R Markdown

##The following is written by Savanna van Mesdag, going through the relevant coding and analyses for the biodiversity analyses for the Warton slag bank and Hodbarrow.

#setwd#

#To run the following code to carry out the analyses, the following packages must be installed#

install.packages("iNEXT", repos =   "http://chao.stat.nthu.edu.tw/wordpress/software_download/")
## Installing package into 'C:/Users/Savanna/AppData/Local/R/win-library/4.3'
## (as 'lib' is unspecified)
## Warning: unable to access index for repository http://chao.stat.nthu.edu.tw/wordpress/software_download/src/contrib:
##   cannot open URL 'http://chao.stat.nthu.edu.tw/wordpress/software_download/src/contrib/PACKAGES'
## Warning: package 'iNEXT' is not available for this version of R
## 
## A version of this package for your version of R might be available elsewhere,
## see the ideas at
## https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages
## Warning: unable to access index for repository http://chao.stat.nthu.edu.tw/wordpress/software_download/bin/windows/contrib/4.3:
##   cannot open URL 'http://chao.stat.nthu.edu.tw/wordpress/software_download/bin/windows/contrib/4.3/PACKAGES'
install.packages('devtools', repos = "https://github.com/r-lib/devtools")
## Installing package into 'C:/Users/Savanna/AppData/Local/R/win-library/4.3'
## (as 'lib' is unspecified)
## Warning: unable to access index for repository https://github.com/r-lib/devtools/src/contrib:
##   cannot open URL 'https://github.com/r-lib/devtools/src/contrib/PACKAGES'
## Warning: package 'devtools' is not available for this version of R
## 
## A version of this package for your version of R might be available elsewhere,
## see the ideas at
## https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages
## Warning: unable to access index for repository https://github.com/r-lib/devtools/bin/windows/contrib/4.3:
##   cannot open URL 'https://github.com/r-lib/devtools/bin/windows/contrib/4.3/PACKAGES'
install.packages('AnneChao/iNEXT', repos =  "http://chao.stat.nthu.edu.tw/wordpress/software_download/")
## Installing package into 'C:/Users/Savanna/AppData/Local/R/win-library/4.3'
## (as 'lib' is unspecified)
## Warning: unable to access index for repository http://chao.stat.nthu.edu.tw/wordpress/software_download/src/contrib:
##   cannot open URL 'http://chao.stat.nthu.edu.tw/wordpress/software_download/src/contrib/PACKAGES'
## Warning: package 'AnneChao/iNEXT' is not available for this version of R
## 
## A version of this package for your version of R might be available elsewhere,
## see the ideas at
## https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages
## Warning: unable to access index for repository http://chao.stat.nthu.edu.tw/wordpress/software_download/bin/windows/contrib/4.3:
##   cannot open URL 'http://chao.stat.nthu.edu.tw/wordpress/software_download/bin/windows/contrib/4.3/PACKAGES'
install.packages("ggthemes", repos = "https://github.com/jrnold/ggthemes")
## Installing package into 'C:/Users/Savanna/AppData/Local/R/win-library/4.3'
## (as 'lib' is unspecified)
## Warning: unable to access index for repository https://github.com/jrnold/ggthemes/src/contrib:
##   cannot open URL 'https://github.com/jrnold/ggthemes/src/contrib/PACKAGES'
## Warning: package 'ggthemes' is not available for this version of R
## 
## A version of this package for your version of R might be available elsewhere,
## see the ideas at
## https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages
## Warning: unable to access index for repository https://github.com/jrnold/ggthemes/bin/windows/contrib/4.3:
##   cannot open URL 'https://github.com/jrnold/ggthemes/bin/windows/contrib/4.3/PACKAGES'
install.packages("vegan", repos = " https://github.com/vegandevs/vegan")
## Installing package into 'C:/Users/Savanna/AppData/Local/R/win-library/4.3'
## (as 'lib' is unspecified)
## Warning: unable to access index for repository   https://github.com/vegandevs/vegan/src/contrib:
##   cannot open URL '  https://github.com/vegandevs/vegan/src/contrib/PACKAGES'
## Warning: package 'vegan' is not available for this version of R
## 
## A version of this package for your version of R might be available elsewhere,
## see the ideas at
## https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages
## Warning: unable to access index for repository   https://github.com/vegandevs/vegan/bin/windows/contrib/4.3:
##   cannot open URL '  https://github.com/vegandevs/vegan/bin/windows/contrib/4.3/PACKAGES'

##The packages also need to be loaded prior to running the analyses and producing graphs#

library(devtools)
## Loading required package: usethis
library(iNEXT)
library(ggplot2)
library(ggthemes)
## Warning: package 'ggthemes' was built under R version 4.3.1
library(vegan)
## Loading required package: permute
## 
## Attaching package: 'permute'
## The following object is masked from 'package:devtools':
## 
##     check
## Loading required package: lattice
## This is vegan 2.6-4

#Hodbarrow Data#

#Loading the Hodbarrow data#

urlfile1 <- 'https://raw.githubusercontent.com/Savannankvm/Biodiversity-analyses-for-Warton-and-Hodbarrow/PhD-files/Hodbarrow_Abundance_Data.csv'

Hodbarrow_Nos <-read.csv(urlfile1)

print(Hodbarrow_Nos)
##     Quadrat_1 Quadrat_2 Quadrat_3 Quadrat_4 Quadrat_5 Quadrat_6 Quadrat_7
## 1           0         0         0         0         0         0         0
## 2           0         0         0         0         0         0         0
## 3           0         0         0         0         0         0         0
## 4           0         0         0         0         0         0         0
## 5           0         0         0         0         0         0         0
## 6           0         0         0         7         0         0         0
## 7           0        70       189         0         0         0         0
## 8           0         0         0         0         0         0         0
## 9           0         0         0         0         0         0         0
## 10          0         0         0         0         0         0         0
## 11          0         0         0         0         0         0         0
## 12          0         0         1         0         0         0         0
## 13          0         0         0         0         0         0         0
## 14          0         0         0         0         0         0         0
## 15          0         0         0         0         0         0         0
## 16          0         0         0         0         0         0         0
## 17          0         0         0         0         0         0         0
## 18          0         0         0         0         0         0         0
## 19          0         0         0         0         0         0         0
## 20          0         0         0         0         0         0         0
## 21          0         0         0         0         0         0         0
## 22          0         0         0         0         0         0         0
## 23          0         0         0         0         0         0         0
## 24          0         0        60         0         0         0         0
## 25          0         0         0         0         0         0         0
## 26          0         0         0         0         0         0         0
## 27          0         0         0        42         0         0         0
## 28          0         0         0         0         0         0         0
## 29          0         0         0         0         3         0         2
## 30          0         0         1         0         0         0         0
## 31          0         0         0         3         2         1         7
## 32          0         0         0         0         1         0         0
## 33          0         0         0         0         0         0         0
## 34          0         4         0         4         5         0         1
## 35          0         0         0         0         0         0         0
## 36          0         0         0         1         0         0         0
## 37          0         0         0         0         0         0         0
## 38          0         0         0         0         0         0         0
## 39          0         0         0         0         0         0         0
## 40          0         0         0         0         0         0         0
## 41          0         0         0         0         0         0         0
## 42          0         0         0         0         0         0         0
## 43          0         0         0         0         0         0        10
## 44          0         0         0         0         0         0         0
## 45          0         0         0         0         0         0         0
## 46          0         0         0         0         0         0         0
## 47          0         0         0         0         0         0         0
## 48          0         0         0         0         0         0         0
## 49          0         0         0         0         0         0         0
## 50          0         0         0        10         0         0         0
## 51          0         0         0        31         0         0         0
## 52          0         0         0         0         0         0         0
## 53          0         0         0         0        36         0        31
## 54          0         0         0         0         0         0         0
## 55         10         0         4         2        44         0        33
## 56          0         0         0         0         0         0         0
## 57          0         0         0         0         0         0         0
## 58          0         0         0         0         0         0         0
## 59          0         0         0         0         0         0         0
## 60          0         0         0         0         0         0         0
## 61          0         0         0         0         0         0         0
## 62          0         0         0         0         0         0         0
## 63          0         0         0         0         0         0         0
## 64          0         0         0         0         0         0         0
## 65          0         0         0         0         0         0         0
## 66          0         0         0         0         0         0         0
## 67          0         0         0         0         0         0         0
## 68          0         0         0         0         0         0         0
## 69          0         0         0         0         0         0         0
## 70          0         0         0         0         0         0         0
## 71         47         0         0         0        23        78        10
## 72          0         0         0        18         0         0         0
## 73          0         0         0         0         0         0         0
## 74          0         0         0         0         0         0         0
## 75          0         0         0         0         0         0         0
## 76          0         0         0         0         0         0         0
## 77          0         0         0       160         0         0         0
## 78          0         0         0         0         0         0         0
## 79          0         0         0         0         0         0         0
## 80          0         0         0         0         0         0         0
## 81          0         0         0         0         0         0         0
## 82          0         0         0         0         0         0         0
## 83          0         0         0         0        16         2        43
## 84          0         0         0         0         0         0         0
## 85          2         0         2         1         6         0         0
## 86          0         2         0         0         1         6         6
## 87          0         0         0         0         0         0         0
## 88          0         0         0         0         0         0         0
## 89          0         0         0         0        57         0        20
## 90          0         0         0         0         0         0         0
## 91          2         0         0         0         0         0         0
## 92          0         0         0        91         0         0         0
## 93          0         0         0         0         0         0         0
## 94          0         5         1       111         2         0         0
## 95          0         0         0         0         0         0         0
## 96          0         0         0         0         0         0         0
## 97          0         0         0         0         0         0         0
## 98          2         0         0        91        39         0         0
## 99          0         0         0         0        50         0         0
## 100         0         0         0         5        20         0        29
## 101         0         0         0         0         0         0         0
## 102         0        69        46         0        55         0         0
## 103         0         0         0         0         0         0         0
## 104         0         0         0         0         0         0         0
## 105         0         0         0         0         0         0         0
## 106         0         0         0         0         0         0         0
## 107         0         0         0         0         0         0         0
## 108         0         0         0         0         0         0         2
## 109         0         0         0         0         0         0         0
## 110         0         0         0         0         0         0         0
## 111         0         0         0         0         0         0         0
## 112         0         0         0         0         0         0         0
## 113         0         0         0         0         0         0         0
## 114         0         0         0         0         0         0         0
## 115         0         0         0         0         0         0         0
## 116         0         0         0         0         0         0         0
## 117         0         0         0         0         0         0         0
## 118         0         0         0         0         0         0         0
## 119         0         0         0         0         0         0         0
## 120         0         0         0         0         0         0         0
## 121         0         0         0         0         0         0         0
## 122         0         0         0         0         0         0         0
## 123         0         0         0         0         0         0         0
## 124         0         0         0         0         0         0         0
## 125         0         0         0         0         0         0         0
## 126         0         0         0         0         0         0         0
## 127         0         0         0         0         0         0         0
## 128         0         0         0         0         0         2         1
## 129         0         0         0         0         0         0         0
## 130         0       216       253         0         0         7         0
## 131       150        30        60         0        70         0         0
## 132         0         0         0         0         0         0         0
## 133         0         0         0         0         0         0         0
## 134         0         0         0         0         0         0        21
## 135         0         0         0         0         0         0         0
## 136         0         0         0         0         0         0         0
## 137         0         0         0         0         3         0         0
## 138         0         0         0         0         0         0         0
## 139         0         0         0         0         0         0         0
## 140         0         0         0         0         0         0         0
## 141         0         0         0         0         0         0         0
## 142         0         0         0         0         0         0         0
## 143         0         0         0         0         0        10         0

#colSums to establish sample size for each of the quadrats.

colSums(Hodbarrow_Nos)
## Quadrat_1 Quadrat_2 Quadrat_3 Quadrat_4 Quadrat_5 Quadrat_6 Quadrat_7 
##       213       396       617       577       433       106       216

#Setting m to sample size for Quadrat 1. This will give me observed #qD value that will be most representative for Quadrat and Community. Will do the same #for the other communities below.

m <- c(213)

Hodbarrow_Datam <- iNEXT(Hodbarrow_Nos, q=c(0), datatype= "abundance", size = m)

Hodbarrow_Datam
## Compare 7 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 213     6 1.0000  0  3  0  0  0  0  0  0  0   1
## 2  Quadrat_2 396     7 1.0000  0  1  0  1  1  0  0  0  0   0
## 3  Quadrat_3 617    10 0.9951  3  1  0  1  0  0  0  0  0   0
## 4  Quadrat_4 577    15 0.9965  2  1  1  1  1  0  1  0  0   1
## 5  Quadrat_5 433    18 0.9954  2  2  2  0  1  1  0  0  0   0
## 6  Quadrat_6 106     7 0.9909  1  2  0  0  0  1  1  0  0   1
## 7  Quadrat_7 216    14 0.9908  2  2  0  0  0  1  1  0  0   2
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 213      Observed       0  6.000000  4.560816  7.439184 1.0000000
## 2   Quadrat_2 213   Rarefaction       0  6.721814  6.064643  7.378985 0.9961347
## 3   Quadrat_2 395   Rarefaction       0  7.000000  6.356812  7.643188 1.0000000
## 4   Quadrat_2 396      Observed       0  7.000000  6.356621  7.643379 1.0000000
## 5   Quadrat_2 397 Extrapolation       0  7.000000  6.356398  7.643602 1.0000000
## 6   Quadrat_3 213   Rarefaction       0  7.424413  6.169247  8.679578 0.9912065
## 7   Quadrat_3 616   Rarefaction       0  9.995138  7.068949 12.921327 0.9951378
## 8   Quadrat_3 617      Observed       0 10.000000  7.069803 12.930197 0.9951430
## 9   Quadrat_3 618 Extrapolation       0 10.004857  7.070331 12.939383 0.9951483
## 10  Quadrat_4 213   Rarefaction       0 12.785465 11.563606 14.007323 0.9881773
## 11  Quadrat_4 576   Rarefaction       0 14.996534 13.220065 16.773003 0.9965338
## 12  Quadrat_4 577      Observed       0 15.000000 13.222088 16.777912 0.9965398
## 13  Quadrat_4 578 Extrapolation       0 15.003460 13.223940 16.782980 0.9965458
## 14  Quadrat_5 213   Rarefaction       0 16.158389 14.840349 17.476429 0.9859379
## 15  Quadrat_5 432   Rarefaction       0 17.995381 16.305535 19.685227 0.9953811
## 16  Quadrat_5 433      Observed       0 18.000000 16.308405 19.691595 0.9954023
## 17  Quadrat_5 434 Extrapolation       0 18.004598 16.311249 19.697946 0.9954235
## 18  Quadrat_6 105   Rarefaction       0  6.990566  5.303976  8.677156 0.9905660
## 19  Quadrat_6 106      Observed       0  7.000000  5.299622  8.700378 0.9909122
## 20  Quadrat_6 107 Extrapolation       0  7.009088  5.294922  8.723254 0.9912457
## 21  Quadrat_6 213 Extrapolation       0  7.243108  4.293901 10.192315 0.9998336
## 22  Quadrat_7 213   Rarefaction       0 13.971964 11.886101 16.057827 0.9905685
## 23  Quadrat_7 215   Rarefaction       0 13.990741 11.889664 16.091818 0.9907407
## 24  Quadrat_7 216      Observed       0 14.000000 11.891284 16.108716 0.9908261
## 25  Quadrat_7 217 Extrapolation       0 14.009174 11.892591 16.125757 0.9909106
##       SC.LCL    SC.UCL
## 1  0.9917852 1.0000000
## 2  0.9938488 0.9984206
## 3  0.9973244 1.0000000
## 4  0.9981019 1.0000000
## 5  0.9981114 1.0000000
## 6  0.9861614 0.9962516
## 7  0.9904616 0.9998139
## 8  0.9901497 1.0000000
## 9  0.9901580 1.0000000
## 10 0.9840657 0.9922889
## 11 0.9931711 0.9998965
## 12 0.9929978 1.0000000
## 13 0.9930071 1.0000000
## 14 0.9810024 0.9908734
## 15 0.9905977 1.0000000
## 16 0.9906228 1.0000000
## 17 0.9906479 1.0000000
## 18 0.9692077 1.0000000
## 19 0.9690973 1.0000000
## 20 0.9695976 1.0000000
## 21 0.9890519 1.0000000
## 22 0.9792862 1.0000000
## 23 0.9794163 1.0000000
## 24 0.9792799 1.0000000
## 25 0.9794121 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 1.0000000 213      Observed       0  6.000000  3.646233  8.353767
## 2   Quadrat_2 0.9961347 213   Rarefaction       0  6.721814  5.981457  7.462171
## 3   Quadrat_2 1.0000000 396      Observed       0  7.000000  6.217566  7.782434
## 4   Quadrat_3 0.9912065 213   Rarefaction       0  7.424413  4.162698 10.686128
## 5   Quadrat_3 0.9951378 616   Rarefaction       0  9.992800  3.823044 16.162556
## 6   Quadrat_3 0.9951430 617      Observed       0 10.000000  3.826402 16.173598
## 7   Quadrat_3 0.9951483 618 Extrapolation       0 10.004857  3.827757 16.181957
## 8   Quadrat_4 0.9881773 213   Rarefaction       0 12.785465 11.123208 14.447721
## 9   Quadrat_4 0.9965338 576   Rarefaction       0 14.995943 12.193834 17.798053
## 10  Quadrat_4 0.9965398 577      Observed       0 15.000000 12.195799 17.804201
## 11  Quadrat_4 0.9965458 578 Extrapolation       0 15.003460 12.198193 17.808728
## 12  Quadrat_5 0.9859379 213   Rarefaction       0 16.158389 14.411232 17.905545
## 13  Quadrat_5 0.9953811 431   Rarefaction       0 17.993045 15.246636 20.739454
## 14  Quadrat_5 0.9954023 433      Observed       0 18.000000 15.248518 20.751482
## 15  Quadrat_5 0.9954235 434 Extrapolation       0 18.004598 15.247670 20.761525
## 16  Quadrat_6 0.9905660 104   Rarefaction       0  6.981784  3.290574 10.672994
## 17  Quadrat_6 0.9909122 106      Observed       0  7.000000  3.282392 10.717608
## 18  Quadrat_6 0.9912457 107 Extrapolation       0  7.009088  3.264401 10.753775
## 19  Quadrat_6 0.9998336 213 Extrapolation       0  7.243108  2.764613 11.721602
## 20  Quadrat_7 0.9905685 213   Rarefaction       0 13.971964 10.428832 17.515096
## 21  Quadrat_7 0.9907407 215   Rarefaction       0 13.988843 10.459847 17.517840
## 22  Quadrat_7 0.9908261 216      Observed       0 14.000000 10.459642 17.540358
## 23  Quadrat_7 0.9909106 217 Extrapolation       0 14.009174 10.455870 17.562478
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator      s.e.       LCL
## 1   Quadrat_1  Species richness  6.000000  6.000000 1.0050059  6.000000
## 2   Quadrat_1 Shannon diversity  2.352515  2.381769 0.1704931  2.047609
## 3   Quadrat_1 Simpson diversity  1.827847  1.835013 0.1235923  1.592777
## 4   Quadrat_2  Species richness  7.000000  7.000000 0.4249070  7.000000
## 5   Quadrat_2 Shannon diversity  3.543784  3.571485 0.1582880  3.261246
## 6   Quadrat_2 Simpson diversity  2.738570  2.750677 0.1603008  2.436493
## 7   Quadrat_3  Species richness 10.000000 14.492707 4.4180641 10.000000
## 8   Quadrat_3 Shannon diversity  4.294224  4.344098 0.1567743  4.036826
## 9   Quadrat_3 Simpson diversity  3.490350  3.504518 0.1385343  3.232996
## 10  Quadrat_4  Species richness 15.000000 16.996534 2.7701247 15.000000
## 11  Quadrat_4 Shannon diversity  7.241096  7.348354 0.3097092  6.741335
## 12  Quadrat_4 Simpson diversity  5.766302  5.814416 0.2561532  5.312365
## 13  Quadrat_5  Species richness 18.000000 18.997691 3.0906588 18.000000
## 14  Quadrat_5 Shannon diversity 11.090385 11.338175 0.4305598 10.494293
## 15  Quadrat_5 Simpson diversity  9.516725  9.708117 0.4156363  8.893485
## 16  Quadrat_6  Species richness  7.000000  7.247642 1.7481356  7.000000
## 17  Quadrat_6 Shannon diversity  2.675814  2.762979 0.3270684  2.121937
## 18  Quadrat_6 Simpson diversity  1.789742  1.803305 0.1929016  1.425225
## 19  Quadrat_7  Species richness 14.000000 14.995370 2.1921126 14.000000
## 20  Quadrat_7 Shannon diversity  9.347900  9.678925 0.4730633  8.751738
## 21  Quadrat_7 Simpson diversity  7.940095  8.204947 0.4806902  7.262812
##          UCL
## 1   7.969775
## 2   2.715930
## 3   2.077249
## 4   7.832802
## 5   3.881724
## 6   3.064861
## 7  23.151953
## 8   4.651370
## 9   3.776040
## 10 22.425878
## 11  7.955373
## 12  6.316467
## 13 25.055270
## 14 12.182056
## 15 10.522749
## 16 10.673924
## 17  3.404022
## 18  2.181386
## 19 19.291832
## 20 10.606112
## 21  9.147082
n <- c(396)

Hodbarrow_Datan <- iNEXT(Hodbarrow_Nos, q=c(0), datatype= "abundance", size = n)

