The goal of the naturaList package is providing tools for checking the identification reliability in species occurrence datasets. The main functionality of the naturaList package is providing an automated way to identify for the taxon of interest, which records has the most reliable level of classification, i.e, those records identified by specialists. In addition other characteristics of the records could be used to derive up to six levels of confidence.
You can install the package from CRAN:
install.packages("naturaList")
Or install the latest released development version from github using:
install.packages("devtools")
devtools::install_github("avrodrigues/naturaList")
The package allows to classify the occurrence records in confidence levels through the function classify_occ()
, that comprises the main function of naturaList package. The most reliable identification of a specimen is made by a specialist in the taxa. The other levels are derived from information contained in the occurrence dataset. The default order of confidence levels used in classification process are:
The user can alter this order, depending on his/her objectives, except for the Level 1 that is always a species determined by a specialist.
An extensive explanation of all the features of naturaList package is provided through vignette articles. To conduct a basic classification process through classify_occ
function the user must provide only two data frames. The first containing the occurrence records and the second with a list of specialists. The classify_occ()
function add a new column in the occurrences dataset named naturaList_levels
, which contains the classification.
library(naturaList)
data("A.setosa")
data("speciaLists")
occ.cl <- classify_occ(A.setosa, speciaLists)
Naturalist also offer an interactive module that allows to visualize occurrence in space, get information by pointing the occurrence of interest and manually edit occurrence records by point and click. This interactive module is activate through function map_module
. An article explaining all features of map_module
function can be accessed in this article
Auxiliary functions that allows the user to access the effects of filtering procedures based on classification levels are clean_eval
and grid_filter
functions. A complete example of the usage of these functions can be found in this article.
See vignette for all articles describing the functionalities of naturaList package.