Juvenile salmonids in streams typically feed on larger invertebrates than the average size available in the drift. Our objective was to describe the allometry of this size-selective foraging in juv...

/pdf/allometry-of-diet-selectivity-in-juvenile-atlantic-salmon-4f4vo8qy7t.pdf

Allometry of diet selectivity in juvenile Atlantic salmon (Salmo salar)

African lungfish genome sheds light on the vertebrate water-to-land transition.

The ability to predict local structural features of a protein from the primary sequence is of paramount importance for unravelling its function in absence of experimental structural information. Two main factors affect the utility of potential prediction tools: their accuracy must enable extraction of reliable structural information on the proteins of interest, and their runtime must be low to keep pace with sequencing data being generated at a constantly increasing speed. Here, we present an updated and extended version of the NetSurfP tool (http://www.cbs.dtu.dk/services/NetSurfP-2.0/), that can predict the most important local structural features with unprecedented accuracy and runtime. NetSurfP-2.0 is sequence-based and uses an architecture composed of convolutional and long short-term memory neural networks trained on solved protein structures. Using a single integrated model, NetSurfP-2.0 predicts solvent accessibility, secondary structure, structural disorder, and backbone dihedral angles for each residue of the input sequences. We assessed the accuracy of NetSurfP-2.0 on several independent test datasets and found it to consistently produce state-of-the-art predictions for each of its output features. We observe a correlation of 80% between predictions and experimental data for solvent accessibility, and a precision of 85% on secondary structure 3-class predictions. In addition to improved accuracy, the processing time has been optimized to allow predicting more than 1,000 proteins in less than 2 hours, and complete proteomes in less than 1 day.

/pdf/netsurfp-2-0-improved-prediction-of-protein-structural-7mjj1x9d5e.pdf

NetSurfP-2.0: improved prediction of protein structural features by integrated deep learning

Brown trout in the River Negro in northern Spain preferentially ate larger aquatic prey items (found throughout the water column). A model based on size-dependent prey encounters was able to accoun...

Prey-size selection by brown trout (Salmo trutta L.) in a stream in northern Spain

Drift-feeding fish are challenged to discriminate between prey and similar-sized particles of debris, which are ubiquitous even in clear-water streams. Spending time and energy pursuing debris mistaken as prey could affect fish growth and the fitness potential of different foraging strategies. Our goal was to determine the extent to which debris influences drift-feeding fish in clear water under low-flow conditions when the distracting effect of debris should be at a minimum. We used high-definition video to measure the reactions of drift-feeding juvenile Chinook salmon (Oncorhynchus tshawytscha) to natural debris and prey in situ in the Chena River, Alaska. Among all potential food items fish pursued, 52 % were captured and quickly expelled from the mouth, 39 % were visually inspected but not captured, and only 9 % were ingested. Foraging attempt rate was only moderately correlated with ingestion rate (Kendall's τ=0.55), raising concerns about the common use of foraging attempts as a presumed index of foraging success. The total time fish spent handling debris increased linearly with foraging attempt rate and ranged between 4 and 25 % of total foraging time among observed groups. Our results help motivate a revised theo- retical view of drift feeding that emphasizes prey detection and discrimination, incorporating ideas from signal detec- tion theory and the study of visual attention in cognitive ecology. We discuss how these ideas could lead to better explanations and predictions of the spatial behavior, prey selection, and energy intake of drift-feeding fish.

Mechanisms of drift-feeding behavior in juvenile Chinook salmon and the role of inedible debris in a clear-water Alaskan stream

A novel technique is described, using serial photography of the gut contents of transparent living larval fishes, to generate individual gut evacuation time series. This technique was applied to Atlantic mackerel Scomber scombrus larvae to compare three widely used models of gut evacuation: linear, exponential and square-root. Regression r 2 for the exponential model exceeded those for the linear and square root models in 20 of 21 time series, strongly supporting the exponential model. At the initial gut fullness for each time series, total gut evacuation rates calculated with the exponential model averaged 2� 2a nd 1� 3 times greater than those calculated with the linear and square-root models, respectively, and would produce correspondingly higher estimates of feeding rates for field-collected larvae with similar levels of gut fullness. The results highlight the importance of choosing the appropriate evacuation model in feeding studies, particularly those intended to examine short-term changes in larval fish feeding rates, a contributing factor to the highly variable yearly recruitment of many marine fish species. Journal compilation # 2009 The Fisheries Society of the British Isles No claim to original US government works

A comparison of gut evacuation models for larval mackerel (Scomber scombrus) using serial photography

The results of a test of a mechanistic encounter model that predicts the size-frequency composition of the diet of drift-feeding coho salmon (Oncorhynchus kisulch, Walbaum) are described. When all taxa in the drift were included in the model the predicted and actual diets differed significantly, although the model explained most of the variance between the diet and the predictions of a null model. When non-consumed taxa, including the distasteful and aposematic taxon Hydracarina, were excluded from the drift composition there was no significant difference between predicted and actual diets. The model's goodness of fit increased when it was modified to predict the biomass size-frequency diet composition, explaining 99% of the weighted sum of squared deviations between the diet and a null model. A number of alternate models are tested and a potentially useful simplification of the model is identified.

Sub‐surface drift feeding by coho salmon (Oncorhynchus kisutch, Walbaum): a model and test

Mark-recapture was used to quantify the relationship between body mass (M T ) and individual growth rates of sub-adult marbled lungfish Protopterus aethiopicus in Lake Baringo, Kenya. Specific growth rate (in mass) was found to be a well defined and decreasing function of M T over the size range of recaptured fish. Growth trajectories based on this function indicated that Lake Baringo African lungfish reached maturity at an age of c. 3 years and had a low reproductive effort.

Marbled lungfish growth rates in Lake Baringo, Kenya, estimated by mark-recapture

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

R. Dunbrack

Author Tools

Chat about Author

Papers

A comparison of gut evacuation models for larval mackerel (Scomber scombrus) using serial photography

Sub‐surface drift feeding by coho salmon (Oncorhynchus kisutch, Walbaum): a model and test

Marbled lungfish growth rates in Lake Baringo, Kenya, estimated by mark-recapture