| Title: | Biodiversity Index Calculation and Bootstrap Confidence Interval Estimation | 
| Version: | 1.0.4 | 
| Description: | Provides tools for the calculation of common biodiversity indices from count data. Additionally, it incorporates bootstrapping techniques to generate multiple samples, facilitating the estimation of confidence intervals around these indices. Furthermore, the package allows for the exploration of how variation in these indices changes with differing numbers of sites, making it a useful tool with which to begin an ecological analysis. Methods are based on the following references: Chao et al. (2014) <doi:10.1890/13-0133.1>, Chao and Colwell (2022) <doi:10.1002/9781119902911.ch2>, Hsieh, Ma,' and Chao (2016) <doi:10.1111/2041-210X.12613>. | 
| License: | MIT + file LICENSE | 
| Encoding: | UTF-8 | 
| RoxygenNote: | 7.2.3 | 
| Imports: | ggplot2, stats | 
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0), vegan | 
| Depends: | R (≥ 2.10) | 
| LazyData: | true | 
| Config/testthat/edition: | 3 | 
| VignetteBuilder: | knitr | 
| URL: | https://github.com/csim063/biosampleR | 
| BugReports: | https://github.com/csim063/biosampleR/issues | 
| NeedsCompilation: | no | 
| Packaged: | 2023-09-13 03:36:49 UTC; simpk | 
| Author: | Craig Eric Simpkins | 
| Maintainer: | Craig Eric Simpkins <simpkinscraig063@gmail.com> | 
| Repository: | CRAN | 
| Date/Publication: | 2023-09-13 18:30:02 UTC | 
Barro-Colorado Island Tree Counts
Description
This dataset contains tree counts from Barro-Colorado Island. It has 50 rows each representing the counts taken from a separate one hectare plot for each of the 225 species (columns)
Usage
BCI
Format
A data frame with 50 rows and 225 columns:
- Abarema.macradenia
- Count for Abarema.macradenia 
- Vachellia.melanoceras
- Count for Vachellia.melanoceras 
- Acalypha.diversifolia
- Count for Acalypha.diversifolia 
- Acalypha.macrostachya
- Count for Acalypha.macrostachya 
- Adelia.triloba
- Count for Adelia.triloba 
- Aegiphila.panamensis
- Count for Aegiphila.panamensis 
- Alchornea.costaricensis
- Count for Alchornea.costaricensis 
- Alchornea.latifolia
- Count for Alchornea.latifolia 
- Alibertia.edulis
- Count for Alibertia.edulis 
- Allophylus.psilospermus
- Count for Allophylus.psilospermus 
- Alseis.blackiana
- Count for Alseis.blackiana 
- Amaioua.corymbosa
- Count for Amaioua.corymbosa 
- Anacardium.excelsum
- Count for Anacardium.excelsum 
- Andira.inermis
- Count for Andira.inermis 
- Annona.spraguei
- Count for Annona.spraguei 
- Apeiba.glabra
- Count for Apeiba.glabra 
- Apeiba.tibourbou
- Count for Apeiba.tibourbou 
- Aspidosperma.desmanthum
- Count for Aspidosperma.desmanthum 
- Astrocaryum.standleyanum
- Count for Astrocaryum.standleyanum 
- Astronium.graveolens
- Count for Astronium.graveolens 
- Attalea.butyracea
- Count for Attalea.butyracea 
- Banara.guianensis
- Count for Banara.guianensis 
- Beilschmiedia.pendula
- Count for Beilschmiedia.pendula 
- Brosimum.alicastrum
- Count for Brosimum.alicastrum 
- Brosimum.guianense
- Count for Brosimum.guianense 
- Calophyllum.longifolium
- Count for Calophyllum.longifolium 
- Casearia.aculeata
- Count for Casearia.aculeata 
- Casearia.arborea
- Count for Casearia.arborea 
- Casearia.commersoniana
- Count for Casearia.commersoniana 
- Casearia.guianensis
- Count for Casearia.guianensis 
- Casearia.sylvestris
- Count for Casearia.sylvestris 
- Cassipourea.guianensis
- Count for Cassipourea.guianensis 
- Cavanillesia.platanifolia
- Count for Cavanillesia.platanifolia 
- Cecropia.insignis
- Count for Cecropia.insignis 
- Cecropia.obtusifolia
- Count for Cecropia.obtusifolia 
