scholarly journals Effects of climate variability and insurance adoption on crop production in select provinces of South Africa

2018 ◽  
Vol 9 (3) ◽  
pp. 500-511 ◽  
Author(s):  
Zelda Anne Elum ◽  
Godwell Nhamo ◽  
Michael Akwasi Antwi
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Climate Variability ◽  
Crop Production ◽  
Climate Change Impacts ◽  
Probit Model ◽  
Weather Conditions ◽  
Study Data ◽  
Agricultural Insurance ◽  
Instrumental Variable Regression

AbstractIncreasing climate variability increases the risks in production and prices of agricultural products. Inarguably, Africa's susceptibility to climate change is high because it hosts the majority of the world's poor who cannot afford the costs of coping mechanisms. Agricultural insurance is being largely put forward as a coping measure of adapting to climate change to sustain farm production and farmers' livelihood. The study critically reviewed numerous publications on climate change impacts and the role of insurance in the adaptation process. It examined the effects of varying weather conditions and insurance on net crop revenue using the instrumental variable regression approach on a Ricardian model. The study further identified factors influencing the purchase of insurance among the farmers with a probit model. The study data were collected from a cross section of farmers in three selected provinces of South Africa. Results of data analysis indicated that owning insurance, number of labourers employed, size of irrigated farmland and rainfall have significant effects on net revenue. It was also revealed that experience, indicated by years of farming and revenue, influenced farmers' adoption of insurance. Consequently, the paper advocates for the provision of efficient irrigation facilities and promotion of insurance among farmers.

scholarly journals Climate Variability Since 1970 and Farmers’ Observations in Northern Ghana

2016 ◽  
Vol 5 (2) ◽  
pp. 41 ◽  
Author(s):  
Emmanuel Nyadzi
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Water Conservation ◽  
Crop Production ◽  
Meteorological Data ◽  
Northern Region ◽  
Northern Ghana ◽  
Climate Variability And Change ◽  
Urban Centers ◽  
Access To Credit

<p>The study examines how farmers’ observations of climate variability and change correspond with 42 years (1970-2011) meteorological data of temperature and rainfall. It shows how farmers in the Northern Region of Ghana adjust to the changing climate and explore the various obstacles that hinder the implementation of their adaptation strategies. With the help of an extension officer, 200 farmers from 20 communities were randomly selected based on their farming records. Temperatures over the last four decades (1970-2009) increased at a rate of 0.04 (± 0.41) ˚C and 0.3(± 0.13)˚C from 2010-2011 which is consistent to the farmers (82.5%) observations. Rainfall within the districts are characterised by inter-annual and monthly variability. It experienced an increased rate of 0.66 (± 8.30) mm from 1970-2009, which was inconsistent with the farmers (81.5%) observation. It however decreased from 2010-2011 at a huge rate of -22.49 (±15.90) mm which probably was the reason majority of the respondents claim rainfall was decreasing. Only 64.5% of the respondents had adjusted their farming activities because of climate variability and change. They apply fertilizers and pesticides, practice soil and water conservation, and irrigation for communities close to dams. Respondents desire to continue their current adaptation methods but may in the future consider changing crop variety, water-harvesting techniques, change crop production to livestock keeping, and possibly migrate to urban centers. Lack of climate change education, low access to credit and agricultural inputs are some militating factors crippling the farmers’ effort to adapt to climate change.</p>

scholarly journals Consequences of Climate Change Impacts and Incidences of Extreme Weather Events in Relation to Crop Production in Bhutan

2020 ◽  
Vol 12 (10) ◽  
pp. 4319 ◽  
Author(s):  
Ngawang Chhogyel ◽  
Lalit Kumar ◽  
Yadunath Bajgai
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climatic Factors ◽  
Climate Change Impacts ◽  
Extreme Weather ◽  
Crop Damage ◽  
Extreme Weather Events ◽  
Cropping Pattern ◽  
The People ◽  
Weather Events

Being a country in the Himalayas, Bhutan is highly prone to the vagaries of weather events that affect agricultural production and the subsequent livelihood of the people. To identify the main issues that affect crop production and the decisions of farmers, a survey was conducted in three different agro-ecosystems in Bhutan. Our key findings indicate that farming and the decisions of farmers were largely affected by different climatic and non-climatic factors. These were in descending order of importance: irrigation availability > farm labour > crop seasonality > crop damage (climatic) > land holding > crop damage (wildlife) > crop damage (diseases and pests). The most important consequences of climate change impacts were the drying of irrigation sources (4.35) and crop losses due to weather events (4.10), whereas land fallowing, the occurrence of flood and soil erosion, weed pressure and changes in cropping pattern (with mean ratings of 2.53–3.03) experienced lesser consequences. The extreme weather events, such as untimely rains, drought and windstorms, were rated as the ‘most common’ to ‘common’ occurrences, thus inflicting a crop loss of 1–19%. These confirm our hearsay knowledge that extreme weather events have major consequences on irrigation water, which is said to be either drying or getting smaller in comparison to the past. Therefore, Bhutan must step up its on-ground farmer-support system towards improving the country’s food production, whilst embracing climate smart farm technologies for adapting to the impacts of change.

