Individual‐level trait diversity concepts and indices to comprehensively describe community change in multidimensional trait space

Fontana, Simone; Petchey, Owen L.; Pomati, Francesco

doi:10.1111/1365-2435.12551

Cited by 65 publications

(136 citation statements)

References 53 publications

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“…Four indices (FRic, FDis, RaoQ and FD PG ) were significantly lower after accounting for ITV whereas FEve was higher, probably reflecting differences among indices in the weighting given to the overall range of trait values present vs. the distribution of traits within the overall range (Albert et al . ; Fontana, Petchey & Pomati ). For instance, FRic measures the volume of trait space occupied by individuals within each habitat as a proportion of that across both habitats combined (Villéger, Mason & Mouillot ).…”

Section: Discussionmentioning

confidence: 99%

Incorporating intraspecific trait variation into functional diversity: Impacts of selective logging on birds in Borneo

et al. 2017

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Summary As conservation increasingly recognizes the importance of species’ functional roles in ecosystem processes, studies are shifting away from measuring species richness towards measures that account for the functional differences between species in a community. These functional diversity (FD) indices have received much recent attention and refinement, but their greatest limitation remains their inability to incorporate information about intraspecific trait variation (ITV). We use an individual‐based model to account for ITV when calculating the functional diversity of two avian communities in Borneo; one in primary (unlogged) forest and one in selectively logged forest. We deal with the scarcity of trait data for individual species by developing a simulation approach, taking data from the literature where necessary. Using a bootstrapping procedure, we produce a range of ecologically feasible FD values taking account of ITV for five commonly used FD indices, and we quantify the confidence that can be placed in these values, using a newly developed bootstrapping method: btFD. We find that incorporating ITV significantly alters the FD values of all indices used in our models. The rank order of FD for the two communities, indicating whether diversity was higher in primary or selectively logged forest, is largely unchanged by the inclusion of ITV. However, by accounting for ITV, we are able to reveal previously unrecognized impacts of selective logging on avian functional diversity through a narrower dispersion of individuals in functional trait space in logged forest. Our results highlight the importance of incorporating ITV into measures of functional diversity, whilst our simulation approach addresses the frequently encountered difficulty of working with sparse trait data and quantifies the confidence that should be placed in such findings.

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Section: Discussionmentioning

confidence: 99%

Incorporating intraspecific trait variation into functional diversity: Impacts of selective logging on birds in Borneo

et al. 2017

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“…Although this framework is focused on defining functional rarity at the species level, it can be easily applied to a variety of taxonomic and population-level scales. For example, the recent awareness that intra-specific functional variability can have important impacts not only on local adaptation but also on community assembly and ecosystem functioning [51][52][53] has led to increased measurement of traits of individuals within species at different locations [54], as well as the development of new diversity metrics [55,56]. Our framework can be easily extended to include intra-specific variability, as functional rarity can be calculated at the individual level [48].…”

Section: Functional Rarity: a Conceptual Frameworkmentioning

confidence: 99%

Functional Rarity: The Ecology of Outliers

Violle

Thuiller

Mouquet

et al. 2017

Trends in Ecology & Evolution

310

370

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Rarity has been a central topic for conservation and evolutionary biologists with the ultimate goal of determining the species characteristics that cause extinction risk. More recently, beyond the rarity of species, the rarity of functions or functional traits, called functional rarity, has gained momentum in helping to understand the impact of biodiversity decline on ecosystem functioning. However a conceptual framework for defining and quantifying functional rarity is still lacking. Here, we introduce twelve different forms of functional rarity along gradients of species scarcity and trait distinctiveness. We then highlight the potential key role of functional rarity in the long-*

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“…Our method requires hairiness to be measured at the individual-level (Fig. S1), which makes it an ideal trait to use in new functional diversity frameworks that use trait probabilistic densities rather than trait averages (Carmona et al, 2016; Fontana et al, 2016). Combining predictive traits, such as pollinator hairiness, with new methods that amalgamate intraspecific trait variation with multidimensional functional diversity, will greatly improve the explanatory power of trait-based pollination studies.…”

Section: Discussionmentioning

confidence: 99%

Hairiness: the missing link between pollinators and pollination

Stavert

Liñán‐Cembrano

Beggs

et al. 2016

PeerJ

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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.

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Individual‐level trait diversity concepts and indices to comprehensively describe community change in multidimensional trait space

Cited by 65 publications

References 53 publications

Incorporating intraspecific trait variation into functional diversity: Impacts of selective logging on birds in Borneo

Incorporating intraspecific trait variation into functional diversity: Impacts of selective logging on birds in Borneo

Functional Rarity: The Ecology of Outliers

Hairiness: the missing link between pollinators and pollination

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