield in West Nusa Tenggara. Statistical models find that the negative impacts of increased minimum temperature on rice yield are statistically significant.   By contrast, the effects of maximum temperature on rice yield are not statistically significant. A key reason for this is that the highest maximum temperature (32⁰C) in the observed period (1976-2011) was lower than 35⁰C, a rice threshold for maximum temperature. By 2090 (2077-2100), rice yield in wetland and dryland is projected to decrease by about 3% (RCP2.6 scenario), 4% (RCP4.5 scenario), 5% (RCP6.0 scenario) and 14% (RCP8.5 scenario).  Second, a system dynamics model was developed to assess the impacts of climate change on three issues including rice yield, harvested areas and rice production by 2090 (2077-2100). After embedding statistical models and estimating the impacts of maximum temperature on rice yield based on existing studies, the impacts of climate change on rice yield are projected. The system dynamics model is also equipped by August SOI to estimate the impacts of climate change on the timing of monsoon onset i.e the beginning of planting seasons. For assessing harvested areas under a changing climate, the system dynamics model is equipped by a mathematical relationship between seasonal rainfall and harvested areas.  Because the system dynamics model includes the impacts of high maximum temperature, the projected loss of rice yield in wetland and dryland is relatively higher compared to that in statistical models. It is projected that rice yield loss will be about 3% (RCP2.6 scenario), 6% (RCP4.5 scenario), 10% (RCP6.0 scenario) and 23% (RCP8.5 scenario) by 2090 (2077-2100). Likewise, rice production loss in wetland and dryland is projected to be about 1% (RCP2.6 scenario), 2% (RCP4.5 scenario), 7% (RCP6.0 scenario) and 19% (RCP8.5 scenario) by 2090 (2077-2100). The projected loss of rice production is relatively lower than rice yield loss as wetland harvested areas are projected to experience a slight increase about 3% by 2090 (2077-2100) under a changing climate. This also means that the ranking of the impacts of climate change from the most significant to the least significant is its impact on rice yield, rice production and harvested areas.   Third, policy options in overcoming the impacts of climate change on rice production are assessed. This study suggests that research on finding rice varieties with three main traits: heat tolerance, short growth duration and high yield is key to balance rice demand and rice supply in West Nusa Tenggara by 2090 (2077-2100). A failure to improve rice yield in such ways is likely to lead to significant reductions in rice supply in the face of climate change.  This study makes theoretical contributions, including the development of statistical models for understanding the impacts of climate change on rice yield and a causal system for investigating the impacts of climate change on rice yield, rice production and harvested areas. Again, the combination of statistical and system dynamics modelling simultaneously investigates the impacts of climate change on rice yield, rice production and harvested areas. This means that this study provides a more holistic view of the impacts of climate change compared to existing studies.  This study also offers practical contributions, advising that declining rice research should be avoided under a changing climate, and suggesting that farming intensification (more climate-resilient rice varieties) is more effective than farming extension (area expansion) in sustaining rice production under a changing climate. Again, research on developing more resilient-climate rice varieties is possible as projected rice yield in sustaining rice production by 2090 (2077-2100) is similar to rice’s yield potential.</p>

scholarly journals The future of pastoral farming in a changing climate

2009 ◽  
pp. 69-72 ◽  
Author(s):  
J.A. Palmer
Keyword(s):  
Climate Change ◽  
Public Policy ◽  
New Zealand ◽  
Climatic Conditions ◽  
Anthropogenic Climate Change ◽  
Regulatory Environment ◽  
Market Forces ◽  
Changing Climate ◽  
History Of ◽  
Pastoral Farming

Pastoral farming in New Zealand has always been a dynamic and uncertain business. Climatic conditions, market forces and the regulatory environment confronting pastoral farmers each have a long history of change, often rapidly and markedly. It is not surprising then that pastoral farmers are a resilient bunch. It is also not surprising that in respect of anthropogenic climate change some farmers are sceptical of what they see as another passing fashion in science, public policy and environmentalism - change to be weathered.

scholarly journals Climate change perception and adaptation among indigenous farmers : A study on Thamis of Dolkha

2019 ◽  
Vol 29 (2) ◽  
pp. 42-48
Author(s):  
B. J. Thapa
Keyword(s):  
Climate Change ◽  
Indigenous Communities ◽  
Close Relation ◽  
Climatic Conditions ◽  
Extreme Weather Events ◽  
Common Finding ◽  
Changing Climate ◽  
Change Perception ◽  
Weather Events ◽  
Adaptation Practices

