Crop and Livestock Compensation/Insurance Against

Crop and Livestock

Compensation/Insurance

against Climate -induced Disasters and

Wildlife Incursions

Report

Enhancing Sustainability and Climate Resilience of Forest

and Agriculture Landscape and Community Livelihoods in

Bhutan

Belt.’

UNDP, BHUTAN SEPTEMBER 2016

TABLE OF CONTENTS Page No.

Acronyms ...... 5 Executive Summary ...... 6 1. Background ...... 9 2. Methodology ...... 10 2.1 Literature review...... 10 2.2 Survey design...... 12 2.2.1 Selection of Gewogs and Chewogs for field study ...... 12 2.2.2. Selection of Chewogs ...... 13 2.2.3. Field Surveys ...... 14 2.3. Data Analysis ...... 16 3. Vulnerabilities and Issues in Agriculture ...... 18 3.1 Trends at Dzongkhag Level ...... 18 3.1.1 Vulnerabilities related to climate-induced loss in crop yield and quality...... 18 3.1.2 Vulnerabilities related to crop loss by wildlife ...... 18 3.1.3 Loss of Four Major Crop Types due to Wildlife ...... 20 3.2 Trends at Gewog Level ...... 22 3.2.1 Vulnerabilities related to agriculture ...... 22 3.2.2 Vulnerabilities related to climate-induced loss in crop yield and quality...... 23 3.2.3 Loss of four major crop types due to wildlife ...... 25 4. Human Wildlife Conflict ...... 28 4.1 Vulnerability by Damage to Crops ...... 28 4.2 Vulnerability by Livestock Depredation ...... 31 4.3 Vulnerability by Severity: Ranking by Chewogs and Gewogs ...... 32 4.4 Trends in Human Wildlife Conflicts ...... 33 4.5 Hotspots of Livestock Depredation ...... 35 4.6 Hotspots Mapping for Severity of Damage within the Project Landscapes ...... 37 4.6.1 Severity of crop damage by climate-induced factors ...... 37 4.6.2 Severity of damage to 4 crops by wildlife incursions ...... 39 4.6.3 Severity of livestock depredation ...... 42 5. Conflict Management Strategy ...... 44 5.1 Policies, Legislation, Regulations and Programs...... 44 5.2 Review of best practices ...... 45 5.2.1 Monetary compensation in South Asia ...... 45 5.2.2 Monetary compensation in the western USA ...... 46 5.2.3 Pre-emptive monetary compensation in Sweden ...... 46 5.2.4 Innovation in livestock insurance in Pakistan ...... 46 5.3 Interventions and Adaptation ...... 47 5.4 Community and Institutional Capacities...... 50 6. Proposed Interventions ...... 53 6.1 Prevailing Schemes for Crop and Livestock Compensation ...... 53 6.2 Monetary compensation for livestock depredation...... 54

6.3 Electric fencing ...... 54 6.4 Community-based insurance through Gewog Environment Conservation Committees ...... 55 6.5 Private Cattle Insurance ...... 57 7. Pilot Project Interventions ...... 58 7.1 Human Wildlife Conflict Management Strategy ...... 58 7.2 Private Livestock Insurance ...... 60 7.3 Private Crops Insurance ...... 62 7.4 Financial Plan ...... 65 Bibliography ...... 67 Annex 1: Terms of Reference ...... 73 Annex 2: Selection of Chewogs for the study ...... 78 Annex 3: Gewog level questionnaire ...... 80 Annex 4: Chewog level questionnaire ...... 81 Annex 5: Livestock Depredation in Project Landscapes (2002-2015) ...... 85 Annex 6: Crop Damage by Climate Induced Factors in Project Landscapes (2011-2015) ...... 89 Annex 7: SAFE Approach to HWC management, adapted for Bhutan ...... 91 Annex 8: Cattle insurance policy (RICB) ...... 96 Annex 9: Crop insurance proposal (RICB) ...... 99 Annex 10: List of consultations ...... 102

List of Tables, Figures & Maps

Table 1: Dzongkhags, Gewogs & Chewogs selected for survey ...... 13 Table 2: Gewogs & Chewogs Covered in Sampled Dzongkhags...... 14 Table 3: Total Households in Chewogs ...... 17 Table 4: Climate Change related issues at Gewog level (UNDP, 2016) ...... 22 Table 5: Ratio Analysis of Crop Loss by Climate-Induced Factors in Landscapes (2011-15) ...... 24 Table 6: Types of HWC reported to Department of Forests & Parks Services ...... 34 Table 7: Comparison of reported HWC across Project Landscapes ...... 34 Table 8: Ratio analysis of livestock depredation (2002-2015)...... 35 Table 9: Livestock depredation in Landscape 1 (2002-2015) ...... 35 Table 10: Livestock depredation in Landscape 2 (2002-2015)...... 36 Table 11: Livestock depredation in Landscape 3 (2002-2015)...... 36 Table 12: Selected human-wildlife conflict interventions since 2000 ...... 53 Table 13: Electric fencing, 2011-2015 ...... 55 Table 14.1: Existing GECCs, initial capitalization, location ...... 56 Table 14.2: GECCs planned for 2016-2017, budget, location ...... 56 Table 15: Cattle insurance at RICB (revised 20% premium of 70% claim of sum insured) ...... 57 Table 16: Revised, minimum insured values, by cultivated area ...... 63 Table 17: Revised, minimum insured value, by cropping stage ...... 64 Table 18: Indicative financial plan for proposed pilots (Amount in Nu.) ...... 66

Figure 1: Age range of farmers surveyed 15 Figure 2: Overall gender ratio during the survey 15 Figure 3: Gender ratio during the survey, by Dzongkhag 16 Figure 4: Households citing natural calamities affecting crop yield & quality in 2013 (DoA, 2013). 18 Fig.5: Households (%) affected by natural calamities, 2014 (DoA, 2014) 19 Figure 6: Farming households affected by various constraints in 2013 (DoA, 2013) 19 Figure 7: Farming households affected by various constraints in 2014 (DoA, 2014) 20 Figure 8: Paddy loss by area & Metric ton for 2014 (DoA, 2014) 20 Figure 9: Wheat loss by area & Metric ton for 2014 (DoA, 2014) 21 Figure 10: Maize loss by area & Metric ton for 2014 (DoA, 2014) 21 Figure 11: Potato loss by area & Metric ton for 2014 (DoA, 2014) 22 Figure 12: Ranking by Climate Change Vulnerability Standardized Index (UNDP, 2016) 23 Figure 13.1: Crop loss across Landscapes in Acres 24 Figure 13.2: Crop loss outside Landscapes in Acres 24 Figure 14: Crop loss throughout Bhutan in Acres due to Climate-induced factors 25 Figure 15: Paddy lost in Acres by Dzongkhag and Gewog, 2013-2015 (DoA, 2016) 26 Figure 16: Maize Lost in Acres by Dzongkhag and Gewog, 2013-2015 (DoA, 2016) 26 Figure 17: Wheat Lost in Acres by Dzongkhag and Gewog, 2013-2015 (DoA, 2016) 27 Figure 18: Potatoes Lost in Acres by Dzongkhag and Gewog, 2014-2015 (DoA, 2016) 27 Figure 19: Total area damaged by wildlife across Landscapes 28 Figure 20: Chewogs by Total Area Damaged (Acres) 29 Figure 21: Cause of crop damage by wildlife species in Chewogs 29 Figure 22: Crop damage by 5 wildlife species in Chewogs 30 Figure 23: Crop damage by wildlife species at various growth stages 30 Figure 24: Perceived causes of livestock management problems 31 Figure 25.1: Total number of livestock loss reported in 2015 31 Figure 25.2: Total percentage of livestock loss reported in 2015 32 Figure 26: Livestock losses by Dzongkhag 32 Figure 27: Severity of livestock loss by Chewog 33 Figure 28: Top predators reported by Chewog 33 Figure 29: Guarding of Crops by Gender 47 Figure 30: Average crop guarding by days & nights in 2014 (DoA, 2014) 48 Figure 31: Preferred measures to reduce wildlife induced crop loss 48 Figure 32: Preferred measures to reduce wildlife induced crop losses 49 Figure 33: Preferred measures to reduce wildlife induced livestock losses 50 Figure 34: Awareness of F&NC Rules 2006 50 Figure 35: Full commercial rate household level insurance 50 Figure 36: Government subsidized household level insurance 51 Figure 37: Gewog/community level insurance 51 Figure 38: Availability of current crop and livestock protection schemes 52 Figure 39: Levels of reluctance or interest for crops and livestock insurance 52 Figure 40: Review of Electric Fencing impact in selected sites, 2013 54 Figure 41: SAFE Baseline matrix (Brooks, 2015) 60

Map 1: Severity of crop damage by climate-induced disasters (2013-2015) ...... 38 Map 2.1: Severity of damage to Paddy in Acres by wildlife incursions (2013-2015) ...... 39 Map 2.2: Severity of damage to Maize in Acres by wildlife incursions (2013-2015) ...... 40 Map 2.3: Severity of damage to Wheat in Acres by wildlife incursions (2013-2015)...... 41 Map 2.4: Severity of damage to Potato in Acres by wildlife incursions (2013-2015)...... 42 Map 3: Severity of livestock depredation by head count (2002-2015) ...... 43

Acknowledgements

Many individuals and institutions in Bhutan contributed to this study, and they are gratefully acknowledged. Foremost, the Gups and people of the communities surveyed throughout the project landscapes are thanked for their sincerity and candor about their experiences, aspirations and insights. The Director of the Department of Forests and Parks Services, and staff of its Wildlife Conservation Division, was generous with information and insights, particularly on biological corridors and human wildlife conflicts. Aum Yeshi Dema and Dr. Thinlay at the National Plant and Protection Center shared both time and information, as did key staff of the Department of Agriculture. The country representative and Aum Deki Wangmo of WWF Bhutan Program made it possible to map the hotspots.

Sincere thanks are owed for constructive and timely advice, to many specialists from the government and the PPG who commented on earlier versions of this report. Dasho Penjore, Governor of the Royal Monetary Authority, provided valuable advice, and key colleagues in the financial industry proved to be a reliable sounding board. From the beginning, Tashi Dorji and Tshering Penjor at UNDP provided constant guidance and support, without which this study would not have been possible.

Acronyms

BC Biological Corridor BIL Bhutan Insurance Ltd. CC Climate change DoA Department of Agriculture EF Electric Fencing FNCA Forest & Nature Conservation Act 1995 FNCR Forest & Nature Conservation Rules 2006 FYP Five Year Plan GECC Gewog Environment Conservation Committee GEF Global Environment Facility GIS Geographic Information System HWC Human wildlife conflict JSWNP Jigme Singye Wangchuck National Park JKSNR Jigme Khesar Strict Nature Reserve LDCF Least Developed Country Fund MoAF Ministry of Agriculture and Forests NCD Nature Conservation Division NP National Park NPPC National Plant Protection Center PA Protected Area PNP Phrumshingla National Park PPG Project Preparation Grant PRA Participatory Rapid Appraisal RCEC Resilient Communities, Effective Corridors RGoB Royal Government of Bhutan RICB Royal Insurance Corporation of Bhutan Ltd. RMA Royal Monetary Authority RNR Renewable Natural Resources SEF Solar electric fencing SI Sum insured UNDP United Nations Development Programme WCD Wildlife Conservation Division WWF World Wildlife Fund

Executive Summary

Climate change has introduced gradual impacts on agriculture and rural livelihoods, through unpredictable weather patterns, reduced yields, loss of biodiversity and genetic resources, occurrence of forest fires and pests and diseases, and overall decline in ecosystem services. This study examines the necessity and feasibility of introducing sustainable and viable compensation schemes to reduce climate change vulnerabilities in local livelihoods, and sustain long-term protection of biodiversity in three protected areas and four biological corridors of Bhutan.

Methodology

The study reviewed (a) damage/loss of crop and livestock to climate-induced disasters in the country with detailed data of such losses in the target project areas including mapping of Gewogs according to severity of damage/loss; (b) existing compensation schemes, their effectiveness and identified opportunities and challenges to strengthen them; and proposes (c) viable compensation options, including community-based schemes in target project areas.

To supplement available secondary data, rapid field surveys were undertaken from 9th April to 22nd May 2016 in 36 Chewogs of 18 Gewogs covering 10 Dzongkhags, representing 39% of 92 Chewogs of the project landscapes. A minimum of a Gewog in each Dzongkhag was included, with 2 Chewogs under each Gewog. Household level surveys were deferred to project commencement in 2017. Dzongkhag and Gewog-level data on land and livestock were extracted from secondary and primary sources. Primary information collected from the central agencies and Dzongkhags was used extensively to analyze trends and design interventions.

Key findings

Fieldwork confirmed 95% of respondents observing an increase in summer temperatures, and 60% in winter temperatures. 9 Gewogs were identified for above-average vulnerability to climate change, with the most vulnerable located inside Landscapes 2 and 3.

Over the last 5 years, out of 1,997 acres adversely affected by climate-induced factors (heavy rainfall, drought, frost, hailstorms, windstorms, and landslides), 17% was reported from project Landscapes, which corresponds to 33% of all households similarly affected across the country. Landscape 2 recorded the highest incidents (61.39%), affecting 60% of households.

Loss to wildlife of four primary crops was analyzed, namely paddy, maize, wheat and potatoes. Data from 2013-2015 was benchmarked against the RNR Census of 2009. During 2013 and 2014, 60% of households reported crop damage by wildlife. Except for wheat, losses in the 3-year period were greater than the baseline estimated. Main wildlife species were wild pigs, deer, monkeys and elephants.

Livestock depredation was identified as the major feature of human wildlife conflict, and concentrated in or near protected areas and biological corridors. Tigers, snow leopards, leopards, bears and wild dogs preyed on yaks, cattle, horses, mules, sheep and goats. During the 2002-2015 period, 2,284 heads of livestock were reported as casualties from around the country, costing the government Nu. 8,837,950 in disbursed compensation. In the 3 Landscapes, 46% (915 livestock) of the national loss was reported. The highest incidences were reported from Landscape 2 with

619 incidents (corresponding to 35% of all incidents in the country). In comparison, only 36 incidents were reported in Landscape 1 and 260 in Landscape 3.

Gewogs in the project Landscapes were mapped for hotspots severity, according to Very High, High, Moderate and Low rankings.

Under crop damage by climate-induced factors, Bjena Gewog in Landscape 2 was ranked under Very High severity, with 166 households losing 179.92 acres of various crops over the 5-year period. At national level, 17% of damages was reported from the Project Landscapes, representing 33% of all households similarly affected across the country. Total damages reported in Landscape 2 is 409.91 acres constituting 61.39% of the 3 Landscapes, affecting 60% of households in the project area. In comparison, Landscape 1 lost 10% and Landscape 3 lost 8% of total acreage of the project sites.

During 2013-2015, under damages to paddy, maize, wheat and potato by wildlife incursions, Korphu Gewog in Landscape 2 ranked Very High severity for paddy loss, followed by Kabjisa, Toepisa and Athang Gewogs under High severity. For maize, 4 Gewogs under Landscape 2 (Phuentenchhu, Patakla, Jigmichhoeling and Doban) were ranked Very High severity. Under 3 Gewogs were ranked under High severity, (Langthil in Landscape 2, Jaray and Metsho in Landscape 3). For wheat, Bji Gewog in Landscape 1 was ranked Very High severity, and Daga Gewog in Landscape 2 was ranked High severity. For potato, Phobji Gewog in Landscape 2 and Tsento Gewog in Landscape 1 were ranked under Very High severity.

Under livestock depredation to wildlife, Nubi Gewog under Trongsa Dzongkhag in Landscape 2 was ranked Very High severity, reporting the highest loss of livestock (195 animals) to wildlife over the 2002-2015 period. At national level, losses from the 3 Landscapes accounted for 46.06% (915 livestock) of all claims submitted to the government for direct monetary compensation during 2002-2015. Landscape 2 accounted for 35% of all incidents in Bhutan, with 619 incidents reported. In comparison, only 36 incidents were reported in Landscape 1 and 260 in Landscape 3. During the random survey, the second highest loss in 2015 was reported from Chendebji under Trongsa Dzongkhag.

The government’s Human-Wildlife Conflicts Management Strategy to address crop damage and livestock depredation was reviewed, as were several best practices of compensation, including monetary compensation in South Asia and the western USA, pre-emptive monetary compensation in Sweden, and an innovative snow leopard insurance scheme in Pakistan.

While initially effective, the HWC management strategy has since been less adaptive and partly failed to address the causes of human wildlife conflicts. This is evident in the growing conflicts between farmers and big cats, wild dog, wild pig and elephants. Direct monetary compensation was found to be unsustainable in Bhutan’s context and experience; in fact, compensation for livestock depredation suddenly stopped in 2015 due to lack of funds. There are presently no active crop insurance schemes throughout Bhutan, but some livestock insurance schemes have been combined with compensation schemes and launched through 26 GECCs (12 are located within Landscapes 2 and 3). During the survey, no insurance schemes were encountered, and the lack of interest to insure crops and livestock was attributed to availability of direct cash compensation for livestock depredation.

Recommendations

The following interventions are recommended for piloting throughout the project Landscapes.

(i) SAFE human wildlife conflict management strategy: Review and retrofit the national HWC management strategy, to adapt and adopt the SAFE Systems approach presently undergoing field- testing in Bhutan. The SAFE system has been found to be more interactive and prescriptive than ongoing tools and has been pioneered by in tiger range countries.

