Phylogenetic relatedness and the determinants of competitive outcomes

Godoy et al. 2014 Phylogenetic relatedness and the determinants of competitive outcomes. Ecology Letters 17 (7): 836-844

Figure 3 from Godoy et al. How fitness, demographic, and competitive differences vary with phylogenetic distance.

Figure 3 from Godoy et al. How fitness, demographic, and competitive differences vary with phylogenetic distance.

Will Pearse

In a fantastic follow-up to the many criticisms of the community phylogenetic approach, Godoy et al. fit a form of the Chesson framework to ecological data, and find that while fitness differences are greater among distant relatives, competitive differences are not. Being phylogenetically dissimilar did not mean that species were more likely to co-exist.

This is an excellent demonstration of a point that many have suspected for some time, but few (none?) have been able to conclusively show in a field experiment. This probably has something to do with the work involved in doing it…! Of course, that it’s been found once does not mean it’s a general pattern, but along with other work from the same authors decomposing traits into niche and fitness components, it seems empirical ecology is now matching its theoretical counterpart. Some are going to take papers such as these as the first nails in the coffin of community phylogenetics: personally, I think they open the door to a whole world of new approaches that we’ve been wanting to explore for some time.

Generating hypotheses about the kinds of traits that map onto different kinds of evolutionary processes means we can ask more sophisticated questions about evolutionary ecology. We don’t need to just stop at declaring that a trait shows ‘phylogenetic signal’, we can ask what model of evolution generated these traits, and (more importantly) how the evolution of those traits interacts with how they play out in species’ modern ecology. Indeed, that’s what many community phylogeneticists have been trying to do since the very beginning.

Now we can start asking more nuanced questions about the kinds of evolutionary models we are fitting. Measuring the traits that enable co-existence in one area is fantastic, but it’s unlikely that only the eighteen species in this study evolved in isolation. How did the surrounding flora (and interactions in other environments) affect the evolution of these interaction components? If (as the authors rightly argue) Brownian motion gives us very little predictive power for deeper phylogenetic structure, are there alternative models that might? Is it ever truly possible for competitive interactions and hierarchy to be strongly conserved, if diffuse competition among many competitors is frequent? If competitive hierarchies change over time, does it make sense to ask if a particular snapshot of them, in particular environmental conditions, is evolutionarily stable? Personally, I think it’s a good time to be a community phylogeneticist…

Lynsey McInnes

Lynsey Bunnefeld

Unlike Will, I’m not a community phylogeneticist (still not sure I buy into communities) and haven’t been following the recent developments in community phylogenetics that seem to be making it a much more robust field (see Will’s post above). Instead, I just jumped into this paper without previously ever having thought of the way you could split up species’ differences into stabilising niche- and average fitness- differences. What a good idea and what a shame that distinction wasn’t recognised long ago.

The authors then go on to see if they can untangle how these two features relate to phylogenetic distance using some nifty field experiments with 18 plant species. Again, I got overwhelmed by the fanciness of the experimental design and the work involved in it. And am happy to believe their findings that only average fitness differences show phylogenetic structure (more distant relatives have bigger differences) and that increased variance over longer phylogenetic distances mean that communities as a whole don’t show phylogenetic structure.

Being the macro person I am, I wonder how these results generalise to other communities and how you might go about finding out without having to conduct an epic field experiment every time you want to try. I think these authors have already published theory for these ideas so it is definitely time to get out of the computer and into the community (haha) but just how might you do it? Early community phylogeneticists went to town fitting models to species presence/absence in areas and giant phylogenies, clearly we need to be more nuanced than that. Could we go a roundabout way and find the traits that underlie the average fitness and the stabilising niche differences and use these in a similar framework to Godoy et al. advocate here? Has this been done already?

The authors find that variance increases with increasing phylogenetic distance, does this mean that clear patterns will not be found as we zoom out from narrowly defined communities? Is this OK?

Will sees these developments as a kind of new dawn for community phylogenetics. I just wonder whether the new dawn is not just tearing the field apart in increasingly nuanced ways. I for one am not confident that we can use phylogeny to robustly predict how communities will respond to change or use snapshots of current communities to work out how they got put together. At least not without a lot of knowledge of the system in hand and then who needs these phylogenetic metrics anyway?


A mean field model for competition: from neutral ecology to the Red Queen

O’Dwyer & Chisholm 2014 A mean field model for competition: from neutral ecology to the Red Queen. Ecology Letters 17: 961-969

I'm reliably informed that this is actually quite simple to understand! Equation 2 from O'Dwyer & Chisholm.

I’m reliably informed that this is actually quite simple to understand! Equation 2 from O’Dwyer & Chisholm.

Will Pearse

To spoil the punch-line, I’m not sure I completely agree that the model in this paper is biological defensible, but I’m quite certain this is a very important contribution. The authors have found a way to incorporate species differences into neutral theory: the most recently speciated species out-competes all others, and as a consequence phylogenetic branching times become more reasonable. Much ink has been spent suggesting Neutral Theory will form the building blocks of models that incorporate species differences, and this (finally!) is an extremely important piece of such work. My main concern is that I think, to be biologically defensible, there has to be some kind of inheritance of fitness from the new species’ ancestor. The only way I can see the youngest species being the best is if the driving force of biology is pathogens – the authors point towards this, and somewhere Ricklefs is jumping for joy – but I just can’t see it. To me, this would require that we change (again) the scope of Neutral models from covering species within the same guild to covering the same ‘pathological guild’. Moreover, I find it hard to believe that each speciation event is coupled with a magic trait that pathogens must evolve, from scratch. Surely a species in a large clade, presumably with an equally large body of pathogens, is even less likely to have such a trait evolve, and we have yet another way for diversity-dependence to rear its head. That said, all is certainly not lost, and this is an (extremely impressive) start. If a similar model could have multiple guilds nested within itself, and allow some degree of exchange between the guilds, I would have little trouble getting behind it. Using diffuse competition to approximate the competitive hierarchy was a wonderful moment in the paper, and it’s fantastic to see an argument used to defend Neutral Theory extending, not defending, it. If we can use these kind of approximations to bring even more niche-based concepts into Neutral Theory, things are looking up!

