1 00:00:25,859 --> 00:00:28,278 {\an8}Over the last three years, 2 00:00:28,278 --> 00:00:31,990 the Earthsounds team has captured the sounds of the natural world 3 00:00:32,491 --> 00:00:37,162 across all seven continents like never before. 4 00:00:38,497 --> 00:00:39,915 That's a lovely rumble. 5 00:00:41,875 --> 00:00:46,255 But these recordings tell a bigger story. 6 00:00:47,214 --> 00:00:52,010 As our planet faces climate change and is losing wildlife... 7 00:00:54,137 --> 00:00:56,682 we're discovering that listening to nature... 8 00:00:58,809 --> 00:01:00,227 Wow, this is brilliant. 9 00:01:01,353 --> 00:01:05,399 ...could provide vital clues to help us protect it. 10 00:01:07,401 --> 00:01:09,611 In this special episode... 11 00:01:09,611 --> 00:01:11,738 There it is. Yeah. Right there. 12 00:01:14,241 --> 00:01:20,998 ...we follow scientists who are using sound in revolutionary ways... 13 00:01:23,417 --> 00:01:26,086 to help save endangered species 14 00:01:27,129 --> 00:01:29,882 and our wildest places. 15 00:01:39,850 --> 00:01:43,437 The pioneering idea of using sound for conservation 16 00:01:44,563 --> 00:01:50,360 started 50 years ago with sound recording legend Bernie Krause. 17 00:01:53,030 --> 00:01:54,573 And we're recording. 18 00:01:56,658 --> 00:02:00,662 Bernie has been returning to Sugarloaf Ridge State Park in California 19 00:02:00,662 --> 00:02:03,290 at the same time each spring 20 00:02:04,249 --> 00:02:08,586 to capture a sonic snapshot of the entire habitat. 21 00:02:08,586 --> 00:02:10,881 What we're doing is recording the dawn chorus 22 00:02:10,881 --> 00:02:13,133 and the dawn chorus is the time of day 23 00:02:13,133 --> 00:02:17,679 when the animals really express themselves at their most vital. 24 00:02:20,432 --> 00:02:22,726 It's a magical moment. 25 00:02:24,561 --> 00:02:27,064 Well, right now I'm hearing California quail. 26 00:02:29,358 --> 00:02:30,526 Song sparrows. 27 00:02:33,529 --> 00:02:38,450 I'm hearing a pileated woodpecker knocking in the background. 28 00:02:38,450 --> 00:02:40,202 And let's see what else? 29 00:02:40,202 --> 00:02:41,995 I hear my stomach rumbling. 30 00:02:45,040 --> 00:02:49,419 These natural sounds are known as a biophony, 31 00:02:50,045 --> 00:02:52,214 the richness of a soundscape. 32 00:02:52,214 --> 00:02:56,343 This biophony is the sound of the natural world. It's its voice. 33 00:02:56,343 --> 00:02:58,095 When it sounds robust, 34 00:02:58,095 --> 00:03:00,931 when all the animals have a place in the choir, 35 00:03:02,307 --> 00:03:03,642 it's a healthy habitat. 36 00:03:03,642 --> 00:03:05,853 When they don't, it's not. 37 00:03:11,817 --> 00:03:14,069 The importance of Bernie's recordings 38 00:03:14,069 --> 00:03:18,907 became clear when disaster struck California's forests. 39 00:03:18,907 --> 00:03:23,829 Well, in October 2017, there was a huge fire. 40 00:03:25,914 --> 00:03:30,294 California's Thomas Fire already more than 270 square miles. 41 00:03:31,670 --> 00:03:35,132 And 70% of this part was burned. 42 00:03:37,134 --> 00:03:39,344 The destruction was extreme. 43 00:03:42,639 --> 00:03:46,393 But clues that the forests were already suffering from a warming climate 44 00:03:47,269 --> 00:03:51,815 can be heard in the bird song years before the fires hit. 45 00:03:51,815 --> 00:03:55,694 Right now, we're looking at soundscapes from Sugarloaf Ridge State Park 46 00:03:55,694 --> 00:03:58,780 and what we have on the screen is a spectrogram, 47 00:03:58,780 --> 00:04:01,074 a graphic illustration of sound. 48 00:04:01,074 --> 00:04:04,995 And what I'm showing is the change that's occurred over time 49 00:04:04,995 --> 00:04:07,122 as a result of climate change. 50 00:04:09,541 --> 00:04:14,922 When Bernie's study started, Sugarloaf Ridge was full of life. 51 00:04:21,512 --> 00:04:25,557 In 1993, the density and diversity of the birds is fabulous. 52 00:04:29,019 --> 00:04:32,773 There are probably 20, maybe 25, different species of birds. 