Global tree-ring response and inferred climate variation following the mid-thirteenth century Samalas eruption

The largest explosive volcanic eruption of the Common Era in terms of estimated sulphur yield to the stratosphere was identified in glaciochemical records 40 years ago, and dates to the mid-thirteenth century. Despite eventual attribution to the Samalas (Rinjani) volcano in Indonesia, the eruption date remains uncertain, and the climate response only partially understood. Seeking a more global perspective on summer surface temperature and hydroclimate change following the eruption, we present an analysis of 249 tree-ring chronologies spanning the thirteenth century and representing all continents except Antarctica. Of the 170 predominantly temperature sensitive high-frequency chronologies, the earliest hints of boreal summer cooling are the growth depressions found at sites in the western US and Canada in 1257 CE. If this response is a result of Samalas, it would be consistent with an eruption window of circa May–July 1257 CE. More widespread summer cooling across the mid-latitudes of North America and Eurasia is pronounced in 1258, while records from Scandinavia and Siberia reveal peak cooling in 1259. In contrast to the marked post-Samalas temperature response at high-elevation sites in the Northern Hemisphere, no strong hydroclimatic anomalies emerge from the 79 precipitation-sensitive chronologies. Although our findings remain spatially biased towards the western US and central Europe, and growth-climate response patterns are not always dominated by a single meteorological factor, this study offers a global proxy framework for the evaluation of paleoclimate model simulations.

Wine market segmentation by age generations in the Western US: expectations after the COVID-19 pandemic

Purpose The purpose of this paper is to investigate if differences exist between the four wine-consuming generations in wine purchasing behavior, the desirability of wine attributes when making a purchase decision and information sources used. It examines if generational market segmentation is an actionable and valuable strategy for the wine industry. Generation Z, Millennials, Generation X and Baby-Boomers are the four generations examined. This research also investigates if the generations behaved differently concerning wine consumption during the COVID-19 pandemic. Further, expectations concerning future wine purchasing behavior are examined. Design/methodology/approach An online survey was conducted between April 29, 2020 and May 7, 2020, with a sample size of 944 consumers from Western US States (California, Washington, Idaho, Oregon and Nevada). One-way analysis of variance technique and Chi-square tests were used to examine differences. Findings Segmentation by generation is appropriate when creating products, pricing, determining channels of distribution and creating messaging for a specific wine brand. The COVID-19 pandemic caused channel shifting that is expected to continue after the pandemic. Originality/value This is the second academic paper that examines differences in wine purchasing behavior between generations including Generation Z and the only study that examines the purchasing behavior changes and expectations for the future by generation concerning the COVID-19 pandemic. Research limitations/implications A national survey should be conducted to confirm that the results from the sample that was mostly from California and neighboring states reflect the national wine consumer in the USA. Practical implications The research identifies the products, prices, channels of distribution and messaging that are appropriate to target each generation.

The Ethnographic Vignette as Innovative Tool in Intersectional Social Justice Activist Research

This chapter leverages ethnographic narratives written during the author's year of nearly daily ‘walking tourism' in New York City on the heels of 9/11 as a vehicle to illustrate an innovative approach to community-based research for intersectional social justice purposes. Since the 1990s, the author has employed creatively crafted vignettes as an activist researcher working with alliances of racial, gender, queer, economic, and labor organizations that joined together to conduct progressive intersectional social justice interventions in a conservative Western US state. Here the author extracts pieces of her “New York Stories” for use as vignettes that could be employed in practice-based research as discussion prompts to foster restorative dialogue and participatory action research efforts in community groups and organizations committed to the work of intersectional social justice.

Pattern-based downscaling of snowpack variability in the western United States

The decline in snowpack across the western United States is one of the most pressing threats posed by climate change to regional economies and livelihoods. Earth system models are important tools for exploring past and future snowpack variability, yet their coarse spatial resolutions distort local topography and bias spatial patterns of accumulation and ablation. Here, we explore pattern-based statistical downscaling for spatially-continuous interannual snowpack estimates. We find that a few leading patterns capture the majority of snowpack variability across the western US in observations, reanalyses, and free-running simulations. Pattern-based downscaling methods yield accurate, high resolution maps that correct mean and variance biases in domain-wide simulated snowpack. Methods that use large-scale patterns as both predictors and predictands perform better than those that do not and all are superior to an interpolation-based “delta change” approach. These findings suggest that pattern-based methods are appropriate for downscaling interannual snowpack variability and that using physically meaningful large-scale patterns is more important than the details of any particular downscaling method.

Genomic Evaluation of the Genus Coltivirus Indicates Genetic Diversity among Colorado Tick Fever Virus Strains and Demarcation of a New Species

The type species of the genus Coltivirus, Colorado tick fever virus (CTFV), was discovered in 1943 and is the most common tick-borne viral infection in the Western US. Despite its long history, very little is known about the molecular diversity of viruses classified within the species Colorado tick fever coltivirus. Previous studies have suggested genetic variants and potential serotypes of CTFV, but limited genetic sequence information is available for CTFV strains. To address this knowledge gap, we report herein the full-length genomes of five strains of CTFV, including Salmon River virus and California hare coltivirus (CTFV-Ca). The sequence from the full-length genome of Salmon River virus identified a high genetic identity to the CTFV prototype strain with >90% amino acid identity in all the segments except segment four, suggesting Salmon River virus is a strain of the species Colorado tick fever coltivirus. Additionally, analysis suggests that segment four has been associated with reassortment in at least one strain. The CTFV-Ca full-length genomic sequence was highly variable from the prototype CTFV in all the segments. The genome of CTFV-Ca was most similar to the Eyach virus, including similar segments six and seven. These data suggest that CTFV-Ca is not a strain of CTFV but a unique species. Additional sequence information of CTFV strains will improve the molecular surveillance tools and provide additional taxonomic resolution to this understudied virus.

