The long-term fitness consequences of early environmental conditions

 

(15) bighorns


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Adam Hayward

The conditions which an individual organism experiences during early development have a profound effect on their success in life. For example, poor maternal nutrition may lead to underdeveloped or small offspring, which are likely to have reduced fitness in later life. A host of studies in the lab and field have shown that the quality of environmental conditions (nutrition, population density, climate, predation, infection) during early life are strongly associated with body mass, survival, ageing rates, reproductive success, disease resistance and lifespan.

There are two (non-mutually exclusive) explanations for why early-life conditions influence later performance. First, a non-adaptive explanation: if conditions are good, development is good and the individual is well set-up for a successful life; if conditions are bad, development is sub-optimal in some way and the individual struggles. This is known as the ‘silver spoon’ hypothesis (although The Who would call it the ‘plastic spoon’ hypothesis), and under this scenario, a bad start in life always leads to poor performance in adulthood. Second, an adaptive explanation: the individual senses its environment during development, assumes that it reflects the environment it will encounter later on, and develops in such a way as to maximise its performance under those conditions. Under this scenario, if conditions match during early and later life, no matter how bad those conditions are, individuals will have higher fitness. This is the ‘predictive adaptive response’ hypothesis, and it has been a popular (but controversial) explanation for the origins of metabolic disease in humans.

Few studies have tested for predictive adaptive responses in long-lived wild animal populations, because it’s difficult: such a test requires measurement of environmental conditions in early life, plus measures of both environmental conditions and performance in later life. Gabriel Pigeon and colleagues, from the University of Sherbrooke in Canada, used more than 40 years of data on a bighorn sheep population to test for predictive adaptive responses in a recent paper. They concentrated on female sheep, and asked whether (1) probability of weaning a lamb and (2) probability of survival in a given year were dependent on early-life environmental conditions, current conditions, and an interaction between the two. They tested 12 different environment variables, including population density and a large number of climatic variables (although only density was important, with the hypothesis being that higher density = more competition = poorer nutrition).

They ran a large number of models for both response variables, including linear and non-linear effects of early-life variables and crucially, interactions between early-life and current conditions. They also attempted to separate out within- and between-cohort and –individual effects, which was rather cool, using a really nice approach developed a few years ago. In short, it was pretty thorough.

Population density at birth explained 32% of variation in weaning success: females born in high density years were less able to wean lambs. There was also an interaction with current population density: in high-density years, females were less likely to wean lambs, but this was only true of females who experienced high density around birth themselves. In other words, experiencing poor conditions in early life made individuals less able to deal with poor conditions in early life (Figure a below). However, population density at birth was very weakly (and non-significantly) associated with survival (Figure b below).(15) Pigeon Fig 2

There were some interesting (if rather mind-bending) results concerning how the current population density influenced weaning success, illustrated below (in the SI, where I went digging, so you/other PEGE members don’t have to!). In (a), each line represents the change in weaning success with increasing current density in a given cohort, and the redder the line, the higher the early density was in that cohort. There are between-cohort effects, because the cohorts are responding differently to current density; however, there is no average within-cohort effect, because the average cohort would show a line with a slope of approximately zero. In (b) each line represents an individual. There are between-individual effects, because individuals who experienced higher current density had lower fitness, but there are no within-individual effects, because all individuals responded in a similar manner to increases in density. This suggests the absence of individual plasticity, and that density affects all members of a cohort in a similar way.

(15) Pigeon S1

The main conclusion of the paper is that analyses did not support a predictive adaptive response. This is perhaps not surprising, given similar conclusions in a recent(ish) meta-analysis of experimental studies in plants and (short-lived) animals and even some not-especially-convincing (OK, it’s mine) stuff on humans using data on climate and famines. Predictive adaptive responses are an incredibly intuitive and lovely hypothesis at first glance. I’ve found this when teaching undergraduates: given the question ‘how can low nutrition during gestation lead to diabetes in later life?’, one or two will always come up with the idea of predicting the future environment. Evidence in support of such responses are rare though. An interesting question to ask is ‘how predictive is predictive?’ Do the fitness benefits of developmental plasticity need to arise when you’re halfway through life? Reaching sexual maturity? Surviving to weaning/fledging? Surviving the pre-natal period? All have been suggested, but the best examples of predictive adaptive responses (for me) are very short-term responses: one in voles, and one in humans. Are they predictive or even adaptive? It’s up for debate.

