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Appendices
Appendix A: Further information on the Maxent Species Distribution Modelling (SDM) procedure
Dr Philip McGowan (Director of World Pheasant Association when work was conducted and co-
author) and Dr Peter Garson (Chair of IUCN-SSC Galliformes Specialist Group) are Galliformes
experts who were consulted for the selection of covariates for niche modelling.
Table A.1. Details on the number of Galliformes locality records in each WWF ecoregion of the study site. Key: EHasm = Eastern Himalayan alpine shrub and meadows, EHb = Eastern Himalayan broadleaf forest, EHsc = Eastern Himalayan sub-alpine conifer forest, Hsb = Himalayan sub-tropical broadleaf forest, Hsp = Himalayan sub-tropical pine forest, NEHsc = North-Eastern Himalayan sub-alpine conifer forest, NTt = Northern Triangle temperate forest, NWHasm = North-western Himalayan alpine shrub and meadows, WHasm = Western Himalayan alpine shrub and meadows, WHb = Western Himalayan broadleaf forest and WHsc = Western Himalayan sub-alpine conifer forest.
WWF ecoregion
Species EHasm EHb EHsc Hsb Hsp NEHscNTt NWHasm WHasm WHb WHsc
Blood pheasant 10 9 27 4 0 3 0 0 0 1 0
Blyth's tragopan 4 17 4 0 0 2 1 0 0 0 0Buff-throated partridge 1 1 0 0 0 13 0 0 0 0 0
Cheer pheasant 1 0 2 2 122 0 0 33 36 146 113Chestnut-breasted hill partridge 3 10 8 0 1 1 0 0 0 0 0
Chukar 2 0 3 0 24 0 0 9 4 7 6
Common peafowl 0 0 0 10 18 0 0 0 0 5 1
Common quail 0 0 0 3 0 0 0 0 1 2 0Common hill partridge 3 24 22 1 11 1 0 1 0 4 1
Himalayan monal 19 16 24 3 45 5 0 67 17 58 44
Himalayan quail 0 0 0 0 4 0 0 0 0 0 0Himalayan snowcock 1 0 2 0 8 0 0 14 7 10 11
Kalij pheasant 5 48 15 5 66 2 0 11 5 35 9
Koklass pheasant 2 0 27 0 71 3 0 54 7 68 29
Red junglefowl 1 32 1 9 44 1 1 6 2 8 10Rufous-throated hill partridge 0 33 8 1 11 0 0 0 0 0 0
Satyr tragopan 12 14 80 3 13 1 0 0 2 4 1
Sclater's monal 21 9 0 0 0 5 0 0 0 0 0
Snow partridge 4 0 2 0 0 0 0 5 5 3 0Temminck's tragopan 2 7 2 0 0 3 0 0 0 0 0
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WWF ecoregion
Species EHasm EHb EHsc Hsb Hsp NEHscNTt NWHasm WHasm WHb WHsc
Tibetan eared pheasant 0 0 0 0 0 8 0 0 0 0 0
Tibetan tragopan 1 0 0 0 0 5 0 0 1 0 0
Tibetan snowcock 9 0 0 0 0 4 0 1 6 0 0
Western tragopan 0 0 0 0 21 0 0 99 9 100 110
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Table A.2. Details of model AICc values based on choice of regularisation multiplier (beta). The regularisation parameter modifies the smoothness of the response curves that are generated for each species distribution model, which can affect both model complexity and the ability of the model to project to different time periods and region. Asterisks (*) indicate the final model used.
