land-use/land-cover change and forest fragmentation in the jigme...

Physical GeoGraPhy, 2016http://dx.doi.org/10.1080/02723646.2016.1248212

Land-use/land-cover change and forest fragmentation in the Jigme Dorji National Park, Bhutan

Kiran Sharmaa , Scott M. Robesonb, Pankaj Thapac and Anup Saikiaa aDepartment of Geography, Gauhati University, Guwahati, india; bDepartment of Geography, indiana University, Bloomington, iN, Usa; cDepartment of Geography, sherubtse college, royal University of Bhutan, Kanglung, Bhutan

ABSTRACTMonitoring land-cover change and understanding the dynamics of forest cover is critically important for the management of forest ecosystems. This study assesses land cover change (1990–2015) in the Jigme Dorji National Park, one of the largest national parks in Bhutan, using Landsat imageries. Overall changes in forest cover, as well as the fragmentation of dense forests within the park, were analyzed using landscape metrics. The results show that total forest area, dense forest area, and moderately dense forest area decreased while open forest area and shrub area increased. During the 25-year study period, the annual deforestation rate was 821 ha year−1, equivalent to 0.63% year−1. The total number of patches of all type increased by 176%, from 250,353 to 691,811, while the mean patch size of forest patches decreased from 1.7 ha to 0.6 ha. The number of smaller patches (0–100 ha size class) in dense forest increased rapidly, indicating that a more fragmented landscape accrued over time, a trend that does not bode well for the maintenance of biodiversity in the national park.

Introduction

Mountain ecosystems and forests are experiencing extensive land use changes, due to natural and anthropogenic processes (Klein, 2001; Liu, Daily, Ehrlich, & Luck, 2003). These changes have not only led to the conversion of land cover but also to increased fragmentation of the landscape, with serious environmental implications (Hansen, Dale, Flather, Iverson, & Currie, 2001; Lung & Schaab, 2010; Tuff, Tuff, & Davies, 2016). Land-use/land-cover change (LULCC) is one of the main driving forces of global environmental change and, therefore, is central to issues related to sustainable development (Lambin, Geist, & Lepers, 2003). The impacts of LULCC are profound and range from biodiversity to the global carbon and hydrologic cycles (Skole et al., 2004). In recent decades, most LULCC is attributable to human activities and development (Hurni et al., 1996), although anthropogenic factors also interact with natural environmental change processes (Verburg & Chen, 2000).

KEYWORDSland-use change; forest fragmentation; landscape metrics; Jigme Dorji National Park

ARTICLE HISTORYreceived 11 June 2016 accepted 11 october 2016

© 2016 informa UK limited, trading as Taylor & Francis Group

CONTACT anup saikia [email protected]

http://orcid.org/0000-0002-7546-0736http://orcid.org/0000-0002-3890-6698http://orcid.org/0000-0003-0448-4869mailto: [email protected]://www.tandfonline.com

2 K. ShARMA eT AL.

Changes in forest cover are a matter of global concern due to the ability of forests to sequester carbon and their significance in sustaining global and regional biodiversity. However, with global rates of forest loss currently reported to be 0.6% per year (Hansen, Stehman, & Potapov, 2010), there is a premium on the conservation of the remaining bio-diversity in areas where forests remain. Although moderate levels of disturbance sometimes can increase biodiversity locally (Hughes, 2010; McKinney, 2002), habitat loss and fragmen-tation caused by deforestation are the single largest threat to biodiversity (Sala et al., 2000). Conversion of forested areas to cropland or other land use types, as well as forest degradation as a result of resources extraction, are leading to widespread forest fragmentation (Crooks, Burdett, Theobald, Rondinini, & Boitani, 2011). Forest conversion and degradation has been identified as the most important factor contributing to the decline and loss of species diversity worldwide (Noss & Cooperrider, 1994).

