loss and damage from typhoon-induced floods and landslides in the philippines: community perceptions...

Int. J. Global Warming, Vol. 9, No. 1, 2016 33

Copyright © 2016 Inderscience Enterprises Ltd.

Loss and damage from typhoon-induced floods and landslides in the Philippines: community perceptions on climate impacts and adaptation options

Lilibeth A. Acosta* Potsdam Institute for Climate Impact Research (PIK), Telegraphenberg A62, 14473 Potsdam, Germany and School of Environmental Science and Management, University of the Philippines in Los Banos (UPLB), Philippines Email: [email protected] *Corresponding author

Elena A. Eugenio School of Environmental Science and Management, Institute of Biological Sciences, College of Arts and Sciences, University of the Philippines in Los Banos, Philippines Email: [email protected]

Paula Beatrice M. Macandog and Damasa B. Magcale-Macandog Institute of Biological Sciences, College of Arts and Sciences, University of the Philippines in Los Banos, Philippines Email: [email protected] Email: [email protected]

Elaine Kuan-Hui Lin George Perkins Marsh Institute, Clark University, USA and Center for Sustainability Science, Academia Sinica, Taiwan Email: [email protected]

34 L.A. Acosta et al.

Edwin R. Abucay and Alfi Lorenz Cura Department of Community and Environmental Resource Planning, College of Human Ecology, University of the Philippines in Los Banos, Philippines Email: [email protected] Email: [email protected]

Mary Grace Primavera Institute of Biological Sciences (IBS), College of Arts and Sciences, University of the Philippines in Los Banos, Philippines Email: [email protected]

Abstract: Loss and damage from floods and landslides are escalating in the Philippines due to increasing frequency and intensity of typhoons. This paper investigates the types and scale of loss and damage in two municipalities that were affected by typhoon-induced floods and landslides in 2004 and 2012. It assesses people’s preferences on adaptation measures and perceptions on human-nature links on occurrence of disasters. It reveals that human loss and property damage are causing psychological distress to affected people, undermining capacity to adapt to the next disasters. Many vulnerable people are not aware of the link between climate and land use change. Moreover, many depend on unsustainable land use for source of livelihoods particularly after disasters. The preference for measures to reduce landslide risks through reforestation and logging/mining prevention is thus low. Insurance is not a preferred mechanism for reducing risks because regular payment of premium is not affordable to vulnerable people.

Keywords: adaptation; adaptive capacity; climate change; conjoint analysis; disasters; floods and landslides; Haiyan; loss and damage; mitigation; Philippines; risks; typhoons.

Reference to this paper should be made as follows: Acosta, L.A., Eugenio, E.A., Macandog, P.B.M., Magcale-Macandog, D.B., Lin, E.K-H., Abucay, E.R., Cura, A.L. and Primavera, M.G. (2016) ‘Loss and damage from typhoon-induced floods and landslides in the Philippines: community perceptions on climate impacts and adaptation options’, Int. J. Global Warming, Vol. 9, No. 1, pp.33–65.

Biographical notes: Lilibeth A. Acosta is Senior Scientist in PIK and Scientific Coordinator/Adjunct Professor in UPLB. She completed her degrees in the fields of agriculture, development and economics from UPLB in the Philippines (BSc), University of Cambridge in England (MPhil) and University of Bonn in Germany (PhD). Her fields of expertise include sustainability and vulnerability in the context of climatic, economic and land-use changes with special focus on mitigation and adaptation, bioenergy and biodiversity, and rural development and food security. She conducts integrated assessment modelling using statistical (e.g., cluster, conjoint, logit, path analyses), fuzzy logic, GIS, linear programming and agent-based techniques.

Loss and damage from typhoon-induced floods and landslides 35

Elena A. Eugenio is a Research Associate in UPLB. She earned her Bachelor of Science in Plant Pathology from the Department of Agriculture and is currently taking up her Master in Environmental Science in the School of Environmental Science and Management in UPLB. She is currently collaborating in international and interdisciplinary projects on integrated sustainability assessment of bioenergy potentials and livelihood vulnerabilities to typhoon associated hazards in Asia. She coordinates online and field surveys and conducts statistical analysis in these projects.

Paula Beatrice M. Macandog is a Research Associate in UPLB. She earned her Bachelor of Science in Economics cum laude and Master of Science in Agricultural Economics from UPLB. She is conducting researches on payments for ecosystem services (PES) in the Philippines to estimate willingness to pay of households for ecosystem services from agroforestry systems, integrated sustainability assessment of bioenergy potentials, and livelihoods vulnerabilities to typhoon associated hazards in Asia.

Damasa B. Magcale-Macandog is a Professor in UPLB. She earned her Doctoral in Botany (Plant Ecology) from the University of New England in Australia; Master of Science in Soil Science (soil fertility) and Bachelor of Science in Agriculture (major in soil science) from UPLB. She has been conducting various researches related to agricultural, biological, agroforestry, ecological, land use change, climate change, bioenergy and biodiversity studies for the past twenty years.

Elaine Kuan-Hui Lin earned her PhD degree from the National Taiwan University and did her post-doctoral research in Clark University, USA. She is currently a Research Scientist in George Perkins Marsh Institute and a visiting scholar in IRDR-ICoD in Taipei. Over these years, she has been devoted to studying the philosophy and theoretical development of vulnerability and adaptation studies and applied the threads of thoughts on observing vulnerabilities of rural communities, particularly in central-northern mountain of Taiwan and more recently in the Philippines, where people are confronted with severe typhoon and associated geological hazards.

Edwin R. Abucay holds an MS in Environmental Science and is currently an Assistant Professor in UPLB. He has more than ten years of research experience in locally and internationally funded projects. His expertise include geographic information system and remote sensing in environmental and resource management; vulnerability assessments related to climate change; land use planning; watershed management; land use change analysis; agent-based modelling; indigenous knowledge on agriculture and environment; environmental and ecological modelling; information and database development, management and programming.

Alfi Lorenz Cura is a graduating student of Bachelor of Science in Human Ecology Major in Human Settlements Planning in UPLB. He conducted and co-authored in several studies and researches about the community, ecoprofile and scalogram analysis, and community’s integrated development plan. He just recently published his undergraduate thesis about post-disaster response and land use management in New Bataan, Compostela Valley.

Mary Grace Primavera earned her BS in Computer Science from UPLB and currently works as Research Assistant in the Institute of Biological Sciences, College of Arts and Sciences in UPLB.


1 Introduction

Catastrophic reports on natural disasters like drought, heat waves, storm/cyclones, floods and landslides are one of the most common media headlines worldwide. Since 1970s the Centre for Research on the Epidemiology of Disasters (CRED) through its Emergency Events Database (EM-DAT) has been recording losses and damages in different countries from these disaster events among others number of killed or affected people and costs of economic damage. EM-DAT statistics show that major drought and storm disasters between 1900 and 2014 occurred in least developed and less developing countries (CRED, 2014), where people have lower capacity to adapt (Warner and Geest, 2013) or where regions are close to vulnerability thresholds (Acosta-Michlik et al., 2008; Acosta and Galli, 2013). While the increasing frequency and intensity of these disasters have been confirmed and affirmed to be impacts of anthropogenic climate change, human loss and economic damage that results from them have not been appropriately compensated by developed countries (Stabinsky et al., 2012), which are largely responsible for higher anthropogenic emissions (den Elzen et al., 2013). International organisations (i.e., ActionAid, CARE International, Germanwatch and WWF) have emphasised that in some countries the magnitude of impacts on land, property, ecosystems and communities will cause irreversible losses that will prevent return to normal life even with effective mitigation and adaptation measures (Sharman et al., 2012).

