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?


Achieving the convention on biological diversity’s goals for plant conservation

L. Joppa et al.. Science 341: 1100-1103. DOI:10.1126/science.1241706. Achieving the convention on biological diversity’s goals for plant conservation


Endemic plant hotspots of the world (from Joppa et al.)

Matt Burgess

Matt Burgess

This paper, which came out 3 weeks ago in Science, assesses the feasibility of the UN Convention on Biological Diversity’s (CBD) goals of protecting 17% of the terrestrial world and, through the Global Strategy for Plant Conservation, 60% of plant species. Using data from a large database of plant species distributions, they show that: a) it is physically possible to achieve these two goals simultaneously (because they were able to find a group of regions comprising 17% of the terrestrial world containing the entire ranges of 67% of plant species); and b) that regions with the most plant species have only slightly more area protected currently than those with fewer species.

I want to start by saying that I think this paper is an important advance in the ‘hotspots’ literature. It identifies regions of high diversity and endemism using an algorithm and data that are transparent and can be updated – an important step forward from previous frameworks based more heavily on expert opinions, as the authors point out.

However, I also feel I must briefly let my grumpy inner economist out of his cage, and reveal myself to the world as a big fan of Hugh Possingham, Steve Polasky, and others who have taken somewhat more pragmatic approaches to the problem of spatial conservation planning. While this paper does an excellent job assessing the physical feasibility of the CBD’s goals, I think it could have, without much extra work, gone much further in addressing other issues affecting the CBD’s practical feasibility.

In particular, I was very surprised to not see the words ‘cost’ or ‘economic’ anywhere in this paper (I even double checked this using command + F after I read through it the first time). As we all know well (e.g.  McCarthy’s et al. 2012), conservation initiatives run on a highly limited budget worldwide. It is critical for spatial conservation planning to take this into account if protected areas are going to maximize the biodiversity protected. As a cartoon example, suppose a country has a billion dollars to spend on protected areas and must choose between protecting one area with 30 000 species at a cost of the full billion or two areas of equal size at 500 million each with 20 000 species each. The authors’ greedy algorithm would suggest protecting the first area (with 30 000 species), but more species (40 000) would be protected with the available budget if the cheaper, lower-diversity areas were protected instead. The authors remark that the areas with highest diversity identified by their analysis are not protected in practice much more commonly than areas with lower diversity. I wonder if these lower diversity areas are chosen because they are relatively cheap. The authors’ mention, in the middle column on page 1100, of a bias in protected areas towards high, cold, dry lands that are far from people seems to support this hypothesis.

To suggest that this paper should have formally addressed costs in its analysis is perhaps a bit unfair, as no paper can address everything. However, I do think the authors should have discussed them, even if only briefly. Moreover, I think incorporating costs into the conservation prioritization framework developed here is a highly fruitful area of further research. For example, this paper estimates the minimum area needed to preserve 60% of the world’s plant species. A future study might try to estimate the minimum cost of such conservation. The similar recent analysis by McCarthy et al. on birds provides one example of how this could be done. Combining spatial planning algorithms optimizing for minimum cost and minimum area could yield estimates of an efficiency frontier balancing the two that would be highly useful for policy-makers and spatial planners (see Polasky et al. 2008 for an example of a similar analysis). Some research groups, notably Hugh Possingham’s (I told you I was a fan), have actually already made some promising strides in this direction (e.g. Wilson et al. 2006). I was also quite surprised to not see this or other similar studies cited or discussed by Joppa et al.

I apologize for this somewhat long-winded post, but to conclude, I think this is a good paper that, with a little bit more analysis or discussion of costs, could have been a classic. Nonetheless, I think this study lays the foundation for tremendously fruitful further research in spatial conservation planning.

Will Pearse

Will Pearse

I have a dirty secret: I love hotspot papers. I love staring at figures like the one above, and thinking about how we live in a world where we can pinpoint where all the world’s diversity is. So bear that in mind.

I think Matt unleashed his grumpy economist  a little too early. This is a great hotspot paper. The authors use fundamental biogeographical theory to show why regional data are untrustworthy; I don’t care what form you think the species-area relationship takes, that one exists means the resolution at which the data were collected matters. Yes, there is no explicit costing in this paper, but that is not the point of it – the paper is trying to make a map of endemism, and I think they do a pretty damn good job of it. Although I have serious issues with using endemism as a conservation prioritisation tool, Red Listing all these species would take far too long and so this is probably the best we can do. This is not a paper that is aiming to come up with a robust (economic) prioritisation of the world’s flora, this is a hotspot paper that is trying to figure out where things are and point out the areas of a priori importance. I think Lynsey (below) is right in pointing out that we have a lot of papers like this (here’s another relevant one), and maps of the world’s phyogenetic diversity are beginning to emerge. Indeed, figure 2 plots the number of species protected under various schemes: since we first have to establish whether the species in protected areas would survive without them, and also how much we value those species, I’m not sure what we can do with graphs like this.

