Laser Vision: Lidar as a Transformative Tool to Advance Critical Zone Science

Observation and quantification of the Earth’s surface is undergoing a revolutionary change due to the increased spatial resolution and extent afforded by light detection and ranging (lidar) technology. As a consequence, lidar-derived information has led to fundamental discoveries within the individual disciplines of geomorphology, hydrology, and ecology. These disciplines form the cornerstones of critical zone (CZ) science, where researchers study how interactions among the geosphere, hydrosphere, and biosphere shape and maintain the “zone of life”, which extends from the top of unweathered bedrock to the top of the vegetation canopy. Fundamental to CZ science is the development of transdisciplinary theories and tools that transcend disciplines and inform other’s work, capture new levels of complexity, and create new intellectual outcomes and spaces. Researchers are just beginning to use lidar data sets to answer synergistic, transdisciplinary questions in CZ science, such as how CZ processes co-evolve over long timescales and interact over shorter timescales to create thresholds, shifts in states and fluxes of water, energy, and carbon. The objective of this review is to elucidate the transformative potential of lidar for CZ science to simultaneously allow for quantification of topographic, vegetative, and hydrological processes. A review of 147 peer-reviewed lidar studies highlights a lack of lidar applications for CZ studies as 38% of the studies were focused in geomorphology, 18% in hydrology, 32% in ecology, and the remaining 12% had an interdisciplinary focus. A handful of exemplar transdisciplinary studies demonstrate lidar data sets that are well-integrated with other observations can lead to fundamental advances in CZ science, such as identification of feedbacks between hydrological and ecological processes over hillslope scales and the synergistic co-evolution of landscape-scale CZ structure due to interactions amongst carbon, energy, and water cycles. We propose that using lidar to its full potential will require numerous advances, including new and more powerful open-source processing tools, exploiting new lidar acquisition technologies, and improved integration with physically based models and complementary in situ and remote-sensing observations. We provide a 5-year vision that advocates for the expanded use of lidar data sets and highlights subsequent potential to advance the state of CZ science

A wall interference assessment/correction system

A Wall Signature method originally developed by Hackett has been selected to be adapted for the Ames 12-ft Wind Tunnel WIAC system in the project. This method uses limited measurements of the static pressure at the wall, in conjunction with the solid wall boundary condition, to determine the strength and distribution of singularities representing the test article. The singularities are used in turn for estimating blockage wall interference. The lifting interference will be treated separately by representing in a horseshoe vortex system for the model's lifting effects. The development and implementation of a working prototype will be completed, delivered and documented with a software manual. The WIAC code will be validated by conducting numerically simulated experiments rather than actual wind tunnel experiments. The simulations will be used to generate both free-air and confined wind-tunnel flow fields for each of the test articles over a range of test configurations. Specifically, the pressure signature at the test section wall will be computed for the tunnel case to provide the simulated 'measured' data. These data will serve as the input for the WIAC method--Wall Signature method. The performance of the WIAC method then may be evaluated by comparing the corrected data with those of the free-air simulation

Seasonal Variability of Saturn's Tropospheric Temperatures, Winds and Para-H2_2 from Cassini Far-IR Spectroscopy

Far-IR 16-1000 $\mu$m spectra of Saturn's hydrogen-helium continuum measured by Cassini's Composite Infrared Spectrometer (CIRS) are inverted to construct a near-continuous record of upper tropospheric (70-700 mbar) temperatures and para-H$_2$ fraction as a function of latitude, pressure and time for a third of a Saturnian year (2004-2014, from northern winter to northern spring). The thermal field reveals evidence of reversing summertime asymmetries superimposed onto the belt/zone structure. The temperature structure that is almost symmetric about the equator by 2014, with seasonal lag times that increase with depth and are qualitatively consistent with radiative climate models. Localised heating of the tropospheric hazes (100-250 mbar) create a distinct perturbation to the temperature profile that shifts in magnitude and location, declining in the autumn hemisphere and growing in the spring. Changes in the para-H$_2$ ($f_p$) distribution are subtle, with a 0.02-0.03 rise over the spring hemisphere (200-500 mbar) perturbed by (i) low-$f_p$ air advected by both the springtime storm of 2010 and equatorial upwelling; and (ii) subsidence of high-$f_p$ air at northern high latitudes, responsible for a developing north-south asymmetry in $f_p$. Conversely, the shifting asymmetry in the para-H$_2$ disequilibrium primarily reflects the changing temperature structure (and the equilibrium distribution of $f_p$), rather than actual changes in $f_p$ induced by chemical conversion or transport. CIRS results interpolated to the same point in the seasonal cycle as re-analysed Voyager-1 observations show qualitative consistency, with the exception of the tropical tropopause near the equatorial zones and belts, where downward propagation of a cool temperature anomaly associated with Saturn's stratospheric oscillation could potentially perturb tropopause temperatures, para-H$_2$ and winds. [ABRIDGED]Comment: Preprint accepted for publication in Icarus, 29 pages, 18 figure

