UPBLFI by Climate Change Adaptation in Agriculture

1656

2 0 Philippine Institutional Strengthening Capacity to 1 Adapt to Climate Change Outcome 3.1 Activity 3.3 1

Development of a Vulnerability Assessment Tool for the Agricultural Sector of Benguet and Ifugao with Capacity Building of its use and Community-based Adaptive Strategies, its Monitoring and Evaluation Procedures.

Synthesis Report

UPLB Foundation Inc.

Lanzones St., UPLB Campus, College, Laguna, 4031 PHILIPPINES Tel: (049) 536 3688 Fax: (049) 536 6265

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Executive Summary Upland communities dependent on agriculture are one of the identified groups prone to be adversely affected by climate change. National governments in their capacity to prioritize projects and the role of local governments in dealing with risk reduction have been recognized as key factors to build resilient communities and nations. Thus, both communities and local authorities should be empowered to manage and reduce disaster risk by having access to the necessary information, resources and authority to implement actions. Extreme and varying climate; accessibility of communities to cropping technology, production inputs and the market; declining ecosystems and vulnerable rural livelihoods are main underlying risk drivers, which need to be addressed to build resilient agricultural communities. In response to the evident lack of a systemic approach to these issues, the Millennium Development Goal Fund from the Spanish Government has worked with partners in the Food and Agriculture Organization of the United Nation to build alliances with the Philippine’s Department of Agriculture to promote agricultural risk reduction for upland communities. It chose to study Benguet and Ifugao in the Cordillera Autonomous Region and draw from their wealth of indigenous knowledge in vulnerability assessment and adaptive capacity from hundreds of years of experience in formulating a sustainable agricultural system for upland communities in the country. The study conducted by UPLBFI for this project aimed to use this indigenous knowledge and to combine with current science-based tools in assessing the vulnerability of pilot sites in Benguet and Ifugao and proposing some adaptive tools that can make a difference in the advent of climate change. Study Component 1A conducted a review of available science-based vulnerability and adaptive capacity assessment tools in order to build on existing methodologies. The framework developed by Smith (2010) was adapted, which looks into the potential impact brought about by climate change and the adaptive capacity of the community. Potential impacts are brought about by the exposure and sensitivity while adaptive capacity describes the ability to adjust or take advantage of climate change. The study looked for practical and easy to follow community-level vulnerability assessment tools that emphasize the agricultural sector and seek to integrate agricultural indigenous knowledge system with scientific and technical concerns.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

After reviewing fourteen different V&A assessment tools they concluded that the most suitable are: ADPC Based Disaster Risk Management: Field Practitioners’ Handbook 2004, CARE Climate Vulnerability and Capacity Analysis (CVCA) Handbook, 2009 and PRRM Vulnerability and Adaptation Assessment Toolkit, 2009. The team was able to integrate the relevant factors and procedures of these tools into one V&A Tool: Agricultural System Vulnerability and Adaptive Capacity Assessment (AgSys-VACA), which has a systematic approach on the different requirements and constraints with regards to upland farming in Benguet and Ifugao. It draws from a wide array of qualitative data gathering tools that investigate area’s biophysical characteristics as well as the local community’s exposure, sensitivity and adaptive capacity to different hazards. Study component 1 B conducted field studies in the identification of Indigenous knowledge-based vulnerability and adaptive capacity assessment tools in Benguet and Ifugao. It drew upon millenniums of farming experience and knowledge existing in these upland tribal communities. Indigenous knowledge (IK) has a peculiarity for predicting weather patterns, based on old traditions handed down by ancestors who for many centuries were keen in observing natural occurrences around them like the behavior of plants and animals, and the characteristics of their physical environment in relation to experienced weather conditions. Many of these indicators have scientific explanations like seasonal migration of birds and insects, and the flowering of bamboo is a survival trait to secure the next generation of the species. The cold spells experienced in January as precursors of coming droughts may be explained by the meteorological conditions which cause droughts. Therefore, these prediction indicators cannot be missed out as illogical because they often have scientific grounding. Located in historically vulnerable areas to extreme weather, indigenous people have been thriving in the Cordilleras for millenniums and have transformed the mountains into remarkable rice production fields. They have perfect knowledge of the terrain and the dynamics of gravity, water and the earth which both supports their communities and their rice terraces. They have a good understanding of the hydrologic cycle and know that having forest cover above the terraces is vital to ensure adequate water for the rice the grow. By historical observations they can tell if there are precursors to the dangers from climatic hazards and have incorporated them into the traditions and beliefs of the community in order to avoid catastrophic events. Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Indigenous knowledge (IK) contains strategies for planting and other practices for adaptation, based on the indicator they see in nature, and it has developed community-wide agricultural activities into rituals. On the other hand, erosion of indigenous cultural practices among younger farmers is a fact. Nowadays, IK is rarely used in lieu of modern agricultural practices. Study component 2A developed a simplified science-indigenous knowledgebased vulnerability assessment tool and adaptation strategies for the upland communities of Benguet and Ifugao. The simplified vulnerability assessment tool is an attempt to provide an easy to use guide for identifying vulnerable agricultural areas in a quick but organized manner. The field questionnaire tool is a product of the integration of agriculture variables, often used for describing agricultural systems and designing appropriate interventions, and actual experiences and observations about agriculture in Benguet and Ifugao province that may provide reliable information about immediately needed and appropriate adaptation measure for agricultural areas and communities. A Vulnerability Index from 0 to 10 was developed to give a comparative evaluation of various areas being assessed. As a contribution to methodology and tool development, optimal planting dates of crops were determined using two approaches. The optimal cropping calendar for corn and rice were constructed based on rainfall and yield probabilities. Although the two methods generally gave different planting dates, they both recommended the first week of May as the optimal planting date of corn for normal years and the last week of April for wet years in Baguio City. On the other hand, the two methods came up with the second week of September as the optimal planting date of corn during wet years in La Trinidad. Lastly, they both arrived at the last week of August as the optimal planting date of rice in Banaue. In contrast to the predictions based on rainfall probabilities, the results for optimal planting dates derived based on yield probabilities are more plausible and therefore recommended. This is because of the fact that estimated crop yields using eco-physical crop simulation model accounts more for the agro-climatic environment and also crop management strategies. To understand the weather scenarios for 2020 and 2050 in Baguio City, the historical analogues of these years were determined using four methods. The first two methods which involved the cluster analysis of years failed to find immediate historical analogue. Hence, two methods involving the use of the least average absolute deviation were explored. Results showed that among the 30 historical years considered, 1995 has the closest weather scenario to 2020 and 2050. Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

However, given data limitations such as: a) incomplete historical weather data and b) unavailability of crop genetic efficients for varieties commonly planted in Ifugao and Benguet; the construction of optimal planting dates for selected varieties was carried out more as a methodological exercise to illustrate its usefulness as a tool for climate change adaptation planning—granted that there is access to complete historical data and available genetic coefficients for local varieties. The optimal/recommended planting dates in this report are not in any way endorsed by FAO and DA for inclusion or adoption into the current agricultural production systems of Ifugao and Benguet.

Study component 2B was the validation, verification and updating of the community-based Crop Loss and Damage Assessment Models of the Department of Agriculture in Benguet and Ifugao to have a more accurate evaluation of the impacts of climate change. Rice yield data from the National Cooperative trials was used to construct a function that relates rice productivity to weather variables such as amount of rainfall, maximum, minimum and mean temperatures and relative humidity. Data sets on the weather variables were obtained from PAGASA Main Office and Benguet PAGASA Station. Two models were constructed, one for the dry season and another for the wet season. The models developed had very low R-squares with the wet season model explaining only 46.66% of the variation in yield while that of the dry season explained only 25.89% percent of the variation in log (yield). This leads to erratic predictions in the yield. The model constructed for the dry season had an even lower R-square even with yield already transformed to its logarithm. Although the use of the models for prediction purposes may not be feasible, several concepts such as the effects of weather variables on yield and their interaction with several other variables were seen and demonstrated by the model. The importance of minimum and maximum temperatures during the vegetative, reproductive and ripening stages were demonstrated. The information generated may shed light on how the factors affect yield for future activities of similar nature. These poor modeling results can be attributed to the absence of reliable and complete data. The data set used was heavy with data gaps. Even data on weather variables were filled with data gaps, sometimes with one whole cropping season data missing. Mismatches between crop and weather data were common. While data on Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

crops from other locations are available, data on the weather variables were not, as seen in the case of Banaue. Rice data were available for Banaue for 1991 to 2009. However, weather data were available only for 1991 to 1993. Furthermore, some data available were expressed only in terms of annual production. The use of response surface regression in place of multiple-linear regression may be a potent tool in modeling the problem at hand but requires a lot of observations to enable estimates of acceptable precision. High R-squares are sometimes obtained without any predictor being declared significant by the tests due to inadequate degrees of freedom for error. While literature suggests nonlinear models, which involve interactions between weather variables, there was no adequate amount of data on which the response surface equation can be validated. Similar to component 2A, the results of component 2B are not recommended by FAO and DA for actual field use or adoption due to the absence of reliable and complete data.

