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These are the user uploaded subtitles that are being translated: 1 00:00:09,133 --> 00:00:10,700 Big or small, 2 00:00:10,733 --> 00:00:14,466 cats have conquered the planet. 3 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. 6 00:00:25,733 --> 00:00:29,766 If we get complacent we could see tigers go extinct. 7 00:00:32,500 --> 00:00:36,500 I couldn't imagine a world without tigers. 8 00:00:39,733 --> 00:00:42,566 It's a critical time for new research 9 00:00:42,600 --> 00:00:45,000 and cat conservation. 10 00:00:45,033 --> 00:00:46,766 Holy mackerel. 11 00:00:46,800 --> 00:00:48,766 He's a loose cannon. 12 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. 15 00:01:34,133 --> 00:01:37,500 Cheetahs are the world's fastest land animal. 16 00:01:44,766 --> 00:01:49,166 It's said they can accelerate faster than a Ferrari. 17 00:02:01,300 --> 00:02:05,966 But no one knows for sure what they're really capable of. 18 00:02:11,633 --> 00:02:15,266 Professor Alan Wilson has spent the last five years 19 00:02:15,300 --> 00:02:17,500 trying to find out. 20 00:02:20,966 --> 00:02:22,333 Cheetahs are amazing, 21 00:02:22,366 --> 00:02:24,733 they're so much faster than anything else. 22 00:02:24,766 --> 00:02:26,533 We've got an animal that has got four times 23 00:02:26,566 --> 00:02:28,466 the acceleration of Usain Bolt 24 00:02:28,500 --> 00:02:30,266 and more than twice the top speed, 25 00:02:30,300 --> 00:02:32,833 how can they not be fascinating to study. 26 00:02:35,033 --> 00:02:37,733 Alan wants to find the cheetah's top speed 27 00:02:37,766 --> 00:02:40,166 when it really counts... 28 00:02:40,200 --> 00:02:44,166 during a hunt. 29 00:02:44,200 --> 00:02:48,533 He's developed high tech collars to record the cheetah's speed, 30 00:02:48,566 --> 00:02:52,033 position, and G force while they're hunting. 31 00:02:56,433 --> 00:02:59,433 The cheetahs soon disappear. 32 00:02:59,466 --> 00:03:02,933 They cover hundreds of miles in search of their prey. 33 00:03:02,966 --> 00:03:05,400 That makes getting any information back 34 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? 36 00:03:12,633 --> 00:03:15,100 He's built his own plane -- 37 00:03:15,133 --> 00:03:17,933 from scratch, 38 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. 40 00:03:26,600 --> 00:03:28,666 We have a tracking antenna on the wing. 41 00:03:28,700 --> 00:03:30,833 We have a three-dimensional laser scanner. 42 00:03:30,866 --> 00:03:33,033 We have a video camera on a gimbal. 43 00:03:33,066 --> 00:03:35,266 That's a missile guidance system. 44 00:03:39,066 --> 00:03:42,066 Okay, let's go find some cheetah. 45 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. 48 00:04:22,000 --> 00:04:24,200 The cheetahs' collars record details 49 00:04:24,233 --> 00:04:28,033 of their movements 300 times a second. 50 00:04:32,066 --> 00:04:34,233 As the plane flies over, 51 00:04:34,266 --> 00:04:39,800 it locks on to each collar and downloads the data. 52 00:04:39,833 --> 00:04:43,733 There we go, we're downloading collar 7-5-0. 53 00:04:43,766 --> 00:04:48,866 Each of those files represents one hunt. 54 00:04:48,900 --> 00:04:51,900 After recording more than 500 hunts, 55 00:04:51,933 --> 00:04:55,933 Alan clocked a cheetah's top speed of 58 miles an hour. 56 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, 58 00:05:07,333 --> 00:05:11,933 only half their potential top speed. 59 00:05:11,966 --> 00:05:14,500 It turns out, for a cheetah, 60 00:05:14,533 --> 00:05:17,066 hunting is not all about the sprint. 61 00:05:26,066 --> 00:05:29,866 So, what are they relying on to catch their dinner? 62 00:05:36,766 --> 00:05:40,900 To investigate, Alan has enlisted three volunteers... 63 00:05:46,233 --> 00:05:48,400 And a rag on a string. 