Vegetation Structure and Prioritizing Plants for Eco-Restoration of Degraded Wildlife Corridor in Dry Tropical Forest of South India

Abstract

Wildlife corridors are critical to manage wildlife and maintain ecological processes. However, they are fragmented and degraded due to various anthropogenic activities. Fragmentation in turn affects population viability of species by affecting their dispersal, re-colonization and genetic exchanges. But the process can be reversed through restoration and management of ‘functional corridors’. So far in the forestry sector, monoculture plantations are known to be the ideal reforestation/afforestation strategy to restore degraded landscape but experts argue that monoculture plantations have failed to recover former biological diversity. Therefore, for successful eco-restoration, first, the regional plant stock has to be identified and then suitable plant species have to be prioritized. The habitat enrichment through assisted vegetation method in the degraded wildlife corridors can improve green cover and also bring back the original vegetation. The study was conducted in the Edeyarahalli-Doddasampige wildlife corridor area, which is part of Biligiri Rangaswamy Temple Tiger Reserve, Western Ghats, India. The vegetation was enumerated through transect and quadrate method. The vegetation structure was analyzed and ten suitable native plant species were prioritized for eco-restoration. The priority was given based on site condition and socio-ecological importance of the plants such as trees with timber value, non-timber forest products, nectar source for honey bees and also food source for elephants. At a time of unprecedented forest destruction, the interventions made through this line of research would not only improve the habitat quality but also increase the functionality of wildlife corridors by providing safe passage for animals’ movement. In addition to this, convergence of local multistakeholders and their responsibility needs to be explored toward eco-restoration process.

1. Introduction

The world’s tropical forests are being fragmented and degraded with significant loss of species diversity and ecosystem services [1, 2, 3, 4]. Unplanned infrastructure development in forest landscapes, clearing of forest land for expansion of human habitation as well as farmland, and unsustainable extraction of forest resources can create growing pressures and also inflict negative impacts on wildlife habitat [5, 6, 7]. According to meta-population, meta-community and island-biogeography theories, degradation and fragmentation of natural wildlife habitats could lead to the extinction of many species across the globe due to loss of sub-population connectedness and inbreeding depression [4, 8]. Therefore, at the time of unprecedented wildlife habitat destruction, eco-restoration of degraded forest areas particularly wildlife corridors is gaining global importance and also emerging as a practical conservation strategy [9, 10, 11, 12]. Under the ‘Green India Mission’, the Indian government is planning to double afforestation efforts by 2020 [13] and also planning to buy private plantations to restore elephant corridors [14, 15].

According to the ‘Field of Dreams Hypothesis’, if a habitat is successfully restored, the species will return but we need to refine the appropriate restoration strategy. So far in the forestry sector, monoculture plantations are known to be the ideal reforestation strategy to restore degraded landscapes [16, 17, 18] but experts argue that monoculture plantations failed to recover their former biological diversity [19, 20, 21]). Therefore, to reverse the effect, the eco-restoration method would be the appropriate strategy. Habitat enrichment through assisted vegetation method can improve green cover as well as bring back the native vegetation and provide resource rich passage for animals’ movement. However, as a first step in the eco-restoration activity, the regional plant stock has to be assessed and then suitable native plant species has to be prioritized based on their socio-ecological importance and site condition [22]. In addition to this, the species which are selected for eco-restoration should be strong and hard enough to withstand and survive in the prevailing climatic conditions; mainly heavy rain and dry seasons [16]. This is because, the type of forest occurring naturally in a place is the result of the complex influence of the climatic, edaphic, topographic, and biotic factors of the locality [23].

The Edeyaralli-Doddasampige wildlife corridor (ED corridor) in Biligiri Rangaswamy Temple Tiger Reserve (BRT), Western Ghats is one such biodiversity rich forest landscape but subjected to various land-use practices leading to fragmentation and degradation of wildlife habitat and wildlife migratory routes. Therefore, action and restoration research has been planned in this degraded corridor to maintain the habitat quality and also increase the functionality of the corridor through assisted vegetation enrichment. For successful eco-restoration, first, the regional plant stock has to be identified and then suitable plant species have to be prioritized. In this study, we have addressed the following two research questions; (i) How are the plant community variables such as species richness, density, diversity and IVI (Importance Value Index) distributed among life forms in the corridor landscape?, (ii) How do we prioritize the suitable plant species/categories for eco-restoration of degraded wildlife corridor?

2. Methods

2.1. Study site

The study has been carried out at Edeyarahalli-Doddasampige wildlife corridor (ED corridor), which is one of the degraded but ecologically important functional corridors between Biligiri Rangaswamy Temple Tiger Reserve (BRT) and Malai Mahadeswara Hills Wildlife Sanctuary (MM Hills) (Figure 1). The dimension of the ED corridor is 0.5 km in length and 2 km in width and the geographical coordinates are 11°55′15″ to 11°56′15″N and 77°15′20″ to 77°15′45″E. The corridor landscape is largely in the dry deciduous and scrub forest type. It harbors rich floral and faunal diversity, mainly IUCN red listed mammal species such as Asian elephant (Elephas maximus), Bengal tiger (Panthera tigris), Indian leopard (Panthera pardus) and Indian wild dog (Cuon alpinus). In addition to this, the corridor landscape is inhabited by Soligas, an indigenous tribal community and a few other non-tribal communities.

Figure 1.

Matrix of forests, wildlife corridors, dependent villages, farmland and road network in and around the corridor landscape (marked in circles).

The corridor landscape is severely degraded due to unplanned land-use practices, past forest management activities- logging and shifting cultivation -and the problem of invasive/exotic plants species [24, 25]. Apart from that, the villagers use this corridor regularly for livestock grazing and fuel wood collection [6]. In addition to this, the state highway (SH-17A) is passing through this wildlife corridor and an average of one vehicle per minute was recorded on this road [26]. This could be an additional threat to the movement of wildlife in this corridor. Irrespective of various threats, ED corridor provides space and passage for more than 15 mammal species (large, medium and small) to move from Western Ghats to forested landscapes of Eastern Ghats [27]. Adjacent to this corridor, in 2007 approx. 25.5 acres of private land was purchased from local farmers to widen the corridor by WTI (Wildlife Trust of India) and its international partner organization International Fund for Animal Welfare (IFAW), with financial support from US Fish and Wildlife Services (USFWS). The land was then handed over to the Karnataka State Forest Department to augment the corridor. This was a pioneering move in corridor conservation in India [6].

2.2. Vegetation enumeration

Transect method was used to enumerate vegetation in the corridor landscape. There were 64 belt transects of 0.1 ha (10 × 100 m), 128 plots of 10 m² and 512 plots of 1 m² were established to enumerate trees, shrubs and herbaceous plants respectively in the study area (Figure 2). Each sampling transect was marked with red ribbons, and the GPS coordinates were recorded at the center of each transect for future study purpose. The sampling was carried out in the month of October, which is the peak wet season in the study area. This is because during the wet season the chances of finding herbaceous species as well as seedlings of woody species in the study area are higher.

