bimac: Anolis bimaculatus lizard size data.

Description Usage Format Details Author(s) Source References Examples

Description

This is the Anolis bimaculatus dataset used in Butler & King (2004). It is used to test a hypothesis of character displacement using an interspecific dataset of body sizes and current data on sympatry/allopatry. The data frame consists of the following columns: species which are species names, size which is the phenotypic data, and the variables ancestor and time which specify the topology of the phylogeny and the location of the nodes in time, respectively. The columns OU.1, OU.3, OU.4, and OU.LP specify four hypothetical arrangements of selective regimes. Explanations of the data are given below.

Usage

1

Format

A data frame with 45 observations on the following 8 variables.

node

Labels for the nodes.

species

Species names for extant species.

size

Body size (head length in mm) of extant species.

ancestor

Ancestral node.

time

Time of node.

OU.1

a factor with levels ns

OU.3

a factor with levels small medium large

OU.4

a factor with levels small medium large anc

OU.LP

a factor with levels small medium large

Details

Body size.

We use the phenotypic data and phylogeny of Losos (1990), which employed the head lengths (of males) as a proxy for body size. In this group of lizards, head length correlates very strongly with snout-to-vent length and the cube root of mass, which are standard measures of body size. The data are head lengths in mm, note that we use the log of this value in analyses.

Tree topology

The tree topology is encoded via two vectors: ancestor and time. Each node of the phylogenetic tree has a corresponding row in the data frame, numbered from 1 to 45. The columns ancestor and time specify the phylogeny. The ancestor variable specifies the topology: it is a list indicating the ancestor of each node. The root node has ancestor 0. The variable time specifies the temporal location of each node, with the root node being at time 0.

Specifications of selective regimes.

(Columns OU.1, OU.3, OU.4, OU.LP). These columns are factors, the levels of which correspond to the “paintings” of the respective adaptive regime hypotheses onto the phylogeny. Each selective regime is named (small, medium, large, etc.). Put the corresponding name on each branch segment to indicate which selective regime it belongs to. Each column corresponds to a different painting of the selective regimes, and thus to a different hypothesis. In this example, there are 3 alternative models (see Butler & King 2004): OU.4 is 4-regime model, OU.3 is 3-regime model (all ancestors are medium), OU.LP is linear parsimony model.

Author(s)

Marguerite A. Butler <mbutler at hawaii dot edu> and Aaron A. King <kingaa at umich dot edu>

Source

Butler, M.A. and A.A. King. 2004. Phylogenetic comparative analysis: a modeling approach for adaptive evolution. American Naturalist 164:683-695.

References

Lazell, J. D. 1972. The anoles (Sauria: Iguanidae) of the Lesser Antilles. Bull. Mus. Comp. Zool., 143:1-115.

Losos, J. B. 1990. A phylogenetic analysis of character displacement in Caribbean Anolis lizards. Evolution, 44:558-569.

Examples

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data(bimac)
tree <- with(bimac,ouchtree(node,ancestor,time/max(time),species))
plot(tree,node.names=TRUE)
print(h1 <- brown(log(bimac['size']),tree))
plot(h1)
print(h2 <- hansen(log(bimac['size']),tree,bimac['OU.1'],sqrt.alpha=1,sigma=1))
plot(h2)
print(h3 <- hansen(log(bimac['size']),tree,bimac['OU.3'],sqrt.alpha=1,sigma=1))
plot(h3)
print(h4 <- hansen(log(bimac['size']),tree,bimac['OU.4'],sqrt.alpha=1,sigma=1))
plot(h4)
h5 <- hansen(log(bimac['size']),tree,bimac['OU.LP'],sqrt.alpha=1,sigma=1,reltol=1e-5)
print(h5 <- update(h5,method='subplex',reltol=1e-11,parscale=c(0.1,0.1),hessian=TRUE))
simdat <- simulate(h5,nsim=10)
hsim <- update(h5,data=simdat[[1]])
print(summary(hsim))
bsim <- update(h1,data=simdat[[1]])
print(summary(bsim))

