Journal of Resources and Ecology ›› 2022, Vol. 13 ›› Issue (3): 483-500.DOI: 10.5814/j.issn.1674-764x.2022.03.013
• Animal Ecology • Previous Articles Next Articles
XIAO Changxi1,2,3(), BAI Defeng1,2, Joseph P. LAMBERT1, LI Yibin3, Lhaba CERING4, GONG Ziling2,5, Philip RIORDAN1,6, SHI Kun1,3,*(
)
Received:
2021-04-16
Accepted:
2574-07-12
Online:
2022-05-30
Published:
2022-04-18
Contact:
SHI Kun
About author:
XIAO Changxi, E-mail: lzxiaocx@gmail.com
XIAO Changxi, BAI Defeng, Joseph P. LAMBERT, LI Yibin, Lhaba CERING, GONG Ziling, Philip RIORDAN, SHI Kun. How Snow Leopards Share the Same Landscape with Tibetan Agro-pastoral Communities in the Chinese Himalayas[J]. Journal of Resources and Ecology, 2022, 13(3): 483-500.
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URL: http://www.jorae.cn/EN/10.5814/j.issn.1674-764x.2022.03.013
Fig. 1 Location of study area and map of the camera-trap surveyed areas (sites) used to model snow leopard (Panthera uncia) habitat use for summer and winter in Qomolangma NNR, China. Notes: Country names are abbreviated: Afghanistan (AFG); Bhutan (BHU); China (CHN); India (IND); Kazakhstan (KAZ); Kyrgyzstan (KYG); Mongolia (MON); Myanmar (MYN); Nepal (NEP); Pakistan (PAK); Russia (RUS); Tajikistan (TAJ); Uzbekistan (UZB). Projection: UTM45 N; Datum: WGS 1984.
Category | Covariate | Detail | Abbreviation |
---|---|---|---|
Environmental covariates | Blue sheep capture rates | Camera-trap capture | BS |
Sites of slope gradient | 30 m, 300 m, 1000 m, 2000 m, 4000 m | SLP30-4000 | |
Sites of terrain ruggedness index | 30 m, 300 m, 1000 m, 2000 m, 4000 m | TRI30-4000 | |
Sites of elevation | 30 m, 300 m, 1000 m, 2000 m, 4000 m | ELE30-4000 | |
Anthropogenic covariates | Grazing activity rates | Camera-trap capture | GRAZE |
Disturbance from human settlements | Kernal density | KD_SETT | |
Distance of the nearest | Dist._SETT | ||
Disturbance from traffic roads | Kernal density | KD_ROAD | |
Distance of the nearest | Dist._ROAD |
Table 1 Candidates of snow leopard (Panthera uncia) habitat use (ψ) covariates
Category | Covariate | Detail | Abbreviation |
---|---|---|---|
Environmental covariates | Blue sheep capture rates | Camera-trap capture | BS |
Sites of slope gradient | 30 m, 300 m, 1000 m, 2000 m, 4000 m | SLP30-4000 | |
Sites of terrain ruggedness index | 30 m, 300 m, 1000 m, 2000 m, 4000 m | TRI30-4000 | |
Sites of elevation | 30 m, 300 m, 1000 m, 2000 m, 4000 m | ELE30-4000 | |
Anthropogenic covariates | Grazing activity rates | Camera-trap capture | GRAZE |
Disturbance from human settlements | Kernal density | KD_SETT | |
Distance of the nearest | Dist._SETT | ||
Disturbance from traffic roads | Kernal density | KD_ROAD | |
Distance of the nearest | Dist._ROAD |
Model name (Abbreviation) | Covariates (Abbreviation) | Hypothesis | Expected influence on ψ | Supporting literature | |
---|---|---|---|---|---|
1 | NULL | N/A | Snow leopard habitat use is not affected by environmental variables | N/A | N/A |
2 | PREY | Blue sheep capture rates (BS) | Snow leopards use habitat based on access to prey | Positive | Barber-Meyer et al., |
3 | TOPOGRAPHY (TOP.) | Slope (SLP) | Snow leopards use high mountain areas with rugged and steep slope terrain | Positive | Sunarto et al., |
Terrain ruggedness index (TRI) | Positive | ||||
Elevation (ELE) | Positive | ||||
4 | HABITAT | Blue sheep capture rates (BS) | Snow leopards use high, steep slope, and rugged habitat where prey is abundant | Positive | Sunarto et al., |
All potential TOP. variables | Positive | ||||
5 | ANTHROPOGENIC INFLUENCE (A.I.) | Grazing activity index (GRAZE) | Snow leopards avoid areas with high levels of human disturbance | Negative | McCarthy and Chapron, |
Disturbance from human settlements (SETT) | Negative | ||||
Disturbance from traffic roads (ROAD) | Negative | ||||
6 | PREY+A.I. | Blue sheep capture rates (BS) | Snow leopards use habitat based on access to prey and avoiding human disturbance | Positive | McCarthy, |
All potential A.I. variables | Negative | ||||
7 | TOP.+A.I. | All potential TOP. variables | Snow leopards use rugged, high elevation habitat with little human disturbance | Positive | Sunarto et al., |
All potential A.I. variables | Negative | ||||
8 | GLOBAL | Blue sheep capture rates (BS) | Snow leopards use high elevation, rugged habitat where prey is abundant and with low human disturbance | Positive | McCarthy and Chapron, |
All potential TOP. variables | Positive | ||||
All potential A.I. variables | Negative |
Table 2 Description of priori candidate models describing the effects of potential environmental variables on the probability of habitat use by snow leopard (Panthera uncia)
Model name (Abbreviation) | Covariates (Abbreviation) | Hypothesis | Expected influence on ψ | Supporting literature | |
---|---|---|---|---|---|
1 | NULL | N/A | Snow leopard habitat use is not affected by environmental variables | N/A | N/A |
2 | PREY | Blue sheep capture rates (BS) | Snow leopards use habitat based on access to prey | Positive | Barber-Meyer et al., |