Hodbarrow_Datan
## Compare 7 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 213     6 1.0000  0  3  0  0  0  0  0  0  0   1
## 2  Quadrat_2 396     7 1.0000  0  1  0  1  1  0  0  0  0   0
## 3  Quadrat_3 617    10 0.9951  3  1  0  1  0  0  0  0  0   0
## 4  Quadrat_4 577    15 0.9965  2  1  1  1  1  0  1  0  0   1
## 5  Quadrat_5 433    18 0.9954  2  2  2  0  1  1  0  0  0   0
## 6  Quadrat_6 106     7 0.9909  1  2  0  0  0  1  1  0  0   1
## 7  Quadrat_7 216    14 0.9908  2  2  0  0  0  1  1  0  0   2
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 212   Rarefaction       0  6.000000  4.874499  7.125501 1.0000000
## 2   Quadrat_1 213      Observed       0  6.000000  4.873738  7.126262 1.0000000
## 3   Quadrat_1 214 Extrapolation       0  6.000000  4.872499  7.127501 1.0000000
## 4   Quadrat_1 396 Extrapolation       0  6.000000  4.577897  7.422103 1.0000000
## 5   Quadrat_2 396      Observed       0  7.000000  6.462877  7.537123 1.0000000
## 6   Quadrat_3 396   Rarefaction       0  8.781349  6.842539 10.720159 0.9936874
## 7   Quadrat_3 616   Rarefaction       0  9.995138  7.368993 12.621282 0.9951378
## 8   Quadrat_3 617      Observed       0 10.000000  7.370731 12.629269 0.9951430
## 9   Quadrat_3 618 Extrapolation       0 10.004857  7.371974 12.637740 0.9951483
## 10  Quadrat_4 396   Rarefaction       0 14.231402 12.809708 15.653095 0.9946438
## 11  Quadrat_4 576   Rarefaction       0 14.996534 13.277411 16.715657 0.9965338
## 12  Quadrat_4 577      Observed       0 15.000000 13.278999 16.721001 0.9965398
## 13  Quadrat_4 578 Extrapolation       0 15.003460 13.280434 16.726487 0.9965458
## 14  Quadrat_5 396   Rarefaction       0 17.813697 16.075281 19.552114 0.9945169
## 15  Quadrat_5 432   Rarefaction       0 17.995381 16.129664 19.861098 0.9953811
## 16  Quadrat_5 433      Observed       0 18.000000 16.130523 19.869477 0.9954023
## 17  Quadrat_5 434 Extrapolation       0 18.004598 16.131332 19.877864 0.9954235
## 18  Quadrat_6 105   Rarefaction       0  6.990566  5.591962  8.389170 0.9905660
## 19  Quadrat_6 106      Observed       0  7.000000  5.596670  8.403330 0.9909122
## 20  Quadrat_6 107 Extrapolation       0  7.009088  5.599886  8.418289 0.9912457
## 21  Quadrat_6 396 Extrapolation       0  7.247637  4.707826  9.787448 0.9999998
## 22  Quadrat_7 215   Rarefaction       0 13.990741 12.229009 15.752473 0.9907407
## 23  Quadrat_7 216      Observed       0 14.000000 12.234034 15.765966 0.9908261
## 24  Quadrat_7 217 Extrapolation       0 14.009174 12.238666 15.779682 0.9909106
## 25  Quadrat_7 396 Extrapolation       0 14.807371 12.129460 17.485283 0.9982673
##       SC.LCL    SC.UCL
## 1  0.9937536 1.0000000
## 2  0.9933098 1.0000000
## 3  0.9933630 1.0000000
## 4  0.9980284 1.0000000
## 5  0.9979226 1.0000000
## 6  0.9897795 0.9975952
## 7  0.9908687 0.9994069
## 8  0.9904732 0.9998128
## 9  0.9904808 0.9998157
## 10 0.9913536 0.9979341
## 11 0.9928837 1.0000000
## 12 0.9926581 1.0000000
## 13 0.9926670 1.0000000
## 14 0.9889183 1.0000000
## 15 0.9894658 1.0000000
## 16 0.9893874 1.0000000
## 17 0.9894078 1.0000000
## 18 0.9748011 1.0000000
## 19 0.9741132 1.0000000
## 20 0.9746349 1.0000000
## 21 0.9984540 1.0000000
## 22 0.9813484 1.0000000
## 23 0.9812492 1.0000000
## 24 0.9813596 1.0000000
## 25 0.9923454 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 1.0000000 213      Observed       0  6.000000  4.324835  7.675165
## 2   Quadrat_2 1.0000000 396      Observed       0  7.000000  6.286843  7.713157
## 3   Quadrat_3 0.9936874 396   Rarefaction       0  8.781349  4.487362 13.075336
## 4   Quadrat_3 0.9951378 616   Rarefaction       0  9.992800  4.810189 15.175411
## 5   Quadrat_3 0.9951430 617      Observed       0 10.000000  4.813686 15.186314
## 6   Quadrat_3 0.9951483 618 Extrapolation       0 10.004857  4.815119 15.194595
## 7   Quadrat_4 0.9946438 396   Rarefaction       0 14.231401 11.509275 16.953528
## 8   Quadrat_4 0.9965338 576   Rarefaction       0 14.995943 11.517272 18.474614
## 9   Quadrat_4 0.9965398 577      Observed       0 15.000000 11.519136 18.480864
## 10  Quadrat_4 0.9965458 578 Extrapolation       0 15.003460 11.520258 18.486663
## 11  Quadrat_5 0.9945170 396   Rarefaction       0 17.813697 13.131558 22.495837
## 12  Quadrat_5 0.9953811 431   Rarefaction       0 17.993045 12.978437 23.007653
## 13  Quadrat_5 0.9954023 433      Observed       0 18.000000 12.977081 23.022919
## 14  Quadrat_5 0.9954235 434 Extrapolation       0 18.004598 12.972933 23.036262
## 15  Quadrat_6 0.9905660 104   Rarefaction       0  6.981784  4.812760  9.150808
## 16  Quadrat_6 0.9909122 106      Observed       0  7.000000  4.814550  9.185450
## 17  Quadrat_6 0.9912457 107 Extrapolation       0  7.009088  4.805995  9.212181
## 18  Quadrat_6 0.9999998 396 Extrapolation       0  7.247637  4.540800  9.954473
## 19  Quadrat_7 0.9907407 215   Rarefaction       0 13.988843 10.816895 17.160792
## 20  Quadrat_7 0.9908261 216      Observed       0 14.000000 10.819421 17.180579
## 21  Quadrat_7 0.9909106 217 Extrapolation       0 14.009174 10.817412 17.200936
## 22  Quadrat_7 0.9982673 396 Extrapolation       0 14.807371 10.558581 19.056162
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator      s.e.       LCL
## 1   Quadrat_1  Species richness  6.000000  6.000000 0.7464968  6.000000
## 2   Quadrat_1 Shannon diversity  2.352515  2.381769 0.1635181  2.061280
## 3   Quadrat_1 Simpson diversity  1.827847  1.835013 0.1087023  1.621960
## 4   Quadrat_2  Species richness  7.000000  7.000000 0.4118868  7.000000
## 5   Quadrat_2 Shannon diversity  3.543784  3.571485 0.1419432  3.293282
## 6   Quadrat_2 Simpson diversity  2.738570  2.750677 0.1270084  2.501745
## 7   Quadrat_3  Species richness 10.000000 14.492707 4.9552532 10.000000
## 8   Quadrat_3 Shannon diversity  4.294224  4.344098 0.1414689  4.066824
## 9   Quadrat_3 Simpson diversity  3.490350  3.504518 0.1263786  3.256821
## 10  Quadrat_4  Species richness 15.000000 16.996534 2.4680674 15.000000
## 11  Quadrat_4 Shannon diversity  7.241096  7.348354 0.2772438  6.804966
## 12  Quadrat_4 Simpson diversity  5.766302  5.814416 0.2411525  5.341765
## 13  Quadrat_5  Species richness 18.000000 18.997691 2.9671498 18.000000
## 14  Quadrat_5 Shannon diversity 11.090385 11.338175 0.3598621 10.632858
## 15  Quadrat_5 Simpson diversity  9.516725  9.708117 0.3481786  9.025700
## 16  Quadrat_6  Species richness  7.000000  7.247642 1.7813040  7.000000
## 17  Quadrat_6 Shannon diversity  2.675814  2.762979 0.3176929  2.140313
## 18  Quadrat_6 Simpson diversity  1.789742  1.803305 0.1959417  1.419267
## 19  Quadrat_7  Species richness 14.000000 14.995370 2.1388733 14.000000
## 20  Quadrat_7 Shannon diversity  9.347900  9.678925 0.4313244  8.833545
## 21  Quadrat_7 Simpson diversity  7.940095  8.204947 0.4258172  7.370361
##          UCL
## 1   7.463107
## 2   2.702259
## 3   2.048066
## 4   7.807283
## 5   3.849689
## 6   2.999609
## 7  24.204825
## 8   4.621372
## 9   3.752216
## 10 21.833857
## 11  7.891742
## 12  6.287066
## 13 24.813197
## 14 12.043491
## 15 10.390535
## 16 10.738933
## 17  3.385646
## 18  2.187344
## 19 19.187485
## 20 10.524306
## 21  9.039533
o <- c(617)

Hodbarrow_Datao <- iNEXT(Hodbarrow_Nos, q=c(0), datatype= "abundance", size = o)

Hodbarrow_Datao
## Compare 7 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 213     6 1.0000  0  3  0  0  0  0  0  0  0   1
## 2  Quadrat_2 396     7 1.0000  0  1  0  1  1  0  0  0  0   0
## 3  Quadrat_3 617    10 0.9951  3  1  0  1  0  0  0  0  0   0
## 4  Quadrat_4 577    15 0.9965  2  1  1  1  1  0  1  0  0   1
## 5  Quadrat_5 433    18 0.9954  2  2  2  0  1  1  0  0  0   0
## 6  Quadrat_6 106     7 0.9909  1  2  0  0  0  1  1  0  0   1
## 7  Quadrat_7 216    14 0.9908  2  2  0  0  0  1  1  0  0   2
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 212   Rarefaction       0  6.000000  4.935235  7.064765 1.0000000
## 2   Quadrat_1 213      Observed       0  6.000000  4.933811  7.066189 1.0000000
## 3   Quadrat_1 214 Extrapolation       0  6.000000  4.931591  7.068409 1.0000000
## 4   Quadrat_1 617 Extrapolation       0  6.000000  4.148292  7.851708 1.0000000
## 5   Quadrat_2 395   Rarefaction       0  7.000000  6.132281  7.867719 1.0000000
## 6   Quadrat_2 396      Observed       0  7.000000  6.131564  7.868436 1.0000000
## 7   Quadrat_2 397 Extrapolation       0  7.000000  6.131327  7.868673 1.0000000
## 8   Quadrat_2 617 Extrapolation       0  7.000000  6.073200  7.926800 1.0000000
## 9   Quadrat_3 617      Observed       0 10.000000  7.165268 12.834732 0.9951430
## 10  Quadrat_4 576   Rarefaction       0 14.996534 12.903901 17.089167 0.9965338
## 11  Quadrat_4 577      Observed       0 15.000000 12.904710 17.095290 0.9965398
## 12  Quadrat_4 578 Extrapolation       0 15.003460 12.905474 17.101446 0.9965458
## 13  Quadrat_4 617 Extrapolation       0 15.133831 12.929724 17.337939 0.9967717
## 14  Quadrat_5 432   Rarefaction       0 17.995381 15.840920 20.149842 0.9953811
## 15  Quadrat_5 433      Observed       0 18.000000 15.844221 20.155779 0.9954023
## 16  Quadrat_5 434 Extrapolation       0 18.004598 15.847228 20.161967 0.9954235
## 17  Quadrat_5 617 Extrapolation       0 18.571214 16.092286 21.050142 0.9980347
## 18  Quadrat_6 105   Rarefaction       0  6.990566  5.464409  8.516723 0.9905660
## 19  Quadrat_6 106      Observed       0  7.000000  5.466405  8.533595 0.9909122
## 20  Quadrat_6 107 Extrapolation       0  7.009088  5.464838  8.553337 0.9912457
## 21  Quadrat_6 617 Extrapolation       0  7.247642  3.631243 10.864040 1.0000000
## 22  Quadrat_7 215   Rarefaction       0 13.990741 12.057162 15.924320 0.9907407
## 23  Quadrat_7 216      Observed       0 14.000000 12.061756 15.938244 0.9908261
## 24  Quadrat_7 217 Extrapolation       0 14.009174 12.065346 15.953002 0.9909106
## 25  Quadrat_7 617 Extrapolation       0 14.971079 11.371026 18.571131 0.9997761
##       SC.LCL    SC.UCL
## 1  0.9924166 1.0000000
## 2  0.9920456 1.0000000
## 3  0.9920995 1.0000000
## 4  0.9989808 1.0000000
## 5  0.9974625 1.0000000
## 6  0.9983234 1.0000000
## 7  0.9983318 1.0000000
## 8  0.9994508 1.0000000
## 9  0.9902912 0.9999948
## 10 0.9924738 1.0000000
## 11 0.9924092 1.0000000
## 12 0.9924187 1.0000000
## 13 0.9927729 1.0000000
## 14 0.9915402 0.9992219
## 15 0.9912767 0.9995280
## 16 0.9912987 0.9995484
## 17 0.9946569 1.0000000
## 18 0.9727445 1.0000000
## 19 0.9711926 1.0000000
## 20 0.9716727 1.0000000
## 21 0.9994175 1.0000000
## 22 0.9815290 0.9999525
## 23 0.9809717 1.0000000
## 24 0.9810890 1.0000000
## 25 0.9972396 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 1.0000000 213      Observed       0  6.000000  3.979565  8.020435
## 2   Quadrat_2 1.0000000 396      Observed       0  7.000000  6.027236  7.972764
## 3   Quadrat_3 0.9951430 617      Observed       0 10.000000  4.767604 15.232396
## 4   Quadrat_4 0.9965338 576   Rarefaction       0 14.995943 11.086584 18.905302
## 5   Quadrat_4 0.9965398 577      Observed       0 15.000000 11.087324 18.912676
## 6   Quadrat_4 0.9965458 578 Extrapolation       0 15.003460 11.088349 18.918571
## 7   Quadrat_4 0.9967717 617 Extrapolation       0 15.133831 11.101052 19.166611
## 8   Quadrat_5 0.9953811 431   Rarefaction       0 17.993045 15.078011 20.908079
## 9   Quadrat_5 0.9954023 433      Observed       0 18.000000 15.083306 20.916694
## 10  Quadrat_5 0.9954235 434 Extrapolation       0 18.004598 15.084994 20.924201
## 11  Quadrat_5 0.9980347 617 Extrapolation       0 18.571214 15.240263 21.902165
## 12  Quadrat_6 0.9905660 104   Rarefaction       0  6.981784  4.023116  9.940452
## 13  Quadrat_6 0.9909122 106      Observed       0  7.000000  4.017372  9.982628
## 14  Quadrat_6 0.9912457 107 Extrapolation       0  7.009088  4.002209 10.015967
## 15  Quadrat_6 1.0000000 617 Extrapolation       0  7.247642  3.550841 10.944442
## 16  Quadrat_7 0.9907407 215   Rarefaction       0 13.988843 10.983983 16.993703
## 17  Quadrat_7 0.9908261 216      Observed       0 14.000000 10.987094 17.012906
## 18  Quadrat_7 0.9909106 217 Extrapolation       0 14.009174 10.986279 17.032069
## 19  Quadrat_7 0.9997761 617 Extrapolation       0 14.971079 10.787009 19.155149
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator      s.e.       LCL
## 1   Quadrat_1  Species richness  6.000000  6.000000 1.0016442  6.000000
## 2   Quadrat_1 Shannon diversity  2.352515  2.381769 0.1343412  2.118466
## 3   Quadrat_1 Simpson diversity  1.827847  1.835013 0.1027838  1.633560
## 4   Quadrat_2  Species richness  7.000000  7.000000 0.5041124  7.000000
## 5   Quadrat_2 Shannon diversity  3.543784  3.571485 0.1573847  3.263017
## 6   Quadrat_2 Simpson diversity  2.738570  2.750677 0.1524920  2.451798
## 7   Quadrat_3  Species richness 10.000000 14.492707 4.7370593 10.000000
## 8   Quadrat_3 Shannon diversity  4.294224  4.344098 0.1904334  3.970855
## 9   Quadrat_3 Simpson diversity  3.490350  3.504518 0.1769519  3.157699
## 10  Quadrat_4  Species richness 15.000000 16.996534 3.3543161 15.000000
## 11  Quadrat_4 Shannon diversity  7.241096  7.348354 0.2821640  6.795322
## 12  Quadrat_4 Simpson diversity  5.766302  5.814416 0.2433963  5.337368
## 13  Quadrat_5  Species richness 18.000000 18.997691 3.6674479 18.000000
## 14  Quadrat_5 Shannon diversity 11.090385 11.338175 0.3789992 10.595350
## 15  Quadrat_5 Simpson diversity  9.516725  9.708117 0.3692233  8.984453
## 16  Quadrat_6  Species richness  7.000000  7.247642 1.7564079  7.000000
## 17  Quadrat_6 Shannon diversity  2.675814  2.762979 0.2997441  2.175492
## 18  Quadrat_6 Simpson diversity  1.789742  1.803305 0.1801559  1.450206
## 19  Quadrat_7  Species richness 14.000000 14.995370 2.3481825 14.000000
## 20  Quadrat_7 Shannon diversity  9.347900  9.678925 0.4688138  8.760067
## 21  Quadrat_7 Simpson diversity  7.940095  8.204947 0.4724409  7.278980
##          UCL
## 1   7.963187
## 2   2.645073
## 3   2.036466
## 4   7.988042
## 5   3.879953
## 6   3.049556
## 7  23.777172
## 8   4.717340
## 9   3.851337
## 10 23.570873
## 11  7.901385
## 12  6.291464
## 13 26.185756
## 14 12.080999
## 15 10.431782
## 16 10.690138
## 17  3.350467
## 18  2.156404
## 19 19.597723
## 20 10.597784
## 21  9.130914
p <- c(577)

Hodbarrow_Datap <- iNEXT(Hodbarrow_Nos, q=c(0), datatype= "abundance", size = p)

Hodbarrow_Datap
## Compare 7 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 213     6 1.0000  0  3  0  0  0  0  0  0  0   1
## 2  Quadrat_2 396     7 1.0000  0  1  0  1  1  0  0  0  0   0
## 3  Quadrat_3 617    10 0.9951  3  1  0  1  0  0  0  0  0   0
## 4  Quadrat_4 577    15 0.9965  2  1  1  1  1  0  1  0  0   1
## 5  Quadrat_5 433    18 0.9954  2  2  2  0  1  1  0  0  0   0
## 6  Quadrat_6 106     7 0.9909  1  2  0  0  0  1  1  0  0   1
## 7  Quadrat_7 216    14 0.9908  2  2  0  0  0  1  1  0  0   2
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 212   Rarefaction       0  6.000000  4.675838  7.324162 1.0000000
## 2   Quadrat_1 213      Observed       0  6.000000  4.674231  7.325769 1.0000000
## 3   Quadrat_1 214 Extrapolation       0  6.000000  4.672383  7.327617 1.0000000
## 4   Quadrat_1 577 Extrapolation       0  6.000000  4.139740  7.860260 1.0000000
## 5   Quadrat_2 395   Rarefaction       0  7.000000  6.154974  7.845026 1.0000000
## 6   Quadrat_2 396      Observed       0  7.000000  6.154434  7.845566 1.0000000
## 7   Quadrat_2 397 Extrapolation       0  7.000000  6.154097  7.845903 1.0000000
## 8   Quadrat_2 577 Extrapolation       0  7.000000  6.098361  7.901639 1.0000000
## 9   Quadrat_3 577   Rarefaction       0  9.801391  7.442622 12.160160 0.9949310
## 10  Quadrat_3 616   Rarefaction       0  9.995138  7.512518 12.477758 0.9951378
## 11  Quadrat_3 617      Observed       0 10.000000  7.514188 12.485812 0.9951430
## 12  Quadrat_3 618 Extrapolation       0 10.004857  7.515692 12.494022 0.9951483
## 13  Quadrat_4 577      Observed       0 15.000000 13.147373 16.852627 0.9965398
## 14  Quadrat_5 432   Rarefaction       0 17.995381 16.193853 19.796910 0.9953811
## 15  Quadrat_5 433      Observed       0 18.000000 16.195825 19.804175 0.9954023
## 16  Quadrat_5 434 Extrapolation       0 18.004598 16.197696 19.811499 0.9954235
## 17  Quadrat_5 577 Extrapolation       0 18.484670 16.228335 20.741006 0.9976359
## 18  Quadrat_6 105   Rarefaction       0  6.990566  5.270953  8.710179 0.9905660
## 19  Quadrat_6 106      Observed       0  7.000000  5.272180  8.727820 0.9909122
## 20  Quadrat_6 107 Extrapolation       0  7.009088  5.270841  8.747334 0.9912457
## 21  Quadrat_6 577 Extrapolation       0  7.247642  3.722072 10.773211 1.0000000
## 22  Quadrat_7 215   Rarefaction       0 13.990741 12.177674 15.803808 0.9907407
## 23  Quadrat_7 216      Observed       0 14.000000 12.183699 15.816301 0.9908261
## 24  Quadrat_7 217 Extrapolation       0 14.009174 12.187892 15.830455 0.9909106
## 25  Quadrat_7 577 Extrapolation       0 14.960190 11.750217 18.170162 0.9996758
##       SC.LCL    SC.UCL
## 1  0.9926363 1.0000000
## 2  0.9922983 1.0000000
## 3  0.9923594 1.0000000
## 4  0.9990662 1.0000000
## 5  0.9976002 1.0000000
## 6  0.9983848 1.0000000
## 7  0.9983943 1.0000000
## 8  0.9993967 1.0000000
## 9  0.9907170 0.9991450
## 10 0.9908634 0.9994122
## 11 0.9906511 0.9996349
## 12 0.9906568 0.9996397
## 13 0.9922577 1.0000000
## 14 0.9898305 1.0000000
## 15 0.9896475 1.0000000
## 16 0.9896715 1.0000000
## 17 0.9925140 1.0000000
## 18 0.9720532 1.0000000
## 19 0.9709149 1.0000000
## 20 0.9714505 1.0000000
## 21 0.9994285 1.0000000
## 22 0.9819032 0.9995782
## 23 0.9810369 1.0000000
## 24 0.9811631 1.0000000
## 25 0.9968492 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 1.0000000 213      Observed       0  6.000000  4.015070  7.984930
## 2   Quadrat_2 1.0000000 396      Observed       0  7.000000  6.046698  7.953302
## 3   Quadrat_3 0.9949310 577   Rarefaction       0  9.801391  4.463823 15.138959
## 4   Quadrat_3 0.9951378 616   Rarefaction       0  9.992800  4.587532 15.398068
## 5   Quadrat_3 0.9951430 617      Observed       0 10.000000  4.591399 15.408601
## 6   Quadrat_3 0.9951483 618 Extrapolation       0 10.004857  4.593582 15.416132
## 7   Quadrat_4 0.9965398 577      Observed       0 15.000000 10.628215 19.371785
## 8   Quadrat_5 0.9953811 431   Rarefaction       0 17.993045 13.840514 22.145576
## 9   Quadrat_5 0.9954023 433      Observed       0 18.000000 13.839772 22.160228
## 10  Quadrat_5 0.9954235 434 Extrapolation       0 18.004598 13.836042 22.173154
## 11  Quadrat_5 0.9976359 577 Extrapolation       0 18.484670 13.422769 23.546571
## 12  Quadrat_6 0.9905660 104   Rarefaction       0  6.981784  4.123488  9.840080
## 13  Quadrat_6 0.9909122 106      Observed       0  7.000000  4.116460  9.883540
## 14  Quadrat_6 0.9912457 107 Extrapolation       0  7.009088  4.101172  9.917004
## 15  Quadrat_6 1.0000000 577 Extrapolation       0  7.247642  3.650560 10.844723
## 16  Quadrat_7 0.9907407 215   Rarefaction       0 13.988843 11.263399 16.714288
## 17  Quadrat_7 0.9908261 216      Observed       0 14.000000 11.263154 16.736846
## 18  Quadrat_7 0.9909106 217 Extrapolation       0 14.009174 11.262402 16.755946
## 19  Quadrat_7 0.9996758 577 Extrapolation       0 14.960190 11.097865 18.822514
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator      s.e.       LCL
## 1   Quadrat_1  Species richness  6.000000  6.000000 1.1008096  6.000000
## 2   Quadrat_1 Shannon diversity  2.352515  2.381769 0.1705492  2.047499
## 3   Quadrat_1 Simpson diversity  1.827847  1.835013 0.1235223  1.592914
## 4   Quadrat_2  Species richness  7.000000  7.000000 0.3910601  7.000000
## 5   Quadrat_2 Shannon diversity  3.543784  3.571485 0.1418110  3.293541
## 6   Quadrat_2 Simpson diversity  2.738570  2.750677 0.1375712  2.481042
## 7   Quadrat_3  Species richness 10.000000 14.492707 5.3367996 10.000000
## 8   Quadrat_3 Shannon diversity  4.294224  4.344098 0.1557878  4.038759
## 9   Quadrat_3 Simpson diversity  3.490350  3.504518 0.1421803  3.225850
## 10  Quadrat_4  Species richness 15.000000 16.996534 2.8043478 15.000000
## 11  Quadrat_4 Shannon diversity  7.241096  7.348354 0.2743669  6.810604
## 12  Quadrat_4 Simpson diversity  5.766302  5.814416 0.2328863  5.357967
## 13  Quadrat_5  Species richness 18.000000 18.997691 2.9623730 18.000000
## 14  Quadrat_5 Shannon diversity 11.090385 11.338175 0.3906700 10.572476
## 15  Quadrat_5 Simpson diversity  9.516725  9.708117 0.3360972  9.049379
## 16  Quadrat_6  Species richness  7.000000  7.247642 1.9238490  7.000000
## 17  Quadrat_6 Shannon diversity  2.675814  2.762979 0.3272902  2.121502
## 18  Quadrat_6 Simpson diversity  1.789742  1.803305 0.1859660  1.438819
## 19  Quadrat_7  Species richness 14.000000 14.995370 1.7308861 14.000000
## 20  Quadrat_7 Shannon diversity  9.347900  9.678925 0.4244086  8.847100
## 21  Quadrat_7 Simpson diversity  7.940095  8.204947 0.4318170  7.358601
##          UCL
## 1   8.157547
## 2   2.716040
## 3   2.077112
## 4   7.766464
## 5   3.849430
## 6   3.020312
## 7  24.952642
## 8   4.649436
## 9   3.783186
## 10 22.492955
## 11  7.886103
## 12  6.270864
## 13 24.803835
## 14 12.103874
## 15 10.366856
## 16 11.018316
## 17  3.404456
## 18  2.167792
## 19 18.387845
## 20 10.510751
## 21  9.051293
q <- c(433)

