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Big or small,
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00:00:10,733 --> 00:00:14,466
cats have conquered
the planet.
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00:00:14,500 --> 00:00:16,600
But as adaptable as they are,
4
00:00:16,633 --> 00:00:21,233
we're encroaching
on their space.
5
00:00:21,266 --> 00:00:25,700
Around the world cat numbers
are decreasing.
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00:00:25,733 --> 00:00:29,766
If we get complacent
we could see tigers go extinct.
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00:00:32,500 --> 00:00:36,500
I couldn't imagine a world
without tigers.
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00:00:39,733 --> 00:00:42,566
It's a critical time
for new research
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00:00:42,600 --> 00:00:45,000
and cat conservation.
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00:00:45,033 --> 00:00:46,766
Holy mackerel.
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00:00:46,800 --> 00:00:48,766
He's a loose cannon.
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00:00:48,800 --> 00:00:52,533
But there are
success stories to be told.
13
00:01:01,300 --> 00:01:04,800
This is an age of
discovery that's revolutionizing
14
00:01:04,833 --> 00:01:08,833
how we view
this amazing, super family.
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00:01:34,133 --> 00:01:37,500
Cheetahs are
the world's fastest land animal.
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00:01:44,766 --> 00:01:49,166
It's said they can accelerate
faster than a Ferrari.
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00:02:01,300 --> 00:02:05,966
But no one knows for sure
what they're really capable of.
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00:02:11,633 --> 00:02:15,266
Professor Alan Wilson has spent
the last five years
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00:02:15,300 --> 00:02:17,500
trying to find out.
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00:02:20,966 --> 00:02:22,333
Cheetahs are amazing,
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00:02:22,366 --> 00:02:24,733
they're so much faster
than anything else.
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00:02:24,766 --> 00:02:26,533
We've got an animal
that has got four times
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00:02:26,566 --> 00:02:28,466
the acceleration of Usain Bolt
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00:02:28,500 --> 00:02:30,266
and more than twice
the top speed,
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00:02:30,300 --> 00:02:32,833
how can they not
be fascinating to study.
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00:02:35,033 --> 00:02:37,733
Alan wants to find
the cheetah's top speed
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00:02:37,766 --> 00:02:40,166
when it really counts...
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00:02:40,200 --> 00:02:44,166
during a hunt.
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00:02:44,200 --> 00:02:48,533
He's developed high tech collars
to record the cheetah's speed,
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00:02:48,566 --> 00:02:52,033
position, and G force
while they're hunting.
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00:02:56,433 --> 00:02:59,433
The cheetahs soon disappear.
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00:02:59,466 --> 00:03:02,933
They cover hundreds of miles
in search of their prey.
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00:03:02,966 --> 00:03:05,400
That makes getting
any information back
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00:03:05,433 --> 00:03:08,166
from the collars
a real challenge.
35
00:03:10,233 --> 00:03:12,600
Alan's solution?
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00:03:12,633 --> 00:03:15,100
He's built his own plane --
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00:03:15,133 --> 00:03:17,933
from scratch,
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00:03:17,966 --> 00:03:20,400
learned how to fly it,
39
00:03:20,433 --> 00:03:24,066
and then filled it to the brim
with the latest technology.
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00:03:26,600 --> 00:03:28,666
We have a tracking
antenna on the wing.
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00:03:28,700 --> 00:03:30,833
We have a three-dimensional
laser scanner.
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00:03:30,866 --> 00:03:33,033
We have a video camera
on a gimbal.
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00:03:33,066 --> 00:03:35,266
That's a missile
guidance system.
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00:03:39,066 --> 00:03:42,066
Okay, let's go find
some cheetah.
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00:04:03,333 --> 00:04:05,966
Coming into the air is just
such a revolution
46
00:04:06,000 --> 00:04:08,166
for wildlife research.
47
00:04:14,833 --> 00:04:17,000
Okay, cheetahs on
the left wingtip.
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00:04:22,000 --> 00:04:24,200
The cheetahs' collars
record details
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00:04:24,233 --> 00:04:28,033
of their movements
300 times a second.
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00:04:32,066 --> 00:04:34,233
As the plane flies over,
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00:04:34,266 --> 00:04:39,800
it locks on to each collar
and downloads the data.
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00:04:39,833 --> 00:04:43,733
There we go, we're
downloading collar 7-5-0.
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00:04:43,766 --> 00:04:48,866
Each of those files
represents one hunt.
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00:04:48,900 --> 00:04:51,900
After recording
more than 500 hunts,
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00:04:51,933 --> 00:04:55,933
Alan clocked a cheetah's top
speed of 58 miles an hour.
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00:05:01,466 --> 00:05:03,200
Impressive.
57
00:05:03,233 --> 00:05:07,300
But what surprised him was that
most hunts were much slower,
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00:05:07,333 --> 00:05:11,933
only half their
potential top speed.
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00:05:11,966 --> 00:05:14,500
It turns out,
for a cheetah,
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00:05:14,533 --> 00:05:17,066
hunting is not all about
the sprint.
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00:05:26,066 --> 00:05:29,866
So, what are they relying on
to catch their dinner?
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00:05:36,766 --> 00:05:40,900
To investigate, Alan has
enlisted three volunteers...
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00:05:46,233 --> 00:05:48,400
And a rag on a string.
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00:05:51,300 --> 00:05:55,500
These hand-reared cheetahs love
chasing a moving lure...
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00:05:57,766 --> 00:06:01,333
Replicating how cheetahs behave
when hunting.
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00:06:09,000 --> 00:06:12,100
Prey animals don't run in
a straight line for long.
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00:06:14,600 --> 00:06:17,666
To follow their prey,
cheetahs must also weave
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00:06:17,700 --> 00:06:19,900
and change direction.
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00:06:22,066 --> 00:06:27,066
This maneuvering inevitably
slows them down,
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00:06:27,100 --> 00:06:30,033
but it's also where
their real strength lies.
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00:06:39,100 --> 00:06:41,166
The accelerations
and decelerations,
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00:06:41,200 --> 00:06:44,666
the G forces they're pulling
in the turns are very high.
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00:06:47,200 --> 00:06:49,500
The force going
through their legs
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00:06:49,533 --> 00:06:53,633
would be enough
to break a human leg bone.
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00:06:58,900 --> 00:07:00,233
The lure's just taken
the corner
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00:07:00,266 --> 00:07:01,400
and the cheetah's banking
77
00:07:01,433 --> 00:07:03,000
and see how it's using
its tail here,
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00:07:03,033 --> 00:07:05,400
which is helping control
the roll of its body
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00:07:05,433 --> 00:07:08,700
and helping stabilize it
and it slowed down to turn
80
00:07:08,733 --> 00:07:12,166
then it's accelerating again
out of shot towards the lure.
