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NARRATOR: Migrations.
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Mysterious feats of navigation...
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endurance...
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and courage.
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Now, technology allows scientists
to go along for the ride...
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MAN: Really diving down...
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MAN: Yook, snap!
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NARRATOR: ...like never before.
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MAN: lt's an incredible thrill.
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Stuff happens that you wouldn't
believe in your wildest dreams.
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NARRATOR: ...learning
where the animals go...
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MAN: Cool! Wow.
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That's perfect.
Look at that!
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NARRATOR: ...why...
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and how they survive.
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MAN: This is really
cutting-edge stuff.
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MAN: We are the first to find out
what they're really doing.
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NARRATOR: This is the inside story
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of the science behind
the great migrations.
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On this October morning,
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elephant seals are nearing
the end of breeding season.
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From here in Patagonia,
they will soon embark
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on an odyssey
through the southern oceans.
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That's why a team of biologists
led by Flavio Quintana is here.
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To deploy a state-of-the-art tag
in hopes of tracking their every move.
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For ten months out of the year,
the seals migrate thousands of miles...
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disappearing into the sea to feed,
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where their behavior
is largely unknown.
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lt is a question vexing Quintana
for much of his 20-year career.
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QUlNTANA: We are always surprised
to study this kind of animal,
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because they are incredible, incredible.
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They are diving machines;
l'm really impressed with that.
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Because they need to come
back to shore to breed and to molt,
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but they spend 80 percent
of their life at sea.
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And nobody knows
what they are doing at sea.
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This is what we
are trying to discover.
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NARRATOR: lf the high-tech tag works,
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scientists will finally solve the mystery
of the elephant seals' migration.
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Quintana's special weapon
is called the Daily Diary,
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invented by this man, Rory Wilson.
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WlLSON: There are
temperature sensors in there,
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there are speed sensors in there,
there are light sensors in there,
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all packaged in this resin.
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This part here,
all this big clunky bit here,
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these are two batteries.
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The batteries are
inside stainless steel,
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and that's in order to protect
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against the ridiculous
amounts of pressures
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to which the animals
expose themselves routinely.
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NARRATOR: lt's the result
of ten years of trial and error.
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No other tag records
such a wide array of data.
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Wilson got the idea for his Daily Diary
while studying penguins.
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WlLSON: lt's terribly depressing.
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You go out on your island,
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you're going to do your whole Ph.D.,
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your doctorate on penguins,
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on what they do at sea,
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and they're all standing
around the edge
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looking at you saying,
"Yes, we're the penguins."
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Then they all jump in the water
and disappear.
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So in a grumpy
and foul-mouthed mood,
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l went back and thought,
"lf l can't see them,
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then l'll find something else
that's just going to record for me."
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Rather makeshift.
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NARRATOR: He tested the prototype
on an animal that follows direction...
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WlLSON: Stay!
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NARRATOR: ...his dog, Moon.
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Moon's Daily Diary recorded
her speed, her temperature,
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every breath, step and wag.
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WlLSON: Here's where l tell her
to run, throw the stick.
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Look at this activity here,
tearing towards the stick.
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Picks it up and then
this very regular canter back.
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NARRATOR: But it also revealed
things Wilson didn't expect.
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WlLSON: Her panting.
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She'll breathe up to six times a second
when she's panting...
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[panting]
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...when she's been running around.
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And when l'm about
to give her a command,
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l put my hand up, and
l discovered looking at the trace,
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she actually holds her breath
when my hand goes up.
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NARRATOR: This intrigued Wilson.
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He wanted to know more
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about the importance of breathing
in animal behavior.
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He returned to his penguins.
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The results were astonishing.
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WlLSON: Each one of these
is a flipper beating.
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lt's swimming
the whole time underwater,
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and relaxing a bit as it comes
back to the surface here.
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You can see as it comes back
for the first breath,
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it's using the buoyancy
to help it go up.
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So what the penguin's doing
is it's gone down,
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slight curve on the way down,
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it's come up,
it's spotted a prey,
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it's come up really rapidly
and it's gone yook, snap...
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and then drifted up to the surface.
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NARRATOR: The penguin takes in
the exact amount of air it needs
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in advance of a dive.
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WlLSON: You know, the penguin
before it goes down is saying:
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"How deep am l going to go
on the next dive,
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how many fish do l think
l'm going to catch?"
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They're inhaling
already at the surface
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the right amount of air volume
to give them neutral buoyancy
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at the depth at which
they're going to forage.
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So the implication is they know:
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"Ha, 30 meters, l need 600 milliliters
to be neutrally buoyant at that,
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so, 600, l'm going down."
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That's quite complicated stuff
for a small bird.
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NARRATOR: Their buoyant bodies
can then rise like balloons through the water,
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effortlessly catching fish
along the way.
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By doing this, the animal
conserves what it needs most
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for its migratory journey:
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energy.
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With this discovery,
Wilson joins Quintana
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to study the migration
of the elephant seals.
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ln two months, these behemoths
will return here to molt‒
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a perfect time to retrieve
the Daily Diaries
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because the batteries
won't last much longer.
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WlLSON: We've never
done this before
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in animals that are
going to go this deep,
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and it can just go horribly wrong.
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NARRATOR: Elephant seals
dive thousands of feet.
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lf the Daily Diary works
under such high pressure,
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we will witness a new era
of biological discovery.
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Quintana identifies females to tag‒
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at 2,000 pounds,
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they're easier to deal with
than the 8,000-pound males.
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Male or female, it's risky business.
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And the colony is restless.
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lt's up to Marcela Uhart
to anesthetize the giants.
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UHART: Elephant seals
are so big and so powerful, you know,
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they have very few predators.
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They don't really fear us that much.
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They actually challenge you.
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[groaning]
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[seal barking]
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UHART: Tomorrow he's going to be
on his own, l think...
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[growling]
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WlLSON: l don't like this
being protective of your friend stuff.
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l'd rather they just deserted them
and left them to it.
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NARRATOR: They name the tagged seals
after submarines and space stations.
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ln all, five females are successfully
rigged with Daily Diaries.
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WlLSON: We have five.
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lf we're lucky,
l think we'll get four back.
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l sort of tip somewhere
between three and four.
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And l'll just hope and pray
that they all are working okay.
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NARRATOR: lf it goes well,
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Wilson will be the first to tell
the story of this hidden journey.
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These seals' ocean pathways
are nearly boundless.
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But that is not the case
with many migratory routes on land.
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As human populations grow
and habitats diminish,
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the great migrating animals
are increasingly in peril...
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particularly the monarch butterfly.
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The monarchs' migration
spans generations of individuals
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and is an astounding
4,000 miles long,
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from Mexico to as far as Canada
and back again each year.
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CHlP TAYLOR: This is one of the world's
most magnificent natural phenomena.
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l mean, here you have
an insect that migrates
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to the same general location
every year,
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and then returns to breed
in the northern part of North America.
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NARRATOR: Chip Taylor
has dedicated his life's work
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to the ceaseless habits
of the monarch.
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For 18 years, he's been
tracking the migration
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with the same device:
a plastic tag.
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And he's learned a surprising
amount from this simple tool.
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ln one study, Taylor released
a monarch born in captivity
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2,000 miles from its birthplace.
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The butterfly still migrated
southwest to Mexico.
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TAYLOR: These butterflies
have to navigate across a continent.
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They have to navigate.
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How does a butterfly
coming out of Maine
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know how to get to Mexico?
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NARRATOR: ln 2009, scientists
discovered the monarch's internal GPS,
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a network of not one
but two internal clocks.
