scholarly journals Determining Statistically Robust Changes in Ungulate Browsing Pressure as a Basis for Adaptive Wildlife Management

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1030
Author(s):  
Kai Bödeker ◽  
Christian Ammer ◽  
Thomas Knoke ◽  
Marco Heurich
Keyword(s):  
Sample Size ◽  
Wildlife Management ◽  
National Park ◽  
Estimation Accuracy ◽  
Management Decision ◽  
Sorbus Aucuparia ◽  
Mixed Effect ◽  
Ungulate Browsing ◽  
The Impact ◽  
Inventory Method

Ungulate browsing has a major impact on the composition and structure of forests. Repeatedly conducted, large-scale regeneration inventories can monitor the extent of browsing pressure and its impacts on forest regeneration development. Based on the respective results, the necessity and extent of wildlife management activities such as hunting, fencing, etc., can be identified at a landscape scale. However, such inventories have rarely been integrated into wildlife management decision making. In this article, we evaluate a regeneration inventory method which was carried out in the Bavarian Forest National Park between 2007 and 2018. We predict the browsing impact by calculating browsing probabilities using a logistic mixed effect model. To provide wildlife managers with feedback on their activities, we developed a test which can assess significant changes in browsing probability between different inventory periods. To find the minimum observable browsing probability change, we simulated ungulate browsing based on the data of a potential browsing indicator species (Sorbus aucuparia) in the National Park. Sorbus aucuparia is evenly distributed, commonly found, selectively browsed and meets the ecosystem development objectives in our study area. We were able to verify a browsing probability change down to ±5 percentage points with a sample size of about 1,000 observations per inventory run. In view of the size of the National Park and the annual fluctuations in browsing pressure, this estimation accuracy seems sufficient. In seeking the maximal cost-efficiency, we were able to reduce this sample size in a sensitivity analysis by about two thirds without severe loss of information for wildlife management. Based on our findings, the presented inventory method combined with our evaluation tool has the potential to be a robust and efficient instrument to assess the impact of herbivores that are in the National Park and other regions.

scholarly journals Wildlife Management Practices Associated with Pathogen Exposure in Non-Native Wild Pigs in Florida, U.S.

Viruses ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 14 ◽  
Author(s):  
Amanda Carr ◽  
Michael Milleson ◽  
Felipe Hernández ◽  
Hunter Merrill ◽  
Michael Avery ◽  
...  
Keyword(s):  
Wildlife Management ◽  
Wildlife Conservation ◽  
Pseudorabies Virus ◽  
Management Practices ◽  
The United States ◽  
Management Decision ◽  
Disease Emergence ◽  
Wild Pigs ◽  
Management Decision Making ◽  
The Impact

Land use influences disease emergence by changing the ecological dynamics of humans, wildlife, domestic animals, and pathogens. This is a central tenet of One Health, and one that is gaining momentum in wildlife management decision-making in the United States. Using almost 2000 serological samples collected from non-native wild pigs (Sus scrofa) throughout Florida (U.S.), we compared the prevalence and exposure risk of two directly transmitted pathogens, pseudorabies virus (PrV) and Brucella spp., to test the hypothesis that disease emergence would be positively correlated with one of the most basic wildlife management operations: Hunting. The seroprevalence of PrV-Brucella spp. coinfection or PrV alone was higher for wild pigs in land management areas that allowed hunting with dogs than in areas that culled animals using other harvest methods. This pattern did not hold for Brucella alone. The likelihood of exposure to PrV, but not Brucella spp., was also significantly higher among wild pigs at hunted sites than at sites where animals were culled. By failing to consider the impact of dog hunting on the emergence of non-native pathogens, current animal management practices have the potential to affect public health, the commercial livestock industry, and wildlife conservation.

MHealth Applications for People with Cognitive Impairment and Their Caregivers: A Scoping Review (Preprint)

2020 ◽  
Author(s):  
Qing Zhao ◽  
Pei Chen ◽  
Yu Zhang ◽  
Haining Liu ◽  
Xianwen Li
Keyword(s):  
Cognitive Impairment ◽  
Sample Size ◽  
Research Design ◽  
Scoping Review ◽  
Life Support ◽  
Small Sample ◽  
Mobile Technologies ◽  
Control Group ◽  
Caregiver Support ◽  
The Impact

