This session continues our introduction to evolution. Dr. Ramakrishnan studies how species are distributed across regions. She expands on the concept of speciation and explains why islands and mountain ranges are often regions of increased biodiversity. Dr. Tishkoff investigates the migration of hominids out of Africa and the evolution of modern humans. She defines many key concepts in evolution including genetic drift, neutral evolution, founder effect, and more. She explains how mitochondrial DNA can be used to study relatedness of humans and other populations. Dr. Hadly finishes with a short, clear, explanation of a genetic bottleneck.
All Course Materials for this Session (Educators only)
- Duration: 23:54
00:00:07.10 Hi, I'm Sarah Tishkoff.
00:00:08.23 I'm a professor at the University of Pennsylvania
00:00:11.02 in the Departments of Biology and Genetics,
00:00:13.24 and today I'm gonna tell you about my research
00:00:15.18 on African integrative genomics,
00:00:17.29 and implications for human origins and disease.
00:00:21.17 So in Part 1, I'm gonna tell you a bit about
00:00:23.24 human evolutionary history,
00:00:25.24 and what the implications are of that
00:00:27.20 on the patterns of genomic variation
00:00:29.18 that we see in populations today.
00:00:34.05 So I want to start by talking about some of the
00:00:35.26 key challenges in human genomics research.
00:00:38.19 And the first one is to characterize
00:00:40.27 the immense array of genomic and phenotypic diversity
00:00:44.29 across ethnically diverse human populations.
00:00:48.14 Secondly, to understand what the evolutionary processes are
00:00:51.16 that are generating and maintaining that variation.
00:00:54.14 And third, to better understand how
00:00:56.04 gene-gene, gene-protein, and gene-environment interactions
00:00:58.28 contribute to phenotypic variability.
00:01:01.27 So first let's start with the evolutionary history
00:01:05.00 of the hominin lineage
00:01:06.26 that's leading to modern humans,
00:01:10.13 which begins around the time that we
00:01:12.03 diverged from our closest genetic relative
00:01:14.04 the Chimpanzee,
00:01:15.18 sometime between 5-7 million years ago.
00:01:18.14 So shown here are some of the fossils
00:01:20.07 from the different species
00:01:22.17 preceding anatomically modern humans.
00:01:25.16 In blue are shown fossils from the oldest lineages,
00:01:30.06 and in fact one of the oldest is Sahelanthropus,
00:01:34.10 which has been dated to at least 7 million years ago,
00:01:37.29 and there's some debate about whether it even
00:01:39.14 belongs on the hominid lineage
00:01:41.09 or if it actually preceded the Chimpanzee and human divergence.
00:01:45.26 After that, in green,
00:01:47.14 we see the Australopithecus genus.
00:01:50.14 In yellow, we see Paranthropus genus.
00:01:54.09 In orange, we have the genus Homo
00:01:56.24 and the species proceeding anatomically modern humans
00:02:01.13 is Homo erectus, dated to about 2 million years ago.
00:02:06.14 And then we have the origins of
00:02:08.15 Homo neanderthalensis
00:02:11.02 and of anatomically modern humans.
00:02:13.24 Neanderthals are thought to have originated
00:02:16.00 somewhere between 300,000-400,000 years ago,
00:02:19.12 and modern humans originated
00:02:20.27 approximately 200,000 years ago.
00:02:24.03 Here's one of the best examples
00:02:26.11 of Australopithecus afarensis.
00:02:29.07 This was a set of fossils that was
00:02:31.24 discovered in the 1970's by Johanson and Gray,
00:02:36.02 named Lucy,
00:02:38.00 and Lucy was about...
00:02:41.04 she lived about 3.2 million years ago.
00:02:43.29 She was very small, only about 3 feet tall,
00:02:46.13 she had a very small brain,
00:02:48.07 and she was bipedal.
00:02:49.27 And being bipedal, in fact,
00:02:51.07 is one of the characteristics of the hominin lineage.
00:02:57.12 And, interestingly,
00:02:59.17 there have been some fossilized footprints
00:03:01.21 identified in Tanzania,
00:03:03.24 and we can see from these that there
00:03:06.08 appears to have been a mother,
00:03:08.27 from the species Australopithecus afarensis,
00:03:12.08 and she was holding the hands of her child.
00:03:14.29 And they must have been walking
00:03:16.15 in ash from recent volcanic activity,
00:03:20.06 and then that ash hardened and preserved these footprints
00:03:23.06 so that we can see them today,
00:03:24.21 and we can clearly see that they were bipedal.
00:03:29.08 So the species preceding modern humans
00:03:31.28 is called Homo erectus.
00:03:33.24 Homo erectus evolved around 2 million years ago,
00:03:39.02 and then after the origin of Homo erectus in Africa,
00:03:42.24 Homo erectus spread across Eurasia
00:03:47.17 and, indeed, shown here are some of the
00:03:49.21 oldest fossils of Homo erectus,
00:03:52.18 dated to as early as 1.9 million years ago (MYA) in Indonesia.
00:04:00.15 And this species was very successful,
00:04:03.14 lasting to as recently as 25,000 years ago
00:04:06.17 in Southeast Asia.
00:04:09.08 A very interesting recent finding was
00:04:11.20 a set of fossils identified on the island of Flores,
00:04:14.26 which is within Indonesia,
00:04:17.25 and these fossils actually show some characteristics
00:04:21.22 that look very similar to Homo erectus,
00:04:24.19 and for that reason it was proposed that
00:04:27.09 this species may have directly evolved
00:04:30.23 from a Homo erectus ancestor
00:04:33.20 that arrived on that island
00:04:36.07 about 1 million years ago
00:04:37.28 and then evolved in isolation.
00:04:39.25 And two of the very unique features of this species
00:04:42.17 is that they were very short, so again,
00:04:46.01 about the same size as Lucy, around 3 feet tall,
00:04:50.15 and secondly, that they had tiny brains.
00:04:53.14 And there's been a lot of debate about
00:04:55.01 whether this is an adaptation or in fact a pathology,
00:04:58.09 and there's still a lot of research being done,
00:05:01.03 but what was clear is that there were multiple species
00:05:04.01 outside of Africa
00:05:05.29 within the past 2 million years.
00:05:08.20 So now let's move on to the origins of
00:05:10.15 Homo neanderthalensis and Homo sapiens.
00:05:13.12 There's some question about the species preceding
00:05:16.28 Neanderthal and Homo sapiens.
00:05:19.17 Some say that it was heidelbergensis,
00:05:22.04 but there's debate about that.
00:05:24.15 However, what is clear is that the Neanderthals species
00:05:28.10 arose somewhere within the past 300,000-400,000 years,
00:05:32.15 and Homo sapiens arose within the past 200,000 years.
00:05:38.04 And this is a fossil from Neanderthals,
00:05:40.29 we can see a few features such as
00:05:44.02 the double arched and very wide brow ridges,
00:05:47.08 a broad nose,
00:05:48.28 a very large brain size,
00:05:50.27 and a retromolar space,
00:05:52.21 and in fact these species were very robust.
00:05:55.16 The males would have been over 6 feet tall,
00:05:57.15 they had very big bones,
00:05:59.19 and they had rather big brains.
00:06:02.20 In fact, here are some reconstructions of Neanderthal.
00:06:06.28 We have the old reconstruction
00:06:09.03 and then the more recent one as well.
00:06:12.11 So, anatomically modern humans, Homo sapiens sapiens,
00:06:16.06 arose approximately 200,000 years ago.
00:06:19.02 In fact, here these red dots
00:06:21.09 are representing locations where fossils have been found
00:06:24.11 of anatomically modern humans,
00:06:26.27 and the oldest fossil is
00:06:28.22 dated to around 150,000-195,000 years ago,
00:06:32.19 in Southern Ethiopia.
00:06:36.23 We also see evidence of early modern human behavior
00:06:40.10 dated to 70,000 years ago,
00:06:42.11 or even as old as 120,000 years ago,
00:06:45.16 in caves in south Africa
00:06:47.13 and also some from east Africa as well.
