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Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:00.00,0:00:20.13,Default,,0000,0000,0000,,{\i1}36C3 preroll music{\i0}
Dialogue: 0,0:00:20.13,0:00:25.17,Default,,0000,0000,0000,,Angel: Right now I'd like to welcome our\Nfirst speaker on stage. The talk will be
Dialogue: 0,0:00:25.17,0:00:30.80,Default,,0000,0000,0000,,about protecting the wild and I'll hand\Nover to her. Please give her a warm round
Dialogue: 0,0:00:30.80,0:00:32.87,Default,,0000,0000,0000,,of applause.
Dialogue: 0,0:00:32.87,0:00:34.86,Default,,0000,0000,0000,,{\i1}Applause{\i0}
Dialogue: 0,0:00:34.86,0:00:43.92,Default,,0000,0000,0000,,Jutta Buschbom: Thank you very much for\Nthe introduction. My name is Jutta
Dialogue: 0,0:00:43.92,0:00:52.11,Default,,0000,0000,0000,,Buschbom, I'm an evolutionary biologist.\NThat is my background. I did do my PHD at
Dialogue: 0,0:00:52.11,0:00:57.29,Default,,0000,0000,0000,,the University of Chicago working on\Nlittle fungees that live in symbiosis with
Dialogue: 0,0:00:57.29,0:01:05.98,Default,,0000,0000,0000,,algae and form colorful rocks, colorful\Ncrust on rocks. I then did a Postdoc in
Dialogue: 0,0:01:05.98,0:01:12.24,Default,,0000,0000,0000,,bioinformatics and after that moved back\Ninto organismal biology, working in forest
Dialogue: 0,0:01:12.24,0:01:19.56,Default,,0000,0000,0000,,genetics. And the ten years I worked in\Nforest genetics for the first time I
Dialogue: 0,0:01:19.56,0:01:26.05,Default,,0000,0000,0000,,encountered questions that were with\Nregard to application, and I found out
Dialogue: 0,0:01:26.05,0:01:37.36,Default,,0000,0000,0000,,that actually moving from research to\Napplication is not trivial. So what I'm
Dialogue: 0,0:01:37.36,0:01:45.87,Default,,0000,0000,0000,,going to present is a high tech way using\Ngenomic data to protect biodiversity in a
Dialogue: 0,0:01:45.87,0:01:51.94,Default,,0000,0000,0000,,way that you can actually reach\Napplication and use conservation genomic
Dialogue: 0,0:01:51.94,0:02:02.60,Default,,0000,0000,0000,,tools. So this summer the draft of the\Nreport of the Intergovernmental Science
Dialogue: 0,0:02:02.60,0:02:12.32,Default,,0000,0000,0000,,Policy Panel for Biodiversity and\NEcosystem Services came out and its
Dialogue: 0,0:02:12.32,0:02:19.93,Default,,0000,0000,0000,,results were quite warning. It stated that\Naround a million animal and plant species
Dialogue: 0,0:02:19.93,0:02:27.33,Default,,0000,0000,0000,,are currently stated and of those...half\Nof those species are already dead species
Dialogue: 0,0:02:27.33,0:02:33.45,Default,,0000,0000,0000,,walking. So because due to the destruction\Nof the habitats or habitat deterioration,
Dialogue: 0,0:02:33.45,0:02:42.95,Default,,0000,0000,0000,,they are not able to reproduce in a\Nsustainable way anymore. A third of the
Dialogue: 0,0:02:42.95,0:02:51.17,Default,,0000,0000,0000,,total species extinction rate risk to date\Nhas arisen in the last 25 years. And just
Dialogue: 0,0:02:51.17,0:03:01.45,Default,,0000,0000,0000,,to give you an idea about the relation we\Nare talking about...currently the rate of
Dialogue: 0,0:03:01.45,0:03:07.68,Default,,0000,0000,0000,,extinction risk is already at least ten to\Nhundreds times higher than it has averaged
Dialogue: 0,0:03:07.68,0:03:13.13,Default,,0000,0000,0000,,over the past 10 million years. And within\Nthese 10 million years there were the Ice
Dialogue: 0,0:03:13.13,0:03:23.26,Default,,0000,0000,0000,,Ages, for example. And most of the\Nextinction risk is due to the fact of land
Dialogue: 0,0:03:23.26,0:03:36.19,Default,,0000,0000,0000,,and sea use change. The report also talks,\Neven talks about that we already seem to
Dialogue: 0,0:03:36.19,0:03:42.42,Default,,0000,0000,0000,,have transgressed a proposed precautionary\Nplanetary boundary, which means within the
Dialogue: 0,0:03:42.42,0:03:48.37,Default,,0000,0000,0000,,boundary we have a stable biological\Nsystem. But having transgressed it, we
Dialogue: 0,0:03:48.37,0:03:55.43,Default,,0000,0000,0000,,might already be in a transition to a new\Nstate that we have no way to find out how
Dialogue: 0,0:03:55.43,0:04:05.24,Default,,0000,0000,0000,,this state is going to look like. So all\Nof these facts that the report is stating
Dialogue: 0,0:04:05.24,0:04:14.73,Default,,0000,0000,0000,,are actually pretty negative. And I was\Nquite happy to read that they also present
Dialogue: 0,0:04:14.73,0:04:20.70,Default,,0000,0000,0000,,that there are actually people who do\Nbetter than most of us. And they point out
Dialogue: 0,0:04:20.70,0:04:27.81,Default,,0000,0000,0000,,that many practices of indigenous people\Nand local communities actually conserve
Dialogue: 0,0:04:27.81,0:04:38.35,Default,,0000,0000,0000,,and sustain wild and domesticated\Nbiodiversity quite well. Today, a higher
Dialogue: 0,0:04:38.35,0:04:44.60,Default,,0000,0000,0000,,proportion of the remaining terrestrial\Nbiodiversity lies in areas managed and
Dialogue: 0,0:04:44.60,0:04:52.89,Default,,0000,0000,0000,,held by indigenous people. And these\Necosystems are more intact and less
Dialogue: 0,0:04:52.89,0:05:01.77,Default,,0000,0000,0000,,declining, less rapidly declining. So we\Nhave examples of lifestyles that actually
Dialogue: 0,0:05:01.77,0:05:10.53,Default,,0000,0000,0000,,do better than most of us. And I know the\Nsolutions won't be simple and it won't be
Dialogue: 0,0:05:10.53,0:05:22.33,Default,,0000,0000,0000,,easy to get there but we can look to what\Nthese people do better than we do. All of
Dialogue: 0,0:05:22.33,0:05:27.93,Default,,0000,0000,0000,,this sounds...it's a global report and it\Nsounds kind of like far away, like
Dialogue: 0,0:05:27.93,0:05:35.99,Default,,0000,0000,0000,,probably somewhere in the tropics, but\Nactually threats to biodiversity happen
Dialogue: 0,0:05:35.99,0:05:45.40,Default,,0000,0000,0000,,also directly in front of our own front\Ndoors. This summer a paper came out from
Dialogue: 0,0:05:45.40,0:05:52.80,Default,,0000,0000,0000,,two colleagues from the University of\NGreifswald, who had analyzed the long term
Dialogue: 0,0:05:52.80,0:05:58.49,Default,,0000,0000,0000,,data set about leaf beetles. And they were\Nasking if we already have a decline of
Dialogue: 0,0:05:58.49,0:06:08.24,Default,,0000,0000,0000,,leaf beetles in Central Europe. So they\Ncompiled long term data sets of leaf
Dialogue: 0,0:06:08.24,0:06:19.14,Default,,0000,0000,0000,,beetle observations for Central Europe,\Nstarting from 1900 now to 2017, so
Dialogue: 0,0:06:19.14,0:06:27.01,Default,,0000,0000,0000,,spanning a hundred and twenty years. And\Nwhat they find is that systematic reports
Dialogue: 0,0:06:27.01,0:06:36.27,Default,,0000,0000,0000,,on leaf beetles and leaf beetle\Nobservations are increasing during this
Dialogue: 0,0:06:36.27,0:06:45.31,Default,,0000,0000,0000,,time interval, time span. But despite the\Nfact that we have...like in the last two
Dialogue: 0,0:06:45.31,0:06:53.27,Default,,0000,0000,0000,,decades, we had very high numbers of\Nreports and observations for leaf beetles,
Dialogue: 0,0:06:53.27,0:07:00.10,Default,,0000,0000,0000,,the number of species, the orange line, is\Ndeclining. It's slightly declining. But
Dialogue: 0,0:07:00.10,0:07:06.01,Default,,0000,0000,0000,,the question is, is this real or not? And\Nwhat was most worrisome to the authors is
Dialogue: 0,0:07:06.01,0:07:15.11,Default,,0000,0000,0000,,that in the data set, the number of\Nspecies here in orange that were having
Dialogue: 0,0:07:15.11,0:07:21.93,Default,,0000,0000,0000,,more reports was declining, while the\Nnumber of species that showed less reports
Dialogue: 0,0:07:21.93,0:07:33.93,Default,,0000,0000,0000,,than before is expanding. So this kind of\Nlong term datasets are very hard to
Dialogue: 0,0:07:33.93,0:07:41.31,Default,,0000,0000,0000,,interpret and many factors can contribute\Nto those patterns. And it's not clear if
Dialogue: 0,0:07:41.31,0:07:48.31,Default,,0000,0000,0000,,this pattern is statistically significant.\NBut if you take a step back and consider
Dialogue: 0,0:07:48.31,0:07:54.47,Default,,0000,0000,0000,,your background knowledge, your prior\Nknowledge about the state of the world, do
Dialogue: 0,0:07:54.47,0:08:02.76,Default,,0000,0000,0000,,you say, like, how does the current state\Nlook like? Does it look good or rather
Dialogue: 0,0:08:02.76,0:08:16.91,Default,,0000,0000,0000,,worrisome? And then with that knowledge,\Ntell me that these results are an
Dialogue: 0,0:08:16.91,0:08:30.15,Default,,0000,0000,0000,,artifact or a bias. I'm worried that once\Nwe have statistical significant signal in
Dialogue: 0,0:08:30.15,0:08:41.79,Default,,0000,0000,0000,,this dataset, it will be already too late.\NSo right now, I've been talking about leaf
Dialogue: 0,0:08:41.79,0:08:49.64,Default,,0000,0000,0000,,beetles and beetles are the largest group\Nwithin insects with about 400.000 species.
