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.

Carinval #32 and still going strong

Want to know what people are talking about? The 32nd Carnival of Evolution is online, hosted by Denim and Tweed. Check it out, pass it along.

Trend in ecology, 2010

Sciences are always in a state of ebb and flow (sorry), and topics of study fall in or out of fashion in response to paradigms shifts, methodological advances, and to support necessary ecological applications.
For the sake of curiosity, I've compiled the top keywords from ecology publications in 2010. Obviously there are many covariates, but it should come as no surprise that the top words were "biodiversity" (667 times), "climate change" (293), and "conservation" (274); other popular keywords were "evolution" (277), "population (ecology)" (273), and the rather vague "patterns" (196).

(click image for larger view)

The evolutionary story of ecosystem function

Twenty years of research has repeatedly shown that communities with greater diversity result higher functioning -namely greater production of biomass. One of the major mechanisms producing this relationship is that different species use differing resources, such that their complementary use of resources uses the total resource pool more thoroughly, thus converting more resources into biomass. Resource preference is the product of evolution and how organisms have adapted to using various resources can influence the strength of the diversity-function.

In a recent paper in Nature, Dominique Gravel and colleagues test how the evolution of specialization versus general resource use affect the strength of the diversity-function relationship. They use bacteria strains that have undergone evolution on diverse resources (generalist) versus on a singular resource (specialist). The resources in their case are different carbon substrates.

Assemblages of generalists were able to use many available resources and generally had greater productivity than specialist assemblages. Generalists also show an increasing relationship between diversity and productivity, because no generalist used all resources and they still showed some preferences. Combining multiple such generalists meant that more of the total resource pool was consumed. Specialists also resulted in the positive relationship, but a much steeper one. Because specialist use many fewer carbon substrates, additional specialists meant that new resources were tapped into. Thus increasing specialist diversity resulted in more new resources being consumed than with the generalist species.

While these results are logical, they are important for two reasons. First is that the strength of the relationship between diversity and function is mechanistically determined by the resource use efficiency of individual strains, and how many of the total substrates they can use. The mechanisms producing different relationships in previous experiments were hypothesized after the results analyzed, as opposed to being predicted. Second, recent work has shown that evolutionary history seems to be a better explanation of community function than the number of species. These results show how the history of evolution can have important consequences for function.

Gravel, D., Bell, T., Barbera, C., Bouvier, T., Pommier, T., Venail, P., & Mouquet, N. (2010). Experimental niche evolution alters the strength of the diversity–productivity relationship Nature, 469 (7328), 89-92 DOI: 10.1038/nature09592

Who is a scientist, I am a scientist: the bees of Blackawton

In discussions of the larger societal implications of scientific findings, the question of who is a scientist is frequently asked. I've talked with with creationists who invoke the authority of someone who has a PhD in a scientific discipline and happens to share their belief of supernatural origins, as a scientific authority. Does the fact that I have a PhD in ecology and evolutionary biology make me scientist or is being scientist something more?

This is an important question. It goes to the core of whose authority we believe for public discussion of such issues as climate change, evolution, risks of vaccines, and so on. Regardless of how we define 'scientist', a scientist participates in science by publishing peer-reviewed research articles in scientific publications. This notion of who is a scientist has been enjoyably stretched by the publication of a paper in Biology Letters by a group of elementary school children from Blackawton, UK. In consultation with a academic scientist and under the supervision of teachers, 25 8-10 year olds devised and carried out an experiment on bee visual perception and behavior, and wrote up their results into a publishable manuscript.

The students trained bees by offering them nectar rewards in different color containers. They then allowed these trained bees to forage in multicolored arenas and they conclusively show that the bees unambiguously select the colored containers they were trained on. Bess learn and adapt their behavior based on previous experience.

Publishing a paper by a group of children may sound like a gimmick, but the study is very interesting. The commentary from the journal says it best: "The children's findings show that bees are able to alter their foraging behaviour based on previously learned colours and pattern cues in a complex scene consisting of a (local) pattern within a larger (global) pattern . As there has been little testing of bees learning colour patterns at small and large scales, the results can add considerably to our understanding of insect behaviour."

The paper is extremely enjoyable to read and will have you chuckling to yourself. Sincerity pours from the words and I was left wondering if I could have reasoned so well at that age. The children develop hypotheses using information available to them, such as watching Dave Letterman's 'Stupid Dog Tricks'. Reading this article made me realize why I love being scientist. The students note that "This experiment is important, because, as far as we know, no one in history (including adults) has done this experiment before" and because they were given the opportunity to carryout this study they "also discovered that science is cool and fun because you get to do stuff that no one has ever done before". Too true. I could not have said it better myself.

Being scientist can mean a lot of things, it can mean knowledge (which the Latin origin, Scientia means), it can mean training and acquired skills, but at its core, being a scientist means conducting research, testing hypotheses and writing publications that are deemed acceptable by other scientists. Therefore the children of Blackawton are scientists, I am a scientist.

Blackawton, P., Airzee, S., Allen, A., Baker, S., Berrow, A., Blair, C., Churchill, M., Coles, J., Cumming, R., Fraquelli, L., Hackford, C., Hinton Mellor, A., Hutchcroft, M., Ireland, B., Jewsbury, D., Littlejohns, A., Littlejohns, G., Lotto, M., McKeown, J., O'Toole, A., Richards, H., Robbins-Davey, L., Roblyn, S., Rodwell-Lynn, H., Schenck, D., Springer, J., Wishy, A., Rodwell-Lynn, T., Strudwick, D., & Lotto, R. (2010). Blackawton bees Biology Letters DOI: 10.1098/rsbl.2010.1056

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The carnival is on!

