# Species Diversity and Tree Regeneration Patterns in Tropical Forests of the Western Ghats, India

Authors: R. Jayakumar; K. K. N. Nair
Journal: ISRN Ecology
 (2013)

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## Abstract

Study Aim. To assess species diversity and tree regeneration patterns of different vegetation types of Western Ghats, India. Rarefaction was used to estimate species diversity of different vegetation types. One-way ANOVA was used to test for differences in tree density and basal area of different vegetation types. Sorenson index of similarity was used to calculate change in species composition between mature trees and regenerating individuals. Results showed that species diversity and regeneration pattern of trees differ in different vegetation types of the forest landscape. Species-area and species-individual accumulation curve (rarefaction) against equal-sized sampling area in different vegetation types showed that species heterogeneity was higher in vegetation types at mid elevations while their abundance was higher in vegetation types at higher elevations. All the vegetation types of the study area were heterogeneously distributed. Tree regeneration was higher in species rich vegetation type with no sign of human disturbances. Change in species composition across mature and regenerating phase was more frequent in disturbed forest as compared to undisturbed or less disturbed forests. New entry species occur in all the vegetation types.


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## Body

## 1. Introduction

Tropical regions of the world are frequently decked with luxuriant vegetation rich in species. The diversity of tree species is a fundamental component of total biodiversity in many ecosystems because trees are ecosystem engineers that provide resources and habitats for almost all other forest organisms [1]. In tropical forests, the diversity of tree species varies by geography, habitat parameters, and levels of disturbance [2]. Trees form the major structural and functional basis of tropical forest ecosystems and can serve as robust indicators of changes and stressors at the landscape scale [3]. The spatial heterogeneity of diversity may be the result of some underlying pattern or process such as environmental heterogeneity, biotic control, and abiotic/biotic coupling process [4]. Spatial patterns of species richness have been used extensively to identify biodiversity “hotspots” [5]. The assumption is that managing areas of high species richness equate to improved conservation outcomes. Therefore richness usually was a positive predictor of places of conservation value, if these are defined as places where species of interest are especially abundant. Understanding species diversity and distribution patterns is important for helping managers to evaluate the complexity and resources of these forests.Quantitative plant diversity inventories of Indian tropical forests are available from various forests of Western Ghats [28–36]. Comparison of the species diversity of different vegetation types is often difficult because of the dissimilarity of the available data. Primary forests of Asia, especially those of the Western and Eastern Ghats of India, are fast disappearing due to diverse anthropogenic impacts. The primary stands are often replaced by forests of secondary species; alternatively, forest landscapes are converted to completely different uses [37]. Earlier studies of tropical tree regeneration have focused mainly on seedlings, which are usually more abundant than other life stages [38–40]. Parameters of seedling stands are crucial components of tree population dynamics [41]. As floristic and structural composition changes from one community to another there are concomitant changes in the competitive abilities of seedlings that depend on shifting opportunities for regeneration [42]. Recruitment, growth, and survival are influenced by a range of microclimatic and edaphic factors, which vary among different tropical forest formations [43]. Phillips [44] analyzed tree turnover in 67 mature forest sites representing most of the major tropical forest regions of the world; across the sites, tree turnover had significantly increased since the 1950s. Increased tree turnover has positive impacts on atmospheric quality and biodiversity [1].The Indian subcontinent has one of the world’s richest floras, with more than 17,000 species of flowering plants alone [45]. The Western Ghats, one of the biodiversity “hotspots,” in which our study was performed, form a mountainous region in peninsular India that extends 1400 km2 from the mouth of the Tapti River in the north to the environs of Kanyakumari in the south [46]. With this background, we evaluated the diversity and regeneration patterns of tree species in a section of the Nilgiri Biosphere Reserve, aiming to provide fundamental data for appropriate management strategies (mainly to propose the study area as Protected Area) that will improve the ecosystem. Specifically, we (i) aim to examine and compare tree species diversity (richness, abundance, and basal area) in six different vegetation types representative of the study area (ii) to assess tree distribution pattern (using Raunkiaer’s frequency class) and also tree girth distribution of different vegetation of the study area and (iii) to determine natural regeneration patterns and changes in species compositions across mature and regenerating phases of trees and also assess occurrence of new entry species in different representative forest types of the landscape.


## 2. Methods

### 2.1. Study Area

The study was conducted in the New Amarambalam Reserve Forests (Figure1), which is situated in the Western Ghats of India (11°14′–11°24′ N, 76°11′–76°33′ E). These stands are part of the Nilgiri Biosphere Reserve within the State of Kerala. The reserve covers an area of about 265 km2. Following the forest type terminology of UNESCO [47], the natural vegetation types of the area were tropical broad-leaved drought deciduous forests (DECI), tropical lowland broad-leaved semideciduous seasonal forests (SEMI), tropical lowland broad-leaved seasonal evergreen forests (EVER), tropical broad-leaved evergreen/submontane forests (SUBM), tropical broad-leaved seasonal evergreen/montane forests (MONT), and tropical broad-leaved drought deciduous woodlands (WOOD). DECI occurred in foothills of Ghats with reduced rainfall, whereas the other forest formations occurred at higher elevations that received rain through most of the year. DECI occurred in an altitudinal range of 40–400 m above mean sea level. Other vegetation types occurred at elevations of 400–2554 m (Table 1). In addition to six vegetation types, another forest formation occurs  on the top of the Ghats (altitudinal range of 1800–2554 m) called short grass savannah that has practically no tree species, excluded from the present study. Temperature in the study area ranged from 17 to 37°C; diurnal variation seldom exceeded 16°C. The area received an average rainfall of about 2600 mm, reaching a maximum of 6000 mm. Most precipitation fell in the South-West monsoon season, which extends from June through the end of September. High altitudes in the Ghats had rainfall through most of the year. The monsoon precipitation was highest on western, southwestern, and northwestern slopes. The climate was hot from March to May and humid during the rainy season.Table 1
Dominant trees (first three) and their densities (trees ha−1) in three different growth phases of six vegetation types. International (UNESCO) and regional (Champion and Seth, 1968*) terminology of vegetation types used. See “regeneration” in Section 2 for procedure used to distinguish dominant species.
Vegetation types
Dominant species
Density of tree phases
UNESCO
Champion and Seth (1968)
Mature
Saplings
Seedlings
Tropical broad-leaved drought deciduous forests(DECI)
Southern tropical moist deciduous forests
Xylia xylocarpa
25.9
23
3166
Terminalia paniculata
22.8
5.2
333
Lagerstroemia microcarpa
15.6
1.2
—
Wrightia tinctoria
10.8
8.6
166
Holarrhena pubescens
—
2.5
4833
Bridelia airy-shawii
0.3
0.2
4666
Radermachera xylocarpa
1.3
1
3500
Tropical lowland broad-leaved semideciduous seasonal forests(SEMI)
West coast tropical semievergreen forests
Pterygota alata
49
81.5
245
Reinwardtiodendron anamalaiense
30
85
3845
Strombosia zeylanica
16
8.5
456
Palaquium ellipticum
14
9.6
240
Xylia xylocarpa
19
12
96
Calophyllum polyanthum
3.6
5.5
453
Tropical lowland broad-leaved  seasonal evergreen forests(EVER)
West coast tropical evergreen forests
Palaquium ellipticum
93
38
4136
Agrostistachys borneensis
71
69
223
Myristica beddomei
39
27
573
Reinwardtiodendron anamalaiense
28
56
1636
Calophyllum polyanthum
4
1.5
1042
Tropical broad-leaved drought deciduous woodlands(WOOD)
Subtropical hill savannahs
Wendlandia thyrsiflora
17
36
356
Phyllanthus emblica
3.2
—
—
Glochidion ellipticum
2.3
2.4
—
Gnidia glauca
2.38
18
160
Macaranga peltata
1.59
4
—
Erythrina stricta
0.8
1.6
80
Tropical broad-leaved evergreen/submontane forests (SUBM)
Southern subtropical broad-leaved hill forests
Myristica beddomei
88
0.5
765
Palaquium ellipticum
55
15
298
Litsea stocksii
32
35
456
Litsea floribunda
4
5
371
Tropical broad-leaved evergreen/montane forests(MONT)
Southern montane wet temperate forests
Turpinia cochinchinensis
116
46
1855
Rhododendron arboreum
102
34
206
Symplocos obtusa
64
33
386
Rhodomyrtus tomentosa
26
44
234
Syzygium calophyllifolium
77
20
868
Litsea floribunda
30
7
870
*Champion, H. G. and Seth, S. K. 1968. A revised survey of the forest types of India. Oxford, UK and  IBH  Publications, New Delhi, India.Figure 1
Location and area maps of New Amarambalam Reserve Forests and adjoining forests.