Intense molecular emission from the Lagoon nebula, M8

The discovery is reported of the second strongest source of mm and submm wavelength CO line emission, towards M8, the Lagoon Nebula in Sagittarius. The ~31 M⊙ molecular core has dimensions ~0.2 x 0.3pc and is centred on the O7V star Herschel 36 (H36), near the Hourglass Nebula in the core of M8. Emission from the CO line wings extends to the north and south of the Hourglass, although a lack of near-IR H2 emission indicates that outflow activity is much less prominent than in many active star-formation regions, and suggests that the CO line wings may trace the expanding edge of a cavity around H36. The molecular line data are compared with new near-IR narrow-band, continuum-subtracted images in He I, H2, and H,+ (Brγ) lines and archival HST emission-line images in Hα, [O III], and [S II]. The optical and near-IR data are found to be broadly consistent with previous photo-ionisation models of the Hourglass, which is excited by H 36. However, there are variations in the He I/Brγ line ratio which are difficult to explain

ISO observations of M8, the Lagoon nebula

In this paper, IRAS, ISO, and molecular line observations of the M8 and M8E sources in the Lagoon Nebula are reported

Developing and Optimizing Shrub Parameters Representing Sagebrush (\u3ci\u3eArtemisia\u3c/i\u3e 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 ecosystem 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 modeling 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 functional 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 sagebrushsteppe ecosystem. 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. Our finding on preliminary parameterization of the sagebrush shrub PFT is an important step towards subsequent studies on shrubland ecosystems using EDv2.2 or any other process-based ecosystem model

Assessing a Multi-Platform Data Fusion Technique in Capturing Spatiotemporal Dynamics of Heterogeneous Dryland Ecosystems in Topographically Complex Terrain

Water-limited ecosystems encompass approximately 40% of terrestrial land mass and play a critical role in modulating Earth’s climate and provisioning ecosystem services to humanity. Spaceborne remote sensing is a critical tool for characterizing ecohydrologic patterns and advancing the understanding of the interactions between atmospheric forcings and ecohydrologic responses. Fine to medium scale spatial and temporal resolutions are needed to capture the spatial heterogeneity and the temporally intermittent response of these ecosystems to environmental forcings. Techniques combining complementary remote sensing datasets have been developed, but the heterogeneous nature of these regions present significant challenges. Here we investigate the capacity of one such approach, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm, to map Normalized Difference Vegetation Index (NDVI) at 30 m spatial resolution and at a daily temporal resolution in an experimental watershed in southwest Idaho, USA. The Dry Creek Experimental Watershed captures an ecotone from a sagebrush steppe ecosystem to evergreen needle-leaf forests along an approximately 1000 m elevation gradient. We used STARFM to fuse NDVI retrievals from the MODerate-resolution Imaging Spectroradiometer (MODIS) and Landsat during the course of a growing season (April to September). Specifically we input to STARFM a pair of Landsat NDVI retrievals bracketing a sequence of daily MODIS NDVI retrievals to yield daily estimates of NDVI at resolutions of 30 m. In a suite of data denial experiments we compared these STARFM predictions against corresponding Landsat NDVI retrievals and characterized errors in predicted NDVI. We investigated how errors vary as a function of vegetation functional type and topographic aspect. We find that errors in predicting NDVI were highest during green-up and senescence and lowest during the middle of the growing season. Absolute errors were generally greatest in tree-covered portions of the watershed and lowest in locations characterized by grasses/bare ground. On average, relative errors in predicted average NDVI were greatest in grass/bare ground regions, on south-facing aspects, and at the height of the growing season. We present several ramifications revealed in this study for the use of multi-sensor remote sensing data for the study of spatiotemporal ecohydrologic patterns in dryland ecosystems

