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5. Results

5.1 Analysis of socio-economic status, land and resource use pattern of households in

Similipal forest

5.1.1 Demographic and socio-economic profile of the villages

There were total of 1418 households in the 30 study villages. The total population size was

8212 of which 3827 (53%) were men and 2161 (47%) women. The average family size varied

between 3.1-11.2 persons per household with the lowest in village Nawana and highest in

village Benipur (Table 4). The sex ratio (females/thousand males) ranged between 189-1214,

with the lowest in village Bhudabalanga and highest in Langighasara (Table 4). This

difference can be attributed to lack of employment, which has led to migration of the men to

other areas in search of jobs.

The landholdings of the 30 villages were 545.9 ha. Occupation wise, majority of the house-

hold were cultivators with the highest number of cultivators in Gurguria and lowest in

Yamunagard (Table 4). Makabadi had the highest land under the cultivation with 28.4 ha and

Balarampur comes next with 26.3 ha (Table 4). Among the crop being cultivated, paddy was

the major crop in this area and other corps was vegetables and spices.

Out of the total household of the villages, 143 (10%) households were selected for detailed

study from 2007 to 2008. The average household size ranged from 3 to 22 (Table 4).

5.1.2 Age and gender of the respondents

The survey was carried out by dividing the respondents into three age categories: young 20-

39, middle aged 40-59 and elderly 60+. A total of 143 people were surveyed. Out of 143

respondents of the survey, 91 were male and 52 were female. Most of the respondents were

between 20-40 yrs (Table 5). The oldest respondent was aged 86.



R e s u l t s | 34

Table 4: Demographic and occupational characteristics of study villages.

Villages Location

(Buffer/

Core/

Periphery)

Total

house-

holds

Total

population

Average

family

size

Male Female Sex ratio

(females

per

thousandmales)

Culti-

vators

Culti-

vated

area

(hectare)

Asanbani Buffer 34 156 4.6 88 68 773 87 9.3 Astakumar Buffer 50 551 11 277 274 989 154 18.6

Badega Buffer 18 188 10.4 91 97 1066 54 21.9

Bakua Core 41 259 6.3 122 137 1123 36 6.9

Balarampur Buffer 65 226 3.5 118 108 915 66 26.3

Bareipani Buffer 113 570 5 403 167 414 100 24.3

Barignbada Buffer 45 229 5.1 119 110 924 70 20.7

Barsia Buffer 72 380 5.3 200 180 900 87 22.7

Benipur Buffer 10 226 22.6 118 108 915 78 26.3

Bhudabalanga Buffer 30 113 3.8 95 18 189 78 23.9

Gadasahi Buffer 14 133 9.5 65 68 1046 45 13.8

Gadsimilipal Buffer 55 290 5.3 164 126 768 85 10.9

Gurguria Buffer 128 540 4.2 270 270 1000 211 15.4

Jenabil Core 25 260 10.4 135 125 926 42 25.9

Kabataghai Core 55 298 5.4 153 145 948 36 20.3

Kandibil Buffer 85 446 5.2 225 221 982 54 12.2

Kasira Buffer 51 245 4.8 123 122 992 64 21.9

Kolha Buffer 47 324 6.9 169 155 917 49 23.9

Koljhari Buffer 26 270 10.4 143 127 888 45 12.6

Kudaghuta Buffer 26 190 7.3 99 91 919 65 13.8

Kukurbuka Buffer 55 371 6.7 203 168 828 122 17.8

Kumari Buffer 57 523 9.2 247 276 1117 64 25.1

Kusumi Buffer 62 280 4.5 145 135 931 56 15.4

Langighasara Buffer 22 93 4.2 42 51 1214 48 10.9

Makabadi Buffer 45 225 5 113 112 991 49 28.4

Nawana Buffer 57 175 3.1 95 80 842 68 24.3

Nigirda Buffer 15 60 4 32 28 875 36 16.2

Saruda Buffer 40 188 4.7 103 85 825 72 8.9

Uski Buffer 57 216 3.8 131 85 649 110 16.6

Yamunagard Core 18 187 10.4 97 90 928 30 10.9

Total 1418 8212 5.8 4385 3827 873 2161 545.9

(Source: Data collected from the V. A. O. office, panchayats and primary health centers of the

respective villages).



R e s u l t s | 35

Table 5: The gender and age classes of respondents.

Gender Age

20-39 40-59 60

Male 54 23 14

Female 32 12 8

Total 86 35 22

5.1.3 Educational levels of local communities

Out of 143 respondents surveyed, 38% of those interviewed were literate and 62% were

illiterate, because the road network and the educational facilities were very poor in these

areas. Among the literate, 26% were men and 12% were women. Fig. 7 shows the level of

education of respondents interviewed in Similipal. In all the literate respondents 22% were at

primary school level, 17% were at high school level and 6% were at higher secondary level.

None of those interviewed had attended University (Fig. 7). There were more women than

men that were illiterate.

Figure 7: Educational status of the respondents (Source: Data collected from the V. A. O. office,

panchayats).



R e s u l t s | 36

5.1.4 Occupation and income

Most of the households (59%) were involved in agriculture. About 42 (29%) households

worked as small holdings cultivators, wage labor and collected NTFPs from the forest

because they have less land holdings which do not support them off season. During summer

and off season they collect NTFPs from the forests, and do labor work, 4% were self-

employed in small businesses and government jobs and 8% were land less people who were

wage labor in the urban centers or in nearby cities (Table 6, Fig. 8).

Figure 8: Occupational status of the respondents.

5.1.5 Income classes

The household economy in the rural society depends on the income derived from different

sources. Table 6 describes the income of respondents from various sources, including

cultivation, NTFPs, daily wages etc. The majorities of the respondents (81%) were from the

low-income classes and earned less than one lakh per year, and 48% earned less than Rs.

