Anthropogenic resource subsidization across western ecosystems has contributed to widespread increases in generalist avian predators, including common ravens (Corvus corax; hereafter, raven). Ravens ...are adept nest predators and can negatively impact species of conservation concern. Predation effects from ravens are especially concerning for greater sage‐grouse (Centrocercus urophasianus; hereafter, sage‐grouse), which have experienced prolonged population decline. Our objectives were to quantify spatiotemporal patterns in raven density, evaluate sage‐grouse nest success concurrent with fluctuating raven densities, and demonstrate a spatially explicit decision support tool to guide management applications to appropriate conflict areas. We combined ~28,000 raven point count surveys with data from more than 900 sage‐grouse nests between 2009 and 2019 within the Great Basin, USA. We modeled variation in raven density using a Bayesian hierarchical distance sampling approach with environmental covariates on detection and abundance. Concurrently, we modeled sage‐grouse nest survival using a hierarchical frailty model as a function of raven density and other environmental covariates that influence the risk of nest failure. Raven density commonly exceeded 0.5 ravens km−2 and increased at low elevations with more anthropogenic development and/or agriculture. Reduced sage‐grouse nest survival was strongly associated with elevated raven density (e.g., >0.5 ravens km−2) and varied with topographic ruggedness, shrub cover, and burned areas. For conservation application, we developed a spatially explicit planning tool that predicts nest survival under current and reduced raven numbers within the Great Basin to help direct management actions to localized areas where sage‐grouse nests are at highest risk of failure. Our modeling framework can be generalized to multiple species where spatially registered abundance and demographic data are available.
A
bstract
The full data set of the Daya Bay reactor neutrino experiment is used to probe the effect of the charged current non-standard interactions (CC-NSI) on neutrino oscillation experiments. Two ...different approaches are applied and constraints on the corresponding CC-NSI parameters are obtained with the neutrino flux taken from the Huber-Mueller model with a 5% uncertainty. For the quantum mechanics-based approach (QM-NSI), the constraints on the CC-NSI parameters
ϵ
eα
and
ϵ
eα
s
are extracted with and without the assumption that the effects of the new physics are the same in the production and detection processes, respectively. The approach based on the weak effective field theory (WEFT-NSI) deals with four types of CC-NSI represented by the parameters
ε
X
eα
. For both approaches, the results for the CC-NSI parameters are shown for cases with various fixed values of the CC-NSI and the Dirac CP-violating phases, and when they are allowed to vary freely. We find that constraints on the QM-NSI parameters
ϵ
eα
and
ϵ
eα
s
from the Daya Bay experiment alone can reach the order
O
(0.01) for the former and
O
(0.1) for the latter, while for WEFT-NSI parameters
ε
X
eα
, we obtain
O
(0.1) for both cases.
The Daya Bay experiment uses reactor antineutrino disappearance to measure the θ13 neutrino oscillation parameter. In this proceeding, the convolutional autoencoder machine learning technique is ...tested against a well-understood uncorrelated accidental background. The eventual goal for this technique is to reduce the background with the largest contribution to the rate uncertainty in the antineutrino data set, β-n decay of 9Li produced by cosmic-ray muons.
In recent decades, feral horse (Equus caballus; horse) populations increased in sagebrush (Artimesia spp.) ecosystems, especially within the Great Basin, to the point of exceeding maximum appropriate ...management levels (AMLmax), which were set by land administrators to balance resource use by feral horses, livestock, and wildlife. Concomitantly, greater sage-grouse (Centrocercus urophasianus; sage-grouse) are sagebrush obligates that have experienced population declines within these same arid environments as a result of steady and continued loss of seasonal habitats. Although a strong body of research indicates that overabundant populations of horses degrade sagebrush ecosystems, empirical evidence linking horse abundance to sage-grouse population dynamics is missing. Within a Bayesian framework, we employed state-space models to estimate population rate of change (λ) using 15 years (2005–2019) of count surveys of male sage-grouse at traditional breeding grounds (i.e., leks) as a function of horse abundance relative to AMLmax and other environmental covariates (e.g., wildfire, precipitation, % sagebrush cover). Additionally, we employed a post hoc impact-control design to validate existing AMLmax values as related to sage-grouse population responses, and to help control for environmental stochasticity and broad-scale oscillations in sage-grouse abundance. On average, for every 50% increase in horse abundance over AMLmax, our model predicted an annual decline in sage-grouse abundance by 2.6%. Horse abundance at or below AMLmax coincided with sage-grouse λ estimates that were consistent with trends at non-horse areas elsewhere in the study region. Thus, AMLmax, as a whole, appeared to be set adequately in preventing adverse effects to sage-grouse populations. Results indicated 76%, 97%, and >99% probability of sage-grouse population decline relative to controls when horse numbers are 2, 2.5, and ≥3 times over AMLmax, respectively. As of 2019, horse herds exceeded AMLmax in Nevada, USA, by >4 times on average across all horse management areas. If feral horse populations continue to grow at current rates unabated, model projections indicate sage-grouse populations will be reduced within horse-occupied areas by >70.0% by 2034 (15-year projection), on average compared to 21.2% estimated for control sites. A monitoring framework that improves on estimating horse abundance and identifying responses of sage-grouse and other key indicator species (plant and animal) would be beneficial to guide management decisions that promote co-occurrence of horses with sensitive wildlife and livestock within landscapes subjected to multiple uses. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of the Wildlife Society.
