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  • 1
    Online Resource
    Online Resource
    Elsevier BV ; 2021
    In:  Proceedings of the Combustion Institute Vol. 38, No. 3 ( 2021), p. 5109-5117
    In: Proceedings of the Combustion Institute, Elsevier BV, Vol. 38, No. 3 ( 2021), p. 5109-5117
    Type of Medium: Online Resource
    ISSN: 1540-7489
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 2197968-6
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  • 2
    In: Combustion and Flame, Elsevier BV, Vol. 234 ( 2021-12), p. 111644-
    Type of Medium: Online Resource
    ISSN: 0010-2180
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 2000795-4
    detail.hit.zdb_id: 240116-2
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  • 3
    In: Remote Sensing, MDPI AG, Vol. 15, No. 18 ( 2023-09-07), p. 4407-
    Abstract: The challenges inherent in field validation data, and real-world light detection and ranging (lidar) collections make it difficult to assess the best algorithms for using lidar to characterize forest stand volume. Here, we demonstrate the use of synthetic forest stands and simulated terrestrial laser scanning (TLS) for the purpose of evaluating which machine learning algorithms, scanning configurations, and feature spaces can best characterize forest stand volume. The random forest (RF) and support vector machine (SVM) algorithms generally outperformed k-nearest neighbor (kNN) for estimating plot-level vegetation volume regardless of the input feature space or number of scans. Also, the measures designed to characterize occlusion using spherical voxels generally provided higher predictive performance than measures that characterized the vertical distribution of returns using summary statistics by height bins. Given the difficulty of collecting a large number of scans to train models, and of collecting accurate and consistent field validation data, we argue that synthetic data offer an important means to parameterize models and determine appropriate sampling strategies.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2513863-7
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  • 4
    In: Fire, MDPI AG, Vol. 6, No. 3 ( 2023-03-02), p. 98-
    Abstract: Terrestrial laser scanning (TLS) data can offer a means to estimate subcanopy fuel characteristics to support site characterization, quantification of treatment or fire effects, and inform fire modeling. Using field and TLS data within the New Jersey Pinelands National Reserve (PNR), this study explores the impact of forest phenology and density of shrub height (i.e., shrub fuel bed depth) measurements on estimating average shrub heights at the plot-level using multiple linear regression and metrics derived from ground-classified and normalized point clouds. The results highlight the importance of shrub height sampling density when these data are used to train empirical models and characterize plot-level characteristics. We document larger prediction intervals (PIs), higher root mean square error (RMSE), and lower R-squared with reduction in the number of randomly selected field reference samples available within each plot. At least 10 random shrub heights collected in situ were needed to produce accurate and precise predictions, while 20 samples were ideal. Additionally, metrics derived from leaf-on TLS data generally provided more accurate and precise predictions than those calculated from leaf-off data within the study plots and landscape. This study highlights the importance of reference data sampling density and design and data characteristics when data will be used to train empirical models for extrapolation to new sites or plots.
    Type of Medium: Online Resource
    ISSN: 2571-6255
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2924038-4
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  • 5
    In: Fire, MDPI AG, Vol. 6, No. 9 ( 2023-09-19), p. 366-
    Abstract: Prescribed fire is a management tool that is frequently used to foster biodiversity. Simultaneously, insects that provide essential ecosystem services are globally declining. Within the pyroentomology literature, there are mixed reports of positive and negative effects that prescribed fires have on insect communities. This is likely due to not accounting for fire heterogeneity created by fire severity. To better understand prescribed fire severity effects on insect communities, we used multispectral reflectance data collected by Sentinel-2 to methodically quantify prescribed fire severity and compared ground beetle (Coleoptera: Carabidae) taxonomic and functional community composition responses between an unburned site and two burned sites with contrasting fire impacts. We found 23 ground beetle species and used 30 morphological, physiological, phenological, and ecological functional traits for each species. We found that our moderate fire severity site had different taxonomic and functional community compositions from both our unburned and high-severity sites. Surprisingly, we did not find a strong difference in taxonomic or functional ground beetle composition between our unburned and high-severity sites. Our results encourage future pyroentomology studies to account for fire severity, which will help guide conservation managers to make more accurate decisions and predictions about prescribed fire effects on insect biodiversity.
