Well, hello, everyone. Welcome to tonight's broadcast.
I'm Chris Butler Minor, the community engagement specialist for Olympic Coast National Marine
Sanctuary. And I'll be facilitating today's live presentation in addition to Rachel Brown with
Feiro Marine Life Center and Cheyenne Palmo, one of our AmeriCorps service members. She's the
Environmental Education and Stewardship Specialist who's also joining us to support the webinar.
We're so pleased to have you join us for our New developments for Passive Acoustic
Monitoring of Sperm Whales in Hawaiian waters." This event is co-hosted by Olympic Coast National
Marine Sanctuary and Feiro Marine Life Center as the second installment of our 2021 Speaker Series,
And the speaker series brings you marine focused topics of interest from subject matter experts.
During the presentation, all attendees will be in listen only mode.
But you're welcome to type questions for the presenter in the question box,
which is going to be on the lower part of your control panel, probably docked on the right,
right-hand side of your screen. Um, it's the same area that you
can let us know about any technical issues that you might be having. And so we'll be monitoring
incoming questions and technical issues and we'll respond to them as quickly as we can.
We're recording this session and will share the recording with registered participants
through e-mail and then also on the Office of National Marine Sanctuaries Webinar Series page
once it's been closed captioned. And just the last little bit of housekeeping,
we are really interested in any feedback that you
might have that will help us improve the experience. So if you don't mind,
please take a few minutes to complete a short evaluation after the presentation.
So I'd like to kick us off by having Cheyenne host a quick Slido poll. And if you're not familiar
with it she’ll give you all the scoop on it. - Awesome! Yeah, So Chris, if you can go
ahead and share your screen to disappear on us.
And just re-share. There's going to be a QRC code that's going to pop up on your screen.
Um, and what you can do is just take your smart phone and open up your camera
and go ahead and scan that QRC code. And I'll bring you to be launched question.
The first question is, have you ever heard of NOAA's National Marine Sanctuaries before?
So I'm going to go ahead and activate that right now.
And we'll see if we get some votes in. We'll do, like, 30 seconds worth of
figuring out, if you have heard of the Office at National Marine Sanctuaries.
And it's perfectly OK if you don't have a smartphone, there's the option to
join via a web browser at slido.com and just click,
and just type, then that number. There's only three questions and they're
not crucial to the presentation itself. So, no worries if you can't participate.
Alright. So I'm going to go ahead and stop this.
You got 66 answers and an 85% of participants said that they had heard of NOAA’s National
Marine Sanctuaries before. Back to you Chris.
-Cool, OK. So let's go on then.
Let's see. We seem to have, there we go. Just having a little delay there.
So. So it sounds like a lot of you are familiar with
it. But for those of you that are not familiar with the National Marine Sanctuary, in a nutshell
there are 14 Sanctuaries plus Papahānaumokuākea and Rose Atoll Marine National Monuments, all of
which protect over 600,000 square miles of ocean. So that's bigger than the entire state of Alaska.
Activities at these sites include resource protection, recreation and tourism,
education and outreach, maritime heritage, plus science and exploration. So NOAA’s national
marine sanctuaries, are established and actively managed by the agency under the National Marine
Sanctuaries Act to sustain appropriate, sustain appropriate ocean uses, including recreation.
So, we're going to do another quick Slido poll, same QRC code, and
event ID. So take it away, Cheyenne.
-All right. So, now that you kind of saw a map, have you personally
ever visited a National Marine sanctuary? Um, and if you'd like to, you can answer your
question in the question box. If you don't have access to the Slido, that's fine.
Right. I like the “maybe” option here. A lot of the time, you don't even realize that
you're in the National Marine sanctuary. Alright, I'll give it like 10 more seconds.
OK, so about 75% of everyone said, ya have been to a marine sanctuary, 15 said no, and a strong,
11% said maybe. Back to you, Chris.
-Interesting, OK, well, hopefully we'll inspire you to, to change that answer to, Yes!
So, um, I just wanted to do that by showing you some amazing photos.
Like let's take a quick tour of some of the treasures that are protected
and National Marine sanctuaries, such as these iconic sea giants or,
the small reef fish and corals found on the East Coast.
National marine sanctuaries seek to preserve the beauty and biodiversity of these special
marine places while also providing a place for charismatic marine creatures to seek shelter.
And these special places also protect some of the nation's most
iconic marine and cultural heritage sites by establishing national marine
sanctuaries that protect shipwrecks and other significant artifacts.
They're also mandated to conduct research, monitoring, resource protection, education
and outreach, and, of course,
management of America's Underwater Treasures to preserve them for future generations.
These places are protected for your enjoyment and pleasure and
sustainability for generations to come. We're going to go to our last Slido.
And Cheyenne, if you don't mind,
posing this question? -Of course. So just to get a general idea for how large the sanctuary
system actually is, how many square miles do national marine sanctuaries encompass?
