raupcrick: Raup-Crick Dissimilarity with Unequal Sampling Densities of...
In vegan: Community Ecology Package
Description
Usage
Arguments
Details
Value
Note
Author(s)
References
See Also
Examples
Description
Function finds the Raup-Crick dissimilarity which is a
probability of number of co-occurring species with species
occurrence probabilities proportional to species frequencies.
Usage
1
Arguments
comm
Community data which will be treated as presence/absence data.
null
Null model used as the method in
oecosimu.
nsimul
Number of null communities for assessing the
dissimilarity index.
chase
Use the Chase et al. (2011) method of tie handling (not
recommended except for comparing the results against the Chase
script).
...
Other parameters passed to oecosimu.
Details
Raup-Crick index is the probability that compared sampling
units have non-identical species composition. This probability can
be regarded as a dissimilarity, although it is not metric: identical
sampling units can have dissimilarity slightly above 0, the
dissimilarity can be nearly zero over a range of shared species, and
sampling units with no shared species can have dissimilarity
slightly below 1. Moreover, communities sharing rare species
appear as more similar (lower probability of finding rare species
together), than communities sharing the same number of common
species.
The function will always treat the data as binary (presence/
absence).
The probability is assessed using simulation with
oecosimu where the test statistic is the observed
number of shared species between sampling units evaluated against a
community null model (see Examples). The default null model is
"r1" where the probability of selecting species is
proportional to the species frequencies.
The vegdist function implements a variant of the
Raup-Crick index with equal sampling probabilities for species using
exact analytic equations without simulation. This corresponds to
null model "r0" which also can be used with the
current function. All other null model methods of
oecosimu can be used with the current function, but
they are new unpublished methods.
Value
The function returns an object inheriting from
dist which can be interpreted as a dissimilarity
matrix.
Note
The test statistic is the number of shared species, and this is
typically tied with a large number of simulation results. The tied
values are handled differently in the current function and in the
function published with Chase et al. (2011). In vegan, the
index is the number of simulated values that are smaller or
equal than the observed value, but smaller than observed value is
used by Chase et al. (2011) with option split = FALSE in
their script; this can be achieved with chase = TRUE in
vegan. Chase et al. (2011) script with split = TRUE
uses half of tied simulation values to calculate a distance measure,
and that choice cannot be directly reproduced in vegan (it is the
average of vegan raupcrick results with
chase = TRUE and chase = FALSE).
Author(s)
The function was developed after Brian Inouye contacted us and
informed us about the method in Chase et al. (2011), and the
function takes its idea from the code that was published with their
paper. The current function was written by Jari Oksanen.
References
Chase, J.M., Kraft, N.J.B., Smith, K.G., Vellend, M. and Inouye,
B.D. (2011). Using null models to disentangle variation in community
dissimilarity from variation in alpha-diversity.
Ecosphere 2:art24 [doi:10.1890/ES10-00117.1]
See Also
The function is based on oecosimu. Function
vegdist with method = "raup" implements a related
index but with equal sampling densities of species, and
designdist demonstrates its calculation.
Examples
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
## data set with variable species richness
data(sipoo)
## default raupcrick
dr1 <- raupcrick(sipoo)
## use null model "r0" of oecosimu
dr0 <- raupcrick(sipoo, null = "r0")
## vegdist(..., method = "raup") corresponds to 'null = "r0"'
d <- vegdist(sipoo, "raup")
op <- par(mfrow=c(2,1), mar=c(4,4,1,1)+.1)
plot(dr1 ~ d, xlab = "Raup-Crick with Null R1", ylab="vegdist")
plot(dr0 ~ d, xlab = "Raup-Crick with Null R0", ylab="vegdist")
par(op)
## The calculation is essentially as in the following oecosimu() call,
## except that designdist() is replaced with faster code
## Not run:
oecosimu(sipoo, function(x) designdist(x, "J", "binary"), method = "r1")
## End(Not run)
Example output
Loading required package: permute
Loading required package: lattice
This is vegan 2.4-3
oecosimu object
Call: oecosimu(comm = sipoo, nestfun = function(x) designdist(x, "J",
"binary"), method = "r1")
nullmodel method 'r1' with 99 simulations
alternative hypothesis: statistic is less or greater than simulated values
Svartholm L.Hogholm Ledholmen S.Hogholm Torvedsh SkataLed Flakaskar
L.Hogholm 2
Ledholmen 3 3
S.Hogholm 1 1 1
Torvedsh 3 3 4 2
SkataLed 1 3 2 2 4
Flakaskar 1 1 1 2 3 3
S.farholm 3 3 4 2 4 4 2
Farholmn 1 2 1 2 2 4 2
Asplandet 1 2 1 2 3 4 3
Granlndet 2 3 3 2 5 6 3
Hanskholm 3 3 4 2 6 4 3
Ragskar 3 3 4 2 6 5 3
Trutland 3 3 5 1 5 3 2
Kaivokari 2 3 3 2 5 6 3
Mustahevo 2 2 3 2 5 5 3
Kaunissri 3 4 5 2 6 6 3
Onas 3 4 4 2 6 6 4
S.farholm Farholmn Asplandet Granlndet Hanskholm Ragskar Trutland
L.Hogholm
Ledholmen
S.Hogholm
Torvedsh
SkataLed
Flakaskar
S.farholm
Farholmn 5
Asplandet 4 4
Granlndet 7 5 6
Hanskholm 6 4 4 6
Ragskar 6 5 4 7 8
Trutland 6 2 4 6 7 7
Kaivokari 6 6 5 8 7 10 7
Mustahevo 5 5 4 8 7 11 7
Kaunissri 9 6 6 10 10 11 11
Onas 7 6 5 9 9 12 9
Kaivokari Mustahevo Kaunissri
L.Hogholm
Ledholmen
S.Hogholm
Torvedsh
SkataLed
Flakaskar
S.farholm
Farholmn
Asplandet
Granlndet
Hanskholm
Ragskar
Trutland
Kaivokari
Mustahevo 11
Kaunissri 13 15
Onas 15 15 22
statistic SES mean 2.5% 50% 97.5% Pr(sim.)
