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0:49

Hello, and welcome to CrowdScience from

0:51

the BBC World Service. This

0:53

is the show that searches the world

0:55

to find answers to our listeners science

0:58

questions. It's a wonderful job.

1:00

And in the course of doing it this year,

1:02

I've met some fascinating people and

1:04

sometimes come across tales don't

1:07

quite fit with the quest in hand,

1:09

but still draw a laugh or a gasp.

1:12

This is the chance to hear that tape.

1:15

Over the course of this episode, I bring

1:17

you a case of workplace bullying, but

1:19

with parrots, you'll get the low down

1:21

on our search for the perfect cocktail

1:23

ice made with forty thousand year old

1:25

Glacial, we traveled to Kenya to

1:27

visit the disaster room where scientists

1:30

keep watch for weird new weather, and

1:32

I'll take you to where the bodies aren't buried.

1:35

Yes, you get to meet the best

1:37

and the worst of humanity preserved

1:39

by a special society who thought

1:41

they could tell what you were just by looking

1:44

at your face. Along the way,

1:46

I'll be joined by members of the crowd science

1:48

team who shared each adventure. And to

1:50

start, I'm joined by Florian Borr.

1:52

Florian, thanks for coming to the studio.

1:54

No worries at all. Happy to be here. So

1:56

earlier this year, we made an episode of

1:58

CrowdScience asking can

2:00

animals count short

2:02

answer? Well,

2:03

it's it's very complicated and think people

2:05

should just go back to a back catalog and listen

2:07

to the long version. One person we

2:09

interviewed as part of that was Irene

2:11

Pepperberg who had a very special parrot

2:13

called

2:14

Alex. Why was Alex so

2:16

unusual? Well well, the big problem

2:18

with this type of research is that you can't

2:20

just ask animals if they can

2:22

count. So if they cannot talk, they can

2:24

communicate with us, and it's kind of difficult to

2:26

find out stuff above them. Right. So flies

2:28

might be amazing at algebra, but we'll never

2:31

know unless we can devise experiments that

2:33

allow them to show off their mathematical

2:35

skills. Exactly. But Alex,

2:37

he could actually tell you. So

2:39

after Irene spent years training

2:41

him, he could tell you a number.

2:43

And I asked Irene to tell me a little

2:46

bit about what Alex was like. He

2:50

was a very interesting creature. He

2:52

was very curious. He

2:54

was very interested in learning. So

2:56

overall, he learned about a hundred different labels

2:59

for various objects and materials

3:02

and places and foods. He learned

3:04

seven colors and five shapes. He

3:06

learned quantities up to eight, which

3:08

again was quite high for a

3:10

nonhuman. So

3:12

I had a long chat with

3:14

Irene and I wanted to know,

3:17

does this mean that parrots can count

3:19

or does this mean special parents

3:21

that you train up every day in the lab

3:23

like Alex can count because

3:26

Alex wasn't the only parent in the lab.

3:28

Right. He was just the first but

3:30

then later he was joined by another parent called

3:33

Griffin.

3:33

And that's how Irene discovered Alex

3:36

could add. But we were just messing

3:38

around with Griffin one afternoon. And

3:40

we were clicking. So we used, you know,

3:42

clicks. How many? And

3:44

I asked Griffin, and he looks at me,

3:46

he turns his little bit, and he won't answer.

3:49

So Irene clicks Toy small.

3:51

And I go,

3:51

Griffin, listen. How

3:54

many? And he turns again, turns this

3:56

little beek won't answer. And on the next cage,

3:58

Alec goes four. And Irene

4:00

looks over at Alex and

4:01

says, no, you're wrong. I picked twice,

4:04

and she tries Griffin again with two

4:06

more clicks. And I go over to Griffin

4:08

and I say, listen, how many?

4:10

And Alex says

4:11

six. When I look at him and I

4:13

realize he's adding all those clicks.

4:16

Alex was a clever bird. Mhmm.

4:18

And I say was because he

4:20

died tragically

4:21

young. Yeah.

4:21

He had a heart attack, so it's kind of the

4:23

equivalent of a human going out in the

4:25

fifties. So as we've established,

4:28

Alex wasn't the only parrot in

4:30

the lab. He was just the first, and I

4:32

wondered if Griffin could step up

4:34

and take his place. And this was

4:36

where Irene told us and this didn't

4:38

get to go in the program, but I love it.

4:40

About workplace intraparate

4:43

bullying. Take a listen to this.

4:48

Is it possible to replace Alex?

4:52

Well, the problem with

4:55

that is replicating exactly

4:57

the same environment. So

5:00

for example, Griffin does not have as much

5:03

speech as Alex, because

5:05

they were in the same room for most of

5:07

the time that we were training Griffin. So

5:10

Alex completely believed

5:13

Griffin. So we'd ask

5:15

Griffin Griffin, you know what color? And

5:17

Alex would either do something like say,

5:19

green, talk clearly. Because

5:21

Griffin was just learning, so he'd

5:23

say, I'm like,

5:23

hey, Alex wouldn't let him do it

5:26

or he'd say, I'm like, no, tell me what shape.

