Application of generalized additive models to examine ontogenetic and seasonal distributions of spiny dogfish (Squalus acanthias) in the Northeast (US) shelf large marine ecosystem

2014 ◽  
Vol 71 (6) ◽  
pp. 847-877 ◽  
Author(s):  
Skyler R. Sagarese ◽  
Michael G. Frisk ◽  
Robert M. Cerrato ◽  
Kathy A. Sosebee ◽  
John A. Musick ◽  
...  
Keyword(s):  
Generalized Additive Models ◽  
Marine Ecosystem ◽  
Additive Models ◽  
Squalus Acanthias ◽  
Seasonal Occurrence ◽  
Spiny Dogfish ◽  
Science Center ◽  
Large Marine Ecosystem ◽  
Northeast Us ◽  
The Relationship

Increased commercial importance of spiny dogfish (Squalus acanthias) combined with an often debated, and controversial, ecological impact has warranted an investigation of the relationship among distribution, environment, and prey to better understand the species ecology and inform management. To elucidate mechanisms behind distributional changes, we modeled seasonal occurrence and abundance of neonate, immature, and mature spiny dogfish as functions of abiotic and biotic factors using generalized additive models and Northeast Fisheries Science Center bottom trawl survey data. Significant nonlinear relationships were widespread throughout dogfish stages and seasons. Seasonal occurrence was tightly linked to depth and bottom temperature, with year and Julian day influential for some stages. While these factors also influenced abundance, ecological factors (e.g., squid abundances) significantly contributed to trends for many stages. Potential impacts of climate change were evaluated by forecasting distributions under different temperature scenarios, which revealed higher regional probabilities of occurrence for most stages during a warmer than average year. Our results can be used to better understand the relationship between sampling periods and movement drivers to survey catchability of the population in the Northeast (US) shelf large marine ecosystem.

Influence of environmental, spatial, and ontogenetic variables on habitat selection and management of spiny dogfish in the Northeast (US) shelf large marine ecosystem

2014 ◽  
Vol 71 (4) ◽  
pp. 567-580 ◽  
Author(s):  
Skyler R. Sagarese ◽  
Michael G. Frisk ◽  
Thomas J. Miller ◽  
Kathy A. Sosebee ◽  
John A. Musick ◽  
...  
Keyword(s):  
Habitat Selection ◽  
Environmental Conditions ◽  
Statistical Power ◽  
Stock Assessment ◽  
Marine Ecosystem ◽  
Spiny Dogfish ◽  
Trawl Survey ◽  
Science Center ◽  
Large Marine Ecosystem ◽  
Northeast Us

Declines in abundance of commercially valuable groundfish have highlighted the ecological and commercial importance of previously underutilized elasmobranchs in the Northeast (US) shelf large marine ecosystem (NES LME). Seasonal distributions and ontogenetic habitats of one such species, spiny dogfish (Squalus acanthias), were investigated using Northeast Fisheries Science Center (NEFSC) bottom trawl survey data (1963–2009). Neonate, immature, and mature dogfish all selected warmer, more saline, and more southerly locations during spring compared with available locations. During autumn, larger dogfish occupied relatively warmer, shallower, and less saline waters while neonates selected higher salinities. There were strong ontogenetic patterns in habitats occupied. Contrary to expectation, geographic range contracted as abundance increased during autumn. This suggests that niche constraints override density-dependent effects, although detection of relationships within stages was limited by low statistical power. The proportion of mature female survey catch within the Mid-Atlantic Bight was significantly related to temperature, suggesting that environmental conditions surveyed may impact population trends. Collectively, these results highlight critical habitats, suggest mechanisms behind ontogenetic habitat selection, and provide insight into how changing environmental conditions may impact stock assessment.

scholarly journals Bounds on Biomass Estimates and Energetic Consequences of Ctenophora in the Northeast U.S. Shelf Ecosystem

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Michael D. Ford ◽  
Jason S. Link
Keyword(s):  
Feeding Strategy ◽  
Marine Ecosystem ◽  
High Energy ◽  
Gelatinous Zooplankton ◽  
Squalus Acanthias ◽  
High Energy Density ◽  
Spiny Dogfish ◽  
Sampling Device ◽  
Large Marine Ecosystem ◽  
Major Increase