(ii) Private livestock insurance: A public-private partnership model using GECCs can help to create a market-based insurance scheme, that will (a) attract participation of livestock owners, (b) guarantee near market-value payment for livestock losses, and (c) ensure a sustainable business model to relieve the government of unsustainable financial handouts. A pilot scheme is proposed to cover 10 Gewogs: this will include 5 Gewogs identified under ‘Very High’ and ‘Moderate’ severity ranking and another 5 Gewogs from ‘Low’ severity. The latter 5 Gewogs are selected based on high livestock loss (above 35 heads) even though they may have been clubbed under ‘Low’ severity.

For every domestic animal insured, participating households will pay 30 basis points of a ‘reasonably-estimated’ annual premium of 1%, while the government will pay another 30 basis points, and the project will pay the balance 40 basis points. In order to subsidize the project’s 40% contribution, and create a reserve fund with any surplus to sustain the scheme, the project will set aside $225,000 to capitalize each Gewog fund with Nu. 1,500,000 ($22,500). The pilot scheme will finance only insurance claims, and in order for insurance to succeed in the pilot sites, direct monetary compensation for livestock depredation has to be discontinued.

(iii) Private crops insurance: Globally, crop insurance remains one of the most heavily subsidized economic sectors. A World Bank survey of 65 countries in 2009-2010 confirmed premium subsidies to be a common mechanism (by 63% of countries) for public sector involvement in crop insurance. Similar to the above livestock insurance proposal, a public-private partnership model using GECCs is proposed for a crop insurance scheme in 17 hotspot Gewogs identified for vulnerability to wildlife and/or climate induced disasters (i.e., 10 Gewogs ranked under Very High severity and 7 Gewogs ranked under High severity).

For every unit of cropland insured, participating households will pay 30 basis points of a ‘reasonably-estimated’ annual premium of 1%, while the government will pay another 30 basis points, and the project will pay the balance 40 basis points. In order to subsidize the project’s 40% contribution, and create a reserve fund with any surplus to sustain the scheme after the project cycle, the project will set aside $380,000 to capitalize each Gewog fund with Nu. 1,500,000 ($22,500). Compared to livestock insurance, the premiums for crop insurance will be more affordable and further subsidies may not be necessary at project conclusion.

(iv) Financial plan: Preliminary estimates indicate a 5-year requirement of Nu. 49,500,000 ($740,000) to implement the above recommendations. Insurance costs are conservatively budgeted, as premiums need to be negotiated with commercial insurers. In a recent development, the central bank has advised the launch of micro-insurance for rural development needs. Once approved, deposit-taking micro-insurance providers can offer a choice to consumers, especially through competitive pricing on annual premiums.

1. Background

In order to reduce climate change vulnerabilities and improve the sustainability of local livelihoods and biodiversity of the country, the Royal Government of Bhutan (RGoB) requested support from the Global Environment Facility (GEF) through the United Nations Development Programme (UNDP) for a full-sized project, ‘Resilient Communities, Effective Corridors (RCEC)- Climate Action in Bhutan’s Central Belt’.

The project aims to operationalize an integrated landscape-based approach to climate change adaptation and biodiversity conservation through;

 Improvement of institutional capacity at national, sub-national and local levels to manage forest and agricultural landscapes sustainably for enhanced climate resilience;  Emplacement of governance system for biological corridors and operationalization of conservation management system in the pilot corridors; and  Development of climate-resilient livelihood options for the local communities.

The objective of this assignment is to review crop and livestock loss to climate-induced disasters and wildlife incursions, examine existing and potential compensation/insurance/ technical measures to mitigate losses, and propose viable options with special attention to community- based modalities. The findings of the assessment will be vital to the formulation and design of the UNDP/GEF/Least Developed Countries Fund (LDCF) project, particularly in relation to development of climate-resilient livelihood options for the local communities and reduction of biodiversity threats from human-wildlife conflicts (HWC).

The assignment is to present (a) an overview of damage/loss of crop and livestock to climate- induced disasters in the country with detailed data of such losses in the target project areas including mapping of the Gewogs according to the severity of damage/loss; (b) existing compensation schemes and opportunities and challenges to strengthen them; and (c) viable compensation options, including community-based schemes in target project areas.

In order to achieve the above, the assignment was tasked to:

 Collate up-to-date data and information on loss of crop and livestock caused by climate- induced disasters and wildlife incursions in the entire country;  Map Gewogs in the target project areas according to severity of crop/livestock losses and damages by climate-induced disasters (e.g. low, moderate, high, very high) and wildlife incursions and identify hotspots;  Take stock of existing measures to alleviate impacts of crop/livestock losses and damages and assess their effectiveness, noting how they have benefitted men and women distinctly;  Review various types of compensation and insurance schemes for damage/loss of crop and livestock to climate-induced disasters (e.g. windstorm, hailstorm, excessive/untimely rain, drought, flashflood, and wildfire) and wildlife incursions within and outside Bhutan, examine successes and failures, assess issues, opportunities and challenges in Bhutan, and propose measures to strengthen existing schemes and/or introduce new, viable options and institutional modalities (government, public, private, community-based, etc);  Carry out a rapid assessment of HWC in targeted Protected Areas (PAs) and Biological Corridors (BCs), identify hotspots, and develop a safe HWC management strategy, building on lessons from WWF’s work in tiger range countries.

2. Methodology

In order to better understand the context and scope of the assignment, a desk review of the relevant literature was carried out, based on which fieldwork, data analysis and consultations were undertaken.

2.1 Literature review

RGoB has recognized that climate change (CC) mainly threatens the agrarian population dependent on subsistence agriculture as a daily livelihood (MoAF, 2014). The farming community is recognized as the most vulnerable group. “Frequent landslides, prolonged dry periods, and unprecedented heavy monsoon rain are visibly affecting agriculture and biodiversity. Main cash crops like rice, potatoes, chillies, apples and oranges are sensitive to water and temperature variations” (ibid.) Dry land crops such as wheat, buckwheat, maize, and barley are even more vulnerable to climate risks, as they are entirely dependent on rainfall.

Rural communities’ proximity to nature, especially those living inside or adjacent to protected areas are exposed to increasing levels of human-wildlife conflict. Not only do these communities bear the brunt of unpredictable climate risks, they also lose an average of 0.33 to 18% of total annual household income to wildlife, in spite of spending about two months each year guarding their crops. The RNR Census of 2009 indicated 33.9% of farmers’ inability to prevent crop damage by wildlife, as a major reason for leaving land fallow (MoAF, 2014). Finally, livestock depredation by wild predators equated to “average annual financial loss of 17% of total per capita cash income. The annual mean livestock loss per household was 1.29 head of stock, which is the equivalent of more than two-thirds of annual cash income.”

56.7% of the total labor force of Bhutan is employed in agriculture sector (NLFS, 2014) practiced on 2.93% of total land. This makes agriculture one of the most important economic sectors, and highly vulnerable to impacts of climate change. Furthermore, agriculture in Bhutan depends mostly on rain-fed crops. The subsistence agriculture economy provides equal importance to both livestock and crop farming. Similarly, livestock are the vital source of draught power, food, and supplement for cash income and means of transportation (NCD, 2008; WCD, 2013). Loss of any domesticated animal such as cow, pig, oxen, poultry and ponies to wild predictors can have a huge impact to the family (Wang & Macdonald, 2006). Livestock depredation affects the livelihood of farmers, provoking retaliatory killings by farmers (NCD, 2008).

Climate change has introduced gradual impacts on agriculture and rural livelihoods, with emerging challenges of unpredictable weather patterns, reduced yields, loss of genetic resources, and occurrence of pests and diseases. Community livelihoods based on pastoralism and agriculture are indicated to be affected by new diseases, pests, and parasites and by shifting phenological and seasonal changes induced by climatic changes. As a result, vulnerability at a community level, particularly among subsistence farmers, is considered to be high (Lhendup et al; WWF, 2011).

The impact is high on overall biodiversity, including significant changes in agriculture, forestry, wildlife and land resources. Occurrence of forest fires, loss of biodiversity, shifts in habitats, occurrence of pests and diseases and overall decline in ecosystem services of the environment are emerging challenges. In particular, forest fires are a recurrent phenomenon, with their number

increasing from 45 incidents in 2007-2008 (destroying 2,631 acres of forest) to 84 in 2015-2016 (destroying 21,195 acres of forests); over these 9 years, a total of 467 forest fires were recorded, which destroyed 133,398.51 acres of forests, valued conservatively at Nu. 2,736,297 (Tshering, pers.comms.). The loss does not include damage to rural and urban infrastructure, livestock and human life.

In the past two decades Bhutan has witnessed an increase in human-wildlife conflict. The increased proximity of human populations to wildlife as their habitat is encroached, fragmented and destroyed has been attributed to be a leading driver of human-wildlife conflict. Around the world, the 20th century also witnessed a surge in the population of wildlife species once on the verge of extinction (Decker & Chase, 1997).

With the exacerbation of human-wildlife conflicts, poverty will only increase. Almost all protected areas have human settlements who predated modern conservation by centuries. Moreover, people are likely to become hostile when their livelihoods are affected by conservation policies (Treves, 1998), and when government policy restricts traditional land uses and/or increase losses of livestock, crops, and human life (Mordi, 1991; Mehta & Kellert, 1998; Conover, 2002; Woodroffe et al, 2005). This can potentially compromise the future of conservation and protected areas (Naughton-Treves, 1998; Bhatnagar, et al, 2000; Straede & Helles, 2000).

Bhutan’s coverage of protected areas is one of the world’s highest. Yet, some parks and the biological corridors remain protected only on paper. All 8 biological corridors covering 9% of the country have yet to be operationalized, let alone being assessed for ecological effectiveness (Kuensel, October 2015). This is in spite of being declared as “Gifts to the Earth” in 1999. Although gazetted as early as 1993, parks like Jigme Khesar Strict Nature Reserve have only recently been able to develop a management plan, and become operational.

The communities that live within the protected areas struggle to survive, as they need to compete for subsistence livelihoods against climate change and the constant presence of both wild herbivore and carnivore species. The protected areas they inhabit are some of the most ecologically intact and diverse in the world, and the corridors allow the documented movement of wildlife in all directions.

Wagner et al (1997) suggest three forms of wildlife damage management methods: managing offending animals or habitat, modifying human activities, and increasing human tolerance to wildlife. Based largely on increasing human tolerance to wildlife, in 2008 Bhutan launched a HWC Management Strategy, to address both crop damage and livestock depredation by wildlife (NCD, 2008). While the strategy was effective in recognizing human interventions, it has since been less adaptive and partly failed to address the causes of human wildlife conflicts throughout Bhutan. This is evident in the growing conflicts between farmers and wild species such as the big cats, wild dog, wild pig and elephants.

Recognizing that humans cannot win this conflict, especially in the protected areas, the government is open to more effective approaches to reduce tensions. By agreeing to operationalize the biological corridors, Bhutan will enable the few remaining wild areas to be properly managed.

In the course of project formulation for half the un-managed BCs, and some of the most diverse national parks in Asia, this study is an opportunity to rapidly assess the challenges facing the

project site’s 88,783 people, and find effective ways of helping these communities adapt to climate change and wildlife incursions.

2.2 Survey design

In line with the objectives of the assignment, field surveys at Gewog and Chewog levels were planned. Structured questionnaires, reviewed by the Project Preparation Grant (PPG) team, were administered at each level during 9 April to 22 May, 2016 in the selected Dzongkhags, Gewogs and Chewogs of all three project Landscape areas.

2.2.1 Selection of Gewogs and Chewogs for field study

Although various sub-consulting groups proposed to administer household level surveys in the landscape area, considering the higher quality data for planning purposes, the joint meeting on 1 April between the PPG team and sub-consultants at Ariya Hotel in Thimphu decided to limit fieldwork to qualitative assessments at the Gewog level. It was felt that household surveys and real-time baseline data collection would be better taken up during project implementation from 2017. Therefore, PRA exercises at Chewog level were planned and undertaken, as per Annexures 2, 3 and 4.

The project Landscape area covers 12 Dzongkhags, 37 Gewogs and 195 Chewogs. The definition of Chewogs is based on the delimitation of Demkhongs by the Election Commission of Bhutan.

In order to enable representation of each Dzongkhag, the study included a minimum of a Gewog in each Dzongkhag. However, those Dzongkhags with less than 10% of their area under a Landscape were omitted in the Gewog selection. Beyond this minimum consideration, the prioritization of Gewogs was done on the following criteria:

o Gewogs with more than 30% of their area falling within a landscape; o Maximum of three Gewogs and minimum of one Gewog in each Dzongkhag, with priority accorded to those Geowgs with highest proportion of their area falling within a landscape; o Where more than three Gewogs qualify, that Gewog with higher proportion of its area within the BC was selected.

Based on the above criteria, 10 Dzongkhags and 18 Gewogs of the Landscape areas were included for field survey. 36 Chewogs representing 39% of the 92 Chewogs of these Gewogs, were selected for survey (Table 1).

Table 1: Dzongkhags, Gewogs & Chewogs selected for survey

Selection framework for study area

% area under Geographical location Chewogs Landscape Landscapes Selection Dzongkhag Gewog JKSNR BC1 Total (>30- 50%) Landscape 1: Jigme Khesar Haa Bji 50 20-25 4 2 Strict Nature Reserve Haa Sangbey 40-45 5 2 (JKSNR) + biological corridors with Jigme Dorji Paro Tsento 15-20 5 2 National Park Dzongkhag Gewog JSWNP BC2+BC3 Korphu 100 5 2 Trongsa Landscape 2: Jigme Singye Tangsibji 70-75 10-15 5 2 Wangchuck National Park Sarpang Jigmechholing 55 20 6 2 (JSWNP) + biological Athang 60 15 5 2 corridors with Jigme Dorji National Park & Wangchuck Wangdue Dangchhu 60 5 2 Centennial Park Phobji 30-35 20 5 2 Punakha Toepisa 50 5 2 Zhemgang Trong 30 5 2 Dzonghag Gewog PNP BC4 Chhumey 30 5 2 Bumthang Landscape 3: Phrumsengla Ura 50 5 2 National Park (PNP)+ Jarey 55-60 5 2 Lhuentse biological corridors with Metsho 55 6 2 Jigme Singye Wangchuck Tsamang 55 5 2 Mongar National Park Saleng 40 6 2 Zhemgang Nangkor 10 45 5 2 10 18 92 36

2.2.2. Selection of Chewogs

Based on the above list, those Chewogs to be included in the surveys were selected using a combination method of spatial assessment (whether a particular Chewog falls within the Landscape area) and random sampling. From the total 92 Chewogs in the selected Gewogs, only 2 Chewogs each were selected under each Gewog.

Thus, from the 10 sampled Dzongkhags, a total of 36 Chewogs out of 18 Gewogs were covered by the two joint survey teams during 19 April to 21 May 2016.

Table 2: Gewogs & Chewogs Covered in Sampled Dzongkhags

Dzongkhag No. of Gewogs No. of Chewogs Lhuntse 2 4 Mongar 2 4 Wangdue 3 6 Punakha 1 2 Paro 1 2 Bumthang 2 4 Trongsa 2 4 Zhemgang 2 4 Sarpang 1 2 Ha 2 4 Total 18 36

2.2.3. Field Surveys

Fieldwork was designed to focus on the same areas identified and selected for the Climate Change Vulnerability Assessment, in order to exploit and benefit from more efficient data collection, than if the assignment were to be executed independently. In this way, any likely duplication and overlap was avoided with the other group. Most of the information required for climate change induced impacts on agriculture and crop loss was collected by the vulnerability assessment team. The present team collected only information related to human-wildlife conflict in the target areas.

PRA techniques and key informants’ interviews were employed to derive information from targeted respondents in the selected Gewogs and Chewogs. For both PRA and key informant sources, a checklist of questions was administered to assess community level climate change vulnerabilities and climate change-induced wildlife incursions.

The following information at community level was collected through PRA and key informants:

Vulnerability of people, crops, livestock, physical assets/resources to adverse effects of climate change:  Type and extent of assets strengthened and/or better managed to withstand the effects of climate change;  Climate-resilient livelihood activities  Extent of adoption of climate-resilient technologies/practices.

Climate change adaptation into relevant policies, plans and associated processes:  Institutional arrangements to lead, coordinate and support the integration of climate change adaptation into relevant policies, plans and associated processes;  Local level plans and processes developed and strengthened to identify, prioritize and integrate adaptation strategies and measures;  Knowledge of and/or experience with crops and livestock compensation/insurance;  Level of interest and financial ability to support crops and livestock compensation/insurance.

The checklist administered at Chewog level comprised of semi-structured questionnaires (Annex 4) for which PRA sessions were used to derive the information.

Respondents at Gewog level included RNR extension agents and health officials of that Gewog, and also the Gup wherever possible. Chewog-level PRA participants included local communities from selected Chewogs, with representation of both men and women. Dzongkhag and Gewog- level information on land and livestock was extracted from secondary sources such as unpublished data from administrative records at the Department of Forests and Parks Services and the Department of Agriculture. In particular, crop damage trends for the years 2013 to 2015 were based on small area estimation conducted using current data.