### 2.2. Disturbances and Threats to the Study Area

Forests near human habitations (DECI) are highly degraded by firewood collection and cattle grazing; this has led to impoverished plant diversity in the area. Seasonal fire in WOOD damages many ecosystem components, including trees and their seedlings. Remaining four vegetation types are more or less undisturbed. Poaching and fishing are also common in the area. Fish are killed with copper sulphate and explosives (locally known as Thotta), with indiscriminate killing of many species of aquatic fauna and flora. In the face of such dangers, the rich, diverse, and dynamic forest formations of the region, which contain rare, endangered, and threatened (RET) tree species [48], require species-, location-, and issue-specific management strategies in addition to the overall protection provided by the Nilgiri Biosphere Reserve.


### 2.3. Vegetation Sampling and Species Diversity Analysis

In the period 2000–2003, we used a stratified random design to sample vegetation [47]. The trees in the vegetation types were classified into three growth phases: mature trees (≥30 cm girth at breast height [gbh]), saplings (≥10<30 cm gbh), and seedlings (<10 cm gbh and >20 cm high). Initially, all standing trees >10 cm gbh were counted in 30m×30m plots (i.e. 900 m2 or 0.09 hectare [ha]) laid randomly in each vegetation type. Within each plot, ten random subplots of 2 m × 2 m were also deployed; in these, we collected data on tree seedlings. A total of 23 ha contained 259 sampling plots. The number of plots deployed in each vegetation type was 45 (4 ha) except for WOOD where total area (34 plots) was sampled. Altitudes of plots were measured with a pocket altimeter accurate to 20 m. Tree gbh values were measured at 1.3 m above ground level.To assess species-area and species-individuals (abundance) relationship and also estimate average species accumulation rate of different vegetation types, species-area curves and species-individual rarefaction curves (individual-based rarefaction) were created, randomly selected 30 plots of 30 m× 30 m size. Rarefaction was used to investigate the richness of the community expected in a random sample of individuals taken from a census or collection. The heterogeneity index, namely, Shannon index was measured using the formula: H′=∑[(ni/N)loge(ni/N)], where H′ is Shannon diversity index, ni is  number of individuals of species “i” in a community sample, and N is total number of individuals of all species in the community sample [49]. Vegetation data including density (number of individuals ha-1), richness (number of species), and basal area (m2ha-1) were assembled. To assess species distribution, Raunkiaer [50] divided percent frequency into five classes: A (0–20%), B (21–40%), C (41–60%), D (61–80%), and E (81–100%) to assess distribution of species. Frequency diagrams represent the homogeneity or heterogeneity of a community as floristic uniformity varies with the value for classes A and E. When classes A, B, and C are relatively frequent, the stand is heterogeneous and the greater the frequency of class E, the greater the homogeneity. To assess girth pattern, ghb of trees (>10 cm gbh) of all the vegetation types was measured and categorized into different girth class interval of 50 cm.


### 2.4. Regeneration

The regeneration status of a tree species in a given forest type was considered “good” when seedling density> sapling density > adult tree density, “fair” when seedling density > sapling density ≤ adult density, “poor”, when the species survived in only the sapling stage but not in the seedling stage, “none”, for species with no sapling or seedling stages but present as adult trees, and “new” when adults of a species were absent but sapling and/or seedling stage(s) were present [31]. When a species frequency distribution fits a “reverse J” pattern (high number of individuals in the seedling stage and gradually declining numbers through the sapling, small tree, and mature tree phases), that species was recognized as the dominant in the whole stand. In order to measure number of species shared between mature and regenerating phases, Sorenson index of similarity [49] was used: S=2c/(a+b), where S is Sorenson index of similarity, c is number of species shared between growth phases (here mature tree phase and regenerating phase, i.e. saplings + seedlings), a is total number of species in growth phase a, and b is total number of species in growth phase b. Species is considered as new recruit when there was no tree species with mature (adult) stage.


### 2.5. Statistical Analysis

One-wayANOVA was used to test differences of density (≥30 cm gbh), overall species richness, and basal area among vegetation types. LSD post hoc tests were used to detect significant pair wise differences among means of dependent variables. One-way analysis of covariance (ANCOVA) was conducted to test of the covariate (abundance) is that it evaluates the relationship between the covariate (abundance) and the dependant variable (species richness), controlling for the factor (vegetation types). Pearson correlation coefficients were calculated to detect significant correlations among vegetation parameters especially cumulative species richness and abundance of each vegetation type. We used the statistical package SPSS (Version 16: www-01.ibm.com/software/analytics/spss/) for all tests. For rarefaction we used statistical software Biodiversity Pro (http://www.smi.ac.uk/peter-lamont/biodiversity-pro).


