Goodrick, S. L. | bioRxiv Science

bioRxiv2019

Coupling Terrestrial Laser Scanning with 3D Fuel Biomass Sampling for Advancing Wildland Fuels Characterization

The spatial pattern of surface fuelbeds in fire-dependent ecosystems are rarely captured using long-standing fuel sampling methods. New techniques, both field sampling and remote sensing, that capture vegetation fuel type, biomass, and volume at super fine-scales (cm to dm) in three-dimensions (3D) are critical to advancing forest fuel and wildland fire science. This is particularly true for computational fluid dynamics fire behavior models that operate in 3D and have implications for wildland fire operations and fire effects research. This study describes the coupling of new 3D field sampling data with terrestrial laser scanning (TLS) data to infer fine-scale fuel mass in 3D. We found that there are strong relationships between fine-scale mass and TLS occupied volume, porosity, and surface area, which were used to develop fine-scale prediction equations using TLS across vegetative fuel types, namely grasses and shrubs. The application of this novel 3D sampling technique to high resolution TLS data in this study represents a major advancement in understanding fire-vegetation feedbacks in highly managed fire-dependent ecosystems.

ecology↗

bioRxiv2019

Simulating groundcover community assembly in a frequently burned ecosystem using a simple neutral model

Fire is a global process that drives patterns of biodiversity. In frequently burned fire-dependent ecosystems, surface fire regimes allow for the coexistence of high plant diversity at fine-scales even where soils are uniform. The mechanisms on how fire impacts groundcover community dynamics are however, poorly understood. Because fire can act as a stochastic agent of mortality, we hypothesized that a neutral mechanism might be responsible for maintaining plant diversity. We used the demographic parameters of the Unified Neutral Theory of Biodiversity (UNTB) as a foundation to model groundcover species richness, using a southeastern U.S. pine woodland as an example. We followed the fate of over 7,000 individuals of 123 plant species for four years and two prescribed burns in frequently burned Pinus palustris sites in NW FL, USA. Using these empirical data and UNTB-based assumptions, we developed two parsimonious autonomous agent models, which were distinct by spatially explicit and implicit local recruitment processes. Using a parameter sensitivity test, we examined how empirical estimates, input species frequency distributions, and community size affected output species richness. We found that dispersal limitation was the most influential parameter, followed by mortality and birth, and that these parameters varied based on scale of the frequency distributions. Overall, these nominal parameters were useful for simulating fine-scale groundcover communities, although further empirical analysis of richness patterns, particularly related to fine-scale burn severity is needed. This modeling framework can be utilized to examine our premise that localized groundcover assemblages are neutral communities at high fire frequencies, as well as examine the extent to which niche-based dynamics determine community dynamics when fire frequency is altered and spatial fire intensity patterns differ.

ecology↗