81
00:07:15,466 --> 00:07:17,200
Rather than speed,
82
00:07:17,233 --> 00:07:21,833
the key to
the cheetahs' hunting success
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00:07:21,866 --> 00:07:23,766
is their agility.
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00:07:28,733 --> 00:07:30,333
We started believing
that cheetahs
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00:07:30,366 --> 00:07:31,500
are the elite sprinter
86
00:07:31,533 --> 00:07:33,800
and that was
their main attribute.
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00:07:33,833 --> 00:07:36,133
What we've seen
is that they're gymnasts,
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00:07:36,166 --> 00:07:38,166
they can accelerate,
they can maneuver,
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00:07:38,200 --> 00:07:40,766
they can turn, and that is what
they're good at,
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00:07:40,800 --> 00:07:46,333
almost the speed is a by-product
of all that athleticism.
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00:07:46,366 --> 00:07:49,400
So they are remarkable athletes,
but we shouldn't think of them
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00:07:49,433 --> 00:07:51,600
as just a speed merchant,
there's much more
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00:07:51,633 --> 00:07:53,666
to their repertoire than that.
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00:07:59,966 --> 00:08:03,266
Even with
the most familiar cats
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00:08:03,300 --> 00:08:06,233
there's still so much
to discover.
96
00:08:25,166 --> 00:08:28,400
Lions.
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00:08:28,433 --> 00:08:31,000
Supreme hunters.
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00:08:31,033 --> 00:08:33,233
The strongest cat.
99
00:08:35,299 --> 00:08:38,666
Could they also be
the smartest big cat?
100
00:08:44,400 --> 00:08:48,400
Dr. Natalia Borrego
certainly thinks so,
101
00:08:48,433 --> 00:08:50,266
and is on a mission
to prove it...
102
00:08:52,966 --> 00:08:55,666
Though it's not
the easiest thing to test
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00:08:55,700 --> 00:08:59,133
in any cat,
let alone a lion.
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00:08:59,166 --> 00:09:01,166
Her theory is based on the fact
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00:09:01,200 --> 00:09:05,133
that lions
live together in prides.
106
00:09:10,033 --> 00:09:11,600
So cats are
all solitary
107
00:09:11,633 --> 00:09:15,200
and effectively live
on their own, except for lions,
108
00:09:15,233 --> 00:09:17,133
they live in prides
and are very social
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00:09:17,166 --> 00:09:19,566
and when we think of other
social species --
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00:09:19,600 --> 00:09:21,833
elephants, dolphins,
spotted hyenas,
111
00:09:21,866 --> 00:09:24,866
chimpanzees -- they're all
very intelligent.
112
00:09:24,900 --> 00:09:29,500
So in theory lions should be
the smartest of the cats.
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00:09:29,533 --> 00:09:32,766
The idea that social
animals are more intelligent
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00:09:32,800 --> 00:09:34,300
is well established,
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00:09:34,333 --> 00:09:37,166
but has never been
proved for lions.
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00:09:45,266 --> 00:09:48,533
Cats are notoriously
uncooperative.
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00:09:48,566 --> 00:09:52,233
What possible IQ test
could you give a lion?
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00:09:54,400 --> 00:09:57,233
Natalia's traveled to
South Africa for the chance
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00:09:57,266 --> 00:10:00,433
to test a slightly
unusual pride.
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00:10:25,300 --> 00:10:28,366
Kevin Richardson has
an unconventional approach
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00:10:28,400 --> 00:10:30,566
to working with lions.
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00:10:34,800 --> 00:10:37,566
For 10 years he's lived
alongside
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00:10:37,600 --> 00:10:39,500
these rescued animals,
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00:10:39,533 --> 00:10:42,366
becoming part of the pride.
125
00:10:51,866 --> 00:10:55,666
Kevin can act as a go-between
to the lions,
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00:10:55,700 --> 00:10:58,166
giving Natalia
a unique opportunity
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00:10:58,200 --> 00:11:00,466
to run her experiments.
128
00:11:02,933 --> 00:11:05,866
So, here looks good.
129
00:11:05,900 --> 00:11:09,433
Natalia has designed
a puzzle for the cats to solve.
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00:11:09,466 --> 00:11:10,866
Mind your fingers.
Yeah.
131
00:11:10,900 --> 00:11:13,966
The lion must work out
how to open a door,
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00:11:14,000 --> 00:11:17,566
then reach her head inside
to get to a reward.
133
00:11:17,600 --> 00:11:19,033
Good.
134
00:11:19,066 --> 00:11:21,200
There's nothing like
this in nature,
135
00:11:21,233 --> 00:11:26,000
so to Ginny the lion,
it's a Rubik's cube.
136
00:11:26,033 --> 00:11:28,266
And if the lions
come, you just pop it down.
137
00:11:28,300 --> 00:11:30,366
I just pop it
back down.
138
00:11:30,400 --> 00:11:31,733
Ginny.
139
00:11:31,766 --> 00:11:35,233
Here.
Look here.
140
00:11:35,266 --> 00:11:38,433
First, she must figure
out how to pull the door
141
00:11:38,466 --> 00:11:40,233
with her paw.
142
00:11:44,633 --> 00:11:46,833
Clever!
143
00:11:49,833 --> 00:11:51,700
Aw, you're so clever.
144
00:11:51,733 --> 00:11:54,333
You are so clever my sweetie,
oh, but it slams, eh?
145
00:11:54,366 --> 00:11:55,866
What did it do?
146
00:11:55,900 --> 00:11:58,766
I think she's more interested
in the box now than the food.
147
00:11:58,800 --> 00:12:00,366
Here. Here.
148
00:12:00,400 --> 00:12:03,566
Next she needs
to learn to stand back
149
00:12:03,600 --> 00:12:05,433
and allow
the door to swing open.
150
00:12:05,466 --> 00:12:06,800
Get your head
out the way.
151
00:12:06,833 --> 00:12:09,166
Get your head out the way.
There we go.
152
00:12:09,200 --> 00:12:12,533
Before, finally,
she can reach her head inside.
153
00:12:12,566 --> 00:12:14,833
That's not bad.
No that's good.
154
00:12:17,166 --> 00:12:18,366
Clever.
One more time?
155
00:12:18,400 --> 00:12:19,600
Yeah.
Two more times?
156
00:12:19,633 --> 00:12:21,000
I think a couple
more times.
157
00:12:21,033 --> 00:12:23,333
Couple more times.
158
00:12:23,366 --> 00:12:24,933
There, see, she got it.
159
00:12:24,966 --> 00:12:28,033
It's taken Ginny
20 minutes to figure it out.
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00:12:28,066 --> 00:12:29,833
But now she's cracked it.
There we go.
161
00:12:29,866 --> 00:12:31,866
Yeah, she's getting her
head out of the way now.