Figure 2.

Survey design for vegetation study in the corridor landscape of BRT Tiger Reserve. The sampling was carried out in the blocks which fall within the circles. One 2 × 2 km sampling block consists of four vegetation plots, eight shrub plots and 32 herb plots.

2.2.1. Data collection

In 10 × 100 m transects all stems >5 cm DBH (diameter at breast height - at 130 cm) were enumerated. The DBH of the individual stems were measured for all the species found in the transects using calibrated DBH tape. The height was measured through visual approximation method [28, 29]. In 10 × 10 m plots all the shrubs and saplings of woody plant species whose DBH fell between 1 and 5 cm were counted and named. Finally, in the 1 × 1 m plots all the herbaceous plants and seedlings of woody plant species (whose stem size was <1 cm) were recorded. For most of the species, botanical names and family names were identified and recorded in the field itself. For unidentified plant species, the specimen samples were collected for herbarium preparation and identification was done in the laboratory by using ‘Flora of the Presidency of Madras’ [30]. For grass species the per cent cover per unit area was calculated through visual estimation rather than counting individual species. The percentage of invasive species Lantana camara cover per plot was also recorded through visual estimation at the time of study period. Visual estimation is fast, requires no specialized equipment, and can be adapted to plants of various growth forms [28, 29]. In addition to this, the number of cut stems and cowpats was recorded in the transects to assess the intensity of fuel wood collection and cattle grazing respectively in the study area.

Plant community variables such as species richness, Shannon’s diversity H′ and evenness J was calculated for the corridor landscape. Simple linear regression models were developed to test the influence of Lantana camara, fuelwood collection and cattle grazing on native plant diversity. In addition to this, species Importance Value Index (IVI) was calculated to identify the dominant species of the study area for both tree and non-tree classes.

For trees the IVI was calculated by using the formula; IVI of sp. i = relative density of sp. i + relative frequency of sp. i + relative dominance of sp. i. However, since data on relative dominance which is derived from basal area is not possible for non-trees, the IVI for undergrowth (non-trees) was calculated using the formula modified as IVI of sp. i = relative density of sp. i + relative frequency of sp. i.

Local community considerations were also considered in addition to scientific data in prioritizing suitable native plant species for eco-restoration. This is because people from the landscape, especially Soliga tribals, possess sophisticated knowledge about biodiversity and traditional forest resource management practices [25, 31, 32]. Therefore, a participatory approach was employed to prioritize native plant species. Three Focus Group Discussions (FGD) were conducted in three corridor landscape dependent villages. In addition, a couple of informal interviews were also conducted. Questions were asked regarding corridors, wildlife, eco-restoration and presence of suitable plant species in the landscape.

3. Results

3.1. Plant community structure

Species richness and Shannon’s diversity H′ is relatively higher in tree class compared to shrub and herbaceous class. The evenness J is more or less similar between shrub and herbaceous class but relatively higher than tree class (Table 1). The corridor landscape had 92 tree species (belonging to 39 families), 75 shrub species (belonging to 41 families) and 185 species (belonging to 65 families). About 73.9% stems belong to different shrub species and 26.1% are saplings of woody species. In terms of total herbaceous stems enumerated in the study area, around 77.8% are herbaceous plants and 22.2% are woody seedlings.

Community variable	Tree; (mean ± se); Per 0.1 ha	Shrub; (mean ± se); Per 10 m^2	Herb; (mean ± se); Per m^2	Grass cover (mean ± se); percent/m^2
	(n = 64)	(n = 128)	(n = 512)	(n = 512)
Species richness	12.48 ± 0.53	6.13 ± 0.28	8.52 ± 0.14	–
Shannon’s H′	2.06 ± 0.05	1.39 ± 0.05	1.72 ± 0.02	–
Evenness J	0.69 ± 0.01	0.78 ± 0.0	0.74 ± 0.006	–
Density	42.76 ± 3.36	21.15 ± 1.32	37.89 ± 1.05	44.90 ± 1.35

Table 1.

Plant community variables among life forms (trees, shrubs, and herbs) of native vegetation in the corridor area.

3.1.1. Resource plants

The study area is endowed with rich plant resources. Out of 92 tree species, 10 species turned out to be important Non-timber forest products (NTFP) resource plants. They represented 2.5% of the total stems enumerated in the area. Among the NTFP category, fruits of Phyllanthus indofischeri ranked high. Nine tree species provided fuelwood (per. Interviews with local people) – and represented 13.5% of the total stems enumerated. Thirteen species were identified as important food resource for elephants (as mentioned in Refs. [33, 34, 35]), which represent 18% of total stems recorded from the study area (Table 2).

Sl. no.	Scientific name	Family	Importance
1	Acacia chundra	Mimosaceae	Fuelwood tree
2	Anogeissus latifolia	Combretaceae	Fuelwood tree
3	Canthium travancoricum	Rubiaceae	Fuelwood tree
4	Chloroxylon swietenia	Rutaceae	Fuelwood tree
5	Erythroxylon monogynum	Erythroxylaceae	Fuelwood tree
6	Grewia asiatica	Tiliaceae	Fuelwood tree
7	Ixora arborea	Rubiaceae	Fuelwood tree
8	Randia dumetorum	Rubiaceae	Fuelwood tree
9	Ziziphus xylopyrus	Rhamnaceae	Fuelwood tree
1	Acacia sinuata	Mimosaceae	NTFP plant (fruit)
2	Azadirachta india	Meliaceae	NTFP plant (fruit)
3	Bombax ceiba	Bombacaceae	NTFP (undeveloped fruit)
4	Decalepis hamiltonii	Asclepiadaceae	NTFP plant (root)
5	Phoenix loureirii	Arecaceae	NTFP plant (leaves)
6	Phyllanthus indofischeri	Euphorbiaceae	NTFP plant (fruit)
7	Syzygium cumini	Myrtaceae	NTFP plant (fruit)
8	Tamarindus indica	Fabaceae	NTFP plant (fruit)
9	Terminalia bellerica	Combretaceae	NTFP plant (fruit)
10	Terminalia chebula	Combretaceae	NTFP plant (fruit)
1	Acacia chundra	Fabaceae	Elephant food plant
2	Acacia leucophlea	Mimosaceae	Elephant food plant
3	Acacia sinuata	Mimosaceae	Elephant food plant
4	Albizia amara	Fabaceae	Elephant food plant
5	Atylosia lineata	Fabaceae	Elephant food plant
6	Bambusa arundinacea	Poaceae	Elephant food plant
7	Capparis seperaria	Capparaceae	Elephant food plant
8	Commiphora caudata	Burseraceae	Elephant food plant
9	Dendrocalamas strictus	Poaceae	Elephant food plant
10	Grewia tilifolia	Malvaceae	Elephant food plant
11	Hardwickia binata	Fabaceae	Elephant food plant
12	Tectona grandis	Verbenaceae	Elephant food plant
13	Ziziphus xylopyrus	Rhamnaceae	Elephant food plant

Table 2.

