information as you go. You must have an internet connection to complete this assignment. To complete this exercise, you will need to install some R packages for working with geospatial data: install.packages(c('dismo','maptools','raster','sp','rgdal','spocc')) Load each of the above required R packages using the function: library() library(dismo) library(maptools) …etc. Set your R working directory to the parent directory of the file folder you ‘usa’ downloaded for this exercise: EXERCISES A. Exploring occurrence records The step in building a species distribution model is collecting data on a species’ occurrence, that is, the specific locations where individuals of the same species have been observed in the wild. Data on thousands of species have been collected and organized in online databases, where data are publically available and freely downloadable. In this exercise, you will query online databases to locate records for a widespread species. First, download occurrence records for painted turtles (Chrysemys picta) using the function in the package (this might take a minute): gbif() dismo dat <- gbif('Chrysemys', 'picta') What does the do? (Hint: use to open the R documentation for gbif()function ?gbif the function in the window.) Help What arguments did you supply to the in order to find records for gbif()function painted turtles? How you use the to find occurrence records for the green sea gbif()function turtle? Run the following line of code to check for georeferenced painted turtle records in other databases: occ(query='Chrysemys picta', from=c('gbif','bison','inat','ebird', 'ecoengine','vertnet'), has_coords=T) How many records did you find? databases could you use to download occurrence records for painted turtles? Why does the eBird database not contain records for painted turtles? Run the for a different species and record the species you chose: occ()function ________________________, the number of georeferenced records you found:
information as you go. You must have an internet connection to complete this assignment. To complete this exercise, you will need to install some R packages for working with geospatial data: install.packages(c('dismo','maptools','raster','sp','rgdal','spocc')) Load each of the above required R packages using the library() function: library(dismo) library(maptools) …etc. Set your R working directory to the parent directory of the ‘usa’ file folder you downloaded for this exercise: EXERCISES A. Exploring occurrence records The step in building a species distribution model is collecting data on a species’ occurrence, that is, the specific locations where individuals of the same species have been observed in the wild. Data on thousands of species have been collected and organized in online databases, where data are publically available and freely downloadable. In this exercise, you will query online databases to locate records for a widespread species. First, download occurrence records for painted turtles (Chrysemys picta) using the gbif() function in the dismo package (this might take a minute): dat <- gbif('Chrysemys', 'picta') What does the gbif()function do? (Hint: use ?gbif to open the R documentation for the function in the Help window.) What arguments did you supply to the gbif()function in order to find records for painted turtles? How you use the gbif()function to find occurrence records for the green sea turtle? Run the following line of code to check for georeferenced painted turtle records in other databases: occ(query='Chrysemys picta', from=c('gbif','bison','inat','ebird', 'ecoengine','vertnet'), has_coords=T) How many records did you find? databases could you use to download occurrence records for painted turtles? Why does the eBird database not contain records for painted turtles? Run the occ()function for a different species and record the species you chose: ________________________, the number of georeferenced records you found:
carter.docx