Lynsey McInnes

Lynsey Bunnefeld

I am still on the fence about this paper. On the one hand, I admire how they have taken neutral theory and changed it a bit in order to produce predictions that more closely match what we see in reality (specifically, they assume new species are fitter than all older species and that leads to more realistic distributions of species ages than the hardcore neutral theory where all individuals are equivalent). This is impressive. On the other hand, this is a bit of a weird tweak to make and doesn’t really seem to be biologically defensible, at least not generally.

I like the idea of neutral theory. I like its simplicity and the fact that it is remarkably good at predicting a lot of recurrent patterns we see in nature. I even like the way it sometimes fails and I really like that it can really irritate people. It is fun to watch people get stressed out about it. I agree that if it is to continue to have relevance, it needs to be continually scrutinised and tweaks applied and tested. This paper provides a remarkably simple and tractable tweak to deal with one of the outstanding issues with neutral theory – that is tends to predict unrealistically long species ages. By making new species fitter than older ones, the authors are able to purge communities of older species more quickly and so reproduce patterns that more closely match those observed in nature. Neat.

But wait? Are new species typically fitter than old ones? The authors’ argument for yes appears to hinge on the new species being free, or at least relatively more free, of nasties that could hold them back. I’m no expert, but my intuition is that not all, or indeed many, new species are ‘free’ in this way. Indeed, don’t most species come about through divergence in geographically or ecologically distinct arenas and might be really quite similar to their close relatives apart from in a key few traits (and not even that sometimes). Indeed, there seems to be mixed evidence at best that you shed the majority of your parasites upon speciation.

OK, but if the assumptions of this model sit uneasily, what other tweaks might be made to neutral theory to reign in unrealistically old species ages? At this is when the authors’ ideas become harder to put down. They have recognised that you need to find something that ‘gets rid’ of older species and their idea seems at least a bit better than species just having an ‘intrinsic’ life span (cycle of life style). An idea that has been bandied about, but with lots of quite robust refutation too. What else might do it? Some kind of slowing down of adaptation to changing environment? Some kind of competitive density effect? Some kind of lag in competitive interactions (your enemies catch up with you and get rid of you?). None of these sound particularly promising.

And so, while I might not agree with the authors’ model I’m pretty happy that people are producing such models and refining and refuting things further. One day we might be able to figure out where these recurrent patterns in biodiversity are coming from and the relative importance of niche and neutral processes. We won’t get there without trying.

Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory

JP Grime. The American Naturalist 111(982): 1169-1194. Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory

I find your lack of competitive ability disturbing. Grime's CSR triangle (main), with his estimates of where trees (top-left) and annual herbs (top-right) might lie within it.    Taken from figures 2 and 3 from Grime (1977).

I find your lack of competitive ability disturbing. Grime’s CSR triangle (main), with his estimates of where trees (top-left) and annual herbs (top-right) might lie within it. Taken from figures 2 and 3 from Grime (1977).

Will Pearse

Will Pearse

I’m a zoologist who somehow keeps looking at plants, and this paper is probably the best demonstration of how plant and animal ecologists really do seem to think differently (in my mind, at least). Grime has a section about animals and fungi at the end, but all of this is clearly written by a plant person – and is all the better for that.

There’s a growing feeling in plant trait ecology that plant traits can be grouped together along some economic spectrum (reflecting pay-back of nutritional investment), be that of leaves or wood. Recently, Peter Reich has argued that all of these can be considered as part of the same system, where plants are either fast-adapted or slow-adapted. I don’t want to point out connections between these ideas and Grime’s CSR strategies, but instead draw attention to how plant functional trait studies have somewhat lost their way. Grime makes it quite clear that position along each of his spectra depends on plant traits, but that there’s no one-to-one matching of trait onto CSR strategy. I feel as thought his general message has been lost among papers pointing out how different species have different adaptation to drought, and how SLA or xylem diameter has changed, as if those particular traits defined those species’ niche dimensions. Convergence means that there are many ways to skin a cat, and there are many ways to be ruderal – individual traits that we have decided to measure do not define species.

I fee Grime implies that there’s very little difference between being in a nutrient-poor or stressful environment based on the species around you or because the environment is inherently that way. He argues an area can be nutrient-poor because all of your neighbours have soaked up all the nutrients and won’t let go. If (as he argues) some species have evolved to maximise nutrient retention, not rate of absorption, this becomes doubly important. I’m constantly referring to abiotic and biotic drivers, and on second thought there’s really very little reason to distinguish between them if they have the same effect – shade is shade, no matter what the cause.

At times I felt like Grime was implying that much of plant traits come from the environment they’re exposed to – I’m not sure things are always as plastic as some would believe, but I certainly agree plants can change. Most importantly, we shouldn’t be teleological in assuming that observed shifts in species’ traits reflect the thing we’re interested in – what may seem like an adaptation to drought may just be a consequence of altered nutrient turnover rates, and without some kind of breeding experiment I don’t think we could ever disentangle the two.

Lynsey McInnes

Lynsey McInnes

I let Will pick the paper this week, forgetting that he was trying to teach himself about plants. He might be a zoologist learning about plants now and again, but I’m just a bad mathematician/pattern seeker masquerading as a biologist. I found this paper tough going, mostly because I haven’t really thought all that much about the ins and outs of actual individual plants making it in their stressful /disturbed/competitive environments. So, I learnt a lot while reading this and would certainly recommend the paper to budding ecologists interested in a framework for classifying their different plant species based on how they might do in different environments.

