Population and Environment

, Volume 30, Issue 6, pp 261–274

An analysis of conservation attitudes and awareness around Kaziranga National Park, Assam, India: implications for conservation and development

Authors

    • Department of Environmental StudiesFlorida International University
  • Rahul J. Shrivastava
    • Miami-Dade County, Park and Recreation Department
Research Brief

DOI: 10.1007/s11111-009-0086-0

Cite this article as:
Heinen, J.T. & Shrivastava, R.J. Popul Environ (2009) 30: 261. doi:10.1007/s11111-009-0086-0

Abstract

Kaziranga National Park and World Heritage Site, Assam, India, situated in a region with a large and diverse human population, was recently expanded due to its global importance for the conservation of many endangered species. Here, we develop detailed demographic and socio-economic profiles of residents around Kaziranga to study conservation attitudes and awareness using a semi-structured survey of 590 households in 37 villages. Results show high variation in attitudes and awareness as a function of ethno-religious group, educational level, and socio-economic and immigration status, indicating more and different needs for economic interventions within some communities than others. We found a high degree of conservation awareness, but most people expressed negative conservation attitudes and almost all lost crops to wildlife. We highlight the complexity of conflict in the area and present a basis for electing a microsite planning approach for conservation and development in areas characterized by high ethnic diversity, high human population densities, and land-dependent large mammals that pose economic risks. The findings imply that highly localized development schemes and participatory approaches to resource management at the village level, coupled with greater efforts at education, are especially needed to achieve conservation and development goals in such cases.

Keywords

AssamConservation attitudesConservation awarenessKaziranga National Park and World Heritage SiteMicrosite analysisPark–people relations

Introduction

India is a nation of megadiversity and some of the highest rural human population densities on earth. The premier species (tiger, Indian rhinoceros, and the elephant) targeted for protection in areas such as Kaziranga National Park and World Heritage Site, Assam (KNP) are land-dependent megavertebrates, even while most of India’s 1.1 billion plus citizens are dependent in part on natural resource extraction. Conservation can, therefore, pose economic hardship on local people. The government has recognized 18 official languages with Hindi being most widely spoken. The social and demographic landscape is complex, rural lifestyles are marginal and resource competition can induce conflict. This is among the most difficult situations for conservation (Heinen 1996; Heinen and Low 1992). Due to movement of labor among provinces during British rule, many people in Assam are descendants of immigrants. They and others who immigrated more recently compete for resources with long-term residents of different ethno-religious groups, which further complicates resource management (e.g., Sah and Heinen 2001).

India has also been progressive for both conservation and social causes by implementing a national program to improve local livelihoods and conservation (Rao 1998). The Government of India (1983) recognized the multiple-use demands on lands bordering protected areas and recommended development inputs to reduce resource dependency. In 1996, the Global Environment Facility funded the India Ecodevelopment Project for US$67 million (World Bank 1996). Project reviews subsequently indicated that implementation was uneven and more site-specific research was recommended (WWF 1999), which was the impetus for our study.

Many studies have been completed in the Indian Subcontinent using household surveys to assess conservation awareness and attitudes as functions of economic and demographic variables to better understand park–people relationships (e.g., Allendorf 2007; Mehta and Heinen 2001; Nepal and Weber 1995; Sekhar 2003; Wang et al. 2006). Results vary by region, resource dependency, etc., but in general show that actual or perceived economic losses can decrease support for conservation programs. Culture, religion, and education also come into play in complex ways (e.g., Heinen 1993). To what degree conservation and development programs have been implemented, and people benefit (Baral and Heinen 2007) is also important.

This is the first study of its kind in KNP and was part of an effort that also studied resource uses and home gardening patterns (Shrivastava and Heinen 2005, 2007). The study is important due to the particularly high and diverse human population in KNP and its global importance for conservation when compared to other areas studied. Here we focus on awareness and attitudes as a function of demographic and socio-economic variability of villagers living near sites proposed as park Addition Areas (AAs; below). We ask the following general questions:
  • What is the demographic structure and socio-economic status of the human population in the periphery of KNP and the periphery of the AAs?

  • What can be predicted about the effects of prohibition of resource extraction from the AAs on local people?

  • Do local conservation attitudes and awareness differ with location of villages and what is the overall level of support for KNP and wildlife conservation?

  • Do any differences in attitudes and awareness among residents support a need for site-specific sustainable development interventions?

