4.6 Article

Inferences to estimate consumer's diet using stable isotopes: Insights from a dynamic mixing model

Journal

PLOS ONE
Volume 17, Issue 2, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0263454

Keywords

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Funding

  1. French government as part of the Programme Investissement d'Avenir [I-SITE ULNE/ANR-16-IDEX-0004 ULNE]
  2. Metropole Europeenne de Lille
  3. Science Foundation Ireland Career Development Award [17/CDA/4695 (T)]
  4. Science Foundation Ireland (SFI) [17/CDA/4695(T)] Funding Source: Science Foundation Ireland (SFI)

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Stable isotope mixing models are used to reconstruct animal diet, but current research neglects the dynamics of isotopic ratios and the impact of time lag on diet reconstruction. By using a dynamic mixing model, it is possible to more accurately estimate the consumer's diet and avoid misinterpretation in ecosystem functioning and food-web structure analysis.
Stable isotope ratios are used to reconstruct animal diet in trophic ecology via mixing models. Several assumptions of stable isotope mixing models are critical, i.e., constant trophic discrimination factor and isotopic equilibrium between the consumer and its diet. The isotopic turnover rate (lambda and its counterpart the half-life) affects the dynamics of isotopic incorporation for an organism and the isotopic equilibrium assumption: lambda involves a time lag between the real assimilated diet and the diet estimated by mixing models at the individual scale. Current stable isotope mixing model studies consider neither this time lag nor even the dynamics of isotopic ratios in general. We developed a mechanistic framework using a dynamic mixing model (DMM) to assess the contribution of A to the dynamics of isotopic incorporation and to estimate the bias induced by neglecting the time lag in diet reconstruction in conventional static mixing models (SMMs). The DMM includes isotope dynamics of sources (denoted delta(s)), lambda and frequency of diet-switch (omega). The results showed a significant bias generated by the SMM compared to the DMM (up to 50% of differences). This bias can be strongly reduced in SMMs by averaging the isotopic variations of the food sources over a time window equal to twice the isotopic half-life. However, the bias will persist (similar to 15%) for intermediate values of the co/A ratio. The inferences generated using a case study highlighted that DMM enhanced estimates of consumer's diet, and this could avoid misinterpretation in ecosystem functioning, food-web structure analysis and underlying biological processes.

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