taxon.response.sort: Plot Taxa Response Curve and Calculate Species Extirpation...

In leppott/InvertExtirp: Extirpation Analysis for Benthic Macroinvertebrates and Fish

Description

The output of this function to return 1.Weighted Average, 2. cdf_Abundance based, 3. cdf_ presence/absence based; 4. ecdf weighted, 5. cdf weight new; 6. Linear logistic regression, 7. quadratic logistic 8. GAM 5~7 using full data range; 9~11. repeat 6~8 but uses observed range for each single taxon; 12 Count. 13. Raw quantiles. Requires Hmisc for wtd.quantile() and Ecdf() and mgcv to gam().

Usage

taxon.response.sort(df1 = df1, xvar = "Conductivity", cutoff = 25,
  region = "all", mtype = 3, dense.N = 201, plot.pdf = F,
  xlabs = "Specific conductivity (uS/cm)", add.map = FALSE,
  GIS.cord = c("LONG_DD", "LAT_DD"), extirpation = NULL,
  maintext = "Macroinvertebrates response to specific conductivity",
  log.x = TRUE, rounder = 0, taus = c(0, 95, 100), nbin = 61,
  sort.vect = sort.vect, wd = getwd())

Arguments

df1	data frame
cutoff	a required minimum sample size for calculation
region	a subregion code to name the final output files
mtype	could be 1 to 3, indicating which regression model to use; default = 3.
dense.N	is the number of areas to cut into in the calculation of area under the curve
plot.pdf	to decide if we want species vs. env plots options "none", "pdf", "tiff"
add.map	to decide if a map should be added before plots.
maintext	title of the multiplots area
log.x	if xvar should be logtransformated
rounder	xvar rounder, default = 0
taus	determine the output the percentile of env variable
nbin	number of bins for logits
sort.vect	when plot, sort the taxa list according to a vector called file called sort.vec
wd	Working directory for saving files.
xvar.	xvariable, could be column index or name

Value

Output to the screen for each taxon as it is completed. CDF and GAM plots are saved to the specified directory in subfolders ("cdf" and "gam"). 1.Weighted Average, 2. cdf_Abundance based, 3. cdf_ presence/absence based; 4. ecdf weighted, 5. cdf weight new; 6. Linear logistic regression, 7. quadratic logistic 8. GAM 5~7 using full data range; 9~11. repeat 6~8 but uses observed range for each single taxon; 12 Count. 13. Raw quantiles

Examples

switch0 <- 1
ecolab <- ifelse (switch0 ==1, "eco69", "eco70")
unitlab <- expression(paste("SO"[4]^{2-phantom()}," + HCO"[3]^{-phantom()}," (mg/L)"))
full.results <- taxon.response.sort(df1 = df1, xvar = "lgSO4HCO3", cutoff = 25, region = ecolab
, mtype = 3, dense.N = 201, plot.pdf = T, xlabs = unitlab, add.map = F, , maintext = ""
, GIS.cord = c("Long_DD", "Lat_DD"), log.x = TRUE, rounder = 0, taus = c(0,95,100), nbin = 61, sort.vect = taxalist
, wd=getwd())
# view results
View(full.results)

leppott/InvertExtirp documentation built on Nov. 8, 2019, 5:58 p.m.