scholarly journals Slave to the Tides: Spatiotemporal Foraging Dynamics of Spring Staging Black Brant

The Condor ◽  
2006 ◽  
Vol 108 (3) ◽  
pp. 661-677 ◽  
Author(s):  
Jeffrey E. Moore ◽  
Jeffrey M. Black
Keyword(s):  
Seasonal Changes ◽  
Negative Binomial ◽  
Bird Species ◽  
Negative Binomial Regression ◽  
Nutrient Content ◽  
Latitudinal Gradients ◽  
Tidal Channels ◽  
Branta Bernicla ◽  
Black Brant ◽  
Site Use

AbstractArctic-nesting geese depend on nutrients acquired during spring migration for reproduction, and thus should attempt to maximize nutrient intake while on staging areas. We investigated site use of Black Brant (Branta bernicla nigricans) at an important staging location—Humboldt Bay, California—to determine whether birds selected the most profitable feeding areas available. Migrating Brant feed almost exclusively on eelgrass (Zostera marina), which is restricted in availability due to daily and seasonal tidal cycles. We mapped foraging Brant locations during low tides and collected eelgrass samples to describe food resources in 31 areas in the bay. We used negative binomial regression to evaluate goose densities during different tidal levels and times of season as a function of food biomass and nutrient content, distance from grit sites, and substrate elevation. Results varied by time of season and tidal depth, but Brant densities were positively correlated with eelgrass protein, calcium, and biomass in most analyses. Brant usually fed in the deepest possible areas permitted by tides, and closer to tidal channels, where biomass and nutrient content of eelgrass were greater and where depletion from grazing was probably less. During higher low tides, Brant fed closer to previously visited grit sites. Tide cycles change over the course of the Brant's staging period on the bay, enabling longer and more frequent access to deeper eelgrass meadows as spring progresses. These seasonal changes in tidal pattern coincide with seasonal changes in Brant use of the bay. Thus, migration patterns for estuarine bird species might be shaped by latitudinal gradients in both food phenology and seasonal tidal patterns.

scholarly journals Dynamics of Dispersed-Nesting Black Brant on the Yukon-Kuskokwim Delta

2020 ◽  
Vol 11 (1) ◽  
pp. 112-120
Author(s):  
James S. Sedinger ◽  
Thomas V. Riecke ◽  
Phillip A. Street ◽  
Julian B. Fischer
Keyword(s):  
Negative Binomial ◽  
Credible Interval ◽  
Nest Density ◽  
Quadratic Regression ◽  
Branta Bernicla ◽  
Black Brant ◽  
Branta Bernicla Nigricans ◽  
Credible Intervals ◽  
Stratum Type

Abstract The number of black brant Branta bernicla nigricans nests within major breeding colonies on the Yukon-Kuskowkim Delta has declined since 1992. It has been hypothesized that these declines are partially explained by increased numbers of black brant breeding outside of these colonies. To assess this hypothesis, we analyzed spatiotemporal patterns in numbers of black brant nests occurring outside major colonies. Nesting densities of black brant vary among three strata: 1) peripheral to major colonies, 2) other coastal habitats, and 3) inland habitats. We sampled some substrata within each stratum type only between 1986 and 1999 (historical strata), whereas we sampled others over the period 1986–2016 (long-term strata). We fit regression models with number of nests on a plot as a response variable, a log link, and year as the explanatory variable. We allowed each stratum (e.g., historical peripheral) to have its own intercept to account for variation in mean nest density but constrained linear and quadratic regression coefficients to be the same for strata in similar habitats (e.g., historical and long-term peripheral). We used a negative binomial distribution for nests to allow for substantial variation in nests per plot. We fit models using Markov Chain Monte Carlo methods in JAGS. Ninety-five percent credible intervals for both linear and quadratic coefficients for the peripheral and coastal strata, where most nests occurred, broadly overlapped zero, indicating modest trends in numbers of nests in these strata. We estimated there were 6,584 (95% credible interval: 4,221−11,269) dispersed nests in 1986, increasing to 11,051 (95% credible interval: 7,450−17,460) in 2016. Our results indicated that increases in dispersed nests were unable to replace declines in colony nests. Furthermore, quadratic trends indicated that potential earlier annual increases in dispersed nests have declined to zero. We conclude that total numbers of black brant nests on the Yukon-Kuskokwim Delta are likely declining, consistent with the trend in fall age ratios over the same period. Uncertainty about trends in areas not sampled since 1994 adds to the uncertainty about the precise magnitude of the decline. We recommend that the area sampled by the random plot program be expanded to include strata sampled only before 1995.

