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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:12,612 --> 00:00:15,647 NARRATOR: Migrations. 2 00:00:15,682 --> 00:00:19,585 Mysterious feats of navigation... 3 00:00:19,619 --> 00:00:22,488 endurance... 4 00:00:22,522 --> 00:00:24,123 and courage. 5 00:00:27,160 --> 00:00:32,097 Now, technology allows scientists to go along for the ride... 6 00:00:32,132 --> 00:00:34,266 MAN: Really diving down... 7 00:00:34,300 --> 00:00:35,534 MAN: Yook, snap! 8 00:00:35,568 --> 00:00:37,603 NARRATOR: ...like never before. 9 00:00:37,637 --> 00:00:39,471 MAN: lt's an incredible thrill. 10 00:00:39,506 --> 00:00:42,975 Stuff happens that you wouldn't believe in your wildest dreams. 11 00:00:44,644 --> 00:00:47,246 NARRATOR: ...learning where the animals go... 12 00:00:47,280 --> 00:00:48,614 MAN: Cool! Wow. 13 00:00:48,648 --> 00:00:49,948 That's perfect. Look at that! 14 00:00:49,983 --> 00:00:51,417 NARRATOR: ...why... 15 00:00:51,451 --> 00:00:53,485 and how they survive. 16 00:00:53,520 --> 00:00:56,121 MAN: This is really cutting-edge stuff. 17 00:00:56,156 --> 00:00:59,925 MAN: We are the first to find out what they're really doing. 18 00:00:59,959 --> 00:01:02,528 NARRATOR: This is the inside story 19 00:01:02,562 --> 00:01:06,598 of the science behind the great migrations. 20 00:01:24,250 --> 00:01:26,418 On this October morning, 21 00:01:26,453 --> 00:01:31,056 elephant seals are nearing the end of breeding season. 22 00:01:33,293 --> 00:01:37,296 From here in Patagonia, they will soon embark 23 00:01:37,330 --> 00:01:40,432 on an odyssey through the southern oceans. 24 00:01:42,569 --> 00:01:48,574 That's why a team of biologists led by Flavio Quintana is here. 25 00:01:48,608 --> 00:01:54,313 To deploy a state-of-the-art tag in hopes of tracking their every move. 26 00:01:56,483 --> 00:02:01,820 For ten months out of the year, the seals migrate thousands of miles... 27 00:02:01,855 --> 00:02:04,189 disappearing into the sea to feed, 28 00:02:04,224 --> 00:02:07,159 where their behavior is largely unknown. 29 00:02:15,735 --> 00:02:22,274 lt is a question vexing Quintana for much of his 20-year career. 30 00:02:22,308 --> 00:02:24,576 QUlNTANA: We are always surprised to study this kind of animal, 31 00:02:24,611 --> 00:02:27,479 because they are incredible, incredible. 32 00:02:27,514 --> 00:02:30,449 They are diving machines; l'm really impressed with that. 33 00:02:30,483 --> 00:02:34,653 Because they need to come back to shore to breed and to molt, 34 00:02:34,687 --> 00:02:38,323 but they spend 80 percent of their life at sea. 35 00:02:38,358 --> 00:02:40,292 And nobody knows what they are doing at sea. 36 00:02:40,326 --> 00:02:42,427 This is what we are trying to discover. 37 00:02:46,566 --> 00:02:49,001 NARRATOR: lf the high-tech tag works, 38 00:02:49,035 --> 00:02:54,740 scientists will finally solve the mystery of the elephant seals' migration. 39 00:02:58,178 --> 00:03:02,247 Quintana's special weapon is called the Daily Diary, 40 00:03:02,282 --> 00:03:06,685 invented by this man, Rory Wilson. 41 00:03:06,719 --> 00:03:09,121 WlLSON: There are temperature sensors in there, 42 00:03:09,155 --> 00:03:13,292 there are speed sensors in there, there are light sensors in there, 43 00:03:13,326 --> 00:03:16,695 all packaged in this resin. 44 00:03:16,729 --> 00:03:19,264 This part here, all this big clunky bit here, 45 00:03:19,299 --> 00:03:20,499 these are two batteries. 46 00:03:20,533 --> 00:03:22,201 The batteries are inside stainless steel, 47 00:03:22,235 --> 00:03:23,268 and that's in order to protect 48 00:03:23,303 --> 00:03:25,470 against the ridiculous amounts of pressures 49 00:03:25,505 --> 00:03:29,141 to which the animals expose themselves routinely. 50 00:03:29,175 --> 00:03:32,878 NARRATOR: lt's the result of ten years of trial and error. 51 00:03:32,912 --> 00:03:36,982 No other tag records such a wide array of data. 52 00:03:40,053 --> 00:03:45,490 Wilson got the idea for his Daily Diary while studying penguins. 53 00:03:48,528 --> 00:03:50,162 WlLSON: lt's terribly depressing. 54 00:03:50,196 --> 00:03:51,330 You go out on your island, 55 00:03:51,364 --> 00:03:52,864 you're going to do your whole Ph.D., 56 00:03:52,899 --> 00:03:54,032 your doctorate on penguins, 57 00:03:54,067 --> 00:03:55,767 on what they do at sea, 58 00:03:55,802 --> 00:03:57,002 and they're all standing around the edge 59 00:03:57,036 --> 00:03:58,904 looking at you saying, "Yes, we're the penguins." 60 00:03:58,938 --> 00:04:02,841 Then they all jump in the water and disappear. 61 00:04:02,875 --> 00:04:06,345 So in a grumpy and foul-mouthed mood, 62 00:04:06,379 --> 00:04:07,913 l went back and thought, "lf l can't see them, 63 00:04:07,947 --> 00:04:11,283 then l'll find something else that's just going to record for me." 64 00:04:13,386 --> 00:04:15,287 Rather makeshift. 65 00:04:15,321 --> 00:04:18,957 NARRATOR: He tested the prototype on an animal that follows direction... 66 00:04:18,992 --> 00:04:19,992 WlLSON: Stay! 67 00:04:20,026 --> 00:04:21,593 NARRATOR: ...his dog, Moon. 68 00:04:24,664 --> 00:04:31,336 Moon's Daily Diary recorded her speed, her temperature, 69 00:04:31,371 --> 00:04:35,073 every breath, step and wag. 70 00:04:39,646 --> 00:04:44,783 WlLSON: Here's where l tell her to run, throw the stick. 71 00:04:44,817 --> 00:04:49,054 Look at this activity here, tearing towards the stick. 72 00:04:50,990 --> 00:04:55,994 Picks it up and then this very regular canter back. 73 00:04:59,098 --> 00:05:02,701 NARRATOR: But it also revealed things Wilson didn't expect. 74 00:05:02,735 --> 00:05:03,835 WlLSON: Her panting. 75 00:05:03,870 --> 00:05:06,038 She'll breathe up to six times a second when she's panting... 76 00:05:06,072 --> 00:05:07,172 [panting] 77 00:05:07,206 --> 00:05:08,607 ...when she's been running around. 78 00:05:08,641 --> 00:05:10,008 And when l'm about to give her a command, 79 00:05:10,043 --> 00:05:13,478 l put my hand up, and l discovered looking at the trace, 80 00:05:13,513 --> 00:05:17,516 she actually holds her breath when my hand goes up. 81 00:05:19,018 --> 00:05:21,553 NARRATOR: This intrigued Wilson. 82 00:05:21,587 --> 00:05:22,821 He wanted to know more 83 00:05:22,855 --> 00:05:26,958 about the importance of breathing in animal behavior. 84 00:05:29,495 --> 00:05:32,464 He returned to his penguins. 85 00:05:35,335 --> 00:05:37,903 The results were astonishing. 86 00:05:40,406 --> 00:05:42,407 WlLSON: Each one of these is a flipper beating. 87 00:05:42,442 --> 00:05:44,009 lt's swimming the whole time underwater, 88 00:05:44,043 --> 00:05:46,311 and relaxing a bit as it comes back to the surface here. 89 00:05:46,346 --> 00:05:48,513 You can see as it comes back for the first breath, 90 00:05:48,548 --> 00:05:51,450 it's using the buoyancy to help it go up. 91 00:05:51,484 --> 00:05:54,186 So what the penguin's doing is it's gone down, 92 00:05:54,220 --> 00:05:55,821 slight curve on the way down, 93 00:05:55,855 --> 00:05:57,889 it's come up, it's spotted a prey, 94 00:05:57,924 --> 00:06:02,661 it's come up really rapidly and it's gone yook, snap... 95 00:06:02,695 --> 00:06:05,430 and then drifted up to the surface. 