WEBVTT

b5d4fcd1-dc38-4473-a316-9d6bfa6c7154-0
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It is my great pleasure today to
introduce Kevin Bourdon,

b5d4fcd1-dc38-4473-a316-9d6bfa6c7154-1
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who is currently an Associate Professor
in the Department of Human and

b5d4fcd1-dc38-4473-a316-9d6bfa6c7154-2
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Revolutionary Biology at the Harvard
University.

f7ef494e-213c-4a9c-ab89-1b191b2a891d-0
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Kevin is a part of Ecologist that focuses
on how climate is affecting mammalians

f7ef494e-213c-4a9c-ab89-1b191b2a891d-1
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and humans.

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He got his PhD at University of Utah and
has been working as a research assistant

44e98d63-fec5-4b55-9177-362e1a37e4c0-1
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at Columbia University ever since.

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And it is our pleasure today to have him
speak about deer Paranthropos.

ce12d4b1-04c0-409a-99df-23e0b4d11d9e-0
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What type of food did you eat or WTF?

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Welcome Kevin.

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Thanks, Sir.

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You can do that.

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Today I'm going to talk about the
relationship between diet and evolution,

a5996044-771a-4d49-a2e6-2a01bbfe09ab-1
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particularly human evolution.

5d030455-7ac1-487f-8e95-3234bdc4ed05-0
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And I'm going to take a different tack,
and I'm not going to focus on us.

652b4990-fa68-4c24-860f-0b4c4a78b286-0
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A lot of the discussion of human
evolution is about us, us, us.

4d98d6aa-b519-43da-a165-c9b6d0243e41-0
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And this is a talk about Parenthropus,
an extinct homonym.

0d648c25-034a-4e29-a23f-cd81064375e1-0
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The last one lived about a million
million 22 years ago.

b22749b9-9b74-4450-a4de-ab88f331ea25-0
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And this is a letter.

04ec2ff8-a538-4054-91e8-7ee0eb55c9ba-0
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This is a Valentine's Day.

00b06953-9fb1-4ff5-a11b-771d7154c5a7-0
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It's a love letter to Parenthropus asking,
dear parenthesis, WTF did you eat?

f9cec061-6f87-4b30-b681-9cd12fd51ab4-0
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Where that stands for what types of food
did you eat?

994db753-1e73-4b4d-ad03-104674408612-0
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And I'll try to explain why understanding
the diet of organisms,

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especially extinct organisms,
helps us understand their paleo biology,

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their their, their ecology in the past.

affe3049-2850-48d4-a710-484af318686a-0
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And this, this letter here,
it's called an aerogram.

3b644f7b-01f7-40ab-9fab-8fb8f91d4a3f-0
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This is a pretty young crowd it looks
like for the most part.

ac012d20-1fd3-4d90-858c-c690b593e581-0
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And long ago in the late Holocene when I
first started in graduate work in Kenya,

ac012d20-1fd3-4d90-858c-c690b593e581-1
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I would get these aerograms and it was a
single sheet of paper,

ac012d20-1fd3-4d90-858c-c690b593e581-2
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blue on the outside,
lined on the backside and you could write

ac012d20-1fd3-4d90-858c-c690b593e581-3
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letters home.

deb5a392-3cb5-44f9-9b9d-49adc7ebea11-0
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So dear mum and Dad,
I'm in a tent in the middle of nowhere in

deb5a392-3cb5-44f9-9b9d-49adc7ebea11-1
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Kenya.

efcdf5a0-799e-4553-8553-2427cd646b60-0
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It's hot, I'm tired and I'm dusty,
etcetera.

7210ff84-5db1-4870-99e8-f0c615d28d14-0
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And then you fold the piece of paper up
to single sheet of paper.

754a0c38-1587-4db8-98a1-a87fb609cb3c-0
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The paper becomes an envelope.

e15143c3-d00b-44c3-9e17-4a8a9b7477ed-0
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It's pre stamped and you can send it
anywhere in the world cost like a dollar

e15143c3-d00b-44c3-9e17-4a8a9b7477ed-1
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or something like that.

1866e0f3-6dd5-472f-8d2e-2ecf8f2e5fe2-0
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So I found an old you can't find them
really anymore because nobody does this.

11cb37cb-b3fd-4ab1-bfc0-db8a108b29d4-0
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But I wrote many home to my family.

53bff13b-83be-4453-a54e-f4fd1200a4dd-0
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And so this is one that I wrote to
parenthesis and hopefully you'll we'll

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dive into a little bit why understanding
the diet helps us understand the

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evolution and particularly how we got
here.

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OK.

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And since it's Darwin Days and we're
celebrating the 216th birthday of Charles

f69126af-5e05-4622-84fc-12d9168c034d-1
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Darwin this week,
I thought I'd start with just some notes,

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not direct quotes,
but just notes on his thoughts on the

f69126af-5e05-4622-84fc-12d9168c034d-3
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role of diet and evolution.

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So I'll let you read those for a moment.

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And clearly Darwin thought about the role
of resources, resource acquisition,

c70423a1-8e8a-4741-b6af-21d4a4ae933c-1
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feeding habits, etcetera on survival,
fitness and reproduction.

b5bf9f03-6087-4943-8ecb-9eab23066fdd-0
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He he also got into the idea of seasonal
availability of food, things like that.

fe30c9c7-4f34-415a-8e6e-712ea8df2f94-0
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And so really at the granular level about
the role of resources in evolution, OK.

63628fd4-06c5-4010-9455-1cf0a6fb489a-0
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So as Sarah mentioned,
thank you for the introduction, Sarah,

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wherever you are.

a90ab15c-5f73-4a88-bac8-a22740dd91a2-0
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And also Ryan,
thank you for the invitation to speak.

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Sorry, I should have started with that.

474daaf1-9334-4c2f-a381-cc737b2e7293-0
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I'm a paleoecologist and so I try to
understand past environments and both the

474daaf1-9334-4c2f-a381-cc737b2e7293-1
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the vegetation and ecology,
the hydroclimate or like rainfall,

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and also the organisms that live in those
environments and how those are all linked.

ac557fa0-713a-4f42-ab4d-af61852a4540-0
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And that's sort of highlighted in this
schematic here on the left or the right.

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Sorry, my left.

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And the principal question my research
group asks is how did climate change

b17d0399-9bd0-46d5-8c28-2ac634a93016-1
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influence major shifts in terrestrial
ecosystems and what were the evolutionary

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consequences?

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OK.

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And we can break that down into a couple
bigger questions.

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The first being what caused the emergence
of the world's tropical and subtropical

f5ba08cf-0a29-4b88-9c0c-4ab0bf45e028-1
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grasslands starting about 10 million
years ago.

3c9b8ab3-08ee-4792-88d1-ebc547c4b0a8-0
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So grasslands are a new feature on Earth,
relatively speaking,

3c9b8ab3-08ee-4792-88d1-ebc547c4b0a8-1
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and I won't dive too deeply into that
today,

3c9b8ab3-08ee-4792-88d1-ebc547c4b0a8-2
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but it's related to us and the evolution
of hominins, our group,

3c9b8ab3-08ee-4792-88d1-ebc547c4b0a8-3
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because we are a very grassy species.

387ddc4a-aed1-42c9-a1b7-7a2736fb39cb-0
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If you think about what you had for
breakfast this morning,

387ddc4a-aed1-42c9-a1b7-7a2736fb39cb-1
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it is probably a grass derived product.

62986df8-c14a-4b00-8d69-010f3b87740d-0
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I'll tell you I had yogurt and granola.

8d3cc9d9-5b48-4d42-8754-4d16ab6c6163-0
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So yogurt comes from cows that eat grass.

dda44521-bce9-46d2-b69e-1cd3003e3b19-0
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Granola is a grain, oats,
which is a type of grass,

dda44521-bce9-46d2-b69e-1cd3003e3b19-1
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and I can drink coffee without Creamer,
but I prefer it with Creamer,

dda44521-bce9-46d2-b69e-1cd3003e3b19-2
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which comes from grass.

552347c6-f2cb-4591-a936-4c1daec51a63-0
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So we have a really grassy diet.

f2672327-3b16-494e-bbb6-f9a197268ba5-0
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You can think about your lunch,
your dinner,

f2672327-3b16-494e-bbb6-f9a197268ba5-1
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as long as you don't get hungry here.

880c68cb-7454-4890-8628-4688c61a4087-0
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But we are a really grassy based species
and that will come through in the talk

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today.

aba31f4b-5936-4aab-8c59-40281dab771e-0
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Although I won't talk about necessarily
the evolution of grasslands,

aba31f4b-5936-4aab-8c59-40281dab771e-1
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I'm going to focus on this second
question.

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Did climate and vegetation play a
significant role in the evolution of

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humans and other large mammals?

2c1b127a-eaab-4400-ae9c-f0812e7622ad-0
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And this schematic kind of shows the
linkages between climate variables like

2c1b127a-eaab-4400-ae9c-f0812e7622ad-1
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the amount of rain an ecosystem gets,
what the CO2 levels are in the atmosphere.

d278fdfb-314c-44f4-8d24-62f3004ea537-0
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Plants take in CO2 right to to produce,
photosynthate and to grow.

e5734a6d-007e-4db6-807f-2434ce65b15d-0
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And then temperature plays a huge role in
what kind of plants can grow in an

e5734a6d-007e-4db6-807f-2434ce65b15d-1
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ecosystem.

9c9f1e5b-631b-4b2a-9e8b-93cd977b204a-0
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So these are climate variables in the
left and the ecosystem,

9c9f1e5b-631b-4b2a-9e8b-93cd977b204a-1
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we have things that control vegetation
structure.

3632a5fe-83a2-4b99-be18-fced750d3c4e-0
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So tree mortality, OK,
depends on things like fire or bibary.

86f8a119-8204-441a-a8c4-84bc7c763106-0
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And then we have this balancing act
between grassy and woody ecosystems.

5ca1f5d9-977e-47c5-9e8a-ef7453c41ff3-0
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So you can think of a pure grassland like
in the Serengeti or Woodlands or forest.

54e65eed-735f-4a93-b1ad-2d5e5eb23c0c-0
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There's a huge range of of ecosystems in
Africa where where the work that I

54e65eed-735f-4a93-b1ad-2d5e5eb23c0c-1
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present comes from today.

48cfeec4-e5dd-4b36-8764-af7339d25912-0
00:06:26.520 --> 00:06:26.920
OK.

86042c6a-d9e0-4c9b-b8a2-d8ce84f8b18a-0
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So focusing on this second question, OK,
did climate and vegetation play a

86042c6a-d9e0-4c9b-b8a2-d8ce84f8b18a-1
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significant role and how we got here?

a5ef8f3d-0479-404f-86c3-67882ab328b5-0
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We have these this sort of patchy fossil
record.

cd268393-3961-4af3-8133-53e0aea5887e-0
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Maybe you've seen sort of phylogenies
like this where we have some fossil and

cd268393-3961-4af3-8133-53e0aea5887e-1
00:06:42.588 --> 00:06:46.520
then we think it gave rise to other
species, things like that.

a24cd19d-295e-4cac-ade2-dbaf543469ca-0
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And what we're exploring is the link
between climate.

945671b2-1967-4910-be83-3d223773982f-0
00:06:50.480 --> 00:06:53.539
So here's some,
let's just call it climate data of maybe

945671b2-1967-4910-be83-3d223773982f-1
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where where these hominins are running
around on the earth.

80f0cbf9-2e1d-4613-a81a-fb75fb865585-0
00:06:57.080 --> 00:07:00.845
And then here we have a more global
record of say temperature,

80f0cbf9-2e1d-4613-a81a-fb75fb865585-1
00:07:00.845 --> 00:07:02.280
ice volume or something.

df3af5c5-290b-4960-8dc8-1a6d8e2da875-0
00:07:02.280 --> 00:07:07.321
And how do we link different scales,
So global records of climate or regional

df3af5c5-290b-4960-8dc8-1a6d8e2da875-1
00:07:07.321 --> 00:07:12.040
records of vegetation with the fossil
record that's a little bit patchy.

6292e616-bee3-47c5-87f8-14234381803a-0
00:07:13.560 --> 00:07:15.821
Well,
first we need to generate these global

6292e616-bee3-47c5-87f8-14234381803a-1
00:07:15.821 --> 00:07:19.240
records, local records of, you know,
vegetation, climate, etcetera.

53032b8b-ab4a-49eb-b8f1-8f8363106c94-0
00:07:20.360 --> 00:07:22.560
And then we need to generate this record.

5ee47563-7195-4fc3-b3d5-127d4e6dd2e2-0
00:07:22.560 --> 00:07:27.560
And this one we we know how to do and
we've been doing it for a very long time.

0f69207b-adf4-49d0-87f6-1111e0f5247a-0
00:07:28.160 --> 00:07:28.480
OK.

655e202c-5388-4a65-b8f6-35c48b3859a3-0
00:07:28.480 --> 00:07:31.440
And that is we,
we just go to the fossil record, OK?

4f17e827-f929-4fe0-b1f2-a9936e7e9fee-0
00:07:31.440 --> 00:07:35.320
It's an amazing,
amazing archive of the story of us.

f2207b48-8534-4e55-95be-9f6d98128c4f-0
00:07:35.920 --> 00:07:39.280
And here is the Leakey family.

00716c71-a579-454f-afbd-92135a0a5364-0
00:07:39.280 --> 00:07:41.720
This is Mary Lewis and one of the sons.

a22f1060-093e-49b1-b73d-1e804151fd39-0
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It's probably Richard Leakey at Old of I
Gorge,

a22f1060-093e-49b1-b73d-1e804151fd39-1
00:07:44.786 --> 00:07:49.577
probably in the early 1950s or so with
one of their mini Dalmatian dogs that

a22f1060-093e-49b1-b73d-1e804151fd39-2
00:07:49.577 --> 00:07:50.200
they kept.

98e39db1-4d6b-4524-aa33-0b0d9d29a83f-0
00:07:51.160 --> 00:07:57.120
And here in Aldevye Gorge is where Mary
discovered this particular homonym.

edf21db6-8c77-4809-ac63-a35eaadf6b11-0
00:07:57.120 --> 00:07:58.880
This is Parenthropus.

532beab2-cd49-4e70-83bd-cfcbada67d31-0
00:07:58.880 --> 00:08:01.633
Boise Eye,
originally called Zingianthropus,

532beab2-cd49-4e70-83bd-cfcbada67d31-1
00:08:01.633 --> 00:08:06.040
but the genus name is eventually changed,
or his name before, actually.

5f3d3160-26fa-4b66-bb39-a862d5011f03-0
00:08:06.040 --> 00:08:07.040
It's a complicated story.

cfd0a1df-243e-4aa2-b0de-dda079d1ae6b-0
00:08:07.320 --> 00:08:10.160
Anyway, This is Parenthropus.

74863acc-0157-4fe1-b3bf-c9fff8729b30-0
00:08:10.680 --> 00:08:13.600
This is 05 old divide hominid 5.

24e8e4d1-3283-4ccf-91fc-200d3d436ffc-0
00:08:13.600 --> 00:08:14.520
It's a specimen number.

7dce7405-a436-4994-bf29-a48570254f8c-0
00:08:14.520 --> 00:08:15.800
It's famous because it's a skull.

ba3d9f9c-7f85-4e5f-a3a0-bc407eff3867-0
00:08:16.080 --> 00:08:18.376
Often times you find a tiny tooth or
something,

ba3d9f9c-7f85-4e5f-a3a0-bc407eff3867-1
00:08:18.376 --> 00:08:20.720
but occasionally you get lucky and find a
skull.

fc5e7381-d039-4181-864e-6430641c3c28-0
00:08:21.120 --> 00:08:26.630
So the hominid fossil record has been in
the process of being assembled over the

fc5e7381-d039-4181-864e-6430641c3c28-1
00:08:26.630 --> 00:08:29.760
last century or so,
and it continues to grow.

dc299434-596a-4208-bd3d-173198efbe50-0
00:08:30.560 --> 00:08:36.336
This is my colleague Isaiah Nengo,
who sadly passed away several years ago,

dc299434-596a-4208-bd3d-173198efbe50-1
00:08:36.336 --> 00:08:41.200
one of the the 1st Kenyan
paleoanthropologist who studies human

dc299434-596a-4208-bd3d-173198efbe50-2
00:08:41.200 --> 00:08:41.960
evolution.

bc9bf269-e8d2-413f-8be5-c398b0d82518-0
00:08:42.880 --> 00:08:47.905
And in the Turkana Basin where Doctor
Mana and I work,

bc9bf269-e8d2-413f-8be5-c398b0d82518-1
00:08:47.905 --> 00:08:52.200
Isaiah discovered in 2014 this baby ape
skull.

6ee0ee4d-f899-469e-9750-254384e7b54e-0
00:08:52.200 --> 00:08:57.360
You can hold it in the palm of your hand
and it's 13.3 million years old.

d71ad7d2-993a-44ca-bcad-ce16f650f90a-0
00:08:57.560 --> 00:08:58.840
It's absolutely incredible.

f19265a9-59f7-46d9-b677-7e6c1181bab4-0
00:08:59.200 --> 00:09:03.757
They did some synchrotron scanning of it
and you can see the molars forming up in

f19265a9-59f7-46d9-b677-7e6c1181bab4-1
00:09:03.757 --> 00:09:05.480
the crypt still inside the jaw.

81ce5ff4-3869-46ed-9264-5389e5cbfefa-0
00:09:06.280 --> 00:09:10.875
And it's provide a a beautiful window
into the evolution of apes 13 million

81ce5ff4-3869-46ed-9264-5389e5cbfefa-1
00:09:10.875 --> 00:09:11.480
years ago.

5803473c-35ad-4f09-9a7e-e4aa37197c16-0
00:09:12.040 --> 00:09:18.396
So the fossil record has produced some
pretty amazing specimens that tell us how

5803473c-35ad-4f09-9a7e-e4aa37197c16-1
00:09:18.396 --> 00:09:22.320
we got here,
but the fossil record is incomplete.

67fcd206-efe9-47fd-93f7-beae72553176-0
00:09:24.040 --> 00:09:29.112
So I'm going to spend a little time on
this diagram so that I hopefully can

67fcd206-efe9-47fd-93f7-beae72553176-1
00:09:29.112 --> 00:09:34.050
convince you that even though the fossil
record is beautiful and amazing,

67fcd206-efe9-47fd-93f7-beae72553176-2
00:09:34.050 --> 00:09:36.320
it leaves something to be desired.

961794fe-42f5-427a-9a2f-e3e71a80524a-0
00:09:36.320 --> 00:09:42.440
So let's take our hypothetical hominin in
orange here, OK?

b57c0d66-dd4a-41c7-b191-af7c2bbefe9e-0
00:09:42.760 --> 00:09:46.800
And it's species range through four
different time slices.

ee8a9f76-16b9-4eca-8b94-c82b06173ee3-0
00:09:46.800 --> 00:09:51.920
Time 1234 going up the Y axis is outlined
in orange.

994556ca-824a-4ba8-a815-e0fca2c57b4c-0
00:09:51.920 --> 00:09:55.073
So in time one it's here,
time 2 it's widely spread,

994556ca-824a-4ba8-a815-e0fca2c57b4c-1
00:09:55.073 --> 00:09:59.120
times 3 it's just sort of to the North
East and time 4 to the West.

db885ba0-5847-4719-8dc1-48c0bda83790-0
00:09:59.720 --> 00:10:04.400
That's the the real sort of range of this
this particular Organism through time.

5abd6085-c37f-456f-bad2-082ba51db33a-0
00:10:05.640 --> 00:10:09.840
The circles ABCDEF are fossil localities.

6dc2bc5e-2445-4dba-a36c-c28a09e720a0-0
00:10:10.000 --> 00:10:10.320
OK.

bf47629a-c070-4ab9-82bf-a4cb73fddae3-0
00:10:10.840 --> 00:10:15.758
If it's a white open circle,
that means that no fossils are found

bf47629a-c070-4ab9-82bf-a4cb73fddae3-1
00:10:15.758 --> 00:10:17.920
there at the particular site.

bf119a72-4366-4f4c-907f-e9b40d5de007-0
00:10:18.400 --> 00:10:22.250
If it's green,
that means at that time period there are

bf119a72-4366-4f4c-907f-e9b40d5de007-1
00:10:22.250 --> 00:10:22.800
fossils.

9d22de05-dad6-4775-84ff-1c135c020cd6-0
00:10:22.880 --> 00:10:24.960
So time one.

