scholarly journals Essential habitat for sardine juveniles in Iberian waters

2017 ◽  
Vol 81 (3) ◽  
pp. 351 ◽  
Author(s):  
Sílvia Rodríguez-Climent ◽  
Maria Manuel Angélico ◽  
Vítor Marques ◽  
Paulo Oliveira ◽  
Laura Wise ◽  
...  
Keyword(s):  
Fishery Management ◽  
Generalized Additive Models ◽  
Management Strategies ◽  
Coastal Region ◽  
Additive Models ◽  
Spawning Grounds ◽  
Significant Relationships ◽  
Juvenile Abundance ◽  
Spatial Differences ◽  
Core Areas

In a period when the Iberian sardine stock abundance is at its historical minimum, knowledge of the sardine juvenile’s distribution is crucial for the development of fishery management strategies. Generalized additive models were used to relate juvenile sardine presence with geographical variables and spawning grounds (egg abundance) and to model juvenile abundance with the concurrent environmental conditions. Three core areas of juvenile distribution were identified: the Northern Portuguese shelf (centred off Aveiro), the coastal region in the vicinity of the Tagus estuary, and the eastern Gulf of Cadiz. Spatial differences in the relationship between juvenile presence and egg abundances suggest that essential juvenile habitat might partially differ from the prevailing spawning grounds. Models also depicted significant relationships between juvenile abundance, temperature and geographical variables in combination with salinity in the west and with zooplankton in the south. Results indicate that the sardine juvenile distribution along the Iberian Peninsula waters are an outcome of a combination of dynamic processes occurring early in life, such as egg and larva retention, reduced mortality and favourable feeding grounds for both larvae and juveniles.

scholarly journals From the Adriatic to Northern Norway—geographic differences in moult increment and moult probability of the European lobster (Homarus gammarus), across the natural range

2020 ◽  
Author(s):  
Matthew T Coleman ◽  
Anne-Lisbeth Agnalt ◽  
Jack Emmerson ◽  
Martial Laurens ◽  
Joanne S Porter ◽  
...  
Keyword(s):  
Fishery Management ◽  
Stock Assessment ◽  
Generalized Additive Models ◽  
Growth Patterns ◽  
Additive Models ◽  
Geographical Differences ◽  
Homarus Gammarus ◽  
Northern Latitudes ◽  
Natural Range ◽  
Geographic Differences

Abstract This study collated existing data on lobster moult increment from studies across the range of Homarus gammarus, together with new tagging data from Orkney, United Kingdom. Generalized additive models were used to investigate geographical differences in absolute moult increment and moult probability. Absolute moult increment was seen to differ significantly between regions and between sexes and showed a non-linear relationship with pre-moult size. Smaller absolute moult increments were observed at southern and northern latitudes with larger increments observed in the centre of the species range. Temperature was identified as a significant factor explaining differences in absolute moult increment between regions, consistent with there being a thermal optimum for growth for in H. gammarus. Moult and double moult probabilities decline with pre-moult size, with greatest probability of moulting occurring around day 250. Probability of double moulting increased with mean annual sea surface temperature. Regionally variable growth patterns, and localized adaptation to abiotic variables such as temperature, should therefore be taken into account when defining lobster stock assessment and fishery management areas.

Changes in the timing and length of the fire season in Spain

2020 ◽  
Author(s):  
Itziar R. Urbieta ◽  
Gonzalo Arellano ◽  
José M. Moreno
Keyword(s):  
Fire Suppression ◽  
Generalized Additive Models ◽  
Summer Season ◽  
Additive Models ◽  
Fire Season ◽  
Burned Area ◽  
Burned Areas ◽  
Spatial Differences ◽  
Mediterranean Regions ◽  
In Fire

<p>Fire activity has decreased in the last decades in Spain, as a whole and in most regions. However, little is known about the changes in the fire season peak, timing, and length. Here we studied the temporal variation in the fire season since the 1970’s for different Spanish regions. We analyzed weekly time series of annually burned area by fitting GAMs (Generalized Additive Models) models in R. Area burned was log transformed and smoothing P-splines were fit to study weekly seasonality. GAMS allowed us to model spring, summer, and autumn fire seasons. Changes in the sign of the smoothing parameter determined the timing (onset/end dates) of each fire season, while the maximum value of the parameter established the peak of the fire season. We applied trend analysis to study inter-annual variation in fire season timing, length, and amplitude. We found temporal and spatial differences in the fire season across regions. In the northern Atlantic regions, models performed better, and captured a bimodal fire season (spring-summer). Nonetheless, the bimodal fire-season structure is no longer distinguishable in recent years, since both are increasing in duration. In the Mediterranean regions, larger peaks of burned areas occur in shorter time spans. The amplitude and duration of the summer season is decreasing, probably due to the increase in fire suppression during the summer. The summer season is starting earlier, while, in general, no trend was found for the end of the season. Furthermore, spring fire peaks in Mediterranean regions are becoming more frequent, suggesting that more attention should be paid to these out-of-season conditions.</p>