## 2.1. Study Area

The study was conducted in the New Amarambalam Reserve Forests (Figure1), which is situated in the Western Ghats of India (11°14′–11°24′ N, 76°11′–76°33′ E). These stands are part of the Nilgiri Biosphere Reserve within the State of Kerala. The reserve covers an area of about 265 km2. Following the forest type terminology of UNESCO [47], the natural vegetation types of the area were tropical broad-leaved drought deciduous forests (DECI), tropical lowland broad-leaved semideciduous seasonal forests (SEMI), tropical lowland broad-leaved seasonal evergreen forests (EVER), tropical broad-leaved evergreen/submontane forests (SUBM), tropical broad-leaved seasonal evergreen/montane forests (MONT), and tropical broad-leaved drought deciduous woodlands (WOOD). DECI occurred in foothills of Ghats with reduced rainfall, whereas the other forest formations occurred at higher elevations that received rain through most of the year. DECI occurred in an altitudinal range of 40–400 m above mean sea level. Other vegetation types occurred at elevations of 400–2554 m (Table 1). In addition to six vegetation types, another forest formation occurs  on the top of the Ghats (altitudinal range of 1800–2554 m) called short grass savannah that has practically no tree species, excluded from the present study. Temperature in the study area ranged from 17 to 37°C; diurnal variation seldom exceeded 16°C. The area received an average rainfall of about 2600 mm, reaching a maximum of 6000 mm. Most precipitation fell in the South-West monsoon season, which extends from June through the end of September. High altitudes in the Ghats had rainfall through most of the year. The monsoon precipitation was highest on western, southwestern, and northwestern slopes. The climate was hot from March to May and humid during the rainy season.Table 1
Dominant trees (first three) and their densities (trees ha−1) in three different growth phases of six vegetation types. International (UNESCO) and regional (Champion and Seth, 1968*) terminology of vegetation types used. See “regeneration” in Section 2 for procedure used to distinguish dominant species.
Vegetation types
Dominant species
Density of tree phases
UNESCO
Champion and Seth (1968)
Mature
Saplings
Seedlings
Tropical broad-leaved drought deciduous forests(DECI)
Southern tropical moist deciduous forests
Xylia xylocarpa
25.9
23
3166
Terminalia paniculata
22.8
5.2
333
Lagerstroemia microcarpa
15.6
1.2
—
Wrightia tinctoria
10.8
8.6
166
Holarrhena pubescens
—
2.5
4833
Bridelia airy-shawii
0.3
0.2
4666
Radermachera xylocarpa
1.3
1
3500
Tropical lowland broad-leaved semideciduous seasonal forests(SEMI)
West coast tropical semievergreen forests
Pterygota alata
49
81.5
245
Reinwardtiodendron anamalaiense
30
85
3845
Strombosia zeylanica
16
8.5
456
Palaquium ellipticum
14
9.6
240
Xylia xylocarpa
19
12
96
Calophyllum polyanthum
3.6
5.5
453
Tropical lowland broad-leaved  seasonal evergreen forests(EVER)
West coast tropical evergreen forests
Palaquium ellipticum
93
38
4136
Agrostistachys borneensis
71
69
223
Myristica beddomei
39
27
573
Reinwardtiodendron anamalaiense
28
56
1636
Calophyllum polyanthum
4
1.5
1042
Tropical broad-leaved drought deciduous woodlands(WOOD)
Subtropical hill savannahs
Wendlandia thyrsiflora
17
36
356
Phyllanthus emblica
3.2
—
—
Glochidion ellipticum
2.3
2.4
—
Gnidia glauca
2.38
18
160
Macaranga peltata
1.59
4
—
Erythrina stricta
0.8
1.6
80
Tropical broad-leaved evergreen/submontane forests (SUBM)
Southern subtropical broad-leaved hill forests
Myristica beddomei
88
0.5
765
Palaquium ellipticum
55
15
298
Litsea stocksii
32
35
456
Litsea floribunda
4
5
371
Tropical broad-leaved evergreen/montane forests(MONT)
Southern montane wet temperate forests
Turpinia cochinchinensis
116
46
1855
Rhododendron arboreum
102
34
206
Symplocos obtusa
64
33
386
Rhodomyrtus tomentosa
26
44
234
Syzygium calophyllifolium
77
20
868
Litsea floribunda
30
7
870
*Champion, H. G. and Seth, S. K. 1968. A revised survey of the forest types of India. Oxford, UK and  IBH  Publications, New Delhi, India.Figure 1
Location and area maps of New Amarambalam Reserve Forests and adjoining forests.


## 2.2. Disturbances and Threats to the Study Area

Forests near human habitations (DECI) are highly degraded by firewood collection and cattle grazing; this has led to impoverished plant diversity in the area. Seasonal fire in WOOD damages many ecosystem components, including trees and their seedlings. Remaining four vegetation types are more or less undisturbed. Poaching and fishing are also common in the area. Fish are killed with copper sulphate and explosives (locally known as Thotta), with indiscriminate killing of many species of aquatic fauna and flora. In the face of such dangers, the rich, diverse, and dynamic forest formations of the region, which contain rare, endangered, and threatened (RET) tree species [48], require species-, location-, and issue-specific management strategies in addition to the overall protection provided by the Nilgiri Biosphere Reserve.


## 2.3. Vegetation Sampling and Species Diversity Analysis

In the period 2000–2003, we used a stratified random design to sample vegetation [47]. The trees in the vegetation types were classified into three growth phases: mature trees (≥30 cm girth at breast height [gbh]), saplings (≥10<30 cm gbh), and seedlings (<10 cm gbh and >20 cm high). Initially, all standing trees >10 cm gbh were counted in 30m×30m plots (i.e. 900 m2 or 0.09 hectare [ha]) laid randomly in each vegetation type. Within each plot, ten random subplots of 2 m × 2 m were also deployed; in these, we collected data on tree seedlings. A total of 23 ha contained 259 sampling plots. The number of plots deployed in each vegetation type was 45 (4 ha) except for WOOD where total area (34 plots) was sampled. Altitudes of plots were measured with a pocket altimeter accurate to 20 m. Tree gbh values were measured at 1.3 m above ground level.To assess species-area and species-individuals (abundance) relationship and also estimate average species accumulation rate of different vegetation types, species-area curves and species-individual rarefaction curves (individual-based rarefaction) were created, randomly selected 30 plots of 30 m× 30 m size. Rarefaction was used to investigate the richness of the community expected in a random sample of individuals taken from a census or collection. The heterogeneity index, namely, Shannon index was measured using the formula: H′=∑[(ni/N)loge(ni/N)], where H′ is Shannon diversity index, ni is  number of individuals of species “i” in a community sample, and N is total number of individuals of all species in the community sample [49]. Vegetation data including density (number of individuals ha-1), richness (number of species), and basal area (m2ha-1) were assembled. To assess species distribution, Raunkiaer [50] divided percent frequency into five classes: A (0–20%), B (21–40%), C (41–60%), D (61–80%), and E (81–100%) to assess distribution of species. Frequency diagrams represent the homogeneity or heterogeneity of a community as floristic uniformity varies with the value for classes A and E. When classes A, B, and C are relatively frequent, the stand is heterogeneous and the greater the frequency of class E, the greater the homogeneity. To assess girth pattern, ghb of trees (>10 cm gbh) of all the vegetation types was measured and categorized into different girth class interval of 50 cm.


## 2.4. Regeneration

The regeneration status of a tree species in a given forest type was considered “good” when seedling density> sapling density > adult tree density, “fair” when seedling density > sapling density ≤ adult density, “poor”, when the species survived in only the sapling stage but not in the seedling stage, “none”, for species with no sapling or seedling stages but present as adult trees, and “new” when adults of a species were absent but sapling and/or seedling stage(s) were present [31]. When a species frequency distribution fits a “reverse J” pattern (high number of individuals in the seedling stage and gradually declining numbers through the sapling, small tree, and mature tree phases), that species was recognized as the dominant in the whole stand. In order to measure number of species shared between mature and regenerating phases, Sorenson index of similarity [49] was used: S=2c/(a+b), where S is Sorenson index of similarity, c is number of species shared between growth phases (here mature tree phase and regenerating phase, i.e. saplings + seedlings), a is total number of species in growth phase a, and b is total number of species in growth phase b. Species is considered as new recruit when there was no tree species with mature (adult) stage.


## 2.5. Statistical Analysis

One-wayANOVA was used to test differences of density (≥30 cm gbh), overall species richness, and basal area among vegetation types. LSD post hoc tests were used to detect significant pair wise differences among means of dependent variables. One-way analysis of covariance (ANCOVA) was conducted to test of the covariate (abundance) is that it evaluates the relationship between the covariate (abundance) and the dependant variable (species richness), controlling for the factor (vegetation types). Pearson correlation coefficients were calculated to detect significant correlations among vegetation parameters especially cumulative species richness and abundance of each vegetation type. We used the statistical package SPSS (Version 16: www-01.ibm.com/software/analytics/spss/) for all tests. For rarefaction we used statistical software Biodiversity Pro (http://www.smi.ac.uk/peter-lamont/biodiversity-pro).


