Landscape characteristics and coho salmon (Oncorhynchus kisutch) distributions: explaining abundance versus occupancy

2012 ◽  
Vol 69 (3) ◽  
pp. 457-468 ◽  
Author(s):  
E.A. Steel ◽  
D.W. Jensen ◽  
K.M. Burnett ◽  
K. Christiansen ◽  
J.C. Firman ◽  
...  
Keyword(s):  
Coho Salmon ◽  
Full Range ◽  
Model Performance ◽  
Oncorhynchus Kisutch ◽  
Monitoring Data ◽  
Published Data ◽  
Data Sets ◽  
Data Set ◽  
Landscape Characteristics ◽  
Oregon Plan

Distribution of fishes, both occupancy and abundance, is often correlated with landscape-scale characteristics (e.g., geology, climate, and human disturbance). Understanding these relationships is essential for effective conservation of depressed populations. We used landscape characteristics to explain the distribution of coho salmon ( Oncorhynchus kisutch ) in the Oregon Plan data set, one of the first long-term, probabilistic salmon monitoring data sets covering the full range of potential habitats. First we compared data structure and model performance between the Oregon Plan data set and two published data sets on coho salmon distribution. Most of the variation in spawner abundance occurred between reaches but much also occurred between years, limiting potential model performance. Similar suites of landscape predictors are correlated with coho salmon distribution across regions and data sets. We then modeled coho salmon spawner distribution using the Oregon Plan data set and determined that landscape characteristics could not explain presence vs. absence of spawners but that the percentage of agriculture, winter temperature range, and the intrinsic potential of the stream could explain some variation in abundance (weighted average R2 = 0.30) where spawners were present. We conclude that the previous use of nonrandom monitoring data sets may have obscured understanding of species distribution, and we suggest minor modifications to large-scale monitoring programs.

Relative testis size and mating systems in anurans: large testis in multiple-male mating in foam-nesting frogs

2011 ◽  
Vol 61 (2) ◽  
pp. 225-238 ◽  
Author(s):  
Wen Bo Liao ◽  
Zhi Ping Mi ◽  
Cai Quan Zhou ◽  
Ling Jin ◽  
Xian Han ◽  
...  
Keyword(s):  
Sperm Competition ◽  
Published Data ◽  
Male Mating ◽  
Data Sets ◽  
Testis Size ◽  
Data Set ◽  
Monogamous Species ◽  
Large Testis ◽  
Testes Size ◽  
Testis Mass

AbstractComparative studies of the relative testes size in animals show that promiscuous species have relatively larger testes than monogamous species. Sperm competition favours the evolution of larger ejaculates in many animals – they give bigger testes. In the view, we presented data on relative testis mass for 17 Chinese species including 3 polyandrous species. We analyzed relative testis mass within the Chinese data set and combining those data with published data sets on Japanese and African frogs. We found that polyandrous foam nesting species have relatively large testes, suggesting that sperm competition was an important factor affecting the evolution of relative testes size. For 4 polyandrous species testes mass is positively correlated with intensity (males/mating) but not with risk (frequency of polyandrous matings) of sperm competition.

scholarly journals Children with 5′-end NF1 gene mutations are more likely to have glioma

2017 ◽  
Vol 3 (5) ◽  
pp. e192 ◽  
Author(s):  
Corina Anastasaki ◽  
Stephanie M. Morris ◽  
Feng Gao ◽  
David H. Gutmann
Keyword(s):  
Gene Mutation ◽  
Statistical Significance ◽  
Gene Mutations ◽  
Neurofibromatosis Type ◽  
Published Data ◽  
Data Sets ◽  
Nonsense Mutations ◽  
Data Set ◽  
Nf1 Gene ◽  
The Relationship

Objective:To ascertain the relationship between the germline NF1 gene mutation and glioma development in patients with neurofibromatosis type 1 (NF1).Methods:The relationship between the type and location of the germline NF1 mutation and the presence of a glioma was analyzed in 37 participants with NF1 from one institution (Washington University School of Medicine [WUSM]) with a clinical diagnosis of NF1. Odds ratios (ORs) were calculated using both unadjusted and weighted analyses of this data set in combination with 4 previously published data sets.Results:While no statistical significance was observed between the location and type of the NF1 mutation and glioma in the WUSM cohort, power calculations revealed that a sample size of 307 participants would be required to determine the predictive value of the position or type of the NF1 gene mutation. Combining our data set with 4 previously published data sets (n = 310), children with glioma were found to be more likely to harbor 5′-end gene mutations (OR = 2; p = 0.006). Moreover, while not clinically predictive due to insufficient sensitivity and specificity, this association with glioma was stronger for participants with 5′-end truncating (OR = 2.32; p = 0.005) or 5′-end nonsense (OR = 3.93; p = 0.005) mutations relative to those without glioma.Conclusions:Individuals with NF1 and glioma are more likely to harbor nonsense mutations in the 5′ end of the NF1 gene, suggesting that the NF1 mutation may be one predictive factor for glioma in this at-risk population.