For many years global climate change negotiations under the UN Framework on Climate Change Convention (UNFCCC) have focused on the need for enhancing understanding of how to assess and address loss and damage. The idea on loss and damage has been discussed in several climate negotiations in Conference of Parties or COP (e.g., 2007 Bali COP13, 2010 Cancún COP16, 2011 Durban COP17, 2012 Qatar COP18, and 2013 Warsaw COP19). In the last conference in Warsaw, there was an official mandate to establish institutional arrangements to address loss and damage associated with the impacts of climate change including functions and modalities, which will be supported by the work of the UNFCCC in this area (Warner et al., 2013). There was a suggestion to establish an International Mechanism on Compensation and Rehabilitation to provide comprehensive framework on loss and damage and to address four distinct types of permanent loss and damage (Stabinsky et al., 2012):

1 loss and damage that can be addressed through insurance or other risk-transfer mechanisms

2 economic loss and damage from extreme events and slow-onset processes not covered through risk-transfer mechanisms

3 economic loss that is difficult to quantify

4 non-economic losses such as loss of ecosystems, cultural heritage, values, and local and indigenous knowledge.


Despite the discussions on loss and damage assessments and the suggestion to establish loss and damage compensation framework, there are no universally agreed definition for the term ‘loss and damage’ (Nishat et al., 2013; Roberts et al., 2014). Below are few definitions for loss and damage in the field of climate change:

• effects that would not have happened in a world without climate change, which have not been mitigated, and which cannot be (or have not been) adapted to (Craeynest, 2010)

• entire range of damage and permanent loss ‘associated with climate change impacts in developing countries that are particularly vulnerable to the adverse effects of climate change’ that can no longer be avoided through mitigation nor can be avoided through adaptation (Hoffmaister and Stabinsky, 2012)

• negative effects of climate variability and climate change that people have not been able to cope with or adapt to (Warner and Geest 2013)

• adverse effects of climate variability and climate change that occur despite global mitigation and local adaptation efforts (van Der Geest et al., 2014).

Behind these definitions is the assumption that mitigation and/or adaptation measures were inadequate or ineffective. Nishat et al. (2013) explained that the failure of both mitigation and adaptation efforts to minimise the impacts of climate change resulted in the emergence and increasing prominence of loss and damage in the international climate negotiations.

Establishing an operational structure and procedure like the Warsaw compensation mechanism will require assessments on what loss and damage would mean not only to the climate negotiators but more importantly to the affected people. To provide factual assessments that will be useful for policy discussions and negotiations to address loss and damage, case studies were conducted in nine countries including Bangladesh (Rabbani et al., 2013), Bhutan (Kusters and Wangdi, 2013), Burkina Faso (Traore and Owiyo, 2013), Ethiopia (Haile et al., 2013), Gambia (Yaffa, 2013), Kenya (Opondo, 2013), Micronesia (Monnereau and Abraham, 2013), Mozambique (Brida et al., 2013) and Nepal (Bauer, 2013). The overall aim of these studies was to understand the patterns of loss and damage in human systems when there are barriers and constraints to adaptation (Warner and Geest, 2013). The assessments were conducted using both qualitative and quantitative research tools based on a working definition of loss and damage of Warner et al. (2013). Empirical evidence from these case studies shows that loss and damage occurs when there are barriers that impede planning and implementation of adaptation, and when physical and social limits to adaptation are reached or exceeded. While these studies have provided initial insights on assessing loss and damage, substantiation from other parts of the world that are equally, if not more, vulnerable to climate change impacts should be further collected and investigated to help develop globally acceptable framework on loss and damage. This paper thus aims to provide additional evidences on loss and damage from and recommendations on compensation and rehabilitation framework for one of the most typhoon-risk countries in the world – the Philippines. In view of the damaging impacts of typhoons, the CRED has listed the Philippines as the world’s most disaster-prone country in 2009. But typhoon Haiyan in 2013, which is the world’s strongest storm recorded at landfall, showed that typhoons can become


horrifyingly devastating and thus pushing even the most typhoon-resilient people into its social, economic, ecological and even psychological limits.

The paper presents case studies in two municipalities (i.e., Infanta, Quezon and New Bataan, Compostela Valley) in the Philippines that experience typhoon-induced floods and landslides. It aims to understand how the extent of loss and damage affects the preferences and opinions of flood- and landslide-affected communities on adaptation options and strategies. The knowledge will inform how relevant are the four types of permanent loss and damage suggested above to the affected people in the Philippines. The paper is organised as follows: Section 2 provides an overview of the typhoons and disasters in the Philippines in the last two decades; Section 3 describes the assessment methods in the two municipalities; Section 4 presents and discusses the results of loss and damage assessments; and Section 5 provides conclusions and recommendations.

2 Philippine typhoons and disasters

Floods and landslides are most frequently occurring natural disasters, accounting for the largest share 49.4% of natural disasters, 51.9% of total disaster victims, 42.2% of the total reported number of people killed and 16.3% of total damages globally in 2012 (CRED, 2014). They are classified as hydrological disasters. In the Philippines, floods and landslides are closely related to typhoon events, which are classified as meteorological disasters. Typhoon-induced floods and landslides are caused by heavy rainfalls. The Philippine is considered to be one of the disaster prone countries in the world due to its geo-physical location and socio-economic conditions. According to the German Watch (Kreft and Eckstein, 2014), the Philippine ranks second in its 2012 Climate Risk Index, which indicates the level of exposure and vulnerability to extreme events and should be understood as warning to be prepared for more frequent and/or more severe events in the future. The Philippines’ exposure to disasters is to a significant extent due to the country’s geographical and physical characteristics, lying along the world’s busiest typhoon belt and on vastness of warm ocean water in Western Pacific Ocean (ADPC, 2003). With its more than 7,000 islands and with long bare coastlines due to mangrove destructions, the Philippines is vulnerable to storm surges. Mangrove forests play an important role in ecosystems because they provide buffer protection for coastal communities from storm surge and sea level rise. Over the past 50 years, the Philippines has lost up to 80% of its mangrove forests through aquaculture and commercial fish farming, human settlement and economic infrastructure (Endangered Species, 2014). Most of the typhoon-induced floods and landslides were however caused by large scale upland deforestation, many through uncontrolled illegal logging or mining and shifting cultivation (Pulhin and Inoue, 2008; Lasco and Pulhin, 2009; Pulhin and Dressler, 2009). Half of the 20 million Filipinos living in upland forest watershed areas are dependent on shifting cultivation for their livelihood (Lasco et al., 2001). The forest cover in the Philippines has declined continuously by an average of 150,000 hectares per year (Lasco and Pulhin, 2009), decreasing from the estimated 27.5 million hectares in 1900 to only 6.7 million hectares in 1990 (GTZ and DENR, 2009).


