Size-related habitat use, aggregation patterns and abundance of anglerfish (Lophius budegassa) in the Mediterranean Sea determined by generalized additive modelling

2003 ◽  
Vol 83 (5) ◽  
pp. 1171-1178 ◽  
Author(s):  
Christos Maravelias ◽  
Costas Papaconstantinou
Keyword(s):  
Generalized Additive Models ◽  
Aegean Sea ◽  
Distribution Patterns ◽  
Habitat Associations ◽  
Additive Models ◽  
Seasonal Effects ◽  
Nursery Ground ◽  
Size Category ◽  
Aegean Area ◽  
Eastern Aegean

Spatial distribution patterns of black anglerfish, Lophius budegassa were examined in relation to size category, bathymetry, locational covariates, and season. Data were collected during a 2-y period (1998–1999) of quasi-synoptic seasonal sampling using demersal trawl surveys in the Aegean Sea. Generalized additive models (GAMs) were used to test the hypotheses that there was size-related variation in species' habitat associations and that the study area might serve as a nursery ground for black anglerfish. The current results supported these hypotheses. Data are presented that reveal size-dependent aggregation patterns of black anglerfish and an important habitat utilization of the north-eastern Aegean area. The modelled anglerfish abundances showed a strongly non-linear dependence on the explanatory covariates. The different size-classes exhibited significant seasonal effects and preferences for specific regions and distinct water depths. The present results also suggested that 1-y-old fish and potential spawners appeared to concentrate in the vicinity of the same areas. Two main areas of juvenile aggregations were detected in the deeper water regions of the study area on a seabed of around 300 m depth; both emerged in the proximity of the locations of larger fish. The bathymetric distribution of intermediate size anglerfish followed an inverse trend, with fish captured mainly in shallower waters. Results indicated a preferential aggregation of 1-y-old L. budegassa in the study area that is hypothesized to influence the supply of recruits to distant regions of the Aegean Sea.

Using habitat association models to predict Alewife and Blueback Herring marine distributions and overlap with Atlantic Herring and Atlantic Mackerel: can incidental catches be reduced?

2015 ◽  
Vol 73 (7) ◽  
pp. 1912-1924 ◽  
Author(s):  
Sara M. Turner ◽  
John P. Manderson ◽  
David E. Richardson ◽  
John J. Hoey ◽  
Jonathan A. Hare
Keyword(s):  
Environmental Gradients ◽  
Generalized Additive Models ◽  
Habitat Associations ◽  
Additive Models ◽  
Clupea Harengus ◽  
Atlantic Herring ◽  
Alosa Pseudoharengus ◽  
Atlantic Mackerel ◽  
Blueback Herring ◽  
River Herring

Abstract Concern over the impacts of incidental catches of Alewife, Alosa pseudoharengus and Blueback Herring, A. aestivalis (collectively managed as ‘river herring’) in the commercial Atlantic Herring (Clupea harengus) and Atlantic Mackerel (Scomber scombrus) fisheries has resulted in the recent implementation of river herring incidental catch limits. These incidental catches are highly variable in frequency and magnitude, and the environmental conditions associated with these catches are poorly understood. We used generalized additive models (GAMs) to describe habitat associations of Alewife, Blueback Herring, Atlantic Herring, and Atlantic Mackerel. Bottom temperature, bottom depth, bottom salinity, solar azimuth and elevation, and region of the Northeast U.S. continental shelf were all significant in the habitat models; GAMs explained 25.2, 16.9, 18.9, and 20.6% of the deviance observed for the presence/absence of Alewife, Blueback Herring, Atlantic Herring, and Atlantic Mackerel. A subset of the data was omitted from the model and the probability of presence was compared with observations; 66–77% of observations were correctly predicted. The individual probabilities of presence were used to quantify and evaluate the accuracy of modelled overlap of Alewife and Blueback Herring with Atlantic Herring (68–72% correct predictions) and Alewife and Blueback Herring with Atlantic Mackerel (57–69% correct predictions). Our findings indicate that environmental gradients influence the distributions and overlap of Alewife, Blueback Herring, Atlantic Herring, and Atlantic Mackerel, and with further testing and refinement these models could be developed into a tool to aid industry in reducing incidental catches of river herring.

scholarly journals Snowpack Distribution Using Topographical, Climatological and Winter Season Index Inputs

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 3
Author(s):  
Douglas M. Hultstrand ◽  
Steven R. Fassnacht ◽  
John D. Stednick ◽  
Christopher A. Hiemstra
Keyword(s):  
Snow Depth ◽  
Depth Distribution ◽  
Generalized Additive Models ◽  
Winter Season ◽  
Regression Tree ◽  
Distribution Patterns ◽  
Time Frame ◽  
Additive Models ◽  
Depth Measurement ◽  
Accumulation Index

