Tree species composition and diversity in relation to anthropogenic disturbances in broad-leaved forests of Bhutan

ABSTRACT

We assessed the impact of anthropogenic activities such as selective felling and resource extraction on plant diversity and forest structure in the broad-leaved forests of Bhutan. The forest area was grouped into three zones according to human influence: settlement-agriculture, semi-disturbed, and natural forest. A total of 140 plant species were identified. Maximum species richness of trees (8 species/plot) was recorded in natural forests and least in the settlement-agriculture zone (3 species/plot). Shannon (1.73 ± 0.62) and Simpson diversity (5.49 ± 2.97) indices were highest for the natural forest zone as compared to the semi-disturbed (0.92 ± 0.74, 2.70 ± 2.05) and settlement-agriculture zones (0.74 ± 0.74, 2.24 ± 2.13). The density and basal area of trees decreased from 373 N ha⁻¹ and 37.9 m² ha⁻¹ in the natural forest zone to 114 N ha⁻¹ and 5.7 m² ha⁻¹ in the settlement-agriculture zone. The diameter distribution revealed a lack of commercial tree species in the higher dbh classes from the settlement-agriculture and semi-disturbed zones due to selective felling. Increasing accessibility and anthropogenic activities caused the reduction in biodiversity of the watershed. Selective felling and resource extraction created gaps which were colonized by non-timber species and this may change the forest structure.

KEYWORDS:

• Disturbance
• forest diversity
• selective felling
• species richness
• Bhutan

EDITED BY John Parrotta

1. Introduction

Watersheds and their forests are rich repositories of biodiversity. They are important for providing services to society such as the production function (e.g., timber and non-timber), protection (e.g., against soil erosion, avalanches), human welfare (e.g., CO₂ sequestration, air, and water quality), and recreational function (Führer 2000). Today, the three important components of a watershed (land, water, and vegetation) are increasingly degraded (Sundriyal & Sharma 1996), leading to a loss in biodiversity (Pereira et al. 2010; Rands et al. 2010; Haddad et al. 2015). The relationship between biodiversity and disturbances (natural and anthropogenic) has been studied extensively (Connell 1978; Khan et al. 1987; Sundriyal & Sharma 1996; Cannon et al. 1998; Masaki et al. 1999; Bengtsson et al. 2000; Peltzer et al. 2000; McKinney 2002; Lorimer & White 2003; Hitimana et al. 2004; Kumar & Ram 2005; Rahman et al. 2009; Seidl et al. 2011; Wangchuk et al. 2014; Covey et al. 2015; Haddad et al. 2015; Pedro et al. 2015; Thom & Seidl 2015). All these studies report a strong impact on biodiversity by influencing forest conditions and forests succession dynamics.

Natural disturbances consist of wildfires, floods, pest calamities, lightning, wind throw, rock fall, and ungulate browsing (Ulanova 2000; Chazdon 2003; Hanewinkel et al. 2008; Seidl et al. 2011; Thom & Seidl 2015), while anthropogenic disturbances include activities such as logging, fodder, fuel wood and leaf litter extraction, agriculture clearing, and the introduction of non-native tree species (Bengtsson et al. 2000; Drapeau et al. 2000; Franklin et al. 2000; Chazdon 2003; Lorimer & White 2003; Onaindia et al. 2004; Wangda et al. 2009). Natural disturbances, which vary in size and frequency (Hiura et al. 1996), effect biodiversity and are an integral part of ecosystems (Dale et al. 2000; Franklin et al. 2002). In combination with stand and/or tree age they influence forest succession dynamics, which suggests that forest vegetation is never stable (Bengtsson et al. 2000). Anthropogenic disturbances due to management may have a higher impact on changes in biodiversity than what would occur under natural conditions (Kumar & Ram 2005). As a result anthropogenic disturbances may lead to less diverse ecosystems and less abundance with lower levels of spatial heterogeneity versus those associated with natural disturbances (Franklin et al. 2000; Mitchell et al. 2002). Anthropogenic impacts are expected to increase with the continued demand for forest resources (Husch et al. 2002; Rands et al. 2010; Hasenauer et al. 2012). It can be expected that this will change old growth forest ecosystems into manmade landscapes (Rahman et al. 2009), leading to habitat fragmentation and declining species richness (McKinney 2002).

Global changes in temperature and carbon dioxide concentration are also predicted to affect biodiversity by changing the competitive situation of tree species within forest stands (Dale et al. 2000; Hillebrand et al. 2008). Thom and Seidl (2015) suggest that increasing disturbances under the expected climate change may lead to higher biological diversity but will negatively affect the ecosystem functions (McKinney 2002; Kumar & Ram 2005). Forest management practices also affect the future development of the forest diversity and the related ecosystem functions (Bengtsson et al. 2000; Peltzer et al. 2000). The impact may vary by region due to the species composition and the applied silvicultural concept (Fredericksen & Mostacedo 2000). Any harvesting or silvicultural operations may lead to a decrease (Cannon et al. 1998; Wangda et al. 2009), an increase (Magnusson et al. 1999; Paillet et al. 2010; Covey et al. 2015), limited (Pelissier et al. 1998) or no effect (Hall et al. 2003; Moktan et al. 2009b; Schweitzer & Dey 2011) on species richness, biodiversity or any other ecosystem service.

Forests in Bhutan, which are almost all owned by the state, can be categorized as either ‘natural forests’ or ‘semi-disturbed’, based on the anthropogenic ‘disturbances’ and ‘accessibility’. The ‘natural forests’, which are usually not under any form of management, may be seen as undisturbed or old growth. In these forests, there are either no anthropogenic disturbances or very limited disturbances in the form of harvesting of non-timber forest products and forest grazing. They are difficult to access and farther away from the human settlements (Dhital 2009). The ‘semi-disturbed’ forests are accessible and nearer to the communities and are preferred for extraction of timber and other resources. These forests are either managed through forest management plans or without management plans (Moktan et al. 2009a). Currently, only about 9% of the forest area is under regular sustainable forest management in Bhutan (DoFPS 2014). The remaining forest area is under tremendous pressure since the major part of the increasingly demanded resources comes from these forests (FRDD 2005b; FRMD 2013).

About 69% of the total population of Bhutan lives in rural areas (NSB 2005) where they are dependent on agriculture and forest resources. With the growth in population the demand for such resources is continuously increasing (DoFPS 2013). The major drivers of deforestation and forest degradation in Bhutan are developmental activities, livestock grazing, forest fire, timber, fuel wood, and non-timber forest product extraction (WMD 2013). Although a loss of forest diversity is expected due to these activities, only very limited impact studies which cover only the conifer belt exist (Gratzer et al. 2002; Roder et al. 2002; Gratzer & Rai 2004; Moktan et al. 2009a, 2009b; Wangchuk et al. 2014).

