232
undertaken by carefully examining the position and shape of stripes on the flanks,
limbs, forequarters and sometimes the tail (Schaller 1967; Karanth and Nichols
1998). Each tiger captured in a photograph was then assigned a unique identification number (e.g. TM1M, TM2F for the first and second tiger of male and female
gender). Similar procedures were undertaken for leopard and clouded leopard.
Individual capture histories for tigers, leopards and clouded leopards were developed in a standard ‘X-matrix format’ (Otis et al. 1978) and these were analyzed
using models developed for closed populations within the programs CAPTURE
(Rexstad and Burnham 1991) and MARK (White 2008). The abundance of all three
species for the effective sampled area was estimated by using a buffer around the
locations, determined using half the mean of the maximum distance moved
(HMMDM) model, and the area associated also with a trapping grid polygon
(Karanth and Nichols 1998). A habitat mask was also used to remove non- tiger
habitat (e.g., deep water, human settlements; Karanth and Nicols 2002). The density
(per 100 km
2
) was then estimated by dividing this area by the population size (number of individuals). The density of individual prey species, which were also recorded
through the camera traps, was estimated using the program DISTANCE (Thomas
et al. 2010). This online software works by using detection functions that model the
probability of detecting an animal given its distance from the transect. Further
details of both methods can be found in Jhala et al. (2010).
Spatial Analysis of Field Data
The spatial configuration of home ranges of individual cats is an important property
of their social systems and has been defined as an area traversed by individuals during normal activities of food gathering, mating and caring for young (Dillon and
Kelly 2007). For this study, the GPS locations for each capture event and for identified individuals were extracted and plotted spatially. Where an animal was photographed, the distance from the camera trap was determined and a minimal-bounding
polygon was constructed around each of the individual point locations where the
same individual was sighted and also for all species of the same type. The resulting
spatial datasets were then used to quantify ranging behavior, niche overlap and
movement in relation to observed land cover types and landscape dynamics. Home
range size is considered an important predictable aspect of an animal’s feeding
strategy and has been related to food density, metabolic needs and the efficiency of
movement. The metric also indicates the degree of overlap as a function of territory
and can reflect the variation in population and community characteristics. For
example, home-range size is frequently correlated inversely with population density
and home-range exclusiveness can indicate significant inter and intra-specific competition (ibid). To calculate the ranging patterns of tigers and sympatric carnivores
within the habitat, a point density tool was used which calculates a magnitude per
unit area from point features falling within a neighborhood around each cell. In
addition, a minimum boundary geometry tool was used, which represents a
S. Ghosh and R. Lucas
undertaken by carefully examining the position and shape of stripes on the flanks,
limbs, forequarters and sometimes the tail (Schaller 1967; Karanth and Nichols
1998). Each tiger captured in a photograph was then assigned a unique identification number (e.g. TM1M, TM2F for the first and second tiger of male and female
gender). Similar procedures were undertaken for leopard and clouded leopard.
Individual capture histories for tigers, leopards and clouded leopards were developed in a standard ‘X-matrix format’ (Otis et al. 1978) and these were analyzed
using models developed for closed populations within the programs CAPTURE
(Rexstad and Burnham 1991) and MARK (White 2008). The abundance of all three
species for the effective sampled area was estimated by using a buffer around the
locations, determined using half the mean of the maximum distance moved
(HMMDM) model, and the area associated also with a trapping grid polygon
(Karanth and Nichols 1998). A habitat mask was also used to remove non- tiger
habitat (e.g., deep water, human settlements; Karanth and Nicols 2002). The density
(per 100 km
2
) was then estimated by dividing this area by the population size (number of individuals). The density of individual prey species, which were also recorded
through the camera traps, was estimated using the program DISTANCE (Thomas
et al. 2010). This online software works by using detection functions that model the
probability of detecting an animal given its distance from the transect. Further
details of both methods can be found in Jhala et al. (2010).
Spatial Analysis of Field Data
The spatial configuration of home ranges of individual cats is an important property
of their social systems and has been defined as an area traversed by individuals during normal activities of food gathering, mating and caring for young (Dillon and
Kelly 2007). For this study, the GPS locations for each capture event and for identified individuals were extracted and plotted spatially. Where an animal was photographed, the distance from the camera trap was determined and a minimal-bounding
polygon was constructed around each of the individual point locations where the
same individual was sighted and also for all species of the same type. The resulting
spatial datasets were then used to quantify ranging behavior, niche overlap and
movement in relation to observed land cover types and landscape dynamics. Home
range size is considered an important predictable aspect of an animal’s feeding
strategy and has been related to food density, metabolic needs and the efficiency of
movement. The metric also indicates the degree of overlap as a function of territory
and can reflect the variation in population and community characteristics. For
example, home-range size is frequently correlated inversely with population density
and home-range exclusiveness can indicate significant inter and intra-specific competition (ibid). To calculate the ranging patterns of tigers and sympatric carnivores
within the habitat, a point density tool was used which calculates a magnitude per
unit area from point features falling within a neighborhood around each cell. In
addition, a minimum boundary geometry tool was used, which represents a
S. Ghosh and R. Lucas