Open-ended interviews were conducted at the center with key, relevant resource managers to:  identify the government’s views on human-wildlife conflict in the study area,  explore government’s support for crop and livestock compensation/insurance,  explore private sector interest in crop and livestock compensation/insurance, and identify the modalities to design pilot schemes for compensation/insurance for crops and livestock.

Figure 1: Age range of farmers surveyed

Above 64+ 7.00% 60-64 5.10% 55-59 6.20% 50-54 9.30% 45-49 11.70% 40-44 15.60% 35-39 10.90% 30-34 12.10% 25-29 13.60% 20-24 6.80% 15-19 1.60% 0.00% 5.00% 10.00% 15.00% 20.00%

15.6% of farmers surveyed were in the 40-44 years’ age category, 13.6% was between 25-29 years, 12.1% was between 30-34 years, and 11.7% was 45-49 years. 10.9% was between 35-39 years old. Overall, 45.1% of respondents were below 39 years, and 54.9% was above 40 years.

Figure 2: Overall gender ratio during the survey

61.10% 38.90%

0.00% 20.00% 40.00% 60.00% 80.00% 100.00% Female Male

The majority of respondents constituted female with 61.1% whereas 38.9% are male. Females dominated Zhemgang, Wangduephodrang, Punakha, Mongar, Lhuntse, Haa and Bumthang.

Figure 3: Gender ratio during the survey, by Dzongkhag

Zhemgang 75.00% 25.00% Wangdue 66.01% 33.99% Trongsa 34.48% 65.52% Sarpang 45.83% 54.17% Punakha 55.00% 45.00% Paro 47.62% 52.38% Mongar 57.89% 42.11% Lhuentse 51.28% 48.72% Ha 60.71% 39.29% Bumthang 72.58% 27.42% 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% Female Male

The large majority (22 Chewogs) had more than 50 households in the Chewogs. Samkhar in Sarpang had 106, followed by Buli in Zhemgang (95 households), Tokaling Tomla in Wangduephodrang (87 households), and Khyimdro Nemphel in Wangduephodrang (85 households). Dochola-Maenchhuna in Punakha and Mochhu in Haa had the least (17 households).

2.3. Data Analysis

Upon completion of field surveys, data compilation and analysis was done in Access. Analysis covered community-level vulnerabilities to adverse effects of climate change including livestock, agriculture, forest resources, and physical community assets/resources. However, only livestock, crops and wildlife related data analysis is presented in this report, as the former is being modeled and extensively discussed by the vulnerabilities assessment group.

Community-level interest and willingness to participate in project-initiated crops and livestock protection schemes were analysed, along with interest for self-help initiatives. The ability to pay for insurance and other forms of crop and livestock insurance was also assessed to study sustainability of project interventions.

Table 3: Total Households in Chewogs

Dzongkhag Gewog Chewog Total Households Ladrong 35 Jaray Nangngey 52 Lhuentse Gorsum 45 Metsho Ung-gar 70 Saling 27 Saleng Thridangbi 70 Mongar Drangmaling_Nangkor 18 Tsamang Thuenmong_Tokari 80 Khyimdro_Nemphel 85 Phobji Damchhoe_Gangphel 36 Tokaling_Tomla 87 Wangdue Dangchhu Uesagang 18 Rookha 41 Athang Lawa_Lamga 44 Dochola_Maenchhuna 17 Punakha Toepisa Goenmkha_Mendrelgang 65 Nyechhu_Shar-ri 74 Paro Tsento Nyamjey_Phangdo 60 Zung-Ngae 80 Chhume Domkhar 60 Bumthang Shing-Nyer 46 Ura Shingkhar 36 Tangsibji 73 Tangsibji Chendenbji 35 Trongsa Korphu Maed 82 Korphu Nyimzhong Toed 72 Gongphu 64 Trong Dhangkhar_Trong 74 Zhemgang Nyakhar 60 Nangkor Buli 95 Samkhar 106 Sarpang Jigmechoeling Gongtsekha 56 Mochhu 17 Sangbay Sangbay Ama 73 Ha Chenpa_Geychhukha 18 Bji Yangthang 55 TOTAL 2,026

3. Vulnerabilities and Issues in Agriculture

Throughout Bhutan, although clearly defined vulnerabilities to climate change are yet to be identified and quantified, trends have been observed over time that indicate declining agricultural productivity and quality due to natural calamities, among others (DoA, 2013 & 2014). In the study area, 95.1% of all participants during consultations observed increase in summer temperatures. 60.2% of all participants observed an increase in winter temperatures. The preliminary analysis conducted under a related study (UNDP, 2016), highlights increasing vulnerabilities in the same study area due to climate change.

3.1 Trends at Dzongkhag Level

3.1.1 Vulnerabilities related to climate-induced loss in crop yield and quality

Across the 20 Dzongkhags of Bhutan, secondary information collected over 2013 and 2014 indicated a high proportion of households citing natural calamities as a limiting factor.

Only Gasa Dzongkhag, in 2013 and 2014, did not report any effects by natural calamities on crop yield and quality (Figs. 4 and 5).

Figure 4: Households citing natural calamities affecting crop yield & quality in 2013 (DoA, 2013).

40 35 30 25 20 15

% HHS % 10 5 0

3.1.2 Vulnerabilities related to crop loss by wildlife

Crop loss attributed to damage by various wildlife species has been well documented in the literature and annual agriculture bulletins and publications. From 2000 it was as high as 42% of total production, with losses from paddy and maize due to wildlife ranging in US $4-5 million per year, and ensuing growth of fallow land and rural to urban migration (Maetz et al, 2012).

During 2013 and 2014, almost 60% of households reported their crops being affected by wildlife, which was most commonly cited as the dominant constraint to agricultural productivity (DoA, 2013 & 2014) (Figs. 6 & 7).

Fig.5: Households (%) affected by natural calamities, 2014 (DoA, 2014)

Dzongkhag Experienced Not Experienced Bumthang 2 98 Chhukha 8 92 Dagana 3 97 Gasa 0 100 Ha 4 96 Lhuentse 4 96 Monggar 17 83 Paro 1 99 Pemagatshel 6 94 Punakha 1 99 Samdrup Jongkhar 5 95 Samtse 11 89 Sarpang 7 93 Thimphu 2 98 Trashigang 21 79 Trashiyangtse 26 74 Trongsa 7 93 Tsirang 9 91 Wangdue 8 92 Zhemgang 3 97 BHUTAN 9 91

Figure 6: Farming households affected by various constraints in 2013 (DoA, 2013)

Landslides/soil erosion 2 Excessive rain 3 Hail strom/wind 7 Drought 9 Unproductive land 10 Shortage of Land 13 Limited access to markets 18 Crop damage by insects/disease 29 Insufficient irrigation supply 33 Labour shortage 47 Crop damage by wild animals 58 0 10 20 30 40 50 60 70

% HHs Affected

Figure 7: Farming households affected by various constraints in 2014 (DoA, 2014)

Crop damage by wild animals 56 Labour shortage 48 Insufficient irrigation supply 37 Crop damage by insects/disease 25 Limited access to markets 18 Shortage of Land 14 Unproductive land 11 Drought 8 Hail strom/wind 4 Excessive rain 2 Landslides/soil erosion 1 0 10 20 30 40 50 60

% HHs Affected

3.1.3 Loss of Four Major Crop Types due to Wildlife

Across the country, a review of damage by wildlife to the four major crop types in 2014 revealed high levels of loss (Figs. 8, 9, 10 & 11) (DoA, 2014). This also represents slightly higher losses by metric tonnes, compared to losses recorded for the same crops in the RNR census of 2008 (MoAF, 2010), although the total acreage affected is slightly lower in 2014.

Figure 8: Paddy loss by area & Metric ton for 2014 (DoA, 2014)

Dzongkhag Area lost (Acres) Quantity lost (MT) Bumthang 0.1 0.2 Chhukha 76 46 Dagana 133 90 Ha 18 12 Lhuentse 81 102 Monggar 28 21 Paro 100 109 Pemagatshel 3 1 Punakha 244 222 Samdrup Jongkhar 87 118 Samtse 112 106 Sarpang 163 150 Thimphu 3 7 Trashigang 59 63 Trashiyangtse 91 106 Trongsa 115 81 Tsirang 233 164 Wangdue 249 291 Zhemgang 66 38 BHUTAN 1,862 1,725

Figure 9: Wheat loss by area & Metric ton for 2014 (DoA, 2014)

Dzongkhag Area lost (Acres) Quantity lost (MT) Bumthang 24 21 Chhukha 9 7 Dagana 1 0.7 Ha 62 33 Lhuentse 0.9 0.9 Monggar 3 3 Paro 34 20 Pemagatshel 1 1 Punakha 9 4 Samdrup Jongkhar 1 1 Samtse 0.9 0.7 Sarpang 0.8 0.6 Thimphu 0.9 0.2 Trashigang 1 0.5 Trashiyangtse 0.7 2 Trongsa 4 2 Tsirang 3 1 Wangdue 12 5 Zhemgang 4 4 BHUTAN 173 108

Figure 10: Maize loss by area & Metric ton for 2014 (DoA, 2014)

Dzongkhag Area lost (Acres) Quantity lost (MT) Chhukha 210 159 Dagana 452 255 Ha 32 19 Lhuentse 233 300 Monggar 695 584 Paro 12 3 Pemagatshel 211 195 Punakha 21 19 Samdrup Jongkhar 399 490 Samtse 285 243 Sarpang 677 538 Thimphu 2 0.87 Trashigang 422 372 Trashiyangtse 166 229 Trongsa 145 143 Tsirang 757 503 Wangdue 44 26 Zhemgang 152 117 BHUTAN 4,914 4,194

Figure 11: Potato loss by area & Metric ton for 2014 (DoA, 2014)

Dzongkhag Area lost (Acres) Quantity lost (MT) Bumthang 12 42 Chhukha 30 132 Dagana 5 0.87 Gasa 0.1 0.14 Ha 47 141 Lhuentse 14 16 Monggar 57 74 Paro 113 199 Pemagatshel 4 6 Samdrup Jongkhar 8 13 Samtse 0.5 0.4 Sarpang 0.6 0.2 Thimphu 10 27 Trashigang 57 101 Trashiyangtse 27 58 Trongsa 6 5 Tsirang 14 8 Wangdue 72 244 Zhemgang 0.18 0.11 BHUTAN 476 1,069

3.2 Trends at Gewog Level

3.2.1 Vulnerabilities related to agriculture

During the survey, several issues were reported throughout the Landscape areas (Table 4), highlighting the vulnerabilities of climate change to agriculture.

Table 4: Climate Change related issues at Gewog level (UNDP, 2016)

% of Survey Issues Reported Gewogs Damage to FRs due to Poor drainage, landslide, erosion & Flood 44.4 Drying up of water source 33.3 Ban on retaliatory killing has increased wild pig population inflicting more damage 27.8 Conflicts in the community due to shortage of water 22.2 Soil erosion due to heavy rainfall 16.7 Reluctance of some farmers in electric fencing 11.1 No capacity in protection of critical land areas 11.1 No capacity in water management 11.1 Weak community ownership in maintenance works of Farm Roads 5.6 Unsuccessful plantations for land protection due to drought 5.6 Availability of NWFP is declining 5.6 Damage of water pipes 5.6

In a related study covering the same survey area and period, a vulnerability standardized index was developed for the first time at Chewog, Gewog and Landscape levels (UNDP, 2016). The index calculates average scores for standardized vulnerability, exposure, sensitivity and adaptive capacity, and the results are relevant for comparison with this study’s own severity ranking for human wildlife conflicts.

In the above study, 9 Gewogs in the Project Landscapes were identified for above-average vulnerability to climate change: Tsamang and Saleng in Mongar, Toepisa in Punakha, Chhume in Bumthang, Dangchhu and Phobji in Wangduephodrang, Nangkor and Trong in Zhemgang, and Korphu in Trongsa (Figure 12). The two highest levels of vulnerable Gewogs occur in Landscapes 2 and 3, overlapping with this study’s own severity rankings.

Figure 12: Ranking by Climate Change Vulnerability Standardized Index (UNDP, 2016)

3.2.2 Vulnerabilities related to climate-induced loss in crop yield and quality

In the data below (Table 5), out of 1,997 acres reported to be adversely affected by climate- induced factors, 17% was reported from Project Landscapes corresponding to 33% of all households similarly affected across the country, over 5 years. This information was collected informally from all Dzongkhags during the survey period, and will be published in 2016.

The highest incidence of crop damage from natural calamities was reported from Landscape 2, particularly within JSWNP and adjacent BCs. Total damages (409.91 acres) in Landscape 2 accounts for 61.39% of the 3 Landscapes, and has affected almost 60% of households in the project area. In comparison, Landscape 1 lost about 10% and Landscape 3 lost about 8% of total acreage of the project sites. The heaviest loss (179.57 acres) occurred in 2015 in Bjena Gewog under Wangduephodrang Dzongkhag falling under Landscape 2. Climate-induced factors damaging crops included heavy rainfall, drought, frost, hailstorms, windstorms, and landslides.

Table 5: Ratio Analysis of Crop Loss by Climate-Induced Factors in Landscapes (2011-15) Total Loss (2011-15) Kgs. Acres Households

Total of 3 Landscapes 459,172 518.09 639 % of Landscape 1 to all 3 Landscapes 4.14% 10.12% 6.81% % of Landscape 2 to all 3 Landscapes 54.59% 61.39% 59.93% % of Landscape 3 to all 3 Landscapes 21.28% 8.49% 13.26% Total national sites except 3 Landscapes 1,545,769 1,479 1,781 Grand National Total 2,004,941 1,997 2,420 % of Landscape 1 to Grand National Total 0.56% 2.05% 1.37% % of Landscape 2 to Grand National Total 26.7% 13.23% 27.43% % of Landscape 3 to Grand National Total 4.95% 1.73% 4.98% % of 3 Landscapes to Grand National Total 32.21% 17.01% 33.79%

Loss was measured both in area (acres) and volume (kilograms). Over the 5-year period for which data was available, a sharply increasing trend was observed with the most loss recorded in 2015, both within the project sites and across the country (Fig.13.1).

Figure 13.1: Crop loss across Landscapes in Acres

Total of 3 Landscapes (loss in Acres) 600 518.09 500

400 339.44 300

200 122.59 100 26.26 29.80 0 0 2011 2012 2013 2014 2015 Total

Figure 13.2: Crop loss outside Landscapes in Acres

Total national sites except 3 Landscapes (Acres) 1600 1479.02 1400 1200 1000

800 706.68

600 482.04 400 143.15 147.15 200 0 0 2011 2012 2013 2014 2015 Total

Figure 14: Crop loss throughout Bhutan in Acres due to Climate-induced factors

Loss in Acres

2500 1,997 1,997

2000 1,479 1,479

1500 1,046 1,046

1000 707

605 605

482 482

518

339 177 177

500 169

147 147

143 143

123

0 0 0 0 2011 2012 2013 2014 2015 Total

Total of 3 Landscapes Total national sites except 3 Landscapes Grand National Total

3.2.3 Loss of four major crop types due to wildlife

Although wildlife has been blamed for extensive damage to almost all crop types cultivated, for the sake of representative analysis, only the four major crops grown in Bhutan – paddy, maize, wheat and potatoes – have been highlighted in this study. Reliable primary data was available only for the past 3 years (2013-2015) (DoA, 2016), and was benchmarked against the RNR Census of 2009. Furthermore, although diverse wildlife species have been blamed, only the major suspects – wild pigs, deer, monkeys and elephants -- are highlighted in this study.

Although loss was measured both spatially and by volume (kilograms), only the acreage is presented here as anecdotal evidence suggests it to be the more accurate estimate of loss.

For paddy, maize and potato, losses in the 3-year period was greater than the baseline estimated in the same Gewogs and Dzongkhags in the Project Landscapes as per the RNR Census of 2009 (Vol. 2). The loss was slightly less for wheat, which may have been due to missing data from several Gewogs for the 2013-2015 period. a) Paddy lost to wildlife: In 2008, 364.6 acres of paddy land was lost to wildlife in 30 Gewogs of the Landscapes’ 12 Dzongkhags (MoAF, 2010). During 2013, 2014 and 2015, in the same areas, 921.2, 753.9 and 699.8 acres of paddy, respectively, were lost to wildlife (DoA, 2016).

Figure 15: Paddy lost in Acres by Dzongkhag and Gewog, 2013-2015 (DoA, 2016)

250 238

200 185 146 146 150

100 81

72 72

59 59

58 58

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Nahi

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Jarey

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Bjena

Saling

Trong

Chang

Nysho

Kabisa

Tsento

Athang

Korphu

Gangzur

Langthel

Dangchu

Tsamang

Toedbisa

Tangsibji

Maedtsho

Nangkhor

Shingkhar

Chhudzom

Sergithang

Sombaykha

Phuntenchu

Jigmecholing GasetshoWom B/thangHaa Lhuentse Mongar ParoPunakha S/pangT/phu Trongsa Tsirang W/due Z/gang 2013 2014 2015

b) Maize lost to wildlife: In 2008, 700.5 acres of maize land was lost to wildlife in 26 Gewogs of 10 Dzongkhags across the Landscapes (MoAF, 2010). During 2013, 2014 and 2015, in the same areas, 1,030, 900 and 945.8 acres of maize, respectively, were lost to wildlife (DoA, 2016).

