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Effects of conservation measures on crop diversity and their implications for climate-resilient livelihoods: the case of Rupa Lake Watershed in Nepal

Effects of conservation measures on crop diversity and their implications for climate-resilient... J. Mt. Sci. (2022) 19(4): 945-957 e-mail: jms@imde.ac.cn http://jms.imde.ac.cn https://doi.org/10.1007/s11629-020-6426-3 Original Article Effects of conservation measures on crop diversity and their implications for climate-resilient livelihoods: the case of Rupa Lake Watershed in Nepal 1,2 BAI Yun-li https://orcid.org/0000-0003-0197-7238; e-mail: ylbai.ccap@igsnrr.ac.cn 1,2 FU Chao * https://orcid.org/0000-0001-6869-2400; e-mail: chao.fu@unep-iemp.org THAPA Balaram https://orcid.org/0000-0002-2639-5544; e-mail: bthapa@libird.org RANA Ram Bahadur https://orcid.org/0000-0003-3974-0738; e-mail: rbrana@libird.org 1,2 ZHANG Lin-xiu https://orcid.org/0000-0002-8386-0350; e-mail: lxzhang.ccap@igsnrr.ac.cn *Corresponding author 1 Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 2 United Nations Environment Programme-International Ecosystem Management Partnership (UNEP-IEMP), Beijing 100101, China 3 Local Initiatives for Biodiversity, Research and Development (LI-BIRD), PO Box 324, Pokhara 33700, Nepal Citation: Bai YL, Fu C, Thapa B, et al. (2022) Effects of conservation measures on crop diversity and their implications for climate-resilient livelihoods: the case of Rupa Lake Watershed in Nepal. Journal of Mountain Science 19(4). https://doi.org/10.1007/s11629-020-6426-3 © The Author(s) 2022. Abstract: Agrobiodiversity conservation is vital for indicate that a strategy that combines both awareness achieving sustainability, but empirical studies on the raising and on-farm conservation measures can effects of different practices or measures on crop generate higher crop diversity and better serve the diversity are rare. This study aims to estimate the climate-resilient livelihoods of people in mountainous effects of raising conservation awareness (RCA), areas. building diversity blocks (BDB), and their combination on crop diversity among 240 randomly Keywords: Agrobiodiversity; Conservation measures; selected households surrounding the Rupa Lake Crop species and varieties; Rupa Lake Watershed in Nepal. Based on descriptive analysis and multiple regression models, the results indicate 1 Introduction that the two single measures had no significant effect on the numbers of crop species and varieties grown by households in 2018. However, the combination of Ending hunger, achieving food security and RCA and BDB had a significantly positive effect on the improving nutrition and health, as highlighted in the number of crop varieties, especially for grain and United Nation 2030 Agenda for Sustainable vegetable crops. Considering that these crops are Development, calls for the conservation and essential in the daily lives of local people, the results sustainable use of agrobiodiversity (Jacobsen et al. Received: 23-Aug-2020 2015; Zimmerer and de Haan 2017), which st 1 Revision: 14-Feb-2021 particularly needs strengthening amidst the nd 2 Revision: 12-Jul-2021 rd 3 Revision: 16-Dec-2021 coronavirus disease (COVID-19) crisis (Zimmerer and Accepted: 22-Mar-2022 945 J. Mt. Sci. (2022) 19(4): 945-957 de Haan 2020). Agrobiodiversity refers to the (Mzyece and Ng’ombe 2020). diversity of plants, animals, and microorganisms that Nepal is a mountainous least developed country underpin agricultural systems (Wood and Lenné 1999; located in the Himalayan region, a known hot spot of Narloch et al. 2013; Dedeurwaerdere and Hannachi crop diversity and climate change (Agnihotri and 2019). Different studies have shown its importance in Palni 2007; Yao et al. 2012; Sharma et al. 2019). Since terms of supplying genetic resources that provide a the 1990s, increasing awareness about the importance wide range of critical benefits, such as income of crop diversity has been driving efforts to enhance opportunities and nutritious diets (Kahane et al. 2013; the conservation and utilization of crop diversity in Sibhatu and Matin 2018), the provision of ecosystem Nepal (Gauchan et al. 2017; Joshi et al. 2017). Dozens services such as soil health and water conservation of on-farm conservation methods and practices for (Hajjar et al. 2008), and adaptations to climate different crops have been performed by local change in agricultural systems (Mijatovic et al. 2013; organizations, such as diversity blocks and raising Dempewolf et al. 2014; Kozicka et al. 2020). conservation awareness (RCA) (Sthapit et al. 2012). Agrobiodiversity is even more important for Some studies have investigated the socioeconomic smallholders in mountainous areas. Compared with and institutional factors that influence farmers’ urban and plain areas, mountainous rural decisions and measures to promote crop diversity in communities are more vulnerable in both ecological Nepal (Gauchan et al. 2005; Bragdon et al. 2009; and socioeconomic aspects (Kruijssen et al. 2009). Poudel and Johnsen 2009; Bhattarai et al. 2015). Agriculture is always the most important sector for Further research is needed to quantitatively assess the employment and income sources for local populations effects of different measures on the on-farm in these areas, whereas they are also susceptible to conservation of local crop diversity. frequent natural disasters, soil erosion and ecological The main objective of this study was to degradation (Panagos et al. 2018). There is broad investigate the effects of two conservation measures evidence that agrobiodiversity, especially crop on crop diversity, using the agro-ecosystems in diversity, which is the most valuable component of Nepal’s Rupa Lake Watershed (RLW) as a case study. agrobiodiversity, can provide natural insurance to The two measures are raising conservation awareness risk-averse farmers (Baumgärtner and Strunz 2009; (RCA) and building diversity blocks (BDB) of grain Di Falco et al. 2010). With diversified crop species crops, vegetables, cash crops, and other crops. Based and varieties, farmers can adapt crops and their on the results of this study, their implications for both livelihoods to changing environments (Fowler and crop diversity conservation and climate-resilient Hodgkin 2004). Crop diversity is thus very important livelihoods in mountainous areas such as the RLW are for the functioning of both ecological and agricultural also explored. systems (Johns et al. 2013). Over the last few decades, a range of practices or 2 Materials and Methods measures have become available to help farmers and communities conserve and utilize local crop genetic 2.1 Context of the study site diversity in their farm systems (Jarvis et al. 2011). Recent evidence implies that crop diversification practices can contribute to climate-smart agriculture The RLW is located in the Pokhara valley by improving productivity, livelihood outcomes, (28°08'10" to 28°12'24.4" N, 84°05'54.5" to resilience of cropping systems and reducing carbon 84°10'5.3" E), Kaski District of Gandaki Province, dioxide emissions (Makate et al. 2016), and thus is a approximately 200 km west of Kathmandu, the promising strategy for farmers to adapt to climate capital city of Nepal (Fig. 1). The climate of the change. However, few recommendations exist on how country is sub-tropical, humid, and marked by heavy to diversify cropping systems in ways that best fit the monsoon rainfall (>2000 mm). However, the agroecological and socioeconomic challenges farmers observed climatic trend analysis in the districts of face (van Zonneveld et al. 2020). An important Nepal (1971-2014) showed that the annual maximum research question that remains largely uninvestigated temperature trend was positive (0.07-0.09°C per year) is how to work out which measures would be the most and significant, but the annual precipitation was relevant for crop diversity in a specific situation significantly decreasing in Kaski (DHM 2017). The 946 J. Mt. Sci. (2022) 19(4): 945-957 Fig. 1 Location, landscape and resource sketch map of the Rupa Lake Watershed. RLW covers a total area of 2,707 ha of land, with steep and BDB. Specifically, RCA comprises activities such slopes of 35°-60° and altitudes varying from 580 to as the promotion of diversity fairs and festivals, 1,420 meters above sea level. Of the total area, 33.57% poetry journeys, Teej songs, community-led lake is agricultural land, 61.85% is forestland, 3.69% is cleaning campaigns, plantation campaigns, water bodies, and 0.89% is barren land. Some 1,933 community biodiversity registers, travelling seminars, households of various castes and ethnicities live in the and the establishment of biodiversity information watershed area. The watershed inhabitants have, for centers. The diversity block is an experimental plot of generations, depended on living on integrated farmers’ varieties that is established and managed by farming systems in which farmland, forest, livestock, local communities for research and development and water resources are intertwined. Historically, purposes (Sthapit et al. 2012). Building a functional these ecosystems have experienced periods of diversity block needs to follow several steps and deterioration due to unsustainable agricultural processes, such as collecting seed samples, field practices and the overuse of watershed resources, layout, planting and labelling the crops, harvesting which have had negative impacts on the habitats of seeds, and storing seeds. With initial external support, local plants, such as wild rice, white lotus, wetland the BDB is used as a practical approach not only to birds and fish varieties (Chaudhary et al. 2015). demonstrate the total amount of local crop varieties In the past two decades, several projects relevant and landraces (e.g. rice, taro, finger millet, orchid, to crop diversity conservation and watershed wild rice, white lotus, and medicinal plants) at public management were implemented in the RLW (Bogati places, but also to regenerate seeds and meet the seed 1996). The large majority of these projects were demands for local varieties from community members. implemented through two local organizations, i.e., Jaibikshrot Samarachyan Abhiyan (JSA) and Rupa 2.2 Sample selection and data collection Lake Restoration and Fishery Cooperative (RLRFC), with support from national and international From the total 1,933 households dwelling in the organizations such as the Local Initiatives for lake basin, 240 households were selected based on Biodiversity, Research and Development (LI-BIRD). stratified random sampling method for face-to-face A community-based management approach was interviews with questionnaires in November- adopted to empower local communities to restore, December 2019. Out of 240 sample households, 120 conserve and sustainably utilize crop diversity to households (50%) were randomly selected from the obtain resilient livelihood outcomes (Sthapit and list of shareholders in the RLRFC and member Mijatovic 2014). Several measures for