List of fuelwood, NTFP, and elephant food plant species in the corridor area.

3.2. Species importance value or IVI

The study site was evaluated for importance value index of each species. For tree species, the top ten most common species found in the sampled area were Anogeissus latifolia, Chloroxylon swietenia, Erythroxylon monogynum, Dalbergia lanceolaria, Strychnos potatorum, Naringi crenulata, Acacia chundra, Diospyros montana, Canthium travencoricum and Ixora arborea (Table 3). Among 92 species, these 10 species contribute 52% of the total IVI (Appendix A).

Dominant tree species	IVI value
Chloroxylon swietenia	32.89
Anogeissus latifolia	30.72
Erythroxylon monogynum	28.76
Acacia chundra	11.88
Dalbergia lanceolaria	11.48
Strychnos potatorum	10.56
Naringi crenulata	08.57
Diospyros montana	08.34
Ixora arborea	07.74
Canthium travancoricum	07.70

Table 3.

Importance Value Index (IVI) for top ten tree species in the corridor landscape of BRT Tiger Reserve.

For non-tree forms such as shrubs/saplings, the top ten and most common species found in the corridor landscape were Lantana camara, Pterolobium hexapetalum, Dodonaea viscosa, Randia dumetorum, Chloroxylon swietenia, Erythroxylon monogynum, Zizyphus oenoplia, Fluggea leucopyrus, Eupatorium odoratum, Dolichandrone falcata and Pavetta indica (Table 4). Among 75 species, these 10 species contribute 70% of the total IVI, of which Lantana camara alone contributes 32% (Appendix B).

Non-tree forms	Dominant species	IVI value
Saplings/shrubs	Lantana camara	64.60
	Pterolobium hexapetalum	13.20
	Dodonia viscosa	11.92
	Randia dumetorum	09.68
	Chloroxylon swietenia	09.54
	Erythroxylon monogynum	07.63
	Ziziphus oenoplia	07.52
	Fluggea leucopyrus	05.88
	Eupatorium odoratum	05.65
	Dolichandrone falcata	05.47
Seedlings/herbs	Leucas martinicensis	16.81
	Oxalis corniculata	12.40
	Eupatorium odoratum	11.00
	Lantana camara	10.96
	Evolvulus alsinoides	05.68
	Atylosia lineata	04.59
	Randia dumetorum	04.57
	Justicia simplex	04.10
	Crotalaria calycina	03.98
	Ziziphus oenoplia	03.10

Table 4.

Importance Value Index (IVI) for top ten non-tree species in the corridor landscape of BRT Tiger Reserve.

For the seedlings/herbaceous plant group, the top ten most important species found in the corridor landscape were Leucas martinicensis, Oxalis corniculata, Eupatorium odoratum, Lantana camara, Evolvulus alsinoides, Atylosia lineata, Randia dumetorum, Justicia simplex, Crotalaria calycina and Ziziphus oenoplia (Table 4). Among 185 species, these 10 species contribute 38% of the total IVI (Appendix C).

The problematic invasive weeds of the landscape, such as Lantana camara and Eupatoruim odoratum are contributing significantly toward total IVI in both shrubs and herbs categories. Lantana camara contributes 32.30% and 5.47% for total IVI of shrubs and herbs respectively, whereas Eupatoruim odoratum contributes 2.82% and 5.89% for total IVI of shrubs and herbs respectively. This indicates the extent of invasion of weeds in the landscape.

3.3. Relationship between vegetation diversity and habitat characteristics

The data was analyzed for relationships between one of the community variables such as vegetation diversity - of trees, shrubs and herbs - (as a response variable) with three habitat covariates such as fuelwood collection, livestock grazing intensity and invasive species – Lantana camara density (as predictor variables). The (four) models were developed to test the relationship between Diversity (H′) of- (i) trees vs. fuelwood collection, (ii) shrubs vs. Lantana camara density, (iii) herbs vs. Lantana camara density and (iv) herbs vs. grazing intensity of livestock.

Even though no statistically significant linear dependence of the mean of y on x was detected (the p-values are >0.05 for all relationships except for Shannon’s diversity vs. Lantana camara density in shrubs) the slope (regression coefficients) shows a negative trend (Figure 3). The negative (marked in minus symbol) slope coefficient value for (i) trees vs. fuelwood collection is −0.007, (ii) shrubs vs. Lantana camara density is −0.006, (iii) herbs vs. Lantana camara density is −0.001 and (iv) herbs vs. grazing intensity of livestock −0.005. This indicates that fuelwood collection, cattle grazing and the density of invasive species like Lantana camara affects the species diversity (H′) of life forms (trees, shrubs and herbaceous species) in the corridor landscape.

Figure 3.

Relationships between species diversity (H′) and three habitat characteristics (fuelwood collection, livestock grazing and Lantana camara density). Cut stems/plot implies fuelwood collection in the landscape.

4. Discussion

Species richness is often treated not only as a measure of biodiversity [36] but also quality of the ecosystem and recovery of forest from disturbances such as logging [37, 38, 39]. The corridor is in the dry deciduous and scrub forest harboring 92 tree species in the sampled area, representing approximately 12% of plant species of the entire BRT forest enumerated [40]. The study site had around 10 NTFP species that provide partial household income for people in the corridor landscape; 12% for Soligas and 7% for non-Soligas [27]. The fruit of Indian Gooseberry tree is not only serves as a livelihood source for local people but also as an important dietary component for wild animals during the lean season [41, 42, 43]. As a result around 17% of amla sapling stems are re-sprouts in the study area. As in Ref. [44], fire and grazing in BRT could be the drivers of the high proportion of re-sprout as part of the demography.

The study result shows that vegetation diversity decreased with increase in fuelwood collection (in tree class), livestock grazing and invasive species (in non-tree class). Subsequently it will severely affect not only the plant community structure and regeneration [45, 46] but also habitat quality of the landscape [24], genetic structure of NTFPs at population level [47] and increment of woody vegetation [48]. Lantana camara is affecting native vegetation mainly of herbaceous class and shrub species, and is responsible for significant reduction in species richness and diversity [49]. As in Ref. [50] the study result from BRT forest showed that Lantana camara is the major driver impacting the demographic pattern of species such as P. emblica and P. indofischeri. This could be due to poor survival of light demanding seedlings of native tropical dry forest species under the conditions of high Lantana camara abundance and shade [51]. If the present scenario continues for a long period of time, it will gradually reduce forest regeneration rates and thus lead to impaired sustainability of the corridors [49, 52, 53].

4.1. Prioritized plant species for eco-restoration: a socio-ecological approach

Globally, conceptual models for restoration of biodiversity have highlighted the importance of regional plant source pool and framework species in restoration [54, 55, 56]. Regional plant species are more important for eco-restoration, because the type of forest occurring naturally in a place is the result of climatic, edaphic, topographic, and biotic factors of the locality [22, 23].