Dialogue: 0,0:08:49.64,0:08:56.20,Default,,0000,0000,0000,,Leaf beetles are a large family of about\N50.000 species which are worldwide
Dialogue: 0,0:08:56.20,0:09:05.08,Default,,0000,0000,0000,,distributed. And here in Germany, we have\Nover 470 leaf beetle species. So how do we
Dialogue: 0,0:09:05.08,0:09:09.74,Default,,0000,0000,0000,,actually know how many species there are\Nand who actually counted all these
Dialogue: 0,0:09:09.74,0:09:15.96,Default,,0000,0000,0000,,species? And is that just a task of\Ntaxonomists. Taxonomy is the science of
Dialogue: 0,0:09:15.96,0:09:21.60,Default,,0000,0000,0000,,naming and defining, including\Ncircumscribing and classifying groups of
Dialogue: 0,0:09:21.60,0:09:32.02,Default,,0000,0000,0000,,biological organisms on the basis of\Nshared characters. So one could have the
Dialogue: 0,0:09:32.02,0:09:37.56,Default,,0000,0000,0000,,picture of some woman with a funny hat\Nrunning over a meadow catching like
Dialogue: 0,0:09:37.56,0:09:44.48,Default,,0000,0000,0000,,butterflies or some guy mushroom hunter\Ncrawling through the forest trying to find
Dialogue: 0,0:09:44.48,0:09:52.38,Default,,0000,0000,0000,,mushrooms. And it's true, as biodiversity\Nscientists we spent a lot of time outdoors
Dialogue: 0,0:09:52.38,0:10:02.29,Default,,0000,0000,0000,,and yeah...on the other hand, biotaxonomy\Nis a high-tech science today. So
Dialogue: 0,0:10:02.29,0:10:11.05,Default,,0000,0000,0000,,taxonomists actually take up new\Ntechnological tools and developments to
Dialogue: 0,0:10:11.05,0:10:17.27,Default,,0000,0000,0000,,help them identify and describe,\Nunderstand the species. So taxonomists
Dialogue: 0,0:10:17.27,0:10:25.11,Default,,0000,0000,0000,,actually are often experts in, for\Nexample, microscopy, mathematics,
Dialogue: 0,0:10:25.11,0:10:36.85,Default,,0000,0000,0000,,biochemistry, even proteomics and\Ngenomics. So throughout the talk, I'm
Dialogue: 0,0:10:36.85,0:10:41.52,Default,,0000,0000,0000,,going to compile this list of people and\Nexperts we're going to need to protect
Dialogue: 0,0:10:41.52,0:10:49.36,Default,,0000,0000,0000,,biodiversity if we want to do this on the\Nbasis of genetic data. Right now, the list
Dialogue: 0,0:10:49.36,0:10:56.43,Default,,0000,0000,0000,,is quite empty. The first entry is a\Ntaxonomists, but that will change quickly
Dialogue: 0,0:10:56.43,0:11:06.26,Default,,0000,0000,0000,,and taxonomists are a subgroup of\Nevolutionary biologists mostly. So I told
Dialogue: 0,0:11:06.26,0:11:15.56,Default,,0000,0000,0000,,you as taxonomists and biodiversity\Nscientists take up technology and...so as
Dialogue: 0,0:11:15.56,0:11:23.61,Default,,0000,0000,0000,,soon as computers came about and the\Ninternet started people started to use
Dialogue: 0,0:11:23.61,0:11:32.42,Default,,0000,0000,0000,,that to compile information about species,\Nand today we have several global resources
Dialogue: 0,0:11:32.42,0:11:40.64,Default,,0000,0000,0000,,available at the species level and above\Nthe species level. So we biodiversity
Dialogue: 0,0:11:40.64,0:11:45.72,Default,,0000,0000,0000,,scientists were among the first who\Ndefined biodiversity information
Dialogue: 0,0:11:45.72,0:11:56.69,Default,,0000,0000,0000,,standards. We have a global catalog of\Nlife. A list of all named species. The
Dialogue: 0,0:11:56.69,0:12:01.81,Default,,0000,0000,0000,,Global Biodiversity Information Facility\Nhas an aim to bring together information
Dialogue: 0,0:12:01.81,0:12:08.63,Default,,0000,0000,0000,,from different sources and they are\Ncompiling, producing this wonderful map.
Dialogue: 0,0:12:08.63,0:12:13.94,Default,,0000,0000,0000,,This is leaf beetles, all the records\Nabout leaf beetles that we have in the
Dialogue: 0,0:12:13.94,0:12:22.20,Default,,0000,0000,0000,,world. And it looks like as if leaf\Nbeetles are highly associated with third
Dialogue: 0,0:12:22.20,0:12:29.58,Default,,0000,0000,0000,,world economics. However that clearly is\Nan artifact and it just shows that we need
Dialogue: 0,0:12:29.58,0:12:34.56,Default,,0000,0000,0000,,many more taxonomists and biodiversity\Nscientists all over the world to find and
Dialogue: 0,0:12:34.56,0:12:45.30,Default,,0000,0000,0000,,identify leaf beetles. So we also need\Nbiodiversity informaticians to help us
Dialogue: 0,0:12:45.30,0:12:52.05,Default,,0000,0000,0000,,compile global lists and distribute\Nknowledge. So far I have been talking
Dialogue: 0,0:12:52.05,0:12:57.89,Default,,0000,0000,0000,,about species which is a simplification.\NThe question is what is...what are species
Dialogue: 0,0:12:57.89,0:13:03.40,Default,,0000,0000,0000,,actually? And so we need to talk about\Ngenetic diversity within and between
Dialogue: 0,0:13:03.40,0:13:16.52,Default,,0000,0000,0000,,species. And I'm going to do so using\Ngulls, which most of us might know. Here
Dialogue: 0,0:13:16.52,0:13:21.67,Default,,0000,0000,0000,,in Europe, we have two large gulls of the\Ngenus Larus. One is in the front, the
Dialogue: 0,0:13:21.67,0:13:31.07,Default,,0000,0000,0000,,lighter gray is our Silbermöwe. And in the\Nback is our Heringsmöwe, the dark one. And
Dialogue: 0,0:13:31.07,0:13:35.74,Default,,0000,0000,0000,,I'm going to use German names because the\NEnglish names go crosswise and that's
Dialogue: 0,0:13:35.74,0:13:43.16,Default,,0000,0000,0000,,completely confusing. So I will stick with\Nthe German names. Here in Europe these two
Dialogue: 0,0:13:43.16,0:13:48.45,Default,,0000,0000,0000,,species seem to be really fine species\Nbecause they barely interbreed, so they
Dialogue: 0,0:13:48.45,0:13:55.68,Default,,0000,0000,0000,,don't hybridize. However, if you take a\Nstep back and look at the genus in
Dialogue: 0,0:13:55.68,0:14:03.12,Default,,0000,0000,0000,,general, you see that the species of the\Ngenus are distributed kind of ringwise
Dialogue: 0,0:14:03.12,0:14:14.51,Default,,0000,0000,0000,,around the Arctic. And so the idea is\Nthat, say during the Ice Age, all of this
Dialogue: 0,0:14:14.51,0:14:22.96,Default,,0000,0000,0000,,area was glaciated and the gulls retreated\Nto a refuge here near the Caspian Sea. And
Dialogue: 0,0:14:22.96,0:14:28.11,Default,,0000,0000,0000,,then after the ice retreated, the gulls\Nmoved back north. One branch moved into
Dialogue: 0,0:14:28.11,0:14:34.35,Default,,0000,0000,0000,,Europe forming our Heringsmöwe and\Nanother branch then moved counterclockwise
Dialogue: 0,0:14:34.35,0:14:41.02,Default,,0000,0000,0000,,around the Arctic, producing different\Nmorphotypes, different species across the
Dialogue: 0,0:14:41.02,0:14:49.45,Default,,0000,0000,0000,,Bering Strait and then into North America.\NThere the dark blue one is...I'm
Dialogue: 0,0:14:49.45,0:14:58.73,Default,,0000,0000,0000,,simplifying, the equivalent of our\NEuropean Silbermöwe, the American
Dialogue: 0,0:14:58.73,0:15:03.83,Default,,0000,0000,0000,,Silbermöwe. Then the idea is that some\Nindividuals crossed back to Europe and
Dialogue: 0,0:15:03.83,0:15:14.80,Default,,0000,0000,0000,,formed our European Silbermöwe. And while\Nall of these species here are
Dialogue: 0,0:15:14.80,0:15:21.77,Default,,0000,0000,0000,,interbreeding, so they hybridize. Only\Nwhen this ring is closed those two species
Dialogue: 0,0:15:21.77,0:15:26.72,Default,,0000,0000,0000,,don't interbreed anymore. And the big\Nquestion is, are we actually dealing with
Dialogue: 0,0:15:26.72,0:15:34.23,Default,,0000,0000,0000,,one single species or are we dealing with\Ndifferent species that just happened to
Dialogue: 0,0:15:34.23,0:15:41.08,Default,,0000,0000,0000,,hybridize more or less? The question is\Nnot trivial because it has consequences