conserving crop households of JSA, while the remaining households diversity were carried out in the RLW, notably RCA were non-shareholders of the RLRFC and 947 J. Mt. Sci. (2022) 19(4): 945-957 nonmembers of JSA. The total number of households conservation measures and crop diversity. Therefore, that were RLRFC shareholders and/or JSA members we further adopted multiple regression models reached 1185. (Cramer and Ridder 1991; Matejka and McKay 2015) Information on household characteristics, to estimate the impact of conservation measures on farmland endowment, and crop production in 2018 the on-farm crop diversity managed by households. was collected from the sample households. The specifications of the models are as follows: Specifically, regarding household characteristics, we Crop = + Intervention + + + (1) gathered information for each family member, Variety = + Intervention + + including age, gender, years of schooling, and ethnicity. With such information, we could obtain + + (2) household demographic characteristics, such as where indicates the -th household in the equations. dependency, education of labourers, and ethnicity of Crop is the vector of dependent variables in Eq. the household. The information on farmland (1), including crop, staple, grain, cash, fruit, and endowment included the types of land owned by a vegetable. These variables indicate the total numbers household and the area and number of plots of each of species of all the crops, staple grain crops, other type of land, such as paddy fields, dry farmland, grain crops, cash crops, fruits, and vegetables grown orchards, tea gardens, forestland, grassland, and fish by a household in 2018, respectively (see all the ponds. variables in Table 1, similarly hereinafter). Staple Information on crop production included the grain crops include rice, wheat, corn, and potato. names and numbers of species and the numbers of Other grain crops include soybean, beans, millet, varieties, which were used to measure crop diversity. barley, and cassava. Cash crops include peanut, In addition, information on the interviewees’ oilseed rape, spices, tea, coffee, herbs, and so on. perception of climate-related disasters was collected Variety is the vector of dependent variables in Eq. during the household interview. All the data were (2), including variety, staple_variety, grain_variety, cleaned and analysed by Stata 15 (StataCorp 2017), a cash_variety, fruit_variety, and vegetable_variety. professional software package for social and economic These variables indicate the total numbers of varieties data analysis. of all the crops, staple grain crops, other grain crops, cash crops, fruits, and vegetables grown by a 2.3 Analysis method household in 2018, respectively. Intervention is the vector of independent In this study, the sample households that variables on the conservation measures in the participated in the same measure (RCA, BDB, or the equations. There are three specific variables, two combined) were identified as a ‘treatment’ group, including RCA, BDB, and combined measures. The named after the measure they participated. For each RCA and BDB indicate the measures mentioned in treatment group, all the other sample households that Section 2.1. The combined measures variable means did not participate in any measure were identified as that the joint measure of RCA and BDB is the ‘control’ group. implemented by a household. In this study, We first used descriptive statistical analysis to households that intervened with combined measures capture the basic characteristics of crop diversity in were excluded from those that intervened with RCA the RLW and then conducted a T-test to determine or BDB to differentiate the effects of combined and the differences in crop diversity between the single measures. treatment and control groups. is the vector of the control variable on The descriptive analysis results identified some household characteristics, including the demographic intuitive relations between conservation measures structure and human capital of a household. The and crop diversity. However, the latter was also conservation and use of crop genetic diversity always subject to other factors, which may have been involve labour-intensive activities such as local seed correlated with the measures and thus may have selection, savings and exchange (Su et al. 2016). The biased the results. Multivariate regressions were demographic structure measured by the dependency adopted to obtain more accurate results by controlling ratio is an indicator used to capture the labour for confounding factors that were correlated with both situation and family care burden of a household. The 948 J. Mt. Sci. (2022) 19(4): 945-957 Table 1 Description of variables Variables Definition Obs Mean Std. D. Min Max Whether intervened with only raising conservation awareness, such as diversity fair and festival, poetry RCA 240 0.117 0.322 0 1 journeys, teej songs, or information centres (1=yes, 0=no) Whether intervened with only building diversity blocks BDB of rice, taro, finger millet, orchid, wildrice, white lotus, 240 0.088 0.283 0 1 or medicinal plants (1=yes, 0=no) Whether intervened with both conservation awareness Combined measures 240 0.150 0.358 0 1 and diversity blocks (1=yes, 0=no) Crop Total number of crop species 240 5.933 2.042 1 12 Staple Number of staple grain crops 240 2.075 0.860 0 4 Grain Number of other grain crops 240 1.025 0.914 0 3 Cash Number of cash crops 240 1.183 0.858 0 4 Fruit Number of fruits 240 0.658 0.556 0 3 Vegetable Whether plant vegetable (1=yes, 0-no) 240 0.954 0.210 0 1 Variety Total number of varieties 240 17.251 7.416 0 38 Staple_variety Number of varieties of staple grain crops 240 3.492 1.994 0 12 Grain_variety Number of varieties of other grain crops 240 1.438 1.596 0 9 Cash_variety Number of varieties of cash crops 240 3.289 2.698 0 13 Fruit_variety Number of varieties of fruits 240 1.658 2.453 0 20 Vegetable_variety Number of varieties of vegetables 240 7.617 4.481 0 40 Land Land size (ha) 240 0.434 0.330 0 2.15 Land_staple Land size of paddy field and dry farmland (ha) 240 0.423 0.326 0 2.15 Land_grain Land size of dry farmland (ha) 240 0.184 0.185 0 1.25 Land size of dry farmland, orchards, and tea gardens Land_cash 240 0.195 0.192 0 1.25 (ha) Land_fruit Land size of orchards and tea gardens (ha) 240 0.011 0.062 0 0.9 Dependency Dependency ratio in a household (%) 239 44.159 47.154 0 300 Education Average years of schooling of labours in household 239 7.664 2.715 0 15 Whether belong to the BCT (Bahun, Chhetri, Tharu) Ethnicity 240 0.788 0.410 0 1 ethnic groups (1=yes, 0=no) Whether the interviewee think the times of drought Drought 240 0.054 0.227 0 1 decreased compared with five years ago (1=yes, 0=no) Whether the interviewee think the times of flood Flood 240 0.546 0.499 0 1 decreased compared with five years ago (1=yes, 0=no) Whether the interviewee think the times of landslide Landslide 240 0.313 0.464 0 1 decreased compared with five years ago (1=yes, 0=no) Gender_interviewee Gender of interviewee (1=male, 0=female) 240 0.425 0.495 0 1 Age_interviewee Age of interviewee (years) 240 49.550 13.390 21 70 Education_interviewee Years of schooling of the interviewee (years) 240 8.871 4.252 0 22 Whether the interviewee belong to the BCT (Bahun, Ethnicity_interviewee 240 0.783 0.413 0 1 Chhetri, Tharu) ethnic groups (1=yes, 0=no) Note: Due to missing data, the sample size of (21) dependency and (22) education is 239. human capital measured by average years of size. in Eq. (2) is the variable of crop species, which schooling of laborers in a household plays an is used to control the effect of crop species on the important role in making decisions on crop planting. varieties. (i=0, 1, 2, 3, 4) is the vector of the Ethnic culture in the form of rituals, food traditions coefficients that captures the determinants of crop and religious practices provides incentives or norms diversity, in which is the effect of conservation for the maintenance of local traditional crop diversity measures on the dependent variables. is the (Subedi et al. 2011; Negi and Maikhuri 2013). constant term, and is the error term. Therefore, has three variables of dependency, During the interview, approximately 30%, 20%, education, and ethnicity, which have been controlled and 48% of households did not farm other grain crops, in other similar studies (Chen and Meng 2007). cash crops, and fruits in 2018, respectively. Therefore, is the vector of the control variable on land there were censored data of the dependent variables endowment which is measured by the landholding of grain, cash, fruit, grain_variety, cash_variety, and 949 J. Mt. Sci. (2022) 19(4): 945-957 fruit_variety. For the continuous dependent variables, among these households, much more than that of any we used the ordinary least squares (OLS) to conduct other crop category. parameter estimation. For the censored dependent variables, we adopted maximum likelihood estimation 3.2 Crop diversity under different measures (MLE) for Tobit regressions. For the binary dependent variables, we also adopted MLE for Probit There were 11.67%, 8.75%, and 15% of regressions. households in the RLW participating in the RCA, BDB, and combined measures treatment groups, respectively. Most households (64.58%) were not 3 Results intervened with any measure and were thus classified in the control group. There were some differences in crop species 3.1 Crop diversity in the RLW diversity between the RCA treatment and control The households in the RLW grew 5.933 crop groups, but the differences were not statistically species in 2018 on average. Among these, staple grain significant. The average number of crop species grown crops accounted for nearly 35% and more than 2 by the RCA treatment group was 5.679, which was species. Additionally, they grew 1.025, 1.183, and 0.360 less than that grown by the control group 0.658 species of other grain crops, cash crops, and (Table 2, row 1). The average numbers of staple and fruits, respectively. Most (95.4%) households grew other grain crop species grown by the RCA treatment vegetables. group were 0.049 more and 0.242 less than those An average of 17.251 crop varieties were grown by grown by the control group, respectively (Table 2, the households in the RLW, including 3.492 varieties rows 2 and 3). The cash crop species and fruit species of staple grain crops, 1.438 varieties of other grain grown by the RCA treatment group were not as crops, and 1.658 varieties of fruits. Cash crops were diversified as those grown by the control group (Table important income sources and were more likely to be 2, rows 4 and 5). However, the households of the RCA grown in this area. The average number of cash crop treatment group were more likely to plant vegetables varieties grown by these households was 3.289, (Table 2, row 6). second only to staple grain crops. Vegetables are very The results of the descriptive analysis indicated important for diversified foods in mountainous areas, some significant differences in crop species diversity especially in remote and less developed rural areas. between the BDB treatment and control groups. The An average of 7.617 vegetable varieties was grown average number of all crop species grown by the BDB Table 2 Descriptive analysis of crop species diversity under different conservation measures Mean Difference Variables T-test p-value (1) Yes (2) No =(2) – (1) (1) Crop 5.679 6.039 0.360 0.878 0.381 (2) Staple 2.107 2.058 -0.049 -0.292 0.771 (3) Grain 0.893 1.135 0.242 1.321 0.188 RCA (4) Cash 1.071 1.200 0.129 0.726 0.449 (5) Fruit 0.607 0.665 0.057 0.480 0.632 (6) Vegetable 0.964 0.961 -0.003 -0.076 0.939 (7) Crop 5.095 6.039 0.943 1.982 0.049** (8) Staple 2.048 2.058 0.010 0.053 0.958 (9) Grain 0.476 1.135 0.659 3.214 0.002*** BDB (10) Cash 0.905 1.200 0.295 1.488 0.138 (11) Fruit 0.619 0.665 0.045 0.334 0.739 (12) Vegetable 0.952 0.961 0.009 0.195 0.846 (13) Crop 6.057 6.039 -0.018 -0.049 0.961 (14) Staple 2.143 2.058 -0.085 -0.527 0.599 (15) Combined Grain 0.914 1.135 0.221 1.302 0.195 (16) measures Cash 1.314 1.200 -0.114 -0.722 0.471 (17) Fruit 0.686 0.665 -0.021 -0.197 0.844 (18) Vegetable 0.914 0.961 0.047 1.181 0.239 Notes: *** and ** indicate p<0.01, p<0.05, respectively. RCA is abbreviated for raising conservation awareness. BDB is abbreviated for building diversity blocks. 