## 3. Results

### 3.1. Species Diversity

In the six vegetation types sampled in the study area, there were 257 tree species belonging to 62 families and 147 genera of angiosperms. Richness of tree species (Figure2) was highest in SEMI (127 spp.) and lowest in the WOOD (28 spp.). Species-area and species-individuals accumulation curve (rarefaction curve) against equal-sized sampling areas in different vegetation types showed a distinct difference in the richness and abundance. Rarefaction can be used to examine the evenness of the distribution of species in assemblages by comparing steepness of curves. Steeper rarefaction curves indicate high heterogeneity. One striking results of rarefaction curves was that SEMI and EVER have the highest curves. This means that species diversity per equal-sized area was highest in these vegetation types but MONT has the most individuals per unit area. Vegetation type at other extreme (low species richness) was WOOD and MONT (Figure 3). The overall difference in species richness among six vegetation types was statistically significant (F5,179=65.1; P<0.0001). Species richness and corresponding abundance were significantly positively correlated in all the vegetation types (DECI: r=0.98, P<0.0001); SEMI: r=0.95, P<0.0001, EVER: r=0.94, P<0.0001; WOOD: r=0.77, P<0.0001; SUBM: r=0.95, P<0.0001; MONT: r=0.87, P<0.0001). A primary analysis evaluating the homogeneity-of-regression (slopes) assumption indicated that the relationship between the covariate (abundance) and the dependant variable (species richness) differs significantly as a function of the independent variable (vegetation types) (R2=0.152; ANCOVA: F6,179=133.4, P<0.001). A significant interaction between the covariate and the factor suggests that the differences on the dependent variable among groups vary as a function of the covariate. Since the result from the ANCOVA was significant, it is not meaningful to proceed further. The highest Shannon index value occurred in SEMI (3.67 for plants with gbh ≥30 cm) and lowest value reported in WOOD (Table 2).Table 2
Vegetation parameters calculated for three tree phases in different vegetation types. See Table1 for explanation of vegetation type abbreviations.
Vegetation types(Altitude range)
Rainfall(mm)
Mean temperature in the coldest month (°C)
Phases of trees
Basal area(m2/ha)
Shannon index
DECI (40–400 m)
1000–1500
28
Mature treesSaplingsSeedlings
23.320.20—
2.792.482.62
SEMI (400–650 m)
2500–3500
24
Mature treesSaplingsSeedlings
45.660.89—
3.673.153.11
EVER (650–1200 m)
3500–5000
22
Mature treesSaplingsSeedlings
48.001.24—
3.343.093.49
WOOD (900–1400 m)
3500–5000
25
Mature treesSaplingsSeedlings
0.690.4—
2.212.161.56
SUBM (1200–1800 m)
5000–6000
13
Mature treesSaplingsSeedlings
36.510.69—
3.263.453.51
MONT (1800–2450 m)
5000–6000
9
Mature treesSaplingsSeedlings
30.871.45—
3.213.192.71
*Mature trees (≥30 cm gbh), saplings (≥ 10 < 30 cm gbh), and seedlings (<10 cm gbh).Figure 2
Species richness (number of species) by tree growth phase in six vegetation types occurring in the Western Ghats. Multiple comparison LSD post hoc test showed richness of all the vegetation types was significantly different (P<0.01–0.05). See Table 1 for an explanation of vegetation type abbreviations.Species accumulation and rarefaction curves of different vegetation types. Curves were created random series of 30 plots of 0.09 ha (i.e., 2.7 ha for each vegetation type). (a) Species-area curves (sample-based rarefaction) and (b) species-individuals curve (individuals-based rarefaction). Looking at the individual-based rarefaction curve, all four vegetation types seem to be quite similar in species richness, except MONT, which is drastically lower although containing the highest number of individuals, WOOD, which contain too few individuals to produce a comparable result. The sample-based rarefaction, on the other hand, identifies SEMI and EVER as the two most species rich communities, differing from the rest. Rarefaction curves for six vegetation types predict the rate of accumulation of species with increasing number of individuals (abundance). See Table1 for an explanation of vegetation type abbreviations.
(a)
(b)Dominant tree species in mature and sapling stages were more or less similar in most vegetation types, but dominant species in the seedling stage varied considerably (Table1). Overall stand density of mature trees (≥30 cm gbh) was highest in MONT (855 trees ha-1) and lowest in WOOD (39 trees ha-1). Densities of both tree saplings and seedlings were highest in EVER (Figure 4). Among 25 tree species dominant across the different forest types, 16 dominated in the tree phase, 15 in the sapling phase, and 14 in the seedling phase. Among the different forest types, there were significant difference in tree (≥30 cm gbh) density (P<0.0001, F5,389=26.9) and basal area (P<0.007, F5,389=3.3). Mean basal area of trees was highest in EVER (48m2ha-1) and lowest in WOOD (Table 2).Figure 4
Densities (noha-1 in log10 scale) of mature trees (≥30 cm gbh (girth at breast height)), saplings (≥10<30 cm gbh), and seedlings (<10 cm gbh) in six vegetation types occurring in the Western Ghats. LSD post hoc test clarified that density of disturbed forest like DECI and WOOD was significantly different with undisturbed vegetation type except MONT.Raunkiaer’s frequency analyses revealed that most of the tree species were rare, as in the case for other tropical forests. In all forest types, 60%–95% of tree species were in the lowest frequency class (Figure5). Furthermore, there were few individuals in the 80%–100% frequency class. In forest types other than DECI, 58%–70% of trees were in the smallest girth category (gbh 50–100 cm); in DECI, only 37% of trees were in the smallest girth class (Figure 6). In WOOD vegetation, which was fire affected and grass dominated, 96% of trees were in the smallest girth class.Percent frequencies of trees (≥30 cm gbh) in different vegetation types. Most of the species were in the lowest frequency class in all vegetation types other than MONT, indicating that a few species were widely distributed; most were restricted in distribution. This is a typical species-abundance distribution (normal distribution) and the tree species in all the vegetation type were heterogeneous distribution in Raunkiaer’s sense.
(a)
(b)
(c)
(d)
(e)
(f)Girth frequency distributions of trees in different vegetation types of the study area. Girth-size was highest in SEMI and EVER. A high percentage of lower girth class trees in DECI results from reduced fuel wood extraction by people of nearby areas. The reverse J-shaped gbh distribution of trees indicates evolving or expanding population.
(a)
(b)
(c)
(d)
(e)
(f)


### 3.2. Regeneration

Frequencies of regenerating species (saplings + seedlings) were maximal in undisturbed forest compared to disturbed one (caused by fuel wood collection and cattle grazing). In DECI, of 71 taxa recorded, only 26 were present in all three growth phases, 24 were present in only one stage, and only 10 species were regenerating well (seedling> sapling > tree). Nevertheless, Lagerstroemia microcarpa, one of the dominant species in DECI, had no seedlings, indicative of poor regeneration potential (Tables 1 and 3; see Supplementary Material Appendix 1 available online at http://dx.doi.org/10.1155/2013/890862). In vegetation types influenced by disturbance and fire, like WOOD, 29% of species were common in all growth phases and seedling richness was very low in these types of vegetation (Supplementary Material Appendix 2).Table 3
Distribution pattern of mature and regenerating phases of trees occur in different vegetation types. Regenerating species and species share in all phases of trees was lower in disturbed vegetation type such as DECI and WOOD as compared to other vegetation types. Percent similarity in species composition (using Sorenson index of similarity) of mature trees and regenerating individuals (saplings + seedlings) in different vegetation types of the study area and new species recruited (trees devoid of adult stage) are also shown.
Vegetation types
Tree species occur in
*Regenerating species (%)
% Similarity between mature trees and regenerating individuals
New entry species (%)
All phases (%)
Mature phase only (%)
Regenerating phase only (%)
DECI
26 (37)
21 (30)
12 (17)
50 (70)
69
12 (17)
SEMI
53 (41)
11 (9)
27 (21)
116 (91)
82
24 (18)
EVER
49 (40)
11 (9)
24 (20)
111 (91)
81
23 (18)
WOOD
8 (29)
8 (29)
11 (39)
20 (71)
49
10 (35)
SUBM
40 (43)
4 (4)
18 (20)
87 (95)
88
20 (21)
MONT
20 (47)
6 (14)
11 (26)
37 (86)
76
10 (23)
*A number of species occur in saplings and/or seedlings, and these species may or may not have mature tree stage; % of species has been given in brackets.In vegetation types at mid elevations, namely, EVER and SEMI, 49%–53% of species were present in all growth phases; 25–30% of species occurred in only one phase (Supplementary Material Appendices 3 and 4). In forests at higher elevations, namely,SUBM and MONT, 43% and 47% of species, respectively, were present in all growth phases. In SUBM, 25 species had poor regeneration potential (Supplementary Material Appendix 5). In MONT, 20 species were present in all growth phases, and 12 had no regeneration potential (Table3, Supplementary Material Appendix 6).


