Nesting tree preference of IGS in the Mudumalai Tiger Reserve.
Abstract
The present study was carried out on the nesting behavior of IGS in the Mudumalai Tiger Reserve during the month of June 2015 to June 2017 (2 years). A total of 192 nesting trees with 279 nests belong to 19 tree species were identified as nesting trees preferences of IGS. Of which Bambusa arundinacea grass species was the dominant nesting grass species of the IGS in Mudumalai Tiger Reserve (11%, n = 22). The overall nest height of the IGS was 19.70 m and a maximum height of 34 m and a minimum height of 8 m. The nest direction shows that the North East held the number of the nest (n = 137), and the nest position shows that the Crown (n = 197) contained the number of the nest. The nest position shows that top (n = 220) were contained the number of nests compared to the middle (n = 59). On the other hand, no nest was placed on the down position.
Keywords
- Indian giant squirrel
- Mudumalai Tiger Reserve
- nesting
- Western Ghats
1. Introduction
The Indian or Malabar giant squirrel (
2. Study area
Mudumalai Tiger Reserve is one of the few areas in the country with a rich and varied terrain, flora and fauna. Mudumalai plays an important role in biodiversity conservation of especially large mammals, by offering habitat contiguity of about 3300 km2 with three other protected areas in the region, namely Nagarahole and Bandipur National Park and Wayanad Wildlife Sanctuary through forest corridors between the Western Ghats and the Eastern Ghats. The reserve was created in 1940, the first in southern India, with an area of 60 km2. In 1956, it was enlarged to 295 km2 and later to a further 321 km2 and 688.59km2 core zone = 321 km2 and buffer zone = 367.59 km2 which it is present extent ( Figure 1 ). Champion and Seth [13] classified the vegetation type in Mudumalai as Southern Tropical dry thorn forest, Southern Tropical dry deciduous forest, Southern Tropical moist deciduous forest, Southern Tropical semi-evergreen, Moist bamboo brakes, and Riparian fringing forest.
3. Methodology
3.1 Data collection
Data were collected from June 2015 to June 2017 mostly on breeding seasons when the squirrels are more active and easily seen. We searched for animals and their nests along the natural trails in the dry thorn forest. Most of the nesting trees were located through intensive searches in the area by inspecting potential nesting trees and nests. The presence of IGS and their activity provide indirect evidence of use as nest trees. The IGS nesting trees were marked with GPS coordinates and classified with identification. The quantification of nesting habitat followed methods suggested by James and Shugart [14] and subsequently by Kannan [15], Mudappa and Kannan [16], and Girikaran et al. [17]. Vegetation and nest tree parameter was quantified in circular plots of 15 m (0.07 ha) with the nest tree as the center. All the trees (GBH > 25 cm) were enumerated and GBH (Girth at Brest Height) measured. Canopy cover was visually estimated. The elevation of the nesting tree distances to the nearest road, habitation was also noted. The nest tree parameters were measured such as tree height, basal area, diameter at breast height, number of primary branches and secondary, canopy cover, canopy height, canopy width and tree status such as (dead or alive) were noted. Such parameters were also quantified in similar-sized plots located 100 m in a random direction from the nest tree, where the nearest tree of GBH > 250 cm was chosen as the centre tree and the same nest tree parameters were also taken into the account for comparison of random (non-nest) plots with nest tree plots were made to determine parameters likely to affects choice of nesting habitat by Indian Giant Squirrel. The availability and density of potential nest tree species were assessed from 16 0.25 ha (50 m × 50 m) vegetation plots (2.5 ha).
