Summary 1.Further advancement in the use of stable isotope analysis in animal ecology and physiology requires a better understanding of how organisms incorporate the macromolecular elements they consume into the tissues they biosynthesize. 2. Mixing models used to infer diets from isotopic data assume that assimilated macromolecules are dissembled into elements and then reassembled in animal tissues. 3. To test this assumption, we fed Nile tilapia diets with contrasting levels of protein and in which the carbon isotopic composition of protein differed from that of other macronutrients (carbohydrates and lipids). We then analysed the d13 C values of individual tilapia amino acids using compound-specific stable isotope analysis (CSIA). 4. C values of their corresponding dietary amino acid as protein intake increased. This pattern is consistent with assimilation of indispensable amino acids of microbial origin by tilapias fed low protein food. 6. Our results suggest that the assumptions of mixing models are sound in situations where omnivores consume protein-deficient diets, as the elemental constituents used to biosynthesize amino acids in tissues may be derived from various ingested macromolecules (e.g. protein, carbohydrates, or lipids) and their elemental components. In contrast, for omnivores that consume sufficient amounts of protein, macromolecular (e.g. protein) routing likely occurs and mixing model assumptions are violated. 7. Our study shows that CSIA is a novel method to quantify the contribution of symbiotic microbes to the amino acid homeostasis of animals.

Understanding rates of isotopic incorporation and discrimination factors between tissues and diet is an important focus of ecologists seeking to use stable isotopes to track temporal changes in diet. We used a diet-shift experiment to measure differences among tissues in (13)C incorporation rates in house sparrows (Passer domesticus). We predicted faster incorporation rates in splanchnic than in structural tissues. We also assessed whether isotopic incorporation data were better supported by the one-compartment models most commonly used by ecologists or by multi-compartment models. We found large differences in the residence time of (13)C among tissues and, as predicted, splanchnic tissues had faster rates of isotopic incorporation and thus shorter retention times than structural tissues. We found that one-compartment models supported isotopic incorporation data better in breath, excreta, red blood cells, bone collagen, and claw tissues. However, data in plasma, intestine, liver, pectoralis muscle, gizzard, and intestine tissues supported two-compartment models. More importantly, the inferences that we derived from the two types of models differed. Two-compartment models estimated longer (13)C residence times, and smaller tissue to diet differences in isotopic composition, than one-compartment models. Our study highlights the importance of considering both one- and multi-compartment models when interpreting laboratory and field isotopic incorporation studies. It also emphasizes the opportunities that measuring several tissues with contrasting isotopic residence times offer to elucidate animal diets at different time scales.

The application of stable isotope analysis to ecology requires estimating the contribution of different isotopic sources to the isotopic signatures of an animal's tissues using mixing models. These models make the physiologically unrealistic assumption that assimilated nutrients are disassembled into their elemental components and that these atoms are then reassembled into biomolecules. We quantified the extent to which mixing models yield erroneous results with an experiment using Nile tilapia (Oreochromis niloticus). The tilapia were fed synthetic diets that varied in protein content and in which the carbon isotopic composition of protein differed widely from that of carbohydrates and lipids. We predicted that dietary protein would contribute disproportionately to the carbon in muscle, whereas the nonprotein components of diet would contribute disproportionately to lipids. Our experiment also allowed us to test the conjecture of a positive correlation between the (15)N enrichment in tissues and protein intake. As predicted, the contribution of protein carbon to muscle was higher than that expected by the assumptions of isotopic mixing in all treatments except that with the lowest dietary protein content. We hypothesized that the unexpectedly high contribution of nonprotein carbon to muscle was the result of assimilating both dispensable and indispensable amino acids synthesized by the fishes' gut microbiota. Although we expected the contribution of carbon in nonprotein dietary ingredients to be higher than expected from a mixing model, we found that protein contributed more than expected, probably as a result of differences in amino acid composition between diet and tissues, which led to excess carbon used for lipid synthesis. Finally, our results verified the positive relationship between dietary protein content and the enrichment in tissue (15)N. Assuming perfect mixing in field isotopic studies can lead to erroneous inferences about the relative contributions of different sources to an animal's diet.

Establishing expressive language benchmarks (ELBs) for children with Down syndrome (DS), as developed by Tager-Flusberg et al. for children with autism, is critically needed to inform the development of novel treatments, identify individualized treatment targets, and promote accurate monitoring of progress. In the present study, we assessed ELB assignments in three language domains (phonology, vocabulary, and grammar) for 53 young children with DS (CA range: 2.50–7.99 years) using standardized assessments. The participants were classified into one of four ELB levels (preverbal, first words, word combinations, and sentences) in each language domain. Associations with additional measures of language, chronological age, nonverbal cognition, and verbal short-term memory were considered. Analyses of individual ELB profiles indicated substantial variability across the three language domains, with six different patterns of variation across domains emerging. At the same time, the ELB categories were significantly associated with independent language measures and broader developmental domains. Moreover, ELB changes were observed in a small sample of children with DS reassessed 18–24 months after the initial visit. Results from the present study suggest the procedures outlined by Tager-Flusberg et al. for defining ELBs are a potentially useful tool for describing the language abilities of children with DS.