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 webpage.
Cultural Resource Detection using Light Detection and Ranging (LiDAR) for Management during Pre-planning in Timber and Fire Activities
Project lead: Grant Snitker
Other NMC Scientists: Claudine Gravel-Miguel
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.
Advancing LiDAR-based natural and cultural resource management applications
Project lead(s): Scott Pokswinski and Grant Snitker
Other NMC Scientists: Matt Snider
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.
Advanced Integrated Fire Science Support
Project lead: Rachel Loehman
Other NMC Scientists: Grant Snitker, Alex Masarie, Audrey Wilson
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.
Integrated Fire Modeling
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
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.