3 | TOPOGRAPHY (TOP.) | Slope (SLP) | Snow leopards use high mountain areas with rugged and steep slope terrain | Positive | Sunarto et al., |
Terrain ruggedness index (TRI) | Positive | ||||
Elevation (ELE) | Positive | ||||
4 | HABITAT | Blue sheep capture rates (BS) | Snow leopards use high, steep slope, and rugged habitat where prey is abundant | Positive | Sunarto et al., |
All potential TOP. variables | Positive | ||||
5 | ANTHROPOGENIC INFLUENCE (A.I.) | Grazing activity index (GRAZE) | Snow leopards avoid areas with high levels of human disturbance | Negative | McCarthy and Chapron, |
Disturbance from human settlements (SETT) | Negative | ||||
Disturbance from traffic roads (ROAD) | Negative | ||||
6 | PREY+A.I. | Blue sheep capture rates (BS) | Snow leopards use habitat based on access to prey and avoiding human disturbance | Positive | McCarthy, |
All potential A.I. variables | Negative | ||||
7 | TOP.+A.I. | All potential TOP. variables | Snow leopards use rugged, high elevation habitat with little human disturbance | Positive | Sunarto et al., |
All potential A.I. variables | Negative | ||||
8 | GLOBAL | Blue sheep capture rates (BS) | Snow leopards use high elevation, rugged habitat where prey is abundant and with low human disturbance | Positive | McCarthy and Chapron, |
All potential TOP. variables | Positive | ||||
All potential A.I. variables | Negative |
Covariate (unit) | Abbreviation (scale) | Relationship to snow leopard occurrence | Season | Effective sample range (mean±SD) | Station ratio recorded to target | Supporting literature |
---|---|---|---|---|---|---|
Grazing activity capture rate index (%) | GRAZE (N/A) | Avoids sites with high levels of human disturbance | Winter | 0-54.55 (7.59±10.24) | 88.53 | McCarthy and Chapron, |
Summer | 0-67.78 (14.71±16.44) | 95.16 | ||||
Blue sheep capture rate index (%) | BS (N/A) | Habitat use based on access to prey | Winter | 0-36.67 (2.80±5.6) | 47.54 | McCarthy, |
Summer | 0-20.45 (2.14±3.66) | 50.77 | ||||
Slope of sites (°) | SLP (1000) | Uses certain steep habitat | Winter | 15.93-32.70 (22.15±3.17) | N/A | Sunarto et al., |
SLP (1000) | Summer | 7.49-32.70 (22.03±3.77) | ||||
Terrain ruggedness index (N/A) | TRI (4000) | Uses rugged terrain habitat | Winter | 12.11-21.36 (15.50±1.96) | N/A | Taubmann et al., |
TRI (30) | Summer | 1.40-4.09 (2.34±0.57) |
Table 3 Description of a priori candidate models describing the effects of environmental variables on the probability of habitat use by snow leopard (Panthera uncia)
Covariate (unit) | Abbreviation (scale) | Relationship to snow leopard occurrence | Season | Effective sample range (mean±SD) | Station ratio recorded to target | Supporting literature |
---|---|---|---|---|---|---|
Grazing activity capture rate index (%) | GRAZE (N/A) | Avoids sites with high levels of human disturbance | Winter | 0-54.55 (7.59±10.24) | 88.53 | McCarthy and Chapron, |
Summer | 0-67.78 (14.71±16.44) | 95.16 | ||||
Blue sheep capture rate index (%) | BS (N/A) | Habitat use based on access to prey | Winter | 0-36.67 (2.80±5.6) | 47.54 | McCarthy, |
Summer | 0-20.45 (2.14±3.66) | 50.77 | ||||
Slope of sites (°) | SLP (1000) | Uses certain steep habitat | Winter | 15.93-32.70 (22.15±3.17) | N/A | Sunarto et al., |
SLP (1000) | Summer | 7.49-32.70 (22.03±3.77) | ||||
Terrain ruggedness index (N/A) | TRI (4000) | Uses rugged terrain habitat | Winter | 12.11-21.36 (15.50±1.96) | N/A | Taubmann et al., |
TRI (30) | Summer | 1.40-4.09 (2.34±0.57) |
Fig. 2 Probability of site use by snow leopards (Panthera uncia), as measured by camera-traps in Qomolangma NNR, China. (a, c) Naïve estimates from a presence vs. absence approach of two seasons; (b, d) Mean estimated probabilities of habitat use of two seasons. Note: Each cell is 5 km×5 km=25 km2.
Models_winter | AICc | ∆AICc | AICcw | Model likelihood | K | -2 log LL |
---|---|---|---|---|---|---|
p(TEAM) | 185.15 | 0 | 0.7917 | 1 | 3 | 178.73 |
p(.) | 187.82 | 2.67 | 0.2083 | 0.2632 | 2 | 183.61 |
Models_summer | AICc | ∆AICc | AICcw | Model likelihood | K | -2 log LL |
p(TEAM) | 150.5 | 0 | 0.6857 | 1 | 3 | 144.09 |
p(.) | 152.06 | 1.56 | 0.3143 | 0.4584 | 2 | 147.86 |
Table 4 Snow leopard (Panthera uncia) detection probability models (p) in winter and summer
Models_winter | AICc | ∆AICc | AICcw | Model likelihood | K | -2 log LL |
---|---|---|---|---|---|---|
p(TEAM) | 185.15 | 0 | 0.7917 | 1 | 3 | 178.73 |
p(.) | 187.82 | 2.67 | 0.2083 | 0.2632 | 2 | 183.61 |
Models_summer | AICc | ∆AICc | AICcw | Model likelihood | K | -2 log LL |
p(TEAM) | 150.5 | 0 | 0.6857 | 1 | 3 | 144.09 |
p(.) | 152.06 | 1.56 | 0.3143 | 0.4584 | 2 | 147.86 |
No. | Models_winter | AICc | ∆AICc | AICcw | Model likelihood | K | -2 log LL |
---|---|---|---|---|---|---|---|
1 | HABITAT | 162.26 | 0 | 0.4155 | 1 | 6 | 148.7 |
2 | TOP. | 162.61 | 0.35 | 0.3488 | 0.8395 | 5 | 151.52 |
3 | GLOBAL | 164.55 | 2.29 | 0.1322 | 0.3182 | 7 | 148.44 |
4 | TOP. +A.I. | 165.04 | 2.78 | 0.1035 | 0.2491 | 6 | 151.48 |
5 | A.I. | 187.16 | 24.9 | 0 | 0 | 4 | 178.45 |