An average of 20 typhoons makes a landfall in the Philippines every year. The Annex presents the most destructive typhoons that caused floods and landslides, which in turn caused severe destruction of houses and livelihoods as well as injuries and deaths of people in the country since 1990. Not only the intensity of typhoons but also the loss and damage have been increasing in the last two decades. For example, the most devastating typhoon (i.e., Mike) that hit the Philippines in the 1990s has affected 5.5 million people and damaged 50,000 houses (Annex). In 2012, Bopha has been considered ‘super typhoon’ with a Category 5 typhoon, the highest scale under the Saffir-Simpson Hurricane Wind Scale (NOAA, 2012). The winds had an average speed of 185 km/hr and gusts reached 210 km/hr. It was considered the most powerful typhoon for over a century until 2012, affecting more than 6 million people, killing at least 1,000 people, damaging more than 200,000 houses, and destroying about 1 billion US$ of agricultural products, infrastructure and private properties in Eastern Mindanao [NDRRMC (2012) as cited in Manuta (2013)]. But just a year after, experience from Haiyan revealed that typhoon intensity can be even more devastating, leaving traumatic experience to larger number of population. According to NOAA (2014), Typhoon Haiyan, which hit the eastern Visayas region of the Philippines on the 8th of November 2013, may be the strongest recorded tropical cyclone to make landfall with sustained speed up to 195 mph (315 km/h). It affected 16 million people, damaged over 1 million houses and caused at least 6,000 deaths (Annex). The economic damage is estimated to be at least 10 billion US$, which is equivalent to around 5% of the country’s annual economic output or GDP (Munich-Re, 2014). According to an OXFAM report (Chughtai, 2013), preparations and early warnings saved many lives and massive relief effort had done well to help millions of people to survive and recover. However, repercussions of typhoon Haiyan go beyond the initial destruction because it has also pushed millions of poor people into deepening debt and destitution – making them even more vulnerable to the next disaster (Chughtai, 2013).

While the loss and damage from typhoon Haiyan were mainly due to tsunami-like storm surge with a height of at least 5 metres (Economist, 2013; NASA, 2013), those from other typhoons were caused by tremendous floods and landslides from heavy and continuous rainfall particularly in areas with uncovered forest. For example, the daily threshold level of 150 mm rainfall was exceeded during the typhoons Bopha (200–330 mm), Ketsana and Parma (455–1,000 mm), Durian (466 mm) and Winnie (328–342 mm). The Annex describes the socio-economic costs of floods and landslides resulting from significant damages to agriculture and infrastructure, and large number of human losses. After Haiyan, the typhoons Ketsana and Parma that hit Metro Manila, Bicol and Central Luzon in 2009 cost the highest economic damage of 4.3 billion US$, followed by typhoon Bopha that raged Compostela Valley in Davao in 2012 causing a damage of 1 billion US$. Aside from economic damages, typhoons also displaced great number of affected families leaving them homeless. Next to Haiyan and Bopha, typhoon Mike caused large misery in 1990 leaving more than 5 million affected families and 50,000 damaged houses. Between 1990 and 2012 the largest number of dead and missing people was recorded after typhoon Thelma in 1991, when massive landslides and mudflows have estimated to have killed up to 8,000 people in Ormoc, Leyte.


3 Methods

3.1 Case study areas

3.1.1 Infanta, Quezon

Infanta is located 144 km northeast of Manila and 136 km north of Lucena City (Figure 1). It has a total land area of 34,276 hectares and total population of about 65,000 (NSO, 2014). The number of families in the municipality is 15,181, while the houses are 13,486. There is thus almost 1:1 ratio of families to houses, with average family size of 4.14. Half of the residents in Infanta rely on tertiary types of economic activity such as wholesale and retail; transportation, storage and communication; finance, insurance, real estate and business service; and community, social and personal services. The other half earns through primary and secondary types of livelihood. Out of this latter group of residents, 28% is still practicing agriculture; hunting and forestry; and fishing, while 22% has ventured into mining and quarrying; manufacturing; electricity, gas and water; and construction (Infanta Government, 2014). Infanta is a floodplain that lies along the coast of the Pacific Ocean and rests at the foot of the Sierra Madre Mountain Range. More than 41% of this land area is low lying with elevations of less than 100 m. Those areas with elevations of more than 100 m are located only in Magsaysay village, which comprises the remaining 59% (NAMRIA, 1994). Infanta is characterised by Type II climate, with no dry season but has a pronounced maximum rain period from November to January. From the period 1971–2000 the measured average annual rainfall is 4,150 mm (Infanta Government, 2014).

Figure 1 Locations of case study areas in the Philippines, with percent of people affected by Haiyan typhoon and level of poverty incidence (see online version for colours)

Source: Philippine map with people affected by Haiyan and poverty incidence is from the Rapid Assessment Report #1, 14 November 2013 of the OML Center (http://www.omlopezcenter.org)


Four successive typhoons brought about damages to the lives and properties of communities in Infanta between November 14 and December 3, 2004 (Annex). The calamity caused major physical damages and claimed lives of more than 1,000 people. As reported by the Philippine Office of Civil Defense, more than 2.3 million people were affected and about 105 million US$ (or 4.6 billion Pesos) were lost in terms of infrastructure and agriculture damages (Cruz et al., 2005). Referring to the data from National Disaster Coordinating Council, Gaillard et al. (2007) mentioned that 5,087 houses were destroyed in Infanta, 1,638 houses in Real and 3,116 houses in General Nakar. These were the three most affected municipalities in Quezon. But Infanta was hardest hit with 12,007 affected families and 176 casualties; i.e., 112 recovered bodies, 53 reported missing and 11 injured (David and Felizardo, 2006). Three villages, which were most affected and damaged in Infanta, were selected as case study areas. They are located along the Agos River, the major river that separates Infanta from the adjacent town of General Nakar (Figure 1). The elevation and position with reference to the Agos River were the criteria considered for choosing the study sites, apart from the extent of damage. The villages are Magsaysay, Ilog and Pinaglapatan:

• Magsaysay: It is an upland area located more than 100 m above sea level and has the highest elevation among the three villages. Its location is the farthest from the town proper of around 5 to 10 km. With a total land area of 22,602 hectares, Magsaysay accounts for 40% of Infanta’s total land area. It is the largest among the three villages in terms of not only area but also population. Magsaysay is inhabited by 2,824 people and comprised of 627 households.

• Ilog: It is a lowland area located in the middle of Infanta and surrounded by a river (or ilog in native language). Among the three villages, Ilog is nearest to the town centre at around 1–2 km. It has a land area of 156 hectares, which is mainly agriculture. The dominant land form is broad alluvial plains with river terraces and river fans, which represent the deposition of the river systems. Ilog is inhabited by 1,920 people and comprised of 410 households.

• Pinaglapatan: It is one of the six coastal villages in Infanta and where the Agos River is connected to the Philippine Sea. Being a coastal area, its elevation is lower than the villages of Ilog and Magsaysay. Pinaglapatan has the smallest land area among the three villages with only 73 hectares. Like other coastal villages in Infanta, mangroves and fishponds are dominant along its coasts. They are important sources of income for 1,142 people or 225 households in the village.

3.1.2 New Bataan, Compostela Valley

New Bataan is classified as a first class municipality in the province of Compostela Valley. The municipality is situated northwest of Davao Oriental province (Figure 1), south of municipality of Compostela and west of municipality of Maragusan (CLUP, 2010). The town has a total land area of 55,315 hectares. According to the census conducted in the year 2010 by the National Statistical Coordination Board (NSCB), New Bataan has a total population of 47,470 and a total household of 10,562 with an average household size of five persons. The municipality is considered an agricultural area with its vast tract of land suitable for cultivation, about 13,591 hectares or 24.57% of its total land area. Half of the total economically active population are farmers and the


other half are employees including teachers, government and private employees (CLUP 2010). The municipality of New Bataan falls under the Type II Climate, which is characterised by no dry season with a very pronounced maximum rain period. The rainy season generally occurs in December to January (sometimes also between October to February) and there is no single dry month in the region.

