Risk attitudes and perceptions on extreme weather events of small scale farmers in siniloan laguna philippines

97 Figure 18: Overall results of rice and vegetable farmers' risk perception based on the number of adaptation strategies ...100 Figure 19: Risk attitude of rice farmers towards extreme

THAI NGUYEN UNIVERSITY

UNIVERSITY OF AGRICULTURE AND FORESTRY

NICOLE ALEXIA VERIDIANO DE CASTRO

RISK ATTITUDES AND PERCEPTIONS ON EXTREME

WEATHER EVENTS OF SMALL-SCALE FARMERS IN

SINILOAN, LAGUNA, PHILIPPINES

BACHELOR THESIS

Study Mode: Full-time Major: Environmental Science and Management Faculty: Advanced Education Program Office

Thai Nguyen, 25/09/2018

This research would not have been made possible without the help of my

advisers namely Asst Prof Maricel A Tapia and Ms Nguyen Thi Thu Huong, as well

as Dr Nikki H Dagamac and Gerard Navarro for their statistical help and unnerving

faith, patience and support on me

I would also like to thank my family (Mom, Dad, Jules and Kuya Jason) for

their support The Redeña-Santos Family (Tito Jhun, Tita Annie, Kuya PJ, Ate Darla,

Carlo, Paulo and Peterd), the Redeña-Valdenarro Family (Tita Issa, Noreen, Noriel

and Nhica), the Corpuz Family and the Lanzador Family for their care and support and

being my second family in Laguna

I would also like to thank my friends (Carlo, Hannah, Alex, Jeanne, Ate

Colleene, Mark and Kuya Jose) for their help when I needed a hand and for keeping

me sane in general

NICOLE ALEXIA VERIDIANO DE CASTRO

TABLE OF CONTENTS

List of Figures v

List of Tables vi

List of Abbreviations ix

Part I Introduction 1

1.1 Research Rationale 1

1.1 Research Questions 4

1.2 Research Objectives 4

1.3 Significance of the Study 5

1.4 Hypotheses 5

1.5 Scope and Limitations 6

1.6 Definition of Terms 6

Part II Review of Related Literature 9

2.1 Extreme Weather Events and its Effects on Agriculture 9

2.1.1 Extreme Weather Events 9

2.2 Risk Perception among Farmers 12

2.2.1 Risk Perception 12

2.2.2 Measurement and Determinant for Risk Perception 15

2.3 Risk Attitude among Farmers 16

2.3.1 Risk Attitude 16

2.3.2 Measurement and Determinant for Risk Attitude 18

2.4 Conceptual Framework 19

Part III Methodology 20

3.1 Materials 20

3.1.1 Farm Survey Questionnaire 20

3.1.2 Qualitative Pre-Survey: Focus Group Discussion (FGD) and Key Informant Interviews (KII) 20

3.2 Description of the Study Area 21

3.3 Selection of Respondents 22

3.4 Data Gathering 25

3.5 Method of Analysis and Data Presentation 26

3.5.1 Quantitative Analysis 26

3.5.2 Qualitative Analysis 26

Part IV Results and Discussion 29

4.1 Profile of Respondents 29

4.1.1 Socio-economic profile 29

4.1.2 Farm profile 29

4.2 Risks to Farming and Adaptation Strategies 37

4.2.1 Risks to Farming 37

4.2.2 Impacts of Extreme Weather Events on production 41

4.2.3 Adaptation Strategies 52

4.2.3.1 Adaptation Strategies to Pests 52

4.2.3.2 Adaptation Strategies to Extreme Weather Events 55

4.2.4 Key farm production decisions 69

4.2.5 Climate’s influence on crop production decisions 72

4.3 Risk Perception and Risk Attitude 75

4.3.1 Risk Perception to Extreme Weather Events 75

4.3.1.1 Extreme Weather Events experienced by the Farmers 75

4.3.1.2 Likelihood of occurrence 77

4.3.1.3 Potential loss 84

4.3.2 Risk Attitude to Extreme Weather Events 99

A Number of Adaptation Strategies 99

B Nature of the Adaptation Strategies 100

4.4 Analysis 103

4.4.1 Relationship of Risk Perception, Risk Attitude and Socioeconomic Characteristics of Rice Farmers 103

4.4.2 Relationship of Risk Perception, Risk Attitude and Socio-economic Characteristics of Vegetable Farmers 106

4.4.3 Overall results 107

4.4.4 Risk Attitude and Perception and Agricultural Practices 110

4.4.4.1 Risk Perception and Agricultural Practices 110

4.4.4.2 Risk Attitude and Agricultural Practices 115

Part V Conclusion and Recommendations 117

5.1 Conclusion 117

5.2 Recommendations 119

References 121

Appendices 130

LIST OF FIGURES

Figure 1: Conceptual framework 19

Figure 2: Slope map of Siniloan, Laguna highlighting the study areas (CLUP, 2013) 22 Figure 3: Risk matrix 27