Example output

Loading required package: subplex

call:
brown(data = log(bimac["size"]), tree = tree)
   nodes ancestors     times labels     size
1      1      <NA> 0.0000000   <NA>       NA
2      2         1 0.3157895   <NA>       NA
3      3         2 0.8421053   <NA>       NA
4      4         3 0.8947368   <NA>       NA
5      5         4 0.9473684   <NA>       NA
6      6         3 0.9473684   <NA>       NA
7      7         1 0.2105263   <NA>       NA
8      8         7 0.3421053   <NA>       NA
9      9         8 0.4736842   <NA>       NA
10    10         9 0.6052632   <NA>       NA
11    11        10 0.7368421   <NA>       NA
12    12         9 0.7368421   <NA>       NA
13    13         8 0.5789474   <NA>       NA
14    14        13 0.6842105   <NA>       NA
15    15        14 0.8947368   <NA>       NA
16    16        15 0.9473684   <NA>       NA
17    17         7 0.7368421   <NA>       NA
18    18        17 0.7894737   <NA>       NA
19    19        18 0.8947368   <NA>       NA
20    20        19 0.9473684   <NA>       NA
21    21        20 0.9736842   <NA>       NA
22    22        19 0.9473684   <NA>       NA
23    23         2 1.0000000     po 2.602690
24    24         4 1.0000000     se 2.660260
25    25         5 1.0000000     sc 2.660260
26    26         5 1.0000000     sn 2.653242
27    27         6 1.0000000     wb 2.674149
28    28         6 1.0000000     wa 2.701361
29    29        10 1.0000000     be 3.161247
30    30        11 1.0000000     bn 3.299534
31    31        11 1.0000000     bc 3.328627
32    32        12 1.0000000     lb 3.353407
33    33        12 1.0000000     la 3.360375
34    34        13 1.0000000     nu 3.049273
35    35        14 1.0000000     sa 2.906901
36    36        15 1.0000000     gb 2.980619
37    37        16 1.0000000     ga 2.933857
38    38        16 1.0000000     gm 2.975530
39    39        17 1.0000000     oc 3.104587
40    40        18 1.0000000     fe 3.346389
41    41        20 1.0000000     li 2.928524
42    42        21 1.0000000     mg 2.939162
43    43        21 1.0000000     md 2.990720
44    44        22 1.0000000     t1 3.058707
45    45        22 1.0000000     t2 3.068053

sigma squared:
           [,1]
[1,] 0.04311003

theta:
NULL
   loglik  deviance       aic     aic.c       sic       dof 
 17.33129 -34.66257 -30.66257 -30.06257 -28.39158   2.00000 

