mapr introduction

Leaflet.js

Leaflet JS is an open source mapping library that can leverage various layers from multiple sources. Using the leaflet library, we can generate a local interactive map of species occurrence data.

An example:

spp <- c('Danaus plexippus','Accipiter striatus','Pinus contorta')
dat <- occ(query = spp, from = 'gbif', has_coords = TRUE, limit = 100)
map_leaflet(dat)

leaflet

Geojson map as a Github gist

You can also create interactive maps via the mapgist function. You have to have a Github account to use this function. Github accounts are free though, and great for versioning and collaborating on code or papers. When you run the map_gist function it will ask for your Github username and password. You can alternatively store those in your .Rprofile file by adding entries for username (options(github.username = 'username')) and password (options(github.password = 'password')).

spp <- c('Danaus plexippus', 'Accipiter striatus', 'Pinus contorta')
dat <- occ(query = spp, from = 'gbif', has_coords = TRUE, limit = 100)
dat <- fixnames(dat)
map_gist(dat, color = c("#976AAE", "#6B944D", "#BD5945"))

gist

base plots

Base plots, or the built in plotting facility in R accessed via plot(), is quite fast, but not easy or efficient to use, but are good for a quick glance at some data.

spnames <- c('Accipiter striatus', 'Setophaga caerulescens', 'Spinus tristis')
out <- occ(query = spnames, from = 'gbif', has_coords = TRUE, limit = 100)
map_plot(out, size = 1, pch = 10)

plot of chunk unnamed-chunk-5

ggplot2

ggplot2 is a powerful package for making visualizations in R. Read more about it here.

dat <- occ(query = 'Lynx rufus californicus', from = 'gbif', has_coords = TRUE, limit = 200)
map_ggplot(dat, map = "usa")

plot of chunk unnamed-chunk-6

via dismo

if that’s your jam, though you might find rgbif easier

library("dismo")
g <- gbif('Batrachoseps', 'luciae', geo = TRUE, end = 300)
map_leaflet(g, lon = "lon", lat = "lat", name = "scientificName")

dismomap