### 3.3. Change in Species Composition among Tree Phases

Overall species richness of mature trees was higher than richness of saplings and seedlings in all vegetation types. Among the dominant species, a few trees had exceptionally large numbers of seedling and saplings. Individual trees did not contribute equally to the seedling population or to later recruitment in the sapling stage. Density of regenerating individuals (saplings + seedlings) was highest in EVER and lowest in WOOD. There was significant difference in the density of regenerating individuals (seedling + saplings) among different vegetation types (F5,611=13.2, P<0.001). Also, there was significant difference in the density of mature and regenerating phase among all vegetation types except WOOD (DECI: F1,130=11.7, P<0.001; SEMI: F1,269=3.7, P<0.05; EVER: F1,255=7.3, P<0.008; WOOD: F1,41=3.4, P<0.059; SUBM: F1,201=10.1, P<0.002; MONT: F1,88=5.1, P<0.026).The overall changes in species composition from mature stage to regenerating stage (sapling + seedling phases) of different vegetation types 21% that is, 79% similarity (using Sorenson index of similarity) between mature and regenerating phase. In disturbed WOOD and DECI, the similarity in species composition between mature trees and regenerating individuals was 49% and 69%, respectively. In little-disturbed vegetation types, species similarity between mature trees and regenerating phases was relatively high. In all the forest types, new entry species (tree species with no adult stages) were present. Percent of new entry species was highest in fire affected WOOD vegetation (Table3).


## 3.1. Species Diversity

In the six vegetation types sampled in the study area, there were 257 tree species belonging to 62 families and 147 genera of angiosperms. Richness of tree species (Figure2) was highest in SEMI (127 spp.) and lowest in the WOOD (28 spp.). Species-area and species-individuals accumulation curve (rarefaction curve) against equal-sized sampling areas in different vegetation types showed a distinct difference in the richness and abundance. Rarefaction can be used to examine the evenness of the distribution of species in assemblages by comparing steepness of curves. Steeper rarefaction curves indicate high heterogeneity. One striking results of rarefaction curves was that SEMI and EVER have the highest curves. This means that species diversity per equal-sized area was highest in these vegetation types but MONT has the most individuals per unit area. Vegetation type at other extreme (low species richness) was WOOD and MONT (Figure 3). The overall difference in species richness among six vegetation types was statistically significant (F5,179=65.1; P<0.0001). Species richness and corresponding abundance were significantly positively correlated in all the vegetation types (DECI: r=0.98, P<0.0001); SEMI: r=0.95, P<0.0001, EVER: r=0.94, P<0.0001; WOOD: r=0.77, P<0.0001; SUBM: r=0.95, P<0.0001; MONT: r=0.87, P<0.0001). A primary analysis evaluating the homogeneity-of-regression (slopes) assumption indicated that the relationship between the covariate (abundance) and the dependant variable (species richness) differs significantly as a function of the independent variable (vegetation types) (R2=0.152; ANCOVA: F6,179=133.4, P<0.001). A significant interaction between the covariate and the factor suggests that the differences on the dependent variable among groups vary as a function of the covariate. Since the result from the ANCOVA was significant, it is not meaningful to proceed further. The highest Shannon index value occurred in SEMI (3.67 for plants with gbh ≥30 cm) and lowest value reported in WOOD (Table 2).Table 2
Vegetation parameters calculated for three tree phases in different vegetation types. See Table1 for explanation of vegetation type abbreviations.
Vegetation types(Altitude range)
Rainfall(mm)
Mean temperature in the coldest month (°C)
Phases of trees
Basal area(m2/ha)
Shannon index
DECI (40–400 m)
1000–1500
28
Mature treesSaplingsSeedlings
23.320.20—
2.792.482.62
SEMI (400–650 m)
2500–3500
24
Mature treesSaplingsSeedlings
45.660.89—
3.673.153.11
EVER (650–1200 m)
3500–5000
22
Mature treesSaplingsSeedlings
48.001.24—
3.343.093.49
WOOD (900–1400 m)
3500–5000
25
Mature treesSaplingsSeedlings
0.690.4—
2.212.161.56
SUBM (1200–1800 m)
5000–6000
13
Mature treesSaplingsSeedlings
36.510.69—
3.263.453.51
MONT (1800–2450 m)
5000–6000
9
Mature treesSaplingsSeedlings
30.871.45—
3.213.192.71
*Mature trees (≥30 cm gbh), saplings (≥ 10 < 30 cm gbh), and seedlings (<10 cm gbh).Figure 2
Species richness (number of species) by tree growth phase in six vegetation types occurring in the Western Ghats. Multiple comparison LSD post hoc test showed richness of all the vegetation types was significantly different (P<0.01–0.05). See Table 1 for an explanation of vegetation type abbreviations.Species accumulation and rarefaction curves of different vegetation types. Curves were created random series of 30 plots of 0.09 ha (i.e., 2.7 ha for each vegetation type). (a) Species-area curves (sample-based rarefaction) and (b) species-individuals curve (individuals-based rarefaction). Looking at the individual-based rarefaction curve, all four vegetation types seem to be quite similar in species richness, except MONT, which is drastically lower although containing the highest number of individuals, WOOD, which contain too few individuals to produce a comparable result. The sample-based rarefaction, on the other hand, identifies SEMI and EVER as the two most species rich communities, differing from the rest. Rarefaction curves for six vegetation types predict the rate of accumulation of species with increasing number of individuals (abundance). See Table1 for an explanation of vegetation type abbreviations.
(a)
(b)Dominant tree species in mature and sapling stages were more or less similar in most vegetation types, but dominant species in the seedling stage varied considerably (Table1). Overall stand density of mature trees (≥30 cm gbh) was highest in MONT (855 trees ha-1) and lowest in WOOD (39 trees ha-1). Densities of both tree saplings and seedlings were highest in EVER (Figure 4). Among 25 tree species dominant across the different forest types, 16 dominated in the tree phase, 15 in the sapling phase, and 14 in the seedling phase. Among the different forest types, there were significant difference in tree (≥30 cm gbh) density (P<0.0001, F5,389=26.9) and basal area (P<0.007, F5,389=3.3). Mean basal area of trees was highest in EVER (48m2ha-1) and lowest in WOOD (Table 2).Figure 4
Densities (noha-1 in log10 scale) of mature trees (≥30 cm gbh (girth at breast height)), saplings (≥10<30 cm gbh), and seedlings (<10 cm gbh) in six vegetation types occurring in the Western Ghats. LSD post hoc test clarified that density of disturbed forest like DECI and WOOD was significantly different with undisturbed vegetation type except MONT.Raunkiaer’s frequency analyses revealed that most of the tree species were rare, as in the case for other tropical forests. In all forest types, 60%–95% of tree species were in the lowest frequency class (Figure5). Furthermore, there were few individuals in the 80%–100% frequency class. In forest types other than DECI, 58%–70% of trees were in the smallest girth category (gbh 50–100 cm); in DECI, only 37% of trees were in the smallest girth class (Figure 6). In WOOD vegetation, which was fire affected and grass dominated, 96% of trees were in the smallest girth class.Percent frequencies of trees (≥30 cm gbh) in different vegetation types. Most of the species were in the lowest frequency class in all vegetation types other than MONT, indicating that a few species were widely distributed; most were restricted in distribution. This is a typical species-abundance distribution (normal distribution) and the tree species in all the vegetation type were heterogeneous distribution in Raunkiaer’s sense.
(a)
(b)
(c)
(d)
(e)
(f)Girth frequency distributions of trees in different vegetation types of the study area. Girth-size was highest in SEMI and EVER. A high percentage of lower girth class trees in DECI results from reduced fuel wood extraction by people of nearby areas. The reverse J-shaped gbh distribution of trees indicates evolving or expanding population.
(a)
(b)
(c)
(d)
(e)
(f)


