scholarly journals Evaluating acoustic-trawl survey strategies using an end-to-end ecosystem model

2020 ◽  
Author(s):  
Arne Johannes Holmin ◽  
Erik A Mousing ◽  
Solfrid S Hjøllo ◽  
Morten D Skogen ◽  
Geir Huse ◽  
...  
Keyword(s):  
Simulated Data ◽  
Ecosystem Model ◽  
Trawl Survey ◽  
Sampling Variance ◽  
Simulation Framework ◽  
Norwegian Sea ◽  
Atlantic Mackerel ◽  
Fish Migrations ◽  
Survey Estimates ◽  
Trawl Surveys

Abstract Fisheries independent surveys support science and fisheries assessments but are costly. Evaluating the efficacy of a survey before initiating it could save costs. We used the NORWECOM.E2E model to simulate Northeast Atlantic mackerel and Norwegian spring spawning herring distributions in the Norwegian Sea, and we ran vessel transects in silico to simulate acoustic-trawl surveys. The simulated data were processed using standard survey estimation software and compared to the stock abundances in the ecosystem model. Three existing real surveys were manipulated to demonstrate how the simulation framework can be used to investigate effects of changes in survey timing, direction, and coverage on survey estimates. The method picked up general sources of biases and variance, i.e. that surveys conducted during fish migrations are more vulnerable in terms of bias to timing and changes in survey direction than during more stationary situations and that increased effort reduced the sampling variance.

Bootstrap confidence limits for groundfish trawl survey estimates of mean abundance

1997 ◽  
Vol 54 (3) ◽  
pp. 616-630 ◽  
Author(s):  
S J Smith
Keyword(s):  
Confidence Intervals ◽  
Probability Model ◽  
Small Sample ◽  
Trawl Survey ◽  
Confidence Limits ◽  
Complex Sampling ◽  
Survey Estimates ◽  
Small Sample Sizes ◽  
Complex Sampling Designs ◽  
Trawl Surveys

Trawl surveys using stratified random designs are widely used on the east coast of North America to monitor groundfish populations. Statistical quantities estimated from these surveys are derived via a randomization basis and do not require that a probability model be postulated for the data. However, the large sample properties of these estimates may not be appropriate for the small sample sizes and skewed data characteristic of bottom trawl surveys. In this paper, three bootstrap resampling strategies that incorporate complex sampling designs are used to explore the properties of estimates for small sample situations. A new form for the bias-corrected and accelerated confidence intervals is introduced for stratified random surveys. Simulation results indicate that the bias-corrected and accelerated confidence limits may overcorrect for the trawl survey data and that percentile limits were closer to the expected values. Nonparametric density estimates were used to investigate the effects of unusually large catches of fish on the bootstrap estimates and confidence intervals. Bootstrap variance estimates decreased as increasingly smoother distributions were assumed for the observations in the stratum with the large catch. Lower confidence limits generally increased with increasing smoothness but the upper bound depended upon assumptions about the shape of the distribution.

scholarly journals Feeding strategy of mackerel in the Norwegian Sea relative to currents, temperature, and prey

2015 ◽  
Vol 73 (4) ◽  
pp. 1127-1137 ◽  
Author(s):  
Leif Nøttestad ◽  
Justine Diaz ◽  
Hector Penã ◽  
Henrik Søiland ◽  
Geir Huse ◽  
...  
Keyword(s):  
Swimming Speed ◽  
Swimming Performance ◽  
Feeding Strategy ◽  
Near Field ◽  
Norwegian Sea ◽  
Swimming Direction ◽  
Atlantic Mackerel ◽  
The North ◽  
Foraging Rate ◽  
Feeding Resources

Abstract High abundance of Northeast Atlantic mackerel (Scomber scombrus L.), combined with limited food resources, may now force mackerel to enter new and productive regions in the northern Norwegian Sea. However, it is not known how mackerel exploit the spatially varying feeding resources, and their vertical distribution and swimming behaviour are also largely unknown. During an ecosystem survey in the Norwegian Sea during the summer feeding season, swimming direction, and speed of mackerel schools were recorded with high-frequency omnidirectional sonar in four different regions relative to currents, ambient temperature, and zooplankton. A total of 251 schools were tracked, and fish and zooplankton were sampled with pelagic trawl and WP-2 plankton net. Except for the southwest region, swimming direction of the tracked schools coincided with the prevailing northerly Atlantic current direction in the Norwegian Sea. Swimming with the current saves energy, and the current also provides a directional cue towards the most productive areas in the northern Norwegian Sea. Average mean swimming speed in all regions combined was ∼3.8 body lengths s−1. However, fish did not swim in a straight course, but often changed direction, suggesting active feeding in the near field. Fish were largest and swimming speed lowest in the northwest region which had the highest plankton concentrations and lowest temperature. Mackerel swam close to the surface at a depth of 8–39 m, with all schools staying above the thermocline in waters of at least 6°C. In surface waters, mackerel encounter improved foraging rate and swimming performance. Going with the flow until temperature is too low, based on an expectation of increasing foraging rate towards the north while utilizing available prey under way, could be a simple and robust feeding strategy for mackerel in the Norwegian Sea.