[1,] 2 1.817643 0.60606 0.00000 0.00000 2.00 0.27
[2,] 3 3.515120 0.59596 0.00000 0.00000 2.00 0.03 *
[3,] 1 1.667133 0.26263 0.00000 0.00000 1.00 0.53
[4,] 3 2.583701 0.90909 0.00000 1.00000 3.00 0.09 .
[5,] 1 0.168818 0.86869 0.00000 1.00000 3.00 1.00
[6,] 1 0.494518 0.68687 0.00000 1.00000 2.00 1.00
[7,] 3 1.804440 1.39394 0.00000 1.00000 3.00 0.19
[8,] 1 0.102129 0.91919 0.00000 1.00000 3.00 1.00
[9,] 1 -0.200991 1.19192 0.00000 1.00000 3.00 1.00
[10,] 2 0.104829 1.89899 0.00000 2.00000 3.00 1.00
[11,] 3 1.630834 1.43434 0.00000 1.00000 3.00 0.29
[12,] 3 1.416663 1.69697 0.00000 2.00000 3.00 0.35
[13,] 3 1.313352 1.85859 0.00000 2.00000 3.00 0.53
[14,] 2 -0.255528 2.27273 0.00000 2.00000 4.00 1.00
[15,] 2 -0.360041 2.33333 1.00000 2.00000 4.00 1.00
[16,] 3 -0.392787 3.29293 2.00000 3.00000 4.00 1.00
[17,] 3 -0.752101 3.48485 2.00000 4.00000 4.00 0.89
[18,] 3 3.405735 0.66667 0.00000 1.00000 2.00 0.03 *
[19,] 1 1.322676 0.32323 0.00000 0.00000 1.00 0.61
[20,] 3 2.934576 0.96970 0.00000 1.00000 2.00 0.03 *
[21,] 3 2.997374 0.85859 0.00000 1.00000 2.00 0.03 *
[22,] 1 0.501892 0.64646 0.00000 1.00000 2.00 1.00
[23,] 3 1.773160 1.38384 0.00000 1.00000 3.00 0.21
[24,] 2 1.412803 0.91919 0.00000 1.00000 2.55 0.39
[25,] 2 0.946661 1.15152 0.00000 1.00000 3.00 0.65
[26,] 3 1.171234 1.82828 0.00000 2.00000 4.00 0.55
[27,] 3 1.629512 1.48485 0.00000 2.00000 3.00 0.25
[28,] 3 1.287925 1.74747 0.00000 2.00000 4.00 0.39
[29,] 3 1.038641 2.11111 1.00000 2.00000 4.00 0.61
[30,] 3 0.995040 2.01010 0.00000 2.00000 4.00 0.67
[31,] 2 -0.241308 2.22222 1.00000 2.00000 4.00 1.00
[32,] 4 1.100855 3.23232 2.00000 3.00000 4.00 0.77
[33,] 4 0.803205 3.49495 2.00000 4.00000 4.00 1.00
[34,] 1 0.918705 0.45455 0.00000 0.00000 2.00 0.81
[35,] 4 3.005561 1.30303 0.00000 1.00000 3.00 0.01 **
[36,] 2 0.828900 1.31313 0.00000 1.00000 3.00 0.85
[37,] 1 0.199147 0.84848 0.00000 1.00000 2.00 1.00
[38,] 4 2.385983 1.70707 0.00000 2.00000 3.55 0.07 .
[39,] 1 -0.267344 1.20202 0.00000 1.00000 2.00 1.00
[40,] 1 -0.477960 1.47475 0.00000 1.00000 3.55 1.00
[41,] 3 0.577918 2.35354 0.00000 3.00000 4.00 1.00
[42,] 4 2.119678 1.85859 0.00000 2.00000 4.00 0.09 .