 

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Fundamental Theorems of Evolution

Queller 2017 Fundamental Theorems of Evolution. The American Naturalist. 189: 345-353.

Figure 1 from Queller (2017) illustrating the relationship between the Price equation and four other fundamental equations of evolutionary biology. An arrow from one equation to another indicates that the latter can be derived form the former. Variables and subscripts are explained in the main text.


 

  Brad Duthie

Conceptual unification of disparate phenomena is a major goal of theory in the natural sciences, and many of the most revolutionary scientific theories are those that have shown how seemingly disparate ideas and observations follow logically from a single unifying framework. The most momentous of these theories include Newton’s unification of gravity and the laws of planetary motion, Darwin’s explanations of adaptation and biodiversity as following from natural selection and descent with modification, respectively, and Einstein’s general relativity unifying gravity, space, and time. In all of these examples, theory has changed how scientists understand the world by revealing a fundamental concept, the consequences of which encompass an entire field of study.

Perhaps to this list of discoveries we should include the unifying equation of George Price, which, in a recent paper in the American Naturalist, David Queller argues to be the most fundamental theorem of evolution. The Price equation as a unifying framework has been a subject of recent interest both within evolutionary biology and across disciplines from mechanics to music. At its core, the Price equation is a unifying framework for understanding any correlated change between any two entities. Queller proposes it to be fundamental because it encompasses all evolutionary forces acting on a population, and because it can be used to derive other less general equations in population and quantitative genetics, all of which require stricter assumptions about the evolutionary forces and environmental conditions affecting entities in the population. The Price equation includes two terms to describe the change in any trait Δz.

The first term isolates how a trait (z) covaries with fitness (w) for entities (i), and encompasses the evolutionary processes of natural selection and drift. The second term encompasses everything else that affects trait change (often called the ‘transmission bias’), such as mutation or background changes in environment. Intepreting the Price equation can be a bit daunting at first, perhaps in part because of how abstract the entities (i) are — representing anything from alleles, to unmeasured genotypes, to organisms, to even groups of organisms as the situation requires. Likewise, traits (z) can be any aspect of phenotype associated with such entities, including fitness (w) itself!

It’s here where Queller’s synthesis really shines, as he carefully walks the reader through how Price’s abstract equation can be used to derive multiple other less fundamental equations in which variables represent something concrete and measureable in empirical populations. These equations include Fischer’s average excess equation describing allele frequency change in population genetics, the Robertson and breeder’s equations of trait change in quantitative genetics, and Fischer’s fundamental theorem of evolution. In all cases, Queller notes the additional assumptions that are required to use these equations, particularly that the second term of the Price equation equals zero meaning that no transmission bias exists.

In our discussion, we reviewed the Price equation and its importance in evolutionary biology. We noted the interesting timeline of the discoveries of the equations; although the Price equation is fundamental in the sense that all of the other equations that Queller cites can be derived from it, it is also the most recent equation to be published. All of the other equations, which serve fundamental roles in population or quantitative genetics, were published decades before Price’s equation and have been used regularly by specialists in these sub-fields. This led us to talk a bit about what we value from theorems in evolutionary biology, and whether all of these theorems are better taught as independent solutions to particular problems in evolutionary biology, or as sub-components of a more fundamental framework grounded in the Price equation. Finally, we discussed the second term of the Price equation, noting that all of the equations that can be derived from the Price equation assume that this term equals zero. This effectively isolates natural selection, or some partition of natural selection, but ignores processes that are known to be important for trait change, particularly changing environment.