6 | PREY | 187.26 | 25 | 0 | 0 | 4 | 178.55 |
7 | NULL | 187.82 | 25.56 | 0 | 0 | 2 | 183.61 |
8 | PREY+A.I. | 189.32 | 27.06 | 0 | 0 | 5 | 178.23 |
No. | Models_summer | AICc | ∆AICc | AICcw | Model likelihood | K | -2 log LL |
1 | A.I. | 150.57 | 0 | 0.2152 | 1 | 4 | 141.87 |
2 | TOP. | 150.68 | 0.11 | 0.2037 | 0.9465 | 5 | 139.61 |
3 | PREY+A.I. | 151.59 | 1.02 | 0.1292 | 0.6005 | 5 | 140.52 |
4 | PREY | 151.67 | 1.10 | 0.1242 | 0.5769 | 4 | 142.97 |
5 | TOP. +A.I. | 151.84 | 1.27 | 0.1141 | 0.5299 | 6 | 138.31 |
6 | NULL | 152.06 | 1.49 | 0.1022 | 0.4747 | 2 | 147.86 |
7 | HABITAT | 152.70 | 2.13 | 0.0742 | 0.3447 | 6 | 139.17 |
8 | GLOBAL | 154.08 | 3.51 | 0.0372 | 0.1729 | 7 | 138.01 |
Table 5 Model selection results for describing the probability of snow leopard (Panthera uncia) site use (ψ) in the cold and warm seasons
No. | Models_winter | AICc | ∆AICc | AICcw | Model likelihood | K | -2 log LL |
---|---|---|---|---|---|---|---|
1 | HABITAT | 162.26 | 0 | 0.4155 | 1 | 6 | 148.7 |
2 | TOP. | 162.61 | 0.35 | 0.3488 | 0.8395 | 5 | 151.52 |
3 | GLOBAL | 164.55 | 2.29 | 0.1322 | 0.3182 | 7 | 148.44 |
4 | TOP. +A.I. | 165.04 | 2.78 | 0.1035 | 0.2491 | 6 | 151.48 |
5 | A.I. | 187.16 | 24.9 | 0 | 0 | 4 | 178.45 |
6 | PREY | 187.26 | 25 | 0 | 0 | 4 | 178.55 |
7 | NULL | 187.82 | 25.56 | 0 | 0 | 2 | 183.61 |
8 | PREY+A.I. | 189.32 | 27.06 | 0 | 0 | 5 | 178.23 |
No. | Models_summer | AICc | ∆AICc | AICcw | Model likelihood | K | -2 log LL |
1 | A.I. | 150.57 | 0 | 0.2152 | 1 | 4 | 141.87 |
2 | TOP. | 150.68 | 0.11 | 0.2037 | 0.9465 | 5 | 139.61 |
3 | PREY+A.I. | 151.59 | 1.02 | 0.1292 | 0.6005 | 5 | 140.52 |
4 | PREY | 151.67 | 1.10 | 0.1242 | 0.5769 | 4 | 142.97 |
5 | TOP. +A.I. | 151.84 | 1.27 | 0.1141 | 0.5299 | 6 | 138.31 |
6 | NULL | 152.06 | 1.49 | 0.1022 | 0.4747 | 2 | 147.86 |
7 | HABITAT | 152.70 | 2.13 | 0.0742 | 0.3447 | 6 | 139.17 |
8 | GLOBAL | 154.08 | 3.51 | 0.0372 | 0.1729 | 7 | 138.01 |
No. | Models_winter | βintercepte ±SE | βGRAZE±SE | βBS±SE | βSLP1000±SE | βTRI30±SE | βTRI4000±SE |
---|---|---|---|---|---|---|---|
1 | HABITAT | 0.38±0.99 | N/A | -1.79±1.74 | 7.41±4.73 | N/A | 2.44±1.41 |
2 | TOP. | -0.27±0.75 | N/A | N/A | 3.89±2.06 | N/A | 1.62±1.01 |
3 | GLOBAL | 0.32±0.95 | -0.55±1.21 | -1.69±1.62 | 6.68±4.24 | N/A | 2.44±1.36 |
4 | TOP. +A.I. | -0.26±0.76 | -0.15±0.74 | N/A | 3.90±2.04 | N/A | 1.66±1.04 |
5 | A.I. | -0.19±0.45 | -0.21±0.40 | N/A | N/A | N/A | N/A |
6 | PREY | -0.18±0.45 | N/A | -0.15±0.36 | N/A | N/A | N/A |
7 | NULL | -0.60±0.36 | N/A | N/A | N/A | N/A | N/A |
8 | PREY+A.I. | -0.18±0.45 | -0.23±0.41 | -0.17±0.36 | N/A | N/A | N/A |
No. | Models_summer | βintercepte ±SE | βGRAZE±SE | βBS±SE | βSLP1000±SE | βTRI30±SE | βTRI4000±SE |
1 | A.I. | -0.34±0.55 | -0.77±0.57 | N/A | N/A | N/A | N/A |
2 | TOP. | -0.20±0.58 | N/A | N/A | 0.65±0.57 | 0.51±0.52 | N/A |
3 | PREY+A.I. | 0.17±1.25 | -0.97±0.89 | 1.58±2.36 | N/A | N/A | N/A |
4 | PREY | 0.06±0.72 | N/A | 0.94±1.03 | N/A | N/A | N/A |
5 | TOP. +A.I. | -0.38±0.56 | -0.63±0.54 | N/A | 0.52±0.48 | 0.49±0.52 | N/A |
6 | NULL | -0.57±0.44 | N/A | N/A | N/A | N/A | N/A |
7 | HABITAT | -0.12±0.65 | N/A | -0.37±0.57 | 0.80±0.66 | 0.70±0.66 | N/A |
8 | GLOBAL | -0.35±0.59 | -0.64±0.56 | -0.29±0.51 | 0.59±0.50 | 0.63±0.59 | N/A |
Table 6 Estimates of the Beta coefficient (β) and standard error (SE) of each covariate of the hypothetical models
No. | Models_winter | βintercepte ±SE | βGRAZE±SE | βBS±SE | βSLP1000±SE | βTRI30±SE | βTRI4000±SE |
---|---|---|---|---|---|---|---|
1 | HABITAT | 0.38±0.99 | N/A | -1.79±1.74 | 7.41±4.73 | N/A | 2.44±1.41 |
2 | TOP. | -0.27±0.75 | N/A | N/A | 3.89±2.06 | N/A | 1.62±1.01 |
3 | GLOBAL | 0.32±0.95 | -0.55±1.21 | -1.69±1.62 | 6.68±4.24 | N/A | 2.44±1.36 |
4 | TOP. +A.I. | -0.26±0.76 | -0.15±0.74 | N/A | 3.90±2.04 | N/A | 1.66±1.04 |
5 | A.I. | -0.19±0.45 | -0.21±0.40 | N/A | N/A | N/A | N/A |
6 | PREY | -0.18±0.45 | N/A | -0.15±0.36 | N/A | N/A | N/A |
7 | NULL | -0.60±0.36 | N/A | N/A | N/A | N/A | N/A |
8 | PREY+A.I. | -0.18±0.45 | -0.23±0.41 | -0.17±0.36 | N/A | N/A | N/A |
No. | Models_summer | βintercepte ±SE | βGRAZE±SE | βBS±SE | βSLP1000±SE | βTRI30±SE | βTRI4000±SE |
1 | A.I. | -0.34±0.55 | -0.77±0.57 | N/A | N/A | N/A | N/A |
2 | TOP. | -0.20±0.58 | N/A | N/A | 0.65±0.57 | 0.51±0.52 | N/A |
3 | PREY+A.I. | 0.17±1.25 | -0.97±0.89 | 1.58±2.36 | N/A | N/A | N/A |
4 | PREY | 0.06±0.72 | N/A | 0.94±1.03 | N/A | N/A | N/A |
5 | TOP. +A.I. | -0.38±0.56 | -0.63±0.54 | N/A | 0.52±0.48 | 0.49±0.52 | N/A |
6 | NULL | -0.57±0.44 | N/A | N/A | N/A | N/A | N/A |
7 | HABITAT | -0.12±0.65 | N/A | -0.37±0.57 | 0.80±0.66 | 0.70±0.66 | N/A |
8 | GLOBAL | -0.35±0.59 | -0.64±0.56 | -0.29±0.51 | 0.59±0.50 | 0.63±0.59 | N/A |
Fig. 3 Seasonal variation in elevations for blue sheep (Pseduois nayaur) and snow leopard (Panthera uncia) in two seasons, winter and summer. Note: Lines show medians of the posterior distribution, shaded areas show the 95% confidence intervals, and points show each of the 6-day means of the raw data for 90 days of winter (Nov. 2017-Jan. 2018) and summer (May-Jul. 2018).
