Data Summary
Number of birds in analysis: 31
Data Summary - Utilization Distributions
|
|
n
|
mean
|
sd
|
median
|
min
|
max
|
range
|
|
forest
|
123
|
0.20
|
0.28
|
0.04
|
0
|
1.00
|
1.00
|
|
shrub
|
123
|
0.35
|
0.32
|
0.27
|
0
|
0.98
|
0.98
|
|
grass
|
123
|
0.17
|
0.23
|
0.05
|
0
|
0.95
|
0.95
|
|
wetland
|
123
|
0.05
|
0.11
|
0.01
|
0
|
0.59
|
0.59
|
|
crops
|
123
|
0.17
|
0.31
|
0.00
|
0
|
0.99
|
0.99
|
|
bare
|
123
|
0.01
|
0.04
|
0.00
|
0
|
0.42
|
0.42
|
|
dev
|
123
|
0.02
|
0.04
|
0.00
|
0
|
0.33
|
0.33
|
|
water
|
123
|
0.03
|
0.06
|
0.00
|
0
|
0.35
|
0.35
|
Data Summary - Non-use Areas
|
|
n
|
mean
|
sd
|
median
|
min
|
max
|
range
|
|
forest
|
123
|
0.25
|
0.33
|
0.06
|
0
|
1.00
|
1.00
|
|
shrub
|
123
|
0.28
|
0.30
|
0.15
|
0
|
0.95
|
0.95
|
|
grass
|
123
|
0.17
|
0.26
|
0.04
|
0
|
0.98
|
0.98
|
|
wetland
|
123
|
0.04
|
0.11
|
0.00
|
0
|
0.68
|
0.68
|
|
crops
|
123
|
0.12
|
0.27
|
0.00
|
0
|
0.98
|
0.98
|
|
bare
|
123
|
0.02
|
0.10
|
0.00
|
0
|
0.80
|
0.80
|
|
dev
|
123
|
0.01
|
0.03
|
0.00
|
0
|
0.22
|
0.22
|
|
water
|
123
|
0.05
|
0.13
|
0.00
|
0
|
0.91
|
0.91
|
Data Summary - Correlations
|
|
forest
|
shrub
|
grass
|
wetland
|
crops
|
bare
|
dev
|
water
|
|
forest
|
1.00
|
-0.26
|
-0.42
|
-0.10
|
-0.31
|
0.02
|
-0.03
|
0.02
|
|
shrub
|
-0.26
|
1.00
|
-0.20
|
-0.07
|
-0.54
|
0.01
|
-0.29
|
-0.27
|
|
grass
|
-0.42
|
-0.20
|
1.00
|
-0.08
|
-0.10
|
-0.09
|
-0.08
|
0.07
|
|
wetland
|
-0.10
|
-0.07
|
-0.08
|
1.00
|
-0.20
|
0.02
|
-0.08
|
0.41
|
|
crops
|
-0.31
|
-0.54
|
-0.10
|
-0.20
|
1.00
|
-0.14
|
0.27
|
-0.15
|
|
bare
|
0.02
|
0.01
|
-0.09
|
0.02
|
-0.14
|
1.00
|
-0.03
|
0.14
|
|
dev
|
-0.03
|
-0.29
|
-0.08
|
-0.08
|
0.27
|
-0.03
|
1.00
|
0.09
|
|
water
|
0.02
|
-0.27
|
0.07
|
0.41
|
-0.15
|
0.14
|
0.09
|
1.00
|
Utilization Distribution Summary
Utilization Distribution Area (ha)
|
|
n
|
mean
|
sd
|
median
|
min
|
max
|
range
|
|
UD50
|
123
|
1018.67
|
2385.08
|
228.79
|
5.09
|
18416.77
|
18411.68
|
|
UD95
|
123
|
4461.04
|
9579.69
|
1218.46
|
22.43
|
73614.92
|
73592.49
|
Model Selection
Top Models
|
Model
|
K
|
AICc
|
delta
|
weight
|
|
~ lcrops + lshrub + lwetland
|
6
|
337.68
|
0.00
|
0.19848237
|
|
~ lcrops + lshrub + lw2 + lwetland
|
7
|
338.27
|
0.59
|
0.14790656
|
|
~ lcrops + ls2 + lshrub + lwetland
|
7
|
338.32
|
0.65
|
0.14375789
|
|
~ lcrops + ls2 + lshrub + lw2 + lwetland
|
8
|
338.69
|
1.01
|
0.11984127
|
|
~ lbare + lcrops + lshrub + lwetland
|
7
|
339.41
|
1.73
|
0.08360013
|
|
~ lcrops + lforest + lshrub + lwetland
|
7
|
339.54
|
1.86
|
0.07828110
|
|
~ lc2 + lcrops + lshrub + lwetland
|
7
|
339.57
|
1.89
|
0.07711787
|
|
~ lcrops + lforest + ls2 + lshrub + lwetland
|
8
|
339.59
|
1.91
|
0.07624458
|
|
~ lcrops + ldev + lshrub + lwetland
|
7
|
339.63
|
1.95
|
0.07476823
|
Coefficients
summary(a.top)
Family: binomial ( logit )
Formula: use ~ lcrops + lshrub + lwetland + (1 | ID) + (1 | bird)
Data: seowFull
AIC BIC logLik deviance df.resid
337.3 358.4 -162.7 325.3 240
Random effects:
Conditional model:
Groups Name Variance Std.Dev.
ID (Intercept) 5.371e-10 2.318e-05
bird (Intercept) 3.939e-12 1.985e-06
Number of obs: 246, groups: ID, 123; bird, 6
Conditional model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.61399 0.71958 3.633 0.00028 ***
lcrops 0.28031 0.09458 2.964 0.00304 **
lshrub 0.26168 0.10121 2.585 0.00973 **
lwetland 0.29387 0.12408 2.368 0.01786 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
confint(a.top)
2.5 % 97.5 % Estimate
cond.(Intercept) 1.20364664 4.0243409 2.613994e+00
cond.lcrops 0.09493575 0.4656829 2.803093e-01
cond.lshrub 0.06330762 0.4600595 2.616836e-01
cond.lwetland 0.05068303 0.5370624 2.938727e-01
ID.cond.Std.Dev.(Intercept) 0.00000000 Inf 2.317559e-05
bird.cond.Std.Dev.(Intercept) 0.00000000 Inf 1.984749e-06
Random Forest Prediction
Call: randomForest(formula = use ~ forest + shrub + grass + wetland + crops + bare + dev + 1, data = seowFull, ntree = 1000, importance = TRUE, localImp = TRUE) Type of random forest: classification Number of trees: 1000 No. of variables tried at each split: 2
OOB estimate of error rate: 47.97%
Confusion matrix: 0 1 class.error 0 63 60 0.4878049 1 58 65 0.4715447 OGR data source with driver: ESRI Shapefile Source: “C:Manuscripts”, layer: “NA_Predict” with 141357 features It has 13 fields Integer64 fields read as strings: NA_Predict NA_Predi_9 
