scholarly journals Statistical relationships between the distributions of groundfish and crabs in the eastern Bering Sea and processed returns from a single-beam echosounder

2009 ◽  
Vol 66 (6) ◽  
pp. 1425-1432 ◽  
Author(s):  
Robert A. McConnaughey ◽  
Stephen E. Syrjala
Keyword(s):  
Bering Sea ◽  
Environmental Control ◽  
Generalized Additive Models ◽  
Sampling Strategy ◽  
Additive Models ◽  
Surficial Sediments ◽  
Single Beam ◽  
Eastern Bering Sea ◽  
Efficient Sampling ◽  
Statistical Relationships

Abstract McConnaughey, R. A., and Syrjala, S. E. 2009. Statistical relationships between the distributions of groundfish and crabs in the eastern Bering Sea and processed returns from a single-beam echosounder. – ICES Journal of Marine Science, 66: 1425–1432. Groundfish and benthic invertebrates are not randomly distributed over the continental shelf of the eastern Bering Sea (EBS). Annual trawl surveys reveal distributional patterns that vary according to species, and substantial interannual variation in these patterns suggests some degree of environmental control. Quantitative habitat models are developed to explain the distribution and abundance of species in the EBS. Simple models based on readily available data (temperature and depth) are somewhat informative, but offer limited practical value. Earlier research in the EBS indicated that surficial sediments affect the distribution and abundance of groundfish. However, traditional sampling with grabs and cores is impractical over large areas, and an efficient sampling strategy is needed. Echosounders allow surveys of large areas, but it is unknown if they measure the relevant properties of sediments. Seabed echoes from a calibrated, single-beam echosounder were recorded over 17 000 km of trackline covering the EBS shelf. Generalized additive models were used to fit acoustic and other variables to abundance data for ten species. The final models explained 28–77% of the variability in abundances, including a marginal contribution of 2–13% by the acoustic predictors.

Spatial Analysis of Bering Sea Groundfish Survey Data Using Generalized Additive Models

1992 ◽  
Vol 49 (7) ◽  
pp. 1366-1378 ◽  
Author(s):  
Gordon Swartzman ◽  
Chisheng Huang ◽  
Stephen Kaluzny
Keyword(s):  
Survey Data ◽  
Bering Sea ◽  
Generalized Additive Models ◽  
Sampling Procedure ◽  
Additive Models ◽  
Trawl Survey ◽  
Flatfish Species ◽  
Eastern Bering Sea ◽  
Abundance Estimates ◽  
Average Abundance

Generalized additive models (GAM) are herein applied to trawl survey data in the eastern Bering Sea with an eye to (1) detecting trends in groundfish distributions and (2) improving abundance estimates by including the trend. GAM is a statistical method, analogous to regression, but without the assumptions of normality or linearity that relate a response variable (in this case, fish abundance) to location (latitude and longitude) and associated environmental variables (e.g. depth and bottom temperature). GAM provided reasonable (i.e. high r2) fits to the spatial distribution of five flatfish species and was able to define a spatial "signature" for each species, namely their preferred depth and temperature range. GAM also gave lower average abundance and abundance variability estimates for these five flatfish species than the stratified sampling procedure previously employed.

Relating spatial distributions of acoustically determined patches of fish and plankton: data viewing, image analysis, and spatial proximity

1999 ◽  
Vol 56 (S1) ◽  
pp. 188-198 ◽  
Author(s):  
Gordon Swartzman ◽  
Richard Brodeur ◽  
Jeffrey Napp ◽  
Danny Walsh ◽  
Roger Hewitt ◽  
...  
Keyword(s):  
Bering Sea ◽  
Generalized Additive Models ◽  
Biological Data ◽  
Additive Models ◽  
Spatial Proximity ◽  
Connected Component ◽  
Proximity Measure ◽  
Nonparametric Regression Model ◽  
Acoustic Data ◽  
Acoustic Images

