Learning to write


I took a writing class!  Yes I did.  I probably shouldn’t admit it, really, because now you’ll all expect me to have improved immensely, and that makes me nervous.

The class was with Stacey Solie (@StaceySolie), and it was fantastic. I learned a lot and here are a few of my favorite tips:

Freewriting: Every day, set aside a dedicated chunk of time to just write.  Don’t worry about punctuation, spelling, grammar, or anything.  It’s great for writer’s block: you don’t even need to start at the beginning or anything.  It just helps get the ball rolling and get you out of whatever funk you’re in.  I’m trying to do at least 15 minutes per day (minimum).

Read your work out loud:  Admittedly, this is one that I knew about before, but it bears repeating.  I don’t do it nearly enough and I really should because when I do, I always catch mistakes.

Stop apologizing for your work: It’s a terrible habit of mine and doesn’t really accomplish anything.  For example, when giving an essay to someone to proof-read, it’s pointless to say things like, “Oh, here you go. It’s really bad, sorry.”  It’s probably got some bad parts, and some good parts, and whoever is reading it will figure it out without you telling them.

So I’m working on building confidence in my writing…



Know when to stop:  Try to recognize when you reach the point when your ongoing efforts cease to result in significant improvements. The “sweet spot”.  Stacey talked about this, and so did one of our guest speakers, Katie Arkema.  Here’s my own interpretation, in graphical form:


Bonus materials!

Thanks to the terrific @realscientists followers, who pointed out a couple of important points that I missed before!

READ! Yup, to become a better writer, you have to read. A lot. I mean, you should read every day, and be critical about it, too.  Ask yourself, what is it that makes a certain piece of writing excellent or terrible? What techniques does the author use? Is there anything about their writing that could be improved upon? These observations will all eventually sink into your brain and make their way into your own writing. Hopefully not word for word though, because that’s not cool.

Practice. This sort of goes with the “free-writing” point above, but let’s give it a whole section unto itself. Because that’s how important it is. Like many skills, it’s more about hard work than innate genius. Have you read that book, Outliers, by Malcolm Gladwell? In it, he talks about what all of these wildly successful people have in common. Sure, there are loads of factors that lead to success, but the one in common between them all was that they’d put a metric butt-load of hours into their craft. Ten thousand hours, minimum, to be exact. So put in your time!

Well there you go.  You know I’m not a writing expert, I’ve just listed/regurgitated things that I thought were useful or inspiring. Hope it helped! Feel free to add to the list in the comments. 🙂



Guest blogging at DSN

A couple of days ago, my very first guest post went up on Deep Sea News.  I am pretty excited about it, being a huge fan of DSN and all.  The post is about the efforts that have gone into protecting North Atlantic right whales near the busy shipping channel that goes through the Stellwagen Bank national marine sanctuary.  Check it out here:  Save the whales? There’s an app for that.

If you don’t already, Deep Sea News is well worth following – I mean, they have a squid with an eye patch as their logo, they have to be amazing.

Q: How loud are fin whale calls?

A:  Really loud!

Now that I’ve finally descended from my little soapbox (see this post), I guess it’s time to take my own advice.  I was inspired to go for it yesterday when I came across this blog post by Jessica Carilli: Why Geochemistry is Awesome.

Just last week(ish) my very first paper was published.  (Huzzah!)  If you feel so inclined, you can check it out for yourself here.  However, even I’ll admit that it’s a bit technical for someone who really just wants to get a big picture overview.  Here goes nothing!

“Source levels of fin whale 20 Hz pulses measured in the Northeast Pacific Ocean”

If you follow my blog, you probably already know that I’m pretty into fin whales.  They’re amazing and huge and, unfortunately, endangered.  And if we want to monitor their recovery and to avoid further risks from things like ship noise, ship strikes, and fishing activity, we need to have an idea of where they are and how they move around.

http://www.beringclimate.noaa.gov/essays_moore.html (photo by Lori Mazzuca)
http://www.beringclimate.noaa.gov/essays_moore.html (photo by Lori Mazzuca)

Problem is, despite being the second largest animal in the entire world, they are tough to keep track of.  They spend a lot of time far from the coast and a lot of time under water.  There are a few different techniques people use to study fin whales (and other whales, for that matter).  These include  visual surveys (from a boat or plane or land), radio and satellite tagging, and (of course) acoustics.  Each of these methods has its pros and cons. Passive acoustic monitoring is good because you can deploy instruments that can monitor for long time periods (months and even years), and you don’t need to worry about conditions at a certain time of year, or whether the animals are visible at the surface.

