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Land-useland-cover change and fragmentation in theNameri Tiger Reserve IndiaAnup Saikia a Rubul Hazarika b amp Dhrubajyoti Sahariah aa Department of Geography Gauhati University Guwahati 781014 Indiab Department of Geography BBorooah College Guwahati 781007 IndiaPublished online 24 May 2013

To cite this article Anup Saikia Rubul Hazarika amp Dhrubajyoti Sahariah (2013) Land-useland-cover change andfragmentation in the Nameri Tiger Reserve India Geografisk Tidsskrift-Danish Journal of Geography 1131 1-10 DOI101080001672232013782991

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Land-useland-cover change and fragmentation in the Nameri Tiger Reserve India

Anup Saikiaa Rubul Hazarikab and Dhrubajyoti Sahariaha

aDepartment of Geography Gauhati University Guwahati 781014 India bDepartment of Geography BBorooah CollegeGuwahati 781007 India

(Received 15 July 2012 final version received 25 February 2013)

Land-useland-cover change is an important agent of ecological degradation in tropical areas where forests are underthreat from the pressure of human activities This study assesses land-use change (1973ndash2007) in the Nameri TigerReserve (NTR) in Assam India using Landsat imageries Dense forests decreased sharply while open forest increasedmarginally The increases in the degraded and open forest categories occurred at the expense of dense forests whichdecreased at an average annual rate of 288 ha year1 or at 056 annually The number of patches in the NTR landscaperecorded a fivefold increase indicating a high degree of fragmentation of the habitat While the number of patches of thedense forests increased by 338 from 270 in 1973 to 1138 in 2007 at an annual rate of increase of 99 per annumtheir mean patch area declined from 1909 to 1282 ha Both class- and patch-level changes corroborate the trend of frag-mentation with a consistent increase in the number of smaller patches Encroachment by small farmers has been the chiefagent in the conversion of dense forest into degraded forest

Keywords land-useland-cover change fragmentation landscape metrics Nameri Tiger Reserve Assam

Introduction

Tropical forests are of intrinsic importance to life onearth and provide numerous ecological social-culturaland economic functions The utility of these landscapesto function as carbon sinks may further enhance theirvalue All over the world ecosystems have been rapidlytransformed in the post-2000 period by human popula-tions through increasingly permanent uses of land (Elliset al 2010) Forests are important on account of theirbiodiversity maintenance and livelihood provisioningservices in addition to the reducing emissions fromdeforestation and forest degradation+ (enhancing forestcarbon stocks) benefits (Mertz et al 2012)

Like other ecosystems tropical forests also continueto decline at varying rates and instances wherein gainsrather than losses are made are more the exception thanthe rule Large-scale deforestation probably imperilsglobal biodiversity more than any other contemporaryphenomenon (Laurance et al 2012) but the fact thateven small changes in the extent of tropical forests canhave impacts on climate biodiversity and human well-being (Banfai amp Bowman 2007) is often not sufficientlyappreciated This is especially true in developing countrycontexts where forests are poorly inventoried and moni-tored and yet these are the forests where currentpressures are much more severe than elsewhere Forestdecline cannot be explained based on a simple causal

explanation (Dessie amp Kinlund 2007) and a multitudeof factors are at play often operating at different scalesHowever understanding the relative importance of multi-ple drivers that affect landscape patterns is a challengeand while case studies tend to focus on one or fewdominant drivers (Turner 2005) meta-analyses havebeen useful to identify the most important drivers ofchange eg van Vliet et al (2012)

Land-useland-cover (LULC) change is of muchinterest in environmental analyses (Bradley amp Mustard2005 Geist amp Lambin 2001 Turner 2001) since land-use change may contribute to ecological degradation(Hunsaker et al 1994) and is considered one of themost important variables of global ecological change(Houet et al 2010 Sivrikaya et al 2007 Vitousek1994) LULC change affects everything from aerosolsand biodiversity to the global carbon and hydrologiccycles (Skole et al 2004) Frequently a distinction ismade between two facets of LULC viz land-covermodification (which affects the character of the landcover without changing its overall classification) andland-cover conversion (which brings complete replace-ment of one cover type by another) with the formerbeing generally more prevalent (Coppin et al 2004Lambin et al 2003) LULC change can be generated byeither natural or human-induced factors or by a combina-tion of the two (Coppin et al 2004 Mannion 2002) In

Corresponding author Email asaikiagauhatiacin

Geografisk Tidsskrift-Danish Journal of Geography 2013Vol 113 No 1 1ndash10 httpdxdoiorg101080001672232013782991

2013 Taylor amp Francis

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any case landscape patterns that accrue from LULCchange result from complex relationships among multiplefactors abiotic and biotic of which disturbance succes-sion and human use of the land are key drivers (Turner2005) In the LULC change scenario tropical areas areparticularly important

In fact nowhere are human-mediated changes in landcover affecting global processes more than in the tropics(Skole et al 2004) and rainforests are threatenedthroughout the tropics by human activities although theintensity of each threat varies by region (Corlett ampPrimack 2008) Globally most rainforest destruction stillresults from small-scale crop cultivation by poor farmerstypically migrants from other rural areas in the samecountry (Corlett amp Primack 2008)

Understanding the links between LULC andlandscape pattern is pivotal to increasing effective landmanagement and environmental sustainability (Sivrikayaet al 2007) and quantifying landscape pattern usinglandscape metrics has been a method of assessing land-use change in several studies (Cakir et al 2008 Leleet al 2008 Li et al 2001) following the developmentof a wide array of landscape indices

An understanding of the relationship between habitatloss fragmentation and population viability for differentspecies is imperative if conservation efforts are to besuccessful (Fahrig 2001) all the more so in the tropicswhere forest cover losses are particularly severe (Achardet al 2002 Sivrikaya et al 2007) This study analysesthe spatial and temporal patterns of LULC in the NameriTiger Reserve (NTR) in Indiarsquos north eastern state ofAssam Changes in the major land-use categories wereassessed using satellite data during the period 1973ndash2007 The classified images were analysed using thespatial statistics programme Fragstats to assess landscapemetrics at class and patch level using commonly usedlandscape indices

The study area

The seven states of Arunachal Pradesh Assam ManipurMeghalaya Mizoram Nagaland and Tripura comprisethe north eastern region (NER) of India Compared tothe rest of the Indian mainland the NER was broughtunder British rule relatively late in 1826 and transportcommerce and trade were less developed in this regionthan elsewhere (Saikia 2004) Although deforestationand forest degradation occurred more slowly in the faceof limited accessibility it also meant that governmentcontrol of expanding tea plantations established oncleared forest lands and the encroachment of immigrantsrsquopeasants from present-day Bangladesh onto forest landswere much more ineffective (Tucker 1988a) Addition-ally the opening of timber mills during the 1920s alongwith the grant of long-term leases on lsquoexceptionally

favourable termsrsquo to Marwari and Bengali contractorsresulted in the commercialization of the upper Assamforests (Tucker 1988b)

While many parts of the NER started experiencingforest losses under colonial rule (Tucker 1988a) land-scapes such as Nameri given the lack of access by roadremained largely unaffected till the mid-twentiethcentury Even the tea industry which spread over exten-sive tracts and resulted from clearing of forest areas forthe establishment of tea estates across the Brahmaputravalley starting from the latter part of the nineteenthcentury including the Sonitpur district in which theNTR is situated allowed the latter to remain unscathed

The NTR established in 1999 extends over an areaof 358 km2 and its core area consists of a 200 km2 zonedesignated as the Nameri National Park (NNP) that wasset up 1998 Tucked away in the foothills of the EasternHimalayas and girdled by the Jia Bhoroli and Dikorairivers on two sides (Figure 1) Nameri is home to a vari-ety of fauna avifauna and flora Two flagship speciesthe tiger and the elephant are also present in thisprotected territory although census counts do not exist

In recent decades smallholder agriculturalists wereencouraged to settle in the NTR much like other north-ern reaches of the Sonitpur district that were until thendensely forested Beginning with the 1990s a plannedinflux of population into the Sonitpur district took placeto claim lands as part of a larger strategy of ethnic domi-nance by the Bodo tribe of the state (Hazarika amp Saikia2013) There was a lack of political will in preventingthe protected areas succumbing to the sustainedencroachment by these small agriculturalists in Sonitpur(Gureja et al 2002)

In the tiger reserve there is official recognition ofthe problem of encroachers and the annual budgetarysanction of funds for the NTR during 2006ndash2007 madegrants for the eviction of encroachers over areas of 15and 30 km2 of the core and buffer areas respectively(Comptroller and Auditor General of India 2006)Assam has by far the largest encroached area among allthe states of India with 12690 ha of protected NationalPark (NP) area in Assam encroached out of a total of17138 ha under encroachment in all 20 NPs in Indiaaccording to data provided (as an answer to a question)in the Indian Parliament (Saikia 2008) Unfortunatelydisaggregated information regarding encroachmentlevels in specific protected areas and their buffers isunavailable

Following the release of a comprehensive country-wide study on the status of tigers and their habitats inIndia (Jhala et al 2008) it became apparent thataccurate and updated LULC information was necessaryas a prerequisite to effective management and planningof protected landscapes Habitat information and aspatio-temporal assessment of the NTR seemed overdue

2 A Saikia et al

Dow

nloa

ded

by [

The

Uni

vers

ity o

f M

anch

este

r L

ibra

ry]

at 0

849

09

Dec

embe

r 20

14

and herein lay the rationale for the study While previousstudies did exist (Forest Survey of India [FSI] 20032005 2012 Khushwaha amp Hazarika 2004 Lele et al2008 Roy amp Joshi 2002) these were at macro scales ofanalysis and not specific to the NTR

Data

In addition to characterizing a landscape into variousland-use categories there is a need to consider their

spatial distribution and arrangement and their landscapemetrics (Herzog amp Lausch 2001) Hence in addition todetermining LULC change in the NTR assessing thedegree of fragmentation of its landscape using suitablelandscape metrics was necessary A focus on spatialheterogeneity in landscape ecology studies emerged inthe 1980s when spatial data and analysis methodsbecame widely available (Turner 2005) and quantifyinglandscape structure is a prerequisite to understandinglandscape dynamics (Cakir et al 2008 Cardille amp

Figure 1 The location of the NTR in Assam India (insets) and LULC of the NTR during 1973

Geografisk Tidsskrift-Danish Journal of Geography 3

Dow

nloa

ded

by [

The

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vers

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f M

anch

este

r L

ibra

ry]

at 0

849

09

Dec

embe

r 20

14

Turner 2002 Li et al 2001) Since no single metric cansufficiently capture the pattern of a given landscape(Turner 2005) this study uses a range of metrics tointerpret the pattern of the NTR landscape

