scholarly journals Disentangling the Effects of Disturbance from Those of Dominant Tall Grass Features in Driving the Functional Variation of Restored Grassland in a Sub-Mediterranean Context

Diversity ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 11 ◽  
Author(s):  
Alessandro Bricca ◽  
Federico Maria Tardella ◽  
Fabio Tolu ◽  
Irina Goia ◽  
Arianna Ferrara ◽  
...  
Keyword(s):  
Plant Traits ◽  
Seed Mass ◽  
Recovery Process ◽  
Functional Variation ◽  
Tall Grass ◽  
Mixed Effect ◽  
Main Driver ◽  
Coexisting Species ◽  
The Impact ◽  
Space Occupation

Land abandonment in sub-Mediterranean grasslands causes the spread of tall-grasses, affecting biodiversity and ecosystem functioning. Mowing allows the recovery of the coenological composition after invasion, but the mechanisms acting at the fine-scale are poorly investigated. Since 2010 in the Central Apennines, we fenced a grassland invaded by Brachypodium rupestre, divided it into two areas, half of each was mowed biyearly and half remained unmown. In 2017 we selected ten 20 × 20 cm experimental units per half-area, collecting data on species occurrences, plant traits, B. rupestre height and phytomass. We used generalized linear mixed-effect modelling to disentangle the role of mowing from the impact of B. rupestre features in driving the community functional variations. Mowing was the main driver in the recovery process, acting as an abiotic filter (enhancement of tolerance-avoidance strategies). Furthermore, the reduction of weaker competitor exclusion processes fostered the increase of functional variation between coexisting species. Both drivers acted on different plant traits (e.g., mowing on life span, vegetative propagation types and plant height, mowing and B. rupestre features on space occupation types, seed mass and leaf anatomy), generally enhancing the extent of functional strategies related to resource acquisition and storage, reproduction, space occupation and temporal niche exploitation.

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

Interactions Between Natural Selection, Recombination and Gene Density in the Genes of Drosophila

Genetics ◽  
2002 ◽  
Vol 160 (2) ◽  
pp. 595-608 ◽  
Author(s):  
Jody Hey ◽  
Richard M Kliman
Keyword(s):  
Gene Expression ◽  
Natural Selection ◽  
Recombination Rate ◽  
Codon Bias ◽  
Gene Density ◽  
Drosophila Genome ◽  
Functional Variation ◽  
Subtle Effect ◽  
Efficiency Of Selection ◽  
The Impact

AbstractIn Drosophila, as in many organisms, natural selection leads to high levels of codon bias in genes that are highly expressed. Thus codon bias is an indicator of the intensity of one kind of selection that is experienced by genes and can be used to assess the impact of other genomic factors on natural selection. Among 13,000 genes in the Drosophila genome, codon bias has a slight positive, and strongly significant, association with recombination—as expected if recombination allows natural selection to act more efficiently when multiple linked sites segregate functional variation. The same reasoning leads to the expectation that the efficiency of selection, and thus average codon bias, should decline with gene density. However, this prediction is not confirmed. Levels of codon bias and gene expression are highest for those genes in an intermediate range of gene density, a pattern that may be the result of a tradeoff between the advantages for gene expression of close gene spacing and disadvantages arising from regulatory conflicts among tightly packed genes. These factors appear to overlay the more subtle effect of linkage among selected sites that gives rise to the association between recombination rate and codon bias.

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.

Effect of education on migration decisions in Ghana: a rural-urban perspective

2016 ◽  
Vol 43 (2) ◽  
pp. 336-356 ◽  
Author(s):  
Franklin Amuakwa-Mensah ◽  
Louis Boakye-Yiadom ◽  
William Baah-Boateng
Keyword(s):  
Educational Attainment ◽  
Rural Areas ◽  
Migration Decision ◽  
Skilled Workers ◽  
Mixed Effect ◽  
Content Type ◽  
Rural And Urban ◽  
Migration Decisions ◽  
Negative Effect ◽  
The Impact

