Compute the following diversity indices and perform corresponding statistical tests to compare the phenotypic diversity for qualitative traits between entire collection (EC) and core set (CS).
Simpson's and related indices
Simpson's Index (\(d\)) (Simpson 1949; Peet 1974)
Simpson's Index of Diversity or Gini's Diversity Index or Gini-Simpson Index or Nei's Diversity Index or Nei's Variation Index (\(D\)) or Hurlbert’s probability of interspecific encounter (\(PIE\)) (Gini 1912, 1912; Greenberg 1956; Berger and Parker 1970; Hurlbert 1971; Nei 1973; Peet 1974)
Maximum Simpson's Index of Diversity or Maximum Nei's Diversity/Variation Index (\(D_{max}\)) (Hennink and Zeven 1990)
Simpson's Reciprocal Index or Hill's \(N_{2}\) (\(D_{R}\)) or Effective number of Species (\(ENS_{d}\)) (Williams 1964; Hill 1973)
Relative Simpson's Index of Diversity or Relative Nei's Diversity/Variation Index (\(D'\)) (Hennink and Zeven 1990)
Simpson’s evenness or equitability (\(D_{e}\))
Shannon-Weaver and related indices
Shannon or Shannon-Weaver or Shannon-Wiener Diversity Index or Shannon entropy (\(H\)) (Shannon and Weaver 1949; Peet 1974)
Maximum Shannon-Weaver Diversity Index (\(H_{max}\)) (Hennink and Zeven 1990)
Relative Shannon-Weaver Diversity Index or Shannon Equitability Index (\(H'\)) or Pielou's Evenness (\(J\)) (Pielou 1966; Hennink and Zeven 1990)
Effective number of species for the Shannon -Weaver Diversity Index (\(ENS_{H}\)) or Hill's \(N_{1}\) (Macarthur 1965; Hill 1973)
McIntosh's measures of diversity
McIntosh Diversity Index (\(D_{Mc}\)) (McIntosh 1967; Peet 1974)
McIntosh Evenness Index (\(E_{Mc}\)) (Pielou 1975)
Usage
diversity.evaluate.core(
data,
names,
qualitative,
selected,
base = 2,
R = 1000,
na.omit = TRUE
)Arguments
- data
The data as a data frame object. The data frame should possess one row per individual and columns with the individual names and multiple trait/character data.
- names
Name of column with the individual names as a character string.
- qualitative
Name of columns with the qualitative traits as a character vector.
- selected
Character vector with the names of individuals selected in core collection and present in the
namescolumn.- base
The logarithm base to be used for computation of Shannon-Weaver Diversity Index (\(I\)). Default is 2.
- R
The number of bootstrap replicates. Default is 1000.
- na.omit
logical. If
TRUE, missing values (NA) are ignored and not included as a distinct factor level for computation. Default isTRUE.
Value
A list with three data frames as follows.
- simpson
- EC_No.Classes
The number of classes in the trait for EC.
- CS_No.Classes
The number of classes in the trait for CS.
- EC_d
The Simpson's Index (\(d\)) for EC.
- EC_D
The Simpson's Index of Diversity (\(D\)) for EC.
- EC_D.max
The Maximum Simpson's Index of Diversity (\(D_{max}\)) for EC.
- EC_D.inv
The Simpson's Reciprocal Index (\(D_{R}\)) for EC.
- EC_D.rel
The Relative Reciprocal Index (\(D'\)) for EC.
- EC_D.e
The Shannon's evenness or equitability (\(D_{e}\)) for EC.
- EC_d.V
The variance of \(d\) for EC according to (Simpson 1949) .
- EC_d.boot.V
The bootstrap variance of \(d\) for EC.
- CS_d
The Simpson's Index (\(d\)) for CS.
- CS_D
The Simpson's Index of Diversity (\(D\)) for CS.
- CS_D.max
The Maximum Simpson's Index of Diversity (\(D_{max}\)) for CS.
- CS_D.inv
The Simpson's Reciprocal Index (\(D_{R}\)) for CS.
- CS_D.rel
The Relative Reciprocal Index (\(D'\)) for CS.
- CS_D.e
The Shannon's evenness or equitability (\(D_{e}\)) for CS.
- CS_d.V
The variance of \(d\) for CS according to (Simpson 1949) .
- CS_d.boot.V
The bootstrap variance of \(d\) for CS.
- d.t.df
The degrees of freedom for t test.
- d.t.stat
The t statistic.
- d.t.pvalue
The p value for t test.
- d.t.significance
The significance of t test for t-test
- d.boot.z.df
The degrees of freedom for bootstrap z score.
- d.boot.z.stat
The bootstrap z score.
- d.boot.z.pvalue
The p value of z score.
- d.boot.z.significance
The significance of z score.
- shannon
- EC_No.Classes
The number of classes in the trait for EC.
- CS_No.Classes
The number of classes in the trait for CS.