A majority of the annual precipitation in many mountains falls as snow, and obtaining accurate estimates of the amount of water stored within the snowpack is important for water supply forecasting. Mountain topography can produce complex patterns of snow distribution, accumulation, and ablation, yet the interaction of topography and meteorological patterns tends to generate similar inter-annual snow depth distribution patterns. Here, we question whether snow depth patterns at or near peak accumulation are repeatable for a 10-year time frame and whether years with limited snow depth measurement can still be used to accurately represent snow depth and mean snow depth. We used snow depth measurements from the West Glacier Lake watershed, Wyoming, U.S.A., to investigate the distribution of snow depth. West Glacier Lake is a small (0.61 km2) windswept (mean of 8 m/s) watershed that ranges between 3277 m and 3493 m. Three interpolation methods were compared: (1) a binary regression tree, (2) multiple linear regression, and (3) generalized additive models. Generalized additive models using topographic parameters with measured snow depth presented the best estimates of the snow depth distribution and the basin mean amounts. The snow depth patterns near peak accumulation were found to be consistent inter-annually with an average annual correlation coefficient (r2) of 0.83, and scalable based on a winter season accumulation index (r2 = 0.75) based on the correlation between mean snow depth measurements to Brooklyn Lake snow telemetry (SNOTEL) snow depth data.

Habitat partitioning and the influence of benthic topography and oceanography on the distribution of fin and minke whales in the Bay of Fundy, Canada

2007 ◽  
Vol 87 (1) ◽  
pp. 149-156 ◽  
Author(s):  
Simon N. Ingram ◽  
Laura Walshe ◽  
Dave Johnston ◽  
Emer Rogan
Keyword(s):  
Linear Relationship ◽  
Linear Models ◽  
Generalized Additive Models ◽  
Bottom Topography ◽  
Distribution Patterns ◽  
Additive Models ◽  
Bay Of Fundy ◽  
Fin Whale ◽  
Minke Whales ◽  
Fin Whales

We collected data on the distribution of fin whales (Balaenoptera physalus) and minke whales (Balaenoptera acutorostrata) in the Bay of Fundy, Canada from a whale-watching vessel during commercial tours between July and September 2002. A single observer recorded the positions, species, numbers and surface activity of whales encountered during boat tours. We controlled for biased search effort by calculating sightings rates for both species in cells measuring 2′ latitude by 2′ longitude throughout the study area. Sightings rates were calculated by dividing the number of sightings of fin and minke whales in each cell by the number of visits by the tour boat to that cell. We used generalized additive models and generalized linear models to examine the influence of benthic topography on whale distribution patterns. Models showed a non-linear relationship for minke whale sighting rates with increasing benthic slopes and a linear relationship for minke and fin whale sightings rates with increasing water depth. Sightings of minkes were concentrated in areas subject to tidal wakes near the northern tips of Grand Manan and Campobello Island. Fin whales were also found off the northern tip of Grand Manan but sighting rates for this species were highest in areas with less benthic sloping topography adjacent to the relatively deep Owen Basin. Foraging was recorded during 87% of all whale encounters and our results indicate that whale distribution in this area is likely to be influenced by depth, bottom topography and fine scale oceanographic features that facilitate foraging.

scholarly journals Krill space: a comparative assessment of mesoscale structuring in polar and temperate marine ecosystems

2012 ◽  
Vol 69 (7) ◽  
pp. 1317-1327 ◽  
Author(s):  
Jarrod A. Santora ◽  
William J. Sydeman ◽  
Isaac D. Schroeder ◽  
Christian S. Reiss ◽  
Brian K. Wells ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Generalized Additive Models ◽  
Marine Ecosystems ◽  
Comparative Assessment ◽  
Habitat Associations ◽  
Shelf Break ◽  
Additive Models ◽  
Reference Points ◽  
Habitat Characteristics ◽  
Chl A