The satellite data used are shown in Table 1 Thesatellite imageries covering the area were georeferencedand training areas were created based on ground truthingfrom within the study area but outside the NNP limitsCare was taken to ensure well-distributed training setsand when selecting clusters of a class the variabilitywithin that class (in the image) were taken into accountto cover for possible differences in soil conditions Thustraining areas were selected taking different representa-tive pixel samples The number of observations per clus-ter was kept to a minimum of 30 per band (Janssen ampHuurneman 2001) and it was ensured that clusters in thedata did not overlap The separability of classes waschecked prior to running the classification A maximumlikelihood algorithm was run using the Erdas Imagine87 (wwwerdascom) programme The LULC categoriesthat were delineated are shown in Table 2

Attribute accuracy is one of the most critical factors indetermining the fitness for use of geographic data and isobtained by comparing values of sample spatial data unitswith reference data obtained either by field checks or fromsources of data with a higher degree of accuracy (Lo ampYeung 2002) In this study field checks were preferredsince an accurate map was unavailable In estimatingaccuracy sample points were compared with ground truthverification data that was generated using a hand-heldglobal positioning system device Sample points wereused in view of time cost and physical accessibilityconsiderations Accuracy assessment verification usingstandard measures such as user accuracy producer

accuracy and Kappa accuracy were performed to assessthe correctness of the classifications Accuracy assess-ments showed encouraging results ranging from an overallaccuracy of 8833 for 1973 to 9000 for 1988 and2007 respectively and Kappa accuracy of 86 88 and88 for 1973 1988 and 2007 respectively

The spatial dynamics of a landscape refers to spatialarrangement of the patches in a landscape and their tem-poral changes in terms of the size adjacency proximityand richness of patches These landscape metrics werederived using the programme Fragstats (McGarigal et al2012) While landscape metrics offer a wide variety ofindices with which a landscape can be analysed we havelimited our choice of indices based on a perusal of forestfragmentation studies (Cakir et al 2008 Galicia et al2008 Hargis et al 1998 Keles et al 2008 OrsquoNeillet al 1988 Sivrikaya et al 2007) and used the follow-ing indices (a) number of patches (NP) (b) per cent oflandscape (PLAND) the percentage of landscape in aparticular class or patch type (c) mean patch size (MPS)the average patch size in a particular class or patch type(d) largest patch index (LPI) the percentage of the land-scape comprised by the largest patch (e) edge density(ED) the sum of the lengths of all edge segments on aper unit area basis Annual deforestation rates werecalculated using the compound interest rate formula(Puyravaud 2003 Vuohelainen et al 2012)

P frac14 100

etht2 t1THORN

In ethA2=A1THORN

where P is percentage of forest loss per year and A1 andA2 are the amount of forest cover at time t1 and t2respectively

Results and discussion

Changes in the Nameri landscape are apparent from theLULC maps of 1973 1988 and 2007 (Figures 1ndash3)respectively Land-cover modification rather than land-cover conversion is apparent in the NTR although in theeastern part of the study area the change closely resem-bles land-cover conversion since the dense forest of1973 has been almost entirely decimated and replaced bynon-forest The most important changes relate to that ofthe dense forest category the area of which decreasedfrom 24985 in 1973 to 15171 ha over the 34 year period(Table 3) Further the rate of loss of dense forest wassubstantially higher during 1988ndash2007 relative to theearlier years The average rate of deforestation was288 ha year1 amounting to a rate of loss of 484year1 using the compound interest rate formula All theother land-use categories increased with open forestsregistering the maximum gain in proportionate terms anddegraded forest in absolute terms

Table 1 Satellite data used in the LULC classification

SatelliteNumber of

bandsResolution

(m)Pathrow

Observationdate

Landsat 1 4 80 14641 16 November 1973Landsat 5 7 30 13641 25 October 1988Landsat 7 8 30 13641 23 January 2007

Table 2 Description of LULC categories

LULC category Description

Dense forest (DF) Forest areas with crown density greaterthan 40

Open forest (OF) Forest areas with crown density greaterthan 10

Degraded forest(DeF)

Forest areas with crown density lessthan 10

Non-forest (NF) Agricultural land including homesteadsRiver amp sand banks

(RSB)River with sand banks

4 A Saikia et al

Dow

nloa

ded

by [

The

Uni

vers

ity o

f M

anch

este

r L

ibra

ry]

at 0

849

09

Dec

embe

r 20

14

any case landscape patterns that accrue from LULCchange result from complex relationships among multiplefactors abiotic and biotic of which disturbance succes-sion and human use of the land are key drivers (Turner2005) In the LULC change scenario tropical areas areparticularly important

In fact nowhere are human-mediated changes in landcover affecting global processes more than in the tropics(Skole et al 2004) and rainforests are threatenedthroughout the tropics by human activities although theintensity of each threat varies by region (Corlett ampPrimack 2008) Globally most rainforest destruction stillresults from small-scale crop cultivation by poor farmerstypically migrants from other rural areas in the samecountry (Corlett amp Primack 2008)

Understanding the links between LULC andlandscape pattern is pivotal to increasing effective landmanagement and environmental sustainability (Sivrikayaet al 2007) and quantifying landscape pattern usinglandscape metrics has been a method of assessing land-use change in several studies (Cakir et al 2008 Leleet al 2008 Li et al 2001) following the developmentof a wide array of landscape indices

An understanding of the relationship between habitatloss fragmentation and population viability for differentspecies is imperative if conservation efforts are to besuccessful (Fahrig 2001) all the more so in the tropicswhere forest cover losses are particularly severe (Achardet al 2002 Sivrikaya et al 2007) This study analysesthe spatial and temporal patterns of LULC in the NameriTiger Reserve (NTR) in Indiarsquos north eastern state ofAssam Changes in the major land-use categories wereassessed using satellite data during the period 1973ndash2007 The classified images were analysed using thespatial statistics programme Fragstats to assess landscapemetrics at class and patch level using commonly usedlandscape indices

The study area

The seven states of Arunachal Pradesh Assam ManipurMeghalaya Mizoram Nagaland and Tripura comprisethe north eastern region (NER) of India Compared tothe rest of the Indian mainland the NER was broughtunder British rule relatively late in 1826 and transportcommerce and trade were less developed in this regionthan elsewhere (Saikia 2004) Although deforestationand forest degradation occurred more slowly in the faceof limited accessibility it also meant that governmentcontrol of expanding tea plantations established oncleared forest lands and the encroachment of immigrantsrsquopeasants from present-day Bangladesh onto forest landswere much more ineffective (Tucker 1988a) Addition-ally the opening of timber mills during the 1920s alongwith the grant of long-term leases on lsquoexceptionally

favourable termsrsquo to Marwari and Bengali contractorsresulted in the commercialization of the upper Assamforests (Tucker 1988b)

While many parts of the NER started experiencingforest losses under colonial rule (Tucker 1988a) land-scapes such as Nameri given the lack of access by roadremained largely unaffected till the mid-twentiethcentury Even the tea industry which spread over exten-sive tracts and resulted from clearing of forest areas forthe establishment of tea estates across the Brahmaputravalley starting from the latter part of the nineteenthcentury including the Sonitpur district in which theNTR is situated allowed the latter to remain unscathed

The NTR established in 1999 extends over an areaof 358 km2 and its core area consists of a 200 km2 zonedesignated as the Nameri National Park (NNP) that wasset up 1998 Tucked away in the foothills of the EasternHimalayas and girdled by the Jia Bhoroli and Dikorairivers on two sides (Figure 1) Nameri is home to a vari-ety of fauna avifauna and flora Two flagship speciesthe tiger and the elephant are also present in thisprotected territory although census counts do not exist

In recent decades smallholder agriculturalists wereencouraged to settle in the NTR much like other north-ern reaches of the Sonitpur district that were until thendensely forested Beginning with the 1990s a plannedinflux of population into the Sonitpur district took placeto claim lands as part of a larger strategy of ethnic domi-nance by the Bodo tribe of the state (Hazarika amp Saikia2013) There was a lack of political will in preventingthe protected areas succumbing to the sustainedencroachment by these small agriculturalists in Sonitpur(Gureja et al 2002)

In the tiger reserve there is official recognition ofthe problem of encroachers and the annual budgetarysanction of funds for the NTR during 2006ndash2007 madegrants for the eviction of encroachers over areas of 15and 30 km2 of the core and buffer areas respectively(Comptroller and Auditor General of India 2006)Assam has by far the largest encroached area among allthe states of India with 12690 ha of protected NationalPark (NP) area in Assam encroached out of a total of17138 ha under encroachment in all 20 NPs in Indiaaccording to data provided (as an answer to a question)in the Indian Parliament (Saikia 2008) Unfortunatelydisaggregated information regarding encroachmentlevels in specific protected areas and their buffers isunavailable

Following the release of a comprehensive country-wide study on the status of tigers and their habitats inIndia (Jhala et al 2008) it became apparent thataccurate and updated LULC information was necessaryas a prerequisite to effective management and planningof protected landscapes Habitat information and aspatio-temporal assessment of the NTR seemed overdue

2 A Saikia et al

Dow

nloa

ded

by [

The

Uni

vers

ity o

f M

anch

este

r L

ibra

ry]

at 0

849

09

Dec

embe

r 20

14

and herein lay the rationale for the study While previousstudies did exist (Forest Survey of India [FSI] 20032005 2012 Khushwaha amp Hazarika 2004 Lele et al2008 Roy amp Joshi 2002) these were at macro scales ofanalysis and not specific to the NTR

Data

In addition to characterizing a landscape into variousland-use categories there is a need to consider their

spatial distribution and arrangement and their landscapemetrics (Herzog amp Lausch 2001) Hence in addition todetermining LULC change in the NTR assessing thedegree of fragmentation of its landscape using suitablelandscape metrics was necessary A focus on spatialheterogeneity in landscape ecology studies emerged inthe 1980s when spatial data and analysis methodsbecame widely available (Turner 2005) and quantifyinglandscape structure is a prerequisite to understandinglandscape dynamics (Cakir et al 2008 Cardille amp

Figure 1 The location of the NTR in Assam India (insets) and LULC of the NTR during 1973

Geografisk Tidsskrift-Danish Journal of Geography 3

Dow

nloa

ded

by [

The

Uni

vers

ity o

f M

anch

este

r L

ibra

ry]

at 0

849

09

Dec

embe

r 20

14

Turner 2002 Li et al 2001) Since no single metric cansufficiently capture the pattern of a given landscape(Turner 2005) this study uses a range of metrics tointerpret the pattern of the NTR landscape