Apart from the impact on biodiversity, fragmentation can also negatively impact eco-system processes and services (Burkhard, Kroll, Muller, & Windhorst, 2009; Laurance, 2007). Quantifying changes in the landscape is imperative for understanding the spatial and structural variability in land use and their associated ecological effects (Turner, 2005). Remote-sensing-based monitoring techniques are particularly effective for forest manage-ment and to formulate land-use policies (Nellis, 2005; Tomppo et al., 2008; Wu, De Pauw, & Zucca, 2013). The analysis of fragmentation using landscape metrics has been a useful approach to assessing land-use change in a wide range of environments (Batistella, Robeson, & Moran, 2003; Cakir, Sivrikaya, & Keles, 2008; Hayes & Robeson, 2009, 2011; Lele, Joshi, & Agrawal, 2008; Li, Lu, Cheng, & Xiao, 2001). In particular, a number of recent studies have quantified landscape patterns within protected areas (Garbarino, Sibona, Lingua, & Motta, 2014; Klauco, Gregorova, Stankov, Markovic, & Lemenkova, 2013; Saikia, Hazarika, & Sahariah, 2013; Terzioğlu et al., 2010; Tomaselli, Tenerelli, & Sciandrello, 2012).

Nestled between India, Nepal, and China, Bhutan has substantial forest resources and its constitution explicitly states, “a minimum of sixty percent of Bhutan’s total land shall be maintained under forest cover for all time” (Anonymous, 2008).

Studies of forest fragmentation in Bhutan’s protected areas, however, do not exist, although a few recent analyses of land-use/land-cover (Bruggeman, Meyfroidt, & Lambin, 2016; Gilani et al., 2015) as also an earlier study using Landsat 2 data (Sargent, Sargent, & Parsell, 1985) are available. Over the period 1990–2010, forest area increased in Bhutan’s protected areas and biological corridors as well as in areas outside protected areas and biological corridors. In the latter instance, non-forest areas were converted to forest areas, such a regeneration being brought about through planting of trees (Gilani et al., 2015). Forest cover in Bhutan remained over 60% during 1990–2011 (Bruggeman et al., 2016).

This study analyses the landscape structure of the Jigme Dorji National Park (JDNP), the second largest protected area of Bhutan. JDNP is part of the Himalayan forest eco-system and possesses rich biodiversity, but there has been no assessment of its land-cover change or degree of fragmentation. Particular focus here is on dense forest cover in JDNP, as this category is of key importance in terms of canopy cover, tree density, and provid-ing habitats for flora and fauna. Here, dense forest cover is defined as forest areas with crown density greater than 70%. As a result, the objectives of this study are (a) to derive land-cover change in the study area during 1990–2015 and (b) to assess the change in landscape structure of the dense-forest land-cover category at class and patch level using landscape metrics.

PhySicAL GeOGRAPhy 3

Study area

Bhutan is a small country situated in the Eastern Himalaya and is a part of the Himalayan biodiversity hotspot (Banerjee & Bandopadhyay, 2016; Chandrappa, Gupta, & Kulshrestha, 2011; Mittermeier, Turner, Larsen, Brooks, & Gascon, 2011; Singh, 2016). With 70% of its area under forest cover (Ministry of Agriculture & Forests [MoAF], 2011), Bhutan has recognized the importance of the landscape approach to biodiversity conservation. For instance, policies in Bhutan have provisioned space for linking protected areas by establish-ing biological corridors (Wangchuk, 2007). Transboundary programs also have been imple-mented with some degree of success in the Himalayas and elsewhere (Chettri & Sharma, 2006; Chettri, Sharma, Shakya, & Bajracharya, 2007; Gurung, 2004; Gurung et al., 2006; Sherpa, Wangchuk, & Wikramanayake, 2004). The combination of the protected areas and biological corridors forms a Bhutan Biological Conservation Complex (B2C2), or a land-scape conservation unit, that encompasses all of the ecosystem types that exist in Bhutan (Sherpa et al., 2004).