Measurement of the 171Tm isomeric lifetime as a teaching laboratory experiment

A teaching experiment is described in which two methods are applied to determine the lifetime of an isomeric state in 171mTm. One method, a single channel measurement, utilizes a delayed coincidence technique while the second, a multichannel measurement, employs time-to-pulse height conversion. Both serve to illustrate several principles of coincidence and timing measurements and can give results of good accuracy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/32703/1/0000070.pd

Helicobacter pylori phagosome maturation in primary human macrophages

Extent: 14p.Background: Helicobacter pylori (H. pylori) is a micro-aerophilic, spiral-shaped, motile bacterium that is the principal cause of gastric and duodenal ulcers in humans and is a major risk factor for the development of gastric cancer. Despite provoking a strong innate and adaptive immune response in the host, H. pylori persists in the gastric mucosa, avoiding eradication by macrophages and other phagocytic cells, which are recruited to the site of infection. Here we have characterised the critical degradative process of phagosome maturation in primary human macrophages for five genotypically and phenotypically distinct clinical strains of H. pylori. Results: All of the H. pylori strains examined showed some disruption to the phagosome maturation process, when compared to control E. coli. The early endosome marker EEA1 and late endosome marker Rab7 were retained on H. pylori phagosomes, while the late endosome-lysosome markers CD63, LAMP-1 and LAMP-2 were acquired in an apparently normal manner. Acquisition of EEA1 by H. pylori phagosomes appeared to occur by two distinct, strain specific modes. H. pylori strains that were negative for the cancer associated virulence factor CagA were detected in phagosomes that recruited large amounts of EEA1 relative to Rab5, compared to CagA positive strains. There were also strain specific differences in the timing of Rab7 acquisition which correlated with differences in the rate of intracellular trafficking of phagosomes and the timing of megasome formation. Megasomes were observed for all of the H. pylori strains examined. Conclusions: H. pylori appeared to disrupt the normal process of phagosome maturation in primary human macrophages, appearing to block endosome fission. This resulted in the formation of a hybrid phagosome-endosome-lysosome compartment, which we propose has reduced degradative capacity. Reduced killing by phagocytes is consistent with the persistence of H. pylori in the host, and would contribute to the chronic stimulation of the inflammatory immune response, which underlies H. pylori-associated disease.Glenn N Borlace, Hilary F Jones, Stacey J Keep, Ross N Butler, Doug A Brook

Regional Scale Dryland Vegetation Classification with an Integrated Lidar-Hyperspectral Approach

The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for mapping dryland vegetation with remote sensing. Consequently, the results of a single classification algorithm or one type of sensor to characterize dryland vegetation typically show low accuracy and lack robustness. In our study, we improved classification accuracy in a semi-arid ecosystem based on the use of vegetation optical (hyperspectral) and structural (lidar) information combined with the environmental characteristics of the landscape. To accomplish this goal, we used both spectral angle mapper (SAM) and multiple endmember spectral mixture analysis (MESMA) for optical vegetation classification. Lidar-derived maximum vegetation height and delineated riparian zones were then used to modify the optical classification. Incorporating the lidar information into the classification scheme increased the overall accuracy from 60% to 89%. Canopy structure can have a strong influence on spectral variability and the lidar provided complementary information for SAM’s sensitivity to shape but not magnitude of the spectra. Similar approaches to map large regions of drylands with low uncertainty may be readily implemented with unmixing algorithms applied to upcoming space-based imaging spectroscopy and lidar. This study advances our understanding of the nuances associated with mapping xeric and mesic regions, and highlights the importance of incorporating complementary algorithms and sensors to accurately characterize the heterogeneity of dryland ecosystems