Greater Sage-Grouse Brood Responses to Livestock Grazing in Sagebrush Rangelands

The distribution and abundance of the greater sage-grouse (Centrocercus urophasianus; sage-grouse) have declined in the last 60 years. Range contractions and population declines have been attributed to loss and fragmentation of their sagebrush (Artemisia spp.) habitats. Grazing by livestock remains the predominant anthropogenic land-use across sagebrush ecosystems in North America, occurring on 87% of remaining sage-grouse habitat. Most of the peer-reviewed literature reports the potential for negative impacts of sagebrush reduction treatments, to increase livestock forage, on sage-grouse habitat. However, few studies have linked livestock grazing at the landscape level to vital rates (e.g., nest initiation rates, nest success, brood movements, and brood success) for ground-nesting birds such as sage-grouse. We analyzed brood habitat selection of sage-grouse in response to vegetation dynamics and, where possible (DLL), in interaction with livestock grazing to determine whether the relationship between sage-grouse and cattle is competitive or facilitative. This research adds new information to the literature pertaining to the knowledge gap between livestock grazing and whether it is facilitative or competitive with brooding sage-grouse. Our results suggest that the relationship between livestock and sage-grouse might be competitive on the short term but facilitative over longer time scales. These findings indicate that deferred-rest rotational grazing practices may allow for spatio-temporal segregation, enhancing the capacity for sage-grouse to optimize the exploitation of available forage while avoiding direct contact with livestock. Further, our results suggest that livestock grazing could have carry-over effects on vegetation dynamics that may benefit sage-grouse in subsequent seasons, although we did not test this directly; more research is needed to understand the effects of livestock grazing across multiple growing seasons

The Spatial dimensions of control in restricted settings

Ph.D.John Peponi

Impact of an Opioid Harm Reduction Consortium: Emergency and Justice Engagement

Utah State University Extension engaged first responders and law enforcement officials in a consortium to identify local needs related to opioid use disorder (OUD). To this end, the Tooele Opioid Response Network (TORN) conducted three first-responder harm reduction summits to meet local overdose prevention needs. The initiative trained over 200 personnel, which resulted in an 87.5% increase in knowledge related to harm reduction. TORN also facilitated the acquisition of $90,000 in funding for jail-based opioid medication and the disbursement of 400 naloxone kits and training to incarcerated persons at discharge

Experimental observation of polarization-resolved nonlinear Thomson scattering of elliptically polarized light

We report experimental results from a study of nonlinear Thomson scattering of elliptically polarized light. Polarization-resolved radiation patterns of the scattered light are measured as a function of the elliptical polarization state of the incident laser light. The relativistic electron trajectory in intense elliptically polarized fields leads to the formation of unique radiated polarization states, which are observed by our measurements and predicted by a theoretical model. The polarization of Thomson scattered light depends strongly on the intensity of the incident light due to nonlinearity. The results are relevant to high-field electrodynamics and to research and development of light sources with novel capabilities

Simplified risk model for waste management and environmental restoration activities

A Simplified Risk Model (SRM) is being developed to support environmental restoration and waste management (EM) planning activities. The SRM is designed to be able to quantitatively estimate risk for various EM alternatives within hours or days, given limited information about the processes covered within the alternative. The risk model covers radiological, chemical, and industrial risk from both accidents and normal, incident free operations. A simple risk equation is used to model accident risk. Normal, incident free operation risk is modeled using a multiplier on accident risk. Ongoing applications of the SRM are expected to lead to significant improvements to the model in the near future