Accounting for responsive movement in line transect estimates of abundance

2001 ◽  
Vol 58 (4) ◽  
pp. 777-787 ◽  
Author(s):  
D L Palka ◽  
P S Hammond
Keyword(s):  
Animal Movement ◽  
Generalized Additive Models ◽  
Radial Distance ◽  
Additive Models ◽  
Line Transect ◽  
The North ◽  
Minke Whales ◽  
Orientation Density ◽  
Using Data ◽  
Animal Orientation

A method is developed to account for effects of animal movement in response to sighting platforms in line transect density estimates using data on animal orientation. Models of expected distributions of animal orientation show that presence of responsive movement is determined by the ratio of animal sightings with angles of orientation in the third quadrant relative to the first quadrant. The distance at which response began is estimated using logistic generalized additive models of the relationship between radial distance and orientation. Density corrected for responsive movement is estimated by applying the Buckland and Turnock two-team analysis method to data poststratified into regions "close" to and "far" from (beyond the distance that responsive movement began) the observation platform instead of the original stratification by observation team. For data collected in the North Atlantic, white-sided dolphins, harbor porpoises, and minke whales responded by avoiding the survey ship, and white-beaked dolphins were attracted to the ship. For these populations, our method to correct for responsive movement gave significantly higher estimates, from 1.4 to 2.7 times the uncorrected estimates.

Diel variation of stomach contents of North Sea cod (Gadus morhua) during a 24-h fishing survey: an analysis using generalized additive models

2000 ◽  
Vol 57 (12) ◽  
pp. 2363-2367 ◽  
Author(s):  
Sara A Adlerstein ◽  
Henny C Welleman
Keyword(s):  
North Sea ◽  
Stomach Content ◽  
Gadus Morhua ◽  
Generalized Additive Models ◽  
Stomach Contents ◽  
Additive Models ◽  
Large Prey ◽  
Diel Variation ◽  
The North ◽  
The North Sea

Results show that the weight of cod (Gadus morhua) stomach contents sampled in the North Sea varies significantly within 24 h. To determine whether feeding varied with time, over 1100 cod stomachs were collected around the clock between 7 and 18 May 1984 in two areas in the central North Sea thought to be representative for feeding studies. Here we investigate temporal feeding patterns based on the analysis of stomach-content data, using generalized additive models (GAMs). Results show significant variation of content weight and indicate morning and evening peaks. The relative peak importance differed between and within areas. We propose that differences are due to diet composition, namely, prey size and diel availability. Cod fed primarily on molluscs, mainly ocean quahog (Cyprina islandica), crustaceans, sandeels (Ammodytes spp.), haddock (Melanogrammus aeglefinus), herring (Clupea harrengus), and several flatfish species. In one area, the diet was dominated by fish, relatively large prey that perform diel vertical migration, and in the other by invertebrates, smaller prey that are digested faster. The diel pattern was more pronounced where invertebrate prey were dominant. Generalisation of results and implications for predation-mortality estimates based on data from the North Sea Stomach Content Database, used to implement multispecies models in the region, are discussed.

Spatial distribution analysis of the North Pacific spiny dogfish,Squalus suckleyi, in the North Pacific using generalized additive models

2017 ◽  
Vol 26 (6) ◽  
pp. 668-679 ◽  
Author(s):  
Toshikazu Yano ◽  
Seiji Ohshimo ◽  
Minoru Kanaiwa ◽  
Tsutomu Hattori ◽  
Masa-aki Fukuwaka ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
North Pacific ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Spiny Dogfish ◽  
Distribution Analysis ◽  
The North ◽  
The North Pacific

scholarly journals Modeling cow somatic cell count using sensor data as input to generalized additive models

2020 ◽  
Vol 87 (3) ◽  
pp. 282-289
Author(s):  
Dorota Anglart ◽  
Charlotte Hallén-Sandgren ◽  
Patrik Waldmann ◽  
Martin Wiedemann ◽  
Ulf Emanuelson
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Sensor Data ◽  
Udder Health ◽  
Independent Variables ◽  
Using Data ◽  
Sampling Event