Purpose – The purpose of this paper is to investigate the effect of education on migration decisions focusing on rural and urban in-migrants by comparing the 2005/2006 and 2012/2013 rounds of the Ghana Living Standards Survey (GLSS5 and GLSS6). After correcting for selectivity bias, the authors observed that anticipated welfare gain and socio-economic variables such as sector of employment, sex, experience, age, educational level and marital status significantly affect an individual’s migration decision. Design/methodology/approach – The authors made use of Sjaastad’s (1962) human capital framework as a basis for examining the impact of education on migration. The migration decision equation was based on the Heckman two stage procedure. Findings – While educational attainment is observed to have a positive effect on migration decision in the period 2005/2006, the authors find a negative effect of educational attainment on migration decision in the period 2012/2013. The effect of educational attainment on migration decision in 2005/2006 for urban in-migrant is higher than the effect for rural in-migrant, with its significance varying for the different stages of educational attainment. In absolute terms, whereas the effect of secondary educational attainment on migration decisions for urban in-migrant is higher than that of rural in-migrant, the reverse holds for higher educational attainment during the period 2012/2013. Social implications – Based on the mixed effect of education on migration decision as evident from the study, policies to enhance the educational system in Ghana should be complemented with job creations in the entire country. Moreover, special attention should be given to the rural sector in such a way that the jobs to be created in the sector do not require skilled workers. With quality education and job creation, the welfare of individuals living in urban and rural areas will be enhanced. Originality/value – In spite of the importance of education in migration decisions, there is scanty literature on the rural-urban dimension. To the best of the author’s knowledge there is no literature in the Ghanaian context which examines the rural and urban perspective of the impact of education on migration with a much recent data. Further, the author consider how the determinants of migration decision have changed over time focusing on rural and urban perspectives.

scholarly journals Statistical Weather-Impact Models: An Application of Neural Networks and Mixed Effects for Corn Production over the United States

2016 ◽  
Vol 55 (11) ◽  
pp. 2509-2527 ◽  
Author(s):  
Jordane A. Mathieu ◽  
Filipe Aires
Keyword(s):  
United States ◽  
The United States ◽  
Weather Data ◽  
Corn Yield ◽  
Mixed Effect ◽  
Local Conditions ◽  
Weather Impact ◽  
Yield Forecasting ◽  
The Impact ◽  
Impact Models

AbstractStatistical meteorological impact models are intended to represent the impact of weather on socioeconomic activities, using a statistical approach. The calibration of such models is difficult because relationships are complex and historical records are limited. Often, such models succeed in reproducing past data but perform poorly on unseen new data (a problem known as overfitting). This difficulty emphasizes the need for regularization techniques and reliable assessment of the model quality. This study illustrates, in a general way, how to extract pertinent information from weather data and exploit it in impact models that are designed to help decision-making. For a given socioeconomic activity, this type of impact model can be used to 1) study its sensitivity to weather anomalies (e.g., corn sensitivity to water stress), 2) perform seasonal forecasting (yield forecasting) for it, and 3) quantify the longer-term (several decades) impact of weather on it. The size of the training database can be increased by pooling data from various locations, but this requires statistical models that are able to use the localization information—for example, mixed-effect (ME) models. Linear, neural-network, and ME models are compared, using a real-world application: corn-yield forecasting over the United States. Many challenges faced in this paper may be encountered in many weather-impact analyses: these results show that much care is required when using space–time data because they are often highly spatially correlated. In addition, the forecast quality is strongly influenced by the training spatial scale. For the application that is described herein, learning at the state scale is a good trade-off: it is specific to local conditions while keeping enough data for the calibration.

scholarly journals The COVID-19 Shock and Consumer Credit: Evidence from Credit Card Data

2021 ◽  
Vol 2021 (008) ◽  
pp. 1-55
Author(s):  
Akos Horvath ◽  
◽  
Benjamin Kay ◽  
Carlo Wix ◽  
◽  
...  
Keyword(s):  
Interest Rates ◽  
Credit Card ◽  
Negative Impact ◽  
Consumer Credit ◽  
Credit Cards ◽  
Sharp Decrease ◽  
Main Driver ◽  
Credit Card Data ◽  
Pandemic Severity ◽  
The Impact

