1 00:00:00,000 --> 00:00:03,000 The oceans cover some 70 percent of our planet. 2 00:00:03,000 --> 00:00:05,000 And I think Arthur C. Clarke probably had it right 3 00:00:05,000 --> 00:00:08,000 when he said that perhaps we ought to call our planet 4 00:00:08,000 --> 00:00:10,000 Planet Ocean. 5 00:00:10,000 --> 00:00:12,000 And the oceans are hugely productive, 6 00:00:12,000 --> 00:00:14,000 as you can see by the satellite image 7 00:00:14,000 --> 00:00:16,000 of photosynthesis, the production of new life. 8 00:00:16,000 --> 00:00:19,000 In fact, the oceans produce half of the new life every day on Earth 9 00:00:19,000 --> 00:00:22,000 as well as about half the oxygen that we breathe. 10 00:00:22,000 --> 00:00:25,000 In addition to that, it harbors a lot of the biodiversity on Earth, 11 00:00:25,000 --> 00:00:27,000 and much of it we don't know about. 12 00:00:27,000 --> 00:00:29,000 But I'll tell you some of that today. 13 00:00:29,000 --> 00:00:31,000 That also doesn't even get into the whole protein extraction 14 00:00:31,000 --> 00:00:33,000 that we do from the ocean. 15 00:00:33,000 --> 00:00:35,000 That's about 10 percent of our global needs 16 00:00:35,000 --> 00:00:38,000 and 100 percent of some island nations. 17 00:00:38,000 --> 00:00:40,000 If you were to descend 18 00:00:40,000 --> 00:00:42,000 into the 95 percent of the biosphere that's livable, 19 00:00:42,000 --> 00:00:44,000 it would quickly become pitch black, 20 00:00:44,000 --> 00:00:46,000 interrupted only by pinpoints of light 21 00:00:46,000 --> 00:00:48,000 from bioluminescent organisms. 22 00:00:48,000 --> 00:00:50,000 And if you turn the lights on, 23 00:00:50,000 --> 00:00:52,000 you might periodically see spectacular organisms swim by, 24 00:00:52,000 --> 00:00:54,000 because those are the denizens of the deep, 25 00:00:54,000 --> 00:00:56,000 the things that live in the deep ocean. 26 00:00:56,000 --> 00:00:59,000 And eventually, the deep sea floor would come into view. 27 00:00:59,000 --> 00:01:02,000 This type of habitat covers more of the Earth's surface 28 00:01:02,000 --> 00:01:04,000 than all other habitats combined. 29 00:01:04,000 --> 00:01:06,000 And yet, we know more about the surface of the Moon and about Mars 30 00:01:06,000 --> 00:01:08,000 than we do about this habitat, 31 00:01:08,000 --> 00:01:10,000 despite the fact that we have yet to extract 32 00:01:10,000 --> 00:01:13,000 a gram of food, a breath of oxygen or a drop of water 33 00:01:13,000 --> 00:01:15,000 from those bodies. 34 00:01:15,000 --> 00:01:17,000 And so 10 years ago, 35 00:01:17,000 --> 00:01:20,000 an international program began called the Census of Marine Life, 36 00:01:20,000 --> 00:01:22,000 which set out to try and improve our understanding 37 00:01:22,000 --> 00:01:24,000 of life in the global oceans. 38 00:01:24,000 --> 00:01:27,000 It involved 17 different projects around the world. 39 00:01:27,000 --> 00:01:29,000 As you can see, these are the footprints of the different projects. 40 00:01:29,000 --> 00:01:32,000 And I hope you'll appreciate the level of global coverage 41 00:01:32,000 --> 00:01:34,000 that it managed to achieve. 42 00:01:34,000 --> 00:01:36,000 It all began when two scientists, Fred Grassle and Jesse Ausubel, 43 00:01:36,000 --> 00:01:39,000 met in Woods Hole, Massachusetts 44 00:01:39,000 --> 00:01:41,000 where both were guests at the famed oceanographic institute. 45 00:01:41,000 --> 00:01:44,000 And Fred was lamenting the state of marine biodiversity 46 00:01:44,000 --> 00:01:47,000 and the fact that it was in trouble and nothing was being done about it. 47 00:01:47,000 --> 00:01:49,000 Well, from that discussion grew this program 48 00:01:49,000 --> 00:01:51,000 that involved 2,700 scientists 49 00:01:51,000 --> 00:01:53,000 from more than 80 countries around the world 50 00:01:53,000 --> 00:01:56,000 who engaged in 540 ocean expeditions 51 00:01:56,000 --> 00:01:59,000 at a combined cost of 650 million dollars 52 00:01:59,000 --> 00:02:01,000 to study the distribution, diversity and abundance 53 00:02:01,000 --> 00:02:04,000 of life in the global ocean. 