Collapsing scenarios_winter | χ²p | ĉ | Collapsing scenarios_summer | χ²p | ĉ |
---|---|---|---|---|---|
5-day sampling occasions | 0.1882 | 0.4276 | 5-day sampling occasions | 0.0133 | 7.4845 |
10-day sampling occasions | 0.1414 | 1.3309 | 10-day sampling occasions | 0.0782 | 1.9145 |
15-day sampling occasions | 0.2261 | 1.0823 | 15-day sampling occasions | 0.1551 | 1.2427 |
18-day sampling occasions | 0.1566 | 1.2545 | 18-day sampling occasions | 0.2545 | 1.0112 |
Table S1 Chi-square probability (χ2p) and over dispersion statistic c-hat (ĉ) results of the MacKenzie and Bailey (2004) goodness-of-fit (GoF) test for snow leopard (Panthera uncia) habitat use models with different collapsing day-periods
Collapsing scenarios_winter | χ²p | ĉ | Collapsing scenarios_summer | χ²p | ĉ |
---|---|---|---|---|---|
5-day sampling occasions | 0.1882 | 0.4276 | 5-day sampling occasions | 0.0133 | 7.4845 |
10-day sampling occasions | 0.1414 | 1.3309 | 10-day sampling occasions | 0.0782 | 1.9145 |
15-day sampling occasions | 0.2261 | 1.0823 | 15-day sampling occasions | 0.1551 | 1.2427 |
18-day sampling occasions | 0.1566 | 1.2545 | 18-day sampling occasions | 0.2545 | 1.0112 |
Models_winter | ψ±SE | p̂±SE | Models_summer | ψ±SE | p̂±SE |
---|---|---|---|---|---|
HABITAT | 0.46±0.08 | 0.18±0.04 | A.I. | 0.44±0.15 | 0.18±0.06 |
TOP. | 0.43±0.09 | 0.19±0.05 | TOP. | 0.45±0.18 | 0.18±0.06 |
GLOBAL | 0.46±0.09 | 0.18±0.04 | PREY+A.I. | 0.50±0.22 | 0.16±0.06 |
TOP. +A.I. | 0.43±0.10 | 0.19±0.05 | PREY | 0.49±0.17 | 0.17±0.06 |
A.I. | 0.45±0.13 | 0.18±0.05 | TOP. +A.I. | 0.42±0.18 | 0.19±0.06 |
PREY | 0.46±0.13 | 0.18±0.05 | NULL | 0.36±0.10 | 0.23±0.07 |
NULL | 0.35±0.08 | 0.24±0.05 | HABITAT | 0.47±0.20 | 0.18±0.06 |
PREY+A.I. | 0.46±0.15 | 0.18±0.06 | GLOBAL | 0.43±0.20 | 0.19±0.06 |
Model averaged | 0.44±0.11 | 0.19±0.05 | Model averaged | 0.45±0.18 | 0.19±0.06 |
Table S2 Summary of model-averaged parameter estimates of the probability of habitat use (ψ) and detection (p?) for snow leopards (Panthera uncia) at two seasons in Qomolangma NNR
Models_winter | ψ±SE | p̂±SE | Models_summer | ψ±SE | p̂±SE |
---|---|---|---|---|---|
HABITAT | 0.46±0.08 | 0.18±0.04 | A.I. | 0.44±0.15 | 0.18±0.06 |
TOP. | 0.43±0.09 | 0.19±0.05 | TOP. | 0.45±0.18 | 0.18±0.06 |
GLOBAL | 0.46±0.09 | 0.18±0.04 | PREY+A.I. | 0.50±0.22 | 0.16±0.06 |
TOP. +A.I. | 0.43±0.10 | 0.19±0.05 | PREY | 0.49±0.17 | 0.17±0.06 |
A.I. | 0.45±0.13 | 0.18±0.05 | TOP. +A.I. | 0.42±0.18 | 0.19±0.06 |
PREY | 0.46±0.13 | 0.18±0.05 | NULL | 0.36±0.10 | 0.23±0.07 |
NULL | 0.35±0.08 | 0.24±0.05 | HABITAT | 0.47±0.20 | 0.18±0.06 |
PREY+A.I. | 0.46±0.15 | 0.18±0.06 | GLOBAL | 0.43±0.20 | 0.19±0.06 |
Model averaged | 0.44±0.11 | 0.19±0.05 | Model averaged | 0.45±0.18 | 0.19±0.06 |
Dist._ sett | KD_ sett | Dist._ road | KD_ road | TRI30 | TRI300 | TRI1000 | TRI2000 | TRI4000 | ELE30 | ELE300 | ELE1000 | ELE2000 | ELE4000 | BS | Graze | SLP30 | SLP300 | SLP1000 | SLP2000 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
KD_sett | -0.632 | |||||||||||||||||||
Dist._road | 0.233 | -0.443 | ||||||||||||||||||
KD_road | 0.071 | 0.188 | -0.645 | |||||||||||||||||
TRI30 | -0.064 | 0.127 | -0.141 | -0.066 | ||||||||||||||||
TRI300 | -0.186 | 0.297 | -0.126 | -0.092 | 0.441 | |||||||||||||||
TRI1000 | -0.324 | 0.372 | -0.120 | -0.112 | 0.330 | 0.657 | ||||||||||||||
TRI2000 | -0.336 | 0.305 | -0.143 | -0.090 | 0.242 | 0.436 | 0.832 | |||||||||||||
TRI4000 | -0.148 | -0.015 | 0.091 | -0.220 | 0.216 | 0.398 | 0.615 | 0.775 | ||||||||||||
ELE30 | 0.549 | -0.475 | 0.385 | 0.030 | -0.263 | -0.262 | -0.333 | -0.321 | -0.149 | |||||||||||
ELE300 | 0.562 | -0.513 | 0.396 | 0.027 | -0.257 | -0.303 | -0.359 | -0.346 | -0.169 | 0.995 | ||||||||||
ELE1000 | 0.615 | -0.600 | 0.413 | 0.009 | -0.233 | -0.352 | -0.394 | -0.402 | -0.242 | 0.944 | 0.968 | |||||||||
ELE2000 | 0.643 | -0.699 | 0.445 | 0.000 | -0.240 | -0.359 | -0.420 | -0.395 | -0.229 | 0.860 | 0.892 | 0.959 | ||||||||
ELE4000 | 0.632 | -0.796 | 0.478 | -0.036 | -0.164 | -0.244 | -0.377 | -0.342 | -0.120 | 0.746 | 0.780 | 0.851 | 0.940 | |||||||
BS | -0.346 | 0.142 | -0.105 | -0.153 | 0.158 | 0.159 | 0.336 | 0.283 | 0.109 | -0.192 | -0.190 | -0.168 | -0.171 | -0.154 | ||||||
Graze | 0.094 | -0.194 | 0.098 | -0.071 | 0.007 | -0.160 | -0.067 | -0.032 | -0.049 | 0.001 | 0.026 | 0.087 | 0.152 | 0.157 | -0.063 | |||||
SLP30 | -0.172 | 0.287 | -0.259 | -0.035 | 0.911 | 0.563 | 0.374 | 0.318 | 0.262 | -0.385 | -0.394 | -0.404 | -0.425 | -0.344 | 0.181 | -0.080 | ||||
SLP300 | -0.151 | 0.284 | -0.178 | -0.085 | 0.326 | 0.896 | 0.622 | 0.438 | 0.406 | -0.213 | -0.253 | -0.323 | -0.335 | -0.240 | 0.137 | -0.170 | 0.443 | |||
SLP1000 | -0.027 | 0.142 | 0.004 | -0.220 | 0.272 | 0.582 | 0.691 | 0.554 | 0.557 | -0.138 | -0.160 | -0.192 | -0.232 | -0.187 | 0.143 | -0.171 | 0.260 | 0.711 | ||