Figure 4: Impacts of drought on rice farmers 42

Figure 5: Impacts of drought on vegetable farmers 43

Figure 6: Impacts of typhoon on rice farmers 44

Figure 7: Impacts of typhoon on vegetable farmers 45

Figure 8: Impacts of excessive rains on rice farmers 46

Figure 9: Impacts of excessive rains on vegetable farmers 47

Figure 10: Impacts of flood on rice farmers 48

Figure 11: Impacts of flood on vegetable farmers 49

Figure 12: Surveyed rice farmers' perception on the probability of different sources of climate risk (1 = very low, 5 = very high) Source: Data on surveyed farmers 81

Figure 13: Surveyed vegetable farmers' perception on the probability of different sources of climate risk (1 = very low, 5 = very high) Source: Data on surveyed farmers 84

Figure 14: Surveyed rice farmers’ perception on the overall potential loss of production in rice farming due to extreme weather events 87

Figure 15: Surveyed vegetable farmers’ perception on the overall potential loss of production in vegetable farming due to extreme weather events 90

Figure 16: Overall risk perception of the rice farmers on different climatic hazards in farming 94

Figure 17: Overall risk perception of the vegetable farmers on different climatic hazards in farming 97

Figure 18: Overall results of rice and vegetable farmers' risk perception based on the number of adaptation strategies 100

Figure 19: Risk attitude of rice farmers towards extreme weather events 101

Figure 20: Risk attitude of vegetable farmers towards extreme weather events 102

LIST OF TABLES

Table 1: Sampling distribution of the rice farmers in each elevation gradient 24

Table 2: Sampling distribution of the vegetable farmers in each elevation gradient 24

Table 3: Risk score and their definitions on the probability and potential loss 27

Table 4: Risk perception risk score multiplying the probability and potential loss 27

Table 5: Socio-economic characteristics of rice farmer-respondents 30

Table 6: Socio-economic characteristics of vegetable farmer-respondents 32

Table 7: Farm profile of rice farmer-respondents 35

Table 8: Farming profile of vegetable farmer-respondents 37

Table 9: Perceived risks to farming by rice farmer-respondents 38

Table 10: Perceived risks to farming by vegetable farmer-respondents 39

Table 11: Adaptation strategies of experienced rice farmers on the impacts of field rats 53

Table 12: Adaptation strategies of rice farmers on the impacts of birds 54

Table 13: Adaptation strategies of experienced rice farmers on the impacts of insects54 Table 14: Adaptation strategies of experienced vegetable farmers on the impacts of field rats 55

Table 15: Adaptation strategies of experienced vegetable farmers on the impacts of insects 55

Table 16: Pre-impact adaptation strategies of rice farmers on drought 57

Table 17: Post-impact adaptation strategies of rice farmers on drought 58

Table 18: Pre-impact adaptation strategies of vegetable farmers on drought 59

Table 19: Post-impact adaptation strategies of vegetable farmers on drought 59

Table 20: Pre-impact adaptation strategies of rice farmers on typhoon 60

Table 21: Post-impact adaptation strategies of rice farmers on typhoon 61

Table 22: Pre-impact adaptation strategies of vegetable farmers on typhoon 62

Table 23: Post-impact adaptation strategies of vegetable farmers on typhoon 62

Table 24: Pre-impact adaptation strategies of rice farmers on excessive rains 64

Table 25: Post-impact adaptation strategies of rice farmers on excessive rains 64

Table 26: Pre-impact adaptation strategies of vegetable farmers on excessive rains 66

Table 27: Post-impact adaptation strategies of vegetable farmers on excessive rains 66

Table 28: Pre-impact adaptation strategies of rice farmers on flood 67

Table 29: Post-impact adaptation strategies of rice farmers on flood 68

Table 30: Pre-impact adaptation strategies of vegetable farmers on flood 69

Table 31: Post-impact adaptation strategies of vegetable farmers on flood 69

Table 32: Factors that influence rice farmers’ key crop production decisions 70

Table 33: Factors that influence vegetable farmers’ key farming production decisions 71

Table 34: Crop production decisions influenced by climate variability and extremities on rice farmers 73

Table 35: Crop production decisions influenced by climate variability and extremities on vegetable farmers 74

