Identifying the key catastrophic variables of urban social-environmental resilience and early warning signal

A review of social-ecological system vulnerability in desertified regions: Assessment, simulation, and sustainable management

Desertified regions face considerable vulnerability due to the combined effects of climate change and human activities, which threaten regional ecological security and societal development. It is therefore necessary to assess, simulate, and manage the vulnerability of desertified regions from the perspective of the social-ecological system, to support desertification control and sustainable development. This study is a systematic review of the vulnerability of the social-ecological system in desertified regions (SESDR) based on a bibliometric analysis, and a summary of the research progresses in vulnerability assessment, simulation, and sustainable management is provided. It was found that SESDR vulnerability research started relatively late, but has developed rapidly in recent years, with an emphasis on the coupling between natural systems and human activities, and multi-scale interactions and dynamics. Using various indicators at different scales, SESDR vulnerability could be assessed in terms of exposure, sensitivity, and adaptability. Modeling the complex interactions among natural and human factors across multiple scales is essential to simulate the vulnerability dynamics of the SESDR. The sustainable management of SESDR vulnerability focuses on rational spatial planning to achieve the maximum benefits, with the right measures in the right places. Four priority research directions were proposed to develop a better understanding of the mechanisms of vulnerability and smart restoration of desertified land. The findings of this study will enable researchers, land managers, and policymakers to develop a more comprehensive understanding of SESDR vulnerability, thereby enabling them to better address the challenges posed by complex resource and environmental issues.

Enhancing urban ecological resilience through integrated green technology progress: evidence from Chinese cities

The effective resolution of environmental pollution caused by carbon haze through coordinated progress in green technology and urban ecological resilience is a crucial approach towards promoting sustainable development in Chinese cities. In this study, panel data from 281 cities in China from 2007 to 2019 were analyzed using the entropy method and the coupling coordination degree model to determine the coupling coordination degree between green technology progress and urban ecological resilience. The coordinated influence model and threshold model were applied to investigate coupled coordination types and influencing factors. Results indicate that green technology progress levels have shown an upward trend with increasing volatility from east to west and decreasing volatility with urban scale expansion. Ecological resilience levels have also steadily increased, albeit at a reduced rate. The coupling coordination degree of green technology progress and urban ecological resilience has evolved overall from low to high levels; however, the coupling coordination type has regressed to some extent, with most regions exhibiting lagging green technological progress. Pressure resilience has a positive impact on the coupling coordination degree, while state resilience and response resilience have a negative impact. Green technology progress has a dual threshold effect on the coupling coordination degree. By exploring the coupling and coordination mechanism between green technology progress and urban ecological resilience, this study not only facilitates collaborative management of pollutants and greenhouse gases in cities but also provides a comprehensive reference for the construction of an institutional system for collaborative carbon and haze management.

A synthetic water-heat-vegetation biodiversity nexus approach to assess coastal vulnerability in eastern China

Climate change pressure and biodiversity degradation in coastal regions have caused an increase in urban vulnerability. Current coastal vulnerability studies fail to consider the interactions among the perturbations. Increases in such interactions contribute to the indeterminate changes in the ecosystem productivity and impact on human well-being. Therefore, by integrating water, heat, and vegetation biodiversity (WHB) indicators using catastrophe theory in the study, the interaction among subsystems was explored to expound on the multi-effect of the urban. The results showed that (1) the overall vulnerability of China's coastal cities has increased, and high-value areas were mainly distributed in the three southern provinces; (2) the spatial-temporal pattern of vulnerability was highly heterogeneous. As low-low clusters, Shanghai and its surrounding cities exhibited spatial aggregation characteristics; (3) social, physical and financial capitals were the first three main adaptive capacity factors. The distance-based linear model (DistLM) evidenced that per capita GDP, and road density explained about 30 % and 10 % of the difference in vulnerability variation. The proposed framework could help decision-makers detect how vulnerable coastal areas exposed to WHB impacts are, with crucial implications for future sustainable management.

The application of resilience theory in urban development: a literature review

In the complex context of urbanization and climate change, how to improve the resilience of cities to deal with various uncertain and unpredictable threats is a new topic with both theoretical and practical challenges. In this paper, the researches on urban resilience are summarized using the bibliometric analysis combined with the visualization analysis. We provide a systematic and objective review of resilience applied to urban development focusing on its conceptual frameworks, research tendencies, and assessment methods. The analysis results demonstrate that an increasing attention has been given to urban resilience, especially in the field of climate change. The degree of research varies significantly in different countries, with the USA dominating in the number of publications, followed by the UK and China. Scholars' attention to urban resilience in different periods is closely related to the development background and disasters experienced by their countries, but there are also some commonalities. Meanwhile, the multi-dimensional research on urban resilience has been recognized by many scholars. Quantitative assessment tools such as simulation model and optimization model have been widely used to assess the level of urban resilience. Based on this, we put forward the future research trends in this field and provide a potential guide for future application of urban resilience.