3.2 Statistical treatment
Mean (M) and Standard Error (SE) was calculated to the nesting trees variables in the study area. Pearson’s correlation coefficient matrix was performed to understand the variables significances among the nesting trees. Man Whitney U test was used to determine differences in 13 parameters between nest (n = 158) and non-nest (n = 250) plots. Principal Component Analysis was used to understand nest site selection. Statistical analyses were performed using
4. Result
A total of 192 nesting trees with 279 nests belonging to 19 trees species were identified as nesting trees preferences of IGS in the Mudumalai Tiger Reserve (
Table 1
). Of which
S.No | Scientific name of the nesting trees | Number of nesting trees | Relative abundances of the nesting trees % | Number of nests | Relative Abundances of the nest in nesting trees % |
---|---|---|---|---|---|
1 |
|
22 | 11 | 56 | 20 |
2 |
|
20 | 10 | 28 | 10 |
3 |
|
18 | 9 | 26 | 9 |
4 |
|
14 | 7 | 22 | 8 |
5 |
|
12 | 6 | 16 | 6 |
6 |
|
12 | 6 | 14 | 5 |
7 |
|
12 | 6 | 12 | 4 |
8 |
|
10 | 5 | 12 | 4 |
9 |
|
10 | 5 | 10 | 4 |
10 |
|
8 | 4 | 8 | 3 |
11 |
|
8 | 4 | 8 | 3 |
12 |
|
8 | 4 | 14 | 5 |
13 |
|
7 | 4 | 7 | 3 |
14 |
|
7 | 4 | 10 | 4 |
15 |
|
6 | 3 | 12 | 4 |
16 |
|
6 | 3 | 8 | 3 |
17 |
|
5 | 3 | 7 | 3 |
18 |
|
4 | 2 | 6 | 2 |
19 |
|
3 | 2 | 3 | 1 |
Total | 192 | 279 |
Fourteen variables of nest tree and centre tree of non-nest sites were measured and are given above ( Table 2 ). Nest trees differed significantly from centre trees of non-nest plots, in terms of size. The height of the tree, basal area, GBH, Branch end, secondary branches, canopy length, canopy cover, and elevation were all significantly greater in nest trees than non-nest centre trees ( Table 2 ). But there was no significant difference in, Branch start, branch start, and branch end distance, Primary branches, canopy width, Distance to human habitation and distances to the road between nest plot and centre trees of non-nest plots. However, there was a significant difference in large tree density (GBH ≥ 25 cm, GBH ≥ 26–75 cm, GBH ≥ 126–175 cm and GBH ≥ 326–375 cm) between the nest and non-nest plots ( Table 2 ).
Variables | Nest plot (n = 192) | Non-nest plot (n = 250) |
|
|
---|---|---|---|---|
Nest/centre tree height (m) | 25.63 ± 0.68 | 21.48 ± 0.47 | 2750 | 0.40* |
Nest/centre tree basal Area (cm) | 423.56 ± 19.28 | 389.35 ± 14.78 | 2125 | 0.03* |
Nest/centre tree girth at breast height (cm) | 397.32 ± 17.25 | 358.46 ± 16.25 | 2091 | 0.00* |
Nest/centre tree branch start (m) | 7.35 ± 0.29 | 5.46 ± 0.37 | 2093 | 0.12 |
Nest/centre tree branch end (m) | 23.35 ± 0.46 | 19.27 ± 0.49 | 2782 | 0.05* |
Nest/centre tree branch start and branch end distance (m) | 9.18 ± 0.37 | 10.23 ± 0.29 | 3272 | 0.77 |
Nest/centre tree primary branches | 3.68 ± 0.19 | 5.16 ± 0.13 | 2951 | 0.17 |
Nest/centre tree Secondary branches | 42.37 ± 1.27 | 44.19 ± 0.78 | 2901 | 0.03* |
Nest/Centre tree Canopy length (m) | 27.53 ± 0.68 | 28.32 ± 0.83 | 2466 | 0.00* |
Nest/Centre tree canopy width (m) | 28.34.88 ± 0.75 | 29.56 ± 0.43 | 2992 | 0.22 |
Nest/Centre tree canopy cover (%) | 78.32 ± 2.35 | 82.34 ± 1.36 | 3078 | 0.05* |
Nest/centre tree Distance to human habitation (km) | 10.36 ± 1.26 | 11.12 ± 0.18 | 3298 | 0.54 |
Nest/centre tree Distance to road (km) | 9.09 ± 0.35 | 8.63 ± 0.52 | 3259 | 0.37 |
Nest/centre tree elevation (m) | 893.68 ± 19.84 | 887.37 ± 17.39 | 4235 | 0.02* |
Tree density/ha | ||||
i. Trees of GBH ≥ 25 cm | 28.35 ± 0.54 | 26.53 ± 0.69 | 2833 | 0.05* |
