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Climate variability and extremes adversely affect the livestock sector directly and indirectly by aggravating the prevalence of livestock diseases, distorting production system and the sector profitability. This paper aims to examine climate variability and its impact on livestock system and livestock disease among pastoralists in Borana, Southern Ethiopia.

Data were collected through a combination of quantitative and qualitative methods using household questionnaire, field observations, focus group discussions and key informant interviews. Areal grid dikadal rainfall and temperatures data from 1985 to 2014 were collected from national meteorological agency. The quantitative and qualitative data were analyzed and interpreted using appropriate analytical tools and procedures.

The result revealed that the study area is hard hit by moisture stress, due to the late onset of rainy seasons, decrease in the number of rainy days and volume of rainfall. The rainfall distribution behavior coupled with the parallel increase in minimum and maximum temperature exacerbated the impact on livestock system and livestock health. Majority of the pastoralists are found to have rightly perceived the very occurrence and manifestations of climate variability and its consequences. Pastoralists are hardly coping with the challenges of climate variability, mainly due to cultural prejudice, poor service delivery and the socio-economic and demographic challenges.

Pastoralists are vulnerable to the adverse impact of climate variability and extreme events.

The finding of the study provides baseline information for practitioners, researchers and policymakers.

This paper provided detailed insights about the rainfall and temperature trend and variability for the past three decades. The finding pointed that pastoralists’ livelihood is under climate variability stress, and it has implications to food insecurity.

Literature contends that not much is known about smallholder farmers’ perceptions of climate variability and the impacts thereof on agricultural practices in Sub-Saharan Africa and South Africa in particular. The purpose of this study is to examine the perceptions of smallholder farmers from Botlokwa (a semi-arid region in South Africa) on climate variability in relation to climatological evidence.

The study area is in proximity to a meteorological station and comprises mainly rural farmers, involved in rain-fed subsistence agriculture. Focus group discussions and closed-ended questionnaires covering demographics and perceptions were administered to 125 purposely sampled farmers. To assess farmers’ perceptions of climate variability, their responses were compared with linear trend and variability of historical temperature and rainfall data (1985-2015). Descriptive statistics were used to provide insights into respondents’ perceptions.

About 64% of the farmers perceived climate variability that was consistent with the meteorological data, whereas 36% either held contrary observations or were unable to discern. Age, level of education, farming experience and accessibility to information influenced the likelihood of farmers to correctly perceive climate variability. No significant differences in perception based on gender were observed. This study concludes that coping and adaption strategies of over one-third of the farmers could be negatively impacted by wrong perceptions of climate variability.

This study highlights discrepancies in perceptions among farmers with similar demographic characteristics. To guarantee sustainability of the sector, intervention by government and other key stakeholders to address underlying factors responsible for observed discrepancies is recommended.

The purpose of this study is to analyze the impact of climate change and variability on agricultural production in Middle East and North Africa region (MENA) where the deleterious impacts of climate change are generally projected to be greatest.

The study used a production function model using Fixed Effect Regression (FER) analysis and then using marginal impact analysis to assess the impact of climate change and variability on agricultural production. Therefore, the study utilized panel data for the period 1961-2009 pooled from 20 countries in MENA region.

Results showed that 1 per cent increase in temperature during winter resulted in 1.12 per cent decrease in agricultural production. It was also observed that 1 per cent increase in temperature variability during winter and spring resulted in 0.09 and 0.14 per cent decrease in agricultural production, respectively. Results also indicated that increasing precipitation during winter and fall season and precipitation variability during winter and summer seasons had negative impact. The estimated parameters of square temperature and precipitation indicated that climate change has significant nonlinear impacts on agricultural production in MENA region.

Despite there are many studies on the impact of climate change on agricultural production, there is a lack of publications to address the economic impact of both climate change and variability on agricultural production in MENA region. Thus, these results are more comprehensive and more informative to policymakers than the results from field trials.

The climate change and related impacts are experienced around the world. There arise different triggering factors to climate change and impact. The purpose of this study is to figure out how changes in vegetation cover may or may not have an impact to climate change. The research will produce ideas for vegetation preservation and replant.

The investigation was probed for 34 years’ time period starting from the year 1981 to 2015. After testing and checking for serial autocorrelation in the vegetation data series, Mann–Kendal nonparametric statistical evaluation was carried out to investigate vegetation cover trends. Sen’s method was deployed to investigate the magnitude of vegetation cover change in natural differential vegetation index (NDVI) unit per year. Furthermore, the ArcGIS spatial analysis tools were used for the calculation of mean NDVI distribution and also for carrying out the spatial investigation of trends at each specific location within the study region.