So far, we're erring on the larger numbers here, which is promising.
I'm usually shooting for about 75 participants. Keep hitting it.
OK, so a majority, a little more than 50%, shot for the 1,425,000 square miles as large number,
and then closely following, behind, 40%, said, 600,000 square miles.
So what are we thinking Chris? What is the answer to that question?
-The answer is 600,000 square miles. If you recall, I mentioned that it was
a little bit bigger, the ocean area and Great Lakes areas that are protected,
are a little bit bigger than the state of Alaska. All right, so let's move on.
And thanks for participating in those polls, by the way.
So, in tonight's talk, we're going to take you from our hosts’ location
of Olympic Coast National Marine Sanctuary. to Papahānaumokuākea Marine National Monument,
which is further west into the Pacific and is the largest contiguous, fully protected
conservation area in the U S and currently the largest marine conservation area in the world.
And to Hawaiian Islands Humpback Whale National Marine Sanctuary, which was created
to protect humpback whales and their habitat. So, now, I'd like to turn the mic over to
Rachel Brown, the Education Manager for Feiro Marine Life Center to introduce our speaker.
-Hello, I’m Rachele Brown, education manager at Feiro Marine Life Center located in
Port Angeles Washington. Feiro Marine Life Center is a community aquarium that was founded in 1981
by a community leader and educator, Arthur D Feiro. Feiro is committed to community on education and specializes in
local marine invertebrates and fish. Thank all of you for joining the partnered 2021
lecture series. Today, we're joined by Dr.
Yvonne Barkley. Yvonne recently earned her PhD from the University of Hawaii at Manoa
in December, where she worked on developing new analytical methods for passive acoustic data
and identifying patterns of false killer whales and sperm whale populations in Hawaiian waters.
She learned about cetacean acoustics after graduating college,
working as an acoustic analyst. She was intrigued by the entire process,
from designing hydrophones for data collection
to the computer programming for analysis. At the time, she was just clicking boxes,
around squiggly lines on a computer screen. but she appreciated her role in the bigger picture
where science and technology are combined to learn more about the patient populations
and the impact that humans have on them. This concept has driven Yvonne's interest
through her career and lead to her work with NOAA Fisheries. She's started as an intern in 2009, leading to
Technician position, and then on to graduate school, intermittently
going to sea for several NOAA cetacean research cruises. Over the years, Yvonne worked with others
sharing her same motivation, which continues to inspire her.
She's currently in a new role as a postdoctoral researcher under the Joint Institute for Marine and
Atmospheric Research. When Yvonne isn't analyzing acoustic data, you can find her mostly outside enjoying the weather in Hawaii
either surfing, hiking, or simply lounging. It is my pleasure to introduce to you,
Doctor Yvonne Barkley.
Well, Cheyenne, maybe you can take a look and see if
there are any questions in the question box right now? - OK I was just about to let you know...
So just as a little update, to people who are joining the call right now. We seem to
have lost Yvonne Barkely, who's the presenter for today.
I can only imagine that Internet is not the strongest where she is calling in from,
but a few people were asking Chris: If and where this recording will be available
after being closed caption? -Oh, great.
So it's going to be on the National Marine Sanctuaries Webinar Series page, so you can go to
sanctuaries.noaa.gov and [Oops, let me make sure that's the right address].
And if you look for webinar series, or even if you type in sanctuary webinar series,
you should be able to find it. And it's actually got a wonderful library of past presentations.
Oh, yay! Yvonne has made it back from the internet abyss.
-Alright, I just made you the presenter, Yvonne. So you should be able to
pull up your presentation. Thank you everyone for your patience.
-Let's see? OK, turn myself off.
Great, I'm assuming I was introduced. Sorry about that.
Slight glitch, the internet connectivity. Uh, OK, I will present.
and Close that. Sorry, one moment.
I am now working on one monitor versus two. It's a little bit different.
Mmm hmm hmm.
OK, we're just gonna go with it.
Great.
Move that down here. OK, thanks, everybody, thanks for bearing with me here,
and tuning in to my talk, where I will be discussing a couple of projects that I recently
completed for my dissertation research, and thanks, Rachele for introducing me.
OK, things can work, that would be great. Excellent.
So we'll start with a little bit of an outline just to show you a roadmap of
where we're headed today and starting with some background information of
the Cetacean Research Program at NOAA's Pacific Island Fisheries Science Center
where I've worked with them throughout my dissertation as well as in my current position.
Let's see, along with, OK, there we go.
Sorry about this. Along with the
study area where my data were collected and where all these projects are based off of,
just going over, also some of the main research methods that we use to study cetaceans in general.
And then of course talking about sperm whales, some of the relevant biological and ecological
information that helped to drive my studies. Then moving into the two different projects that
I worked on, including localization of sperm whales, and then also incorporating, incorporating that
acoustic data into species distribution models. And then talking a little bit about some
future and current directions that we're going with these types of data.
