Agricultural vulnerability over the Chinese Loess Plateau in response to climate change: Exposure, sensitivity, and adaptive capacity

Li, Xueling; Philp, Joshua; Cremades, Roger; Roberts, Anna; He, Liang; Li, Longhui; Yu, Qiang

doi:10.1007/s13280-015-0727-8

Cited by 39 publications

(18 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cumulative vulnerability index (CVI) in this study was determined as the positive function of EI and SI, but negative function of ACI following Li et al (2015), as under:…”

Section: Cumulative Vulnerability Index (Cvi)mentioning

confidence: 99%

Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India

Krishnan

Ananthan

Jeevamani

et al. 2018

Ambio

View full text Add to dashboard Cite

The impacts of climate change are of particular concern to the coastal region of tropical countries like India, which are exposed to cyclones, floods, tsunami, seawater intrusion, etc. Climate-change adaptation presupposes comprehensive assessment of vulnerability status. Studies so far relied either on remote sensing-based spatial mapping of physical vulnerability or on certain socio-economic aspects with limited scope for upscaling or replication. The current study is an attempt to develop a holistic and robust framework to assess the vulnerability of coastal India at different levels. We propose and estimate cumulative vulnerability index (CVI) as a function of exposure, sensitivity and adaptive capacity, at the village level, using nationally comparable and credible datasets. The exposure index (EI) was determined at the village level by decomposing the spatial multi-hazard maps, while sensitivity (SI) and adaptive capacity indices (ACI) were estimated using 23 indicators, covering social and economic aspects. The indicators were identified through the literature review, expert consultations, opinion survey, and were further validated through statistical tests. The socio-economic vulnerability index (SEVI) was constructed as a function of sensitivity and adaptive capacity for planning grassroot-level interventions and adaptation strategies. The framework was piloted in Sindhudurg, a coastal district in Maharashtra, India. It comprises 317 villages, spread across three taluks viz., Devgad, Malvan and Vengurla. The villages in Sindhudurg were ranked based on this multi-criteria approach. Based on CVI values, 92 villages (30%) in Sindhudurg were identified as highly vulnerable. We propose a decision tool for identifying villages vulnerable to changing climate, based on their level of sensitivity and adaptive capacity in a two-dimensional matrix, thus aiding in planning location-specific interventions. Here, vulnerability indicators are classified and designated as 'drivers' (indicators with significantly high values and intervention priority) and 'buffers' (indicators with low-to-moderate values) at the village level. The framework provides for aggregation or decomposition of CVI and other sub-indices, in order to plan spatial contingency plans and enable swift action for climate adaptation.

show abstract

“…Cumulative vulnerability index (CVI) in this study was determined as the positive function of EI and SI, but negative function of ACI following Li et al (2015), as under:…”

Section: Cumulative Vulnerability Index (Cvi)mentioning

confidence: 99%

Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India

Krishnan

Ananthan

Jeevamani

et al. 2018

Ambio

View full text Add to dashboard Cite

show abstract

“…Wheat is the dominant crop in the Loess Plateau, accounting for 35% of the total planting area [1,2]. Dryland wheat production in Loess Plateau is highly dependent on the timing and extent of rainfall, whereas most of the precipitation is mainly concentrated during the summer fallow period.…”

Section: Introductionmentioning

confidence: 99%

Subsoiling and Sowing Time Influence Soil Water Content, Nitrogen Translocation and Yield of Dryland Winter Wheat

et al. 2019

View full text Add to dashboard Cite

Dryland winter wheat in the Loess Plateau is facing a yield reduction due to a shortage of soil moisture and delayed sowing time. The field experiment was conducted at Loess Plateau in Shanxi, China from 2012 to 2015, to study the effect of subsoiling and conventional tillage and different sowing dates on the soil water storage, Nitrogen (N) accumulation, and remobilization and yield of winter wheat. The results showed that subsoiling significantly improved the soil water storage (0–300 cm soil depth) and increased the contribution of N translocation to grain N and grain yield (17–36%). Delaying sowing time had reduced the soil water storage at sowing and winter accumulated growing degree days by about 180 °C. The contribution of N translocation to grain yield was maximum in glume + spike followed by in leaves and minimum by stem + sheath. Moreover, there was a positive relationship between the N accumulation and translocation and the soil moisture in the 20–300 cm range. Subsoiling during the fallow period and the medium sowing date was beneficial for improving the soil water storage and increased the N translocation to grain, thereby increasing the yield of wheat, especially in a dry year.

show abstract

“…In order to sustain agriculture industry, the Chinese government should take measures on environmental pollution and degradation, climate change and replace with new policies with the environment and ecology-friendly agricultural technologies. Li et al [6] reported that western China was the most vulnerable area, where climate sensitive dry land agriculture was the primary economic activity. The Loess Plateau is a home to an estimated population upwards of 108 million, of which more than 70% are reported to be living and working in agricultural areas.…”

Section: Resultsmentioning

confidence: 99%

Food security and sustainable crops production with considering climate change in China

Shahrajabian

Хесам²,

Sun

et al. 2019

Vestn. Ross. univ. družby nar., Ser. Agron. životnovod.

View full text Add to dashboard Cite

Increase in the mean seasonal temperature can reduce the duration of many crops which may lead to final yield reduction. China needs to cope with the adverse effects of climate change by developing heat and drought resistant high yielding varieties and cultivars to ensure food security in China. Farmers should adapt to climate change strategies which integrate traditional experience and indigenous knowledge with scientific researches and government polices as key factors. Climate change will extend growing seasons for some crops and make shorter growing seasons for other crops in Northern part of China and will bring less reliable rains, soils that retain less water, the spread of dangerous pests and unwanted weeds. The catastrophic consequences of climate change can be avoided if all countries work and cooperate together towards significant reduction in the emission of greenhouse gases.

show abstract

Agricultural vulnerability over the Chinese Loess Plateau in response to climate change: Exposure, sensitivity, and adaptive capacity

Cited by 39 publications

References 25 publications

Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India

Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India

Subsoiling and Sowing Time Influence Soil Water Content, Nitrogen Translocation and Yield of Dryland Winter Wheat

Food security and sustainable crops production with considering climate change in China

Contact Info

Product

Resources

About