Methods

Study area

KNP is located in Naogaon and Golaghat districts in central Assam (Fig. 1) on the south bank of the Brahmaputra River. With a population of 26.6 million in 2000 (GOI 2001a), Assam has more than twice the combined population of the other six states in northeastern India; its population density (340/km2) is higher than India’s average (324/km2; GOI 2001b). Assam has a heterogeneous set of three unique social groups, commonly known as the hill tribes, plains tribes, and the non-tribals (Singh 1987; Table 1). Immigration has added to this complexity and resident–immigrant relations are a political concern (Chaudhuri 1982; Hazarika 1994).
https://static-content.springer.com/image/art%3A10.1007%2Fs11111-009-0086-0/MediaObjects/11111_2009_86_Fig1_HTML.gif
Fig. 1

Location of Kaziranga National Park and World Heritage Site and survey villages in Assam (adapted from GOA 1998)

Table 1

Ethno-religious profile of Naogoan and Golaghat Districts, Assam (1a) and the microsites (1b) sampled for this study. Numbers in Table 1b are percentages

Ethno-religious groups

District Golaghat

District Naogaon

Households in the study area (%)

Households surveyed N (%)

Households surveyed N (%)

a

 Brahmin

9 (2.4)

4 (1.8)

2.2

 Kshatriya

12 (3.2)

15 (6.9)

4.6

 Kayastha

105 (28.2)

13 (6)

20

 SCa

64 (17.2)

21 (9.6)

14.4

 Tribal

171 (46)

89 (40.8)

44.1

 Muslim

3 (0.8)

76 (34.9)

13.4

 Christian

8 (2.2)

0

1.3

Microsite

Brahmin and Kshatriya

Kayastha

SCa

Tribal

Muslim

Christian

b

 KNPP

5.1

23.4

14.4

36.4

20.6

0

 Area 1

36.4

12.1

6.1

30.3

15.2

0

 Area 2

5.2

21.6

14.9

51.5

0.7

6

 Area 3

0

3.7

25.9

70.4

0

0

 Area 4

7.1

2.4

11.9

78.6

0

0

aScheduled castes

High mean annual rainfall (up to 3,750 mm) from May to October influence vegetation patterns and floods occur frequently, displacing people and wildlife. Agriculture is the single largest occupation followed by tea estate employment. Rice accounts for two-thirds of cultivated land; other crops include oilseeds, legumes, betel-nut, coconut, and fruits. Fishing is common and sporadic conflicts occur over access and control of fisheries (Shrivastava and Heinen 2007). KNP, of global importance for tiger, elephant, and rhinoceros conservation (Rodgers and Panwar 1988; Government of Assam [GOA] 1998), is an IUCN category II—National Park (UNEP 1991). The area has been protected since 1908 and, in 2001–2002, over 46,000 tourists entered (UNESCO 2002). The flora is also very diverse and has been studied extensively (Kanjilal and Bor 1997; Hajra and Jain 1994).

Addition areas: sites in the periphery of Kaziranga

As a result of a major study on habitat loss and animal movements, The Wildlife Institute of India recommended an extension of KNP from 473.71 to 797.95 km2 in 1998 and the Assam government initiated the process of adding six Addition Areas (AAs; GOA 1998). Their status in January 2001, when the fieldwork for this study was completed, is described below.

Areas 1–4 and another area (Kaziranga National Park Periphery [KNPP]) were taken up for study (Fig. 1). Notification for AA1 (43.79 km2) was published by the State in 1997 and control had been handed over to the Forest Department. The State published notification for AA2 (6.47 km2) in 1985; in 1996, residents lost a case against eviction but final notification was stalled pending court orders. AA3, an elephant migratory corridor, lies between the highway and KNP in Golaghat District. Notification was published for 0.69 km2 in 1985 and compensation was paid but had not been disbursed. AA4 (0.89 km2) was notified in 1989 but compensation was unpaid pending a case brought by a tea plantation. The fifth and sixth AAs were not included for study. AA5 is a small (1.15 km2) tract of land adjacent to KNP and located near a tea estate. AA6 (367.5 km2), the largest, consists of the section of the Brahmaputra forming the park’s northern boundary, while we focus on the southern boundary along mammal migration corridors. A fifth site—villages within the 2-km southern boundary but not bordering any AA (i.e., KNPP)—was included for comparison.