BACKGROUND Mobile health application has become an important tool for healthcare systems. One such tool is the delivery of assisting in people with cognitive impairment and their caregivers. OBJECTIVE This scoping review aims to explore and evaluate the existing evidence and challenges on the use of mHealth applications that assisting in people with cognitive impairment and their caregivers. METHODS Nine databases, including PubMed, EMBASE, Cochrane, PsycARTICLES, CINAHL, Web of Science, Applied Science & Technology Source, IEEE Xplore and the ACM Digital Library were searched from inception through June 2020 for the studies of mHealth applications on people with cognitive impairment and their caregivers. Two reviewers independently extracted, checked synthesized data independently. RESULTS Of the 6101 studies retrieved, 64 studies met the inclusion criteria. Three categories emerged from this scoping review. These categories are ‘application functionality’, ‘evaluation strategies’, ‘barriers and challenges’. All the included studies were categorized into 7 groups based on functionality: (1) cognitive assessment; (2) cognitive training; (3) life support; (4) caregiver support; (5) symptom management; (6) reminiscence therapy; (7) exercise intervention. The included studies were broadly categorized into four types: (1) Usability testing; (2) Pilot and feasibility studies; (3) Validation studies; and (4) Efficacy or Effectiveness design. These studies had many defects in research design such as: (1) small sample size; (2) deficiency in active control group; (3) deficiency in analyzing the effectiveness of intervention components; (4) lack of adverse reactions and economic evaluation; (5) lack of consideration about the education level, electronic health literacy and smartphone proficiency of the participants; (6) deficiency in assessment tool; (7) lack of rating the quality of mHealth application. Some progress should be improved in the design of smartphone application functionality, such as: (1) the design of cognitive measurements and training game need to be differentiated; (2) reduce the impact of the learning effect. Besides this, few studies used health behavior theory and performed with standardized reporting. CONCLUSIONS Preliminary results show that mobile technologies facilitate the assistance in people with cognitive impairment and their caregivers. The majority of mHealth application interventions incorporated usability outcome and health outcomes. However, these studies have many defects in research design that limit the extrapolation of research. The content of mHealth application is urgently improved to adapt to demonstrate the real effect. In addition, further research with strong methodological rigor and adequate sample size are needed to examine the feasibility, effectiveness, and cost-effectiveness of mHealth applications for people with cognitive impairment and their caregivers.

How Does Public Debt Affect the Indian Macroeconomy? A Structural VAR Approach

2020 ◽  
Vol 14 (3) ◽  
pp. 253-284
Author(s):  
Ranjan Kumar Mohanty ◽  
Sidheswar Panda
Keyword(s):  
Economic Growth ◽  
Interest Rate ◽  
Public Debt ◽  
Positive Impact ◽  
Decomposition Analysis ◽  
Structural Var ◽  
Adverse Impact ◽  
Mixed Effect ◽  
Domestic Debt ◽  
The Impact

The study investigates the macroeconomic effects of public debt in India during 1980–2017 using a structural vector autoregression framework. The objective is to examine the impact of public debt on the interest rate, investment, inflation and economic growth in India. The results of the impulse response functions show that public debt has an adverse impact on economic growth but a positive impact on the long-term interest rate in the short run and a mixed effect (both negative and positive) on investment and inflation. We also find that domestic debt has a more adverse impact on the economy than external debt. The estimated variance decomposition analysis finds that much of the variation in selected macro variables are explained by public debt and growth in India. This study suggests that public debt especially domestic debt should be controlled and channelled productively to have a favourable impact on the economy. JEL Classification: H63, O40, C40

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

scholarly journals Dynamic Optimization Method for Broadband ADCP Waveform with Environment Constraints

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3768
Author(s):  
Yongshou Yang ◽  
Shiliang Fang
Keyword(s):  
Distance Estimation ◽  
Acoustic Doppler Current Profiler ◽  
Optimization Method ◽  
Measurement Range ◽  
Velocity Estimation ◽  
Estimation Accuracy ◽  
Dynamic Configuration ◽  
Optimal Velocity ◽  
Flood Warning ◽  
The Impact

Broadband acoustic Doppler current profiler (ADCP) is widely used in agricultural water resource explorations, such as river discharge monitoring and flood warning. Improving the velocity estimation accuracy of broadband ADCP by adjusting the waveform parameters of a phase-encoded signal will reduce the velocity measurement range and water stratification accuracy, while the promotion of stratification accuracy will degrade the velocity estimation accuracy. In order to minimize the impact of these two problems on the measurement results, the ADCP waveform optimization problem that satisfies the environment constraints while keeping high velocity estimation accuracy or stratification accuracy is studied. Firstly, the relationship between velocity or distance estimation accuracy and signal waveform parameters is studied by using an ambiguity function. Secondly, the constraints of current velocity range, velocity distribution and other environmental characteristics on the waveform parameters are studied. For two common measurement applications, two dynamic configuration methods of waveform parameters with environmental adaptability and optimal velocity estimation accuracy or stratification accuracy are proposed based on the nonlinear programming principle. Experimental results show that compared with the existing methods, the velocity estimation accuracy of the proposed method is improved by more than 50%, and the stratification accuracy is improved by more than 22%.

