1 00:00:02,366 --> 00:00:07,796 (Nature sounds) 2 00:00:07,820 --> 00:00:10,512 When I first began recording wild soundscapes 3 00:00:10,536 --> 00:00:12,443 45 years ago, 4 00:00:12,467 --> 00:00:14,865 I had no idea that ants, 5 00:00:14,889 --> 00:00:18,344 insect larvae, sea anemones and viruses 6 00:00:18,368 --> 00:00:20,472 created a sound signature. 7 00:00:20,496 --> 00:00:21,915 But they do. 8 00:00:21,939 --> 00:00:25,328 And so does every wild habitat on the planet, 9 00:00:25,352 --> 00:00:28,563 like the Amazon rainforest you're hearing behind me. 10 00:00:28,587 --> 00:00:32,137 In fact, temperate and tropical rainforests 11 00:00:32,161 --> 00:00:35,317 each produce a vibrant animal orchestra, 12 00:00:35,341 --> 00:00:38,545 that instantaneous and organized expression 13 00:00:38,569 --> 00:00:43,353 of insects, reptiles, amphibians, birds and mammals. 14 00:00:43,377 --> 00:00:46,280 And every soundscape that springs from a wild habitat 15 00:00:46,304 --> 00:00:49,872 generates its own unique signature, 16 00:00:49,896 --> 00:00:52,789 one that contains incredible amounts of information, 17 00:00:52,813 --> 00:00:57,148 and it's some of that information I want to share with you today. 18 00:00:57,172 --> 00:01:00,354 The soundscape is made up of three basic sources. 19 00:01:00,378 --> 00:01:02,893 The first is the geophony, 20 00:01:02,917 --> 00:01:05,259 or the nonbiological sounds that occur 21 00:01:05,283 --> 00:01:07,236 in any given habitat, 22 00:01:07,260 --> 00:01:09,828 like wind in the trees, water in a stream, 23 00:01:09,852 --> 00:01:13,422 waves at the ocean shore, movement of the Earth. 24 00:01:13,446 --> 00:01:16,700 The second of these is the biophony. 25 00:01:16,724 --> 00:01:19,822 The biophony is all of the sound 26 00:01:19,846 --> 00:01:22,940 that's generated by organisms in a given habitat 27 00:01:22,964 --> 00:01:26,560 at one time and in one place. 28 00:01:26,584 --> 00:01:31,094 And the third is all of the sound that we humans generate 29 00:01:31,118 --> 00:01:32,912 that's called anthrophony. 30 00:01:32,936 --> 00:01:36,273 Some of it is controlled, like music or theater, 31 00:01:36,297 --> 00:01:40,190 but most of it is chaotic and incoherent, 32 00:01:40,214 --> 00:01:43,895 which some of us refer to as noise. 33 00:01:43,919 --> 00:01:46,595 There was a time when I considered wild soundscapes 34 00:01:46,619 --> 00:01:48,327 to be a worthless artifact. 35 00:01:48,351 --> 00:01:52,409 They were just there, but they had no significance. 36 00:01:52,433 --> 00:01:55,782 Well, I was wrong. What I learned from these encounters 37 00:01:55,806 --> 00:02:00,558 was that careful listening gives us incredibly valuable tools 38 00:02:00,582 --> 00:02:03,142 by which to evaluate the health of a habitat 39 00:02:03,166 --> 00:02:06,954 across the entire spectrum of life. 40 00:02:06,978 --> 00:02:10,166 When I began recording in the late '60s, 41 00:02:10,190 --> 00:02:13,442 the typical methods of recording were limited 42 00:02:13,466 --> 00:02:17,910 to the fragmented capture of individual species 43 00:02:17,934 --> 00:02:21,006 like birds mostly, in the beginning, 44 00:02:21,030 --> 00:02:26,707 but later animals like mammals and amphibians. 