Drawing ecological inferences from coincident patterns of population- and community-level biodiversity

Vellend et al. Molecular Ecology (early view) DOI:10.1111/mec.12756. Drawing ecological inferences from coincident patterns of population- and community-level biodiversity

What's your favourite intraspecific (blue) and interspecific/community-level (red) trait-environment relationship? Taken from Vellend et al.

What’s your favourite intraspecific (blue) and interspecific/community-level (red) trait-environment relationship? Taken from Vellend et al.

Will Pearse

Will Pearse

I picked this paper and broke our 6-month run of old-school classics (sorry!) because the topic looked interesting, and Mark Vellend seems to write so many good reviews I couldn’t help myself. Like Lynsey, I thought the paper was going to take a few different directions, but I enjoyed it nonetheless.

Figure 1 (which I’ve put at the top of this article) is the sort of graph that lots of people seem to grappling with, and I’m glad to see it in print. It’s an extension of one from another excellent paper, and the essential point is that an inter-specific relationship could be the opposite of the intra-specific relationship among the same species. The similarities with Felsenstein’s classic graph showing why we need to control for phylogenetic history are striking – different results are found at different (phylo)genetic scales. If you view individuals as existing in a hierarchy from clade–>region(–>community?)–>species–>individual, then I think it’s amazing that we find these reversals at all scales. Why is it that ecological/evolutionary units seems to have discrete, real boundaries among them? I sense it’s related to the balance between character displacement (species spread out into discrete groups) and niche filling (within those groups there is variation), but I sense we need some more simulation analyses to truly understand why this keeps happening. I may try something over on my R blog next week (sorry for the plug!).

I found the sudden appearance of a meta-analysis later in the paper surprising but kind of cool. The general idea is that discrete fragments of habitat should show a greater potential for genetic drift than same-sized sections of continuous habitat, and changes in the correlation between genetic and species diversity reveal this. The results seem to support their conclusions, and (like all such provocative graphs) leave me wondering how further we could tease this all apart. Biogeographic history, generation time, age of habitat patch, etc., should all affect these sorts of correlations, and on second thought it somewhat shocks me that we don’t have better data on all this (“correlations were calculated from data not collected for this purpose“). If we are to stand a chance of understanding some of the hierarchical patterns that I described above, we need slightly more joined-up analyses of different levels of diversity. Indeed, there’s enough meta-data on GenBank that maybe someone (not me!) could have a go at this.

Lynsey McInnes

Lynsey McInnes

I was looking forward to this paper as I thought it would help clarify my own pet interest in integrating population and species level patterns of biodiversity and would give me more ammunition in my plot to have all above species level analyses incorporate intraspecific variation. The paper kind of managed to do this. It was slightly disconcerting how many times the authors stated what the paper was not going to talk about, but it did eventually end up focusing on congruent diversity patterns at the above (species numbers) and below (genetic diversity) species level and on congruent patterns of trait variation along environment gradients when considering multiple species or multiple populations of the same species. Both concepts sound fairly dull, let’s be honest, but have not been assessed vigourously in the literature so it was really nice to see a summary of these results. Conclusion: sometimes intra- and interspecies patterns are similar, sometimes not.

I guess where I felt the paper fell short (and this is probably due to me wanting the paper to be something it wasn’t trying to be) was that it did not really focus on how insights at one level of diversity could inform insights on another level. For instance, what are the characteristics (trait variation, genetic diversity) of populations that make up large range species vs. small range species? I.e. how do some species obtain large ranges, while others break up into multiple smaller ones? Are all large range species en route to becoming multiple small range ones or are there certain ‘types’ of population that can maintain a large range species over evolutionary time?

A ton of work has been done about edge and centre populations and adaption/movement in response to environmental change, I would have liked to have read more about how population characteristics can suggest how a species might respond (maladapted gene flow, good gene flow, rapid evolution, local extinction). Species’ ranges are dynamic because populations come and go. How do we integrate this knowledge with our desire to study emergent patterns above the species level (diversity fluxes at the regional scale, for instance)?

