Increasing productivity in an increasingly productive world

Is it worth the time?

One of the things I have been thinking about lately is how to further increase my own productivity.  Regardless of your career goals, increasing your productivity is only going to help you accomplish more (by definition) and increase your esteem as a professional.  Productivity is an interesting concept to me because it is, to a large extent, quantifiable.  How many papers did you publish this year?  How much funding did you bring in?  What kinds of committees did you serve on and what did you accomplish exactly?  All of these variables represent some measure of a person’s productivity.  Naturally, a lot of effort is spent on determining what the best measures of an individual’s productivity are – and this is a very healthy and necessary practice.  For academics and researchers, these measures usually boil down to the quality and quantity of published papers (not always in that order).

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What we’re reading: Grouper spawning, pollinator-mediated isolation, and ambivalent advice about grad school

Librarian

In the journals

Almany, G.R., Hamilton, R.J., Bode, M., Matawai, M., Potuku, T., Saenz-Agudelo, P., et al. 2013. Dispersal of grouper larvae drives local resource sharing in a coral reef fishery. Current Biology 23: 626–630. doi: 10.1016/j.cub.2013.03.006.

Using genetic parentage analysis, we measured larval dispersal from a single, managed spawning aggregation of squaretail coral grouper (Plectropomus areolatus) and determined its contribution to fisheries replenishment within five community tenure areas up to 33 km from the aggregation at Manus Island, Papua New Guinea.

Moe, A.M. & Weiblen, G.D. 2012. Pollinator-mediated reproductive isolation among dioecious fig species (Ficus, Moraceae). Evolution 66: 3710–21. doi: 10.1111/j.1558-5646.2012.01727.x.

Selection on pollinators maintaining host specificity appears to be an important mechanism of contemporary reproductive isolation among these taxa that could potentially influence their diversification.

In the news

On the mounting costs of the U.S. “sequester” for science funding.

NSF pushes back on Congressional prying into peer review.

“I’m very glad that I went to graduate school—my life would be different, and definitely worse, without it. But when I’m asked to give students advice about what they should do, I’m stumped.”

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CSEE Kelowna

For those of you who find yourselves in Kelowna, British Columbia this week, you are hopefully enjoying yourself at the annual Canadian Society for Ecology and Evolution (CSEE) meeting!

CSEE 2013

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What we’re reading: Evolutionary context for disease markers and why everyone has at least one famous ancestor

Library

In the journals

Dudley, J.T., Chen, R., Sanderford, M., Butte, A.J. & Kumar, S. 2012. Evolutionary meta-analysis of association studies reveals ancient constraints affecting disease marker discovery. Molecular Biology and Evolution 29: 2087–94. doi: 10.1093/molbev/mss079.

We find that the current approaches show a propensity for discovering disease-associated SNPs (dSNPs) at conserved genomic positions because the effect size (odds ratio) and allelic P value of genetic association of an SNP relates strongly to the evolutionary conservation of their genomic position.

Ralph, P. & Coop, G. 2013. The geography of recent genetic ancestry across Europe. PLoS Biology 11: e1001555. doi: 10.1371/journal.pbio.1001555.

 We find that a pair of modern Europeans living in neighboring populations share around 2–12 genetic common ancestors from the last 1,500 years, and upwards of 100 genetic ancestors from the previous 1,000 years.

See also: the authors’ FAQ on the article and very nice discussion by Carl Zimmer.

In the news

More (not particularly optimistic) thoughts on political interference with peer review.

What do you do to help make your lab a nice place to work?

Jeremy’s launching a new side project: surveying LGBTQ folks working in science. If that describes you or any of your friends or colleagues, take the survey and pass along the link!

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What we’re reading: GWA with low coverage and rare variants, cardenolide resistance, and felony experimentation

Bookshelf

As we head into the weekend, here’s a few things we’ve noticed that are worth your screen-time.

In the journals

Navon, O., Sul, J.H., Han, B., Conde, L., Bracci, P., Riby, J., et al. 2013. Rare variant association testing under low-coverage sequencing. Genetics, doi: 10.1534/genetics.113.150169.

