Climate Change Impact on Livestock: Adaptation and Mitigation

This chapter provides an overview of the impact of climate change on livestock production and its adaptation and mitigation. Animal agriculture is the major contributor to increasing methane (CH4) and nitrous oxide (N2O) concentrations in Earth’s atmosphere. Generally there are two-way impacts of livestock on climate change. The first part is the livestock contribution to climate change, while the second part is concerned with livestock getting affected by climate change. Hence, improving livestock production under changing climate scenario must target both reducing greenhouse gas (GHG) emission from livestock and reducing the effect of climate change on livestock production. These efforts will optimize livestock production under the changing climate scenario. The role of livestock on climate change is primarily due to enteric CH4 emission and those from manure management. Various GHG mitigation strategies include manipulation of rumen microbial ecosystem, plant secondary metabolites, ration balancing, alternate hydrogen sinks, manure management, and modeling to curtail GHG emission. Adapting to climate change and reducing GHG emissions may require significant changes in production technology and farming systems that could affect productivity. Many viable opportunities exist for reducing CH4 emissions from enteric fermentation in ruminant animals and from livestock manure management facilities. To be considered viable, these emission reduction strategies must be consistent with the continued economic viability of the producer and must accommodate cultural factors that affect livestock ownership and management. The direct impacts of climate change on livestock are on its growth, milk production, reproduction, metabolic activity, and disease occurrences. The indirect impacts of climate change on livestock are in reducing water and pasture availability and other feed resources. Amelioration of environmental stress impact on livestock requires multidisciplinary approaches which emphasize animal nutrition, housing, and animal health. It is important to understand the livestock responses to the environment and analyze them, in order to design modifications of nutritional and environmental management, thereby improving animal comfort and performance.

Both climate and agricultural policy changes are commonly seen as important drivers for agricultural production. In this study, scena-rios of climate and political change were calculated for the Upper Danube catchment area using the regional optimization model ACRE. Two political scenarios were calculated for the year 2020. One scenario assumes the continuation of the Common Agricultural Policy reform 2003 the other assumes a strong shift away from payments of the first pillar to payments of the second pillar of the CAP. Both scenarios were combined with four different scenarios of climate change and technological progress derived from ICCP SRES assumptions and the ACCELERATES project. The results of the scenario calculations were analysed with respect to their implica-tions for the whole catchment area as well as for selected districts. Climate change and technological progress both cause small changes in agricultural land use: fodder crop area tends to be converted to cash crop area, and intensive grasslands tend to be converted into extensive grasslands. Climate change and technological progress increase crop productivity, and consequently, total gross margin increases. The impact of climate change might get stronger toward the end of the century which is beyond the scope of the investigations presented here. The impact of climate change might thus switch from bringing net benefits in the short to medium term to bringing net losses for the area investigated in the long run.

Because of their important roles in employment generation and sustainable production, the forage and livestock sectors have grown in popularity across the country in recent years. By the year 2050, global average temperatures are expected to rise by 1–2 °C. As a result, increased frequency of high temperatures, storms, or drought, a quantum leap in chemical use, a shift in virulence pattern, and the emergence of pathogens in new areas are expected. A better approach to combating the effects of climate change would be the discovery and deployment of new genes. Under the climate change scenario, abiotic stress-tolerant varieties and integrated disease management (IDM) have increased yield and productivity. Early plant breeding programmes were successful in terms of yield gains, with quality traits such as improved disease resistance and digestibility becoming increasingly important breeding targets. Demands for more sustainable production systems have recently necessitated the use of high-yielding, high-quality forages that enable efficient animal production while minimizing environmental impact. This chapter provides an overview of the impact of climate change on forage production due to diseases, as well as potential management strategies for mitigating its negative effects on forage crops in order to achieve sustainable production through breeding and molecular approaches.

Quantitatively projecting the impact of future climate change on the socio-economy and exploring its internal mechanism are of great practical significance to adapt to climate change and prevent climate risks. Based on the economy-climate (C-D-C) model, this paper introduces a yield impact of climate change (YICC) model that can quantitatively project the climate change impact. The model is based on the YICC as its core concept and uses the impact ratio of climate change (IRCC) indicator to assess the response of the economic system to climate change over a long period of time. The YICC is defined as the difference between the economic output under changing climate condition and that under assumed invariant climate condition. The IRCC not only reflects the sensitivity of economic output to climate change but also reveals the mechanism of the nonlinear interaction between climate change and non-climatic factors on the socio-economic system. Using the main grain-producing areas in China as a case study, we use the data of the ensemble average of 5 GCMs in CMIP6 to project the possible impact of climate change on grain production in the next 15–30 years under three future scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). The results indicate that the long-term climate change in the future will have a restraining effect on production in North region and enhance production in South region. From 2021 to 2035, climate change will reduce production by 0.60–2.09% in North region, and increase production by 1.80–9.01% in South region under three future scenarios. From 2021 to 2050, compared with the climate change impact in 2021–2035, the negative impact of climate change on production in North region will weaken, and the positive impact on production in South region will enhance with the increase in emission concentration. Among them, climate change will reduce grain output in North region by 0.52–1.99%, and increase output in South region by 1.35–9.56% under the three future scenarios. The combination of economic results and climate change research is expected to provide scientific support for further revealing the economic mechanism of climate change impacts.