Hodbarrow_Dataq <- iNEXT(Hodbarrow_Nos, q=c(0), datatype= "abundance", size = q)

Hodbarrow_Dataq
## Compare 7 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 213     6 1.0000  0  3  0  0  0  0  0  0  0   1
## 2  Quadrat_2 396     7 1.0000  0  1  0  1  1  0  0  0  0   0
## 3  Quadrat_3 617    10 0.9951  3  1  0  1  0  0  0  0  0   0
## 4  Quadrat_4 577    15 0.9965  2  1  1  1  1  0  1  0  0   1
## 5  Quadrat_5 433    18 0.9954  2  2  2  0  1  1  0  0  0   0
## 6  Quadrat_6 106     7 0.9909  1  2  0  0  0  1  1  0  0   1
## 7  Quadrat_7 216    14 0.9908  2  2  0  0  0  1  1  0  0   2
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 212   Rarefaction       0  6.000000  4.822300  7.177700 1.0000000
## 2   Quadrat_1 213      Observed       0  6.000000  4.819364  7.180636 1.0000000
## 3   Quadrat_1 214 Extrapolation       0  6.000000  4.815617  7.184383 1.0000000
## 4   Quadrat_1 433 Extrapolation       0  6.000000  4.199835  7.800165 1.0000000
## 5   Quadrat_2 395   Rarefaction       0  7.000000  6.142831  7.857169 1.0000000
## 6   Quadrat_2 396      Observed       0  7.000000  6.142466  7.857534 1.0000000
## 7   Quadrat_2 397 Extrapolation       0  7.000000  6.142257  7.857743 1.0000000
## 8   Quadrat_2 433 Extrapolation       0  7.000000  6.132719  7.867281 1.0000000
## 9   Quadrat_3 433   Rarefaction       0  9.009026  6.880757 11.137295 0.9940068
## 10  Quadrat_3 616   Rarefaction       0  9.995138  7.255139 12.735137 0.9951378
## 11  Quadrat_3 617      Observed       0 10.000000  7.256622 12.743378 0.9951430
## 12  Quadrat_3 618 Extrapolation       0 10.004857  7.257821 12.751893 0.9951483
## 13  Quadrat_4 433   Rarefaction       0 14.418875 12.593721 16.244030 0.9952155
## 14  Quadrat_4 576   Rarefaction       0 14.996534 12.701722 17.291346 0.9965338
## 15  Quadrat_4 577      Observed       0 15.000000 12.701653 17.298347 0.9965398
## 16  Quadrat_4 578 Extrapolation       0 15.003460 12.701577 17.305343 0.9965458
## 17  Quadrat_5 433      Observed       0 18.000000 16.185426 19.814574 0.9954023
## 18  Quadrat_6 105   Rarefaction       0  6.990566  5.101757  8.879376 0.9905660
## 19  Quadrat_6 106      Observed       0  7.000000  5.100983  8.899017 0.9909122
## 20  Quadrat_6 107 Extrapolation       0  7.009088  5.099022  8.919154 0.9912457
## 21  Quadrat_6 433 Extrapolation       0  7.247640  3.586644 10.908637 1.0000000
## 22  Quadrat_7 215   Rarefaction       0 13.990741 12.186537 15.794945 0.9907407
## 23  Quadrat_7 216      Observed       0 14.000000 12.192352 15.807648 0.9908261
## 24  Quadrat_7 217 Extrapolation       0 14.009174 12.196936 15.821412 0.9909106
## 25  Quadrat_7 433 Extrapolation       0 14.861905 12.189282 17.534528 0.9987699
##       SC.LCL    SC.UCL
## 1  0.9926012 1.0000000
## 2  0.9919958 1.0000000
## 3  0.9920536 1.0000000
## 4  0.9976796 1.0000000
## 5  0.9971718 1.0000000
## 6  0.9979490 1.0000000
## 7  0.9979593 1.0000000
## 8  0.9982986 1.0000000
## 9  0.9894636 0.9985499
## 10 0.9903800 0.9998955
## 11 0.9901806 1.0000000
## 12 0.9901880 1.0000000
## 13 0.9909235 0.9995075
## 14 0.9920081 1.0000000
## 15 0.9920143 1.0000000
## 16 0.9920206 1.0000000
## 17 0.9889397 1.0000000
## 18 0.9709551 1.0000000
## 19 0.9705023 1.0000000
## 20 0.9710055 1.0000000
## 21 0.9980418 1.0000000
## 22 0.9821110 0.9993705
## 23 0.9814791 1.0000000
## 24 0.9816069 1.0000000
## 25 0.9947332 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 1.0000000 213      Observed       0  6.000000  3.843960  8.156040
## 2   Quadrat_2 1.0000000 396      Observed       0  7.000000  6.014354  7.985646
## 3   Quadrat_3 0.9940068 433   Rarefaction       0  9.009026  3.258550 14.759502
## 4   Quadrat_3 0.9951378 616   Rarefaction       0  9.992800  3.761785 16.223815
## 5   Quadrat_3 0.9951430 617      Observed       0 10.000000  3.799160 16.200840
## 6   Quadrat_3 0.9951483 618 Extrapolation       0 10.004857  3.828720 16.180994
## 7   Quadrat_4 0.9952155 433   Rarefaction       0 14.418876  9.290877 19.546874
## 8   Quadrat_4 0.9965338 576   Rarefaction       0 14.995943  9.140106 20.851780
## 9   Quadrat_4 0.9965398 577      Observed       0 15.000000  9.140696 20.859304
## 10  Quadrat_4 0.9965458 578 Extrapolation       0 15.003460  9.141131 20.865789
## 11  Quadrat_5 0.9954023 433      Observed       0 18.000000 13.528182 22.471818
## 12  Quadrat_6 0.9905660 104   Rarefaction       0  6.981784  3.797326 10.166242
## 13  Quadrat_6 0.9909122 106      Observed       0  7.000000  3.791936 10.208064
## 14  Quadrat_6 0.9912457 107 Extrapolation       0  7.009088  3.777968 10.240207
## 15  Quadrat_6 1.0000000 433 Extrapolation       0  7.247640  3.363755 11.131525
## 16  Quadrat_7 0.9907407 215   Rarefaction       0 13.988843 11.458394 16.519293
## 17  Quadrat_7 0.9908261 216      Observed       0 14.000000 11.462707 16.537293
## 18  Quadrat_7 0.9909106 217 Extrapolation       0 14.009174 11.463670 16.554678
## 19  Quadrat_7 0.9987699 433 Extrapolation       0 14.861905 11.519133 18.204677
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator      s.e.       LCL
## 1   Quadrat_1  Species richness  6.000000  6.000000 1.0554353  6.000000
## 2   Quadrat_1 Shannon diversity  2.352515  2.381769 0.1463405  2.094947
## 3   Quadrat_1 Simpson diversity  1.827847  1.835013 0.1058224  1.627605
## 4   Quadrat_2  Species richness  7.000000  7.000000 0.5565851  7.000000
## 5   Quadrat_2 Shannon diversity  3.543784  3.571485 0.1505437  3.276425
## 6   Quadrat_2 Simpson diversity  2.738570  2.750677 0.1412151  2.473901
## 7   Quadrat_3  Species richness 10.000000 14.492707 5.8274745 10.000000
## 8   Quadrat_3 Shannon diversity  4.294224  4.344098 0.1408744  4.067989
## 9   Quadrat_3 Simpson diversity  3.490350  3.504518 0.1260779  3.257410
## 10  Quadrat_4  Species richness 15.000000 16.996534 2.6103235 15.000000
## 11  Quadrat_4 Shannon diversity  7.241096  7.348354 0.2606609  6.837468
## 12  Quadrat_4 Simpson diversity  5.766302  5.814416 0.2280752  5.367396
## 13  Quadrat_5  Species richness 18.000000 18.997691 2.3776287 18.000000
## 14  Quadrat_5 Shannon diversity 11.090385 11.338175 0.3605567 10.631496
## 15  Quadrat_5 Simpson diversity  9.516725  9.708117 0.3493551  9.023394
## 16  Quadrat_6  Species richness  7.000000  7.247642 1.6396261  7.000000
## 17  Quadrat_6 Shannon diversity  2.675814  2.762979 0.3120218  2.151428
## 18  Quadrat_6 Simpson diversity  1.789742  1.803305 0.1806287  1.449279
## 19  Quadrat_7  Species richness 14.000000 14.995370 2.1146839 14.000000
## 20  Quadrat_7 Shannon diversity  9.347900  9.678925 0.4666143  8.764378
## 21  Quadrat_7 Simpson diversity  7.940095  8.204947 0.4778524  7.268373
##          UCL
## 1   8.068615
## 2   2.668592
## 3   2.042421
## 4   8.090887
## 5   3.866545
## 6   3.027454
## 7  25.914347
## 8   4.620207
## 9   3.751626
## 10 22.112674
## 11  7.859240
## 12  6.261435
## 13 23.657757
## 14 12.044853
## 15 10.392840
## 16 10.461250
## 17  3.374531
## 18  2.157331
## 19 19.140075
## 20 10.593473
## 21  9.141521
r <- c(106)

Hodbarrow_Datar <- iNEXT(Hodbarrow_Nos, q=c(0), datatype= "abundance", size = r)

Hodbarrow_Datar
## Compare 7 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 213     6 1.0000  0  3  0  0  0  0  0  0  0   1
## 2  Quadrat_2 396     7 1.0000  0  1  0  1  1  0  0  0  0   0
## 3  Quadrat_3 617    10 0.9951  3  1  0  1  0  0  0  0  0   0
## 4  Quadrat_4 577    15 0.9965  2  1  1  1  1  0  1  0  0   1
## 5  Quadrat_5 433    18 0.9954  2  2  2  0  1  1  0  0  0   0
## 6  Quadrat_6 106     7 0.9909  1  2  0  0  0  1  1  0  0   1
## 7  Quadrat_7 216    14 0.9908  2  2  0  0  0  1  1  0  0   2
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 106   Rarefaction       0  5.245657  4.165839  6.325475 0.9858387
## 2   Quadrat_1 212   Rarefaction       0  6.000000  4.897322  7.102678 1.0000000
## 3   Quadrat_1 213      Observed       0  6.000000  4.896948  7.103052 1.0000000
## 4   Quadrat_1 214 Extrapolation       0  6.000000  4.895581  7.104419 1.0000000
## 5   Quadrat_2 106   Rarefaction       0  5.969452  5.454704  6.484201 0.9887561
## 6   Quadrat_2 395   Rarefaction       0  7.000000  6.239968  7.760032 1.0000000
## 7   Quadrat_2 396      Observed       0  7.000000  6.239362  7.760638 1.0000000
## 8   Quadrat_2 397 Extrapolation       0  7.000000  6.239268  7.760732 1.0000000
## 9   Quadrat_3 106   Rarefaction       0  6.360050  5.622921  7.097178 0.9887665
## 10  Quadrat_3 616   Rarefaction       0  9.995138  7.114482 12.875793 0.9951378
## 11  Quadrat_3 617      Observed       0 10.000000  7.114830 12.885170 0.9951430
## 12  Quadrat_3 618 Extrapolation       0 10.004857  7.115057 12.894657 0.9951483
## 13  Quadrat_4 106   Rarefaction       0 10.959510 10.204869 11.714151 0.9753072
## 14  Quadrat_4 576   Rarefaction       0 14.996534 13.104236 16.888832 0.9965338
## 15  Quadrat_4 577      Observed       0 15.000000 13.105529 16.894471 0.9965398
## 16  Quadrat_4 578 Extrapolation       0 15.003460 13.106814 16.900106 0.9965458
## 17  Quadrat_5 106   Rarefaction       0 14.048474 13.094013 15.002934 0.9726455
## 18  Quadrat_5 432   Rarefaction       0 17.995381 15.731741 20.259021 0.9953811
## 19  Quadrat_5 433      Observed       0 18.000000 15.731869 20.268131 0.9954023
## 20  Quadrat_5 434 Extrapolation       0 18.004598 15.731858 20.277337 0.9954235
## 21  Quadrat_6 106      Observed       0  7.000000  5.372654  8.627346 0.9909122
## 22  Quadrat_7 106   Rarefaction       0 12.438862 11.034749 13.842975 0.9797776
## 23  Quadrat_7 215   Rarefaction       0 13.990741 12.054513 15.926968 0.9907407
## 24  Quadrat_7 216      Observed       0 14.000000 12.059735 15.940265 0.9908261
## 25  Quadrat_7 217 Extrapolation       0 14.009174 12.063781 15.954566 0.9909106
##       SC.LCL    SC.UCL
## 1  0.9803630 0.9913143
## 2  0.9922789 1.0000000
## 3  0.9918885 1.0000000
## 4  0.9919414 1.0000000
## 5  0.9851160 0.9923961
## 6  0.9978070 1.0000000
## 7  0.9990276 1.0000000
## 8  0.9990350 1.0000000
## 9  0.9831631 0.9943699
## 10 0.9898530 1.0000000
## 11 0.9897726 1.0000000
## 12 0.9897784 1.0000000
## 13 0.9699502 0.9806643
## 14 0.9925909 1.0000000
## 15 0.9925996 1.0000000
## 16 0.9926083 1.0000000
## 17 0.9666179 0.9786731
## 18 0.9894369 1.0000000
## 19 0.9892782 1.0000000
## 20 0.9893105 1.0000000
## 21 0.9702032 1.0000000
## 22 0.9702698 0.9892854
## 23 0.9823620 0.9991195
## 24 0.9812957 1.0000000
## 25 0.9814189 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9858387 106   Rarefaction       0  5.245657  3.862317  6.628996
## 2   Quadrat_1 1.0000000 213      Observed       0  6.000000  3.952989  8.047011
## 3   Quadrat_2 0.9887561 106   Rarefaction       0  5.969452  5.277972  6.660933
## 4   Quadrat_2 1.0000000 396      Observed       0  7.000000  6.210581  7.789419
## 5   Quadrat_3 0.9887665 106   Rarefaction       0  6.360050  3.045542  9.674557
## 6   Quadrat_3 0.9951378 616   Rarefaction       0  9.992800  1.868919 18.116681
## 7   Quadrat_3 0.9951430 617      Observed       0 10.000000  1.871980 18.128020
## 8   Quadrat_3 0.9951483 618 Extrapolation       0 10.004857  1.873828 18.135886
## 9   Quadrat_4 0.9753072 106   Rarefaction       0 10.959510  9.739899 12.179121
## 10  Quadrat_4 0.9965338 576   Rarefaction       0 14.995943 11.099305 18.892581
## 11  Quadrat_4 0.9965398 577      Observed       0 15.000000 11.100369 18.899631
## 12  Quadrat_4 0.9965458 578 Extrapolation       0 15.003460 11.102086 18.904834
## 13  Quadrat_5 0.9726455 106   Rarefaction       0 14.048474 12.654227 15.442721
## 14  Quadrat_5 0.9953811 431   Rarefaction       0 17.993045 13.820557 22.165533
## 15  Quadrat_5 0.9954023 433      Observed       0 18.000000 13.821413 22.178587
## 16  Quadrat_5 0.9954235 434 Extrapolation       0 18.004598 13.819477 22.189718
## 17  Quadrat_6 0.9909122 106      Observed       0  7.000000  3.564657 10.435343
## 18  Quadrat_7 0.9797776 106   Rarefaction       0 12.438862 10.494299 14.383425
## 19  Quadrat_7 0.9907407 215   Rarefaction       0 13.988843 11.099361 16.878326
## 20  Quadrat_7 0.9908261 216      Observed       0 14.000000 11.103387 16.896613
## 21  Quadrat_7 0.9909106 217 Extrapolation       0 14.009174 11.103022 16.915326
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator      s.e.       LCL
## 1   Quadrat_1  Species richness  6.000000  6.000000 1.0100169  6.000000
## 2   Quadrat_1 Shannon diversity  2.352515  2.381769 0.1782317  2.032442
## 3   Quadrat_1 Simpson diversity  1.827847  1.835013 0.1262180  1.587630
## 4   Quadrat_2  Species richness  7.000000  7.000000 0.4989073  7.000000
## 5   Quadrat_2 Shannon diversity  3.543784  3.571485 0.1561497  3.265437
## 6   Quadrat_2 Simpson diversity  2.738570  2.750677 0.1557277  2.445456
## 7   Quadrat_3  Species richness 10.000000 14.492707 4.9059630 10.000000
## 8   Quadrat_3 Shannon diversity  4.294224  4.344098 0.1468151  4.056346
## 9   Quadrat_3 Simpson diversity  3.490350  3.504518 0.1348369  3.240243
## 10  Quadrat_4  Species richness 15.000000 16.996534 3.3222900 15.000000
## 11  Quadrat_4 Shannon diversity  7.241096  7.348354 0.2740974  6.811133
## 12  Quadrat_4 Simpson diversity  5.766302  5.814416 0.2274806  5.368562
## 13  Quadrat_5  Species richness 18.000000 18.997691 2.6774100 18.000000
## 14  Quadrat_5 Shannon diversity 11.090385 11.338175 0.3801393 10.593115
## 15  Quadrat_5 Simpson diversity  9.516725  9.708117 0.3607887  9.000984
## 16  Quadrat_6  Species richness  7.000000  7.247642 2.1862904  7.000000
## 17  Quadrat_6 Shannon diversity  2.675814  2.762979 0.3350025  2.106386
## 18  Quadrat_6 Simpson diversity  1.789742  1.803305 0.1921667  1.426666
## 19  Quadrat_7  Species richness 14.000000 14.995370 2.5553803 14.000000
## 20  Quadrat_7 Shannon diversity  9.347900  9.678925 0.4516908  8.793628
## 21  Quadrat_7 Simpson diversity  7.940095  8.204947 0.4328089  7.356657
##          UCL
## 1   7.979597
## 2   2.731097
## 3   2.082396
## 4   7.977840
## 5   3.877533
## 6   3.055898
## 7  24.108218
## 8   4.631850
## 9   3.768794
## 10 23.508103
## 11  7.885575
## 12  6.260269
## 13 24.245318
## 14 12.083234
## 15 10.415250
## 16 11.532692
## 17  3.419572
## 18  2.179945
## 19 20.003824
## 20 10.564223
## 21  9.053237
s <- c(216)

Hodbarrow_Datas <- iNEXT(Hodbarrow_Nos, q=c(0), datatype= "abundance", size = s)