In this paper, we propose two novel methods for detecting association of rare SNPs with disease risk, using low coverage, error-prone sequencing. We show by simulation that our methods outperform previous methods under both low and high coverage sequencing, and under different disease architectures.

Petschenka, G., Fandrich, S., Sander, N., Wagschal, V., Boppré, M. & Dobler, S. n.d. Stepwise evolution of resistance to toxic cardenolides via genetic substitutions in the Na+/K+-ATPase of milkweed butterflies (Lepidoptera: Danaini). Evolution, doi: 10.1111/evo.12152.

Despite the monarch butterfly (Danaus plexippus) being famous for its adaptations to the defensive traits of its milkweed host plants, little is known about the macroevolution of these traits.

In the news

Infuriating: Sixteen-year-old conducts a DIY chemistry experiment that probably all of us have seen done, ends up charged with a felony.

Still more on the increasingly worrying politics around U.S. government funding for science by Phil Plait.

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Well, at least we’ve got the President on our side

Follow-up about yesterday’s fretting about Congresspeople wanting to interfere with peer review at the National Science Foundation: President Obama was asked about this yesterday at an event celebrating the 150th anniversary of the National Academy of Sciences—and he looks to be on the right side:

Without directly referencing the new legislation [to re-work NSF peer review], President Obama spoke of maintaining the NSF’s control over social-science grants. “One of the things that I’ve tried to do over these last four years, and will continue to do over the next four years, is to make sure that we are promoting the integrity of our scientific process,” he said. “Not just in the physical and life sciences, but in psychology and anthropology and economics and political science, all of which are sciences,” he said.

Not that this is reason to breathe a sigh of relief and go about your business; as I said yesterday, I think we may see Republicans trying to make NSF into a punching bag a lot more frequently in the near future.

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Congress takes a worrying interest in peer review at NSF

Capitol Hill Spring

The U.S. Capitol, where the House Committee on Space, Science, and Technology is getting to be way more “House of Cards” than “The West Wing.”

Science Insider reported yesterday that Lamar Smith, a Republican congressman from Texas and the chairman of the U.S. House Committee on Space, Science, and Technology, is planning to introduce legislation to change the way the National Science Foundation decides how to fund proposed projects. The article doesn’t provide access to the full text of the draft bill, but says that it would require NSF director to certify, on the Foundation’s website, that every funded project

1) “… in the interests of the United States to advance the national health, prosperity, or welfare, and to secure the national defense by promoting the progress of science; 2) “… the finest quality, is groundbreaking, and answers questions or solves problems that are of utmost importance to society at large; and 3) “… not duplicative of other research projects being funded by the Foundation or other Federal science agencies.”

This is on the heels of an April 17 hearing in which the committee chairman suggested that “we might be able to improve the process by which NSF makes its funding decisions,” asking acting NSF Director Cora Merrett how the agency could better ensure that it funds projects in “the national interest.”

Of course, it’s often difficult to point to specific applications that any particular project of basic scientific research might have for “the national interest.” That’s the point of NSF—to fund research that won’t be done by the private sector because the “payoff” is just … knowledge. Not some specific technology or profit or benefit, but the foundation for work that might, eventually, lead to all of those things.

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What we’re reading: readings for DNA Day, estimating Ne, and open-sourced data visualization

Microfiche Reader on Level 7

As we head into the weekend, here’s a few things we’ve noticed that might be worth your screen-time.

In the journals

Sixty years ago Thursday, Nature published three papers that unravelled (ha!) the molecular structure of DNA. They’re freely available online. But here’s the paper from that archive you mignt not know about already, which was published almost 70 years ago:

Avery, O.T., MacLeod, C.M. & McCarty, M. 1979. Studies on the chemical nature of the substance inducing transformation of pneumococcal types. The Journal of Experimental Medicine 79: 137–159.

Griffith found that mice injected subcutaneously with a small amount of a living R culture derived from Pneumococcus Type II together with a large inoculum of heat-killed Type III (S) cells frequently succumbed to infection … The fact that the R strain was avirulent and incapable by itself of causing fatal bacteremia and the additional fact that the Type III cells contained no viable organisms brought convincing evidence that the R forms growing under these conditions had newly acquired the capsular structure and biological specificity of Type III pneumococci.

