Study area and sample plots

The study was conducted in Kumaun (west Himalaya) from 1995 to 1996 at three sites with similar altitudes: Kalika, 1500–2050 m; Binsar, 1400–2100 m; and Jalna, 1500–1960 m (Figure 2). All sites were either P roxburghii forests, Q leucotrichophora forests, or mixed Quercus forests. Each forest type is hereafter referred to as Myrica habitat. Considering the relative density (RD) of Myrica trees, each habitat type was categorized into three density classes: abundant Myrica (>30% RD), scattered Myrica (1–30% RD), and no-Myrica (with Myrica individuals at recruitment stage).

Three sample plots (1 ha each) in each class were randomly identified, and ten 10 m × 10 m quadrats were placed, at random, on each plot.

Vegetation analysis

The individuals of all tree species in each quadrat were recorded and CBH (circumference at breast height, 1.3 m from the ground) measured. Individuals were categorized as trees (>31 cm CBH), saplings (11–30 cm CBH), and seedlings (<10 cm CBH). Male and female trees were counted separately. Quadrat data were used for the analysis of density, frequency, and dominance following Misra (1968) and Müller-Dombois and Ellenberg (1974). Density distributions in different size categories (Saxena et al 1984; Rawal 1991) were used to characterize population structure after grouping the individuals into 5 CBH classes: (A) <10 cm, (B) 11–30 cm, (C) 31–65 cm, (D) 66–100 cm, (E) 101–135 cm, and (F) >135 cm.

Fruit yield

Potential fruit yield (kg/tree) was estimated 10–15 days prior to fruit ripening during April–May 1996. Five female trees in each of the 5 CBH classes were marked in all habitats. The number of main branches, the number of offshoots per main branch (ie, the average per 5 randomly observed main branches per tree), and the amount of fruit per type of offshoot (ie, the average per 5 offshoots from the low, middle, and upper canopy of each tree) were counted for marked individuals. The yield was calculated following Dhyani and Khali (1993).

Fruit-yield data were pooled and mean yield (kg/tree) for each CBH class (A–F) calculated. For each site, fruit yield in tonnes/ha was obtained by multiplying fruit yield per tree by the density of female plants/ha. The total yield for each site was calculated as total yield = (yield/ha) × total area. The fruit from all CBH classes in different habitats and sites was mixed and weighed in 5 lots of 1 kg each. The amount of fruit in each lot was then counted and the mean value (1800 [±55]) was considered as a standard for conversion into kilograms.

Harvesting and market trends

The extent of harvesting and involvement in resource collection were assumed to depend on market availability and accessibility; two of the selected sites (Kalika and Jalna) were found to be fairly easily accessible, while Binsar is far away from the market (Table 1). The peak collection period normally falls in the second week of May and lasts until the first week of June. During this period, information was obtained for three consecutive days at each site.

After identification of the main routes along which the bulk of the harvest was brought to market, the number of persons involved in resource collection (hereafter referred to as collectors) was recorded and grouped into adults and children. Since the fruit supply is carried from forest to market at fixed times (early morning and late evening), it was easy to count the number of persons bearing fruit who passed along these routes. Collection of fruit by villagers for their own consumption was ignored. Ten individuals in each group (adults and children) were randomly interviewed and their harvest weighed to generate data on the average collection per individual, the number of days spent in fruit collection, and the total income generated. The average harvest per day was 15 kg per adult and 9 kg per child. On average, an individual was involved in collection for 35 days per year and the number of persons involved varied from one site to another (Kalika: 50 adults, 30 children; Jalna: 26 adults, 12 children; Binsar: 5 adults, 4 children). For each group, total extraction was calculated as Te = (C × D) 3 P, where Te = total extraction, C = collection per day per individual, D = number of days involved in fruit collection, and P = number of persons involved. Since the information was obtained for the peak collection period, the data analysis reflects maximum realized extraction.

The contractors purchase fruit from the collectors and sell it to retailers for marketing (Figure 3a,b). Both contractors and retailers (n = 5) were contacted to obtain information on the benefits accrued in each case. The income values are given in Indian rupees (US$ 1 = IRs 35.00, 1996 exchange rates). Projections of potential income (with Myrica fruit processed into squash, jam, or jelly) were made on the basis of reported values (Dhyani and Dhar 1994). The involvement of rural inhabitants as fruit collectors and the income that subsequently accrued (within a 25-km radius of the sites) was also analyzed for three villages at each site. One adult member from each household (n = 10) was contacted in each village to gather information on involvement in and extent of fruit collection.