54 00:02:04,000 --> 00:02:06,000 And so what did we find? 55 00:02:06,000 --> 00:02:08,000 We found spectacular new species, 56 00:02:08,000 --> 00:02:11,000 the most beautiful and visually stunning things everywhere we looked -- 57 00:02:11,000 --> 00:02:13,000 from the shoreline to the abyss, 58 00:02:13,000 --> 00:02:16,000 form microbes all the way up to fish and everything in between. 59 00:02:16,000 --> 00:02:19,000 And the limiting step here wasn't the unknown diversity of life, 60 00:02:19,000 --> 00:02:21,000 but rather the taxonomic specialists 61 00:02:21,000 --> 00:02:23,000 who can identify and catalog these species 62 00:02:23,000 --> 00:02:25,000 that became the limiting step. 63 00:02:25,000 --> 00:02:28,000 They, in fact, are an endangered species themselves. 64 00:02:28,000 --> 00:02:30,000 There are actually four to five new species 65 00:02:30,000 --> 00:02:32,000 described everyday for the oceans. 66 00:02:32,000 --> 00:02:35,000 And as I say, it could be a much larger number. 67 00:02:35,000 --> 00:02:38,000 Now, I come from Newfoundland in Canada -- 68 00:02:38,000 --> 00:02:40,000 It's an island off the east coast of that continent -- 69 00:02:40,000 --> 00:02:43,000 where we experienced one of the worst fishing disasters 70 00:02:43,000 --> 00:02:45,000 in human history. 71 00:02:45,000 --> 00:02:47,000 And so this photograph shows a small boy next to a codfish. 72 00:02:47,000 --> 00:02:49,000 It's around 1900. 73 00:02:49,000 --> 00:02:51,000 Now, when I was a boy of about his age, 74 00:02:51,000 --> 00:02:53,000 I would go out fishing with my grandfather 75 00:02:53,000 --> 00:02:55,000 and we would catch fish about half that size. 76 00:02:55,000 --> 00:02:57,000 And I thought that was the norm, 77 00:02:57,000 --> 00:02:59,000 because I had never seen fish like this. 78 00:02:59,000 --> 00:03:02,000 If you were to go out there today, 20 years after this fishery collapsed, 79 00:03:02,000 --> 00:03:05,000 if you could catch a fish, which would be a bit of a challenge, 80 00:03:05,000 --> 00:03:07,000 it would be half that size still. 81 00:03:07,000 --> 00:03:10,000 So what we're experiencing is something called shifting baselines. 82 00:03:10,000 --> 00:03:12,000 Our expectations of what the oceans can produce 83 00:03:12,000 --> 00:03:14,000 is something that we don't really appreciate 84 00:03:14,000 --> 00:03:17,000 because we haven't seen it in our lifetimes. 85 00:03:17,000 --> 00:03:20,000 Now most of us, and I would say me included, 86 00:03:20,000 --> 00:03:22,000 think that human exploitation of the oceans 87 00:03:22,000 --> 00:03:24,000 really only became very serious 88 00:03:24,000 --> 00:03:26,000 in the last 50 to, perhaps, 100 years or so. 89 00:03:26,000 --> 00:03:28,000 The census actually tried to look back in time, 90 00:03:28,000 --> 00:03:31,000 using every source of information they could get their hands on. 91 00:03:31,000 --> 00:03:33,000 And so anything from restaurant menus 92 00:03:33,000 --> 00:03:35,000 to monastery records to ships' logs 93 00:03:35,000 --> 00:03:37,000 to see what the oceans looked like. 94 00:03:37,000 --> 00:03:39,000 Because science data really goes back 95 00:03:39,000 --> 00:03:41,000 to, at best, World War II, for the most part. 96 00:03:41,000 --> 00:03:43,000 And so what they found, in fact, 97 00:03:43,000 --> 00:03:45,000 is that exploitation really began heavily with the Romans. 98 00:03:45,000 --> 00:03:48,000 And so at that time, of course, there was no refrigeration. 99 00:03:48,000 --> 00:03:50,000 So fishermen could only catch 100 00:03:50,000 --> 00:03:52,000 what they could either eat or sell that day. 101 00:03:52,000 --> 00:03:54,000 But the Romans developed salting. 102 00:03:54,000 --> 00:03:56,000 And with salting, 103 00:03:56,000 --> 00:03:59,000 it became possible to store fish and to transport it long distances. 104 00:03:59,000 --> 00:04:02,000 And so began industrial fishing. 105 00:04:02,000 --> 00:04:05,000 And so these are the sorts of extrapolations that we have 106 00:04:05,000 --> 00:04:07,000 of what sort of loss we've had 107 00:04:07,000 --> 00:04:10,000 relative to pre-human impacts on the ocean. 