BiodiversityR: Package for Community Ecology and Suitability Analysis

群集生態学のためのパッケージ。GUIアプリケーションもある

> library(BiodiversityR)

Loading required package: tcltk

Warning: replacing previous import by 'ggplot2::unit' when loading 'Hmisc'

Warning: replacing previous import by 'ggplot2::arrow' when loading 'Hmisc'

Warning: replacing previous import by 'scales::alpha' when loading 'Hmisc'

BiodiversityR 2.5-4: use function 'BiodiversityRGUI()' to launch the BiodiversityR Graphical User Interface

> data("ifri")

バージョン: 2.5.4

関数名 概略
BCI.env Barro Colorado Island Quadrat Descriptions
BiodiversityR-package GUI for biodiversity, suitability and community ecology analysis
BiodiversityRGUI GUI for Biodiversity Analysis and Ordination
CAPdiscrim Canonical Analysis of Principal Coordinates based on Discriminant Analysis
NMSrandom Calculate the NMS Result with the Smallest Stress from Various Random Starts
PCAsignificance PCA Significance
accumresult Alternative Species Accumulation Curve Results
add.spec.scores Add Species Scores to Unconstrained Ordination Results
balanced.specaccum Balanced Species Accumulation Curves
caprescale Rescaling of Capscale Results to Reflect Total Sums of Squares Of Distance Matrix
crosstabanalysis Presence-absence Analysis by Cross Tabulation
deviancepercentage Calculate Percentage and Significance of Deviance Explained by a GLM
dist.eval Distance Matrix Evaluation
dist.zeroes Distance Matrix Transformation
distdisplayed Compare Distance Displayed in Ordination Diagram with Distances of Distance Matrix
disttransform Community Matrix Transformation
diversityresult Alternative Diversity Results
ensemble.batch Suitability mapping based on ensembles of modelling algorithms: batch processing
ensemble.dummy.variables Suitability mapping based on ensembles of modelling algorithms: handling of categorical data
ensemble.raster Suitability mapping based on ensembles of modelling algorithms: consensus mapping
ensemble.test Suitability mapping based on ensembles of modelling algorithms: comparison of different algorithms and calibration
evaluation.strip.data Evaluation strips for ensemble suitability mapping
faramea Faramea occidentalis abundance in Panama
ifri Example data from the International Forestry Resources and Institutions (IFRI) research network
importancevalue Importance Value
loaded.citations Give Citation Information for all Loaded Packages
makecommunitydataset Make a Community Dataset from a Stacked Dataset
multiconstrained Pairwise Comparisons for All Levels of a Categorical Variable by RDA, CCA or Capscale
nested.anova.dbrda Nested Analysis of Variance via Distance-based Redundancy Analysis or Non-parametric Multivariate Analysis of Variance
nnetrandom Calculate the NNET Result with the Smallest Value from Various Random Starts
ordicoeno Coenoclines for an Ordination Axis
ordisymbol Add Other Graphical Items to Ordination Diagrams
radfitresult Alternative Rank Abundance Fitting Results
rankabundance Rank Abundance Curves
removeNAcomm Synchronize Community and Environmental Datasets
renyiresult Alternative Renyi Diversity Results
residualssurface Show and Interpolate Two Dimensional Distribution of Residuals
spatialsample Spatial Sampling within a Polygon
transfgradient Gradient for Hypothetical Example of Turover of Species Composition
transfspecies Hypothetical Example of Turover of Species Composition
warcom Warburgia ugandensis AFLP Scores
warenv Warburgia ugandensis Population Structure

BCI.env

パナマ共和国バロ・コロラド島の長期生態観察プロットの環境データセット

> data("BCI.env")
> dplyr::glimpse(BCI.env)

Observations: 50
Variables: 7
$ UTM.EW    (dbl) 625754, 625754, 625754, 625754, 625754, 625854, 6258...
$ UTM.NS    (dbl) 1011569, 1011669, 1011769, 1011869, 1011969, 1011569...
$ elevation (dbl) 130.2525, 136.8100, 143.6775, 147.0075, 144.3850, 13...
$ convex    (dbl) -7.872500, -10.700000, -14.667500, -16.757500, -12.4...
$ slope     (dbl) 6.6948280, 5.0868422, 3.1047944, 1.8728129, 5.118724...
$ aspectEW  (dbl) -0.89108252, -0.21903766, 0.03051372, -0.86414183, -...
$ aspectNS  (dbl) -0.4538413, -0.9757164, -0.9995343, -0.5032483, 0.74...

ifri

インドネシアの森林プロットで調査された樹木種の幹数（個体数）と断面積のデータセット

> data("ifri")
> ifri %>% {
+   print(dim(.))
+   dplyr::tbl_df(.)
+ }

[1] 486   5

Source: local data frame [486 x 5]

   forest  plotID  species count  basal
   (fctr)  (fctr)   (fctr) (int)  (dbl)
1     LOT LOTP001 Lirituli     4 5140.0
2     LOT LOTP001 Prunsero     1 1385.4
3     LOT LOTP001 Sassalbi     1 1012.2
4     LOT LOTP001 Platocci     1  730.6
5     LOT LOTP001 Acerrubr     1  317.3
6     LOT LOTP001 Cornflor     1  201.1
7     LOT LOTP001 Acernegu     1  102.1
8     LOT LOTP002 Querrubr     2 7166.8
9     LOT LOTP002 Fraxamer     2 2694.9
10    LOT LOTP002 Pinustro     2  287.7
..    ...     ...      ...   ...    ...

rankabundance

> data("dune.env", package = "vegan")
> data("dune", package = "vegan")
> dune %>% rankabundance()

         rank abundance proportion plower pupper accumfreq logabun
Poatriv     1        63        9.2    6.0   12.4       9.2     1.8
Lolipere    2        58        8.5    4.9   12.0      17.7     1.8
Scorautu    3        54        7.9    5.7   10.0      25.5     1.7
Bracruta    4        49        7.2    4.6    9.7      32.7     1.7
Agrostol    5        48        7.0    3.3   10.7      39.7     1.7
Poaprat     6        48        7.0    4.8    9.2      46.7     1.7
Trifrepe    7        47        6.9    4.5    9.2      53.6     1.7
Alopgeni    8        36        5.3    1.8    8.7      58.8     1.6
Elymrepe    9        26        3.8    1.1    6.5      62.6     1.4
Planlanc   10        26        3.8    1.2    6.4      66.4     1.4
Eleopalu   11        25        3.6    0.3    7.0      70.1     1.4
Anthodor   12        21        3.1    0.8    5.4      73.1     1.3
Sagiproc   13        20        2.9    0.9    5.0      76.1     1.3
Juncarti   14        18        2.6    0.4    4.9      78.7     1.3
Rumeacet   15        18        2.6    0.3    4.9      81.3     1.3
Achimill   16        16        2.3    0.7    4.0      83.6     1.2
Bromhord   17        15        2.2    0.4    4.0      85.8     1.2
Ranuflam   18        14        2.0    0.4    3.7      87.9     1.1
Bellpere   19        13        1.9    0.6    3.2      89.8     1.1
Juncbufo   20        13        1.9    0.0    3.8      91.7     1.1
Salirepe   21        11        1.6   -0.3    3.6      93.3     1.0
Callcusp   22        10        1.5   -0.3    3.2      94.7     1.0
Hyporadi   23         9        1.3   -0.4    3.1      96.1     1.0
Trifprat   24         9        1.3   -0.3    2.9      97.4     1.0
Airaprae   25         5        0.7   -0.4    1.8      98.1     0.7
Comapalu   26         4        0.6   -0.3    1.5      98.7     0.6
Vicilath   27         4        0.6   -0.1    1.3      99.3     0.6
Empenigr   28         2        0.3   -0.3    0.9      99.6     0.3
Cirsarve   29         2        0.3   -0.3    0.9      99.9     0.3
Chenalbu   30         1        0.1   -0.2    0.5     100.0     0.0
         rankfreq
Poatriv       3.3
Lolipere      6.7
Scorautu     10.0
Bracruta     13.3
Agrostol     16.7
Poaprat      20.0
Trifrepe     23.3
Alopgeni     26.7
Elymrepe     30.0
Planlanc     33.3
Eleopalu     36.7
Anthodor     40.0
Sagiproc     43.3
Juncarti     46.7
Rumeacet     50.0
Achimill     53.3
Bromhord     56.7
Ranuflam     60.0
Bellpere     63.3
Juncbufo     66.7
Salirepe     70.0
Callcusp     73.3
Hyporadi     76.7
Trifprat     80.0
Airaprae     83.3
Comapalu     86.7
Vicilath     90.0
Empenigr     93.3
Cirsarve     96.7
Chenalbu    100.0

> # dune %>% rankabundance() %>% 
> #   rankabunplot(scale     = "abundance", 
> #                addit     = FALSE, 
> #                specnames = c(1, 2, 3))
> # dune %>% rankabuncomp(y      = dune.env, 
> #                       factor = "Management", 
> #                       scale  = "proportion", 
> #                       legend = FALSE)