Hodbarrow_Datas
## Compare 7 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 213     6 1.0000  0  3  0  0  0  0  0  0  0   1
## 2  Quadrat_2 396     7 1.0000  0  1  0  1  1  0  0  0  0   0
## 3  Quadrat_3 617    10 0.9951  3  1  0  1  0  0  0  0  0   0
## 4  Quadrat_4 577    15 0.9965  2  1  1  1  1  0  1  0  0   1
## 5  Quadrat_5 433    18 0.9954  2  2  2  0  1  1  0  0  0   0
## 6  Quadrat_6 106     7 0.9909  1  2  0  0  0  1  1  0  0   1
## 7  Quadrat_7 216    14 0.9908  2  2  0  0  0  1  1  0  0   2
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 212   Rarefaction       0  6.000000  4.806794  7.193206 1.0000000
## 2   Quadrat_1 213      Observed       0  6.000000  4.806158  7.193842 1.0000000
## 3   Quadrat_1 214 Extrapolation       0  6.000000  4.804564  7.195436 1.0000000
## 4   Quadrat_1 216 Extrapolation       0  6.000000  4.801336  7.198664 1.0000000
## 5   Quadrat_2 216   Rarefaction       0  6.733287  5.984950  7.481623 0.9962572
## 6   Quadrat_2 395   Rarefaction       0  7.000000  6.208601  7.791399 1.0000000
## 7   Quadrat_2 396      Observed       0  7.000000  6.208055  7.791945 1.0000000
## 8   Quadrat_2 397 Extrapolation       0  7.000000  6.207804  7.792196 1.0000000
## 9   Quadrat_3 216   Rarefaction       0  7.450737  6.266906  8.634569 0.9912625
## 10  Quadrat_3 616   Rarefaction       0  9.995138  7.245202 12.745074 0.9951378
## 11  Quadrat_3 617      Observed       0 10.000000  7.246353 12.753647 0.9951430
## 12  Quadrat_3 618 Extrapolation       0 10.004857  7.247370 12.762344 0.9951483
## 13  Quadrat_4 216   Rarefaction       0 12.820735 11.502210 14.139261 0.9883736
## 14  Quadrat_4 576   Rarefaction       0 14.996534 12.709128 17.283939 0.9965338
## 15  Quadrat_4 577      Observed       0 15.000000 12.710197 17.289803 0.9965398
## 16  Quadrat_4 578 Extrapolation       0 15.003460 12.711121 17.295800 0.9965458
## 17  Quadrat_5 216   Rarefaction       0 16.200342 14.974200 17.426483 0.9861703
## 18  Quadrat_5 432   Rarefaction       0 17.995381 16.329500 19.661262 0.9953811
## 19  Quadrat_5 433      Observed       0 18.000000 16.331268 19.668732 0.9954023
## 20  Quadrat_5 434 Extrapolation       0 18.004598 16.332973 19.676222 0.9954235
## 21  Quadrat_6 105   Rarefaction       0  6.990566  5.426302  8.554830 0.9905660
## 22  Quadrat_6 106      Observed       0  7.000000  5.425542  8.574458 0.9909122
## 23  Quadrat_6 107 Extrapolation       0  7.009088  5.421750  8.596425 0.9912457
## 24  Quadrat_6 216 Extrapolation       0  7.243589  4.512275  9.974903 0.9998513
## 25  Quadrat_7 216      Observed       0 14.000000 12.227387 15.772613 0.9908261
##       SC.LCL    SC.UCL
## 1  0.9935494 1.0000000
## 2  0.9933394 1.0000000
## 3  0.9934039 1.0000000
## 4  0.9935304 1.0000000
## 5  0.9938167 0.9986977
## 6  0.9974625 1.0000000
## 7  0.9982064 1.0000000
## 8  0.9982155 1.0000000
## 9  0.9864402 0.9960848
## 10 0.9905798 0.9996957
## 11 0.9904905 0.9997955
## 12 0.9904982 0.9997984
## 13 0.9836704 0.9930769
## 14 0.9928153 1.0000000
## 15 0.9926619 1.0000000
## 16 0.9926720 1.0000000
## 17 0.9814457 0.9908950
## 18 0.9904091 1.0000000
## 19 0.9903350 1.0000000
## 20 0.9903648 1.0000000
## 21 0.9721552 1.0000000
## 22 0.9706599 1.0000000
## 23 0.9711844 1.0000000
## 24 0.9912518 1.0000000
## 25 0.9813052 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 1.0000000 213      Observed       0  6.000000  4.427508  7.572492
## 2   Quadrat_2 0.9962572 216   Rarefaction       0  6.733287  5.895813  7.570760
## 3   Quadrat_2 1.0000000 396      Observed       0  7.000000  6.087789  7.912211
## 4   Quadrat_3 0.9912625 216   Rarefaction       0  7.450737  3.977252 10.924222
## 5   Quadrat_3 0.9951378 616   Rarefaction       0  9.992800  4.748890 15.236710
## 6   Quadrat_3 0.9951430 617      Observed       0 10.000000  4.753477 15.246523
## 7   Quadrat_3 0.9951483 618 Extrapolation       0 10.004857  4.757339 15.252375
## 8   Quadrat_4 0.9883736 216   Rarefaction       0 12.820735 10.762304 14.879166
## 9   Quadrat_4 0.9965338 576   Rarefaction       0 14.995943 11.128411 18.863476
## 10  Quadrat_4 0.9965398 577      Observed       0 15.000000 11.129962 18.870038
## 11  Quadrat_4 0.9965458 578 Extrapolation       0 15.003460 11.131625 18.875295
## 12  Quadrat_5 0.9861703 216   Rarefaction       0 16.200342 14.515091 17.885592
## 13  Quadrat_5 0.9953811 431   Rarefaction       0 17.993045 15.325867 20.660223
## 14  Quadrat_5 0.9954023 433      Observed       0 18.000000 15.327495 20.672505
## 15  Quadrat_5 0.9954235 434 Extrapolation       0 18.004598 15.326438 20.682757
## 16  Quadrat_6 0.9905660 104   Rarefaction       0  6.981784  3.901324 10.062244
## 17  Quadrat_6 0.9909122 106      Observed       0  7.000000  3.896303 10.103697
## 18  Quadrat_6 0.9912457 107 Extrapolation       0  7.009088  3.881077 10.137098
## 19  Quadrat_6 0.9998513 216 Extrapolation       0  7.243589  3.443367 11.043811
## 20  Quadrat_7 0.9908261 216      Observed       0 14.000000 11.380234 16.619766
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator      s.e.       LCL
## 1   Quadrat_1  Species richness  6.000000  6.000000 1.0179790  6.000000
## 2   Quadrat_1 Shannon diversity  2.352515  2.381769 0.1685340  2.051449
## 3   Quadrat_1 Simpson diversity  1.827847  1.835013 0.1216978  1.596490
## 4   Quadrat_2  Species richness  7.000000  7.000000 0.4783205  7.000000
## 5   Quadrat_2 Shannon diversity  3.543784  3.571485 0.1755750  3.227364
## 6   Quadrat_2 Simpson diversity  2.738570  2.750677 0.1620346  2.433095
## 7   Quadrat_3  Species richness 10.000000 14.492707 5.2133851 10.000000
## 8   Quadrat_3 Shannon diversity  4.294224  4.344098 0.1601963  4.030119
## 9   Quadrat_3 Simpson diversity  3.490350  3.504518 0.1474408  3.215540
## 10  Quadrat_4  Species richness 15.000000 16.996534 2.8014414 15.000000
## 11  Quadrat_4 Shannon diversity  7.241096  7.348354 0.2596370  6.839475
## 12  Quadrat_4 Simpson diversity  5.766302  5.814416 0.2300697  5.363487
## 13  Quadrat_5  Species richness 18.000000 18.997691 2.6721769 18.000000
## 14  Quadrat_5 Shannon diversity 11.090385 11.338175 0.3951325 10.563729
## 15  Quadrat_5 Simpson diversity  9.516725  9.708117 0.3779204  8.967407
## 16  Quadrat_6  Species richness  7.000000  7.247642 1.7047297  7.000000
## 17  Quadrat_6 Shannon diversity  2.675814  2.762979 0.3707945  2.036235
## 18  Quadrat_6 Simpson diversity  1.789742  1.803305 0.2348662  1.342976
## 19  Quadrat_7  Species richness 14.000000 14.995370 2.2033178 14.000000
## 20  Quadrat_7 Shannon diversity  9.347900  9.678925 0.4895731  8.719380
## 21  Quadrat_7 Simpson diversity  7.940095  8.204947 0.4902522  7.244070
##          UCL
## 1   7.995202
## 2   2.712090
## 3   2.073536
## 4   7.937491
## 5   3.915606
## 6   3.068259
## 7  24.710754
## 8   4.658077
## 9   3.793497
## 10 22.487258
## 11  7.857233
## 12  6.265344
## 13 24.235061
## 14 12.112620
## 15 10.448827
## 16 10.588850
## 17  3.489723
## 18  2.263635
## 19 19.313794
## 20 10.638471
## 21  9.165824

#Now to run the analysis again without specificying the size, can do this for #looking at the other diversity indices

Hodbarrow_Data <- iNEXT(Hodbarrow_Nos, q=c(0), datatype= "abundance")

print(Hodbarrow_Data)
## Compare 7 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 213     6 1.0000  0  3  0  0  0  0  0  0  0   1
## 2  Quadrat_2 396     7 1.0000  0  1  0  1  1  0  0  0  0   0
## 3  Quadrat_3 617    10 0.9951  3  1  0  1  0  0  0  0  0   0
## 4  Quadrat_4 577    15 0.9965  2  1  1  1  1  0  1  0  0   1
## 5  Quadrat_5 433    18 0.9954  2  2  2  0  1  1  0  0  0   0
## 6  Quadrat_6 106     7 0.9909  1  2  0  0  0  1  1  0  0   1
## 7  Quadrat_7 216    14 0.9908  2  2  0  0  0  1  1  0  0   2
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##     Assemblage    m        Method Order.q        qD    qD.LCL    qD.UCL
## 1    Quadrat_1    1   Rarefaction       0  1.000000  1.000000  1.000000
## 10   Quadrat_1  106   Rarefaction       0  5.245657  4.104625  6.386689
## 20   Quadrat_1  213      Observed       0  6.000000  4.614662  7.385338
## 30   Quadrat_1  314 Extrapolation       0  6.000000  4.308948  7.691052
## 40   Quadrat_1  426 Extrapolation       0  6.000000  4.066912  7.933088
## 41   Quadrat_2    1   Rarefaction       0  1.000000  1.000000  1.000000
## 50   Quadrat_2  198   Rarefaction       0  6.658619  6.065476  7.251763
## 60   Quadrat_2  396      Observed       0  7.000000  6.356621  7.643379
## 70   Quadrat_2  584 Extrapolation       0  7.000000  6.268932  7.731068
## 80   Quadrat_2  792 Extrapolation       0  7.000000  6.210242  7.789758
## 81   Quadrat_3    1   Rarefaction       0  1.000000  1.000000  1.000000
## 90   Quadrat_3  308   Rarefaction       0  8.184868  6.400305  9.969431
## 100  Quadrat_3  617      Observed       0 10.000000  7.303895 12.696105
## 110  Quadrat_3  909 Extrapolation       0 11.216753  7.634757 14.798750
## 120  Quadrat_3 1234 Extrapolation       0 12.187737  7.605178 16.770297
## 121  Quadrat_4    1   Rarefaction       0  1.000000  1.000000  1.000000
## 130  Quadrat_4  288   Rarefaction       0 13.521031 12.152755 14.889308
## 140  Quadrat_4  577      Observed       0 15.000000 12.940943 17.059057
## 150  Quadrat_4  850 Extrapolation       0 15.753114 13.073719 18.432510
## 160  Quadrat_4 1154 Extrapolation       0 16.262687 12.944076 19.581298
## 161  Quadrat_5    1   Rarefaction       0  1.000000  1.000000  1.000000
## 170  Quadrat_5  216   Rarefaction       0 16.200342 14.791499 17.609184
## 180  Quadrat_5  433      Observed       0 18.000000 16.074743 19.925257
## 190  Quadrat_5  638 Extrapolation       0 18.610638 16.083357 21.137920
## 200  Quadrat_5  866 Extrapolation       0 18.862668 15.785215 21.940122
## 201  Quadrat_6    1   Rarefaction       0  1.000000  1.000000  1.000000
## 210  Quadrat_6   53   Rarefaction       0  5.984367  4.696065  7.272669
## 220  Quadrat_6  106      Observed       0  7.000000  5.024498  8.975502
## 230  Quadrat_6  156 Extrapolation       0  7.209450  4.607453  9.811447
## 240  Quadrat_6  212 Extrapolation       0  7.242935  4.143499 10.342371
## 241  Quadrat_7    1   Rarefaction       0  1.000000  1.000000  1.000000
## 250  Quadrat_7  108   Rarefaction       0 12.479137 11.277366 13.680908
## 260  Quadrat_7  216      Observed       0 14.000000 12.141037 15.858963
## 270  Quadrat_7  318 Extrapolation       0 14.608278 12.054150 17.162406
## 280  Quadrat_7  432 Extrapolation       0 14.860664 11.704609 18.016718
##            SC     SC.LCL    SC.UCL
## 1   0.5449553 0.48078990 0.6091206
## 10  0.9858387 0.97895685 0.9927205
## 20  1.0000000 0.99204586 1.0000000
## 30  1.0000000 0.99567927 1.0000000
## 40  1.0000000 0.99755900 1.0000000
## 41  0.3635469 0.32611842 0.4009753
## 50  0.9954684 0.99269139 0.9982455
## 60  1.0000000 0.99784542 1.0000000
## 70  1.0000000 0.99916632 1.0000000
## 80  1.0000000 0.99970841 1.0000000
## 81  0.2853459 0.26503927 0.3056526
## 90  0.9927106 0.98851421 0.9969070
## 100 0.9951430 0.99110131 0.9991847
## 110 0.9964584 0.99258391 1.0000000
## 120 0.9975081 0.99424217 1.0000000
## 121 0.1719863 0.15790276 0.1860699
## 130 0.9918886 0.98801923 0.9957579
## 140 0.9965398 0.99262150 1.0000000
## 150 0.9978450 0.99462626 1.0000000
## 160 0.9987282 0.99628503 1.0000000
## 161 0.1030066 0.09459232 0.1114209
## 170 0.9861703 0.98103914 0.9913015
## 180 0.9954023 0.99001404 1.0000000
## 190 0.9982163 0.99424285 1.0000000
## 200 0.9993778 0.99656617 1.0000000
## 201 0.5545373 0.42838883 0.6806857
## 210 0.9694034 0.95032277 0.9884841
## 220 0.9909122 0.97069915 1.0000000
## 230 0.9985985 0.98501985 1.0000000
## 240 0.9998273 0.99081664 1.0000000
## 241 0.1218777 0.10620992 0.1375455
## 250 0.9801126 0.97118951 0.9890357
## 260 0.9908261 0.98050767 1.0000000
## 270 0.9964323 0.98893093 1.0000000
## 280 0.9987585 0.99345782 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##     Assemblage        SC    m        Method Order.q        qD     qD.LCL
## 1    Quadrat_1 0.5449607    1   Rarefaction       0  1.000008  0.9544906
## 5    Quadrat_1 0.9733952   47   Rarefaction       0  4.102612  2.9872241
## 10   Quadrat_1 0.9858387  106   Rarefaction       0  5.245657  3.8291939
## 15   Quadrat_1 0.9937549  165   Rarefaction       0  5.850119  3.9063266
## 19   Quadrat_1 1.0000000  213      Observed       0  6.000000  3.7031362
## 20   Quadrat_2 0.3635490    1   Rarefaction       0  1.000005  0.9432211
## 24   Quadrat_2 0.9867185   88   Rarefaction       0  5.748195  4.9921793
## 29   Quadrat_2 0.9954684  198   Rarefaction       0  6.658619  6.0146491
## 34   Quadrat_2 0.9987366  307   Rarefaction       0  6.946986  6.1972719
## 38   Quadrat_2 1.0000000  396      Observed       0  7.000000  6.1745875
## 39   Quadrat_3 0.2853459    1   Rarefaction       0  1.000000  0.9634445
## 48   Quadrat_3 0.9927106  308   Rarefaction       0  8.184868  3.3437309
## 58   Quadrat_3 0.9951430  617      Observed       0 10.000000  3.9035149
## 68   Quadrat_3 0.9964584  909 Extrapolation       0 11.216753  4.4645489
## 78   Quadrat_3 0.9975081 1234 Extrapolation       0 12.187737  4.8841711
## 79   Quadrat_4 0.1719914    1   Rarefaction       0  1.000027  0.9667507
## 88   Quadrat_4 0.9918886  288   Rarefaction       0 13.521031 11.1221325
## 98   Quadrat_4 0.9965398  577      Observed       0 15.000000 11.1304822
## 108  Quadrat_4 0.9978450  850 Extrapolation       0 15.753114 11.3211341
## 118  Quadrat_4 0.9987282 1154 Extrapolation       0 16.262687 11.4305831
## 119  Quadrat_5 0.1030066    1   Rarefaction       0  1.000000  0.9703826
## 128  Quadrat_5 0.9861703  216   Rarefaction       0 16.200342 14.1409293
## 138  Quadrat_5 0.9954023  433      Observed       0 18.000000 14.7928621
## 148  Quadrat_5 0.9982163  638 Extrapolation       0 18.610638 14.5917926
## 158  Quadrat_5 0.9993778  866 Extrapolation       0 18.862668 14.4199677
## 159  Quadrat_6 0.5545389    1   Rarefaction       0  1.000003  0.8366023
## 168  Quadrat_6 0.9694034   53   Rarefaction       0  5.984366  3.8866246
## 178  Quadrat_6 0.9909122  106      Observed       0  7.000000  3.5600866
## 188  Quadrat_6 0.9985985  156 Extrapolation       0  7.209450  3.1882610
## 198  Quadrat_6 0.9998273  212 Extrapolation       0  7.242935  3.1195305
## 199  Quadrat_7 0.1218798    1   Rarefaction       0  1.000017  0.9411355
## 208  Quadrat_7 0.9801126  108   Rarefaction       0 12.479137 10.7487385
## 218  Quadrat_7 0.9908261  216      Observed       0 14.000000 10.7566457
## 228  Quadrat_7 0.9964323  318 Extrapolation       0 14.608278 10.5536783
## 238  Quadrat_7 0.9987585  432 Extrapolation       0 14.860664 10.4136588
##        qD.UCL
## 1    1.045526
## 5    5.218000
## 10   6.662120
## 15   7.793912
## 19   8.296864
## 20   1.056790
## 24   6.504211
## 29   7.302589
## 34   7.696699
## 38   7.825412
## 39   1.036556
## 48  13.026005
## 58  16.096485
## 68  17.968958
## 78  19.491303
## 79   1.033304
## 88  15.919930
## 98  18.869518
## 108 20.185095
## 118 21.094791
## 119  1.029617
## 128 18.259755
## 138 21.207138
## 148 22.629484
## 158 23.305369
## 159  1.163403
## 168  8.082108
## 178 10.439913
## 188 11.230640
## 198 11.366340
## 199  1.058898
## 208 14.209536
## 218 17.243354
## 228 18.662877
## 238 19.307668
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator      s.e.       LCL
## 1   Quadrat_1  Species richness  6.000000  6.000000 0.9719895  6.000000
## 2   Quadrat_1 Shannon diversity  2.352515  2.381769 0.1662787  2.055869
## 3   Quadrat_1 Simpson diversity  1.827847  1.835013 0.1192926  1.601204
## 4   Quadrat_2  Species richness  7.000000  7.000000 0.4370453  7.000000
## 5   Quadrat_2 Shannon diversity  3.543784  3.571485 0.1572965  3.263190
## 6   Quadrat_2 Simpson diversity  2.738570  2.750677 0.1416105  2.473125
## 7   Quadrat_3  Species richness 10.000000 14.492707 3.5858101 10.000000
## 8   Quadrat_3 Shannon diversity  4.294224  4.344098 0.1328393  4.083738
## 9   Quadrat_3 Simpson diversity  3.490350  3.504518 0.1170370  3.275130
## 10  Quadrat_4  Species richness 15.000000 16.996534 2.9149300 15.000000
## 11  Quadrat_4 Shannon diversity  7.241096  7.348354 0.2584223  6.841855
## 12  Quadrat_4 Simpson diversity  5.766302  5.814416 0.2201463  5.382937
## 13  Quadrat_5  Species richness 18.000000 18.997691 2.3392021 18.000000
## 14  Quadrat_5 Shannon diversity 11.090385 11.338175 0.4389713 10.477807
## 15  Quadrat_5 Simpson diversity  9.516725  9.708117 0.3704369  8.982074
## 16  Quadrat_6  Species richness  7.000000  7.247642 1.6116566  7.000000
## 17  Quadrat_6 Shannon diversity  2.675814  2.762979 0.2789601  2.216228
## 18  Quadrat_6 Simpson diversity  1.789742  1.803305 0.1658390  1.478267
## 19  Quadrat_7  Species richness 14.000000 14.995370 2.6669049 14.000000
## 20  Quadrat_7 Shannon diversity  9.347900  9.678925 0.4364679  8.823464
## 21  Quadrat_7 Simpson diversity  7.940095  8.204947 0.4369687  7.348504
##          UCL
## 1   7.905064
## 2   2.707670
## 3   2.068822
## 4   7.856593
## 5   3.879781
## 6   3.028229
## 7  21.520765
## 8   4.604458
## 9   3.733906
## 10 22.709692
## 11  7.854852
## 12  6.245895
## 13 23.582442
## 14 12.198543
## 15 10.434160
## 16 10.406430
## 17  3.309731
## 18  2.128344
## 19 20.222408
## 20 10.534387
## 21  9.061390

#Running further analyses to obtain additional biodiversity indices, including sample coverage#

Hodbarrow2 <- estimateD(Hodbarrow_Nos, q = c(0,1,2), datatype = "abundance", base="coverage")
Hodbarrow2
##    Assemblage         m        Method Order.q        SC        qD    qD.LCL
## 1   Quadrat_1  193.2463   Rarefaction       0 0.9975081  5.975376  4.353247
## 2   Quadrat_1  193.2463   Rarefaction       1 0.9975081  2.349177  2.008298
## 3   Quadrat_1  193.2463   Rarefaction       2 0.9975081  1.827118  1.587406
## 4   Quadrat_2  252.7154   Rarefaction       0 0.9975081  6.847050  5.960194
## 5   Quadrat_2  252.7154   Rarefaction       1 0.9975081  3.526803  3.230030
## 6   Quadrat_2  252.7154   Rarefaction       2 0.9975081  2.731753  2.459093
## 7   Quadrat_3 1234.0000 Extrapolation       0 0.9975081 12.187737  5.662402
## 8   Quadrat_3 1234.0000 Extrapolation       1 0.9975081  4.323037  4.020444
## 9   Quadrat_3 1234.0000 Extrapolation       2 0.9975081  3.497420  3.248530
## 10  Quadrat_4  766.2629 Extrapolation       0 0.9975081 15.558731 10.242826
## 11  Quadrat_4  766.2629 Extrapolation       1 0.9975081  7.270478  6.835323
## 12  Quadrat_4  766.2629 Extrapolation       2 0.9975081  5.778112  5.372501
## 13  Quadrat_5  565.6096 Extrapolation       0 0.9975081 18.456957 13.598232
## 14  Quadrat_5  565.6096 Extrapolation       1 0.9975081 11.157573 10.406869
## 15  Quadrat_5  565.6096 Extrapolation       2 0.9975081  9.560917  8.857226
## 16  Quadrat_6  140.6078 Extrapolation       0 0.9975081  7.179738  3.131475
## 17  Quadrat_6  140.6078 Extrapolation       1 0.9975081  2.702222  2.074095
## 18  Quadrat_6  140.6078 Extrapolation       2 0.9975081  1.793061  1.420941
## 19  Quadrat_7  356.7592 Extrapolation       0 0.9975081 14.725004 10.870616
## 20  Quadrat_7  356.7592 Extrapolation       1 0.9975081  9.509648  8.577919
## 21  Quadrat_7  356.7592 Extrapolation       2 0.9975081  8.042524  7.167765
##       qD.UCL
## 1   7.597505
## 2   2.690055
## 3   2.066830
## 4   7.733905
## 5   3.823576
## 6   3.004413
## 7  18.713072
## 8   4.625631
## 9   3.746310
## 10 20.874637
## 11  7.705634
## 12  6.183722
## 13 23.315682
## 14 11.908277
## 15 10.264609
## 16 11.228002
## 17  3.330349
## 18  2.165182
## 19 18.579391
## 20 10.441378
## 21  8.917282

#Running vegan analyses for Hodbarrow, to obtain species evenness indices

R1 <- diversity(Hodbarrow_Nos$Quadrat_1)

Revenness1 <- R1/log(specnumber(Hodbarrow_Nos$Quadrat_1))

summary(Revenness1)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.4775  0.4775  0.4775  0.4775  0.4775  0.4775
R2 <- diversity(Hodbarrow_Nos$Quadrat_2)

Revenness2 <- R2/log(specnumber(Hodbarrow_Nos$Quadrat_2))

summary(Revenness2)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.6502  0.6502  0.6502  0.6502  0.6502  0.6502
R3 <- diversity(Hodbarrow_Nos$Quadrat_3)

Revenness3 <- R3/log(specnumber(Hodbarrow_Nos$Quadrat_3))

summary(Revenness3)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.6329  0.6329  0.6329  0.6329  0.6329  0.6329
R4 <- diversity(Hodbarrow_Nos$Quadrat_4)

Revenness4 <- R4/log(specnumber(Hodbarrow_Nos$Quadrat_4))

summary(Revenness4)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.7311  0.7311  0.7311  0.7311  0.7311  0.7311
R5 <- diversity(Hodbarrow_Nos$Quadrat_5)

Revenness5 <- R5/log(specnumber(Hodbarrow_Nos$Quadrat_5))

summary(Revenness5)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.8324  0.8324  0.8324  0.8324  0.8324  0.8324
R6 <- diversity(Hodbarrow_Nos$Quadrat_6)

Revenness6 <- R6/log(specnumber(Hodbarrow_Nos$Quadrat_6))

summary(Revenness6)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.5058  0.5058  0.5058  0.5058  0.5058  0.5058
R7 <- diversity(Hodbarrow_Nos$Quadrat_7)

Revenness7 <- R7/log(specnumber(Hodbarrow_Nos$Quadrat_7))

summary(Revenness7)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   0.847   0.847   0.847   0.847   0.847   0.847

#Now for some data visualisation for the Hodbarrow data, including species curves graphs#

Hodbarrow_Data_Graph1 <- ggiNEXT(x = Hodbarrow_Data, se=TRUE, 
                                 facet.var= "None", grey=TRUE)
## Scale for fill is already present.
## Adding another scale for fill, which will replace the existing scale.
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
Hodbarrow_Data_Graph1
## Warning: The shape palette can deal with a maximum of 6 discrete values because
## more than 6 becomes difficult to discriminate; you have 7. Consider
## specifying shapes manually if you must have them.
## Warning: Removed 1 rows containing missing values (`geom_point()`).