Climate Change and Health: Strengthening the Evidence Base for Policy

Impact of climate change on farms in smallholder farming systems: Yield impacts, economic implications and distributional effects

78.2 Impact of Climate Change on the Health and Well-Being of Indigenous Communities in Australia

Introduction: One of the few certain impacts of climate change is the increase in the heat stress exposure. Heat exposure in the working environment is an important factor of occupational health. Among various heat indices, Wet Bulb Globe Temperature (WBGT) is a well-established measure of occupational heat stress, health and work capacity. It is a linear combination of four environmental factors namely temperature, humidity, wind speed and radiation. In this work, we examined the changes in WBGT under the climate change scenario over India for the period 1975-2100. Methodology: RegCM4.3 model outputs of meteorological parameters are analyzed to calculate the WBGT (indoor). The biases in the model simulations are corrected first for the historical period (1975-2004) with respect to Indian Metrological Department data and MERRA reanalysis data using the technique of linear regression. For the future, projected outputs from RegCM are analyzed for RCP4.5 and RCP8.5 scenarios. WBGT range is subdivided into five risk levels using comfort classes (Balazejezyk et al., 2011) as comfort (WBGT<WBGT<WBGT<WBGT30). The analysis and interpretation are carried out in view of the seven surface temperature homogeneous zones of India to understand the impact of climate change on heat stress exposure. Results: Spatial mapping for the entire country was carried out using GIS to identify the hotspots. In the last three decades, 21%, 33%, 34% 10% and 2% of the days annually correspond to 'comfort', 'warm', 'hot', 'very hot' and 'sweltering' conditions. The relative occurrences of the various comfort classes show large heterogeneity in space and time. The changes in the future for different 'climate change' scenarios are also quantified. Discussions: This study is a first attempt to assess the impact of climate change on heat stress and the implication for occupational health and productivity loss for the entire country.

An essential part of hydrological research focuses on hydrological extremes, such as river peak flows and associated floods, because of their large impact on economy, environment, and human life. These extremes can be affected by potential future environmental change, including global climate change and land cover change. In this paper, the relative impact of both climate change and urban expansion on the peak flows and flood extent is investigated for a small‐scale suburban catchment in Belgium. A rainfall‐runoff model was coupled to a hydrodynamic model in order to simulate the present‐day and future river streamflow. The coupled model was calibrated based on a series of measured water depths and, after model validation, fed with different climate change and urban expansion scenarios in order to evaluate the relative impact of both driving factors on the peak flows and flood extent. The three climate change scenarios that were used (dry, wet winter, wet summer) were based on a statistical downscaling of 58 different RCM and GCM scenario runs. The urban expansion scenarios were based on three different urban growth rates (low, medium, high urban expansion) that were set up by means of an extrapolation of the observed trend of urban expansion. The results suggest that possible future climate change is the main source of uncertainty affecting changes in peak flow and flood extent. The urban expansion scenarios show a more consistent trend. The potential damage related to a flood is, however, mainly influenced by land cover changes that occur in the floodplain. Copyright © 2011 John Wiley & Sons, Ltd.

Srinivasan, M.S., J. Schmidt, S. Poyck, and E. Hreinsson, 2011. Irrigation Reliability Under Climate Change Scenarios: A Modeling Investigation in a River-Based Irrigation Scheme in New Zealand. Journal of the American Water Resources Association (JAWRA) 47(6):1261–1274. DOI: 10.1111/j.1752-1688.2011.00568.x Abstract: The impact of climate change (CC) on irrigation reliability in a river-based irrigation scheme in New Zealand was investigated. Reliability was defined as the river’s ability to meet the demand. Two future periods were considered, 2030-49 (“2040”) and 2080-99 (“2090”), and reliability at these periods were compared against those in 1980-99 (“current”). A hydrology model, calibrated and validated for current condition, was applied to simulate flows for CC scenarios. Annual precipitation and mean temperatures were predicted to increase under CC scenarios over current condition. Occurrence of high intensity rainfall events indicated large flows under CC scenarios, though these increases could be occurring outside the irrigation season (September-April). Compared to current condition, under CC scenarios, the number of days per season supply falling below demand could increase by 5 (2040) to 17% (2090). Snow storage plays a major role in sustaining flows in early spring under current condition. However, with increasing temperatures under CC scenarios, the average annual snow water storage could decrease from 155 mm (current) to 97-134 mm (2040) and 40-90 mm (2090). Under CC scenarios, to sustain the current levels of land and water uses in this scheme, storage options need to be explored.