- EC_I
The Shannon-Weaver Diversity Index (\(I\)) for EC.
- EC_I.max
The Maximum Shannon-Weaver Diversity Index (\(I_{max}\)) for EC.
- EC_I.rel
The Relative Shannon-Weaver Diversity Index (\(I'\)) for EC.
- EC_I.ens
The Effective Number of Species for Shannon-Weaver Diversity Index (\(ENS_{H}\)) for EC
- EC_I.V
The variance of \(I\) for EC according to (Hutcheson 1970) .
- EC_I.boot.V
The bootstrap variance of \(I\) for EC.
- CS_I
The Shannon-Weaver Diversity Index (\(I\)) for CS.
- CS_I.max
The Maximum Shannon-Weaver Diversity Index (\(I_{max}\)) for CS.
- CS_I.rel
The Relative Shannon-Weaver Diversity Index (\(I'\)) for CS.
- CS_I.ens
The Effective Number of Species for Shannon-Weaver Diversity Index (\(ENS_{H}\)) for CS.
- CS_I.V
The variance of \(I\) for CS according to (Hutcheson 1970) .
- CS_I.boot.V
The bootstrap variance of \(I\) for CS.
- I.t.stat
The t statistic.
- I.t.df
The degrees of freedom for t test.
- I.t.pvalue
The p value for t test.
- I.t.significance
The significance of t test for t-test
- I.boot.z.df
The degrees of freedom for bootstrap z score.
- I.boot.z.stat
The bootstrap z score.
- I.boot.z.pvalue
The p value of z score.
- I.boot.z.significance
The significance of z score.
- mcintosh
- CS_No.Classes
The number of classes in the trait for CS.
- EC_D.Mc
The McIntosh Index (\(D_{Mc}\)) for EC.
- CS_D.Mc
The McIntosh Index (\(D_{Mc}\)) for CS.
- M.boot.z.stat
The bootstrap z score.
- M.boot.z.df
The degrees of freedom for bootstrap z score.
- M.boot.z.pvalue
The p value of z score.
- M.boot.z.significance
The significance of z score.
Details
The diversity indices and the corresponding statistical
tests implemented in diversity.evaluate.core are as follows.
Simpson's and related indices
Simpson's index (\(d\)) which estimates the probability that two accessions randomly selected will belong to the same phenotypic class of a trait, is computed as follows (Simpson 1949; Peet 1974) .
\[d = \sum_{i = 1}^{k}p_{i}^{2}\]
Where, \(p_{i}\) denotes the proportion/fraction/frequency of accessions in the \(i\)th phenotypic class for a trait and \(k\) is the number of phenotypic classes for the trait.
The value of \(d\) can range from 0 to 1 with 0 representing maximum diversity and 1, no diversity.
\(d\) is subtracted from 1 to give Simpson's index of diversity (\(D\)) (Greenberg 1956; Berger and Parker 1970; Hurlbert 1971; Peet 1974; Hennink and Zeven 1990) originally suggested by Gini (1912, 1912) and described in literature as Gini's diversity index or Gini-Simpson index. It is the same as Nei's diversity index or Nei's variation index (Nei 1973; Hennink and Zeven 1990) . Greater the value of \(D\), greater the diversity with a range from 0 to 1.
\[D = 1 - d\]
The maximum value of \(D\), \(D_{max}\) occurs when accessions are uniformly distributed across the phenotypic classes and is computed as follows (Hennink and Zeven 1990) .
\[D_{max} = 1 - \frac{1}{k}\]
Reciprocal of \(d\) gives the Simpson's reciprocal index (\(D_{R}\)) (Williams 1964; Hennink and Zeven 1990) and can range from 1 to \(k\). This was also described in Hill (1973) as \(N_{2}\) or as Effective number of Species (\(ENS_{d}\)).
\[D_{R} = \frac{1}{d}\]
Relative Simpson's index of diversity or Relative Nei's diversity/variation index (\(H'\)) (Hennink and Zeven 1990) is defined as follows (Peet 1974) .
\[D' = \frac{D}{D_{max}}\]
Simpson’s evenness or equitability (\(D_{e}\) is described as follows (Pielou 1966; Hill 1973) .
\[D_{e} = \frac{1}{d \cdot k}\]
Differences in Simpson's diversity index for qualitative traits of EC and CS can be tested by a t-test using the associated variance estimate described in Simpson (1949) (Lyons and Hutcheson 1978) .
The t statistic is computed as follows.
\[t = \frac{d_{EC} - d_{CS}}{\sqrt{V_{d_{EC}} + V_{d_{CS}}}}\]
Where, the variance of \(d\) (\(V_{d}\)) is,
\[V_{d} = \frac{4N(N-1)(N-2)\sum_{i=1}^{k}(p_{i})^{3} + 2N(N-1)\sum_{i=1}^{k}(p_{i})^{2} - 2N(N-1)(2N-3) \left( \sum_{i=1}^{k}(p_{i})^{2} \right)^{2}}{[N(N-1)]^{2}}\]
The associated degrees of freedom is computed as follows.
\[df = (k_{EC} - 1) + (k_{CS} - 1)\]
Where, \(k_{EC}\) and \(k_{CS}\) are the number of phenotypic classes in the trait for EC and CS respectively.