[43,] 4 1.908853 2.10101 0.00000 2.00000 4.00 0.11
[44,] 5 2.305181 2.44444 0.45000 3.00000 4.00 0.03 *
[45,] 3 0.200440 2.76768 0.45000 3.00000 5.00 1.00
[46,] 3 0.214574 2.77778 1.00000 3.00000 4.55 1.00
[47,] 5 1.010835 4.16162 2.00000 4.00000 5.00 0.79
[48,] 4 -0.577281 4.39394 3.00000 4.00000 5.00 1.00
[49,] 2 2.527566 0.49495 0.00000 0.00000 2.00 0.11
[50,] 2 2.645547 0.43434 0.00000 0.00000 2.00 0.11
[51,] 2 3.731935 0.29293 0.00000 0.00000 1.00 0.01 **
[52,] 2 1.842759 0.77778 0.00000 1.00000 2.00 0.27
[53,] 2 2.774377 0.41414 0.00000 0.00000 2.00 0.09 .
[54,] 2 1.989873 0.66667 0.00000 1.00000 2.00 0.23
[55,] 2 1.687789 0.78788 0.00000 1.00000 2.00 0.35
[56,] 2 1.839639 0.78788 0.00000 1.00000 2.00 0.27
[57,] 2 1.893740 0.75758 0.00000 1.00000 2.00 0.25
[58,] 1 -0.092981 1.06061 0.00000 1.00000 2.00 1.00
[59,] 2 1.361407 1.11111 0.00000 1.00000 2.00 0.55
[60,] 2 1.069329 1.28283 0.00000 1.00000 2.00 0.81
[61,] 2 0.624806 1.71717 1.00000 2.00000 2.00 1.00
[62,] 2 0.332411 1.86869 1.00000 2.00000 2.00 1.00
[63,] 4 3.258578 1.24242 0.00000 1.00000 3.00 0.01 **
[64,] 3 3.509236 0.76768 0.00000 1.00000 2.00 0.01 **
[65,] 4 1.905159 2.00000 0.00000 2.00000 4.00 0.17
[66,] 2 0.707557 1.32323 0.00000 1.00000 3.00 0.83
[67,] 3 1.235700 1.74747 0.00000 2.00000 3.55 0.49
[68,] 5 1.775376 2.69697 0.00000 3.00000 5.00 0.19
[69,] 6 3.338042 2.24242 0.00000 2.00000 4.00 0.01 **
[70,] 6 3.010334 2.40404 0.00000 2.00000 5.00 0.01 **
[71,] 5 1.982252 2.86869 1.00000 3.00000 5.00 0.11
[72,] 5 1.812934 2.96970 1.00000 3.00000 5.00 0.19
[73,] 5 1.469862 3.33333 1.00000 3.00000 5.00 0.33
[74,] 6 1.248159 4.74747 3.00000 5.00000 6.00 0.47
[75,] 6 0.924673 5.18182 3.00000 5.00000 6.00 0.85
[76,] 3 2.091606 1.03030 0.00000 1.00000 3.00 0.13
[77,] 4 1.775855 2.18182 0.00000 2.00000 4.00 0.21
[78,] 4 2.770045 1.38384 0.00000 1.00000 3.00 0.01 **
[79,] 4 2.145736 1.77778 0.00000 2.00000 4.00 0.11
[80,] 6 3.020112 2.70707 1.00000 3.00000 4.55 0.01 **
[81,] 4 1.925850 2.25253 1.00000 2.00000 4.00 0.21
[82,] 5 2.344439 2.44444 1.00000 2.00000 5.00 0.09 .
[83,] 3 -0.044063 3.05051 1.00000 3.00000 5.00 1.00
[84,] 6 2.247203 3.33333 1.00000 3.00000 6.00 0.09 .