    Type of Medium: Online Resource
    ISSN: 2571-6255
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2924038-4
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  • 6
    Online Resource
    Online Resource
    CSIRO Publishing ; 2021
    In:  International Journal of Wildland Fire Vol. 30, No. 5 ( 2021-4-30), p. 391-397
    In: International Journal of Wildland Fire, CSIRO Publishing, Vol. 30, No. 5 ( 2021-4-30), p. 391-397
    Abstract: Currently, our ability to link wildland fire behaviour to fire effects is through the lens of fire severity assessments, because there are no ground-based post-fire metrics that are able to quantitively capture aspects of heat transfer to plants. This presents a particular challenge when considering tree mortality linked to cambial damage, which can occur in both low-intensity surface fires through to high-intensity crown fires. Recent research suggests that measuring the amount of light reflected from charcoals produced by wildland fires will provide information about the energy flux that created the char. We created an experimental forest fire in which we had instrumented individual trees to record the energy delivered to the bark close to the base of the trees. We then assessed the bark charcoal reflectance of the same trees. We found that bark charcoal reflectance showed a strong positive correlation (r2  〉  0.86, P = 0.0031) with increasing duration of heating and the total energy delivered to the bark. We suggest that this may provide useful quantitative data that can be included in models or post-fire surveys to estimate tree mortality due to cambial kill.
    Type of Medium: Online Resource
    ISSN: 1049-8001 , 1448-5516
    Language: English
    Publisher: CSIRO Publishing
    Publication Date: 2021
    SSG: 12
    SSG: 23
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  • 7
    In: Atmosphere, MDPI AG, Vol. 11, No. 3 ( 2020-02-29), p. 242-
    Abstract: Prescribed fires are conducted extensively in pine-dominated forests throughout the Eastern USA to reduce the risk of wildfires and maintain fire-adapted ecosystems. We asked how fire behavior and fuel consumption during prescribed fires are associated with turbulence and energy fluxes, which affect the dispersion of smoke and transport of firebrands, potentially impacting local communities and transportation corridors. We estimated fuel consumption and measured above-canopy turbulence and energy fluxes using eddy covariance during eight prescribed fires ranging in behavior from low-intensity backing fires to high-intensity head fires in pine-dominated forests of the New Jersey Pinelands, USA. Consumption was greatest for fine litter, intermediate for understory vegetation, and least for 1 + 10 hour wood, and was significantly correlated with pre-burn loading for all fuel types. Crown torching and canopy fuel consumption occurred only during high-intensity fires. Above-canopy air temperature, vertical wind velocity, and turbulent kinetic energy (TKE) in buoyant plumes above fires were enhanced up to 20.0, 3.9 and 4.1 times, respectively, compared to values measured simultaneously on control towers in unburned areas. When all prescribed fires were considered together, differences between above-canopy measurements in burn and control areas (Δ values) for maximum Δ air temperatures were significantly correlated with maximum Δ vertical wind velocities at all (10 Hz to 1 minute) integration times, and with Δ TKE. Maximum 10 minute averaged sensible heat fluxes measured above canopy were lower during low-intensity backing fires than for high-intensity head fires, averaging 1.8 MJ m−2 vs. 10.6 MJ m−2, respectively. Summed Δ sensible heat values averaged 70 ± 17%, and 112 ± 42% of convective heat flux estimated from fuel consumption for low-intensity and high-intensity fires, respectively. Surprisingly, there were only weak relationships between the consumption of surface and understory fuels and Δ air temperature, Δ wind velocities, or Δ TKE values in buoyant plumes. Overall, low-intensity fires were effective at reducing fuels on the forest floor, but less effective at consuming understory vegetation and ladder fuels, while high-intensity head fires resulted in greater consumption of ladder and canopy fuels but were also associated with large increases in turbulence and heat flux above the canopy. Our research quantifies some of the tradeoffs involved between fire behavior and turbulent transfer of smoke and firebrands during effective fuel reduction treatments and can assist wildland fire managers when planning and conducting prescribed fires.
