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- Permanent Link:
- http://dpanther.fiu.edu/dpService/dpPurlService/purl/FI13010965/00001
Notes
- Summary:
- This research paper develops a methodology for quantitatively disaggregating and mapping the variability of vulnerability to climate change across a country, applied to the case of Tajikistan. The model is intended to inform policymakers by highlighting areas where adaptation efforts need to be targeted. The authors begin by discussing the intimate relationship between poverty and vulnerability to climate related disaster, and why Tajikistan is an ideal case because it is one of the poorest countries in Eastern Europe and Central Asia, and is identified as the most at-risk within the region. Their methodology focuses on two variables, vulnerability and adaptive capacity. Vulnerability is the risk a household faces of falling below the poverty line due to losses in income related to climate-based disaster events. Adaptive capacity refers to the ability to adjustment assets, livelihoods, or behaviors to face climate change. This capacity is based on physical, financial, human, and social capital, which are unevenly distributed throughout society. Not only are the poor generally the most exposed to climate-related disaster, but also least capable of adaptation. A vulnerability index is constructed by analyzing exposure to climate variability and natural disaster, sensitivity to these events, and adaptive capacity. To determine adaptive capacity they look at per capita household consumption and level of education attainment. Institutional strength is measured by using survey data on trust as a form of social capital, quality of public services, and level of corruption. To determine exposure to climate change, they use temperature and precipitation variability and frequency of natural disasters. Sensitivity to climate change is measured by looking at agricultural, demographic, health, and poverty data as they relate to disaster events. Tajikistan is divided into 10 geographic areas depicting different agro-ecological zones. Results showed that vulnerability varied according to socio-economic and institutional factors in ways not clearly linked to levels of exposure. Urban areas were least vulnerable; having the lowest sensitivity, the second-highest adaptive capacity, and average exposure, along with comparatively better socio-economic and institutional development. Prime agricultural valleys had higher levels of vulnerability, so policy should focus on rural areas emphasizing sustainable land management and income diversification. Migration to urban areas or abroad is discussed as one strategy that rural populations typically employed to increase adaptive capacity. ( English,English,English )
- Subject:
- Climate Change Adaptation
- Scope and Content:
- 1. Introduction p. 2; 2. Vulnerability and adaptive capacity p. 4; 3. Data and methodology p. 5; Conceptual approach p. 5; From concept to choice of variables p. 6; Variables in the index p. 7; Index methodology p. 8; Agro-ecological zones used in the analysis p. 9; 4. Results p. 10; Results for agro-ecological zones p. 10; Results at the oblast level p. 13; 5. Concluding remarks p. 14; References p. 16; Appendixes: Appendix 1: Formulas and variables p. 17; Appendix 2: Composition of the geographical zones p. 18; Figures: Figure 1: The 10 agro-ecological zones with oblast capitals p. 9; Figure 2: Vulnerability map for Tajikistan (10 agro-ecological zones); Figure 3: Components of the vulnerability index p. 11; Figure 4: Exposure index p. 12; Figure 5: Sensitivity index p. 12; Figure 6: Adaptive capacity p. 13; Figure 7: Vulnerability map for Tajikistan (oblast level) p. 14; Figure 8: Components of the vulnerability index (oblast level) p. 14; Tables: Table 1: Population by zone p. 18
- Citation/Reference:
- Heltberg, R., Bonch-Osmolovskiy, M. (2011). Mapping vulnerability to climate change. The World Bank.
Record Information
- Source Institution:
- Florida International University
- Rights Management:
- This publication is released under the Creative Commons Attribution 3.0 license. For full details of the license, please refer to the following: http://creative-commons.org/licenses/by/3.0/legalcode
- Resource Identifier:
- FI13010965
778847668 ( oclc )
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