call:
hansen(data = log(bimac["size"]), tree = tree, regimes = bimac["OU.1"], 
    sqrt.alpha = 1, sigma = 1)
   nodes ancestors     times labels OU.1     size
1      1      <NA> 0.0000000   <NA>   ns       NA
2      2         1 0.3157895   <NA>   ns       NA
3      3         2 0.8421053   <NA>   ns       NA
4      4         3 0.8947368   <NA>   ns       NA
5      5         4 0.9473684   <NA>   ns       NA
6      6         3 0.9473684   <NA>   ns       NA
7      7         1 0.2105263   <NA>   ns       NA
8      8         7 0.3421053   <NA>   ns       NA
9      9         8 0.4736842   <NA>   ns       NA
10    10         9 0.6052632   <NA>   ns       NA
11    11        10 0.7368421   <NA>   ns       NA
12    12         9 0.7368421   <NA>   ns       NA
13    13         8 0.5789474   <NA>   ns       NA
14    14        13 0.6842105   <NA>   ns       NA
15    15        14 0.8947368   <NA>   ns       NA
16    16        15 0.9473684   <NA>   ns       NA
17    17         7 0.7368421   <NA>   ns       NA
18    18        17 0.7894737   <NA>   ns       NA
19    19        18 0.8947368   <NA>   ns       NA
20    20        19 0.9473684   <NA>   ns       NA
21    21        20 0.9736842   <NA>   ns       NA
22    22        19 0.9473684   <NA>   ns       NA
23    23         2 1.0000000     po   ns 2.602690
24    24         4 1.0000000     se   ns 2.660260
25    25         5 1.0000000     sc   ns 2.660260
26    26         5 1.0000000     sn   ns 2.653242
27    27         6 1.0000000     wb   ns 2.674149
28    28         6 1.0000000     wa   ns 2.701361
29    29        10 1.0000000     be   ns 3.161247
30    30        11 1.0000000     bn   ns 3.299534
31    31        11 1.0000000     bc   ns 3.328627
32    32        12 1.0000000     lb   ns 3.353407
33    33        12 1.0000000     la   ns 3.360375
34    34        13 1.0000000     nu   ns 3.049273
35    35        14 1.0000000     sa   ns 2.906901
36    36        15 1.0000000     gb   ns 2.980619
37    37        16 1.0000000     ga   ns 2.933857
38    38        16 1.0000000     gm   ns 2.975530
39    39        17 1.0000000     oc   ns 3.104587
40    40        18 1.0000000     fe   ns 3.346389
41    41        20 1.0000000     li   ns 2.928524
42    42        21 1.0000000     mg   ns 2.939162
43    43        21 1.0000000     md   ns 2.990720
44    44        22 1.0000000     t1   ns 3.058707
45    45        22 1.0000000     t2   ns 3.068053

alpha:
          [,1]
[1,] 0.1921554

sigma squared:
           [,1]
[1,] 0.04836469

theta:
$size
      ns 
2.953805 

   loglik  deviance       aic     aic.c       sic       dof 
 15.69682 -31.39364 -25.39364 -24.13048 -21.98715   3.00000 

call:
hansen(data = log(bimac["size"]), tree = tree, regimes = bimac["OU.3"], 
    sqrt.alpha = 1, sigma = 1)
   nodes ancestors     times labels   OU.3     size
1      1      <NA> 0.0000000   <NA> medium       NA
2      2         1 0.3157895   <NA> medium       NA
3      3         2 0.8421053   <NA> medium       NA
4      4         3 0.8947368   <NA> medium       NA
5      5         4 0.9473684   <NA> medium       NA
6      6         3 0.9473684   <NA> medium       NA
7      7         1 0.2105263   <NA> medium       NA
8      8         7 0.3421053   <NA> medium       NA
9      9         8 0.4736842   <NA> medium       NA
10    10         9 0.6052632   <NA> medium       NA
11    11        10 0.7368421   <NA> medium       NA
12    12         9 0.7368421   <NA> medium       NA
13    13         8 0.5789474   <NA> medium       NA
14    14        13 0.6842105   <NA> medium       NA
15    15        14 0.8947368   <NA> medium       NA
16    16        15 0.9473684   <NA> medium       NA
17    17         7 0.7368421   <NA> medium       NA
18    18        17 0.7894737   <NA> medium       NA
19    19        18 0.8947368   <NA> medium       NA
20    20        19 0.9473684   <NA> medium       NA
21    21        20 0.9736842   <NA> medium       NA
22    22        19 0.9473684   <NA> medium       NA
23    23         2 1.0000000     po  small 2.602690
24    24         4 1.0000000     se  small 2.660260
25    25         5 1.0000000     sc  small 2.660260
26    26         5 1.0000000     sn  small 2.653242
27    27         6 1.0000000     wb  small 2.674149
28    28         6 1.0000000     wa  small 2.701361
29    29        10 1.0000000     be  large 3.161247
30    30        11 1.0000000     bn  large 3.299534
31    31        11 1.0000000     bc  large 3.328627
32    32        12 1.0000000     lb  large 3.353407
33    33        12 1.0000000     la  large 3.360375
34    34        13 1.0000000     nu medium 3.049273
35    35        14 1.0000000     sa medium 2.906901
36    36        15 1.0000000     gb medium 2.980619
37    37        16 1.0000000     ga medium 2.933857
38    38        16 1.0000000     gm  large 2.975530
39    39        17 1.0000000     oc medium 3.104587
40    40        18 1.0000000     fe medium 3.346389
41    41        20 1.0000000     li medium 2.928524
42    42        21 1.0000000     mg medium 2.939162
43    43        21 1.0000000     md medium 2.990720
44    44        22 1.0000000     t1 medium 3.058707
45    45        22 1.0000000     t2 medium 3.068053