Shannon-Weaver and related indices
An index of information \(H\), was described by Shannon and Weaver (1949) as follows.
\[H = -\sum_{i=1}^{k}p_{i} \log_{2}(p_{i})\]
\(H\) is described as Shannon or Shannon-Weaver or Shannon-Wiener diversity index or Shannon entropy in literature (Shannon and Weaver 1949; Peet 1974) .
Alternatively, \(H\) is also computed using natural logarithm instead of logarithm to base 2.
\[H = -\sum_{i=1}^{k}p_{i} \ln(p_{i})\]
The maximum value of \(H\) (\(H_{max}\)) is \(\ln(k)\). This value occurs when each phenotypic class for a trait has the same proportion of accessions (Hennink and Zeven 1990) .
\[H_{max} = \log_{2}(k)\;\; \textrm{OR} \;\; H_{max} = \ln(k)\]
The relative Shannon-Weaver diversity index or Shannon equitability index (\(H'\)) or Pielou's Evenness (\(J\)) is the Shannon diversity index (\(I\)) divided by the maximum diversity (\(H_{max}\)) (Pielou 1966; Hennink and Zeven 1990) .
\[H' = \frac{H}{H_{max}}\]
(Macarthur 1965) described the Effective number of species for the Shannon index (\(ENS_{H}\)) as follows.
\[ ENS_{H} = e^{H}\]
Differences in Shannon-Weaver diversity index for qualitative traits of EC and CS can be tested by Hutcheson t-test (Hutcheson 1970) .
The Hutcheson t statistic is computed as follows.
\[t = \frac{H_{EC} - H_{CS}}{\sqrt{V_{H_{EC}} + V_{H_{CS}}}}\]
Where, the variance of \(H\) (\(V_{H}\)) is,
\[V_{H} = \frac{\sum_{i=1}^{k}n_{i}(\log_{2}{n_{i}})^{2} \frac{(\sum_{i=1}^{k}\log_{2}{n_{i}})^2}{N}}{N^{2}}\]
\[\textrm{OR}\]
\[V_{H} = \frac{\sum_{i=1}^{k}n_{i}(\ln{n_{i}})^{2} \frac{(\sum_{i=1}^{k}\ln{n_{i}})^2}{N}}{N^{2}}\]
The associated degrees of freedom is approximated as follows.
\[df = \frac{(V_{H_{EC}} + V_{H_{CS}})^{2}}{\frac{V_{H_{EC}}^{2}}{N_{EC}} + \frac{V_{H_{CS}}^{2}}{N_{CS}}}\]
McIntosh's Measure of Diversity
A similar index of diversity was described by McIntosh (1967) as follows (\(D_{Mc}\)) (Peet 1974) .
\[D_{Mc} = \frac{N - \sqrt{\sum_{i=1}^{k}n_{i}^2}}{N - \sqrt{N}}\]
Where, \(n_{i}\) denotes the number of accessions in the \(i\)th phenotypic class for a trait and \(N\) is the total number of accessions so that \(p_{i} = {n_{i}}/{N}\).
An additional measure of evenness was proposed by Pielou (1975) as follows.
\[E_{Mc} = \frac{N - \sqrt{\sum_{i=1}^{k}n_{i}^2}}{N - \frac{N}{\sqrt{S}}}\]
Testing for difference with bootstrapping
Bootstrap statistics are employed to test the difference between the Simpson, Shannon-Weaver and McIntosh indices for qualitative traits of EC and CS (Solow 1993) .
If \(I_{EC}\) and \(I_{CS}\) are the diversity indices with the original number of accessions, then random samples of the same size as the original are repeatedly generated (with replacement) \(R\) times and the corresponding diversity index is computed for each sample.
\[I_{EC}^{*} = \lbrace H_{EC_{1}}, H_{EC_{}}, \cdots, H_{EC_{R}} \rbrace\]
\[I_{CS}^{*} = \lbrace H_{CS_{1}}, H_{CS_{}}, \cdots, H_{CS_{R}} \rbrace\]
Then the bootstrap null sample \(I_{0}\) is computed as follows.
\[\Delta^{*} = I_{EC}^{*} - I_{CS}^{*}\]
\[I_{0} = \Delta^{*} - \overline{\Delta^{*}}\]
Where, \(\overline{\Delta^{*}}\) is the mean of \(\Delta^{*}\).
Now the original difference in diversity indices (\(\Delta_{0} = I_{EC} - I_{CS}\)) is tested against mean of bootstrap null sample (\(I_{0}\)) by a z test. The z score test statistic is computed as follows.
\[z = \frac{\Delta_{0} - \overline{H_{0}}}{\sqrt{V_{H_{0}}}}\]
Where, \(\overline{H_{0}}\) and \(V_{H_{0}}\) are the mean and variance of the bootstrap null sample \(H_{0}\).