00:06:51.05 So after modern humans arose in Africa within the past 200,000 years,
00:06:55.08 one or a few small groups of individuals
00:06:57.25 migrated across the rest of the globe
00:07:00.11 within the past 50,000-100,000 years.
00:07:03.23 Indeed, we think that Europeans...
00:07:07.15 there were no people in Europe, actually,
00:07:09.06 until about 40,000 years ago,
00:07:11.13 and then modern humans crossed the Bering Straits
00:07:14.15 and went into the Americas
00:07:16.28 within the past 30,000 years.
00:07:19.05 The earliest migration event was actually into Australo-Melanesia,
00:07:23.11 dated to about 40,000-60,000 years ago.
00:07:26.14 And then we have much more recent migration events,
00:07:29.03 such as into the Pacific Islands,
00:07:31.12 within the past few thousand years.
00:07:34.11 Now, interestingly,
00:07:36.16 when modern humans migrated out of Africa
00:07:39.08 within the past 50,000-100,000 years,
00:07:42.05 they would have run into Neanderthals,
00:07:44.10 in fact they overlapped in their distribution.
00:07:47.08 So shown here is the distribution of Neanderthals,
00:07:50.22 and the modern humans who lived at that time
00:07:52.25 were referred to as Cro-Magnon,
00:07:55.17 and in fact we did not see anatomically modern humans
00:07:59.09 in this region, in Europe, until about 40,000 years ago.
00:08:03.03 They would have been in the Middle East a little bit earlier,
00:08:05.23 but it appears they overlapped
00:08:08.18 for about at least 10,000 years with Neanderthals.
00:08:12.13 And as we'll discuss later,
00:08:13.27 there is some evidence that there could have been actual admixture
00:08:17.05 between Neanderthal and anatomically modern humans
00:08:20.18 during that time.
00:08:22.26 So now I want to discuss the evolutionary forces
00:08:25.27 that influence the patterns of genetic variation
00:08:28.08 that we see today.
00:08:30.04 And these include mutation,
00:08:32.14 genetic drift,
00:08:35.09 and natural selection.
00:08:37.16 So let's first introduce some terminology.
00:08:40.05 The gene pool refers to the set of all genomes
00:08:42.25 in a specified population,
00:08:44.10 and here we have an example from a population of warthogs.
00:08:47.22 So where we have at a single genetic locus
00:08:51.03 two alleles, big B or little b,
00:08:54.17 and here's an example of an individual
00:08:56.11 who is homozygous for the big B allele,
00:08:59.07 and an individual homozygous for the little b allele,
00:09:02.12 and here's an individual who is heterozygous
00:09:05.08 for big B and little b.
00:09:07.12 And together, the set of alleles in that population
00:09:10.19 represents the gene pool.
00:09:13.28 So when we are doing population genetics analyses,
00:09:16.25 we can't actually go out and look at every genotype
00:09:21.00 for every individual in the population,
00:09:23.14 that would be unfeasible.
00:09:25.13 So what we typically do is to
00:09:26.23 infer frequencies by estimating them
00:09:30.10 from a random sample.
00:09:32.25 So in population genetics
00:09:35.01 generation, each new individual
00:09:37.16 is viewed as drawing from a set of gametes
00:09:39.20 with alternative alleles,
00:09:41.08 so let's use an example here
00:09:43.01 in which we have a set of marbles in a bowl.
00:09:46.05 And initially, we have a distribution of
00:09:51.26 60 of the white marbles
00:09:54.13 relative to 40 of the green marbles,
00:09:56.27 and these, the white and the green,
00:09:58.08 are representing different alleles.
00:10:00.14 So let's say that we're gonna pick...
00:10:02.04 we're gonna reach into this bag
00:10:04.04 and we're gonna randomly draw out
00:10:06.09 another hundred of these marbles.
00:10:09.01 And now in the next generation
00:10:10.26 we have 80 of the white and we have 20 of the green.
00:10:15.02 We're gonna reach back in,
00:10:16.01 we're gonna grab another set of a hundred,
00:10:18.09 and now in the next generation
00:10:20.15 we have 100 of the white alleles and 0 of the green.
00:10:26.08 And this is a demonstration of
00:10:27.15 how we get changes in allele frequency over time.
00:10:31.25 Allele frequencies will also change over time
00:10:34.23 due to genetic drift,
00:10:36.21 which is defined as random fluctuations
00:10:39.01 of allele frequencies from generation to generation,
00:10:42.03 simply due to chance.
00:10:44.19 So as we see, sometimes things could happen,
00:10:47.16 like these bugs are getting squashed,
00:10:50.00 and that's gonna change, perhaps,
00:10:52.07 the allele frequency in the next generation.
00:10:55.19 Here's another example from some lady bugs,
00:10:58.23 and we can see that, perhaps,
00:11:01.03 in the next generation, just by chance,
00:11:03.10 we're gonna see more of these ladybugs
00:11:04.29 with the dark colors,
00:11:06.12 or we might see more that are with the medium colors and dots.
00:11:10.16 And the fact is that drift is just an inevitable fact of life.
00:11:16.15 I also want to define what we mean by neutral evolution.
00:11:20.08 So we define a selectively neutral allele
00:11:22.10 as one that does not affect reproductive fitness of individuals
00:11:25.20 who carry that allele,
00:11:27.20 so it's frequency in the population
00:11:29.25 changes by chance or genetic drift alone.
00:11:32.18 And here we have an example:
00:11:35.04 this is just a substitution
00:11:37.22 in the third position of the codon,
00:11:41.02 and when we have substitutions
00:11:44.09 of nucleotides in the third position,
00:11:46.20 very typically they result in a silent or synonymous change.
00:11:51.05 So here there's been a substitution,
00:11:53.00 but there's no change in the amino acid;
00:11:55.02 it remains as valine.
00:11:57.26 So the rate at which genetic drift occurs
00:12:00.01 is going to inversely proportional to the population size, N,
00:12:03.23 and it's going to be very fast in small populations.
00:12:06.27 And here's an example that we can look at
00:12:08.23 based on computer simulation.
00:12:11.20 So let's assume here that we're looking at a single locus
00:12:15.15 and it has two alleles
00:12:18.06 that are at 50% frequency each,
00:12:21.25 as we can see here.
00:12:23.22 We have a sample size of 25,
00:12:27.06 and we're going to do the simulation
00:12:29.03 over 80 generations.
00:12:31.14 Now, each of these lines here
00:12:34.03 represents a different simulation,
00:12:36.27 and what we can see is that
00:12:38.23 over time alleles are either going to
00:12:44.02 be lost from the population
00:12:46.08 or they're going to reach fixation,
00:12:48.17 which means that they go to 100% frequency.
00:12:52.10 And the rate at which this occurs
00:12:54.00 is going to depend on the sample size.
00:12:56.09 So in a small sample it's gonna be very rapid,
00:12:59.19 but in this example where we have a larger sample, now N=300,
00:13:03.26 you can see that it just takes more time.
00:13:05.23 There's not as much genetic drift occurring.
00:13:08.19 Now, the end result is gonna be the same,
00:13:10.15 it just takes more time.
00:13:14.09 The change in allele frequency also is going to depend
00:13:17.27 on the initial allele frequencies.
00:13:19.20 So in this particular case,
00:13:21.05 we've now changed the starting frequency:
00:13:23.20 it's not 50%, it's now 10%.
00:13:27.06 And you can see that there's much more
00:13:29.28 probability of loss of the allele in this case,
00:13:34.11 and here we have just one of the alleles reaching fixation.
00:13:42.08 So again, in this particular case,
00:13:44.05 about 1 out of 10 will eventually become fixed,
00:13:47.14 or reach 100% frequency.
00:13:51.09 Now here's an example from a large population.
00:13:54.01 It'll take longer for this to occur,
00:13:56.02 but the proportion of alleles are gonna be
00:13:58.12 roughly the same,
00:13:59.29 so again roughly 1 out of 10 will go to fixation,
00:14:03.06 it's just gonna take longer.
00:14:05.16 Other important terms in population genetics
00:14:07.26 are bottleneck and founder effects,
00:14:10.08 and this is because genetic drift
00:14:11.23 has a large effect on allele frequencies
00:14:14.10 when a population originates
00:14:16.05 via a small number of people from a larger population.