An extended discussion of Queller’s paper can be found on Brad’s own website.

Ecosystem restoration strengthens pollination network resilience and function

Kaiser-Bunbury et al. 2017. Ecosystem restoration strengthens pollination network resilience and function. Nature 542,223–227

Figure 1 from the paper. The island of Mahé with study sites and pollination networks (for more details see the paper itself).


Kat Raines

I chose this article as it merges my past and present research areas. I currently work in radioecology, focussing specifically on pollinators in Chernobyl but previously I worked for three years in the Seychelles archipelago on invasive species projects focussing on everything from plants to mammals. I thought this paper looked interesting (although slightly out of my research field) and attempted to answer some of the big questions relating to ecosystem restoration in response to the removal of invasive species.

The aim of this paper by Kaiser-Bunbury et al. is to examine whether ecosystem restoration through the clearing of invasive plant species affects pollination networks. This study was undertaken as a community field experiment on the island of Mahé, Seychelles. The Seychelles archipelago is ideal to conduct invasive species projects as it is relatively isolated from other islands and main land Africa and Mahé offers mid altitude inselbergs as discrete sites from which 8 were selected for this study. Half the inselberg sites were cleared of invasive species and therefore referred to as restored and compared to sites that had not been restored. They found that restoration markedly changed pollinator numbers, behaviour, performance and network structure.

The authors noted that the removal of dense thickets from the restored sites could have had an effect and we wondered exactly how much this would affect pollinator’s ability to even see flowers and whether it was then appropriate comparing sites with dense vegetation to sites with a greater number of clear areas therefore increasing the visibility of flowers.

This study found that interactions in restored networks were more generalised and therefore indicate higher functional redundancy therefore making these networks more robust. This concept was a main point in the discussion for the group as we debated whether it was better to have a high number of specialised pollinators or whether it was better to be more generalised and to what extent this matters on an isolated island with a high number of endemic species. It has been shown that specialist species suffer from habitat loss the most and tend to go extinct first whereas more generalised species are more robust therefore increasing the ecosystem’s resilience. We also wondered if these findings could be extrapolated and applied to other regions and habitats as increased pollinator interaction is obviously a very important outcome for ecosystem restoration.

In conclusion we enjoyed the paper and were impressed with the amount of effort that went into data collection for the plant-pollinator networks. Ecosystem restoration is a powerful tool in conservation but it is relatively unknown what the effects of restoration are on ecosystem functions so this paper is a notable addition to that knowledge base.

Sexual segregation and flexible mating patterns in temperate bats

Angell et al. 2013 Sexual segregation and flexible mating patterns in temperate bats. PloS One. 8(1): e54194.  

Figure 3 from the paper. Posterior distributions for paternity probabilities at the group level. Posterior distributions for the probabilities that fathers (at the group level) came from roosts in the (blue) upper-elevation, (yellow) mid-elevation and (green) low-elevation, and from (red) swarming sites. For (A) low-elevation offspring (the inset graph shows the Wharfedale roost posterior distributions in greater detail), and (B) mid-elevation offspring. 


Following the last two discussions, this week’s paper was selected on the basis that it used non-lethal DNA collection techniques to determine how intra-specific niche separation influences mating patterns.

Matthew Guy

A large number of temperate bat species, including Myotis daubentonii, display sexual segregation along altitudinal gradients. In these species, mating usually occurs during autumn swarming events. However, at the upper limit of the female range, Senior et al. (2005), found evidence of summer mating within roosts where dominant males are tolerated by females. Using the same population of M. daubentonii, this paper extends this work to identify if this is the dominant mating strategy throughout the altitudinal range of the species and, if not, can the differences in mating strategy be explained by foraging habitat quality?