In our study we will focus on broad-leaved forests which are widely distributed in the Eastern Himalayas (Davidson 2000; Ohsawa 2002), including Southern and Eastern Bhutan (Norbu 2002), spreading along the major river basins (MoAF 2010). While previous studies focused on forest composition and regeneration in broad-leaved forests of dry valley slopes in Western Bhutan (Wangda & Ohsawa 2002, 2006a, 2006b), and the effects of grazing and logging on tree regeneration and diversity in mixed species forest areas (Van Ijssel 1990; Davidson 2000; Norbu 2002; Buffum et al. 2009; Covey et al. 2015), there are very limited or no studies focusing on species diversity and composition in relation to ‘natural’ and ‘disturbed forests’ due to anthropogenic utilization. The mission of this study is to investigate and assess management effects on forest biodiversity and timber species abundance in the broad-leaved forests within the watershed 144a in Dagana, Bhutan. We are specifically interested in:

1. species composition and species richness of different management zones,

2. differences in the biodiversity across the different management zones, and

3. the impact of selective cutting and/or other anthropogenic activities on timber and non-timber species.

2. Materials and methods

2.1. Study area

The study area is located within the geographical limit of 26°54ʹ16ʺ to 27°01ʹ36ʺ north and 89°51ʹ19ʺ to 89°57ʹ58ʺ east in the district of Dagana (Figure 1). The area, which has a low socioeconomic development status (NSB 2014), is classified as degraded (WMD 2015), and is part of the Dagachhu sub-basin which belongs to the bigger Punatsangchhu river basin. The watershed has an area of 6422 ha and consists of the Buedulumchhu, Baleychhu, Zharingaychhu, and Lemichhu sub-watersheds. It comprises four geogs (group of villages) with 701 households and has an officially registered population of 6136.

Figure 1. Map of the study area showing the three different management zones along with the inventory plots.

The altitude of the watershed ranges from 500 to 2400 m.a.s.l (Table 1). The three climate stations located in the watershed at elevation of 1600, 1200, and 1000 m.a.s.l were established only in 2015. The 1 year climate data collected from these three stations corresponds with the data obtained from the two nearby stations. The mean annual precipitation is 2020 mm at Daga Dzong (1460 m.a.s.l.) and 1770 mm at Drujaygang station (1140 m.a.s.l.). The maximum precipitation occurs within the monsoon period from June to September. Mean monthly temperatures in Dagana range from 9.3°C in January to 20.7°C in July. Mean temperatures in Drujaygang range from 12.7°C in January to 24.2°C in July. Geologically, the area is located within the crystalline zone of the high Himalayas which was formed from migmatites and granite-gneisses (WMD 2015). The forest covers about 76% of the land area. According to the classification of Grierson and Long (1983), three types of forests can be distinguished: (i) sub-tropical forests (up to 1000 m), (ii) warm, broad-leaved forests (1000–2000 m), and (iii) cool, broad-leaved forests (2000 m and above). The dominant species recorded within the watershed are given in Appendix 1.

Table 1. Mean, minimum (Min), maximum (Max), and standard deviation (Sd) of (i) site characteristics elevation and slope as wells as (ii) the stand characteristics density, basal area, volume, mean dbh, and mean height.

	Natural forest (n = 36)				Semi-disturbed (n = 31)				Settlement&Agri (n = 29)
	Mean	Min	Max	Sd	Mean	Min	Max	Sd	Mean	Min	Max	Sd
Elevation (m)	1951	1392	2413	231	1429	675	1848	326	1229	906	1788	248
Slope (°)	27.5	3	61	13	26.8	5	44.5	7.8	22.5	5	39	7.7
Quadratic mean dbh (cm)	36.8	18.7	68.3	11.8	21.9	0	73.0	15.9	19.1	0	38.3	12.6
Mean tree height (m)	16.93	9.3	28.2	4.3	10,8	0	24	5.77	7.8	0	16.1	5.4
Trees (N ha^−1)	373	40	1080	236	175	0	820	200	114	0	540	145
Saplings (N ha^−1)	305	0	1220	277	241	0	1500	329	80	0	620	140
Estd.Seedl (N ha^−1)	1181	0	6250	1659	1427	0	8000	1950	655	0	3250	960
UnEstd.Seedl (N ha^−1)	2250	0	9750	2621	2161	0	40500	7196	1363	0	11750	2560
Recruits (N ha^−1)	2021	0	14000	3313	1395	0	2100	4072	500	0	6750	1341
Basal Area (m^2 ha^−1)	37.9	2.4	98.2	23.9	9.63	0	45.8	12.7	5.7	0	27.6	7.2
Volume (m^3 ha^−1)	418.9	13.2	1376.5	324.3	84.8	0	480	124.4	49.8	0	274.6	69.1

n = Number of Plots; Trees (dbh ≥10 cm), Saplings (dbh ≥5 to <10 cm), Estd.Seedl: Established Seedlings (dbh <5 cm and height >2 m), UnEstd.Seedl: Unestablished seedlings (dbh <5 cm and height <2 m), Recruits (current year seedlings).

2.2. Study design

The forest area can be divided in to three different anthropogenic ‘disturbance zones’: (i) settlement-agriculture, (ii) semi-disturbed, and (iii) natural forest zones (Figure 1). The settlement-agriculture zone with an area of 1666 ha consists of settlements and private agricultural fields with a few patches of private forests that are strongly protected. The settlement-agriculture zone is located within elevation range from 906 to 1778 m.a.s.l with mean elevation of 1229 m.a.s.l. The slope of the area is gentle to moderately steep with a mean slope of 22.5° (Table 1). The semi-disturbed zone with an area of 1834 ha is the buffer zone between settlement-agriculture and the natural forest zone. Timber and other resources for the rural households are supplied from these forests based on a single tree selection system without any forest management plans. It shows strong anthropogenic management impacts because it is located next to human settlements within the elevation range of 675–1848 m.a.s.l and thus easy to assess for extracting timber, fuel wood, non-timber forest products, and cattle grazing. The road network is concentrated in these two zones of settlement-agriculture and semi-disturbed zones (Waiba 2015). The slope of the area varies from 5° to 44° with a mean slope of 26.8°. The natural forest zone overlaps with the semi-disturbed zone with elevation ranging from 1392 to 2413 m.a.s.l and mean elevation of 1951 m.a.s.l (Table 1). In the natural forest zone, only minor anthropogenic disturbances due to harvesting and limited forest grazing are evident. The natural forest zone with an area of 2921 ha is difficult to access, and farther away from the human settlement areas. The slope of the natural forest zone varies from a very gentle slope of 3° to a steep slope of 60° and a mean slope of 27.5^o. The steeper slopes are only found in the upper part of the forest zone with bamboo undergrowth. The mean elevation and mean slope of the three zones confirms the comparability of the results and therefore assumes that the differences in the diversity and species composition are mainly due to anthropogenic disturbances (Table 1).