alpha:
         [,1]
[1,] 1.125965

sigma squared:
           [,1]
[1,] 0.05170735

theta:
$size
   large   medium    small 
3.899393 2.972447 2.294089 

   loglik  deviance       aic     aic.c       sic       dof 
 19.57786 -39.15573 -29.15573 -25.62631 -23.47826   5.00000 

call:
hansen(data = log(bimac["size"]), tree = tree, regimes = bimac["OU.4"], 
    sqrt.alpha = 1, sigma = 1)
   nodes ancestors     times labels   OU.4     size
1      1      <NA> 0.0000000   <NA>    anc       NA
2      2         1 0.3157895   <NA>    anc       NA
3      3         2 0.8421053   <NA>    anc       NA
4      4         3 0.8947368   <NA>    anc       NA
5      5         4 0.9473684   <NA>    anc       NA
6      6         3 0.9473684   <NA>    anc       NA
7      7         1 0.2105263   <NA>    anc       NA
8      8         7 0.3421053   <NA>    anc       NA
9      9         8 0.4736842   <NA>    anc       NA
10    10         9 0.6052632   <NA>    anc       NA
11    11        10 0.7368421   <NA>    anc       NA
12    12         9 0.7368421   <NA>    anc       NA
13    13         8 0.5789474   <NA>    anc       NA
14    14        13 0.6842105   <NA>    anc       NA
15    15        14 0.8947368   <NA>    anc       NA
16    16        15 0.9473684   <NA>    anc       NA
17    17         7 0.7368421   <NA>    anc       NA
18    18        17 0.7894737   <NA>    anc       NA
19    19        18 0.8947368   <NA>    anc       NA
20    20        19 0.9473684   <NA>    anc       NA
21    21        20 0.9736842   <NA>    anc       NA
22    22        19 0.9473684   <NA>    anc       NA
23    23         2 1.0000000     po  small 2.602690
24    24         4 1.0000000     se  small 2.660260
25    25         5 1.0000000     sc  small 2.660260
26    26         5 1.0000000     sn  small 2.653242
27    27         6 1.0000000     wb  small 2.674149
28    28         6 1.0000000     wa  small 2.701361
29    29        10 1.0000000     be  large 3.161247
30    30        11 1.0000000     bn  large 3.299534
31    31        11 1.0000000     bc  large 3.328627
32    32        12 1.0000000     lb  large 3.353407
33    33        12 1.0000000     la  large 3.360375
34    34        13 1.0000000     nu medium 3.049273
35    35        14 1.0000000     sa medium 2.906901
36    36        15 1.0000000     gb medium 2.980619
37    37        16 1.0000000     ga medium 2.933857
38    38        16 1.0000000     gm  large 2.975530
39    39        17 1.0000000     oc medium 3.104587
40    40        18 1.0000000     fe medium 3.346389
41    41        20 1.0000000     li medium 2.928524
42    42        21 1.0000000     mg medium 2.939162
43    43        21 1.0000000     md medium 2.990720
44    44        22 1.0000000     t1 medium 3.058707
45    45        22 1.0000000     t2 medium 3.068053

alpha:
         [,1]
[1,] 14.67003

sigma squared:
          [,1]
[1,] 0.2253265

theta:
$size
     anc    large   medium    small 
2.827657 3.297563 3.105650 2.582588 

   loglik  deviance       aic     aic.c       sic       dof 
 23.61159 -47.22319 -35.22319 -29.97319 -28.41022   6.00000 