So, to start with, the mission of the Cetacean Research Program is generally to study the
whale and dolphin populations or cetacean populations within the Central and Western
Pacific Ocean. And that is done in order to support conservation and management efforts.
All of this research is really guided by mandates of the Marine Mammal Protection Act,
which is what all cetacean species are protected under that
as well as some of the endangered species protected under the Endangered Species Act.
So, the study area includes the Hawaiian archipelago,
shown here, which is actually home, to at least 25 different cetacean species that we know of.
And this includes the north-west Hawaiian Islands, the Hawaiian Islands up in the
north-west. I wish I had my little walk, we can hopefully see my little
arrow here. So this area which encompasses the Papahānaumokuākea Marine National Monument,
as well as the Main Hawaiian Islands, which I am located on here, hopefully with the
good Internet connection, on Oahu in the middle of the Pacific. And this encompasses the five
separate areas of NOAA’s Humpback Marine or National Marine Sanctuary, as well.
So, to just chat a little bit about the different tools that we use to study these
species that primarily live underwater.
A lot of these are complimentary to each other, and most of them are have really established
the current knowledge of what we know about Cetacean species worldwide.
OK. Starting with visual observations. This is kinda the most basic tool that we
have, to just see animals at the surface. And that can tell us a lot of information
about what species are present, how many there are, and a number of other pieces of information
that includes photos and being able to take photos of these animals at the surface. And
we perform then photo identification analysis which can take the images of their dorsal fins
and flukes, which have sometimes have different scratches and markings and niches in them,
and notches rather, to use them as sort of fingerprints to identify
individuals and even estimate how many animals are in a population, using the photos.
We can also collect tissue samples, which allows us to run genetic analysis to look more at the
population structure of the species and tell what animals are related to each other between,
you know, even different geographic regions or within the same region.
We can also deploy tags and track animal movements using satellite telemetry data.
This is an example of a tag within a dorsal fin of a pilot whale.
And this really gives us a good idea of
their habitat range and where they are within this either study area or just where they tend to go off,
you know, hundreds of kilometers away from where you're thinking they normally would reside.
And lastly, a newer approach, at least to me, I have not ever used an unmanned aerial vehicle or a UAV.
And this is your, in other words, it's a drone that is used to look at cetaceans from above.
And we can tell things like their body condition, sort of the composition of the groups themselves,
whether mom and calf pairs, or what kind of animals or in a group.
And all of these tools are very complimentary, as I said before.
But these ones, in particular, in particular, really rely on seeing animals at surface.
And for a species that primarily live underwater, sometimes that can be problematic.
So that's where passive acoustic data collection comes in.
Is because animals, cetaceans, make a lot of sounds underwater.
So we can passively listen to them using hydrophones, or underwater microphones.
And so, these come in a lot of different, a lot of different configurations.
The one in this diagram, like this ship is towing a towed array of hydrophones that are housed in
this case within tubing. These little yellow rectangles here, with the black dots, are kind
of a diagram of what a towed hydrophone array is and that's towed behind the research vessel
so that we can hear everything that is within the water column making noise at this point.
Oh, I forgot, this is where I sit on the ship when we are collecting these data in the field during
the research surveys. And this is,
the data comes in, and we are analyzing and processing them using a lot of computers.
And at this point, we know that we can detect all the known cetacean species.
And those include both baleen and toothed whales, because both of these types of
whales rely on sound to survive. Baleen whales in particular,
communicate or vocalize in lower frequency ranges, less than usually one kilohertz.
Just for your reference, my voice is about 150 hertz. They typically produce moans,
groans, and song, and are primarily used for long range communication and mating.
Then we have the toothed Whales, which is where sperms also fall under and so those are higher
in frequency. We call it the mid to high frequency range, which is 1 to 140 Kilohertz, thereabouts.
And those include whistles, echolocation clicks, burst pulses,
and are mainly used for communication, foraging, and navigation. And so yes,
this is where sperm whales fall under as a toothed whale.
And I want to talk a little bit about some of the applications of passive acoustic data so that
I can put my work into context for you. So, we can really use these data to detect animals
and to see what's there. Is it even biological or not? I guess, when we're out in the field,
sometimes we hear all kinds of sounds and we're able to know if they are a cetacean species.
Sometimes not, though. There are some, some instances.
There's also a classification of acoustic data which helps us,
tells us, who or what species are present. Then there's localization, which is what we use to
estimate where the animals are using their sounds. The distribution of the animals can be studied
using passive acoustic data to show that, tell us where and perhaps
why animals are located where they are. Then the Holy Grail of passive acoustic data
is to be able to estimate density or estimate the number of whales in an area
because that's a really important parameter when it comes to conservation management.
