End Member and Bayesian mixing models consistently indicate near‐surface flowpath dominance in a pristine humid tropical rainforest

2021 ◽  
Author(s):  
Christian Birkel ◽  
Alicia Correa Barahona ◽  
Clément Duvert ◽  
Sebastián Granados Bolaños ◽  
Andres Chavarría Palma ◽  
...  
Keyword(s):  
Tropical Rainforest ◽  
Mixing Models ◽  
Near Surface ◽  
Bayesian Mixing Models

scholarly journals Fish and maize: Bayesian mixing models of fourteenth- through seventeenth-century AD ancestral Wendat diets, Ontario, Canada

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Robert S. Feranec ◽  
John P. Hart
Keyword(s):  
Native American ◽  
Seventeenth Century ◽  
Great Lakes ◽  
Tooth Enamel ◽  
Mixing Models ◽  
Agricultural Systems ◽  
Southern Ontario ◽  
Bayesian Mixing Models ◽  
Freshwater Bodies ◽  
Dietary Mixing

Abstract Freshwater and marine fish have been important components of human diets for millennia. The Great Lakes of North America, their tributaries and smaller regional freshwater bodies are important Native American fisheries. The ethnohistorical record, zooarchaeological remains, and isotopic values on human bone and tooth collagen indicate the importance of fish in fourteenth- through seventeenth-century ancestral Wendat diets in southern Ontario, which is bordered by three of the Great Lakes. Maize (Zea mays ssp. mays) was the primary grain of Native American agricultural systems in the centuries prior to and following sustained European presence. Here we report new Bayesian dietary mixing models using previously published δ13C and δ15N values on ancestral Wendat bone and tooth collagen and tooth enamel. The results confirm previous estimates from δ13C values that ancestral Wendat diets included high proportions of maize but indicate much higher proportions of fish than has previously been recognized. The results also suggest that terrestrial animals contributed less to ancestral Wendat diets than is typically interpreted based on zooarchaeological records.

scholarly journals Diet sources of the endangered Attwater's prairie‐chicken in Texas: evidence from δ 13 C, δ 15 N, and Bayesian mixing models

Ecosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
Author(s):  
Zaria Torres‐Poché ◽  
Miguel A. Mora ◽  
Thomas W. Boutton ◽  
Michael E. Morrow
Keyword(s):  
Mixing Models ◽  
Bayesian Mixing Models ◽  
Prairie Chicken ◽  
Attwater's Prairie Chicken

scholarly journals Experimentally Derived δ13C and δ15N Discrimination Factors for Gray Wolves and the Impact of Prior Information in Bayesian Mixing Models

PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0119940 ◽  
Author(s):  
Jonathan J. Derbridge ◽  
Jerod A. Merkle ◽  
Melanie E. Bucci ◽  
Peggy Callahan ◽  
John L. Koprowski ◽  
...  
Keyword(s):  
Prior Information ◽  
Mixing Models ◽  
Δ13c And Δ15n ◽  
Gray Wolves ◽  
Bayesian Mixing Models ◽  
Discrimination Factors ◽  
The Impact

Variations in Diet and Stature: Are They Linked? Bioarchaeology and Paleodietary Bayesian Mixing Models from Linköping, Sweden

2012 ◽  
Vol 24 (4) ◽  
pp. 543-556 ◽  
Author(s):  
Caroline Arcini ◽  
Torbjörn Ahlström ◽  
Göran Tagesson
Keyword(s):  
Mixing Models ◽  
Bayesian Mixing Models

scholarly journals Bias in Diet Determination: Incorporating Traditional Methods in Bayesian Mixing Models

PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e80019 ◽  
Author(s):  
Valentina Franco-Trecu ◽  
Massimiliano Drago ◽  
Federico G. Riet-Sapriza ◽  
Andrew Parnell ◽  
Rosina Frau ◽  
...  
Keyword(s):  
Mixing Models ◽  
Traditional Methods ◽  
Bayesian Mixing Models

scholarly journals Sample preservation and pre-treatment in stable isotope analysis: Implications for the study of aquatic food webs

2020 ◽  
Author(s):  
Marc Jürgen Silberberger ◽  
Katarzyna Koziorowska-Makuch ◽  
Karol Kuliński ◽  
Monika Kędra
Keyword(s):  
Stable Isotope ◽  
Food Webs ◽  
Stable Isotope Analysis ◽  
Isotope Analysis ◽  
Mixing Models ◽  
Sample Preservation ◽  
Aquatic Food Webs ◽  
Bayesian Mixing Models ◽  
Aquatic Food ◽  
Pre Treatment

Abstract. Stable isotope analysis has become one of the most widely used techniques in ecology. However, uncertainties about the effects of sample preservation and pre-treatment on the ecological interpretation of stable isotope data and especially on Bayesian stable isotope mixing models remain. Here, Bayesian mixing models were used to study how three different preservation methods (drying, freezing, formalin) and two pre-treatments (acidification, lipid removal) affect the estimation of diet composition for two benthic invertebrate species (Limecola balthica, Crangon crangon). Furthermore, commonly used mathematical lipid normalization and formalin correction were applied to check if they improve the model results. Preservation effects were strong on model outcomes for frozen as well as formalin preserved L. balthica samples, but not for C. crangon. Pre-treatment effects varied with species and preservation method and neither lipid normalization nor mathematical formalin correction consistently resulted in improved model outcomes. Our analysis highlights that particularly small changes in δ15N introduced by different preservation and pre-treatments display a so far unrecognized source of error in stable isotope studies. We conclude that mathematical correction of stable isotopes data should be avoided for Bayesian mixing models and that previously unaddressed effects of sample preservation (especially those arising from preservation by freezing) have potentially biased our understanding of the utilization of organic matter in aquatic food webs.

scholarly journals Strontium Isotopes and the Reconstruction of the Chaco Regional System: Evaluating Uncertainty with Bayesian Mixing Models

PLoS ONE ◽  
2014 ◽  
Vol 9 (5) ◽  
pp. e95580 ◽  
Author(s):  
Brandon Lee Drake ◽  
Wirt H. Wills ◽  
Marian I. Hamilton ◽  
Wetherbee Dorshow
Keyword(s):  
Strontium Isotopes ◽  
Mixing Models ◽  
Bayesian Mixing Models ◽  
Regional System

Competition influence in the segregation of the trophic niche of otariids: a case study using isotopic bayesian mixing models in Galapagos pinnipeds

2014 ◽  
Vol 28 (23) ◽  
pp. 2550-2558 ◽  
Author(s):  
Diego Páez-Rosas ◽  
Mónica Rodríguez-Pérez ◽  
Marjorie Riofrío-Lazo
Keyword(s):  
Trophic Niche ◽  
Mixing Models ◽  
Bayesian Mixing Models
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