We use credit card data from the Federal Reserve Board's FR Y-14M reports to study the impact of the COVID-19 shock on the use and availability of consumer credit across borrower types from March through August 2020. We document an initial sharp decrease in credit card transactions and outstanding balances in March and April. While spending starts to recover by May, especially for risky borrowers, balances remain depressed overall. We find a strong negative impact of local pandemic severity on credit use, which becomes smaller over time, consistent with pandemic fatigue. Restrictive public health interventions also negatively affect credit use, but the pandemic itself is the main driver. We further document a large reduction in credit card originations, especially to risky borrowers. Consistent with a tightening of credit supply and a flight-to-safety response of banks, we find an increase in interest rates of newly issued credit cards to less creditworthy borrowers.

scholarly journals Economic Growth of Asia Pacific Countries

2018 ◽  
Vol 2 (1) ◽  
pp. 52-60
Author(s):  
Nabaz T. Khayyat ◽  
Sherwan Kafoor
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Trade Openness ◽  
Government Expenditure ◽  
Asia Pacific ◽  
Tax Rate ◽  
Education And Health ◽  
Fixed Capital Formation ◽  
Main Driver ◽  
The Impact

This empirical study examines the determinant of economic growth among Asia Pacific countries. While many other studies focused on specific economies with particular determinants identified from previous studies, this study expands the boundaries of countries to examine different factors that are expected to affect the economic growth in Asia Pacific countries. Estimation results of this study are based on the analysis of a panel data for the period 1994–2011. The impact of total population, industry share of GNI, interest rate, gross fixed capital formation, and tax rate are statistically examined to be strongly significant for the whole sample. In the case of government expenditure and trade openness, they are examined to be significant to some degree. Finally, though human capital is expected to be the main driver of economic growth, the result from correlation analysis revealed that there is a high correlation between expenditure on education and health. To show the impact of human capital on economic growth in Asia Pacific countries, estimation with years of schooling may enhance the study instead of using expenditure on education and health.

scholarly journals The Impact of COVID-19 on Adolescent Mental Health: Preliminary Findings From a Longitudinal Sample of Healthy and At-Risk Adolescents

2021 ◽  
Vol 9 ◽  
Author(s):  
Zsofia P. Cohen ◽  
Kelly T. Cosgrove ◽  
Danielle C. DeVille ◽  
Elisabeth Akeman ◽  
Manpreet K. Singh ◽  
...  
Keyword(s):  
Psychological Functioning ◽  
Life Stress ◽  
Early Life ◽  
Early Life Stress ◽  
Self Report ◽  
Depression And Anxiety ◽  
Mixed Effect ◽  
Symptoms Of Depression ◽  
The Impact ◽  
At Risk Adolescents

Background: The COVID-19 pandemic has brought on far-reaching consequences for adolescents. Adolescents with early life stress (ELS) may be at particular risk. We sought to examine how COVID-19 impacted psychological functioning in a sample of healthy and ELS-exposed adolescents during the pandemic.Methods: A total of 24 adolescents (15 healthy, nine ELS) completed self-report measures prior to and during the COVID-19 pandemic. The effect of COVID-19 on symptoms of depression and anxiety were explored using linear mixed-effect analyses.Results: With the onset of the pandemic, healthy but not ELS-exposed adolescents evidenced increased symptoms of depression and anxiety (ps < 0.05). Coping by talking with friends and prioritizing sleep had a protective effect against anxiety for healthy adolescents (t = −3.76, p = 0.002).Conclusions: On average, this study demonstrated large increases in depression and anxiety in adolescents who were healthy prior to the COVID-19 pandemic, while ELS-exposed adolescents evidenced high but stable symptoms over time.

scholarly journals Influence of ablation-related processes in the built-up of simulated Northern Hemisphere ice sheets during the last glacial cycle

2012 ◽  
Vol 6 (6) ◽  
pp. 4897-4938 ◽  
Author(s):  
S. Charbit ◽  
C. Dumas ◽  
M. Kageyama ◽  
D. M. Roche ◽  
C. Ritz
Keyword(s):  
Northern Hemisphere ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Glacial Cycle ◽  
Satisfactory Description ◽  
Last Glacial ◽  
Transient Simulations ◽  
Main Driver ◽  
The Impact ◽  
The Last Glacial