950 J. Mt. Sci. (2022) 19(4): 945-957 treatment group was significantly less than that vegetables among the household figs in the combined grown by the control group (p<0.05) (Table 2, row 7). measures group was lower than that in the control The differences in staple crop species diversity group (Table 2, row 18). between the BDB treatment and control groups were For crop variety diversity, the descriptive analysis not significant (Table 2, row 8). The average number showed some differences between the RCA and of other grain crop species grown by the BDB control groups. In terms of the average total number treatment group was significantly less than that of varieties, there was no significant difference grown by the control group (p<0.01) (Table 2, row 9). between the two groups. However, the average The differences in cash crop and fruit species diversity number of staple crop varieties in the RCA treatment between the BDB treatment and control groups were group was significantly greater than that in the not significant (Table 2, rows 10 and 11). The control group (p<0.1) (Table 3, row 2). The numbers households in the BDB treatment group were less of other grain crop, cash crop, fruit, and vegetable likely to plant vegetables (Table 2, row 12). This result varieties in the RCA treatment group were less than indicates that the differences in crop species diversity those in the control group, but the differences were between the BDB treatment and control groups were not significant (Table 3, rows 3-6). mainly attributed to their differences in the diversity All the average numbers of varieties in the BDB of other grain crop species. treatment group were less than those in the control The differences in crop species diversity between group. However, the differences in the numbers of the treatment and control groups were minor and not staple crop, cash crop, fruit, and vegetable varieties significant even at the 10% level in the cases of between the two groups were not significant even at combined measures. The average number of crop the 10% level (Table 3, rows 8, 10, 11, and 12). The species in the combined measures group was 6.057, average number of other grain crop varieties grown by which was 0.018 more than that in the control group the BDB treatment group was significantly less than (Table 2, row 13). The average numbers of staple and that grown by the control group (p<0.01) (Table 3, other grain crop species in the combined measures row 9). group were 0.085 more and 0.221 less than those in The combined measures seemed to have more the control group, respectively (Table 2, rows 14 and effects on improving the variety diversity of all the 15). The average numbers of cash crop species and crops and of the staple grain crops. The average fruit species in the combined measures group were number of all the crop varieties was significantly more diversified than those in the control group higher than that in the control group (p<0.05) (Table (Table 2, rows 16 and 17). The probability of planting 3, row 13). The staple crop varieties grown by the Table 3 Descriptive analysis of crop variety diversity under different conservation measures Variables Mean Difference T-test p-value =(2) – (1) (1) Yes (2) No (1) Variety 16.036 17.187 1.151 0.758 0.449 (2) Staple_variety 3.857 3.187 -0.670 -1.877 0.062* (3) Grain_variety 1.286 1.516 0.230 0.723 0.471 RCA (4) Cash_variety 2.893 3.394 0.501 0.937 0.350 (5) Fruit_variety 1.429 1.645 0.217 0.456 0.649 (6) Vegetable_variety 6.571 7.439 0.867 1.053 0.294 (7) Variety 14.81 17.187 2.378 1.407 0.161 (8) Staple_variety 3.143 3.187 0.044 0.113 0.910 (9) Grain_variety 0.571 1.516 0.945 2.735 0.007*** BDB (10) Cash_variety 2.619 3.394 0.775 1.278 0.203 (11) Fruit_variety 1.190 1.645 0.455 0.844 0.400 (12) Vegetable_variety 7.286 7.439 0.153 0.164 0.870 (13) Variety 19.971 17.187 -2.784 -2.009 0.046** (14) Staple_variety 4.657 3.187 -1.470 -4.038 0.000*** (15) Combined Grain_variety 1.571 1.516 -0.055 -0.186 0.853 (16) measures Cash_variety 3.543 3.394 -0.149 -0.292 0.771 (17) Fruit_variety 1.657 1.645 -0.012 -0.028 0.978 (18) Vegetable_variety 8.514 7.439 -1.076 -1.414 0.159 Notes: *** and ** indicate p<0.01, p<0.05, respectively. RCA is abbreviated for raising conservation awareness. BDB is abbreviated for building diversity blocks. 951 J. Mt. Sci. (2022) 19(4): 945-957 households with combined measures were also except for significantly negative effects on cash crop significantly greater than those grown by the control and vegetable species diversity in this study (p<0.01, group (p<0.01) (Table 3, row 14). The varieties of Table 4, row 4, columns 4 and 6). If the dependency other grain crops, cash crops, fruits, and vegetables in ratio increased by 1%, the number of cash crop species the combined measures group were greater than those decreased by 0.001, and the probability of growing in the control group, but the differences were not vegetables in a household decreased by 0.1%. Growing significant (Table 3, rows 15-18). cash crops and vegetables is always more labor- intensive than growing other categories of crops. A high dependency ratio means there are more elderly 3.3 Results of multivariate regressions individuals and children in the household, which 3.3.1 Effects of measures on crop species implies there is no enough labor to be engaged in diversity growing cash crops and vegetables. Farmland endowment was another important Consistent with the descriptive analysis results, factor affecting crop species diversity. If the the regression results showed that neither RCA nor landholding size increased by 1 ha, the total number the combined measures had a significant effect on of crop species increased by approximately 1.431 crop species diversity since their coefficients were not (p<0.01, Table 4, row 7, column 1). The numbers of significant even at the 10% level (Table 4, rows 1 and staple and cash crop species were more likely to be 3). The measure of BDB had a significantly negative affected by landholding size (p<0.01, Table 4, rows 8 effect on crop species diversity, especially on the and 10, columns 2 and 4). Previous studies found that diversity of other grain crop species (Table 4, row 2, maintaining high crop diversity might be hard for columns 1, and 3). small landholders because of their low-quality land, Furthermore, as a critical variable of household and they could rarely grow multiple crops (Isakson characteristics, the dependency ratio had no 2011; McDougall et al. 2013). The quality of land used significant effect on the diversity of most crop species Table 4 Impacts of interventions on the number of crop species Crop Staple Grains Cash Fruit Vegetable Variables (1) (2) (3) (4) (5) (6) -0.486 0.006 -0.187 -0.095 -0.025 -0.006 (1) RCA (0.412) (0.176) (0.134) (0.122) (0.077) (0.041) -0.819* 0.033 -0.517*** -0.162 -0.028 -0.013 (2) BDB (0.464) (0.198) (0.120) (0.133) (0.086) (0.046) -0.061 0.037 -0.128 0.051 -0.002 -0.037 (3) Combined measures (0.378) (0.161) (0.128) (0.120) (0.073) (0.037) -0.002 -0.001 0.001 -0.001* 0.001 -0.001** (4) Dependency (0.003) (0.001) (0.001) (0.001) (0.001) (0.000) 0.046 0.017 0.011 -0.007 0.006 0.009* (5) Education (0.049) (0.021) (0.017) (0.015) (0.009) (0.005) 0.131 0.104 -0.054 0.094 0.063 -0.014 (6) Ethnicity (0.327) (0.139) (0.110) (0.099) (0.061) (0.032) 1.431*** (7) Land (0.409) 0.501** (8) Land_staple (0.176) 0.167 0.045 (9) Land_Grain (0.248) (0.070) 0.859*** (10) Land_cash (0.210) 0.614 (11) Land_fruit (0.401) 5.101*** 1.713*** 0.929*** (12) Constant (0.473) (0.202) (0.047) (13) Observations 239 239 239 239 239 239 Note: Standard errors in parentheses. *** indicates p<0.01, ** indicates p<0.05, * indicates p<0.1. The marginal effects are reported in columns (3), (4), and (5). 952 J. Mt. Sci. (2022) 19(4): 945-957 3.3.2 Effects of measures on crop variety for growing staple and cash crops was usually higher diversity than that of land used for growing other crops. Therefore, the coefficients of landholding size and Looking at the effects of measures after crop species number were significant in the cases of controlling other variables, we found that BDB had no staple grain and cash crops in this study. The significant effect on the varieties even at the 10% level numbers of other grain crop and fruit species were (Table 5, row 2). The measure of RCA had a positive not affected by landholding size. For many effect on the number of varieties of staple grain crops households, other grain crops, such as beans, were (Table 5, row 1, column 2). The combined measures usually consumed by the households themselves and had significant effects on crop variety diversity (Table thus planted in small areas or even interplanted with 5, row 3). Specifically, the average number of all crop staple grain crops. Fruit trees were also planted in varieties grown by the combined measures treatment small areas and even on barren land. Therefore, their group was 4.102 more than that grown by the control species numbers were not sensitive to landholding group (p<0.01, Table 5, row 3, column 1). The average size. numbers of varieties of staple grain crops, other grain Table 5 Impacts of interventions on the number of crop varieties Variety Staple_variety Grains_variety Cash_variety Fruit_variety Vegetable_variety Variables (1) (2) (3) (4) (5) (6) -0.603 0.579** 0.051 -0.138 -0.031 -0.807 (1) RCA (1.566) (0.288) (0.152) (0.337) (0.241) (0.836) 0.080 0.043 -0.181 -0.012 -0.179 -0.014 (2) BDB (1.771) (0.324) (0.190) (0.390) (0.257) (0.946) Combined 4.102** 1.375*** 0.269* 0.177 0.266 2.164** (3) measures (1.434) (0.263) (0.146) (0.325) (0.243) (0.766) -0.008 -0.002 -0.001 0.001 -0.001 0.002 (4) Dependency (0.010) (0.002) (0.001) (0.002) (0.002) (0.006) 0.250 -0.018 0.005 0.034 -0.003 0.150 (5) Education (0.185) (0.034) (0.018) (0.041) (0.029) (0.101) 0.471 0.292 -0.012 -0.114 0.186 0.617 (6) Ethnicity (1.238) (0.228) (0.115) (0.269) (0.191) (0.651) 2.377*** (7) Crop (0.249) 1.496*** (8) Staple (0.108) 1.134*** (9) Grains (0.052) 1.775*** (10) Cash (0.131) 1.371*** (11) Fruit (0.148) 7.738*** (12) Vegetable (1.345) 3.436** (13) Land (1.589) 0.426 (14) Land_staple (0.292) 0.494* 3.345** (15) Land_grain (0.267) (1.439) 0.967 (16) Land_cash (0.593) 0.100 (17) Land_fruit (1.265) -0.479 -0.054 -2.328 (18) Constant (2.197) (0.378) (1.578) (19) Observations 239 239 239 239 239 239 Note: Standard errors in parentheses. *** indicates p<0.01, ** indicates p<0.05, * indicates p<0.1. The marginal effects are reported in columns (3), (4), and (5). 