The yearly mean NDVI during the study period was observed to have a decreasing trend. The mean NDVI value ranges between 0.32 and 0.98 NDVI unit, and hence, this means from less or poor vegetated zones to higher or healthier vegetated zones. The mean NDVI value was seen decreasing toward the highlands regions. The NDVI-rainfall correlation was observed to be stronger than the NDVI-temperature correlation. The % area coverage of NDVI-rainfall positive correlation was higher than the negative correlation. The % area coverage of NDVI-temperature negative correlation was higher than the positive correlation within the study region. Rainfall is seen as a highly influencing climatic factor for vegetation growth than the temperature within the study region.

This study in this country is a new approach for climate change monitoring and planning for the survival of the people of Papua New Guinea, especially for the farmer and those who is living in the coastal area.

This paper aims to explore the impact of climate change on yields and yield variances in major rainfed crops and measure possible changes in yields under projected climate changes in different agro-climatic zones of Tamil Nadu, India. Although many empirical studies report the influence of climate change on crop yield, only few address the effect on yield variances. Even in such cases, the reported yield variances were obtained through simulation studies rather than from actual observations. In this context, the present study analyzes the impact of climate change on crops yield and yield variance using the observed yields.

The Just-Pope yield function (1978) is used to analyze the impact of climate change on mean yield and variance. The estimated coefficient from Just-Pope yield function and the projected climatic data for the year 2030 are incorporated to capture the projected changes in crop yield and variances.

By the year 2030, the yield of pulses is estimated to decline in all the zones (Northeast, Northwest, Western, Cauvery delta, South and Southern zones), with significant declines in the Northeast zone (6.07 per cent), Cauvery delta zone (3.55 per cent) and South zone (3.54 per cent). Sorghum yield may suffer more in Western zone (2.63 per cent), Southern zone (1.92 per cent) and Northeast zone (1.62 per cent). Moreover, the yield of spiked millet is more likely to decrease in the Southern zone (1.39 per cent), Northeast zone (1.21 per cent) and Cauvery delta zone (0.24 per cent), and the yield of cotton may also decline in the Northeast zone (12.99 per cent), Northwest zone (8.05 per cent) and Western zone (2.10 per cent) of Tamil Nadu, India.

The study recommends introducing appropriate crop insurance policies to address possible financial losses to the farmers. Prioritizing area-specific stress-tolerant crop varieties without complementing yield would sustain crops cultivation further.

The idea is to propagate the concept of climate resilience in India beyond international mandates and bold statements, enabled through utilization of open data. The research underscores need for climate responsive planning for megacities in India with an example of National Capital Territory of Delhi, the capital of India whose trends and policies often form a blueprint for others to follow.

The research was conducted in six distinct, yet inter-related stages: literature review, data collection, data analysis at four levels – city, zonal, planning division and flood plains inhabited by climate vulnerable population with least adaptive capacity, formulating alternative scenarios of future development, evaluation of scenarios, conclusions and recommendations.

India has approximately 8,000 urban centres. Less than 2% of these centres have a planning document. Less than 1% of these documents acknowledge climate change as a phenomenon let alone a challenge to urban future. It is therefore a priority to address the challenge from a planning perspective for India.

Methodologies for evaluating the multiplier effect are still in their pre-final stage and there exist uncertainties and margin of error.

Aligned with pre-tested methodologies, the research through extensive empirical and spatial-temporal analysis indicates severity and irreversibility of socio-economic and environmental losses.

Risks and vulnerabilities to climate change and climate induced disasters exhibit multiplier effect that varies spatially across a region's demography. Quantitative analysis of multiplier effect on the secondary environment is rarely explored in climate studies. The paper addresses this lacuna by examining climate risks to Indian megacities with a case example of Delhi. The findings suggest that urbanization, climate risks and natural environment are interlinked, where an impact of one generates ripples across other two and their secondary environment plus sectors.

This research aims to develop a model that may be used to determine the effective adaptive measures to implement in a system affected by climate change.

The three primary dimensions of the model were individually investigated and then the linkages among them were developed. Specifically, the nature of climate change was examined and the issues emerging from the changes were analyzed. Next, an intensive study of system vulnerabilities was conducted, and the third factor in the model, risk, is then explored. Afterwards, the conceptual framework, which is the foundation of the climate change vulnerability risk model, was devised and the model created.

The model is a three‐dimensional matrix with the nature of climate change, vulnerabilities, and risks as its chief dimensions. It identifies the four natures of climate change, namely: variability, intensity, frequency, and quantity and the vulnerability types to be socio‐economic, biophysical, technological, and institutional. Meanwhile, risks are classified as income, biodiversity, health, mortality, and infrastructure risks.