[85,] 5 1.485939 3.46465 1.45000 4.00000 5.00 0.31
[86,] 6 1.095491 4.89899 3.00000 5.00000 6.00 0.65
[87,] 6 0.926178 5.22222 3.00000 5.00000 6.00 0.89
[88,] 2 0.740554 1.39394 0.00000 1.00000 3.00 0.89
[89,] 2 1.440800 0.90909 0.00000 1.00000 2.00 0.45
[90,] 3 2.162006 1.17172 0.00000 1.00000 3.00 0.13
[91,] 3 1.448291 1.65657 0.00000 2.00000 3.00 0.35
[92,] 3 1.787215 1.42424 0.00000 1.00000 3.00 0.25
[93,] 3 1.371511 1.78788 0.00000 2.00000 3.00 0.47
[94,] 2 0.124722 1.88889 0.00000 2.00000 3.55 1.00
[95,] 3 0.903659 2.10101 0.00000 2.00000 4.00 0.75
[96,] 3 0.910055 2.13131 0.00000 2.00000 4.00 0.63
[97,] 3 -0.265521 3.21212 1.45000 3.00000 4.00 1.00
[98,] 4 0.762539 3.48485 2.00000 4.00000 4.00 1.00
[99,] 5 2.523460 2.19192 0.00000 2.00000 4.00 0.03 *
[100,] 4 1.104999 2.71717 1.00000 3.00000 5.00 0.47
[101,] 7 1.982558 4.28283 2.00000 4.00000 7.00 0.15
[102,] 6 1.848986 3.42424 1.00000 3.00000 6.00 0.17
[103,] 6 1.708111 3.95960 2.00000 4.00000 6.55 0.19
[104,] 6 1.250563 4.39394 2.00000 4.00000 7.00 0.45
[105,] 6 0.788095 4.98990 3.00000 5.00000 7.00 0.65
[106,] 5 -0.432260 5.58586 3.00000 6.00000 8.00 0.95
[107,] 9 0.957030 7.71717 5.00000 8.00000 10.00 0.49
[108,] 7 -1.793108 8.64646 7.00000 9.00000 10.00 0.21
[109,] 4 2.272249 1.73737 0.00000 2.00000 4.00 0.13
[110,] 5 1.903690 2.81818 1.00000 3.00000 5.00 0.11
[111,] 4 1.755976 2.16162 0.00000 2.00000 4.00 0.19
[112,] 5 2.102507 2.67677 1.00000 3.00000 4.55 0.07 .
[113,] 2 -0.668663 2.81818 0.45000 3.00000 5.00 0.79
[114,] 6 2.493512 3.17172 1.00000 3.00000 5.00 0.05 *
[115,] 5 1.353937 3.48485 2.00000 4.00000 5.55 0.35
[116,] 6 1.285942 4.96970 3.00000 5.00000 6.00 0.53
[117,] 6 0.982807 5.25253 4.00000 5.00000 6.00 0.85
[118,] 6 1.852104 3.48485 1.00000 3.00000 6.00 0.15
[119,] 4 0.991012 2.72727 0.45000 3.00000 5.00 0.59
[120,] 4 0.703399 3.08081 1.00000 3.00000 5.00 0.81
[121,] 4 0.320755 3.52525 1.00000 3.00000 6.00 0.97
[122,] 5 0.704324 3.95960 1.00000 4.00000 6.00 0.73
[123,] 4 -0.057234 4.08081 1.45000 4.00000 7.00 1.00
[124,] 6 -0.311300 6.32323 4.45000 6.00000 8.00 1.00
[125,] 5 -2.200414 6.89899 5.00000 7.00000 8.00 0.11
[126,] 6 1.080346 4.45455 2.00000 4.00000 7.00 0.47
[127,] 7 1.253298 5.10101 2.45000 5.00000 8.00 0.39
[128,] 6 0.329366 5.55556 3.00000 6.00000 8.00 1.00
[129,] 8 1.209777 6.33333 4.00000 6.00000 9.00 0.39
[130,] 8 0.714667 6.75758 3.00000 7.00000 10.00 0.77
[131,] 10 -0.187295 10.24242 8.00000 10.00000 12.55 1.00
[132,] 9 -1.764598 11.06061 9.00000 11.00000 13.00 0.21
[133,] 8 3.084507 4.11111 1.00000 4.00000 6.00 0.01 **
[134,] 7 1.538724 4.78788 2.00000 5.00000 8.00 0.27
[135,] 7 1.322415 5.22222 2.45000 5.00000 8.00 0.27
[136,] 7 0.901068 5.56566 3.00000 6.00000 8.00 0.57
[137,] 10 1.649916 8.00000 5.00000 8.00000 10.00 0.19
[138,] 9 0.506304 8.43434 6.00000 9.00000 10.00 1.00
[139,] 7 1.096162 5.49495 3.00000 5.00000 8.00 0.53
[140,] 10 3.029523 5.81818 2.45000 6.00000 8.00 0.01 **
[141,] 11 3.178976 6.11111 3.00000 6.00000 9.00 0.01 **
[142,] 11 1.181489 9.52525 7.00000 10.00000 11.00 0.55
[143,] 12 1.577920 10.07071 7.45000 10.00000 12.00 0.21
[144,] 7 0.064148 6.89899 4.00000 7.00000 9.55 1.00
[145,] 7 -0.270320 7.41414 4.00000 8.00000 10.55 0.99
[146,] 11 -0.022061 11.03030 9.00000 11.00000 14.00 1.00
[147,] 9 -2.172582 11.82828 9.00000 12.00000 14.00 0.09 .
[148,] 11 1.649133 8.52525 6.00000 8.00000 11.00 0.27
[149,] 13 0.533069 12.25253 10.00000 12.00000 15.00 0.85
[150,] 15 1.373913 13.13131 10.00000 13.00000 15.00 0.29
[151,] 15 1.262834 12.95960 9.45000 13.00000 15.55 0.41
[152,] 15 0.643627 14.04040 11.00000 14.00000 16.55 0.85
[153,] 22 -0.879350 23.37374 21.00000 23.00000 26.55 0.59
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
vegan documentation built on May 2, 2019, 5:51 p.m.
