Study sites and sampling
The study was conducted in Garhwal region (Western Himalaya) from 2016 to 2017 at eight Rhododendron arboreum rich areas in four hill districts (Chamoli, Tehri, Pauri and Rudraprayag). Voucher specimen of Rhododendron arboreum collected and have been deposited in the Herbarium, Botany department, HNB Garhwal University (specimen no. GUH 8510)6. Identification of R. arboreum has been done through A Field Guide book authored by Rai et al.7. Since it is a wild species and flowers have been collected for our research and field study under the permission from competent authority of State Forest Department, Govt. of Uttarakhand. According to IUCN’s Red List Categories and Criteria, globally Rhododendron arboreum comes under Least Concern (LC) category8. These sites are situated between 30°08′47″ to 30°24′06″ N latitude and 78°25′05″ to 79°12′39″ E longitude with altitudes from 1820 m asl in Nandasain and 2270 m asl in Jadipani (Table 1; Fig. 1). All sites were well stocked (mean stand density ≥ 500 tree/ha) with Rhododendron arboreum trees mixed with Quercus leucotrichophora. We referred these resource rich sites as R. arboreum habitats (Table 1). Stratified random sampling method (i.e. stand density and CBH class’s strata) were carried out these eight sites. Total sampled area 0.2 ha in each site; two sample plots (size of each plot is 0.1 ha or 31.62 × 31.62 m) nested within 0.2 ha in each site were laid out for trees enumeration. Sample size (number of R. arboreum tree) for a total population in each site were 166 in Phadkhal; 110 in Khirsu; 104 in Khadpatiya; 166 in Ghimtoli; 80 in Jadipani; 74 in Ranichauri; 74 in Nandasain and 96 in Nauti. Out of the standing trees in sample plots, flower bearing trees were 96 in Phadkhal; 90 in Khirsu; 102 in Khadpatiya; 126 in Ghimtoli; 64 in Jadipani; 58 in Ranichauri; 68 in Nandasain and 82 in Nauti, and without flower or smaller trees were 70 in Phadkhal; 20 in Khirsu; 02 in Khadpatiya; 40 in Ghimtoli; 16 in Jadipani; 16 in Ranichauri; 06 in Nandasain and 14 in Nauti. The individuals of all tree species in each plot were recorded along with their CBH (circumference at breast height, 1.3 m above from the ground). Individuals were categorized as mature trees (≥ 31 cm CBH), saplings (11–30 cm CBH) and seedlings (≤ 10 cm CBH)9. Further all the tree individuals have been grouped into 8 CBH classes: (A) 5–15 cm, (B) 16–25 cm, (C) 26–35 cm, (D) 36–45 cm, (E) 46–55 cm, (F) 56–65 cm, (G) 66–75 cm, (H) 76–85 cm. Recorded data were used for the analysis of density10.
Locations of Rhododendron arboreum study sites in Garhwal region (ARC GIS software 10.5 version was used for map preparation. The map was created by Mr. Raman Patel, Research scholar, Dept. of Geology, HNB Garhwal University, Srinagar, Uttarakhand, India).
Flower yield estimation
Flower yield (kg/tree) was estimated during full bloom (flowering season/harvest season February–April 2017). In each sample plot, numbers of flower bearing trees varied from 29–63 trees/0.1 ha. At each site of 0.2 ha sample plot, total 40 trees, 05 flower bearing trees in each of the 08 CBH classes were marked for estimation of flower yield. The number of main branches, the number of sub- branches/offshoots per main branches (i.e. average per five randomly selected main branches per tree), and the amount of flower per sub-branches/offshoot (i.e. the average per five offshoots from the low, middle and upper canopy of each tree) were counted form marked individuals. This way flower yield/tree was calculated9,11,12.
The flowers from all CBH classes in each site were mixed and weighted in 5 lots of 1 kg each. The number of flowers in each lot was then counted and the mean value (400.0 ± 9.56) was considered as a standard for conversion into kilograms. Based on this conversion flower yield kg/tree was obtained. Flower yield data were pooled and mean yield (kg/tree) for each CBH class (A–H) calculated. For each site, flower yield in kg/0.2 ha was obtained by multiplying flower yield/tree by the density of flower bearing trees/0.2 ha. The total yield kg/ha for each site was calculated as total yield = (yield/ha) × density of flower bear trees/ha9,11,12.
Extraction/harvesting and marketing trends
Flower extraction and collection were totally dependent on market availability and accessibility of site; one of the selected sites (Ranichauri) was easily accessible, while Phadkhal, Khirsu and Jadipani were moderately accessible. Khadpatiya, Ghimtoli, Nandasain and Nauti sites were far-flung from market (Table 1). The highest extraction was recorded between second week of February and first week of April. During this period, data was obtained for three consecutive days at each site.