Village selection, interview methods, and data analysis

The geography of KNP, location of AAs, and recommendations by the India Ecodevelopment Project (World Bank 1996) dictated that sampling be in a 40-km long by 2-km wide belt along the southern periphery. District revenue maps for 1989–1990 were obtained and villages within 2 km of KNP and AAs were identified: 20 in Naogaon and 25 in Golaghat. A further selection of villages immediately bordering KNP or AAs resulted in a sample of 37 villages: 14 in Naogaon and 23 in Golaghat. They were grouped into five microsites (Fig. 1; KNPP, and AA1 through AA4).

Two field assistants, one male and one female (both fluent in Assamese and Hindi), and the second author made up the field team. The questionnaire was adapted from Sah (1997) and pre-tested in September 2001. Secondary data (reports, etc.) were collected from KNP and local government offices. Interviews began in October 2000 and were completed in January 2001. We randomly sampled 10% of households per village. Interviews lasted 30–40 min and were voluntary. Conservation awareness questions were declined by 1.2% of respondents, while 0.5% declined to answer those on attitudes. A literate respondent was one having at least 1 year of schooling and illiteracy was defined as less than 1 year.

We estimated farm income for an average year and included the sale of cash crops and livestock calculated as the mean of incomes for 1999 and 2000, if known for both years. Otherwise, income for either year was used (Leones and Rozelle 1991). Livestock were converted into standardized units based on the mean sale price for each species in 1999–2000. The mean price for a cow (IRs. 2204.35) was considered 1 unit and other livestock were standardized to: buffalo, 2.9; bull, 1.5; calf, 0.8; pig, 0.4; goat, 0.25; duck, 0.05; and chicken, 0.03. Off-farm income included that from businesses, private, and government salaries and pensions. The ‘Labor’ category included full-time work such as daily wage in agriculture and road maintenance. The tea industry is the largest employer. Tea workers include those living on tea estates and those living in nearby villages; only the latter were surveyed. Land in shifting cultivation was not included and lands that were seasonally or perennially flooded or used only for thatch harvest or cattle grazing were classed as unproductive. Data were analyzed using SPSS Version 10.0 and Statistica 99 (StatSoft Inc.).

Results

We return to the study objectives to structure presentation of our results.

Demography and socio-economics of the study area and microsites

Of the 590 households sampled, 63% were in Golaghat and 37% in Naogaon. Districts had different ethno-religious composition (Table 1) but mean respondent age and household size were similar and comparable to Assam as a whole (GOI 1991). Illiteracy was highest among tribals and correlated with age (r = 0.245, P < 0.01). Only 2.9% were educated beyond 10th grade and almost half of female and one-third of male respondents were illiterate. Ethno-religious groups differed by occupation (Table 2); Muslims were the most likely to be in business. Farm income also varied among ethno-religious groups (F6,583 = 7.2, P < 0.01), with Muslims having the highest mean.
Table 2

Significant differences found between economic variables and ethno-religious groups across the entire sample

Variable

Chi-square

F

Degrees of freedom

Significance (P)

Occupation

94.16

 

20

<0.001

Farm income

 

7.2

6 (n = 583)

<0.01

Livestock holdings

 

10.3

5 (n = 563)

<0.001

Mean land holdings (ha)

 

3.03

5 (n = 585)

<0.05

Resident/immigrant

96.9

 

5

0.001

Livestock holdings varied among ethno-religious groups (F5,563 = 10.3, P < 0.001). We categorized standard livestock holdings into low, medium, and high, and half of households were in the low category (less than 5 units). Mean land holdings varied among ethno-religious groups (F5,585 = 3.03, P = 0.01); land ownership rate was highest among Brahmins (84.6%), followed by tribals, but the mean area was highest among Kshatriyas (1.2 ha). Land holdings and household size were also positively correlated (r = 0.220, P < 0.01). Although only 62% of Muslims were landowners, they had the highest percent of cropped land (80.5%). The frequency of immigrants also differed among ethno-religious groups (χ2 = 96.9, df = 5, P < 0.001). Christians had the lowest percentage of immigrants, while Muslims had the highest.