00:14:19.16 So here we have an example of a bottleneck,
00:14:22.10 and what a bottleneck means is that
00:14:24.01 there's been a decrease in population size
00:14:26.21 at some time in the past.
00:14:28.14 So you can think of it as a population crash.
00:14:31.10 And what happens when the population is very small,
00:14:34.28 you're going to have a higher rate of genetic drift,
00:14:37.12 and we can see here that these alleles,
00:14:39.20 which are represented by the different colors,
00:14:42.00 have shifted from what we're seeing
00:14:44.18 back at this earlier time.
00:14:46.25 Now we go through the bottleneck,
00:14:48.19 and now we're seeing predominantly
00:14:50.07 these white and black alleles.
00:14:53.09 Another example we can look at is a founder event,
00:14:57.20 which is sort of a special case of a bottleneck event.
00:15:00.11 And in this case it's where a population, a small population,
00:15:05.03 breaks off from the larger population,
00:15:07.25 and again there's going to be increased genetic drift
00:15:10.26 in this initially small population
00:15:13.12 and here, by chance,
00:15:15.05 we just happened to see more of these dark blue
00:15:18.12 and light blue alleles.
00:15:21.09 The pattern of variation that we see
00:15:22.23 in the human genome
00:15:24.09 is also dependent on the effective population size,
00:15:27.17 which we distinguish as capital N sub e.
00:15:32.10 And the definition of the effective population size
00:15:35.10 is the number of breeding individuals in a population.
00:15:38.19 So estimates of Ne
00:15:40.17 are most strongly influenced by population sizes
00:15:43.07 when they're at their smallest,
00:15:45.10 and it could take many generations
00:15:47.02 to recover from a bottleneck event.
00:15:49.11 So estimates of Ne in modern populations
00:15:51.21 reflect the size of the population
00:15:53.20 prior to population expansion.
00:15:56.22 Pretty consistently, studies of nuclear sequence diversity in humans
00:16:00.24 have estimated an effective population size
00:16:03.15 of about 10,000.
00:16:05.19 Now, by contrast, if we look at Chimpanzees,
00:16:08.29 the estimate is closer to 35,000.
00:16:12.14 And so what that means is that
00:16:14.01 humans have undergone a bottleneck
00:16:16.18 sometime during their evolutionary history.
00:16:19.22 So the pattern of genomic variation
00:16:21.25 that we see in modern populations today
00:16:24.00 is a reflection of our evolutionary and demographic history.
00:16:27.14 So how much do we differ?
00:16:29.17 Well, identical twins
00:16:31.27 have no differences at the nucleotide level.
00:16:35.06 If we compare unrelated humans,
00:16:36.29 we differ at about 1 out of 1,000 nucleotide sites.
00:16:41.12 And if we compare humans to our closest genetic relative, the Chimpanzee,
00:16:45.02 we differ at about 1 out of 100 sites.
00:16:47.29 So, as a whole, our species is very similar,
00:16:50.27 and that simply reflects our recent common ancestry
00:16:54.05 from Africa within the past 100,000 years.
00:16:57.06 But when you consider that there are
00:16:58.27 over 3 billion DNA bases in the genome,
00:17:02.02 that results in 3 million differences
00:17:04.16 between each pair of genomes,
00:17:06.05 more than enough to generate the diversity
00:17:08.29 that will make each of us unique.
00:17:12.02 Now I want to introduce a statistic
00:17:14.13 that we typically use to look at how much variation
00:17:17.06 there is among populations,
00:17:20.01 and this is referred to as an Fst statistic.
00:17:24.00 And it's simply looking at the proportion of genetic variation
00:17:27.03 that is within populations,
00:17:29.06 relative to that which is between populations.
00:17:32.18 Fst can be measured based upon heterozygosity,
00:17:37.20 and heterozygosity is simply a measure of genetic variation,
00:17:41.26 which is very simply calculated as
00:17:44.15 1 minus the sum of the allele frequencies squared.
00:17:49.09 And so once we calculate
00:17:51.26 the heterozygosity for each locus,
00:17:53.29 we can look at the average,
00:17:55.23 and we can look at the average within a subpopulation,
00:17:58.03 or in the total combined population.
00:18:00.29 Now, just as an example,
00:18:03.15 if we were to see here that
00:18:06.22 in the case of Fst = 1,
00:18:09.12 it means that there is no overlap at all in the allele frequencies.
00:18:13.15 So we can see that in population 1 they have all A's,
00:18:16.13 and in population 2 they have all B's.
00:18:19.15 And in the case of Fst = 0,
00:18:22.18 there is complete similarity,
00:18:26.08 so here we see exactly the same number
00:18:28.13 of A alleles and exactly the same number of B alleles.
00:18:32.01 And then here's an intermediate case
00:18:33.29 where we have about 0.11, 11%,
00:18:39.07 showing that there's just a small amount of differentiation
00:18:43.04 between these two populations.
00:18:46.09 So what do we see in humans?
00:18:47.29 Well, the average Fst between human populations
00:18:51.04 is about 15%,
00:18:53.15 and what that means is that the majority of genetic variation
00:18:56.04 is found within a population,
00:18:59.07 and only about 15% of the genetic diversity
00:19:02.08 differs between populations.
00:19:04.23 Again, this is reflecting our recent common ancestry in Africa,
00:19:09.00 within the past 50,000-100,000 years.
00:19:14.13 Now, interestingly,
00:19:16.09 if we were to do this calculation from Chimpanzee populations,
00:19:19.08 we see that the value is around 32%,
00:19:22.15 so there's actually a lot more differentiation
00:19:25.04 among Chimpanzee populations
00:19:27.07 than among human populations,
00:19:29.18 again reflecting our overall close genetic similarity to each other.
00:19:36.19 So I now want to talk about the
00:19:38.04 different sources of DNA that we use
00:19:40.04 to reconstruct human evolutionary history.
00:19:43.01 One source of DNA is
00:19:45.29 that which is present in the nuclear genome
00:19:48.06 that's located in the nucleus of the cell.
00:19:51.03 And there's another type of genome
00:19:53.20 which is present in the mitochondria of the cell,
00:19:56.15 and the mitochondria is the energy-producing organelle.
00:20:02.13 So what is the difference between these different genomes?
00:20:06.03 Well, the nuclear genome
00:20:08.09 consists of 22 autosomal pairs of chromosomes
00:20:12.26 and then the sex chromosomes,
00:20:14.15 XX for females and XY for males.
00:20:17.27 The nuclear genome is about 3.4 billion bases in size,
00:20:22.02 and it consists of about 20,000 coding genes.
00:20:25.10 It's inherited from both parents,
00:20:27.21 but it also undergoes extensive recombination each generation.
00:20:32.07 But, one of the reasons it's useful is that there's
00:20:34.18 so many different locations where we can study variation,
00:20:38.08 given that there are 3 billion nucleotides,
00:20:41.02 it's just a little bit more difficult to trace them back
00:20:43.29 to a single common ancestor.
00:20:46.20 By contrast, the mitochondria DNA genome
00:20:50.21 is very small, it's only about 16,000 nucleotides in size,
00:20:55.14 and it's circular,
00:20:57.17 and it's passed on only through the maternal lineage.
00:21:00.19 There's also no recombination
00:21:02.17 and it has a very high mutation rate.
00:21:05.00 All of these features make it very useful
00:21:07.01 for tracing evolutionary history.
00:21:09.27 So let me give you another example of what I'm referring to.
00:21:13.12 The mitochondrial DNA is inherited through the maternal lineage,
00:21:17.05 whereas the nuclear DNA is inherited from both parents.
00:21:22.08 So if we were to trace back from a present day individual,
00:21:25.26 they will have inherited their nuclear genome
00:21:28.20 from their parents,
00:21:30.17 their parents would have inherited from their set of parents,
00:21:33.28 and then their set of parents, and so on.
00:21:36.15 So we can trace it back to a large number of ancestors.
00:21:39.16 But by contrast, if we're tracing back mitochondrial DNA lineages,
00:21:44.00 we can see that they're only passed on
00:21:46.25 through the maternal lineage,
00:21:49.10 so they're essentially inherited from a single lineage.
