Search for: All records

In recent years, discussions comparing high-threshold and continuous accounts of recognition-memory judgments have increasingly turned their attention toward critical testing. One of the de ning features of this approach is its requirement for the relationship between theoretical assumptions and predictions to be laid out in a transparent and precise way. One of the (fortunate) consequences of this requirement is that it encourages researchers to debate the merits of the different assumptions at play. The present work addresses a recent attempt to overturn the dismissal of high-threshold models by getting rid of a background selective- in uence assumption. However, it can be shown that the contrast process proposed to explain this violation undermines a more general assumption that we dubbed“single-item generalization.” We argue that the case for the dismissal of these assumptions and the claimed support for the proposed high-threshold contrast account does not stand the scrutiny of their theoretical properties and empirical implications. 

From June 10-13 of 2022, an atmospheric river delivered heavy rain to high elevations around northern Yellowstone National Park (YNP), resulting in extreme flooding in the Yellowstone River basin below Yellowstone Lake. The extreme 2022 flood was only one of several historical events caused by high June temperatures and rapid snowmelt, with a variable component of rain on snow. Large and extreme floods on the Yellowstone River (YR) also occurred in June 1996 and 1918, allowing comparison of their magnitude, duration, and mechanisms of generation for the YR and its Lamar River and Soda Butte Creek tributaries. In 2022, peak discharge on the YR at Corwin Springs was 1550 m3/s, the flood of record and 170% of the 1996 peak, and Lamar River peak discharge was 172% of 1996 peak. In 1918, gaged discharge is only available for the YR at Corwin Springs, with significant uncertainty. On Soda Butte Creek, however, overbank gravels and indirect discharge estimates indicate that the 1918 peak discharge was conservatively 240% higher than 1996 and 127% higher than 2022. In 2022, flood duration above 700 m3/s at the YR Corwin Springs gage was only 2 days, compared to 9 days in 1996 and 14 days in 1918. In early June 1918 and 1996, snowpack was above average, and anomalously warm weather combined with relatively minor rainfall to produce long-duration flooding. In early June 2022, similarly high temperatures occurred, but snowpack was less than in 1918; early May snowpack in 2022 was 64% that of 1996. The June 10-13 atmospheric river released 5-10 cm of rain across northern YNP that added to snowmelt, producing a short duration but extremely high peak discharge. The 2022 flood caused major bank erosion especially in confined reaches but resulted in less floodplain disruption and overbank gravel deposition than in 1918 on the Lamar River and Soda Butte Creek. The potential exists for an even larger peak discharge than in 2022 if atmospheric river rainfall as in 2022 is superimposed on rapid melting of a deep snowpack, caused by the kind of unseasonable warmth that occurred in 1997 and 1918. Anthropogenic climate change is likely to increase the probability of extreme floods in YNP, as higher temperatures increase snowmelt rates, shift late-spring precipitation from snow to rain, and promote widespread intense rainfall including that from atmospheric rivers. 

Abstract We develop alternative families of Bayes factors for use in hypothesis tests as alternatives to the popular default Bayes factors. The alternative Bayes factors are derived for the statistical analyses most commonly used in psychological research – one-sample and two-samplet tests, regression, and ANOVA analyses. They possess the same desirable theoretical and practical properties as the default Bayes factors and satisfy additional theoretical desiderata while mitigating against two features of the default priors that we consider implausible. They can be conveniently computed via an R package that we provide. Furthermore, hypothesis tests based on Bayes factors and those based on significance tests are juxtaposed. This discussion leads to the insight that default Bayes factors as well as the alternative Bayes factors are equivalent to test-statistic-based Bayes factors as proposed by Johnson.Journal of the Royal Statistical Society Series B: Statistical Methodology,67, 689–701. (2005). We highlight test-statistic-based Bayes factors as a general approach to Bayes-factor computation that is applicable to many hypothesis-testing problems for which an effect-size measure has been proposed and for which test power can be computed. 

In June of 2022 an extreme atmospheric river flood caused extensive bank erosion and infrastructure damage in northern Yellowstone National Park (YNP). On the lower Lamar River, peak discharge was 170% of the next highest peak of 1996 (gaged since 1923) and resulted in widespread overbank gravel deposition and channel change. In June 1918, however, flooding on the Lamar system produced similar peak flows, as shown by indirect discharge estimates and tree-ring dating. In 2022, peak discharges and flood effects varied considerably in northern YNP. The upper Lamar River had a peak discharge significantly less than 1918, likely the result of less precipitation and snowmelt in the relatively low elevations of the upper Lamar drainage in the Absaroka Range. The high flows experienced by the lower Lamar River, however, were the result of extreme discharges in tributaries that drain the Beartooth Range where Soda Butte Creek and Pebble Creek had discharges similar or greater than 1918 and discharge on Slough Creek produced extensive mid channel bar deposition greater than 2 m. In western YNP, the Gallatin River experienced little bank erosion or bed material transport, although some reaches showed minor channel scour and gravel bar deposition on glacial outwash substrates. In central YNP, the Gardiner River experienced minimal bank erosion on upper reaches, however, there was extensive bank erosion, landslides, and sediment deposition in the Gardner River Canyon where the steep, confined channel focused stream power along the valley margins. Flood magnitudes differed markedly between the Gallatin and Beartooth drainages despite similar amounts of rainfall and snowmelt. The Gallatin River drainage, dominated by highly fractured and macroporous limestone and extensive thick colluvium with gentler range flanks allows for greater infiltration and reduced peak flows. In contrast, basins in the Beartooth Range drain steeper slopes of low-permeability laharic volcaniclastic rocks, with more exposed bedrock and relief up to 900 m, which promotes rapid runoff and extreme flooding. The frequency and magnitude of rain-on-snow floods is likely increasing in YNP because of anthropogenic warming, as the high-elevation snowpack becomes more susceptible to rapid melting and late spring precipitation shifts from snow to rain. 

Abstract BackgroundThe global human footprint has fundamentally altered wildfire regimes, creating serious consequences for human health, biodiversity, and climate. However, it remains difficult to project how long-term interactions among land use, management, and climate change will affect fire behavior, representing a key knowledge gap for sustainable management. We used expert assessment to combine opinions about past and future fire regimes from 99 wildfire researchers. We asked for quantitative and qualitative assessments of the frequency, type, and implications of fire regime change from the beginning of the Holocene through the year 2300. ResultsRespondents indicated some direct human influence on wildfire since at least ~ 12,000 years BP, though natural climate variability remained the dominant driver of fire regime change until around 5,000 years BP, for most study regions. Responses suggested a ten-fold increase in the frequency of fire regime change during the last 250 years compared with the rest of the Holocene, corresponding first with the intensification and extensification of land use and later with anthropogenic climate change. Looking to the future, fire regimes were predicted to intensify, with increases in frequency, severity, and size in all biomes except grassland ecosystems. Fire regimes showed different climate sensitivities across biomes, but the likelihood of fire regime change increased with higher warming scenarios for all biomes. Biodiversity, carbon storage, and other ecosystem services were predicted to decrease for most biomes under higher emission scenarios. We present recommendations for adaptation and mitigation under emerging fire regimes, while recognizing that management options are constrained under higher emission scenarios. ConclusionThe influence of humans on wildfire regimes has increased over the last two centuries. The perspective gained from past fires should be considered in land and fire management strategies, but novel fire behavior is likely given the unprecedented human disruption of plant communities, climate, and other factors. Future fire regimes are likely to degrade key ecosystem services, unless climate change is aggressively mitigated. Expert assessment complements empirical data and modeling, providing a broader perspective of fire science to inform decision making and future research priorities.