Common name Latin nameNumber locality records
Number model parameters
Beta AICc
Blood pheasant Ithaginis cruentus
56 7 1 1,356
56 7 0.5* 1,353
56 6 2 1,361
56 5 5 1,384
Blyth’s tragopan Tragopan blythii
36 4 1 901
36 4 0.5* 899
36 4 2 906
36 1 5 905
Buff-throated partridge Tetraophasis szechenyii
15 4 1 359
15 4 0.5 356
15 2 2* 356
15 1 5 361
Cheer pheasant Catreus wallichi
463 28 1 11,097
463 26 0.5* 11,075
463 25 2 11,129
463 22 5 11,270
Chestnut-breasted hill partridge
Arborophila mandelli
27 4 1* 656
27 5 0.5 656
27 4 2 664
27 2 5 683
Chukar Alectoris chukar
77 6 1 2,080
77 8 0.5* 2,077
77 3 2 2,097
77 3 5 2,098
Common peafowl Pavo cristatus
65 9 1 1,667
65 10 0.5* 1,666
65 9 2 1,677
65 5 5 1,685
Common quail Coturnix coturnix
12 2 1 342
12 2 0.5* 339
12 2 2 351
12 0 5 346
Common hill partridge Arborophila torqueola
68 5 1 1,710
68 5 0.5* 1,708
68 4 2 1,711
68 3 5 1,719
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Common name Latin nameNumber locality records
Number model parameters
Beta AICc
Himlalayan monal Lophophorus impejanus
303 36 1* 7,789
314 38 0.5 8,257
314 36 2 8,250
314 25 5 8,278
Himalayan snowcock Tetraogallus himalayensis
62 6 1 1,574
62 7 0.5* 1,569
62 4 2 1,582
62 4 5 1,596
Kalij pheasant Lophura leucomenalos
202 28 1* 5,186
202 28 0.5 5,186
202 27 2 5,198
202 17 5 5,219
Koklass pheasant Pucrasia macrolopha
275 29 1* 7,132
275 29 0.5 7,132
275 29 2 7,142
275 20 5 7,187
Red junglefowl Gallus gallus
116 22 1 2,968
116 28 0.5* 2,963
116 10 2 2,985
116 7 5 2,999
Rufous-throated hill partridge
Arborophila rufogularis
53 14 1 1,183
53 16 0.5* 1,180
53 11 2 1,191
53 8 5 1,217
Satyr tragopan Tragopan satyra
132 13 1 3,147
132 17 0.5* 3,134
132 13 2 3,138
132 10 5 3,173
Sclater’s monal Lophophorus sclateri
37 6 1 933
37 6 0.5* 930
37 7 2 941
37 5 5 957
Snow partridge Lerwa lerwa
19 9 1 499
19 13 0.5 548
19 7 2 491
19 4 5* 491
Tibetan eared pheasant Crossoptilon harmani
52 6 1 1,314
52 8 0.5* 1,306
52 6 2 1,314
52 6 5 1,331
5
Common name Latin nameNumber locality records
Number model parameters
Beta AICc
Tibetan partridge Perdix hodgsoniae
33 4 1* 894
33 5 0.5 899
33 4 2 898
33 4 5 916
Tibetan snowcock Tetraogallus tibetanus
98 8 1 2,677
98 9 0.5* 2,669
98 8 2 2,671
98 7 5 2,678
Temminck’s tragopan Tragopan temminckii
16 5 1 413
16 5 0.5* 406
16 2 2 414
16 1 5 417
Western tragopan Tragopan melanocephalus
350 22 1* 8,384
350 22 0.5 8,384
350 15 2 8,385
350 12 5 8,468
Table A.3. Details of Maxent models including Area Under Curve (AUC) and standard deviation of SDM results. In unbiased data, a high AUC indicates that sites with high predicted suitability values tend to be areas of known presence and locations with lower model prediction values tend to be areas where the species is not known to be present (absent or a random point). An AUC score of 0.5 means that the model is as good as a random guess. The smaller the standard deviation, the more precise the model’s predictions are. Site delimitation method codes: SS = study site only, ON = occupied or neighbouring ecoregions and ER = Himalayan ecoregions only. Feature function codes: l = linear, q = quadratic and p = product.
Species
Site delimitation method
Feature function Beta AUC
Standard deviation
Blood pheasant SS lq 0.5 0.86 0.06
Blyth's tragopan ON lq 0.5 0.82 0.11
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Species
Site delimitation method
Feature function Beta AUC
Standard deviation
Buff-throated partridge ER lq 2 0.87 0.21
Cheer pheasant ER lqp 0.5 0.90 0.03Chestnut- breasted hill partridge ON lq 1 0.86 0.08
Chukar ON lq 0.5 0.90 0.04
Common peafowl ON lq 0.5 0.85 0.07
Common quail ON l 2 0.47 0.13
Common hill partridge SS lq 0.5 0.85 0.08
Himalayan monal SS lqp 1 0.80 0.04
Himalayan snowcock ON lq 0.5 0.93 0.04
Kalij phesant SS lqp 1 0.80 0.04
Koklass pheasant ON lqp 1 0.92 0.02
Red junglefowl SS lqp 0.5 0.82 0.05Rufous- throated hill partridge ER lq 0.5 0.94 0.05
Satyr tragopan ER lq 0.5 0.88 0.05
Sclater's monal ON lq 0.5 0.81 0.07
Snow partridge ER lq 5 0.83 0.12
Temminck's tragopan ON lq 0.5 0.78 0.24
Tibetan eared pheasant ON lq 0.5 0.93 0.06
Tibetan partridge ON lq 1 0.80 0.12
Tibetan snowcock ON lq 0.5 0.80 0.12
Western tragopan ON lqp 1 0.95 0.01
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Table A.4. Details of predictor variables used in final Maxent models. Key: MAT = Maximum Annual Temperature, MAVT = Maximum Annual Variability in Temperature, MAP = Maximum Annual Precipitation, MAVP = Maximum Annual Variability in Precipitation.