ii. Trees of GBH ≥ 26–75 cm | 5.17 ± 0.16 | 4.52 ± 0.32 | 2496 | 0.00* |
iii. Trees of GBH ≥ 76–125 cm | 3.36 ± 0.17 | 3.85 ± 0.19 | 3612 | 0.35 |
iv. Trees of GBH ≥ 126- 175 cm | 3.13 ± 0.29 | 2.98 ± 0.93 | 2843 | 0.04* |
v. Trees of GBH ≥ 176–225 cm | 2.38 ± 0.59 | 1.87 ± 0.53 | 3036 | 0.16 |
vi. Trees of GBH ≥ 226–275 cm | 1.25 ± 0.17 | 1.89 ± 0.23 | 3314 | 0.65 |
vii. Trees of GBH ≥ 276- 325 cm | 1.35 ± 0.29 | 1.59 ± 0.12 | 3194 | 0.37 |
viii. Trees of GBH ≥ 325 cm | 1.13 ± 0.75 | 1.38 ± 0.74 | 2841 | 0.03* |
ix. Trees of GBH ≥ 376–425+ cm | 0.52 ± 0.46 | 0.75 ± 0.49 | 3217 | 0.04* |
The principal component analysis (PCA) was carried out using the nest site characteristics data from all the nests of IGS observed (n = 158). Table 3 shows Pearson’s correlation matrix between the 14 variables.
H | BA | DBH | BS | BE | BSBED | PB | SB | CL | CW | CC | DHH | DR | ELEV | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
1.000 | |||||||||||||
|
−0.241 | 1.000 | ||||||||||||
|
0.014 | 0.901* | 1.000 | |||||||||||
|
0.866* | −0.269 | 0.019 | 1.000 | ||||||||||
|
0.992* | −0.272 | 0.000 | 0.884* | 1.000 | |||||||||
|
0.876* | −0.177 | 0.019 | 0.546* | 0.862* | 1.000 | ||||||||
|
0.012 | 0.692* | 0.635* | −0.239 | −0.047 | 0.207 | 1.000 | |||||||
|
−0.029 | 0.700* | 0.593* | −0.044 | −0.087 | −0.050 | 0.570* | 1.000 | ||||||
|
−0.053 | 0.785* | 0.738* | −0.318 | −0.126 | 0.151 | 0.886* | 0.612* | 1.000 | |||||
|
0.862* | −0.123 | 0.025 | 0.501 | 0.825* | 0.971* | 0.292 | 0.056 | 0.256 | 1.000 | ||||
|
−0.551** | 0.292 | 0.117 | −0.341 | −0.518 | −0.484** | −0.141 | 0.256 | −0.119 | −0.575** | 1.000 | |||
|
0.488* | 0.245 | 0.376 | 0.441 | 0.469* | 0.511* | 0.136 | 0.405 | 0.187 | 0.476 | 0.691* | 1.000 | ||
|
0.602* | 0.369 | 0.436 | 0.481* | 0.564* | 0.596* | 0.269 | 0.539* | 0.360 | 0.623* | 0.056 | 0.842* | 1.000 | |
|
0.224 | −0.052 | −0.054 | 0.154 | 0.176 | 0.200 | −0.153 | 0.177 | 0.114 | 0.224 | −0.114 | 0.216 | 0.254 | 1 |
PCA extracted three principal components that elucidated 87.12% variability ( Table 4 ). The first component explained 39.02% variability that gives details of seven nest tree variables such as tree height, Branch Start, Branch End, Branch Start and Branch End Distance, Canopy Width, Distance to human habitation and Distance to Road in the plot and that were positively correlated with the first component. High values on the first component corresponding to the tallness of nest trees, Branch Start, Branch End, Branch Start and Branch End Distance, Canopy Width. Thus, the first component represents, with increasing values, the size of the nest tree and tallness will also increase. The first component was also positively correlated to Distance to human habitation and Distance to Road variable, which indicates, with increasing values, greater distance to human habitation and roads. The second component explained 29.07% variability that explained five nest tree variables such as basal area, GBH, Primary Branch, Secondary Branch and Canopy Length ( Table 4 ). High values on the second component correspond to a basal area GBH, Primary Branch, Secondary Branch and Canopy Length. Thus, the second component also represents, with increasing values, the size of the nest tree and basal area and branch structure of the tree will also increase. The third component explained 11.68% of the total variance and was related to Canopy cover and human habitation. The fourth component explains 7.35% of the total variance and was related to Canopy cover and Elevation ( Table 4 ).