953 J. Mt. Sci. (2022) 19(4): 945-957 4 Discussion crops, and vegetables grown by the combined measures treatment group were 1.375, 0.268 and 2.164, respectively, more than those grown by the The results of this study have evident control group (p<0.05, Table 5, row 3, columns 2, 3 implications for both crop diversity conservation and and 6). The results indicate that staple grain crops climate-resilient livelihoods in mountainous areas like and vegetables contributed the most to the increase in the RLW. In terms of crop diversity conservation, the total number of crop varieties grown by neither of the two single measures but their households under combined measures. combination could increase the crop diversity of In contrast to household characteristics, crop households in the RLW. The results indicate at least species significantly affected crop variety diversity in two things. First, there is a considerable challenge in this study. The regression results show that no enhancing crop diversity that is demanding on a household characteristics were related to crop variety range of local climatic, geographical, and diversity (Table 5, rows 4, 5 and 6). However, the socioeconomic regimes (Raza et al. 2019; Kozicka et al. types of crop species were highly related to crop 2020). Second, a comprehensive strategy that brings variety diversity. Specifically, the coefficient of the farmers multiple kinds of support, from knowledge to variable crop was 2.377, which implies that the material sources, can help them address such a number of crop varieties would increase by 2.377 challenge more effectively. It can be expected that following an increase of 1 in the number of crop introducing more conservation measures, e.g. species (p<0.01, Table 5, row 7, column 1). The capacity building through training and workshops, coefficients for different categories of crops were all product value addition and marketing, will enhance over 1 (p<0.01, Table 5, rows 8-12, columns 2-6), the effects of existing measures on crop diversity. which indicated that crop variety diversity expanded This study demonstrated the potential more dramatically than did crop species diversity. A mechanisms underlying different measures for reason to explain the result is that, given that climatic conserving crop diversity. RCA activities are essential impacts vary less among different varieties of a for exposing farming communities to the knowledge specific crop species than among different crop and information on biodiversity, and for inspiring species (Raza et al. 2019), farmers are inclined to them to participate in the conservation and adopt multiple varieties to reduce climate-related management of crop diversity (Shrestha et al. 2013). farming risks. However, most of them do not directly translate into Farmland endowment also had significant effects the adoption new varieties if without access of seeds on crop variety diversity. 1-ha increase of land would and other materials. In contrast, diversity blocks can result in increase of 3.436 varieties (p<0.01, Table 5, provide a constant supply of seeds. However, the row 13, column 1). The impact of land endowment on success and sustainability of BDB is dependent upon crop variety diversity differed among categories of the interest, level of awareness, and capacity of the crop species. For staple grain crops, the expansion of local community in sustaining the varieties and seed landholding size did not lead to a corresponding sources, especially given they need to address major increase in the number of crop varieties (Table 5, row technical and financial problems in linking diversity 14, column 2), which implies the trend of specialized blocks with community seed production, community production of grain crops along landholding size seed banks and local markets. We thus inferred that enlargement. However, for other grain crops and the BDB measure when combined with RCA activities vegetables, 1-ha increase of land would lead to can increase both access to seeds and knowledge and increase of 0.494 and 3.345 varieties, respectively thus be effective in enhancing crop diversity. (p<0.1, Table 5, row 15, columns 3 and 6). Other grain In terms of implications for livelihoods, it was crops are considered as livelihood crops due to their found in this study that combined measures had plenty of vegetable proteins and are usually planted significantly positive effects on the variety diversity of for traditional festivals. Vegetables are high-yield, staple grain crops, other grain crops and vegetables. whereas also high-risk in climate shocks, thus farmers Staple grain crops are the most essential crops needed may tend to grow more diversified crops to lower risk in daily life, while other grain crops and vegetables and stabilize crop income (Khan and Verma 2018). are the main sources of multiple nutrients that are critical for human health, especially for smallholder 954 J. Mt. Sci. (2022) 19(4): 945-957 farmers in mountainous areas, as these farmers are 2009). This study provides evidence of an increase in poor and have little market access. Although cash crop diversity with land endowment. crops and fruits can make more profits than other crops, they always require increased inputs and face 5 Conclusion and Perspectives more technical and environmental risks in production. Our results support the assumption that crop diversity conservation can be enhanced by focusing on Our results showed that combined measures small-scale and low-input production processes significantly improved crop variety diversity, (Johns and Sthapit 2004). especially for staple grain crops, other grain crops, Previous studies argued that a higher diversity of and vegetables. This result indicates that the crops could strengthen farmers’ adaptive capacity and combined measures are an efficient way to protect resilience, allowing for increased productivity, stable crop variety diversity, which is the core of incomes and nutritional security at household level agrobiodiversity. We inferred that the BDB measure (Pellegrini and Tasciotti 2014; Makate et al. 2016; when combined with RCA activities can increase both Kozicka et al. 2020). In this study, we did not access to seeds and knowledge that are needed to investigate household livelihoods, and thus could not sustain and enhance crop diversity. assess livelihood outcomes of conservation measures Grains and vegetables are both essential to in the study area. Instead, our results from a maintain the food security, nutrition and health of multivariate regression indicated that the total farmers in mountainous areas. From this perspective, number of crop varieties had a positive effect on the a combination of both raising awareness and on-farm interviewee’s perception of decreasing climate-related conservation measures is recommended to generate disasters compared with five years ago (Table 6, row higher crop variety diversity and improve the 1). We preliminarily inferred combined measures that livelihoods of people in other mountainous areas. deliver higher crop diversity can support the Considering the significant effect of farmland livelihoods of smallholder farmers and rural endowment on both crop species and variety communities by alleviating the impacts of climate- diversities, innovating land use mechanisms to related disasters. However, the effects of different improve farmland endowment for smallholder conservation measures on smallholder farmers’ farmers may be a promising means to promote crop livelihood resilience need to be further investigated diversity. under an extended framework for vulnerability This study has identified several determinants of assessment combined with a sustainable livelihood crop diversity among smallholder farmers in framework (Xu et al. 2020). mountainous areas using local household survey data, Additionally, our results indicated significant which may be a valuable addition to the existing effects of farmland endowment measured by literature. However, we are fully aware of some landholding size on crop diversity in the RLW. A shortcomings in this study. For example, due to a previous survey in the same area indicated that limited sample size, estimations of the heterogeneous landholding size was one of the most important effects of conservation measures among different factors influencing the willingness of farmers to pay groups of households were lacking. For the same for rice landrace conservation (Poudel and Johnsen reason, we did not analyse the impact of different Table 6 Impacts of crop varieties on the interviewee’s perception of climate change Whether the interviewee think the disaster decreasing compared with five years ago (1=yes, 0=no) Variables Drought Flood Landslide Variety 0.003** (0.001) 0.010* (0.005) 0.012*** (0.005) Crop -0.013 (0.008) -0.019 (0.019) -0.014 (0.018) Land -0.129** (0.055) -0.038 (0.104) 0.080 (0.092) Gender_interviewee -0.049 (0.031) 0.164** (0.077) -0.134* (0.070) Age_interviewee 0.002* (0.001) 0.003 (0.003) 0.010*** (0.003) Ethnicity_interviewee -0.026 (0.030) 0.061 (0.078) -0.166** (0.068) Education_interviewee 0.008** (0.004) 0.004 (0.010) 0.021** (0.008) Observations 240 240 240 Note: Standard errors in parentheses. *** indicates p<0.01, ** indicates p<0.05, * indicates p<0.1. 955 J. Mt. Sci. (2022) 19(4): 945-957 Open Access RCA activities and could not suggest specific activities that should be promoted in combined measures. It should be noted that some RCA activities, such as This article is licensed under a Creative Commons diversity fairs, are not only a participatory tool for Attribution 4.0 International License, which permits raising public awareness on the value of conserving use, sharing, adaptation, distribution and reproduction local varieties, but also provide an opportunity for the in any medium or format, as long as you give exchange of seeds and knowledge. These activities are appropriate credit to the original author(s) and the more likely to increase levels of diversity in the farms source, provide a link to the Creative Commons license, of the participants when combined with the BDB and indicate if changes were made. The images or other measure. 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Effects of conservation measures on crop diversity and their implications for climate-resilient livelihoods: the case of Rupa Lake Watershed in Nepal