The corresponding degrees of freedom is estimated as follows.
\[df = (k_{EC} - 1) + (k_{CS} - 1)\]
References
Berger WH, Parker FL (1970).
“Diversity of planktonic foraminifera in deep-sea sediments.”
Science, 168(3937), 1345–1347.
Gini C (1912).
Variabilita e Mutabilita. Contributo allo Studio delle Distribuzioni e delle Relazioni Statistiche. [Fasc. I.].
Tipogr. di P. Cuppini, Bologna.
Gini C (1912).
“Variabilita e mutabilita.”
In Pizetti E, Salvemini T (eds.), Memorie di Metodologica Statistica.
Liberia Eredi Virgilio Veschi, Roma, Italy.
Greenberg JH (1956).
“The measurement of linguistic diversity.”
Language, 32(1), 109.
Hennink S, Zeven AC (1990).
“The interpretation of Nei and Shannon-Weaver within population variation indices.”
Euphytica, 51(3), 235–240.
Hill MO (1973).
“Diversity and evenness: A unifying notation and its consequences.”
Ecology, 54(2), 427–432.
Hurlbert SH (1971).
“The nonconcept of species diversity: a critique and alternative parameters.”
Ecology, 52(4), 577–586.
Hutcheson K (1970).
“A test for comparing diversities based on the Shannon formula.”
Journal of Theoretical Biology, 29(1), 151–154.
Lyons NI, Hutcheson K (1978).
“C20. Comparing diversities: Gini's index.”
Journal of Statistical Computation and Simulation, 8(1), 75–78.
Macarthur RH (1965).
“Patterns of species diversity.”
Biological Reviews, 40(4), 510–533.
McIntosh RP (1967).
“An index of diversity and the relation of certain concepts to diversity.”
Ecology, 48(3), 392–404.
Nei M (1973).
“Analysis of gene diversity in subdivided populations.”
Proceedings of the National Academy of Sciences, 70(12), 3321–3323.
Peet RK (1974).
“The measurement of species diversity.”
Annual Review of Ecology and Systematics, 5(1), 285–307.
Pielou EC (1966).
“The measurement of diversity in different types of biological collections.”
Journal of Theoretical Biology, 13, 131–144.
Pielou EC (1975).
Ecological diversity.
New York : Wiley.
ISBN 978-0-471-68925-6.
Shannon CE, Weaver W (1949).
The Mathematical Theory of Communication, number v. 2 in The Mathematical Theory of Communication.
University of Illinois Press.
Simpson EH (1949).
“Measurement of diversity.”
Nature, 163(4148), 688–688.
Solow AR (1993).
“A simple test for change in community structure.”
The Journal of Animal Ecology, 62(1), 191.
Williams CB (1964).
Patterns in the Balance of Nature and Related Problems in Quantitative Ecology.
Academic Press.
Examples
data("cassava_CC")
data("cassava_EC")
ec <- cbind(genotypes = rownames(cassava_EC), cassava_EC)
ec$genotypes <- as.character(ec$genotypes)
rownames(ec) <- NULL
core <- rownames(cassava_CC)
quant <- c("NMSR", "TTRN", "TFWSR", "TTRW", "TFWSS", "TTSW", "TTPW", "AVPW",
"ARSR", "SRDM")
qual <- c("CUAL", "LNGS", "PTLC", "DSTA", "LFRT", "LBTEF", "CBTR", "NMLB",
"ANGB", "CUAL9M", "LVC9M", "TNPR9M", "PL9M", "STRP", "STRC",
"PSTR")
ec[, qual] <- lapply(ec[, qual],
function(x) factor(as.factor(x)))
# \donttest{
diversity.evaluate.core(data = ec, names = "genotypes",
qualitative = qual, selected = core)
#> $simpson
#> Trait EC_No.Classes CS_No.Classes EC_d EC_D
#> 1 CUAL 5 4 0.379231526565524 0.620768473434476
#> 2 LNGS 3 3 0.422400150078142 0.577599849921858
#> 3 PTLC 5 5 0.477398006104682 0.522601993895318
#> 4 DSTA 5 5 0.351400071089646 0.648599928910354
#> 5 LFRT 5 4 0.448935347916114 0.551064652083886
#> 6 LBTEF 6 6 0.223971174841036 0.776028825158964
#> 7 CBTR 3 3 0.51874284166756 0.48125715833244
#> 8 NMLB 10 9 0.206703725435988 0.793296274564012
#> 9 ANGB 4 4 0.350516387291879 0.64948361270812
#> 10 CUAL9M 5 5 0.309073521363567 0.690926478636433
#> 11 LVC9M 5 5 0.425299451029954 0.574700548970046