Dialogue: 0,0:15:41.08,0:15:48.74,Default,,0000,0000,0000,,for protection. If we are dealing with one\Nsingle species, all the gulls in Eurasia
Dialogue: 0,0:15:48.74,0:15:53.01,Default,,0000,0000,0000,,could go extinct and it wouldn't matter\Nbecause we still would have the gulls in
Dialogue: 0,0:15:53.01,0:15:58.54,Default,,0000,0000,0000,,North America. However, if we have\Ndifferent species in all of these areas,
Dialogue: 0,0:15:58.54,0:16:04.71,Default,,0000,0000,0000,,we would need to protect individuals or\Nthe species on a regional level and
Dialogue: 0,0:16:04.71,0:16:17.28,Default,,0000,0000,0000,,protect all of these different species. So\Nto investigate this question about: Do we
Dialogue: 0,0:16:17.28,0:16:23.59,Default,,0000,0000,0000,,have different species? And what were the\Nevolutionary processes and histories that
Dialogue: 0,0:16:23.59,0:16:31.10,Default,,0000,0000,0000,,brought about the species? A group of\Nscientists investigated that using DNA
Dialogue: 0,0:16:31.10,0:16:39.93,Default,,0000,0000,0000,,sequences. And on the left, you have the\Nmodel, the theoretical model of the ring
Dialogue: 0,0:16:39.93,0:16:46.38,Default,,0000,0000,0000,,species. And here on the right you have\Nreality. And the scientists found that the
Dialogue: 0,0:16:46.38,0:16:51.63,Default,,0000,0000,0000,,reality is always much more complex. So,\Nfor example, they found two refuges or
Dialogue: 0,0:16:51.63,0:16:58.43,Default,,0000,0000,0000,,they proposed two refuges. But what they\Nfound was that genetic diversity was
Dialogue: 0,0:16:58.43,0:17:07.35,Default,,0000,0000,0000,,correlated with those species or\Nmorphotypes. So what that also means is
Dialogue: 0,0:17:07.35,0:17:15.73,Default,,0000,0000,0000,,that genetic diversity is cultivated with\Ngeographic origin. What we learn from this
Dialogue: 0,0:17:15.73,0:17:24.36,Default,,0000,0000,0000,,type of analysis is we learn about\Nevolutionary processes and history, about
Dialogue: 0,0:17:24.36,0:17:30.17,Default,,0000,0000,0000,,variability and differentiation of our\Ngene flow and migration, about speciation
Dialogue: 0,0:17:30.17,0:17:37.59,Default,,0000,0000,0000,,processes. That we all need to understand\Nour species, which will allow us to
Dialogue: 0,0:17:37.59,0:17:43.44,Default,,0000,0000,0000,,protect them. So we need evolutionary\Nbiologists who do follow genetics and
Dialogue: 0,0:17:43.44,0:17:59.03,Default,,0000,0000,0000,,population genetics. So once we found out\Nthat one can use genetic diversity, to
Dialogue: 0,0:17:59.03,0:18:07.13,Default,,0000,0000,0000,,infer geographic origin because genetic\Ndiversity is correlated with geography,
Dialogue: 0,0:18:07.13,0:18:18.50,Default,,0000,0000,0000,,people immediately said: 'Okay, we can use\Nit for conservation applications.'. And
Dialogue: 0,0:18:18.50,0:18:24.05,Default,,0000,0000,0000,,it's also...we learned that we...often it\Nis unclear what is a species, species
Dialogue: 0,0:18:24.05,0:18:32.56,Default,,0000,0000,0000,,boundaries are unclear and some species\Nhave huge distribution ranges with
Dialogue: 0,0:18:32.56,0:18:37.34,Default,,0000,0000,0000,,different clusters of viability within\Nthis huge range. So we know that we need
Dialogue: 0,0:18:37.34,0:18:42.94,Default,,0000,0000,0000,,to protect within species genetic\Ndiversity, which means that we need to
Dialogue: 0,0:18:42.94,0:18:50.65,Default,,0000,0000,0000,,understand within species population\Nstructure and we need to build useful and
Dialogue: 0,0:18:50.65,0:18:58.92,Default,,0000,0000,0000,,reliable models of population structure.\NThese models are actually required for all
Dialogue: 0,0:18:58.92,0:19:03.74,Default,,0000,0000,0000,,of our applications. They are required for\Nmonitoring, for example, for conservation
Dialogue: 0,0:19:03.74,0:19:11.89,Default,,0000,0000,0000,,strategies, for functional adaptation and\Nadaptability, questions of productability
Dialogue: 0,0:19:11.89,0:19:19.19,Default,,0000,0000,0000,,of different provenances, its impact on\Nmanagement regimes, breeding strategies,
Dialogue: 0,0:19:19.19,0:19:27.61,Default,,0000,0000,0000,,and also for enforcement applications.\NFrom the studies I showed you before with
Dialogue: 0,0:19:27.61,0:19:34.11,Default,,0000,0000,0000,,the gulls we also know that we need to\Napproach the question of a population
Dialogue: 0,0:19:34.11,0:19:47.07,Default,,0000,0000,0000,,structure on a distribution range wide\Nscale. So here's the map produced by
Dialogue: 0,0:19:47.07,0:19:53.63,Default,,0000,0000,0000,,EUFORGENE, the European Network for forest\Nreproductive material for one of our
Dialogue: 0,0:19:53.63,0:20:02.00,Default,,0000,0000,0000,,native oaks, the sessil oak. And the dots\Nare the sites for genetic conservation
Dialogue: 0,0:20:02.00,0:20:12.12,Default,,0000,0000,0000,,units. And so that is one strategy how to\Nrepresent within species genetic diversity
Dialogue: 0,0:20:12.12,0:20:22.02,Default,,0000,0000,0000,,and how to sample it. And you can see this\Nis a hypothetical example, but we likely
Dialogue: 0,0:20:22.02,0:20:32.46,Default,,0000,0000,0000,,will see a gradient from west to east or\Nmight see one at this scale. Then once we
Dialogue: 0,0:20:32.46,0:20:37.80,Default,,0000,0000,0000,,have these kind of global data sets, we\Ncan go to the fine scale and maybe, for
Dialogue: 0,0:20:37.80,0:20:44.10,Default,,0000,0000,0000,,example, do a national genetic monitoring.\NAnd we will find much finer scale
Dialogue: 0,0:20:44.10,0:20:51.21,Default,,0000,0000,0000,,gradients. We also will find especially\Nfor first trace outliers, so for stands
Dialogue: 0,0:20:51.21,0:20:59.15,Default,,0000,0000,0000,,that don't fit the usual pattern. And that\Nis because the first reproductive material
Dialogue: 0,0:20:59.15,0:21:07.66,Default,,0000,0000,0000,,has been moved around a lot. And so these\Nlighter or darker dots is material that
Dialogue: 0,0:21:07.66,0:21:16.15,Default,,0000,0000,0000,,was moved to Germany from the outside. And\Nwe only will identify these outliers if we
Dialogue: 0,0:21:16.15,0:21:21.38,Default,,0000,0000,0000,,have the whole reference dataset. If we\Ndon't have the whole reference dataset, we
Dialogue: 0,0:21:21.38,0:21:28.80,Default,,0000,0000,0000,,might not identify these outliers - stands\Nwith a different history. Or in a worst
Dialogue: 0,0:21:28.80,0:21:34.28,Default,,0000,0000,0000,,case, these outliers might actually bias\Nour gradients. And we are always talking
Dialogue: 0,0:21:34.28,0:21:42.77,Default,,0000,0000,0000,,about very slight gradients. So it's easy\Nto bias these gradiants, dilute them, so
Dialogue: 0,0:21:42.77,0:21:50.71,Default,,0000,0000,0000,,we actually won't get the results we need.\NTo compile these kinds of reference
Dialogue: 0,0:21:50.71,0:21:57.85,Default,,0000,0000,0000,,datasets that's huge collaborative efforts\Nbecause people need to go out into the
Dialogue: 0,0:21:57.85,0:22:04.50,Default,,0000,0000,0000,,field and collect the reference samples\Nand that might be scientists, that might
Dialogue: 0,0:22:04.50,0:22:13.67,Default,,0000,0000,0000,,be people from local communities, citizen\Nscientists, managers, owners, government
Dialogue: 0,0:22:13.67,0:22:20.18,Default,,0000,0000,0000,,officials who provide background\Ninformation, maps, distribution
Dialogue: 0,0:22:20.18,0:22:27.93,Default,,0000,0000,0000,,information and also in many parts of the\Nworld might protect the people who are
Dialogue: 0,0:22:27.93,0:22:34.51,Default,,0000,0000,0000,,actually collecting the samples. And it\Nmight be conservation activists and NGOs.