96 00:06:11,904 --> 00:06:15,507 NARRATOR: The penguin takes in the exact amount of air it needs 97 00:06:15,541 --> 00:06:18,977 in advance of a dive. 98 00:06:19,011 --> 00:06:20,746 WlLSON: You know, the penguin before it goes down is saying: 99 00:06:20,780 --> 00:06:23,548 "How deep am l going to go on the next dive, 100 00:06:23,583 --> 00:06:26,385 how many fish do l think l'm going to catch?" 101 00:06:28,454 --> 00:06:31,390 They're inhaling already at the surface 102 00:06:31,424 --> 00:06:34,693 the right amount of air volume to give them neutral buoyancy 103 00:06:34,727 --> 00:06:36,428 at the depth at which they're going to forage. 104 00:06:36,462 --> 00:06:38,764 So the implication is they know: 105 00:06:38,798 --> 00:06:43,335 "Ha, 30 meters, l need 600 milliliters to be neutrally buoyant at that, 106 00:06:43,369 --> 00:06:46,938 so, 600, l'm going down." 107 00:06:46,973 --> 00:06:49,708 That's quite complicated stuff for a small bird. 108 00:06:51,677 --> 00:06:56,248 NARRATOR: Their buoyant bodies can then rise like balloons through the water, 109 00:06:56,282 --> 00:06:59,785 effortlessly catching fish along the way. 110 00:06:59,819 --> 00:07:02,888 By doing this, the animal conserves what it needs most 111 00:07:02,922 --> 00:07:05,457 for its migratory journey: 112 00:07:05,491 --> 00:07:06,992 energy. 113 00:07:10,530 --> 00:07:13,632 With this discovery, Wilson joins Quintana 114 00:07:13,666 --> 00:07:17,335 to study the migration of the elephant seals. 115 00:07:19,739 --> 00:07:23,508 ln two months, these behemoths will return here to molt‒ 116 00:07:23,543 --> 00:07:26,545 a perfect time to retrieve the Daily Diaries 117 00:07:26,579 --> 00:07:30,115 because the batteries won't last much longer. 118 00:07:32,652 --> 00:07:34,352 WlLSON: We've never done this before 119 00:07:34,387 --> 00:07:36,588 in animals that are going to go this deep, 120 00:07:36,622 --> 00:07:39,124 and it can just go horribly wrong. 121 00:07:43,062 --> 00:07:46,898 NARRATOR: Elephant seals dive thousands of feet. 122 00:07:46,933 --> 00:07:50,235 lf the Daily Diary works under such high pressure, 123 00:07:50,269 --> 00:07:54,739 we will witness a new era of biological discovery. 124 00:07:57,143 --> 00:08:00,445 Quintana identifies females to tag‒ 125 00:08:00,480 --> 00:08:02,180 at 2,000 pounds, 126 00:08:02,215 --> 00:08:06,885 they're easier to deal with than the 8,000-pound males. 127 00:08:10,456 --> 00:08:15,260 Male or female, it's risky business. 128 00:08:15,294 --> 00:08:18,096 And the colony is restless. 129 00:08:20,633 --> 00:08:25,337 lt's up to Marcela Uhart to anesthetize the giants. 130 00:08:25,371 --> 00:08:28,306 UHART: Elephant seals are so big and so powerful, you know, 131 00:08:28,341 --> 00:08:31,243 they have very few predators. 132 00:08:31,277 --> 00:08:33,278 They don't really fear us that much. 133 00:08:33,312 --> 00:08:35,347 They actually challenge you. 134 00:08:37,650 --> 00:08:40,018 [groaning] 135 00:08:58,037 --> 00:09:00,672 [seal barking] 136 00:09:04,777 --> 00:09:08,013 UHART: Tomorrow he's going to be on his own, l think... 137 00:09:16,422 --> 00:09:18,690 [growling] 138 00:09:20,459 --> 00:09:23,662 WlLSON: l don't like this being protective of your friend stuff. 139 00:09:23,696 --> 00:09:27,766 l'd rather they just deserted them and left them to it. 140 00:09:27,800 --> 00:09:33,605 NARRATOR: They name the tagged seals after submarines and space stations. 141 00:09:38,644 --> 00:09:44,115 ln all, five females are successfully rigged with Daily Diaries. 142 00:09:48,020 --> 00:09:49,688 WlLSON: We have five. 143 00:09:49,722 --> 00:09:52,791 lf we're lucky, l think we'll get four back. 144 00:09:52,825 --> 00:09:56,227 l sort of tip somewhere between three and four. 145 00:09:56,262 --> 00:10:01,166 And l'll just hope and pray that they all are working okay. 146 00:10:03,269 --> 00:10:05,036 NARRATOR: lf it goes well, 147 00:10:05,071 --> 00:10:10,609 Wilson will be the first to tell the story of this hidden journey. 148 00:10:14,046 --> 00:10:18,116 These seals' ocean pathways are nearly boundless. 149 00:10:20,953 --> 00:10:26,124 But that is not the case with many migratory routes on land. 150 00:10:26,158 --> 00:10:31,663 As human populations grow and habitats diminish, 151 00:10:31,697 --> 00:10:35,734 the great migrating animals are increasingly in peril... 152 00:10:35,768 --> 00:10:39,738 particularly the monarch butterfly. 153 00:10:39,772 --> 00:10:43,708 The monarchs' migration spans generations of individuals 154 00:10:43,743 --> 00:10:47,212 and is an astounding 4,000 miles long, 155 00:10:47,246 --> 00:10:52,517 from Mexico to as far as Canada and back again each year. 156 00:10:56,822 --> 00:11:00,592 CHlP TAYLOR: This is one of the world's most magnificent natural phenomena. 157 00:11:00,626 --> 00:11:02,560 l mean, here you have an insect that migrates 158 00:11:02,595 --> 00:11:04,896 to the same general location every year, 159 00:11:04,930 --> 00:11:09,267 and then returns to breed in the northern part of North America. 160 00:11:11,437 --> 00:11:13,905 NARRATOR: Chip Taylor has dedicated his life's work 161 00:11:13,939 --> 00:11:16,541 to the ceaseless habits of the monarch. 162 00:11:18,144 --> 00:11:20,679 For 18 years, he's been tracking the migration 163 00:11:20,713 --> 00:11:25,383 with the same device: a plastic tag. 164 00:11:29,522 --> 00:11:33,458 And he's learned a surprising amount from this simple tool. 165 00:11:35,194 --> 00:11:38,730 ln one study, Taylor released a monarch born in captivity 166 00:11:38,764 --> 00:11:42,967 2,000 miles from its birthplace. 167 00:11:43,002 --> 00:11:46,805 The butterfly still migrated southwest to Mexico. 168 00:11:48,874 --> 00:11:52,243 TAYLOR: These butterflies have to navigate across a continent. 169 00:11:52,278 --> 00:11:55,480 They have to navigate. 170 00:11:55,514 --> 00:11:57,682 How does a butterfly coming out of Maine 171 00:11:57,717 --> 00:11:59,884 know how to get to Mexico? 172 00:12:03,389 --> 00:12:08,226 NARRATOR: ln 2009, scientists discovered the monarch's internal GPS, 173 00:12:08,260 --> 00:12:12,397 a network of not one but two internal clocks. 174 00:12:14,500 --> 00:12:18,503 A clock in the brain tracks the location of the sun. 175 00:12:20,439 --> 00:12:22,540 And a second clock, in the antennae, 176 00:12:22,575 --> 00:12:24,943 keeps track of time. 177 00:12:26,045 --> 00:12:28,079 TAYLOR: What they are programmed to do 178 00:12:28,114 --> 00:12:32,083 is follow and respond to certain physical cues, 179 00:12:32,118 --> 00:12:35,820 and these physical cues have a default sort of mechanism 180 00:12:35,855 --> 00:12:39,624 of getting them to the right place. 181 00:12:39,658 --> 00:12:44,729 Now the trick for us is to try to figure out what are those cues? 182 00:12:46,932 --> 00:12:50,602 NARRATOR: Understanding these cues has never been more important. 183 00:12:53,372 --> 00:12:57,809 The monarch population is down by halfjust from last year. 184 00:12:59,445 --> 00:13:01,646 lts ancient flyway is unrecognizable 185 00:13:01,680 --> 00:13:04,949 as development overwhelms the landscape. 