Hodbarrow_Data_Graph2 <- ggiNEXT(x = Hodbarrow_Data, se=TRUE, type = 1,
                                 facet.var= "None", grey=TRUE)
## Scale for fill is already present.
## Adding another scale for fill, which will replace the existing scale.
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
Hodbarrow_Data_Graph2
## Warning: The shape palette can deal with a maximum of 6 discrete values because
## more than 6 becomes difficult to discriminate; you have 7. Consider
## specifying shapes manually if you must have them.

## Warning: Removed 1 rows containing missing values (`geom_point()`).

Hodbarrow_Data_Graph3 <- ggiNEXT(x = Hodbarrow_Data, se=TRUE, type = 2,
                                 facet.var= "None", grey=TRUE)
## Scale for fill is already present.
## Adding another scale for fill, which will replace the existing scale.
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
Hodbarrow_Data_Graph3
## Warning: The shape palette can deal with a maximum of 6 discrete values because
## more than 6 becomes difficult to discriminate; you have 7. Consider
## specifying shapes manually if you must have them.

## Warning: Removed 1 rows containing missing values (`geom_point()`).

Hodbarrow_Data_Graph4 <- ggiNEXT(x = Hodbarrow_Data, se=TRUE, type = 3,
                                 facet.var= "None", grey=TRUE)
## Scale for fill is already present.
## Adding another scale for fill, which will replace the existing scale.
## Scale for colour is already present.
## Adding another scale for colour, which will replace the existing scale.
Hodbarrow_Data_Graph4
## Warning: The shape palette can deal with a maximum of 6 discrete values because
## more than 6 becomes difficult to discriminate; you have 7. Consider
## specifying shapes manually if you must have them.

## Warning: Removed 1 rows containing missing values (`geom_point()`).

#Warton#

#Loading the Warton data

urlfile2 <- 'https://raw.githubusercontent.com/Savannankvm/Biodiversity-analyses-for-Warton-and-Hodbarrow/PhD-files/Warton_Abundance_Data.csv'

Warton_Nos <-read.csv(urlfile2)

print(Warton_Nos)
##     Quadrat_1 Quadrat_2 Quadrat_3 Quadrat_4 Quadrat_5 Quadrat_6 Quadrat_7
## 1           0         0         0         0         0         0         0
## 2           0         0         0         0         0         0         0
## 3           0         0         0         0         0         0         0
## 4           0         0         0         0         0        27         0
## 5           0         0         0         0         0         0         0
## 6           0         0         0         0         0         0         0
## 7           0         0         0         0         0         0         0
## 8           0         0         0         0         0         0         0
## 9           1         0         0         0         0         0         0
## 10          0         0         0         0         0         0         0
## 11          0         0         0         0         0        11         0
## 12          0         0        11         0         0        10         0
## 13          0         0         0         0         0         0         0
## 14          0         0         0         0         0         0         0
## 15          0         0         0         0         0         0         0
## 16          0         0         0         0         0         0         0
## 17          0         0         0         0         0         0         0
## 18          0         0         0         0         0         0         0
## 19          0         0         0         0         0         0         0
## 20          0         0         0         0         0         0         0
## 21          0         0         0         0         0         0         0
## 22         60         0         0         0         0         0        50
## 23          0         0         0         0         0         0         0
## 24          0         0         0        20         0         0         0
## 25          0         0         0       120         0        10         0
## 26          0         0         0         0         0         0         0
## 27          0         0         0         0         0         0         0
## 28          0         0        23         0         0         0         0
## 29          0         0         0        24         0         0         0
## 30          0         0         0         0         0         0         0
## 31         11         5         4         0         0         0         3
## 32          0         0         0         0         0         0         0
## 33          0         0         0         0         0         0         0
## 34          0         0         0         0         0         0         0
## 35          0         0         0         0         0         0         0
## 36          1         0         0         0         0         0         0
## 37          0         0         0         0         0         0         0
## 38          0         0         0         0         0         0         0
## 39          0         0         0         0         0         0         0
## 40          0         0         0         0         0         0         0
## 41          0         0         0         0         0         0         0
## 42          0         0         0         0         0         0         0
## 43          0         0         0         0         0         0         0
## 44          0         0         0         0         0         0         0
## 45          0         0         0         0         0         0         0
## 46          0         0         0         0         0         0         0
## 47          0         0         0         0         0         0        50
## 48          0         0         0         0         0         0         0
## 49          0         0         0         0         0         0         0
## 50          0         0         0         0         0         0         0
## 51          0         0         0         0         0         0         0
## 52          0         0         0         0         0         0         0
## 53         16         0         0         0         0         0         0
## 54          0         0        17        55        27         5         0
## 55          0         0         0         0         0         0         0
## 56          0         0         0         0         0         0         0
## 57          0         0         0         0         0         0         0
## 58          0         0         0         0         0         0         0
## 59          0         0         0        20         0         0         0
## 60          0         0         0         0         0         0        60
## 61          0         0         0         0         0         0         0
## 62          0         0         0         0         0         0         0
## 63          0         0         0         0         0         0         0
## 64          0         0         0         0         1         0         0
## 65          0         0         0         0         0         0         0
## 66          0         0         0         0         0         0         0
## 67          0         0         0         0         0         0         0
## 68          0         0         0         0         0         0         0
## 69          0         0         0         0         0         0         0
## 70          0         0         0         0         0         0         0
## 71         42         0        40        58        70        23         0
## 72          0         0         8         3         0         0         0
## 73          0         0         0         0         0         0         0
## 74          0         0         0         0       160        10         0
## 75          0         0         0         0         0         0         0
## 76          0         0         0         0         0         0         0
## 77         60       150        60         0         0         0         0
## 78          0         0         0         0         0         0         0
## 79          0         0         0         0         0         0         0
## 80          0         0         0         0         0         0         0
## 81          0         0         0         0         0         0         0
## 82          0         0         0         0         0         0         0
## 83          0         0         0         0         0         0         0
## 84          0         0         0         0         0         0         0
## 85          0         0         0         0         0         0         0
## 86          5         0         0         0         0         0         0
## 87          0         0         0         0         0         0         0
## 88          0         0         0         0         0         0         0
## 89          0         0       220        19         0         0         0
## 90          0         0         0         0         0         0         0
## 91          0         0         0         0         0         0         0
## 92          0         0         5         0         0         0         0
## 93          0         1         0         0         6         4         0
## 94          0         0         0         0         2        63         0
## 95          0         0         0         0         0         0         0
## 96          0         0         0         0         0         0         0
## 97          0         0         0         0         0         0         0
## 98         33       286         2         0        54         0         1
## 99          0         0         0         1        19         0         0
## 100         1         0         0         0         0         1         0
## 101         0         0         0         0         0         0         0
## 102         0         0         0         0         0         0         0
## 103         0         0         0         0         0         0         0
## 104         0         0         0         0         0         0         0
## 105         0         0         0         0         0         0         0
## 106         0         0         0         0         0         0         0
## 107         0         0         0         0         0         0         0
## 108         0         0         0         0         0         0         0
## 109         0         0         0         0        30         0         0
## 110         0         0         0         0         0         0         0
## 111         0         0         0         0         0         0         0
## 112         0         0         0         0         0         0         0
## 113         0         0         0         0         0         0         0
## 114         0         0         0         0         0         0         0
## 115         0         0         0         0         0         0         0
## 116         0         0         0         0         0         0         0
## 117        60         0         0         0       140        20         0
## 118         0         0         0         0         0         0         0
## 119         0         0         0         0         0         0         0
## 120         0         0         0         0         0         0         0
## 121         0         0         0         0         0         0         0
## 122         0         0         0         0         0         0         0
## 123         0         0         0         0         0         0         0
## 124         0         0         0         0         0         0         0
## 125         0         0         0         0         0         0         0
## 126         0         0         0         0         0         0         0
## 127         0         0         0         0         0         0         0
## 128         0         1         3         2         1         0         0
## 129         0         0         0         0         0         0         0
## 130       283         7       159         0         0        20        45
## 131        60         0         0         0         0         0       110
## 132         0         0         0         0         0         0         0
## 133       162       118         0         0         0         0         0
## 134         0         0         0         0         0         0         0
## 135         0         0         0         0         0         2         0
## 136         0         0         0         0         0         0         0
## 137         0         0         0         0         0         0         0
## 138         0         0         0         0         7         0         0
## 139         0         0         0         0         0         0         0
## 140         0         0         0         0         0         0         0
## 141         0         0         0         0         0         0         0
## 142         0         0         0         0         0         0         0
## 143         0         0         0         0         0         0         0
##     Quadrat_8
## 1           0
## 2           0
## 3           0
## 4           0
## 5           0
## 6           0
## 7           0
## 8           0
## 9           0
## 10          0
## 11          0
## 12          0
## 13          0
## 14          0
## 15          0
## 16          0
## 17         20
## 18          0
## 19          0
## 20          0
## 21          0
## 22          0
## 23          0
## 24          0
## 25          0
## 26          0
## 27          0
## 28         52
## 29          0
## 30          0
## 31          0
## 32          0
## 33          0
## 34          0
## 35          8
## 36          0
## 37          0
## 38          0
## 39          0
## 40          0
## 41          0
## 42          0
## 43          0
## 44          0
## 45          0
## 46          0
## 47          0
## 48          0
## 49          0
## 50          0
## 51          0
## 52          0
## 53          0
## 54         25
## 55          0
## 56          0
## 57          0
## 58          0
## 59          0
## 60          0
## 61          0
## 62          0
## 63          0
## 64          0
## 65          0
## 66          0
## 67          0
## 68          0
## 69          0
## 70          0
## 71         13
## 72          0
## 73          0
## 74          0
## 75          0
## 76          0
## 77          0
## 78          0
## 79          0
## 80          0
## 81          0
## 82          0
## 83          0
## 84          0
## 85          0
## 86          0
## 87          0
## 88          0
## 89          0
## 90          0
## 91         80
## 92          0
## 93          0
## 94          0
## 95          0
## 96          0
## 97          0
## 98          0
## 99        114
## 100         0
## 101         0
## 102         0
## 103         0
## 104         0
## 105         0
## 106         0
## 107         0
## 108         0
## 109        20
## 110         0
## 111         0
## 112         0
## 113         0
## 114         0
## 115         0
## 116         0
## 117         0
## 118         0
## 119         0
## 120         0
## 121         0
## 122         0
## 123         0
## 124         0
## 125         0
## 126         0
## 127         0
## 128         0
## 129         0
## 130         0
## 131         0
## 132        11
## 133         0
## 134         0
## 135         0
## 136         0
## 137         0
## 138         0
## 139         0
## 140         0
## 141         0
## 142         0
## 143         0

#colSums to establish sample size for each of the quadrats.

colSums(Warton_Nos)
## Quadrat_1 Quadrat_2 Quadrat_3 Quadrat_4 Quadrat_5 Quadrat_6 Quadrat_7 Quadrat_8 
##       795       568       552       322       517       206       319       343

#Setting m to sample size for Quadrat 1. This will give me observed #qD value that will be most representative for Quadrat and Community. Will do the same #for the other communities below.

m <- c(795)

Warton_Datam <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance", size = m)

Warton_Datam
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 795      Observed       0 14.000000 12.415615 15.584385 0.9962312
## 2   Quadrat_2 567   Rarefaction       0  6.996479  6.007201  7.985756 0.9964789
## 3   Quadrat_2 568      Observed       0  7.000000  6.010069  7.989931 0.9964912
## 4   Quadrat_2 569 Extrapolation       0  7.003509  6.013229  7.993788 0.9965036
## 5   Quadrat_2 795 Extrapolation       0  7.549386  6.488212  8.610560 0.9984223
## 6   Quadrat_3 551   Rarefaction       0 12.000000 11.066808 12.933192 1.0000000
## 7   Quadrat_3 552      Observed       0 12.000000 11.066311 12.933689 1.0000000
## 8   Quadrat_3 553 Extrapolation       0 12.000000 11.065836 12.934164 1.0000000
## 9   Quadrat_3 795 Extrapolation       0 12.000000 10.957453 13.042547 1.0000000
## 10  Quadrat_4 321   Rarefaction       0  9.996894  8.336597 11.657192 0.9968944
## 11  Quadrat_4 322      Observed       0 10.000000  8.336915 11.663085 0.9969136
## 12  Quadrat_4 323 Extrapolation       0 10.003086  8.336368 11.669805 0.9969328
## 13  Quadrat_4 795 Extrapolation       0 10.472041  7.660720 13.283361 0.9998365
## 14  Quadrat_5 516   Rarefaction       0 11.996132 10.052845 13.939418 0.9961315
## 15  Quadrat_5 517      Observed       0 12.000000 10.053683 13.946317 0.9961390
## 16  Quadrat_5 518 Extrapolation       0 12.003861 10.053964 13.953758 0.9961465
## 17  Quadrat_5 795 Extrapolation       0 12.830838 10.018998 15.642679 0.9977460
## 18  Quadrat_6 205   Rarefaction       0 12.995146 11.615701 14.374591 0.9951456
## 19  Quadrat_6 206      Observed       0 13.000000 11.616361 14.383639 0.9951925
## 20  Quadrat_6 207 Extrapolation       0 13.004807 11.615739 14.393876 0.9952390
## 21  Quadrat_6 795 Extrapolation       0 13.495938 10.875421 16.116456 0.9999842
## 22  Quadrat_7 318   Rarefaction       0  6.996865  5.793679  8.200051 0.9968652
## 23  Quadrat_7 319      Observed       0  7.000000  5.795697  8.204303 1.0000000
## 24  Quadrat_7 320 Extrapolation       0  7.000000  5.794984  8.205016 1.0000000
## 25  Quadrat_7 795 Extrapolation       0  7.000000  5.626698  8.373302 1.0000000
## 26  Quadrat_8 342   Rarefaction       0  9.000000  9.000000  9.000000 1.0000000
## 27  Quadrat_8 343      Observed       0  9.000000  9.000000  9.000000 1.0000000
## 28  Quadrat_8 344 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
## 29  Quadrat_8 795 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
##       SC.LCL    SC.UCL
## 1  0.9941187 0.9983436
## 2  0.9946865 0.9982712
## 3  0.9952389 0.9977436
## 4  0.9952556 0.9977515
## 5  0.9978592 0.9989854
## 6  0.9980805 1.0000000
## 7  0.9982776 1.0000000
## 8  0.9982842 1.0000000
## 9  0.9993022 1.0000000
## 10 0.9915781 1.0000000
## 11 0.9908510 1.0000000
## 12 0.9908929 1.0000000
## 13 0.9980652 1.0000000
## 14 0.9921695 1.0000000
## 15 0.9916650 1.0000000
## 16 0.9916808 1.0000000
## 17 0.9948612 1.0000000
## 18 0.9866880 1.0000000
## 19 0.9862357 1.0000000
## 20 0.9863406 1.0000000
## 21 0.9995346 1.0000000
## 22 0.9933085 1.0000000
## 23 0.9972390 1.0000000
## 24 0.9972562 1.0000000
## 25 0.9998604 1.0000000
## 26 1.0000000 1.0000000
## 27 1.0000000 1.0000000
## 28 1.0000000 1.0000000
## 29 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9962312 795      Observed       0 14.000000 12.152050 15.847950
## 2   Quadrat_2 0.9964789 563   Rarefaction       0  6.983786  6.020563  7.947009
## 3   Quadrat_2 0.9964912 568      Observed       0  7.000000  6.035651  7.964349
## 4   Quadrat_2 0.9965036 569 Extrapolation       0  7.003509  6.038700  7.968317
## 5   Quadrat_2 0.9984223 795 Extrapolation       0  7.549386  6.486466  8.612306
## 6   Quadrat_3 1.0000000 552      Observed       0 12.000000 10.849438 13.150562
## 7   Quadrat_4 0.9968944 321   Rarefaction       0  9.995413  7.212665 12.778160
## 8   Quadrat_4 0.9969136 322      Observed       0 10.000000  7.214361 12.785639
## 9   Quadrat_4 0.9969328 323 Extrapolation       0 10.003086  7.213593 12.792580
## 10  Quadrat_4 0.9998365 795 Extrapolation       0 10.472041  7.055219 13.888863
## 11  Quadrat_5 0.9961315 516   Rarefaction       0 11.995720  8.577835 15.413605
## 12  Quadrat_5 0.9961390 517      Observed       0 12.000000  8.579354 15.420646
## 13  Quadrat_5 0.9961465 518 Extrapolation       0 12.003861  8.581580 15.426142
## 14  Quadrat_5 0.9977460 795 Extrapolation       0 12.830838  8.846311 16.815365
## 15  Quadrat_6 0.9951456 204   Rarefaction       0 12.992177 10.806870 15.177484
## 16  Quadrat_6 0.9951925 206      Observed       0 13.000000 10.809938 15.190062
## 17  Quadrat_6 0.9952390 207 Extrapolation       0 13.004807 10.810168 15.199447
## 18  Quadrat_6 0.9999842 795 Extrapolation       0 13.495938 10.795874 16.196003
## 19  Quadrat_7 0.9968652 318   Rarefaction       0  6.995767  5.618382  8.373152
## 20  Quadrat_7 1.0000000 319      Observed       0  7.000000  5.614709  8.385291
## 21  Quadrat_8 1.0000000 343      Observed       0  9.000000  9.000000  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 1.52482794 14.007619
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.22536699  6.693377
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.23699857  4.659278
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.66388551  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.07275328  3.011225
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.07201855  2.594440
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.65928739 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.21744093  4.900805
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.16330717  3.511229
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.64763186 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.28033971  5.457025
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.30237653  4.059527
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.17247264 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.23573170  5.792041
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.21516518  4.466008
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.60182960 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.44481663  8.088698
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.56705717  5.604555
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.75961931  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.15567870  4.699353
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.22021380  4.093817
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.29622047  5.764780
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.31966594  4.357576
##          UCL
## 1  19.984834
## 2   7.576800
## 3   5.588295
## 4   9.299431
## 5   3.296413
## 6   2.876748
## 7  13.292180
## 8   5.753158
## 9   4.151381
## 10 13.727746
## 11  6.555936
## 12  5.244821
## 13 18.254100
## 14  6.716092
## 15  5.309440
## 16 16.637101
## 17  9.832347
## 18  7.827379
## 19  8.488826
## 20  5.309603
## 21  4.957039
## 22  9.000000
## 23  6.925943
## 24  5.610643
n <- c(568)

Warton_Datan <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance", size = n)

Warton_Datan
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 568   Rarefaction       0 13.141557 11.826893 14.456220 0.9961859
## 2   Quadrat_1 794   Rarefaction       0 13.996226 12.341756 15.650697 0.9962264
## 3   Quadrat_1 795      Observed       0 14.000000 12.344001 15.655999 0.9962312
## 4   Quadrat_1 796 Extrapolation       0 14.003769 12.345934 15.661603 0.9962359
## 5   Quadrat_2 568      Observed       0  7.000000  6.183682  7.816318 0.9964912
## 6   Quadrat_3 551   Rarefaction       0 12.000000 11.111342 12.888658 1.0000000
## 7   Quadrat_3 552      Observed       0 12.000000 11.111044 12.888956 1.0000000
## 8   Quadrat_3 553 Extrapolation       0 12.000000 11.110781 12.889219 1.0000000
## 9   Quadrat_3 568 Extrapolation       0 12.000000 11.106512 12.893488 1.0000000
## 10  Quadrat_4 321   Rarefaction       0  9.996894  8.209746 11.784043 0.9968944
## 11  Quadrat_4 322      Observed       0 10.000000  8.209784 11.790216 0.9969136
## 12  Quadrat_4 323 Extrapolation       0 10.003086  8.208831 11.797341 0.9969328
## 13  Quadrat_4 568 Extrapolation       0 10.390295  7.799096 12.981493 0.9993303
## 14  Quadrat_5 516   Rarefaction       0 11.996132 10.123273 13.868990 0.9961315
## 15  Quadrat_5 517      Observed       0 12.000000 10.124243 13.875757 0.9961390
## 16  Quadrat_5 518 Extrapolation       0 12.003861 10.124690 13.883032 0.9961465
## 17  Quadrat_5 568 Extrapolation       0 12.187683 10.139971 14.235395 0.9965020
## 18  Quadrat_6 205   Rarefaction       0 12.995146 11.212885 14.777406 0.9951456
## 19  Quadrat_6 206      Observed       0 13.000000 11.213291 14.786709 0.9951925
## 20  Quadrat_6 207 Extrapolation       0 13.004807 11.212901 14.796714 0.9952390
## 21  Quadrat_6 568 Extrapolation       0 13.482765 10.563406 16.402124 0.9998569
## 22  Quadrat_7 318   Rarefaction       0  6.996865  5.872568  8.121162 0.9968652
## 23  Quadrat_7 319      Observed       0  7.000000  5.873738  8.126262 1.0000000
## 24  Quadrat_7 320 Extrapolation       0  7.000000  5.872855  8.127145 1.0000000
## 25  Quadrat_7 568 Extrapolation       0  7.000000  5.718989  8.281011 1.0000000
## 26  Quadrat_8 342   Rarefaction       0  9.000000  8.999192  9.000808 1.0000000
## 27  Quadrat_8 343      Observed       0  9.000000  9.000000  9.000000 1.0000000
## 28  Quadrat_8 344 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
## 29  Quadrat_8 568 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
##       SC.LCL    SC.UCL
## 1  0.9939827 0.9983890
## 2  0.9938670 0.9985859
## 3  0.9935524 0.9989100
## 4  0.9935610 0.9989108
## 5  0.9954492 0.9975333
## 6  0.9979597 1.0000000
## 7  0.9981343 1.0000000
## 8  0.9981405 1.0000000
## 9  0.9982310 1.0000000
## 10 0.9914990 1.0000000
## 11 0.9907861 1.0000000
## 12 0.9908274 1.0000000
## 13 0.9964021 1.0000000
## 14 0.9920470 1.0000000
## 15 0.9916740 1.0000000
## 16 0.9916883 1.0000000
## 17 0.9923601 1.0000000
## 18 0.9864128 1.0000000
## 19 0.9855614 1.0000000
## 20 0.9856654 1.0000000
## 21 0.9980007 1.0000000
## 22 0.9933785 1.0000000
## 23 0.9972390 1.0000000
## 24 0.9972562 1.0000000
## 25 0.9994205 1.0000000
## 26 0.9991919 1.0000000
## 27 1.0000000 1.0000000
## 28 1.0000000 1.0000000
## 29 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9961859 568   Rarefaction       0 13.141557 11.057642 15.225471
## 2   Quadrat_1 0.9962264 791   Rarefaction       0 13.984626 11.767185 16.202067
## 3   Quadrat_1 0.9962312 795      Observed       0 14.000000 11.776244 16.223756
## 4   Quadrat_1 0.9962359 796 Extrapolation       0 14.003769 11.778047 16.229491
## 5   Quadrat_2 0.9964912 568      Observed       0  7.000000  6.137040  7.862960
## 6   Quadrat_3 1.0000000 552      Observed       0 12.000000 10.807940 13.192060
## 7   Quadrat_4 0.9968944 321   Rarefaction       0  9.995413  7.110567 12.880258
## 8   Quadrat_4 0.9969136 322      Observed       0 10.000000  7.114921 12.885079
## 9   Quadrat_4 0.9969328 323 Extrapolation       0 10.003086  7.114036 12.892137
## 10  Quadrat_4 0.9993303 568 Extrapolation       0 10.390295  6.968060 13.812529
## 11  Quadrat_5 0.9961315 516   Rarefaction       0 11.995720  8.649427 15.342013
## 12  Quadrat_5 0.9961390 517      Observed       0 12.000000  8.650932 15.349068
## 13  Quadrat_5 0.9961465 518 Extrapolation       0 12.003861  8.652904 15.354818
## 14  Quadrat_5 0.9965020 568 Extrapolation       0 12.187683  8.710117 15.665248
## 15  Quadrat_6 0.9951456 204   Rarefaction       0 12.992177 10.289818 15.694536
## 16  Quadrat_6 0.9951925 206      Observed       0 13.000000 10.292784 15.707216
## 17  Quadrat_6 0.9952390 207 Extrapolation       0 13.004807 10.292638 15.716977
## 18  Quadrat_6 0.9998569 568 Extrapolation       0 13.482765 10.224063 16.741467
## 19  Quadrat_7 0.9968652 318   Rarefaction       0  6.995767  5.705858  8.285677
## 20  Quadrat_7 1.0000000 319      Observed       0  7.000000  5.665491  8.334509
## 21  Quadrat_8 1.0000000 343      Observed       0  9.000000  9.000000  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 1.82579137 14.000000
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.22793245  6.688349
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.23141918  4.670213
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.68624396  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.08263051  2.991866
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.08272140  2.573463
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.58710035 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.26062468  4.816167
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.19192645  3.455136
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.80905621 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.28727399  5.443434
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.30067837  4.062855
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.21903404 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.25572214  5.752860
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.22265425  4.451330
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.57160624 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.51587688  7.949423
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.61344554  5.513636
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.67979500  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.15097645  4.708570
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.20379469  4.125998
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.27399094  5.808350
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.29134157  4.413090
##          UCL
## 1  20.574712
## 2   7.581828
## 3   5.577360
## 4   9.343253
## 5   3.315772
## 6   2.897725
## 7  13.150696
## 8   5.837797
## 9   4.207474
## 10 14.044132
## 11  6.569527
## 12  5.241493
## 13 18.345358
## 14  6.755273
## 15  5.324119
## 16 16.577864
## 17  9.971623
## 18  7.918298
## 19  8.332374
## 20  5.300386
## 21  4.924859
## 22  9.000000
## 23  6.882374
## 24  5.555128
o <- c(552)