50,000- per year (Table 6). Fewer (19%) earned more than one lakh per annum (Table 6). The

majority of those earning less than Rs. 50,000- per year were households engaged in

cultivation, NTFPs collection, daily wage labor and a combination of these (Table 6).



R e s u l t s | 37

Table 6: Annual income of the respondents of the studied households.

Occupation Annual income Total

<50,000 50,000-

100,000

100,000 +

Agricultural cultivator 17 46 21 84 (58)

NTFPs collector 12 0 0 12 (8)

Agriculture and NTFPs collectors 12 1 0 13 (9)

Daily wages 11 0 0 11 (8)

Daily wages and NTFPs collectors 4 0 0 4(3)

Agriculture and wages 13 0 0 13 (9)

Agriculture and Forest Department 0 0 4 4 (3)

Agriculture and Business 0 0 1 1

Service 0 0 1 1

Total 69 (48%) 47 (33%) 27 (19%) 143

5.1.6 Livestock population and its impacts

A majority of 1295 among the 1418 households in the region owned livestock. Since the

households are mostly agriculturists, livestock are a source of farm labor, capital asset and a

source of meat and milk. The local households owned cattle, buffalo, sheep and goat. In the

villages of Saruda and Nigirda 100% of household owns livestock while the village Gurguria

fewer households (51%) own livestock (Table 7). The 1418 households owned a total of

10,522 livestock, out of which 51% were cattle, 26% buffalo and 21% goat. A household

owned an average of 9.27 livestock (Table 7, Source: Data collected from the V. A. O. office,

panchayats). The average number of animals/household varied between 2.8-47.6 with the

lowest in village Saruda and highest in village Benipur (Table 7).

Use of forest biomass

Fodder and fuel-wood are the two most heavily exploited forest products in India (Davidar et

al., 2010). We observed that fuel-wood is harvested on a daily basis. In all the 143 household

of the surveyed study villages, 100% of the families collected fuel-wood either as the chief

source of fuel for cooking and heating in winter or for selling in nearby market. Annually a



R e s u l t s | 38

total of 59, 9330 kg of wood or about 600 tons yr -1

, was extracted from the forest by the 143

households, of which 21, 2430 kg (35%) of fuel-wood was used for household needs, and

31,7280 kg (53%) of fuel-wood was sold (Table 8).

Table 7: Ownership of livestock among the households surveyed in the 30 villages.

Village Total

households

surveyed

Livestock

ownership

(%)

Cow Goat Buffalo Sheep Total

livestock

population

Average

number of

animals/

household

Asanbani 34 30 (88) 145 0 109 0 254 7.5

Astakumar 50 49 (98) 256 27 181 36 500 10.0

Badega 18 12 (67) 159 0 134 0 293 16.3

Bakua 41 37 (90) 83 76 0 0 159 3.9

Balarampur 65 55 (85) 234 0 193 0 427 6.6

Bareipani 113 104 (92) 308 30 306 0 644 5.7

Barignbada 45 32 (71) 112 123 0 0 235 5.2

Barsia 72 67 (93) 286 19 212 0 517 7.2

Benipur 10 6 (60) 260 216 0 0 476 47.6

Bhudabalanga 30 27 (90) 145 0 152 0 297 9.9

Gadasahi 14 12 (86) 78 77 0 0 155 11.1

Gadsimilipal 55 50 (91) 349 30 220 82 681 12.4

Gurguria 128 65 (51) 246 208 16 33 503 3.9

Jenabil 25 22 (88) 152 169 0 0 321 12.8

kabataghai 55 50 (91) 223 292 3 2 520 9.5

Kandibil 85 60 (71) 228 190 24 32 474 5.6

Kasira 51 44 (86) 204 185 39 0 428 8.4

Kolha 47 35 (74) 144 25 122 50 341 7.3

Koljhari 26 23 (88) 75 0 75 0 150 5.8

Kudaghuta 26 14 (54) 195 0 171 0 366 14.1

Kukurbuka 55 49 (89) 200 19 155 0 374 6.8

Kumari 57 54 (95) 170 248 0 0 418 7.3

Kusumi 62 45 (73) 179 135 0 0 314 5.1

Langighasara 22 15 (68) 70 32 2 2 106 4.8

Makabadi 45 34 (76) 167 11 142 0 320 7.1

Nawana 57 49 (86) 228 15 210 0 453 7.9

Nigirda 15 15 (100) 85 0 71 0 156 10.4

Saruda 40 40 (100) 66 0 46 0 112 2.8

Uski 57 45 (79) 212 0 161 0 373 6.5

Yamunagard 18 15 (83) 78 77 0 0 155 8.6

Total 1418 5337 2204 2744 237 10522 9.27

(Source: Data collected from the V. A. O. office, panchayats)



R e s u l t s | 39

Table 8: Data on biomass harvest and use by the surveyed households.

Villages Total

households

No. of

house-

holds

surveyed

No.

collecting

fuel-wood

Total

fuel-wood

collected

(kg yr-1

)

Quantity

of wood

sold (kg

yr-1

)

Quantity

used for

domestic

purposes

(kg yr-1)

No.

collecting

fodder

from

forest

Quantity

of fodder

(kg yr-1

)