Out of 92 tree species, 10 species contribute 52% of the total IVI of the corridor landscape. Among the 10 species Anogeissus latifolia, Canthium travancoricum, Erythroxylon monogynum and Ixora arborea are the top five species which have been exploited for fuelwood. People prefer these trees as firewood due to their calorific value, ease of carrying as headload, and frequency of availability. Though species such as Cassia spectabilis and Eucalyptus sp. could form good fuelwood and timber trees respectively they are not collected by people as they are planted by the Forest Department. Some of the other tree species with high IVI in this landscape are not preferred either as fuelwood species or as domestic timber requirements due to multiple reasons. For instance, Chloroxylon swietenia, Acacia chundra, and Strychnos potatorum are tree species with thick/rough bark and are uncomfortable to carry as headload. Similarly Diospyros montana is not harvested for fuelwood because of the belief that doing so could splinter the family by inciting fights between family members. Similarly, people believe that Terminalia bellerica is one of the sacred trees in the landscape and belongs to the god Shani Devaru, (a local deity regarded as an incarnation of Shiva). Hence, we have shortlisted Anogeissus latifolia as a dominant and firewood tree species, and Terminalia crenulata, Dalbergia lanceolaria and Albizia odoratissima as timber tree species for vegetation enrichment. Since Phyllanthus indofischeri and Terminalia bellerica are major NTFP species that serve as a source of livelihood for local people [41] and also form part of the dietary requirement for ungulates during the lean season, people generally do not cut these trees for fuelwood. So, we have shortlisted these two species also for vegetation enrichment. Since honey is a major NTFP in this landscape, people suggested the planting of one nectar yielding tree species for honey bees in the landscape such as Pterocarpus marsupium. In addition to these, Acacia chundra, Hardwickia binata and Bambusa arundinacea were identified and shortlisted as important plant sources of elephant’s food in the landscape [33, 34, 35].

Ten suitable native plant species were identified for vegetation enrichment based on their Important Value Index, ecological importance and recommendation by the community. Our research prioritized similar plant species for restoration such as Anogeissus latifolia (dominant tree and source of firewood), Terminalia crenulata, Dalbergia lanceolaria and Albizia odoratissima (timber trees), Phyllanthus indofischeri and Terminalia bellirica (NTFP trees), Pterocarpus marsupium (nectar source for honey bees), Acacia chundra, Hardwickia binata and Bambusa arundinacea (elephant food plants).

4.2. Species selected for clonal propagation

The plant species such as Bambusa aurindinacea, Tectona grandis, Gmelina arborea and Dalbergia sissoo in the corridor landscape may have the capability to propagate through clonal methods. Clonally propagated species (CPS) have the capacity to tolerate adverse conditions and give significantly better growth rates, and better disease resistance with most desirable timber traits [57]. In addition to this, clonal propagation trait not only could persist and maintain species richness but also retain genetic diversity of the species in the forests even after experiencing disturbance in the form of forest fire, grazing, and harvesting pressure from fuelwood collection [58, 59]. Since clonal propagation of dry tropical forest trees influence the tree species composition and demography, we suggested planting CPS, including bamboo along the forest boundary and teak in the farmland of the study area.

4.3. Nursing plants

Most of the forest landscapes in BRT have been subjected to different kinds of forest management practices such as shifting cultivation, logging, monoculture plantation, etc., both by the indigenous community and the State Forest Department in the past. This makes it more complex when it comes to understanding the structure, composition and successional status of native species [24, 25]. However, in eco-restoration, in order to improve the performance of target species, the “nursing” procedure seems to be promising, and shows enhanced plant survival and growth [18]. Therefore, in the same landscape, two native species, Pterolobium hexapetalum and Dodonaea viscosa were identified. These could play the role of nursing plants as they cover the native shrub and sapling communities extensively in more open forested areas. Being a prickly straggler, Pterolobium hexapetalum is not grazed by cattle and other ungulates. Likewise, Dodonaea viscosa, a bushy plant, is a pioneer species that is not eaten by cattle or other ungulates. Based on our field observations, we believe that these two native plants P. hexapetalum and D. viscosa could play the role of nursing by protecting seedlings from grazing and browsing, and influence the regeneration of tree seedlings and saplings.

5. Conclusion

In a human-dominated forest landscape like BRT, corridors have been subjected to severe anthropogenic disturbances and poor management. Fuelwood collection and livestock grazing coupled with invasive species Lantana camara have affected the vegetation dynamics of the corridor landscape. This will indirectly affect not only the dependent animal community but also the livelihoods of local people at some point in the same landscape. Our study has provided base line information on composition and size of the regional plant species pool, and also selected 10 native plant species for vegetation enrichment as part of eco-restoration in the corridor. Active and large scale Lantana camara removal coupled with enrichment planting activity needs to be initiated in and around the corridors to improve the habitat quality of the corridor landscape. Exploring the possibilities of using native shrub plants such as Pterolobium hexapetalum and Dodonaea viscosa as nursing plants to promote the survival rate of saplings of tree species could be one of the strategies. Convergence in the form of collaboration with local community, local institutions, local stakeholders, civil society, government and non-government research organizations is essential for improved protection and sustainable management of these important corridors. Such collaboration may help to increase the likelihood of persistence of animal populations by providing functional connectivity between the fragments. In fact the local community showed interest in establishing decentralized nurseries in the landscape to raise the selected plant species on incentive basis in collaboration with the Forest Department and the Village Panchayat. At a time of unprecedent habitat destruction, this could promote not only local participation and co-management of the wildlife corridor in a human-dominated forest landscape but also contribute toward ‘UN-REDD Programme Strategic Framework’ which is aiming to enhance carbon stocks in degraded forests [60].

Acknowledgments

We acknowledge financial support received from USAID India (AID-386 A-14-00011) and research permission from the Karnataka State Forest Department to carry out field work.

