A Spatially Explicit Model of Red Imported Fire Ant Behavior for Managing Species at Risk on Military Lands

Abstract

Cave cricket populations are essential to the survival of many rare invertebrates that are endemic to the karst regions of Fort Hood, TX. These crickets bring organic matter into the caves, where it serves as an energy source for a variety of karst invertebrates. At Fort Hood, Red Imported Fire Ants (RIFA) migrating from South America into the southern United States prey upon cave crickets, which potentially threatens some populations of rare invertebrates. Observational studies have documented this risk, and Fort Hood wildlife biologists are actively managing fire ant mounds located near caves in order to protect karst invertebrates. This report outlines a method for developing a simple, localized computer model that can be used as a cost-effective tool in proactive cave management activities. The model developed in this study combines the expertise of natural resources personnel, information from field studies, and digital mapping data to create a spatially explicit model of RIFA behavior as relates to cricket populations. The model was developed using the public domain NetLogo modeling program and did not require the intervention of a computer programmer. Ecologists and biologists need no computer expertise to develop NetLogo models, and the results are transparent enough to be understood by other technical peers with no computer expertise.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2009
Accession Number
ADA505312

Entities

People

  • Bart Rossmann
  • James Westervelt
  • John E. Drake
  • Tim Peterson

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computers
  • Ecological And Environmental Processes
  • Endangered Species
  • Engineering
  • Engineers
  • Environment
  • Habitats
  • Hot Water
  • Invertebrates
  • Management Personnel
  • Medical Personnel
  • Natural Resources
  • Payload
  • South America
  • United States
  • Water Purification
  • Wildlife

Fields of Study

  • Environmental science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Aquatic Ecology
  • Archaeological Resource Survey