##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