Exploring Changes in Cereal-Based Farming Systems in Terai and Mid-Hills of Nepal

Exploring changes in cereal-based farming systems in Terai and Mid-hills of Nepal

Name student: Dharma Dawadi Period: September, 2015 to May, 2016 Farming Systems Ecology Group Droevendaalsesteeg 1 – 6708 PB Wageningen - The Netherlands

Exploring changes in cereal-based farming systems in Terai and Mid- hills of Nepal

Name student: Dharma Dawadi Reg. No: 831207173030 Credits: 36 ECTS Code No: FSE-80436 MSc Thesis Farming System Ecology September, 2015 - May, 2016

Supervisor(s): dr.ir. EN (Erika) Speelman Mrs. Victoria Alomia Hinojosa, MSc

Examiner: dr.ir. WAH (Walter) Rossing

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Preface

It’s done finally, what a great sense of relief and happiness. This report is the synergistic effort of various persons, without which I could not imagine this piece of work. Among many supporters and contributor, firstly I would like to express my sincere gratitude to Erika Speelman, PhD and Victoria Alomia, MSc, supervisor of my MSc thesis. After every single meeting with you both, I could feel my inside with a great positive energy which made me think about the various options of doing things. You were always supportive of me and your continuous encouragement, constructive criticism, persistent inspiration, valuable suggestions and regular supervision throughout the thesis period were highly admirable. During the entire periods of thesis (proposal preparation, survey, and result analysis), I learned and enjoyed a lot working on this topic and working with you. I also want to thank Dr. Jeroen Groot, Associate Professor of Farming System Ecology Department for his moral support, inspiration and valuable advice.

I am very grateful to chairman of District Agriculture Development Office and District Livestock service provider office from Palpa, Nawalparasi and Dadeldhura for their cooperation and support in entire survey periods. Similarly, I would also like to thank the VDC/Municipality representative of Palpa (Boughapokharathok,Tansen Municipality and Bandhipokhara VDC), Nawalparasi (Sunwol Municipality, Jamuniya and Jahada VDCs) and Dadeldhura (Samaijee VDC, Ashigram VDC and Amargadi Municipality) respectively.

I am also thankful to Ms. Asmita Bhattarai, Mr. Chetraj Pathak, Mr. Shrawan Paudel, Mr. Bhuwan for supporting me during field survey. The research could not have been accomplished without the generous support of many friends. I would like to thank Dr. Arun Pratihast for proofreading as well as managing the GIS data and providing resources and tips from time to time. I am also thankful to my friends Sudeep Subedi, Tanka Khanal, Bihani Thapa, Binita Thapa, Seeva Aryal, Suresh Baral, Arun Thapa, Rajan Dhakal, Madhav Paudel, Eakraj dai for their encouragement and support during research periods.

I would like to thank the Netherland Government for providing me the NUFFIC Fellowship to grow myself professionally and personally. At last, I thank all of my family members for their never ending support, encouragement, cooperation, love, and understanding during my study period.

Acronyms

ADB Agriculture Development Banks AI Artificial Insemination APP Agriculture Perspective Plan ASC Agriculture Service Centre CA Cluster Analysis CBS Central Bureau of Statistics CIMMYT International Maize and Wheat Improvement Centre CLDP Community Livestock Development Project CPA Comprehensive Peace Agreement DADO District Agriculture Development Office DDC District Development Committee DLSO District Livestock Service Offices EAP Economically Active Population FAO Food and Agriculture Organization FFSs Farmers Field Schools FGD Focus Group Discussion FSS Food Self Sufficiency FYM Farm Yard Manure GDP Gross Domestic Product GO Governmental organization GoN Government of Nepal HH Household HMRP Hill Maize Research Project IFPRI International Food Policy Research Institute KISAN Knowledge based Integrated Sustainable Agriculture and Nutrition project LU Land use masl Meter above sea level MoAD Ministry of Agriculture and Development NEAT Nepal Economic, Agriculture and Trade Activity NGO Non-Governmental Organization NRs. Nepalese Rupees OPV Open pollinated Variety PCA Principle Component Analysis SLC School Leaving Certificate SSQ Semi-Structured Questionnaire TLU Tropical livestock unit USD US Dollars VDC Village Development Committee

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Table of contents

Acronyms ...... vii List of table ...... xi List of figure ...... xiii Executive summary ...... xv 1. Introduction ...... 1 1.1 Background ...... 1 1.2 Objectives ...... 4 1.2.1 General objective ...... 4 1.2.2 Specific objectives ...... 4 1.3 Research questions ...... 4 1.4 Hypotheses ...... 4 2. Review of Literature ...... 5 2.1 Demographic change and migration situation of Terai and Mid-hills of Nepal ...... 5 2.2 Land use patterns and farming systems in Terai and Mid-hills of Nepal ...... 5 2.3 Access to agricultural resource in Terai and the Mid-hills of Nepal ...... 6 2.4 Limitations of agriculture production in Terai and the Mid-hills of Nepal ...... 7 3. Materials and methods ...... 9 3.1 Research and Theoretical framework ...... 9 3.2 Description of study site ...... 10 3.3 Data collection ...... 12 3.3.1 Selection of sites and participants ...... 12 3.3.2 Secondary data collection ...... 14 3.3.3 Semi-structure questionnaire (SSQ) ...... 14 3.3.4 Focus group discussions (FGD) ...... 14 3.4 Data analysis ...... 15 4. Results ...... 19 4.1 Demographic and socio-economic characteristics ...... 19 4.2 Land use patterns and access to resources ...... 22 4.2.1 Land use pattern ...... 22 4.2.2 Access to agricultural extension services, markets and roads ...... 24 4.3 Changes in Agricultural practices ...... 25 4.3.1 Changes in diversity of agricultural crops ...... 25 1 Time line information were compile based on the information gathered from FGD, Key informant interview...... 26 4.3.2 Changes in percentage share of different crops ...... 26 4.3.3 Changes in cropping pattern and composition of crops ...... 29 4.3.4 Adoption of improved seeds and inorganic fertilisers ...... 30 4.3.5 Productivity of the crops ...... 31

4.4 Changes in Livestock numbers ...... 31 4.5 Problems for agriculture production ...... 33 4.6 Drivers of agriculture intensification ...... 33 4.7 Changes and shifting of the farming systems ...... 34 4.8 Typologies of farming HH ...... 36 5. Discussion ...... 41 5.1 Demographic and socioeconomic characteristics of the HH ...... 41 5.2 Land use patterns and access to resources ...... 42 5.3 Changes in Agricultural practices ...... 43 5.4 Changes in livestock numbers ...... 44 5.5 Problems for agriculture production ...... 45 5.6 Drivers of intensification and diversification ...... 45 5.7 Changes and shifting of the farming systems ...... 46 5.8 Typology and trajectory of HH ...... 49 6. Conclusion ...... 51 References ...... 52 Annexes ...... 58

List of table

Table 1. Major demographic and agricultural characteristics of the survey districts...... 10 Table 2. Adapted month as per season for data calculation...... 11 Table 3. A number of surveyed HH and their altitude range in each site of survey Districts...... 12 Table 4. Data on different aspects with their indicators ...... 14 Table 5. Data analysis methods used for demographic and socio-economic indicators ...... 15 Table 6. Data analysis methods of Agricultural indicators ...... 17 Table 7. Changes on demographic and socioeconomic indicators from 1985 to 2015...... 19 Table 8. Demographic and socioeconomic characteristics of the HH in three districts...... 20 Table 9. Timeline study of the survey sites1 ...... 26 Table 10. Major cropping pattern from 1985 to 2015 in Palpa, Nawalparasi and Dadeldhura...... 29 Table 11. Problems of agriculture production in three districts...... 33 Table 12. Different types of farming systems with their description ...... 35 Table 13. Types of HH and their average value of each indicators...... 36

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List of figure

Figure 1. Research framework showing influences on the trajectories of farm HH systems modified with (Cramb, 2014)...... 9 Figure 2. Research phase and steps...... 9 Figure 3. The average monthly rainfall pattern in Palpa, Nawalparasi and Dadeldhura from 1987 to 2014. Source: Department of Hydrology and Meteorology, Kathmandu)...... 11 Figure 4. Map of the research sites (Nawalparasi, Palpa and Dadeldhura). GPS coordinates and altitude range of the HH were taken by using the Gramini e-Trex 20 (Annex 2)...... 13 Figure 5. HH size (a) and types of migration pattern (b) in Palpa, Nawalparasi, and Dadeldhura at 2015...... 21 Figure 6. Relationship between average size of landholding (ha) and age of the respondents in Palpa (a), Nawalparasi (b) and Dadeldhura)...... 22 Figure 7. Percentage of agricultural land, forest land and shrub land per HH in Nawalparasi (a) Palpa (b) and Dadeldhura (c) in 2015 ...... 22 Figure 8. Qualitative land use change in Palpa, Nawalparasi and Dadeldhura since 1985 until 2015. Figure format adopted from (Speelman et al., 2014). The dotted lines represents the decreasing trends...... 23 Figure 9. Access to agricultural extension services (%), market (km) and roads (km) in Palpa, Nawalparasi and Dadeldhura from 1985 to 2015...... 24 Figure 10. The diversity of crops (total number of crops per year) in Palpa, Nawalparasi and Dadeldhura from 1985 to 2015...... 25 Figure 11. Percent share of different types of crops during summer (June-September) and winter (November to February) from 1985 to 2015 in Palpa, Nawalparasi and Dadeldhura. The figure a, b, c represents the percentage share of summer crops and figure d, e and f represent the percentage share of winter crops in Palpa, Nawalparasi and Dadeldhura respectively...... 27 Figure 12. Percent share of fallow period and vegetables during the spring season (March- May) from 1985 to 2015 in Palpa, Nawalparasi, and Dadeldhura...... 28 Figure 13. Adoption of improved seeds (a) and inorganic fertilisers (b) in Palpa, Nawalparasi and Dadeldhura from 1985 to 2015...... 30 Figure 14. The productivity of major cereals in Palpa, Nawalparasi, and Dadeldhura from 1985 to 2015. Secondary data taken from Ministry of Agriculture and Cooperatives (MoAD)...... 31 Figure 15. An average number of buffalo (a), cattle (b), goat (c) and poultry (d) per HH in Palpa, Nawalparasi and Dadeldhura from 1985 to 2015...... 32 Figure 16. Drivers of intensification of agriculture in Palpa, Nawalparasi and Dadeldhura. L-local, N-national and I-international drivers...... 34

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Figure 17. Percent share of different farming systems in Palpa, Nawalparasi and Dadeldhura at 2015...... 35

Figure 18. Correlation circle of the PC1-PC2 and PC1-PC3 in Palpa (a), Nawalparasi (b) and Dadeldhura (c) as a output of the PCA and cluster analysis. The direction and length of the arrows within each circle showed the strength of the correlations between variables, and variables and PC's...... 38 Figure 19. HH total annual agricultural income with respect to agricultural investment (%) and their potential livelihood strategies. The USD 500 taken as a reference value and less than USD 500 considered as a hanging in HH, 500 to 1000 as a stepping up HH and more than 1000 stepping out HH...... 39 Figure 20. General qualitative view of shifting of agriculture during past, present and future projection...... 47

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Executive summary

The major objective of the study was to explore how the cereal-based farming systems in Terai and Mid-hills of Nepal have changed over the last decades and what were the main drivers of these changes. The present study explores the socioeconomic and demographic changes, changes in land use pattern and access to resources, changes in agricultural practices and their associated drivers of change in Palpa, Nawalparasi and Dadeldhura districts of Nepal.

Both primary and secondary data were collected. The primary data were collected by semi- structured questionnaire (SSQ) with household (HH) and focused group discussion (FGD) with farmers and key informants. One district from the Terai/lower altitude (Nawalparasi) and two districts from the Mid-hills; Palpa and Dadeldhura were selected for the research. This research was the part of the larger study of PhD research under Farming System Ecology group of Wageningen University. Similarly, altitude, market access, distance to the Indian market and total annual rainfall pattern as a secondary criteria used to select the district. Three different sites were selected for each district for the HH survey. Altogether 180 HH (50 from Palpa, 67 from Nawalparasi and 63 from Dadeldhura) were selected for HH survey during September to December, 2015 by using SSQ. After selecting the district, surveying communities (clusters) were selected based on the ethnicity of the HH as a strata by using stratified sampling. A random HH was selected at the start followed by snowball sampling to select the possible HH based on the ethnicity. The non-responding HH were avoided and HH nearby community with same ethnic group were taken for fulfilling the quota for that ethnic group. Two FGD were organized with groups of elderly people and key informant to explore the time line information and changes on the different socio-economic and agricultural practices. Also, key informant interviews were also conducted in each district. The quantitative data gathered from the SSQ and secondary source were analysed by using the SPSS version 20, Microsoft excel, dudi.pca packages of statistical software of R version 3.1.0 (R Development core team). The mean of the selected quantitative variables was used for the analysis.

There has been a significant change in the demographic and socio-economic characteristics as well as land use pattern and agricultural practices of the HH from each surveyed district between 1985 and 2015. The major demographic and socio-economic characteristics like HH size, types of migration, total annual income, non-farm income and HH food security changed considerably during the last three decades. The average size of the HH reduced (7-20%) in Papa, Nawalparasi and Dadeldhura. The literacy rate of the respondents remained quite low and the majority of the respondents had an education in between primary and secondary levels; 50% in Palpa, 60 % in both Nawalparasi and Dadeldhura. Although, the majority of the HH (>70%) depends on agriculture for their livelihoods, income from this sector does not contribute more on the total annual HH income, which mainly (>74%) contributed by the non-farm sources; 92% in Palpa, 80% in Nawalparasi and 74% Dadeldhura respectively. More than 50% HH experienced

xv migration of at least one members per HH in all three districts. There has been an increase of a 44 to 53% of migrating HH in 2015 as compared to the year 1985. Due to the migration of economically active population from HH, higher dependency ratio was recorded in all three districts; 81% in Palpa, and around 52% both in Nawalparasi and Dadeldhura.

The average land holding of the HH was less than one hectare and more than 56% of the land holding was used for agriculture purpose in 2015. However, land use pattern and access to resource changed markedly since 1985. Land use pattern shifted towards the market-oriented vegetable production system from the subsistence cereal production system. Access to agriculture extension services and access to market and roads increased in all three districts. From the year 2000, the agricultural extension services to the HH increased rapidly in all three districts. Overall only less than 5% HH had access to an agricultural extension during 1985 which remained almost same until 1995, and after the year 1995, it increased with faster rates and reached to around 40% for all three districts at 2015. On the other hand, the distance to markets and roads from HH decreased from 1985 to 2015. Distance to market was reduced from around 4.5 km to the 3 km in Dadeldhura, 3 km to around 2.5 km in Palpa and 2.5 km to 2 km in Nawalparasi from 1985 to 2015 due to the development of the new local markets.

Different agricultural practices like the diversity of the crops, crop rotation pattern, the percent share of crops, adoption of fertiliser and improved seed, and productivity of the major cereals changed from 1985 until 2015. The diversity of the agricultural crops increased linearly from 5 to 6 agricultural crops during 1985 to around 8 to10 crops at 2015. The percentage share of the different types of crops per HH during summer (June- September), winter (October-February) and spring (March-May) changed from 1985 to 2015. During summer, an almost constant pattern was observed for the maize with rice bean and maize mixed with other crops, whereas percentage share of sole maize and millet decreased considerably in Palpa since 1985. Similarly, more than 90% HH grew rice as a constant pattern since 1985, however, percentage share of vegetable increased and other crops (other than rice and vegetables) decreased considerably in Nawalparasi. In Dadeldhura, mixed crop maize with soybean and vegetable increase linearly and reached up to 30% and 20% in the year 2015 respectively during summer season. During the winter season, percentage share of the winter cereal decreased from around 50 % to 30% in all three districts. However, there were an increasing trend of percentage share of vegetable since 2005. The mixed crop mustard with lentil seems almost constant, with only less than 5% changes since 1985. On the other hand, the percentage share of sole mustard decreased in Nawalparasi, remained constant in Dadeldhura and slightly increased in Palpa since 1985. During the spring season, the percentage share of fallow land decreased and vegetable increased in all three districts.

Due to the changes of diversity and percentage share of the crops during different cropping seasons, the overall cropping pattern of each surveyed district changed from the cereal-based cropping pattern into vegetable and cash crop based cropping pattern. The adoption of improved seed and inorganic fertiliser per HH were increased since 1985. The adoption of improved seeds

xvi reached from almost less than 2 % in 1985 to 50% in Nawalparasi and Palpa, and around 25% Dadeldhura. Similarly, adoption of inorganic fertiliser rocketed after the year 2005 into around 50% in Nawalparasi, 35% in Palpa and 20% in Dadeldhura respectively. The pproductivity of the crops especially cereals also changed due to the introduction of the high yielding modern varieties and hybrids. Besides that, the average number of livestock per HH decreased in Palpa and Nawalparasi, but increased in Dadeldhura.

The major common drivers responsible for the change of livelihood during the time are the increased access to resources (seeds, inputs, credits), political stability after the peace agreement in 2006, better agricultural road connectivity, increase income of HH (due to agriculture as well as non-farm income source), development of agricultural technology and its increased access to the farmers, and government policies. Those drivers alone as well as collectively influences the changes in agricultural practice and land use pattern towards market-oriented mixed crop- livestock production systems.

