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If you are capable, please help us to create good quality subtitles: https://c3subtitles.de/talk/894 Thanks! 1 00:00:15,170 --> 00:00:17,569 Give a warm applause 2 00:00:17,570 --> 00:00:19,639 for Dr. Benjamin 3 00:00:19,640 --> 00:00:22,010 Leon Bulahdelah ski. 4 00:00:33,140 --> 00:00:35,719 Doctoral researcher at the Potsdam 5 00:00:35,720 --> 00:00:37,939 Institute for Climate Impact 6 00:00:37,940 --> 00:00:40,819 Research, and he's designing 7 00:00:40,820 --> 00:00:44,429 quantitative computer models. 8 00:00:44,430 --> 00:00:46,919 And global nitrogen cycle 9 00:00:46,920 --> 00:00:49,679 simulation, so it's like civilization 10 00:00:49,680 --> 00:00:52,229 eight nor with more realistic. 11 00:00:52,230 --> 00:00:54,059 And what we can learn from it and what 12 00:00:54,060 --> 00:00:55,199 how we can use it. 13 00:00:55,200 --> 00:00:56,200 You will hear now. 14 00:01:07,070 --> 00:01:08,070 Station, 15 00:01:09,350 --> 00:01:11,720 what we are doing there is we are doing 16 00:01:12,860 --> 00:01:15,739 computer simulations 17 00:01:15,740 --> 00:01:17,899 of all kinds of sciences, from 18 00:01:17,900 --> 00:01:20,389 natural sciences to social sciences, 19 00:01:20,390 --> 00:01:22,759 um, but this campus 20 00:01:22,760 --> 00:01:24,919 has actually a long history already 21 00:01:24,920 --> 00:01:25,999 of science. 22 00:01:26,000 --> 00:01:27,919 So it used to be the Astrophysical 23 00:01:27,920 --> 00:01:29,659 Institute at the Astrophysical 24 00:01:29,660 --> 00:01:31,849 Observatory and Metrological 25 00:01:31,850 --> 00:01:34,099 Observatory, and quite 26 00:01:34,100 --> 00:01:36,419 a few experiments were carried out there. 27 00:01:36,420 --> 00:01:38,749 So we, um, 28 00:01:38,750 --> 00:01:40,819 there was the Gevalia measure, the 29 00:01:40,820 --> 00:01:42,169 value of gravity. 30 00:01:42,170 --> 00:01:44,509 The first earthquake was recorded or 31 00:01:44,510 --> 00:01:47,059 some equations 32 00:01:47,060 --> 00:01:49,159 of the relativity theory 33 00:01:49,160 --> 00:01:52,009 of the field equations were solved 34 00:01:52,010 --> 00:01:54,379 in this former institute since 35 00:01:54,380 --> 00:01:56,569 1990. Now it's 36 00:01:56,570 --> 00:01:58,249 the Potsdam Institute for Climate Impact 37 00:01:58,250 --> 00:01:59,359 Research. 38 00:01:59,360 --> 00:02:01,309 And what you can see nicely here, these 39 00:02:01,310 --> 00:02:03,979 buildings are still the old cupolas, 40 00:02:03,980 --> 00:02:06,649 which show which have inside 41 00:02:06,650 --> 00:02:08,719 or which used to have inside large 42 00:02:08,720 --> 00:02:10,189 telescopes. 43 00:02:10,190 --> 00:02:12,619 And these telescopes are a bit a symbol 44 00:02:12,620 --> 00:02:13,620 for the first 45 00:02:14,810 --> 00:02:16,879 scientific revolution, the first 46 00:02:16,880 --> 00:02:19,189 Copernican revolution, 47 00:02:19,190 --> 00:02:21,679 which happened about 48 00:02:21,680 --> 00:02:23,030 400 years ago. 49 00:02:24,170 --> 00:02:26,449 And the scientific revolution 50 00:02:26,450 --> 00:02:28,669 was sparked by 51 00:02:28,670 --> 00:02:31,459 the technical development of lenses 52 00:02:31,460 --> 00:02:34,369 which allow you to use microscopes 53 00:02:34,370 --> 00:02:35,719 or telescopes. 54 00:02:35,720 --> 00:02:37,909 And this opened 55 00:02:37,910 --> 00:02:39,469 up a new field of research because 56 00:02:39,470 --> 00:02:41,689 suddenly you could see things which 57 00:02:41,690 --> 00:02:44,119 were quite small, even 58 00:02:44,120 --> 00:02:46,279 larger, you could see things 59 00:02:46,280 --> 00:02:48,499 in detail, and you suddenly 60 00:02:48,500 --> 00:02:50,569 had a view inside 61 00:02:50,570 --> 00:02:53,149 the huge complexity, 62 00:02:53,150 --> 00:02:55,579 both inside a cell or 63 00:02:55,580 --> 00:02:57,919 inside of our universe. 64 00:02:57,920 --> 00:03:00,019 Some scholars argue that today now 65 00:03:00,020 --> 00:03:02,509 we are living in the second Copernican 66 00:03:02,510 --> 00:03:04,699 revolution and this 67 00:03:04,700 --> 00:03:06,829 second Copernican revolution is 68 00:03:06,830 --> 00:03:09,379 triggered by the development of so-called 69 00:03:09,380 --> 00:03:10,380 microscopes. 70 00:03:11,450 --> 00:03:13,249 Probably nobody of you ever heard this 71 00:03:13,250 --> 00:03:14,779 word because it's invented. 72 00:03:14,780 --> 00:03:16,610 Um, hello, translators. 73 00:03:17,720 --> 00:03:19,849 But maybe you can 74 00:03:19,850 --> 00:03:21,259 think what it means. 75 00:03:21,260 --> 00:03:23,869 It's kind of the inverse of a microscope 76 00:03:23,870 --> 00:03:26,089 instead of showing you things 77 00:03:26,090 --> 00:03:27,289 in more detail. 78 00:03:27,290 --> 00:03:29,239 Actually, it has to be because it shows 79 00:03:29,240 --> 00:03:31,219 you things in less detail. 80 00:03:31,220 --> 00:03:33,289 It reduces the complexity 81 00:03:33,290 --> 00:03:34,669 of the real world. 82 00:03:34,670 --> 00:03:36,529 And this is something that is really 83 00:03:36,530 --> 00:03:38,539 necessary because the complexity of the 84 00:03:38,540 --> 00:03:40,489 real world is sometimes overwhelming. 85 00:03:40,490 --> 00:03:42,739 And if you want to make decisions, we 86 00:03:42,740 --> 00:03:45,109 sometimes need simpler 87 00:03:45,110 --> 00:03:47,479 versions of the real world to understand 88 00:03:47,480 --> 00:03:48,480 them. 89 00:03:49,040 --> 00:03:51,709 So how can a microscope look like? 90 00:03:51,710 --> 00:03:53,389 Well, the first approach is quite 91 00:03:53,390 --> 00:03:54,559 straightforward. 92 00:03:54,560 --> 00:03:56,689 If you want to see something in 93 00:03:56,690 --> 00:03:58,879 less detail, you just go 94 00:03:58,880 --> 00:04:00,979 go one step back or 95 00:04:00,980 --> 00:04:02,719 two step X or even further. 96 00:04:03,860 --> 00:04:06,080 So one option is a satellite 97 00:04:07,220 --> 00:04:08,539 from out of this. 98 00:04:08,540 --> 00:04:10,669 If you look from a satellite on the 99 00:04:10,670 --> 00:04:12,739 earth, you can see the 100 00:04:12,740 --> 00:04:15,229 micro development on the planet. 101 00:04:15,230 --> 00:04:17,599 And while 102 00:04:17,600 --> 00:04:19,338 things that you can see is first of all, 103 00:04:19,339 --> 00:04:20,989 the Earth is quite a beautiful planet, 104 00:04:20,990 --> 00:04:22,040 but you can also see 105 00:04:23,090 --> 00:04:25,039 what's happening on the planet right now, 106 00:04:25,040 --> 00:04:27,319 that the streets are 107 00:04:27,320 --> 00:04:29,389 going into pristine forests, that 108 00:04:29,390 --> 00:04:31,519 we are burning down forests all 109 00:04:31,520 --> 00:04:32,719 over the world. 110 00:04:32,720 --> 00:04:34,939 Um, that at 111 00:04:34,940 --> 00:04:37,729 nighttime the earth is still illuminated 112 00:04:37,730 --> 00:04:40,699 by electric lights from the cities. 113 00:04:40,700 --> 00:04:42,859 And you can see how strongly 114 00:04:42,860 --> 00:04:45,139 we already shape the way 115 00:04:45,140 --> 00:04:47,059 the planet looks like today. 116 00:04:47,060 --> 00:04:48,559 You can clearly see that we are now 117 00:04:48,560 --> 00:04:50,360 living already in the Anthropocene. 