#> 12 TNPR9M 5 5 0.247165582455527 0.752834417544473
#> 13 PL9M 3 2 0.498635332682619 0.501364667317381
#> 14 STRP 4 4 0.322189843207836 0.677810156792164
#> 15 STRC 2 2 0.510325630074306 0.489674369925694
#> 16 PSTR 3 2 0.555306757465823 0.444693242534177
#> EC_D.max EC_D.inv EC_D.rel EC_D.e
#> 1 0.8 2.63691156971154 0.775960591793095 0.32218131003573
#> 2 0.666666666666667 2.36742340128195 0.866399774882787 0.577100796301158
#> 3 0.8 2.09468826265002 0.653252492369147 0.382700415107987
#> 4 0.8 2.84575924216273 0.810749911137942 0.308356493865177
#> 5 0.8 2.22749223165839 0.688830815104857 0.362933821365038
#> 6 0.833333333333333 4.46486026922774 0.931234590190757 0.21476865454389
#> 7 0.666666666666667 1.92773744459853 0.72188573749866 0.692630390139725
#> 8 0.9 4.83784217188518 0.881440305071124 0.126056308602935
#> 9 0.75 2.85293366089411 0.865978150277494 0.384921182164377
#> 10 0.8 3.23547612745411 0.863658098295541 0.289466399369593
#> 11 0.8 2.35128448338761 0.718375686212558 0.348007323741784
#> 12 0.8 4.04587074812462 0.941043021930592 0.265662668096846
#> 13 0.666666666666667 2.005473608579 0.752047000976072 0.664852062904388
#> 14 0.75 3.10376016215672 0.903746875722886 0.368834838921803
#> 15 0.5 1.9595331707216 0.979348739851389 1.02108672764693
#> 16 0.666666666666667 1.80080646697613 0.667039863801265 0.749580388120504
#> EC_d.V EC_d.boot.V CS_d
#> 1 6.2401326584027e-05 6.68750117708326e-05 0.378472222222222
#> 2 2.66303075243519e-05 2.65811066561584e-05 0.387755102040816
#> 3 6.43256463380354e-05 6.50509760875086e-05 0.421343537414966
#> 4 4.49202770089222e-05 4.79613335074667e-05 0.303500566893424
#> 5 3.64033438958825e-05 3.49448546349972e-05 0.426587301587302
#> 6 1.01110395238633e-05 9.78006680330427e-06 0.200538548752834
#> 7 4.63756492257553e-05 4.76343377864573e-05 0.487244897959184
#> 8 1.57355754103247e-05 1.55372775046521e-05 0.198058390022676
#> 9 3.10366375721298e-05 3.19525542264521e-05 0.342120181405896
#> 10 1.34905804296262e-05 1.35415192137175e-05 0.288052721088435
#> 11 4.98247003940663e-05 4.74038435990513e-05 0.388676303854875
#> 12 2.56650302792209e-05 2.636407723636e-05 0.2218679138322
#> 13 3.79031161219323e-06 3.95703022757023e-06 0.500283446712018
#> 14 9.34647324671549e-06 9.00340235241142e-06 0.311862244897959
#> 15 1.21791747807758e-05 1.11330159341353e-05 0.518140589569161
#> 16 6.1357244865428e-05 5.80204406696967e-05 0.555555555555556
#> CS_D CS_D.max CS_D.inv CS_D.rel
#> 1 0.621527777777778 0.75 2.64220183486239 0.828703703703704
#> 2 0.612244897959184 0.666666666666667 2.57894736842105 0.918367346938775
#> 3 0.578656462585034 0.8 2.37336024217962 0.723320578231292
#> 4 0.696499433106576 0.8 3.29488676161569 0.87062429138322
#> 5 0.573412698412698 0.75 2.34418604651163 0.764550264550265
#> 6 0.799461451247165 0.833333333333333 4.98657243816254 0.959353741496599
#> 7 0.512755102040816 0.666666666666667 2.05235602094241 0.769132653061224
#> 8 0.801941609977324 0.888888888888889 5.04901610017889 0.90218431122449
#> 9 0.657879818594104 0.75 2.92294946147473 0.877173091458806
#> 10 0.711947278911565 0.8 3.47158671586716 0.889934098639456
#> 11 0.611323696145125 0.8 2.57283500455789 0.764154620181406
#> 12 0.7781320861678 0.8 4.50718620249122 0.972665107709751
#> 13 0.499716553287982 0.5 1.99886685552408 0.999433106575964
#> 14 0.688137755102041 0.75 3.20654396728016 0.917517006802721
#> 15 0.481859410430839 0.5 1.92997811816193 0.963718820861678
#> 16 0.444444444444444 0.5 1.8 0.888888888888889
#> CS_D.e CS_d.V CS_d.boot.V d.t.df
#> 1 0.402234636871508 0.000664974207441761 0.000711254556902111 7