Table 36: Extreme weather events experienced by the rice farmers 76

Table 37: Extreme weather events experienced by the vegetable farmers 77

Table 38: Risk rate of rice farmers on drought 78

Table 39: Risk rate of rice farmers on typhoon 79

Table 40: Risk rate of rice farmers on excessive rains 79

Table 41: Risk rate of rice farmers on flood 80

Table 42: Risk rate of vegetable farmers on drought 81

Table 43: Risk rate of vegetable farmers on typhoon 82

Table 44: Risk rate of vegetable farmers on excessive rains 82

Table 45: Risk rate of vegetable farmers on flood 83

Table 46: Perceived potential loss of rice farmers on drought 85

Table 47: Perceived potential loss of rice farmers on typhoon 85

Table 48: Perceived potential loss of rice farmers on excessive rains 86

Table 49: Perceived potential loss of rice farmers on flood 86

Table 50: Perceived potential loss of vegetable farmers on drought 88

Table 51: Perceived potential loss of vegetable farmers on typhoon 88

Table 52: Perceived potential loss of vegetable farmers on excessive rains 89

Table 53: Perceived potential loss of vegetable farmers on flood 89

Table 55: Risk perception of rice farmers on typhoon 92

Table 56: Risk perception of rice farmers on excessive rains 93

Table 57: Risk perception of rice farmers on flood 93

Table 58: Risk perception of vegetable farmers on drought 95

Table 59: Risk perception of vegetable farmers on typhoon 95

Table 60: Risk perception of vegetable farmers on excessive rains 96

Table 61: Risk perception of vegetable farmers on flood 96

Table 62: Summary table of significant correlation analyses on rice farmers’ risk perception and risk attitude on selected variables 104

Table 63: Summary table of significant correlation analyses on vegetable farmers' risk perception and risk attitude on selected variables 106

Table 64: Summary table of significant correlation analyses on farmers’ risk perception and risk attitude on selected variables 107

Table 65: Overall correlation analysis on the relationship between farmers' agricultural practices and risk perception towards extreme weather events 112

Table 66: Overall simple linear regression analysis on the relationship between farmers' agricultural practices and risk perception towards extreme weather events 114 Table 67: Overall correlation analysis on the relationship between farmers’ agricultural practices and risk attitude towards extreme weather events 115

Table 68: Overall ordered probit regression analysis on the relationship between farmers’ agricultural practices and risk attitude towards extreme weather events 116

LIST OF ABBREVIATIONS

PART I INTRODUCTION 1.1 Research Rationale

In Southeast Asia, agriculture is a major source of livelihood in almost every country where approximately 115 million hectares of land is devoted for agricultural production (ADB, 2009) In the Philippines, agriculture provides 30% of employment and 10% of the country’s gross domestic product in 2013 (NEDA, 2015) However, agriculture in the Philippines is highly vulnerable to climate change (FAO, 2017; IPCC, 2014) The increase in global temperature and rainfall variability are expected to have a critical impact on the country’s agriculture sector Moreover, drought and typhoons increase the regularity of pest infestations therefore intensifying the risks the farmers have to face in their production In fact, over the last decade, about 37% of the economic impacts of natural and climate-related events was assimilated by the Philippine’s agriculture sector (FAO, 2017) The adverse impacts of climate change such as more frequent and severe typhoons, floods and drought threaten the country’s food security, rural livelihoods and economy since most of the country’s economy relies on agriculture and natural resources as a primary source of income (Redfern et al., 2012), such as small-scale farmers Hence, climate extremes threaten and disproportionately affect small-scale farmers, which remain to be the poorest members of the population (FAO, 2017)

Small-scale farmers produced 80% of the food consumed in Asia and occupy 85% of Asia’s farmlands (FAO, 2012; FAO, 2014) Their significant contribution on an Asian country’s economy will be severely affected by the

effects of climate change as well as worsening issues of food security, especially

on developing countries such as the Philippines Small-scale farmers are considered disproportionately vulnerable to climate change and natural disasters because they are often poor, have very limited assets and are greatly dependent

on natural resources (Frank & Penrose Buckley, 2012) Their livelihood’s dependence on acceptable temperature ranges and patterns of rainfall makes their crop yields at risk due to climatic variability Any sudden or unexpected climatic changes directly affect their agricultural production hence, affecting their household’s food security, income and well-being (Vignola et al., 2015; IPCC, 2007; Agriculture: Vulnerability to Climate Change, n.d.) Moreover, the risk associated with their livelihood is high Farming’s dependence on climate makes small-scale farmers’ livelihood exposed to possibilities of losses of production and uncertainty of return on their investment (Lucas & Pabuayon, 2011) Moreover, they have few livelihood options when typhoons and floods wipe out their production Although small-scale farmers are well experienced in dealing with climatic variability, the increased variability brought about by climate change is beyond the capacity of traditional coping strategies practiced (Pettengell, 2010) Therefore, as the impacts of climate change is expected to continue to intensify, it is important to enhance small-scale farmers’ adaptive capacity to reduce their vulnerability to these impacts through determining and understanding how these farmers decide under risky situations, which is through understanding a farmers’ risk perception and risk attitude

The risk perception and risk attitude of small-scale farmers towards extreme weather events are very important since these influences how they would respond under risky situations, specifically in risk management strategies Previous studies revealed that a farmer’s risk attitude (risk-averse, risk-neutral and risk-taker) is the foremost step in understanding the behavior and coping strategies of small-scale farmers to mitigate the impacts of environmental hazards such as extreme weather events (Lucas & Pabuayon, 2011; Saqib et al., 2016) A farmer’s risk attitude towards a hazard is influenced by the farmer’s perception towards the risk (Hillson & Murray-Webster, 2005) Therefore, by better identifying and understanding the risks perceived by small-scale farmers as well

as their chosen response to those risks is important in designing improved risk management strategies and policies to improve not only their agricultural production, but also the resilience and capacity of small-scale farmers to current and future extreme weather events brought about by climate change