SLP2000 | 0.072 | -0.202 | 0.234 | -0.323 | 0.262 | 0.366 | 0.513 | 0.500 | 0.703 | -0.052 | -0.055 | -0.071 | -0.048 | 0.047 | 0.135 | -0.131 | 0.215 | 0.468 | 0.809 | |
SLP4000 | 0.177 | -0.394 | 0.231 | -0.200 | 0.232 | 0.236 | 0.359 | 0.372 | 0.623 | -0.066 | -0.054 | -0.061 | 0.015 | 0.205 | 0.023 | -0.074 | 0.164 | 0.302 | 0.519 | 0.831 |
Table S3 Correlation matrix of the continuous covariates in winter
Dist._ sett | KD_ sett | Dist._ road | KD_ road | TRI30 | TRI300 | TRI1000 | TRI2000 | TRI4000 | ELE30 | ELE300 | ELE1000 | ELE2000 | ELE4000 | BS | Graze | SLP30 | SLP300 | SLP1000 | SLP2000 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
KD_sett | -0.632 | |||||||||||||||||||
Dist._road | 0.233 | -0.443 | ||||||||||||||||||
KD_road | 0.071 | 0.188 | -0.645 | |||||||||||||||||
TRI30 | -0.064 | 0.127 | -0.141 | -0.066 | ||||||||||||||||
TRI300 | -0.186 | 0.297 | -0.126 | -0.092 | 0.441 | |||||||||||||||
TRI1000 | -0.324 | 0.372 | -0.120 | -0.112 | 0.330 | 0.657 | ||||||||||||||
TRI2000 | -0.336 | 0.305 | -0.143 | -0.090 | 0.242 | 0.436 | 0.832 | |||||||||||||
TRI4000 | -0.148 | -0.015 | 0.091 | -0.220 | 0.216 | 0.398 | 0.615 | 0.775 | ||||||||||||
ELE30 | 0.549 | -0.475 | 0.385 | 0.030 | -0.263 | -0.262 | -0.333 | -0.321 | -0.149 | |||||||||||
ELE300 | 0.562 | -0.513 | 0.396 | 0.027 | -0.257 | -0.303 | -0.359 | -0.346 | -0.169 | 0.995 | ||||||||||
ELE1000 | 0.615 | -0.600 | 0.413 | 0.009 | -0.233 | -0.352 | -0.394 | -0.402 | -0.242 | 0.944 | 0.968 | |||||||||
ELE2000 | 0.643 | -0.699 | 0.445 | 0.000 | -0.240 | -0.359 | -0.420 | -0.395 | -0.229 | 0.860 | 0.892 | 0.959 | ||||||||
ELE4000 | 0.632 | -0.796 | 0.478 | -0.036 | -0.164 | -0.244 | -0.377 | -0.342 | -0.120 | 0.746 | 0.780 | 0.851 | 0.940 | |||||||
BS | -0.346 | 0.142 | -0.105 | -0.153 | 0.158 | 0.159 | 0.336 | 0.283 | 0.109 | -0.192 | -0.190 | -0.168 | -0.171 | -0.154 | ||||||
Graze | 0.094 | -0.194 | 0.098 | -0.071 | 0.007 | -0.160 | -0.067 | -0.032 | -0.049 | 0.001 | 0.026 | 0.087 | 0.152 | 0.157 | -0.063 | |||||
SLP30 | -0.172 | 0.287 | -0.259 | -0.035 | 0.911 | 0.563 | 0.374 | 0.318 | 0.262 | -0.385 | -0.394 | -0.404 | -0.425 | -0.344 | 0.181 | -0.080 | ||||
SLP300 | -0.151 | 0.284 | -0.178 | -0.085 | 0.326 | 0.896 | 0.622 | 0.438 | 0.406 | -0.213 | -0.253 | -0.323 | -0.335 | -0.240 | 0.137 | -0.170 | 0.443 | |||
SLP1000 | -0.027 | 0.142 | 0.004 | -0.220 | 0.272 | 0.582 | 0.691 | 0.554 | 0.557 | -0.138 | -0.160 | -0.192 | -0.232 | -0.187 | 0.143 | -0.171 | 0.260 | 0.711 | ||
SLP2000 | 0.072 | -0.202 | 0.234 | -0.323 | 0.262 | 0.366 | 0.513 | 0.500 | 0.703 | -0.052 | -0.055 | -0.071 | -0.048 | 0.047 | 0.135 | -0.131 | 0.215 | 0.468 | 0.809 | |
SLP4000 | 0.177 | -0.394 | 0.231 | -0.200 | 0.232 | 0.236 | 0.359 | 0.372 | 0.623 | -0.066 | -0.054 | -0.061 | 0.015 | 0.205 | 0.023 | -0.074 | 0.164 | 0.302 | 0.519 | 0.831 |
BS | Graze | Dist._ SETT | KD_ SETT | Dist._ ROAD | KD_ ROAD | TRI30 | TRI300 | TRI1000 | TRI2000 | TRI4000 | ELE30 | ELE300 | ELE1000 | ELE2000 | ELE4000 | SLP30 | SLP300 | SLP1000 | SLP2000 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Graze | -0.093 | |||||||||||||||||||
Dist._SETT | -0.109 | -0.126 | ||||||||||||||||||
KD_SETT | 0.002 | 0.051 | -0.629 | |||||||||||||||||
Dist._ROAD | -0.018 | -0.115 | 0.290 | -0.492 | ||||||||||||||||
KD_ROAD | -0.124 | 0.140 | 0.030 | 0.205 | -0.631 | |||||||||||||||
TRI30 | 0.184 | 0.020 | -0.151 | 0.141 | -0.175 | -0.072 | ||||||||||||||
TRI300 | 0.332 | -0.044 | -0.149 | 0.170 | -0.160 | -0.062 | 0.434 | |||||||||||||
TRI1000 | 0.327 | 0.012 | -0.209 | 0.161 | -0.060 | -0.086 | 0.320 | 0.670 | ||||||||||||
TRI2000 | 0.301 | 0.072 | -0.229 | 0.160 | -0.118 | -0.039 | 0.275 | 0.481 | 0.865 | |||||||||||
TRI4000 | 0.399 | 0.059 | -0.088 | -0.058 | 0.028 | -0.125 | 0.275 | 0.432 | 0.665 | 0.793 | ||||||||||
ELE30 | -0.136 | -0.243 | 0.581 | -0.543 | 0.422 | 0.005 | -0.362 | -0.319 | -0.245 | -0.246 | -0.153 | |||||||||
ELE300 | -0.159 | -0.214 | 0.587 | -0.576 | 0.434 | 0.001 | -0.363 | -0.348 | -0.256 | -0.258 | -0.166 | 0.995 | ||||||||
ELE1000 | -0.203 | -0.150 | 0.626 | -0.649 | 0.454 | -0.018 | -0.340 | -0.355 | -0.253 | -0.277 | -0.218 | 0.950 | 0.971 | |||||||
ELE2000 | -0.188 | -0.125 | 0.642 | -0.732 | 0.482 | -0.019 | -0.347 | -0.340 | -0.259 | -0.273 | -0.219 | 0.874 | 0.901 | 0.960 | ||||||
ELE4000 | -0.148 | -0.124 | 0.627 | -0.818 | 0.502 | -0.042 | -0.262 | -0.221 | -0.198 | -0.211 | -0.112 | 0.752 | 0.782 | 0.851 | 0.942 | |||||
SLP30 | 0.211 | 0.023 | -0.228 | 0.312 | -0.295 | -0.027 | 0.908 | 0.548 | 0.347 | 0.326 | 0.300 | -0.462 | -0.475 | -0.480 | -0.496 | -0.410 | ||||
SLP300 | 0.420 | -0.036 | -0.103 | 0.158 | -0.215 | -0.057 | 0.279 | 0.871 | 0.627 | 0.478 | 0.439 | -0.278 | -0.301 | -0.316 | -0.310 | -0.217 | 0.399 | |||
