A1 Journal article (refereed)
A Bayesian stable isotope mixing model for coping with multiple isotopes, multiple trophic steps and small sample sizes (2022)
Heikkinen, R., Hämäläinen, H., Kiljunen, M., Kärkkäinen, S., Schilder, J., & Jones, R. I. (2022). A Bayesian stable isotope mixing model for coping with multiple isotopes, multiple trophic steps and small sample sizes. Methods in Ecology and Evolution, 13(11), 2586-2602. https://doi.org/10.1111/2041-210x.13989
JYU authors or editors
Publication details
All authors or editors: Heikkinen, Risto; Hämäläinen, Heikki; Kiljunen, Mikko; Kärkkäinen, Salme; Schilder, Jos; Jones, Roger I.
Journal or series: Methods in Ecology and Evolution
ISSN: 2041-210X
eISSN: 2041-210X
Publication year: 2022
Publication date: 11/10/2022
Volume: 13
Issue number: 11
Pages range: 2586-2602
Publisher: Wiley-Blackwell
Publication country: United Kingdom
Publication language: English
DOI: https://doi.org/10.1111/2041-210x.13989
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/83573
Abstract
The model incorporates isotopes of multiple elements (e.g. C, N, H) for two trophic levels, when the structure of the food web is known. In addition, the model allows inclusion of latent trophic levels (i.e. for which no empirical data are available) intermediate between sources and measured consumers. Running the model in simulations driven by a real dataset from Finnish lakes, we tested the sensitivity of the posterior distributions by altering critical prior parameters and assumptions in the data-generating process.
Importantly, we found that the model estimations were particularly sensitive to the assigned prior value for ω (the fraction of H in aquatic consumer tissue that is derived from environmental water rather than diet) so that reliable empirical data for this parameter are required. When reliable information is not available for ω, we suggest that an uninformative prior should be used.
The proposed model and inferences are suitable for studies where resources for collecting new data are limited, but useful prior information for each specific trophic level is available from earlier studies.
Keywords: Bayesian analysis; isotopes; food webs
Free keywords: Bayesian mixing model; informative prior; multiple levels; stable isotope
Contributing organizations
Related projects
- Consumer allochthony in lakes
- Hämäläinen, Heikki
- Research Council of Finland
- Holistic evaluation and restoration measures of human impacts on freshwater ecosystems across biogeographical gradients (FreshRestore)
- Eloranta, Antti
- Research Council of Finland
Ministry reporting: Yes
Reporting Year: 2022
JUFO rating: 2
- Aquatic Sciences (Department of Biological and Environmental Science BIOENV) WET
- Computational Science (Faculty of Information Technology IT) LASK
- Multiobjective Optimization Group (Faculty of Information Technology IT) MOG
- School of Resource Wisdom (University of Jyväskylä JYU) JYU.Wisdom
- Statistics (Department of Mathematics and Statistics MATHS) TIL