In summer 2014 a forest inventory was conducted within the study area. The inventory design was adopted from the design of the national forest inventory of Bhutan (FRMD 2012). Within the watershed, we established 96 inventory points in a systematic grid of 800 m by 800 m. Thirty-six plots of the 96 plots are in the natural forest zone, 31 in the semi-disturbed zone, and 29 in the settlement-agriculture zone (Table 1). Circular plots with plot size of 500 m² (r = 12.62 m) were established to collect sapling (dbh ≥5 to <10 cm) and tree data (dbh ≥10 cm). The regeneration data of the plots was collected on an inner plot area of 40 m² (r = 3.57 m). No herbaceous data were collected. All plot radii were corrected for slope.

2.3. Forest stand data

Recorded tree data consists of the tree species, dbh, tree height, height to live crown base, azimuth, and horizontal distance from the plot center. For saplings, only the dbh and the height were recorded. Regeneration data were recorded by the number of (i) established seedlings (dbh <5 cm and height >2 m), (ii) un-established seedlings (dbh <5 cm and height <2 m), and (iii) recruits (current year seedlings) within the regeneration plot. In addition to the tree parameters, information on elevation, topography, slope, aspect, land ownership, forest management type, understory, and disturbances (grazing, forest fire, etc.) were recorded.

The number of trees, mean tree height, quadratic mean diameter, basal area, and stand volume were calculated for each plot (Table 1). We sorted the trees into timber and non-timber species to study the impact of selective cutting on the species composition. A taxonomist from the Department of Forests & Park Services (DoFPS) and a local timber harvesting contractor were part of the inventory team which helped with the identification of the species. The existing forest management plans of same forest types in the country, having information on the available timber species, their harvesting plan and management, also aided in sorting the species into timber and non-timber (FRDD 2005a, 2006, 2008). Additionally, we also interviewed representatives of the local people on their preferred tree species for timber, firewood, and fodder species. The interviews were conducted during the Watershed Management Planning workshop held by the office of the Watershed Management Division, DoFPS (WMD 2015). The timber species, as per the forest management plans, are shown with one asterisk (*) and results from the interview with the local people are shown with two asterisks (**) (Appendix 1). We calculated the stem number per hectare by dbh class for, ‘timber’ and ‘non-timber’ species, and management zone. Basal area and diameter distribution were used to study the abundance of timber species in the zones. The age distribution within the forest could not be assessed due to lack of information and when age is not available, dbh is often used as a substitute for age (Veblen 1992). Volume was calculated according to the volume equations of Laumans (1994), FSI (1996), FRDD (2005c) – Appendix 2.

Next we calculated the diversity indices, species richness, and evenness for each of our inventory plots. Biodiversity was assessed with the species richness, Shannon index, Simpson’s index, and evenness. Species richness refers to the number of species recorded in each of the plot (Spellerberg & Fedor 2003). The Shannon index H’ (Shannon & Weaver 1949) is a measure of the number of species S and their even distribution according to the proportion of species p_i and can be calculated as:

(1)

The Simpson index D is measure of diversity, which takes into account the number of species S and the relative abundance of each species with values starting from one. Higher values obtained with the Simpson index indicate greater diversity. It is calculated as (Simpson 1949):

(2)

Evenness indicates how even the species are distributed in the forest with values ranging from 0 to 1, where 1 means an equal distribution and values approaching 0 mean unequal distribution. It was calculated as:

(3)

where H’ is the Shannon index and S is the number of species (Pielou 1969).

The plot results were assigned to one of our management zones (natural forest zone, semi-disturbed zone or settlement-agriculture zone) and the corresponding means and the standard deviations were calculated. In order to compare the diversity between different dbh classes, we grouped the diversity (Shannon index) of trees, saplings, and seedlings based on the quadratic mean dbh classes (10–30, 30–50 & 50–70) of trees for each of the zones. We then calculated the mean of the diversity for each of the dbh classes for trees, saplings, and established seedlings.

All data and statistical analysis were conducted in R environment (R Core Team 2015). We used the generalized linear model (glm) to assess any significant differences between the three different zones, while considering other available variables such as elevation, slope, and forest type (Equation 4).

(4)

The variables which were significant at 5% probability and with variance inflation factor (VIF) <5 were taken up in the final model for assessing the significant differences in the means between the zones. A 5% probability is required for significance and a VIF of <5 to avoid multicollinearity. The glm procedure with the Tukey’s multiple comparison of means test was used for post-hoc comparison of the means between the zones (Bretz et al. 2010). Regeneration of the different zones was compared using the Kruskal–Wallis test for all means. When the Kruskal–Wallis statistic was significant, we employed the post-hoc Kruskal Nemenyi test for multiple means comparison (Pohlert 2014).

3. Results

3.1. Species composition, richness, and diversity of the different zones

We started our analysis by comparing the stand characteristics and the biodiversity between the three different management zones of: (i) the settlement-agriculture zone where we expect the highest impact on biodiversity, (ii) the semi-disturbed zone with the cuttings of only highly valuable tree species and resource extraction, and (iii) a natural forest zone with only very minor or no anthropogenic activities (Figure 1). This natural forest zone may be seen as undisturbed or old growth forests representing a ‘reference area’ to assess the ‘potential’ species richness and biodiversity in our study area. Our forest inventory within the watershed 144a recorded 124 tree species (Table 2) and 16 shrub species (Table 3). These values indicate that the biodiversity of the forests within the area is rich. The highest number of species (83 tree and 12 shrub species) were recorded in the natural forest zone, 51 tree and 8 shrub species in the semi-disturbed zone and 41 tree and 3 shrub species in the settlement-agriculture zone (Tables 2 and 3). Maximum species richness for trees (8 species/plot) was recorded in the natural forest and least in the settlement-agriculture zone (3 species/plot) (Figure 2(a)). The glm with Tukey’s multiple comparison of means indicated no significant differences for the density of trees (N ha⁻¹) between natural forests and the semi-disturbed zones (Table 4). The basal area (m² ha⁻¹) and volume (m³ ha⁻¹) of trees (dbh ≥10 cm) were significantly higher in the natural forest zone than the other two disturbed zones (Table 4). The diversity (Shannon and Simpson’s) indices were significantly higher in the natural forest zone than in the other two zones (Table 4; Figure 2(b,c)). However, the diversity of established seedlings were highest in the semi-disturbed zone (Figure 2(b,c)). Oliver and Larson (1996) and Buffum et al. (2008) also confirmed the increase in seedling diversity after disturbances. As with the diversity, the evenness was highest in the natural forest zones, except for the established seedlings which had highest numbers in the semi-disturbed zone (Table 4). The differences in mean biodiversity values for the trees and saplings between the zones were higher for the quadratic dbh class of 30–50 and 50–70 indicating that cutting of trees was frequent in the higher dbh classes (Figure 3).

Table 2. Density (N ha⁻¹) and standard deviation of the tree species in the three zones.