- Cedrela.odorata
- Count for Cedrela.odorata 
- Ceiba.pentandra
- Count for Ceiba.pentandra 
- Celtis.schippii
- Count for Celtis.schippii 
- Cespedesia.spathulata
- Count for Cespedesia.spathulata 
- Chamguava.schippii
- Count for Chamguava.schippii 
- Chimarrhis.parviflora
- Count for Chimarrhis.parviflora 
- Maclura.tinctoria
- Count for Maclura.tinctoria 
- Chrysochlamys.eclipes
- Count for Chrysochlamys.eclipes 
- Chrysophyllum.argenteum
- Count for Chrysophyllum.argenteum 
- Chrysophyllum.cainito
- Count for Chrysophyllum.cainito 
- Coccoloba.coronata
- Count for Coccoloba.coronata 
- Coccoloba.manzinellensis
- Count for Coccoloba.manzinellensis 
- Colubrina.glandulosa
- Count for Colubrina.glandulosa 
- Cordia.alliodora
- Count for Cordia.alliodora 
- Cordia.bicolor
- Count for Cordia.bicolor 
- Cordia.lasiocalyx
- Count for Cordia.lasiocalyx 
- Coussarea.curvigemma
- Count for Coussarea.curvigemma 
- Croton.billbergianus
- Count for Croton.billbergianus 
- Cupania.cinerea
- Count for Cupania.cinerea 
- Cupania.latifolia
- Count for Cupania.latifolia 
- Cupania.rufescens
- Count for Cupania.rufescens 
- Cupania.seemannii
- Count for Cupania.seemannii 
- Dendropanax.arboreus
- Count for Dendropanax.arboreus 
- Desmopsis.panamensis
- Count for Desmopsis.panamensis 
- Diospyros.artanthifolia
- Count for Diospyros.artanthifolia 
- Dipteryx.oleifera
- Count for Dipteryx.oleifera 
- Drypetes.standleyi
- Count for Drypetes.standleyi 
- Elaeis.oleifera
- Count for Elaeis.oleifera 
- Enterolobium.schomburgkii
- Count for Enterolobium.schomburgkii 
- Erythrina.costaricensis
- Count for Erythrina.costaricensis 
- Erythroxylum.macrophyllum
- Count for Erythroxylum.macrophyllum 
- Eugenia.florida
- Count for Eugenia.florida 
- Eugenia.galalonensis
- Count for Eugenia.galalonensis 
- Eugenia.nesiotica
- Count for Eugenia.nesiotica 
- Eugenia.oerstediana
- Count for Eugenia.oerstediana 
- Faramea.occidentalis
- Count for Faramea.occidentalis 
- Ficus.colubrinae
- Count for Ficus.colubrinae 
- Ficus.costaricana
- Count for Ficus.costaricana 
- Ficus.insipida
- Count for Ficus.insipida 
- Ficus.maxima
- Count for Ficus.maxima 
- Ficus.obtusifolia
- Count for Ficus.obtusifolia 
- Ficus.popenoei
- Count for Ficus.popenoei 
- Ficus.tonduzii
- Count for Ficus.tonduzii 
- Ficus.trigonata
- Count for Ficus.trigonata 
- Ficus.yoponensis
- Count for Ficus.yoponensis 
- Garcinia.intermedia
- Count for Garcinia.intermedia 
- Garcinia.madruno
- Count for Garcinia.madruno 
- Genipa.americana
- Count for Genipa.americana 
- Guapira.myrtiflora
- Count for Guapira.myrtiflora 
- Guarea.fuzzy
- Count for Guarea.fuzzy 
- Guarea.grandifolia
- Count for Guarea.grandifolia 
- Guarea.guidonia
- Count for Guarea.guidonia 
- Guatteria.dumetorum
- Count for Guatteria.dumetorum 
- Guazuma.ulmifolia
- Count for Guazuma.ulmifolia 
- Guettarda.foliacea
- Count for Guettarda.foliacea 
- Gustavia.superba
- Count for Gustavia.superba 
- Hampea.appendiculata
- Count for Hampea.appendiculata 
- Hasseltia.floribunda
- Count for Hasseltia.floribunda 
- Heisteria.acuminata
- Count for Heisteria.acuminata 
- Heisteria.concinna
- Count for Heisteria.concinna 
- Hirtella.americana
- Count for Hirtella.americana 
- Hirtella.triandra
- Count for Hirtella.triandra 
- Hura.crepitans
- Count for Hura.crepitans 
- Hieronyma.alchorneoides
- Count for Hieronyma.alchorneoides 
- Inga.acuminata
- Count for Inga.acuminata 
- Inga.cocleensis
- Count for Inga.cocleensis 
- Inga.goldmanii
- Count for Inga.goldmanii 
- Inga.laurina
- Count for Inga.laurina 
- Inga.semialata
- Count for Inga.semialata 
- Inga.nobilis
- Count for Inga.nobilis 