Asanbani 34 2 2 5840 0 3650 0 0

Astakumar 50 9 9 37960 22080 14600 2 2920

Badega 18 3 3 13140 7680 4380 0 0

Bakua 41 6 6 24090 19200 8760 2 2555

Balarampur 65 4 4 21900 8640 5840 0 0

Bareipani 113 11 11 47450 24000 19345 5 6205

Barignbada 45 3 3 13140 7200 4745 0 0

Barsia 72 5 5 21900 14400 6205 1 1095

Benipur 10 5 5 18250 9600 7300 0 0

Bhudabalanga 30 3 3 12045 6240 4015 3 4015

Gadasahi 14 2 2 12410 7200 2555 0 0

Gadsimilipal 55 10 10 47450 19200 14600 0 0

Gurguria 128 7 7 28105 16800 10950 0 0

Jenabil 25 7 7 21900 8640 10950 2 2555

Kabataghai 55 5 5 25550 4800 7300 3 3650

Kandibil 85 4 4 18250 14400 5475 0 0

Kasira 51 3 3 12775 7680 3650 1 1825

Kolha 47 6 6 23725 14400 9125 2 3650

Koljhari 26 3 3 15330 6240 4015 3 1825

Kudaghuta 26 3 3 12775 9600 4380 3 6570

Kukurbuka 55 7 7 21900 14400 8760 4 5475

Kumari 57 8 8 29200 14400 12045 3 3650

Kusumi 62 4 4 15330 10560 6205 1 1825

Langighasara 22 3 3 12775 12000 4380 0 0

Makabadi 45 4 4 13870 3840 5110 0 0

Nawana 57 3 3 16425 10560 5110 0 0

Nigirda 15 2 2 10950 5760 3285 1 1460

Saruda 40 5 5 20075 12480 7665 2 2190

Uski 57 3 3 10220 2400 4380 0 0

Yamunagard 18 3 3 14600 2880 3650 0 0

Total 1418 143 143 599330 317280 212430 38 51465

Table 9: Daily harvesting of biomass such as fuel-wood and fodder for domestic purposes.

Biomass use and sources Fuel-wood

(kg /day)

Fodder

(kg/day)

Total Biomass

(kg/day)

Requirement per household 4.04 3.7 7.7

Forest sources 4.04 1.8 5.8

Other sources (agricultural residues) 0 1.9 1.9



R e s u l t s | 40

The average harvesting of fuel-wood per household use was 1456 kg, whereas 2341 kg was

collected for sale, indicating that about 1.6 times more fuel-wood was collected if for sale

than for household sustenance.

Since most of the households own livestock, 105 households graze their animals in Similipal

forests and 38 collected fodder from the forest to feed their livestock. A total of 51,465 kg of

fodder (or about 50 tons yr -1

) was extracted by 38 households from the forest in a year (Table

8). Fodder is also obtained from the other sources such as agricultural residues (Table 9). Our

survey indicates that each household uses almost 4 kg of fuel-wood a day for cooking and

other purpose and 3.7 kg of fodder for livestock feeding. The total biomass requirement of a

household is almost 7.7 kg, of which about 5.8 kg comes from forest (Table 9).

Using a logistic regression, I tested whether those that sold fuel-wood were more likely to

have lower income levels, be older, be illiterate and be less likely to own land. The result of

the logistic regression on the variables associated with the likelihood of selling fuel-wood is

significant overall (Table 10).

Table 10: The logistic regression between likelihood of selling fuel-wood to annual income, age,

education (male), hectares of land owned, total livestock owned, location in core or buffer.

Predictor variables Coefficient Std. Error Coeff./SE P Value

Constant 2.4026 0.86332 2.78 0.0054

Annual income -1.50E-05 7.79E-06 -1.92 0.0545

Age -0.0346 0.01483 -2.33 0.0196

Education male 0.00695 0.43585 0.02 0.9873

Land owned (hectare ) 0.38121 0.22857 1.67 0.0953

Total livestock -0.0305 0.03754 -0.81 0.4165

Location (core-buffer) -0.44264 0.5207 -0.85 0.3953

Distance to forest 0.01258 0.2218 0.06 0.9548

The only two variables that were significantly but negatively associated with the likelihood of

selling fuel-wood were income and age. This indicates that poorer and younger people were



R e s u l t s | 41

more likely to be wood sellers (Table 10). Variables such as male illiteracy (education male),

livestock owned, location in the core zone or buffer zone and distance to forest were not

associated with likelihood of selling wood (Table 10).

5.1.7 Resource collection

As mentioned in the earlier section, all the surveyed households collected resources from the

Similipal Tiger Reserve. Collection of fuel-wood from forests requires at least 2 to 4 hours of

work per day in the study areas. The villagers travel 0.5-3 km in the forest every day to

collect fuel-wood and fodder from the forest. Of the total households surveyed, all the

household collected wood for their own use and 82 household of the 143 collected fuel-wood

to sell in the market (Table 11). Our survey indicates that the households, who collected fuel-

wood for sale, collected about 1.6 times more wood than those that collected for their own

household use.

5.1.7.1 Harvesting pressure as a function of distance from the forest boundary

There was no significant correlation between village size and distance to forest boundary

indicating that village size was independent from access to the forest (r = 0.06, ns). There was

a no relationship between distance from the forest boundary and the number of households

collecting fuel-wood (r = 0.02, p = 0.08). There was no relationship between fodder

collection and distance to forest boundary (r = 0.13, ns). The proportion of fuel-wood

collectors was significantly negatively correlated with the village population size (r = 0.24, p

= 0.003) but fodder collectors were significantly positively correlated with village population

size (r = 0.31, p = 0.001). This finding suggests that as the village size increases, fuel-wood

collection decreases as a source of livelihood whereas the opposite is the case with fodder

collection, which increases with village size.



R e s u l t s | 42

Table 11: Proportion of resource harvesters in each village.

