Isotope mixing models require individual isotopic tracer content for correct quantification of sediment source contributions

2018 ◽  
Vol 32 (7) ◽  
pp. 981-989 ◽  
Author(s):  
Hari Ram Upadhayay ◽  
Samuel Bodé ◽  
Marco Griepentrog ◽  
Roshan Man Bajracharya ◽  
William Blake ◽  
...  
Keyword(s):  
Mixing Models ◽  
Sediment Source ◽  
Isotopic Tracer ◽  
Source Contributions ◽  
Isotope Mixing Models

scholarly journals Best practices for use of stable isotope mixing models in food-web studies

2014 ◽  
Vol 92 (10) ◽  
pp. 823-835 ◽  
Author(s):  
Donald L. Phillips ◽  
Richard Inger ◽  
Stuart Bearhop ◽  
Andrew L. Jackson ◽  
Jonathan W. Moore ◽  
...  
Keyword(s):  
Stable Isotope ◽  
Concentration Dependence ◽  
Probability Distributions ◽  
Mixing Models ◽  
Web Studies ◽  
Source Contributions ◽  
Spatio Temporal ◽  
Discrimination Factors ◽  
Isotope Mixing Models ◽  
User Friendly

Stable isotope mixing models are increasingly used to quantify consumer diets, but may be misused and misinterpreted. We address major challenges to their effective application. Mixing models have increased rapidly in sophistication. Current models estimate probability distributions of source contributions, have user-friendly interfaces, and incorporate complexities such as variability in isotope signatures, discrimination factors, hierarchical variance structure, covariates, and concentration dependence. For proper implementation of mixing models, we offer the following suggestions. First, mixing models can only be as good as the study and data. Studies should have clear questions, be informed by knowledge of the system, and have strong sampling designs to effectively characterize isotope variability of consumers and resources on proper spatio-temporal scales. Second, studies should use models appropriate for the question and recognize their assumptions and limitations. Decisions about source grouping or incorporation of concentration dependence can influence results. Third, studies should be careful about interpretation of model outputs. Mixing models generally estimate proportions of assimilated resources with substantial uncertainty distributions. Last, common sense, such as graphing data before analyzing, is essential to maximize usefulness of these tools. We hope these suggestions for effective implementation of stable isotope mixing models will aid continued development and application of this field.

scholarly journals Exploring source differences on diet-tissue discrimination factors in the analysis of stable isotope mixing models

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Wilbert T. Kadye ◽  
Suzanne Redelinghuys ◽  
Andrew C. Parnell ◽  
Anthony J. Booth
Keyword(s):  
Stable Isotope ◽  
Food Sources ◽  
Mixing Models ◽  
Single Source ◽  
Practical Applications ◽  
Source Contributions ◽  
Tissue Discrimination ◽  
Discrimination Factors ◽  
Isotope Mixing Models ◽  
The Individual

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.

Accuracy of mixing models in predicting sediment source contributions

2014 ◽  
Vol 497-498 ◽  
pp. 139-152 ◽  
Author(s):  
Arman Haddadchi ◽  
Jon Olley ◽  
Patrick Laceby
Keyword(s):  
Mixing Models ◽  
Sediment Source ◽  
Source Contributions

A revised model for lipid-normalizing δ13C values from aquatic organisms, with implications for isotope mixing models

2006 ◽  
Vol 43 (6) ◽  
pp. 1213-1222 ◽  
Author(s):  
MIKKO KILJUNEN ◽  
JONATHAN GREY ◽  
TUULA SINISALO ◽  
CHRIS HARROD ◽  
HEMMO IMMONEN ◽  
...  
Keyword(s):  
Aquatic Organisms ◽  
Mixing Models ◽  
Δ13c Values ◽  
Isotope Mixing Models

scholarly journals Do mixing models with different input requirement yield similar streamflow source contributions? Case study: a tropical montane catchment

2021 ◽  
Author(s):  
Jorge Ramón ◽  
Alicia Correa ◽  
Edison Timbe ◽  
Giovanny M. Mosquera ◽  
Enma Mora ◽  
...  
Keyword(s):  
Mixing Models ◽  
Source Contributions

scholarly journals Resolving archaeological populations with Sr-isotope mixing models

2007 ◽  
Vol 22 (7) ◽  
pp. 1502-1514 ◽  
Author(s):  
Janet Montgomery ◽  
Jane A. Evans ◽  
Rachel E. Cooper
Keyword(s):  
Mixing Models ◽  
Sr Isotope ◽  
Isotope Mixing Models

scholarly journals Bayesian stable isotope mixing models

2013 ◽  
pp. n/a-n/a ◽  
Author(s):  
Andrew C. Parnell ◽  
Donald L. Phillips ◽  
Stuart Bearhop ◽  
Brice X. Semmens ◽  
Eric J. Ward ◽  
...  
Keyword(s):  
Stable Isotope ◽  
Mixing Models ◽  
Isotope Mixing Models

Provenance of detrital sediments in Santa Barbara Basin, California, USA: Changes in source contributions between the Last Glacial Maximum and Holocene

2019 ◽  
Vol 132 (1-2) ◽  
pp. 65-84 ◽  
Author(s):  
Tiffany J. Napier ◽  
Ingrid L. Hendy ◽  
M. Florencia Fahnestock ◽  
Julia G. Bryce
Keyword(s):  
Last Glacial Maximum ◽  
Glacial Maximum ◽  
Sediment Flux ◽  
Santa Barbara ◽  
Santa Barbara Basin ◽  
Last Glacial ◽  
Sediment Routing ◽  
Source Contributions ◽  
Terrestrial Sediments ◽  
Isotope Mixing Models

AbstractDetrital terrestrial sediments preserved in near-shore marine basins bear distinctive geochemical identifiers that can be used to identify the on-shore sediment sources and sediment routing through time. Santa Barbara Basin (SBB), offshore of southern California, USA, contains a well-known, continuous, high-resolution Holocene flood record that can provide insights into the frequency and changes in on-shore sources across time for such events. Here SBB-adjacent stream bed sediments are characterized using mineralogical, elemental, and radiogenic strontium and neodymium isotopic compositions. Modern and Holocene SBB flood deposits and Last Glacial Maximum (LGM) sediments were similarly analyzed. The Southern Slopes of the Santa Ynez Mountains and Topatopa Mountains account for ∼85% of SBB Holocene flood deposit sediments, as calculated from Sr-Nd isotope mixing models. During the LGM sea level low stand, the Southern Slopes contribution increased (to ≥90%), while relative sediment contribution from Santa Clara River diminished. This loss was likely compensated, however, by increased sediment flux from the Southern Slopes and the Channel Islands.

scholarly journals Application of stable isotope mixing models for defining trophic biomagnification pathways of mercury and selenium

2014 ◽  
Vol 59 (4) ◽  
pp. 1181-1192 ◽  
Author(s):  
H. J. Jones ◽  
K. M. Swadling ◽  
E. C. V. Butler ◽  
L. A. Barry ◽  
C. K. Macleod
Keyword(s):  
Stable Isotope ◽  
Mixing Models ◽  
Isotope Mixing Models
Sign in / Sign up

Export Citation Format

Share Document