Warton_Datao <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance", size = o)

Warton_Datao
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 552   Rarefaction       0 13.080425 11.620578 14.540271 0.9961730
## 2   Quadrat_1 794   Rarefaction       0 13.996226 12.252852 15.739601 0.9962264
## 3   Quadrat_1 795      Observed       0 14.000000 12.255473 15.744527 0.9962312
## 4   Quadrat_1 796 Extrapolation       0 14.003769 12.257783 15.749754 0.9962359
## 5   Quadrat_2 552   Rarefaction       0  6.943662  6.080713  7.806611 0.9964789
## 6   Quadrat_2 567   Rarefaction       0  6.996479  6.125858  7.867100 0.9964789
## 7   Quadrat_2 568      Observed       0  7.000000  6.128860  7.871140 0.9964912
## 8   Quadrat_2 569 Extrapolation       0  7.003509  6.131990  7.875028 0.9965036
## 9   Quadrat_3 552      Observed       0 12.000000 11.111044 12.888956 1.0000000
## 10  Quadrat_4 321   Rarefaction       0  9.996894  8.747276 11.246513 0.9968944
## 11  Quadrat_4 322      Observed       0 10.000000  8.747825 11.252175 0.9969136
## 12  Quadrat_4 323 Extrapolation       0 10.003086  8.747956 11.258217 0.9969328
## 13  Quadrat_4 552 Extrapolation       0 10.378994  8.482562 12.275427 0.9992604
## 14  Quadrat_5 516   Rarefaction       0 11.996132  9.792869 14.199394 0.9961315
## 15  Quadrat_5 517      Observed       0 12.000000  9.793896 14.206104 0.9961390
## 16  Quadrat_5 518 Extrapolation       0 12.003861  9.794553 14.213169 0.9961465
## 17  Quadrat_5 552 Extrapolation       0 12.130784  9.813256 14.448312 0.9963920
## 18  Quadrat_6 205   Rarefaction       0 12.995146 11.272501 14.717790 0.9951456
## 19  Quadrat_6 206      Observed       0 13.000000 11.272180 14.727820 0.9951925
## 20  Quadrat_6 207 Extrapolation       0 13.004807 11.271069 14.738546 0.9952390
## 21  Quadrat_6 552 Extrapolation       0 13.480277 10.601425 16.359128 0.9998329
## 22  Quadrat_7 318   Rarefaction       0  6.996865  5.969604  8.024126 0.9968652
## 23  Quadrat_7 319      Observed       0  7.000000  5.970471  8.029529 1.0000000
## 24  Quadrat_7 320 Extrapolation       0  7.000000  5.968928  8.031072 1.0000000
## 25  Quadrat_7 552 Extrapolation       0  7.000000  5.706535  8.293465 1.0000000
## 26  Quadrat_8 342   Rarefaction       0  9.000000  9.000000  9.000000 1.0000000
## 27  Quadrat_8 343      Observed       0  9.000000  9.000000  9.000000 1.0000000
## 28  Quadrat_8 344 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
## 29  Quadrat_8 552 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
##       SC.LCL    SC.UCL
## 1  0.9943526 0.9979934
## 2  0.9941127 0.9983402
## 3  0.9938255 0.9986368
## 4  0.9938344 0.9986374
## 5  0.9948809 0.9980769
## 6  0.9948529 0.9981049
## 7  0.9954492 0.9975333
## 8  0.9954652 0.9975419
## 9  0.9982501 1.0000000
## 10 0.9913552 1.0000000
## 11 0.9906127 1.0000000
## 12 0.9906598 1.0000000
## 13 0.9965284 1.0000000
## 14 0.9918802 1.0000000
## 15 0.9914320 1.0000000
## 16 0.9914469 1.0000000
## 17 0.9919310 1.0000000
## 18 0.9865579 1.0000000
## 19 0.9858341 1.0000000
## 20 0.9859400 1.0000000
## 21 0.9977221 1.0000000
## 22 0.9929873 1.0000000
## 23 0.9961463 1.0000000
## 24 0.9961704 1.0000000
## 25 0.9991058 1.0000000
## 26 1.0000000 1.0000000
## 27 1.0000000 1.0000000
## 28 1.0000000 1.0000000
## 29 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9961730 552   Rarefaction       0 13.080425 11.226634 14.934215
## 2   Quadrat_1 0.9962264 791   Rarefaction       0 13.984626 11.930500 16.038752
## 3   Quadrat_1 0.9962312 795      Observed       0 14.000000 11.935210 16.064790
## 4   Quadrat_1 0.9962359 796 Extrapolation       0 14.003769 11.937422 16.070115
## 5   Quadrat_2 0.9964789 552   Rarefaction       0  6.943662  6.097519  7.789805
## 6   Quadrat_2 0.9964789 563   Rarefaction       0  6.983786  6.137643  7.829929
## 7   Quadrat_2 0.9964912 568      Observed       0  7.000000  6.153643  7.846357
## 8   Quadrat_2 0.9965036 569 Extrapolation       0  7.003509  6.156931  7.850086
## 9   Quadrat_3 1.0000000 552      Observed       0 12.000000 10.904594 13.095406
## 10  Quadrat_4 0.9968944 321   Rarefaction       0  9.995413  7.868536 12.122289
## 11  Quadrat_4 0.9969136 322      Observed       0 10.000000  7.869891 12.130109
## 12  Quadrat_4 0.9969328 323 Extrapolation       0 10.003086  7.869632 12.136540
## 13  Quadrat_4 0.9992604 552 Extrapolation       0 10.378994  7.806996 12.950992
## 14  Quadrat_5 0.9961315 516   Rarefaction       0 11.995720  8.277978 15.713462
## 15  Quadrat_5 0.9961390 517      Observed       0 12.000000  8.279257 15.720743
## 16  Quadrat_5 0.9961465 518 Extrapolation       0 12.003861  8.281435 15.726287
## 17  Quadrat_5 0.9963920 552 Extrapolation       0 12.130784  8.314163 15.947406
## 18  Quadrat_6 0.9951456 204   Rarefaction       0 12.992177 10.246586 15.737768
## 19  Quadrat_6 0.9951925 206      Observed       0 13.000000 10.250161 15.749839
## 20  Quadrat_6 0.9952390 207 Extrapolation       0 13.004807 10.249380 15.760235
## 21  Quadrat_6 0.9998329 552 Extrapolation       0 13.480277 10.164392 16.796161
## 22  Quadrat_7 0.9968652 318   Rarefaction       0  6.995767  5.728457  8.263077
## 23  Quadrat_7 1.0000000 319      Observed       0  7.000000  5.604818  8.395182
## 24  Quadrat_8 1.0000000 343      Observed       0  9.000000  9.000000  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 1.95007441 14.000000
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.21496514  6.713764
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.20660970  4.718839
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.73112210  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.08592884  2.985402
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.08338273  2.572167
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.90674348 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.20002903  4.934932
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.16484676  3.508212
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.50248608 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.27242907  5.472529
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.31789531  4.029111
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.11548042 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.23504735  5.793382
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.22812096  4.440616
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.38426293 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.45938987  8.060135
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.52220000  5.692474
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.74265095  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.15822049  4.694372
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.21847279  4.097229
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.29820547  5.760890
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.32312367  4.350799
##          UCL
## 1  20.818302
## 2   7.556412
## 3   5.528734
## 4   9.431212
## 5   3.322237
## 6   2.899021
## 7  13.777185
## 8   5.719031
## 9   4.154399
## 10 13.443266
## 11  6.540432
## 12  5.275237
## 13 18.142397
## 14  6.714751
## 15  5.334833
## 16 16.210678
## 17  9.860910
## 18  7.739460
## 19  8.455569
## 20  5.314585
## 21  4.953627
## 22  9.000000
## 23  6.929834
## 24  5.617420
p <- c(322)

Warton_Datap <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance", size = p)

Warton_Datap
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 322   Rarefaction       0 12.137804 11.081728 13.193881 0.9953642
## 2   Quadrat_1 794   Rarefaction       0 13.996226 12.081672 15.910781 0.9962264
## 3   Quadrat_1 795      Observed       0 14.000000 12.084131 15.915869 0.9962312
## 4   Quadrat_1 796 Extrapolation       0 14.003769 12.085963 15.921575 0.9962359
## 5   Quadrat_2 322   Rarefaction       0  6.116193  5.300485  6.931902 0.9960988
## 6   Quadrat_2 567   Rarefaction       0  6.996479  5.923162  8.069796 0.9964789
## 7   Quadrat_2 568      Observed       0  7.000000  5.925753  8.074247 0.9964912
## 8   Quadrat_2 569 Extrapolation       0  7.003509  5.928647  8.078371 0.9965036
## 9   Quadrat_3 322   Rarefaction       0 11.712217 10.769682 12.654752 0.9967434
## 10  Quadrat_3 551   Rarefaction       0 12.000000 11.066800 12.933200 1.0000000
## 11  Quadrat_3 552      Observed       0 12.000000 11.066311 12.933689 1.0000000
## 12  Quadrat_3 553 Extrapolation       0 12.000000 11.065877 12.934123 1.0000000
## 13  Quadrat_4 322      Observed       0 10.000000  8.365444 11.634556 0.9969136
## 14  Quadrat_5 322   Rarefaction       0 11.100084  9.796067 12.404101 0.9945563
## 15  Quadrat_5 516   Rarefaction       0 11.996132 10.277296 13.714967 0.9961315
## 16  Quadrat_5 517      Observed       0 12.000000 10.278999 13.721001 0.9961390
## 17  Quadrat_5 518 Extrapolation       0 12.003861 10.280389 13.727333 0.9961465
## 18  Quadrat_6 205   Rarefaction       0 12.995146 11.335020 14.655271 0.9951456
## 19  Quadrat_6 206      Observed       0 13.000000 11.334560 14.665440 0.9951925
## 20  Quadrat_6 207 Extrapolation       0 13.004807 11.333014 14.676601 0.9952390
## 21  Quadrat_6 322 Extrapolation       0 13.336232 11.027568 15.644896 0.9984412
## 22  Quadrat_7 318   Rarefaction       0  6.996865  6.048429  7.945302 0.9968652
## 23  Quadrat_7 319      Observed       0  7.000000  6.049666  7.950334 1.0000000
## 24  Quadrat_7 320 Extrapolation       0  7.000000  6.048643  7.951357 1.0000000
## 25  Quadrat_7 322 Extrapolation       0  7.000000  6.046585  7.953415 1.0000000
## 26  Quadrat_8 322   Rarefaction       0  9.000000  8.999007  9.000993 1.0000000
## 27  Quadrat_8 342   Rarefaction       0  9.000000  9.000000  9.000000 1.0000000
## 28  Quadrat_8 343      Observed       0  9.000000  9.000000  9.000000 1.0000000
## 29  Quadrat_8 344 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
##       SC.LCL    SC.UCL
## 1  0.9925143 0.9982142
## 2  0.9941916 0.9982612
## 3  0.9937823 0.9986800
## 4  0.9937909 0.9986809
## 5  0.9937165 0.9984812
## 6  0.9947656 0.9981922
## 7  0.9952376 0.9977449
## 8  0.9952531 0.9977541
## 9  0.9945262 0.9989605
## 10 0.9975950 1.0000000
## 11 0.9976892 1.0000000
## 12 0.9976962 1.0000000
## 13 0.9904479 1.0000000
## 14 0.9912651 0.9978475
## 15 0.9923794 0.9998837
## 16 0.9921344 1.0000000
## 17 0.9921493 1.0000000
## 18 0.9855712 1.0000000
## 19 0.9846841 1.0000000
## 20 0.9847935 1.0000000
## 21 0.9927060 1.0000000
## 22 0.9930920 1.0000000
## 23 0.9966695 1.0000000
## 24 0.9966903 1.0000000
## 25 0.9967315 1.0000000
## 26 0.9999053 1.0000000
## 27 1.0000000 1.0000000
## 28 1.0000000 1.0000000
## 29 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9953642 322   Rarefaction       0 12.137804 10.429181 13.846428
## 2   Quadrat_1 0.9962264 791   Rarefaction       0 13.984626 11.896634 16.072618
## 3   Quadrat_1 0.9962312 795      Observed       0 14.000000 11.909687 16.090313
## 4   Quadrat_1 0.9962359 796 Extrapolation       0 14.003769 11.911599 16.095939
## 5   Quadrat_2 0.9960988 322   Rarefaction       0  6.116193  5.136639  7.095747
## 6   Quadrat_2 0.9964789 563   Rarefaction       0  6.983786  5.969460  7.998112
## 7   Quadrat_2 0.9964912 568      Observed       0  7.000000  5.984222  8.015778
## 8   Quadrat_2 0.9965036 569 Extrapolation       0  7.003509  5.986568  8.020449
## 9   Quadrat_3 0.9967434 322   Rarefaction       0 11.712217 10.664766 12.759668
## 10  Quadrat_3 1.0000000 552      Observed       0 12.000000 10.589562 13.410438
## 11  Quadrat_4 0.9969136 322      Observed       0 10.000000  6.937288 13.062712
## 12  Quadrat_5 0.9945563 322   Rarefaction       0 11.100084  8.651533 13.548636
## 13  Quadrat_5 0.9961315 516   Rarefaction       0 11.995720  9.253122 14.738318
## 14  Quadrat_5 0.9961390 517      Observed       0 12.000000  9.254970 14.745030
## 15  Quadrat_5 0.9961465 518 Extrapolation       0 12.003861  9.257612 14.750110
## 16  Quadrat_6 0.9951456 204   Rarefaction       0 12.992177 10.274365 15.709989
## 17  Quadrat_6 0.9951925 206      Observed       0 13.000000 10.276214 15.723786
## 18  Quadrat_6 0.9952390 207 Extrapolation       0 13.004807 10.275057 15.734558
## 19  Quadrat_6 0.9984412 322 Extrapolation       0 13.336232 10.185071 16.487393
## 20  Quadrat_7 0.9968652 318   Rarefaction       0  6.995767  5.811499  8.180036
## 21  Quadrat_7 1.0000000 319      Observed       0  7.000000  5.776651  8.223349
## 22  Quadrat_8 1.0000000 322   Rarefaction       0  9.000000  8.999997  9.000003
## 23  Quadrat_8 1.0000000 343      Observed       0  9.000000  9.000000  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 1.90415470 14.000000
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.20224507  6.738695
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.19015529  4.751089
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.69039265  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.09843521  2.960890
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.08899162  2.561174
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.68445874 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.24061028  4.855394
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.19885357  3.441559
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.61800809 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.30023347  5.418034
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.33633496  3.992970
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.48436342 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.24840335  5.767205
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.23605542  4.425064
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.44913206 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.58087399  7.822031
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.66691640  5.408835
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.66099005  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.15260593  4.705376
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.20020142  4.133041
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.25912372  5.837489
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.28721251  4.421183
##          UCL
## 1  20.728301
## 2   7.531481
## 3   5.496484
## 4   9.351384
## 5   3.346749
## 6   2.910014
## 7  13.341514
## 8   5.798569
## 9   4.221051
## 10 13.669685
## 11  6.594927
## 12  5.311378
## 13 18.865394
## 14  6.740928
## 15  5.350385
## 16 16.337819
## 17 10.099015
## 18  8.023099
## 19  8.295517
## 20  5.303580
## 21  4.917816
## 22  9.000000
## 23  6.853235
## 24  5.547036
q <- c(517)

Warton_Dataq <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance", size = q)

Warton_Dataq
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 517   Rarefaction       0 12.945828 11.515727 14.375929 0.9961342
## 2   Quadrat_1 794   Rarefaction       0 13.996226 12.065736 15.926717 0.9962264
## 3   Quadrat_1 795      Observed       0 14.000000 12.067833 15.932167 0.9962312
## 4   Quadrat_1 796 Extrapolation       0 14.003769 12.069665 15.937873 0.9962359
## 5   Quadrat_2 517   Rarefaction       0  6.820418  6.110514  7.530321 0.9964784
## 6   Quadrat_2 567   Rarefaction       0  6.996479  6.257337  7.735621 0.9964789
## 7   Quadrat_2 568      Observed       0  7.000000  6.260262  7.739738 0.9964912
## 8   Quadrat_2 569 Extrapolation       0  7.003509  6.263388  7.743630 0.9965036
## 9   Quadrat_3 517   Rarefaction       0 11.995838 11.174650 12.817027 0.9997546
## 10  Quadrat_3 551   Rarefaction       0 12.000000 11.179874 12.820126 1.0000000
## 11  Quadrat_3 552      Observed       0 12.000000 11.179849 12.820151 1.0000000
## 12  Quadrat_3 553 Extrapolation       0 12.000000 11.179546 12.820454 1.0000000
## 13  Quadrat_4 321   Rarefaction       0  9.996894  8.249058 11.744730 0.9968944
## 14  Quadrat_4 322      Observed       0 10.000000  8.248745 11.751255 0.9969136
## 15  Quadrat_4 323 Extrapolation       0 10.003086  8.247574 11.758599 0.9969328
## 16  Quadrat_4 517 Extrapolation       0 10.349987  7.920216 12.779759 0.9990807
## 17  Quadrat_5 517      Observed       0 12.000000  9.617245 14.382755 0.9961390
## 18  Quadrat_6 205   Rarefaction       0 12.995146 11.149913 14.840378 0.9951456
## 19  Quadrat_6 206      Observed       0 13.000000 11.149490 14.850510 0.9951925
## 20  Quadrat_6 207 Extrapolation       0 13.004807 11.148359 14.861256 0.9952390
## 21  Quadrat_6 517 Extrapolation       0 13.473277 10.517059 16.429495 0.9997653
## 22  Quadrat_7 318   Rarefaction       0  6.996865  5.878943  8.114787 0.9968652
## 23  Quadrat_7 319      Observed       0  7.000000  5.880021  8.119979 1.0000000
## 24  Quadrat_7 320 Extrapolation       0  7.000000  5.878577  8.121423 1.0000000
## 25  Quadrat_7 517 Extrapolation       0  7.000000  5.664206  8.335794 1.0000000
## 26  Quadrat_8 342   Rarefaction       0  9.000000  9.000000  9.000000 1.0000000
## 27  Quadrat_8 343      Observed       0  9.000000  9.000000  9.000000 1.0000000
## 28  Quadrat_8 344 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
## 29  Quadrat_8 517 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
##       SC.LCL    SC.UCL
## 1  0.9937593 0.9985092
## 2  0.9940963 0.9983565
## 3  0.9937443 0.9987180
## 4  0.9937525 0.9987193
## 5  0.9951025 0.9978543
## 6  0.9950846 0.9978731
## 7  0.9956664 0.9973161
## 8  0.9956816 0.9973256
## 9  0.9975587 1.0000000
## 10 0.9977135 1.0000000
## 11 0.9977839 1.0000000
## 12 0.9977915 1.0000000
## 13 0.9910886 1.0000000
## 14 0.9904997 1.0000000
## 15 0.9905430 1.0000000
## 16 0.9955986 1.0000000
## 17 0.9911143 1.0000000
## 18 0.9866162 1.0000000
## 19 0.9856410 1.0000000
## 20 0.9857464 1.0000000
## 21 0.9975357 1.0000000
## 22 0.9929223 1.0000000
## 23 0.9964484 1.0000000
## 24 0.9964706 1.0000000
## 25 0.9989736 1.0000000
## 26 1.0000000 1.0000000
## 27 1.0000000 1.0000000
## 28 1.0000000 1.0000000
## 29 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9961342 517   Rarefaction       0 12.945828 11.114586 14.777070
## 2   Quadrat_1 0.9962264 791   Rarefaction       0 13.984626 11.864431 16.104821
## 3   Quadrat_1 0.9962312 795      Observed       0 14.000000 11.873667 16.126333
## 4   Quadrat_1 0.9962359 796 Extrapolation       0 14.003769 11.875430 16.132108
## 5   Quadrat_2 0.9964784 517   Rarefaction       0  6.820418  6.154168  7.486667
## 6   Quadrat_2 0.9964789 563   Rarefaction       0  6.983786  6.317520  7.650052
## 7   Quadrat_2 0.9964912 568      Observed       0  7.000000  6.333306  7.666694
## 8   Quadrat_2 0.9965036 569 Extrapolation       0  7.003509  6.336384  7.670634
## 9   Quadrat_3 0.9997546 517   Rarefaction       0 11.995838 10.852173 13.139504
## 10  Quadrat_3 1.0000000 552      Observed       0 12.000000 10.813043 13.186957
## 11  Quadrat_4 0.9968944 321   Rarefaction       0  9.995413  7.088557 12.902268
## 12  Quadrat_4 0.9969136 322      Observed       0 10.000000  7.089132 12.910868
## 13  Quadrat_4 0.9969328 323 Extrapolation       0 10.003086  7.088657 12.917515
## 14  Quadrat_4 0.9990807 517 Extrapolation       0 10.349987  6.999569 13.700406
## 15  Quadrat_5 0.9961390 517      Observed       0 12.000000  7.391332 16.608668
## 16  Quadrat_6 0.9951456 204   Rarefaction       0 12.992177 10.224363 15.759991
## 17  Quadrat_6 0.9951925 206      Observed       0 13.000000 10.227103 15.772897
## 18  Quadrat_6 0.9952390 207 Extrapolation       0 13.004807 10.226457 15.783158
## 19  Quadrat_6 0.9997653 517 Extrapolation       0 13.473277 10.124802 16.821752
## 20  Quadrat_7 0.9968652 318   Rarefaction       0  6.995767  5.594736  8.396799
## 21  Quadrat_7 1.0000000 319      Observed       0  7.000000  5.553254  8.446746
## 22  Quadrat_8 1.0000000 343      Observed       0  9.000000  9.000000  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 2.07062080 14.000000
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.21662505  6.710511
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.21821498  4.696093
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.61553206  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.08850986  2.980343
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.08765701  2.563789
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.83522226 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.22595898  4.884110
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.17494508  3.488419
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.55566392 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.30556776  5.407579
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.32169759  4.021658
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.34363419 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.27466283  5.715737
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.23947377  4.418364
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.87436503 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.54059860  7.900969
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.63483331  5.471716
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.59931791  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.15565381  4.699402
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.22944160  4.075731
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.24052071  5.873950
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.28084395  4.433665
##          UCL
## 1  21.054569
## 2   7.559666
## 3   5.551480
## 4   9.204660
## 5   3.327295
## 6   2.907398
## 7  13.637006
## 8   5.769853
## 9   4.174191
## 10 13.547492
## 11  6.605382
## 12  5.282690
## 13 18.589570
## 14  6.792396
## 15  5.357084
## 16 17.171261
## 17 10.020077
## 18  7.960217
## 19  8.174642
## 20  5.309554
## 21  4.975126
## 22  9.000000
## 23  6.816774
## 24  5.534553
r <- c(206)