108 00:04:10,000 --> 00:04:12,000 They range from 65 to 98 percent 109 00:04:12,000 --> 00:04:14,000 for these major groups of organisms, 110 00:04:14,000 --> 00:04:16,000 as shown in the dark blue bars. 111 00:04:16,000 --> 00:04:19,000 Now for those species the we managed to leave alone, that we protect -- 112 00:04:19,000 --> 00:04:21,000 for example, marine mammals in recent years and sea birds -- 113 00:04:21,000 --> 00:04:23,000 there is some recovery. 114 00:04:23,000 --> 00:04:25,000 So it's not all hopeless. 115 00:04:25,000 --> 00:04:28,000 But for the most part, we've gone from salting to exhausting. 116 00:04:28,000 --> 00:04:30,000 Now this other line of evidence is a really interesting one. 117 00:04:30,000 --> 00:04:33,000 It's from trophy fish caught off the coast of Florida. 118 00:04:33,000 --> 00:04:36,000 And so this is a photograph from the 1950s. 119 00:04:36,000 --> 00:04:38,000 I want you to notice the scale on the slide, 120 00:04:38,000 --> 00:04:40,000 because when you see the same picture from the 1980s, 121 00:04:40,000 --> 00:04:42,000 we see the fish are much smaller 122 00:04:42,000 --> 00:04:44,000 and we're also seeing a change 123 00:04:44,000 --> 00:04:46,000 in terms of the composition of those fish. 124 00:04:46,000 --> 00:04:48,000 By 2007, the catch was actually laughable 125 00:04:48,000 --> 00:04:50,000 in terms of the size for a trophy fish. 126 00:04:50,000 --> 00:04:52,000 But this is no laughing matter. 127 00:04:52,000 --> 00:04:54,000 The oceans have lost a lot of their productivity 128 00:04:54,000 --> 00:04:57,000 and we're responsible for it. 129 00:04:57,000 --> 00:04:59,000 So what's left? Actually quite a lot. 130 00:04:59,000 --> 00:05:02,000 There's a lot of exciting things, and I'm going to tell you a little bit about them. 131 00:05:02,000 --> 00:05:04,000 And I want to start with a bit on technology, 132 00:05:04,000 --> 00:05:06,000 because, of course, this is a TED Conference 133 00:05:06,000 --> 00:05:08,000 and you want to hear something on technology. 134 00:05:08,000 --> 00:05:10,000 So one of the tools that we use to sample the deep ocean 135 00:05:10,000 --> 00:05:12,000 are remotely operated vehicles. 136 00:05:12,000 --> 00:05:15,000 So these are tethered vehicles we lower down to the sea floor 137 00:05:15,000 --> 00:05:18,000 where they're our eyes and our hands for working on the sea bottom. 138 00:05:18,000 --> 00:05:21,000 So a couple of years ago, I was supposed to go on an oceanographic cruise 139 00:05:21,000 --> 00:05:24,000 and I couldn't go because of a scheduling conflict. 140 00:05:24,000 --> 00:05:27,000 But through a satellite link I was able to sit at my study at home 141 00:05:27,000 --> 00:05:30,000 with my dog curled up at my feet, a cup of tea in my hand, 142 00:05:30,000 --> 00:05:32,000 and I could tell the pilot, "I want a sample right there." 143 00:05:32,000 --> 00:05:34,000 And that's exactly what the pilot did for me. 144 00:05:34,000 --> 00:05:37,000 That's the sort of technology that's available today 145 00:05:37,000 --> 00:05:39,000 that really wasn't available even a decade ago. 146 00:05:39,000 --> 00:05:41,000 So it allows us to sample these amazing habitats 147 00:05:41,000 --> 00:05:43,000 that are very far from the surface 148 00:05:43,000 --> 00:05:45,000 and very far from light. 149 00:05:45,000 --> 00:05:48,000 And so one of the tools that we can use to sample the oceans 150 00:05:48,000 --> 00:05:50,000 is acoustics, or sound waves. 151 00:05:50,000 --> 00:05:52,000 And the advantage of sound waves 152 00:05:52,000 --> 00:05:54,000 is that they actually pass well through water, unlike light. 153 00:05:54,000 --> 00:05:56,000 And so we can send out sound waves, 154 00:05:56,000 --> 00:05:59,000 they bounce off objects like fish and are reflected back. 155 00:05:59,000 --> 00:06:02,000 And so in this example, a census scientist took out two ships. 156 00:06:02,000 --> 00:06:04,000 One would send out sound waves that would bounce back. 157 00:06:04,000 --> 00:06:06,000 They would be received by a second ship, 158 00:06:06,000 --> 00:06:09,000 and that would give us very precise estimates, in this case, 159 00:06:09,000 --> 00:06:11,000 of 250 billion herring 160 00:06:11,000 --> 00:06:13,000 in a period of about a minute. 