Variables | Communality | PC1 | PC2 | PC3 | PC4 | ||||
---|---|---|---|---|---|---|---|---|---|
r | c | r | c | r | c | r | c | ||
Height | 0.978 | 0.895* | 0.153 | −0.408 | −0.094 | −0.074 | −0.042 | 0.076 | 0.069 |
BA | 0.923 | 0.134 | 0.023 | 0.947* | 0.217 | −0.006 | −0.004 | 0.087 | 0.079 |
GBH | 0.794 | 0.323 | 0.055 | 0.798* | 0.183 | −0.060 | −0.034 | 0.224 | 0.203 |
Branch Start | 0.792 | 0.700* | 0.120 | −0.452 | −0.104 | 0.235 | 0.134 | 0.208 | 0.188 |
Branch End | 0.968 | 0.860* | 0.147 | −0.454 | −0.104 | −0.053 | −0.030 | 0.142 | 0.129 |
Branch Start and Branch End Distance | 0.884 | 0.852* | 0.146 | −0.285 | −0.065 | −0.270 | −0.154 | 0.063 | 0.057 |
Primary Branch | 0.916 | 0.292 | 0.050 | 0.722* | 0.166 | −0.553 | −0.316 | 0.056 | 0.050 |
Secondary Branch | 0.784 | 0.328 | 0.056 | 0.776* | 0.178 | 0.242 | 0.138 | −0.129 | −0.117 |
Canopy Length | 0.965 | 0.303 | 0.052 | 0.813* | 0.187 | −0.424 | −0.242 | −0.178 | −0.162 |
Canopy Width | 0.918 | 0.876* | 0.150 | −0.211 | −0.048 | −0.323 | −0.184 | −0.053 | −0.048 |
Canopy Cover | 0.815 | −0.409 | −0.070 | 0.373 | 0.085 | 0.639* | 0.365 | 0.618* | 0.288 |
Distance to Human habitation | 0.801 | 0.714* | 0.122 | 0.205 | 0.047 | 0.459* | 0.256 | 0.219 | 0.198 |
Distance to Road | 0.918 | 0.845* | 0.144 | 0.287 | 0.066 | 0.331 | 0.189 | 0.106 | 0.096 |
Elevation | 0.855 | 0.316 | 0.054 | −0.039 | −0.009 | 0.309 | 0.176 | 0.812* | 0.736 |
Eigen value | 5.85 | 4.36 | 1.75 | 1.10 | |||||
% Variance explained | 39.02 | 29.07 | 11.68 | 7.35 | |||||
% Cumulative explained | 39.02 | 68.10 | 79.77 | 87.12 |
A total of 24 potential nest tree species of IGS that occurred at the study area was identified based tree genera or species those that generally attain a large tree size (
Table 5
). Of these only 19 species were used for nesting by IGS in the Mudumalai Tiger Reserve. All of these trees were emergent, large girth trees and are relatively more common than other species; in fact,
S.No | Scientific name | Height (m) | DBH | Overall tree density/ha | Tree density/ha (GBH ≥ 250 cm) |
---|---|---|---|---|---|
1 |
|
8–26 | 96.57 | 1.2 | 0 |
2 |
|
5–28 | 93.44 | 8.91 | 0.26 |
3 |
|
6– | 75.1 | 2.06 | 0 |
4 |
|
7–28 | 191.8 | 2.33 | 0.73 |
5 |
|
8–18 | 114.52 | 3.46 | 0 |
6 |
|
8–25 | 228.61 | 2.46 | 0.93 |
7 |
|
4–28 | 175.75 | 1.40 | 0.47 |
8 |
|
2–34 | 188.64 | 29.3 | 10.4 |
9 |
|
6–26 | 107.36 | 0.80 | 0.17 |
10 |
|
9–24 | 296.15 | 1.86 | 0.53 |
11 |
|
4–21 | 94.66 | 2.86 | 0.06 |
12 |
|
11–26 | 120.71 | 0.53 | 0.06 |
13 |
|
8–20 | 134.17 | 1.13 | 0.13 |
14 |
|
7–28 | 150.73 | 4.40 | 0.6 |
15 |
|
8–16 | 96.5 | 0.86 | 0 |
16 |
|
8–18 | 92.56 | 1.13 | 0.13 |
17 |
|
8–23 | 215.23 | 0.45 | 0.12 |
18 |
|
5–18 | 136.21 | 5.89 | 0.03 |
19 |
|
4–15 | 142.27 | 0.26 | 0 |
20 |
|
6–16 | 112.65 | 0.58 | 0 |
21 |
|
10–23 | 286.12 | 0.34 | 0.05 |
22 |
|
8–22 | 254.85 | 0.19 | 0.06 |
23 |
