Adapting our sea ports to the challenges of climate change: Development and validation of a Port Resilience Index

Marine Policy ◽  
2021 ◽  
Vol 130 ◽  
pp. 104573
Author(s):  
Fernando León-Mateos ◽  
Antonio Sartal ◽  
Lucas López-Manuel ◽  
María A. Quintás
Keyword(s):  
Climate Change ◽  
Resilience Index ◽  
Sea Ports ◽  
Development And Validation

scholarly journals Assessing community resilience to natural disaster and climate change in Maitara Island, North Maluku-Indonesia

2018 ◽  
Vol 229 ◽  
pp. 02002
Author(s):  
Mohammad Ridwan Lessy ◽  
Jefry Bemba ◽  
Nani Nagu
Keyword(s):  
Climate Change ◽  
Quantitative Methods ◽  
Secondary Data ◽  
Coastal Communities ◽  
Disaster Mitigation ◽  
Primary Data ◽  
Small Island ◽  
Small Islands ◽  
Human Aspects ◽  
Resilience Index

Small Islands face some of the main problems of any coastal area due to climate change and natural disasters. This study aims to analyze the resilience of coastal communities on a small island in terms of disasters and climate change, and to identify the strategies and adaptations that communities have undertaken as anticipatory for disaster and climate change in the future. Qualitative analysis combined with quantitative methods is used in this research to provide a clear estimate of the categories of resilience in each village. The primary data was collected by using interviews and focus discussion group and secondary data acquired through the documentation on related stakeholders. The resilience index provided by the Ministry of Maritime and Fisheries Affairs is used to categorize the resilience scales of villages. The results of this study show that the human aspects and natural resources aspects have high scores in resilience, but disaster and climate change aspects; environmental/infrastructures aspects; and economic aspects should be improved. Furthermore, the community had been taking participation in disaster mitigation.

scholarly journals Measuring Urban Resilience to Climate Change in Three Chinese Cities

2020 ◽  
Vol 12 (22) ◽  
pp. 9735
Author(s):  
Mingshun Zhang ◽  
Yaguang Yang ◽  
Huanhuan Li ◽  
Meine Pieter van Dijk
Keyword(s):  
Climate Change ◽  
Urban China ◽  
Decision Makers ◽  
Research Needs ◽  
Urban Resilience ◽  
Policy Makers ◽  
Wide Range ◽  
Resilience Index ◽  
Weak Points ◽  
Monitoring Progress

Building an urban resilience index results in developing an increasingly popular tool for monitoring progress towards climate-proof cities. This paper develops an urban resilience index in the context of urban China, which helps planners and policy-makers at city level to identify whether urban development is leading to more resilience. The urban resilience index (URI) suggested in this research uses data on 24 indicators distributed over six URI component indices. While no measure of such a complex phenomenon can be perfect, the URI proved to be effective, useful and robust. Our findings show that the URI ensures access to integrated information on urban resilience to climate change. It allows comparisons of cities in a systematic and quantitative way, and enables identification of strong and weak points related to urban resilience. The URI provides tangible measures of not only overall measures of urban resilience to climate change, but also urban resilience components and related indicators. Therefore, it could meet a wide range of policy and research needs. URI is a helpful tool for urban decision-makers and urban planners to quantify goals, measure progress, benchmark performance, and identify priorities for achieving high urban resilience to climate change.

scholarly journals The Identity Resilience Index: Development and Validation in Two UK Samples

Identity ◽  
2021 ◽  
pp. 1-17
Author(s):  
Glynis M. Breakwell ◽  
Emanuele Fino ◽  
Rusi Jaspal
Keyword(s):  
Index Development ◽  
Resilience Index ◽  
Development And Validation

A Study on the Difference of Urban and Rural Resilience under Climate Change- A Case Study of Chiayi County

2020 ◽  
Author(s):  
Shin-En Pai ◽  
Hsueh-Sheng Chang
Keyword(s):  
Climate Change ◽  
Rural Areas ◽  
Binary Logistic Regression ◽  
International Strategy ◽  
Sendai Framework ◽  
Resilience Index ◽  
The Face ◽  
The Difference ◽  
Urban And Rural Areas ◽  
The Impact

<p>In recent years, the impact of climate change has caused critical risks to urban and rural systems, how to mitigate the damage caused by extreme climate events has become a topic of considerable concern in various countries in recent years. The United Nations International Strategy for Disaster Reduction (UNISDR) mentioned in the Hyogo Framework for Action (HFA) and the Sendai Framework for Disaster Risk Reduction 2015-2030 (Sendai Framework) that improving community resilience will help to deal with the harm caused by climate change. However, most of the previous research on resilience have only focused solely on urban or rural only, and have failed to clearly identify the differences in resilience between urban and rural areas. In fact, if we can understand the difference in resilience between urban and rural in the face of climate change, it will provide planners with better planning strategies or resource allocation. Based on this, the study first developed the resilience index through literature review, and then filtered and screened the index through Principle Component Analysis (PCA). After that, the resilience index was applied to empirical areas, and the spatial correlation of resilience was explored through Local Indicators of Spatial Autocorrelation (LISA). Finally, the binary logistic regression is used to analyze the difference in resilience of urban or rural under climate change.</p>

Development and validation of the anthropogenic climate change dissenter inventory

2016 ◽  
Vol 25 (6) ◽  
pp. 867-882 ◽  
Author(s):  
Andrew P. K. Bentley ◽  
Heather L. Petcovic ◽  
David P. Cassidy
Keyword(s):  
Climate Change ◽  
Anthropogenic Climate Change ◽  
Development And Validation

Possible Impacts of Climate Change on Wind Gusts under Downscaled Future Climate Conditions: Updated for Canada