Predictor
Blood pheasant Oct NDVI, Dec NDVI, MAT, MAVT, MAP, MAVP, study site
Blyth’s tragopan Jan NDVI, Feb NDVI, Mar NDVI, Oct NDVI, Dec NDVI, occupied neighbour
Buff-throated partridge Jul NDVI, ecoregions
Cheer pheasant Jan NDVI, Sep NDVI, MAVT, MAVP, elevation, slope, ecoregions
Chestnut-breasted hill partridge Feb NDVI, May NDVI, Oct NDVI, Dec NDVI, MAT, occupied neighbour
Chukar Apr NDVI, MAVT, MAVP, elevation, occupied neighbour
Common peafowl Feb NDVI, March NDVI, Apr NDVI, May NDVI, Jul NDVI, MAVP, slope, occupied neighbour
Common quail Jun NDVI, MAT, occupied neighbour
Common hill partridge Aug NDVI, Oct NDVI, Nov NDVI, Dec NDVI, MAT, MAVT, study site
Himalayan monal Jan NDVI, Feb NDVI, Jun NDVI, Jul NDVI, Aug NDVI, MAT, MAVT, MAVP, elevation, slope, study site
Himalayan snowcock Jun NDVI, MAVP, elevation, slope, occupied neighbour
Kalij pheasant Mar NDVI, Apr NDVI, Jun NDVI, Sep NDVI, Nov NDVI, MAT, MAVT, MAP, MAVP, study site
Koklass pheasant May NDVI, Jun NDVI, Jul NDVI, Aug NDVI, MAT, MAVT, MAVP, elevation, slope, occupied neighbour
Red junglefowl Feb NDVI, Mar NDVI, May NDVI, Jul NDVI, Aug NDVI, Sep NDVI, Oct NDVI, Nov NDVI, MAT, MAP, MAVP, elev, study site
Rufous-throated hill partridge Feb NDVI, Mar NDVI, May NDVI, Jul NDVI, Oct NDVI, Dec NDVI, MAT, MAP, ecoregions
Satyr tragopan Apr NDVI, Jun NDVI, Oct NDVI, MAT, MAVT, elevation, ecoregions
Sclater’s monal Jul NDVI, Dec NDVI, MAT, MAVP, elevation, slope, occupied neighbour
Snow partridge Feb NDVI, Mar NDVI, Apr NDVI, May NDVI, Dec NDVI, MAT, MAVP, elevation, ecoregions
Tibetan eared pheasant Jul NDVI, MAT, MAVT, MAP, MAVP, slope, occupied neighbour
Tibetan partridge Jul NDVI, MAT, MAP, occupied neighbour
Tibetan snowcock Jul NDVI, Oct NDVI, MAT, MAVT, MAVP, occupied neighbour
Temminck’s tragopan Nov NDVI, Dec NDVI, MAT, MAVP, elevation, slope, occupied neighbour
Western tragopan Jun NDVI, Jul NDVI, MAT, MAVT, MAP, slope, occupied neighbour
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Maxent result maps
Figure A.1.a. SDMs for 23/24 species with Himalayan quail shown as point data only (N = 24 maps in total). Polygons = BirdLife shapefile, green dots = point localities and warmer colours = most suitable habitat and cool colours = least suitable habitat. Key: A = Blood pheasant, B = Blyth’s tragopan and C = Buff-throated partridge
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Figure A.1.b. SDMs for 23/24 species with Himalayan quail shown as point data only (N = 24 maps in total). Polygons = BirdLife shapefile, green dots = point localities and warmer colours = most suitable habitat and cool colours = least suitable habitat. Key: D = Cheer pheasant, E = Chestnut-breasted hill partridge, F = Chukar and I = common hill partridge.
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Figure A.1.c. SDMs for 23/24 species with Himalayan quail shown as point data only (N = 24 maps in total). Polygons = BirdLife shapefile, green dots = point localities and warmer colours = most suitable habitat and cool colours = least suitable habitat. Key: G = Common peafowl and H = Common quail.
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Figure A.1.d. SDMs for 23/24 species with Himalayan quail shown as point data only (N = 24 maps in total). Polygons = BirdLife shapefile, green dots = point localities and warmer colours = most suitable habitat and cool colours = least suitable habitat. Key: J = Himalayan snowcock, K = Himalayan monal and L = Himalayan quail.
