Fish diets provide information that can be used to explore and model complex ecosystems, and infer resource partitioning among species. The exhaustive sampling of prey items captured by each species remains, however, a demanding task. Therefore, predicting diets from other variables, such as functional traits, may be a valuable method. Here, we attempted to predict trophic guild and diet overlap for 35 fish species using 13 ecomorphological traits related to feeding ecology. We compared linear discriminant analysis and random forest (RF) classifiers in their ability to predict trophic guild. We used generalized dissimilarity modelling to predict diet overlap from functional distances between species pairs. All models were evaluated using the same cross-validation procedure. We found that fish trophic guilds were accurately predicted by an RF classifier, even with a limited number of traits, when no more than 7 guilds were defined. Prediction was no longer accurate when finer trophic guilds were created (8 or more guilds), whatever the combination of traits. Furthermore, predicting the degree of diet dissimilarity between species pairs, based on their ecomorphological traits dissimilarities, was profoundly unreliable (at least 76% of unexplained variation). These results suggest that we can predict fish trophic guilds accurately from ecomorphological traits, but not diet overlap and resource partitioning because of inherent versatility in fish diets. More generally, our statistical framework may be applied to any kind of marine organism for which feeding strategies need to be determined from traits.
KEY WORDS: Generalized dissimilarity modeling · Mediterranean · Fish · Non-linear model · Random forest · VersatilityResale or republication not permitted without written consent of the publisher Mar Ecol Prog Ser 436: 17-28, 2011 ing biotic indicators relevant to human impacts (SosaLopez et al. 2005). In addition, overlap in diet composition and resource partitioning between species is a key element of interspecific competition that can determine stable coexistence (Sala & Ballesteros 1997, Colloca et al. 2010. Determining the level of diet overlap among species is, therefore, also a major tool in predicting extirpations of species as a result of competitive interactions with invasive species (Karlson et al. 2007, Glen & Dickman 2008, Arismendi et al. 2009, Gregory & Macdonald 2009, Zeug et al. 2009).In practice, identifying the diet composition of species is a very time-consuming and demanding task with many potential biases. Indeed, a complete knowledge of prey items targeted by omnivorous species is unrealistic in prey-rich communities (Araújo et al. 2008). Diet composition is often assessed using stomach contents, which are influenced by many temporal (Lehikoinen 2005, Horppila 2009) and spatial factors (e.g. opportunistic behaviors; Link & Garrison 2002). Hence stomach content analysis is a time-consuming method that can only provide a fragmentary image of a species' diet.An alternative approach to ...