Anthropogenic climate change is perceived as one of the most threatening global environmental issues today. A common finding in the past researches is that most of the vulnerable communities affected by the changing climate are the indigenous ones living in rural parts of the world, mostly from the developing nations. These indigenous communities have a close relation with their surrounding environments which have provided them a vast knowledge and clues about the micro-climatic conditions in their surroundings. These clues shape their perceptions and adaptation practices. This research was conducted on the indigenous Thami Community of Nepal focusing on their perceptions towards changing climate and their adaptation practices in congruence with their local and indigenous knowledge about their environment. As Thamis are mostly reliant on subsistence agricultural farming for their livelihood, this study mainly focuses on the impacts of climate change on agriculture practices of Thami Community of Dolakha district. In this study it was found that the practices of Thamis were severely affected by the changing environmental conditions. The farmers perceived changes in temperatures, precipitation and extreme weather events, and interpreted those as per their understanding of their surroundings

scholarly journals Mapping Chinese Rice Suitability to Climate Change

2016 ◽  
Vol 8 (6) ◽  
pp. 33 ◽  
Author(s):  
Tianyi Zhang ◽  
Xiaoguang Yang
Keyword(s):  
Climate Change ◽  
Rice Yield ◽  
Significant Proportion ◽  
Climatic Conditions ◽  
Rice Production ◽  
Yield Stability ◽  
Agricultural Technology ◽  
High Yield ◽  
Yield Gap ◽  
Northeastern Region

<p>Climate change has the potential to affect Chinese rice production; however, the rice crop could become more suitable to new climatic conditions because of benefits derived from new agricultural technologies. In this paper, a county-level dataset and crop model were used to analyze actual rice yield suitability by measuring the yield gap and yield stability from 1980 to 2011 in 1561 counties of China. The results showed that the national yield gap between the actual and potential yields was approximately 23.0%, which is close to the threshold for profitable planting. However, a number of counties in the northeastern and southwestern regions showed a 30 to 50% yield gap, which indicates a relatively lower suitability of the rice. The rice yield stability results indicated that the actual stability has exceeded the potential stability in most of the counties of China, thus indicating a high level of suitability. Temporally, a decreasing trend was observed for both the yield gap and stability, suggesting that the suitability of rice in China has improved, which might be associated with the development of agricultural technology. The only noteworthy locations presenting a high yield gap and yield instability were several counties in the northeastern region. Since the northeastern region accounts for a significant proportion of China's rice production, further investigations should be conducted to identify the underlying causes of the yield gaps and determine methods of increasing the yield stability. The implementation of more suitable agricultural technology in the area is also suggested to improve the rice suitability in the region.</p>

Enhancing urban infrastructure investment planning practices for a changing climate

2006 ◽  
Vol 53 (10) ◽  
pp. 13-20 ◽  
Author(s):  
J. He ◽  
C. Valeo ◽  
F.J.-C. Bouchart
Keyword(s):  
Climate Change ◽  
Urban Infrastructure ◽  
Climatic Conditions ◽  
Storm Water ◽  
Infrastructure Investment ◽  
Urban Water ◽  
Water Infrastructure ◽  
Water Drainage ◽  
Investment Planning ◽  
Changing Climate

Climate change raises many concerns for urban water management because of the effects on all aspects of the hydrological cycle. Urban water infrastructure has traditionally been designed using historical observations and assuming stationary climatic conditions. The capability of this infrastructure, whether for storm-water drainage, or water supply, may be over- or under-designed for future climatic conditions. In particular, changes in the frequency and intensity of extreme rainfall events will have the most acute effect on storm-water drainage systems. Therefore, it is necessary to take future climatic conditions into consideration in engineering designs in order to enhance water infrastructure investment planning practices in a long time horizon. This paper provides the initial results of a study that is examining ways to enhance urban infrastructure investment planning practices against changes in hydrologic regimes for a changing climate. Design storms and intensity–duration–frequency curves that are used in the engineering design of storm-water drainage systems are developed under future climatic conditions by empirically adjusting the general circulation model output, and using the Gumbel distribution and the Chicago method. Simulations are then performed on an existing storm-water drainage system from NE Calgary to investigate the resiliency of the system under climate change.

Artificial neural networks for rice yield prediction in mountainous regions

2007 ◽  
Vol 145 (3) ◽  
pp. 249-261 ◽  
Author(s):  
B. JI ◽  
Y. SUN ◽  
S. YANG ◽  
J. WAN
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Rice Yield ◽  
Climatic Conditions ◽  
Linear Regression Models ◽  
Learning Rates ◽  
Rice Yields ◽  
Ann Models ◽  
Multiple Linear Regression Models ◽  
Hidden Nodes

Decision-making processes in agriculture often require reliable crop response models. The Fujian province of China is a mountainous region where weather aberrations such as typhoons, floods and droughts threaten rice production. Agricultural management specialists need simple and accurate estimation techniques to predict rice yields in the planning process. The objectives of the present study were to: (1) investigate whether artificial neural network (ANN) models could effectively predict Fujian rice yield for typical climatic conditions of the mountainous region, (2) evaluate ANN model performance relative to variations of developmental parameters and (3) compare the effectiveness of multiple linear regression models with ANN models. Models were developed using historical yield data at multiple locations throughout Fujian. Field-specific rainfall data and the weather variables (daily sunshine hours, daily solar radiation, daily temperature sum and daily wind speed) were used for each location. Adjusting ANN parameters such as learning rate and number of hidden nodes affected the accuracy of rice yield predictions. Optimal learning rates were between 0·71 and 0·90. Smaller data sets required fewer hidden nodes and lower learning rates in model optimization. ANN models consistently produced more accurate yield predictions than regression models. ANN rice grain yield models for Fujian resulted in R2 and RMSE of 0·87 and 891 vs 0·52 and 1977 for linear regression, respectively. Although more time consuming to develop than multiple linear regression models, ANN models proved to be superior for accurately predicting rice yields under typical Fujian climatic conditions.