Dialogue: 0,0:22:34.51,0:22:41.15,Default,,0000,0000,0000,,So once the samples have been collected\Nthey need to be stored somewhere for the
Dialogue: 0,0:22:41.15,0:22:51.15,Default,,0000,0000,0000,,long term and the information needs to be\Ndatabased. And that is the work of
Dialogue: 0,0:22:51.15,0:22:57.43,Default,,0000,0000,0000,,scientific connections, which are mostly\Nat natural history museums and there the
Dialogue: 0,0:22:57.43,0:23:04.46,Default,,0000,0000,0000,,samples are processed. They're organized\Nin ways that you can find them again. All
Dialogue: 0,0:23:04.46,0:23:09.68,Default,,0000,0000,0000,,the metadata is entered, which curators\Ndo, collection managers, preparators,
Dialogue: 0,0:23:09.68,0:23:17.03,Default,,0000,0000,0000,,technical staff at the scientific\Ncollections. So once we have these kind of
Dialogue: 0,0:23:17.03,0:23:24.91,Default,,0000,0000,0000,,data sets, large scale data sets, what are\Nwe actually doing with them? So the
Dialogue: 0,0:23:24.91,0:23:32.51,Default,,0000,0000,0000,,foundation for all of our applications is\Npopulation structure and there
Dialogue: 0,0:23:32.51,0:23:42.37,Default,,0000,0000,0000,,specifically population assignment. So the\Nprocess is set first. We decide on a
Dialogue: 0,0:23:42.37,0:23:46.66,Default,,0000,0000,0000,,question and design our project\Naccordingly that we can answer the
Dialogue: 0,0:23:46.66,0:23:51.94,Default,,0000,0000,0000,,question. Then we need to infer the\Npopulation structure model and optimize
Dialogue: 0,0:23:51.94,0:23:57.48,Default,,0000,0000,0000,,it. In the next step we need to check if a\Nmodel actually is good enough for
Dialogue: 0,0:23:57.48,0:24:03.04,Default,,0000,0000,0000,,application because we might have found\Nthe best model, but it might still not be
Dialogue: 0,0:24:03.04,0:24:07.48,Default,,0000,0000,0000,,good enough for application. So we need to\Ntest that. And that is the step of
Dialogue: 0,0:24:07.48,0:24:12.83,Default,,0000,0000,0000,,population assignment or predictive\Nassignment. And then in the end, we want
Dialogue: 0,0:24:12.83,0:24:19.33,Default,,0000,0000,0000,,to test our hypothesis. Are the two stands\Ndifferent or does an individual come from
Dialogue: 0,0:24:19.33,0:24:31.06,Default,,0000,0000,0000,,stand A or from stand B? And here we\Nidentify error rates and accuracy. So this
Dialogue: 0,0:24:31.06,0:24:38.89,Default,,0000,0000,0000,,whole process is very statistical. And so\Nthe analysis of these reference data they
Dialogue: 0,0:24:38.89,0:24:48.24,Default,,0000,0000,0000,,need to be accompanied by biostatisticians\Nwho can tell us how to analyze our data.
Dialogue: 0,0:24:48.24,0:24:55.29,Default,,0000,0000,0000,,So what is the state-of-the-art right now?\NWhat kind of geographic resolution do we
Dialogue: 0,0:24:55.29,0:25:02.99,Default,,0000,0000,0000,,actually get of this non model specie\Ncurrently? And I'm going to present the
Dialogue: 0,0:25:02.99,0:25:09.60,Default,,0000,0000,0000,,example of an African timber tree\Nspecies, which is a very valuable timber.
Dialogue: 0,0:25:09.60,0:25:18.11,Default,,0000,0000,0000,,It's one example but basically all results\Nfor species who have large distribution
Dialogue: 0,0:25:18.11,0:25:26.06,Default,,0000,0000,0000,,ranges and are continuously distributed\Nand are also long-lived, are very similar.
Dialogue: 0,0:25:26.06,0:25:33.46,Default,,0000,0000,0000,,So this kind of results seem to be species\Nindependent. So the species are Milica
Dialogue: 0,0:25:33.46,0:25:40.37,Default,,0000,0000,0000,,regia and excelsa, African teak, which\Ncannot be grown in plantations for timber
Dialogue: 0,0:25:40.37,0:25:51.16,Default,,0000,0000,0000,,quality. So it is harvested unsustainably\Nfrom natural forests. It's distributed in
Dialogue: 0,0:25:51.16,0:26:00.58,Default,,0000,0000,0000,,West, Central and East Africa. Here's a\Nblack rectangle. And a group of a dozen
Dialogue: 0,0:26:00.58,0:26:06.29,Default,,0000,0000,0000,,scientists got together and they actually\Nsampled a reference dataset for these two
Dialogue: 0,0:26:06.29,0:26:18.66,Default,,0000,0000,0000,,species. It's about over 400 samples, they\Nanalyzed four marker systems, resulting in
Dialogue: 0,0:26:18.66,0:26:24.57,Default,,0000,0000,0000,,a total of something like 100 markers,\Ngenetic markers, and then they optimized
Dialogue: 0,0:26:24.57,0:26:32.66,Default,,0000,0000,0000,,the population model and used different\Nparameter settings. And we're going to
Dialogue: 0,0:26:32.66,0:26:40.08,Default,,0000,0000,0000,,concentrate here on the best solution that\Nthey found. And basically this rectangle
Dialogue: 0,0:26:40.08,0:26:47.87,Default,,0000,0000,0000,,here is the black one over here. So the\Nresolution is... they found population
Dialogue: 0,0:26:47.87,0:26:54.69,Default,,0000,0000,0000,,structure with clear clusters. So the\Npopulations and the species from West
Dialogue: 0,0:26:54.69,0:27:01.49,Default,,0000,0000,0000,,Africa can be distinguished from those\Npopulations in Central Africa. And the
Dialogue: 0,0:27:01.49,0:27:08.46,Default,,0000,0000,0000,,ones in East Africa can be differentiated.\NSo that is really good. So we have
Dialogue: 0,0:27:08.46,0:27:13.48,Default,,0000,0000,0000,,population structure. We know their\Nsignal. The problem is still that our
Dialogue: 0,0:27:13.48,0:27:21.51,Default,,0000,0000,0000,,resolution is much lower than we would\Nneed to have it because we basically need
Dialogue: 0,0:27:21.51,0:27:32.09,Default,,0000,0000,0000,,resolution at least on a country level,\Nbecause most of the laws are national. So
Dialogue: 0,0:27:32.09,0:27:41.77,Default,,0000,0000,0000,,it might be legal to harvest a tree in one\Ncountry, but not in another country. So we
Dialogue: 0,0:27:41.77,0:27:49.32,Default,,0000,0000,0000,,need to get our resolution down to country\Nlevel or even to regional level. If you
Dialogue: 0,0:27:49.32,0:27:52.36,Default,,0000,0000,0000,,want to distinguish, was the tree\Nharvested in a national park in a
Dialogue: 0,0:27:52.36,0:28:02.29,Default,,0000,0000,0000,,protected area or outside in a managed\Nforest. And when as biodiversity
Dialogue: 0,0:28:02.29,0:28:10.74,Default,,0000,0000,0000,,scientists, we don't know how to continue,\None thing is to look for what people do
Dialogue: 0,0:28:10.74,0:28:17.18,Default,,0000,0000,0000,,with model organisms and specifically what\Npeople do in human population genomics
Dialogue: 0,0:28:17.18,0:28:24.18,Default,,0000,0000,0000,,because there thousands of populations\Ngeneticists are working and there is a
Dialogue: 0,0:28:24.18,0:28:28.21,Default,,0000,0000,0000,,completely different funding background\Ndue to the interest of the medical and the
Dialogue: 0,0:28:28.21,0:28:39.12,Default,,0000,0000,0000,,pharma industry. So they are always\Nadvanced. What we can learn from there,
Dialogue: 0,0:28:39.12,0:28:46.66,Default,,0000,0000,0000,,from the human populations genomics is\Nthat we need two features. One is we
Dialogue: 0,0:28:46.66,0:28:53.57,Default,,0000,0000,0000,,already know that we need distribution\Nwide sampling, which provides a spatial
Dialogue: 0,0:28:53.57,0:28:59.95,Default,,0000,0000,0000,,context. The second feature is that we\Nneed genome wide sequencing, preferably
Dialogue: 0,0:28:59.95,0:29:09.21,Default,,0000,0000,0000,,genome sequencing, which provides us steps\Nin time because our genomes are archives
Dialogue: 0,0:29:09.21,0:29:14.71,Default,,0000,0000,0000,,of our evolutionary history. They are\Nrecords of all the processes and events
Dialogue: 0,0:29:14.71,0:29:21.43,Default,,0000,0000,0000,,and these steps in time then translate\Nalso into resolution. Once we have these
Dialogue: 0,0:29:21.43,0:29:30.15,Default,,0000,0000,0000,,two features, actually these reference\Ndatasets open Pandora's box. Suddently we
Dialogue: 0,0:29:30.15,0:29:36.39,Default,,0000,0000,0000,,can ask all kinds of questions and\Nobjectives, even those that we still don't
Dialogue: 0,0:29:36.39,0:29:47.01,Default,,0000,0000,0000,,know. We can develop all kinds of\Napplications which is done for humans.
