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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