scholarly journals Impact of Climate Change on Crops Adaptation and Strategies to Tackle Its Outcome: A Review

Plants ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 34 ◽  
Author(s):  
Ali Raza ◽  
Ali Razzaq ◽  
Sundas Mehmood ◽  
Xiling Zou ◽  
Xuekun Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Crop Production ◽  
Climate Changes ◽  
Heat Waves ◽  
Negative Impact ◽  
Global Climate ◽  
Climate Change Impacts ◽  
Annual Rainfall ◽  
Ozone Level

Agriculture and climate change are internally correlated with each other in various aspects, as climate change is the main cause of biotic and abiotic stresses, which have adverse effects on the agriculture of a region. The land and its agriculture are being affected by climate changes in different ways, e.g., variations in annual rainfall, average temperature, heat waves, modifications in weeds, pests or microbes, global change of atmospheric CO2 or ozone level, and fluctuations in sea level. The threat of varying global climate has greatly driven the attention of scientists, as these variations are imparting negative impact on global crop production and compromising food security worldwide. According to some predicted reports, agriculture is considered the most endangered activity adversely affected by climate changes. To date, food security and ecosystem resilience are the most concerning subjects worldwide. Climate-smart agriculture is the only way to lower the negative impact of climate variations on crop adaptation, before it might affect global crop production drastically. In this review paper, we summarize the causes of climate change, stresses produced due to climate change, impacts on crops, modern breeding technologies, and biotechnological strategies to cope with climate change, in order to develop climate resilient crops. Revolutions in genetic engineering techniques can also aid in overcoming food security issues against extreme environmental conditions, by producing transgenic plants.

Assessing climate change impacts on greenhouse gas emissions, N losses in drainage and crop production in a subsurface drained field

2020 ◽  
Vol 705 ◽  
pp. 135969 ◽  
Author(s):  
Qianjing Jiang ◽  
Zhiming Qi ◽  
Lulin Xue ◽  
Melissa Bukovsky ◽  
Chandra A. Madramootoo ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Crop Production ◽  
Climate Change Impacts ◽  
N Losses ◽  
Gas Emissions

Global contribution of climate variability and trends to maize yield change in observations and crop models during 1980-2010

2020 ◽  
Author(s):  
Xiaomeng Yin ◽  
Guoyong Leng
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Statistical Model ◽  
Yield Loss ◽  
Climate Change Impacts ◽  
Maize Yield ◽  
Climate Impacts ◽  
Future Climate Change ◽  
Crop Models ◽  
Process Based Models

&lt;p&gt;Understanding historical crop yield response to climate change is critical for projecting future climate change impacts on yields. Previous assessments rely on statistical or process-based crop models, but each has its own strength and weakness. A comprehensive comparison of climate impacts on yield between the two approaches allows for evaluation of the uncertainties in future yield projections. Here we assess the impacts of historical climate change on global maize yield for the period 1980-2010 using both statistical and process-based models, with a focus on comparing the performances between the two approaches. To allow for reasonable comparability, we develop an emulator which shares the same structure with the statistical model to mimic the behaviors of process-based models. Results show that the simulated maize yields in most of the top 10 producing countries are overestimated, when compared against FAO observations. Overall, GEPIC, EPIC-IIASA and EPIC-Boku show better performance than other models in reproducing the observed yield variations at the global scale. Climate variability explains 42.00% of yield variations in observation-based statistical model, while large discrepancy is found in crop models. Regionally, climate variability is associated with 55.0% and 52.20% of yield variations in Argentina and USA, respectively. Further analysis based on process-based model emulator shows that climate change has led to a yield loss by 1.51%-3.80% during the period 1980-1990, consistent with the estimations using the observation-based statistical model. As for the period 1991-2000, however, the observed yield loss induced by climate change is only captured by GEPIC and pDSSAT. In contrast to the observed positive climate impact for the period 2001-2010, CLM-Crop, EPIC-IIASA, GEPIC, pAPSIM, pDSSAT and PEGASUS simulated negative climate effects. The results point to the discrepancy between process-based and statistical crop models in simulating climate change impacts on maize yield, which depends on not only the regions, but also the specific time period. We suggest that more targeted efforts are required for constraining the uncertainties of both statistical and process-based crop models for future yield predictions.&amp;#160;&lt;/p&gt;

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