Developing Ecological Forecasting Models

Research Task: 8327CMC.1.0
Task Manager: Catherine Jarnevich

High-performance modeling and use of space-based observations are essential elements of the Nation’s emerging assault on invasive plants, animals, and disease organisms. As a part of this effort, and in cooperation with Colorado State University and others, FORT scientists developed the Global Organism Detection and Monitoring system (www.niiss.org). This Web-based data management system features online spatial modeling tools to assist DOI land managers and others with management decisions and activities related to invasive species. FORT also recently created an “Advanced Invasive Species Modeling Room,” where scientists are exploring the latest in predictive modeling techniques, including which techniques work better with different datasets, taxa, and spatial extents and resolutions. Predictive models developed at FORT using the modeling room are being used to create on-demand, regional and national-scale assessments of invasion patterns, vulnerable habitats, potential distributions of specific invaders, and how all of these may be affected by changing climate. For example, researchers developed a model using current climate conditions that identifies suitable habitat for the invasive kudzu vine in the southeastern United States. They then applied the model to future climate conditions, creating predictions for where populations might decrease, be stable, or increase in the future. Both GODM and the Advanced Modeling Room provide the means for delivering advanced decision-support capabilities that can be used in a wide range of management applications. These systems have successfully been tested in wildlife refuges, national parks, and in research areas of other USGS scientists. Species tested have included weeds like dalmation toadflax and leafy spurge, tamarisk, the invasive diatom Didymosphenia geminata, Burmese pythons, the problematic rodent nutria, and the avian disease Salmonella.

 For more information contact Catherine Jarnevich

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