SLP1000 | 0.413 | -0.062 | 0.023 | -0.024 | 0.026 | -0.177 | 0.191 | 0.586 | 0.741 | 0.649 | 0.620 | -0.115 | -0.120 | -0.101 | -0.129 | -0.079 | 0.189 | 0.734 | ||
SLP2000 | 0.483 | -0.026 | 0.083 | -0.239 | 0.204 | -0.252 | 0.200 | 0.438 | 0.662 | 0.635 | 0.733 | -0.040 | -0.036 | -0.020 | -0.009 | 0.073 | 0.167 | 0.553 | 0.884 | |
SLP4000 | 0.390 | -0.018 | 0.168 | -0.372 | 0.203 | -0.158 | 0.210 | 0.332 | 0.565 | 0.551 | 0.695 | -0.078 | -0.064 | -0.043 | 0.025 | 0.194 | 0.153 | 0.409 | 0.666 | 0.867 |
Table S4 Correlation matrix of the continuous covariates in summer
BS | Graze | Dist._ SETT | KD_ SETT | Dist._ ROAD | KD_ ROAD | TRI30 | TRI300 | TRI1000 | TRI2000 | TRI4000 | ELE30 | ELE300 | ELE1000 | ELE2000 | ELE4000 | SLP30 | SLP300 | SLP1000 | SLP2000 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Graze | -0.093 | |||||||||||||||||||
Dist._SETT | -0.109 | -0.126 | ||||||||||||||||||
KD_SETT | 0.002 | 0.051 | -0.629 | |||||||||||||||||
Dist._ROAD | -0.018 | -0.115 | 0.290 | -0.492 | ||||||||||||||||
KD_ROAD | -0.124 | 0.140 | 0.030 | 0.205 | -0.631 | |||||||||||||||
TRI30 | 0.184 | 0.020 | -0.151 | 0.141 | -0.175 | -0.072 | ||||||||||||||
TRI300 | 0.332 | -0.044 | -0.149 | 0.170 | -0.160 | -0.062 | 0.434 | |||||||||||||
TRI1000 | 0.327 | 0.012 | -0.209 | 0.161 | -0.060 | -0.086 | 0.320 | 0.670 | ||||||||||||
TRI2000 | 0.301 | 0.072 | -0.229 | 0.160 | -0.118 | -0.039 | 0.275 | 0.481 | 0.865 | |||||||||||
TRI4000 | 0.399 | 0.059 | -0.088 | -0.058 | 0.028 | -0.125 | 0.275 | 0.432 | 0.665 | 0.793 | ||||||||||
ELE30 | -0.136 | -0.243 | 0.581 | -0.543 | 0.422 | 0.005 | -0.362 | -0.319 | -0.245 | -0.246 | -0.153 | |||||||||
ELE300 | -0.159 | -0.214 | 0.587 | -0.576 | 0.434 | 0.001 | -0.363 | -0.348 | -0.256 | -0.258 | -0.166 | 0.995 | ||||||||
ELE1000 | -0.203 | -0.150 | 0.626 | -0.649 | 0.454 | -0.018 | -0.340 | -0.355 | -0.253 | -0.277 | -0.218 | 0.950 | 0.971 | |||||||
ELE2000 | -0.188 | -0.125 | 0.642 | -0.732 | 0.482 | -0.019 | -0.347 | -0.340 | -0.259 | -0.273 | -0.219 | 0.874 | 0.901 | 0.960 | ||||||
ELE4000 | -0.148 | -0.124 | 0.627 | -0.818 | 0.502 | -0.042 | -0.262 | -0.221 | -0.198 | -0.211 | -0.112 | 0.752 | 0.782 | 0.851 | 0.942 | |||||
SLP30 | 0.211 | 0.023 | -0.228 | 0.312 | -0.295 | -0.027 | 0.908 | 0.548 | 0.347 | 0.326 | 0.300 | -0.462 | -0.475 | -0.480 | -0.496 | -0.410 | ||||
SLP300 | 0.420 | -0.036 | -0.103 | 0.158 | -0.215 | -0.057 | 0.279 | 0.871 | 0.627 | 0.478 | 0.439 | -0.278 | -0.301 | -0.316 | -0.310 | -0.217 | 0.399 | |||
SLP1000 | 0.413 | -0.062 | 0.023 | -0.024 | 0.026 | -0.177 | 0.191 | 0.586 | 0.741 | 0.649 | 0.620 | -0.115 | -0.120 | -0.101 | -0.129 | -0.079 | 0.189 | 0.734 | ||
SLP2000 | 0.483 | -0.026 | 0.083 | -0.239 | 0.204 | -0.252 | 0.200 | 0.438 | 0.662 | 0.635 | 0.733 | -0.040 | -0.036 | -0.020 | -0.009 | 0.073 | 0.167 | 0.553 | 0.884 | |
SLP4000 | 0.390 | -0.018 | 0.168 | -0.372 | 0.203 | -0.158 | 0.210 | 0.332 | 0.565 | 0.551 | 0.695 | -0.078 | -0.064 | -0.043 | 0.025 | 0.194 | 0.153 | 0.409 | 0.666 | 0.867 |
Models_winter | AICc | ∆AICc | AICcw | Model Likelihood | K | -2 log LL | Models_summer | AICc | ∆AICc | AICcw | Model Likelihood | K | -2 log LL |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ψ(SLP1000) | 165.17 | 0.00 | 0.9517 | 1.0000 | 4 | 156.46 | ψ(SLP1000) | 149.41 | 0.00 | 0.1154 | 1.0000 | 4 | 140.71 |
ψ(TRI4000) | 173.10 | 7.93 | 0.0181 | 0.0190 | 4 | 164.39 | ψ(SLP4000) | 150.07 | 0.66 | 0.0830 | 0.7189 | 4 | 141.37 |
ψ(TRI1000) | 173.17 | 8.00 | 0.0174 | 0.0183 | 4 | 164.46 | ψ(TRI30) | 150.16 | 0.75 | 0.0793 | 0.6873 | 4 | 141.46 |
ψ(SLP300) | 176.19 | 11.02 | 0.0039 | 0.0040 | 4 | 167.48 | ψ(SLP2000) | 150.21 | 0.80 | 0.0774 | 0.6703 | 4 | 141.51 |
ψ(SLP2000) | 176.49 | 11.32 | 0.0033 | 0.0035 | 4 | 167.78 | ψ(.) | 150.50 | 1.09 | 0.0669 | 0.5798 | 3 | 144.09 |
ψ(TRI2000) | 176.67 | 11.50 | 0.0030 | 0.0032 | 4 | 167.96 | ψ(GRAZE) | 150.57 | 1.16 | 0.0646 | 0.5599 | 4 | 141.87 |
ψ(TRI300) | 177.94 | 12.77 | 0.0016 | 0.0017 | 4 | 169.23 | ψ(TRI4000) | 150.80 | 1.39 | 0.0576 | 0.4991 | 4 | 142.10 |
ψ(ELE2000) | 181.79 | 16.62 | 0.0002 | 0.0002 | 4 | 173.08 | ψ(SLP300) | 150.87 | 1.46 | 0.0556 | 0.4819 | 4 | 142.17 |
ψ(SLP4000) | 182.43 | 17.26 | 0.0002 | 0.0002 | 4 | 173.72 | ψ(SLP30) | 150.91 | 1.50 | 0.0545 | 0.4724 | 4 | 142.21 |
ψ(ELE4000) | 183.20 | 18.03 | 0.0001 | 0.0001 | 4 | 174.49 | ψ(TRI1000) | 151.47 | 2.06 | 0.0412 | 0.3570 | 4 | 142.77 |
ψ(ELE1000) | 183.51 | 18.34 | 0.0001 | 0.0001 | 4 | 174.80 | ψ(BS) | 151.67 | 2.26 | 0.0373 | 0.3230 | 4 | 142.97 |
ψ(KD_SETT) | 184.08 | 18.91 | 0.0001 | 0.0001 | 4 | 175.37 | ψ(TRI300) | 152.02 | 2.61 | 0.0313 | 0.2712 | 4 | 143.32 |