Abstract Santora, J. A., Sydeman, W. J., Schroeder, I. D., Reiss, C. S., Wells, B. K., Field, J. C, Cossio, A. M., and Loeb, V. J. 2012. Krill space: a comparative assessment of mesoscale structuring in polar and temperate marine ecosystems. – ICES Journal of Marine Science, 69: . The spatial organization, mesoscale variability, and habitat associations of krill within portions of the Antarctic Peninsula and California Current marine ecosystems are compared. Using a decade of acoustic observations and remotely sensed oceanography (2000–2009), the hypothesis that mesoscale spatial organization of krill in both systems closely relates to geospatial variability of the shelf break and is non-linearly related to geostrophic flow and positively related to chlorophyll a (Chl a) is tested. Directional-dependence analysis to measure spatial variability of krill is used along with spatially explicit generalized additive models to quantify and compare the spatial relationships among krill and habitat characteristics in both systems. The results suggest the following aspects of krill spatial organization: (i) areas of dense aggregation, i.e. hot spots, are present in both systems and are orientated in the direction of the shelf break, (ii) moderate levels of eddy kinetic energy seem to concentrate krill in favourable habitats and lessen the likelihood of advection away from the system, and (iii) variable responses to surface Chl a concentration suggest that real-time Chl a values may not be useful as a global predictor of important krill habitat. The results provide valuable reference points for marine spatial management of krill and for refining ecosystem and foodweb models.

Occurrence of primary almandine-spessartine-rich garnet and zinnwaldite phenocrysts in a Neogene rhyolite on the island of Chios, Aegean Sea, Greece

1999 ◽  
Vol 63 (4) ◽  
pp. 503-510 ◽  
Author(s):  
P. Mitropoulos ◽  
A. Katerinopoulos ◽  
A. Kokkinakis
Keyword(s):  
Volcanic Rocks ◽  
Aegean Sea ◽  
Mineralogical Composition ◽  
Volatile Constituents ◽  
Aegean Area ◽  
Tectonic Environment ◽  
Eastern Aegean ◽  
Rapid Ascent ◽  
Residual Product ◽  
Back Arc

AbstractPrimary almandine and spessartine-rich garnet and zinnwaldite phenocrysts occur along with feldspar (plagioclase and sanidine) phenocrysts, in the rhyolite of Profitis Ilias, which is located on the SE coast of the island of Chios, Greece. The distinctive mineralogical composition of this rhyolite is described. Although formed in the back-arc tectonic environment of the Aegean volcanic arc, the Profitis llias rhyolite shows significant trace element compositional differences when compared with typical arc or back-arc volcanic rocks of the area. It shows extreme depletion in Sr and Ba and enrichment in Nb and Mn, and has much more affinity with A-type granites and particularly Li-mica granites.Apparently, both zinnwaldite and spessartine-rich garnet can be generated as primary phases from a granite melt enriched in volatile constituents at low P–T. This granite melt could be the residual product of an un-exposed, earlier formed, typical back-arc granite of the area, enriched in volatile constituents from a subcrustal source above the active mantle of the eastern Aegean area.The extensive and deep faulting in the broad eastern Aegean lithosphere section would have facilitated the rapid ascent of that volatile-enriched granite melt, the parent of the Profitis Ilias rhyolite.

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.

scholarly journals Morphotectonic Analysis along the Northern Margin of Samos Island, Related to the Seismic Activity of October 2020, Aegean Sea, Greece

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 102
Author(s):  
Paraskevi Nomikou ◽  
Dimitris Evangelidis ◽  
Dimitrios Papanikolaou ◽  
Danai Lampridou ◽  
Dimitris Litsas ◽  
...  
Keyword(s):  
Fault Zone ◽  
Seismic Activity ◽  
Volcanic Rocks ◽  
Active Tectonics ◽  
Normal Fault ◽  
Aegean Sea ◽  
Northern Margin ◽  
The North ◽  
Eastern Aegean ◽  
Half Graben

On 30 October 2020, a strong earthquake of magnitude 7.0 occurred north of Samos Island at the Eastern Aegean Sea, whose earthquake mechanism corresponds to an E-W normal fault dipping to the north. During the aftershock period in December 2020, a hydrographic survey off the northern coastal margin of Samos Island was conducted onboard R/V NAFTILOS. The result was a detailed bathymetric map with 15 m grid interval and 50 m isobaths and a morphological slope map. The morphotectonic analysis showed the E-W fault zone running along the coastal zone with 30–50° of slope, forming a half-graben structure. Numerous landslides and canyons trending N-S, transversal to the main direction of the Samos coastline, are observed between 600 and 100 m water depth. The ENE-WSW oriented western Samos coastline forms the SE margin of the neighboring deeper Ikaria Basin. A hummocky relief was detected at the eastern margin of Samos Basin probably representing volcanic rocks. The active tectonics characterized by N-S extension is very different from the Neogene tectonics of Samos Island characterized by NE-SW compression. The mainshock and most of the aftershocks of the October 2020 seismic activity occur on the prolongation of the north dipping E-W fault zone at about 12 km depth.

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.

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