Fire Science – CAFES

Fire Science – CAFES

Fire Science at the New Mexico Consortium includes the work of the Center for Applied Fire and Ecosystem Science. The mission of Center for Applied Fire and Ecosystem Science is to advance next generation tools, technologies, and science in support of ecosystems, conservation, and cultural resource management and research. They draw from expertise in fire behavior and ecosystem process modeling, field-based conservation and wildlife studies, quantitative fire archaeology and fire effects, paleo-fire studies, advanced fuels mapping, and remote sensing. Center scientists work closely with federal, tribal, and academic partners to develop tools and science to inform conservation and management of cultural and natural resources across the US.

For more information see the Center for Applied Fire and Ecosystem Science (CAFES) webpage

RELATED PROJECTS

Cultural Resource Detection using Light Detection and Ranging (LiDAR) for Management during Pre-planning in Timber and Fire Activities

Project lead: Grant Snitker, NMC Research Scientist
Other NMC Scientists: Claudine Gravel-Miguel, NMC Research Scientist
Other Partners: USDA Forest Service, Kisatchie National Forest

NMC scientists are working with USDA Forest Service and US Fish and Wildlife Service partners to collect and process point-cloud data for the Kisatchie National Forest. Additionally, we are using machine-learning approaches to enhance feature detection tools for site identification, predictive models, and cultural resource management. This project is sponsored by the USDA Forest Service. 

Advancing LiDAR-based natural and cultural resource management applications

Project lead(s): Scott Pokswinski and Grant Snitker, NMC Research Scientists
Other Scientists: Matt Snider, NMC Research Scientist
Other Partners: US Fish and Wildlife Service

This project applies vegetation measured through LiDAR as inputs for QUIC-Fire on USFWS priority landscapes across the SE US to evaluate prescriptions used to treat fuels for desired outcomes. The use of lidar before and after fire will provide an ideal monitoring of model performance at management scales. Additionally, NMC scientists are developing additional LiDAR feature detection workflow for archaeological sites on the same priority landscapes. Using existing cultural resource databases/datasets and new targeted archeological surface surveys, we will validate detection results and provide additional assistance in integrating this work into existing cultural resource management planning procedures for the USFWS. This project is sponsored by US Fish and Wildlife Service under the US Department of the Interior. 

Advanced Integrated Fire Science Support

Project Manager: Rachel Loehman, USGS, NMC Affiliate 
PI: Grant Snitker, NMC Research Scientist
Other Scientists: Alex Masarie, NMC Fire Science Programmer, Audrey Wilson, NMC Research Scientist
Other Partners: US Geological Survey

The overarching research goals of the project are to develop data collection methods, data sets, analytical and modeling frameworks, and applied tools to enhance understanding of the relationship of land cover, the pre-fire environment, fire behavior, and fire characteristics with resulting transient or persistent shifts in plant communities and their distributions, altered wildlife habitat, loss of ecosystem services, and alteration, loss, or damage to cultural resources and traditional landscapes. Resulting products, tools, and information will provide support for federal, state, tribal, and local resource managers and other identified stakeholder groups invested in land management and conservation, and will support land management decisions related to pre-fire risk mitigation and fuels treatments, fire operations, resource management and conservation, and post-fire assessments and predictions of ecosystem impacts, resilience, and recovery. This project is sponsored by USGS.

NSF Convergence Accelerator – Track D: Artificial Intelligence and Community Driven Wildland Fire Innovation via a WIFIRE Commons Infrastructure for Data and Model Sharing

Project lead(s): Rod Linn, Scott Pokswinski
Other NMC Scientists: Rachel Loehman, Grant Snitker, Alex Masarie, Audrey Wilson
Other Partners: US Geological Survey, US Fish and Wildlife Service, USDA Forest Service, Department of Defense

WIFIRE Commons will integrate three existing technologies, WIFIRE, MINT and QUIC-Fire as part of this Phase 1 Project to show the promise of using AI to enhance a comprehensive data framework to run next generation coupled-fire-atmospheric modeling for fire planning, risk management, and ecosystem resilience. Through QUIC’s plume tracking function, smoke transport can be assessed as a function of ignition patterns and injection heights accurately modeled for hand off to long distance dispersion transport. WIFIRE Commons will use QUIC-Fire and FIRETEC as the main drivers of the AI Innovations to demonstrate the use of high-fidelity data. Utilizing computational fluid dynamics models that integrate fire-atmospheric interactions with spatially explicit fuels, NMC research staff support various projects aimed at improving fire modeling. This project supports fire modeling efforts ranging from validation and innovation to implementation of new models into current fire management scenarios. Innovative fire models will improve our understanding of post-wildfire evaluations and improve prescribed fire planning and provide fire managers with decision support tools.

Building capacity for next generation fuel and fire management, training and science delivery

Project lead(s): Scott Pokswinski
Other NMC Scientists:
Other Partners:

Information coming soon.

Next-generation fire spread modeling to inform the management of climate- and fire-driven ecological transformations in the Rio Grande Basin (CASC)

Project lead(s): Rod Linn, Scott Pokswinski
Other NMC Scientists: Alex Masarie, Niko Tutland
Other Partners: US Geological Survey, US Fish and Wildlife Service, USDA Forest Service, Department of Defense

The objective is to use 3-d, field-derived, fuel models and next-generation fire models to understanding the range of current and potential future fire behaviors across a range of changing ecological conditions to increase the scale and efficacy of managed fire

A Multiscale Study of the Coupling Between Flow, Fire and Vegetation – Influence of Vegetation Distribution and Flow on Fire Behavior and Plume Development for Risk Mitigation in Prescribed Burns

Project lead(s): Scott Pokswinski
Other NMC Scientists:
Other Partners:

The goal of this project is to logistically support and collect non-fire data for a set of field ongoing experiments to support plume measurement campaigns under a forest canopy.

Validation of QUIC-Fire smoke plume dispersion modeling for complex wildland fires

Project lead: Scott Pokswinski, NMC Research Scientist
Other NMC Scientists: 
Other Partners: 

Smoke impacts on the public (communities, highways, airports) and on DoD missions is a significant constraint on DoD prescribed fire operations and the magnitude of this constraint continues to increase as urban encroachment on DoD lands increases. This project is to demonstrate and enhance the wildland fire plume development and smoke dispersion capabilities of the new operational-speed coupled fire/atmosphere model, QUIC-Fire. This project will demonstrate and validate QUIC-Fire’s ability to capture the influences of ignition patterns (i.e., fire geometry) on plume-core development and downwind dispersion under a range of realistic wind conditions through improved representation of near-field weather conditions, fire/atmosphere coupling, and plume organization and teach the tools to prescribed fire managers.

Incident Research Management Team-New Mexico Consortium

Project lead(s): Scott Pokswinski
Other NMC Scientists:
Other Partners:

Provide oversight, planning and logistical support for DoD Wildland Fire Science Initiative (WFSI) research burn campaigns.