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A clock in the brain
tracks the location of the sun.
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And a second clock,
in the antennae,
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keeps track of time.
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TAYLOR: What they
are programmed to do
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is follow and respond
to certain physical cues,
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and these physical cues
have a default sort of mechanism
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of getting them to the right place.
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Now the trick for us is to try
to figure out what are those cues?
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NARRATOR: Understanding these cues
has never been more important.
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The monarch population is down
by halfjust from last year.
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lts ancient flyway
is unrecognizable
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00:13:01,680 --> 00:13:04,949
as development
overwhelms the landscape.
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And the milkweed plant
the monarch needs to lay its eggs
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is vanishing.
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TAYLOR: We're losing 6,000 acres a day
in this country due to development.
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00:13:22,501 --> 00:13:26,404
That's 2.2 million acres a year.
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00:13:26,438 --> 00:13:31,176
That's just an astounding amount
of habitat to turn into concrete.
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00:13:31,210 --> 00:13:33,845
And you just can't
keep on doing that
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00:13:33,879 --> 00:13:38,116
without having a really significant
impact on wildlife out there.
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00:13:40,252 --> 00:13:42,687
NARRATOR: Knowing how far
the monarchs fly each day
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00:13:42,721 --> 00:13:45,557
and where they stop
could save them.
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00:13:47,626 --> 00:13:52,664
An electronic tag that records
precise data could help.
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But this creature is light as smoke,
and a tag is a heavy load.
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00:14:04,777 --> 00:14:07,445
Enter Martin Wikelski.
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00:14:08,948 --> 00:14:11,282
He's a migration ecologist,
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00:14:11,317 --> 00:14:15,653
leading the charge
to miniaturize tag technology.
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00:14:17,990 --> 00:14:19,657
WlKELSKl: The smaller
you can get the tag,
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00:14:19,692 --> 00:14:23,394
the more power you can output,
the better the study we can do.
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00:14:23,429 --> 00:14:26,164
And that's going to be
a total breakthrough
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00:14:26,198 --> 00:14:30,735
in our understanding
of the natural environment.
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00:14:30,769 --> 00:14:32,170
We need to understand
small animals
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00:14:32,204 --> 00:14:34,105
to understand life on Earth,
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00:14:34,139 --> 00:14:37,442
and that's what we still
have no clue about.
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00:14:39,478 --> 00:14:40,879
NARRATOR: With radio tags,
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00:14:40,913 --> 00:14:43,548
Wikelski followed the route
of a one-ounce thrush,
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00:14:43,582 --> 00:14:47,285
discovering how it
navigates at night.
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00:14:47,319 --> 00:14:51,022
Then he went smaller,
switching to insects.
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00:14:53,125 --> 00:14:56,661
His team designed
a tiny hearing aid battery
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00:14:56,695 --> 00:15:00,231
attached to an antenna
made of a guitar string.
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00:15:02,067 --> 00:15:06,471
The smaller the device,
the simpler the data.
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00:15:06,505 --> 00:15:10,275
This radio tag only tracked
location and direction.
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00:15:10,309 --> 00:15:13,278
But it was a start.
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00:15:13,312 --> 00:15:16,080
Wikelski tried it on bees.
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00:15:16,115 --> 00:15:17,682
They flew.
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00:15:17,716 --> 00:15:19,284
He tried it on dragonflies
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00:15:19,318 --> 00:15:24,555
and discovered that one migrated
a hundred miles in a single day.
220
00:15:27,559 --> 00:15:32,063
But the monarch is
half the weight of a dragonfly.
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00:15:32,097 --> 00:15:34,666
TAYLOR: l first learned
about Martin's work a few years ago
222
00:15:34,700 --> 00:15:35,700
when l heard of his studies
223
00:15:35,734 --> 00:15:38,469
where he was putting radio tags
on dragonflies,
224
00:15:38,504 --> 00:15:39,904
and l thought that was
pretty fascinating.
225
00:15:39,939 --> 00:15:42,440
l thought, "Aw, man you'll never
get them small enough
226
00:15:42,474 --> 00:15:44,409
to put them on monarchs."
227
00:15:46,912 --> 00:15:49,047
NARRATOR:
Martin Wikelski's Kitty Hawk
228
00:15:49,081 --> 00:15:52,884
is the butterfly house
in Constance, Germany.
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00:15:53,686 --> 00:15:55,353
WlKELSKl: Nice.
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00:16:03,495 --> 00:16:09,133
NARRATOR: The tag is the smallest yet,
half the weight of this butterfly.
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00:16:12,071 --> 00:16:13,638
WlKELSKl: Available radio tag,
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00:16:13,672 --> 00:16:16,741
and they just barely got it
in the size range
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00:16:16,775 --> 00:16:18,643
that the butterfly
might fly with it.
234
00:16:18,677 --> 00:16:22,880
And now we just try it.
235
00:16:22,915 --> 00:16:26,918
NARRATOR: Trial one: no go.
236
00:16:26,952 --> 00:16:31,389
A slight antenna adjustment,
then trial two.
237
00:16:33,692 --> 00:16:35,760
And liftoff.
238
00:16:35,794 --> 00:16:37,929
WlKELSKl: Wow!
239
00:16:45,070 --> 00:16:46,738
[laughing]
240
00:16:48,107 --> 00:16:49,807
Oh, there it is.
241
00:16:49,842 --> 00:16:52,143
lt's working.
242
00:16:52,177 --> 00:16:56,714
lt's totally amazing, l mean,
the first flight of a butterfly with a tag!
243
00:16:56,749 --> 00:17:00,718
So it's working, l mean, you see
it's just flying all over the place.
244
00:17:00,753 --> 00:17:03,788
So l think it's going to work
in the field as well.
245
00:17:03,822 --> 00:17:05,790
This is flying beautifully.
246
00:17:05,824 --> 00:17:08,092
lt's amazing.
247
00:17:08,127 --> 00:17:10,361
NARRATOR: Wikelski and Taylor
will now team up
248
00:17:10,396 --> 00:17:15,800
to see if they are on the brink
of a new age of monarch science.
249
00:17:15,834 --> 00:17:18,503
[rooster crows]
250
00:17:22,641 --> 00:17:25,243
The migration ecologist
Martin Wikelski
251
00:17:25,277 --> 00:17:29,480
finally meets
the monarch sage Chip Taylor.
252
00:17:29,515 --> 00:17:32,183
Together, they'll conduct
the first test ever
253
00:17:32,217 --> 00:17:36,421
of an electronic tag
on a monarch butterfly.
254
00:17:36,455 --> 00:17:39,123
lt's a meeting of like minds...
255
00:17:39,158 --> 00:17:43,394
but not when it comes
to catching butterflies.
256
00:17:43,429 --> 00:17:47,432
TAYLOR: Come up behind the butterfly
while it's sitting on a flower.
257
00:17:47,466 --> 00:17:50,768
What you don't want to do
is swing at them in the air.
258
00:17:50,803 --> 00:17:51,803
WlKELSKl: Okay.
259
00:17:51,837 --> 00:17:53,971
TAYLOR: Get it! Whoa!
260
00:18:01,747 --> 00:18:04,882
l mean, he's like a little kid;
it's wonderful.
261
00:18:06,785 --> 00:18:09,153
At my age, l don't do that anymore.
262
00:18:09,188 --> 00:18:11,689
l prefer the sneaky method!
263
00:18:11,723 --> 00:18:13,958
Looks like we got one here.
264
00:18:18,597 --> 00:18:21,599
NARRATOR: The scientists
catch six in all.
