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Modeling impact of economic development projects on Tiger conservation landscape – a
case study from Nilgiris, India
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Abstract
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The Nilgiris, part of the Nilgiri Biosphere Reserve (NBR) in the Western Ghats range of
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southwestern India support a good population of Indian tiger (Panthera tigris). However,
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anthropogenic disturbances pose threat to the tiger habitat in the region. We used geographic
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information system (GIS) based ‘Tiger Filter’ model to assess the impact of developmental
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projects on tiger populations and landscape. The model uses field-based information to
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identify core habitat areas and potential corridors for dispersal, connecting these core areas.
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The model indicates that the proposed road widening and the railway line will result in
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fragmentation of core habitat areas and decrease in connectivity between habitat patches. The
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model allows identification of key restoration areas and thereby makes recommendations for
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appropriate mitigation such that adverse impacts on tiger conservation landscape will be
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minimized.
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Keywords: Nilgiris, tiger filter, habitat patch, core area, potential corridor.
G. Areendran*1, M. Raj1, K. Raj1, S. Mazumdar1, J. Forest2, M. Munsi1, and E.
Wikramanayake2
1
Indira Gandhi Conservation Monitoring Centre, WWF-India, 172-B, Lodi Estate, New Delhi
110003, India
2
Conservation Science Program, WWF US, 1250 Twenty-Fourth Street NW, Washington
D.C. 20037, U.S.A.
E-Mail: gareendran@wwfindia.net1, mohanraj@wwfindia.net1, kraj@wwfindia.net1,
smazumdar@wwfindia.net1, jessicaforrest@wwfus.org2, madhushreemunsi@gmail.com1,
ericw@snt.lk2
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1. INTRODUCTION
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The historical range distribution of tigers extended from the Caspian Sea to the island of Bali
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in Indonesia (Seidensticker et al., 1999). Over the past century this range has shrunk, with
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tiger extinctions in Bali and Java, and from large parts of central Asia around the Caspian
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Sea. Even within the current distribution, habitat loss and fragmentation has now restricted
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tigers to a mere 7% of the historic range (Dinerstein et al., 2007), where they are being
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confined to isolated protected areas and other remaining habitat patches.
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As a space-requiring large carnivore, tiger’s ecology and behavior is compromised as
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populations become isolated in habitat patches that are too small to sustain ecologically,
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demographically, and genetically viable populations, prompting a paradigm shift in tiger
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conservation strategies (Wikramanayake et al., 1999). Thus in the last decade conservation
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biologists have identified landscapes where breeding populations are ecologically and
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genetically linked by corridors, allowing for tiger populations to be managed as meta-
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populations (Wikramanayake et al., 1999; Sanderson et al., 2010). One imperative
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conservation issue is to ensure that the remaining tiger conservation landscapes are not
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fragmented during national and regional development processes and plans.
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Wikramanayake et al., (2004) used geographic information system (GIS) based cost distance
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model to design a tiger conservation landscapes in the Terai Arc landscape located along the
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Himalayan foothills. Worldwide geospatial tools are being used to devise management plans
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for conservation purpose. GIS together with remote sensing has been recognized as
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invaluable tool for studies ranging from assessing suitability of habitats for wildlife
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populations, evaluating human impact on wild land, to management of wildlife corridor
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(Kushwaha et al., 2000, Singh et al., 2002, Kushwaha and Hazarika, 2004, Nandy et al.,
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2007, Beier et al., 2008).
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The ‘Tiger Filter’ is a GIS based model developed to help in assessing the impacts of
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economic development projects on tiger conservation landscapes and build appropriate
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mitigations to prevent loss and fragmentation of critical tiger habitat. The model identifies
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‘core areas’ and ‘potential corridors’ between these core areas using field-based information
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about tiger populations, distributions, and habitat use. The “Tiger Filter” is thus intended to
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provide a science based decision making to the government and other stakeholder for altering
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economic development projects to have least impact on the tiger population, habitat and their
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conservation landscapes. It also provides guidance and strategic directions to maintain habitat
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integrity and connectivity within conservation landscape. Finally it is helpful for the forest
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managers to incorporate tiger conservation priorities in the mainstream of national economic
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development and land use planning.