call:
hansen(data = data, tree = object, regimes = regimes, sqrt.alpha = sqrt.alpha, 
    sigma = sigma, method = "subplex", hessian = TRUE, reltol = 1e-11, 
    parscale = ..3)
   nodes ancestors     times labels  OU.LP     size
1      1      <NA> 0.0000000   <NA> medium       NA
2      2         1 0.3157895   <NA> medium       NA
3      3         2 0.8421053   <NA>  small       NA
4      4         3 0.8947368   <NA>  small       NA
5      5         4 0.9473684   <NA>  small       NA
6      6         3 0.9473684   <NA>  small       NA
7      7         1 0.2105263   <NA> medium       NA
8      8         7 0.3421053   <NA> medium       NA
9      9         8 0.4736842   <NA>  large       NA
10    10         9 0.6052632   <NA>  large       NA
11    11        10 0.7368421   <NA>  large       NA
12    12         9 0.7368421   <NA>  large       NA
13    13         8 0.5789474   <NA> medium       NA
14    14        13 0.6842105   <NA> medium       NA
15    15        14 0.8947368   <NA> medium       NA
16    16        15 0.9473684   <NA> medium       NA
17    17         7 0.7368421   <NA> medium       NA
18    18        17 0.7894737   <NA> medium       NA
19    19        18 0.8947368   <NA> medium       NA
20    20        19 0.9473684   <NA> medium       NA
21    21        20 0.9736842   <NA> medium       NA
22    22        19 0.9473684   <NA> medium       NA
23    23         2 1.0000000     po  small 2.602690
24    24         4 1.0000000     se  small 2.660260
25    25         5 1.0000000     sc  small 2.660260
26    26         5 1.0000000     sn  small 2.653242
27    27         6 1.0000000     wb  small 2.674149
28    28         6 1.0000000     wa  small 2.701361
29    29        10 1.0000000     be  large 3.161247
30    30        11 1.0000000     bn  large 3.299534
31    31        11 1.0000000     bc  large 3.328627
32    32        12 1.0000000     lb  large 3.353407
33    33        12 1.0000000     la  large 3.360375
34    34        13 1.0000000     nu medium 3.049273
35    35        14 1.0000000     sa medium 2.906901
36    36        15 1.0000000     gb medium 2.980619
37    37        16 1.0000000     ga medium 2.933857
38    38        16 1.0000000     gm  large 2.975530
39    39        17 1.0000000     oc medium 3.104587
40    40        18 1.0000000     fe medium 3.346389
41    41        20 1.0000000     li medium 2.928524
42    42        21 1.0000000     mg medium 2.939162
43    43        21 1.0000000     md medium 2.990720
44    44        22 1.0000000     t1 medium 3.058707
45    45        22 1.0000000     t2 medium 3.068053

 'optim'  diagnostic message:  success! tolerance satisfied
alpha:
         [,1]
[1,] 2.610141

sigma squared:
           [,1]
[1,] 0.05054862

theta:
$size
   large   medium    small 
3.355242 3.040732 2.565031 

   loglik  deviance       aic     aic.c       sic       dof 
 24.81823 -49.63646 -39.63646 -36.10705 -33.95899   5.00000 
$call
hansen(data = data, tree = object, regimes = regimes, sqrt.alpha = sqrt.alpha, 
    sigma = sigma)

$conv.code
[1] 0

$optimizer.message
NULL

$alpha
         [,1]
[1,] 6.437829

$sigma.squared
           [,1]
[1,] 0.04394736

$optima
$optima$size
   large   medium    small 
3.265152 3.027534 2.556598 


$loglik
[1] 34.00384

$deviance
[1] -68.00769

$aic
[1] -58.00769

$aic.c
[1] -54.47828

$sic
[1] -52.33022

$dof
[1] 5

$call
brown(data = data, tree = object)

$sigma.squared
          [,1]
[1,] 0.0376242

$theta
$theta$size
[1] 2.90548


$loglik
[1] 18.89653

$deviance
[1] -37.79306

$aic
[1] -33.79306

$aic.c
[1] -33.19306

$sic
[1] -31.52207

$dof
[1] 2

ouch documentation built on May 2, 2019, 6:53 p.m.