186 00:13:08,487 --> 00:13:11,556 And the milkweed plant the monarch needs to lay its eggs 187 00:13:11,590 --> 00:13:13,458 is vanishing. 188 00:13:18,430 --> 00:13:22,467 TAYLOR: We're losing 6,000 acres a day in this country due to development. 189 00:13:22,501 --> 00:13:26,404 That's 2.2 million acres a year. 190 00:13:26,438 --> 00:13:31,176 That's just an astounding amount of habitat to turn into concrete. 191 00:13:31,210 --> 00:13:33,845 And you just can't keep on doing that 192 00:13:33,879 --> 00:13:38,116 without having a really significant impact on wildlife out there. 193 00:13:40,252 --> 00:13:42,687 NARRATOR: Knowing how far the monarchs fly each day 194 00:13:42,721 --> 00:13:45,557 and where they stop could save them. 195 00:13:47,626 --> 00:13:52,664 An electronic tag that records precise data could help. 196 00:13:56,035 --> 00:14:01,739 But this creature is light as smoke, and a tag is a heavy load. 197 00:14:04,777 --> 00:14:07,445 Enter Martin Wikelski. 198 00:14:08,948 --> 00:14:11,282 He's a migration ecologist, 199 00:14:11,317 --> 00:14:15,653 leading the charge to miniaturize tag technology. 200 00:14:17,990 --> 00:14:19,657 WlKELSKl: The smaller you can get the tag, 201 00:14:19,692 --> 00:14:23,394 the more power you can output, the better the study we can do. 202 00:14:23,429 --> 00:14:26,164 And that's going to be a total breakthrough 203 00:14:26,198 --> 00:14:30,735 in our understanding of the natural environment. 204 00:14:30,769 --> 00:14:32,170 We need to understand small animals 205 00:14:32,204 --> 00:14:34,105 to understand life on Earth, 206 00:14:34,139 --> 00:14:37,442 and that's what we still have no clue about. 207 00:14:39,478 --> 00:14:40,879 NARRATOR: With radio tags, 208 00:14:40,913 --> 00:14:43,548 Wikelski followed the route of a one-ounce thrush, 209 00:14:43,582 --> 00:14:47,285 discovering how it navigates at night. 210 00:14:47,319 --> 00:14:51,022 Then he went smaller, switching to insects. 211 00:14:53,125 --> 00:14:56,661 His team designed a tiny hearing aid battery 212 00:14:56,695 --> 00:15:00,231 attached to an antenna made of a guitar string. 213 00:15:02,067 --> 00:15:06,471 The smaller the device, the simpler the data. 214 00:15:06,505 --> 00:15:10,275 This radio tag only tracked location and direction. 215 00:15:10,309 --> 00:15:13,278 But it was a start. 216 00:15:13,312 --> 00:15:16,080 Wikelski tried it on bees. 217 00:15:16,115 --> 00:15:17,682 They flew. 218 00:15:17,716 --> 00:15:19,284 He tried it on dragonflies 219 00:15:19,318 --> 00:15:24,555 and discovered that one migrated a hundred miles in a single day. 220 00:15:27,559 --> 00:15:32,063 But the monarch is half the weight of a dragonfly. 221 00:15:32,097 --> 00:15:34,666 TAYLOR: l first learned about Martin's work a few years ago 222 00:15:34,700 --> 00:15:35,700 when l heard of his studies 223 00:15:35,734 --> 00:15:38,469 where he was putting radio tags on dragonflies, 224 00:15:38,504 --> 00:15:39,904 and l thought that was pretty fascinating. 225 00:15:39,939 --> 00:15:42,440 l thought, "Aw, man you'll never get them small enough 226 00:15:42,474 --> 00:15:44,409 to put them on monarchs." 227 00:15:46,912 --> 00:15:49,047 NARRATOR: Martin Wikelski's Kitty Hawk 228 00:15:49,081 --> 00:15:52,884 is the butterfly house in Constance, Germany. 229 00:15:53,686 --> 00:15:55,353 WlKELSKl: Nice. 230 00:16:03,495 --> 00:16:09,133 NARRATOR: The tag is the smallest yet, half the weight of this butterfly. 231 00:16:12,071 --> 00:16:13,638 WlKELSKl: Available radio tag, 232 00:16:13,672 --> 00:16:16,741 and they just barely got it in the size range 233 00:16:16,775 --> 00:16:18,643 that the butterfly might fly with it. 234 00:16:18,677 --> 00:16:22,880 And now we just try it. 235 00:16:22,915 --> 00:16:26,918 NARRATOR: Trial one: no go. 236 00:16:26,952 --> 00:16:31,389 A slight antenna adjustment, then trial two. 237 00:16:33,692 --> 00:16:35,760 And liftoff. 238 00:16:35,794 --> 00:16:37,929 WlKELSKl: Wow! 239 00:16:45,070 --> 00:16:46,738 [laughing] 240 00:16:48,107 --> 00:16:49,807 Oh, there it is. 241 00:16:49,842 --> 00:16:52,143 lt's working. 242 00:16:52,177 --> 00:16:56,714 lt's totally amazing, l mean, the first flight of a butterfly with a tag! 243 00:16:56,749 --> 00:17:00,718 So it's working, l mean, you see it's just flying all over the place. 244 00:17:00,753 --> 00:17:03,788 So l think it's going to work in the field as well. 245 00:17:03,822 --> 00:17:05,790 This is flying beautifully. 246 00:17:05,824 --> 00:17:08,092 lt's amazing. 247 00:17:08,127 --> 00:17:10,361 NARRATOR: Wikelski and Taylor will now team up 248 00:17:10,396 --> 00:17:15,800 to see if they are on the brink of a new age of monarch science. 249 00:17:15,834 --> 00:17:18,503 [rooster crows] 250 00:17:22,641 --> 00:17:25,243 The migration ecologist Martin Wikelski 251 00:17:25,277 --> 00:17:29,480 finally meets the monarch sage Chip Taylor. 252 00:17:29,515 --> 00:17:32,183 Together, they'll conduct the first test ever 253 00:17:32,217 --> 00:17:36,421 of an electronic tag on a monarch butterfly. 254 00:17:36,455 --> 00:17:39,123 lt's a meeting of like minds... 255 00:17:39,158 --> 00:17:43,394 but not when it comes to catching butterflies. 256 00:17:43,429 --> 00:17:47,432 TAYLOR: Come up behind the butterfly while it's sitting on a flower. 257 00:17:47,466 --> 00:17:50,768 What you don't want to do is swing at them in the air. 258 00:17:50,803 --> 00:17:51,803 WlKELSKl: Okay. 259 00:17:51,837 --> 00:17:53,971 TAYLOR: Get it! Whoa! 260 00:18:01,747 --> 00:18:04,882 l mean, he's like a little kid; it's wonderful. 261 00:18:06,785 --> 00:18:09,153 At my age, l don't do that anymore. 262 00:18:09,188 --> 00:18:11,689 l prefer the sneaky method! 263 00:18:11,723 --> 00:18:13,958 Looks like we got one here. 264 00:18:18,597 --> 00:18:21,599 NARRATOR: The scientists catch six in all. 265 00:18:23,869 --> 00:18:25,269 Success will be determined 266 00:18:25,304 --> 00:18:28,906 if the tags do not disrupt the monarchs' migration. 267 00:18:30,642 --> 00:18:34,412 And if the insects can be found after takeoff. 268 00:18:34,446 --> 00:18:36,180 WlKELSKl: l'll just get the transmitter. 269 00:18:36,215 --> 00:18:38,082 NARRATOR: But Taylor has his doubts. 270 00:18:38,117 --> 00:18:39,784 TAYLOR: One of the things about these kinds of tests 271 00:18:39,818 --> 00:18:42,720 is that you do them indoors, you do them under ideal conditions, 272 00:18:42,754 --> 00:18:44,088 and then we bring them out here in the field, 273 00:18:44,123 --> 00:18:45,890 and we're dealing with 20-mile-an-hour winds, 274 00:18:45,924 --> 00:18:48,826 and it's going to be quite challenging for the butterfly 275 00:18:48,861 --> 00:18:50,862 to figure out how to handle all of this mass 276 00:18:50,896 --> 00:18:53,397 that you're attaching to the abdomen. 277 00:18:56,902 --> 00:18:58,703 WlKELSKl: Now it's up to the butterfly. 278 00:18:58,737 --> 00:19:02,440 TAYLOR: Well, we're not going to name it lcarus, right? 