Study component 3A conducted a Trainors’ Training on the Vulnerability and Impact Assessment Tools on Agriculture for Local Stakeholders in Benguet and Ifugao. The training was designed to disseminate the Simplified Science-Indigenous Knowledge-Based Vulnerability Assessment Tool and Adaptation Strategies from Study component 2A to the local stakeholders (LGUs, farmers and MAO) that could re-echo these procedures to other communities and municipalities in Benguet and Ifugao. Specifically, the Component aimed to: •

Update the stakeholders of the current development on climate change;

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Update the stakeholders on the available climatic and biophysical information;

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Provide the stakeholders with vulnerability and impact assessment tool developed by the preceding project components;

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Train the stakeholders in using the assessment tools and how they can teach stakeholders from other communities use it; and

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Enable the participants to conduct their own vulnerability and impact assessment. The final Study component 3B conducted a training on Capacity Building of

Local Stakeholders on Community-Based climate Change Adaptations in Benguet Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

and Ifugao: Monitoring and Evaluation of Adaptation Measures. The objective of this component was to train locals on the monitoring and evaluation of Climate Change and to identify the factors related to performance and effectiveness of the adaptation and risk mitigation strategies in Benguet and Ifugao that were taught in Component 3A. Training participants included Farmer Leaders, DA Regional Staff, LGU Representatives, SUC Representatives, NGO, etc. The activities of the component were as follows: •

Prepare a learning module for seminar/workshops in Monitoring and Evaluation of the performance and effectiveness of Adaptation and Risk Mitigation Measures.

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Conduct a seminar/workshop in Monitoring and Evaluation of the Performance and Effectiveness of Adaptation and Risk Mitigation Measures in Benguet; and

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Conduct a seminar/workshop in Monitoring and Evaluation of the Performance and Effectiveness of Adaptation and Risk Mitigation Measures in Ifugao

A set of final conclusions and recommendation was drawn upon the results of all study components.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Table of Contents Title Executive Summary

Page 2

Introduction

Component Results

Component 1A: Review and Screening of Available Vulnerability Assessment Tools for Their Application in the Agricultural Sectors in Benguet and Ifugao

Component 1B: Local Knowledge and Tools for Assessing Vulnerability of the Agricultural Systems to Changing Climate: The Case of Ifugao and Benguet Provinces

Component 2A: Simplified Vulnerability Assessment Tools Combining Indigenous and Scientific Knowledge for the Agricultural Sector in Benguet and Ifugao

Component 2B: Updating of the Crop Damage and Loss Assessment Model of the Department of Agriculture

Component 3A: Trainors’ Training on the Vulnerability and Impact Assessment Tools on Agriculture for Local Stakeholders in Benguet and Ifugao

Component 3B: Capacity Building of Local Stakeholders on Community-Based Climate Change Adaptations in Benguet and Ifugao: Monitoring and Evaluation of Adaptation Measures

Conclusion and Recommendations

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Introduction Food production areas in the uplands of the Philippines are considered to be particularly vulnerable to climate change since crop and livestock productivity is highly dependent on climatic conditions. Changes in temperature and amount of rainfall coupled with the occurrence of extreme weather events such as drought, heavy rains, and landslides may cause changes in the growing seasons, heat stress in plants and animals, outbreaks of pests or diseases and increase in soil erosion with adverse affects on people and the environment. National governments in their capacity to prioritize projects and the role of local governments in dealing with risk reduction have been recognized as key factors to build resilient communities and nations. Thus, both communities and local authorities should be empowered to manage and reduce disaster risk by having access to the necessary information, resources and authority to implement actions. Extreme and varying climate; accessibility of communities to cropping technology, production inputs and the market; declining ecosystems and vulnerable rural livelihoods are main underlying risk drivers, which need to be addressed to build resilient agricultural communities. In response to the evident lack of a systemic approach to these issues, the Millennium Development Goal Fund from the Spanish Government has worked with partners in the Food and Agriculture Organization of the United Nation to build alliances with the Philippine’s Department of Agriculture to promote agricultural risk reduction for upland communities in the Cordillera Autonomous Region. In 2007, the Presidential Task Force on Climate Change (2007) stated that the northern part of Luzon is one of the two regions in the Philippines that have warmed and dried the most. It is also the area that is most frequently hit by tropical cyclones since 1980. The projects focused on two provinces in Northern Luzon namely, Benguet and Ifugao and recognized the wealth of indigenous knowledge in vulnerability assessment and adaptive capacity from hundreds of years of experience and its high relevance for formulating a sustainable agricultural system for upland communities in the country. The study conducted by UPLBFI for this project aimed to use this indigenous knowledge and to combine with current science-based tools in assessing the vulnerability of pilot sites in Benguet and Ifugao and proposing some adaptive tools that can make a difference in the advent of climate change. Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Figure 1 provides an overview of the study components and how they are interlinked.

Figure 1. Methodological Framework of the UPLBFI study for MDG-F 1656 Outcome 3.1

In order to develop a vulnerability assessment tool for the agricultural sectors in Benguet and Ifugao, Component 1A of the study reviewed various existing science-based vulnerability assessment tools for various hazards in literature to gather and build upon their important practical application to agriculture in upland communities.

Component 1B documented indigenous knowledge and practices the ethnic people of the Cordillera used to sustain their upland agricultural systems for thousands of years. It conducted focus group discussions, key informant interviews and field verification to identify local knowledge, as well as indigenous vulnerability assessment tools for agriculture in Benguet and Ifugao.

Component 2A worked with the results of components 1A and 1B in the design and development of a simplified vulnerability assessment tools combining scientific and indigenous knowledge for the agricultural sectors of Benguet and Ifugao including the integration of the hazards assessment tools. It also developed adaptation tools such as cropping calendar and climate scenario analog of 2020 and 2050. Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Component 2B seeked to recalibrate the Department of Agriculture’s Crop Loss Assessment Procedures for vegetables that are widely produce in Benguet in order to have a more accurate valuation of crop financial losses after a hazard. This would allow a cost effective approach in planning hazard mitigation and adaptation projects in the future.

Component 3A developed and carried out a training module on the developed vulnerability assessment tool, giving detailed criterion in the formulation of the assessment team as well as the proper conduct and analysis of the assessment.

Component 3B was a capacity building activity for the planning and use of community-based adaptive strategies, and their monitoring and evaluation in order to refine their effective applications in vulnerable communities.

The following chapters will present key findings of all study components drawing upon the individual reports for all components.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Component Results

Component 1A: Review and Screening of Available Vulnerability Assessment Tools for Their Application in the Agricultural Sectors in Benguet and Ifugao A review was conducted on available vulnerability assessment tools in order to select or develop a framework and tool appropriate for assessing climate change vulnerability and adaptive capacity of the agriculture sector particularly for highland agriculture of Benguet and Ifugao provinces. The following steps were followed in the review and assessment of the existing vulnerability tools: 1. Collection of reference materials on vulnerability assessment and on topics related to assessing climate change effects, hazard mitigation and adaptation in developing countries. 2. Setting of criteria for the screening of the vulnerability tools. In order to determine the applicability of the tools for the agriculture sector of Benguet and ifugao, a set of criteria was formulated: a) The assessment addresses vulnerabilities to hazards due to climate change; b) The assessment must be at the community level; c) Emphasis of the assessment should be on the agricultural sector of the community; d) The assessment must have a holistic view of the community’s agricultural sector considering the biophysical, economic, socio-cultural, and political components; e) The assessment should be practical and easy to follow, particularly the data collection; and f)

The assessment must seek to integrate agricultural indigenous knowledge system with scientific and technical concerns.

3. The assessment tools were evaluated in terms of their strengths and weaknesses on the following aspects: purpose, framework, scale/level, methods, and agriculture-related data requirements.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

4. Development of the proposed vulnerability assessment framework and methodology for the agricultural sector of Benguet and Ifugao. This was done by integrating the strengths of the different tools that were reviewed. A total of nine vulnerability assessment tools were reviewed and screened. Most of the tools reviewed were designed mainly (or at least a part of the tools) to assess vulnerability and adaptation to natural hazards, including hazards due to climate change. Among the tools reviewed, only three dealt specifically with vulnerability to climate change: PRRM & DENR (2009); Daze, A., K. Ambrose and C. Ehrhart (2009); and Hamill, A., B. Riche and N. Clot (2007). A new tool was developed that is suitable for Benguet and Ifugao by integrating the relevant features of the tools that were reviewed. It is called Community-based Climate Change Vulnerability and Adaptive Capacity Assessment of the Agricultural Sector for Benguet and Ifugao (AgSys-VACA). The general procedure was adapted from Kuban, R. and H. McKenzie-Carey but the conduct of vulnerability assessment was patterned from the Participatory Disaster Risk Assessment procedure of Abarquez, I. & Zubair Murshed (2004) which includes hazard assessment, vulnerability assessment and capacity assessment. Some community-based and participatory data collection techniques were taken from the rest of the reviewed assessment tools. Since the reviewed assessment tools lack information on the agricultural sector, other data on agriculture needs to be collected and the methods for collecting this data were added. Basic Features of the Assessment Tool: a.

