Happy 10th birthday, neutral theory!

Rosindell, Hubbell, and Etienne. (2011). The unified neutral theory of biodiversity and biogeography at age ten.

I would argue that neutral theory is not only the most controversial idea, but also the most successful idea to permeate community ecology in the last ten years. A quick keyword search suggests that ~30 ecological papers related to the topic were published in the last year, including some with titles still reflecting the controversy; “Different but equal: the implausible assumption at the heart of neutral theory”. Neutral theory makes a seemingly unreasonable assumption—that species identity doesn’t matter—and yet seems to predict species-area relationships and species abundance distributions as well or better than niche theory does. This made it an infuriating challenge for many ecologists. The number and quality of papers that it inspired—both in support and opposition—are a reminder that disagreement is good for science.

It’s been a decade since the publication of “The Unified Neutral Theory of Biodiversity and Biogeography”, in which Steve Hubbell proposed a controversial model in which coexistence results from drift, dispersal and speciation, rather than ecological differences between species. To mark this anniversary, a review in TREE by James Rosindell, Stephen Hubbell, and Rampal Etienne reflects on neutral theory’s first ten years, and examine the influence neutral theory has had in many areas of community ecology. The authors also note that some of the limitations of neutral theory can be dealt with by extending the classic formulation of the model, so that unrealistic assumptions related to spatial structure, speciation rates, or the zero-sum assumption can be relaxed. The excessive interest in neutral theory’s species-abundance predictions left its other predictions unexamined, and there is still room for tests of how neutral theory informs species-time relationships, modes of speciation, and even conservation decisions.

Despite these accomplishments, the review is remarkably subdued, underlined by statements such as neutral theory is a “good starting point”, a “valuable null model”, and a “useful baseline”. However, it seems unnecessary to state, as some have, that "neutral theory is dead". Its legacy, captured in the final paragraphs, is still incredibly important: “…niches have dominated our attention and left less obvious, but still important processes forgotten… Perhaps the most important contribution of neutral theory has been to highlight the key roles of dispersal limitation, speciation and ecological drift, by showing how much can be explained by these processes alone...”

George Box said it best: “All models are wrong, but some are useful”.

Carnival three-five.

The 35th installment of the Carnival of Evolution is available from Lab Rat. Want to know who said what about evolution? Go to the Carnival.

Ecological interactions and evolutionary relatedness: contrary effects of conserved niches

Over the past several years a multitude of papers linking patterns of evolutionary relatedness to community structure and species coexistence. Much of this work has looked at co-occurrence patterns and looked for non-random patterns of relatedness. The key explanations of patterns has been that communities comprised of more distantly-related species is thought to be structured by competitive interactions, excluding close relatives. Alternatively, communities comprised of species that are closely related, are thought to share some key feature that allows them to persist in a particular set of environmental conditions or stress. This whole area of research is completely predicated on close relatives having more similar niche requirements then two distant relatives. This predication is seldom tested.In a recent paper in the Proceedings of the National Academy of Science, Jean Burns and Sharon Strauss examine the ecological similarity among 32 plant species and tested if evolutionary relationships offered insight into these similarities. The ecological aspects they examined were germination and early survival rates as well as interaction strengths among species. To assess how these were influenced by evolutionary relatedness, they planted each species in the presence of one of four other species varying in time since divergence from a common ancestor, creating a gradient of relatedness for each species. They found that germination and early survival decreased with increasing evolutionary distance. This surprising result means that species germinating near close relatives do better early on then if they are near distant relatives. The explanation could be that they share many of their biotic and abiotic requirements, and these conserved traits influence early success.

Conversely, when they examined interaction strengths over a longer period (measured as relative individual biomass with and without a competitor), they found that negative interactions were stronger among close relatives.

These two results reveal how evolutionary history can offer insight into ecological interactions, and that the mutually exclusive models of competitive exclusion versus environmental filtering do not capture the full and subtle influence of conserved ecologies. Evolutionarily conserved traits can explain both correlated environmental responses and competitive interactions.