JDNP is the second largest protected area in Bhutan and is on the Tentative List for UNESCO World Heritage Site designation. JDNP encompasses an area of 4316 km2 in the northwestern corner of Bhutan and falls within the biologically rich Eastern Himalayan alpine ecosystem (Figure 1). It represents one of the last remaining tracts of the upper Himalayan mountain ecosystem. The park is endowed with temperate broadleaved to alpine forest types, and includes more than 100 species of mammals, 317 species of birds, and many species of insects, reptiles, amphibians and butterflies (Tharchen, 2013). Its habitat zones range from riverine areas to alpine meadows spanning elevations from 1400 to 7000 m (Riley & Riley, 2005). A survey of fauna by Thinley et al. (2015) using camera traps revealed 12 predators, of which two species were listed as endangered, three as vulnerable, and two as threatened on the IUCN Red List. Five species, namely clouded leopard (Neofelis nebulosa Griffith), tiger, leopard, leopard cat (Prionailurus bengalensis Kerr), and Himalayan black bear (Ursus thibetanus [Baron] Cuvier) were listed in Schedule I of Forest and Nature Conservation Act of Bhutan 1995, which accords them the highest protection. Though most predators occurred in all four major habitat types, the highest diversity of wild predators

Figure 1. The location of Jigme Dorji National Park in Bhutan (inset) and its land use/land cover in 1990. source: image date: 7 November 1990.

4 K. ShARMA eT AL.

was found in the mixed conifer forest. Such studies underscore the JDNP as an important conservation area for wild predators, most notably cat species. Two more species of wild predators, namely the snow leopard (Panthera uncia Schreber) and manul or Pallas’s cat (Otocolobus manul Pallas) have been documented at elevations above 4200 m in the JDNP (Thinley, 2013; Thinley et al., 2015). JDNP also is one of the larger tiger habitats among protected areas in Bhutan (Johnsingh, Panda, & Madhusudan, 2010).

Such a rich biodiversity notwithstanding, increasing population in the region is placing greater pressure on the park, including demands for already scarce fuel wood and pasture (Sherpa & Norbu, 1999). In some areas of JDNP, grazing is a major concern, though in other national parks of Bhutan (such as Jigme Singye Wangchuck and Royal Manas) it does not pose any immediate threats to ecosystem stability (Ministry of Agriculture [MoA], 2002). The park also suffers from “extensive harvesting of medicinal plants for the Chinese market and from other forms of poaching – euphemistically called ‘traditional harvesting of nonforest produce’” (Rijksen, 2002).

Data and methods

Landsat 5 TM and Landsat 8 OLI satellite imagery were selected for LULC classification of the study area. Selection of the dates for this imagery was based on minimal cloud cover, time of year, and the time frame in which land-cover change could be monitored since the designation of the protected area (no suitable Landsat 7 ETM + data are available during the period of this study). The images were acquired at the same time of the year to avoid problems of seasonal variation (Table 1) and to access images with minimal cloud cover content. Using ERDAS Imagine 9.2 software, a supervised classification using the maximum likelihood algorithm was adopted. The forest areas were classified into dense forest, mod-erately dense forest, open forest, and shrub (Table 2) following the Forest Survey of India (FSI, 2013) forest classification scheme. Google Earth and data collected using GPS and a spherical densiometer (to assess canopy cover) served as ground control points (GCPs) and training sites. This study used six GCPs. The accuracy of the images was checked with the overall accuracy of 88% in 1990, 76.2% in 2010 and 87.7 in 2015, respectively, and Kappa accuracy of 84, 81 and 78% for 1990, 2010, and 2015, respectively.

While there are myriad metrics for assessing landscape pattern and quantifying their spatial heterogeneity (Lele et al., 2008; Yuan et al., 2015), we use the indices that are most applicable for forest-fragmentation studies (Batistella et al., 2003; Cakir et al., 2008; Galicia,

Table 1. satellite data used in lUlc classification.

Satellite Number of bands Resolution (m) Path/row Observation datelandsat 5 7 30 138/4 7 November 1990landsat 5 7 30 138/4 6 February 2010landsat 8 12 30 138/4 25 November 2015

Table 2. Description of forest categories.