Let’s imagine for a moment that you have a hydrophone (which is an underwater microphone, essentially) and you want to listen to some fin whales.


There you are, hydrophone off the side of the boat, and you get lucky – you record a fin whale call!  Woo hoo!  Just hearing it is great.  But something else that is extremely useful is to be able to say how far away that whale was when it made the call (R in the picture).  That’s where some basic acoustics comes in.  If you measure how loud the call is at the hydrophone, and you know how loud the call was when it was generated, and you know something about the acoustic properties of the water, you can figure out how far away it was.  You can think of it like this: if you’re in a big room, and you shut your eyes, and someone else in the room starts talking, you can tell roughly how far away they are just by how loud their voice sounds in your ears.

Here’s the math, dead simple, I promise:

ML = SL - TL     (EQ 1)

In that equation, ML is “measured level”, SL is “source level”, and TL is “transmission loss”.  If you re-arrange the equation solving for TL, you get:

TL = SL - ML        (EQ 2)

What’s the deal with transmission loss?  Well, it accounts for the acoustic energy that is lost between the source (the whale) and the receiver (the hydrophone).  And it’s dependent on the range – the further apart the source and receiver, the greater the transmission loss.  Here’s the equation for transmission loss:

TL = 20 \log_{10}(R).         (EQ 3)

What all this boils down to is that if you know the source level (SL) and measure the receive level (ML), you can calculate transmission loss (TL), which you can then use to calculate range.  Awesome!  Except for one thing… source levels of fin whale calls are not really well known.  There have been very few published papers reporting fin whale source levels (e.g. [1],[2],[3]).  These results are useful, but because of the difficulties inherent in estimating source levels, relatively few calls were used in the final estimates (at most, 83).


This is where a BIG FAT DATASET really comes in handy.  And that’s just what we have:  a three year ocean bottom seismometer (OBS) deployment off the coast of Vancouver Island.  That’s 8 seismometers, collecting data for three years, at 128 samples every second.  And we see TONS of fin whale calls, especially during the winter months.

Fin whales have a very distinctive call.  It’s very low frequency, very loud, and only lasts for about a second.  And typically, a fin whale will make this call about one time every 25 seconds (although it does vary by location).  A couple of things make this call particularly handy for me.  First of all, they are so low frequency that they get picked up on OBSs.  Second, they are very similar from one call to the next, making an automatic detection algorithm relatively straightforward.  That means I can write code to tell my computer what the call looks like, and it will run through the data and find instances where that call shows up.  With hundreds of thousands of calls on 8 instruments, searching for the calls manually would take a hundred graduate students like a hundred years.  Okay, that’s an exaggeration, but it would take a LONG time.

How do we use this data to get at source levels?  The thing that makes it possible is that, in the first year of this three year dataset, we actually know where the whale is at the time of the call.  This is because my office mate, Dax, did his masters work on tracking whales near the OBS network.  Since we know where each call was generated, and we know where the seismometers are, we can calculate the range between source and receiver.


If you look back up to Equation 3, you can see that if we know the range, R, we can calculate the transmission loss.  And with TL and ML, we can estimate source level!  See, that wasn’t so bad…

A Slight Complication

If you know a bit about acoustics or seismology, you might have seen this coming:  OBSs don’t measure acoustic pressure level (ML) directly.  They actually measure ground velocity.  The amplitude of the ground velocity is definitely related to ML, but it’s dependent on what the seafloor is made of at that location, and angle at which the incoming sound hits the seafloor.  I would say that this is the most technical and complicated part of my paper, and since it is not critical to understanding the results, and also because it would take a long time, I will leave this for a separate blog post at some future date.  (if you’re especially curious, I encourage you to check it out in the actual paper).

The moment you’ve all been waiting for…

Or, um, you know.  Maybe not…  Anyway – the results!  A total of 1241 calls on 32 whale tracks were used to estimate source levels.  The mean source level was estimated to be 189.9 +/-5.8 dB re 1uPa @ 1m (see below for an explanation of this notation).  This is within the range of previous estimates, although slightly in the loud side.  The most recently published results were in 2008, where fin whale call source levels were measured in the Southern Ocean [1].  They found a mean source level of 189 +/- 4 dB, based on a total of 83 calls.