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J. Mt. Sci. (2022) 19(4): 945-957 e-mail: jms@imde.ac.cn http://jms.imde.ac.cn https://doi.org/10.1007/s11629-020-6426-3 Original Article Effects of conservation measures on crop diversity and their implications for climate-resilient livelihoods: the case of Rupa Lake Watershed in Nepal 1,2 BAI Yun-li https://orcid.org/0000-0003-0197-7238; e-mail: ylbai.ccap@igsnrr.ac.cn 1,2 FU Chao * https://orcid.org/0000-0001-6869-2400; e-mail: chao.fu@unep-iemp.org THAPA Balaram https://orcid.org/0000-0002-2639-5544; e-mail: bthapa@libird.org RANA Ram Bahadur https://orcid.org/0000-0003-3974-0738; e-mail: rbrana@libird.org 1,2 ZHANG Lin-xiu https://orcid.org/0000-0002-8386-0350; e-mail: lxzhang.ccap@igsnrr.ac.cn *Corresponding author 1 Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 2 United Nations Environment Programme-International Ecosystem Management Partnership (UNEP-IEMP), Beijing 100101, China 3 Local Initiatives for Biodiversity, Research and Development (LI-BIRD), PO Box 324, Pokhara 33700, Nepal Citation: Bai YL, Fu C, Thapa B, et al. (2022) Effects of conservation measures on crop diversity and their implications for climate-resilient livelihoods: the case of Rupa Lake Watershed in Nepal. Journal of Mountain Science 19(4). https://doi.org/10.1007/s11629-020-6426-3 © The Author(s) 2022. Abstract: Agrobiodiversity conservation is vital for indicate that a strategy that combines both awareness achieving sustainability, but empirical studies on the raising and on-farm conservation measures can effects of different practices or measures on crop generate higher crop diversity and better serve the diversity are rare. This study aims to estimate the climate-resilient livelihoods of people in mountainous effects of raising conservation awareness (RCA), areas. building diversity blocks (BDB), and their combination on crop diversity among 240 randomly Keywords: Agrobiodiversity; Conservation measures; selected households surrounding the Rupa Lake Crop species and varieties; Rupa Lake Watershed in Nepal. Based on descriptive analysis and multiple regression models, the results indicate 1 Introduction that the two single measures had no significant effect on the numbers of crop species and varieties grown by households in 2018. However, the combination of Ending hunger, achieving food security and RCA and BDB had a significantly positive effect on the improving nutrition and health, as highlighted in the number of crop varieties, especially for grain and United Nation 2030 Agenda for Sustainable vegetable crops. Considering that these crops are Development, calls for the conservation and essential in the daily lives of local people, the results sustainable use of agrobiodiversity (Jacobsen et al. Received: 23-Aug-2020 2015; Zimmerer and de Haan 2017), which st 1 Revision: 14-Feb-2021 particularly needs strengthening amidst the nd 2 Revision: 12-Jul-2021 rd 3 Revision: 16-Dec-2021 coronavirus disease (COVID-19) crisis (Zimmerer and Accepted: 22-Mar-2022 945 J. Mt. Sci. (2022) 19(4): 945-957 de Haan 2020). Agrobiodiversity refers to the (Mzyece and Ng’ombe 2020). diversity of plants, animals, and microorganisms that Nepal is a mountainous least developed country underpin agricultural systems (Wood and Lenné 1999; located in the Himalayan region, a known hot spot of Narloch et al. 2013; Dedeurwaerdere and Hannachi crop diversity and climate change (Agnihotri and 2019). Different studies have shown its importance in Palni 2007; Yao et al. 2012; Sharma et al. 2019). Since terms of supplying genetic resources that provide a the 1990s, increasing awareness about the importance wide range of critical benefits, such as income of crop diversity has been driving efforts to enhance opportunities and nutritious diets (Kahane et al. 2013; the conservation and utilization of crop diversity in Sibhatu and Matin 2018), the provision of ecosystem Nepal (Gauchan et al. 2017; Joshi et al. 2017). Dozens services such as soil health and water conservation of on-farm conservation methods and practices for (Hajjar et al. 2008), and adaptations to climate different crops have been performed by local change in agricultural systems (Mijatovic et al. 2013; organizations, such as diversity blocks and raising Dempewolf et al. 2014; Kozicka et al. 2020). conservation awareness (RCA) (Sthapit et al. 2012). Agrobiodiversity is even more important for Some studies have investigated the socioeconomic smallholders in mountainous areas. Compared with and institutional factors that influence farmers’ urban and plain areas, mountainous rural decisions and measures to promote crop diversity in communities are more vulnerable in both ecological Nepal (Gauchan et al. 2005; Bragdon et al. 2009; and socioeconomic aspects (Kruijssen et al. 2009). Poudel and Johnsen 2009; Bhattarai et al. 2015). Agriculture is always the most important sector for Further research is needed to quantitatively assess the employment and income sources for local populations effects of different measures on the on-farm in these areas, whereas they are also susceptible to conservation of local crop diversity. frequent natural disasters, soil erosion and ecological The main objective of this study was to degradation (Panagos et al. 2018). There is broad investigate the effects of two conservation measures evidence that agrobiodiversity, especially crop on crop diversity, using the agro-ecosystems in diversity, which is the most valuable component of Nepal’s Rupa Lake Watershed (RLW) as a case study. agrobiodiversity, can provide natural insurance to The two measures are raising conservation awareness risk-averse farmers (Baumgärtner and Strunz 2009; (RCA) and building diversity blocks (BDB) of grain Di Falco et al. 2010). With diversified crop species crops, vegetables, cash crops, and other crops. Based and varieties, farmers can adapt crops and their on the results of this study, their implications for both livelihoods to changing environments (Fowler and crop diversity conservation and climate-resilient Hodgkin 2004). Crop diversity is thus very important livelihoods in mountainous areas such as the RLW are for the functioning of both ecological and agricultural also explored. systems (Johns et al. 2013). Over the last few decades, a range of practices or 2 Materials and Methods measures have become available to help farmers and communities conserve and utilize local crop genetic 2.1 Context of the study site diversity in their farm systems (Jarvis et al. 2011). Recent evidence implies that crop diversification practices can contribute to climate-smart agriculture The RLW is located in the Pokhara valley by improving productivity, livelihood outcomes, (28°08'10" to 28°12'24.4" N, 84°05'54.5" to resilience of cropping systems and reducing carbon 84°10'5.3" E), Kaski District of Gandaki Province, dioxide emissions (Makate et al. 2016), and thus is a approximately 200 km west of Kathmandu, the promising strategy for farmers to adapt to climate capital city of Nepal (Fig. 1). The climate of the change. However, few recommendations exist on how country is sub-tropical, humid, and marked by heavy to diversify cropping systems in ways that best fit the monsoon rainfall (>2000 mm). However, the agroecological and socioeconomic challenges farmers observed climatic trend analysis in the districts of face (van Zonneveld et al. 2020). An important Nepal (1971-2014) showed that the annual maximum research question that remains largely uninvestigated temperature trend was positive (0.07-0.09°C per year) is how to work out which measures would be the most and significant, but the annual precipitation was relevant for crop diversity in a specific situation significantly decreasing in Kaski (DHM 2017). The 946 J. Mt. Sci. (2022) 19(4): 945-957 Fig. 1 Location, landscape and resource sketch map of the Rupa Lake Watershed. RLW covers a total area of 2,707 ha of land, with steep and BDB. Specifically, RCA comprises activities such slopes of 35°-60° and altitudes varying from 580 to as the promotion of diversity fairs and festivals, 1,420 meters above sea level. Of the total area, 33.57% poetry journeys, Teej songs, community-led lake is agricultural land, 61.85% is forestland, 3.69% is cleaning campaigns, plantation campaigns, water bodies, and 0.89% is barren land. Some 1,933 community biodiversity registers, travelling seminars, households of various castes and ethnicities live in the and the establishment of biodiversity information watershed area. The watershed inhabitants have, for centers. The diversity block is an experimental plot of generations, depended on living on integrated farmers’ varieties that is established and managed by farming systems in which farmland, forest, livestock, local communities for research and development and water resources are intertwined. Historically, purposes (Sthapit et al. 2012). Building a functional these ecosystems have experienced periods of diversity block needs to follow several steps and deterioration due to unsustainable agricultural processes, such as collecting seed samples, field practices and the overuse of watershed resources, layout, planting and labelling the crops, harvesting which have had negative impacts on the habitats of seeds, and storing seeds. With initial external support, local plants, such as wild rice, white lotus, wetland the BDB is used as a practical approach not only to birds and fish varieties (Chaudhary et al. 2015). demonstrate the total amount of local crop varieties In the past two decades, several projects relevant and landraces (e.g. rice, taro, finger millet, orchid, to crop diversity conservation and watershed wild rice, white lotus, and medicinal plants) at public management were implemented in the RLW (Bogati places, but also to regenerate seeds and meet the seed 1996). The large majority of these projects were demands for local varieties from community members. implemented through two local organizations, i.e., Jaibikshrot Samarachyan Abhiyan (JSA) and Rupa 2.2 Sample selection and data collection Lake Restoration and Fishery Cooperative (RLRFC), with support from national and international From the total 1,933 households dwelling in the organizations such as the Local Initiatives for lake basin, 240 households were selected based on Biodiversity, Research and Development (LI-BIRD). stratified random sampling method for face-to-face A community-based management approach was interviews with questionnaires in November- adopted to empower local communities to restore, December 2019. Out of 240 sample households, 120 conserve and sustainably utilize crop diversity to households (50%) were randomly selected from the obtain resilient livelihood outcomes (Sthapit and list of shareholders in the RLRFC and member Mijatovic 2014). Several measures for conserving crop households of JSA, while the remaining households diversity were carried out in the RLW, notably RCA were non-shareholders of the RLRFC and 947 