AbstractThis research paper presents a study investigating if sensor data from an automatic milking rotary could be used to model cow somatic cell count (composite milk SCC: CMSCC). CMSCC is valuable for udder health monitoring and individual cow udder health surveillance could be improved by predicting CMSCC between routine samplings. Data regularly recorded in the automatic milking rotary, in one German dairy herd, were collected for analysis. The cows (Holstein-Friesian, n = 372) were milked twice daily and sampled once weekly in afternoon milkings for 8 weeks for CMSCC. From the potential independent variables, including quarter conductivity, milk flow, blood in milk, kick-offs, not milked quarters and incomplete milkings, new variables that combined quarter data were created. Past period records, i.e. lags, of up to seven days before the actual CMSCC sampling event were added in the dataset to investigate if they were of use in modeling the cell count. Univariable generalized additive models (GAM) were used to screen the data to select potential independent variables. Furthermore, several multivariable GAM were fitted in order to compare the importance of the potential independent variables and to explore how the model performance would be affected by using data from various number of days before the CMSCC sampling event. The result of the model selection showed that the best explanation of CMSCC was provided by the model incorporating all significant variables from the variable screening for the seven preceding days, including the day of the CMSCC sampling event. However, using data from only three days before the CMSCC sampling event is suggested to be sufficient to model CMSCC. Variables combining conductivity quarter data, together with quarter conductivity, are suggested to be important in describing CMSCC. We conclude that CMSCC can be modeled with a high degree of explanation using the information routinely recorded by the milking robot.

scholarly journals Sardine potential habitat and environmental forcing off western Portugal

2010 ◽  
Vol 67 (8) ◽  
pp. 1553-1564 ◽  
Author(s):  
Juan P. Zwolinski ◽  
Paulo B. Oliveira ◽  
Victor Quintino ◽  
Yorgos Stratoudakis
Keyword(s):  
Chlorophyll A ◽  
Seasonal Pattern ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Seasonal Effect ◽  
Oceanic Circulation ◽  
Environmental Forcing ◽  
Potential Habitat ◽  
The North ◽  
Spatio Temporal

Abstract Zwolinski, J. P., Oliveira, P. B., Quintino, V., and Stratoudakis, Y. 2010. Sardine potential habitat and environmental forcing off western Portugal. – ICES Journal of Marine Science, 67: 1553–1564. Relationships between sardine (Sardina pilchardus) distribution and the environment off western Portugal were explored using data from seven acoustic surveys (spring and autumn of 2000, 2001, 2005, and spring 2006). Four environmental variables (salinity, temperature, chlorophyll a, and acoustic epipelagic backscatter other than fish) were related to the acoustic presence and density of sardine. Univariate quotient analysis revealed sardine preferences for waters with high chlorophyll a content, low temperature and salinity, and low acoustic epipelagic backscatter. Generalized additive models depicted significant relationships between the environment and sardine presence but not with sardine density. Maps of sardine potential habitat (SPH) built upon the presence/absence models revealed a clear seasonal effect in the across-bathymetry and alongshelf extension of SPH off western Portugal. During autumn, SPH covered a large part of the northern Portuguese continental shelf but was almost absent from the southern region, whereas in spring SPH extended farther south but was reduced to a narrow band of shallow coastal waters in the north. This seasonal pattern agrees with the spatio-temporal variation of primary production and oceanic circulation described for the western Iberian shelf.

scholarly journals Factors associated with the spatial heterogeneity of COVID-19 in France: a nationwide ecological study

2020 ◽  
Author(s):  
Jean Gaudart ◽  
Jordi Landier ◽  
laetitia huiart ◽  
Eva Legendre ◽  
Laurent Lehot ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Ecological Study ◽  
Generalized Additive Models ◽  
Principal Component ◽  
Additive Models ◽  
Factors Associated ◽  
North East ◽  
The North ◽  
Incidence And Mortality ◽  
The Impact