45 00:02:26,731 --> 00:02:30,219 To me, this was a little like trying to understand 46 00:02:30,243 --> 00:02:33,284 the magnificence of Beethoven's Fifth Symphony 47 00:02:33,308 --> 00:02:36,193 by abstracting the sound of a single violin player 48 00:02:36,217 --> 00:02:38,763 out of the context of the orchestra 49 00:02:38,787 --> 00:02:41,866 and hearing just that one part. 50 00:02:41,890 --> 00:02:44,883 Fortunately, more and more institutions 51 00:02:44,907 --> 00:02:46,951 are implementing the more holistic models 52 00:02:46,975 --> 00:02:49,314 that I and a few of my colleagues have introduced 53 00:02:49,338 --> 00:02:53,187 to the field of soundscape ecology. 54 00:02:53,211 --> 00:02:58,255 When I began recording over four decades ago, 55 00:02:58,279 --> 00:03:00,664 I could record for 10 hours 56 00:03:00,688 --> 00:03:02,899 and capture one hour of usable material, 57 00:03:02,923 --> 00:03:05,956 good enough for an album or a film soundtrack 58 00:03:05,980 --> 00:03:08,675 or a museum installation. 59 00:03:08,699 --> 00:03:11,628 Now, because of global warming, 60 00:03:11,652 --> 00:03:13,046 resource extraction, 61 00:03:13,070 --> 00:03:16,115 and human noise, among many other factors, 62 00:03:16,139 --> 00:03:18,791 it can take up to 1,000 hours or more 63 00:03:18,815 --> 00:03:21,624 to capture the same thing. 64 00:03:21,648 --> 00:03:24,679 Fully 50 percent of my archive 65 00:03:24,703 --> 00:03:27,875 comes from habitats so radically altered 66 00:03:27,899 --> 00:03:30,775 that they're either altogether silent 67 00:03:30,799 --> 00:03:35,496 or can no longer be heard in any of their original form. 68 00:03:35,520 --> 00:03:37,782 The usual methods of evaluating a habitat 69 00:03:37,806 --> 00:03:41,108 have been done by visually counting the numbers of species 70 00:03:41,132 --> 00:03:45,313 and the numbers of individuals within each species in a given area. 71 00:03:45,337 --> 00:03:48,865 However, by comparing data that ties together 72 00:03:48,889 --> 00:03:51,665 both density and diversity from what we hear, 73 00:03:51,689 --> 00:03:57,038 I'm able to arrive at much more precise fitness outcomes. 74 00:03:57,062 --> 00:03:59,078 And I want to show you some examples 75 00:03:59,102 --> 00:04:01,868 that typify the possibilities unlocked 76 00:04:01,892 --> 00:04:04,890 by diving into this universe. 77 00:04:04,914 --> 00:04:06,282 This is Lincoln Meadow. 78 00:04:06,306 --> 00:04:08,497 Lincoln Meadow's a three-and-a-half-hour drive 79 00:04:08,521 --> 00:04:11,390 east of San Francisco in the Sierra Nevada Mountains, 80 00:04:11,414 --> 00:04:13,487 at about 2,000 meters altitude, 81 00:04:13,511 --> 00:04:16,296 and I've been recording there for many years. 82 00:04:16,320 --> 00:04:20,216 In 1988, a logging company convinced local residents 83 00:04:20,240 --> 00:04:23,378 that there would be absolutely no environmental impact 84 00:04:23,402 --> 00:04:25,022 from a new method they were trying 85 00:04:25,046 --> 00:04:26,742 called "selective logging," 86 00:04:26,766 --> 00:04:28,297 taking out a tree here and there 87 00:04:28,321 --> 00:04:31,580 rather than clear-cutting a whole area. 88 00:04:31,604 --> 00:04:33,340 With permission granted to record 89 00:04:33,364 --> 00:04:35,303 both before and after the operation, 90 00:04:35,327 --> 00:04:39,921 I set up my gear and captured a large number of dawn choruses 91 00:04:39,945 --> 00:04:43,454 to very strict protocol and calibrated recordings, 92 00:04:43,478 --> 00:04:45,648 because I wanted a really good baseline. 