scholarly journals Evaluating artificial shelter arrays as a minimally invasive monitoring tool for the hellbender Cryptobranchus alleganiensis

2020 ◽  
Vol 41 ◽  
pp. 167-181 ◽  
Author(s):  
CM Bodinof Jachowski ◽  
BE Ross ◽  
WA Hopkins
Keyword(s):  
Activity Patterns ◽  
Invasive Monitoring ◽  
Seasonal Activity ◽  
Monitoring Tool ◽  
Monitoring Tools ◽  
Ranking Criteria ◽  
Cryptobranchus Alleganiensis ◽  
Model Ranking ◽  
Eastern Usa ◽  
The Relationship

Hellbenders Cryptobranchus alleganiensis are critically imperiled amphibians throughout the eastern USA. Rock-lifting is widely used to monitor hellbenders but can severely disturb habitat. We asked whether artificial shelter occupancy (the proportion of occupied shelters in an array) would function as a proxy for hellbender abundance and thereby serve as a viable alternative to rock-lifting. We hypothesized that shelter occupancy would vary spatially in response to hellbender density, natural shelter density, or both, and would vary temporally with hellbender seasonal activity patterns and time since shelter deployment. We established shelter arrays (n = 30 shelters each) in 6 stream reaches and monitored them monthly for up to 2 yr. We used Bayesian mixed logistic regression and model ranking criteria to assess support for hypotheses concerning drivers of shelter occupancy. In all reaches, shelter occupancy was highest from June-August each year and was higher in Year 2 relative to Year 1. Our best-supported model indicated that the extent of boulder and bedrock (hereafter, natural shelter) in a reach mediated the relationship between hellbender abundance and shelter occupancy. More explicitly, shelter occupancy was positively correlated with abundance when natural shelter covered <20% of a reach, but uncorrelated with abundance when natural shelter was more abundant. While shelter occupancy should not be used to infer variation in hellbender relative abundance when substrate composition varies among reaches, we showed that artificial shelters can function as valuable monitoring tools when reaches meet certain criteria, though regular shelter maintenance is critical.

Inducing Unconscious Stress

2020 ◽  
Vol 34 (3) ◽  
pp. 192-201
Author(s):  
Melanie M. van der Ploeg ◽  
Jos F. Brosschot ◽  
Markus Quirin ◽  
Richard D. Lane ◽  
Bart Verkuil
Keyword(s):  
Repeated Measures ◽  
Activity Patterns ◽  
Physiological Changes ◽  
Implicit Measures ◽  
Prime Word ◽  
Student Sample ◽  
Priming Task ◽  
Subject Design ◽  
The Relationship ◽  
Stress And Health

Abstract. Stress-related stimuli may be presented outside of awareness and may ultimately influence health by causing repetitive increases in physiological parameters, such as blood pressure (BP). In this study, we aimed to corroborate previous studies that demonstrated BP effects of subliminally presented stress-related stimuli. This would add evidence to the hypothesis that unconscious manifestations of stress can affect somatic health. Additionally, we suggest that these findings may be extended by measuring affective changes relating to these physiological changes, using measures for self-reported and implicit positive and negative affectivity. Using a repeated measures between-subject design, we presented either the prime word “angry” ( n = 26) or “relax” ( n = 28) subliminally (17 ms) for 100 trials to a student sample and measured systolic and diastolic BP, heart rate (HR), and affect. The “angry” prime, compared to the “relax” prime, did not affect any of the outcome variables. During the priming task, a higher level of implicit negative affect (INA) was associated with a lower systolic BP and diastolic BP. No association was found with HR. Self-reported affect and implicit positive affect were not related to the cardiovascular (CV) activity. In sum, anger and relax primes elicited similar CV activity patterns, but implicit measures of affect may provide a new method to examine the relationship between (unconscious) stress and health.

Seasonal Activity of Haemaphysalis longicornis (Acari: Ixodidae) in Southern New York State

2020 ◽  
Author(s):  
Nicholas P Piedmonte ◽  
Vanessa C Vinci ◽  
Thomas J Daniels ◽  
Bryon P Backenson ◽  
Richard C Falco
Keyword(s):  
United States ◽  
New York ◽  
Activity Patterns ◽  
New York State ◽  
The United States ◽  
Haemaphysalis Longicornis ◽  
Seasonal Activity ◽  
Eastern Asia ◽  
Short Life ◽  
Human Bite