The approach is community-based;

Anchored on the definition that climate change vulnerability is the result of the interaction and interrelation of three major factors: sensitivity to the hazard, exposure and adaptation capacity;

It views agriculture as a holistic system with biophysical, economic, socio-cultural, and political components;

Two major components of the assessment: 1. Climate Change Variables and their Impact on the different components of the agricultural system, 2. Capability of the system to cope with adversities and to develop into a resilient production system.

There are three major phases of the assessment with several activities in each phase, listed as follows: Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

a. Pre-assessment and planning phase 1. Organize the vulnerability and capacity assessment team 2. Study the area through secondary information 3. Plan and prepare for the field work b. Actual assessment 1. Site reconnaissance 2. Describe climate-related hazards in the community (types, location, frequency, seasonality, impacts, and magnitude of damage) 3. Describe vulnerabilities and capacities of the community 4. Conduct hazard mapping 5. Identify and assess current adaptation measures c. Post-assessment phase 1. Systematize, Analyze and Interpret the Data 2. Validate the Data with the Community

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Component 1B: Local Knowledge and Tools for Assessing Vulnerability of the Agricultural Systems to Changing Climate: The Case of Ifugao

and Benguet Provinces

The people of Cordillera, collectively known as Igorots or people of the mountain, lived to their name. They consider themselves as part of the land and the forest, with forest not just as source of wood, lumber, and many others but their life itself. They nurture the land and the forests to ensure that it will remain capable of nurturing them. This perspective enables them to survive the many challenges of nature over time, including the harsh climatic environment. The Cordillera is one of the regions in the Philippines that host many indigenous people groups with rich culture and cultural practices, like the Isneg, Kalinga, Bontok, Kankanaey, Tingguian, Gaddang, Ayangan and Tuwali, Kalanguya or Ikalahan, Ibaloy. These groups of people live in the hinterland and survived many environmental challenges using the indigenous knowledge that was handed down by their forefathers from generation to generation. In the Philippines indigenous knowledge’s contribution in resource management is well recognized, having been validated for their technical and scientific soundness by many investigators. While local knowledge, beliefs, indigenous tools and practices in the Cordillera enable them to live with nature, their knowledge have not been assessed in terms of technical soundness, effectiveness and applicability in the context of climate change. Indigenous knowledge (IK) can be defined as knowledge that an indigenous (local) community accumulates over generations of living in a particular environment. This encompasses all forms of knowledge – technologies, know-how skills, practices and beliefs – that enable the community to achieve stable livelihoods in their environment. It is also defined as institutionalized local knowledge that has been built upon and passed on from one generation to the other by word of mouth and served as basis for local-level decision-making in many rural communities. Thereby, it has value not only for the culture in which it develops, but also for scientists and planners who are determined to improve conditions of those who are in rural communities. Aiming to contribute to national processes of developing adaptation strategies for the impacts of climate change in agriculture, this study entitled “Local knowledge and tools for assessing vulnerability of the agricultural systems to changing climate”, was conducted in the Cordillera region. This was based on the premise that integrating indigenous knowledge into national climate change policies can lead to Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

the development of effective alleviation and adaptation strategies. The study, therefore, aims to identify and verify local knowledge and indigenous tools/practices in, a) assessing climatic condition, b) identifying climate change impacts on agriculture and the community, c) identifying adaptation options, and, d) assessing the vulnerability of their source of livelihood, agriculture in particular. This study focuses on two provinces in the Cordillera, the Ifugao province where the famous rice terraces can be found and the Benguet province, which is considered as the “salad bowl” of the country. Benguet and Ifugao are considered as particularly vulnerable to climate change, and agricultural activities in these provinces are considered at risk to climate change.

Synthesis of the Methodology For this study component, three approaches were utilized to determine the level of awareness of the agricultural sector in Ifugao and Benguet on climate change, observed impacts, tools and indicators used by local communities for assessing their vulnerability and some adaptation strategies practiced in their provinces during previous events. The approaches used were focus group discussions (FGD), key informant interview (KII) and formal field survey (FFS). Each approach was conducted after the other. FGD was conducted for a selected group of people in the agricultural sector (MAO, MPDO, Farmer leaders). For the KII knowledgeable individuals on agriculture and their locality are selected from among the farmer sector group Each of the three methods has strengths and weaknesses that can be designed and utilized for specific purpose. In this case, all of the three methods were utilized in the area to ensure that all methods are tested before introducing them to the stakeholders in Ifugao and Benguet as tools for data gathering for their assessment of their future vulnerability to climate change impacts. Each method served as a tool for validation of the gathered information. Data gatherings were conducted in the four pilot municipalities in each province, namely, Atok, Buguias, Sablan and Tuba in Benguet province and Alfonso Lista, Banaue, Kiangan, and Mayoyao in Ifugao province. For the formal field survey, additional respondents from four non-pilot municipalities in each province were interviewed.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Synthesis of the Results and Discussion The synthesis of the results and discussion was divided into four parts: a) respondents’ level of awareness and indicators of climate change, b) observed impacts of climate change to agriculture and community, c) tools and indicators of vulnerability to climate change, and d) adaptation strategies and adaptive capacity. Local knowledge and vulnerability assessment tools were identified based on the responses, either explicitly or implicitly.

A. Indicators of climate change The respondents may not be aware of the greenhouse gases, sea level rise, greenhouse effect and climatic change projections but they are definitely aware of the changing climatic condition. The respondents from both provinces in all data gathering activities, including respondents from non-pilot municipalities, showed a high level of awareness of the changing climatic condition. In the following a list of perceived indicators of climate change, enumerated by the respondents in all data gathering activities, is presented: •

longer dry season or drought

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frequent occurrence of typhoon

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unpredictable weather

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increasing intensity of rainfall

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shorter cycle of El Nino and La Nina event

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extreme coldness at night and extreme hotness during daytime

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emergence of new pest and diseases

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migration of different kinds of birds

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dying of birds, high mortality of livestock due to changing temperature and longer dry season

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movement pattern of animals like snakes seen from the lowland

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changing hue of colors of the sky

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more flooding and more landslide

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deviation of climate pattern from the traditional Tiarco calendar

In addition to the above list, respondents also mentioned increasing intensity of typhoons and drought in their locality as well as occurrence of frost and hailstorm which were not observed for a long time. Subsequently, communities are Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

experiencing other climate related hazards like flooding, landslides, and pest and diseases outbreak. Interestingly, the two provinces have their own set of indicators of impending climate associated disasters. In Benguet for example, some participants recall that their folks use animal and insect behavior to predict weather changes. Sneezing carabao is an indicator that a typhoon will be hitting their area, movement of termites and ants is an indicator of the long rain coming and the humming of Kiling bird signal that the worst/strong typhoon has already gone. Old folks rely on cloud formation and sun-moon arrangement or formation to detect possible typhoon coming. In the case of Ifugao, indicators include flowering of bamboo, vigorous growth of endemic grass (“filao”) as an indicator of a shifting weather condition, changing hue of the color of the sky on the east side – an indicator of strong rains or typhoon, dark clouds moving to the southern direction - an indicator of strong rains coming and frequent morning thunders – an indicator of changing climate for the next 3-5 years, snails crawling upward the plants – an indicator of strong typhoons coming. Anecdotal as it seems, there also some scientific explanation behind it. Animals have better sensory perception that human and they are more sensitive to air movement and changing temperature. Early flowering of bamboo is an adaptation response of plants to ensure propagation in spite of impending disaster.

Impacts of climate change The observed climatic changes have positive and negative impacts in both provinces, though mostly negative. Some of the cited effects include: •

Low crop production due to lack of water or destroyed crops due to flooding of fields;

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Increased pests population specifically whorl maggot in rice, aphids in beans, weevil in sweet potato, giant worms in paddies and many others

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High mortality rate in poultry (chicken) due to hot weather and sporadic rains

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Fish kills (tilapia in ponds) due to cold weather

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Very poor growth of vegetables due to daily temperature aberrations (i.e. too hot in the morning and too cold in the evening)

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

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Negative effects on crops: stunted growth, crop damage, poor quality of produce, higher input hence low net profit, and occurrence of more pests and diseases.

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Livestock: stunted growth and higher mortality and morbidity rate were observed resulting to low income and low return on investment.

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In agroforestry and watershed area, reported impacts include scarcity of potable and irrigation water supply, inadequacy of surface water for production and domestic use, and stunted growth of trees and seedlings.

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Aquaculture and fisheries: Delayed growth of fingerlings and higher mortality rate were also observed in ponds and field fish culture.

