SYMPOSIA PAPER Published: 01 January 2004

Quantitative Habitat Analysis: A New Tool for the Integration of Modeling, Planning, and Management of Natural Resources


Federal laboratories are often caught between the need to meet mission objectives and the mandate to act as national stewards for natural resources. Following the initiation of the Manhattan Project in 1943, restricted land use at Los Alamos National Laboratory (LANL) retained many undisturbed areas that function as ecosystem sanctuaries for plants and animals throughout the 43 mi2 site. We developed a Quantitative Habitat Analysis (QHA) that enables both managers and scientists to better meet the goals of ecosystem management and sustainable development for LANL. QHA is a multi-faceted modeling, planning, and management tool with the goal of applying existing models in a new way. QHA provides an objective, standardized, and replicable system for management of wild areas by federal agencies. As part of the development of QHA, we reviewed 42 existing wildlife and habitat models, assessments, or evaluation methods and 12 computer programs. A pilot field study was conducted on 12 plots testing five different methods to determine the most suitable for data collection for the tool. Once methods were selected and models determined, a QHA application tool was created in ArcView to test the pilot data within the tool for user-friendly application. This year, 45 field sites were sampled. QHA currently comprises five main sub-models analyzed within a geographic information system using ArcView: 1) Ecological Land Classification (landscape level effects), 2) Rapid Ecological Assessment (general assessment)/U.S. National Vegetation Classification Element Occurrence (ecosystem “health”), 3) BEHAVE (wildfire and fuels monitoring), 4) Habitat Analysis and Modeling System (wildlife), and 5) ECORSK.6 (bio-contaminants). Key to this QHA tool was the use of “common currencies.” The common currencies consist of weighted scores that calculate a “grade” or means of comparison between different programs and scoring methods. Development and calibration of the QHA continues.

Author Information

Marsh, LK
Los Alamos National Laboratory, Los Alamos, NM
Haarmann, T
Los Alamos National Laboratory, Los Alamos, NM
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Developed by Committee: E47
Pages: 94–106
DOI: 10.1520/STP11945S
ISBN-EB: 978-0-8031-5501-5
ISBN-13: 978-0-8031-3476-8