53 00:04:34,608 --> 00:04:37,152 But as California's climate warmed up, 54 00:04:37,736 --> 00:04:39,655 the bird song started to change. 55 00:04:39,655 --> 00:04:44,618 When we move to 2014, the birds have dropped off precipitously. 56 00:04:49,790 --> 00:04:54,294 Now, Bernie was picking up only a quarter of what was there before. 57 00:04:56,755 --> 00:04:58,966 Hardly hear anything at all. 58 00:05:01,552 --> 00:05:03,804 This was an early warning 59 00:05:03,804 --> 00:05:06,515 that the forests were dangerously heating up 60 00:05:07,015 --> 00:05:09,393 and worse was to come. 61 00:05:10,853 --> 00:05:15,399 So, when we get to 2015, things have really changed. 62 00:05:15,399 --> 00:05:19,862 We have finally come to what I call a silent spring. 63 00:05:25,868 --> 00:05:28,412 There are almost no birds. 64 00:05:33,417 --> 00:05:36,962 It's the first time in my life I've ever heard a silent spring. 65 00:05:39,798 --> 00:05:45,721 We're just losing all of this wonderful orchestra. 66 00:05:47,556 --> 00:05:51,810 Eight of the ten hottest years ever recorded in California 67 00:05:52,394 --> 00:05:54,563 have been in the last decade. 68 00:05:58,984 --> 00:06:02,196 But Bernie's studies show if we listen to nature, 69 00:06:03,488 --> 00:06:07,659 we can hear powerful clues about the health of our wild places. 70 00:06:09,203 --> 00:06:14,917 After 50 years of this work, I'm just seeing and hearing less and less. 71 00:06:14,917 --> 00:06:16,960 And it's not because I'm losing my hearing. 72 00:06:17,586 --> 00:06:20,797 It's because these things are going really fast, 73 00:06:21,673 --> 00:06:24,760 and we've got to figure out a way to protect that. 74 00:06:30,432 --> 00:06:34,311 One solution could lie in taking Bernie's approach 75 00:06:35,812 --> 00:06:41,318 and supersizing it in the wildest places on the planet. 76 00:06:44,404 --> 00:06:49,701 Tropical forests are home to more endangered species than anywhere else. 77 00:06:55,582 --> 00:07:02,422 But each year over 20 million acres of forest are cut down, 78 00:07:02,422 --> 00:07:05,092 putting animals under increasing pressure. 79 00:07:09,721 --> 00:07:12,307 I think we may have found our tree. 80 00:07:12,307 --> 00:07:13,642 - That one? - Yeah. 81 00:07:16,311 --> 00:07:17,938 To help protect them, 82 00:07:17,938 --> 00:07:23,610 conservation group Rainforest Connection is taking sound recording to another level 83 00:07:24,570 --> 00:07:27,948 in a new branch of acoustic science. 84 00:07:27,948 --> 00:07:30,868 Bioacoustics is the study of species through sound. 85 00:07:31,451 --> 00:07:33,704 Majority of the species are vocal. 86 00:07:34,204 --> 00:07:38,750 Being able to listen and understand why they're vocalizing, 87 00:07:38,750 --> 00:07:41,420 it's a really amazing way of ultimately conserving them. 88 00:07:42,629 --> 00:07:45,757 Bourhan Yassin and Kris Harmon 89 00:07:45,757 --> 00:07:50,095 want to track Puerto Rico's noisiest forest residents, 90 00:07:50,762 --> 00:07:54,433 especially one of the world's rarest birds, 91 00:07:54,433 --> 00:07:56,518 the Puerto Rican parrot. 92 00:07:56,518 --> 00:07:59,730 The reason that we're monitoring the parrot, it's critically endangered. 93 00:07:59,730 --> 00:08:01,732 There are only a handful that are left, 94 00:08:01,732 --> 00:08:04,484 so it's really important to know what is going on with them. 95 00:08:05,569 --> 00:08:10,532 They plan to do this by miking up 4,000 acres 96 00:08:11,200 --> 00:08:13,493 in Rio Abajo State Forest, 97 00:08:13,493 --> 00:08:17,289 using a network of high-tech recorders called guardians. 98 00:08:18,165 --> 00:08:21,919 The guardian device is a mobile computer in the middle of the forest. 99 00:08:21,919 --> 00:08:25,172 So it has a lot of capability to not just record audio 100 00:08:25,172 --> 00:08:28,550 but also understand its surrounding and analyze the audio. 101 00:08:28,550 --> 00:08:32,554 There's a microphone that gets plugged in in the front of the box. 102 00:08:38,352 --> 00:08:41,145 To eavesdrop on the entire forest, 103 00:08:41,855 --> 00:08:44,066 the best place to position the recorders... 