DNA was extracted from wing punches and a novel Bayesian approach was used to assign the probability of parentage of juveniles from low altitudinal roosts to males from different roosting sites and swarming sites. During our discussion, nobody had a lot of experience with the genetic methods used and we found the results section difficult to read. However, the figures clearly demonstrate that the probability that these juveniles are fathered by males from anywhere other than swarming sites is very low. We thought that this was a really nice example of how figures can be used to give a clear overall impression of complex data, especially for the lay person. This result was in contrast to that found by Senior et al. at mid-elevation roosts suggesting a flexible mating strategy over an altitudinal gradient.

Foraging habitat quality was assessed using bat activity, weight and temperature, all of which declined significantly with altitude. The paper surmises that by excluding males from roosts, pregnant and lactating females can reduce intra-specific competition for the high-quality foraging grounds. However, the carrying capacity at intermediate sites is lower and so supports fewer females. In these areas, the thermoregulatory benefits provided by males in the roost outweigh the costs incurred by additional competition. The paper pulls these results together qualitatively, stating that the mating strategy is adapted to the social structure, which, in turn has evolved in response to environmental conditions at a given altitude. However, we felt that an analysis of prevalent mating strategy (i.e. probability juveniles were fathered at swarming events) within individual roosts and local foraging habitat quality together would address the second part of the research question more directly.

Over all, we felt that the paper was well written and, in combination with the Senior et al. paper results, presented an interesting behavioural response. However, the scope of the paper is fairly limited, largely due to a combination of studying a single species and developing ideas of a previous single study. One potential way to widen the papers appeal could have been to incorporate a discussion on how the novel genetic technique developed in this study could be applied to other species populations.

The paper ends by posing the question: Is this flexible mating behaviour capable of dealing with changes in prey distribution and roost microclimate predicted by climate change? Our discussions came to the conclusion that climate change could cause a decrease in the success rate of mating during autumn swarming events, potentially reducing gene flow. An increase in temperature would drive prey species upstream, where the higher proportions of more turbulent water would reduce the quantity and quality of the forging grounds. This could lead to a reduction in females within local nursery roosts making them more reliant on males for roost thermoregulation, and hence, an increase in the prevalence of summer mating. We thought that actually addressing the question, at least to some extent, in the discussion would have made for interesting conclusion and again potentially widen the papers appeal.

Field work ethics in biological research

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Costello et al. 2016. Field work ethics in biological research. Biological Conservation. 203:268-271.


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Eilidh McNab

This week’s journal club, whilst focussed on a single article, was also a chance for the group to have a wider discussion around the ethics of field work.

Historically much natural history research has been undertaken through ‘collecting’ specimens – i.e. killing and preserving individuals. The scientific descriptions of most species on the planet come from ‘type’ specimens held in museums; the individual(s) from which the species is defined and named. Early ornithologists went out birding with shotguns, not binoculars. However, in recent decades this view of biological science has been gradually replaced by non-lethal methods (such as camera-trapping, DNA analysis, radio-tracking, etc.) and the use of fatal collecting methods (certainly amongst vertebrates) is growing increasingly rare (aside from e.g. medical research, which I will not discuss here).

In this week’s paper, Costello et al. (all editors of the journal Biological Conservation, in which the paper is published) confront the ongoing issue of articles submitted to the journal that have, in their view, involved the unnecessary lethal collection of vertebrates, and have therefore been rejected for publication. The three recent examples that the authors discuss involved fish; in two instances researchers employed the use of gill-nets (which often lead to mortality of other non-target species as well), and in another there were very high rates of mortality due to tagging in a capture-release study. Importantly, in all instances the papers were not investigating a novel idea; instead they were simply showing well-understood phenomena in a different location. A table presenting a checklist of considerations for respectful conduct during field sampling highlights this as an important point; any negative impacts must be justifiable in terms of the advancement of scientific knowledge. However, as was pointed out in our debate on this paper, often it is not known what the results may be in advance of a study! Even fairly closely-related species can react very differently, and without first carrying out the field research this can’t necessarily be predicted.