Sl. no.	Botanical name	Family	Relative density	Relative frequency	Relative basal area	IVI
1	Chloroxylon swietenia	Rutaceae	17.21	6.13	9.55	32.89
2	Anogeissus latifolia	Combretaceae	13.08	5.63	12.01	30.72
3	Erythroxylon monogynum	Erythroxylaceae	14.58	6.26	7.93	28.76
4	Acacia chundra	Mimosaceae	4.86	4.38	2.65	11.89
5	Dalbergia lanceolaria	Fabaceae	2.74	3.63	5.11	11.48
6	Strychnos potatorum	Strychnaceae	4.02	3.38	3.17	10.57
7	Naringi crenulata	Rutaceae	3.22	3.13	2.23	8.57
8	Diospyros montana	Ebenaceae	2.45	4.13	1.77	8.35
9	Ixora arborea	Rubiaceae	2.67	3.75	1.32	7.74
10	Canthium travancoricum	Rubiaceae	2.92	3.00	1.78	7.70
11	Randia dumetorum	Rubiaceae	2.52	3.25	0.91	6.69
12	Dalbergia latifolia	Fabaceae	0.47	0.75	5.25	6.47
13	Atlantia monophylla	Rutaceae	2.67	2.63	0.92	6.21
14	Acacia leucophlea	Mimosaceae	0.62	0.63	4.35	5.60
15	Lantana camara	Verbenaceae	0.66	2.25	2.39	5.30
16	Diospyros melanoxylon	Ebenaceae	1.57	2.63	0.50	4.70
17	Ziziphus oenoplia	Rhamnaceae	1.94	2.38	0.38	4.70
18	Prosopis cineraria	Fabaceae	0.44	1.00	2.64	4.08
19	Albizia amara	Fabaceae	0.69	1.50	1.84	4.04
20	Stereospermum personatum	Bignoniaceae	0.55	1.50	1.42	3.47
21	Cassine glauca	Celastraceae	1.06	1.63	0.71	3.39
22	Cassia fistula	Caesalpinaceae	0.91	2.13	0.31	3.36
23	Premna tometosa	Verbenaceae	0.69	1.63	0.97	3.30
24	Phyllanthus indofischeri	Euphorbiaceae	0.69	1.63	0.95	3.28
25	Bambusa arundinacea	Poaceae	1.24	0.63	1.33	3.20
26	Grewia tiliifolia	Tiliaceae	0.99	1.75	0.39	3.12
27	Ferronia elephantum	Rutaceae	0.44	1.25	1.24	2.93
28	Bauhinia purpurea	Fabaceae	0.15	0.25	2.51	2.91
29	Albizia odoratissima	Fabaceae	0.15	0.50	2.21	2.86
30	Vitex altissima	Verbenaceae	0.55	1.38	0.88	2.80
31	Diospyros sp.	Ebenaceae	0.11	0.25	2.20	2.56
32	Morinda tinctoria	Rubiaceae	0.62	1.13	0.78	2.53
33	Canthium parviflorum	Rubiaceae	0.80	1.50	0.21	2.51
34	Maytenus emarginata	Celastraceae	0.80	1.38	0.29	2.47
35	Ziziphus xylopyrus	Rhamnaceae	0.84	1.25	0.36	2.45
36	Dolichandrone falcata	Bignoniaceae	1.06	0.88	0.15	2.08
37	Gmelina arborea	Verbenaceae	0.15	0.50	1.13	1.78
38	Aglaia odoratissima	Meliaceae	0.37	0.88	0.45	1.69
39	Dodonaea viscosa	Sapindaceae	0.69	0.88	0.10	1.67
40	Commiphora caudata	Burseraceae	0.26	0.63	0.77	1.65
41	Hardwickia binata	Caesalpinaceae	0.29	1.00	0.24	1.54
42	Pterocarpus marsupium	Fabaceae	0.18	0.63	0.70	1.51
43	Schleichera oleosa	Sapindaceae	0.04	0.13	1.30	1.47
44	Unid2	Unid	0.07	0.25	1.12	1.45
45	Garuga pinnata	Meliaceae	0.11	0.25	1.06	1.42
46	Terminalia paniculata	Combretaceae	0.33	0.63	0.42	1.37
47	Celtis tetrandra	Ulmaceae	0.11	0.25	0.99	1.35
48	Haldina cordifolia	Rubiaceae	0.11	0.38	0.81	1.30
49	Acacia sinuata	Mimosaceae	0.77	0.38	0.12	1.26
50	Flacourtia montana	Flacourtiaceae	0.22	0.25	0.63	1.10
51	Terminalia bellirica	Combretaceae	0.07	0.25	0.71	1.03
52	Ficus sp.	Moraceae	0.22	0.25	0.55	1.02
53	Terminalia chebula	Combretaceae	0.26	0.63	0.10	0.99
54	Gmelina asiatica	Verbenaceae	0.29	0.63	0.06	0.97
55	Boswellia serrata	Burseraceae	0.29	0.38	0.27	0.94
56	Pterolobium hexapetalum	Caesalpinaceae	0.26	0.63	0.05	0.93
57	Caralluma umbellata	Asclepiadaceae	0.37	0.38	0.18	0.92
58	Azadirachta india	Meliaceae	0.22	0.50	0.13	0.85
59	Capparis seperaria	Capparaceae	0.18	0.50	0.15	0.84
60	Acacia nilotica	Fabaceae	0.18	0.13	0.53	0.84
61	Ziziphus jujuba	Rhamnaceae	0.18	0.25	0.36	0.79
62	Cadaba fruticosa	Capparaceae	0.11	0.38	0.28	0.76
63	Santalum album	Santalaceae	0.22	0.50	0.03	0.75
64	Spondias pinnata	Anacardiaceae	0.04	0.13	0.59	0.75
65	Holarrhena antidycenterica	Apocynaceae	0.15	0.50	0.06	0.71
66	Butea monosperma	Fabaceae	0.11	0.38	0.21	0.70
67	Pongamia pinnata	Fabaceae	0.11	0.25	0.31	0.67
68	Acacia sp.	Mimosaceae	0.07	0.25	0.34	0.66
69	Dendrocalamas sp.	Poaceae	0.26	0.38	0.03	0.66
70	Flacourtia indica	Flacourtiaceae	0.22	0.38	0.03	0.63
71	Gardenia gammifera	Rubiaceae	0.11	0.38	0.12	0.60
72	Anacardium occidentale	Anacardiaceae	0.04	0.13	0.42	0.58
73	Strychnos sp.	Strychnaceae	0.26	0.25	0.07	0.58
74	Cleistanthus sp.	Phyllanthaceae	0.11	0.38	0.08	0.57
75	Wrightia tinctoria	Apocynaceae	0.11	0.38	0.07	0.55
76	Bridelia retusa	Euphorbiaceae	0.11	0.38	0.06	0.55
77	Terminalia crenulata	Combretaceae	0.07	0.13	0.22	0.41
78	Memecylon umbellatum	Melastomataceae	0.15	0.25	0.01	0.41
79	Bombax cieba	Bombacaceae	0.04	0.13	0.19	0.35
80	Tamarindus indiaca	Fabaceae	0.04	0.13	0.18	0.34
81	Carissa carandas	Apocynaceae	0.07	0.25	0.02	0.34
82	Celastrus paniculata	Celastraceae	0.07	0.25	0.01	0.33
83	Unid3	Unid	0.04	0.13	0.03	0.20
84	Erythrina variegata	Fabaceae	0.04	0.13	0.03	0.19
85	Unid1	Unid	0.04	0.13	0.01	0.18
86	Mallotus philippensis	Euphorbiaceae	0.04	0.13	0.01	0.18
87	Lagerstromia parviflora	Lythraceae	0.04	0.13	0.01	0.17
88	Grewia asiatica	Tiliaceae	0.04	0.13	0.01	0.17
89	Pyrenacantha volubilus	Icacinaceae	0.04	0.13	0.01	0.17
90	Chionanthus malabaricus	Olacaceae	0.04	0.13	0.00	0.17
91	Cocculus sp.	Menispermaceae	0.04	0.13	0.00	0.17
92	Syzygium cuminii	Myrtaceae	0.04	0.13	0.00	0.16
			100	100	100	300