The satellite data used are shown in Table 1 Thesatellite imageries covering the area were georeferencedand training areas were created based on ground truthingfrom within the study area but outside the NNP limitsCare was taken to ensure well-distributed training setsand when selecting clusters of a class the variabilitywithin that class (in the image) were taken into accountto cover for possible differences in soil conditions Thustraining areas were selected taking different representa-tive pixel samples The number of observations per clus-ter was kept to a minimum of 30 per band (Janssen ampHuurneman 2001) and it was ensured that clusters in thedata did not overlap The separability of classes waschecked prior to running the classification A maximumlikelihood algorithm was run using the Erdas Imagine87 (wwwerdascom) programme The LULC categoriesthat were delineated are shown in Table 2

Attribute accuracy is one of the most critical factors indetermining the fitness for use of geographic data and isobtained by comparing values of sample spatial data unitswith reference data obtained either by field checks or fromsources of data with a higher degree of accuracy (Lo ampYeung 2002) In this study field checks were preferredsince an accurate map was unavailable In estimatingaccuracy sample points were compared with ground truthverification data that was generated using a hand-heldglobal positioning system device Sample points wereused in view of time cost and physical accessibilityconsiderations Accuracy assessment verification usingstandard measures such as user accuracy producer

accuracy and Kappa accuracy were performed to assessthe correctness of the classifications Accuracy assess-ments showed encouraging results ranging from an overallaccuracy of 8833 for 1973 to 9000 for 1988 and2007 respectively and Kappa accuracy of 86 88 and88 for 1973 1988 and 2007 respectively

The spatial dynamics of a landscape refers to spatialarrangement of the patches in a landscape and their tem-poral changes in terms of the size adjacency proximityand richness of patches These landscape metrics werederived using the programme Fragstats (McGarigal et al2012) While landscape metrics offer a wide variety ofindices with which a landscape can be analysed we havelimited our choice of indices based on a perusal of forestfragmentation studies (Cakir et al 2008 Galicia et al2008 Hargis et al 1998 Keles et al 2008 OrsquoNeillet al 1988 Sivrikaya et al 2007) and used the follow-ing indices (a) number of patches (NP) (b) per cent oflandscape (PLAND) the percentage of landscape in aparticular class or patch type (c) mean patch size (MPS)the average patch size in a particular class or patch type(d) largest patch index (LPI) the percentage of the land-scape comprised by the largest patch (e) edge density(ED) the sum of the lengths of all edge segments on aper unit area basis Annual deforestation rates werecalculated using the compound interest rate formula(Puyravaud 2003 Vuohelainen et al 2012)

P frac14 100

etht2 t1THORN

In ethA2=A1THORN

where P is percentage of forest loss per year and A1 andA2 are the amount of forest cover at time t1 and t2respectively

Results and discussion

Changes in the Nameri landscape are apparent from theLULC maps of 1973 1988 and 2007 (Figures 1ndash3)respectively Land-cover modification rather than land-cover conversion is apparent in the NTR although in theeastern part of the study area the change closely resem-bles land-cover conversion since the dense forest of1973 has been almost entirely decimated and replaced bynon-forest The most important changes relate to that ofthe dense forest category the area of which decreasedfrom 24985 in 1973 to 15171 ha over the 34 year period(Table 3) Further the rate of loss of dense forest wassubstantially higher during 1988ndash2007 relative to theearlier years The average rate of deforestation was288 ha year1 amounting to a rate of loss of 484year1 using the compound interest rate formula All theother land-use categories increased with open forestsregistering the maximum gain in proportionate terms anddegraded forest in absolute terms

Table 1 Satellite data used in the LULC classification

SatelliteNumber of

bandsResolution

(m)Pathrow

Observationdate

Landsat 1 4 80 14641 16 November 1973Landsat 5 7 30 13641 25 October 1988Landsat 7 8 30 13641 23 January 2007

Table 2 Description of LULC categories

LULC category Description

Dense forest (DF) Forest areas with crown density greaterthan 40

Open forest (OF) Forest areas with crown density greaterthan 10

Degraded forest(DeF)

Forest areas with crown density lessthan 10

Non-forest (NF) Agricultural land including homesteadsRiver amp sand banks

(RSB)River with sand banks

4 A Saikia et al

Dow

nloa

ded

by [

The

Uni

vers

ity o

f M

anch

este

r L

ibra

ry]

at 0

849

09

Dec

embe

r 20

14

and herein lay the rationale for the study While previousstudies did exist (Forest Survey of India [FSI] 20032005 2012 Khushwaha amp Hazarika 2004 Lele et al2008 Roy amp Joshi 2002) these were at macro scales ofanalysis and not specific to the NTR

Data

In addition to characterizing a landscape into variousland-use categories there is a need to consider their

spatial distribution and arrangement and their landscapemetrics (Herzog amp Lausch 2001) Hence in addition todetermining LULC change in the NTR assessing thedegree of fragmentation of its landscape using suitablelandscape metrics was necessary A focus on spatialheterogeneity in landscape ecology studies emerged inthe 1980s when spatial data and analysis methodsbecame widely available (Turner 2005) and quantifyinglandscape structure is a prerequisite to understandinglandscape dynamics (Cakir et al 2008 Cardille amp

Figure 1 The location of the NTR in Assam India (insets) and LULC of the NTR during 1973

Geografisk Tidsskrift-Danish Journal of Geography 3

Dow

nloa

ded

by [

The

Uni

vers

ity o

f M

anch

este

r L

ibra

ry]

at 0

849

09

Dec

embe

r 20

14

Turner 2002 Li et al 2001) Since no single metric cansufficiently capture the pattern of a given landscape(Turner 2005) this study uses a range of metrics tointerpret the pattern of the NTR landscape

The satellite data used are shown in Table 1 Thesatellite imageries covering the area were georeferencedand training areas were created based on ground truthingfrom within the study area but outside the NNP limitsCare was taken to ensure well-distributed training setsand when selecting clusters of a class the variabilitywithin that class (in the image) were taken into accountto cover for possible differences in soil conditions Thustraining areas were selected taking different representa-tive pixel samples The number of observations per clus-ter was kept to a minimum of 30 per band (Janssen ampHuurneman 2001) and it was ensured that clusters in thedata did not overlap The separability of classes waschecked prior to running the classification A maximumlikelihood algorithm was run using the Erdas Imagine87 (wwwerdascom) programme The LULC categoriesthat were delineated are shown in Table 2

Attribute accuracy is one of the most critical factors indetermining the fitness for use of geographic data and isobtained by comparing values of sample spatial data unitswith reference data obtained either by field checks or fromsources of data with a higher degree of accuracy (Lo ampYeung 2002) In this study field checks were preferredsince an accurate map was unavailable In estimatingaccuracy sample points were compared with ground truthverification data that was generated using a hand-heldglobal positioning system device Sample points wereused in view of time cost and physical accessibilityconsiderations Accuracy assessment verification usingstandard measures such as user accuracy producer

accuracy and Kappa accuracy were performed to assessthe correctness of the classifications Accuracy assess-ments showed encouraging results ranging from an overallaccuracy of 8833 for 1973 to 9000 for 1988 and2007 respectively and Kappa accuracy of 86 88 and88 for 1973 1988 and 2007 respectively

The spatial dynamics of a landscape refers to spatialarrangement of the patches in a landscape and their tem-poral changes in terms of the size adjacency proximityand richness of patches These landscape metrics werederived using the programme Fragstats (McGarigal et al2012) While landscape metrics offer a wide variety ofindices with which a landscape can be analysed we havelimited our choice of indices based on a perusal of forestfragmentation studies (Cakir et al 2008 Galicia et al2008 Hargis et al 1998 Keles et al 2008 OrsquoNeillet al 1988 Sivrikaya et al 2007) and used the follow-ing indices (a) number of patches (NP) (b) per cent oflandscape (PLAND) the percentage of landscape in aparticular class or patch type (c) mean patch size (MPS)the average patch size in a particular class or patch type(d) largest patch index (LPI) the percentage of the land-scape comprised by the largest patch (e) edge density(ED) the sum of the lengths of all edge segments on aper unit area basis Annual deforestation rates werecalculated using the compound interest rate formula(Puyravaud 2003 Vuohelainen et al 2012)

P frac14 100

etht2 t1THORN

In ethA2=A1THORN

where P is percentage of forest loss per year and A1 andA2 are the amount of forest cover at time t1 and t2respectively

Results and discussion

Changes in the Nameri landscape are apparent from theLULC maps of 1973 1988 and 2007 (Figures 1ndash3)respectively Land-cover modification rather than land-cover conversion is apparent in the NTR although in theeastern part of the study area the change closely resem-bles land-cover conversion since the dense forest of1973 has been almost entirely decimated and replaced bynon-forest The most important changes relate to that ofthe dense forest category the area of which decreasedfrom 24985 in 1973 to 15171 ha over the 34 year period(Table 3) Further the rate of loss of dense forest wassubstantially higher during 1988ndash2007 relative to theearlier years The average rate of deforestation was288 ha year1 amounting to a rate of loss of 484year1 using the compound interest rate formula All theother land-use categories increased with open forestsregistering the maximum gain in proportionate terms anddegraded forest in absolute terms

Table 1 Satellite data used in the LULC classification

SatelliteNumber of

bandsResolution

(m)Pathrow

Observationdate

Landsat 1 4 80 14641 16 November 1973Landsat 5 7 30 13641 25 October 1988Landsat 7 8 30 13641 23 January 2007

Table 2 Description of LULC categories

LULC category Description

Dense forest (DF) Forest areas with crown density greaterthan 40

Open forest (OF) Forest areas with crown density greaterthan 10

Degraded forest(DeF)

Forest areas with crown density lessthan 10

Non-forest (NF) Agricultural land including homesteadsRiver amp sand banks

(RSB)River with sand banks

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Turner 2002 Li et al 2001) Since no single metric cansufficiently capture the pattern of a given landscape(Turner 2005) this study uses a range of metrics tointerpret the pattern of the NTR landscape

The satellite data used are shown in Table 1 Thesatellite imageries covering the area were georeferencedand training areas were created based on ground truthingfrom within the study area but outside the NNP limitsCare was taken to ensure well-distributed training setsand when selecting clusters of a class the variabilitywithin that class (in the image) were taken into accountto cover for possible differences in soil conditions Thustraining areas were selected taking different representa-tive pixel samples The number of observations per clus-ter was kept to a minimum of 30 per band (Janssen ampHuurneman 2001) and it was ensured that clusters in thedata did not overlap The separability of classes waschecked prior to running the classification A maximumlikelihood algorithm was run using the Erdas Imagine87 (wwwerdascom) programme The LULC categoriesthat were delineated are shown in Table 2