Figure 16: Maize Lost in Acres by Dzongkhag and Gewog, 2013-2015 (DoA, 2016)

180

156 156 144 144

160 138 122.1 122.1

140 118 113.9 113.9

120 107.4

90 90

84 84

82 82 80.9 80.9

100 78.4

74 74

63 63

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Nahi

Nubi

Tang Daga

Jarey

Kazhi

Bjena

Saling

Trong

Chang

Kabisa

Tsento

Athang

Korphu

Gangzur

Langthel

Dangchu

Tsamang

Toedbisa

Tangsibji

Maedtsho

Nangkhor

Shingkhar

Chhudzom

Sergithang

Sombaykha

Phuntenchu

Jigmecholing GasetshoWom B/thangHaa L/tse Mongar ParoPunakha S/pangT/phu Trongsa Tsirang W/due Z/gang 2013 2014 2015 c) Wheat lost to wildlife: In 2008, 206.3 acres of wheat land was lost to wildlife in 22 Gewogs of 8 Dzongkhags across the Landscapes (MoAF, 2010). During 2013, 2014 and 2015, in the

same areas, 157.6, 89.4 and 199.6 acres of wheat, respectively, were lost to wildlife (DoA, 2016).

Figure 17: Wheat Lost in Acres by Dzongkhag and Gewog, 2013-2015 (DoA, 2016)

70 63

60 52.5 52.5 50

40 33

30 24.5

18.9 18.9

17 17

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Ura

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Jarey

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Samar

Kabisa

Tsento

Athang

Korphu

Chumey

Langthel

Dangchu

Tsamang

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Maedtsho

Nangkhor

Shingkhar

Sergithang

Sombaykha GasetshoWom B/thang Haa L/tse MongarParo P/kha Trongsa Tsirang W/due Z/gang 2013 2014 2015 d) Potato lost to wildlife: In 2008, 134.3 acres of potato land was lost to wildlife in 16 Gewogs of 6 Dzongkhags across the Landscapes (MoAF, 2010). During 2014 and 2015, in the same areas, 130.4 and 154.3 acres of potato, respectively, were lost to wildlife.

Figure 18: Potatoes Lost in Acres by Dzongkhag and Gewog, 2014-2015 (DoA, 2016)

35 30 30

30 27 27

25 23.6 22.3 22.3

20 17.8

15 2014

11.9 11.9

11.3 11.3 9.4 9.4

9 9 2015

8.6 8.6 8 8

10 7.8

7 7

6.9 6.9

Potato Potato Area Lost (Acres)

7 7

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Bjee

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Jarey

Kazhi

Bjena

Sephu

Chang

Nysho

Samar

Phobji

Tsento

Athang

Gangtey

Chumey

Gangzur

Langthel

Dangchu

Toedbisa

Tangsibji

Chhudzom

Sergithang Sombaykha B/thang Haa L/tse Paro P/khaS/pangT/phu Trongsa Tsirang W/due

4. Human Wildlife Conflict

Throughout Bhutan, human-wildlife conflict has dominated the public discourse on rural socio- economic development since the 1970s, with the debate receiving more attention and participation in the past two decades. More recently, the vulnerabilities to and impact from climate change on agricultural systems have entered the policy discourse, but have yet to be properly identified and quantified to influence or guide public policy.

The discussion in this chapter focuses on human-wildlife conflict, as findings from the rapid survey supported the trends revealed at Dzongkhag and national levels, as focusing mainly on human-wildlife conflicts. While damages to crops by climate-induced factors were reported, concrete evidence could not be established except at a broad, qualitative level. Thus, by far the major issues centered around crop damage and livestock loss due to wildlife.

4.1 Vulnerability by Damage to Crops

During the survey, feedback for the past one year revealed Landscape 2 as recording the most area damaged by wildlife (167 acres), followed by Landscape 3 (146 acres) and Landscape 1 (52 acres) (Fig. 19). This corresponds logically to the size of the landscapes, as Landscape 1 is the smallest and will have the least area damaged by wildlife. A more accurate measure of vulnerability/severity would be to assess the percentage ratio of the damaged area to arable area for that location. However, information on crop damages will be presently difficult to overlay at specific Gewog and Chewog levels within the project Landscape boundaries. This is because the information collected in the RNR Census of 2009 (MoAF, 2010) recording land holdings by landuse types at Dzongkhag and national levels (Table 16 on pp. 36), will be updated only in 2017, and has not yet been captured at Gewog and Chewog levels. Therefore, in order to present a more accurate vulnerability/severity ranking, the project could establish such baseline information early in the project cycle.

Figure 19: Total area damaged by wildlife across Landscapes

Total Area Damaged (Acres)

52 Landscape1 146 (JKSNR_BC1) Landscape2 167 (JSWNP_BC2+BC3) Landscape3 (TNP_BC4)

At the Chewog level, Korphu Maed Chewog under Trongsa Dzongkhag (Landscape 2) experienced the largest area damaged to wild animals (57 acres). This was followed by Kamchhoe Gangphel (51 acres) in Wangduephodrang (Landscape 2), Ladrong (45 acres) in Lhuntse

(Landscape 3), Zung Ngae (36 acres) in Bumthang (Landscape 2) and Mochhu (30 acres) in Haa (Landscape 1).

Figure 20: Chewogs by Total Area Damaged (Acres)

60 57 51

50 45

40 36 30

15 15

20 15

10 10 10

5 5 5 5

4 4

10 4

3 3 3

2 2

1 1

0 0 0 0 0 0 0 0

Total Area Damaged (Acres) Damaged Area Total

Buli

Saling

Rookha

Gorsum

Ung-gar Mochhu

Ladrong

Nyakhar

Samkhar

Gongphu

Domkhar

Tangsibji

Uesagang

Nangngey

Shingkhar

Yangthang

Thridangbi

Zung-Ngae

Chendenbji

Shing-Nyer

Gongtsekha

Lawa Lamga Lawa

Korphu Maed Korphu

Sangbay Ama Sangbay

Tokaling Tomla Tokaling

Nyechhu_Shar-ri

Nyimzhong Toed Nyimzhong

Dhangkhar Trong Dhangkhar

Nyamjey_Phangdo

Thuenmong Tokari Thuenmong

Khyimdro Nemphel Khyimdro

Chenpa Geychhukha Chenpa

Damchhoe Gangphel Damchhoe

Dochola Maenchhuna Dochola

Drangmaling Nangkor Drangmaling Goenmkha Mendrelgang Goenmkha Lhuentse Mongar Wangdue PunakhaParo Bumthang Trongsa ZhemgangSarpang Ha

Farmers from 36 Chewogs in all 10 Dzongkhags blamed wild pigs as the main cause of their crop loss and damage. 23 Chewogs identified deer, 21 Chewogs identified monkeys, 12 Chewogs identified porcupine, and 8 Chewogs identified bears.

Figure 21: Cause of crop damage by wildlife species in Chewogs

40 34 35 30 25 21 23 20 15 12 10 8 No. of Chewogs of No. 5 0

Wild Animals

The major crops lost to wildlife were identified as maize, paddy, buckwheat, vegetables and potatoes, and fruits. 24 Chewogs reported loss of maize to wild pigs, followed by monkeys (20 Chewogs), deer (15 Chewogs), porcupine (10 Chewogs) and bears (8 Chewogs). 5 Chewogs lost paddy to wild pigs, 4 Chewogs lost to monkeys and 5 Chewogs lost to deer. 18 Chewogs lost

buckwheat to wild pigs, 11 Chewogs lost to deer and a Chewog reported loss to porcupines. Vegetables and potatoes were lost to wild pigs in 22 Chewogs, to porcupines in 8 Chewogs and to monkeys in 7 Chewogs. 4 Chewogs reported loss of fruit mainly to monkeys.

Figure 22: Crop damage by 5 wildlife species in Chewogs

30 Maize 24 25 22 Paddy 20 20 18 Wheat/Buckwheat 15 Fruits 15 11 10 Vegetables (Potato) No. of Chewogs Chewogs of No. 8 8 10 7 5 5 4 4 5 1 0 0 0 0 0 0 0 0 0 0

Deer

Bear

Monkey

Wildboar Porcupine Wile Animals

The cropping stage during damage by wildlife was also identified. 20 Chewogs attributed crop loss throughout the entire crop stage (A-D) to wild pigs, followed by porcupines (8 Chewogs) and monkeys (6 Chewogs). During the flowering to matured stage (B-D) 23 Chewogs reported damage by deer. At semi-final to matured stage (C-D) 8 Chewogs blamed bears, followed by monkeys (15 Chewogs), porcupine (3 Chewogs) and wild pigs (14 Chewogs).

Figure 23: Crop damage by wildlife species at various growth stages

25 23 20 20 15 15 14 C-D B-D 10 8 8 No. of Chewogs of No. A-D 6 5 3 1 1 0 0 0 0 0 0 Bear Deer Monkey Porcupine Wildboar Wild Animals

A= planting, B= flowering, C= yield formation (ears, cobs, tubers, roots, seeds), D= matured stage just before harvest

4.2 Vulnerability by Livestock Depredation

Problems associated with livestock management, the other mainstay of rural agriculture, were also surveyed and documented. Throughout the survey area, the majority of farmers (22.4%) attributed attacks on livestock by wildlife as their biggest livestock management problem. 20.19% cited poor grazing areas as a constraint, 18.13% cited insufficient funds to purchase livestock management equipment, 16.61% cited disease, 12.2% cited insufficient water, and 9.72% cited lack of labour.

Figure 24: Perceived causes of livestock management problems

Poor grazing area 20.19% Lack of labourer 9.72% Insuficient water 12.20% Insuficient funds to purchase 18.13% Diseases 16.61% Difficult to access suport if not formed groups 0.69% Attack by wild animals 22.47%

0.00% 5.00% 10.00% 15.00% 20.00% 25.00%

Since depredation ranked highest for livestock losses, the total number of domestic animals lost in the past year was estimated in all 36 Chewogs in the 10 Dzongkhags surveyed. Poultry, cattle and yaks were reported to be the highest losses, followed by horses, goats and sheep.

Figure 25.1: Total number of livestock loss reported in 2015

Yak 103

Sheep 44

Poultry 510

Horses 56

Goat 45

Cattle 478

0 50 100 150 200 250 300 350 400 450 500

Figure 25.2: Total percentage of livestock loss reported in 2015

Yak 8.33%

Sheep 3.56%

Poultry 41.26%

Horses 4.53%

Goat 3.64%

Cattle 38.67%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00%

4.3 Vulnerability by Severity: Ranking by Chewogs and Gewogs

During the survey, Landscape 1 (i.e., Haa Dzongkhag) reported the highest percentage of livestock loss due to wildlife in the past one year (37.18%), followed by Landscape 2 (26.3% in Zhemgang, 11.4% in Trongsa), and Landscape 3 (11.14% in Lhuntse, 5.31% in Mongar). Paro and Punakha Dzongkhags did not report the loss of any livestock to wildlife in 2015.

Figure 26: Livestock losses by Dzongkhag

Ha 37.18% Mongar 5.31% Zhemgang 26.30% Lhuentse 11.14% Wangdue 5.31% Trongsa 11.40% Sarpang 2.72% Bumthang 0.65% Paro 0.00% Punakha 0.00% 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00% 40.00%

At the Chewog level, most cattle loss was reported in Sangbay Ama in Haa, Chendebji in Trongsa, and Ladrong in Lhuntse. Most goat losses were reported in Samkhar (Sarpang); horses in Sangbay Ama (Haa); poultry in Thridangbi (Mongar); and sheep in Khyimdro Nemphel (Wangduephodrang). The highest number of yaks were lost from Yangthang (Haa).

Figure 27: Severity of livestock loss by Chewog

160 140 150 120 100 100 100 80 85 60 50 50 Cattle 40 40 45 45 30 No. of Animals of No. 20 Goat 0 0 Horse

Poultry

Saling

Rookha

Gorsum

Mochhu

Ladrong

Nyakhar

Samkhar Gongphu

Tangsibji Sheep Zung-Ngae

Shing-Nyer Yak

Korphu Maed Korphu

Tokaling_Tomla

Nyechhu_Shar-ri

Khyimdro_Nemphel

Chenpa_Geychhukha

Dochola_Maenchhuna Drangmaling_Nangkor Lhuentse Mongar Wangdue PunakhaParoBumthangTrongsaZhemgangSarpang Ha

Top predators responsible for livestock loss were also identified during the survey. 12 Chewogs reported wild dogs as their top predator, 10 Chewogs identified tigers, 7 Chewgos identified leopards, and 4 Chewogs identified bears. 3 Chewogs identified eagles, and 2 Chewogs identified foxes.

Figure 28: Top predators reported by Chewog

35 30 25 20 15 10

Number Chewogs of Number 5 0 Cattle Goats Horses Poulty Sheep Yak Eagles 0 0 0 3 0 0 Fox 0 0 0 2 0 0 Bear 4 0 0 0 0 1 Wild dogs 12 0 2 0 1 1 Leopard 7 1 5 3 1 0 Tiger 10 0 2 0 0 1

4.4 Trends in Human Wildlife Conflicts

At a broad level, several types of human-wildlife conflict can be identified, such as human casualties, damage to property, crop loss and livestock depredation. During the past 3 years, the

central government recorded these conflicts whenever they were reported by field offices. Across Bhutan, trends reflect only reported incidents, and do not capture all incidents.

Table 6: Types of HWC reported to Department of Forests & Parks Services 2015 2014 2013 Property Property Property Livestock Human Livestock Human Livestock Human Dz. damage damage damage Depredation Casualties Depredation Casualties Depredation Casualties (house) (House) (House)

Bumthang 2 2 Chukha 2 Gasa 13 6 3 1 16 Haa 7 Mongar 1 Paro 2 2 3 P’Gatshel 5 1 1 Punakha 1 1 1 Samtse 2 Sarpang 1 3 1 1 SJongkhar 5 Tashigang 6 9 Trongsa 146 1 2 12 67 Thimphu 10 11 1 1 WPhodrang 10 14 1 1 Zhemgang 7 4 1 Total 202 7 4 61 6 4 90 8 5

From the above data, and additional information presented below, livestock depredation constitutes the major known cases of human wildlife conflict, and is heavily concentrated in areas falling within and/or adjacent to protected areas including the biological corridors.

The majority of cases occurred within Landscape 2. Out of 350 incidents across the country, 280 occurred inside Landscape 2 over the 3-year period (Table 7).

Table 7: Comparison of reported HWC across Project Landscapes 2015 2014 2013

Property Property Property Livestock Human Livestock Human Livestock Human damage damage damage Depredation Casualties Depredation Casualties Depredation Casualties (house) (House) (House)

Landscape 1 9 2 3

Landscape 2 167 1 2 46 3 3 74 1 1

Landscape 3 2 2 1

Total 178 1 4 48 3 4 74 1 4

4.5 Hotspots of Livestock Depredation

As an indicator, vulnerability of resident communities to wildlife-induced disasters is best demonstrated through livestock depredation records available with the central government.

Records over a 14-year period at Wildlife Conservation Division were collated and analyzed, to assess livestock losses attributed to wild predators/carnivores. The data collected since 2002 is available in Annex 5. The detailed records were maintained in the government since the launch in 2002 of direct monetary compensation for verified livestock depredation. However, only livestock kills attributed to tigers, snow leopard, wild dog, leopard, and bears were recorded, as depredation by other predators such as smaller cats, raptors, snakes, etc. were not compensated. To simplify presentation, all livestock types (yaks, cattle, horses, mules, sheep, goats, poultry, etc.) are broadly categorized together.

Table 8: Ratio analysis of livestock depredation (2002-2015) Livestock loss Compensation Total of 3 Landscapes 915 Nu. 3,107,550

% of Landscape 1 to all 3 Landscapes 8.35% 9.69% % of Landscape 2 to all 3 Landscapes 69.92% 67.73% % of Landscape 3 to all 3 Landscapes 14.59% 15.44% Total national sites except 3 Landscapes 1,369 Nu. 5,730,400 Grand National Total 2,284 Nu. 8,837,950 % of Landscape 1 to Grand National Total 4.24% 2.87% % of Landscape 2 to Grand National Total 35.08% 32.73% % of Landscape 3 to Grand National Total 6.74% 5.87% % of 3 Landscapes to Grand National Total 46.06% 41.47%

The above data represents 46.06% (915 livestock) of all claims submitted to the government for direct monetary compensation, for livestock killed by tigers, snow leopards, leopards, bears and wild dogs. Nu. 3,107,550 was disbursed as compensation for 915 livestock.

Over the 14-year period, an overall total of 2,284 heads of livestock were reported as casualties from around the country, costing the government Nu. 8,837,950 in disbursed compensation. However, actual incidents may be even higher as under-reporting does occur. During the survey, it was verbally reported that some livestock depredation (particularly in Landscape 2) were not being reported due to perceived shortage of funds in the government.