Previous descriptions have noted that the stomach samples of spiny dogfish, Squalus acanthias, showed a major increase in the overall occurrence and hence implied abundance of Ctenophora. This apparent and persistent gelatinous zooplankton outbreak is increasingly more common in the world’s oceans. We briefly explore the energetic ramifications of ctenophores in the spiny dogfish diet, inferring that the presence of gelatinous zooplankton represents an ambient feeding strategy. Relative to other prey, ctenophores are not a high energy density prey item. However, given varying assumptions of the amount of ctenophores consumed, they may be an important staple in the diet of spiny dogfish. We also examine the utility of using spiny dogfish as a gelatinous zooplankton sampling device. Using five calculation methodologies, we provide bounds on potential abundance and biomass estimates of ctenophores in the Northeast U.S. shelf ecosystem. We then contextualize these findings relative to the implications for the Northeast U.S. and any large marine ecosystem.

scholarly journals Spatiotemporal overlap of spiny dogfish (Squalus acanthias) and commercial fisheries in the northeast U.S. shelf large marine ecosystem

2015 ◽  
Vol 113 (2) ◽  
pp. 101-120 ◽  
Author(s):  
Skyler R. Sagarese ◽  
Michael G. Frisk ◽  
Robert M. Cerrato ◽  
Kathy A. Sosebee ◽  
John A. Musick ◽  
...  
Keyword(s):  
Marine Ecosystem ◽  
Squalus Acanthias ◽  
Commercial Fisheries ◽  
Spiny Dogfish ◽  
Large Marine Ecosystem

The Relationship between Mobility and COVID-19 in Germany: Modeling Case Occurrence using Apple's Mobility Trends Data

2021 ◽  
Author(s):  
Mark David Walker ◽  
Mihály Sulyok
Keyword(s):  
Generalized Additive Models ◽  
Information Criterion ◽  
Additive Models ◽  
Online Data ◽  
German Government ◽  
Explanatory Variables ◽  
Mobility Data ◽  
Community Mobility ◽  
The Relationship ◽  
Potential Use

Abstract Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. Objective The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany? Methods AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response. Results Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with “driving,” 2511. “transit,” 2513. “walking,” 2508). Conclusion These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.

ENVIRONMENTAL DISASTERS IN NORTHEAST BRAZIL: HYDROMETEOROLOGICAL, SOCIAL AND SANITARY FACTORS

2021 ◽  
Author(s):  
Marcos Samuel Matias Ribeiro ◽  
Lara de Melo Barbosa Andrade ◽  
Maria Helena Constantino Spyrides ◽  
Kellen Carla Lima ◽  
Pollyane Evangelista da Silva ◽  
...  
Keyword(s):  
Generalized Additive Models ◽  
Flash Floods ◽  
Additive Models ◽  
Northeast Brazil ◽  
Waste Collection ◽  
Climate Conditions ◽  
Environmental Disasters ◽  
Basic Services ◽  
The Relationship ◽  
Drought Occurrence

AbstractThe occurrence of environmental disasters affects different social segments, impacting health, education, housing, economy and the provision of basic services. Thus, the objective of this study was to estimate the relationship between the occurrence of disasters and extreme climate, sociosanitary and demographic conditions in the Northeast region of Brazil during the period from 1993 to 2013. Initially, we analyzed the spatial pattern of the incidence of events and, subsequently, generalized additive models for location, scale and shape were used in order to identify and estimate the magnitude of associations between factors. Results showed that droughts are the predominant disasters in the NEB representing 81.1% of the cases, followed by events triggered by excessive rainfall such as flash floods (11.1%) and floods (7.8%). Climate conditions presented statistically significant associations with the analyzed disasters, in which indicators of excess rainfall positively contributed to the occurrence of flash floods and floods, but negatively contributed to the occurrence of drought. Sociosanitary factors, such as percentage of households with inadequate sewage, waste collection and water supply, were also positively associated with the model’s estimations, i.e., contributing to an increase in the occurrence of events, with the exception of floods, which were not significantly influenced by sociosanitary parameters. A decrease of 19% in the risk of drought occurrence was estimated, on average. On the other hand, events caused by excessive rainfall increased by 40% and 57%, in the cases of flash floods and floods, respectively.

scholarly journals Spatial distribution of marine macro-litter on the seafloor in the northern Mediterranean Sea: the MEDITS initiative