Attribute accuracy is one of the most critical factors indetermining the fitness for use of geographic data and isobtained by comparing values of sample spatial data unitswith reference data obtained either by field checks or fromsources of data with a higher degree of accuracy (Lo ampYeung 2002) In this study field checks were preferredsince an accurate map was unavailable In estimatingaccuracy sample points were compared with ground truthverification data that was generated using a hand-heldglobal positioning system device Sample points wereused in view of time cost and physical accessibilityconsiderations Accuracy assessment verification usingstandard measures such as user accuracy producer

accuracy and Kappa accuracy were performed to assessthe correctness of the classifications Accuracy assess-ments showed encouraging results ranging from an overallaccuracy of 8833 for 1973 to 9000 for 1988 and2007 respectively and Kappa accuracy of 86 88 and88 for 1973 1988 and 2007 respectively

The spatial dynamics of a landscape refers to spatialarrangement of the patches in a landscape and their tem-poral changes in terms of the size adjacency proximityand richness of patches These landscape metrics werederived using the programme Fragstats (McGarigal et al2012) While landscape metrics offer a wide variety ofindices with which a landscape can be analysed we havelimited our choice of indices based on a perusal of forestfragmentation studies (Cakir et al 2008 Galicia et al2008 Hargis et al 1998 Keles et al 2008 OrsquoNeillet al 1988 Sivrikaya et al 2007) and used the follow-ing indices (a) number of patches (NP) (b) per cent oflandscape (PLAND) the percentage of landscape in aparticular class or patch type (c) mean patch size (MPS)the average patch size in a particular class or patch type(d) largest patch index (LPI) the percentage of the land-scape comprised by the largest patch (e) edge density(ED) the sum of the lengths of all edge segments on aper unit area basis Annual deforestation rates werecalculated using the compound interest rate formula(Puyravaud 2003 Vuohelainen et al 2012)

P frac14 100

etht2 t1THORN

In ethA2=A1THORN

where P is percentage of forest loss per year and A1 andA2 are the amount of forest cover at time t1 and t2respectively

Results and discussion

Changes in the Nameri landscape are apparent from theLULC maps of 1973 1988 and 2007 (Figures 1ndash3)respectively Land-cover modification rather than land-cover conversion is apparent in the NTR although in theeastern part of the study area the change closely resem-bles land-cover conversion since the dense forest of1973 has been almost entirely decimated and replaced bynon-forest The most important changes relate to that ofthe dense forest category the area of which decreasedfrom 24985 in 1973 to 15171 ha over the 34 year period(Table 3) Further the rate of loss of dense forest wassubstantially higher during 1988ndash2007 relative to theearlier years The average rate of deforestation was288 ha year1 amounting to a rate of loss of 484year1 using the compound interest rate formula All theother land-use categories increased with open forestsregistering the maximum gain in proportionate terms anddegraded forest in absolute terms

Table 1 Satellite data used in the LULC classification

SatelliteNumber of

bandsResolution

(m)Pathrow

Observationdate

Landsat 1 4 80 14641 16 November 1973Landsat 5 7 30 13641 25 October 1988Landsat 7 8 30 13641 23 January 2007

Table 2 Description of LULC categories

LULC category Description

Dense forest (DF) Forest areas with crown density greaterthan 40

Open forest (OF) Forest areas with crown density greaterthan 10

Degraded forest(DeF)

Forest areas with crown density lessthan 10

Non-forest (NF) Agricultural land including homesteadsRiver amp sand banks

(RSB)River with sand banks

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Landscape metrics and fragmentation

Often the size and shape of patches indicate theireconomic function and larger patches of non-forest toforest represent abandoned logging areas (Southworthet al 2002) in a similar manner much of the degradedforest patches represent hitherto dense forest areas thatwere converted to degraded forest andor non-forestpatches The number of NP along with the MPSprovides useful information on the way the patterndevelops rather than these two indices consideredseparately and when NP increases along with a decreasein MPS it indicates that the landscape pattern is frag-mented (Hulshoff 1995) In Nameri the MPS for all theland-use categories decreased substantially while the NPregistered a sharp upward trend indicating a consistentfragmentation during 1973ndash2007 (Table 4)

The decline in MPS was uniform across land-usecategories that exhibited human-induced effects while adecline in the river and sand banks (RSB) category couldbe attributable to changes in the riverrsquos volume rather thananthropogenic effects possibly why MPS of RSBremained the same during 1988 and 2007 The ED like theother metrics used in this study has increased across cate-gories although for dense forest the rate of increase of EDwas lower This is because the edge per unit area is takeninto account in this index The decline in MPS of the

dense forest was the most significant change but fragmen-tation did not occur in the core area of the reserve in thebetter protected NNP As a result the LPI did not decreaseduring the 1973ndash2007 period (Table 5) In fact since theLPI is based on the area of the largest patch expressed as apercentage of the total landscape area gains made in theLPI for dense forest indicate that the larger patches in theNNP have not been affected and since the PLANDreduced from 6975 to 4236 the LPI values increasedfor dense forests However the gains made by LPIincrease for forests are deceptive on two counts Firstlythe rate of increase of LPI for dense forests fares poorlywhen compared to that for the non-forest area which shotup by 83 over the 34 year period Thus LPI of non-for-est area which include agriculture and homestead areashave expanded more rapidly than that for non-forest Sec-ondly gains in LPI for open and degraded forest accruedout of the dense forest and the expansion of the formeronly attests to the decline in the health of dense forestcover across the entire study area

Dense forests patch level metrics

Since dense forest was the LU category most adverselyaffected in the NTR landscape a patch-level analysis wasundertaken (Table 6) Generally an increase in the

Figure 2 LULC of the NTR 1988

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number of smaller patches is considered one of the basicindicators of forest fragmentation (Sivrikaya et al 2007)and by this yardstick the dense forests had been severely

impacted as the NP of less than 1 ha size rose fivefoldover 1973 while the less than 5 ha size patches increasednominally from 43 in 1973 to 51 by 2007 In terms of

Figure 3 LULC of the NTR 2007

Table 3 LULC change in NTR Areas are in hectares and negative signs denote a decrease

Land-use category1973 1988 2007 variation variation variationha ha ha 1973ndash1988 1988ndash2007 1973ndash2007

DF 2498513 2357645 1517148 564 3565 3928OF 6595 33432 71631 40693 11426 98614DeF 364148 477132 1183068 3103 14795 22489NF 449629 461691 476793 2679 327 604RSB 262958 251944 333204 419 3225 2671Total 3581844 3581844 3581844

Table 4 Landscape metrics of NTR

Land use

PLAND NP MPS ED

1973 1988 2007 1973 1988 2007 1973 1988 2007 1973 1988 2007

DF 6975 6582 4236 270 953 1183 1909 2474 1282 1209 1770 1743OF 018 093 200 95 1055 1971 1055 032 036 035 256 554DeF 1017 1332 3303 1173 3483 3379 4406 137 350 1066 2149 2933NF 1255 1289 1331 556 3341 3215 3652 138 148 984 2260 1913RSB 734 703 930 229 888 888 3842 638 638 576 914 914

10000 10000 10000 2323 9720 10636 14864 3419 2456 3869 7350 8058

6 A Saikia et al

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proportion to total patches these two patch categoriesincreased their share from 86 in 1973 to 945 in1988 and to 965 by 2007 Correspondingly the pro-portion of NP of the medium and larger patches catego-ries (100ndash499 ha and 1000ndash5000+ ha respectively)declined from 44 in 1973 to 16 and 07 by 1988and 2007 respectively (Table 7) In terms of proportionof area by patch size the share of the medium and largerpatches declined from 961 (1973) to 933 (2007)

Thus fragmentation of dense forests resulted in anincrease in the number as well as share of area of thesmaller patch categories and an opposite trend for themedium and larger patch categories The rate of increaseof the smaller patch categories was far greater than therate of decline (in numerical terms as well as share ofarea) of the medium and larger patches

It appears that an increasing number of encroacherscontribute to forest clearing and extraction activities inthe study area but no official records or secondary data

regarding the number of such encroachers exist Withrising population pressure fuelwood requirements havesteadily grown In fact fuelwood consumption is animportant cause of forest decline in many developingcountries (Bhatt amp Sachan 2004 Davidar et al 2007Puyravaud et al 2010 Rawat et al 2009) althoughopinion as to whether fuelwood harvesting leads to forestloss or degradation remains divided (Webb amp Dhakal2011) It is estimated to be important in north-east India(Maikhuri 1991) where 90 of the regionrsquos rural popu-lation uses biomass as an important source of energy(Bhatt et al 2001) As in Tanzania a lack of affordablealternatives to fuelwood usage (Ahrends et al 2010)exists in Nameri Fuelwood and timber is extracted fromthe forest in Nameri and openly sold in the market oralong the roadside Previous studies on fuelwoodconsumption place consumption rates between 31 and104 kgcapitaday for communities in the foothills ofArunachal Pradesh (Maikhuri 1991) an area to theimmediate north of the study area and between 348 and669 in Meghalaya (Bhatt amp Sachan 2004)

Conclusion

Within the tropics Southeast Asia has the highest ratesof forest loss and degradation (Achard et al 2002) Theintensity of land transformation varies tremendouslyacross the surface of the earth with some biomes andregions almost entirely transformed and others almostuninfluenced by direct human activity (Ellis et al 2010)The NTR belongs to the latter category a position that isset to rapidly change as its forests steadily disappearLandscape variables describing the mosaic and structure

Table 6 Patch characteristics of dense forests

Patch size

1973 1988 2007

NP Area MPS NP Area MPS NP Area MPS

lt1 189 955 05 838 1651 020 1095 1956 011ndash49 44 89 2 63 1364 217 51 964 1950ndash19 14 1215 87 23 223 97 17 1719 10120ndash99 11 6673 607 13 6036 464 10 5495 549100ndash999 7 19029 2718 11 38256 3477 7 26402 37711000ndash4999 3 104322 3477 4 134537 3363 1 28105 28105000+ 2 116765 5838 1 51688 5168 1 8707 8707

Table 5 LPI and its changes Areas are in hectares

1973 1988 2007 Rate of change 1973ndash2007()