Village Totalhousehold

surveyed

Totalpopulation

Distance toforest

boundary

(km)

Forest fuel-wood collectors

for domestic use

(%)

Fuel-wood

sellers

(%)

Foddercollectors

(%)

Asanbani 2 7 2.5 2 (6) 0 0

Astakumar 9 63 0.3 9 (18) 4 (8) 2 (4)

Baghdega 3 17 0.3 3 (17) 1 (6) 0

Bakua 6 28 1 6 (15) 4 (10) 2 (5)

Balarampur 4 27 0.5 4 (6) 2 (3) 0

Bareipani 11 52 0.5 11(8) 7 (6) 5 (4)

Barignbada 3 17 1.5 3 (7) 2 (4) 0

Barsia 5 29 0.6 5 (7) 2 (3) 1 (1)

Benipur 5 32 2.8 5 (50) 2 (20) 0

Bhudabalanga 3 21 1.7 3 (10) 2 (7) 3 (10)

Gadasahi 2 22 2.5 2 (14) 2 (14) 0

Gadsimilipal 10 88 2 10 (18) 5 (9) 0

Gurguria 7 33 0.5 7 (5) 3 (2) 2 (2)

Jenabil 7 39 0.1 7 (28) 3 (12) 3 (12)

Kabataghai 29 29 0.75 5 (9) 4(7) 0

Kandibil 4 23 1.5 4 (5) 4 (5) 0

Kasira 3 18 0.5 3 (6) 3 (6) 1 (2)

Kolha 6 34 1.8 6(13) 2 (4) 3 (6)

Koljhari 3 20 1.2 3 (12) 1 (4) 2 (8)Kudaghuta 3 20 1.5 3 (12) 3 (12) 3 (12)

Kukurbuka 7 32 2.8 7 (13) 5 (9) 4 (7)

Kumari 8 34 1.3 8 (14) 5 (9) 3 (5)

Kusumi 4 23 1.2 4 (6) 4 (6) 1 (2)

Langighasara 3 12 1 3 (14) 3 (14) 0

Makabadi 4 21 1.8 4 (9) 1 (2) 0

Nawana 3 16 2.8 3 (5) 3 (5) 0

Nigirda 2 8 3 2 (13) 1 (7) 1 (7)

Saruda 5 35 0.2 5 (13) 5 (13) 2 (5)

Uski 3 17 0.5 3 (5) 1 (2) 0

Yamunagard 3 12 0.5 3 (17) 1 (6) 0

5.1.8 Economy of fuel-wood

All the surveyed household 143 collected wood for their own use and for sale. Of these 51

collected wood for their own use, and the total quantity collected was approximately 1500 kg

per week, 92 collected almost 9400 kg for sale and their own use per week. The households

that collected wood for sale collected 1.6 times quantity of those that collected only for their



R e s u l t s | 43

own use. The market value of the wood was Rs. 2 per kg and the market value of a head load

which approximately weighing 50-60 kg work out to be Rs.100-120, whereas it is sold by the

collectors for Rs. 50-60 (Table 12).

Table 12: Estimates of biomass collected from the forest and sold in market over a year.

Forest

product

collected

Total

harvesting

households

Total

biomass

collected

per day

(mean

±SD)

Economic

value at

market

value of Rs.

2 per kg

per day

Quantity

used for

domestic

purposes

(kg) per

day

Quantity

sold (kg)

per week

Economic

value at

sale value

(Rs 2 per

kg)

Fuel-wood 143 4.04±0.8 3284 582 6610 13220

Fodder 38 3.7 ± 1 0 0 0 0



R e s u l t s | 44

5.2 Impacts of human disturbances on vegetation structure of Similipal Tiger Reserve

5.2.1 Species richness, species diversity and basal area

A total of 90 species of trees, shrubs and lianas belonging to 41 different families were

identified in the disturbed and undisturbed sites. A total of 86 species from 39 families were

recorded in the undisturbed sites and 70 species from 36 families in the disturbed sites (Table

13 & 14). The number of shrub species was much higher in the disturbed sites. Stem density

(ha-1), species diversity as measured by the Shannon-Wiener index, basal area (m² ha-1) and

was lower in disturbed sites as compared to the undisturbed sites (Table 14).

Table 13: Comparison of species richness of trees, shrubs and lianas in the disturbed and undisturbed

plots.

Life Form Species richness Total

Disturbed Undisturbed

Trees 57 73 76

Shrubs 7 6 7

Lianas 6 7 7

Total 70 86 90

Table 14: Comparison of species richness and diversity, stem density (ha-1

) and basal area (m2ha

-1) in

disturbed and undisturbed plots (mean±SEM).

Parameters Disturbed

(8 ha)

Undisturbed

(8 ha)

t =test p

Species richness 70 86

No. of families 36 39

Species diversity (Shannon-Weiner

index)

1.69 2.28

Stem density ha-

876±110 1472±191 t = 2.69 p = 0.0173Basal area (m² ha- ) 55±20 72±11 t = 8.51 p = 0.0001

Fifty five tree species were common to both plots. Species diversity was higher in the

undisturbed (Shannon-Wiener index = 2.28) compared with the disturbed plots (Shannon-

Wiener index = 1.69). Stem density was significantly higher in the undisturbed plots which

had an average of 1472 stems ha-1

compared with 876 stems ha-1

in the disturbed plots (Paired

Ttest, t = 2.60, df = 7, p = 0.002). The average basal area was significantly higher in the



R e s u l t s | 45

undisturbed plots 71 m² ha-1

compared with 55 m² ha-1

in the disturbed plots (Paired T test =

8.29, df = 7, p < 0.0001) (Table 14). Twenty species recorded in undisturbed sites were not

recorded in the disturbed sites but 4 species recorded in the disturbed sites were absent in

undisturbed sites (Appendix 1).

The stem densities of different species varied among sites and in every site Shorea robusta

was dominant. Stem densities (Mann Whitney U test = 5.33, p = 0.02), and basal area (Mann

Whitney U test = 5.39, p = 0.02) were significantly higher in the core zone compared with the

buffer zone. Tree density and basal area in the disturbed sites was lower than in the

undisturbed sites (Table 15). This finding suggests that degradation is higher near the villages

where human impact is greater.

Table 15: Comparison of human impact in disturbed (D) and undisturbed (UD) plots in the eight sites.

