NicheToolBox

In this tutorial I show how the application works. The application was developed for GSOC 2016

Installation

Go to the github repo of the project nichetoolbox repo.

Then copy and run the installation instructions in R:

if (!require('devtools')) install.packages('devtools')
devtools::install_github('luismurao/nichetoolbox')

Launching the app

library(nichetoolbox)
run_nichetoolbox()

First look

The AppSettings section

In this section you need to specify the folder that contains the niche layers that you will use for the modeling process, as well as the folder where you will save your workflow.

Loading niche layers

On the left panel go to Niche layers section and select the folder where your niche raster layers are. Remeber that they need to have the same spatial extent and resolution (raster formats accepted: .asc, .bil, .sdat, .rst, .nc, .tif, .envi, .img).

Press the Load niche layers button and wait. In a few seconds appears a plot showing one of the layers contained in the folder

Workflow

To get track of your work in NicheToolBoox, you need to specify the folder where you want to save your analysis, data, maps etc. Go to Workflow section and select the folder.

The Data section

Now, we are ready to work with NicheToolBoox. First, we need some georeferenced records of the species we want to model. NicheToolBoox can work with two source of longitude/ latitude data: a) GBIF records, which you can search, download and clean GBIF records, b) you can upload and clean your own occurrence data from a local file.

Seaching GBIF records

Go to Data -> GBIF data. Enter species genus, species name where corresponds and optinonally specify the number of records that you want to search (occ search limit). Press Search GBIF button and wait. If the species is in the GBIF portal a data table will be displayed, if the species is not in GBIF, it will display the following menssage: No ocurrences found

In the example we searched for the species Ambystoma tigrinum which generated 480 records.

GBIF data cleaning

You can remove duplicate records using a separation distance in decimimal degrees (the default is 0). For Ambystoma tigrinum I had 480 records before cleaning, and after clicking Clean duplicates with a XX distance it remained 154, so there were 326 duplicate records!!!

Clean duplicates by group

Suppose that your species has a huge geographic range and you want to work only with the records that match certain criteria, for example records that lie within Canada. You can curate duplicate records using a grouping variable; in this example the grouping variable must be country. Go to Clean duplicates by group section and select the grouping variable in this case country, then select the country (Canada) and click Clean duplicates by group.

From 154 records only 2 are in Canada.

GBIF visualizations

The GBIF dataset has some fields that can be used to get some exciting visualizations, particulary fields related to observation date (year, month, day) and country. In Data -> GBIF data -> GBIF visualizations tab you can play with interactive plots, create animated visualizations and display a calendar of the reported records by year.

User data

You can use and clean your own latitude and longitude data for the modeling process. Go to Data -> User data and upload your data. The data cleaning process is exactly the same as the GBIF data.