104 00:08:44,066 --> 00:08:45,108 Incoming. 105 00:08:50,614 --> 00:08:54,910 ...is over 100 feet up at the top of the canopy. 106 00:09:06,171 --> 00:09:07,548 Kris, can you hear me okay? 107 00:09:07,548 --> 00:09:10,300 - Yeah, I've got you. No problem. - I don't think I can go any higher. 108 00:09:10,300 --> 00:09:13,011 I have a beautiful view of the valley in front of me. 109 00:09:13,011 --> 00:09:15,597 - We'll get started on the installation. - Awesome. Good luck. 110 00:09:25,691 --> 00:09:27,776 Just doing a quick mic test on the guardian mic. 111 00:09:27,776 --> 00:09:29,570 Yeah, that came through crystal clear. 112 00:09:29,570 --> 00:09:30,821 - You're good. - Awesome. 113 00:09:30,821 --> 00:09:32,447 I think we're good to go man. 114 00:09:37,536 --> 00:09:39,997 This is the first guardian installed in Rio Abajo. 115 00:09:39,997 --> 00:09:41,081 How cool is that? 116 00:09:41,999 --> 00:09:44,543 No, that's perfect. Honestly, couldn't ask for better. 117 00:09:48,463 --> 00:09:52,009 Each device can detect sounds from up to a mile away 118 00:09:53,260 --> 00:09:58,015 and uses artificial intelligence to pick out the calls of specific animals. 119 00:10:00,851 --> 00:10:04,479 The AI is running, and we have it set to pick up I think 40 different species 120 00:10:04,479 --> 00:10:06,481 and automatically identify those. 121 00:10:06,481 --> 00:10:09,568 So instead of any of us having to go in and look for anything 122 00:10:09,568 --> 00:10:13,530 and sort of manually find the species, the model is constantly running, 123 00:10:13,530 --> 00:10:16,074 and so, we'll have output really 24-7. 124 00:10:18,076 --> 00:10:19,745 As well as Puerto Rico, 125 00:10:19,745 --> 00:10:24,124 this technology is up and running in 35 countries, 126 00:10:25,042 --> 00:10:29,213 constantly listening for the calls of over 3,000 species. 127 00:10:34,885 --> 00:10:38,722 But the guardians can do something even more amazing. 128 00:10:41,225 --> 00:10:45,270 They can pick out the telltale sounds of illegal logging 129 00:10:46,605 --> 00:10:50,192 and send an alert to rangers on the ground. 130 00:10:50,192 --> 00:10:52,861 There is no other system, that I'm aware of, 131 00:10:52,861 --> 00:10:56,490 where within a handful of minutes you can detect a threat, 132 00:10:57,115 --> 00:11:02,621 send a message to enforcement, and have a patrol respond to that threat. 133 00:11:12,130 --> 00:11:16,051 Detecting the calls of animals and illegal logging 134 00:11:16,051 --> 00:11:19,012 in dense jungle is remarkable. 135 00:11:24,393 --> 00:11:26,061 But off the coast of Hawaii, 136 00:11:27,062 --> 00:11:30,482 cutting-edge technology is also being used 137 00:11:32,067 --> 00:11:34,945 to follow the ocean's greatest singers. 138 00:11:39,908 --> 00:11:44,746 Humpback whales are the Pacific's long-distance travelers. 139 00:11:50,127 --> 00:11:53,881 But to protect them, we need to know where they roam. 140 00:11:56,133 --> 00:11:59,469 They're known to migrate from their Hawaiian breeding grounds 141 00:11:59,469 --> 00:12:05,142 thousands of miles to their northern feeding grounds. 142 00:12:09,146 --> 00:12:13,150 But where else they travel is largely a mystery. 143 00:12:21,158 --> 00:12:23,410 All right. You guys, are you ready? 144 00:12:23,410 --> 00:12:24,828 - We're ready. - All right. 145 00:12:24,828 --> 00:12:27,080 Cool. We're ready to rock and roll here. 146 00:12:27,080 --> 00:12:28,749 So excited to do this. 147 00:12:31,418 --> 00:12:34,254 And marine biologist Beth Goodwin and her team 148 00:12:35,088 --> 00:12:37,007 are hoping to solve this... 149 00:12:37,007 --> 00:12:38,091 Oh, yeah. 150 00:12:38,759 --> 00:12:42,971 ...by tracking the humpbacks using their remarkable song. 151 00:12:47,017 --> 00:12:48,185 This is great. 