Measurement and analysis of regional flood disaster resilience based on a support vector regression model refined by the selfish herd optimizer with elite opposition-based learning

Flood disasters are sudden, frequent, uncertain and highly hazardous natural disasters. The precise identification of the spatiotemporal evolution characteristics, key driving factors and influencing mechanisms of resilience has become a hot spot in disaster risk reduction research. Therefore, the cumulative information contribution rate-Pearson correlation coefficient (CICR- PCC) model is used in this paper to construct a flood disaster resilience index system by quantitative methods, and a support vector regression model refined by the selfish herd optimizer with elite opposition-based learning (EO-SHO-SVR) is built to improve the accuracy of flood disaster resilience evaluation. On this basis, the EO-SHO-SVR model is used to analyze the spatiotemporal evolution of flood disaster resilience in the Jiansanjiang branch of China Beidahuang Agricultural Reclamation Group Co., Ltd. over the past 22 years. In addition, to verify the comprehensive performance of the EO-SHO-SVR model, support vector regression (SVR), imperial competition algorithm-improved support vector regression (ICA-SVR), and unimproved selfish herd optimizer support vector regression (SHO-SVR) models were selected for comparative analysis. The results show that during the study period, the resilience levels reached a plateau of high levels from 1997 to 2018 after experiencing a state of steady low levels followed by increased volatility. Among the investigated factors, land-average flood prevention investment, GDP per capita, agricultural machinery power per unit of arable land, water conservancy project investment as a percentage of GDP, and rainfall are the main driving factors that cause spatiotemporal differences in flood disaster resilience in the study area. Spatially, the resilience levels in the Jiansanjiang branch are ordered as northern farms > southern farms > central farms, and the comprehensive index of resilience shows an increasing trend from west to east. In the model comparison, the EO-SHO-SVR model has outstanding advantages in fitting performance, reliability, rationality and stability, which fully demonstrates that the EO-SHO-SVR model is highly advanced and practical in the measurement of flood disaster resilience. These research results can provide a more accurate evaluation model of regional flood disaster resilience. In addition, they can also provide valuable information for regional flood resilience improvement and flood risk avoidance.

How Are School Menus Evaluated in Different Countries? A Systematic Review

School meals should focus on quality of life issues, particularly on reducing food shortages, overweight, obesity and its consequences. As an essential tool for quality assurance, creating the menu is an activity of great complexity and requires multidisciplinary knowledge. This activity covers the observation of countless aspects of quality, highlighting nutritional, sensory, cultural, hygienic, and sanitary issues, among others. This study aims to identify and analyze instruments and methods to evaluate school menus in different countries. The authors developed specific search strategies for Scopus, Web of Science, Science Direct, Pubmed, Lilacs, ProQuest Global, and Google Scholar. The included studies’ methodological quality was assessed using the statistical analysis and meta-analysis review tool (MASTARI). A total of 16 cross-sectional studies met the inclusion criteria and were analyzed. Brazil and Spain were the countries that presented the highest number of studies (n = 5; 31.25% for each). The majority of the studies have a qualitative approach (n = 12, 75%), and only 25% (n = 4) of the studies present quantitative assessment methods to evaluate school menus. No school menu assessment tools were found to assess all aspects of menu planning. The results show a lack of a methodology or of instruments for evaluating the menus offered for school meals that can contribute to better dietary care offered to students.

Swans and elephants: A typology to capture the challenges of food supply chain risk assessment

As a result of internal or external shocks, food supply chains can transition between existing regimes of assembly and planned activity to situations that are unexpected or unknown. These events can occur without warning, causing stress, shift, even collapse, and impact on business/supply chain viability.

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Black elephants and black swans are of concern in food supply chains.

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Black swans can evolve to grey and white swans with appropriate risk mitigation.

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If supply chain controls become lax, white swans can revert to grey swans.

Sustainable Development of Industry-Environmental System Based on Resilience Perspective

The contradiction between industrial development and ecological environment pressure has been becoming progressively severe. Under this circumstance, more attention has been paid to the balance between industrial economic development and environmental deterioration and resource consumption. Thus, this study takes the development of industry and ecological environment change as an interactive system consideration, and comprehensively evaluates the changes of the industrial–environment system on resilience perspective with innovation. Accordingly, this paper establishes a comprehensive evaluation model. The Environmental Performance Index (EPI) and Industrial Structure Entropy (ISE) were applied to analyze the current environment pressure and industrial conditions. Then, the catastrophe theory was used to evaluate the reasonably established index system for the impact of various factors in the industrial–environment system on the resilience change. Next, the adaptive cycle model was used to analyze the evaluation results and reveals the dynamic change law of the system in the resilience range. Finally, Chengdu was selected as the research area to verify the validity of the whole study. It was found that the resilient change process of Chengdu industry–environmental system accord with the four-stage theory of adaptive cycle model. The resilient level of the city was also improved during the cycle. The result of the study can be useful to future plans and decisions. What is more, understanding the characteristics of each stage will be helpful to determine the reasonable implementation time of each key factor and improve its feedback ability.