I did appreciate the authors’ discussion of trait vs. ‘diversity’ variation approaches to looking st intra/interspecific congruence. Molecular diversity measures are relatively easy to collect and more or less comparable across sampling units (a can of worms we won’t open here). Traits are harder to collect, it’s harder to choose relevant traits to collect in the first place and inference might be bamboozled if you are looking at a deficient trait or one collected poorly. I am guessing that a little way in the future, such studies will use the genetic variation behind the trait of interest (when genomes shower down on us like rain). Until then, a mix of both approaches is probably most informative.

Onwards and upwards.


Macroecology: Does it ignore or can it encourage further ecological syntheses based on spatially local experimental manipulations?

Macroecology: Does it ignore or can it encourage further ecological syntheses based on spatially local experimental manipulations?

"Macroecology... is not a fruitful path for thoe of us seeking to understand how ecosystems are sutrcutred and function" - Paine (2010). Image from seaotters.com

Macroecology… is not a fruitful path for those of us seeking to understand how ecosystems are structured and function” – Paine (2010). Image from seaotters.com

Will Pearse

Will Pearse

This paper made  a real impression on me; I also think it wins the ‘most polite knock-down of a field’ award, in that the first two paragraphs make it clear he doesn’t like the field but somehow he does it so politely I want to read on.

Paine is right; marine ecosystems are different, and since they’re the largest part of our planet we shouldn’t be so terrestrially-focused. I feel that much of what a terrestrial ecologist means by ‘history’ is really ‘dispersal limitation’; at evolutionary timescales vicariance and/or distance leads to speciation where we wouldn’t otherwise expect it, and in ecology it leads to species with identical environmental tolerances not co-existing. Thus when Paine identifies marine ecosystems as having huge dispersal distances (particularly in the larval stages), he’s essentially pointing us towards how terrestrial and marine ecologists are always going to view history differently. If everything truly can be everywhere, then historical contingency is a very different thing in water.

Paine is also right when he says that a species list is no end-goal for a field. Yet, for all the importance of local-scale contingency (Paine did invent the keystone species concept!), it’s worth remembering that species distribution models (SDMs) do actually work (some/most of the time). That’s not to say that they always work – trophic cascades and other biotic interactions are always mentioned but seldom modelled in SDMs – but if everything can be everywhere in water, can that change how they should be modelled? Can trophic cascades be captured by understanding the environmental conditions that enable those keystone species to survive there?

I think Paine is missing an important trick when he discusses comparative experiments. He wants comparative experiments on taxonomically similar species to identify underlying rules, and macroecology is the search for those same principles that determine a system’s rules of engagement. We study the species pool because, particularly on land, that determines what smaller-scale communities look like; maybe fundamental differences in dispersal mean the kind of macroecology Paine discusses is more appropriate for terrestrial systems. I’m always harping on about the importance of changing the phylogenetic, spatial, and temporal scales at which we examine an assemblage to help us better understand ecology. Perhaps terrestrial ecology has shifted too far in favour of laptop-jockeys like me who re-analyse datasets, and maybe we do need more local-scale experiments where we can test ecological mechanisms. Yet if broad brush-strokes without detail will never help us understand mechanism, detailed work without a context will never help us predict.

Lynsey McInnes

Lynsey McInnes

This paper is great. I think my fellow commuters were perplexed by what I was reading that was making me smile so much. As a macroecologist, I’d never heard of this man Paine until this paper came out in Am Nat a couple of years ago. But Paine is no macroecologist, so perhaps that’s OK. In fact, he is a vocal marine microecologist (I think) and is attempting in this address to argue the dual points that ‘micro’ ecology has a lot of insights to give that are impossible from macroecological techniques (fair enough, really) and then a slightly weirder, this might be my fault because I know more about terrestrial than marine systems, but not really that much about either, that macroecology is better suited to terrestrial than marine systems?

Well, we picked a nothing if not provocative paper to relaunch PEGE with.

Paine’s address is packed with home truths about macroecological approaches, but regularly (at least to me) jumps off the deep end into ridiculous. Macroecology (‘the study of relationships between organisms and their environment at large spatial scales to characterise and explain statistical patterns of abundance, distribution and diversity’) is often berated for being overly concerned with documenting pattern without a thought to processing generating patterns, and I think this criticism does stand true. However, there is a. plenty of work that tries much harder to understand process and b. more fundamentally (and this is where my opinion differs from Paine’s) I think there are processes operating at these broad scales that are of interest to identify and understand (a factor that probably contributes to so many people attempting to document the patterns these processes produce).