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2. METHODS
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2.1 Study area
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The model was developed and applied as a pilot analysis for the Nilgiris in the Western Ghats
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mountain range of southwestern India. The Nilgiris, is part of the Nilgiri Biosphere Reserve
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(NBR) in Western Ghats, and is home to several endemic floral and faunal species (Baskaran
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and Boominathan, 2010; Sharma, 2008), and is ranked very high for biodiversity values in
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South Asia (Sharma, 2008). The ‘area of interest’ has a diversity of vegetation types and
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supports globally important populations of Asian elephant, tiger, gaur, and other endangered
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mega fauna species (Baskaran and Boominathan, 2010).
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The northern part of the NBR was selected as the ‘area of interest’ for the analysis (Figure 1).
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Overall, the area is a landscape of contiguous land management units with some degree of
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protection and conservation-related regulations, from Waynad Wildlife Sanctuary in the west
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to the Segur plateau, which connects to the Sathyamangalam forest division, in the east. The
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landscape
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(http://www.forests.tn.nic.in).
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Figure 1
includes
two
important
tiger
reserves
in
Mudumalai
and
Bandipur
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There are several scattered villages and a network of roads, some of which bisect tiger
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reserves and other protected areas, throughout in the landscape (Figure 2). These are
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considered to be major sources of disturbance to wildlife (Daniel et al., 1995). Two
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development projects, the proposed widening of the Manthavadi road and the railway line
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(now scrapped following protests by environmentalists and conservationists) from Bannari to
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Talavadi in the Sathyamangalam forest division (Figure 2) are expected to further fragment
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existing habitat and decrease connectivity.
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Figure 2
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2.2 Data Input
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Base maps for the tiger habitat model were prepared by using administrative maps of the
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forest division of Nilgiri Biosphere Reserve provided by Karnataka forest department. Survey
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of India (SOI) toposheets (1:50000) were used for generating roads, railroads, settlements,
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and other relevant infrastructure data (Table 1). Archived data for land use/land cover
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(LULC) for Landsat ETM (path and row 143/52 and 144/52) of 27th March 2001 with a
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spatial resolution of 30 m was available with the authors and was used for the model.
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Table 1
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2.3 Habitat Suitability Mapping
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‘Habitat values’ were assigned to each land use/land cover class (Table 2). These values
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reflect the relative ‘suitability’ of the land use classes to tigers, based on habitat quality,
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habitat use and occupancy by tigers and prey species. The scores were developed with the
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interactive focused discussions with field biologist, field foresters, local people and intensive
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field knowledge. In this index, higher scores represent relatively more suitability in terms of
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tiger occupancy and abundance and lesser scores reflect relatively lower suitability.
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Table 2
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Scores were assigned to reflect a relative ‘ecological cost’ of occupying or using areas of the
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landscape based on anthropogenic impacts (Table 3). These ‘ecological cost scores’ were
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assigned negative numbers to counter the ‘habitat suitability’ values of an area. Thus, tigers
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close to a settlement (<1 km) would have to bear an ecological cost of -3, with the cost
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decreasing further from the settlement (i.e., ecological cost of -2 for 1 to 2 km from the
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centre, and a cost of -1 for 2 to 3 km from the centre).
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Table 3
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Similarly, tigers venturing close to roads would have to bear greater ecological costs than
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tigers further away, represented by negative numbers. Because larger roads have a greater
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impact (e.g., decreasing the probability of crossing a wider road during dispersal because of
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more vehicular traffic, less habitat cover on either side of the road, etc.), wider and more
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intensely used roads were assigned appropriate ecological cost scores to reflect the
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probability of using or survival in these areas.
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The habitat values and ecological cost scores were summed in ArcGIS to derive a ‘Habitat
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Suitability Map’ in raster format (Figure 3). Thus, each pixel (30 m) would have a ‘Habitat
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Suitability Score’ that reflects the likelihood of use and occupancy by tigers.