93 00:04:45,672 --> 00:04:47,833 This is an example of a spectrogram. 94 00:04:47,857 --> 00:04:50,264 A spectrogram is a graphic illustration of sound 95 00:04:50,288 --> 00:04:53,437 with time from left to right across the page -- 96 00:04:53,461 --> 00:04:55,944 15 seconds in this case is represented — 97 00:04:55,968 --> 00:04:58,799 and frequency from the bottom of the page to the top, 98 00:04:58,823 --> 00:05:00,018 lowest to highest. 99 00:05:00,042 --> 00:05:03,152 And you can see that the signature of a stream 100 00:05:03,176 --> 00:05:07,957 is represented here in the bottom third or half of the page, 101 00:05:07,981 --> 00:05:11,400 while birds that were once in that meadow 102 00:05:11,424 --> 00:05:14,457 are represented in the signature across the top. 103 00:05:14,481 --> 00:05:15,612 There were a lot of them. 104 00:05:15,636 --> 00:05:18,776 And here's Lincoln Meadow before selective logging. 105 00:05:18,800 --> 00:05:33,569 (Nature sounds) 106 00:05:33,593 --> 00:05:35,447 Well, a year later I returned, 107 00:05:35,471 --> 00:05:37,204 and using the same protocols 108 00:05:37,228 --> 00:05:39,919 and recording under the same conditions, 109 00:05:39,943 --> 00:05:42,147 I recorded a number of examples 110 00:05:42,171 --> 00:05:44,247 of the same dawn choruses, 111 00:05:44,271 --> 00:05:46,390 and now this is what we've got. 112 00:05:46,414 --> 00:05:47,670 This is after selective logging. 113 00:05:47,694 --> 00:05:49,980 You can see that the stream is still represented 114 00:05:50,004 --> 00:05:51,650 in the bottom third of the page, 115 00:05:51,674 --> 00:05:56,153 but notice what's missing in the top two thirds. 116 00:05:56,177 --> 00:06:01,666 (Nature sounds) 117 00:06:01,690 --> 00:06:11,153 Coming up is the sound of a woodpecker. 118 00:06:11,177 --> 00:06:13,743 Well, I've returned to Lincoln Meadow 15 times 119 00:06:13,767 --> 00:06:15,227 in the last 25 years, 120 00:06:15,251 --> 00:06:18,913 and I can tell you that the biophony, 121 00:06:18,937 --> 00:06:21,818 the density and diversity of that biophony, 122 00:06:21,842 --> 00:06:24,370 has not yet returned to anything like it was 123 00:06:24,394 --> 00:06:26,568 before the operation. 124 00:06:26,592 --> 00:06:29,666 But here's a picture of Lincoln Meadow taken after, 125 00:06:29,690 --> 00:06:32,904 and you can see that from the perspective of the camera 126 00:06:32,928 --> 00:06:34,015 or the human eye, 127 00:06:34,039 --> 00:06:36,790 hardly a stick or a tree appears to be out of place, 128 00:06:36,814 --> 00:06:39,730 which would confirm the logging company's contention 129 00:06:39,754 --> 00:06:42,359 that there's nothing of environmental impact. 130 00:06:42,383 --> 00:06:48,776 However, our ears tell us a very different story. 131 00:06:48,800 --> 00:06:50,603 Young students are always asking me 132 00:06:50,627 --> 00:06:52,056 what these animals are saying, 133 00:06:52,080 --> 00:06:56,887 and really I've got no idea. 134 00:06:56,911 --> 00:07:02,156 But I can tell you that they do express themselves. 135 00:07:02,180 --> 00:07:05,234 Whether or not we understand it is a different story. 