Once I got to the end of the paper, I realised it, in fact, did fit into my pattern seeking world view (Grime was trying to squeeze plants into a triangle with three distinct lifestyles at its vertices, after all). But only if you are willing to really work for your patterns. Counting species is easy, but disentangling how many of each kind of species is already one step harder. Especially when, of course, the three strategies form a triangle rather than three distinct boxes.

I am typing as I think here, but I just wonder how macroecology, and its resulting insights, would change if we stopped counting species and really tried to count function. Sure, there have been macroecological studies of functional diversity, genetic diversity, body size, but all still very much tied to species counts. I wonder if we will ever let go of the notion of a species as this magic unit. But perhaps it is a magic unit and function/type/etc. still ultimately harks back to species.

I really don’t know if broad-scale analyses need finer divisions than species counts, but, as Will states above, macro people obsess over the relative importance of biotic and abiotic drivers of diversity patterns and thinking in terms of Grime’s classification, or some other similarly nuanced one,might actually help us spend work out what the biotic drivers might be or rather how they might work.

Ok, this is a real ramble now. In short, I appreciated all that I learnt in this paper and it underlined that we macro people have to get more smart in what we measure if we really mean it when we say we want to know how diversity is ‘generated & maintained’ (& turns over).

Mechanisms of maintenance of species diversity

Peter Chesson. Annual Reviews in Ecology, Evolution, and Systematics 31: 343-366. Mechanisms of maintenance of species diversity

Species' relative abundances fluctuating over time under various models of coexistence. If you just want to think of it as a pretty picture, that's probably OK too. Figure 2 from Chesson (2000).

Species’ relative abundances fluctuating over time under various models of coexistence. If you just want to think of it as a pretty picture, that’s probably OK too; we won’t tell anyone. Figure 2 from Chesson (2000).

Will Pearse

Will Pearse

I’m shocked how many people consider this a classic that “must be read” and yet haven’t read it themselves because it contains “too much math”. I don’t care if you haven’t read this (I’ve not read every paper most people consider a classic), and I think focusing on what people haven’t done is pointless, but I think this is a very readable coverage of what is (otherwise) very difficult math. I do find this field very math-heavy, but with only 9 equations (~1 per 3 pages) this is a really insightful review that for novices like me is helpful.

Chesson very nicely re-phrases coexistence around the ratio of species’ competitive differences and their niche differences; if species are sufficiently different, or compete sufficiently little, they will coexist. This came up an awful lot in the community phylogenetic talks I attended at ESA last year, in part because it torpedoes the assumption made by many that closely related species are more similar to one-another and that’s all that matters for co-existence. I manically circled the idea that species’ niches have an effect (e.g., reducing resources) and a response (e.g., ability to grow given certain resources). Chesson seems desperate for us to stop thinking of a niche as something that is solely a function of a species itself: it’s a function of the context within which we see the species, and that is always shifting. Even when we say a species’ niche involves competing with other species, we’re still missing the key component that the species is using up resources, thus warping the effect-response space that all the species around it experience and themselves modify.

Which sounds a lot like I’m saying the paper is about non-linearities and changes through time; it isn’t, and Chesson very artfully points out that a lot of insight can still be had by setting up simple models in well-considered ways. It is pretty dismissive of Neutral dynamics (…although it was written in 2000!) and the take-home from the section/paragraph “nonequilibrium coexistence” could be paraphrased as “stop using this unhelpful phrase”. I was particularly struck by how Chesson viewed the importance of Neutral Theory for exploring biogeographical dynamics; more than a decade later we’re starting to do this, and we’re even having discussions of how species can evolve, under neutral dynamics, to not be neutral today. This opens a whole can of worms as to what we can usefully call a N/neutral model, but more importantly helps us unify questions at a number of different levels of ecology. Which is a good thing!

Much of what’s in this paper is probably uncontroversial to a community ecologist (right?), but I think remarkably little of it has found its way into the mainstream evolutionary biology literature. I find that interesting because I’m often surprised by how much evolutionary biologists keep track of what ecologists are doing. I can’t think of any serious modelling studies where species’ effect and response traits are seriously modelled across a phylogeny (please correct me!), and I wonder what we would find if we looked.

Lynsey McInnes

Lynsey McInnes

I can’t imagine I am the only PEGE person to have cited this paper on the mechanisms of species’ coexistence without having carefully read it? Its been cited 1694 times! So, choosing it for this week’s PEGE was a great excuse to actually sit down and use some train time to read it through and through.

Now, I have always cited this paper when writing about macroevolution and the idea of equilibrium species numbers and turnover in ‘evolutionary’ time. Oops. Chesson sidelines this view of species’ coexistence early on in his paper and instead focuses throughout on ecological/contemporary notions of species’ coexistence in a – relevantly sized, more or less closed – patch. No matter, I am convinced that most if not all of what he talks about is also relevant or at least interesting for people working at longer timescales.

The problem perhaps is that too many people have jumped on the bandwagon of these ideas being relevant to understanding the build up and maintenance of species diversity that we have become blinkered to the possibility that ecological limits might not be constraining diversity at broad (temporal and spatial) scales. It feels so easy and so neat to extrapolate Chesson’s (and others) equations and explanations of how populations of species manage to stably coexist with each other (a delicate balancing act of getting more intraspecific than interspecific competition, with divergence along at least one relevant niche axis) to how ENTIRE species diversify in the presence of one another until their niche space (in physical or ‘hyper’ space) is full. It is also really easy to obtain patterns, for example in phylogenies, that agree with the idea of diversification slowing as niches fill up.

I have a feeling we are on the cusp of entering a new phase of macroevolutionary analyses where we break ranks with trying to match one for one ecological and evolutionary phenomena. I think it is already much more common to think of what units within species evolve (populations/metapopulations depending on gene flow) and also to think of niches as much more labile (e.g., what about niche construction or extent of niche breadth). Similarly, in both macroecology and macroevolution, biotic interactions are moving from postscript to centre stage as more data becomes available to address the effects of biotic interactions on the patterns we can observe and experimental systems are emerging where these effects can be empirically manipulated.