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Figure A.1.e. SDMs for 23/24 species with Himalayan quail shown as point data only (N = 24 maps in total). Polygons = BirdLife shapefile, green dots = point localities and warmer colours = most suitable habitat and cool colours = least suitable habitat. Key: M = Kalij pheasant, N = Koklass pheasant and O = Red junglefowl.
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Figure A.1.f. SDMs for 23/24 species with Himalayan quail shown as point data only (N = 24 maps in total). Polygons = BirdLife shapefile, green dots = point localities and warmer colours = most suitable habitat and cool colours = least suitable habitat. Key: P = Rufous-throated hill partridge, Q = Satyr tragopan and R = Sclater’s monal.
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Figure A.1.g. SDMs for 23/24 species with Himalayan quail shown as point data only (N = 24 maps in total). Polygons = BirdLife shapefile, green dots = point localities and warmer colours = most suitable habitat and cool colours = least suitable habitat. Key: S = Snow partridge, T = Tibetan partridge and U = Tibetan eared pheasant.
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Figure 1. SDMs for 23/24 species with Himalayan quail shown as point data only (N = 24 maps in total). Polygons = BirdLife shapefile, green dots = point localities and warmer colours = most suitable habitat and cool colours = least suitable habitat. Key: V = Tibetan snowcock, W = Temminck’s tragopan and X = Western tragopan.
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Appendix B: Calculation of raw Zonation weights and Zonation results
The following section outlines details of species-specific conservation values. We describe how these
values were obtained and re-scaled below.
Confidence in Maxent results. Smoothed response curves (Figure A.2) and maps that
broadly agreed with expert opinion with AUCs greater than 0.5 (better than random) were
scored between 1 (most confident) and 3 (least confident) to reflect our confidence in the
Maxent niche modelling procedure. Examples of poor maps include the Common quail (Fig
A.2. A) and good maps the Western tragopan (Fig A.2. B).
Figure A.2. Examples of ‘good’ (A) and ‘bad’ (B) Maxent receiver operator characteristics. A shows a smooth mean AUC with small standard deviations well above the random prediction line. B shows a jagged mean AUC with large standard deviations below the random prediction line.
Red List. Red List categories were taken from the IUCN Red List (IUCN, 2012) and
converted to numerical scores (Least Concern = 1, Near Threatened = 2, Vulnerable = 3,
Endangered = 4, Critically Endangered = 5). Thus, higher scores corresponded to a higher
global extinction risk.
Phylogenetic distinctiveness (PD). We generated PD scores on a taxonomically complete,
time-calibrated, DNA sequence based Bayesian phylogenetic hypothesis that includes all 291
extant Galliformes taxa (Stein et al 2015). Sixty-two of the 291 in-group taxa were data
deficient (no DNA sequence data), and taxonomic constraints (among species within a genus
or among genera with a family) were used to include the data-deficient taxa. Stein et al (2015)
generated a large posterior distribution of trees to account for the uncertain affinities of data
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deficient taxa. We calculated PD scores (fair proportions; Redding et al., 2008) for all 291 in-
group taxa on 10000 fully resolved tree (Martyn, Kuhn, Mooers, Moulton, & Spillner, 2012)
sampled from the posterior distribution. Fair proportions partitions shared branches according
to the number of descendent taxa, such that a shared branch contributes branch length/number
of descendant taxa to the PD score. For simplicity, the analyses presented here use mean PD
score and included all 24 focal taxa. We conducted additional analyses that excluded two
data-deficient taxa, Chestnut-breasted hill partridge-breasted partridge (Arborophila mandelli)
and Snow partridge (Lerwa lerwa), and the results were qualitatively similar (data not
shown).
Relative range change. Measures of range change were calculated after Telfer et al. (2002).
