scholarly journals Standardizing catch rates: is logbook information by itself enough?

2008 ◽  
Vol 65 (2) ◽  
pp. 255-266 ◽  
Author(s):  
J. Bishop ◽  
W. N. Venables ◽  
C. M. Dichmont ◽  
D. J. Sterling
Keyword(s):  
Relative Abundance ◽  
Prediction Models ◽  
Expert Knowledge ◽  
External Information ◽  
Linear Regression Models ◽  
Catch Per Unit Effort ◽  
Estimation Model ◽  
Catch Rates ◽  
Logbook Data ◽  
Estimation Models

Abstract Bishop, J., Venables, W. N., Dichmont, C. M., and Sterling, D. J. 2008. Standardizing catch rates: is logbook information by itself enough? – ICES Journal of Marine Science, 65: 255–266. The goal of the work was to maximize the accuracy of standardized catch per unit effort as an index of relative abundance. Linear regression models were fitted to daily logbook data from a multispecies penaeid trawl fishery in which within-vessel changes in efficiency are common. Two model-fitting strategies were compared. The predictive strategy focused on maximizing the explained variance, and the estimation strategy on finding realistic coefficients for important components of changing catchability. Realistic values could not always be obtained, because the regression factors were not orthogonal, and data on the presence of technology were sometimes unreliable or systematically incomplete. It was not possible to separate fishing power from abundance by analysing logbook data alone; it was necessary to incorporate external information within the standardization model. Therefore, the resultant estimation models incorporated external information and expert knowledge by offsets. There was no single best estimation model. Instead, a series of models provided an envelope of possible changes in relative fishing power and prawn abundance since 1970. Compared with the prediction models, the estimation models revealed different trends in relative fishing power and relative abundance.

Does habitat or depth influence catch rates of pelagic species?

2007 ◽  
Vol 64 (11) ◽  
pp. 1581-1594 ◽  
Author(s):  
Keith A Bigelow ◽  
Mark N Maunder
Keyword(s):  
Relative Abundance ◽  
Environmental Conditions ◽  
Environmental Data ◽  
Catch Per Unit Effort ◽  
Blue Shark ◽  
Species Vulnerability ◽  
Thunnus Obesus ◽  
Catch Rates ◽  
The Relationship ◽  
The Vertical Distribution

The efficiency of a pelagic longline fishing operation and the species composition of the resulting catch is influenced primarily by the relationship between the distribution of hooks and species vulnerability, with vulnerability described by either depth or some suite of environmental variables. We therefore fitted longline catch rate models to determine whether catch is estimated better by vertically distributing a species by depth or by environmental conditions (e.g., temperature, thermocline gradient, and oxygen concentration). Catch rates were estimated by two methods: (i) monitoring longlines where the vertical distribution of hooks and catch in relation to depth and environmental conditions is known, and (ii) applying a statistical habitat-based standardization (statHBS) model to fishery and environmental data to develop relative abundance indices for bigeye tuna (Thunnus obesus) and blue shark (Prionace glauca). Results indicated that an understanding of gear dynamics and environmental influences are important for analyzing catch-per-unit-effort (CPUE) data correctly. Analyses based on depth-specific catch rates can lead to serious misinterpretation of abundance trends, despite the use of sophisticated statistical techniques (e.g., generalized linear mixed models). This illustrates that inappropriate inclusion or exclusion of important covariates can bias estimates of relative abundance, which may be a common occurrence in CPUE analysis.

scholarly journals Interpreting catch per unit effort data to assess the status of individual stocks and communities

2006 ◽  
Vol 63 (8) ◽  
pp. 1373-1385 ◽  
Author(s):  
Mark N. Maunder ◽  
John R. Sibert ◽  
Alain Fonteneau ◽  
John Hampton ◽  
Pierre Kleiber ◽  
...  
Keyword(s):  
Relative Abundance ◽  
Stock Assessment ◽  
Limited Information ◽  
Catch Per Unit Effort ◽  
Fish Stocks ◽  
Unit Effort ◽  
Strategy Evaluation ◽  
The Status ◽  
Catch Rates ◽  
Management Advice