Statistical analysis

The relationships between various phytosociological parameters, yield, and extraction were statistically tested using the SYSTAT package (Wilkinson 1986).

Species performance

Abundance:On average, Myrica tree density varied from 90 individuals/ha (Binsar: P roxburghii forest) to 155 individuals/ha (Kalika: Q leucotrichophora forest). Among the tree species, the relative density of Myrica (15.4–25.8%) ranked second in all habitats, indicating that it is an important tree component in these forests (Table 2).

Myrica tree density had no relationship to total forest tree density. The relationship was similar for recruits (except in P roxburghii forests, r = 0.575, P < 0.01). However, Myrica tree density (r = 0.717, P < 0.001) increased significantly with total forest tree biomass in P roxburghii forests (assuming that biomass corresponds to basal area). By contrast, Myrica seedling density (r = 20.466, P < 0.05) and sapling density (r = 20.540, P < 0.05) declined with increasing forest biomass in these forests. Such relationships were not apparent for other habitats.

Recruitment and population structure: For all habitats, there was a low frequency of Myrica seedlings, a higher frequency of saplings (P roxburghii, 42.3%; Q leucotrichophora, 50.1%; mixed Quercus, 54.3%), and a continuous decrease toward higher tree classes (Figure 4). If seedling and sapling density are considered as indicators of recruitment, recruitment consistently increased from abundant Myrica stands to no-Myrica stands across stands of different abundance levels (Figure 5).

Fruit yield and extraction

Variation in yield: Comparing the different habitats, the maximum fruit yield (42.1 kg/individual) was in P roxburghii forests and the minimum (28.9 kg/individual) in mixed Quercus forests. There was a positive correlation between fruit yield and tree size category (pine forest, r = 0.977, P < 0.001; Quercus forest, r = 0.980, P < 0.001; mixed Quercus forest, r = 0.996, P < 0.001; n = 9). The mean fruit yield per tree varied significantly depending on the CBH class (LSD 8.24; P < 0.05; Table 3). The potential yield/ha ranged between 4.3 tonnes/ha (Kalika) and 2.0 tonnes/ha (Binsar) (Table 4).

Extraction and market trends: Considering that the fruit is harvested randomly and not from any specific habitat, it was important to assess the realized and the potential yields for all the sites (Table 5). The data reveal that only a small proportion of available resource (potential yield) was being harvested (6.3% for Kalika, 2.8% for Binsar, 7.2% for Jalna).

While passing through different stages of trade, the value of the resource changes considerably (ie, collector to contractor at Rs 12.5/kg, contractor to retail market at Rs 18.0/kg, and retailer to consumer at Rs 25.0/kg). Myrica fruit contributes 50,000–450,000 rupees per year to the economy of the nearby villages (Table 5). The total value of harvested fruit while passing through different trading phases is relatively high (Rs 100,000–890,000 per season).

Ecological patterns

The performance (relative density) of M esculenta in different habitats was comparable (P roxburghii, 16.6–24.8%; Q leucotrichophora, 15.4–25.8%; and mixed Quercus, 15.4–22.9%). However, within a habitat, the distribution of the species exhibited heterogeneity (ie, abundant Myrica, scattered Myrica, and no-Myrica stands). Considering the abundance of Myrica as an indication of stand maturity, the mature Myrica stands (ie, abundant Myrica) showed little variation in density across habitat types (F = 2.824, not significant), but there was a significant difference across sites (F = 54.50, P < 0.05). In contrast, developing stands (ie, scattered Myrica) exhibited differences under varying habitat types (F = 4.597, P < 0.05). However, when sites were compared, this relationship was not significant (F = 1.118, not significant) (Table 6). This indicates that, during the development of a Myrica stand, the pace of Myrica establishment depends greatly on micro (habitat) conditions, irrespective of the nature of macro (site) conditions. The importance of this finding must be considered when developing strategies for afforestation including Myrica.