Site Species richness Stem density ha-

Basal area (m ha-

)

D UD D UD D UD

Gurguria 18 23 635 778 20.25 33.52

Nawana 18 27 609 1300 22.76 47.14

Makabadi 16 22 652 760 25.99 45.7

Balarampr 17 25 528 1296 20.61 47.94

Bakua 22 36 1133 2048 48.62 81.59

Yamunagard 22 37 1116 2165 99.43 112.66

Kabataghi 20 28 955 1528 56.78 83.52

Jenabil 27 37 1380 1901 108.47 123.34

5.2.2 Uses of plant parts for different purposes

Out of 90 species recorded in study regions, 87 species were used for fuel-wood (Table 16).

Other products extracted were for food, base for country alcohol, resins, tendu leaves and

others. Some species like Shorea robusta, Madhuca indica, Bauhinia vahli yielded more than

one product: fuel-wood, resins, leaves, chew stick, rope and oil. Madhuca indica fruits were

used for making country liquor (Table 18).



R e s u l t s | 46

5.2.3 Extraction pressure of biomass

The mean monthly extraction pressure was 6%, and ranged from 1% in Jenabil to 11% in

Gurguria (Table 17). This shows that on average 6% of all trees had new cuttings every month

and most of the cases the whole plant was removed. The buffer zone villages like Gurguria,

Makabadi, Nawana and Balarampur had higher levels of extraction pressure than core areas

villages. There was significant difference in the mean monthly extraction pressure between

the core zone and buffer zone villages (Wilcoxon signed rank test: p < 0.02). The village size

was negatively correlated with stem densities of each plot (r = – 0.23, p < 0.05) indicating that

plots closer to larger villages have lower stem densities. This suggests that there is increasing

pressure on forests with increasing village size.

Table 16: Number of species harvested for different purposes by the local people.

Plant parts used Number of species Uses

Wood 87 Fuel-wood and implements

Fruit 10 Food

Seed 6 Oil and medicine

Leaves 3 Plates, fodder, mat, local beedi

Bark 3 Rope and medicine

Flower 4 food and medicine

Stem 4 chew stick and rope

Table 17: The mean monthly extraction pressure and total population of villages.

Village N Core/Buffer Stem density

(ha-1

)

Mean extraction pressure

(%)

Gurguria 547 Buffer 635 11.06 Nawana 216 Buffer 609 9.88

Makabadi 225 Buffer 652 10.4

Balarampur 226 Buffer 528 9.56

Bakua 259 Core 1133 1.99

Yamunagard 192 Core 1116 1.77

Kabatagai 187 Core 955 2.01

Jenabil 260 Core 1380 1.29



R e s u l t s | 47

The mean monthly extraction pressure was positively correlated with village size (r = 0.43,

p < 0.05). This finding illustrates that the extraction pressure increases as the size of the

village and thereby leading to deforestation over time due to increasing pressure from

villages.

Table 18: List of the species recorded in disturbed and undisturbed sites, plant part harvested and

uses.

Name Stem densityha

-1(D)

Stem densityha

-1 (UD)

Plant partsharvested

Uses

Aegle marmelos (L.) Corr . 13 52 wood, leaves, fruit fuel-wood, medicine

Alangium salviifolium

(L. f.)

114 147 wood fuel-wood, medicine

Albizia procera (Roxb.) 24 60 wood fuel-wood

Anogeissus latifolia (Roxb.

ex DC.)

187 137 wood and gum fuel-wood, timber,

gum

Artocarpus lacucha (Roxb.) 73 132 fruits, leaves fruits, fodder

Barringtonia acutangula (L.) 16 163 wood fuel-wood

Bauhinia malabarica(Roxb.)

0 28 wood fuel-wood

Bauhinia vahlii (Wight &Arn.)

59 111 wood, bark fuel-wood, rope

Bauhinia variegata (L.) 22 41 wood fuel-wood

Bombax ceiba (L.) 26 98 wood, fruits fuel-wood, silk cotton

Boswellia serrata (Roxb.) 0 77 wood, leaves fuel-wood, medicine

Bridelia retusa (Willd.) 22 80 wood timber, fuel-wood

Buchanania lanzan Spreng. 93 169 seeds, wood fuel-wood, food,timber

Careya arborea (Roxb.) 37 100 wood fuel-wood

Casearia elliptica (Willd.) 111 237 wood fuel-wood

Casearia graveolens Dalz. 36 108 wood fuel-wood

Cassia fistula (L.) 63 45 wood fuel-wood

Cayratia auriculata (Roxb.) 29 117 wood fuel-wood

Cayratia trifolia (L.) 4 86 wood fuel-wood

Cedrela toona (Roxb.) 0 19 wood fuel-wood



R e s u l t s | 48

Cleistanthus collinus (Roxb.) 27 81 wood fuel-wood

Cochlospermum religiosum(L.) Alston

0 36 wood fuel-wood

Crateva religiosa G. Forst. 0 59 wood fuel-wood

Croton roxburghii Balak. 42 102 wood fuel-wood

Dalbergia latifolia (Roxb.) 0 91 wood timber, fuel-wood

Dalbergia sisoo (Roxb.) 0 45 wood timber, Fuel-wood

Dillenia pentagyna (Roxb.) 211 181 seeds, wood fuel-wood, oil

Dioscorea spp. (L.) 0 13 tuber food

Diospyros malabarica(Desr.) Kostel.

0 12 wood fuel-wood

Diospyros melanoxylon(Roxb.)

14 28 leaves, fruits fuel-wood, tenduleaves, food

Diospyros montana (Roxb.) 21 0 wood fuel-wood

Phyllanthus emblica (L) 19 16 fruit medicine

Entada rheedii Spreng. 94 60 wood fuel-wood

Erythrina suberosa (Roxb.) 38 0 wood fuel-wood

Euonymus glaber (Roxb.) 11 53 wood fuel-wood

Ficus benghalensis (L.) 0 2 wood fuel-wood

Ficus hispida L. f. 3 81 wood fuel-wood

Ficus religiosa (L.) 1 15 wood fuel-wood

Gardenia gummifera L. f. 0 32 wood fuel-wood

Garuga pinnata (Roxb.) 5 32 wood fuel-wood

Glochidion lanceolarium(Roxb.)