Forest DescriptionDense forest Forest areas with crown density greater than 70%Moderately dense forest Forest areas with crown density greater than 40–70%open forest Forest areas with crown density greater than 10–40%shrub Vegetation cover less than 10%


Zarco-Arista, Mendoza-Robles, Palacio-Prieto, & Garcia-Romero, 2008; Hargis, Bissonette, & David, 1998; Keles, Sivrikaya, Cakir, & Kose, 2008; O’Neill et al., 1988; Sivrikaya, Kadiogullari, Keles, Baskent, & Terzioglu, 2007). Using the spatial metrics program Fragstats (McGarigal, Cushman, & Ene, 2012), we analyze the following: (a) number of patches (NP), (b) percentage of landscape in a particular class or patch type (PLAND), (c) the mean patch size in a particular class or patch type (MPS), (d) percentage of the landscape composed of the largest patch (LPI), and (e) the sum of the lengths of all edge segments on a per unit area basis (or edge density, ED).

Annual deforestation rates were calculated using the compound growth rate formula (Puyravaud, 2003; Vuohelainen, Coad, Marthews, Malhi, & Killeen, 2012):

where, P is percentage of forest loss per year, and A1 and A2 are the amount of forest cover at time t1 and t2, respectively. These quantitative landscape indices not only represent the ecological functions of individual patches (Forman & Godron, 1986; Gardner, O’Neill, & Turner, 1993; Imbernon & Branthomme, 2001; Patton, 1975), but also reflect spatial struc-ture within the entire landscape (Fuller, 2001; Gustafson & Parker, 1992; O’neill, Riitters, Wickham, & Jones, 1999; Viedma & Melia, 1999). In addition, LandScan gridded population data (http://web.ornl.gov/sci/landscan/index.shtml) have been used to show population distribution within the JDNP.

Results and discussion

Landscape-level land-cover change

Analyzing the overall land cover dynamics between 1990 and 2015 shows that dense forest is the predominant land-cover class in JDNP, but that these forests are under increasing pressure primarily from anthropogenic influences including grazing of domestic cattle and yak herds (Thinley & Tharchen, 2014). This is most clearly evidenced by a declining percentage of the dense forest category from 32.8% in 1990 to 27.9% in 2015 (Table 3). The average rate of deforestation for dense forest was 821 ha year−1, amounting to a rate of loss of −0.63% year−1. Open forest, shrub, and agriculture classes increased, with open forests

(1)P =

[

100(

t2− t

1

)

]

ln(A2∕A

1)

Table 3. land-cover change of the Jigme Dorji National Park 1990–2015.

LULc categories 1990 (ha) 2010 (ha) 2015 (ha)

% change 1990–2010

% change 2010–2015

% change 1990–2015

Rate of gain/loss

(ha year−1)snow 76,984.70 61,764.10 63,637.50 −19.77 3.03 −17.30 −533.80Water 14,610.60 3362.60 1849.00 −76.98 −45.01 −87.30 −510.40Dense forest 140,987.10 121,558.00 120,439.80 −13.80 −0.92 −14.50 −821.80Moderately

dense forest46,206.00 34,157.10 37,811.10 −26.07 10.70 −18.10 −335.80

open forest 47,439.50 78,804.60 81,619.40 66.11 3.60 72.10 +1367.10shrub 25,923.20 49,433.80 54,167.80 90.70 9.60 108.90 +1129.70agriculture 108.90 1071.90 1117.50 884.80 4.30 926.80 +40.30Barren land 77,897.00 79,710.60 69,144.60 2.40 −13.20 −11.30 −350.09Built-up 40.80 319.10 394.70 682.60 23.70 868.20 +14.15Total 430,197.40 430,181.51 430,181.50

http://web.ornl.gov/sci/landscan/index.shtml

6 K. ShARMA eT AL.

and shrub registering large gains in area (Table 3). Thus, over a mere quarter century, a landscape dominated by dense forest evolved into a landscape that contained much more open forest and agricultural land cover. An increase of the importance of the built-up class also is noted, ostensibly due to the pressures exerted by increases in population. Similar trends of deforestation have occurred in other tropical and temperate realms of the world.