152 00:12:48,185 --> 00:12:52,606 These whales are going off, they're groaning and creaking and... 153 00:12:56,693 --> 00:13:00,113 You know, when I listen to these songs, I am just in awe, 154 00:13:01,073 --> 00:13:02,324 but I'd like to know more. 155 00:13:04,243 --> 00:13:06,286 To find out where the whales travel 156 00:13:07,621 --> 00:13:10,916 means searching thousands of miles of open ocean... 157 00:13:12,793 --> 00:13:16,004 ...and conventional technology just won't work. 158 00:13:17,005 --> 00:13:19,258 We've developed tracking devices, 159 00:13:19,258 --> 00:13:21,885 tags, that you can put on the humpback whale. 160 00:13:21,885 --> 00:13:25,264 But those tags, they don't last four or five months. 161 00:13:31,436 --> 00:13:34,690 So they've come up with an ingenious sonic solution. 162 00:13:34,690 --> 00:13:36,233 Murray, I'm taking the break off. 163 00:13:37,234 --> 00:13:39,069 Going down, Europa. 164 00:13:42,906 --> 00:13:48,036 A self-propelled, acoustic probe called a Wave Glider 165 00:13:48,036 --> 00:13:51,707 that can travel across oceans for up to a year at a time. 166 00:13:53,250 --> 00:13:57,379 A Wave Glider is a two-part vehicle that has a surface component, 167 00:13:57,379 --> 00:14:00,799 and it's attached to an underwater part. 168 00:14:00,799 --> 00:14:02,176 We call it the sub. 169 00:14:02,885 --> 00:14:06,346 The sub has six set of wings or fins. 170 00:14:06,346 --> 00:14:09,433 The float's not steering, it's literally just a bobber, 171 00:14:09,433 --> 00:14:13,979 and as it bobs these wings are kind of going up and down all the time. 172 00:14:13,979 --> 00:14:18,150 And it just takes the tiniest bit of ripple in the water for it to move. 173 00:14:19,776 --> 00:14:25,782 What's really cool is we've attached a smart hydrophone underneath the sub 174 00:14:26,700 --> 00:14:32,039 so we can download and listen where the Wave Glider is and what she's hearing. 175 00:14:32,831 --> 00:14:33,999 Okay. Are you ready? 176 00:14:36,835 --> 00:14:40,380 This Wave Glider, nicknamed Europa, 177 00:14:40,380 --> 00:14:46,261 is heading out to search 5,000 miles of ocean between Hawaii and Mexico. 178 00:14:49,306 --> 00:14:55,938 What are the odds of this ten-foot-long, autonomous vehicle intersecting a whale? 179 00:14:55,938 --> 00:14:58,482 I mean, really, it's like searching for a needle in a haystack. 180 00:14:58,482 --> 00:14:59,525 Ready? 181 00:14:59,525 --> 00:15:00,609 - Ready. - Yup. 182 00:15:02,152 --> 00:15:04,071 And the time has come... 183 00:15:06,823 --> 00:15:08,700 to set it off. 184 00:15:08,700 --> 00:15:10,202 And there she goes. 185 00:15:12,829 --> 00:15:13,664 Wow. 186 00:15:17,000 --> 00:15:18,001 We did it. 187 00:15:19,002 --> 00:15:21,713 - Wow. - Have a good trip, Europa! 188 00:15:23,090 --> 00:15:25,092 In five months' time, 189 00:15:25,092 --> 00:15:28,136 if Europa can navigate safely back to Hawaii... 190 00:15:30,389 --> 00:15:35,477 it could redefine what we know about where these ocean giants roam. 191 00:15:53,829 --> 00:15:55,789 On the other side of the planet... 192 00:15:59,793 --> 00:16:05,340 another pioneering acoustic project is gathering vital clues... 193 00:16:08,302 --> 00:16:12,431 to help save one of the world's rarest predators. 194 00:16:17,060 --> 00:16:19,104 African wild dogs. 195 00:16:22,482 --> 00:16:28,530 Less than 700 packs are left in the wild and their numbers are dropping. 196 00:16:30,282 --> 00:16:33,452 In recent years, their home in Southern Africa 197 00:16:33,452 --> 00:16:39,333 has experienced more frequent and intense heat waves because of climate change. 198 00:16:43,795 --> 00:16:47,382 Scientists believe this could be contributing to their decline... 199 00:16:50,260 --> 00:16:52,513 and that's where sound can help. 200 00:16:59,144 --> 00:17:00,854 If you see a wild dog let me know. 201 00:17:02,272 --> 00:17:05,108 Kasim Rafiq from the University of Washington 202 00:17:06,108 --> 00:17:09,404 is teaming up with conservation group Wild Entrust... 203 00:17:09,404 --> 00:17:11,698 Okay. Let's go see the dogs. 204 00:17:12,281 --> 00:17:17,663 ...to identify the most important places wild dogs hunt and raise their pups 205 00:17:19,122 --> 00:17:22,542 by tapping into their highly chatty nature. 