136 00:07:05,258 --> 00:07:07,562 I was walking along the shore in Alaska, 137 00:07:07,586 --> 00:07:09,906 and I came across this tide pool 138 00:07:09,930 --> 00:07:12,938 filled with a colony of sea anemones, 139 00:07:12,962 --> 00:07:15,014 these wonderful eating machines, 140 00:07:15,038 --> 00:07:17,865 relatives of coral and jellyfish. 141 00:07:17,889 --> 00:07:20,223 And curious to see if any of them made any noise, 142 00:07:20,247 --> 00:07:21,394 I dropped a hydrophone, 143 00:07:21,418 --> 00:07:24,386 an underwater microphone covered in rubber, 144 00:07:24,410 --> 00:07:25,574 down the mouth part, 145 00:07:25,598 --> 00:07:27,335 and immediately the critter began 146 00:07:27,359 --> 00:07:29,544 to absorb the microphone into its belly, 147 00:07:29,568 --> 00:07:32,238 and the tentacles were searching out of the surface 148 00:07:32,262 --> 00:07:34,649 for something of nutritional value. 149 00:07:34,673 --> 00:07:37,154 The static-like sounds that are very low, 150 00:07:37,178 --> 00:07:39,158 that you're going to hear right now. 151 00:07:39,182 --> 00:07:43,560 (Static sounds) 152 00:07:43,584 --> 00:07:46,427 Yeah, but watch. When it didn't find anything to eat -- 153 00:07:46,451 --> 00:07:47,816 (Honking sound) 154 00:07:47,840 --> 00:07:50,476 (Laughter) 155 00:07:50,500 --> 00:07:52,973 I think that's an expression that can be understood 156 00:07:52,997 --> 00:07:54,390 in any language. 157 00:07:54,414 --> 00:07:59,256 (Laughter) 158 00:07:59,280 --> 00:08:00,856 At the end of its breeding cycle, 159 00:08:00,880 --> 00:08:03,012 the Great Basin Spadefoot toad 160 00:08:03,036 --> 00:08:05,087 digs itself down about a meter under 161 00:08:05,111 --> 00:08:08,237 the hard-panned desert soil of the American West, 162 00:08:08,261 --> 00:08:10,116 where it can stay for many seasons 163 00:08:10,140 --> 00:08:13,616 until conditions are just right for it to emerge again. 164 00:08:13,640 --> 00:08:15,736 And when there's enough moisture in the soil 165 00:08:15,760 --> 00:08:18,531 in the spring, frogs will dig themselves to the surface 166 00:08:18,555 --> 00:08:22,602 and gather around these large, vernal pools 167 00:08:22,626 --> 00:08:24,639 in great numbers. 168 00:08:24,663 --> 00:08:28,045 And they vocalize in a chorus 169 00:08:28,069 --> 00:08:31,253 that's absolutely in sync with one another. 170 00:08:31,277 --> 00:08:32,849 And they do that for two reasons. 171 00:08:32,873 --> 00:08:36,278 The first is competitive, because they're looking for mates, 172 00:08:36,302 --> 00:08:37,731 and the second is cooperative, 173 00:08:37,755 --> 00:08:40,212 because if they're all vocalizing in sync together, 174 00:08:40,236 --> 00:08:44,371 it makes it really difficult for predators like coyotes, 175 00:08:44,395 --> 00:08:48,590 foxes and owls to single out any individual for a meal. 176 00:08:48,614 --> 00:08:51,862 This is a spectrogram of what the frog chorusing looks like 177 00:08:51,886 --> 00:08:54,123 when it's in a very healthy pattern. 