    Type of Medium: Online Resource
    ISSN: 2073-4433
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2605928-9
    SSG: 23
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  • 8
    In: Ecological Applications, Wiley, Vol. 32, No. 7 ( 2022-10)
    Abstract: Over the past century, fire suppression has facilitated broad ecological changes in the composition, structure, and function of fire‐dependent landscapes throughout the eastern US, which are in decline. These changes have likely contributed mechanistically to the enhancement of habitat conditions that favor pathogen‐carrying tick species, key wildlife hosts of ticks, and interactions that have fostered pathogen transmission among them and to humans. While the long‐running paradigm for limiting human exposure to tick‐borne diseases focuses responsibility on individual prevention, the continued expansion of medically important tick populations, increased incidence of tick‐borne disease in humans, and emergence of novel tick‐borne diseases highlights the need for additional approaches to stem this public health challenge. Another approach that has the potential to be a cost‐effective and widely applied but that remains largely overlooked is the use of prescribed fire to ecologically restore degraded landscapes that favor ticks and pathogen transmission. We examine the ecological role of fire and its effects on ticks within the eastern United States, especially examining the life cycles of forest‐dwelling ticks, shifts in regional‐scale fire use over the past century, and the concept that frequent fire may have helped moderate tick populations and pathogen transmission prior to the so‐called fire‐suppression era that has characterized the past century. We explore mechanisms of how fire and ecological restoration can reduce ticks, the potential for incorporating the mechanisms into the broader strategy for managing ticks, and the challenges, limitations, and research needs of prescribed burning for tick reduction.
    Type of Medium: Online Resource
    ISSN: 1051-0761 , 1939-5582
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2010123-5
    SSG: 12
    SSG: 23
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  • 9
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 53, No. 4 ( 2014-04), p. 793-812
    Abstract: Smoke prediction products are one of the tools used by land management personnel for decision making regarding prescribed fires. This study documents the application to a prescribed fire of a smoke prediction system that employs ARPS-CANOPY, a modified version of the Advanced Regional Prediction System (ARPS) model containing a canopy submodel, as the meteorological driver. In this paper, the performance of ARPS-CANOPY in simulating meteorological fields in the vicinity of a low-intensity fire is assessed using flux-tower data collected prior to and during a low-intensity prescribed fire in the New Jersey Pine Barrens in March 2011. A three-dimensional high-resolution plant area density dataset is utilized to define the characteristics of the canopy, and the fire is represented in ARPS-CANOPY as a heat flux to the atmosphere. The standard ARPS model is compared with reanalysis and upper-air data to establish that the model can simulate the observed synoptic-mesoscale and planetary boundary layer features that are salient to this study. ARPS-CANOPY profiles of mean turbulent kinetic energy, wind speed/direction, and temperature exhibit patterns that appear in the flux-tower observations during both the preburn phase of the experiment and the period of time the flux tower experienced perturbed atmospheric conditions due to the impinging fire. Last, the character and source of turbulence in and around the fire line are examined. These results are encouraging for smoke prediction efforts since transport of smoke from low-intensity fires is highly sensitive to the near-surface meteorological conditions and, in particular, turbulent flows.
    Type of Medium: Online Resource
    ISSN: 1558-8424 , 1558-8432
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2014
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
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  • 10
    In: Fire Safety Journal, Elsevier BV, Vol. 120 ( 2021-03), p. 103051-
    Type of Medium: Online Resource
    ISSN: 0379-7112
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 1483569-1
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