Sl. no.	Botanical name	Family	Relative density	Relative frequency	IVI
1	Lantana camara	Verbenaceae	51.60	13.00	64.60
2	Pterolobium hexapetalum	Caesalpinaceae	5.87	7.33	13.20
3	Dodonia viscosa	Sapindaceae	6.58	5.33	11.92
4	Randia dumetorum	Rubiaceae	3.90	5.78	9.68
5	Chloroxylon swietenia	Rutaceae	3.09	6.44	9.54
6	Erythroxylon monogynum	Erythroxylaceae	2.07	5.56	7.63
7	Ziziphus oenoplia	Rhamnaceae	2.18	5.33	7.52
8	Fluggea leucopyrus	Phyllanthaceae	1.77	4.11	5.88
9	Eupatorium odoratum	Asteraceae	4.20	1.44	5.65
10	Dolichandrone falcata	Bignoniaceae	2.36	3.11	5.47
11	Pavetta indica	Rubiaceae	2.33	2.78	5.10
12	Toddalia asiatica	Rutaceae	1.36	3.00	4.36
13	Atlantia monophylla	Rutaceae	1.29	2.33	3.62
14	Acacia sinuata	Mimosaceae	1.32	2.22	3.55
15	Naringi crenulata	Rutaceae	1.32	2.11	3.43
16	Diospyros montana	Ebenaceae	0.59	2.67	3.26
17	Canthium travancoricum	Rubiaceae	0.73	2.00	2.73
18	Anogeissus latifolia	Combretaceae	0.70	1.56	2.25
19	Bambusa arundinacea	Poaceae	0.45	1.33	1.78
20	Ixora arborea	Rubiaceae	0.45	1.22	1.67
21	Flacourtia montana	Flacourtiaceae	0.50	1.11	1.61
22	Acacia chundra	Mimosaceae	0.36	1.22	1.58
23	Strychnos potatorum	Strychnaceae	0.39	1.11	1.50
24	Cassia fistula	Caesalpinaceae	0.25	1.22	1.47
25	Albizia amara	Fabaceae	0.27	1.11	1.38
26	Grewia tiliifolia	Tiliaceae	0.23	1.00	1.23
27	Santalum album	Santalaceae	0.21	0.89	1.10
28	Capparis seperaria	Capparaceae	0.25	0.78	1.03
29	Wrightia tinctoria	Apocynaceae	0.20	0.78	0.97
30	Grewia asiatica	Tiliaceae	0.25	0.67	0.92
31	Canthium parviflorum	Rubiaceae	0.23	0.67	0.90
32	Diospyros melanoxylon	Ebenaceae	0.16	0.67	0.83
33	Jasminum roxberghianum	Oleaceae	0.23	0.44	0.68
34	Cipadessa baccifera	Meliaceae	0.20	0.44	0.64
35	Maytenus emarginata	Celastraceae	0.13	0.44	0.57
36	Dalbergia lanceolaria	Fabaceae	0.09	0.44	0.53
37	Argyreia cuneata	Convolvulaceae	0.07	0.44	0.52
38	Memecylon umbellatum	Melastomataceae	0.14	0.33	0.48
39	Flacourtia indica	Flacourtiaceae	0.13	0.33	0.46
40	Ferronia elephantum	Rutaceae	0.07	0.33	0.40
41	Acacia leucophlea	Mimosaceae	0.05	0.33	0.39
42	Carissa carandas	Apocynaceae	0.05	0.33	0.39
43	Diospyros sp.	Ebenaceae	0.05	0.33	0.39
44	Premna tometosa	Verbenaceae	0.05	0.33	0.39
45	Stereospermum personatum	Bignoniaceae	0.05	0.33	0.39
46	Solanum torvum	Solanaceae	0.09	0.22	0.31
47	Azadirachta india	Meliaceae	0.05	0.22	0.28
48	Caralluma umbellata	Asclepiadaceae	0.05	0.22	0.28
49	Cassine glauca	Celastraceae	0.05	0.22	0.28
50	Maesa indica	Myrsinaceae	0.05	0.22	0.28
51	Prosopis cineraria	Fabaceae	0.05	0.22	0.28
52	Albizia odoratissima	Fabaceae	0.04	0.22	0.26
53	Celastrus paniculata	Celastraceae	0.04	0.22	0.26
54	Cycas sp.	Cycadaceae	0.04	0.22	0.26
55	Gardenia gammifera	Rubiaceae	0.04	0.22	0.26
56	Holarrhena antidycenterica	Apocynaceae	0.04	0.22	0.26
57	Jasminum sp.	Oleaceae	0.04	0.22	0.26
58	Opuntia elatior	Cactaceae	0.04	0.22	0.26
59	Phyllanthus emblica	Euphorbiaceae	0.04	0.22	0.26
60	Senna auriculata	Fabaceae	0.04	0.22	0.26
61	Tectona grandis	Verbenaceae	0.04	0.22	0.26
62	Vitex altissima	Verbenaceae	0.04	0.22	0.26
63	Barleria sp.	Acanthaceae	0.14	0.11	0.25
64	Phoenix loureirii	Arecaceae	0.11	0.11	0.22
65	Aglaia odoratissima	Meliaceae	0.02	0.11	0.13
66	Cocculus sp.	Menispermaceae	0.02	0.11	0.13
67	Decalepis hamiltonii	Apocynaceae	0.02	0.11	0.13
68	Dendrocalamas sp.	Poaceae	0.02	0.11	0.13
69	Givotia rottlerformis	Euphorbiaceae	0.02	0.11	0.13
70	Hardwickia binata	Caesalpinaceae	0.02	0.11	0.13
71	Jasminum angustifolium	Oleaceae	0.02	0.11	0.13
72	Lagerstromia parviflora	Lythraceae	0.02	0.11	0.13
73	Pyrenacantha volubilus	Icacinaceae	0.02	0.11	0.13
74	Ximenia americana	Olacaceae	0.02	0.11	0.13
75	Ziziphus xylopyrus	Rhamnaceae	0.02	0.11	0.13
			100	100	200

