4.2 Article

Tools for quantifying isotopic niche space and dietary variation at the individual and population level

期刊

JOURNAL OF MAMMALOGY
卷 93, 期 2, 页码 329-341

出版社

OXFORD UNIV PRESS INC
DOI: 10.1644/11-MAMM-S-187.1

关键词

isotope mixing models; isotopic niches; sea otters; stable isotope analysis

类别

资金

  1. Monterey Bay National Marine Sanctuary Foundation
  2. United States Marine Mammal Commission
  3. National Science Foundation [ATM-0502491, DIOS-0848028]
  4. Carnegie Institution of Washington
  5. W. M. Keck Foundation [072000]

向作者/读者索取更多资源

Ecologists are increasingly using stable isotope analysis to inform questions about variation in resource and habitat use from the individual to community level. In this study we investigate data sets from 2 California sea otter (Enhydra lutris nereis) populations to illustrate the advantages and potential pitfalls of applying various statistical and quantitative approaches to isotopic data. We have subdivided these tools, or metrics, into 3 categories: IsoSpace metrics, stable isotope mixing models, and DietSpace metrics. IsoSpace metrics are used to quantify the spatial attributes of isotopic data that are typically presented in bivariate (e.g., delta C-13 versus delta N-15) 2-dimensional space. We review IsoSpace metrics currently in use and present a technique by which uncertainty can be included to calculate the convex hull area of consumers or prey, or both. We then apply a Bayesian-based mixing model to quantify the proportion of potential dietary sources to the diet of each sea otter population and compare this to observational foraging data. Finally, we assess individual dietary specialization by comparing a previously published technique, variance components analysis, to 2 novel DietSpace metrics that are based on mixing model output. As the use of stable isotope analysis in ecology continues to grow, the field will need a set of quantitative tools for assessing isotopic variance at the individual to community level. Along with recent advances in Bayesian-based mixing models, we hope that the IsoSpace and DietSpace metrics described here will provide another set of interpretive tools for ecologists.

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