The Galliformes point locality data were aggregated into a Behrmann equal area projection
using a grid with cells measuring 48.24 x 48.24 km, approximating to half a decimal degree
resolution. Only point locality data from Himalayan Galliformes species were used to obtain
measures of sampling effort in the Himalayan network of cells. Data were split into pre-
(<1980) and post-1980 (≥1980) or early vs. later time bins to ensure congruence with other
similar analyses conducted using this database (Mace et al., 2010) and to demarcate the rapid
escalation of anthropogenic change starting around the year 1980 (Millennium Ecosystem
Assessment, 2005). To control for change in geographical coverage with time, only cells that
were surveyed for both time periods being compared were included. The number of grid cells
containing one or more records was counted for each species in each time period. Only
species with a minimum of five cells in the early period were included in the analysis to avoid
curvilinearity given that the rarest species have a far greater capacity to expand than decline
(two species were excluded on these grounds; see Table A.5; Telfer et al., 2002). These grid
cells were then expressed as proportions of the total survey area and logit-transformed. A
linear regression model was fitted to the logit-transformed proportions from the earlier and
later periods and weighted to account for heteroscedasticity. Each species’ standardised
residual was then taken to represent an index of its change in geographic range size, relative
to the trend in the whole group. Full details of the method are in Telfer et al. (2002). The
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standardised residuals represent relative change only and without calibration of the index it is
difficult to know if the direction of the residuals represents absolute positive or negative
changes. The standardised residuals represent range contractions and expansions relative to
the trend of the group analysed and not absolute changes.
Endemism to the Himalaya. Measures of endemism were calculated from the proportion of
the Greater Himalaya that intersected the focal species’ global range as measured by BirdLife
range maps (BirdLife International and NatureServe, 2011). The endemism measure reflected
the important of the Greater Himalaya as an areal proportion of each species’ total global
range. A continuous scale was used as definitions of endemism area inherently scale
dependent (Laffan & Crisp, 2003) with 1 = endemic and 0 = not endemic.
Re-scaling the raw weight scores. Scores were scaled to be congruent to the Red List
categories (between 1-5) using the general formula x '=( ( x−a ) ( d−c )b−a )+c where mapping
from (a,b) to (c,d). Note: the adjusted weights for the relative range scores were reversed in
polarity as species that have negative raw scores are higher priorities.
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Table A.5 Summary of the species used in the analysis with details of species-specific weightings. Note: the adjusted weights for the relative range change scores have been reversed in polarity as species that have negative raw scores are higher priorities. Confidence in Maxent results were assessed by G. Buchanan and J. Dunn.
Raw weights (adjusted weights)
Common name Latin name
Confidence in Maxent results
Red List
Endemism
Relative Range Change
Phylogenetic distinctiveness
Blood pheasant
Ithaginis cruentus 2 1 0.22
(1.85)-0.80
(3.17) 35.63 (5.00)
Blyth's tragopan
Tragopan blythii 2 3 0.23
(1.89)1.20
(1.20) 10.43 (1.67)
Buff-throated partridge
Tetraophasis szechenyii 3 1 0.21
(1.81) N/A 14.15 (2.16)
Cheer pheasant
Catreus wallechi 1 3 0.74
(3.95)0.67
(1.72) 11.74 (1.84)
Chestnut-breasted hill partridge
Arborophila mandelli 2 1 1.00
(5.00)0.67
(1.72) 8.32 (1.39)
Chukar Alectoris chukar 1 1 0.03
(1.08)-0.59
(2.97) 8.18 (1.37)
Common peafowl Pavo cristatus 1 1 0.12
(1.44)0.82
(1.57) 15.07 (2.28)
Common quail
Coturnix coturnix 3 1 0.04
(1.12)0.68
(1.71) 9.98 (1.61)
Common hill partridge
Arborophila torqueola 1 1 0.01
(1.00)-0.09
(2.47) 8.11 (1.36)
Himalayan monal
Lophophorus impejanus 2 1 0.58
(3.30)1.40
(1.00) 13.29 (2.04)
Himalayan quail
Ophrysia superciliosa N/A 5 0.78
(4.11) N/A N/A
Himalayan snowcock
Tetraogallus himalayensis 1 1 1.00
(5.00)0.34
(2.05) 10.28 (1.65)
Kalij pheasant
Lophura leucomenalos 2 1 0.33
