Abstract
BackgroundFunctional traits are the primary biotic component driving organism influence on ecosystem functions; in consequence, traits are widely used in ecological research. However, most animal trait-based studies use easy-to-measure characteristics of species that are at best only weakly associated with functions. Animal-mediated pollination is a key ecosystem function and is likely to be influenced by pollinator traits, but to date no one has identified functional traits that are simple to measure and have good predictive power.MethodsHere, we show that a simple, easy to measure trait (hairiness) can predict pollinator effectiveness with high accuracy. We used a novel image analysis method to calculate entropy values for insect body surfaces as a measure of hairiness. We evaluated the power of our method for predicting pollinator effectiveness by regressing pollinator hairiness (entropy) against single visit pollen deposition (SVD) and pollen loads on insects. We used linear models and AICC model selection to determine which body regions were the best predictors of SVD and pollen load.ResultsWe found that hairiness can be used as a robust proxy of SVD. The best models for predicting SVD for the flower species Brassica rapa and Actinidia deliciosa were hairiness on the face and thorax as predictors (R2 = 0.98 and 0.91 respectively). The best model for predicting pollen load for B. rapa was hairiness on the face (R2 = 0.81).DiscussionWe suggest that the match between pollinator body region hairiness and plant reproductive structure morphology is a powerful predictor of pollinator effectiveness. We show that pollinator hairiness is strongly linked to pollination—an important ecosystem function, and provide a rigorous and time-efficient method for measuring hairiness. Identifying and accurately measuring key traits that drive ecosystem processes is critical as global change increasingly alters ecological communities, and subsequently, ecosystem functions worldwide.
Highlights
Trait-based approaches are widely used in functional ecology, from the level of individual organisms to ecosystems (Cadotte, Carscadden & Mirotchnick, 2011)
The face, thorax ventral, head ventral and abdomen ventral regions were retained in four of the five top models, which indicates that hairiness of the face and ventral regions is important for pollen deposition on A. deliciosa
We show that insect pollinator hairiness is a strong predictor of single visit pollen deposition (SVD) for the open-pollinated flower B. rapa
Summary
Trait-based approaches are widely used in functional ecology, from the level of individual organisms to ecosystems (Cadotte, Carscadden & Mirotchnick, 2011). Most animal trait-based studies quantify easy-to-measure morphological characteristics, without a mechanistic underpinning to demonstrate these ‘‘traits’’ have any influence on the ecosystem function of interest (Didham, Leather & Basset, 2016). This results in low predictive power, where trait selection lacks strong justification through explicit ecological questions (Gagic et al, 2015; Petchey & Gaston, 2006). Animal-mediated pollination is a key ecosystem function and is likely to be influenced by pollinator traits, but to date no one has identified functional traits that are simple to measure and have good predictive power. Identifying and accurately measuring key traits that drive ecosystem processes is critical as global change increasingly alters ecological communities, and subsequently, ecosystem functions worldwide
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