And so my research falls within, that I'm talking about today at least is, falls within
the localization and distribution categories. OK, let's see, so the new developments. I've, I
will say that a lot of work has been done in these two fields, especially when it comes to sperm
whales. And I learned a lot of these techniques when I was first starting out as an intern even.
And along the way, I gradually learned about some of the limitations that established methods have.
Which, you know in any case there, there's always limitations, which is what really drove my
path into grad / graduate school to try to address some of them.
And so, really this work is improving upon the existing methods that we have
to study localization distributions from whales. Then, including the towed array data, which I'll
be using by my projects, to use primarily and using that data, in those data in different
analyses to then better understand the ecology of sperm whales, which helps us improve and make
conservation management efforts more effective.
So, getting into whales themselves, they are found everywhere. So, this map, you see, just with all
the blue that's, basically, their range. Sperm whales reside in areas high and high
latitudes within ice free waters, all the way to the warmer waters along the equator,
including the Olympic Coast National Marine Sanctuary, about here the pink star,
and the Hawaiian archipelago. It is within the orange circle.
And in Hawaii, we have sperm whales here year round,
from all the different demographic groups, including females, males, and juveniles.
And sperm whales themselves are really fascinating species.
They, there's books about these animals that I can't even touch upon,
all of the details that are interesting to me. So, I'll just be telling you some of the more
relevant biological information that is, that my work relies on.
So part of that is just to know that these animals are the largest toothed whale species that we have
on the planet, as well as they are the largest hunting predator,
which makes them really easy to see. They're one of the easiest
cetaceans to see at the surface and identify visually.
They prey upon different species of squid and fish,
which reside lower in the water column, really, really deep.
And so that forces these whales to dive to forage and search for their food at depths,
sometimes over 6,000 feet and they can dive for up to an hour, specifically about 45 minutes.
And so they are spending most of their time at depth.
Luckily, they make a lot of sound when they're doing that. So that's where passive acoustic data
and monitoring comes in. We can detect their echolocation clicks.
And the characteristics of these clicks makes them the loudest animal on earth.
And I'll play a few examples in a moment. But, let's see if they, all these attributes,
that the fact that they're really large, helps us see them visually, the fact that they're really
loud and helps us study them acoustically. So, this was a prime species for me to try and
develop new techniques for using towed array data. All right. So talking a little bit about their
echolocation clicks. Like I said, they're really loud.
They're lower frequency than other cetacean species.
Let me just march through here because we have a spectrogram.
This is how we are visualizing the sound. And I want to say that the dark lines
along this plot, with frequency on the Y axis and time in seconds on the X axis,
shows that the lines or the lines themselves, shows longer duration clicks than any other
species that clicks. All the other toothed whales have very short, echolocation clicks.
And these different characteristics allow us to detect these whales at great
distances of usually over six miles, sometimes. And there are also four types of echolocation
clicks, so that when we're viewing in this picture around, includes the regular foraging
or regular clicks that are used for foraging. And I will pull up an example of that. Now. #snap or click#
So, hopefully, you could hear that. But, if you had trouble, they, each
of those lines on each of those snapping sounds is basically what you can do with your fingers.
And those are, you know, every click per a second helps them search for food.
They also make creaks, which are also for foraging and those sound
like. #rapid, louder repeating clicking# Yes.
So those are thought to be when the whale is
sort of zeroing in on their prey. They're, they're producing these more rapid clicks.
They also use clicks to socialize in sort of a Morse code type of pattern.
I will play an example here in this spectrogram. #rapid clicks# OK.
So, there are different patterns of codas that exist all over the world.
Then there are people dedicated to just trying to
identify them and compare them between regions. That's pretty interesting.
And last, but not least, we have the Slow Clicks, which are primarily produced by males,
as far as we know. Those sound like
they're slow, obviously a few seconds between the clicks, compared to the other click types.
There we go. #intermittent clicks# So those are
the four main types of clicks that sperm whales produce and makes them, also just adds to their,
as to why I think they're so interesting. So to study these animals to study sperm whales
along with others, all cetacean species here in the Hawaiian Islands
we conduct line transect surveys. And these can last from one month to several months,
And they're primarily used to estimate the total number of animals in a population
for each species. And we call that estimating density and abundance.
For this type of analysis, we rely on getting perpendicular distances from / of the groups of
animals or individuals to the track line, which is shown here in this black line. Here is our little
ship. And here are sperm whales at the surface that are able to be seen by the visual observers.
And as these analyses are conducted, they're usually using just the visual
observation data at this point. So if you watch the boat:
that cruises down the track line. We're able to get instantaneous distances from / of
the groups from the track line and then that's put into these analyses to estimate abundance.
However, as we know now, sperm whales are at depth a lot of the time echolocating.
So, if we could get the passive acoustic data included into these abundance estimations,
in theory, we could produce more precise estimates of how many animals are in a population.