scholarly journals The Effects of Social Distancing Policies on non-SARS-CoV-2 Respiratory Pathogens

2021 ◽  
Author(s):  
Jeff Nawrocki ◽  
Katherine Olin ◽  
Martin C Holdrege ◽  
Joel Hartsell ◽  
Lindsay Meyers ◽  
...  
Keyword(s):  
Public Health ◽  
Influenza A ◽  
Detection Rate ◽  
Respiratory Illness ◽  
Respiratory Pathogens ◽  
Public Health Response ◽  
Mixed Effect ◽  
Detection Rates ◽  
Social Distancing ◽  
The Impact

Abstract Background The initial focus of the US public health response to COVID-19 was the implementation of numerous social distancing policies. While COVID-19 was the impetus for imposing these policies, it is not the only respiratory disease affected by their implementation. This study aimed to assess the impact of social distancing policies on non-SARS-CoV-2 respiratory pathogens typically circulating across multiple US states. Methods Linear mixed-effect models were implemented to explore the effects of five social distancing policies on non-SARS-CoV-2 respiratory pathogens across nine states from January 1 through May 1, 2020. The observed 2020 pathogen detection rates were compared week-by-week to historical rates to determine when the detection rates were different. Results Model results indicate that several social distancing policies were associated with a reduction in total detection rate, by nearly 15%. Policies were associated with decreases in pathogen circulation of human rhinovirus/enterovirus and human metapneumovirus, as well as influenza A, which typically decrease after winter. Parainfluenza viruses failed to circulate at historical levels during the spring. Total detection rate in April 2020 was 35% less than historical average. Many of the pathogens driving this difference fell below historical detection rate ranges within two weeks of initial policy implementation. Conclusion This analysis investigated the effect of multiple social distancing policies implemented to reduce transmission of SARS-CoV-2 on non-SARS-CoV-2 respiratory pathogens. These findings suggest that social distancing policies may be used as an impactful public health tool to reduce communicable respiratory illness.

scholarly journals Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

2019 ◽  
Vol 13 (11) ◽  
pp. 3045-3059 ◽  
Author(s):  
Nick Rutter ◽  
Melody J. Sandells ◽  
Chris Derksen ◽  
Joshua King ◽  
Peter Toose ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Layer Thickness ◽  
Snow Water Equivalent ◽  
Estimation Accuracy ◽  
Snow Layer ◽  
Data Set ◽  
Snow Water ◽  
Retrieval Errors ◽  
Snow Microstructure ◽  
The Impact

Abstract. Spatial variability in snowpack properties negatively impacts our capacity to make direct measurements of snow water equivalent (SWE) using satellites. A comprehensive data set of snow microstructure (94 profiles at 36 sites) and snow layer thickness (9000 vertical profiles across nine trenches) collected over two winters at Trail Valley Creek, NWT, Canada, was applied in synthetic radiative transfer experiments. This allowed for robust assessment of the impact of estimation accuracy of unknown snow microstructural characteristics on the viability of SWE retrievals. Depth hoar layer thickness varied over the shortest horizontal distances, controlled by subnivean vegetation and topography, while variability in total snowpack thickness approximated that of wind slab layers. Mean horizontal correlation lengths of layer thickness were less than a metre for all layers. Depth hoar was consistently ∼30 % of total depth, and with increasing total depth the proportion of wind slab increased at the expense of the decreasing surface snow layer. Distinct differences were evident between distributions of layer properties; a single median value represented density and specific surface area (SSA) of each layer well. Spatial variability in microstructure of depth hoar layers dominated SWE retrieval errors. A depth hoar SSA estimate of around 7 % under the median value was needed to accurately retrieve SWE. In shallow snowpacks <0.6 m, depth hoar SSA estimates of ±5 %–10 % around the optimal retrieval SSA allowed SWE retrievals within a tolerance of ±30 mm. Where snowpacks were deeper than ∼30 cm, accurate values of representative SSA for depth hoar became critical as retrieval errors were exceeded if the median depth hoar SSA was applied.

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