Sunday, December 15, 2013

Morals and the ethics of collaboration

Why can't scientists stick to science at conferences? I find it hard enough to speak to strangers, and to be welcomed by racist comments that I don't know I can address if I am in the perpetrator's country makes it much harder. Racism and sexism are trashy. You shouldn't have to hide racist/sexist/other-ist thoughts. They shouldn't even come to your mind. Yes - the ideal world. 

But are we too sensitive? Do we rush to conclusions too early? Perhaps. The only time I can remember being called explicitly racist was in fourth grade, after I said I didn't want to watch riverdance for the third day straight and said that Irish people drink beer on St. Patrick's Day (apparently saying that Irish people eat boiled dinner isn't racist though). It seemed (and still seems) ridiculous that my teacher should assume I was discriminating against Irish culture, but it made complete sense to her. 

So am I ridiculous in crying racism after some conference attendees told me that Chinese students are lazy, sleep in the lab and only ever pretend to do work, playing video games all the time instead? Maybe. But it is just another reminder that we need to think about what comes out of our mouths and how, because after that comment, I couldn't bring myself to talk science with them. Or talk to them full stop, for that matter. 

Conferences and face-to-face interactions are vital for the spread of scientific knowledge and forging collaborations, but if these are going to be shrouded in ideals that one party vehemently opposes, then once again ideals have shaped the path of science. Human rights and environmental charities are constantly scorning universities and companies for investing in morally grey areas, so why do scientists think it is OK to collaborate with scientists who hold grey morals? 

I think this is probably because we like to think of science and society as separate when convenient. And it is hard to hold a firm stance against poor morals because so many technological improvements have emerged from dark times and/or dark minds (SONAR, RADAR, and the Haber-Bosch process to name a few). 

But where do we draw the line in collaborations? If we ignore the discriminatory tendencies of our collaborators and work with them to advance science, are we also subtly advancing their ideals? What if we cite papers written by people with questionable morals (James Watson comes to mind here)?

Ultimately, are we not guilty by association if we knowingly collaborate with discriminatory colleagues? Is this how the closed-minded norms perpetuate in fields that like to consider themselves open, in the heads of people who like to think of themselves as educated and/or liberals?

Thursday, October 31, 2013

Has the sun set on societies?

My mum asked me to write a post on how society publishers could keep young scientists involved, as this is something that many scholarly publishers, libraries, and societies are thinking about. Her comments were something along the lines of "We oldies, who are the ones making decisions about the future of our organizations, are worried about keeping early career scientists involved. For example, most societies are run by the older generation, and although some (eg. AGU, ESA) do have a good group of early career scientists, these appear to be exceptions to the rule. How can we get more of you involved?"

One factor could be the cliqueyness of conferences. The primary incentive of society memberships I can see are 1. access to jobs boards/listservs and 2. going to conferences (for societies that require membership to attend conferences). But how do you break into a group of scientists who are talking to one another if they are all friends? Would you rather not stick with your own kind? It is kind of like the first day of school all over again, only you probably don't have quite as much courage to ask to join someone else's game (conversation), or the brazen spirit to get over rejection. Then again, later career scientists may feel the same way about talking to earlier career scientists. People are just awkward.

Perhaps the best way to get all age groups is to create intergenerational labs. While as a grad student I may be able to relate to my pre-tenure advisor, I look at many later stage professors and they seem a world away. And since many of them got tenure in a different era, they really are. There are certain full professors I can relate to, but the initial interactions and courage to talk to one another is contingent upon our daily bumping into each other rather than any intellectual exchanges. Of course, deciding who shares which lab space isn’t really within the powers of societies, but holding workshops specifically designed to bridge the generational gap is (so offering miniseminars or discussion groups at conferences where the organizers put together a small group of scientists at different stages in their careers and from different institutions to talk).*

From a publishers perspective, keeping early career scientists involved with the societies they work with is seen as vital for maintaining readership. I can’t really say how to keep up readership in the early career sector, but I know what I want. I want those pesky career services adverts to go away – or at least to not compromise job post quality and relevance in the name of money (do I really seem like the kind to want a job in pharmaceuticals if I am reading a paper on theoretical ecology?).  I don’t need a society’s calculator tools; labs have already developed plenty enough of those, which are high quality so don't waste your resources trying to compete with them. A publisher’s website does not need to be a one-stop shop, and should stop wasting its energy trying to be. Remove that banner stuff and those sidebar links and fill as much of the page as possible with actual content– the screen on my laptop is quite small and I want to see the figures as I read.  Just give me the papers I want to read, please. This isn’t the superbowl.

But perhaps ultimately what societies and publishers can do to involve a younger audience is to stop assuming everyone is going into academia (and in a few instances, perhaps industry). Develop resources that don't immediately exclude the majority of young scientists that aren't in or aspire to be in tenure track positions. 

What do you want from societies and publishers (besides free access to all the journals in the world)? Is there something you think that societies could provide to entice you to participate more, or are societies a lost cause in your mind?

* I would like to point out that there are of course numerous exceptions to my sweeping generalizations about societies, publishers, and conferences and/or organizations doing the things I suggest are good here. The purpose of these statements are to demonstrate instances of where I think these organizations are headed in the right direction.

Sunday, October 13, 2013

What makes a paper mind-alteringly good?

Sorry about the overly-dramatic title, but after reading what I think is a very well planned and executed paper on the phylogenetic and geographical dispersion of drought tolerance in plants earlier, I have been thinking about the power that single articles can have over our outlook on our work.

If the world's journal archives were about to be obliterated, the one article I would grab would be Davidsson and Janssens' 2006 paper in Nature on how climate-induced changes in decomposition may feed back. Actually, this is the only paper I kept from my undergraduate, and I have been reading the same dog-eared, scribbled-on copy for the past five years. It is also the only paper for which I have gone through and read every paper cited in it.

But why did this article appeal to me initially? I didn't understand most of it the first time I read it. Or the second. It took a week of staring at Box 1 to understand what it was talking about, and some of the other arguments in the paper seemed flawed to me because the lines of logic they were following weren't laid out, and disagreed with the facts I was aware of the time. But from what I could decode, I knew this paper would be really important for my understanding of the carbon cycle under climate change. And in my young inexperienced state, I thought that it must be good and right, because it was published in Nature.

Despite my interest in the paper's important topic, it was the dense challenge of the paper, working through the hidden complexities of the carbon cycle, that got me. Every time I read it, I get something new out of it, and it helps me frame my work in the bigger picture and remind my why I love my work.

But what article do you keep returning to?

Basic psychology would tell us that for most of us, our most powerful article will be one of the first we read on a topic; our experiences early in life (whether research or real) shape how we perceive subsequent events, and therefore we will find ourselves returning to the point (paper) which established our mindsets. I would think that review articles would also be favored over primary research articles, because they put the research in context and are generally written by people with respected views. Of course, regurgitating what is known doesn't help, but putting a new spin we hadn't thought of (for example pulling in information from other disciplines) would make an influential article in my books.

I think this would mean that journals that want to be cited lots should favor interdisciplinary reviews. I believe I read somewhere that this already happens - does it? That seems like it would be a much too simple key to "success"!

Thursday, October 3, 2013

What to do when you're wrong...

Sorry for the delay in posts. I've been busy being wrong.

As we know, one of the first tenets of "good" science is reproducibility. If I follow someone else's protocol, using the same starting material, I should get the same results. But if you do that, and you get a different result, how do you know whether the alternate result is because you didn't quite replicate the protocol, or because the original conclusions were wrong? Or what if you interpreted the same results differently?

I can imagine this is an especially large problem when you are new to a protocol (or at least that is my excuse), as you lack a sense of the range of possible outcomes. For example, a labmate was trying to interpret a catalase test earlier, and would have said that all our results were negative compared to the plate of mixed soil bacteria I had, where adding a drop of hydrogen peroxide caused a baking soda and vinegar type volcano effect. Two of the bacteria were supposed to be catalase positive, and if we added tons of hydrogen peroxide directly to a plate with a high density of bacteria and looked really really close for a few minutes and imagined a positive result, we got one or two small bubbles. This is exactly the same as if I drop a drop of the hydrogen peroxide on uninoculated media. So did the authors who stated these organisms were catalase positive actually mean it, or did some nervous inexperienced student  who was told to look for any sign of bubbling squirt a bubble onto the slide and say there was a positive result? Who decides where the boundaries of a positive or a negative result are - would it not depend on "how" positive or negative your control organisms are? Do people publish the organisms they used as controls alongside their determination of whether something shows a positive or a negative result? No evidence for these yet.

Maybe we should just mandate that all standards in genomics tables be replaced by full-colour pictures. Voluptuously bubbling hydrogen peroxide. Stunning Gram stains. Replace someone else's interpretation of ambiguous data with informative eye candy.

In another instance, I have been working (a bit too long) on trying to get well-published qpcr primers to work, and finding that the conditions as close to the original ones I can reproduce in my lab just don't work. I was afraid I had contaminated the freezer stock of my organism, or put too much or too little template, or used the wrong temperature...something that was my fault. I tried to come up with an answer and a solution for my PI for when I told her that things weren't really working. But apparently, however, what I thought was close enough to the original conditions probably is not; the primers were tested against a sequence placed in a purified plasmid, and I am using genomic DNA.

Which brings us to another class of issues with reproducing an experiment - what if you purposefully are not exactly reproducing an experiment, because you don't believe the methods used are valid and/or reliable and/or result in biologically meaningful conclusions? Why waste time and money trying to reproduce an experiment that was invalid when it was made, and still invalid now, just to try and compare your results to ones you cannot trust? At my stage, I think it is so you can fit in; the ability to reproduce something invalid is a valuable skill for perpetuating some of the falsehoods of science, which you have to be able to do in order to prove your worth in breaking the (methodological) status quo.

So why use a plasmid template for qPCR, even if it does a poor job representing the kinds of templates you will be comparing with from the environment? Because it is one of the standards for this kind of data collection; we can hide behind completely non-reproducible data, uncertain whether it is due to the methods, or because we are dealing with "complex" environmental samples that nobody else is likely to exactly mimic.

But no matter what I may do to try and convince myself I wasn't wrong, I was. I tried to reproduce results under the conditions I thought they should be done, not those in which they were intended.

So if you are wrong, either make sure you do it reproducibly so you can challenge what is deemed right, or do so using conditions nobody expects ever to exactly reproduce. But know when to accept that it is you, not science, not the protocol, that is wrong.

Sunday, September 1, 2013

Science on the Free Market?

My mum's friend sent me this article discussing how science is moving away from fundamental research, and towards translational work, and asked for my opinion.

The article is titled "Should Science be for Sale?", which immediately made me think of some kind of sinister plan to buy people out of presenting the whole truth.  

Although faking science is not limited to the former Soviet Republics, the author points out that it has been getting worse there. I agree this is bad; when people build science on bad science, it may take years for its consequences on scientific theory to emerge. However, the author tries to blame this "evil" on the fact that people increasingly see science as a means to an end, rather than for its own holy sake. Yes money can lead to greed and cheating the system, but it can also lead to healthy competition - a bit of a free market with the tax-paying public as customers - for doing the research that matters, and so the author's implied sentiment that applied research is filthy compared to basic science is a bit simple-minded and snooty to me.* 

But by no means do I think science is a holy palace either. Science has its traditions about what should and should not be published which don't always coincide with simple rules of following the scientific method. It is true that scientific knowledge is financially-driven - science journals are after all really just glorified tabloids looking for the biggest and best (fact-checked) stories to boost readership - and researchers need to do the work that will get them money from the governmental funding agencies that decide the country's research agenda. 

While applied research may be more explicitly designed to facilitate progress towards these goals, and to fit in with where the government is funding, by no means does this mean that basic research is excluded from these funding calls. You just have to spin it a bit harder to make it sexy, and ultimately I think this is better for the researchers. Any taxpayer is entitled to know what areas of science his or her money is going to, and to ask scientists how they are attempting to make the world a better place. Taxpayers don't always have to understand exactly how this research will get to that end-point, but by forcing research proposals to consider broader impacts, it better prepares scientists to legitimize their work to their funders, and to think about how their work will ultimately contribute to society. It gives people a goal, and making coherent progress is difficult without one (not to mention checking the boxes on annual reports!)

I think that if this country is going to continue to succeed in science, ALL scientists will have to promote their research and give it credibility in the eyes of the public, who, whether as taxpayers or as private donors, determine its future. We absolutely need more basic research, but if you are up on your high, unapplied horse and refuse to even distantly relate it to a topic of public or private interest, don't whine when funding dries up.

* This attitude towards applied sciences apparently is even worse in maths than in (other?) science. Last year I lived with a mathematician who was complaining about lack of funding for his field, so I asked him what the end goal of his work was - how could it eventually be applied to physics or economics to improve knowledge of the world. He said that application was a no-go word, and even thinking about it would lead to ostracization, so he couldn't tell me what he did or where his research was headed. It was like he was bitter that he had to reduce or filthy himself with applied work, even though the taxpayer had funded grad school for him. 

Wednesday, August 21, 2013

Fighting foreigners with foreigners: aphid vs. vine

Apparently the NYC Department of Parks and Recreation is releasing thousands of weevils originally from Asia to fight mile-a-minute, an invasive vine also native to Asia, which has taken over parts of the city.
I want your MAM(my)! 

When I first read this, it immediately triggered alarm bells to go off in my head. I don't know if it is the combination of quasi-hippie environmentalist and old-school naturalist professors I had during my undergraduate, which insisted on letting things be, or my mother's insistence that two wrongs don't make a right, but I thought this would be yet another human manipulation destined for failure. Think cane toads, native to central America and introduced to sugar cane fields in the Caribbean and Australia to keep down pests, but now spreading well beyond its range and killing off many of its would-be predators with its poisonous skin. Or, the story (for which I can find absolutely no evidence for now) that rats were introduced to an island, then snakes were introduced to eliminate the rats, and the plan backfired and the snakes have taken over the island, killing much of the native wildlife (it almost sounds like the story of Guam and brown tree snakes, but isn't).

However, I am glad to learn that we have learned from our mistakes, and when we say that extensive research was done to evaluate both safety and efficacy of the aphids in targeting mile-a-minute, hopefully we mean it (see references here). As with most pest invasion studies, potential control mechanisms were identified by looking for the herbivores which keep the plant in check in its native environment. Researchers identified Rhinoncomimus latipes aphids (they really need a good common name - can we nickname them munch-a-minutes?) as good potential targets for further research, and their breeding began in controlled environments in the US.

The potential heroes of the story...

Of course, organisms don't always behave the same in a new environment as they did in their original environment (this is why things may be minor members of a diverse community in their native habitat, and invade in another), so the next step was to evaluate whether they still feed primarily (or ideally uniquely) on mile-a-minute. Researchers at the University of Delaware dusted these aphids red, and placed them at the base of non-target plants, or yellow, and placed them at the base of mile-a-minute, and followed them through time to see where they ended up. The researchers found that aphids which originally started on mile-a-minute did not stray onto non-host plants, and those on non-host plants found their way onto mile-a-minute more and more as time went on. This is all good.

However, there are still other questions which remain unanswered. For example, do the aphids have natural predators? If mile-a-minute declines, or is in low density in some places, will the aphids switch to other food sources (like us and previously disregarded fish)? Will they reproduce with native mites and make new, super cabbage-eating mites which will upset community gardeners? And, as far as I can tell, although we know it munches on the weed, we don't know whether the mite occurs in sufficient density to have a noticeable impact on mile-a-minute population.

While some of these worries may seem a little far-fetched, all have previously emerged as problems. That said, we cannot be frozen by fear; we live in a dynamic world we change for better or worse.  We don't have enough knowledge to predict the future, so we should try and balance gathering enough information to make an informed decision, and making a decision in a timely manner. After all, researchers need results for grant applications or to appease investors, and some are willing to release their experimental creatures into the wild without full ecological impact assessments in order to undercut scientists with possibly more ethical methods.

Sunday, August 11, 2013

The chemistry of decomposition - what is really going on down there?

I recently visited Jerry Melillo's warming plots at the Harvard Forest, and I don't know why, but I was amazed by how much the leaf litter had decomposed over the past few months. This got me thinking about the structure of carbon of the remaining litter. The historic view has been that labile sugars go first, then cellulose, then lignin, but what about the waxes and other compounds which don't fit into these categories? To a certain extent, our understanding of litter decomposition has been limited by our ability to detect and distinguish these other compounds, but tools like NMR are changing that.

The husband-wife duo of Nishanth Tharayil and Vidya Suseela at Clemson have once again teamed up with Baoshan Xing at UMass to study the fine chemistry of litter. In one of their previous papers, the authors noted that reducing precipitation increased the relative abundance of tannins in red maple litter; in this paper they looked at how the chemistry of Japanese knotweed litter, that horrible invasive which is actually quite delectable when young, changes through time in litter subject to different warming and precipitation treatments at the Boston Area Climate Experiment.

In this experiment, the authors made "old" and "new" litter bags by harvesting Japanese knotweed which had either been decomposing upright following senescence the previous year, or just-senesced stems. They were placed at the edges of the high (~+3C) and ambient temperature plots, under drought (50% of precipitation removed year-round), ambient, or wet (an extra 50% of rain applied during the growing season) treatment, and harvested at four time points over a period of three years. By pulling peaks from various methods I don't understand (DRIFT Spectroscopy, and 13C cross-polarization magic angle spinning NMR spectroscopy), they confirmed that decomposition of recalcitrant litter is generally more temperature sensitive than more labile stuff. Again, as previously noted, decomposition is greatest when supplemental precipitation is applied in conjunction with warming. But perhaps the most interesting point was that while the effect of climate treatment on overall decomposition rate did not differ between new and old litter, specific (recalcitrant) compounds did decompose more fully in the older litter, which the authors cite as evidence that initial litter chemistry does matter.

As my PI pointed out, there are a few problems with the way in which this experiment was designed. First, the authors used litter from a plant not found in the warming experiment, collected at a site a hundred miles away. The authors state that this litter was chosen because all litter is clonal, and therefore should have been initially identical, but wouldn't litter taken from one of the trees at or near the experimental site not be adequate? Perhaps the problem would be that litter allowed to decompose in-situ for a year would start with clearly different microbial communities than the litter which had just-fallen from a tree. That said, we know that there is often microbial succession during decomposition, and therefore the litter going in old probably had a different microbial community associated with it than the "new" litter, whether or not it was harvested from immediately adjacent stems from a clonal population. In this instance, differences in decomposition with litter starting chemistry could be due to the presence of a microbe at the litter source site initiating decomposition of compounds that microbial populations are not as well-suited to break down. For instance, there could be fungi at the source litter site which are much less abundant at the experimental warming site because it is a well-trodden former agricultural field with relatively low organic matter content.

My PI also pointed out that using litter which starts from the same plant but is in different stages of decay is not a particularly biologically informative way to answer a question. She said that using various kinds of leaf litters which naturally differ in their starting chemistry, as occurs in ecosystems today and potentially exacerbated by climate-induced shifts in species composition and litter chemistry, would make the results of the experiment more useful in ecosystem carbon models. I believe the litter bags for that experiment are decomposing in-situ as I type.

As I alluded to above, my main beef with the paper was, of course, that they didn't talk about whether the microbial community differed between warming treatments. I am interested in knowing whether the differences in decomposition are due to purely physical effects, or whether changes in the microbial community also played a role. I would also like to know if succession of microbes on the different litter ages and in the different plots followed the same pattern, just being accelerated in some instances, or whether the communities were completely different.

This is a kind of chronic problem with ecologists; they generally ignore microbes (or suppose what is happening without validating the assumption). Almost every paper I read, I hope with all my heart that they have soil cared for nicely and kept in an ultra-low freezer somewhere. But anytime I inquire, the answer is no. If they want to really understand what happened in their system, it is their loss.

But please, if you are doing anything involving soil, or are doing a study in which you expect soil or litter-degrading microbes to be adhered to your object of interest, please flash freeze that soil/litter at collection and place in a -80C freezer. If you don't have access to one, contact me before you collect your samples and I will send a self-addressed cooler with dry ice, and I will fill my PI's freezer with random samples as long as I can without her noticing.

Monday, July 29, 2013

The Science OR

Today I got an email via Ecolog, informing me of the birth of a new way for scientists to disseminate their research. Launched by Queens University a couple of weeks ago, one of SciOR's main objectives is to place accountability in the article review process.

The idea that reviewers can say whatever they want and reject papers that conflict with their own beliefs, all behind a veil of anonymity, is not new. Nor is the idea that journal editors select what knowledge is published, and therefore the sphere of knowledge that scientists have. So how does SciOR (or Science Open Reviewed) claim to offer a way around this?

1. Reviewers register with the website and advertise their reviewing experience and offer a list of topics they feel qualified to review papers on. 

2. Authors post paper titles and abstracts as a sales pitch for their papers; SciOR provides a platform for potential reviewers to contact the author's and offer their reviewing services.

3. Authors pick from the list of offers (or invite new ones), and both author and reviewer complete a No-Conflict-of-Interest (NCOI) declaration.

4. Authors pay the reviewers, if that was part of the agreement, and SciOR facilitate the transaction.

5. The authors revise and re-upload the paper, asking for more reviews if they so wish.

6. SciOR serves as a kind of marketer for these articles; journal editors from other journals (or the in-house Proceedings of Science Open Reviewed) pick from the rack of finished reviewed products. They then contact the authors and the authors unpost the paper.

I don't really have enough experience with the peer review process to know if this will work, but the idea of paying reviewers seems a little weird. I don't like the assumption that the SciOR people make that many reviewers don't offer their services "because they are nice people wanting to help advance science", but rather imply that people enjoy the power the position gives them.  Wouldn't money take it the other way? If people are interested in power, not the advancement of science, then wouldn't this hold true for authors too, meaning that a reviewer powered by money could become a popularist, letting things slip through? Sure there is a second round of editing before complete acceptance, but editors are not specialists in the subject and therefore may not catch mistakes. Meanwhile, the reviewer has cash in hand and the author another publication to his/her name.

Furthermore, is this really any better and more open than the traditional publication model? First, if journals are going to send the paper out for review again, why bother marketing a reviewed product? Won't this retard the publication timeline? Second, external journals are still picking and choosing the articles it thinks are interesting, while the editor of the Proceedings of SciOR has his/her say on the remainders. Editors are still controlling what we know. Foucault lives on.

What do you think - can ScienceOR resuscitate science communication?

Thursday, July 25, 2013

X, Y, (and Z?)

Since it is my lab tech Rebecca's last full day tomorrow before she leaves for grad school in Florida, I thought I would write about one of her favorite topics: sex determination.

Let's start with us humans - as you know, humans with two copies of the X chromosome are female, and those with two different ones (XY) are males. But what if you are missing an X or a Y chromosome? What if you have an extra sex chromosome? XYY individuals aren't "super men", but XXYY (or XXXY or XXY) individuals are sterile males. Women with an extra X chromosome (XXX - trisomy X) are developmentally delayed, so there is such a thing as being "too much woman". But missing an X chromosome results in Turner's syndrome for women (XO), and spontaneous abortion for males (OY).

So what does this tell us about these chromosomes and sex determination? Well, you HAVE to have the Y chromosome to be male, and an X chromosome to live, but having more X chromosomes doesn't make you more of a woman - it just makes you sicker. This is because the X chromosome actually carries a lot of important information - including sperm production - while the Y chromosome has been shrinking for the past millions of years and pretty much just carries a single important gene. This gene, SRY (pronounced "sorry"), is a regulator for testis development early on, but all the genes controlled by this are on other chromosomes. Thus came the (in)famous statement that y chromosome shrinkage may be driving men extinct - although this has been disproved. One reason for this is because the SRY gene alone can determine maleness, and it is possible for it to insert into the X chromosome (XX males).

Look how tiny the Y chromosome is compared to the X chromosome! Image from:

But what about other organisms. That fly buzzing over your half-rotten bowl of fruit you haven't quite managed to finish? Femaleness is decided based on having two X chromosomes, rather than maleness being on the presence or absence of a Y chromosome. Those cockroaches crawling out of your walls? They only have X chromosomes, with males having a single copy and females having two. And that sparrow outside your window? It is like the opposite of humans - men have two chromosomes the same while females have two different ones.

But perhaps the most intriguing method of sex determination is found in sea turtles (and alligators), whose sex is determined by egg incubation temperature. Hot eggs are female, and cooler eggs become male; the temperature difference is very slight, and therefore a mother can somewhat control the sex ratio of her offspring by rearranging eggs. However, some researchers worry that this temperature differential will not be possible under a future climate, and so the reptilian world will be run by females. Of course, females are generally better at spacing sexual encounters than males, so a female-shifted population may not be all bad and could mean more sea turtles.

How many methods of sex determination can you count? From

Or what about organisms which can reproduce without sex (an administrator at denies Jesus was conceived this way). Or those which switch sex at some point in the lifecycle (think Nemo). Or earthworms, which just serve as whatever sex they feel like, and usually have sex with another worm, but can also just fertilize their own eggs.

There are so many more organisms - like sharks (thanks Rebecca!)- that we know nothing about. Understanding sex determination is more than just an intellectual question - it has important implications for managing wildlife, whether it be on the endangered species list, our menu, or a novel invasive species.

Sunday, July 21, 2013

Now, now...share nicely!

In lab meeting a couple of years ago, we discussed whether making government-funded ecology research publicly available would actually benefit science. The general consensus was that while the public should have the right to access research its tax dollars have paid for, making data open would not really benefit them or science. My labmates argued that there is already too much data and too few people with the knowledge necessary to make meaning from the data. Furthermore, they argued, the frequency with which some grants require data to be made publicly available would require researchers to take time away from science during peak field season in order to enter and upload the data. And I followed along.

However, attitudes are shifting. Recently there has been a flurry of papers and blog posts on open data and what it means for ecology. For example, in a really nice article in Frontiers in Ecology and the Environment, Hampton and colleagues argue that if ecologists are to survive, they must both share and use shared data. Yet in a survey, the authors found that less than half of the papers produced using NSF funds had also published some or all of the data used to write the paper. As another incentive to "open" data, the authors argue that there are instances - such as when rapid responses to environmental crises are needed - when open data is used more extensively than what they refer to as "dark data". Thus worries about data overload and lack of relevance appear to be unfounded; the government needs bang for its buck, not tree-hugging.

Joern Fischer, a professor at Leuphana University responded to this paper on his blog, stating that while he believes sharing is a nice idea, in practice there is no shortage of data, and allowing other people not intimate with the sites from which the data was collected is dangerous. Ecology is apparently a touchy-feely science which cannot be reduced to data points that can be used to look for larger global patterns, a point which the Hampton paper also brings up.

But I would argue that 1. getting too intimate with your site is dangerous (you start seeing patterns which aren't there, so you MAKE them there when you do statistical analyses), and 2. we really just need more complete metadata, including many pictures of research sites throughout the seasons. For example, there have been fires in various plots at the Boston Area Climate Experiment, and they have been logged in the online shared lab notebook. However, to my knowledge, this information is only accessible to people working at the site. "Hidden" metadata like this must be made available to anyone reading papers and using the associated data to complete a meta-analysis of climate warming effects themselves. 

Another point that Joern brings up is that field ecologists will do the hard work collecting data and have to publish in smaller, regional, less-prestigious journals while the modelers sit at their desks, distant from the field, and compile all this data into articles the top journals are begging for. I have a number of gripes with this statement. First, if you are doing ecology to get publicity, you are in the wrong field. That applies for all desk-, lab-, and field-bound types. Second, this separation between writers and doers is ancient - how many techs do biomedical labs have, and yet PIs write the paper with no input from the technicians about what funky things happened along the way? Third, having gone from an almost exclusively field-based position to an almost exclusively computer-based one, I would do anything to be spending my summer outside looking at nature's pixels; working at a computer is not some lazy-ass bliss. Nothing is. Fourth, most ecological data collection can be done by minimally-trained volunteers (Earthwatch actually requires that projects it funds use volunteer data collectors extensively); I reckon the future of ecology will be a PI with some model or question they want to ask, going to public data, identifying a hole, and involving the public to collect that data, and possibly analyze it. It seems like a grant-writers dream given the current funding requirements.

So what are we really worried about? The idea of more work? Being responsible for a broader array of literature? Isn't it our job to understand the world? Ecologists don't write grants which say "I want to understand exactly what happens in the four 6m*6m plots I will be studying", but rather "I will design a study using four 6m*6m plots superficially representative of the broader environment with the hope of understanding patterns and processes in ecology which can be extended to larger spatial scales". 

But to scale up in this day and age, we have a responsibility to not just conjecture, but actually test it. If nobody is asking the same question (or if it has been asked, but the data has been analyzed inappropriately), and we only have published results to go on, how will we do this? We can ask people for their raw data, but emailing busy professors who have to dig up datasets not necessarily formatted for sharing is a time-consuming process. 

It's time to go beyond the costs of taking the time now to put your data in a clear format for others (and you a few years down the line) to access, and to think long-term. That is not to say that I think all data should be analyzed blindly without respect to site intricacies; we don't know what factors are important in ecological data, and how they may differ with time and space. However, looking over larger landscapes allows us to examine broader patterns and identify best practices for land management in the absence of finer resolution data, and if the metadata we have does not predict responses of interest at a broader scale, we have a reason to apply for more funding to do field work and ask why. 

For a field so obsessed with statistics, such aversion to testing the effect of increasing sample size seems ridiculous. 

For a more positive spin on open data, Chris Lortie of York University has made a pre-print available on the role of open data in meta-analyses which is available here.

Saturday, July 13, 2013

Cows can fly!

At the Gordon Conference last week, I was introduced to flying cows (aka Hoatzin, or stinkbirds), which, like happy cows, feed almost exclusively on leaves. Because a diet composed exclusively of leaves is incredibly poor in nutrients and hard to digest, like cows, hoatzins use microbes to ferment the food they eat. 

A hoatzin. Hoatzins are awesome not only because they are "flying bioreactors", but also because they are a bit like modern-day versions of Archeopteryx, the ancient gliding bird ancestor which had claws on its wings which enabled it to climb up trees.  Hoatzins live in the Amazon basin. Image courtesy of

 Both animals have a wide array of bacteria which make cellulase and lignase enzymes the host animal cannot. These enzymes break down leaf components such as cellulose (long strings of glucose linked together) and lignin (the irregular, phenolic (or ringed) compounds which give the leaf structure), which the microbes ferment into short-chain fatty acids such as butyric acid (which gives Parmesan its "distinctive" smell), propionic acid (which smells like really bad sweat), and acetic acid (as in vinegar). Because this process is relatively slow, the animals must eat a lot of food and have a large fermentation chamber; hoatzins are poor flyers and have to have an extra bump on their chest to help balance on branches so their full gut doesn't topple them, and the cow rumen is so big you could probably fit an adult human in it, though I don't think anyone has tried it.

Compare how much space the crop - the pouch birds use to store food if it over-gorges itself - takes up in the hoatzin (left) compared to the chicken (right). This is where the "pre-digestion" of vegetation occurs in the hoatzin. Small amounts of fermented fluid are released into the small intestine where the short chain fatty acids can be absorbed. Pictures from and

 Cows and hoatzins aren't the only animals which depend on microbes to break down their food. We too depend on microbes, except the majority of our microbes live in our large intestine and feed on our "leftovers" because most of our nutrients are absorbed in the small intestine. Research indicates that some other organisms, such as the giant panda, have lost some of the ability to degrade complex plant matter, and their genomes contain fewer genes encoding enzymes involved in this process than their nearest omnivorous relatives. This might explain why there have been reports of mother panda's feeding offspring their feces - populating your gut with the right microbes is obviously important if you cannot digest your food yourself.

Of course, pandas aren't the only animals to practice coprophagy (poo-eating). Babies do it. Dogs do it. And rodents like rabbits and guinea pigs do it. The last two animals are relatively easy to explain...they are hindgut fermenters, which means the majority of the microbes responsible for breaking down the plants they eat live in a part of the gut which comes after where the majority of absorption occurs. Therefore, in order to get all of the nutrients out of the food they have taken in, the food has to pass through the gut a second time. But babies and dogs...let's just say I don't kiss them. 
If you want to learn more about poo, Wikipedia has your a** covered

Monday, July 8, 2013

Baas-Becking for Trouble?

I am currently at my first conference (The GRC on Applied & Environmental Microbiology), and I thought that writing about some of the topics being covered at it would be good. Last night, the conference opened with a discussion of the ubiquity of microbe "species", so I thought that would be a good place to start here too.