Table 9: Livestock depredation in Landscape 1 (2002-2015) Dzongkhag Gewog Livestock loss Compensation Haa Bji 2 Nu. 10,500 Sombay 0 0 Sama 19 Nu. 33,750 Sub-total 21 Nu. 44,250 Paro Tsento 15 Nu. 99,000 Total 36 Nu. 143,250

Table 10: Livestock depredation in Landscape 2 (2002-2015) Dzongkhag Gewog Livestock loss Compensation Punakha Kabji 53 Nu. 203,500 Toepisa 5 Nu. 18,000 Sub-total 58 Nu. 221,500 Sarpang Chhudzom/Doban 1 Nu. 4,500 Jigmecholing 0 0 Sub-total 1 Nu. 4,500 Thimphu Chang 0 0 Trongsa Korphu 78 Nu. 301,250 Langthel 18 Nu. 75,000 Nubi 195 Nu. 723,000 Tangsibji 44 Nu. 161,750 Sub-total 335 Nu. 1,261,000 Tsirang Patakla 0 0 Phuentenchu 0 0 Sub-total 0 0 W’phodrang Athang 14 Nu. 42,250 Bjena 35 Nu. 117,500 Daga 0 0 Dangchhu 39 Nu. 141,500 Gase Tsho Wom 1 Nu. 7,500 Gangtey 48 Nu. 100,700 Kazhi 17 Nu. 74,500 Nahi 0 0 Nyisho 11 Nu. 38,250 Phobji 19 Nu. 24,500 Sephu 19 Nu. 107,000 Sub-total 203 Nu. 653,700 Zhemgang Trong 22 Nu. 76,250 Total 619 Nu. 2,216,950

Table 11: Livestock depredation in Landscape 3 (2002-2015) Dzongkhag Gewog Livestock loss Compensation Bumthang Chhume 37 Nu. 96,950 Tang 18 Nu. 47,000 Ura 58 Nu. 97,900 Sub-total 113 Nu. 241,850 Lhuntsi Gangzur 5 Nu. 21,000 Jarey 14 Nu. 39,000 Metsho 28 Nu. 92,000 Sub-total 47 Nu. 152,000 Mongar Tsamang 14 Nu. 25,000 Saleng 3 Nu. 5,250 Sub-total 17 Nu. 30,250 Trongsa Langthel 14 Nu. 58,500 Zhemgang Nangkhor 62 Nu. 245,750 Shingkhar 7 Nu. 19,000 Sub-total 69 Nu. 264,750 Total 260 Nu. 747,350

The highest incidence of livestock depredation was reported from Landscape 2, particularly within JSWNP and adjacent biological corridors. 619 known incidents were reported in Landscape 2, which represents 35.08% of all incidents in the country. In comparison, only 36 incidents were reported in Landscape 1 and 260 in Landscape 3. The survey also recorded the second highest number of cattle lost to depredation in Chendebji under Trongsa Dzongkhag within Landscape 2.

It is not surprising that Landscape 2 reports the highest conflict incidents, and thus poses the greatest challenges to resident human communities. Earlier studies confirmed the habitat integrity, species-richness, and complex human-wildlife dynamics of the unique biological corridor ecosystem that constitutes Royal Manas NP, Jigme Singye Wangchuck NP, Wangchuck Centennial Park, Jigme Dorji NP, and related BCs.

In spite of rich natural prey base, easier predation on free-grazing cattle is a major contributor in this region. Perhaps as a result of high livestock depredation, the majority of survey respondents cited herding as the preferred measure to reduce wildlife-induced loss of livestock.

4.6 Hotspots Mapping for Severity of Damage within the Project Landscapes

Based on the above analysis of crop loss due to natural calamities and wildlife incursions, and livestock depredation, preliminary mapping identified specific hotspots based on the following simple criteria: a) Severity of incidents (acreage, numbers, weights, trends) b) Vulnerability to climate change and wildlife incursions c) Gewog coverage within Project Landscapes

All Gewogs within the 3 Landscapes were ranked out of 5 levels of severity: a) None (White) b) Low (Green) c) Moderate (Yellow) d) High (Blue) e) Very High (Red)

All Gewogs were clustered into equal ranges of common units identified such as acreage, livestock numbers, weights, etc. Analysis was conducted in GIS, and multiple layers of information were processed, to generate the results presented below.

4.6.1 Severity of crop damage by climate-induced factors

Ranking codes:

The severity of damage was categorized by loss of total acreage, and ranged from zero to almost 180 acres, over the period 2011 to 2015. Thus, zero loss constituted no severity (white code), damage between 1 to 50 acres constituted low severity (green code), 51 to 100 acres constituted

moderate severity (yellow code), 101 to 150 acres constituted high severity (blue code), and 151 to 200 acres constituted very high severity (red code).

Result:

Under Very High severity ranking, Bjena Gewog under Wangduephodrang Dzongkhag in Landscape 2 was identified to be the most severely affected by crop damage from climate-induced factors (Map 1). Over the 5-year period, 166 households in Bjena reported losing 179.92 acres of various crops to climate-induced factors. The latter were identified to be heavy rainfall, drought, frost, hailstorms, windstorms, and landslides.

Map 1: Severity of crop damage by climate-induced disasters (2013-2015)

No Gewogs fell under the High severity category; Tsento and Kazhi Gewogs, under Paro and Wangduephodrang Dzongkhags respectively, fell under the Moderate severity category; 13 Gewogs fell under the Low severity category; all other Gewogs in the Project Landscapes reported no damages during the 5-year period.

As per Table 5 above, out of 1,997 acres reported to be adversely affected by climate-induced factors, 17% was reported from the Project Landscapes, representing 33% of all households similarly affected across the country.

The highest incidence of crop damage from natural calamities was reported from Landscape 2, particularly within JSWNP and adjacent biological corridors. Total damages (acres) in Landscape 2 were 61.39% of all damages throughout the 3 Landscapes, and affected almost 60% of households in the project area. In comparison, Landscape 1 lost about 10% and Landscape 3 lost about 8% of total acreage of the project sites. The heaviest loss (179.92 acres) occurred in 2015 in Bjena Gewog under Wangduephodrang Dzongkhag within Landscape 2.

4.6.2 Severity of damage to 4 crops by wildlife incursions a) Damage to paddy by wildlife i) Ranking codes:

The severity of damage to paddy was categorized by loss of total acreage. Loss ranged from zero to 284 acres, over the period 2013 to 2015. Thus, zero loss constituted no severity (white code), damage between 1 to 75 acres constituted low severity (green code), 76 to 151 acres constituted moderate severity (yellow code), 152 to 226 acres constituted high severity (blue code), and 227 to 302 acres constituted very high severity (red code). ii) Result:

Under Very High severity ranking, Korphu Gewog under Trongsa Dzongkhag in Landscape 2 was identified to be the most severely affected by wildlife incursions (Map 2.1), reporting damages to 284 acres of paddy over the 3-year period.

Map 2.1: Severity of damage to Paddy in Acres by wildlife incursions (2013-2015)

This was followed by Kabjisa and Toepisa Gewogs under Punakha Dzongkhag and Athang Gewog under Wangduephodrang Dzongkhag in Landscape 2, as being vulnerable under High severity ranking. 6 Gewogs fell under the moderate severity category, and remaining 20 Gewogs fell under the low severity category. b) Damage to maize by wildlife i) Ranking codes:

The severity of damage to maize was categorized by loss of total acreage. Loss ranged from zero to 323 acres, over the period 2013 to 2015. Thus, zero loss constituted no severity (white code), damage between 1 to 80 acres constituted low severity (green code), 81 to 161 acres constituted moderate severity (yellow code), 162 to 242 acres constituted high severity (blue code), and 243 to 323 acres constituted very high severity (red code). ii) Result:

Under Very High severity ranking, Phuentenchhu and Patakla Gewogs under Tsirang Dzongkhag, and Jigmichhoeling and Doban Gewogs under Sarpang Dzongkhag in Landscape 2 were identified to be the most severely affected by wildlife incursions (Map 2.2) over the 3-year period.

Map 2.2: Severity of damage to Maize in Acres by wildlife incursions (2013-2015)

This was followed by Langthil Gewog under Trongsa Dzongkhag in Landscape 2, and Jaray and Metsho Gewogs under Lhuntsi Dzongkhag in Landscape 3, as being vulnerable under High severity ranking. 6 Gewogs fell under the moderate severity category, 14 Gewogs fell under the low severity category, and only 2 Gewogs did not report any damages. c) Damage to wheat by wildlife i) Ranking codes:

The severity of damage to wheat was categorized by loss of total acreage. Loss ranged from zero to 100 acres, over the period 2013 to 2015. Thus, zero loss constituted no severity (white code), damage between 1 to 25 acres constituted low severity (green code), 26 to 50 acres constituted moderate severity (yellow code), 51 to 75 acres constituted high severity (blue code), and 76 to 100 acres constituted very high severity (red code).

ii) Result:

Under Very High severity ranking, Bji Gewog under Haa Dzongkhag in Landscape 1 was identified to be the most severely affected by wildlife incursions (Map 2.3) over the 3-year period.

Map 2.3: Severity of damage to Wheat in Acres by wildlife incursions (2013-2015)

This was followed by Daga Gewog under Wangduphodrang Dzongkhag in Landscape 2, as being vulnerable under High severity ranking. 3 Gewogs reported moderate severity, 22 Gewogs fell under the low severity category, and only a single Gewog did not report any damages. d) Damage to potato by wildlife i) Ranking codes:

The severity of damage to potato was categorized by loss of total acreage. Loss ranged from zero to 60 acres, over the period 2013 to 2015. Thus, zero loss constituted no severity (white code), damage between 1 to 15 acres constituted low severity (green code), 16 to 30 acres constituted moderate severity (yellow code), 31 to 45 acres constituted high severity (blue code), and 46 to 60 acres constituted very high severity (red code). ii) Result:

Under Very High severity ranking, Phobji Gewog under Wangduephodrang Dzongkhag in Landscape 2 and Tsento Gewog under Paro Dzongkhag in Landscape 1, were identified to be the most severely affected by wildlife incursions (Map 2.4) over the 3-year period.

Map 2.4: Severity of damage to Potato in Acres by wildlife incursions (2013-2015)

No Gewogs fell under the high severity category. Under the moderate severity category, Bji Gewog under Haa Dzongkhag in Landscape 1 and Sephu and Gangte Gewogs under Wangduephodrang Dzongkhags in Landscape 2, fell under moderate severity ranking. 21 Gewogs fell under the low severity category, while no Gewogs reported any damages.

4.6.3 Severity of livestock depredation a) Ranking codes:

The severity of damage was categorized by head counts of livestock lost in a particular Gewog, and ranged from zero to 195 animals, over the period 2002 to 2015. Thus, zero loss constituted no severity (white code), damage between 1 to 50 animals constituted low severity (green code), 51 to 100 animals constituted moderate severity (yellow code), 101 to 150 animals constituted high severity (blue code), and 151 to 200 animals constituted very high severity (red code).

Result:

Under Very High severity ranking, Nubi Gewog under Trongsa Dzongkhag in Landscape 2 reported losing the most livestock (195 animals) to wildlife over the 14-year period (Map 3). No Gewogs fell under the High severity category; 4 Gewogs of Korphu, Nangkhor, Ura and Kabjisa, under Trongsa, Zhemgang, Bumthang and Punakha Dzongkhags respectively, fell under the Moderate severity category; 25 Gewogs fell under the Low severity category; remaining 7 Gewogs in the Project Landscapes reported no damages during the 14-year period.

The above data represents 46.06% (915 livestock) of all claims submitted to the government for direct monetary compensation. The highest incidence of livestock depredation (619 incidents) was reported from Landscape 2, representing 35% of all incidents in Bhutan. In comparison, only

36 incidents were reported in Landscape 1 and 260 in Landscape 3. During the random survey, the second highest loss in 2015 was reported from Chendebji under Trongsa Dzongkhag.

Livestock lost were commonly identified as yaks, cattle, ponies, mules, and sheep; the predators were identified to be the tiger, snow leopard, leopard, wild dog, wolf, and bear.

Map 3: Severity of livestock depredation by head count (2002-2015)

5. Conflict Management Strategy

5.1 Policies, Legislation, Regulations and Programs

The following key documents provide the national policy context for assessing human wildlife conflict, and introducing mitigation interventions. While no single policy and/or legal document clearly outline a comprehensive human wildlife conflict intervention, they all contain the guidelines and parameters within which the government has been intervening. All documents and interventions prioritize the conservation of nature, and any attention and resources devoted to mitigation interventions is subservient to this overarching policy goal.

The Constitution of Bhutan: As the supreme law, it mandates 60% of total area to be forested, enshrines environmental stewardship in citizens, and prioritizes nature conservation over exploitation.

Convention on Biological Diversity, 1992: This guides Bhutan’s obligations and responsibilities under international law, to the protection and enhancement of national biodiversity. Related protocols on bio-prospecting and the Convention on International Trade in Endangered Species prohibit any unregulated cross-border movement of wildlife and derivatives.

Bhutan, 2020: It outlines the country’s development goals, objectives and targets with a twenty- year perspective to maximize GNH. It enunciates Bhutan’s development pursuits to be carried out within the limits of environmental sustainability and without impairing the ecological productivity and natural diversity, providing the policy context for sustainable development - implicitly encompassing a path that is resilient to and mitigates climate change.

Forest and Nature Conservation Act, 1995 and Forest and Nature Conservation Rules and Regulations, 2006: The Act and Rules govern all forest management and nature conservation activities, including utilization and protection. It is silent on human-wildlife conflict management, except to prioritise conservation. However, the Rules permit killing of non-endangered problem species on affected farmlands.

National Human Wildlife Conflict Management Strategy, 2008: This is the only explicit formal instrument to address human wildlife conflict, by recognizing conflict and possible mitigation interventions. It advocates building tolerance for wildlife incursions, and seeks to provide temporary relief. Although considered a living document, it fails to address the causes of conflict nor does it promote sustainable principles of intervention.

National Forest Policy, 2012: This serves as the guiding policy framework for forest management and nature conservation. It recognizes the important role of sustainable forest management in CC mitigation and adaptation. The policy adopts an integrated landscape-level approach to sustainable forest management.

Bhutan Poverty Assessment, 2014: This identifies that crop losses due to pest and diseases, and wild life and natural disasters like storms, earthquake and drought make the community vulnerable to poverty. The principal risk in agriculture across all communities was identified as wildlife attacking both food and cash crops. The community believes that increasing conflict is as a result of human encroachment due to deforestation, construction of roads, erecting of

electricity poles and other developmental activities. Farmers have no access to compensation for the damage given the challenges in assessing the extent of the damage caused and in absence of crop insurance.

Intended Nationally Determined Contributions (INDC), 2015: Under this important international commitment pledged at the COP21 in Paris in December 2015, Bhutan reconfirmed its target to remain carbon neutral. Amongst others, priority adaptations include:  climate resilient agriculture to contribute towards achieving food and nutrition security.  sustainable forest management and conservation of biodiversity to ensure sustained environmental services  resilience to climate change induced hazards  climate resilient livestock farming practices to contribute towards poverty alleviation and self-sufficiency

5.2 Review of best practices

Managing conflict between humans and wildlife probably began with sedentary agricultural civilisations. They are prevalent throughout the world today, and only the issues and interventions vary by environment, culture, social perception and affluence of societies. As a mitigation tool for human wildlife conflict, compensation programs for livestock or crop losses -- either direct monetary compensation or insurance schemes -- can work best as part of a toolbox, along with equally important efforts like reducing mortality of natural prey, reducing illegal hunting, increasing habitat protection, and investing in educational programs.

Thus, compensation programs for wildlife damage to human endeavors are generally considered a successful, ‘humane and socially acceptable’ approach to increase human tolerance to wildlife (Wagner et al, 1997; Allen & McCarthy, 2001; Conover, 2002; Yoder, 2002). Given the cultural barriers in Bhutan against scientific culling as a management tool, compensation schemes are appropriate, although several problems exist that are similar to what Wagner et al (1997) observed globally: compensation’s failure to solve the actual problem, complicated claims procedures, inadequate levels of compensation, prevention of more innovative and enduring solutions, and even the risk of attracting immigrants into the concerned protected areas (Saberwal et al, 1994; Studsord & Wegge, 1995; Maikhuri et al, 2001).

Four different approaches are discussed below.

5.2.1 Monetary compensation in South Asia

There are many livestock compensation initiatives around the world, with varying degrees of success and nuanced approaches to suit local circumstances. The most common intervention has been the direct monetary compensation scheme, popular when funds are available from either government or private donors, and unpopular once the cash reserves are depleted. Monetary compensation has been tried in Bhutan, Nepal, India, and Pakistan, where it has seen limited success due to depletion of funds, inability of governments to sustain funding, moral hazards and low rates of compensation for often high-value livestock lost to predators. Ownership patterns differ across the region. Some schemes are administered by the government (as in the case of Bhutan), managed through local member-based entities (as in Bhutan, India, Pakistan and Nepal),

or managed through community-level collaborative micro-finance institutions (as in Nepal). In the absence of other compensation instruments, they are an important incentive to protect retaliatory killing of endangered predators such as the tiger and snow leopard.

5.2.2 Monetary compensation in the western USA

On the other hand, monetary compensation has been more effective in the developed world, attested by examples from the United States and Sweden. The wolf’s recovery in the Greater Yellowstone region of western USA is due largely to cash compensation for livestock kills to ranchers. Private initiatives such as the Defenders of Wildlife established in 1987, paid out more than $1.3 million for livestock depredation by wolves and helped pave the way for the wolf’s re- introduction as an iconic predator. In 2010, the program was transitioned to other western states and indigenous tribes, which began to offer their own compensation under the 2009 Omnibus Public Land Management Act. In a sign of the program’s appeal to recipient stakeholders, compensation levels can be as high as seven times the market value for livestock killed by wolves, and almost four times the market value for livestock killed by grizzly bears.

