Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska

Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has been hypothesized by local ecologists to result in the conversion of forest to grassland and subsequent increased fire danger. This hypothesis stands in contrast to empirical studies in the continental US which suggested that beetle mortality has only a negligible effect on fire danger. In response, we conducted a study using Landsat data and modeling techniques to map land cover change in the Kenai Peninsula and to integrate change maps with other geospatial data to predictively map fire danger for the same region. We collected Landsat imagery to map land cover change at roughly five-year intervals following a severe, mid-1990s beetle infestation to the present. Land cover classification was performed at each time step and used to quantify grassland encroachment patterns over time. The maps of land cover change along with digital elevation models (DEMs), temperature, and historical fire data were used to map and assess wildfire danger across the study area. Results indicate the highest wildfire danger tended to occur in herbaceous and black spruce land cover types, suggesting that the relationship between spruce beetle damage and wildfire danger in costal Alaskan forested ecosystems differs from the relationship between the two in the forests of the coterminous United States. These change detection analyses and fire danger predictions provide the Kenai National Wildlife Refuge (KENWR) ecologists and other forest managers a better understanding of the extent and magnitude of grassland conversion and subsequent change in fire danger following the 1990s spruce beetle outbreak

Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska

Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has heightened local wildfire risk as canopy loss facilitates the conversion from bare to fire-prone grassland. We collected images from NASA satellite-based Earth observations to visualize land cover succession at roughly five-year intervals following a severe, mid-1990's beetle infestation to the present. We classified these data by vegetation cover type to quantify grassland encroachment patterns over time. Raster band math provided a change detection analysis on the land cover classifications. Results indicate the highest wildfire risk is linked to herbaceous and black spruce land cover types, The resulting land cover change image will give the Kenai National Wildlife Refuge (KENWR) ecologists a better understanding of where forests have converted to grassland since the 1990s. These classifications provided a foundation for us to integrate digital elevation models (DEMs), temperature, and historical fire data into a model using Python for assessing and mapping changes in wildfire risk. Spatial representations of this risk will contribute to a better understanding of ecological trajectories of beetle-affected landscapes, thereby informing management decisions at KENWR

Combining Regulatory Instruments and Low-Cost Sensors to Quantify the Effects of 2020 California Wildfires on PM2.5 in San Joaquin Valley

The San Joaquin Valley in California has some of the worst air quality conditions in the nation, affected by a variety of pollution sources including wildfires. Although wildfires are part of the regional ecology, recent increases in wildfire activity may pose increased risk to people and the environment. The 2020 wildfire season in California included the largest wildfires reported to date and resulted in poor air quality across the state. In this study, we looked at the air quality effects of these wildfires in the San Joaquin Valley area. We determined that four wildfires (LNU Lightning Complex, SCU Lightning Complex, Creek, and Castle) were primarily affecting the air quality in the area. The daily PM2.5 emissions from each one of these wildfires were estimated and the largest daily emissions, 1935 ton/day, were caused by the Creek fire. To analyze the air quality in the study area, we developed a method utilizing a combination of regulatory and low-cost sensor data to estimate the daily PM2.5 concentration levels at 5 km spatial resolution. The concentrations maps showed that the highest average concentration levels were reached on 17 September with an average of 130 μg/m3 when about one-fifth of the study area was affected by hazardous PM2.5 levels. A sensitivity study of our interpolation method showed that the addition of low-cost sensors to regulatory data improved the performance of area-wide concentration estimates and reduced the mean absolute error and the root mean square error by more than 20%

Combining Regulatory Instruments and Low-Cost Sensors to Quantify the Effects of 2020 California Wildfires on PM2.5 in San Joaquin Valley