We combined the upper three Hindu castes and excluded Christian households due to low sample size and found that ethno-religious groups were different among sites (Table 3); tribals dominated all except AA1 and KNPP. Neither the percent of literate respondents nor household income varied among sites. The sites differed by occupation (χ2 = 66.3, df = 12, P < 0.01); AA2 had the highest percentage in agriculture and labor, while AA1 had the highest in business. Farm incomes were highest in KNPP, AA1 and AA4 while off-farm incomes were highest where more respondents worked on tea estates. The proportion of lease-holders and landless differed among sites (χ2 = 24.6, df = 4, P < 0.01) as did landholdings (F4,585 = 2.87, P < 0.05). AA1 had the lowest percentage of lease-holders and the highest percentage of respondents in the small-landholding category (0.0–0.49 ha). AAs also differed in the frequency of periodic, annual, and landless categories (χ2 = 47.8, df = 8, P < 0.01); KNPP had the highest percentage of periodic-leaseholders. Livestock units also varied (F4,585 = 4.81, P < 0.001), with AA1 having the highest; livestock and land holdings were correlated (r = 0.246, P = 0.01). The ratio of residents to immigrants varied among sites; AA1 had the highest percentage of immigrants (66.7%) and AA4 the lowest (26.2%). KNPP had the highest percentage of immigrants from villages within the same district, while AA2 had the highest percentage from other districts in Assam.
Table 3

Significant differences found among microsites for economic and demographic variables

Variable

Chi-square

F

Degrees of freedom

Significance (P)

Ethnicity

82.6

 

12

<0.001

Occupation

66.3

 

12

<0.01

Land owner/landless

24.6

 

4

<0.01

Mean land holdings (ha)

 

2.87

4 (n = 585)

<0.05

Land tenure

47.8

 

8

<0.01

Livestock holdings

 

4.81

4 (n = 585)

<0.001

Resident/immigrant

20

 

4

<0.001

Conservation awareness

Respondents were asked nine questions concerning restrictions on resource extraction from KNP. The resources were fuelwood, fodder, tree lopping, timber, poles, thatch, edible plants, medicinal plants, and livestock grazing. Positive responses (aware of the restriction) were assigned one point, while negative responses (unaware) and no response were assigned zero; 584 respondents gave valid answers. Individual villages scores ranged from 0.71 to 1.0 with a mean of 0.94. Scores were summed for each of the nine questions and divided by the maximum possible to obtain cumulative awareness scores for each question that ranged from 0.86 to 1.0. To determine if awareness varied by site and other factors, respondents were divided into two groups: those who were aware of all restrictions (72.6%) and those who were not (27.4%).

Awareness varied among the five sites (Table 4). KNPP had the highest scores and AA3 the lowest. Awareness did not vary by gender, literacy, or age but ethno-religious group was an important predictor: 96% of Muslims but only 50% of Christians were fully aware, with other groups in between. Awareness varied with occupation (χ2 = 13.59, df = 5, P = 0.018); salaried respondents had the highest score, while laborers and tea workers had the lowest. Farm and off-farm income showed no relationship with awareness, nor did landholding size. Awareness varied with land tenure (χ2 = 21.77, df = 3, P < 0.001). Of periodic leaseholders, 78.1% were aware when compared to 54.2% of annual leaseholders. Respondents with fewer livestock were more aware of restrictions (r = −0.121, P = 0.004). Awareness also varied with immigrant’s place of origin (χ2 = 8.33, df = 3, P = 0.04) but not with immigration status. Immigrants from within KNP had the lowest scores and out-of-state immigrants, the highest.
Table 4

Significant differences in conservation awareness scores across microsites, ethnicity, economic variables and immigration

Variable

Chi-square

Degrees of freedom

Significance (P)

Microsites

11.58

4

<0.05

Ethnicity

27.62

5

<0.001

Occupation

13.59

5

<0.05

Land tenure

21.77

3

<0.001

Immigrant’s place of origin

8.33

3

<0.05

Conservation attitudes

The final section of the survey had eight questions on: (i) support for KNP, (ii) costs and benefits of KNP, (iii) large mammal conservation, (iv) attitudes toward the AAs and (v) the management of KNP. There were 587 valid respondents. Positive responses scored one point, ambiguous responses (e.g., ‘don’t know’) scored half a point and negative responses scored zero. Scores of individual villages ranged from 0.31 to 0.81 with a mean of 0.49 and they differed between districts (F1,35 = 4.78, P = 0.04). Scores on all questions were summed and divided by the maximum possible to obtain cumulative scores ranging from 0.24 to 0.77 out of a maximum of 1.0. Only three questions: respondent’s support for KNP; the significance of AAs for large mammals; and more protected area required for large mammals, obtained an attitude score higher than 0.50. The two questions that pertained to benefits from KNP and support for AAs obtained the lowest scores. Respondents were divided into two groups based on their scores on an 8-point scale: those scoring 4 or below (58.3%: unfavorable attitude) and those scoring above 4 (41.7%: favorable attitude). These were used to study any relationships with attitudes and other variables.