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Description Usage Arguments Details Value Note Author(s) References See Also Examples
Description
Function finds the Raup-Crick dissimilarity which is a probability of number of co-occurring species with species occurrence probabilities proportional to species frequencies.
Usage
1 |
Arguments
comm |
Community data which will be treated as presence/absence data. |
null |
Null model used as the |
nsimul |
Number of null communities for assessing the dissimilarity index. |
chase |
Use the Chase et al. (2011) method of tie handling (not recommended except for comparing the results against the Chase script). |
... |
Other parameters passed to |
Details
Raup-Crick index is the probability that compared sampling units have non-identical species composition. This probability can be regarded as a dissimilarity, although it is not metric: identical sampling units can have dissimilarity slightly above 0, the dissimilarity can be nearly zero over a range of shared species, and sampling units with no shared species can have dissimilarity slightly below 1. Moreover, communities sharing rare species appear as more similar (lower probability of finding rare species together), than communities sharing the same number of common species.
The function will always treat the data as binary (presence/ absence).
The probability is assessed using simulation with
oecosimu where the test statistic is the observed
number of shared species between sampling units evaluated against a
community null model (see Examples). The default null model is
"r1" where the probability of selecting species is
proportional to the species frequencies.
The vegdist function implements a variant of the
Raup-Crick index with equal sampling probabilities for species using
exact analytic equations without simulation. This corresponds to
null model "r0" which also can be used with the
current function. All other null model methods of
oecosimu can be used with the current function, but
they are new unpublished methods.
Value
The function returns an object inheriting from
dist which can be interpreted as a dissimilarity
matrix.
Note
The test statistic is the number of shared species, and this is
typically tied with a large number of simulation results. The tied
values are handled differently in the current function and in the
function published with Chase et al. (2011). In vegan, the
index is the number of simulated values that are smaller or
equal than the observed value, but smaller than observed value is
used by Chase et al. (2011) with option split = FALSE in
their script; this can be achieved with chase = TRUE in
vegan. Chase et al. (2011) script with split = TRUE
uses half of tied simulation values to calculate a distance measure,
and that choice cannot be directly reproduced in vegan (it is the
average of vegan raupcrick results with
chase = TRUE and chase = FALSE).
Author(s)
The function was developed after Brian Inouye contacted us and informed us about the method in Chase et al. (2011), and the function takes its idea from the code that was published with their paper. The current function was written by Jari Oksanen.
References
Chase, J.M., Kraft, N.J.B., Smith, K.G., Vellend, M. and Inouye, B.D. (2011). Using null models to disentangle variation in community dissimilarity from variation in alpha-diversity. Ecosphere 2:art24 [doi:10.1890/ES10-00117.1]
See Also
The function is based on oecosimu. Function
vegdist with method = "raup" implements a related
index but with equal sampling densities of species, and
designdist demonstrates its calculation.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ## data set with variable species richness
data(sipoo)
## default raupcrick
dr1 <- raupcrick(sipoo)
## use null model "r0" of oecosimu
dr0 <- raupcrick(sipoo, null = "r0")
## vegdist(..., method = "raup") corresponds to 'null = "r0"'
d <- vegdist(sipoo, "raup")
op <- par(mfrow=c(2,1), mar=c(4,4,1,1)+.1)
plot(dr1 ~ d, xlab = "Raup-Crick with Null R1", ylab="vegdist")
plot(dr0 ~ d, xlab = "Raup-Crick with Null R0", ylab="vegdist")
par(op)
## The calculation is essentially as in the following oecosimu() call,
## except that designdist() is replaced with faster code
## Not run:
oecosimu(sipoo, function(x) designdist(x, "J", "binary"), method = "r1")
## End(Not run)
|
Example output
Loading required package: permute
Loading required package: lattice
This is vegan 2.4-3
oecosimu object
Call: oecosimu(comm = sipoo, nestfun = function(x) designdist(x, "J",
"binary"), method = "r1")
nullmodel method 'r1' with 99 simulations
alternative hypothesis: statistic is less or greater than simulated values
Svartholm L.Hogholm Ledholmen S.Hogholm Torvedsh SkataLed Flakaskar
L.Hogholm 2
Ledholmen 3 3
S.Hogholm 1 1 1
Torvedsh 3 3 4 2
SkataLed 1 3 2 2 4
Flakaskar 1 1 1 2 3 3
S.farholm 3 3 4 2 4 4 2
Farholmn 1 2 1 2 2 4 2
Asplandet 1 2 1 2 3 4 3
Granlndet 2 3 3 2 5 6 3
Hanskholm 3 3 4 2 6 4 3
Ragskar 3 3 4 2 6 5 3
Trutland 3 3 5 1 5 3 2
Kaivokari 2 3 3 2 5 6 3
Mustahevo 2 2 3 2 5 5 3
Kaunissri 3 4 5 2 6 6 3
Onas 3 4 4 2 6 6 4
S.farholm Farholmn Asplandet Granlndet Hanskholm Ragskar Trutland
L.Hogholm
Ledholmen
S.Hogholm
Torvedsh
SkataLed
Flakaskar
S.farholm
Farholmn 5
Asplandet 4 4
Granlndet 7 5 6
Hanskholm 6 4 4 6
Ragskar 6 5 4 7 8
Trutland 6 2 4 6 7 7
Kaivokari 6 6 5 8 7 10 7
Mustahevo 5 5 4 8 7 11 7
Kaunissri 9 6 6 10 10 11 11
Onas 7 6 5 9 9 12 9
Kaivokari Mustahevo Kaunissri
L.Hogholm
Ledholmen
S.Hogholm
Torvedsh
SkataLed
Flakaskar
S.farholm
Farholmn
Asplandet
Granlndet
Hanskholm
Ragskar
Trutland
Kaivokari
Mustahevo 11
Kaunissri 13 15
Onas 15 15 22
statistic SES mean 2.5% 50% 97.5% Pr(sim.)
