Linking Life-History Traits, Ecology, and Niche Breadth Evolution in North American Eriogonoids (Polygonaceae)

Pink (Japanese) knotweed Persicaria capitata from Wikipedia


Lynsey McInnes

Lynsey McInnes

Another micro/macro choice from me. Surprise!

I liked this paper. I thought it was a thoughtful attempt to address a specific question that is bypassed by many a macroevolutionary biologist. The authors want to tease apart whether they can explain patterns across species in niche breadth and rate of niche breadth evolution by looking below the species level (given that niche breadth is really not a good ‘species-level’ trait).

Now, bridging the micro to macroevolutionary divide might be expected to require multiple data points per species to get a measure of intraspecific variation. The authors sidestep this by using measures of climatic tolerance to characterise niche breadth, reasoning that evidence for local adaptation in plants is common and a broad niche necessarily comes about through intraspecific variation. I kind of agree, but do wonder what other ways intraspecific variability could be/might need to be quantified.

They find that perennials have higher rates of niche breadth evolution while annuals have higher rates of niche position evolution. In essence, they put this down to perennials inhabiting more variable, colder and higher environments and annuals specialising in more stable environments. Perennial species thus do better with a broad niche as there are always some adaptations floating around the species to deal with the different conditions thrown on them. Annuals on the other hand have evolutionary speed on their side to pop out a new species when needs be (so that across species niche position change is more rapid). The authors concede that some of their reasoning is (very thoughtful) conjecture although the story they build up is a convincing one.

The authors state themselves that to understand what mechanisms underlie these variations across life-history strategies needs more evidence. One place to start would be looking for confirmation of local adaptation across populations of each species and to find out the genetic mechanisms underlying this. Another would be to fill out the phylogeny to see if sampling gaps are biasing the story. From the phylogeny it looks like perenniality is pretty clustered on the tree, how clustered? And what is missing? Do the independent origins of perenniality have the same kind of niche breadth? What are the problems with using this kind of niche modelling approach? How much broader a niche could these species persist in if they had the opportunity?

I wonder what other systems this type of approach would be good for? Is variance in climate experienced within the range a good measure of intraspecific variability? It obviously captures something but how correlated is it with range size?  Have we just shifted the question of how life history strategies affect range size to how do they affect a convoluted measure of range size? This might be a good thing, but it might also be dangerous if niche breadth/climatic tolerance is not the main driver of range size variation (saying that, it probably often is).

A lot to think about.


Will Pearse

Will Pearse

This is an interesting paper; the methods are very through, and I enjoyed the focus on the evolution of intraspecific variation.

I like the idea that annuals, by hiding in the seed bank, can avoid adverse environmental conditions and this have a narrower niche breadth. The pedant in me is tempted to argue that this dependence on the seed bank will require specific adaptations and an extension of the niche, but I don’t think that’s tremendously important. If true, this hypothesis suggests that climatically stable regions (the tropics) should show less annual vs. perennial variation. I also wonder whether an annual spending longer underground has fewer effective generations and so a reduced capacity for evolution.

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The intrinsic dimensionality of plant traits and its relevance to community assembly

Daniel Laughlin. Journal of Ecology (early view). DOI: 10.1111/1365-2745.12187. The intrinsic dimensionality of plant traits and its relevance to community assembly

Plant traits, plant traits, everywhere, and plenty of root traits with which to absorb water. From Laughlin's paper.

Plant traits, plant traits, everywhere, and plenty of root traits with which to absorb water. From Laughlin’s paper.


Will Pearse

Will Pearse

I think I should read more essays, because I really enjoyed this one. I’ve been searching for good recovering-zoologist-friendly summaries of the plant trait literature and this is one. The methods were also nice, and it’s cool to see how machine learning is really finding its place as a useful tool and not just something to scare reviewers with. I’m going to talk a little bit about plant traits in general (which I’m not qualified to do), and then have a brief digression on dimensionality (which I’m also not qualified to do).

