The first reported case of COVID-19 in Tennessee (TN) occurred on March 5, 2020, growing to 580,809 cases state-wide by the end of 2020. A GIS dashboard was developed using data from the TN Department of Health to communicate state-wide COVID-19 spread, and a relationship between pandemic development and rurality was observed during the first wave (through September 2020), noted in other US and global research. Because > 90% of TN counties are designated rural or mixed-rural, we examined metrics to describe development as it relates to rurality. Metrics included days to the first case/hospitalization/fatality, days between state and county peak, and days to an incidence rate of ten per 100,000. Metrics were compared within different classes of rurality, using seven rurality classification schemes. Significant differences were noted in four of the five metrics between classes of rurality. Rural counties in TN experienced significant lags to the first case, hospitalization, and fatality, and the peak cases in rural counties were delayed relative to urban counties when outlier counties with early state prison outbreaks were excluded. In rural TN counties, regardless of rurality definition, cases, hospitalizations, and fatalities were slower to appear. However, once community spread was established, rurality no longer had a protective effect.

The Priority Risk Index is increasingly used as a methodology for quantifying jurisdictional risk for hazard mitigation planning purposes, and it can evolve to meet specific community needs. The index incorporates probability, impact, spatial extent, warning time, and duration when assessing each hazard, but it does not explicitly integrate a vulnerability and consequence analysis into its final scoring. To address this gap, a new index was developed- the Enhanced Priority Risk Index (EPRI). The new index adds a sixth category, vulnerability, calculated from a vulnerability and consequence analysis of the impacts on seven sectors identified in Standard 4.1.2 of the Emergency Management Accreditation Program (EMAP). To obtain a vulnerability score, impacts are ranked by sector from low (1) to very high (4), then a weighting factor is applied to each sector. The vulnerability score is added to the EPRI and provides risk levels based on the number of exploitable weaknesses and countermeasures identified within a specific jurisdiction. The vulnerability score and resulting EPRI are scalable and can be applied across jurisdictions, providing a transferable methodology that improves the hazard identification and risk assessment process and provides an approach for meeting EMAP accreditation standards.

Sinking Creek (HUC 06010103046), in the Watauga watershed of northeast Tennessee, is impaired due to Escherichia coli. To assess how E. coli and other water quality parameters fluctuated during storm events, water samples were collected with automated samplers during eight storms at two locations: Sinking Creek and a feeder spring. Turbidity and electrical conductivity data loggers were deployed in the creek, and dissolved oxygen (DO) was measured in situ. The presence of optical brighteners, used in detergents and an indicator of residential wastewater, was assessed using cotton fabric deployed at both sites and analyzed by an external laboratory. The Colilert Quanti-Tray method was used to process water samples for E. coli. Relationships between water quality parameters and lagged precipitation were assessed using cross-correlation. At the creek, E. coli and turbidity increased within 2 h of precipitation, exceeding the single sample water quality standard of 941 cfu 100 ml−1 during the storm. At the spring, E. coli became elevated more quickly than at the stream, within 30 min of precipitation, and decreased below the standard during the event. Electrical conductivity decreased within 1.5 h of the storm at the creek, and DO levels were higher at the creek than at the spring. Optical brightener analysis indicated possible presence of residential wastewater during one of two sampled storms. Targeted sampling and dye tracing are recommended to validate this hypothesis. These results may be used to inform field methods in similar storm sampling studies and will be useful in watershed restoration efforts in Sinking Creek.

A common concern about volcanic unrest is that the communication of information about increasing volcanic alert levels (VALs) to the public could cause serious social and economic impacts even if an eruption does not occur. To test this statement, this study examined housing prices and business patterns from 1974–2016 in volcanic regions with “very-high” threat designations from the U.S. Geological Survey (USGS)—Long Valley Caldera (LVC), CA (caldera); Mount St. Helens (MSH), Washington (stratovolcano); and Kīlauea, Hawaiʻi (shield volcano). To compare economic trends in nonvolcanic regions that are economically dependent on tourism, Steamboat Springs, CO, served as a control as it is a ski-tourism community much like Mammoth Lakes in LVC. Autoregressive distributed lag (ARDL) models predicted that housing prices were negatively affected by VALs at LVC from 1982–1983 and 1991–1997. While VALs associated with unrest and eruptions included in this study both had short-term indirect effects on housing prices and business indicators (e.g., number of establishments, employment, and salary), these notifications were not strong predictors of long-term economic trends. Our findings suggest that these indirect effects result from both eruptions with higher level VALs and from unrest involving lower-level VAL notifications that communicate a change in volcanic activity but do not indicate that an eruption is imminent or underway. This provides evidence concerning a systemic issue in disaster resilience. While disaster relief is provided by the U.S. federal government for direct impacts associated with disaster events that result in presidential major disaster declarations, there is limited or no assistance for indirect effects to businesses and homeowners that may follow volcanic unrest with no resulting direct physical losses. The fact that periods of volcanic unrest preceding eruption are often protracted in comparison to precursory periods for other hazardous events (e.g., earthquakes, hurricanes, flooding) makes the issue of indirect effects particularly important in regions susceptible to volcanic activity.