DF 658 519 873 3265OF 001 004 004 30000DeF 028 116 429 141516NF 05 026 095 8383

Table 7 Proportions of dense forest by patch size Figures arein percentage

Patch Size

1973 1988 2007

NP Area NP Area NP Area

lt1 703 04 879 07 926 131ndash49 164 04 66 06 43 0650ndash19 52 05 24 09 14 1120ndash99 41 27 14 26 08 36100ndash999 26 76 12 162 06 1741000ndash4999 11 418 04 571 01 1855000+ 07 467 01 219 01 574Total 100 100 100 100 100 100

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of landscapes may be used as proxies to assess the diver-sity of certain types of habitat dependent species (Moseret al 2002) and the increasing fragmentation in NTRcould have caused a decline of such species In thiscontext the findings of a recent study are relevant oneof the factors determining occupancy of a forest patchby tigers in India was the forest patch size (Jhala et al2008) an attribute that declined consistently in the studyarea during 1973ndash2007 This trend is likely to continuein the NTR landscape and although there appears to beno universally applicable minimum lsquothresholdrsquo amountof native vegetation (Fischer amp Lindenmayer 2007)fragmentation makes forests vulnerable to further degra-dation (Laurance et al 2011) There is already muchreason for concern as the proportion of dense forest lostduring the period of this study is very substantial andone of the consequences has been growing human ele-phant conflicts in the Sonitpur district (Chartier et al2011) In achieving conservation of habitat dependentmammals like tigers and avoiding humanndashanimal con-flicts some areas need to be strictly allocated for conser-vation (Dewi et al 2013) If conservation is to succeedin the NTR and its buffer areas ways and means ofcontrolling the problem of encroachment must be swiftlysought before further habitat loss and degradation occur

AcknowledgementThis paper forms a part of a study funded by the RuffordSmall Grants Foundation

ReferencesAchard F Eva HD Stibig H Mayaux P Gallego J

Richards T amp Malingreau J (2002) Determination ofdeforestation rates of the worldrsquos humid tropical forestsScience 297 999ndash1002

Ahrends A Burgess ND Milledge SAH Bulling MTFisher B Smart JCR hellip Lewis SL (2010) Predict-able waves of sequential forest degradation and biodiversityloss spreading from an African city Proceedings of theNational Academy of Sciences 107 14556ndash14561

Banfai DS amp Bowman DMJS (2007) Drivers of rain-forestboundary dynamics in Kakadu National Park northern Austra-lia a field assessment Journal of Tropical Ecology 23 73ndash86

Bhatt BP amp Sachan MS (2004) Firewood consumptionpattern of different tribal communities in northeast IndiaEnergy Policy 32 1ndash6

Bhatt BP Singh R Misra LK Tomar JMS Singh M Chau-han DS hellip Datta M (2001) Agroforestry research and prac-tices an overview In ND Verma amp BP Bhatt (Eds) Stepstowards modernization of agriculture in NEH region (pp 365ndash392) Umiam Indian Council for Agricultural Research (ICAR)

Bradley BA amp Mustard JF (2005) Identifying land covervariability distinct from land cover change cheatgrass in theGreat Basin Remote Sensing of Environment 94 204ndash213

Cakir G Sivrikaya F amp Keles S (2008) Forest coverchange and fragmentation using Landsat data in MaccedilkaState Forest Enterprise in Turkey Environmental Monitor-ing amp Assessment 137 51ndash66

Cardille JA amp Turner MG (2002) Understanding land-scape metrics In SE Gergel amp MG Turner (Eds)Learning landscape ecology A practical guide to con-cepts and techniques (pp 85ndash110) New York NYSpringer-Verlag

Chartier L Zimmermann A amp Ladle RJ (2011) Habitatloss and humanndashelephant conflict in Assam India Does acritical threshold exist Oryx 45 528ndash533

Comptroller and Auditor General of India (2006) Centrallysponsored plan scheme ldquoProject TigerrdquondashAdministrativeapproval for funds release to Nameri Tiger Reserve Assamduring 2006ndash2007 No 4-1(22)2006-PT Government ofIndia New Delhi Ministry of Environment amp ForestsRetrieved from httpprojecttigernicinsanction2006Sanc-tion20Nameri20TRpdf

Coppin P Jonckheere I Nackaerts K Muys B amp Lambin E(2004) Digital change detection methods in ecosystem moni-toring a review International Journal of Remote Sensing 251565ndash1596

Corlett RT amp Primack RB (2008) Tropical rainforest con-servation A global perspective In W Carson amp S Schnit-zer (Eds) Tropical forest community ecology (pp 442ndash457) Chichester Blackwell Science

Davidar P Arjunan M Mammen PC Garrigues JPPuyravaud JP amp Roessingh K (2007) Forest degrada-tion in the Western Ghats biodiversity hotspot Resourcecollection livelihood concerns and sustainability CurrentScience 93 1573ndash1578

Dessie G amp Kinlund P (2007) Khat expansion and forestdecline in Wondo Genet Ethiopia Geografiska Annaler BHuman Geography 90 187ndash203

Dewi S van Noordwijka M Ekadinataa A amp Pfund JL(2013) Protected areas within multifunctional landscapesSqueezing out intermediate land use intensities in the tro-pics Land Use Policy 30 38ndash56

Ellis EC Goldewijk KK Siebert S Lightman D amp Rama-nkutty N (2010) Anthropogenic transformation of the biomes1700ndash2000 Global Ecology and Biogeography 19 589ndash606

Fahrig L (2001) How much habitat is enough BiologicalConservation 100 65ndash74

Fischer J amp Lindenmayer DB (2007) Landscape modifica-tion and habitat fragmentation a synthesis Global Ecologyand Biogeography 16 265ndash280

Forest Survey of India (2003) State of forest report 2003Dehra Dun Ministry of Environment amp Forests

Forest Survey of India (2005) State of forest report 2005Dehra Dun Ministry of Environment amp Forests

Forest Survey of India (2012) State of forest report 2011Dehra Dun Ministry of Environment amp Forests

Galicia L Zarco-Arista AE Mendoza-Robles KI Palacio-Prieto JL amp Garciacutea-Romero A (2008) Land usecoverlandforms and fragmentation patterns in a tropical dryforest in the southern Pacific region of Mexico SingaporeJournal of Tropical Geography 29 137ndash154

Geist HJ amp Lambin EF (2001) What drives tropical defor-estation A meta-analysis of proximate and underlyingcauses of deforestation based on subnational case studyevidence (LUCC Report Series 4) Louvain-la-NeuveLUCC International Project Office

Gureja N Menon V Sarkar P amp Kyarong SS (2002)Ganesha to Bin Laden Human-elephant conflict in Sonit-pur district of Assam New Delhi Wildlife Trust of India

Hargis CD Bissonette JA amp Turner DL (1998) Thebehavior of landscape metrics commonly used in the studyof habitat fragmentation Landscape Ecology 13 167ndash186

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number of smaller patches is considered one of the basicindicators of forest fragmentation (Sivrikaya et al 2007)and by this yardstick the dense forests had been severely

impacted as the NP of less than 1 ha size rose fivefoldover 1973 while the less than 5 ha size patches increasednominally from 43 in 1973 to 51 by 2007 In terms of

Figure 3 LULC of the NTR 2007

Table 3 LULC change in NTR Areas are in hectares and negative signs denote a decrease

Land-use category1973 1988 2007 variation variation variationha ha ha 1973ndash1988 1988ndash2007 1973ndash2007

DF 2498513 2357645 1517148 564 3565 3928OF 6595 33432 71631 40693 11426 98614DeF 364148 477132 1183068 3103 14795 22489NF 449629 461691 476793 2679 327 604RSB 262958 251944 333204 419 3225 2671Total 3581844 3581844 3581844

Table 4 Landscape metrics of NTR

Land use

PLAND NP MPS ED

1973 1988 2007 1973 1988 2007 1973 1988 2007 1973 1988 2007

DF 6975 6582 4236 270 953 1183 1909 2474 1282 1209 1770 1743OF 018 093 200 95 1055 1971 1055 032 036 035 256 554DeF 1017 1332 3303 1173 3483 3379 4406 137 350 1066 2149 2933NF 1255 1289 1331 556 3341 3215 3652 138 148 984 2260 1913RSB 734 703 930 229 888 888 3842 638 638 576 914 914

10000 10000 10000 2323 9720 10636 14864 3419 2456 3869 7350 8058

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proportion to total patches these two patch categoriesincreased their share from 86 in 1973 to 945 in1988 and to 965 by 2007 Correspondingly the pro-portion of NP of the medium and larger patches catego-ries (100ndash499 ha and 1000ndash5000+ ha respectively)declined from 44 in 1973 to 16 and 07 by 1988and 2007 respectively (Table 7) In terms of proportionof area by patch size the share of the medium and largerpatches declined from 961 (1973) to 933 (2007)

Thus fragmentation of dense forests resulted in anincrease in the number as well as share of area of thesmaller patch categories and an opposite trend for themedium and larger patch categories The rate of increaseof the smaller patch categories was far greater than therate of decline (in numerical terms as well as share ofarea) of the medium and larger patches

It appears that an increasing number of encroacherscontribute to forest clearing and extraction activities inthe study area but no official records or secondary data

regarding the number of such encroachers exist Withrising population pressure fuelwood requirements havesteadily grown In fact fuelwood consumption is animportant cause of forest decline in many developingcountries (Bhatt amp Sachan 2004 Davidar et al 2007Puyravaud et al 2010 Rawat et al 2009) althoughopinion as to whether fuelwood harvesting leads to forestloss or degradation remains divided (Webb amp Dhakal2011) It is estimated to be important in north-east India(Maikhuri 1991) where 90 of the regionrsquos rural popu-lation uses biomass as an important source of energy(Bhatt et al 2001) As in Tanzania a lack of affordablealternatives to fuelwood usage (Ahrends et al 2010)exists in Nameri Fuelwood and timber is extracted fromthe forest in Nameri and openly sold in the market oralong the roadside Previous studies on fuelwoodconsumption place consumption rates between 31 and104 kgcapitaday for communities in the foothills ofArunachal Pradesh (Maikhuri 1991) an area to theimmediate north of the study area and between 348 and669 in Meghalaya (Bhatt amp Sachan 2004)

Conclusion

Within the tropics Southeast Asia has the highest ratesof forest loss and degradation (Achard et al 2002) Theintensity of land transformation varies tremendouslyacross the surface of the earth with some biomes andregions almost entirely transformed and others almostuninfluenced by direct human activity (Ellis et al 2010)The NTR belongs to the latter category a position that isset to rapidly change as its forests steadily disappearLandscape variables describing the mosaic and structure

