Understanding the spatial disparity in socio-economic recovery of coastal communities following typhoon disasters.

The increasing risk of climate change in the Anthropocene underscores the importance and urgency of enhancing resilience to climate-related disasters. However, the assessment of resilience to disasters with traditional statistical data is spatially inexplicit and timeliness inadequate, and the determinants of resilience remain unclear. In this study, we employed spatially detailed daily nighttime light images to assess socio-economic disturbance and track near real-time recovery of coastal communities in Southeast China following super typhoon Meranti. Furthermore, we constructed a "exposure-sensitivity-adaptive capacity" framework to explore the role of key factors in shaping spatiotemporal patterns of recovery. Our case study showed a significant spatial disparity in socio-economic recovery in the post-typhoon period. Low-urbanized areas recovered relatively rapidly with the weakest socio-economic disturbance they suffered, and middle-urbanized areas experienced the slowest recovery despite the disruption being moderate. Remarkably, high-urbanized areas were the most severely impacted by the typhoon but recovered fast. The exposure to hazard, socio-economic sensitivity, and adaptive capacity in communities explained well the spatial disparity of resilience to the typhoon. Maximum wind speed, percentage of the elderly, and percentage of low-income population significantly negatively correlated with resilience, whereas commercial activity intensity, spatial accessibility of hospitals, drainage capacity, and percentage of green open space showed significantly positive relationships with resilience. Notably, the effects of key factors on resilience were spatially heterogeneous. For instance, maximum wind speed exhibited the strongest influence on resilience in middle-urbanized areas, while the effect of commercial activity intensity was most pronounced in low-urbanized areas. Conversely, spatial accessibility of hospitals and drainage capacity showed the strongest influence in high-urbanized areas. Our study highlights the necessity of linking post-disaster recovery with intensity of hazard, socio-economic sensitivity, and adaptive capacity to understand community resilience for better disaster risk reduction.

Assessing Agricultural Livelihood Vulnerability to Climate Change in Coastal Bangladesh.

The adverse impacts of climate change exert mounting pressure on agriculture-dependent livelihoods of many developing and developed nations. However, integrated and spatially specific vulnerability assessments in less-developed countries like Bangladesh are rare, and insufficient to support the decision-making needed for climate-change resilience. Here, we develop an agricultural livelihood vulnerability index (ALVI) and an integrated approach, allowing for (i) mapping out the hot spots of vulnerability distribution; (ii) identifying key factors of spatially heterogeneous vulnerability; and (iii) supporting intervention planning for adaptation. This study conceptualized vulnerability as a function of exposure, sensitivity, and adaptive capacity by developing a composite index from a reliable dataset of 64 indicators comprising biophysical, agro-ecological, and socioeconomic variables. The empirical studies of coastal Bangladesh revealed that Bhola, Patuakhali, and Lakshmipur districts, around the mouth of the deltaic Meghna estuaries, are the hot spot of vulnerability distribution. Furthermore, the spatially heterogeneous vulnerability was triggered by spatial variation of erosion, cyclones, drought, rain-fed agriculture, land degradation, soil phosphorus, crop productivity, sanitation and housing condition, infant mortality, emergency shelters, adoption of agro-technology. The integrated approach could be useful for monitoring and evaluating the effectiveness of adaptation intervention by substituting various hypothetical scenarios into the ALVI framework for baseline comparison.

Comprehensive Environmental Assessment of Potato as Staple Food Policy in China.

The Chinese government projected 30% of total consumed potatoes as a staple food (PSF) by 2020. We comprehensively assessed the potential impacts of PSF on rice and flour consumption, rice and wheat planting, energy and nutrient supply, irrigation-water, chemical nitrogen (N), phosphorus pentoxide (P2O5) and potassium oxide (K2O) fertilizer inputs and total greenhouse gases (GHG) emission for potatoes, rice and wheat, by assuming different proportions of potato substitutes for rice and flour. The results showed that per capita, 2.9 ± 0.3 and 4.7 ± 0.5 kg more potatoes per year would enter the Chinese staple-food diet, under the government's target. PSF consumed are expected to reach 5.2 ± 0.7 Tg yr-1, equivalent to substituting potatoes for 4.2 ± 0.8-8.5 ± 0.8 Tg yr-1 wheat and 5.1 ± 0.9-10.1 ± 1.8 Tg yr-1 rice under different scenarios. While this substitution can increase the nutrient supply index by 63% towards nutrient reference values, it may induce no significant effect on staple-food energy supply with lower chemical fertilizer (except for K2O) and irrigation-water inputs and GHG emissions in different substitution scenarios than the business as usual scenario. The reduction in rice and wheat demands lead to wheat in the North China Plain and early rice decrease by 6.1-11.4% and 12.1-24.1%, respectively. The total GHG reduction is equal to 1.1-9.0% of CO2 equivalent associated with CH4 and N2O emitted from the Chinese agroecosystem in 2005. The saved irrigation water for three crops compared to 2012 reaches the total water use of 17.9 ± 4.9-21.8 ± 5.9 million people in 2015. More N fertilizer, irrigation-water, and GHG can be reduced, if the PSF ratio is increased to 50% together with potato yield improves to the optimal level. Our results implied that the PSF policy is worth doing not only because of the healthier diets, but also to mitigate resource inputs and GHG emissions and it also supports agricultural structure adjustments in the areas of irrigated wheat on the North China Plain and early rice across China, designed to increase the adaptability to climate change.

Driving forces of nitrogen flows and nitrogen use efficiency of food systems in seven Chinese cities, 1990 to 2015.

The effects of population growth (PG), dietary changes (DC), native rural-to-urban migration (NM), migration from regions distant from the cities (M), and agricultural patterns and practices (AP) on N use in food systems and the food trade, and on apparent and virtual nitrogen (N) and N use efficiencies (NUE), at the city scale, are not well understood. Here we selected seven Chinese cities as the study subjects, analyzed the food trade effects on apparent and virtual N inputs and NUE, and quantified the relative magnitudes of these factors on N inputs to cities' food systems during 1990-2015, by designing several scenarios. Our results show that food-sink cities are relying more and more on external food and feed, but in 2015 they transferred 33.8-74.9% of their N input for food or feed productions to areas outside their boundaries, and the food trade showed different effects on the virtual N cost of food N consumption. Apparent NUEs of food systems were 33.1-74.9% higher than those calculated from virtual N costs in Beijing, Tianjin, Shanghai, Lanzhou and Xiamen in 2015. But in cities that export large amounts of food and feed-for example, Chongqing and Changchun-apparent NUE was underestimated by 4.0-46.4% relative to virtual NUE. Native PG, DC, NM, M, and AP accounted for 1.2-14.1%, -6.6-30.0%, 0.6-8.2%, -7.7-131.0%, and -43.8-12.8%, respectively, of the increase in virtual N inputs associated with cities' food systems in 2015, compared to 1990. Our study concludes that M, DC, and AP changes should be considered for mitigating N input in these Chinese cities, and virtual N exports induced by the food trade should also be included if the city is a net food exporter. Selective food trade could help improve the NUE of cities' food systems, and virtual NUE should be used as an indicator, rather than apparent NUE.