162
00:12:31,900 --> 00:12:33,466
There we go.
One more time.
163
00:12:33,500 --> 00:12:36,300
Okay, okay, cool.
Yeah, there you go.
164
00:12:36,333 --> 00:12:37,333
Easy now
she's got it.
165
00:12:37,366 --> 00:12:38,600
Well done.
166
00:12:38,633 --> 00:12:40,000
That deserves
a round of applause.
167
00:12:42,866 --> 00:12:46,233
Next comes
the crucial part of the test.
168
00:12:46,266 --> 00:12:49,033
Kevin has brought the lions
into an enclosure
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00:12:49,066 --> 00:12:53,466
to allow pride mate, Libby,
to watch Ginny's efforts.
170
00:12:56,466 --> 00:12:58,833
The ability to learn by
watching others
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00:12:58,866 --> 00:13:02,100
is considered a real sign
of intelligence.
172
00:13:02,133 --> 00:13:04,000
It would put lions
in the company
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00:13:04,033 --> 00:13:06,766
of the brightest minds
in the natural world.
174
00:13:06,800 --> 00:13:09,233
Good.
Yeah you slam that door.
175
00:13:09,266 --> 00:13:11,433
That's it, stay open.
Good girl.
176
00:13:11,466 --> 00:13:12,966
No there she goes.
177
00:13:13,000 --> 00:13:15,800
She can see
what she's doing. Yeah.
178
00:13:15,833 --> 00:13:18,100
Yeah, I think she's got
it
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00:13:18,133 --> 00:13:19,400
and it's time
to let Libby out.
180
00:13:19,433 --> 00:13:22,066
If lions can learn
from each other,
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00:13:22,100 --> 00:13:25,900
Libby should solve
the puzzle in seconds.
182
00:13:25,933 --> 00:13:27,433
If not...
See what she does
183
00:13:27,466 --> 00:13:29,566
It's going to
take her another 20 minutes.
184
00:13:29,600 --> 00:13:31,800
Now she goes
to the right side.
185
00:13:38,633 --> 00:13:40,633
There, I think,
I don't think you can get
186
00:13:40,666 --> 00:13:42,600
any clearer than that,
that was amazing.
187
00:13:42,633 --> 00:13:44,733
Yeah, here we go
my girl, here here, here here.
188
00:13:44,766 --> 00:13:47,166
Good job, Libby.
189
00:13:47,200 --> 00:13:50,166
It's the very first
time anyone has shown
190
00:13:50,200 --> 00:13:54,433
that lions learn
from each other.
191
00:13:54,466 --> 00:13:58,333
She knows
that that's the one.
192
00:13:58,366 --> 00:14:02,366
Natalia has tested
leopards and tigers --
193
00:14:02,400 --> 00:14:04,800
lions outperform them both.
194
00:14:07,000 --> 00:14:08,800
It looks like Natalia
is right...
195
00:14:08,833 --> 00:14:10,400
Now she doesn't
even bother.
196
00:14:10,433 --> 00:14:13,433
Lions are
the smartest big cat.
197
00:14:13,466 --> 00:14:15,033
So the experiments
went really well,
198
00:14:15,066 --> 00:14:18,166
much better than expected,
and it really did show
199
00:14:18,200 --> 00:14:21,133
that lions can learn
socially from each other.
200
00:14:25,266 --> 00:14:26,733
Their intelligence
201
00:14:26,766 --> 00:14:28,700
and ability to learn from
each other
202
00:14:28,733 --> 00:14:31,866
allows lions to hunt
like no other cat.
203
00:15:05,066 --> 00:15:08,100
No cat is easy to study,
204
00:15:08,133 --> 00:15:12,333
though at least lions
are relatively easy to find.
205
00:15:18,600 --> 00:15:23,000
But most cats are so elusive...
206
00:15:23,033 --> 00:15:27,766
secretive...
207
00:15:27,800 --> 00:15:32,500
and well camouflaged...
208
00:15:32,533 --> 00:15:36,000
that they're rarely seen,
let alone studied.
209
00:15:38,100 --> 00:15:41,066
Learning more about these cats
takes people
210
00:15:41,100 --> 00:15:44,300
whose dedication
knows no bounds.
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00:15:51,300 --> 00:15:53,900
Someone like
Dr. Andrew Hearn.
212
00:16:00,900 --> 00:16:03,200
Deep in the forests of Borneo,
213
00:16:03,233 --> 00:16:06,800
a chance encounter set him off
on his life's mission.
214
00:16:10,400 --> 00:16:12,300
I was part of
an expedition team
215
00:16:12,333 --> 00:16:15,933
to an uncharted area
of Indonesian Borneo.
216
00:16:15,966 --> 00:16:18,600
One morning I went along a trail
just to go
217
00:16:18,633 --> 00:16:20,000
and sit down and relax
218
00:16:20,033 --> 00:16:22,233
and see what wildlife
I could see.
219
00:16:24,633 --> 00:16:28,500
And I was sat there quietly,
and a small little red cat
220
00:16:28,533 --> 00:16:30,766
walked out of the side
of the forest,
221
00:16:30,800 --> 00:16:32,033
walked across the trail,
222
00:16:32,066 --> 00:16:35,266
paused about 20 meters
in front of me.
223
00:16:35,300 --> 00:16:38,066
I grabbed my notebook,
started to sketch it,
224
00:16:38,100 --> 00:16:39,600
but I had no idea
what it was.
225
00:16:39,633 --> 00:16:42,366
It was only when I returned back
to the camp later that day,
226
00:16:42,400 --> 00:16:44,166
spoke to some of
the Indonesian staff and said,
227
00:16:44,200 --> 00:16:45,866
"Do you know this --
do you know this cat?"
228
00:16:45,900 --> 00:16:48,466
So it was only then that I
learned that this was this, um,
229
00:16:48,500 --> 00:16:52,300
the Borneo Bay cat,
and it quickly became apparent
230
00:16:52,333 --> 00:16:56,600
that nothing was known
about this animal.
231
00:16:56,633 --> 00:17:00,533
The bay cat is one of
the world's least known cats...
232
00:17:03,733 --> 00:17:06,766
And Andrew has devoted
every year since
233
00:17:06,800 --> 00:17:09,266
to finding out
anything about them.
234
00:17:12,766 --> 00:17:14,933
But the chance of him seeing
another one
235
00:17:14,966 --> 00:17:18,433
would be like
winning the lottery twice.
236
00:17:33,600 --> 00:17:36,700
So, how do you study
something you can't see?
237
00:17:40,933 --> 00:17:42,600
Camera traps.
238
00:17:42,633 --> 00:17:45,000
Combining a sensitive
motion sensor
239
00:17:45,033 --> 00:17:47,666
with a high resolution camera,
240
00:17:47,700 --> 00:17:50,466
Andrew and his team
deploy dozens of these
241
00:17:50,500 --> 00:17:52,700
through the forest...
