This study examines the livelihood vulnerability of a variety of rural households by calculating the livelihood vulnerability index (LVI) with reference to the IPCC vulnerability framework and the sustainable livelihoods framework (SLF). The index consists of household parameters of all the three dimensions of vulnerability such as exposure, sensitivity, and adaptability. Respective indicators were based on a literature review and discussions with residents. We explored the variables with significant explanatory power for households’ LVI by means of a multiple linear regression model using latent variables. Data for desired parameters for LVI was collected from 540 randomly selected households in 35 villages of Gannan Plateau (in the east margin of Qinghai-Tibet Plateau) through face-to-face interviews. The present study highlights that livelihood vulnerability between households with different socioeconomic characteristics is far from equivalent because of uneven exposure, sensitivity, and adaptability of climate change. Moreover, at the regional level, adaptability and exposure have a higher explanatory value than sensitivity. The urgent need to reduce the high exposure to climate risks such as blizzard and drought improve the level of livelihood diversification and enhance the ability of farmers to make flexible use of all kinds of livelihood capital are essentially required for reducing both current and future community vulnerability to climate change and advancing sustainable livelihood. It also facilitates the adaptation strategies of other communities around the globe will face similar ecological and economic challenges as they deal with the impacts of global climate change.

Multiple types of global change processes increasingly impact rural development programs; the interplay between these processes can impact rural livelihoods in unforeseen and surprising ways. To date, most of the studies examining farmers’ risk perceptions and risk management strategies have been agriculture-focused with little attention to their livelihood system. This study introduces the framework of the sustainable livelihood approach (SLA) to examine farmers’ risk perceptions and the risk management strategies of smallholder households in rural China. Based on data collected from a sample of 540 smallholder households, we used descriptive statistics for analyzing and classifying risk sources and risk management strategies. A multinomial logistic regression model is employed to explore the role of livelihood assets in farmers’ preferred risk management strategies. The results find that farmers express higher levels of concern about educational risk, health risk and employment risk. They put more faith in internal coping strategies (e.g. ‘resort to acquaintances’ and ‘sell livestock’) rather than reduction or mitigation strategies (e.g. ‘buy insurance’, ‘employ new techniques’ and ‘diversify income sources’) to manage those risks. Further, these results differ according to the geographical and farmer characteristics. Livelihood assets are likely to affect the choice of the farmers’ preferred risk management strategies.