Warton_Datar <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance", size = r)

Warton_Datar
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 206   Rarefaction       0 11.511241 10.796139 12.226342 0.9934525
## 2   Quadrat_1 794   Rarefaction       0 13.996226 12.556116 15.436337 0.9962264
## 3   Quadrat_1 795      Observed       0 14.000000 12.558638 15.441362 0.9962312
## 4   Quadrat_1 796 Extrapolation       0 14.003769 12.560684 15.446854 0.9962359
## 5   Quadrat_2 206   Rarefaction       0  5.579448  4.786611  6.372286 0.9942326
## 6   Quadrat_2 567   Rarefaction       0  6.996479  5.852468  8.140489 0.9964789
## 7   Quadrat_2 568      Observed       0  7.000000  5.855098  8.144902 0.9964912
## 8   Quadrat_2 569 Extrapolation       0  7.003509  5.858049  8.148968 0.9965036
## 9   Quadrat_3 206   Rarefaction       0 11.084026 10.311234 11.856819 0.9917208
## 10  Quadrat_3 551   Rarefaction       0 12.000000 11.239993 12.760007 1.0000000
## 11  Quadrat_3 552      Observed       0 12.000000 11.239362 12.760638 1.0000000
## 12  Quadrat_3 553 Extrapolation       0 12.000000 11.238841 12.761159 1.0000000
## 13  Quadrat_4 206   Rarefaction       0  9.464713  8.132265 10.797160 0.9934801
## 14  Quadrat_4 321   Rarefaction       0  9.996894  8.447043 11.546745 0.9968944
## 15  Quadrat_4 322      Observed       0 10.000000  8.448111 11.551889 0.9969136
## 16  Quadrat_4 323 Extrapolation       0 10.003086  8.448617 11.557556 0.9969328
## 17  Quadrat_5 206   Rarefaction       0 10.361249  9.367007 11.355490 0.9922834
## 18  Quadrat_5 516   Rarefaction       0 11.996132 10.082852 13.909411 0.9961315
## 19  Quadrat_5 517      Observed       0 12.000000 10.082904 13.917096 0.9961390
## 20  Quadrat_5 518 Extrapolation       0 12.003861 10.082921 13.924801 0.9961465
## 21  Quadrat_6 206      Observed       0 13.000000 11.331268 14.668732 0.9951925
## 22  Quadrat_7 206   Rarefaction       0  6.602082  5.699299  7.504865 0.9957054
## 23  Quadrat_7 318   Rarefaction       0  6.996865  5.932893  8.060838 0.9968652
## 24  Quadrat_7 319      Observed       0  7.000000  5.934547  8.065453 1.0000000
## 25  Quadrat_7 320 Extrapolation       0  7.000000  5.933471  8.066529 1.0000000
## 26  Quadrat_8 206   Rarefaction       0  8.999392  8.988427  9.010357 0.9999636
## 27  Quadrat_8 342   Rarefaction       0  9.000000  9.000000  9.000000 1.0000000
## 28  Quadrat_8 343      Observed       0  9.000000  9.000000  9.000000 1.0000000
## 29  Quadrat_8 344 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
##       SC.LCL    SC.UCL
## 1  0.9909034 0.9960015
## 2  0.9941363 0.9983166
## 3  0.9937759 0.9986864
## 4  0.9937837 0.9986881
## 5  0.9914476 0.9970177
## 6  0.9947360 0.9982217
## 7  0.9953198 0.9976627
## 8  0.9953355 0.9976716
## 9  0.9892480 0.9941936
## 10 0.9977316 1.0000000
## 11 0.9977292 1.0000000
## 12 0.9977370 1.0000000
## 13 0.9885541 0.9984061
## 14 0.9915497 1.0000000
## 15 0.9905852 1.0000000
## 16 0.9906289 1.0000000
## 17 0.9879827 0.9965840
## 18 0.9911039 1.0000000
## 19 0.9909963 1.0000000
## 20 0.9910108 1.0000000
## 21 0.9873303 1.0000000
## 22 0.9923158 0.9990950
## 23 0.9933194 1.0000000
## 24 0.9970576 1.0000000
## 25 0.9970760 1.0000000
## 26 0.9996136 1.0000000
## 27 1.0000000 1.0000000
## 28 1.0000000 1.0000000
## 29 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9934525 206   Rarefaction       0 11.511241 10.444373 12.578108
## 2   Quadrat_1 0.9962264 791   Rarefaction       0 13.984626 12.130344 15.838908
## 3   Quadrat_1 0.9962312 795      Observed       0 14.000000 12.134091 15.865909
## 4   Quadrat_1 0.9962359 796 Extrapolation       0 14.003769 12.135966 15.871571
## 5   Quadrat_2 0.9942326 206   Rarefaction       0  5.579448  4.614613  6.544283
## 6   Quadrat_2 0.9964789 563   Rarefaction       0  6.983786  5.865754  8.101818
## 7   Quadrat_2 0.9964912 568      Observed       0  7.000000  5.880839  8.119161
## 8   Quadrat_2 0.9965036 569 Extrapolation       0  7.003509  5.883272  8.123746
## 9   Quadrat_3 0.9917208 206   Rarefaction       0 11.084027 10.302655 11.865399
## 10  Quadrat_3 1.0000000 552      Observed       0 12.000000 10.814445 13.185555
## 11  Quadrat_4 0.9934801 206   Rarefaction       0  9.464713  7.085137 11.844288
## 12  Quadrat_4 0.9968944 321   Rarefaction       0  9.995413  7.604528 12.386297
## 13  Quadrat_4 0.9969136 322      Observed       0 10.000000  7.600223 12.399777
## 14  Quadrat_4 0.9969328 323 Extrapolation       0 10.003086  7.600142 12.406030
## 15  Quadrat_5 0.9922834 206   Rarefaction       0 10.361249  8.150992 12.571505
## 16  Quadrat_5 0.9961315 516   Rarefaction       0 11.995720  8.243951 15.747489
## 17  Quadrat_5 0.9961390 517      Observed       0 12.000000  8.244933 15.755067
## 18  Quadrat_5 0.9961465 518 Extrapolation       0 12.003861  8.246918 15.760804
## 19  Quadrat_6 0.9951925 206      Observed       0 13.000000 10.865558 15.134442
## 20  Quadrat_7 0.9957054 206   Rarefaction       0  6.602082  5.314770  7.889394
## 21  Quadrat_7 0.9968652 318   Rarefaction       0  6.995767  5.707590  8.283944
## 22  Quadrat_7 1.0000000 319      Observed       0  7.000000  5.687528  8.312472
## 23  Quadrat_8 0.9999636 206   Rarefaction       0  8.999392  8.999317  8.999467
## 24  Quadrat_8 1.0000000 343      Observed       0  9.000000  9.000000  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 1.64554935 14.000000
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.21251860  6.718560
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.22087283  4.690884
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.77680788  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.09353918  2.970486
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.09587506  2.547682
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.58338861 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.20490662  4.925372
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.15237585  3.532654
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.74021474 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.28353923  5.450754
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.31455906  4.035649
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.57912370 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.25278705  5.758613
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.25094346  4.395884
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.64408587 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.57087563  7.841627
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.69913077  5.345696
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.64457440  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.16433605  4.682385
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.23373853  4.067309
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.24581477  5.863574
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.28232376  4.430765
##          UCL
## 1  20.221444
## 2   7.551617
## 3   5.556689
## 4   9.520755
## 5   3.337153
## 6   2.923506
## 7  13.143421
## 8   5.728591
## 9   4.129956
## 10 13.909205
## 11  6.562207
## 12  5.268698
## 13 19.051121
## 14  6.749520
## 15  5.379565
## 16 16.719922
## 17 10.079418
## 18  8.086238
## 19  8.263343
## 20  5.326571
## 21  4.983547
## 22  9.000000
## 23  6.827150
## 24  5.537454
s <- c(319)

Warton_Datas <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance", size = s)

Warton_Datas
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 319   Rarefaction       0 12.123846 11.165735 13.081956 0.9953385
## 2   Quadrat_1 794   Rarefaction       0 13.996226 12.271490 15.720963 0.9962264
## 3   Quadrat_1 795      Observed       0 14.000000 12.273996 15.726004 0.9962312
## 4   Quadrat_1 796 Extrapolation       0 14.003769 12.276270 15.731268 0.9962359
## 5   Quadrat_2 319   Rarefaction       0  6.104448  5.427043  6.781852 0.9960777
## 6   Quadrat_2 567   Rarefaction       0  6.996479  6.204131  7.788827 0.9964789
## 7   Quadrat_2 568      Observed       0  7.000000  6.207066  7.792934 0.9964912
## 8   Quadrat_2 569 Extrapolation       0  7.003509  6.210230  7.796788 0.9965036
## 9   Quadrat_3 319   Rarefaction       0 11.702282 10.783715 12.620849 0.9966607
## 10  Quadrat_3 551   Rarefaction       0 12.000000 11.179700 12.820300 1.0000000
## 11  Quadrat_3 552      Observed       0 12.000000 11.179849 12.820151 1.0000000
## 12  Quadrat_3 553 Extrapolation       0 12.000000 11.179719 12.820281 1.0000000
## 13  Quadrat_4 319   Rarefaction       0  9.990625  8.188870 11.792380 0.9968555
## 14  Quadrat_4 321   Rarefaction       0  9.996894  8.191209 11.802580 0.9968944
## 15  Quadrat_4 322      Observed       0 10.000000  8.192352 11.807648 0.9969136
## 16  Quadrat_4 323 Extrapolation       0 10.003086  8.193132 11.813040 0.9969328
## 17  Quadrat_5 319   Rarefaction       0 11.083688  9.612392 12.554984 0.9945234
## 18  Quadrat_5 516   Rarefaction       0 11.996132  9.938347 14.053916 0.9961315
## 19  Quadrat_5 517      Observed       0 12.000000  9.939040 14.060960 0.9961390
## 20  Quadrat_5 518 Extrapolation       0 12.003861  9.939483 14.068239 0.9961465
## 21  Quadrat_6 205   Rarefaction       0 12.995146 11.130046 14.860245 0.9951456
## 22  Quadrat_6 206      Observed       0 13.000000 11.130523 14.869477 0.9951925
## 23  Quadrat_6 207 Extrapolation       0 13.004807 11.130855 14.878760 0.9952390
## 24  Quadrat_6 319 Extrapolation       0 13.331464 11.057804 15.605123 0.9983951
## 25  Quadrat_7 319      Observed       0  7.000000  6.022822  7.977178 1.0000000
## 26  Quadrat_8 319   Rarefaction       0  9.000000  8.998694  9.001306 1.0000000
## 27  Quadrat_8 342   Rarefaction       0  9.000000  9.000000  9.000000 1.0000000
## 28  Quadrat_8 343      Observed       0  9.000000  9.000000  9.000000 1.0000000
## 29  Quadrat_8 344 Extrapolation       0  9.000000  9.000000  9.000000 1.0000000
##       SC.LCL    SC.UCL
## 1  0.9926576 0.9980194
## 2  0.9941946 0.9982582
## 3  0.9939082 0.9985541
## 4  0.9939177 0.9985541
## 5  0.9939819 0.9981735
## 6  0.9946865 0.9982712
## 7  0.9951001 0.9978824
## 8  0.9951174 0.9978898
## 9  0.9944235 0.9988978
## 10 0.9974985 1.0000000
## 11 0.9975630 1.0000000
## 12 0.9975701 1.0000000
## 13 0.9908139 1.0000000
## 14 0.9908250 1.0000000
## 15 0.9904350 1.0000000
## 16 0.9904778 1.0000000
## 17 0.9906134 0.9984335
## 18 0.9918610 1.0000000
## 19 0.9915981 1.0000000
## 20 0.9916119 1.0000000
## 21 0.9872295 1.0000000
## 22 0.9864909 1.0000000
## 23 0.9866035 1.0000000
## 24 0.9940345 1.0000000
## 25 0.9965023 1.0000000
## 26 0.9998908 1.0000000
## 27 1.0000000 1.0000000
## 28 1.0000000 1.0000000
## 29 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9953385 319   Rarefaction       0 12.123846 10.800295 13.447397
## 2   Quadrat_1 0.9962264 791   Rarefaction       0 13.984626 12.391198 15.578054
## 3   Quadrat_1 0.9962312 795      Observed       0 14.000000 12.404291 15.595709
## 4   Quadrat_1 0.9962359 796 Extrapolation       0 14.003769 12.406777 15.600761
## 5   Quadrat_2 0.9960777 319   Rarefaction       0  6.104448  5.391918  6.816977
## 6   Quadrat_2 0.9964789 563   Rarefaction       0  6.983786  6.261650  7.705922
## 7   Quadrat_2 0.9964912 568      Observed       0  7.000000  6.275234  7.724766
## 8   Quadrat_2 0.9965036 569 Extrapolation       0  7.003509  6.278249  7.728769
## 9   Quadrat_3 0.9966607 319   Rarefaction       0 11.702282 10.785203 12.619361
## 10  Quadrat_3 1.0000000 552      Observed       0 12.000000 10.699596 13.300404
## 11  Quadrat_4 0.9968555 319   Rarefaction       0  9.990625  7.181564 12.799686
## 12  Quadrat_4 0.9968944 321   Rarefaction       0  9.995413  7.191659 12.799166
## 13  Quadrat_4 0.9969136 322      Observed       0 10.000000  7.193022 12.806978
## 14  Quadrat_4 0.9969328 323 Extrapolation       0 10.003086  7.192454 12.813718
## 15  Quadrat_5 0.9945234 319   Rarefaction       0 11.083688  8.089100 14.078275
## 16  Quadrat_5 0.9961315 516   Rarefaction       0 11.995720  8.464990 15.526450
## 17  Quadrat_5 0.9961390 517      Observed       0 12.000000  8.466745 15.533255
## 18  Quadrat_5 0.9961465 518 Extrapolation       0 12.003861  8.468385 15.539337
## 19  Quadrat_6 0.9951456 204   Rarefaction       0 12.992177 10.502610 15.481744
## 20  Quadrat_6 0.9951925 206      Observed       0 13.000000 10.506741 15.493259
## 21  Quadrat_6 0.9952390 207 Extrapolation       0 13.004807 10.507028 15.502587
## 22  Quadrat_6 0.9983951 319 Extrapolation       0 13.331464 10.537630 16.125297
## 23  Quadrat_7 1.0000000 319      Observed       0  7.000000  5.685622  8.314378
## 24  Quadrat_8 1.0000000 319   Rarefaction       0  9.000000  8.999996  9.000004
## 25  Quadrat_8 1.0000000 343      Observed       0  9.000000  9.000000  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 1.52433377 14.008587
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.22928078  6.685706
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.23867112  4.656000
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.76288980  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.09484440  2.967928
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.09955609  2.540468
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.55963137 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.25288305  4.831340
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.18994168  3.459026
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.61957007 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.27906067  5.459532
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.31485775  4.035064
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.37863887 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.23355311  5.796311
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.21922624  4.458049
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.47710222 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.47559828  8.028367
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.59990862  5.540168
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.65644401  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.13685431  4.736249
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.18635668  4.160176
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.25276759  5.849947
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.29989641  4.396323
##          UCL
## 1  19.983866
## 2   7.584470
## 3   5.591573
## 4   9.493476
## 5   3.339711
## 6   2.930720
## 7  13.096857
## 8   5.822623
## 9   4.203584
## 10 13.672746
## 11  6.553429
## 12  5.269284
## 13 18.658178
## 14  6.711822
## 15  5.317400
## 16 16.392640
## 17  9.892678
## 18  7.891766
## 19  8.286607
## 20  5.272708
## 21  4.890681
## 22  9.000000
## 23  6.840777
## 24  5.571896
t <- c(343)

Warton_Datat <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance", size = t)

Warton_Datat
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##    Assemblage   m        Method Order.q        qD    qD.LCL    qD.UCL        SC
## 1   Quadrat_1 343   Rarefaction       0 12.233488 11.288083 13.178894 0.9955254
## 2   Quadrat_1 794   Rarefaction       0 13.996226 12.465874 15.526579 0.9962264
## 3   Quadrat_1 795      Observed       0 14.000000 12.468451 15.531549 0.9962312
## 4   Quadrat_1 796 Extrapolation       0 14.003769 12.470668 15.536870 0.9962359
## 5   Quadrat_2 343   Rarefaction       0  6.196808  5.395260  6.998356 0.9962229
## 6   Quadrat_2 567   Rarefaction       0  6.996479  6.040576  7.952382 0.9964789
## 7   Quadrat_2 568      Observed       0  7.000000  6.043089  7.956911 0.9964912
## 8   Quadrat_2 569 Extrapolation       0  7.003509  6.045774  7.961243 0.9965036
## 9   Quadrat_3 343   Rarefaction       0 11.775135 10.928822 12.621449 0.9972773
## 10  Quadrat_3 551   Rarefaction       0 12.000000 11.142847 12.857153 1.0000000
## 11  Quadrat_3 552      Observed       0 12.000000 11.142466 12.857534 1.0000000
## 12  Quadrat_3 553 Extrapolation       0 12.000000 11.142183 12.857817 1.0000000
## 13  Quadrat_4 321   Rarefaction       0  9.996894  8.282589 11.711200 0.9968944
## 14  Quadrat_4 322      Observed       0 10.000000  8.282648 11.717352 0.9969136
## 15  Quadrat_4 323 Extrapolation       0 10.003086  8.282580 11.723593 0.9969328
## 16  Quadrat_4 343 Extrapolation       0 10.060953  8.275934 11.845973 0.9972911
## 17  Quadrat_5 343   Rarefaction       0 11.212226  9.958806 12.465645 0.9947691
## 18  Quadrat_5 516   Rarefaction       0 11.996132 10.363770 13.628493 0.9961315
## 19  Quadrat_5 517      Observed       0 12.000000 10.365444 13.634556 0.9961390
## 20  Quadrat_5 518 Extrapolation       0 12.003861 10.366651 13.641071 0.9961465
## 21  Quadrat_6 205   Rarefaction       0 12.995146 11.353143 14.637149 0.9951456
## 22  Quadrat_6 206      Observed       0 13.000000 11.353497 14.646503 0.9951925
## 23  Quadrat_6 207 Extrapolation       0 13.004807 11.353009 14.656605 0.9952390
## 24  Quadrat_6 343 Extrapolation       0 13.365990 11.107796 15.624185 0.9987287
## 25  Quadrat_7 318   Rarefaction       0  6.996865  5.861832  8.131899 0.9968652
## 26  Quadrat_7 319      Observed       0  7.000000  5.863345  8.136655 1.0000000
## 27  Quadrat_7 320 Extrapolation       0  7.000000  5.862207  8.137793 1.0000000
## 28  Quadrat_7 343 Extrapolation       0  7.000000  5.836209  8.163791 1.0000000
## 29  Quadrat_8 343      Observed       0  9.000000  9.000000  9.000000 1.0000000
##       SC.LCL    SC.UCL
## 1  0.9933318 0.9977191
## 2  0.9941132 0.9983396
## 3  0.9937245 0.9987378
## 4  0.9937334 0.9987384
## 5  0.9942408 0.9982051
## 6  0.9942470 0.9987108
## 7  0.9945648 0.9984177
## 8  0.9945839 0.9984232
## 9  0.9952837 0.9992709
## 10 0.9978195 1.0000000
## 11 0.9979463 1.0000000
## 12 0.9979529 1.0000000
## 13 0.9904293 1.0000000
## 14 0.9901463 1.0000000
## 15 0.9901881 1.0000000
## 16 0.9909739 1.0000000
## 17 0.9916916 0.9978466
## 18 0.9927157 0.9995473
## 19 0.9922757 1.0000000
## 20 0.9922920 1.0000000
## 21 0.9865472 1.0000000
## 22 0.9858327 1.0000000
## 23 0.9859354 1.0000000
## 24 0.9940448 1.0000000
## 25 0.9933020 1.0000000
## 26 0.9969063 1.0000000
## 27 0.9969256 1.0000000
## 28 0.9973385 1.0000000
## 29 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##    Assemblage        SC   m        Method Order.q        qD    qD.LCL    qD.UCL
## 1   Quadrat_1 0.9955254 343   Rarefaction       0 12.233488 10.889455 13.577522
## 2   Quadrat_1 0.9962264 791   Rarefaction       0 13.984626 12.282267 15.686985
## 3   Quadrat_1 0.9962312 795      Observed       0 14.000000 12.294192 15.705808
## 4   Quadrat_1 0.9962359 796 Extrapolation       0 14.003769 12.296573 15.710964
## 5   Quadrat_2 0.9962229 343   Rarefaction       0  6.196808  5.262333  7.131283
## 6   Quadrat_2 0.9964789 563   Rarefaction       0  6.983786  5.945771  8.021802
## 7   Quadrat_2 0.9964912 568      Observed       0  7.000000  5.958050  8.041950
## 8   Quadrat_2 0.9965036 569 Extrapolation       0  7.003509  5.960853  8.046164
## 9   Quadrat_3 0.9972773 343   Rarefaction       0 11.775135 10.820621 12.729650
## 10  Quadrat_3 1.0000000 552      Observed       0 12.000000 10.804955 13.195045
## 11  Quadrat_4 0.9968944 321   Rarefaction       0  9.995413  6.996735 12.994091
## 12  Quadrat_4 0.9969136 322      Observed       0 10.000000  6.998149 13.001851
## 13  Quadrat_4 0.9969328 323 Extrapolation       0 10.003086  6.997751 13.008422
## 14  Quadrat_4 0.9972911 343 Extrapolation       0 10.060953  6.990699 13.131207
## 15  Quadrat_5 0.9947691 343   Rarefaction       0 11.212226  9.100152 13.324299
## 16  Quadrat_5 0.9961315 516   Rarefaction       0 11.995720  9.596907 14.394533
## 17  Quadrat_5 0.9961390 517      Observed       0 12.000000  9.598656 14.401344
## 18  Quadrat_5 0.9961465 518 Extrapolation       0 12.003861  9.600673 14.407049
## 19  Quadrat_6 0.9951456 204   Rarefaction       0 12.992177 10.467184 15.517170
## 20  Quadrat_6 0.9951925 206      Observed       0 13.000000 10.470177 15.529823
## 21  Quadrat_6 0.9952390 207 Extrapolation       0 13.004807 10.469416 15.540199
## 22  Quadrat_6 0.9987287 343 Extrapolation       0 13.365990 10.411738 16.320242
## 23  Quadrat_7 0.9968652 318   Rarefaction       0  6.995767  5.668957  8.322578
## 24  Quadrat_7 1.0000000 319      Observed       0  7.000000  5.603705  8.396295
## 25  Quadrat_8 1.0000000 343      Observed       0  9.000000  9.000000  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 1.88526355 14.000000
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.22918405  6.685896
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.24049383  4.652427
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.69972138  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.08582788  2.985600
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.08612436  2.566793
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.57697267 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.21685498  4.901954
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.15453269  3.528427
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.65780163 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.32028491  5.378734
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.33610994  3.993411
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.34953078 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.24247367  5.778827
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.23125913  4.434465
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.68161642 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.48235774  8.015119
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.54702626  5.643815
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.64168732  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.14924821  4.711957
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.20241403  4.128704
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.25409589  5.847343
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.27549101  4.444157
##          UCL
## 1  20.691275
## 2   7.584281
## 3   5.595146
## 4   9.369668
## 5   3.322039
## 6   2.904395
## 7  13.130846
## 8   5.752010
## 9   4.134184
## 10 13.747679
## 11  6.634227
## 12  5.310937
## 13 18.601127
## 14  6.729306
## 15  5.340984
## 16 16.793480
## 17  9.905927
## 18  7.788119
## 19  8.257684
## 20  5.296999
## 21  4.922152
## 22  9.000000
## 23  6.843381
## 24  5.524062