The deeper question I think we can all ask is why we need papers like this, and why we shouldn’t just all be out in the field waving placards and setting up reserves. To answer that, I want to talk about when I (briefly) met Lucas Joppa (I think) and Stuart Pimm while doing my MSc at Silwood Park. Felix Whitton and I were running a conservation news website (Conservation Today; the site is dead but check out these talks), and Pimm gave us a ~two hour interview. I specifically remember Pimm saying that it was more important to worry about what was going on “at the coal face” than spend your time making hotspot maps of the world. So why one more hotspot paper for him? Because papers like this give conservation NGOs easy-to-interpret guides (“have you thought about parks in this country, because they have a load of endemics”), and give us an opening to get more money (“hey *insert name of rich person*, this easy-to-understand map that was published in Science says we need more parks here!”). Pimm and others are out there trying to get money to get things saved, and papers like this help them. Fundamentally, it’s not the economic efficiency of a park system that saves wildlife, it’s the product of economic efficiency and the money available.

Lynsey McInnes

Lynsey McInnes

Another permutation of sub-optimal range data, area-selection algorithms and conservation prioritisation! Rejoice! In all honesty, I wanted to dislike this paper as I feel we are all really going round in circles with these kinds of analyses, but there are things to like in this paper and things to ponder. I also love the style of Joppa, Jenkins et al. (check out this PNAS paper, they are just cutting about other methodologies in a way that is simply fun to read).

Anyways, I am fairly sure that Matt is going to focus on the economic (un)feasability of their conservation guidelines, so I will skip that side of things altogether.

I like that they take actual established guidelines for protected areas and numbers of plant species that need protecting and try and work back from there to establish if they can find the optimal areas that would cover these species numbers in the minimum possible areas. They then show there is substantial overlap with restricted range vertebrate species. All it,well and good. Again, ignoring the economic and political side of protected area designation, do these results tell us much we didn’t know already. A bit…

My biggest concern, and this goes for most such studies, is do we really just want to protect areas with high numbers of species? Don’t we want to conserve ecosystem function or phylogenetic diversity (i.e. a variety of species and a source of new ones)? Don’t we want to make sure that there are corridors for species’ movement and that protected areas are well-connected and likely to be useful in the future? Don’t we want to square conservation goals with existing landuse scenarios and development goals? I am of the opinion that Myers’ hotspots were profoundly important in identifying to scientists and the general public that there are regions with there is a ton more biodiversity than elsewhere, that these are typically beautiful, interesting and probably contain a lot of tapped and untapped resources. Everything since then has (really) just reinforced his original set, perhaps adding a couple more outliers, or more pristine habitats that didn’t make his cut because they hadn’t been screwed up yet. But really tropical areas, islands, some outlier temperate areas are always identified. If you change your criteria, you might get a high latitude region or two. Where do we really want to go from here?

I would say, let’s get campaigning and conserving. Let’s get action happening to protect at least some of these amazing places. Let’s work out what is feasible (politically and economically) and get going.

Niche syndromes, species extinction risks, and management under climate change

DF Sax, R Early, and J Bellamare. Trends in Ecology and Evolution 28(9): 517-523. doi:10.1016/j.tree.2013.05.010. Niche syndromes, species extinction risks, and management under climate change

Do you have a niche syndrome? You can get a cream for that you know... From Sax et al. (joke from Sarah!)

Do you have a niche syndrome? You can get a cream for that you know… From Sax et al. (joke from Sarah!)

Sarah Whitmee

Sarah Whitmee

I chose this paper before I knew that Lynsey and Will were to review a very similar one just two weeks earlier, coincidence or something more sinister? Actually, I don’t think either of those things, but is in fact due to a new phase in the field of species distribution modelling (SDM), one in which concepts are clarified and the assumptions of models are questioned and tested. Well that’s my hope anyway…. Nevertheless, it is becoming increasingly clear that a big assumption made by those practicing the dark art of SDM, namely a linear relationship between the realised niche (the area of environmental space actually occupied by a species) and the true environmental tolerance limits of a species does not exist, at least not for most species. This was illustrated in the Araujo et al study discussed here, where it was neatly demonstrated that lower thermal tolerances varied widely across species while upper tolerances were much more conserved. Happily, I think this study complements the earlier paper, phew!

The authors start in true TREE style with a nice overview of the current state of the field and the definitions of key terms. While often this is just restating the obvious it’s actually a pretty useful exercise for anyone working in SDM to go through, varying definitions of the fundamental, realized and potential niche plague the discipline and formally stating them for yourself can help later down the line when trying to interpret and understand models.