242
00:17:55,733 --> 00:17:57,533
and spend months
243
00:17:57,566 --> 00:18:00,166
trekking through
the jungle checking them.
244
00:18:04,633 --> 00:18:07,900
Back at base there are
thousands of hours of footage
245
00:18:07,933 --> 00:18:10,133
to plow through.
246
00:18:14,266 --> 00:18:17,333
Most contain no cats whatsoever.
247
00:18:22,233 --> 00:18:25,733
But eventually,
Andrew struck gold.
248
00:18:31,600 --> 00:18:33,233
Almost.
249
00:18:33,266 --> 00:18:36,033
So this is the first-ever
video of the bay cat
250
00:18:36,066 --> 00:18:38,266
in the world.
251
00:18:40,300 --> 00:18:43,733
It's not the finest video,
it's not the most exciting,
252
00:18:43,766 --> 00:18:46,766
but to us
that was just spectacular.
253
00:18:46,800 --> 00:18:48,400
We were absolutely blown away
254
00:18:48,433 --> 00:18:51,700
when this thing appeared on
the camera traps in front of us.
255
00:18:51,733 --> 00:18:55,500
This is the fruit
of 12 years' labor.
256
00:18:55,533 --> 00:19:02,566
Yet to this day, only two
videos of wild bay cats exist:
257
00:19:02,600 --> 00:19:06,666
Andrew's and this one,
more recently captured.
258
00:19:12,733 --> 00:19:17,866
No wonder we know so little
about these cats,
259
00:19:17,900 --> 00:19:21,733
and now,
it's a race against time.
260
00:19:21,766 --> 00:19:24,833
Borneo has one of the highest
rates of deforestation
261
00:19:24,866 --> 00:19:28,133
in the world.
262
00:19:28,166 --> 00:19:30,700
To protect some space
for the bay cat,
263
00:19:30,733 --> 00:19:34,733
Andrew wants to find out
what kind of forest they need.
264
00:19:38,333 --> 00:19:41,133
He has managed to
capture photographs
265
00:19:41,166 --> 00:19:43,333
which help shed some light.
266
00:19:49,900 --> 00:19:52,133
In, what is it,
12 odd years
267
00:19:52,166 --> 00:19:55,466
we've only got
something like 60 photos.
268
00:19:55,500 --> 00:19:58,766
They're so rare,
they're so hard come by.
269
00:19:58,800 --> 00:20:02,733
Each photograph of the bay cat
is worth its weight in gold.
270
00:20:02,766 --> 00:20:04,900
It helps to piece together
the ecology
271
00:20:04,933 --> 00:20:07,733
and the conservation needs
of these cats.
272
00:20:09,933 --> 00:20:12,300
Much of
the deforestation in Borneo
273
00:20:12,333 --> 00:20:15,166
is to make space for palm oil.
274
00:20:15,200 --> 00:20:18,933
While some cats can make it
in these plantations,
275
00:20:18,966 --> 00:20:21,166
bay cats disappear.
276
00:20:24,100 --> 00:20:26,166
For the bay cat to survive,
277
00:20:26,200 --> 00:20:31,366
some natural forest
must be protected.
278
00:20:31,400 --> 00:20:33,333
Andrew's determined
to uncover
279
00:20:33,366 --> 00:20:37,366
whatever else he can about
the mysterious bay cat,
280
00:20:37,400 --> 00:20:40,633
even if it takes
another 12 years.
281
00:20:47,733 --> 00:20:49,933
Camera traps are revolutionizing
282
00:20:49,966 --> 00:20:53,100
our understanding
of the entire cat family.
283
00:20:55,933 --> 00:20:59,233
Deploying them in the remotest
corners of the planet
284
00:20:59,266 --> 00:21:03,166
for months at a time
is yielding unique insights
285
00:21:03,200 --> 00:21:06,266
into these very private lives.
286
00:21:15,000 --> 00:21:19,300
In China, two cats that
wouldn't normally cross paths,
287
00:21:19,333 --> 00:21:24,266
a leopard and a snow leopard,
are filmed by the same camera
288
00:21:24,300 --> 00:21:26,766
just days apart.
289
00:21:32,000 --> 00:21:37,566
In Costa Rica, a margay argues
with an angry possum.
290
00:21:50,033 --> 00:21:53,000
And in the dunes
of the Western Sahara,
291
00:21:53,033 --> 00:21:56,600
camera traps record
the first ever shots
292
00:21:56,633 --> 00:21:59,600
of wild sand cat kittens.
293
00:22:09,800 --> 00:22:13,766
One pioneering study has taken
the use of camera traps
294
00:22:13,800 --> 00:22:15,800
to another level.
295
00:22:22,466 --> 00:22:27,033
Mountain lions, also known
as cougars or pumas.
296
00:22:36,833 --> 00:22:39,800
Camera traps are now challenging
what we know
297
00:22:39,833 --> 00:22:42,000
about this American icon.
298
00:22:48,333 --> 00:22:50,900
She's here.
299
00:22:50,933 --> 00:22:54,766
It all started
with Dr. Mark Elbroch's passion
300
00:22:54,800 --> 00:22:58,133
for these charismatic cats.
301
00:22:58,166 --> 00:23:00,433
Here she is,
running across.
302
00:23:00,466 --> 00:23:02,666
Look at the size
of the footprint.
303
00:23:06,000 --> 00:23:07,733
I live mountain lions.
304
00:23:07,766 --> 00:23:12,400
I track them, I watch videos
of them, I go to sleep at night
305
00:23:12,433 --> 00:23:15,166
and I dream
about mountain lions.
306
00:23:15,200 --> 00:23:17,700
This guy's a,
he's a loose cannon.
307
00:23:17,733 --> 00:23:20,533
This is the part where
you try not to get bit.
308
00:23:23,733 --> 00:23:25,366
In the Teton Mountains
309
00:23:25,400 --> 00:23:27,166
of Wyoming, Mark and his team
310
00:23:27,200 --> 00:23:29,300
want to learn more
about mountain lion
311
00:23:29,333 --> 00:23:32,466
hunting and feeding behavior.
312
00:23:32,500 --> 00:23:35,766
Using GPS collars to track
the animals,
313
00:23:35,800 --> 00:23:37,933
they identify cat hotspots.
314
00:23:37,966 --> 00:23:39,300
...quite a bit,
which is good.
315
00:23:39,333 --> 00:23:41,766
No, so we should get in there
and set some cameras
316
00:23:41,800 --> 00:23:44,000
-Sounds good.
317
00:24:04,100 --> 00:24:05,966
Mark expected
an insight
318
00:24:06,000 --> 00:24:09,233
into the solitary life
of lone cats...