Development of Microsatellite Loci Exhibiting Reverse Ascertainment Bias and a Sexing Marker for use in Emperor Geese (Chen Canagica)

2017 ◽  
Vol 10 (4) ◽  
pp. 201-210 ◽  
Author(s):  
Meg C. Gravley ◽  
George K. Sage ◽  
Joel A. Schmutz ◽  
Sandra L. Talbot
Keyword(s):  
Microsatellite Loci ◽  
Statistical Power ◽  
Ascertainment Bias ◽  
Next Generation Sequencing Technology ◽  
Branta Bernicla ◽  
Black Brant ◽  
Expected Heterozygosity ◽  
Cackling Geese ◽  
The 1960S ◽  
Goose Species

The Alaskan population of Emperor Geese ( Chen canagica) nests on the Yukon–Kuskokwim Delta in western Alaska. Numbers of Emperor Geese in Alaska declined from the 1960s to the mid-1980s and since then, their numbers have slowly increased. Low statistical power of microsatellite loci developed in other waterfowl species and used in previous studies of Emperor Geese are unable to confidently assign individual identity. Microsatellite loci for Emperor Goose were therefore developed using shotgun amplification and next-generation sequencing technology. Forty-one microsatellite loci were screened and 14 were found to be polymorphic in Emperor Geese. Only six markers – a combination of four novel loci and two loci developed in other waterfowl species – are needed to identify an individual from among the Alaskan Emperor Goose population. Genetic markers for identifying sex in Emperor Geese were also developed. The 14 novel variable loci and 15 monomorphic loci were screened for polymorphism in four other Arctic-nesting goose species, Black Brant ( Branta bernicla nigricans), Greater White-fronted ( Anser albifrons), Canada ( B. canadensis) and Cackling ( B. hutchinsii) Goose. Emperor Goose exhibited the smallest average number of alleles (3.3) and the lowest expected heterozygosity (0.467). Greater White-fronted Geese exhibited the highest average number of alleles (4.7) and Cackling Geese the highest expected heterozygosity (0.599). Six of the monomorphic loci were variable and able to be characterised in the other goose species assayed, a predicted outcome of reverse ascertainment bias. These findings fail to support the hypothesis of ascertainment bias due to selection of microsatellite markers.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

scholarly journals Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Nabil Shaaban ◽  
Bárbara Peleteiro ◽  
Maria Rosario O. Martins
Keyword(s):  
Length Of Stay ◽  
Regression Model ◽  
Random Effects ◽  
Count Data ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Comprehensive Approach ◽  
Negative Binomial Regression Model ◽  
Hiv Patients ◽  
Binomial Regression

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.

scholarly journals Association between breakfast skipping and metabolic outcomes by sex, age, and work status stratification

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jun Heo ◽  
Won-Jun Choi ◽  
Seunghon Ham ◽  
Seong-Kyu Kang ◽  
Wanhyung Lee
Keyword(s):  
Regression Analysis ◽  
Negative Binomial ◽  
Metabolic Diseases ◽  
Young Male ◽  
Negative Binomial Regression ◽  
Final Analysis ◽  
Work Status ◽  
Breakfast Skipping ◽  
Metabolic Outcomes ◽  
Binomial Regression

Abstract Background The association between breakfast skipping and abnormal metabolic outcomes remains controversial. A comprehensive study with various stratified data is required. Objective The aim of this study was to investigate the relationship between abnormal metabolic outcomes and breakfast skipping by sex, age, and work status stratification. Methods We used data from the Korea National Health and Nutrition Examination Surveys from 2013 to 2018. A total of 21,193 (9022 men and 12,171 women) participants were included in the final analysis. The risk of metabolic outcomes linked to breakfast skipping was estimated using the negative binomial regression analysis by sex, work status, and age stratification. Results A total of 11,952 (56.4%) participants consumed breakfast regularly. The prevalence of abnormal metabolic outcomes was higher among those with irregular breakfast consumption habits. Among young male workers, negative binomial regression analysis showed that irregular breakfast eaters had a higher risk of abnormal metabolic outcomes, after adjusting for covariates (odds ratio, 1.15; 95% confidence interval, 1.03–1.27). Conclusions The risk of abnormal metabolic outcomes was significant in young men in the working population. Further studies are required to understand the association of specific working conditions (working hours or shift work) with breakfast intake status and the risk of metabolic diseases.