Sl. no.	Botanical name	Family	Relative density	Relative frequency	IVI
1	Leucas martinicensis	Lamiaceae	12.75	4.06	16.81
2	Oxalis corniculata	Oxalidaceae	8.41	3.99	12.40
3	Eupatorium odoratum	Asteraceae	6.96	4.03	11.00
4	Lantana camara	Verbenaceae	5.32	5.64	10.96
5	Evolvulus alsinoides	Convolvulaceae	3.15	2.52	5.68
6	Atylosia sp.	Fabaceae	2.05	2.54	4.59
7	Randia dumetorum	Rubiaceae	1.79	2.77	4.57
8	Justicia simplex	Acanthaceae	2.33	1.76	4.10
9	Crotalaria calycina	Fabaceae	2.14	1.83	3.98
10	Ziziphus oenoplia	Rhamnaceae	1.40	2.36	3.76
11	Sida acuta	Malvaceae	2.33	1.33	3.66
12	Ipomoea sp.	Convolvulaceae	1.46	2.06	3.52
13	Phyllanthus amarus	Euphorbiaceae	1.29	2.22	3.51
14	Atylosia lineata	Fabaceae	2.43	1.05	3.48
15	Urena lobata	Malvaceae	1.46	1.67	3.14
16	Anogeissus latifolia	Combretaceae	0.84	2.18	3.02
17	Desmodiastrum racemosum	Fabaceae	1.30	1.54	2.84
18	Jasmium angustifolium	Oleaceae	1.17	1.49	2.66
19	Barleria prionitis	Acanthaceae	1.39	1.24	2.63
20	Fluggea leucopyrus	Phyllanthaceae	0.75	1.83	2.59
21	Pterolobium hexapetalum	Caesalpinaceae	0.81	1.72	2.53
22	Cynotis arachnoidea	Commelinaceae	1.15	1.31	2.46
23	Triumfetta rhomboidea	Tiliaceae	1.27	1.08	2.35
24	Achyranthes aspera	Verbenaceae	1.23	1.08	2.30
25	Curculigo orchioides	Hypoxidaceae	0.76	1.49	2.25
26	Grewia asiatica	Tiliaceae	0.74	1.44	2.18
27	Jasminum roxberghianum	Oleaceae	0.93	1.17	2.10
28	Acacia chundra	Mimosaceae	0.61	1.47	2.08
29	Rhynchosia viscosa	Fabaceae	1.15	0.92	2.07
30	Euphorbia hirta	Euphorbiaceae	1.02	0.96	1.98
31	Ocimum americanum	Lamiaceae	0.96	0.96	1.93
32	Hemedesmus indicus	Apocynaceae	0.80	1.10	1.90
33	Gymnema sylvestre	Asclepiadaceae	0.97	0.87	1.84
34	Leucas aspera	Lamiaceae	1.21	0.60	1.80
35	Dolichandrone falcata	Bignoniaceae	0.69	1.08	1.77
36	Dodonia viscosa	Sapindaceae	0.56	1.19	1.75
37	Anaphalis subdecurrense	Asteraceae	0.58	1.10	1.68
38	Scilla sp.	Asparagaceae	0.60	1.08	1.68
39	Galactia tenuiflora	Fabaceae	0.86	0.80	1.66
40	Chloroxylon swietenia	Rutaceae	0.57	1.01	1.58
41	Senna auriculata	Fabaceae	0.79	0.71	1.50
42	Abutilon sp.	Malvaceae	0.74	0.76	1.49
43	Diospyros montana	Ebenaceae	0.43	1.03	1.46
44	Indigofera sp.	Fabaceae	0.99	0.46	1.45
45	Acacia sinuata	Mimosaceae	0.61	0.83	1.43
46	Senna occidenatlis	Fabaceae	0.75	0.66	1.41
47	Orthosiphon rubicundus	Lamiaceae	0.59	0.78	1.37
48	Toddalia asiatica	Rutaceae	0.41	0.94	1.35
49	Ixora arborea	Rubiaceae	0.41	0.94	1.35
50	Crepis sp.	Asteraceae	0.94	0.25	1.19
51	Barleria buxifolia	Acanthaceae	0.37	0.73	1.10
52	Stachytarpheta india	Verbenaceae	0.60	0.50	1.10
53	Asparagas gonocladus	Asparagaceae	0.27	0.78	1.05
54	Stenosiphonium russelianium	Acanthaceae	0.51	0.53	1.03
55	Bidens sp.	Asteraceae	0.43	0.60	1.03
56	Cissampelos pareira	Menispermaceae	0.34	0.66	1.00
57	Ageratum conyzoides	Asteraceae	0.71	0.25	0.96
58	Cynotis sp.	Commelinaceae	0.57	0.39	0.96
59	Erythroxylon monogynum	Erythroxylaceae	0.24	0.66	0.90
60	Prosopis cineraria	Fabaceae	0.31	0.55	0.86
61	Pavetta indica	Rubiaceae	0.25	0.60	0.84
62	Andrographis serpyllifolia	Acanthaceae	0.35	0.46	0.80
63	Atlantia monophylla	Rutaceae	0.29	0.50	0.79
64	Dalbergia lanceolaria	Fabaceae	0.27	0.50	0.78
65	Hyptis suaveolens	Lamiaceae	0.51	0.25	0.76
66	Mimosa pudica	Mimosaceae	0.41	0.34	0.76
67	Sida rhombifolia	Malvaceae	0.31	0.41	0.72
68	Dalbergia latifolia	Fabaceae	0.24	0.48	0.72
69	Maytenus emarginata	Celastraceae	0.26	0.46	0.72
70	Senna sp.	Fabaceae	0.39	0.25	0.64
71	Pteridium sp.	Dennstaedtiaceae	0.56	0.07	0.63
72	Albizia amara	Fabaceae	0.16	0.46	0.62
73	Bidens barbidens	Asteraceae	0.27	0.30	0.57
74	Indigofera tinctoria	Fabaceae	0.19	0.37	0.56
75	Parthenium hysterophorus	Asteraceae	0.22	0.30	0.52
76	Canthium parviflorum	Rubiaceae	0.15	0.34	0.50
77	Artemisia pallens	Asteraceae	0.26	0.23	0.49
78	Albizia odoratissima	Fabaceae	0.15	0.30	0.45
79	Croton sp.	Euphorbiaceae	0.10	0.34	0.44
80	Leucas sp.	Lamiaceae	0.23	0.21	0.44
81	Cipadessa baccifera	Meliaceae	0.18	0.25	0.43
82	Eradale gida*	Fabaceae	0.24	0.18	0.43
83	Mimosa sp.	Mimosaceae	0.20	0.23	0.43
84	Naringi crenulata	Rutaceae	0.10	0.32	0.42
85	Strobilanthes callosa	Acanthaceae	0.27	0.11	0.39
86	Malva sp.	Malvaceae	0.20	0.18	0.38
87	Phyllanthus indofischeri	Euphorbiaceae	0.12	0.25	0.38
88	Solanum torvum	Solanaceae	0.14	0.21	0.35
89	Theriophonum sp.	Araceae	0.15	0.18	0.33
90	Cocculus sp.	Menispermaceae	0.10	0.23	0.33
91	Azima tetracantha	Salvadoraceae	0.07	0.23	0.30
92	Strychnos potatorum	Strychnaceae	0.09	0.21	0.30
93	Ocimum sp.	Lamiaceae	0.25	0.05	0.30
94	Stylosanthus sp.	Fabaceae	0.11	0.18	0.29