237a5359-e000-4a3e-b939-3a95cbc7ed4a-0
00:10:25.040 --> 00:10:27.952
OK,
our hypothetical hominin is around and

237a5359-e000-4a3e-b939-3a95cbc7ed4a-1
00:10:27.952 --> 00:10:30.120
it's in the southern range here.

6a35ca10-45df-41b8-855f-29d570548f02-0
00:10:30.120 --> 00:10:34.085
Are the ranges here OK,
But because the circles are open,

6a35ca10-45df-41b8-855f-29d570548f02-1
00:10:34.085 --> 00:10:36.000
we never find fossils of it.

3e7a0cc6-df89-47a1-9851-0eaef3a86ab2-0
00:10:36.200 --> 00:10:39.260
It doesn't mean it never existed,
it just means it wasn't recorded in the

3e7a0cc6-df89-47a1-9851-0eaef3a86ab2-1
00:10:39.260 --> 00:10:39.840
fossil record.

1f4e8ee6-45f1-40de-bc8a-3ef51b9115a1-0
00:10:40.440 --> 00:10:40.720
OK.

c009490a-d8e0-4515-8a92-0dc6a856e02e-0
00:10:42.120 --> 00:10:45.635
In time 2,
we see that our hypothetical hominin has

c009490a-d8e0-4515-8a92-0dc6a856e02e-1
00:10:45.635 --> 00:10:50.840
expanded its range to South and then up
the Rift Valley into eastern Africa.

9fbbdd01-8011-44ad-a625-79dd7b9c56b6-0
00:10:51.080 --> 00:10:56.494
And we see it at these two sites and this
site and at this site C that wasn't part

9fbbdd01-8011-44ad-a625-79dd7b9c56b6-1
00:10:56.494 --> 00:10:59.560
of it's home range, but there are fossils,
OK.

cf7945f0-382d-48b0-ae7f-18bad9268e71-0
00:11:00.120 --> 00:11:05.760
So we end up having this real record in
orange, OK.

9ca3bd8d-81ec-4508-ac7e-75ecfa5027b2-0
00:11:05.920 --> 00:11:12.137
A second challenge in addition to our
incomplete fossil record is that we have

9ca3bd8d-81ec-4508-ac7e-75ecfa5027b2-1
00:11:12.137 --> 00:11:15.600
different scales of questions and
evidence.

85f173b8-f57d-4bce-be81-c1aeef9900b3-0
00:11:15.800 --> 00:11:19.826
So on the left,
this is the scales of our questions and

85f173b8-f57d-4bce-be81-c1aeef9900b3-1
00:11:19.826 --> 00:11:22.200
you can pick a question up there.

3c6b64ab-001a-49a0-a8d1-d39b8b187293-0
00:11:22.360 --> 00:11:24.080
I'm going to talk about diet today.

d9e9d774-e1fd-4b1f-929d-ee7054049617-0
00:11:25.440 --> 00:11:29.560
And on the right we have scales of
evidence.

8e314cc9-0e18-465d-8b97-45c34dbb8cff-0
00:11:29.960 --> 00:11:34.132
OK, so you need to,
the point of this plot is to say your

8e314cc9-0e18-465d-8b97-45c34dbb8cff-1
00:11:34.132 --> 00:11:38.880
question should be answered by evidence
at the appropriate scale.

08c22c21-921d-43d2-9922-da07cda145a9-0
00:11:38.880 --> 00:11:41.360
And our axis are space.

9ccee5f6-4d97-42ed-b1f9-3c4ba9cad341-0
00:11:41.360 --> 00:11:45.680
It's a log based scale of square
kilometres and time.

264c8f9c-a2de-4bcf-bc84-a2bef2296e9c-0
00:11:45.760 --> 00:11:48.840
They're the same on both in years,
log base scale years.

bab26db1-ec55-4c18-b48a-6037c4a13f79-0
00:11:48.840 --> 00:11:53.522
So something like a fossil site where you
find a fossil, you know,

bab26db1-ec55-4c18-b48a-6037c4a13f79-1
00:11:53.522 --> 00:11:58.694
footprint or something or some fossils
can answer really local questions,

bab26db1-ec55-4c18-b48a-6037c4a13f79-2
00:11:58.694 --> 00:12:01.280
small scale questions, but important.

1b5cc1c8-da0a-46fc-ac0c-daa8398b9748-0
00:12:01.280 --> 00:12:05.320
What was the paleo environment of a
particular hominin fossil occurrence?

2043d228-e0d9-46d1-a886-4befc81672f2-0
00:12:06.560 --> 00:12:06.840
OK.

8a149214-9d54-416d-9e37-7d712ffc1431-0
00:12:06.840 --> 00:12:10.518
And then you can scale up to longer time
scales about, say,

8a149214-9d54-416d-9e37-7d712ffc1431-1
00:12:10.518 --> 00:12:12.480
macro evolution or biogeography.

7b0cd8ed-9d48-418d-b2bf-d2fd6e0ea23a-0
00:12:12.720 --> 00:12:16.880
But then your scales of evidence need to
also expand.

7e64dc45-8371-452f-a6ed-7db9c0643c9b-0
00:12:16.880 --> 00:12:22.032
So if you want to ask about biogeography,
you should be looking at a base and scale

7e64dc45-8371-452f-a6ed-7db9c0643c9b-1
00:12:22.032 --> 00:12:24.240
something like perhaps this or this.

24d18231-12e5-407b-9c63-f0f0a4140521-0
00:12:24.520 --> 00:12:27.505
OK,
so this is a nice road map that my

24d18231-12e5-407b-9c63-f0f0a4140521-1
00:12:27.505 --> 00:12:32.480
colleague Tyler Faith published telling
us all don't scale jump.

0c5a41f9-ac98-4e49-8aa3-185287127fd7-0
00:12:32.640 --> 00:12:37.244
Don't ask a macro evolutionary question
with, you know,

0c5a41f9-ac98-4e49-8aa3-185287127fd7-1
00:12:37.244 --> 00:12:40.040
a data set that's not appropriate.

76d8aa12-4c85-421a-8971-19ef8002c3c1-0
00:12:40.040 --> 00:12:41.080
It's too small scale.

1732ae2b-857c-411c-91f6-d74aa1d2ca0e-0
00:12:41.200 --> 00:12:44.000
So you can check me on that and make sure
I follow those rules today.

69666980-4750-465f-81f8-b6089b6477fc-0
00:12:45.440 --> 00:12:47.732
OK,
I know all the biologists got out of

69666980-4750-465f-81f8-b6089b6477fc-1
00:12:47.732 --> 00:12:50.864
class this week,
but you still get one very short class

69666980-4750-465f-81f8-b6089b6477fc-2
00:12:50.864 --> 00:12:51.200
today.

2cdbd014-5e0b-40ab-b336-c1b361465191-0
00:12:51.200 --> 00:12:52.200
It's like 3 sides long.

c5eb1cda-8fd0-412e-b019-94031debaf8b-0
00:12:52.280 --> 00:12:53.640
It's called hominins, one O 1.

5bb149f8-8f37-4a9b-82b8-062fa876ac6b-0
00:12:55.080 --> 00:12:59.880
This is the fossil record of the hominin
lineage.

2cf35314-7911-4eb4-a392-43cd2c473656-0
00:12:59.880 --> 00:13:04.583
It's the Hominini, our tribe in the group,
or the family Hominidae,

2cf35314-7911-4eb4-a392-43cd2c473656-1
00:13:04.583 --> 00:13:09.080
which includes great apes and us,
so Gorillaz, chimps, etcetera.

0a7b2f2b-6937-4276-b1b1-fb7273e42cd8-0
00:13:10.960 --> 00:13:15.440
The earliest purported hominins stretch
back to about 7,000,000 years.

61614c18-f5a6-4399-9b72-4c69c0cfcf39-0
00:13:15.440 --> 00:13:20.086
It's Sahelanthropus chadensis from
central Africa, from Chad,

61614c18-f5a6-4399-9b72-4c69c0cfcf39-1
00:13:20.086 --> 00:13:24.357
Auroran tuganensis from central Kenya,
and Artapithecus,

61614c18-f5a6-4399-9b72-4c69c0cfcf39-2
00:13:24.357 --> 00:13:27.880
Cadaba and Ramidus from the Awash in
Ethiopia.

2a356e44-0582-4d09-bc4d-97240b0d890c-0
00:13:28.400 --> 00:13:35.674
OK, these are relatively small hominins,
small brain, small body, short limbs,

2a356e44-0582-4d09-bc4d-97240b0d890c-1
00:13:35.674 --> 00:13:37.240
probably bipedal.

8906b0b0-b137-4d45-8dc6-c6fa5fea5deb-0
00:13:37.240 --> 00:13:41.324
We think most of them were bipedal,
meaning walking on 2 legs,

8906b0b0-b137-4d45-8dc6-c6fa5fea5deb-1
00:13:41.324 --> 00:13:44.760
but we're able to climb much better than
we can, OK.

4ae71d4b-5609-494a-b9b6-0229ac19f69b-0
00:13:44.760 --> 00:13:50.313
And then we have the australopithecenes
here coming on the scene around 44.34.

4ae71d4b-5609-494a-b9b6-0229ac19f69b-1
00:13:50.313 --> 00:13:51.720
2 million years ago.

82c85e9b-6be6-471d-982f-daa607026705-0
00:13:51.720 --> 00:13:57.800
And here, this one, afarensis,
Australopithecus afarensis is Lucy.

89699e63-2966-4723-9d4e-7f2d734dd1d0-0
00:13:57.800 --> 00:14:02.119
Lucy's 50 years old this year,
was discovered in 1974 at Haddar by Don

89699e63-2966-4723-9d4e-7f2d734dd1d0-1
00:14:02.119 --> 00:14:03.640
Johansson and colleagues.

d7ad15cd-342b-4547-870d-67471b1ec551-0
00:14:05.080 --> 00:14:09.368
And then this is where you get the split
and and remember the how incomplete the

d7ad15cd-342b-4547-870d-67471b1ec551-1
00:14:09.368 --> 00:14:10.480
fossil record is, OK?

3be6627e-4086-4eff-9cc2-2efcebde00a7-0
00:14:10.520 --> 00:14:13.360
This is our our sort of the way most
people lay it out.

e471baf0-7ea9-4e89-aeb6-63980d0df41f-0
00:14:14.240 --> 00:14:16.320
And it's grouped into to grades, OK?

d8a8d14f-81fe-4b6f-b6fa-6302076e7a7a-0
00:14:16.320 --> 00:14:20.485
And so there's a grade that goes off to
the right and a grade that goes off to

d8a8d14f-81fe-4b6f-b6fa-6302076e7a7a-1
00:14:20.485 --> 00:14:20.960
the left.

29d2f5c5-9621-4bd8-8fd0-81ac0dbf3238-0
00:14:22.840 --> 00:14:26.959
OK,
And that happens to be Parenthropus and

29d2f5c5-9621-4bd8-8fd0-81ac0dbf3238-1
00:14:26.959 --> 00:14:27.240
us.

b4893512-2222-4bbf-b572-8a95b0630a9e-0
00:14:27.280 --> 00:14:29.840
OK, We're way up here, right?

cbcca6f5-38c8-4ea9-b5bc-79bf350bbe7a-0
00:14:32.000 --> 00:14:34.000
This is a parenthesis skull.

a562b5c7-26f8-4619-9db0-ad10a80a00f2-0
00:14:34.000 --> 00:14:38.271
These two are parenthesis skulls in the
most defining feature is the sagittal

a562b5c7-26f8-4619-9db0-ad10a80a00f2-1
00:14:38.271 --> 00:14:38.600
Crest.

ed85bce2-12de-4008-aab0-3409b7da38bc-0
00:14:38.600 --> 00:14:40.280
There you can see, right.

091a8638-ec1f-4f3c-8a97-aa5e32b4db8c-0
00:14:40.280 --> 00:14:43.833
So if you saw like, you know,
Homo erectus walking down the street,

091a8638-ec1f-4f3c-8a97-aa5e32b4db8c-1
00:14:43.833 --> 00:14:48.014
you probably just walk by be like, OK,
but if you saw one of these walking down

091a8638-ec1f-4f3c-8a97-aa5e32b4db8c-2
00:14:48.014 --> 00:14:50.783
the street,
it would be you would turn your head and

091a8638-ec1f-4f3c-8a97-aa5e32b4db8c-3
00:14:50.783 --> 00:14:53.240
stop and stare because they're very
different.

7d672642-79ab-41ae-8f5d-c73fafe2f796-0
00:14:53.240 --> 00:14:53.520
They were.

351066d6-06d0-42e5-a832-c1614da469ab-0
00:14:53.720 --> 00:14:55.320
Well, I'll go,
I'll show you the next couple of slides.

da9fda95-b56b-4c37-96a0-0a4d84a9ddf9-0
00:14:55.320 --> 00:14:59.000
But morphologically they were very
different than us.

4510cc07-4eb5-4f6c-8d5e-fd4cee7fdc7b-0
00:14:59.000 --> 00:15:00.520
You would not mistake them for us.

9bcf4805-c625-4e5b-b44c-efc452a43e7a-0
00:15:00.520 --> 00:15:06.623
Whereas something like Homo erectus or
**** regaster, you might OK,

9bcf4805-c625-4e5b-b44c-efc452a43e7a-1
00:15:06.623 --> 00:15:11.560
see we're already in the next course
hominids one O 2.

69147ee6-1aab-44d3-b066-847dced4071d-0
00:15:13.800 --> 00:15:17.137
So plotted here,
we have age from three million years ago

69147ee6-1aab-44d3-b066-847dced4071d-1
00:15:17.137 --> 00:15:19.440
to present on the X axis and two Y axis.

9e9036fe-6ac5-410a-a6e1-56a4fd013121-0
00:15:19.440 --> 00:15:21.040
This is probably the easiest one to look
at.

d0da8f49-2aa9-4298-a25b-631d5d76796b-0
00:15:21.040 --> 00:15:25.160
This is brain size,
endocranial volume in cubic centimeters.

12ca0417-d224-4198-93b8-5629a287b732-0
00:15:25.160 --> 00:15:28.560
So whoever just won that water bottle,
can you hold it up?

c89e5f27-6790-4f33-8416-c6e8bb1993c5-0
00:15:33.920 --> 00:15:35.760
OK, so that's one litre that's here.

70550fcf-3c22-416e-ab00-994d5d32f8c2-0
00:15:36.200 --> 00:15:39.480
It's not so far from the size of our
brains today.

8774c3f7-24f2-437c-b964-88b6fc5d4fc2-0
00:15:39.640 --> 00:15:46.276
The the total volume 1.2 litres or so,
1200 CCS and here's parenthesis in

8774c3f7-24f2-437c-b964-88b6fc5d4fc2-1
00:15:46.276 --> 00:15:48.160
circles through time.

22f79364-dbcb-4137-a180-3976e593db98-0
00:15:48.200 --> 00:15:53.560
And here's the **** lineage through time
in terms of brain size.

4d67ac2d-4120-48be-95e5-03f2bca8621f-0
00:15:53.560 --> 00:15:56.720
So you can see there's 22 relatively
different trends.

6502f77f-2712-4474-8896-f02b2c90c107-0
00:15:57.200 --> 00:16:00.415
OK,
there's this is parenthesis increase in

6502f77f-2712-4474-8896-f02b2c90c107-1
00:16:00.415 --> 00:16:04.800
brain size going from somewhere in 400
maybe to 5 or 600CC.

720e39c5-8d8f-447e-9deb-90cbc26626eb-0
00:16:05.360 --> 00:16:09.968
And then here's us starting at around 600
and and sky rocketing up essentially

720e39c5-8d8f-447e-9deb-90cbc26626eb-1
00:16:09.968 --> 00:16:10.960
doubling in size.

8aae06d0-a35e-4ff9-8792-675ca5f8dce8-0
00:16:11.520 --> 00:16:14.720
OK, so big brains win.

e878cecc-4b83-4187-a33c-aa2dd85ae7d4-0
00:16:14.720 --> 00:16:15.560
Obviously we're here.

96d680de-dfdf-4366-84db-f6168b1003f1-0
00:16:15.560 --> 00:16:15.960
They're not.

0f4a1c2d-99ac-45da-a7cc-ae7f5d9eea44-0
00:16:16.600 --> 00:16:17.120
I'm kidding.

796adedb-9c17-4435-9b60-a1631183fca9-0
00:16:17.120 --> 00:16:18.280
That's a simplified version.

ff4a2113-3161-4ebe-92bc-2d5f0d6582f9-0
00:16:18.720 --> 00:16:22.586
And then on the right here we have the
the body plans and again I mentioned

ff4a2113-3161-4ebe-92bc-2d5f0d6582f9-1
00:16:22.586 --> 00:16:24.520
parenthesis is very different looking.

4082af76-fc1d-45f3-b2a6-2a9831959251-0
00:16:24.520 --> 00:16:28.239
It has it's much shorter and it has this
sort of flared rib cage, OK,

4082af76-fc1d-45f3-b2a6-2a9831959251-1
00:16:28.239 --> 00:16:31.480
where ours is more narrower,
it's different in the pelvises.

79bfcf08-6c36-4025-8c7a-6ad35f2c3bb1-0
00:16:31.960 --> 00:16:36.080
And then the limb bones are very
different.

b976284c-99e4-4da6-9b1a-51f067542ccc-0
00:16:36.080 --> 00:16:38.000
We have much longer legs, right.

1e353e48-4249-4318-ac27-f47bc4b6d016-0
00:16:38.000 --> 00:16:39.120
Look at the femurs there.

3699aa83-9572-497c-893c-80069f7a7581-0
00:16:39.400 --> 00:16:39.680
OK.

75eb5f49-2403-4c36-a04c-8ecf98d242a5-0
00:16:40.760 --> 00:16:45.389
It's important to note that the bones
that have been found for parenthesis that

75eb5f49-2403-4c36-a04c-8ecf98d242a5-1
00:16:45.389 --> 00:16:49.440
have been really connected to that
species post cranial are very few.

802547ed-6c1c-4360-8a86-529cb8aa7a61-0
00:16:49.440 --> 00:16:52.640
They're shown in the sort of shaded
sections there.

0f5f0167-c351-4c0c-896a-974f9a447fd6-0
00:16:53.120 --> 00:16:57.084
So and because **** and Parenthropus were
around at the same time,

0f5f0167-c351-4c0c-896a-974f9a447fd6-1
00:16:57.084 --> 00:17:01.109
if you find an isolated bone,
it's hard to say which which genus it

0f5f0167-c351-4c0c-896a-974f9a447fd6-2
00:17:01.109 --> 00:17:01.760
belongs to.

dd0cf433-cdcd-47f5-9b97-0b45f71846bb-0
00:17:02.840 --> 00:17:06.200
OK,
so here's a quick summary of Parenthropus.

9531a929-4e3f-428c-bb43-aada13171610-0
00:17:07.200 --> 00:17:08.560
And I think if I do this.

9af93371-97e1-4e41-b84e-ee308f7f461b-0
00:17:09.720 --> 00:17:12.920
OK, so here's the skull,
here's the sagittal Crest.

80d10b69-f5b9-49a4-81b5-71f11400a1ae-0
00:17:13.240 --> 00:17:18.930
OK, And as the the 3D rendering rotates,
I want you to notice how flat and and

80d10b69-f5b9-49a4-81b5-71f11400a1ae-1
00:17:18.930 --> 00:17:24.189
prognathic or slope the faces,
OK compared to us where our face is very,

80d10b69-f5b9-49a4-81b5-71f11400a1ae-2
00:17:24.189 --> 00:17:28.367
very flat, OK,
It also has this huge zygomatic arch here,

80d10b69-f5b9-49a4-81b5-71f11400a1ae-3
00:17:28.367 --> 00:17:28.799
right?

d0668519-181b-4623-99be-a8784f7ca2dc-0
00:17:29.040 --> 00:17:33.544
So there's some morphological differences
that I'll explain why we think they were

d0668519-181b-4623-99be-a8784f7ca2dc-1
00:17:33.544 --> 00:17:36.148
there,
but a very different skull compared to a

d0668519-181b-4623-99be-a8784f7ca2dc-2
00:17:36.148 --> 00:17:36.799
human skull.

ca88af0c-a097-4d78-bf82-e75e110579e1-0
00:17:37.480 --> 00:17:42.320
OK, with the teeth,
I'm going to now focus on the jaw.