118 00:04:51,530 --> 00:04:53,749 A second option to see 119 00:04:53,750 --> 00:04:56,119 the earth system 120 00:04:56,120 --> 00:04:58,459 in a reduced form is 121 00:04:58,460 --> 00:05:01,309 you can rebuild it in a smaller scale. 122 00:05:01,310 --> 00:05:03,379 This has been this has been carried 123 00:05:03,380 --> 00:05:05,449 out in the 1990s with the 124 00:05:05,450 --> 00:05:06,860 Biosphere two experiment. 125 00:05:08,060 --> 00:05:10,099 It's basically a whole earth system in a 126 00:05:10,100 --> 00:05:12,289 glass house, in a confined glass house, 127 00:05:12,290 --> 00:05:14,119 which has an ocean, which has a 128 00:05:14,120 --> 00:05:16,909 rainforest and a desert, 129 00:05:16,910 --> 00:05:19,519 and also eight human scientists 130 00:05:19,520 --> 00:05:20,959 living within. 131 00:05:20,960 --> 00:05:23,029 And you can see 132 00:05:23,030 --> 00:05:25,129 it as a successful failure in the 133 00:05:25,130 --> 00:05:27,259 way that, um, 134 00:05:27,260 --> 00:05:29,479 after a very short time already 135 00:05:29,480 --> 00:05:31,969 the whole ecosystem collapsed. 136 00:05:31,970 --> 00:05:33,920 The fish in the oceans died, 137 00:05:35,060 --> 00:05:36,799 the ecosystems were run over by 138 00:05:36,800 --> 00:05:38,029 cockroaches and ends. 139 00:05:38,030 --> 00:05:41,689 The CO2 levels rose extremely. 140 00:05:41,690 --> 00:05:43,939 And the scientists, which 141 00:05:43,940 --> 00:05:46,009 were basically confined in 142 00:05:46,010 --> 00:05:48,409 this room, were 143 00:05:48,410 --> 00:05:49,399 getting quite hungry. 144 00:05:49,400 --> 00:05:51,049 And towards the end of the experiments, 145 00:05:51,050 --> 00:05:53,209 they actually had to import food from 146 00:05:53,210 --> 00:05:54,749 outside of the system. 147 00:05:54,750 --> 00:05:56,989 So it's not as easy to 148 00:05:56,990 --> 00:05:58,789 rebuild such a nervous system. 149 00:05:58,790 --> 00:06:00,559 And actually we can be happy that we are 150 00:06:00,560 --> 00:06:02,869 living in such a stable one as we 151 00:06:02,870 --> 00:06:04,750 have currently on the planet Earth. 152 00:06:05,930 --> 00:06:08,299 Now, the last the third 153 00:06:08,300 --> 00:06:10,759 option of reducing complexity 154 00:06:10,760 --> 00:06:13,009 is we put the real 155 00:06:13,010 --> 00:06:15,319 world into a set of equations, 156 00:06:15,320 --> 00:06:17,689 a computer model, and 157 00:06:17,690 --> 00:06:20,509 used this computer model to simulate 158 00:06:20,510 --> 00:06:22,079 the Earth system. 159 00:06:22,080 --> 00:06:23,080 Um. 160 00:06:25,070 --> 00:06:27,139 There's a clear advantage of this, 161 00:06:27,140 --> 00:06:29,089 first of all, it's quite cheap, so you 162 00:06:29,090 --> 00:06:32,089 can repeat it, you can do several, 163 00:06:32,090 --> 00:06:34,449 um, well, thousands of 164 00:06:34,450 --> 00:06:35,959 of simulations. 165 00:06:35,960 --> 00:06:37,939 And of course, in reality, we only have 166 00:06:37,940 --> 00:06:39,919 one planet. Right. So we can only carry 167 00:06:39,920 --> 00:06:40,969 out one experiment. 168 00:06:40,970 --> 00:06:41,989 And that's the experiment we are 169 00:06:41,990 --> 00:06:42,990 currently living in. 170 00:06:43,880 --> 00:06:46,159 Um, so there's 171 00:06:46,160 --> 00:06:48,229 no option to repeat it if we fucked 172 00:06:48,230 --> 00:06:49,999 up the climate or something else. 173 00:06:51,380 --> 00:06:52,679 Sorry. Um, 174 00:06:54,710 --> 00:06:57,229 so this has been the first 175 00:06:57,230 --> 00:06:59,599 computer model or the first widely 176 00:06:59,600 --> 00:07:00,589 known computer model? 177 00:07:00,590 --> 00:07:02,689 It's the world's three model from 178 00:07:02,690 --> 00:07:05,449 1972, uh, 179 00:07:05,450 --> 00:07:07,759 known by the report, The Limits 180 00:07:07,760 --> 00:07:09,860 of Growth of the Club of Rome. 181 00:07:10,880 --> 00:07:12,799 The basic message was that if you have 182 00:07:12,800 --> 00:07:15,169 exponential growth of the population 183 00:07:15,170 --> 00:07:17,089 and the exponential growth of the economy 184 00:07:18,380 --> 00:07:20,839 while you have limited natural resources, 185 00:07:20,840 --> 00:07:23,059 there will be one point where the 186 00:07:23,060 --> 00:07:24,889 social system collapses, where the 187 00:07:24,890 --> 00:07:27,019 population is going down up to 188 00:07:27,020 --> 00:07:29,149 a level where the planet can sustain it 189 00:07:29,150 --> 00:07:30,479 again. 190 00:07:30,480 --> 00:07:32,609 Of course, this was one of 191 00:07:32,610 --> 00:07:34,859 the first computer models, it was really 192 00:07:34,860 --> 00:07:36,929 simple. It was also being 193 00:07:36,930 --> 00:07:38,339 heavily criticized for being 194 00:07:38,340 --> 00:07:39,689 oversimplified. 195 00:07:39,690 --> 00:07:42,479 And luckily for us, 196 00:07:42,480 --> 00:07:45,119 those projections didn't become true. 197 00:07:45,120 --> 00:07:47,579 Um, but 198 00:07:47,580 --> 00:07:49,739 it already shows by 199 00:07:49,740 --> 00:07:52,829 triggering off quite a big debate 200 00:07:52,830 --> 00:07:55,259 that it was quite a useful, um, 201 00:07:55,260 --> 00:07:57,089 computer model because suddenly we were 202 00:07:57,090 --> 00:07:59,429 thinking long periods forward 203 00:07:59,430 --> 00:08:01,559 and, um, and of course, 204 00:08:01,560 --> 00:08:03,989 we did not stop with this one 205 00:08:03,990 --> 00:08:06,389 computer model, but we continuously 206 00:08:06,390 --> 00:08:07,319 further developed it. 207 00:08:07,320 --> 00:08:10,049 So this was 1972, 35, 208 00:08:10,050 --> 00:08:12,119 more than 35 years 209 00:08:12,120 --> 00:08:13,529 ago. 210 00:08:13,530 --> 00:08:15,869 And, um, since then, 211 00:08:15,870 --> 00:08:18,059 of course, computers became much 212 00:08:18,060 --> 00:08:19,229 more powerful. 213 00:08:19,230 --> 00:08:21,929 And, of course, also some 214 00:08:21,930 --> 00:08:24,029 a bit slower technological progress 215 00:08:24,030 --> 00:08:26,889 in the science community happened. 216 00:08:26,890 --> 00:08:29,279 So we are still on the challenge 217 00:08:29,280 --> 00:08:31,979 of making good, simplified 218 00:08:31,980 --> 00:08:33,509 computer models. Of course, they are 219 00:08:33,510 --> 00:08:35,908 wrong. That's what a model is always 220 00:08:35,909 --> 00:08:36,989 because it's simplified. 221 00:08:36,990 --> 00:08:38,729 It leaves out processes that are 222 00:08:38,730 --> 00:08:40,798 important, but they are useful for us 223 00:08:40,799 --> 00:08:41,799 for decision making. 224 00:08:43,669 --> 00:08:45,739 So at Potsdam 225 00:08:45,740 --> 00:08:47,839 Institute, we have quite an awesome 226 00:08:47,840 --> 00:08:50,239 ensemble of different models, 227 00:08:50,240 --> 00:08:52,609 um, uh, here you can see, for example, 228 00:08:52,610 --> 00:08:54,739 climate models feeding information 229 00:08:54,740 --> 00:08:56,719 to a vegetation model which calculates 230 00:08:56,720 --> 00:08:59,299 carbon stocks, the natural vegetation 231 00:08:59,300 --> 00:09:01,849 crop yields, uh, hydrology 232 00:09:01,850 --> 00:09:02,839 and so on. 233 00:09:02,840 --> 00:09:05,059 Then we have information 234 00:09:05,060 --> 00:09:07,219 from suchan vegetation 235 00:09:07,220 --> 00:09:09,409 model, uh, being handed over to 236 00:09:09,410 --> 00:09:11,209 a land use and agriculture model, which 237 00:09:11,210 --> 00:09:13,789 is the model called Magpie. 