AbstractDespite being one of the most common pieces of information used in assessing the status of fish stocks, relative abundance indices based on catch per unit effort (cpue) data are notoriously problematic. Raw cpue is seldom proportional to abundance over a whole exploitation history and an entire geographic range, because numerous factors affect catch rates. One of the most commonly applied fisheries analyses is standardization of cpue data to remove the effect of factors that bias cpue as an index of abundance. Even if cpue is standardized appropriately, the resulting index of relative abundance, in isolation, provides limited information for management advice or about the effect of fishing. In addition, cpue data generally cannot provide information needed to assess and manage communities or ecosystems. We discuss some of the problems associated with the use of cpue data and some methods to assess and provide management advice about fish populations that can help overcome these problems, including integrated stock assessment models, management strategy evaluation, and adaptive management. We also discuss the inappropriateness of using cpue data to evaluate the status of communities. We use tuna stocks in the Pacific Ocean as examples.

scholarly journals Factors Influencing Creatine Kinase Response in Youth National Team Soccer Players

2021 ◽  
pp. 194173812199938
Author(s):  
Gabor Schuth ◽  
Gyorgy Szigeti ◽  
Gergely Dobreff ◽  
Peter Revisnyei ◽  
Alija Pasic ◽  
...  
Keyword(s):  
Creatine Kinase ◽  
Prediction Models ◽  
Soccer Players ◽  
Linear Regression Models ◽  
Level Of Evidence ◽  
Internal Load ◽  
Youth Soccer ◽  
National Team ◽  
Weekly Training ◽  
The Relationship

Background: Previous studies have examined the relationship between external training load and creatine kinase (CK) response after soccer matches in adults. This study aimed to build training- and match-specific CK prediction models for elite youth national team soccer players. Hypothesis: Training and match load will have different effects on the CK response of elite youth soccer players, and there will be position-specific differences in the most influential external and internal load parameters on the CK response. Study Design: Prospective cohort study. Level of Evidence: Level 4. Methods: Forty-one U16-U17 youth national team soccer players were measured over an 18-month period. Training and match load were monitored with global positioning system devices. Individual CK values were measured from whole blood every morning in training camps. The dataset consisted of 1563 data points. Clustered prediction models were used to examine the relationship between external/internal load and consecutive CK changes. Clusters were built based on the playing position and activity type. The performance of the linear regression models was described by the R2 and the root-mean-square error (RMSE, U/L for CK values). Results: The prediction models fitted similarly during games and training sessions ( R2 = 0.38-0.88 vs 0.6-0.77), but there were large differences based on playing positions. In contrast, the accuracy of the models was better during training sessions (RMSE = 81-135 vs 79-209 U/L). Position-specific differences were also found in the external and internal load parameters, which best explained the CK changes. Conclusion: The relationship between external/internal load parameters and CK changes are position specific and might depend on the type of session (training or match). Morning CK values also contributed to the next day’s CK values. Clinical Relevance: The relationship between position-specific external/internal load and CK changes can be used to individualize postmatch recovery strategies and weekly training periodization with a view to optimize match performance.

Ecological and environmental factors affecting the foraging activity of the White-bellied Heron Ardea insignis (Hume, 1878) in Bhutan

2021 ◽  
pp. 1-18
Author(s):  
PEMA KHANDU ◽  
GEORGE A. GALE ◽  
SARA BUMRUNGSRI
Keyword(s):  
Relative Abundance ◽  
Habitat Restoration ◽  
Prey Species ◽  
Catch Per Unit Effort ◽  
Factors Affecting ◽  
Prey Biomass ◽  
Gravel Mining ◽  
Unit Effort ◽  
Prey Preferences ◽  
The Government

Summary White-bellied Heron Ardea insignis (WBH) is critically endangered, but we lack data on many aspects of its basic ecology and threats to the species are not clearly understood. The goal of this study was to analyse WBH foraging microhabitat selection, foraging behaviour, and prey preferences in two river basins (Punatsangchhu and Mangdechhu) in Bhutan which are likely home to one of the largest remaining populations of WBH. We also explored the relationship between the relative abundance of the WBH and prey biomass catch per unit effort within four foraging river microhabitats (pool, pond, riffle and run). Prey species were sampled in 13 different 100-m thalweg lengths of the rivers using cast nets and electrofishing gear. Riffles and pools were the most commonly used microhabitats; relative abundance was the highest in riffles. The relative abundance of WBH and prey biomass catch per unit effort (CPUE) also showed a weak but significant positive correlation (rs = 0.22). The highest biomass CPUE was observed in riffles while the lowest was found in the ponds. From the 97 prey items caught by the WBH, 95% of the prey were fish. The WBH mainly exploited three genera of fish (Garra, Salmo, and Schizothorax) of which Schizothorax (64%) was the most frequently consumed. This study provides evidence in support of further protection of critical riverine habitat and fish resources for this heron. Regular monitoring of sand and gravel mining, curbing illegal fishing, habitat restoration/mitigation, and developing sustainable alternatives for local people should be urgently implemented by the government and other relevant agencies. Further study is also required for understanding the seasonal variation and abundance of its prey species in their prime habitats along the Punatsangchhu and Mangdechhu basins.