Abstract The Asian longhorned tick, Haemaphysalis longicornis Neumann, is a species native to eastern Asia that has recently been discovered in the United States. In its native range, H. longicornis transmits pathogens that cause disease in humans and livestock. It is currently unknown whether H. longicornis will act as a vector in the United States. Understanding its seasonal activity patterns will be important in identifying which times of the year represent greatest potential risk to humans and livestock should this species become a threat to animal or public health. A study site was established in Yonkers, NY near the residence associated with the first reported human bite from H. longicornis in the United States. Ticks were collected once each week from July 2018 to November 2019. Haemaphysalis longicornis larvae were most active from August to November, nymphs from April to July, and adult females from June to September. This pattern of activity suggests that H. longicornis is capable of completing a generation within a single year and matches the patterns observed in its other ranges in the northern hemisphere. The data presented here contribute to a growing database for H. longicornis phenology in the northeastern United States. Potential implications of the short life cycle for the tick’s vectorial capacity are discussed.

086 Sleep midpoint after job loss predicts breakfast skipping patterns

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A36-A36
Author(s):  
Leah Callovini ◽  
Gaby Gubka ◽  
Candace Mayer ◽  
Darlynn Rojo-Wissar ◽  
David Glickenstein ◽  
...  
Keyword(s):  
Job Loss ◽  
Activity Patterns ◽  
Sleep Onset ◽  
Daily Routine ◽  
Cross Sectional ◽  
Circadian Phase ◽  
Breakfast Skipping ◽  
Occupational Transitions ◽  
The Relationship ◽  
Significant Covariates

Abstract Introduction Few studies have examined circadian phase after job loss, an event that upends daily routine. It is common that a daily routine begins with the consumption of breakfast, and breakfast behavior may contribute to health status in adults. Therefore, we sought to examine whether a later midpoint of sleep was associated with breakfast skipping among adults whose schedules were no longer dictated by employment. Methods Data were obtained from the Assessing Daily Activity Patterns Through Occupational Transitions (ADAPT) study. The sample of 155 participants had involuntarily lost their jobs in the last 90 days. Both cross-sectional and 18-month longitudinal analyses assessed the relationship between sleep midpoint after job loss and current and later breakfast skipping. Assessment periods were 14 days. Sleep was measured via actigraphy, and breakfast skipping was measured via daily diary (1 = had breakfast; 0 = did not have breakfast). The midpoint of sleep was calculated as the circular center based on actigraphy sleep onset and offset times. Results The midpoint of sleep at baseline was negatively associated with breakfast consumption at baseline (B = -.09, SE = .02, p = .000). Also, a later midpoint was associated with breakfast skipping over the next 18 months (estimate = -.08; SE = .02; p = .000). Prospective findings remained significant when adjusting for gender, ethnicity, age, perceived stress, body mass index (BMI), education, and reemployment over time. Education (estimate = 14.26, SE = 6.23, p &lt; .05) and BMI (estimate = -.51, SE = .25, p &lt; .05) were the only significant covariates. No other sleep indices predicted breakfast behavior cross-sectionally or prospectively. Conclusion Consistent with research in adolescents, unemployed adults with a later circadian phase are more likely to skip breakfast more often. Breakfast skipping was also associated with higher BMI. Taken together, these findings provide support for the future testing of sleep/wake scheduling interventions to modify breakfast skipping and potentially mitigate weight gain after job loss. Support (if any) #1R01HL117995-01A1

Guided Exploration

2021 ◽  
Vol 5 (EICS) ◽  
pp. 1-34
Author(s):  
Markus Weninger ◽  
Elias Gander ◽  
Hanspeter Mössenböck
Keyword(s):  
Time Behavior ◽  
Monitoring Tool ◽  
Memory Leak ◽  
Root Cause ◽  
Churn Analysis ◽  
Monitoring Tools ◽  
Guided Exploration ◽  
Monitoring Applications ◽  
Novice Users ◽  
Memory Monitoring

Many monitoring tools that help developers in analyzing the run-time behavior of their applications share a common shortcoming: they require their users to have a fair amount of experience in monitoring applications to understand the used terminology and the available analysis features. Consequently, novice users who lack this knowledge often struggle to use these tools efficiently. In this paper, we introduce the guided exploration (GE) method that aims to make interactive monitoring tools easier to use and learn. In general, tools that implement GE should provide four support operations on each analysis step: they should automatically (1) detect and (2) highlight the most important information on the screen, (3) explain why it is important, and (4) suggest which next steps are appropriate. This way, tools guide users through their analysis processes, helping them to explore the root cause of a problem. At the same time, users learn the capabilities of the tool and how to use them efficiently. We show how GE can be implemented in new monitoring tools as well as how it can be integrated into existing ones. To demonstrate GE's feasibility and usefulness, we present how we extended the memory monitoring tool AntTracks to provided guided exploration support during memory leak analysis and memory churn analysis. We use these guidances in two user scenarios to inspect and improve the memory behavior of the monitored applications. We hope that our contribution will help usability researchers and developers in making monitoring tools more novice-friendly by improving their usability and learnability.