scholarly journals Predicting invasion potential of Senna didymobotrya (Fresen.) Irwin & Barneby under the changing climate in Africa

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Elias Ch. Weldemariam ◽  
Sintayehu W. Dejene
Keyword(s):  
Climate Change ◽  
Species Distribution Model ◽  
Characteristic Curve ◽  
Climatic Conditions ◽  
Eastern Africa ◽  
Distribution Model ◽  
Climate Conditions ◽  
Changing Climate ◽  
Bioclimatic Variables ◽  
Suitable Area

Abstract Background Senna didymobotrya is a native African flowering shrub. It is suspected that climate change encourages the introduction and spread of invasive alien species. The possible invasion of S. didymobotrya across the continent is expected to increase in the future due to ongoing climate change. Nonetheless, there is still paucity of empirical evidence on the extent to which the changing climate contributes to the surge of the flowering shrub. This study, therefore, investigated the present and potential invasion of S. didymobotrya using the species distribution model under changing climate conditions. The two representative concentration pathways (RCP4.5 and RCP8.5) and eight bioclimatic variables and one topographic variable were used to simulate the current and future (2050s and 2070s) invasion of S. didymobotrya in Africa. The model performance was assessed using the area under the receiver operating characteristic curve (AUC) and true skill statistics (TSS). Results The results of the study showed that under the current climatic conditions, 18% of Africa is suitable for the establishment and invasion of S. didymobotrya. The most suitable hotspot for S. didymobotrya invasion is eastern Africa, followed by southern Africa. The predicted model showed that by 2050, 3.3% and 3.12% of the continent would be highly suitable areas for the invasion of the species under RCP4.5 and RCP8.5, respectively. In the 2070s, under RCP4.5 and RCP8.5, the highly suitable area would be 3.13% and 2.7%, respectively. In relation to the current suitability, the cumulative projected areas of the low and moderate suitability class under RCP4.5 and RCP8.5 will rise by the years 2050 and 2070. However, under both RCPs, the non-suitable area for S. didymobotrya invasion would gradually decrease. Conclusions From the findings, it can be concluded that the ecosystem’s vulnerability to S. didymobotrya invasion under future climatic conditions will proliferate significantly. Hence, to prevent the projected harm to biodiversity and ecosystem services, governments need to focus their future biodiversity management and policy directions on the means and strategies of minimizing the invasion and the distribution rate of S. didymobotrya across habitat types.

scholarly journals Modeling Climate Change Effects on Rice Yield and Soil Carbon Under Variable Water and Nutrient Management

2021 ◽  
Vol 13 (2) ◽  
pp. 568
Author(s):  
Zewei Jiang ◽  
Shihong Yang ◽  
Jie Ding ◽  
Xiao Sun ◽  
Xi Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Bayesian Model Averaging ◽  
Rice Yield ◽  
Paddy Fields ◽  
Dndc Model ◽  
Carbon Management ◽  
Rice Yields ◽  
Rcp 8.5 ◽  
The Impact

Soil organic carbon (SOC) conservation in agricultural soils is vital for sustainable agricultural production and climate change mitigation. To project changes of SOC and rice yield under different water and carbon management in future climates, based on a two-year (2015 and 2016) field test in Kunshan, China, the Denitrification Decomposition (DNDC) model was modified and validated and the soil moisture module of DNDC was improved to realize the simulation under conditions of water-saving irrigation. Four climate models under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5), which were integrated from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), were ensembled by the Bayesian Model Averaging (BMA) method. The results showed that the modified DNDC model can effectively simulate changes in SOC, dissolved organic carbon (DOC), and rice yield under different irrigation and fertilizer management systems. The normalized root mean squared errors of the SOC and DOC were 3.45–17.59% and 8.79–13.93%, respectively. The model efficiency coefficients of SOC and DOC were close to 1. The climate scenarios had a great impact on rice yield, whereas the impact on SOC was less than that of agricultural management measures on SOC. The average rice yields of all the RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 scenarios in the 2090s decreased by 18.41%, 38.59%, 65.11%, and 65.62%, respectively, compared with those in the 2020s. The long-term effect of irrigation on the SOC content of paddy fields was minimal. The SOC of the paddy fields treated with conventional fertilizer decreased initially and then remained unchanged, while the other treatments increased obviously with time. The rice yields of all the treatments decreased with time. Compared with traditional management, controlled irrigation with straw returning clearly increased the SOC and rice yields of paddy fields. Thus, this water and carbon management system is recommended for paddy fields.

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