ψ(.) | 185.15 | 19.98 | 0.0000 | 0.0000 | 3 | 178.73 | ψ(Dist._SETT) | 152.20 | 2.79 | 0.0286 | 0.2478 | 4 | 143.50 |
ψ(ELE300) | 185.34 | 20.17 | 0.0000 | 0.0000 | 4 | 176.63 | ψ(KD_ROAD) | 152.41 | 3.00 | 0.0258 | 0.2231 | 4 | 143.71 |
ψ(SLP30) | 185.58 | 20.41 | 0.0000 | 0.0000 | 4 | 176.87 | ψ(TRI2000) | 152.43 | 3.02 | 0.0255 | 0.2209 | 4 | 143.73 |
ψ(TRI30) | 185.92 | 20.75 | 0.0000 | 0.0000 | 4 | 177.21 | ψ(Dist._ROAD) | 152.52 | 3.11 | 0.0244 | 0.2112 | 4 | 143.82 |
ψ(ELE30) | 185.96 | 20.79 | 0.0000 | 0.0000 | 4 | 177.25 | ψ(ELE2000) | 152.64 | 3.23 | 0.0230 | 0.1989 | 4 | 143.94 |
ψ(KD_ROAD) | 186.06 | 20.89 | 0.0000 | 0.0000 | 4 | 177.35 | ψ(ELE4000) | 152.71 | 3.30 | 0.0222 | 0.1920 | 4 | 144.01 |
ψ(Dist._SETT) | 186.40 | 21.23 | 0.0000 | 0.0000 | 4 | 177.69 | ψ(ELE30) | 152.75 | 3.34 | 0.0217 | 0.1882 | 4 | 144.05 |
ψ(GRAZE) | 187.16 | 21.99 | 0.0000 | 0.0000 | 4 | 178.45 | ψ(ELE300) | 152.76 | 3.35 | 0.0216 | 0.1873 | 4 | 144.06 |
ψ(BS) | 187.26 | 22.09 | 0.0000 | 0.0000 | 4 | 178.55 | ψ(KD_SETT) | 152.77 | 3.36 | 0.0215 | 0.1864 | 4 | 144.07 |
ψ(Dist._ROAD) | 187.37 | 22.20 | 0.0000 | 0.0000 | 4 | 178.66 | ψ(ELE1000) | 152.78 | 3.37 | 0.0214 | 0.1854 | 4 | 144.08 |
Table S5 Portion of snow leopard (Panthera uncia) single covariate occupancy models (ψ) in winter and summer
Models_winter | AICc | ∆AICc | AICcw | Model Likelihood | K | -2 log LL | Models_summer | AICc | ∆AICc | AICcw | Model Likelihood | K | -2 log LL |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ψ(SLP1000) | 165.17 | 0.00 | 0.9517 | 1.0000 | 4 | 156.46 | ψ(SLP1000) | 149.41 | 0.00 | 0.1154 | 1.0000 | 4 | 140.71 |
ψ(TRI4000) | 173.10 | 7.93 | 0.0181 | 0.0190 | 4 | 164.39 | ψ(SLP4000) | 150.07 | 0.66 | 0.0830 | 0.7189 | 4 | 141.37 |
ψ(TRI1000) | 173.17 | 8.00 | 0.0174 | 0.0183 | 4 | 164.46 | ψ(TRI30) | 150.16 | 0.75 | 0.0793 | 0.6873 | 4 | 141.46 |
ψ(SLP300) | 176.19 | 11.02 | 0.0039 | 0.0040 | 4 | 167.48 | ψ(SLP2000) | 150.21 | 0.80 | 0.0774 | 0.6703 | 4 | 141.51 |
ψ(SLP2000) | 176.49 | 11.32 | 0.0033 | 0.0035 | 4 | 167.78 | ψ(.) | 150.50 | 1.09 | 0.0669 | 0.5798 | 3 | 144.09 |
ψ(TRI2000) | 176.67 | 11.50 | 0.0030 | 0.0032 | 4 | 167.96 | ψ(GRAZE) | 150.57 | 1.16 | 0.0646 | 0.5599 | 4 | 141.87 |
ψ(TRI300) | 177.94 | 12.77 | 0.0016 | 0.0017 | 4 | 169.23 | ψ(TRI4000) | 150.80 | 1.39 | 0.0576 | 0.4991 | 4 | 142.10 |
ψ(ELE2000) | 181.79 | 16.62 | 0.0002 | 0.0002 | 4 | 173.08 | ψ(SLP300) | 150.87 | 1.46 | 0.0556 | 0.4819 | 4 | 142.17 |
ψ(SLP4000) | 182.43 | 17.26 | 0.0002 | 0.0002 | 4 | 173.72 | ψ(SLP30) | 150.91 | 1.50 | 0.0545 | 0.4724 | 4 | 142.21 |
ψ(ELE4000) | 183.20 | 18.03 | 0.0001 | 0.0001 | 4 | 174.49 | ψ(TRI1000) | 151.47 | 2.06 | 0.0412 | 0.3570 | 4 | 142.77 |
ψ(ELE1000) | 183.51 | 18.34 | 0.0001 | 0.0001 | 4 | 174.80 | ψ(BS) | 151.67 | 2.26 | 0.0373 | 0.3230 | 4 | 142.97 |
ψ(KD_SETT) | 184.08 | 18.91 | 0.0001 | 0.0001 | 4 | 175.37 | ψ(TRI300) | 152.02 | 2.61 | 0.0313 | 0.2712 | 4 | 143.32 |
ψ(.) | 185.15 | 19.98 | 0.0000 | 0.0000 | 3 | 178.73 | ψ(Dist._SETT) | 152.20 | 2.79 | 0.0286 | 0.2478 | 4 | 143.50 |
ψ(ELE300) | 185.34 | 20.17 | 0.0000 | 0.0000 | 4 | 176.63 | ψ(KD_ROAD) | 152.41 | 3.00 | 0.0258 | 0.2231 | 4 | 143.71 |
ψ(SLP30) | 185.58 | 20.41 | 0.0000 | 0.0000 | 4 | 176.87 | ψ(TRI2000) | 152.43 | 3.02 | 0.0255 | 0.2209 | 4 | 143.73 |
ψ(TRI30) | 185.92 | 20.75 | 0.0000 | 0.0000 | 4 | 177.21 | ψ(Dist._ROAD) | 152.52 | 3.11 | 0.0244 | 0.2112 | 4 | 143.82 |
ψ(ELE30) | 185.96 | 20.79 | 0.0000 | 0.0000 | 4 | 177.25 | ψ(ELE2000) | 152.64 | 3.23 | 0.0230 | 0.1989 | 4 | 143.94 |
ψ(KD_ROAD) | 186.06 | 20.89 | 0.0000 | 0.0000 | 4 | 177.35 | ψ(ELE4000) | 152.71 | 3.30 | 0.0222 | 0.1920 | 4 | 144.01 |
ψ(Dist._SETT) | 186.40 | 21.23 | 0.0000 | 0.0000 | 4 | 177.69 | ψ(ELE30) | 152.75 | 3.34 | 0.0217 | 0.1882 | 4 | 144.05 |
ψ(GRAZE) | 187.16 | 21.99 | 0.0000 | 0.0000 | 4 | 178.45 | ψ(ELE300) | 152.76 | 3.35 | 0.0216 | 0.1873 | 4 | 144.06 |
ψ(BS) | 187.26 | 22.09 | 0.0000 | 0.0000 | 4 | 178.55 | ψ(KD_SETT) | 152.77 | 3.36 | 0.0215 | 0.1864 | 4 | 144.07 |
ψ(Dist._ROAD) | 187.37 | 22.20 | 0.0000 | 0.0000 | 4 | 178.66 | ψ(ELE1000) | 152.78 | 3.37 | 0.0214 | 0.1854 | 4 | 144.08 |
Models_winter | AICc | ∆AICc | AICcw | Model Likelihood | K | -2 log LL | Models_summer | AICc | ∆AICc | AICcw | Model Likelihood | K | -2 log LL |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ψ(TRI4000+SLP1000) | 162.61 | 0.00 | 0.7130 | 1.0000 | 5 | 151.52 | ψ(.) | 150.50 | 0.00 | 0.1259 | 1.0000 | 3 | 144.09 |
ψ(TRI2000+SLP1000) | 166.46 | 3.85 | 0.1040 | 0.1459 | 5 | 155.37 | ψ(TRI30+SLP1000) | 150.68 | 0.18 | 0.1151 | 0.9139 | 5 | 139.61 |
ψ(TRI300+SLP1000) | 167.09 | 4.48 | 0.0759 | 0.1065 | 5 | 156.00 | ψ(TRI30+SLP4000) | 150.99 | 0.49 | 0.0985 | 0.7827 | 5 | 139.92 |
ψ(TRI30+SLP1000) | 167.49 | 4.88 | 0.0621 | 0.0872 | 5 | 156.40 | ψ(TRI30+SLP2000) | 151.34 | 0.84 | 0.0827 | 0.6570 | 5 | 140.27 |