Gathering plant trait data is hard, and while Laughlin isn’t the first to point out that our view of the botanical world is biased by what we can easily gather data on, he does it very eloquently. I was at the TRY working group meeting a few months ago, and I was very struck by how hard everyone is scrambling to fill in the gaps in our trait knowledge. We know remarkably little about plant roots, and I can’t help but wonder if knowing more might get people thinking a little more about facilitation. I’ve heard all kinds of weird things about facilitation (whatever it is, I’m not certain it’s sufficient to just call it “negative competition”), and I feel the roots, and the mycorrhiza they harbour, are the key to understanding it. I’m a great fan of the leaf economic spectrum (even if the details are sparking some debate), and given the work on above-ground vs. below-ground allocation of biomass I think it’s only a short time until we start seeing root-above-ground economic spectra.

I agree entirely that we can and should reduce the dimensionality of the plant trait literature; TRY has 682 different traits when I last checked and I fail to believe they’re all completely independent. We know that niche convergence need not be convergence of traits, and finding the principle axes of variation should help us better understand the evolution of trait trade-offs. This many niche axes are also sufficient to allow co-existence of large numbers of species because there’s a lot of niche space to split among many species; this is the complex (and often chaotic) situation that allowed us to ‘solve’ the Paradox of the Plankton. Thinking in terms of a smaller number of niche axes does make things more tractable, and I do happen to think that Laughlin is right, but there is a sting in the tail of even a ‘simple’ six dimensional description of plants. If we (conservatively) assume there are only six niche axes and that species can either have low, medium, or high values along that trait axis, we have 729 (3^6) different kinds of species – or 2187 species with the 7 axes indicated on the figure at the top of this post! Discretising continuous variation like this also has its problems, but I still have a feeling that plant traits are going to remain complex for some time yet!


Lynsey McInnes

Lynsey McInnes

I wanted to read this paper this week simply because I was curious what the intrinsic dimensionality of plant traits was…I didn’t really have a feeling whether it would 3 traits or 10 or what those traits would be. So, I learnt quite a bit through reading this essay!

It looks like intrinsic dimensionality is about 5ish depending on what dataset (i.e., what traits) you look at. The general (n = 3 anyway) conclusion is you need a trait from each of the major bits of a plant (leaf, stem, root, etc.) and that within major organs, traits are correlated, bordering on redundant. This all sounds reasonable, but I’m pleased to see it documented here.

Of course, it would have been great if n could have been bigger to explore the wrapper relationship of the effect on dimensionality of the traits and species included in the tests. Presumably you might get an extra dimension if you ramp up either no. of traits or no. of species, but this could probably be anticipated and dealt with.

I know it wasn’t the subject of the essay, but how easy is it to measure these traits? The author mentions the lack of root measurements as these are (obviously) harder to measure than leaf traits for example. Is it realistic to suggest targetting them? Are there any non-root traits that could cover them (if I remember correctly, I think not really). What is the relationship of dimensionality with richness? Could species numbers cover for trait diversity? (Maybe both have asymptotic effects?). I’ve no real idea if that is a reasonable suggestion or not, I am a big fan of the idea that trait, or functional, diversity captures ecosystem processes better than species identity, but I’ve not actually thought before whether there is a simple relationship between the two (wouldn’t that be nice?).

The author alludes often to this exercise being useful for community assembly studies, especially in this time of rapid environmental change. Although (I think) we still don’t really know how stable communities are through time (transient mixes of species that happen to come together in one place vs. tightly co-evolved units), understanding how the mix of traits changes in a community through time could help reveal the answer (contingent on a ton of data being available). For instance, if just a small number of trait dimensions needs to be studied, perhaps one could extract how their trait values change through time (or through space). Does a community retain the same trait values over time for ‘optimal’ functioning? Or is a lot of change apparent? Is there turnover of species identity, but retention of trait diversity? Are there datasets available to use for these types of studies?

Exciting times.
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