5.2.3 Pre-emptive monetary compensation in Sweden

In a different example of monetary compensation in the developed world, the government of Sweden pays its Sami herders (of reindeer) “assumed damages” for the number of natural predators observed in a specific locality. Predators include the wolverine, lynx, brown bear and golden eagle, and even their dens or nests. Almost similar to indexed crop insurance schemes that are more viable for large pastoral and/or agri-business schemes (Greatrex et al, 2015), Sweden’s plan makes payments (as high as $30,000 for each predator family found) directly tied to achievement of its conservation goals, rather than trying to determine the impacts of reimbursing for livestock losses. The basic premise for Sweden’s approach is that farmers and herders can receive more money if carnivore numbers are higher, and will be thus motivated to take more measures to protect their livestock with fencing, guard dogs, or other methods.

5.2.4 Innovation in livestock insurance in Pakistan

In what may be of direct relevance to Bhutan, a snow leopard insurance scheme founded in northern Pakistan in 1998, pioneered an effective and sustainable mechanism to benefit snow leopards, local herders, and private tourism. The founder, social scientist Shafqat Hussain, brought together local herders in Pakistan’s Baltistan region and a private tourism company to launch an insurance scheme that would compensate livestock losses partly out of tourism revenues generated from snow leopard tourism (Handerwerk, 2013).

In this initiative, the amount of compensation depends on what people agree to pay within each village’s unique system. Premiums can be as high as 2% of a goat’s value, of which the herder pays half a percent, and the rest is paid from a common fund endowed by local tourism revenues. Members are responsible for the insurance scheme’s verification, disbursement of funds, and collection of premiums, with minimum room for fraud and other undesirable leakages. 5,000 people across ten villages have been participating in this fully locally-owned scheme, which has ensured the survival of a growing snow leopard population.

In the literature, insurance for crops against climate-induced factors was found to be predominantly relevant to large agricultural systems and pastoral units, beyond the scale applicable to Bhutan. While crops insurance is presently non-existent in Bhutan, the indexed crop insurance schemes being adopted for large pastoral and/or agri-business schemes in India, Central Asia, and Africa (Greatrex et al, 2015; Parida, 2016) could be adapted over time to suit Bhutan’s geographical conditions and evolving socio-economic situations. Certainly, the rapid shift to high-technology applications for ‘indexing’ private insurance can be more efficient than conventional boots-on-the-ground approaches, but the technological upgrade will require supporting infrastructure not presently available. Closer to Bhutan, recent developments in India revamping micro-insurance interventions through the government’s Pradhan Mantri Fasal Bima Yojana initiatives (Parida, 2016) is worth monitoring for possible replication.

5.3 Interventions and Adaptation

Throughout most of the surveyed areas, government interventions ongoing elsewhere have yet to be introduced. These include awareness creation, improved agricultural practices, land swapping, electric fencing, and livestock and crop protection and compensation. At the level of households, Chewogs and Gewogs, it could be said that the single major strategy being observed for protection of livelihoods has been a defensive one.

In 35 Chewogs, farmers reported guarding their crops throughout the season. Only one Chewog reported not guarding crops. Throughout, both female and male farmers were involved in guarding crops (Figure 29).

Figure 29: Guarding of Crops by Gender

50.00% 50.00%

0.00% 20.00% 40.00% 60.00% 80.00% 100.00% Male Female

Time incurred on guarding crops was not established, but it may not differ from the national averages between nights and days, recorded in 2014 below.

In the past 10 years, various interventions and techniques have been piloted throughout the country to help farmers protect their crops. These include fencing (simple and electric), low cost energizers, electric and manual light and sound alarms, experimental use of bay and catch-hunting dogs (Maetz et al, 2012), and most recently, wide-scale fabricated electric fencing following its legalization in 2013 (NPPC, 2015).

Figure 30: Average crop guarding by days & nights in 2014 (DoA, 2014)

200 180 160 140 120 100 80 60 40 20 0

Avg no. of Days spent Avg no. of Nights spent

On their own, respondents professed various measures to reduce wildlife-induced crop loss.

Figure 31: Preferred measures to reduce wildlife induced crop loss

Solar fencing 1.41 Wire mesh fencing 0.50 Retaliatory killing ) 4.27 Monetary/other compensation 21.96 Insurance 9.20 Improve breed/technlogy 7.29 Guarding 20.00 Fencing 11.21 Electric fencing 18.44 Culling of problem species 5.43 Bio-pesticides application 0.30 0.00 5.00 10.00 15.00 20.00 25.00

Although a majority of farmers (21.96%) preferred monetary and other direct compensation to reduce wildlife induced crop losses, 20% preferred guarding crops and 18.44% preferred electric fencing. Another 11.21% preferred conventional fencing, while 9.2% preferred insurance. Less than 5% preferred culling of problem species and retaliatory killing. A minority (1%) expressed preference for bio-pesticide applications, and wire-mesh and solar fencing.

In spite of the success of electric fencing elsewhere in the country, it received little attention and interest in the areas surveyed, as those communities have yet to fully participate in such initiatives. Communities were aware of electric fencing, and were also aware that local inputs were required, such as purchase of materials and labour contributions. Some respondents appeared to be discouraged by the perceived high costs of installing electric fencing, and preferred more basic crop protection interventions like guarding and conventional fencing. Responses were also wildlife-species specific: for instance, farmers in southern Bhutan indicated that electric fencing

was not adequate against marauding elephants, calling for more innovation and adaptation. However, in northern regions like Bumthang, electric fencing has proven successful on smaller species like deer and wild pig.

At the Dzongkhag-wide level, responses vary (Figure 32). In Lhuntse, most farmers first preferred electric fencing, followed by monetary compensation and guarding as measures towards reducing wildlife induced crop losses. In Mongar, a majority preferred guarding crops, followed by electric fencing, insurance, and monetary compensation. In Wangduephodrang, farmers equally preferred electric fencing, guarding and monetary compensation. In Punakha, farmers equally preferred culling of problem species, fencing, insurances, monetary compensation, retaliatory killing and wire mesh fencing. Most farmers in Paro preferred electric fencing, followed by monetary compensation. In Trongsa the majority preferred fencing, guarding and monetary compensation. In Zhemgang, fencing and guarding were closely followed by insurance, and improved breed technology. In Sarpang, farmers only preferred guarding, monetary compensation, improved breed technology and fencing as a measure. Only farmers from Bumthang preferred solar fencing, those in Punakha preferred wire mesh fencing, and farmers from Bumthang chose bio-pesticides as preferred methods.

Figure 32: Preferred measures to reduce wildlife induced crop losses

160 140 120 100 80 60 40 20

Number Farmers of Number 0 Wangd Punakh Bumtha Zhemga Lhuntse Mongar Paro Trongsa Sarpang Haa ue a ng ng Bio-pesticides application 0 0 0 0 0 6 0 0 0 0 Culling of problem species 3 9 7 10 3 24 24 0 0 28 Electric fencing 39 29 152 0 21 24 17 29 0 56 Fencing 0 12 46 10 0 59 29 44 9 14 Guarding 20 38 152 0 0 63 29 44 24 28 Improve breed/technlogy 0 0 0 0 0 11 22 32 24 56 Insurance 0 19 0 10 0 39 22 37 0 56 Monetary/other compensation 31 19 152 10 11 63 29 42 24 56 Retaliatory killing 0 11 18 10 3 5 24 0 0 14 Wire mesh fencing 0 0 0 10 0 0 0 0 0 0 Solar fencing 0 0 0 0 0 28 0 0 0 0

In order to reduce wildlife-induced livestock losses, the majority of farmers (23.21%) preferred herding, clearly indicating that most livestock depredation occurred during un-herded grazing in the forests. 23% preferred monetary and other direct compensation and improved breeds. 17.39% chose stall-feeding. Less than 10% preferred insurance, while 4.72% chose culling of problem species.

Figure 33: Preferred measures to reduce wildlife induced livestock losses

Stall feeding 17.39%

Monetary/other compensation 22.69%

Insurance 9.37%

Improve breed/technlogy 22.62%

Herding 23.21%

Culling of problem species 4.72%

0.00% 5.00% 10.00% 15.00% 20.00% 25.00%

5.4 Community and Institutional Capacities

The survey revealed that a large number of respondents (67.9%) were aware of Forest and Nature Conservation Rules of 2006. Only 32.1% were not aware of regulations concerning human relations with their natural environment (Figure 34). Gender wise, more females (59.70%) were aware of the rules.

Figure 34: Awareness of F&NC Rules 2006

Awareness of Forest & NC Rules 2006

67.90% 32.10%

0.00% 20.00% 40.00% 60.00% 80.00% 100.00% Aware Unaware

34.32% of farmers were aware of commercial insurance, such as household level insurance. 33.73% reported being able to afford some form of scheme; 31.95% were willing to join.

Figure 35: Full commercial rate household level insurance

31.95%34.32%

33.73%

Level of Awareness Affordability Willingness to join

Only 11.99% of farmers were aware of any government supported or subsidized household level insurance. Of this, 43.78% reported their affordability, while 44.23% were willing to join.

Figure 36: Government subsidized household level insurance

11.99%

44.23%

43.78%

Level of awareness Affordability Willingness to join

28.73% were aware of community level insurance schemes. 44.20% reported their affordability, while 27.07% were willing to join.

Figure 37: Gewog/community level insurance

27.07% 28.73%

44.20%

Level of Awareness Affordability Willingness to join

In spite of the above feedback, there was little support for either government subsidized or commercial insurance schemes as a sustainable form of protection for crops and livestock. Throughout the survey, farmers showed far greater interest in direct compensation from the government for crop damage and livestock depredation. Respondents demonstrated high levels of awareness of these compensation schemes, but were not aware of the unsustainability of such schemes caused by limited government funds.

Presently, there are no active crop insurance schemes throughout Bhutan. Some livestock insurance schemes have been launched through 26 insurance-cum-compensation schemes funded by the government as GECCs. 12 GECCs are located within Landscapes 2 and 3 (Table 12). Royal Insurance Corporation of Bhutan Ltd. has since 2012 been offering cattle insurance policies, with minimum success. No insurance schemes were encountered throughout the survey, and is reflected in respondents’ feedback (Figure 38).

Figure 38: Availability of current crop and livestock protection schemes

Does the community have any household-level 100.00% 0.00% crops insurance scheme? Does the community have any household-level 88.24% 11.76% livestock insurance scheme? Does the community have any livestock 82.35% 5.88% 11.76% depredation compensation scheme… Does the community have any community-level 94.40% 5.60%0.00% livestock insurance? Does the community have any community-level 88.24% 11.76% crops insurance? Does the community have any electric fencing? 17.65% 76.47% 5.88% Does community have any community-level crop 58.82% 29.41% 11.76% protection scheme? 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% None Few Most

The lack of interest to insure crops and livestock, particularly the latter, can be attributed to the availability of direct cash compensation for loss of livestock caused by tigers, snow/leopards, bears and wild dogs. However, when farmers were informed of the principles, mechanisms and benefits of market-based insurance schemes, similar to the rural household initiatives fully privatized from 2013, an equal number of respondents showed interest and support for community-level insurance platforms for their livestock and crops (62.5% and 58.83%, respectively) (Figure 39).

Figure 39: Levels of reluctance or interest for crops and livestock insurance

Is the community reluctant to establish 5.88% 35.29% 58.82% community-level livestock insurance scheme?

Is the community reluctant to establish 11.76% 29.41% 58.82% community level crops insurance scheme?

Is the community interested to establish 37.50% 56.25% 6.25% community-level livestock insurance scheme?

Is the community interested to establish 41.18% 41.18% 17.65% community-level crops insurance scheme?

0.00% 20.00% 40.00% 60.00% 80.00% 100.00% None Few Most

6. Proposed Interventions 6.1 Prevailing Schemes for Crop and Livestock Compensation

Since 2008, and even earlier for direct compensation, the government has actively promoted various initiatives to help farmers protect their crops and livestock, as a direct way of ensuring survival of Bhutan’s top ecological predators and other threatened wildlife species. This was in spite of budget constraints, conflicting priorities, and often skeptical stakeholders. Some of the major initiatives are briefly reviewed below for effectiveness and long-term viability.

Table 12: Selected human-wildlife conflict interventions since 2000

Instrument & year Benefits Shortcomings Remarks --Science based mgmt. --Lack of capacity Discontinued; Problem species --Controlled culling --Long-term research inconclusive results; management (wild -- Ecological balance horizon wild pigs in pig control), 2000 --Govt. outreach / --Expensive Thimphu site proven public relations --Religious sentiments feral --Immediate payout --Tedious claims process Uncertain future. --Accurate records --High risk of fraud Monetary Due to lack of funds, --Happy public --Low value of compensation, 2002 claims were unpaid --Can reduce retaliatory compensation (10%) in 2015 killing --Unsustainable Alarms (sound & --Effective (short-term) --Wildlife adaptation lights, trip wire), --Local technology --High-tech for local use Uncertain status 2004 --Inexpensive --Low innovation --Effective --Expensive materials --Local fabrication --Skilled installation Ongoing; requires Electric fencing, --Cheap grid power --Displaces problem rigorous monitoring 2008 --Reduced guarding --Have to meet wildlife & innovation --Food security adaptation --Local governance --Micro funds (Nu. Gewog --Participatory 300,000-500,000) 26 active GECCs, 17 Environment conservation --Low returns & lower more planned in Conservation --Peer pressure compensation 2016-17 Committee, 2009 --Seed funds required --Diversion of funds --Pioneering self-help --Very low rate of Ensure GECC intervention compensation Community-based oversight to avoid --Reduced donor --Beyond regulatory crops & livestock regulatory concern; dependence oversight (illegal) insurance, 2009 Potential distribution --Community/peer --Risk of mis-mgmt (through GECCs) channel for pressure to participate --May insure only high- commercial insurer/s value breeds --Legal mechanism --Very low rate of Household-level --Sustainable (with “law compensation Could collaborate private cattle of large numbers”) --High transaction costs with GECCs to insurance, revived --Prompt payouts -Excludes ordinary cattle efficiently insure 2012 --Efficient, market- --Minimum profits, loss crops & livestock based business in 2015

From the above, the most relevant for discussion are direct monetary compensation, electric fencing, community-based insurance through GECCs, and private cattle insurance.

6.2 Monetary compensation for livestock depredation

Although unsustainable, it is still the most effective and visible prevailing compensation scheme to protect threatened wildlife species (ie, tiger, snow leopard, bear and wild dog). Funded primarily by private external donors, the scheme was highly popular as a minimum compensation was assured for verified livestock kills by the above wild predators. In the absence of any market- value compensation for losses, the minimum amounts offered by the government served important conservation goals.

From 2002 to date, the government disbursed Nu. 8,711,150 in direct cash compensation for 2,242 incidents of livestock depredation. All field verification is conducted by forestry and parks staff, before payments are issued by the central government. External funds have often been supplemented by government resources.

In 2015, due to the lack of funds, no payments were made for claims submitted.

6.3 Electric fencing

Following several years of experimentation with alarm systems and conventional and solar fencing, the government has launched fully electrified fencing as a popular, cost-effective crop protection system. Both conservationists and agriculturalists have supported the initiative, which has proven to reduce active guarding and improve food security based on a field review of interventions in 6 Gewogs in southern and central Bhutan (WCD, 2013).

Figure 40: Review of Electric Fencing impact in selected sites, 2013

Gewogs Singhe Lhamoi Lancghen Norbugang Tashi Ura Overall Zingkha phug choling

Impact variables N=15 N=49 N=13 N=17 N=76 N=4 N=174 Increased yield reported, % 100 75 100 88 1 75 73 Quantity increased (kg) 8,015 28,692 5,803 11,410 450 4,250 9,770 Mean increase (kg) 534 755 (586) 967 (484) 761 (671) 450 (5.9) 1,417 976 Total amt. saved, Nu. 280,525 1,004,220 104,454 399,350 15,750 191,250 332,592 Total amt. saved/hh 18,702 26,425 17,409 26,623 15,750 47,813 25,454 (20,494) (8,705) (23,491) (207) Amt. saved/hh, % per capita GDP 16 22 14 22 13 39 21 Reduced guarding reported, % 100 98 100 100 0 0 66 Total nights reduced 1,530 4,645 4,745 1,650 0 0 12,570 Mean no of nights reduced/hh 102 98 365 97 0 0 110 Total amt. saved/hh (Nu) 10,200 9,800 36,500 9,700 0 0 11,033 Total amt. saved (Nu) 153,000 464,500 474,500 165,000 0 0 209,500 WCD investment on fencing, Nu. 2,900,000 651,000 1,691,210 0 994,308 0 4,545,308

Source: Assessment Impact (WCD-DoFPS & UNDP, 2013)

Through adaptation and local fabrication, the government has made available EF wiring and accessories for Nu. 35,000 per kilometer. A total of 1,236 kilometers of EF has been installed in all 20 Dzongkhags for Nu. 92.72 million (NPPC, 2016). 6,638 beneficiaries provided 60% of the costs (as labor, poles and transportation), while the government subsidized the balance 40% for EF materials and accessories. As a result, 4,346 acres of dry land and 1,679 acres of wet land have been fenced, although crop yield and savings are yet to be quantified (Table 13).