For comparison, the Nameri NP in the neighboring state of Assam, India saw dense forests decrease at an average annual rate 0.56%, while the overall rate of forest loss was 4.84% annually during 1973–2007 (Saikia et al., 2013). Likewise, in Nepal’s Kailash Sacred Landscape, forest area decreased by about 9% during 1990–2009 (Uddin et al., 2015). Compared to other forest-dominated landscapes, Bhutan is well placed with several factors weighing in its favor, as it “possesses the lowest population and the highest forest cover of any nation in Eurasia, (and) the highest percentage of its natural territory conserved” (Rijksen, 2002). But, the fact that its dense forest cover has declined markedly during 1990–2015 requires continued attention and monitoring (Figure 2).

Landscape metrics and fragmentation

The most important indicators of landscape fragmentation are the number of patches and the change in the number of smaller patches, as measured by patch density (Echeverria et al., 2006; Kammerbauer & Ardon, 1999; Southworth, Munroe, & Nagendra, 2004). Changes in NP, PLAND, MPS, and ED during the study period of 1990–2015 point towards an increasing fragmentation of forest areas (Table 4). PLAND for dense and moderately dense forests declined markedly during 1990–2010.

Figure 2. land use/land cover of the Jigme Dorji National Park, 2010. source: image date: 6 February 2010.


Tabl

e 4.

lan

dsca

pe m

etric

s of t

he JD

NP.

a Per

cent

age

of la

ndsc

ape

in a

par

ticul

ar c

lass

or p

atch

type

.

Land

-use

/ la

nd-c

over

cat

e-go

ries

(yea

r)

PLA

ND

a (%

)N

P (n

umbe

r of p

atch

es)

MPS

(mea

n pa

tch

size

) ha

eD (e

dge

dens

ity) (

m h

a−1 )

1990

2010

2015

1990

2010

2015

1990

2010

2015

1990

2010

2015

snow

9.56

7.67

8.14

8617

9626

101,

077

8.93

6.41

0.63

12.2

12.3

437

.04

Wat

er1.

820.

410.

2314

,090

19,2

1916

,255

1.04

0.17

0.11

4.38

8.55

2.91

Den

se fo

rest

17.5

215

.09

15.2

113

,046

40,5

8847

,556

10.8

2.99

2.53

37.8

923

.62

42.4

2M

oder

atel

y de

nse

fore

st5.

744.

254.

7858

,261

60,4

7812

3,89

50.

790.

560.

326

.631

.04

42.4

4

ope

n fo

rest

5.9

9.78

10.3

139

,699

47,1

6316

1,43

21.

191.

670.

541

.96

30.5

372

.19

shru

b3.

226.

136.

8461

,165

45,3

3016

5,71

10.

421.

090.

3231

.425

.161

.25

agric

ultu

re0.

013

0.13

0.14

794

7524

954

0.13

0.14

1.17

1.52

0.15

0.18

Barr

en la

nd9.

679.

98.

7354

,369

27,5

9779

,389

1.43

2.89

0.87

31.3

48.4

352

.97

Built

-up

0.00

510.

044

0.03

930

831

941

60.

132

1.0

0.94

0.55

0.05

0.05

8 K. ShARMA eT AL.

However, both categories gained marginally during the 2010–2015 period, most likely showing the results of a policy of forest plantation undertaken across Bhutan. PLAND for the open forest category and shrub, however, registered a consistent decline over the entire 1990–2015 span. Agriculture, barren land, and built-up areas showed a nominally declining trend for PLAND.

Of the various land-cover classes, the dense forest category showed very rapid fragmen-tation patterns characterized by a fourfold increase in the number of patches, increasing edge density, and decreasing mean patch size. In contrast, cultivated land and built-up area showed increased MPS, as well as increased NP and ED (as PLAND for these categories also increased).

