Biology subjects

Pokswinski, S.

Publications and source records attributed to Pokswinski, S..

5 recordsLinked to original sources

bioRxiv2024

Terrestrial 3D Laser Scanning for Ecosystem and Fire Effects Monitoring

Long-term terrestrial ecosystem monitoring is a critical component of documenting outcomes of land management actions, assessing progress towards management objectives, and guiding realistic long-term ecological goals, all through repeated observation and measurement. Traditional monitoring methods have evolved for specific applications in forestry, ecology, and fire and fuels management. While successful monitoring programs have clear goals, trained expertise, and rigorous sampling protocols, new advances in technology and data management can help overcome the most common pitfalls in data quality and repeatability. This paper presents Terrestrial Laser Scanning (TLS), a specific form of LiDAR (Light Detection and Ranging), as an emerging sampling method that can complement and enhance existing monitoring methods. TLS captures in high resolution the 3D structure of a terrestrial ecosystem (forest, grassland, etc.), and is increasingly efficient and affordable (<$30,000). Integrating TLS into ecosystem monitoring can standardize data collection, improve efficiency, and reduce bias and error. Streamlined data processing pipelines can rigorously analyze TLS data and incorporate constant improvements to inform management decisions and planning. The approach described in this paper utilizes portable, push-button TLS equipment that, when calibrated with initial transect sampling, captures detailed forestry, fuels, and ecological features in less than 5 minutes per plot. We also introduce an interagency automated processing pipeline and dashboard viewer for instant, user-friendly analysis, and data retrieval of hundreds of metrics. Forest metrics and inventories produced with these methods offer effective decision-support data for managers to quantify landscape-scale conditions and respond with efficient action. This protocol further supports interagency compatibility for efficient natural resource monitoring across jurisdictional boundaries with uniform data, language, methods, and data analysis. With continued improvement of scanner capabilities and affordability, these data will shape the future of terrestrial ecosystem monitoring as an important means to address the increasingly fast pace of ecological change facing natural resource managers.

ecology↗

bioRxiv2023

Terrestrial laser scan metrics predict surface vegetation biomass and consumption in a frequently burned southeastern U.S. ecosystem

Fire-prone landscapes found throughout the world are increasingly managed with prescribed fire for a variety of objectives. These frequent low-intensity fires directly impact lower forest strata, and thus estimating surface fuels or understory vegetation is essential for planning, evaluating, and monitoring management strategies and studying fire behavior and effects. Traditional fuel estimation methods have applications for stand-level and canopy fuel loading; however, local-scale understory biomass remains challenging because of complex within-stand heterogeneity and fast recovery post-fire. Previous studies have demonstrated how single location terrestrial laser scanning (TLS) can be used to estimate plot-level vegetation characteristics and impacts from prescribed fire. To build upon this methodology, co-located single TLS scans and physical biomass measurements were used to generate linear models for predicting understory vegetation and fuel biomass as well as consumption by fire in a southeastern U.S. pineland. A variable selection method was used to select the six most important TLS-derived structural metrics for each linear model, where model fit ranged in R2 from 0.61 to 0.74. This study highlights a prospect for efficiently estimating vegetation and fuel characteristics relevant to prescribed burning via the integration of a single-scan TLS method adaptable by managers and relevant for coupled fire-atmosphere models.

ecology↗

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↗

bioRxiv2019

Scale dependent patterns in interaction diversity maintain resiliency in a frequently disturbed ecosystem

Frequently disturbed ecosystems are characterized by resilience to ecological disturbances. For example, longleaf pine ecosystems are exposed to frequent fire disturbance, and this feature sustains biodiversity. We examined how fire frequency maintains beta diversity of multi-trophic interactions, as this community parameter provides a measure of functional redundancy of an ecosystem. We found that turnover in interaction diversity at small local scales is highest in the most frequently burned stands, conferring immediate resiliency to disturbance by fire. Interactions become more specialized and less resilient as fire frequency decreases. Local scale patterns of interaction diversity contribute to broader scale patterns and confer long-term ecosystem resiliency. Such natural disturbances are likely to be important for maintaining regional diversity of interactions for a broad range of ecosystems.

ecology↗