The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Recent Bayesian stable-isotope mixing models are highly sensitive to variation in discrimination factors
Open accessAbstract
Stable isotopes are now used widely in ecological studies, including diet reconstruction, where quantitative inferences about diet composition are derived from the use of mixing models. Recent Bayesian models (MixSIR, SIAR) allow users to incorporate variability in discrimination factors (delta13C or delta15N), or the amount of change in either delta13C or delta15N between prey and consumer, but to date there has been no systematic assessment of the effect of variation in delta13C or delta15N on model outputs. We used whole blood from Common Terns (Sterna hirundo) and muscle from their common prey items (fish and euphausiids) to build a series of mixing models in SIAR (stable isotope analysis in R) using various discrimination factors from the published literature for marine birds. The estimated proportion of each diet component was affected significantly by delta13C or delta15N. We also use recently published stable-isotope data on the reliance of critically endangered Balearic Shearwaters (Puffinus mauretanicus) on fisheries discards to show that discrimination factor choice can have profound implications for conservation and management actions. It is therefore crucial for researchers wishing to use mixing models to have an accurate estimate of delta13C and delta15N, because quantitative diet estimates can help to direct future research or prioritize conservation and management actions.
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A RAPID METHOD OF TOTAL LIPID EXTRACTION AND PURIFICATION
Bligh, E. G., & Dyer, W. J. (1959) · Canadian Journal of Biochemistry and Physiology · doi:10.1139/o59-099 · Cited by 54,751
Influence of diet on the distribution of nitrogen isotopes in animals
Deniro, M. J., & Epstein, S. (1981) · Geochimica et Cosmochimica Acta · doi:10.1016/0016-7037(81)90244-1 · Cited by 6,138
Source Partitioning Using Stable Isotopes: Coping with Too Much Variation
Parnell, A. C., Inger, R., Bearhop, S., & Jackson, A. L. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009672 · Cited by 2,940
Source partitioning using stable isotopes: coping with too many sources
Phillips, D. L., & Gregg, J. W. (2003) · Oecologia · doi:10.1007/s00442-003-1218-3 · Cited by 2,079
Bhattacharyya, A. (1943) · Medical Entomology and Zoology · Cited by 2,002
The Divergence and Bhattacharyya Distance Measures in Signal Selection
Kailath, T. (1967) · IEEE Transactions on Communications · doi:10.1109/tcom.1967.1089532 · Cited by 1,856
Measurement of "Overlap" in Comparative Ecological Studies
Horn, H. S. (1966) · The American Naturalist · doi:10.1086/282436 · Cited by 1,613
Sources of variation in consumer-diet ?15N enrichment: a meta-analysis
Vanderklift, M. A., & Ponsard, S. (2003) · Oecologia · doi:10.1007/s00442-003-1270-z · Cited by 1,545
Mechanism of Carbon Isotope Fractionation Associated with Lipid Synthesis
DeNiro, M. J., & Epstein, S. (1977) · Science · doi:10.1126/science.327543 · Cited by 1,459
Caut, S., Angulo, E., & Courchamp, F. (2009) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2009.01620.x · Cited by 1,425
Cited by
Analyzing mixing systems using a new generation of Bayesian tracer mixing models
Stock, B. C., Jackson, A. L., Ward, E. J., Parnell, A. C., Phillips, D. L., & Semmens, B. X. (2018) · PeerJ · doi:10.7717/peerj.5096 · Cited by 1,524
Best practices for use of stable isotope mixing models in food-web studies
Phillips, D. L., Inger, R., Bearhop, S., Jackson, A. L., Moore, J. W., Parnell, A. C., Semmens, B. X., & Ward, E. J. (2014) · Canadian Journal of Zoology · doi:10.1139/cjz-2014-0127 · Cited by 1,232
Metadata
- Authors
- Bond, A. L., & Diamond, A. W.
- Venue
- Ecological Applications
- Publisher
- Wiley
- Published
- 2011-06
- Volume
- 21
- Issue
- 4
- Pages
- 1017-1023
- ISSN
- 1051-0761 (ISSN-L)
- OpenAlex
- W2153297504
- Cited by
- 437
- References
- 27
- FWCI
- 18.20
- Type
- journal article
- Language
- en
- Open access
- bronze
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