## 3.2. Regeneration

Frequencies of regenerating species (saplings + seedlings) were maximal in undisturbed forest compared to disturbed one (caused by fuel wood collection and cattle grazing). In DECI, of 71 taxa recorded, only 26 were present in all three growth phases, 24 were present in only one stage, and only 10 species were regenerating well (seedling> sapling > tree). Nevertheless, Lagerstroemia microcarpa, one of the dominant species in DECI, had no seedlings, indicative of poor regeneration potential (Tables 1 and 3; see Supplementary Material Appendix 1 available online at http://dx.doi.org/10.1155/2013/890862). In vegetation types influenced by disturbance and fire, like WOOD, 29% of species were common in all growth phases and seedling richness was very low in these types of vegetation (Supplementary Material Appendix 2).Table 3
Distribution pattern of mature and regenerating phases of trees occur in different vegetation types. Regenerating species and species share in all phases of trees was lower in disturbed vegetation type such as DECI and WOOD as compared to other vegetation types. Percent similarity in species composition (using Sorenson index of similarity) of mature trees and regenerating individuals (saplings + seedlings) in different vegetation types of the study area and new species recruited (trees devoid of adult stage) are also shown.
Vegetation types
Tree species occur in
*Regenerating species (%)
% Similarity between mature trees and regenerating individuals
New entry species (%)
All phases (%)
Mature phase only (%)
Regenerating phase only (%)
DECI
26 (37)
21 (30)
12 (17)
50 (70)
69
12 (17)
SEMI
53 (41)
11 (9)
27 (21)
116 (91)
82
24 (18)
EVER
49 (40)
11 (9)
24 (20)
111 (91)
81
23 (18)
WOOD
8 (29)
8 (29)
11 (39)
20 (71)
49
10 (35)
SUBM
40 (43)
4 (4)
18 (20)
87 (95)
88
20 (21)
MONT
20 (47)
6 (14)
11 (26)
37 (86)
76
10 (23)
*A number of species occur in saplings and/or seedlings, and these species may or may not have mature tree stage; % of species has been given in brackets.In vegetation types at mid elevations, namely, EVER and SEMI, 49%–53% of species were present in all growth phases; 25–30% of species occurred in only one phase (Supplementary Material Appendices 3 and 4). In forests at higher elevations, namely,SUBM and MONT, 43% and 47% of species, respectively, were present in all growth phases. In SUBM, 25 species had poor regeneration potential (Supplementary Material Appendix 5). In MONT, 20 species were present in all growth phases, and 12 had no regeneration potential (Table3, Supplementary Material Appendix 6).


## 3.3. Change in Species Composition among Tree Phases

Overall species richness of mature trees was higher than richness of saplings and seedlings in all vegetation types. Among the dominant species, a few trees had exceptionally large numbers of seedling and saplings. Individual trees did not contribute equally to the seedling population or to later recruitment in the sapling stage. Density of regenerating individuals (saplings + seedlings) was highest in EVER and lowest in WOOD. There was significant difference in the density of regenerating individuals (seedling + saplings) among different vegetation types (F5,611=13.2, P<0.001). Also, there was significant difference in the density of mature and regenerating phase among all vegetation types except WOOD (DECI: F1,130=11.7, P<0.001; SEMI: F1,269=3.7, P<0.05; EVER: F1,255=7.3, P<0.008; WOOD: F1,41=3.4, P<0.059; SUBM: F1,201=10.1, P<0.002; MONT: F1,88=5.1, P<0.026).The overall changes in species composition from mature stage to regenerating stage (sapling + seedling phases) of different vegetation types 21% that is, 79% similarity (using Sorenson index of similarity) between mature and regenerating phase. In disturbed WOOD and DECI, the similarity in species composition between mature trees and regenerating individuals was 49% and 69%, respectively. In little-disturbed vegetation types, species similarity between mature trees and regenerating phases was relatively high. In all the forest types, new entry species (tree species with no adult stages) were present. Percent of new entry species was highest in fire affected WOOD vegetation (Table3).