00:21:52.03 We can trace them back to a single common female ancestor,
00:21:56.01 and that's why they're been very useful
00:21:57.29 for human evolutionary genetics studies.
00:22:00.21 So for example, if we were to consider
00:22:02.26 these dots to be mitochondrial DNA lineages,
00:22:06.20 and let's start at generation 11 at the bottom,
00:22:10.12 shown by the red dots,
00:22:12.06 and imagine those are different mitochondrial DNA sequences
00:22:15.00 from different individuals.
00:22:17.10 At some time in the past, these two individuals, for example,
00:22:22.06 coalesced back to a common ancestor,
00:22:24.26 and then this group coalesces back to a common ancestor here,
00:22:29.29 and ultimately they all coalesce back
00:22:32.20 to a single common ancestor.
00:22:35.03 Now, in the popular literature,
00:22:36.22 the single common ancestor for mitochondrial DNA
00:22:39.04 is often referred to as "mitochondrial Eve",
00:22:42.21 but one thing to remember is that
00:22:45.17 Eve was not alone, she lived within a population,
00:22:49.06 as we can see here by the other colors.
00:22:51.22 But those lineages just never made it
00:22:54.22 down to the present day.
00:22:57.25 So this is a phylogenetic tree
00:23:00.11 constructed by sequencing mitochondrial DNA
00:23:03.10 whole genome lineages
00:23:05.02 from ethnically diverse individuals.
00:23:07.19 So each individual actually represents
00:23:10.29 a branch on this tree,
00:23:13.02 and if two individuals are very closely related to each other,
00:23:16.05 they'll be very close to each other
00:23:19.01 in the tree.
00:23:21.03 So one of the first things you can see
00:23:22.19 using Chimpanzee as an outgroup
00:23:25.01 is that all modern human lineages
00:23:27.25 coalesce at about 170,000 years ago,
00:23:31.12 and so that corresponds very well with the
00:23:33.05 time of origin of anatomically modern humans.
00:23:36.23 So another thing that we can see is that
00:23:39.25 all of the oldest genetic lineages
00:23:42.26 are from African individuals.
00:23:45.22 We can also see that
00:23:48.12 the very oldest lineages
00:23:50.15 are from the San and the Mbuti pygmy hunter-gatherers,
00:23:54.28 and then the more recent lineages
00:23:57.13 are from non-African populations.
00:24:00.01 And that is a pattern that's very consistent
00:24:02.17 with the model of a recent African origin
00:24:05.12 of modern humans.
00:24:07.23 Now, another way that we can compare mitochondrial DNA sequences
00:24:11.21 is to simply count up the number of sites
00:24:14.04 at which they differ when we compare any pair of sequences.
00:24:17.23 And when we do this,
00:24:19.09 we observe that
00:24:22.11 any two African lineages will differ from each other
00:24:25.03 at many more sites than any two non-African lineages.
00:24:29.06 And again, that means that there has been more time
00:24:32.02 for variation to accumulate in Africa,
00:24:34.16 and is consistent with an African origin
00:24:37.08 of modern humans.
00:24:39.20 When we sequence the mitochondrial DNA lineages,
00:24:42.21 we can classify them as haplotypes,
00:24:45.10 and those haplotypes belong to
00:24:47.16 larger subsets of haplogroups.
00:24:50.01 You can think of a haplotype as simply
00:24:52.14 the arrangement of genetic variants along a chromosome,
00:24:55.19 or in the case of the mitochondrial DNA
00:24:57.22 there's just a single genome,
00:24:59.14 so it's really just the different nucleotide differences
00:25:02.27 amongst different mitochondrial DNA lineages.
00:25:06.24 And one of the first things that you can note is that
00:25:09.26 there are different haplogroups
00:25:11.29 in different regions of the world.
00:25:13.19 So here are some that seem to be pretty specific to Africa,
00:25:16.20 but are also present in some regions
00:25:18.20 where there may have been some gene flow
00:25:20.20 from Africa.
00:25:22.21 Then we have others that may be more common in Europe,
00:25:25.12 or in east Asia,
00:25:28.18 or in the Americas.
00:25:30.19 And for that reason,
00:25:32.11 mitochondrial DNA can be very useful for
00:25:34.11 tracing recent human migration events.
00:25:38.13 Now, by contrast,
00:25:40.02 the Y chromosome is also inherited with no recombination,
00:25:45.14 and so it can also be very useful for tracing back
00:25:48.01 through the male lineages.
00:25:50.16 And here is a phylogeny constructed from Y chromosome variation,
00:25:55.07 and as with the mitochondrial DNA,
00:25:58.08 what we see is that the oldest lineages
00:26:01.19 are specific to Africans,
00:26:04.02 and the more recent lineages
00:26:06.05 are found predominantly in Non-Africans,
00:26:08.13 although we do see some in Africans as well.
00:26:11.25 Again, this is consistent with the recent African origin of modern humans.
00:26:18.14 We can also look at Y chromosome haplogroups,
00:26:22.09 and one of the things that's a little bit different
00:26:24.04 is you can see that they're a bit more differentiated
00:26:26.16 between geographic regions.
00:26:29.03 So for example,
00:26:30.24 here we just see haplogroups that are in blue,
00:26:34.04 and we see very distinct haplogroups
00:26:36.20 in the Americas, shown in purple.
00:26:39.26 And one of the reasons for that may have to do with
00:26:43.08 sex-biased migration,
00:26:46.01 that you may have, for example,
00:26:47.16 one male traveling long distances.
00:26:50.06 And it may also have to do with patterns of mating structure.
00:26:54.20 So for example, in some populations or ethnic groups,
00:26:57.23 you may have one male who has many different wives,
00:27:01.05 and because of that the effective population size of the Y chromosome
00:27:07.01 is actually smaller than the mitochondrial DNA,
00:27:09.28 and we tend to get more genetic differentiation
00:27:12.27 around the world.
00:27:15.07 So now I want to talk about analyses of ancient DNA,
00:27:18.27 for example, in this case from Neanderthal,
00:27:22.12 and these are some images of scientists
00:27:25.20 working on a Neanderthal fossil.
00:27:29.10 And this type of analysis is very challenging
00:27:32.01 for a number of reasons.
00:27:33.25 One is that DNA which is that old,
00:27:38.04 on the order of say 30,000 years old
00:27:40.10 to even 100,000 years old,
00:27:42.06 is going to be highly degraded,
00:27:44.24 and if there's any contamination
00:27:46.25 with modern human DNA,
00:27:49.02 that is much more likely to amplify
00:27:51.19 than the old degraded DNA
00:27:54.01 from the archaic species,
00:27:56.21 so one has to be extremely careful when analyzing this DNA.
00:28:01.03 Now, more recently,
00:28:02.24 there was a pinky finger bone
00:28:05.07 identified in a cave in Siberia
00:28:07.22 from a region called Denisova,
00:28:10.11 so it's referred to as the Denisova
00:28:13.21 or Denisovan genome.
00:28:16.11 Here I'm presenting a phylogenetic tree
00:28:18.29 based on mitochondrial DNA variation
00:28:21.24 comparing modern humans, shown in blue here,
00:28:26.09 to Neanderthals shown in red,
00:28:29.01 and the Denisova individual shown in yellow.
00:28:32.23 And what we can see is that the
00:28:34.17 time to most recent common ancestry in humans,
00:28:37.08 as we've already discussed,
00:28:39.00 is about 200,000 years ago.
00:28:41.13 The time to most recent common ancestry
00:28:43.14 between humans and Neanderthals
00:28:46.01 is about 500,000 years ago,
00:28:48.13 for the mitochondrial DNA lineages.
00:28:51.03 And the time to most recent common ancestry
00:28:53.20 with the Denisova mitochondrial lineages
00:28:57.08 is about 1 million years ago.
00:29:00.05 So this is demonstrating a couple of things.
00:29:02.20 From the mitochondrial DNA perspective,
00:29:05.07 there's no evidence of any admixture
00:29:07.13 with anatomically modern humans.
00:29:10.02 The Neanderthal sequences are clearly
00:29:12.18 very distinct from modern humans.