	Density (Mean ± SD)
Species	Natural forests	Semi-disturbed	Settlement and Agri
Acer campbellii	5.6 ± 18.9	0.6 ± 3.6	-
Acer hookeri	0.6 ± 3.3	-	-
Acer laevigatum	1.6 ± 5.6	-	-
Acer thompsonii	0.6 ± 3.3	-	-
Ailanthus integrifolia	-	0.6 ± 3.6	2.1 ± 8.2
Alangium chinense	-	-	1.4 ± 7.4
Albezia chinensis	-	-	0.7 ± 3.7
Albizia gambelii	-	5.2 ± 18.6	2.1 ± 6.2
Albizia jilibrissinn	-	0.6 ± 3.6	-
Albizia lebbeck	-	-	0.7 ± 3.7
Albizia procera	-	0.6 ± 3.6	-
Alnus nepalensis	-	17.4 ± 82.9	11 ± 52
Alseodaphne sp.	10.6 ± 33.6
Amoora wallichii	4.4 ± 12.7	-	3.44 ± 12
Aphanamixis polystachya	1.1 ± 6.7	-	-
Artocarpus chama	-	-	0.7 ± 3.7
Aurelia sp.	-	-	0.7 ± 3.7
Bauhinia purpurea	-	-	0.7 ± 3.7
Beilschmiedia sp.	22.8 ± 40.9	4.5 ± 19.1	-
Betula alnoides	1.7 ± 10	-	-
Bischofia javanica	-	-	1.4 ± 5.2
Bombax ceiba	-	2.6 ± 8.6	2.8 ± 11.6
Callicarpa arborea	-	1.3 ± 5	0.7 ± 3.7
Carpinus viminea	1.1 ± 4.6	-	-
Casearia glomerata	7.8 ± 18.1	7.1 ± 26.1	-
Casearia sp.	1.1 ± 4.6
Castanopsis hystrix	8.9 ± 23.1	0.6 ± 3.6	-
Castanopsis indica	1.7 ± 5.6	1.9 ± 7.9	-
Castanopsis tribuloides	5.6 ± 15.6	-	-
Celtis australis	-	1.2 ± 7.2	-
Celtis sp	-	1.3 ± 7.2	2.8 ± 10.3
Celtis tetranda	-	0.6 ± 3.6	1.4 ± 7.4
Choerospondias axill	-	0.6 ± 3.6	-
Chukrasia tabularis	-	-	1.3 ± 5.2
Cinnamomum bejolghota	8.9 ± 27.6	-	0.7 ± 3.7
Cinnamomum glaucescens	1.1 ± 4.6
Cinnamomum impressinervium	1.7 ± 10	-	-
Dalbergia sericea	-	4.5 ± 18.5	2.1 ± 6.2
Daphniphyllum sp.	1.7 ± 10	-	-
Debregeasia longifolia	-	1.3 ± 5	-
Echinocarpus decicarpus	1.1 ± 4.6
Elaeocarpus lanceifolius	1.7 ± 7.4	-	-
Elaeocarpus sp.	5.0 ± 21	1.3 ± 4.9	0.7 ± 3.7
Engelhardtia spicata	2.2 ± 8	12.9 ± 33.3	-
Eryobutrea sp.	3.3 ± 16.9	-	-
Erythrina arborescens	0.6 ± 3.3	-	0.7 ± 3.7
Exbucklandia populne	1.7 ± 7.4	-	-
Ficus auriculata	-	3.2 ± 18	6.2 ± 19.3
Ficus nerifolia	1.7 ± 7.4	0.6 ± 3.6	1.4 ± 7.4
Ficus semicordata	-	1.3 ± 7.2	2.8 ± 8.8
Ficus sp.	0.6 ± 3.3	1.3 ± 7.2	2.1 ± 6.2
Garcinia sp.	1.7 ± 7.4	-	-
Glochidion sp.	2.8 ± 7	2.6 ± 11.2	-
Gordonia excelsa	-	2.6 ± 14.4	-
Grewia sp.	-	0.6 ± 3.6	2.8 ± 14.9
Gynocardia odorata	-	-	0.7 ± 3.7
Helicea neligerica	0.6 ± 3.3	-	-
Lindera pulcherrima	15.6 ± 43.6	-	-
Lithocarpus elegans	13.3 ± 46.6	0.6 ± 3.6	-
Lithocarpus fenestratus	8.8 ± 29.3	-	-
Litsea luecaena	-	-	0.7 ± 3.7
Litsea sp.	9.4 ± 21.1	-	-
Macaranga denticulata	1.1 ± 6.7	1.3 ± 5	-
Macaranga indica	-	7.1 ± 27.6	2.8 ± 11.6
Macaranga pustulata	14.4 ± 54.8	9.7 ± 46.7	-
Macropanyx dispermus	8.3 ± 18.7	-	-
Magnolia campbellii	-	0.6 ± 3.6	-
Mallotus philippinensis	-	-	2.8 ± 8.8
Mangifera indica	-	2.6 ± 14.4	0.7 ± 3.7
Michelia cathcartii	7.8 ± 14.6	-	2.8 ± 14.9
Michelia doltsopa	2.2 ± 6.4	-	-
Michelia velutina	2.8 ± 7	1.3 ± 5	-
Morus laevigata	-	0.6 ± 3.4	-
Myrsine semiserrata	0.6 ± 3.3	-	-
Neolitsea sp.	0.6 ± 3.3	-	-
Nyssa javanica	2.8 ± 8.5	-	-
Olia sp (fodder tree)	7.8 ± 15.3	-	-
Oroxylum indicum	-	-	4.1 ± 22.3
Oroxylum sp.	-	1.9 ± 10.8
Ostodes paniculata	10.6 ± 31.2	18.7 ± 69.1	8.3 ± 22.4
Ostodes sp.	1.7 ± 5.6	0.6 ± 3.6	0.6 ± 3.7
Persea clarkeana	7.2 ± 23.5	-	-
Persea duthiei	0.6 ± 3.3	-	-
Persea fructifera	4.4 ± 9.7	-	-
Persea lanceolata	5.6 ± 24.2	-	-
Persea sp.	5.6 ± 13.2	0.6 ± 3.6	-
Phoebe attenuata	0.6 ± 3.3	-	-
Phoebe lanceolata	4.4 ± 23.5	-	-
Phyllanthus emblica	1.1 ± 6.7	-	-
Pieris formosa	1.7 ± 10	-	-
Pinus roxburghii	1.1 ± 6.7	-	-
Polygala auriculata	0.6 ± 3.3	-	-
Prunus sp.	1.1 ± 4.6	-	-
Pyrularia edulis	0.6 ± 3.3	1.3 ± 5	-
Quercus glauca	8.9 ± 53.3	-	-
Quercus griffithii	1.1 ± 6.7	-	-
Quercus lamellosa	5.6 ± 14	-	-
Quercus tribuloides	-	0.6 ± 3.6	-
Rapanea sp.	0.6 ± 3.3
Rhododendron arboreum	4.4 ± 26.7	-	-
Rhododendron grande	7.2 ± 31	-	-
Rhododendron griffithianum	1.7 ± 10	-	-
Rhododendron maddenii	1.1 ± 6.7	-	-
Rhus chinensis	1.1 ± 4.6	4.5 ± 10	0.7 ± 3.7
Rhus hookeri	-	2.6 ± 11.2
Rhus succedanea	0.6 ± 3.3	0.6 ± 3.6	2.8 ± 14.9
Sapindus mukorossi	-	-	2.1 ± 11.1
Sapium insigne	-	-	0.7 ± 3.7
Saurauja napaulensis	-	-	0.7 ± 3.7
Schefflera sp.	1.1 ± 4.6	-	-
Schima wallichii	1.1 ± 6.7	12.9 ± 38.8	25.5 ± 67.2
Sorbus cuspidata	1.1 ± 6.7	-	-
Sterculia sp.	4.4 ± 12.7	-	-
Symplocos ramosissima	20.6 ± 58.5	0.6 ± 3.6	-
Symplocus lucida	10.6 ± 24.1	1.3 ± 5	-
Symplocus sp.	0.6 ± 3.3	-	-
Syzigium cumini	-	0.6 ± 3.6
Syzigium sp.	8.3 ± 36.7	0.6 ± 3.6	-
Talauma hodgsoni	0.6 ± 3.3	-	-
Terminalia myriocarpa	-	0.6 ± 3.6	0.7 ± 3.7
Terpenia sp.	6.7 ± 19.7	-	-
Tetradium fraxinifolium	0.6 ± 3.3	-	-
Tetradium sp.	2.2 ± 10.5	0.6 ± 3.6	-
Toona ciliata	1.1 ± 4.7	-	-