Macbeth, G.M., Broderick, D., Buckworth, R.C. & Ovenden, J.R. 2013. Linkage disequilibrium estimation of effective population size with immigrants from divergent populations: A case study on Spanish mackerel (Scomberomorus commerson). G3: Genes|Genomes|Genetics 3: 709–717. doi: 10.1534/g3.112.005124.

A correspondence analysis algorithm was developed to detect and remove outlier genotypes that could possibly be inadvertently sampled from cryptic species or nonbreeding immigrants from genetically separate populations. … When putative immigrants were removed from the empirical data, 95% of the Ne estimates from jacknife resampling were greater than 24,000.

In the news

Grad student stipends aren’t exactly geared towards a life of luxury—at Southern Fried Science, they’re doing a series of posts providing advice for life on the stipend. (Via Scicurious, who adds her own thoughts.)

Trevor Bedford is building a pretty neat online library of his own science visualizations. We especially like the coalescent simulation.

Ken Wissoker, the editorial director of Duke University Press talks about the future of academic publishing, and doesn’t sound too worried.

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Species distribution models in R

Our example dataset, from Godsoe et al. (2010).

Our example dataset, from Godsoe et al. (2010).

One of our most consistently popular posts of the past few months has been Kim Gilbert’s introduction to using geographic data to make maps in R. But once you’ve made a nice map of your collection sites, you’ve only just started to tap the possibilities of spatial data in R. With a suite of packages anchored by dismo, you can use R and open-sourced climate data to determine the environmental conditions your favorite species requires—by building a species distribution model.

Species distribution models (SDMs) are handy any time you want to extrapolate where a species might be based on where you know it actually is. Maybe you’re trying to figure out where would be fruitful to do more sampling; maybe you want to know where your favorite critters probably lived back during the last ice age; maybe you want to know what regions will be suitable for your favorite critters after another century of global climate change. The basic idea is,

  1. Take a list of locations where you know you can find a species and identify the climate (or other environmental conditions) at those locations;
  2. Build a statistical model (using one or more of several available methods) that differentiates the climate (or other conditions) at the points where your species is found from other points where your species isn’t found; and
  3. Apply the model to climate (or other conditions) from some other time or place to estimate a probability that your species would be happy there.

This post provides a little demonstration of what you can do given a reasonably good set of collection sites and a no-longer-cutting-edge laptop. But caveat lector: actually building SDMs for publication-grade analysis requires a lot more work that what I’m presenting here. If you like the possibilities, you should start by reading the “vingnette” documents “Species distribution modeling in R” [pdf] (by dismo developers Roger Hijmans and Jane Elith) and “Boosted regression trees for ecological modeling” [PDF] (by Elith and John Leathwick). Those provide lots of detail and further reading lists, including a relatively recent review by Hijmans and Elith. They’re also the starting point for the demonstrations below.

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What we’re reading: Coelocanth genomics, barcoded pollen, and publication priorities

BookshelfAs we head into the weekend, here’s a few things we’ve noticed that might be worth your screen-time.

In the journals

Amemiya, C.T., Alföldi, J., Lee, A.P., Fan, S., Philippe, H., MacCallum, I., et al. 2013. The African coelacanth genome provides insights into tetrapod evolution. Nature 496: 311–316. doi: 10.1038/nature12027.

Coelacanth protein-coding genes are significantly more slowly evolving than those of tetrapods, unlike other genomic features.

Parducci, L., Matetovici, I., Fontana, S.L., Bennett, K.D., Suyama, Y., Haile, J., et al. 2013. Molecular- and pollen-based vegetation analysis in lake sediments from central Scandinavia. Molecular Ecology doi: 10.1111/mec.12298.

Here, we compared pollen-based and metabar- coding approaches to explore the Holocene plant composition around two lakes in cen- tral Scandinavia. At one site, we also compared barcoding results with those obtained in earlier studies with species-specific primers.

In the news

We should all have such a problem: how do you decide what papers to publish first?

Is science’s image problem really a careers problem?

Shameless self-promotion: Jeremy reviews a new book on scientific teaching.

More on E.O. Wilson: maybe the real problem is that he doesn’t understand how collaboration works.

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