Using functional traits to predict pollination services: A review

Abstract

Pollination is a fundamental ecosystem service. Predictive and mechanistic models linking pollinator community structure to pollination services increasingly incorporate information on unique functional differences among species, so called effects traits. There is little consensus as to which traits are most important in supporting pollination services at either an individual or community level. Here, we synthesise the state of current knowledge regarding the role and efficacy of traits for predicting pollination, as well as the use of different methods for describing the trait structure of pollinator assemblages. We find a wide range of traits are currently used to predict pollination services, including morphological, behavioural and phenological characteristics. However, we show that the evidence demonstrating their importance is often limited or mixed. There is a trade-off in how traits are used between those that are easier to measure, available for many species but have only limited evidence for their role in pollination, vs. those that are harder to measure but with a more robust link with pollination service delivery. We highlight how community weighted means and measures of functional diversity offer important, albeit different insights into pollination service delivery. We discuss how their relative importance is likely to depend on the goals of the study. To maximise fully the utilisation of traits to predict pollination services, future research should be directed towards the widespread and consistent validation of the links among different traits and the pollination service across crop and semi-natural plant communities. Ideally this also needs to address geographical and taxonomic biases in trait collection.