|
5–13 | 116.57 | 0.68 | 0 |
24 |
|
6–12 | 154.36 | 0.75 | 0.02 |
5. Discussion
Preference for nesting trees could depend on factors such as access to nesting material and food, nest safety and the branching pattern of the tree species. A total of 18 tree species and one grass species were recognized as nesting trees of IGS in the Mudumalai Tiger Reserve. Of which
A total of 192 nesting trees harboring 279 nests in an average of 2.66 nesting trees per km and 3.87 nests/km in a 72 km transect. In the previous study stated that a total of 83 nests were located along 54.2 km transects, giving an encounter rate of 1.5 nests/km of transects [12]. Previously the number of nests was reported in the moist deciduous forest [18] but in this study, I recorded the high number of nests in dry thorn forest riverine patches, it’s evident that riverine patches afford good habitat for IGS in the environment. The assortment of nesting sites in most of the arboreal animal communities was seen in the riparian ecosystem, since of the diversity of plant species and tallness of the trees establish in these kinds of habitats and also accessibility of water for thermoregulation and humidity the stage of the enormous role for assortment of this habitat [19].
The nesting tree characters shows that the average height of the nesting tree and DBH and Trunk size and canopy had a very good percentage. Among the 19 nesting trees
The canopy length and width, as well as branch start and branch end, was very good in
This study found that a single tree holds a maximum five numbers of nest and minimum one nest and the average height of the nesting trees was 24.4 m. There were more than one or two nests in a single tree [18]. The tree species with multiple numbers of nests were
6. Conclusion
Mudumalai Tiger Reserve faces severe pressure from the collection of non–timber forest products (NTFP) collection. Fruits of
References
- 1.
Corbet GB, Hill J. The Mammals of the Indo Malayan Region. Natural History Museum Publications, Oxford University Press Oxford, England, 1992. p. 488 - 2.
Molur S, Srinivasalu B, Srinivasalu C, Walker S, Nameer PO, Ravi KL. Status of South Asian Non–volant Small Mammals: Conservation Assessment and Management Plan (C. A. M. P.) Workshop Report. South Asia, Coimbatore, India: Zoo Outreach Organisation/ CBSG; 2005 - 3.
Molur S. Ratufa indica . The IUCN Red List of Threatened Species 2016: e.T19378A22262028. DOI: 10.2305/IUCN.UK.2016-2.RLTS.T19378A22262028.en [Accessed: 01 May 2020] - 4.
Favre DS. International Trade in Endangered Species Guide to CITES. London: Martines Nijhoff Publishers; 1989 - 5.
Prater SH. The Book of Indian Animals. Mumbai: Bombay Natural History Society and Oxford University Press; 1971. p. 197 - 6.
Hayssen V. Patterns of body and tail length and body mass in sciuridae. Journal of Mammalogy. 2008; 89 (4):852-873 - 7.
