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).


How does ecological disturbance influence genetic diversity?

Banks et al. TREE 28(11): 670-679. How does ecological disturbance influence genetic diversity?

How disturbed are your genetics? From Banks et al.

How disturbed are your genetics? From Banks et al.

Will Pearse

Will Pearse

Disturbance is a topic very close to my heart (that’s meant to be a physiology joke), mostly because I get very annoyed when people don’t define precisely what they mean by it. So I was very heartened to read this review, where the authors discuss the various temporal and spatial scales of disturbance, and also because it’s a very nicely written paper.

Disturbance, within certain conditions, can be part of the background homogeneity of a system, and the authors are keen to stress that in this paper. I was a little surprised to not find mention of the intermediate disturbance hypothesis (even though some find it controversial), since it’s so appropriate in this context. I found figure 1 (partially reproduced above), where the authors go through some case studies of what different kinds of disturbance look like, quite helpful in reminding me that disturbance can be lots of different things, and it can have lots of different effects (not always bad). However, that figure 1 is made up of case studies reflects our lack of a coherent framework to structure how we think about disturbance. Moreover, the right hand side of the figure (which I cropped out, sorry!) talks about two case studies that involve “metapopulation” and “patch dynamics”; this makes a lot of intuitive sense to me, but on reflection I find that kind of weird. Metapopulation theory is a concept humans have generated, it’s not a thing that biological systems recognise, and I think it might be better to categorise systems on the basis of properties they share rather than how we find it easiest to model them.

So what would such a categorisation look like? After reading this paper I think disturbance severity, duration, and extent (bear with me) are three important axes. With ‘extent’ I want to incorporate the ability to temporally and spatially escape a disturbance; spatially means whether the disturbance is everywhere and whether you can move to avoid it, and temporally that means whether the disturbance happens very often or very infrequently and would probably incorporate seed bank effects. I’m sorry ‘extent’ is such a poor descriptor; I’m decaffeinated and would appreciate better suggestions! I’ve very deliberately chosen to put space and time on the same axis; you might prefer to split them. You might also prefer to add predictability as another axis; I don’t, not because I don’t think it’s important, but because I think a system’s history (which, in turn, incorporates predictability) affects quite a lot and the other axes mostly capture what the system has been doing in the past. Not a lot about genetics in this post (sorry!), and instead a framework that almost certainly already exists somewhere and I’ve forgotten I’ve read it. Please do tell me where!

Lynsey McInnes

Lynsey McInnes

I had high hopes for this paper. I’m attracted to any paper that deals with intraspecific variation head-on and am well aware that intraspecfic variation affects and is affected by processes occurring on varying spatial and temporal scales. So, a paper dealing with how disturbance affects genetic diversity seemed right up my street. I was curious about the direction the paper would take as my feeling was genetic diversity is generally quite hard to measure particularly in non-equilibrium populations (such as those that have been disturbed) and assigning particular genetic signatures to historical events (‘disturbances’) is notoriously difficult as not only can a range of different events leave the same genetic signature, the same event can leave different signatures depending on the ecology and population structure of the species involved.

It was good for my ego to find that the authors largely confirmed my suspicions of these issues, but sad for the paper that there seems no easy way out.

It seems that the current state of understanding is that we live in an increasingly ‘disturbed’ world . Events such as tsunamis, fires and grazing impact nearby populations, reducing the number of individuals and thus most likely (at least) point estimates of genetic diversity and the challenge is to recognise the types of populations/species that will find recovery from such impacts difficult or impossible (if one is interested in conserving viable populations, otherwise all impacting populations are interesting, for instance, what kinds of species can you bombard with disturbances and they bounce right back to pre-disturbance levels of abundance and genetic diversity?). It seems however, that little research has focussed on the relationship between disturbance and genetic diversity and that there are many outstanding questions.

The second half of this paper gave a helpful overview of these outstanding questions and laid out some helpful ways forward. Namely, and understandably, the integration of multiple sources of data (event type, species’ traits, samples across the range and through time, etc.) will help to unravel the impact, or non impact, of putative disturbances on genetic diversity and, more importantly, what these effects mean for the longer term survival of species and/or communities. In fact, the paper lists FOURTEEN outstanding questions linking disturbance and genetic diversity and all of these are interesting. It would have been nice if these had been dealt with in more detail in the paper, perhaps focussing on a couple and on real routes forward to addressing them.

Maybe I missed this in the paper, but I also felt that what was missing was strong evidence that one expects any general link between disturbance and genetic diversity. As next gen sequencing gets cheaper and more accessible for non-model organisms, it will become trivial to look for these links, but, I feel, we need to know what we are looking for before we go looking for it. The general view is that more genetic diversity per population is better to ensure buffering against a variety of disturbances, but the authors show this is not always the case. Individuals can come from beyond the disturbance centre to make up for lost individuals and/or diversity. To predict this rescue effect one has to have a bigger picture encompassing knowledge of the genetic diversity of multiple populations within and beyond the disturbance centre. Are there enough individuals for recovery and do these individuals possess the desired adaptations? (So, I might differ from Will in thinking metapopulation theory might be helpful here).