1fa04905-f273-49e6-b2fc-5c4bf0f04ecf-0
00:17:42.360 --> 00:17:46.960
The lower jaw here,
it has an incredibly robust mandible.

d6a47285-3709-4c2a-9bfa-4c17ef00daf0-0
00:17:47.440 --> 00:17:51.680
The Bony structure here is very thick and
tall and wide.

3ba2acb9-5ac8-4109-b7ac-54aeda044411-0
00:17:52.440 --> 00:17:55.960
And then the most remarkable thing are
the teeth, OK,

3ba2acb9-5ac8-4109-b7ac-54aeda044411-1
00:17:55.960 --> 00:18:01.176
so that these huge flat teeth and even
the premolars here have become molarised

3ba2acb9-5ac8-4109-b7ac-54aeda044411-2
00:18:01.176 --> 00:18:05.480
or inflated so that you have this huge
amount of chewing surface.

1fcf9df4-aee8-490b-9f91-9b1032d82d51-0
00:18:05.480 --> 00:18:07.960
So everybody look at your thumb.

70783849-64fc-4f2d-b77a-adc963a95453-0
00:18:08.760 --> 00:18:11.915
OK,
so that's about the size of the occlusal

70783849-64fc-4f2d-b77a-adc963a95453-1
00:18:11.915 --> 00:18:15.000
or chewing surface of a Pyranthropis
molar.

70672e25-1b8d-4f64-a249-d4a07ffeaa9b-0
00:18:15.320 --> 00:18:16.280
OK, now look at your pinky.

7b1f4ec8-5dca-451a-8f43-310d3615d021-0
00:18:16.280 --> 00:18:18.560
Put it next to it like this.

7c3b0f5c-1dad-495b-9762-195439b90f97-0
00:18:18.560 --> 00:18:22.160
And that's about the size of your average
molar in a human.

c28e278a-31d2-409a-985e-52687dc9cc89-0
00:18:22.320 --> 00:18:27.640
So massive, massive teeth, thick enamel,
very, very thick enamel.

8c67f56d-1458-4482-9540-303131f6c270-0
00:18:28.040 --> 00:18:30.400
And so the question is,
why did they have these teeth?

17e1fd0d-6d71-4e7d-b1da-cbb41e710e44-0
00:18:31.120 --> 00:18:32.560
It's been a question since the beginning.

efe868db-71c5-44fe-8191-3c518cfe8c70-0
00:18:33.720 --> 00:18:37.520
So and Speaking of which,
the beginning is in 1938.

85a5a3fb-ba94-4952-96d3-d910d32313c2-0
00:18:37.720 --> 00:18:42.073
Parenthesis robustus,
so same genus but from South Africa was

85a5a3fb-ba94-4952-96d3-d910d32313c2-1
00:18:42.073 --> 00:18:44.040
discovered at Crom Dry Cave.

07ae9d15-713e-4478-9da8-c5380cff659f-0
00:18:44.560 --> 00:18:46.440
It's around 2.2 to 2.1 million years.

cd7cc229-5d17-4ab0-a5aa-1c0690917f26-0
00:18:46.440 --> 00:18:50.989
It's a pretty limited window and we don't
actually know the phylogenetic

cd7cc229-5d17-4ab0-a5aa-1c0690917f26-1
00:18:50.989 --> 00:18:51.800
relationship.

d635eb7e-7537-4ece-bd88-0e90ebfe5a7d-0
00:18:51.800 --> 00:18:56.322
They're in the same genus that people
argue if they're if it's convergent

d635eb7e-7537-4ece-bd88-0e90ebfe5a7d-1
00:18:56.322 --> 00:19:00.172
evolution, you know,
the large teeth and the sagittal Crest of

d635eb7e-7537-4ece-bd88-0e90ebfe5a7d-2
00:19:00.172 --> 00:19:03.962
the South African robustness versus the
East African species,

d635eb7e-7537-4ece-bd88-0e90ebfe5a7d-3
00:19:03.962 --> 00:19:06.039
which are athiopicus in Boise Eye.

60261bc0-9561-4648-bd4b-c5f85d7a0a92-0
00:19:06.720 --> 00:19:11.440
So athiopicus is the first it was around
about 2.62 point 3,000,000 years ago.

bc7fec45-e947-46cc-8950-327e7fdeb0d7-0
00:19:12.040 --> 00:19:14.349
And then Boise Eye is the the younger
variant,

bc7fec45-e947-46cc-8950-327e7fdeb0d7-1
00:19:14.349 --> 00:19:16.560
which was around for almost a million
years.

af7f9042-5631-4860-ae62-cf2540533953-0
00:19:16.560 --> 00:19:17.360
Pretty long run.

5710c69d-1dc5-47d4-b7da-2a36f6928bc3-0
00:19:17.680 --> 00:19:19.920
We've only been here 300,000 years humans.

bb7afe3d-41f9-4599-b006-500319672a6b-0
00:19:19.920 --> 00:19:25.760
So and this this is AOH 5 discovered by
Mary Leakey at old of Eichorge.

c80c2110-aa7b-444b-ad4e-8405bddb156b-0
00:19:29.920 --> 00:19:34.760
So early diet estimates based on a tooth
morphology structure.

7c381ba8-6e1b-4eed-9e1a-c76ca01e4671-0
00:19:35.080 --> 00:19:39.200
First leaky suggested was carnivorous,
hypercarnivorous.

eb2ce884-7710-4280-95b3-5d595e0b1cd2-0
00:19:40.080 --> 00:19:44.146
Then later many thought it was a hard
object feeder and it became known as

eb2ce884-7710-4280-95b3-5d595e0b1cd2-1
00:19:44.146 --> 00:19:44.960
Nutcracker man.

a4f08e96-c58e-4a78-8fd4-2e586a55e6ba-0
00:19:45.320 --> 00:19:48.312
OK,
because seeds and nuts have really high

a4f08e96-c58e-4a78-8fd4-2e586a55e6ba-1
00:19:48.312 --> 00:19:49.400
caloric density.

fb400168-6340-481c-8314-557a105f930f-0
00:19:49.400 --> 00:19:52.560
They're great food,
but it wreaks havoc on your teeth.

0ff0757c-103f-4d28-900c-5c3713b5e1a0-0
00:19:52.560 --> 00:19:54.560
If you've ever chipped tooth,
you know what I'm talking about.

e098c235-294b-428e-ae30-d7404b9b0b71-0
00:19:55.280 --> 00:19:55.560
OK.

f9907730-0576-4664-88bf-6366a6122fce-0
00:19:57.480 --> 00:19:57.840
All right.

c4bf3618-afd3-412e-b522-c371d455f607-0
00:19:58.600 --> 00:19:59.920
So where did parenthesis live?

671f96f7-3859-4e74-90e8-fc1412d4eb7b-0
00:19:59.920 --> 00:20:03.160
Yeah, that's the root.

9a31654f-897e-49eb-b8fc-e45e764e1ec4-0
00:20:03.160 --> 00:20:04.080
It's showing the root.

6b3d7b5d-a71a-4f41-9882-d6fc629b1939-0
00:20:04.520 --> 00:20:04.880
Yeah.

e9de5c41-d3be-4a38-8e09-fb7c46feafb2-0
00:20:05.040 --> 00:20:06.120
They just have really deep roots.

03a6a3c6-235d-499c-a565-184b6db0bd1e-0
00:20:06.120 --> 00:20:07.040
Ours have pretty deep roots.

f7a7e5a8-2f7c-4f16-953d-6914b938fc57-0
00:20:07.040 --> 00:20:07.480
Not that deep.

c325efae-057c-4df7-9f34-4f73a889bd14-0
00:20:07.480 --> 00:20:07.960
Not that deep.

89376a9c-e1f1-4522-a4fc-998bd60ae115-0
00:20:08.240 --> 00:20:08.480
Yeah.

dc83b502-53b5-4bfd-81ec-fbf3f70b1278-0
00:20:08.680 --> 00:20:09.720
So it's very deeply rooted.

abe21587-0bd2-44c0-949c-3032e01763ca-0
00:20:09.840 --> 00:20:11.360
Everything's robust about these things.

2d4af3d9-dc17-47a6-916d-a1c3f3dea10b-0
00:20:12.240 --> 00:20:13.520
They're called megadon.

d3ee3e03-e54c-445b-abd4-42888b3a5237-0
00:20:13.520 --> 00:20:14.320
So big teeth.

a35b6681-8eb6-4e1d-8cbb-c56603a31453-0
00:20:14.640 --> 00:20:17.720
It's called the megadon clade or grade of
hominid.

f8affb6a-f0f6-4bc7-88fd-418a4f0ce929-0
00:20:17.720 --> 00:20:19.600
OK, so where did parenthesis live?

a782f897-b0dd-4d05-b69f-d277b3693c45-0
00:20:19.600 --> 00:20:23.720
These are sites where we have found
parenthesis fossils.

d9375563-1b19-409f-9596-e67c4c3343ea-0
00:20:23.720 --> 00:20:24.440
So here's.

24d699ef-c541-441b-a1d4-0c280b5b6007-0
00:20:26.120 --> 00:20:30.283
Southern in Tanzania and southern Kenya,
old Avai, Laitoli,

24d699ef-c541-441b-a1d4-0c280b5b6007-1
00:20:30.283 --> 00:20:32.920
Peninch and then moving up into Kenya.

b137e3cf-b612-4eea-abc8-bd1f8f796a77-0
00:20:33.440 --> 00:20:33.960
Interesting.

860a2c3e-b5c1-4e29-84ba-5b5099b5d10f-0
00:20:33.960 --> 00:20:36.200
It's never been found in Ethiopia.

86f32f47-e384-47f4-966b-e55fb30f9493-0
00:20:36.240 --> 00:20:37.960
Highly, highly fossiliferous.

f5834fc9-79dd-45d0-bffb-f0b373fa1559-0
00:20:37.960 --> 00:20:41.277
That's where you know,
lots of Lucy like things have been found

f5834fc9-79dd-45d0-bffb-f0b373fa1559-1
00:20:41.277 --> 00:20:43.040
and many, many early **** fossils.

c8e800d3-4fc6-4e9b-81b1-fa7b47ae4310-0
00:20:43.080 --> 00:20:46.480
Oldest ***** from up here,
but it stretches all along the Rift

c8e800d3-4fc6-4e9b-81b1-fa7b47ae4310-1
00:20:46.480 --> 00:20:48.640
Valley, even down all the way to Malawi.

ecb63755-d784-4137-913a-0db346a2fbdd-0
00:20:48.640 --> 00:20:52.240
This is a key site found in the 90s that
expanded the range.

7dccb7c8-f745-48f0-a6aa-9ff4e0aca195-0
00:20:52.720 --> 00:20:54.280
Remember that earlier plot of where?

773172b0-f12a-4261-8ede-47552de162b2-0
00:20:54.280 --> 00:20:55.680
Where were these hominids living?

b253e8a1-a6c7-4b71-a1bd-bcd5b7bd2b05-0
00:20:56.800 --> 00:20:59.360
Way far South to the southern rift.

dceccc18-c45e-4c60-92e5-6df23ba39d5c-0
00:20:59.600 --> 00:21:02.840
OK, so yeah, again,
where did Paranthropus really live?

255c2001-f4d1-43ac-8fe1-f83e613c2cdb-0
00:21:03.960 --> 00:21:05.000
Maybe we don't know yet.

37a1b5d9-9f5e-4ea0-8d5d-860a73ebde2b-0
00:21:05.000 --> 00:21:08.520
People are really confused why it's never
been found here.

732a6b46-a05c-4810-b46a-64639043390c-0
00:21:08.520 --> 00:21:10.200
Was there a biogeographic barrier?

3be6108b-1595-43cb-a993-bb1726d2ed9e-0
00:21:10.200 --> 00:21:11.560
The environment not right?

957c5f3f-bc47-4293-a306-c7335b6b1b8b-0
00:21:11.560 --> 00:21:12.120
We don't know.

20025b21-cdf5-4936-82a8-6a31048aa5e0-0
00:21:12.520 --> 00:21:13.920
Or did we just not found the fossils?

9f994ca1-141f-4cdc-b4e1-0cb6772ce5e9-0
00:21:14.160 --> 00:21:19.066
And then most recently, this last fall,
a new Paranthropis site was discovered

9f994ca1-141f-4cdc-b4e1-0cb6772ce5e9-1
00:21:19.066 --> 00:21:21.800
here on the Houma Peninsula,
Lake Victoria.

0dae5774-3562-492c-b2f6-25e5c720fe9c-0
00:21:22.240 --> 00:21:25.160
It extended the age back to 2.
8 million years.

ab5e0a43-2dcb-4bc1-9787-a277b805f500-0
00:21:25.440 --> 00:21:28.160
So I have to update that previous slide
and the range.

259fe0ac-22a5-4391-96db-5f4117021f5e-0
00:21:28.240 --> 00:21:30.040
OK, so these things are always changing.

b4ec3286-e316-414f-990f-b32a3cea8a96-0
00:21:30.160 --> 00:21:30.440
Yeah.

899b9970-d11a-4295-8e14-885799c30d36-0
00:21:31.360 --> 00:21:36.498
I was just wondering if you're not going
to know what the the ranges of time are

899b9970-d11a-4295-8e14-885799c30d36-1
00:21:36.498 --> 00:21:37.640
for T1 through T4.

aaaed662-67f3-4099-b07d-b2eec8122557-0
00:21:37.800 --> 00:21:39.040
Oh, it's just hypothetical.

c46030ac-d71a-40d2-a6fb-8723452a4699-0
00:21:39.200 --> 00:21:43.940
It's like an exercise in what what is
what do we actually know and what really

c46030ac-d71a-40d2-a6fb-8723452a4699-1
00:21:43.940 --> 00:21:44.480
happened?

3fa167f5-e1d5-4ade-a52f-32f53e40b716-0
00:21:44.960 --> 00:21:45.920
Yeah, good question.

cca5b19c-9cb3-431b-80c3-2dc05d9102f1-0
00:21:46.160 --> 00:21:48.599
OK,
So why should we be studying our interest

cca5b19c-9cb3-431b-80c3-2dc05d9102f1-1
00:21:48.599 --> 00:21:50.720
in the diets of these things or even us?

b0f591f6-b8d5-4ee1-92a2-6824e62631f7-0
00:21:51.280 --> 00:21:53.474
OK, well,
animals interact most of their

b0f591f6-b8d5-4ee1-92a2-6824e62631f7-1
00:21:53.474 --> 00:21:55.240
environment when they're feeding.

1362e5e7-e549-4373-977b-42f58350b5a4-0
00:21:55.240 --> 00:21:58.671
So there's a lot of information about
their ecology through their feeding

1362e5e7-e549-4373-977b-42f58350b5a4-1
00:21:58.671 --> 00:22:01.640
habits, how much time they spend,
where they go, what they eat.

d6e0274d-9c87-44e3-a257-922f29f73c3e-0
00:22:02.920 --> 00:22:04.720
Is it a seasonal available resource?

e9c68c26-6317-4892-9f01-b46b19e8091a-0
00:22:04.760 --> 00:22:05.920
Is it available year round?

c0c05445-e3f7-4565-8bf9-98901659869f-0
00:22:07.120 --> 00:22:10.285
And from that we can begin to ask,
in the case of us,

c0c05445-e3f7-4565-8bf9-98901659869f-1
00:22:10.285 --> 00:22:13.920
and I showed this earlier,
the encephalization of the massive

c0c05445-e3f7-4565-8bf9-98901659869f-2
00:22:13.920 --> 00:22:17.320
expansion of our brains,
did diet lead to our big brains?

11ec33e8-1371-4b7c-929d-514879782214-0
00:22:18.120 --> 00:22:23.461
The answer is almost decidedly yes,
because the brain is a really expensive

11ec33e8-1371-4b7c-929d-514879782214-1
00:22:23.461 --> 00:22:27.960
tissue or organ to run,
and we need a lot of calories for that.

a802aa10-7b3b-4615-b1f0-b4c03e62632b-0
00:22:29.480 --> 00:22:29.800
OK.

3ebf5364-14c0-4611-a0b0-3e939b7a5d83-0
00:22:30.920 --> 00:22:33.925
Also,
diet informs us about what's available,

3ebf5364-14c0-4611-a0b0-3e939b7a5d83-1
00:22:33.925 --> 00:22:37.910
what's on the menu,
Habitat resources gives us some idea for

3ebf5364-14c0-4611-a0b0-3e939b7a5d83-2
00:22:37.910 --> 00:22:38.759
niche breath.

a20829aa-05fa-4172-9a45-1f784cbffb91-0
00:22:38.760 --> 00:22:43.877
So what this whatever Organism can eat or
survive on and is it competing with other

a20829aa-05fa-4172-9a45-1f784cbffb91-1
00:22:43.877 --> 00:22:45.400
things in that ecosystem.

62c81035-e176-43c1-bef0-92849136931b-0
00:22:47.640 --> 00:22:50.864
It can inform us about how food drives
selection of dental phenotypes,

62c81035-e176-43c1-bef0-92849136931b-1
00:22:50.864 --> 00:22:53.680
thicker enamel versus thinner enamel,
big teeth, small teeth.

2b2d3c1f-968c-4d3e-8545-14a54f49e158-0
00:22:54.600 --> 00:22:59.585
And an important point is that fossil
teeth provide a record of diet in in many

2b2d3c1f-968c-4d3e-8545-14a54f49e158-1
00:22:59.585 --> 00:23:00.520
different ways.

85b04de3-428a-45cd-8dd7-0832a8c8edd6-0
00:23:02.600 --> 00:23:06.980
OK,
so here's here's some examples of how we

85b04de3-428a-45cd-8dd7-0832a8c8edd6-1
00:23:06.980 --> 00:23:08.440
can study diet.

2bbb0c59-2f72-4cc3-a063-459e131f16d2-0
00:23:10.080 --> 00:23:12.886
And the important thing is that the
morphology of the shape,

2bbb0c59-2f72-4cc3-a063-459e131f16d2-1
00:23:12.886 --> 00:23:16.659
what these early studies were looking at
are recording sort of macro evolutionary

2bbb0c59-2f72-4cc3-a063-459e131f16d2-2
00:23:16.659 --> 00:23:17.120
processes.

5cf716e9-b53e-4526-9d20-41e16fc55277-0
00:23:17.120 --> 00:23:21.480
So those are out here and we've got on
the Y axis time here.

dcaec708-cc68-45e2-ac6e-5d2aab3296dd-0
00:23:21.480 --> 00:23:26.568
So studies of like collecting dung and
things tell us kind of about the last

dcaec708-cc68-45e2-ac6e-5d2aab3296dd-1
00:23:26.568 --> 00:23:30.600
meal or the last few meals,
two things modern ecologists do.

e3846be7-5c72-4080-a1e7-8a307558481c-0
00:23:31.040 --> 00:23:33.560
Or you can look at stomach contents or
field observations.

5263c624-89f0-4ed6-ace5-02696e4ef6dd-0
00:23:33.560 --> 00:23:35.882
Those operate over the time scale for
like, you know,

5263c624-89f0-4ed6-ace5-02696e4ef6dd-1
00:23:35.882 --> 00:23:37.560
a day to a year or something like that.

24753cfb-4003-40cf-83ec-0545eacb9580-0
00:23:38.560 --> 00:23:41.040
And in the fossil record,
we use a variety of different techniques.

f7f476c1-5e41-456a-9843-40b98296692e-0
00:23:41.040 --> 00:23:44.320
I'll talk about microwave briefly and
stable isotopes.

912d91ed-c3f8-4f27-b36f-e24fa9ed065e-0
00:23:44.320 --> 00:23:47.991
And those span years,
centuries of Millennium because we have

912d91ed-c3f8-4f27-b36f-e24fa9ed065e-1
00:23:47.991 --> 00:23:50.360
the advantage of looking into deep time.

3b5194d3-438b-494f-b150-57243c269dfd-0
00:23:50.920 --> 00:23:51.200
OK.

0ed7bc0e-f6ae-4845-bd33-af00a4b2ee0d-0
00:23:52.720 --> 00:23:56.844
So the morphology tells us what the
Organism was able to eat,

0ed7bc0e-f6ae-4845-bd33-af00a4b2ee0d-1
00:23:56.844 --> 00:23:59.040
what it long term evolved to eat.