49 125 wood fuel-wood

Glycosmis pentaphylla

(Retz.)


Gmelina arborea (Roxb.) 0 48 wood fuel-wood, timber

Gnetum ula Brongn. 2 0 wood fuel-wood

Haldina cordifolia (Roxb.) 9 41 wood fuel-wood

Homalium nepalens Benth. 48 83 wood fuel-wood

Hymenodictyon excelsum

(Roxb.)

0 25 wood fuel-wood

Hyptianther asticta Willd. 23 29 wood fuel-wood

Indigofera cassioides DC. 16 5 wood, flowers fuel-wood



R e s u l t s | 49

Ixora parviflora Vahl. 39 0 wood fuel-wood

Kydia calycina (Roxb.) 26 32 wood fuel-wood

Lagerstroemia parviflora

(Roxb.)


Lannea coromandelica(Houtt.) Merr.

6 49 wood fuel-wood

Litsea glutinosa (Lour.)Robins.

0 87 wood fuel-wood

Madhuca indica Gmel. 42 143 flower, fruits, wood fuel-wood, liquor,food

Mangifera indica (L.) 8 110 fruits fuel-wood, timber andfood

Melia dubia (L.) 58 223 wood fuel-wood

Michelia champaca( L.) 40 60 flower, wood fuel-wood, flower

Miliusa velutina (Dunal)

Hook. f.


Millettia extensa Benth. 12 120 wood fuel-wood

Mitragyna parvifolia (Roxb.) 24 67 wood fuel-wood

Nyctanthes arbor-tristis (L.) 0 15 wood fuel-wood

Ochna obtusata DC. 44 57 wood fuel-wood

Phoebe wightii Meisn. 42 51 wood fuel-wood

Pongamia pinnata (L.) Pierre

16 193 seeds, wood fuel-wood, oil

Protium serratum (Wall. ex

Colebr.) Engl.

9 55 wood fuel-wood

Prunus ceylanica (Wight.) 41 41 wood fuel-wood

Pterocarpus marsupium

(Roxb.)

101 122 timber wood fuel-wood

Samanea saman (Jacq.)Merr.


Schleichera oleosa (Lour.)Oken.

4 132 seeds, leaves, wood fuel-wood, fodder, oil

Schrebera swietenioides

(Roxb.)

0 73 wood fuel-wood

Securinega virosa (Roxb. exWilld.)

0 74 wood fuel-wood

Shorea Robusta Gaertn .f 4202 4431 wood, leaves, seeds,

timber, sap

timber, fuel-wood, oil,

resin, utensils

Sterospermum suaveolens 28 245 wood fuel-wood



R e s u l t s | 50

(Roxb.)

Suregada angustifolia.(Baill.)


Symplocos cochinchinensis

(Lour.)

0 65 wood fuel-wood

Syzygium cerasoides (Roxb.) 8 37 fruits, wood fuel-wood, food,

timber

Syzygium cumini (L.) Skeels 114 120 fruits, leaves fuel-wood, food,fodder

Terminalia arjuna (L.) 107 278 fruits fuel-wood

Terminalia bellirica (L.) 45 128 fruits fuel-wood

Terminalia chebula (L.) 55 36 fruits fuel-wood

Terminalia tomentosa(Roxb.)

107 236 wood fuel-wood, timber

Toona ciliata Roem. 0 29 wood fuel-wood

Trewia nudiflora (L.) 6 129 wood fuel-wood

Vitex leucoxylon (L.) 12 169 wood fuel-wood

Wendlandia exerta (Roxb.) 42 19 wood fuel-wood

Wendlandia tinctoria(Roxb.)

0 37 wood fuel-wood

Xylia xylocarpa (Roxb.) 5 82 wood fuel-wood

Ziziphus rugosa Lam. 2 28 wood fuel-wood

Zizyphus zujuba Lam. 2 21 fruit fuel-wood, food



R e s u l t s | 51

5.3 Attitude of local people towards conservation of wild life in Similipal Tiger Reserve

The previous chapters provided information on the socio-economic activities of the

households and their dependence on the forests for fuel-wood and fodder, and their impact on

the forest. Therefore, it is essential to empower local people to manage natural resources,

however, without information on the relationship between the protected area and local

communities, designing a management plan would be difficult.

5.3.1 Socio-economic profile

In the survey of attitudes towards Similipal Tiger Reserve, there were 116 younger people, 79

middle aged and 22 elder people in the database, the majority of whom (79%) were primarily

agriculturists (Table 19). Daily wage workers were relatively fewer (12%). Very few of the

respondents were employed by the Forest Department (Table 19). All the respondents were

residents and their ancestors had resided in the villages for generations. A total of 146 of the

respondents were men and 71 were women. The majority (190) was from buffer zone

villages, and 27 were from the core zone.

Table 19: Occupation of the respondents and dependence upon forest products with relation to age

classes.

Age N Occupation (%) Forest Other Hunting

Agriculture NTFPs Daily

wage

Forest

Dept

fuel-

wood

NTFPs

Younger

(20-34)

116 95 (82) 5 (4) 13 (11) 3 (3) 116 6 7

Middle

(35-49)

79 59 (75) 4 (5) 14 (18) 2 (3) 79 4 5

Elder

(50+)

22 17 (77) 3 (13) 2 (9) 0 22 4 1

Total 217 171 (79) 12 (6) 27 (12) 5 (2) 217 14 13

All the respondents used fuel-wood harvested from the forest for their domestic and

agricultural requirements (Table 19). Few people (6%) collected other NTFPs and few hunted

for bush meat (6%).