I absolutely believe that intraspecific variation within and between populations in terms of genes and ecology must be considered if we hope to understand how populations will cope in the face of point disturbances and longer term environmental fluctuations. This paper drove home to me quite how difficult this endeavour is going to be.

Biodiversity decreases disease through predictable changes in host community competence

Johnson, P. et al., 2013. Nature 494: 230-233. DOI:10.1038/nature11883. Biodiversity decreases disease through predictable changes in host community competence

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

Neither of us know anything about disease transmission, but we’d probably both claim to be ‘biodiversity scientists’ (whatever that means), so I picked this paper to shake things up a little bit. The paper is a very large-scale empirical demonstration that more diverse communities have fewer pathogens, implying that biodiversity in of itself helps stop disease transmission. It focuses on a single system, and they have measured one heck of a lot of frogs!

I have quite strong views about Ricklefs – I love his work, but I find his emphasis on pathogens strange. In Ricklefs’ view of the world, pathogens are the hidden puppeteers that control species diversity and many evolutionary dynamics. I argue that there is some truth to this, but it’s just too easy to say that observed patterns are because of something we can’t easily test. However, this paper demonstrates this effect rather clearly – not only is the rate of abnormalities reduced in more diverse systems when density is controlled for, but also the species found in the depauperate assemblages are the ones most tolerant of infection. I’m not convinced that pathogens are the only things driving this pattern; we might expect generally more ‘hardy’ individuals to survive in difficult environments, and if conditions are particularly harsh we might expect individuals to either die, or survive and thrive because they’re tolerant of the conditions but have reduced competition. However, this does paper does provide hope that we might actually be able to start measuring pathogen infection and explicitly linking infection with observed ecological patterns.

I’m not wildly enamoured with figure 3b – I think there’s a lot of scatter in the lower-left corner of the plot, and that the figure is influenced by a few outliers in the top-right. This means I’m not convinced there’s as strong a connection between snail density and amphibian density as the authors, but I’m willing to admit I’m being snarky. I’m much more excited about the experimental results that suggest this increase in transmission rate is not just a consequence of density changes – that there’s something about being in a diverse assemblage that gives a system more resilience to pathogens. This leads to a second question, I think – what’s the effect of increasing diversity in the pathogens? Is a more diverse pathogen community able to overpower a power diverse host community? While we’re on this subject (and perhaps this is something disease ecologists know a little more about), what is a pathogen community?

Lynsey McInnes

Lynsey McInnes

Wow, thanks Will! When I choose papers they fall right into his area of expertise – we he chooses papers, they fall right between either of our areas of expertise. Moving on…

I enjoyed reading this paper. It struck me that the authors took a hypothesis that has been being bandied about and went through a painstaking process to unpick it using a neat set-up incorporating field observations and lab and mesocosm experiments (I love mesocosms). In the process they got to play with a lot of diseased frogs.

My understanding is that support is accumulating for the idea that diversity in a community (here in terms of species numbers, presumably acting as a proxy for functional diversity) decreases disease transmission among individuals. Yet another plus point for maintaining diverse communities.

The authors stress that this effect is not just due to changing density of the species most able to transmit disease although the numbers point to this being part of the effect. Which is fair enough I guess. Rather, there is some kind of ‘dilution effect.’ How does the effect actually work? I don’t know enough about disease transmission to understand or really even speculate.

The authors state this ‘One possible explanation for the negative relationship between a host’s competence and its assembly order is that defences are costly and may incur trade-offs with resource investment in reproduction or dispersal. Indeed, studies in both eco-immunology and conservation support linkages between a species life history traits (for example, ‘pace of life’) and its vulnerability to infection or extinction, respectively.’ But I am not sure how this really relates to their findings and (I may have missed this), but I did think the analyses were concerned with host diversity versus assembly order (which is surely another dimension of the diversity issue?). My naïve thought process would lead me to think of the opposite: in diverse assemblages, hosts devote less to defense at the expense of reproduction, dispersal (indeed to competition with other species), that they are more vulnerable? I am without a doubt that someone could explain why my reasonings is wrong, but in the space of this paper, the authors did not manage to.

I was pleased to see the authors advocate considering more aspects of community competence than simply host diversity, (‘climate’, ‘resources’, ‘habitat’ – yay, ecology!), but did wonder why they did not consider any further biotic aspects (apart from snails P/A and density) of their communities that might affect their conclusions. What of interspecific competition? Are there any other unaccounted for disease hosts? I feel strongly like I’m missing something, but why do less resistant hosts dominate in low diversity communities? What are their traits?

And, the usual, from a macro-scale biologist. How do these results scale to different systems, different sites?

An interesting paper, timely, nuanced and thought-provoking.

A functional approach reveals community responses to disturbances

D. Mouillot et al., 2012. Trends in Ecology and Evolution 28(3): 167-177. DOI:10.1016/j.tree.2012.10.004. A functional approach reveals community responses to disturbances

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 like the work of David Mouillot and Sébastien Villéger, and in my opinion they shouldn’t need to write a review paper explaining the suite of  approaches they’ve developed, because we should all be using them already. However, we’re not, and so they have, but we have the consolation prize of a really nice summary of some really nice approaches.

