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Atticus E L Stovall

Publications and source records attributed to Atticus E L Stovall.

Integrating Forest Structural Diversity Measurement Into Ecological Research

The measurement of forest structure has evolved steadily due to advances in technology, methodology, and theory. Such advances have greatly increased our capacity to describe key forest structural elements and resulted in a range of measurement approaches from traditional analog tools such as measurement tapes to highly derived and computationally intensive methods such as advanced remote sensing tools (e.g., lidar, radar). This assortment of measurement approaches results in structural metrics unique to each method, with the caveat that metrics may be biased or constrained by the measurement approach taken. While forest structural diversity (FSD) metrics foster novel research opportunities, understanding how they are measured or derived, limitations of the measurement approach taken, as well as their biological interpretation is crucial for proper application. We review the measurement of forest structure and structural diversity—an umbrella term that includes quantification of the distribution of functional and biotic components of forests. We consider how and where these approaches can be used, the role of technology in measuring structure, how measurement impacts extend beyond research, and current limitations and potential opportunities for future research.

Jeff W. Atkins↗

Evaluating the success of treatments that slow spread of an invasive insect pest

BACKGROUND Treatments for the suppression and eradication of insect populations undergo substantial testing to ascertain their efficacy and safety, but the generally limited spatial and temporal scope of such studies limit knowledge of how contextual factors encountered in operational contexts shape the relative success of pest management treatments. These contextual factors potentially include ecological characteristics of the treated area, or the timing of treatments relative to pest phenology and weather events. We used an extensive database on over 1000 treatments of nascent populations of Lymantria dispar (L.) (gypsy moth) to examine how place-based and time-varying conditions shape the success of management treatments. RESULTS We found treatment success to vary across states and years, and to be highest in small treatment blocks that are isolated from other populations. In addition, treatment success tended to be lower in treatment blocks with open forest canopies, possibly owing to challenges of effectively distributing treatments in these areas. CONCLUSIONS Our findings emphasize the importance of monitoring for early detection of nascent gypsy moth colonies in order to successfully slow the spread of the invasion. Additionally, operations research should address best practices for effectively treating with patchy and open forest canopies. © 2021 Society of Chemical Industry.

Jonathan A Walter↗

Evaluating Current and Future Sensor-Specific Biomass Calibration in the Tallest Mangrove Forest on Earth

High-resolution global-scale estimates of aboveground biomass density will soon be available from a suite of spaceborne LiDAR and radar missions. The 2016-2017 AfriSAR campaign was specifically designed to evaluate a suite of sensors for estimating biomass in a range of tropical forest environments. Here, we compare the calibration and biomass estimates from 5 different active sensors - ALOS Global Digital Surface Model (DSM), Shuttle Radar Topography Mission (SRTM), Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), NASA Land Vegetation Ice Sensor (LVIS), and TanDEM-X (TDX) - in the tallest known mangrove forest on Earth - Pongara National Park, Gabon. We leverage this comparison to evaluate the implications for future satellite missions that are aimed at improving global estimates of forest carbon storage. Our findings are directly relevant for space-borne missions estimating terrestrial carbon storage - GEDI, ICESat-2, NISAR, BIOMASS, Tandem-X, and Tandem-L - highlighting the specific uncertainty and bias that can be expected in several global biomass products in mangrove ecosystems.

Atticus E L Stovall↗