2 What are the climate-related risks in agricultural production and the farmers’ adaptation strategies?

3 What risk do the farmers perceive as they are most exposed to and the farmers’ risk attitudes?

4 What is the relationship between the farmers’ risk attitude and their perceived farming risks?

5 How do the farmers’ socioeconomic characteristics influence their risk perception and risk attitude?

1.2 Research Objectives

 To describe the socio-economic and socio-demographic profile of the respondents

 To identify the climate-related risks in agricultural production and the farmers’ adaptation strategies

 To determine the risk attitude and risk perception of the farmers

 To analyze the relationship between the farmers’ risk attitude and perceived farming risks, as well as the influence of socio-economic characteristics

1.3 Significance of the Study

This study provided baseline information about risk attitude and perceptions of small-scale farmers of Siniloan, Laguna This information would help in capacity building efforts to reduce vulnerability to extreme weather events as well as in designing risk management tools and strategies for farmers to

avoid and overcome losses due to various sources of risk

1.5 Scope and Limitations

The study was conducted from March 2018 to May 2018, in Siniloan, Laguna, Philippines The focus group discussion (FGD) for each category was carried out in the month of March 2018 while the household survey was carried out in the months of April to May 2018 and the data analysis in the month of June 2018

Although the research has reached its aims, there were some unavoidable limitations that have been encountered during the study: (1) a larger number of respondents was desirable but limited by lack of manpower as well as the availability of the respondents to be interviewed; (2) There was a small number

of rice farmers in the upland area of Siniloan, Laguna, hence fewer respondents for this stratum; (3) Gathering the desired number of farmers for the FGD in the upland area since not only was there a small number of farmers as previously stated, but their farms are far away from each other as well; (4) Probable bias seems to be unavoidable since the willingness of some farmers to be interviewed and their honesty when answering the questionnaire is subjective causing now random measurement errors in determining the risk perception and risk attitude

1.6 Definition of Terms

Exposure is defined as the people, property, systems, or other elements present

in hazard zones that thereby subject to potential losses

Extreme weather event pertains to an event that is rare at particular place and

Hazard is the potential occurrence of a natural or human-induced physical event

that may cause loss of life, injury, or other health impacts, as well as damage and loss to property, infrastructure, livelihoods, service provision, and environmental resources

Lowland is an area where the land is at, near, or below the sea level and where

there are not usually mountains or large hills

Perception is way of understanding reality and experience through the senses

which enables judgment

Rainfed relates to agricultural farming practices that rely on rainfall for water

Risk is defined as the possibility of physical and/or social and/or financial

harm/detriment/loss due to a hazard within a particular time frame; Probability of damage

Risk attitude is an individual’s willingness to take risks

Risk-Averse is the willingness of an individual to accept a lower expected return

to obtain lower risk

Risk-Neutral is an individual’s discomfort with uncertainty in the long term

therefore prepared to take whatever short-term actions are necessary to deliver a certain long-term outcome

Risk Perception refers to people’s perception of the possibility that a hazard will

affect them

Risk-Taker is an individual’s willingness to receive greater benefits even if the

risk of obtaining them is high

Risk-Tolerant is an individual’s tolerance to uncertainty and has no strong

desire to respond to threats or opportunities in any way They could tolerate an uncertain outcome if necessary

Small-scale farmers are farmers who cultivate small areas of land (usually less

than 10 ha, often less than 2 ha) and depend on their farms as their main source

of both food security and income

Upland is lands at a higher elevation than the flood plain or low stream terrace

Waterside is an area that is next to a river, lake or ocean

PART II REVIEW OF RELATED LITERATURE

2.1 Extreme Weather Events and its Effects on Agriculture

2.1.1 Extreme Weather Events

The occurrence of weather events being stochastic is an absolute fact A special report on extreme events of the Intergovernmental Panel on Climate Change (IPCC) found evidence that since the 1950s, there have been clear changes in many types of weather events The world has experienced more droughts, floods, and storms due to climate change (IPCC, 2012) In Southeast Asia, extreme weather events such as intense rains and floods, droughts and typhoons have been reported to be more frequent and intense in which the Philippines is among the affected countries (IPCC, 2007)

A report by IPCC (2014) observed that climate change has significantly affected global agriculture in the 21st century and indicated that most countries, including the Philippines, will experience an increase in average temperature, more frequent heat waves, more stressed water resources and periods of heavy precipitation The future impacts of changing climate are projected to worsen as temperature continues to rise and precipitation becomes more unpredictable as well as extreme events These will have greater impacts on sectors with direct exposure to climate change such as agriculture (IPCC, 2012)

