Methods for identifying origin, movement, and foraging areas of animals are essential for understanding ecosystem connectivity, nutrient flows, and other ecological processes. Telemetric methods can provide detailed spatial coverage but are limited to a minimum body size of specimen for tagging. In recent years, stable isotopes have been increasingly used to track animal migration by linking landscape isotope patterns into movement (isoscapes). However, compared to telemetric methods, the spatial resolution of bulk stable isotopes is low. Here, we examined a novel approach by evaluating the use of compound-specific hydrogen and carbon stable isotopes of fatty acids (δH and δC) from fish liver, muscle, brain, and eye tissues for identifying site specificity in a 254 km sub-alpine river catchment. We analyzed 208 fish (European bullhead, rainbow trout, and brown trout) collected in 2016 and 2018 at 15 different sites. δC values of these fish tissues correlated more among each other than those of δH values. Both δH and δC values showed tissue-dependent isotopic fractionation, while fish taxa had only small effects. The highest site specificity was for δC values, while the δH isotopic difference between linoleic acid and alpha-linolenic acid resulted in the highest site specificity. Using linear discrimination analysis of FA isotope values, over 90% of fish could be assigned to their location of origin; however, the accuracy dropped to about 56% when isotope data from 2016 were used to predict the sites for samples collected in 2018, suggesting temporal shifts in site specificity of δH and δC. However, the predictive power of δH and δC over this time interval was still higher than site specificity of bulk tissue isotopes for a single time point. In summary, compound-specific isotope analysis of fatty acids may become a highly effective tool for assessing fine and large-scale movement and foraging areas of animals.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352314 | PMC |
http://dx.doi.org/10.1021/acs.est.2c02089 | DOI Listing |
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