A Bayesian framework for stable isotope mixing models

By Erik B. Erhardt, Edward J. Bedrick. Environmental and Ecological Statistics, 2013

47 citations recorded by the source corpus.

Subfields: Atmospheric Science, Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/97329b359186f9d2118ffb513db19f0b4781e34e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Richard Inger
2. S. Bearhop
3. Andrew C. Parnell
4. A. Jackson
5. B. Semmens
6. D. Phillips
7. Eric J. Ward
8. J. Moore

In Ecology

1. S. Bearhop
2. Richard Inger
3. Keith A. Hobson
4. Andrew C. Parnell
5. A. Jackson
6. D. Phillips
7. B. Semmens
8. J. Moore

In Global and Planetary Change

1. S. Bearhop
2. Richard Inger
3. B. Semmens
4. Andrew C. Parnell
5. A. Jackson
6. J. Moore
7. Eric J. Ward
8. D. Phillips

Citations in the corpus

• Best practices for use of stable isotope mixing models in food-web studies (2014, methodology): “…2010), SIAR (Parnell et al. 2010), MixSIAR (Stock and Semmens 2013), IsotopeR (Hopkins and Ferguson 2012), FRUITS (Fernandes et al. 2014), and that of Erhardt and Bedrick (2013) explicitly deal with variability among consumer and source isotopic values (which implicitly include measurement errors).”