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1. Introduction

1.1 Background

Nepal is a mountainous country which lies at the northern rim of South Asia with diverse topography, climate, and vegetation (Maskey RB, 2003). Based on the physiography, geology, and geomorphology, there are five main agro-ecological regions commonly known as Terai (14%; below 300 masl), Siwalik (14%; 300-900 masl), Middle Mountain (30%; 900-3000 msal), High Mountain (19%3000-5000 masl;) and High Himalayan (23%; above 5000masl) regions (Maskey RB, 2003). Topographic elevation changes from 60 masl in the southern plain to 8848 masl at the Mt Everest (Dahal, 2006; Dahal and Bhandary, 2013). In Nepal, a greater proportion of the area is covered by the Hills and mountains (over 70% of the total land area) with the highest population density per unit cultivated land. Only about 20% of the total area is cultivable; another 33% is forested; most of the rest is mountainous. The lowland Terai region produces an agricultural surplus, part of which supplies the food-deficient hill areas in Nepal. There are mainly three sectors contributing national Gross domestic product (GDP) i.e. agriculture (36.8%), industry (14.5%) and services (48.7%) (CIA, 2015).

The agricultural sector plays a critical role in the Nepalese economy (Dillon et al., 2011; Karki and Gurung, 2012) as this sector contributes more than one-third to Nepal’s GDP, and more than two-third of its population depend on it for their employment and livelihood (CBS, 2001; Deshar, 2013). Nepalese agriculture is mainly dominated by cereal crops where rice is ranked first, followed by the maize and wheat. Recently, pulses, vegetables, some cash crops, and fruits of different varieties also increase considerably. Regarding the livestock, a considerable population of cattle, goats, and poultry exists both in Terai as well as Mid-hills of Nepal. In the Terai, rice is most preferred and the cropping pattern is rice based because of the partial water availability and climatic condition suitable for its production. However, in the Mid-hills, the cropping pattern is dominated by the maize due to the sloppy land with terraces and no irrigation facilities. In the higher mountains, the choice of the crops is limited due to the temperature where potato and temperate fruits such as apples and walnuts are grown.

The current agricultural production system is characterized by smallholding, rain-fed subsistence- oriented production systems with low productivity. Agricultural production in the country is diverse with its subsistence oriented, diverse across the country and also the risk-prone nature. However, despite a good agricultural production potential of various agro-ecosystem and a vast labour pool in the agriculture sector, agricultural productivity remains low. The major reasons of lower productivity of the agricultural systems are land fragmentation and erosion (Acharya et al., 2007), limited irrigation facilities, limited access to agricultural inputs, depletion of natural resources, seasonal variability of rainfall, including climate change (Malla, 2009), yield losses from insect-pest and weed infestations are major reasons of low-crop productivity (Basnyat,

1995; Dahal et al., 2007; Tiwari et al., 2010; Das and Bauer, 2012). Recently, migration (within and outside the district and outside the country) reduced the availability of the labour for agriculture. On the other hand, it is the alternative source of the income for rural (Thieme and Wyss, 2005; Dahal et al., 2007; Wagle, 2012). Additionally, off-farm employment opportunity for the farmer is limited, which affects the socio-economic condition of farmers.

In the last few decades, there have been changes in the land use pattern and agricultural practices in the Terai as well as Mid-hills of Nepal. The trajectory of cautious, risk averse experimentation has been involved more with agricultural activities in Terai and more with non-agricultural activities in the hills (Cameron John, 1998). There have been changes of agricultural holdings due to land fragmentation (Deshar, 2013; Paudel et al., 2013), land use pattern due to the intensification of the agricultural practice and source of income from agricultural and non-farm activities in Terai and Mid-hills of Nepal. In addition to that, there have been significant changes on access to agricultural resource from last few decades in Terai as well in the Mid-hills of Nepal. Although there is recent access to resources (irrigation facilities in Terai, adoption of improved seeds, chemical fertilisers and pesticides), access to agricultural loans and advance farming technology, the performance of the Nepalese agriculture has not been satisfactory (Deshar, 2013). Especially, land holding size per family and field sizes haves both decreased markedly during recent years, both in Mid-hills as well as Terai (FAO, 2010). Due to decreasing yield and productivity of the cereal crops, many farmers are now shifting cereals to cash crops and or with livestock components (Dahal et al., 2009). Such changes in agricultural practices have major and far-reaching impacts on HH income and HH farming systems. Similarly different types of the farming HH play a crucial role on their agricultural production and income thereby influencing the farming systems.

Typologies are used to explore the heterogeneity of the smallholder farming systems (Kuivanen et al., 2016). The typologies are categorised based on the different indicators but mainly by the resource endowment (Tittonell et al., 2005; Kuivanen et al., 2016). Typology have been used since long in the field of sociology (Whatmore et al., 1987) and have become popular in the agricultural science as it helps to analyse the farms with different indicators at diversity in field (Andersen et al., 2007; Dossa et al., 2011) as well as at HH-level (Tittonell et al., 2010). The major purpose of typologies are to identify farm diversity and its associated causes (Tittonell et al., 2005), explore and analysed agricultural trajectories (Iraizoz et al., 2007) including implementation as well as monitoring of the agricultural development projects (Emtage et al., 2007; Álvarez-Alonso, 2014). Similarly, HH typologies are very useful ways to categorizing the data to analyse the behaviours of the HH in their resource allocation, utilization and opportunities (Maltsoglou and Taniguchi, 2004). However, the participatory typologies can give a better understanding and representation of the heterogeneity, its accuracy might be affected by the several socio-cultural constraints (Kuivanen et al., 2016).

Understanding the drivers of such trajectories and possible impacts of major changes in family income and farming systems can provide important theoretical support for reforming the cropping system and adjusting the distribution of agricultural production of the farms in the future. Hence, the present study will be carried out to analyse the trajectories of change on demography, HH income, land use pattern, agricultural practices and access to resources from last 25 years in Terai and Mid-hills of Nepal. Therefore, the present research will provide a comprehensive understanding of the trajectories of farming system and the drivers of each specific trajectory. The study also aims to identify the extent to what socioeconomic and institutional factors, including access to resources, affect trajectories of farming systems in Terai and Mid-hills of Nepal.

1.2 Objectives

1.2.1 General objective To explore how cereal-based farming systems in the Terai and Mid-hills of Nepal changed over the last three decades and to identify the main drivers of these changes.

1.2.2 Specific objectives The following specific objectives were formulated:  To explore the demographic and socioeconomic changes of farms from 1985 to 2015.  To explore the changes in land use pattern and access to resources in Terai and the Mid- hills of Nepal.  To explore the changes in agricultural practices (number of crops, crop rotations, the percentage share of the crops and productivity of major cereals etc.) and to identify the drivers accountable for these changes.  To explore the changes in livestock rearing practices (number of animals)) in the Terai and the Mid-hills of Nepal.

1.3 Research questions

To address the general and specific objectives, the following research questions were formulated:  What have been the changes in crops and livestock production over the last decades in Terai and Mid-hills and what have been the drivers of these changes?  What have been the changes in access to agricultural resources and institutionalization of farm in Terai and the Mid-hills of Nepal?  What have been major drivers of local changes in land use, agricultural practice and land tenure?

1.4 Hypotheses

The following hypothesis were formulated:  Demographic changes, HH income, and non-farm activities are main drivers in changes of the farming system.  Farmers with better access to market have a better chance to shift and diversify their crops and livestock.  Non-farm income creates opportunities to intensify cropping systems of both the Terai and the Mid-hills of Nepal.

2. Review of Literature

2.1 Demographic change and migration situation of Terai and Mid-hills of Nepal

Nepalese HH consist of an average of 4.4 people with per capita GDP 426.48 US dollars in 2014 (CBS, 2014). The major demographic change includes the migration pattern and population growth in Nepal (KC, 2003; CBS, 2012). The total population of the country is 28.12 million with a 2.25% annual growth rate and 2.70% unemployment rate (CBS, 2012). In Nepal, dependent population (children below 15 years and aging people above 65 years; who are not considered in the labour force) is higher in Nepal’s population structure with 63.7% total dependency ration of the population (CBS, 2014). Although the correlation between demographic change and forest/forestry is complex, population growth, urbanization, migration and the dependent population have great implications on land and resource use systems.

In Nepal, migration is common (overall around 50%) and at least one person from every four HH migrated mostly to India and Gulf countries for their family income and food security (CBS, 2012; CBS, 2014). There are mainly three types of migration in Nepal i.e. population moving across country, hill to Terai migration and foreign migration. Generally, the migration to the Terai from the hills and Mid-hills increased after the eradication of malaria in the late 1950s and has been increasing ever since. The foreign migration consists of students, labour migrants, and the people working in diplomatic missions and NGOs (Gartaula and Niehof, 2013). Many factors like poverty, destitution, unequal allocation of and distribution of resources, geographical variation of labour demand and so on attributed to migration in Nepal (KC, 2003). Among the many factors, unemployment and the lack of local opportunities, lower salary of higher skill educated people and low agricultural income are the major drivers of the migration (Tiwary, 2005; Gartaula and Niehof, 2013). As a result of migration, the availability of labour in agriculture and forestry tends to decline.

2.2 Land use patterns and farming systems in Terai and Mid-hills of Nepal

There are various factors HH size, age of HH head, total income from non-agricultural sources, possession of HH assets, migration status, and HH food sufficiency) which determines the land holding size and land use pattern in Nepal (Gartaula et al., 2014). Major land use patterns of the Terai and Mid-hills of Nepal are classified as land occupied by forest, shrubs, agriculture, water bodies, barren land, and snow (CBS, 2014). Land under temporary crops and land under permanent crops and pastures are considered agricultural land and forest and woodland are considered as non-agricultural land in Nepal (CBS, 2013). The majority of the land use in selected district are by forest, agriculture and pastures. Among the agricultural land use, cereals

5 are the dominating crops among all three districts. In all selected districts, major staple crops, maize, potato, and millets.

Regarding the farming systems, it varies sharply from the higher altitude north to the lower south, and from the wet east to the arid west (Tiwary, 2005; Tiwari et al., 2008). The rice-wheat and rice-maize cropping systems are the major cropping system of the country (Manandhar et al., 2009; Timsina et al., 2010) characterized by summer (monsoon) rice followed by an irrigated and or rain fed wheat in the dry winter, and sometimes a short spring vegetable crop. In the Terai, rice based agroecosystem dominated mostly paddy, wheat and maize. The major cropping pattern in Terai are: paddy-maize/wheat-paddy; paddy-vegetable/potato/oilseed-paddy; paddy- wheat/mustard/ lentil-fallow; maize/millet-wheat/mustard and lentil-fallow etc. Similarly, in the Mid-hills: potatoes, millets and maize constitute the staple food crops, including a variety of fruits (apples and citrus and vegetable (green leaf, root crops etc.). Many farmers grow staple crops (maize, wheat, oat, barley, buckwheat) with pulses and vegetables as an inter or mixed crops (Tiwary, 2005). In both Terai as well as Mid-hills, livestock is the integral part of the Nepalese farming system and considered as a social asset in Nepal. There has been decreasing the fertility status of the soil both in Terai as well as Mid-hills of Nepal resulting to decrease the agriculture productivity (Kiff et al., 1995; Vaidya et al., 1995; Mathema et al., 1999; Pilbeam et al., 2000). The reasons of decreasing fertility are soil erosion, declining rates of FYM/compost application, degradation of forest resources and changes in the livestock management systems such as the decline in in-situ manuring practices.

2.3 Access to agricultural resource in Terai and the Mid-hills of Nepal

Generally, access to resources (inputs, irrigation, etc.) is higher in Terai districts as compared with hills due to the strong road network, more flat land (as compare to the Mid-hills) and a relatively larger number of service providers (extension service, financial institutions, agro-vets and others). Regarding access to resources (financial, agricultural extension, and community activities) among men and women in both Terai and Mid-hills, males tremendously dominated in gaining access to all financial, agricultural and community services than women (Devkota, 2006). Although there has been an increasing number of banks and financial institutions across the country, access to financial services to the farmers in many parts is not satisfactory (Ferrari, 2007; Dulal et al., 2010). Generally, family and friends are by far the largest informal providers of loans to rural HH. Those HH which borrows from informal providers do not bother trying to borrow from financial institutions because of some administrative procedure and delay access to money.

2.4 Limitations of agriculture production in Terai and the Mid-hills of Nepal

There are many issues and challenges in the production of the crops and livestock in both Terai as well as Mid-hills of Nepal. The major issues are smaller farm size, fragmented land with almost no land management (CBS, 2012; Deshar, 2013) short and poor supply of basic modern technology inputs (seeds, fertilizers, feeds and breeds) poor irrigation facilities and drought (Shrestha and Nepal, 2016), higher cost of production and less competitive products (as compared with India), higher interest on agricultural credits and credits is also not available on time and poor pasture and communal grazing land (ADB, 2009; IFPRI, 2009; CBS, 2014). Seed is another critical factors only about 25 percent of HH found using improved seeds and the rest are using their own seed due to poor awareness on seed replacement as well as limited availability of improved seeds (ADB, 2009). Similarly, government funding in agriculture is not getting high priority, poor extension service (agriculture and veterinary) to the farmer's field and higher prices of fertilisers are other challenges for agriculture intensification in Nepal. There are also challenge in Agriculture commercialization due to uncompetitive agriculture as compare with neighbour country (India due to heavy subsidies for Indian farmers), subsistence production systems (poor market-oriented), poor physical infrastructure and poor market access, higher cost of production, declining public sector investment and weak coordination among stakeholders (central, regional, district level) in planning, monitoring and evaluation. Due to the 12 years armed conflict, food insecurity and lack of opportunities, including climate change and natural calamities (landslides, floods, earthquake etc.) (Malla, 2009), within and outside migration decreased the overall farm productivity both Terai as well as Mid-hills of Nepal.

3. Materials and methods

3.1 Research and Theoretical framework

The trajectories of change on the cereal-based farming system in Palpa, Nawalparasi and Dadeldhura district were analysed based on the changes explored on different demographic and agricultural practices from 1985 to 2015. The influence of the trajectories of change was analysed based on the different indicator used in the framework as presented in Figure 1.

Figure 1. Research framework showing influences on the trajectories of farm HH systems modified with (Cramb, 2014).

This research was carried out in three phases: research design phase, data collection phase, and data analysis and conclusion phase with six steps (Figure 2).

Figure 2. Research phase and steps.

3.2 Description of study site

The research was conducted in one Terai district (Nawalparasi) and two Mid-hills districts ( Palpa and Dadeldhura) of Nepal. The major demographic and agricultural characteristics of the Terai and Mid-hill agro-ecosystems are presented in Table 1.

Table 1. Major demographic and agricultural characteristics of the survey districts. Terai Mid-hills Particulars Nawalparasi Palpa Dadeldhura Demographic information1 Population (2011) 643,508 261,180 142,094 Population density/km2 298 190 92 Population growth rate (2001 to 2011) 1.34 -0.28 1.19 Total no of HH 128,760 59,260 27,023 HH having migration member 65,335 27,010 - Average HH size 5 4.41 5.25 Net migration rate (%) 13.9 -23.7 -12.2 Out migrants (%) 0.9 2.2 0.9 In migrants (%) 3.3 0.5 0.4 Own non-agricultural business, wage earnings (within and Major non-farm activities outside district and outside country), pension, loans etc. Agro-ecosystem information1 Common farm size, ha 0.74 0.77 0.64 Total area of agricultural holding, ha 56,125.20 11,616.80 11,616.80 Total arable land 51,023.70 10,231.50 10,231.50 Fodder + Grasses area, ha 305.8 56.6 56.6 Rice, maize, maize, wheat, potato, millet, barley, Stable food crops wheat, potato buckwheat, soybean Livestock Cattle, buffalo, goat, poultry, sheep, pigs Access to irrigation, ha 42,583.70 0 0 Access to agricultural market Average Poor Poor Climatic data Total annual rainfall2 2397(1778-3280) 1380 (450-2473) 1329 (790-1812) Topography3 (% of land) - Lower tropical (<300masl) 56.20% 0.30% 0.60% - Upper tropical (300-1000 masl) 34.90% 51.30% 34.70% - Sub-tropical (1000-2000 masl) 5.70% 47.30% 55.80% - Temperate (2000-3000 masl) 0 0 8.90% 1 (CBS, 2014), 2average data from 1987 to 2014 from Department of Hydrology and Meteorology, Nepal and 3 (CBS, 2013).

Nepal has four climatic seasons, namely summer (June to August), autumn (September to November), winter (December- February) and spring (March to May). However, the months mentioned in Table 2 considered for the further data analysis of diversity of crops and percentage share of crops in surveyed districts.

Table 2. Adapted month as per season for data calculation. Seasons Counted months Reason Summer June to September Some farmers harvest summer crops up to September. Winter October- February Farmers plant winter crops from mid-October and harvested up to February. Spring March-May Farmers plant some short duration crops or crops between winter and beginning of the summer season.

In Nepal, there are abundant rain in all districts during the rainy season from June to September. During the winter and spring, the average rainfall were very low that makes the water deficit during the winter which makes the lower productivity of crops during the winters and springs (Figure 3). However, there are slightly higher winter rain occurs in Dadeldhura as compare to the Palpa and Nawalparasi which showed the better option of winter crops and vegetable in Dadeldhura.