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Habitat suitability scores indices (≥7 to 10 as Good Habitat; ≥ 4 to 7 as Suitable Habitat; ≥2
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to 4 as Marginal Habitat; and, < 2 as Unsuitable Habitat) were used to represent the habitat
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suitability. This classification was based on consultations with field biologists and cross
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validation with field data.
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Figure 3
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The Habitat Suitability Map was used to calculate and identify ‘core areas’ that can support
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breeding tigers. In Tiger habitat landscape matrix, patches of habitat with habitat suitability
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scores of more than equal to 7 and with the patch size more than equal to 75 km 2 were
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considered as ‘core areas’ based on the following criteria : (a) the estimated average territory
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size of a breeding female tiger in the Nilgiri is ~ 15 km2; (b) a core breeding population is
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estimated at ≥ 5 breeding females and (c) thus, a minimum size of a core area required to
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support at least 5 breeding females is ≥ 75 km2. While ‘habitat patches’ with the scores more
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than or equal to 4 and patch size between 1 and less than 75 km2 were regarded as moderate
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suitable but were non-core areas.
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2.4 Cost Distance Model
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A ‘cost grid’ from the habitat suitability map was created, where the habitat suitability scores
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were inverted to a scale of 1 to 18, with 18 as the highest ecological cost of traversing
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landscape’s habitat and 1 as the lowest cost; thus a tiger dispersing from a core area would be
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more likely to survive in areas (pixels) with the lowest cost scores in this cost grid. A cost
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distance model was applied to the cost grid in ArcGIS to identify the degree of connectivity
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between core areas, and thus ‘potential corridors’ for dispersal. The cost distance model helps
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to determine an ecological cost of moving between core areas, based on habitat suitability
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and distance travelled. This can help determine potential paths used by tigers during
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dispersal, assuming that tigers are more likely to use habitat linkages with lower ecological
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costs to movement.
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The ‘better’ corridors, lower ecological costs (those more likely to be used) are indicated in
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the Figure 4. The probability of a corridor being used for dispersal purpose decreases with
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increasing ecological cost.
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Figure 4
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Smaller, non-core habitat fragments act as ‘stepping stone’ habitat in the context of
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landscape-scale connectivity, and are thus essential for corridor functionality. If these
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fragments are removed from the landscape, the cost distance model shows that connectivity
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can be severely compromised.
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2.5 Impacts of infrastructure on connectivity
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To model the impacts of infrastructure on connectivity, Manthavadi highway project and
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Sathyamangalam railroad were used. The plans to upgrade the existing Manthavadi road to a
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four-lane highway will increase the width of the road, and result in greater vehicular traffic. It
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is also likely that there will be a wider clearing on either side of the road. These
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developments will represent a wider gap that tigers will have to cross, relative to the current
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road. Therefore, ecological cost of the wider road was re-adjusted from the criteria for a 2-
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lane road to a 4-lane highway. The proposed railroad track was also overlayed and assigned
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ecological cost scores (Table 3). A habitat suitability map was derived with re-adjusted
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habitat suitability scores, and cost-distance model applied to show the impacts of road
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expansion (Figure 5) and railroad (Figure 6) on tiger habitat and connectivity.
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Figure 5
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Figure 6
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3. RESULTS AND DISCUSSION
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The habitat suitability map (Figure 3) shows that there are seven core areas in the Nilgiris
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(Table 4). However, several of these have tenuous habitat linkages that represent bottlenecks,
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which are highlighted as a result of the cost distance model (Figure 4). Cost distance model
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also shows that overall, the core areas are linked by relatively low-cost corridors, represented
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in yellow with cost distance values <28,429 (cost distance value represents the total sum of
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costs multiplied by distance of traversing from a grid pixel in the matrix back to its source).