Analysis of the knowledge structure and the evolution of research topics in specific areas has been the focus of information science (IS). Such analysis helps to enrich interested researchers’ understanding of the functions, activities and evolving constraints of the knowledge domain. This study aims to investigate the knowledge domain associated with the vulnerability assessment in the context of climate change (VACC) research in this fast-growing field between January 1991 and December 2017. A bibliometric approach, along with CiteSpace software, was used to identify and visualize thematic patterns, landmark articles and emerging trends. The data used for the bibliometric analysis include 6,584 original research articles and reviews published between 1991 and 2017. The results indicate that the number of documents pertaining to VACC presented a general growth trend over the last twenty-seven years. Climatic Change was the most productive journal. Among countries, the USA, England and Australia predominated, and the University of Chinese Academy of Sciences and U.S. Geological Survey were the two institutions with the largest amount of VACC research. Existing studies in the field of VACC research have focused primarily on environmental sciences. Importantly, emerging trends in VACC research have shifted away from vulnerability assessments of natural ecosystems based on model simulation methods in the context of climate change toward indicator-based assessments of social ecosystem vulnerability, adaptive capacity and resilience under multidimensional stressors and shocks, which are likely to define the new frontier in the field of VACC research. Analysis of the knowledge structure and the evolution of research topics in specific areas has been the focus of information science (IS). Such analysis helps to enrich interested researchers’ understanding of the functions, activities and evolving constraints of the knowledge domain. This study aims to investigate the knowledge domain associated with the vulnerability assessment in the context of climate change (VACC) research in this fast-growing field between January 1991 and December 2017. A bibliometric approach, along with CiteSpace software, was used to identify and visualize thematic patterns, landmark articles and emerging trends. The data used for the bibliometric analysis include 6,584 original research articles and reviews published between 1991 and 2017. The results indicate that the number of documents pertaining to VACC presented a general growth trend over the last twenty-seven years. Climatic Change was the most productive journal. Among countries, the USA, England and Australia predominated, and the University of Chinese Academy of Sciences and U.S. Geological Survey were the two institutions with the largest amount of VACC research. Existing studies in the field of VACC research have focused primarily on environmental sciences. Importantly, emerging trends in VACC research have shifted away from vulnerability assessments of natural ecosystems based on model simulation methods in the context of climate change toward indicator-based assessments of social ecosystem vulnerability, adaptive capacity and resilience under multidimensional stressors and shocks, which are likely to define the new frontier in the field of VACC research. KNOWLEDGE ORGANIZATION is a forum for all those interested in the organization of knowledge on a universal or a domain-specific scale, using concept-analytical or concept-synthetical approaches, as well as quantitative and qualitative methodologies. KNOWLEDGE ORGANIZATION also addresses the intellectual and automatic compilation and use of classification systems and thesauri in all fields of knowledge, with special attention being given to the problems of terminology. KNOWLEDGE ORGANIZATION publishes original articles, reports on conferences and similar communications, as well as book reviews, letters to the editor, and an extensive annotated bibliography of recent classification and indexing literature. KNOWLEDGE ORGANIZATION should therefore be available at every university and research library of every country, at every information center, at colleges and schools of library and information science, in the hands of everybody interested in the fields mentioned above and thus also at every office for updating information on any topic related to the problems of order in our information-flooded times.

Climate change has major effects on background insect herbivory, but only a few studies have involved long-term investigation, and the effects of wind on bigger insect herbivores such as moths have been largely neglected. We correlated climatic data during the period 2006–2017 with a set of background herbivory data of Culcula panterinaria (Bremer et Grey) derived from a long-term investigation (2007–2017) in the oak forest of Luanchuan county, Henan, China and discuss the impacts of wind speed on background insect herbivory. Background insect herbivory was significantly correlated with wind speed parameters of both the same year and previous year, implying direct and cumulative effects of wind speed on background insect herbivory. Our study offers a new perspective for monitoring and predicting background insect herbivory.

中国正步入深度老龄化与人口流动高活跃性的时代，从人口流动的视角识别人口老龄化的地域类型，对于不同区域更具针对性地落实积极应对人口老龄化国家战略具有重要意义。论文结合人口流动复合指标法与老年人口区位商指数，提出一种划分人口老龄化地域类型的方法。基于第五、六、七次中国人口普查分县数据，对2000—2020年中国县市人口老龄化地域类型进行识别，将其归纳为自然老化型、(逆)替代集聚型、(逆)残留集聚型、(逆)汇合集聚型7类。在此基础上，采用多元线性回归模型，对不同地域类型人口老龄化的形成原因进行分析。结果表明：① 自然老化型县市空间分布范围大幅度收缩，黄淮海地区、云贵高原以及浙江、江西、湖南南部与广西等地区是主要分布区。② 残留集聚型县市分布范围扩展至东北地区、成渝地区、长江中游以及甘肃省大部分地区。逆残留集聚型县市主要分布于珠三角外围、青藏高原和南疆地区。③ 汇合集聚型县市主要为地级市市辖区或县级市；逆汇合集聚型县市集中分布于京津、长三角、珠三角城市群的核心区域。④ 替代集聚型与逆替代集聚型县市主要分布于胡焕庸线西北半壁，替代集聚型县市数量减少，逆替代集聚型县市数量增加。⑤ 自然老化型县市人口老龄化主要决定于区域社会经济发展；汇合集聚、逆汇合集聚县市老龄化主要受人口流入影响；残留集聚、逆残留集聚型县市，人口流出改变了区域老龄化进程；替代集聚与逆替代集聚型县市，人口老龄化进程同时被人口流入与流出所影响。