scholarly journals Evaluating total uncertainty for biomass- and abundance-at-age estimates from eastern Bering Sea walleye pollock acoustic-trawl surveys

2016 ◽  
Vol 73 (9) ◽  
pp. 2208-2226 ◽  
Author(s):  
Mathieu Woillez ◽  
Paul D. Walline ◽  
James N. Ianelli ◽  
Martin W. Dorn ◽  
Christopher D. Wilson ◽  
...  
Keyword(s):  
Bering Sea ◽  
Walleye Pollock ◽  
Target Strength ◽  
Acoustic Backscatter ◽  
Trawl Survey ◽  
Data Types ◽  
Total Uncertainty ◽  
Functional Relationships ◽  
Eastern Bering Sea ◽  
Trawl Surveys

Abstract A comprehensive evaluation of the uncertainty of acoustic-trawl survey estimates is needed to appropriately include them in stock assessments. However, this evaluation is not straightforward because various data types (acoustic backscatter, length, weight, and age composition) are combined to produce estimates of abundance- and biomass-at-age. Uncertainties associated with each data type and those from functional relationships among variables need to be evaluated and combined. Uncertainty due to spatial sampling is evaluated using geostatistical conditional (co-) simulations. Multiple realizations of acoustic backscatter were produced using transformed Gaussian simulations with a Gibbs sampler to handle zeros. Multiple realizations of length frequency distributions were produced using transformed multivariate Gaussian co-simulations derived from quantiles of the empirical length distributions. Uncertainty due to errors in functional relationships was evaluated using bootstrap for the target strength-at-length and the weight-at-length relationships and for age–length keys. The contribution of each of these major sources of uncertainty was assessed for acoustic-trawl surveys of walleye pollock in the eastern Bering Sea in 2006–2010. This simulation framework allows a general computation for estimating abundance- and biomass-at-age variance–covariance matrices. Such estimates suggest that the covariance structure assumed in fitting stock assessment models differs substantially from what careful analysis of survey data actually indicate.

Ecological effects of trawling fisheries on the eastern Australian continental shelf: a modelling study

2013 ◽  
Vol 64 (11) ◽  
pp. 1068 ◽  
Author(s):  
Marie Savina ◽  
Robyn E Forrest ◽  
Elizabeth A Fulton ◽  
Scott A Condie
Keyword(s):  
Continental Shelf ◽  
New South ◽  
Ecosystem Model ◽  
Fish Biomass ◽  
Trawl Survey ◽  
Fishing Pressure ◽  
Survey Area ◽  
Trawl Fishery ◽  
South Wales ◽  
Survey Results

The New South Wales Offshore Trawl Fishery began to expand in 1976, following a large exploratory trawl survey carried out on the fishing grounds of the upper continental slope. This survey was repeated 20 years later with the same vessel and using similar protocols. Comparison of the survey results suggested that the overall fish biomass in the survey area had substantially decreased after 20 years. We have implemented an ecosystem model using the Atlantis framework to (1) emulate the evolution of the shelf ecosystems from 1976 to 1996 and (2) explore the effects of alternative fishing pressures on those ecosystems. We have been able to emulate the observed decline of most of the commercial groups of fish species in the Offshore Trawl Fishery, including sharks, and our results confirmed that fishing pressure was the most important cause of these observed changes. Fourteen fishing scenarios highlight the competing nature of some of the ecosystem-based sustainable fishing objectives.

