Item talk:Q301069
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Energetic status of Alaskan Chinook Salmon: Interpopulation comparisons and predictive modeling using bioelectrical impedance analysis", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70228329", "url": "https://pubs.usgs.gov/publication/70228329" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70228329 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1002/nafm.10398", "url": "https://doi.org/10.1002/nafm.10398" } ], "journal": { "@type": "Periodical", "name": "North American Journal of Fisheries Management", "volumeNumber": "40", "issueNumber": "1" }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "North American Journal of Fisheries Management" } ], "datePublished": "2020", "dateModified": "2022-02-10", "abstract": "Adult Pacific Salmon Oncorhynchus spp. undertake energetically demanding migrations wherein they must have adequate energy reserves to survive to spawning locations and reproduce. Proximate analysis provides insight into available energy stores (e.g., lipids), but the ability to non-lethally monitor energetic status may be useful for managers to better understand how energetic status affects salmon populations in light of population declines and threats from climate change and habitat alteration. Chinook Salmon Oncorhynchus tshawytscha (N = 129) were sampled for proximate analysis from four populations in Alaska to examine variation in energetic status pre- and post-spawning migration and to create predictive bioelectrical impedance analysis (BIA) models for this species. We also tested two BIA devices (Q2 and CQR), whether models were generalizable to a con-specific (Chum Salmon Oncorhynchus keta), and the feasibility of integrating BIA into field studies. Populations sampled pre- spawning migration had higher percent lipid (N = 77; mean = 42.57%) than those collected post spawning migration (N = 52; mean = 19.71%). Total percent lipid and water were more accurately predicted from the Q2 device based on BIA measurements (RMSE = 5.33; RMSE = 2.43, respectively), relative to CQR device measurements (RMSE = 6.27; RMSE = 2.66). Between-species (Chinook to Chum RMSE = 19.47; Chum to Chinook RMSE = 7.69) models were less accurate than species specific models created for Chinook and Chum Salmon, therefore single species models should be used. We field-tested the BIA model to predict Chinook Salmon %lipid and %water on a remote Southeast Alaska river. Techniques were quickly taught to field crews and predictions were similar to other pre-spawning migration estimates. 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