[1,] 2 1.817643 0.60606 0.00000 0.00000 2.00 0.27
[2,] 3 3.515120 0.59596 0.00000 0.00000 2.00 0.03 *
[3,] 1 1.667133 0.26263 0.00000 0.00000 1.00 0.53
[4,] 3 2.583701 0.90909 0.00000 1.00000 3.00 0.09 .
[5,] 1 0.168818 0.86869 0.00000 1.00000 3.00 1.00
[6,] 1 0.494518 0.68687 0.00000 1.00000 2.00 1.00
[7,] 3 1.804440 1.39394 0.00000 1.00000 3.00 0.19
[8,] 1 0.102129 0.91919 0.00000 1.00000 3.00 1.00
[9,] 1 -0.200991 1.19192 0.00000 1.00000 3.00 1.00
[10,] 2 0.104829 1.89899 0.00000 2.00000 3.00 1.00
[11,] 3 1.630834 1.43434 0.00000 1.00000 3.00 0.29
[12,] 3 1.416663 1.69697 0.00000 2.00000 3.00 0.35
[13,] 3 1.313352 1.85859 0.00000 2.00000 3.00 0.53
[14,] 2 -0.255528 2.27273 0.00000 2.00000 4.00 1.00
[15,] 2 -0.360041 2.33333 1.00000 2.00000 4.00 1.00
[16,] 3 -0.392787 3.29293 2.00000 3.00000 4.00 1.00
[17,] 3 -0.752101 3.48485 2.00000 4.00000 4.00 0.89
[18,] 3 3.405735 0.66667 0.00000 1.00000 2.00 0.03 *
[19,] 1 1.322676 0.32323 0.00000 0.00000 1.00 0.61
[20,] 3 2.934576 0.96970 0.00000 1.00000 2.00 0.03 *
[21,] 3 2.997374 0.85859 0.00000 1.00000 2.00 0.03 *
[22,] 1 0.501892 0.64646 0.00000 1.00000 2.00 1.00
[23,] 3 1.773160 1.38384 0.00000 1.00000 3.00 0.21
[24,] 2 1.412803 0.91919 0.00000 1.00000 2.55 0.39
[25,] 2 0.946661 1.15152 0.00000 1.00000 3.00 0.65
[26,] 3 1.171234 1.82828 0.00000 2.00000 4.00 0.55
[27,] 3 1.629512 1.48485 0.00000 2.00000 3.00 0.25
[28,] 3 1.287925 1.74747 0.00000 2.00000 4.00 0.39
[29,] 3 1.038641 2.11111 1.00000 2.00000 4.00 0.61
[30,] 3 0.995040 2.01010 0.00000 2.00000 4.00 0.67
[31,] 2 -0.241308 2.22222 1.00000 2.00000 4.00 1.00
[32,] 4 1.100855 3.23232 2.00000 3.00000 4.00 0.77
[33,] 4 0.803205 3.49495 2.00000 4.00000 4.00 1.00
[34,] 1 0.918705 0.45455 0.00000 0.00000 2.00 0.81
[35,] 4 3.005561 1.30303 0.00000 1.00000 3.00 0.01 **
[36,] 2 0.828900 1.31313 0.00000 1.00000 3.00 0.85
[37,] 1 0.199147 0.84848 0.00000 1.00000 2.00 1.00
[38,] 4 2.385983 1.70707 0.00000 2.00000 3.55 0.07 .
[39,] 1 -0.267344 1.20202 0.00000 1.00000 2.00 1.00
[40,] 1 -0.477960 1.47475 0.00000 1.00000 3.55 1.00
[41,] 3 0.577918 2.35354 0.00000 3.00000 4.00 1.00
[42,] 4 2.119678 1.85859 0.00000 2.00000 4.00 0.09 .