Turns out no matter how hard I try to leave it behind, I am still a macro-scale biologist at heart and it is fun to pull out the macro-scale implications of more or less any paper that I read.

The loss of indirect interactions leads to cascading extinctions of carnivores

Sanders et al. The loss of indirect interactions leads to cascading extinctions  of carnivores Ecology Letters (2013) 16: 664–669

The population-consumption-environment nexus. Apparently. From

Broad bean aphids on a broad bean. From Wikipedia.

Regan Early

Regan Early

I chose this paper because I’m moving from biogeography and species distribution modelling into experimental research into the fundamental processes underlying species distributions. Well, really I want to do both at the same time, and an experimental system like this seems ideal to ask how biotic interactions might affect species geographic distributions.

My first instinct is that these experiments seem so elegant, and simple, that I don’t quite understand why they haven’t been done long ago. Perhaps someone with a stronger background in experimental ecology can help me out here.

The authors convinced me that this paper is important because carnivore extinctions are important. First carnivores are disproportionately likely to go extinct – their (usually) larger body size and low abundance make it particularly hard for them to wait out disturbances as can species lower down the food web. Second, carnivore extinctions can exert complex effects down the food web, which bounce back and result in even more complex effects back up the food web, i.e. on other top predators. To test these ideas out, the authors made toy communities consisting of a food plant, three aphid species, and three parasitoid wasp species, each of which specialized on a particular aphid species. In three sets of these communities one of the species of wasps was culled, and in the fourth set of communities all species were allowed to remain. What happened was that for two of the wasp species, their removal led to reduced persistence of one or more of the other wasp species. So we might assume that the reduction of one carnivore caused its aphid prey to grow in numbers, outcompeting the aphids on which another wasp species relies, and causing the bounce-back extinction effect at high trophic levels, right? It sounds like a text book example. Except that’s not what happened. Only one of the three aphid species showed a clear decline following the extinction of a wasp predating their competitor species, and no aphid species went extinct. The competitor species did increase in numbers though, and it seems that this confused the predators of the other aphids. The wasps were now so overwhelmed by the weird smells and evasive manoeuvers of all the aphids that they couldn’t eat, that their spidery-sense couldn’t find the aphids they did want to eat (this is a metaphor – I am not actually confusing my arthropods).

For me, the wider upshot of this is that as communities lose species, we should expect ripple effects that are really hard to predict using standard techniques of population growth and per capita attack rates. In this case extinction seemed to be mediated by anti-predator behaviour. To my knowledge, we don’t have a good framework for predicting which species might be susceptible to these effects. The authors argue that it should be common for attack rates to be reduced when predators are faced with and confused by too much prey that they can’t actually eat . But they don’t cite a wealth of evidence for this. It seems like a cross-taxonomic review of this phenomenon is in order, as a step towards developing tools to quantitatively predict its effects. I’m certainly prepared to be convinced that indirectly-driven secondary extinctions deserve our attention. This is particularly the case in marine systems where top predators are regularly harvested and prey species display complex behavioural adjustments when their predators disappear.

Finally all predators here were specialists and, as the authors point out, a generalist predator might help smooth out big differences in population densities of different prey species. They argue that this means the loss of biodiversity will increase susceptibility to extinction cascades. This may well be correct, but the argument seems a bit disingenuous – retaining a few generalist species could prevent secondary extinctions. Happily, for biodiversity’s sake, complexity does seem to make biological systems more resilient (Loreau, Naeem et al. 2001, Reusch, Ehlers et al. 2005). The challenge will be to evaluate why and how by approximating this phenomenon with microcosms, where more complexity means more noise and less signal.

Lynsey McInnes

Lynsey McInnes

What a neat paper. I’ve said it before, I’m a big fan of micro/mesocosm experiments. They seem so elegant and useful, a step up from computer simulations, but easier to manage than field experiments. I agree with Regan that it is surprising this kind of thing has not been done before; seems like an important, yet tractable question. That the authors find it is more complicated than simply host extinction that causes the ripple effects of extinction on other parasitoid species underlines we have a long way to go before being able to robustly predict the effects of single extinctions on ecological communities.

The authors acknowledge that a generalist predator might smooth out these effects, and I’d be interested to see if they do. I imagine there is only so much a generalist can smooth and extinctions of specialists (of which there are many) will eventually impact communities in the way demonstrated here. Seems like there is plenty of studies showing this kind of effect (that diversity itself aids resilience).

I guess what I’d like to see now is to go one step back from an experiment/question like this one and see an attempt to work out how to predict which predators or prey are vulnerable to extinction ( here the authors have identified members of higher trophic levels, but surely not all members?). The next step would be to see whether an extinction can be corrected for by a generalist or other specialist and for how long/how broadly. When does a community or at least a specific trophic level become so homogenised that it falls apart? How much does diversity per se matter? I know this has been studied before, but am not sure how general the conclusions have been or whether specific traits or scenarios have been identified as more or less likely to lead to collapse. An approach such an Laughlin’s axes of functional traits might be helpful in this regard.

I had it hammered home to melast week that a field element to all ecology is necessary for it to be meaningful. I’ve chosen to take this to mean that an exchange between theory, models, field data and experiments is necessary for the best kinds of ecological insights. I take this paper as a good example of this, clear question, well tested, conclusions related to but distinct to expectations and with plenty of fodor for future investigations. Oh yes, and with an applied angle too. Nice.

Ecological character displacement: glass half full or half empty?

Yoel E. Stuart and Jonathan B. Losos. Trends in Ecology and Evolution 28(7): 402-408. DOI:10.1016/j.tree.2013.02.014. Ecological character displacement: glass half full or half empty?

