New habitat classification tool

Habitat models have important roles in the conservation of wildlife and plants including species that are listed as threatened or endangered. For example, models are used to predict where a species is likely to occur, evaluate threats to species viability, and establish conservation goals and priorities. Common limitations of models include limited accessibility of software, instability of results, and outputs that are difficult to interpret.

NCASI has developed a new habitat model—the NCASI Relative Frequency Function Tool. The model is simple to use, does not require a large sample size, does not require absence data, and produces results that are easily interpretable and easily exported to other software.

The Relative Frequency Function (RFF) algorithm used in the NCASI software compares the relative frequencies of a species’ sample points to that of random points or absence points on the landscape to compute a frequency ratio. In tests with artificial and actual data describing species habitat use and geographic distribution, the RFF method in all cases gave results comparable to other methods tested. The RFF method is particularly well-suited to irregularly shaped distributions and can classify sample points even when the data contain missing values.

Free software is available at along with a hyperlink to a recent paper by Dr. Craig Loehle of NCASI describing the modeling approach. The paper, currently available online in an “early view” version, will appear in Volume 35 of the journal Ecography.

Contact information