4e60c4dc-ecb7-4d6d-bb34-4bc29453eb9e-0
00:23:59.800 --> 00:24:03.475
But these things like micro wear,
which is the scratches on the surface of

4e60c4dc-ecb7-4d6d-bb34-4bc29453eb9e-1
00:24:03.475 --> 00:24:07.200
the teeth and isotopes give us week to
season to annual scale time windows.

e553106d-f0ed-4483-97c8-d7e374a5c2b5-0
00:24:07.200 --> 00:24:09.544
So it's what it indeed it what it was
really eating,

e553106d-f0ed-4483-97c8-d7e374a5c2b5-1
00:24:09.544 --> 00:24:10.960
not what it was designed to eat.

033cf2b5-25a8-4a6a-8b2e-65f04ff3d0d2-0
00:24:11.200 --> 00:24:12.360
And those don't always match up.

9b2b3253-4347-408a-9375-9b38110321e0-0
00:24:12.960 --> 00:24:14.720
OK, All right.

ac39a8d5-6cac-44c4-8022-7a3acb3d8529-0
00:24:15.000 --> 00:24:19.998
So micro wear tells us about pits and
scratches on a tooth and if you're

ac39a8d5-6cac-44c4-8022-7a3acb3d8529-1
00:24:19.998 --> 00:24:23.080
crushing like a hard object versus
shearing.

5aecc930-34b0-4224-9b56-b98418394611-0
00:24:24.040 --> 00:24:27.720
If you watch a horse or a cow eat,
they do a lot of shearing, right?

4c29c411-a927-40ce-a8c0-1fd8a98256b0-0
00:24:27.840 --> 00:24:29.800
It's sort of like this with the teeth.

fc3f1ad8-0269-4239-a2b9-2e9443392abd-0
00:24:30.880 --> 00:24:31.200
OK.

8f41c063-c9ec-47a5-81f3-998d2fcf763a-0
00:24:31.600 --> 00:24:34.328
And so they,
we've done this microwave analysis,

8f41c063-c9ec-47a5-81f3-998d2fcf763a-1
00:24:34.328 --> 00:24:35.720
we the community, not me.

ca6dcbc9-027c-4816-81a1-69af554c726a-0
00:24:36.560 --> 00:24:39.501
And we look at something called
complexity, which tells us,

ca6dcbc9-027c-4816-81a1-69af554c726a-1
00:24:39.501 --> 00:24:41.560
are they accessing softer or harder foods?

68dba74d-53f2-4572-9398-71605f4dd2f2-0
00:24:42.040 --> 00:24:46.496
And in the case of Parenthropus,
here's the South Africa and robustness,

68dba74d-53f2-4572-9398-71605f4dd2f2-1
00:24:46.496 --> 00:24:51.014
and here's the East Africa and Boise Eye,
they have pretty low complexity

68dba74d-53f2-4572-9398-71605f4dd2f2-2
00:24:51.014 --> 00:24:52.480
suggesting softer foods.

9a00f6cf-7e20-459a-8432-4b910692030c-0
00:24:52.960 --> 00:24:58.265
This was a big surprise and was the first
nail in the coffin for The Nutcracker Man

9a00f6cf-7e20-459a-8432-4b910692030c-1
00:24:58.265 --> 00:24:58.960
hypothesis.

7d70aa6e-ed15-4c1b-bb17-43ceea0ebcf2-0
00:25:00.400 --> 00:25:02.720
And now I'm going to move into stable
isotope methods.

b6d3df6b-87c4-450f-a468-20cae81f01d9-0
00:25:02.720 --> 00:25:07.457
And this is the one slide where you just
need to pay attention for a quick second

b6d3df6b-87c4-450f-a468-20cae81f01d9-1
00:25:07.457 --> 00:25:11.040
because most of the talk is based on this
principle here, OK?

fda309be-86f2-4cd7-ad95-b994d56e7a33-0
00:25:13.320 --> 00:25:17.600
Carbon isotopes are stable isotopes that
exist in nature.

fa1b23e8-f1e3-4e91-98b5-93ce0b716f56-0
00:25:17.600 --> 00:25:19.960
We are all about 1% carbon 13.

edfec2db-7fb6-4467-a42b-5aab5d7f2a68-0
00:25:20.120 --> 00:25:21.120
It's not radioactive.

d213aeee-2a6d-4176-91f0-902ad44a81f0-0
00:25:21.680 --> 00:25:25.202
And the rest of us, carbon 12,
tiny bit of tiny,

d213aeee-2a6d-4176-91f0-902ad44a81f0-1
00:25:25.202 --> 00:25:30.163
tiny bit of carbon 14 in US,
OK in Africa today and over the past 10

d213aeee-2a6d-4176-91f0-902ad44a81f0-2
00:25:30.163 --> 00:25:34.260
million years,
trees and shrubs which produce foods like

d213aeee-2a6d-4176-91f0-902ad44a81f0-3
00:25:34.260 --> 00:25:38.358
leaves, seeds,
fruits and nuts use the C3 photosynthetic

d213aeee-2a6d-4176-91f0-902ad44a81f0-4
00:25:38.358 --> 00:25:42.600
pathway and that has a very distinct
carbon isotope ratio.

d58f33de-63d3-463e-b06c-fa3ab1dba12e-0
00:25:43.280 --> 00:25:46.681
And all grasses, all,
pretty much all lowland grasses in

d58f33de-63d3-463e-b06c-fa3ab1dba12e-1
00:25:46.681 --> 00:25:51.156
Eastern Africa are C4 grasses and they
have a very distinct carbon isotope

d58f33de-63d3-463e-b06c-fa3ab1dba12e-2
00:25:51.156 --> 00:25:55.929
signature and that also includes some
sedges and then their underground storage

d58f33de-63d3-463e-b06c-fa3ab1dba12e-3
00:25:55.929 --> 00:25:57.600
organs like tubers or corns.

193bc596-56ec-4795-9585-40a4d683e7a7-0
00:25:57.760 --> 00:25:57.880
OK.

a29f5792-b599-4b7b-8877-b3390f649b18-0
00:25:58.480 --> 00:26:03.052
So using carbon isotopes,
we can tell something is browsing or

a29f5792-b599-4b7b-8877-b3390f649b18-1
00:26:03.052 --> 00:26:07.480
using eating fruits and nuts from from C3
plants or grasses.

4b5bdb31-c8b5-41be-a4f5-5f51724a4083-0
00:26:07.480 --> 00:26:09.640
There are obviously seeds of grasses,
right?

649d9c08-0a31-44a8-b4cd-dadad37ec39e-0
00:26:09.640 --> 00:26:13.084
We eat them all the time,
but we can differentiate between these

649d9c08-0a31-44a8-b4cd-dadad37ec39e-1
00:26:13.084 --> 00:26:16.687
two food types using isotopes,
and these isotopes are stored in our

649d9c08-0a31-44a8-b4cd-dadad37ec39e-2
00:26:16.687 --> 00:26:20.554
teeth as your teeth form through your
childhood and into your adulthood,

649d9c08-0a31-44a8-b4cd-dadad37ec39e-3
00:26:20.554 --> 00:26:23.840
when you finish forming your wisdom teeth,
so we can go back.

246ca05b-7a69-4b51-9a8f-0a308bba4539-0
00:26:23.840 --> 00:26:28.800
This is a broken fossil tooth of
Australopithecus from Ethiopia.

cae7e13f-553e-4624-b3a6-f3f94761e1c8-0
00:26:29.200 --> 00:26:30.120
Here's the enamel.

600a78da-64cc-4eb8-9b3f-0c18c3e56296-0
00:26:30.120 --> 00:26:32.800
This dark part, when it fossilizes,
it turns dark.

d65da920-c43a-424c-9071-7bd0511c112b-0
00:26:33.320 --> 00:26:37.471
And we just drill here,
remove some powder, put it in a vial,

d65da920-c43a-424c-9071-7bd0511c112b-1
00:26:37.471 --> 00:26:40.686
take it home,
measure the carbon isotope ratio,

d65da920-c43a-424c-9071-7bd0511c112b-2
00:26:40.686 --> 00:26:43.833
and voila,
we have the diet of that particular

d65da920-c43a-424c-9071-7bd0511c112b-3
00:26:43.833 --> 00:26:47.985
hominin from this is 3.
4 million years ago or something like

d65da920-c43a-424c-9071-7bd0511c112b-4
00:26:47.985 --> 00:26:48.319
that.

44bb68e9-ae5f-498a-8bf3-c724ac52e0bc-0
00:26:49.120 --> 00:26:54.384
OK, Carbon tells us about the diet,
the proportion of C3 brows to graze that

44bb68e9-ae5f-498a-8bf3-c724ac52e0bc-1
00:26:54.384 --> 00:26:57.120
was in it, and oxygen tells us about it.

3a9bbcb4-50fd-4255-b8b3-edc81f3724ac-0
00:26:57.120 --> 00:26:58.920
Body water, it's environment.

c4b90af2-fd92-433f-8b66-8f34dadd5ef9-0
00:26:59.080 --> 00:27:02.680
OK, so you are what you eat and drink.

8a79ce0e-c8eb-48d6-a59b-899333a92a57-0
00:27:04.320 --> 00:27:08.411
OK,
so now we're going to dive into some data

8a79ce0e-c8eb-48d6-a59b-899333a92a57-1
00:27:08.411 --> 00:27:11.880
from northern Kenya, southern Ethiopia.

280a6fe9-dd72-4049-9bfa-d2d9a3111fa4-0
00:27:11.880 --> 00:27:16.480
This is the Turkana Basin where the Leaky
family worked for many, many decades.

8e03942b-94d2-4296-bb99-26e6eb2db4b4-0
00:27:16.480 --> 00:27:18.320
They're still active, in fact,
Louise Leaky.

be3d6330-92cc-40dd-aa8c-e81e5556e2a5-0
00:27:19.440 --> 00:27:22.477
And there are three main geological
formations here,

be3d6330-92cc-40dd-aa8c-e81e5556e2a5-1
00:27:22.477 --> 00:27:27.120
the Shingura and Nachikui Niku before,
and they're all pretty much the same age.

70d2a9c9-dbad-4024-a00c-79522c3096c4-0
00:27:27.120 --> 00:27:30.480
They just have different names because
they're far apart from each other.

1e206dda-86b9-4b57-86cd-f29dd73c555f-0
00:27:30.480 --> 00:27:32.911
But at some point,
some geologists realized, hey,

1e206dda-86b9-4b57-86cd-f29dd73c555f-1
00:27:32.911 --> 00:27:34.760
wait a minute, these are all the same.

11639565-20a1-425f-a28f-4a3cc58cc74d-0
00:27:34.760 --> 00:27:35.640
They're tied together.

f61e5adf-1009-4a40-b32f-11ca425e9cfd-0
00:27:36.120 --> 00:27:40.754
We still call them by different names,
but they they all represent the same time

f61e5adf-1009-4a40-b32f-11ca425e9cfd-1
00:27:40.754 --> 00:27:44.760
period of about four to 1,000,000 years,
key time in human evolution.

4262c4c7-242d-4743-ab61-74cc72909347-0
00:27:45.600 --> 00:27:50.320
And so they were all tied together by
volcanic ash layers.

1e1c740b-7207-4088-9b60-e1dcb0d26c37-0
00:27:50.320 --> 00:27:53.293
So here's the Shingura Formation in the
north,

1e1c740b-7207-4088-9b60-e1dcb0d26c37-1
00:27:53.293 --> 00:27:56.520
the Nachikui in the West could be for in
the east.

4b2afdf1-74f0-4cc5-928c-61ed5a2d31d5-0
00:27:56.920 --> 00:28:02.200
And this is the thickness of the outcrops
of the stratigraphic unit compiled.

9fd39c4f-c38e-4782-866e-99d3f43d4b9c-0
00:28:02.200 --> 00:28:07.880
So in the Omo up here, there's about 700,
almost a kilometre thick of sediments.

79f571a9-2ef6-4f6c-ad64-161588fca6b5-0
00:28:07.880 --> 00:28:10.440
And we can date the ashes in the Rift
Valley.

e8f53e57-637c-4a61-8b29-09986f9ca53b-0
00:28:10.520 --> 00:28:12.040
These volcanoes are erupting all the time.

8615dce2-fdcd-468d-a1ea-0321806bf5e1-0
00:28:12.040 --> 00:28:14.640
You can see 3.43 point.

e96fd26b-c696-464b-98e3-5563a4237a81-0
00:28:14.640 --> 00:28:17.360
I can't read that zero or something 1,000,
000 years.

0e55bf52-583b-464a-bbde-77829f4db7b3-0
00:28:17.600 --> 00:28:21.188
But we have a amazing,
amazing age control because of the

0e55bf52-583b-464a-bbde-77829f4db7b3-1
00:28:21.188 --> 00:28:25.520
volcanic activity of the Rift Valley to
precisely date these fossils.

1506b87a-cc25-4cbb-b12c-6794ae90d9b8-0
00:28:25.920 --> 00:28:27.920
So we know how old they are very
precisely.

4540ccf6-fb7f-482d-9d92-5e72e0925d51-0
00:28:28.280 --> 00:28:32.745
And we can also tie those volcanic ash
layers because they have chemical

4540ccf6-fb7f-482d-9d92-5e72e0925d51-1
00:28:32.745 --> 00:28:34.520
fingerprints that are unique.

cbd2439d-c076-4da3-9118-876b3973df79-0
00:28:34.840 --> 00:28:38.276
So if we find it here,
we can look for it here and fingerprint

cbd2439d-c076-4da3-9118-876b3973df79-1
00:28:38.276 --> 00:28:38.440
it.

9d084348-9451-45ac-ba95-703204e333c3-0
00:28:38.480 --> 00:28:42.925
And in that way,
these lines tie exact time horizons

9d084348-9451-45ac-ba95-703204e333c3-1
00:28:42.925 --> 00:28:43.680
together.

95f2448f-e965-4531-88af-9af3a0f5af20-0
00:28:44.320 --> 00:28:47.407
And in this way,
we can integrate the entire fossil record

95f2448f-e965-4531-88af-9af3a0f5af20-1
00:28:47.407 --> 00:28:50.600
of this whole basin and ask questions
about human evolution.

04cec0fe-4153-49be-afe6-04680bd6ac1e-0
00:28:50.600 --> 00:28:54.760
So it's the richest hominin record in all
of eastern Africa.

44dad065-90b2-4a44-ba4b-8fad5d04f539-0
00:28:55.080 --> 00:28:59.971
It's the best dated and people have begun
to notice regional differences whether

44dad065-90b2-4a44-ba4b-8fad5d04f539-1
00:28:59.971 --> 00:29:04.440
you're living along a major axial river
on the shoreline of a paleo lake.

04f27678-57af-4955-a188-68f9c11018e0-0
00:29:04.920 --> 00:29:09.320
It's just a wonderful sort of test bed
for evolutionary theory and and study.

8393e7ee-9ca5-4fc3-899b-df6e7a9a62a2-0
00:29:15.560 --> 00:29:19.040
OK,
so about a decade ago we published the

8393e7ee-9ca5-4fc3-899b-df6e7a9a62a2-1
00:29:19.040 --> 00:29:25.515
first data set of hominin diet and it
came from these two formations around the

8393e7ee-9ca5-4fc3-899b-df6e7a9a62a2-2
00:29:25.515 --> 00:29:25.920
lake.

5999d72e-a279-4f65-b6a0-a0fad7143f0c-0
00:29:26.040 --> 00:29:30.520
And here we have age from 4 to 4,000,
000 years to present.

542fb4dc-1aa3-46e7-8985-857126c2cd48-0
00:29:31.080 --> 00:29:33.560
And here we have the the carbon isotope
value.

bd43bcf0-4a63-4292-80e6-504c4efc1f45-0
00:29:33.560 --> 00:29:38.608
But I just put the tree in the grass here
so you know if it's the C3 diet or AC4

bd43bcf0-4a63-4292-80e6-504c4efc1f45-1
00:29:38.608 --> 00:29:38.920
diet.

bcac1c1d-0405-4051-b3d8-82141d238f9b-0
00:29:38.920 --> 00:29:43.640
So leaves, seeds, nuts,
etcetera and grassy.

69e670b3-6558-4c0b-b17c-9f602b54924c-0
00:29:43.840 --> 00:29:44.160
OK.

f8aac44a-d9ab-4029-a033-96f6f8ef502b-0
00:29:44.520 --> 00:29:49.258
And then these are the various hominin
taxa we analyze starting with

f8aac44a-d9ab-4029-a033-96f6f8ef502b-1
00:29:49.258 --> 00:29:52.280
Australopithecus, anemensis,
Kenyanthropus.

c75d4efb-246d-4182-86b1-308b3a77c2f6-0
00:29:52.560 --> 00:29:57.280
And then throughout the talk,
all the purple dots are Parenthropus and

c75d4efb-246d-4182-86b1-308b3a77c2f6-1
00:29:57.280 --> 00:30:02.267
the anything in blue is some blue
diamonds or some variety of of the genus

c75d4efb-246d-4182-86b1-308b3a77c2f6-2
00:30:02.267 --> 00:30:02.600
****.

cf14fe17-93f8-476b-b4fc-7f2467537c4a-0
00:30:03.880 --> 00:30:10.440
So the important takeaways early on this
particular taxon was just eating C3 foods.

a3b994e9-e036-49ac-a367-b2b8f59d24ea-0
00:30:10.800 --> 00:30:15.544
And then when we moved to Kenyanthropus,
suddenly there's a huge increase in the

a3b994e9-e036-49ac-a367-b2b8f59d24ea-1
00:30:15.544 --> 00:30:19.117
breadth of their diet, including C3,
but also mixed feeding,

a3b994e9-e036-49ac-a367-b2b8f59d24ea-2
00:30:19.117 --> 00:30:20.639
combining C3 and C4 foods.

49a04b29-0584-4cf8-b362-475cd6031fdf-0
00:30:20.880 --> 00:30:24.440
So we know that's an an expansion of the
dietary niche.

010c239d-8084-4177-8fb8-34810b9fb654-0
00:30:24.560 --> 00:30:28.169
OK,
Then the record in this part of the basin

010c239d-8084-4177-8fb8-34810b9fb654-1
00:30:28.169 --> 00:30:32.800
is pretty silent between about,
I don't know, 2.8 and 2.2.

42698e19-81a6-4625-9a4c-5a588a39ef00-0
00:30:33.000 --> 00:30:35.160
There's a few fossils,
but there's not a lot.

3f5ae0fe-39dd-487a-8567-4cd73e1590f6-0
00:30:35.160 --> 00:30:36.240
So there's this huge gap.

727da7cc-d767-4e85-8d6e-0afef85292ad-0
00:30:36.280 --> 00:30:38.880
There's a gap here and obviously a huge
gap here.

e024fb8e-d673-4f1d-97ba-1bd7f9f61468-0
00:30:39.240 --> 00:30:41.480
But this is where something interesting
happens.

ac28eb20-ea75-49af-a4a7-6986d3d347df-0
00:30:41.480 --> 00:30:44.859
We go from the Australopithecines to
these two new genera,

ac28eb20-ea75-49af-a4a7-6986d3d347df-1
00:30:44.859 --> 00:30:46.120
Pyranthropus and ****.

475f9976-de01-48ef-b4e2-0ec9a7d5e145-0
00:30:46.520 --> 00:30:51.574
And you can see from the plot there's a
huge amount of dietary difference between

475f9976-de01-48ef-b4e2-0ec9a7d5e145-1
00:30:51.574 --> 00:30:54.040
Parenthropus up here and **** down here.

cfc98375-f05e-4501-a5d2-bae4c7f60a3f-0
00:30:54.040 --> 00:30:55.520
There's very little overlap.

bc5c0269-e575-4480-b9d0-e5f720065e88-0
00:30:55.920 --> 00:30:59.333
So it's almost like they said, OK,
they're at the grocery store and like,

bc5c0269-e575-4480-b9d0-e5f720065e88-1
00:30:59.333 --> 00:31:00.440
you can have that aisle.

3ab7c522-0a5f-48fc-85cf-977f76678e20-0
00:31:00.440 --> 00:31:01.960
I'm going to have this aisle, right?