279 00:19:02,474 --> 00:19:04,842 WlKELSKl: Let's call it lcarus and see if lcarus can fly. 280 00:19:08,580 --> 00:19:09,580 WlKELSKl: Wow. 281 00:19:09,615 --> 00:19:11,349 TAYLOR: Wow. lt's flying pretty well, look at that. 282 00:19:11,383 --> 00:19:12,383 WlKELSKl: That's amazing. 283 00:19:12,417 --> 00:19:14,552 TAYLOR: lt's staying close to the ground, though. 284 00:19:14,586 --> 00:19:16,420 WlKELSKl: Wow, it's flying! 285 00:19:18,023 --> 00:19:21,826 TAYLOR: All right, let's start with liftoff here. 286 00:19:21,860 --> 00:19:22,860 WlKELSKl: Wow! 287 00:19:22,895 --> 00:19:24,862 TAYLOR: There she goes. 288 00:19:24,897 --> 00:19:26,664 That's cool. 289 00:19:26,698 --> 00:19:28,966 That's terrific, look at that! 290 00:19:29,001 --> 00:19:30,401 WlKELSKl: Wow, it's really taking off. 291 00:19:30,435 --> 00:19:32,670 TAYLOR: lt's really catching the wind. 292 00:19:32,704 --> 00:19:36,007 WlKELSKl: lt's coming over to your side. 293 00:19:36,041 --> 00:19:37,041 TAYLOR: Big Boy. 294 00:19:37,075 --> 00:19:38,509 WlKELSKl: Wow, that's a big one. 295 00:19:38,544 --> 00:19:41,279 TAYLOR: That's the biggest butterfly we've got. 296 00:19:41,313 --> 00:19:43,948 There it goes. 297 00:19:43,982 --> 00:19:45,883 WlKELSKl: There she goes. 298 00:19:49,521 --> 00:19:52,023 l think he still wants to feed. 299 00:19:52,057 --> 00:19:54,759 [laughing] 300 00:20:07,105 --> 00:20:10,174 NARRATOR: Taylor and Wikelski take to the air, too, 301 00:20:10,209 --> 00:20:12,710 in pursuit of the tagged monarchs. 302 00:20:14,346 --> 00:20:20,284 With radio receivers in tow, they listen for a telltale click. 303 00:20:20,319 --> 00:20:24,722 WlKELSKl: We are looking for liftoff right now. 304 00:20:24,756 --> 00:20:28,259 NARRATOR: Each butterfly is on its own frequency. 305 00:20:28,293 --> 00:20:29,293 [click] 306 00:20:29,328 --> 00:20:30,695 WlKELSKl: There it is, do you hear it? 307 00:20:30,729 --> 00:20:32,964 We've got a signal. 308 00:20:32,998 --> 00:20:38,002 NARRATOR: An auspicious start— some signals come in loud and clear. 309 00:20:38,036 --> 00:20:42,940 WlKELSKl: So liftoff is still probably at the field down there. 310 00:20:45,410 --> 00:20:49,046 NARRATOR: But the test is incomplete until a butterfly has flown 311 00:20:49,081 --> 00:20:54,151 more than a few miles in a northeasterly direction. 312 00:20:54,186 --> 00:20:56,520 TAYLOR: Martin, any sign of lcarus? 313 00:20:56,555 --> 00:20:58,356 WlKELSKl: Nope, we will go a little lower 314 00:20:58,390 --> 00:21:00,691 and search closer to the ground. 315 00:21:00,726 --> 00:21:02,493 TAYLOR: Let's hope it works. 316 00:21:04,696 --> 00:21:05,730 [buzzing] 317 00:21:05,764 --> 00:21:07,565 WlKELSKl: Yep, yep, there it is. 318 00:21:07,599 --> 00:21:09,033 l do hear lcarus. 319 00:21:09,067 --> 00:21:11,202 TAYLOR: Good old lcarus. 320 00:21:11,236 --> 00:21:13,404 WlKELSKl: lcarus is down there, yes. 321 00:21:13,438 --> 00:21:17,375 NARRATOR: All but one are accounted for. 322 00:21:17,409 --> 00:21:20,211 Big Boy is still missing. 323 00:21:22,714 --> 00:21:24,015 TAYLOR: Martin, do you hear anything? 324 00:21:24,049 --> 00:21:26,117 WlKELSKl: Nope. 325 00:21:26,151 --> 00:21:29,587 NARRATOR: Perhaps he's a long distance flyer... 326 00:21:29,621 --> 00:21:34,625 or the weight weighed him down, plummeting him to Earth. 327 00:21:36,295 --> 00:21:39,797 Taylor and Wikelski continue northeast. 328 00:21:42,534 --> 00:21:45,069 Five miles out. 329 00:21:45,103 --> 00:21:46,537 Nothing. 330 00:21:49,608 --> 00:21:52,143 Ten miles out. 331 00:21:52,177 --> 00:21:53,978 [buzzing] 332 00:21:54,012 --> 00:21:55,112 And they get it. 333 00:21:55,147 --> 00:21:56,347 WlKELSKl: That's the signal! 334 00:21:56,381 --> 00:21:57,648 TAYLOR: That's fantastic! 335 00:21:57,683 --> 00:22:02,320 [cheering] 336 00:22:04,356 --> 00:22:07,858 [laughing] 337 00:22:14,132 --> 00:22:18,269 TAYLOR: lt was incredible! lt was unbelievable! 338 00:22:18,303 --> 00:22:21,672 We got Big Boy out there about 15 miles! 339 00:22:23,809 --> 00:22:25,343 NARRATOR: There's one last step. 340 00:22:25,377 --> 00:22:27,778 They need to find Big Boy on the ground 341 00:22:27,813 --> 00:22:30,081 to identify his stopover point 342 00:22:30,115 --> 00:22:33,250 and find out if he's still in good condition. 343 00:22:33,285 --> 00:22:34,852 WlKELSKl: That's three miles out there. 344 00:22:34,886 --> 00:22:36,020 TAYLOR: Yeah. 345 00:22:36,054 --> 00:22:38,856 NARRATOR: They follow Big Boy's radio signal. 346 00:22:40,692 --> 00:22:43,094 Weaker. 347 00:22:43,128 --> 00:22:44,228 Stronger. 348 00:22:44,262 --> 00:22:48,366 WlKELSKl: ln a few hundred meters, l think we should take a right. 349 00:22:48,400 --> 00:22:51,335 [static] 350 00:22:52,371 --> 00:22:54,672 NARRATOR: Weaker again. 351 00:22:54,706 --> 00:22:57,108 WlKELSKl: No, that's not good. 352 00:22:57,142 --> 00:23:00,745 Maybe we should have gone left and then go north, l don't know. 353 00:23:00,779 --> 00:23:03,147 TAYLOR: Big Boy's moved out of town. 354 00:23:05,817 --> 00:23:08,352 WlKELSKl: There it is, l've got a signal. 355 00:23:08,387 --> 00:23:10,521 Yes! 356 00:23:10,555 --> 00:23:12,423 Okay, now we get it. 357 00:23:22,868 --> 00:23:26,504 WlKELSKl: On this side or the other side? 358 00:23:26,538 --> 00:23:30,207 TAYLOR: lt's not appropriate for him to say, "Come to me, Big Boy." 359 00:23:31,843 --> 00:23:34,478 WlKELSKl: Hey! Here he is! 360 00:23:34,513 --> 00:23:36,614 That's it! 361 00:23:36,648 --> 00:23:37,882 [laughing] 362 00:23:37,916 --> 00:23:39,083 TAYLOR: Fantastic! 363 00:23:39,117 --> 00:23:40,451 WlKELSKl: Yes! 364 00:23:40,485 --> 00:23:42,319 TAYLOR: Fantastic! All right! 365 00:23:42,354 --> 00:23:43,988 Good for you! 366 00:23:45,924 --> 00:23:50,928 NARRATOR: A scientific breakthrough, the first test of its kind. 367 00:23:50,962 --> 00:23:54,865 Big Boy is found in perfect condition. 368 00:23:54,900 --> 00:23:56,434 WlKELSKl: lt's really perfect. 369 00:23:56,468 --> 00:23:58,502 TAYLOR: Yeah, this antenna is not an impediment at all. 370 00:23:58,537 --> 00:23:59,203 WlKELSKl: No, no. 371 00:23:59,237 --> 00:24:00,471 TAYLOR: Hot damn... 372 00:24:00,505 --> 00:24:02,540 [laughing] 373 00:24:02,574 --> 00:24:04,375 hot damn! 374 00:24:06,178 --> 00:24:08,879 NARRATOR: The technology works, 375 00:24:08,914 --> 00:24:13,117 and the future for these insects as well as countless other animals 376 00:24:13,151 --> 00:24:15,820 may soon be the better for it. 377 00:24:15,854 --> 00:24:19,023 TAYLOR: Big Boy is ready to go, go to Wisconsin, 378 00:24:19,057 --> 00:24:20,825 find a girlfriend, there he goes. 379 00:24:20,859 --> 00:24:22,193 WlKELSKl: Yeah. 380 00:24:22,227 --> 00:24:24,094 TAYLOR: There he goes, all right! 381 00:24:24,129 --> 00:24:26,831 And look it, he's going northeast, he headed out that way. 382 00:24:26,865 --> 00:24:28,666 Right along the tree line, northeast. 383 00:24:28,700 --> 00:24:32,369 WlKELSKl: A lot of people complain that it's hard to discover things these days 384 00:24:32,404 --> 00:24:33,504 because everything's known. 