No longer tracking greenery in high altitudes: Pastoral practices of Rupshu nomads and
their implications for biodiversity conservation
Methods
We applied the ‘Area tool’ in ‘Hawth’s tools extension’ of ArcGIS 9.2 (ESRI Inc.) for
estimating the approximate area of seasonal pasture. Areas > 5,300 m in elevation were
removed from the analysis as they lie above the vegetation limit.
Argali use
The vantage points for observations of argali were determined during previous
reconnaissance surveys to allow for a complete overview of the study area. The observation
of argali groups covered the entire daylight period, i.e. between 0600 and 1900 hrs. The
observed groups’ locations (n=102) were recorded into a GPS and overlaid on topographical
maps and DEM.
Livestock use
Each nomad campsite was assigned a weight (SUD/campsite) which we used to generate the
intensity of use for the point using kernel density estimation (KDE) (Figure 2b). We used
fixed kernel estimation using the Gaussian kernel function to estimate the density around the
point (Silverman, 1986; Seaman & Powell, 1996). The smoothing parameter (h) was chosen
using least squares cross validation (LSCV) method (Summer h: 2676.9, Winter h: 3795.5)
(Worton 1995; Gitzen and Millspaugh 2003). As in the context of ‘home range’ analysis, the
density at any location is also an estimate of time spent there, which we estimated as SUD /
campsite. Hence, for camp locations, the 50% volume contour (VC) will show the area with
higher pressure and intensity progressively reduced towards the edge (95% VC). In the home
range context, it will show that these are the 'core zones' - areas that are important due to
some key resource (snow free pastures, lower altitude, and seasonal water).
Argali locations were mainly based on actual observations of the groups. For comparison
with livestock activity areas, it was important to estimate utilization distributions (UD)
(Worton 1989) and make spatial predictions in terms of area of influence or home ranges for
both of the considered groups. We therefore used KDE to delineate spatially the utilizing
distribution of argali based on the density of the argali observations. Fixed-kernel estimates
for argali were made using Gaussian bivariate normal function and bandwidth selection using
LSCV procedure (Summer h-2772.4, Winter h-4703.2). For argali, 50% (VC) will show a
boundary of the area that contains core of the probability density distribution (Seaman &
Powell 1996). The 95% VC would contain most of the points that were used to generate the
kernel density estimate. This density forms a basis for measuring the overlap in area of
individuals or species in terms of area and intensity of use (Smith & Dobson 1994).
Each of the volume contours for both the groups were converted into polygons to estimate
area enclosed by them. The KDE estimation was carried out using ade4 library in R (Chessel
et al. 2004) and areas for the polygons enclosed by VCs were estimated in ArcGIS 9 using
area module of Hawth’s tool extension.
To assess the UD overlap, we used the following formula to estimate the overlap index (OI)
(Cole’s coefficient of association – (Cole 1949, Kenward 2001):
OI  2 *  Overlap  A1  / A1  A2

1
Where A1 is area of argali UD polygon and A2 is area of livestock UD polygon. We assessed
the OI bounded by the 50 % and 95% volume contours of the two UDs. Overlap among the
seasonal polygons was estimated using intersect tool in the ArcToolbox in ArcGIS 9. The
overlapping polygons were obtained using this method and their area was estimated again
using the ‘area’ module (see above). We assessed the OI of 50% and 95% volume contours
for argali and livestock during summer and winter.
The overlapping polygons were obtained using this method and their area was estimated
again using the ‘area’ module. We assessed the OI of 50% and 95% volume contours for
argali and livestock during summer and winter.
To estimate the magnitude of the habitat variables in the utilizing polygons of argali and
livestock, we sampled 300 random points, each in the argali and core zones. Terrain variables
altitude and slope were extracted from DEM using ArcGIS 9 (ESRI Inc). We observed the
distribution of the habitat variables altitude and slope for all the sampled points from the core
zones of livestock activity and argali groups.
Results
Table S1. Individual camp sites and the estimated grazing intensity. SU-Sheep units (total
number of livestock including Sheep, goat, Yak and horse), SUD- Sheep Unit Days
(measurement of time spent by livestock at a camp site).
Days spent SUD
CampID No. of families SU
at site
1
2
578
31
17,918
2
2
578
31
17,918
3
2
578
31
17,918
4
3
866
31
26,846
5
6
1,148 25
28,700
6
4
765
134
1,02,510
7
2
578
91
52,598
8
24
4,592 89
4,08,688
9
2
578
91
52,598
10
2
578
91
52,598
11
3
866
89
77,074
12
6
1,733 89
1,54,237
13
4
1,155 89
1,02,795
14
12
2,297 89
2,04,433
15
2
578
31
17,918
16
2
578
31
17,918
17
8
2,310 61
1,40,910
18
5
1,444 91
1,31,404
19
3
866
91
78,806
20
2
578
91
52,598
21
32
5,882 134
7,88,132
22
16
2,965 134
3,97,326
23
32
5,882 60
3,52,934
24
25
4,606 85
3,91,510
25
32
5,882 35
2,05,878
26
16
4,376 61
2,66,936
2
27
28
29
Overlap Index (OI)
12
10
9
2,236
2,769
2,502
89
89
61
1,98,990
2,46,468
1,52,596
Table S2. Seasonal range use of the argali (Ovis ammon) and livestock groups and their
spatial overlap in the Tso Kar basin of easter Ladakh, India.
50% Volume contours (Km2)
95% Volume contours (Km2)
Overlap (@)
Season
Argali
Livestock Overlap
Argali
Livestock Overlap 50% 95%
Summer
28.55
7.26
0
109.01
32.1
19.43
0
13.67
Winter
36.83
24.03
7.85
136.8
141.4
167.6
12.93 60.24
Argali
summer Vs
28.55
24.03
2.41
109.01
141.4
90.78
4.61
36.25
Livestock
winter
B
OI for 50% Volume contour
The overlap was marginal for all the three tested combinations (Table 2 and Figure 3-a,b and
c). The largest value of OI was 12.9 %, which was for the combination of argali and livestock
in winter. For other two combinations, argali summer vs livestock summer and argali summer
vs livestock winter, the OI values were extremely low or 0, indicating no overlap or very
marginal overlap.
OI for 95% Volume contour
OI for 95% volume contours varied for different combinations (Table 2, Figure 3-a,b and c).
Highest overlap for 95% VCs was observed for winter whereas the least overlap was
observed for summer. The OI values for argali summer vs livestock winter, however, were
intermediate.
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Figure S1. Maps showing – a) Seasonal pastures in winter, nomads’ camp sites locations, b).
Utilizing Distribution of livestock around camp sites, estimated based on grazing pressure
(calculated as Sheep unit days (SUD)) along with 50% and 95% Volume contours calculated
using Kernel density estimation.
4