178 00:08:54,147 --> 00:09:04,139 (Frogs croaking) 179 00:09:04,163 --> 00:09:08,104 Mono Lake is just to the east of Yosemite National Park 180 00:09:08,128 --> 00:09:09,933 in California, 181 00:09:09,957 --> 00:09:12,788 and it's a favorite habitat of these toads, 182 00:09:12,812 --> 00:09:15,675 and it's also favored by U.S. Navy jet pilots, 183 00:09:15,699 --> 00:09:18,721 who train in their fighters flying them at speeds 184 00:09:18,745 --> 00:09:21,179 exceeding 1,100 kilometers an hour 185 00:09:21,203 --> 00:09:23,960 and altitudes only a couple hundred meters 186 00:09:23,984 --> 00:09:26,539 above ground level of the Mono Basin, 187 00:09:26,563 --> 00:09:30,213 very fast, very low, and so loud 188 00:09:30,237 --> 00:09:33,079 that the anthrophony, the human noise, 189 00:09:33,103 --> 00:09:35,103 even though it's six and a half kilometers 190 00:09:35,127 --> 00:09:37,903 from the frog pond you just heard a second ago, 191 00:09:37,927 --> 00:09:41,469 it masked the sound of the chorusing toads. 192 00:09:41,493 --> 00:09:44,735 You can see in this spectrogram that all of the energy 193 00:09:44,759 --> 00:09:47,482 that was once in the first spectrogram is gone 194 00:09:47,506 --> 00:09:49,229 from the top end of the spectrogram, 195 00:09:49,253 --> 00:09:52,063 and that there's breaks in the chorusing at two and a half, 196 00:09:52,087 --> 00:09:54,255 four and a half, and six and a half seconds, 197 00:09:54,279 --> 00:09:57,354 and then the sound of the jet, the signature, 198 00:09:57,378 --> 00:09:59,913 is in yellow at the very bottom of the page. 199 00:09:59,937 --> 00:10:09,558 (Frogs croaking) 200 00:10:09,582 --> 00:10:11,952 Now at the end of that flyby, 201 00:10:11,976 --> 00:10:15,441 it took the frogs fully 45 minutes 202 00:10:15,465 --> 00:10:17,845 to regain their chorusing synchronicity, 203 00:10:17,869 --> 00:10:20,790 during which time, and under a full moon, 204 00:10:20,814 --> 00:10:23,571 we watched as two coyotes and a great horned owl 205 00:10:23,595 --> 00:10:26,694 came in to pick off a few of their numbers. 206 00:10:26,718 --> 00:10:30,220 The good news is that, with a little bit of habitat restoration 207 00:10:30,244 --> 00:10:32,925 and fewer flights, the frog populations, 208 00:10:32,949 --> 00:10:36,648 once diminishing during the 1980s and early '90s, 209 00:10:36,672 --> 00:10:40,181 have pretty much returned to normal. 210 00:10:40,205 --> 00:10:43,120 I want to end with a story told by a beaver. 211 00:10:43,144 --> 00:10:44,594 It's a very sad story, 212 00:10:44,618 --> 00:10:48,472 but it really illustrates how animals 213 00:10:48,496 --> 00:10:50,454 can sometimes show emotion, 214 00:10:50,478 --> 00:10:55,106 a very controversial subject among some older biologists. 215 00:10:55,130 --> 00:10:58,339 A colleague of mine was recording in the American Midwest 216 00:10:58,363 --> 00:11:00,881 around this pond that had been formed 217 00:11:00,905 --> 00:11:04,780 maybe 16,000 years ago at the end of the last ice age. 218 00:11:04,804 --> 00:11:06,933 It was also formed in part by a beaver dam 219 00:11:06,957 --> 00:11:09,851 at one end that held that whole ecosystem together 220 00:11:09,875 --> 00:11:12,603 in a very delicate balance. 221 00:11:12,627 --> 00:11:16,378 And one afternoon, while he was recording, 222 00:11:16,402 --> 00:11:20,202 there suddenly appeared from out of nowhere 223 00:11:20,226 --> 00:11:22,650 a couple of game wardens, 224 00:11:22,674 --> 00:11:24,245 who for no apparent reason, 225 00:11:24,269 --> 00:11:25,824 walked over to the beaver dam, 226 00:11:25,848 --> 00:11:29,106 dropped a stick of dynamite down it, blowing it up, 227 00:11:29,130 --> 00:11:33,136 killing the female and her young babies. 