Risk assessment for the sustainability of coastal communities: A preliminary study

With communities increasingly concentrated in coastal regions globally, governments and stakeholders call for cohesive risk assessments for future sustainability in the wake of natural hazards. This can only be achieved through risk-based decision-making and smart resources treatment. To provide a basis for such actions, we here propose a risk assessment (RA) framework focusing on the risk-resilience-sustainability nexus. In contrast to focusing on the traditional RA approach, we propose an integrative approach based on hazard, vulnerability, and resilience covering the full spectrum of RA for effective risk reduction. We further explain how the proposed framework can simultaneously provide useful input for resilience management in parallel to achieving certain Sustainable Development Goals (SDGs). We apply this framework for typhoon risk assessment (represented by a Typhoon Risk Index-TRI) of coastal counties of mainland China. Different TRIs e.g. total population, elderly population, non-adult population, and economic status are calculated for each coastal county to supplement multi-objective empirical measures for risk reduction. The RA results show a large spatial heterogeneity in typhoon risk with an increase in the risk from north to south along the coast of mainland China. The comparative results from this study are relevant to the prioritization of different regions for immediate or gradual actions, wise decision-making, and risk reduction through proper treatment of resources-related policy implications. The evaluation of the SDGs achievement status reveals that the overall performance of coastal provinces in mainland China is higher to achieve SDGs 3 and 15 followed by 13 and 8. The study shows that while Guangdong province is in the highest risk category, its achievement status for SDG-13 (climate actions, strengthening resilience) is the lowest relative to other provinces, which is critical. This study represents a major scientific contribution to mainland China's coastal risk management and calls for aligning risk-informed planning and sustainability frameworks.

Understand the resilience and regime shift of the wetland ecosystem after human disturbances

Wetland protection and restoration are important for human's sustainable development, and assess the resilience and regime shift of wetland ecosystem under human disturbances is necessary for this purpose. Geochemical records, including nitrogen (N), phosphorus (P), heavy metals and polycyclic aromatic hydrocarbons (PAHs) from seven wetland cores dated by ²¹⁰Pb and ¹³⁷Cs analysis were used to identify the historical background of human disturbances on wetlands in the Sanjiang Plain. We also carried out paleoecological analysis (including plant macrofossils and diatoms) in one core (Honghe wetland) to reconstruct the successions of wetland ecological communities. The resilience and regime shift of ecosystem were evaluated based on autocorrelation and the Sequential t-test analysis of regime-shifts algorithm. Our results show that enrichment factors (EFs) of N, P and heavy metals (Cu, Zn, Pb etc.), and the concentrations of PAHs experienced slight increases from the 1920s but dramatic increases from the late 1970s. The dominant species of plant community began to change from Drepanocladus aduncus to Carex lasiocarpa from the late 1970s, and the diatoms began to change from wet-indicator to dry-indicator species from the 1950s in Honghe wetland. The regime shift of the wetland ecosystem occurred around 1990 CE, which due to a drop in water level caused by human activities, such as wetland drainage for the reclamation and the excessive use of groundwater for irrigation purpose, rather than climate moisture variations. There is a time gap between the severe disturbances and regime shift due to the stronger resilience of wetland ecosystem. The ecological characteristics (e.g. water level, biological compositions, and EFs of nutrient elements and heavy metals) of Honghe wetland before the late 1970s (release phase) were used as reference conditions for wetland restoration.

Environmental Warning System Based on the DPSIR Model: A Practical and Concise Method for Environmental Assessment

Though we are in urgent need of environmental warnings to slow environmental deterioration, currently, there is no internationally concise method for environmental warnings. In addition, the existing approaches do not combine the three aspects of ecology, resources, and environment. At the same time, the three elements of the environment (air, water, and soil) are separated in most environmental warning systems. Thus, the method this paper gives is an innovative attempt and aims to make environmental assessment more practical. This paper establishes the index system of an environmental early warning based on the Driving–Pressure–State–Influence–Response (DPSIR) model. The Analytic Hierarchy Process (AHP) method was used to determine the weights. Next, single and integrated index methods further assess the environmental warning state, in which the weighted summation method is used to summarize the data and results. The case of Tianjin is used to confirm the applicability of this method. In conclusion, the method in this paper is more well-behaved and, therefore, more suitable to assist cities in their environmental assessment.