Table 3. Density (N ha⁻¹) and standard deviation of the shrub species in the three zones.

	Density (Mean ± SD)
Species	Natural Forests	Semi-disturbed	Settlement and Agri
Aeglia sp.	0.6 ± 3.3	-
Brassaiopsis dispermum	2.2 ± 8	-
Brassaiopsis mitis	0.6 ± 3.3	1.3 ± 5	0.7 ± 3.7
Clerodendron sp.	1.7 ± 7.4	0.6 ± 3.6	-
Eurya acuminata	5.6 ± 14	15.5 ± 43.4	2.8 ± 14.9
Homalia sp.	0.6 ± 3.3	-	-
Hydrangea sp.	1.1 ± 6.7	-	-
Ilex sp.	0.6 ± 3.3	-	-
Lyonia ovalifolia	12.2 ± 49.5	0.6 ± 3.6
Maesa chesea	1.1 ± 4.6	3.2 ± 11.7	-
Mussaenda sp.	-	0.6 ± 3.6	-
Premna sp.	-	-	0.7 ± 3.7
Sauraria sp.	0.6 ± 3.3	-	-
Vernonia sp.	1.1 ± 6.7	-	-
Wendlandia sp.	-	1.9 ± 7.9	-
Zanthoxylum sp.	-	0.6 ± 3.6	-

Table 4. Mean values ± standard deviations of density, basal area, and diversity indices for the different zones.

Parameters		Natural forest (n = 36)	Semi-disturbed (n = 31)	Settlement and Agri (n = 29)
Density (N/ha)	Trees	373 ± 235.62^a	175 ± 199.74^a	114 ± 145.41^b
Basal Area (m^2ha^−1)	Trees	37.89 ± 23.9^a	9.63 ± 12.73^b	5.71 ± 7.19^b
Volume (m^3ha^−1)	Trees	418.9 ± 324.29^a	84.77 ± 124.4^b	49.8 ± 69.1^b
Shannon index	Trees	1.73 ± 0.62^a	0.92 ± 0.74^b	0.74 ± 0.74^b
	Saplings	1.23 ± 0.72^a	0.99 ± 0.73^a	0.45 ± 0.72^b
	Estd.Seedl	0.53 ± 0.62^a	0.59 ± 0.52^a	0.33 ± 0.59^a
	UnEstd.Seedl	0.80 ± 0.72	0.46 ± 0.58	0.52 ± 0.59
	Recruits	0.40 ± 0.51	0.24 ± 0.47	0.15 ± 0.40
Simpsons index	Trees	5.49 ± 2.97^a	2.70 ± 2.05^b	2.24 ± 2.13^b
	Saplings	3.52 ± 2.36^a	2.79 ± 2.04^a,b	1.50 ± 2.23^c,b
	Estd.Seedl	1.60 ± 1.56 ^a	1.74 ± 1.21^a	1.13 ± 1.61^a
	UnEstd.Seedl	2.34 ± 2.06	1.47 ± 1.41	1.43 ± 1.52
	Recruits	1.21 ± 1.27	0.71 ± 1.12	0.50 ± 1.08
Evenness	Trees	0.85 ± 0.18^a	0.59 ± 0.43^b	0.56 ± 0.46^b
	Saplings	0.72 ± 0.35^a	0.62 ± 0.41^a	0.30 ± 0.43^b
	Estd.Seedl	0.45 ± 0.46^a	0.56 ± 0.44^a,b	0.25 ± 0.42^a,c
	UnEstd.Seedl	0.56 ± 0.40	0.41 ± 0.45	0.44 ± 0.47
	Recruits	0.37 ± 0.45	0.21 ± 0.40	0.12 ± 0.33

Values in columns followed by the same letter(s) are not significantly different (p < 0.05) according to GLM and Tukey’s multiple comparison of means test.

n = Number of plots in each zone; Trees (dbh ≥10 cm), Saplings (dbh ≥5 to <10 cm), Estd.Seedl: Established Seedlings (dbh <5 cm and height >2 m), UnEstd.Seedl: Unestablished seedlings (dbh <5 cm and height <2 m), Recruits (current year seedlings).

Figure 2. Species richness and diversity: (a) mean number of species per plot, (b) Shannon–Weaver index, and (c) Simpson’s index. Minima, median, maxima, and outliers are indicated. a = Trees (dbh ≥10 cm), b = Saplings (dbh ≥5 to <10 cm), c = Established Seedlings (dbh <5 cm and height >2 m), d = Unestablished seedlings (dbh <5 cm and height <2 m), e = Recruits (current year seedlings).

Figure 3. Mean Shannon–Weaver biodiversity values of trees, saplings, and seedlings grouped by quadratic mean dbh class of trees. (a) Trees (dbh ≥10 cm), (b) saplings (dbh ≥5 to <10 cm), and (c) established seedlings (dbh <5 cm and height >2 m).