#> 2 0.544444444444444 0.000253494320337725 0.000240257761836584 4
#> 3 0.345628214548126 0.00106773305088108 0.00104798654736355 8
#> 4 0.287150269610337 0.000464316667250201 0.000464735179959108 8
#> 5 0.43598615916955 0.000434218289438062 0.000428477928488368 7
#> 6 0.20847367488034 6.05627470284696e-05 6.0452161171105e-05 10
#> 7 0.650082918739635 0.000257136051752956 0.000270835513259535 4
#> 8 0.138552619952284 0.000216132859442877 0.000204518681279425 17
#> 9 0.380008616975442 0.000360254817691854 0.000352890437968318 6
#> 10 0.280919677515676 0.000144703074224106 0.000152287794801069 8
#> 11 0.327158919670801 0.000503057233986995 0.000487240519916225 8
#> 12 0.257025771787633 0.000134121919501297 0.000143697014401447 8
#> 13 1.00056721497448 2.11737525161229e-05 1.40416164854234e-05 3
#> 14 0.363299351251158 8.69838142388246e-05 8.63936473121947e-05 6
#> 15 1.03764705882353 0.00022467592663519 0.000201952305242796 2
#> 16 1.125 0.000601970661850899 0.000601207763998725 3
#> d.t.stat d.t.pvalue d.t.significance d.boot.z.df
#> 1 0.02815376878219 0.978325351754391 ns 7
#> 2 2.06997700767549 0.10723294813912 ns 4
#> 3 1.66600295615057 0.134274950280504 ns 8
#> 4 2.12261420536943 0.0665538249488766 ns 8
#> 5 1.0301574783912 0.337209790540494 ns 7
#> 6 2.78735177789005 0.0192068432217533 * 10
#> 7 1.80798358527422 0.144886591272101 ns 4
#> 8 0.567755084270463 0.577623407084813 ns 17
#> 9 0.424456215383704 0.686031514328123 ns 6
#> 10 1.6713011659847 0.133206249679844 ns 8
#> 11 1.55754090990284 0.157957033254601 ns 8
#> 12 2.00128917457502 0.0803555866511265 ns 8
#> 13 -0.329859967245677 0.763196306139146 ns 3
#> 14 1.05224751693921 0.333206278005286 ns 6
#> 15 -0.507791421657648 0.662061546648583 ns 2
#> 16 -0.00966012858117729 0.99289893656246 ns 3
#> d.boot.z.stat d.boot.z.pvalue d.boot.z.significance
#> 1 0.0275212882188481 0.978812135373164 ns
#> 2 2.14817887304654 0.098182032704849 ns
#> 3 1.68166677243456 0.13113810025065 ns
#> 4 2.09891549611266 0.069053916740305 ns
#> 5 1.03166697933988 0.336549450852584 ns
#> 6 2.82533970685804 0.0179951522790031 *
#> 7 1.73767783492423 0.157264335515885 ns
#> 8 0.581591476650998 0.568474385095018 ns
#> 9 0.426083455919101 0.684908883579996 ns
#> 10 1.6305427679191 0.141633454275904 ns
#> 11 1.56637783409065 0.155893973673908 ns
#> 12 1.9863174533999 0.0822405673333897 ns
#> 13 0.38950879498154 0.722904437177963 ns
#> 14 1.05400674082793 0.332462522918394 ns
#> 15 0.542596692443321 0.641786855685194 ns
#> 16 0.00948924181640027 0.993024548633537 ns
#>
#> $shannon
#> Trait EC_No.Classes CS_No.Classes EC_I EC_I.max
#> 1 CUAL 5 4 1.60118025300384 1.6094379124341
#> 2 LNGS 3 3 1.34638092645118 1.09861228866811
#> 3 PTLC 5 5 1.29757991678528 1.6094379124341
#> 4 DSTA 5 5 1.75217791456181 1.6094379124341
#> 5 LFRT 5 4 1.32020430332539 1.6094379124341
#> 6 LBTEF 6 6 2.26107917725546 1.79175946922805
#> 7 CBTR 3 3 1.04940762729587 1.09861228866811
#> 8 NMLB 10 9 2.46043656290491 2.30258509299405
#> 9 ANGB 4 4 1.63181278826841 1.38629436111989
#> 10 CUAL9M 5 5 1.81895733334165 1.6094379124341
#> 11 LVC9M 5 5 1.45781261313429 1.6094379124341
#> 12 TNPR9M 5 5 2.15936383275215 1.6094379124341
#> 13 PL9M 3 2 1.02393231699601 1.09861228866811
#> 14 STRP 4 4 1.70471635517281 1.38629436111989
#> 15 STRC 2 2 0.985051563686417 0.693147180559945
#> 16 PSTR 3 2 0.932902628052214 1.09861228866811
#> EC_I.rel EC_I.ens EC_I.V EC_I.boot.V
#> 1 0.994869227718287 4.95888170692978 0.000495550546246209 0.000483712338849248
#> 2 1.22552873323805 3.84349045523356 0.00026683714279372 0.000270031896212135
#> 3 0.806231732681647 3.66042740085471 0.00076741293709653 0.000765753466729798