Figure 3. The average monthly rainfall pattern in Palpa, Nawalparasi and Dadeldhura from 1987 to 2014. Source: Department of Hydrology and Meteorology, Kathmandu).

3.3 Data collection

Primary and secondary data were collected; primary data were collected by using the semi- structured questionnaire (SSQ) with HH, FGDs with key farmers including key informants, and key informant interviews. Secondary data were collected by various secondary sources.

3.3.1 Selection of sites and participants

Three sites of each district were selected for the HH survey (Figure 4). Total number of surveyed HH in each sites of respective districts were presented in Table 3. A multistage sampling was used for the research where a selection of the district was the first stage, selection of VDCs as a second stage and selection of the HH as a third stage. Different types of the sampling were used for each step. Altitude, regional market access, distance to Indian border and rainfall pattern were the criteria used for selecting the district for the research. Similarly, this research was the part of a PhD research (2013-2017) under Farming System Ecology group of Wageningen University. Therefore, one Terai district (Nawalparasi) and one mid-hill district (Palpa) who have better access to a regional market, close to Indian boarder and different annual rainfall pattern were chosen.

Table 3. A number of surveyed HH and their altitude range in each site of survey Districts. Districts Survey sites No of Average altitude range of HH (masl) with HH min to max range Palpa Tansen Municipality 20 1254 (884-1410) (n=50) Boughapokharathok VDCs 17 1197 (1081-1302) Bandhipokhara VDCs 13 1323 (1000-1508) Nawalparasi Sunwal Municipality 26 112 (88-150) (n=67) Jahada VDCs 21 90 (87-103) Jamuniya VDCs 20 94 (85-105) Dadeldhura Amargadi Municipality 21 1283 (1228-1778) (n=63) Ashigram VDCs 20 1899 (1282-1993) Samaijhee VDCs 22 1515 (1443-1571)

After selecting the district, surveying clusters (VDCs and Municipalities) were selected by considering the mixture of the different ethnic communities and their involvement in agriculture. Then, the first HH was randomly selected in each district. After, snowball sampling method was used to select HH based on the ethnicity. The sample was not proportional to the total population of each ethnic group. Snowball sampling was taken due to the diverse and scattered nature of the HH in the communities. The interviewed HH were asked to point a farmers from the ethnicity searched. This method consist one finding the research unit (subject) and ask the unit (subject) to give the name of another subject to the researcher, who in turn provides the name of the third, and so on (Vogt,

1999). This process continued until the total number of HH was fulfilled as per the HH survey plan (Annex 1) in each district. The non-responding HH were avoided and if there was only one HH with one ethnic group in the community researched, then a HH from nearby community with same ethnic group was taken in order to reach the quota for that ethnic group.

Figure 4. Map of the research sites (Nawalparasi, Palpa and Dadeldhura). GPS coordinates and altitude range of the HH were taken by using the Gramini e-Trex 20 (Annex 2).

3.3.2 Secondary data collection

Secondary data were collected from different sources to validate the results obtained from the primary source of data. Data were collected from the Village Development Committee (VDC) /Municipality, District Agriculture Development Office (DADO), District Livestock Service Organization (DLSO) and other related organizations of each district. In addition to that, information from academic literature (research publications, books, etc.) was gathered on required aspects of the research.

3.3.3 Semi-structure questionnaire (SSQ)

A standardized SSQ was designed to fulfill the defined objectives of the research (Annex 3). Both, open (respondents gives his/her own answer to a question) and closed-ended (respondents to select answers from a list already given by the researcher) questions were used in questionnaires. The relevance and sequence of the questions were also considered while designing the questionnaire. The SSQ was developed to gather the information on the biophysical, socioeconomic characteristics, including drivers that lead towards changes on such activities. The following information were assessed from the SSQ based on the indicator mentioned in Table 4. A 180 HH survey (Annex 2) was conducted by using the SSQ in the selected study sites during September to November, 2015.

Table 4. Data on different aspects with their indicators S.N Aspects Indicators 1 Socioeconomic Age of respondents, HH size, education of respondents, sex ration, total factors annual income, share of agriculture income and non-farm income, non- farm activities, period of food self-sufficiency (FSS) etc. 2 Land use Size of land holding, types of land (owned, rented, etc.) land cover by crops, trends in land use (increasing vs. decreasing etc.). 3 Access to Access to extension service, access to markets, access to roads, access to resources inputs (improved seeds and inorganic fertilisers) etc. 4 Agricultural Diversity of agricultural crops, area and productivity of crops, crop Practices rotation pattern, challenges to agricultural production, number and types of livestock etc.

3.3.4 Focus group discussions (FGD)

Two FGDs were organized with groups of elderly people as key informant who had better understanding of the trajectories of changes in their local area. Accordingly, participants were selected among influential farmers; community representatives who have a better understanding of their local territories, and government agricultural development agents/service providers of respective study sites. Participatory mapping of the resources and timelines were employed to

14 gather better information and comprehensive understanding of perceptions of farmers in their local areas by simply sketches. FGD was focused to gather information on the farming systems, historical changes in access to agricultural resources and to determine the starting points for the trajectory analysis as per the checklist (Annex 4). Also, farmers were asked to identify the crucial periods that affected their farming systems during the predetermined period of study i.e. from 1985 to 2015.

3.4 Data analysis

Collected data were analysed by using the SPSS version 20, Microsoft excel, and R package. The means of the selected quantitative variables of HH demographic and socioeconomic data were calculated to analyse the changes from 1985 to 2015 by using SPSS statistical software version 16 (Field, 2009), excel and R software with ade4 package (Chessel et al., 2004). A principal component analysis (PCA) and cluster analysis were conducted in each of the districts to determine the farm types. The research focused from the year of 1985 as the social, political and economic transformation of the country started from 1990 as the country started to a constitutional monarchy in 1990. After that, the social, political and economic development started to grow considerably with major changes on agriculture sector. Hence, the study was conducted by keeping the year 1985 as a starting year of the study to understand the past observations and to predict the future projection and possibilities. The details of the methodology used in the data analysis for each individual are presented in each paragraph below.

Table 5. Data analysis methods used for demographic and socio-economic indicators Indicators Data analysis methods Age groups The mean age of the respondents per district was counted as an age of respondents. Age groups were calculated as; young- < 35 years, adult-between 36 to 64 years, and elderly people-> 65 years old. Education It was calculated based on level of education; no education-who did not join formal class, primary education-1 to 5 classes, secondary education- 6 to 10 class, and higher education- >10 class. Headship of HH Head of the HH is counted as a person who is more responsible for economic well-being of HH. Sex ratio (male to The sex ratio is calculated by dividing the number of males (of all ages) by the number female) of females (of all ages) and multiplying by 100. No of children It was calculated based on total number of kids less than 15 years per HH. Economically Average number of Economically active population (EAP) was counted for the total active population number of HH members with an age over than 15 years up to 64 years.

Indicators Data analysis methods Dependency ratio The dependency ratio refers to the number of dependent population over economic active population (Wöss and Türk, 2011) and calculated as: Dependency ratio: 100 × (population (0-14) + population (65+)) /population (15-64). Migration Calculated average number of members per HH migrated into different places for their jobs. - Outside district Number of HH member migrated into outside district but within country counted as an migration outside district migration. - India migration Number of family members migrated into different states (parts) of India. - Gulf migration Number of family members migrated into different Gulf countries (UAE, Dubai, Bahrain, Quarter, Lebanon, Oman) including Malaysia. - India + Gulf Number of members migrated into both India and any one Gulf countries. HH income Total annual HH income were calculated as the aggregate of agricultural income and non-farm income. Both crop components (income from sales of crops and vegetables) and livestock components (sales of livestock’s and livestock products including forage) were counted as agricultural income. Non-farm income HH non-farm income was derived from the income obtained from non-farm enterprises; remittance, seasonal labours, unskilled wage labours, services, small shops and trades - Remittance Income from remittance. - Seasonal Income from labour works during peak seasons; agricultural labour during peak labours agricultural seasons and other labours like cutting timbers, forage/grasses on a daily labour basis. - Unskilled wage Daily wage labour other than seasonal labour; labour work in construction, roads, house- labours building etc. - Services Income from temporary and or permanent jobs ( government and private) with monthly salary. - Small shops and Counted income from; general provision shops, tea shops, cloth shops and tailors, trades electrical goods shops, dairy-products stores, bookseller, Bamboo seller, fuelwood seller etc. HH expenditure HH expenditure was calculated based on the expense made on four categories; HH needs, investment in agriculture, healthcare services and children’s education. HH was asked to share their estimated amount in Nepalese rupees and or % value of expenditure on each category. Later, the value is converted into % fraction. - HH needs All HH expenses on foods, accommodation, cloths including some festive expenditure. - In Agriculture All investment in agriculture (crops as well as animal, inputs, labour). - Healthcare Expenses made on health care services and medicines for HH members. The very high services cost due to exceptional diseases is not considered for this. For example, cancer treatment for one family member. - Children All expenses made for education i.e. children education fees, dress, and stationary. education

Table 6. Data analysis methods of Agricultural indicators Agricultural Description of data analysis methods indicators Land use change It were classified into agricultural land, forest land and shrub land. - Agricultural land Land used for agriculture purpose (crops and vegetables) in % - Forest land Land covered by the permanent trees (forest), agroforestry etc. in % - Shrubs and forage Land covered by shrubs, bushes, young broadleaf regeneration and pasture grasses in %. land Diversity of crops Calculated based on total number of agricultural crops (cereals, legumes, pulses and (number) vegetables) that farmers grew for their HH needs and income sources. The trees and crops grown in kitchen gardens are not considered as a diversity of crops. Percentage share of Calculated based on the total counts of crops grown in their selected sample plots (2-4 crops plots) of HH from 1985 to 2015. The total number of plots were 135, 139 and 139 in Palpa, 188, 182 and 190 in Nawalparasi and 187, 189 and 186 in Dadeldhura during summer (June to September), winter (November to February) and spring (March to May) respectively. Adoption of improved Calculated based on the frequency of the total number of HH using both improved seeds seeds and inorganic as well as inorganic fertilisers for the first time since 1985 which later converted into a fertilisers (%) percentage value for each respective year from 1985 to 2015. Number of livestock An average number of buffalo, cattle, goat and poultry per HH were calculated based on their total number per HH in each year from 1985 to until the year 2015. Access to agricultural The access to agricultural extension services counted based on the number of a HH extension (%) which have an extension service since 1985. The HH which had an opportunity of participating training, facilitations, workshops, demonstration, exposure tours etc. from extension service provider consider as a HH having agriculture extension access. Access to markets and Access to markets and access to roads was measured based on the distance to market roads (km) and roads from HH during the different periods of times from 1985 to 2015. Problems of agriculture Respondents were asked to state the priority wise major problems for agriculture production production in the past 5 years. The index value of each problem was calculated based on the following formula. Indexing = ΣSi fi / N, where I = priority index, Σ = summation, Si = scale value at ith priority, fi = frequency of ith priority and N = total number of observation. Types of farming The Percent value is calculated based on the agricultural income index and tropical systems livestock unit index. Agricultural income index was calculated by dividing the agriculture income of each HH by overall average national income of the HH. Subsistence system with index less than 0.80, semi-subsistence with 0.81 to 1.50, market oriented system with 1.51 to 5 and commercial system with index greater than 5. Types of household Categorized based on the size of the land holding and tropical livestock unit. Weighted index value was calculated based on the index value of land holding and TLU index. Land holding index was calculated by dividing the land holding of household by overall average national size of the HH (0.74ha). Similarly, TLU index calculated by dividing individual TLU1 of HH with average national TLU (2.4). Then average weighted index value is calculated (based on this two land holding index and TLU index). Low resource HH is those with weighted index less than 0.6, medium to low resource HH with 0.61 to 1, medium resource HH is those with vale 1-1.5 and wealthier resource HH is greater than vale 1.5.

Tropical livestock conversion units are as follows: Buffalo=1, cattle=0.70, goats=0.10, pigs=0.20 and chicken=0.01(Maltsoglou and Taniguchi, 2004; Chilonda and Otte, 2006).

4. Results

4.1 Demographic and socio-economic characteristics

The demographic and socioeconomic characteristics are presented in Table 7 and Table 8. The average age of the respondents were 57, 51 and 44 years in Palpa, Nawalparasi and Dadeldhura where, the majority of the respondents were between age groups of 36 to 64 years. However, one- third of the respondents in Dadeldhura was younger (< 35 years) and almost exact proportion of the respondents in Palpa was elderly people (> 65 years). In all three districts, more than 60% respondents was female with a higher figure in Nawalparasi (70.15%). Similarly, greater than 60% respondents were head of the HH in all three districts. Generally, male headed HH was dominated both in Palpa (52%) and Nawalparasi (61.19%) and female headed HH was dominated in Dadeldhura (51%).

The literacy rate of the respondents remained quite low. The majority of the respondents had an education in between primary and secondary levels (50% in Palpa, 60 % in both Nawalparasi and Dadeldhura) in all three districts. On the other hand, there was also a higher percent of the respondents without any formal education in all three districts and Palpa dominates (52%) the other two districts in case of illiterate respondents.

The average HH size of the district were 7 members per HH in Palpa and 6 members per HH both in Nawalparasi and Dadeldhura (Table 7). Almost more than 70% of the HH are medium size (5 to 9 members per HH) in all three districts. Only 15 to 20% HH are small sized (up to 4 members) HH. However, Palpa had a higher % of larger size HH than the other two districts (Figure 5a). HH size was decreased by 6.41%, 19.90% and 20.28% in Palpa, Nawalparasi and Dadeldhura respectively from 1985 to 2015 (Table 7). For the sex ratio, it was higher in Dadeldhura (121.06) and recorded almost equal in Palpa and Nawalparasi with around 100 males per 100 females. Around 2 numbers of the HH members were children under 15 years in Dadeldhura and almost one member in each district were elderly people. The higher dependency ratio was recorded in Palpa (81.06%) and an almost equal dependency ratio of around 52% found in Nawalparasi and Dadeldhura. More than 50% HH have migration with at least one person per HH in all three districts. The proportion of the migrating HH were around 44 to 53% increase from the year 1985 to the year 1985 (Table 7).

Table 7. Changes on demographic and socioeconomic indicators from 1985 to 2015.

Although, more than 70% of the HH depend on agriculture for their livelihoods, income from this sector does not play the crucial roles on the total annual HH income, which mainly contributed by the non-farm sources. The non-farm income source dominates greater than 75% in all three districts with 92% in Palpa and 80% in Nawalparasi. Only one fourth of annual income comes from agriculture sector in both Nawalparasi and Dadeldhura and only less than 10% of agriculture income contributed to the total HH income for Palpa.

Table 8. Demographic and socioeconomic characteristics of the HH in three districts. Demographic and socioeconomic characters of HH Districts Palpa Nawalparasi Dadeldhura Average age of respondents (year) 57 51 44 Young respondents (<35 year) % 8 10.45 31.75 Adult respondents (36-64year) % 58 79.10 61.90 Elderly respondents (>65 year) % 34 10.45 6.35 Gender composition of respondents Male (%) 40 29.85 39.68 Female (%) 60 70.15 60.32 HH head composition of respondents Male headed HH (%) 52 61.19 9.52 Female headed HH (%) 22 16.42 50.79 No HH head (%) 26 22.39 38.10 Education of respondents None (No education) (%) 52 35.82 36.50 Primary (up to 5 classes) (%) 12 29.85 39.69 Secondary (6 to 10 classes) (%) 36 32.84 22.22 Post-secondary (Post SLC) (%) 0 1.49 1.59 Population structure of HH Sex ratio (males per 100 females) 106.50 99.72 121.06 Average number of kids 1.30 1.42 1.73 Average no of economically active population (EAP) (16-64 4.98 4.61 4.08 year) Average no of elderly population (> 65 years) 0.58 0.37 0.50 Dependency ratio 81.06 51.14 52.04 HH depend on Agriculture (%) 88.00 70.15 76.19 Total annual income of HH (USD) 3103 2767 1523 Non-farm income (%) 91.88 80.28 74.13 Agriculture income (%) 8.12 19.72 25.87 Annual expenditure of HH HH needs (%) 61.04 68.09 60.25 Children education (%) 10.42 7.82 17.72 Healthcare (%) 9.03 10.11 9.22 Agriculture investment (%) 19.51 13.92 12.81

Figure 5. HH size (a) and types of migration pattern (b) in Palpa, Nawalparasi, and Dadeldhura at 2015.

Overall, there was a higher variation in total annual income per HH in each surveyed district. Palpa district ranked first for higher HH annual income (USD 3103) followed by Nawalparasi (USD 2767) and Dadeldhura (USD 1523) (Table 8). This income is solely determined by the non-farm income source (especially from remittance and seasonal labour). Only less than 10% migration was outside district migration and the rest of the migration places were outside the country. Among the surveyed HH, the majority of the member migrated into the India (35%) from Dadeldhura whereas from Palpa and Nawalparasi almost around 25% went to the Gulf (Figure 5b).