We developed a point-and-click acoustic data viewer (FishViewer) for exploratory comparison of up to three acoustic survey transects (or three frequencies) at a time and other environmental and biological data (e.g., surface temperature and seabird abundance). FishViewer also contains image-processing tools (e.g., morphological and threshold filters) for distinguishing between fish shoals and plankton patches and for patch identification. These tools and methods are illustrated using survey data collected at three frequencies (38, 120, and 200 kHz) near the Pribilof Islands, Bering Sea, during September 1995. Data were also visualized by converting the patches identified in the acoustic images to polygons, showing the boundaries of each patch using a connected component algorithm. Proximity between these fish shoal and plankton patch polygons was examined statistically using an interval-based nonparametric regression model (generalized additive models) and a distance-based proximity measure. The methods presented for data refinement, visualization, and the establishment of fish-plankton patch proximity serve as a paradigm for scale-robust hypothesis formulation and testing of spatial patterns of fish and plankton.

scholarly journals Spatio-temporal distribution of euphausiids: an important component to understanding ecosystem processes in the Gulf of Alaska and eastern Bering Sea

2016 ◽  
Vol 73 (8) ◽  
pp. 2020-2036 ◽  
Author(s):  
Kirsten A. Simonsen ◽  
Patrick H. Ressler ◽  
Christopher N. Rooper ◽  
Stephani G. Zador
Keyword(s):  
Primary Production ◽  
Bering Sea ◽  
Gulf Of Alaska ◽  
Additive Models ◽  
Trophic Levels ◽  
Production Model ◽  
Trawl Survey ◽  
Large Spatial Scale ◽  
Eastern Bering Sea ◽  
Abundance And Distribution

Abstract Euphausiids (principally Thysanoessa spp.) are found in high abundance in both the eastern Bering Sea (EBS) and the Gulf of Alaska (GOA). They are an important part of these cold-water coastal and pelagic ecosystems as a key prey item for many species, including marine mammals, seabirds, and fish, forming an ecological link between primary production and higher trophic levels. Acoustic-trawl (AT) survey methods provide a means of monitoring euphausiid abundance and distribution over a large spatial scale. Four years of AT and bottom-trawl survey data (2003, 2005, 2011, and 2013) were available from consistently sampled areas around Kodiak Island, including Shelikof Strait, Barnabas Trough, and Chiniak Trough. We identified euphausiid backscatter using relative frequency response and targeted trawling, and created an annual index of abundance for euphausiids. This index has broad application, including use in the stock assessments for GOA walleye pollock (Gadus chalcogrammus) and other species, as an ecosystem indicator, and to inform ecological research. We then used generalized additive models (GAMs) to examine the relationship between relative euphausiid abundance and potential predictors, including pollock abundance, temperature, bottom depth, and primary production. Model results were compared with an updated GAM of euphausiid abundance from the EBS to determine if the factors driving abundance and distribution were consistent between both systems. Temperature was not a strong predictor of euphausiid abundance in the GOA as in the EBS; warmer temperatures and lack of seasonal ice cover in the GOA may be a key difference between these ecosystems. Pollock abundance was significant in both the GOA and the EBS models, but was not a strongly negative predictor of euphausiid abundance in either system, a result not consistent with top-down control of euphausiid abundance.

scholarly journals Standardization of landing efficiency for opilio crab in the western Bering Sea by using of generalized additive models

2021 ◽  
Vol 201 (2) ◽  
pp. 359-370
Author(s):  
I. S. Chernienko
Keyword(s):  
Bering Sea ◽  
Space Form ◽  
Generalized Additive Models ◽  
Information Criterion ◽  
Additive Models ◽  
Significant Difference ◽  
Akaike Criterion ◽  
Explained Variance ◽  
Modal Values ◽  
Delay Difference

Generalized additive models are applied for standardization of daily landing per unit effort (LPUE) for opilio crab using the data of fishery statistics for the West Bering Sea fishery zone in 2003–2020. A set of 12 models with various combinations of predictors was examined and the best model with the smallest value of Akaike criterion was selected (information criterion Akaike 21743, explained variance 58.6 %). The selected model reflects the effect of depth, distance from the coast, daily effort and tensor product of geographic coordinates and day of the year. LPUE was standardized using the selected model by substituting median values of nominal predictors and modal values of categorical predictors. Then the crab stock was estimated using the state-space form of Deriso-Schnute delay-difference model. The estimates based on both standardized and nominal indices are compared and a significant difference between them is found: the stock is assessed as 23,040 t with nominal indices but as 17,070 t using the standardized indices.