Agriculture is a risky business by nature since it relies on climate for its production (Agriculture: Vulnerability to Climate Change, n.d.) Due to climate

change, the increase and variability in the occurrence of extreme weather events such as typhoons, floods and droughts puts farm productivity at risk by potentially lowering crop yield and limiting farm planting options Furthermore, climate change expands and changes the suitable habitats for pests, such as rodents, which is the primary pre-harvest pest of rice (Palis et al., 2010), and diseases, and form new combinations as well Moreover, climate change leads to unpredictable distribution of pests and diseases, thus increasing its risk on agricultural production (Reynolds, 2010) The risks of extreme weather events increase the overall cost of agricultural production by declining the production output, hence decreasing food supply and income of the farmers Therefore, the negative impacts of climate change on agriculture threaten food security and income of small-scale farmers in the affected areas This is particularly true in the Philippines wherein they operate under a risky and uncertain situation

Eiser et al (2012) stated that some communities are more vulnerable, or resilient, than others due to the physical features of an environment (e.g susceptibility to storms or floods) as well as the adaptive or maladaptive responses of the individuals and communities to such hazards It is therefore needed to raise the resilience and adaptive capacity of small-scale farmers to the risks in their production to ensure the safety of their livelihood, income, food security, as well as the economy of the Philippines

2.1.2 Drought

The increasing temperature and variations in humidity puts the crops’ ability to maintain their genetic resistance to pests and diseases, such as herbivorous insects, fungi, bacteria and viruses, at risk The increase in temperature likely leads to new and perhaps unpredictable distribution of pests and diseases (Gregory et al., 2009) Drought is considered the most serious risk

to rice production since most of the farmers’ preferred rice varieties are susceptible to drought stress (Serraj et al., 2009) Farmers’ dependence on rainfall for irrigation leads to a decrease in crop yield due to the increase of climate change events It has been observed that rice crops suffer significant decreases in yields due to drought stress during its reproductive stages, especially during its flowering stages In 2016, the Philippines was affected by an El Niño-induced drought causing watercourses and irrigations to dry up leading to a loss

of 250,000 MT on rice production from 2015-2016

2.1.3 Typhoon, Excessive Rains and Flood

Typhoons and excessive rains result in heavy flooding and increase runoff and soil erosion This results in reduced soil fertility therefore damaging the crops and reducing the productivity (USAID, 2017) More frequent and severe tropical cyclones caused by the shifting of La Niña would continue to exert pressure on agricultural production and certainly cause uncontrolled flooding throughout Southeast Asia (DILG, 2011) In fact, an average of 20 tropical cyclones enters the Philippine Area of Responsibility (PAR) every year (Lee,

2015) In late 2017, the Philippines’ agricultural production was severely affected by Typhoon Tembin (Vinta) causing flashfloods and landslides and leaving a damage on agriculture worth USD 64.4 million (FAO, 2018) Although rice thrives in wet conditions, it cannot survive when submerged underwater for long time periods and affects rice crops at any stage of growth (Redfern et al., 2012) The increased rainfall variability and frequency of extreme weather events put the agriculture sector at high risk of increased pest infestations

2.1.4 Projected Effects of Climate Change on Philippine Agriculture

Agriculture in the Philippines has become significantly threatened by the effects of climate change since a large portion of small-scale farmers are located

in geographically vulnerable locations The changes in temperature greatly influence not only the growth duration, but also the growth pattern and the productivity of rice crops (Redfern et al., 2012) It has been reported by Peng et

al (2004), that an increase of 1C in the mean temperature results in a decrease

on rice yields in the Philippines by as much as 15% Rice yield in the Philippines are predicted to decline about 75% for this century due to water scarcity and increased temperatures, assuming there would be no adaptation and no technical improvements (ADB, 2009)

2.2 Risk Perception among Farmers

2.2.1 Risk Perception

People interpret risk not only on the severity of the threat, but also on a

perception, as defined by Gaillard (2015), is “people’s perception of the possibility that a hazard will affect them” A farmer’s risk perception is important

when choosing an effective adaptation strategy to various sources of risk, since farmers who are unaware of the potential risks are clearly unable to manage them effectively (Gaillard, 2015; Sulewski & Kloczko-Gajewska, 2014) It has been found in previous researches that farmers have considered various risk factors as important Some of which are weather and extreme climatic events such as drought (Sulewski & Kloczko-Gajewska, 2014), pest and diseases (Ullah et al., 2015), and yield and price risk (Lucas & Pabuayon, 2011; Peria et al., 2016) How these perceptions on risk are rated is influenced by various factors

Researchers (Eiser et al., 2012; Rohrmann, 2008; Wauters et al., 2012) have stated that that these perceptions on risk are shaped by the farmers’ past experiences, direct experience (e.g personal experience with the hazard) and indirect experience (e.g media and education) as well as recent events It is assumed that high risk perception leads to personal preparedness, thus having better risk mitigation behavior However, Wachinger et al (2013) have stated that is not necessarily true and at times being the opposite Many studies, including a study of Hall et al (2009), have evidence that farmers with high risk perception will still do not choose to personally prepare themselves in the risks of natural hazards

It has been suggested by Wachinger et al (2013) that risk perception is best influenced by direct experience, since experience with a natural hazard usually leads to a higher risk perception A study of Ruin et al (2007) as cited by