scholarly journals Changes in Planktivory and Herbivory Regimes in a Shallow South American Lake (Lake Blanca Chica, Argentina) Over the Last 250 Years

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 597
Author(s):  
David Carrozzo ◽  
Simona Musazzi ◽  
Andrea Lami ◽  
Francisco E. Córdoba ◽  
María de los Ángeles González Sagrario
Keyword(s):  
Size Structure ◽  
Generalized Additive Models ◽  
Management Strategies ◽  
Zooplankton Community ◽  
Fish Predation ◽  
Additive Models ◽  
Fish Scales ◽  
Pheophorbide A ◽  
Food Web Structure ◽  
Species Dominance

Shallow lakes are vulnerable ecosystems impacted by human activities and climate change. The Cladocera occupy a central role in food webs and are an excellent paleoecological indicator of food web structure and trophic status. We conducted a paleolimnological study in Lake Blanca Chica (Argentina) to detect changes on the planktivory and herbivory regimes over the last 250 years. Generalized additive models were fitted to the time series of fish predation indicators (ephippial abundance and size, mucrone size, fish scales, and the planktivory index) and pheophorbide a concentration. The cladoceran assemblage changed from littoral-benthic to pelagic species dominance and zooplankton switched from large-bodied (Daphnia) to small-bodied grazers (Bosmina) ca. 1900 due to increased predation. The shift in planktivory regime (ca. 1920–1930), indicated by fish scales and the planktivory index, as well as herbivory (ca. 1920–1950), was triggered by eutrophication. Changes in planktivory affected the size structure of Bosmina, reducing its body size. This study describes the baseline for the lake as well as the profound changes in the composition and size structure of the zooplankton community due to increased predation and the shift in the planktivory regime. These findings will provide a reference status for future management strategies of this ecosystem.

Impact of Weather, Activities, and Service Disruptions on Transportation Demand

2020 ◽  
pp. 036119812096632
Author(s):  
Simon Lepage ◽  
Catherine Morency
Keyword(s):  
Travel Demand ◽  
Moving Average ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Subway Station ◽  
Transportation Demand ◽  
Transportation Service ◽  
Moving Average Models ◽  
Spatial Differences ◽  
Demand Fluctuations

This paper aims to estimate short-term transportation demand fluctuations because of events such as meteorological events, major activities, and subway service disruptions. Four different modes are analyzed and compared, being bikesharing, taxi, subway, and bus. Case study includes 3 years of transactional data on working days collected in Montreal, Canada. Generalized additive models (GAM) are developed for every mode. The dependent variable is the hourly number of trip departures from one subway station neighborhood. Independent variables are data from various events. Different models are calibrated for every subway station neighborhood to better understand spatial differences. Also, performance of GAM and autoregressive integrated moving average models are compared for prediction on different horizons. Results suggest that presence of rain decreases bikesharing, subway, and bus demand, while increasing taxi demand. In fact, after four consecutive hours of rain, bikesharing demand decreases by 28.0%, subway and bus demand decreases by 4.6%, while taxi increases by 13.9%. Wind is only found significant for bikesharing. Temperature is found significant for all four modes but has a larger effect on bikesharing and taxi. Moreover, demand increases significantly during subway service disruptions for the three alternative modes studied, especially for taxi, suggesting an increase in demand of 182% during disruptions of 1 h. Furthermore, activities influence demand for all four modes, but subway seems to be the most affected one. This method allows for a better understanding of travel behaviors and makes it possible to consider a more dynamic adaptation of the transportation service supply to match travel demand based on various events. This could lead to better co-planning of events and transportation service, for example by temporarily increasing subway frequency or changing the position of some bikesharing stations.

scholarly journals Failure to estimate reliable sex ratios of guanaco from road-survey data