Interestingly, farmers’ observations, experiences and own knowledge of the biophysical characteristics of their farms, enable them to further describe the effects of climate change based on farm location and orientation as follows: •

Rice terraces in higher elevations are more affected by heavy rains.

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During extended dry months, insufficient water supply affects rice production

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In the case of typhoon occurrence, less damage were experienced in farms with surrounding natural barriers.

Vulnerable groups and tools for assessing vulnerability

When asked to identify vulnerable groups or areas or communities, respondents have their own basis for claiming vulnerability of certain crops, animals, people or places. In Ifugao for example, farmers claimed that farms without plant cover can be easily eroded and dried up and eventually prone to landslide. Similarly, farms in steep slopes and with high elevations like Banaue and Mayoyao are prone to landslide especially when there are no longer “muyong” or communal forest in the area. Towns with poor road network are vulnerable in climate extremes because they cannot sell and buy products and assistance cannot be delivered immediately like in the municipality of Tinoc. Municipalities with denuded forest are said to be prone to drought like Alfonso Lista and Banaue because of lack of supply of water during extended dry season. Farmers from Kiangan claimed that the new generation of farmers is most vulnerable to climate change because they have not learned to

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

watch, analyze and adapt to the changing climatic condition. They are dependent on new information and technologies that are not tested overtime. In Ifugao, rice production systems and the tourism industry are the two most vulnerable sectors to the impacts of climate change. In the case of Benguet, not only the farmers but also those who are dependent on the supply of vegetables are vulnerable to climate change. Benguet is the salad bowl of the country, any loss in production in this area will affect the economy not only of the province but also of the people in the lowland who imports vegetable from this area. In conducting vulnerability assessment, both the direct impact and indirect impact areas over time should be looked into. To assess one’s vulnerability, tools and methods suggested by some respondents are characterization of the area and identification of crops and livestock that are highly affected by the changing climatic condition. To the majority of the respondents, vulnerability assessment is a new term. For researchers it is difficult to extract information as to local ways of doing it. However, local government officials in Ifugao suggested that the best way to do it is to make a complete list of constituents with database of their location and other socio-economic profile, which is exactly what, is being done by the scientific community. As to the tools and methods for data gathering, the following methods were utilized during the conduct of this study: historical accounting, hazard and resources spot mapping, and evaluation of seasonal calendar coupled with focus group discussion, key informant interview and formal field survey. In the following some identified local knowledge and techniques for assessing adverse effects of climate on the agricultural systems are discussed: (1) Post damage assessment through an organized masterlist of affected farms – A record of farms affected in terms of crop damage, erosion, flooded fields or unplanted or farm kept idle are prepared and done by the municipal agriculture office along with other local government units. Often this is utilized or required for declaring calamity areas and allocating calamity funds and support from national government. (2) Visual observation and actual count of abandoned farms - Abandonment of rice farms for them indicates that the farm owner is seriously affected by either the extended dry season or too much rain. Abandonment of the farm to them indicates that the farm owner is unable to cope or recover from the damage and that the farmers need to seek employment (non-farm) for income to enable them to buy food. It has to be noted that rice farming in most part of Ifugao, especially in Banaue and Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Kiangan is solely for home consumption. Reconstruction of the terraces, according to them is labor requiring so before they use their time on reconstructing the terraces, the farmers would opt to do non-farm work to be able to buy food for the family. According to the staff from local government and municipal agriculture often those who abandon the rice fields are the economically poor farmers/farm households. (3) Knowledge of Elevation, Slope and Soil erodibility – Farmers can anticipate the likely damages and extent of damages that the farm will have based on the elevation and slope. (4) Extent of typhoon effects based on farm orientation and surrounding natural barriers – Adverse effects of strong winds and typhoon were observed to be less in areas where there are surrounding natural barriers. As the farmers put it, the degree of adverse effects depends on the farm orientation, whether facing the wind direction or covered by natural barriers (mountain and trees). Repeated experiences on community or individual effort in prioritizing rehabilitation of dikes and terraces based on proximity of farms to watershed and water source – As earlier discussed, farms in terraces in higher elevations are often destroyed by flooding during heavy and continuous downpour causing water overflow destroying dikes and terraces resulting to landslide and soil erosion. In the advent of drought or extremely dry season, farms in terraces located in lower elevations are more affected. Extreme soil dryness, as observed by the farmers causes the problem worms to bore their way out of the soil creating large holes destroying the terraces and causing soil erosion.

Adaptation strategies employed in the past In the past, many farmers in these provinces have been exposed to environmental changes and have developed coping strategies to face these climaterelated phenomena. They may therefore have to offer valuable knowledge to learn from for future adaptation to climate change. This section reports the different adaptation strategies performed by the farmers to cope with climate-related hazards.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Table 1. Adaptation Strategies of upland communities to Climate related hazards Climate related Hazards Drought

Flooding

Landslide

Impacts

Adaptation strategies

Stunted growth, crop loss, Adjustment of cropping dried up of field calendar Increasing farm inputs Improved local irrigation systems Crop rotation Planting of new variety Crop loss Building of dikes Re-channeling of irrigation water Sacrificing animals to gods Staggered cropping Finding other sources of income Multi-cropping system Destruction of fields, Loss of human lives Crop and animal loss

Reforestation Building of dikes Repair of fields

Changing planting or harvest dates, according to them, are effective and cheap option to respond to drought. However, the major risk could be shifting to a different market window that might give them lower prices. Another strategy that some farmers adopted is changing varieties. This is another low-cost option, although some varieties can be more expensive. Many farmers in Benguet also used crop rotation and staggered cropping. Some farmers in Ifugao mentioned finding another water source or increased use of irrigation as ways to cope.

Some Lessons Learned from the local discussion and interviews (FGD, KII, FFS)

1. In developing vulnerability and adaptation assessment tools for the Ifugao and Benguet provinces, local rating of the climate hazard (e.g. daily temperature aberrations, rainfall variability, typhoon) that affect most of their agricultural system is an important consideration. This will provide basis for prioritizing and developing effective adaptation measures. 2. Based on the information gathered in this activity, important considerations in assessing vulnerability of the production system are: farm location in terms of elevation and slope, presence of natural barriers, proximity to water source, poverty or income level of the farm households, cultures and traditions, Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

historical events. The extent and degree of the effects of climate change impacts on the agricultural systems vary based on the characteristics of the farm and the farm household. 3. All local assessments of damages are based on local experiences, observations and knowledge of their agricultural landscape and practices. They are expressed in terms of loss in crop yields, erosion and damages on dikes; damaged crops, increased pest incidence, alteration of the cropping systems and cropping calendar, number of abandoned farms, death of fish and livestock (chicken). 4. Local ways of anticipating changes in weather are not purely anecdotal. Most of the indicators mentioned have some scientific basis and explanation and should not be discounted at once.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Component 2A: Simplified Vulnerability Assessment Tools Combining Indigenous and Scientific Knowledge for the Agricultural Sector in Benguet and Ifugao Impacts of climate change can bring significant losses and damages to the agricultural sector. Since the agricultural sector is the largest contributor to the Philippine economy, it is therefore important to assess its vulnerability to climate change. Vulnerability assessment of the agricultural sector to climate change will facilitate the decision-making process of stakeholders of the agricultural sector about their options for adapting to climate change within the scope of their resources. This study component aimed to (1) design and develop simplified vulnerability assessment tools for the agricultural sectors of Benguet and Ifugao; (2) determine optimal cropping calendar for selected agricultural crops such as rice, corn and vegetables using rainfall and yield probabilities for Benguet and Ifugao; (3) analyze the projected climatic variability in the two provinces by through finding the historical analogues that resemble the anticipated climate conditions of 2020 and 2050 for Benguet and Ifugao; and, (4) recommend optimal planting dates for rice, corn and vegetables for the years 2020 and 2050. To achieve these objectives, the study performed an integrated analysis of data and information generated from the focused group discussion (FGD), key informant interviews (KII), and from formal surveys in pilot barangays as well as in non-pilot municipalities. Indigenous knowledge and scientific information were integrated in a simple procedure for conducting vulnerability assessment at the farm level. The conceptual framework for the development of the vulnerability assessment tool was based on the climate change vulnerability concept presented by Allen Consulting (2005, cited by Smith 2010). Vulnerability is defined as “a function of the character, magnitude, and rate of climate variation to which a system is exposed, its sensitivity, and its adaptive capacity” (IPCC 2001, cited by Smith (2010). Allen (2005) demonstrated that exposure to a climate event combined with sensitivity to that event may be interpreted as potential harm and that potential harm may be offset by the adaptive capacity, resulting in a particular vulnerability level for a system.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

The climate and agriculture data requirements for assessing vulnerability and adaptive capacity are presented in Study Component 1A report. For a simplified vulnerability assessment these variables are grouped into the following categories: A. Exposure to climate-related hazards, B. Sensitivity of the community to the climate-hazards, and C. Adaptive capacity of the community