Fish and invertebrate by-catch in the crab pot fishery in the Isle of Man, Irish Sea

2017 ◽  
Vol 98 (8) ◽  
pp. 2099-2111
Author(s):  
Fikret Öndes ◽  
Michel J. Kaiser ◽  
Lee G. Murray
Keyword(s):  
Irish Sea ◽  
Target Species ◽  
Catch Per Unit Effort ◽  
Isle Of Man ◽  
Ecosystem Effects ◽  
By Catch ◽  
Catch Rates ◽  
Taxonomic Groups ◽  
Catch Composition ◽  
Autumn And Winter

Baited trap or pot fisheries are considered to have relatively few wider ecosystem effects on the marine environment, particularly when compared with towed mobile fishing gear. However, this assumption is rarely tested in the field. This study aimed to determine the composition of non-target species that occur in crustacean pots and to assess spatial and temporal differences in catches in the waters around the Isle of Man, Irish Sea. The data were collected using fishery independent surveys and a questionnaire study. Based on fishery independent surveys, a total of five taxonomic groups and 43 species occurred as by-catch. The dominant by-catch species was velvet crab Necora puber. The by-catch per unit effort (BPUE) for all of the non-target species was low particularly in comparison to towed bottom gear fisheries around the Isle of Man. BPUE of species composition varied considerably between different locations around the Isle of Man. The results of both the fishery independent and questionnaire data suggested that the by-catch rates varied with season with peak BPUE occurring in spring which then declined into autumn and winter. By-catch composition did not decrease significantly with an increasing target species catch. Overall, by-catch was low relative to target species catch which may be partially attributable to the use of escape panels in pot fisheries in the Isle of Man.

Aspects of the fishery, maturation and net selectivity of the wedge sole (Dicologoglossa cuneata) off south-western Iberia: implications for fishery management

2009 ◽  
Vol 90 (7) ◽  
pp. 1465-1474 ◽  
Author(s):  
Miguel Neves Santos ◽  
Pedro Gil Lino
Keyword(s):  
Fishery Management ◽  
River Mouth ◽  
Mesh Size ◽  
Scientific Basis ◽  
Catch Per Unit Effort ◽  
Important Species ◽  
Gill Net ◽  
Catch Rates ◽  
Log Normal ◽  
First Maturity

The wedge sole (Dicologoglossa cuneata, Moreau 1881) is a commercially important species for the artisanal fleet operating off the south-western Iberian Peninsula. During 2004 and 2005 a study was undertaken aiming to provide a scientific basis for management. Data collection included information on aspects of the fishery, spawning season, size at first maturity, tangle and gill-net selectivity. Seven nominal mesh sizes were used (40, 45 and 50 mm tangle nets and 40, 50, 60 and 70 mm gill-nets). Spawning lasts from December to June, with peaks in March and May. Length at first maturity for females was estimated at 18.5 cm. Catch rates decreased sharply with increasing mesh size, with tangle nets providing the highest yields. The log-normal selectivity model provided the best fit for specimens that were wedged. The higher catch-per-unit-effort of the smaller mesh sizes and the modal length of the fitted selectivity curve being below the size-at-maturity for wedge sole, suggests that the 50 mm nominal mesh size tangle net is the most appropriate for ensuring the fishery sustainability. Nevertheless, the minimum legal size should increase to at least 18 cm and a time–area closure should be implemented off the Guadiana River mouth.

scholarly journals Prediction Models for the Estimation of Soil Moisture Content

2011 ◽  
Author(s):  
Swathi Gorthi ◽  
Huifang Dou
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Prediction Models ◽  
Recursive Partitioning ◽  
Machine Learning Techniques ◽  
Linear Regression Models ◽  
Remotely Sensed Data ◽  
Modeling Tools ◽  
Wide Range

This paper provides a survey on different kinds of prediction models developed for the estimation of soil moisture content of an area, using empirical information including meteorological and remotely sensed data. The different models employed extend over a wide range of machine learning techniques starting from Basic Linear Regression models through models based on Bayesian framework, Decision tree learning and Recursive partitioning, to the modern non-linear statistical data modeling tools like Artificial Neural Networks. The fundamental mathematical backgrounds, pros and cons, prediction results and efficiencies of all the models are discussed.

scholarly journals Factors affecting relative abundance of low-mobility fishing resources: spiny lobster in the Galapagos Marine Reserve