Although income from agriculture sector is quite low, the cumulative investment in this sector (both on crop cultivation and livestock rearing) is quite high. There were around one fifth of investment in this sector where HH from Palpa district invests maximum (19.51%) than the other two districts. The majority of the HH had a higher expenditure (<60%) for their basic HH needs (foods, clothes, and shelter) in all three districts. Similarly, every HH made an expense of around 10% for the healthcare services. HH from Dadeldhura expenses more (17.72%) on their children’s education as they have a higher number of children in their HH as compare to the other two districts. Overall, HH from all three districts were recorded food deficit for 3 to 5 months during off season. Higher FSS was observed in Nawalparasi (9 months) district than the other two districts. Overall, FSS period of HH has increased around 16 to 33 % since 1985 to 2015 (Table 8).

4.2 Land use patterns and access to resources

4.2.1 Land use pattern

The average land holding of the HH was 0.74, 0.77 and 0.65 ha in Palpa, Nawalparasi and Dadeldhura where 56%, 60% and 69% of land are used for the agricultural purpose in Palpa, Nawalparasi and Dadeldhura at 2015. The relation between age and total land holding are presented in Figure 6. The majority of the respondents is adult group having less than 1 ha total land holding in all surveyed districts.

Figure 6. Relationship between average size of landholding (ha) and age of the respondents in Palpa (a), Nawalparasi (b) and Dadeldhura).

The major land use patterns of the HH are agricultural land, forest land and shrub land. The major area used for the agricultural purpose, however there are still a huge area covered by the forest and shrubs in Palpa and Dadeldhura (Figure 7). Agriculture land holding of the HH were 97% in Nawalparasi, 45% in Palpa and 48% in Dadeldhura. Similarly, exact 41% of the land were covered by the forest in both Palpa and Dadeldhura, however, this was very negligible in Nawalparasi. Similarly, shrub land was around 11 to 14 % in both Palpa and Dadeldhura.

Figure 7. Percentage of agricultural land, forest land and shrub land per HH in Nawalparasi (a) Palpa (b) and Dadeldhura (c) in 2015

Based on the information gathered from FGDs (Annex 5 and 6), timeline study (Table 9) and key informant interview (Annex 7), the qualitative land use change since 1985 until 2015 in all three survey district are presented in Figure 8. Generally, in all three districts, there has been a significant change in land use pattern and different land use practices for home consumption changed into market-oriented land use practices.

Figure 8. Qualitative land use change in Palpa, Nawalparasi and Dadeldhura since 1985 until 2015. Figure format adopted from (Speelman et al., 2014). The dotted lines represents the decreasing trends.

4.2.2 Access to agricultural extension services, markets and roads

The pattern of access to agricultural extension services, markets and roads in Palpa, Nawalparasi and Dadeldhura district since from 1985 until 2015 were presented in Figure 9. The agricultural extension services to the HH increased rapidly from the year 2000 in all three districts. During the period of 1985, only less than 5% HH have access to an agricultural extension which remains almost same up to the year 1995. After the year 1995, there is an increasing trend of the extension services and after this period, it increased with faster rates and reached to around 40% for all three districts at 2015.

However, HH from Nawalparasi districts has higher agricultural extension services (43.28%) than HH from other two districts (around 36%), which seems an almost similar pattern. There is a rapid increase of the extension services in Dadeldhura from 2005. On the other hand, the distance to markets and roads from HH decreased from 1985 (Fig 9 b, c). The distance to market was around 4.5 km in Dadeldhura during the period of 1985 which is later reached in around 3 km. Similarly, the distance to market is also reduced from 3 km to around 2.5 km in Palpa and 2.5 km to 2 km in Nawalparasi. Access to roads from their HH was also decreased since 1985, however, there are almost no changes on road access in Palpa and Dadeldhura up to 2000 with the only slight decreasing trend in Nawalparasi. But after the period of 2000, there are better access to roads in all HH if we compare the road access to 1985.

Figure 9. Access to agricultural extension services (%), market (km) and roads (km) in Palpa, Nawalparasi and Dadeldhura from 1985 to 2015.

4.3 Changes in Agricultural practices

Changes in the different agricultural practices like changes on the diversity of the crops, crops rotation, percent share of crops, adoption of fertiliser and improved seed, and productivity of the major cereals are explored from 1985 to until 2015. Mainly, diversity of crops and percentage share of crops were counted based on the seasons of the Nepal (Table 2).

4.3.1 Changes in diversity of agricultural crops

The diversity of the agricultural crops grown in the HH has increased linearly over the time since 1985 in all three districts (Figure10). However, the diversity of the crops is higher in Palpa and Dadeldhura than Nawalparasi from 1985 to 2015. There are only 5 to 6 different number of crops grown annually in all three districts during the periods of 1985 which increase 64%, 80% and 99% from 1985 to 2015 in Palpa, Nawalparasi and Dadeldhura respectively. The growth rate of the number of crops in Palpa and Nawalparasi are almost similar (13%) while in Dadeldhura, the growth rate over the time is 18%. After the year 2007/8, the growth of the numbers of crops in Dadeldhura slightly exceeded Palpa. However, current diversity of the crops in Nawalparasi is quite lower (around 8 different crops) as compared to Palpa and Nawalparasi where an average number of crops per HH are around 10 crops.

Figure 10. The diversity of crops (total number of crops per year) in Palpa, Nawalparasi and Dadeldhura from 1985 to 2015.

Table 9. Timeline study of the survey sites1

1 Time line information were compile based on the information gathered from FGD, Key informant interview.

4.3.2 Changes in percentage share of different crops

The percentage share of the different types of crops per HH during summer (June- September) and winter season (October-February) are presented in Figure 11. Similarly, spring (March-May) is presented in Figure 12. There have been significant changes in the percentage share of different crops per HH since 1985 in all three districts during the summer, spring and winter season except rice in Nawalparasi.

During summer, maize-based cropping systems, especially sole maize practice, maize with rice - beans as mixed crops are dominating in Palpa. However, there are almost constant pattern observed for the maize with rice bean and maize mixed with other crops whereas percentage share of sole maize decreased considerably since 1985. Also, percentage share of the millet is decreasing from 10% at 1985 to almost around 2% at 2015 in Palpa (Figure 11a). Similarly, in Nawalparasi, 90% of the HH has been growing rice with constant pattern since 1985. However, the percentage share of vegetable and other crops are constant until 2002. After this year, the percentage share of vegetables increased and other crops (other than rice and vegetables) decreased considerably (Figure 11b).

Figure 11. Percent share of different types of crops during summer (June to September) and winter (November to February) from 1985 to 2015 in Palpa, Nawalparasi and Dadeldhura. The figure a, b, c represents the percentage share of summer crops and figure d, e and f represent the percentage share of winter crops in Palpa, Nawalparasi and Dadeldhura respectively.

At present, the percentage share of vegetable reached to around 10% during summer in Nawalparasi. in Dadeldhura, the share of maize with soybean and vegetable increased linearly, however, the rest of the crops decreased from 1985 during the summer season (Figure 11c). The maize with soybean as a mixed crop dominates with higher % as it covers greater than 30% area per HH in Dadeldhura at 2015. The vegetable reached to around 20% in Dadeldhura which was quite higher than the other two districts.

During the winter season (November to February), percentage share of the winter cereal decreased in all three districts (Figure 11e). The share of the winter cereal was around 50% in Dadeldhura and Nawalparasi during 1985 which was plunged into around 30% in 2015. However, there was increasing percentage share of vegetable since 2005 in all three districts. Among the three districts, there is a higher percentage share of vegetables per HH (35%) in Nawalparasi as compared with Palpa and Dadeldhura. The percentage share of winter vegetables in Palpa and Dadeldhura are almost identical during the year 2015 (Figure 11d). The sole mustard and mustard mixed with lentil are the other major crops during the winter season in all three districts. The percentage share of the mustard mixed with lentil seems almost constant, with only less than 5% changes since 1985. On the other hand, percentage share of sole mustard decreased in Nawalparasi, remained constant in Dadeldhura and slightly increased in Palpa since 1985 (Figure 11e).

During the spring from March to May, there are more than 50% land remained fallow. The higher fallow pattern of their land was observed in Palpa, followed by Dadeldhura and Nawalparasi from 1985 to 2015 (Figure 12). At 2015, the percentage share of fallow was more than 75% in Palpa and Dadeldhura and 40% in Nawalparasi. There has been slightly decreased percentage share of fallow since 1985 however, the figure of fallow land still considerably higher in all three districts. On the other hand, there is an increasing trend of growing vegetable in spring season since 2000, which reached to 30% in Nawalparasi, around 25% in Palpa and 15% in Dadeldhura at 2015.

Figure 12. Percent share of fallow period and vegetables during the spring season (March-May) from 1985 to 2015 in Palpa, Nawalparasi, and Dadeldhura. 28

4.3.3 Changes in cropping pattern and composition of crops

Different types of cropping pattern exists across the country depending upon the topography and altitude ranges in Nepal. Normally, the rice-based cropping system dominates in Nawalparasi and maize-based cropping system dominates in both Palpa and Dadeldhura. The major cropping pattern are presented in Table 10. During the period of 1985 to 1995, cereal- based cropping patterns dominate for all three districts. Until 1995, the major cropping patterns were rice-wheat-fallow and rice-mustard (+lentil) -fallow in Nawalparasi. Similarly, in Palpa and Dadeldhura, the major cropping pattern were maize (+millet) -wheat-fallow, maize (+soybean) - mustard (+lentil) -fallow and maize+rice bean-wheat/mustard-fallow respectively (Table 10). Similarly, in between 1995 to 2005, introduction of the short duration varieties and cash crops were major changes (Table 10). The major cropping pattern in Nawalparasi were rice-wheat/winter maize-fallow, rice-mustard+lentil/vegetables- fallow/maize. in Palpa and Dadeldhura, the major cropping pattern during this period were maize+millet-wheat-fallow, maize+ soybean-mustard+lentil-fallow etc. After 2005, the vegetable was grown over the all seasons with different combination of cereals, pulses, legumes and forage crops. The general seasonal calendar of the crops are presented in Annex 8.

Table 10. Major cropping pattern from 1985 to 2015 in Palpa, Nawalparasi and Dadeldhura.

Note: Symbol – represents seasonal difference, ,+ represents the mixed systems and / represents and or.

4.3.4 Adoption of improved seeds and inorganic fertilisers

There have been a gradual temporal changes on both adoptions of improved seed as well as inorganic fertilisers from 1985 to 2015 (Figure 13). There were almost no adoption of the improved seeds as well as inorganic fertilizers up to 1995 in all three districts. There has been an increasing adoption rate of both improved seeds and inorganic fertilisers among HH since 1995. The adoption rate of improved seeds and inorganic fertiliser seems very similar in Palpa and Nawalparasi. The higher adoption of improved seed (50% each) found in Palpa and Nawalparasi after 2012/13 whereas, in the Dadeldhura, just around 25% % of the HH used improved seeds (Figure 13a).

There is an earlier adoption of the chemical fertilisers with a higher % of HH in Palpa as compared with Nawalparasi and Dadeldhura. However, Nawalparasi beats Palpa on adopting inorganic fertilisers since 2010 (Figure 13b). Up to 2005, there was only around 10% HH used urea as an inorganic fertiliser in Palpa and Nawalparasi which later rocketed into more than 35% in Palpa and 50% in Nawalparasi respectively. In Dadeldhura, the % of the HH using inorganic fertiliser increased slowly from 2003 to less than 5% of HH and reached around 20% in 2015.

Figure 13. Adoption of improved seeds (a) and inorganic fertilisers (b) in Palpa, Nawalparasi and Dadeldhura from 1985 to 2015.

4.3.5 Productivity of the crops

In general, the productivity of the cereal increasing over the time series and yield growth rate of rice, wheat and maize are positive except the few years (Figure 14). There are quite fluctuation of productivity among the each district during the entire periods from 1985 to 2015. There was a lower productivity of rice at 1992 in Palpa and Dadeldhura. Similarly, the sharp decrease of wheat at 1993 in Nawalparasi and at 2001 in Dadeldhura which also decline in Palpa and Dadeldhura again in 2009. There are quite lower productivity during the early 10 years of the time periods for all rice, wheat, and maize. However, after the year 2010, there are increasing trend of productivity of cereals in all districts (Figure 14).

Figure 14. The productivity of major cereals in Palpa, Nawalparasi, and Dadeldhura from 1985 to 2015. Secondary data taken from Ministry of Agriculture and Cooperatives (MoAD).

4.4 Changes in Livestock numbers

The annual average number of buffalo, cattle, goat and poultry per HH were decreased from 1985 to 2015 except cattle in Dadeldhura which showed the increasing trend (Figure 15). The average annual number of buffalo were 3 in Palpa and 2 for both in Dadeldhura and Nawalparasi during 1985 which reduced to 2 buffalo in Palpa and 1 buffalo per HH in both Dadeldhura and Nawalparasi at 2015 (Figure 15a).

Similarly, an average number of cattle per HH also decreased since 1985 in Palpa and Nawalparasi, however, there was an increasing trend of an average number of cattle in Dadeldhura. The average cattle number per HH were 3 in Palpa and 2 in both Nawalparasi

31 and Dadeldhura at 1985 which after 3 decades changes into 3 numbers per HH in Dadeldhura and 2 in Palpa and remains 1 in Nawalparasi (Figure 15b). After the period of 2000, there was an increasing trend of an average number of cattle per HH in Dadeldhura with 3 average number of cattle per HH at 2015. Similarly, after 2010, there was also increased trends of cattle in Palpa.

For goats, average number per HH decreased in Palpa and Dadeldhura, however, in Nawalparasi, it remained constant over the time series with slightly increasing trend after 2005. The average number of goats per HH were 7 in Palpa, 5 in Dadeldhura and 3 in Nawalparasi which reduced into 5 numbers in Palpa, 3 numbers in Dadeldhura with the same number in Nawalparasi.

During the period of 1985 to 1995, there were a negative growth rate of livestock and poultry, however, after 1995 onwards, there was a positive growth rate of a number of cattle in Dadeldhura (Figure 15). The 29% to 41% of negative growth rate was found for buffaloes from 1985 to 2015 with higher negative figures in Dadeldhura. Similar types of a pattern were also observed for the cattle with the negative growth rate of 30 to 48% in Palpa and Nawalparasi, however, there was a positive growth rate of cattle in Dadeldhura with a 44 % increase from 1985 to 2015. For the goats, the high negative growth rate was in Dadeldhura (-55.59%) followed by Palpa, but there was almost constant pattern of growth of the goat in the Nawalparasi (-0.52%). There was greater than 25% negative growth rate of poultry observed in all districts from 1985 to 2015.

Figure 15. An average number of buffalo (a), cattle (b), goat (c) and poultry (d) per HH in Palpa, Nawalparasi and Dadeldhura from 1985 to 2015.

4.5 Problems for agriculture production

Overall, lack of irrigation, wild animals, timely availability of agricultural inputs, labour shortage, lack of extension services and bad weather condition are the major problems for agriculture production in three districts (Table 11). However, some problems are major in one district would not be the problems for the other district.

Lack of the irrigation is the main dominating problems with the first rank for the agricultural production in all three districts. The loss of the standing crops by the wild animals was another major problem in Palpa and Dadeldhura. Many wild animals (monkey, porcupines, wild deer etc.) create the significant loss of the crops in Mid-hills. The monkey was the major problems among wild animals as they eat the harvestable product and sometimes also made a physical damage before the prematurity phase of the crops. However, this problem was almost negligible in Nawalparasi.

Other important problems are the labour shortage during the peak season and lack of timely availability of the basic inputs including the bad weather conditions. There are also other minor problems like lack of extension services, market price, insects and disease in all districts.

Table 11. Problems of agriculture production in three districts.

Note: No of HH=total number of HH mentioning each problems, value=total index value for each problems.

4.6 Drivers of agriculture intensification

The main drivers based on the farmers perceptions that are associated with the intensification of the agriculture production are presented in Figure 16. Those drivers are international (I), national (N) and local (L) levels which have greater influences on different periods of times on the agricultural system and intensification of the agriculture in the three districts (Figure 16). Among the national drivers, national agricultural policies and projects greatly influence the intensification of the agriculture. However, many local drivers like local projects, local technology transfer and demonstration program from privet as well as government side have higher impact on intensification of the agriculture in the survey sites. The major drivers are grouped into different headings which are describe in each separate paragraphs below.

Figure 16. Drivers of intensification of agriculture in Palpa, Nawalparasi and Dadeldhura. L- local, N-national and I-international drivers.

4.7 Changes and shifting of the farming systems

The four types of farming systems are classified based on the income from the agriculture sectors, different intensification activities and major crops as well as livestock’s production practices (Table 12). Subsistence farming system covers a huge proportions of the farming systems in all three survey districts with around 40 to 50% coverage (Figure 17). Similarly, the semi-subsistence farming systems also represent second huge coverage with 19 to 40%.

However, market oriented production system has been increasing so far which account the 10 to 24% in the survey district at 2015. Higher market oriented production systems was observed in Nawalparasi followed by Dadeldhura and Palpa respectively. Overall, the subsistence to semi-subsistence farming systems counts for around 80 % in all three districts.

Table 12. Different types of farming systems with their description

1 is the average income of HH from agriculture in the country.

Figure 17. Percent share of different farming systems in Palpa, Nawalparasi and Dadeldhura at 2015.

