Data from: Automated peak detection method for behavioral event identification: detecting Balaenoptera musculus and Grampus griseus feeding attempts

The desire of animal behaviorists for more flexible methods of conducting inter-study and inter-specific comparisons and meta-analysis of various animal behaviors compelled us to design an automated, animal behavior peak detection method that is potentially generalizable to a wide variety of data ty...

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Bibliographic Details
Main Authors: Sweeney, David A., DeRuiter, Stacy L., McNamara-Oh, Ye Joo, Marques, Tiago A., Arranz, Patricia, Calambokidis, John
Format: Dataset
Language:unknown
Published: 2019
Subjects:
psy
Online Access:https://doi.org/10.5061/dryad.bd8j403
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record_format openpolar
spelling fttriple:oai:gotriple.eu:50|dedup_wf_001::b4522de63eea12d3931f03080c8dbcad 2023-05-15T15:36:19+02:00 Data from: Automated peak detection method for behavioral event identification: detecting Balaenoptera musculus and Grampus griseus feeding attempts Sweeney, David A. DeRuiter, Stacy L. McNamara-Oh, Ye Joo Marques, Tiago A. Arranz, Patricia Calambokidis, John 2019-01-01 https://doi.org/10.5061/dryad.bd8j403 undefined unknown http://dx.doi.org/10.5061/dryad.bd8j403 https://dx.doi.org/10.5061/dryad.bd8j403 lic_creative-commons oai:services.nod.dans.knaw.nl:Products/dans:oai:easy.dans.knaw.nl:easy-dataset:125608 10.5061/dryad.bd8j403 oai:easy.dans.knaw.nl:easy-dataset:125608 10|eurocrisdris::fe4903425d9040f680d8610d9079ea14 10|openaire____::9e3be59865b2c1c335d32dae2fe7b254 re3data_____::r3d100000044 10|re3data_____::84e123776089ce3c7a33db98d9cd15a8 10|re3data_____::94816e6421eeb072e7742ce6a9decc5f 10|openaire____::081b82f96300b6a6e3d282bad31cb6e2 Life sciences medicine and health care blue whale Grampus griseus Risso’s dolphin norm-jerk 2010 - 2014 Balaenoptera musculus lunge prey capture detector Southern California Bight Catalina Island envir psy Dataset https://vocabularies.coar-repositories.org/resource_types/c_ddb1/ 2019 fttriple https://doi.org/10.5061/dryad.bd8j403 2023-01-22T16:51:06Z The desire of animal behaviorists for more flexible methods of conducting inter-study and inter-specific comparisons and meta-analysis of various animal behaviors compelled us to design an automated, animal behavior peak detection method that is potentially generalizable to a wide variety of data types, animals, and behaviors. We detected the times of feeding attempts by 12 Risso’s dolphins (Grampus griseus) and 36 blue whales (Balaenoptera musculus) using the norm-jerk (rate of change of acceleration) time series. The automated peak detection algorithm identified median true-positive rates of 0.881 for blue whale lunges and 0.410 for Risso’s dolphin prey capture attempts, with median false-positive rates of 0.096 and 0.007 and median miss rates of 0.113 and 0.314, respectively. Our study demonstrates that our peak detection method is efficient at automatically detecting animal behaviors from multisensor tag data with high accuracy for behaviors that are appropriately characterized by the data time series. example_detectionsPDF file containing examples of how to perform detections using detect_peaks using a few different signals.testset1Dataset used in creating the example_detections PDF file.blue_whale_figuresROC and side-by-side plots similar to those seen in the manuscript for all of the blue whale data used in this study.risso_dolphin_figuresdataAll data and code used in this study.detector stats tableAll detection statistics for all individual animals used in this study. Dataset Balaenoptera musculus Blue whale Unknown Catalina ENVELOPE(-59.633,-59.633,-62.333,-62.333)
institution Open Polar
collection Unknown
op_collection_id fttriple
language unknown
topic Life sciences
medicine and health care
blue whale
Grampus griseus
Risso’s dolphin
norm-jerk
2010 - 2014
Balaenoptera musculus
lunge
prey capture
detector
Southern California Bight
Catalina Island
envir
psy
spellingShingle Life sciences
medicine and health care
blue whale
Grampus griseus
Risso’s dolphin
norm-jerk
2010 - 2014
Balaenoptera musculus
lunge
prey capture
detector
Southern California Bight
Catalina Island
envir
psy
Sweeney, David A.