Check out the 31st edition of the Carnival of Evolution, hosted by The Dispersal of Darwin. Check it out, a fun read for sure!

Science 2.0 - science comes of age on the Internet

by Marc Cadotte, Nicholas Mirotchnick and Caroline Tucker

The Internet is not just for lolcats and porn anymore, scientists have begun using it in constructive ways. The past few weeks’ controversy about the ability (or lack thereof) of bacteria to incorporate arsenic exemplifies how the relationship between science and the Internet is changing. If you’ve missed the debate over the recent Science paper, researchers funded by NASA’s exobiology/evolutionary biology program published experimental results suggesting that a Halomonas species could incorporate arsenic into its DNA in the absence of available phosphorus. This paper received extensive attention in the mainstream media, but also vocal criticism, which was expressed primarily through postings and comments on scientific blogs. Until recently, for scientific communication the Internet has functioned primarily as an electronic source of published journal articles. Earlier attempts to take advantage of the Internet’s potential (immediacy, accessibility, and ability to connect individuals, organizations, and ideas) in scientific discourse have been mixed (e.g. Nature Precedings versus PLoS ONE). The use of blogs as a forum for scientific debate suggests that this is changing: posters tended to be active scientists and the comments were similarly knowledgeable. In contrast to this online approach, the authors of the Science paper stated that they would only respond to peer-reviewed critiques and would not engage in discussions on the blogosphere.

The story of the arsenic-utilizing bacteria highlights an emergent tension in the transition to internet-based scientific discourse. Traditional communication in science has been primarily unidirectional, from the authors of a study to the readership of a journal. Any discourse transpired on the pages of a journal, regulated by editorial and peer review. This gatekeeping meant that this discourse was technically sound and kept personal grudges and tangential discussions to a minimum. This also meant, however, that only a few voices were heard, the discussion was slow (occurring over months) and only happened for one back and forth (journals will not devote precious page space to on-going discussions and debates).

This method of discourse is changing. Journals have experimented with online discussion or commenting features on their websites. Methods in Ecology and Evolution, for example, has a correspondence page with discussion threads for each paper they publish, and PloS ONE allows for comments to be posted to every paper they publish. While, in concept, these are positive developments for scientific communication, commenting features are seldom, if ever, used. The main obstacle to their success is that they are only available on the publishers’ websites, but scientists access articles in many different ways, from database searches to library links. Few scientists actually go to individual journal websites to access papers. This is not to say that there are not discussions about scientific papers occurring online. As highlighted by the arsenic bacterial episode, blogs are an important avenue for discussing and disseminating new ideas in science. Blogs may not, however, actually foster conversations very well. One person or a few people usually run them and there is little discussion among blogs (a comment on a blog post at blog X will not be part of the discussion of the same story at blog Y). Rather, the greatest potential to foster discourse is through virtual networks where people are linked together either through friendships or professional self-identification (e.g., as fisheries biologists), with Google Reader being a particularly powerful communication tool.

It’s exciting to think about what the future of science will look like, given the changes that we’ve already started to see. The major upside of new channels of communication is that they give us the potential to quickly reach thousands of readers, instead of the handful that usually read any given journal article. They also let us communicate in both directions, and in real time. The pitfall, of course, is that they’re free-for-alls; anyone can blog about science.

But here’s what’s unexpected: these free-for-alls have been amazingly reliable at filtering out the bad and promoting the good. Inaccuracies are pulled from Wikipedia faster than anyone had predicted, the social news site Reddit is “astonishingly” altruistic, with users eliminating offensive or erroneous comments from the site and promoting other users’ questions and problems, and the reputations of blogs are shattered if their content becomes unreliable. Social networking has revolutionized the way we consume news, with sites like Facebook and Twitter launching the best articles into viral webspace. The open-access world has evolved self-regulating mechanisms that work surprisingly well so far and if these media are to continue to grow, we will have to ensure that these mechanisms remain built-in.

Seems like an easy task, right? Apparently not. For some reason, academics are slow and conservative when it comes to adopting new media. A letter to Nature two weeks ago scolded scientists for not contributing their share to Wikipedia pages. Various facebooks for academics, like Mendeley and ResearchGATE have emerged, but last week, another Nature article complained that researchers aren’t jumping on the bandwagon. These sites are potential collaborative goldmines, but we seem to be incapable mastering what tweens can do with two thumbs.

It’s not so hard to imagine a world where anyone with a broadband connection can contribute creative ideas to science, the good ideas get automatically filtered to the top and the information is all free to anyone. In this world, children count ants (or bees!) in their backyards and upload their data to global networks. Revolutionary discoveries are published instantly on blogs and thousands of scientists get to decide if they’re valid. Every gene ever sequenced and every tree height ever measured can be readily downloaded in an Excel (or OpenOffice) spreadsheet. In this world, the report on our little arsenophilic friends might never have been published in Science, because instead of being reviewed by two referees, the thousands of readers on the blogosphere would have filtered it out, if was in fact porous.

Academics should be the first, not the last, to adopt new communication tools. We are no longer limited by the postal service, email or PDFs; the web has gone 2.0 and we should follow suit. So go forth, young researchers, and blog, edit and share. And then go tweet about it all so your eight year-old kid knows how hip you are.