00:29:14.28 It's also showing you that there was another species, Denisova,
00:29:18.15 that appears to be distinct from the Neanderthals,
00:29:21.07 and they diverge even earlier than Neanderthals
00:29:24.09 from modern humans.
00:29:26.21 So if we were to compare pairwise nucleotide diversity,
00:29:31.01 for example,
00:29:33.02 among anatomically modern humans shown in blue,
00:29:35.24 you can see that there's not a lot of diversity,
00:29:38.15 as expected considering that
00:29:40.13 we all have a very recent common ancestry.
00:29:43.04 If you compare the modern human mitochondrial genomes to Neanderthal,
00:29:48.03 you can see that they're more divergent,
00:29:50.07 as expected, given that the mitochondrial DNA lineage
00:29:54.04 diverged about 500,000 years ago.
00:29:57.02 If we compare to the
00:29:59.03 Denisovan mitochondrial DNA lineage,
00:30:01.10 they're even more divergent.
00:30:04.04 And then if we compare to Chimpanzee,
00:30:06.14 of course as expected,
00:30:08.11 given that they diverged at least 5 million years ago,
00:30:11.14 they are the most different in terms of sequence variation.
00:30:15.13 Now, several years ago
00:30:18.13 there was a draft sequence produced of
00:30:21.20 the Neanderthal genome using next-generation sequencing technology.
00:30:25.25 And this was an absolutely amazing feat,
00:30:28.17 but at the time they had very low coverage,
00:30:31.07 meaning that any particular region of the genome
00:30:33.19 was sequenced only about once or twice.
00:30:36.20 Now, more recently,
00:30:38.07 as the technology has improved,
00:30:40.05 they've gotten much better coverage of the Neanderthal sequence,
00:30:43.04 and quite recently they now have a 30-fold coverage,
00:30:46.22 meaning that on average most sites
00:30:49.03 will have sequenced 30 times.
00:30:51.22 And so you'll have a much better accuracy
00:30:54.23 when determining nucleotide variation.
00:31:01.07 So, when the Neanderthal genome
00:31:03.25 was compared to the human genome,
00:31:06.11 what you can do is first
00:31:08.10 look at how much divergence has occurred
00:31:11.02 since modern humans differentiated from Chimpanzees
00:31:15.10 within the past 6.5 million years.
00:31:18.12 And you can look at the divergence
00:31:20.24 that has occurred specifically in the human lineage
00:31:24.06 since they diverged from Neanderthal,
00:31:26.21 and they've only accumulated
00:31:29.07 about 8% of this total divergence.
00:31:34.08 And so the estimate of the time of population divergence
00:31:38.06 between humans and Neanderthals
00:31:40.15 is about 400,000 years ago.
00:31:43.09 Furthermore, it has been estimated that
00:31:45.24 there may have been a small amount of admixture
00:31:48.16 between Neanderthals and anatomically modern humans,
00:31:52.01 as shown by this red arrow here.
00:31:54.18 So the estimated amount of admixture is about 1-2%,
00:32:00.15 of the modern human genome,
00:32:02.17 may be of Neanderthal ancestry.
00:32:05.03 But what is of interest is to note that
00:32:07.24 this is only present in Non-Africans.
00:32:10.13 It is not present in African genomes.
00:32:13.05 And so what we can infer from that is
00:32:15.16 that this admixture event probably occurred
00:32:18.25 before modern humans spread across the globe.
00:32:22.01 It may have occurred, for example, in the Middle East,
00:32:24.28 and that's why we're seeing it present in all Non-Africans,
00:32:29.18 and we don't see it at all in Africans.
00:32:32.15 Now, more recently, there has been
00:32:34.22 whole genome sequencing of the Denisovan individual,
00:32:39.20 and what that has shown is that
00:32:42.09 the Denisovan species, or this individual,
00:32:45.15 appears to have diverged from modern day humans
00:32:48.13 around 800,000 years ago,
00:32:51.09 consistent with what we saw from the mitochondrial DNA.
00:32:55.21 They also observed low levels of heterozygosity in Denisova,
00:32:59.21 suggesting that they may have had
00:33:01.19 a small population size.
00:33:04.06 Additionally, when a phylogenetic tree
00:33:07.24 was constructed from the nuclear DNA variation,
00:33:11.13 they could see that the modern humans
00:33:15.11 tend to cluster together,
00:33:17.09 and as we expect they're divergent
00:33:19.01 from the Denisova and the Neanderthals.
00:33:21.29 The Neanderthals tend to cluster together,
00:33:24.06 so they're clearly divergent from Denisova.
00:33:27.03 But what's interesting is if you look at how much
00:33:31.01 variation there is amongst the modern humans,
00:33:34.11 as indicated by the length of these lineages,
00:33:38.06 and then you compare that to Neanderthals,
00:33:40.14 which have very short branches.
00:33:43.06 What that suggests is
00:33:44.28 that there was not a lot of genetic variation
00:33:47.09 amongst the Neanderthals,
00:33:49.23 and therefore they may have undergone a bottleneck,
00:33:52.11 so they might have undergone a population crash
00:33:54.20 at some point in the past.
00:33:57.07 So in summary,
00:33:59.04 what we can see is that
00:34:01.23 Homo erectus left Africa
00:34:04.05 within the past 2 million years,
00:34:06.28 and spread throughout Eurasia,
00:34:09.09 giving rise, possibly,
00:34:11.09 to species like Homo floresiensis,
00:34:14.17 and surviving until quite recently,
00:34:17.12 as recently as around 25,000 years ago.
00:34:20.28 Then we have other species like Neanderthal and Denisovans,
00:34:27.02 who may have originated from a different species,
00:34:30.07 such as heidelbergensis,
00:34:33.10 and they differentiated sometime
00:34:36.12 around 600,000 or 700,000 years ago in the case of Denisova,
00:34:39.29 or in Neanderthals around 400,000 years ago.
00:34:43.05 And then we have the modern human lineage,
00:34:46.11 Homo sapiens,
00:34:49.00 which arose around 200,000 years ago
00:34:51.07 and spread out of Africa.
00:34:53.21 And when they did so,
00:34:55.02 they would have encountered these other species,
00:34:57.09 and there may have then been low levels of gene flow.
00:35:01.20 And in fact for the case of the Denisovan genome,
00:35:03.23 it appears that the gene flow
00:35:05.26 was predominantly with populations from Oceania,
00:35:10.01 implying that this admixture
00:35:12.17 may have occurred in a different location and a different time.
00:35:16.00 Now, we still don't know exactly
00:35:18.05 how much admixture there may have been
00:35:20.12 between archaic species
00:35:22.23 and modern humans in Africa,
00:35:25.01 but there's some preliminary data suggesting that
00:35:27.10 this has occurred there as well.
00:35:29.14 The problem is that the fossils don't preserve as well in Africa,
00:35:32.19 so we don't have any DNA sequences
00:35:34.26 from archaic lineages in Africa at this point.
00:35:40.01 So in conclusion,
00:35:41.18 Africa has the most genetic diversity in the world.
00:35:44.15 Human dispersions out of Africa
00:35:46.11 populated the entire world,
00:35:48.15 and we are the last of a series of hominin dispersal events
00:35:51.14 out of Africa.
00:07.3 Hi. I'm Liz Hadly.
00:09.2 I'm a professor at Stanford University,
00:11.2 and I'm here to tell you about some of the work
00:13.1 that my lab and I have been working on
00:16.2 for the last several decades.
00:18.1 So, by training, I'm a paleontologist,
00:20.2 which means that I go back in time
00:22.2 and study how different animals have been affected
00:25.2 by changing environments of the past.
00:28.1 Those environmental changes include climate change,
00:30.1 they include volcanic eruptions,
00:31.3 and they include dispersal between continents.
00:34.2 What I'm here to tell you about today is that,
00:37.2 I've learned that what's happening on the planet now
00:40.0 is essentially equivalent
00:42.1 to the kinds of changes that I've been looking at
00:44.1 in the fossil record.
00:46.2 The biggest reason why these things are happening
00:48.3 is that the world population is enormous,
00:51.3 and it's continuing to grow.