3d731b38-b37b-45d9-806f-364681667db3-0
00:31:02.000 --> 00:31:03.360
There's niche separation.

a1cefda3-8448-4ee8-ab5f-82f60d9e36ec-0
00:31:04.240 --> 00:31:07.203
OK,
So that was 10 years ago and it was the

a1cefda3-8448-4ee8-ab5f-82f60d9e36ec-1
00:31:07.203 --> 00:31:12.322
first comprehensive data set we had of
hominid diet through time using this

a1cefda3-8448-4ee8-ab5f-82f60d9e36ec-2
00:31:12.322 --> 00:31:13.400
isotopic method.

c5836f2d-8081-4cac-be30-2a177c78f961-0
00:31:17.200 --> 00:31:22.797
In 2020, this group,
John Wynne ET Alt looked at the hominin

c5836f2d-8081-4cac-be30-2a177c78f961-1
00:31:22.797 --> 00:31:28.670
fossils in Ethiopia, same age,
but they really keyed in on this

c5836f2d-8081-4cac-be30-2a177c78f961-2
00:31:28.670 --> 00:31:32.800
phosiliferous region from about 2.7 to 2.
2.

bc600d5c-6eea-422f-b71e-ce96725a2725-0
00:31:32.800 --> 00:31:38.120
So it sort of fills this gap and the
numbers are more or less the same.

5e45264b-34c1-4fa1-954e-6c33dc17b2e2-0
00:31:38.120 --> 00:31:42.318
Sorry, the writing's a little small,
but purple's parenthopis and blue is ****

5e45264b-34c1-4fa1-954e-6c33dc17b2e2-1
00:31:42.318 --> 00:31:45.880
and it suddenly the story is a little bit
more complicated, right?

b1850a80-eb88-4e02-82e5-1d351094462e-0
00:31:45.880 --> 00:31:50.080
You see blue and and purple overlapping,
which you don't really see here.

83fda5a1-3a1c-4faf-b9a9-51ff81e492a2-0
00:31:50.360 --> 00:31:53.452
OK, so it,
this is just so easy story is now

83fda5a1-3a1c-4faf-b9a9-51ff81e492a2-1
00:31:53.452 --> 00:31:55.720
suddenly like complicated, right?

0a79db4f-02aa-4d59-92d5-75340b3a101a-0
00:31:56.480 --> 00:32:00.187
Furthermore,
they did some change point analysis and

0a79db4f-02aa-4d59-92d5-75340b3a101a-1
00:32:00.187 --> 00:32:05.015
found that in general there,
there are some early paranthopenes down

0a79db4f-02aa-4d59-92d5-75340b3a101a-2
00:32:05.015 --> 00:32:08.233
here and **** and then at 2.
4 million years,

0a79db4f-02aa-4d59-92d5-75340b3a101a-3
00:32:08.233 --> 00:32:13.970
they all slid up this dietary scale and
began incorporating much more C4 in their

0a79db4f-02aa-4d59-92d5-75340b3a101a-4
00:32:13.970 --> 00:32:14.320
diet.

ead73f3d-ff49-4a22-af24-af778a3f63c2-0
00:32:14.600 --> 00:32:18.280
So the question is why is there an
environmental driver to that?

0e72f079-36b0-4449-b015-2d40f8271986-0
00:32:19.920 --> 00:32:21.880
OK, so we have these two data sets.

50261f03-4713-4148-a7d4-8e0194587f68-0
00:32:21.880 --> 00:32:25.000
Of course we have to add a third data set.

200d699a-ba56-4b17-9963-4c7ceaeca69b-0
00:32:25.360 --> 00:32:28.638
So in 2019,
I went to the the National Museum in

200d699a-ba56-4b17-9963-4c7ceaeca69b-1
00:32:28.638 --> 00:32:32.920
Ethiopia with my colleagues and it's our
taxi driver every day.

fbc6a07d-27b1-4c30-893f-fa0f1b210f3d-0
00:32:33.920 --> 00:32:37.025
And these are all the hominin fossils,
these isolated teeth,

fbc6a07d-27b1-4c30-893f-fa0f1b210f3d-1
00:32:37.025 --> 00:32:41.200
they don't let you like drill or sample
teeth that are in these beautiful skulls.

225f37f7-95ab-42e1-9251-219a1ae7b018-0
00:32:41.880 --> 00:32:44.640
We, we work on isolated,
generally broken teeth.

840ab15f-1e99-43d0-ac5b-d3ba21d07fcb-0
00:32:45.000 --> 00:32:49.840
Then we can identify the species but are
not morphologically as valuable.

e00f5952-4060-493c-bb0f-f2251868f404-0
00:32:50.160 --> 00:32:50.520
OK.

d36d80ef-337b-4ee5-a087-2bdc9b1d3dc6-0
00:32:50.520 --> 00:32:52.939
And from that previous slide on the
methods,

d36d80ef-337b-4ee5-a087-2bdc9b1d3dc6-1
00:32:52.939 --> 00:32:57.080
we mostly sample broken teeth because we
can see the enamel dent injunction.

b3d7605e-ad48-4321-9e09-4f822b2ee43d-0
00:32:57.080 --> 00:32:59.360
It's just really the right thing for
everybody.

bcb5a3c7-375d-46af-8a97-f3c4ea80745b-0
00:32:59.760 --> 00:33:03.605
Anyway, all these little,
they're like film canisters,

bcb5a3c7-375d-46af-8a97-f3c4ea80745b-1
00:33:03.605 --> 00:33:08.080
if anybody knows what a film can is with
the specimens in them.

7f5f7369-507b-412d-87b7-3262b41b68aa-0
00:33:08.120 --> 00:33:12.951
And so we go and I put on this little
visor that magnifies things and you take

7f5f7369-507b-412d-87b7-3262b41b68aa-1
00:33:12.951 --> 00:33:16.560
a Dremel little tiny dental bit and you
drill some powder.

596f7e90-93cd-4342-a35e-81c19bbb6b03-0
00:33:16.720 --> 00:33:21.904
So we went and drilled, I don't know,
about 80 or 90 teeth of hominids,

596f7e90-93cd-4342-a35e-81c19bbb6b03-1
00:33:21.904 --> 00:33:27.160
but also lots of primates, baboons,
circle pittacoids, all these things.

e916636a-5a6a-477a-9d46-fc57df9421a3-0
00:33:28.400 --> 00:33:31.213
Importantly,
we're also adding something called

e916636a-5a6a-477a-9d46-fc57df9421a3-1
00:33:31.213 --> 00:33:34.437
calcium isotopes,
which tells us about perhaps trophic

e916636a-5a6a-477a-9d46-fc57df9421a3-2
00:33:34.437 --> 00:33:37.310
level,
something that this carbon isotope method

e916636a-5a6a-477a-9d46-fc57df9421a3-3
00:33:37.310 --> 00:33:38.600
doesn't tell us about.

9f17b25f-c6a6-4788-a895-eda3650e20f0-0
00:33:39.640 --> 00:33:44.123
And so our goal was to contextualise
hominidata with herbivore and carnivore

9f17b25f-c6a6-4788-a895-eda3650e20f0-1
00:33:44.123 --> 00:33:44.880
isotope data.

499d049f-46ab-40a8-b403-af0e612dd633-0
00:33:44.880 --> 00:33:48.400
So what everyone else was eating on the
landscape, add new data.

e2b0629d-c9cd-497f-8ae1-b4d3fcbee6ff-0
00:33:48.960 --> 00:33:52.819
And then at the end I'm going to talk
about actually trying to characterise the

e2b0629d-c9cd-497f-8ae1-b4d3fcbee6ff-1
00:33:52.819 --> 00:33:53.640
ecosystem itself.

acb59e9b-89ac-4361-9695-a6d7b37e6d86-0
00:33:55.200 --> 00:34:01.623
OK, so here's our data from this region,
the Omo and again we see that

acb59e9b-89ac-4361-9695-a6d7b37e6d86-1
00:34:01.623 --> 00:34:08.680
Australopithecus had mostly C3 diet,
but varied maybe contracts through time.

6f745899-e137-4714-b52c-f901d8a687f0-0
00:34:08.680 --> 00:34:10.840
The pink shrinks into a narrow vertical
range.

25f493ce-28ad-46ee-becf-d2542ab9a2c8-0
00:34:11.240 --> 00:34:15.860
And again we have this C3 sort of diet
for **** paranthus down here and then

25f493ce-28ad-46ee-becf-d2542ab9a2c8-1
00:34:15.860 --> 00:34:19.160
shifts up here and there's they're all
mixed up still.

bb659bd7-3184-45e8-a83b-1020dc4d7e23-0
00:34:19.520 --> 00:34:26.159
OK, so if we we overlay oh,
and we see as the previous group did the

bb659bd7-3184-45e8-a83b-1020dc4d7e23-1
00:34:26.159 --> 00:34:32.317
same 2.4 million year dietary shift, blah,
blah, blah, yes, OK,

bb659bd7-3184-45e8-a83b-1020dc4d7e23-2
00:34:32.317 --> 00:34:36.839
so now I'm putting all three studies
together.

bee34e9c-3e4d-4913-bfb1-dbbc03f55263-0
00:34:36.840 --> 00:34:38.920
It's a messy plot, right?

4c46dcfa-26cd-4ee5-b0b2-87e52a0f2d1f-0
00:34:40.200 --> 00:34:45.504
The key points are that in the Pliocene,
which is this geological window here, OK,

4c46dcfa-26cd-4ee5-b0b2-87e52a0f2d1f-1
00:34:45.504 --> 00:34:50.362
we see the dietary breath increase and
that's shifting from this particular

4c46dcfa-26cd-4ee5-b0b2-87e52a0f2d1f-2
00:34:50.362 --> 00:34:53.238
taxon,
Australopithecus and emensis to a new

4c46dcfa-26cd-4ee5-b0b2-87e52a0f2d1f-3
00:34:53.238 --> 00:34:57.073
genus, Kineanthropus,
Platyat and Australopitheous and they

4c46dcfa-26cd-4ee5-b0b2-87e52a0f2d1f-4
00:34:57.073 --> 00:34:57.840
have a much.

5b2c2197-bb84-4f7b-b5e5-cffe9cc4b549-0
00:34:57.840 --> 00:35:00.800
So this huge opening up of hominin diets,
that's a key.

082f2a36-9124-4c80-b44d-da1da30b48fb-0
00:35:00.920 --> 00:35:06.476
So a key question is what led to this
massive expansion ecological dietary

082f2a36-9124-4c80-b44d-da1da30b48fb-1
00:35:06.476 --> 00:35:07.440
niche breath.

ffecb995-4faf-467a-8b0e-0ce785e32a1b-0
00:35:08.600 --> 00:35:10.600
We see contraction of the osteopath diet.

0a76af27-18d9-4042-bfa7-66dfe27bc84b-0
00:35:10.600 --> 00:35:14.520
So it goes from really broad,
these dark pink squares to really narrow.

50d8a421-a93d-43c7-bb45-2888e99ab9b8-0
00:35:15.400 --> 00:35:20.227
We see this shift in the Omo and then
eventually we see this niche partitioning

50d8a421-a93d-43c7-bb45-2888e99ab9b8-1
00:35:20.227 --> 00:35:24.753
between paranthropist and **** and they
they take their own aisles of the,

50d8a421-a93d-43c7-bb45-2888e99ab9b8-2
00:35:24.753 --> 00:35:25.840
the grocery store.

a693cc8b-f5d8-4124-88da-2c00e8575fac-0
00:35:27.400 --> 00:35:30.682
OK,
so we have to go back to our handy guide

a693cc8b-f5d8-4124-88da-2c00e8575fac-1
00:35:30.682 --> 00:35:34.840
of are we asking the right questions at
the right scale?

081b9ae7-ab73-4b72-9d94-1f2571a1dec9-0
00:35:34.960 --> 00:35:39.994
And I would say, yes,
we're trying to understand ecosystem

081b9ae7-ab73-4b72-9d94-1f2571a1dec9-1
00:35:39.994 --> 00:35:41.360
change and diet.

aab28693-2b86-4453-9218-43300ad6ef7b-0
00:35:41.720 --> 00:35:43.962
And we're looking at outcrop based
records,

aab28693-2b86-4453-9218-43300ad6ef7b-1
00:35:43.962 --> 00:35:46.358
fossil records being collected over,
you know,

aab28693-2b86-4453-9218-43300ad6ef7b-2
00:35:46.358 --> 00:35:50.080
the fossils we analyse were collected
essentially over the last century.

3953f858-a490-425e-9888-19689a51ef9f-0
00:35:50.080 --> 00:35:53.440
So we're working off the efforts of many,
many people over many, many years.

136bc89c-be1e-4082-9741-e57e1ae2a01b-0
00:35:54.080 --> 00:35:54.440
OK.

b1da31d0-9ce3-47c2-a1c4-cf5bfbf48742-0
00:35:56.400 --> 00:36:01.241
And this particular place in southern
Ethiopia, the Elmo Valley,

b1da31d0-9ce3-47c2-a1c4-cf5bfbf48742-1
00:36:01.241 --> 00:36:02.880
has some fossil sites.

2045a320-bb1e-4971-b7c1-3489705c053c-0
00:36:02.880 --> 00:36:07.280
So fossil collection area might be half
the size of this room, OK.

c3b1801e-2294-4da1-ba7e-17280612f93f-0
00:36:07.560 --> 00:36:08.960
So really, really localized.

23cf37ed-bb45-4dd1-8002-b638f0742423-0
00:36:08.960 --> 00:36:12.390
And in some of these small areas,
we find many, many hominins,

23cf37ed-bb45-4dd1-8002-b638f0742423-1
00:36:12.390 --> 00:36:13.480
relatively speaking.

0a4787a2-61d6-40bc-9afe-421f86f0f303-0
00:36:14.160 --> 00:36:16.680
So we can actually get to a very granular
scale.

384a0531-9201-4cbd-9d47-1937de51fe93-0
00:36:16.680 --> 00:36:19.560
So here I'm plotting the carbon isotope
ratio here.

3cedb410-dd7f-44ba-a0c2-2c40a74a4e76-0
00:36:19.560 --> 00:36:23.560
So this is diet C3 versus C4,
and this is oxygen.

701c93a2-0700-44b3-8aac-84212934b8db-0
00:36:24.400 --> 00:36:26.755
Remember,
this tells us something about their

701c93a2-0700-44b3-8aac-84212934b8db-1
00:36:26.755 --> 00:36:29.880
drinking water, leaf water,
their sort of body water signal.

027f5bb9-0093-465d-b28d-5bb77b637add-0
00:36:31.080 --> 00:36:33.577
And again,
purple and blue represent the two general

027f5bb9-0093-465d-b28d-5bb77b637add-1
00:36:33.577 --> 00:36:34.520
we're interested in.

e9c92dd6-2d73-4455-bf8c-4b8d7b6357cb-0
00:36:34.520 --> 00:36:37.334
And you can see that in carbon space,
they're pretty close,

e9c92dd6-2d73-4455-bf8c-4b8d7b6357cb-1
00:36:37.334 --> 00:36:39.680
and they're almost identical in the
oxygen space.

6af72ea5-5703-4b2f-802f-b7425d63c86e-0
00:36:39.680 --> 00:36:42.960
So pretty similar diets here at a single
site.

6894ddac-a80b-4132-ab13-697c3b2ea0f7-0
00:36:42.960 --> 00:36:45.160
So this is like a single slice of time.

854a2cb6-7f6c-40c1-9eba-7c0a2184536b-0
00:36:46.200 --> 00:36:49.426
It doesn't mean these fossils were or
these hominids were living at the exact

854a2cb6-7f6c-40c1-9eba-7c0a2184536b-1
00:36:49.426 --> 00:36:49.840
same time.

4fb86457-24bd-4dce-bb9b-dcaedff6af8e-0
00:36:50.120 --> 00:36:52.000
The geologic record mixes time up.

d3802e70-a08a-4684-8bf3-f31b17185cde-0
00:36:52.360 --> 00:36:56.390
But let's say this is something like a 10,
000 year time slice,

d3802e70-a08a-4684-8bf3-f31b17185cde-1
00:36:56.390 --> 00:37:01.240
which is really good resolution when you
are 2.3 million years back in time.

2e4e3e82-fbf3-45c0-89fe-ad00372dd0b2-0
00:37:01.640 --> 00:37:01.840
OK.

70c42dfd-74d1-49ef-ad8e-265b3d18b56c-0
00:37:02.160 --> 00:37:04.760
So we can see that there was strong
dietary overlap.

5eefa9e3-72cd-4d7c-a5eb-5612aaf930e0-0
00:37:04.760 --> 00:37:09.834
And that question still remains as to was
there an environmental pressure or change

5eefa9e3-72cd-4d7c-a5eb-5612aaf930e0-1
00:37:09.834 --> 00:37:14.365
in the vegetation or resources available
that pushed all the hominids into

5eefa9e3-72cd-4d7c-a5eb-5612aaf930e0-2
00:37:14.365 --> 00:37:16.480
essentially the same dietary niche?

1fe2cbb6-2435-4f70-927c-7ceda64539b7-0
00:37:18.520 --> 00:37:23.059
OK, So to answer that,
we decided to actually look at the

1fe2cbb6-2435-4f70-927c-7ceda64539b7-1
00:37:23.059 --> 00:37:23.920
vegetation.

000e1d02-81b6-4709-bf62-9b90db6ebb95-0
00:37:23.920 --> 00:37:25.040
What was the vegetation like?

28b6161b-ebd8-4159-8999-ac3c95b4ddcb-0
00:37:25.040 --> 00:37:29.065
So we have to get out of the teeth and
into the ecosystem to understand what the

28b6161b-ebd8-4159-8999-ac3c95b4ddcb-1
00:37:29.065 --> 00:37:29.960
plants were doing.

6b6c89c1-baf7-4a4e-83f1-5e8b191742de-0
00:37:32.120 --> 00:37:36.280
OK, So we went to the Omo,
the place where all these fossils are

6b6c89c1-baf7-4a4e-83f1-5e8b191742de-1
00:37:36.280 --> 00:37:36.600
from.

e15b9387-21ac-420b-9510-d729b70e503d-0
00:37:37.400 --> 00:37:41.600
And these are now biomarkers,
which are molecular plant fossils.

1fb70aa5-94d3-4229-8b35-dc80a6b7c570-0
00:37:41.600 --> 00:37:42.560
And plants die.

a904d425-f8d8-4b58-9639-5e6c5a9206fa-0
00:37:42.600 --> 00:37:46.715
They leave some waxes in the sediment,
just like if you have a jade plant at

a904d425-f8d8-4b58-9639-5e6c5a9206fa-1
00:37:46.715 --> 00:37:48.640
home, you know, they're really waxy.

d1161595-2f0c-477a-85fa-b916eb7cef69-0
00:37:48.720 --> 00:37:53.240
Those waxes actually record whether that
plant is AC-3 or AC4 plant.

ff7c69ea-3182-4c5a-9b08-cb1f0ee02882-0
00:37:53.560 --> 00:37:58.281
So we go and we get these waxes out of
ancient sediments from 4 to 1,000,

ff7c69ea-3182-4c5a-9b08-cb1f0ee02882-1
00:37:58.281 --> 00:37:58.920
000 years.

fb27b5fd-119a-4914-9630-0439087380a6-0
00:37:59.440 --> 00:38:03.555
And just as we did with the teeth,
we can actually reconstruct the amount of

fb27b5fd-119a-4914-9630-0439087380a6-1
00:38:03.555 --> 00:38:05.960
woody to grassy vegetation on the
landscape.

e8223bf2-3c32-4812-9bd7-69ed3d48d7e6-0
00:38:05.960 --> 00:38:12.802
And so each dot is a measurement from the
fossil soil where we take the waxes and

e8223bf2-3c32-4812-9bd7-69ed3d48d7e6-1
00:38:12.802 --> 00:38:19.562
say up here at this particular point the
landscape was about 30% C 4 and 70% C 3

e8223bf2-3c32-4812-9bd7-69ed3d48d7e6-2
00:38:19.562 --> 00:38:20.479
vegetation.

dddc3088-8cfc-4639-94be-43f2a4728e71-0
00:38:20.680 --> 00:38:25.600
So the overall trend you can see is
moving towards more C4 on the landscape.

30db69f7-ffbe-48e2-9a9c-3360f29a5927-0
00:38:27.960 --> 00:38:29.680
These are just histograms where we're
bending.

dd2d6bd5-24f1-435f-82a4-474ffac2d973-0
00:38:29.680 --> 00:38:32.000
It sort of highlights that shift to the
right.

a005966a-f62b-4bd3-9ac1-2bc976c9abcc-0
00:38:32.400 --> 00:38:34.000
OK, we looked at mammal diet.