scholarly journals Seasonal activity pattern of Swamp deer (Rucervus duvaucelii duvaucelii) in Dudhwa National Park, Uttar Pradesh, India

2014 ◽  
Vol 6 (1) ◽  
pp. 246-253 ◽  
Author(s):  
Kaleem Ahmed ◽  
Jamal A. Khan
Keyword(s):  
Activity Pattern ◽  
National Park ◽  
Time Budget ◽  
Activity Patterns ◽  
Winter Season ◽  
Uttar Pradesh ◽  
Seasonal Activity ◽  
Adult Males ◽  
Continuous Feeding ◽  
Swamp Deer

The data on activity pattern and time budget of Swamp deer (Rucervus duvauceli duvauceli) were collected through instantaneous scan sampling from Dudhwa National Park, Uttar Pradesh, India Diurnal activity pattern of Swamp deer showed marked reduction in resting in winter as compared to summer. In winter resting in adult males showed polymodal pattern with peaks occurring at different hours of the day and continued throughout the day without any break. Feeding of adult females in winter and summer seasons showed a polymodal pattern with peaks occurring at different hours of the day without break. In yearling males feeding and resting was observed to occur throughout the day during winter season with peaks occurring between 11:00 to 12:00 hours. Yearling females showed continuous feeding throughout the day with peaks in different times in both the seasons. The seasonal distribution of activity patterns of the fawns showed that feeding was slightly more in summer as compared to winter. In time budget, of the expenditure on different activities, resting accounted for 63.77% and feeding 24.70%. In both the seasons resting was the major portion of their activity. Analysis showed that in all age and sex categories of Swamp deer in the Dudhwa NP, resting dominated on all other activities. The observation on endangered Swamp deer indicates synchronization in activity only in the feeding in the morning and evening hours and resting throughout the day.

Modern Drought Monitoring Tool for Decision Support System

2011 ◽  
pp. 1212-1218
Author(s):  
T. Tadesse ◽  
D. A. Wilhite
Keyword(s):  
United States ◽  
Meteorological Drought ◽  
Decision Makers ◽  
Drought Monitoring ◽  
Monitoring Tool ◽  
Knowledge Based ◽  
Monitoring Tools ◽  
The World ◽  
Central United States ◽  
Supply Interruptions

Drought is a natural disaster that influences many aspects of society. Since the demand for water is increasing along with the population in many parts of the world, water supply interruptions caused by drought can be expected to produce greater impacts. This is because the impacts of drought are determined not only by the frequency and intensity of meteorological drought but also by the number of people at risk and their degree of risk (Wilhite, 2000). For example, the increase in population in Africa and Asia increases drought vulnerability significantly. Thus, policies that promote the development and implementation of appropriate drought mitigation measures today will help to reduce the economic, social, and environmental impacts associated with future droughts and the need for government intervention. To monitor drought, different types of indicators (e.g., drought indices) have been used in many parts of the world. Because there is no single definition for drought, determining which indicators to use poses more difficulties for planners. Decision makers use different policies and strategies based on the historical records of their countries. For example, in Australia, when meteorological drought (annual rainfalls in the lowest 10% of recorded values) occurred over at least 10% of the continent, it coincided with damaging agricultural droughts resulting significant losses of crops and livestock (Heathcote, 2000). Because of the varied and potentially catastrophic losses resulting from drought in many parts of the world, both governmental and non-governmental decision makers need better predictive and monitoring tools to assist them in dealing more effectively with drought. Better early warning and prediction is the foundation of a new drought management paradigm based on risk management. In South Africa, the Weather Bureau issues extended outlooks for short and long periods using numerical modeling and statistical methods (Vogel, Lang, & Monnik, 2000). In United States, recent advances in science and technology are enhancing drought monitoring capabilities and the availability of such information, which allows decision makers to make more knowledge-based decisions to lessen the impacts of drought. In this article, we highlight the role of government in drought planning and mitigation, the potential of data mining techniques and their outputs (e.g., maps and tables) for improving informed decision making, and also present a newly developed drought monitoring tool, the Vegetation Drought Response Index (VegDRI) as an example over the central United States.

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