238 00:09:13,790 --> 00:09:15,589 And then we also have a macroeconomic 239 00:09:15,590 --> 00:09:18,589 model and energy model which stimulates 240 00:09:18,590 --> 00:09:20,779 the development of the industry, of 241 00:09:20,780 --> 00:09:23,029 the service sector, of the, 242 00:09:23,030 --> 00:09:25,939 um, of the energy sector, 243 00:09:25,940 --> 00:09:27,529 and, of course, also always the 244 00:09:27,530 --> 00:09:29,239 greenhouse gas emissions. 245 00:09:29,240 --> 00:09:31,339 I want to focus today on the 246 00:09:31,340 --> 00:09:32,479 magpie model. 247 00:09:32,480 --> 00:09:33,919 Magpie's stands for a model of 248 00:09:33,920 --> 00:09:35,809 agricultural production and its impact on 249 00:09:35,810 --> 00:09:37,339 the environment. 250 00:09:37,340 --> 00:09:38,989 This is the model I'm working with. 251 00:09:40,040 --> 00:09:42,139 It's developed by a large 252 00:09:42,140 --> 00:09:44,359 group of approximately currently 253 00:09:44,360 --> 00:09:46,260 15 people, um, 254 00:09:47,300 --> 00:09:49,819 of various scientific backgrounds. 255 00:09:49,820 --> 00:09:52,339 So we have economists, um, 256 00:09:52,340 --> 00:09:54,349 we have physicists. 257 00:09:54,350 --> 00:09:56,659 We have, um, uh, 258 00:09:56,660 --> 00:09:58,729 um, uh, biologists, 259 00:09:58,730 --> 00:10:01,189 geologists and so on. 260 00:10:01,190 --> 00:10:03,319 And the basic question that we want 261 00:10:03,320 --> 00:10:05,659 to answer, if our model is 262 00:10:05,660 --> 00:10:07,819 how will the agrifood system look like in 263 00:10:07,820 --> 00:10:09,679 the year 2050 and beyond? 264 00:10:11,140 --> 00:10:13,359 Why is this important, probably 265 00:10:13,360 --> 00:10:15,549 for you, agriculture is not so important. 266 00:10:15,550 --> 00:10:18,249 Hardly anyone still works in agriculture. 267 00:10:18,250 --> 00:10:20,919 But for our planet, agriculture is 268 00:10:20,920 --> 00:10:23,169 really important. It's our main interface 269 00:10:23,170 --> 00:10:24,369 with nature. 270 00:10:24,370 --> 00:10:26,439 If you look at our planet, 30 percent 271 00:10:26,440 --> 00:10:28,659 of the terrestrial surface is 272 00:10:28,660 --> 00:10:30,699 covered by agriculture, either by 273 00:10:30,700 --> 00:10:32,459 cropland or pastures. 274 00:10:32,460 --> 00:10:34,779 Um, if you look at 275 00:10:34,780 --> 00:10:37,719 greenhouse gas emissions, 25 percent 276 00:10:37,720 --> 00:10:40,029 of the greenhouse gas emissions come 277 00:10:40,030 --> 00:10:42,459 from land use, change and agriculture. 278 00:10:42,460 --> 00:10:44,679 So, again, uh, struggling 279 00:10:44,680 --> 00:10:45,819 with agriculture. 280 00:10:45,820 --> 00:10:48,069 If you look at water, 70 281 00:10:48,070 --> 00:10:49,989 percent of human water withdrawals are 282 00:10:49,990 --> 00:10:52,089 for irrigation water. 283 00:10:52,090 --> 00:10:53,739 If you look at water pollution, at 284 00:10:53,740 --> 00:10:56,409 herbicides, it's biodiversity 285 00:10:56,410 --> 00:10:58,869 always. There is, um, 286 00:10:58,870 --> 00:11:01,269 agriculture as one of the major drivers. 287 00:11:01,270 --> 00:11:03,639 Also, we are now really 288 00:11:03,640 --> 00:11:05,739 changing the nutrient cycles 289 00:11:05,740 --> 00:11:08,169 of the world, increasing, 290 00:11:08,170 --> 00:11:10,509 for example, the nitrogen cycle 291 00:11:10,510 --> 00:11:13,209 by a factor of three or four, um, 292 00:11:13,210 --> 00:11:15,669 relatively two earlier years. 293 00:11:15,670 --> 00:11:17,859 And there's also another thing, of 294 00:11:17,860 --> 00:11:19,899 course, agriculture is also really 295 00:11:19,900 --> 00:11:21,699 important for us humans, because we can 296 00:11:21,700 --> 00:11:23,049 live without energy. We can't live 297 00:11:23,050 --> 00:11:24,189 without food. 298 00:11:24,190 --> 00:11:26,929 And if you look at 299 00:11:26,930 --> 00:11:29,769 the global nineteen, 300 00:11:29,770 --> 00:11:32,259 uh, leading risk factors 301 00:11:32,260 --> 00:11:34,449 worldwide, um, 302 00:11:34,450 --> 00:11:36,190 for preliminary death. 303 00:11:38,480 --> 00:11:40,789 11 of them are connected somehow 304 00:11:40,790 --> 00:11:42,379 to nutrition. 305 00:11:42,380 --> 00:11:44,569 So either we eat too much, 306 00:11:44,570 --> 00:11:46,429 which is rich or too little, which is 307 00:11:46,430 --> 00:11:47,629 green. 308 00:11:47,630 --> 00:11:50,359 Um, it's something like iron 309 00:11:50,360 --> 00:11:52,429 deficiency, vitamin A deficiency, 310 00:11:52,430 --> 00:11:54,259 suboptimal breastfeeding. 311 00:11:54,260 --> 00:11:56,419 But on the other hand, there's 312 00:11:56,420 --> 00:11:58,279 also a lot of things connected to 313 00:11:58,280 --> 00:12:01,039 unhealthy diets like high blood pressure, 314 00:12:01,040 --> 00:12:02,989 high blood glucose, overweight and 315 00:12:02,990 --> 00:12:04,219 obesity. 316 00:12:04,220 --> 00:12:06,559 On these top 19, you cannot 317 00:12:06,560 --> 00:12:08,629 find wars or terrorism or something like 318 00:12:08,630 --> 00:12:08,809 that. 319 00:12:08,810 --> 00:12:10,669 But it's really about mostly about 320 00:12:10,670 --> 00:12:11,569 chronic diseases. 321 00:12:11,570 --> 00:12:13,219 And most of the chronic diseases are 322 00:12:13,220 --> 00:12:15,620 strongly connected with our daily diets. 323 00:12:18,420 --> 00:12:20,549 So how does such a model look 324 00:12:20,550 --> 00:12:22,649 like basically we start 325 00:12:22,650 --> 00:12:24,879 off with the food requirements, 326 00:12:24,880 --> 00:12:27,089 what do people actually eat 327 00:12:27,090 --> 00:12:29,369 and what what what do they actually 328 00:12:29,370 --> 00:12:31,619 need as food to sustain their body 329 00:12:31,620 --> 00:12:33,119 functions? 330 00:12:33,120 --> 00:12:35,609 Well, this, of course, depends on 331 00:12:35,610 --> 00:12:37,919 how large the population is and 332 00:12:37,920 --> 00:12:40,079 what each of them eats. 333 00:12:40,080 --> 00:12:42,269 At the moment, we are already at 334 00:12:42,270 --> 00:12:44,429 a world population of seven point 335 00:12:44,430 --> 00:12:46,799 six billion, um, 336 00:12:46,800 --> 00:12:48,329 and we are still growing. 337 00:12:48,330 --> 00:12:50,699 We will most likely be, 338 00:12:50,700 --> 00:12:53,129 um, eight point five to 10 339 00:12:53,130 --> 00:12:56,099 billion people in the year 2050. 340 00:12:56,100 --> 00:12:58,529 So then we need to do some more 341 00:12:58,530 --> 00:13:00,359 refreshments here. 342 00:13:00,360 --> 00:13:02,549 Um, and 343 00:13:02,550 --> 00:13:04,709 eventually afterwards, there is 344 00:13:04,710 --> 00:13:06,929 an option that it might decline or 345 00:13:06,930 --> 00:13:07,829 further increase. 346 00:13:07,830 --> 00:13:09,899 And this depends a lot of 347 00:13:09,900 --> 00:13:12,119 on education and on 348 00:13:12,120 --> 00:13:13,120 family planning. 349 00:13:14,460 --> 00:13:16,829 At the same time, what people 350 00:13:16,830 --> 00:13:18,989 need to sustain their 351 00:13:18,990 --> 00:13:21,729 body functions per capita is is quite, 352 00:13:21,730 --> 00:13:23,850 uh, is quite, 353 00:13:25,380 --> 00:13:26,929 quite always the same. 354 00:13:26,930 --> 00:13:29,399 Actually, there are some differences 355 00:13:29,400 --> 00:13:30,929 depending on demography. 