4.8 Typologies of farming HH

The selected socioeconomic and agricultural variables were: size of the HH, percentage share of hire labour, investment in agriculture (%), access to market (km) nonfarm income (%), food self-sufficiency (months) and tropical livestock units of Palpa, Nawalparasi and Dadeldhura. The eigenvalue obtained from each PCAs was used to determine the number of components to be included in the farming system’s trajectories analysis (Annex 9). The correlation circles for the principle components PC1-PC2 and PC1-PC3 were presented in the Figure 18.

Based on the eigenvalue, the first three PC with eigenvalue greater than one were selected for the analysis. The first three PCs explained the 55.87%, 53.51% and 50.51% of the total variation of the farm diversities in Palpa, Nawalparasi and Dadeldhura (Figure 18). Among them, the first PC solely explained the 23%, 24% and 20% of the total variance in Palpa, Nawalparasi and Dadeldhura. For Palpa, the first PC was associated with food self- sufficiency, HH size and access to markets with negative loadings. However, hire labour (%) and agriculture investment were positively associated with PC1. The second PC describe 18% variance and was associated with non-farm income and land holding of the HH also with negative loading. Third PC was associated with tropical livestock units. For Nawalparasi, the first PC was associated with food self-sufficiency and tropical livestock unit with negative loadings. Second PC which describe 16% variance was associated with market access, non- farm income and food security with positive loadings. Similarly, third PC with 13% described variance was associated with HH size with positive loading and land holding with negative loading. in Dadeldhura, the variance of the first PC was associated to tropical livestock unit, agriculture investment with negative loading and market access with positive loadings. The second PC explain 16% of the variance in Dadeldhura.

Table 13. Types of HH and their average value of each indicators.

Based on the variables used of resource endowment and using the principle component analysis, all 180 surveyed HH were grouped into 4 farm types: larger and wealthier farm, medium resource HH, medium to low resource HH and low resource HH by adopting (Tittonell et al., 2010) (Table 12). The wealthier HH with higher resource endowment are those having higher land holding (>1.4 ha) and higher tropical livestock unit (> 4.5) with medium to higher food self-sufficiency (6-12 months). The second group; medium resource HH are those with medium land holding (around 0.7 ha) and medium tropical livestock unit (3-4 unit) with medium to higher food self-sufficiency (5-12 months). Similarly, medium to low resource HH are those having medium to lower land holding and TLU with medium to lower food self-sufficiency with lower hire labour % and medium investment in agriculture. Finally, low resource HH are those with small land holding and lower TLU with lower food self-sufficiency with lower hire labour and lower investment in agriculture. This type of HH highly depends on nonfarm income source (61 to 95%). Overall, 12 to13% HH are wealthier HH with higher resources, 17 to 54% of HH in medium resources, 18 to 24% medium to low resources and 16 to 46% low resources HH in the surveyed districts.

Based on the indicators used for the study, three broad types of livelihood strategy are classified as described by (Dorward et al., 2009): hanging in, stepping up and stepping out. HH which only maintain and protect the existing levels of wealth and welfare in the face of threats of stresses and shocks with only survival and coping strategies (surviving through a mix of local farm production, labouring and off-farm income earning) considered as hanging in. Similarly, HH which involve investments in assets to expand the scale or productivity of existing assets and activities through local production are considered as a stepping up. Those HH which have the strategies of accumulation of assets to allow investments or switches into new activities and assets by diversifying income sources, including off-farm work are considered as a stepping out.

The average farm income of the HH is NRs 15000 (around 150 USD) and mean annual income of the Nepalese HH is NRs 48, 366 for 2010 (FAO, 2010) which is almost equivalent to 500 USD. This 500 USD is taken as a reference value below 500 USD is considered a lower income and hanging in group. The average per capita GDP is only 140 USD per agricultural workers in Nepal (IFPRI, 2012). Based on the income for the agriculture source, the majority of the HH earn less than 1000 USD annually Figure 18. There are around 77% of HH which have less than 500 USD annual agricultural income in the survey district. Only 12% HH have agricultural income range of 500 to 1000 USD and only 11% of the HH with more than 1000 USD per annum. This reflects that almost the majority of the HH are subsistence and falls under the hanging in livelihood strategy with severe poverty traps. Only few HH are in stepping up (12%) and stepping out (11%) position if we consider 500 USD income from agriculture as a bench mark.

1 Figure 18. Correlation circle of the PC1-PC2 and PC1-PC3 in Palpa (a), Nawalparasi (b) and Dadeldhura (c) as a output of the PCA and cluster analysis. The direction and length of the arrows within each circle showed the strength of the correlations between variables, and variables and PC's.

1 hhsize-HH family member (number), area- HH land holding (ha), hirelab-Hire labour % of HH, aginvest-Investment in agriculture per HH (%), market-Market access (km), nfincome- percentage share of non-farm income per HH, foods-Food self-sufficiency (months) and tlu- Tropical livestock unit.

Figure 19. HH total annual agricultural income with respect to agricultural investment (%) and their potential livelihood strategies. The USD 500 taken as a reference value and less than USD 500 considered as a hanging in HH, 500 to 1000 as a stepping up HH and more than 1000 stepping out HH.

5. Discussion

5.1 Demographic and socioeconomic characteristics of the HH

The majority of the respondents were the HH head either as a male headed and or female headed in survey districts. The higher quantity of older respondent in Palpa was because the higher number of respondents were head of the HH. The high percentage of the younger respondents in Dadeldhura was because a high number of the respondents were not a head of HH. Similarly, the higher female respondents in all three districts was because of the migration pattern of the country as most of the male members from HH went to India and another country looking for work opportunities (CBS, 2001). This headship of the HH governed by many factors (Sproule et al., 2015) like age (older), sex (generally, but not necessarily), economic status (main provider), access to and control over resources etc. (Adhikari, 2011). Generally, the male were dominating as a head of the HH and female dominated only if the male migrated and only if male doesn’t have any formal education and or if they are widowed. Generally, male headship rate is higher in Terai and female headship rate is higher in mid-hill region of Nepal due to male selectivity of out migration from hill (Kayastha and Shrestha, 2003).

The literacy rate of the respondents from all three districts remains quite low as education facilities in the rural area started and the majority of the HH members who were born before the 1980s, got a poor chance to admit schools all survey districts due to the lack of schools in their communities. The literacy rate of the respondents was in line with the national literacy rate of 65.9 % (CBS, 2012). Generally, the head of the HH is less likely to be educated and if educated, they have on average less education than other members of the family as they are responsible for arranging all basic needs of HH including health and education.

The size of the HH has decreased since 1985 to 2015. However, the size of the HH in Palpa, Nawalparasi and Dadeldhura is slightly higher than the national average of HH size of 5 members per HH in 2011 (CBS, 2012). In average 2 members of HH were children and one member was elderly people in all the surveyed district. The higher number of both children, as well as elderly people in the HH bring the highest dependency ratio which means that almost half of the population per HH depends on other members of their HH in all three districts. Maharjan and Khatri-Chhetri (2006) reported the more than 40% dependency ratio per HH in Nepal.

The non-farm income sources for the HH played the crucial role on total annual HH income (Seddon et al., 2002; Joshi and Pandey, 2006; Reardon et al., 2007). The remittance and seasonal labour dominate the source of non-farm income in all surveyed HH. Over half of the HH are involved in foreign labour migration (Sunam and McCarthy, 2015) and almost 32% of the HH received remittance in Nepal (Devkota, 2007) which help to reduce the poverty of the HH (Joshi et al., 2015). Due to the lack of capital or skills or both, the economic opportunity in rural HH is very limited which influences the EAP for migration to foreign

41 countries and labour from Nepal spreading over the east, south-east, south and west Asia to perform unskilled jobs. About 8 million Nepalese are in India and half-a-million in the Gulf countries (Devkota, 2007; Poudyal, 2010). The difference in non-farm income was due to the variation in the migration place as most of the HH members from Dadeldhura went to India (with lower wages/salary) and people from the other district ( Palpa and Nawalparasi) prefers the gulf countries that offer higher salaries which created the huge gap on their earnings.

Although income from agriculture sector is quite lower, the cumulative investment in this sector (both on crop cultivation and livestock rearing) is quite high. There were around one fifth of investment in this sector. Similarly, another important sector of HH expenditure is the children education. The higher expenses made in this sector in Dadeldhura was due to the high number of children in each HH as compare to the other two districts.

The higher FSS in Nawalparasi (9 months) are due to the district located in the Terai with higher rainfall, which favours better agriculture production as compare to the other two districts. Similarly, food security situation of the HH is not optimal in all there survey district as there were one fourth of the year with food deficit. Small land holding of the HH and lower productivity, migration and recent shifting of the land use patterns are the major drivers responsible for the food self-insufficiency (Joshi and Maharjan, 2007). The major ways to cope HH food security and combat poverty situation is to use the non-farm income source (CBS, 2001; Devkota, 2006; Sunam and McCarthy, 2015). The huge investment in agriculture sector with lower productivity, cultural expenses (dowry, death rituals, and marriage), health expenses and loss of land of HH stepping down toward the vicious cycle of poverty (Sunam and McCarthy, 2015).

5.2 Land use patterns and access to resources

The most of the land use in Nepal is for agriculture and pastoral purpose. Land in the mountainous region is used in small percentage for the agriculture as compared with Terai (Gautam et al., 2003; Phuyal, 2013; Tiwari and Joshi, 2014). There have been many changes in the land use pattern since 1985, for example, one important change within the non-forestry land use was increased fragmentation of lowland agricultural areas due to urbanization and increased crop diversification in the remaining lowlands (Paudel et al., 2016). Similarly, winter cropped agricultural area in mountain and fragmentation of non-forestry land increased and forest as well as shrub land changed into agricultural land are the major land use change (Gautam et al., 2003). Jaquet et al (2015) mentioned that land use is changing due to the changed demographic pattern and outmigration. The outmigration of males from HH for their income has a huge impact on the livelihood of HH as well as in agriculture as it leads to a labour shortage and increased the work burden on women (Gartaula and Niehof, 2013; Jaquet et al., 2015) resulting towards the change in agricultural practices and land use pattern.

In the last three decades, land use pattern of the HH changed from the subsistence cereal- based pattern to a market-oriented production system with the introduction of different new

42 approaches and practices (Figure 18). The general intensification steps showed that, there are changes in farming practices and the introduction of the new tools and techniques for farm production. Similarly, HH have better access to agricultural extension services and other inputs.

Among the three survey district, the higher extension services were found in Nawalparasi because of the flat topography that characterized the Terai and allow better road access. However, in Dadeldhura, increased construction of the agricultural roads and implementation of the different local and governmental project increase the access to agricultural extension. Similarly, the distance to market and roads also decreased and HH have a better market and road access due to the same construction of roads resulting to increase the local market due to better road access (Khanna, 2016). Before 1990, the market was only the district headquarter but now the situation changed and there are few local markets established in the communities. The government policy under the eight plan during the period of 1992 to 1997 with major emphasis on extension services through grassroots Agriculture Service Centres (ASCs) is the main reason for the expansion of extension coverage in the country (FAO, 2010). Later Agriculture perspective plan (APP) from 1995 to 2015 and National agriculture policy (2004) as well as agricultural extension strategy (2007) plays the crucial roles for increasing agricultural extension services to the farmers.

5.3 Changes in Agricultural practices

There has been a significant changes in the different agricultural practices both in Terai as well as Mid-hill districts. The diversity of the crops, adoption of the improved seeds, inorganic fertilisers, and higher productivity increased since 1985. In the country, most of the agricultural technologies have been promoted in the last 20 years (Manandhar et al., 2009). The introduction of the improved seeds and high yielding varieties of different crops not only increase the diversity of the agricultural crops, but also changed the cropping pattern of the HH. Deshar et al (2013) reported that due to the stagnant and decreasing productivity of the cereal, many farmers shifted to growing cash crops.

The major reasons of the increasing diversity are the introduction of the high yielding modern varieties and new crops as an alternative source of income, increased awareness on high- value crops, increased access to resources (seeds, fertilisers), agricultural extension services and markets. There has been a trend of adopting different commercial crops like cauliflower, cabbage, tomato, okra, cucurbits as well as forage crops during the different time periods which increased the diversity leading to increasing land equivalent ration (Jaquet et al., 2015) and land productivity (Li et al., 2009) in all survey district. Bhatta et al (2015) mentioned that farmers responded based on their available resources and climatic conditions. He further added that farmers responded more frequently to the market-related drivers than climatic stressors. Some farmers also consider the importance of the secondary products of crops like straw from rice, wheat and maize and some want to improve the soil fertility condition by incorporating legumes for nitrogen fixation. Some adopt labour intensive crops as most of the HH have a higher number of family migration for the income (Joshi and Pandey, 2006). The

43 diversity of the crops (types of crops as well as varieties and cultivars) are crucial for securing the livelihood of the rural people as it creates the alternative income sources. After the Comprehensive Peace Agreement (CPA) in 2006, the agricultural mechanization, access to markets and labour, agriculture extension services, proximity to road transport are increased (Upreti, 2010; Aryal, 2011).

Maize-based cropping system is dominated in the Mid-hills (Atreya et al., 2006; Rana et al., 2009; Timsina et al., 2010) and rice based cropping pattern dominated in the Terai (Timsina et al., 2010) due to the different climatic condition with different pattern of rainfall. During the rainy season, there are abundant rain in all district while during the winter and spring, the average rainfall is very low. That causes a water deficit during the winter leading to lower productivity during the winters as well as springs. Terai has a higher total annual rainfall pattern as compared with Mid-hills and total annual rainfall pattern decreased towards the western part of the country (Gautam et al., 2010). Therefore, in Dadeldhura, monsoon starts slightly later and also end up with one month earlier than Palpa and Nawalparasi, but presents slightly higher rainfall during winter which might be the reason of still higher percentage share of winter cereal in Dadeldhura. The only HH, which have limited access to irrigation (drinking water used for irrigating small area), might grow vegetables in Palpa and Dadeldhura. Due to the increasing access to drinking water in the Mid-hill district since 1985, the percentage share of the vegetable during the spring increased since 1985. However, in the Nawalparasi, there are partial irrigation facilities which might be the reason of the higher percent share of the vegetables per HH. On the other hand, a higher fallow period during the spring is because of the lack of moisture in the soil (Subedi et al., 1997; Dixit et al., 2009) and there are poor rainfall observed during this period. Due to the different rainfall pattern, farmers grow maize mixed with rice bean and maize mixed with soybean dominates during the summer in Mid-hills and paddy in Terai during the summer.

5.4 Changes in livestock numbers

The decreasing trend of the buffalo, cattle and goats per HH are associated with many factors. Among them, abroad migration of the HH members, replacing local breed with improve ones, introduction of the cattle insurance and artificial insemination (AI) are the dominating factors. Similarly, reducing the free range area with protection of community forest by fencing and limited fodder and forage during dry season are other important factors that reduce the number of livestock’s per HHs. The average number of livestock has decreased since 1985 to until 2015 in all districts (CBS, 2014). The main factor affecting it is abroad migration of the economically active HH members which limits the average daily working hours for agriculture including the size of the livestock in HH (CBS, 2014). Also, recently there are increasing trends of replacing the unproductive number of livestock with improved breeds with higher productivity, which increased their source of income per HH (Agrawal and Gupta, 2005). The impact of the livestock promoting different projects, increase access to resources and breeds, increase access to animal feeds as well as the introduction of the cattle insurance and artificial insemination (AI) services that boost the livestock sectors from last 5 to 6 years in all surveyed districts.

5.5 Problems for agriculture production

Agriculture in Nepal is associated with many factors like rainfall and bad weather conditions, fluctuating market price, poor rural infrastructure and lack of access to credits. Among the many problems presented in the result section, the main problems for the agriculture production is the lack of irrigation. The urgent need of promoting irrigation based structure is need to further intensifying and diversifying the agriculture in Nepal. It not only reduced the cropping intensity, but also decrease the diverse income options for the rural HHs (Jha et al., 2016). After the rainfall, the increasing monkey population since last decades creates the huge problems in the Mid-hills (Awasthi and Singh, 2015) as it damage the crops. Monkey especially damage the major crops like maize and other cereals as well as fruits and vegetables (Devi and Saikia, 2008). Many other wild animals (wild deer and wild goat, porcupines, Rabbit and mouse etc.) also create the significant loss of the crops like loss of harvestable product, physical damage of crops, injury to human beings as well as livestock’s and change of spreading disease etc. (Studsrød and Wegge, 1995). Timely unavailability of the fertilizers, even duplicate and low quality fertilizer in insufficient amount are also the major challenges. Besides that, soil erosion and reduce soil fertility, reduce amount of FYM due to decreasing livestock, weeds, insects and diseases are the problems that hinder the growth and productivity of the agriculture.

5.6 Drivers of intensification and diversification

Many drivers are collectively associated with the commercialization and intensification of the agriculture in Nepal (Dahal et al., 2008; ADB, 2009; CBS, 2014). Among them, National policy, institutionalization and political stability are the major ones. After the first people’s movement at 1990, the economy of the country woke up from a slumber and Nepal entered into the social and economic transformation. After that, various political changes has been made and different policies are implemented. The Agriculture perspective plan (1995-2015), and National agriculture policy-2004 are the major policy level drivers for diversification and intensification of the agriculture. The fertilizer transport subsidies, pocket focused program and crop and livestock insurance program are the main drivers that leads towards the agriculture innovation and intensification (CBS, 2014). Similarly, country developed the multilevel institutional partnership and collaboration with non-governmental and farmers organization for technological innovation also helps to intensify the agricultural systems. Recent transformation of farmers groups in to farmers cooperatives also plays a great roles on local economic development and farmers empowerments.