Burns, J., & Strauss, S. (2011). More closely related species are more ecologically similar in an experimental test Proceedings of the National Academy of Sciences, 108 (13), 5302-5307 DOI: 10.1073/pnas.1013003108

The bellybutton, biodiversity reserve of the body

Although less recognized--and less glamourous--than most biodiversity hotspots, the human bellybutton harbours it own diverse collection of species, and these species tell us something about ourselves. That's the premise behind the Belly Button Biodiversity Project, which is getting some press for its large-scale sampling of bellybutton bacteria. For interesting discussion about where the data could lead, see Rob Dunn's (one of the researchers) website. His post, including the comments, hints at how much there is to learn about the ecology of human bacteria.

Update: Rob Dunn has now published a book "The Wild Life of Our Bodies", telling more stories of our changing relationships with other species.

Carnival time.

The 34th edition of the Carnival of Evolution is hosted at Quintessence of Dust. Everything from the evolution of perfection to the evolution of small importance will be found there.

White-nose syndrome and wind turbines: why biodiversity matters

Linking ecosystem services to economic benefits is a vital step in connecting ecological research to policy and political action. The UN Environmental Programme’s The Economics of Ecosystems and Biodiversity (TEEB) initiative represents a concerted effort to draw attention to the economic benefits of biodiversity and cost of ecosystem degradation, and to bring together scientists, economists and policy-makers.

Accordingly, Boyles et al. (Nature, 2011) paint a troubling picture about the value of economic benefits that insectivorous bats provide to the North American economy, and the degree of extinction risk they currently face. The authors point out that bats are “among the most overlooked, yet economically important, non-domesticated animals in North America”, and their loss would cost North Americans more than 3.7 billion dollars/year. Given rapid declines in populations due to white-nose syndrome (over 1 million bats killed) and wind turbine fatalities (projected to reach up to 30,000-100,000 fatalities/year as wind turbine installations increase), the authors suggest action can't wait.



Hopefully using the universal language of money helps translate scientific knowledge into political action. After all, bats are only one group of species: imagine the true cost of current rates of biodiversity loss and ecosystem destruction, from the smallest microorganism to the largest megafauna. The total must be staggering. And so, it seems, is the scale of action required to halt this decline.

The regional community, maximum entropy, and other ideas in ecology

Looking through my feed of community ecology papers this month, I couldn’t help but notice that while most tested well-established concepts–density-dependence, niche partitioning, metacommunities, competition, dispersal limitation–there was also–as I suppose is usually true–a subset of papers championing newer, less established ideas.

For example, the article “Applying a regional community concept to forest birds of eastern North America” by Robert Ricklefs, furthers the regional community concept he introduced in 2008. Ricklefs is uncomfortable with how ecologists typically define local communities – i.e as spatially and ecologically discreet entities – and the predominant focus in community ecology on local coexistence. He argues that communities make sense as entities only at a larger scale, taking into account that local communities are not isolated, but instead interact as a function of overlapping ranges and species dispersal. In this paper he applies this concept to Breeding Bird Survey data to examine the distribution and abundance of birds in eastern NA.

Partel, Szava-Kovats, and Zobel are also critical of the predominant focus on local diversity. In their paper “Dark diversity: shedding light on absent species”, they pitch the idea of “dark diversity” as a valid diversity metric. Dark diversity accounts for the number of species which belong to the species pool for a particular habitat in a region but are not actually present in a local community of that habitat type. The resulting value can be used to calculate a dimensionless ratio of local to dark diversity, suitable for comparison of diversity components in dissimilar regions.

Lastly, in “A strong test of a maximum entropy model of trait-based community assembly”, Shipley et al. further test Shipley’s model of Entropy Maximization, using it to predict the composition of communities in the South African fynbos. The model predicts community composition (species identity and relative abundances) through an assumption of random assembly (or entropy maximization) within environmental constraints on species traits.