Associations between flatfish abundance and surficial sediments in the eastern Bering Sea

2000 ◽  
Vol 57 (12) ◽  
pp. 2410-2419 ◽  
Author(s):  
Robert A McConnaughey ◽  
Keith R Smith
Keyword(s):  
Bering Sea ◽  
Food Habits ◽  
Prey Availability ◽  
Sediment Type ◽  
Trawl Survey ◽  
Surficial Sediments ◽  
Sediment Properties ◽  
Eastern Bering Sea ◽  
Yellowfin Sole ◽  
Hippoglossoides Elassodon

Spatially explicit relationships between pleuronectid flatfish abundance and surficial sediments in the eastern Bering Sea were investigated using published sediment descriptions and trawl survey data (1982-1994). Flatfish food habits were also examined because sediment properties are known to affect the distribution and abundance of benthic prey. For six species, we compared sediment textures in areas of highest and lowest abundance (kilograms per hectare). Sand predominated in areas of high yellowfin sole (Pleuronectes asper) (YFS) (p << 0.001) and rock sole (Lepidopsetta spp.) (RS) (p << 0.001) abundance, while mixed sand and mud was most common in areas of lowest abundance. In contrast, mixed sand and mud predominated in areas preferred by flathead sole (Hippoglossoides elassodon) (FHS) (p << 0.001), Alaska plaice (Pleuronectes quadrituberculatus) (AP) (p = 0.002), and arrowtooth flounder (Atheresthes stomias) (ATF) (p = 0.004), with more diverse substrates in low-density areas. Areas of high and low Greenland turbot (Reinhardtius hippoglossoides) (GT) (p = 0.845) abundance had similar sediment textures (primarily mixed sand and mud). Species with highly restricted diets (AP) or piscivores with weak sediment associations (GT, ATF) had relatively inflexible food habits, whereas YFS, RS, and FHS food habits varied considerably with sediment type. Our findings suggest that benthic-feeding pleuronectids prefer certain sediment textures because of adaptive differences in prey availability.

scholarly journals Environmental drivers of plant assemblages: are there differences between palustrine and lacustrine wetlands? A case study from the northern Apennines (Italy)

2019 ◽  
pp. 34 ◽  
Author(s):  
Claudia Angiolini ◽  
Daniele Viciani ◽  
Gianmaria Bonari ◽  
Antonio Zoccola ◽  
Alessandro Bottacci ◽  
...  
Keyword(s):  
Plant Species ◽  
Environmental Control ◽  
Generalized Additive Models ◽  
Central Italy ◽  
Floristic Composition ◽  
Northern Apennines ◽  
Additive Models ◽  
Environmental Drivers ◽  
Species Assemblages ◽  
Indirect Ordination

Mountain wetlands are among the most vulnerable habitats in the Mediterranean basin. Their conservation requires knowledge of plant species assemblages and their environmental drivers. In this study, we investigated what the main environmental factors driving species composition in mountain wetlands are. Differences in environmental control and floristic composition between palustrine and lacustrine wetlands were explored. We used a dataset of 168 vegetation plots (relevés), sampled at 45 mountain wetlands in the northern Apennines (central Italy). Direct ordination showed that water depth, geology type and altitude were the main factors responsible for species distribution. The most important gradient was linked to soil moisture, with hygrophilous species increasing with moisture levels. Indicator Species Analysis underlined a clear distinction in the distribution of aquatic plants between wetland subsystems. Geology and rainfall affected species assemblages in lacustrine and palustrine subsystems. Indirect ordination and Generalized Additive Models revealed that plant species and their attributes significantly changed in the wetland subsystems with an increase in hydrophytes with increasing rainfall in palustrine wetlands and a decrease in thermophilous species along an altitudinal gradient in lacustrine wetlands. Management and conservation guidelines for northern Apennines wetlands are suggested.

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.

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