385 00:24:33,538 --> 00:24:35,539 Absolutely not! 386 00:24:35,574 --> 00:24:36,607 Everything's new. 387 00:24:36,641 --> 00:24:40,244 Every time we look at it, we see something new here. 388 00:24:43,048 --> 00:24:48,452 NARRATOR: Taylor now has a new tool in which to continue his life's work. 389 00:24:51,756 --> 00:24:55,392 TAYLOR: l watch this population go up, and l watch it go down. 390 00:24:55,427 --> 00:24:59,296 l watch its life and death struggles all of the time. 391 00:24:59,331 --> 00:25:03,567 l'm so intimately attached and involved with this butterfly. 392 00:25:04,369 --> 00:25:06,804 And l don't know how to explain it any other way. 393 00:25:06,838 --> 00:25:10,407 lt's just what l am, 394 00:25:10,442 --> 00:25:13,444 and that's about all l can say about it. 395 00:25:18,316 --> 00:25:21,852 NARRATOR: Migration is seldom attempted alone. 396 00:25:21,887 --> 00:25:25,289 But there's more than safety in numbers. 397 00:25:30,061 --> 00:25:36,600 For mathematical ecologist John Fryxell, migration is math in motion. 398 00:25:38,703 --> 00:25:43,040 Where we see animals, he sees mathematical patterns. 399 00:25:43,074 --> 00:25:45,809 And he's using these patterns to unlock the key 400 00:25:45,844 --> 00:25:48,846 to wildebeest survival and migration. 401 00:25:50,015 --> 00:25:52,449 FRYXELL: l think migration is kind of a theme in my life. 402 00:25:52,484 --> 00:25:55,619 There's just something about mobility that fascinates me. 403 00:25:55,654 --> 00:25:57,755 The urge to try and predict patterns of movement 404 00:25:57,789 --> 00:26:00,224 to me is just really intriguing. 405 00:26:01,726 --> 00:26:05,329 NARRATOR: ln the Serengeti grasslands of Tanzania, 406 00:26:05,363 --> 00:26:09,300 wildebeest are on their 300-mile journey. 407 00:26:12,270 --> 00:26:17,408 This annual event is among the great natural spectacles on the planet, 408 00:26:17,442 --> 00:26:20,477 as herds of zebra, gazelle and wildebeest 409 00:26:20,512 --> 00:26:24,515 chase the rain and the grass it nurtures. 410 00:26:28,386 --> 00:26:32,890 But the wildebeest pay a hefty toll... 411 00:26:32,924 --> 00:26:36,393 five out of six young don't make it. 412 00:26:47,305 --> 00:26:50,541 And yet the herd is a million strong. 413 00:26:53,078 --> 00:26:56,246 Fryxell is determined to figure out how‒ 414 00:26:56,281 --> 00:27:00,451 despite these odds‒ the herd thrives. 415 00:27:03,722 --> 00:27:08,626 He begins by observing the wildebeest behavior from the air. 416 00:27:11,696 --> 00:27:15,366 From up here, he can see the patterns of the herds. 417 00:27:15,400 --> 00:27:20,004 FRYXELL: We can see a hyena over there heading over to the track. 418 00:27:20,038 --> 00:27:24,842 Certainly there's some complex dynamics within the whole herd of wildebeest. 419 00:27:24,876 --> 00:27:26,677 Well, the interesting thing during the migration 420 00:27:26,711 --> 00:27:30,014 is it's a series of individuals, one after the other, 421 00:27:30,048 --> 00:27:34,551 following blindly behind the movement of a key individual. 422 00:27:34,586 --> 00:27:35,886 l mean, this is, you know, really interesting, 423 00:27:35,920 --> 00:27:38,188 this kind of streaming behavior of the wildebeest, 424 00:27:38,223 --> 00:27:39,990 you know, going forward. 425 00:27:43,061 --> 00:27:46,597 Clearly there are some individuals that are at the front of the line. 426 00:27:46,631 --> 00:27:48,032 The behavior of some leaders 427 00:27:48,066 --> 00:27:49,533 gets translated to the rest of the group, 428 00:27:49,567 --> 00:27:52,803 and then the group behaves like a super organism. 429 00:27:54,572 --> 00:27:57,041 NARRATOR: Wildebeest as super organism‒ 430 00:27:57,075 --> 00:28:00,811 individuals affecting the behavior of the whole. 431 00:28:02,647 --> 00:28:04,715 Fryxell then looks at what forces 432 00:28:04,749 --> 00:28:08,752 shape the migratory path of this super organism. 433 00:28:10,255 --> 00:28:15,559 He suspects the key to why they survive in such great numbers is here‒ 434 00:28:15,593 --> 00:28:17,961 starting with an insect. 435 00:28:19,998 --> 00:28:23,100 The dung beetle thrives on wildebeest manure, 436 00:28:23,134 --> 00:28:26,804 which it collects into balls and stores underground, 437 00:28:26,838 --> 00:28:30,240 fertilizing the soil... 438 00:28:30,275 --> 00:28:33,844 allowing more wildebeest to graze. 439 00:28:35,380 --> 00:28:38,449 Millions of mouths mow the grass, 440 00:28:38,483 --> 00:28:43,721 keeping trees in check, but allowing brush to grow. 441 00:28:45,690 --> 00:28:51,862 Forming the perfect cover for predators that eat wildebeest. 442 00:28:54,399 --> 00:28:58,135 lt all leads, in the end, to the predators. 443 00:28:58,169 --> 00:29:00,938 Fryxell believes predators‒ more than anything‒ 444 00:29:00,972 --> 00:29:03,540 shape the herd's patterns. 445 00:29:07,545 --> 00:29:11,048 And his team takes a closer look at the lioness. 446 00:29:11,082 --> 00:29:12,349 MAN: Okay. 447 00:29:12,383 --> 00:29:14,384 [fires rifle] 448 00:29:21,693 --> 00:29:26,597 FRYXELL: Nine, so now we move to the upper right canine. 449 00:29:27,465 --> 00:29:32,136 NARRATOR: The GPS on the collar will allow the team to track its movement. 450 00:29:35,673 --> 00:29:40,878 An accelerometer records her every start, stop and speed, 451 00:29:40,912 --> 00:29:48,152 which tells when the hunter rests, prowls or takes to the chase. 452 00:29:49,354 --> 00:29:52,222 FRYXELL: Five, six, seven wildebeest... 453 00:29:52,257 --> 00:29:54,625 NARRATOR: Using on-site observations... 454 00:29:54,659 --> 00:29:56,026 FRYXELL: ...21 wildebeest. 455 00:29:56,060 --> 00:30:00,464 NARRATOR: ...data from collared predators and collared wildebeests, 456 00:30:00,498 --> 00:30:02,766 Fryxell can build mathematical models 457 00:30:02,801 --> 00:30:06,737 that predict the behavior of predator and prey. 458 00:30:08,406 --> 00:30:09,907 lt reads like a video game 459 00:30:09,941 --> 00:30:14,678 where he can create different scenarios between lions and wildebeest. 460 00:30:16,581 --> 00:30:21,418 First, Fryxell conjures up wildebeests that do not herd. 461 00:30:23,021 --> 00:30:27,057 He spreads them out like marbles over the landscape. 462 00:30:28,359 --> 00:30:31,562 Then he lets a simulated lion loose. 463 00:30:33,031 --> 00:30:38,068 FRYXELL: There's a kill, and another kill. 464 00:30:38,102 --> 00:30:43,407 And the net result is that it's very easy for the lion to encounter fresh prey, 465 00:30:43,441 --> 00:30:45,375 so with that very high density of prey, 466 00:30:45,410 --> 00:30:46,810 you see the lion doesn't even have to go very far 467 00:30:46,845 --> 00:30:49,179 before it finds a new meal. 468 00:30:52,851 --> 00:30:57,054 NARRATOR: ln this model, the wildebeest do not stand a chance. 469 00:31:00,124 --> 00:31:05,662 The next simulation more closely models a typical herd's behavior. 470 00:31:05,697 --> 00:31:08,332 FRYXELL: Grouping together creates great big vacant areas 471 00:31:08,366 --> 00:31:11,535 that aren't very efficient for the lion to search in. 472 00:31:11,569 --> 00:31:13,804 NARRATOR: Here, the wildebeest evade predators 473 00:31:13,838 --> 00:31:19,776 by grouping together and forming what he calls holes in the landscape, 474 00:31:19,811 --> 00:31:24,248 vast areas where a lion can't see a wildebeest. 