265
00:18:23,869 --> 00:18:25,269
Success will be determined
266
00:18:25,304 --> 00:18:28,906
if the tags do not disrupt
the monarchs' migration.
267
00:18:30,642 --> 00:18:34,412
And if the insects
can be found after takeoff.
268
00:18:34,446 --> 00:18:36,180
WlKELSKl: l'll just get the transmitter.
269
00:18:36,215 --> 00:18:38,082
NARRATOR: But Taylor has his doubts.
270
00:18:38,117 --> 00:18:39,784
TAYLOR: One of the things
about these kinds of tests
271
00:18:39,818 --> 00:18:42,720
is that you do them indoors,
you do them under ideal conditions,
272
00:18:42,754 --> 00:18:44,088
and then we bring them
out here in the field,
273
00:18:44,123 --> 00:18:45,890
and we're dealing
with 20-mile-an-hour winds,
274
00:18:45,924 --> 00:18:48,826
and it's going to be
quite challenging for the butterfly
275
00:18:48,861 --> 00:18:50,862
to figure out how to handle
all of this mass
276
00:18:50,896 --> 00:18:53,397
that you're attaching
to the abdomen.
277
00:18:56,902 --> 00:18:58,703
WlKELSKl: Now it's up to the butterfly.
278
00:18:58,737 --> 00:19:02,440
TAYLOR: Well, we're not going
to name it lcarus, right?
279
00:19:02,474 --> 00:19:04,842
WlKELSKl: Let's call it lcarus
and see if lcarus can fly.
280
00:19:08,580 --> 00:19:09,580
WlKELSKl: Wow.
281
00:19:09,615 --> 00:19:11,349
TAYLOR: Wow. lt's flying pretty well,
look at that.
282
00:19:11,383 --> 00:19:12,383
WlKELSKl: That's amazing.
283
00:19:12,417 --> 00:19:14,552
TAYLOR: lt's staying close
to the ground, though.
284
00:19:14,586 --> 00:19:16,420
WlKELSKl: Wow, it's flying!
285
00:19:18,023 --> 00:19:21,826
TAYLOR: All right, let's start
with liftoff here.
286
00:19:21,860 --> 00:19:22,860
WlKELSKl: Wow!
287
00:19:22,895 --> 00:19:24,862
TAYLOR: There she goes.
288
00:19:24,897 --> 00:19:26,664
That's cool.
289
00:19:26,698 --> 00:19:28,966
That's terrific, look at that!
290
00:19:29,001 --> 00:19:30,401
WlKELSKl: Wow, it's really taking off.
291
00:19:30,435 --> 00:19:32,670
TAYLOR: lt's really catching the wind.
292
00:19:32,704 --> 00:19:36,007
WlKELSKl: lt's coming over to your side.
293
00:19:36,041 --> 00:19:37,041
TAYLOR: Big Boy.
294
00:19:37,075 --> 00:19:38,509
WlKELSKl: Wow, that's a big one.
295
00:19:38,544 --> 00:19:41,279
TAYLOR: That's the biggest
butterfly we've got.
296
00:19:41,313 --> 00:19:43,948
There it goes.
297
00:19:43,982 --> 00:19:45,883
WlKELSKl: There she goes.
298
00:19:49,521 --> 00:19:52,023
l think he still wants to feed.
299
00:19:52,057 --> 00:19:54,759
[laughing]
300
00:20:07,105 --> 00:20:10,174
NARRATOR: Taylor and Wikelski
take to the air, too,
301
00:20:10,209 --> 00:20:12,710
in pursuit of the tagged monarchs.
302
00:20:14,346 --> 00:20:20,284
With radio receivers in tow,
they listen for a telltale click.
303
00:20:20,319 --> 00:20:24,722
WlKELSKl: We are looking
for liftoff right now.
304
00:20:24,756 --> 00:20:28,259
NARRATOR: Each butterfly
is on its own frequency.
305
00:20:28,293 --> 00:20:29,293
[click]
306
00:20:29,328 --> 00:20:30,695
WlKELSKl: There it is, do you hear it?
307
00:20:30,729 --> 00:20:32,964
We've got a signal.
308
00:20:32,998 --> 00:20:38,002
NARRATOR: An auspicious start—
some signals come in loud and clear.
309
00:20:38,036 --> 00:20:42,940
WlKELSKl: So liftoff is still
probably at the field down there.
310
00:20:45,410 --> 00:20:49,046
NARRATOR: But the test is incomplete
until a butterfly has flown
311
00:20:49,081 --> 00:20:54,151
more than a few miles
in a northeasterly direction.
312
00:20:54,186 --> 00:20:56,520
TAYLOR: Martin, any sign of lcarus?
313
00:20:56,555 --> 00:20:58,356
WlKELSKl: Nope, we will go
a little lower
314
00:20:58,390 --> 00:21:00,691
and search closer to the ground.
315
00:21:00,726 --> 00:21:02,493
TAYLOR: Let's hope it works.
316
00:21:04,696 --> 00:21:05,730
[buzzing]
317
00:21:05,764 --> 00:21:07,565
WlKELSKl: Yep, yep, there it is.
318
00:21:07,599 --> 00:21:09,033
l do hear lcarus.
319
00:21:09,067 --> 00:21:11,202
TAYLOR: Good old lcarus.
320
00:21:11,236 --> 00:21:13,404
WlKELSKl: lcarus is down there, yes.
321
00:21:13,438 --> 00:21:17,375
NARRATOR: All but one
are accounted for.
322
00:21:17,409 --> 00:21:20,211
Big Boy is still missing.
323
00:21:22,714 --> 00:21:24,015
TAYLOR: Martin, do you hear anything?
324
00:21:24,049 --> 00:21:26,117
WlKELSKl: Nope.
325
00:21:26,151 --> 00:21:29,587
NARRATOR: Perhaps he's
a long distance flyer...
326
00:21:29,621 --> 00:21:34,625
or the weight weighed him down,
plummeting him to Earth.
327
00:21:36,295 --> 00:21:39,797
Taylor and Wikelski
continue northeast.
328
00:21:42,534 --> 00:21:45,069
Five miles out.
329
00:21:45,103 --> 00:21:46,537
Nothing.
330
00:21:49,608 --> 00:21:52,143
Ten miles out.
331
00:21:52,177 --> 00:21:53,978
[buzzing]
332
00:21:54,012 --> 00:21:55,112
And they get it.
333
00:21:55,147 --> 00:21:56,347
WlKELSKl: That's the signal!
334
00:21:56,381 --> 00:21:57,648
TAYLOR: That's fantastic!
335
00:21:57,683 --> 00:22:02,320
[cheering]
336
00:22:04,356 --> 00:22:07,858
[laughing]
337
00:22:14,132 --> 00:22:18,269
TAYLOR: lt was incredible!
lt was unbelievable!
338
00:22:18,303 --> 00:22:21,672
We got Big Boy
out there about 15 miles!
339
00:22:23,809 --> 00:22:25,343
NARRATOR: There's one last step.
340
00:22:25,377 --> 00:22:27,778
They need to find Big Boy
on the ground
341
00:22:27,813 --> 00:22:30,081
to identify his stopover point
342
00:22:30,115 --> 00:22:33,250
and find out if he's
still in good condition.
343
00:22:33,285 --> 00:22:34,852
WlKELSKl: That's three miles out there.
344
00:22:34,886 --> 00:22:36,020
TAYLOR: Yeah.
345
00:22:36,054 --> 00:22:38,856
NARRATOR: They follow
Big Boy's radio signal.
346
00:22:40,692 --> 00:22:43,094
Weaker.
347
00:22:43,128 --> 00:22:44,228
Stronger.