scholarly journals Recommendations for bacterial ribosome profiling experiments based on bioinformatic evaluation of published data

2020 ◽  
Vol 295 (27) ◽  
pp. 8999-9011 ◽  
Author(s):  
Alina Glaub ◽  
Christopher Huptas ◽  
Klaus Neuhaus ◽  
Zachary Ardern
Keyword(s):  
Ribosome Profiling ◽  
Published Data ◽  
Data Sets ◽  
Drug Induced ◽  
Data Set ◽  
Protein Coding ◽  
Bacterial Ribosome ◽  
Translation Start ◽  
Selection Step ◽  
Basic Characteristics

Ribosome profiling (RIBO-Seq) has improved our understanding of bacterial translation, including finding many unannotated genes. However, protocols for RIBO-Seq and corresponding data analysis are not yet standardized. Here, we analyzed 48 RIBO-Seq samples from nine studies of Escherichia coli K12 grown in lysogeny broth medium and particularly focused on the size-selection step. We show that for conventional expression analysis, a size range between 22 and 30 nucleotides is sufficient to obtain protein-coding fragments, which has the advantage of removing many unwanted rRNA and tRNA reads. More specific analyses may require longer reads and a corresponding improvement in rRNA/tRNA depletion. There is no consensus about the appropriate sequencing depth for RIBO-Seq experiments in prokaryotes, and studies vary significantly in total read number. Our analysis suggests that 20 million reads that are not mapping to rRNA/tRNA are required for global detection of translated annotated genes. We also highlight the influence of drug-induced ribosome stalling, which causes bias at translation start sites. The resulting accumulation of reads at the start site may be especially useful for detecting weakly expressed genes. As different methods suit different questions, it may not be possible to produce a “one-size-fits-all” ribosome profiling data set. Therefore, experiments should be carefully designed in light of the scientific questions of interest. We propose some basic characteristics that should be reported with any new RIBO-Seq data sets. Careful attention to the factors discussed should improve prokaryotic gene detection and the comparability of ribosome profiling data sets.

Nature of intrafractional and interfractional prostate motion during stereotactic radiation.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 152-152
Author(s):  
Karthikeyan Perumal ◽  
Mahadev Potharaju
Keyword(s):  
Treatment Time ◽  
Published Data ◽  
Data Sets ◽  
Data Set ◽  
Stereotactic Radiation ◽  
X Ray ◽  
Total Treatment Time ◽  
Prostate Motion ◽  
Predictable Pattern ◽  
Total Treatment

152 Background: To characterize the intra-fraction and inter-fraction prostate motion as tracked by the X-ray images of the implanted gold fiducials during stereotactic radiotherapy with CyberKnife. The published data have analysed the linear and angular prostate motion intrafraction and interfraction prostate motion among patients. We sought to quantify the same within each patient. Methods: Twenty Five patients with localized prostate cancer treated with CyberKnife radiosurgery between January 2013 and August 2015 were studied retrospectively. A data set constitutes the deviations derived from X-ray images obtained between two consecutive couch motions. Results: Included in the analysis were 3926 data sets. A total of 210 non-coplanar fields were used per fraction. The mean total treatment time for all fields per fraction was 36.13 minutes. The detected and corrected movements over all were in a range of ± 10.1 mm in linear direction (Right: mean 1.1±0.4 mm; Left: mean 1.0±0.6 mm; Superior: mean 0.7±0.3 mm; Inferior: mean 1.6±0.6 mm; Anterior: mean 1.6±0.7 mm; Posterior: mean 0.5±0.3 mm with maximum (max) movement range of Right max 9.9±6.4 mm, Left max 7.1±3.4 mm, Superior max 8.6±5.4 mm, Inferior max 10.1±8.5 mm, Anterior max 9.2±6.5 mm, Posterior max 8.4±2.9 mm) and angular movements were in a range of ± 6.7 deg in all directions (Right Angle: mean 0.6±0.3 deg; Left Angle: mean 0.6±0.3 deg; Head Up(H-U): mean 1.3±0.6 deg; Head Down(H-D): mean 1.4±0.6 deg; Counter-Clockwise movement (CCW): mean 0.7±0.3 deg; Clockwise movement (CW): mean 0.5±0.3 deg with max rotation range of Right angle max 2.4±2 deg, Left angle max 2.7±2 deg, H-U max 10.2±3.5 deg, H-D max 6.7±4.8 deg, CCW 4±2.9 deg, CW max 2.8±2.4 deg). There was an unpredictable change in prostate motion inter-fraction in each patient. But, a unique observation is that a predictable pattern exists for prostate motion intra-fraction within a patient. Change in the linear or angular prostate motion intra-fraction in any direction is not erratic. Conclusions: The linear and rotational prostate motion intra-fraction in any direction has a predictable pattern and any change is gradual and not erratic. The motion shows secular trend during the course of treatment.