Dialogue: 0,0:29:47.01,0:29:59.40,Default,,0000,0000,0000,,Currently, there are at least four global\Ndatasets on human diversity. These are
Dialogue: 0,0:29:59.40,0:30:08.86,Default,,0000,0000,0000,,very widely reused and these big datasets\N- so they are big data with regard to the
Dialogue: 0,0:30:08.86,0:30:18.85,Default,,0000,0000,0000,,number of samples and also the genomes or\Nthe genome representations and this
Dialogue: 0,0:30:18.85,0:30:26.47,Default,,0000,0000,0000,,results in very information rich data\Nwhich initiates analytical development so
Dialogue: 0,0:30:26.47,0:30:33.80,Default,,0000,0000,0000,,people continuously are developing new\Nstatistical methods. And right now, a new
Dialogue: 0,0:30:33.80,0:30:42.33,Default,,0000,0000,0000,,wave is coming in of these methods. So\Nonce you have these global datasets,
Dialogue: 0,0:30:42.33,0:30:47.50,Default,,0000,0000,0000,,people start in human populations\Ngenomics, started to do these intense
Dialogue: 0,0:30:47.50,0:30:56.30,Default,,0000,0000,0000,,regional samplings. And this is the\Nexample of the United Kingdom Biobank.
Dialogue: 0,0:30:56.30,0:31:02.79,Default,,0000,0000,0000,,It's a project with 500.000 volunteers,\Nthey are all UK citizens from all over the
Dialogue: 0,0:31:02.79,0:31:13.98,Default,,0000,0000,0000,,islands. And each individual was genotyped\Nin a vet lab for 820.000 markers. That's
Dialogue: 0,0:31:13.98,0:31:19.62,Default,,0000,0000,0000,,completely I mean, that's a different\Nnumber than the 100 or 1000...in
Dialogue: 0,0:31:19.62,0:31:26.41,Default,,0000,0000,0000,,biodiversity scientists we normally\Nanalyse a maximum of a couple of 10.000
Dialogue: 0,0:31:26.41,0:31:36.22,Default,,0000,0000,0000,,markers. So that's a completely different\Nnumber. But then statistical geneticists
Dialogue: 0,0:31:36.22,0:31:47.14,Default,,0000,0000,0000,,come. They do some weird and wonderful\Nvoodoo and they derive 96 million markers
Dialogue: 0,0:31:47.14,0:31:53.46,Default,,0000,0000,0000,,per genome that is per individual from\Nthese 820.000 markers that were produced
Dialogue: 0,0:31:53.46,0:32:00.63,Default,,0000,0000,0000,,in the lab. So that's a hundred fold\Nincrease. And once you have this kind of
Dialogue: 0,0:32:00.63,0:32:07.51,Default,,0000,0000,0000,,dataset for a genome, you suddenly or you\Nfinally become country level and within
Dialogue: 0,0:32:07.51,0:32:18.97,Default,,0000,0000,0000,,country level resolution. So these panels\Nare examples. So the first panel shows
Dialogue: 0,0:32:18.97,0:32:25.98,Default,,0000,0000,0000,,individuals who were born in Edinburgh and\Nthe question was "Where were people born
Dialogue: 0,0:32:25.98,0:32:32.42,Default,,0000,0000,0000,,who had a similar ancestral background,\Ngenetic background?". And what they found
Dialogue: 0,0:32:32.42,0:32:41.98,Default,,0000,0000,0000,,was that was all over Scotland and\NNorthern Ireland. Northern Yorkshire was
Dialogue: 0,0:32:41.98,0:32:50.25,Default,,0000,0000,0000,,even more local. So people from Yorkshire\Ndon't seem to get around a lot. For London
Dialogue: 0,0:32:50.25,0:32:54.09,Default,,0000,0000,0000,,the situation is completely different.\NThat is what we would expect because
Dialogue: 0,0:32:54.09,0:32:59.58,Default,,0000,0000,0000,,London is a people magnet. People move\Nthere all the time. They meet there, they
Dialogue: 0,0:32:59.58,0:33:05.70,Default,,0000,0000,0000,,get children and the kids born in London,\Ntheir genetic ancestry has nothing to do
Dialogue: 0,0:33:05.70,0:33:12.76,Default,,0000,0000,0000,,with London. It's from all over the place,\Nfrom the British Isles and the world. So
Dialogue: 0,0:33:12.76,0:33:21.60,Default,,0000,0000,0000,,that's why the colors are strongly\Ndissolved. So this study came out also
Dialogue: 0,0:33:21.60,0:33:26.10,Default,,0000,0000,0000,,this summer. And it's the first time that\NI have seen that we actually really can
Dialogue: 0,0:33:26.10,0:33:36.58,Default,,0000,0000,0000,,achieve regional resolution. And I find\Nthis possibility for biodiversity science
Dialogue: 0,0:33:36.58,0:33:46.82,Default,,0000,0000,0000,,really exciting. So it was made possible\Nby very sophisticated statistical
Dialogue: 0,0:33:46.82,0:33:51.89,Default,,0000,0000,0000,,approaches which are able to analyze\Ngenetic data from highly complex
Dialogue: 0,0:33:51.89,0:33:59.45,Default,,0000,0000,0000,,evolutionary and ecological systems. And\Nat the same time these analyses are able
Dialogue: 0,0:33:59.45,0:34:04.91,Default,,0000,0000,0000,,to handle big data. We we're talking about\Ngigabytes and terabytes of data and
Dialogue: 0,0:34:04.91,0:34:13.81,Default,,0000,0000,0000,,results. So a statistical geneticist are\Ndeveloping new methods of data
Dialogue: 0,0:34:13.81,0:34:20.31,Default,,0000,0000,0000,,representation to handle this amount of\Ndata. And then we are able to sufficiently
Dialogue: 0,0:34:20.31,0:34:25.52,Default,,0000,0000,0000,,extract the signal for a very specific\Nquestion from data which are very low
Dialogue: 0,0:34:25.52,0:34:36.92,Default,,0000,0000,0000,,signal to noise ratio. So to get there, we\Nneed many experts and specialists. So we
Dialogue: 0,0:34:36.92,0:34:41.66,Default,,0000,0000,0000,,need statistical geneticists, big data\Nexperts who also might contribute machine
Dialogue: 0,0:34:41.66,0:34:49.30,Default,,0000,0000,0000,,learning expertise. We need molecular\Nbiologists who know how to sequence
Dialogue: 0,0:34:49.30,0:34:54.26,Default,,0000,0000,0000,,complex genomes. We now need\Nbioinformatics with an expertise in
Dialogue: 0,0:34:54.26,0:35:05.01,Default,,0000,0000,0000,,genomics for assembly, annotation and\Nalignment of genomic sequences. The result
Dialogue: 0,0:35:05.01,0:35:12.57,Default,,0000,0000,0000,,is actually this: This is the author list\Nfor the thousands genomes project
Dialogue: 0,0:35:12.57,0:35:20.38,Default,,0000,0000,0000,,reference data set, and I don't expect you\Nto be able to read it, but the bold type
Dialogue: 0,0:35:20.38,0:35:25.54,Default,,0000,0000,0000,,is of interest because it shows all the\Ndifferent tasks that are necessary to
Dialogue: 0,0:35:25.54,0:35:36.14,Default,,0000,0000,0000,,produce a standardized and highly cleaned\Nreverence dataset. So the whole author
Dialogue: 0,0:35:36.14,0:35:41.88,Default,,0000,0000,0000,,list is something like 1.5 pages long and\Neven considering that some authors will
Dialogue: 0,0:35:41.88,0:35:51.13,Default,,0000,0000,0000,,have contributed to several tasks. The\Npublications for reference datasets mostly
Dialogue: 0,0:35:51.13,0:35:57.08,Default,,0000,0000,0000,,have author lists that are far over 50\Npeople. So they are huge collaborative
Dialogue: 0,0:35:57.08,0:36:05.22,Default,,0000,0000,0000,,efforts. Now we take the step into\Nbiodiversity science. Here these are eight
Dialogue: 0,0:36:05.22,0:36:13.44,Default,,0000,0000,0000,,gastrotrichs, they are little worm like...\Norganisms who live in the sediments of
Dialogue: 0,0:36:13.44,0:36:23.07,Default,,0000,0000,0000,,freshwater lakes and marine sediment. They\Nare in general a couple of hundreds micro
Dialogue: 0,0:36:23.07,0:36:29.57,Default,,0000,0000,0000,,meters large. And I don't have any\Nnumbers, but my guess would be that maybe
Dialogue: 0,0:36:29.57,0:36:38.64,Default,,0000,0000,0000,,worldwide, a hundred to a thousand people\Nactually work on these species. There are
Dialogue: 0,0:36:38.64,0:36:44.83,Default,,0000,0000,0000,,800 species of gastrotrichs. So let's say\Nthere's one, two, maybe three experts per
Dialogue: 0,0:36:44.83,0:36:52.24,Default,,0000,0000,0000,,species for these organisms. So how are\Nthese three people going to manage all
Dialogue: 0,0:36:52.24,0:37:01.42,Default,,0000,0000,0000,,these tasks to produce a reference\Ndataset? You might say, well, it's
Dialogue: 0,0:37:01.42,0:37:05.21,Default,,0000,0000,0000,,gastrotrichs, I mean, have never heard\Nabout them. Maybe they are not so
Dialogue: 0,0:37:05.21,0:37:08.35,Default,,0000,0000,0000,,important. Maybe you don't need a\Nreference data sets, but actually some of
Dialogue: 0,0:37:08.35,0:37:17.58,Default,,0000,0000,0000,,those species are bioindicators for water\Nquality. So what we observe right now is a
Dialogue: 0,0:37:17.58,0:37:27.51,Default,,0000,0000,0000,,gap for biodiversity conservation. In\Nmodel organisms, we have Pandora's Box
Dialogue: 0,0:37:27.51,0:37:34.63,Default,,0000,0000,0000,,open. We have all the statistical analyses\Nat our hands to analyze our data sets.
