View source: R/mastifFunctions.R
mastMap | R Documentation |
Maps dispersal data (trees and seed traps) with predictions.
mastMap(mapList)
mapList |
|
Generates of map of seed traps and trees, with symbols scaled to the sizes relative to seed counts in sdata$seedNames
and treeSymbol
. Sizes are adjusted with scaleTree
and scaleTrap
.
If PREDICT = TRUE
, then predictions come in the object fitted in mastif
with predictList
used to specify prediction plots and years. See the help page for mastif
.
More detailed vignettes can be obtained with:
browseVignettes('mastif')
Only graphical outputs.
James S Clark, jimclark@duke.edu
Clark, J.S., C. Nunes, and B. Tomasek. 2019. Foodwebs based on unreliable foundations: spatio-temporal masting merged with consumer movement, storage, and diet. Ecological Monographs, e01381.
mastSim
simulates data
A more detailed vignette is can be obtained with:
browseVignettes('mastif')
website 'http://sites.nicholas.duke.edu/clarklab/code/'.
# simulate data (see \link{\code{mastSim}}) seedNames <- specNames <- 'acerRubr' sim <- list(nyr=10, ntree=30, nplot=5, specNames = specNames, seedNames = seedNames) inputs <- mastSim(sim) inputs$mapPlot <- 'p1' inputs$mapYears = inputs$years[1] mastMap( inputs ) # for Pinus d <- "https://github.com/jimclarkatduke/mast/blob/master/pinusExample.rdata?raw=True" repmis::source_data(d) specNames <- c("pinuEchi","pinuRigi","pinuStro","pinuTaed","pinuVirg") seedNames <- c(specNames, "pinuUNKN") mapList <- list( treeData = treeData, seedData = seedData, specNames = specNames, seedNames = seedNames, xytree = xytree, xytrap = xytrap, mapPlot = 'DUKE_BW', mapYears = c(2004:2007), treeScale = .5, trapScale=1.2, plotScale = 1.2, LEGEND=TRUE) mastMap(mapList)
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