5:28

And Griffin would look at us, look at Alex, shrug his

5:31

little birdie show and tell her, or do I answer her? No.

5:35

So although he has quite a a decent

5:37

amount of speech. It's nothing like what Alex

5:39

did. And he's also become the

5:42

kind of student I'd say that just tell me what I have

5:44

to do to get a, because

5:46

he was afraid of making a mistake. So,

5:50

you know, he's very, very smart. And he's as I

5:52

said, he's done things that Alex never

5:54

never even But

5:56

we have to show him what to do, and then he's like,

5:58

okay, I'll do what I get it. Bingo. You

6:00

know, I've got it. And

6:02

he won't make inferences to a certain extent,

6:05

but, you

6:05

know, not the kinds of leaps

6:07

that Alex was doing because he

6:09

hasn't got the confidence. And

6:12

that's Alex's fault. I think

6:14

so. That's a great story and also

6:16

a little bit

6:17

tragic. Yes.

6:19

I mean, Alex was an only group of fifteen

6:21

years. And he had this army

6:23

of students

6:25

who talked to him the way they talked to a

6:27

toddler. Where do you wanna go? What do you wanna

6:29

do? What do you wanna eat? That

6:31

was Irene Pepperberg talking about

6:33

Alex, yet having the whole

6:35

lab to himself being a

6:37

toddler and then suddenly

6:40

This other bird Griffin comes

6:42

alone. Yeah. I think it's a it's an incredible

6:44

story. It's like it's like yeah. Him being an

6:46

only child for fifteen years. And sort

6:48

of having these researchers treat him

6:50

like a baby for the longest time. And

6:52

then somebody else comes along and suddenly

6:54

needs to share that lab space with

6:57

some other bird that you don't know that just

6:59

comes along and takes your

7:00

place.

7:00

Who can't even speak properly?

7:03

I know. Right? Who would but it it

7:05

makes it an interesting case because I think you

7:07

have Alex who's like the scientific

7:09

wonder and at the same time like a

7:11

horrible bully to like another

7:13

parent. I don't know. It's interesting

7:15

because you have you have like heroes, scientific

7:18

heroes, I guess. And sometimes you find out if you

7:20

look back at history that there were kind of mean

7:22

and not quite

7:24

nice. And even Alex, the parent

7:26

wasn't as nice as people thought it was.

7:28

So are you suggesting we should cancel Alex?

7:30

Yes. I think so. I think she should cancel

7:32

him. And definitely, that's that's

7:34

the room we should go down. I

7:37

mean, the other thing that I find interesting is that as

7:39

a science communicator, CrowdScience you try

7:41

not to sort of anthropomorphize animals

7:43

too much. But in this case, you

7:45

know, the question was kind of our had two animals

7:47

of similar mathematical abilities

7:49

humans. Are they human in some way? And

7:51

I think this, to me, at least, feels

7:54

like it's an incredibly human thing to

7:56

sort of feel jealousy of

7:58

another being being there and

8:00

taking your place and and sort of pulling,

8:02

like, it just the episode

8:04

was a lot about the intelligence of animals

8:06

I mean, Pepperburg said that Alex is an example

8:08

of sort of how smart animals can be,

8:11

but maybe with some of that social intelligence

8:13

and intelligence in general come

8:16

some of the real flowers that

8:18

humans have like jealousy and

8:21

harassment and

8:21

bullying. The

8:22

ability to be mean is it may

8:25

be a byproduct of of intelligence.

8:27

Maybe. Maybe.

8:29

Well, I'm so pleased that we had a chance to tell

8:31

this story because it stayed with me ever since

8:33

we made that program. And it just

8:35

didn't fit in the

8:36

original. It wasn't about counting.

8:37

No. No. It wasn't, but still

8:40

incredibly interesting.

8:41

Florian, thank you so much.

8:43

Thank you. You

8:45

can stay with me whilst I

8:48

talk about bodies in Edinburgh or

8:50

you can head off. Oh, I'm gonna

8:52

stay.

8:55

Have you ever come across the

8:58

and I'm gonna say science

9:00

in massive inverted commas

9:02

here. Science of phrenology. Do

9:04

you know what that is? Yes. Yeah. Yeah. I

9:06

remember hearing about that. It's about feeling

9:08

somebody's head and sort of

9:10

being able to tell by the bumps,

9:12

how certain characteristics

9:14

and personality traits and stuff. That was

9:16

it. Right?

9:16

So at the start of the year,

9:19

we had a question about

9:21

can you tell someone's intelligence by

9:23

the size and shape of their head?

9:25

And so I went up to Edembury University

9:28

where in Edembury University

9:30

anatomy

9:30

department, they have one of the

9:32

largest collections of

9:35

frenology, analyzed death

9:38

masks --

9:38

Oh, wow. -- from this society, and this

9:40

thing was this was hugely

9:43

popular in the

9:45

eighteen twenties, eighteen thirties. Mhmm.