161 00:06:13,000 --> 00:06:16,000 And that's an area about the size of Manhattan Island. 162 00:06:16,000 --> 00:06:18,000 And to be able to do that is a tremendous fisheries tool, 163 00:06:18,000 --> 00:06:21,000 because knowing how many fish are there is really critical. 164 00:06:21,000 --> 00:06:23,000 We can also use satellite tags 165 00:06:23,000 --> 00:06:25,000 to track animals as they move through the oceans. 166 00:06:25,000 --> 00:06:27,000 And so for animals that come to the surface to breathe, 167 00:06:27,000 --> 00:06:29,000 such as this elephant seal, 168 00:06:29,000 --> 00:06:31,000 it's an opportunity to send data back to shore 169 00:06:31,000 --> 00:06:34,000 and tell us where exactly it is in the ocean. 170 00:06:34,000 --> 00:06:36,000 And so from that we can produce these tracks. 171 00:06:36,000 --> 00:06:38,000 For example, the dark blue 172 00:06:38,000 --> 00:06:40,000 shows you where the elephant seal moved in the north Pacific. 173 00:06:40,000 --> 00:06:43,000 Now I realize for those of you who are colorblind, this slide is not very helpful, 174 00:06:43,000 --> 00:06:45,000 but stick with me nonetheless. 175 00:06:45,000 --> 00:06:47,000 For animals that don't surface, 176 00:06:47,000 --> 00:06:49,000 we have something called pop-up tags, 177 00:06:49,000 --> 00:06:52,000 which collect data about light and what time the sun rises and sets. 178 00:06:52,000 --> 00:06:54,000 And then at some period of time 179 00:06:54,000 --> 00:06:57,000 it pops up to the surface and, again, relays that data back to shore. 180 00:06:57,000 --> 00:07:00,000 Because GPS doesn't work under water. That's why we need these tools. 181 00:07:00,000 --> 00:07:03,000 And so from this we're able to identify these blue highways, 182 00:07:03,000 --> 00:07:05,000 these hot spots in the ocean, 183 00:07:05,000 --> 00:07:07,000 that should be real priority areas 184 00:07:07,000 --> 00:07:09,000 for ocean conservation. 185 00:07:09,000 --> 00:07:11,000 Now one of the other things that you may think about 186 00:07:11,000 --> 00:07:14,000 is that, when you go to the supermarket and you buy things, they're scanned. 187 00:07:14,000 --> 00:07:16,000 And so there's a barcode on that product 188 00:07:16,000 --> 00:07:19,000 that tells the computer exactly what the product is. 189 00:07:19,000 --> 00:07:22,000 Geneticists have developed a similar tool called genetic barcoding. 190 00:07:22,000 --> 00:07:24,000 And what barcoding does 191 00:07:24,000 --> 00:07:26,000 is use a specific gene called CO1 192 00:07:26,000 --> 00:07:29,000 that's consistent within a species, but varies among species. 193 00:07:29,000 --> 00:07:31,000 And so what that means is we can unambiguously identify 194 00:07:31,000 --> 00:07:33,000 which species are which 195 00:07:33,000 --> 00:07:35,000 even if they look similar to each other, 196 00:07:35,000 --> 00:07:37,000 but may be biologically quite different. 197 00:07:37,000 --> 00:07:39,000 Now one of the nicest examples I like to cite on this 198 00:07:39,000 --> 00:07:42,000 is the story of two young women, high school students in New York City, 199 00:07:42,000 --> 00:07:44,000 who worked with the census. 200 00:07:44,000 --> 00:07:47,000 They went out and collected fish from markets and from restaurants in New York City 201 00:07:47,000 --> 00:07:49,000 and they barcoded it. 202 00:07:49,000 --> 00:07:51,000 Well what they found was mislabeled fish. 203 00:07:51,000 --> 00:07:53,000 So for example, 204 00:07:53,000 --> 00:07:55,000 they found something which was sold as tuna, which is very valuable, 205 00:07:55,000 --> 00:07:58,000 was in fact tilapia, which is a much less valuable fish. 206 00:07:58,000 --> 00:08:00,000 They also found an endangered species 207 00:08:00,000 --> 00:08:02,000 sold as a common one. 208 00:08:02,000 --> 00:08:04,000 So barcoding allows us to know what we're working with 209 00:08:04,000 --> 00:08:07,000 and also what we're eating. 210 00:08:07,000 --> 00:08:09,000 The Ocean Biogeographic Information System 211 00:08:09,000 --> 00:08:11,000 is the database for all the census data. 212 00:08:11,000 --> 00:08:14,000 It's open access; you can all go in and download data as you wish. 213 00:08:14,000 --> 00:08:17,000 And it contains all the data from the census 214 00:08:17,000 --> 00:08:19,000 plus other data sets that people were willing to contribute. 