356 00:13:30,930 --> 00:13:33,059 You can see that Africa has a lower 357 00:13:33,060 --> 00:13:35,309 requirement because there are a lot of 358 00:13:35,310 --> 00:13:37,379 young kids are, uh, in 359 00:13:37,380 --> 00:13:39,749 contrast, in China, a lot of, uh, 360 00:13:39,750 --> 00:13:41,849 young adults, uh, you have 361 00:13:41,850 --> 00:13:42,839 high food requirements. 362 00:13:42,840 --> 00:13:44,429 But of course, this will shift as soon as 363 00:13:44,430 --> 00:13:45,989 we have demographic change in the future. 364 00:13:45,990 --> 00:13:47,999 And then we will have, in contrast, high 365 00:13:48,000 --> 00:13:51,059 food requirements in Africa per capita. 366 00:13:51,060 --> 00:13:53,129 But in general, the range is really low, 367 00:13:53,130 --> 00:13:55,559 2000 to 2300 kilocalories 368 00:13:55,560 --> 00:13:57,719 per capita per day in population 369 00:13:57,720 --> 00:13:58,720 average. 370 00:13:59,350 --> 00:14:02,019 But this is, of course, what the people 371 00:14:02,020 --> 00:14:04,029 would require, what they actually 372 00:14:05,110 --> 00:14:07,449 what they actually consume is much more 373 00:14:07,450 --> 00:14:10,719 so you can see in Germany we have 3500 374 00:14:10,720 --> 00:14:11,979 kilocalories. 375 00:14:11,980 --> 00:14:13,629 In India, it's closer to the food 376 00:14:13,630 --> 00:14:15,219 requirements of two thousand four hundred 377 00:14:15,220 --> 00:14:16,239 fifty. 378 00:14:16,240 --> 00:14:18,489 But you can also see not only that, 379 00:14:18,490 --> 00:14:20,829 there's a lot of overconsumption. 380 00:14:20,830 --> 00:14:23,349 You can also see that the diets are quite 381 00:14:23,350 --> 00:14:24,879 different. 382 00:14:24,880 --> 00:14:26,979 In Germany. We eat quite a lot of animal 383 00:14:26,980 --> 00:14:29,349 products which people 384 00:14:29,350 --> 00:14:31,689 in Nigeria or India don't, 385 00:14:31,690 --> 00:14:33,939 and we actually don't 386 00:14:33,940 --> 00:14:35,529 eat too much fruits and vegetables, which 387 00:14:35,530 --> 00:14:37,069 is a shame for us. 388 00:14:37,070 --> 00:14:38,979 Um, but. 389 00:14:40,150 --> 00:14:42,609 Um, you 390 00:14:42,610 --> 00:14:44,889 can see that we consume 391 00:14:44,890 --> 00:14:47,229 about one third more than we need, and 392 00:14:47,230 --> 00:14:48,369 what's the reason for this? 393 00:14:48,370 --> 00:14:50,949 Basically, it's that we waste 394 00:14:50,950 --> 00:14:53,379 most of our quite a substantial fraction 395 00:14:53,380 --> 00:14:54,429 of our food. 396 00:14:54,430 --> 00:14:56,709 About 30 percent of the food gets 397 00:14:56,710 --> 00:14:59,349 wasted in households, um, 398 00:14:59,350 --> 00:15:01,749 just because people, well, 399 00:15:01,750 --> 00:15:03,629 don't care too much about it. 400 00:15:05,560 --> 00:15:08,019 Um, and you can see 401 00:15:08,020 --> 00:15:09,789 a quite strong correlation, 402 00:15:10,930 --> 00:15:13,359 so as soon as, um, 403 00:15:13,360 --> 00:15:15,489 people increase their living standards, 404 00:15:15,490 --> 00:15:17,259 as soon as the Human Development Index 405 00:15:17,260 --> 00:15:19,359 increases, you'll also see 406 00:15:19,360 --> 00:15:21,579 that the food waste 407 00:15:21,580 --> 00:15:23,559 is starting or the overconsumption. 408 00:15:23,560 --> 00:15:26,139 This also includes, uh, overconsumption 409 00:15:26,140 --> 00:15:27,339 in the sense that people eat more 410 00:15:27,340 --> 00:15:29,229 calories, but also that the window is 411 00:15:29,230 --> 00:15:30,429 quite narrow. 412 00:15:30,430 --> 00:15:31,630 Most of it is food waste. 413 00:15:33,920 --> 00:15:37,009 OK. And the same you can see for 414 00:15:37,010 --> 00:15:39,349 per capita calories in 415 00:15:39,350 --> 00:15:41,569 order to share of livestock products. 416 00:15:41,570 --> 00:15:43,369 You can see that the share of livestock 417 00:15:43,370 --> 00:15:45,649 products strongly increases 418 00:15:45,650 --> 00:15:48,389 with income. On the left, you see just 419 00:15:48,390 --> 00:15:51,109 a scatterplot between 420 00:15:51,110 --> 00:15:53,299 income and livestock share 421 00:15:53,300 --> 00:15:54,889 for all countries of the world for the 422 00:15:54,890 --> 00:15:56,179 last 50 years. 423 00:15:56,180 --> 00:15:58,249 And you can see that countries 424 00:15:58,250 --> 00:16:00,049 strongly increase their meat consumption, 425 00:16:00,050 --> 00:16:02,269 especially when they move from 426 00:16:02,270 --> 00:16:04,609 very low incomes to medium incomes 427 00:16:04,610 --> 00:16:05,779 for very high incomes. 428 00:16:05,780 --> 00:16:07,789 Eventually, the livestock share declines 429 00:16:07,790 --> 00:16:08,689 again. 430 00:16:08,690 --> 00:16:10,369 And you see the same actually also for 431 00:16:10,370 --> 00:16:12,499 processed foods like oil, sugar 432 00:16:12,500 --> 00:16:14,629 consumption goes up. 433 00:16:14,630 --> 00:16:16,699 Um, unfortunately, you don't 434 00:16:16,700 --> 00:16:18,079 see it for fruits and vegetables, which 435 00:16:18,080 --> 00:16:19,969 would be healthier, but they are, etc. 436 00:16:19,970 --> 00:16:21,739 It's quite as an early income. 437 00:16:23,950 --> 00:16:26,499 And then, of course, this food, 438 00:16:26,500 --> 00:16:28,569 the food demand has 439 00:16:28,570 --> 00:16:30,459 to be satisfied by production before 440 00:16:30,460 --> 00:16:31,929 that, there's some trade. 441 00:16:31,930 --> 00:16:33,879 International trade is increasing over 442 00:16:33,880 --> 00:16:35,559 the last decades quite strongly, much 443 00:16:35,560 --> 00:16:36,939 more than production. 444 00:16:36,940 --> 00:16:39,519 And next to food demand, 445 00:16:39,520 --> 00:16:42,639 there's also the demand for materials, 446 00:16:42,640 --> 00:16:44,889 but also for bioenergy, which will play 447 00:16:44,890 --> 00:16:47,079 a role, an increasing role. 448 00:16:47,080 --> 00:16:48,849 I don't know if you heard the talk 449 00:16:48,850 --> 00:16:50,979 before, which 450 00:16:50,980 --> 00:16:53,439 may play an increasing role in the future 451 00:16:53,440 --> 00:16:55,599 if we want to mitigate climate change 452 00:16:55,600 --> 00:16:58,779 because bio bioenergy is one option to 453 00:16:58,780 --> 00:17:00,849 take CO2 emissions again out of 454 00:17:00,850 --> 00:17:01,850 the atmosphere. 455 00:17:02,970 --> 00:17:05,449 Then Fuji's, of course, also processed 456 00:17:05,450 --> 00:17:07,279 and here the livestock products really 457 00:17:07,280 --> 00:17:09,439 play a huge role because 458 00:17:09,440 --> 00:17:11,779 in order to feed one or 459 00:17:11,780 --> 00:17:14,299 in order to produce one calorie of 460 00:17:14,300 --> 00:17:16,489 livestock products, you need 461 00:17:16,490 --> 00:17:18,858 multiple plant calories 462 00:17:18,859 --> 00:17:20,029 to feed the animal. 463 00:17:20,030 --> 00:17:22,639 At the moment, approximately half 464 00:17:22,640 --> 00:17:24,259 of the proteins that are produced 465 00:17:24,260 --> 00:17:26,989 worldwide on the crop lands 466 00:17:26,990 --> 00:17:29,269 are fed to animals 467 00:17:29,270 --> 00:17:31,879 and additionally, also 468 00:17:31,880 --> 00:17:33,949 a large, even larger quantity 469 00:17:33,950 --> 00:17:36,259 of of pasture, which is grazed 470 00:17:36,260 --> 00:17:37,260 by animals. 