3.2. Impact of selective cutting in different zones

In the watershed 144a about 17 species of the 124 tree species are of commercial value (Table 2; Appendix 2). Thus we grouped our data by ‘timber’ and ‘non-timber’ species to analyze the potential differences in the tree species composition by management intensity (our forest zones). The diameter distribution of all the trees in the study area shows un-evenly aged forest (Figure 4). In the natural forest zone, the density of timber species was 118 N ha⁻¹, in the semi-disturbed zone it was 42 N ha⁻¹, and in settlement-agriculture zone it was 45 N ha⁻¹ (Figure 4(a)). The density of timber species above the dbh of 40 cm in the natural forest zone was 47 N ha⁻¹, while it was only 6 N ha⁻¹ in the semi-disturbed zone followed by 4 N ha⁻¹ in the settlement-agriculture zone (Figure 4(b)). Bigger dbh trees of the timber species were found only in the natural forest zone (Figure 4(b)), while bigger dbh trees of non-timber species were present in the semi-disturbed zone (Figure 4(c,d)). The basal area calculated showed maximum basal area for the preferred timber species in the natural forest zone rather than in the semi-disturbed and settlement-agriculture zones (Figure 5(a)). The elevation gradient effect on the missing of certain commercial species from the semi-disturbed zone was studied by comparing the data from plots below 2000 m.a.s.l. The effect was only seen for the Acer spp. but not for other commercial species (Figure 5(b)).

Figure 4. Diameter distribution of timber and non-timber species across the three zones. (a) Timber species distribution, (b) timber species above dbh class of 40 cm, (c) non-timber species distribution, and (d) non-timber species of dbh above 40 cm. * dbh of 40 cm and above are usually cut for timber.

Figure 5. Basal area for the timber species across the three zones: (a) basal area/ha and (b) basal area/ha (plots below 2000 m.a.s.l). a = Acer spp., b = Alnus nepalensis, c = Castanopsis spp., d = Cinnamomum spp., e = Michelia spp., f = Persea spp., g = Phoebe spp., h = Quercus spp., i = Schima wallichi, j = Syzigium spp, k = Terminalia myriocarpa, l = Toona ciliata.

We studied the regeneration pattern in three zones by analyzing the seedlings and sapling density (N ha⁻¹) of the ‘timber’, ‘non-timber’, and ‘shrub’ species in each of the management zones. The density (N ha⁻¹) of unestablished seedlings (dbh <5 cm and height <2 m) and recruits (current year seedlings) of timber species were significantly higher in the natural forest zone than in the semi-disturbed and settlement-agriculture zones (Table 5; Figure 6). The Kruskal–Wallis test indicated no significant differences for the saplings (dbh ≥5 to <10 cm) and established seedlings of the timber species (dbh <5 cm and height >2 m) between the three zones. The presence of higher established seedling density of timber species (242 N ha⁻¹) in the semi-disturbed zone, as compared to the natural forest zone, (215 N ha⁻¹) was due to the presence of high Schima wallichii and Alnus nepalensis seedlings in the private forests, as well as in the landslide and erosion areas in the semi-disturbed zone (Figure 6).

Table 5. Density (N ha⁻¹) ± standard deviation of saplings and seedlings for the different zones.

		Density (Mean ± SD)
Species groups		Natural forests	Semi-disturbed	Settlment and Agri
Timber	Saplings	56 ± 83^a	21 ± 48^a	25 ± 53^a
	Estd.Seedl	215 ± 397^a	242 ± 518^a	52 ± 140^a
	UnEstd.Seedl	847 ± 1064^a	685 ± 2657^b	328 ± 1024^b
	Recruits	1403 ± 2619^a	484 ± 2213^b	86 ± 278^b
Non-timber	Saplings	158 ± 149^a	88 ± 79^a	49 ± 101^b,^c
	Estd.Seedl	674 ± 1253^a	782 ± 1269^a	439 ± 719^a
	UnEstd.Seedl	1181 ± 1894^a	1024 ± 2994^a	759 ± 1410^a
	Recruits	535 ± 1156^a	532 ± 1308^a	371 ± 1085^a
Shrubs	Saplings	91 ± 181^a	132 ± 274^a	6 ± 14^b,c
	Estd.Seedl	292 ± 553^a	403 ± 746^a	164 ± 355^a
	UnEstd.Seedl	222 ± 450^a	452 ± 1645^a	276 ± 588^a
	Recruits	83 ± 260^a	379 ± 1510^a	43 ± 165^a

Values in columns followed by the same letter(s) are not significantly different (p < 0.05) according to Pairwise comparisons using posthoc Kruskal Nemenye test.

Saplings (dbh ≥5 to <10 cm), Estd.Seedl: Established Seedlings (dbh <5 cm and height >2 m), UnEstd.Seedl: Unestablished seedlings (dbh <5 cm and height <2 m), Recruits (current year seedlings).

Figure 6. Seedling and Sapling density (N ha⁻¹) of the timber, non-timber and shrub species across the three zones. (a) Recruits (current year seedlings), (b) Unestablished Seedlings (dbh <5 cm and height <2 m), (c) Established Seedlings (dbh <5 cm and height >2 m), and (d) Saplings (dbh ≥5 to <10 cm).

4. Discussion

Species composition and species richness are important indicators for assessing the biodiversity (Husch et al. 2002) and may strongly depend and/or be influenced by the applied management practices. The listing of 140 plant species in the area shows the forest is rich in diversity (Tables 2 and 3) and can be considered to be among the highly diverse forests in the Himalayan region (Ohsawa 1987, 1991, 2002; Singh & Singh 1987). The record of 83 trees and 12 shrub species in the natural forest zone is comparable to other studies carried out in similar forest types of Bhutan, India, and Nepal. Wangda and Ohsawa (2006b) listed 78 tree species in west central part of Bhutan and Buffum et al. (2008) reported 39 tree species from the 260 ha forest in eastern part of Bhutan. Sundriyal and Sharma (1996) recorded 81 tree species in the temperate forest in Sikkim, while Hussain et al. (2008) counted 63 tree and 56 shrub species in Kumaon Himalaya, India. Carpenter (2005) reported 159 tree species in eastern part of Nepal and Shrestha et al. (2013) recorded 31 (19 tree and 12 shrub) and 37 (23 tree and 14 shrub) plant species in the two sites within the elevation range of 2650–2800 m.a.s.l in Nepal.

The lower number of species recorded in the semi-disturbed and settlement-agriculture zones (Figure 2(a)) as compared to in the natural forest agree with the findings of earlier studies. Bhuyan et al. (2003) reported only 16 species in highly disturbed site as compared to 47 species in the least disturbed site in the eastern part of India and Sunil et al. (2011) observed 34 tree species in the low disturbed sites against tree species of 14 in the highly disturbed sites in the southern part of India. In Bangladesh, Rahman et al. (2009) recorded 57 mature tree species in the low disturbed site, compared to 2 mature tree species in the highly disturbed sites. A tree species richness of 37 was the highest value found in natural forests, followed by the successional forest (31 species). The lowest was found in plantation forests, with only 9 species in Nepal (Webb & Sah 2003). All these studies attribute the differences in the results to the degree of disturbances caused by anthropogenic activities. Similarly, significant differences in diversity (Shannon and Simpsons) were seen between three zones, with the natural forest zone having highest diversity (Table 4; Figure 2(b,c)) indicating the negative impact of the anthropogenic activities on the tree species diversity in the two disturbed zones. This corresponds with earlier studies (Bhat et al. 2000; Hall et al. 2003; Sagar et al. 2003; Onaindia et al. 2004; Kariuki et al. 2006; Rahman et al. 2009; Wangda et al. 2009; Semwal et al. 2010; Sunil et al. 2011; Joshi & Yadava 2015).