(2.29)0.62
(1.77) 6.39 (1.13)
Koklass pheasant
Pucrasia macrolopha 1 1 0.10
(1.36)1.19
(1.21) 24.83 (3.57)
Red junglefowl Gallus gallus 2 1 0.05
(1.16)0.71
(1.68) 9.58 (1.55)
Rufous- throated hill partridge
Arborophila rufogularis 1.5 1 0.26
(2.01)-0.42
(2.80) 8.28 (1.38)
Satyr tragopan
Tragopan satyra 1 2 1.00
(5.00)0.09
(2.29) 11.45 (1.80)
Sclater's monal
Lophophorus sclateri 2 3 0.55
(3.18)-0.07
(2.45) 13.29 (2.04)
Snow partridge Lerwa lerwa 2 1 0.4 (2.58) -0.21
(2.59) 23.39 (3.38)
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Raw weights (adjusted weights)
Common name Latin name
Confidence in Maxent results
Red List
Endemism
Relative Range Change
Phylogenetic distinctiveness
Temminck's tragopan
Tragopan temmincki 3 1 0.06
(1.20)0.01
(2.37) 10.97 (1.74)
Tibetan eared pheasant
Crossoptilon harmani 1 2 0.62
(3.46)-1.47
(3.83) 5.39 (1.00)
Tibetan partridge
Perdix hodgsoniae 2 1 0.17
(1.65)-2.65
(5.00) 13.37 (2.06)
Tibetan snowcock
Tetraogallus tibetanus 2 1 0.17
(1.65)0.05
(2.33) 12.07 (1.88)
Western tragopan
Tragopan melanocephalus
1 3 0.78 (4.11)
1.20 (4.11)
10.48 (1.67)
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Figure A.3 The top two panels show the average Zonation response curves across all species for both A) unconstrained and B) constrained solutions. The bottom two panels show the minimum response curves for the worst off species for both C) unconstrained and D) constrained solutions. Response curve colours correspond to the following Zonation solutions: blue = distribution discounting, red = endemism, green = Red List, purple = phylogenetic distinctiveness and orange = range change. The vertical lines represent 1-proportion of the Himalayan landscape taken up by PAs (i.e. 81.9% of the landscape lost). Comparisons between the proportion of species distributions where the response curves intersect the vertical line (A vs. B and C vs. D) indicate the efficacy of the current PA network in capturing Galliformes distributions. i.e. if PAs were perfectly placed, the proportions of distributions remaining would be equal.
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Figure A.4 Zonation result maps (A = basic, B = distribution discounting, C = weighted by Red List, D = weighted by endemism, E = weighted by range change, F = weighted by phylogenetic distinctiveness) for species of Galliformes occurring in the Himalayan region. The warmest colours indicate the most important conservation areas and the coolest colours indicate the least important conservation areas: black = 0-20% (least important areas), dark blue = 20-50%, blue = 50-75%, yellow = 75-90%, pink = 90-95%, dark red = 95-98% and red = 98-100% (most important areas). The top fraction (18.1%) of each solution corresponds to an area of approximately 118,513 km2 out of a total of 654,772 km2, which is equal to the current area taken up by PAs. Note: weighted solutions presented here were weighted after accounting for data uncertainty using distribution discounting.
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Appendix C: Further information on the overlap between important areas as identified by different
measures of conservation value
Figure A.5a. Comparison maps for Kappa statistics. Black indicates areas with equal value rasters (0+ 0 or 1+1) whereas red indicates areas with unequal value rasters (0+1). Total no. of cells in area = 687,532. Overlaps are shown for: A = basic x distribution discounting, B = distribution discounting x endemism, C = distribution discounting x Red List, D = distribution discounting x phylogenetic diversity, E = distribution discounting x range changes, F = endemism x range changes
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Figure A.5b. Comparison maps for Kappa statistics. Black indicates areas with equal value rasters (0+0 or 1+1) whereas red indicates areas with unequal value rasters (0 and 1). Total no. of cells in area = 687,532. Overlaps are shown for: G = endemism x phylogenetic diversity, H = endemism x range changes, I = Red List x phylogenetic diversity, J = Red List x range changes, K = phylogenetic diversity x range changes.
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Table A.6. Table showing details of the protected areas used in the analysis. N = 119. Country codes: PAK = Pakistan, NPL = Nepal, MMR = Myanmar, BTN = Bhutan and IND = India.