00:54.3 If we manage somehow to hold our population
00:58.1 to just replacing every man and woman
01:00.3 with another man and woman,
01:02.2 we will still reach 9 billion people
01:06.2 by the year 2045,
01:08.3 and that means trouble for other animals
01:11.2 on the planet.
01:13.0 As a matter of fact, world population growth
01:15.0 has really contributed to our colonization of the planet.
01:19.1 As humans expanded out of Africa
01:21.2 somewhere between 100 and 200 thousand years ago,
01:24.1 they colonized Australia,
01:26.2 they colonized Asia,
01:28.0 they colonized Europe,
01:29.1 and, last of all, they colonized the Americas.
01:32.0 So, by about 13 thousand years ago,
01:34.1 humans had reached every continent
01:38.1 except Antarctica.
01:40.3 So, this expansion was also tied to
01:44.1 extinctions of large animals,
01:46.2 so we call this the late Pleistocene megafaunal extinction,
01:49.3 and in addition to the loss of these animals, for example,
01:53.1 all of which were present in North America
01:56.1 until about 10 thousand years ago,
01:59.0 there was also a climate warming event.
02:01.2 So, not only the expansion of humans,
02:03.2 but also this climate change
02:05.2 that happened at the same time...
02:07.2 it turns out those are exactly the same two features
02:10.0 that are affecting the planet today.
02:13.1 Humans, in fact, have been killing,
02:14.3 deliberately killing, wildlife for thousands of years,
02:19.2 and through that and the expansion out of Africa,
02:22.3 it turns out that every continent
02:24.2 lost their large animals, not just North America.
02:27.2 What you see here are bar graphs of just the number of species
02:30.0 in different size categories
02:34.1 and over here are the larger animals --
02:36.2 and Africa is really the only continent that has maintained
02:39.1 most of the large animals, like we see these elephants today,
02:41.2 whereas in North America and the other continents
02:44.1 lost their megafauna, lost their large animals.
02:47.2 These elephants now are threatened with extinction as well.
02:51.2 They have a gestation time of 22 months
02:54.0 and, on average,
02:56.1 one elephant is killed every 15 minutes.
02:58.2 There is no way that this large,
03:01.1 slow metabolism animal
03:03.1 could actually keep up with the deliberate
03:06.1 slaughter of these animals.
03:08.2 We're much, much better
03:10.2 at killing wildlife. As a matter of fact, we specialize in going after the very last
03:16.1 of some of these exquisite animals.
03:19.2 So, among about 5500 mammal species,
03:22.2 almost a quarter of them are threatened,
03:25.1 and most of them are threatened deliberately with hunting,
03:28.2 but there's more than that.
03:30.2 Humans, it turns out, have commensal animals
03:33.3 -- our cows, horses, and sheep --
03:35.3 are actually...
03:37.2 they dominate the biomass of the planet.
03:39.2 So, these are to scale in terms of the number of individuals
03:42.2 and their body mass,
03:44.1 so you see humans here and our livestock and pets.
03:47.0 Wild animals, on the other hand,
03:48.3 have just a tiny proportion of the total biomass
03:52.1 that dominates the planet today,
03:55.1 so that means there's little room for these wild animals,
03:58.1 because we consume most of the energy
04:01.3 on the planet.
04:03.3 The other thing that's happening is climate is changing.
04:06.2 So, this is a diagram of climate change
04:09.2 over the last 5 million years,
04:11.2 and you'll not they're changing scales as we go here
04:13.1 -- this is in millions of years and then thousands of years,
04:16.2 and then just the number of years before the present,
04:18.2 and then we finally move into the future over here.
04:21.0 So, what you'll see is that, in the last 5 million years,
04:23.3 the climates we're about ready to experience,
04:26.2 within the next 50-100 years,
04:28.3 are warmer than anything we've experienced
04:32.0 in our lifetime as a species,
04:34.1 and that any of the mammal species, for example,
04:37.0 that we're used to interacting with on the planet
04:39.0 have experienced in their lifetimes.
04:41.2 As a matter of fact, in the western US alone,
04:44.0 wildfires have doubled in frequency since 1988,
04:48.1 putting many people at risk for losing their homes.
04:55.1 Climate is also contributing to actual biome shifts.
04:57.3 This is a particular X-ray image
05:00.2 of the area around Pinnacles National Park,
05:02.3 showing that the trees that are standing there right now
05:06.2 are threatened with death in the near future
05:12.3 and blue, here, are the only healthy trees in this particular environment.
05:16.1 So in just a few years,
05:18.2 we're seeing a major shift
05:20.3 in where trees are present
05:22.2 and where trees are not present on the landscape,
05:24.2 simply because of climate,
05:26.3 and then the interaction between climate and things like
05:30.0 beetles, in particular, for trees.
05:32.2 We've lost a tremendous amount of forest cover.
05:36.2 The rate of loss has slowed down,
05:38.2 but that really doesn't matter in some ways,
05:41.2 because we've lost
05:44.3 a vast amount of many of these forests
05:47.1 in just the last 14 years
05:51.0 around the world.
05:54.0 Humans, in fact, are really good at causing habitat loss.
05:57.1 We can do this...
05:58.2 basically go out...
06:00.0 this is like hunting for trees...
06:01.1 we go out and we just take them down.
06:04.2 We transform ecosystems in radical ways.
06:07.2 This is an image of what
06:09.3 New York used to look like before we actually
06:12.2 built up the city
06:14.2 next to what the place looks like now.
06:15.2 And clearly there's no way for biodiversity,
06:18.1 at least most biodiversity,
06:20.1 to thrive in an environment that's so human-dominated.
06:24.1 In fact, if you look at the sum total of the terrestrial land on the planet,
06:28.2 we have used and coopted about 51% of the land
06:32.2 area just for our use,
06:34.1 mostly for production of food for ourselves
06:36.2 and our commensal animals.
06:38.3 If you look at this, you'll see that the only places
06:41.1 that we haven't really occupied
06:44.1 and we haven't transformed
06:46.0 are the hard to reach places
06:47.2 -- the Sahara Desert, the Congo,
06:49.2 the Amazon,
06:51.0 two of the places that have the largest
06:54.2 tropical forests left in the planet --
06:56.1 and the boreal forests and the tundra region.
06:59.2 So we've taken all the easily farmable land in the world.
07:03.2 Now, we need to basically farm this land we already have co-opted
07:08.0 more efficiently
07:10.1 in order to feed the coming mouths.
07:13.2 One of the things that matters a lot
07:15.2 when you think about how much of the land
07:17.3 we've actually changed on the planet
07:20.2 is that just by this simple rule,
07:22.2 this is one of the fundamental rules in ecology,
07:25.2 is that the number of species
07:28.1 is a function of the size of the place they occupy.
07:31.3 This is a rule of island biogeography,
07:34.2 and so here what we see across the x axis
07:36.2 is the size of the island,
07:38.1 these are the islands in the Caribbean,
07:40.2 and then number of species on the y axis,
07:43.0 and so the larger the island is
07:45.3 the more species are found on the island.
07:49.3 More area means more species.
07:52.2 Here you see an image
07:55.0 for different continents on the planet
07:56.3 and the number of amphibians.
07:58.1 So, even on a continental scale,
08:00.3 we're finding that larger areas
08:03.2 mean more species.
08:06.2 So, when you look at the amount of land
08:09.1 we've actually set aside to be protected on the planet,
08:12.3 it amounts to only 13% of our land surface.
08:15.2 So, even though we've co-opted
08:18.2 the function of 51%,
08:20.1 we've only actively set aside 13% of this to be protected,
08:24.1 and areas like Yellowstone National Park,
08:26.1 the world's first national park,
08:28.1 as you can see,
08:30.1 are isolated from all the other protected areas in North America.
08:35.2 So what these patches mean
08:38.0 is that we don't have a lot of connectivity
08:40.2 between our protected areas.
08:43.2 That exacerbates our attempts at conservation,
08:46.3 because animals like to move
08:49.1 to deal with different environments.
08:51.1 As the climates change,
08:52.2 they like to move to novel environments.