scholarly journals Coronary deaths during Midsummer festival in Finland: miseries of long, light nights

2021 ◽  
Author(s):  
Simo Näyhä
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Alcohol Consumption ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Adverse Consequence ◽  
Heavy Alcohol ◽  
Summer Peak ◽  
Binomial Regression ◽  
Heavy Alcohol Consumption

AbstractThis paper examines whether the anomalous summer peak in deaths from coronary heart disease (CHD) in Finland could be attributed to adverse effects of the Midsummer festival and alcohol consumption during the festival. Daily deaths from CHD and alcohol poisoning in Finland, 1961–2014, that occurred during the 7 days centering on Midsummer Day were analysed in relation to deaths during 14 to 4 days before and 4 to 14 after Midsummer Day. Daily counts of deaths from CHD among persons aged 35–64 years were regressed on days around the Midsummer period by negative binomial regression. Mortality from CHD was highest on Midsummer Day (RR 1.25 (95% confidence interval 1.12–1.31), one day after the peak in deaths from alcohol poisonings. RR for CHD on Midsummer Day was particulary high (RR = 1.43; 1.09–1.86) in the 2000s, 30% of deaths being attributable to that day. In conclusion, the anomalous and prominent summer peak in deaths from CHD in Finland is an adverse consequence of the Midsummer festival. The most likely underlying reason is heavy alcohol consumption during the festival period, especially on Midsummer Eve. In the 2000s, one third of deaths from CHD on Midsummer Day are preventable.

scholarly journals Analysis of Pneumonia Occurrence in Relation to Climate Change in Tanga, Tanzania

2021 ◽  
Vol 18 (9) ◽  
pp. 4731
Author(s):  
Samweli Faraja Miyayo ◽  
Patrick Opiyo Owili ◽  
Miriam Adoyo Muga ◽  
Tang-Huang Lin
Keyword(s):  
Climate Change ◽  
Negative Binomial ◽  
Health Management ◽  
Severe Pneumonia ◽  
Positive Association ◽  
Negative Binomial Regression ◽  
Health Management Information System ◽  
Cold Temperatures ◽  
Climate Indicators ◽  
And Control

In 2018, 70% of global fatalities due to pneumonia occurred in about fifteen countries, with Tanzania being among the top eight countries contributing to these deaths. Environmental and individual factors contributing to these deaths may be multifaceted, but they have not yet been explored in Tanzania. Therefore, in this study, we explore the association between climate change and the occurrence of pneumonia in the Tanga Region, Tanzania. A time series study design was employed using meteorological and health data of the Tanga Region collected from January 2016 to December 2018 from the Tanzania Meteorological Authority and Health Management Information System, respectively. The generalized negative binomial regression technique was used to explore the associations between climate indicators (i.e., precipitation, humidity, and temperature) and the occurrence of pneumonia. There were trend differences in climate indicators and the occurrence of pneumonia between the Tanga and Handeni districts. We found a positive association between humidity and increased rates of non-severe pneumonia (incidence rate ratio (IRR) = 1.01; 95% CI: 1.01–1.02; p ≤ 0.05) and severe pneumonia (IRR = 1.02; 95% CI: 1.01–1.03; p ≤ 0.05). There was also a significant association between cold temperatures and the rate of severe pneumonia in Tanga (IRR = 1.21; 95% CI: 1.11–1.33; p ≤ 0.001). Other factors that were associated with pneumonia included age and district of residence. We found a positive relationship between humidity, temperature, and incidence of pneumonia in the Tanga Region. Policies focusing on prevention and control, as well as promotion strategies relating to climate change-related health effects should be developed and implemented.

Sign in / Sign up

Export Citation Format

Share Document