Table 6 Patch characteristics of dense forests

Patch size

1973 1988 2007

NP Area MPS NP Area MPS NP Area MPS

lt1 189 955 05 838 1651 020 1095 1956 011ndash49 44 89 2 63 1364 217 51 964 1950ndash19 14 1215 87 23 223 97 17 1719 10120ndash99 11 6673 607 13 6036 464 10 5495 549100ndash999 7 19029 2718 11 38256 3477 7 26402 37711000ndash4999 3 104322 3477 4 134537 3363 1 28105 28105000+ 2 116765 5838 1 51688 5168 1 8707 8707

Table 5 LPI and its changes Areas are in hectares

1973 1988 2007 Rate of change 1973ndash2007()

DF 658 519 873 3265OF 001 004 004 30000DeF 028 116 429 141516NF 05 026 095 8383

Table 7 Proportions of dense forest by patch size Figures arein percentage

Patch Size

1973 1988 2007

NP Area NP Area NP Area

lt1 703 04 879 07 926 131ndash49 164 04 66 06 43 0650ndash19 52 05 24 09 14 1120ndash99 41 27 14 26 08 36100ndash999 26 76 12 162 06 1741000ndash4999 11 418 04 571 01 1855000+ 07 467 01 219 01 574Total 100 100 100 100 100 100

Geografisk Tidsskrift-Danish Journal of Geography 7

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of landscapes may be used as proxies to assess the diver-sity of certain types of habitat dependent species (Moseret al 2002) and the increasing fragmentation in NTRcould have caused a decline of such species In thiscontext the findings of a recent study are relevant oneof the factors determining occupancy of a forest patchby tigers in India was the forest patch size (Jhala et al2008) an attribute that declined consistently in the studyarea during 1973ndash2007 This trend is likely to continuein the NTR landscape and although there appears to beno universally applicable minimum lsquothresholdrsquo amountof native vegetation (Fischer amp Lindenmayer 2007)fragmentation makes forests vulnerable to further degra-dation (Laurance et al 2011) There is already muchreason for concern as the proportion of dense forest lostduring the period of this study is very substantial andone of the consequences has been growing human ele-phant conflicts in the Sonitpur district (Chartier et al2011) In achieving conservation of habitat dependentmammals like tigers and avoiding humanndashanimal con-flicts some areas need to be strictly allocated for conser-vation (Dewi et al 2013) If conservation is to succeedin the NTR and its buffer areas ways and means ofcontrolling the problem of encroachment must be swiftlysought before further habitat loss and degradation occur

AcknowledgementThis paper forms a part of a study funded by the RuffordSmall Grants Foundation

ReferencesAchard F Eva HD Stibig H Mayaux P Gallego J

Richards T amp Malingreau J (2002) Determination ofdeforestation rates of the worldrsquos humid tropical forestsScience 297 999ndash1002

Ahrends A Burgess ND Milledge SAH Bulling MTFisher B Smart JCR hellip Lewis SL (2010) Predict-able waves of sequential forest degradation and biodiversityloss spreading from an African city Proceedings of theNational Academy of Sciences 107 14556ndash14561

Banfai DS amp Bowman DMJS (2007) Drivers of rain-forestboundary dynamics in Kakadu National Park northern Austra-lia a field assessment Journal of Tropical Ecology 23 73ndash86

Bhatt BP amp Sachan MS (2004) Firewood consumptionpattern of different tribal communities in northeast IndiaEnergy Policy 32 1ndash6

Bhatt BP Singh R Misra LK Tomar JMS Singh M Chau-han DS hellip Datta M (2001) Agroforestry research and prac-tices an overview In ND Verma amp BP Bhatt (Eds) Stepstowards modernization of agriculture in NEH region (pp 365ndash392) Umiam Indian Council for Agricultural Research (ICAR)

Bradley BA amp Mustard JF (2005) Identifying land covervariability distinct from land cover change cheatgrass in theGreat Basin Remote Sensing of Environment 94 204ndash213

Cakir G Sivrikaya F amp Keles S (2008) Forest coverchange and fragmentation using Landsat data in MaccedilkaState Forest Enterprise in Turkey Environmental Monitor-ing amp Assessment 137 51ndash66

Cardille JA amp Turner MG (2002) Understanding land-scape metrics In SE Gergel amp MG Turner (Eds)Learning landscape ecology A practical guide to con-cepts and techniques (pp 85ndash110) New York NYSpringer-Verlag

Chartier L Zimmermann A amp Ladle RJ (2011) Habitatloss and humanndashelephant conflict in Assam India Does acritical threshold exist Oryx 45 528ndash533

Comptroller and Auditor General of India (2006) Centrallysponsored plan scheme ldquoProject TigerrdquondashAdministrativeapproval for funds release to Nameri Tiger Reserve Assamduring 2006ndash2007 No 4-1(22)2006-PT Government ofIndia New Delhi Ministry of Environment amp ForestsRetrieved from httpprojecttigernicinsanction2006Sanc-tion20Nameri20TRpdf

Coppin P Jonckheere I Nackaerts K Muys B amp Lambin E(2004) Digital change detection methods in ecosystem moni-toring a review International Journal of Remote Sensing 251565ndash1596

Corlett RT amp Primack RB (2008) Tropical rainforest con-servation A global perspective In W Carson amp S Schnit-zer (Eds) Tropical forest community ecology (pp 442ndash457) Chichester Blackwell Science

Davidar P Arjunan M Mammen PC Garrigues JPPuyravaud JP amp Roessingh K (2007) Forest degrada-tion in the Western Ghats biodiversity hotspot Resourcecollection livelihood concerns and sustainability CurrentScience 93 1573ndash1578

Dessie G amp Kinlund P (2007) Khat expansion and forestdecline in Wondo Genet Ethiopia Geografiska Annaler BHuman Geography 90 187ndash203

Dewi S van Noordwijka M Ekadinataa A amp Pfund JL(2013) Protected areas within multifunctional landscapesSqueezing out intermediate land use intensities in the tro-pics Land Use Policy 30 38ndash56

Ellis EC Goldewijk KK Siebert S Lightman D amp Rama-nkutty N (2010) Anthropogenic transformation of the biomes1700ndash2000 Global Ecology and Biogeography 19 589ndash606

Fahrig L (2001) How much habitat is enough BiologicalConservation 100 65ndash74

Fischer J amp Lindenmayer DB (2007) Landscape modifica-tion and habitat fragmentation a synthesis Global Ecologyand Biogeography 16 265ndash280

Forest Survey of India (2003) State of forest report 2003Dehra Dun Ministry of Environment amp Forests

Forest Survey of India (2005) State of forest report 2005Dehra Dun Ministry of Environment amp Forests

Forest Survey of India (2012) State of forest report 2011Dehra Dun Ministry of Environment amp Forests

Galicia L Zarco-Arista AE Mendoza-Robles KI Palacio-Prieto JL amp Garciacutea-Romero A (2008) Land usecoverlandforms and fragmentation patterns in a tropical dryforest in the southern Pacific region of Mexico SingaporeJournal of Tropical Geography 29 137ndash154

Geist HJ amp Lambin EF (2001) What drives tropical defor-estation A meta-analysis of proximate and underlyingcauses of deforestation based on subnational case studyevidence (LUCC Report Series 4) Louvain-la-NeuveLUCC International Project Office

Gureja N Menon V Sarkar P amp Kyarong SS (2002)Ganesha to Bin Laden Human-elephant conflict in Sonit-pur district of Assam New Delhi Wildlife Trust of India

Hargis CD Bissonette JA amp Turner DL (1998) Thebehavior of landscape metrics commonly used in the studyof habitat fragmentation Landscape Ecology 13 167ndash186

8 A Saikia et al

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proportion to total patches these two patch categoriesincreased their share from 86 in 1973 to 945 in1988 and to 965 by 2007 Correspondingly the pro-portion of NP of the medium and larger patches catego-ries (100ndash499 ha and 1000ndash5000+ ha respectively)declined from 44 in 1973 to 16 and 07 by 1988and 2007 respectively (Table 7) In terms of proportionof area by patch size the share of the medium and largerpatches declined from 961 (1973) to 933 (2007)

Thus fragmentation of dense forests resulted in anincrease in the number as well as share of area of thesmaller patch categories and an opposite trend for themedium and larger patch categories The rate of increaseof the smaller patch categories was far greater than therate of decline (in numerical terms as well as share ofarea) of the medium and larger patches

It appears that an increasing number of encroacherscontribute to forest clearing and extraction activities inthe study area but no official records or secondary data

regarding the number of such encroachers exist Withrising population pressure fuelwood requirements havesteadily grown In fact fuelwood consumption is animportant cause of forest decline in many developingcountries (Bhatt amp Sachan 2004 Davidar et al 2007Puyravaud et al 2010 Rawat et al 2009) althoughopinion as to whether fuelwood harvesting leads to forestloss or degradation remains divided (Webb amp Dhakal2011) It is estimated to be important in north-east India(Maikhuri 1991) where 90 of the regionrsquos rural popu-lation uses biomass as an important source of energy(Bhatt et al 2001) As in Tanzania a lack of affordablealternatives to fuelwood usage (Ahrends et al 2010)exists in Nameri Fuelwood and timber is extracted fromthe forest in Nameri and openly sold in the market oralong the roadside Previous studies on fuelwoodconsumption place consumption rates between 31 and104 kgcapitaday for communities in the foothills ofArunachal Pradesh (Maikhuri 1991) an area to theimmediate north of the study area and between 348 and669 in Meghalaya (Bhatt amp Sachan 2004)

Conclusion

Within the tropics Southeast Asia has the highest ratesof forest loss and degradation (Achard et al 2002) Theintensity of land transformation varies tremendouslyacross the surface of the earth with some biomes andregions almost entirely transformed and others almostuninfluenced by direct human activity (Ellis et al 2010)The NTR belongs to the latter category a position that isset to rapidly change as its forests steadily disappearLandscape variables describing the mosaic and structure

Table 6 Patch characteristics of dense forests

Patch size

1973 1988 2007

NP Area MPS NP Area MPS NP Area MPS

lt1 189 955 05 838 1651 020 1095 1956 011ndash49 44 89 2 63 1364 217 51 964 1950ndash19 14 1215 87 23 223 97 17 1719 10120ndash99 11 6673 607 13 6036 464 10 5495 549100ndash999 7 19029 2718 11 38256 3477 7 26402 37711000ndash4999 3 104322 3477 4 134537 3363 1 28105 28105000+ 2 116765 5838 1 51688 5168 1 8707 8707

Table 5 LPI and its changes Areas are in hectares

1973 1988 2007 Rate of change 1973ndash2007()