R e s u l t s | 52

A little over half (53%) the respondents supported protection of nature because it was a

common heritage of the people (Table 20). The rest opposed the protected area: among those

that opposed the protected area, the majority (42%) opposed it, because, it was imposed on

them. Very few (4%) thought it was a waste of money which could be better spent on helping

the poor (Table 20). There was no significant difference among the age classes in terms of

support or lack of support of the protected area and conservation (2 = 0.40, df = 2, ns).

Table 20: Local support for conservation among the respondents.

Age N Support (%) No support (%)

Common

heritage

Money better

used for poverty

alleviation

Conservation

imposed

Younger (20-34) 116 64 (55) 4 (4) 48 (41)

Middle (35-49) 79 40 (51) 4 (5) 35 (44)

Elder (50+) 22 12 (55) 1 (5) 9 (41)

Total 217 116 (53) 9 (4) 92 (42)

Conservation measures imposed a cost on the local communities because they lose access to

forest resources upon which they depend for household requirements. Therefore, they were

asked whether they were willing to bear the cost in terms of loss of resources. The support of

the respondents for conservation was contingent upon limited (28%) or no costs (80%) (Table

21). Very few (5%) were agreeable to bearing a cost. There was no significant difference in

the willingness to accept costs for conservation between the different age categories (2 =

4.52, df = 2, ns), different occupation/economic activities (2 = 0.17, df = 2, ns), and between

respondents in the core and buffer zones (Fisher’s exact test = 0.442, ns).

About 64% of the respondents preferred the PA to be managed by local communities, and

only 9% were in favour of management by the Forest Department. About 28% did not want

the protected area at all (Table 21). There was no significant difference between young and

middle aged people with regard to opinion management of PA’s (2 = 0.08, df = 1, ns). The

elderly people were completely against management by the Forest Department.



R e s u l t s | 53

Table 21: Local opinion about conservation cost to be borne by local communities and the

management of the protected area.

Age N Conservation cost Management

(%)At no cost Little cost Cost

acceptable

FD Local

Community

No PA

Younger (20-34) 116 95 (82) 15 (13) 6 (5) 11 (9) 82 (45) 23 (20)

Middle (35-49) 79 64 (81) 12 (10) 3 (4) 8 (10) 52 (66) 19 (24)

Elder (50+) 22 14 (64) 6 (5) 2 (9) 0 4 (18) 18 (84)

Total 217 173 (80) 33 (28) 11 (5) 19 (9) 138 (64) 60 (28)

Women were less in favour of the Similipal PA (49%) than men (36%) although this was not

significant (2 = 2.40, df = 1, ns). Among those that favoured the PA, the large majority

wanted it to be a community managed than by the Forest Department, although a higher

proportion of men supported management of the PA by the Forest Department (Table 22).

Overall there were no significant differences between men and women for support/opposition

to PA.

Table 22: Gender and support for the protected area and its management.

Gender N Favour PA (%) Opposed to PA

(%)Local community

decision

Forest Department

decision

Male 147 21 (36) 17 (28) 21 (36)

Female 70 39 (49) 2 (2) 39 (49)

5.3.2 Perceptions of species decline

People who supported conservation as a common heritage of the country were more likely to

perceive a decline of the tiger (Wilcoxon Signed Rank Test = 2.911, p = 0.004), less likely to

perceive the decline of the elephant (Wilcoxon Signed Rank Test = -2.11, p = 0.035), and more

likely to see the disappearance of trees (Wilcoxon Signed Rank Test = 5.98, p < 0.0001). This

suggests that conservation attitudes and perception of decline supported the hypotheses in two

cases but not in the case of elephants.



R e s u l t s | 54

Local people of all age classes perceived that both the tiger and the Asian elephant had

declined over time (Table 23, Fig. 9-10). In all 90% of the respondents agreed that the tiger

and the elephant had disappeared (Table 24-25). The recollections of tiger sightings per

annum were significantly higher 20 and 10 years ago than at present, with only 20% not

having seen any tiger 20 years ago, whereas presently 92% had not sighted a tiger presently

(2 = 128.8, df = 2, p < 0.0001, Table 24, Fig.9).

Table 23: Mean annual tiger and elephant sightings as recollected by respondents .

0

10

20

30

40

50

60

70

80

90

100

20 years 10 years now

% o

f r e s p o n d e n t s

Past to present sightings

% annual tiger sightings

0

1 to 4

5+

Figure 9: Recollections of annual tiger sightings over the years. Blue= no sightings, red=1-4 tigers per

year and green= over 5 tigers per year.

The distribution of tiger sightings differed significantly between 20 years and present

(Kolgomorov Smirnov = 0.95, p < 0.0001), but did not differ significantly between 10 years

and present (Kolgomorov Smirnov = 0.52, ns), indicating that the decline had taken place

Tiger

sightings

Annual sightings

(Mean ± SD)

Elephant

sightings

Annual sightings

(Mean ± SD)

20 years ago 0.38 ± 0.9 20 years ago 1.8± 3

10 years ago 0.22 ± 0.8 10 years ago 0.8 ± 1

Now 0.1 ± 0.4 Now 0.4 ± 0.8



R e s u l t s | 55

over 10 years ago. Comparison of 0 and 1-4 categories of tiger sightings over different time

periods using 2 test (2 = 128.8, df = 2, p < 0.0001).

The recollections of elephant sightings per annum were significantly higher 20 and 10 years

ago than at present, with only 20% not having seen any elephant 20 years ago, with 89% not

having seen an elephant now and the number of elephants sighted has declined significantly

from 20 years to present when just the 0 and 1-4 elephant categories were compared over the

3 time frames (2 = 39.42, df = 2, p < 0.0001, Table 24, Fig. 10).

Table 24: Tiger sightings and perceptions of tiger decline by age classes.