#> 4 1.08868934988106 5.76714936682217 0.000644551217715297 0.000699114782445066
#> 5 0.820289054412 3.74418624882682 0.0005480962422548 0.000517967395505657
#> 6 1.26193231630002 9.59343660098374 0.000259759685726472 0.000270960747240493
#> 7 0.955211987086096 2.85595882482654 0.000312696844542415 0.000303746752454349
#> 8 1.06855402234261 11.709922542064 0.000496178249738945 0.000505419831711688
#> 9 1.17710410864701 5.11313535399957 0.000306008701151613 0.000308011811117831
#> 10 1.13018173567856 6.16542661257166 0.000397228605602063 0.000382066367282386
#> 11 0.90578990458197 4.29655102280072 0.000698631874341118 0.00066531132699232
#> 12 1.34168818571345 8.66562311895419 0.000264448274894998 0.000279996361013181
#> 13 0.932023360340673 2.78412131411744 0.000100041535943681 0.000101885631821939
#> 14 1.22969291586506 5.49982544890899 0.00021912035039574 0.000213669110846319
#> 15 1.42112900595031 2.67794996583331 2.53468656861686e-05 2.75749116254995e-05
#> 16 0.849164566676391 2.54187660232952 0.000206905486943159 0.000215626202139427
#> CS_I CS_I.max CS_I.rel CS_I.ens
#> 1 1.60715392433211 1.38629436111989 1.15931649828959 4.98859309107096
#> 2 1.44881563572518 1.09861228866811 1.31876882378736 4.25806842343285
#> 3 1.60685189446012 1.6094379124341 0.998393216691366 4.98708661445017
#> 4 1.94652505102181 1.6094379124341 1.20944401519528 7.0043056374023
#> 5 1.39390699808299 1.38629436111989 1.00549135679738 4.030566747009
#> 6 2.3831722498942 1.79175946922805 1.330073757568 10.839233139215
#> 7 1.12338192727968 1.09861228866811 1.02254629669362 3.07523686413742
#> 8 2.56080478714959 2.19722457733622 1.16547248449867 12.9462320853624
#> 9 1.69700114892879 1.38629436111989 1.22412757097122 5.45755642804107
#> 10 1.92688046691671 1.6094379124341 1.19723814881589 6.86805167421241
#> 11 1.59702066650884 1.6094379124341 0.992284731315619 4.93829764981337
#> 12 2.24730159981114 1.6094379124341 1.39632699245436 9.46216863896461
#> 13 0.999591034189098 0.693147180559945 1.44210502794168 2.71717037141627
#> 14 1.74920954558179 1.38629436111989 1.26178796844324 5.75005572221205
#> 15 0.97366806454962 0.693147180559945 1.40470608819769 2.64763837799998
#> 16 0.91829583405449 0.693147180559945 1.32482084585941 2.50501778435487
#> CS_I.V CS_I.boot.V I.t.stat
#> 1 0.00466900952090494 0.00480057355817968 -0.083123660050637
#> 2 0.00183098114336171 0.00187582523489003 -2.23647066374941
#> 3 0.00915269666156106 0.00931692085852008 -3.10514822627186
#> 4 0.00501290672204481 0.00517355690951426 -2.58385107753543
#> 5 0.00481441616742965 0.00488793329864121 -1.00646624014807
#> 6 0.00172264312694065 0.00188540992637979 -2.74217439229004
#> 7 0.00290287113955504 0.00298363121894339 -1.30452382793487
#> 8 0.00546163553548553 0.00546757466250246 -1.3003275918761
#> 9 0.00354899161566695 0.00363110411244662 -1.04992396937323
#> 10 0.00380714696318465 0.00434151206919941 -1.66442333074281
#> 11 0.00676974620846264 0.00669096782843366 -1.61083557606938
#> 12 0.00129552549169971 0.00131598463869385 -2.22646968440541
#> 13 7.02197242512667e-06 4.25209205129464e-05 2.35246259571922
#> 14 0.0020863467552808 0.00212048454008538 -0.926646485957522
#> 15 0.000443961107972778 0.000440238137447901 0.52546865211132
#> 16 0.00132275132275134 0.00145971081458055 0.373471875118422
#> I.t.df I.t.pvalue I.t.significance I.boot.z.df
#> 1 205.323489838581 0.933834195011031 ns 7
#> 2 220.068588438007 0.0263241034578902 * 4
#> 3 197.214845421711 0.00218182272218803 ** 8
#> 4 213.627424864319 0.0104369229742795 * 8
#> 5 208.16009186019 0.315359849464886 ns 7
