Post provided by Mark Wong
Throw a rock at a conference and you’ll likely hit an ecologist who examines the variation among organisms’ functional traits for one reason or another. From understanding the assembly of communities and their responses to environmental change, to the effects of biodiversity on ecosystem functions, and – well, why not – modelling the global spectrum of ecological form and function, assessments of functional diversity have quickly become the bread and butter of community, ecosystem and macro ecology.
In this blog post, Mark Wong discusses his paper ‘Including intraspecific trait variability to avoid distortion of functional diversity and ecological inference: lessons from natural assemblages’, recently published in Methods in Ecology & Evolution.
Functional traits are all the rage but terms and conditions apply
Today’s ecologists are obsessed with measuring every trait of every species, amassing colossal trait databases, and building multidimensional trait spaces on which to measure a seemingly endless array of functional diversity metrics. This is all well and good – except for one inconvenient truth: the ways we calculate functional diversity among species in communities may very well mask the important functional variability among conspecific individuals and populations.
Ecologists have sounded the alarm on the exclusive use of species mean trait values in functional diversity assessments for some time now. Reading for my DPhil in 2018, I encountered many highly cited papers which emphasised the importance of intraspecific trait variability to functional diversity, and which called for their integration in functional diversity assessments. This had me wondering just how ‘damaging’ ignoring intraspecific trait variability could be to our understanding of functional diversity patterns and ecological processes at greater scales. However, I didn’t find many papers investigating this in empirical communities as compared to simulated ones.
A collaboration across a thousand miles begins with a single email
One neat paper I read then was the description of a novel trait probability density (TPD) framework by Carlos Carmona and colleagues. The framework allowed one to probabilistically represent the trait variability among individuals in populations, populations in species, species in communities, and even beyond; all while facilitating comparisons across these ecological scales. Intrigued, I decided I’d use TPD to include intraspecific trait variability in my DPhil research on the functional diversity of grassland ant communities in Hong Kong. As I’d never met Carlos and he was some four thousand miles away in Estonia, I sent him an email about things I didn’t understand when using his newly published TPD R package.
Being the genuinely helpful and all-round amazing person that he is, Carlos not only solved my technical problems, but we also discussed my interest in comparing functional diversity patterns from ‘Classic’ methods which use only species mean trait values, to those incorporating intraspecific trait variability with TPD. As fate would have it, Carlos also had an ideal dataset for Spanish plant communities and traits which he, Cristina Rota, Francisco Azcarate and Begoña Peco, had sampled systematically at individual, population and species levels. We decided to bring this together with my data on Hong Kong ant communities. Our goal was a cross-taxa evaluation of the importance of intraspecific trait variability to functional diversity patterns and especially inferences based on these patterns.
What happens when we ignore intraspecific trait variability?
The results of our serendipitous collaboration are now published in Methods in Ecology & Evolution; our article explored different Classic and TPD methods for estimating the functional diversity of our plant and ant communities. These methods ranged from those of high resolution (including as many levels of trait variability as permitted by the data) to those of low resolution (including trait variability between species only). We asked: do the estimated values and patterns of functional diversity across communities change as we increasingly ignore intraspecific trait variability – including specific facets among-population and among-individual variability – from our calculations? And consequently, do these effects also change our pattern-based inferences of ecological processes structuring the communities, such as abiotic gradients or invasive species?
Carlos’ plants and my ants told us: YES and YES.
The main takeaway from our paper which I find most compelling was that a failure to account for intraspecific trait variability altogether can very drastically alter the relationships between functional diversity patterns and environmental factors. These relationships can be altered to the extent where linear relationships go non-linear, even generating false positive (Type I errors) or false negative (Type II errors) effects for the factors structuring the communities.
Our study therefore empirically demonstrates the importance of including intraspecific trait variability in functional diversity assessments. We also discuss how this may be reasonably done when investigators have limited trait data available (because not everyone’s a plant ecologist!).
Since our first exchange, I’ve witnessed Carlos become a father (twice!) and an Associate Professor; in turn he’s seen me complete my DPhil to earn my Dr title. We’ve learned to not only underestimate the importance of intraspecific trait variability but also the exciting research and meaningful friendships that spontaneous inquisitive emails can lead to.
To read the full study, see the Methods in Ecology and Evolution article, ‘Including intraspecific trait variability to avoid distortion of functional diversity and ecological inference: lessons from natural assemblages’ recently accepted online.