I’d argue that an across scales approach is the most valuable. Are local scale happenings relevant to emergent broader scale patterns? Are they divergent? How do ecological responses at one trophic level affect others? How do responses on evolutionary timescales affect things? What governs turnover through time and across space? What allows invasion from one site into another? And so on. Sure, documenting yet another latitudinal diversity gradient, or an exception to it, doesn’t get us much further in any endeavour, but a comparative analysis of food web structure across continents does.

I am not sure I followed Paine’s terrestrial vs. marine arguments, but I think the crux of it might have been that ‘local’ or ‘micro’ in marine systems is already way broader than in terrestrial systems where people can more easily summarise whatever they wish in 100km grid cells (oh the horror) and go to town with their pattern documentation. I would argue that both systems have interesting and important ‘micro’ and ‘macro’ ecology and that perhaps the easier route to deeper understanding of ecology or ecological responses comes from an objective comparison of the two (like here and here).

Lastly, Paine laments the ‘niche craze era.’ What a great phrase. And so true. I, and many others, jumped on the – somewhat specialised – niche conservatism bandwagon and went a little crazy. We documented crude patterns using deficient taxonomies and didn’t get very far in working out what drives change in some dimensions’ of a species niche and not others. This was perhaps because we didn’t know what a niche was or how to quantify as we embarked on this endeavour or perhaps because we didn’t care. No doubt about it, understanding species’ roles in ecosystems is more vital than quantifying variation along some orthogonalised niche axis, but once robust methods are devised (and I don’t think they have been yet) to quantify ‘role’ (and I mean on a ‘micro’ or ‘macro’ scale), I imagine they will simply be some axis of the (again not properly defined yet) elusive niche. I see these advances as an exciting challenge for the pretty near future than a reason for contention.

I recommend this paper to all brands of ecologist. It helped me realise I did still find macroecology and the insights it seeks to identify interesting and important, while feeling chasistised that macroecologists can sometimes, in fact often, be lax in defining relevant and appropriate research goals.

The problem of pattern and scale in ecology: what have we learned in 20 years?

Jérôme Chave, early view. Ecology Letters. DOI:10.1111/ele.12048. The problem of pattern and scale in ecology: what have we learned in 20 years?

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 am not a field ecologist, and I downed quadrats and upped my laptop because of the two papers Chave repeatedly cites in this paper: Lawton (1999) and Levin (1992). These papers made me see there was a place for biologists who looked across taxa, space, and time, to find general rules in ecology. This paper demonstrates just how far ecology has come in a little over two decades, and left me with an awful lot of hope for the next two. There’s a lot of material in this paper, and (judging by the sections I think I know something about) it’s all been very deeply considered.

Chave’s review almost operates in reverse of Levin’s paper. He starts with the eco-evolutionary problems that Levin left until the end, presumably because what was an exciting possible avenue in 1992 has now become an exciting reality in 2013. I encourage anyone who feels Chave overplays the importance of computing power to go back to Levin’s review; figure 1 is a 10 x 10 degree grid cell model of the world, and the only colour figure (13) pales in comparison to Chave’s (perhaps bafflingly!) complex reprinted figure 3. Whatever you think of the current vogue for ‘big data’ and complex modelling techniques, I don’t think anyone in 1992 would have predicted the changes that increased computer power, in combination with the open source R ecosystem, would bring. We are beginning to tame the complexity Levin hoped we could explore.

Which is why I would have enjoyed a discussion of agent-based models, and (perhaps more explicitly, if I missed the subtext) the importance of emergent properties of systems. Agent-based models are an excellent way of using information on individual-level actions to predict higher-level properties of systems, and I feel (as an outsider) are changing the way we look at species movement and dispersal. I’ve been thinking a lot about abstract properties of different kinds of systems (after re-reading this recently) – to what extent can we find general properties of ecological systems, at higher scales (be they temporal, spatial, or something else) that allow us to better predict changes in those systems? What general rules and patterns can we pull out of analyses conducted across multiple scales?