Country Name Designated
IUCN category
Status year Area km2
PAK HalejiWildlife Sanctuary IV 1977 2.81
PAK ManshiWildlife Sanctuary IV 1977 22.72
PAK SalkhalaWildlife Sanctuary IV 1982 7.73
PAK KargahWildlife Sanctuary IV 1975 0.66
PAK BajwatWildlife Sanctuary IV 1964 1.12
PAK Chitral Gol National Park II 1984 149.45
NPL Langtang National Park II 1976 1321.74
NPL Sagarmatha National Park II 1976 389.94
NPL Royal Chitwan National Park II 1973 1179.70
NPL Rara National Park II 1976 113.96
NPL Royal Bardia National Park II 1976 909.15
NPLRoyal Suklaphanta
Wildlife Reserve IV 1976 369.45
NPL Koshi TappuWildlife Reserve IV 1976 150.88
NPL Shey-Phoksundo National Park II 1984 3636.40
NPL Khaptad National Park II 1984 233.51
NPL ParsaWildlife Reserve IV 1984 476.51
NPL Shivapuri National Park II 1985 91.08
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Country Name Designated
IUCN category
Status year Area km2
NPL Makalu-Barun National Park II 1991 875.06
MMR Khakaborazi National Park II 1996 3732.31
MMR Hukaung ValleyWildlife Sanctuary III 2001 224.35
MMR HponkanraziWildlife Sanctuary III 2001 2132.69
MMR BumhpabumWildlife Sanctuary III 2002 200.09
BTN Jigme Dorji National Park II 1974 4079.90
BTNJigme Singye Wangchuck National Park II 1995 1730.22
BTN KhalingWildlife Sanctuary IV 1974 294.60
BTN Royal Manas National Park II 1966 959.85
BTN Thrumshingla National Park II 1998 784.54
BTN ToorsaStrict Nature Reserve Ia 1993 650.69
BTN SaktengWildlife Sanctuary IV 1993 754.46
BTN PhibsooWildlife Sanctuary IV 1993 236.60
BTN BumdelingWildlife Sanctuary IV 1995 1563.29
IND Khangchendzonga National Park II 1977 735.45
IND Corbett National Park II 1936 318.63
IND Dudhwa National Park II 1977 633.94
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Country Name Designated
IUCN category
Status year Area km2
IND Kedarnath Sanctuary IV 1972 451.44
INDGovind Pashu Vihar Sanctuary IV 1955 597.19
IND Katarniyaghat Sanctuary IV 1977 342.20
IND Nanda Devi National Park Ib 1982 141.64
IND Manas Sanctuary IV 1928 0.58
IND Namdapha National Park II 1983 1800.73
IND Itanagar Sanctuary IV 1978 185.31
IND Pakhui Sanctuary IV 1977 855.12
IND Sonai-Rupai Sanctuary IV 1998 0.34
IND Valmiki Sanctuary IV 1978 161.51
IND Dachigam National Park II 1981 332.33
IND Overa Sanctuary IV 1981 31.92
IND Kistwar National Park II 1981 738.01
IND Hokarsar Lake Sanctuary IV 1992 13.72
IND Sechu Tuan Nala Sanctuary IV 1962 284.46
IND Gamgul Siahbehi Sanctuary IV 1962 89.98
IND Tundah Sanctuary IV 1962 106.26
IND Kugti Sanctuary IV 1962 509.91
IND Kalatop-Khajjair Sanctuary IV 1958 60.83
IND Nargu Sanctuary IV 1962 285.54
IND Shikari Devi Sanctuary IV 1962 76.97
28
Country Name Designated
IUCN category
Status year Area km2
IND Bandli Sanctuary IV 1962 12.84
IND Gobindsagar Sanctuary IV 1962 178.53
IND Naina Devi Sanctuary IV 1982 38.84
IND Majathal Sanctuary IV 1954 23.85
IND Daranghati Sanctuary IV 1962 33.04
IND Shilli Sanctuary IV 1963 2.01
IND Shimla Catchment Sanctuary IV 1958 36.29
IND Talra Sanctuary IV 1962 35.94
IND Darlaghat Sanctuary IV 1962 115.24
IND Raksham Chitkul Sanctuary IV 1962 29.53
IND Lippa Asrang Sanctuary IV 1962 63.20
IND Manali Sanctuary IV 1954 98.50
IND Khokhan Sanctuary IV 1954 17.39
IND Kanawar Sanctuary IV 1954 80.66
IND Chail Sanctuary IV 1976 126.40
IND Tirthan Sanctuary IV 1992 61.61
IND Garumara Sanctuary IV 1984 8.46
IND Chapramari Sanctuary IV 1976 9.56
IND Mahananda Sanctuary IV 1976 160.32
IND Mehao Sanctuary IV 1980 317.56
IND Great Himalayan National Park II 1962 742.55
29
Country Name Designated
IUCN category
Status year Area km2
IND Valley Of Flowers National Park II 1982 31.66
IND Neora Valley National Park II 1992 92.36
IND Buxa Sanctuary IV 1986 95.47
IND Rupi Bhaba Sanctuary IV 1982 855.28