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However, some core areas—such as the one that extends across Sathyamangalam and Nilgiri
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North (in centre of the landscape) - are long and narrow (Figure 4), a shape that can allow
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anthropogenic impacts to intrude into the centre of the core area. Therefore such core areas
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may not be well suited to support breeding tigers. The cost distance model, however, allows
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us to strategically identify and prioritize sources of anthropogenic impact and implement
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mitigations to reduce these intrusive impacts. For instance, minimizing the impacts from
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selected villages can change the configuration of the core area and reduce the perimeter/area
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ratio, thus creating more secure, undisturbed core areas (Figure 7).
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Figure 7
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The seven core areas, representing 3760 km2 can potentially support 250 tigers (approx.)
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(Table 4). If Sathyamangalam rail road is built, an important core area would become
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fragmented. Iincrease in the number of core areas from 7 to 8 is because of fragmentation
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accompanied by a decrease in the total core area, smaller average core size, and importantly,
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a decrease in the number of breeding tigers that can be supported in these core areas. If the
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goal is to double the tiger population in the landscape, it is important instead, to reduce
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further fragmentation of core areas and restore additional habitat.
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Table 4
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A ‘core area’ thus represents natural habitat patches with relatively least anthropogenic
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impacts that can sustain at least 5 breeding female tigers. They should be managed for tigers
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and their prey, strictly enforced against illegal hunting and other human activities that can
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negatively impact tiger populations. These areas should be declared as ‘no-go’ areas for
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development. The population size of 5 breeding females does not represent a minimum viable
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population for genetic purposes; but to define the spatial extent of the core area only. Habitat
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linkages between the core areas that will be more likely to be used by dispersing tigers than
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other matrix areas have been defined as ‘potential dcorridors’. Potential corridors are
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identified and distinguished from other matrix habitat by the suitability of the habitat for tiger
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use, distance from core areas, availability and suitability for prey species, degree of
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disturbance and anthropogenic impacts.
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Because tiger numbers are correlated to their prey base, a recovery program should also
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include reducing hunting of tigers and prey, and other anthropogenic impacts in the core
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areas, especially those that result in habitat degradation, undue disturbance, and human-tiger
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conflict.
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Assessing the impacts of infrastructure on tiger habitat
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Tigers are a conservation dependant species that require large spaces; however, tiger habitat
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is becoming increasingly fragmented and populations are being isolated within smaller
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spaces, compromising the integrity of tiger ecology, behavior, and population viability
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(Wikramanayake et al., 1998, 2010). Thus, over the last decade, tiger conservationists have
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been calling for conserving landscapes where core areas with breeding populations are
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connected with corridors to manage meta-populations (Wikramanayake et al., 1999,
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Dinerstein et al., 2006, Dinerstein et al., 2007). But as tiger range countries push for
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economic development, the function of the intervening habitat matrix in tiger landscapes, that
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represent the connectivity, is overlooked; thus infrastructure and other economic
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development projects are planned for these areas without assessing the impacts to
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conservation efforts at landscape scales. Consequently, critical tiger corridors would be
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severed and populations may become isolated and the long-term ecological, demographic and
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genetic viability would be compromised.
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As demonstrated in this analysis of the impacts of Manthavadi road expansion and
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Sathyamangalam railroad, the output maps can be used to demonstrate to policy-makers the
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impacts of large development projects on tiger habitat and tiger populations. However, a
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prerequisite is the preparation of a tiger habitat and conservation layer that identifies core
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areas and important corridors that can be integrated into government land-use planning
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processes within appropriate institutions.
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Thus, it is important that this analysis should be applied to: first, define the current state and
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configuration of the core areas and corridors in the tiger landscape; second, identify priority
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restoration areas to ensure adequate core habitat and corridors are available to conserve a
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viable tiger population and meet conservation targets; third, include this core and corridor
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configuration into the land-use planning processes at appropriate institutions at local,
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provincial, state, national etc. so they become legitimate conservation areas (rather than be
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considered ‘undeveloped’ lands); and fourth, assess and monitor any planned and pipeline
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infrastructure and development projects against this map to determine the impacts on core
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areas and tiger corridors, and appropriate decisions should be taken about project
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implementation. We suggest that the analysis be applied to tiger conservation landscapes
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before they become further fragmented and tigers are confined to small, isolated protected
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areas that will eventually compromise their ecological, demographic, and genetic integrity,
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and thus the long-term survival.
