Contents lists available at ScienceDirect Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind Original Articles Extent of vulnerability in wheat producing agro-ecologies of India: Tracking from indicators of cross-section and multi-dimension data R. Sendhil a, ⁎ , Ankita Jha b , Anuj Kumar c , Satyavir Singh c a Scientist (Agricultural Economics), Social Sciences, ICAR-Indian Institute of Wheat and Barley Research, Karnal 132 001, Haryana, India b Scientist (Agricultural Meteorology), Resource Management, ICAR-Indian Institute of Wheat and Barley Research, Karnal 132 001, Haryana, India c Principal Scientist (Agricultural Extension), Social Sciences, ICAR-Indian Institute of Wheat and Barley Research, Karnal 132 001, Haryana, India ARTICLE INFO Keywords: Wheat Climate vulnerability Principal component analysis Climate smart farming ABSTRACT India’s geography, monsoon dependency and weather anomalies place wheat production prospects and sus- tainability at crossroads across agro-ecologies owing to its vulnerability. An attempt has been made to track the vulnerability in wheat producing regions for climate smart farming in India sourcing relevant historical data on multi-dimensional indicators for sensitivity, exposure and adaptive capacity. The composite vulnerability index has been estimated for 16 wheat growing states using the Intergovernmental Panel on Climate Change (IPCC) approach. First, the variables were normalised to make them unit free for comparison and second, weights were assigned to each variable across three dimensions (sensitivity, exposure and adaptive capacity) using the prin- cipal component analysis. Later, the regions were categorised into three groups based on the magnitude of the index viz., high, moderate, and less. Jharkhand registered the highest sensitivity (0.61) while Punjab registered the lowest (0.18). Considering the exposure of regions to various climatic and weather variables in the wheat growing season (Rabi: November-April), it was found that Jharkhand had the highest exposure (0.48) and Punjab witnessed the lowest (0.30). In terms of adaptation to climate change, it was found that Maharashtra (0.63) had the highest adaptive capacity, followed by Haryana and Punjab. On the contrary, Jharkhand had the lowest adaptive capacity (0.21). Overall, the analysis of cross-sectional and multi-dimensional data indicated that Jharkhand is the most vulnerable region and Punjab is the least vulnerable region across wheat producing ecologies. Vulnerability mapping indicated that the magnitude of vulnerability is high in five regions (con- tributing 19% of total production), moderate in six regions (12% production) and low in five wheat growing regions (69% production). Regional prioritization has to be made in lieu of deviation in area and yield to minimize production losses. Further, adaptive measures and climate smart farming need to be practiced at farm and regional levels by formulating suitable policies and investment plans. 1. Introduction Global warming is one of the alarming issues of the 21 st century and the mean temperature is expected to increase more in the near future. Anthropogenic green house gas (GHG) emissions have increased since pre-industrial era and have led to unparalleled atmospheric con- centrations of carbon dioxide, methane and nitrous oxide (Climate Change, 2014). Burning of fossil fuels and land use changes has boosted the quantities of GHGs and has the potential to alter the present climate system. The Intergovernmental Panel on Climate Change (IPCC) which was established during 1988 in response to the widespread human in- duced GHG emissions reported that among others, agriculture sector is going to be affected in a larger scale due to its vulnerable nature to climate change. The adverse effects are going to be more in the developing countries (Kato et al., 2011). However, the impact on pro- ductivity will be different among crops and regions. The yield levels are projected to increase and extend northwards, especially for cereals and winter crops in mid and high latitudes (Maracchi et al., 2005; Tuck et al., 2006; Olesen et al., 2007). Crops prevalent in plains of southern Europe viz. maize, sunflower and soybean could also become feasible at higher altitudes (Hildén et al., 2005; Audsley et al., 2006; Olesen et al., 2007). In this scenario, crop yield could increase by as much as 30% by 2050s, (Alexandrov et al., 2002; Ewert et al., 2005; Richter and Semenov, 2005; Audsley et al., 2006; Olesen et al., 2007). In wheat, the cereal with maximum acreage in the world, climate change strongly influences the yield (Rao and Sinha, 1994; Ortiz et al., 2008) because of its sensitivity (Sendhil et al., 2016). The future climate scenarios evince that global warming may be beneficial in some https://doi.org/10.1016/j.ecolind.2018.02.053 Received 1 January 2018; Received in revised form 17 February 2018; Accepted 22 February 2018 ⁎ Corresponding author. E-mail address: r.sendhil@icar.gov.in (R. Sendhil). Ecological Indicators 89 (2018) 771–780 1470-160X/ © 2018 Elsevier Ltd. All rights reserved. T