And, so, with towed arrays, we can actually do that at this point.
We do this on the ship in real time to also help track animals, to help visual observers find them.
And so, it starts by detecting the clicks themselves.
In this plot here, it's showing the bearings that we can calculate from the array to the whale,
given some software and different calculations, that and as the whale
passes the ship or 90 degrees of the ship and out in that red dotted line,
we can, um, calculate multiple bearings over time. Because we have a moving ship and a moving whale
it's a little more complicated than visual observations getting the distances
to then estimate the distance to the whale using multiple bearings.
And so, with that, there, you can picture a lot more bearings happening for each of those dots.
For example, you could get a bearing in theory but, for this example, just showing you how
this works, we can then use the software to estimate that perpendicular distance.
So, what I just described is really, can be thought about as two dimensional localization,
where you have the array at one depth, and you're assuming that the animals are at the same depth.
With sperm whales, that gets a little trickier since they're usually
way much deeper than the array. So, these assumptions
that two-D, localization follow...
let's see, so the assumptions include that the animals are near the surface,
we have a constant sound speed as we're detecting them and localizing them,
which is not necessarily the case all the time, and then that we know the exact position of the
hydrophones as the towed array is being dragged through the water, and that we're assuming the
animals are stationary relative to the array. So really, and when it comes to Sperm whales, a
lot of these assumptions are violated. Again, since Sperm whales are vocalizing at depth,
and sound changes with depth, the first two assumptions don't really hold and even
knowing the hydrophones positions at all times is hard, because
in theory, these hydrophones are actually moving a little bit with the ocean currents and all that.
And so with violations and assumptions, we also don't include errors with this
type of localization, which can lead to biased distance estimates and perhaps,
not the most accurate way of getting these distances that we need to estimate local abundances.
So, that's where I developed this, what we're calling a model-based localization tool, for the
towed array data. And this approach I'll describe, accounts for the depth of the sperm whales.
It also is able to incorporate errors that are from, that occur due to the sound propagation or
the change in sound speed over with depth, ah the hydrophone positions, and then time
difference of arrival measurements or TDOA measurements, which I'll describe a little later.
And so the model-based approach, this a term, and this is a term that helps, or that
really, accounts for the effects of the ocean environment on how sound travels through it.
So this diagram, is just is a way to show how sound travels. It can,
due to differences in temperature and pressure with depth. For example, this for a whale hanging
out in the shadow zone wouldn't necessarily be heard by a towed array near the surface.
So, that could cause problems when it comes to localization.
And, at this point, there had been, or at the time of my dissertation research,
no, sorry, there had been no model-based localization methods for shallow towed arrays,
which is the datasets that I've been focused on. And so, TDOA stands for time difference of
arrival. This is a really important parameter in this approach, which is basically mean the
clicks that we're hearing from the sperm whales reached the hydrophones at different times.
And that's how we're using that information to estimate the direction to the whale
and then ultimately establish a location using multiple measurements of TDOA.
So stepping through some of the process that was used to develop this approach (I'm happy to answer
more technical questions afterwards as well) But we started off with the raw data or the
recordings that we were listening to, and the spectragrams using the spectragrams.
And then taking those recordings and cleaning them up a little bit,
reducing the noise in the background and narrowing down the data itself to this,
the frequency range of the sperm whale echolocation clicks.
Then taking the clicks themselves and detecting, when we detect them, we can also extract them.
And then use that information to measure the TDOA. And this is really an automated approach,
which is handy because that really limits the operator error.
And so we have our measured TDOAs from the data. And we're using those along with some of the
modeled side to produce these what we're calling "volumes of ambiguity." And it's a kind of ambiguous
term, but really it just means it's our way of, um, deriving 3-D, a three-dimensional
shape to represent all possible locations where sperm whales could be located because
those two-dimensional bearings don't really show us the whole picture. And
this approach also allows us to incorporate the differences in sound speed and different errors.
And so, if you can picture a very empty grid of grid space in,
which is where we, we can model the TDOAs themselves, and that are generated based
on the different, the environment, and the changes in sound speed that do occur.
Then, taking the, the measured TDOAs and these modeled TDOAs,
we compute these ambiguity volumes using this equation here, which then can incorporate the
errors, and everything is it's really a nice way of being able to incorporate all
these pieces into one, one ambiguity volume. And then from that ambiguity volume, we can
estimate a distance and depth, which is what we need for the abundance estimations.
So, to just give an example of what this really looks like, because I know it's probably hard
to visualize it, because it was for me when I first started getting into this. I ran some
simulations or really just some experiments that I can program in all the different
parameters, such as how deep the whale is, how far it is, from the track line, how the ship
is moving, whether, it's either going straight down, or if it's making a turn of some sort.
And when you calculate the measured TDOAs, Model TDOAs, and produce ambiguity volumes
they look like this. And so we have our whale, which is located, we know that it's located here,
and when the volumes are calculated, this yellow and orange shape is what's produced.
