Package 'ggvegan' reference manual

Title:	'ggplot2' Plots for the 'vegan' Package
Description:	Functions to produce ggplot2-based plots of objects produced by functions in the vegan package.
Authors:	Gavin L. Simpson [aut, cre], Jari Oksanen [aut], Didzis Elferts [ctb]
Maintainer:	Gavin L. Simpson <[email protected]>
License:	GPL-2
Version:	0.1.999
Built:	2024-10-29 03:00:31 UTC
Source:	https://github.com/gavinsimpson/ggvegan

Adds species and site score layers to an existing plot

Description

Adds species and site score layers to an existing plot

Usage

add_spp_site_scores(object, plt, vars, geom, draw_list, arrows)
add_spp_site_scores(object, plt, vars, geom, draw_list, arrows)

Arguments

`object`	an ordination object.
`plt`	a ggplot object.
`vars`	character; length 2 vector of dimension names.
`geom`	character; vector of length 1 or 2 indicating which geoms will be used ofr the species or site scores.
`draw_list`	logical; vector of types of scores indicating which are available and requested for plotting.
`arrows`	logical; length 1 vector indicating if species scores should be drawn using arrows.

Scale Vectors to Data

Description

Scale vector arrows to fill proportion of the data.

Usage

arrow_mul(arrows, data, at = c(0, 0), fill = 0.75)
arrow_mul(arrows, data, at = c(0, 0), fill = 0.75)

Arguments

`arrows`	a two-column matrix-like object containing coordinates for the arrows/vectors on x and y axes.
`data`	a two-column matrix-like object containing coordinates of the data on the x and y axes.
`at`	numeric vector of length 2; location of the origin of the arrows.
`fill`	numeric; what proportion of the range of the data to fill

Value

a numeric multiplier that will scale the arrows

Author(s)

Gavin L. Simpson

ggplot-based plot for objects of class `"anosim"`

Description

Produces a multi-layer ggplot object representing the output of objects produced by anosim.

Usage

## S3 method for class 'anosim'
autoplot(
  object,
  notch = TRUE,
  varwidth = TRUE,
  xlab = NULL,
  ylab = NULL,
  title = "Analysis of similarities",
  subtitle = NULL,
  caption = bquote(R == .(R) * "," ~ P == .(P)),
  ...
)
## S3 method for class 'anosim'
autoplot(
  object,
  notch = TRUE,
  varwidth = TRUE,
  xlab = NULL,
  ylab = NULL,
  title = "Analysis of similarities",
  subtitle = NULL,
  caption = bquote(R == .(R) * "," ~ P == .(P)),
  ...
)

Arguments

`object`	an object of class `"anosim"`, the result of a call to `anosim`.
`notch`	logical; make notched (default) or standard box plot?
`varwidth`	logical; make box width proportional to the square-root of the number of observations in the group (default)?
`xlab`	character; label for the x-axis.
`ylab`	character; label for the y-axis.
`title`	character; title for the plot.
`subtitle`	character; subtitle for the plot.
`caption`	character; caption for the plot.
`...`	additional arguments passed to other methods.

Value

A ggplot object.

Author(s)

Didzis Elferts. Modifications by Gavin L. Simpson.

Examples


data(dune)
data(dune.env)
dune.dist <- vegdist(dune)
dune.ano <- with(dune.env, anosim(dune.dist, Management))

autoplot(dune.ano, notch = FALSE)
data(dune)
data(dune.env)
dune.dist <- vegdist(dune)
dune.ano <- with(dune.env, anosim(dune.dist, Management))

autoplot(dune.ano, notch = FALSE)

ggplot-based plot for objects of class `"cca"`

Description

Produces a multi-layer ggplot object representing the output of objects produced by cca, or capscale.

Usage

## S3 method for class 'cca'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites", "biplot", "centroids"),
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  ...
)
## S3 method for class 'cca'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites", "biplot", "centroids"),
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  ...
)

Arguments

`object`	an object of class `"cca"`, the result of a call to `cca` or `capscale`.
`axes`	numeric; which axes to plot, given as a vector of length 2.
`geom`	character; which geoms to use for the layers. Can be a vector of length equal to `length(display)`, in which case the ith element of `type` refers to the ith element of `display`.
`layers`	character; which scores to plot as layers
`legend.position`	character or two-element numeric vector; where to position the legend. See `theme` for details. Use `"none"` to not draw the legend.
`title`	character; subtitle for the plot
`subtitle`	character; subtitle for the plot
`caption`	character; caption for the plot
`ylab`	character; label for the y-axis
`xlab`	character; label for the x-axis
`...`	Additional arguments passed to `fortify.cca`.

Details

TODO

Value

Returns a ggplot object.

Author(s)

Gavin L. Simpson

Examples

data(dune)
data(dune.env)

sol <- cca(dune ~ A1 + Management, data = dune.env)
autoplot(sol)
data(dune)
data(dune.env)

sol <- cca(dune ~ A1 + Management, data = dune.env)
autoplot(sol)

ggplot-based plot for objects of class `"decorana"`

Description

Produces a multi-layer ggplot object representing the output of objects produced by decorana.

Usage

## S3 method for class 'decorana'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites"),
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  ...
)
## S3 method for class 'decorana'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites"),
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  ...
)

Arguments

`object`	an object of class `"decorana"`, the result of a call to `decorana`.
`axes`	numeric; which axes to plot, given as a vector of length 2.
`geom`	character; which geoms to use for the layers. Can be a vector of length equal to `length(display)`, in which case the ith element of `type` refers to the ith element of `display`.
`layers`	character; which scores to plot as layers
`legend.position`	character or two-element numeric vector; where to position the legend. See `theme` for details. Use `"none"` to not draw the legend.
`title`	character; subtitle for the plot
`subtitle`	character; subtitle for the plot
`caption`	character; caption for the plot
`ylab`	character; label for the y-axis
`xlab`	character; label for the x-axis
`...`	Additional arguments passed to `fortify.decorana`.