Table 13: Electric fencing, 2011-2015

Dzongkhag Length, Km. Beneficiaries Area Dryland Wetland Total Acre Bumthang 103.766 562 146.1 0 146.1 Chukha 25.12 237 340 206.2 546.2 Dagana 84 282 103 205.8 308.8 Gasa 24.78 20 12.61 0 12.61 Haa 42.7775 394 322.6 322.6 Lhuentse 41.13 320 178.45 53.34 231.79 Mongar 46.04 293 120.12 5 125.12 Paro 17.6 60 64 70 134 Pema Gatshel 39.55 307 575 Punakha 18.5 52 37.92 183.75 221.67 S'jongkhar 80.29 643 216 270 486 Samtse 24.5 215 160 32 192 Sarpang 206.956 1267 593 Trashigang 115.5 470 902.1 214.92 1170.32 Trashiyangtse 70.3 625 1262.2 108.1 1801.7 Thimphu 66.11 283 231.71 0 231.71 Trongsa 108.441 40 61.16 60.2 121.36 Tsirang 40.55 7 20 W'phodang 41.7 373 24.17 132.85 157.01 Zhemgang 38.6 188 164.2 137 301.2 Total 1,236 6,638 4,346 1,679 7,698 Source: NPPC, 2016

The government has invested significant effort and resources in this initiative, pioneering and legalizing this new technology. Valuable technical assistance is provided through training and monitoring. However, as a highly specialized intervention, the learning curve may be steep as rural communities have yet to fully master the technology. For instance, improper installation, poor maintenance (due to its high maintenance) and high costs often lead to breakdowns and failure, compared to lower-maintenance conventional wire fencing. Moreover, while fencing may solve a problem in one location, it may divert wildlife to neighboring non-fenced agricultural fields, often with higher intensity of incursions. Thus, it could end up exacerbating, rather than removing, the problem.

6.4 Community-based insurance through Gewog Environment Conservation Committees

The establishment of GECCs from 2009 helped to transfer responsibilities to resolve human- wildlife conflicts from the center to local governments. Initiated voluntarily by communities and modestly funded, primarily through a one-time grant from the Bhutan Trust Fund for Environmental Conservation, these grassroots level bodies have demonstrated local ownership of development and conservation issues. To date, 26 GECCs have been established throughout rural

Bhutan, especially in human-wildlife conflict regions. Many of them were capitalized with only Nu. 200,000 each, which has since been increased to Nu. 500,000.

Table 14.1: Existing GECCs, initial capitalization, location

Gewog Dzongkhag Nu. Landscape 1. Tashicholing Samtse 200,000 n/a 2. Khatoe Gasa 200,000 n/a 3. Khamoe Gasa n/a 4. Naro Thimphu n/a 5. Lunana Gasa 200,000 n/a 6. Lingshi Thimphu n/a 7. Tareythang 200,000 n/a 8. Norbugang Samdrup Jongkhar 200,000 n/a 9. Phangkhar Zhemgang 200,000 n/a 10. Lhamoizingkha Dagana 200,000 n/a 11. Chimung Pemagatshel 200,000 n/a 12. Langchenphug Samdrup Jongkhar 200,000 n/a 13. Dhur Chokor Bumthang 200,000 n/a 14. Bardo Zhemgang n/a 15. Bjena Wangduephodrang 200,000 2 16. Dangchu Wangduephodrang 200,000 2 17. Langthel Trongsa 2 18. Nubi Trongsa 200,000 2 19. Korphu Trongsa 200,000 2 20. Tangsibji Trongsa 2 21. Tsamang Mongar 200,000 3 22. Nangkhor Zhemgang 3 23. Shingkhar Zhemgang 3 24. Ura Bumthang 3 25. Jarey Lhuentse 3 26. Metsheo Lhuentse 3

Source: WCD-DoFPS, 2016

Table 14.2: GECCs planned for 2016-2017, budget, location

Gewog Dzongkhag Landscape 1. Tsento Paro 1 2. Chumey Bumthang 3 3. Tading Samtse n/a 4. Phuntshopelri Samtse n/a 5. Laya Gasa n/a 6. Goenshari Punakha n/a 7. Samtenling Sarpang n/a 8. Lingshi Gasa n/a 9. Khamoe Gasa n/a 10. Tsaling Mongar n/a 11. Dekiling Samtse n/a 12. Shompangkha Sarpang n/a 13. Singhe Sarpang n/a 14. Karmaling Dagana n/a 15. Goshing Zhemgang n/a 16. Ngala Zhemgang n/a 17. Bjoka Zhemgang n/a

Source: WCD-DoFPS, 2016

GECCs encourage community members to insure crops and livestock, particularly high-value animals in the higher altitude regions, for compensation levels determined locally. Many of them have effectively replaced central government’s role in compensating crop damage and livestock depredation. Thus, empowered with both development and local governance mandates, GECCs have potential for human-wildlife conflict management, where even central government and external donors had limited success. By promoting accountability and effectiveness, they can play

a stronger role to receive government subsidies and channel private insurance initiatives, which would otherwise be limited to uncertain household-level interest. GECCs in the project area will need to be closely partnered for proposed interventions, as lack of oversight (by the government or donors) may have contributed to perceived inactivity or even ineffectiveness in a few sites.

6.5 Private Cattle Insurance

To date only Royal Insurance Corporation of Bhutan (RICB), a publicly traded company, has been engaged in commercial insurance in rural Bhutan. In 2013, RICB took over rural housing insurance from the government’s subsidized initiatives, and quickly turned around service delivery (such as a guaranteed two-week payout window), new products and profitability. Its cattle insurance policy was revamped in 2012, and aggressively launched in rural Bhutan.

Table 15: Cattle insurance at RICB (revised 20% premium of 70% claim of sum insured) Year Policies Premium, Nu. Claims Payouts, Nu. Profit/Loss, Nu. 2012 450 1,664,983 88 1,600,052 64,931 2013 198 812,916 38 775,035 37,881 2014 267 1,464,900 44 818,650 646,250 2015 134 618,731 50 1,108,275 (489,544) Source: RICB, 2016(a)

RICB has experienced difficulty in penetrating the rural market. Farmers are less interested in high premiums and below-market value compensation for high-value livestock. High transaction costs also limit profit margins and further expansion.

7. Pilot Project Interventions

Recognizing the tremendous progress Bhutan has achieved since the advent of modernization in the 1950s, by charting a globally admired path of sustainable development, and attempting to balance human development with environmental conservation, it may be timely to embark on a paradigm shift to address emerging challenges of climate change and implications for national development. With strong foundations for biodiversity conservation secured in the past five decades, Bhutan has to look further into the future to adapt and demonstrate resilience, against the onslaught of global externalities and a unique position between the world’s two emerging social and economic super powers. For Bhutan, the present century will be very much a struggle for adaptation and survival against climate change, and it will be compelled to pioneer new approaches to environmental management, as it did successfully for biodiversity conservation long before it became popular.

It is proposed under this planned project to update the national HWC management strategy and pilot two pioneering interventions aimed at balancing human needs and environmental concerns in the most sustainable way possible. Both interventions are self-help initiatives, that will require upfront investments. The process will require updating and retrofitting the national strategy for human wildlife conflict management, and establishing an efficient PPP to insure rural livelihoods against climate and wildlife induced disasters. Successful project components can then be replicated throughout Bhutan.

Throughout the region, the use of micro-finance instruments in agriculture, wildlife conservation and climate change, has yet to be fully explored. Kashyap et al (2006) cited several problems for private insurers to supply crop insurance to low-income consumers, including administrative costs, fraud, adverse selection and moral hazard. However, interest has recently grown to adapt innovation and technology to old principles, and India (among others) is aggressively pursuing public sector micro-insurance for rural agriculture (Parida, 2016).

In Bhutan, an opportunity exists to create a win-win-win situation for farmers, entrepreneurs and natural resource managers, who have for decades grappled with HWC in rural areas. Existing private insurers in the country have indicated some interest to explore viability of providing livestock and crop insurance. During this study it was suggested (Penjore, 2016), to also explore the potential role of micro-insurance to support such rural-based needs. Regulatory approval for deposit-taking micro-insurance is pending a feasibility study, and will be encouraged to formalize and benefit market-based insurance requirements outside the prevailing insurance industry. At the least, micro-insurance agents can perhaps offer a more cost-effective alternative, in terms of premium pricing and specialized services, than prevailing mainstream industry entities like RICB and Bhutan Insurance Ltd. (BIL).

7.1 Human Wildlife Conflict Management Strategy

In 2008, the government launched Bhutan’s first-ever HWC management strategy. In spite of its strategic intentions and clear policy targets for species-specific interventions and cross-cutting themes, developed by an impressive team of international and local experts with full government support, its full potential was hindered by institutional and resource constraints. The strategy was implemented actively in the field and center, and a rapid impact assessment was conducted in 2013. Since then, the government has maintained the strategy as a living document.

While the strategy of 2008 served as a pioneering interdisciplinary approach to address all issues and recognized the human dimensions of conflict, it lacks the analytical and operational capability to quickly respond to issues and threats, translate vision into policy and operations, and guide development planning at the center and on the ground. Thus, like current approaches throughout other countries, the strategy seems to focus only on the symptoms (and not causes) of conflict, lacks strategic direction, and fail to measure progress and impact.

Today, HWCs are emerging not only from rural subsistence-level communities, but increasingly from less conventional arenas such as growing urbanization and related aspirations, the covert multi-billion-dollar global wildlife trade, and the fluid dynamics of an electorally-empowered political economy.

With the government mid-way into the 11th Five Year Plan (11FYP), it may be timely to evaluate the ongoing HWC strategy of 2008 in order to update the national strategy. This will help to attract new resources for the 12th FYP, integrate new approaches and practices, build on the positive experiences whilst addressing the existing deficiencies, and help prepare for the uncertainties of democratic transitions (with an eye on political elections in 2018).

In the interest of time and for want of better local alternatives, the government could consider adapting and adopting a more interactive tool such as the SAFE Systems approach to human wildlife conflict management, pioneered by WWF in various tiger range countries. The SAFE approach was developed as a response to the inability of “current approaches to HWC globally…to tackle the dynamic, emotive and complex challenge of minimizing and managing HWC” (Brooks, 2015).

WWF is already assisting the government to pilot the SAFE approach through the National Plant Protection Center. Specialized training and fieldwork was ongoing at the time of this study, with results to be available in July 2016. Fieldwork covered 10 villages in 7 Gewogs under 4 Dzongkhags; at least 3 villages under Bjena and Sephu Gewogs of Wangduephodrang Dzongkhag were covered, which falls under the Project Landscape 2. As per the protocols and methodology adapted for Bhutan (Annex 6), a SAFE system can offer “a single long term goal--to make the area safer, a baseline for safety monitored over time, application to any conflict context, accounts for the drivers of conflict, and aligns HWC management decisions with existing development plans and processes that contribute to economic, human, and environmental goals.”

As a highly interactive and quantitative tool, in essence the SAFE Baseline (Figure 35) aims to achieve the highest possible score for the criteria met for safety at a particular site.

Figure 41: SAFE Baseline matrix (Brooks, 2015)

Safe Person 100% 50% 75% 50% Monitoring 25% Safe Assets 75% 0% 75%

Safe Safe Habitat Wildlife 100% 67%

7.2 Private Livestock Insurance

In Bhutan, one of the biggest threats to endangered apex predators, such as the tiger, snow leopard and wild dog, is retaliatory killing by livestock owners who are affected by depredation. The most effective, efficient and sustainable form of protecting the valuable livestock of rural Bhutan, against any form of risk -- induced by wildlife, climate change or accident -- is through private commercial insurance. Over five decades, Bhutan has learned enough lessons to realize that any other method will be inefficient, unsustainable and eventually of no benefit, especially to those who funded such short-sighted interventions.

As an initiative to compensate for livestock depredation losses, and procure public support for conservation of these endangered species, the government has endowed GECCs in known hotspots to create a basic form of livestock and crops insurance. However, the scheme is constrained by modest level of contributions to these funds and extremely low payouts during livestock losses.

Scope

A PPP-based model of collaboration can help to create a market-based insurance scheme, that will (i) attract participation of livestock owners, (ii) guarantee near market-value payment for livestock losses, and (iii) ensure a sustainable business model to relieve the government of unsustainable financial handouts.

To date, only RICB has tried to insure cattle in rural Bhutan through a limited policy that excludes predation by wildlife (RICBL, 2016(a); Annex 8). The experience with private insurance has been limited by rural stakeholders accustomed to handouts from the government, such as direct monetary compensation for livestock depredation caused by globally endangered predators. However, private insurance can offer much more than a handout, as the market value compensation for lost livestock can help affected owners sustain their livelihoods.

A primary constraint to private insurance has been unfamiliarity with market-based economic instruments, and ensuing lack of trust in communities slowly emerging from a traditional barter economy. This can be addressed by requiring private insurers to structure operations through the local GECC, which can serve in the manner of successful micro-finance models as product facilitator, financial guarantor and dispute arbitrator between member households and private insurers.

Financing modality

The project could capitalise 10 Gewogs in the Project Landscapes. These will be the 5 Gewogs identified under Very High and Moderate severity ranking (i.e., Nubi, Korphu, Nangkhor, Ura and Kabjisa) and the next highest 5 from Low severity ranking (i.e., Tangsibji, Bjena, Dangchhu, Chhume and Gangtey). The latter 5 Gewogs are selected based on high livestock loss (above 35 heads) even though they may have been clubbed under Low severity.

For every domestic animal insured under this scheme, participating members will pay 30 basis points of a “reasonably-estimated” annual premium of 1%, while the government will pay another 30 basis points, and the project will pay the balance 40 basis points. In order to subsidize the project’s 40% contribution to annual premiums, and to create a reserve fund with any surplus to sustain the scheme after the project cycle, the project will set aside approximately $225,000 to capitalize each Gewog fund with Nu. 1,500,000 ($22,500).

The project can engage a private insurer in Bhutan, to jointly implement this pilot scheme. The insurer could adopt a ‘vehicle fleet’ business strategy to package, discount and retain large- volume business, since profitability is an essential requirement based on ‘the law of large numbers.’ The pricing of annual premiums has to be modest enough to attract rural livestock owners who desire (and must receive) near-market value compensation as payouts, yet remain profitable for the business model to be sustainable. The pilot scheme will finance only insurance claims, and for insurance to succeed, direct monetary compensation for livestock depredation has to be discontinued in the Project Landscapes.

Proper incentivisation is critical for all parties -- the insurer, insured and GECC. The most important factor is to retain the interest of the private insurer, as the scheme’s central thesis of sustainability cannot succeed without the insurer. To retain a commercial interest, the insurer may encourage all livestock owners in the Gewog to insure all livestock, in return for significant group discounts and extended policies for property liability cover. With constant support and mentoring by the government, private insurers can be encouraged to remain engaged in this pilot scheme in spite of modest profit margins, as part of their corporate social responsibility.

The insurer has to visit each site to market the benefits of insuring important livestock not only against depredation by wildlife, but also other casualties. Communities have to be educated on insurance terms, conditions and benefits, and near market-value compensation for any claims.

The latter will attract strong interest; as present compensation levels are only a tiny fraction of their livestock’s market value.

Exit strategy

At project conclusion, the insurance scheme and reserve fund will be administered directly by the GECC, chaired by the local Gup and joined by district sector heads and community representatives. The most critical component of the pilot scheme is for the GECC to negotiate a phased discount on annual premiums, so that participants will eventually be able to fund the full premium through a staggered increase on their portion of the annual premium.

Provision of a financial subsidy as co-financing to the GECC is necessary, in order to retain the commercial interest of insurers, who would otherwise not be able to operate without a profit margin. Subsidizing livestock owners’ annual premiums will reduce the upfront financial burden on them, and encourage their full long-term participation.

An option to the above co-funding scheme is to spend project funds upfront, by paying the full insurance premium to the insurer, and depositing livestock owners’ contributions into the GECC fund. This will help to expend the ‘sinking fund’ as opposed to saving in local endowments that may not be permissible under the United Nations’ financial protocols.

Sustainability

At project conclusion, the private insurer will fully take over the scheme and work directly with participating communities to agree on a revised annual premium. By then, the GECC would have benefitted from project oversight and technical assistance to design socio-economically viable and innovative mechanisms to sustain livestock insurance. Project funds will be expended, or deposited in the reserve fund so that future premiums can be partially supported by the corpus available at the GECC. The important assumption here is that, with careful monitoring and implementation, a private enterprise can more effectively cater to and sustain schemes of mutual interest and benefit. If successful, this pilot can generate a paradigm shift in public service delivery throughout Bhutan, and thus has high pioneering potential.

7.3 Private Crops Insurance

Throughout the world, crop insurance remains one of the most heavily subsidized economic sectors, due to the importance to domestic food security and high risks associated with externalities such as climate, disease and market forces. A World Bank survey of 65 countries in 2009-2010 confirmed premium subsidies to be a common mechanism (by 63% of countries) for public sector involvement in crop insurance (Olivier & Charles, 2010; Kumar, 2016). Even in the agri-businesses of North America, where annual premiums can be as high as 10%, up to 70% of such risk premiums are still subsidized by the government.

At the other extreme, in June 2016, India is revamping micro-insurance interventions through high level government innovation and intervention aimed at “not capping premium, while capping amount payable by farmers” (Parida, 2016). The Indian prime minister’s Pradhan Mantri Fasal Bima Yojana initiative seeks to radically transform decades of agricultural insurance to help farmers, insurers and the economy, with a focus on financial innovation and high technology

(Parida, 2016).

