Abstract
BackgroundBayesian mixing models have allowed for the inclusion of uncertainty and prior information in the analysis of trophic interactions using stable isotopes. Formulating prior distributions is relatively straightforward when incorporating dietary data. However, the use of data that are related, but not directly proportional, to diet (such as prey availability data) is often problematic because such information is not necessarily predictive of diet, and the information required to build a reliable prior distribution for all prey species is often unavailable. Omitting prey availability data impacts the estimation of a predator's diet and introduces the strong assumption of consumer ultrageneralism (where all prey are consumed in equal proportions), particularly when multiple prey have similar isotope values.MethodologyWe develop a procedure to incorporate prey availability data into Bayesian mixing models conditional on the similarity of isotope values between two prey. If a pair of prey have similar isotope values (resulting in highly uncertain mixing model results), our model increases the weight of availability data in estimating the contribution of prey to a predator's diet. We test the utility of this method in an intertidal community against independently measured feeding rates.ConclusionsOur results indicate that our weighting procedure increases the accuracy by which consumer diets can be inferred in situations where multiple prey have similar isotope values. This suggests that the exchange of formalism for predictive power is merited, particularly when the relationship between prey availability and a predator's diet cannot be assumed for all species in a system.
Highlights
Trophic interactions are fundamental components of biodiversity, directly contributing to ecosystem organization and dynamics [1]
Our results indicate that our weighting procedure increases the accuracy by which consumer diets can be inferred in situations where multiple prey have similar isotope values
The work is made available under the Creative Commons CC0 public domain dedication
Summary
Background Trophic interactions are fundamental components of biodiversity, directly contributing to ecosystem organization and dynamics [1]. It is impossible to directly observe or document feeding relationships [3]. In many such cases, ratios of stable isotopes (typically those of carbon: 13C:12C and nitrogen: 15N:14N) can be used to investigate the diets of consumers [4]. Bayesian mixing models have allowed for the inclusion of uncertainty and prior information in the analysis of trophic interactions using stable isotopes. The use of data that are related, but not directly proportional, to diet (such as prey availability data) is often problematic because such information is not necessarily predictive of diet, and the information required to build a reliable prior distribution for all prey species is often unavailable. Omitting prey availability data impacts the estimation of a predator’s diet and introduces the strong assumption of consumer ultrageneralism (where all prey are consumed in equal proportions), when multiple prey have similar isotope values
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