External morphology explains the success of biological invasions

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Azzurro et al. 2014 External morphology explains the success of biological invasions. Ecology Letters 17: 1455-1463.


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Zarah Pattison

There is rarely a shortage of papers attempting to explain why particular species are more or less invasive than others. Since Charles Elton’s seminar work in 1958 (The Ecology of Invasions by Animals and Plants) there has been a rapid increase, particularly in the last 20 years, in publications surrounding the topic of invasion ecology. The silver bullet to help prevent invasions would be to determine which characteristics contribute most to invasion success and therefore enable us to predict the seriousness of an invasion for prevention and management. Azzuro et al. (2014) offered something a bit unique in their attempt to explain invasiveness by using the external morphology of species, fish species in this instance.

The aim of this study was to explore whether morphological traits could explain the abundance of introduced fish species entering the Mediterranean Sea via the Suez Canal. The Mediterranean Basin is suggested to have a monopoly of vacant niches, which may be contributing to the successful establishment of invasive species therein. Therefore the use of species morphology as a proxy for its ecological status in a community, could explain niche availability and the potential population increase post establishment.

Our initial thoughts were positive. The paper was written well, succinct and enjoyable. A large data set was used in an analysis which none of us had expertise in, but it was still clear what the authors were trying to achieve. (Very) basically a polygon encompassing the morphological space of the native fish community was used and the traits of non-native fish species were plotted across the native morphospace. The results showed that invasive non-native fish species were more abundant either outside or on the outer perimeter of the native morphospace where niche occupancy was low. Non-native species morphologically similar to native species, were less abundant and less likely to establish.

The paper definitely added to the breadth of our invasion ecology knowledge. However, like most studies in invasion ecology, the results are difficult to generalise. Negative caveats of many invasion ecology papers focused on specific species are just that: species specific and not amenable to generalisation. This can be frustrating from a conservation point of view. The authors themselves discussed the limitations of this study particularly in the case of invasive non-native lionfish (Pterois spp.) which has a rather unique morphology. Another point raised was that environmental conditions were not taken into account in this study, particularly fishing quotas which could lead to fluctuating populations regardless of native status. Additionally, life history/functional traits, which are used in many plant invasion studies, were not considered.

Overall the paper delivered its aim, but the title is very confident. Perhaps “External morphology can additionally explain the success of species specific biological invasions” would be more appropriate. However, we can’t test for everything in a study (we all know this!) and we all agreed this was a good piece of interesting science.

Join us next week where Eilidh McNab will lead a discussion of a paper recently published in Biological Conservation entitled: Field work ethics in biological research.

Modelling competition and dispersal in a statistical phylogeographic framework

Ranjard et al. 2014 Modelling Competition and Dispersal in a Statistical Phylogeographic Framework. Systematic Biology. 63: 743-752.

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Figure 1 from Ranjard et al. The three scenarios are based on the landscape and colored locations displayed at the bottom left.’ Can you guess which says which?


Will Pearse

The authors have put together an impressive method that detects whether competition and (consequentially?) biased dispersal can be detected using data on species’ present-day distributions and phylogeny. Does the method work? Well, that depends on whether you agree (1) with the model, and (2) that present-day distributions map in a 1:1 fashion onto past processes/distributions.

I’m pretty sold one (1), but then again I have neither the time nor the capacity to go through the maths in much detail! The introduction was interesting to me, since it smelt a little bit like it invokes the community phylogenetics sin everyone loves to hate; I would get mercilessly slaughtered for invoking competition or co-existence on the basis of niche overlap. Inferring about past processes at this scale, however, is a different beast – we’re data and method limited, so I think it’s completely acceptable to start putting testable models out there. Moreover, unlike those sinful community phylogenetics papers, this paper has a testable, verifiable model.

My only real problem comes with (2), and I somehow doubt the authors would disagree with me. The island case-study they use is a great one, and I think the model works perfectly for data like that where we’re dealing with very discrete, very tractable movements between patches of land. However, I think some care would have to be taken when dealing with continental distributions where variation in habitat type will mask the dispersal events the authors are looking at. Again, I think the authors are more than aware of this, and I don’t think they intend this method to be fit to GBIF data or something, but I’m interested to see if this could be tried with some modifications. Combined with this paper (which we’re covering soon), it’s a good time to be a phylogeny nerd – the methods are coming in, so now we need to just use them 😀


Lynsey McInnes

Lynsey Bunnefeld

I enjoyed this paper, even though it made my brain explode. It is a funny mix of idealistic and hopeful. The authors set up a framework to detect the effects of dispersal and competition on genealogies. They argue that population expansion and establishment (eventually speciation) are processes affected by dispersal ability (here characterised by an overall rate of dispersal away from a source population and a dispersal kernel shape parameter), but also by competition (here characterised by how much an already occupied location is refractory to further occupation). The authors argue that researchers have focussed on the effect of dispersal (generally characterised as distance among sites rather than intrinsic organismic traits) while ignoring the effects of competition (despite a large body of ecological literature on the effects of competitive exclusiveness). This is probably true and is likely due to the fact, as the authors note, that it is pretty damn hard to capture the effects of competition adequately.

The authors make a start here by setting up a relatively simple model to find out whether genealogical shapes and geographic patterns of occupancy suggest evidence for biased dispersal among sites (more to closer sites) and competitive exclusion (longer branches to the present as fewer sites are available for colonisation/establishment). They find evidence for both in a bush cricket genus endemic to the Hawaiian archipelago and their sensitivity analyses generally suggest they are able to detect competition when it has had an effect.

So far, so good. I don’t really feel qualified to destroy their methodology, so I’m not quite going to. I imagine there are better way to characterise these processes and that there are probably alternative explanations for the signals they recover, but we won’t dwell on them here.

My biggest problem with this paper and I am not at all sure whether it is not just me being dim is that I’m not really sure at what time-scales this method is expected to perform well. The authors jump back and forth between species and populations. Considering populations, I doubt you would be able to reconstruct bifurcating phylogenies with the resolution needed to detect longer/shorter terminal branches. Indeed, bifurcating trees are not the expectation and only populations geographically very far away from each other are expected to be isolated enough that gene flow from neighbouring populations would not homogenise gene pools. I.e. if a lot of individuals from the source population are dropping on to a second population, they are unlikely to be excluded unless they are so locally adapted to some place else that the environment kicks them out rather than conspecific competitors? Perhaps this is what the authors are trying to characterise anyway, and I am just misunderstanding their definition of competitor/competition.

I think my concern is that any successful model of genetic variation in space should probably take into account dispersal ability, competitors, but also environmental variation (this might be abiotic factors, but also biotic factors such as interspecific competition or intraspecific competition (if populations of conspecifics vary according to other aspects of the environment).

Again, I might be confused, as my head has yet to settle on whether it thinks according to bifurcating trees in macroevolutionary time or networks in population genetics time. My hunch is the authors have tried to operate across both time-scales, and I am not sure it works (or at least I can’t quite grasp it).

I’ll leave it there. Any help, much appreciated!

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