64 00:05:51,300 --> 00:05:55,500 These hand-reared cheetahs love chasing a moving lure... 65 00:05:57,766 --> 00:06:01,333 Replicating how cheetahs behave when hunting. 66 00:06:09,000 --> 00:06:12,100 Prey animals don't run in a straight line for long. 67 00:06:14,600 --> 00:06:17,666 To follow their prey, cheetahs must also weave 68 00:06:17,700 --> 00:06:19,900 and change direction. 69 00:06:22,066 --> 00:06:27,066 This maneuvering inevitably slows them down, 70 00:06:27,100 --> 00:06:30,033 but it's also where their real strength lies. 71 00:06:39,100 --> 00:06:41,166 The accelerations and decelerations, 72 00:06:41,200 --> 00:06:44,666 the G forces they're pulling in the turns are very high. 73 00:06:47,200 --> 00:06:49,500 The force going through their legs 74 00:06:49,533 --> 00:06:53,633 would be enough to break a human leg bone. 75 00:06:58,900 --> 00:07:00,233 The lure's just taken the corner 76 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, 78 00:07:03,033 --> 00:07:05,400 which is helping control the roll of its body 79 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 83 00:07:21,866 --> 00:07:23,766 is their agility. 84 00:07:28,733 --> 00:07:30,333 We started believing that cheetahs 85 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. 87 00:07:33,833 --> 00:07:36,133 What we've seen is that they're gymnasts, 88 00:07:36,166 --> 00:07:38,166 they can accelerate, they can maneuver, 89 00:07:38,200 --> 00:07:40,766 they can turn, and that is what they're good at, 90 00:07:40,800 --> 00:07:46,333 almost the speed is a by-product of all that athleticism. 91 00:07:46,366 --> 00:07:49,400 So they are remarkable athletes, but we shouldn't think of them 92 00:07:49,433 --> 00:07:51,600 as just a speed merchant, there's much more 93 00:07:51,633 --> 00:07:53,666 to their repertoire than that. 94 00:07:59,966 --> 00:08:03,266 Even with the most familiar cats 95 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. 97 00:08:28,433 --> 00:08:31,000 Supreme hunters. 98 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 103 00:08:55,700 --> 00:08:59,133 in any cat, let alone a lion. 104 00:08:59,166 --> 00:09:01,166 Her theory is based on the fact 105 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 109 00:09:17,166 --> 00:09:19,566 and when we think of other social species -- 110 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. 113 00:09:29,533 --> 00:09:32,766 The idea that social animals are more intelligent 114 00:09:32,800 --> 00:09:34,300 is well established, 115 00:09:34,333 --> 00:09:37,166 but has never been proved for lions. 116 00:09:45,266 --> 00:09:48,533 Cats are notoriously uncooperative. 117 00:09:48,566 --> 00:09:52,233 What possible IQ test could you give a lion? 118 00:09:54,400 --> 00:09:57,233 Natalia's traveled to South Africa for the chance 119 00:09:57,266 --> 00:10:00,433 to test a slightly unusual pride. 120 00:10:25,300 --> 00:10:28,366 Kevin Richardson has an unconventional approach 121 00:10:28,400 --> 00:10:30,566 to working with lions. 122 00:10:34,800 --> 00:10:37,566 For 10 years he's lived alongside 123 00:10:37,600 --> 00:10:39,500 these rescued animals, 124 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, 126 00:10:55,700 --> 00:10:58,166 giving Natalia a unique opportunity 127 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. 130 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, 132 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. 160 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 169 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 171 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 173 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 179 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, 181 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. 211 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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