475 00:31:27,185 --> 00:31:31,088 The super organism then goes a step further: 476 00:31:31,122 --> 00:31:34,825 the holes in the landscape move. 477 00:31:34,859 --> 00:31:37,494 FRYXELL: Well, when you're the best meal on four hooves, 478 00:31:37,528 --> 00:31:40,664 the best thing you can do is be unpredictable. 479 00:31:40,698 --> 00:31:42,032 The last thing you want to be 480 00:31:42,066 --> 00:31:45,168 is a meal where the lions expect you to be. 481 00:31:47,138 --> 00:31:49,239 NARRATOR: Lions know when seasonal herds 482 00:31:49,274 --> 00:31:51,642 pass through their territory, 483 00:31:51,676 --> 00:31:55,379 but they won't know exactly where to find them. 484 00:31:55,413 --> 00:31:58,849 FRYXELL: So we can see this on this map of the Serengeti ecosystem, 485 00:31:58,883 --> 00:32:02,586 where the bright colors signify really high densities of animals, 486 00:32:02,620 --> 00:32:07,224 large herds that are shifting without any kind of predictable pattern 487 00:32:07,258 --> 00:32:09,559 across the landscape from month to month. 488 00:32:09,594 --> 00:32:11,528 Now imagine that you're a lion or hyena 489 00:32:11,562 --> 00:32:13,931 trying to make a living in that kind of landscape. 490 00:32:13,965 --> 00:32:15,499 lt's virtually impossible for you to know 491 00:32:15,533 --> 00:32:18,835 what would be the best place for you to set up a territory. 492 00:32:20,905 --> 00:32:23,040 NARRATOR: The herd as super organism, 493 00:32:23,074 --> 00:32:25,943 and the surprisingly random nature of its movement, 494 00:32:25,977 --> 00:32:27,744 keep a predator guessing, 495 00:32:27,779 --> 00:32:31,515 keeping the wildebeest a million strong. 496 00:32:34,852 --> 00:32:36,954 But this ingenious survival mechanism 497 00:32:36,988 --> 00:32:40,691 could never work without a large habitat. 498 00:32:43,261 --> 00:32:46,129 And large habitats are increasingly rare 499 00:32:46,164 --> 00:32:50,434 as humans encroach on wild spaces. 500 00:32:53,237 --> 00:32:56,139 For many of the world's migratory animals, 501 00:32:56,174 --> 00:32:59,409 this is the main threat to their survival. 502 00:33:06,651 --> 00:33:10,153 ln Mali, West Africa, the desert elephant 503 00:33:10,188 --> 00:33:13,957 once roamed vast distances unimpeded. 504 00:33:16,060 --> 00:33:20,330 Now the last animals of their kind are under threat. 505 00:33:23,201 --> 00:33:27,270 Tracker El Mehdi Doumbia and biologist Jake Wall 506 00:33:27,305 --> 00:33:30,007 from the organization Save the Elephants 507 00:33:30,041 --> 00:33:35,145 have collared nine of the 350 elephants here. 508 00:33:35,179 --> 00:33:37,514 The more they can learn about the herd's habits... 509 00:33:37,548 --> 00:33:39,383 WALL: Good, fresh tracks. 510 00:33:39,417 --> 00:33:44,154 NARRATOR: ...the better they will be able to protect their migratory routes. 511 00:33:44,188 --> 00:33:46,323 WALL: These elephants don't give us a moment to rest, 512 00:33:46,357 --> 00:33:47,724 they keep moving, 513 00:33:47,759 --> 00:33:49,960 we keep having to work really, really hard 514 00:33:49,994 --> 00:33:51,762 to try and find them, 515 00:33:51,796 --> 00:33:56,333 and, even with the tracking data, it's not an easy job. 516 00:33:56,367 --> 00:33:58,935 NARRATOR: The only way the Mali elephants can survive 517 00:33:58,970 --> 00:34:02,439 is to move. 518 00:34:02,473 --> 00:34:08,078 They walk endlessly over a home range of over 12,000 square miles 519 00:34:08,112 --> 00:34:11,114 in the harsh heat of the Sahel. 520 00:34:13,017 --> 00:34:17,854 No other elephants travel farther in search of food and water. 521 00:34:20,758 --> 00:34:25,562 During the dry season, they end up here. 522 00:34:25,596 --> 00:34:31,268 Lake Banzena is one of the few places to find water year round. 523 00:34:38,109 --> 00:34:42,446 The herds linger until distant rains begin. 524 00:34:54,192 --> 00:34:57,260 Elephants can hear rain fall vast distances away 525 00:34:57,295 --> 00:35:00,664 because of its low infrasonic signal. 526 00:35:02,467 --> 00:35:08,338 Then, within 24 hours, they go to where the rain is. 527 00:35:08,372 --> 00:35:11,908 And this year, water is most critical. 528 00:35:11,943 --> 00:35:16,146 lt is the worst drought in 26 years. 529 00:35:21,119 --> 00:35:23,587 The herd must move fast, 530 00:35:23,621 --> 00:35:27,224 because between the lake and the next stopover point 531 00:35:27,258 --> 00:35:31,995 lies 60 miles of desert... 532 00:35:32,029 --> 00:35:36,333 and a big obstacle: the Gandamia Plateau. 533 00:35:38,336 --> 00:35:41,571 There's just one way through: 534 00:35:41,606 --> 00:35:45,542 la portes des elephants, the elephants' door— 535 00:35:45,576 --> 00:35:50,213 a cut in the mountain the herds have been using for centuries. 536 00:35:55,086 --> 00:35:59,523 lt's also a place with increasing human settlement... 537 00:35:59,557 --> 00:36:01,091 and where elephants compete 538 00:36:01,125 --> 00:36:04,761 with herders and their animals for water. 539 00:36:07,598 --> 00:36:09,900 These images capture a dramatic scene 540 00:36:09,934 --> 00:36:12,702 as villagers and a Save the Elephants team 541 00:36:12,737 --> 00:36:17,941 desperately try to rescue a teenage female and three juveniles. 542 00:36:20,778 --> 00:36:25,515 They fell, one after another, into a man-made well searching for water. 543 00:36:27,585 --> 00:36:30,020 The older elephant crushed and killed a younger one 544 00:36:30,054 --> 00:36:33,690 during the three-day ordeal. 545 00:36:33,724 --> 00:36:38,828 These tragedies happen as humans settle on ancient elephant paths. 546 00:36:44,168 --> 00:36:48,371 But 3,000 miles to the east, in the grasslands of Kenya... 547 00:36:48,406 --> 00:36:49,472 lAlN DOUGLAS-HAMlLTON: l am just going to put a little bit of water 548 00:36:49,507 --> 00:36:51,041 on the back without splashing. 549 00:36:51,075 --> 00:36:52,976 DABALLEN: Don't step on the ears, please. 550 00:36:53,010 --> 00:36:56,446 NARRATOR: ...a solution is being tested. 551 00:36:56,480 --> 00:37:00,750 Biologist lain Douglas-Hamilton has gained near legendary status 552 00:37:00,785 --> 00:37:04,321 for being the African elephant's custodian. 553 00:37:04,355 --> 00:37:06,223 DOUGLAS-HAMlLTON: You don't think that's too loose? 554 00:37:06,257 --> 00:37:07,757 We're collaring elephants 555 00:37:07,792 --> 00:37:11,995 because we believe that by understanding their movements, 556 00:37:12,029 --> 00:37:14,598 we can understand their decisions. 557 00:37:14,632 --> 00:37:20,737 And if we understand their decisions, we understand what they need. 558 00:37:20,771 --> 00:37:25,475 Elephants are at a tough time now, and we have to plan for their future. 559 00:37:27,245 --> 00:37:30,614 NARRATOR: Over the years, Douglas-Hamilton has witnessed first hand 560 00:37:30,648 --> 00:37:35,051 the disastrous consequences of human-elephant conflict. 561 00:37:36,487 --> 00:37:41,825 Poaching for ivory tusks was once the chief killer of elephants. 562 00:37:44,328 --> 00:37:49,065 Today, it's farmers who protect their crops. 563 00:37:54,472 --> 00:37:56,673 Douglas-Hamilton with his wife Oria 564 00:37:56,707 --> 00:37:59,843 founded Save the Elephants 40 years ago 565 00:37:59,877 --> 00:38:05,782 to study and protect this severely endangered species. 