#> 6 221.982338302534 0.00660128212793374 ** 10
#> 7 205.90491319267 0.193511253079244 ns 4
#> 8 199.746997945695 0.194987041994507 ns 17
#> 9 198.073409342984 0.295032389672131 ns 6
#> 10 204.664065671499 0.097558069731458 ns 8
#> 11 204.247107694347 0.108759859193219 ns 8
#> 12 242.577447747539 0.0269016983557465 * 8
#> 13 1837.93308927511 0.0187545059227561 * 3
#> 14 204.916304701679 0.3552001943646 ns 6
#> 15 187.669671190779 0.599877733009115 ns 2
#> 16 224.120762900574 0.709150296735105 ns 3
#> I.boot.z.stat I.boot.z.pvalue I.boot.z.significance
#> 1 0.0816151261682393 0.937237366880844 ns
#> 2 2.20804536110578 0.0918257677192241 ns
#> 3 3.08699009808722 0.0149576074571947 *
#> 4 2.53734329919595 0.0348546381941696 *
#> 5 0.989361829502098 0.355443761348068 ns
#> 6 2.63447567425041 0.0249696070188221 *
#> 7 1.27767390552231 0.270478762219057 ns
#> 8 1.30252773052818 0.210106229408213 ns
#> 9 1.03779040230213 0.339369867309314 ns
#> 10 1.57822986458477 0.153165342145742 ns
#> 11 1.60829881122977 0.146436407724478 ns
#> 12 2.18775796377732 0.0601308095874048 ns
#> 13 2.02010593122144 0.136642216305489 ns
#> 14 0.920412488631991 0.39285907429174 ns
#> 15 0.529555857008772 0.649326086935845 ns
#> 16 0.358406267034263 0.743776008270476 ns
#>
#> $mcintosh
#> Trait EC_No.Classes CS_No.Classes EC_D.Mc EC_E.Mc
#> 1 CUAL 5 4 0.393778012434178 0.480227786771547
#> 2 LNGS 3 3 0.358820738546382 0.525115218256116
#> 3 PTLC 5 5 0.316779500161785 0.386325070099539
#> 4 DSTA 5 5 0.417380876241608 0.509012408283666
#> 5 LFRT 5 4 0.338215427137732 0.412467026846746
#> 6 LBTEF 6 6 0.539900644138108 0.632092884556734
#> 7 CBTR 3 3 0.286749615427161 0.419642932289509
#> 8 NMLB 10 9 0.558974562677424 0.605947984498653
#> 9 ANGB 4 4 0.418145333938704 0.543941007506402
#> 10 CUAL9M 5 5 0.455147453452433 0.555070235829135
#> 11 LVC9M 5 5 0.356538441668976 0.434812664331503
#> 12 TNPR9M 5 5 0.515402077468806 0.62855312166947
#> 13 PL9M 3 2 0.301198604544138 0.440788265484237
#> 14 STRP 4 4 0.443181993303366 0.576509745249164
#> 15 STRC 2 2 0.292763414762376 0.571258413744031
#> 16 PSTR 3 2 0.261175379595452 0.382216387533749
#> CS_D.Mc CS_E.Mc M.boot.z.stat M.boot.z.df
#> 1 0.416968887221027 0.513065385542589 0.99460293625151 7
#> 2 0.40884307929476 0.565950226384141 3.46783277479897 4
#> 3 0.380225207834671 0.438612745225263 2.2738192752375 8
#> 4 0.486635921075666 0.561363930823417 3.25064028587058 8
#> 5 0.375861861492538 0.462484652422527 2.15010573810129 7
#> 6 0.598348264293068 0.662621632177028 5.92988531160087 10
#> 7 0.327215963767637 0.452956056123639 2.96146258220075 4
#> 8 0.601358283540837 0.624332795289677 2.43902555318006 17
#> 9 0.449791785009108 0.553452793870588 1.80927337245031 6
#> 10 0.502026774187731 0.579118209592271 3.88926220676601 8
#> 11 0.408042032313971 0.470701132572847 2.52849788059365 8
#> 12 0.573194332783244 0.661214287399217 4.19030542335567 8
#> 13 0.317162433070916 0.585385640236862 4.50532682556703 3
#> 14 0.478468357680793 0.58873829661372 3.85325830114453 6
#> 15 0.303603702882552 0.560360337349431 0.911854542963119 2
#> 16 0.275932675604997 0.50928801500014 0.819045753756123 3
#> M.boot.z.pvalue M.boot.z.significance
#> 1 0.353059203135146 ns
#> 2 0.0256341480264864 *
#> 3 0.052576089898046 ns
#> 4 0.0116898700454197 *
#> 5 0.0686029150382776 ns
#> 6 0.000145105134520755 **
#> 7 0.0414941513850029 *
#> 8 0.0259867089753573 *
#> 9 0.120396110387685 ns
#> 10 0.00461403041701568 **
#> 11 0.0353379983338816 *
#> 12 0.00303649104150158 **
#> 13 0.0204253515117484 *
#> 14 0.00842801033696131 **
#> 15 0.458100293127608 ns
#> 16 0.472768376779912 ns
#>
# }