319
00:24:14,966 --> 00:24:17,133
But the more he watched,
320
00:24:17,166 --> 00:24:21,000
the more he began to realize
something else was going on.
321
00:24:25,733 --> 00:24:31,066
Here comes the nine
year old resident female,
322
00:24:31,100 --> 00:24:32,833
and she comes round
and she turns
323
00:24:32,866 --> 00:24:36,433
and here comes
a six year old female.
324
00:24:36,466 --> 00:24:39,600
She's doing mild hissing and in
the beginning we thought,
325
00:24:39,633 --> 00:24:41,000
gosh, all that hissing,
326
00:24:41,033 --> 00:24:43,266
it's the pre-runner to violence,
327
00:24:43,300 --> 00:24:46,000
it's super aggressive.
328
00:24:46,033 --> 00:24:48,233
No, hissing seems
pretty normal
329
00:24:48,266 --> 00:24:51,566
now that we've seen it over
and over and over again.
330
00:24:51,600 --> 00:24:53,133
So what happened next?
331
00:24:53,166 --> 00:24:56,700
They spent two days together
and this is what they did.
332
00:24:58,700 --> 00:25:01,266
They shared a meal.
333
00:25:01,300 --> 00:25:03,500
It blew me away.
334
00:25:06,233 --> 00:25:09,633
That wasn't his only
surprising discovery.
335
00:25:16,033 --> 00:25:17,700
It's thought that males
336
00:25:17,733 --> 00:25:20,666
are normally aggressive
towards females,
337
00:25:20,700 --> 00:25:23,333
even capable of killing them.
338
00:25:23,366 --> 00:25:26,700
But the cameras show
that's not true either.
339
00:25:31,000 --> 00:25:33,400
Every time we've seen
a male approach
340
00:25:33,433 --> 00:25:36,066
a female outside courtship
341
00:25:36,100 --> 00:25:39,300
this is exactly what they do,
they slink in.
342
00:25:39,333 --> 00:25:42,733
Notice how low he's holding
his body to the ground,
343
00:25:42,766 --> 00:25:46,233
his ears are to the side
and almost sagging,
344
00:25:46,266 --> 00:25:49,600
they minimize their profile,
they try to look smaller,
345
00:25:49,633 --> 00:25:52,133
it is completely
non-aggressive,
346
00:25:52,166 --> 00:25:54,666
he clearly just wants
to share a meal.
347
00:25:54,700 --> 00:25:57,933
And you can see as he comes
in there's no hissing,
348
00:25:57,966 --> 00:25:59,833
there's nothing,
she just watches.
349
00:25:59,866 --> 00:26:03,000
And it's the kitten
that does all the hissing.
350
00:26:05,100 --> 00:26:06,766
There they are,
351
00:26:06,800 --> 00:26:11,100
massive resident adult male
feeding on the carcass,
352
00:26:11,133 --> 00:26:14,933
three month old kitten
and mother
353
00:26:14,966 --> 00:26:16,733
falling asleep
in the background.
354
00:26:20,233 --> 00:26:22,666
Rather than always
being aggressive,
355
00:26:22,700 --> 00:26:27,166
males become positively meek
when they want to share a meal.
356
00:26:30,900 --> 00:26:35,933
After analyzing 13 years of data
and thousands of videos,
357
00:26:35,966 --> 00:26:40,066
Mark has discovered these social
interactions follow a pattern.
358
00:26:42,533 --> 00:26:45,966
Mountain lions
remember each other,
359
00:26:46,000 --> 00:26:48,666
and they're much more
likely to share their dinner
360
00:26:48,700 --> 00:26:52,333
with a cat that has been
generous with them in the past.
361
00:26:55,733 --> 00:26:57,500
We're beginning
to describe a species
362
00:26:57,533 --> 00:27:01,000
that has some sort of
social system,
363
00:27:01,033 --> 00:27:03,233
that is interacting
with a frequency
364
00:27:03,266 --> 00:27:07,333
that challenges this idea
that they are solitary animals
365
00:27:07,366 --> 00:27:09,366
and it's just opening our eyes
366
00:27:09,400 --> 00:27:11,800
and completely turning
everything on its head
367
00:27:11,833 --> 00:27:15,233
on what we thought were the
social lives of mountain lions.
368
00:27:22,233 --> 00:27:25,433
Cats never fail
to surprise us.
369
00:27:36,000 --> 00:27:39,133
Covering more than
30 square miles
370
00:27:39,166 --> 00:27:42,033
and employing 20,000 people...
371
00:27:44,766 --> 00:27:49,900
Secunda CTL is the biggest
industrial complex in Africa.
372
00:27:57,166 --> 00:27:59,666
An unlikely place for a cat...
373
00:28:11,233 --> 00:28:16,400
But ecologist Daan Loock
made an amazing discovery here.
374
00:28:16,433 --> 00:28:18,533
It all started with reports of
375
00:28:18,566 --> 00:28:21,633
strange creatures
prowling the site after dark.
376
00:28:31,600 --> 00:28:34,766
I just can't make out
what it is.
377
00:28:34,800 --> 00:28:37,866
Hopefully it crosses here
but I don't think so,
378
00:28:37,900 --> 00:28:42,333
there's a lot of thickets
just to our left hand side,
379
00:28:42,366 --> 00:28:45,066
I think it will,
there it is just in front of us!
380
00:28:45,100 --> 00:28:47,100
There it is!
381
00:28:47,133 --> 00:28:49,333
Oh, that's very special.
382
00:28:51,766 --> 00:28:55,600
The strange creature
is a serval.
383
00:29:05,400 --> 00:29:06,666
There it goes.
384
00:29:06,700 --> 00:29:10,633
I'm very excited, I must say.
385
00:29:10,666 --> 00:29:13,566
Daan covered the site
in camera traps,
386
00:29:13,600 --> 00:29:18,266
and to his surprise,
there were servals everywhere.
387
00:29:18,300 --> 00:29:20,833
He worked out that
the population density
388
00:29:20,866 --> 00:29:25,300
is six times higher than in
the most pristine wilderness.
389
00:29:29,300 --> 00:29:32,400
Servals are not merely
surviving here...
390
00:29:32,433 --> 00:29:37,100
This is the densest population
known.
391
00:29:50,666 --> 00:29:53,300
Servals are found
across Africa
392
00:29:53,333 --> 00:29:56,800
and specialize in hunting
rodents and small birds.
393
00:30:01,466 --> 00:30:04,366
They have the biggest ears
of any cat,
394
00:30:04,400 --> 00:30:06,566
to help pinpoint their prey.
395
00:30:13,600 --> 00:30:17,933
And with spring-like legs,
they pounce over ten feet.
396
00:30:21,633 --> 00:30:25,133
By fitting servals
with GPS radio collars,
397
00:30:25,166 --> 00:30:29,166
Daan was able to answer
why there were so many on site.