I’m what used to be called a community phylogeneticist – I use phylogenies to understand community ecological data. We are often (and rightly) accused of using phylogenetic data when trait data would probably be better for the question at hand – the phylogenetic middleman problem – and this paper describes the kinds of analyses we should do instead. However, we also come under fire because when we assume that phylogenetic overdispersion reflects competition, because it’s hard to map these observed patterns onto mechanisms (yes, I’m citing that paper again). The problem is that this exact critique can be applied to functional trait studies – if I find a community of species that are extremely dissimilar in terms of their functional traits, does that mean similar species have engaged in strong excluding competition, does it mean facilitation of dissimilar individuals is taking place, or does it mean something else? These issues are probably easier to tackle with trait data, but I still get worried when I start mapping trait patterns onto ecosystem processes.

Another thing that always confuses me in functional trait ecology is choice of traits. I don’t mean the boring (but important) “how many, and which, traits do we need to pick” issue, I mean what do we do when there’s variation in how important the traits we’ve collected are? These multidimensional trait spaces, to my mind, implicitly assume that all traits are equally informative. What if xylem diameter really doesn’t matter as much as specific leaf area? Can we weight the dimensions of these functional trait spaces to take this into account? How could we even detect that particular trait axes were more important? I think this is particularly important given we measure traits, in part, on the basis of what’s easy to collect – they’re what we hope are proxies for things we think are important in a system. Presumably someone has thought about this and I’ve just missed that literature – I’d be grateful for any links to papers.

There was very little about intraspecific variation in this paper, but then again it’s simple to incorporate into any of the measures: instead of abundances of each point in trait space, have lots of points (all of them close together, likely) for each measurement of a species. There was also little about choice of null models; this is something that does concern me slightly, because I’m unsure how to tell if we can compare measurements from a five-dimensional space to those from a ten-dimensional space safely. This probably reflects my dodgy maths! Moreover, in many other areas of ecology people get very concerned about the particular null model being used to test data – I just permute species identities for trait studies, and I can’t remember seeing anyone else doing anything else. Is that OK? Are there better ways of disentangling species composition and abundance?

Lynsey McInnes

Lynsey McInnes

Another strange pick from me that fell right into the community phylogeneticist niche that Will occupies. What a gift for him! Anyways, I was drawn to this paper because I like traits and functionality and am dubious (in a largely uninformed way) about most ways of defining communities. This paper kind of covers most of these topics…

I enjoyed this paper, but found it a bit difficult to follow. I think this is mostly due to me joining the discussion without having really thought that much about these ideas and issues beforehand. I liked the links to the niche/neutral debate, especially that the authors refrained from being really shitty about neutral theory and the contribution it can bring to thinking about ecological patterns and processes.

Some thoughts that came to mind…

Data availability/processing. The methods put forward in this paper look data/effort hungry. Which traits to use? How to score them objectively? Collating abundance data? Worrying about missing rare species/traits (although maybe this doesn’t matter)? Worrying about trait x trait interactions? Minefield! But in terms of providing early warning signals for community functioning probably worthwhile?

My next worry is how common is it to have this detailed information on shifting abundances following disturbance in order to benefit from these early warning signals of impending local extinction? Perhaps it is fairly common (or at least feasible) in communities where we try hard to obtain this information. Also (and there probably exists a whole research field on this), maybe we want to be focussed on some emergent properties of communities that can be quantified without monitoring abundances of all species involved, i.e., if functional traits are what is important rather than species diversity or identity then don’t we want some way of measuring community functionality that is not dependent on being able to monitor species’ abundances…

All this emphasis on traits over species diversity made me wonder how these techniques and approaches fit within the whole debate on species identification via traits vs. DNA barcodes? If a species is largely functionally redundant, do we care about its species’ status? I’m being artificially simplistic, of course, and I fully believe there is a place for these functional approaches and DNA barcoding approaches depending on both the aim of the exercise (discovering diversity vs. predicting responses to disturbance being an obvious distinction) and the nature/location of the community.

I’ve always been on the edge of the field of community phylogenetics but never had the guts to dive right in. But it does seem that a big criticism of CP (beyond the maze of dodgy metrics) is the focus on species as the be all and end all of most measures, rather than figuring out how trait differences (big and small) influence the different community structures that we observe (filtered, overdispersed, etc.). CP would probably benefit from incorporating some of this focus on traits, no?

The focus here is clearly on quite rapid timescales but with the increasing recognition that ecological and evolutionary timescales have a big chunk of overlap, I found it interesting that the authors didn’t devote much time to speculating on any possible evolutionary responses of species that decline in abundance. Yep, the scope is probably minimal and the trait values they would ‘need’ in the truncated functional space are likely already ‘taken’, but even so…

And finally, back to what is a community? It would be fun if these kinds of methods could somehow be adapted to identify clusters of function that somehow correspond meaningfully to the abstract idea of a community that most of us already hold in our heads…

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