Mycorrhizal status helps explain invasion success of alien plant species

 

pege-mycorrhiza-picture

Menzel et al. 2017 Ecology. Mycorrhizal status helps explain invasion success of alien plant species 98: 92-102.


pictureofme

John Wilson

For my first ever contribution to the PEGE Journal Club (or anywhere) I chose a nicely written article on the importance of mycorrhizal associations to the success of invasive plants. Menzel et al. analysed interactions between the mycorrhizal status and functional traits of 266 plants species and used the geographic distribution as a measure of invasion success. I think we were all quite impressed that this was possible with publicly available data, and some not-too-magical statistics.

The take home message of the study, going by the title, and first line of the discussion, was that mycorrhizal plants are likely to be more successful as invaders. However, since ~90% of plant families are mycorrhizal, is it so surprizing that most invaders are also mycorrhizal? We were also underwhelmed that facultative mycorrhizals plants (FM) seemed to be present in more grid cells. FM plants are free of the constraints on obligate mycorrhizal plants (OM), and may have alternative strategies to choose from, depending on local conditions. These points at first led us to discuss where the interest lay, particularly for a journal like Ecology. Eventually, pushing some slight publication envy aside, we discussed the interactions with plant functional traits. These seem more interesting than the broad statement that plants make fungal associations. It was interesting that rhizomes are particularly associated with FM plant invaders. I was curious whether they are more important to individual plants with a fungal partner or without, or whether the rhizome was also used a storage organ or not made a difference. It perhaps makes sense that plants with a store of carbon could afford to trade with a mycorrhiza, however, no other storage organs showed a similar relationship. The effect of different lifespans was a surprise for us. Discussing this we decided that we might have expected annuals to spread more widely than they apparently have. Also, that variable lifespans increased OM plant success seemed to be an interesting counterpoint to the variable association with fungi for FM plants, perhaps suggesting that having a “choice” between different strategies is useful for invaders adapting to new habitats.

We then wondered whether there was something particularly unique about habitats available in Germany, since Menzel et al. seemed reluctant to suggest a similar pattern would be found outside Germany. Although the data covered only Germany, it seems reasonable to extend the conclusions to other temperate regions, at a minimum to the rest of temperate Europe. We were curious about these limited expectations, since they also mention results from the UK that agreed with their own. However, contradictory results from California seemed to be enough to cause caution in their interpretation.

To finish up, I am now wondering how these results could be used. Perhaps expanding the models to include different combinations of traits, or taking into account factors like propagule pressure would be useful. Alien plants imported into parks or gardens, can co-exist quite peaceably with their neighbours, maybe for 10 or more years, before eventually overstepping their welcome. I don’t know how feasible this would be, but it would be pretty cool if this sort of information was added to the databases and could help identify or monitor potential invasives before they became invasive.

 

Join us next week where Zarah Pattison will lead the discussion of a paper by Azzuro et al. External morphology explains the success of biological invasions.

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).

Spatial scaling of functional structure in bird and mammal assemblages

Belmaker et al. The American Naturalist 181(4): 464-478. DOI:10.1086/669906. Spatial scaling of functional structure in bird and mammal assemblages.

This is a guest post with Chris Trisos. 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!


Chris Trisos

Chris Trisos

Belmaker and Jetz tackle two major problems in community ecology. First, community assembly processes such as environmental filtering and competitive exclusion can leave either the same pattern or can act in opposing directions to leave a random pattern in community trait structure, neither of which can be interpreted as clear evidence for either assembly process. Second, how the relative importance of community assembly processes changes across spatial scales is still unclear.

The first problem is dealt with by delimiting an ecological species pool. This consists of the subset of species within the regional species pool that also fall within the trait volume of the local community, and thus can survive under the local environmental conditions. Now, the functional difference between the regional pool and the ecological pool can be used to test for environmental filtering and, because the signal of environmental filtering has been factored out, it should be easier to detect the influence of species interactions on community assembly using the functional difference between the ecological pool and the local community.

Belmaker and Jetz apply this approach to regions and local communities over a range of nested spatial scales from 400 to 3 million km2. The general expectation is that environmental filtering dominates at relatively large spatial scales and biotic interactions at smaller spatial scales. Interestingly, their results, at least for mammals, suggest that both environmental filtering and competitive exclusion operate across the entire range of spatial scales.

Now for some picking at the details. This paper is not the first to delimit ecological species pools, but it is novel in quantifying the functional difference between regional, ecological, and local species pools, as opposed to just the trait structure within each pool. The functional difference used here is the average nearest-neighbour distance in trait space between the species absent from the ecological or local species pool and those present in it (fig. 1). This is a pretty cool approach and certainly forces you to consider more explicitly what is different about the species that are absent when compared with focusing only within communities.