566 00:38:05,816 --> 00:38:08,151 This rustic outpost is the repository 567 00:38:08,185 --> 00:38:10,320 of the organization's studies on elephants 568 00:38:10,354 --> 00:38:13,423 from all over the African continent... 569 00:38:15,092 --> 00:38:17,861 information that scientists throughout the world 570 00:38:17,895 --> 00:38:19,929 have come to rely on. 571 00:38:19,964 --> 00:38:21,531 DOUGLAS-HAMlLTON: lt's actually a kilometer wide. 572 00:38:21,565 --> 00:38:23,400 lt's working well. 573 00:38:23,434 --> 00:38:25,802 NARRATOR: Today, the team is collaring an elephant 574 00:38:25,836 --> 00:38:29,806 with a state-of-the-art device that might save its life‒ 575 00:38:29,840 --> 00:38:34,778 a tag that sends an alert when the animal nears a farm. 576 00:38:34,812 --> 00:38:38,381 DOUGLAS-HAMlLTON: Many elephants across Africa get shot 577 00:38:38,416 --> 00:38:42,652 because they cause damage to human property, 578 00:38:42,687 --> 00:38:47,324 to crops, to livelihoods, and indeed they kill people. 579 00:38:47,358 --> 00:38:52,362 And you want every high-tech option that you can deploy. 580 00:38:58,069 --> 00:39:00,870 NARRATOR: lain Douglas-Hamilton searches for a herd, 581 00:39:00,905 --> 00:39:03,206 scanning the landscape by air 582 00:39:03,240 --> 00:39:07,444 while researcher David Daballen's team is on the ground. 583 00:39:11,349 --> 00:39:13,717 DOUGLAS-HAMlLTON: David, David! 584 00:39:13,751 --> 00:39:14,884 DABALLEN: Sorry, lain? 585 00:39:14,919 --> 00:39:16,119 DOUGLAS-HAMlLTON: Where l am circling 586 00:39:16,153 --> 00:39:20,423 there are two groups of elephants tightly under the trees. 587 00:39:22,159 --> 00:39:24,327 DABALLEN: He has found them in a perfect place. 588 00:39:24,362 --> 00:39:25,395 We don't want to lose them, 589 00:39:25,429 --> 00:39:27,797 because they are not quite often at the moment around. 590 00:39:27,832 --> 00:39:31,634 We want to take the opportunity to dart them, put a collar, 591 00:39:31,669 --> 00:39:33,903 because we know that from our past experience 592 00:39:33,938 --> 00:39:36,306 they will defend so much. 593 00:39:36,340 --> 00:39:37,440 And if we have four cars 594 00:39:37,475 --> 00:39:40,210 we can position ourselves in different positions 595 00:39:40,244 --> 00:39:41,711 to make sure that the females 596 00:39:41,746 --> 00:39:44,647 will not see the female that has gone down. 597 00:39:49,120 --> 00:39:53,223 NARRATOR: They identify the female to be collared. 598 00:39:53,257 --> 00:39:55,358 DABALLEN: Dart in. 599 00:40:04,668 --> 00:40:06,936 She's down, she's down! 600 00:40:06,971 --> 00:40:08,204 Let's get a good position. 601 00:40:08,239 --> 00:40:10,206 Drive. 602 00:40:12,243 --> 00:40:15,311 Drive, drive! 603 00:40:23,854 --> 00:40:25,121 NARRATOR: Once she's unconscious, 604 00:40:25,156 --> 00:40:30,160 Daballen has only 20 minutes to attach the collar. 605 00:40:30,194 --> 00:40:34,130 The anesthesia makes the trunk muscles go slack‒ 606 00:40:34,165 --> 00:40:37,967 a stick will keep her airway open. 607 00:40:38,002 --> 00:40:39,536 This particular collar will do 608 00:40:39,570 --> 00:40:42,806 what Douglas-Hamilton once only dreamed of: 609 00:40:42,840 --> 00:40:46,643 lt will allow an elephant to communicate with him. 610 00:40:48,078 --> 00:40:52,515 The collar sends its alert to a cell phone via text message. 611 00:40:54,385 --> 00:40:59,923 This high-tech innovation is called geofencing. 612 00:40:59,957 --> 00:41:02,926 When an elephant crosses a virtual fence line, 613 00:41:02,960 --> 00:41:07,630 the GPS unit in the collar sends an SMS or text message 614 00:41:07,665 --> 00:41:10,133 to a server in Nairobi. 615 00:41:10,167 --> 00:41:13,870 The server then sends text alerts to a list of recipients 616 00:41:13,904 --> 00:41:16,105 who can quickly intercept the herd 617 00:41:16,140 --> 00:41:19,909 before it reaches a farm or human settlement. 618 00:41:21,912 --> 00:41:24,280 DABALLEN: Get in the car! 619 00:41:35,459 --> 00:41:39,395 NARRATOR: The female awakes groggy but unharmed‒ 620 00:41:39,430 --> 00:41:42,098 the collar fits perfectly. 621 00:41:46,470 --> 00:41:48,938 She will blow out the stick in her trunk, 622 00:41:48,973 --> 00:41:52,742 but for now it assures her an open airway. 623 00:41:54,845 --> 00:41:57,881 DOUGLAS-HAMlLTON: Sometimes when you have dense agriculture, 624 00:41:57,915 --> 00:41:59,148 the best thing you can do 625 00:41:59,183 --> 00:42:02,585 is to separate the people from the elephants. 626 00:42:02,620 --> 00:42:04,954 When an elephant crosses a certain boundary, 627 00:42:04,989 --> 00:42:07,123 we get an alarm to be set off, 628 00:42:07,157 --> 00:42:10,460 and it gets sent to us on a mobile telephone, 629 00:42:10,494 --> 00:42:15,765 which allows us to plan much better how to cope with the crop raiding. 630 00:42:15,799 --> 00:42:18,868 This is really cutting-edge stuff. 631 00:42:21,672 --> 00:42:25,909 NARRATOR: Geofencing is still in the testing phase, 632 00:42:25,943 --> 00:42:30,013 but Douglas-Hamilton believes this is the future. 633 00:42:32,349 --> 00:42:35,318 But there is a terrible setback. 634 00:42:37,755 --> 00:42:43,993 A torrential storm causes the banks of the Ewaso Ng'iro River to crest, 635 00:42:44,028 --> 00:42:47,664 creating the worst flood in memory. 636 00:42:50,200 --> 00:42:55,004 Save the Elephants' research center is all but gone. 637 00:42:58,342 --> 00:43:02,378 Most of the buildings and much of the decade's long research 638 00:43:02,413 --> 00:43:04,280 are missing. 639 00:43:06,517 --> 00:43:09,385 DOUGLAS-HAMlLTON: Well, this flood has had a terrible effect on our work. 640 00:43:09,420 --> 00:43:10,520 First of all, it's caused 641 00:43:10,554 --> 00:43:13,489 hundreds of thousands of dollars worth of damage. 642 00:43:13,524 --> 00:43:16,492 l don't know how we're gonna get the money to rebuild, 643 00:43:16,527 --> 00:43:21,531 but we've also lost some data, which is particularly precious to us. 644 00:43:26,870 --> 00:43:29,305 NARRATOR: But Douglas-Hamilton and his team are determined 645 00:43:29,340 --> 00:43:33,009 to dig themselves out and start over again. 646 00:43:33,043 --> 00:43:34,944 DOUGLAS-HAMlLTON: We've got to carry on. 647 00:43:34,979 --> 00:43:38,247 Our mission is to secure a future for elephants. 648 00:43:38,282 --> 00:43:41,284 l've been working on elephants for 43 years, 649 00:43:41,318 --> 00:43:43,720 and it's all to save the elephants. 650 00:43:43,754 --> 00:43:45,922 So we're not going to give up on that. 651 00:43:50,027 --> 00:43:54,197 NARRATOR: As Save the Elephants recovers, 652 00:43:54,231 --> 00:43:57,567 the Mali elephants survive the drought. 653 00:44:00,270 --> 00:44:04,841 And Douglas-Hamilton with his team will continue tracking elephants, 654 00:44:04,875 --> 00:44:08,978 working to preserve their ancient paths. 655 00:44:12,282 --> 00:44:14,717 DOUGLAS-HAMlLTON: l think the worst-case scenario 656 00:44:14,752 --> 00:44:17,086 would be a cutting of the migration routes, 657 00:44:17,121 --> 00:44:20,690 completely cut off from their water supplies. 