Increases in edge density are a primary outcome of habitat fragmentation and involves an increase in habitat along edges but a decrease in habitat in large, homogeneous patches. This measure is entirely dependent on the ratio of patch area to patch edge, so landscapes with small patches or irregular shapes will have higher edge density values than landscapes with large patches or simple shapes (Hargis et al., 1998). Edge density in the JDNP increased by 11% in dense forest, 56% in moderately dense forest, and 72% in open forest during 1990–2015. Differences in biotic and abiotic factors accrue within adjoining patches and over time increased edge habitats and their effects as well as greater loss of connectivity (Kabba & Li, 2011) come into play. Edge effects are dominant drivers of change in many fragmented landscapes and can cause serious impacts on ecosystem functioning and under-mine habitat quality (Dantas de Paula, Groeneveld, & Huth, 2016; Haddad et al., 2015; Laurance et al., 2007).

The NP reveals interesting tendencies among the dense, moderately dense, and open forests and shrub categories. The NP of dense forest more than tripled while the open forest category registered a fourfold increase. In contrast, NP for moderately dense forest and shrub doubled (or more) during 1990–2015. Such a trend was consistent during both 1990–2010 and 2010–2015 for dense forest. However, the rate of growth or fragmentation slowed during 2010–2015 for the moderately dense and open forests and the shrub cate-gories. Thus fragmentation strengthened in JDNP during the period, giving rise to a more isolated and diverse assemblage of landscape patches and ecological processes.

Results for Largest Patch Index (LPI) show that dense forest had the largest LPI among the LULC classes, but the rate of change in dense forest for LPI decreased 17% during the 1990–2015 period (Table 5). On the other hand, LPI for other land use class including agriculture and built-up land increased marginally (Figure 3).

Table 5. changes over time in lPi (percent of the landscape occupied by the largest patch).

aModerately dense forest.

LU category 1990 2010 2015 Rate of change (%) 1990–2015snow 3.7 1.81 2.6551 −28.24Water 0.032 0.01 0.0027 −91.56 Dense forest 14.14 11.4 11.6959 −17.28Mod. dense foresta 0.07 0.06 0.0223 −68.14open forest 0.14 0.69 0.1304 −6.86shrub 0.0096 0.06 0.0421 338.54agriculture 0.0006 0.0004 0.0007 16.66Barren land 0.3882 1.14 0.6548 68.67Built-up 0.0002 0.0002 0.0002 0


Patch level metrics of dense forests

While human activities generally are the proximate cause of the declines in patch size and associated impacts on wildlife (Bender, Contreras, & Fahrig, 1998), careful planning can help to achieve a more desirable distribution of patches (Baskent & Jordan, 2002). Patchiness in forested area is of special importance because it serves as an important indicator of nat-ural habitat fragmentation (Kammerbauer & Ardon, 1999). Generally, an increase in the number of smaller patches is considered one of the basic indicators of forest fragmentation (Sivrikaya et al., 2007) and when NP increases along with a decrease in MPS it indicates that the landscape pattern is fragmented (Hulshoff, 1995). Changes in patchiness of dense forest are of primary concern, as they are a key indicator of forest fragmentation and prime habitat. For dense forest patches, the NP in the

10 K. ShARMA eT AL.

Tabl

e 6.

Pat

ch m

etric

s of t

he d

ense

fore

st la

nd-u

se c

ateg

ory.

a NP

is n

umbe

r of p

atch

es.

b MPs

is m

ean

patc

h si

ze.

Patc

h si

ze19

9020

1020

15N

PaA

rea

(ha)

MPS

b (ha

)N

PA

rea

(ha)

MPS

(ha)

NP

Are

a (h

a)M

PS (h

a)<

111

,184

2472

.76

0.22

38,2

8674

96.9

0.2

45,2

8075

940.

161–

4.9

1387

2991

.29

2.15

1912

3835

.35

2.0

1841

3849

2.1

5.0–

1934

832

05.3

9.21

219

2584

.811

.830

531

5410

.34

20–9

910

443

55.9

41.8

7328

57.6

839

.14

110

4461

40.5

510

0–99

916

4154

.925

9.6

2051

56.9

125

7.8

1547

6931

7.93

1000

–499

96

9949

.416

58.2

577

55.9

315

51.2

450

3412

58.5

5000

+1

113,

857.