398
00:30:48,866 --> 00:30:52,366
Most importantly,
Daan's map reveals the servals
399
00:30:52,400 --> 00:30:55,633
are concentrated
in particular areas --
400
00:30:55,666 --> 00:30:57,866
around water.
401
00:31:00,700 --> 00:31:04,700
Ponds and streams used to cool
the heavy industry
402
00:31:04,733 --> 00:31:07,566
create the perfect habitat
for rodents...
403
00:31:10,700 --> 00:31:13,233
abundant food for the servals.
404
00:31:18,433 --> 00:31:20,766
With no other big predators,
405
00:31:20,800 --> 00:31:22,866
there's no competition.
406
00:31:22,900 --> 00:31:26,533
Servals have become
the apex predators...
407
00:31:26,566 --> 00:31:28,766
and run riot.
408
00:31:32,200 --> 00:31:35,933
Now, this site has the highest
concentration of servals
409
00:31:35,966 --> 00:31:38,166
anywhere in the world.
410
00:31:40,866 --> 00:31:42,666
All across the planet,
411
00:31:42,700 --> 00:31:45,600
cats are adapting to
urban habitats.
412
00:31:52,166 --> 00:31:55,133
In response,
people often need to learn
413
00:31:55,166 --> 00:31:57,666
how to live alongside cats.
414
00:32:04,500 --> 00:32:06,700
Mumbai, India.
415
00:32:09,566 --> 00:32:11,766
One of the world's
largest cities,
416
00:32:11,800 --> 00:32:14,700
home to over 20 million people.
417
00:32:31,033 --> 00:32:34,133
Mumbai is also home
to the world's
418
00:32:34,166 --> 00:32:38,866
highest known
density of leopards.
419
00:32:38,900 --> 00:32:41,666
In the dead of night,
they creep into the city
420
00:32:41,700 --> 00:32:43,866
from the surrounding forests.
421
00:32:51,000 --> 00:32:53,933
Krishna Tiwari grew up
in Mumbai.
422
00:33:00,200 --> 00:33:02,100
He's now dedicated his life
423
00:33:02,133 --> 00:33:04,500
to studying the city's
urban leopards.
424
00:33:07,433 --> 00:33:09,733
He saw a leopard
the day before yesterday
425
00:33:09,766 --> 00:33:13,300
and when the leopard saw him
he just ran away
426
00:33:13,333 --> 00:33:15,500
to the other side of the wall.
427
00:33:19,633 --> 00:33:23,000
The story is the same
all across the city.
428
00:33:26,133 --> 00:33:29,466
People encounter
leopards on a regular basis.
429
00:33:31,900 --> 00:33:34,233
She came out
at around 8:30
430
00:33:34,266 --> 00:33:36,533
to wash clothes here
and when she put up a torch
431
00:33:36,566 --> 00:33:38,500
she saw a leopard
sitting on the rocks
432
00:33:38,533 --> 00:33:39,800
and as soon as, you know,
433
00:33:39,833 --> 00:33:42,200
there was light on the leopard
he just got up,
434
00:33:42,233 --> 00:33:44,166
and she was so afraid
that you know she came back
435
00:33:44,200 --> 00:33:47,066
to the house
and called her husband.
436
00:33:47,100 --> 00:33:48,666
The outcome
of these encounters
437
00:33:48,700 --> 00:33:51,000
isn't always so peaceful...
438
00:33:54,066 --> 00:33:58,266
After all, the leopards are
coming into the city to hunt.
439
00:34:07,600 --> 00:34:11,100
Livestock are abundant
and unprotected.
440
00:34:31,366 --> 00:34:34,766
Stealth is the leopard's
most effective weapon.
441
00:34:46,400 --> 00:34:49,100
Dogs often provide
an early warning...
442
00:34:55,533 --> 00:35:00,133
But drawing attention from
a leopard isn't a good idea.
443
00:35:07,566 --> 00:35:10,166
Dogs are also on the menu.
444
00:35:36,700 --> 00:35:40,300
And sadly,
it doesn't stop there.
445
00:35:44,000 --> 00:35:48,600
In the 23 years
from 1990 to 2013,
446
00:35:48,633 --> 00:35:53,766
176 people were attacked
by leopards in Mumbai.
447
00:36:00,866 --> 00:36:04,300
But in just one month
during 2004,
448
00:36:04,333 --> 00:36:06,966
10 people were killed.
449
00:36:13,433 --> 00:36:16,900
Something had to be done.
450
00:36:16,933 --> 00:36:20,466
Krishna and the authorities
took a bold approach.
451
00:36:25,466 --> 00:36:30,166
Pioneering an education program,
Krishna wanted to teach people
452
00:36:30,200 --> 00:36:33,233
how to live safely
alongside leopards.
453
00:36:41,366 --> 00:36:45,533
Simple measures like staying
in groups at night,
454
00:36:45,566 --> 00:36:47,800
locking up livestock,
455
00:36:47,833 --> 00:36:49,833
and not running
from leopards
456
00:36:49,866 --> 00:36:52,833
has made a huge difference.
457
00:36:52,866 --> 00:36:57,700
20,000 people
have attended the meetings.
458
00:36:57,733 --> 00:37:01,300
The awareness program
has been a great success
459
00:37:01,333 --> 00:37:04,466
as the last four years
have seen no leopard attacks
460
00:37:04,500 --> 00:37:06,700
and I think it's a good
and long-term solution
461
00:37:06,733 --> 00:37:09,600
to reduce the human/leopard
conflicts in Mumbai.
462
00:37:15,000 --> 00:37:18,033
Unfortunately,
educating the local dogs
463
00:37:18,066 --> 00:37:21,966
has proven trickier.
464
00:37:22,000 --> 00:37:24,700
They provide a vital
early warning,
465
00:37:24,733 --> 00:37:26,900
but are still being taken.
466
00:37:32,566 --> 00:37:37,700
Raj has lost 3 dogs
to leopard attacks.
467
00:37:37,733 --> 00:37:39,466
He then hit on an idea
468
00:37:39,500 --> 00:37:42,300
which might help
protect his current pet.
469
00:37:53,766 --> 00:37:55,066
He thinks that the dog,
470
00:37:55,100 --> 00:37:59,266
the leopard will think
that it is also a leopard.
471
00:37:59,300 --> 00:38:01,433
Even you know it's being
protected by other dogs
472
00:38:01,466 --> 00:38:05,100
so I think it's a good idea.
473
00:38:05,133 --> 00:38:08,533
The jury's still out
on whether this even works,
474
00:38:08,566 --> 00:38:12,000
and anyway,
what self-respecting dog
475
00:38:12,033 --> 00:38:14,300
wants to be dressed up
as a cat?
476
00:38:20,166 --> 00:38:22,433
He's certainly not convinced.