348
00:22:44,262 --> 00:22:48,366
WlKELSKl: ln a few hundred meters,
l think we should take a right.
349
00:22:48,400 --> 00:22:51,335
[static]
350
00:22:52,371 --> 00:22:54,672
NARRATOR: Weaker again.
351
00:22:54,706 --> 00:22:57,108
WlKELSKl: No, that's not good.
352
00:22:57,142 --> 00:23:00,745
Maybe we should have gone left
and then go north, l don't know.
353
00:23:00,779 --> 00:23:03,147
TAYLOR: Big Boy's moved
out of town.
354
00:23:05,817 --> 00:23:08,352
WlKELSKl: There it is,
l've got a signal.
355
00:23:08,387 --> 00:23:10,521
Yes!
356
00:23:10,555 --> 00:23:12,423
Okay, now we get it.
357
00:23:22,868 --> 00:23:26,504
WlKELSKl: On this side
or the other side?
358
00:23:26,538 --> 00:23:30,207
TAYLOR: lt's not appropriate for him
to say, "Come to me, Big Boy."
359
00:23:31,843 --> 00:23:34,478
WlKELSKl: Hey! Here he is!
360
00:23:34,513 --> 00:23:36,614
That's it!
361
00:23:36,648 --> 00:23:37,882
[laughing]
362
00:23:37,916 --> 00:23:39,083
TAYLOR: Fantastic!
363
00:23:39,117 --> 00:23:40,451
WlKELSKl: Yes!
364
00:23:40,485 --> 00:23:42,319
TAYLOR: Fantastic!
All right!
365
00:23:42,354 --> 00:23:43,988
Good for you!
366
00:23:45,924 --> 00:23:50,928
NARRATOR: A scientific breakthrough,
the first test of its kind.
367
00:23:50,962 --> 00:23:54,865
Big Boy is found
in perfect condition.
368
00:23:54,900 --> 00:23:56,434
WlKELSKl: lt's really perfect.
369
00:23:56,468 --> 00:23:58,502
TAYLOR: Yeah, this antenna
is not an impediment at all.
370
00:23:58,537 --> 00:23:59,203
WlKELSKl: No, no.
371
00:23:59,237 --> 00:24:00,471
TAYLOR: Hot damn...
372
00:24:00,505 --> 00:24:02,540
[laughing]
373
00:24:02,574 --> 00:24:04,375
hot damn!
374
00:24:06,178 --> 00:24:08,879
NARRATOR: The technology works,
375
00:24:08,914 --> 00:24:13,117
and the future for these insects
as well as countless other animals
376
00:24:13,151 --> 00:24:15,820
may soon be the better for it.
377
00:24:15,854 --> 00:24:19,023
TAYLOR: Big Boy is ready to go,
go to Wisconsin,
378
00:24:19,057 --> 00:24:20,825
find a girlfriend,
there he goes.
379
00:24:20,859 --> 00:24:22,193
WlKELSKl: Yeah.
380
00:24:22,227 --> 00:24:24,094
TAYLOR: There he goes, all right!
381
00:24:24,129 --> 00:24:26,831
And look it, he's going northeast,
he headed out that way.
382
00:24:26,865 --> 00:24:28,666
Right along the tree line, northeast.
383
00:24:28,700 --> 00:24:32,369
WlKELSKl: A lot of people complain
that it's hard to discover things these days
384
00:24:32,404 --> 00:24:33,504
because everything's known.
385
00:24:33,538 --> 00:24:35,539
Absolutely not!
386
00:24:35,574 --> 00:24:36,607
Everything's new.
387
00:24:36,641 --> 00:24:40,244
Every time we look at it,
we see something new here.
388
00:24:43,048 --> 00:24:48,452
NARRATOR: Taylor now has a new tool
in which to continue his life's work.
389
00:24:51,756 --> 00:24:55,392
TAYLOR: l watch this population go up,
and l watch it go down.
390
00:24:55,427 --> 00:24:59,296
l watch its life and death struggles
all of the time.
391
00:24:59,331 --> 00:25:03,567
l'm so intimately attached
and involved with this butterfly.
392
00:25:04,369 --> 00:25:06,804
And l don't know how
to explain it any other way.
393
00:25:06,838 --> 00:25:10,407
lt's just what l am,
394
00:25:10,442 --> 00:25:13,444
and that's about all
l can say about it.
395
00:25:18,316 --> 00:25:21,852
NARRATOR: Migration is
seldom attempted alone.
396
00:25:21,887 --> 00:25:25,289
But there's more than safety
in numbers.
397
00:25:30,061 --> 00:25:36,600
For mathematical ecologist John Fryxell,
migration is math in motion.
398
00:25:38,703 --> 00:25:43,040
Where we see animals,
he sees mathematical patterns.
399
00:25:43,074 --> 00:25:45,809
And he's using these patterns
to unlock the key
400
00:25:45,844 --> 00:25:48,846
to wildebeest survival
and migration.
401
00:25:50,015 --> 00:25:52,449
FRYXELL: l think migration
is kind of a theme in my life.
402
00:25:52,484 --> 00:25:55,619
There's just something about mobility
that fascinates me.
403
00:25:55,654 --> 00:25:57,755
The urge to try and predict
patterns of movement
404
00:25:57,789 --> 00:26:00,224
to me is just really intriguing.
405
00:26:01,726 --> 00:26:05,329
NARRATOR: ln the Serengeti
grasslands of Tanzania,
406
00:26:05,363 --> 00:26:09,300
wildebeest are on
their 300-mile journey.
407
00:26:12,270 --> 00:26:17,408
This annual event is among
the great natural spectacles on the planet,
408
00:26:17,442 --> 00:26:20,477
as herds of zebra, gazelle
and wildebeest
409
00:26:20,512 --> 00:26:24,515
chase the rain
and the grass it nurtures.
410
00:26:28,386 --> 00:26:32,890
But the wildebeest
pay a hefty toll...
411
00:26:32,924 --> 00:26:36,393
five out of six young
don't make it.
412
00:26:47,305 --> 00:26:50,541
And yet the herd
is a million strong.
413
00:26:53,078 --> 00:26:56,246
Fryxell is determined
to figure out how‒
414
00:26:56,281 --> 00:27:00,451
despite these odds‒
the herd thrives.
415
00:27:03,722 --> 00:27:08,626
He begins by observing
the wildebeest behavior from the air.
416
00:27:11,696 --> 00:27:15,366
From up here, he can see
the patterns of the herds.
417
00:27:15,400 --> 00:27:20,004
FRYXELL: We can see a hyena
over there heading over to the track.
418
00:27:20,038 --> 00:27:24,842
Certainly there's some complex dynamics
within the whole herd of wildebeest.
419
00:27:24,876 --> 00:27:26,677
Well, the interesting thing
during the migration
420
00:27:26,711 --> 00:27:30,014
is it's a series of individuals,
one after the other,
421
00:27:30,048 --> 00:27:34,551
following blindly behind
the movement of a key individual.
422
00:27:34,586 --> 00:27:35,886
l mean, this is, you know,
really interesting,
423
00:27:35,920 --> 00:27:38,188
this kind of streaming behavior
of the wildebeest,
424
00:27:38,223 --> 00:27:39,990
you know, going forward.
425
00:27:43,061 --> 00:27:46,597
Clearly there are some individuals
that are at the front of the line.
426
00:27:46,631 --> 00:27:48,032
The behavior of some leaders
427
00:27:48,066 --> 00:27:49,533
gets translated to the rest
of the group,
428
00:27:49,567 --> 00:27:52,803
and then the group behaves
like a super organism.
