Model output and observational data were in agreement, both indicating that despite their abundance in the intertidal region, marine foods comprised only a small proportion of baboon diet. This suggests that stable isotope analysis is a viable tool for investigating marine food consumption by natural-foraging primates in temperate regions.

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An extensive ecological literature applies stable isotope mixing models to derive quantitative dietary reconstructions from isotope ratios of consumer tissues. While this approach works well for some organisms, it is challenging for consumers with complex, varied diets, including humans; indeed, many archaeologists have avoided the use of mixing models because uncertainties in model outputs are sufficiently large that the findings are not helpful in understanding ancient lifeways. Here, we exploit an unparalleled opportunity to evaluate the feasibility of dietary quantification in a nutritionally and isotopically complex context on the Cape Peninsula, South Africa. Delta values (δ13C and δ15N) of 213 indigenous food samples enable us to characterise four food groups: terrestrial plants, terrestrial vertebrates, marine invertebrates and marine vertebrates. A recent study of baboons that consumed marine and terrestrial foods provides insight into the relationship between such foods and consumer tissue isotopes. We use this information to refine our interpretation of δ15N and especially δ13C in bone collagen from 35 archaeological hunter-gatherers, achieving better estimates of the relative importance of marine and terrestrial foods in the diet than has hitherto been possible. Based on Bayesian stable isotope mixing model (SIMM) outputs, we infer that the trophic enrichment factor (TEF) for δ13Cbone collagen in these coastal humans is closer to +3 than +5‰. In the most 13C- and 15N-rich individuals, 65–98% of bone collagen (95% credible intervals) derived from marine foods. Conversely, in 13C and 15N-poor individuals, 7–44% of bone collagen derived from marine foods. The uncertainties discussed here highlight the need for caution when implementing SIMMs in studies of consumers with complex diets. To our knowledge, this work constitutes the most detailed and most tightly constrained study of this problem to date.

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The original version of this article unfortunately contained two mistakes in captions in the BActivity Budgets^section. The relevant figure and table, with the correct captions (corrections underlined), are shown below. Both mistakes were made by the authors in the final submission and were not noticed at proofing stage.