As part of the analysis, we looked at the variation of source levels over the duration of a dive and also between tracks.  We were surprised that we didn’t see any obvious trend over a dive – we expected that maybe as the whales ran out of breath, their calls would get progressively quieter, but we didn’t see any evidence of that.

Where the slop comes from

Part of reporting scientific results includes keeping track of where the uncertainties in the results come from.  The biggest contributors in this analysis were:  1) uncertainties in the location of the whales at the time of the call and 2) interference between the direct path acoustic arrival, and the “echo” that bounced off the sea surface.  Other potential sources of error include: estimated seafloor properties used to convert ground velocity to acoustic pressure level, sound speed profile, differences in the coupling between the seismic instruments and the seafloor.

The end… for now

And there you have it – that’s the gist of my paper.  I would love to dig into more of the analysis of the amplitude variations along tracks, and between individuals.  Maybe an even bigger “big fat dataset” would allow me to tease out additional clues…


** In my explanation above, I reported results as 189 dB re 1uPa @ 1m.  If you don’t study acoustics, that will probably look pretty mysterious.  Here’s what it means:  dB is decibels, which is a measure of loudness.  Decibels are measured as a logarithmic ratio of pressures:

dB = 20log_{10}\left(\frac{P_{meas}}{P_{ref}}\right)

Pmeas is the pressure you’re measuring, and Pref is a reference pressure. The reference pressure in water is 1uPa (micro Pascal) at a distance of 1 meter from the sound source.


[1]  Širović, Ana, John A. Hildebrand, and Sean M. Wiggins. “Blue and fin whale call source levels and propagation range in the Southern Ocean.” The Journal of the Acoustical Society of America 122 (2007): 1208.

[2] Charif, Russell A., et al. “Estimated source levels of fin whale (Balaenoptera physalus) vocalizations: Adjustments for surface interference.” Marine Mammal Science 18.1 (2002): 81-98.

[3] Watkins, William A., et al. “The 20‐Hz signals of finback whales (Balaenoptera physalus).” The Journal of the Acoustical Society of America 82 (1987): 1901.

Reading and writing and super-mussels

Don’t tell me how to interpret your results!

super musselsThe other day, I stumbled on a climate change skeptic website while doing research for my ocean acidification post.  This ‘skeptic’ article included a summary of a peer reviewed article by a prominent scientist on the effect of an acidic ocean environment on mussels near deep sea hydrothermal vents.  The summary included this description of the results of that paper:

[…] there is ample reason to believe that even the worst case atmospheric CO2-induced acidification scenario that can possibly be conceived would not prove a major detriment to most calcifying sea life. Consequently, what will likely happen in the real world should be no problem at all […]

Well, that’s amazing!  If that was the only summary I read, I might be led to believe a few things:

  1. There is rock-solid evidence indicating that ocean acidification, though it may be happening, is totally not a big deal.  Dude, look at those mussels!  They are doing great!
  2. The mussels adapted to environments even more acidic than the most dire projections by acidification “alarmists”, and
  3. the scientist who did that work is well-known and well-respected, and is clearly a climate change skeptic also.

I was curious, so I looked up the original paper to learn more [1]. This is the first sentence of the abstract by Tunnicliffe et al. (2009):

Increasing atmospheric carbon dioxide levels are causing ocean acidification, compromising the ability of some marine organisms to build and maintain support structures as the equilibrium state of inorganic carbon moves away from calcium carbonate.

Seems pretty reasonable to me.  Carbon dioxide is increasing, the ocean is becoming more acidic, and marine organisms are having a hard time because of it.  So I read on:

Few marine organisms tolerate conditions where ocean pH falls significantly below today’s value of about 8.1 and aragonite and calcite saturation values below 1.

So far they don’t seem very “skeptical” of ocean acidification.  Reading further:

We identify four-decade-old mussels, but suggest that the mussels can survive for so long only if their protective shell covering remains intact: crabs that could expose the underlying calcium carbonate to dissolution are absent from this setting.  The mussels’ ability to precipitate shells in such low-pH conditions is remarkable.  Nevertheless, the vulnerability of molluscs to predators is likely to increase in a future ocean with low pH.