It is this idea of abstraction that made me particularly enjoy Chave’s section on using compartmental analysis to define the ecological niche. I’m not a bacterial ecologist, but I wish I were, because I think it’s almost impossible to quantify any other kind of ecosystem in this level of detail. Finding repeating units (like these network motifs) and using them to infer process falls right into the category of the emergent property driven analysis I mentioned above, and gives hope for definitions of niche that aren’t dependent on traits, environmental tolerances, or phylogeny. Grouping species along niche axes that derive from properties of their organisation, which are more intangible but arguably more real than things we can measure with a ruler, could be incredibly powerful. Despite the risks and potential pitfalls, measuring the niche according to dimensions of species’ own organisation, not what we decide is important a priori and can measure, sounds exciting to me.

Lynsey McInnes

Lynsey McInnes

This paper has been floating around online, hailed as a forthcoming classic. Perhaps. I have to say I’ve read it at least four times now and it doesn’t get any easier. There is absolutely tons of great and thoughtful stuff in here, but sometimes the typos, the poor sentence structure and some logical leaps made extracting that thoughtful stuff quite difficult (at least for me). Anyway, moving on from these critiques and focusing on what I was able to extract from the paper…

Scale matters! Looking back over the four papers Will & I have chosen so far for PEGE, this paper does indeed seem right up our street – turns out we are both a bit taken by processing operating across a range of temporal and spatial scales and seem drawn to studies addressing scale issues head on. So, at the very least, PEGE is helping us identify our research interests.

It is indeed amazing the progress ‘ecology’ has made in the past twenty years and this does seem largely due to access to more data, more computing power and the development of swankier and swankier methods and models. My fear is that progress on these fronts has been too rapid and that data and methods are thrown at sometimes quite vague questions, ‘just because we can.’ I think I might be biased here as this issue might plague my own field – macroecology – more than others (this certainly seems the case from some of the cool study examples outlined here). But, to sound a general note of caution, aimed mostly at myself, take things slow, think about the interesting questions and pursue their answers with appropriate methods and data (not necessarily the most elaborate methods and data).

One of the main messages I did extract from the paper is that biotic interactions matter in understanding species’ ecologies. Whether this in the form of interaction networks, community dynamics or broad-scale diversity patterns, how species’ interact with conspecifics, congeners, competitors, mutualists or across trophic levels matters. Recognising this and quantifying these interactions is going to be crucial in predicting how species and in turn communities will respond to global change. Sprinkle in the potential for rapid evolutionary responses (mostly likely different speeds for different populations/species) and these predictions sound hellishly difficult, but might still be possible.

The second main message was perhaps that a crucial species’ trait to consider is dispersal ability. Debate still rages on what dispersal is, but in terms of scale-dependent processes, it’s central. It can influence population connectivity, species’ range size, species’ ability to track good abiotic environmental conditions and/or biotic interactions and on longer temporal scales can influence rates of speciation and extinction. In short, getting a better handle on dispersal (ability, evolution, variation) will help unify our understanding of species’ distributions (and more).

Lastly, I really appreciated Chave’s call for more crosstalk among disciplines from geneticists to ecologists to earth system scientists, an understanding of emergent patterns will only be gotten from fusing information, techniques and expertise from disparate disciplines. Easy to say, hard to do, no doubt.

Founder takes all: density-dependent processes structure biodiversity

Waters et al. 2013. Trends in Ecology and Evolution 28(2) 78-85. DOI:10.1016/j.tree.2012.08.024. Founder takes all: density-dependent processes structure biodiversity

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

This week’s paper is a whistle-stop tour of how diversity-dependence drives a lot of ecological patterns, and I found it pretty damn hard to disagree with anything they wrote. Essentially, the authors argue that once a species has established in a particular area, it stops other (similar) species invading by virtue of numerical superiority – density dependence drives everything.