On December 4, 2012 Compostela Valley was unexpectedly struck by Typhoon Pablo, affecting more than thousands of families and ruining large number of local livelihoods (Annex). Although communities were given advanced warnings and prepared themselves for expected disaster, the typhoon caused heavy damage in many provinces of Mindanao with 1,067 deaths, 800 missing and 160 million US$ (or 7 billion Pesos) worth of damage to infrastructure and agriculture (Manuta, 2013). The province of Compostela Valley had the most number of recorded deaths (236 people). Within the province, the municipality of New Bataan was severely affected by flash floods, mudslides, and strong winds. Flood water reportedly came down from the mountain slopes, bringing with it mud, logs and rocks. Fallen trees and rocks that blocked the main roads also made it hard for rescuers to immediately reach the area. Many of the affected families, mostly farm workers in plantations, have lost their sources of livelihood (CDRC, 2013). Among the most affected villages, three were selected as case study sites in New Bataan, namely Andap, Cabinuangan and Cogonon:

• Andap: It is situated at the mouth of a mountain drainage network and at the base of steeply-sided slopes. It is nested on an alluvial fan, normally found at the base of mountains where water drains. Andap is a rural village covering the largest area of the municipality with 11,240.55 hectares, i.e., 20.32% of the total land area. It has a total population of 7,550 with 1,574 households. There were at least 70 people who died and about 290 people missing after the typhoon. More than 1,250 houses were either partially or totally damaged.

• Cabinuangan: It is an urban area serving as main growth centre of the municipality. Cabinuangan has a total population of 10,390 with 2,364 households. It has a total land area of 2,997.74 hectares where 3.24% is forest area. The typhoon caused 66 deaths, 144 missing people and about 1,900 damaged houses in the village.

• Cogonon: It is one of the smallest villages with 652.17 hectares, accounting for only 1.18% of the total land area in the municipality. Cogonon has a total population of 1,223 with 285 households. No casualties were so far reported but there were about 300 damaged houses in the village. It is one of the poorest villages in New Bataan.

3.2 Survey administration

The survey instrument used in this study was a structured questionnaire combined with open-ended questions. It was pretested in Village Andap in New Bataan, Compostela Valley in June 2013. Over the course of the survey preparation, the questionnaire was revised and improved so that it is designed to gather relevant information on individual experiences and preferences on adaptation strategies. Specifically, it consisted of seven sections:


1 socio-economic and demographic profiling

2 overview of livelihood activities

3 typhoon-induced disaster experiences

4 disaster recovery and adaptation strategies

5 health and social networks

6 conjoint analysis survey

7 opinions on impacts of Typhoon Haiyan in the Visayas regions.

With the support of local government officials, the household surveys in Infanta, Quezon and New Bataan, Compostela Valley were successfully implemented in November 2013. Multiple-stage sampling was applied in selecting survey respondents. The first stage involved stratification at the municipal level using extent of damage and economic characteristics as criteria for stratification. The sampling resulted in the selection of the villages of Ilog, Magsaysay and Pinaglapatan as case study sites for Infanta, Quezon and the villages of Andap, Cogonon and Cabinuangan for New Bataan, Compostela Valley. The second stage sampling aimed to determine the appropriate sample size in each village. The sample size was calculated using the Cochran method at a 95% confidence level and 8% confidence interval. The following equation was applied:

2

2

2

211 1

Z PQEn

Z PQN E

=⎡ ⎤⎛ ⎞+ −⎜ ⎟⎢ ⎥⎝ ⎠⎣ ⎦

Households affected by landslides denoted by P and Q was defined as 1 – P, when the values of P and Q are between 1 and 0, inclusively; where

maximum tolerable errortabular value of the Z statistics at a certain level of total number of households

EZN

===

α

The resulting sample size for Infanta and New Bataan were 109 and 140, respectively. Specifically, the sample sizes in each village were as follows:

• Infanta: Pinaglapatan – 36, Ilog – 39, Magsaysay – 34

• New Bataan: Andap – 35, Cabinuangan – 70, Cogonon – 35.

The third sampling stage involved stratification at the village level to capture different livelihood sources in the survey. Stratification at this level aimed to determine whether the nature of livelihood influences preferences for adaptation strategies. Finally, random sampling was employed in identifying respondents to be included in the survey using the research randomiser of the Social Psychology Network (http://www.surveysystem.com/sscalc.htm).


3.3 Conjoint analysis

Conjoint analysis (also known as choice models or experiments) is a practical technique for measuring preferences and assessing trade-off decisions. It is widely used in different scientific fields (e.g., psychology, economics, and environment) to transform subjective choice responses into estimated parameters. Farber and Griner (2000) provide a summary of its application to environmental valuation. In conjoint analysis the attributes of an environmental good are used to understand the general trade-offs which an individual is willing to make (Hanley et al., 1998). Considerable attention has been given to this technique both in academe and industry to measure preferences through utility trade-offs among products and services (Lee et al., 2006; Green and Srinivasan, 1990), particularly in agro-environments (e.g., Tano et al., 2003; Stevens et al., 2002; Moran et al., 2007; Blamey et al., 2000; Acosta-Michlik et al., 2011; Acosta et al., 2012, 2014). The preferences are assumed to be influenced by the individual’s subjective perceptions on the presented choices. Thus, the preference structure is a function of the individual’s economic, social and cultural conditions, which affect his or her decision. Public preferences have an important role in decision-making because they may in fact highlight stark policy trade-offs (Hall et al., 2004). In choice-based conjoint analysis, a set of attributes and their respective levels define the respondents’ choices. In this paper, the attributes correspond to household assistance, livelihood assistance, agriculture assistance, sources of assistance and risk reduction measure for flood/landslide impacts (Table 1). Table 1 Attributes and attribute levels in the conjoint questionnaire

Level number

Attributes

Household assistance

Livelihood assistance

Agriculture assistance

Sources of assistance

Risk reduction measure

1 Food supply Crop production

Machine/tools Relatives/ friends

Prevent logging

2 Medicine supply

Livestock production

Seed/seedlings Farm associations

Stop mining

3 Shelter/housing Agro-forest production

Livestock/ animals

Government Regulate squatters

4 Money/loan Family business

Pesticides/ fertilisers

NGOs Reforestation

5 Alternative livelihood

Non-agriculture job

Crop insurance Church Reduce soil erosion

The combinations of attribute levels define the choice tasks in the conjoint surveys (Figure 2). Seven choice tasks were presented to each respondent, where each choice task has different combinations of attribute levels. The choice tasks were computer-generated using the SSIWeb Sawtooth. The software was used not only to construct the choice tasks and prepare the conjoint questionnaire, but also to analyse the responses of the respondents (i.e., compute utilities and preference weights) as described below. We used complete enumeration for random task generation method and traditional full profile for design module setting. Moreover, the software package includes a statistical test (i.e.,


logit efficiency) to validate the survey design in terms of the optimal number of options, choice tasks, and questionnaire versions. The validation results showed relatively good fit for a survey design with 35 versions (each version has different sets of choice tasks) and 200 respondents. On the basis of these results, we aimed to survey a minimum of 200 respondents in the two municipalities.

Figure 2 Example of choices in a conjoint task of the survey questionnaire (see online version for colours)

Adaptation strategies CHOICES

1 2 3

Household assistance Livelihood assistance Agriculture assistance Source of assistance Landslide risk reduction

Food supply Crop production Machine/tools Relatives/friends Prevent logging

Medicine supply Livestock production Seed/seedlings Farm associations Stop mining

Shelter/housing Agro-forest production Livestock/animals Government Regulate squatters

Tick only one choice □ □ □

A conjoint study leads to a set of part-worths or utilities, which measure the relative desirability or worth of an attribute level (Orme, 2010, 2006). The higher the utility, the more desirable is the attribute level. The respondents’ choices were analysed using a hierarchical Bayes choice-based conjoint (HCBC) model that is able to capture preferences of individuals (i.e., respondent level) and groups of individuals (i.e., segment level) (Orme, 2009):

i i i iY X ε= +β (1)

Θi i iz δ= +β (2)

Where in the first equation, Yi is a vector of the responses from the choice tasks, Xi is a matrix of the attribute levels, βi is the p-dimensional vector of regression coefficients representing the utilities, and εi is a p-dimensional vector of random error terms. In the second equation, Θ is a p by q matrix of regression coefficients (i.e., utilities), zi is a q-dimensional vector of covariates and δi is a p-dimensional vector of random error terms. The HCBC model is called hierarchical because it models respondents’ preferences as a function of a lower- or individual-level (within-respondents) model and an upper-level (pooled across respondents) model (Orme and Howell, 2009). According to Lenk et al. (1996), hierarchical Bayes analysis creates the opportunity to recover both the individual-level part-worths and heterogeneity in part-worths, even when the number of responses per respondent is less than the number of parameters per respondent. This makes the model in equations (1) and (2) very useful in cases of small respondent population, where i = 1…n is the number of respondents. Equation (1) reflects the individual-level model and assumes that the respondent chooses options according to the sum of utilities as specified in logit models. Equation (2) is an upper-level model that describes the heterogeneity in the individual utilities across the population of respondents.