- Inga.oerstediana
- Count for Inga.oerstediana 
- Inga.pezizifera
- Count for Inga.pezizifera 
- Inga.punctata
- Count for Inga.punctata 
- Inga.ruiziana
- Count for Inga.ruiziana 
- Inga.sapindoides
- Count for Inga.sapindoides 
- Inga.spectabilis
- Count for Inga.spectabilis 
- Inga.umbellifera
- Count for Inga.umbellifera 
- Jacaranda.copaia
- Count for Jacaranda.copaia 
- Lacistema.aggregatum
- Count for Lacistema.aggregatum 
- Lacmellea.panamensis
- Count for Lacmellea.panamensis 
- Laetia.procera
- Count for Laetia.procera 
- Laetia.thamnia
- Count for Laetia.thamnia 
- Lafoensia.punicifolia
- Count for Lafoensia.punicifolia 
- Licania.hypoleuca
- Count for Licania.hypoleuca 
- Licania.platypus
- Count for Licania.platypus 
- Lindackeria.laurina
- Count for Lindackeria.laurina 
- Lonchocarpus.heptaphyllus
- Count for Lonchocarpus.heptaphyllus 
- Luehea.seemannii
- Count for Luehea.seemannii 
- Macrocnemum.roseum
- Count for Macrocnemum.roseum 
- Maquira.guianensis.costaricana
- Count for Maquira.guianensis.costaricana 
- Margaritaria.nobilis
- Count for Margaritaria.nobilis 
- Marila.laxiflora
- Count for Marila.laxiflora 
- Maytenus.schippii
- Count for Maytenus.schippii 
- Miconia.affinis
- Count for Miconia.affinis 
- Miconia.argentea
- Count for Miconia.argentea 
- Miconia.elata
- Count for Miconia.elata 
- Miconia.hondurensis
- Count for Miconia.hondurensis 
- Mosannona.garwoodii
- Count for Mosannona.garwoodii 
- Myrcia.gatunensis
- Count for Myrcia.gatunensis 
- Myrospermum.frutescens
- Count for Myrospermum.frutescens 
- Nectandra.cissiflora
- Count for Nectandra.cissiflora 
- Nectandra.lineata
- Count for Nectandra.lineata 
- Nectandra.purpurea
- Count for Nectandra.purpurea 
- Ochroma.pyramidale
- Count for Ochroma.pyramidale 
- Ocotea.cernua
- Count for Ocotea.cernua 
- Ocotea.oblonga
- Count for Ocotea.oblonga 
- Ocotea.puberula
- Count for Ocotea.puberula 
- Ocotea.whitei
- Count for Ocotea.whitei 
- Oenocarpus.mapora
- Count for Oenocarpus.mapora 
- Ormosia.amazonica
- Count for Ormosia.amazonica 
- Ormosia.coccinea
- Count for Ormosia.coccinea 
- Ormosia.macrocalyx
- Count for Ormosia.macrocalyx 
- Pachira.quinata
- Count for Pachira.quinata 
- Pachira.sessilis
- Count for Pachira.sessilis 
- Perebea.xanthochyma
- Count for Perebea.xanthochyma 
- Cinnamomum.triplinerve
- Count for Cinnamomum.triplinerve 
- Picramnia.latifolia
- Count for Picramnia.latifolia 
- Piper.reticulatum
- Count for Piper.reticulatum 
- Platymiscium.pinnatum
- Count for Platymiscium.pinnatum 
- Platypodium.elegans
- Count for Platypodium.elegans 
- Posoqueria.latifolia
- Count for Posoqueria.latifolia 
- Poulsenia.armata
- Count for Poulsenia.armata 
- Pourouma.bicolor
- Count for Pourouma.bicolor 
- Pouteria.fossicola
- Count for Pouteria.fossicola 
- Pouteria.reticulata
- Count for Pouteria.reticulata 
- Pouteria.stipitata
- Count for Pouteria.stipitata 
- Prioria.copaifera
- Count for Prioria.copaifera 
- Protium.costaricense
- Count for Protium.costaricense 
- Protium.panamense
- Count for Protium.panamense 
- Protium.tenuifolium
- Count for Protium.tenuifolium 
- Pseudobombax.septenatum
- Count for Pseudobombax.septenatum 
- Psidium.friedrichsthalianum
- Count for Psidium.friedrichsthalianum 
- Psychotria.grandis
- Count for Psychotria.grandis 
- Pterocarpus.rohrii
- Count for Pterocarpus.rohrii 
- Quararibea.asterolepis
- Count for Quararibea.asterolepis 
- Quassia.amara
- Count for Quassia.amara 
- Randia.armata
- Count for Randia.armata 
- Sapium.broadleaf
- Count for Sapium.broadleaf 
- Sapium.glandulosum
- Count for Sapium.glandulosum 
- Schizolobium.parahyba
- Count for Schizolobium.parahyba 