429
00:27:54,572 --> 00:27:57,041
NARRATOR: Wildebeest
as super organism‒
430
00:27:57,075 --> 00:28:00,811
individuals affecting
the behavior of the whole.
431
00:28:02,647 --> 00:28:04,715
Fryxell then looks at what forces
432
00:28:04,749 --> 00:28:08,752
shape the migratory path
of this super organism.
433
00:28:10,255 --> 00:28:15,559
He suspects the key to why they survive
in such great numbers is here‒
434
00:28:15,593 --> 00:28:17,961
starting with an insect.
435
00:28:19,998 --> 00:28:23,100
The dung beetle thrives
on wildebeest manure,
436
00:28:23,134 --> 00:28:26,804
which it collects into balls
and stores underground,
437
00:28:26,838 --> 00:28:30,240
fertilizing the soil...
438
00:28:30,275 --> 00:28:33,844
allowing more wildebeest
to graze.
439
00:28:35,380 --> 00:28:38,449
Millions of mouths
mow the grass,
440
00:28:38,483 --> 00:28:43,721
keeping trees in check,
but allowing brush to grow.
441
00:28:45,690 --> 00:28:51,862
Forming the perfect cover
for predators that eat wildebeest.
442
00:28:54,399 --> 00:28:58,135
lt all leads, in the end,
to the predators.
443
00:28:58,169 --> 00:29:00,938
Fryxell believes predators‒
more than anything‒
444
00:29:00,972 --> 00:29:03,540
shape the herd's patterns.
445
00:29:07,545 --> 00:29:11,048
And his team takes
a closer look at the lioness.
446
00:29:11,082 --> 00:29:12,349
MAN: Okay.
447
00:29:12,383 --> 00:29:14,384
[fires rifle]
448
00:29:21,693 --> 00:29:26,597
FRYXELL: Nine, so now we move
to the upper right canine.
449
00:29:27,465 --> 00:29:32,136
NARRATOR: The GPS on the collar
will allow the team to track its movement.
450
00:29:35,673 --> 00:29:40,878
An accelerometer records
her every start, stop and speed,
451
00:29:40,912 --> 00:29:48,152
which tells when the hunter rests,
prowls or takes to the chase.
452
00:29:49,354 --> 00:29:52,222
FRYXELL: Five, six,
seven wildebeest...
453
00:29:52,257 --> 00:29:54,625
NARRATOR: Using
on-site observations...
454
00:29:54,659 --> 00:29:56,026
FRYXELL: ...21 wildebeest.
455
00:29:56,060 --> 00:30:00,464
NARRATOR: ...data from collared predators
and collared wildebeests,
456
00:30:00,498 --> 00:30:02,766
Fryxell can build
mathematical models
457
00:30:02,801 --> 00:30:06,737
that predict the behavior
of predator and prey.
458
00:30:08,406 --> 00:30:09,907
lt reads like a video game
459
00:30:09,941 --> 00:30:14,678
where he can create different scenarios
between lions and wildebeest.
460
00:30:16,581 --> 00:30:21,418
First, Fryxell conjures up
wildebeests that do not herd.
461
00:30:23,021 --> 00:30:27,057
He spreads them out
like marbles over the landscape.
462
00:30:28,359 --> 00:30:31,562
Then he lets a simulated lion loose.
463
00:30:33,031 --> 00:30:38,068
FRYXELL: There's a kill,
and another kill.
464
00:30:38,102 --> 00:30:43,407
And the net result is that it's very easy
for the lion to encounter fresh prey,
465
00:30:43,441 --> 00:30:45,375
so with that very high
density of prey,
466
00:30:45,410 --> 00:30:46,810
you see the lion doesn't even
have to go very far
467
00:30:46,845 --> 00:30:49,179
before it finds a new meal.
468
00:30:52,851 --> 00:30:57,054
NARRATOR: ln this model,
the wildebeest do not stand a chance.
469
00:31:00,124 --> 00:31:05,662
The next simulation more closely
models a typical herd's behavior.
470
00:31:05,697 --> 00:31:08,332
FRYXELL: Grouping together
creates great big vacant areas
471
00:31:08,366 --> 00:31:11,535
that aren't very efficient
for the lion to search in.
472
00:31:11,569 --> 00:31:13,804
NARRATOR: Here, the wildebeest
evade predators
473
00:31:13,838 --> 00:31:19,776
by grouping together and forming
what he calls holes in the landscape,
474
00:31:19,811 --> 00:31:24,248
vast areas where a lion
can't see a wildebeest.
475
00:31:27,185 --> 00:31:31,088
The super organism
then goes a step further:
476
00:31:31,122 --> 00:31:34,825
the holes in the landscape move.
477
00:31:34,859 --> 00:31:37,494
FRYXELL: Well, when you're
the best meal on four hooves,
478
00:31:37,528 --> 00:31:40,664
the best thing you can do
is be unpredictable.
479
00:31:40,698 --> 00:31:42,032
The last thing you want to be
480
00:31:42,066 --> 00:31:45,168
is a meal where the lions
expect you to be.
481
00:31:47,138 --> 00:31:49,239
NARRATOR: Lions know
when seasonal herds
482
00:31:49,274 --> 00:31:51,642
pass through their territory,
483
00:31:51,676 --> 00:31:55,379
but they won't know
exactly where to find them.
484
00:31:55,413 --> 00:31:58,849
FRYXELL: So we can see this
on this map of the Serengeti ecosystem,
485
00:31:58,883 --> 00:32:02,586
where the bright colors signify
really high densities of animals,
486
00:32:02,620 --> 00:32:07,224
large herds that are shifting
without any kind of predictable pattern
487
00:32:07,258 --> 00:32:09,559
across the landscape
from month to month.
488
00:32:09,594 --> 00:32:11,528
Now imagine that you're
a lion or hyena
489
00:32:11,562 --> 00:32:13,931
trying to make a living
in that kind of landscape.
490
00:32:13,965 --> 00:32:15,499
lt's virtually impossible
for you to know
491
00:32:15,533 --> 00:32:18,835
what would be the best place
for you to set up a territory.
492
00:32:20,905 --> 00:32:23,040
NARRATOR: The herd
as super organism,
493
00:32:23,074 --> 00:32:25,943
and the surprisingly random
nature of its movement,
494
00:32:25,977 --> 00:32:27,744
keep a predator guessing,
495
00:32:27,779 --> 00:32:31,515
keeping the wildebeest
a million strong.
496
00:32:34,852 --> 00:32:36,954
But this ingenious
survival mechanism
497
00:32:36,988 --> 00:32:40,691
could never work
without a large habitat.
498
00:32:43,261 --> 00:32:46,129
And large habitats
are increasingly rare
499
00:32:46,164 --> 00:32:50,434
as humans encroach
on wild spaces.
500
00:32:53,237 --> 00:32:56,139
For many of the world's
migratory animals,
501
00:32:56,174 --> 00:32:59,409
this is the main threat
to their survival.
502
00:33:06,651 --> 00:33:10,153
ln Mali, West Africa,
the desert elephant
503
00:33:10,188 --> 00:33:13,957
once roamed vast distances
unimpeded.
504
00:33:16,060 --> 00:33:20,330
Now the last animals
of their kind are under threat.
505
00:33:23,201 --> 00:33:27,270
Tracker El Mehdi Doumbia
and biologist Jake Wall
506
00:33:27,305 --> 00:33:30,007
from the organization
Save the Elephants
507
00:33:30,041 --> 00:33:35,145
have collared nine
of the 350 elephants here.
