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TableĀ 4 Model selection results of the analysis of breeding territories (nĀ =Ā 56) vs. abandoned territories (nĀ =Ā 20)

From: Rodent-avoidance, topography and forest structure shape territory selection of a forest bird

Hypothesis

Variables in model

LL

K

AICc

Ī”AICc

Weight

Forest structure

(a) Ground variables

Number of tussocks, year, number of tussocks x year

āˆ’22.315

7

60.277

0

0.202

Ā 

Number of tussocks, number of bushes2

āˆ’22.774

7

61.194

0.917

0.128

Ā 

Number of tussocks, number of bushes2, cover of herb layer

āˆ’21.562

8

61.273

0.996

0.123

Ā 

Number of tussocks, year, number of tussocks x year, number of bushes

āˆ’21.798

8

61.745

1.468

0.097

Ā 

Number of tussocks, year, number of tussocks x year, cover of herb layer

āˆ’21.986

8

62.122

1.845

0.080

Ā 

ā€¦

Ā Ā Ā Ā Ā 
Ā 

Null

āˆ’31.868

4

72.299

12.022

0.000

(b) Tree variables

Number of trees2, tree dbh2, tree species diversity2

āˆ’17.092

10

57.569

0

0.091

Ā 

Number of trees, tree species diversity2

āˆ’21.187

7

58.020

0.452

0.072

Ā 

Number of trees, tree dbh2, tree species diversity2

āˆ’18.652

9

58.031

0.462

0.072

Ā 

Number of trees2

āˆ’22.514

6

58.246

0.677

0.065

Ā 

Number of trees, tree species diversity2, tree dbh

āˆ’20.060

8

58.269

0.701

0.064

Ā 

Number of trees, tree dbh2, tree species diversity2, sky visibility

āˆ’17.695

10

58.776

1.207

0.050

Ā 

Number of trees2, tree dbh2, tree species diversity2, sky visibility

āˆ’16.336

11

58.797

1.229

0.049

Ā 

Number of trees2, tree species diversity2

āˆ’20.364

8

58.877

1.308

0.047

Ā 

Number of trees2, tree dbh2, tree species diversity2, sky visibility2

āˆ’15.234

12

59.420

1.852

0.036

Ā 

ā€¦

Ā Ā Ā Ā Ā 
Ā 

Null

āˆ’31.868

4

72.299

14.730

0.000

(c) Tree species composition

Proportion conifers

āˆ’29.723

5

70.303

0

0.265

Ā 

Proportion conifers, proportion beech

āˆ’29.533

6

72.283

1.981

0.098

Ā 

Proportion conifers, proportion other deciduous trees

āˆ’29.539

6

72.295

1.992

0.098

Ā 

ā€¦

Ā Ā Ā Ā Ā 
Ā 

Null

āˆ’31.868

4

72.299

1.996

0.098

Rodent-avoidance

Null

āˆ’31.868

4

72.299

0

0.575

Ā 

Rodent numbers

āˆ’31.023

5

72.903

0.605

0.425

Disturbance

Distance to forest edge, distance to path2

āˆ’20.719

7

57.084

0

0.694

Ā 

Distance to forest edge2, distance to path2

āˆ’20.453

8

59.055

1.97

0.259

Ā 

ā€¦

Ā Ā Ā Ā Ā 
Ā 

Null

āˆ’31.868

4

72.299

15.214

0.000

Topography

Slope steepness2, elevation2, southness, eastness

āˆ’13.541

10

50.467

0

0.692

Ā 

ā€¦

Ā Ā Ā Ā Ā 
Ā 

Null

āˆ’31.868

4

72.299

21.832

0.000

Across hypothesesa

Slope steepness, distance to forest edge, number of trees

āˆ’14.985

7

45.457

0

0.734

Ā 

ā€¦

Ā Ā Ā Ā Ā 
Ā 

Null

āˆ’31.868

4

72.299

26.842

0.000

  1. For each hypothesis, the top-ranked model (Ī”AICcĀ =Ā 0), the models with Ī”AICcĀ <Ā 2 to the top-ranked model and the null model (referred to as ā€œnullā€) are shown. ā€œā€¦ā€ refers to additional models examined, but not listed in detail to avoid overlong table
  2. LL log-likelihood; K number of parameters in the model (including intercept), weight Akaike weight (chance of the model to be the best one, given the candidate models)
  3. The quadratic effect of a variable x, composed of a linear and a quadratic component (xĀ Ā±Ā x2), is denoted as x2
  4. Each model included x- and y-coordinates (and their interaction) of territories to account for spatial autocorrelation
  5. a Only linear terms of variables from best models per hypothesis and at most three habitat variables jointly used due to convergence problems with quadratic terms and more than three habitat variable per model