Oblique Field Magnetic Flux Leakage Inline Survey Tool: Implementation and Results

2010 ◽  
Author(s):  
James Simek ◽  
Jed Ludlow ◽  
Phil Tisovec
Keyword(s):  
Experimental Data ◽  
Magnetic Flux ◽  
Full Range ◽  
Magnetic Flux Leakage ◽  
Metal Loss ◽  
Data Sets ◽  
Data Set ◽  
Survey Tool ◽  
Oblique Field ◽  
Flux Leakage

InLine Inspection (ILI) tools using the magnetic flux leakage (MFL) technique are the most common type used for performing metal loss surveys worldwide. Based upon the very robust and proven magnetic flux leakage technique, these tools have been shown to operate reliably in the extremely harsh environments of transmission pipelines. In addition to metal loss, MFL tools are capable of identifying a broad range of pipeline features. Most MFL surveys to date have used tools employing axially oriented magnetizers, capable of detecting and quantifying many categories of volumetric metal loss features. For certain classes of axially oriented features, MFL tools using axially oriented fields have encountered difficulty in detection and subsequent quantification. To address features in these categories, tools employing circumferential or transversely oriented fields have been designed and placed into service, enabling enhanced detection and sizing for axially oriented features. In most cases, multiple surveys are required, as current tools do not incorporate the ability to collect both data sets concurrently. Applying the magnetic field in an oblique direction will enable detection of axially oriented features and may be used simultaneously with an axially oriented tool. Referencing previous research in adapting circumferential or transverse designs for inline service, the concept of an oblique field magnetizer will be presented. Models developed demonstrating the technique are discussed, shown with experimental data supporting the concept. Efforts involved in the implementation of an oblique magnetizer, including magnetic models for field profiles used to determine magnetizer configurations and sensor locations are presented. Experimental results are provided detailing the response of the system to a full range of metal loss features, supplementing modeling in an effort to determine the effects of variables introduced by magnetic property and velocity induced differences. Included in the experimental data results are extremely narrow axially oriented features, many of which are not detected or identified within the axial data set. Experimental and field verification results for detection accuracies will be described in comparison to an axial field tool.

scholarly journals The benefits of segmentation: Evidence from a South African bank and other studies

2017 ◽  
Vol 113 (9/10) ◽  
Author(s):  
Douw G. Breed ◽  
Tanja Verster
Keyword(s):  
South African ◽  
Direct Marketing ◽  
Model Performance ◽  
Predictive Modelling ◽  
Modelling Technique ◽  
Gradient Boosting ◽  
Data Sets ◽  
Data Set ◽  
Linear Modelling ◽  
Modelling Techniques

We applied different modelling techniques to six data sets from different disciplines in the industry, on which predictive models can be developed, to demonstrate the benefit of segmentation in linear predictive modelling. We compared the model performance achieved on the data sets to the performance of popular non-linear modelling techniques, by first segmenting the data (using unsupervised, semi-supervised, as well as supervised methods) and then fitting a linear modelling technique. A total of eight modelling techniques was compared. We show that there is no one single modelling technique that always outperforms on the data sets. Specifically considering the direct marketing data set from a local South African bank, it is observed that gradient boosting performed the best. Depending on the characteristics of the data set, one technique may outperform another. We also show that segmenting the data benefits the performance of the linear modelling technique in the predictive modelling context on all data sets considered. Specifically, of the three segmentation methods considered, the semi-supervised segmentation appears the most promising.

scholarly journals The use of genetic programming to develop a predictor of swash excursion on sandy beaches

2018 ◽  
Vol 18 (2) ◽  
pp. 599-611 ◽  
Author(s):  
Marinella Passarella ◽  
Evan B. Goldstein ◽  
Sandro De Muro ◽  
Giovanni Coco
Keyword(s):  
Genetic Programming ◽  
Sandy Beaches ◽  
Coastal Hazards ◽  
Coastal Processes ◽  
Published Data ◽  
Data Sets ◽  
Prediction Errors ◽  
Data Set ◽  
Physical Insight ◽  
Insight Into

Abstract. We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation). Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches) and providing physical insight into coastal processes.