471 00:17:38,610 --> 00:17:40,679 And finally, we have 472 00:17:40,680 --> 00:17:42,839 crops and these crops are standing 473 00:17:42,840 --> 00:17:45,029 on a land, and here you can 474 00:17:45,030 --> 00:17:46,779 see some land use dynamics. 475 00:17:46,780 --> 00:17:48,839 Here you can see a projection or 476 00:17:48,840 --> 00:17:51,059 scenario, a future scenario 477 00:17:51,060 --> 00:17:53,189 of how 478 00:17:53,190 --> 00:17:55,649 the cropland might expand 479 00:17:55,650 --> 00:17:56,939 in the future. 480 00:17:56,940 --> 00:17:58,889 Quite strong expansion, especially in the 481 00:17:58,890 --> 00:18:01,019 tropical areas, because they are 482 00:18:01,020 --> 00:18:02,910 also the population growth, this largest. 483 00:18:04,600 --> 00:18:06,959 And next to land use, 484 00:18:06,960 --> 00:18:08,230 this also, while 485 00:18:09,430 --> 00:18:11,109 on the one hand you have cropland 486 00:18:11,110 --> 00:18:12,519 expansion, but this is not the only 487 00:18:12,520 --> 00:18:14,409 option, of course, to increase production 488 00:18:14,410 --> 00:18:16,779 in the past is made up only 10 percent 489 00:18:16,780 --> 00:18:18,279 of the increase of production. 490 00:18:18,280 --> 00:18:20,439 The largest increase actually came always 491 00:18:20,440 --> 00:18:22,509 from the intensification of the 492 00:18:22,510 --> 00:18:24,039 existing areas. 493 00:18:24,040 --> 00:18:26,140 And here you can see the 494 00:18:27,730 --> 00:18:29,379 basically the crop yields that we would 495 00:18:29,380 --> 00:18:31,899 need in the future in order to sustain 496 00:18:31,900 --> 00:18:34,569 our, um, or 497 00:18:34,570 --> 00:18:35,890 to fulfill the demand. 498 00:18:37,600 --> 00:18:39,699 And finally, our model 499 00:18:39,700 --> 00:18:41,649 also considers all the interactions with 500 00:18:41,650 --> 00:18:43,749 the biochemical cycles. 501 00:18:43,750 --> 00:18:45,849 So how do we change the nitrogen 502 00:18:45,850 --> 00:18:47,089 and phosphorus cycle? 503 00:18:48,200 --> 00:18:50,409 Also, how will water scarcity 504 00:18:50,410 --> 00:18:52,059 change? This is a picture where you can 505 00:18:52,060 --> 00:18:54,939 see the water scarcity in 2010 506 00:18:54,940 --> 00:18:56,109 and 2050. 507 00:18:56,110 --> 00:18:57,819 So it's basically not a water scarcity, 508 00:18:57,820 --> 00:18:59,979 but how much of the water 509 00:18:59,980 --> 00:19:01,779 that is available will be the use? 510 00:19:03,500 --> 00:19:05,569 And, um, uh, the 511 00:19:05,570 --> 00:19:07,879 nitrogen cycle is the third 512 00:19:07,880 --> 00:19:10,699 most important, um, uh, 513 00:19:10,700 --> 00:19:12,859 biochemical cycle of the world has 514 00:19:12,860 --> 00:19:14,599 been changed tremendously by modern 515 00:19:14,600 --> 00:19:15,619 agriculture. 516 00:19:15,620 --> 00:19:17,749 We are now about five times the amount 517 00:19:17,750 --> 00:19:19,609 of nitrogen which flows through the cycle 518 00:19:19,610 --> 00:19:21,859 than in pre-industrial times. 519 00:19:23,700 --> 00:19:25,589 And finally, we end up with emissions 520 00:19:25,590 --> 00:19:28,019 and, uh, well, 521 00:19:28,020 --> 00:19:30,089 if we assume a scenario where 522 00:19:30,090 --> 00:19:32,369 we don't take action, 523 00:19:32,370 --> 00:19:34,469 we can assume that or we 524 00:19:34,470 --> 00:19:36,779 simulate that the emissions will further 525 00:19:36,780 --> 00:19:37,709 increase. 526 00:19:37,710 --> 00:19:40,439 While actually in order to keep 527 00:19:40,440 --> 00:19:42,509 up or stay below the two 528 00:19:42,510 --> 00:19:44,129 degree aim, we would actually need the 529 00:19:44,130 --> 00:19:46,349 land use sector to sequester carbon. 530 00:19:46,350 --> 00:19:48,269 So we need to take CO2 out of the 531 00:19:48,270 --> 00:19:50,339 atmosphere. This is something that only 532 00:19:50,340 --> 00:19:52,529 the land use sector can provide 533 00:19:52,530 --> 00:19:53,849 at low costs, either through 534 00:19:53,850 --> 00:19:56,729 afforestation, through plantation 535 00:19:56,730 --> 00:19:58,859 of biomass or 536 00:19:58,860 --> 00:20:01,079 through accumulation 537 00:20:01,080 --> 00:20:02,819 of carbon in soils. 538 00:20:04,570 --> 00:20:06,669 So this is the whole integrated 539 00:20:06,670 --> 00:20:08,979 model, and the great thing is that, um, 540 00:20:08,980 --> 00:20:11,079 uh, well, it's an 541 00:20:11,080 --> 00:20:13,389 optimization model where everything 542 00:20:13,390 --> 00:20:14,499 influences everything. 543 00:20:14,500 --> 00:20:16,689 So if you put a carbon price in, this 544 00:20:16,690 --> 00:20:19,389 will change the whole supply chain. 545 00:20:19,390 --> 00:20:21,219 It will change the food demand. 546 00:20:21,220 --> 00:20:23,649 It will change the global trade patterns. 547 00:20:23,650 --> 00:20:25,599 It will change the land use pattern. 548 00:20:25,600 --> 00:20:28,059 If you you can also see the interactions, 549 00:20:28,060 --> 00:20:29,799 for example, between the nitrogen and the 550 00:20:29,800 --> 00:20:32,049 water cycle or, um, 551 00:20:32,050 --> 00:20:34,479 uh, how, um, 552 00:20:34,480 --> 00:20:37,299 uh, well, and 553 00:20:37,300 --> 00:20:39,189 but you can also see quite well the trade 554 00:20:39,190 --> 00:20:41,379 offs that exist in our in our earth 555 00:20:41,380 --> 00:20:42,069 system. 556 00:20:42,070 --> 00:20:44,229 So if you only want to solve 557 00:20:44,230 --> 00:20:46,869 one specific aim, it's still, 558 00:20:46,870 --> 00:20:49,719 well, quite, quite easily possible. 559 00:20:49,720 --> 00:20:52,209 Um, but as soon as you have multiple 560 00:20:52,210 --> 00:20:54,399 goals, for example, if you want to 561 00:20:54,400 --> 00:20:56,499 provide enough food for, uh, for the 562 00:20:56,500 --> 00:20:58,809 whole world population, this will also 563 00:20:58,810 --> 00:21:01,389 require you to increase your food 564 00:21:01,390 --> 00:21:03,489 food production and 565 00:21:03,490 --> 00:21:05,139 then you will have the environmental 566 00:21:05,140 --> 00:21:06,099 impact. 567 00:21:06,100 --> 00:21:09,039 If you want to reduce, 568 00:21:09,040 --> 00:21:11,289 uh, greenhouse gas emissions, you 569 00:21:11,290 --> 00:21:12,939 will need bioenergy. 570 00:21:12,940 --> 00:21:14,649 And this, of course, also has negative 571 00:21:14,650 --> 00:21:16,749 impacts, again, on biodiversity, on food 572 00:21:16,750 --> 00:21:18,849 consumption, on food prices and so 573 00:21:18,850 --> 00:21:21,129 on. So it's a very complex system. 574 00:21:21,130 --> 00:21:23,519 And, um, it's 575 00:21:23,520 --> 00:21:26,409 it's a really a challenge, 576 00:21:26,410 --> 00:21:28,629 but it's possible, um, uh, 577 00:21:28,630 --> 00:21:31,389 to transform our 578 00:21:31,390 --> 00:21:33,549 society sustainably that we 579 00:21:33,550 --> 00:21:35,769 actually meet all these goals at the same 580 00:21:35,770 --> 00:21:38,709 time. What's really crucial there is, 581 00:21:38,710 --> 00:21:41,709 on the one hand, the consumption side. 582 00:21:41,710 --> 00:21:43,899 So we really need to reduce 583 00:21:43,900 --> 00:21:45,639 food waste and we need to reduce the 584 00:21:45,640 --> 00:21:47,739 consumption of animal products by 585 00:21:47,740 --> 00:21:48,939 large scale. 