I’m not a bacterial ecologist, so ‘microbial sectoring’ was entirely new to me. In it, bacteria spread through an agar plate and competitively exclude different genotypes as they do so, creating wedge-shaped patterns of genetic diversity once the colonies have matured. The authors (rightly, I think) view this as a sort of postglacial colonisation in miniature, and suggest that ecologically equivalent marine species are excluded through similar processes, even in the absence of dispersal limitation. However, I’m not sure I agree with their definition of ecologically equivalent; in most neutral models, ecologically equivalent species intermingle and successfully coexist because there’s no way to tell those species apart. I think density-dependent processes like allelopathy might drive these kinds of patterns, since without some kind of selectivity conspecifics wouldn’t be able to recruit either. There are (a number!) of counter-arguments to what I’ve just said, and I’m just pedantically splitting hairs since I’m invoking a different kind of density-dependence to explain these patterns!

I think invasive species are another exciting area where we can see differences among advancing species. There’re a few examples of invading populations that have different traits and genetic compositions to native populations, and it makes good intuitive sense that individuals able to survive dispersal by humans should be well-adapted to slightly different conditions to the rest of their source populations. Equally, individuals on the leading edge of an expanding range might be better-adapted to dispersal, or have higher reproductive rates to enable rapid colonisation, like human colonists expanding along a river in Quebec seemed to bring a number of genes for female fertility with them. However, before I get too teleological, the authors stress that sometimes genes are just piggybacking on advancing waves – they’re just allelic surfers.

Lynsey McInnes

Lynsey McInnes

Hm. This was a weird article! I started off thinking – wow, profound – and quickly segued into – wow, trivial? I’m basically not sure I got the point. I certainly don’t disagree that density-dependent processes are important and that they operate at a variety of temporal and spatial scales. But I don’t think I’ve gained any deeper understanding of general biological processes by having these across-scale processes highlighted to me.

The authors also skirt around the genetic underpinnings of the processes they talk about, making it unclear whether they are actually the same at microcosm to continental scales. I guess computer simulations have shown, e.g., how deleterious mutations can surf on an invasion front, and how newly-established populations (e.g., following postglacial reconstruction) can exhibit less genetic diversity than “older” populations.  I’m biased because I’ve just started thinking of the underlying genetics of macro-scale processes myself, but the paper did make me wonder what’s going on with the genetics of all these events.

So far, I’ve mostly thought of density-dependent processes in the context of cladogenesis (following the past couple of years flurry of publications reporting evidence of declines in diversification rates widely thought to be due to the operation of ecological limits/filling of niche space), i.e., the density- (or diversity-) dependence of cladogenesis. The authors touch on this idea, but don’t go into much detail. On the one hand, it’s perhaps a little off-topic, the authors seem most pre-occupied by density-dependent processes operating as a kind of barrier to the influx of further genetic diversity after an initial colonisation event, while, within the diversification/cladogenesis literature, density-dependence has largely been invoked in relation to something like a closed system where all members (lineages) are equally affected and the niche/range/genetic diversity of the initial colonizer would be similarly reduced to accommodate additional lineages. But perhaps this outcome is just one step further along from what the authors concern themselves with and so is relevant to the discussion. I.e., does the founder advantage (or our ability to detect it) drop off through time?

Data. I know this is a review, but it would have been great to see some kind of more or less formal meta-analysis of the existing data across scales to innumerate instances of founder takes all events (versus instances where there wasn’t evidence for this – stronger competitors arriving later? This must happen sometimes – surely?). Alternatively, some kind of ‘simple’ simulations exploring a broad parameter space to see when founder takes all is expected versus when it might break down (A REALLY strong competitor coming later? Some kinds of poor trait x environment combinations? Incredibly slow dispersal rates? A highly stochastic environment?)

One other thing, there is not much discussion on what makes a founder? Are there traits associated with being first in line? Are these shared/analogous across taxa?

But perhaps I’m trying to sketch out a set of companion papers, and I should be less demanding!

To end on a more positive note – first, if nothing else, the paper has put me a bit on edge – why is it bothering me so much? So, in the end, it has ticked the thought-provoking box. Second, I did appreciate the breadth of examples the authors drew upon (simulations, microcosms, terrestrial and marine ecosystems, human dispersal & human impact) and I will go away now and think some more on the connections they have highlighted.

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