508
00:33:35,179 --> 00:33:37,514
The more they can learn
about the herd's habits...
509
00:33:37,548 --> 00:33:39,383
WALL: Good, fresh tracks.
510
00:33:39,417 --> 00:33:44,154
NARRATOR: ...the better they will be able
to protect their migratory routes.
511
00:33:44,188 --> 00:33:46,323
WALL: These elephants
don't give us a moment to rest,
512
00:33:46,357 --> 00:33:47,724
they keep moving,
513
00:33:47,759 --> 00:33:49,960
we keep having to work
really, really hard
514
00:33:49,994 --> 00:33:51,762
to try and find them,
515
00:33:51,796 --> 00:33:56,333
and, even with the tracking data,
it's not an easy job.
516
00:33:56,367 --> 00:33:58,935
NARRATOR: The only way
the Mali elephants can survive
517
00:33:58,970 --> 00:34:02,439
is to move.
518
00:34:02,473 --> 00:34:08,078
They walk endlessly over a home range
of over 12,000 square miles
519
00:34:08,112 --> 00:34:11,114
in the harsh heat of the Sahel.
520
00:34:13,017 --> 00:34:17,854
No other elephants travel farther
in search of food and water.
521
00:34:20,758 --> 00:34:25,562
During the dry season,
they end up here.
522
00:34:25,596 --> 00:34:31,268
Lake Banzena is one of the few places
to find water year round.
523
00:34:38,109 --> 00:34:42,446
The herds linger
until distant rains begin.
524
00:34:54,192 --> 00:34:57,260
Elephants can hear rain fall
vast distances away
525
00:34:57,295 --> 00:35:00,664
because of its low
infrasonic signal.
526
00:35:02,467 --> 00:35:08,338
Then, within 24 hours,
they go to where the rain is.
527
00:35:08,372 --> 00:35:11,908
And this year,
water is most critical.
528
00:35:11,943 --> 00:35:16,146
lt is the worst drought in 26 years.
529
00:35:21,119 --> 00:35:23,587
The herd must move fast,
530
00:35:23,621 --> 00:35:27,224
because between the lake
and the next stopover point
531
00:35:27,258 --> 00:35:31,995
lies 60 miles of desert...
532
00:35:32,029 --> 00:35:36,333
and a big obstacle:
the Gandamia Plateau.
533
00:35:38,336 --> 00:35:41,571
There's just one way through:
534
00:35:41,606 --> 00:35:45,542
la portes des elephants,
the elephants' door—
535
00:35:45,576 --> 00:35:50,213
a cut in the mountain the herds
have been using for centuries.
536
00:35:55,086 --> 00:35:59,523
lt's also a place with
increasing human settlement...
537
00:35:59,557 --> 00:36:01,091
and where elephants compete
538
00:36:01,125 --> 00:36:04,761
with herders and their animals
for water.
539
00:36:07,598 --> 00:36:09,900
These images capture
a dramatic scene
540
00:36:09,934 --> 00:36:12,702
as villagers and
a Save the Elephants team
541
00:36:12,737 --> 00:36:17,941
desperately try to rescue
a teenage female and three juveniles.
542
00:36:20,778 --> 00:36:25,515
They fell, one after another,
into a man-made well searching for water.
543
00:36:27,585 --> 00:36:30,020
The older elephant crushed
and killed a younger one
544
00:36:30,054 --> 00:36:33,690
during the three-day ordeal.
545
00:36:33,724 --> 00:36:38,828
These tragedies happen as humans
settle on ancient elephant paths.
546
00:36:44,168 --> 00:36:48,371
But 3,000 miles to the east,
in the grasslands of Kenya...
547
00:36:48,406 --> 00:36:49,472
lAlN DOUGLAS-HAMlLTON:
l am just going to put a little bit of water
548
00:36:49,507 --> 00:36:51,041
on the back without splashing.
549
00:36:51,075 --> 00:36:52,976
DABALLEN: Don't step
on the ears, please.
550
00:36:53,010 --> 00:36:56,446
NARRATOR: ...a solution
is being tested.
551
00:36:56,480 --> 00:37:00,750
Biologist lain Douglas-Hamilton
has gained near legendary status
552
00:37:00,785 --> 00:37:04,321
for being the African elephant's
custodian.
553
00:37:04,355 --> 00:37:06,223
DOUGLAS-HAMlLTON: You don't think
that's too loose?
554
00:37:06,257 --> 00:37:07,757
We're collaring elephants
555
00:37:07,792 --> 00:37:11,995
because we believe
that by understanding their movements,
556
00:37:12,029 --> 00:37:14,598
we can understand
their decisions.
557
00:37:14,632 --> 00:37:20,737
And if we understand their decisions,
we understand what they need.
558
00:37:20,771 --> 00:37:25,475
Elephants are at a tough time now,
and we have to plan for their future.
559
00:37:27,245 --> 00:37:30,614
NARRATOR: Over the years,
Douglas-Hamilton has witnessed first hand
560
00:37:30,648 --> 00:37:35,051
the disastrous consequences
of human-elephant conflict.
561
00:37:36,487 --> 00:37:41,825
Poaching for ivory tusks was once
the chief killer of elephants.
562
00:37:44,328 --> 00:37:49,065
Today, it's farmers
who protect their crops.
563
00:37:54,472 --> 00:37:56,673
Douglas-Hamilton
with his wife Oria
564
00:37:56,707 --> 00:37:59,843
founded Save the Elephants
40 years ago
565
00:37:59,877 --> 00:38:05,782
to study and protect this
severely endangered species.
566
00:38:05,816 --> 00:38:08,151
This rustic outpost
is the repository
567
00:38:08,185 --> 00:38:10,320
of the organization's studies
on elephants
568
00:38:10,354 --> 00:38:13,423
from all over the African continent...
569
00:38:15,092 --> 00:38:17,861
information that scientists
throughout the world
570
00:38:17,895 --> 00:38:19,929
have come to rely on.
571
00:38:19,964 --> 00:38:21,531
DOUGLAS-HAMlLTON: lt's actually
a kilometer wide.
572
00:38:21,565 --> 00:38:23,400
lt's working well.
573
00:38:23,434 --> 00:38:25,802
NARRATOR: Today, the team
is collaring an elephant
574
00:38:25,836 --> 00:38:29,806
with a state-of-the-art device
that might save its life‒
575
00:38:29,840 --> 00:38:34,778
a tag that sends an alert
when the animal nears a farm.
576
00:38:34,812 --> 00:38:38,381
DOUGLAS-HAMlLTON: Many elephants
across Africa get shot
577
00:38:38,416 --> 00:38:42,652
because they cause damage
to human property,
578
00:38:42,687 --> 00:38:47,324
to crops, to livelihoods,
and indeed they kill people.
579
00:38:47,358 --> 00:38:52,362
And you want every high-tech option
that you can deploy.
580
00:38:58,069 --> 00:39:00,870
NARRATOR: lain Douglas-Hamilton
searches for a herd,
581
00:39:00,905 --> 00:39:03,206
scanning the landscape by air
582
00:39:03,240 --> 00:39:07,444
while researcher David Daballen's
team is on the ground.
583
00:39:11,349 --> 00:39:13,717
DOUGLAS-HAMlLTON:
David, David!
584
00:39:13,751 --> 00:39:14,884
DABALLEN: Sorry, lain?
585
00:39:14,919 --> 00:39:16,119
DOUGLAS-HAMlLTON:
Where l am circling
586
00:39:16,153 --> 00:39:20,423
there are two groups of elephants
tightly under the trees.
