scholarly journals High variability in stable isotope diet–tissue discrimination factors of two omnivorous freshwater fishes in controlledex situconditions

2016 ◽  
Vol 219 (7) ◽  
pp. 1060-1068 ◽  
Author(s):  
Georgina M. A. Busst ◽  
J. Robert Britton
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniel J. Madigan ◽  
Owyn E. Snodgrass ◽  
John R. Hyde ◽  
Heidi Dewar

AbstractStable isotope analysis (SIA) measurements from long-term captivity studies provide required parameters for interpretation of consumer SIA data. We raised young-of-the-year (14–19 cm) California yellowtail (Seriola dorsalis) on a low δ15N and δ13C diet (pellet aquaculture feed) for 525 days, then switched to a high δ15N and δ13C diet (mackerel and squid) for 753 days. Yellowtail muscle was sequentially sampled from each individual after the diet switch (0 to 753 days) and analyzed for δ15N and δ13C, allowing for calculation of diet-tissue discrimination factors (DTDFs) from two isotopically different diets (low δ15N and δ13C: pellets; high δ15N and δ13C: fish/squid) and turnover rates of 15N and 13C. DTDFs were diet dependent: Δ15N = 5.1‰, Δ13C = 3.6‰ for pellets and Δ15N = 2.6‰, Δ13C = 1.3‰ for fish/squid. Half-life estimates from 15N and 13C turnover rates for pooled yellowtail were 181 days and 341 days, respectively, but varied considerably by individual (15N: 99–239 d; 13C: 158–899 d). Quantifying DTDFs supports isotopic approaches to field data that assume isotopic steady-state conditions (e.g., mixing models for diet reconstruction). Characterizing and quantifying turnover rates allow for estimates of diet/habitat shifts and “isotopic clock” approaches, and observed inter-individual variability suggests the need for large datasets in field studies. We provide diet-dependent DTDFs and growth effects on turnover rates, and associated error around these parameters, for application to field-collected SIA data from other large teleosts.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Wilbert T. Kadye ◽  
Suzanne Redelinghuys ◽  
Andrew C. Parnell ◽  
Anthony J. Booth

Abstract Stable isotope mixing models are regularly used to provide probabilistic estimates of source contributions to dietary mixtures. Whilst Bayesian implementations of isotope mixing models have become prominent, the use of appropriate diet-tissue discrimination factors (DTDFs) remains as the least resolved aspect. The DTDFs are critical in providing accurate inferences from these models. Using both simulated and laboratory-based experimental data, this study provides conceptual and practical applications of isotope mixing models by exploring the role of DTDFs. The experimental study used Mozambique Tilapia Oreochromis mossambicus, a freshwater fish, to explore multi-tissue variations in isotopic incorporation patterns, and to evaluate isotope mixing model outputs based on the experiment- and literature-based DTDFs. Isotope incorporation patterns were variable for both muscle and fin tissues among the consumer groups that fed diet sources with different stable isotope values. Application of literature-based DTDFs in isotope mixing models consistently underestimated the dietary proportions of all single-source consumer groups. In contrast, application of diet-specific DTDFs provided better dietary estimates for single-source consumer groups. Variations in the proportional contributions of the individual sources were, nevertheless, observed for the mixed-source consumer group, which suggests that isotope assimilation of the individual food sources may have been influenced by other underlying physiological processes. This study provides evidence that stable isotope values from different diet sources exhibit large variations as they become incorporated into consumer tissues. This suggests that the application of isotope mixing models requires consideration of several aspects such as diet type and the associated biological processes that may influence DTDFs.


Bioanalysis ◽  
2019 ◽  
Vol 11 (18) ◽  
pp. 1685-1692 ◽  
Author(s):  
Tom Verhaeghe

Two case studies are presented of validated assays where the internal standard showed high variability, and there was a clear response difference between study samples and standards and quality controls. In the first case a co-eluting peak boosted the stable isotope labeled internal standard response in samples from hepatically impaired subjects. In the second case the blank plasma matrix suppressed the structural analog internal standard response. For both assays the issue could be resolved by adapting the chromatographic conditions and re-validating the assay (case 1) or by diluting the study samples with blank plasma (case 2).


2020 ◽  
Vol 41 (4) ◽  
pp. 501-507
Author(s):  
Julian Glos ◽  
Katharina Ruthsatz ◽  
Dominik Schröder ◽  
Jana C. Riemann

Abstract Analyses of stable isotope ratios are widely applied in studies on a large variety of aspects in trophic ecology. Most studies rely on a precise estimation of the relevant discrimination factor Δ (also called the fractionation factor), that reflects the fractionation or differences in isotope ratios of a certain element (mainly nitrogen N and carbon C) between an animal’s diet and its tissue and is used to identify one step in the food web. We experimentally determined ΔN and ΔC of two species of widespread amphibians in Europe, Rana temporaria and Bufo bufo, and tested for the effect of food source (cyanobacteria Spirulina vs. zooplanktonic Daphnia) on Δ and for interspecific differences. Our study shows high variation in Δ in relation to the food source, but low interspecific differences. Tadpoles that were fed with Spirulina did have considerably lower ΔN than tadpoles fed with Daphnia in both species, and lower ΔC only in R. temporaria. The range of Δ obtained here can be a useful baseline for future trophic studies on tadpoles of Rana and Bufo. The strong diet-dependency of Δ, however, argues strongly against the use of a fixed discrimination factor in future isotope studies.


2012 ◽  
Vol 85 (5) ◽  
pp. 431-441 ◽  
Author(s):  
Hannah B. Vander Zanden ◽  
Karen A. Bjorndal ◽  
Walter Mustin ◽  
José Miguel Ponciano ◽  
Alan B. Bolten

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