Harvesting or tree cutting influences the species distribution, especially if only a limited number of trees are removed. The remaining trees may get a competitive advantage and thus effect the regeneration of the forest stand. Additionally, the diameter distribution will change due to harvesting operations and this may be seen as a measure for assessing the disturbance effects within forests (Hitimana et al. 2004). The analysis of diameter distribution and basal area suggests that selective felling has a negative impact on the diameter distribution of preferred timber species (Figures 4 and 5). The differences in basal area (m² ha⁻¹) between the three zones were highest for the highly valuable and most preferred species, such as Michelia spp., Phoebe spp., Persea spp., and Toona ciliata (Figure 5(a)). Our results also suggest that the lack of timber species or reduction in their density (N ha⁻¹) is due to selective felling and not caused by changing site conditions due to elevation (Figure 5(b)). Ohsawa (2002) reported that species richness in mixed forest stands is independent from elevation gradient, however, the dominance and structure may change with elevation (Sharma et al. 2009; Kumar & Sharma 2014).

Forests which are rich in biodiversity, when accessible and unrestricted for resource extraction, can lead to forests with lower species diversity (Vetaas 1993; Sundriyal & Sharma 1996; Murali & Setty 2001; Kumar & Ram 2005). The natural forest zone which is not under any form of sustainable management lies farther away from the settlements and is not easily accessible by roads. In this zone, the disturbances are limited to minor harvesting of non-timber forest products and limited cattle grazing. However, the two disturbed zones of settlement-agriculture and semi-disturbed are in close proximity to human settlements and are accessible by roads. The road density of 10.6 m/ha (Waiba 2015) in the watershed is fairly high and concentrates in the semi-disturbed and settlement-agriculture zones. Road networks increase resource extraction and encroachment into the forest leading to a reduction in biodiversity (Sundriyal & Sharma 1996; Watkins et al. 2003; Hitimana et al. 2004). Timber and other resources for the rural households are supplied on standing tree basis (Moktan et al. 2009a) from the forests of the semi-disturbed zone because of the area being easily accessible. However, there is no management plan or a resource inventory for ensuring sustainable cutting of the trees leading to reduction or removal of the timber species from the semi-disturbed and settlement-agriculture zones. Sundriyal and Sharma (1996) and Bhuyan et al. (2003) reported indiscriminate cutting of trees and selective felling for timber as the major cause of forest destruction in the eastern part of India while Sunil et al. (2011) described the lack of native tree species and bigger trees in the disturbed zones due to timber harvesting and fuel wood extraction in southern India. The density of shade intolerant species was higher due to removal of bigger commercial trees by selective logging in Australia (Kariuki et al. 2006). Rahman et al. (2009) and Hitimana et al. (2004) also observed standing large size stems and basal area only in the least disturbed sites in the forests of Bangladesh and Kenya, respectively.

Selection cutting is assumed to mimic natural forest development by leaving trees distributed in all age classes (Oliver & Larson 1996). However, our results indicate that the selective felling in combination with other anthropogenic disturbances leads to regeneration and establishment of non-timber and shrub species in the two disturbed zones. This may have significant impact on the forest structure in the coming years (Table 5; Figure 6). Peltzer et al. (2000) in Western Kenya, Kumar and Ram (2005) in Eastern India and Joshi and Yadava (2015) in the central part of India also observed higher shrub density in disturbed sites. The lack of timber species regenerating in the forests could also mean less availability of the timber for people in the future. Although the local forest department office have initiated plantations of commercial species in the barren areas of the semi-disturbed zones, there seems to have been neither follow up nor monitoring on the natural regeneration after removal of trees, which explains for the less regeneration of timber species in the two disturbed zones. Gaps created by selective felling, if not treated, can be colonized by competing plants other than timber species (Fredericksen & Mostacedo 2000; Kariuki et al. 2006; Moktan et al. 2009a) and aggravated further by grazing (Davidson 2000; Tashi 2004).

Forest management interventions will be required to deal with the existing disturbances and expected disturbances under climate change (Dale et al. 2000). Therefore, we recommend some interventions but not limited to for improving the conditions of the two disturbed zones. Urgently, the forest areas without a management plan must immediately be treated under the management regime of either a forest management plan or a community based forest management plan (FRDD 2005b). The ‘natural forests’ which may be seen as a reserve, should focus on biodiversity and nature conservation issues. The management plans must be accompanied by regular (every 10 years) forest inventories to control the past management and update and adjust future sustainable management activities to avoid further loss in biodiversity. For instance, the establishment of community forests has led to the improvement of forest conditions by reducing deforestation (Nagendra 2007; Nagendra et al. 2008; Chhetri et al. 2009; Porter-Bolland et al. 2012) with a positive outcome in biodiversity conservation (Persha et al. 2010).

The forest field officials need to be trained in silviculture practices, reforestation, and afforestation activities (FRDS 1996, 1997; Beck 2011). Reforestation and afforestation activities should be carried out in the two disturbed zones through plantation of local and native species. Research on the use of non-commercial tree species to reduce the pressure on commercial species (see Beck (2011) and enforcement of forest laws and regulations is needed. Additionally, strict monitoring on the amount of resource extraction and on the status of the regeneration/plantation should be carried out to improve the forest conditions (Nagendra 2007, 2009). This ensures that exploitation is avoided and the forest management activities are under control.

5. Conclusion

Forests with rich biodiversity provide various ecosystem services for sustaining rural livelihood and national development in Bhutan. The well-being of forest dependent communities rely on how well the forests are conserved and managed (Norbu 2002). However, the impacts of anthropogenic disturbances are now felt in these forests which are expected to increase further with the growing population and enhanced accessibility. The significantly lower biodiversity and stand characteristics in the disturbed zones confirm the increasing anthropogenic activities and its negative impact on diversity. Easy accesses to these forests have further contributed toward the decline in diversity.

Anthropogenic disturbances have also increased the composition of non-valuable species, which may not be useful for the local population. The single tree selection system seems to be failing in regenerating the timber species, probably due to lack of monitoring or silviculture stand improvement after felling of the trees. A single tree selection system, if carried out repeatedly without silvicultural stand improvement, might increase the proportion of non-timber species (Kariuki et al. 2006). It also leads to the removal of only bigger and more valuable timber species. This indicates that such forest areas, which are accessible and managed based on single tree selection system, warrant more attention from the concerned agencies to ensure their sustainability. Our findings may also be considered as a test case for providing insights into the change of the forest structure if no regular monitoring and management plan is in place.