A glass for the eternal optimist - for sale from ThinkGeek

A glass for the eternal optimist – for sale from ThinkGeek

Will Pearse

Will Pearse

I think I’m not the only one with a slight science-crush on Jonathan Losos, and it’s papers like this that do it. Short, sharp, and to the point. The authors argue that tests of ecological character displacement haven’t been as strict as they should have been, and judge case studies according to the criteria the field itself set.

Let’s briefly cover obvious potential gotchas. These six criteria are well-known (>450 citations, and I’d heard of them), but they’re probably not the only criteria and it might be unfair to judge a field by its adherence to one paper’s suggestion. That said, while you might be able to think of some more (please chime in!), I think they’re all pretty fair and I’d be surprised to receive hate-mail about how dreadful the criteria are.

I think it might be worth reflecting on why we’ve been publishing ever-more-exciting sounding examples of character displacement, instead of actually examining whether the examples we have are definitely character displacement. Cynically, I think we all prefer (and fund) nice shiny new example that look great on the cover of Nature, not the boring follow-ups that fill in the (necessary) details. What’s worse, I think we’re all guilty (to some extent) of confirmation bias, and maybe we don’t want to look too carefully at systems that have earned us front-covers of journals in case we find something we don’t want to see.

But back to the biology. There’s a reason figure 3 shows that the least-confirmed criterion is demonstrated competition in nature: it requires ecological data and ecological fieldwork, both things that evolutionary biologists would probably rather not be doing. The last few decades have seen some amazing increases in statistical firepower in evolutionary biology, in part because we have only so much data and we must soak up every ounce of signal we can. However, ecological data isn’t limited in the same way, and I (and others) seem to think that ecological experiments might be an excellent way to improve our understanding of evolution.

Lynsey McInnes

Lynsey McInnes

It’s hard to argue with the conclusions of this paper. Thoughtful, thorough and interesting, it’s a plea to be a bit less lax when purporting to find evidence for instances or the prevalence of ecological character displacement (ECD). ECD -such a satisfying idea, yet difficult to conclusively demonstrate. Schluter and Mcphail’s six criteria provide a comprehensive ticklist to complete, and appear exceedingly difficult to meet (without a shitload of effort).

But what is the appeal of ECD? It’s an exciting phenomenon, bridging ecology and evolution and providing an interesting explanation for divergence. More interesting, say, than adaptation to different abiotic environments or just some other non-adaptive mechanism of divergence.

And yet maybe ECD has been elevated to too high a status. Maybe it is just one interesting mechanism of adaptive divergence, alongside apparent competition or haphazard adaptation to available niches, or some other mechanism and it has been credited with undue (and certainly undemonstrated) importance?

Anoher thing I noticed: studies that meet all six criteria are from well studied systems, sticklebacks, finches, anoles, etc. If other studies had similar amounts of time devoted to them would the other criteria have been met? I didn’t check whether not meeting them equated to them not having been tested for or them actually failing to be met?

The authors highlight the idea that climate change and invasive species are now providing great conditions to witness evolution in real time and thus to test for instances of ECD, as novel communities are brought together providing opportunities or competition for resources and character displacement. Indeed this seems like an opportunity too good to miss, but will nonetheless require careful delineation of what responses are expected and high levels of study to dismiss alternative mechanisms.

I also wonder how ECD fits in with the current trend to look for niche conservatism and/or niche evolution in every clade of organisms. If a clade shows niche conservatism along some environmental axis, do they often also show ECD along some complementary axis? Perhaps we will be understand diversification if researchers in the different camps talked more to one another and there was a better integration of the potential effects of various abiotic and biotic factors.

Mycorrhizas in the Central European flora: relationships with plant life history traits and ecology

Stefan Hempel et al., 2013. Ecology 94(6): 1389-1399. DOI:10.1890/12-1700.1. Mycorrhizas in the Central European flora: relationships with plant life history traits and ecology

I'm reliably informed there are some mycorrhizae in this photo...

I’m reliably informed there are some mycorrhizae in this photo…

Will Pearse

Aaron David

One of the overarching goals in ecology is to understand the distributions of species and how interacting species shape these distributions. In the world of plant-symbiont interactions, one ongoing question is when is it advantageous to have a symbiont? Hempel et al. compile a dataset of Central European plants and their mycorrhizal associations in order to address several ecological hypotheses. Hempel et al. classify plants as obligate (OM), facultative (FM), or non-mycorrhizal (NM), and ask whether certain types of plants are more associated with various life-history traits (ie. life-form, life-span, pollination, etc.) or environments. The authors find support that different mycorrhizal statuses are over/underrepresented in with different traits and environments. The paper provides strong evidence that mycorrhizal associations may influence plant distributions, and that the benefit of such associations is very much environment dependent. Those such patterns have been shown for individual plant species, Hempel et al. show the generality of this pattern using a large set of plant species.

The authors tackle the exciting question of when it is advantageous to form mycorrhizal associations. For instance, they report that OM plants are found in higher than expected abundance with low soil acidity, while FM plants are found in higher abundance with high soil acidity (NM abundance wasn’t affected by acidity). This result was somewhat puzzling to me, as I would have expected the NM plants to be found with the high soil acidity and the FM to be unaffected. This could suggest that while some plants are able to adjust their associations in different environments, this may not be a general rule for FM plants. The authors define FM plants as those that can form a mycorrhizal association but are not always found with one. Therefore it’s possible that the FM plants as a whole might be composed of NM plants with the occasional mycorrhizal association. It would be interesting to see the FM group split into more definitive categories.