Whilst lethal collecting or increased mortality due to methodology are the main topics, the paper discusses a number of other important issues surrounding field research. One of the first sections highlights the “uneven treatment of species”; and whether the relevant authorities (be they university ethics committees, or government officials) are more likely to allow lethal collection of one taxa over another. They ponder whether the case studies discussed involving fish would have been given permission had it been birds, mammals or reptiles involved – most likely not. This led to some discussion in the group about how much we understand about the way fish react to stimuli; a recent study looked at the use of compounds commonly used to euthanise laboratory zebrafish specimens, which was assumed to slowly send them to sleep. This compound was actually shown to drastically alter their behaviour prior to death, forcing the normally shade-seeking fish out into brightly lit areas of the tank. If this is the behavioural response, can we truly understand how the fish are reacting internally? And is it really as humane as was formerly thought?

Another important topic discussed within the paper was the impacts to non-target species that may result from any programme of fieldwork. This could include trampling (of vegetation or of e.g. invertebrates), or the transfer of invasive plant species or diseases (such as the fungus that causes white-nosed syndrome in North American bats, which has wiped out millions of individuals; the disease may have been inadvertently introduced by European-based cavers or bat ecologists).

The paper finished with a number of different solutions to the issues discussed. This included the use of low-impact methods where at all practicable, such as camera-traps, hair and faeces collection, drones, and observations. They also highlighted the importance of applying the ‘precautionary principle’ to research work, and to consider the possible impacts to the whole ecosystem being studied, not necessarily just the target species.

What is not really discussed in the paper is the perspective of different ‘types’ of researcher; for example a virologist may have a different view of lethal collecting to a conservation biologist. Another point that was brought up during our discussions, but is again not mentioned in the paper, is the cultural significance of certain organisms. Whilst a university ethics board may approve the lethal collection of a species, if it is viewed as particularly important, maybe even sacred, to native peoples in the study area, this should certainly be an important consideration for any researcher.

Whilst the paper is only three pages long, it succinctly covers a range of key considerations when planning any programme of field work. We concluded that this is an important paper to remind scientific researchers not just to fully explore all potential sampling methods before resorting to lethal collecting, but also to consider other potentially negative impacts that could be caused by the study. For example disturbance to other non-target organisms and the spreading of invasive species due to researcher movements should be considered prior to any research work. Whilst there were some comments that the paper may be viewed as a little ‘preaching to the converted’, the fact that multiple papers have been submitted to Biological Conservation that do not meet the ethical standards set by the journal highlights that it is still an important topic to discuss. This importance is highlighted by the fact that this article is one of the most downloaded from the journal in the last 90 days.

Join us this Friday when Matt Guy will lead a discussion on a recent paper in PloS ONE by Angell et al. entitled Sexual Segregation and Flexible Mating Patterns in Temperate Bats.

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0054194

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.

Mycorrhizal status helps explain invasion success of alien plant species

 

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


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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.

Evolution of dispersal strategies and dispersal syndromes in fragmented landscapes

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Cote et al. Evolution of dispersal strategies and dispersal syndromes in fragmented landscapes. Ecography, in press. (Image from http://sarinasunbeam.deviantart.com/art/Seed-Dispersal-Infocomic-606992414)


Lynsey McInnes

Lynsey Bunnefeld

PEGE journal club has morphed into a hybrid in-person/online journal club hosted by the University of Stirling. One half of the PEGE admin has moved to Stirling as a lecturer (me) and is hoping to harness the insights of the department as a whole when discussing matters in the PEGE realm.

We are still straightening out details and may migrate to a new website soon, but in the meantime, a rotating series of bloggers from the Biological & Environmental Sciences department at the University of Stirling will write up a short blog summarising a paper and our discussion every two weeks. As before, we’d be really happy to hear your thoughts on the paper and our interpretation in the comments below. In case you are wondering, Will Pearse is now an assistant prof at Utah State University and we’re even still friends! 