With higher probability being in the color black, which can't really see because it's actually in
the middle of this, sort of horseshoe shaped volume. And so this is our boat
It's going this straight track line and you can see that the
whale is located directly below the ship. This is all the possible locations that it
can technically be located. And if you're assuming that they're at the surface this,
these two points here on either side of the U shape, would be where that two-dimensional
localization approach would estimate the whale, which is much farther away from the track line
then the whale is truly located. So that is where those biased distance estimates could occur.
So I was curious to what happens when you turn the boat.
And, as the turn itself can then cancel out some of that, um,
some of the shape of the volume and really make it more precise in that little blob, here.
So, this, turning the ship is very important, when to make these localization estimates more precise,
and those distance estimates more precise. OK, so some conclusions, just to wrap this up.
We've developed a more automated approach for localizing sperm whales in general.
So that's part of this, too, is really important.
because tackling, re-localizing data, it was not an easy thing
to do before I develop this, this method. So this takes out a lot of the user error,
it helps us able to control a lot of the parameters more easily.
Then that includes incorporating the effects of the environment, the different errors themselves,
and even understand how the whale's position can affect these distance estimates that are so
important for getting good abundance estimates. And these locations themselves, also can be,
they're now given position bounds, sort of an error range around the best distance estimate.
Now, we can also measure sort of a plus, plus or minus range around that best distance.
And, as we knew before, with even two-dimensional localization, we could turn the ship to improve
the location, the location estimates. And it holds true for this method, which, just, in general,
will give us more precise information. At the moment this is, this paper is in review. So,
hopefully, that will be something I can share in the future, ah the published paper.
OK, good job, everybody. We got through the localization part.
And, we will now move into how we can use this data, these data and this location information,
and look at the distribution patterns as from animals in the Hawaiian archipelago.
All right. So, we're calling this the Species Distribution Models, or SDMs.
This is basically a tool, a statistical tool ,that helps us
predict the different patterns of distribution that over time and space for species.
And we can take these, there are field observations which can be either, either visual
observations or passive acoustic detections and relate that to environmental variables.
And that helps us better understand the ecological relationships
between a species and their environment,
and even just predict where the animals may occur based on different environmental measurements.
And so for cetaceans, we primarily use sighting data at this point to produce cetacean SDMs.
And then a sort of a rough overview of how that's done,
so we have our ship and our track line again. And the ship moves down the track line.
Its detecting animals, which are denoted with the stars.
And when these types of analyses, they chop the data up to kind of get, put it in uniform
units, to be put into the model. And that's done by segmenting the track line,
finding the midpoint with the red dot there, and then associating all the different
sightings along each segment to that midpoint with environmental data, to make it more co, cohesive.
And so the spatial models for cetaceans, can also just with the number of
cetaceans estimated in each of these groups, we can model the species density over space.
So for example, a paper by Elith and co-authors estimated sperm whale density to
have this broad pattern of increasing up towards the north-west Hawaiian islands, which is shown in
the orange and red colors in that, in that plot. So that's one way that we can use SDM to estimate
and predict where these animals can be. And I was part of this project after that
to try to incorporate pathway acoustic data into these SDMs because we hear so many whales
when we're out in the field, that they're not really accounted for in some of these
analyses. So it would be interesting to know how that would change, these, the results.
So using that same track line segment method I just described,
we incorporated both sighting and acoustic data into these models, to try and test that theory.
And so unfortunately, with this sort of exploratory study, we weren't really
sure of the accuracy of the models themselves. And you can see with the visual model on the top
panel compared to the a model, they're really different.
And it's, it's hard to know if one is better than the other without
further analyses, which is where my PhD came in. So part of this, we thought, would be due
to the fact that sperm whales can be acoustically detected
really far away. And perhaps, the environmental data wasn't being correctly associated with
those farther or more distant whales. And that's where the localization part
of this came in and really drove that study as well as this one.
And so, the data that I were was able to use included survey data
from four years from 2010, 13, 2016, and 2017. And it's really spans the entire archipelago.
So it was giving us a really good sample size of over, just over 200 sperm whale encounters.
And this includes all sighted and acoustic, acoustically detected sperm whale groups.
And so when it comes to putting them all together, it's really important to have location data for
the sperm whales to, to input into the model. And so, I broke them down into different
categories including: sperm whales that were sighted only; sperm whales that were
acoustically detected and we were able to localize them using the model based approach.
Some sperm whales were not able to be localized when we acoustically detected them so, but
we could still include them in the model. Then, we had the combination, where we both,
we sighted or we saw and heard the animal, the sperm whales.
And with acoustic data, we were or, I categorized the sprawl counters down to
foraging animals and non-forging animals. And based on a type of click that we,
that I identified within the acoustic detection. So that is kind of a really important point.