Age N Recollections of tiger sightings (%) Tiger

gone

(%)

20 years ago 10 years ago Current

0 1-4 5+ 0 1-4 5+ 0 1-4 5+

Younger

(20-34)

116 - - - 106 10 0 110 6 0 108 (93)

Middle

(35-50)

79 19 38 22 62 17 0 72 7 0 66 (84)

Old

(50+)

22 1 8 13 16 6 0 18 4 0 21 (95)

Total 217 20

(20)

46

(46)

35

(35)

184

(85)

33

(15)

0 200

(92)

17

(8)

0 195

(90)

0

10

20

3040

50

60

70

80

20 years 10 years now

% o

f r e s p o n d e n t s

Past to present sightings

% annual elephant sightings

0

1 to 4

5+

Figure 10: Recollections of annual elephant sightings over the years. Blue= no sightings, red=1-4

tigers per year and green= over 5 tigers per year.



R e s u l t s | 56

The distribution of elephant sightings differed significantly between 20 years and present

(Kolgomorov Smirnov = 0.94, p < 0.0001), and between 10 years and present (Kolgomorov

Smirnov = 0.71, ns), suggesting that elephant decline has been going on since 20 years.

Table 25: Annual sightings of elephants as remembered by the local respondents.

Age N Recollections of elephant sightings (%) Elephant

gone

(%)

20 years ago 10 years ago Current

0 1-4 5+ 0 1-4 5+ 0 1-4 5+

Younger

(20-34)

116 - - - 99 17 0 101 15 0 108 (93)

Middle

(35-50)

79 19 38 22 17 62 0 75 4 0 66 (84)

Old

(50+)

22 1 8 13 11 11 0 18 4 0 21 (95)

Total 20

(20)

46

(46)

35

(35)

127

(59)

90

(41)

0 194

(89)

23

(11)

0 195

(90)

Twenty years ago there were significant differences in the mean numbers of tigers sighted in

the core zone as compared with the buffer zone with the numbers in the core zone being

higher (Table 26), whereas presently core zone sightings had declined to levels in the buffer

zone (Table 26).

Table 26: Mean annual tiger and elephant sightings 20 years and at present in the core and buffer

zones

Species/time frame Mean annual sightings

Core

(N=27)

Buffer

(N=190)

T test df p

Tiger 20 years ago 1.407± 1.5 0.237±0.699 -6.79 215 <0.0001

Tiger Now 0.85±0.36 0.78±0.41 -0.81 215 ns

Elephant 20 years ago 2.82± 3.35 1.62±2.68 -2.11 215 0.04

Elephant Now 0 0.05±0.21

The mean annual sightings of elephants were significantly higher in the core zone as

compared with the buffer zone 20 years ago; however, the respondents had not sighted any

elephants currently in the core zone and the sightings had declined in the buffer zone (Table

26).



R e s u l t s | 57

5.3.3 Hunting

The middle aged and older local respondents who were former or current hunters also

recollected that hunting was relatively easy 20 years ago, and fewer agreed that it was easy 10

years ago and no one agreed that hunting was currently easy. This indicates a decline in the

prey base (Table 27).

Table 27: Number of hunters of different age classes over a 20 year period .

Age N Currently

Hunters

Easy Hunting

20 years ago 10 years ago now

Younger (20-34) 116 7 - 1 0

Middle (35-50) 79 5 18 4 0Old (50+) 22 1 10 4 0

5.3.4 Disappearance of the forest

The disappearance of trees appears to be more recent as per the recollections of the local

people. All the elderly people and a high proportion of the middle aged people recollected that

there were more trees and larger trees 20 years ago. The opinions of the different age classes

significantly differed (2 = 85.49, df = 2, p < 0.0001, Table 28). About 95% of the younger

respondents considered that there were more trees now, whereas only 32% and 2% of the

middle aged and elderly respectively considered there were more trees now (Table 28). When

comparing younger and middle aged people, the opinion of the middle aged significantly

differed from that of the young (2 = 72.6, df = 2, p < 0.0001).

Tree size appears to have declined more rapidly than numbers (2 = 7.49, df = 2, p = 0.02)

according to local perceptions, since all the elderly respondents agreed that trees were more

abundant and larger 20 years ago, whereas 89% and 76 % of the middle aged agreed to the

same statement. Similarly all elderly respondents agreed that trees were more abundant and

larger 10 years ago, whereas 94% and 71% of the middle aged agreed to the same statement.



R e s u l t s | 58

The views of the young differed probably because they were still too young to recollect the

loss of trees (Table 28).

Table 28: The perceptions of tree abundance and size over different time periods amongdifferent age classes.

Age N Tree abundance and size (%)

20 years ago 10 years ago Now

More

trees

Bigger

trees

More

trees

Bigger

trees

More

trees

Bigger

trees

Younger

(20-34)

116 19 (16) 6 (5) 65(56) 108 (93) 110 (95) 50 (43)

Middle

(35-50)

79 60 (76) 70 (89) 74 (94) 56 (71) 25 (32) 0

Old

(50+)

22 22 (100) 22 (100) 22 (100) 8 (36) 2 (9) 0

There were significant differences between perceptions of higher tree abundance in the core

zone as compared with the buffer zone 20 years ago and at present (Table 29), however, the

perceptions of larger trees during the same time frame, did not significantly differ (Table 29).

Table 29: Comparison of perceptions of greater tree abundance and size between core and buffer zone

20 years ago and at present.

Category Core

(N=27)

Buffer

(N=189)

T test df P

Tree abundance

20 years ago 0.481±0.51 1.418±2.66 1.82 201 0.07

Now 0.48±0.89 0.05±0.24 -5.53 215 <0.0001

Tree size

20 years ago 0.56±0.51 0.44±0.50 -1.16 215 ns

Now 0.22±42 0.23±42 0.05 215 ns

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