Days of Our Ocelot: Finding an Elusive Cat‰Ûªs Habitat in North Mexico

EarthzineDEVELOP 2015 Fall VPS, DEVELOP Virtual Poster Session, Forecasting Wetland Cover and Species Habitat, Original

This is a part of the 2015 Fall VPS. For more VPS articles, click here

Habitat Probability Map created using Fuzzy Logic to show areas likely to be inhabited by ocelots. Image Credit: North Mexico Ecological Forecasting Team

Habitat Probability Map created using Fuzzy Logic to show areas likely to be inhabited by ocelots. Image Credit: North Mexico Ecological Forecasting Team

Category:åÊForecasting Wetland Cover and Species Habitat

Project Team: North Mexico Ecological Forecasting

Team Location: NASA Marshall Space Flight Center ‰ÛÒ Huntsville, Alabama

Authors:

Ryan Schick

Padraic Conner

Maggi Klug

Leigh Sinclair

Mentors/Advisors:

Dr. Jeffrey Luvall (NASA at the National Space Science Technology Center)

Dr. Robert Griffin (University of Alabama in Huntsville)

Abstract:

Ocelots (Leopardus pardalis) are medium-sized wild cats that have a distribution reaching from Argentina to the southwestern portion of the United States (U.S.). Although the ocelot is one of the most abundant wild cats throughout most of its range, the population in the U.S. is less than 100 and is protected under the Endangered Species Act. This ocelot population is separated from the main population by the U.S.-Mexico border and is facing a loss of habitat due to anthropogenic disturbance. Because of this separation, the U.S. population is now showing signs of inbreeding, which causes health issues and decreases the chance of survival. The U.S. Fish and Wildlife Service, along with other partners, are preparing to translocate ocelots from Mexico to the United States to bolster the gene pool of the U.S. population. This project aided in this goal by using remotely sensed data to delineate suitable habitat areas and examine where ocelots are most likely to be found in northeastern Mexico. Landsat 5 and 8 were used to create supervised land cover classifications for 1996, 2004, and 2014 to assess temporal changes. Suomi National Polar-orbiting Partnership (NPP) was used to derive Normalized Difference Vegetation Index (NDVI) for use in the MaxEnt model and to verify land cover classifications. Shuttle Radar Topography Mission (SRTM) v2 data was used to create digital elevation models. The land cover and elevation data, along with presence data and environmental variables, were analyzed by the Princeton Maximum Entropy model and the ‰ÛÏFuzzy Logic‰Û tool to identify suitable ocelot habitat.

Previous Story / Next Story