Climate change vulnerability profiles for North East India

Climate change vulnerability profiles are developed at the district level for agriculture, water and forest sectors for the North East region of India for the current and projected future climates. An index-based approach was used where a set of indicators that represent key sectors of vulnerability (agriculture, forest, water) is selected using the statistical technique principal component analysis. The impacts of climate change on key sectors as represented by the changes in the indicators were derived from impact assessment models. These impacted indicators were utilized for the calculation of the future vulnerability to climate change. Results indicate that majority of the districts in North East India are subject to climate induced vulnerability currently and in the near future. This is a first of its kind study that exhibits ranking of districts of North East India on the basis of the vulnerability index values. The objective of such ranking is to assist in: (i) identifying and prioritizing the most vulnerable sectors and districts; (ii) identifying adaptation interventions, and (iii) mainstreaming adaptation in development programmes.

Spatio-temporal landscape modelling for natural hazard vulnerability analysis in select watersheds of Central Western Ghats

Natural hazards such as landslides are triggered by numerous factors such as ground movements, rock falls, slope failure, debris flows, slope instability, etc. Changes in slope stability happen due to human intervention, anthropogenic activities, change in soil structure, loss or absence of vegetation (changes in land cover), etc. Loss of vegetation happens when the forest is fragmented due to anthropogenic activities. Hence land cover mapping with forest fragmentation can provide vital information for visualising the regions that require immediate attention from slope stability aspects. The main objective of this paper is to understand the rate of change in forest landscape from 1973 to 2004 through multi-sensor remote sensing data analysis. The forest fragmentation index presented here is based on temporal land use information and forest fragmentation model, in which the forest pixels are classified as patch, transitional, edge, perforated, and interior, that give a measure of forest continuity. The analysis carried out for five prominent watersheds of Uttara Kannada district– Aganashini, Bedthi, Kali, Sharavathi and Venkatpura revealed that interior forest is continuously decreasing while patch, transitional, edge and perforated forest show increasing trend. The effect of forest fragmentation on landslide occurrence was visualised by overlaying the landslide occurrence points on classified image and forest fragmentation map. The increasing patch and transitional forest on hill slopes are the areas prone to landslides, evident from the field verification, indicating that deforestation is a major triggering factor for landslides. This emphasises the need for immediate conservation measures for sustainable management of the landscape. Quantifying and describing land use - land cover change and fragmentation is crucial for assessing the effect of land management policies and environmental protection decisions.

Assessing Indian cities for vulnerability to climate change

This paper critically evaluates the vulnerability of Indian cities to climate change in the context of sustainable development. City-scale indicators are developed for multiple dimensions of security and vulnerability. Factor analysis is employed to construct a vulnerability ranking of 46 major Indian cities. The analysis reveals that high aggregate levels of wealth do not necessarily make a city less vulnerable. Two, cities with diversified economic opportunities could adapt better to the new risks posed by climate change, than cities with unipolar opportunities. Three, highly polluted cities are more vulnerable to the health impacts of climate change, and cities with severe groundwater depletion will find it difficult to cope with increased rainfall variability. Policy and sustainability issues are discussed for these results.

Farmers' vulnerability to climate variability in Dimapur district of Nagaland, India

Certain parts of the State of Nagaland situated in the northeastern region of India have been experiencing rainfall deficit over the past few years leading to severe drought-like conditions, which is likely to be aggravated under a climate change scenario. The state has already incurred considerable losses in the agricultural sector. Regional vulnerability assessments need to be carried out in order to help policy makers and planners formulate and implement effective drought management strategies. The present study uses an 'index-based approach' to quantify the climate variability-induced vulnerability of farmers in five villages of Dimapur district, Nagaland. Indicators, which are reflective of the exposure, sensitivity and adaptive capacity of the farmers to drought, were quantified on the basis of primary data generated through household surveys and participatory rural appraisal supplemented by secondary data in order to calculate a composite vulnerability index. The composite vulnerability index of village New Showba was found to be the least, while Zutovi, the highest. The overall results reveal that biophysical characteristics contribute the most to overall vulnerability. Some potential adaptation strategies were also identified based on observations and discussions with the villagers.

