Predicted distribution of wavyleaf basketgrass in Maryland and surrounding states. Areas most suitable for the grass are indicated by warm colors and areas less suitable are indicated by cool colors. White markers represent input presence points. Source: Maryland Department of Natural Resources and DEVELOP
Authors: Christine Suss, Chad Hawkins
Advisor/Science Mentor: Dr. John L. Schnase
Abstract: In the summer of 2010, a DEVELOP team used NASA’s Invasive Species Forecasting System (ISFS) to create a predictive habitat suitability map for wavyleaf basketgrass (Oplismenus hirtellus). This map showed habitats potentially vulnerable to invasion by wavyleaf basketgrass (WLBG), knowledge which could help natural resource managers hone their survey efforts for early detection of new invasions. The ISFS performs a stepwise logistic regression statistical analysis utilizing satellite data products to obtain information about relevant environmental predictors. The team also produced a second map product using an alternate model, MaxEnt, which performed a maximum entropy statistical analysis across the same set of satellite data layers using only WLBG presence points. It was concluded that the MaxEnt approach was better suited for the needs of the Maryland Department of Natural Resources’ Wildlife and Heritage Service (WHS). This project will build on the successful summer 2010 project. Input into the MaxEnt model will be a combination of in-situ presence points and covariates (environmental predictors) comprised of environmental data and NASA Earth observation data that are ecologically relevant to the grass. MaxEnt will produce a list of top covariate contributors and create habitat suitability maps to predict its potential distribution. Later work on the project will involve integrating MaxEnt into the ISFS framework for further use by the WHS. This will help the WHS in its management of wavyleaf basketgrass.
Video transcript available here.