As a first step of the vulnerability assessment, the particular climate hazard and agriculture variables for a specific community or barangay are gathered using the corresponding percentage or qualitative description and measured in a scale of 0 to 10, with 10 having the highest score. Table 2 assesses the exposure of the farming areas and their various farming system to the particular hazard. This data would be obtained from secondary data of the Municipal or Barangay Agricultural Office. The particular hazard is also evaluated in terms of frequency of occurrence and duration based on secondary data or primary data from PAGASA or local weather stations. Table 2. Variables referring to the Exposure of the agriculture sector of Benguet and Ifugao to climate-related hazards. Cat. Data Score A Exposure Source What proportion of the community’s land area is related to A1 0 - 10 MAO agriculture? What proportion of the agricultural area could be directly A2 0 - 10 MAO affected by the hazard? What proportion of the community is dependent on A3 0 - 10 MAO agriculture? How frequent does the community experiences this hazard in Weather 0 - 10 A4 a 10-year period? Data How long does this hazard affect the agricultural sector to Weather 0 - 10 A5 cause damage? Data

Table 3 below summarizes the variables referring to the sensitivity or risk of the farming areas and the farming community in Benguet and Ifugao provinces to climate related hazards. Often the variables are described and rated in terms of impact experience for a particular hazard. For example, the score can be described in terms of the percentage of crop lost due to the particular hazard such as typhoon and flooding. As suggested in component 1A report, data collection for each variable identified here may differ (e.g. through reconnaissance, key informant or key informant panel interviews). The assessment team may even get information about Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

these variables through a review and study of secondary data about Benguet and Ifugao. Table 3. Variables referring to the Sensitivity of the agriculture sector of Benguet and Ifugao to climate-related hazards. Cat. Data Score B Risk/Impact Source What proportion of profit in agricultural production may be lost? (Ilang porsyento ang pwede masira sa ani o kita sanhi 0 - 10 Farmer B1 ng hazard) B2

B3 B4 B5 B6 B7

What proportion of the agricultural assets of the community was damaged?

0 - 10

Barangay

What is the opportunity cost from the hazard? (not able to market, low growth rate of plants and animal) (Anong bahagi ng kita ang nawala sanhi ng hazard)

0 - 10

Farmer

What is the proportion of subsistence farmers?

0 - 10

MAO

What is the proportion of old (above 70 y.o.) and young (below 8 y.o.) in your community? What proportion of agriculture contributes to the community's income? What is the proportion of your population that is not knowledgeable to the hazard?

0 - 10

Barangay

0 - 10

Barangay

0 - 10

Barangay

Table 4 presents the qualitative description of the variables referring to the adaptive capacity of the farming areas and farming community to climate change hazards, specifically in Benguet and Ifugao. Many of these variables can be measured in terms of availability, such as resource availability and physical capacity. Other variables that refer to adaptive capacity can be measured in terms of the percentage of the population or the farming community. For the economic capacity, it can be noted that versatility of skills or the ability to earn income other than farming is included to differentiate it from the economic condition of the farming community (cited in Table 3) where sole dependence on agriculture for income is used as descriptor of sensitivity.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Table 4. Variables referring to the Adaptive Capacity of the Agriculture sector of Benguet and Ifugao to climate-related hazards. Cat. C

C3 C4

Adaptive Capacity

Score

Data Source

How much agricultural area is isolated during the hazard? Marami bang lugar sa inyo barangay ang hindi maabot ng tulong sa panahon ng sakuna?

0 - 10

Farmers

How much is the need for support systems during the hazard? (Ex. Bayanihan, Government and NGO support, Credit facility, etc.) Marami bang NGO at ahensya ng gobyerno tumutulong sa inyo sa panahon ng hazard?

0 - 10

Farmers

0 - 10

Barangay

0 - 10

Barangay

0 - 10

MAO

What proportion of your community cannot afford to spend for adaptation cost? What proportion of people in your community has no other sources of income? What is the need of your community's technological adaptation (Knowledge of adaptation techniques both scientific and indigenous practices?)

Community-level Vulnerability Index After having shown the qualitative description and measures of the variables for assessing vulnerability of the agriculture sector of Benguet and Ifugao (Tables 2-4 of the previous section), a qualitative variable, the scoalled community-level vulnerability index is quantified. The definition of ‘community-level’ here refers to the Barangay spatial boundary. The index follows a rating scale of 0 - 10 in terms, with 10 indicating the most vulnerable (see Table 5). Table 5. Qualitative interpretation of a vulnerability index Index Value Qualitative Interpretation 0 – 1.99 Lightly vulnerable 2 – 3.99 Moderately vulnerable 4 – 5.99 Vulnerable 6 – 7.99 Highly vulnerable 8 – 10.0 Extremely vulnerable

In line with the definition of vulnerability, the Community-level Vulnerability Index (CLVI) is computed as follows: Community-Level Vulnerability Index (CLVI) = Potential Impact (PI) * Adaptive Capacity Deficit Index (ACDI) With: Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Adaptive Capacity Deficit Index (ACDI) = Scores C1 + C2 + C3 + C4 4 * 10 Potential Impact (PI) = Exposure Index (EI) * Sensitivity Index (SI) With: Sensitivity Index (SI) = Scores B1 + B2 +B3 + B4 + B5 5 Area Exposed Score + Population Exposed Score Exposure Index (EI) = ----------------------------------------------------------------- + Effect of 2 Frequency & Duration Where, Scores A1 * A2 Area Exposed Score = -------------------------------100 A3 Score Population Exposed Score = --------------10

Scores A4* A5 Effects of Frequency & Duration = (1 – (A3 Score /10)) * ----------------------100 The effect of hazard frequency of occurrence and its duration in the community takes into account the populations whose livelihood is not related to agriculture but who are consumer of agricultural products. When the frequency and duration of the hazard become more and longer, respectively, even other sources of income like mining and tourisms will also be negatively affected. Thus, consumer buying capacity or its access to agricultural products will also worsen the plight of the farmers with respect to the particular hazard. Results of the Pretest in Benguet The Agricultural Systems Vulnerability and Adaptive Capacity Assessment Tool was pretested Benguet. The pilot sites of Atok and Buguias were visited and both meetings were attended by some 20 farmers, farmer leaders and local government officials, like the Municipal Agricultural Officer. The pretest in Paoay, Atok and Loo, Buguias in Benguet for various hazards the community members identified, showed that the perceived community Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

vulnerability notion was very similar to the calculated AgSys VACA tools’ Indices which are shown in Table 6 and 7. For instance, the result of the pretest in Paoay, Atok: and their perceived notion of Typhoon vulnerability is 7, and the AgSys VACA results showed 6.54, both having a qualitative interpretation of ‘Highly Vulnerable’. Their perceived notion of Monsoon vulnerability is 5, and the AgSys VACA results showed 4.99, both having a qualitative interpretation of ‘Vulnerable’. Thus, the tool was found to provide an objective assessment of climate hazards which is similar the communities own perceptions of vulnerability. Perceptions about vulnerability and rating may vary among stakeholders, especially senior and junior-level positions and the use of this tool might be able to eliminate biases resulting from such difference. As such, it was suggested that the results of the assessment be disseminated to the political leaders and policy makers in the municipality.

Table 6. Results of the pretesting of the vulnerability assessment tool in Paoay, Atok, Benguet. Item / Hazard Typhoon Monsoon Exposure Index (EI) Sensitivity Index (SI) Potential Impact (EI x SI) Adaptive Capacity Deficit Index Vulnerability Index Qualitative Interpretation

0.950 7.400 7.030 0.880 6.186 Highly Vulnerable

0.950 6.000 5.700 0.640 3.648 Moderately Vulnerable

Table 7. Results of the pretesting of the vulnerability assessment tool in Loo, Buguias, Benguet. Item / Hazard Typhoon Landslide Flood 0.590 Exposure Index (EI) 0.950 0.538 6.400 Sensitivity Index (SI) 8.000 3.600 3.776 Potential Impact (EI x SI) 7.600 1.937 0.540 Adaptive Capacity Deficit Index 0.720 0.720 2.039 Vulnerability Index 5.472 1.394 Lightly Moderately Qualitative Interpretation Vulnerable Vulnerable Vulnerable

Hailstorm 0.201 2.400 0.482 0.420 0.203 Lightly Vulnerable

During the pre-test, the tool was found easy to understand and use. However, there were specific comments and suggestions to make the tool more appropriate and practical for the agricultural conditions. For example, it was proposed to use as much as possible secondary agricultural and demographic data that are more reliable Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

and based on municipal, barangay records. Further, it was also suggested to include the Department of Social Welfare and Development (DSWD) and the Public Works and Highways (DPWH) as members of the assessment team.

