Abstract

This study assessed the resilience of a Community-Based Forest Management (CBFM) community in Ligao, Albay, Philippines to weather-related disasters. Resiliency was measured using 38 indicators comprising human, social, natural, financial, and physical capitals. The study used household survey administered to 180 respondents, complemented by focus group discussions (FGD), key informant interviews (KII), and secondary data gathering. Index of five capital assets was calculated using the equation for data normalization by a scale of 0 to 1. The overall resiliency index was estimated by getting the weighted average of all the capital assets. Pearson Correlation, Chi-square and Spearman Correlation were used to analyze the relationship of age, gender, and household size to the overall resiliency of the community. The CBFM community is less resilient with an index of 0.382. This was attributed to a lesser access to social and natural capitals with indices of 0.233 and 0.244, respectively. However, the CBFM program remains a promising strategy in improving the adaptive capacity of upland communities by contributing to the enhancement of their social and natural assets. Results revealed that there is a positive correlation between household size and resiliency while age and gender were not correlated. To build resiliency, it is recommended to increase community capacity through education and skills development, ensure access to services, provide technical and financial support from the government and promote collaboration among various stakeholders.

Highlights

  • Climate change is indisputable as exhibited by gradual changes in mean temperature and precipitation patterns, sea level rise, increased frequency of extreme weather-related events, and potentially catastrophic transformations of ecosystems (IPCC, 2007)

  • Pearson Correlation was used to analyze the relationship of resiliency with age

  • Spearman Correlation was used to analyze the relationship of resiliency with household size, which did not follow a normal distribution

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Summary

Introduction

Climate change is indisputable as exhibited by gradual changes in mean temperature and precipitation patterns, sea level rise, increased frequency of extreme weather-related events, and potentially catastrophic transformations of ecosystems (IPCC, 2007). These changes will increase the probability of extreme weather events which may be associated either with high precipitation (i.e., storms, flood and landslides) or with low precipitation (i.e., drought, heat and wildfire) (Keim, 2008). The country continuously faces the threat of extreme events as identified in the Climate Risk Index (CRI) (Harmeling, 2009)

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