Wachinger et al (2013) found that individuals without direct experience with flood tend to underestimate the danger whilst those with experience tend to overestimate the danger However, this is not usually the case A study of Hall et

al (2009) as cited by Wauters et al (2012) stated that farmers who had experienced a hazard but did not have any damages are more likely to believe that the future event will not likely affect them, therefore having a low risk perception

Results of the study of Lucas and Pabuayon (2011) found that farmers perceive rice production as relatively risky due to their past experiences, in which typhoons occur frequently when the farmers have mostly planted rice Moreover, risk perception is also influenced by certain socio-economic and demographic factors Resource-poor farmers are more likely to perceive farming as not risky

as they have little to lose or gain compared with resource-abundant farmers (Lucas & Pabuayon, 2011) A farmers’ geographic location is an influencing factor on their perception on risk It has been noted by Sulewski and Kloczko-Gajewska (2014) that farmers from different geographic locations experience different climatic conditions and, therefore, have different risk perceptions which could be the result of different exposures to the probabilities of different risk factors, as well as farmers’ mentality and awareness, and could be a mixture of both

According to Rohrmann (2008), “risk perceptions steer decisions about

the acceptability of risks and are a core influence on behaviors before, during and

influences their risk attitude, hence influencing decisions of the farmers’ actions

to be made, particularly in risk management and adaptive capacity (Peria et al., 2016)

However, neither perceptions of nor attitudes towards risk should be taken

as equivalents of actual behavior as stated by Rohrmann (2008) Moreover, measurement errors could not be avoided and one source of error is random measurement error (Bard & Barry, 2000)

2.2.2 Measurement and Determinant for Risk Perception

In measuring risk perception, three paradigms define different types of variables that have been shown to affect peoples’ risk perception—the axiomatic measurement paradigm, the psychometric paradigm and socio-cultural paradigm The most common method used by researchers (Lucas & Pabuayon, 2011; Quinn

et al., 2003; Smith et al., 2000) to measure risk perception is by a psychometric method/theory The psychometric paradigm identifies people’s emotions towards the risky situations that affect the judgment of the risk in ways that go beyond their objective consequences The axiomatic measurement paradigm focuses on the way how people subjectively convert objective risk information such as financial losses and likelihood of occurrence, to reflect the impacts of the risk on their lives (Slovic, 2002) The socio-cultural measurement paradigm examines the effect of the social and cultural groups on the risk perception

2.3 Risk Attitude among Farmers

2.3.1 Risk Attitude

Wauters et al (2014) defined the term “risk attitude” as “people’s willingness to take risks” and is seen as an important determinant or risk behavior Different individuals have different risk attitudes that may cause them

to act differently (i.e risk-averse, risk-neutral, or risk-taker) (Wauters et al., 2014) The same uncertain situation will evoke different preferred attitudes from different individuals or groups, depending on how they perceive the uncertainty And since attitude is a driver of behavior, different people will exhibit different responses to the same situation, as a result of their differing underlying risk attitudes A person’s risk attitude is a unique reflection of one’s personality since

it is influenced by socio-economic factors as well as life experiences A person’s risk attitude also influences how a farmer manages his business (Bard & Barry, 2000) The “true risk attitudes” of persons are not always apparent Thus, risk attitudes must always be measured indirectly Humans tend to hold domain-specific attitudes In fact, risk attitude is neither necessarily stable, nor homogeneous across hazard types (Rohrmann, 2008).

Past literatures (Lucas & Pabuayon, 2011; Roumasset, 1976; Ullah et al., 2015) have indicated that majority of agricultural producers are highly risk averse in nature and will avoid a risky situation even if the returns are higher Studies of Mosley and Verschoor (2003) and Lamb (2003) reported that farmers with lower incomes are more risk averse compared to regular employees

situations where the probability of failure is high This is in accordance with the safety-first rule, which suggests that a farmer normally seeks to meet the needs of his household before anything else (Lucas & Pabuayon, 2011) However, some researches differ from the previous studies

The results of the study of Wauters et al (2014) found that small-scale farmers are more in the risk-neutral spectrum They have stated that studies with farmers’ identified as risk averse may have a cultural background that of which those with risk neutral are more entrepreneurial than other countries However, this statement has no clear comparative evidence The risk attitude of the farmers may also be influenced by the level of exposure to extreme events This is supported by the study of Peria et al (2016) which also had a majority of risk-neutral respondents These are individuals who reside in areas more exposed to extreme events and regularly have to deal with drought, soil erosion and floods that significantly affect their crops, livestock, properties and even lives Moreover, their results indicated that most of the risk-takers reside in areas less exposed to extreme events and have continuous supply of water, and were not greatly affected by floods during typhoons and heavy rains Risk-taking attitudes were also observed by Lucas and Pabuayon (2011) on farmer leaders who had actively attended farmer trainings or seminars This implies that the exposure of the farmers to such activities as well as the knowledge of the farmers influence their risk attitudes