DeRuiter, Stacy L.
McNamara-Oh, Ye Joo
Marques, Tiago A.
Arranz, Patricia
Calambokidis, John
Data from: Automated peak detection method for behavioral event identification: detecting Balaenoptera musculus and Grampus griseus feeding attempts
topic_facet Life sciences
medicine and health care
blue whale
Grampus griseus
Risso’s dolphin
norm-jerk
2010 - 2014
Balaenoptera musculus
lunge
prey capture
detector
Southern California Bight
Catalina Island
envir
psy
description The desire of animal behaviorists for more flexible methods of conducting inter-study and inter-specific comparisons and meta-analysis of various animal behaviors compelled us to design an automated, animal behavior peak detection method that is potentially generalizable to a wide variety of data types, animals, and behaviors. We detected the times of feeding attempts by 12 Risso’s dolphins (Grampus griseus) and 36 blue whales (Balaenoptera musculus) using the norm-jerk (rate of change of acceleration) time series. The automated peak detection algorithm identified median true-positive rates of 0.881 for blue whale lunges and 0.410 for Risso’s dolphin prey capture attempts, with median false-positive rates of 0.096 and 0.007 and median miss rates of 0.113 and 0.314, respectively. Our study demonstrates that our peak detection method is efficient at automatically detecting animal behaviors from multisensor tag data with high accuracy for behaviors that are appropriately characterized by the data time series. example_detectionsPDF file containing examples of how to perform detections using detect_peaks using a few different signals.testset1Dataset used in creating the example_detections PDF file.blue_whale_figuresROC and side-by-side plots similar to those seen in the manuscript for all of the blue whale data used in this study.risso_dolphin_figuresdataAll data and code used in this study.detector stats tableAll detection statistics for all individual animals used in this study.
format Dataset
author Sweeney, David A.
DeRuiter, Stacy L.
McNamara-Oh, Ye Joo
Marques, Tiago A.
Arranz, Patricia
Calambokidis, John
author_facet Sweeney, David A.
DeRuiter, Stacy L.
McNamara-Oh, Ye Joo
Marques, Tiago A.
Arranz, Patricia
Calambokidis, John
author_sort Sweeney, David A.
title Data from: Automated peak detection method for behavioral event identification: detecting Balaenoptera musculus and Grampus griseus feeding attempts
title_short Data from: Automated peak detection method for behavioral event identification: detecting Balaenoptera musculus and Grampus griseus feeding attempts
title_full Data from: Automated peak detection method for behavioral event identification: detecting Balaenoptera musculus and Grampus griseus feeding attempts
title_fullStr Data from: Automated peak detection method for behavioral event identification: detecting Balaenoptera musculus and Grampus griseus feeding attempts
title_full_unstemmed Data from: Automated peak detection method for behavioral event identification: detecting Balaenoptera musculus and Grampus griseus feeding attempts
title_sort data from: automated peak detection method for behavioral event identification: detecting balaenoptera musculus and grampus griseus feeding attempts
publishDate 2019
url https://doi.org/10.5061/dryad.bd8j403
long_lat ENVELOPE(-59.633,-59.633,-62.333,-62.333)
geographic Catalina
geographic_facet Catalina
genre Balaenoptera musculus
Blue whale
genre_facet Balaenoptera musculus
Blue whale
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op_relation http://dx.doi.org/10.5061/dryad.bd8j403
https://dx.doi.org/10.5061/dryad.bd8j403
op_rights lic_creative-commons
op_doi https://doi.org/10.5061/dryad.bd8j403
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