Throughout Bhutan, crop insurance has never been introduced at a commercial scale before. Some initiatives were attempted at a small scale, particularly through the GECCs, with limited success. Yet, it is even more critical than livestock depredation, as a family’s subsistence for an entire year can be threatened by a single catastrophe.

Scope

Similar to the livestock insurance proposal presented above, a PPP model of collaboration can help to create a market-based crops insurance scheme, that will (i) attract participation of farmers, (ii) guarantee near market-value payment for crop damage and loss, and (iii) ensure a sustainable business model to relieve the government of unsustainable financial handouts.

Considering the detrimental effect that climate change or wildlife incursions can have on rural livelihoods, the project could introduce a crop insurance scheme in identified hotspots. The role of community funds through GECCs can be valuable as a bridge between all stakeholders.

RICB’s proposal

Although the government has been negotiating with RICB over a specific crop insurance proposal since 2009, progress has been held back by financial constraints in the government and related concerns. RICB’s proposal (RICBL, 2016(b); Annex 9) was found to be quite relevant to the project’s requirements to address climate and wildlife induced crop damages, although it requires some modifications in certain areas.

All staple crops identified by the government will be covered, and insured against damages due to weather (rainfall, hailstorm, drought, floods and landslides), pests and diseases, and wildlife (wild pigs, elephants, monkeys and deer).

Only certain components around low payouts and cost sharing burdens need to be streamlined for project implementation. In the event of claims, farmers’ welfare must be protected by ensuring compensation remains commensurate with the market value of crop loss. Therefore, the policy offered by RICB has to be negotiated to increase the policy coverage/sum insured with corresponding increase in annual premiums. During consultations, RICB management was amenable to at least doubling the sum insured, with further details subject to analysis of market valuation vis. crop yield and productivity.

The proposed policy coverage could be revised to the following minimum baseline, and limited for each category by land holding size:

Table 16: Revised, minimum insured values, by cultivated area

Marginal (< 1 acre) Small (1-3 acres) Big (> 3 acres) Premium Sum Insured Premium Sum Insured Premium Sum Insured All identified 1% of SI 1% of SI 1% of SI Nu. 80,000 Nu. 120,000 Nu. 200,000 crops (Nu. 800) (Nu. 1,200) (Nu. 2,000)

Regarding coverage against specific perils as proposed below, the insurer has proposed to the government to payout only half the insured value for claims during sowing and germination stage, and full value for damages during pod formation and maturity. In the event of partial loss or damage, farmers will be compensated on a percentage of land/crop loss in relation to total cultivated area.

Table 17: Revised, minimum insured value, by cropping stage Perils Floods & Pest & Wild Stages of cropping Weather Landslides Diseases Animals Sowing & 100% 100% 100% 100% germination Pod formation & 100% 100% 100% 100% maturity

With further consultation with cropping specialists, the above coverage can be negotiated to favor farmers and ensure food security in times of loss. Compensation has to be available as close to market valuation as possible in the cropping cycle, and premiums can be priced accordingly. Compensation from damages can be fixed equally at both stages of cropping.

Financing modality

The project could capitalize 17 Gewogs in the Project Landscapes. These will be the 10 Gewogs identified under Very High severity ranking (ie., Bjena, Korphu, Sergithang, Phuentenchhu, Doban, Jigmichhoeling, Bji, Phobji, Gangtey and Tsento) and the 7 Gewogs under High severity ranking (ie., Athang, Kabjisa, Toepisa, Langthil, Metsho, Jarey and Daga).

For every crop insured under this scheme, participating members will pay 30 basis points of a desired annual premium of 1%, while the government will pay another 30 basis points, and the project will pay the balance 40 basis points. In order to subsidize the project’s 40% contribution to annual premiums, and to create a reserve fund with any surplus to sustain the scheme after the project cycle, the project will set aside approximately $380,000 to capitalize each Gewog fund with Nu. 1,500,000 ($22,500).

Meeting the high premium for market valuation of crops will serve to counter RICB’s proposal to seek reimbursement for any losses arising from claims payouts in excess of premium revenues. Similar to the rural housing insurance scheme, the entire process of premium collection, claims procedures and field verification and claims payouts can be administered by district and GECC staff. This will help reduce any overhead for the insurer. By assuring any potential insurer of a profitable scheme, it is hoped to retain their long-term interest in such initiatives. Based on experiences with rural housing insurance, the business may likely be a labor-intensive and low- profit long-term operation. However, the potential for eventual large volume business for the insurer, once project success is replicated throughout the country, can serve to retain commercial interest.

Exit strategy

At project conclusion, the insurance scheme and reserve fund will be administered directly by the GECC, chaired by the local Gup and joined by district sector heads and community

representatives. The most critical component of the pilot scheme is for the GECC to negotiate a phased discount on annual premiums, so that participants will be able to fund the full premium through a staggered increase on their portion of the annual premium. Through a five-year process of learning and financial benefit, farmers should be convinced of the economic value of commercial insurance. Compared to livestock insurance, the premiums for crop insurance will be more affordable and further subsidies will not be necessary.

The initial provision of a financial subsidy as co-financing to the GECC is necessary, in order to retain the commercial interest of insurers, who would otherwise not be able to operate without a profit margin. Similarly, subsidizing farmers’ annual premiums will reduce the upfront financial burden on them, and encourage their full long-term participation.

Again, an option to the above co-funding scheme (as also proposed under livestock insurance) is to spend project funds upfront, by paying the full insurance premium to the insurer, and depositing farmers’ contributions into the GECC fund. This will help to expend the ‘sinking fund’ as opposed to saving in local endowments that may not be permissible under the United Nations’ financial protocols.

Sustainability

Sustainability of project interventions will depend entirely on demonstration effects and hands- on learning. Therefore, it will be important for farmers in the pilot project to be educated and closely guided on what often can be complex and uncertain financial details.

Project success can be measured by the private insurer fully taking over the scheme and work directly with participating communities to agree on a revised annual premium. By project conclusion, the GECC would have benefitted from project oversight and technical assistance to design socio-economically viable and innovative mechanisms to sustain crops insurance. Project funds will be expended, or deposited in the reserve fund so that future premiums can be partially supported by the corpus available at the GECC. The important assumption here is that, with careful monitoring and implementation, a private enterprise can more effectively cater to and sustain schemes of mutual interest and benefit. If successful, this pilot crop insurance scheme can generate a major paradigm shift in public service delivery throughout Bhutan. It can potentially transform the way agriculture is viewed in Bhutan, by establishing resilience of rural livelihoods, enhancing economic growth and ensuring environmental conservation.

7.4 Financial Plan

An indicative financial plan is projected below, reflecting establishment and minimum recurrent costs for the above three interventions proposed. Preliminary estimates indicate a 5-year requirement of Nu. 49,500,000 ($740,000) to implement the above recommendations.

Costs have been estimated conservatively, and will require further analysis in order to prepare a detailed budget, particularly for negotiating and pricing annual premiums for livestock and crops insurance. Existing insurance companies have indicated some interest to explore livestock and crop insurance, but require detailed analysis before any pricing is offered. In a recent development, the study was advised by the central bank (Penjore, 2016) to consider utilizing micro-insurance for rural development needs. Regulatory approval for deposit-taking micro-

insurance is pending, and can be encouraged to formalize and benefit market-based insurance requirements outside the prevailing insurance industry. At the least, micro-insurance providers can offer rural stakeholders a choice, in terms of service delivery and competitive pricing on annual premiums.

Table 18: Indicative financial plan for proposed pilots (Amount in Nu.)

Livestock HWC mgmt. Crops insurance Activity insurance Total strategy (17 Gewogs) (10 Gewogs) Feasibility study 0 500,000 500,000 1,000,000 Consultation 200,000 100,000 100,000 400,000 Technical assistance 300,000 500,000 500,000 1,300,000 Capacity building of GECCs 200,000 500,000 500,000 1,200,000 5-year capitalization 0 15,000,000 25,500,000 40,500,000 Annual M&E 300,000 900,000 900,000 2,100,000 Mid-term M&E 200,000 500,000 500,000 1,200,000 End-term evaluation 300,000 1,000,000 1,000,000 2,300,000 Total 1,500,000 18,000,000 29,000,000 49,500,000

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Annex 1: Terms of Reference

TERMS OF REFERENCE

FOR INDIVIDUAL CONSULTANTS/CONTRACTORS

POST TITLE: National Consultant for Study on Crop and Livestock Compensation/ Insurance against Climate-induced Disasters and Wildlife Incursions

AGENCY/PROJECT NAME: UNDP/GEF/LDCF Project on Enhancing Sustainability and Climate Resilience of Forest and Agricultural Landscapes and Community Livelihoods in Bhutan.

COUNTRY OF ASSIGNMENT: Bhutan

1) GENERAL BACKGROUND

In order to reduce climate change vulnerabilities and improve the sustainability of local livelihoods and biodiversity of the country, the Royal Government of Bhutan has requested support from the Global Environment Facility through UNDP for a full-sized project titled “Enhancing Sustainability and Climate Resilience of Forest and Agricultural Landscapes and Community Livelihoods in Bhutan.” The project aims to operationalize an integrated landscape-based approach to climate change adaptation and biodiversity conservation. It seeks to do so through: (a) improvement of institutional capacity at national, sub-national and local levels to manage forest and agricultural landscapes sustainably for enhanced climate resilience; (b) emplacement of governance system for biological corridors and operationalization of conservation management system in the pilot corridors; and (c) development of climate-resilient livelihood options for the local communities.

Based on the project identification form (PIF) document, which articulates the project concept and key components, the GEF has approved project preparation grant (PPG) to develop the Project Document and

GEF CEO Endorsement Document. The PPG phase commenced in January 2016 and is scheduled to end in December 2016. In order to aid the project design and formulation of the Project Document, a series of sub-consulting assignments has been anticipated.

2) OBJECTIVES OF THE ASSIGNMENT

The objective of the assignment is to review crop and livestock loss to climate-induced disasters and wildlife incursions, examine existing and potential compensation/insurance/technical measures to mitigate losses, and propose viable options with special attention to community-based modalities. The findings of the assessment will be vital to the formulation and design of the UNDP/GEF/LDCF project, particularly in relation to development of climate-resilient livelihood options for the local communities and reduction of biodiversity threats from human-wildlife conflicts.

3) SCOPE OF WORK AND KEY TASKS

Under the supervision of GNHC and UNDP, and in close consultation with the PPG team, the consultant will carry out the following tasks:

(1) Collate up-to-date data and information on loss of crop and livestock caused by climate- induced disasters and wildlife incursions in the entire country;

(2) Map the gewogs in the target project areas according to the severity of crop/ livestock losses and damages by climate-induced disasters (e.g. low, moderate, high, very high) and wildlife incursions and identify the hotspots;

(3) Take stock of existing measures to alleviate the impacts of crop/ livestock losses and damages and assess their effectiveness including taking note of how they have benefitted men and women distinctly;

(4) Review various types of compensation and insurance schemes for damage/ loss of crop and livestock to climate-induced disasters (e.g. windstorm, hailstorm, excessive/ untimely rain, drought, flashflood, and wildfire) and wildlife incursions within and outside Bhutan, examine what have worked and what have not, assess the issues, opportunities and challenges in Bhutan, and propose measures to strengthen existing schemes and/or introduce new viable options including institutional modalities (government, public, private, community-based, etc);

(5) Carry out a rapid assessment of human-wildlife conflicts in the targeted PAs and biological corridors, identify the hotspots, and develop a human-wildlife conflict management strategy,

including a safe HWC management system building on lessons from WWF’s work in tiger range countries.

4) DURATION OF ASSIGNMENT, DUTY STATION AND EXPECTED PLACES OF TRAVEL

The consultant will be employed for 40 working days spread over the period from the week of 21st March to the week of 30th May, 2016. He/ she will be expected to travel to the target project areas to consult local governments, local communities, extension agents, and other relevant local stakeholders.

5) FINAL PRODUCTS

(1) An inception report detailing the methodology and work plan for the consulting assignment, and outlining the table of contents of the consulting report;

(2) A detailed report that: (a) provides an overview of damage/loss of crop and livestock to climate-induced disasters in the country with detailed data of such losses in the target project areas including mapping of the gewogs according to the severity of the damage/loss; (b) assesses existing compensation schemes and identify opportunities and challenges to strengthen them; and (c) proposes viable compensation options, including community-based schemes in the target project areas.

6) PROVISION OF MONITORING AND PROGRESS CONTROLS

The consultant will receive technical guidance and support from the PPG team comprising of two international and a national consultants. The PPG team will ensure that the methodology of the assessment is in alignment with the intended objectives of the project, and monitor quality of the final products. UNDP will provide technical advice and liaise with GNHC and project partners to conduct field assessment in the target landscapes.

7) DEGREE OF EXPERTISE AND QUALIFICATIONS

 Master’s degree or higher in agriculture development economics, community-based natural resources management or related field;  At least seven years of relevant progressive work experience;  Extensive experience of working with local governments and local communities;  High level of proficiency in Dzongkha and local Bhutanese dialects;  Very good analytical and report writing skills in English.

8) CRITERIA FOR SELECTION OF THE BEST OFFER

The criteria which shall serve as basis for evaluating offers will be:  Combined Scoring method – where the qualifications and relevant work experience will be weighted a max. of 70%, and combined with the price offer which will be weighted a max of 30%

Criteria Weight Max. Point

Technical 70  Academic background 10  Relevant work experience 10  Knowledge and understanding about different models of 20 insurance schemes, including community-based insurance schemes against climate-induced disasters and crop damages by wildlife.

 Experience in designing insurance schemes for crop and livestock affected by climate-induced disasters and wildlife - as 20 demonstrated through similar assignments in the past, publication and reports.

 Appraisal and feedback from past clients on related assignments 10 Sub-total A. (Technical) 70

Financial 30 30

Sub-Total B.(Financial) 30

Total (A+B) 100

9) PAYMENT TERMS

The applicant is required to submit a lum-sum financial proposal for the period of 40 working days. The selected consultant will be paid upon payment certification from the hiring manager, in the following manner:  25% upon submission and acceptance of the inception note detailing the methodology and work plan for the assignment;  25% upon completion of the field work and assessment;

 50% upon submission and acceptance of the final report by the PPG team, UNDP and GNHC. 10) AWARD OF CONTRACT

The consultant who fulfill the requirements will be assessed based on a combined scoring of:  Technical evaluation comprising of 70%, and

 Financial evaluation of 30%. 11) FINANCIAL PROPOSAL

Please indicate fee structure:

i. If Lump-sum (provide breakdown of this lump sum i.e travel, per diem and fee for anticipated number of working days); and

ii. Daily fee (inclusive of fees, including any other relevant expenses related to this assignment).

12) RECOMMENDED PRESENTATION OF OFFER

Please submit the below preferred documents with you Presentation of Offer: a) Duly accomplished Letter of Confirmation of Interest and Availability; b) Personal CV or P11, indicating all past experience from similar projects, as well as the contact details (email and telephone number) of the Candidate and at least three (3) professional references; c) Brief description of why the individual considers him/herself as the most suitable for the assignment, and a methodology on how they will approach and complete the assignment. The proposal should be submitted in electronic format by Monday 14th March 2016 to [email protected].

Annex 2: Selection of Chewogs for the study

Annex 3: Gewog level questionnaire

Annex 4: Chewog level questionnaire

81 82

842

Annex 5: Livestock Depredation in Project Landscapes (2002-2015)

853

864

875

886

Annex 6: Crop Damage by Climate Induced Factors in Project Landscapes (2011-2015)

897

908 Annex 7: SAFE Approach to HWC management, adapted for Bhutan

942

953

Annex 8: Cattle insurance policy (RICB)

964

975

986

Annex 9: Crop insurance proposal (RICB)

997

1008

1019

10102

Annex 10: List of consultations

10311

10412

C. In Thimphu

1. Director, Department of Forests and Parks Services, Ministry of Agriculture and Forests

2. Chief Forestry Officer, Wildlife Conservation Division, Department of Forests & Parks Services

3. Head, Biological Corridors, Wildlife Conservation Division, Department of Forests & Parks Services

4. Head, Human Wildlife Conflicts, Wildlife Conservation Division, Department of Forests & Parks Services

5. Director General, Department of Agriculture, Ministry of Agriculture and Forests

6. Program Director, National Plant Protection Center, Ministry of Agriculture & Forests

7. Sr. Specialist, National Plant Protection Center, Ministry of Agriculture & Forests

8. Chief Agriculture Officer, Department of Agriculture, Ministry of Agriculture & Forests

9. Statistical Officer, Department of Agriculture, Ministry of Agriculture & Forests

10. Chief Statistical Officer, Consumer Price Division, National Statistics Bureau

11. Country Representative, World Wildlife Fund Bhutan Program

12. Executive Director, Bhutan Insurance Ltd.

13. General Manager, General Insurance Department, Royal Insurance Corporation of Bhutan

14. Head, Corporate Strategy & Planning Division, Royal Insurance Corporation of Bhutan

15. Chief Underwriter, General Insurance Department, Royal Insurance Corporation of Bhutan

16. Asst. Chief Underwriter, General Insurance Department, Royal Insurance Corporation of Bhutan

17. Chief Executive Officer, GIC Ltd.

18. The Governor, Royal Monetary Authority

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