- Senna.dariensis
- Count for Senna.dariensis 
- Simarouba.amara
- Count for Simarouba.amara 
- Siparuna.guianensis
- Count for Siparuna.guianensis 
- Siparuna.pauciflora
- Count for Siparuna.pauciflora 
- Sloanea.terniflora
- Count for Sloanea.terniflora 
- Socratea.exorrhiza
- Count for Socratea.exorrhiza 
- Solanum.hayesii
- Count for Solanum.hayesii 
- Sorocea.affinis
- Count for Sorocea.affinis 
- Spachea.membranacea
- Count for Spachea.membranacea 
- Spondias.mombin
- Count for Spondias.mombin 
- Spondias.radlkoferi
- Count for Spondias.radlkoferi 
- Sterculia.apetala
- Count for Sterculia.apetala 
- Swartzia.simplex.var.grandiflora
- Count for Swartzia.simplex.var.grandiflora 
- Swartzia.simplex.continentalis
- Count for Swartzia.simplex.continentalis 
- Symphonia.globulifera
- Count for Symphonia.globulifera 
- Handroanthus.guayacan
- Count for Handroanthus.guayacan 
- Tabebuia.rosea
- Count for Tabebuia.rosea 
- Tabernaemontana.arborea
- Count for Tabernaemontana.arborea 
- Tachigali.versicolor
- Count for Tachigali.versicolor 
- Talisia.nervosa
- Count for Talisia.nervosa 
- Talisia.princeps
- Count for Talisia.princeps 
- Terminalia.amazonia
- Count for Terminalia.amazonia 
- Terminalia.oblonga
- Count for Terminalia.oblonga 
- Tetragastris.panamensis
- Count for Tetragastris.panamensis 
- Tetrathylacium.johansenii
- Count for Tetrathylacium.johansenii 
- Theobroma.cacao
- Count for Theobroma.cacao 
- Thevetia.ahouai
- Count for Thevetia.ahouai 
- Tocoyena.pittieri
- Count for Tocoyena.pittieri 
- Trattinnickia.aspera
- Count for Trattinnickia.aspera 
- Trema.micrantha
- Count for Trema.micrantha 
- Trichanthera.gigantea
- Count for Trichanthera.gigantea 
- Trichilia.pallida
- Count for Trichilia.pallida 
- Trichilia.tuberculata
- Count for Trichilia.tuberculata 
- Trichospermum.galeottii
- Count for Trichospermum.galeottii 
- Triplaris.cumingiana
- Count for Triplaris.cumingiana 
- Trophis.caucana
- Count for Trophis.caucana 
- Trophis.racemosa
- Count for Trophis.racemosa 
- Turpinia.occidentalis
- Count for Turpinia.occidentalis 
- Unonopsis.pittieri
- Count for Unonopsis.pittieri 
- Virola.multiflora
- Count for Virola.multiflora 
- Virola.sebifera
- Count for Virola.sebifera 
- Virola.surinamensis
- Count for Virola.surinamensis 
- Vismia.baccifera
- Count for Vismia.baccifera 
- Vochysia.ferruginea
- Count for Vochysia.ferruginea 
- Xylopia.macrantha
- Count for Xylopia.macrantha 
- Zanthoxylum.ekmanii
- Count for Zanthoxylum.ekmanii 
- Zanthoxylum.juniperinum
- Count for Zanthoxylum.juniperinum 
- Zanthoxylum.panamense
- Count for Zanthoxylum.panamense 
- Zanthoxylum.setulosum
- Count for Zanthoxylum.setulosum 
- Zuelania.guidonia
- Count for Zuelania.guidonia 
Source
https://www.science.org/doi/10.1126/science.1066854
Calculate the change in variance with increasing number of sites
Description
Calculate the change in variance with increasing number of sites
Usage
calc_delta_var(
  data,
  col_name,
  site_name = "num_sites",
  rep_name = "rep",
  visualize = FALSE
)
Arguments
| data | A data frame containing the biodiversity indices to analyze, for a different number of sites over multiple repetitions. | 
| col_name | The name of the column containing the biodiversity index to analyze. | 
| site_name | The name of the column containing the number of sites. | 
| rep_name | The name of the column containing the repetition number. | 
| visualize | A logical indicating whether to visualize the results. | 
Value
A data frame with the number of sites and the variance and standard deviation of the mean of the biodiversity index for each number of sites.