477
00:38:27,266 --> 00:38:30,533
Krishna's mission to spread
tolerance is working.
478
00:38:38,333 --> 00:38:41,700
And Mumbai's leopard
population is thriving.
479
00:38:44,800 --> 00:38:48,500
It's a rare example of people
accepting their presence
480
00:38:48,533 --> 00:38:50,966
and making space for cats.
481
00:38:59,766 --> 00:39:02,933
Elsewhere, it's a very
different story.
482
00:39:06,966 --> 00:39:09,700
Nearly half of all wild cats
483
00:39:09,733 --> 00:39:13,000
are threatened
with extinction.
484
00:39:13,033 --> 00:39:17,166
As top predators they need
a lot of food and space...
485
00:39:22,666 --> 00:39:25,766
And with an ever-growing
human population,
486
00:39:25,800 --> 00:39:28,533
competition for that space
is rising.
487
00:39:33,566 --> 00:39:37,533
In the last 20 years,
leopards have been wiped out
488
00:39:37,566 --> 00:39:40,066
from 40% of their range.
489
00:39:53,733 --> 00:39:58,200
Cheetahs have become extinct
in 25 countries.
490
00:40:03,600 --> 00:40:06,200
Not even lions are spared.
491
00:40:06,233 --> 00:40:10,266
Numbers have fallen by nearly
half in two decades.
492
00:40:10,300 --> 00:40:14,033
The King of Beasts
could go extinct in the wild.
493
00:40:32,766 --> 00:40:35,566
The driving passion people
feel for cats
494
00:40:35,600 --> 00:40:38,966
is now their greatest
hope for survival.
495
00:40:41,866 --> 00:40:44,033
Holy mackerel.
496
00:40:50,666 --> 00:40:52,066
Especially
for the animal
497
00:40:52,100 --> 00:40:55,233
that's long been the face
of cat conservation.
498
00:41:08,000 --> 00:41:11,233
Dr. Krithi Karanth's love
of tigers
499
00:41:11,266 --> 00:41:15,033
started at a very young age.
500
00:41:15,066 --> 00:41:16,333
I first saw a tiger
501
00:41:16,366 --> 00:41:19,033
when I was two years old
with my father
502
00:41:19,066 --> 00:41:22,166
and my grandfather
in Nagarhole National Park.
503
00:41:22,200 --> 00:41:25,633
I was amazed and in awe.
504
00:41:25,666 --> 00:41:30,300
There is nothing like seeing
a tiger in the wild.
505
00:41:30,333 --> 00:41:31,633
Years later,
506
00:41:31,666 --> 00:41:34,766
and now a world-renowned
tiger conservationist,
507
00:41:34,800 --> 00:41:37,033
Krithi remains enthralled.
508
00:41:47,366 --> 00:41:50,300
There are no words
that can really capture
509
00:41:50,333 --> 00:41:53,000
the emotion of seeing a tiger.
510
00:41:53,033 --> 00:41:56,300
Every single time
I've seen a tiger in the wild
511
00:41:56,333 --> 00:42:00,833
I've been either left speechless
or giggling silly or crying,
512
00:42:00,866 --> 00:42:05,066
I mean it's a range of emotions,
but you never forget.
513
00:42:05,100 --> 00:42:07,300
To me, tigers are truly one
514
00:42:07,333 --> 00:42:10,066
of the most spectacular
cats on the planet.
515
00:42:14,000 --> 00:42:16,166
But like so
many of the cats,
516
00:42:16,200 --> 00:42:19,766
survival of the tiger
is on a knife edge.
517
00:42:21,333 --> 00:42:22,766
We see images
and stories
518
00:42:22,800 --> 00:42:25,066
about tigers all the time,
519
00:42:25,100 --> 00:42:28,500
could give us the impression
that they're not endangered
520
00:42:28,533 --> 00:42:30,600
but they absolutely are.
521
00:42:30,633 --> 00:42:32,233
They're one of the most
threatened big cats
522
00:42:32,266 --> 00:42:35,900
in the world today.
523
00:42:35,933 --> 00:42:37,633
Over the last century,
524
00:42:37,666 --> 00:42:43,533
95% of wild tigers
have vanished.
525
00:42:43,566 --> 00:42:46,366
There are now more tigers
in captivity
526
00:42:46,400 --> 00:42:48,233
in the United States alone
527
00:42:48,266 --> 00:42:50,066
than in all the wild.
528
00:43:01,466 --> 00:43:02,866
It is impossible for me
529
00:43:02,900 --> 00:43:05,533
to imagine
a world without wild tigers.
530
00:43:08,233 --> 00:43:10,166
But if we get complacent
531
00:43:10,200 --> 00:43:12,733
we could see tigers go extinct.
532
00:43:29,300 --> 00:43:31,033
Sorry.
533
00:43:31,066 --> 00:43:33,600
I --
I couldn't,
534
00:43:33,633 --> 00:43:36,233
I couldn't imagine a world
without tigers.
535
00:43:48,266 --> 00:43:50,833
Krithi has spent
her life raising awareness
536
00:43:50,866 --> 00:43:53,233
and funding to save the tiger.
537
00:44:00,833 --> 00:44:04,700
She's set up a project that
helps villagers get compensation
538
00:44:04,733 --> 00:44:07,500
when tigers
attack their livestock.
539
00:44:07,533 --> 00:44:11,233
It's helping ease some of
the conflict with local people.
540
00:44:17,433 --> 00:44:20,700
Here in India, the greatest
challenge is giving tigers
541
00:44:20,733 --> 00:44:23,400
the space
they so desperately need.
542
00:44:26,133 --> 00:44:28,400
One solution is
to help villagers
543
00:44:28,433 --> 00:44:32,333
who currently live within
the National Parks to relocate.
544
00:44:39,733 --> 00:44:42,433
Krithi is part of a team
that assists those
545
00:44:42,466 --> 00:44:46,566
who choose to make a new home
beyond the park boundaries.
546
00:44:51,000 --> 00:44:52,866
Once you move people out,
547
00:44:52,900 --> 00:44:55,500
the vegetation comes back,
the prey numbers rebound,
548
00:44:55,533 --> 00:44:57,333
and then tiger numbers
come back.
549
00:44:57,366 --> 00:44:59,633
So, ecological recovery
takes time,
550
00:44:59,666 --> 00:45:02,700
but I think nature knows
how to heal itself.
551
00:45:05,400 --> 00:45:07,100
There's been
a lot of time,
552
00:45:07,133 --> 00:45:09,566
money, and effort spent --
553
00:45:09,600 --> 00:45:12,666
and the tide may be turning.
554
00:45:12,700 --> 00:45:14,033
After a long time
555
00:45:14,066 --> 00:45:15,933
we're seeing
wild tigers come back,
556
00:45:15,966 --> 00:45:19,900
population stabilize and recover
in many tiger reserves.