As a fungal ecologist, I found this paper provided interesting insights towards questions of fungal distributions. One of the burgeoning areas in fungal ecology is understanding the distributions of mycorrhizal associations (see the work of Peter Kennedy). Hempel et al.’s results suggest to me that these limitations to mycorrhizae distributions could arise from local environmental conditions or host plant distributions. Of course as the author’s note, it’s not necessarily clear which symbiont is limiting the other. One way to test this idea would be to overlay maps of mycorrhizae distributions with those of plant distributions. Environmental sampling of soil can be used to get a broader picture of mycorrhizae distributions, since many may live as saprobes in addition to being symbionts, though it’s likely the authors could generate a similar distribution map using their available data. Understanding both sides of symbiont distribution would more fully address how species are limited.

Will Pearse

Will Pearse

I’m no mycologist (for what it’s worth I love eating them), but I still thought this was an interesting paper. Literature reviews like this, where massive databases that are going to be of use to future scientists are just thrown out for all to enjoy, are exactly what science should be about. Hurrah.

I think the conclusions of this paper are sound, but I’m going to draw attention to two things just to be picky. Firstly, I have been brought up to think that the phylogenetic corrections employed here should be avoided (listen to Rob Freckleton please). This is a very touchy subject (I’ve heard of people bursting into tears over it!), but in brief the authors create eigenvectors that represent the phylogeny, and then by including them in their analyses hope to correct for phylogeny. A similar approach is used in spatial analyses, but for both it’s hard to know how many eigenvectors is ‘sufficient’, and it’s always unclear to me why you wouldn’t just other methods that directly incorporate the phylogenetic variance-covariance matrix you’re making eigenvectors to describe. Phew. Got that off my chest. Secondly, I wonder what effect the publication bias (that the authors find) will have on these results, particularly as the results are in agreement with what we might expect.

However, as I say, I think the results are pretty sound, and so I wonder whether we could model the co-evolution of plant and fungi. Indeed, there are some very neat new methods (we covered one recently) that examine these questions. More specifically, I wonder if the evolution of a tight association with mycorrhizae would allow a clade to break away from its close relatives and suddenly radiate out into as-yet unexplored habitats and niches. Equally, there could be links between mycorrhizal diversity and plant associations, although I’m almost certain this has already been looked at, and defining fungal species is hard (I think!). I’d quite like to hear from more fungus people!

Predicting ecosystem stability from community composition and biodiversity

de Mazancourt et al. (2013). Ecology Letters 16(5): 617-625. DOI:10.1111/ele.12088. Predicting ecosystem stability from community composition and biodiversity

Decomposing variation in community structure is… exactly as difficult as you would expect (taken from de Mazancourt et al.)

Will Pearse

Will Pearse

I’ve lost track of how many papers have tried to put forward a new way to understand ecosystem stability. I was drawn to this paper because it develops a novel conceptual framework that requires no more data than we already have, yet has greater explanatory power than other methods. The math is better, and so the model is better.

de Mazancourt et al. use data on individual species to predict what might seem like an abstract component of ecosystems – the coefficient of variation of community biomass. They’re not just predicting biomass or community composition, rather the stability of that composition over time. You’ve probably noticed I’m always desperate to link species’ ecology with how those species evolved; I wonder what the evolution of synchrony of environmental responses looks like. Do species that have coexisted for millions of years tend to be more synchronised? Or do they respond differently, and by responding differently ensure stable coexistence because they are occupying different niches (which reminds me of last week’s diversification limits paper)?

A fair bit of space is taken up with mechanisms by which observational error (which is an important component of their model) could have a biological interpretation. I’m not sure I quite follow, but I would be interested to know what effect intraspecific variation (which might be viewed as ‘error’) could have on all this. Intraspecific variation is a real (if, in my opinion, small) source of variation, and we might expect it to play a greater role in species that are more prevalent within a community (there are more of them, and so more opportunity for variation).

Finally, it is almost unbelievable that they were able to explain more than 70% of variation in the Texas dataset. So, seeing as how they’ve done unbelievably well in some datasets, and just plain-old-fashioned-very-well in others, why is there this variation? What is it about Texas that is so amenable to this method, and what makes Jena so different? I have literally no idea, and would be very grateful for ideas!

Lynsey McInnes

Lynsey McInnes

I told Will the paper I had chosen was too hard (what do you think – check it out here) and he came back with this one! Much harder! Although, so neat. I think I more or less get it. The authors set out to develop new theory as to why we ecosystems are so often more stable when they are more species rich. They neatly set out the conundrum of increasing richness stabilizing total community biomass, but at the same time destabilizing individual species abundances. Why does stabilization win out in most ecosystems?

The author list comprises a distinguished group of researchers working in this field and they bring together theory with four amazing time-series datasets. They are all set to make progress. And they do!  Basically (I believe) they find that stability is obtained through three distinct, but of course interacting, mechanisms: and I paraphrase, in more diverse communities you get a nicely complementary set of species that response asynchronously to environmental fluctuations so there is less chance of community collapse; in more diverse communities demographic stochasticity is weakened so you don’t get crashes of individual species; and finally more diverse communities, in effect, homogenize the intrinsic heterogeneity of an area through the provision of a set of species that altogether occupy all available ‘niches.’

The neat thing about this paper is that all of these mechanisms have been floating around in the literature already and have now been brought together into a single model and that model is verified with four independent empirical studies. The authors provide visually satisfying path diagrams to show how one gets from species richness to observed coefficient of variation of community biomass through each of the above mechanisms and they show the strength and direction of each effect.

Although this paper was a bit of dive back in time to one or two of my undergraduate lectures on overyielding and the insurance hypothesis, I did appreciate this paper and was thankful that it was well-written and well-explained. So many people work on elements of this puzzle, particularly motivated by curbing biodiversity loss into the future, but I think it’s grand projects like these – that set the situation up in a coherent framework – that might be most helpful in really demonstrating why and how diversity is beneficial to ecosystem stability. I imagine the authors’ heads are already teeming with next steps: climate change, evolutionary responses, invasive species, etc. One might want to know both how perturbing a system affects stability, but also if the relationship between diversity and stability stays the same during and post perturbation.