Woah.  It actually seems like she’s found this remarkable organism who lives in a unique environment that can survive massively acidic conditions.  But she is NOT extrapolating these results to other types of calcifying organisms.  And in fact, even these tough mussels do in fact suffer from the increased acidity – they have far thinner shells than nearby mussels living in less acidic waters, which leaves them more vulnerable to predators.  If you read on in the paper, you learn that part of the reason these mussels have such incredible survival rates in these conditions is due to a lack of predators:  typical predators in nearby (less-acidic) waters are crabs, but the crabs can’t survive in the very low pH environment.

All this got me thinking about the differences that exist between authors’ intended message and how their work is subsequently portrayed and disseminated to the public.  What was Dr. Tunnicliffe trying to communicate?

I see a couple of different problems:  1)  The language used in peer reviewed literature is technical and often uses a lot of field-specific jargon, and 2) Access to peer-reviewed scientific articles is limited (by cost, mainly).

Easy on the jargon!

Was the “climate skeptic” summary accurate?  Was my summary accurate?  Were we both wrong?

I thought Dr. Tunnicliffe’s article was really well-written, clear, and informative, and even so – look how easy it was to subjectively interpret and share her results!

A lot of the time, scientists write peer-reviewed articles for each other.  That’s not to say they’re intentionally being exclusive – it just makes sense to try to aim their writing to other scientists who will use the work as a jumping-off point.  And, as a reader, if you’re not sufficiently familiar with a particular field, it can be difficult to glean the relevant information and to parse the jargon, particularly when you don’t have several hours to critically read it.

So what’s a scientist to do?  I really would like to know. It’s important to have rigorous and peer-reviewed documentation of your research so that others in the same field can build on or question your findings. That’s basically what makes science tick.  But what if authors could also write summaries intended for non-scientists (or scientists in other fields, for that matter) to accompany their more technical papers.  Like Cliff’s Notes of their own work.  So my blog readers could look up the Tunnicliffe paper and easily see for themselves whether my simpleminded take on it was total hooey.  (it might very well be…)

If a scientist publishes a peer-reviewed article and no one reads it, is it really science?

Of course, I think I’d be remiss not to mention that I am one of those privileged few who have almost unrestricted access to any peer-reviewed literature I care to get my grubby hands one – while I’m a student at a large American university, I can log into my school’s library website and look at anything I want instantly.  And if I can’t get it instantly in PDF format, I can ask the library to order it in for me, free of charge.  So without even getting to the fact that scientific papers are dense and difficult to synthesize, they’re simply off-limits to almost everyone unless they’re willing to fork over the cash.  For example, the Tunnicliffe paper on the Nature Geoscience website costs $32.  Whew.

And we wonder why there’s a mistrust of the scientific community:  we write as cryptically as we can (hey – in scientists’ defense – getting all those technical details into a reasonable number of pages for publication is not easy, people), and then we publish in peer-reviewed journals that charge people $30-40 for the PDF.  Ugh.

But!  The peer-review system is important in maintaining a certain standard and ensuring the credibility of published results.  I don’t know how to change that.  So:  until we figure out how to make peer-reviewed articles more open, maybe some “published-article Cliff’s Notes” or “cheat sheets” wouldn’t hurt.  (I guess now that I’ve said it, it would be shameful of me NOT to do it for my own paper.  At least I’ve only got the one.)

I’d love to have feedback!  It would help me figure out if anyone is thinking the same thing or if I’m totally out to lunch on this one.


More on open access:


Some interesting thoughts on the future of the scientific journal industry (think social media-style):



[1]  Tunnicliffe, Verena, et al. “Survival of mussels in extremely acidic waters on a submarine volcano.Nature Geoscience 2.5 (2009): 344-348.

LaTex and JASA template

Today Dax and I are figuring out how to use LaTex to put together a JASA paper.  Yay!  So fun – I love figuring out LaTex stuff.  First off, we had to get Dax’s computer all set up to run LaTex.  We went with the MacTex-2010 distribution, it’s pretty much got all you need, and you don’t need to worry about getting the right dependencies or any of that stuff.  It installs all of this stuff:

We haven’t had a chance to investigate much – so far we’re just running TeXShop – it’s pretty straightforward, and does syntax highlighting automatically.  BibDesk for the references is fine too, but I prefer JabRef.  And as it turns out, JabRef was the easiest way to get Dax’s Endnote database converted to BibTex .bib format.