Modeling the vulnerability of an urban groundwater system due to the combined impacts of climate change and management scenarios

Climate change impact on a groundwater-dependent small urban town has been investigated in the semiarid hard rock aquifer in southern India. A distributed groundwater model was used to simulate the groundwater levels in the study region for the projected future rainfall (2012-32) obtained from a general circulation model (GCM) to estimate the impacts of climate change and management practices on groundwater system. Management practices were based on the human-induced changes on the urban infrastructure such as reduced recharge from the lakes, reduced recharge from water and wastewater utility due to an operational and functioning underground drainage system, and additional water extracted by the water utility for domestic purposes. An assessment of impacts on the groundwater levels was carried out by calibrating a groundwater model using comprehensive data gathered during the period 2008-11 and then simulating the future groundwater level changes using rainfall from six GCMs Institute of Numerical Mathematics Coupled Model, version 3.0 (INM-CM. 3.0); L'Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4); Model for Interdisciplinary Research on Climate, version 3.2 (MIROC3.2); ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G); Hadley Centre Coupled Model, version 3 (HadCM3); and Hadley Centre Global Environment Model, version 1 (HadGEM1)] that were found to show good correlation to the historical rainfall in the study area. The model results for the present condition indicate that the annual average discharge (sum of pumping and natural groundwater outflow) was marginally or moderately higher at various locations than the recharge and further the recharge is aided from the recharge from the lakes. Model simulations showed that groundwater levels were vulnerable to the GCM rainfall and a scenario of moderate reduction in recharge from lakes. Hence, it is important to sustain the induced recharge from lakes by ensuring that sufficient runoff water flows to these lakes.

Characterizing drought using the reliability-resilience-vulnerability concept

This study borrows the measures developed for the operation of water resources systems as a means of characterizing droughts in a given region. It is argued that the common approach of assessing drought using a univariate measure (severity or reliability) is inadequate as decision makers need assessment of the other facets considered here. It is proposed that the joint distribution of reliability, resilience, and vulnerability (referred to as RRV in a reservoir operation context), assessed using soil moisture data over the study region, be used to characterize droughts. Use is made of copulas to quantify the joint distribution between these variables. As reliability and resilience vary in a nonlinear but almost deterministic way, the joint probability distribution of only resilience and vulnerability is modeled. Recognizing the negative association between the two variables, a Plackett copula is used to formulate the joint distribution. The developed drought index, referred to as the drought management index (DMI), is able to differentiate the drought proneness of a given area when compared to other areas. An assessment of the sensitivity of the DMI to the length of the data segments used in evaluation indicates relative stability is achieved if the data segments are 5years or longer. The proposed approach is illustrated with reference to the Malaprabha River basin in India, using four adjoining Climate Prediction Center grid cells of soil moisture data that cover an area of approximately 12,000 km(2). (C) 2013 American Society of Civil Engineers.

Challenges in vulnerability assessment of forests under climate change

Forest-management goals in the context of climate change are to reduce the adverse impact of climate change on biodiversity, ecosystem services and carbon stocks. For developing an effective adaptation strategy, knowledge on nature and sources of vulnerability of forests is necessary to conserve or enhance carbon sinks. However, assessing the vulnerability of forest ecosystems is a challenging task, as the mechanisms that determine vulnerability cannot be observed directly. In this article, we list the challenges in forest vulnerability assessments and propose an assessment of inherent vulnerability by using process-based indicators under the current climate. We also suggest periodic assessment of vulnerability, which is necessary to review adaptation strategies for the management of forests and forest carbon stocks.

Assessing ``inherent vulnerability'' of forests: a methodological approach and a case study from Western Ghats, India

The objective of this study is to present a methodological approach to assess the inherent vulnerability of forests and apply it to a case study. Addressing inherent vulnerability, resulting from current stresses, is a necessary step for building resilience to long-term climate change. The proposed approach includes use of analytical framework that enables selection of vulnerability criteria and indicators systematically, application of pairwise comparison method (PCM) for assigning weights, and synthesis of a composite vulnerability index. This methodological approach has been applied at local scale to Aduvalli Protected Forest in Western Ghats in South India, where a vulnerability index value of 0.248 is estimated. Results of the case study indicate that `preponderance of invasive species' and forest dependence of community are the major sources of vulnerability at present for Aduvalli Protected Forest. Adoption of this methodology can assist in development of forest management plans to enhance adaptability of Aduvalli PF to current as well as future stresses, including climate change. This methodological approach can be applied across forest-types after appropriate changes to criteria and indicators and their weights, to estimate the inherent vulnerability to enable development of adaptation strategy.

DECT evaluation of noncalc fied coronary artery plaque

Purpose: Composition of the coronary artery plaque is known to have critical role in heart attack. While calcified plaque can easily be diagnosed by conventional CT, it fails to distinguish between fibrous and lipid rich plaques. In the present paper, the authors discuss the experimental techniques and obtain a numerical algorithm by which the electron density (rho(e)) and the effective atomic number (Z(eff)) can be obtained from the dual energy computed tomography (DECT) data. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques. Methods: For the purpose of calibration of the CT machine, the authors prepare aqueous samples whose calculated values of (rho(e), Z(eff)) lie in the range of (2.65 x 10(23) <= rho(e) <= 3.64 x 10(23)/cm(3)) and (6.80 <= Z(eff) <= 8.90). The authors fill the phantom with these known samples and experimentally determine HU(V-1) and HU(V-2), with V-1,V-2 = 100 and 140 kVp, for the same pixels and thus determine the coefficients of inversion that allow us to determine (rho(e), Z(eff)) from the DECT data. The HU(100) and HU(140) for the coronary artery plaque are obtained by filling the channel of the coronary artery with a viscous solution of methyl cellulose in water, containing 2% contrast. These (rho(e), Z(eff)) values of the coronary artery plaque are used for their characterization on the basis of theoretical models of atomic compositions of the plaque materials. These results are compared with histopathological report. Results: The authors find that the calibration gives Pc with an accuracy of 3.5% while Z(eff) is found within 1% of the actual value, the confidence being 95%. The HU(100) and HU(140) are found to be considerably different for the same plaque at the same position and there is a linear trend between these two HU values. It is noted that pure lipid type plaques are practically nonexistent, and microcalcification, as observed in histopathology, has to be taken into account to explain the nature of the observed (rho(e), Z(eff)) data. This also enables us to judge the composition of the plaque in terms of basic model which considers the plaque to be composed of fibres, lipids, and microcalcification. Conclusions: This simple and reliable method has the potential as an effective modality to investigate the composition of noncalcified coronary artery plaques and thus help in their characterization. In this inversion method, (rho(e), Z(eff)) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (rho(e), Z(eff)) does not interfere with each other and the nature of the plaque can be identified in terms of a three component model. (C) 2015 American Association of Physicists in Medicine.

Multi-scale vulnerability assessment for adaptation planning

Vulnerability of communities and natural ecosystems, to potential impacts of climate change in developing countries like India, and the need for adaptation are rapidly emerging as central issues in the debate around policy responses to climate change. The present study presents an approach to identify and prioritize the most vulnerable districts, villages and households in Karnataka State, through a multi-scale assessment of inherent vulnerability to current climate variability. It also identifies the drivers of inherent vulnerability, thereby providing a tool for developing and mainstreaming adaptation strategies, in ongoing developmental or dedicated adaptation programmes. The multi-scale assessment was made for all 30 districts at the state level in Karnataka, about 1220 villages in Chikballapur district, and at the household level for two villages - Gundlapalli and Saddapalli - in Bagepalli taluk of Chikballapur district. At the district, village and household levels, low levels of education and skills are the dominant factors contributing to vulnerability. At the village and household level, the lack of income diversification and livelihood support institutions are key drivers of vulnerability. The approach of multi-scale vulnerability assessment facilitates identification and prioritization of the drivers of vulnerability at different scales, to focus adaptation interventions to address these drivers.

High impulsivity predicting vulnerability to cocaine addiction in rats: some relationship with novelty preference but not novelty reactivity, anxiety or stress.