Science-based Adaptation Measures for Benguet and Ifugao

To ensure sustainable food production and to eliminate threats to food security brought about by climate change, also scientific vulnerability assessment tools should be developed to inform adaptation strategies. One such strategy is through improvement in the analysis and interpretation of weather and climate data. Adaptive measures include understanding climatic patterns through establishment of farm weather information and advisories, and adjusting cropping systems through determination of optimal cropping calendar. This study determined the optimal cropping calendar for selected agricultural crops such as rice and tomato using rainfall and yield probabilities for Benguet and Ifugao, and it analyzed the projected climatic variability through finding the historical analogues that resemble the anticipated climate conditions of 2020 and 2050 for Benguet. Sequences of daily historical weather data of Benguet and Ifugao were obtained from the respective local agro-meteorological stations of Baguio City (19712000), La Trinidad (1976-1990), and Banaue (1979-1993). For each station, the years with available weather data were grouped according to the three climatic classifications, namely: dry, wet and normal years based on the Standardized Precipitation Index (SPI). For each climatic classification, synthetic weather data were generated and combined with the historical ones to form 50 years (1960 – 2010) which were use for the computation of rainfall and yield probabilities.

i) Results for BAGUIO CITY Determination of Optimal Cropping Calendar for Tomato in Baguio City Based on the yield probabilities of Magilis tomato variety, the calculated optimal planting dates for tomato during dry years in Baguio City is week 51 (third week of December), for normal years it is week 8 (fourth week of February), and for wet years it is week 36 (first week of September).

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Finding the Historical Analogue for 2020 and 2050 in Baguio City To prepare the farmers of Baguio City for the climate conditions in 2020 and 2050, it is necessary for them to understand such conditions in the simplest way possible. One approach to do this is to find the historical analogues of 2020 and 2050 in terms of climate conditions. This will relate the future conditions to what they have already experienced in the past. Four methods were implemented to find the historical analogues. These are the following: (1) Cluster Analysis using the standardized yearly summaries of five weather variables; (2) Cluster Analysis using the extracted principal components; (3) least average absolute deviation analysis using the daily values of five weather variables; and (4) least average absolute deviation analysis using the extracted principal components. Results showed that the first two methods which involved the cluster analysis of years failed to find immediate historical analogue. However, the two methods involving the use of the least average absolute deviation showed that among the 30 historical years considered, 1995 has the closest weather scenario to 2020 and 2050.

ii) Results for LA TRINIDAD, BENGUET Determination of Optimal Cropping Calendar for Tomato in La Trinidad, Benguet Based on the target yield of at most 12500 kg/ha of Magilis tomato variety, the calculated optimal planting date for tomato during dry years in La Trinidad, Benguet is week 4 (fourth week of January), else it is week 36 (first week of September). Moreover, for normal and wet years the optimal planting dates are week 2 (second week of January) and week 36 (first week of September), respectively.

iii) Results for BANAUE, IFUGAO Determination of Optimal Cropping Calendar for Rice in Banaue, Ifugao Determining the optimal cropping calendar based on rainfall probabilities selects the planting date that will most likely satisfy the water requirements of rice during each stage of its growth development. According to Saseendran (1998), certain water requirements must be met for optimum production of rice. At least 200 mm of cumulative precipitation falling in the week preceding the transplanting date is needed for successful transplanting and plant establishment. When rice reaches the Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

physiological maturity, which is during the 110th day of the 125-day crop growth period, it will use at least 1200 mm of water. Lastly, the rice grains must remain relatively dry during the last 15 days of the crop period following maturity, to avoid deterioration of rice quality. In this study, it was assumed that the quality of rice will be maintained if no more than 80 mm of rain falls during this 15-day period. Results indicated that during dry years in Banaue, the optimal planting dates for rice is from week 29 (third week of July) to week 32 (first week of August), from week 33 (third week of August) to week 37 (second week of September) during normal years, and from week 36 (first week of September) to week 39 (fourth week of September) during wet years. The approach based on the yield probabilities of IR72 rice variety showed that the optimal planting date for rice during dry years in Banaue are week 34 (fourth week of August) and week 35 (fifth week of August), for normal years it is week 35 (fifth week of August) and for wet years any week between week 29 (third week of July) and week 33 (third week of August). Compared to the predictions based on rainfall probabilities, the results for optimal planting dates derived based on yield probabilities are more plausible and therefore recommended. This is because of the fact that estimated crop yields using ecophysical crop simulation model accounts more for the agro-climatic environment and also crop management strategies.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Component 2B: Updating of the Crop Damage and Loss Assessment Model of the Department of Agriculture Crop yield models for rice and four major vegetable crops were constructed to assess the effects of weather variables on yield. The weather variables used as independent variables included daily maximum, minimum and average temperature, daily rainfall and relative humidity from BSU PAGASA weather station for the period 1991 to 2009. Yield Models for Rice

The yield data used to construct the model were obtained from the National Rice Cooperative Trials for Adverse Environments (Cold Tolerance). Yield performance of promising rice genotypes observed in designed experiments in various locations in the Cordilleras from 1992 to 2009 wet and dry seasons was used as the dependent variable. The independent variables in the model consisted of cumulated data on the amount of rainfall, maximum and minimum temperatures and relative humidity. The growing period for each season was divided into three stages: vegetative, reproductive and ripening. Based on the number of days to maturity and records of sowing and transplanting dates, inclusive dates for each growth stage for each season were established. Weather variables were summed for each period using daily data provided by PAGASA. Summing and averaging of the weather variables were done for each genotype as they differed in the number of days to maturity. The variables taken at the vegetative stage were daily rainfall at (MRAINV), daily maximum temperature (MTMAXV), daily minimum temperature (MTMINV) and relative humidity (MRHUMV). The same variables were obtained at the reproductive stage, namely daily rainfall at the reproductive stage (MRAINRP), daily maximum temperature (MTMAXRP), daily minimum temperature (MTMINRP) and daily relative humidity (MRHUMRP). Similar variables obtained at ripening stage are denoted as MRAINP, MTMAXP, MTMINP and MRHUMP, accordingly. The ripening stage was made to coincide with the last 30 days of the growing period. The reproductive stage was defined as the period 35 days before the start of ripening. The vegetative stage included the remaining days of the growing period from sowing date up to the onset of the reproductive stage.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Initially, multiple linear regression analysis was used to construct separate yield models for dry and wet seasons. For both seasons, maximum temperature at vegetative stage showed a negative effect on yield while rainfall showed positive effects. Rainfall during ripening had a negative effect on wet season yield but showed high positive effects during the dry season. These models, however, gave a very poor fit of 22.10% for dry season and 38.6% for the wet season. This means that the linear models could explain less than 40% of the variation in the data. Second order models were fitted to the same set of data and showed improved adequacy of fit for dry season at 46.66% and for wet season at 72.49%. Yield Models for vegetable Annual production data for four major vegetable crops namely cabbage, Chinese cabbage, snapbeans and potato were used as independent variables to construct yield models using multiple linear regression. The annual yields were expressed as linear functions of weather variables accumulated for each month. A generally increasing trend for cabbage production was observed through the years, with minimum productivity observed in 1994. Likewise, productivity of Chinese cabbage and white potato generally exhibited an increasing trend from 1999 to 2009. Snap beans productivity, on the other hand, remained constant through the years. In the following more details are provided for each vegetable crop. a) Cabbage Cabbage production data were obtained from all municipalities of Benguet except Tublay with missing values from 1991 to 1999 for Kabayan, Kibungan and Kapangan. Buguias proved to be the top producer of cabbage with highest production at 112,100 metric tons from 5,350 hectares planted in 2007 and 109,998 metric tons from 5,405 hectares planted in 2008. With the widest area planted, Buguias remained to be the region’s major supplier of cabbage. The model gave an R2 = 97.35% implying that only about 3% of the variation in productivity cannot be explained by the model. The crop yield model was constructed as follows:

Y49.84140.55144*TMAX11.7351*TMAX40.5562* =−−++ 0.2176*RAIN61.2084*TMEAN7 ++

TMIN4

Where Y is yield in mt/ha; TMAX1 is average maximum temperature in January; TMAX4 is the average maximum temperature in April; TMIN4 is average minimum temperature in April; RAIN6 is the average daily rainfall in June and TMEAN7 is average mean temperature in July. Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

b) Chinese cabbage Chinese cabbage production data was obtained from all 13 municipalities with missing data from Tuba for the years 2000-2009. Chinese cabbage production ranged from 15.6 metric tons obtained in Kapangan in 2009 to 47,103 metric tons obtained in Buguias in 2008. Buguias proved to be the largest producer of Chinese cabbage with largest production volumes observed in 2007, 2008 and 2009 at more than 47,000 metric tons. Three variables were significantly affecting productivity of Chinese cabbage at the 5% level of significance. These are maximum temperature in April (TMAX4), mean temperature in July (TMEAN7) and maximum temperature in August (TMAX8). TMAX4 and TMEAN7 showed positive effects increasing yield by 1.5678 and 1.2980 metric tons per hectare for every °C degree increase holding other independent variables constant. In contrast, maximum temperature in August showed negative effects pulling down yield by 1.0822 mt/ha for every °C degree increase in temperature. The yield model obtained for Chinese cabbage was:

Y24.31911.5678*TMAX41.2980*TMEAN71.08 =−++−

22*TMAX8

Where TMAX4 = maximum temperature in April; TMEAN7= mean temperature in July;

and TMAX8 = maximum temperature in August.

