What are some of the general rules for community ecology that have emerged from the functional traits research program?
So in my 2015 post on “Steering the trait bandwagon” I mostly identified gaps and shortcomings in where traits have gone since my 2006 paper you refer to (and of course several other key papers and authors advocating use of traits). I still think that every time someone publishes a paper just saying “we measured some traits on a group of species” people are at risking of thinking the trait-based approach is intellectually shallow. I also stand by most of my “steers” in that post (e.g. to get more multivariate, to get traits by environment, to work more on the individual level). But I read this question as an invitation to highlight advances or accomplishments in traits (or at least I’m going to choose to read it that way) and provide the positive side of the assessment. So some key accomplishments in the trait world:
- We are building large databases of traits, most especially plants (of which the largest are into millions of records, tens of thousands of species, and dozens of traits including BIEN and TRY but there are all kinds of regional and more specialized databases). But also macroinvertebrates, corals, fungi, lizards, butterflies, deep sea vent fauna, fish (here and here), ants (here and here), and etc. Building a database is of course a means, not an end, scientifically. But I have been impressed at the rapid explosion and quality of trait databases.They are a key step towards generality and a positive reflection on the movement to open data.
- Assembly can be better described by traits than species – Although far from the only example of this claim, I think the paper led by Julie Messier, my former graduate student, now faculty at Waterloo, is still the most powerful example of this. Look at the figure below from Messier et al 2010. The graphs represent kernel densities of a trait distribution. Left to right gives 3 sites along a gradient in Panama (North/Atlantic/wet to South/Pacific/dry). At each site, for 4-8 plots (30m x 30m) every individual was sampled for a number of traits including leaf-mass-per-area (LMA). The thin lines represent different plots (~100 m apart) at the same site. The thick line represents the average. While there is some plot-to-plot variability, it seems clear that not just the mean but the variance and skew of the trait distribution is conserved across plots within a site presumably experiencing identical climatic conditions (but varies across sites with varying climatic conditions). I find this result especially impressive as it is in the tropics and the overlap of species between plots within site is only about 13-33%. In other words, 67-87% of the species are different between plots, and yet the trait distribution is strongly conserved. If we were to take a classical species-based approach we would have to throw up our hands and say species composition is primarily just stochastic outcomes of dispersal, yet with a trait based approach we see some real ecophysiogical determinism coming in that is missed with a species approach.
- Abundance and demographic rates like mortality can be better predicted by traits than species – Closely related to #2, if traits are being “filtered” then traits must be tied to demographic processes and outcomes. Traits have been successful at predicting relative abundance of different species (Shipley 2006, Laughlin 2012), and species demographic rates (Poorter 2008, but see Yang 2018 for reasons why predicting rates for a single species out of context has real limits as also suggested in my steering traits post). Somewhat more promising as a future direction, traits are good at predicting outcomes of competition such as predicting impacts of neighbors on growth and mortality of a focal individual better than taxonomic identity or relatedness (Uriarte 2012, Fortunel 2016) and the same for coexistence mechanisms (Kraft 2015). There are many more I could have cited. Contrast that success to the success of traditional species-interaction/community-matrix approaches to predicting community dynamics outcomes such as relative abundance or effects of competition (basically close to zero). The community matrx is parameter hungry (~(n^2)/2 paramaters for n species). And the only way to parameterize is is to phenomenologically measure the nature of each pairwise interaction. Not really going to to happen. The fact that we can measure traits of individual species (in isolation – so ~ n parameters not n^2) and use them to predict the outcomes of species interactions is exciting and relatively unprecedented.
- Functional diversity is interesting and clearly separable from taxonomic diversity and relevant to ecosystem function – it has been commonplace for at least a decade now to note that we should supplement taxonomic diversity (be it richness or a measure that incorporates evenness) with phylogenetic and functional diversity. I’m not going to address phylogenetic diversity here, but I would claim that functional diversity (especially taking residuals after controlling for taxonomic diversity) has provided some really interesting and unexpected results. Lamanna 2014 showed that taxonomic and functional diversity follow taxonomic diversity in being higher in the tropics, but at a gamma or regional scale functional diversity is actually higher in temperate zones. Petchey 2007 found that functional redundancy in individual bird assemblages is lower than expected by chance, again suggesting environmental filtering might be acting but then when looked at over 20 years, functional redundancy is being lost just as fast as taxonomic richness so there is no evidence of functional redundancy buffering ecosystem functioning against species loss. Tilman 1997 showed that functional diversity and functional composition are both better than taxonomic diversity in predicting ecosystem function. And Dynamic Global Vegetation models (a key improvement over GCMs in predicting climate change) are increasingly moving to using traits (van Bodgeom 2014). Again this is just the tip of the iceberg, but it suggests that taking a functional diversity view of the world adds new information beyond species richness. Functional composition and diversity are also key to model ecosystem functioning.
- There are some recurring syndromes or axes of trait variation – understanding the diversity of 10,000,000 species is a core challenge. Finding major, repeatable axes of variation is a key tool for reducing this dimensionality. The finding of the role of body size and a fast-slow-continuum in life history has been a major advance for example. A recent (Diaz 2016) paper confirmed that in plants a whole plant and plant organ size dimension captures the most variation with much of the rest captured by a fast-slow-leaf dimension (also see Westoby 1998, Wright 2004). I am sure there are some more axes out there related to, e.g. reproduction and seeds or wood and height as well as in other organisms but I haven’t seen those wholly and decisively nailed down yet to the same degree as the first two axes I mentioned in plants.
That would be my summary of some of the key findings and results in the trait world (most but not all since 2006). For sure we have a lot of work still to do. But at a minimum, I think traits have established themselves as an approach that brings something new, different and valuable that hasn’t been there in community ecology before.
What do you think? Have traits changed or improved our understanding of ecology? Are there key advances (or papers) I left out?