Similarly, access to resources and infrastructures are another important drivers. Increased access to resources and technologies (access to inputs ,access to extension services, access to markets and roads, better access to agriculture fields from homes) have a positive and influential effect on the intensification of the agriculture (ADB, 2009).

In addition, climate change and rainfall pattern is another important factors of diversification. As the majority of the HH depends on agriculture and the agriculture system entirely depends

45 on the rainfall, the changing climate has a huge effect on agriculture sectors of the country. Farmers are practicing more traditional and conservation farming practice with integrating new agricultural technology to combat the climate change which also promotes the intensification. For example, crop failures due to drought leads to some drought tolerant crops in the cropping pattern might help to diversify the crops. Declining production and productivity due to the water stress are the major challenge of climate change.

Also, population pressure and labour migration influence the farming system. Due to the labour shortage in the agriculture sectors especially during the peak agriculture seasons, the HH are willing to change the labour intensive crops. Due to the shortage of the agricultural labours, HH favours the higher adoption of the new labour intensive technology. In all surveyed three district, crops like millets decreased considerably due to its higher labour requirements.

Finally, impact of development projects and NGOs have made the significant social change in the country. Many development projects and local NGOs have been influencing as a major change driver in the selected survey district towards the diversification and intensification of the agriculture as well as land use change.

5.7 Changes and shifting of the farming systems

Agricultural intensification of Nepalese HH has not been well documented. In this context, four types of farming systems were categorized based on the different intensification activities and present income from agriculture (2015) for the year 2015 (Figure 20). Three other hypothetical shifting of farming systems i.e. hypothetical farming system during 1985 to 1995 (a), during 1995 to 2005 (b) and future projection during 2025 (d) are prepared based on the other various qualitative information and empirical evidence from the research. However, many factors influence agricultural intensification i.e. socio-economic situation (Jakovac et al., 2016), HH land holding, access to agricultural extension and resources (Durga and Kumar, 2016), population pressure, access to markets, employment opportunity, transport facilities, institutional development and policies (Arnold and Dewees, 1997; Matson et al., 1997; Stoop et al., 2002; Westarp et al., 2004; Dahal et al., 2009; Raut et al., 2010; Tscharntke et al., 2012).

During the period of 1985 to 1995, the nature of the farming system was based o subsistence crops only focusing on the needs of their HH food consumption without any surplus for the market. The major dominating crops were cereals (maize, wheat, rice) and some legume crops (pea, pigeon pea). HH grow crops only in the summer and winter season and other periods have remained fallow. HH had a local livestock, which was used for the dual purpose i.e. for milk and for animal power for ploughing. During this period, most of the HH in all three districts used local varieties without replacing their seeds, low use of improved agricultural practices and lack of agricultural extension services as well as access to agricultural resources (ADB, 2009; Dahal et al., 2009). They treat their lands with some

46 legume-based rotation and use of farm yard manure (FYM) and compost for maintaining soil fertility. Due to the limited access to resources (irrigation, chemical fertiliser, pesticides, etc.), poor extension and poor road connection, HH were not aware of marketing opportunities.

Figure 20. General qualitative view of shifting of agriculture during past, present and future projection.

During the period of 1995 to 2005, HH shifted their farming system from subsistence level to semi-subsistence (mixed crop-livestock) farming systems which provided not only the basic needs of the HH, but also increase the production and productivity of their land. During this periods, farmers started to use different types of new technology and inputs for their farming. During this period, the introduction of the vegetable started and also stared the use of the inorganic fertilisers and pesticides (CBS, 2012). There were also the introduction of the hybrid seeds, new forage crops, improved breeds of livestock and small agricultural tools like a sprayer, sprinklers, hand tractors, chaff cutter etc. in the communities which shifted their farming systems towards semi-intensive mixed crop-livestock farming systems (ADB, 2009). During this period, many local projects and many development organizations working in the districts which plays a crucial role in facilitating farmers by providing free access to technology, increasing the number as well as a variety of improved crops by encouraging them and maximizing the use of inorganic fertilisers to increase the production and productivity (Raut et al., 2011).

The period from 2005 to 2015 is the period of market-oriented mixed crop-livestock production systems. There are many crops grown by the HH and farmers used improved seeds and breeds. Farmer’s dropout unproductive crops and only used selected productive crops which supported their HH needs as well generated extra income for the HH (Personal- communication, 2015). During this period, many HH introduces new crops, especially vegetables, improved seeds for cereals and legumes as well as pulses. Many farmers also started to use hybrids for vegetables and cereals. The farming systems become more market- oriented and farmers choose their crops based on the market opportunity and potential price of their crops (Dahal et al., 2009; Dhakal et al., 2012). Similarly, there is an increasing trend

47 of growing improved breed of cattle by replacing their unproductive local cattle which have higher milk production capacity. In addition to that, farmers grow many forage crops and also used forage/fodder from community forest and animal feeds from market. They also have an easy access to required veterinary services. The majority of the farmers used mechanized tools like a thresher, power tiller/mini-tiller, tractor etc. and farmers groups converted into agricultural cooperatives. There are significant changes in the access to services and resources (CBS, 2012).

A horizontal expansion of the land is almost impossible and HH food demand is increasing due to the population growth, the HH integrates high-value crops in their cropping pattern and they changed their land used pattern based on the market opportunity of their produce. In this context, the future farming practice of the HH will be more market-oriented and towards the commercial production systems of the crops.

Different drivers are responsible for current land use change and changes in agricultural practices. The land use change from subsistence agriculture to market-oriented agricultural production is triggered by recent infrastructure development (irrigation, agricultural roads), technological innovations (high yielding varieties, modern practices and agricultural mechanization), institutional support (subsidies and buyback guarantees) and increased agricultural extension programs (governmental as well as private sector). Recently, communities changed towards urbanization due to the influence of remittance and this has changed the land use and land cover pattern (Thieme and Wyss, 2005; Rimal, 2011; Rimal, 2013).

Many specific drivers are responsible for changing each indicator, however there are common drivers of agriculture intensification and shifting of farming system in surveyed district. The major drivers are increased access to resources (seeds, inputs, credits), political stability after the comprehensive peace agreement (CPA) in 2006, better agricultural road networks and increased mobile services, increase income of HH (due to agriculture as well as non-farm income source) (Khanal and Watanabe, 2006) and government policy are the common driver that increase the agriculture intensification as well as enhance to shift cereal- based farming system towards market-oriented production systems.

5.8 Typology and trajectory of HH

Among the four types of HH classified based on the PCA and CA, The huge percentage of the HH in all district are lower to medium resource endowment. Although, the typologies are made only focusing on the land holding and the TLU, other associated indicators are found related to the types of the HH. Generally, wealthier HH have higher capacity to hire higher number of labours as well as higher investment in agriculture and vice versa.

Similarly, the trajectory of change of HH from the year 1985 to the year 2015 are generalized based on the different socio-economic and agricultural indicators used for the analysis. The three types of qualitative trajectory has been seen from the empirical evidence as mentioned below;

Trajectory 1. Decreased HH size, livestock number and land holding This type of trajectory of the HH is common in all district. Due to the segregation of family resulting to divide their parent’s lands, the size of the land holding decreased on each generation. Also, the size of the livestock decreased by divided their resource first and keeping lower number due to the less number of family members.

Trajectory 2. Increased HH migration and non-farm income source with similar HH size, land holding and livestock numbers Another trajectory of the HH could be the increasing of migration of the family members resulting to increase the income from remittance. This trajectory type of the HH have the same existing resources like land holding, number of livestock’s and almost similar pattern of cropping systems over the years with only changes on the migration. This type of trajectory of the HH is common in all district. Also, the number of the livestock decreased by replacing unproductive livestock by improve ones. The migration of the family members increased for searching the income and alternative livelihood strategies.

Trajectory 3. Increased improve cattle and improve adoption practice of agriculture with vegetable farming Increasing adoption of both improved cattle and improved seeds are another trajectory of the HH in surveyed districts. The farmers started to introduce the improved breeds as well as varieties of crops to increase the production and productivity of the cattle as well crops. This trajectory also consist of the group of HH with increased diversity of crops, increased adoption of the improved seeds, breeds and inorganic fertilizers in all three districts.

6. Conclusion

Based on the research conducted and empirical evidence describe above, we can derive the following conclusions: size of the HH, migration pattern, annual total income of the HH and FSS period of HH have changed since 1985. The size of the HH decreased in all surveyed districts. Almost every HH has a migrating member and remittance provide major sources of income used for combating the food security of HH. The majority of the HH used remittance as a non-farm income source for their agriculture well as HH expenses. Similarly, access to resources (agricultural extension services, adoption of improved seeds and fertilisers), access to markets and roads per HH increased since 1985 which motivate farmers to shift the cereal- based farming system into market-oriented production systems with tremendous market opportunities.

The diversity of the agricultural crops as well as cropping intensity of the HH increased and fallow periods has been decreased. The percentage share of different crops during summer, winter, and spring season per HH since 1985 in all three districts changed remarkably. At the same time unproductive and lower market demanded crops were replaced by the productive high value cash crops. The percentage share of vegetable increased significantly in all seasons in all districts resulting to change the cereal-based cropping pattern into vegetable and cash crop based cropping pattern. The productivity of the crops, especially cereals increased due to the introduction of the high yielding modern varieties and hybrids. Besides that, the average number of the livestock per HH in all district decreased except cattle in Dadeldhura. The decreasing livestock number might be due to the less family labour for agriculture by higher migration and replacement of the unproductive local cattle by improved breed.

There are huge percentage of the HH under lower to medium resource capacity (around 90%) and almost majority of the HH are under the hanging in livelihood strategies. Three types of qualitative trajectory has been found: trajectory 1; Decreased HH size, livestock number and land holding, trajectory 2; Increased HH migration and non-farm income source with similar HH size, land holding and livestock numbers and trajectory 3; increased improved cattle and improved adoption practice of agriculture with vegetable farming.

The present land use change and agriculture intensification are governed by many drivers like recent development in infrastructures (agricultural road networks and increased mobile services), agricultural innovation and technology development, increase access to resources, increase access to agricultural extension services, and agriculture promoting government policies.

Overall, there has been a considerable changes in the agricultural practices leading to more intensified agriculture with less fallow land which was mainly pushed by the outside (NGOs/Service providers etc.) factors. Hence, future research study on quantification of agricultural intensification in the mixed based farming system would be recommended.

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Annexes

Annex 1. HH survey plan from each districts

Annex 2. List of survey HH with GPS, altitude and their ethnicity.

S.N Name of Farmers Distritc contact Date gps_n gps_e ht_meter ethnicity

1 Topali Bishowkarma Palpa 7-sep 27.87987 83.52016 1178 Dalit 2 Tiltama thapa Palpa 7-sep 27.88977 83.53311 1177 Janajati 3 Bir bahadur ale Palpa 7-sep 27.88752 82.52630 1155 Janajati 4 Hirasing rana Palpa 9847226685 7-sep 27.89117 83.52200 1221 Janajati 5 Rana Bahadur Resmi Palpa 9847116744 8-sep 27.89066 83.59975 1263 Janajati 6 Pritam rana Palpa 8-sep 27.89002 83.53218 1106 Janajati 7 Belisara pun Palpa 8-sep 27.87976 83.52034 1178 Janajati 8 Keharsing ale Palpa 9-sep 27.88979 83.53313 1178 Janajati 9 Bharat B.K. Palpa 9847011762 9-sep 27.88798 83.51892 1302 Dalit 10 Sumitra Sunar Palpa 9-sep 27.86370 83.53964 1300 Dalit 11 Jit Bahadur rana Palpa 9847231464 9-sep 27.88800 83.51945 1259 Janajati 12 Pabisara rana Palpa 9-sep 27.88805 83.51960 1287 Janajati 13 Bhoj bahadur KC Palpa 10-sep 27.89720 83.51741 1102 Brahmin 14 Mohan bahadur rana Palpa 10-sep 27.88696 83.52583 1102 Janajati 15 chabi rana Palpa 9844792368 10-sep 27.89168 83.52308 1196 Janajati 16 Jhaman sing darlami Palpa 9847098789 10-sep 27.89532 83.51625 1263 Janajati 17 Meharman thapa Palpa 9844773900 10-sep 27.88966 83.53304 1081 Janajati 18 Siva karki Palpa 11-sep 27.89128 83.50372 1000 Brahmin 19 Thakur pandey Palpa 9847419123 11-sep 27.84206 83.55457 902 Brahmin 20 Rekha bista Palpa 11-sep 27.86776 83.51800 1317 Brahmin 21 mena gaire Palpa 11-sep 27.84289 83.55372 884 Brahmin 22 resmi raj koirala Palpa 9847114438 11-sep 27.84323 83.55478 941 Brahmin 23 mitthu rawal Palpa 12-sep 27.87358 83.51083 1408 Brahmin 24 ram bahadur khadka Palpa 12-sep 27.86812 83.50836 1295 Brahmin 25 masura miya Palpa 9847028040 12-sep 27.87528 83.52302 1348 Madeshi 26 Tul bahadur mukhiya Palpa 13-sep 27.87526 83.52287 1294 Brahmin 27 Dhan bahadur bhandari Palpa 13-sep 27.86942 83.51135 1292 Brahmin 28 man kumari karki Palpa 9847307352 13-sep 27.87289 83.51205 1197 Brahmin 29 Dev bahadur bohara Palpa 13-sep 27.87280 83.51202 1410 Brahmin 30 om bahadur karki Palpa 14-sep 27.87062 83.50731 1316 Brahmin 31 chandrawati thapa Palpa 14-sep 27.87060 83.50729 1316 Brahmin 32 buddha bahadur rawal Palpa 14-sep 27.86862 83.50727 1303 Brahmin 33 Narayani karki Palpa 9847033595 15-sep 27.87224 83.51216 1404 Brahmin 34 Amit dargi Palpa 15-sep 27.86390 83.51654 1218 Dalit 35 Kumar ghale Palpa 9867021133 15-sep 27.86353 83.51649 1215 Janajati 36 sushila bista Palpa 9847399060 16-sep 27.86779 83.51842 1320 Brahmin 37 laxman karki Palpa 522767 16-sep 27.86942 83.51135 1292 Brahmin 38 krisna bahadur karki Palpa 16-sep 27.87230 83.51258 1404 Brahmin 39 Ganesh kumari rawal Palpa 16-sep 27.87048 83.50711 1327 Brahmin 40 saraswati rawal Palpa 17-sep 27.87365 83.51133 1412 Brahmin 41 Chabilal Thadarai Palpa 9847128611 17-sep 27.85404 83.49143 1271 Dalit 42 lal bahadur bhat Palpa 9847002243 17-sep 27.85078 83.49845 1210 Brahmin 43 man kumari rana Palpa 18-sep 27.85106 83.49848 1238 Janajati 44 ram bahadur thadarai Palpa 18-sep 27.85466 83.49192 1272 Dalit 45 Nerpa Bahadur Karki Palpa 18-sep 27.89010 83.50840 1272 Brahmin 46 shanta karki Palpa 19-sep 27.89033 83.50793 1494 Brahmin 47 Bishnu kumari karki Palpa 9847005052 19-sep 27.89096 83.50465 1493 Brahmin 48 prem lal gahatraj Palpa 19-sep 27.86188 83.49732 1495 Dalit 49 Naran Bahadur Khadka Palpa 19-sep 27.86268 83.51479 1209 Brahmin