206 00:17:23,752 --> 00:17:26,713 Sound is a key way in which the animals of this area communicate. 207 00:17:26,713 --> 00:17:29,675 But it's also a key way for us as researchers 208 00:17:29,675 --> 00:17:31,385 to understand what's happening. 209 00:17:32,719 --> 00:17:35,138 But tracking fast-moving predators 210 00:17:35,722 --> 00:17:40,727 that roam over 500 square miles is no easy task. 211 00:17:41,645 --> 00:17:43,939 African wild dogs are very, very hard to follow 212 00:17:45,023 --> 00:17:48,485 because they move very, very fast across these landscapes 213 00:17:48,485 --> 00:17:50,237 that are dotted with these massive holes 214 00:17:50,237 --> 00:17:53,073 from elephants and, like, aardvarks and warthogs. 215 00:17:53,073 --> 00:17:55,909 And often if you try and follow them when they're hunting... 216 00:17:57,619 --> 00:17:59,580 you just drive your Land Rover straight into it. 217 00:18:00,789 --> 00:18:03,458 So the team has come up with a novel approach: 218 00:18:04,126 --> 00:18:08,172 miking up the dogs with a lightweight, acoustic collar. 219 00:18:08,755 --> 00:18:11,466 A normal wildlife tracking collar tells us where the animals are going, 220 00:18:12,593 --> 00:18:15,262 but it doesn't tell us what the animals are doing in those areas. 221 00:18:15,262 --> 00:18:18,265 The acoustic part-- So, it's a little box that we designed 222 00:18:18,265 --> 00:18:21,476 and that fits onto the side of a normal wildlife tracking collar, 223 00:18:21,476 --> 00:18:24,730 and it allows us to hear exactly what the animals are getting up to. 224 00:18:26,982 --> 00:18:28,692 Using these acoustic collars, 225 00:18:28,692 --> 00:18:32,738 the team will be able to monitor the pack 24-7. 226 00:18:35,157 --> 00:18:38,535 But first, they need to find a healthy adult to collar. 227 00:18:38,535 --> 00:18:40,078 They're probably under there. 228 00:18:40,078 --> 00:18:44,750 And vet Rob Jackson and Kasim know just the individual. 229 00:18:47,252 --> 00:18:49,213 Let me just ID the dog first. 230 00:18:49,213 --> 00:18:51,381 Where is Jessie? 231 00:18:53,884 --> 00:18:56,428 One of the pack's large males, Jessie, 232 00:18:56,929 --> 00:18:59,932 will give them the best chance to eavesdrop 233 00:18:59,932 --> 00:19:02,726 into the heart of wild dog family life. 234 00:19:02,726 --> 00:19:06,480 - Okay, well, can we dart? - Yeah. 235 00:19:11,443 --> 00:19:15,906 The anesthetic dart is harmless and will sedate him for 20 minutes. 236 00:19:16,865 --> 00:19:18,951 Okay, have you got that blindfold? 237 00:19:18,951 --> 00:19:20,661 Okay, you can come out, Kas. 238 00:19:20,661 --> 00:19:23,121 Let's get the collar on, let's get the dart out. 239 00:19:24,915 --> 00:19:27,918 It's a chance to give Jessie a health check. 240 00:19:28,418 --> 00:19:32,589 The teeth gives an indication of how healthy it is. 241 00:19:32,589 --> 00:19:36,677 They should be very strong to bring down their preys and stuff. 242 00:19:41,181 --> 00:19:44,643 Yeah, he's moving. Perfect. 243 00:19:46,520 --> 00:19:49,356 He's breathing nicely. He appears healthy. 244 00:19:49,356 --> 00:19:50,649 All good. 245 00:19:53,277 --> 00:19:57,573 The onboard mic starts picking up the family's most intimate calls... 246 00:19:59,533 --> 00:20:01,618 closer than ever before. 247 00:20:15,841 --> 00:20:17,217 A few days later, 248 00:20:17,217 --> 00:20:21,763 the collar captures a key sound that the team has been hoping for. 249 00:20:24,558 --> 00:20:26,059 One of my favorite vocalizations 250 00:20:26,059 --> 00:20:28,937 occurs when the wild dogs are getting ready to move. 251 00:20:28,937 --> 00:20:31,857 They create this weird sound that sounds like birds twittering. 252 00:20:31,857 --> 00:20:34,109 And I love that for two reasons. 253 00:20:34,109 --> 00:20:36,486 One, you get, like, caught up in the emotion of it. 254 00:20:36,486 --> 00:20:39,323 And two, it means that something really exciting is gonna happen. 