The association of Myrica with P roxburghii is revealing. Poor recruitment of Myrica in mature P roxburghii forests is interesting in view of the fact that P roxburghii itself is considered a colonizer on newer sites (Singh 1993) in the region. Presumably, after P roxburghii becomes established, M esculenta starts to colonize, as reflected in the abundance of new recruits in no-Myrica stands. Such associations are widely reported in the region, especially in Garhwal Himalaya (Kusum Lata and Bisht 1993). Detailed investigation of this issue is needed.

Poor recruitment of Myrica was evident in all habitats. In forestry, poor recruitment is generally attributed to various types of disturbances, for example, fire, grazing, overharvesting, compaction of soil, etc. Further, NTFPs are subject to predation and/or extraction by mammals and human beings, adversely affecting recruitment (Murali et al 1996). These factors may contribute to poor recruitment of Myrica. As far as fire is concerned, it is a common phenomenon in P roxburghii forests but not in Quercus and mixed Quercus forests. In protected sites, grazing, harvesting of biomass, and extraction of fruit are expected to be minimal (eg, in Binsar). It also seems unlikely that the pressure of harvesting (which affects less than 8% of the total yield potential) could have drastically reduced natural regeneration as suggested for Amla (Phyllanthus emblica) in the Biligiri Rangan Hills in India, where approximately 13% of the fruit is harvested (Uma Shankar et al 1996).

Instead, we believe that physical dormancy due to the hard seed coat might be responsible for poor regeneration. The species responds poorly even in germination trials carried out in nursery conditions. Various presowing treatments, for example, mechanically scarified seeds soaked in GA3 solution and prechilling for different lengths of time, increased the germination rate by up to 50% (our unpublished data). Furthermore, the species tends to occupy newer sites at a distance from the mature Myrica stands, suggesting an ability to invade these despite poor regeneration. Poor recruitment in Myrica-dominated stands might also be due to phenolic and other chemical compounds produced by the species (Sun et al 1988). However, this requires further investigation.

Potential for income generation

The present study indicates that Myrica fruit can contribute to the cash economy of local rural inhabitants (Figure 6). At the village level, an average of 60% of households are involved in the harvest and trade of Myrica fruit, wherever the resource is available. An average collection of 73–297 kg per household per season fetches a household Rs 913–3713 (US$ 26–106) per season. This income is significant considering the low annual per capita income in the region (for 1992–1993, Rs 973, or US$ 29.5), particularly in the district of Almora (Rs 594.32, or US$ 17, as calculated at constant 1980–1981 prices; Anonymous 1992–1997). In this respect, the income-generating potential of Myrica correlates well with the potential of NTFPs elsewhere (Hegde et al 1996). Moreover, the extraction and trade of Myrica fruit are largely carried out by rural women (Figure 7). Generally, women in the region contribute very little to income-generating ventures (Swaroop 1991). Their activities with regard to extraction of minor forest products are mostly confined to noncash collections (Rao and Saxena 1996). Myrica therefore offers a potential to improve rural women's income.

Compared to other economically important tree species in the region, for example, Diploknema butyracea (Rs 840–10,920, or US$ 24–312/ha) (Tewari 1997), Myrica has a higher income-generating potential (Rs 25,000–106,250/ha, or US$ 714–3036/ha). This suggests that the species could play an important role in the future.

Value addition

To achieve optimum benefits, value addition can aid the rural economy. For example, if the total realized extraction of Myrica, that is, 57.1 tonnes (from all sites) had been processed as jam, it could have generated Rs 3,150,000 instead of the realized benefits of Rs 1,440,000. Production of squash and syrup could have contributed much more (Dhyani and Dhar 1994). Myrica products exceed the economic potential of other promising trees in the region, for example, Ficus glomerata, with a net income (jelly) of Rs 48.4/kg, and F hispida, with Rs 40.48/kg from jam (Dhyani and Khali 1993). However, these estimates are currently not of great use to the local people because they do not have adequate knowledge of or access to improved processing, packaging technologies, and marketing. Similar cases have been reported elsewhere (Tewari and Campbell 1995).

There is nevertheless a potential for government incentives to promote small-scale village enterprises that could greatly increase rural people's incomes. Such measures can also help to reduce overharvesting and promote conservation (Hegde et al 1996; Uma Shankar et al 1996). Finally, also within the context of ecological and economic sustainability, the availability and yield potential of M esculenta in the region is good. There is no danger of depletion considering current extraction trends, so regeneration of Myrica, albeit poor, does not pose an immediate problem.