J. Mt. Sci. (2022) 19(4): 945-957 nonmembers of JSA. The total number of households conservation measures and crop diversity. Therefore, that were RLRFC shareholders and/or JSA members we further adopted multiple regression models reached 1185. (Cramer and Ridder 1991; Matejka and McKay 2015) Information on household characteristics, to estimate the impact of conservation measures on farmland endowment, and crop production in 2018 the on-farm crop diversity managed by households. was collected from the sample households. The specifications of the models are as follows: Specifically, regarding household characteristics, we Crop = + Intervention + + + (1) gathered information for each family member, Variety = + Intervention + + including age, gender, years of schooling, and ethnicity. With such information, we could obtain + + (2) household demographic characteristics, such as where indicates the -th household in the equations. dependency, education of labourers, and ethnicity of Crop is the vector of dependent variables in Eq. the household. The information on farmland (1), including crop, staple, grain, cash, fruit, and endowment included the types of land owned by a vegetable. These variables indicate the total numbers household and the area and number of plots of each of species of all the crops, staple grain crops, other type of land, such as paddy fields, dry farmland, grain crops, cash crops, fruits, and vegetables grown orchards, tea gardens, forestland, grassland, and fish by a household in 2018, respectively (see all the ponds. variables in Table 1, similarly hereinafter). Staple Information on crop production included the grain crops include rice, wheat, corn, and potato. names and numbers of species and the numbers of Other grain crops include soybean, beans, millet, varieties, which were used to measure crop diversity. barley, and cassava. Cash crops include peanut, In addition, information on the interviewees’ oilseed rape, spices, tea, coffee, herbs, and so on. perception of climate-related disasters was collected Variety is the vector of dependent variables in Eq. during the household interview. All the data were (2), including variety, staple_variety, grain_variety, cleaned and analysed by Stata 15 (StataCorp 2017), a cash_variety, fruit_variety, and vegetable_variety. professional software package for social and economic These variables indicate the total numbers of varieties data analysis. of all the crops, staple grain crops, other grain crops, cash crops, fruits, and vegetables grown by a 2.3 Analysis method household in 2018, respectively. Intervention is the vector of independent In this study, the sample households that variables on the conservation measures in the participated in the same measure (RCA, BDB, or the equations. There are three specific variables, two combined) were identified as a ‘treatment’ group, including RCA, BDB, and combined measures. The named after the measure they participated. For each RCA and BDB indicate the measures mentioned in treatment group, all the other sample households that Section 2.1. The combined measures variable means did not participate in any measure were identified as that the joint measure of RCA and BDB is the ‘control’ group. implemented by a household. In this study, We first used descriptive statistical analysis to households that intervened with combined measures capture the basic characteristics of crop diversity in were excluded from those that intervened with RCA the RLW and then conducted a T-test to determine or BDB to differentiate the effects of combined and the differences in crop diversity between the single measures. treatment and control groups. is the vector of the control variable on The descriptive analysis results identified some household characteristics, including the demographic intuitive relations between conservation measures structure and human capital of a household. The and crop diversity. However, the latter was also conservation and use of crop genetic diversity always subject to other factors, which may have been involve labour-intensive activities such as local seed correlated with the measures and thus may have selection, savings and exchange (Su et al. 2016). The biased the results. Multivariate regressions were demographic structure measured by the dependency adopted to obtain more accurate results by controlling ratio is an indicator used to capture the labour for confounding factors that were correlated with both situation and family care burden of a household. The 948 J. Mt. Sci. (2022) 19(4): 945-957 Table 1 Description of variables Variables Definition Obs Mean Std. D. Min Max Whether intervened with only raising conservation awareness, such as diversity fair and festival, poetry RCA 240 0.117 0.322 0 1 journeys, teej songs, or information centres (1=yes, 0=no) Whether intervened with only building diversity blocks BDB of rice, taro, finger millet, orchid, wildrice, white lotus, 240 0.088 0.283 0 1 or medicinal plants (1=yes, 0=no) Whether intervened with both conservation awareness Combined measures 240 0.150 0.358 0 1 and diversity blocks (1=yes, 0=no) Crop Total number of crop species 240 5.933 2.042 1 12 Staple Number of staple grain crops 240 2.075 0.860 0 4 Grain Number of other grain crops 240 1.025 0.914 0 3 Cash Number of cash crops 240 1.183 0.858 0 4 Fruit Number of fruits 240 0.658 0.556 0 3 Vegetable Whether plant vegetable (1=yes, 0-no) 240 0.954 0.210 0 1 Variety Total number of varieties 240 17.251 7.416 0 38 Staple_variety Number of varieties of staple grain crops 240 3.492 1.994 0 12 Grain_variety Number of varieties of other grain crops 240 1.438 1.596 0 9 Cash_variety Number of varieties of cash crops 240 3.289 2.698 0 13 Fruit_variety Number of varieties of fruits 240 1.658 2.453 0 20 Vegetable_variety Number of varieties of vegetables 240 7.617 4.481 0 40 Land Land size (ha) 240 0.434 0.330 0 2.15 Land_staple Land size of paddy field and dry farmland (ha) 240 0.423 0.326 0 2.15 Land_grain Land size of dry farmland (ha) 240 0.184 0.185 0 1.25 Land size of dry farmland, orchards, and tea gardens Land_cash 240 0.195 0.192 0 1.25 (ha) Land_fruit Land size of orchards and tea gardens (ha) 240 0.011 0.062 0 0.9 Dependency Dependency ratio in a household (%) 239 44.159 47.154 0 300 Education Average years of schooling of labours in household 239 7.664 2.715 0 15 Whether belong to the BCT (Bahun, Chhetri, Tharu) Ethnicity 240 0.788 0.410 0 1 ethnic groups (1=yes, 0=no) Whether the interviewee think the times of drought Drought 240 0.054 0.227 0 1 decreased compared with five years ago (1=yes, 0=no) Whether the interviewee think the times of flood Flood 240 0.546 0.499 0 1 decreased compared with five years ago (1=yes, 0=no) Whether the interviewee think the times of landslide Landslide 240 0.313 0.464 0 1 decreased compared with five years ago (1=yes, 0=no) Gender_interviewee Gender of interviewee (1=male, 0=female) 240 0.425 0.495 0 1 Age_interviewee Age of interviewee (years) 240 49.550 13.390 21 70 Education_interviewee Years of schooling of the interviewee (years) 240 8.871 4.252 0 22 Whether the interviewee belong to the BCT (Bahun, Ethnicity_interviewee 240 0.783 0.413 0 1 Chhetri, Tharu) ethnic groups (1=yes, 0=no) Note: Due to missing data, the sample size of (21) dependency and (22) education is 239. human capital measured by average years of size. in Eq. (2) is the variable of crop species, which schooling of laborers in a household plays an is used to control the effect of crop species on the important role in making decisions on crop planting. varieties. (i=0, 1, 2, 3, 4) is the vector of the Ethnic culture in the form of rituals, food traditions coefficients that captures the determinants of crop and religious practices provides incentives or norms diversity, in which is the effect of conservation for the maintenance of local traditional crop diversity measures on the dependent variables. is the (Subedi et al. 2011; Negi and Maikhuri 2013). constant term, and is the error term. Therefore, has three variables of dependency, During the interview, approximately 30%, 20%, education, and ethnicity, which have been controlled and 48% of households did not farm other grain crops, in other similar studies (Chen and Meng 2007). cash crops, and fruits in 2018, respectively. Therefore, is the vector of the control variable on land there were censored data of the dependent variables endowment which is measured by the landholding of grain, cash, fruit, grain_variety, cash_variety, and 949 J. Mt. Sci. (2022) 19(4): 945-957 fruit_variety. For the continuous dependent variables, among these households, much more than that of any we used the ordinary least squares (OLS) to conduct other crop category. parameter estimation. For the censored dependent variables, we adopted maximum likelihood estimation 3.2 Crop diversity under different measures (MLE) for Tobit regressions. For the binary dependent variables, we also adopted MLE for Probit There were 11.67%, 8.75%, and 15% of regressions. households in the RLW participating in the RCA, BDB, and combined measures treatment groups, respectively. Most households (64.58%) were not 3 Results intervened with any measure and were thus classified in the control group. There were some differences in crop species 3.1 Crop diversity in the RLW diversity between the RCA treatment and control The households in the RLW grew 5.933 crop groups, but the differences were not statistically species in 2018 on average. Among these, staple grain significant. The average number of crop species grown crops accounted for nearly 35% and more than 2 by the RCA treatment group was 5.679, which was species. Additionally, they grew 1.025, 1.183, and 0.360 less than that grown by the control group 0.658 species of other grain crops, cash crops, and (Table 2, row 1). The average numbers of staple and fruits, respectively. Most (95.4%) households grew other grain crop species grown by the RCA treatment vegetables. group were 0.049 more and 0.242 less than those An average of 17.251 crop varieties were grown by grown by the control group, respectively (Table 2, the households in the RLW, including 3.492 varieties rows 2 and 3). The cash crop species and fruit species of staple grain crops, 1.438 varieties of other grain grown by the RCA treatment group were not as crops, and 1.658 varieties of fruits. Cash crops were diversified as those grown by the control group (Table important income sources and were more likely to be 2, rows 4 and 5). However, the households of the RCA grown in this area. The average number of cash crop treatment group were more likely to plant vegetables varieties grown by these households was 3.289, (Table 2, row 6). second only to staple grain crops. Vegetables are very The results of the descriptive analysis indicated important for diversified foods in mountainous areas, some significant differences in crop species diversity especially in remote and less developed rural areas. between the BDB treatment and control groups. The An average of 7.617 vegetable varieties was grown average number of all crop species grown by the BDB Table 2 Descriptive analysis of crop species diversity under different conservation measures Mean Difference Variables T-test p-value (1) Yes (2) No =(2) – (1) (1) Crop 5.679 6.039 0.360 0.878 0.381 (2) Staple 2.107 2.058 -0.049 -0.292 0.771 (3) Grain 0.893 1.135 0.242 1.321 0.188 RCA (4) Cash 1.071 1.200 0.129 0.726 0.449 (5) Fruit 0.607 0.665 0.057 0.480 0.632 (6) Vegetable 0.964 0.961 -0.003 -0.076 0.939 (7) Crop 5.095 6.039 0.943 1.982 0.049** (8) Staple 2.048 2.058 0.010 0.053 0.958 (9) Grain 0.476 1.135 0.659 3.214 0.002*** BDB (10) Cash 0.905 1.200 0.295 1.488 0.138 (11) Fruit 0.619 0.665 0.045 0.334 0.739 (12) Vegetable 0.952 0.961 0.009 0.195 0.846 (13) Crop 6.057 6.039 -0.018 -0.049 0.961 (14) Staple 2.143 2.058 -0.085 -0.527 0.599 (15) Combined Grain 0.914 1.135 0.221 1.302 0.195 (16) measures Cash 1.314 1.200 -0.114 -0.722 0.471 (17) Fruit 0.686 0.665 -0.021 -0.197 0.844 (18) Vegetable 0.914 0.961 0.047 1.181 0.239 Notes: *** and ** indicate p<0.01, p<0.05, respectively. RCA is abbreviated for raising conservation awareness. BDB is abbreviated for building diversity blocks. 