411

3,85

7.4

191

,870

.11

91,8

70.1

191

,578

91,5

78To

tal

13,0

4614

0,98

7.1

10.8

40,5

1612

1,55

7.7

3.0

47,5

5612

0,43

92.

53


nominal gains made in area and MPS in the intermediate size categories were more than outweighed by increases in NP in the smallest size category and declines in area as well as MPS of the largest patch size category.

These changes towards a splintering of dense forests are perhaps more evident when the patch – size results are analyzed as proportions of the dense forest class (Table 7). The share of the

12 K. ShARMA eT AL.

Poaching of wildlife and high-value medicinal plants by poachers from across the inter-national border to the north of the park appears to be more of a problem than by settlers within (Thinley & Tharchen, 2014).

Conclusions

This study has analyzed land-cover dynamics of JDNP between 1990 and 2015 using sat-ellite-based estimates. Results showed that forest cover decreased throughout the study period, with an increase in open forest and other land use classes. Importantly, these land use/cover changes have resulted in the reduction of dense and moderately dense forest, as well as increased fragmentation (increases in patch number and decreases in patch size). Due to increasing population density of both humans and livestock, there is ostensibly a relatively higher pressure on the resources of this protected area. The current scenario could be an outcome of the impacts of grazing of feral livestock and firewood collection, as noted in other work (Rijksen, 2002).

Continued monitoring of the spatial and temporal composition and configuration of this forest ecosystem is increasingly important for forest management and maintaining biodiversity. An irreplaceable wealth of biodiversity is concentrated in a very small por-tion of our planet and an extraordinary concentration of biodiversity within hotspots exists (Mittermeier et al., 2011), with the JDNP typifying this situation considering that Bhutan lies entirely within the Himalayan biodiversity hotspot. Bhutan has had an excellent

Figure 4. Population distribution in the Jigme Dorji National Park, derived from landscan 2014 data.


conservation record and is a world leader in protected area planning and management (Rajaratnam, Vernes, & Sangay, 2016). If Bhutan’s ecosystems and mountain biodiversity are to be protected, this trend of fragmentation of the JDNP must be prioritized and afforded due attention by authorities and its stakeholders.

Acknowledgements

The population map of the JDNP 2014 was made using the LandScan 2014™ High Resolution Global Population Data Set copyrighted by UT-Battelle, LLC, operator of Oak Ridge National Laboratory under Contract No. DE-AC05-00OR22725 with the United States Department of Energy. The United States Government has certain rights in this data set. Neither UT-Battelle, LLC nor the United States Department of Energy, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of the data set.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported with funding from the Sherubtse College, Royal University of Bhutan.

ORCID

Kiran Sharma http://orcid.org/0000-0002-7546-0736Pankaj Thapa http://orcid.org/0000-0002-3890-6698Anup Saikia http://orcid.org/0000-0003-0448-4869

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http://dx.doi.org/10.1016/j.landurbplan.2015.04.003http://dx.doi.org/10.1016/j.landurbplan.2015.04.003http://dx.doi.org/10.1007/s100210000033http://dx.doi.org/10.1046/j.1472-4642.1999.00069.xhttp://dx.doi.org/10.1046/j.1472-4642.1999.00069.xhttp://dx.doi.org/10.1007/s00267-012-9901-yhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.472.7857&rep=rep1&type=pdfhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.472.7857&rep=rep1&type=pdfhttp://dx.doi.org/10.1007/s10745-013-9634-4http://dx.doi.org/10.1007/s10745-013-9634-4http://dx.doi.org/10.1016/B978-0-12-802213-9.00035-3http://dx.doi.org/10.1080/17538947.2013.825656http://dx.doi.org/10.1007/s10980-015-0219-z

AbstractIntroductionStudy areaData and methodsResults and discussionLandscape-level land-cover changeLandscape metrics and fragmentationPatch level metrics of dense forests

ConclusionsAcknowledgementsDisclosure statementFundingReferences

land-use/land-cover change and forest fragmentation in the jigme...

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