Background
Wildfire is a major proximate cause of historical and ongoing losses of intact big sagebrush (
Artemisia tridentata
Nutt.) plant communities and declines in sagebrush obligate wildlife ...species. In recent decades, fire return intervals have shortened and area burned has increased in some areas, and habitat degradation is occurring where post-fire re-establishment of sagebrush is hindered by invasive annual grasses. In coming decades, the changing climate may accelerate these wildfire and invasive feedbacks, although projecting future wildfire dynamics requires a better understanding of long-term wildfire drivers across the big sagebrush region. Here, we integrated wildfire observations with climate and vegetation data to derive a statistical model for the entire big sagebrush region that represents how annual wildfire probability is influenced by climate and fine fuel characteristics.
Results
Wildfire frequency varied significantly across the sagebrush region, and our statistical model represented much of that variation. Biomass of annual and perennial grasses and forbs, which we used as proxies for fine fuels, influenced wildfire probability. Wildfire probability was highest in areas with high annual forb and grass biomass, which is consistent with the well-documented phenomenon of increased wildfire following annual grass invasion. The effects of annuals on wildfire probability were strongest in places with dry summers. Wildfire probability varied with the biomass of perennial grasses and forbs and was highest at intermediate biomass levels. Climate, which varies substantially across the sagebrush region, was also predictive of wildfire probability, and predictions were highest in areas with a low proportion of precipitation received in summer, intermediate precipitation, and high temperature.
Conclusions
We developed a carefully validated model that contains relatively simple and biologically plausible relationships, with the goal of adequate performance under novel conditions so that useful projections of average annual wildfire probability can be made given general changes in conditions. Previous studies on the impacts of vegetation and climate on wildfire probability in sagebrush ecosystems have generally used more complex machine learning approaches and have usually been applicable to only portions of the sagebrush region. Therefore, our model complements existing work and forms an additional tool for understanding future wildfire and ecological dynamics across the sagebrush region.
With human activities increasingly impacting natural resources in relatively remote locations, there is a need for simple and efficient methods to explore the ecological consequences of these ...activities. Little is understood about the influences of off-highway vehicle (OHV) use on wildlife populations. We examined the effect of OHV activity on developmental instability in a phrynosomatid lizard (i.e., western fence lizard Sceloporus occidentalis) in the western Great Basin, USA. We measured fluctuating asymmetry (FA) of bilateral head-scale patterns in populations of lizards at 3 OHV and 3 non–OHV sites. Fluctuating asymmetry was higher at OHV sites relative to non-OHV sites, supporting the idea that OHV activity can stress wildlife populations. We found FA to be a good tool for uncovering responses to stress in natural populations, and we recommend exploring FA as a means of uncovering developmental instability in other systems that merit conservation interest
The motivation to adopt innovative communication and e-learning practices in education settings can be stimulated by events such as natural disasters. Education institutions in the Pacific Rim ...cannot avoid the likelihood of natural disasters that could close one or more buildings on a campus and impact their ability to continue current educational practices. For one university, the impetus to innovate was a series of seismic events. This paper presents findings from studies that identified resilient practices within this ‘late adopter’ university in New Zealand. The findings indicate that the combined use of social media and e-learning to support teaching, learning, communication and related organisational practices fosters resilience for students, staff and organisations in times of crises. Recommendations are presented that have relevance to all educational organisations which could be impacted by similar events.
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