Details

TODO

Value

Returns a ggplot object.

Author(s)

Gavin L. Simpson

Examples

data(dune)

sol <- decorana(dune)
autoplot(sol)
autoplot(sol, display = "species", geom = "text")
data(dune)

sol <- decorana(dune)
autoplot(sol)
autoplot(sol, display = "species", geom = "text")

ggplot-based plot for `envfit` objects

Description

Produces a multi-layer ggplot object representing the output of objects produced by isomap.

Usage

## S3 method for class 'envfit'
autoplot(
  object,
  geom = c("label", "text", "label_repel", "text_repel"),
  line.col = "black",
  xlab = NULL,
  ylab = NULL,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ...
)
## S3 method for class 'envfit'
autoplot(
  object,
  geom = c("label", "text", "label_repel", "text_repel"),
  line.col = "black",
  xlab = NULL,
  ylab = NULL,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

`object`	an object of class `"envfit"`, the result of a call to `envfit`.
`geom`	character; which geom to use to label vectors and factor centroids.
`line.col`	colour with which to draw vectors.
`xlab`	character; label for the x-axis.
`ylab`	character; label for the y-axis.
`title`	character; subtitle for the plot.
`subtitle`	character; subtitle for the plot.
`caption`	character; caption for the plot.
`...`	additional arguments passed to `fortify`.

Value

A ggplot object.

Author(s)

Gavin L. Simpson

Examples

data(varespec, varechem)
ord1 <- metaMDS(varespec)
fit1 <- envfit(ord1, varechem, perm = 199)

autoplot(fit1, geom = 'label_repel')

data(dune, dune.env)
ord2 <- cca(dune)
fit2 <- envfit(ord2 ~ Moisture + A1, dune.env, perm = 199)

autoplot(fit2)
data(varespec, varechem)
ord1 <- metaMDS(varespec)
fit1 <- envfit(ord1, varechem, perm = 199)

autoplot(fit1, geom = 'label_repel')

data(dune, dune.env)
ord2 <- cca(dune)
fit2 <- envfit(ord2 ~ Moisture + A1, dune.env, perm = 199)

autoplot(fit2)

Plot Fisher's log-series

Description

Draws a bar plot of species rank abundance with Fisher's log-series superimposed.

Usage

## S3 method for class 'fisherfit'
autoplot(
  object,
  show.fitted = TRUE,
  xlab = "Abundance",
  ylab = "Number of Species",
  title = "Fisher's log-series distribution",
  bar.col = NA,
  bar.fill = "grey35",
  line.col = "red",
  size = 1,
  subtitle = NULL,
  caption = NULL,
  ...
)
## S3 method for class 'fisherfit'
autoplot(
  object,
  show.fitted = TRUE,
  xlab = "Abundance",
  ylab = "Number of Species",
  title = "Fisher's log-series distribution",
  bar.col = NA,
  bar.fill = "grey35",
  line.col = "red",
  size = 1,
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

`object`	an object of class `fisherfit`.
`show.fitted`	logical; should the estimated distribution also be plotted?
`xlab`	character; label for the x axis.
`ylab`	character; label for the y axis.
`title`	character; subtitle for the plot.
`bar.col`	colour for the bar outlines. The default, `NA`, does not draw outlines around bars.
`bar.fill`	fill colour for the bars.
`line.col`	colour for Fisher's log-series curve.
`size`	numeric; size aesthetic for the log-series curve.
`subtitle`	character; subtitle for the plot.
`caption`	character; caption for the plot.
`...`	additional arguments passed to other methods.

Value

A ggplot object.

Author(s)

Gavin L. Simpson

Examples


data(BCI)
mod <- fisherfit(BCI[5,])
autoplot(mod)
data(BCI)
mod <- fisherfit(BCI[5,])
autoplot(mod)

ggplot-based plot for objects of class `"isomap"`

Description

Produces a multi-layer ggplot object representing the output of objects produced by isomap.

Usage

## S3 method for class 'isomap'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  network = TRUE,
  line.col = "grey85",
  size = 0.7,
  xlab = NULL,
  ylab = NULL,
  title = "Isometric feature mapping",
  subtitle = NULL,
  caption = NULL,
  ...
)
## S3 method for class 'isomap'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  network = TRUE,
  line.col = "grey85",
  size = 0.7,
  xlab = NULL,
  ylab = NULL,
  title = "Isometric feature mapping",
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

`object`	an object of class `"isomap"`, the result of a call to `isomap`.
`axes`	numeric; which axes to plot, given as a vector of length 2.
`geom`	character; which geom to use for the MDS scores layer.
`network`	logical; should the edges of the ISOMAP network be drawn?
`line.col`	colour with which to draw the network edges.
`size`	numeric; size aesthetic for the log-series curve.
`xlab`	character; label for the x-axis.
`ylab`	character; label for the y-axis.
`title`	character; subtitle for the plot.
`subtitle`	character; subtitle for the plot.
`caption`	character; caption for the plot.
`...`	additional arguments passed to other methods.

Value

A ggplot object.

Author(s)

Gavin L. Simpson

Examples


data(BCI)
dis <- vegdist(BCI)
ord <- isomap(dis, k = 3)

autoplot(ord)

autoplot(ord, geom = "text")
data(BCI)
dis <- vegdist(BCI)
ord <- isomap(dis, k = 3)

autoplot(ord)

autoplot(ord, geom = "text")

ggplot-based plot for objects of class `"metaMDS"`

Description

Produces a multi-layer ggplot object representing the output of objects produced by metaMDS.