215 00:08:19,000 --> 00:08:21,000 And so what you can do with that 216 00:08:21,000 --> 00:08:24,000 is to plot the distribution of species and where they occur in the oceans. 217 00:08:24,000 --> 00:08:26,000 What I've plotted up here is the data that we have on hand. 218 00:08:26,000 --> 00:08:29,000 This is where our sampling effort has concentrated. 219 00:08:29,000 --> 00:08:31,000 Now what you can see 220 00:08:31,000 --> 00:08:33,000 is we've sampled the area in the North Atlantic, 221 00:08:33,000 --> 00:08:35,000 in the North Sea in particular, 222 00:08:35,000 --> 00:08:37,000 and also the east coast of North America fairly well. 223 00:08:37,000 --> 00:08:40,000 That's the warm colors which show a well-sampled region. 224 00:08:40,000 --> 00:08:42,000 The cold colors, the blue and the black, 225 00:08:42,000 --> 00:08:44,000 show areas where we have almost no data. 226 00:08:44,000 --> 00:08:46,000 So even after a 10-year census, 227 00:08:46,000 --> 00:08:49,000 there are large areas that still remain unexplored. 228 00:08:49,000 --> 00:08:52,000 Now there are a group of scientists living in Texas, working in the Gulf of Mexico 229 00:08:52,000 --> 00:08:54,000 who decided really as a labor of love 230 00:08:54,000 --> 00:08:56,000 to pull together all the knowledge they could 231 00:08:56,000 --> 00:08:58,000 about biodiversity in the Gulf of Mexico. 232 00:08:58,000 --> 00:09:01,000 And so they put this together, a list of all the species, 233 00:09:01,000 --> 00:09:03,000 where they're known to occur, 234 00:09:03,000 --> 00:09:06,000 and it really seemed like a very esoteric, scientific type of exercise. 235 00:09:06,000 --> 00:09:09,000 But then, of course, there was the Deep Horizon oil spill. 236 00:09:09,000 --> 00:09:11,000 So all of a sudden, this labor of love 237 00:09:11,000 --> 00:09:14,000 for no obvious economic reason 238 00:09:14,000 --> 00:09:16,000 has become a critical piece of information 239 00:09:16,000 --> 00:09:19,000 in terms of how that system is going to recover, how long it will take 240 00:09:19,000 --> 00:09:21,000 and how the lawsuits 241 00:09:21,000 --> 00:09:24,000 and the multi-billion-dollar discussions that are going to happen in the coming years 242 00:09:24,000 --> 00:09:27,000 are likely to be resolved. 243 00:09:27,000 --> 00:09:29,000 So what did we find? 244 00:09:29,000 --> 00:09:31,000 Well, I could stand here for hours, but, of course, I'm not allowed to do that. 245 00:09:31,000 --> 00:09:33,000 But I will tell you some of my favorite discoveries 246 00:09:33,000 --> 00:09:35,000 from the census. 247 00:09:35,000 --> 00:09:38,000 So one of the things we discovered is where are the hot spots of diversity? 248 00:09:38,000 --> 00:09:41,000 Where do we find the most species of ocean life? 249 00:09:41,000 --> 00:09:43,000 And what we find if we plot up the well-known species 250 00:09:43,000 --> 00:09:45,000 is this sort of a distribution. 251 00:09:45,000 --> 00:09:47,000 And what we see is that for coastal tags, 252 00:09:47,000 --> 00:09:49,000 for those organisms that live near the shoreline, 253 00:09:49,000 --> 00:09:51,000 they're most diverse in the tropics. 254 00:09:51,000 --> 00:09:53,000 This is something we've actually known for a while, 255 00:09:53,000 --> 00:09:55,000 so it's not a real breakthrough. 256 00:09:55,000 --> 00:09:57,000 What is really exciting though 257 00:09:57,000 --> 00:09:59,000 is that the oceanic tags, or the ones that live far from the coast, 258 00:09:59,000 --> 00:10:01,000 are actually more diverse at intermediate latitudes. 259 00:10:01,000 --> 00:10:04,000 This is the sort of data, again, that managers could use 260 00:10:04,000 --> 00:10:07,000 if they want to prioritize areas of the ocean that we need to conserve. 261 00:10:07,000 --> 00:10:10,000 You can do this on a global scale, but you can also do it on a regional scale. 262 00:10:10,000 --> 00:10:13,000 And that's why biodiversity data can be so valuable. 