4 Results and discussion

4.1 Socio-ecological profile

The social profile of the respondents is described in Table 2. The respondents in Infanta are relatively older than those in New Bataan. The largest proportion with age above 50 years is found in the village of Ilog in Infanta. Overall, there are more respondents who have completed elementary education in New Bataan than in Infanta. Moreover, there are more respondents who have reached or completed college and university studies in the former municipality. Education is considered source of knowledge and awareness, thus many respondents in New Bataan can be assumed to have more capacity to adapt to climate change impacts. The household size of families in Infanta is generally larger, where more than 10% of the respondents having more than nine household members. More than half of the respondents have been residing for more than 30 years in both municipalities. They are thus very familiar not only with social but also ecological environment in their respective areas. Satellite images of affected communities in Infanta, Quezon and New Bataan, Compostela Valley after the landslide events are shown in Figure 3. In Infanta, the river has expanded tremendously and many agricultural areas were flooded or covered with drifted logs, uprooted trees and thick mud [Figure 3(a)]. It was not possible to cultivate the areas for many years leaving many farmers with no source of livelihoods. In Andap village in Compostela Valley, the change in the ecology was even more dramatic with not only agricultural but also residential areas covered with heavy rocks and thick mud [Figure 3(b)]. The agricultural areas will probably not be easily cultivated again in the near future. Many residents in Andap who survived the floods and landslides were permanently relocated. Table 2 Social characteristic of respondents in the case study villages in the Philippines

Variable Infanta New Bataan

Total Pinaglapatan Ilog Magsaysay Cabinuangan Cogonon Andap

Age 30 and below 2.78 5.13 11.76 12.86 14.29 22.73 10.92 31–50 52.78 33.33 35.29 48.57 32.14 50.00 42.79 51–70 41.67 48.72 38.24 31.43 42.86 18.18 37.12 71 and above 2.78 12.82 14.71 7.14 10.71 9.09 9.17

Education No formal education

3.57 0.43

Elementary 50.00 30.77 41.18 22.86 28.57 47.83 34.35 High school 38.89 43.59 47.06 40.00 50.00 43.48 43.04 Vocational/ technical school

12.82 2.94 11.43 3.57 8.70 7.39

College/university graduate

11.11 12.82 8.82 25.71 14.29 14.78

Notes: Values refer to proportion of respondents per village. Thus, in each village the values of categories for each variable add up to 100%.


Table 2 Social characteristic of respondents in the case study villages in the Philippines (continued)

Variable Infanta New Bataan


HH size 4 and below 41.67 43.59 42.42 48.57 50.00 60.87 47.16 5 to 8 47.22 46.15 45.45 51.43 46.43 34.78 46.72 9 and above 11.11 10.26 12.12 3.57 4.35 6.11

Years residing 10 and below 5.56 2.63 29.41 7.14 7.14 9.09 9.65 11 to 30 27.78 34.21 32.35 27.14 39.29 36.36 31.58 31 to 50 41.67 28.95 29.41 52.86 25.00 50.00 39.91 51 and above 25.00 34.21 8.82 12.86 28.57 4.55 18.86

Total respondents 36 39 34 70 28 22 229


Figure 3 Changes in ecology of villages after the floods and landslides in (a) Infanta and (b) New Bataan (see online version for colours)

(a)

Source: (a) SPOT 5 satellite imagery from Center for Space and Remote Sensing Research, National Central University, Taiwan; LandSat 8 from USGS (http://glovis.usgs.gov); National Mapping Resource and Information Agency, Philippines; http://www.philgis.org; http://www.gadm.org; http://www.geofrabrik.de; photo taken by Ninfa Z. Bito as cited in David and Felizardo (2006) (b) LandSat 8 from USGS (http://glovis.usgs.gov); http://www.philgis.org; http://www.gadm.org; http://www.geofrabrik.de; photo taken by daebo75 on 2 January 2013 as cited in http://ph.geoview.info/


Figure 3 Changes in ecology of villages after the floods and landslides in (a) Infanta and (b) New Bataan (continued) (see online version for colours)

(b)

Source: (a) SPOT 5 satellite imagery from Center for Space and Remote Sensing Research, National Central University, Taiwan; LandSat 8 from USGS (http://glovis.usgs.gov); National Mapping Resource and Information Agency, Philippines; http://www.philgis.org; http://www.gadm.org; http://www.geofrabrik.de; photo taken by Ninfa Z. Bito as cited in David and Felizardo (2006) (b) LandSat 8 from USGS (http://glovis.usgs.gov); http://www.philgis.org; http://www.gadm.org; http://www.geofrabrik.de; photo taken by daebo75 on 2 January 2013 as cited in http://ph.geoview.info/

4.2 Loss and damage in communities

Table 3 presents the losses of respondents from floods and landslides due to deaths of family members, relatives and neighbours. Only few respondents in Infanta have lost members of their families. In the village of Andap in New Bataan, more than 15% of the respondents have lost at least two family members. While the respondents’ family members who died from the disaster were low, the deaths of relatives and neighbours were high in both municipalities. The number of losses outside family members is higher in New Bataan than in Infanta. In the village of Cogonon and Andap, many respondents have lost more than 40 neighbours. The disaster impacts in the latter village were however most extreme in terms of human losses, with more than half of the respondents having dead neighbours. Table 4 shows the property damages of respondents in the six villages in Infanta and New Bataan. Most of their houses have been destroyed by floods and landslides. In Infanta, the respondents in the village of Magsaysay have extreme damage where more than half of their houses were not only partially but totally damaged. In New Bataan, the disaster impacts were very extensive where more than 95% of the houses were destroyed in the village of Andap. However, many of respondents with totally destroyed houses were able to reconstruct their houses, mainly through the support from family, religious and other private organisations. In Cogonon, only half of respondents were able to have their houses reconstructed. The highest human loss and


property damage was experience in Andap, which may explain why it was the focus of many external support. Table 3 Number of family members, relatives and neighbours who died from disaster

Losses Infanta New Bataan


Family None 100.00 97.44 85.29 92.86 100.00 73.91 92.61 One 2.56 14.71 5.71 8.70 5.22 2 to 5 1.43 13.04 1.74 11 to 20 4.35 0.43

Relatives None 94.44 66.67 76.47 68.57 89.29 8.70 70.00 One 5.56 7.69 11.76 11.43 21.74 9.57 2 to 5 12.82 8.82 15.71 10.71 21.74 11.74 6 to 10 5.13 2.94 2.86 17.39 3.91 11 to 20 7.69 1.43 21.74 3.91 41 to 70 4.35 0.43 71 to 100 4.35 0.43