Usage

## S3 method for class 'metaMDS'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites"),
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  ...
)
## S3 method for class 'metaMDS'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites"),
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  ...
)

Arguments

`object`	an object of class `"metaMDS"`, the result of a call to `metaMDS`.
`axes`	numeric; which axes to plot, given as a vector of length 2.
`geom`	character; which geoms to use for the layers. Can be a vector of length equal to `length(display)`, in which case the ith element of `type` refers to the ith element of `display`.
`layers`	character; which scores to plot as layers
`legend.position`	character or two-element numeric vector; where to position the legend. See `theme` for details. Use `"none"` to not draw the legend.
`title`	character; subtitle for the plot
`subtitle`	character; subtitle for the plot
`caption`	character; caption for the plot
`ylab`	character; label for the y-axis
`xlab`	character; label for the x-axis
`...`	Additional arguments passed to `fortify.metaMDS`.

Details

TODO

Value

Returns a ggplot object.

Author(s)

Gavin L. Simpson

Examples

## load example data
data(dune)

sol <- metaMDS(dune)
autoplot(sol)
## load example data
data(dune)

sol <- metaMDS(dune)
autoplot(sol)

ggplot-based plot for objects of class `"poolaccum"`

Description

Produces a multi-layer ggplot object representing the output of objects produced by poolaccum.

Usage

## S3 method for class 'poolaccum'
autoplot(
  object,
  facet = TRUE,
  ribbon = facet,
  ncol = NULL,
  ribbon.alpha = 0.3,
  xlab = "Size",
  ylab = "Richness",
  title = "Accumulated species richness",
  subtitle = NULL,
  caption = NULL,
  ...
)
## S3 method for class 'poolaccum'
autoplot(
  object,
  facet = TRUE,
  ribbon = facet,
  ncol = NULL,
  ribbon.alpha = 0.3,
  xlab = "Size",
  ylab = "Richness",
  title = "Accumulated species richness",
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

`object`	an object of class `"poolaccum"`, the result of a call to `poolaccum`.
`facet`	logical; should extrapolated richness estimators be shown in separate facets?
`ribbon`	logical; show the quantile-based uncertainty interval? Uses `geom_ribbon` for plot.
`ncol`	numeric; if facetting the plot, how many columns to use. Default arguuments will result in three columns.
`ribbon.alpha`	numeric; alpha transparency used for the uncertainty interval. Passed to the `alpha` aesthetic of `ggplot2::geom_ribbon()`.
`xlab`	character; label for the x axis.
`ylab`	character; label for the y axis.
`title`	character; title for the plot.
`subtitle`	character; subtitle for the plot.
`caption`	character; caption for the plot.
`...`	additional arguments passed to `fortify.poolaccum()`.

Value

A ggplot object.

Author(s)

Didzis Elferts & Gavin L. Simpson

Examples

data(BCI)
pool <- poolaccum(BCI)

autoplot(pool)

## Turn off facetting; turns off ribbon too
autoplot(pool, facet = FALSE)
data(BCI)
pool <- poolaccum(BCI)

autoplot(pool)

## Turn off facetting; turns off ribbon too
autoplot(pool, facet = FALSE)

ggplot-based plot for objects of class `"prc"`

Description

Produces a multi-layer ggplot object representing the output of objects produced by prc.

Usage

## S3 method for class 'prc'
autoplot(
  object,
  select,
  xlab,
  ylab,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  legend.position = "top",
  ...
)
## S3 method for class 'prc'
autoplot(
  object,
  select,
  xlab,
  ylab,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  legend.position = "top",
  ...
)

Arguments

`object`	an object inheriting from class `"prc"`, the result of a call to `prc`.
`select`	a logical vector where `TRUE` selects and `FALSE` deselects species. Alternatively a numeric vector that contains the indices selecting species. Note that these are with respect to the original species matrix, not the fortified object.
`xlab`	character; label for the x-axis
`ylab`	character; label for the y-axis
`title`	character; subtitle for the plot
`subtitle`	character; subtitle for the plot
`caption`	character; caption for the plot
`legend.position`	character; position for the legend grob. See argument `legend.position` in function `theme`.
`...`	Additional arguments passed to `fortify.prc`.

Details

TODO

Value

Returns a ggplot object.

Author(s)

Gavin L. Simpson

Examples

data(pyrifos)
week <- gl(11, 12, labels=c(-4, -1, 0.1, 1, 2, 4, 8, 12, 15, 19, 24))
dose <- factor(rep(c(0.1, 0, 0, 0.9, 0, 44, 6, 0.1, 44, 0.9, 0, 6), 11))

## Fit PRC model
mod <- prc(pyrifos, dose, week)

## plot
want <- colSums(pyrifos)
autoplot(mod, select = want)
data(pyrifos)
week <- gl(11, 12, labels=c(-4, -1, 0.1, 1, 2, 4, 8, 12, 15, 19, 24))
dose <- factor(rep(c(0.1, 0, 0, 0.9, 0, 44, 6, 0.1, 44, 0.9, 0, 6), 11))

## Fit PRC model
mod <- prc(pyrifos, dose, week)

## plot
want <- colSums(pyrifos)
autoplot(mod, select = want)

Plot Preston's log-normal model of species abundance

Description

Draws a bar plot of species rank abundance with Fisher's log-series superimposed.