586 00:21:48,940 --> 00:21:51,519 So halving animal consumption, 587 00:21:51,520 --> 00:21:54,279 having the food waste in Western society 588 00:21:54,280 --> 00:21:55,929 would be something that we should aim 589 00:21:55,930 --> 00:21:59,019 for. And this is really difficult. 590 00:21:59,020 --> 00:22:01,119 Um, at the same time, 591 00:22:01,120 --> 00:22:03,399 the whole production system can be much 592 00:22:03,400 --> 00:22:04,669 more efficient. 593 00:22:04,670 --> 00:22:06,789 A small price on on carbon 594 00:22:06,790 --> 00:22:08,709 would be sufficient to trigger off 595 00:22:08,710 --> 00:22:11,349 technical innovations probably and 596 00:22:11,350 --> 00:22:13,419 to implement low cost carbon, 597 00:22:13,420 --> 00:22:15,429 uh, mitigation technologies. 598 00:22:16,940 --> 00:22:18,829 But these are probably the two things 599 00:22:18,830 --> 00:22:20,239 that we need most. 600 00:22:20,240 --> 00:22:21,240 We need 601 00:22:23,760 --> 00:22:25,849 a policy that puts prices 602 00:22:25,850 --> 00:22:28,669 on emissions, on carbon or nitrogen, 603 00:22:28,670 --> 00:22:31,129 on water pollution, 604 00:22:31,130 --> 00:22:33,289 and we need some kind of 605 00:22:33,290 --> 00:22:35,629 policies that change the preferences 606 00:22:35,630 --> 00:22:37,819 of the people in a way that they, 607 00:22:37,820 --> 00:22:40,639 for example, education, school education 608 00:22:40,640 --> 00:22:43,039 for what is a healthy diet. 609 00:22:43,040 --> 00:22:45,079 How how do you cook at home? 610 00:22:45,080 --> 00:22:47,179 And so on all day, all these 611 00:22:47,180 --> 00:22:49,369 kind of projects have to be really 612 00:22:49,370 --> 00:22:50,370 encouraged. 613 00:22:52,520 --> 00:22:55,279 So what can you do? 614 00:22:55,280 --> 00:22:57,649 Well, one advice I would 615 00:22:57,650 --> 00:22:59,839 want to give out is get involved 616 00:22:59,840 --> 00:23:00,799 in modeling. 617 00:23:00,800 --> 00:23:03,709 Um, uh, most of us are actually, 618 00:23:03,710 --> 00:23:06,109 um, uh, well, we 619 00:23:06,110 --> 00:23:08,509 are we are not computer scientists, 620 00:23:08,510 --> 00:23:10,399 uh, from the beginning, but we have to 621 00:23:10,400 --> 00:23:12,619 learn quite a lot, all of this. 622 00:23:12,620 --> 00:23:13,789 But we are rather coming from 623 00:23:13,790 --> 00:23:16,009 disciplinary backgrounds, economists 624 00:23:16,010 --> 00:23:18,169 or or biologists 625 00:23:18,170 --> 00:23:19,669 or something like that. 626 00:23:19,670 --> 00:23:21,739 And but most of our time is 627 00:23:21,740 --> 00:23:23,959 actually software development. 628 00:23:23,960 --> 00:23:26,059 And, um, it's not 629 00:23:26,060 --> 00:23:27,739 that we don't want software developers, 630 00:23:27,740 --> 00:23:29,869 it's just that few people actually 631 00:23:29,870 --> 00:23:30,919 apply there. 632 00:23:30,920 --> 00:23:32,029 So I think 633 00:23:33,470 --> 00:23:35,149 putting up the standards of software 634 00:23:35,150 --> 00:23:37,309 development in the whole field would 635 00:23:37,310 --> 00:23:38,509 be really a great thing. 636 00:23:39,710 --> 00:23:41,779 Um, the second thing is there's a lot 637 00:23:41,780 --> 00:23:43,999 of data out, um, and 638 00:23:44,000 --> 00:23:46,519 there's a lot of, um, uh, 639 00:23:46,520 --> 00:23:48,829 well, also, uh, great 640 00:23:48,830 --> 00:23:51,049 science that could be communicated, 641 00:23:51,050 --> 00:23:53,269 um, uh, using good 642 00:23:53,270 --> 00:23:55,939 visualization techniques, using 643 00:23:55,940 --> 00:23:58,099 um also maybe artistic 644 00:23:58,100 --> 00:23:59,439 projects and so on. 645 00:23:59,440 --> 00:24:01,039 I just want to give you one example 646 00:24:01,040 --> 00:24:03,139 before I come to the question and answer 647 00:24:03,140 --> 00:24:06,169 here. In the last year, we made a, 648 00:24:06,170 --> 00:24:09,289 uh, workshop with arts students, 649 00:24:09,290 --> 00:24:11,209 uh, who developed interactive 650 00:24:11,210 --> 00:24:13,129 installations using our data. 651 00:24:13,130 --> 00:24:14,509 For example, here, it's an audio 652 00:24:14,510 --> 00:24:16,639 installation where people could hear the 653 00:24:16,640 --> 00:24:18,769 sound of different, um, 654 00:24:18,770 --> 00:24:20,899 uh, scenarios, depending 655 00:24:20,900 --> 00:24:23,369 on whether it's a, um, 656 00:24:23,370 --> 00:24:25,489 a scenario where all the forests 657 00:24:25,490 --> 00:24:27,379 are cut down and you have roday 658 00:24:27,380 --> 00:24:29,539 agricultural sounds or more 659 00:24:29,540 --> 00:24:31,879 urban sounds in another scenario. 660 00:24:31,880 --> 00:24:32,880 Um, uh, 661 00:24:34,100 --> 00:24:36,229 or, uh, maybe I just 662 00:24:36,230 --> 00:24:38,359 pick one more because we have limited 663 00:24:38,360 --> 00:24:40,609 time. This is, uh, 664 00:24:40,610 --> 00:24:42,949 an artwork by a student 665 00:24:42,950 --> 00:24:45,659 from Bangladesh and 666 00:24:45,660 --> 00:24:48,169 um, uh, she created a climate box. 667 00:24:48,170 --> 00:24:50,089 You can enter this climate box, throw in 668 00:24:50,090 --> 00:24:52,279 a coin, and then, um, 669 00:24:52,280 --> 00:24:53,329 using an arduino. 670 00:24:53,330 --> 00:24:55,489 It's, uh, it all starts moving. 671 00:24:55,490 --> 00:24:57,709 You get told the story of climate 672 00:24:57,710 --> 00:24:58,699 change. 673 00:24:58,700 --> 00:25:00,679 Um, but at the same time, also the 674 00:25:00,680 --> 00:25:03,229 weather in the climate box is changing. 675 00:25:03,230 --> 00:25:05,389 So suddenly it becomes hotter and there's 676 00:25:05,390 --> 00:25:07,969 a fan blowing in hot air and, 677 00:25:07,970 --> 00:25:10,039 uh, suddenly it starts raining and 678 00:25:10,040 --> 00:25:12,199 there's flashlights and, 679 00:25:12,200 --> 00:25:14,809 uh, and then if you don't spend 680 00:25:14,810 --> 00:25:17,039 more money on it, um, uh, 681 00:25:17,040 --> 00:25:18,709 then it becomes even worse and worse and 682 00:25:18,710 --> 00:25:19,710 worse. 683 00:25:20,330 --> 00:25:21,330 So. 684 00:25:25,170 --> 00:25:27,149 This artwork was actually inspired 685 00:25:27,150 --> 00:25:29,579 because she said, well, people 686 00:25:29,580 --> 00:25:31,649 back home, they see climate 687 00:25:31,650 --> 00:25:33,749 change as something abstract, but 688 00:25:33,750 --> 00:25:35,339 as long as they don't feel that they will 689 00:25:35,340 --> 00:25:37,259 do something. So she came up with this 690 00:25:37,260 --> 00:25:39,479 idea, OK, now 691 00:25:39,480 --> 00:25:40,919 I'm ready for a question. 692 00:25:40,920 --> 00:25:41,939 Answer. Thank you very much. 693 00:25:52,780 --> 00:25:54,969 Everybody with questions, please go to 694 00:25:54,970 --> 00:25:57,069 the microphones in the 695 00:25:57,070 --> 00:25:59,349 room and Internet 696 00:25:59,350 --> 00:26:00,909 over the signal. 697 00:26:00,910 --> 00:26:02,490 So microphone one, please. 698 00:26:05,560 --> 00:26:07,650 It's just I got an electric chair. 699 00:26:09,300 --> 00:26:11,219 Thanks for the Talk Back question. 