IND Baltal-Thajwas Sanctuary IV 1987 148.94
IND Overa-Aru Sanctuary IV 1981 454.90
IND Jasrota Sanctuary IV 1987 4.22
IND Hirapora Sanctuary IV 1987 119.74
IND Limber Sanctuary IV 1987 11.21
IND Lachipora Sanctuary IV 1987 79.57
IND Fambong Lho Sanctuary IV 1984 68.13
IND City Forest National Park II 1992 8.98
IND Gulmarg Sanctuary IV 1987 125.98
IND Askot Musk Deer Sanctuary IV 1986 223.31
IND Mouling National Park II 1986 435.20
IND Sonanadi Sanctuary IV 1987 60.78
IND Sohagibarwa Sanctuary IV 1987 157.39
IND Pong Dam Lake Sanctuary IV 1982 247.71
IND Pin Valley National Park II 1958 849.23
IND Kais Sanctuary IV 1954 12.13
30
Country Name Designated
IUCN category
Status year Area km2
INDKyongnosla Alpine Sanctuary IV 1977 19.47
IND Shingba Sanctuary IV 1984 39.57
IND Nameri Sanctuary IV 1985 21.32
IND Singalila National Park II 1992 78.09
IND Maenam Sanctuary IV 1987 42.77
IND Binsar Sanctuary IV 1988 45.43
IND Churdhar Sanctuary IV 1985 30.18
IND Tale Valley Sanctuary IV 1995 335.71
IND Dibang Sanctuary IV 1991 766.50
IND Manas National Park II 1990 3.77
IND Valmiki National Park II 1989 334.35
IND Govind National Park II 1990 493.83
IND Sohelwa Sanctuary IV 1988 240.37
IND Gangotri National Park II 1989 214.81
IND Eagle Nest Sanctuary IV 1989 215.35
IND Kamlang Sanctuary IV 1989 780.00
IND Kane Sanctuary IV 1991 54.63
IND Sessa Orchid Sanctuary IV 1989 99.26
INDBarsey Rhododendron Sanctuary IV 1998 137.64
IND Gorumara National Park II 1992 79.13
IND Kibber Sanctuary IV 1992 1279.40
31
Country Name Designated
IUCN category
Status year Area km2
IND Sainj Sanctuary IV 1994 89.73
IND Sangla Sanctuary IV 1989 648.04
32
Table A.7. Table showing the number of cells for each unique combination of Zonation solutions (total number of cells = 755,532 across a total area of 654,772 km2). Cell size is 0.009 decimal degrees corresponding to approximately 1 km. Thus, 1 cell ≈ 1 km2. Zonation solution codes: DD = distribution discounting, EN = endemism, PD = phylogenetic distinctiveness, RL = Red List and RRC = relative range change.
DD EN PD RL RRC No. cells
0 0 0 0 0 466,986
0 0 1 0 0 32,584
1 1 0 0 0 2,120
0 1 0 0 0 15,146
0 0 0 0 1 29,519
1 0 1 0 0 16,352
1 1 1 0 0 2,144
0 1 0 0 1 4,422
1 1 0 0 1 5,795
1 0 0 0 1 5,634
0 0 1 0 1 5,230
1 0 1 0 1 14,676
1 1 1 0 1 6,882
0 1 1 0 1 2,274
0 0 0 1 1 1,262
0 1 1 1 1 1,765
1 1 1 1 1 34,257
0 0 1 1 1 377
0 1 0 1 1 4,766
1 1 0 1 1 13,635
1 1 0 1 0 13,056
0 1 1 0 0 5,115
1 0 0 0 0 3,901
1 1 1 1 0 6,538
0 0 0 1 0 29,391
0 1 0 1 0 16,495
0 1 1 1 0 2,342
1 0 1 1 1 3,348
0 0 1 1 0 1,106
1 0 1 1 0 1,762
1 0 0 1 1 2,910
1 0 0 1 0 3,742
33
Figure A.6 Map showing the existing protected area network in red and potential areas for expansion of the network in blue. Blue areas indicate overlap between five different Zonation solutions and if these areas were formally protected, would conserve multiple facets of conservation value for Galliformes. To aid conservation practitioners and legislators, this map is also provided in .kml format for use with Google Earth in the online version of the Appendix and locality place names and latitude/longitude coordinates are provided in Table A.8.
34
Table A.8 Description and latitude/longitude coordinates of potential target localities for PA expansion.
Locality description Latitude LongitudeNear Tiba Kangri, Nyingchi, China 29°49'60.00''N 94°51'60.00''ENear Daga, Bhutan 27°5'49.021''N 89°52'26.04''ENear North Royal Manas NP, Bhutan 27°1'49.88''N 90°42'54.99''ENear Rohru, Himachal Pradesh, India 31°12'7.20''N 77°45'6.84''ESouth of Dharamsala, Himchal Pradesh, India 32°13'8.55''N 76°19'24.25''ESouth of Wakro, Arunachal Pradesh, India 27°46'57.27''N 96°20'51.57''ENear Gorakhani, Takasindu, Nepal 27°29'24.00''N 86°30'36.00''E