Usage

## S3 method for class 'prestonfit'
autoplot(
  object,
  show.fitted = TRUE,
  xlab = "Abundance",
  ylab = "Number of Species",
  title = "Preston's lognormal distribution",
  subtitle = NULL,
  caption = NULL,
  bar.col = NA,
  bar.fill = "grey35",
  line.col = "red",
  size = 1,
  ...
)
## S3 method for class 'prestonfit'
autoplot(
  object,
  show.fitted = TRUE,
  xlab = "Abundance",
  ylab = "Number of Species",
  title = "Preston's lognormal distribution",
  subtitle = NULL,
  caption = NULL,
  bar.col = NA,
  bar.fill = "grey35",
  line.col = "red",
  size = 1,
  ...
)

Arguments

`object`	an object of class `prestonfit`.
`show.fitted`	logical; should the estimated distribution also be plotted?
`xlab`	character; label for the x axis.
`ylab`	character; label for the y axis.
`title`	character; title for the plot.
`subtitle`	character; subtitle for the plot.
`caption`	character; caption for the plot.
`bar.col`	colour for the bar outlines. The default, `NA`, does not draw outlines around bars.
`bar.fill`	fill colour for the bars.
`line.col`	colour for Fisher's log-series curve.
`size`	numeric; size aesthetic for the log-series curve.
`...`	additional arguments passed to other methods.

Value

A ggplot object.

Author(s)

Gavin L. Simpson

Examples


data(BCI)
pfit <- prestonfit(colSums(BCI))
autoplot(pfit)
data(BCI)
pfit <- prestonfit(colSums(BCI))
autoplot(pfit)

ggplot-based plot for objects of class `'rda'`

Description

Produces a multi-layer ggplot object representing the output of objects produced by rda.

Usage

## S3 method for class 'rda'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites", "biplot", "centroids"),
  arrows = TRUE,
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  const,
  ...
)
## S3 method for class 'rda'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites", "biplot", "centroids"),
  arrows = TRUE,
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  const,
  ...
)

Arguments

`object`	an object of class `"rda"`, the result of a call to `rda`
`axes`	numeric; which axes to plot, given as a vector of length 2.
`geom`	character; which geoms to use for the layers. Can be a vector of up to length 2, in which case, the first element of `geom` will be used for any site scores (both weighted sum or linear combination scores), and the second element will be used for species scores. The latter will be ignored if `arrows = TRUE`.
`layers`	character; which scores to plot as layers
`arrows`	logical; represent species (variables) using vectors?
`legend.position`	character or two-element numeric vector; where to position the legend. See `theme` for details. Use `"none"` to not draw the legend.
`title`	character; subtitle for the plot
`subtitle`	character; subtitle for the plot
`caption`	character; caption for the plot
`ylab`	character; label for the y-axis
`xlab`	character; label for the x-axis
`const`	General scaling constant to `rda` scores. See `scores.rda` for details.
`...`	Additional arguments passed to `fortify.cca`.

Details

TODO

Value

Returns a ggplot object.

Author(s)

Gavin L. Simpson

Examples


data(dune)

pca <- rda(dune)
autoplot(pca)

## Just the species scores
autoplot(pca, layers = "species")
data(dune)

pca <- rda(dune)
autoplot(pca)

## Just the species scores
autoplot(pca, layers = "species")

Check user-supplied layers against list of valid layers

Description

Check user-supplied layers against list of valid layers

Usage

check_user_layers(user, valid, message = FALSE)
check_user_layers(user, valid, message = FALSE)

Arguments

`user`	character; vector of user supplied layer names.
`valid`	character; vector of valid layer names.
`message`	logical; should a message be raised in the case of invalid user-supplied layer names.

Fortify analysis of similarities (ANOSIM) results

Description

Prepares a fortified version of results from anosim objects.

Usage

## S3 method for class 'anosim'
fortify(model, data, ...)
## S3 method for class 'anosim'
fortify(model, data, ...)

Arguments

`model`	an object of class `anosim`.
`data`	original data set. Currently ignored.
`...`	additional arguments for other methods. Currently ignored.

Value

A data frame with columns Rank and Class with ranks of dissimilarity.

Author(s)

Didzis Elferts

Examples

data(dune, dune.env)
dune.dist <- vegdist(dune)
dune.ano <- with(dune.env, anosim(dune.dist, Management))

df <- fortify(dune.ano)

ggplot(df, aes(x = Class, y = Rank)) +
    geom_boxplot(notch = FALSE, varwidth = TRUE)

data(dune, dune.env)
dune.dist <- vegdist(dune)
dune.ano <- with(dune.env, anosim(dune.dist, Management))

df <- fortify(dune.ano)

ggplot(df, aes(x = Class, y = Rank)) +
    geom_boxplot(notch = FALSE, varwidth = TRUE)

Fortify a `"cca"` object.

Description

Fortifies an object of class "cca" to produce a data frame of the selected axis scores in long format, suitable for plotting with ggplot.

Usage

## S3 method for class 'cca'
fortify(
  model,
  data,
  axes = 1:6,
  display = c("sp", "wa", "lc", "bp", "cn"),
  ...
)
## S3 method for class 'cca'
fortify(
  model,
  data,
  axes = 1:6,
  display = c("sp", "wa", "lc", "bp", "cn"),
  ...
)

Arguments

`model`	an object of class `"cca"`, the result of a call to `cca`, `rda`, or `capscale`.
`data`	currently ignored.
`axes`	numeric; which axes to extract scores for.
`display`	numeric; the scores to extract in the fortified object.
`...`	additional arguments passed to `scores.cca`, and `scores.rda`.

Details

TODO

Value

A data frame in long format containing the ordination scores. The first two components are the axis scores.

Author(s)

Gavin L. Simpson

Examples

data(dune)
data(dune.env)

sol <- cca(dune ~ A1 + Management, data = dune.env)
head(fortify(sol))
data(dune)
data(dune.env)

sol <- cca(dune ~ A1 + Management, data = dune.env)
head(fortify(sol))

Fortify a `"decorana"` object.

Description

Fortifies an object of class "decorana" to produce a data frame of the selected axis scores in long format, suitable for plotting with ggplot.