RATIONALE: Impulsivity is a vulnerability marker for drug addiction in which other behavioural traits such as anxiety and novelty seeking ('sensation seeking') are also widely present. However, inter-relationships between impulsivity, novelty seeking and anxiety traits are poorly understood. OBJECTIVE: The objective of this paper was to investigate the contribution of novelty seeking and anxiety traits to the expression of behavioural impulsivity in rats. METHODS: Rats were screened on the five-choice serial reaction time task (5-CSRTT) for spontaneously high impulsivity (SHI) and low impulsivity (SLI) and subsequently tested for novelty reactivity and preference, assessed by open-field locomotor activity (OF), novelty place preference (NPP), and novel object recognition (OR). Anxiety was assessed on the elevated plus maze (EPM) both prior to and following the administration of the anxiolytic drug diazepam, and by blood corticosterone levels following forced novelty exposure. Finally, the effects of diazepam on impulsivity and visual attention were assessed in SHI and SLI rats. RESULTS: SHI rats were significantly faster to enter an open arm on the EPM and exhibited preference for novelty in the OR and NPP tests, unlike SLI rats. However, there was no dimensional relationship between impulsivity and either novelty-seeking behaviour, anxiety levels, OF activity or novelty-induced changes in blood corticosterone levels. By contrast, diazepam (0.3-3 mg/kg), whilst not significantly increasing or decreasing impulsivity in SHI and SLI rats, did reduce the contrast in impulsivity between these two groups of animals. CONCLUSIONS: This investigation indicates that behavioural impulsivity in rats on the 5-CSRTT, which predicts vulnerability for cocaine addiction, is distinct from anxiety, novelty reactivity and novelty-induced stress responses, and thus has relevance for the aetiology of drug addiction.

Increase in the density of resting microglia precedes neuritic plaque formation and microglial activation in a transgenic model of Alzheimer's disease

The formation of cerebral senile plaques composed of amyloid beta peptide (A beta) is a fundamental feature of Alzheimer's disease (AD). Glial cells and more specifically microglia become reactive in the presence of A beta. In a triple transgenic model of AD (3 x Tg-AD), we found a significant increase in activated microglia at 12 (by 111%) and 18 (by 88%) months of age when compared with non-transgenic (non-Tg) controls. This microglial activation correlated with A beta plaque formation, and the activation in microglia was closely associated with A beta plaques and smaller A beta deposits. We also found a significant increase in the area density of resting microglia in 3 x Tg-AD animals both at plaque-free stage (at 9 months by 105%) and after the development of A plaques (at 12 months by 54% and at 18 months by 131%). Our results show for the first time that the increase in the density of resting microglia precedes both plaque formation and activation of microglia by extracellular A beta accumulation. We suggest that AD pathology triggers a complex microglial reaction: at the initial stages of the disease the number of resting microglia increases, as if in preparation for the ensuing activation in an attempt to fight the extracellular A beta load that is characteristic of the terminal stages of the disease. Cell Death and Disease (2010) 1, e1; doi:10.1038/cddis.2009.2; published online 14 January 2010

Assessing societal vulnerability of U.S. Pacific Northwest communities to storm induced coastal change

Progressive increases in storm intensities and extreme wave heights have been documented along the U.S. West Coast. Paired with global sea level rise and the potential for an increase in El Niño occurrences, these trends have substantial implications for the vulnerability of coastal communities to natural coastal hazards. Community vulnerability to hazards is characterized by the exposure, sensitivity, and adaptive capacity of human-environmental systems that influence potential impacts. To demonstrate how societal vulnerability to coastal hazards varies with both physical and social factors, we compared community exposure and sensitivity to storm-induced coastal change scenarios in Tillamook (Oregon) and Pacific (Washington) Counties. While both are backed by low-lying coastal dunes, communities in these two counties have experienced different shoreline change histories and have chosen to use the adjacent land in different ways. Therefore, community vulnerability varies significantly between the two counties. Identifying the reasons for this variability can help land-use managers make decisions to increase community resilience and reduce vulnerability in spite of a changing climate. (PDF contains 4 pages)