Neighbours None 97.22 76.92 94.12 98.57 60.71 79.57 One 2.78 5.88 3.57 1.74 2 to 5 12.82 10.71 4.35 3.91 6 to 10 2.56 1.43 3.57 1.30 11 to 20 2.56 7.14 4.35 1.74 21 to 40 5.13 0.87 41 to 70 3.57 8.70 1.30 71 to 100 3.57 13.04 1.74 Above 100 7.14 69.57 7.83



Table 4 Houses damaged and lost, by level of damage and by village

Loss and damage Infanta New Bataan


Extent of house damage

Not destroyed 8.33 7.69 8.82 7.14 14.29 7.83 Slightly destroyed 38.89 23.08 14.71 41.43 46.43 30.43 Heavily destroyed 22.22 20.51 11.76 25.71 21.43 4.35 19.57 Totally destroyed 30.56 48.72 64.71 25.71 17.86 95.65 42.17



Table 4 Houses damaged and lost, by level of damage and by village (continued)

Loss and damage Infanta New Bataan


Ability to reconstruct house

Not reconstructed 27.78 17.95 29.41 22.86 50.00 8.70 25.65 Reconstructed 72.22 82.05 70.59 77.14 50.00 91.30 74.35



Table 5 Most important loss and damage experienced by the respondents

Damages Infanta New Bataan


No drinking water 2.78 5.13 2.94 14.29 39.29 8.70 11.74 No water for use 7.14 17.86 4.35 4.78 Lack of electricity 7.69 8.82 1.43 3.04 Lack of transport Road destruction 2.56 0.43 Damages of house 8.33 10.26 14.71 8.57 7.83 House relocation Homelessness 13.89 17.95 11.76 21.74 9.13 Temporary shelter 2.78 9.13 Lost of livelihood 19.44 5.13 17.65 3.57 21.74 0.43 No food 41.67 43.59 35.29 68.57 35.71 26.09 46.96 No medical support Destruction of farm 5.56 2.56 2.94 1.74 Destroyed forest 2.56 3.57 0.87 Soil erosion 2.78 0.43 Others 2.78 2.56 5.88 17.39 3.48

100.00 100.00 100.00 100.00 100.00 100.00 100.00

Note: Values refer to proportion of respondents per village.

In addition to property damages, the villages in Infanta and New Bataan have experienced other infrastructural and ecological losses and damages (Table 5), which were considered as sources of discomforts in the daily lives of the respondents. None of the respondents considers lack of transport, relocation of house and lack of medical support as important concerns after the flood and landslide events. Lack of food was a major problem for many respondents in all three villages in Infanta. The extent of the problem was however felt by even more respondents in Cabinuangan in New Bataan where almost 70% considers lack of food as their most important concern. This was


however not the case in the other two villages, in particular Andap. Consultation with local experts revealed that few days after the floods and landslides in the municipality, most relief goods were sent to most affected villages including Andap. Other villages had to wait for days or even beg along the street for them to get relief support. However, about 18% of the respondents in Andap have other important concerns including house damages and human losses. After lack of food, the next most important concern in many villages was lost of livelihood particularly in the villages of Pinaglapatan, Magsaysay and Andap. But lost of houses was equally important for the respondents in the villages of Ilog and Andap. Unlike other villages, lack of water for drinking and other uses was an important problem by many respondents in Cogonon. The physical destructions on farm, forest and soil after floods and landslides were a major concern for only few respondents.

An often overlooked impact of floods and landslides on the previously affected people is psychological damage, which can affect them again during occurrence of other typhoons. Referring to typhoon Haiyan, which have caused immense devastation in the central part of the Philippines few months before the conduct of the survey, we asked the respondents how they felt during and after the typhoon. Many of them expressed fear although the central paths of typhoon Haiyan were far from their regions (Figure 1). The feeling of fear was particularly high in the villages of Cabinuangan and Andap (Figure 4). Self-pity was the next most important emotion among respondents particularly in Pinaglapatan and Cogonon. While hopelessness was a common feeling in all villages in Infanta, it was not the case in New Bataan. It was the feeling of anxiety which affected many respondents in the villages of Cogonon and Andap in New Bataan. These various apprehensions felt by respondents are indicators of psychological distress that can affect capacity to adapt. Norris et al. (2008) explained that varying degrees of wellness of individuals (and communities) before as well as after disasters must be taken into account in assessing post-disaster adaptation. Moreover, they emphasised that natural disasters are especially likely to engender severe psychological distress when they occur in the developing world.

Figure 4 Respondents’ prominent feelings during and after devastation of typhoon Haiyan (see online version for colours)


4.3 Preferences on adaptation assistance

The results of the analysis from conjoint surveys reveal that about half of the respondents in all six villages prefer to receive household assistance after flood or landslide events (Figure 5). However, the source of the assistance is not very relevant to them with only 6% giving preference to this attribute. Across the different villages the diversity of preferences is most evident for household assistance. The preference for this type of assistance is highest in Andap, followed by Cogonon and Magsaysay. The preference for household assistance is relatively low in Cabinuangan where many respondents give more importance to landslide risk reduction. In Andap, where the village centre vanished from huge stones and thick mud after the landslide [Figure 3(b)], the respondents have lowest preference for landslide reduction measures. During the consultation through participatory rural appraisal (PRA) prior to the survey, residents in the village expressed their concerns about logging and mining activities in the adjacent mountains. They also expressed concern about lack of livelihood support in the village. The results of the survey reveal, however, that the extent of the human loss and property damage in the village makes household assistance a top priority. Preference for livelihood assistance is highest in the village of Ilog.

Figure 5 Preferences for types and sources of adaptation (see online version for colours)


Table 6 presents the utility values for the attribute levels (i.e., conjoint choices) under the three types of adaptation assistance (i.e., household, livelihood and agriculture). The large utility values for choices of household assistance further reveal the high level of preferences attributed by the respondents to this attribute. However, the preferences vary significantly across the six villages. Food supply has large utility for the respondents in Cogonon with a value of 74. This is followed by Magsaysay where food supply has a utility value of 40. After food supply, alternative livelihood is the most preferred assistance for the household particularly in the villages of Andap and Pinaglapatan with utility values of at least 25. Medicine is least preferred household assistance in villages like Andap, Magsaysay and Pinaglapatan. Money and loan have positive utility only in Andap, while shelter and housing only in Cabinuangan. In New Bataan the largest number of relocated residents is from Andap. Hence the low preference for shelter and housing indicates that the respondents in this village have received appropriate relocation assistance, but would require other types of assistance including food supply, alternative livelihood and money/loan. For the second type of assistance, many respondents in Andap give highest preference to crop production as livelihood assistance (Table 6). Before the landslide farming was the main livelihood in Andap, but now large farm areas are covered with huge stones and cannot be cultivated. Due to the proximity of Ilog to Infanta’s municipal centre, respondents in this village give highest preference to non-agriculture job. Farming was the main livelihood source before the landslide but many farms in Ilog were also covered by mud and huge logs after the landslide. The respondents in the urban village of Cabinuangan and upland village of Magsaysay also give highest preference to non-agriculture job. The respondents in Magsaysay have least preference to agroforest production. Assistance on agroforest production is only highly preferred in Cogonon. The respondents in Pinaglapatan have highest utility value for livestock production, which can provide them additional or alternative income from fishing.

For the third type of assistance, i.e., agricultural assistance, crop insurance has the highest utility in all case study villages in Infanta but relatively low in Compostela Valley particularly in the poorest village of Cogonon (Table 6). The provision of seeds/seedlings is the most preferred agricultural support by respondents in Cogonon and Andap, while machine and tools are mostly needed by respondents in Cabinuangan. Although livestock assistance is not considered top priority for respondents, it has positive utility value in all villages and is the second most preferred assistance in several villages. The provision of fertilisers and pesticides is the least preferred assistance in all villages. In the conjoint surveys, the respondents were also asked to choose one among five possible sources of household, livelihood and agricultural assistance (Table 6). Government is considered either the most or second most preferred source of assistance by respondents in all villages, except for Andap. In the latter village, the most preferred sources of assistance are farm associations and NGOs. In Ilog the NGOs have the highest utility value followed by the government, while in Magsaysay and Cogonon the exact opposite is the case. Religious organisations have positive utilities only in two villages in Infanta.