2020 ◽  
Vol 83 (S1) ◽  
pp. 257 ◽  
Author(s):  
Maria Teresa Spedicato ◽  
Walter Zupa ◽  
Pierluigi Carbonara ◽  
Fabio Fiorentino ◽  
Maria Cristina Follesa ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Generalized Additive Models ◽  
Marine Ecosystem ◽  
Anthropogenic Pollution ◽  
Additive Models ◽  
Spatial Density ◽  
Southern Cyprus ◽  
Local Water ◽  
Global Threat ◽  
Anticyclonic Eddies

Marine litter is one of the main sources of anthropogenic pollution in the marine ecosystem, with plastic representing a global threat. This paper aims to assess the spatial distribution of plastic macro-litter on the seafloor, identifying accumulation hotspots at a northern Mediterranean scale. Density indices (items km–2) from the MEDITS trawl surveys (years 2013-2015) were modelled by generalized additive models using a Delta-type approach and several covariates: latitude, longitude, depth, seafloor slope, surface oceanographic currents and distances from main ports. To set thresholds for the identification of accumulation areas, the percentiles (85th, 90th and 95th) of the plastic spatial density distribution were computed on the raster data. In the northern Mediterranean marine macro-litter was widespread (90.13% of the 1279 surveyed stations), with plastic by far the most recurrent category. The prediction map of the plastic density highlighted accumulation areas (85th, 90th and 95th percentiles of the distribution, respectively, corresponding to 147, 196 and 316 items km–2) in the Gulf of Lions, eastern Corsica, the eastern Adriatic Sea, the Argo-Saronic region and waters around southern Cyprus. Maximum densities were predicted in correspondence to the shallower depths and in proximity to populated areas (distance from the ports). Surface currents and local water circulation with cyclonic and anticyclonic eddies were identified as drivers likely facilitating the sinking to the bottoms of floating debris.

scholarly journals A Longitudinal Analysis of the Impact of Distance Driven on the Probability of Car Accidents

Risks ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 91
Author(s):  
Jean-Philippe Boucher ◽  
Roxane Turcotte
Keyword(s):  
Poisson Distribution ◽  
Fixed Effects ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Panel Count Data ◽  
Insurance Company ◽  
Smooth Functions ◽  
Claim Frequency ◽  
The Impact ◽  
The Relationship

Using telematics data, we study the relationship between claim frequency and distance driven through different models by observing smooth functions. We used Generalized Additive Models (GAM) for a Poisson distribution, and Generalized Additive Models for Location, Scale, and Shape (GAMLSS) that we generalize for panel count data. To correctly observe the relationship between distance driven and claim frequency, we show that a Poisson distribution with fixed effects should be used because it removes residual heterogeneity that was incorrectly captured by previous models based on GAM and GAMLSS theory. We show that an approximately linear relationship between distance driven and claim frequency can be derived. We argue that this approach can be used to compute the premium surcharge for additional kilometers the insured wants to drive, or as the basis to construct Pay-as-you-drive (PAYD) insurance for self-service vehicles. All models are illustrated using data from a major Canadian insurance company.

scholarly journals Leopard Seals (Hydrurga leptonyx) in New Zealand Waters Predating on Chondrichthyans

2021 ◽  
Vol 8 ◽  
Author(s):  
Krista van der Linde ◽  
Ingrid N. Visser ◽  
Rick Bout ◽  
Chris Lalas ◽  
Lara Shepherd ◽  
...  
Keyword(s):  
New Zealand ◽  
Dna Sequencing ◽  
High Frequency ◽  
Marine Ecosystem ◽  
Marine Ecosystems ◽  
Squalus Acanthias ◽  
Spiny Dogfish ◽  
Frequency Of Occurrence ◽  
Morphological Examination ◽  
Hydrurga Leptonyx

Leopard seals (Hydrurga leptonyx) are top-order predators that prey on a wide variety of species including crustaceans, cephalopods, fishes, birds, and pinnipeds. While multiple diet studies have been conducted worldwide, there are no previous accounts of leopard seals predating on chondrichthyans. As part of a wider study on the diet of leopard seals in New Zealand (NZ) waters, researchers and citizen scientists recorded 39 observations of predation and collected 127 scats (166 total records) between 1942 and 2019. Predation on chondrichthyans was detected in 23.1% (n = 9) of observations of predation and 7.1% (n = 9) of scats (the latter via morphological examination and DNA sequencing). From both observations of predations and scats, three chondrichthyan species or genus were identified; elephantfish (Callorhinchus milii), ghost sharks (Hydrolagus spp.) and spiny dogfish (Squalus acanthias). While this is the first published record of leopard seals feeding on chondrichthyans, the relatively high frequency of occurrence within our NZ records, and that certain individuals appeared to target this type of prey, indicates that these species could constitute a substantial, or important, part of the diet for some leopard seals in this region. As chondrichthyans form an important part of the NZ marine ecosystems, our recognition of an additional top-order predator of these species contributes to understanding the overall health of, and future impacts of predators on, the wider NZ marine ecosystem.