The R2 obtained for the model is 85.88% indicating a fairly adequate model. This implies that 85.88% of the variation in yield productivity can be explained by the three variables given in the model above. The model reveals that as TMAX4 increases the yield increases by 1.5678 mt/ha which is similar to the result obtained for cabbage. The same was also true for TMEAN7 which showed positive effects for yield in Chinese cabbage. It shows that as TMEAN7 increases, the yield productivity also increases by 1.298 mt/ha. c) Snapbeans Production data on snap beans was obtained from all 13 municipalities. Snap beans production ranged from 15 metric tons obtained in Atok in 2007 to 11,582 metric tons in Mankayan in 1994. Mankayan proved to be the top producer of snapbeans with smallest production of 961 metric tons in 2009. The production trend for snap beans was observed to be either constant for the 19 years considered or on Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

the downtrend. This was observed even for the largest snapbean-producing municipality. A drastic decrease in snapbean production was observed for the period 1991-1999 and 2000-2009. This decrease may be attributed to decreasing area planted to the crop which was as wide as 1,454 hectares in 1992 to a measly 114 hectares in 2009. Since there was no significant variability in snapbean production across years, no model was constructed. d) White Potato Production data for white potato were obtained from 8 municipalities, namely Atok, Buguias, Bakun, Bokod, La Trinidad, Mankayan, Tuba and Tublay. White potato production ranged from 0.1 metric tons obtained in Atok in 2000 to 104,219 metric tons obtained in Buguias in 2008. The largest producer of white potato was Buguias, followed by Mankayan and Kibungan. In terms of production per hectare, Bakun showed the highest productivity with yield per hectare ranging from 10 to 25 mt/ha. From 1995 to 2009, yields per hectare of potato for Bakun did not fall below 20 mt/ha except in 2007 when white potato yield was only 17.9 mt/ha. Results showed that only Atok and Mankayan exhibited increases in productivity. The yield model obtained showed only maximum temperature in September as the critical weather variable accounting for 63.04% of the total variation in yield. The white potato yield model obtained is as follows:

Y17.06131.4455*TMAX9 =−+ Where Y= yield of white potato per hectare; and TMAX 9 is the temperature in September. The model shows that as the maximum temperature in September increases, the yield increases by 1.4455 mt/ha. Similarities observed for the constructed models included the significance of maximum temperatures in April (TMAX4) and mean temperature in July (TMEAN7) for cabbage and Chinese cabbage. Although high R-squares were obtained for these two models, there are several limitations of the study that hinder valid interpretation of the roles of these variables on yield. Firstly, there was no information on the time of planting for the crops. This could have been very informative in interpreting the effects of the considered weather variables. Seasonal data would have generated more information to allow valid interpretation. Secondly, the weather data used were common for all the municipalities which are clearly not the case in Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

actual conditions. High variability in weather variables such as temperature exists among the municipalities, from Atok to La Trinidad to Sablan. These models are the only models developed so far for these crops.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Component 3A: Trainors’ Training on the Vulnerability and Impact Assessment Tools on Agriculture for Local Stakeholders in Benguet and Ifugao A three-day Training of Trainors on Climate Change Vulnerability and Impact Assessment tools for Ifugao was conducted at Ifugao State University, Lamut, Ifugao on November 10-12, 2010. For Benguet it was conducted at Benguet State University, La Trinidad, Benguet on December 6-8, 2010. A total of 13 participants attended the training from Ifugao and 32 participants from Benguet. Participants were composed mainly of Municipal Agricultural Officers (MAO), agricultural technicians, farmers, and local government officials of the project site municipalities. The training module was designed to capacitate the local stakeholders (LGUs, farmers and MAO) in conducting vulnerability and impact assessment using available tools and methods suitable to the said provinces. It aimed to: a) update the stakeholders of the current development on climate change; b) update the stakeholders on the available climatic and biophysical information on their province; c) provide the stakeholders with vulnerability and impact assessment tools available; d) train the stakeholders in using the assessment tools appropriate to the area; and e) enable the participants to conduct their own vulnerability and impact assessment. To meet the above objectives, the 3-day training was divided into five parts, namely: a) introduction to climate change, b) climate change impacts on agriculture, c) vulnerability and impact assessment framework, d) tools and methods for vulnerability and impact assessment and e) vulnerability and impact assessment workshop (see Table 8). On the first day of the training, the main topics were: a) Understanding of Climate Change Science and its Impacts, b) Philippine Climate Change Scenarios, and c) Impacts of Climate Change in Ifugao Province. On the second day, the main focus was on the vulnerability and impact assessment. Topics discussed included: a) Vulnerability and Impact Assessment (VIA) Framework, b) Tools and Methods for VIA such as Focus Group Discussion (FGD), Key Informant Interview (KII) and Geographic Information Systems (GIS). The third day served as the culminating hands-on activity of the training, wherein participants were grouped by the municipality they represented and were instructed to conduct their own vulnerability and impact assessment. At the end of the day, participants presented their outputs. Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Table 8: Summary of topics of the training in vulnerability and impact assessment tools.

Day 1: Climate Change Science

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Climate Change Vulnerability Basic Concepts

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Philippine Climate Change Scenarios and its Impacts to Agriculture

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Climate Change Impacts in Cordillera Region

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FGD, KII and Formal Field Survey Outputs on CC Impacts in Ifugao/Benguet

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Vulnerability and Impact Assessment Framework

Day 2: Vulnerability and Impact Assessment Methods/Tools

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V&A Assessment Approaches, Framework, Tools and Methods: An Overview

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Proposed community-based vulnerability and impact assessment tools

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Updated Socio-economic and Bio-physical Characteristics of Ifugao/Benguet

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GIS Mapping as a Tool for Vulnerability and Adaptation Assessment to Impacts of Climate Change

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Exercises on timeline, historical, spot mapping and other tools and approaches

Day 3: Conduct of Vulnerability and Impact Assessment

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Guided Vulnerability and Impact Assessment Exercise and Output Presentation

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Component 3B: Capacity Building of Local Stakeholders on CommunityBased Climate Change Adaptations in Benguet and Ifugao: Monitoring and Evaluation of Adaptation Measures A three-day training on the Monitoring and Evaluation of Climate Change Adaptation Measures and risk mitigation strategies for Ifugao was conducted at Ifugao State University, Lamut, Ifugao on December 1-3, 2010. For Benguet it was conducted at Benguet State University, La Trinidad, Benguet on December 8-10, 2010. A total of 14 participants attended the training from Ifugao and 30 participants from Benguet. Participants were mainly composed of Municipal Agricultural Officers (MAO), agricultural technicians, farmers, and local government officials of the project site municipalities. The training module was designed to capacitate the local stakeholders (LGUs and MAO) in conducting monitoring and evaluation using available tools and methods suitable to the said provinces. Figure 2 shows the framework used to monitor and evaluate the adaptation measures and risk mitigation strategies for Ifugao and Benguet. Table 9 outlines the workshop design.

Figure 2. Monitoring and evaluation framework Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Table 9: Outline of the workshop conducted in the two provinces. Day 1: Review of Monitoring and Evaluation

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A quick guide for monitoring and evaluation.

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Monitoring and evaluation tips.

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Criteria of a good M&E design

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Importance of Monitoring and Evaluation

The Types of Monitoring and Evaluation (M&E)

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Technical/Infrastructure Monitoring System

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Cost or Financial Monitoring System

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Input Delivery ME system

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Project Benefit ME System

Project Benefit Monitoring and Evaluation Systems (PBMES)

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Monitoring of Key Indicator Sub-System (KISS)

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Evaluation SS (ESS)

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Information User SS

Day 2: PBME Administrative module Review on Basic Statistical Concepts

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Different sampling methodology

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Determining appropriate sample size

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How to construct a box whisker plot

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When is the result statistically significant?

Review on scaling and indexing. Steps to be followed in conducting factor analysis using Statistical Package for Social Science (SPSS) Day 3: Conduct of Monitoring and Evaluation

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Guided Monitoring and Evaluation Workshops and Output Presentation

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Group work 1: Four groups were formed to come up with adaptation measures that are: Technological, Institutional, Infrastructure and Policy related. Group work 2: Participants were grouped according to their municipality of origin to come up with an M and E system for at least four (4) identified adaptation strategies (projects) stating briefly the objectives, indicators to be used in Monitoring and Evaluation, targets, time frame including person responsible and completion date.