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List of Tables
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Table 1: Data sources used to create land cover and land use map for the area of interest.
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Table 2: Habitat values assigned to each LULC classes
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Table 3: Ecological cost scores based on anthropogenic impacts
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Table 4: Core areas and corridor information in the Nilgiris landscape
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Table 1: Data sources used to create land cover and land use map for the area of interest.
Data
Land use/ land cover
Road
Settlement
Protected Area
Proposed Railway
Proposed road through
Bandipur
Scale/ resolution
30 m
1:50K
1:50K
1:50K
1:50K
Source
Satellite Image - Landsat
SOI toposheets
SOI toposheets
Forest Department
WWF India
Field data
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Table 2: Habitat values assigned to each LULC classes
Land use/ land cover
classes
Semi Evergreen Forest
Dry Deciduous Forest
Moist deciduous
Thorn Forest/scrub
Shola Grassland
Water Body
Open/Barren/Rocky area
Plantation
Wasteland
Settlement
Agriculture
Fallow land
Habitat value
7
10
8
8
6
0
0
2
0
0
-2
0
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347
348
349
350
351
352
353
354
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Table 3: Ecological cost scores based on anthropogenic impacts
Distance to Settlement
< 1 km
1 to 2 km
2 to 3 km
3 km and more
Distance to Road (2-lane, low to moderate
traffic)
< 1 km
1 to 2 km
2 to 3 km
3 km and more
Distance to Road (4- lanes, high traffic)
< 1 km
1 to 2 km
2 to 3 km
3 km and more
Distance to Railway
< 1 km
1 to 2 km
2 to 3 km
3 km and more
Ecological Cost
Score
-3
-2
-1
0
-3
-2
-1
0
-4
-3
-2
0
-3
-2
-1
0
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Table 4: Core areas and corridor information in the Nilgiris landscape
Description
Area of core habitat
Current
scenario
4653 km2
Predicted scenario after
development
4406 km2
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8
664 km2
550 km2
0.0019
0.002
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Number of core habitat areas
(area ≥ 75 km2)
Average core area size (area ≥ 75
km2)
Core area configuration Index
(Average Perimeter/Area of core
blocks) (area ≥ 75 km2)
List of Figures
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Figure 1: The ‘area of interest’ (within the box) in the Nilgiris of the Western Ghats range in
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southwestern India.
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Figure 2: Land cover, protected areas and physical features of the Nilgiris with the proposed
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Manthavadi road expansion and the Sathyamangalam rail road traces
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Figure 3: (a) Habitat Suitability Map of the Nilgiris based on habitat type and the ‘ecological
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cost’ from anthropogenic impacts. (b) Classification of Habitat types. The circles are due to
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the estimated anthropogenic impacts from settlements that ‘adjust’ the habitat scores.
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Figure 4: The cost distance model The map highlights bottlenecks, where connectivity is
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narrow and tenuous (e.g. indicated by blue arrows), and human-impact areas where
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restoration can be strategically directed (e.g. conservation efforts can be directed to the
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villages indicated by ‘X’s to restore habitat and increase the extent of the core area.
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Figure 5: The impact of Manthavadi road expansion project on tiger habitat and corridors.
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The corridor cost values increases from the (a) pre-expansion model to the (b) post expansion
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model, making it more unsuitable (refer color ramp in figure 4).
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Figure 6: The potential impact of the Sathyamangalam railroad on tiger habitat and corridors.
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The (a) core area across Sathyamangalam and Nilgiri north (b) will become more fragmented
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as a result of the railroad (refer color ramp in figure 4).
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Figure 7: If the impact of (a) six villages (indicated by red arrows) along the south-western
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border of the Nilgiri north-Sathyamangalam core area are (b) removed or minimized, the
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configuration of the core area can be significantly improved. (refer to the suitability classes in
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figure 3a).
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429
a
b
430
431
Figure 6
432
433
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435
436
437
438
439
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441
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24
444
445
446
447
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449
a
b
450
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452
Figure 7
25