• Energy Research

Abstract Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

This data product contains 1) weights of destructively sampled biomass, 2) terrestrial laser scanning (TLS) point cloud data, and 3) maps of predicted biomass and consumption derived from field observations and TLS data. Data were acquired at three burn units within Pebble Hill Plantation, Georgia, in April 2018 and June 2019. Sampling was done in conjunction with prescribed burning, with the goal of quantifying biomass before and after prescribed fire. Field observation plots were sampled following the methodology of Hawley et al. (2018). In April 2018, 8 plots were measured before prescribed burning and 8 plots were measured after prescribed burning in unit PHP1. In June 2019, 20 plots were measured before prescribed burning, which occurred on 17 and 18 June, and 6 plots were measured directly after prescribed burning in burn units PHP1, PHP2, and PHP3. Only 6 of 20 planned plots were measured post-fire in 2019 because of a severe weather event with precipitation and winds that disturbed post-fire biomass. Following sampling in the field, destructively-sampled biomass was oven dried and weighed; thus these data represent dry biomass weights. Terrestrial laser scanning data were acquired both before and after prescribed burning. TLS point clouds coincident with field observation plots were extracted, and models predicting field-observed biomass from TLS point clouds were created. Models were then applied to TLS point clouds to map biomass before and after prescribed burning; consumption by prescribed fire was estimated by differencing pre- and post-fire biomass maps.