658 00:44:20,724 --> 00:44:23,426 lt would then only be a matter of time 659 00:44:23,460 --> 00:44:27,330 before the elephants had nothing to live with. 660 00:44:27,364 --> 00:44:29,832 That would be my worst-case scenario for Mali. 661 00:44:29,867 --> 00:44:33,369 But it's not going to happen. We've got to prevent it. 662 00:44:36,674 --> 00:44:40,376 NARRATOR: Working in the natural world is always a gamble. 663 00:44:40,411 --> 00:44:45,048 Science needs data, and if nature doesn't cooperate, 664 00:44:45,082 --> 00:44:50,953 data will get destroyed, eaten or swept out to sea. 665 00:44:54,758 --> 00:45:01,831 ln Patagonia, the scientists return, hoping their gamble pays off. 666 00:45:01,865 --> 00:45:07,103 The elephant seals have returned to molt after two months at sea. 667 00:45:09,807 --> 00:45:14,544 With good fortune, the five Daily Diaries will return, too. 668 00:45:16,213 --> 00:45:19,148 Flavio Quintana's team use GPS 669 00:45:19,183 --> 00:45:22,852 to find out when the tagged seals arrive... 670 00:45:24,321 --> 00:45:26,956 and where they settle on the beach. 671 00:45:28,525 --> 00:45:30,026 Over the course of a week, 672 00:45:30,060 --> 00:45:33,763 the team retrieves four out of the five tags. 673 00:45:35,199 --> 00:45:39,469 Each Daily Diary is perfectly intact. 674 00:45:43,907 --> 00:45:49,412 7,300 miles away, Rory Wilson at his lab in Swansea, Wales, 675 00:45:49,446 --> 00:45:52,749 begins to read the much anticipated story‒ 676 00:45:52,783 --> 00:45:56,519 the secrets of the seal migration. 677 00:45:56,553 --> 00:45:59,922 WlLSON: You know, you're opening the book on it for the first time, 678 00:45:59,957 --> 00:46:01,557 it's an incredible thrill. 679 00:46:01,592 --> 00:46:05,294 Stuff happens that you wouldn't believe in your wildest dreams. 680 00:46:06,497 --> 00:46:11,834 NARRATOR: First, Wilson reconstructs the movement of the seal named Mir. 681 00:46:11,869 --> 00:46:13,269 WlLSON: This is the moment 682 00:46:13,303 --> 00:46:17,974 where Mir comes off the continental shelf, the platform 683 00:46:18,008 --> 00:46:19,809 and goes down into the deep water, 684 00:46:19,843 --> 00:46:21,811 and you can actually see this in her depth traces... 685 00:46:21,845 --> 00:46:25,448 and they get deeper and deeper. 686 00:46:25,482 --> 00:46:29,218 NARRATOR: Mir's deepest dive was nearly half a mile, 687 00:46:29,253 --> 00:46:32,955 an acrobatic feeding frenzy. 688 00:46:32,990 --> 00:46:34,657 WlLSON: The animal was in free fall, 689 00:46:34,691 --> 00:46:39,128 the body was in all these extraordinary ballet-like postures. 690 00:46:39,163 --> 00:46:42,098 And you think, whoa, l never thought elephant seals did that! 691 00:46:42,132 --> 00:46:44,867 NARRATOR: Then Wilson looks at how the seal swam 692 00:46:44,902 --> 00:46:47,904 as it traveled great distances. 693 00:46:47,938 --> 00:46:51,541 He compares its sway— side-to-side movement... 694 00:46:51,575 --> 00:46:54,811 WlLSON: So these are the tail beats, and the glide, 695 00:46:54,845 --> 00:46:56,512 and the tail beat and the glide... 696 00:46:56,547 --> 00:47:00,249 NARRATOR: ...to the surge‒ vertical and horizontal position. 697 00:47:00,284 --> 00:47:03,586 WlLSON: And as the tail beats occur, the animal's pointing up, 698 00:47:03,620 --> 00:47:05,955 and when she glides, she points down. 699 00:47:05,989 --> 00:47:08,891 So up and down. 700 00:47:08,926 --> 00:47:10,426 NARRATOR: Then calculates pressure 701 00:47:10,460 --> 00:47:13,629 to determine the depth and length of her dips. 702 00:47:13,664 --> 00:47:16,599 WlLSON: And the interesting thing is she's doing exactly the same thing 703 00:47:16,633 --> 00:47:21,003 as sparrows do when they fly or some of these small birds. 704 00:47:21,038 --> 00:47:26,175 NARRATOR: To his surprise, elephant seals are behaving like birds: 705 00:47:26,210 --> 00:47:28,377 they fly underwater. 706 00:47:28,412 --> 00:47:31,714 This is how they conserve energy. 707 00:47:33,817 --> 00:47:39,689 Small birds flap their wings to gain momentum when flying up, 708 00:47:39,723 --> 00:47:43,526 and hitch a ride on the current going down. 709 00:47:48,332 --> 00:47:50,499 WlLSON: You see small birds flap, flap, flap, flap and glide down, 710 00:47:50,534 --> 00:47:51,567 flap, flap, flap and glide down, 711 00:47:51,602 --> 00:47:55,137 and that's a way of saving energy. 712 00:47:55,172 --> 00:47:58,774 An animal as big as an elephant seal does it, 713 00:47:58,809 --> 00:48:02,845 and an animal as small as a sparrow does it as well. 714 00:48:05,582 --> 00:48:09,085 NARRATOR: Both the small bird and the enormous elephant seal 715 00:48:09,119 --> 00:48:13,856 evolved to conserve energy in similar ways. 716 00:48:13,891 --> 00:48:17,059 WlLSON: Energy is critical for animals, for their survival... 717 00:48:17,094 --> 00:48:19,562 but they spend it in going out to get stuff to feed. 718 00:48:19,596 --> 00:48:23,933 So this balance of energy expenditure against energy gain 719 00:48:23,967 --> 00:48:25,534 on migrations or off them 720 00:48:25,569 --> 00:48:27,503 is something that's really critical to animals. 721 00:48:27,537 --> 00:48:30,673 And as we go gleefully through the planet 722 00:48:30,707 --> 00:48:32,275 and change everything, 723 00:48:32,309 --> 00:48:35,678 we really need to be considering that. 724 00:48:37,314 --> 00:48:41,150 NARRATOR: For the first time, we are able to witness the elephant seal 725 00:48:41,184 --> 00:48:43,953 as it journeys through the ocean. 726 00:48:46,089 --> 00:48:47,423 WlLSON: Lovely data, aren't they? 727 00:48:47,457 --> 00:48:50,793 Really beautiful, beautiful stuff that comes out of this tag. 728 00:48:52,863 --> 00:48:55,064 NARRATOR: With inventions like the Daily Diary, 729 00:48:55,098 --> 00:48:59,035 the invisible is becoming visible. 730 00:48:59,069 --> 00:49:00,436 lt is in these details 731 00:49:00,470 --> 00:49:04,407 where the true secrets of the elephant seal reside... 732 00:49:06,643 --> 00:49:08,978 revealing how this great wanderer 733 00:49:09,012 --> 00:49:13,416 can survive its long trek through the southern seas. 734 00:49:16,486 --> 00:49:19,388 Wilson and his colleagues won't stop here. 735 00:49:19,423 --> 00:49:21,357 They will continue to test. 736 00:49:21,391 --> 00:49:22,892 WlKELSKl: Wow, it's really taking off. 737 00:49:22,926 --> 00:49:24,260 TAYLOR: lt's really catching the wind. 738 00:49:24,294 --> 00:49:25,328 NARRATOR: lnvent... 739 00:49:25,362 --> 00:49:28,864 DOUGLAS-HAMlLTON: We get an alarm to be set off. 740 00:49:28,899 --> 00:49:32,001 NARRATOR: ...break new ground. 741 00:49:32,035 --> 00:49:37,373 And with each technological advance, the science of the great migrations 742 00:49:37,407 --> 00:49:41,844 gives us a larger understanding of our world. 743 00:49:43,413 --> 00:49:47,083 WlLSON: lt's a little bit frustrating that the Daily Diary is still as big as it is. 744 00:49:47,117 --> 00:49:49,952 l still want it to be smaller, l want it on swifts, 745 00:49:49,987 --> 00:49:51,487 but there's no limit to that. 746 00:49:51,521 --> 00:49:54,123 When are you going to stop? Ants, you know? 61686

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