Introduction There is a substantial literature about the future impacts of climate change (Nordhaus 1991; Cline 1992b; Fankhauser 1995; Mendelsohn et al . 2000; Tol 2002a); see Tol (2009b) for an overview. Less is known, however, about the impacts of climate change in the past. While there is no immediate policy relevance of estimates of past effects – as liability is yet to be established (Tol and Verheyen 2004) – such estimates would serve to validate models of future impacts – and thus help to improve these models and build confidence. In this chapter, I turn this question on its head. I use a model to backcast past impacts, thus generating hypotheses to be tested against observations. Unfortunately, there are no direct observations of the economic impact of past climate change. Note that the cause of climate change, past or future, is irrelevant for its impacts. There are, however, some studies that estimate particular aspects of the impact of past climate change, typically focussing on biophysical impacts.

Regional inequalities of future climate change impact on rice (Oryza sativa L.) yield in China

In climate change (CC) impact studies, various weather-dependent models (e.g. crop growth models or rainfall-runoff models) are employed to assess possible CC impacts on crop yields, river flows, as well as on various climatological and other indices. To perform such experiments, one has to decide what meteorological data (representing present & future climate) will be used as inputs. Two most commonly used approaches at hand are Regional Climate Models (RCMs) and Stochastic Weather Generators (WGs). While one might say, that these two approaches are the rivals which compete for getting the main role in providing the weather data for CC impact studies, we want to demonstrate that these two approaches could be rather allies  which could be very effective while being used together.In our presentation, we show three ways of such co-operation: (1) To produce weather series representing the future climate by the WG, WG parameters must be modified by CC scenarios, which may be derived by comparing RCM simulations of present vs. future climates. (2) To assess separate effects of changes (projected by RCMs) in individual weather variables (e.g. temperature or precipitation) and their statistical characteristics (means, variabilities, spatial and/or temporal correlations), WG may be used: only selected WG parameters representing chosen variable and its statistical characteristic may be modified before producing the synthetic series. (3) To assess statistical significance of the changes derived from a given RCM simulation, WG may be also used: the significancy of projected changes may be based on analyzing the spread of the changes derived by comparing multiple pairs of synthetic time series produced by WG calibrated with RCM simulations for future vs. present time slices.In the experiment, we use: (a) our multi-site multi-variate parametric weather generator SPAGETTA, (b) E-OBS data to calibrate the generator for the present climate conditions in 8 European regions, and (c) outputs from ensemble of 19 RCM simulations for present and future climate (CORDEX database) in these regions.Acknowledgement: The experiment was made within the frame of the PERUN project funded by the Technological Agency of the Czech Republic (project no. SS0203004000).

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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 impact of climate change on the territory and population is only increasing every year. Extreme weather events are expected to be repetitive and difficult to predict. New research shows that the effects of global warming are felt in large cities, at least twice as strong as in rural areas. That is why taking the necessary precautionary measures becomes an urgent task. The key, according to researchers, is adaptation and prevention. The authors of the article, analyzing the prerequisites and consequences of climate change, propose a scheme of organizational and economic mechanisms to counteract climate change in complex urban environments. Long-term goals include reducing urban heat islands through urban planning and climate-friendly home design to create a conducive, non-air-conditioned environment. In order to maximize the effectiveness of such adaptation measures, active multidisciplinary collaboration is required with the involvement of professionals in many industries. The assessment of the impact of climate change on the environment and human health has identified a number of gaps in knowledge and problems in the implementation of appropriate health measures. The article substantiates the relevance of climate change research in Ukraine. In addition, the main results of the research on population safety in the global climate change are summarized. Factors of the impact of global climate change on the environment, man, society, economy and complex agglomerations are highlighted. The consequences of climate change of natural, economic and social nature are presented. Directions and measures to adapt natural and socio-economic systems to global climate change are substantiated. The classification of the mechanisms of counteraction and mitigation of the negative effects of global climate change is given.