DF 658 519 873 3265OF 001 004 004 30000DeF 028 116 429 141516NF 05 026 095 8383

Table 7 Proportions of dense forest by patch size Figures arein percentage

Patch Size

1973 1988 2007

NP Area NP Area NP Area

lt1 703 04 879 07 926 131ndash49 164 04 66 06 43 0650ndash19 52 05 24 09 14 1120ndash99 41 27 14 26 08 36100ndash999 26 76 12 162 06 1741000ndash4999 11 418 04 571 01 1855000+ 07 467 01 219 01 574Total 100 100 100 100 100 100

Geografisk Tidsskrift-Danish Journal of Geography 7

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of landscapes may be used as proxies to assess the diver-sity of certain types of habitat dependent species (Moseret al 2002) and the increasing fragmentation in NTRcould have caused a decline of such species In thiscontext the findings of a recent study are relevant oneof the factors determining occupancy of a forest patchby tigers in India was the forest patch size (Jhala et al2008) an attribute that declined consistently in the studyarea during 1973ndash2007 This trend is likely to continuein the NTR landscape and although there appears to beno universally applicable minimum lsquothresholdrsquo amountof native vegetation (Fischer amp Lindenmayer 2007)fragmentation makes forests vulnerable to further degra-dation (Laurance et al 2011) There is already muchreason for concern as the proportion of dense forest lostduring the period of this study is very substantial andone of the consequences has been growing human ele-phant conflicts in the Sonitpur district (Chartier et al2011) In achieving conservation of habitat dependentmammals like tigers and avoiding humanndashanimal con-flicts some areas need to be strictly allocated for conser-vation (Dewi et al 2013) If conservation is to succeedin the NTR and its buffer areas ways and means ofcontrolling the problem of encroachment must be swiftlysought before further habitat loss and degradation occur

AcknowledgementThis paper forms a part of a study funded by the RuffordSmall Grants Foundation

ReferencesAchard F Eva HD Stibig H Mayaux P Gallego J

Richards T amp Malingreau J (2002) Determination ofdeforestation rates of the worldrsquos humid tropical forestsScience 297 999ndash1002

Ahrends A Burgess ND Milledge SAH Bulling MTFisher B Smart JCR hellip Lewis SL (2010) Predict-able waves of sequential forest degradation and biodiversityloss spreading from an African city Proceedings of theNational Academy of Sciences 107 14556ndash14561

Banfai DS amp Bowman DMJS (2007) Drivers of rain-forestboundary dynamics in Kakadu National Park northern Austra-lia a field assessment Journal of Tropical Ecology 23 73ndash86

Bhatt BP amp Sachan MS (2004) Firewood consumptionpattern of different tribal communities in northeast IndiaEnergy Policy 32 1ndash6

Bhatt BP Singh R Misra LK Tomar JMS Singh M Chau-han DS hellip Datta M (2001) Agroforestry research and prac-tices an overview In ND Verma amp BP Bhatt (Eds) Stepstowards modernization of agriculture in NEH region (pp 365ndash392) Umiam Indian Council for Agricultural Research (ICAR)

Bradley BA amp Mustard JF (2005) Identifying land covervariability distinct from land cover change cheatgrass in theGreat Basin Remote Sensing of Environment 94 204ndash213

Cakir G Sivrikaya F amp Keles S (2008) Forest coverchange and fragmentation using Landsat data in MaccedilkaState Forest Enterprise in Turkey Environmental Monitor-ing amp Assessment 137 51ndash66

Cardille JA amp Turner MG (2002) Understanding land-scape metrics In SE Gergel amp MG Turner (Eds)Learning landscape ecology A practical guide to con-cepts and techniques (pp 85ndash110) New York NYSpringer-Verlag

Chartier L Zimmermann A amp Ladle RJ (2011) Habitatloss and humanndashelephant conflict in Assam India Does acritical threshold exist Oryx 45 528ndash533

Comptroller and Auditor General of India (2006) Centrallysponsored plan scheme ldquoProject TigerrdquondashAdministrativeapproval for funds release to Nameri Tiger Reserve Assamduring 2006ndash2007 No 4-1(22)2006-PT Government ofIndia New Delhi Ministry of Environment amp ForestsRetrieved from httpprojecttigernicinsanction2006Sanc-tion20Nameri20TRpdf

Coppin P Jonckheere I Nackaerts K Muys B amp Lambin E(2004) Digital change detection methods in ecosystem moni-toring a review International Journal of Remote Sensing 251565ndash1596

Corlett RT amp Primack RB (2008) Tropical rainforest con-servation A global perspective In W Carson amp S Schnit-zer (Eds) Tropical forest community ecology (pp 442ndash457) Chichester Blackwell Science

Davidar P Arjunan M Mammen PC Garrigues JPPuyravaud JP amp Roessingh K (2007) Forest degrada-tion in the Western Ghats biodiversity hotspot Resourcecollection livelihood concerns and sustainability CurrentScience 93 1573ndash1578

Dessie G amp Kinlund P (2007) Khat expansion and forestdecline in Wondo Genet Ethiopia Geografiska Annaler BHuman Geography 90 187ndash203

Dewi S van Noordwijka M Ekadinataa A amp Pfund JL(2013) Protected areas within multifunctional landscapesSqueezing out intermediate land use intensities in the tro-pics Land Use Policy 30 38ndash56

Ellis EC Goldewijk KK Siebert S Lightman D amp Rama-nkutty N (2010) Anthropogenic transformation of the biomes1700ndash2000 Global Ecology and Biogeography 19 589ndash606

Fahrig L (2001) How much habitat is enough BiologicalConservation 100 65ndash74

Fischer J amp Lindenmayer DB (2007) Landscape modifica-tion and habitat fragmentation a synthesis Global Ecologyand Biogeography 16 265ndash280

Forest Survey of India (2003) State of forest report 2003Dehra Dun Ministry of Environment amp Forests

Forest Survey of India (2005) State of forest report 2005Dehra Dun Ministry of Environment amp Forests

Forest Survey of India (2012) State of forest report 2011Dehra Dun Ministry of Environment amp Forests

Galicia L Zarco-Arista AE Mendoza-Robles KI Palacio-Prieto JL amp Garciacutea-Romero A (2008) Land usecoverlandforms and fragmentation patterns in a tropical dryforest in the southern Pacific region of Mexico SingaporeJournal of Tropical Geography 29 137ndash154

Geist HJ amp Lambin EF (2001) What drives tropical defor-estation A meta-analysis of proximate and underlyingcauses of deforestation based on subnational case studyevidence (LUCC Report Series 4) Louvain-la-NeuveLUCC International Project Office

Gureja N Menon V Sarkar P amp Kyarong SS (2002)Ganesha to Bin Laden Human-elephant conflict in Sonit-pur district of Assam New Delhi Wildlife Trust of India

Hargis CD Bissonette JA amp Turner DL (1998) Thebehavior of landscape metrics commonly used in the studyof habitat fragmentation Landscape Ecology 13 167ndash186

8 A Saikia et al

Dow

nloa

ded

by [

The

Uni

vers

ity o

f M

anch

este

r L

ibra

ry]

at 0

849

09

Dec

embe

r 20

14

of landscapes may be used as proxies to assess the diver-sity of certain types of habitat dependent species (Moseret al 2002) and the increasing fragmentation in NTRcould have caused a decline of such species In thiscontext the findings of a recent study are relevant oneof the factors determining occupancy of a forest patchby tigers in India was the forest patch size (Jhala et al2008) an attribute that declined consistently in the studyarea during 1973ndash2007 This trend is likely to continuein the NTR landscape and although there appears to beno universally applicable minimum lsquothresholdrsquo amountof native vegetation (Fischer amp Lindenmayer 2007)fragmentation makes forests vulnerable to further degra-dation (Laurance et al 2011) There is already muchreason for concern as the proportion of dense forest lostduring the period of this study is very substantial andone of the consequences has been growing human ele-phant conflicts in the Sonitpur district (Chartier et al2011) In achieving conservation of habitat dependentmammals like tigers and avoiding humanndashanimal con-flicts some areas need to be strictly allocated for conser-vation (Dewi et al 2013) If conservation is to succeedin the NTR and its buffer areas ways and means ofcontrolling the problem of encroachment must be swiftlysought before further habitat loss and degradation occur

AcknowledgementThis paper forms a part of a study funded by the RuffordSmall Grants Foundation

ReferencesAchard F Eva HD Stibig H Mayaux P Gallego J

Richards T amp Malingreau J (2002) Determination ofdeforestation rates of the worldrsquos humid tropical forestsScience 297 999ndash1002

Ahrends A Burgess ND Milledge SAH Bulling MTFisher B Smart JCR hellip Lewis SL (2010) Predict-able waves of sequential forest degradation and biodiversityloss spreading from an African city Proceedings of theNational Academy of Sciences 107 14556ndash14561

Banfai DS amp Bowman DMJS (2007) Drivers of rain-forestboundary dynamics in Kakadu National Park northern Austra-lia a field assessment Journal of Tropical Ecology 23 73ndash86

Bhatt BP amp Sachan MS (2004) Firewood consumptionpattern of different tribal communities in northeast IndiaEnergy Policy 32 1ndash6

Bhatt BP Singh R Misra LK Tomar JMS Singh M Chau-han DS hellip Datta M (2001) Agroforestry research and prac-tices an overview In ND Verma amp BP Bhatt (Eds) Stepstowards modernization of agriculture in NEH region (pp 365ndash392) Umiam Indian Council for Agricultural Research (ICAR)

Bradley BA amp Mustard JF (2005) Identifying land covervariability distinct from land cover change cheatgrass in theGreat Basin Remote Sensing of Environment 94 204ndash213

Cakir G Sivrikaya F amp Keles S (2008) Forest coverchange and fragmentation using Landsat data in MaccedilkaState Forest Enterprise in Turkey Environmental Monitor-ing amp Assessment 137 51ndash66

Cardille JA amp Turner MG (2002) Understanding land-scape metrics In SE Gergel amp MG Turner (Eds)Learning landscape ecology A practical guide to con-cepts and techniques (pp 85ndash110) New York NYSpringer-Verlag

Chartier L Zimmermann A amp Ladle RJ (2011) Habitatloss and humanndashelephant conflict in Assam India Does acritical threshold exist Oryx 45 528ndash533

Comptroller and Auditor General of India (2006) Centrallysponsored plan scheme ldquoProject TigerrdquondashAdministrativeapproval for funds release to Nameri Tiger Reserve Assamduring 2006ndash2007 No 4-1(22)2006-PT Government ofIndia New Delhi Ministry of Environment amp ForestsRetrieved from httpprojecttigernicinsanction2006Sanc-tion20Nameri20TRpdf