557
00:45:19,933 --> 00:45:23,500
It shows that we can
change the future for cats
558
00:45:23,533 --> 00:45:26,633
if there is
the will to protect them.
559
00:45:37,233 --> 00:45:41,100
One pioneering project is even
attempting to rescue a cat
560
00:45:41,133 --> 00:45:44,233
from the very edge
of extinction.
561
00:45:53,866 --> 00:45:57,800
Just a century ago,
thousands of Iberian lynx
562
00:45:57,833 --> 00:46:01,233
roamed the ancient woodlands
of Spain and Portugal.
563
00:46:08,433 --> 00:46:11,433
But a combination of
habitat loss, hunting,
564
00:46:11,466 --> 00:46:15,266
and lack of prey caused
their numbers to collapse.
565
00:46:20,000 --> 00:46:24,100
By 2002, fewer than
a hundred were left.
566
00:46:28,266 --> 00:46:33,133
The Iberian lynx was declared
the rarest cat on the planet.
567
00:46:41,033 --> 00:46:46,100
Today, an international team of
scientists and conservationists
568
00:46:46,133 --> 00:46:50,233
are working to bring
these cats back from the brink.
569
00:46:57,400 --> 00:47:01,300
The team has undertaken
an intensive breeding program
570
00:47:01,333 --> 00:47:04,400
on a scale
never attempted before.
571
00:47:08,833 --> 00:47:14,166
Vicky Ascensio is a vet
dedicated to the project.
572
00:47:14,200 --> 00:47:17,200
She works at the newest
of the breeding centers.
573
00:47:19,733 --> 00:47:22,333
Spread across Spain
and Portugal,
574
00:47:22,366 --> 00:47:24,500
these multi-million
dollar facilities
575
00:47:24,533 --> 00:47:28,066
are built to meet
a lynx's every need.
576
00:47:30,966 --> 00:47:35,033
To ensure they can produce
as many cubs as possible
577
00:47:35,066 --> 00:47:37,900
for release back into the wild.
578
00:47:42,700 --> 00:47:46,833
It's also designed so Vicky
can keep a close eye on each
579
00:47:46,866 --> 00:47:50,266
and every precious cub.
580
00:47:50,300 --> 00:47:53,900
In total we have
116 cameras.
581
00:47:56,766 --> 00:47:59,833
We try to see
the animals 24 hours.
582
00:47:59,866 --> 00:48:02,466
This hands-off
approach is vital
583
00:48:02,500 --> 00:48:04,733
so the cubs never meet a human.
584
00:48:07,366 --> 00:48:10,433
They are all day
very quiet, very calm,
585
00:48:10,466 --> 00:48:13,933
and they don't see that
we are always looking them.
586
00:48:13,966 --> 00:48:18,633
It's very important for us
specially when we have cubs.
587
00:48:18,666 --> 00:48:21,533
The Iberian lynx
has become a species
588
00:48:21,566 --> 00:48:23,733
in intensive care.
589
00:48:28,400 --> 00:48:32,800
The breeding centers are just
one piece of the puzzle.
590
00:48:32,833 --> 00:48:37,233
The team is also working hard
to improve the natural habitat
591
00:48:37,266 --> 00:48:41,533
so young lynx can be released
into ideal conditions.
592
00:48:48,933 --> 00:48:52,666
Today Vicky is running
some crucial health checks.
593
00:48:55,366 --> 00:49:00,333
One-year-old cubs Navio and Noa
are scheduled for release.
594
00:49:06,000 --> 00:49:09,366
We are checking that
all the animal is healthy
595
00:49:09,400 --> 00:49:13,600
and also we take some samples
to see that he has not
596
00:49:13,633 --> 00:49:17,466
any infections or diseases
or something like that.
597
00:49:17,500 --> 00:49:21,800
Our goal always is to release
the animals.
598
00:49:21,833 --> 00:49:24,033
It's our most important goal.
599
00:49:32,666 --> 00:49:34,833
The cubs are ready.
600
00:49:37,400 --> 00:49:40,500
A release is
big news around here.
601
00:49:40,533 --> 00:49:45,033
Crowds gather to catch a glimpse
of this iconic Spanish cat.
602
00:49:49,666 --> 00:49:52,633
This is a very
special moment for me
603
00:49:52,666 --> 00:49:56,233
because it's an animal
that was born in the center
604
00:49:56,266 --> 00:50:00,000
and now you are
giving him the freedom.
605
00:50:00,033 --> 00:50:03,166
It's very emotional for us.
606
00:50:11,200 --> 00:50:14,666
Navio and Noa
are given their freedom,
607
00:50:14,700 --> 00:50:17,400
running wild for the first time.
608
00:50:57,933 --> 00:51:00,500
This ambitious project
has become
609
00:51:00,533 --> 00:51:04,400
one of the most successful
reintroductions on the planet.
610
00:51:04,433 --> 00:51:10,033
Nearly 500 cats once again roam
these ancient woodlands.
611
00:51:21,300 --> 00:51:23,300
The more we learn about cats,
612
00:51:23,333 --> 00:51:26,566
the more they surprise
and amaze us.
613
00:51:32,533 --> 00:51:35,933
Only by understanding
their needs can we help
614
00:51:35,966 --> 00:51:38,133
safeguard their future.
615
00:51:43,133 --> 00:51:45,833
There's a lot of work
still to do,
616
00:51:45,866 --> 00:51:49,066
but across the globe people
are putting heart and soul
617
00:51:49,100 --> 00:51:51,400
into finding answers...
618
00:51:54,966 --> 00:51:58,500
and making sure
the future always has a place
619
00:51:58,533 --> 00:52:00,433
for cats --
620
00:52:00,466 --> 00:52:03,433
big and small.
621
00:52:12,400 --> 00:52:14,866
-This is an animal you should
622
00:52:12,400 --> 00:52:14,866
never underestimate.
623
00:52:14,900 --> 00:52:18,433
-Squirrels are one of the most
agile animals on Earth.
624
00:52:18,466 --> 00:52:20,966
-From outwitting rattlesnakes
625
00:52:21,000 --> 00:52:23,733
to surviving
626
00:52:21,000 --> 00:52:23,733
sub-zero temperatures,
627
00:52:23,766 --> 00:52:26,533
but ordinary.
628
00:52:23,766 --> 00:52:26,533
squirrels are anything
629
00:52:27,766 --> 00:52:29,966
Now, one orphaned red squirrel
630
00:52:30,000 --> 00:52:32,300
and a cast of
631
00:52:30,000 --> 00:52:32,300
cheeky characters
632
00:52:32,333 --> 00:52:35,733
are going to reveal the secret
633
00:52:32,333 --> 00:52:35,733
to squirrel success.
48857
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