An assessment of social vulnerability to climate change among the districts of Arunachal Pradesh, India

Maiti, Sanjit; Jha, Sujeet Kumar; Garai, Sanchita; Nag, Arindam; Bera, Asit Kumar; Paul, Vijay; Upadhaya, R.C.; Deb, S. M.

doi:10.1016/j.ecolind.2017.02.006

Cited by 67 publications

(16 citation statements)

References 10 publications

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“…The state is considered a part of the Eastern Himalayas, a biodiversity hotspot with a geographical area of 82,023 km 2 and a population density of 17 people per square kilometer ( Census, 2011 ). It is mostly hilly and mountainous, and it is also considered an important eco-region ( Olson and Dinerstein, 1998 ; Bharali and Khan, 2011 ; Maiti et al, 2017 ).…”

Section: Methodsmentioning

confidence: 99%

Glycome Profiling and Bioprospecting Potential of the Himalayan Buddhist Handmade Paper of Tawang Region of Arunachal Pradesh

et al. 2022

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The paper and pulp industry (PPI) is one of the largest industries that contribute to the growing economy of the world. While wood remains the primary raw material of the PPIs, the demand for paper has also grown alongside the expanding global population, leading to deforestation and ecological imbalance. Wood-based paper production is associated with enormous utilization of water resources and the release of different wastes and untreated sludge that degrades the quality of the environment and makes it unsafe for living creatures. In line with this, the indigenous handmade paper making from the bark of Daphne papyracea, Wall. ex G. Don by the Monpa tribe of Arunachal Pradesh, India is considered as a potential alternative to non-wood fiber. This study discusses the species distribution modeling of D. papyracea, community-based production of the paper, and glycome profiling of the paper by plant cell wall glycan-directed monoclonal antibodies. The algorithms used for ecological and geographical modeling indicated the maximum predictive distribution of the plant toward the western parts of Arunachal Pradesh. It was also found that the suitable distribution of D. papyracea was largely affected by the precipitation and temperature variables. Plant cell walls are primarily made up of cellulose, hemicellulose, lignin, pectin, and glycoproteins. Non-cellulosic cell wall glycans contribute significantly to various physical properties such as density, crystallinity, and tensile strength of plant cell walls. Therefore, a detailed analysis of non-cellulosic cell wall glycan through glycome profiling and glycosyl residue composition analysis is important for the polymeric composition and commercial processing of D. papyracea paper. ELISA-based glycome profiling results demonstrated that major classes of cell wall glycans such as xylan, arabinogalactans, and rhamnogalacturonan-I were present on D. papyracea paper. The presence of these polymers in the Himalayan Buddhist handmade paper of Arunachal Pradesh is correlated with its high tensile strength. The results of this study imply that non-cellulosic cell wall glycans are required for the production of high-quality paper. To summarize, immediate action is required to strengthen the centuries-old practice of handmade paper, which can be achieved through education, workshops, technical know-how, and effective marketing aid to entrepreneurs.

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Section: Methodsmentioning

confidence: 99%

Glycome Profiling and Bioprospecting Potential of the Himalayan Buddhist Handmade Paper of Tawang Region of Arunachal Pradesh

et al. 2022

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“…For each state, the value of each indicator has been derived by a standardized value multiplied by corresponding factor loading. PCA techniques were widely used in previous studies for vulnerability assessment such as climatic vulnerability [ 50 , [54] , [55] , [56] , [57] ]. For retention of principal components, several statistical tests are performed to find out the suitability of representative data in the case of PCA analysis.…”

Section: Methodsmentioning

confidence: 99%

Habitat vulnerability in slum areas of India – What we learnt from COVID-19?

Das

Giri

Sarkar

et al. 2021

International Journal of Disaster Risk Reduction

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UN-Habitat identified the present COVID-19 pandemic as ‘city-centric’. In India, more than 50% of the total cases were documented in megacities and million-plus cities. The slums of cities are the most vulnerable due to its unhygienic environment and high population density that requires an urgent implementation of public healthcare measures. This study aims to examine habitat vulnerability in slum areas to COVID-19 in India using principal component analysis and Fuzzy AHP based technique to develop slum vulnerability index to COVID-19 (SVI covid-19 ). Four slum vulnerability groups (i.e. principal components) were retained with eigen-values greater than 1 based on Kaiser criterion - poor slum household status; lack of social distance maintenance; high concentrations of slum population and towns and mobility of the households. This study also mapped composite SVI covid-19 on the basis of PCA and Fuzzy AHP method at the state level for a better understanding of spatial variations. The result shows that slums located in the eastern and central parts of India (particularly Uttar Pradesh, Bihar, Jharkhand, Odisha, West Bengal) were more vulnerable to COVID-19 transmission due to lack of availability as well as accessibility to the basic services and amenities to slum dwellers. Thus, the findings of the study may not only help to understand the habitat vulnerability in slum areas to COVID-19 but it will also teach a lesson to implement effective policies for enhancing the quality of slum households (HHs) and to reduce the health risk from any infectious disease in future.

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“…Numerous approaches have been proposed to evaluate vulnerability: the Exposure-Sensitivity-Adaptive Capacity (ESA) Framework [ 21 , 22 , 23 ], the Pressure-Support-State-Response (PSSR) model [ 24 ], the Driver-Pressure-State-Impact-Response Framework (DPSIR) [ 25 ], and the Composite Index (CI) method [ 26 , 27 ]. For now, there is no internationally recognized standard or rule to stipulate how many and what parameters should be selected to capture atmospheric environment vulnerability.…”

Section: Methodsmentioning

confidence: 99%

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region

Zhang

Shen

Liu

2018

IJERPH

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Assessing and quantifying atmospheric vulnerability is a key issue in urban environmental protection and management. This paper integrated the Analytical hierarchy process (AHP), fuzzy synthesis evaluation and Geographic Information System (GIS) spatial analysis into an Exposure-Sensitivity-Adaptive capacity (ESA) framework to quantitatively assess atmospheric environment vulnerability in the Beijing-Tianjin-Hebei (BTH) region with spatial and temporal comparisons. The elaboration of the relationships between atmospheric environment vulnerability and indices of exposure, sensitivity, and adaptive capacity supports enable analysis of the atmospheric environment vulnerability. Our findings indicate that the atmospheric environment vulnerability of 13 cities in the BTH region exhibits obvious spatial heterogeneity, which is caused by regional diversity in exposure, sensitivity, and adaptive capacity indices. The results of atmospheric environment vulnerability assessment and the cause analysis can provide guidance to pick out key control regions and recognize vulnerable indicators for study sites. The framework developed in this paper can also be replicated at different spatial and temporal scales using context-specific datasets to support environmental management.

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An assessment of social vulnerability to climate change among the districts of Arunachal Pradesh, India

Cited by 67 publications

References 10 publications

Glycome Profiling and Bioprospecting Potential of the Himalayan Buddhist Handmade Paper of Tawang Region of Arunachal Pradesh

Glycome Profiling and Bioprospecting Potential of the Himalayan Buddhist Handmade Paper of Tawang Region of Arunachal Pradesh

Habitat vulnerability in slum areas of India – What we learnt from COVID-19?

Atmospheric Environment Vulnerability Cause Analysis for the Beijing-Tianjin-Hebei Metropolitan Region

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