An unbiased method to estimate individual specialisation from multi‐tissue isotopic data

Abstract

Abstract Individual specialisation could affect several ecological and evolutionary processes. Assessing isotopic data from different tissues of a single individual (multi‐tissue approach) represents a common method to estimate individual trophic specialisation (ITS). However, a neglected problem with this approach is that isotopic values of two tissues from a single individual are not statistically independent, and hence, an underestimation of the within‐individual component of variance should be theoretically expected. In this study, we evaluate this potential problem by comparing ITS estimations as currently calculated (uncorrected ITS) against ITS estimations based on a new method that considers the non‐independence problem (corrected ITS). We used unpublished δ15N and δ13C data for nine fish species, together with previously published δ15N and δ13C data for eight other vertebrate species, to estimate (and compare) components of variance and ITS values, using uncorrected and corrected isotopic data. In addition, for each species, we used a Monte Carlo resampling routine to test the null hypothesis that all individuals sample equally from the population diet distribution. We found that the use of uncorrected δ15N values provided an average ITS estimation which is, depending on the overlap among tissues turnover rates, 14%–35% (fish dataset) and 17%–40% (all species dataset) lower than estimations based on corrected values. Similarly, the use of uncorrected δ13C values provided an average ITS estimation which is 12%–29% (fish dataset) and 21%–45% (all species dataset) lower than corrected estimations. The implications of these results in an ecological context are of great significance. For instance, the fish dataset showed that while uncorrected estimations indicate that three (δ13C) or four (δ15N) species are trophic specialists at the individual level, a moderate correction in isotopic values indicate that none (δ13C) or only one (δ15N) species is a trophic specialist at that level. Noticeably, this last result is much more congruent with dietary data obtained from stomach content analysis. Given the several pros of the multi‐tissue approach, such as its reduced operative costs, we suggest not to abandon this method, but to cope with the non‐independence problem by using the correction proposed here or, at least, by selecting body tissues with a minimal overlap in their turnover rates.