Usage

## S3 method for class 'decorana'
fortify(model, data, axes = 1:4, display = c("sites", "species"), ...)
## S3 method for class 'decorana'
fortify(model, data, axes = 1:4, display = c("sites", "species"), ...)

Arguments

`model`	an object of class `"decorana"`, the result of a call to `decorana`.
`data`	currently ignored.
`axes`	numeric; which axis scores are required?
`display`	character; the scores to extract in the fortified object.
`...`	additional arguments passed to `scores.decorana`.

Details

TODO

Value

A data frame in long format containing the ordination scores. The first two components are the axis scores.

Author(s)

Gavin L. Simpson

Examples

data(dune)

sol <- decorana(dune)
head(fortify(sol))
head(fortify(sol, display = "species"))
data(dune)

sol <- decorana(dune)
head(fortify(sol))
head(fortify(sol, display = "species"))

Fortify method for `envfit` objects

Description

Produces a tidy data frame from the results of an envfit object.

Usage

## S3 method for class 'envfit'
fortify(model, data, ...)
## S3 method for class 'envfit'
fortify(model, data, ...)

Arguments

`model`	an object of class `envfit`, the result of a call to `envfit`.
`data`	additional data to augment the `envfit` results. Currently ignored.
`...`	arguments passed to `scores.envfit`.

Value

A data frame with columns label, type, containing the label for, and whether each row refers to, the fitted vector or factor. Remaining variables are coordinates on the respective ordination axes returned by scores.envfit.

Author(s)

Gavin L. Simpson

Examples

data(varespec, varechem)
ord <- metaMDS(varespec)
fit <- envfit(ord, varechem, perm = 199)

fortify(fit)

data(dune, dune.env)
ord <- cca(dune)
fit <- envfit(ord ~ Moisture + A1, dune.env, perm = 199)

fortify(fit)
data(varespec, varechem)
ord <- metaMDS(varespec)
fit <- envfit(ord, varechem, perm = 199)

fortify(fit)

data(dune, dune.env)
ord <- cca(dune)
fit <- envfit(ord ~ Moisture + A1, dune.env, perm = 199)

fortify(fit)

Tidied species rank abundance data and estimated Fisher's log-series

Description

Prepares a data frame of results from a fisherfit object suitable for plotting with ggplot.

Usage

## S3 method for class 'fisherfit'
fortify(model, data, ...)
## S3 method for class 'fisherfit'
fortify(model, data, ...)

Arguments

`model`	an object of class `fisherfit`
`data`	original data set. Currently ignored.
`...`	other arguments pass to methods. Currently ignored.

Value

A data frame with columns 'Rank' and 'Abundance'. Additionally, Fisher's $\alpha$ and the nuisance parameter are returned as attributes 'alpha' and 'k' respectively.

Author(s)

Gavin L. Simpson

Examples


data(BCI)
mod <- fisherfit(BCI[5,])
head(fortify(mod))
data(BCI)
mod <- fisherfit(BCI[5,])
head(fortify(mod))

Fortify isometric feature mapping results

Description

Prepares fortified versions of results from isomap objects.

Usage

## S3 method for class 'isomap'
fortify(model, data = NULL, axes = 1:6, what = c("sites", "network"), ...)
## S3 method for class 'isomap'
fortify(model, data = NULL, axes = 1:6, what = c("sites", "network"), ...)

Arguments

`model`	an object of class `isomap`.
`data`	data.frame; additonal data to be added to the forified object.
`axes`	numeric; which axes to return. For `what = "network"` this must be of length two only.
`what`	character; what aspect of the results should be fortified? `"sites"` returns to ordination scores from the multidimensional scaling part of the model. `"network"` returns the coordinates for edges joining points.
`...`	additional arguments for other methods. Currently ignored.

Details

Two different objects can be created from the results of an isomap object. The first is the standard scores representation of fortified ordinations in vegan, which results in a wide data frame where rows cotain observations and columne the coordinates of observations on the MDS axes. Because ISOMAP also produces a network or sorts, the coordinates of the edges of the network can also be returned in a tidy format using what = "network".

Value

A data frame. For what = "sites", the data frame contains one variable per dimension of the multidimensional scaling embedding of the dissimilarities. Variables are named "DimX" with "X" being an integer. An adidtional variable is label, containing a label for each observation. For what = "network", the data frame contains four variables cotaining the coordinates in the chosen MDS axes for the start and end points of the network edges.

Author(s)

Gavin L. Simpson

Examples

data(BCI)
dis <- vegdist(BCI)
ord <- isomap(dis, k = 3)

df <- fortify(ord, data = data.frame(Richness = specnumber(BCI)))
net <- fortify(ord, what = "network", axes = 1:2)

ggplot(df, aes(x = Dim1, y = Dim2)) +
    geom_segment(data = net,
                 aes(x = xfrom, y = yfrom,
                     xend = xto, yend = yto),
                 colour = "grey85", size = 0.8) +
    geom_point(aes(size = Richness)) +
    coord_fixed()
data(BCI)
dis <- vegdist(BCI)
ord <- isomap(dis, k = 3)

df <- fortify(ord, data = data.frame(Richness = specnumber(BCI)))
net <- fortify(ord, what = "network", axes = 1:2)

ggplot(df, aes(x = Dim1, y = Dim2)) +
    geom_segment(data = net,
                 aes(x = xfrom, y = yfrom,
                     xend = xto, yend = yto),
                 colour = "grey85", size = 0.8) +
    geom_point(aes(size = Richness)) +
    coord_fixed()

Fortify a `"mataMDS"` object.

Description

Fortifies an object of class "metaMDS" to produce a data frame of the selected axis scores in long format, suitable for plotting with ggplot.

Usage

## S3 method for class 'metaMDS'
fortify(model, data, ...)
## S3 method for class 'metaMDS'
fortify(model, data, ...)

Arguments

`model`	an object of class `"metaMDS"`, the result of a call to `metaMDS`.
`data`	currently ignored.
`...`	additional arguments passed to `scores.metaMDS`. Note you can't use `display`.