They then get down to the business end of the paper, the introduction of a new concept: the ‘tolerance niche’. The tolerance niche is defined as “the set of physical conditions and resources that allow individuals to live and grow, but preclude a species from establishing self-sustaining populations”. While I’m not convinced that the field of species distribution modelling needs more jargon I can see the usefulness of this concept in theory, specifically in relation to predicting the impacts of climate change on species persistence. The idea is that while a species cannot thrive in these tolerance zones they can persist temporarily in them, for example during dispersal to reach new suitable climates or to outlast temporary climate fluctuations. The introduced concept is then used to illustrate a number of niche syndromes, or ways we might want to think about species responses under climate change. They choose horticultural plants as a key group for illustrating how you could formulate hypotheses for these niche syndromes and also how you might work out a species tolerance niche, from evidence of specimens in botanic gardens outside a species native distribution.

Overall I like this paper, its clear and well thought through. I buy into the idea of the tolerance niche and think it’s a good step towards more dynamic species distribution models, rather than the time-slice approach employed in earlier analyses. Being a macroecologist I have a problem with this paper that I often encounter with the more fine scale SDM work. While the concept or model works well for a single species or a particularly well studied ecosystem (its no coincidence that a large proportion of SDM studies are all about the South African fynbos you know) these concepts fall down due to a lack of data when you try to scale up for multi-species predictions. The example species given in the paper works beautifully for the concept they are proposing but I wonder how many other species show such clear relationships. So I would have like to have seen more real world examples to convince me that the tolerance niche can truly be estimated. I know very little about plants (outside the ones in my garden) but I’m nervous about the idea of inferring tolerance simply from presence in a botanic garden outside the native distribution with a better understanding of how the plant is managed in situ for example it might be protected against winter frost or supplemented with food or key nutrients. I guess for species of key conservation concern such an approach might pay dividends.

I did like the idea of managed relocation for slow growing species, putting them in an area that they can tolerate in the short-term but which will eventually become climatically suitable for growth and reproduction. It’s a risky business though and I would want a much higher confidence in my climate models before attempting such a bold step.

To sum up the tolerance niche is a neat concept but how applicable it will be in the long term, I’m not sure. I’m a fan of these authors though so perhaps other will have a different view.

Will Pearse

Will Pearse

Like Sarah, I like these authors (and I know Lynsey does too!), so perhaps this is going to be a bit of a biased PEGE. I view the essential idea of this paper as defining the idea of a tolerance niche: conditions where a species can just-about survive, but can’t form a self-sustaining population. I buy it, and think it’s a nice idea and a great paper.

Indeed, I think similar ideas have been floating around in population biology for some time. We have source populations, that fire off propagules into the meta-community, and sink populations, where propagules arrive, individuals persist, but there’s a net loss of individuals and so that population can’t sustain itself. These concepts have really helped population biologists think about meta-community dynamics, and as we try to link macroecology more intimately with local-scale abundance changes and interactions, it seems sensible to conceptually link these concepts.

I wonder if we can go a step further, and stop treating different parts of the niche (fundamental, realised, tolerance, etc.) as discrete boundaries, and instead be up-front in acknowledging that we know species do better in certain parts of their niche than others, and maybe try to quantify that. Essentially, just have some value (why not fitness) that changes throughout niche space, and acknowledge that, in some parts of niche space, fitness will be so low that a population won’t be sustaining. Indeed, such an approach (borrowing heavily from Chesson) would let us handle realised vs. fundamental in a much more intuitive way, because we could distinguish between niche differences and fitness differences when trying to understand whether species can coexist. Because, as I’m sure we can all agree, parameterising a fitness function across niche space would be really, really tractable and easy to do :p

Hopefully the above makes sense; I have a very serious case of man flu!

Lynsey McInnes

Lynsey McInnes

This paper touches on plenty of topics that we have covered in different guises here at PEGE, with a perhaps more applied angle than most. In essence, the authors seem to be drawing attention to the potential importance of a kind of buffer zone of conditions that species could survive in beyond their current distributional limits (the tolerance niche) and how this zone might be extremely important in mitigating climate change induced species’ disasters.

The idea seems pretty reasonable and meshes well with experimental studies that find that translated populations can make it in conditions not found anywhere within their range. The authors also showcase a brilliant dataset of naturalised and garden centre/botanical garden populations of a plant species in the eastern US. The inclusion of this data lifts the paper from one based on loose concepts to one with real results; that was nice!

However, I do still worry how ‘useful’ the concept of a tolerance niche is going to be beyond these plant examples. In effect, the authors are creating an additional category of niche that in most cases is going to be quite difficult to identify? I would have liked to have seen one additional step to go the figure one and that would be to investigate traits that predict the extent and/or location of this tolerance niche. For instance, the authors draw attention to the distinction between short- and long-lived species, but are there any other distinguishing features? These could be along the lines perhaps of large range (probably also has a bit of tolerance niche), restricted range endemic (probably doesn’t), is part of a complicated food web (probably doesn’t have much of a tolerance niche), most kinds of generalist (probably do have tolerance niches). The next step, as the authors emphasise, is where is the tolerance niche located in relation to the realised niche and how easy is it to get to?