700 00:26:11,220 --> 00:26:13,109 When you looked at the needs of people, 701 00:26:13,110 --> 00:26:15,449 you spoke about calorie requirements. 702 00:26:15,450 --> 00:26:17,159 However, nutrition is much more than 703 00:26:17,160 --> 00:26:19,269 calories and especially and not 704 00:26:19,270 --> 00:26:21,389 not in Germany, but in 705 00:26:21,390 --> 00:26:23,849 Zaal area, when you further reduce 706 00:26:23,850 --> 00:26:26,099 the animal protein part, 707 00:26:26,100 --> 00:26:27,869 you get problems with malnutrition. 708 00:26:27,870 --> 00:26:29,729 Is that something you factor in or just 709 00:26:29,730 --> 00:26:31,889 plain calories and you 710 00:26:31,890 --> 00:26:33,869 eat sorghum or sorghum? 711 00:26:33,870 --> 00:26:35,009 No, of course. 712 00:26:35,010 --> 00:26:37,589 Um, dietary dietary diversity 713 00:26:37,590 --> 00:26:38,739 is really important. 714 00:26:38,740 --> 00:26:41,099 Um, I would not say that the animal 715 00:26:41,100 --> 00:26:43,199 protein is the only way of of 716 00:26:43,200 --> 00:26:45,389 of, uh, solving this, 717 00:26:45,390 --> 00:26:47,669 uh, because, um, uh, you 718 00:26:47,670 --> 00:26:49,889 can have a, uh, a balanced 719 00:26:49,890 --> 00:26:52,109 diet also without animal protein. 720 00:26:52,110 --> 00:26:53,939 But it's important. Actually, one of the 721 00:26:53,940 --> 00:26:56,459 most important challenges is to drive up 722 00:26:56,460 --> 00:26:58,589 the consumption of vegetables and fruits, 723 00:26:58,590 --> 00:27:01,109 um, by by 724 00:27:01,110 --> 00:27:02,849 by several factors. 725 00:27:02,850 --> 00:27:05,069 Um, and there's hardly 726 00:27:05,070 --> 00:27:07,319 any, um, positive 727 00:27:07,320 --> 00:27:10,349 limitation to the, uh, 728 00:27:10,350 --> 00:27:12,479 the especially for 729 00:27:12,480 --> 00:27:15,059 vegetables, to the health impacts 730 00:27:15,060 --> 00:27:17,189 of, um, higher consumption 731 00:27:17,190 --> 00:27:19,399 of vegetables and fruits. 732 00:27:19,400 --> 00:27:20,939 Of course, we look at the dietary 733 00:27:20,940 --> 00:27:23,129 composition and um, 734 00:27:23,130 --> 00:27:25,589 there we also don't only look at at, 735 00:27:25,590 --> 00:27:27,779 uh, livestock versus plant calories, 736 00:27:27,780 --> 00:27:30,359 but also now on fruits and vegetables 737 00:27:30,360 --> 00:27:32,309 and unprocessed calories. 738 00:27:32,310 --> 00:27:34,679 Um, but 739 00:27:34,680 --> 00:27:36,749 yeah, of course, I think it's, uh, 740 00:27:36,750 --> 00:27:39,419 it's a major problem that 741 00:27:39,420 --> 00:27:41,609 we should not play out goals 742 00:27:41,610 --> 00:27:44,069 like food security against 743 00:27:44,070 --> 00:27:45,329 goals like climate change. 744 00:27:45,330 --> 00:27:47,729 We need to simply tackle both of them 745 00:27:47,730 --> 00:27:50,009 and as urgently as possible. 746 00:27:50,010 --> 00:27:51,379 Um, uh. 747 00:27:51,380 --> 00:27:52,380 Yeah. 748 00:27:54,060 --> 00:27:56,359 I think we have five minutes, 749 00:27:56,360 --> 00:27:58,579 so next, microphone number 750 00:27:58,580 --> 00:27:59,580 two, please. 751 00:28:00,830 --> 00:28:03,109 Sorry, I think I'm too small for this 752 00:28:03,110 --> 00:28:04,110 one. 753 00:28:05,810 --> 00:28:08,029 OK, um, so I've got two 754 00:28:08,030 --> 00:28:09,029 questions. 755 00:28:09,030 --> 00:28:11,569 Uh, you were talking about trade offs. 756 00:28:11,570 --> 00:28:14,089 So what would you think 757 00:28:14,090 --> 00:28:16,159 is the best solution 758 00:28:16,160 --> 00:28:18,349 to the crucial trade off between, 759 00:28:18,350 --> 00:28:20,809 um, biodiversity 760 00:28:20,810 --> 00:28:23,229 and land conversion for food security? 761 00:28:24,370 --> 00:28:26,709 The second question is, you were talking 762 00:28:26,710 --> 00:28:29,109 about how important it is that 763 00:28:29,110 --> 00:28:31,329 we invest in societies, drive 764 00:28:31,330 --> 00:28:34,209 up our vegetable and fruit consumption, 765 00:28:34,210 --> 00:28:36,309 but this again would mean that 766 00:28:36,310 --> 00:28:38,949 we shift the land usage 767 00:28:38,950 --> 00:28:41,379 for high calorie 768 00:28:41,380 --> 00:28:43,629 foods, even if they are not 769 00:28:43,630 --> 00:28:46,239 dairy or, well, livestock 770 00:28:46,240 --> 00:28:47,349 in any way. 771 00:28:47,350 --> 00:28:49,449 Um, so that, again, we use 772 00:28:49,450 --> 00:28:51,549 more land and this again 773 00:28:51,550 --> 00:28:52,629 would cause more. 774 00:28:52,630 --> 00:28:55,149 Well, rivalry between 775 00:28:55,150 --> 00:28:57,579 global food users. 776 00:28:57,580 --> 00:29:00,219 Um, isn't this contradictory 777 00:29:00,220 --> 00:29:02,409 to food security and aren't 778 00:29:02,410 --> 00:29:04,629 we quite healthy already 779 00:29:04,630 --> 00:29:07,969 if we stopped eating sugar like crazy. 780 00:29:07,970 --> 00:29:10,329 Thank you. OK, ok. 781 00:29:10,330 --> 00:29:12,479 Um from 782 00:29:12,480 --> 00:29:15,319 uh I forgot the first question again. 783 00:29:15,320 --> 00:29:17,469 What was the first question. 784 00:29:17,470 --> 00:29:19,659 Um, uh, 785 00:29:19,660 --> 00:29:20,709 biodiversity. 786 00:29:20,710 --> 00:29:22,799 Yeah. So, uh, there's certainly 787 00:29:22,800 --> 00:29:25,029 a um uh a trade off between 788 00:29:25,030 --> 00:29:27,879 those two. But as I said before, 789 00:29:27,880 --> 00:29:29,979 um, uh, in the past, only 790 00:29:29,980 --> 00:29:32,439 10 percent of the cropland 791 00:29:32,440 --> 00:29:34,269 in the last 50 years only increased by 792 00:29:34,270 --> 00:29:36,729 approximately 10, 11 percent. 793 00:29:36,730 --> 00:29:39,039 And all the rest of the productivity 794 00:29:39,040 --> 00:29:41,169 improvements were actually reached 795 00:29:41,170 --> 00:29:43,419 on, uh, on the area. 796 00:29:43,420 --> 00:29:45,489 At the moment, they are quite large yield 797 00:29:45,490 --> 00:29:47,679 gaps in wide, wide areas 798 00:29:47,680 --> 00:29:49,509 of the world where you could actually 799 00:29:49,510 --> 00:29:51,639 intensify, um, uh, 800 00:29:51,640 --> 00:29:53,349 and where it would be actually good to 801 00:29:53,350 --> 00:29:55,839 intensify the systems, um, 802 00:29:55,840 --> 00:29:58,899 uh, to a certain degree and 803 00:29:58,900 --> 00:30:01,059 without any land expansion actually 804 00:30:01,060 --> 00:30:02,709 necessary. 805 00:30:02,710 --> 00:30:04,599 There are certain areas where, I guess 806 00:30:04,600 --> 00:30:07,269 land expansion is possible. 807 00:30:07,270 --> 00:30:09,879 Um, it's always a trade off, of course. 808 00:30:09,880 --> 00:30:12,309 Um, uh, and we are trying 809 00:30:12,310 --> 00:30:14,409 to build in exactly this trade off by 810 00:30:14,410 --> 00:30:16,479 now, including biodiversity 811 00:30:16,480 --> 00:30:17,799 indicators in our model. 812 00:30:17,800 --> 00:30:19,899 But this is still a work in progress. 813 00:30:19,900 --> 00:30:22,059 Uh, to the second question on the fruits 814 00:30:22,060 --> 00:30:23,469 and vegetables, fruits and vegetables 815 00:30:23,470 --> 00:30:25,329 actually make up only a tiny share of 816 00:30:25,330 --> 00:30:26,649 current land use. 817 00:30:26,650 --> 00:30:28,839 Um, I think less than, uh, less than 10 818 00:30:28,840 --> 00:30:30,399 percent, definitely. 