Details

TODO

Value

A data frame in long format containing the ordination scores. The first two components are the axis scores.

Author(s)

Gavin L. Simpson

Examples

## load example data
data(dune)

ord <- metaMDS(dune)
head(fortify(ord))
## load example data
data(dune)

ord <- metaMDS(dune)
head(fortify(ord))

Fortify extrapolated species richness of a species pool

Description

Prepares a fortified version of results from vegan::poolaccum() objects.

Usage

## S3 method for class 'poolaccum'
fortify(model, data, alpha = 0.05, ...)
## S3 method for class 'poolaccum'
fortify(model, data, alpha = 0.05, ...)

Arguments

`model`	an object of class `vegan::poolaccum()`.
`data`	original data set. Currently ignored.
`alpha`	level of quantiles for envelopes shown (default 0.05).
`...`	additional arguments passed to `vegan::summary.poolaccum()`, notably `display` to control which indices should be computed.

Value

A data frame with columns index, size, richness, lower, upper, and std_dev, containing the richness index, permutation richness estimator, sample size, upper and lower $1 - \alpha$ quantile interval, and standard deviation of permutation estimates, respectively.

Author(s)

Didzis Elferts & Gavin L. Simpson

Examples

data(BCI)
pool <- poolaccum(BCI)
df <- fortify(pool)

ggplot(df, aes(x = size, y = richness, colour = index)) +
    geom_ribbon(aes(ymin = lower, ymax = upper, x = size, fill = index),
                alpha = 0.3, inherit.aes = FALSE) +
    geom_line() +
    facet_wrap(~ index)
data(BCI)
pool <- poolaccum(BCI)
df <- fortify(pool)

ggplot(df, aes(x = size, y = richness, colour = index)) +
    geom_ribbon(aes(ymin = lower, ymax = upper, x = size, fill = index),
                alpha = 0.3, inherit.aes = FALSE) +
    geom_line() +
    facet_wrap(~ index)

Fortify a `"prc"` object

Description

Fortifies an object of class "prc" to produce a data frame of the selected axis scores in long format, suitable for plotting with ggplot.

Usage

## S3 method for class 'prc'
fortify(model, data, scaling = 3, axis = 1, ...)
## S3 method for class 'prc'
fortify(model, data, scaling = 3, axis = 1, ...)

Arguments

`model`	an object of class `"prc"`, the result of a call to `prc`.
`data`	currently ignored.
`scaling`	the desired scaling. See `scores.cca` for details.
`axis`	numeric; which PRC axis to extract. Default is `axis = 1`, which is the most generally useful choice.
`...`	additional arguments currently ignored.

Details

TODO

Value

A data frame in long format containing the ordination scores. The first three components are the Time, Treatment, and associated Response. The last two components, score and label are an indictor factor and a label for the rows for use in plotting.

Author(s)

Gavin L. Simpson

Tidied species octave abundance data

Description

Prepares a data frame of results from a fisherfit object suitable for plotting with ggplot.

Usage

## S3 method for class 'prestonfit'
fortify(model, data, ...)
## S3 method for class 'prestonfit'
fortify(model, data, ...)

Arguments

`model`	an object of class `prestonfit`
`data`	original data set. Currently ignored.
`...`	other arguments pass to methods. Currently ignored.

Value

A data frame with columns 'Octave' and 'Abundance'.

Author(s)

Gavin L. Simpson

Examples


data(BCI)
pfit <- prestonfit(colSums(BCI))
head(fortify(pfit))
data(BCI)
pfit <- prestonfit(colSums(BCI))
head(fortify(pfit))

Add a biplot arrow layer to an ordiggplot

Description

Add a biplot arrow layer to an ordiggplot

Usage

geom_ordi_arrow(
  score,
  data,
  text = TRUE,
  box = FALSE,
  arrow.params = list(),
  text.params = list(),
  ...
)
geom_ordi_arrow(
  score,
  data,
  text = TRUE,
  box = FALSE,
  arrow.params = list(),
  text.params = list(),
  ...
)

Arguments

`score`	Ordination score to be added to the plot.
`data`	Alternative data to the function that will be used instead of `score`.
`text`	Add text labels to the plot.
`box`	Draw a box behind the text (logical).
`arrow.params`, `text.params`	Parameters to modify arrows or their text labels.
`...`	other arguments passed to `ggplot2::geom_segment()`, `ggplot2::geom_label()`, or `ggplot2::geom_text()`

Crosshair for axes in eigenvector methods

Description

Crosshair for axes in eigenvector methods

Usage

geom_ordi_axis(lty = 3, ...)
geom_ordi_axis(lty = 3, ...)

Arguments

`lty`	Linetype.
`...`	other arguments passed to `ggplot2::geom_hline()` and `ggplot2::geom_vline()`

Add a label layer to an ordiggplot

Description

Add a label layer to an ordiggplot

Usage

geom_ordi_label(score, data, ...)
geom_ordi_label(score, data, ...)

Arguments

`score`	Ordination score to be added to the plot.
`data`	Alternative data to the function that will be used instead of `score`.
`...`	other arguments passed to `ggplot2::geom_label()`

Add a point layer to an ordiggplot

Description

Add a point layer to an ordiggplot

Usage

geom_ordi_point(score, data, ...)
geom_ordi_point(score, data, ...)

Arguments

`score`	Ordination score to be added to the plot.
`data`	Alternative data to the function that will be used instead of `score`.
`...`	other arguments passed to `ggplot2::geom_point()`

Add a text layer to an ordiggplot

Description

Add a text layer to an ordiggplot

Usage

geom_ordi_text(score, data, ...)
geom_ordi_text(score, data, ...)

