2020
DOI: 10.1002/ece3.7022
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Using stable isotopes to infer stock‐specific high‐seas distribution of maturing sockeye salmon in the North Pacific

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Cited by 6 publications
(3 citation statements)
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“…The Importantly, the models developed in this work are effectively averaging over any ontogenetic (French et al, 1976;Myers et al, 2016;Neave et al, 1976) and stock-specific (Espinasse et al, 2020;McKinnell et al, 1997;Shelton et al, 2021;Urawa et al, 2009;Weitkamp & Neely, 2002) distribution patterns, which may themselves be related to differences in temperature preferences among ages and populations, that complicates effective prediction of spatial responses to climate variation. The distribution models and temperature preferences estimated here are intended to represent general basin-wide patterns for each species that can act as a new baseline from which to develop investigations into the influences of F I G U R E 5 Change in thermal habitat suitability scores by month (rows) and species (columns), calculated using the SST effect curves estimated in Model 3 standardized to a [0,1] scale, between mean sea surface temperature conditions matching a cold (1983)(1984)(1985)(1986) and warm (2013-2016) period for sockeye (left), chum (middle) and coho (right) salmon.…”
Section: Discussionmentioning
confidence: 99%
“…The Importantly, the models developed in this work are effectively averaging over any ontogenetic (French et al, 1976;Myers et al, 2016;Neave et al, 1976) and stock-specific (Espinasse et al, 2020;McKinnell et al, 1997;Shelton et al, 2021;Urawa et al, 2009;Weitkamp & Neely, 2002) distribution patterns, which may themselves be related to differences in temperature preferences among ages and populations, that complicates effective prediction of spatial responses to climate variation. The distribution models and temperature preferences estimated here are intended to represent general basin-wide patterns for each species that can act as a new baseline from which to develop investigations into the influences of F I G U R E 5 Change in thermal habitat suitability scores by month (rows) and species (columns), calculated using the SST effect curves estimated in Model 3 standardized to a [0,1] scale, between mean sea surface temperature conditions matching a cold (1983)(1984)(1985)(1986) and warm (2013-2016) period for sockeye (left), chum (middle) and coho (right) salmon.…”
Section: Discussionmentioning
confidence: 99%
“…on the spectral data. Savitzky Golay (SG) [ 42 ] smoothing was usually applied to improve the signal-to-noise ratio (SNR) and to decrease the noise of the original spectra. In this research, SG9 smoothing (three filter windows with a filter width of nine points) was employed to boost NIR resolution and lessen background and baseline.…”
Section: Methodsmentioning
confidence: 99%
“…Notably, the isoscapes should preferentially be based on consistent observational data, i.e., isotopic compositions of materials or organisms that belong to similar trophic level, and these individuals should be situated low enough in the food webs that most predators can be compared to them. Particulate organic matter (Kurle and Mcwhorter, 2017;Seyboth et al, 2018;St John Glew et al, 2021), jellyfish (Mackenzie et al, 2014;St John Glew et al, 2019), zooplankton composition or individuals (Brault et al, 2018;Espinasse et al, 2020b;Matsubayashi et al, 2020) have been used in previous studies to produce large spatial scale isoscapes. A balance needs to be found between the quality (spatiotemporal resolution, consistence in analysing, and sampling procedure among samples) and the quantity of data.…”
Section: Model Structure and Isoscape Limitationsmentioning
confidence: 99%