Dialogue: 0,0:37:34.63,0:37:39.71,Default,,0000,0000,0000,,However, in none model organisms, we are\Nstill stuck with summary statistics that
Dialogue: 0,0:37:39.71,0:37:46.84,Default,,0000,0000,0000,,don't provide us the resolution that we\Nneed. And we know that to close this gap,
Dialogue: 0,0:37:46.84,0:37:52.60,Default,,0000,0000,0000,,even for a single species, it's a huge\Neffort. But at the same time, we have over
Dialogue: 0,0:37:52.60,0:38:03.56,Default,,0000,0000,0000,,35.000 species listed by scientists which\Nneed already now effective protection. So
Dialogue: 0,0:38:03.56,0:38:10.01,Default,,0000,0000,0000,,we need to find a way to close this gap\Nand actually move in this direction. And
Dialogue: 0,0:38:10.01,0:38:19.94,Default,,0000,0000,0000,,the good thing is, so all of this... in\Nbiodiversity science, in academia, and we
Dialogue: 0,0:38:19.94,0:38:24.89,Default,,0000,0000,0000,,need to make the transition over the\Nconservational genomic gap into the big
Dialogue: 0,0:38:24.89,0:38:32.13,Default,,0000,0000,0000,,loop of real world conservation tasks. And\Nthe good thing is we already know what we
Dialogue: 0,0:38:32.13,0:38:37.94,Default,,0000,0000,0000,,have to do. So we need to have reference\Ndata sets, distribution range wide. We
Dialogue: 0,0:38:37.94,0:38:43.96,Default,,0000,0000,0000,,need to have statistics. And it's going to\Nbe big data. So we need collection
Dialogue: 0,0:38:43.96,0:38:54.14,Default,,0000,0000,0000,,management, data management and an\Nanalysis environment. So looking at
Dialogue: 0,0:38:54.14,0:38:59.88,Default,,0000,0000,0000,,different ingredients or different steps\Nthe first we need is a general data
Dialogue: 0,0:38:59.88,0:39:05.27,Default,,0000,0000,0000,,infrastructure for global diversity of\Nreference data sets that actually can be
Dialogue: 0,0:39:05.27,0:39:11.78,Default,,0000,0000,0000,,used across species for preferably as many\Nspecies as possible and provide a working
Dialogue: 0,0:39:11.78,0:39:19.75,Default,,0000,0000,0000,,environment for biodiversity scientists\Nand experts. It should be user friendly so
Dialogue: 0,0:39:19.75,0:39:25.76,Default,,0000,0000,0000,,it can be used by scientists, but also\Nthat people from local communities and
Dialogue: 0,0:39:25.76,0:39:33.49,Default,,0000,0000,0000,,citizen scientists can add their\Nobservation data and their data into this
Dialogue: 0,0:39:33.49,0:39:41.34,Default,,0000,0000,0000,,data infrastructure. I have listed quite a\Nlot of features that these kind of
Dialogue: 0,0:39:41.34,0:39:48.40,Default,,0000,0000,0000,,infrastructures should have. And I'm going\Nto argue that these features are not some
Dialogue: 0,0:39:48.40,0:40:02.61,Default,,0000,0000,0000,,nice to have, but actually some must have.\NBecause our goal is always application. So
Dialogue: 0,0:40:02.61,0:40:13.28,Default,,0000,0000,0000,,we need developers, managers and curators\Nfor data infrastructures. Since our goal
Dialogue: 0,0:40:13.28,0:40:30.90,Default,,0000,0000,0000,,is application, our main features are\Nquality control and error reduction. These
Dialogue: 0,0:40:30.90,0:40:38.88,Default,,0000,0000,0000,,are the basis. So that our conservation\Ntools can be robustly and reliably applied
Dialogue: 0,0:40:38.88,0:40:46.46,Default,,0000,0000,0000,,under real world operating conditions. And\Nthe way to achieve quality and error
Dialogue: 0,0:40:46.46,0:40:52.76,Default,,0000,0000,0000,,reduction is through chains of custody. So\Nit means that from project of sign, from
Dialogue: 0,0:40:52.76,0:40:58.30,Default,,0000,0000,0000,,the questions through all the steps that\Nare necessary to produce a reference data
Dialogue: 0,0:40:58.30,0:41:08.22,Default,,0000,0000,0000,,set and then...so from sample collection,\Ngenomic statistical analysis down to
Dialogue: 0,0:41:08.22,0:41:15.60,Default,,0000,0000,0000,,application. These steps need to be\Ndocumented and standardized. They need to
Dialogue: 0,0:41:15.60,0:41:22.24,Default,,0000,0000,0000,,be, each one of them needs to be validated\Nand reproducible. They should be modular
Dialogue: 0,0:41:22.24,0:41:28.100,Default,,0000,0000,0000,,so they can be user friendly. And the\Nwhole chain of custody needs to be
Dialogue: 0,0:41:28.100,0:41:40.69,Default,,0000,0000,0000,,scalable. So if our chains of custody have\Nthese characteristics, we actually will
Dialogue: 0,0:41:40.69,0:41:51.39,Default,,0000,0000,0000,,have tools that will work in everyday\Nlife. So we need professional developers
Dialogue: 0,0:41:51.39,0:41:59.52,Default,,0000,0000,0000,,and programmers who are able to produce\Nthese very collaborative softwares. We
Dialogue: 0,0:41:59.52,0:42:06.13,Default,,0000,0000,0000,,need free and open source experts. So we\Nalways can ensure that our code and that
Dialogue: 0,0:42:06.13,0:42:13.86,Default,,0000,0000,0000,,our infrastructures are still integer and\Nwe can check them. And I'm a biologist, I
Dialogue: 0,0:42:13.86,0:42:19.39,Default,,0000,0000,0000,,don't have any background in hardware, but\NI've heard a couple of talks here in the
Dialogue: 0,0:42:19.39,0:42:26.10,Default,,0000,0000,0000,,conference about Green IT. And I have\Nthe feeling we should have people who know
Dialogue: 0,0:42:26.10,0:42:33.85,Default,,0000,0000,0000,,hardware and software and know how to\Ndevelop these high tech tools in a way
Dialogue: 0,0:42:33.85,0:42:38.45,Default,,0000,0000,0000,,sustainable so that by developing these\Ntools, we don't use more resources than we
Dialogue: 0,0:42:38.45,0:42:48.94,Default,,0000,0000,0000,,are trying to protect. So I've shown all\Nthese features and characteristics that
Dialogue: 0,0:42:48.94,0:42:57.46,Default,,0000,0000,0000,,the software should have. And I'm arguing\Nthat these features are necessary because
Dialogue: 0,0:42:57.46,0:43:04.82,Default,,0000,0000,0000,,of the reality we find us in. It is one of\Nrising over-exploitation and destruction
Dialogue: 0,0:43:04.82,0:43:19.80,Default,,0000,0000,0000,,of nature. So the extent of environmental\Ncrimes is up in the billions. All
Dialogue: 0,0:43:19.80,0:43:29.03,Default,,0000,0000,0000,,environmental crime together, the green\Nbubbles are only second to drug associated
Dialogue: 0,0:43:29.03,0:43:35.49,Default,,0000,0000,0000,,crimes. They are up there with\Ncounterfeiting or human trafficing. So
Dialogue: 0,0:43:35.49,0:43:45.48,Default,,0000,0000,0000,,these are multi-billion enterprises. They\Nare often transnational and industries
Dialogue: 0,0:43:45.48,0:44:02.02,Default,,0000,0000,0000,,with huge profits. So if there's some\Ncrime, some mafia boss, some criminal
Dialogue: 0,0:44:02.02,0:44:09.54,Default,,0000,0000,0000,,manager who just bribed a government\Nofficial somewhere in the neck in the
Dialogue: 0,0:44:09.54,0:44:17.86,Default,,0000,0000,0000,,woods, it just would make sense that that\Nperson would not wait or not take the
Dialogue: 0,0:44:17.86,0:44:23.81,Default,,0000,0000,0000,,risks to be discovered just because some\Ncustoms officer pulls out a container
Dialogue: 0,0:44:23.81,0:44:29.17,Default,,0000,0000,0000,,somewhere in the harbor, for example,\Nopens it and says "This looks kind of
Dialogue: 0,0:44:29.17,0:44:37.38,Default,,0000,0000,0000,,weird. Let's take a sample, send it to a\Nlab." and then a population geneticist
Dialogue: 0,0:44:37.38,0:44:44.17,Default,,0000,0000,0000,,comes back and says "Oh, yes, this sample\Nis not from area A as documented, but