255 00:20:40,199 --> 00:20:43,243 This twittering call is a sign the pack... 256 00:20:43,243 --> 00:20:45,412 - Let's go. - ...is preparing to hunt. 257 00:20:50,125 --> 00:20:52,169 Mike, Mike, you can follow us. 258 00:20:53,795 --> 00:20:58,091 The dogs can cover up to five miles of rough ground on a hunt, 259 00:20:59,551 --> 00:21:02,471 and Kasim knows he can't track them for long. 260 00:21:04,181 --> 00:21:06,099 It looks like they spotted something. 261 00:21:07,935 --> 00:21:09,770 Yeah, impala, impala. 262 00:21:09,770 --> 00:21:11,772 I think we might lose them. 263 00:21:12,272 --> 00:21:15,901 Now, the acoustic collar comes into its own. 264 00:21:27,371 --> 00:21:30,958 The GPS tracks exactly where the dogs go... 265 00:21:33,627 --> 00:21:38,298 and the microphone reveals key information about their behavior. 266 00:21:40,509 --> 00:21:43,220 This time, a successful hunt. 267 00:21:54,898 --> 00:21:59,278 Over five months, the team collects 900 hours of audio. 268 00:22:01,697 --> 00:22:04,032 And by listening to the dogs around the clock, 269 00:22:04,658 --> 00:22:09,204 these onboard recordings will help them better understand 270 00:22:09,204 --> 00:22:14,543 how the pack's ability to hunt is being affected by rising temperatures. 271 00:22:15,460 --> 00:22:19,173 The acoustic collars are gonna give us this ability 272 00:22:19,173 --> 00:22:21,633 to translate exactly what the animals have been doing. 273 00:22:22,426 --> 00:22:25,345 And I think that's really important because it's gonna give us insights 274 00:22:25,345 --> 00:22:28,974 into how climate change is impacting the ability of these animals to survive. 275 00:22:28,974 --> 00:22:30,559 And that's very, very exciting. 276 00:22:38,066 --> 00:22:42,487 From the African Savannah to the polar ice caps... 277 00:22:45,449 --> 00:22:51,371 the impacts of climate change are being seen and heard across the planet. 278 00:22:55,918 --> 00:23:00,923 Temperatures in the Arctic are rising four times faster than anywhere else. 279 00:23:02,633 --> 00:23:07,804 The loss of ice is affecting wildlife and raising sea levels. 280 00:23:09,723 --> 00:23:12,351 But it's also creating another problem. 281 00:23:18,524 --> 00:23:20,734 Ocean noise pollution. 282 00:23:24,947 --> 00:23:27,908 As the Arctic ice cap thins and shrinks, 283 00:23:28,992 --> 00:23:32,955 shipping lanes are opening up in places never possible before. 284 00:23:36,750 --> 00:23:38,293 For Arctic wildlife, 285 00:23:39,002 --> 00:23:42,589 the dramatic increase in ships is disastrous. 286 00:23:48,095 --> 00:23:52,057 It's something that Norwegian sound recordist, Jana Winderen, 287 00:23:52,057 --> 00:23:56,395 is experiencing in her work to capture the sounds of the Arctic's animals... 288 00:24:04,027 --> 00:24:07,698 including its most endearing heavyweights... 289 00:24:11,618 --> 00:24:12,619 walrus. 290 00:24:14,037 --> 00:24:16,123 The breeding season is approaching, 291 00:24:16,123 --> 00:24:20,878 and Jana is hoping to record their incredible underwater calls. 292 00:24:29,428 --> 00:24:31,346 There is a knocking sound. 293 00:24:34,224 --> 00:24:37,311 I can hear them really well, but I can't see it just right now. 294 00:24:39,646 --> 00:24:42,316 Tick, tick, tick, tick, tick, tick, tick. Like this. 295 00:24:48,030 --> 00:24:50,490 That is the courtship sound of the walrus. 296 00:24:52,492 --> 00:24:54,244 Wow, this is brilliant. 297 00:24:54,244 --> 00:24:58,707 She's just like-- They're just over there. Look. 298 00:25:01,543 --> 00:25:04,713 Walrus are masters of underwater sound. 299 00:25:06,173 --> 00:25:09,343 Their courtship knocks carry for miles, 300 00:25:09,343 --> 00:25:12,930 helping them find mates in this icy wilderness. 301 00:25:23,232 --> 00:25:27,778 That's the first time I've seen walruses so close. 302 00:25:27,778 --> 00:25:30,030 You can see like the eyes looking, you know. 303 00:25:30,030 --> 00:25:31,156 It's brilliant. 