Examples
ss <- generate_subsamples(BCI,
                         min_sites = 1,
                        max_sites = 5,
                       step = 1,
                     reps = 5)
data <- ss
data  <- unlist(data, recursive = FALSE)
data <- do.call(rbind, data)
calc_delta_var(data,
             col_name = "richness",
           site_name = "num_sites",
        rep_name = "rep",
     visualize = TRUE)
Calculate biodiversity summary indices from count data
Description
Calculate biodiversity summary indices from count data
Usage
calc_diversity_indices(data)
Arguments
| data | A data frame of count data, with sites as rows and species as columns. | 
Value
A data frame with sites as rows and diversity indices as columns. The columns are: abundance, species richness, Shannon diveristy index, Simpson diversity index, Chao1, Difference between Choa1 and species richness.
Examples
ind <- calc_diversity_indices(BCI)
Create multiple resamples of a data set.
Description
Create multiple resamples of a data set.
Usage
create_resample(data, reps = 100, summary = TRUE, seed = sample(0:9999, 1))
Arguments
| data | A data frame of count data, with sites as rows and species as columns. | 
| reps | The number of resamples to create. | 
| summary | A logical indicating whether to calculate summary indices
using  | 
| seed | A random seed to use for reproducibility. | 
Value
A list of data frames, if summary = FALSE, each data frame
is a resample of the original data set. If summary = TRUE,
each data frame is a resample of the original data set with
diversity indices calculated using
calc_diversity_indices.
Examples
rs <- create_resample(BCI, reps = 10, summary = TRUE)
Generate subsamples of a data frame with a number of sites between a minimum and maximum value.
Description
Generate subsamples of a data frame with a number of sites between a minimum and maximum value.
Usage
generate_subsamples(
  data,
  min_sites = 1,
  max_sites = nrow(data),
  step = 1,
  reps = 100,
  summary = TRUE,
  seed = sample(0:9999, 1)
)
Arguments
| data | A data frame of count data, with sites as rows and species as columns. | 
| min_sites | The minimum number of sites to include in a subsample. | 
| max_sites | The maximum number of sites to include in a subsample. Defaults to the number of sites in the original data set. | 
| step | The number of sites to increase by at each iteration. | 
| reps | The number of subsamples with a given number of sites to create. | 
| summary | A logical indicating whether to calculate summary indices
using  | 
| seed | A random seed to use for reproducibility. | 
Value
A list of lists of data frames, if summary = FALSE, each data
frame is a subsample of the original data set. If summary =
      TRUE, each data frame is a subsample of the original data set with
diversity indices calculated using
calc_diversity_indices.
Examples
ss <- generate_subsamples(BCI,
                          min_sites = 1,
                          max_sites = 5,
                          step = 1,
                          reps = 2)
Calculate biodiversity measures and summary statistics for a data set using repeated sampling
Description
Calculate biodiversity measures and summary statistics for a data set using repeated sampling
Usage
get_sample_stats(data, sites_col = 1, reps = 100, indices = "all")
Arguments
| data | A data frame of count data, with sites as rows and species as columns. | 
| sites_col | The column number of column containing site IDs. | 
| reps | The number of resamples to create. | 
| indices | A vector of indices to calculate. Use "all" to calculate all indices. Available indices are: abundance, richness, shannon, simpson, chao1, and chao_diff. | 
Value
A list of two data frames. The first data frame contains site specific data with sites as rows and summary statistics as columns. The second contains an overall summary of the data.
Examples
stats <- get_sample_stats(BCI, reps = 5)