[43,] 4 1.908853 2.10101 0.00000 2.00000 4.00 0.11
[44,] 5 2.305181 2.44444 0.45000 3.00000 4.00 0.03 *
[45,] 3 0.200440 2.76768 0.45000 3.00000 5.00 1.00
[46,] 3 0.214574 2.77778 1.00000 3.00000 4.55 1.00
[47,] 5 1.010835 4.16162 2.00000 4.00000 5.00 0.79
[48,] 4 -0.577281 4.39394 3.00000 4.00000 5.00 1.00
[49,] 2 2.527566 0.49495 0.00000 0.00000 2.00 0.11
[50,] 2 2.645547 0.43434 0.00000 0.00000 2.00 0.11
[51,] 2 3.731935 0.29293 0.00000 0.00000 1.00 0.01 **
[52,] 2 1.842759 0.77778 0.00000 1.00000 2.00 0.27
[53,] 2 2.774377 0.41414 0.00000 0.00000 2.00 0.09 .
[54,] 2 1.989873 0.66667 0.00000 1.00000 2.00 0.23
[55,] 2 1.687789 0.78788 0.00000 1.00000 2.00 0.35
[56,] 2 1.839639 0.78788 0.00000 1.00000 2.00 0.27
[57,] 2 1.893740 0.75758 0.00000 1.00000 2.00 0.25
[58,] 1 -0.092981 1.06061 0.00000 1.00000 2.00 1.00
[59,] 2 1.361407 1.11111 0.00000 1.00000 2.00 0.55
[60,] 2 1.069329 1.28283 0.00000 1.00000 2.00 0.81
[61,] 2 0.624806 1.71717 1.00000 2.00000 2.00 1.00
[62,] 2 0.332411 1.86869 1.00000 2.00000 2.00 1.00
[63,] 4 3.258578 1.24242 0.00000 1.00000 3.00 0.01 **
[64,] 3 3.509236 0.76768 0.00000 1.00000 2.00 0.01 **
[65,] 4 1.905159 2.00000 0.00000 2.00000 4.00 0.17
[66,] 2 0.707557 1.32323 0.00000 1.00000 3.00 0.83
[67,] 3 1.235700 1.74747 0.00000 2.00000 3.55 0.49
[68,] 5 1.775376 2.69697 0.00000 3.00000 5.00 0.19
[69,] 6 3.338042 2.24242 0.00000 2.00000 4.00 0.01 **
[70,] 6 3.010334 2.40404 0.00000 2.00000 5.00 0.01 **
[71,] 5 1.982252 2.86869 1.00000 3.00000 5.00 0.11
[72,] 5 1.812934 2.96970 1.00000 3.00000 5.00 0.19
[73,] 5 1.469862 3.33333 1.00000 3.00000 5.00 0.33
[74,] 6 1.248159 4.74747 3.00000 5.00000 6.00 0.47
[75,] 6 0.924673 5.18182 3.00000 5.00000 6.00 0.85
[76,] 3 2.091606 1.03030 0.00000 1.00000 3.00 0.13
[77,] 4 1.775855 2.18182 0.00000 2.00000 4.00 0.21
[78,] 4 2.770045 1.38384 0.00000 1.00000 3.00 0.01 **
[79,] 4 2.145736 1.77778 0.00000 2.00000 4.00 0.11
[80,] 6 3.020112 2.70707 1.00000 3.00000 4.55 0.01 **
[81,] 4 1.925850 2.25253 1.00000 2.00000 4.00 0.21
[82,] 5 2.344439 2.44444 1.00000 2.00000 5.00 0.09 .
[83,] 3 -0.044063 3.05051 1.00000 3.00000 5.00 1.00
[84,] 6 2.247203 3.33333 1.00000 3.00000 6.00 0.09 .
