Title: Linking habitat suitability with a longleaf pine-hardwood model: Building a species-predictive fire-land management framework

Abstract

Active management of fire-dependent ecosystems for specific species leads to complex tradeoffs, which affect conservation outcomes to other species. Therefore a multi-species evaluation of management actions is required. Habitat Suitability Models (HSMs) can help in predicting the likelihood of species occurrence using corresponding environmental variables and empirical relationships that link occurrence with specific environmental conditions. Incorporating multiple species into HSMs and relating them to habitat dynamics is crucial for ecosystems that require active management with prescribed fire. To address this issue, we developed multi-species HSM driven within an existing population model of the longleaf pine-hardwood ecosystem to assess the suitability of an ecosystem given different fire management strategies and environmental conditions. The population model used in this study provides spatial and temporal changes of longleaf pine-hardwood habitat structure in response to fire. These habitat values are used by the HSM to calculate habitat suitability for three threatened and endangered faunal species of this ecosystem, which all thrive with frequent fire, but have unique habitat requirements. Transient habitat conditions are traced to predict longleaf pine ecosystem trajectories under various management strategies, thereby evaluating current land management actions, such as thinning or prescribed fire frequencies. We tested a suite of environmental conditionsmore » to emphasize the sensitivity of the species to different fire management actions. The results of our modeling suggest that maximum suitable habitat for all three species can be achieved with fire frequency occurring at approximately once every three years. The modeling results support current management actions and provide a new habitat assessment tool that incorporates ecological factors for multiple species, thus providing for habitat optimization.« less

Authors:

Jafarov, Elchin E. ^[1]; Loudermilk, Louise E. ^[2]; Hiers, Kevin J. ^[3]; Williams, Brett ^[4]; Linn, Rodman  ^[1];

• Search DOE PAGES for author "Linn, Rodman"
• Search DOE PAGES for ORCID "0000-0002-5746-4880"

Jones, Chas ^[5]; Hill, Samantha C. ^[6]; Atchley, Adam L.  ^[1]

• Search DOE PAGES for author "Atchley, Adam L."
• Search DOE PAGES for ORCID "0000-0003-2203-1994"

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+ Show Author Affiliations

1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2. USDA Forest Service, Southern Research Station, Athens, GA (United States). Center for Forest Health and Disturbance
3. Tall Timbers Research Station, Tallahassee, FL (United States)
4. Eglin AFB, FL (United States). Air Force Wildland Fire Branch
5. Affiliated Tribes of Northwest Indians, Corvallis, OR (United States)
6. Univ. of Utah, Salt Lake City, UT (United States)

Publication Date:

Sat Dec 11 00:00:00 EST 2021

Research Org.:

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Org.:

U.S. Department of Defense (DOD). Strategic Environmental Research and Development Program; USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:

1739941

Report Number(s):

LA-UR-20-20178
Journal ID: ISSN 0304-3800

Grant/Contract Number:  

89233218CNA000001; RC18–1346; RC-2643

Resource Type:

Accepted Manuscript

Journal Name:

Ecological Modelling

Additional Journal Information:

Journal Volume: 440; Journal ID: ISSN 0304-3800

Publisher:

Elsevier

Country of Publication:

United States

Language:

English

Subject:

54 ENVIRONMENTAL SCIENCES; Computer science; Earth sciences; habitat suitability model, longleaf pine, hardwood, fire management