ψ(TRI4000+SLP300) | 169.02 | 6.41 | 0.0289 | 0.0406 | 5 | 157.93 | ψ(TRI300+SLP1000) | 151.71 | 1.21 | 0.0688 | 0.5461 | 5 | 140.64 |
ψ(TRI1000+SLP4000) | 173.17 | 10.56 | 0.0036 | 0.0051 | 5 | 162.08 | ψ(TRI30+SLP300) | 151.95 | 1.45 | 0.0610 | 0.4843 | 5 | 140.88 |
ψ(TRI300+SLP2000) | 173.29 | 10.68 | 0.0034 | 0.0048 | 5 | 162.20 | ψ(TRI2000+SLP4000) | 151.95 | 1.45 | 0.0610 | 0.4843 | 5 | 140.88 |
ψ(TRI2000+SLP300) | 174.19 | 11.58 | 0.0022 | 0.0031 | 5 | 163.10 | ψ(TRI4000+SLP30) | 152.05 | 1.55 | 0.0580 | 0.4607 | 5 | 140.98 |
ψ(TRI1000+SLP2000) | 174.40 | 11.79 | 0.0020 | 0.0028 | 5 | 163.31 | ψ(TRI300+SLP4000) | 152.39 | 1.89 | 0.0489 | 0.3887 | 5 | 141.32 |
ψ(TRI1000+SLP30) | 175.21 | 12.60 | 0.0013 | 0.0018 | 5 | 164.12 | ψ(TRI4000+SLP300) | 152.43 | 1.93 | 0.0480 | 0.3810 | 5 | 141.36 |
ψ(TRI4000+SLP30) | 175.30 | 12.69 | 0.0013 | 0.0018 | 5 | 164.21 | ψ(TRI1000+SLP4000) | 152.44 | 1.94 | 0.0477 | 0.3791 | 5 | 141.37 |
ψ(TRI2000+SLP2000) | 176.53 | 13.92 | 0.0007 | 0.0009 | 5 | 165.44 | ψ(TRI300+SLP2000) | 152.56 | 2.06 | 0.0449 | 0.3570 | 5 | 141.49 |
ψ(TRI300+SLP4000) | 177.22 | 14.61 | 0.0005 | 0.0007 | 5 | 166.13 | ψ(TRI1000+SLP30) | 152.61 | 2.11 | 0.0438 | 0.3482 | 5 | 141.54 |
ψ(TRI30+SLP300) | 178.57 | 15.96 | 0.0002 | 0.0003 | 5 | 167.48 | ψ(TRI2000+SLP300) | 153.23 | 2.73 | 0.0322 | 0.2554 | 5 | 142.16 |
ψ(TRI2000+SLP4000) | 178.59 | 15.98 | 0.0002 | 0.0003 | 5 | 167.50 | ψ(TRI2000+SLP30) | 153.24 | 2.74 | 0.0320 | 0.2541 | 5 | 142.17 |
ψ(TRI30+SLP2000) | 178.86 | 16.25 | 0.0002 | 0.0003 | 5 | 167.77 | ψ(TRI300+SLP30) | 153.27 | 2.77 | 0.0315 | 0.2503 | 5 | 142.20 |
ψ(TRI2000+SLP30) | 178.92 | 16.31 | 0.0002 | 0.0003 | 5 | 167.83 | |||||||
ψ(TRI300+SLP30) | 179.52 | 16.91 | 0.0002 | 0.0002 | 5 | 168.43 | |||||||
ψ(TRI30+SLP4000) | 184.43 | 21.82 | 0.0000 | 0.0000 | 5 | 173.34 | |||||||
ψ(.) | 185.15 | 22.54 | 0.0000 | 0.0000 | 3 | 178.73 |
Table S6 True optimum multi-scale approach of topographic gradient variables of snow leopard (Panthera uncia) habitat use in winter and summer
Models_winter | AICc | ∆AICc | AICcw | Model Likelihood | K | -2 log LL | Models_summer | AICc | ∆AICc | AICcw | Model Likelihood | K | -2 log LL |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ψ(TRI4000+SLP1000) | 162.61 | 0.00 | 0.7130 | 1.0000 | 5 | 151.52 | ψ(.) | 150.50 | 0.00 | 0.1259 | 1.0000 | 3 | 144.09 |
ψ(TRI2000+SLP1000) | 166.46 | 3.85 | 0.1040 | 0.1459 | 5 | 155.37 | ψ(TRI30+SLP1000) | 150.68 | 0.18 | 0.1151 | 0.9139 | 5 | 139.61 |
ψ(TRI300+SLP1000) | 167.09 | 4.48 | 0.0759 | 0.1065 | 5 | 156.00 | ψ(TRI30+SLP4000) | 150.99 | 0.49 | 0.0985 | 0.7827 | 5 | 139.92 |
ψ(TRI30+SLP1000) | 167.49 | 4.88 | 0.0621 | 0.0872 | 5 | 156.40 | ψ(TRI30+SLP2000) | 151.34 | 0.84 | 0.0827 | 0.6570 | 5 | 140.27 |
ψ(TRI4000+SLP300) | 169.02 | 6.41 | 0.0289 | 0.0406 | 5 | 157.93 | ψ(TRI300+SLP1000) | 151.71 | 1.21 | 0.0688 | 0.5461 | 5 | 140.64 |
ψ(TRI1000+SLP4000) | 173.17 | 10.56 | 0.0036 | 0.0051 | 5 | 162.08 | ψ(TRI30+SLP300) | 151.95 | 1.45 | 0.0610 | 0.4843 | 5 | 140.88 |
ψ(TRI300+SLP2000) | 173.29 | 10.68 | 0.0034 | 0.0048 | 5 | 162.20 | ψ(TRI2000+SLP4000) | 151.95 | 1.45 | 0.0610 | 0.4843 | 5 | 140.88 |
ψ(TRI2000+SLP300) | 174.19 | 11.58 | 0.0022 | 0.0031 | 5 | 163.10 | ψ(TRI4000+SLP30) | 152.05 | 1.55 | 0.0580 | 0.4607 | 5 | 140.98 |
ψ(TRI1000+SLP2000) | 174.40 | 11.79 | 0.0020 | 0.0028 | 5 | 163.31 | ψ(TRI300+SLP4000) | 152.39 | 1.89 | 0.0489 | 0.3887 | 5 | 141.32 |
ψ(TRI1000+SLP30) | 175.21 | 12.60 | 0.0013 | 0.0018 | 5 | 164.12 | ψ(TRI4000+SLP300) | 152.43 | 1.93 | 0.0480 | 0.3810 | 5 | 141.36 |
ψ(TRI4000+SLP30) | 175.30 | 12.69 | 0.0013 | 0.0018 | 5 | 164.21 | ψ(TRI1000+SLP4000) | 152.44 | 1.94 | 0.0477 | 0.3791 | 5 | 141.37 |
ψ(TRI2000+SLP2000) | 176.53 | 13.92 | 0.0007 | 0.0009 | 5 | 165.44 | ψ(TRI300+SLP2000) | 152.56 | 2.06 | 0.0449 | 0.3570 | 5 | 141.49 |
ψ(TRI300+SLP4000) | 177.22 | 14.61 | 0.0005 | 0.0007 | 5 | 166.13 | ψ(TRI1000+SLP30) | 152.61 | 2.11 | 0.0438 | 0.3482 | 5 | 141.54 |
ψ(TRI30+SLP300) | 178.57 | 15.96 | 0.0002 | 0.0003 | 5 | 167.48 | ψ(TRI2000+SLP300) | 153.23 | 2.73 | 0.0322 | 0.2554 | 5 | 142.16 |
ψ(TRI2000+SLP4000) | 178.59 | 15.98 | 0.0002 | 0.0003 | 5 | 167.50 | ψ(TRI2000+SLP30) | 153.24 | 2.74 | 0.0320 | 0.2541 | 5 | 142.17 |
ψ(TRI30+SLP2000) | 178.86 | 16.25 | 0.0002 | 0.0003 | 5 | 167.77 | ψ(TRI300+SLP30) | 153.27 | 2.77 | 0.0315 | 0.2503 | 5 | 142.20 |
ψ(TRI2000+SLP30) | 178.92 | 16.31 | 0.0002 | 0.0003 | 5 | 167.83 | |||||||
ψ(TRI300+SLP30) | 179.52 | 16.91 | 0.0002 | 0.0002 | 5 | 168.43 | |||||||
ψ(TRI30+SLP4000) | 184.43 | 21.82 | 0.0000 | 0.0000 | 5 | 173.34 | |||||||
ψ(.) | 185.15 | 22.54 | 0.0000 | 0.0000 | 3 | 178.73 |
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