Is regional species diversity bounded or unbounded?

Howard V. Cornell, 2013. Biological Reviews 88(1): 140-165. DOI:10.1111/j.1469-185X.2012.00245.x. Is regional species diversity bounded or unbounded?

This post is PEGE’s contribution to the first PEGE/EvoBio journal clubs crossover. Add your comments to the bottom of this post and then come and join us with the guys over at EB-JC ( next Monday (May 13th, 4:30p ET) to discuss things further over video chat.

EB-JC works a bit differently from us so we are keen to join forces and see what happens.

Is speciation rate bounded, unbounded, or... sort of both?

Is speciation rate bounded, unbounded, or… sort of both? (from Cornell 2013)

Will Pearse

Will Pearse

This paper is a brave attempt to reconcile the debate over what limits diversity through evolutionary time. Cornell’s ‘damped increase hypothesis’ is a compromise between a constant (unbounded) rate of speciation and one where clades have a (bounded) carrying capacity determined by ecological interactions. He acknowledges that diversity tends to increase through time, but this increase can be tempered by ecology; those looking for fireworks should look elsewhere (go read ‘that’ Wiens paper), because this is an attempt to reconcile and move forward.

It’s easy(ish) to derive models of evolutionary diversification, the problem is finding reliable data to validate them. You can’t sequence what isn’t here, so molecular phylogenies can’t incorporate extinct species, while the fossil record has biased sampling and makes it difficult to distinguish among species and higher taxonomic groups. Moreover, distinguishing between a clade becoming more diverse because of increased speciation or decreased extinction would be hard even with perfect data. Despite a number of really cool methods (I like these), I sometimes worry we may never be able to sort this mess out.

Much of this paper hinges on whether niche space ever gets filled. If species can fill up niche space, then it’s reasonable to expect that competitive effects would limit diversification, and Cornell’s first conclusion is that we need more experimental tests of whether these kinds of competitive effects exist. That’s not to say we need more research on competition – we have decades of that in ecology – but we need more explicit tests in extant clades that biogeographers are examining. We can’t turn back the clock, but we can validate the assumptions of our models in the present where we’re not data-limited. Now that is eco-evolutionary modelling!

Cornell spends a good deal of time discussing the importance of migration on clade dynamics, and species moving into an area and occupying niches is a rather thorny problem. However, I’m just not sure we’re ever going to be able to handle this; after decades of work, we’re only just beginning to understand how we can model species’ distributions in the present day, and attempting to do that using only biased fossil distributions for all of evolutionary time sounds like an incredibly tall order. Perhaps one thing we could do is look for correlated extinctions/speciations in the fossil record. Imagine a new species has just evolved that occupies a new kind of niche; if we assume it spreads essentially instantaneously in evolutionary time, any slow-down in other clades’ diversification rates should be immediately detectable.

Lynsey McInnes

Lynsey McInnes

This paper has been in my to read pile since I spotted it sometime last year. It probably remained there because it’s long, dense and comprehensive and takes more than a commuter train ride to get through. So when Rafael Maia over at Evo Bio journal club challenged Will and I to find a super cool paper on the geography of speciation, we decided to go with this one as it more or less covers ALL super cool papers on the geography of speciation ever published. So, thanks Howard Cornell for summarized this research field for us and providing us with plenty of food for thought for our first EB/PEGE journal club crossover.

For those of you who know me/have read my posts here at the site, you can guess that I chose this one and that it appeals to my interest in understanding the spatial nature of diversification. First, a note about the style of the paper. I really enjoyed reading it, and managed the whole thing in a single sitting and I think that is down to Cornell’s extremely clear writing style and his total command of the subject he is writing about. Wow. I was also impressed with his ability to navigate through a field that has become quite contentious in recent years; he managed to extract relevant points from a suite of Rabosky & Wiens papers without explicitly acknowledging the animosity apparent between these two camps. In fact, he elegantly concludes that regional diversity is, in effect, both bounded and unbounded and puts forward the damped increase hypothesis to cover this inclusive idea. Hoorah.

Enough rambling, what has Cornell left us to talk about?

First, I really liked his repeated emphasis on taxonomic scale. By this, he meant the conclusions we reach on the diversification of a clade will dependent on the breadth of diversity found within the clade (i.e., a subclade of mammals, a clade restricted to a single region, a clade found in a region with ecologically-similar species from different clades, a clade that has newly-colonised an area, and vice versa). I think this is an underappreciated point within macroevolution and one that deserves more explicit treatment in the future. If we are using a phylogeny to understand diversification of a group, we want to use a well-defined monophyletic clade, maybe we even want to compare two or more than two monophyletic clades. This is fine and admirable, but when doing so, we have to remember that the clade does not exist in isolation (ecologically-(dis)similar species probably occupy the same area, the clade probably included additional taxa that have now gone extinct, the size and nature of the area it currently occupies have probably changed substantially since the origin of the clade, and so and so on). If we really, really want to understand how clades diversify, we have to try really, really hard to account for at least some of the above. At the very least we have to circumscribe what we are trying to understand (How an area became populated? How a clade diversified? How extrinsic/intrinsic traits shape diversity/diversification?)

Years ago, I remember Joaquin Hortal – community ecologist extraordinaire – scoff in the face of the idea of ecological limits to diversity. His reasoning was that he knew of no system that was totally full, there was always scope to squeeze in new species if only the new species could be transported to the area in question. I kinda believed him, but somehow decided that he was talking at some kind of narrower scale than me, that at the continental scale or global scale of entire clade (what is an entire clade?!?!), limits could be reached. I think Cornell’s paper is the first I have read that both implicitly recognises and reconciles these multiple scales that I had in mind. I do wonder if we will ever work out a way to identify the optimal spatial and taxonomic scale to look at how diversity is generated or even if such an optimum exists?