There were differences in attitudes among sites (Table 5) but attitudes were generally negative in all. KNPP had the highest percentage of favorable respondents (47.6%), while AA2 had the lowest (27.1%). Ethno-religious groups also differed with Kayasthas having the most favorable scores (59.3%). All other groups held predominantly unfavorable attitudes. Age was not correlated with attitude, but education was (r = 0.116, P = 0.005) and scores varied with occupation (χ2 = 13.86, df = 5, P = 0.017). In the business class, 69.2% held favorable attitudes when compared to 33.8% of tea workers. Attitudes were correlated with total income (r = 0.151, P < 0.01) and off-farm income (r = 0.164, P < 0.01) but not with farm income. Attitudes were not related to land or livestock holdings, land tenure, or immigration status. Awareness and attitude scores were negatively correlated (r = −0.133, P < 0.01) and the AAs held more negative attitudes than KNPP (Fig. 2). Wildlife depredation was widespread in the area, with 96% of respondents reporting losses. Attitudes were more favorable among respondents who did not report wildlife losses, did not fish, and/or did not use timber or thatch (Table 5). Of respondents who did not report wildlife losses, 64% held favorable attitudes when compared to 41% of those who did.
Table 5

Significant differences in conservation attitude scores across microsites, ethnicity, and economic variables

Variable

Chi-square

F

Degrees of freedom

Significance (P)

Microsites

17.3

 

4

<0.005

Ethnicity

25.39

 

5

<0.01

Occupation

13.86

 

5

<0.05

Wildlife depredation (yes/no)

 

3.86

1 (n = 585)

=0.05

Fisherman (yes/no)

9.79

 

1

<0.05

Timber use (yes/no)

12.42

 

1

<0.001

Thatch use (yes/no)

6.79

 

1

=0.005

Reed use (yes/no)

9.51

 

1

<0.05

https://static-content.springer.com/image/art%3A10.1007%2Fs11111-009-0086-0/MediaObjects/11111_2009_86_Fig2_HTML.gif
Fig. 2

Inverse relationship between attitude and awareness scores within the 37 villages surveyed. Each symbol in the figure represents one village

Discussion

Northeastern India represents the quintessential population-environment challenge as related to conservation and development: high biological diversity, charismatic large mammals, and a wealth of natural resources, along with a dense and highly diverse human population and the need to develop economically. Despite the government’s attempts, Assam lags behind other parts of India on several indicators (GOI 2002). The World Bank (1994) credit for agricultural improvement in Assam, the emergence of HIV/AIDS and increasing prevalence of malaria and Japanese encephalitis (Prakash et al. 1997) and immigration are factors with indeterminate influences on land use, forest cover, and conservation (e.g., Fearnside 1997). Particularly in Assam, demographic studies are constrained by the political sensitivity of immigration, and others (e.g., Baruah 1994; Singh 1987) have explored the influence of state-to-state and cross-border immigration on its polity and demography.

There is debate about the impact of natural population growth and immigration on resource use. For example, outside competition for gum collection is thought to lead the Chenchu in central India to exploit Sterculia urens to the point of endangerment (Devarapalli and Kumar 1999) and mechanisms within tribal societies that prevent over use do not function when users include those without allegiance to tribal law (Gadgil et al. 1993). Degradation can be avoided by a change to other more productive subsistence systems (Boserup 1990), but this is less achievable in fluid social circumstances.

Demographic and socio-economic differences among microsites

In a study of relationships between Hindu castes and three indicators of social status: land holdings, income, and literacy in two districts in Assam, hierarchy and land holdings were positively but insignificantly correlated, but the correlation was significant with income and percent literacy (Chauhan 1980). The conclusion was that caste hierarchy and socio-economic development are not independent. Our study looked at a more complete ethno-religious profile and found that ethno-religious groups differed based more on physical assets such as land and livestock. We found demographic composition to vary within the study area and broadly divide it into two: the first is KNPP and AA1 where no one group dominated, and the second is AAs 2, 3, and 4 with tribal majorities. Indigenous and tea-tribes together were the largest group (44.1%).

Broadly, demographic differences among sites were due to geography, availability of and access to arable land and the chronological sequence and pattern of settlement. Upper caste Hindus and Muslims settled the fertile Brahmaputra floodplain (Chaudhuri 1982), while tribals mainly settled the Karbi foothills. Variables we found to be important in affecting attitudes and awareness both among ethno-religious groups and sites were: occupation, livestock holdings, incidence of land ownership, size of land holdings, and the proportion of residents to immigrants. Our results also show that different sets of variables may be responsible for variation among ethno-religious groups on one hand and among sites on the other. For example, literacy, total income and immigration status varied significantly among ethnic groups, but not among sites.

