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- Theses and posters from College of Medicine - Phoenix graduates are now available in the repository. Visit the Scholarly Projects 2019 collection to view this year's submissions.
- Congratulations to Spring 2019 graduates from the Honors College. Honors College Theses from 250 graduates are now available in the repository.
- Sixteen titles from the UA Press Open Arizona collection are now available in the repository. The scholarship "emphasizes the relevance of the southwestern United States to understanding contemporary American life." You can read, browse, and download these books from both the Open Arizona website and from the Open Arizona collection in the repository.
- Congratulations to Spring 2019 graduates in the Master of Landscape Architecture program. Their master's reports are now available in the repository.
Congratulations to Spring 2019 graduates in the Sustainable Built Environments program. Their capstone projects, now available in the repository, focus on sustainable architecture in Tucson.
We're celebrating three years of the UA Open Access Policy! The policy was passed by Faculty Senate in April 2016. Since then, we've made more than 4,500 articles authored by UA faculty, researchers and staff publically available in the repository. Browse these materials and learn how to add your content to the repository.
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Disturbance Ecology in the AnthropoceneWith the accumulating evidence of changing disturbance regimes becoming increasingly obvious, there is potential for disturbance ecology to become the most valuable lens through which climate-related disturbance events are interpreted. In this paper, I revisit some of the central themes of disturbance ecology and argue that the knowledge established in the field of disturbance ecology continues to be relevant to ecosystem management, even with rapid changes to disturbance regimes and changing disturbance types in local ecosystems. Disturbance ecology has been tremendously successful over the past several decades at elucidating the interactions between disturbances, biodiversity, and ecosystems, and this knowledge can be leveraged in different contexts. Primarily, management in changing and uncertain conditions should be focused primarily on the long-term persistence of that native biodiversity that has evolved within the local disturbance regime and is likely to go extinct with rapid changes to disturbance intensity, frequency, and type. Where possible, conserving aspects of natural disturbance regimes will be vital to preserving functioning ecosystems and to that native biodiversity that requires disturbance for its continued existence, though these situations may become more limited over time. Finally, scientists must actively propose management policies that incorporate knowledge of disturbance ecology. Successful policies regarding changing disturbance regimes for biodiversity will not merely be reactive, and will recognize that for natural ecosystems as for human society, not all desired outcomes are simultaneously possible.
Credibility of Convection-Permitting Modeling to Improve Seasonal Precipitation Forecasting in the Southwestern United StatesSub-seasonal to seasonal (S2S) forecasts are critical for planning and management decisions in multiple sectors. This study shows results from dynamical downscaling using a regional climate model at a convection-permitting scale driven by boundary conditions from the global reanalysis of the Climate Forecast System Model (CFSR). Convection-permitting modeling (CPM) enhances the representation of regional climate by better resolving the regional forcings and processes, associated with topography and land cover, in response to variability in the large-scale atmospheric circulation. We performed dynamically downscaled simulations with the Weather Research and Forecasting (WRF) model over the Upper and Lower Colorado basin at 12 km and 3 km grid spacing from 2000 to 2010 to investigate the potential of dynamical downscaling to improved the modeled representation of precipitation the Southwestern United States. Employing a convection-permitting nested domain of 3 km resolution significantly reduces the bias in mean (similar to 2 mm/day) and extreme (similar to 4 mm/day) summer precipitation when compared to coarser domain of 12 km resolution and coarse resolution CFSR products. The convection-permitting modeling product also better represents eastward propagation of organized convection due to mesoscale convective systems at a subdaily scale, which largely account for extreme summer rainfall during the North American monsoon. In the cool season both coarse and high-resolution simulations perform well with limited bias of similar to 1 mm/day for the mean and similar to 2 mm/day for the extreme precipitation. Significant correlation was found (similar to 0.85 for summer and similar to 0.65 for winter) for both coarse and high-resolution model with observed regionally and seasonally averaged precipitation. Our findings suggest that the use of CPM is necessary in a dynamical modeling system for S2S prediction in this region, especially during the warm season when precipitation is mostly convectively driven.