Arguments

`score`	Ordination score to be added to the plot.
`data`	Alternative data to the function that will be used instead of `score`.
`...`	other arguments passed to `ggplot2::geom_text()`

Extract the names of the dimensions to plot as a character vector

Description

Find the character vector of names for the two dimensions of data to be plotted.

Usage

getDimensionNames(object)
getDimensionNames(object)

Arguments

object

a fortified ordination object.

Value

A length 2 character vector of dimension names.

Author(s)

Gavin L. Simpson

Adds a label layer using one of a set of common geoms

Description

Adds labels to a plot using one of geom_label, geom_text, geom_label_repel or geom_text_repel.

Usage

label_fun(data, geom = c("label", "text", "label_repel", "text_repel"), vars)
label_fun(data, geom = c("label", "text", "label_repel", "text_repel"), vars)

Arguments

`data`	data frame; data set to use for the label layer. Must contain a variable `label` containing the strings to use as labels.
`geom`	character; which geom to use for labelling.
`vars`	character; vector of names of variables to ass to the `x` and `y` aesthetics of the chosen geom.

Author(s)

Gavin L. Simpson

List of layers to draw for a given vegan object

Description

List of layers to draw for a given vegan object

Usage

layer_draw_list(valid, layers = NULL, available = NULL)
layer_draw_list(valid, layers = NULL, available = NULL)

Arguments

`valid`	character; vector of valid layer names
`layers`	character; a vector of layer names for `object` that has already been filtered for validity.
`available`	charecter; what layers are actually available

Create a ggplot Object

Description

Function ordiggplot sets up an ordination graph but draws no result. You can add new graphical elements to this plot with ⁠geom_ordi_*⁠ function of this package, or you can use standard ggplot2 ⁠geom_*⁠ functions and use ggscores as their data argument.

Usage

ordiggplot(model, axes = c(1, 2), arrowmul, ...)

ggscores(score)
ordiggplot(model, axes = c(1, 2), arrowmul, ...)

ggscores(score)

Arguments

`model`	An ordination result object from vegan.
`axes`	Two axes to be plotted
`arrowmul`	Multiplier to arrow length. If missing, the arrow length are adjusted to fit to other scores, but if some score types are not displayed, the arrows may be badly scaled, and manual adjustment can be useful.
`...`	Parameters passed to underlying functions.
`score`	Ordination score to be added to the plot.

Details

The ggvegan package has two contrasting approaches to draw ordination plots. The autoplot functions (e.g. autoplot.rda(), autoplot.cca(), and autoplot.metaMDS) draw a complete plot with one command, but the design is hard-coded in the function. However, you can add new elements to the graph.

In contrast, function ordiggplot() only sets up an ordination plot, and does not draw anything. It allows you to add layers to the plot one by one with full flexibility of the ggplot2 functions. There are some specific functions ⁠geom_ordi_*⁠ functions that are similar as similarly named ⁠geom_*⁠ functions. For these you need to give the type of ordination scores to be added, and in addition, you can give any ⁠geom_*⁠ function arguments to modify the plot. Alternatively, you can use any ggplot2 function and in its data argument use ggscores() function to select the data elements for the function.

The ordiggplot() function extracts results using fortify() functions of this package, and it accepts the arguments of those functions. This allows setting, e.g., the scaling of ordination axes.

Examples

library("vegan")
data(dune, dune.env, varespec, varechem)
m <- cca(dune ~ Management + A1, dune.env)

## use geom_ordi_* functions
ordiggplot(m) + geom_ordi_axis() +
  geom_ordi_point("sites") +
  geom_ordi_text("species", col = "darkblue",
                 mapping = aes(fontface = "italic")) +
  geom_ordi_label("centroids") +
  geom_ordi_arrow("biplot")

## use ggscores + standard geom_* functions
ordiggplot(m, scaling = "sites") +
  geom_point(data = ggscores("sites")) +
  geom_text(data = ggscores("species"),
            mapping = aes(fontface = "italic")) +
  geom_label(data = ggscores("centroids"), fill = "yellow") +
  geom_ordi_arrow("biplot")

## Messy arrow biplot for PCA
m <- rda(dune)
ordiggplot(m) +
  geom_ordi_axis() +
  geom_ordi_point("sites") +
  geom_ordi_arrow("species")

## Fitted vectors, selecting variables with formula
 
m <- metaMDS(varespec, trace = FALSE)
## plot
ordiggplot(m) +
  geom_ordi_point("sites") +
  geom_ordi_arrow("sites", stat = "vectorfit", edata = varechem,
                  formula = ~ N + Ca + Al + Humdepth + pH)

library("vegan")
data(dune, dune.env, varespec, varechem)
m <- cca(dune ~ Management + A1, dune.env)

## use geom_ordi_* functions
ordiggplot(m) + geom_ordi_axis() +
  geom_ordi_point("sites") +
  geom_ordi_text("species", col = "darkblue",
                 mapping = aes(fontface = "italic")) +
  geom_ordi_label("centroids") +
  geom_ordi_arrow("biplot")

## use ggscores + standard geom_* functions
ordiggplot(m, scaling = "sites") +
  geom_point(data = ggscores("sites")) +
  geom_text(data = ggscores("species"),
            mapping = aes(fontface = "italic")) +
  geom_label(data = ggscores("centroids"), fill = "yellow") +
  geom_ordi_arrow("biplot")

## Messy arrow biplot for PCA
m <- rda(dune)
ordiggplot(m) +
  geom_ordi_axis() +
  geom_ordi_point("sites") +
  geom_ordi_arrow("species")

## Fitted vectors, selecting variables with formula
 
m <- metaMDS(varespec, trace = FALSE)
## plot
ordiggplot(m) +
  geom_ordi_point("sites") +
  geom_ordi_arrow("sites", stat = "vectorfit", edata = varechem,
                  formula = ~ N + Ca + Al + Humdepth + pH)

Number of scores

Description

Returns the number of scores returns in object x.