Lucas and Pabuayon (2011) stated that some farmers’ socio-economic characteristics such as wealth influence their risk attitude This is supported by

the findings of (Binswanger, 1980; Holt & Laury, 2002) which indicated that risk aversion is greater in developing countries and decreases with respect to wealth However, few researches such as the findings of Peria et al (2016) and Roumasset (1976) differ from the results of the previous studies The results of their researches reveal that farmers in the Philippines are generally risk-neutral However, risk attitudes are not fixed and may vary depending on the nature of the risk, including other factors such as the socio-economic profile of the respondents (age, education and income) (Saqib et al., 2016), farm profile (farm size) (Saqib et al., 2016), exposure to information, family commitments and responsibilities, as well as past experiences from the risks and the farmers’ perception on the risk (Peria et al., 2016)

2.3.2 Measurement and Determinant for Risk Attitude

There are numerous methods used by researchers to elicit risk attitude A measurement used by researchers (Lucas & Pabuayon, 2011) in determining the risk attitude of the farmers is through the lottery test, which uses a set of lottery The study of Peria et al (2016) measured an individual’s risk attitude by providing future scenarios of climate extremes Researchers have also used the Equally Likely Certainty Equivalent Method (ELCEM) which is a series of questions identifying the annual income of a farmer and identifying the acceptable income chosen by the farmer under series of scenarios influenced by the impacts of hazards on their income

2.4 Conceptual Framework

A farmer’s farming practices depend on his attitude and perception towards risk, particularly in extreme weather events such as typhoon, flood, drought and excessive rains in which the farmer is mostly exposed and vulnerable to A farmer’s risk attitude and perception are domain-specific; hence,

it varies among different risk sources Therefore, the risk attitude and perception

on climate vary depending on the extreme weather event (Figure 1)

Agricultural Practices

PART III METHODOLOGY 3.1 Materials

3.1.1 Farm Survey Questionnaire

A farm survey questionnaire with structured questions was used in the study This was pre-tested to determine ease of facilitation and to assess its validity The questionnaire used for the survey has five (5) sections:

(1) Personal information;

(2) Farming system and experience;

(3) Perceived farm risks;

(4) Risk perception, attitude and adaptation Strategies;

(5) Key production decisions influenced by climate extremes;

The questions were asked in Philippine’s native tongue, Tagalog

3.1.2 Qualitative Pre-Survey: Focus Group Discussion (FGD) and Key

Informant Interviews (KII)

A FGD involving questions that mirrored the farm survey questionnaire was conveyed with selected rice farmers in each category and selected vegetable farmers in the upland area This is to gather qualitative data that can explore the views of the respondents that cannot be measured statistically, which can support and enhance the result from the farm survey as well as to frame the actual survey questionnaire Key Informant Interviews were also held with the members of the Office of the Municipal Agriculturist (OMA) responsible for the rice and

3.1.3 Materials for Data Gathering and Management

A camera and voice recorder was used to capture images and record the answers of the selected respondents from the FGD and KII, which were materials for validating the results and enriching the discussion of this study

The gathered data was inputted in Microsoft Excel 2010, which was also used for the descriptive analysis of the farm survey A general-purpose statistical software, STATA, was used for the correlation and regression analyses on the risk attitude and perception of the respondents and their relationship with selected variables

3.2 Description of the Study Area

The study was conducted in Siniloan, Laguna, Philippines, wherein the municipality is considered as a rice producing municipality Laguna is located in South-Eastern Luzon, about 30 kilometers outside the Philippines’ capital, Manila (Figure 2) It is highly exposed to multitude of hazards, predominantly flooding This is due to the overflow from the province’s largest lake, Laguna de Bay, during heavy downpours causing the inland rivers to turn farmlands into vast bodies of water and is worsened by improper waste management (Lim, 2015)

To better understand the interconnectedness of social, environmental and ecological processes critical for sustainable development, the Ridge-to-Reef Approach was used in site selection Barangays Kapatalan and Magsaysay were chosen in consultation with the local municipality to represent the upland whilst Halayhayin and Wawa to represent the lowland and waterside, respectively

Multiple barangays were chosen to represent the upland for there were only limited farmers practicing rice crops residing in the area

Figure 2: Slope map of Siniloan, Laguna highlighting the study areas (CLUP, 2013)

For the farm survey, the number of respondents was determined by the population of small-scale rice and vegetable farmers in each elevation gradient using the Slovin’s formula at 90% confidence level shown below The Slovin’s formula was used since nothing about the behavior of the population is known at all

(1+𝑁𝑒2)

Where:

n = sample size;

N = total population size;

e = desired margin of error (acceptable error)

Table 1: Sampling distribution of the rice farmers in each elevation gradient

Note: Ni = Population of the barangay; ni = Proportionate allocation of the population

Table 2: Sampling distribution of the vegetable farmers in each elevation gradient

Percentage (%)

Note: Ni = Population of the barangay; ni = Proportionate allocation of the population