5b8fae6e-f8c4-4640-a1cc-c0cf3c791aa3-0
00:38:34.000 --> 00:38:36.940
So you know, elephants, pigs, hippos,
rhinos,

5b8fae6e-f8c4-4640-a1cc-c0cf3c791aa3-1
00:38:36.940 --> 00:38:41.030
everything running around and they using
change point analysis,

5b8fae6e-f8c4-4640-a1cc-c0cf3c791aa3-2
00:38:41.030 --> 00:38:46.080
we see there's a shift here at about 2.
7 million years, OK, to more C4 foods.

16b0aac7-236b-4f9c-9abd-f9bf3bdf74e7-0
00:38:47.560 --> 00:38:51.940
And then here's the sort of hominin
lineage structure at this particular

16b0aac7-236b-4f9c-9abd-f9bf3bdf74e7-1
00:38:51.940 --> 00:38:53.320
fossil site in the Omo.

fc9578cf-5fc6-4635-a4c7-9afd19964c44-0
00:38:54.160 --> 00:38:58.861
You have Australopithecus for a while,
then you start to see the Parenthropus

fc9578cf-5fc6-4635-a4c7-9afd19964c44-1
00:38:58.861 --> 00:39:01.876
species come in,
and then **** comes in around 2.

fc9578cf-5fc6-4635-a4c7-9afd19964c44-2
00:39:01.876 --> 00:39:02.720
32 point four.

719c93c1-fbaa-4e30-bfbf-7d05f6a15106-0
00:39:03.160 --> 00:39:05.840
OK,
we'll set some pretty old stone tools

719c93c1-fbaa-4e30-bfbf-7d05f6a15106-1
00:39:05.840 --> 00:39:06.160
here.

696ca7ea-a02e-4193-a754-c81d4d02ff99-0
00:39:08.520 --> 00:39:11.952
OK,
Now we have some enamel data from the

696ca7ea-a02e-4193-a754-c81d4d02ff99-1
00:39:11.952 --> 00:39:16.936
teeth of the hominins,
and we can see that compared to other

696ca7ea-a02e-4193-a754-c81d4d02ff99-2
00:39:16.936 --> 00:39:19.960
herbivores, OK, Or let's say mammals.

3a863433-ccc4-430d-8aba-bf12becd0b58-0
00:39:19.960 --> 00:39:22.280
We don't know if these were herbivores or
not yet.

0a18a708-7efe-4b0e-907e-ed7460872b6c-0
00:39:23.000 --> 00:39:26.400
The dietary shift comes a little bit
later and that's pretty common.

3b60e0d3-0755-4c2e-a6f9-8e2b0d0aaeac-0
00:39:26.400 --> 00:39:28.280
Not everybody's going to change at the
same time.

76bc77b6-35d3-48f7-a4dd-9d0c6ed7e656-0
00:39:28.280 --> 00:39:31.160
Different organisms have different
ecologies, OK.

ed3584d9-123c-4e21-aa68-b0650d2cfe3f-0
00:39:31.160 --> 00:39:38.280
So this shift I think can be explained by
this shift in in available resources.

e8aa9788-97f7-4cab-83ff-bcee3fdd5942-0
00:39:38.280 --> 00:39:43.343
We went from having more C3 type woody
vegetation on the landscape to more open

e8aa9788-97f7-4cab-83ff-bcee3fdd5942-1
00:39:43.343 --> 00:39:48.280
resources on the landscape grasses and
things or tubers of those grasses, OK.

4d233d63-fde9-49d3-b479-c99bef96ec6b-0
00:39:48.560 --> 00:39:51.667
So to me,
that's the best explanation for why

4d233d63-fde9-49d3-b479-c99bef96ec6b-1
00:39:51.667 --> 00:39:57.207
perhaps the hominins all got packed into
this small dietary niche space over here

4d233d63-fde9-49d3-b479-c99bef96ec6b-2
00:39:57.207 --> 00:39:59.640
and then later differentiated again.

a1c736e1-a69b-4e08-b7e4-4f5e7ceea92a-0
00:40:05.320 --> 00:40:09.160
OK, so here's some key key takeaways.

b4d8b744-bd96-4714-8b33-d61556b73efa-0
00:40:09.240 --> 00:40:14.095
We see this vegetation shift AT27 and
consequently following that different

b4d8b744-bd96-4714-8b33-d61556b73efa-1
00:40:14.095 --> 00:40:17.417
mammal groups change their diet at
different times,

b4d8b744-bd96-4714-8b33-d61556b73efa-2
00:40:17.417 --> 00:40:22.399
with hominins all moving up into this
more C4 or grassy base diet around 2.4.

ff373364-7081-4cfe-ad90-4c18ee5d493c-0
00:40:23.760 --> 00:40:27.021
Where on the flip side,
some of the herbivores responded right

ff373364-7081-4cfe-ad90-4c18ee5d493c-1
00:40:27.021 --> 00:40:30.800
away, even earlier to that, OK,
so perhaps had more dietary flexibility.

d5ce75fd-0990-45a6-9de2-d556b7d6e2c7-0
00:40:33.680 --> 00:40:36.681
So why,
why did the hominid diet lag other

d5ce75fd-0990-45a6-9de2-d556b7d6e2c7-1
00:40:36.681 --> 00:40:37.240
mammals?

e905af95-f94c-45e4-b8e6-1b378ce67352-0
00:40:37.240 --> 00:40:40.160
Is it interspecific competition?

370a6530-622c-4773-ad60-a02531e994d2-0
00:40:40.280 --> 00:40:41.760
Is it environmental pressure?

4336f032-219c-4f4b-97bf-7c9d533d62a7-0
00:40:41.760 --> 00:40:42.880
We don't, we don't know.

1d6a7031-6b11-4906-8ef7-ddde2e5a2c46-0
00:40:42.920 --> 00:40:45.000
It's a really difficult question to
answer.

8b4d51ad-f04f-4025-8e2a-46d489bd3fff-0
00:40:45.560 --> 00:40:49.358
But by collecting more and more data,
we start to get at these questions or be

8b4d51ad-f04f-4025-8e2a-46d489bd3fff-1
00:40:49.358 --> 00:40:50.320
able to answer them.

8c3b42d3-dba1-449e-a7bb-dd8e49cb58a6-0
00:40:50.720 --> 00:40:50.960
OK.

98d07619-1f1d-482e-8f1e-d0b06b4bdf03-0
00:40:52.200 --> 00:40:55.314
And importantly,
the spatial and temporal scales of the

98d07619-1f1d-482e-8f1e-d0b06b4bdf03-1
00:40:55.314 --> 00:40:58.040
vegetation proxy and the diet proxy are
similar.

3aaa9880-95ed-49b3-9f28-2c7d392736c9-0
00:40:58.280 --> 00:40:59.960
So we're following the rules here.

f0681df8-c968-451f-b1d9-b3ebf5fe6700-0
00:41:01.240 --> 00:41:04.800
OK, so long-awaited.

9f1f48ea-3364-48fc-9b0c-893f60337021-0
00:41:04.800 --> 00:41:08.400
Here's my love letter and my conclusions
to parenthesis.

b8dd6d0b-9152-47de-8a60-7eb613aec227-0
00:41:09.280 --> 00:41:12.850
Dear parenthesis, we now know,
thanks to isotopes,

b8dd6d0b-9152-47de-8a60-7eb613aec227-1
00:41:12.850 --> 00:41:16.350
that through most of your time in Eastern
Africa,

b8dd6d0b-9152-47de-8a60-7eb613aec227-2
00:41:16.350 --> 00:41:19.920
your diet was based on 65 to 80% C four
resources.

123c3769-adc6-423c-9930-b62ff2335645-0
00:41:20.360 --> 00:41:24.960
You surprised us eating C3 foods and
mixed C3 feeding in the Omo.

a7fb2e0d-b859-4f61-b4e6-e3fa6bd71947-0
00:41:25.040 --> 00:41:27.731
There's a few two data points that were
surprising us,

a7fb2e0d-b859-4f61-b4e6-e3fa6bd71947-1
00:41:27.731 --> 00:41:29.640
but we know you did this in Malawi too.

7dce88d0-5ed4-447f-b037-981ad2ff904e-0
00:41:29.760 --> 00:41:31.480
In the southern southern African sites.

b6457cd4-29ce-4b39-bf94-5ea9e1cf7c81-0
00:41:33.000 --> 00:41:34.920
Microware shows you weren't eating hard
food.

8d1e6741-f270-4774-881a-58fcb790567e-0
00:41:34.920 --> 00:41:37.280
I'd hard food items, low complexity.

e53a9d9d-abbe-43b5-a1f7-42dadefcd0fd-0
00:41:37.320 --> 00:41:40.880
That's a microware term,
but instead tough items.

7c6f72cb-3a07-4524-81af-4fa9c946499e-0
00:41:41.160 --> 00:41:43.320
So it was doing more shearing like this,
right?

3a6d8b27-ae81-4568-9011-74f31e0f5c70-0
00:41:44.120 --> 00:41:45.600
Some of the grass eating mammals.

ff6f3d01-8121-4aac-bab1-d23dccf2cdfd-0
00:41:46.800 --> 00:41:47.800
So did you eat meat?

f3138f46-4b6c-4b5f-8fc3-d14000f03977-0
00:41:49.160 --> 00:41:50.520
I bet not, or not much.

7f0d0f72-a64c-4353-8d1f-5006bdbba715-0
00:41:50.920 --> 00:41:55.793
We are going to measure calcium isotopes
in your teeth with colleagues Jeremy

7f0d0f72-a64c-4353-8d1f-5006bdbba715-1
00:41:55.793 --> 00:41:59.917
Martin, Vincent Balter,
Pierre Jean Daudin in Lyon to try to find

7f0d0f72-a64c-4353-8d1f-5006bdbba715-2
00:41:59.917 --> 00:42:00.480
this out.

5d95b339-27cb-473c-9beb-af77cc107e10-0
00:42:00.520 --> 00:42:01.600
It's a hard measurement to make.

1bd6e878-5f29-4c22-aaba-2cb19d5664dc-0
00:42:01.600 --> 00:42:03.360
So our French colleagues are doing that.

f5808173-08b2-4bed-b5d7-d452c008f90e-0
00:42:05.200 --> 00:42:08.320
And my colleague Gilles did the microware.

7f8e4155-533b-4a48-90f5-8b989858b1de-0
00:42:09.600 --> 00:42:11.240
So we're trying to do some niche breath
modelling.

df4f58f2-a52e-46b8-91c7-ef4bf37af3a0-0
00:42:11.240 --> 00:42:13.454
Sorry,
I'll keep reading using microware isotope

df4f58f2-a52e-46b8-91c7-ef4bf37af3a0-1
00:42:13.454 --> 00:42:13.680
data.

f4ed154d-bbd9-4e61-82b6-99c17940541f-0
00:42:13.680 --> 00:42:14.680
We hope you don't mind.

68e6943d-3b9d-4d1e-ba58-761893b68fdc-0
00:42:15.600 --> 00:42:18.645
We won't call you a Nutcracker A
Nutcracker anymore,

68e6943d-3b9d-4d1e-ba58-761893b68fdc-1
00:42:18.645 --> 00:42:21.920
but your diet and ecology is still a
tough nut to crack.

303d1724-11c5-4b25-820f-99ab72c03601-0
00:42:22.680 --> 00:42:26.000
Yours truly, Kevin,
on behalf of my many colleagues.

42a1e12e-f6eb-443c-b9b4-107473942c41-0
00:42:26.800 --> 00:42:29.760
And then PS what happened in the Omo from
2.7 to 2.3.

613d6aea-a7a3-4554-9b75-765980091702-0
00:42:29.760 --> 00:42:32.200
Dying to note, which is outstanding.

fde4a88b-d2cb-4ef7-b521-4b41790a6477-0
00:42:32.200 --> 00:42:33.920
We can't can't quite figure out.

92132874-125c-47c0-8a11-fd187ba91060-0
00:42:34.400 --> 00:42:34.680
OK.

c1d510bd-6c28-494b-8a08-33305e8077a6-0
00:42:35.520 --> 00:42:40.777
And then I thought I'd just close with in
the Earth and evolutionary and paleo

c1d510bd-6c28-494b-8a08-33305e8077a6-1
00:42:40.777 --> 00:42:46.101
science is some of the efforts under way
at Harvard and and in the larger Earth

c1d510bd-6c28-494b-8a08-33305e8077a6-2
00:42:46.101 --> 00:42:51.160
science community to increase diversity,
equity, inclusion and anti racism.

0121b33e-3bb7-4d6c-b92e-47ac669bcbb8-0
00:42:51.160 --> 00:42:52.720
So it's just some examples at Harvard.

9d3ba74f-6c6f-48d1-b7c6-661ce6c3d0f9-0
00:42:53.720 --> 00:42:57.880
The main thing is to listen,
learn and discuss.

0c1f0fc5-0e4c-4b49-a506-5ebdb4fa6b85-0
00:42:58.320 --> 00:42:59.880
Professors are really good at talking.

a1d905bf-80bb-421a-a239-868950d11ede-0
00:42:59.880 --> 00:43:00.880
We like to talk a lot.

34182a46-a51b-4f46-8af2-65f1c382c2b4-0
00:43:00.880 --> 00:43:05.331
So this is a challenge for me listening
and this these are some of the

34182a46-a51b-4f46-8af2-65f1c382c2b4-1
00:43:05.331 --> 00:43:09.720
initiatives we're trying to put forth to
increase diversity sciences.

17faceda-b0a7-4094-a3cf-ab3d815803a5-0
00:43:10.160 --> 00:43:13.960
We participate in this thing called URGE
Unlearning Racism in the Geosciences.

2cd526e5-da08-4d65-830d-821721e49495-0
00:43:13.960 --> 00:43:15.200
That's a nationwide effort.

7f25fbb1-0322-47d9-b3bc-8bee35155d62-0
00:43:17.160 --> 00:43:22.664
And so one of the things we've been doing
is, is training African sciences,

7f25fbb1-0322-47d9-b3bc-8bee35155d62-1
00:43:22.664 --> 00:43:24.040
African scientists.

6cb89ae4-3e32-475a-930e-474a24762476-0
00:43:24.040 --> 00:43:28.720
There's a master's program that is
operating in the Turkana Basin.

02e94058-c4b7-4844-961d-5f52646aed7f-0
00:43:28.720 --> 00:43:32.514
It's the only masters in the entire
country of Kenya focused on human

02e94058-c4b7-4844-961d-5f52646aed7f-1
00:43:32.514 --> 00:43:35.766
evolutionary biology,
despite them having probably the best

02e94058-c4b7-4844-961d-5f52646aed7f-2
00:43:35.766 --> 00:43:37.880
record of human evolution in the world.

2048a943-19a1-401d-8ac6-8f466b751364-0
00:43:38.120 --> 00:43:42.160
And this was started by my late colleague
Isaiah Nengo in 2018.

c3e6a7a2-c34d-42a0-9f95-de9ad0231afe-0
00:43:42.160 --> 00:43:44.600
And there have been about 9 or 10
graduates.

81020515-74f3-4fd3-9cd6-c14c09e96691-0
00:43:44.600 --> 00:43:50.109
It's a very small cohort, like 3A year,
but I think out of the 9 or 10 graduates,

81020515-74f3-4fd3-9cd6-c14c09e96691-1
00:43:50.109 --> 00:43:54.880
like 8 of them are now in PhD programs in
the United States or Europe.

10ba3cd9-6faa-4419-830a-74a814dd6dac-0
00:43:55.320 --> 00:43:59.689
And they really need this sort of
bridging masters program because the

10ba3cd9-6faa-4419-830a-74a814dd6dac-1
00:43:59.689 --> 00:44:03.135
undergraduate education is lacking in
paleanthropology,

10ba3cd9-6faa-4419-830a-74a814dd6dac-2
00:44:03.135 --> 00:44:04.920
biology and things like that.

7fb1f67a-cf8e-4ea8-9fe5-a775161d08cd-0
00:44:05.720 --> 00:44:11.380
And so it's really a way to help them get
prepared to enter PhD programs in Europe

7fb1f67a-cf8e-4ea8-9fe5-a775161d08cd-1
00:44:11.380 --> 00:44:17.040
or the US And so we do things like train
them on how to drill teeth in the museum.

f1a38f85-89f1-46ac-9160-fc59a07b2a8c-0
00:44:17.400 --> 00:44:21.526
This is doing some water isotope
extraction at our lab in Kenya is

f1a38f85-89f1-46ac-9160-fc59a07b2a8c-1
00:44:21.526 --> 00:44:25.960
building a rainfall collector so we can
measure water isotopes of rain.

ab0cbd55-d094-443c-b138-ab06455cfd5e-0
00:44:27.200 --> 00:44:30.290
And then a lot of work in the National
Museum of Kenya,

ab0cbd55-d094-443c-b138-ab06455cfd5e-1
00:44:30.290 --> 00:44:34.375
which hosts perhaps the most wonderful
fossil collection in the world for

ab0cbd55-d094-443c-b138-ab06455cfd5e-2
00:44:34.375 --> 00:44:37.080
understanding human evolution capacity
building.

79ce7b6e-7783-455e-a4d3-db5bf09ff031-0
00:44:37.080 --> 00:44:42.711
That's another big effort is to actually
build labs and infrastructure in Eastern

79ce7b6e-7783-455e-a4d3-db5bf09ff031-1
00:44:42.711 --> 00:44:48.205
Africa so that researchers and students
can have access to these facilities and

79ce7b6e-7783-455e-a4d3-db5bf09ff031-2
00:44:48.205 --> 00:44:52.119
and be trained in Kenya rather than
having to go abroad.

e553b950-3f3e-447a-b19a-b5b3dd19b74b-0
00:44:52.760 --> 00:44:56.131
So we established this what's called the
Permil lab,

e553b950-3f3e-447a-b19a-b5b3dd19b74b-1
00:44:56.131 --> 00:44:59.440
Paleoon Eco hydrology research,
Impala isotope lab.

366e1dc6-2316-45e7-ba61-7358c2d68a9e-0
00:44:59.760 --> 00:45:01.040
This is the Impala research centre.

eab78dca-ab30-43ed-9d8d-73a800d910c1-0
00:45:01.040 --> 00:45:03.680
It's an ecology based research centre in
central Kenya.

b8288a21-c08e-4278-9b92-db4a1ad58e30-0
00:45:04.240 --> 00:45:08.858
And so we have this laser water isotope
analyzer and we go out and we collect

b8288a21-c08e-4278-9b92-db4a1ad58e30-1
00:45:08.858 --> 00:45:11.760
soil,
we can extract the moisture from the soil.

8ec3c6d0-a47c-4441-aa54-1991e7c62d1a-0
00:45:12.040 --> 00:45:16.240
We can get water out of plants and get it
out of rivers, out of reservoirs.

f4a91edf-06e8-4294-b4cc-77492ef21c4e-0
00:45:16.680 --> 00:45:19.320
And then here we are training students in
the lab.

420f2127-5a6d-41a4-a632-fd6d06c2e8a6-0
00:45:19.320 --> 00:45:21.680
This is the lab manager, John Gitonga.

5777a5c3-bb71-4703-a5c0-bea5cc3b603a-0
00:45:23.040 --> 00:45:24.800
So capacity building is a big thing.

177cfde8-47f2-43b5-80de-41bc4450fa31-0
00:45:25.440 --> 00:45:26.680
And then teaching.

ebe5a048-2bc9-4766-822f-b38497a55ba8-0
00:45:26.680 --> 00:45:31.156
So I, before I came to Harvard,
I was at Columbia and we taught an

ebe5a048-2bc9-4766-822f-b38497a55ba8-1
00:45:31.156 --> 00:45:32.760
undergrad course abroad.

ae403975-cb29-4c7a-96ee-58dca30e2b6a-0
00:45:32.760 --> 00:45:35.028
And they would just,
the students would be there for a

ae403975-cb29-4c7a-96ee-58dca30e2b6a-1
00:45:35.028 --> 00:45:35.400
semester.

5ed953f8-58bc-499c-bb19-16a17fa7e71b-0
00:45:35.400 --> 00:45:36.800
I would swoop in for three weeks.

497325ba-1432-41be-a9d2-78f857f07ae7-0
00:45:37.200 --> 00:45:41.920
And we do all kinds of ecological studies
using water isotopes.

facfd811-0a01-45ac-a14c-03f3232ae40c-0
00:45:41.920 --> 00:45:44.760
This is again,
extracting water from plants or soils.

e30e4f53-9388-4037-9a68-ddc461249a16-0
00:45:45.720 --> 00:45:46.760
We're not logging here.

fe56a5e4-5dfe-4f2c-bf57-d5207f792b1f-0
00:45:46.760 --> 00:45:50.640
This is a tree that fell next to a river
in a storm.

a3e79075-4010-4c26-89fd-162c2e77d136-0
00:45:50.640 --> 00:45:54.120
The the stream eroded away the bank and
the tree fell.