950 J. Mt. Sci. (2022) 19(4): 945-957 treatment group was significantly less than that vegetables among the household figs in the combined grown by the control group (p<0.05) (Table 2, row 7). measures group was lower than that in the control The differences in staple crop species diversity group (Table 2, row 18). between the BDB treatment and control groups were For crop variety diversity, the descriptive analysis not significant (Table 2, row 8). The average number showed some differences between the RCA and of other grain crop species grown by the BDB control groups. In terms of the average total number treatment group was significantly less than that of varieties, there was no significant difference grown by the control group (p<0.01) (Table 2, row 9). between the two groups. However, the average The differences in cash crop and fruit species diversity number of staple crop varieties in the RCA treatment between the BDB treatment and control groups were group was significantly greater than that in the not significant (Table 2, rows 10 and 11). The control group (p<0.1) (Table 3, row 2). The numbers households in the BDB treatment group were less of other grain crop, cash crop, fruit, and vegetable likely to plant vegetables (Table 2, row 12). This result varieties in the RCA treatment group were less than indicates that the differences in crop species diversity those in the control group, but the differences were between the BDB treatment and control groups were not significant (Table 3, rows 3-6). mainly attributed to their differences in the diversity All the average numbers of varieties in the BDB of other grain crop species. treatment group were less than those in the control The differences in crop species diversity between group. However, the differences in the numbers of the treatment and control groups were minor and not staple crop, cash crop, fruit, and vegetable varieties significant even at the 10% level in the cases of between the two groups were not significant even at combined measures. The average number of crop the 10% level (Table 3, rows 8, 10, 11, and 12). The species in the combined measures group was 6.057, average number of other grain crop varieties grown by which was 0.018 more than that in the control group the BDB treatment group was significantly less than (Table 2, row 13). The average numbers of staple and that grown by the control group (p<0.01) (Table 3, other grain crop species in the combined measures row 9). group were 0.085 more and 0.221 less than those in The combined measures seemed to have more the control group, respectively (Table 2, rows 14 and effects on improving the variety diversity of all the 15). The average numbers of cash crop species and crops and of the staple grain crops. The average fruit species in the combined measures group were number of all the crop varieties was significantly more diversified than those in the control group higher than that in the control group (p<0.05) (Table (Table 2, rows 16 and 17). The probability of planting 3, row 13). The staple crop varieties grown by the Table 3 Descriptive analysis of crop variety diversity under different conservation measures Variables Mean Difference T-test p-value =(2) – (1) (1) Yes (2) No (1) Variety 16.036 17.187 1.151 0.758 0.449 (2) Staple_variety 3.857 3.187 -0.670 -1.877 0.062* (3) Grain_variety 1.286 1.516 0.230 0.723 0.471 RCA (4) Cash_variety 2.893 3.394 0.501 0.937 0.350 (5) Fruit_variety 1.429 1.645 0.217 0.456 0.649 (6) Vegetable_variety 6.571 7.439 0.867 1.053 0.294 (7) Variety 14.81 17.187 2.378 1.407 0.161 (8) Staple_variety 3.143 3.187 0.044 0.113 0.910 (9) Grain_variety 0.571 1.516 0.945 2.735 0.007*** BDB (10) Cash_variety 2.619 3.394 0.775 1.278 0.203 (11) Fruit_variety 1.190 1.645 0.455 0.844 0.400 (12) Vegetable_variety 7.286 7.439 0.153 0.164 0.870 (13) Variety 19.971 17.187 -2.784 -2.009 0.046** (14) Staple_variety 4.657 3.187 -1.470 -4.038 0.000*** (15) Combined Grain_variety 1.571 1.516 -0.055 -0.186 0.853 (16) measures Cash_variety 3.543 3.394 -0.149 -0.292 0.771 (17) Fruit_variety 1.657 1.645 -0.012 -0.028 0.978 (18) Vegetable_variety 8.514 7.439 -1.076 -1.414 0.159 Notes: *** and ** indicate p<0.01, p<0.05, respectively. RCA is abbreviated for raising conservation awareness. BDB is abbreviated for building diversity blocks. 951 J. Mt. Sci. (2022) 19(4): 945-957 households with combined measures were also except for significantly negative effects on cash crop significantly greater than those grown by the control and vegetable species diversity in this study (p<0.01, group (p<0.01) (Table 3, row 14). The varieties of Table 4, row 4, columns 4 and 6). If the dependency other grain crops, cash crops, fruits, and vegetables in ratio increased by 1%, the number of cash crop species the combined measures group were greater than those decreased by 0.001, and the probability of growing in the control group, but the differences were not vegetables in a household decreased by 0.1%. Growing significant (Table 3, rows 15-18). cash crops and vegetables is always more labor- intensive than growing other categories of crops. A high dependency ratio means there are more elderly 3.3 Results of multivariate regressions individuals and children in the household, which 3.3.1 Effects of measures on crop species implies there is no enough labor to be engaged in diversity growing cash crops and vegetables. Farmland endowment was another important Consistent with the descriptive analysis results, factor affecting crop species diversity. If the the regression results showed that neither RCA nor landholding size increased by 1 ha, the total number the combined measures had a significant effect on of crop species increased by approximately 1.431 crop species diversity since their coefficients were not (p<0.01, Table 4, row 7, column 1). The numbers of significant even at the 10% level (Table 4, rows 1 and staple and cash crop species were more likely to be 3). The measure of BDB had a significantly negative affected by landholding size (p<0.01, Table 4, rows 8 effect on crop species diversity, especially on the and 10, columns 2 and 4). Previous studies found that diversity of other grain crop species (Table 4, row 2, maintaining high crop diversity might be hard for columns 1, and 3). small landholders because of their low-quality land, Furthermore, as a critical variable of household and they could rarely grow multiple crops (Isakson characteristics, the dependency ratio had no 2011; McDougall et al. 2013). The quality of land used significant effect on the diversity of most crop species Table 4 Impacts of interventions on the number of crop species Crop Staple Grains Cash Fruit Vegetable Variables (1) (2) (3) (4) (5) (6) -0.486 0.006 -0.187 -0.095 -0.025 -0.006 (1) RCA (0.412) (0.176) (0.134) (0.122) (0.077) (0.041) -0.819* 0.033 -0.517*** -0.162 -0.028 -0.013 (2) BDB (0.464) (0.198) (0.120) (0.133) (0.086) (0.046) -0.061 0.037 -0.128 0.051 -0.002 -0.037 (3) Combined measures (0.378) (0.161) (0.128) (0.120) (0.073) (0.037) -0.002 -0.001 0.001 -0.001* 0.001 -0.001** (4) Dependency (0.003) (0.001) (0.001) (0.001) (0.001) (0.000) 0.046 0.017 0.011 -0.007 0.006 0.009* (5) Education (0.049) (0.021) (0.017) (0.015) (0.009) (0.005) 0.131 0.104 -0.054 0.094 0.063 -0.014 (6) Ethnicity (0.327) (0.139) (0.110) (0.099) (0.061) (0.032) 1.431*** (7) Land (0.409) 0.501** (8) Land_staple (0.176) 0.167 0.045 (9) Land_Grain (0.248) (0.070) 0.859*** (10) Land_cash (0.210) 0.614 (11) Land_fruit (0.401) 5.101*** 1.713*** 0.929*** (12) Constant (0.473) (0.202) (0.047) (13) Observations 239 239 239 239 239 239 Note: Standard errors in parentheses. *** indicates p<0.01, ** indicates p<0.05, * indicates p<0.1. The marginal effects are reported in columns (3), (4), and (5). 952 J. Mt. Sci. (2022) 19(4): 945-957 3.3.2 Effects of measures on crop variety for growing staple and cash crops was usually higher diversity than that of land used for growing other crops. Therefore, the coefficients of landholding size and Looking at the effects of measures after crop species number were significant in the cases of controlling other variables, we found that BDB had no staple grain and cash crops in this study. The significant effect on the varieties even at the 10% level numbers of other grain crop and fruit species were (Table 5, row 2). The measure of RCA had a positive not affected by landholding size. For many effect on the number of varieties of staple grain crops households, other grain crops, such as beans, were (Table 5, row 1, column 2). The combined measures usually consumed by the households themselves and had significant effects on crop variety diversity (Table thus planted in small areas or even interplanted with 5, row 3). Specifically, the average number of all crop staple grain crops. Fruit trees were also planted in varieties grown by the combined measures treatment small areas and even on barren land. Therefore, their group was 4.102 more than that grown by the control species numbers were not sensitive to landholding group (p<0.01, Table 5, row 3, column 1). The average size. numbers of varieties of staple grain crops, other grain Table 5 Impacts of interventions on the number of crop varieties Variety Staple_variety Grains_variety Cash_variety Fruit_variety Vegetable_variety Variables (1) (2) (3) (4) (5) (6) -0.603 0.579** 0.051 -0.138 -0.031 -0.807 (1) RCA (1.566) (0.288) (0.152) (0.337) (0.241) (0.836) 0.080 0.043 -0.181 -0.012 -0.179 -0.014 (2) BDB (1.771) (0.324) (0.190) (0.390) (0.257) (0.946) Combined 4.102** 1.375*** 0.269* 0.177 0.266 2.164** (3) measures (1.434) (0.263) (0.146) (0.325) (0.243) (0.766) -0.008 -0.002 -0.001 0.001 -0.001 0.002 (4) Dependency (0.010) (0.002) (0.001) (0.002) (0.002) (0.006) 0.250 -0.018 0.005 0.034 -0.003 0.150 (5) Education (0.185) (0.034) (0.018) (0.041) (0.029) (0.101) 0.471 0.292 -0.012 -0.114 0.186 0.617 (6) Ethnicity (1.238) (0.228) (0.115) (0.269) (0.191) (0.651) 2.377*** (7) Crop (0.249) 1.496*** (8) Staple (0.108) 1.134*** (9) Grains (0.052) 1.775*** (10) Cash (0.131) 1.371*** (11) Fruit (0.148) 7.738*** (12) Vegetable (1.345) 3.436** (13) Land (1.589) 0.426 (14) Land_staple (0.292) 0.494* 3.345** (15) Land_grain (0.267) (1.439) 0.967 (16) Land_cash (0.593) 0.100 (17) Land_fruit (1.265) -0.479 -0.054 -2.328 (18) Constant (2.197) (0.378) (1.578) (19) Observations 239 239 239 239 239 239 Note: Standard errors in parentheses. *** indicates p<0.01, ** indicates p<0.05, * indicates p<0.1. The marginal effects are reported in columns (3), (4), and (5). 