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Nancy Glenn

Publications and source records attributed to Nancy Glenn.

4 recordsLinked to original sources

Future direction of fuels management in sagebrush rangelands

Sagebrush ecosystems in the United States have been declining since EuroAmerican settlement, largely due to agricultural and urban development, invasive species, and altered fire regimes, resulting in loss of biodiversity and wildlife habitat. To combat continued conversion to undesirable ecological states and loss of habitat to invasive species fueled by frequent fire, a variety of fuel treatments, including networks of fuel breaks, are being implemented or proposed in sagebrush ecosystems, particularly in and around the Great Basin. In this forum paper we briefly review current knowledge of common fuel treatment approaches, their intended benefits, potential risks, and limitations. We additionally discuss challenges for fuel treatment strategies in the context of changes in climate, invasive species, wildlife habitat, and human population, and we explore how advances in geospatial technologies, monitoring, and fire behavior modeling, as well as accounting for social context, can improve the efficacy of fuels management in sagebrush ecosystems. Finally, given continued potential for ecosystem transformation, we describe approaches to future fuels management by considering the applicability of the Resist-Accept-Direct (RAD) framework. The intent of the paper is to provide scientists and land managers with key information and a forward-thinking framework for fuels science and adaptive management that can respond to both expected and unexpected changes in sagebrush rangelands.

Rangeland Ecology and Management

Developing and optimizing shrub parameters representing sagebrush (Artemisia spp.) ecosystems in the Northern Great Basin using the Ecosystem Demography (EDv2.2) model

Ecosystem dynamic models are useful for understanding ecosystem characteristics over time and space because of their efficiency over direct field measurements and applicability to broad spatial extents. Their application, however, is challenging due to internal model uncertainties and complexities arising from distinct qualities of the ecosystems being analyzed. The sagebrush-steppe in western North America, for example, has substantial spatial and temporal heterogeneity as well as variability due to anthropogenic disturbance, invasive species, climate change, and altered fire regimes, which collectively make modelling dynamic ecosystem processes difficult. Ecosystem Demography (EDv2.2) is a robust ecosystem dynamic model, initially developed for tropical forests, that simulates energy, water, and carbon fluxes at fine scales. Although EDv2.2 has since been tested on different ecosystems via development of different Plant Function Types (PFT), it still lacks a shrub PFT. In this study, we developed and parameterized a shrub PFT representative of sagebrush (Artemisia spp.) ecosystems in order to initialize and test it within EDv2.2, and to promote future broad-scale analysis of restoration activities, climate change, and fire regimes in the sagebrush-steppe. Specifically, we parameterized the sagebrush PFT within EDv2.2 to estimate gross primary production (GPP), using data from two sagebrush study sites in the northern Great Basin. To accomplish this, we employed a three-tier approach: 1) To initially parameterize the sagebrush PFT, we fitted allometric relationships for sagebrush using field-collected data, information from existing sagebrush literature, and parameters from other land models. 2) To determine influential parameters in GPP prediction, we used a sensitivity analysis to identify the five most sensitive parameters. 3) To improve model performance and validate results, we optimized these five parameters using an exhaustive search method to estimate GPP, and compared results with observations from two Eddy Covariance (EC) sites in the study area. Our modeled results were encouraging, with reasonable fidelity to observed values, although some negative biases (i.e., seasonal underestimates of GPP) were apparent.

Great Basin

Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe

Terrestrial laser scanning (TLS) provides fast collection of high-definition structural information, making it a valuable field instrument to many monitoring applications. A weakness of TLS collections, especially in vegetation, is the occurrence of unsampled regions in point clouds where the sensor’s line-of-sight is blocked by intervening material. This problem, referred to as occlusion, may be mitigated by scanning target areas from several positions, increasing the chance that any given area will fall within the scanner’s line-of-sight from at least one position. Because TLS collections are often employed in remote regions where the scope of sampling is limited by logistical factors such as time and battery power, it is important to design field protocols which maximize efficiency and support increased quantity and quality of the data collected. This study informs researchers and practitioners seeking to optimize TLS sampling methods for vegetation monitoring in dryland ecosystems through three analyses. First, we quantify the 2D extent of occluded regions based on the range from single scan positions. Second, we measure the efficacy of additional scan positions on the reduction of 2D occluded regions (area) using progressive configurations of scan positions in 1 ha plots. Third, we test the reproducibility of 3D sampling yielded by a 5-scan/ha sampling methodology using redundant sets of scans. Analyses were performed using measurements at analysis scales of 5 to 50 cm across the 1-ha plots, and we considered plots in grass and shrub-dominated communities separately. In grass-dominated plots, a center-scan configuration and 5 cm pixel size sampled at least 90% of the area up to 18 m away from the scanner. In shrub-dominated plots, sampling at least 90% of the area was only achieved within a distance of 12 m. We found that 3 and 5 scans/ha are needed to sample at least ~ 70% of the total area (1 ha) in the grass and shrub-dominated plots, respectively, using 5 cm pixels to measure sampling presence-absence. The reproducibility of 3D sampling provided by a 5 position scan layout across 1-ha plots was 50% (shrub) and 70% (grass) using a 5-cm voxel size, whereas at the 50-cm voxel scale, reproducibility of sampling was nearly 100% for all plot types. Future studies applying TLS in similar dryland environments for vegetation monitoring may use our results as a guide to efficiently achieve sampling coverage and reproducibility in datasets.

Idaho

Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review

The study of mass and energy transfer across landscapes has recently evolved to comprehensive considerations acknowledging the role of biota and humans as geomorphic agents, as well as the importance of small-scale landscape features. A contributing and supporting factor to this evolution is the emergence over the last two decades of technologies able to acquire high resolution topography (HRT) (meter and sub-meter resolution) data. Landscape features can now be captured at an appropriately fine spatial resolution at which surface processes operate; this has revolutionized the way we study Earth-surface processes. The wealth of information contained in HRT also presents considerable challenges. For example, selection of the most appropriate type of HRT data for a given application is not trivial. No definitive approach exists for identifying and filtering erroneous or unwanted data, yet inappropriate filtering can create artifacts or eliminate/distort critical features. Estimates of errors and uncertainty are often poorly defined and typically fail to represent the spatial heterogeneity of the dataset, which may introduce bias or error for many analyses. For ease of use, gridded products are typically preferred rather than the more information-rich point cloud representations. Thus many users take advantage of only a fraction of the available data, which has furthermore been subjected to a series of operations often not known or investigated by the user. Lastly, standard HRT analysis work-flows are yet to be established for many popular HRT operations, which has contributed to the limited use of point cloud data. In this review, we identify key research questions relevant to the Earth-surface processes community within the theme of mass and energy transfer across landscapes and offer guidance on how to identify the most appropriate topographic data type for the analysis of interest. We describe the operations commonly performed from raw data to raster products and we identify key considerations and suggest appropriate work-flows for each, pointing to useful resources and available tools. Future research directions should stimulate further development of tools that take advantage of the wealth of information contained in the HRT data and address the present and upcoming research needs such as the ability to filter out unwanted data, compute spatially variable estimates of uncertainty and perform multi-scale analyses. While we focus primarily on HRT applications for mass and energy transfer, we envision this review to be relevant beyond the Earth-surface processes community for a much broader range of applications involving the analysis of HRT.

Earth-Science Reviews