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Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Outputs from Group work 1: Identified adaptation measures Technological Measures Ifugao • Installation of rain gauge in the locality to determine the volume of water that may come • Provide sufficient outlet in paddy field • Open drainage of Irrigation Dam and close intake • No pasturing of animals at riverbanks • Prune trees that may cause accident in the residential areas • Plant drought resistant crops • Establishment of fire prevention belt on the forest/mountain • Construction of deep well/big reservoir for water supply • Employing traditional practices on natural forest trees regeneration • Build a NOAH’s Ark • Construction of flood control on flood prone areas • Clean Drainage Canal • Observe proper waste disposal

Technological Measures Benguet • Crop rotation • Crop programming • Planting of resistant varieties • Organic agriculture • Integrated farming system • Good Agricultural Practices (GAP) • Sloping Agricultural Land Technology (SALT) • Agro-reforestation • Rip rapping • Establishment of drainage system • Rain shelter • Establishment of catch basin/SFR/SWIP • Windbreaker establishment • Provision of mechanical drier • Crop diversification • Establishment of automated weather station

Infrastructure Measures Ifugao Infrastructure Measures Benguet Construcion of: Construction of: 1. Support Infrastructure • deep well water source • rehabilitation of farm-to-market • strong impounding dams roads • irrigation system (surface, • greenhouses/rain shelters for underground, pipes, PVC); crops irrigation water control • nurseries • water tanks • flood controls • post harvest storage ware house • tram lines • sewerage; sewerage water spill waste in farms and roads • foot trails/foot paths • covered sidewalks and waiting • foot and road bridges shed • composting facilities • concrete farms to market roads, • training center bridges and foot bridges to farms • fish hatchery & fish tanks/fish • evacuation center cages • ware houses 2. Post-Harvest Facilities • strong wide and high river control • marketing center /trading posts/ collection center or bagsakan center • multi-purpose drying pavement • processing center/packaging center/ cold storage facilities Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

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seed storage 3. Irrigation Systems • small farm reservoirs (FSR) • small water impounding projects • spring development • Rehabilitation & expansion of communal irrigation systems (CIS) • pump irrigation facilities Institutional Measures Ifugao Institutional Measures Benguet The following must be provided • Integration of environmental with awareness to the curriculum 1. Trainings and workshops to be • Awareness on waste management able to provide services • Use of biodegradable or recyclable properly packaging 2. Necessary resources for the • Promotion of organic farming conduct of their services • Strengthening or rural/urban-based • LGU (BDCC, MDCC, PDCC organization & other stakeholders • Farmers’ Association • Recognizing/Empowering women • Environment Council participation • CWA • Municipal ecological solid waste • Others (NGOs) management • • Nursery development program • Municipal composting project • Program on natural organic agriculture • Include IEC on adaptive measures on climate change during homily or Holy Mass • Strengthening collaboration/linkages among institutions – i.e., public-private l • Protective horticulture projects • Presence/availability of longer term on management plan for institutional programs & projects Policy Related Measures Ifugao Policy-Related Measures Benguet • Establish an information Center • Check vulnerable areas as priority accessible to every Sitio within of the project the barangay and accessible to • Make use of available data to help new technology, instrument to identify areas of study fast tract information delivery • Irrigation: PVC or rubberized hose /dissemination & Community-managed irrigation • Inform farmers in advance to system (save the house/forest) harvest matured crops before the • Strengthening KSP through typhoon occurs. institutions/organizations with the • Implement immediate mitigating active integral role of elders & measure before any calamity women occurs • Earlier data/information Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

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Implement planting calendar to be followed by the farmers • Practice organic farming • Conduct yearly tree planting to denuded area • Protect and preserve forest area Output from Group work II:

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dissemination Generate a warning system: radio, tangguyob, text, ringing of bells, owaw

For each of the following options an adaptation strategy was defined with statement of the objectives, indicators to be used in monitoring and evaluation, targets, time frame including, person responsible and date of completion. Ifugao • LGU Material Recovery with Shredder Facility • Agro-Forestry Land Management Technology Demo • Flood Control and Erosion Mitigation • Vegetable Agro-forestry (VAF) • Organic Fertilizer Production • TRAMLINES for Barangay Nagacadan • Organic Vegetable Production

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Benguet • Rehabilitation of Pasdong irrigation system in Atok • Construction of 5 greenhouses in the 8 barangays in Atok • Reforestation of denuded communal areas at Poblacion, Atok • Communal Forest in Buguias • Communal Irrigation in Buguias • Multipurpose Seed Storage in Buguias • Information education campaign in Sablan • Municipal Composting in Sablan • Prevent Soil Erosion and Siltation at Water Sources and Farmlands within the Municipality of Tuba

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

Conclusion and Recommendations Project Applications International treaties are being pushed so that richer countries compensate in financial and technological assistance to empower poor countries severely exposed to climatic related hazards. The vulnerability assessment tool for upland agriculture is a tool that could map out those communities that are most vulnerable and prioritize their development through specific adaptive options that will best suit them. The developed Agricultural Systems Vulnerability and Adaptive Capacity Assessment Tool (AgSys-VACA), is a community-based procedure that could document the risk of a Barangay to different hazards and their adaptive strength to manage them. It could be then integrated with the bio-physical data gathered by the respective SUCs and overlaid through GIS programs to create hazard maps at the barangay-level. This data could then integrated be with the other barangays to form the municipality’s Vulnerability Index, further integration of the municipalities into province and provinces into region. These vulnerability maps will be an unbiased indicator of the communities needing funds and technology to prepare themselves to extreme climate related events. Potentially, the tool can be disseminated and implemented throughout Benguet and Ifugao using the training modules developed by the project for the vulnerability assessment team at the Municipal level as well as the monitoring and evaluation of adaptive measures at the Provincial level. However, both training modules might need to be further improved beforehand. The documentation of indigenous practices in Benguet and Ifugao done in Component 1B shows a varied array of natural predictors of hazards as well as adaptive measures implemented to mitigate these hazards over millennia of upland farming in the Cordilleras. Many of these hazard predictors have scientific explanation and could be use to warn communities of pending climate change hazards. Though many of this indigenous knowledge have been eroded by modern farming techniques and employment options for indigenous people, it would be an advantage to use this indigenous knowledge as part of early warning systems. The scientific adaptive tools developed, namely the cropping calendar and the historical analog of scenario 2020 and 2050, are some of the options the local government unit in Benguet could use in order to guide farmers in planning the best strategies to assure better yield and reduce risk from climate-related crop failure. Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

However, the modeling results have to be interpreted with great care due to significant gaps in the underlying data. Data Gaps The study clearly experienced the need for a more organized and tedious collection of weather and crop production data. Indeed quality of results of some study components suffered from lack of data. There are many gaps in the historical weather data available from PAGASA. Some provinces did not have a single functional government weather station, like in the case of Banaue, Ifugao. There is a wide distance between meteorological stations. It seems there is only one station to gather weather variables per province. There exist crop production data sheets that Municipal Agricultural Offices use to document the agricultural crops planted per barangay. They should serve as the basis for the monitoring of crops planted, time of planting, their area covered, production inputs, pest and diseases observed, yield, etc. However, during the conduct of our research, the study team was often not able to receive these historical datasets, partially due to breakdown in communications or difficulties in cooperation. To fill in the data gaps, Component 2B returned to Benguet and asked the vegetable farmers directly through FGD their experiences in crop loss due to specific hazards in the past years. They recalled the times a typhoon hit their community, what was the growth stage of their crops and estimated the crop damage and lost.

Recommendations The project has increased the understanding of vulnerabilities and adaptive capacity in the upland farming in Benguet and Ifugao. Natural predictors of hazards were observed through the millennia and were incorporated in this body of indigenous knowledge which has guided ethnic communities in food production. This documented knowledge could be harmonized with scientific technology, such as cropping calendars and infrastructure development, to help the provinces to adapt to climate change through sound early warning system for climate-related hazards that inform early action. The developed Agricultural Systems Vulnerability and Adaptive Capacity (AgSysVACA) assessment tool is adequate to roughly quantify the vulnerability index of a particular barangay or community. It relies on secondary data which the Barangay or the Municipal Agricultural Office already have as well as first hand Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1

experiences of farmers in evaluating exposure, risks and deficits in adaptive capacity towards a particular hazard. Further enhancement of the tool will deal on the weights given to indicators to proportionally model its effect on the overall vulnerability to a certain hazard. This can be done by a panel agricultural system experts, MAOs and farmer leaders who can justify their importance in factoring in these indicators. The crop loss model developed in Component 2B could be used to valuate crop losses due to a particular hazard and should be the basis for cost-effective measures in mitigation options. However, the model would have to be improved by implementing proper documentation of crop production, occurrence of future hazards and their effect on the community’s crop production. The dissemination and implementation of the developed AgSysVACA assessment tool could be use Province-wide at the Barangay level to categorize their vulnerabilities to different hazards. The results from this assessment should be overlapped with the bio-physical and social characteristics of the communities done by the respective provincial SUCs to map out vulnerable areas that will be the basis for future mitigation development projects in the two provinces, and eventually the whole Cordillera. The developed training modules could be used for further training activities in Benguet and Ifugao in the context of future projects.

Synthesis Report of UPLBFI study for MDG-F 1656 Outcome 3.1