08:54.2 This is Yellowstone National Park,
08:57.1 seen from Earth Observatory,
08:59.1 and what you see is a nice long line there
09:02.1 showing you the division between
09:04.1 the forest service land on the west
09:06.2 and national park land on the east.
09:09.3 And what you'll see is clear-cutting
09:15.2 defines, now, the western border of Yellowstone National Park.
09:17.1 This is true for many of the protected areas of the world.
09:20.3 There's not a lot of buffer
09:23.1 for the animals that want to move away from Yellowstone
09:25.2 to a part of the landscape
09:28.1 that they can adjust to.
09:31.1 It's not just the transformation of habitat
09:34.0 that matters either;
09:35.2 it's that our transportation system itself
09:38.2 has disrupted a lot of these corridors of connection.
09:41.2 This slide, which is really spectacular
09:44.1 at showing how much of the landscape
09:46.3 we cut up with our transportation,
09:49.2 shows that...
09:51.2 in green you see the global roads,
09:53.3 you see in yellow our urban areas,
09:56.0 in blue you see our shipping routes,
09:58.2 and in white you see our air networks.
10:01.1 So it's not just on land,
10:03.0 it's not just what we've kind of transformed in terms of deforestation...
10:06.1 it's the roads we've built,
10:07.2 it's the number of ships we send across the ocean,
10:10.2 and it's the number of planes that fly in the sky,
10:12.3 all of which interrupt and threaten
10:16.2 animals that need to move across this landscape.
10:20.0 Species move to follow their habitats
10:22.2 and they've done this in the past.
10:24.1 This is in fact one of the first signs
10:26.2 of adjusting to climate that we see,
10:28.3 and the black dots, here, you see,
10:30.3 are data from the Pleistocene,
10:32.2 showing that these animals used to be present
10:36.2 greater than 10 thousand years ago,
10:38.0 somewhere between 10 and 20 thousand years ago,
10:39.2 at these parts of North America,
10:41.3 and as climates warmed
10:44.2 at the end of the Pleistocene
10:46.3 into what we call the Holocene,
10:48.1 which is the last 10 thousand years,
10:49.2 this species, the Northern Bog Lemming,
10:51.2 moved to the north,
10:53.3 and now you see its range occupying
10:56.2 the orange part of this figure.
10:58.2 So these species just responded
11:01.0 by moving pole-ward as climates changed.
11:03.2 This is a very typical response
11:06.0 among animals of the world,
11:07.2 that they move pole-ward as climates warm
11:10.0 and they move equator-ward as climates cool.
11:13.3 In fact, species are already moving north today.
11:16.3 There are examples of species
11:19.2 interacting with species that they don't normally see,
11:22.2 so southern species
11:24.2 are now starting to encounter species
11:27.1 from northern boreal forest or tundra regions,
11:29.1 and there are really interesting
11:32.1 and sometimes not very positive interactions
11:35.1 that result from those interactions.
11:37.1 They create new ecosystems.
11:39.1 So, these are animals just doing what they need to do
11:43.0 and challenging us, too,
11:44.2 in thinking about what is natural, what is pristine,
11:47.2 and what we should expect in the future.
11:50.1 So, I already said that animals are on the move
11:53.1 and what that means is that
11:55.2 they need to find areas that they can colonize,
11:57.3 where they can live.
12:00.1 And it turns out that this fundamental rule of island biogeography,
12:03.2 that includes more...
12:05.2 larger area means larger number of species...
12:08.1 it also includes a concept of connectivity.
12:11.2 So, the closer these islands or these populations
12:15.0 are to each other,
12:16.1 the more likely they are to maintain more species.
12:18.3 So, what you see across the x axis
12:20.3 is the number of species present,
12:22.3 and this is the rate of extinction shown in red
12:26.3 and immigration, shown in blue.
12:28.1 And so when the populations
12:31.3 are far from the mainland,
12:33.1 there are many fewer species
12:35.1 that can be maintained,
12:36.1 and when they're close to another population
12:40.0 they can maintain more species.
12:41.3 Likewise, when the island area is small,
12:44.1 it maintains very few species
12:46.2 compared to when the islands are large.
12:48.3 So it's this equilibrium,
12:51.0 it's this balance between these rates
12:52.2 that really matters,
12:54.3 and we have to think about this in moving into the future.
12:58.1 So really what that means is biodiversity
13:01.1 is threatened even in protected areas,
13:03.2 and it's threatened surely by overexploitation,
13:05.2 by hunting, deliberate poaching,
13:08.0 but it is also threatened by ecosystem transformation.
13:11.2 Protected areas don't preserve entire ecosystems,
13:15.0 and so the transformation of what's happening outside the protected areas
13:18.1 matters to the species that live within it.
13:21.1 Novel species are interacting with disease
13:25.0 and bringing new diseases into places
13:27.1 that they haven't yet been because they are responding to climate change
13:30.2 and other sources of environmental transformation,
13:33.3 and that means that the connectivity between these protected areas
13:39.0 is very important.
13:40.1 So, finally, the thing that's really pushing all of this is climate change,
13:43.3 and that's what's very important
13:46.1 to consider going into the future.
13:48.2 Now, one of the things that happens as populations
13:51.1 get fragmented
13:53.1 is that their population size, the animals' population size,
13:56.2 starts to decline.
13:58.3 And extinction, the loss of a species forever on the plant,
14:01.2 is just when population size goes to zero.
14:04.2 So, here we see amphibians, birds, mammals,
14:07.2 and many other species,
14:09.2 and these are all animals that are threatened somehow with extinction.
14:13.0 There are animals shown in black
14:14.2 that are completely extinct in the wild.
14:16.3 There are animals shown in these warmer colors
14:19.2 that show different kinds of threats to their systems,
14:23.0 whether they're facing eminent extinction
14:25.1 or whether their populations are threatened.
14:28.2 And so, all this is to show is that
14:31.3 there are many animals, many... over...
14:34.2 you know, thousands of animals that are threatened with extinction
14:37.3 because of population demise.
14:41.0 In fact, global population numbers of wildlife
14:45.0 are 50% of what they were
14:47.1 just in 1970,
14:49.1 so animals of all types
14:51.1 -- birds, fish, reptiles, and mammals --
14:54.0 are showing really large declines
14:56.2 in the number of populations
14:58.2 that are on the planet,
15:00.2 just the number of individuals of these species
15:03.1 have declined by half.
15:06.0 I want to give you an example of what this means.
15:08.1 So, this is the Iberian lynx,
15:10.1 it's found in Spain, and this animal, in 1900,
15:13.1 was occupying most of Spain.
15:15.2 And you can see its demise through the '60s, the '80s,
15:18.1 and in 2010 there are two populations remaining,
15:24.0 one with 73 individuals and the other with 173 individuals.
15:28.2 So, not only have we lost populations,
15:31.1 and clearly we've lost individuals,
15:33.0 we're just down to a couple hundred of these lynx.
15:36.2 And what does that mean?
15:38.1 It means that they've gone through what we call a population bottleneck,
15:42.1 and I'll explain what that means to the species in just a second.
15:46.1 In particular, what we see is that as population size declines,
15:50.2 so, as we decrease population size,
15:53.2 we actually decrease genetic diversity as well,
15:56.2 and so in general the larger the population is
16:00.0 the more genetic diversity will be maintained in that population.
16:03.2 And why do we care about population diversity?
16:06.3 We care about population diversity
16:08.2 because that's the toolkit that species have
16:11.2 to move into the future.
16:13.2 So, if we... you know,
16:15.1 if we kind of look at this in a little simulated model, here,
16:18.3 if you think of every one of these marbles,
16:20.2 these different colored marbles,
16:22.2 as some sort of a...
16:24.2 different kinds of a...
16:26.1 a genotype of some sort,
16:28.2 we start with a lot of genetic diversity
16:30.1 and then you just grab a few of these marbles,
16:32.3 you're going to get a bottleneck.
16:35.2 There's no way you can get all of this diversity
16:37.2 if you decrease the number of marbles
16:39.1 that you've pulled out of the system.
16:40.2 That's called a bottleneck.
16:42.3 You can recover, you can recover in numbers.