304 00:25:33,617 --> 00:25:37,621 But the walrus calls are increasingly being drowned out. 305 00:25:43,919 --> 00:25:45,921 Yeah, I can hear the boat. 306 00:25:52,511 --> 00:25:55,430 And even if I don't see the boat, I can hear it. 307 00:25:59,017 --> 00:26:00,853 It's really worrying, because it's... 308 00:26:00,853 --> 00:26:05,440 You know, with this shipping lane, it will separate habitats from each other. 309 00:26:07,025 --> 00:26:09,403 Species that are migrating 310 00:26:09,403 --> 00:26:12,072 or they're going to a particular area to feed... 311 00:26:12,072 --> 00:26:16,785 They might have suddenly, like, a shipping lane right through their dinner table, 312 00:26:16,785 --> 00:26:19,580 and they can't hear each other, you know? 313 00:26:19,580 --> 00:26:23,083 And they can't meet each other. They can't meet a mate. 314 00:26:23,083 --> 00:26:29,339 So, it's like eating dinner every day in the middle of a motorway. 315 00:26:34,178 --> 00:26:38,182 Recent studies show underwater noise pollution in the Arctic 316 00:26:38,182 --> 00:26:41,226 has doubled in just six years... 317 00:26:43,228 --> 00:26:45,772 but we still have time to tackle it. 318 00:26:47,816 --> 00:26:53,197 There is regulations that can be done in terms of how much sound the ship makes, 319 00:26:53,197 --> 00:26:58,368 or what time of year you're having the traffic. 320 00:26:59,494 --> 00:27:03,415 This is the mating ground and, you know, 321 00:27:03,415 --> 00:27:09,421 we don't need to kind of just drive straight through it all year around. 322 00:27:10,797 --> 00:27:13,509 Sound pollution is one of the more straightforward 323 00:27:13,509 --> 00:27:16,011 types of pollutants to deal with. 324 00:27:16,970 --> 00:27:21,808 You simply turn it off or at least turn it down. 325 00:27:24,228 --> 00:27:29,983 Recordings like Jana's will help scientists identify key hot spots 326 00:27:29,983 --> 00:27:33,737 that marine mammals use to broadcast their courtship calls... 327 00:27:35,822 --> 00:27:39,284 helping us better protect them throughout the Arctic Ocean. 328 00:27:49,336 --> 00:27:51,088 Okay, you guys good? 329 00:27:51,088 --> 00:27:52,881 Okay, we're ready? Okay, here we go. 330 00:27:54,299 --> 00:27:55,676 Back in the Pacific, 331 00:27:55,676 --> 00:28:00,973 it's been five months since Beth and her team launched the acoustic Wave Glider. 332 00:28:01,932 --> 00:28:02,975 All clear. 333 00:28:06,061 --> 00:28:10,107 Now it's time to retrieve it and discover if their efforts 334 00:28:10,107 --> 00:28:14,027 to track humpback whales through sound have paid off. 335 00:28:14,528 --> 00:28:16,989 Right now, as of about five minutes ago, 336 00:28:16,989 --> 00:28:20,826 she was off of this bay right here, about ten miles offshore. 337 00:28:20,826 --> 00:28:23,370 This is our time. We're gonna go get her. 338 00:28:23,370 --> 00:28:25,163 Let's do this, okay? 339 00:28:30,502 --> 00:28:34,882 Europa has been traveling all the way to Mexico and back 340 00:28:34,882 --> 00:28:37,467 in search for humpback whale song 341 00:28:38,051 --> 00:28:41,054 in unidentified areas where people aren't expecting to hear them. 342 00:28:42,639 --> 00:28:45,434 If Europa has recorded humpback song, 343 00:28:45,434 --> 00:28:49,188 it could shed new light on the whales' migration routes 344 00:28:49,188 --> 00:28:50,772 throughout the North Pacific. 345 00:28:51,815 --> 00:28:55,068 The team just needs to find it and bring it safely aboard... 346 00:28:56,570 --> 00:28:59,489 but the ocean has other plans. 347 00:29:00,616 --> 00:29:02,284 Not liking that weather moving in. 348 00:29:02,284 --> 00:29:05,037 The swell's picking up here a little bit. Okay, watch these... 349 00:29:07,414 --> 00:29:08,457 Oh, yeah. 350 00:29:12,211 --> 00:29:15,255 All eyes out. We should be right on it. 351 00:29:16,882 --> 00:29:19,927 There it is. Yeah. Right there. Where the birds are. 352 00:29:20,552 --> 00:29:24,890 All set for a lively recovery on the high seas. 353 00:29:24,890 --> 00:29:26,850 Don't fall off up there. 