Re‐constructing nutritional history of Serengeti wildebeest from stable isotopes in tail hair: seasonal starvation patterns in an obligate grazer

RATIONALE Nutritional bottlenecks often limit the abundance of animal populations and alter individual behaviours; however, establishing animal condition over extended periods of time using non-invasive techniques has been a major limitation in population ecology. We test if the sequential measurement of δ(15) N values in a continually growing tissue, such as hair, can be used as a natural bio-logger akin to tree rings or ice cores to provide insights into nutritional stress. METHODS Nitrogen stable isotope ratios were measured by continuous-flow isotope-ratio mass spectrometry (IRMS) from 20 sequential segments along the tail hairs of 15 migratory wildebeest. Generalized Linear Models were used to test for variation between concurrent segments of hair from the same individual, and to compare the δ(15) N values of starved and non-starved animals. Correlations between δ(15) N values in the hair and periods of above-average energy demand during the annual cycle were tested using Generalized Additive Mixed Models. RESULTS The time series of nitrogen isotope ratios in the tail hair are comparable between strands from the same individual. The most likely explanation for the pattern of (15) N enrichment between individuals is determined by life phase, and especially the energetic demands associated with reproduction. The mean δ(15) N value of starved animals was greater than that of non-starved animals, suggesting that higher δ(15) N values correlate with periods of nutritional stress. CONCLUSIONS High δ(15) N values in the tail hair of wildebeest are correlated with periods of negative energy balance, suggesting they may be used as a reliable indicator of the animal's nutritional history. This technique might be applicable to other obligate grazers. Most importantly, the sequential isotopic analysis of hair offers a continuous record of the chronic condition of wildebeest (effectively converting point data into time series) and allows researchers to establish the animal's nutritional diary.