263 00:10:13,000 --> 00:10:16,000 Now while a lot of the species we discovered in the census 264 00:10:16,000 --> 00:10:18,000 are things that are small and hard to see, 265 00:10:18,000 --> 00:10:20,000 that certainly wasn't always the case. 266 00:10:20,000 --> 00:10:22,000 For example, while it's hard to believe 267 00:10:22,000 --> 00:10:24,000 that a three kilogram lobster could elude scientists, 268 00:10:24,000 --> 00:10:26,000 it did until a few years ago 269 00:10:26,000 --> 00:10:29,000 when South African fishermen requested an export permit 270 00:10:29,000 --> 00:10:32,000 and scientists realized that this was something new to science. 271 00:10:32,000 --> 00:10:34,000 Similarly this Golden V kelp 272 00:10:34,000 --> 00:10:36,000 collected in Alaska just below the low water mark 273 00:10:36,000 --> 00:10:38,000 is probably a new species. 274 00:10:38,000 --> 00:10:40,000 Even though it's three meters long, 275 00:10:40,000 --> 00:10:42,000 it actually, again, eluded science. 276 00:10:42,000 --> 00:10:45,000 Now this guy, this bigfin squid, is seven meters in length. 277 00:10:45,000 --> 00:10:48,000 But to be fair, it lives in the deep waters of the Mid-Atlantic Ridge, 278 00:10:48,000 --> 00:10:50,000 so it was a lot harder to find. 279 00:10:50,000 --> 00:10:53,000 But there's still potential for discovery of big and exciting things. 280 00:10:53,000 --> 00:10:56,000 This particular shrimp, we've dubbed it the Jurassic shrimp, 281 00:10:56,000 --> 00:10:58,000 it's thought to have gone extinct 50 years ago -- 282 00:10:58,000 --> 00:11:00,000 at least it was, until the census discovered 283 00:11:00,000 --> 00:11:03,000 it was living and doing just fine off the coast of Australia. 284 00:11:03,000 --> 00:11:06,000 And it shows that the ocean, because of its vastness, 285 00:11:06,000 --> 00:11:08,000 can hide secrets for a very long time. 286 00:11:08,000 --> 00:11:11,000 So, Steven Spielberg, eat your heart out. 287 00:11:11,000 --> 00:11:14,000 If we look at distributions, in fact distributions change dramatically. 288 00:11:14,000 --> 00:11:17,000 And so one of the records that we had 289 00:11:17,000 --> 00:11:20,000 was this sooty shearwater, which undergoes these spectacular migrations 290 00:11:20,000 --> 00:11:22,000 all the way from New Zealand 291 00:11:22,000 --> 00:11:24,000 all the way up to Alaska and back again 292 00:11:24,000 --> 00:11:26,000 in search of endless summer 293 00:11:26,000 --> 00:11:28,000 as they complete their life cycles. 294 00:11:28,000 --> 00:11:30,000 We also talked about the White Shark Cafe. 295 00:11:30,000 --> 00:11:33,000 This is a location in the Pacific where white shark converge. 296 00:11:33,000 --> 00:11:35,000 We don't know why they converge there, we simply don't know. 297 00:11:35,000 --> 00:11:37,000 That's a question for the future. 298 00:11:37,000 --> 00:11:39,000 One of the things that we're taught in high school 299 00:11:39,000 --> 00:11:42,000 is that all animals require oxygen in order to survive. 300 00:11:42,000 --> 00:11:45,000 Now this little critter, it's only about half a millimeter in size, 301 00:11:45,000 --> 00:11:47,000 not terribly charismatic. 302 00:11:47,000 --> 00:11:49,000 But it was only discovered in the early 1980s. 303 00:11:49,000 --> 00:11:51,000 But the really interesting thing about it 304 00:11:51,000 --> 00:11:54,000 is that, a few years ago, census scientists discovered 305 00:11:54,000 --> 00:11:56,000 that this guy can thrive in oxygen-poor sediments 306 00:11:56,000 --> 00:11:58,000 in the deep Mediterranean Sea. 307 00:11:58,000 --> 00:12:00,000 So now they know that, in fact, 308 00:12:00,000 --> 00:12:02,000 animals can live without oxygen, at least some of them, 309 00:12:02,000 --> 00:12:05,000 and that they can adapt to even the harshest of conditions. 310 00:12:05,000 --> 00:12:08,000 If you were to suck all the water out of the ocean, 311 00:12:08,000 --> 00:12:10,000 this is what you'd be left behind with, 312 00:12:10,000 --> 00:12:12,000 and that's the biomass of life on the sea floor. 313 00:12:12,000 --> 00:12:15,000 Now what we see is huge biomass towards the poles 314 00:12:15,000 --> 00:12:18,000 and not much biomass in between. 315 00:12:18,000 --> 00:12:20,000 We found life in the extremes. 