95	Pogostemon sp.	Lamiaceae	0.08	0.21	0.29
96	Abutilon hirtum	Malvaceae	0.15	0.14	0.29
97	Strychnos sp.	Strychnaceae	0.06	0.23	0.29
98	Cynanchum tunicatum	Asclepiadaceae	0.08	0.21	0.28
99	Jasminum sp.	Oleaceae	0.13	0.14	0.27
100	Pyrenacantha volubilus	Icacinaceae	0.12	0.14	0.26
101	Crotalaria sp.	Fabaceae	0.11	0.14	0.25
102	Ziziphus xylopyrus	Rhamnaceae	0.06	0.18	0.25
103	Santalum album	Santalaceae	0.09	0.14	0.23
104	Flacourtia montana	Flacourtiaceae	0.07	0.16	0.23
105	Lantana indica	Verbenaceae	0.06	0.16	0.22
106	Diospyros melanoxylon	Ebenaceae	0.06	0.16	0.22
107	Sida sp.	Malvaceae	0.09	0.11	0.20
108	Ferronia yesphantum	Rutaceae	0.06	0.14	0.19
109	Dioscorea oppositifolia	Dioscoreaceae	0.05	0.14	0.19
110	Sansevieria trifasciata	Asparagaceae	0.07	0.11	0.19
111	Ceropegia sp.	Apocynaceae	0.06	0.11	0.17
112	Thotti*	Unidentified	0.08	0.09	0.17
113	Helicteres isora	Malvaceae	0.04	0.11	0.15
114	Pterocarpus marsupium	Fabaceae	0.04	0.11	0.15
115	Plectranthus amboinicus	Lamiaceae	0.10	0.05	0.15
116	Barleria sp.	Acanthaceae	0.06	0.09	0.15
117	Hardwickia binata	Fabaceae	0.03	0.11	0.15
118	Maesa indica	Myrsinaceae	0.05	0.09	0.14
119	Asaparagus racemosus	Asparagaceae	0.03	0.11	0.14
120	Mallotus philippensis	Euphorbiaceae	0.03	0.11	0.14
121	Stereospermum personatum	Bignoniaceae	0.03	0.11	0.14
122	Rauvolfia serpentina	Apocynaceae	0.09	0.05	0.14
123	Bambusa arundinacea	Poaceae	0.05	0.09	0.14
124	Ocimum tenuiflorum	Lamiaceae	0.05	0.09	0.14
125	Schleichera oleosa	Sapindaceae	0.04	0.09	0.13
126	Nela bhuthale*	Unidentified	0.08	0.05	0.13
127	Cryptolepis buchnani	Asclepiadaceae	0.04	0.09	0.13
128	Memecylon umbellatum	Melastomataceae	0.03	0.09	0.12
129	Nicandra physalodes	Solanaceae	0.05	0.07	0.12
130	Padavara baale*	Unidentified	0.03	0.09	0.12
131	Cassia fistula	Caesalpinaceae	0.02	0.09	0.11
132	Wrightia tinctoria	Apocynaceae	0.02	0.09	0.11
133	Celastrus paniculata	Celastraceae	0.05	0.05	0.10
134	Canthium travancoricum	Rubiaceae	0.02	0.07	0.09
135	Diospyros sp.	Ebenaceae	0.02	0.07	0.09
136	Argyreia cuneata	Convolvulaceae	0.02	0.07	0.08
137	Breynia retusa	Euphorbiaceae	0.02	0.07	0.08
138	Dioscorea sp.	Dioscoreaceae	0.02	0.07	0.08
139	Flacourtia indica	Flacourtiaceae	0.02	0.07	0.08
140	Gardenia gammifera	Rubiaceae	0.02	0.07	0.08
141	Actiniopteris radiata	Pteridaceae	0.03	0.05	0.07
142	Tephrosia sp.	Fabaceae	0.03	0.05	0.07
143	Vitex altissima	Verbenaceae	0.03	0.05	0.07
144	Caralluma umbellata	Asclepiadaceae	0.02	0.05	0.07
145	Cleistanthus sp.	Phyllanthaceae	0.02	0.05	0.06
146	Coccinia grandis	Cucurbitaceae	0.02	0.05	0.06
147	Elaeagnus conferta	Elaeagnaceae	0.02	0.05	0.06
148	Holarrhena antidycenterica	Apocynaceae	0.02	0.05	0.06
149	Phyllanthus virgatus	Euphorbiaceae	0.02	0.05	0.06
150	Acacia sp.	Mimosaceae	0.01	0.05	0.06
151	Argyreia cymosa	Convolvulaceae	0.01	0.05	0.06
152	Azadirachta india	Meliaceae	0.01	0.05	0.06
153	Millettia racemosa	Fabaceae	0.01	0.05	0.06
154	Odavara*	Unidentified	0.01	0.05	0.06
155	Terminalia bellirica	Combretaceae	0.01	0.05	0.06
156	Terminalia crenulata	Combretaceae	0.01	0.05	0.06
157	Nada kappali*	Unidentified	0.03	0.02	0.05
158	Carissa carandas	apocynaceae	0.02	0.02	0.04
159	Celtis tetrandra	Ulmaceae	0.02	0.02	0.04
160	Gmelina arborea	Verbenaceae	0.02	0.02	0.04
161	Acanthus sp.	Acanthaceae	0.01	0.02	0.03
162	Arda chandra*	Unidentified	0.01	0.02	0.03
163	Eucalyptus globulus	Myrtaceae	0.01	0.02	0.03
164	Physalis minima	Solanaceae	0.01	0.02	0.03
165	Ximenia americana	Olacaceae	0.01	0.02	0.03
166	Antu huruligida*	Unidentified	0.01	0.02	0.03
167	Antu pulle*	Unidentified	0.01	0.02	0.03
168	Bombax cieba	Bombacaceae	0.01	0.02	0.03
169	Canthium sp.	Rubiaceae	0.01	0.02	0.03
170	Casearia tomentosa	Salicaceae	0.01	0.02	0.03
171	Cassine glauca	Celastraceae	0.01	0.02	0.03
172	Dendrocalamas sp.	Poaceae	0.01	0.02	0.03
173	Gloriosa superba	Colchicaceae	0.01	0.02	0.03
174	Hambu bhuthale*	Unidentified	0.01	0.02	0.03
175	Hittina kudi*	Unidentified	0.01	0.02	0.03
176	Huriyana hambu*	Unidentified	0.01	0.02	0.03
177	Lamium sp.	Lamiaceae	0.01	0.02	0.03
178	Maathadakana hambu*	Unidentified	0.01	0.02	0.03
179	Morinda tinctoria	Rubiaceae	0.01	0.02	0.03
180	Nela gorava*	Unidentified	0.01	0.02	0.03
181	Premna tometosa	Verbenaceae	0.01	0.02	0.03
182	Sanna javana*	Lamiaceae	0.01	0.02	0.03
183	Syzygium cuminii	Myrtaceae	0.01	0.02	0.03
184	Tectona grandis	Verbenaceae	0.01	0.02	0.03
185	Ziziphus jujuba	Rhamnaceae	0.01	0.02	0.03
			100	100	200

Note: The botanical names of the * marked plant species were unidentified, instead the Soliga vernacular names were given.