The San Joaquin Valley in California has some of the worst air quality conditions in the nation, affected by a variety of pollution sources including wildfires. Although wildfires are part of the regional ecology, recent increases in wildfire activity may pose increased risk to people and the environment. The 2020 wildfire season in California included the largest wildfires reported to date and resulted in poor air quality across the state. In this study, we looked at the air quality effects of these wildfires in the San Joaquin Valley area. We determined that four wildfires (LNU Lightning Complex, SCU Lightning Complex, Creek, and Castle) were primarily affecting the air quality in the area. The daily PM2.5 emissions from each one of these wildfires were estimated and the largest daily emissions, 1935 ton/day, were caused by the Creek fire. To analyze the air quality in the study area, we developed a method utilizing a combination of regulatory and low-cost sensor data to estimate the daily PM2.5 concentration levels at 5 km spatial resolution. The concentrations maps showed that the highest average concentration levels were reached on 17 September with an average of 130 μg/m3 when about one-fifth of the study area was affected by hazardous PM2.5 levels. A sensitivity study of our interpolation method showed that the addition of low-cost sensors to regulatory data improved the performance of area-wide concentration estimates and reduced the mean absolute error and the root mean square error by more than 20%

Wind Tunnel Experiments to Study Chaparral Crown Fires.

The present protocol presents a laboratory technique designed to study chaparral crown fire ignition and spread. Experiments were conducted in a low velocity fire wind tunnel where two distinct layers of fuel were constructed to represent surface and crown fuels in chaparral. Chamise, a common chaparral shrub, comprised the live crown layer. The dead fuel surface layer was constructed with excelsior (shredded wood). We developed a methodology to measure mass loss, temperature, and flame height for both fuel layers. Thermocouples placed in each layer estimated temperature. A video camera captured the visible flame. Post-processing of digital imagery yielded flame characteristics including height and flame tilt. A custom crown mass loss instrument developed in-house measured the evolution of the mass of the crown layer during the burn. Mass loss and temperature trends obtained using the technique matched theory and other empirical studies. In this study, we present detailed experimental procedures and information about the instrumentation used. The representative results for the fuel mass loss rate and temperature filed within the fuel bed are also included and discussed

Wind Tunnel Experiments to Study Chaparral Crown Fires.

The present protocol presents a laboratory technique designed to study chaparral crown fire ignition and spread. Experiments were conducted in a low velocity fire wind tunnel where two distinct layers of fuel were constructed to represent surface and crown fuels in chaparral. Chamise, a common chaparral shrub, comprised the live crown layer. The dead fuel surface layer was constructed with excelsior (shredded wood). We developed a methodology to measure mass loss, temperature, and flame height for both fuel layers. Thermocouples placed in each layer estimated temperature. A video camera captured the visible flame. Post-processing of digital imagery yielded flame characteristics including height and flame tilt. A custom crown mass loss instrument developed in-house measured the evolution of the mass of the crown layer during the burn. Mass loss and temperature trends obtained using the technique matched theory and other empirical studies. In this study, we present detailed experimental procedures and information about the instrumentation used. The representative results for the fuel mass loss rate and temperature filed within the fuel bed are also included and discussed

Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska

Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has been hypothesized by local ecologists to result in the conversion of forest to grassland and subsequent increased fire danger. This hypothesis stands in contrast to empirical studies in the continental US which suggested that beetle mortality has only a negligible effect on fire danger. In response, we conducted a study using Landsat data and modeling techniques to map land cover change in the Kenai Peninsula and to integrate change maps with other geospatial data to predictively map fire danger for the same region. We collected Landsat imagery to map land cover change at roughly five-year intervals following a severe, mid-1990s beetle infestation to the present. Land cover classification was performed at each time step and used to quantify grassland encroachment patterns over time. The maps of land cover change along with digital elevation models (DEMs), temperature, and historical fire data were used to map and assess wildfire danger across the study area. Results indicate the highest wildfire danger tended to occur in herbaceous and black spruce land cover types, suggesting that the relationship between spruce beetle damage and wildfire danger in costal Alaskan forested ecosystems differs from the relationship between the two in the forests of the coterminous United States. These change detection analyses and fire danger predictions provide the Kenai National Wildlife Refuge (KENWR) ecologists and other forest managers a better understanding of the extent and magnitude of grassland conversion and subsequent change in fire danger following the 1990s spruce beetle outbreak

Reimagine fire science for the anthropocene.

Acknowledgements: The authors thank Kathy Bogan with CIRES Communications for the figure design and creation, and two anonymous reviewers for comments on an earlier version of the manuscript.Funder: National Center for Atmospheric Research 12|0; DOI: https://doi.org/10.13039/100005323Fire 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

Reimagine fire science for the anthropocene

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