2009 ◽  
Vol 87 (10) ◽  
pp. 886-894 ◽  
Author(s):  
Julieta Pedrana ◽  
Alejandro Rodríguez ◽  
Javier Bustamante ◽  
Alejandro Travaini ◽  
Juan I. Zanón Martínez
Keyword(s):  
Sex Ratio ◽  
Null Hypothesis ◽  
Generalized Additive Models ◽  
Sex Ratios ◽  
Time Of Day ◽  
Additive Models ◽  
Family Group ◽  
Juvenile Abundance ◽  
Adult Sex Ratio ◽  
Parsimonious Model

The guanaco ( Lama guanicoe (Müller, 1776)) is a monomorphic polygynous mammal whose adult sex ratio is expected to be balanced or biased towards females. Remarkably male-biased sex ratios of adult guanacos are often estimated from road surveys. We analyzed the distribution of guanaco social groups recorded during road surveys in Patagonia, Argentina, to test the hypothesis that group assignation based upon behavioral traits is not unequivocal and can be biased by survey factors. Guanacos are organized into three social units (family groups, male groups, and solitary males) that are identified by their grouping behaviour. We recorded 992 guanaco groups, and estimated an adult sex ratio of 3.2 males/female. We used generalized additive models to test the null hypothesis that the probability of recording a group as a family group was constant. Alternatively, this probability could decrease when juvenile abundance and (or) detectability was low. The most parsimonious model showed that the probability of classifying a “family” group increased with date, and decreased with group size, distance to the observer, and time of day. Our results do not support the null hypothesis and suggest that road surveys are unsuitable to estimate reliably the social structure or sex ratio of guanaco populations.

scholarly journals Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

2020 ◽  
Vol 17 (17) ◽  
pp. 6339
Author(s):  
François Freddy Ateba ◽  
Manuel Febrero-Bande ◽  
Issaka Sagara ◽  
Nafomon Sogoba ◽  
Mahamoudou Touré ◽  
...  
Keyword(s):  
Wind Speed ◽  
Malaria Incidence ◽  
Generalized Additive Models ◽  
Community Health Center ◽  
Additive Model ◽  
Additive Models ◽  
Functional Regression ◽  
Novel Approach ◽  
Malaria Incidence Rate ◽  
Mean Wind Speed

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.

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.

scholarly journals Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Narayan Sharma ◽  
René Schwendimann ◽  
Olga Endrich ◽  
Dietmar Ausserhofer ◽  
Michael Simon
Keyword(s):  
Hospital Mortality ◽  
Patient Population ◽  
Generalized Additive Models ◽  
Routine Data ◽  
Predictive Performance ◽  
Population Based ◽  
Mortality Prediction ◽  
Additive Models ◽  
General Hospitals ◽  
Net Reclassification Improvement

Abstract Background Understanding how comorbidity measures contribute to patient mortality is essential both to describe patient health status and to adjust for risks and potential confounding. The Charlson and Elixhauser comorbidity indices are well-established for risk adjustment and mortality prediction. Still, a different set of comorbidity weights might improve the prediction of in-hospital mortality. The present study, therefore, aimed to derive a set of new Swiss Elixhauser comorbidity weightings, to validate and compare them against those of the Charlson and Elixhauser-based van Walraven weights in an adult in-patient population-based cohort of general hospitals. Methods Retrospective analysis was conducted with routine data of 102 Swiss general hospitals (2012–2017) for 6.09 million inpatient cases. To derive the Swiss weightings for the Elixhauser comorbidity index, we randomly halved the inpatient data and validated the results of part 1 alongside the established weighting systems in part 2, to predict in-hospital mortality. Charlson and van Walraven weights were applied to Charlson and Elixhauser comorbidity indices. Derivation and validation of weightings were conducted with generalized additive models adjusted for age, gender and hospital types. Results Overall, the Elixhauser indices, c-statistic with Swiss weights (0.867, 95% CI, 0.865–0.868) and van Walraven’s weights (0.863, 95% CI, 0.862–0.864) had substantial advantage over Charlson’s weights (0.850, 95% CI, 0.849–0.851) and in the derivation and validation groups. The net reclassification improvement of new Swiss weights improved the predictive performance by 1.6% on the Elixhauser-van Walraven and 4.9% on the Charlson weights. Conclusions All weightings confirmed previous results with the national dataset. The new Swiss weightings model improved slightly the prediction of in-hospital mortality in Swiss hospitals. The newly derive weights support patient population-based analysis of in-hospital mortality and seek country or specific cohort-based weightings.

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