Table 6 Conjoint utilities for different attribute levels, by village

Attribute levels Infanta New Bataan


Household assistance Food supply 29.68 30.38 39.68 17.88 73.62 28.28 32.89 Medicine supply –24.21 –15.98 –32.22 –3.59 –12.57 –35.77 –17.46 Shelter/housing –21.60 –5.69 –12.07 7.91 –26.50 –31.96 –10.14 Money/loan –10.07 –18.51 –7.48 –9.96 –13.98 5.88 –9.97 Alternative livelihood 26.19 9.79 12.10 –12.24 –20.58 33.58 4.68

Livelihood assistance Crop production 2.45 6.42 2.11 7.92 0.45 10.31 5.28 Livestock production 5.02 –0.90 –2.13 –3.60 –11.24 –6.97 –2.84 Agroforest production

–0.49 –4.47 –3.91 –5.84 5.68 –0.71 –2.57

Family business –9.64 –11.48 –1.13 –10.32 5.17 –2.00 –6.33 Non-agriculture job 2.67 10.43 5.06 11.84 –0.07 –0.64 6.47

Agriculture assistance Machine/tools 3.50 1.54 –7.25 8.15 1.27 –2.50 2.12 Seed/seedlings 0.74 2.09 3.21 –14.92 14.31 7.14 –1.14 Livestock/animals 6.04 2.04 6.33 3.32 5.25 0.14 3.89 Pesticides/fertilisers –18.50 –13.19 –13.26 –2.28 –6.76 –7.78 –9.39 Crop insurance 8.22 7.52 10.97 5.72 –14.07 2.99 4.51

Source of assistance Relatives/friends 5.83 –0.87 –3.77 –2.67 –7.94 –2.32 –1.81 Farm associations –14.72 –9.42 –3.95 –10.21 0.86 3.44 –7.14 Government 4.55 3.16 7.90 16.80 7.24 –3.63 8.05 NGOs 1.90 4.24 4.80 1.46 4.46 3.36 3.05 Church 2.44 2.89 –4.98 –5.39 –4.62 –0.85 –2.15

Landslide risk reduction

Prevent logging 4.15 –5.11 –7.69 –2.62 –12.09 0.51 –3.57 Stop mining –7.48 –10.89 –2.88 –0.10 –4.25 –4.94 –4.48 Regulate squatters –10.33 –12.65 –5.03 –16.88 –5.50 –3.56 –10.67 Reforestation 5.99 14.83 0.52 5.29 2.88 –6.43 4.85 Reduce soil erosion 7.67 13.82 15.09 14.31 18.96 14.42 13.88

Notes: The utility values were computed using zero-centred difference as rescaling method. In each attribute, the values of the utilities for all six levels thus sum up to zero. The utilities are measures of preferences where 1 utilities with positive values are preferred over those with negative values 2 for positive utilities, the larger the utility values the higher the preference

level. The signs and values of the utilities together thus measure the respondents’ willingness to trade-off less preferred attribute level for more preferred ones.


Finally, based on the results of conjoint surveys for reducing landslide risks, the utility values for reducing soil erosion are highest in all villages, except for Ilog (Table 6). This reflects the extent of and thus concern on soil erosion, which has been labelled the country’s worst environmental problem [Tujan (2000) as cited in Schmitt (2009)]. Referring to the report of the Philippine Forest Management Bureau, Schmitt (2009) explained that between 71 and 84 million tons of soil are eroded from the country’s agricultural lands every year and that the eroded soil leads among others to landslides. In the lowland village of Ilog reforestation is the most preferred measure to reduce landslide risks. Discussion with residents in Ilog during the survey revealed that they think illegal logging in the upland village of Magsaysay contributed to the landslides. But for the respondents in Magsaysay preventing logging is the least preferred measure to reduce landslide risks. Majority of respondents in this village reached only elementary and high school education (Table 1), so raising awareness on the link between logging and landslide is critical. Illegal logging has been identified as one of the major causes of forest denudation, which is associated to catastrophic floods and landslides in the Philippines (Pulhin and Inoue, 2008; Cedamon et al., 2011). Many respondents also depend on forests for their living so capacity building on sustainable agroforest livelihood should be provided. However, assistance on agroforest production is least preferred by respondents in Magsaysay. Reforestation is considered the second most important measure after reduction of soil erosion, except in Andap. Regulating illegal construction of houses in upland areas has only low utility for respondents in all villages. This can be explained by the prevalence of informal settlers in the Philippines (Cruz, 2010). Many upland farmers are considered kaingin (i.e., slash and burn) squatters who are not recognised by the government (Cedamon et al., 2010), unless they are covered by the government’s forest programs providing them limited tenure (Pulhin and Inoue, 2008). Forest squatters face particularly high insecurity with regard to duration of land tenure (Harrison, 2003), which contributes to the lack of incentive among upland farmers to participate in agroforest initiatives.

4.4 Opinion on disaster events

Awareness on the relationship of the impacts of changes in climate and land use to disaster events is critical to reducing landslide risks. We thus asked the opinions of the respondents on the link between climate change and typhoons as well as the reasons for the typhoon-induced disasters in the Philippines. Figure 6 reveals that most respondents, in particular those in New Bataan, think that climate change is related to the increasing intensity of typhoons. But in Infanta, at least 15% of respondents in all three villages do not know if there is a link between climate change and typhoons. This may reflect the higher level of awareness in New Bataan, which could be attributed to larger number of respondents in this municipality who have higher education. About 20% of the respondents in Magsaysay and Andap are not sure about the issue between climate change and typhoons. Among all villages, respondents in Magsaysay are least aware on this issue. Table 7 reveals that, except for Pinaglapatan, at least 20% of the respondents in all villages think that the disasters in the Philippines are related to religion (e.g., lack of faith in God, selfish society, etc.). Many respondents who think that destruction of environment is linked to deforestation, logging and mining are found in the three villages in Infanta. The level of awareness on the link between fragile environment and disaster events is relatively lower in New Bataan. The proportion of respondents who answered


‘do not know’ on the reasons for disasters related to typhoons is highest in Pinaglapatan (22%) and Andap (18%). Considering the vulnerability of New Bataan to landslide, it is critical to build awareness of people about disaster risks. Based on the geohazard maps published by the Department of Environment and Natural Resources (DENR), New Bataan is in permanent danger due to its very high susceptibility to landslides (Villanueva, 2012). In particular, the village of Andap is situated at the apex of alluvial fans and in the path of potential debris flows (Ferrer et al., 2014).

Figure 6 Opinions on the link between climate change and typhoons (see online version for colours)

Table 7 Opinions on the reasons for typhoon-related disasters in the Philippines, by village

Reasons Infanta New Bataan


1 Climate change 19.44 7.89 15.63 22.86 17.86 18.18 17.70 2 Environment

destruction 38.89 31.58 37.50 17.14 28.57 18.18 27.43

3 Both 1 and 2 5.56 5.26 3.13 2.86 7.14 4.55 4.42 4 Natural reasons 5.56 10.53 9.38 12.86 3.57 9.09 9.29 5 Geographic 6 Religious 5.56 21.05 21.88 18.57 21.43 18.18 17.70 7 Others 2.78 2.63 11.43 7.14 13.64 6.64 8 Do not know 22.22 13.16 12.50 12.86 14.29 18.18 15.04 100.00 100.00 100.00 100.00 100.00 100.00 100.00

Note: Values refer to proportion of respondents per village.