2014 ◽  
Vol 27 (3) ◽  
pp. 1255-1270 ◽  
Author(s):  
Chad Shouquan Cheng ◽  
Edwina Lopes ◽  
Chao Fu ◽  
Zhiyong Huang
Keyword(s):  
Climate Change ◽  
Simulation Models ◽  
Wind Gust ◽  
Special Report ◽  
Future Projection ◽  
Climate Conditions ◽  
Extreme Wind ◽  
Emissions Scenarios ◽  
Development And Validation ◽  
Impacts Of Climate Change

Abstract The methods used in earlier research focusing on the province of Ontario, Canada, were adapted for the current paper to expand the study area over the entire nation of Canada where various industries (e.g., transportation, agriculture, energy, and commerce) and infrastructure are at risk of being impacted by extreme wind gust events. The possible impacts of climate change on future wind gust events across Canada were assessed using a three-step process: 1) development and validation of hourly and daily wind gust simulation models, 2) statistical downscaling to derive future station-scale hourly wind speed data, and 3) projection of changes in the frequency of future wind gust events. The wind gust simulation models could capture the historically observed daily and hourly wind gust events. For example, the percentage of excellent and good validations for hourly wind gust events ≥90 km h−1 ranges from 62% to 85% across Canada; the corresponding percentage for wind gust events ≥40 km h−1 is about 90%. For future projection, the modeled results indicated that the frequencies of the wind gust events could increase late this century over Canada using the ensemble of the downscaled eight-GCM simulations [Special Report on Emissions Scenarios (SRES) A2 and B1]. For example, the percentage increases in future daily wind gust events ≥70 km h−1 from the current condition could be 10%–20% in most of the regions across Canada; the corresponding increases in future hourly wind gust events ≥70 km h−1 are projected to be 20%–30%. In addition, the inter-GCM and interscenario uncertainties of future wind gust projections were quantitatively assessed.

scholarly journals Livelihoods Strategies and Household Resilience to Food Insecurity: A Case Study from Rural Tunisia

2019 ◽  
Vol 11 (3) ◽  
pp. 907 ◽  
Author(s):  
Mohamed Dhraief ◽  
Boubaker Dhehibi ◽  
Hamed Daly Hassen ◽  
Meriem Zlaoui ◽  
Chaima Khatoui ◽  
...  
Keyword(s):  
Climate Change ◽  
Food Insecurity ◽  
Safety Net ◽  
Food Prices ◽  
Negative Effects ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Resilience Index ◽  
Household Incomes ◽  
Different Levels

Due to the decrease of household incomes, the increase of food prices, and the negative effects of climate change on agricultural production, Tunisia faces a food insecurity challenge, especially in rural and arid areas. The purpose of our research is to understand and explore household resilience to food insecurity in two villages, Selta and Zoghmar, in central Tunisia. A cross-sectional survey of 250 sample households was conducted in the villages. Factor analysis and regression models were employed to analyze the data using SPSS version 21. The results indicate that only around 36% of the households were resilient at different levels. In Selta, 62.8% and in Zoghmar 66.7% of the households were vulnerable. As indicated by the factor loadings and beta coefficients, income and food access, adaptive capacity, and the social safety net were important dimensions of household resilience to food insecurity, being positively correlated with the resilience index. However, asset possession, and climate change negatively affect household resilience. Therefore, interventions must target strategies that address the different levels of resilience reflected by the resilience estimators. These estimators were generated by focusing mainly on building farmers’ knowledge of how to face the different difficulties and challenges.

scholarly journals A global indicator of the capacity of terrestrial ecosystems to retain biological diversity under climate change: the Bioclimatic Ecosystem Resilience Index

2019 ◽  
Author(s):  
Simon Ferrier ◽  
Thomas D Harwood ◽  
Chris Ware ◽  
Andrew J Hoskins
Keyword(s):  
Climate Change ◽  
Biological Diversity ◽  
Spatial Configuration ◽  
Natural Habitat ◽  
Terrestrial Ecosystems ◽  
Ecosystem Resilience ◽  
Forest Change ◽  
Habitat Condition ◽  
Resilience Index ◽  
Projected Changes

AbstractAn important element of the Convention on Biological Diversity’s Aichi Target 15 – i.e. to enhance “ecosystem resilience … through conservation and restoration” – remains largely unaddressed by existing indicators. We here develop an indicator addressing just one of many possible dimensions of ecosystem resilience, by focusing on the capacity of ecosystems to retain biological diversity in the face of ongoing, and uncertain, climate change. The Bioclimatic Ecosystem Resilience Index (BERI) assesses the extent to which a given spatial configuration of natural habitat will promote or hinder climate-induced shifts in biological distributions. The approach uses existing global modelling of spatial turnover in species composition within three broad biological groups (plants, invertebrates and vertebrates) to scale projected changes in composition under a plausible range of climate scenarios. These projections serve as filters through which to analyse the configuration of habitat observed at a given point in time (e.g. for a particular year) – represented as a grid in which cells are scored in terms of habitat condition. BERI is then calculated, for each cell in this grid, as a function of the connectedness of that cell to areas of natural habitat in the surrounding landscape which are projected to support a similar composition of species under climate change to that currently associated with the focal cell. All analyses are performed at 30-arcsecond grid resolution (approximately 1km cells at the equator). Results can then be aggregated to report on status and trends for any desired set of reporting units – e.g. ecoregions, countries, or ecosystem types. We present example outputs for the Moist Tropical Forest Biome, based on a habitat-condition time series derived from the Global Forest Change dataset. We also describe how BERI is now being extended to cover all biomes (forest and non-forest) across the entire terrestrial surface of the planet.

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