Critical thermal maxima of coho salmon (Oncorhynchus kisutch) fry under field and laboratory acclimation regimes

1995 ◽  
Vol 73 (5) ◽  
pp. 993-996 ◽  
Author(s):  
John T. Konecki ◽  
Carol A. Woody ◽  
Thomas P. Quinn
Keyword(s):  
Coho Salmon ◽  
Oncorhynchus Kisutch ◽  
Washington State ◽  
Published Data ◽  
Critical Thermal Maximum ◽  
Temperature Regimes ◽  
Thermal Maximum ◽  
Critical Thermal Maxima ◽  
Laboratory Acclimation ◽  
Two Populations

Juvenile coho salmon (Oncorhynchus kisutch) from three populations in Washington State were captured in the field and tested for critical thermal maximum (CTM). Tolerances varied among the populations (mean CTMs were 28.21, 29.13, and 29.23 °C) and exceeded published data from some laboratory tests. The population from a relatively cool stream had a lower CTM than the two populations from warmer streams. However, after the salmon had been in the laboratory for 3 months under constant, common temperature regimes, the CTMs no longer differed, indicating that the population-specific differences resulted from different acclimation regimes rather than from genetic adaptation.

Reference points for coho salmon (Oncorhynchus kisutch) harvest rates and escapement goals based on freshwater production

2000 ◽  
Vol 57 (4) ◽  
pp. 677-686 ◽  
Author(s):  
Michael J Bradford ◽  
Ransom A Myers ◽  
James R Irvine
Keyword(s):  
Reference Point ◽  
Historical Data ◽  
Coho Salmon ◽  
Oncorhynchus Kisutch ◽  
Reference Points ◽  
Data Sets ◽  
Ocean Productivity ◽  
Freshwater Habitats ◽  
Marine Survival ◽  
Stick Model

We describe a simple scheme for the management of coho salmon (Oncorhynchus kisutch) population aggregates that uses reference points derived from an empirical analysis of freshwater production data. We fit a rectilinear "hockey stick" model to 14 historical data sets of female spawner abundance and resulting smolt production and found that at low spawner abundance, the average productivity was about 85 smolts per female spawner. Variation in productivity among streams may be related to the quality of the stream habitat. We show how freshwater productivity can be combined with forecasts of marine survival to provide a limit reference point harvest rate. Our method will permit harvest rates to track changes in ocean productivity. We also used the historical data to estimate that, on average, a density of 19 female spawners·km-1 is required to fully seed freshwater habitats with juveniles. However, there was considerable variation among the streams that might limit the utility of this measure as a reference point. Uncertainty in the forecasts of marine survival and other parameters needs to be incorporated into our scheme before it can be considered a precautionary approach.

scholarly journals An empirical investigation of alternative semi-supervised segmentation methodologies

2019 ◽  
Vol 115 (3/4) ◽  
Author(s):  
Douw G. Breed ◽  
Tanja Verster
Keyword(s):  
Logistic Regression ◽  
Model Performance ◽  
Predictive Modelling ◽  
Data Sets ◽  
Validation Data ◽  
Data Set ◽  
Supervised Segmentation ◽  
Improved Performance ◽  
Validation Set ◽  
Combination Approach

Segmentation of data for the purpose of enhancing predictive modelling is a well-established practice in the banking industry. Unsupervised and supervised approaches are the two main types of segmentation and examples of improved performance of predictive models exist for both approaches. However, both focus on a single aspect – either target separation or independent variable distribution – and combining them may deliver better results. This combination approach is called semi-supervised segmentation. Our objective was to explore four new semi-supervised segmentation techniques that may offer alternative strengths. We applied these techniques to six data sets from different domains, and compared the model performance achieved. The original semi-supervised segmentation technique was the best for two of the data sets (as measured by the improvement in validation set Gini), but others outperformed for the other four data sets. Significance: We propose four newly developed semi-supervised segmentation techniques that can be used as additional tools for segmenting data before fitting a logistic regression. In all comparisons, using semi-supervised segmentation before fitting a logistic regression improved the modelling performance (as measured by the Gini coefficient on the validation data set) compared to using unsegmented logistic regression.

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