316 00:12:20,000 --> 00:12:22,000 And so there were new species that were found 317 00:12:22,000 --> 00:12:24,000 that live inside ice 318 00:12:24,000 --> 00:12:26,000 and help to support an ice-based food web. 319 00:12:26,000 --> 00:12:28,000 And we also found this spectacular yeti crab 320 00:12:28,000 --> 00:12:31,000 that lives near boiling hot hydrothermal vents at Easter Island. 321 00:12:31,000 --> 00:12:33,000 And this particular species 322 00:12:33,000 --> 00:12:36,000 really captured the public's attention. 323 00:12:36,000 --> 00:12:39,000 We also found the deepest vents known yet -- 5,000 meters -- 324 00:12:39,000 --> 00:12:42,000 the hottest vents at 407 degrees Celsius -- 325 00:12:42,000 --> 00:12:44,000 vents in the South Pacific and also in the Arctic 326 00:12:44,000 --> 00:12:46,000 where none had been found before. 327 00:12:46,000 --> 00:12:49,000 So even new environments are still within the domain of the discoverable. 328 00:12:49,000 --> 00:12:51,000 Now in terms of the unknowns, there are many. 329 00:12:51,000 --> 00:12:53,000 And I'm just going to summarize just a few of them 330 00:12:53,000 --> 00:12:55,000 very quickly for you. 331 00:12:55,000 --> 00:12:58,000 First of all, we might ask, how many fishes in the sea? 332 00:12:58,000 --> 00:13:00,000 We actually know the fishes better than we do any other group in the ocean 333 00:13:00,000 --> 00:13:02,000 other than marine mammals. 334 00:13:02,000 --> 00:13:05,000 And so we can actually extrapolate based on rates of discovery 335 00:13:05,000 --> 00:13:08,000 how many more species we're likely to discover. 336 00:13:08,000 --> 00:13:10,000 And from that, we actually calculate 337 00:13:10,000 --> 00:13:13,000 that we know about 16,500 marine species 338 00:13:13,000 --> 00:13:15,000 and there are probably another 1,000 to 4,000 left to go. 339 00:13:15,000 --> 00:13:17,000 So we've done pretty well. 340 00:13:17,000 --> 00:13:19,000 We've got about 75 percent of the fish, 341 00:13:19,000 --> 00:13:21,000 maybe as much as 90 percent. 342 00:13:21,000 --> 00:13:24,000 But the fishes, as I say, are the best known. 343 00:13:24,000 --> 00:13:27,000 So our level of knowledge is much less for other groups of organisms. 344 00:13:27,000 --> 00:13:29,000 Now this figure is actually based on a brand new paper 345 00:13:29,000 --> 00:13:32,000 that's going to come out in the journal PLoS Biology. 346 00:13:32,000 --> 00:13:34,000 And what is does is predict how many more species there are 347 00:13:34,000 --> 00:13:36,000 on land and in the ocean. 348 00:13:36,000 --> 00:13:38,000 And what they found 349 00:13:38,000 --> 00:13:41,000 is that they think that we know of about nine percent of the species in the ocean. 350 00:13:41,000 --> 00:13:43,000 That means 91 percent, even after the census, 351 00:13:43,000 --> 00:13:45,000 still remain to be discovered. 352 00:13:45,000 --> 00:13:47,000 And so that turns out to be about two million species 353 00:13:47,000 --> 00:13:49,000 once all is said and done. 354 00:13:49,000 --> 00:13:51,000 So we still have quite a lot of work to do 355 00:13:51,000 --> 00:13:53,000 in terms of unknowns. 356 00:13:53,000 --> 00:13:55,000 Now this bacterium 357 00:13:55,000 --> 00:13:58,000 is part of mats that are found off the coast of Chile. 358 00:13:58,000 --> 00:14:00,000 And these mats actually cover an area the size of Greece. 359 00:14:00,000 --> 00:14:03,000 And so this particular bacterium is actually visible to the naked eye. 360 00:14:03,000 --> 00:14:06,000 But you can imagine the biomass that represents. 361 00:14:06,000 --> 00:14:08,000 But the really intriguing thing about the microbes 362 00:14:08,000 --> 00:14:10,000 is just how diverse they are. 363 00:14:10,000 --> 00:14:12,000 A single drop of seawater 364 00:14:12,000 --> 00:14:14,000 could contain 160 different types of microbes. 365 00:14:14,000 --> 00:14:16,000 And the oceans themselves 366 00:14:16,000 --> 00:14:19,000 are thought potentially to contain as many as a billion different types. 367 00:14:19,000 --> 00:14:22,000 So that's really exciting. What are they all doing out there? 