#Now to run the analysis again without specificying the size, can do this for #looking at the other diversity indices

Warton_Data <- iNEXT(Warton_Nos, q=c(0), datatype= "abundance")

print(Warton_Data)
## Compare 8 assemblages with Hill number order q = 0.
## $class: iNEXT
## 
## $DataInfo: basic data information
##   Assemblage   n S.obs     SC f1 f2 f3 f4 f5 f6 f7 f8 f9 f10
## 1  Quadrat_1 795    14 0.9962  3  0  0  0  1  0  0  0  0   0
## 2  Quadrat_2 568     7 0.9965  2  0  0  0  1  0  1  0  0   0
## 3  Quadrat_3 552    12 1.0000  0  1  1  1  1  0  0  1  0   0
## 4  Quadrat_4 322    10 0.9969  1  1  1  0  0  0  0  0  0   0
## 5  Quadrat_5 517    12 0.9961  2  1  0  0  0  1  1  0  0   0
## 6  Quadrat_6 206    13 0.9952  1  1  0  1  1  0  0  0  0   3
## 7  Quadrat_7 319     7 1.0000  1  0  1  0  0  0  0  0  0   0
## 8  Quadrat_8 343     9 1.0000  0  0  0  0  0  0  0  1  0   0
## 
## $iNextEst: diversity estimates with rarefied and extrapolated samples.
## $size_based (LCL and UCL are obtained for fixed size.)
## 
##     Assemblage    m        Method Order.q        qD    qD.LCL    qD.UCL
## 1    Quadrat_1    1   Rarefaction       0  1.000000  1.000000  1.000000
## 10   Quadrat_1  397   Rarefaction       0 12.466585 11.476188 13.456983
## 20   Quadrat_1  795      Observed       0 14.000000 12.545643 15.454357
## 30   Quadrat_1 1172 Extrapolation       0 15.132009 13.166723 17.097295
## 40   Quadrat_1 1590 Extrapolation       0 15.894670 13.536423 18.252917
## 41   Quadrat_2    1   Rarefaction       0  1.000000  1.000000  1.000000
## 50   Quadrat_2  284   Rarefaction       0  5.961774  5.282812  6.640736
## 60   Quadrat_2  568      Observed       0  7.000000  6.244533  7.755467
## 70   Quadrat_2  837 Extrapolation       0  7.611091  6.821625  8.400556
## 80   Quadrat_2 1136 Extrapolation       0  7.863143  7.047378  8.678907
## 81   Quadrat_3    1   Rarefaction       0  1.000000  1.000000  1.000000
## 90   Quadrat_3  276   Rarefaction       0 11.529472 10.879572 12.179373
## 100  Quadrat_3  552      Observed       0 12.000000 11.529809 12.470191
## 110  Quadrat_3  814 Extrapolation       0 12.000000 11.297889 12.702111
## 120  Quadrat_3 1104 Extrapolation       0 12.000000 11.096618 12.903382
## 121  Quadrat_4    1   Rarefaction       0  1.000000  1.000000  1.000000
## 130  Quadrat_4  161   Rarefaction       0  9.126945  7.972321 10.281569
## 140  Quadrat_4  322      Observed       0 10.000000  8.308868 11.691132
## 150  Quadrat_4  475 Extrapolation       0 10.305738  8.146708 12.464768
## 160  Quadrat_4  644 Extrapolation       0 10.430990  7.897586 12.964395
## 161  Quadrat_5    1   Rarefaction       0  1.000000  1.000000  1.000000
## 170  Quadrat_5  258   Rarefaction       0 10.724628  9.570945 11.878310
## 180  Quadrat_5  517      Observed       0 12.000000 10.453678 13.546322
## 190  Quadrat_5  762 Extrapolation       0 12.753956 10.757985 14.749927
## 200  Quadrat_5 1034 Extrapolation       0 13.262507 10.888767 15.636246
## 201  Quadrat_6    1   Rarefaction       0  1.000000  1.000000  1.000000
## 210  Quadrat_6  103   Rarefaction       0 12.158108 10.986248 13.329969
## 220  Quadrat_6  206      Observed       0 13.000000 11.242935 14.757065
## 230  Quadrat_6  304 Extrapolation       0 13.305422 11.073050 15.537795
## 240  Quadrat_6  412 Extrapolation       0 13.430235 10.850468 16.010002
## 241  Quadrat_7    1   Rarefaction       0  1.000000  1.000000  1.000000
## 250  Quadrat_7  159   Rarefaction       0  6.373436  5.498890  7.247983
## 260  Quadrat_7  319      Observed       0  7.000000  5.865416  8.134584
## 270  Quadrat_7  470 Extrapolation       0  7.000000  5.716648  8.283352
## 280  Quadrat_7  638 Extrapolation       0  7.000000  5.639360  8.360640
## 281  Quadrat_8    1   Rarefaction       0  1.000000  1.000000  1.000000
## 290  Quadrat_8  171   Rarefaction       0  8.995791  8.934652  9.056930
## 300  Quadrat_8  343      Observed       0  9.000000  9.000000  9.000000
## 310  Quadrat_8  506 Extrapolation       0  9.000000  9.000000  9.000000
## 320  Quadrat_8  686 Extrapolation       0  9.000000  9.000000  9.000000
##            SC    SC.LCL    SC.UCL
## 1   0.1951682 0.1747782 0.2155581
## 10  0.9958230 0.9939407 0.9977053
## 20  0.9962312 0.9938031 0.9986592
## 30  0.9976551 0.9962061 0.9991040
## 40  0.9986144 0.9977207 0.9995080
## 41  0.3655513 0.3409574 0.3901452
## 50  0.9957529 0.9939677 0.9975381
## 60  0.9964912 0.9954128 0.9975697
## 70  0.9986392 0.9982209 0.9990574
## 80  0.9995251 0.9993792 0.9996711
## 81  0.2610077 0.2397559 0.2822594
## 90  0.9952631 0.9932507 0.9972755
## 100 1.0000000 0.9975067 1.0000000
## 110 1.0000000 0.9987797 1.0000000
## 120 1.0000000 0.9993503 1.0000000
## 121 0.2149533 0.1873008 0.2426057
## 130 0.9914908 0.9856841 0.9972975
## 140 0.9969136 0.9907591 1.0000000
## 150 0.9988068 0.9951753 1.0000000
## 160 0.9995823 0.9973657 1.0000000
## 161 0.2045942 0.1866164 0.2225720
## 170 0.9936361 0.9902825 0.9969898
## 180 0.9961390 0.9923518 0.9999262
## 190 0.9975973 0.9952361 0.9999586
## 200 0.9985810 0.9971043 1.0000000
## 201 0.1488989 0.1212821 0.1765157
## 210 0.9862494 0.9759304 0.9965684
## 220 0.9951925 0.9863508 1.0000000
## 230 0.9981435 0.9927638 1.0000000
## 240 0.9993494 0.9960212 1.0000000
## 241 0.2209736 0.2040824 0.2378647
## 250 0.9945215 0.9907873 0.9982557
## 260 1.0000000 0.9968406 1.0000000
## 270 1.0000000 0.9987741 1.0000000
## 280 1.0000000 0.9995724 1.0000000
## 281 0.2006376 0.1759642 0.2253111
## 290 0.9997938 0.9986424 1.0000000
## 300 1.0000000 1.0000000 1.0000000
## 310 1.0000000 1.0000000 1.0000000
## 320 1.0000000 1.0000000 1.0000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$size_based to view complete output.
## 
## $coverage_based (LCL and UCL are obtained for fixed coverage; interval length is wider due to varying size in bootstraps.)
## 
##     Assemblage        SC    m        Method Order.q        qD     qD.LCL
## 1    Quadrat_1 0.1951698    1   Rarefaction       0  1.000008  0.9453960
## 10   Quadrat_1 0.9958230  397   Rarefaction       0 12.466585 11.0408004
## 20   Quadrat_1 0.9962312  795      Observed       0 14.000000 12.1512956
## 30   Quadrat_1 0.9976551 1172 Extrapolation       0 15.132009 12.8594715
## 40   Quadrat_1 0.9986144 1590 Extrapolation       0 15.894670 13.3671694
## 41   Quadrat_2 0.3655588    1   Rarefaction       0  1.000017  0.9716444
## 50   Quadrat_2 0.9957529  284   Rarefaction       0  5.961774  5.2505579
## 60   Quadrat_2 0.9964912  568      Observed       0  7.000000  6.2715262
## 70   Quadrat_2 0.9986392  837 Extrapolation       0  7.611091  6.7962881
## 80   Quadrat_2 0.9995251 1136 Extrapolation       0  7.863143  7.0431238
## 81   Quadrat_3 0.2610100    1   Rarefaction       0  1.000008  0.9497780
## 85   Quadrat_3 0.9825762  123   Rarefaction       0 10.074595  9.2632403
## 90   Quadrat_3 0.9952631  276   Rarefaction       0 11.529472 10.9636665
## 95   Quadrat_3 0.9988210  428   Rarefaction       0 11.935737 11.0350896
## 99   Quadrat_3 1.0000000  552      Observed       0 12.000000 10.8220641
## 100  Quadrat_4 0.2149550    1   Rarefaction       0  1.000008  0.9411407
## 109  Quadrat_4 0.9914908  161   Rarefaction       0  9.126945  7.1274399
## 119  Quadrat_4 0.9969136  322      Observed       0 10.000000  7.3860309
## 129  Quadrat_4 0.9988068  475 Extrapolation       0 10.305738  7.3417816
## 139  Quadrat_4 0.9995823  644 Extrapolation       0 10.430990  7.3034727
## 140  Quadrat_5 0.2045956    1   Rarefaction       0  1.000006  0.9599128
## 149  Quadrat_5 0.9936361  258   Rarefaction       0 10.724628  9.0705769
## 159  Quadrat_5 0.9961390  517      Observed       0 12.000000  9.8220282
## 169  Quadrat_5 0.9975973  762 Extrapolation       0 12.753956 10.2841281
## 179  Quadrat_5 0.9985810 1034 Extrapolation       0 13.262507 10.6420074
## 180  Quadrat_6 0.1488989    1   Rarefaction       0  1.000000  0.9116579
## 189  Quadrat_6 0.9862494  103   Rarefaction       0 12.158108 10.2664187
## 199  Quadrat_6 0.9951925  206      Observed       0 13.000000 10.3729306
## 209  Quadrat_6 0.9981435  304 Extrapolation       0 13.305422 10.3370791
## 219  Quadrat_6 0.9993494  412 Extrapolation       0 13.430235 10.3137575
## 220  Quadrat_7 0.2209752    1   Rarefaction       0  1.000007  0.9716737
## 224  Quadrat_7 0.9911954   71   Rarefaction       0  5.753959  4.8891572
## 229  Quadrat_7 0.9945215  159   Rarefaction       0  6.373436  5.1458888
## 234  Quadrat_7 0.9964015  247   Rarefaction       0  6.763167  5.3832540
## 239  Quadrat_7 1.0000000  319      Observed       0  7.000000  5.5949345
## 240  Quadrat_8 0.2006376    1   Rarefaction       0  1.000000  0.9225117
## 244  Quadrat_8 0.9908143   76   Rarefaction       0  8.758813  8.5967655
## 249  Quadrat_8 0.9997938  171   Rarefaction       0  8.995791  8.9949298
## 254  Quadrat_8 0.9999995  266   Rarefaction       0  8.999995  8.9999927
## 258  Quadrat_8 1.0000000  343      Observed       0  9.000000  9.0000000
##        qD.UCL
## 1    1.054620
## 10  13.892370
## 20  15.848704
## 30  17.404547
## 40  18.422170
## 41   1.028390
## 50   6.672990
## 60   7.728474
## 70   8.425893
## 80   8.683162
## 81   1.050239
## 85  10.885949
## 90  12.095278
## 95  12.836384
## 99  13.177936
## 100  1.058874
## 109 11.126450
## 119 12.613969
## 129 13.269694
## 139 13.558508
## 140  1.040100
## 149 12.378678
## 159 14.177972
## 169 15.223784
## 179 15.883006
## 180  1.088342
## 189 14.049798
## 199 15.627069
## 209 16.273766
## 219 16.546712
## 220  1.028340
## 224  6.618762
## 229  7.600984
## 234  8.143080
## 239  8.405066
## 240  1.077488
## 244  8.920860
## 249  8.996652
## 254  8.999998
## 258  9.000000
## 
## NOTE: The above output only shows five estimates for each assemblage; call iNEXT.object$iNextEst$coverage_based to view complete output.
## 
## $AsyEst: asymptotic diversity estimates along with related statistics.
##    Assemblage         Diversity  Observed Estimator       s.e.       LCL
## 1   Quadrat_1  Species richness 14.000000 16.996226 1.35773777 14.335109
## 2   Quadrat_1 Shannon diversity  7.058677  7.135088 0.26608567  6.613570
## 3   Quadrat_1 Simpson diversity  5.097346  5.123786 0.27947407  4.576027
## 4   Quadrat_2  Species richness  7.000000  7.998239 0.59392045  7.000000
## 5   Quadrat_2 Shannon diversity  3.132205  3.153819 0.08324010  2.990672
## 6   Quadrat_2 Simpson diversity  2.727260  2.735594 0.08172973  2.575407
## 7   Quadrat_3  Species richness 12.000000 12.000000 0.57780692 12.000000
## 8   Quadrat_3 Shannon diversity  5.272867  5.326982 0.21852499  4.898681
## 9   Quadrat_3 Simpson diversity  3.811754  3.831305 0.17114144  3.495874
## 10  Quadrat_4  Species richness 10.000000 10.498447 1.62305718 10.000000
## 11  Quadrat_4 Shannon diversity  5.913462  6.006481 0.29151522  5.435121
## 12  Quadrat_4 Simpson diversity  4.600000  4.652174 0.30246619  4.059351
## 13  Quadrat_5  Species richness 12.000000 13.996132 2.38579650 12.000000
## 14  Quadrat_5 Shannon diversity  6.170838  6.254067 0.27795155  5.709292
## 15  Quadrat_5 Simpson diversity  4.851244  4.887724 0.25323903  4.391385
## 16  Quadrat_6  Species richness 13.000000 13.497573 1.49173448 13.000000
## 17  Quadrat_6 Shannon diversity  8.679505  8.960523 0.56158217  7.859842
## 18  Quadrat_6 Simpson diversity  6.534647  6.715967 0.66825705  5.406207
## 19  Quadrat_7  Species richness  7.000000  7.000000 0.59090713  7.000000
## 20  Quadrat_7 Shannon diversity  4.955898  5.004478 0.14676588  4.716822
## 21  Quadrat_7 Simpson diversity  4.475962  4.525428 0.18038163  4.171887
## 22  Quadrat_8  Species richness  9.000000  9.000000 0.00000000  9.000000
## 23  Quadrat_8 Shannon diversity  6.271077  6.345362 0.29210614  5.772844
## 24  Quadrat_8 Simpson diversity  4.926881  4.984109 0.32204886  4.352905
##          UCL
## 1  19.657344
## 2   7.656607
## 3   5.671546
## 4   9.162302
## 5   3.316967
## 6   2.895781
## 7  13.132481
## 8   5.755283
## 9   4.166736
## 10 13.679581
## 11  6.577840
## 12  5.244997
## 13 18.672207
## 14  6.798842
## 15  5.384064
## 16 16.421319
## 17 10.061204
## 18  8.025727
## 19  8.158157
## 20  5.292134
## 21  4.878970
## 22  9.000000
## 23  6.917879
## 24  5.615314
summary(Warton_Data)
##          Length Class      Mode
## DataInfo 14     data.frame list
## iNextEst  2     -none-     list
## AsyEst    7     data.frame list

#Now to obtain additional biodiversity indices for the Warton data, including sample coverage#

W1 <- diversity(Warton_Nos$Quadrat_1)

Warton2 <- estimateD(Warton_Nos, q = c(0,1,2), datatype = "abundance", base="coverage")
Warton2
##    Assemblage         m        Method Order.q        SC        qD    qD.LCL
## 1   Quadrat_1 1571.0768 Extrapolation       0 0.9985810 15.868118 12.369665
## 2   Quadrat_1 1571.0768 Extrapolation       1 0.9985810  7.104569  6.629994
## 3   Quadrat_1 1571.0768 Extrapolation       2 0.9985810  5.110373  4.644646
## 4   Quadrat_2  825.1063 Extrapolation       0 0.9985810  7.594533  6.978302
## 5   Quadrat_2  825.1063 Extrapolation       1 0.9985810  3.140309  2.954099
## 6   Quadrat_2  825.1063 Extrapolation       2 0.9985810  2.729852  2.531995
## 7   Quadrat_3  411.3288   Rarefaction       0 0.9985810 11.913994 10.728373
## 8   Quadrat_3  411.3288   Rarefaction       1 0.9985810  5.253358  4.858314
## 9   Quadrat_3  411.3288   Rarefaction       2 0.9985810  3.805113  3.498142
## 10  Quadrat_4  447.1026 Extrapolation       0 0.9985810 10.269278  7.817770
## 11  Quadrat_4  447.1026 Extrapolation       1 0.9985810  5.944195  5.340198
## 12  Quadrat_4  447.1026 Extrapolation       2 0.9985810  4.614480  4.015782
## 13  Quadrat_5 1034.0000 Extrapolation       0 0.9985810 13.262507  9.580330
## 14  Quadrat_5 1034.0000 Extrapolation       1 0.9985810  6.222248  5.769152
## 15  Quadrat_5 1034.0000 Extrapolation       2 0.9985810  4.869416  4.498865
## 16  Quadrat_6  331.6812 Extrapolation       0 0.9985810 13.350706 10.567531
## 17  Quadrat_6  331.6812 Extrapolation       1 0.9985810  8.809870  7.834413
## 18  Quadrat_6  331.6812 Extrapolation       2 0.9985810  6.602189  5.593161
## 19  Quadrat_7  317.4628   Rarefaction       0 0.9968652  6.995181  5.771381
## 20  Quadrat_7  317.4628   Rarefaction       1 0.9968652  4.955628  4.631220
## 21  Quadrat_7  317.4628   Rarefaction       2 0.9968652  4.475725  4.056158
## 22  Quadrat_8  124.7522   Rarefaction       0 0.9985810  8.965447  8.946573
## 23  Quadrat_8  124.7522   Rarefaction       1 0.9985810  6.138467  5.732351
## 24  Quadrat_8  124.7522   Rarefaction       2 0.9985810  4.829860  4.389391
##       qD.UCL
## 1  19.366571
## 2   7.579144
## 3   5.576100
## 4   8.210763
## 5   3.326518
## 6   2.927708
## 7  13.099616
## 8   5.648403
## 9   4.112085
## 10 12.720786
## 11  6.548192
## 12  5.213179
## 13 16.944683
## 14  6.675344
## 15  5.239967
## 16 16.133881
## 17  9.785328
## 18  7.611218
## 19  8.218981
## 20  5.280037
## 21  4.895292
## 22  8.984320
## 23  6.544582
## 24  5.270330
Wevenness1 <- W1/log(specnumber(Warton_Nos$Quadrat_1))

summary(Wevenness1)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.7405  0.7405  0.7405  0.7405  0.7405  0.7405
W2 <- diversity(Warton_Nos$Quadrat_2)

Wevenness2 <- W2/log(specnumber(Warton_Nos$Quadrat_2))

summary(Wevenness2)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.5867  0.5867  0.5867  0.5867  0.5867  0.5867
W3 <- diversity(Warton_Nos$Quadrat_3)

Wevenness3 <- W3/log(specnumber(Warton_Nos$Quadrat_3))

summary(Wevenness3)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.6691  0.6691  0.6691  0.6691  0.6691  0.6691
W4 <- diversity(Warton_Nos$Quadrat_4)

Wevenness4 <- W4/log(specnumber(Warton_Nos$Quadrat_4))

summary(Wevenness4)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.7718  0.7718  0.7718  0.7718  0.7718  0.7718
W5 <- diversity(Warton_Nos$Quadrat_5)

Wevenness5 <- W5/log(specnumber(Warton_Nos$Quadrat_5))

summary(Wevenness5)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.7324  0.7324  0.7324  0.7324  0.7324  0.7324
W6 <- diversity(Warton_Nos$Quadrat_6)

Wevenness6 <- W6/log(specnumber(Warton_Nos$Quadrat_6))

summary(Wevenness6)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.8425  0.8425  0.8425  0.8425  0.8425  0.8425
W7 <- diversity(Warton_Nos$Quadrat_7)

Wevenness7 <- W7/log(specnumber(Warton_Nos$Quadrat_7))

summary(Wevenness7)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.8225  0.8225  0.8225  0.8225  0.8225  0.8225
W8 <-diversity(Warton_Nos$Quadrat_8)

Wevenness8 <-W8/log(specnumber(Warton_Nos$Quadrat_8))

summary(Wevenness8)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.8356  0.8356  0.8356  0.8356  0.8356  0.8356

#Now for Warton data visualisation, including species curve visualisation#

Warton_Data_Graph1 <- ggiNEXT(x = Warton_Data, se=TRUE, color.var="Order.q")

Warton_Data_Graph1

Warton_Data_Graph2 <- ggiNEXT(x = Warton_Data, se=TRUE, type = 1,
                              facet.var="None", color.var="Order.q") 

Warton_Data_Graph2

Warton_Data_Graph3 <- ggiNEXT(x = Warton_Data, se=TRUE, type = 2,
                              facet.var="None", color.var="Order.q") 

Warton_Data_Graph3

Warton_Data_Graph4 <- ggiNEXT(x = Warton_Data, se=TRUE, type = 3,
                              facet.var="None", color.var="Order.q") 

Warton_Data_Graph4