New ideas are a constant in ecology, but they face stiff competition in an already crowded field. The possible mechanisms of local coexistence, for example, are already a long list. What determines which of these–or any–ideas become entrenched in ecology? The likelihood of a concept becoming established must be a complex function relying on a cost-benefit analysis–what does applying this idea cost compared to the gain in understanding it produces?–further adjusted by intangible variables like timing and the skill and prestige of an idea’s advocate. After all, some ideas require decades to establish properly, requiring changes in the theoretical climate or technical capabilities, for example, neutral theory or spatial ecology. Others seem to catch on immediately. Philosophers have written more cogently on how scientific ideas change and paradigms shift, but as participants in the process, we have a rather unique perspective. After all, as scientists we play an active role in driving these shifts in thought and action. You might argue that the merit of the ecological ideas that become established are as much a reflection on those who accept and institute them, as on those who propose them.

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awesome infographic by Caroline Tucker

(click to go large)

There exists a problem in science so complicated that decades of work have yet to solve it. Its causes and consequences make some of the toughest questions in complex analysis or astrophysics look like child’s play. And yet when we consider this problem, the conclusion is immediately obvious and simple: it should not exist.

I am talking about the fact that today, in 2011, female scientists are punished solely because they are female scientists.

In theory, this problem doesn’t exist anymore. Multiple waves of feminism should have chipped away whatever glass ceilings once capped our ivory towers. Women are receiving more PhDs than men in many fields and they are earning such a high proportion of bachelor’s degrees that we may have to rethink that name.

But in the last several weeks, some disturbing realities have resurfaced in the science media. At the end of January, Nature reported that women earn fewer scholarly awards than they should, based on the proportion of their respective fields that they represent. That same week, Science published a graph showing the number of European Research Council grants awarded to women in its last funding round – 9.4%.

Stats like these are nothing new; they pop up all the time. What is new, however, is the article that followed in Proceedings of the National Academy of Sciences a few days later. It turns out that there is no longer much evidence for overt discrimination against women applying for jobs or grants in quantitative fields. Instead, disparities in available resources are causing many of the differences between women and men’s scientific careers.

Yes, there are discrepancies in publication acceptance rates and grants, but the authors attribute these to factors like women occupying more positions at teaching-intensive schools rather than research institutions. When they compared men and women with similar resources, the biases disappeared, or in some cases, favoured women. (If you don’t want to read the whole article, there’s a nice summary of it here.)

Ok great, the science community isn’t explicitly discriminating against women. But this leads us to a much more troubling conclusion; the culprits are actually deeply engrained societal expectations and constraints that likely extend well beyond the sciences, and certainly beyond the scope of this blog post, though a few of them are highlighted in this thoughtful opinion piece.

Here’s what I will say: it’s not written in our DNA. How many times have you heard lines like, “Men and women are just different, they always will be, our brains aren’t wired the same”? This kind of just so statement is rarely backed up with evidence. For a good debunking of these misconceptions, check out two new books, reviewed here.

Now it’s possible that I, as a young male grad student, do not hold the most valuable two cents on these issues. I could keep rambling about things that I don’t fully understand, but my perspective is limited, and I think maybe the most constructive thing to do at this point would be to hear about other people’s ideas and experiences in the comments section below. So I’m cutting this short and leaving it incomplete in favour of a more open forum. In particular, it occurred to me that we in the ecology and evolution community have a unique opportunity to shed light on many gender issues. The PNAS article focuses on the underrepresentation of women in math-intensive fields, but comparing mathy fields to less-mathy fields entails a lot of confounding factors. In ecology and evolution, however, we cover the whole spectrum, from the completely mathless and descriptive, to the suspender-wearing, calculator-toting quants. We generally all come from relatively similar biology backgrounds, eliminating many of those confounding factors, and it would be great to hear how you all think these issues play out in E & E. So go for it blogosphere, do your thing.