587
00:39:22,159 --> 00:39:24,327
DABALLEN: He has found them
in a perfect place.
588
00:39:24,362 --> 00:39:25,395
We don't want to lose them,
589
00:39:25,429 --> 00:39:27,797
because they are not quite often
at the moment around.
590
00:39:27,832 --> 00:39:31,634
We want to take the opportunity
to dart them, put a collar,
591
00:39:31,669 --> 00:39:33,903
because we know that
from our past experience
592
00:39:33,938 --> 00:39:36,306
they will defend so much.
593
00:39:36,340 --> 00:39:37,440
And if we have four cars
594
00:39:37,475 --> 00:39:40,210
we can position ourselves
in different positions
595
00:39:40,244 --> 00:39:41,711
to make sure that the females
596
00:39:41,746 --> 00:39:44,647
will not see the female
that has gone down.
597
00:39:49,120 --> 00:39:53,223
NARRATOR: They identify
the female to be collared.
598
00:39:53,257 --> 00:39:55,358
DABALLEN: Dart in.
599
00:40:04,668 --> 00:40:06,936
She's down, she's down!
600
00:40:06,971 --> 00:40:08,204
Let's get a good position.
601
00:40:08,239 --> 00:40:10,206
Drive.
602
00:40:12,243 --> 00:40:15,311
Drive, drive!
603
00:40:23,854 --> 00:40:25,121
NARRATOR:
Once she's unconscious,
604
00:40:25,156 --> 00:40:30,160
Daballen has only 20 minutes
to attach the collar.
605
00:40:30,194 --> 00:40:34,130
The anesthesia makes
the trunk muscles go slack‒
606
00:40:34,165 --> 00:40:37,967
a stick will keep her airway open.
607
00:40:38,002 --> 00:40:39,536
This particular collar will do
608
00:40:39,570 --> 00:40:42,806
what Douglas-Hamilton
once only dreamed of:
609
00:40:42,840 --> 00:40:46,643
lt will allow an elephant
to communicate with him.
610
00:40:48,078 --> 00:40:52,515
The collar sends its alert
to a cell phone via text message.
611
00:40:54,385 --> 00:40:59,923
This high-tech innovation
is called geofencing.
612
00:40:59,957 --> 00:41:02,926
When an elephant crosses
a virtual fence line,
613
00:41:02,960 --> 00:41:07,630
the GPS unit in the collar
sends an SMS or text message
614
00:41:07,665 --> 00:41:10,133
to a server in Nairobi.
615
00:41:10,167 --> 00:41:13,870
The server then sends text alerts
to a list of recipients
616
00:41:13,904 --> 00:41:16,105
who can quickly intercept the herd
617
00:41:16,140 --> 00:41:19,909
before it reaches a farm
or human settlement.
618
00:41:21,912 --> 00:41:24,280
DABALLEN: Get in the car!
619
00:41:35,459 --> 00:41:39,395
NARRATOR: The female awakes
groggy but unharmed‒
620
00:41:39,430 --> 00:41:42,098
the collar fits perfectly.
621
00:41:46,470 --> 00:41:48,938
She will blow out the stick
in her trunk,
622
00:41:48,973 --> 00:41:52,742
but for now it assures her
an open airway.
623
00:41:54,845 --> 00:41:57,881
DOUGLAS-HAMlLTON: Sometimes
when you have dense agriculture,
624
00:41:57,915 --> 00:41:59,148
the best thing you can do
625
00:41:59,183 --> 00:42:02,585
is to separate the people
from the elephants.
626
00:42:02,620 --> 00:42:04,954
When an elephant crosses
a certain boundary,
627
00:42:04,989 --> 00:42:07,123
we get an alarm to be set off,
628
00:42:07,157 --> 00:42:10,460
and it gets sent to us
on a mobile telephone,
629
00:42:10,494 --> 00:42:15,765
which allows us to plan much better
how to cope with the crop raiding.
630
00:42:15,799 --> 00:42:18,868
This is really cutting-edge stuff.
631
00:42:21,672 --> 00:42:25,909
NARRATOR: Geofencing is still
in the testing phase,
632
00:42:25,943 --> 00:42:30,013
but Douglas-Hamilton
believes this is the future.
633
00:42:32,349 --> 00:42:35,318
But there is a terrible setback.
634
00:42:37,755 --> 00:42:43,993
A torrential storm causes the banks
of the Ewaso Ng'iro River to crest,
635
00:42:44,028 --> 00:42:47,664
creating the worst flood in memory.
636
00:42:50,200 --> 00:42:55,004
Save the Elephants' research center
is all but gone.
637
00:42:58,342 --> 00:43:02,378
Most of the buildings and much
of the decade's long research
638
00:43:02,413 --> 00:43:04,280
are missing.
639
00:43:06,517 --> 00:43:09,385
DOUGLAS-HAMlLTON: Well, this flood
has had a terrible effect on our work.
640
00:43:09,420 --> 00:43:10,520
First of all, it's caused
641
00:43:10,554 --> 00:43:13,489
hundreds of thousands of dollars
worth of damage.
642
00:43:13,524 --> 00:43:16,492
l don't know how we're gonna
get the money to rebuild,
643
00:43:16,527 --> 00:43:21,531
but we've also lost some data,
which is particularly precious to us.
644
00:43:26,870 --> 00:43:29,305
NARRATOR: But Douglas-Hamilton
and his team are determined
645
00:43:29,340 --> 00:43:33,009
to dig themselves out
and start over again.
646
00:43:33,043 --> 00:43:34,944
DOUGLAS-HAMlLTON:
We've got to carry on.
647
00:43:34,979 --> 00:43:38,247
Our mission is to secure
a future for elephants.
648
00:43:38,282 --> 00:43:41,284
l've been working
on elephants for 43 years,
649
00:43:41,318 --> 00:43:43,720
and it's all to save
the elephants.
650
00:43:43,754 --> 00:43:45,922
So we're not going
to give up on that.
651
00:43:50,027 --> 00:43:54,197
NARRATOR:
As Save the Elephants recovers,
652
00:43:54,231 --> 00:43:57,567
the Mali elephants
survive the drought.
653
00:44:00,270 --> 00:44:04,841
And Douglas-Hamilton with his team
will continue tracking elephants,
654
00:44:04,875 --> 00:44:08,978
working to preserve
their ancient paths.
655
00:44:12,282 --> 00:44:14,717
DOUGLAS-HAMlLTON: l think
the worst-case scenario
656
00:44:14,752 --> 00:44:17,086
would be a cutting
of the migration routes,
657
00:44:17,121 --> 00:44:20,690
completely cut off
from their water supplies.
658
00:44:20,724 --> 00:44:23,426
lt would then only be
a matter of time
659
00:44:23,460 --> 00:44:27,330
before the elephants
had nothing to live with.
660
00:44:27,364 --> 00:44:29,832
That would be my
worst-case scenario for Mali.
661
00:44:29,867 --> 00:44:33,369
But it's not going to happen.
We've got to prevent it.
662
00:44:36,674 --> 00:44:40,376
NARRATOR: Working in the natural world
is always a gamble.
663
00:44:40,411 --> 00:44:45,048
Science needs data,
and if nature doesn't cooperate,
664
00:44:45,082 --> 00:44:50,953
data will get destroyed, eaten
or swept out to sea.
665
00:44:54,758 --> 00:45:01,831
ln Patagonia, the scientists return,
hoping their gamble pays off.
666
00:45:01,865 --> 00:45:07,103
The elephant seals have returned
to molt after two months at sea.
667
00:45:09,807 --> 00:45:14,544
With good fortune,
the five Daily Diaries will return, too.