Abstract. Since the original formulation of the positive-degree-day (PDD) method, different PDD calibrations have been proposed in the literature in response to the increasing number of observations. Although these formulations provide a satisfactory description of the present-day Greenland geometry, they have not all been tested for paleo ice sheets. Using the climate-ice sheet model CLIMBER-GRISLI coupled with different PDD models, we evaluate how the parameterization of the ablation may affect the evolution of Northern Hemisphere ice sheets in the transient simulations of the last glacial cycle. Results from fully coupled simulations are compared to time-slice experiments carried out at different key periods of the last glacial period. We find large differences in the simulated ice sheets according to the chosen PDD model. These differences occur as soon as the onset of glaciation, therefore affecting the subsequent evolution of the ice system. To further investigate how the PDD method controls this evolution, special attention is given to the role of each PDD parameter. We show that glacial inception is critically dependent on the representation of the impact of the temperature variability from the daily to the inter-annual time scale, whose effect is modulated by the refreezing scheme. Finally, an additional set of sensitivity experiments has been carried out to assess the relative importance of melt processes with respect to initial ice sheet configuration in the construction and the evolution of past Northern Hemisphere ice sheets. Our analysis reveals that the impacts of the initial ice sheet condition may range from quite negligible to explaining about half of the LGM ice volume depending on the representation of stochastic temperature variations which remain the main driver of the evolution of the ice system.

scholarly journals Comparative adherence between DOAC and VKA in patients with atrial fibrillation: a 23-year retrospective observational study in Canada

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
S Salmasi ◽  
A Safari ◽  
M.A De Vera ◽  
L Lynd ◽  
M Koehoorn ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Drug Class ◽  
Oral Anticoagulants ◽  
Current Evidence ◽  
Mixed Effect ◽  
Medication Discontinuation ◽  
The Impact ◽  
Rolling Windows ◽  
Over Time

Abstract Background A recent systematic review highlighted significant gaps in the evidence on atrial fibrillation (AF) patients' adherence to oral anticoagulants (OAC). Current evidence suffers from short follow-up times, focuses on the first OAC and does not take switching into account. There is also lack of observational data on adherence to warfarin due to its varying dose that complicates the calculations. As such there is lack of evidence on comparative adherence between VKAs and DOACs and whether the convenience of DOACs translates into better adherence in AF patients. Purpose Our objective was to measure AF patients' long-term OAC adherence and compare the impact of taking direct oral anticoagulants (DOAC) versus vitamin K antagonists (VKA) on adherence, while accounting for switching. Methods Using linked, population-based administrative data containing physician billings, hospitalization and prescription records of 4.8 million British Columbians (1996–2019), incident adult cases of AF were identified. The primary measure of adherence was proportion of days covered (PDC). Consecutive rolling 90-day windows were created for each patient starting from their first OAC prescription fill date until the end of their follow-up. The PDC for each 90-day rolling window was calculated and averaged to yield mean adherence over the follow-up period for each patient. Permanent medication discontinuation resulted in a PDC of 0 for all subsequent rolling windows after their supply ran out. As such, both poor execution and non-persistence were measured simultaneously. The association between drug class and adherence was assessed using generalized mixed effect linear regression models with drug class treated as time-varying covariate to account for switching. Results The study cohort was 30,264 AF patients [mean age 72.2 years (SD11.0), 44.6% female, mean CHA2DS2-VASc 2.94 (SD1.4)] with mean follow-up of 7.7 (SD 4.8) years. The mean PDC was 0.71 (SD 0.27) with 51% of the cohort having mean PDC values below the conventional threshold of adherence (PDC<0.8). Adherence dropped over time with the greatest decline in the first two years after therapy initiation. After controlling for all other confounders and accounting for switching, taking VKA compared to DOAC was, on average, associated with a 1-day decrease in number of days of medication-taking per year. Conclusion AF patients' OAC adherence was below the conventional threshold of 0.8, and dropped over time, particularly in the first two years. Drug class had no clinically meaningful impact on medication adherence. Our study highlights the need for effective adherence interventions particularly early in OAC therapy. Our findings also emphasizes that prescribers should not assume inherently better adherence for DOACs and should instead choose OAC in conversation with the patient and in accordance with their values and preferences. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Canadian Institutes of Health Research grant

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