Dialogue: 0,0:44:44.17,0:44:52.45,Default,,0000,0000,0000,,actually it's from area B and it was\Nillegally logged." If we have reference
Dialogue: 0,0:44:52.45,0:44:58.66,Default,,0000,0000,0000,,data sets, information rich reference data\Nsets, they become highly valuable and they
Dialogue: 0,0:44:58.66,0:45:08.43,Default,,0000,0000,0000,,need protection themselves against\Nmanipulation and destruction. So we will
Dialogue: 0,0:45:08.43,0:45:14.74,Default,,0000,0000,0000,,need to think about IT security from the\Nbeginning. Also, these data sets are often
Dialogue: 0,0:45:14.74,0:45:20.07,Default,,0000,0000,0000,,very politically sensitive because if it\Nis shown that in a certain country there
Dialogue: 0,0:45:20.07,0:45:25.68,Default,,0000,0000,0000,,is the illegal logging repeatedly, that\Ncountry might not be too excited about
Dialogue: 0,0:45:25.68,0:45:41.38,Default,,0000,0000,0000,,this information. So we need to think\Nabout IT security experts. So my hope is
Dialogue: 0,0:45:41.38,0:45:48.60,Default,,0000,0000,0000,,that these kind of very high tech digital\Nconservation tools can actually contribute
Dialogue: 0,0:45:48.60,0:45:55.69,Default,,0000,0000,0000,,to the U.N. Sustainable Development Goals\Nby empowering indigenous people, local
Dialogue: 0,0:45:55.69,0:46:02.81,Default,,0000,0000,0000,,communities and also us to protect and\Nforce and sustainably use our lands and
Dialogue: 0,0:46:02.81,0:46:10.14,Default,,0000,0000,0000,,our biodiversity by providing some\Nmanagement and law enforcement tools. So
Dialogue: 0,0:46:10.14,0:46:14.06,Default,,0000,0000,0000,,we need people from around the world,\Nusers from around the world who use these
Dialogue: 0,0:46:14.06,0:46:25.79,Default,,0000,0000,0000,,tools and help to develop them further and\Nto maintain them. And finally here, these
Dialogue: 0,0:46:25.79,0:46:33.91,Default,,0000,0000,0000,,high tech tools will just another\Ntechnological fix. If we don't manage to
Dialogue: 0,0:46:33.91,0:46:45.77,Default,,0000,0000,0000,,get our back down, our way of life down to\Nsustainable levels. So what we need is to
Dialogue: 0,0:46:45.77,0:46:53.76,Default,,0000,0000,0000,,today...this year, the Earth Overshoot Day\Nwas at the end of July. So at the end of
Dialogue: 0,0:46:53.76,0:47:01.64,Default,,0000,0000,0000,,July, we had used all the resources that\Nwe had available for the whole year. And
Dialogue: 0,0:47:01.64,0:47:09.40,Default,,0000,0000,0000,,we need to get this back to the end of the\Nyear so that our resources actually
Dialogue: 0,0:47:09.40,0:47:22.91,Default,,0000,0000,0000,,sustain us for the whole year. The graphic\Nhere for Germany suggests that we are on a
Dialogue: 0,0:47:22.91,0:47:29.82,Default,,0000,0000,0000,,good way. We are reducing our resource\Nconsumption and maybe even our biocapacity
Dialogue: 0,0:47:29.82,0:47:38.10,Default,,0000,0000,0000,,moves up a little bit. So actually it\Nseems that our personal lifestyles and
Dialogue: 0,0:47:38.10,0:47:46.33,Default,,0000,0000,0000,,choices make a difference and we just need\Nto close this gap here much quicker. So
Dialogue: 0,0:47:46.33,0:47:53.69,Default,,0000,0000,0000,,protecting biodiversity needs all of us to\Nachieve that. And with that, thank you
Dialogue: 0,0:47:53.69,0:47:57.77,Default,,0000,0000,0000,,very much.
Dialogue: 0,0:47:57.77,0:48:08.02,Default,,0000,0000,0000,,{\i1}Applause{\i0}
Dialogue: 0,0:48:08.02,0:48:12.68,Default,,0000,0000,0000,,Angel: So thank you Jutta for this very\Ninteresting talk and the very valuable
Dialogue: 0,0:48:12.68,0:48:16.61,Default,,0000,0000,0000,,work you're doing. We have three mics\Nhere. Please line up at the microphones if
Dialogue: 0,0:48:16.61,0:48:22.81,Default,,0000,0000,0000,,you have any questions or suggestions or\Nwant to participate and work together with
Dialogue: 0,0:48:22.81,0:48:29.66,Default,,0000,0000,0000,,Jutta. We have one question from the\NInternet, so please Signal-Angel start.
Dialogue: 0,0:48:29.66,0:48:34.75,Default,,0000,0000,0000,,Signal-Angel: Why do wild plant species\Nwithin a genus are further apart than wild
Dialogue: 0,0:48:34.75,0:48:42.51,Default,,0000,0000,0000,,animal species within a genus?\NAngel: Could you repeat it, please?
Dialogue: 0,0:48:42.51,0:48:49.07,Default,,0000,0000,0000,,Signal-Angel: Why do wild plant species\Nwithin a genus are further apart than wild
Dialogue: 0,0:48:49.07,0:48:55.91,Default,,0000,0000,0000,,animal species within a genus?\NJutta: I'm not sure I understand the
Dialogue: 0,0:48:55.91,0:49:01.18,Default,,0000,0000,0000,,background for the question.\NMic 1: Because animals move and plants
Dialogue: 0,0:49:01.18,0:49:06.45,Default,,0000,0000,0000,,don't move.\NJutta: Oh, okay. If that is the idea
Dialogue: 0,0:49:06.45,0:49:12.30,Default,,0000,0000,0000,,behind the question. Plants actually move,\Ntoo. They don't move as individuals, but
Dialogue: 0,0:49:12.30,0:49:24.29,Default,,0000,0000,0000,,they move their genetic material through\Npollen or fragments. So actually diversity
Dialogue: 0,0:49:24.29,0:49:30.76,Default,,0000,0000,0000,,in plants and in animals can be quite\Nsimilar. So the idea is that plants are
Dialogue: 0,0:49:30.76,0:49:36.46,Default,,0000,0000,0000,,just stuck and should have a completely\Ndifferent population structure does not
Dialogue: 0,0:49:36.46,0:49:43.13,Default,,0000,0000,0000,,hold because plants move around their\Ngenetic material through seeds, through
Dialogue: 0,0:49:43.13,0:49:49.61,Default,,0000,0000,0000,,pollen, through vegetative propagules.\NAngel: So thank you microphone 1 for
Dialogue: 0,0:49:49.61,0:49:55.100,Default,,0000,0000,0000,,helping out. Please ask your question. Mic\N1: So my question is about the success
Dialogue: 0,0:49:55.100,0:50:00.94,Default,,0000,0000,0000,,factor of it. If you think of this,\Nwhatever database being set up there and I
Dialogue: 0,0:50:00.94,0:50:07.43,Default,,0000,0000,0000,,think it's gonna be a huge database...I\Ndownloaded my own genome on the Internet.
Dialogue: 0,0:50:07.43,0:50:12.99,Default,,0000,0000,0000,,It was about 150 megabytes. And if we\Nmultiply that, I think the genetic
Dialogue: 0,0:50:12.99,0:50:17.54,Default,,0000,0000,0000,,variation from one person to another is\Nabout 1 percent only. So we can compress
Dialogue: 0,0:50:17.54,0:50:25.01,Default,,0000,0000,0000,,that to 4 megabytes per person. If we\Nsequence all the humans in the world, that
Dialogue: 0,0:50:25.01,0:50:32.69,Default,,0000,0000,0000,,would be 32 petabytes, that would cost\Napproximately 15 billion dollars. And
Dialogue: 0,0:50:32.69,0:50:36.89,Default,,0000,0000,0000,,that's only for the storage. Now comes the\Nentire management. Of course, we don't
Dialogue: 0,0:50:36.89,0:50:41.47,Default,,0000,0000,0000,,want to digitize all the human genome, but\Nrather the plants and animal species
Dialogue: 0,0:50:41.47,0:50:46.31,Default,,0000,0000,0000,,genome. So it's a huge data program. And\Nwhat would be for you the success factors
Dialogue: 0,0:50:46.31,0:50:51.23,Default,,0000,0000,0000,,for this thing to really fly? And did you\Ntalk to organizations like WikiData or
Dialogue: 0,0:50:51.23,0:50:56.47,Default,,0000,0000,0000,,others or where would it ideally be\Nhosted? At a university or an
Dialogue: 0,0:50:56.47,0:51:02.17,Default,,0000,0000,0000,,international nonprofit or who would be\Nrunning the thing?