368 00:14:22,000 --> 00:14:24,000 We actually don't know. 369 00:14:24,000 --> 00:14:26,000 The most exciting thing, I would say, about this census 370 00:14:26,000 --> 00:14:28,000 is the role of global science. 371 00:14:28,000 --> 00:14:30,000 And so as we see in this image of light during the night, 372 00:14:30,000 --> 00:14:32,000 there are lots of areas of the Earth 373 00:14:32,000 --> 00:14:35,000 where human development is much greater 374 00:14:35,000 --> 00:14:37,000 and other areas where it's much less, 375 00:14:37,000 --> 00:14:39,000 but between them we see large dark areas 376 00:14:39,000 --> 00:14:41,000 of relatively unexplored ocean. 377 00:14:41,000 --> 00:14:43,000 The other point I'd like to make about this 378 00:14:43,000 --> 00:14:45,000 is that this ocean's interconnected. 379 00:14:45,000 --> 00:14:47,000 Marine organisms do not care about international boundaries; 380 00:14:47,000 --> 00:14:49,000 they move where they will. 381 00:14:49,000 --> 00:14:52,000 And so the importance then of global collaboration 382 00:14:52,000 --> 00:14:54,000 becomes all the more important. 383 00:14:54,000 --> 00:14:56,000 We've lost a lot of paradise. 384 00:14:56,000 --> 00:14:59,000 For example, these tuna that were once so abundant in the North Sea 385 00:14:59,000 --> 00:15:01,000 are now effectively gone. 386 00:15:01,000 --> 00:15:04,000 There were trawls taken in the deep sea in the Mediterranean, 387 00:15:04,000 --> 00:15:06,000 which collected more garbage than they did animals. 388 00:15:06,000 --> 00:15:09,000 And that's the deep sea, that's the environment that we consider to be 389 00:15:09,000 --> 00:15:11,000 among the most pristine left on Earth. 390 00:15:11,000 --> 00:15:13,000 And there are a lot of other pressures. 391 00:15:13,000 --> 00:15:16,000 Ocean acidification is a really big issue that people are concerned with, 392 00:15:16,000 --> 00:15:19,000 as well as ocean warming, and the effects they're going to have on coral reefs. 393 00:15:19,000 --> 00:15:22,000 On the scale of decades, in our lifetimes, 394 00:15:22,000 --> 00:15:24,000 we're going to see a lot of damage to coral reefs. 395 00:15:24,000 --> 00:15:27,000 And I could spend the rest of my time, which is getting very limited, 396 00:15:27,000 --> 00:15:29,000 going through this litany of concerns about the ocean, 397 00:15:29,000 --> 00:15:31,000 but I want to end on a more positive note. 398 00:15:31,000 --> 00:15:33,000 And so the grand challenge then 399 00:15:33,000 --> 00:15:35,000 is to try and make sure that we preserve what's left, 400 00:15:35,000 --> 00:15:37,000 because there is still spectacular beauty. 401 00:15:37,000 --> 00:15:39,000 And the oceans are so productive, 402 00:15:39,000 --> 00:15:42,000 there's so much going on in there that's of relevance to humans 403 00:15:42,000 --> 00:15:45,000 that we really need to, even from a selfish perspective, 404 00:15:45,000 --> 00:15:47,000 try to do better than we have in the past. 405 00:15:47,000 --> 00:15:49,000 So we need to recognize those hot spots 406 00:15:49,000 --> 00:15:51,000 and do our best to protect them. 407 00:15:51,000 --> 00:15:53,000 When we look at pictures like this, they take our breath away, 408 00:15:53,000 --> 00:15:55,000 in addition to helping to give us breath 409 00:15:55,000 --> 00:15:57,000 by the oxygen that the oceans provide. 410 00:15:57,000 --> 00:16:00,000 Census scientists worked in the rain, they worked in the cold, 411 00:16:00,000 --> 00:16:02,000 they worked under water and they worked above water 412 00:16:02,000 --> 00:16:04,000 trying to illuminate the wondrous discovery, 413 00:16:04,000 --> 00:16:06,000 the still vast unknown, 414 00:16:06,000 --> 00:16:09,000 the spectacular adaptations that we see in ocean life. 415 00:16:09,000 --> 00:16:12,000 So whether you're a yak herder living in the mountains of Chile, 416 00:16:12,000 --> 00:16:15,000 whether you're a stockbroker in New York City 417 00:16:15,000 --> 00:16:17,000 or whether you're a TEDster living in Edinburgh, 418 00:16:17,000 --> 00:16:19,000 the oceans matter. 419 00:16:19,000 --> 00:16:21,000 And as the oceans go so shall we. 420 00:16:21,000 --> 00:16:23,000 Thanks for listening. 421 00:16:23,000 --> 00:16:25,000 (Applause)