819 00:30:30,400 --> 00:30:32,469 Um, and at 820 00:30:32,470 --> 00:30:34,629 the same time, uh, they 821 00:30:34,630 --> 00:30:36,889 are producing quite high yields because, 822 00:30:36,890 --> 00:30:38,949 uh, it's not the land, 823 00:30:38,950 --> 00:30:41,049 which is the, uh, the the main resource 824 00:30:41,050 --> 00:30:43,149 there, but it's labor which goes in 825 00:30:43,150 --> 00:30:45,189 and, uh, capital. 826 00:30:45,190 --> 00:30:47,349 It's not necessarily a clean production 827 00:30:47,350 --> 00:30:49,599 either, because you have large nutrient 828 00:30:49,600 --> 00:30:51,969 runoff, often large pesticide use. 829 00:30:51,970 --> 00:30:54,039 But in terms of land use, it's not such a 830 00:30:54,040 --> 00:30:55,209 bad thing. 831 00:30:55,210 --> 00:30:57,279 You get quite high, um, 832 00:30:57,280 --> 00:30:59,469 uh, tons of, 833 00:30:59,470 --> 00:31:01,539 um, uh, product produce out of a 834 00:31:01,540 --> 00:31:02,769 vegetable farm. 835 00:31:02,770 --> 00:31:05,019 Um, but of course, there are also 836 00:31:05,020 --> 00:31:06,939 trade offs here. There's a sustainable 837 00:31:06,940 --> 00:31:09,429 probably if sugar is providing 838 00:31:09,430 --> 00:31:11,559 really cheap calories, um, 839 00:31:11,560 --> 00:31:13,449 uh, without large environmental 840 00:31:13,450 --> 00:31:16,029 footprint, if you calculated per calorie. 841 00:31:16,030 --> 00:31:17,979 In contrast, fruits and vegetables 842 00:31:17,980 --> 00:31:20,619 provides very little calories but provide 843 00:31:20,620 --> 00:31:22,689 a very nutritious food 844 00:31:22,690 --> 00:31:24,910 in terms of fiber, vitamins and so on, 845 00:31:26,890 --> 00:31:28,249 we have a lot of question. 846 00:31:28,250 --> 00:31:30,669 I see aid and one from the Internet. 847 00:31:30,670 --> 00:31:32,949 Uh, I we have just two minutes, so 848 00:31:32,950 --> 00:31:34,899 I take one from the Internet, one from 849 00:31:34,900 --> 00:31:37,449 five, and I ask everybody else 850 00:31:37,450 --> 00:31:40,179 to ask the speaker afterwards. 851 00:31:40,180 --> 00:31:41,109 Yeah, he is here. 852 00:31:41,110 --> 00:31:42,609 And he answered all your questions. 853 00:31:42,610 --> 00:31:45,299 So Internet. What is your question. 854 00:31:45,300 --> 00:31:47,379 OK, so 855 00:31:47,380 --> 00:31:49,539 the ACA asks, how do 856 00:31:49,540 --> 00:31:51,069 I get involved in modeling? 857 00:31:51,070 --> 00:31:53,529 Can I play with Magpie by downloading 858 00:31:53,530 --> 00:31:55,749 code and data somewhere 859 00:31:55,750 --> 00:31:56,799 along the Internet? 860 00:31:56,800 --> 00:31:58,450 Um, uh, the 861 00:31:59,680 --> 00:32:01,779 the model will become open source next 862 00:32:01,780 --> 00:32:04,239 year. So we are currently, um, 863 00:32:04,240 --> 00:32:06,459 in the process of the whole 864 00:32:06,460 --> 00:32:09,099 legal stuff of making it open source. 865 00:32:09,100 --> 00:32:11,229 Um, so the next model version of 866 00:32:11,230 --> 00:32:12,549 our model will be published. 867 00:32:12,550 --> 00:32:13,550 Open source. 868 00:32:20,260 --> 00:32:21,939 Microphone five, please. 869 00:32:21,940 --> 00:32:23,659 Hi, thanks for the great talk. 870 00:32:23,660 --> 00:32:25,929 Yes, last year there was also some talk 871 00:32:25,930 --> 00:32:28,149 about food plant 872 00:32:28,150 --> 00:32:30,219 based food innovation that that 873 00:32:30,220 --> 00:32:31,419 is science based. 874 00:32:31,420 --> 00:32:33,199 So my question is twofold. 875 00:32:33,200 --> 00:32:35,799 First, do you implement technological 876 00:32:35,800 --> 00:32:37,359 innovation that would lead to a more 877 00:32:37,360 --> 00:32:39,789 plant based diet 878 00:32:39,790 --> 00:32:42,039 and in general in the model 879 00:32:42,040 --> 00:32:43,629 and the second one, how hopeful are you 880 00:32:43,630 --> 00:32:45,839 personally that those will having 881 00:32:45,840 --> 00:32:48,349 an important impact in the future? 882 00:32:48,350 --> 00:32:51,339 You're speaking now of some kind of, um, 883 00:32:51,340 --> 00:32:53,499 plant based meat 884 00:32:53,500 --> 00:32:55,079 replacement products and so on? 885 00:32:55,080 --> 00:32:56,289 Um, yes. 886 00:32:56,290 --> 00:32:58,359 We we we actually published 887 00:32:58,360 --> 00:33:00,549 a study or a commentary 888 00:33:00,550 --> 00:33:03,309 this year also on, um, 889 00:33:03,310 --> 00:33:05,469 a quite extreme case of this, which is 890 00:33:05,470 --> 00:33:07,719 basically landless food production. 891 00:33:07,720 --> 00:33:10,209 So you can breed microbes 892 00:33:10,210 --> 00:33:12,429 based on fertilizer 893 00:33:12,430 --> 00:33:14,929 and energy, um, 894 00:33:14,930 --> 00:33:16,989 which is a kind of a space 895 00:33:16,990 --> 00:33:18,939 food technology which was developed by 896 00:33:18,940 --> 00:33:21,879 the Russians. But now it actually becomes 897 00:33:21,880 --> 00:33:24,399 commercial, um, uh, 898 00:33:24,400 --> 00:33:26,229 commercially cheap. 899 00:33:26,230 --> 00:33:28,719 Um, uh, I guess it will certainly 900 00:33:28,720 --> 00:33:31,299 happen for certain, uh, 901 00:33:31,300 --> 00:33:32,709 protein foods. 902 00:33:32,710 --> 00:33:35,529 So it will, for example, replace, 903 00:33:35,530 --> 00:33:37,749 um, uh, soybean or 904 00:33:37,750 --> 00:33:39,819 fishmeal in animal feeding 905 00:33:39,820 --> 00:33:41,479 to a certain proportion. 906 00:33:41,480 --> 00:33:43,839 Um, I'm not so sure about, 907 00:33:43,840 --> 00:33:46,449 uh, the actual nutritional 908 00:33:46,450 --> 00:33:48,789 value of this, um, 909 00:33:48,790 --> 00:33:50,379 or about. 910 00:33:50,380 --> 00:33:53,409 Well, I'm a bit skeptical how how 911 00:33:53,410 --> 00:33:55,149 positive I would judge it, but I would 912 00:33:55,150 --> 00:33:58,299 judge it quite realistic 913 00:33:58,300 --> 00:34:00,459 also for the whole meat replacement 914 00:34:00,460 --> 00:34:02,649 product based on on plant based, 915 00:34:02,650 --> 00:34:04,989 um, uh uh, 916 00:34:04,990 --> 00:34:07,419 on plant basis, I think it will become 917 00:34:07,420 --> 00:34:09,218 economically cheaper. 918 00:34:09,219 --> 00:34:11,529 And then you will have a tipping 919 00:34:11,530 --> 00:34:14,079 point where simply because 920 00:34:14,080 --> 00:34:16,599 of economic reason, it's cheaper, people 921 00:34:16,600 --> 00:34:18,819 will reduce their meat consumption, or 922 00:34:18,820 --> 00:34:20,948 for example, a burger will consist of 923 00:34:20,949 --> 00:34:23,259 half fake meat and half real 924 00:34:23,260 --> 00:34:24,669 meat because it's cheaper. 925 00:34:24,670 --> 00:34:27,249 And, um, I think this transformation 926 00:34:27,250 --> 00:34:29,559 will happen. And somehow the breeding 927 00:34:29,560 --> 00:34:31,749 animals just for 928 00:34:31,750 --> 00:34:34,178 for for their meat seems 929 00:34:34,179 --> 00:34:36,279 the technology, which is somehow outdated 930 00:34:36,280 --> 00:34:37,989 for the 21st century, if you ask me. 931 00:34:41,750 --> 00:34:43,999 Then give more than a big 932 00:34:44,000 --> 00:34:46,069 applause to Dr. 933 00:34:46,070 --> 00:34:47,329 Benjamin Leon. 934 00:34:53,310 --> 00:34:54,310 Thank you.