Backgrounddata


Longitude and latitude
values, as well as values of four environmental variables (from the Bio-ORACLE dataset;
  Tyberghein et al., 2012) for each of 10,000
background points. The background points were selected randomly along shorelines of all continents in the northern hemisphere.

datasets

Complex niche models show low performance in identifying
the most important range-limiting environmental variables and in
transferring habitat suitability to novel environmental conditions
(Warren and Seifert, 2011; Warren et al., 2014). This package helps to
identify the most important set of uncorrelated variables and to
fine-tune Maxent's regularization multiplier. In combination, this
allows to constrain complexity and increase performance of Maxent niche
models (assessed by information criteria, such as AICc (Akaike, 1974) ,
and by the area under the receiver operating characteristic (AUC)
(Fielding and Bell, 1997). Users of this package should be familiar with
Maxent niche modelling.

Alexander Jueterbock

MaxentVariableSelection

Selecting the Best Set of Relevant Environmental Variables along
with the Optimal Regularization Multiplier for Maxent Niche
Modeling

Backgrounddata function

A data frame that specifies environmental conditions and geographic
  locations of 10,000 background sites.
  <dl>
    <dt><code>species</code></dt><dd>The species name is here set to 'bg', which
      stands for background</dd> <dt><code>longitude</code></dt><dd>longitudinal coordinate</dd> <dt><code>latitude</code></dt><dd>latitudinal coordinate</dd> <dt><code>calcite</code></dt><dd>Mean calcite concentration (mol/m3)</dd> <dt><code>parmean</code></dt><dd>Mean photosynthetically active radiation (Einstein/m2/day)</dd> <dt><code>salinity</code></dt><dd>Mean salinity (PSS)</dd> <dt><code>sstmax</code></dt><dd>Maximum sea surface temperature (degree celsius)</dd> </dl> 

Backgrounddata: CSV file with background/pseudoabsence data

Description

Arguments

Format

References

Examples