50 mohan lal gahatraj Palpa 19-sep 27.86162 83.49725 1508 Dalit 51 hemraj gaire Nawalparashi 9814460020 20-sep 27.60999 83.65271 113 Brahmin 52 Renuka basyal Nawalparashi 20-sep 27.61669 83.65147 119 Brahmin 53 Nathu tharu Nawalparashi 9817470878 20-sep 27.62118 83.64492 120 Madeshi 54 Jogi kumal Nawalparashi 20-sep 27.60815 83.65008 112 Janajati 55 mera devi chaudhary Nawalparashi 9817487691 21-sep 27.61827 83.64772 116 Madeshi 56 chan bahadur khaptari Nawalparashi 21-sep 27.62085 83.64485 113 Brahmin 57 sabitri gharti chhetri Nawalparashi 21-sep 27.63161 83.64034 150 Brahmin 58 Gun bahadur thapa Nawalparashi 21-sep 27.63622 83.63988 146 Brahmin 59 Man bahadur thapa magar Nawalparashi 9617835846 22-sep 27.61526 83.63839 115 Janajati 60 Womapati kafle Nawalparashi 22-sep 27.61923 83.65877 130 Brahmin 61 Nirmaya Rana Nawalparashi 9815436350 22-sep 27.61349 83.65416 110 Janajati 62 Here Kunwar Nawalparashi 22-sep 27.61297 83.57729 114 Dalit 63 Laxmi kharal Nawalparashi 23-sep 27.61909 83.58668 117 Brahmin 64 Tulsi Ram chapagai Nawalparashi 9818963882 23-sep 27.57633 83.59656 112 Brahmin 65 yam bahadur sunar Nawalparashi 9847004592 23-sep 27.57632 83.59655 111 Dalit 66 purna prasad timalsina Nawalparashi 9857011740 23-sep 27.59529 83.58421 88 Brahmin 67 sanjay kohar Nawalparashi 9804419958 24-sep 27.58188 83.58932 88 Dalit 68 Buddhu Baniya Nawalparashi 9806930704 24-sep 27.57926 83.59396 104 Brahmin 69 Padam bahadur thapa Nawalparashi 9807467684 24-sep 27.57763 83.59572 99 Janajati 70 Hom nath bhandari Nawalparashi 9818238937 26-sep 27.58108 83.59217 114 Brahmin 71 Krishna Adhikari Nawalparashi 26-sep 27.58094 83.59225 109 Brahmin 72 Man bahadur tamang Nawalparashi 26-sep 27.57070 83.58548 104 Janajati 73 Tek bahadur pariwar Nawalparashi 9815404424 27-sep 27.57080 83.58554 101 Dalit 74 Bhim prasad dawadi Nawalparashi 27-sep 27.57615 83.59664 103 Brahmin 75 Dummaya sunar Nawalparashi 9847042137 27-sep 27.57614 83.59663 102 Dalit 76 Khadag sumai Nawalparashi 9821567959 27-sep 27.59455 83.57999 105 Dalit 77 Raghunath Yadav Nawalparashi 9808981560 7-dec 27.59453 83.57996 103 Madeshi 78 Attiwulla Dewan Nawalparashi 9821424060 7-dec 27.50641 83.74889 89 Madeshi 79 Voj raj Neupane Nawalparashi 8-dec 27.50260 83.74768 87 Brahmin 80 Dewanti Tharu Nawalparashi 9847214362 8-dec 27.49843 83.74685 89 Madeshi 81 Dhanpati Chaudhary Nawalparashi 9807485581 8-dec 27.49879 83.74727 93 Madeshi 82 Shreeram Tharu Nawalparashi 8-dec 27.49799 83.74719 90 Madeshi 83 Nanda K chaudhary Nawalparashi 9-dec 27.49844 83.74683 92 Madeshi 84 Murari Chaudhary Nawalparashi 9811916793 9-dec 27.49854 83.74643 90 Madeshi 85 Laxmi Shrestha Nawalparashi 9-dec 27.49871 83.74737 93 Janajati 86 Nar Bahadur Chaudhary Nawalparashi 9811966640 9-dec 27.49831 83.74705 89 Madeshi 87 Dudhnath Chaudhary Nawalparashi 9847068227 9-dec 27.50729 83.74888 90 Madeshi 88 Chan Kumari Tharu Nawalparashi 9816454276 10-dec 27.50676 83.74903 91 Madeshi 89 Lal Bahadur Malla Nawalparashi 9804496116 10-dec 27.49680 83.75758 88 Janajati 90 Kesun Mishra Nawalparashi 9821592756 10-dec 27.49593 83.74712 87 Brahmin 91 Jagadish Kahar Nawalparashi 10-dec 27.49618 83.74751 87 Dalit 92 Aasa Gautam Nawalparashi 9807454391 11-dec 27.49669 83.75782 90 Brahmin 93 Motichan Harijan Nawalparashi 9847289470 11-dec 27.49826 83.75512 88 Dalit 94 Indra BK Nawalparashi 11-dec 27.49833 83.74707 89 Dalit 95 Gambi Devi Chaudhary Nawalparashi 11-dec 27.48802 83.74458 90 Madeshi 96 Ranju Chaudhary Nawalparashi 9821481308 12-dec 27.48810 83.74458 87 Madeshi 97 Ramkripal Thakur Nawalparashi 12-dec 27.48679 83.77912 92 Madeshi 98 Ramdulari Chaudhary Nawalparashi 12-dec 27.48705 83.77911 92 Madeshi 99 Homnath Pathak Nawalparashi 9813362229 12-dec 27.49005 83.77395 97 Brahmin 100 Indrapari Chaudhary Nawalparashi 9847515344 13-dec 27.48678 83.77910 92 Madeshi 101 Nirmala BK Nawalparashi 13-dec 27.48582 83.72955 92 Dalit

102 Rajesh BK Nawalparashi 13-dec 27.48603 83.77950 85 Dalit 103 Nirmala Harijan Nawalparashi 9807505510 13-dec 27.48983 83.77958 96 Dalit 104 Shivalal Chamar Nawalparashi 14-dec 27.48589 83.77966 93 Dalit 105 Jagadish Tharu Nawalparashi 14-dec 27.48589 83.77966 93 Madeshi 106 Harka Bahadur Chaudhary Nawalparashi 14-dec 27.48021 83.77992 88 Madeshi 107 Bhagmani Harijan Nawalparashi 14-dec 27.48552 83.77980 97 Dalit 108 Basundhara Bhurtel Nawalparashi 9804463825 14-dec 27.49761 83.78265 90 Brahmin 109 Rukmagat Basyal Nawalparashi 9819446239 15-dec 27.49763 83.78299 95 Brahmin 110 Dilmaya Thapa Nawalparashi 9847193839 15-dec 27.48986 83.77370 102 Janajati 111 Sangita Kewar Nawalparashi 15-dec 27.49767 83.78292 96 Dalit 112 Achyut Parajuly Nawalparashi 15-dec 27.49767 83.78292 96 Brahmin 113 Kesara Bashyal Nawalparashi 9847192546 15-dec 27.49778 83.78294 96 Brahmin 114 Khublal Chaudhary Nawalparashi 9847257714 16-dec 27.49817 83.78384 94 Madeshi 115 Musuri Manandhar Nawalparashi 9867019521 16-dec 27.48893 83.77332 92 Janajati 116 Nabadevi Shrestha Nawalparashi 16-dec 27.49818 83.73344 102 Janajati 117 Bablu Manandhar Nawalparashi 9847127059 16-dec 27.48903 83.77342 100 Janajati 118 Laxmi Devi Bhatta Dadeldhura 9807432707 17-dec 29.34855 80.59073 1571 Brahmin 119 Karan Parki Dadeldhura 17-dec 29.34508 80.58305 1443 Dalit 120 Bhawani Sing Mahar Dadeldhura 9812739802 17-dec 29.34384 80.57844 1543 Brahmin 121 Prem Bahadur Kaine Dadeldhura 9848743082 17-dec Brahmin 122 Dammaridevi Bhatta Dadeldhura 9804655252 17-dec 29.34842 80.59065 1562 Brahmin 123 Tej Sing Mahar Dadeldhura 9848802378 18-dec 29.34383 80.57792 1551 Brahmin 124 Harising Bohora Dadeldhura 9848851514 18-dec 29.34222 80.58525 1489 Brahmin 125 Ganesh Saud Dadeldhura 9868725203 18-dec 29.34331 80.57757 1563 Brahmin 126 Shalibhan Saud Dadeldhura 9848717254 18-dec 29.34288 80.58031 1495 Brahmin 127 Devidutta Pathak Dadeldhura 9848859659 18-dec 29.34127 80.57900 1504 Brahmin 128 Basanti Bista Dadeldhura 98488827681 19-dec 29.35003 80.58495 1499 Brahmin 129 Laxmi Bista Dadeldhura 984889718 19-dec 29.34987 80.58515 1497 Brahmin 130 Dhan Bahadur Bista Dadeldhura 9848826430 19-dec 29.98100 80.58488 1499 Brahmin 131 Bhuwan Tamrakar Dadeldhura 9848759280 19-dec 29.34456 80.59206 1514 Dalit 132 Durga Tamrakar Dadeldhura 9848740793 19-dec 29.34382 80.59185 1490 Dalit 133 Sunita BK Dadeldhura 9860792496 19-dec 29.34534 80.59193 1503 Dalit 134 Krisan tamata Dadeldhura 15-nov 29.34586 80.59090 1515 Dalit 135 Dilip sing mahar Dadeldhura 9848777483 15-nov 29.34329 80.57874 1539 Brahmin 136 Dev Bista Dadeldhura 9848743531 15-nov 29.35077 80.58322 1561 Brahmin 137 Laxmi pathak Dadeldhura 16-nov 29.34124 80.57839 1510 Brahmin 138 Bhawani sing saud Dadeldhura 9849285479 16-nov 29.24253 80.58125 1480 Brahmin 139 Hira Devi Bohora Dadeldhura 16-nov 29.34226 80.58141 1475 Brahmin 140 Gobari Kami Dadeldhura 9848847908 18-nov 29.24995 80.63552 1939 Dalit 141 Laxmi Kami Dadeldhura 18-nov 29.24987 80.63548 1940 Dalit 142 Sundari BK Dadeldhura 9848993111 18-nov 29.24912 80.63478 1960 Dalit 143 Ganesh Raj Bhatta Dadeldhura 9848859148 20-nov 29.25227 80.63805 1953 Brahmin 144 Sundar dev bhatta Dadeldhura 20-nov Brahmin 145 Kamalesh Bhatta Dadeldhura 9843003603 19-nov 29.25264 80.63580 1947 Brahmin 146 Bhim Bdr Diyal Dadeldhura 9848806803 19-nov 29.23272 80.65091 1282 Brahmin 147 Janaki Bhatta Dadeldhura 23-nov 29.25025 80.63297 1993 Brahmin 148 Narayan Dutta Bhatta Dadeldhura 23-nov 29.25059 80.63325 1989 Brahmin 149 Ram dutta Bhatta Dadeldhura 23-nov 29.25047 80.63311 1987 Brahmin 150 Prem Sangar Bhatta Dadeldhura 9848776829 23-nov 29.25048 80.63314 1987 Brahmin 151 Ramesh BK Dadeldhura 9810627703 24-nov 29.24910 80.63498 1949 Dalit 152 Anamol Bhatta Dadeldhura 9848776545 24-nov 29.25149 80.63251 1982 Brahmin 153 Dharmananda Bhatta Dadeldhura 24-nov 29.24902 80.63374 1992 Brahmin

154 Chintamani Bhatta Dadeldhura 25-nov 29.25130 80.63197 1987 Brahmin 155 Parmananda Bhatta Dadeldhura 9868422486 25-nov 29.25147 80.63249 1982 Brahmin 156 Ram Bhatta Dadeldhura 25-nov Brahmin 157 Harilal Ayear Dadeldhura 9848981985 26-nov 29.28156 80.61770 1746 Dalit 158 Harka Budayer Dadeldhura 9848626203 26-nov 29.26015 80.63354 1781 Dalit 159 Ramesh BK Dadeldhura 26-nov 29.26011 80.63351 1781 Dalit 160 Dipendra Ayer Dadeldhura 26-nov 29.26072 80.63268 1778 Brahmin 161 Kamali Devi Khadka Dadeldhura 26-nov 29.30103 80.65357 1228 Brahmin 162 Ser Bahadur Khadka Dadeldhura 26-nov 29.30133 80.65416 1235 Brahmin 163 Bhim Kami Dadeldhura 9848979921 27-nov 29.30090 80.65353 1230 Dalit 164 Resima kami Dadeldhura 27-nov 29.30068 80.65332 1246 Dalit 165 Nandi Kami Dadeldhura 27-nov 29.30091 80.65354 1231 Dalit 166 Hikmat Kami Dadeldhura 27-nov 29.30092 80.65352 1231 Dalit 167 Dan Bdr Khadka Dadeldhura 9848767430 27-nov 29.30272 80.64851 1279 Brahmin 168 Beludevi Khadka Dadeldhura 27-nov 29.30108 80.65355 1278 Brahmin 169 Harani Devi Khadka Dadeldhura 9865654103 28-nov 29.30104 80.65299 1253 Brahmin 170 Shanti Devi Kami Dadeldhura 28-nov 29.30106 80.65353 1278 Dalit 171 Bhaga Sarki Dadeldhura 28-nov 29.29940 80.65228 1260 Dalit 172 Samjana Sarki Dadeldhura 28-nov 29.29942 80.65250 1256 Dalit 173 Maina Sarki Dadeldhura 28-nov 29.29914 80.65126 1278 Dalit 174 Padam Khadka Dadeldhura 29-nov 29.30273 80.64851 1297 Brahmin 175 Tikeswori Khadka Dadeldhura 29-nov 29.30069 80.65265 1262 Brahmin 176 Bir B Khadka Dadeldhura 29-nov 29.30035 80.65215 1263 Brahmin 177 Sabitra Ayer Dadeldhura 29-nov 29.29994 80.65226 1269 Brahmin 178 Kalpana Khadka Dadeldhura 29-nov 29.30100 80.65305 1252 Brahmin 179 Kausala Khadka Dadeldhura 29-nov 29.29995 80.65227 1269 Brahmin 180 Mina Khadka Dadeldhura 29-nov 29.30027 80.65277 1264 Brahmin

Annex 3. A standardized Semi structure questionnaire format.

This is a questionnaire developed for the purpose of my research on the “Trajectories of change in Cereal based agroecosystems in Terai and Mid hills of Nepal”, as a partial fulfilment for the thesis in Wageningen University, Nederland. The information provided in this survey will be treated with confidentiality and only for the study purpose. So, I am looking forward to your positive cooperation. I would also like to thank you in advance.

A. General information Questionnaire No: Date: District: VDC: Place: Farm code: GPS Coordinate of HH:

1. What is your name?...... Male Female 2. What is your age/date of birth? ...... 3. What is your education?…………………………………………………………………………………………………………………… … 4. What is your marital status i. Marriedii. Unmarried 5. Are you head of HH? i. Yes ii. No 6. How many members does your HH consist of? Name Date of birth Current age Sex Education Remarks

7. What is/are your main occupation from your perspectives? ......

8. When you started your farm? ...... 9. Do/did your family/HH member migrated from your hh? i. Yes ii. No 10. If yes, Could you also tell about types, time period and reason of migration to fill below mentioned table?

Name Seasonal/permanent Time periods (when Where to Reason for Income and duration-Month) migration

11. Do you work outside your own farm i. yes ii. No If yes, please fill on the table

12. What were and are the non-farm activities? Activities Time spent in Season of work Total Specific off farm Off Active When income, year, Use of activities season production crop fail NRs income (hr/day) period Seasonal labour Unskilled wage labour Salary and skilled employment Small business (own shop) Trading (petty trade) Government service Remittance (India and third country) ......

13. How much amount of your income did/do you invest on following heading? (average annual figure) (Backup data) Heading Amount invested (NRs.) or tentative figure in % 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 15 14 13 12 11 10 09 08 07 06 05 04 03 02 01 00 99 98 97 96 95 94 93 92 91 90 89 88 87 86 85 HH needs- foods, cloths Children education Healthcare

Travel/recrea tion Cultural cost Own business investment, if any Agriculture investment (Seeds, fertilizers, equipments etc) Investment on livestock  Breeds  Fodder/f orage  Concent rate Irrigatio

B. Land use change and resource utilization

Map of the Field/plot with HH and Distance:

14. How much land do you have? ......

15. How much land does your house/shed and building covers?......

16. Do you classify your land as a wet land (ghol khet), semi wet land,, dry (Pakho bari) and do you have specific crops on each types of land? Type of land Area share Major preferred crops (cropping pattern) Wet land

Semi wet land

Dry land

Other

Farmers perception on Soil Fertility (Backup Question) 17. What criteria do you used to judge the fertility status of your soil? ......

18. How do you classify your land in term of fertility status (Backup Question) Wetland/Ghol Khet Fertility status Temporal dimension At present 5 y ago 10 y ago 15 y ago 20 y ago Yes No Yes No yes no yes no yes no More fertile Fertile Less fertile

Upland/Pakho Bari Fertility status Temporal dimension At present 5 y ago 10 y ago 15 y ago 20 y ago Yes No Yes No yes no yes no yes no More fertile Fertile Less fertile

19. What could be the reason for status of fertility status and its relative importance? S.N Reason of more fertile Ranked Reason of fertile Ranked Reason of less fertile Ranked 1 2 3 4 5

20. Do you have forest area? i.yes ii.no if yes how much area...... ? 21. Do you have permanent shrub? i.yes ii.no, if yes how much area...... ? 22. Do you have a ponf ? i yes ii no if yes how much area...... ? and what purpose do you use it? ......

Land use change-Fill separate page: Q Annex 1 M-Maize, R-Rice, W-Wheat,M-Millet,B-Buckwheat,P-Potato,C-Cauli,B-Brocauli,L-Latte 1 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 Reason of 5 14 13 12 11 10 09 08 07 06 05 04 03 02 01 00 99 98 97 96 95 94 93 92 91 90 89 88 87 86 85 change Plot 1 (size and type) Summer Winter Spring Plot 2 (size) Summer Winter Spring Plot 3 (size) Summer Winter Spring Plot 4 (size) Summer Winter Spring Plot 5 (size) Summer Winter Spring Irrigated area Types- Irrigation Sole crops Intercrops Mixed crop Types of Seeds Types of Fertilizers Investment Amt FYM Types of Seeds(L,I,H) ………… C Fertilizers (Amount) Urea/Ha DAP/ha MOP/ha ………… Sowing cost Weeding cost Harvesting cost Labour cost Family Labour, No Hire labour, No Exchange labour, No Labour Rate/day

23. What were/are the drivers/reason of land use change in your farm? (Also discussed on FGD) Reason of land use change Prefered crops and livestocks/land use Remarks HH needs Migration/labour shortage Land characters Price Reccomendation from others Participatory local projects Access to resources (seed, fertilizers, credits) Irrigation facilities Subsidy program Cultural belief ......