394bdabb-5e24-4114-982a-7f3f377799e7-0
00:45:54.360 --> 00:45:57.749
So we cut a slab out to try to do some
tree ring,

394bdabb-5e24-4114-982a-7f3f377799e7-1
00:45:57.749 --> 00:46:00.800
like dendro ecology stuff using what we
had.

e0e0f39a-3eec-48bc-b7ed-277b03101e0e-0
00:46:00.880 --> 00:46:05.162
We study what happens to bones on the
landscape, like how to make a fossil,

e0e0f39a-3eec-48bc-b7ed-277b03101e0e-1
00:46:05.162 --> 00:46:06.120
things like that.

fc451041-caed-4cdd-a5c4-add1f6560688-0
00:46:07.280 --> 00:46:09.840
And then of course,
we we hang out with the local kids a lot.

d31dd9c8-b47e-43ce-b403-e259e1eb7382-0
00:46:09.840 --> 00:46:14.600
They're always interested in what the
researchers are doing OK with that.

70bd7809-0ef4-4d48-920b-a95d233be02b-0
00:46:14.600 --> 00:46:15.880
I thank you for your time.

ce0925a9-3eac-4012-9bb8-5e9ea913183e-0
00:46:15.880 --> 00:46:19.000
I'd be happy to take questions after the
attendance check in.

1e5e012c-b2b6-4c8e-b879-f4e8e12e7154-0
00:46:28.760 --> 00:46:29.520
So good question.

6a7b1558-a9c3-4194-9b83-f0c36c3af67f-0
00:46:29.520 --> 00:46:33.496
So, you know,
the the morphological characteristics

6a7b1558-a9c3-4194-9b83-f0c36c3af67f-1
00:46:33.496 --> 00:46:36.860
again,
are this sort of macro evolutionary,

6a7b1558-a9c3-4194-9b83-f0c36c3af67f-2
00:46:36.860 --> 00:46:40.759
like what it was sort of evolved to do
and handle.

34f24e09-e564-4a92-815c-3f37e714b962-0
00:46:41.160 --> 00:46:44.960
That doesn't necessarily mean it's what
it's actually eating at the time.

074a41dc-9a64-457f-ad0f-bb6854150ef5-0
00:46:45.880 --> 00:46:49.371
And so yes,
pyranthropus had much thicker enamel and

074a41dc-9a64-457f-ad0f-bb6854150ef5-1
00:46:49.371 --> 00:46:52.863
that gave it,
I think ironically gives it more niche

074a41dc-9a64-457f-ad0f-bb6854150ef5-2
00:46:52.863 --> 00:46:58.331
breath or possibility to eat more things
than **** because we don't have the teeth

074a41dc-9a64-457f-ad0f-bb6854150ef5-3
00:46:58.331 --> 00:46:59.320
for doing that.

8048bdbb-f73e-49c0-811c-a9156b82db72-0
00:47:00.320 --> 00:47:04.028
But it had the most restricted diet of
all the hominins we've ever looked at

8048bdbb-f73e-49c0-811c-a9156b82db72-1
00:47:04.028 --> 00:47:05.040
using this technique.

75cbc076-6883-4a5a-80e7-f34954473c59-0
00:47:05.440 --> 00:47:08.200
But I'll give you an example using
elephants, right?

6b15994d-8cdf-41a8-a8e0-00163928ae07-0
00:47:08.200 --> 00:47:11.106
Elephants have these massively high
crowned teeth,

6b15994d-8cdf-41a8-a8e0-00163928ae07-1
00:47:11.106 --> 00:47:15.493
and most high crown teeth in the mammal
world are evolved for grazing eating

6b15994d-8cdf-41a8-a8e0-00163928ae07-2
00:47:15.493 --> 00:47:18.913
grasses because teeth wear down when
you're eating grasses,

6b15994d-8cdf-41a8-a8e0-00163928ae07-3
00:47:18.913 --> 00:47:22.560
they're gritty and they're just much more
abrasive than leaves.

97b78c68-1170-48f5-969b-a0ce84cc2f89-0
00:47:23.080 --> 00:47:25.387
So elements have evolved these really
high crown teeth,

97b78c68-1170-48f5-969b-a0ce84cc2f89-1
00:47:25.387 --> 00:47:28.520
and we know they were eating grasses in
the past using this same technique.

9bf9eb48-02a7-4ed0-9bf5-ed4f51f513ad-0
00:47:28.640 --> 00:47:33.971
But today, Loxedana, the African elephant,
both the forest and the Savannah elephant

9bf9eb48-02a7-4ed0-9bf5-ed4f51f513ad-1
00:47:33.971 --> 00:47:36.480
mostly eat brows, They mostly eat trees.

6d0aea84-cbf1-489c-9256-facdc06bca1b-0
00:47:36.640 --> 00:47:38.320
So here's a tooth that's evolved.

52a6fe5d-12dd-4a18-aa2b-8a311761a80b-0
00:47:38.320 --> 00:47:39.480
It's specialized to eat grass.

886b36c4-676b-4c45-8e3b-e045035de051-0
00:47:39.480 --> 00:47:41.939
It used to,
but now it's using it for something else

886b36c4-676b-4c45-8e3b-e045035de051-1
00:47:41.939 --> 00:47:42.960
and it's working fine.

dc3cc40e-f417-414b-a8c3-d02427d68bd8-0
00:47:43.240 --> 00:47:45.600
The only reason elephants are in trouble
is US, right?

8b3ff526-78fe-4dd9-aecc-7960b05a7789-0
00:47:46.240 --> 00:47:48.040
Land use change, poaching,
things like that.

088e4f80-a41f-4e96-954c-8e45fae5ef8c-0
00:47:48.040 --> 00:47:51.920
So teeth can be evolved for one thing,
but actually do other things.

7bb24473-6820-47e6-bf2d-ea22f408b797-0
00:47:51.920 --> 00:47:56.377
And so it's probably more to do with the
resources available on the landscape as

7bb24473-6820-47e6-bf2d-ea22f408b797-1
00:47:56.377 --> 00:48:00.560
to why these two hominin genera were
collapsed into a particular food type.

d4a015ec-ea90-4b50-8539-74867d9db3f2-0
00:48:01.040 --> 00:48:01.160
Yeah.

1c561f3f-5749-493b-a738-d9c88fdfe695-0
00:48:01.560 --> 00:48:04.040
And I will say the isotope method is a
little bit broad.

c50cda0e-7c08-4f28-b51c-2bd2660066c7-0
00:48:04.280 --> 00:48:06.640
We just know it was C4 based.

5156459a-fd34-4abb-b844-5ededc8fccf0-0
00:48:07.080 --> 00:48:11.304
It could have been a wildebeest that was
eating only C4 grasses and then we,

5156459a-fd34-4abb-b844-5ededc8fccf0-1
00:48:11.304 --> 00:48:13.280
our ancestors were eating that meat.

5931c1a2-dad7-4bfe-9cd0-695adc14b0d6-0
00:48:13.280 --> 00:48:19.051
We can't tell between omnivore, carnivore,
We can't differentiate that with trophic

5931c1a2-dad7-4bfe-9cd0-695adc14b0d6-1
00:48:19.051 --> 00:48:21.800
level stuff with this particular method.

ef921d88-7081-4dd4-b9db-5f85a26016b5-0
00:48:22.000 --> 00:48:29.474
Yeah, I was just curious,
do you keep any of the fossils for

ef921d88-7081-4dd4-b9db-5f85a26016b5-1
00:48:29.474 --> 00:48:33.640
yourself or you just give them to?

7335ab75-9f98-4b18-b519-f9f2be86dabe-0
00:48:33.640 --> 00:48:36.680
These are the national treasures of these
countries.

8914ba58-38bb-47ad-ac2f-1af475d5daa3-0
00:48:36.680 --> 00:48:39.920
And so I would be in jail if I kept them
for myself.

220c3351-9c0d-4fb9-841d-e764958cc273-0
00:48:40.840 --> 00:48:43.600
And I'll just tell a quick student
vignette, which is one year.

b7f261bc-42fa-4536-8b96-28b69c7fe538-0
00:48:43.600 --> 00:48:46.920
We're at a stone tool site with the
students from Columbia and Princeton.

a3a87545-18cf-462b-8dda-8d76312d81ff-0
00:48:47.440 --> 00:48:52.918
And one student who shall never be named,
slipped a stone tool in their pocket and

a3a87545-18cf-462b-8dda-8d76312d81ff-1
00:48:52.918 --> 00:48:57.802
they came back here and a year and a half
later wrote me and said, Kevin,

a3a87545-18cf-462b-8dda-8d76312d81ff-2
00:48:57.802 --> 00:48:59.320
I can't sleep at night.

8a7581bb-3e00-40fb-aa1d-fa84a23ca8d6-0
00:48:59.840 --> 00:49:02.400
I've done this thing, what should I do?

c8091679-5ffe-478f-b0ee-dc9c22b7e6fb-0
00:49:02.400 --> 00:49:04.120
And so I called my stone tool friend.

16b427ac-8085-4293-a261-0cede807c8d6-0
00:49:04.120 --> 00:49:09.788
Like we got a situation and he basically
said you should just take it back with

16b427ac-8085-4293-a261-0cede807c8d6-1
00:49:09.788 --> 00:49:11.560
you and put it back near.

61259b27-f586-4eb9-9fd5-74010e832f92-0
00:49:11.560 --> 00:49:13.080
But it's out of context.

99fcee7d-fbf7-4d86-93b7-ea8ccf41ed40-0
00:49:13.080 --> 00:49:15.769
So what I decided to do is throw it in
the lake,

99fcee7d-fbf7-4d86-93b7-ea8ccf41ed40-1
00:49:15.769 --> 00:49:19.830
at this lake in the Lake Turkana,
where it'll probably hopefully never be

99fcee7d-fbf7-4d86-93b7-ea8ccf41ed40-2
00:49:19.830 --> 00:49:20.159
found.

271bce00-419a-4bcf-be98-96659ab4d398-0
00:49:20.160 --> 00:49:20.520
I don't know.

8591b941-a37c-491e-a1ab-5ba01df1f509-0
00:49:20.640 --> 00:49:24.800
So this person is so guilt ridden that
that they eventually gave that back.

0bb99cbe-5d02-4a6c-b7fc-c29d911cce0f-0
00:49:24.800 --> 00:49:29.231
So we always work under a very strict set
of rules and guidelines to how we treat

0bb99cbe-5d02-4a6c-b7fc-c29d911cce0f-1
00:49:29.231 --> 00:49:29.880
the fossils.

ff363c16-a2c5-484a-a089-ce471545e361-0
00:49:29.920 --> 00:49:32.976
Before we drill a fossil,
we have to ask and get permission from

ff363c16-a2c5-484a-a089-ce471545e361-1
00:49:32.976 --> 00:49:36.455
the museum research staff that yes,
this one can be drilled because it it

ff363c16-a2c5-484a-a089-ce471545e361-2
00:49:36.455 --> 00:49:37.960
damages the fossil a little bit.

4fcc7aaf-f7af-42c5-8147-56ab8a8d324f-0
00:49:38.160 --> 00:49:39.400
But you get good information.

d1641a4b-e410-4aca-a344-ed1a0843ffa7-0
00:49:45.680 --> 00:49:46.760
Thank you, that was a great talk.

59f71a16-83a4-4caa-93ff-116bee600759-0
00:49:47.800 --> 00:49:52.894
I'm wondering about the ISO ratio itself
ties to the food and they eat,

59f71a16-83a4-4caa-93ff-116bee600759-1
00:49:52.894 --> 00:49:56.432
but what I'm wondering throughout that
time zone,

59f71a16-83a4-4caa-93ff-116bee600759-2
00:49:56.432 --> 00:50:02.305
the organs in itself is evolving and I'm
wondering if the fractionation due to the

59f71a16-83a4-4caa-93ff-116bee600759-3
00:50:02.305 --> 00:50:06.480
organs in itself,
can we actually tell something about it?

b58a5623-5345-418b-a9c4-237c129a0c30-0
00:50:06.880 --> 00:50:09.200
Earlier species versus later species?

6a794b97-89a2-4d48-9b40-23564077e2f0-0
00:50:09.200 --> 00:50:12.240
There's, you know,
carbon or oxygen differences.

f511ad5a-102a-4b89-8ce9-51c564891058-0
00:50:12.280 --> 00:50:16.440
It's not due to the fact that the
environment is basically organs.

40b2827f-d853-44fa-ba2e-06071eb0fd67-0
00:50:16.640 --> 00:50:18.880
How picking up 1413.

12e11e01-be1d-4b29-8985-2ba9b8d50b0c-0
00:50:19.440 --> 00:50:20.600
Yeah, or oxygen.

65f3dc11-8908-46d8-8d41-dbea9cdfcc6e-0
00:50:22.160 --> 00:50:23.200
It's a really great question.

652cbe8b-4694-4241-a4cf-88bf5989be6c-0
00:50:23.200 --> 00:50:26.286
So he's asking like a 300 level,
400 level course question here,

652cbe8b-4694-4241-a4cf-88bf5989be6c-1
00:50:26.286 --> 00:50:29.610
which is when you eat something,
the carbon gets incorporated in your

652cbe8b-4694-4241-a4cf-88bf5989be6c-2
00:50:29.610 --> 00:50:30.560
teeth, the isotopes.

7e5b66de-88ea-4c8d-99d7-3c93a0005a0f-0
00:50:30.560 --> 00:50:35.515
But there's a a shift called a
fractionation factor between the diet and

7e5b66de-88ea-4c8d-99d7-3c93a0005a0f-1
00:50:35.515 --> 00:50:37.960
the actual mineral tooth that forms.

734a0cf2-f9d8-4423-9c06-13fe09f1e7c8-0
00:50:37.960 --> 00:50:41.680
But we've measured that fractionation
that offset across mammals.

2236e5d0-9a96-4a39-b3de-21ec56e1223e-0
00:50:42.200 --> 00:50:46.160
And the biggest determinant is gut
Physiology.

70e91909-a72a-46d5-9a58-ecfdf8888845-0
00:50:46.160 --> 00:50:49.964
So unless we've become ruminants or we're
ruminants and are not now that's the

70e91909-a72a-46d5-9a58-ecfdf8888845-1
00:50:49.964 --> 00:50:50.880
biggest difference.

9e6065f0-9785-4d50-aeb9-be796bf670a8-0
00:50:52.320 --> 00:50:53.320
It's pretty constant.

9b74fd36-8eab-4583-8d65-140b7f8a5d59-0
00:50:53.320 --> 00:50:55.560
It's about the same across primates.

86f9f87f-4a6b-4203-9c39-f6530e92b353-0
00:50:55.560 --> 00:50:58.091
There's,
there's subtle variations on the order of

86f9f87f-4a6b-4203-9c39-f6530e92b353-1
00:50:58.091 --> 00:51:01.169
one to two per mil,
but not over the course of like 3 to 6 to

86f9f87f-4a6b-4203-9c39-f6530e92b353-2
00:51:01.169 --> 00:51:02.560
8 per mil that we're seeing.

57dbb39e-cad3-4c7e-adf4-3669237082d2-0
00:51:02.800 --> 00:51:03.720
Yeah, good question.

534de778-5642-4223-98da-81bc400e04a5-0
00:51:11.480 --> 00:51:18.840
The genes that do tooth morphology are
famously so.

f3450f39-ede0-4418-9c78-b3cb9b740080-0
00:51:18.960 --> 00:51:25.764
The shovel shaped molars from the Bering
strain were actually modified for vitamin

f3450f39-ede0-4418-9c78-b3cb9b740080-1
00:51:25.764 --> 00:51:32.160
D production in breast tissue and the
change in shape of teeth was secondary.

418bb548-1b2a-4a5a-94c2-f37416a5d575-0
00:51:32.520 --> 00:51:37.973
Have you looked at EDAR gene or any of
the genes that are involved in producing

418bb548-1b2a-4a5a-94c2-f37416a5d575-1
00:51:37.973 --> 00:51:39.200
teeth for biology?

6ef0b2b8-1169-4b0a-93ef-dc8869ec297f-0
00:51:40.600 --> 00:51:43.560
If I knew anything about genes, I might.

394aa012-e114-4d77-835a-e859d70504fe-0
00:51:43.840 --> 00:51:45.840
I I'm in, I'm now in a biology department.

1d16549d-f307-4f63-bbde-923af2098ccb-0
00:51:45.840 --> 00:51:47.040
I'm trained as an earth scientist.

ca2bc420-d55e-4f0e-a551-850d81ba50fb-0
00:51:47.200 --> 00:51:50.413
Yeah,
and we're hiring a human geneticist and I

ca2bc420-d55e-4f0e-a551-850d81ba50fb-1
00:51:50.413 --> 00:51:53.492
in,
I feel like I'm in genetics one O 1 so we

ca2bc420-d55e-4f0e-a551-850d81ba50fb-2
00:51:53.492 --> 00:51:56.839
can look at the modern genes in, in,
in primates.

24e402e9-3d4a-4d85-b6e5-4e9000dac7be-0
00:51:56.840 --> 00:52:00.852
And my colleague Leslie Lusko,
who took this photo,

24e402e9-3d4a-4d85-b6e5-4e9000dac7be-1
00:52:00.852 --> 00:52:06.795
is actually looking at genes in primates
to try to understand the phenotypic

24e402e9-3d4a-4d85-b6e5-4e9000dac7be-2
00:52:06.795 --> 00:52:12.120
variation in which genes turn off which
aspects of molar morphology.

acb3fa15-5b4a-4284-83a8-3103065048c5-0
00:52:13.360 --> 00:52:15.840
She's in in Spain at an institute there.

69611755-2a90-4513-897c-d50557776c36-0
00:52:15.840 --> 00:52:17.720
But I have not.

cf90edb5-2e24-4ea1-819d-61dbc90e7a23-0
00:52:17.800 --> 00:52:23.028
And for like ancient DNA, we can't,
we can't get that far back into millions

cf90edb5-2e24-4ea1-819d-61dbc90e7a23-1
00:52:23.028 --> 00:52:23.640
of years.

f634e4b6-9d8e-4237-82a2-f3930aace99f-0
00:52:23.640 --> 00:52:25.880
We can go back, say, 50 or 60,000 years.

8b25c7e4-5c97-4138-a9f3-97a0ea186139-0
00:52:26.240 --> 00:52:30.968
But Africa has proved remarkably
challenging for ancient DNA because of

8b25c7e4-5c97-4138-a9f3-97a0ea186139-1
00:52:30.968 --> 00:52:31.560
the heat.

2ead224f-d6b3-4f33-a0e3-a12b583f369d-0
00:52:31.920 --> 00:52:35.728
So the only ancient genomes that have
been published from there come from high

2ead224f-d6b3-4f33-a0e3-a12b583f369d-1
00:52:35.728 --> 00:52:37.560
up in the mountains where it's cooler.

4e38d33f-f3e2-4458-a7a9-1b238d9304f6-0
00:52:38.120 --> 00:52:41.800
All the sort of low insights that
proteins at the end, everything's baked.

34d4022f-935a-4e1d-968d-f5a1a4ea8db5-0
00:52:42.320 --> 00:52:42.560
Yeah.

51f581d7-e751-4feb-901e-0a0b9f28b8e1-0
00:52:43.120 --> 00:52:47.000
So great suggestion,
way out of my field of expertise.

58b35f41-f4e9-4a9a-86dc-93ed778766c3-0
00:52:47.400 --> 00:52:49.280
Yeah,
I think they're really interesting though.

d55d31b3-d60d-4277-be25-12e1c28da3ef-0
00:52:50.360 --> 00:52:54.500
I think even if you could do A at a
phonogenetic level,

d55d31b3-d60d-4277-be25-12e1c28da3ef-1
00:52:54.500 --> 00:53:00.120
I will say we have just recovered some
ancient proteins out of tooth enamel

d55d31b3-d60d-4277-be25-12e1c28da3ef-2
00:53:00.120 --> 00:53:05.814
going back to 29,000,000 years and that,
you know, these are small proteins,

d55d31b3-d60d-4277-be25-12e1c28da3ef-3
00:53:05.814 --> 00:53:08.920
but like enamel proteins, dentin proteins.

ecb9a5be-1614-45ec-946b-32c4b931ea58-0
00:53:08.920 --> 00:53:12.200
So they are preserved,
but they're smaller snippets.