To do the Endnote –> BibTex conversion, we had to follow these steps (after http://wiki.lyx.org/BibTeX/Programs):

  1. In Endnote:  Edit -> Output styles -> Open Style Manager
  2. Check the box marked “Refer Export”
  3. Go to File -> Export.  Save file as type:  “Text only”, Output style: “Refer Export”.
  4. In JabRef:  File -> Import into new database
  5. Choose File Format “Refer/Endnote”, and select exported Endnote .txt file.
  6. In the intermediate viewer window, you can optionally select not to import duplicates, or select which entries you would like to import.  Click OK, and you’re done!

Easy Peasy!

Now for the JASA format.  I found this zip file on the JASA website under For Authors -> JASA.  The second to last option in the first section is Download files for preparation of JASA manuscripts in TeX format. This zip file contains a folder that contains all sorts of JASA/LaTex goodness. I didn’t have a chance to dig in too deep, but I sort of went through and grabbed the bits that I thought relevent, at least to have a first go at it. This meant the template file, the jasatex.cls file, the jasanum.bst file.  There are instructions for installing “JasaTex”, but from what I can tell, it looks like it’s just instructions on getting the style files into the right folders in the Tex system sub-directories.

This was enough to get started, and Dax is filling in his LaTex document with an early draft of his paper – and it looks great! The JASA-LaTex package also includes a handy guide that discusses some LaTex basics and general guidelines.  Very handy.

Writing and reading

I don’t know why I didn’t focus on it more during my masters – it was certainly just as important then as it is now – but I need to figure out this whole writing and reading thing.  There are a lot things to learn in graduate school.  There’s the science itself: the math, the biology, the physics, the coding (etc, etc…).  But what I am starting to realize is that I need to figure out how to write, and how to read.  And to do both of these things well.  Because everything else really hinges on those abilities.

I just got a first draft of an abstract back from my advisor.  There was not a single sentence that was left untouched, with corrections to everything from spelling to syntax to content.  I need to re-word almost all of the first half, and entirely re-write the second half.  And the worst part is that I thought it was pretty decent when I emailed it to him last week.  *sigh*

So after a few minutes of indulgent self-pity, I figured I should probably suck it up and remember that this is how I’m going to learn things.  It made me think of Dr. Shubov, my math teacher at UNH.  One day I asked her a question, prefaced with how it was a stupid question.  She responded (to the class in general, I think) that we only have stupid questions because we don’t know anything yet, so go ahead and ask.  (as opposed to every other teacher I’ve had, who always told us that there was no such thing as a stupid question).  I liked this a lot, and she is still one of my favorite teachers.

So I guess the point is, I don’t know anything now, so I might as well go ahead and ask the stupid questions, accept that my drafts will be full of errors, and that I’ll make many, many mistakes – and try to use it as a way to improve.

Well, that’s my little soapbox motivational speech for the day.

End-of-quarter stress time!

It’s the end of the first quarter – only one more week of classes left. I find myself buried under piles of work, with far more to do than I think I have time for. The only thing that prevents me from a complete state of panic is that I’ve been here before, and I know that somehow it all gets done.

A lot of what I have to do in the next 2 weeks involves writing. Writing! I remember naively deciding to go into engineering because I wouldn’t have to write. Little did I realize that writing – communication skills in general, really – are VERY important skills to have, regardless of what field you are in. Writing continues to be one of my toughest challenges. I am quite happy to churn through some math, I know that there’s a right way to do it, and I’ve learned that if I persist for long enough, I generally figure it out. Synthesizing and clearly communicating a set of ideas or a process is much more challenging. But I suppose that’s one of the reasons I’m here – to learn those very skills, to build my strengths and to grow in areas where I am weakest.

There are a lot of resources in the web to help with writing, researching, giving presentations, and all sorts of different aspects of being a graduate student. I like to read this one every once in a while, it’s well written and has some good advice in it:

So long, and thanks for the PhD!

It’s really written for CS students, but much of what it talks about applies to a much broader audience, certainly an audience that includes science and/or engineering graduate students.