Dialogue: 0,0:51:02.17,0:51:14.52,Default,,0000,0000,0000,,Jutta: Yeah, I mean, it's just really big\Ndata. I think our first goal is not to
Dialogue: 0,0:51:14.52,0:51:23.67,Default,,0000,0000,0000,,think about having all predicted 5 to 10\Nmillion species be sequenced on a
Dialogue: 0,0:51:23.67,0:51:30.24,Default,,0000,0000,0000,,population level. I think we need to think\Nabout the next step. And there it would
Dialogue: 0,0:51:30.24,0:51:35.53,Default,,0000,0000,0000,,make sense to start with species that are\Nactually highly exploited, like many
Dialogue: 0,0:51:35.53,0:51:40.58,Default,,0000,0000,0000,,timber species and also many marine\Nfishes. I think that's where we should
Dialogue: 0,0:51:40.58,0:51:48.04,Default,,0000,0000,0000,,start. And to host this kind of data I\Nthink it should be in political
Dialogue: 0,0:51:48.04,0:51:56.41,Default,,0000,0000,0000,,independent hands. So it should be with an\NNGO or with the U.N., some organization
Dialogue: 0,0:51:56.41,0:52:02.45,Default,,0000,0000,0000,,that is independent.\NMic 1: Are you the first to think about
Dialogue: 0,0:52:02.45,0:52:06.51,Default,,0000,0000,0000,,this or are there existing initiatives?\NJutta: There are actually existing
Dialogue: 0,0:52:06.51,0:52:14.22,Default,,0000,0000,0000,,initiatives. I have been in contact with\Nthe Forest Stewardship Council and they
Dialogue: 0,0:52:14.22,0:52:23.22,Default,,0000,0000,0000,,are actually starting to sample their\Nconcessions and initiated to build up the
Dialogue: 0,0:52:23.22,0:52:28.73,Default,,0000,0000,0000,,samples, they work together with Kew\NBotanical Gardens and the U.S. Forest
Dialogue: 0,0:52:28.73,0:52:37.59,Default,,0000,0000,0000,,Service. And right now they're analyzing\Nthe samples, using isotopes which is
Dialogue: 0,0:52:37.59,0:52:45.58,Default,,0000,0000,0000,,another method which is very powerful and\Ncan also produce geographic information.
Dialogue: 0,0:52:45.58,0:53:00.71,Default,,0000,0000,0000,,And so, yeah, so people are moving in this\Nway. So, yeah, I think the idea is out
Dialogue: 0,0:53:00.71,0:53:05.84,Default,,0000,0000,0000,,there, just we have to start and we have\Nto really do it and provide one
Dialogue: 0,0:53:05.84,0:53:13.21,Default,,0000,0000,0000,,infrastructure so that we can combine, for\Nexample, morphological data, isotope data
Dialogue: 0,0:53:13.21,0:53:18.33,Default,,0000,0000,0000,,and genomic data into one dataset, which\Nwill increase our resolution and our
Dialogue: 0,0:53:18.33,0:53:23.98,Default,,0000,0000,0000,,reliability.\NAngel: Okay. Microphone number two,
Dialogue: 0,0:53:23.98,0:53:27.07,Default,,0000,0000,0000,,please.\NMic 2: Thank you for your valuable talk.
Dialogue: 0,0:53:27.07,0:53:32.66,Default,,0000,0000,0000,,My question would be you'd start your talk\Nwith the possible decrease of leaf beetles
Dialogue: 0,0:53:32.66,0:53:37.10,Default,,0000,0000,0000,,in the data set you showed on slide number\Nsix there was an increase in leaf beetle
Dialogue: 0,0:53:37.10,0:53:41.93,Default,,0000,0000,0000,,population until the 70s, something about\Nthat. Is there a possible explanation for
Dialogue: 0,0:53:41.93,0:53:49.87,Default,,0000,0000,0000,,that?\NJutta: Yeah, I believe it is, because
Dialogue: 0,0:53:49.87,0:53:55.36,Default,,0000,0000,0000,,people started to much more systematically\Nobserve leaf beetles. So it's a sample
Dialogue: 0,0:53:55.36,0:54:05.87,Default,,0000,0000,0000,,effort. And also at that time the people -\Nso it's a multi-people collaboration who
Dialogue: 0,0:54:05.87,0:54:12.37,Default,,0000,0000,0000,,actually has assembled this dataset so the\Npeople who are part of this collaboration
Dialogue: 0,0:54:12.37,0:54:16.95,Default,,0000,0000,0000,,they edit their own private data sets. And\Nthat's why you have an increase I think.
Dialogue: 0,0:54:16.95,0:54:23.51,Default,,0000,0000,0000,,While the people from the nineteen\Nhundreds, nineteen hundred ten you only
Dialogue: 0,0:54:23.51,0:54:29.01,Default,,0000,0000,0000,,can use the data that is available in\Npublications and samples in museums or in
Dialogue: 0,0:54:29.01,0:54:33.29,Default,,0000,0000,0000,,scientific collections. I think that is\Nthe reason why you have the sharp
Dialogue: 0,0:54:33.29,0:54:35.59,Default,,0000,0000,0000,,increase.\NMic 2: Thank you.
Dialogue: 0,0:54:35.59,0:54:38.75,Default,,0000,0000,0000,,Angel: So we have another question of\Nmicrophone number two.
Dialogue: 0,0:54:38.75,0:54:44.46,Default,,0000,0000,0000,,Mic 2: Thank you for your fine talking.\NExcuse me. Maybe my question is a bit off
Dialogue: 0,0:54:44.46,0:54:51.73,Default,,0000,0000,0000,,topic. Do you think the methods and roles\Nthat you identified in your talk could be
Dialogue: 0,0:54:51.73,0:54:59.88,Default,,0000,0000,0000,,transferred to the assessment of raw\Nmaterials? I'm thinking about metals?
Dialogue: 0,0:54:59.88,0:55:09.35,Default,,0000,0000,0000,,Jutta: Maybe the data infrastructure, like\Nif you wanted to collect raw metals or
Dialogue: 0,0:55:09.35,0:55:16.47,Default,,0000,0000,0000,,materials from all over the world and...a\Nsampleized scientific collection and to
Dialogue: 0,0:55:16.47,0:55:22.39,Default,,0000,0000,0000,,have kind of a reference dataset that\Nmight work, actually. But the genomics
Dialogue: 0,0:55:22.39,0:55:29.17,Default,,0000,0000,0000,,obviously won't. So that part of what you\Nwould need to use different methods from
Dialogue: 0,0:55:29.17,0:55:36.01,Default,,0000,0000,0000,,physics, obviously. But actually the\Ninfrastructure, certain parts will be
Dialogue: 0,0:55:36.01,0:55:40.25,Default,,0000,0000,0000,,quite similar. I think so, yes.\NAngel: So we have one more question from
Dialogue: 0,0:55:40.25,0:55:43.42,Default,,0000,0000,0000,,the Internet.\NSignal-Angel: Who does contract a
Dialogue: 0,0:55:43.42,0:55:51.62,Default,,0000,0000,0000,,freelance evolutionary biologist? Can you\Ngive an example of this kind of work you
Dialogue: 0,0:55:51.62,0:56:01.43,Default,,0000,0000,0000,,proposed?\NJutta: So I see this gap between science
Dialogue: 0,0:56:01.43,0:56:07.74,Default,,0000,0000,0000,,and applications, that we need these\Napplications and there's a huge potential
Dialogue: 0,0:56:07.74,0:56:18.15,Default,,0000,0000,0000,,for these applications. We know that\Nillegal logging and that is my background,
Dialogue: 0,0:56:18.15,0:56:23.77,Default,,0000,0000,0000,,but doesn't seem to be much different, for\Nexample, in marine fisheries. We know that
Dialogue: 0,0:56:23.77,0:56:29.73,Default,,0000,0000,0000,,there is this huge amount of illegal\Nlogging and timber trade going on. And we
Dialogue: 0,0:56:29.73,0:56:39.67,Default,,0000,0000,0000,,need to have some assets actually that\Nhave the power to detect illegally traded
Dialogue: 0,0:56:39.67,0:56:49.79,Default,,0000,0000,0000,,timber. So I think there is a huge need\Nfor these kind of methods and
Dialogue: 0,0:56:49.79,0:57:00.87,Default,,0000,0000,0000,,organizations who are interested in these\Nkind of methods. Our governments, their
Dialogue: 0,0:57:00.87,0:57:12.72,Default,,0000,0000,0000,,companies, NGOs, customs, Interpol. So,\Nyeah.
Dialogue: 0,0:57:12.72,0:57:19.70,Default,,0000,0000,0000,,Angel: Do we have any other questions? So\Nthank you again Jutta for your talk and
Dialogue: 0,0:57:19.70,0:57:23.74,Default,,0000,0000,0000,,the valuable work you're doing. Please\Ngive a warm round of applause to Jutta.
Dialogue: 0,0:57:23.74,0:57:29.01,Default,,0000,0000,0000,,{\i1}Applause{\i0}
Dialogue: 0,0:57:29.01,0:57:33.60,Default,,0000,0000,0000,,{\i1}36c3 postrol music{\i0}
Dialogue: 0,0:57:33.60,0:57:56.00,Default,,0000,0000,0000,,Subtitles created by c3subtitles.de\Nin the year 2020. Join, and help us!