The research is the first phase of a three‐stage study on the linkages among climate change, vulnerability, and risks. It is the development stage of the framework that exemplifies the interrelationships among these variables and is the basis of the statistical and econometric analyses in the later stages.

The climate change vulnerability risk model was developed to act as an analytical guide in understanding the effects of climate change to systems. The model may be used to determine the effective adaptive measures to apply in the system, through a comparative analysis of the variables in the matrix.

This chapter reviews factors responsible for climate change, impacts of the change on animal health, zoonotic diseases, and their linkage with One-Health program.

This chapter is based on the available literature related to climate change and its effect on animal health and production from different points. The causes and change forcers of climate change, direct and indirect effects of the change on animal health management, host–pathogen–vector interaction, and zoonotic diseases are included. Inter-linkage between climate change and One-Health program are also assessed.

Beside natural causes of climatic change, greenhouse gases are increasing due to human activities, causing global climate changes which have direct and indirect animal health and production performance impacts. The direct impacts are increased ambient temperature, floods, and droughts, while the indirect are reduced availability of water and food. The change and effect also promote diseases spread, increase survival and availability of the pathogen and its intermediate vector host, responsible for distribution and prevalence of tremendous zoonotic, infectious, and vector-borne diseases. The adverse effect on the biodiversity, distribution of animals and micro flora, genetic makeup of microbials which may lead to emerging and re-emerging disease and their outbreaks make the strong linkage between climate change and One-Health.

Global climate change is receiving increasing international attention where international organizations are increasing their focus on tackling the health impacts. Thus, there is a need for parallel mitigation of climate change and animal diseases in a global form.

Most research on climate change is limited to environmental protection, however this chapter provides a nexus between climate change, animal health, livestock production, and the One-Health program for better livelihood.

This paper aims to explore the local knowledge on climate change, its impacts and the responses they are making at the household or community level to deal with the changes on the basis of their experiences and perceptions.

The study was based on household survey conducted with one male and one female respondent in 202 households. Alongside, series of focused group discussions were conducted with local people to capture the perception on about climate change, its impacts and adaptation strategies applied to enhance their resilience capacity to changing climate. Rainfall and temperature data were collected from Department of Hydrology and Meteorology (DHM) for seven and four different stations, respectively, within Kathmandu Valley and analyzed to understand the climatic trend.

The perception of most of the local people on changes in temperature was almost in line with the recorded long-term climatic trend both showing an increasing trend, whereas the perception of decreasing both monsoon and non-monsoon rainfall did not match with the recorded data as the rainfall data analysis did not reflect any clear long-term pattern. People have been facing several impacts such as decrease in water sources, decrease in agricultural crop production, increase in new crop pest and weeds in agricultural crops. Local people are responding to these impacts as per their own skills and traditional knowledge.

This is totally original research article and the impacts and adaptations measures documented in this article may represent the case of peri-urban areas of least developed countries like Nepal.

The purpose of this paper is to examine the status of the supply reliability of groundwater irrigation, and discuss how it is affected by climate change and tubewell density in rural China.

This study is based on a nine-province village survey and secondary climate data. A Tobit model (or censored regression model) was used to estimate the determinants of supply reliability of groundwater irrigation.

Results show that the supply reliability of groundwater irrigation was 89 percent on average in the past three years. The non-linear relationship in the econometric results revealed that the 30-year annual temperature significantly influenced the supply reliability of groundwater irrigation. When the temperature rises above the turning point (6.30°C), it shifts from a positive to a negative relationship with the supply reliability of groundwater irrigation. The 30-year annual temperature in eight of the nine provinces (i.e. except for Jilin Province) was higher than the turning point. If the temperature increases by 20°C in the future, other factors being constant, the supply reliability of groundwater irrigation will decline by 20 percent. However, if precipitation increases by 10 percent, the supply reliability of groundwater irrigation could improve by 3 percent, while reducing precipitation by 10 percent will lower the supply reliability of groundwater irrigation by 3 percent. Increasing the density of tubewells considerably improves the supply reliability of groundwater irrigation. However, although increasing the density of tubewells may yield enough groundwater for irrigation, this one-sided approach raises sustainability concerns.

Although increasing the density of tubewells may ensure that enough groundwater is available for irrigation, such a conclusion is one sided, and sustainability concerns should be raised in assessing this method of creating supply reliability.

This paper improves the understanding of the impact of climate variables on agriculture irrigation and water supply reliability in the micro scale, and provides a scientific basis for relevant policy making.