Dr Joan Pauline Talubo

Resilience is a multi-faceted concept that traces its evolution based on the field of discipline wherein it was used. Various researchers have defined the term throughout the years according to their own expertise. This has impacted the development and evolution of the concept and how it was used in each specific discipline. One of the most recent and important use of the term is in the disaster paradigm. This paper traces the evolution of the definition of resilience and narrows it down to the disaster realm, eventually focusing on small islands as a socio-ecological system. It also discusses the relationship of resilience with vulnerability and enumerates the various tools and methods that have been used to measure both concepts. This review also presents an integration which identifies social, economic and ecological resilience as the different facets of disaster resilience of small islands. This paper reveals that there are gaps in defining disaster resilience of small islands through a socio-ecological systems approach. Moreover, there are few studies on using the participatory approach for determining indicators of disaster resilience which contributes to a research-policy gap in resilience studies. The paper recommends a strong future research direction on how to translate research findings into a tool that could help communities at the local level, especially those living in small islands.

Despite the existence of a wide range of literature on indicators of disaster resilience in various geographical contexts that have been developed by different agencies and academia, not much has been done to include the insights of practitioners at the local level. This paper seeks to address the lack of practitioner insight and perspective by proposing a mixed methodology in developing composite indicators for the resilience of an island community to disasters. We used a combination of participatory approaches, such as semi-structured interviews with key informants, the web-based Delphi method, and expert interviews through a case study site in the Philippines—the Batanes island province. Principal Component Analysis (PCA) was utilized to analyse the data from web-Delphi, and the results from the content analysis of the interviews were used to support these findings. From a broad list of 144 indicators, the process identified 22 composite indicators for assessing the disaster resilience of an island community. We conclude that the development of new approaches for assessing disaster resilience of island communities is a positive step towards a better understanding and operationalization of the concept of resilience. The process followed in this paper is a significant milestone in developing new approaches to answer the question of what makes an island community resilient to disasters

Disaster resilience is an encompassing concept, which refers to the capacity of a society to bounce back after a disaster, the level of preparedness to face this disaster and the ability to quickly and successfully recover. It has been established that the unit of analysis of resilience has become the socio-ecological system since resilience is a system concept. A socio-ecological system (SES) is a system that includes both the human (societal) and biophysical (ecological) subsystems that are in mutual interaction with each other. Hence, a small island can be considered as a socio-ecological system and was used as the unit of analysis in this paper. This paper integrates three specific facets of disaster resilience namely, social, ecological and economic by means of developing a conceptual framework. Indicators in each of these three aspects were analysed through multi-criteria decision analysis (MCDA). The indicators include socio-demographic profile, economic activities and physical characteristics of the case study area. The integrated approach will help in looking at disaster resilience of small islands with an interdisciplinary perspective. A set of sample indicators in the three aspects were selected based on literature and the existing secondary data. The relationship of the indicators included in the dataset was analysed using Pearson’s Correlation. Analytical Hierarchy Process (AHP) was used to compute for the weights of the indicators. A disaster resilience index for each municipality was computed using the summation of the product of the normalized value of the indicator and the weight derived from AHP. The Basco municipality emerged as the most resilient among the six municipalities in the province with a resilience index of 1.42, while Sabtang is the least resilient with a disaster resilience index of 0.35.  Basco is the capital of the province, has the biggest population and also the center of commerce and trade and where the provincial government institutions area located, while Sabtang has the second highest poverty incidence and the least area for agriculture.