228 00:11:33,160 --> 00:11:35,968 Horrified, my colleagues remained behind 229 00:11:35,992 --> 00:11:38,009 to gather his thoughts 230 00:11:38,033 --> 00:11:41,493 and to record whatever he could the rest of the afternoon, 231 00:11:41,517 --> 00:11:46,386 and that evening, he captured a remarkable event: 232 00:11:46,410 --> 00:11:50,575 the lone surviving male beaver swimming in slow circles 233 00:11:50,599 --> 00:11:56,308 crying out inconsolably for its lost mate and offspring. 234 00:11:56,332 --> 00:11:59,217 This is probably the saddest sound 235 00:11:59,241 --> 00:12:02,135 I've ever heard coming from any organism, 236 00:12:02,159 --> 00:12:04,878 human or other. 237 00:12:06,517 --> 00:12:22,156 (Beaver crying) 238 00:12:22,180 --> 00:12:23,971 Yeah. Well. 239 00:12:23,995 --> 00:12:26,553 There are many facets to soundscapes, 240 00:12:26,577 --> 00:12:29,769 among them the ways in which animals taught us to dance and sing, 241 00:12:29,793 --> 00:12:32,394 which I'll save for another time. 242 00:12:32,418 --> 00:12:35,412 But you have heard how biophonies 243 00:12:35,436 --> 00:12:39,255 help clarify our understanding of the natural world. 244 00:12:39,279 --> 00:12:41,719 You've heard the impact of resource extraction, 245 00:12:41,743 --> 00:12:44,783 human noise and habitat destruction. 246 00:12:44,807 --> 00:12:47,046 And where environmental sciences have typically 247 00:12:47,070 --> 00:12:50,103 tried to understand the world from what we see, 248 00:12:50,127 --> 00:12:54,571 a much fuller understanding can be got from what we hear. 249 00:12:54,595 --> 00:12:58,428 Biophonies and geophonies are the signature voices 250 00:12:58,452 --> 00:13:00,419 of the natural world, 251 00:13:00,443 --> 00:13:01,772 and as we hear them, 252 00:13:01,796 --> 00:13:04,444 we're endowed with a sense of place, 253 00:13:04,468 --> 00:13:07,861 the true story of the world we live in. 254 00:13:07,885 --> 00:13:09,780 In a matter of seconds, 255 00:13:09,804 --> 00:13:12,495 a soundscape reveals much more information 256 00:13:12,519 --> 00:13:14,043 from many perspectives, 257 00:13:14,067 --> 00:13:18,665 from quantifiable data to cultural inspiration. 258 00:13:18,689 --> 00:13:21,566 Visual capture implicitly frames 259 00:13:21,590 --> 00:13:25,562 a limited frontal perspective of a given spatial context, 260 00:13:25,586 --> 00:13:27,935 while soundscapes widen that scope 261 00:13:27,959 --> 00:13:33,120 to a full 360 degrees, completely enveloping us. 262 00:13:33,144 --> 00:13:36,892 And while a picture may be worth 1,000 words, 263 00:13:36,916 --> 00:13:41,265 a soundscape is worth 1,000 pictures. 264 00:13:41,289 --> 00:13:43,389 And our ears tell us 265 00:13:43,413 --> 00:13:46,984 that the whisper of every leaf and creature 266 00:13:47,008 --> 00:13:50,058 speaks to the natural sources of our lives, 267 00:13:50,082 --> 00:13:55,120 which indeed may hold the secrets of love for all things, 268 00:13:55,144 --> 00:13:57,078 especially our own humanity, 269 00:13:57,102 --> 00:14:03,363 and the last word goes to a jaguar from the Amazon. 270 00:14:03,387 --> 00:14:17,111 (Growling) 271 00:14:17,135 --> 00:14:19,311 Thank you for listening. 272 00:14:19,335 --> 00:14:25,032 (Applause)