Like in many countries and regions, spread of the COVID 19 pandemic has exhibited important spatial heterogeneity across France, one of the most affected countries so far. To better understand factors associated with incidence, mortality and lethality heterogeneity across the 96 administrative departments of metropolitan France, we thus conducted a geoepidemiological analysis based on publicly available data, using hierarchical ascendant classification (HAC) on principal component analysis (PCA) of multidimensional variables, and multivariate analyses with generalized additive models (GAM). Our results confirm a marked spatial heterogeneity of in-hospital COVID 19 incidence and mortality, following the North East / South West diffusion of the epidemic. The delay elapsed between the first COVID-19 associated death and the onset of the national lockdown on March 17th, 2020, appeared positively associated with in-hospital incidence, mortality and lethality. Mortality was also strongly associated with incidence. Mortality and lethality rates were significantly higher in departments with older population, but they were not significantly associated with the number of intensive-care beds available in 2018. We did not find any significant association between incidence, mortality or lethality rates and incidence of new chloroquine and hydroxychloroquine dispensations in pharmacies either, nor between COVID 19 incidence and climate, nor between economic indicators and in-hospital COVID 19 incidence or mortality. This ecological study highlights the impact of population age structure, epidemic spread and transmission mitigation policies in COVID-19 morbidity or mortality heterogeneity.

scholarly journals Trends in the distribution and abundance of cetaceans from aerial surveys in Icelandic coastal waters, 1986-2001

2009 ◽  
Vol 7 ◽  
pp. 117 ◽  
Author(s):  
Daniel G Pike ◽  
Charles GM Paxton ◽  
Thorvaldur Gunnlaugsson ◽  
Gísli A Víkingsson
Keyword(s):  
Relative Abundance ◽  
Minke Whale ◽  
Humpback Whales ◽  
Line Transect ◽  
Survey Area ◽  
Balaenoptera Acutorostrata ◽  
The North ◽  
Aerial Surveys ◽  
Minke Whales ◽  
Abundance Estimates

Aerial surveys were carried out in coastal Icelandic waters 4 times between 1986 and 2001 as part of the North Atlantic Sightings Surveys. The surveys had nearly identical designs in 3 of the 4 years. The target species was the minke whale (Balaenoptera acutorostrata) but all species encountered were recorded. Sighting rate and density from line transect analysis were used as indices of relative abundance to monitor trends over the period, and abundance estimates corrected for perception biases were calculated for some species from the 2001 survey. More than 11 species were sighted, of which the most common were the minke whale, humpback whale (Megaptera novaeangliae), dolphins of genus Lagenorhychus, and the harbour porpoise (Phocoena phocoena). Minke whales anddolphins showed little change in distribution or abundance over the period. There were an estimated 31,653 (cv 0.30) dolphins in the survey area in 2001. Humpback whales increased rapidly at a rate of about 12%, with much of the increase occurring off eastern and northeastern Iceland. In 2001 there were an estimated 4,928 (cv 0.463) humpback whales in the survey area. The relative abundance of harbour porpoises decreased over the period, but estimates for this species were compromised by uncorrected perception biases and poor coverage. The ecological and historical significance of these findings with respect to previous whaling activities and present-day fisheries is discussed.

scholarly journals Density surface fitting to estimate the abundance of humpback whales based on the NASS-95 and NASS- 2001 aerial and shipboard surveys

2009 ◽  
Vol 7 ◽  
pp. 143 ◽  
Author(s):  
Charles GM Paxton ◽  
M Louise Burt ◽  
Sharon L Hedley ◽  
Gísli A Víkingsson ◽  
Thorvaldur Gunnlaugsson ◽  
...  
Keyword(s):  
Confidence Intervals ◽  
Generalized Additive Models ◽  
Model Fitting ◽  
Humpback Whale ◽  
Additive Models ◽  
Humpback Whales ◽  
Bootstrap Sampling ◽  
Distance Analysis ◽  
The North ◽  
Abundance Estimates