A Focus Group Discussion involving three (3) farmers from the upland and five (5) farmers from the lowland and waterside was conducted to gather qualitative data The upland involved only three (3) respondents since there are only a limited number of rice farmers in the area and their farms are distant from each other as stated in the limitations This was also conducted with three (3) vegetable farmers in the upland since these are crops more commonly practiced

by the upland farmers in Siniloan, Laguna The discussion was a pre-survey of each category involving open-ended questions wherein the responses obtained were used as a baseline for the options of the Farm Survey Questionnaire as well

as to enrich the discussion with the gathered qualitative data The findings in the

FGDs would also be able to provide insights and better explain and understand the results from the actual survey

3.4 Data Gathering

The study used both primary and secondary data, the collected data from the farmers from the selected barangays from each ecosystem (upland, lowland and waterside) in Siniloan, Laguna and the municipality archives, respectively

The primary data include the farmers’ (i) socio-economic profile such as: age, gender, educational attainment, main and other occupation, as well as their civil status; (ii) farm profile and farming system; (iii) perceived farm risks; (iv) risk perception, attitude and adaptation Strategies and; (v) key production decisions influenced by climate extremes All data were obtained through face-to-face interviews using a structured questionnaire A FGD with selected rice farmers on the chosen barangays from the upland, lowland and waterside and an addition of vegetable farmers for the upland was conducted in validation of the gathered results as well as to enrich the gathered information

The secondary data to support this research were from past researches, articles and reports related to the effects of extreme weather events on farmers from sources such as the web and library of the College of Forestry and Natural Resources in University of the Philippines

3.5 Method of Analysis and Data Presentation

3.5.1 Quantitative Analysis

Descriptive analysis was used to summarize the data obtained such as: (i)

The socioeconomic characteristics of the respondents; (ii) Perceived risks; (iii) Risk attitude and; (iv) Adaptation strategies to perceived risks Frequency distribution and percentages were calculated as well as data range, mean and standard deviation

For the relationship analyses, the Chi-squared Test of Independence (X 2 )

was used to identify the relationship between risk attitudes and risk perceptions

of the respondents The Pearson Correlation Coefficient (Pearson’s r) was used to

analyze the relationship between the farmers’ socioeconomic characteristics and agricultural practices to their risk perception and risk attitude The Simple Linear Regression and Ordered Probit Regression were used to analyze the relationship between the farmers’ agricultural practices to their risk perception and risk attitude, respectively

3.5.2 Qualitative Analysis

Eliciting Farmers’ Risk Perceptions

The farmers’ risk perceptions were determined by identifying the risks they recognize that influence their livelihood and ranking them based on their significance Furthermore, the farmers’ risk perceptions were also determined through questions on the events of weather extremities (i.e drought, flood,

= very low, 2 = low, 3 = neutral, 4 = high, and 5 = very high) to represent the probability and potential loss of the stated climate extreme on destroying their production (Table 3)

To calculate the risk perception, the data from the probability and potential loss in risk rates was then multiplied (risk perception = probability x potential loss) The product of the two variables would then elicit the farmers’ risk perception (Table 4 & Figure 3)

Table 3: Risk score and their definitions on the probability and potential

Low (21 to 40)

Medium (41 to 60)

High (61 to 80)

Very High (81 to 100) Consequence

Figure 3: Risk matrix

Eliciting Farmers’ Risk Attitudes

The analysis of the farmers’ risk attitudes involved a situational question Specifically, they were asked on their adaptation strategy to avoid potential risks and impacts of an extreme weather event as well as their adaptation strategy during/after the event The farmers’ chosen adaptation strategy to secure their income will elicit their risk attitude with the more they avoided the potential impacts (e.g do not plant), the more they were likely to be risk averse

The risk attitudes, risk-neutral and risk-tolerant, were considered as one,

being risk-neutral

PART IV RESULTS AND DISCUSSION 4.1 Profile of Respondents

4.1.1 Socioeconomic profile

Rice Farmers

A majority of the small-scale rice (Oryza sativa) farmer-respondents in the

three (3) barangays in Siniloan, Laguna were male (85%), married (80%) and had

an average age of 56 years old Most of the farmer-respondents had obtained elementary education (45%), had farming as their main (76%) and only source of income (41%), and about one quarter also worked as fishermen (24%) The average household size was 4 with the majority of the respondents (46%) having 4-6 members in the family (Table 5)

In terms of livelihood, most of the respondents in the lowland area of Brgy Halayhayin and the upland area of Brgys Magsaysay and Kapatalan were small-scale farmers (84%) while the respondents in the waterside area of Brgy Wawa were mostly small-scale farmers (70%) They also worked as fishermen (21%) with fishing being an option (24%) for livelihood in times of extreme weather events such as La Niña These findings validated the results from the FGD wherein their adaptation strategy in times of extreme weather events was through a different source of income such as fishing

Table 5: Socio-economic characteristics of rice farmer-respondents

Barangay

Profile

Waterside Brgy Wawa (n = 33)

Lowland Brgy Halayhayin (n = 31)

Upland

Total (n = 74)

Brgy Magsaysay &

Kapatalan (n = 10)