Questionnaire based survey was carried out in selective forest fringe villages. Across the sites, total sixteen villages were selected for questionnaire survey, three villages each in Jadipani, Ranichauri, Nandasain and Nauti sites, while one village each in Phadkhal, Khirsu, Khadpatiya and Ghimtoli. In each village 15 families were randomly chosen for semi-structured questionnaire survey.
Considering the market availability for trading of the R. arboreum flower products, Nandasain and Nauti sites are located nearest to local market whereas Khadpatiya and Ghimtoli sites are farthest from local market. As far as the access to resources is concerned, four sites represent open and easy access to resource and four sites represent open and moderate access of resource (Table 1). During questionnaire survey, villagers were asked about the number of persons involved in resource collection (hereafter referred as collectors), age of collectors, timing of collection (early morning and late evening) etc. Ten individuals in each group (adults and children) were randomly interviewed on their harvest load to generate data on the average collection per individual, the number of days spent in flower collection, and the total income generated through this activity.
Squash/juice making factories are generally located nearby urban centers; local NGOs and small entrepreneurs are engaged in this work. These peoples purchase flower from the collectors or middleman for preparation of value product (squash). Collectors of each families (varied from n = 15 in Nanadasain to n = 31 in Jadipani) and buyers (n = 5 each site) were contacted to obtain information on the benefits accrued. The income values are given in Indian rupees (USD 1 = Rs. 68.00, 2017 exchange rates). Projections of potential (probable/-could generate) income (with flower processed into juice or squash) were made. The involvement of rural inhabitants as flowers collectors and the income that subsequently accrued (within a 10 km radius of fringe area) was also analyzed for sixteen villages across the sites. One adult member from each household was contacted in a village to collect information on involvement of flower collection/extraction.
Juice/squash preparation methods and value-added products
The collected flowers are graded for their size and healthiness and the stamens are separated from petals by laborers in the juice processing unit. Petals are cleaned washed with tap water and grinded into small pieces. The petal mass is retained in the water and then boiled for one hour. The slurry (aqueous solution) obtained in this process is left at room temperature for cooling and when it get cold, filtered through linen cloth. The filtrate solution is the pure juice of the flower. For the preparation of squash from the pure juice, about 2 kg of sugar is boiled in one liter of water. Further one liter of pure juice and a small quantity of citric acid (10 g/2 kg sugar) are added to this solution. The mixture is boiled again for 30 min and then left to cool at room temperature13. The obtained solution known as squash is then filtered through linen cloth and stored into containers and bottles for marketing. For long term storage and good test and aroma small amount of sodium benzoate and vanilla or kawra is also mixed in the squash.
Cost–benefit analysis of value- added products
The cost–benefit analysis of value added products prepared from the R. arboreum flowers was calculated in Rs./day which includes labour charges of workers involved in flower collection and materials/items required for preparation of different value added products viz: sugar, preservatives, essence, plastic containers/bottles, packaging materials etc. Labour charge was calculated on the basis of existing daily wages as per market rates. The monetary output was calculated as per the current market rates of the products (Table 2). The cost- benefit analysis of the squash product prepared from the flowers was calculated as Rs./day which includes: (i) Man days incumbent for the flowers extraction from the forest and for the preparation of squash product, (ii) Essential items such as sugar, preservatives etc. and their monetary equivalents, (iii) The total quantity of squash product and their monetary equivalents.
Statistical analysis
Data failed to meet the assumption of normality (Shapiro–Wilk test) as well as homogeneity (Levene statistic); therefore, a non-parametric test (i.e. Independent–Samples Kruskal–Wallis test) was applied for one-way ANOVA. However, to find the interaction of site and cbh on flower production (yield), the same data set was subjected to two-way analysis using univariate analysis. To find if (?) flower yield depends on tree diameter or not, data of actual cbh and flower yield per tree were used to determine a correlation (Pearson Correlation Coefficient) between them. In case of correlation found significant then regression equation was developed to predict flower production based on tree diameter. All analysis were performed using IBM-SPSS 16.0 version14.
Ethics approval and consent to participate
All necessary approval, free prior informed consent, permit, and certification were secured. This was done to adhere to the ethical standards of human participation in scientific research. This study was approved by Research and Consultancy Cell (Ethics Committee) of HNB Garhwal University, Srinagar Garhwal, Uttarakhand, India. All the methods were performed in accordance with the relevant guidelines and regulations.
Source: Ecology - nature.com
