Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region, 2015-2017

These data comprise the laboratory experiments on Arctic Grayling (Thymallus arcticus) and Dolly Varden charr (Salvelinus malma) as part of the larger Drift Model Project fish foraging and behavior study conducted by the Grossman Lab at the University of Georgia. Specifically, these data describe th...

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Main Authors: Grossman, Gary, Bozeman, Bryan
Format: Dataset
Language:English
Published: Axiom Data Science 2020
Subjects:
Online Access:https://dx.doi.org/10.24431/rw1k46c
https://search.dataone.org/#view/10.24431/rw1k46c
id ftdatacite:10.24431/rw1k46c
record_format openpolar
spelling ftdatacite:10.24431/rw1k46c 2023-05-15T14:31:22+02:00 Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region, 2015-2017 Grossman, Gary Bozeman, Bryan 2020 https://dx.doi.org/10.24431/rw1k46c https://search.dataone.org/#view/10.24431/rw1k46c en eng Axiom Data Science dataset Dataset 2020 ftdatacite https://doi.org/10.24431/rw1k46c 2021-11-05T12:55:41Z These data comprise the laboratory experiments on Arctic Grayling (Thymallus arcticus) and Dolly Varden charr (Salvelinus malma) as part of the larger Drift Model Project fish foraging and behavior study conducted by the Grossman Lab at the University of Georgia. Specifically, these data describe the results of many single- and multi-fish foraging experiments conducted on Arctic Grayling and Dolly Varden charr experimental specimens in an artificial stream flume in Athens, Georgia. The dataset consists of four Microsoft excel workbooks, two for single-fish experiments and two for multi-fish experiments (i.e., one workbook per species per experiment type). The data consists of: 1) individual markers for experimental specimens (or pairs in multi-fish experiments), 2) batch (i.e., experimental specimen groups), 3) predictor variable values (i.e., treatment velocities, fish sizes, days in captivity, and size rank and dominance [for multi-fish experiments]), 4) response variable values (i.e., prey capture success percentages, holding velocities, and reactive distances), and 5) other values of potential interest but not included in analyses (i.e., capture velocity, raw prey capture numbers, and variable measurements in alternate units). Fish used in all experiments were captured via hook and line between fall of 2015 and fall of 2016 from Panguingue Creek in Interior Alaska and immediately shipped to the University of Georgia upon capture. We subjected experimental specimens to a series of increasing water velocity treatment trials in an experimental stream flume to determine how prey capture success, holding velocity, and reactive distance were affected by treatment velocity, fish size, and days kept in captivity with additional categorical predictor variables of size rank (i.e., larger or smaller) and dominance (based on holding position within experimental stream flume) for multi-fish experiments. Treatment velocity and holding velocity measurements were made immediately prior to and following treatment velocity trials with a handheld electronic velocity meter. We made prey capture success measurements in real time immediately following each treatment velocity trial by recording the number of prey captured per fixed number of prey releases. Finally, reactive distance and capture velocity measurements were made after experiments had been completed via trial video analysis using the VidSync (www.vidsync.org) computer software. Dolly Varden charr and Arctic Grayling are economically and ecologically important species in Interior Alaska and understanding how these species utilize and select microhabitats has important implications for their management and overall stream fish-habitat relationship scholarship and conservation. Data are presented as two CSV files: Grayling_Dominance_Experiment_Data.csv Dolly_Dominance_Experiment_Data.csv Dataset Arctic grayling Arctic Kuskokwim Thymallus arcticus Alaska Yukon DataCite Metadata Store (German National Library of Science and Technology) Arctic Varden ENVELOPE(7.656,7.656,62.534,62.534) Yukon
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
description These data comprise the laboratory experiments on Arctic Grayling (Thymallus arcticus) and Dolly Varden charr (Salvelinus malma) as part of the larger Drift Model Project fish foraging and behavior study conducted by the Grossman Lab at the University of Georgia. Specifically, these data describe the results of many single- and multi-fish foraging experiments conducted on Arctic Grayling and Dolly Varden charr experimental specimens in an artificial stream flume in Athens, Georgia. The dataset consists of four Microsoft excel workbooks, two for single-fish experiments and two for multi-fish experiments (i.e., one workbook per species per experiment type). The data consists of: 1) individual markers for experimental specimens (or pairs in multi-fish experiments), 2) batch (i.e., experimental specimen groups), 3) predictor variable values (i.e., treatment velocities, fish sizes, days in captivity, and size rank and dominance [for multi-fish experiments]), 4) response variable values (i.e., prey capture success percentages, holding velocities, and reactive distances), and 5) other values of potential interest but not included in analyses (i.e., capture velocity, raw prey capture numbers, and variable measurements in alternate units). Fish used in all experiments were captured via hook and line between fall of 2015 and fall of 2016 from Panguingue Creek in Interior Alaska and immediately shipped to the University of Georgia upon capture. We subjected experimental specimens to a series of increasing water velocity treatment trials in an experimental stream flume to determine how prey capture success, holding velocity, and reactive distance were affected by treatment velocity, fish size, and days kept in captivity with additional categorical predictor variables of size rank (i.e., larger or smaller) and dominance (based on holding position within experimental stream flume) for multi-fish experiments. Treatment velocity and holding velocity measurements were made immediately prior to and following treatment velocity trials with a handheld electronic velocity meter. We made prey capture success measurements in real time immediately following each treatment velocity trial by recording the number of prey captured per fixed number of prey releases. Finally, reactive distance and capture velocity measurements were made after experiments had been completed via trial video analysis using the VidSync (www.vidsync.org) computer software. Dolly Varden charr and Arctic Grayling are economically and ecologically important species in Interior Alaska and understanding how these species utilize and select microhabitats has important implications for their management and overall stream fish-habitat relationship scholarship and conservation. Data are presented as two CSV files: Grayling_Dominance_Experiment_Data.csv Dolly_Dominance_Experiment_Data.csv
format Dataset
author Grossman, Gary
Bozeman, Bryan
spellingShingle Grossman, Gary
Bozeman, Bryan
Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region, 2015-2017
author_facet Grossman, Gary
Bozeman, Bryan
author_sort Grossman, Gary
title Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region, 2015-2017
title_short Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region, 2015-2017
title_full Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region, 2015-2017
title_fullStr Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region, 2015-2017
title_full_unstemmed Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region, 2015-2017
title_sort development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile chinook salmon in the arctic-yukon-kuskokwim region, 2015-2017
publisher Axiom Data Science
publishDate 2020
url https://dx.doi.org/10.24431/rw1k46c
https://search.dataone.org/#view/10.24431/rw1k46c
long_lat ENVELOPE(7.656,7.656,62.534,62.534)
geographic Arctic
Varden
Yukon
geographic_facet Arctic
Varden
Yukon
genre Arctic grayling
Arctic
Kuskokwim
Thymallus arcticus
Alaska
Yukon
genre_facet Arctic grayling
Arctic
Kuskokwim
Thymallus arcticus
Alaska
Yukon
op_doi https://doi.org/10.24431/rw1k46c
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