However, I am not as confident as the authors that high and low functional differences between species pools map as neatly as they suggest onto clustering and overdispersion in trait space within species pools. This is especially true for the link between low functional difference, trait overdispersion, and competitive exclusion in community assembly. One can easily imagine a case where the functional difference measure is very similar for two separate ecological pool to local community pairings, but where the pattern of trait overdispersion within the two local communities is very different. Fig. 2c and d gives an example of this. Because of this I would like to have seen a comparison of functional difference with a measure of trait overdispersion or regular spacing within local communities (e.g. standard deviation in neighbour distances). This is an important link to clarify given that a lot of theory on species interactions structuring local communities makes predictions about the overdispersion or clustering of trait structures within local communities as opposed to between communities and species pools. It would also be neat (if the dataset is available – maybe for plants?) to link functional difference measures to measures of species interaction strength. It might be that, for competitive exclusion, a given functional difference is associated with a higher strength or more asymmetrical interaction between pairings of present and absent species than between pairings where both species are present in the local community.

I’m also unsure about whether the standardized effect size of functional differences can be used to infer the importance of a given community assembly process, as is done in the paper to test for the importance of biotic interactions in the tropics (any thoughts?). A process that results in weak effect sizes could still have a very important role in structuring a community. For example, the potential for environmental change aside, a species that is only just unable to survive at a site due to local environmental conditions is perhaps no more or less environmentally filtered than a species with trait values far from the survival set for the local environmental conditions.


Will Pearse

Will Pearse

This is a cool paper that examines some fundamental aspects of ecology: using functional trait data to examine shifts in community structure. I don’t think it’s immediately obvious on a first-reading just how massive the bird trait database they’ve collected is – this is an incredibly useful resource, and this alone probably makes the paper worth reading.

I’m particularly interested in definitions of source pool, and so I like the authors’ attempt to understand what an ecological source pool actually is. My only concern is that they define their ecological pool by drawing a convex hull drawn around observed communities’ trait distances (top of p. 470); I think it’s going to be harder to detect deviation from the ecological pool on the basis of functional traits if you’ve used those traits to construct the ecological pool. However, the authors have explicitly defined their ecological pools in an intuitive way that’s readily applicable to other study systems, and they do detect some pattern, so perhaps I’m being unduly harsh. In passing, we’ve discussed the methods the authors use in a previous post.

It’s beyond the scope of this paper, but here’s something I’m always interested in: can we use these functional measures to detect certain kinds of community? Are there some examples of communities in this dataset where there’s no overlap in species between communities, but their functional composition is the same? In other words, can we find communities that are functional analogues of one another? Can we use these convex hull methods to partition communities into different sub-components, either to examine the functional dispersion within  them, or to see if these functional groups exist in other communities? These are big questions (I’m missing obvious references about them, right?) but they’re exactly the kinds of questions that papers like this make me want to explore.


Lynsey McInnes

Lynsey McInnes

Congrats for making it down to the third comment! Thanks Chris for choosing a great paper and contributing loads of interesting discussion points. Now, as a non-community ecologist, I feel a bit out on a limb here, but let’s see if I can contribute something useful too!

First, I did really enjoy this paper although I sometimes struggled to keep the various scales and metrics straight in my head (probably a function of me not using the associated figures to their full potential). I appreciated that they set up the reasoning behind the paper well and I bought in to most of their arguments for why this is an interesting question and why their methods are good for answering it. I second Will in being impressed with their trait dataset too!

Although not an innovation of these authors, I appreciated the simple distinction of ecological vs. regional pools – quickly and effectively removing one element of the question – environmental filtering. Makes you wonder why people didn’t do this (or some permutation of it) straight from the birth of community phylogenetics? I wonder how much richness of the local community matters to what breadth of things get caught in the ecological pool and whether this causes any problems with extracting functional difference between the two scales. I guess repeating the analyses at a whole host of spatial scales helped address this potential issue and looking at the effect of latitude helped untangle whether things are different in packed out tropical areas as opposed to spacious temperate ones.

If I understand correctly, the authors find that functional difference is generally lower than random between the ecological pool and the local community indicating that the local community is a kind of matching subset of species able to cope with the local environmental conditions, suggesting some kind of assembly rules/competitive exclusion is going on.  I swing between thinking this a really cool result and wondering what all the fuss is about, but I recognize that such a reaction is simply due to not being well versed in the decades of controversy surrounding these ideas.

My, more real, concern is that the authors purport to have gotten at process/mechanism in their analyses and it feels to me more like they have carried out an impressively robust and thorough analysis to show a set of results that they already kind of knew. That sounds unduly harsh – what I really want to say is – now comes the fun part! There are still some differences among communities and regions, and it would be exciting to know what leads to these differences: for example when are simple physical problems like dispersal limitation the cause of certain community compositions, when is it competitive exclusion? Is it intrinsic traits, extrinsic environment or stochastic events that underline such differences? It strikes me that the next step might be to incorporate a temporal perspective on the arrival of species (or rather traits) into a community and the effects this has, to incorporate finer-scale characterization of the landscape and environment (paleo conditions too, why not?) and, as Chris hinted at, get plant/producer information in there as well. That all sounds massively difficult and like a step away from finding generalities to finding specifics; I would counter that the authors have done a great job at clearing up longstanding issues in community assembly and their setup stands them in the best position to take the next step. I’d be interested to see how this goes.

*As a sidenote, one day prior to reading this paper I read a recent paper by Alex Pigot & Jo Tobias in Ecology Letters – Species interactions constrain geographic range expansion over evolutionary time – the authors take a temporal perspective on this question and it strikes me that some modification of their setup could be helpful in tackling more head on the temporal element of community assembly. Just a thought.

%d bloggers like this: