Lots of other interesting stories in the story collection as well, so if you have the time, do check it out (free samples accessible).

But what if that water’s frozen?

Recently, bacteria from the Antarctic permafrost (aka Planococcus halocryophilus strain Or1) have been isolated that can grow at -15°C and can keep metabolizing (eating, digesting, etc.) at -25°C.

Brrr…

So, what’s their trick?

The research team from Canada/USA/Australia set out to find some features of the beasties that allow them to do this, and report their results in The ISME Journal.

Here’s what they found in short (for the details, the article is freely available):

• The cell envelope becomes encrusted (for protection?) at low temperatures.
  

  a) at 25°C (arrows point at nodules), b) at -15°C, c) dividing at -15°C. (from Mykytczuk et al., 2013)

• 

  Cell wall structure of Gram-positive and -negative bacteria. (Wikimedia Commons, Graevemoore)

  The plasma membrane is seriously remodeled, replacing branching fatty acids with saturated ones.

• Unsurprisingly, the bacteria contain numerous genes involved in mechanisms to cope with cold and salty conditions. Additional analyes show that, as the temperatures drop, several of these genes are activated.

• The building blocks of their proteins (amino acids) are distributed in such a way that the proteins, which are very important for the proper functioning of the cell, are very flexible.

• Our little friends exploit isozyme exchange, which means that they can switch between enzymes that are build out of different amino acids, but perform the same function. So, to put it simply, they have regular and cold versions of important enzymes.

A whole bag of tricks they got (yes, I felt like Yoda there).

An interesting find. The limits of life seem to be pushed further and further back the more we learn.

In their conclusion, the authors highlight the following two points:

• Organisms such as this can teach us a lot about dealing with the cold.

• This bacteria, and similar organisms, might prove useful in the search for extraterrestrial life (cold, watery, salty habitats are thought to be present on, for example, Mars and Saturn’s moon Enceladus).

(Slightly philosophical afterthought: However, E.T., if he/she/it exists, could look radically different as well… Beware the limits of inference under (necessarily?) incomplete knowledge…)

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Mykytczuk, N., Foote, S., Omelon, C., Southam, G., Greer, C., & Whyte, L. (2013). Bacterial growth at −15 °C; molecular insights from the permafrost bacterium Planococcus halocryophilus Or1 The ISME Journal, 7 (6), 1211-1226 DOI: 10.1038/ismej.2013.8

Now imagine you live with a lot of people together, in an enclosed city.

Read the rest at United Academics…

Conceptual model of eco-evolutionary dynamics (Carlson, Quinn & Hendry. 2011. Heredity.)

For a long time, it has been thought that evolutionary and ecological research were quite separated from each other. After all, evolution takes place on long timescales while ecological events usually happen much faster. At least, that was the common perception. Lately, however, it has become clear that, in some cases, the relevant timescales in the consideration of evolutionary and population dynamics are not that dissimilar. Hence, the recent development of eco-evolutionary dynamics.

Such feedback loops between ecology and evolution are thought to be particularly strong in cooperatively growing species that produce ‘common goods’. A bunch of do-gooders, in other words. But, as with all do-gooders, cheaters might lurk in the shadows, ready to reap the benefits without suffering from any of the costs. As such, the cheaters will be fitter than the cooperators. So, the amount of cheaters will rise and that of the cooperators will fall. But, that also means less common goods. Which in turn means that cheating becomes less rewarding. And so it goes back and forth, sometimes leading to a viable equilibrium.

A recent study in PLOS Biology has tested this in yeast.

The laboratory populations of yeast possessed a ‘social gene’, SUC2, which allows the yeast cells to break down sucrose into fructose and glucose. But, the vast majority of the sugars produced this way are not available for the producing cell and diffuses away to other cells.

Then what happened?

• Populations without cheaters either quickly collapsed or rapidly approached a stable population size (depending on the starting size of the population).

• Populations with cheaters moved towards an equilibrium, a (happy?) living together of do-gooders and freeloaders.

Cheating doesn’t seem too bad then?

The researchers, however, did find something else as well. Populations with cheaters were less resilient to environmental challenges. Indeed, when the environment in which the yeast was growing rapidly deteriorated, the populations with cheaters collapsed, even at rates of deterioration that cheater-free populations could recover from.

In the conclusion, the authors mention that it could be important to consider the interplay between evolutionary and population dynamics to understand the variation in cooperative behaviors in species, and the “demographic fate of those species that rely on cooperation for their survival.”

Which makes me think about humans (apologies for the anthropocentrism).

Rely on cooperation for survival? Check.

Rapid environmental change(s)? Check.

Cheaters in the population? Check.

A recipe for disaster?

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Sanchez, A., & Gore, J. (2013). Feedback between Population and Evolutionary Dynamics Determines the Fate of Social Microbial Populations PLOS Biology, 11 (4) DOI: 10.1371/journal.pbio.1001547

Design of one of the first ecological experiments, studying the performance of different species mixtures planted in different soils (by George Sinclair in Woburn Abbey, Bedfordshire, UK, 1816) (Wikimedia Commons, public domain)

That’s what a few researchers set out to investigate in a recent paper in PLOS ONE.

In their attempt to provide some insight into the matter, they conducted two surveys, one aimed at a large number of journals (136) that publish ecological research, and a second one that focused on eight major (or ‘core’) journals.

Next, they randomly selected 25 articles per year (from 1981 – 2010) from each journal. These articles were subsequently characterized for three aspects (I’ll keep it general, for those interested in more details, the paper is open access):

Domain of Research

Despite the relatively recent emphasis on the importance of interactions between species and communities, and the call for a ‘whole ecosystem perspective’, the majority of articles (over 60% in both surveys) still focused on single species. With regards to topic, there were two topics that have been getting increased attention in recent years, in both surveys: biodiversity and climate change. The other slight changes differed between the general and core survey.

Just a small glimpse of the complexity of species interactions. (Wikimedia Commons, NOAA Great Lakes Environmental Research Laboratory)

Type of Research

The major research tools didn’t change: observation and experiment accounted for over 80% of the research. Intriguingly, modeling is just as common as it was thirty years ago, despite the greatly growing availability of new modeling tools. Data analysis did become more prevalent, starting its rise in the nineties (long live the internet?). Comparing the two surveys revealed that the experiment/observation ratio was higher in the core journals.

Basic or Problem-solving?

Here, the biggest change was found. In both surveys, a steady, consistent increase in problem-solving studies (which the authors define as investigations that “relate to actual, specific environmental problems, in an attempt to provide solutions (or at least new insights on how to make progress towards solutions)”)could be discerned, on average a roughly 5% annual change.

(Lack of) Change?

So, is ecology a rapidly changing field? According to this study, not so much. There are changes in the research, for sure, but these seem to be trickling through rather slowly. The main research subjects and research methodologies haven’t changed all that much in the last three decades.

However, some points worth noting, as mentioned by  the authors.

• The rate at which basic questions are being answered wasn’t investigated (which is very difficult to do).

• Conceptual shifts that pervade the field (for example, network thinking) couldn’t be detected.

• Changes in particular methods and technologies (say, molecular and genetic tools) weren’t studied.

What can we say, then, based on this study? Well, the main change that came to light in this general survey of ecological research, is a shift from basic to problem-solving inquiries. If this persists, it may be some form of a transition in the field of ecology.

The authors conclude as follows:

Our results may be disturbing to some researchers, insofar as they portray an ecological discipline which is considerably less dynamic than ecologists would like to believe. The value of this research is precisely in reviving the debate and presenting an opportunity for self-assessment to those who strive to advance the discipline, all of which can serve to stimulate the investigation of new and groundbreaking tools, paradigms and perspectives. Only through meta-scale monitoring of the scope of research can we understand, and hope to influence, the trajectory of ecological research in the years to come.

Keep in mind, though, that assessing an entire and broad field of research, such as ecology, is a tricky thing. Besides the three points already stated earlier, think about the following:

• Are the three aspects assessed here the only ones that could point towards big changes?

• And what constitutes a ‘big change’ in this context?

• Also, it might be so that new theoretical ideas and developments are harder to test (it might be more convenient to focus on one or a few species, rather than the entire biological community, including micro-organisms, of an ecosystem).

• For those philosophically inclined, does science/ecology move in fits and starts (paradigm shifts etcetera), or is this a (partially?) flawed conception? How exactly does science change/progress?

Nevertheless, always interesting to get a broad view on the research in a certain discipline, and the (lack of?) change therein.

_________________________________________________________

Carmel, Y., Kent, R., Bar-Massada, A., Blank, L., Liberzon, J., Nezer, O., Sapir, G., & Federman, R. (2013). Trends in Ecological Research during the Last Three Decades – A Systematic Review PLoS ONE, 8 (4) DOI: 10.1371/journal.pone.0059813

Wondering how the hybrids come into play? Find out at United Academics…

]]> http://beastbardbot.wordpress.com/2013/04/29/hybrid-chimps-in-europe/feed/ 0 gunnardw http://beastbardbot.wordpress.com/2013/04/27/a-year-of-blogging/ http://beastbardbot.wordpress.com/2013/04/27/a-year-of-blogging/#comments Sat, 27 Apr 2013 11:51:41 +0000 http://beastbardbot.wordpress.com/?p=710 ]]> Exactly one year ago, The Beast, the Bard and the Bot were born.

Time for some reflection.

But first, a bit of numerical material (current at the time of writing).

Some Numbers

Posts: 96, including this one.

Total views: 19672

Max views on single day: 631

Top 5 countries providing visitors:

1. United States (8264)
2. United Kingdom (1931)
3. Canada (1206)
4. Belgium (922)
5. India (640)

Top 5 most viewed posts:

1. Animal Empathy? (938)
2. Picky Moms, Sexy Sons (855)
3. Biological Dark Matter and the Shadow Biosphere (786)
4. Malthus, Darwin and the (Sustainable?) Future of Humanity (752)
5. Are Humans Still Evolving? (719)

Of course, keep in mind that later, more recent posts have had less time to accumulate views.

Are these good or bad numbers? Who knows. What does good and bad even mean in this context? The more, the merrier? Or does the time people spend here count as well? In other words, is a visitor who quickly browses through several posts/pages ‘better’ than someone who reads one post in detail? After all, the former will get you more views than the latter. On the other hand, the latter is probably more interested in what’s written than the former.

Anyway, I guess it’s probably neither good nor bad. It is what it is.

And, naturally, a big thank you to all visitors, large or small, long- or short-term, interested or bored.

Fitting the Profile

A couple of fairly recent studies have looked at blogs that focus on scientific research and have investigated the profile of the bloggers behind them. So, who are those science bloggers (note that it’s a snapshot. Things change.)?

• The bulk (about two thirds) is male: check.

• The majority categorize their blog as being about biology (36%, first reference)/life sciences (39%, ref. 2): check.

• Almost three quarters of science bloggers included in the study has an active Twitter account: check (@evolveon. Shameless, I know.)

• Most (about 82% in ref. 1 and 86% in ref. 2) write in English: check.

• They tend to know what they’re talking about. Almost a third possesses a PhD, and over a quarter is working towards one: uncheck (although I try to make sure the information here is accurate, and I do have some university education under my belt.)

• Almost 60% is affiliated with/studying at an academic institute: half check. (About the first half of the year: yup. Student. Second half: nope.)

• They feel comfortable blogging under their real name (84%): let’s say a three-quarter check. (The attentive reader has no problem finding out who I am.)

• Close to 70% have independent blogs, meaning that they don’t belong to a blogging network: check.

Score? 6.25/8. Or: ‘Congratulations/Commiserations (delete as applicable), your score indicates you’re an average science blogger.’ Hmm, again is this a good or bad thing? And does that question even make sense?

What’s Next?

Good question.

I (and perhaps some of you as well) have noticed that, when this thingy started, I posted more, and more regularly. Then, after a while, it tailed off a bit, becoming more sporadic and erratic. I don’t know what that means, if anything. It’s often recommended to maintain a fairly regular schedule when blogging, but I don’t want it to become a chore, an obligation. So, I blog when I feel like it. Hah, it’s not like I’m getting paid for it or something. (Hint to whoever’s willing to pay for science/philosophy writings?)

Well where does this leave me?

‘To blog or not to blog?’, that is the unoriginal cliché question.

Why do I even blog? Vanity? Trying to get better at writing? Spreading interesting tidbits of science news? Probably some odd mixture of all of these and more. Occasionally, the feeling that there are already too much blogs creeps up on me, but is that so?

To conclude, who knows what the future holds in its sweaty palms? Not me. For now, The Beast, the Bard and the Bot remains, even though I’m considering some changes.

All I can really say at this point, is that I don’t know what’s next.

But stay tuned…

______________________________________________________

Fausto, S., Machado, F., Bento, L., Iamarino, A., Nahas, T., & Munger, D. (2012). Research Blogging: Indexing and Registering the Change in Science 2.0 PLoS ONE, 7 (12) DOI: 10.1371/journal.pone.0050109

Shema, H., Bar-Ilan, J., & Thelwall, M. (2012). Research Blogs and the Discussion of Scholarly Information PLoS ONE, 7 (5) DOI: 10.1371/journal.pone.0035869

And most of these well-known publishing venues for research are primarily (or exclusively) interested in spectacular positive results.

Thus arises temptation.

Why not round up or down a little bit? Why not get rid of these nasty outliers? Or, in worse cases, why not make up some data from scratch?

Fraudulent science is born.

Recently, several high profile cases of scientific misconduct have been uncovered, such as the all-time record holding anesthesiologist Yoshitaka Fujii (172 papers) and social psychologist Diederik Stapel (> 50 papers) (and here’s a list of others). Of course, it’s not just perpetrated by people who already find themselves at a fairly advanced stage of their career. Starting researchers do it too, often in the attempt to improve academic job prospects. But when you get caught, the end of your academic career looms (let’s call this ‘publish and perish’).

So who’s to blame? When another case of scientific misconduct arises, the finger of the scientific community eagerly points towards the whole ‘publish or perish’ culture. The pressure to perform, to get data that can result in top-journal publications, weighs heavily on the shoulders of academic researchers, both young and old.

Can this be changed? Perhaps. But there are many aspects to consider, for example:

Supply and Demand

A first thing to realize, is that supply and demand come into play here. There is a limited supply of academic funding and job opportunities, for a large community of (aspiring) researchers. This means that funding agencies and academic institutions alike have to make a choice from an often large pool of applicants. How to make that choice? Why not look at the number and quality of publications? Or, to make it even easier, why not pour that into a single number (for example, the h- or g-index)? The issue is whether or not this number, or the publication record, captures all relevant aspects of an applicant. It seems an oversimplification.

Perhaps other things should be taken into account more. Outreach, teaching, originality, and other aspects of an (aspiring) researcher matter too. Of course, this is probably more difficult to capture in a list of publications, or an index. Also bear in mind that the ever-increasing pool of fresh PhD’s isn’t exactly going to lessen the competition. While a large number of highly educated people is not necessarily a detrimental development, it might prove fruitful to provide them with more research-inclined job options, beyond academia.

Too Positive

Another issue is the strong emphasis on spectacular, positive results in the vast majority of top-tier journals. And maybe the audience’s expectation of this. We all want to see great breakthroughs and exciting new hypotheses. But science advances as much by breakthroughs as it does by experiments that fail to support a hypothesis. As the saying goes, we learn by mistake. ‘Why doesn’t it work?’ is a question that often underlies new understanding. Sadly, negative results are really hard to get published (incidentally potentially leading to unnecessary and sometimes time-consuming expensive repetitions of experiments). There are, however, some recently established journals that focus on negative results (for example, the All Results Journals, or the Journal of Negative Results in BioMedicine, among others).

But, it would certainly be helpful if some of the top-ranked journals reserve a few (or even one) spot(s) in their issues for an interesting experiment that provided negative results. Other things in the publisher’s sphere of influence that might potentially diminish the occurrence of scientific fraud are open access and sharing of raw data, both of which seem to be gaining traction, and double-blind peer review, perhaps combined with a review emphasis on the experimental approach rather than the results and whether or not these support a certain hypothesis.

Degrees and Gray Zones

Not all fraud is equally bad. Making up data seems worse than deleting one annoying data-point. Nevertheless, both are generally considered to be justifiably ‘wrong’. But what about other things, such as scientific salami slicing (the practice where a certain experiment or research line is ‘cut’ into as much publications as possible), duplicate publications, or adding authors just for the sake of their name and fame? Are these practices ‘wrong’? They are frowned upon, for sure, but do they constitute legitimate cases of scientific fraud? After all, despite being surreptitious ways to boost one’s publication record or get published, they don’t involve fabricating or ‘massaging’ the data.

It might be a good idea for ethicists, philosophers and scientists to get together and discuss these matters. Where do we draw the line? What should be forbidden, and what merely frowned upon? And another question: are there differences between disciplines, and, if so, how should these be taken into account?

Ethics, Detection and Rehab

A final point to be addressed here is that of prevention and rehabilitation. Sure enough, it appears as though a large part of the responsibility lies with funding agencies, research institutions and the scientific publishers. However, the researchers themselves are not exempt from it. They too, bear some responsibility. Therefore, it could be useful to have graduate students follow a course on research ethics (which already often happens), and encourage them to look after each other (not in an ‘Orwellian-snitch’ sense, but as support when things become too much, so that, rather than doing something regrettable, they can talk to someone in a similar situation and, hopefully, refrain from making a potentially career-ending mistake). Perhaps the recent flurry of misconduct cases suggests that the detection rate is going up, due to increased vigilance among colleagues, better plagiarism detecting software,…?

Beyond prevention, there is the matter of rehabilitation. Getting caught for scientific fraud means, in the majority of cases, the end of an academic career, regardless of possible great work that was done by the person as well. When does an academic who’s been lead astray deserve a second chance, bearing in mind the earlier degrees and gray zones in scientific misconduct?

A Joint Effort

Scientists are people too, they can make judgment errors. Does this mean science is unreliable? No, fraudulent science is a minute proportion of the whole scientific enterprise (one does wonder, however, how much goes undetected…). There is no single solution. What is needed is a shift in perspective, a collaborative culture, unity in the quest for truth. To get closer to that unattainable ideal, inch by inch, agencies, institutions, publishers and scientists all have to work together.

_____________________________________________________

Fanelli, D. (2009). How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data PLoS ONE, 4 (5) DOI: 10.1371/journal.pone.0005738

Grieneisen, M., & Zhang, M. (2012). A Comprehensive Survey of Retracted Articles from the Scholarly Literature PLoS ONE, 7 (10) DOI: 10.1371/journal.pone.0044118

Primack, R. (2013). Scientific misconduct occurs, but is rare Biological Conservation, 157 DOI: 10.1016/j.biocon.2013.01.005

It’s called ‘Download’ and it’s about a man who awakes when his personality is downloaded into a new body after centuries of death/non-existence/’suspended digitization’/or whatever you want to call it.

The whole process from acceptance to publication went very smoothly, so kudos to the Interstellar Fiction staff.

Head over there and read it. And, if you have a spare moment or two, be sure to read the other stories as well. I’m honored to have my thingy among them.

No. You use cameras to capture their image.

For more, head over to United Academics.