668
00:45:16,213 --> 00:45:19,148
Flavio Quintana's team use GPS
669
00:45:19,183 --> 00:45:22,852
to find out when
the tagged seals arrive...
670
00:45:24,321 --> 00:45:26,956
and where they settle
on the beach.
671
00:45:28,525 --> 00:45:30,026
Over the course of a week,
672
00:45:30,060 --> 00:45:33,763
the team retrieves
four out of the five tags.
673
00:45:35,199 --> 00:45:39,469
Each Daily Diary
is perfectly intact.
674
00:45:43,907 --> 00:45:49,412
7,300 miles away, Rory Wilson
at his lab in Swansea, Wales,
675
00:45:49,446 --> 00:45:52,749
begins to read
the much anticipated story‒
676
00:45:52,783 --> 00:45:56,519
the secrets of the seal migration.
677
00:45:56,553 --> 00:45:59,922
WlLSON: You know, you're opening
the book on it for the first time,
678
00:45:59,957 --> 00:46:01,557
it's an incredible thrill.
679
00:46:01,592 --> 00:46:05,294
Stuff happens that you wouldn't
believe in your wildest dreams.
680
00:46:06,497 --> 00:46:11,834
NARRATOR: First, Wilson reconstructs
the movement of the seal named Mir.
681
00:46:11,869 --> 00:46:13,269
WlLSON: This is the moment
682
00:46:13,303 --> 00:46:17,974
where Mir comes off
the continental shelf, the platform
683
00:46:18,008 --> 00:46:19,809
and goes down
into the deep water,
684
00:46:19,843 --> 00:46:21,811
and you can actually see this
in her depth traces...
685
00:46:21,845 --> 00:46:25,448
and they get deeper and deeper.
686
00:46:25,482 --> 00:46:29,218
NARRATOR: Mir's deepest dive
was nearly half a mile,
687
00:46:29,253 --> 00:46:32,955
an acrobatic feeding frenzy.
688
00:46:32,990 --> 00:46:34,657
WlLSON: The animal was in free fall,
689
00:46:34,691 --> 00:46:39,128
the body was in all these
extraordinary ballet-like postures.
690
00:46:39,163 --> 00:46:42,098
And you think, whoa, l never
thought elephant seals did that!
691
00:46:42,132 --> 00:46:44,867
NARRATOR: Then Wilson looks
at how the seal swam
692
00:46:44,902 --> 00:46:47,904
as it traveled great distances.
693
00:46:47,938 --> 00:46:51,541
He compares its sway—
side-to-side movement...
694
00:46:51,575 --> 00:46:54,811
WlLSON: So these are the tail beats,
and the glide,
695
00:46:54,845 --> 00:46:56,512
and the tail beat
and the glide...
696
00:46:56,547 --> 00:47:00,249
NARRATOR: ...to the surge‒
vertical and horizontal position.
697
00:47:00,284 --> 00:47:03,586
WlLSON: And as the tail beats occur,
the animal's pointing up,
698
00:47:03,620 --> 00:47:05,955
and when she glides,
she points down.
699
00:47:05,989 --> 00:47:08,891
So up and down.
700
00:47:08,926 --> 00:47:10,426
NARRATOR:
Then calculates pressure
701
00:47:10,460 --> 00:47:13,629
to determine the depth
and length of her dips.
702
00:47:13,664 --> 00:47:16,599
WlLSON: And the interesting thing
is she's doing exactly the same thing
703
00:47:16,633 --> 00:47:21,003
as sparrows do when they fly
or some of these small birds.
704
00:47:21,038 --> 00:47:26,175
NARRATOR: To his surprise,
elephant seals are behaving like birds:
705
00:47:26,210 --> 00:47:28,377
they fly underwater.
706
00:47:28,412 --> 00:47:31,714
This is how they
conserve energy.
707
00:47:33,817 --> 00:47:39,689
Small birds flap their wings
to gain momentum when flying up,
708
00:47:39,723 --> 00:47:43,526
and hitch a ride
on the current going down.
709
00:47:48,332 --> 00:47:50,499
WlLSON: You see small birds
flap, flap, flap, flap and glide down,
710
00:47:50,534 --> 00:47:51,567
flap, flap, flap and glide down,
711
00:47:51,602 --> 00:47:55,137
and that's a way of saving energy.
712
00:47:55,172 --> 00:47:58,774
An animal as big
as an elephant seal does it,
713
00:47:58,809 --> 00:48:02,845
and an animal as small
as a sparrow does it as well.
714
00:48:05,582 --> 00:48:09,085
NARRATOR: Both the small bird
and the enormous elephant seal
715
00:48:09,119 --> 00:48:13,856
evolved to conserve energy
in similar ways.
716
00:48:13,891 --> 00:48:17,059
WlLSON: Energy is critical for animals,
for their survival...
717
00:48:17,094 --> 00:48:19,562
but they spend it in going out
to get stuff to feed.
718
00:48:19,596 --> 00:48:23,933
So this balance of energy expenditure
against energy gain
719
00:48:23,967 --> 00:48:25,534
on migrations or off them
720
00:48:25,569 --> 00:48:27,503
is something that's
really critical to animals.
721
00:48:27,537 --> 00:48:30,673
And as we go gleefully
through the planet
722
00:48:30,707 --> 00:48:32,275
and change everything,
723
00:48:32,309 --> 00:48:35,678
we really need to be
considering that.
724
00:48:37,314 --> 00:48:41,150
NARRATOR: For the first time,
we are able to witness the elephant seal
725
00:48:41,184 --> 00:48:43,953
as it journeys through the ocean.
726
00:48:46,089 --> 00:48:47,423
WlLSON: Lovely data, aren't they?
727
00:48:47,457 --> 00:48:50,793
Really beautiful, beautiful stuff
that comes out of this tag.
728
00:48:52,863 --> 00:48:55,064
NARRATOR: With inventions
like the Daily Diary,
729
00:48:55,098 --> 00:48:59,035
the invisible is becoming visible.
730
00:48:59,069 --> 00:49:00,436
lt is in these details
731
00:49:00,470 --> 00:49:04,407
where the true secrets
of the elephant seal reside...
732
00:49:06,643 --> 00:49:08,978
revealing how this great wanderer
733
00:49:09,012 --> 00:49:13,416
can survive its long trek
through the southern seas.
734
00:49:16,486 --> 00:49:19,388
Wilson and his colleagues
won't stop here.
735
00:49:19,423 --> 00:49:21,357
They will continue to test.
736
00:49:21,391 --> 00:49:22,892
WlKELSKl: Wow, it's really taking off.
737
00:49:22,926 --> 00:49:24,260
TAYLOR: lt's really catching the wind.
738
00:49:24,294 --> 00:49:25,328
NARRATOR: lnvent...
739
00:49:25,362 --> 00:49:28,864
DOUGLAS-HAMlLTON:
We get an alarm to be set off.
740
00:49:28,899 --> 00:49:32,001
NARRATOR: ...break new ground.
741
00:49:32,035 --> 00:49:37,373
And with each technological advance,
the science of the great migrations
742
00:49:37,407 --> 00:49:41,844
gives us a larger understanding
of our world.
743
00:49:43,413 --> 00:49:47,083
WlLSON: lt's a little bit frustrating
that the Daily Diary is still as big as it is.
744
00:49:47,117 --> 00:49:49,952
l still want it to be smaller,
l want it on swifts,
745
00:49:49,987 --> 00:49:51,487
but there's no limit to that.
746
00:49:51,521 --> 00:49:54,123
When are you going to stop?
Ants, you know?
61686
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