Advancing Fire Science with Large Forest Plots and a Long-Term Multidisciplinary Approach

James Lutz,Andrew Larson,Mark Swanson

doi:10.3390/fire1010005

James Lutz, Andrew Larson + Show 1 more

Open Access

https://doi.org/10.3390/fire1010005

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Abstract

Large, spatially explicit forest plots have the potential to address currently understudied aspects of fire ecology and management, including the validation of physics-based fire behavior models and next-generation fire effects models. Pre-fire forest structures, fire-mediated mortality, and post-fire forest development can be examined in a spatial context, and value can be added to current multidisciplinary approaches by adding a long-term perspective. Here we propose that the fire science community begin to build a collaborative network of fire-related large forest dynamics plots to examine explicit spatial patterns of surface fuels, tree mortality, and post-fire regeneration throughout ecosystems with frequent-fire forests.

Highlights

Large, spatially explicit forest plots have the potential to address currently understudied aspects of fire ecology and management, including the validation of physics-based fire behavior models and next-generation fire effects models
We suggest that large, spatially explicit forest plots modeled after the Smithsonian ForestGEO network [2] are a key investment needed to meet one of the most pressing research challenges in fire science
Recent modeling studies illustrate the effects of fine-scale differences in stand structure on fire behavior (e.g., [3]), with the finding that aggregated fuel patterns increase the variability of fire behavior. These initial results suggest a promising pathway for testing conceptual models for forest dynamics and the generation of spatial heterogeneity in frequent-fire forests [4,5]), and for the design and evaluation of fuel reduction, restoration, and climate change adaptation treatments in frequent-fire forests [6,7]

Summary

Introduction

We suggest that large, spatially explicit forest plots modeled after the Smithsonian ForestGEO network [2] are a key investment needed to meet one of the most pressing research challenges in fire science. The high-frequency, low- and moderate-severity fire regime forest types are the most appropriate ecosystems for investment in large, spatially explicit forest plots. Recent modeling studies illustrate the effects of fine-scale differences in stand structure on fire behavior (e.g., [3]), with the finding that aggregated fuel patterns (i.e., arising from spatially aggregated tree patterns) increase the variability of fire behavior.

Results

Conclusion