In the, for one of the reasons why acoustic data can be important and more informative sometimes or
at least provide a more complete picture. And so using these categories,
from sightings of the non-foraging whales I create a different models for each scenario.
So oh first, the environmental variables that were included in these models
were all biologically relevant to sperm whales, including what I'm calling
static variables that are environmental variables that don't change over time.
So that means bathymetry, distances to land or seamounts, and other, um, static variables that
really help, or at least are acting as a proxy for a suitable prey habitat or
features that might influence the water column, to then influence
prey and and presuming that sperm whales will be located where there is more food.
Also, I included dynamic variables that do change over time.
A lot of these are remotely sensed from satellites. They are also all really acting
as proxy for primary productivity or related to the prey in some way.
The last one there at temperature, 584 meters was a, a new variable that I found,
that for to me, new to me, and it was modeled from a model dataset.
And that depth in particular was representative of one of the main depth ranges for
a type of squid that sperm whales tend to eat, a species of Cockeyed Squid.
So with all this environmental variable on the location of the whales themselves,
we can then create the models. So this is again that
tract line segment method for configuring a model.
And if you want to just picture the sperm whales, instead, that's great. Sometimes they’re,
then they can be associated with the environmental data at the midpoint.
But what about those whales that are really far away? Those
are the ones that we think were problematic before in the models using acoustic data.
So part of this was to develop a different way of configuring the model itself.
And by using a grid format, we can, the point was to more closely associate that environmental,
at the red dots which are the Grid's centroids, to the whales that are located
farther from the tract line, in hopes that this would provide us more accurate results.
So starting with model results, for the sighting base models, that just used
data from whales that we're only seeing, so we have a performance metric here just
to give us an idea or a relative measure of performance, comparing the models
themselves between the models. We have the output and these
are using generalized additive models. And for those of you who are familiar with those,
they're pretty common in the cetacean SDM world. And so, the important environmental predictors
that created the best model included sea surface temperature with a decreasing
relationship and a standard deviation of sea surface height, which is one of those variables
that's a good proxy for primary productivity. Then, we have this spatial term here, which is a
basically using the location of the whale to help predict the distribution that was found important,
predicting more whales with yellow, which is a little counter-intuitive.
But, yes, more whales predicted in the yellow than the red.
And we compare that to an acoustic-based model that used only acoustically detected whales.
The performance metric of the percent of deviance explained, is a little bit lower
even with larger sample size. And it predicted, the environmental predictors
were selected to be depths and sea surface height, which are slightly different than before.
But this spatial terrain shows a little bit more of a detail on the contours of these lines here,
showing higher probability of sperm whales groups being detected in yellow, again.
But, in more of a range in the north-west and a little bit north of the Hawaiian Islands,
the main Hawaiian islands. We combined all of these data together.
We have a slightly better performance metric. Again, with depth as being important,
standard deviation of sea surface height,
and a little bit more detail and the contouring of the spatial terrain here.
Moving into the foraging category... So these are all whales that were producing either the regular,
regular clicks or the creaks foraging for prey. And it had a very, much higher
performance metric, not as high still though as a sighting based model, surprisingly.
But it did predict or did select the temperature at depth of 584 meters,
also standard deviation of sea surface height, and even chlorophyll for this model. But you can
see here the spatial terrain is a little more interesting. It kind of shows the
foraging males to be predicted here with between, this is Pearl and Hermes, sorry,
Pearl and Hermes Atoll, Lisianski and Laysan area of the north-west and also a little bit
of a higher probability north of Maui and the Big Island.
When we look at the non-foraging whales, the ones that are probably producing, I think the codas
and the slow clicks primarily, and those look very similar to the first sighting-based model
as far as a spatial terrain. But it also selected depth as an important variable
for predicting where non-foraging whales would be.
So we can take these models and then predict onto new data, to sort of see how well they work still.
And when we look at the models that using just the sightings, it does fairly well.
It's still predicts the whale's just to be similar to the previous models done by Forney and
co-authors up in the north-west region. But then you look at the
foraging and non-foraging models. You see these sort of hotspots in red.
These are like higher density areas for these types of whale groups to be located.
So it's interesting that the sighted whales and the non-foraging models are very similar,
that, not exactly sure why, but it was an interesting comparison.
But really, it's the main takeaway is that the passive acoustic data allows us to really
look at these different types of groups of sperm whales instead of just viewing them all as 1 type.
So in conclusion, we found that depth, sea surface height, the temperature at depth of 584 meters,
and even just the location of the whale groups were very important when building
the models. And that including the acoustic data, help distinguish two
foraging areas that we didn't really know about before.
Of course, that will take further surveys to really confirm that. But it would be
interesting to maybe focus in on those areas in the future and see if there were more,
more whales in that area. Then, all together these two analyses,
these two projects I just described really help us improve how we can utilize the acoustic data
to help us better understand sperm whale populations here in Hawaii.
