Prescribed fire is a critical forest management tool across Department of War (DoW) lands in the southeastern U.S., yet uncertainty in how forest change will influence fire behavior limits planning effectiveness. While existing technologies can model forest succession and fire behavior independently, operational tools to integrate these capabilities remain lacking, and key elements such as model parameterization and fire behavior analysis are underdeveloped.

The objective of this project to develop a suite of tools to integrate a widely used forest succession model, Landscape Disturbance and Succession model (LANDIS-II), and a powerful fire behavior model, QUIC-Fire, into a flexible and accessible workflow for assessing fire behavior outcomes in predicted fuels under future weather forecasts. The objectives of this project are to demonstrate and evaluate the following:  

• A tool for creating fully-parameterized LANDIS-II simulations across the southeast U.S. 
• An automated coupling of LANDIS-II and QUIC-Fire to produce three-dimensional (3D) fuel inputs from LANDIS-II outputs.  
• A suite of analytical functions to assess management-relevant fire behavior metrics from QUIC-Fire.   
• The full technology integration workflow in a case study conducted on DoW lands in the Eastern Innovation Landscape Network (EILN). 

Forest succession and fuel changes can be predicted across broad landscapes using LANDIS-II. While the technology is well-established and widely used in long-term research, its operational use in forest planning contexts is limited due to the complex model parameterization process. The first objective for the technical integration workflow is to create a point-and-click application to collate all the data necessary to create a full-parameterized LANDIS-II simulation. Recent work has developed the Rapid Initial Community Builder to parameterize forest inputs; this work will expand on it to include the ability to select from a suite of future Earth Systems Model (ESM) projections, greatly increasing the accessibility of LANDIS-II for adaptive management.

The second technology that will be integrated is QUIC-Fire, a fine-scale yet fast-running model of fire behavior that can be used to improve prescribed fire planning. Recently, the team has completed a method for translating the outputs from LANDIS-II into 3D fuel arrays used by QUIC-Fire. This method would be further generalized and assessed in the second objective of the work, with improvements pertaining to important surface fuels. While some outcomes from QUIC-Fire can be intuitively evaluated, certain metrics that are relevant for fire management plans, such as Rate of Spread, are difficult to calculate from the available outputs.

The third objective is to codify recent efforts by the team to create analytical tools for QUIC-Fire outputs. Both the LANDIS-II output translation and QUIC-Fire analysis tools will be implemented as Python packages. Successful integration of the technologies will be demonstrated by evaluating the functionality and ease of use for each tool in the workflow, as well as in a case study based on DoW lands within the EILN. 

For management in fire-maintained systems, understanding how predicted forest conditions will influence fire behavior is crucial. Forest landscape succession modeling provides an avenue for assessing fuel changes over time and under multiple ESM projections. Together, the technology integration tools would aid in fire management planning by elucidating links between weather conditions and prescribed burning practices or wildland fire risk. Critically, the workflow will be both flexible and easy to use, making it ripe for integration into adaptive planning on DoW lands in the southeast U.S (Anticipated Project Completion - 2027)