Development of Adaptive Management Tools to Guide Habitat Allocations for At-Risk Species

Abstract

The Department of Defense is increasingly engaging landowners outside installation boundaries to help protect biodiversity at a landscape scale. Such activities include the acquisition of recovery habitat for species at risk and cooperation with conservation partners. The objectives of this project were to 1) contrast the ability of data provided by different conservation partners to reduce uncertainty in dynamic landscape simulation models (i.e., individual-based, spatially explicit population models, IB-SEPMs); 2) apply Decision Analysis to identify the most cost-effective allocation of habitat, given uncertainty in the IB-SEPM; and 3) contrast the ability of the technique to be applied to well-studied (i.e., red-cockaded woodpecker) and poorly-studied (gopher tortoise) species. The study found that the natural history of the red-cockaded woodpecker was sufficiently understood to prioritize habitat allocations to protect the abundance of the species but not to protect genetic diversity of the species. In contrast, for the gopher tortoise this study concluded that we do not sufficiently understand the species natural history traits to protect either abundance or genetic diversity. The methods developed here provide an approach for managing habitat area and connectivity that includes uncertainty regarding species natural history, helps to prioritize collection of monitoring data, and supports cost-effective decision making.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2014
Accession Number
ADA602238

Entities

People

  • Douglas J. Bruggeman
  • Michael E Jones

Organizations

  • Michigan State University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Agent-Based Simulations
  • Animals
  • Birds
  • Computational Science
  • Data Mining
  • Databases
  • Forests
  • Genetic Structures
  • Genetic Variation
  • Genetics
  • Habitats
  • Information Science
  • Medical Personnel
  • Monte Carlo Method
  • Surveys
  • Wildlife
  • Wildlife Management

Fields of Study

  • Environmental science

Readers

  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Wetland-Land-Environmental Management.

Technology Areas

  • Biotechnology