Microbial Community Analyses Inform Geochemical Reaction Network Models for Predicting Pathways of Greenhouse Gas ProductionThe mechanisms, pathways, and rates of CO2 and CH4 production are central to understanding carbon cycling and greenhouse gas flux in wetlands. Thawing permafrost regions are of particular interest because they are disproportionally affected by climate warming and store large reservoirs of organic C that may be readily converted to CO2 and CH4 upon thaw. This conversion is accomplished by a community of microorganisms interacting in complex ways to transform large organic compounds into fatty acids and ultimately CO2 and CH4. While the central role of microbes in this process is well-known, geochemical rate models rarely integrate microbiological information. Herein, we expanded the geochemical rate model of Neumann et al., (2016, Biogeochemistry 127: 57-87) to incorporate a Bayesian probability analysis and applied the result to quantifying rates of CO2, CH4, and acetate production in closed-system incubations of peat collected from three habitats along a permafrost thaw gradient. The goals of this analysis were twofold. First, we integrated microbial community analyses with geochemical rate modeling by using microbial data to inform the best model choice among equally mathematically feasible model variants. Second, based on model results, we described changes in organic carbon transformation among habitats to understand the changing pathways of greenhouse gas production along the permafrost thaw gradient. We found that acetoclasty, hydrogenotrophy, CO2 production, and homoacetogenesis were the important reactions in this system, with little evidence for anaerobic CH4 oxidation. There was a distinct transition in the reactions across the thaw gradient. The collapsed palsa stage presents an initial disequilibrium where the abrupt (physically and temporally) change in elevation introduces freshly fixed carbon into anoxic conditions then fermentation products build up over time as the system transitions through the acid phase and electron acceptors are depleted. In the bog, fermentation slows, while methanogenesis increases. In the fully thawed fen, most of the terminal electron acceptors are depleted and the system becomes increasingly methanogenic. This suggests that as permafrost regions thaw and dry palsas transition into wet fens, CH4 emissions will rise, increasing the warming potential of these systems and accelerating climate warming feedbacks.
Bayesian Markov-Chain Monte Carlo Inversion of Low-Temperature Thermochronology Around Two 8 − 10 m Wide Columbia River Flood Basalt DikesFlood basalt volcanism involves large volumes of magma emplaced into the crust and surface environment on geologically short timescales. The mechanics of flood basalt emplacement, including dynamics of the crustal magma transport system and the tempo of individual eruptions, are not well-constrained. Here we study two exhumed dikes from the Columbia River Flood Basalt province in northeast Oregon, USA, using apatite and zircon (U-Th)/He thermochronology to constrain dike emplacement histories. Sample transects perpendicular to the dike margins document transient heating of granitic host rocks. We model heating as due to dike emplacement, considering a thermal model with distinct melt-fraction temperature relationships for basaltic magma and granitic wallrock, and a parameterization of unsteady flow within the dike. We model partial resetting of thermochronometers by considering He diffusion in spherical grains as a response to dike heating. A Bayesian Markov-Chain Monte Carlo framework is used to jointly invert for six parameters related to dike emplacement and grain-scale He diffusion. We find that the two dikes, despite similar dimensions on an outcrop scale, exhibit different spatial patterns of thermochronometer partial resetting away from the dike. These patterns predict distinct emplacement histories. We extend previousmodeling of a presumed feeder dike atMaxwell Lake in theWallowaMountains of northeastern Oregon, finding posterior probability distribution functions (PDFs) that predict steady heating from sustained magma flow over 1-6 years and elevated farfield host rock temperatures. This suggests regional-scale heating in the vicinity of Maxwell Lake, which might arise from nearby intrusions. The other dike, within the Cornucopia subswarm, is predicted to have a 1-4 year thermally active lifespan with an unsteady heating rate suggestive of lowmagma flow rate compared to Maxwell Lake, in a cool near-surface thermal environment. In both cases, misfit of near-dike partial resetting of thermochronometers by models suggests either heat transfer via fluid advection in host rocks or pulsed magma flow in the dikes. Our results highlight the diversity of dike emplacement histories within the Columbia River Flood Basalt province and the power of Bayesian inversion methods for quantifying parameter trade-offs and uncertainty in thermal models.
The CAT Vehicle Testbed: A Simulator with Hardware in the Loop for Autonomous Vehicle ApplicationsThis paper presents the CAT Vehicle (Cognitive and Autonomous Test Vehicle) Testbed: a research testbed comprised of a distributed simulation-based autonomous vehicle, with straightforward transition to hardware in the loop testing and execution, to support research in autonomous driving technology. The evolution of autonomous driving technology from active safety features and advanced driving assistance systems to full sensor-guided autonomous driving requires testing of every possible scenario. However, researchers who want to demonstrate new results on a physical platform face difficult challenges, if they do not have access to a robotic platform in their own labs. Thus, there is a need for a research testbed where simulation-based results can be rapidly validated through hardware in the loop simulation, in order to test the software on board the physical platform. The CAT Vehicle Testbed offers such a testbed that can mimic dynamics of a real vehicle in simulation and then seamlessly transition to reproduction of use cases with hardware. The simulator utilizes the Robot Operating System (ROS) with a physics-based vehicle model, including simulated sensors and actuators with configurable parameters. The testbed allows multi-vehicle simulation to support vehicle to vehicle interaction. Our testbed also facilitates logging and capturing of the data in the real time that can be played back to examine particular scenarios or use cases, and for regression testing. As part of the demonstration of feasibility, we present a brief description of the CAT Vehicle Challenge, in which student researchers from all over the globe were able to reproduce their simulation results with fewer than 2 days of interfacing with the physical platform.