Narrator: A landfill is not exactly a romantic location,
but behind the mounds of garbage in Santa Cruz, California,
a stagnant pond has the ambiance this amphibian needs
to get in the mood.
At night, if you listen very carefully,
you can hear the mating call
of the California red-legged frog.
[frog croaks]
Gary Kittleson: The call is very quiet,
which makes it difficult.
It has usually a few pulses,
kind of like [imitates frog croaking].
Narrator: It's a sound that's increasingly rare
as red-legged frog populations dwindle.
They're facing pressure from predators and from farmers
who need the water in these breeding grounds
to irrigate their crops.
But now, scientists are using cutting-edge AI technology
to track the threatened red-legged frog
and balance California's strict conservation laws
with the needs of the region's $1 billion farming industry.
Jeff Schlueter: So, we're improving conservation
by improving monitoring.
We're going to put out six or seven sensors for five months.
We're going to have tens of thousands
of minute-long recordings.
Most of that won't have any frogs in it.
Narrator: This is Jeff Schlueter.
He works for Conservation Metrics,
a Santa Cruz company that uses machine learning
to streamline the normally cumbersome process
of tracking at-risk wildlife.
If you were going to just manually scroll
through spectrograms,
it's really hard to identify the call.
So using a machine-learning algorithm,
you can process huge data sets in hours or days
as opposed to weeks or months.
Narrator: But to know where to deploy the sensors,
which are equipped with sensitive microphones,
you have to find the frogs first
and record a sample mating call.
[frog croaks]
Oh, look! That guy's coming out.
Narrator: Gary Kittleson is the expert who can find them.
Today, he's checking in on the fairly healthy numbers
of the frogs behind the dump.
Gary: There's one looking right at you.
Jeff: From what I know, Gary is the frog guy
in Santa Cruz County or in the Central Coast.
Gary: They're a fairly large frog, 3 to 5 inches.
They're called red-legged frogs,
but they don't often have red legs,
and if they do, their legs are usually red underneath.
23.
Narrator: The frogs are so rare and skittish,
even Gary misses them.
Gary: 24.
[tape rewinds]
24.
Narrator: The frogs are even more elusive
on the opposite side of Santa Cruz in these wetlands,
which are part of the Watsonville Slough.
Gary's been hired by the local water authority
to determine whether water could be drawn out of here
for nearby farmers without impacting the frogs.
Doing so might even protect them from their predators.
Gary: Predatory fish and bullfrogs
are really the two main stressors
for the red-legged frog in the sloughs.
By draining the sloughs,
you decrease the habitat for bullfrogs,
and you will decrease the area for predatory fish.
Narrator: To be clear,
it's not a question of whether water should be taken out
or whether this land should be
completely protected from development.
It was farmland long before the frogs started disappearing.
It's a question of, if water is drawn out,
how much should be taken out, and when?
Paired with hydraulic modeling,
the acoustic sensors will tell scientists
when exactly the frogs are breeding
and how to optimize water drainage with that in mind,
thus creating the best possible scenario
for both the frogs and the farmers.
Gary: I think it's a good project,
but I also know it's going to be really hard
to kind of twist the dials and get it right.
And if you don't get it right,
it's wrong, you know?
You can really do some damage.
Narrator: But can you hear the red-legged frog's call
in this recording?
[nature sounds]
No, right?
That's where machine learning comes in.
In biology, there's an effect
called soundscape partitioning.
Different creatures choose unique audio frequencies
to communicate with each other.
In this spectrogram,
a kind of frog known as the chorus frog is up here.
The red-legged frog is down here.
Jeff: That allows us to see the red-legged frog calls
and the machine learning model to detect them,
even if there's a lot of masking noise from chorus frogs.
Narrator: Conservation Metrics' algorithm
has been trained on hundreds of hours of recording,
and it's learned to pinpoint the sound
of the red-legged frog.
Prior to the existence of this technology,
Gary would camp out at potential breeding areas
and tally frog calls using a pad and pencil.
Gary: We would spend days and not hear any.
And then one night, one of us would be in one spot
where you'd hear, like, 20 or 30 frogs,
because the weather was right,
the ambient temperature, the relative humidity.
Who knows what it was?
But that's what really kind of intrigued me.
I kept thinking about how much I kept missing.
Deploy one there.
Narrator: The algorithm doesn't replace Gary.
In fact, it requires his expertise.
Gary: We should stick one out
so you get more of the larger expanse.
Narrator: After six months of collecting data,
the team found only about 20 frogs
in the 200 acres they surveyed
around the Watsonville Slough.
It's a very fragile population.
By comparison, there are 50 to 60 frogs
in two acres around the landfill,
where there are fewer predators.
But with the tools Conservation Metrics deployed,
the water-diversion project could help grow their numbers.
This same technology is being used
to track at-risk wildlife around the world --
the northern spotted owl, African forest elephants,
and mountain lions, among many others.
It's a hopeful reminder
that if humans are to strike a better balance
with other species, maybe all we have to do is listen.
[frog croaks]