And yes, this, this can be applied to other populations, the sperm whales in
other parts of the world as well. And so, for that, at this point,
I wrap those projects up. And I'm sort of working on a new piece to this whole puzzle of acoustic
abundance estimation in a postdoctoral research position with this Cetacean Research Program,
looking at the relationship between sperm whale click rates and their group size, to try to get at the
question of what proportion of time are these whales making sound so that we have a better,
so that we can get better acoustic abundance estimates for these for this population.
And with that, I want to just acknowledge that all of the data that I analyzed for my PhD
was collected during these really large scale surveys. And it took a ton of crew and scientists,
the board, the Oscar Elton Study NOAA ship during these these long line
transect series to collect the data. So, I'm very thankful for that.
And just acknowledging my funding from the NOAA fisheries, NSF
Graduate Research Fellowship Fellowship Program, and the Hawaii Institute of Marine Biology.
And then my advisor, Doctor Franklin, as, as well as my committee members,
Doctor Eva Nosal, and Doctor Erin Oleson, that helps really get these projects going and
helped me through the process. And also, Taiki Sakai from the south-west Fishery Science Center.
He was instrumental in helping me with the species distribution modeling part with
figuring out how to grid out my,
my data and an associate, the experiment, was with environmental data in that format.
With that, I'd like to thank you all for listening today, and bearing with
me with the technical difficulties, and I will, I'm glad to take any questions.
-Thank you, Yvonne. That was really interesting and great photos.
I appreciate that. Well, what we'll do,
if it's OK with you, since we just have a couple of minutes, is to just maybe pick two questions
and, and then assure everyone that all of your questions have been collected
in the question box. And so we'll be sending them off to Yvonne to get answers to all the questions.
Um so one question that was asked is, can you identify and distinguish between
individuals' sperm whales based solely on their clicks?
-Hmm, I'm going to click characteristics of themselves.
At this point, not necessarily out there. We can identify between
individual sperm whales based on the localization data because that plot I showed with the
black dots as the whale moved past the ship. If there were several lines of those bearings
we can denote individual whales clicking and diving in the same area,
but using just their click characteristics, as far as I know, that's not quite possible yet.
-OK, sort of a somewhat related question, have you tried to use passive acoustic data to estimate the
size of sperm whales using this technique? -Yeah.
Yeah. So one another factoid about sperm whales is that
their heads are about a third of their body size and that's where the clicks are produced.
And so there's the way that the clicks are emitted, it's
they are bounced inside and out or sorry, they're bounced within their head as they are emitted.
And people have used that information and the timing of the clicks, because they're not what I
showed in the spectragrams were these dark lines. And in reality,
there's multiple pulses within a click. And people have used those measurements, to
estimate the size of the whale. And that's has been validated by
actually going in the field, recording clicks from whales, sort of as head on as they can,
and then comparing that to the length of the world that they measure from the field, also.
So that is a really interesting aspect of sperm whale acoustics that is possible to measure or at
least estimate their body size using their clicks. -Great. Oh, that's really interesting. I
hadn't really thought about that before. Well, as I mentioned, we're getting really
close to time, so I'm not going to keep everyone, but I am going to assure you that Yvonne will
answer the questions you've posed to her. And we'll get those off to her fairly quickly,
and hopefully she couldn't get them turned around for you all in the next week or so.
Not too much pressure there, I hope. Then also, I wanted to thank you for, not only
Yvonne, but all of the attendees. And I wanted to give you a little
information about some other options, um, that for events that we have.
So, um, I am going to change, there, and, so, if I can try to, wanted to show
you something but, I'm having some challenges here switching over to myself, there we go.
OK, so, let's do this from this current slide. So, um, some of the resources that the sanctuary
offers, sanctuary system offers as, so we have some national marine sanctuaries live
interactions and these are they're all in archive right now but there's some amazing
topics that are available for viewing in on the national marine sanctuary website.
There are ongoing events “Exploring by the Seat of your Pants." These are really great for
school age children, but adults would find them interesting,
as well. And as you can see, it, there are a lot of different topics coming up very soon.
And also, there are more National Marine Sanctuary Webinar Series and the next one,
which is tomorrow, is “Understanding Marine Biodiversity in the Papahānaumokuākea
Marine National Monument” and you'll find that there are several others, as well.
And then just lastly, put out a little Save the Date for you, March 17th. So a month away,
also at 4:00 PM Pacific Standard, will have Jennifer Hagen, who is the Marine Policy
Advisor at the Quileute Indian Tribe with our Natural Resources Department. And she'll
be talking to us about some research that she's doing with larval crab and Harmful Algal Blooms.
So again, we'll get back to you with all of your questions. I hope you've enjoyed this.
And then just a little reminder to please take a few moments to complete the survey,
and have a very good evening. We'll see you next time.