Caldera systems such as Long Valley Caldera, California; Taupo, New Zealand; and Campi Flegrei, Italy, experience centuries to millennia without eruption, but have the potential for large eruptions. This raises questions about how local residents' behavioral responses to these low-probability high-consequence events differ from their responses to events, such as wildfires and earthquakes, that have higher probabilities. To examine this issue, a multi-hazard mail survey of 229 households explored perceptions of—and responses to—volcano, earthquake and wildfire hazards in the Long Valley Volcanic Region. Response efficacy was the only significant predictor of emergency preparedness, which suggests that hazard managers can increase household emergency preparedness by emphasizing this attribute of protective actions. In addition to response efficacy, expected personal consequences, hazard intrusiveness, and affective responses were all significantly related to information seeking. This indicates that hazard managers can also increase households’ information seeking about local hazards and appropriate protective actions by communicating the certainty and severity of hazard impacts (thus increasing expected personal consequences) and that they communicate this information repeatedly (thus increasing hazard intrusiveness) to produce significant emotional involvement (thus increasing affective response).

This observational study was conducted to evaluate the anatomic relationship between the proximocaudal femoral joint capsule insertion and the femoral caudolateral curvilinear osteophyte (CCO), across ancient and modern domestic and non-domestic canids. Museum specimens of proximal femora were screened for presence of remnant enthesophytes of the caudal joint capsule insertion (first inclusion criterion) and then for the CCO (second inclusion criterion). The initially screened population included 267 dry bone specimens: Six Canis species, hybrid coyote × domestic dog, and five vulpines (three Vulpes species, one Urocyon, and one Nyctereutes). Proximocaudal joint capsule insertion remnant enthesophytes were limiting at n = 19 specimens: Seven ancient domestic dogs, four modern coyotes, two ancient coyotes, two modern hybrid coyote × dog, two modern red foxes, and two modern raccoon dogs. The joint capsule enthesophytes are associated with inflammation, but are observed far less frequently than the CCO. The CCO is seen radiographically but is visible more frequently by direct inspection. The primary inclusion criterion necessarily was a visible caudal joint capsule insertion; spatial relationships of the CCO can be assigned with confidence only when a capsule insertion line can be recognized clearly. We demonstrate that the anatomic CCO associates with the joint capsule insertion being nonspecific and species-independent. A joint capsule insertion-CCO spatial relationship across species is an important new observation, strongly indicating that both are pathological features. Our data indicate need for new research to characterize the canid coxofemoral joint and its overt and incipient pathology in a phylogenetic context. Anat Rec, 302:2164–2170, 2019.

Mitigation: Mechanics, Monitoring, Modeling, and Assessment - Proceedings of the 7th International Conference on Debris-Flow Hazards Mitigation. All rights reserved. Debris-slides are a frequent hazard in fragile decomposed metasedimentary rocks in the Anakeesta rock formation in Great Smoky Mountain National Park. The spatial distribution of an existing debris-slide area could be used to prepare susceptibility map for future debris-slide initiation zones. This work aims to create a debris-slide susceptibility map by using a knowledge-driven method in a GIS platform in Anakeesta formation of Great Smoky Mountain National Park. Six geofactors, namely, elevation, annual rainfall, slope curvature, landcover, soil texture and various slope failure modes were used to create the susceptibility map. Debris-slide locations were mapped from the satellite imagery, previous studies, and field visits. A Weighted Overlay Analysis was performed in order to generate the final susceptibility map, where individual classes of geofactors were ranked and were assigned weights based on their influence on debris-slide. The final susceptibility map was classified into five categories: very low, low, moderate, high and very high susceptible zones. Validation of the result shows very high category predicted ~10%, high and moderate categories predicted 75.5% and ~14.5% of the existing debris-slide pixels respectively. This study successfully depicts the advantage and usefulness of the knowledge-driven method, which can save considerable amount of time and reduce complicated data analysis unlike statistical or physical based methods. However, the accuracy of the model highly depends on the researcher’s experience of the area and selection of respective geofactors.