Coppin P Jonckheere I Nackaerts K Muys B amp Lambin E(2004) Digital change detection methods in ecosystem moni-toring a review International Journal of Remote Sensing 251565ndash1596

Corlett RT amp Primack RB (2008) Tropical rainforest con-servation A global perspective In W Carson amp S Schnit-zer (Eds) Tropical forest community ecology (pp 442ndash457) Chichester Blackwell Science

Davidar P Arjunan M Mammen PC Garrigues JPPuyravaud JP amp Roessingh K (2007) Forest degrada-tion in the Western Ghats biodiversity hotspot Resourcecollection livelihood concerns and sustainability CurrentScience 93 1573ndash1578

Dessie G amp Kinlund P (2007) Khat expansion and forestdecline in Wondo Genet Ethiopia Geografiska Annaler BHuman Geography 90 187ndash203

Dewi S van Noordwijka M Ekadinataa A amp Pfund JL(2013) Protected areas within multifunctional landscapesSqueezing out intermediate land use intensities in the tro-pics Land Use Policy 30 38ndash56

Ellis EC Goldewijk KK Siebert S Lightman D amp Rama-nkutty N (2010) Anthropogenic transformation of the biomes1700ndash2000 Global Ecology and Biogeography 19 589ndash606

Fahrig L (2001) How much habitat is enough BiologicalConservation 100 65ndash74

Fischer J amp Lindenmayer DB (2007) Landscape modifica-tion and habitat fragmentation a synthesis Global Ecologyand Biogeography 16 265ndash280

Forest Survey of India (2003) State of forest report 2003Dehra Dun Ministry of Environment amp Forests

Forest Survey of India (2005) State of forest report 2005Dehra Dun Ministry of Environment amp Forests

Forest Survey of India (2012) State of forest report 2011Dehra Dun Ministry of Environment amp Forests

Galicia L Zarco-Arista AE Mendoza-Robles KI Palacio-Prieto JL amp Garciacutea-Romero A (2008) Land usecoverlandforms and fragmentation patterns in a tropical dryforest in the southern Pacific region of Mexico SingaporeJournal of Tropical Geography 29 137ndash154

Geist HJ amp Lambin EF (2001) What drives tropical defor-estation A meta-analysis of proximate and underlyingcauses of deforestation based on subnational case studyevidence (LUCC Report Series 4) Louvain-la-NeuveLUCC International Project Office

Gureja N Menon V Sarkar P amp Kyarong SS (2002)Ganesha to Bin Laden Human-elephant conflict in Sonit-pur district of Assam New Delhi Wildlife Trust of India

Hargis CD Bissonette JA amp Turner DL (1998) Thebehavior of landscape metrics commonly used in the studyof habitat fragmentation Landscape Ecology 13 167ndash186

8 A Saikia et al

Dow

nloa

ded

by [

The

Uni

vers

ity o

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anch

este

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ibra

ry]

at 0

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Dec

embe

r 20

14

Hazarika R amp Saikia A (2013) The pachyderm and thepixel An assessment of elephant habitat suitability in Son-itpur India International Journal of Remote Sensing doi101080014311612013787503 (In press)

Herzog F amp Lausch A (2001) Supplementing land use statis-tics with landscape metrics some methodological consider-ations Environmental Monitoring and Assessment 72 37ndash50

Houet T Loveland TR Hubert-Moy L Gaucherel CNapton D Barnes CA amp Sayler K (2010) Exploringsubtle land use and land cover changes A framework forfuture landscape studies Landscape Ecology 25 249ndash266

Hulshoff RM (1995) Landscape indices describing a Dutchlandscape Landscape Ecology 10 101ndash111

Hunsaker CT OrsquoNeill RV Jackson BL Timmins SPLevine DA amp Norton DJ (1994) Sampling to charac-terize landscape pattern Landscape Ecology 9 207ndash226

Janssen LLF amp Huurneman GC (2001) Principles ofremote sensing Enschede ITC Press

Jhala YV Gopal R amp Qureshi Q (2008) Status of thetigers co-predators and prey in India New DelhiNational Tiger Conservation Authority Government ofIndia and Wildlife Institute of India

Keles S Sivrikaya F Cakir G amp Koumlse S (2008) Urbani-zation and forest cover change in regional directorate ofTrabzon forestry from 1975 to 2000 using landsat dataEnvironmental Monitoring amp Assessment 140 1ndash14

Khushwaha SPS amp Hazarika R (2004) Assessment of hab-itat loss in Kameng and Sonitpur elephant reserves CurrentScience 87 1447ndash1453

Lambin EF Geist HJ amp Lepers E (2003) Dynamics ofland-use and land-cover change in tropical regions AnnualReview of Environment and Resources 28 205ndash241

Laurance WF Camargo J Luizao R Laurance SGPimm SL Bruna E hellip Lovejoy TE (2011) The fateof Amazonian forest fragments A 32-year investigationBiological Conservation 144 56ndash67

Laurance WF Carolina-Useche D Rendeiro J Kalka MBradshaw CJA Sloan SP hellip Zamzani F (2012)Averting biodiversity collapse in tropical forest protectedareas Nature 489 290ndash294

Lele N Joshi PK amp Agrawal SP (2008) Assessing forestfragmentation in northeastern region (NER) of India usinglandscape matrices Ecological Indicators 8 657ndash663

Li X Lu L Cheng GD amp Xiao HL (2001) Quantifying land-scape structure of the Heihe River Basin northwest China usingFRAGSTATS Journal of Arid Environments 48 521ndash535

Lo CP amp Yeung AKW (2002) Concepts and techniques ofgeographic information systems Upper Saddle River NJPrentice Hall

Maikhuri RK (1991) Fuelwood consumption pattern of dif-ferent tribal communities living in Arunachal Pradesh innortheast India Bioresource Technology 35 291ndash296

Mannion AM (2002) Dynamic world Land-cover andland-use change London Arnold

McGarigal K Cushman SA amp Ene E (2012) FRAGSTATSv4 Spatial pattern analysis program for categorical andcontinuous maps Amherst Computer software programproduced by the authors at the University of MassachusettsRetrieved from wwwumassedulandecoresearchfragstatsfragstatshtml

Mertz O Muumlller D Sikor T Hett C Heinimann ACastella JC hellip Sun Z (2012) The forgotten D Chal-lenges of addressing forest degradation in complex mosaiclandscapes under REDD+ Geografisk Tidsskrift-DanishJournal of Geography 112(1) 63ndash76

Moser D Zechmeister HG Plutzar CNS Wrbka T ampGrabherr G (2002) Landscape patch shape complexity asan effective measure for plant species richness in rurallandscapes Landscape Ecology 17 657ndash669

OrsquoNeill RV Krummel JR Gardner RH Sugihara GJackson B DeAngelis DL hellip Graham RL (1988)Indices of landscape pattern Landscape Ecology 1 153ndash162

Puyravaud JP (2003) Standardizing the calculation of theannual rate of deforestation Forest Ecology and Manage-ment 177 593ndash596

Puyravaud JP Davidar P amp Laurance WF (2010) Crypticloss of Indiarsquos native forests Science 329 32

Rawat YS Vishvakarma SCR amp Todaria NP (2009) Fuelwood consumption pattern of tribal communities in colddesert of the Lahaul valley north-western Himalaya IndiaBiomass and Bioenergy 33 1547ndash1557

Roy PS amp Joshi PK (2002) Forest cover assessment innorth east India The potential of temporal wide swathsatellite sensor data (IRS-1C WiFS) International Journalof Remote Sensing 23 4881ndash4896

Saikia A (2004 August 9ndash13) Indigenous control and sustain-ability of common resources in the hills of north east IndiaTenth Biennial Conference of the International Associationfor the Study of Common Property Oaxaca Retrieved fromhttpdlcdlibindianaedudlchandle105351055

Saikia A (2008) Forest fragmentation in north east India InS Deka (Ed) North east India geo-environmental issues(pp 227ndash248) Guwahati Eastern Book House

Sivrikaya FC Kadiogullari AI Keles S Baskent EZ ampTerzioglu S (2007) Evaluating land useland coverchanges and fragmentation in the Camili forest planningunit of north eastern Turkey from 1972 to 2005 Land Deg-radation amp Development 18 383ndash396

Skole DL Cochrane MA Matricardi EAT Chomentow-ski W Pedlowski M amp Kimble D (2004) Pattern toprocess in the Amazon region Measuring forest conver-sion regeneration and degradation In G Gutman ACJanetos CO Justice EF Moran JF Mustard RR Rind-fuss D Skole BL TurnerII amp MA Cochrane (Eds)Land change science Observing monitoring and under-standing trajectories of change on the Earthrsquos surface (pp77ndash95) Dordrecht Kluwer Academic

Southworth J Harini N amp Tucker C (2002) Fragmentationof a landscape incorporating landscape metrics into satel-lite analyses of land-cover change Landscape Research27 253ndash269

Tucker RP (1988a) The depletion of Indiarsquos forestsunder British imperialism Planters foresters and peas-ants in Assam and Kerala In D Worster (Ed) Theends of the earth Perspectives on modern environmen-tal history (pp 118ndash140) Cambridge CambridgeUniversity Press

Tucker RP (1988b) The British empire and Indiarsquos forestresources The timberlands of Assam and Kumaon 1914ndash1950 In JF Richards amp RP Tucker (Eds) World defores-tation in the twentieth century (pp 91ndash111) Durham DukeUniversity Press

Turner BL (2001) Land-Use and Land-Cover ChangeAdvances in 15 Decades of Sustained InternationalResearch GAIA-Ecological Perspectives in ScienceHumanities and Economics 10 269ndash272

Turner MG (2005) Landscape ecology What is the state ofthe science Annual Review of Ecology Evolution andSystematics 36 319ndash344

Geografisk Tidsskrift-Danish Journal of Geography 9

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van Vliet N Mertz O Heinimann A Langanke T PascualU Schmook B hellip Ziegler A (2012) Trends driversand impacts of changes in swidden cultivation in tropicalforest-agriculture frontiers A global assessment GlobalEnvironmental Change 22 418ndash429

Vitousek PM (1994) Beyond global warming Ecology andglobal change Ecology 75 1861ndash1876

Vuohelainen AJ Coad L Marthews TR Malhi Y amp Kil-leen TJ (2012) The effectiveness of contrasting protectedareas in preventing deforestation in Madre de Dios PeruEnvironmental Management 50 645ndash663

Webb EL amp Dhakal A (2011) Patterns and drivers of fuel-wood collection and tree planting in a Middle Hillwatershed of Nepal Biomass and Bioenergy 35 121ndash132

10 A Saikia et al

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