The above just gave me the nagging feeling that the tolerance niche concept might be quite difficult to implement as, like everything macro- it seems (I’m having a down on general patterns week), these things depend on so many other things: landscape structure, biotic interactions, the usual suspects. So, while the concept of the tolerance niche could provide US with a kind of buffer so that we can worry less about species’ survival (they can probably tolerate a bit more heat, drought, what have you) than they currently do, it seems like a difficult concept to draw strong or helpful conclusions from across broad taxonomic or spatial scales.

In conclusion, this was a well-written, thoughtful paper, but I am not convinced that the new concept and piece of jargon are robust or flexible (can something actually ever be robust and flexible?) enough to be rolled out very widely. As always, its a data problem…

Phylogenetic trait-based analyses of ecological networks

Rafferty, N.E., and Ives, A.I. Ecology (in press). DOI:10.1890/12-1948.1. Phylogenetic trait-based analyses of ecological networks

By Alvesgaspar (Own work) [GFDL or CC-BY-SA-3.0], via Wikimedia Commons

An animal and a plant, or a plant and an animal. They’re all in a phylogeny, somewhere, right? By Alvesgaspar (Own work) [GFDL or CC-BY-SA-3.0], via Wikimedia Commons

Will Pearse

Will Pearse

There are relatively few studies of ecological interaction networks that use phylogenetic information, and so this study, which no only does so but also suggests a new method for doing it, is great.

Anthony Ives is constantly developing new methods that are useful to eco-phylogeneticists and ecologists in general, and this paper is an excellent example. Phylogenetic linear mixed models are a way of simultaneously examining trait and phylogenetic information, and strike me as an extension of Ives’ earlier work with Matt Helmus. I love these methods; they allow us to answer questions we’re actually interested in (what determines species interactions) using phylogenetic and trait data. They don’t just look at a property of our data (like phylogenetic dispersion) and then force us to infer from that other properties of the system. My only criticism (which is better communicated by Nate Swenson) is we should go further – why collect phylogenetic information if we only use it to validate trait data? I, probably unfairly, want to shift the question to ‘what determines how species interactions evolve‘.

I think the interaction network literature is filled with cases of people trying to find unifying, abstract aspects of structure – motifs. I wonder if this is because the phrase ‘interaction network’ can cover so many kinds of interactions (pollinators, herbivores, competitors, etc.) in so many different taxa. Maybe eco-phylogeneticists can help, and there are over-arching phylogenetic patterns that can unify all these different systems and approaches. Every organisms on Earth fits into the Tree of Life somewhere, and that makes every single interaction network study, be it of bats or bell-flowers, comparable in some way. Which can only be a good thing!

Lynsey McInnes

Lynsey McInnes

I was really excited about this paper when I chose it. Traits, phylogenies, my pet interest ecological networks! I have the feeling the paper is really good, but I have to say I struggled with it. I think I dove too quickly into the deep end. Maybe I should have gotten more comfortable with the network literature or the traits on phylogenies literature, but I still haven’t learnt to do things like that…

Across biological sub-fields, everybody knows that species’ interactions matter, but, at least in the fields I have most experience of, namely macroecology and macroevolution, explicitly incorporating the effect of species’ interactions (or making them the point of an analysis) is only a very recent development. I think this means that any advance is a good one (and I feel like we’ve mentioned this a number of times before on PEGE).  So, in that respect, this paper is neat. It takes a well-studied, tractable set of plant-pollinator interactions and attempts to parse out the reasons underlying the different communities: do traits or relatedness underlie them? The authors make the case that methods such as theirs can help predict how guilds of species will fare under climate change as  it allows them to anticipate whether phenological mismatch will take hold or whether, in the pool of the other guild, species exist that can match advancing phenologies. Admirable.

I guess the missing link as I see it can be surmised from the title of the paper – ecological networks. What about evolutionary responses? Is it necessary to consider that mismatches might be ameliorated by co-evolutionary responses to environmental change? Is the timescale too short? Will there be less pressure for evolutionary change if, for the plants for example within the pollinator pool there are species ready to pollinate them following their flowering advance. Perhaps teasing apart this additional potential response will be a feature of a subsequent paper from these guys.

I also wonder how space affects these patterns. How do patterns and expectations change as one investigates multiple populations across a larger region? How does local adaptation affect responses? What about variation in the available plants/pollinators across space? What about gene flow among populations? How might one go about incorporating traits, phylogeny and interactions with intraspecific variation and space? Is that too much to consider at once?

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