This week, I (Lynsey) chose the paper and committed to writing up our discussion. What follows is my own interpretation of events, apologies if I have misrepresented anything we discussed.

 

I chose a paper by Cote and colleagues from a recent special issue on fragmentation published in Ecography. I was excited about this paper as it promised to integrate three areas of interest of mine: space (fragmentation), intraspecific trait variation (evolving strategies) and species categorisation (dispersal syndromes). However, these grand promises proved problematic. To summarise our discussion: we came out sceptical of the framework proposed by the authors to integrate these three angles; we deemed it infeasible at best and foolish at worse.

Dispersal is a fiendishly difficult phenomenon to get your head around. Do we mean dispersal capacity or propensity? Is a mean or a kernel adequate to categorise the dispersal ‘ability’ of all members of a species? How much intraspecific variation in dispersal ability exists? Is this variance constant? How does it evolve? The authors acknowledge all of these issues and propose to address them head on. They put forward the idea of dispersal syndromes with covarying traits that either enable, enhance or match – the authors thus do not consider dispersal ability as a trait, but rather an emergent feature that comes about as a result of a bunch of possible traits. So far, so interesting.

Where the paper crumbles (for me) is that they go on to overlay the complexity of categorising dispersal syndromes on top of a fragmented landscape. I’m no expert on the process of fragmentation, but I do know it’s a fiendishly complicated topic too. The authors list four ways in which fragmentation modifies a landscape: it reduces habitat quality, increases number of habitat patches, reduces patch size and increases isolation among patches. Each of these four effects are likely to interact with dispersal capacity AND propensity in non-linear ways. And that’s without even considering these effects as selective pressures promoting the evolution of increased or reduced dispersal.

And so we got stuck. We didn’t feel that we have a good grasp (even for a single snapshot of time) of how to adequately characterise dispersal (although we all agreed it was an interesting problem) and so we were hesitant as to the utility of a framework of predicting how dispersal ability (or the traits that covary with it) are likely to interact with or evolve in response to a fragmenting landscape. A pragmatic solution we came up with was to think about holding some variables constant and looking at the evolution of dispersal strategies in those contexts (for example, varying only one of fragmentation’s four effects, not all four).

To conclude, the authors’ aims were admirable, but we were unsure whether we are really in a position to populate their proposed framework at the moment and, even if we were, we were unsure what generalities could emerge: because dispersal ability is a complex phenomenon we were not convinced a framework could be developed that robustly predicts how it might respond and evolve in species found on fragmented landscapes. Are there not too many unknowns and idiosyncracies of species * landscape? Saying that, we would be happy to be proven wrong!

Next week, John Wilson has chosen a recent paper from Ecology by Menzel et al for us to discuss: Mycorrhizal status helps explain invasion success of alien plant species. Join us!

 

Rapid diversification associated with ecological specialization in Neotropical Adelpha butterflies

Ebel et al. 2015 Rapid diversification associated with ecological specialization in Neotropical Adelpha butterflies Molecular Ecology 20: 2392-2405.

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Figure 1 from Ebel et al. “Adelpha wing pattern and species diversity. (a) Examples of the nine Adelpha mimicry types. The number above each image indicates the number of species and subspecies with the pattern. From top left: A. iphiclus iphiclus, A. naxia naxia, A. thesprotia, A. cocala cocala, A. salmoneus colada, A. boreas boreas, A justina justina, A. zina zina, A. levona, A. rothschildi, A. epione agilla, A. lycorias wallisii, A. ethelda ethelda, A. leuceria juanna, A. gelania gelania, A. seriphia barcanti, A. mesentina mesentina, A. melona deborah. (b) Five species have a unique wing pattern. From left: A. seriphia egregia, A. demialba demialba, A. justina inesae, A. zina pyrczi, A. lycorias lara. (c) Adelpha species richness across the Neotropical region (modified with permission from Mullen et al. 2011).”