Acknowledgments

This study was carried out under the project ‘Climate change adaptation potentials of forests in Bhutan – building human capacities and knowledge base (BC-CAP)’ with funding from the Austrian Government through the Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management, executed by the Department of Forests & Park Services, Ministry of Agriculture and Forests, Bhutan, and the University of Natural Resources and Life Sciences, Austria. We would like to thank: Georg Gratzer, Pema Wangda, Kinley Tenzin for the managerial support, Kezang Yangden for the technical inputs on GPS for data management, Karma Tenzin, Dorji Gyeltshen (Taxonomist), Karma Wangdra, Cheten Wangdra, Kinga Thinley, Janga B. Mongar, and Tendi Zangmo for helping with the field work, Rinchen Dorji for the GIS support, Younten Phuntsho for arranging relevant documents on forestry in Bhutan, Andras Darabant for providing helpful comments on an earlier version of the manuscript, and Adam Moreno for English editing. Finally we thank the editors and the three anonymous reviewers for their helpful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management [BMLFUW -UW.1.3.2/0124- V/4/2013].

Appendices

Appendix 1. Forest types and dominant species encountered in the watershed

Table

Forest type	Altitude (m.a.s.l)	Dominant tree species
Cool-temperate Broad-leaved forests	>2000	Acer campbellii* Symplocos ramosissima Beilschmiedia sp. Castanopsis tribuloides* Castanopsis hystrix* Lithocarpus elegans Casearia glomerata	Lindera pulcherrima Lyonia ovalifolia Persea clarkeana* Rhododendron grande Symplocos lucia Terpena sp.
Warm-temperate Broad-leaved forests	1000–2000	Schima wallichii** Alnus nepalensis** Beilschimiedia sp. Alseodaphne sp. Casearia glomerata Cinnamomum bejolghota* Dalbergia sericea Engelhardia spicata Terminalia myriocarpa** Eurya acuminata Castanopsis tribuloides* Castanopsis indica*	Ficus auriculata Macaranga indica Macaranga pustulata Michelia cathcartii** Michelia doltsopa** Michelia velutina** Ostodes paniculata Quercus glauca Toona ciliata** Phoebe spp.** Persea fructifera**
Sub-tropical forests	<1000	Schima wallichii** Rhus succedanea Ostodes paniculata Grewia sp.	Albizia gambelii Ficus semicordata Bombax ceiba** Alangium chinense

* Timber from other records.

** Timber species as per local preference.

Appendix 2. Equations used for calculating volume

Table

^(Reference)Name of the species		Volume equations	n	R^2	Eq.no.
^(1)Acer spp.	G	V = 0.03873 + 0.36273	250	-	E.1
^(1)Ailanthus integrifolia	G	ln(V) = −1.94825 + 1.7273*ln(D) + 1.1669*ln(H)	103	-	E.2
^(2)Albezia chinensis	G	V = −1.5567 + 0.0006182 + 0.0000054684 + 0.090192 H	36	0.865	E.3
^(2)Albizia spp.	G	V = 0.009134 + 0.171315	255	0.75	E.4
^(1)Alnus nepalensis	G	ln(V) = −0.565323 + 1.984601*ln(D) + 0.822937*ln(H)	150		E.5
^(2)Amoora wallichii	G	V = 0.0778 + 0.0000286 (Dia in cm)	-	-	E.6
^(1)Aphanamixis polystachya	G	V = −0.09768 + 0.01051 H	48	-	E.7
^(1)Beilschmiedia spp.	G	ln(V) = −0.565323 + 1.984601*ln(D) + 0.822937*ln(H)	150	-	E.8
^(1)Betula alnoides	G	ln(V) = −0.46151 + 2.039844*ln(D) + 0.837461*ln(H)	77	-	E.9
^(2)Bischofia javanica	L	V = 0.25571–2.33118D + 11.12071	19	0.999	E.10
^(1)Bombax ceiba	G	ln(V) = −0.70448 + 2.13777*ln(D) + 0.91127*ln(H)	81	-	E.11
^(2)Callicarpa arborea	L	−0.04506 + 2.33446D	61	0.926	E.12
^(2)Casearia spp.	L	V = 0.14031–2.06478D + 11.25750	23	0.997	E.13
^(1)Castanopsis spp.	G	V = −0.00794 + 0.34759	82	-	E.14
^(3)Cinnamomum spp.	L	V = 0.00003*D^2,813 (Dia in cm)			E.15
^(2)Dalbergia sericea	L	0.76896 + 7.31777*D −4.01953*D	16	0.915	E.16
^(2)Elaeocarpus spp.	L	0.43843 + 5.72522D −2.59907D	15	0.991	E.17
^(1)Engelhardtia spicata	G	ln(V) = −0.14969 + 2.1532*ln(D) + 0.76463*ln(H)	40	-	E.18
^(2)Exbucklandia populnea	G	V = 0.0258 + 0.000172 + 0.0000332H			E.19
^(2)Grewia spp.	L	V = −0.44075 + 7.49221D-36.09962 + 71.91238	78	0.977	E.20
^(3)Litsea spp.	L	V = 0.0001D^2.438 (Dia in cm)	-	-	E.21
^(2)Mallotus philippinensis	L	V = 0.14749–2.87503*D + 19.61977-19.116303*	-	-	E.22
^(1)Michelia spp.	G	V = 0,00667 + 0,32947H	94	-	E.23
^(3)Morus laevigata	L	V = 0.00009D^2,5249 (Dia in cm)	-	-	E.24
^(3)Myrsine semiserrata	L	V = 0,00009 D^2,5249 (Dia in cm)	-	-	E.25
^(1)Persea spp.	G	ln(V) = −0.56664 + 2.03335ln(D) + 0,87279*ln(H)	122	-	E.26
^(1)Phoebe spp.	G	V = −0.0432 + 0.3622H	34	-	E.28
^(1)Pinus roxburghii	G	V = −0.00156 + 0.32159H	154	-	E.29
^(1)Quercus spp.	G	V = −0,002111 + 0.392382H	148	-	E.30
^(3)Rhododendron spp.	L	V = 0,00009*D^2,4641	-	-	E.31
^(1)Schima wallichii	G	ln(V) = −0.565323 + 1.984601*Ln(D) + 0.822937*Ln(H)	150	-	E.32
^(1)Sterculia spp.	G	V = 0.00231 + 0.34018H	75	-	E.33
^(1)Symplocos spp.	G	V = 0.00155 + 0.34028H	69	-	E.34
^(2)Syzigium cumini	L	V = −0.00094 + 6.15921	30	0.982	E.35
^(2)Syzigium spp.	L	V = −0.13284 + 1.88944D −4.96385 + 21.41051	78	0.935	E.36
^(1)Terminalia myriocarpa	G	V = 0.00635 + 0,35936H	59	-	E.37
^(2)Toona ciliata	L	V = 0.21869 – 2.04074D + 10.41713 + 1.85232	74	0.996	E.38
^(3)Rest of the Species(South)	L	V = 0.00009D^2,5249 (Dia in cm)			E.39

- = Not available; n = total number of sample trees used for deriving regression equation; R² = co-efficient of determination. (G) = General equation; (L) = Local Equation. References: 1 = (Laumans 1994), 2 = (FSI 1996), 3 = (FRDD 2005c).