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. 2020 Jun 18;10:9941. doi: 10.1038/s41598-020-66626-1

Table 2.

Output of the generalized linear mixed models to analyze wolf habitat selection in Scandinavia, using the scores of the PC1 as response variable (variation in PC1 was mostly explained by Elevation).

Type of location Type of Home Range Model rank Model Coefficients df logLik AICc Delta AICc Model weight
All locations KERN 1 Seasons 6 −36,7 87,6 0 0,60
Estimate Lower 95% CI Upper 95% CI t value
(Intercept) 0,36291 0,04687 0,67895 2,297
Allopatric Winter −0,38762 −0,7811 0,00586 −1,97
Sympatric Summer 0,05266 −0,50846 0,61378 0,188
Sympatric Winter −0,9522 −1,4583 −0,4461 −3,763
2 Seasons + Moose 7 −35,8 88,8 1,15 0,34
Estimate Lower 95% CI Upper 95% CI t value
(Intercept) 0,43673 −0,15909 1,03255 1,466
Allopatric Winter −0,38642 −0,78402 0,01118 −1,944
Sympatric Summer 0,02202 −0,58134 0,62538 0,073
Sympatric Winter −0,98664 −1,54896 −0,42432 −3,509
Moose −0,25475 −2,05037 1,54087 −0,284
3 Null Model 3 −43,4 93,3 5,68 0,04
4 Moose 4 −42,5 93,9 6,33 0,03
MCP 1 Seasons 6 −34,3 82,8 0 0,53
Estimate Lower 95% CI Upper 95% CI t value
(Intercept) −0,2327 −0,5319 0,0665 −1,556
Allopatric Winter 0,226 −0,141 0,593 1,232
Sympatric Summer −0,2629 −0,7983 0,2725 −0,982
Sympatric Winter 0,7697 0,2837 1,2557 3,168
2 Seasons + Moose 7 −33,1 83,4 0,57 0,4
Estimate Lower 95% CI Upper 95% CI t value
(Intercept) −0,4383 −0,9983 0,1217 −1,565
Allopatric Winter 0,2164 −0,1532 0,586 1,171
Sympatric Summer −0,1832 −0,7498 0,3834 −0,647
Sympatric Winter 0,8615 0,3321 1,3909 3,255
Moose 0,7463 −0,9443 2,4369 0,883
3 Null Model 3 −40,5 87,5 4,71 0,05
4 Moose 4 −39,8 88,6 13,38 0,001
Only moving locations KERN 1 Seasons 6 −31,5 77,2 0 0,64
Estimate Lower 95% CI Upper 95% CI t value
(Intercept) 0,387227 0,102661 0,671793 −2,722
Allopatric Winter 0,357956 0,027826 0,688086 2,169
Sympatric Summer 0,001058 −0,523912 0,526028 0,004
Sympatric Winter 0,954532 0,46789 1,441174 3,923
2 Seasons + Moose 7 −30,7 78,5 1,24 0,35
Estimate Lower 95% CI Upper 95% CI t value
(Intercept) −0,4504 −1,01538 0,11458 −1,594
Allopatric Winter 0,35728 0,02378 0,69078 2,143
Sympatric Summer 0,02766 −0,54028 0,5956 0,097
Sympatric Winter 0,98447 0,44175 1,52719 3,628
Moose 0,21745 −1,51675 1,95165 0,251
3 Null Model 3 −39,8 86,2 8,98 0,007
4 Moose 4 −38,9 86,8 9,58 0,005
MCP 1 Seasons 6 −30,1 74,5 0 0,52
Estimate Lower 95% CI Upper 95% CI t value
(Intercept) 0,05595 −0,21069 0,32259 0,42
Allopatric Winter −0,09552 −0,4332 0,24216 −0,566
SympatricSummer 0,5935 0,12438 1,06262 2,53
Sympatric Winter −0,44264 −0,86248 −0,0228 −2,109
2 Seasons + Moose 7 −29 75,1 0,61 0,38
Estimate Lower limit Upper limit t value
(Intercept) 0,25888 −0,22414 0,7419 1,072
Allopatric Winter −0,08504 −0,42502 0,25494 −0,5
Sympatric Summer 0,51485 0,02347 1,00623 2,096
Sympatric Winter −0,53346 −0,98548 −0,08144 −2,36
Moose −0,7433 −2,18704 0,70044 −1,03
3 Null Model 3 −36,01 78,8 4,31 0,06
Moose 4 −35,22 79,5 5 0,04

Habitat selection was analyzed for wolf territories sympatric or allopatric with brown bears, taking into account seasonality (winter vs spring-summer seasons), moose density, and wolf territory id (random factor). We tested models with two types of wolf GPS locations (using only moving locations in one set of models, and all locations in another set), and two proxies of habitat availability, i.e., building models with MCP and kernel methods (see Methods for further details).