Lynsey McInnes

Lynsey Bunnefeld

This was a funny choice from Will as it seems much more up my street than his. Indeed, my colleague James Nicholls and co. are developing similar phylogenomic methodologies to look at rapid diversification within Inga. James uses a targeted sequence approach that seems to also have worked pretty well. But I am too lazy to make this a post about the pros and cons of different genomic techniques.

In fact I’m not sure what to make this post about. I’m not sure what I think about this paper. On the one hand, it clearly represents an amazing amount of work – processing the samples, doing the bioinformatics and the bazillion versions of phylogenetic reconstruction and the assessment of missing data effects. I could not find any details in the main text, but they also appear to have dated the tree (and apparently better than previous attempts). And then they find neat relationships between toxicity of a common host plant family and convergent mimicry patterns across a variety of species. It’s a really nice story.

On the other hand, I am still not 100% convinced by the robustness of the various available methods of character state reconstruction (not discussed in the text) or of diversification rate shift detection (discussed a little bit). No doubt about it, a better phylogenetic hypothesis helps make these tests more meaningful, but they still rely heavily on accurate dating (at least relatively) and on some degree of rate conservatism across the tree(s) – or else you might infer different rates on every branch.

Grumble grumble. I am consistently amazed that these methods, that seem so dodgy, often recover relationships that make ecological sense (as here). So I should probably stop complaining and concede that they might be recovering real patterns (at least now that the phylogenetic hypotheses are more robust and the effects of missing data or rubbish dating priors are better characterized).

So where to next? Should the focus be on improving these methods so it is easier to detect real patterns, should it be on collecting more data for interesting clades to fill in missing data (species, traits) or should it be on collating multiple such datasets to look for concordant patterns across clades? For instance, here, what are the plants doing? To answer that we need to consider the interaction of multiple plant families with a single butterfly genus. How do we do that?

And what are the limits of these macro-methods? This butterfly clade appears to be a recent and rapid radiation. How do we look at character evolution and predictors of rate shifts when species might still be hybridizing? Is there real scope to link population and phylogenomics? How quickly will technology and bioinformatics pipelines progress in order to use complete genomes (and tons of them) to answer such questions. My gut feeling is actually not that fast and that the next ten years or so are going to see a flurry of methods to continue asking these questions with dodgy, patchy data and then, in 10 years, we will have to start over when we are confronted with a whole different kind of dataset requiring a whole different set of techniques.

As ever, exciting times.


Will Pearse

Sorry this post is so late; entirely my fault, not Lynsey’s. This feels like an excellent paper to get back on the horse with, because (as all phylogenetics papers do these days), it makes me feel very old. I feel as if I just popped out for a packet of cigarettes and suddenly the whole world changed – pyRAD? Is that like… PAUP*? What year is it?

And yet, somehow, the problems are the same. We have thousands of loci, but we have to concatenate them. We have a wonderfully resolved tree, but we still have to use the same old ancestral state reconstructions. I’m not criticising this paper, which is excellent, and I’m not even sure I’m criticising the methods, which are the best we can do at present. Yet, somehow, I still feel a bit worried whenever I see any  sort of reconstruction – even (especially?) when I’m doing it myself.

Which is why it’s so nice to see methods being applied with care, and in such great diversity, to a system with strong a priori hypotheses. Above Lynsey asks whether we need new models or more data. It’s easy to look at the grey branches (“we don’t know”) on these phylogenies and think that we need more data, but in reality I think some of that would be gap-filling. The data we have has already cost a lot of blood and sweat, and is beyond a phylogeneticist’s wildest dreams a decade ago – is that not enough? What we need are explicit models that tell us what an adaptive radiation looks like. That does mean a lot more sweat, and it could mean even more data collection than these authors have already done, but without it, we’ll have no broad framework within which to place data-rich case studies such as these.

*in this case, the asterisk stands for “absolutely not”.

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.

phylo_comp_dispersal

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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