In leppott/BioMonTools: Tools for Biomonitoring and Bioassessment

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Purpose

To create taxa distribution maps.

Usage

Map taxonomic observations from a data frame. Input a dataframe with SampID , TaxaID, TaxaCount, Latitude, and Longitude. Other arguments are format (jpg vs. pdf), file name prefix, and output directory. Files are saved with the prefix "map.taxa." by default.

Uses the maps package map function.

For maps package map function need database (usa, state, county) and regions (e.g., maryland). Additional map function arguments can be passed through the MapTaxaObs function.

Example, Data

Data used should have Sample Identifier, Taxa Identifier, Taxa Count (can be 1 for all), Latitude/Longitude (decimal degrees).

# Packages
#library(BioMonTools)
#library(knitr)
# Data
df_obs <- BioMonTools::data_Taxa_MA
# Show
knitr::kable(head(df_obs))

Example, ggplot

The ggplot2 package can be used to create single maps that are returned to the console for further editing.

# Packages
#library(BioMonTools)
#library(ggplot2)
#library(knitr)

#
df_obs <- BioMonTools::data_Taxa_MA

TaxaID <- "TaxaName"
TaxaCount <- "Count"
Lat <- "Latitude"
Long <- "Longitude"

myTaxa <- "ALEWIFE, ADULTS, 0.5-25 ppt"

df_map <- subset(df_obs, df_obs[, TaxaID] == myTaxa)

myDB <- "state"
myRegion <- "massachusetts"

Lat <- "Latitude"
Long <- "Longitude"

# Base Map
m1 <- ggplot2::ggplot(data=subset(ggplot2::map_data(myDB)
                                  , region %in% c(myRegion))) + 
          ggplot2::geom_polygon(ggplot2::aes(x = long
                                    , y = lat
                                    , group = group)
                                , fill = "light gray",
                                color = "black") + 
          ggplot2::coord_fixed(1.3) + 
          ggplot2::theme_void()
# Add points (all)
m1 <- m1 + ggplot2::geom_point(data=df_obs
                               , ggplot2::aes(df_obs[, Long]
                                              , df_obs[, Lat])
                               , fill=NA
                               , color="gray")
# Add points (Taxa)
m1 <- m1 + ggplot2::geom_point(data=df_map
                               , ggplot2::aes(df_map[,Long]
                                              , df_map[,Lat])
                               , color="blue")
# Map Title (center)
m1 <- m1 + 
  ggplot2::labs(title = myTaxa) +
  ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5))
# Caption (left justified)
m1 <- m1 + ggplot2::labs(caption = "caption1 \n caption2") + 
  ggplot2::theme(plot.caption = ggplot2::element_text(hjust = 0))

# Show Results
knitr::kable(head(df_obs))
m1

Example, PDF

The example below will create a PDF with one map per page.

df_obs <- data_Taxa_MA
SampID <- "estuary"
TaxaID <- "TaxaName"
TaxaCount <- "Count"
Lat <- "Latitude"
Long <- "Longitude"
output_dir <- getwd()
output_prefix <- "maps.taxa."
output_type <- "pdf"

myDB <- "state"
myRegion <- "massachusetts"
myXlim     <- c(-(73 + (30/60)), -(69 + (56/60)))
myYlim     <- c((41 + (14/60)), (42 + (53/60)))

# Run function with extra arguments for map
BioMonTools::MapTaxaObs(df_obs, SampID, TaxaID, TaxaCount, Lat, Long
                        , output_dir, output_prefix, output_type
                        , database="state", regions="massachusetts"
                        , xlim=myXlim, ylim=myYlim)