16:45.1 You can actually start reproduction
16:47.1 of this particular hypothetical species,
16:51.0 but you can't recover the initial genetic diversity,
16:53.1 because it takes so long,
16:55.1 in evolutionary time,
16:56.2 to accumulate.
16:58.0 So not only are numbers of individuals important,
17:00.3 but it's important to retain those individuals
17:02.3 as long as possible
17:05.1 to maintain genetic diversity.
17:07.1 Genetic diversity is a toolkit for adaptation.
17:11.2 Here's a great example.
17:13.1 These are the wolves of Isle Royale.
17:15.1 They've been studied for over 50 years,
17:17.1 it's the longest study of a predator-prey system
17:20.1 that we know about.
17:22.0 Wolves colonized this island
17:24.2 in Lake Superior in the 1940s
17:27.2 and they bounced around,
17:28.2 there's a pretty close relationship
17:30.2 between wolves and their moose prey,
17:32.3 where there's kind of a dynamic between the two of them.
17:37.2 There's been some severe winter declines in moose
17:41.1 and then that affects the wolves in some way.
17:44.1 There's been a particular canine parvovirus
17:47.1 that caused a large crash in the number of wolves,
17:49.2 and every one of these diamonds
17:51.2 shows you that there was a winter bridge to the mainland
17:55.1 that wolves could colonize across,
17:57.2 and so the population
18:00.3 was continually being rescued.
18:02.3 You see now that there aren't very many of these colonization events
18:06.3 and in fact the wolves are in decline.
18:11.2 And not only are they in decline,
18:13.1 but because they are losing their genetic diversity,
18:17.2 abnormalities in this population
18:20.0 have increased dramatically.
18:22.0 So, for example, these particular abnormalities
18:25.1 in their spinal column...
18:27.0 in Isle Royale, their incidence is about 1 in every 3,
18:31.2 and in a normal population
18:34.0 it would just be about 1%.
18:36.1 What this means is...
18:38.1 you can see in this last wolf here, of these three...
18:41.0 these are the last three wolves remaining on Isle Royale as of 2015,
18:46.1 and this last wolf has a shortened tail,
18:49.1 it's slightly twisted,
18:51.1 and his back... he looks like he has scoliosis.
18:53.2 They think that this is the pup of these two, this pair,
18:56.3 but these are the last three left,
18:58.3 and clearly this wolf has been affected by inbreeding.
19:04.2 So, there is this possibility
19:08.2 to rescue populations
19:10.2 by bringing in some kind of new individuals
19:13.2 to a population,
19:15.0 and that indeed is what happened to the Florida puma.
19:16.2 So, in the mid-1990s,
19:20.3 puma were brought in from Texas,
19:23.3 and what you see in terms of the population size,
19:25.2 which was on decline,
19:27.2 is that they basically started breeding more frequently,
19:30.2 and so the population really bounced up in individuals,
19:34.1 but there was also a rescue of genetic variation.
19:37.3 The eight Texas puma...
19:40.3 you see before this time,
19:43.0 there's hardly any variation,
19:45.2 and after that time there's an enormous increase
19:48.2 in the amount of genetic variation in this population,
19:51.2 suggesting that there's been genetic rescue
19:54.1 just by adding eight individuals
19:56.2 from another healthier population.
20:00.0 Small populations, then,
20:02.1 to kind of summarize this part,
20:04.1 small populations
20:06.2 tend to result in inbreeding, and so...
20:09.1 and the reason is because it brings out
20:12.0 the recessive deleterious genotypes.
20:15.3 In this case, you'll see this lineage
20:19.1 showing this recessive allele
20:21.1 that doesn't get expressed in the offspring
20:24.1 because there's always this dominant allele,
20:26.3 this large A,
20:28.2 that is overprinting it.
20:31.1 When there's inbreeding,
20:33.0 you have the opportunity to produce an individual
20:36.2 that has both of these recessive alleles,
20:39.0 and what that means is that
20:40.3 these deleterious phenotypes
20:43.0 then become expressed.
20:45.3 Okay, so what are these recessive deleterious alleles?
20:49.2 What do they result in?
20:50.2 What's the problem with inbreeding?
20:52.2 It turns out that inbreeding creates
20:56.1 a pretty typical list of problems with many animals:
21:00.0 their faces aren't symmetrical;
21:02.2 they have reduced fertility,
21:04.1 and this is true both in terms of the number of offspring that they produce
21:11.0 and also whether their sperm are even viable;
21:12.3 there are many genetic disorders, including Down's syndrome,
21:14.2 that show up in animals;
21:16.3 they have a much lower birth rate;
21:18.1 higher infant mortality;
21:20.3 and because they have a slowed growth rate,
21:23.1 they also reach a much smaller adult size;
21:26.2 and then most importantly, perhaps,
21:28.2 in this changing world
21:30.1 is that they really lose a lot of their abilities
21:33.0 to respond with their immune system.
21:36.0 So, I want to point out...
21:38.0 here is an example in tigers,
21:40.1 these are white tigers...
21:42.2 white tigers, for those of you who don't know,
21:44.1 white tigers are not Siberian
21:45.2 -- they look like they should be,
21:47.1 they have this white coat --
21:48.2 it turns out they're completed created in zoos.
21:51.1 White tigers are actually Bengal tigers,
21:53.2 they're from India,
21:55.1 and they've been highly inbred in zoos
21:57.1 because people like white tigers.
21:59.2 But it turns out the white coat
22:01.2 is also associated with the same gene
22:06.0 that creates cross-eyes in the individuals,
22:10.0 so it crosses the optic nerve,
22:12.2 and so every white tiger that you see
22:15.1 is cross-eyed.
22:16.3 And you can see this other tiger, here,
22:18.3 with a severely misformed face and a very asymmetrical face,
22:23.0 he has a cleft palate,
22:24.3 he has a lot of problems.
22:26.1 This animal could not survive in the wild.
22:30.1 So, to conclude,
22:32.2 I just want to really underscore that
22:35.1 humans dominate the planet.
22:37.3 Populations of wild animals and species of animals
22:40.3 are threatened with extinction --
22:43.1 they're in decline.
22:44.2 What does that matter?
22:46.1 Why does that matter?
22:48.0 Declining populations lose genetic diversity.
22:50.2 They're more likely to lose all those tools
22:53.1 that they need to adapt to whatever the future
22:56.0 is bringing to us.
22:57.2 And then, importantly,
22:59.2 the connectivity between these populations,
23:02.1 the ability for these animals to move
23:04.2 and find a new home,
23:06.2 is increasingly getting more and more difficult.
23:09.1 That's critical for their survival.
23:12.1 So, what I want to do is conclude
23:14.2 by saying thank you to all of
23:17.1 the former and current members of my lab,
23:18.3 all of my collaborators,
23:20.1 the funding agencies I've had through the years,
23:21.3 and Stanford University.
- Uma Ramakrishnan iBioSeminar: Biogeography: Studying the Distribution of Species Across Space
- Sarah Tishkoff iBioSeminar: African Genomics: Human Evolution and Migration
- Elizabeth Hadly iBioSeminar: Loss of Biodiversity in a Human-dominated World
Elizabeth Hadly is the Paul S. and Billie Achilles Chair of Environmental Science and a professor of biology at Stanford University. She is a Senior Fellow in the Stanford Woods Institute for the Environment, and, in September 2016, Hadly will become the Faculty Director for the Stanford Jasper Ridge Biological Preserve. Hadly’s lab studies the… Continue Reading
Dr. Uma Ramakrishnan is a professor at the National Center for Biological Sciences (NCBS) in Bengaluru, India. Her passion for ecology and evolutionary biology led her to complete a bachelor’s degree in Physics, Chemistry and Math. Ramakrishnan obtained her PhD on population genetics from the University of California, San Diego and continued her postdoctoral training… Continue Reading
Sarah Tishkoff studied anthropology and genetics as an undergraduate at the University of California, Berkeley. She received her PhD in genetics from Yale University and was a post-doctoral fellow at Pennsylvania State University. From 2000-2007, she was a faculty member in the Department of Biology at the University of Maryland. Currently, Dr. Tishkoff is the… Continue Reading