scholarly journals A Decision Support Model for the Necessity of Cardio-Angiography, A Result of Generalized Additive and logistic Regression Model

2021 ◽  
Author(s):  
Fatemeh Rezaeisharif ◽  
Azadeh Saki ◽  
Ali Taghipour ◽  
Mohammad Tajfard
Keyword(s):  
Coronary Artery ◽  
Blood Sugar ◽  
Logistic Regression Model ◽  
Generalized Additive Models ◽  
Coronary Artery Occlusion ◽  
Artery Occlusion ◽  
Additive Models ◽  
Evidence Based ◽  
Hs Crp ◽  
The Relationship

Introduction: Angiography is used as the gold standard for diagnosis of coronary artery disease (CAD). It is an invasive procedure and has several complications. Also, some patients refuse angiograms for reasons such as fear, high cost, and loss of trust in physician diagnosis. The negative results of this test is more than a third. Therefore, having a statistical predictive model for estimating the risk of CAD, as an evidence-based support system, can help the physician and patient decide on the necessity of angiography. Aims: In this study we aimed to find an evidence-based supportive model for decision making on the necessity of angiography in people who were candidates for angiography by the physician after initial tests. Methods: In this study, 1187 patients who had been referred to Ghaem Hospital of Mashhad University of Medical Sciences and diagnosed with physicians after initial tests were enrolled. Demographic data, lipid and blood sugar levels, and the history of underlying disorders were variables that were studied in the statistical model fitting. Initially, generalized additive models were used singularly for quantitative predictors, then by applying right transformations on the predictor variables we entered them simultaneously in logistic and count regression models. These two models were fitted to the data using R software and then compared in terms of predictive accuracy. Findings: Generalized additive models showed that the relationship between CAD with the hs-CRP level was not monotone. Exploratory analyzes showed that 62% of people with hs-CRP level <3 and 50% of people with hs-CRP levels between 3 and 6 were suffered from the CAD. The highest rate of CAD was seen in the range of 6-8 (93%) but with increasing the hs-CRP level to above 8 it decreased to 70%. The relationship between age and the risk of CAD was S-shaped. Risk of CAD in diabetic subjects with normal FBS was equal to that of nondiabetic subjects with normal fasting blood sugar. The age, gender, diabetes, FBS, and hs-CRP were significant in both models (p <0.05). The area under the ROC curve was upgraded to 81 for the logistic model. Conclusion: The most important finding of this exploratory study was that out of 232 patients with hs-CRP level between 6 to 8, 217 (93%) had coronary artery occlusion, for these subjects the probability of occluding a coronary artery was 0.93. The present study also showed that if the blood sugar is controlled in patients with diabetes, then this disease will not be a risk factor for patients with coronary artery occlusion. The logistic regression model presented in this study is recommended as the final model to support decision-making about the necessity of angiography.

scholarly journals Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental Health and Income

2019 ◽  
Vol 16 (20) ◽  
pp. 4009 ◽  
Author(s):  
Alexander Silbersdorff ◽  
Kai Sebastian Schneider
Keyword(s):  
Mental Health ◽  
Health Inequalities ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Mental Health Score ◽  
Cross Sectional ◽  
Regression Techniques ◽  
German Socioeconomic Panel ◽  
The Relationship ◽  
Distributional Regression

This study addresses the much-discussed issue of the relationship between health and income. In particular, it focuses on the relation between mental health and household income by using generalized additive models of location, scale and shape and thus employing a distributional perspective. Furthermore, this study aims to give guidelines to applied researchers interested in taking a distributional perspective on health inequalities. In our analysis we use cross-sectional data of the German socioeconomic Panel (SOEP). We find that when not only looking at the expected mental health score of an individual but also at other distributional aspects, like the risk of moderate and severe mental illness, that the relationship between income and mental health is much more pronounced. We thus show that taking a distributional perspective, can add to and indeed enrich the mostly mean-based assessment of existent health inequalities.

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