## 4. Discussion

### 4.1. Species Diversity

The use of species-individuals curves in addition to species-area curves provides a clear insight into species diversity. More sampling area is required for species rich vegetation type compared to species poor one, and in general, the minimum area varies with number of species from one vegetation type to another [51]. In our data, species-rich communities like SEMI and EVER seem to have less dominance than species-poor communities. However, lower rarefaction curve in MONT suggests that abundance effect may not be the sole reason for high richness. The accumulation of new species with increasing sampling effort can be visualized with a species accumulation curve. Increasing the area sampled increases observed species richness both because more individuals get included in the sample and because large areas are environmentally more heterogeneous than small areas [52]. The correlation between species richness and abundance suggests that process affecting change in either richness or abundance also affects species diversity.Species richness of DECI was reduced, likely due to low rainfall and anthropogenic disturbances such as firewood collection and cattle grazing. In fire affected WOOD, grasses were the dominant life forms; these were intermingled with a few fire tolerant, light demanding trees. High species richness of trees in SEMI, EVER, and SUBM was probably related to high rainfall and optimal climatic conditions (Table2). Low temperature and high wind velocity in the MONT may negatively impact tree growth and reduce species richness there. DECI stands were dominated by members of the family Fabaceae, while Euphorbiaceae and Rubiaceae dominated in EVER at mid elevations. High elevation SUBM and MONT were dominated by members of the Lauraceae and Myrtaceae, which have volatile oils in their tissues that resist freezing damage in plant cells [53].Compared to DECI, tree species diversity was very high in other forest types at higher elevations other than in the fire-affected WOOD. High species diversity of SEMI is due its transitional nature; that is, this vegetation type is ecotone area suitable for both deciduous and evergreen tree species; so there is an increase in the number of species. Species diversity indices for saplings were lower than those for mature trees and seedlings in DECI is due to overharvesting of saplings for firewood. The lowest species diversity value in WOOD indicates low species richness and dominance of one or two species in the tree community. In the present study, Shannon index values for tree species are similar to values for other tropical forests of the world (Table4). However, detailed comparisons with other studies are inadvisable because of large differences in sample size, standard girth parameters, and environmental conditions.Table 4
Vegetation parameters of forest communities in the tropics of India and other countries.
Forest types
Location
Plot size (ha)
Tree girth studied (cm)
Tree density(no./ha)
Tree basal area (m2/ha)
Shannon index
References
Present study
DECI
Western Ghats (NBR)
4 ha
≥30 cm
132
23.4
2.79
Present study
SEMI
“
4 ha
≥30 cm
368
45.7
3.67
“
EVER
“
4 ha
≥30 cm
485
48.0
3.34
“
WOOD
“
3 ha
≥30 cm
39
0.69
2.21
“
SUBM
“
4 ha
≥30 cm
390
36.5
3.26
“
MONT
“
4 ha
≥30 cm
855
30.9
3.21
“
India
Evergreen forests
Silent valley, Western Ghat
—
≥31.5
620–709
29–103
—
[6]
Moist deciduous forests
Peppara, WGhats
—
≥30
590–740
13–51
2–3.3
[7]
Moist deciduous forests
Chimmony, Western Ghats
—
≥30
558
37
1.9–2.4
[8]
Semievergreen forests
Peppara, Western Ghats
—
≥30
670–940
45–62
2.9
[7]
Semievergreen forests
Chimmony, Western Ghats
—
≥30
728
47
2.7–3.2
[8]
Scrub jungle to wet evergreen forests
Kalakkad R.F., Western Ghats
0.2
>20
320–1260
18–107
—
[9]
Evergreen forests
Karnataka
0.44
—
446–1386
33–48
—
[10]
Evergreen forests
Peppara
—
≥30
860–1370
76
3.3
[7]
Evergreen forests
Nelliampathi, Western Ghats
—
≥30
—
49.8
3–3.7
[11]
Dry tropical forests
Vindhya region
—
>30
294–559
7–23
—
[12]
Dry evergreen forests
Puthupet Sacred Grove, Coromandel coast
0.2
>20
280
11
—
[13]
Tropical wet evergreen forests
Kalakkad-Mundanthurai Tiger Reserve, Western Ghats
0.50
>30
315–418
54–84
—
[14]
Tropical wet evergreen forests
Kodayar, Western Ghats
0.50
>30
352–1173
28–81
—
[15]
Subtropical hill forests
Peppara. Western Ghats
—
≥30
1580–1930
27–34
2.7
[7]
Montane temperate forests
Mannavan shola
—
≥30
566
52
3.99
[16]
Other countries
Tropical rain forests (young forests)
Barrow Colorado Island, Panama
5
>18
84–171
2.6–5.2
—
[17]
Tropical rain forests(old forests)
Barrow Colorado Island, Panama
50
>18
143–177
4.3–5
—
[18]
Tropical rain forests
Amazonia
3
31.4
1420
28–68
—
[19]
Equatorial insular forests
Eastern Carolline Island, Panama
50
>31.4
98–114
17
—
[20]
Tropical rain forests
Jungka Reserve, Malaysia
11
91
104
23
—
[21]
Tropical rain forests
Gunung Silam, Malaysia
0.04
31.4
513–1596
23–46
—
[22]
Tropical moist forests
Singapore
0.4
>6.3
604
—
—
[23]
Tropical rain forests
Valcan Barva, Costa Rica
6
>31.4
391–617
—
—
[24]
Slope forests
New Caledonia
2.8
>31.4
1533
49
—
[25]
Alluvium forests
New Caledonia
2.6
>31.4
1183
47
—
[25]
Equatorial forests
Kongo Island
—
—
440–553
10–45
—
[26]
Tropical rain forests
Amazonia
3
>31.4
1720
78
—
[19]
Tropical seasonal rain forests
Xishuangbanna, China
2500 m2
15
154
—
3.4
[27]
Tropical montane rain forests
Xishuangbanna, China
1600 m2
15
123
—
3.2
[27]
Evergreen broad leaved forests
Xishuangbanna, China
1200 m2
15
165
—
2.5
[27]
Monsoon forests
Xishuangbanna, China
400 m2
10
150
—
1.6
[27]
“Study conducted in 6 different vegetation types of Western Ghats (NBR).Density and frequency distributions of trees contribute to the structure of tropical forests. Tree density in DECI was much lower than that of other forest types, perhaps due to low rainfall and anthropogenic disturbances. Density was least in the fire-affected WOOD. Sapling densities were elevated in SEMI and EVER. Late secondary successional species were well represented in the sapling population of EVER, which may be indicative of recent natural disturbances in this forest type that promoted regeneration of late secondary species. MONT had high sapling density, due to the stunted nature of trees caused by very low temperature and high wind velocity prevalent there [54].Densities of trees in the study area were similar to estimates from tropical forests within India and other tropical regions (Table4). In tropical forests outside India there is much variation in the densities of trees >30 cm gbh (98–1930 trees ha-1), especially in Amazonian forests. In the Neotropics, maximum species richness of tree individuals >10 cm gbh reaches 300 ha-1 [55]. In South-East Asia, the highest richness is 225 ha-1 [56].In the present study, most of the species were in frequency class 0%–20% and fewest were in frequency class 80%–100%. The frequency distribution of tree species suggested that most of them had low frequency as would be expected in typical species-abundance distribution. A plant species should be considered homogeneously distributed when the numbers of individuals are the same in all parts of a community [50]. Hence, tree species in all the vegetation types of the study area were heterogeneously distributed. Girth class frequency distributions of most species in vegetation types we studied fit “reverse J”-shaped patterns, with most trees in smaller girth classes and few old trees. Vegetation types other than WOOD fit negative exponential patterns indicative of relatively undisturbed or less disturbed conditions in the stands. The high annual precipitation rate and optimum temperature of EVER may have contributed to high tree growth rate and higher tree basal area.


### 4.2. Regeneration

All other vegetation types had better regeneration than DECI. In WOOD, the transition rate of stems from small girth classes to larger girth classes was low. Poor tree regeneration in DECI and WOOD can probably be attributed to fuel wood collection, frequent fires and grazing by cattle. In all forest types, 29%–47% of tree species were present in all three growth phases; other species were present in either one or two growth phases. Dominant species occurred in all girth classes of vegetation types other than WOOD, in which most trees were in the smaller girth classes. There were more large trees in vegetation types like SEMI and EVER, and in these, sapling and seedling densities were adequate for restocking the complement of canopy trees.Change in species composition across mature and regenerating tree phases was more frequent in disturbed forest types like DECI and WOOD. In some cases, the dominant species in adult and seedling stages were quite different in these two disturbed forest types. Our results are not congruent with observations made in northeastern India [39] where tree seedling survival rate increases with increasing forest disturbance. We found species without regenerating phases; these are unlikely to persist. Others that occurred only in seedling and sapling stages were new entrants to the forest species complement. These are examples of discontinuous population structures. Such structures occur in a number of other tropical countries [57–59]. The dominant species in a forest stand is generally present in all size classes [38]. The size class structures of trees indicate the probability of species persistence into the future; this information is very valuable in the design of management strategies aiming to improve stand structure and species diversity. Changes in species composition and recruitment of new species in different vegetation types are indicative of future species composition in changing environments.