Generalized additive models (GAMs) with spatially referenced covariates were fitted to data collected during the 1995 and 2001 Icelandic (shipboard and aerial) and Faroese (shipboard only) components of the North Atlantic Sightings Surveys (NASS-95 and NASS-2001). The shipboard surveys extended from the east coast of Greenland, around Iceland, down to an area along the west coast ofIreland (in 1995) and to the north of the United Kingdom (in 2001). In contrast, the aerial surveys were limited to Icelandic coastal waters only. The aim of the analysis was to predict density, and hence abundance, of humpback whales throughout the survey regions and also to establish if there was any evidence that humpback whale density was related to sea surface temperature or depth.Fitting GAMs to the 1995 data proved problematic and so various subsets of the data were used in an attempt to improve the model fitting. Such difficulties did not occur with the 2001 data. Confidence intervals (CIs) for the abundance estimates were estimated using bootstrap sampling methods.The estimated humpback whale abundance for the region covered by the aerial and shipboard surveys in 1995 was 10,521 (95% CI: 3,716–24,636) using all available data and 7,625 (3,641–22,424) if survey blocks with 0 sightings around the Faroes and south of 60˚ N where no humpback whales were detected were excluded from the analysis. The estimate for the total survey region in 2001 was 14,662 (9,441–29,879). The high upper bounds of the confidence intervals were thought to be caused by a paucity of effort over wide areas of the survey leading to interpolation. Overall, the uncertainty associated with these abundance estimates was approximately equal to, or greater than, that associated with a stratified distance analysis. Given these wide CIs the evidence for a substantial difference in abundance between years was equivocal. However there was evidence to suggest that humpback whales congregated in shallower waters between 6–8˚C.

Structure in a sea of sand: fish abundance in relation to man-made structures in the North Sea

2018 ◽  
Vol 77 (3) ◽  
pp. 1206-1218 ◽  
Author(s):  
Serena R Wright ◽  
Christopher P Lynam ◽  
David A Righton ◽  
Julian Metcalfe ◽  
Ewan Hunter ◽  
...  
Keyword(s):  
North Sea ◽  
Gadus Morhua ◽  
Oil And Gas ◽  
Generalized Additive Models ◽  
Strong Association ◽  
Additive Models ◽  
Artificial Structures ◽  
Habitat Alterations ◽  
The North ◽  
The North Sea

Abstract Artificial structures in the marine environment may have direct and/or indirect impact on the behaviour and space use of mobile foragers. This study explores whether environmental and physical features in the North Sea—including artificial structures (wrecks, wind turbines, cables, and oil and gas structures) were associated with local abundance of three fish species: cod (Gadus morhua), plaice (Pleuronectes platessa), and thornback ray (Raja clavata). Generalized additive models (GAMs) were used to compare distributions between data collected by fisheries surveys and electronic tags. Distributions of cod, plaice, and ray were correlated with environmental variables including temperature, depth, and substrate, matching findings from previous studies. All species showed seasonal increases in their abundance in areas with high densities of artificial structures, including oil and gas platforms and wrecks. Independent of whether fish purposefully associate with these features or whether structures happen to coincide with locations frequented by these populations, the strong association suggests that greater consideration needs to be given to regulation of habitat alterations, including decommissioning.

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 Comparative analysis of statistical tools to identify recruitment–environment relationships and forecast recruitment strength

2005 ◽  
Vol 62 (7) ◽  
pp. 1256-1269 ◽  
Author(s):  
Bernard A. Megrey ◽  
Yong-Woo Lee ◽  
S. Allen Macklin
Keyword(s):  
Linear Regression ◽  
Generalized Additive Models ◽  
Simulated Data ◽  
Additive Models ◽  
Clupea Harengus ◽  
Influential Factor ◽  
Data Simulation ◽  
Sea Temperature ◽  
The North ◽  
The North Atlantic Oscillation

Abstract Many of the factors affecting recruitment in marine populations are still poorly understood, complicating the prediction of strong year classes. Despite numerous attempts, the complexity of the problem often seems beyond the capabilities of traditional statistical analysis paradigms. This study examines the utility of four statistical procedures to identify relationships between recruitment and the environment. Because we can never really know the parameters or underlying relationships of actual data, we chose to use simulated data with known properties and different levels of measurement error to test and compare the methods, especially their ability to forecast future recruitment states. Methods examined include traditional linear regression, non-linear regression, Generalized Additive Models (GAM), and Artificial Neural Networks (ANN). Each is compared according to its ability to recover known patterns and parameters from simulated data, as well as to accurately forecast future recruitment states. We also apply the methods to published Norwegian spring-spawning herring (Clupea harengus L.) spawner–recruit–environment data. Results were not consistently conclusive, but in general, flexible non-parametric methods such as GAMs and ANNs performed better than parametric approaches in both parameter estimation and forecasting. Even under controlled data simulation procedures, we saw evidence of spurious correlations. Models fit to the Norwegian spring-spawning herring data show the importance of sea temperature and spawning biomass. The North Atlantic Oscillation (NAO) did not appear to be an influential factor affecting herring recruitment.

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