354 00:29:26,850 --> 00:29:29,061 All right, Murray, I've got the helm! 355 00:29:30,103 --> 00:29:31,188 Oh, yeah. Okay! 356 00:29:31,188 --> 00:29:33,398 Yeehaw, this is rough. 357 00:29:33,398 --> 00:29:34,483 Yeah. 358 00:29:36,568 --> 00:29:38,654 If the team don't get this right, 359 00:29:38,654 --> 00:29:41,657 all of Europa's precious data could be lost. 360 00:29:41,657 --> 00:29:43,325 I'm getting you a little closer. 361 00:29:43,825 --> 00:29:46,537 - Come on! - Go, go stretch. 362 00:29:46,537 --> 00:29:48,330 - One more. Yeah, here we go. - We're on! 363 00:29:48,330 --> 00:29:49,248 All right. 364 00:29:49,831 --> 00:29:51,667 Look at her, she's looking great! 365 00:29:51,667 --> 00:29:53,418 Watch-- Watch-- 366 00:29:55,587 --> 00:29:58,799 - Okay. Break off. - We got her. 367 00:30:00,050 --> 00:30:01,802 - All right. - Nice! 368 00:30:02,845 --> 00:30:04,471 So, we got Europa back. 369 00:30:04,471 --> 00:30:08,225 She's got quite a few gooseneck barnacles growing on her. 370 00:30:08,225 --> 00:30:12,688 A little bit of algae, but basically she looks in great shape. 371 00:30:13,981 --> 00:30:15,566 As the crew head for home, 372 00:30:16,817 --> 00:30:20,946 Beth can't wait to check out what Europa has been recording. 373 00:30:20,946 --> 00:30:24,449 Let's download an audio file from a thousand miles offshore. 374 00:30:24,950 --> 00:30:27,119 If it's captured whale song, 375 00:30:27,119 --> 00:30:31,123 it'll be proof of humpbacks in the mid-Pacific. 376 00:30:31,123 --> 00:30:34,084 Okay. Here we go. Let me listen. 377 00:30:36,962 --> 00:30:40,465 Yeah, yeah, yeah! It's a song, that's pretty clear. 378 00:30:40,465 --> 00:30:42,342 Okay. Here we go. Here's another one. 379 00:30:44,970 --> 00:30:46,388 Yes, those are even louder. 380 00:30:46,388 --> 00:30:47,639 - Those are even clearer. - Wow. 381 00:30:48,515 --> 00:30:52,811 It's the sound that Beth and the team have waited for for so long. 382 00:30:53,312 --> 00:30:56,481 Oh, my God. We heard whales. All right, you guys. That's great. 383 00:30:56,481 --> 00:30:58,025 That's so great. Cool. 384 00:30:58,025 --> 00:30:59,318 - Good job. - Yay. 385 00:31:03,113 --> 00:31:07,242 Europa ended up being out on this mission 150 days, 386 00:31:07,910 --> 00:31:11,496 and she traveled 5,000 nautical miles, 387 00:31:11,496 --> 00:31:15,751 and we collected 1,700 hours of audio data. 388 00:31:18,086 --> 00:31:23,217 Incredibly, Europa captured thousands of humpback recordings 389 00:31:23,217 --> 00:31:27,763 which show that as well as migrating north to the feeding grounds, 390 00:31:29,139 --> 00:31:33,352 the whales are also traveling between Hawaii and Mexico 391 00:31:34,436 --> 00:31:36,980 in numbers never recorded before. 392 00:31:39,316 --> 00:31:42,319 Not only could the whales be migrating back and forth 393 00:31:42,319 --> 00:31:45,739 between Mexico and Hawaii, within the same season, 394 00:31:45,739 --> 00:31:47,366 but they could be actually lingering 395 00:31:47,366 --> 00:31:51,245 or having a group of them out there, traveling back and forth. 396 00:31:51,245 --> 00:31:54,039 Or they could even be out there breeding and calving. 397 00:31:55,916 --> 00:31:59,670 This discovery of a corridor between Hawaii and Mexico 398 00:32:00,462 --> 00:32:04,633 will help us better understand and protect these ocean giants 399 00:32:05,425 --> 00:32:08,095 on their travels across the North Pacific. 400 00:32:11,890 --> 00:32:15,185 The fact that we heard any at all is quite phenomenal 401 00:32:15,185 --> 00:32:17,980 for the technology of the Wave Glider and the hydrophone, 402 00:32:17,980 --> 00:32:20,274 but also for the discovery of having them out there. 403 00:32:20,274 --> 00:32:22,234 So I feel pretty pleased about that. 404 00:32:22,234 --> 00:32:23,902 It's pretty impressive, really. 405 00:32:25,112 --> 00:32:28,365 It's just one of the remarkable ways 406 00:32:28,365 --> 00:32:32,369 we're now able to track and protect animals... 407 00:32:35,289 --> 00:32:36,999 simply by listening... 408 00:32:40,294 --> 00:32:42,713 to the sounds of our planet.