## 4.1. Species Diversity

The use of species-individuals curves in addition to species-area curves provides a clear insight into species diversity. More sampling area is required for species rich vegetation type compared to species poor one, and in general, the minimum area varies with number of species from one vegetation type to another [51]. In our data, species-rich communities like SEMI and EVER seem to have less dominance than species-poor communities. However, lower rarefaction curve in MONT suggests that abundance effect may not be the sole reason for high richness. The accumulation of new species with increasing sampling effort can be visualized with a species accumulation curve. Increasing the area sampled increases observed species richness both because more individuals get included in the sample and because large areas are environmentally more heterogeneous than small areas [52]. The correlation between species richness and abundance suggests that process affecting change in either richness or abundance also affects species diversity.Species richness of DECI was reduced, likely due to low rainfall and anthropogenic disturbances such as firewood collection and cattle grazing. In fire affected WOOD, grasses were the dominant life forms; these were intermingled with a few fire tolerant, light demanding trees. High species richness of trees in SEMI, EVER, and SUBM was probably related to high rainfall and optimal climatic conditions (Table2). Low temperature and high wind velocity in the MONT may negatively impact tree growth and reduce species richness there. DECI stands were dominated by members of the family Fabaceae, while Euphorbiaceae and Rubiaceae dominated in EVER at mid elevations. High elevation SUBM and MONT were dominated by members of the Lauraceae and Myrtaceae, which have volatile oils in their tissues that resist freezing damage in plant cells [53].Compared to DECI, tree species diversity was very high in other forest types at higher elevations other than in the fire-affected WOOD. High species diversity of SEMI is due its transitional nature; that is, this vegetation type is ecotone area suitable for both deciduous and evergreen tree species; so there is an increase in the number of species. Species diversity indices for saplings were lower than those for mature trees and seedlings in DECI is due to overharvesting of saplings for firewood. The lowest species diversity value in WOOD indicates low species richness and dominance of one or two species in the tree community. In the present study, Shannon index values for tree species are similar to values for other tropical forests of the world (Table4). However, detailed comparisons with other studies are inadvisable because of large differences in sample size, standard girth parameters, and environmental conditions.Table 4
Vegetation parameters of forest communities in the tropics of India and other countries.
Forest types
Location
Plot size (ha)
Tree girth studied (cm)
Tree density(no./ha)
Tree basal area (m2/ha)
Shannon index
References
Present study
DECI
Western Ghats (NBR)
4 ha
≥30 cm
132
23.4
2.79
Present study
SEMI
“
4 ha
≥30 cm
368
45.7
3.67
“
EVER
“
4 ha
≥30 cm
485
48.0
3.34
“
WOOD
“
3 ha
≥30 cm
39
0.69
2.21
“
SUBM
“
4 ha
≥30 cm
390
36.5
3.26
“
MONT
“
4 ha
≥30 cm
855
30.9
3.21
“
India
Evergreen forests
Silent valley, Western Ghat
—
≥31.5
620–709
29–103
—
[6]
Moist deciduous forests
Peppara, WGhats
—
≥30
590–740
13–51
2–3.3
[7]
Moist deciduous forests
Chimmony, Western Ghats
—
≥30
558
37
1.9–2.4
[8]
Semievergreen forests
Peppara, Western Ghats
—
≥30
670–940
45–62
2.9
[7]
Semievergreen forests
Chimmony, Western Ghats
—
≥30
728
47
2.7–3.2
[8]
Scrub jungle to wet evergreen forests
Kalakkad R.F., Western Ghats
0.2
>20
320–1260
18–107
—
[9]
Evergreen forests
Karnataka
0.44
—
446–1386
33–48
—
[10]
Evergreen forests
Peppara
—
≥30
860–1370
76
3.3
[7]
Evergreen forests
Nelliampathi, Western Ghats
—
≥30
—
49.8
3–3.7
[11]
Dry tropical forests
Vindhya region
—
>30
294–559
7–23
—
[12]
Dry evergreen forests
Puthupet Sacred Grove, Coromandel coast
0.2
>20
280
11
—
[13]
Tropical wet evergreen forests
Kalakkad-Mundanthurai Tiger Reserve, Western Ghats
0.50
>30
315–418
54–84
—
[14]
Tropical wet evergreen forests
Kodayar, Western Ghats
0.50
>30
352–1173
28–81
—
[15]
Subtropical hill forests
Peppara. Western Ghats
—
≥30
1580–1930
27–34
2.7
[7]
Montane temperate forests
Mannavan shola
—
≥30
566
52
3.99
[16]
Other countries
Tropical rain forests (young forests)
Barrow Colorado Island, Panama
5
>18
84–171
2.6–5.2
—
[17]
Tropical rain forests(old forests)
Barrow Colorado Island, Panama
50
>18
143–177
4.3–5
—
[18]
Tropical rain forests
Amazonia
3
31.4
1420
28–68
—
[19]
Equatorial insular forests
Eastern Carolline Island, Panama
50
>31.4
98–114
17
—
[20]
Tropical rain forests
Jungka Reserve, Malaysia
11
91
104
23
—
[21]
Tropical rain forests
Gunung Silam, Malaysia
0.04
31.4
513–1596
23–46
—
[22]
Tropical moist forests
Singapore
0.4
>6.3
604
—
—
[23]
Tropical rain forests
Valcan Barva, Costa Rica
6
>31.4
391–617
—
—
[24]
Slope forests
New Caledonia
2.8
>31.4
1533
49
—
[25]
Alluvium forests
New Caledonia
2.6
>31.4
1183
47
—
[25]
Equatorial forests
Kongo Island
—
—
440–553
10–45
—
[26]
Tropical rain forests
Amazonia
3
>31.4
1720
78
—
[19]
Tropical seasonal rain forests
Xishuangbanna, China
2500 m2
15
154
—
3.4
[27]
Tropical montane rain forests
Xishuangbanna, China
1600 m2
15
123
—
3.2
[27]
Evergreen broad leaved forests
Xishuangbanna, China
1200 m2
15
165
—
2.5
[27]
Monsoon forests
Xishuangbanna, China
400 m2
10
150
—
1.6
[27]
“Study conducted in 6 different vegetation types of Western Ghats (NBR).Density and frequency distributions of trees contribute to the structure of tropical forests. Tree density in DECI was much lower than that of other forest types, perhaps due to low rainfall and anthropogenic disturbances. Density was least in the fire-affected WOOD. Sapling densities were elevated in SEMI and EVER. Late secondary successional species were well represented in the sapling population of EVER, which may be indicative of recent natural disturbances in this forest type that promoted regeneration of late secondary species. MONT had high sapling density, due to the stunted nature of trees caused by very low temperature and high wind velocity prevalent there [54].Densities of trees in the study area were similar to estimates from tropical forests within India and other tropical regions (Table4). In tropical forests outside India there is much variation in the densities of trees >30 cm gbh (98–1930 trees ha-1), especially in Amazonian forests. In the Neotropics, maximum species richness of tree individuals >10 cm gbh reaches 300 ha-1 [55]. In South-East Asia, the highest richness is 225 ha-1 [56].In the present study, most of the species were in frequency class 0%–20% and fewest were in frequency class 80%–100%. The frequency distribution of tree species suggested that most of them had low frequency as would be expected in typical species-abundance distribution. A plant species should be considered homogeneously distributed when the numbers of individuals are the same in all parts of a community [50]. Hence, tree species in all the vegetation types of the study area were heterogeneously distributed. Girth class frequency distributions of most species in vegetation types we studied fit “reverse J”-shaped patterns, with most trees in smaller girth classes and few old trees. Vegetation types other than WOOD fit negative exponential patterns indicative of relatively undisturbed or less disturbed conditions in the stands. The high annual precipitation rate and optimum temperature of EVER may have contributed to high tree growth rate and higher tree basal area.


## 4.2. Regeneration

All other vegetation types had better regeneration than DECI. In WOOD, the transition rate of stems from small girth classes to larger girth classes was low. Poor tree regeneration in DECI and WOOD can probably be attributed to fuel wood collection, frequent fires and grazing by cattle. In all forest types, 29%–47% of tree species were present in all three growth phases; other species were present in either one or two growth phases. Dominant species occurred in all girth classes of vegetation types other than WOOD, in which most trees were in the smaller girth classes. There were more large trees in vegetation types like SEMI and EVER, and in these, sapling and seedling densities were adequate for restocking the complement of canopy trees.Change in species composition across mature and regenerating tree phases was more frequent in disturbed forest types like DECI and WOOD. In some cases, the dominant species in adult and seedling stages were quite different in these two disturbed forest types. Our results are not congruent with observations made in northeastern India [39] where tree seedling survival rate increases with increasing forest disturbance. We found species without regenerating phases; these are unlikely to persist. Others that occurred only in seedling and sapling stages were new entrants to the forest species complement. These are examples of discontinuous population structures. Such structures occur in a number of other tropical countries [57–59]. The dominant species in a forest stand is generally present in all size classes [38]. The size class structures of trees indicate the probability of species persistence into the future; this information is very valuable in the design of management strategies aiming to improve stand structure and species diversity. Changes in species composition and recruitment of new species in different vegetation types are indicative of future species composition in changing environments.


## 5. Conclusions

The species diversity of trees varied across vegetation types in the Western Ghats landscape. Rarefaction curves show that species diversity is highest in SEMI and EVER and lowest in WOOD while species abundance is highest in MONT. Vegetation types of study area are in heterogeneous in distribution. There were large differences in species composition of adult trees and regenerating individuals in the disturbed vegetation types as compared to undisturbed stands. The present study reveals that the anthropogenic disturbance causes disruption of forest structure and change in species composition which ultimately leads to reduction of tree species richness and abundance which are the major attributes of forests. New recruits were found in all vegetation types, indicating that they were not headed to extinction; however, disturbed stands may move to new species compositions in the future.



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*Source: 890862-2013-05-30.xml*