Resources: 24. Do you have access to irrigation water? i. Yes ii.no if yes, since when……………………..? and what was the reason for starting irrigation? ......

25. Is there any change in type or number of crops you have been cultivating as a result of access to irrigation water? …………………………………………………………………………………………………………………………………… ……………………………………………………………..…......

26. When and how long you hire labour for farm activities? When (within year) How long (hr) No of hire labour Type of activities

27. Do you exchange labour for farm activities? i. Yes ii. No If yes, when and how long and for what type of activities do you exchange labour for farm activities? When (within How long Type of activities For whome (family members, neighbours, year) (hr) others)

28. How many hour in a day do you and your family members work in your farm for agriculture activities? ......

S.N Name of members Designation/relation Time in hour Types of activities (avg/day) 1

C. Changes in Agriculture practices 29. What are the major current challenges to agricultural production for you? (discussed-FGD) (Prioritywise rank (1, 2, 3) i. …………………………………………………………………………………………………….. ii. …………………………………………………………………………………………………….. iii. …………………………………………………………………………………………………… iv. …………………………………………………………………………………………………. v. ………………………………………………………………………………………………… vi. …………………………………………………………………………………………………

(Note: Land shortage, Labour shortage, migration (inside, outside and foreign), Soil fertility, lack of irrigation, lack of improved seeds, Water shortage,high cost of inputs, Lack of inputs, Lack of Extension services, Insect, Pests and disease, weed problems, Feed for livestock, Weather condition change/bad weather, Policy limitation, other etc)

30. Did you encounter any other challenges in the past?, If so what were the challenges and how did you tackle that problems? Challange Time period Explanation how farmers tackle such problems over time

31. What were the consequences of those challenges?

32. What are your practices for balancing fertility status of your soil? i. By using only FYM/Compost ii. Only chemical fertilizer III. By using FYM+Chemical IV. Using green manure/Mulching V. FYM+Chemical+Green manure VI. Crop rotation with legume VII. FYM+Chemical+Green manure+ROTATION 33. What is your future plan for continuing farm and extending farm size? Continuing farm: upto ………………years Extending farm size: Now……………….ha, Extension of ……………………ha, How………………………………………………………………………… …………………………………………………………………………………………………………………………………… ………………………………………………………… 34. How did you manage your seed requirement for crops? i. using own seed ii. Burrowing from neighbours iii. Purchase from neighbours iv. purchase from agrovets

35. What is area, Production, productivity and price of dominant crops over a time?...... Q Annex 2 Fill Separate Page-Excel (productivity will be calculated later based on area and production)= Also collect information from VDC (VDC Profile, VDC Annual report/DADO/DLSO Report)

Livestock Sector: 36. Do you have livestock? i. Yes ii.No 37. Since when did you started rearing livestocks…………………………………………….? Livestocks Since When Reason of Selection/Rearing Buffalo Cattle (cow and He cow) Goat Sheep Poultry Duck Pigeon

38. What were the reasons of livestock increasing/decreasing in your farm? …………………………………………………………………………………………………………………………………… ……………………………………………………………...... ………………………… …………………………………………………………………......

39. How did you manage forage + grasses for livestock’s? Periods Forage/ Grasses + fodder For Buffalo/cow/oxen For Goat/sheep Who is responsible/who work for 2010- 2015 2005- 2010 2000- 2005 1995- 2000 1990- 1995 1985- 1990

40. Do you have communal forage land? i. Yes ii. No

41. How large (size/area)and how many members are benefiting from it? ......

Question number 35- What is area, Production, productivity and price of dominant crops over a time? Questionnaire Annex 2 District Address Area in: ha Bigha Dhur Hall Ropani Name- HH Area and Production of major crops

Crop 1:……………………………… Crop 2:……………………………… Crop 3:…………………………… Crop 4:………………………………

Time Area Production Amount sold Price/kg Area Production Amount sold Price/kg Area Production Amount sold Price/kg Area Production Amount sold Price/kg

2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985

42. How do you defined the properties of your communal grazing land (also discussed on FGD) Communal grazing Description Present situation land properties CGL management Open access, semi open, systems closed/protected, others etc. CGL Boundaries Delineated, unfenced and fuzzy etc. CGL User groups Controlled, predefined group, encroachment by outsiders etc. CGL management Tenable, ...... rules CGL size Limited, fairly limited, extensive

Range conditions Very poor, poor, good but poor quality, good with high quality etc. Arable cultivation on Restricted, limited, open access, etc. CGL Arable grazing right No/yes privet grazing right, other etc. during dry season

Livestock Management: (Q 43 Separate Page) 43. What were/are the numbers, types and livestock management practice you have follwed?

Access to market: 44. What were/are the distance to following market from your hh? Distance to Distance to local Distance to Distance to agri. Periods Types of Transport main road main market (km) haat (km) market (km) 2015 (KM)

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1985

Question 43-What were/are the numbers, types and livestock management practice you have followed? Annex 3-Livestock management systems Buffalo Cow Goat Sheep Poultry

Grazing type Shed Treatme Grazing type Shed Treat. Grazing type Shed Treat. Grazing type Shed Treat. Rearing Treatme nt type nt Peri N Ty F S M Te Per L C N Ty F S M Te Per L C N Ty F S M Te Per L C N Ty F S M Te Per L C N Ty F Ca L C ods o pes G F ix mp m o l o pes G F ix mp m o l o pes G F ix mp m o l o pes G F ix mp m o l o pes R ge o l 2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1985

Note: No-Numbers, Types (Local, Improved, AI), FG-Free grazing, ST-Stall Feeding, Mix- (Mixed: FG+SF), Lo-Local, Cl-Clinic, FR-Free rang

Institutional Access 45. Do you have access to extension services? i. Yes ii. No If yes, since when…………………………….?

46. what are the common inputs you have been using? …………………………………………………………………………………………….. ………………………………………………………………………………………………………………………………………… ……………………………………………………….. 47. What were/are the types of inputs you are using? Seed:

Fertilizers:

48. How the prices of agricultural inputs changed over time? (Secondary data) DADO/DLSO

………………………………………………………………………………………………………………………………………… ………………………………………………………………………………………………………………………………………… …………………………………………………………………………………………………………..

49. How were the change in access to agricultural inputs over a time? (Farmers Opinion) ………………………………………………………………………………………………………………………………………… ………………………………………………………..……………………………………………………………………………… …………………...... 50. Do you have access to credit service? i. Yes ii. No 51. If yes, are you using this service? i. Yes ii. No If yes, since when?...... 52. Are there any FG/cooperatives in your area? i. Yes ii. No If yes, since when?...... 53. Are you a member of any FG/ cooperatives? i. Yes ii. No If yes, since when?......

54. What are/were the services provided by the FG/cooperatives? Major services from Farmer groups Major services from Cooperatives

55. Are you involved in any form of local organization except FG/Cooperatives in the community? I. Yes ii. No

56. If yes, what are the benefits of this organization to your crop production?

Access to Credit (Backup Question) 57. What are the most important sources of credit (formal/informal such as Bank, NGO, Merchants etc.) for you and for what purpose you used it. List them Source of Credit Purpose Amount Remarks Credits from close relatives Credit from neighbous Credits from village landlord Credits from Merchants Credits from village cooperatives/SHGs Credita from Banks/FIs

Food security situation

Food security……………………………. months Feed security…………………………… months Forage self-sufficiency……………… months

Thank you

Annex 4. Checklist for focused group discussion

Target group Tool Objectives Checklist Selected key informants Informal Obtain - How do you explain farming practice in discussion overview this area and FGD information - What the environment looks like over a on farming time systems in the area

Determine - Did you observe any changes in farming the starting system point of - When did change observed trajectory - How did you recall access to resource analysis Participatory Perception - Demography (population growth, HH mapping on changes size) (1985 to - Environmental change/weather events 2015) - Land use pattern (Forest area/woodland, grassland, crop land, built-up area, barren land, water, roads) - HH land use strategies (vegetables, cereals, cash crops, fruits, forage/fodder) - Expansion of cropland, length of fallow, crop types and rotations - Forest and grazing area - Degraded area - Market access and farmers training centres/extension services Timeline Timelines - The most historical events recording of events - Bad/extreme weather (rainfall, flood, mud slides, drought, etc.) - Access to resource or technologies Self- Farm - Diversity between farm HHs categorization typology - Criteria used to categories into groups criteria - Types of farms/farmers identification

Annex 5. List of participant of FGD, Palpa.

Date: 20 September, 2015 Place: Boughapokharathok-2, Chinari at Community Building, Palpa S. Name of Gend N Participant er Address Contact 1 Tejesara Rana F Boughapokharathok2, Chinari 9847297189 2 Tekesara Somare F Boughapokharathok2, Chinari 3 Bhimkumari Rana F Boughapokharathok2, Chinari 4 Dalkumari Rana F Boughapokharathok2, Chinari 5 Janak Somare M Boughapokharathok2, Chinari 9847000297 6 Deukala Somare F Boughapokharathok2, Chinari 9847455192 7 Rewoti Rana F Boughapokharathok2, Chinari 8 Harka Bahadur Rana M Boughapokharathok2, Chinari 9 Sangita Rana F Boughapokharathok2, Chinari 9844792283 10 Premisara Rana F Boughapokharathok2, Chinari 9847419984 11 Lum Kumari Resmi F Boughapokharathok2, Chinari 12 Deusara Somare F Boughapokharathok2, Chinari 13 Susila Rana F Boughapokharathok2, Chinari 9847348700 14 Gangisara Rana F Boughapokharathok2, Chinari 9847167752 15 Gyanisara Rana F Boughapokharathok2, Chinari 16 Lilakumari Rana F Boughapokharathok2, Chinari 9847115659 17 Khagisara Rana F Boughapokharathok2, Chinari 18 Man Bahadur Rana M Boughapokharathok2, Chinari 9847154979 19 Shanti Somare F Boughapokharathok2, Chinari 9847495949 20 Dependra Rana F Boughapokharathok2, Chinari 9847028404 21 Kisan Rana M Boughapokharathok2, Chinari 9847563081 22 Tulsiram Somare M Boughapokharathok2, Chinari 9857060826 23 Lekhraj Somare M Boughapokharathok2, Chinari 24 Manish Somare M Boughapokharathok2, Chinari 9847415572 25 Kisan Rana M Boughapokharathok2, Chinari 9847498126 26 Chabilal Somare M Boughapokharathok2, Chinari 9847146639 Hum Bahadur 27 Somare M Boughapokharathok2, Chinari 9847101911 28 Juddhabir Somare M Boughapokharathok2, Chinari 9847028456 Netra Bahadur 29 Masange M Boughapokharathok2, Chinari 9807581971 30 Topali Rana F Boughapokharathok2, Chinari 31 Hirasing Somare M Boughapokharathok2, Chinari 9857060989 32 Bhupal Rana M Boughapokharathok2, Chinari 9847456510 33 Rukbir Resmi M Boughapokharathok2, Chinari 9847347130 34 Giriraj Rana M Boughapokharathok2, Chinari 9849048400 Baikuntha Nath District Agriculture Development 35 Khanal M Organization (DADO)

Annex 6. List of Participant of FGD, Dadeldhura.

Date: 26 November,2015 Place: VDC Office, Samaijhee-7 S. Name of Gend Contact N Participant er Address Number Padma singh 1 Thagunna Male Samaijhee-7 9848519194 2 Sundar Bhatta Male Samaijhee-7 3 Kamles Bhatta Male Samaijhee-7 4 Taradutta Bhatta Male Samaijhee-7 5 Man Bahadur BK Male Samaijhee-7 6 Ramesh BK Male Samaijhee-7 7 Karan Parki Male Samaijhee-7 Femal 8 Sundari devi BK e Samaijhee-7 Femal 9 Durga Tamrakar e Samaijhee-7 Femal 10 Bhuwan Tamrakar e Samaijhee-7 Femal 11 Janaki Bhatta e Samaijhee-7 12 Bahadur bistha Male Samaijhee-7 9848851699 Femal 13 Madhavi Bhatta e Samaijhee-7 9848710069 Chamber of commerce and industry, 14 Madhav Poudel Male Dadeldhura 15 Sudeep Subedi Male District Agriculture Development Office 16 Chetraj Pathak Male Veterenary Doctor, Samaijhee 17 Chandan Shrestha Male NGO Representative Ganesh Prasad Technical office, DADO Service center, 18 Bhanari Male Samaijee VDC 9858733182 19 Man Bahadur Raut Male Assistant, Ashigram VDC 9848847181 Technical office, DADO Service center, 20 Ankilal Bhatta Male Ashigram VDC 9848776545 21 Khadka Sahi Male Information officer, DLSO Dadeldhura 9848604444 Ratan Bahadur 22 Ayer Male Office assistant, Samaijhee VDC Office 9848766449 23 Khadga Shahi Male District Livestock service office (DLSO) 9848604444

Annex 7. List of key informant interviewed regarding local changes in Agriculture

S. Name of Contact N Participant District Gender Address Number 1 Yubraj Gayali Palpa Male District Livestock Service Office 9847067265 Baikuntha Nath District Agriculture Development 2 Khanal Palpa Male Organization (DADO) Kul Bahadur 3 Gahatraj Palpa Male Bandipokhara VDC Office 9847025590 Karna Bahadur 4 Saud Palpa Male Saud Agrovet 9858751675 Ganesh Prasad Dadeldh Technical office, DADO Service 5 Bhanari ura Male center, Samaijee VDC 9858733182 Man Bahadur Dadeldh 6 Raut ura Male Assistant, Ashigram VDC 9848847181 Dadeldh Technical office, DADO Service 7 Ankilal Bhatta ura Male center, Ashigram VDC 9848776545 Dadeldh Information officer, DLSO 8 Khadka Sahi ura Male Dadeldhura 9848604444 Ratan Bahadur Dadeldh Office assistant, Samaijhee VDC Ayer ura Male Office 9848766449 Mahadev Nawalpa Technical Officer, Agriculture 9 Chaudhary rasi Male service center, DADO 9847274727 Nawalpa Support Office,Agriculture service 10 Krishna Acharya rasi Male center, Jahada 9847088761 Nawalpa 11 Shanta Gautam rasi Male VDC Secretary, Jamuniya VDC 9847093881

Annex 8. The general seasonal calendar of the crops.

Annex 9. Summary of the Eigen value, variance and principle component value of Palpa, Nawalparasi and District.

PC1 PC2 PC3 PC4 PC5 Palpa Eigen value 1.82 1.43 1.20 1.06 0.82 Projected inertia (%) 22.79 17.96 15.11 13.27 10.32 Cumulative projected inertia (%) 22.79 40.75 55.87 69.14 79.46 HHize -0.60 -0.49 -0.06 -0.06 -0.13 area 0.22 -0.63 0.40 -0.29 0.12 hirelab 0.49 -0.35 -0.35 -0.61 0.01 aginvest 0.49 0.30 0.33 0.01 -0.71 market -0.52 0.14 0.12 -0.70 -0.26 nfincome -0.01 -0.72 -0.21 0.33 -0.43 foodss -0.75 0.03 0.41 -0.01 -0.06 tlu 0.31 -0.20 0.76 0.08 0.19 Nawalparasi Eigen value 1.95 1.27 1.06 1.03 0.94 Projected inertia (%) 24.39 15.85 13.27 12.85 11.71 Cumulative projected inertia (%) 24.39 40.23 53.51 66.36 78.07 HHize -0.40 -0.37 0.64 0.25 0.23 area -0.39 -0.05 -0.43 -0.10 -0.10 hirelab -0.39 0.30 -0.20 0.79 0.03 aginvest 0.07 -0.03 -0.33 -0.39 -0.36 market 0.07 0.74 0.21 -0.31 0.39 nfincome 0.37 0.48 0.27 0.03 -0.11 foodss -0.69 0.51 0.02 0.07 -0.25 tlu -0.67 -0.07 0.45 -0.27 0.01 Dadeldhura Eigen value 1.58 1.29 1.15 1.07 0.83 Projected inertia (%) 19.82 16.24 14.45 13.43 10.43 Cumulative projected inertia (%) 19.82 36.06 50.51 63.94 74.37 HHize -0.31 -0.14 0.36 0.63 0.50 area -0.47 -0.31 0.05 -0.61 0.34 hirelab -0.32 -0.65 0.10 -0.15 -0.32 aginvest -0.60 0.34 0.37 -0.20 -0.30 market 0.57 -0.31 0.39 -0.34 0.35 nfincome 0.21 -0.58 0.36 0.30 -0.38 foodss -0.02 -0.42 -0.77 0.08 0.05 tlu -0.66 -0.14 -0.10 0.19 0.12 Note: HHize-HH family member (number), area- HH land holding (ha), hirelab-Hire labour % of HH, aginvest-Investment in agriculture per HH (%), market-Market access (km), nfincome- percentage share of non-farm income per HH, foods-Food self-sufficiency (months) and tlu-Tropical livestock unit.

Annex 10. Different pictures taken during the survey period from Palpa.

Annex 11. Different pictures taken during the survey period from Nawalparasi.

Annex 12. Different pictures taken during the survey period from Dadeldhura.