Calculation of untrawlable areas within the boundaries of a bottom trawl survey

2003 ◽  
Vol 60 (6) ◽  
pp. 657-669 ◽  
Author(s):  
Mark Zimmermann
Keyword(s):  
Relative Abundance ◽  
Species Group ◽  
Bottom Trawl ◽  
Trawl Survey ◽  
Gis Analysis ◽  
Target Species ◽  
Abundance Estimates ◽  
Original Target ◽  
Catch Rates ◽  
Trawl Surveys

A geographic information system (GIS) analysis of 5039 bottom trawl events from U.S. west coast bottom trawl surveys (1977–1998) estimated that the survey area was about 77% trawlable but five of the 30 strata were less than 50% trawlable. Untrawlable areas, by definition, cannot be surveyed with the bottom trawl; however, there has never been a means of identifying and excluding these areas from relative abundance estimates, which are calculated only from hauls completed in the trawlable portions of each stratum. Unknown amounts of untrawlable habitat are a problem for relative abundance estimation in many bottom trawl surveys. This manuscript describes one method of using the bottom trawling events of a survey, such as ripped-up hauls and abandoned stations, to calculate the amount of area that is untrawlable. A comparison of catch rates between undamaged tows and a limited number of damaged tows, which are normally discarded as faulty samples, showed that Sebastes catch rates were generally higher in damaged tows. Thus untrawlable areas may have substantial importance on relative abundance estimates of Sebastes, the original target species group for this survey.

scholarly journals Carbon and nutrient mixed layer dynamics in the Norwegian Sea

2007 ◽  
Vol 4 (5) ◽  
pp. 3229-3265 ◽  
Author(s):  
H. S. Findlay ◽  
T. Tyrrell ◽  
R. G. J. Bellerby ◽  
A. Merico ◽  
I. Skjelvan
Keyword(s):  
Model Prediction ◽  
Co2 Flux ◽  
Detailed Comparison ◽  
Ecosystem Model ◽  
Seasonal Cycles ◽  
Surface Layers ◽  
Carbonate System ◽  
Saturation State ◽  
Norwegian Sea ◽  
Calcite Saturation

Abstract. A coupled carbon-ecosystem model is compared to recent data from Ocean Weather Ship M (66° N, 02° E) and used to investigate nutrient and carbon processes within the Norwegian Sea. Nitrate is consumed by phytoplankton in the surface layers over the summer; however the data show that silicate does not become rapidly limiting for diatoms, in contrast to the model prediction and in contrast to data from other temperate locations. The model estimates atmosphere-ocean CO2 flux to be 37 g C m−2 yr−1. A detailed comparison of the carbonate system at other ocean locations reveals that although coccolithophore blooms occur at OWS M, they are not as prevalent here as other areas. The seasonal cycles of calcite saturation state and [CO32−] are similar in the model and in data: values range from ~3 and ~120 μmol kg−1 respectively in winter, to ~4 and ~170 μmol kg−1 respectively in summer. The timing of coccolithophore blooms within the year therefore coincides with a time of high calcite saturation state, as predicted by previous modelling work.

scholarly journals AdmixSim: A Forward-Time Simulator for Various and Complex Scenarios of Population Admixture

2016 ◽  
Author(s):  
Xiong Yang ◽  
Xumin Ni ◽  
Ying Zhou ◽  
Wei Guo ◽  
Kai Yuan ◽  
...  
Keyword(s):  
Population Genetic ◽  
Genetic Architecture ◽  
Simulated Data ◽  
Population Admixture ◽  
Simulation Framework ◽  
Computer Tool ◽  
Background Population ◽  
Fisher Model ◽  
In Silico Simulation ◽  
Break Points

Background: Population admixture has been a common phenomenon in human, animals and plants, and plays a very important role in shaping individual genetic architecture and population genetic diversity. Inference of population admixture, however, is challenging and typically relies on in silico simulation. We are aware of the lack of a computer tool for such a purpose, especially a simulator is not available for generating data under various and complex admixture scenarios. Results: Here we developed a forward-time simulator (AdmixSim) under standard Wright Fisher model, which can simulate admixed populations with: 1) multiple ancestral populations; 2) multiple waves of admixture events; 3) fluctuating population size; and 4) fluctuating admixture proportions. Results of analysis of the simulated data by AdmixSim show that our simulator can fast and accurately generate data resemble real one. We included in AdmixSim all possible parameters that allow users to modify and simulate any kinds of admixture scenarios easily so that it is very flexible. AdmixSim records recombination break points and trace of each chromosomal segment from different ancestral populations, with which users can easily do further analysis and comparative studies with empirical data. Conclusions: AdmixSim is expected to facilitate the study of population admixture by providing a simulation framework with flexible implementation of various admixture models and parameters.

scholarly journals Sampling variance of species identification in fisheries acoustic surveys based on automated procedures associating acoustic images and trawl hauls

2003 ◽  
Vol 60 (3) ◽  
pp. 437-445 ◽  
Author(s):  
Pierre Petitgas ◽  
Jacques Massé ◽  
Pierre Beillois ◽  
Emilie Lebarbier ◽  
Arnaud Le Cann
Keyword(s):  
Species Identification ◽  
Energy Allocation ◽  
Sampling Variance ◽  
Acoustic Image ◽  
Spatial Continuity ◽  
Acoustic Images ◽  
Acoustic Surveys ◽  
Survey Estimates ◽  
Aggregation Step ◽  
Automated Procedures