The 2-km belt around the park periphery reflects contradictions and inequalities. Residents had relatively large land holdings mostly under legal lease agreements. KNPP also had the highest immigrant population, and new immigrants had small land holdings and settled closest to KNP, a finding consistent with others exploring immigration patterns near protected areas in developing countries (e.g., Wittemyer et al. 2008). Productive land around KNP has been appropriated and new immigrants have little option but to homestead on small plots near the park. The implications are twofold: increasing numbers of households in low-lying KNPP are at risk of flood damage, and conflict between wildlife, livestock, and people is certain to require intervention in this area.

Awareness widespread but attitudes mixed

Within the high levels of conservation awareness found here, residents were most aware of the ban on tree lopping and medicinal plant collection followed by fuelwood collection, fodder harvest, and grazing. Significant differences in awareness existed between sites; KNPP was classed as high-awareness while AA3 was low. Demography, occupation, land tenure, and migrant’s place of origin were also associated with awareness scores. Our results imply that different demographic groups internalize regulations differently; regulations impact groups to different degrees and ultimately govern interactions with park authorities and influence attitudes. We found that high levels of regulatory awareness can be accompanied by negative conservation attitudes, yet attitudes toward KNP were largely positive. However, dissatisfaction was common on the issue of deriving benefits from the park and park enlargement, even though there was general agreement that large mammals needed more protected habitat.

Differences in conservation attitudes were found among sites, but they were generally unfavorable in all. However, people in KNPP exhibited attitudes somewhat more favorable in spite of high crop losses. Literacy and education were positively correlated with conservation attitudes indicating the role that education can play in influencing park–people relations (Heinen 1993). Education also influences occupation (a predictor of attitude), and, in rural India, it is often affected by ethno-religious factors.

Conclusions

Our data show that sites differed with respect to most variables studied. Local variability within ethno-religious groups, livestock holdings, land holdings, land tenure, immigration status, wildlife depredation, and attitudes all are important in developing conservation and development proposals for peripheral villages. KNP is a remnant of the Brahmaputra floodplain ecosystem and corridors to the Karbi Hills are crucial for animal migration during floods; for national and global conservation aims, they must be maintained and their management will depend on local acceptance.

This study brings forward several salient points and recommendations. Conservation attitudes supportive of KNP, but unfavorable of the AAs or of material benefits from KNP, stem from a loss of access to fishing and natural resources, wildlife depredation, and in some cases perceptions of village relocation. There is a need to improve attitudes toward the AAs by positive public engagement. Fishing access is likely to continue as a source of conflict and pond-fisheries development must be explored. Since attitudes frequently improve with education, revenues (e.g., from tourism) should be used to expand conservation education programs in local schools and civic groups. In general, efforts at the local level are needed to provide educational and employment opportunities if attitudes toward conservation are to be supportive in the long term (Borgerhoff Mulder and Coppolollo 2006; Heinen and Mehta 2000).

Following the resolution on Joint Forest Management (JFM) of 1990 (GOI 2005) the GOA adopted guidelines for the constitution of Forest Protection and Regeneration Committees with the involvement of NGOs and village councils. Although the efficacy of JFM (Jagannadha et al. 2005) and its ability to empower (Bhattacharya and Basnyat 2003) remain uneven, it provides a framework for constituting user committees for planning and resource management. We further suggest a microsite-based planning approach on the basis of high demographic and socio-economic variability. Incorporating economic incentives and targeting development interventions (e.g., Heinen 1996), are especially necessary in KNP due to: (1) differences in resource use patterns by site, (2) extractive patterns among sites that result from highly fluid populations, (3) high ethno-religious diversity, (4) high human population densities, and (5) wildlife populations that cause crop damage, to achieve the simultaneous conservation and development goals around this remarkable protected area.

Acknowledgments

We thank the interviewees and the Assam State Forest Department for granting permission. D. M. Singh, U. Bora, P. S. Das, D. D. Boro, and R. Sarma from KNP provided valuable insights and P. K. Malik of the Wildlife Institute of India facilitated the fieldwork. Nasser Ahmed and family were gracious hosts during visits to Guwahati and Debajit, Jyotishmita and Ronjoy proved very able field assistants. The National Geographic Society funded the fieldwork and a WWF-US Education for Nature fellowship funded the second author. Florida International University’s Human Subjects Review Panel approved this study.

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© Springer Science+Business Media, LLC 2009