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.
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:
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:
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:
. (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. ,,). 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).
A BIG FAT DATASET
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 . 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:
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.
 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.
 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.
 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.