953 J. Mt. Sci. (2022) 19(4): 945-957 4 Discussion crops, and vegetables grown by the combined measures treatment group were 1.375, 0.268 and 2.164, respectively, more than those grown by the The results of this study have evident control group (p<0.05, Table 5, row 3, columns 2, 3 implications for both crop diversity conservation and and 6). The results indicate that staple grain crops climate-resilient livelihoods in mountainous areas like and vegetables contributed the most to the increase in the RLW. In terms of crop diversity conservation, the total number of crop varieties grown by neither of the two single measures but their households under combined measures. combination could increase the crop diversity of In contrast to household characteristics, crop households in the RLW. The results indicate at least species significantly affected crop variety diversity in two things. First, there is a considerable challenge in this study. The regression results show that no enhancing crop diversity that is demanding on a household characteristics were related to crop variety range of local climatic, geographical, and diversity (Table 5, rows 4, 5 and 6). However, the socioeconomic regimes (Raza et al. 2019; Kozicka et al. types of crop species were highly related to crop 2020). Second, a comprehensive strategy that brings variety diversity. Specifically, the coefficient of the farmers multiple kinds of support, from knowledge to variable crop was 2.377, which implies that the material sources, can help them address such a number of crop varieties would increase by 2.377 challenge more effectively. It can be expected that following an increase of 1 in the number of crop introducing more conservation measures, e.g. species (p<0.01, Table 5, row 7, column 1). The capacity building through training and workshops, coefficients for different categories of crops were all product value addition and marketing, will enhance over 1 (p<0.01, Table 5, rows 8-12, columns 2-6), the effects of existing measures on crop diversity. which indicated that crop variety diversity expanded This study demonstrated the potential more dramatically than did crop species diversity. A mechanisms underlying different measures for reason to explain the result is that, given that climatic conserving crop diversity. RCA activities are essential impacts vary less among different varieties of a for exposing farming communities to the knowledge specific crop species than among different crop and information on biodiversity, and for inspiring species (Raza et al. 2019), farmers are inclined to them to participate in the conservation and adopt multiple varieties to reduce climate-related management of crop diversity (Shrestha et al. 2013). farming risks. However, most of them do not directly translate into Farmland endowment also had significant effects the adoption new varieties if without access of seeds on crop variety diversity. 1-ha increase of land would and other materials. In contrast, diversity blocks can result in increase of 3.436 varieties (p<0.01, Table 5, provide a constant supply of seeds. However, the row 13, column 1). The impact of land endowment on success and sustainability of BDB is dependent upon crop variety diversity differed among categories of the interest, level of awareness, and capacity of the crop species. For staple grain crops, the expansion of local community in sustaining the varieties and seed landholding size did not lead to a corresponding sources, especially given they need to address major increase in the number of crop varieties (Table 5, row technical and financial problems in linking diversity 14, column 2), which implies the trend of specialized blocks with community seed production, community production of grain crops along landholding size seed banks and local markets. We thus inferred that enlargement. However, for other grain crops and the BDB measure when combined with RCA activities vegetables, 1-ha increase of land would lead to can increase both access to seeds and knowledge and increase of 0.494 and 3.345 varieties, respectively thus be effective in enhancing crop diversity. (p<0.1, Table 5, row 15, columns 3 and 6). Other grain In terms of implications for livelihoods, it was crops are considered as livelihood crops due to their found in this study that combined measures had plenty of vegetable proteins and are usually planted significantly positive effects on the variety diversity of for traditional festivals. Vegetables are high-yield, staple grain crops, other grain crops and vegetables. whereas also high-risk in climate shocks, thus farmers Staple grain crops are the most essential crops needed may tend to grow more diversified crops to lower risk in daily life, while other grain crops and vegetables and stabilize crop income (Khan and Verma 2018). are the main sources of multiple nutrients that are critical for human health, especially for smallholder 954 J. Mt. Sci. (2022) 19(4): 945-957 farmers in mountainous areas, as these farmers are 2009). This study provides evidence of an increase in poor and have little market access. Although cash crop diversity with land endowment. crops and fruits can make more profits than other crops, they always require increased inputs and face 5 Conclusion and Perspectives more technical and environmental risks in production. Our results support the assumption that crop diversity conservation can be enhanced by focusing on Our results showed that combined measures small-scale and low-input production processes significantly improved crop variety diversity, (Johns and Sthapit 2004). especially for staple grain crops, other grain crops, Previous studies argued that a higher diversity of and vegetables. This result indicates that the crops could strengthen farmers’ adaptive capacity and combined measures are an efficient way to protect resilience, allowing for increased productivity, stable crop variety diversity, which is the core of incomes and nutritional security at household level agrobiodiversity. We inferred that the BDB measure (Pellegrini and Tasciotti 2014; Makate et al. 2016; when combined with RCA activities can increase both Kozicka et al. 2020). In this study, we did not access to seeds and knowledge that are needed to investigate household livelihoods, and thus could not sustain and enhance crop diversity. assess livelihood outcomes of conservation measures Grains and vegetables are both essential to in the study area. Instead, our results from a maintain the food security, nutrition and health of multivariate regression indicated that the total farmers in mountainous areas. From this perspective, number of crop varieties had a positive effect on the a combination of both raising awareness and on-farm interviewee’s perception of decreasing climate-related conservation measures is recommended to generate disasters compared with five years ago (Table 6, row higher crop variety diversity and improve the 1). We preliminarily inferred combined measures that livelihoods of people in other mountainous areas. deliver higher crop diversity can support the Considering the significant effect of farmland livelihoods of smallholder farmers and rural endowment on both crop species and variety communities by alleviating the impacts of climate- diversities, innovating land use mechanisms to related disasters. However, the effects of different improve farmland endowment for smallholder conservation measures on smallholder farmers’ farmers may be a promising means to promote crop livelihood resilience need to be further investigated diversity. under an extended framework for vulnerability This study has identified several determinants of assessment combined with a sustainable livelihood crop diversity among smallholder farmers in framework (Xu et al. 2020). mountainous areas using local household survey data, Additionally, our results indicated significant which may be a valuable addition to the existing effects of farmland endowment measured by literature. However, we are fully aware of some landholding size on crop diversity in the RLW. A shortcomings in this study. For example, due to a previous survey in the same area indicated that limited sample size, estimations of the heterogeneous landholding size was one of the most important effects of conservation measures among different factors influencing the willingness of farmers to pay groups of households were lacking. For the same for rice landrace conservation (Poudel and Johnsen reason, we did not analyse the impact of different Table 6 Impacts of crop varieties on the interviewee’s perception of climate change Whether the interviewee think the disaster decreasing compared with five years ago (1=yes, 0=no) Variables Drought Flood Landslide Variety 0.003** (0.001) 0.010* (0.005) 0.012*** (0.005) Crop -0.013 (0.008) -0.019 (0.019) -0.014 (0.018) Land -0.129** (0.055) -0.038 (0.104) 0.080 (0.092) Gender_interviewee -0.049 (0.031) 0.164** (0.077) -0.134* (0.070) Age_interviewee 0.002* (0.001) 0.003 (0.003) 0.010*** (0.003) Ethnicity_interviewee -0.026 (0.030) 0.061 (0.078) -0.166** (0.068) Education_interviewee 0.008** (0.004) 0.004 (0.010) 0.021** (0.008) Observations 240 240 240 Note: Standard errors in parentheses. *** indicates p<0.01, ** indicates p<0.05, * indicates p<0.1. 955 J. Mt. Sci. (2022) 19(4): 945-957 Open Access RCA activities and could not suggest specific activities that should be promoted in combined measures. It should be noted that some RCA activities, such as This article is licensed under a Creative Commons diversity fairs, are not only a participatory tool for Attribution 4.0 International License, which permits raising public awareness on the value of conserving use, sharing, adaptation, distribution and reproduction local varieties, but also provide an opportunity for the in any medium or format, as long as you give exchange of seeds and knowledge. These activities are appropriate credit to the original author(s) and the more likely to increase levels of diversity in the farms source, provide a link to the Creative Commons license, of the participants when combined with the BDB and indicate if changes were made. The images or other measure. 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Journal

Journal of Mountain Science – Springer Journals

Published: Apr 1, 2022

Keywords: Agrobiodiversity; Conservation measures; Crop species and varieties; Rupa Lake

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