5 Conclusions

The paper analysed loss and damage in two municipalities in the Philippines which were affected by floods and landslides resulting from combined impacts of climatic extremes (typhoons) and land use change (deforestation). The mitigation measures necessary to


avoid disasters like these should thus not only be huge reduction in emissions, which are expected from developed countries, but also strict control of deforestation and extensive reforestation, which are critical problems in many developing countries. The results of the study show that many vulnerable people are not yet aware of the complex link between climate and land use change. Raising awareness should thus be considered an important component of any mitigation strategies. This is particularly important in rural and farm areas where people are less educated and do not have access to information from media and science. The government should initiate awareness campaigns to people in vulnerable communities on the implications of geohazard risks, as indicated in the DENR’s geohazard maps.

Many loss and damage in society (lives, livelihood) and economy (production, infrastructure) are easily quantifiable and often reported and recorded. However, psychological distress which is important for adaptation to recurring disasters is not given much attention. Many post-disaster adaptation measures like food relief and temporary shelters are often given to affected people, but not psychological assistance to help them recover from traumatic experience. The study revealed that many people affected by typhoon-related landslides are emotionally and psychologically distressed from re-occurrence of strong typhoons. This is non-economic loss or damage that should be taken into consideration in any mechanism on compensation and rehabilitation.

The means to address loss and damage should be adapted to the local needs and values of local communities. The paper analysed the preferences for adaptation measures. Providing loan is not a preferred adaptation measure by the farmers because, after losing their properties and sources of livelihoods, they will not have the capacity to repay the debts and interests. Insurance did not also come out as an important mechanism for reducing disaster risks in all villages. Regular crop insurance, for example, will require payments from the farmers, but their small income does not allow such mechanism to work. Production support in the form of seeds/seedlings, livestock or tools are preferable because it will allow them to recover from livelihood loss or damage, which farmers cannot easily afford to replace or recover. Risk-transfer will thus work only within a ‘polluter pays principle’ mechanism where the major emitters, either countries or industries, should pay for the insurance premium. The affected people or countries should then be allowed claims from insurance in case of loss and damage from climate change related disasters.

The loss of ecosystems and indigenous knowledge is not only a consequence but also cause of ‘loss and damage’ in disaster events. The loss of indigenous knowledge on the ecological values of forests has led to destruction of upland ecosystem, which is vital to protecting lowland areas. Although half of the surveyed respondents think that typhoon-related disasters are linked to climate change and environment destruction, only few consider reforestation and logging/mining prevention as important measures to reduce landslide risks. The main problem is not only lack of knowledge but lack of alternative livelihoods. Several farmers in Andap, the village with largest loss and damage from landslide impacts, are forced to work in mining in the nearby upland village, where some of them think the huge stones that covered their village came from. Loss and damage should thus address the cause of the problem, which in developing countries in many cases is the lack of sustainable alternative livelihoods after the disaster. This is an economic loss that needs to be taken into consideration in the international mechanism on compensation and rehabilitation.


Following these conclusions, we would like to make important policy recommendations that are relevant for designing support framework for International Mechanism on Compensation and Rehabilitation:

a capacity-building for local communities to build awareness on the direct links between environment (e.g., forest ecosystem and environment protection) and disasters is an indispensable rehabilitation support

b creating reliable global database on quantity and value of loss and damage covering not only human loss (e.g., deaths) and economic damage (e.g., properties, infrastructure) but also health injuries (e.g., physical, mental) is important for rapid estimation of compensation and prompt delivery of rehabilitation support

c insurance system requiring affected communities to prepare paper work and wait longer time before receiving compensation is not effective and desirable for poor people who do not have capital reserve or alternative livelihood

d rehabilitation support through immediate replacement of lost or damaged sources of livelihood is important in helping affected people to continue sustainable (e.g., farming, agro-forestry) and avoid destructive (e.g., logging, mining) livelihoods.

Acknowledgements

The authors would like to thank the people who participated and local officials who supported the conduct of the survey and PRA. The paper is based on the project on Livelihoods Vulnerabilities to Typhoon Associated Hazards in Southeast Asia: A comparative study in Taiwan and the Philippines with funding support from the Integrated Research on Disaster Risk – International Center of Excellence (IRDRICoE), Academia Sinica, Taiwan.

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Annex

Floods and landslides caused by typhoons in the Philippines, 1990–2013

Typh

oon

nam

e Ye

ar

Inte

rnat

iona

l Lo

cal

Floo

d/la

ndsl

ide

loca

tions

N

umbe

r affe

cted

pe

ople

N

umbe

r dam

age

hous

es

Econ

omic

dam

age

(mill

ion

US$

) D

eath

s/m

issi

ng

2013

H

aiya

n Y

olan

da

Cen

tral V

isay

as

16,0

00,0

00

1,10

0,00

0 5,

000–

10,0

00

6,00

0–10

,000

20

12

Bop

ha

Pabl

o C

ompo

stel

la V

alle

y, D

avao

6,

200,

000

89,6

66

1,00

0 1,

867

2009

K

etsa

na, P

arm

a O

ndoy

, Pep

eng

Met

ro M

anila

, Bic

ol R

egio

n an

d C

entra

l Luz

on

4,47

8,28

4 N

D

4,30

0 20

0–1,

000

2006

C

hanc

hu

Cal

oy

Gui

nsau

gon,

Sou

ther

n Le

yte

42,1

23

600–

3,54

2 2

41

2006

D

uria

n R

emin

g A

lbay

25

,020

65

,617

11

4*

500–

700

2006

X

angs

ane

Mile

nyo

Mt.

Mak

iling

in L

agun

a 11

6,67

5 23

,790

1

125–

197

2004

W

inni

e, M

uifa

, M

erbo

k, N

anm

adol

W

inni

e, U

ndin

g,

Vio

leta

, Yoy

ong

Infa

nta,

Que

zon

12,0

07

76,0

62

15–1

8 34

0

2000

K

ai-ta

k Ed

eng

Paya

tas

1,15

6,03

1 21

3 3*

42

19

95

Ang

ela

Ros

ing

Bic

ol

ND

96

,000

24

2*

900

1993

Fl

o K

adia

ng

Nor

ther

n an

d C

entra

l Luz

on

ND

N

D

196*

57

6 19

91

Thel

ma

Urin

g O

rmoc

, Ley

te

598,

454

4500

28

3,

000–

8,00

0 19

90

Mik

e R

upin

g C

ebu

5,49

8,29

0 50

,000

14

74

8

Not

e: *

Con

verte

d in

to U

S$ u

sing

cur

rent

exc

hang

e ra

te.

Sour

ce:

AD

B (2

011)

, Alc

onab

a (2

013)

, Alo

jado

(201

0), B

acan

i (20

13),

Bha

ttach

aryy

a (2

013)

, Bro

wn

(201

3), C

DR

C (2

013)

, Con

de (2

009)

, De

Jesu

s (20

13),

Earth

Obs

erva

tory

(200

6), F

ano

et a

l. (2

007)

, GFD

RR

(200

9), G

MA

(201

3), G

uint

o (2

006)

, IFR

C (2

006)

, Int

erA

ksyo

n (2

013)

, IR

IN (2

010)

, Mic

hael

an

d Pa

dua

(201

2), N

ASA

(200

9), P

AG

ASA

(200

6), P

anel

a (2

012)

, Sab

illo

(201

3), U

SAID

(204

), an

d V

anzi

(200

0)

loss and damage from typhoon-induced floods and landslides in the philippines: community perceptions...

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