Abstract During the acoustic surveys of fish stocks, a small number of echo traces are identified to species by fishing. During data analysis, the process of echogram scrutiny leads to allocating echo-trace backscattered energies to species. While the precision of survey estimates is generally based on the spatial variation in the energy, no variance term accounts for species identification and energy allocation. In this paper, the sampling variance of species identification is developed and automated procedures are used allowing energy allocation to be carried out by a non-expert. The procedures are based on the fact that at the sampling stage trawl hauls are linked with particular acoustic images. The procedures have two steps: the classification step corresponds to species identification and the aggregation step to energy allocation. Classification is performed on the identified images and results in defining groups of images and estimating in each the sampling variability of the species identification. Aggregation is performed on non-identified images and results in post-stratifying the data. The estimation (map, abundance and variance per species) is then derived automatically and is conditioned by the post-stratification. Two approaches are followed, one based on the echo-trace characteristics making full use of the echogram (acoustic-image classification) and the other on the spatial continuity of the species composition between trawl hauls (trawl-haul classification). These methods are described and compared. The species-identification variance term is also compared to the spatial variance.

Use of Statistical Models for the Estimation of Abundance from Groundfish Trawl Survey Data

1990 ◽  
Vol 47 (5) ◽  
pp. 894-903 ◽  
Author(s):  
Stephen J. Smith
Keyword(s):  
Statistical Models ◽  
Gadus Morhua ◽  
Finite Population ◽  
Trawl Survey ◽  
Survey Area ◽  
Sample Mean ◽  
Population Mean ◽  
Model Based ◽  
Design Consistency ◽  
Trawl Surveys

Estimates of fish abundance from stratified random trawl surveys are highly variable and a number of estimators from various statistical models have been suggested to provide more precise estimates. However, model-based estimates of the survey finite population mean which are not based on the sample mean, can be biased and nonrobust to deviations from the model. This is demonstrated in particular for estimates based on the Δ-distribution. A criterion known as asymptotic design consistency (ADC) is presented for selecting those models that can provide estimates of the finite population mean which are asymptotically robust to deviations from the model. The concept of a predictive estimate is presented as a means of incorporating models into an estimate of the finite population mean which can provide more information than the sample mean. Predictive estimates use statistical models to relate the abundance measured in the sample to covariates measured over the whole survey area. This paper demonstrates that consistent relationships exist between the catch of age 4 cod (Gadus morhua) in the survey trawl and concurrently measured hydrographic covariates which can be used to construct model-based ADC predictive estimates of the finite population mean.

scholarly journals Accounting for the bin structure of data removes bias when fitting size spectra

2020 ◽  
Vol 636 ◽  
pp. 19-33 ◽  
Author(s):  
AM Edwards ◽  
JPW Robinson ◽  
JL Blanchard ◽  
JK Baum ◽  
MJ Plank
Keyword(s):  
Simulated Data ◽  
Likelihood Method ◽  
Size Spectrum ◽  
Trawl Survey ◽  
Power Law Distribution ◽  
Data Types ◽  
Data Set ◽  
Size Spectra ◽  
High Resolution Data ◽  
Biased Estimates

Size spectra are recommended tools for detecting the response of marine communities to fishing or to management measures. A size spectrum succinctly describes how a property, such as abundance or biomass, varies with body size in a community. Required data are often collected in binned form, such as numbers of individuals in 1 cm length bins. Numerous methods have been employed to fit size spectra, but most give biased estimates when tested on simulated data, and none account for the data’s bin structure (breakpoints of bins). Here, we used 8 methods to fit an annual size-spectrum exponent, b, to an example data set (30 yr of the North Sea International Bottom Trawl Survey). The methods gave conflicting conclusions regarding b declining (the size spectrum steepening) through time, and so any resulting advice to ecosystem managers will be highly dependent upon the method used. Using simulated data, we showed that ignoring the bin structure gives biased estimates of b, even for high-resolution data. However, our extended likelihood method, which explicitly accounts for the bin structure, accurately estimated b and its confidence intervals, even for coarsely collected data. We developed a novel visualisation method that accounts for the bin structure and associated uncertainty, provide recommendations concerning different data types and have created an R package (sizeSpectra) to reproduce all results and encourage use of our methods. This work is also relevant to wider applications where a power-law distribution (the underlying distribution for a size spectrum) is fitted to binned data.

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