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7278 ◽  
Author(s):  
Juan Carlos Murillo-Posada ◽  
Silvia Salas ◽  
Iván Velázquez-Abunader
Keyword(s):  
Monitoring System ◽  
Relative Abundance ◽  
Spatial Scales ◽  
Marine Reserve ◽  
Spiny Lobster ◽  
Fishing Effort ◽  
Additive Models ◽  
Catch Per Unit Effort ◽  
Monthly Basis ◽  
Galapagos Marine Reserve

Management of low-mobility or benthic fisheries is a difficult task because variation in the spatial distribution and population dynamics of the resources make the monitoring and assessment of these fisheries challenging. We assumed that environmental, spatial, and temporal factors can contribute to the variability of the relative abundance of such species; we used Generalized Additive Models for Location Scale and Shape (GAMLSS) to test this hypothesis using as a case study the lobster fishery (targeting two species) in the Galapagos Marine Reserve, Ecuador. We gathered data on each of the two species of lobster on a monthly basis over seven years, including: (a) onboard observers’ records of catch data, fishing effort, and ground location by trip, and (b) data from interviews undertaken with fishers at their arrival to port, recording the same type of information as obtained from onboard observers. We use this information to analyze the effect of the measured variables and to standardize the Catch per Unit Effort (CPUE) in each case, using the GAMLSS. For both species, the temperature, region, fishing schedule, month, distance, and the monitoring system were significant variables of the selected models associated with the variability of the catch rate. ForPanulirus penicillatus, CPUE was higher at night than during the day, and forPanulirus gracilisit was higher during the day. Increased temperature resulted in a decrease of CPUE values. It was evident that temporal, spatial scales and monitoring system can influence the variability of this indicator. We contend that the identification of drivers of change of relative abundance in low-mobility species can help to support the development of monitoring and assessment programs for this type of fisheries.

scholarly journals Mexican Stock Exchange Performance after the Crisis of 2008: Application of Data Mining

2020 ◽  
Vol 18 ((1)) ◽  
Author(s):  
Eliseo Ramírez Reyes ◽  
Arturo Morales Castro ◽  
Néstor Juan Sanabria Landazábal
Keyword(s):  
Neural Networks ◽  
Default Risk ◽  
Regression Models ◽  
Prediction Models ◽  
Stock Exchange ◽  
Sovereign Default ◽  
Linear Regression Models ◽  
Exchange Performance ◽  
Sovereign Default Risk ◽  
Dow Jones Industrial Average

Different prediction models are explored to analyze the performance of the Mexican Stock Exchange (PQI) after the 2008 crisis. These models have demonstrated a good prognostic capacity for both multivariable and univariable approaches given their non-parametric characteristics. The selected variables were: Dow Jones Industrial Average Index (DJIA), CPI, International Reserves (IR), CETES28, USDMX exchange rate, (M1) and the sovereign default risk of Mexico (MRDS). The models were evaluated with MAPE and compared with linear regression models (LR) and neural networks (NN). The results show that the models have a similar performance according to the percentages of error they presented.

Black Bass Diversity: Multidisciplinary Science for Conservation

2015 ◽  
Keyword(s):  
Mixed Model ◽  
Micropterus Salmoides ◽  
Underlying Mechanism ◽  
Treated Wastewater ◽  
Fish Length ◽  
Catch Per Unit Effort ◽  
Explanatory Factors ◽  
Black Bass ◽  
Intersex Condition ◽  
Catch Rates

<em>Abstract</em>.—Reports of testicular oocytes (intersex) in fish are increasing worldwide. Intersex is often associated with estrogens in treated wastewater effluents, but few studies have explored other potentially explanatory factors. Our recent survey of intersex Largemouth Bass <em>Micropterus salmoides</em> in 11 impoundments across Georgia, USA found high incidence (>80%) of intersex fish in some impoundments but none in others. To explore factors associated with intersex in the impoundments, which did not receive wastewater, we examined potential predictor variables that varied among the levels of individual fish, impoundment, or landscape in a binomial mixed-model regression approach. Our model indicated effects of fish length, catch per unit effort (an index of fish density), and impoundment, which was the strongest effect. The probability of intersex was highest in smaller fish from impoundments with the highest catch rates. The underlying mechanism(s) for the impoundment effect remain unclear, but we hypothesize that estrogens excreted by high densities of fish and cyanobacteria may influence intersex. Additional studies are needed to understand the long-term population implications of intersex and the role of other biological and environmental factors, particularly at the impoundment level, in development of the intersex condition.

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