ecotraj (version 1.1.1)

trajectoryPlot: Trajectory plots

Description

Set of plotting functions for Ecological Trajectory Analysis:

Usage

trajectoryPCoA(
  x,
  traj.colors = NULL,
  axes = c(1, 2),
  survey.labels = FALSE,
  time.labels = FALSE,
  ...
)
trajectoryPlot(
  coords,
  sites,
  surveys = NULL,
  times = NULL,
  traj.colors = NULL,
  axes = c(1, 2),
  survey.labels = FALSE,
  time.labels = FALSE,
  ...
)

Value

Function trajectoryPCoA returns the result of calling cmdscale.

Arguments

x

An object of class trajectories.

traj.colors

A vector of colors (one per site). If selection != NULL the length of the color vector should be equal to the number of sites selected.

axes

The pair of principal coordinates to be plotted.

survey.labels

A boolean flag to indicate whether surveys should be added as text next to arrow endpoints

time.labels

A boolean flag to indicate whether times should be added as text next to arrow endpoints

...

Additional parameters for function arrows.

coords

A data.frame or matrix where rows are ecological states and columns are coordinates in an arbitrary space

sites

A vector indicating the site corresponding to each ecological state.

surveys

A vector indicating the survey corresponding to each ecological state (only necessary when surveys are not in order).

times

A numeric vector indicating survey times.

Author

Miquel De Cáceres, CREAF

Anthony Sturbois, Vivarmor nature, Réserve Naturelle nationale de la Baie de Saint-Brieuc

Details

• Function trajectoryPCoA performs principal coordinates analysis (cmdscale) and draws trajectories in the ordination scatterplot.

• Function trajectoryPlot draws trajectories in a scatter plot corresponding to the input coordinates.

References

De Cáceres M, Coll L, Legendre P, Allen RB, Wiser SK, Fortin MJ, Condit R & Hubbell S. (2019). Trajectory analysis in community ecology. Ecological Monographs 89, e01350.

See Also

trajectoryMetrics, transformTrajectories, cmdscale, cyclePCoA

Examples

#Description of sites and surveys
sites <- c("1","1","1","2","2","2")
surveys <- c(1,2,3,1,2,3)
  
#Raw data table
xy<-matrix(0, nrow=6, ncol=2)
xy[2,2]<-1
xy[3,2]<-2
xy[4:6,1] <- 0.5
xy[4:6,2] <- xy[1:3,2]
xy[6,1]<-1

#Define trajectory data
x <- defineTrajectories(dist(xy), sites, surveys)
  
#Draw trajectories using original coordinates
trajectoryPlot(xy, sites, surveys, 
               traj.colors = c("black","red"), lwd = 2)

#Draw trajectories in a PCoA
trajectoryPCoA(x, 
               traj.colors = c("black","red"), lwd = 2)   
  
#Should give the same results if surveys are not in order 
#(here we switch surveys for site 2)
temp <- xy[5,]
xy[5,] <- xy[6,]
xy[6,] <- temp
surveys[5] <- 3
surveys[6] <- 2
  
trajectoryPlot(xy, sites, surveys, 
               traj.colors = c("black","red"), lwd = 2)   
 
x <- defineTrajectories(dist(xy), sites, surveys)
trajectoryPCoA(x, 
               traj.colors = c("black","red"), lwd = 2)