Perhaps one of the most provocative statements made by a microbiologist to date is Baas Becking's 1934 statement that "alles is overal: maar het milieu selecteert". This translates to "Everything is everywhere but the environment selects", which I interpret as through wind and wave, microbes have the ability to disperse anywhere on the planet, although whether or not they are able to thrive and grow depends on their needs.

 You may think this sounds a bit obvious - how could something like Neisseria gonorrhoeae, the human-dependent bacteria which causes gonorrhea, be found surviving and thriving in Antarctica, thousands of miles from the nearest human? And we know that the obligate pathogen Bacillus anthracis, which causes anthrax, is not in most people's lungs, because if it was, they would be dead.
And yet this question is under particularly intense debate at the moment. But why?

To understand this question, we have to consider the journey environmental microbiology has taken since Becking made this statement. Twenty or thirty years ago, if you wanted to know whether your microbe of interest was everywhere, you would have to take samples of water or soil or rocks from all different places, and then use a series of different growth conditions to try and enrich for the microbe. But not all microbes are culturable using current techniques, or perhaps at all, so we are missing out on some of the picture. But perhaps more importantly, a given microbe may be very easily cultivated and identified in samples from some places, and present but impossible to culture from another place, meaning that it may be present - even thriving - but not detected. Shockingly, this is the case for some strains of fecal bacteria used as indicators of water quality - they may become unculturable after passing through wastewater treatment, making it difficult to assess the safety of the effluent. 

Fortunately, the rapid growth of new culture-independent methods for detecting microbes in the environment has ensured that our understanding of who is present (though not always what they are doing) is much less of a problem. In these methods, researchers collect a piece of the environment (seawater, soil, leaves, rocks), extract the DNA, and using microbe-specific DNA fragments as primers to intiate sequencing reactions, they sequence the DNA (usually just the ribosomal RNA sequences) in the sample. These rRNA sequences are like barcodes for the microbes, and the most widely-used definition of bacterial "species" is based on similarity of this sequence. Thus by sequencing just a short stretch of DNA, we can see who is present, and theoretically we can detect any microbe that is present whether or not we know anything about its preferred growth conditions. This makes it much easier to answer the "everything is everywhere" question! Theoretically.

Even with this enhanced ability to see who is where, we are still debating whether everything is everywhere, possibly because, as my PI pointed out, this question means something very different to the day it was first made. In a study examining seasonal changes in the microbial community at a site in the English Channel, it was noted that organisms previously thought to be lost from the community were in fact present in low numbers and possibly deeper in the water column; this is the so called microbial seedbank hypothesis. Microbes are everywhere, in low abundance in various stages of dormancy, and the environment selects from this pool. Here, time (everywhen) is used as an analog for everywhere.
But other studies have concluded that in fact, everything is not everywhere. For example, in a study utilizing data from thousands of samples taken all over the global oceans, researchers from Woods Hole found that in some instances, geographical proximity, rather than environment type,  dominates whether a given microbial species is present. The environment selects, but dispersal limitations also play a key role in this.

Some researchers have responded to the observation that everything is not everywhere by stating that not all microbes are found in all samples because "sequencing isn't deep enough" - that is, not enough DNA has been sampled and sequenced from the environment - and some of the "singletons" (or sequences which appear only once in a sample) which are routinely assumed to be sequencing errors and therefore discarded may be real, though rare organisms. Furthermore, there is always at least some sequencing bias - the primers used to initiate sequencing runs may not bind all bacterial genomes equally or at all, meaning that some microbes are missed. Even if we could sequence all kinds of bacteria, the depth neccessary would come at a high cost: Tim Vogel of the Ecole Centrale de Lyon estimated that we would need about a thousand Illumina sequencing runs to get all the microbes in a gram of soil, which would cost in the millions of dollars per sample. Of course, as many of the speakers and commentors brought up last night, a much cheaper way to prove that everything is everywhere is to define everything at a broad taxonomic level (ie bacteria vs. E. coli 0157:H7 substrain xxx) and everywhere at a large scale (for example, on this continent)!

So after all that, is it worth it to try and sequence all these bacteria to see if everything really is everywhere? Last night, Rob Knight told us that knowing that everything is everywhere is very important for understanding how to treat patients. Take a patient about to undergo chemotherapy that will wipe out his immune system. If a potential pathogen is already in his body, putting him in a clean room will do little good. But if it isn't, then taking this preventative approach could save his life. But in other systems such as soils, there appears to be sufficient microbes doing the same thing, and stochastic processes driving the extinction and local recolonization of species, that everything being everywhere isn't a particularly good (or "biologically informative") debate to have. Maybe we need to look at whether functions - rather than arbitrarily defined species - are everywhere, and what functions the environment selects for.