Borges R, Mali R, Somanathan H. The status, ecology and conservation of the Malabar Giant Squirrel Ratufa indica . Final report, Wildlife Institute of India. Indo-US Project; 1998 - 8.
Ramachandran KK. Certain aspects of ecology and behaviour of Malabar Giant Squirrel Ratufa indica (Schreber) [PhD Thesis]. Department of Zoology, University of Kerala; 1992 - 9.
Payne JB. Abundance of diurnal squirrels at the Kuala Lompat post of the Krau Game Reserve, Peninsular Malaysia. In: Marshall AG, editor. Abundance of Animals in Malaysian Rain Forests. United Kingdom: Department of Geography, University of Hull; 1979. pp. 37-51 - 10.
Pradhan AK, Shrotriya S, Rout SD. Observation on Nest- site selection by Indian giant squirrel in Karlapat Wildlife Sanctuary, Odish. Small Mammal. 2012; 4 (2):12-13 - 11.
Pradhan AK, Shrotriya S, Rout SD, Dash PK. Nesting and feeding habits of the Indian giant squirrel ( Ratufa indica ) in Karlapat wildlife sanctuary, India. Animal Biodiversity and Conservation. 2017;40 (1):63-69 - 12.
Baskaran N, Venkatesan S, Mani J, Srivastava SK, Ajay DA. Some aspects of the ecology of Indian giant squirrel ( Ratufa indica Erxleben, 1777) in the tropical forests of Mudumalai Wildlife Sanctuary, southern India and their conservation implications. Journal of Threatened Taxa. 2011;3 (7):1899-1908 - 13.
Champion HG, Seth SK. A Revised, Survey of the Forest Types of India. New Delhi: Govt. of India Press; 1968. p. 404 - 14.
James EC, Shugart HH Jr. A quantitative method of habitat description. Audubon Field Notes. 1970; 241 :727-736 - 15.
Kannan R. Ecology and conservation of the Great Pied Hornbill ( Buceros bicornis ) in the Western Ghats of Southern India [PhD Thesis]. USA: University of Arkansas; 1994 - 16.
Mudappa D, Kannan R. Nest site characteristics and nesting success of Malabar Grey hornbill in southern Western Ghats, India. Wilson Bulletien. 1997; 109 (1):102-111 - 17.
Girikaran P, Samson A, Ramakrishnan B, Ramasubramanian S. Nesting tree preference of Malabar pied hornbill ( Anthracoceros coronatus ) in pillur valley, Western Ghats, Southern India. Nature Conservation Research. 2019;4 (3):45-53 - 18.
Srinivas V, Venugopal PD, Ram S. Site occupancy of the Indian giant squirrel Ratufa indica (Erxleben) in Kalakad Mundanthurai Tiger Reserve, Tamil Nadu, India. Current Science. 2008;95 (7):889-894 - 19.
Archana M. Watershed Management. New Delhi: Author Press; 2001. p. 200 - 20.
Datta A, Goyal SP. Comparison of forest structure and use by the Indian giant squirrel ( Ratufa indica ) in two riverine forests of Central India. Biotropica. 1996;28 (3):394-399 - 21.
Prakash S, Mishra AK, Raziuddin M. Studies on the nesting habits of Indian giant squirrel Ratufa indica centralis riley 1913 in Dalma Wildlife Sanctuary, Jharkhand, India. Journal of Life Science. 2011;12 (12):9-18 - 22.
Kumara HN, Singh M. Distribution and relative abundance of giant squirrels and flying squirrels in Karnatak, India. Mammalia. 2009; 70 :40-47 - 23.
Kanoje RS. Nesting sites of Indian giant squirrels in Sitanadi wildlife sanctuary, India. Current Science (Bangalore). 2008; 7 :882-884 - 24.
Nayak BK, Patra AK. Feeding and nesting ecology of Indian giant squirrel Ratufa indica (Erxleben, 1777) In Kuldiha wildlife sanctuary, Balasore, Odisha, India and its conservation. International Journal of Bioassays. 2015;4 (03):3741-3746