8250814b-5cc8-47c6-9c3c-a27c3a17562f-0
00:53:12.200 --> 00:53:15.866
And I don't know that it's,
it's not the gene, it's just a protein,

8250814b-5cc8-47c6-9c3c-a27c3a17562f-1
00:53:15.866 --> 00:53:17.160
but it's a step forward.

1dd53dc3-bf69-4c37-bcef-1f726bbaa44d-0
00:53:17.320 --> 00:53:17.480
Yeah.

f88c0977-fcd1-48d1-82af-256061a5e64f-0
00:53:23.240 --> 00:53:23.320
Hi.

39c9c96f-752e-46ad-b8b7-08d82a969a79-0
00:53:23.320 --> 00:53:27.491
I just want to ask,
let me just start with saying back to you,

39c9c96f-752e-46ad-b8b7-08d82a969a79-1
00:53:27.491 --> 00:53:31.000
let me mention how was your research done
in Africa?

fcaaefc4-aad8-43be-af55-630d18ce8322-0
00:53:31.040 --> 00:53:32.960
Because there's a bunch of evidence out
here with that.

f250d4dc-0826-49f0-9ecb-2718711f8b1e-0
00:53:33.400 --> 00:53:37.280
Would you say that'd be a more further
support to the out of Africa.

e95537b5-ccd8-4fa3-a781-1a407acfd80e-0
00:53:38.640 --> 00:53:41.777
Yeah,
that's a pretty that has not been

e95537b5-ccd8-4fa3-a781-1a407acfd80e-1
00:53:41.777 --> 00:53:46.640
challenged in any major way,
at least for the early hominins.

feb94470-d090-467e-81a5-68f9fe87a997-0
00:53:46.920 --> 00:53:52.316
The waves of out of Africa,
there was an early Homo erectus 1.

feb94470-d090-467e-81a5-68f9fe87a997-1
00:53:52.316 --> 00:53:56.600
7 million years and then later Homo
sapiens left.

5943f44a-98cd-482f-b56a-90a401b8a827-0
00:53:56.600 --> 00:53:59.760
And so there's still a lot of debate
about the timing and the nature.

82e21ca5-5f00-4bf5-9f74-3ca9e22f3123-0
00:53:59.760 --> 00:54:02.880
Was it a push or a pull and what were the
conditions like?

5cb4f3e7-60d3-4976-b2a3-c593d0a2a022-0
00:54:03.960 --> 00:54:07.368
But yeah,
it's not really the question as to where

5cb4f3e7-60d3-4976-b2a3-c593d0a2a022-1
00:54:07.368 --> 00:54:09.440
hominins evolved at this point.

0dd7ba1f-f921-465a-86bb-2b99368ab1d8-0
00:54:09.640 --> 00:54:11.200
It's just how they left and when.

4776655e-6932-4063-ab6d-88ba206d09c3-0
00:54:11.520 --> 00:54:11.640
Yeah.

e8a6c489-e2bc-4f62-bec8-134a24909226-0
00:54:14.880 --> 00:54:15.920
Any other questions?

cbb02123-34a1-4316-8726-12f7a4621cfc-0
00:54:19.560 --> 00:54:20.600
So the bones are around you.

659f90eb-a4c6-4df3-ae85-f34fa78cffda-0
00:54:20.600 --> 00:54:20.840
All right.

e1bf2551-cc4d-4f87-ac0f-7ce244b24996-0
00:54:23.200 --> 00:54:23.560
Thank you.

5f2214ee-4336-4ba7-b328-bb2cfa9c26f8-0
00:54:25.080 --> 00:54:32.178
So you showed a figure with two skeleton
so and **** and said that the leg bones

5f2214ee-4336-4ba7-b328-bb2cfa9c26f8-1
00:54:32.178 --> 00:54:36.560
were much smaller and parenthesis,
is that right?

72e8472c-23f1-4563-93f2-8986a6576d7e-0
00:54:36.560 --> 00:54:41.540
They have like shorter, shorter,
shorter legs, but pretty much longer arms,

72e8472c-23f1-4563-93f2-8986a6576d7e-1
00:54:41.540 --> 00:54:44.882
I think,
or proportionately shaded areas of the of

72e8472c-23f1-4563-93f2-8986a6576d7e-2
00:54:44.882 --> 00:54:48.880
the bones were the only bones that have
been actually found.

b5c42d37-c2cf-4d25-a800-a73340bc1878-0
00:54:49.160 --> 00:54:49.560
Yeah.

51d93987-fdac-4f5e-9ad0-b277803eaf69-0
00:54:49.600 --> 00:54:51.840
How do they know that their lives are
short?

63b47590-214d-41f9-9fde-e73a634ae882-0
00:54:53.120 --> 00:54:53.320
Yeah.

69aa1d89-e7d0-4761-8410-2cf3fae6cbd4-0
00:54:53.800 --> 00:54:56.480
This is like a major reconstruction
effort.

13e71821-ea0a-49cf-8cdd-3db1468a0ab8-0
00:54:56.480 --> 00:54:57.600
You're talking about this diagram.

3148a912-8978-4be5-8dfe-8d083f4f006d-0
00:54:57.600 --> 00:54:57.760
Yeah.

3e91af07-e1fd-4b34-979b-697cabf296ff-0
00:54:58.600 --> 00:54:58.880
Yes.

036445d0-120a-4863-bf99-63d288c9739b-0
00:54:59.920 --> 00:55:01.360
So you can tell a lot.

186b3796-706f-4739-8fa3-a02b0d52e514-0
00:55:02.240 --> 00:55:05.480
So here they have, I guess,
2 femoral heads and you probably.

7d59c860-ad3c-4c18-819c-7a7cf369ca8e-0
00:55:06.280 --> 00:55:07.600
I'm not a morphologist.

0a32a8f6-0238-4791-934b-2a9532c3ab5c-0
00:55:07.600 --> 00:55:09.160
Not a paleontologist than a wannabe.

44b9a3e8-2e45-40ba-8b20-9379229ad810-0
00:55:10.680 --> 00:55:13.600
So this is fully reconstructed the tib
fib.

7d377753-2df6-4720-89f5-17428da55ad6-0
00:55:13.920 --> 00:55:18.016
There's some Ankley bone here, you know,
whoop to do,

7d377753-2df6-4720-89f5-17428da55ad6-1
00:55:18.016 --> 00:55:24.161
but here they're probably using the the
morphology of the femoral head and maybe

7d377753-2df6-4720-89f5-17428da55ad6-2
00:55:24.161 --> 00:55:27.120
the the thickness of the cortical bone.

293e1cd6-38df-4703-8c87-32db64addf71-0
00:55:27.120 --> 00:55:31.840
I'm not sure I I tend to trust most
paleontologists on this stuff.

22a7cc76-04aa-4f36-b4c7-24781fcb00fb-0
00:55:31.840 --> 00:55:34.424
The way they talk about bones is,
you know, they're not,

22a7cc76-04aa-4f36-b4c7-24781fcb00fb-1
00:55:34.424 --> 00:55:35.920
they're not making this stuff up.

d846e236-7635-4160-a34d-5a3e965768e1-0
00:55:35.920 --> 00:55:38.080
But it's true, we could use a lot.

3a03fd65-811c-42a3-be47-e0aac561d689-0
00:55:38.080 --> 00:55:39.760
We could use a lot more of this skeleton.

9e930c2d-4f67-4c9c-8848-78374c0240ac-0
00:55:39.760 --> 00:55:40.600
This is actually us.

933ab5f3-ce2f-4211-92a1-e394e9267cfa-0
00:55:40.600 --> 00:55:42.720
This is just a **** sapien,
your average human.

72b4e257-3691-48d8-8a3e-2993964683c2-0
00:55:42.720 --> 00:55:47.920
So it just really drives from the point
of how incomplete the fossil record is.

05e58ce1-de00-4aed-b763-fb4a3a734c80-0
00:55:48.320 --> 00:55:48.600
Yeah.

7ac11e9f-a053-4829-81ba-f539fa782256-0
00:55:49.720 --> 00:55:50.680
Hand bones would be great.

52325b89-9357-46c4-8e12-d27319aaa81d-0
00:55:50.680 --> 00:55:56.680
Is there a thumb there?

df171ad5-2047-432f-9069-bbfa63fc06b6-0
00:55:56.680 --> 00:55:57.080
Can't tell.

4c08d1da-67fa-4d15-b878-c7e7c9c39778-0
00:55:58.760 --> 00:56:03.368
So if I got this correct,
it sounds like for a period everybody

4c08d1da-67fa-4d15-b878-c7e7c9c39778-1
00:56:03.368 --> 00:56:06.320
just kind of more converging on AC4 then.

281fb691-3656-4cdc-8196-3f91f4fcb092-0
00:56:07.280 --> 00:56:11.504
But then after once we got past 2.
2 million years ago,

281fb691-3656-4cdc-8196-3f91f4fcb092-1
00:56:11.504 --> 00:56:15.200
then **** genius like did we go back to
more C3?

4734fa26-3956-46ef-bc75-77f6ab149bbd-0
00:56:16.040 --> 00:56:21.840
And are we still,
I mean we still have grasses, right.

752855ee-7c77-4fd8-a84d-83a617e0ec0c-0
00:56:21.840 --> 00:56:27.098
But was that because we started eating
more foods from trees or even though the

752855ee-7c77-4fd8-a84d-83a617e0ec0c-1
00:56:27.098 --> 00:56:32.160
landscape is still creating Savannah like
yeah, I mean our great innovation.

46754cbf-2107-4ec0-a681-40671f071982-0
00:56:32.160 --> 00:56:37.000
I think what most people would argue is
that where's the whoa?

76503eed-f46a-497b-ad43-61db06462b02-0
00:56:37.000 --> 00:56:38.000
It doesn't shine on there.

7f5c0225-85c6-4a0d-95f3-11bf5977fdbe-0
00:56:39.160 --> 00:56:44.320
Whoa is so we're we're not fully see
through.

16c8f49c-fe42-469a-a8eb-9e9841e533ba-0
00:56:44.320 --> 00:56:46.080
You can see here we're kind of mixed.

42514f13-b0b6-43a4-a676-cbba4ffd48ea-0
00:56:46.080 --> 00:56:50.843
And what I think the most popular
evolutionary theory now is we ****

42514f13-b0b6-43a4-a676-cbba4ffd48ea-1
00:56:50.843 --> 00:56:54.640
figured out a way to have these very
generalist diets.

940dce23-bec7-4e30-8830-28fee5ffe429-0
00:56:54.640 --> 00:56:57.520
And that's been interpreted as
flexibility.

7ca79127-2ea1-4f90-a4c5-8b975b7c30b3-0
00:56:57.960 --> 00:57:03.712
And perhaps the reason why **** became a
very successful lineage and parenthropist

7ca79127-2ea1-4f90-a4c5-8b975b7c30b3-1
00:57:03.712 --> 00:57:09.325
who was kind of packed in at the upper
end of that dietary range eventually went

7ca79127-2ea1-4f90-a4c5-8b975b7c30b3-2
00:57:09.325 --> 00:57:09.880
extinct.

f47e749e-46e6-4def-8c4a-80f79e871dc8-0
00:57:09.920 --> 00:57:10.840
But we still don't know.

183ff7f0-550a-4f1f-8352-21028bf4d29f-0
00:57:10.840 --> 00:57:15.822
But the way people like to tell a story
is in this ever increasingly harsh

183ff7f0-550a-4f1f-8352-21028bf4d29f-1
00:57:15.822 --> 00:57:20.339
environment in eastern Africa,
as it became more arid, more grassy,

183ff7f0-550a-4f1f-8352-21028bf4d29f-2
00:57:20.339 --> 00:57:25.920
more resource limited or at least drier,
we found a way to expand our niche breath.

19053068-acff-49af-aba3-32e041ac6d97-0
00:57:25.920 --> 00:57:29.846
And then you add like carnivore and
hunting and stone tools and,

19053068-acff-49af-aba3-32e041ac6d97-1
00:57:29.846 --> 00:57:31.840
and that really changes the game.

acf00efc-85a5-4d73-b564-db6cf6faff7e-0
00:57:32.080 --> 00:57:35.440
But we think that Parenthropist may have
been using stone tools as well.

273a8146-548a-48a4-9e87-4fa911408e9c-0
00:57:35.880 --> 00:57:38.019
Again,
these are some of the great and many

273a8146-548a-48a4-9e87-4fa911408e9c-1
00:57:38.019 --> 00:57:39.040
unanswered questions.

d775bec7-97f1-42ae-b91a-b49715f4e36f-0
00:57:41.440 --> 00:57:44.680
Any other questions about you?

3b00e65d-ec3d-445b-b6d3-35ba6248ea8a-0
00:57:44.680 --> 00:57:48.080
Actually,
I have one and it's been totally outside

3b00e65d-ec3d-445b-b6d3-35ba6248ea8a-1
00:57:48.080 --> 00:57:49.880
of your field of expertise.

94b25c06-bbfd-41b8-96f3-f8ec97b9456b-0
00:57:51.040 --> 00:57:56.225
The maps you're showing us are the
incomplete fossil record that you remind

94b25c06-bbfd-41b8-96f3-f8ec97b9456b-1
00:57:56.225 --> 00:57:56.840
us about.

996217cf-8899-4345-ba1d-878d6213a20c-0
00:57:57.720 --> 00:58:03.282
Has anyone sort of made an estimate 2.
2 million years ago how many of these

996217cf-8899-4345-ba1d-878d6213a20c-1
00:58:03.282 --> 00:58:04.800
organisms were alive?

9dd0dca1-e490-4cc9-9e24-07487a580df1-0
00:58:06.760 --> 00:58:10.144
Well,
the probably the best way to do that is

9dd0dca1-e490-4cc9-9e24-07487a580df1-1
00:58:10.144 --> 00:58:12.720
just to look in A at a fossil site.

1c4e9098-4035-4f44-aaae-f3374058281a-0
00:58:12.720 --> 00:58:13.480
The the record.

fbaf1f44-ef9c-44a2-89cb-e1e72aeeddda-0
00:58:13.480 --> 00:58:15.240
OK, how many fossils do we have here?

ddfa41f6-f89f-490d-99ce-1e5a604905ed-0
00:58:15.240 --> 00:58:15.920
What are they?

750cb99c-ed35-4698-87b7-101bd5f44ba0-0
00:58:16.400 --> 00:58:21.451
And the general rule is that most sites,
hominins make up less than 1% of what we

750cb99c-ed35-4698-87b7-101bd5f44ba0-1
00:58:21.451 --> 00:58:21.760
find.

d6821427-e25d-4c4c-94c8-729980a78b3e-0
00:58:22.120 --> 00:58:28.216
So there is this conundrum of how these
lineages survive both of them for a

d6821427-e25d-4c4c-94c8-729980a78b3e-1
00:58:28.216 --> 00:58:32.227
million years or more for us millions of
years 2.

d6821427-e25d-4c4c-94c8-729980a78b3e-2
00:58:32.227 --> 00:58:36.800
6 and existed at such low numbers
throughout the record.

eff4b061-3552-406d-bb56-2cccca96d88f-0
00:58:37.480 --> 00:58:41.616
And you know, now population,
we have a different problem population,

eff4b061-3552-406d-bb56-2cccca96d88f-1
00:58:41.616 --> 00:58:42.680
but they were low.

050b6a63-6ac1-42ff-bf3d-cf712bb49ad5-0
00:58:42.680 --> 00:58:46.501
We know that that they were low,
but I don't know if there's been a number

050b6a63-6ac1-42ff-bf3d-cf712bb49ad5-1
00:58:46.501 --> 00:58:50.577
of people talk about thousands and with
ancient DNA you can look at relatedness

050b6a63-6ac1-42ff-bf3d-cf712bb49ad5-2
00:58:50.577 --> 00:58:53.023
and like where this thing runs of
homozygosity,

050b6a63-6ac1-42ff-bf3d-cf712bb49ad5-3
00:58:53.023 --> 00:58:54.960
who's who's marrying who and breeding.

c542828d-e6ed-4ece-986f-89ed744cc174-0
00:58:54.960 --> 00:58:57.771
So in the more near term,
we have records of that,

c542828d-e6ed-4ece-986f-89ed744cc174-1
00:58:57.771 --> 00:59:01.520
but that far back it's it's much more
unconstrained, the estimates.

b5cc281a-4715-449d-9fe5-fedc64508eb1-0
00:59:01.520 --> 00:59:06.760
So payback on that.

daa98789-b67f-4eb7-aed8-9a4abc81f182-0
00:59:07.880 --> 00:59:13.454
What are the characteristics of the death
of a person or individual that are

daa98789-b67f-4eb7-aed8-9a4abc81f182-1
00:59:13.454 --> 00:59:15.120
causing the impossible?

c76087b9-ec49-4fe8-adbe-7632a5fcd470-0
00:59:15.960 --> 00:59:17.600
Is there?

5002e285-40df-4e0f-9a7a-8981748a29e8-0
00:59:17.600 --> 00:59:20.760
Oh, just get buried,
get buried fast and not in a box.

46b98434-141f-4542-850d-f86cf3b9d689-0
00:59:20.760 --> 00:59:23.920
So that could that be river?

ac046ec1-a6d2-4896-8395-708d45373c63-0
00:59:24.920 --> 00:59:25.040
Yeah.

fbcac44d-4959-49f7-a690-056624aa1b13-0
00:59:25.040 --> 00:59:28.080
I'm wondering about lifestyles where they
live.

cc3eb872-4d44-40d0-8be8-8505cb1e09c8-0
00:59:28.080 --> 00:59:30.197
Oh,
there's there's a huge bias in the fossil

cc3eb872-4d44-40d0-8be8-8505cb1e09c8-1
00:59:30.197 --> 00:59:30.520
record.

7aec73eb-453e-4c8e-952f-8bc3d336dfaf-0
00:59:30.520 --> 00:59:33.940
And that's what we do, the students,
we say, OK, let's look at this fossil,

7aec73eb-453e-4c8e-952f-8bc3d336dfaf-1
00:59:33.940 --> 00:59:36.865
what's happened to it,
Have carnivores come and not on it, blah,

7aec73eb-453e-4c8e-952f-8bc3d336dfaf-2
00:59:36.865 --> 00:59:37.360
blah, blah.

2de0ebe0-6dad-41b2-816c-368f4c8f6a42-0
00:59:37.360 --> 00:59:40.000
And then is this going to be a fossil?

ebfb23aa-f601-4299-bf03-e7fa21b8b550-0
00:59:40.000 --> 00:59:43.880
And if it's in the Highlands, the uplands,
there's no way it's going to get buried.

8d1814f6-52ad-4dbc-8f50-7ffdf69fd4e3-0
00:59:43.880 --> 00:59:49.000
And the sun usually just blasts away the
the sun, the wind, the rain, soil acidity.

e04f17b2-50b7-46fe-99b2-bd49bced4b18-0
00:59:49.000 --> 00:59:54.411
So the key is that often times there's a
site that Sarah and I work at where every

e04f17b2-50b7-46fe-99b2-bd49bced4b18-1
00:59:54.411 --> 00:59:57.280
other step you're smashing a hippo or
croc.

dfe105de-0533-4dcd-80f7-d5a177b0b6e8-0
00:59:57.720 --> 01:00:01.400
And it's a hippo or croc because these
are ancient river deposits.

75f62ded-bbfe-4dd5-bc73-336d4567b61f-0
01:00:01.400 --> 01:00:04.572
And so naturally,
the things that actually live there are

75f62ded-bbfe-4dd5-bc73-336d4567b61f-1
01:00:04.572 --> 01:00:06.760
the ones that are most often fossilized.

b7da83e3-6370-4641-8246-7d14f66348df-0
01:00:06.760 --> 01:00:11.256
So there's a bias in the record for
things that were using river environments,

b7da83e3-6370-4641-8246-7d14f66348df-1
01:00:11.256 --> 01:00:15.640
lake environments where you have burial,
sedimentation process is happening.

8653ee61-ea8d-4f09-9af9-b86d2a60543c-0
01:00:16.000 --> 01:00:16.240
Yeah.

fcfb4b74-b974-482a-ba97-a28dd9fa3d10-0
01:00:17.600 --> 01:00:18.160
Thank you very much.

1eb7bd7e-6ade-4649-a08c-a24546a39e3f-0
01:00:19.160 --> 01:00:19.480
Thank you.