Social structuration in medieval rural society based on stable isotope analysis of dietary habits and mobility patterns: San Juan de Momoitio (Biscay, north Iberian Peninsula)

2020 ◽  
Vol 31 ◽  
pp. 102300
Author(s):  
Iranzu Guede ◽  
Maria Cruz Zuluaga ◽  
Luis Angel Ortega ◽  
Ainhoa Alonso-Olazabal ◽  
Xabier Murelaga ◽  
...  
Author(s):  
Brandon D Hoenig ◽  
Allison M Snider ◽  
Anna M Forsman ◽  
Keith A Hobson ◽  
Steven C Latta ◽  
...  

Abstract Identifying the composition of avian diets is a critical step in characterizing the roles of birds within ecosystems. However, because birds are a diverse taxonomic group with equally diverse dietary habits, gaining an accurate and thorough understanding of avian diet can be difficult. In addition to overcoming the inherent difficulties of studying birds, the field is advancing rapidly, and researchers are challenged with a myriad of methods to study avian diet, a task that has only become more difficult with the introduction of laboratory techniques to dietary studies. Because methodology drives inference, it is important that researchers are aware of the capabilities and limitations of each method to ensure the results of their study are interpreted correctly. However, few reviews exist which detail each of the traditional and laboratory techniques used in dietary studies, with even fewer framing these methods through a bird-specific lens. Here, we discuss the strengths and limitations of morphological prey identification, DNA-based techniques, stable isotope analysis, and the tracing of dietary biomolecules throughout food webs. We identify areas of improvement for each method, provide instances in which the combination of techniques can yield the most comprehensive findings, introduce potential avenues for combining results from each technique within a unified framework, and present recommendations for the future focus of avian dietary research.


PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3436 ◽  
Author(s):  
Shaena Montanari

Stable isotope analysis of feces can provide a non-invasive method for tracking the dietary habits of nearly any mammalian species. While fecal samples are often collected for macroscopic and genetic study, stable isotope analysis can also be applied to expand the knowledge of species-specific dietary ecology. It is somewhat unclear how digestion changes the isotope ratios of animals’ diets, so more controlled diet studies are needed. To date, most diet-to-feces controlled stable isotope experiments have been performed on herbivores, so in this study I analyzed the carbon and nitrogen stable isotope ratios in the diet and feces of the meerkat (Suricata suricatta), a small omnivorous mammal. The carbon trophic discrimination factor between diet and feces (Δ13Cfeces) is calculated to be 0.1 ± 1.5‰, which is not significantly different from zero, and in turn, not different than the dietary input. On the other hand, the nitrogen trophic discrimination factor (Δ15Nfeces) is 1.5 ± 1.1‰, which is significantly different from zero, meaning it is different than the average dietary input. Based on data generated in this experiment and a review of the published literature, carbon isotopes of feces characterize diet, while nitrogen isotope ratios of feces are consistently higher than dietary inputs, meaning a discrimination factor needs to be taken into account. The carbon and nitrogen stable isotope values of feces are an excellent snapshot of diet that can be used in concert with other analytical methods to better understand ecology, diets, and habitat use of mammals.


2020 ◽  
Vol 57 (1) ◽  
pp. 35-52
Author(s):  
Olga E. Poshekhonova ◽  
Dmitry I. Razhev ◽  
Sergey M. Slepchenko ◽  
Zhanna V. Marchenko ◽  
Vladimir N. Adaev

2003 ◽  
Author(s):  
R. T. Short ◽  
Gottfried P. Kibelka ◽  
Robert H. Byrne ◽  
David Hollander

2017 ◽  
Author(s):  
Peter Mortensen ◽  
◽  
Nathan D. Stansell ◽  
Byron A. Steinman ◽  
Gilles Y. Brocard ◽  
...  

Author(s):  
Andreas Hilkert ◽  
John K. Böhlke ◽  
Stanley J. Mroczkowski ◽  
Kyle L. Fort ◽  
Konstantin Aizikov ◽  
...  

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