Few studies utilise modern species distribution data and modeling to make predictions for examining potential fossil localities. Instead, species distribution modeling is often used for palaeoenvironmental interpretations. Using palaeoclimate data to model potential past distributions for a species provides a prediction showing areas where its fossil remains may be found. In this study, the current, Last Glacial Maximum, and Last Interglacial potential distributions of the arid steppe-obligate saiga antelope (Artiodactyla: Bovidae, Saiga tatarica) were modeled using the species distribution model Maxent. Few fossil records exist, but available fossil locality records were used to validate both palaeo models, resulting in speculative predictions about where the saiga may have lived. Known fossil localities of saiga from the Last Glacial Maximum time period were located within predicted moderately suitable environments, while four of seven Last Interglacial fossil localities were located within predicted moderately suitable environments, suggesting that models can accurately identify areas where fossils for the saiga can be found. Specifically, these models suggest saiga fossils may be located in northwestern and northeastern China, the western and central regions of the Middle East, and southern Alaska. The predicted areas in northeastern China are of particular interest because saiga fossils have not been identified in this region, but some palaeontologists theorize that northeast China may have been suitable for saiga in the past. The models lend credence to this argument.

Through the Cenozoic, paleoclimate records show general trends of global cooling and increased aridity, and environments in North America shifted from predominantly forests to more open habitats. Paleobotanical records indicate grasses were present on the continent in the Eocene; however, paleosol and phytolith studies indicate that open habitats did not arise until the late Eocene or even later in the Oligocene. Studies of large mammalian herbivores have documented changes in ecomorphology and community structure through time, revealing that shifts in mammalian morphology occurred millions of years after the environmental changes thought to have triggered them. Smaller mammals, like rodents and lagomorphs, should more closely track climate and habitat changes due to their shorter generation times and smaller ranges, but these animals have received much less study. To examine changes in smaller mammals through time, we have assembled and analyzed an ecomorphological database of all North American rodent and lagomorph species. Analyses of these data found that rodent and lagomorph community structure changed dramatically through the Cenozoic, and shifts in diversity and ecology correspond closely with the timing of habitat changes. Cenozoic rodent and lagomorph species diversity is strongly biased by sampling of localities, but sampling-corrected diversity reveals diversity dynamics that, after an initial density-dependent diversification in the Eocene, track habitat changes and the appearance of new ecological adaptations. As habitats became more open and arid through time, rodent and lagomorph crown heights increased while burrowing, jumping, and cursorial adaptations became more prevalent. Through time, open-habitat specialists were added during periods of diversification, while closed-habitat taxa were disproportionately lost in subsequent diversity declines. While shifts among rodents and lagomorphs parallel changes in ungulate communities, they started millions of years earlier than in larger mammals. This is likely a consequence of the smaller mammal' greater sensitivity to environmental changes and more rapid evolution. These results highlight the importance of examining understudied members of vertebrate faunas for understanding the evolution of terrestrial communities through time.

Electromagnetic induction (EMI) has been used in archaeology for decades, but still lags in use and development when compared to magnetometry and ground-penetrating radar. While it has become more popular than electrical resistivity area survey, it is now less commonly used than electrical resistivity tomography. The EMI method is likely underutilized due to drift problems and a lack of multi-sensor, vehicle-towed systems capable of rapid, high-density data collection. In this article we demonstrate not only the effectiveness of EMI survey, but a case where entire villages would have remained undetected without it. At the Singer-Hieronymus Site in central Kentucky, USA, a vehicle-towed frequency domain EMI survey detected the location of plazas, residential areas, and trash disposal areas across multiple Fort Ancient villages that contained both intact and heavily disturbed deposits. Additionally, three new villages were revealed. Through this process, we discovered how Fort Ancient village dynamics may be studied through a geophysical investigation of village shape, size, and spatial organization.