To conclude a bit of a rambley post, I really appreciated this paper. It summarized the weight of evidence for two hypotheses that had somehow recently become quite polarized in the literature and emerged with a happier medium incorporating the best bits of both. Cornell also sets out his vision for making progress in this field and this involves taking a more thoughtful approach to improving our understanding of regional diversity patterns: collect more and better data, incorporate multiple types of data in any analysis, analyse it properly, and perhaps most importantly think about the SCALE of your analysis before you set out and as you interpret your results. Onwards and upwards!

Niche incumbency, dispersal limitation and climate shape geographical distributions in a species-rich island adaptive radiation

Algar, A.C. et al., 2012. Global Ecology and Biogeography 22(4): 391-402. DOI:10.1111/geb.12003. Niche incumbency, dispersal limitation and climate shape geographical distributions in a species-rich island adaptive radiation

Below, we give our first impressions of this article. Please comment below, or tweet Will or Lynsey (maybe use #pegejc). Think of this as a journal club discussion group!

Will Pearse

Will Pearse

I saw this work presented at Imperial College London, and I remember being impressed with Algar’s honesty. I can’t remember when I last saw someone actively drawing attention to the potential pitfalls in an analysis, and it  made me trust him all the more. This paper is a neat, self-contained look at what controls Anolis distributions, and concludes (quite rightly) that a number of factors play a role. I really like the approach they take, and I think it has potential to answer a lot of ecological and evolutionary questions.

The setup of niche incumbency as whether species tend to co-exist with things that are similar to them is nice and general, and I like the creation of these ‘morphological landscapes’ of how similar species are to one another. I think that’s a great way to visualise things across a landscape, and fits in quite nicely with previous posts about using phylogenetic similarity to improve the fit of species distribution models. Perhaps the only (likely unfair) criticism I’d make is the use of phylogenetically-constrained measures of species’ traits to make this landscape. We constrain according to phylogeny when we’re trying to ask questions about evolution; I think these processes of incumbency play out in ecological time, and so I don’t think it matters if species are similar because of niche conservatism. Put another way, I don’t care how or why species are similar, I care whether they are similar, and so I don’t see the need to control for phylogeny. Following on from this, I would be interested to ask what aspects of niche we can ascribe to the traits they measure, what aspects we can ascribe to phylogenetic similarity, and then what aspects are non-overlapping between the two. This would help us understand whether phylogeny is capturing something different to the traits they used – sort of the phylogenetic middleman problem turned around the other way.

I wonder what the effect of different spatial scales of action are on these results. Plotting maps like those in figure 2 implies that we can link these processess at the same spatial scale; lizards compete with one-another on smaller scales than climate variables, and this might complicate matters. Equally, small-scale environmental variation would mess around with this even further, although I’m not sure how I would model that (anyone?). If we really think blue-sky, perhaps agent-based modeling could be used to get at this sort of thing, although given current computer constraints we’d probably end up being limited to single species-pair interactions, and one of the great strengths of this paper is that it isn’t so limited.

Lynsey McInnes

Lynsey McInnes

Algar et al. generate measures of morphological similarity of co-occurring congeners and of dispersal cost to determine whether niche incumbency (i.e., a morphological (and thus ecologically) similar species is already there) or dispersal limitation (i.e, some factor prevents a species reaching ecologically suitable habitat) contribute in determining distribution patterns of Anolis lizards in Hispaniola or whether they are totally determined by climate (or by nothing in particular (in their null model)). They find some signal strength for niche incumbency and dispersal limitation, although measures of climate are still overwhelmingly the most explanatory factors.

I liked this paper a lot. It felt like the authors had spent a great deal of effort thinking about how best to quantify some notoriously tricky factors in a bid to unpick what really underlies the distribution of a diverse group in a restricted area. They also admirably do not harp on about the stacks of papers that generate climate-only SDMs with a biotic interaction/dispersal caveat stuck in at the end (I include my own papers here!).

I’ve been wondering for ages how to go about getting a better understanding of how the ranges of members of a clade are determined in a certain area (in my head I populate a 100×100 grid with a single species in a single cell and see the lineage diversify into x number of species each with abutting ranges vying for occupancy – in a heavy-handed dismissal of climate, I over-emphasise the role of biotic interactions perhaps). I imagine you can get quite far with (much better developed) simulations of range dynamics along the lines of Pigot et al. But this paper represents an impressive attempt to get at that type of question with empirical data (sure, Hispaniolan anoles are probably the system with the most comprehensive data ever – but why not start high?). I do wonder what other systems this approach could be used in (maybe the non-adaptive radiation of salamanders where expectations might be different if many species are ecologically equivalent? A bigger effect of phylogeny perhaps?). Amassing all the necessary data is always going to be a problem when you try and look at more explanatory factors, right?

This setup might also be useful to bring more clarity to the ‘ecological limits’ explanation for the prevalence of slowdowns in diversification. The idea has taken off in recent years and is extremely intuitively appealing, but the actual mechanisms by which a large clade in a large area (whatever large might mean) actually experience ecological limits remains, perhaps surprisingly, unclear. Do members of the clade prevent further diversification through their occupation of all available niches? What determines the niche breadth of the constituent species? Does niche breadth of the constituent species change as a clade becomes more diverse? Aspects of these questions have been tackled before, but, not to my knowledge, all in one go. Perhaps these questions are relevant to a broader time-scale than what is the focus of this paper, but they run along the same lines.

The result – that there is often a significant effect of niche incumbency and dispersal limitation, but climate still matters is not at all surprising, but it is nice to see it quantified. I wonder at the usefulness of their null model – all non-null models were so obviously going to be better – perhaps comparing climate-only versus climate + extras would have been sufficient? But maybe this is a more philosophical question on the relevance of null models.

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