[85,] 5 1.485939 3.46465 1.45000 4.00000 5.00 0.31
[86,] 6 1.095491 4.89899 3.00000 5.00000 6.00 0.65
[87,] 6 0.926178 5.22222 3.00000 5.00000 6.00 0.89
[88,] 2 0.740554 1.39394 0.00000 1.00000 3.00 0.89
[89,] 2 1.440800 0.90909 0.00000 1.00000 2.00 0.45
[90,] 3 2.162006 1.17172 0.00000 1.00000 3.00 0.13
[91,] 3 1.448291 1.65657 0.00000 2.00000 3.00 0.35
[92,] 3 1.787215 1.42424 0.00000 1.00000 3.00 0.25
[93,] 3 1.371511 1.78788 0.00000 2.00000 3.00 0.47
[94,] 2 0.124722 1.88889 0.00000 2.00000 3.55 1.00
[95,] 3 0.903659 2.10101 0.00000 2.00000 4.00 0.75
[96,] 3 0.910055 2.13131 0.00000 2.00000 4.00 0.63
[97,] 3 -0.265521 3.21212 1.45000 3.00000 4.00 1.00
[98,] 4 0.762539 3.48485 2.00000 4.00000 4.00 1.00
[99,] 5 2.523460 2.19192 0.00000 2.00000 4.00 0.03 *
[100,] 4 1.104999 2.71717 1.00000 3.00000 5.00 0.47
[101,] 7 1.982558 4.28283 2.00000 4.00000 7.00 0.15
[102,] 6 1.848986 3.42424 1.00000 3.00000 6.00 0.17
[103,] 6 1.708111 3.95960 2.00000 4.00000 6.55 0.19
[104,] 6 1.250563 4.39394 2.00000 4.00000 7.00 0.45
[105,] 6 0.788095 4.98990 3.00000 5.00000 7.00 0.65
[106,] 5 -0.432260 5.58586 3.00000 6.00000 8.00 0.95
[107,] 9 0.957030 7.71717 5.00000 8.00000 10.00 0.49
[108,] 7 -1.793108 8.64646 7.00000 9.00000 10.00 0.21
[109,] 4 2.272249 1.73737 0.00000 2.00000 4.00 0.13
[110,] 5 1.903690 2.81818 1.00000 3.00000 5.00 0.11
[111,] 4 1.755976 2.16162 0.00000 2.00000 4.00 0.19
[112,] 5 2.102507 2.67677 1.00000 3.00000 4.55 0.07 .
[113,] 2 -0.668663 2.81818 0.45000 3.00000 5.00 0.79
[114,] 6 2.493512 3.17172 1.00000 3.00000 5.00 0.05 *
[115,] 5 1.353937 3.48485 2.00000 4.00000 5.55 0.35
[116,] 6 1.285942 4.96970 3.00000 5.00000 6.00 0.53
[117,] 6 0.982807 5.25253 4.00000 5.00000 6.00 0.85
[118,] 6 1.852104 3.48485 1.00000 3.00000 6.00 0.15
[119,] 4 0.991012 2.72727 0.45000 3.00000 5.00 0.59
[120,] 4 0.703399 3.08081 1.00000 3.00000 5.00 0.81
[121,] 4 0.320755 3.52525 1.00000 3.00000 6.00 0.97
[122,] 5 0.704324 3.95960 1.00000 4.00000 6.00 0.73
[123,] 4 -0.057234 4.08081 1.45000 4.00000 7.00 1.00
[124,] 6 -0.311300 6.32323 4.45000 6.00000 8.00 1.00
[125,] 5 -2.200414 6.89899 5.00000 7.00000 8.00 0.11
[126,] 6 1.080346 4.45455 2.00000 4.00000 7.00 0.47
[127,] 7 1.253298 5.10101 2.45000 5.00000 8.00 0.39
[128,] 6 0.329366 5.55556 3.00000 6.00000 8.00 1.00
[129,] 8 1.209777 6.33333 4.00000 6.00000 9.00 0.39
[130,] 8 0.714667 6.75758 3.00000 7.00000 10.00 0.77
[131,] 10 -0.187295 10.24242 8.00000 10.00000 12.55 1.00
[132,] 9 -1.764598 11.06061 9.00000 11.00000 13.00 0.21
[133,] 8 3.084507 4.11111 1.00000 4.00000 6.00 0.01 **
[134,] 7 1.538724 4.78788 2.00000 5.00000 8.00 0.27
[135,] 7 1.322415 5.22222 2.45000 5.00000 8.00 0.27
[136,] 7 0.901068 5.56566 3.00000 6.00000 8.00 0.57
[137,] 10 1.649916 8.00000 5.00000 8.00000 10.00 0.19
[138,] 9 0.506304 8.43434 6.00000 9.00000 10.00 1.00
[139,] 7 1.096162 5.49495 3.00000 5.00000 8.00 0.53
[140,] 10 3.029523 5.81818 2.45000 6.00000 8.00 0.01 **
[141,] 11 3.178976 6.11111 3.00000 6.00000 9.00 0.01 **
[142,] 11 1.181489 9.52525 7.00000 10.00000 11.00 0.55
[143,] 12 1.577920 10.07071 7.45000 10.00000 12.00 0.21
[144,] 7 0.064148 6.89899 4.00000 7.00000 9.55 1.00
[145,] 7 -0.270320 7.41414 4.00000 8.00000 10.55 0.99
[146,] 11 -0.022061 11.03030 9.00000 11.00000 14.00 1.00
[147,] 9 -2.172582 11.82828 9.00000 12.00000 14.00 0.09 .
[148,] 11 1.649133 8.52525 6.00000 8.00000 11.00 0.27
[149,] 13 0.533069 12.25253 10.00000 12.00000 15.00 0.85
[150,] 15 1.373913 13.13131 10.00000 13.00000 15.00 0.29
[151,] 15 1.262834 12.95960 9.45000 13.00000 15.55 0.41
[152,] 15 0.643627 14.04040 11.00000 14.00000 16.55 0.85
[153,] 22 -0.879350 23.37374 21.00000 23.00000 26.55 0.59
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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