SnowClim v1.0: High-resolution snow model and data for the western United States

Seasonal snowpack dynamics shape the biophysical and societal characteristics of many global regions. However, snowpack accumulation and duration have generally declined in recent decades largely due to anthropogenic climate change. Mechanistic understanding of snowpack spatiotemporal heterogeneity and climate change impacts will benefit from snow data products that are based on physical principles, that are simulated at high spatial resolution, and that cover large geographic domains. Existing datasets do not meet these requirements, hindering our ability to understand both contemporary and changing snow regimes and to develop adaptation strategies in regions where snowpack patterns and processes are important components of Earth systems. We developed a computationally efficient physics-based snow model, SnowClim, that can be run in the cloud. The model was evaluated and calibrated at Snowpack Telemetry sites across the western United States (US), achieving a site-median root mean square error for daily snow water equivalent of 62 mm, bias in peak snow water equivalent of −9.6 mm, and bias in snow duration of 1.2 days when run hourly. Positive biases were found at sites with mean winter temperature above freezing where the estimation of precipitation phase is prone to errors. The model was applied to the western US using newly developed forcing data created by statistically downscaling pre-industrial, historical, and pseudo-global warming climate data from the Weather Research and Forecasting (WRF) model. The resulting product is the SnowClim dataset, a suite of summary climate and snow metrics for the western US at 210 m spatial resolution (Lute et al., 2021). The physical basis, large extent, and high spatial resolution of this dataset will enable novel analyses of changing hydroclimate and its implications for natural and human systems.

Mountain Pine Beetle Impacts on Health through Lost Forest Air Pollutant Sinks

The mountain pine beetle (MPB) destroys millions of coniferous trees annually throughout Western US forests. Coniferous forests are important air pollutant sinks, removing pollutants from the air such as PM2.5 (particulate matter < 2.5 μm in diameter), O3 (ozone), SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and CO (carbon monoxide). In this paper, US Forest Service data on MPB tree mortality in the Western US is combined with a forest air pollution model (i-Tree Eco) and standard health impact functions to assess the human mortality and morbidity impacts of MPB-induced tree mortality. Modeling results suggest considerable spatial and temporal heterogeneity of impacts across the Western US. On average, MPB is associated with 10.0–15.7 additional deaths, 6.5–40.4 additional emergency room (ER) visits, and 2.2–10.5 additional hospital admissions per year over 2005–2011 due to lost PM2.5 sinks. For every 100 trees killed by MPB, the average PM2.5 mortality health costs are $418 (2019$). Impacts on other criteria pollutants are also estimated. Several sensitivity checks are performed on model inputs. These results have important policy implications for MPB management and on our understanding of the complex couplings between forest pests, forest health, and human health.

Asthma exacerbation due to climate change-induced wildfire smoke in the Western US

Climate change and human activities have drastically altered the natural wildfire balance in the Western US and increased population health risks due to exposure to pollutants from fire smoke. Using dynamically downscaled climate model projections, we estimated additional asthma emergency room visits and hospitalizations due to exposure to smoke fine particulate matter (PM2.5) in the Western US in the 2050s. Isolating the amount of PM2.5 from wildfire smoke is both difficult to estimate and, thus, utilized by relatively few studies. In this study, we use a sophisticated modeling approach to estimate future increase in wildfire smoke exposure over the reference period (2003-2010) and subsequent health care burden due to asthma exacerbation. Average increases in smoke PM2.5 during future fire season ranged from 0.05-9.5 µg/m3 with the highest increases seen in Idaho, Montana, and Oregon. Using the Integrated Climate and Land-Use Scenarios (ICLUS) A2 scenario, we estimated the smoke-related asthma events could increase at a rate of 15.1 visits per 10,000 persons in the Western US, with the highest rates of increased asthma (25.7-41.9 per 10,000) in Idaho, Montana, Oregon, and Washington. Finally, we estimated healthcare costs of smoke-induced asthma exacerbation to be over $1.5 billion during a single future fire season. Here we show the potential future health impact of climate-induced wildfire activity, which may serve as a key tool in future climate change mitigation and adaptation planning.

Forest fires and climate-induced tree range shifts in the western US

Due to climate change, plant populations experience environmental conditions to which they are not adapted. Our understanding of the next century’s vegetation geography depends on the distance, direction, and rate at which plant distributions shift in response to a changing climate. In this study we test the sensitivity of tree range shifts (measured as the difference between seedling and mature tree ranges in climate space) to wildfire occurrence, using 74,069 Forest Inventory Analysis plots across nine states in the western United States. Wildfire significantly increased the seedling-only range displacement for 2 of the 8 tree species in which seedling-only plots were displaced from tree-plus-seedling plots in the same direction with and without recent fire. The direction of climatic displacement was consistent with that expected for warmer and drier conditions. The greater seedling-only range displacement observed across burned plots suggests that fire can accelerate climate-related range shifts and that fire and fire management will play a role in the rate of vegetation redistribution in response to climate change.