Documenting the sacrifice

Whether working in remote regions or with poisonous animals, biologists often put themselves in peril in the name of discovery. The first organized expeditions of naturalists sailed to exotic lands, their bravery supplemented by their curiosity, were threatened by storms while at sea, new and deadly diseases, unfamiliar animals, and new cultures. Add plane crashes and paramilitary groups to this list and not much has changed.

In a great New York Times piece titled 'Dying for Discovery', Richard Conniff recounts several stories of naturalists, ecologists and conservation biologists killed while pursuing their passion for discovery. But just how many field biologists have died while working to understand life's secrets? This is an interesting question, and begs the further question, are they adequately memorialized?

Gary Polis (1946-2000) desert ecologist, drown with four other biologists during a storm in the Sea of Cortez.

In an attempt to tell the stories of the fallen naturalists, Conniff hosts an interactive list, called the Wall of the Dead, which lists all biologists killed in the field and that he has a record of. People are able to add names, and I've visited this list several times over the past month and it has grown substantially. I've known a few field biologists that have died -and added one to the list, and know several that survived near-death experiences, and this list is a great and important monument to their memories.

Further studies of the decline effect find decline of the decline effect

“The Truth Wears Off: Is something wrong with the scientific method?”

The Decline Effect explored in an article by Jonah Lehrer in the New Yorker refers to a temporal decline in the size of an observed effect: for example, the therapeutic value of antidepressants appears to have declined threefold since the original trials. Based on the cases presented, this effect is not limited to medical and psychological studies. One example in evolutionary biology is the relationship between physical symmetry and female choice: initial studies consistently found strong selection for symmetry in mates by females, but as time passed, the evidence grew increasingly smaller.

This may be a result of selective reporting – scientists focus on results that are novel and interesting, even if they are in fact simply statistical outliers, or worse, the result of unconscious human bias. This sentiment is troubling; humans – scientists or not– are proficient pattern finders, but our subconscious (or conscious) beliefs influence what we search for. Lehrer argues that replication – the process of carrying out additional, comparable but independent studies – isn’t an effective part of the scientific method. After all, if study results are biased, and replications don’t agree, how can we know what to trust?

I don’t disagree with most of the article’s points: that scientists can produce biased results, PhD not withstanding, that more effort and time should be invested in data collection and experimental methodology, that the focus on 5% statistical significance is problematic. For one, it’s not clear from the article how prevalent the decline effect is. However, I wonder whether Lehrer, similar to the scientists he’s reporting on, has selected specific, interesting data points, while ignoring the general trend of the research. In 2001, Jennions and Moller published evidence of a small negative trend in effect size over time for 200+ studies, however, they suggest this is due to a bias toward high statistical significance, which requires either large effect sizes (the early studies published), or small effect sizes in combination with large sample sizes (a scenario which takes more time).

Even if the decline effect is rampant, does it represent a failure of replicability? Lehrer states that replication is flawed because “it appears that nature often gives us different answers”. As ecologists though, we know that nature doesn’t give different answers, we ask it different questions (or the same question in different contexts). Ecology is complex and context-dependent, and replication is about investigating the general role of a mechanism that may have been studied only in a specific system, organism, or process. Additional studies will likely produce slightly or greatly different results, and optimally a comprehensive understanding of the effect results. The real danger is that scientists, the media, and journals over-emphasize the significance of initial, novel results, which haven’t (and may never be) replicated.

Is there something wrong with the scientific method (which is curiously never defined in the article)? The decline effect hardly seems like evidence that we’re all wasting our time as scientists – for one, the fact that “unfashionable” results are still publishable suggests that replicability is doing what it’s supposed to, that is, correct for unusual outcomes and produce something close to the average effect size. True, scientists are not infallible, but the strength of the scientific process today is that it doesn’t operate on the individual level: it relies on a scientific community made of peers, reviewers, editors, and co-authors, and hopefully this encourages greater accuracy in our conclusions.