Usage

scoresLength(x)
scoresLength(x)

Arguments

`x`	The object whose number of scores is required.

Value

a numeric vector of length 1 with the number of scores.

Author(s)

Gavin L. Simpson

Add Fitted Vectors to Ordination plots

Description

Fits arrows to show the direction of fastest increase in continuous environmental variables in ordination space.The arrows are scaled relative to their correlation coefficient, and they can be added to an ordination plot with geom_ordi_arrow().

Usage

stat_vectorfit(
  mapping = NULL,
  data = NULL,
  geom = "text",
  position = "identity",
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE,
  edata = NULL,
  formula = NULL,
  arrowmul = NULL,
  ...
)
stat_vectorfit(
  mapping = NULL,
  data = NULL,
  geom = "text",
  position = "identity",
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE,
  edata = NULL,
  formula = NULL,
  arrowmul = NULL,
  ...
)

Arguments

`mapping`	Set of aesthetic mappings created by `aes()`. If specified and `inherit.aes = TRUE` (the default), it is combined with the default mapping at the top level of the plot. You must supply `mapping` if there is no plot mapping.
`data`	The data to be displayed in this layer. There are three options: If `NULL`, the default, the data is inherited from the plot data as specified in the call to `ggplot()`. A `data.frame`, or other object, will override the plot data. All objects will be fortified to produce a data frame. See `fortify()` for which variables will be created. A `function` will be called with a single argument, the plot data. The return value must be a `data.frame`, and will be used as the layer data. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`geom`	The geometric object to use to display the data, either as a `ggproto` `Geom` subclass or as a string naming the geom stripped of the `geom_` prefix (e.g. `"point"` rather than `"geom_point"`)
`position`	Position adjustment, either as a string naming the adjustment (e.g. `"jitter"` to use `position_jitter`), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
`na.rm`	Remove missing values (Not Yet Implemented).
`show.legend`	logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders()`.
`edata`	Environmental data where the continuous variables are found.
`formula`	Formula to select variables from `edata`. If missing, all continuos variables of `edata` are used.
`arrowmul`	Multiplier to arrow length. If missing, the multiplier is selected automatically so that arrows fit the current graph.
`...`	Other arguments passed to the functions.

Examples

library("vegan")

data(mite, mite.env)
m <- metaMDS(mite, trace = FALSE, trymax = 100)

## add fitted vectors for continuous variables
ordiggplot(m) +
  geom_ordi_point("sites") +
  geom_ordi_arrow("sites", stat = "vectorfit", edata = mite.env)

## can be faceted
ordiggplot(m) + geom_ordi_point("sites") +
  geom_ordi_arrow("sites", stat = "vectorfit", edata = mite.env) +
  facet_wrap(mite.env$Topo)
library("vegan")

data(mite, mite.env)
m <- metaMDS(mite, trace = FALSE, trymax = 100)

## add fitted vectors for continuous variables
ordiggplot(m) +
  geom_ordi_point("sites") +
  geom_ordi_arrow("sites", stat = "vectorfit", edata = mite.env)

## can be faceted
ordiggplot(m) + geom_ordi_point("sites") +
  geom_ordi_arrow("sites", stat = "vectorfit", edata = mite.env) +
  facet_wrap(mite.env$Topo)

Valid layers for vegan objects

Description

Valid layers for vegan objects

Usage

valid_layers(object, ...)

## S3 method for class 'rda'
valid_layers(object, ...)

## S3 method for class 'cca'
valid_layers(object, ...)
valid_layers(object, ...)

## S3 method for class 'rda'
valid_layers(object, ...)

## S3 method for class 'cca'
valid_layers(object, ...)

Arguments

`object`	An R object.
`...`	Additional arguments passed to methods.

Package 'ggvegan'

Help Index

Adds species and site score layers to an existing plot

Description

Usage

Arguments

Scale Vectors to Data

Description

Usage

Arguments

Value

Author(s)

ggplot-based plot for objects of class "anosim"

Description

Usage

Arguments

Value

Author(s)

Examples

ggplot-based plot for objects of class "cca"

Description

Usage

Arguments

Details

Value

Author(s)

Examples

ggplot-based plot for objects of class "decorana"

Description

Usage

Arguments

Details

Value

Author(s)

Examples

ggplot-based plot for envfit objects

Description

Usage

Arguments

Value

Author(s)

Examples

Plot Fisher's log-series

Description

Usage

Arguments

Value

Author(s)

Examples

ggplot-based plot for objects of class "isomap"

Description

Usage

Arguments

Value

Author(s)

Examples

ggplot-based plot for objects of class "metaMDS"

Description

Usage

Arguments

Details

Value

Author(s)

Examples

ggplot-based plot for objects of class "poolaccum"

Description

Usage

Arguments

Value

Author(s)

Examples

ggplot-based plot for objects of class "prc"

Description

Usage

Arguments

Details

Value

Author(s)

Examples

Plot Preston's log-normal model of species abundance

ggplot-based plot for objects of class `"anosim"`

ggplot-based plot for objects of class `"cca"`

ggplot-based plot for objects of class `"decorana"`

ggplot-based plot for `envfit` objects

ggplot-based plot for objects of class `"isomap"`

ggplot-based plot for objects of class `"metaMDS"`

ggplot-based plot for objects of class `"poolaccum"`

ggplot-based plot for objects of class `"prc"`

ggplot-based plot for objects of class `'rda'`

Fortify a `"cca"` object.

Fortify a `"decorana"` object.

Fortify method for `envfit` objects

Fortify a `"mataMDS"` object.