9:47

This idea that you could tell a lot

9:49

about someone from what

9:51

their face looked like on the outside.

9:54

So I was focused on that program and

9:56

intelligence, but there were so many more

9:58

interesting stories in

10:00

this phrenology

10:01

center. So this is a

10:04

recut, director's cut.

10:06

Nice.

10:07

Phrenology was a nineteenth century science,

10:10

which we see today very much is a pseudo

10:12

science. That's Malcolm McCollum.

10:15

Curator of Edinburgh's Anatomical Museum.

10:18

Edinburgh in Scotland was the center of

10:20

interest for phrenology in the

10:22

UK. And phrenologists would report on

10:24

people's personality based on

10:26

examinations of their skulls.

10:28

Malcolm and I are in a room filled

10:30

with skulls. Preserved body parts as well,

10:32

and plaster casts of the heads

10:34

of people of

10:35

note. Isaac Newton, Helios.

10:38

Oh, hello Isaac Newton.

10:40

So Isaac Newton, great

10:43

scientist. So one of the world's

10:45

most famous scientists. We

10:47

know that un discovered gravity and the

10:49

laws underpin modern

10:52

physics today. So the technology is

10:54

new with us. And they

10:56

decided that as the

10:58

organ of weight was very

11:00

important for him in terms of his

11:02

reading. And was understanding the concept of how

11:04

heavy something else. So that

11:06

was their main takeaway of the psychological

11:08

reading of Isaac

11:09

Newton. It's this organ of weight

11:11

that's enlarged. And

11:13

just to

11:13

clarify, an organ of weight

11:16

is your ability to

11:19

way how heavy things

11:19

are. Yeah.

11:21

I've got it seems that I've just talked

11:23

about this sort of stuff to the concept of how heavy

11:25

something is.

11:26

Let's go to Tardy. Who's Tardy?

11:29

Tardy was probably well,

11:32

probably one of the world's worst pilots. He

11:34

was involved in

11:36

a rather bloody mutiny on a on

11:38

a pirate ship. And we've actually got

11:41

a copy of his skull here. Well, first of

11:43

all, he couldn't navigate a ship. And

11:45

also apparently suffered from sea

11:47

sickness. No

11:48

problem. So you didn't mean worst

11:50

pirate has in most blood first. No. No. No.

11:53

He's less I sound like comically

11:55

bad, but also very dark because

11:57

somebody has murdered a lot of people.

11:59

Highlights were interesting differentologists because they're obviously

12:01

quite a unique breed to BiTE and what they

12:03

are doing. The report for

12:05

Tarete has the most

12:07

developed region were associated with

12:09

destructive

12:09

us, and that was explained

12:12

as yearning for the pilot's

12:14

life.

12:14

Alright. Who's this chap next door? It

12:16

was known as chief Buchanan, the states from the nineteen

12:18

oh five, so it actually is really late

12:20

in terms of the phrenology

12:22

collection. He was a group who were

12:24

taken as living

12:26

specimens and natural history museum. So it was like almost a

12:28

human zoo, and they

12:30

were they were captured that the

12:32

faces were captured through life masks.

12:34

And he actually came up dead and brow as well.

12:36

So as he came on another tour, but the

12:38

phrenologists were kind of interesting and

12:40

what made them the people

12:43

that they were in terms of some of their

12:45

attributes. As the nineteenth

12:47

century went on, places like this

12:49

medical school were collecting skulls from all over

12:51

the world. Using the networks of the British

12:53

Empire, British

12:56

Army, former and medical

12:58

graduates were basically collecting

13:00

skulls illegally

13:02

stealing them basically. And then they

13:04

were finding the way back there and where they'd be

13:06

measured them exhaustively and then

13:08

used in an automated as

13:10

well. Okay. And Edrimi

13:12

University is repatriating these

13:14

now, aren't you? Yes.

13:16

Repatriation started here in

13:18

nineteen forty seven, Pascal went back

13:20

to Schlosser or Salon as it was at the

13:22

time. And then there was a large wave

13:24

of repatriations in the 1990s to

13:27

Australia, New Zealand and Fiji.

13:30

And most recently, we've been working

13:32

with indigenous groups around the world

13:34

to try and return some of their

13:36

ancestors. Thanks

13:38

once again to Malcolm McCalumbar.

13:41

This is CrowdScience the BBC World

13:43

Service on Marni Chest and this

13:46

is the episode where we play the

13:48

stories that have stuck with us on our

13:50

travels this year. Joining me now

13:52

in this video is producer Ben Mottley.

13:54

Hello, Ben. Hello.

13:55

Ben, I'm gonna play you probably

13:58

the most memorable welcome

14:00

I've ever received. Yes. This was

14:02

just the most

14:04

wonderful thing to record that

14:06

I have ever experienced.

14:27

Ben, where was that? That

14:29

was in Southern Kenya near the

14:31

Tanzania border with Mount

14:33

Kilimanjaro towering over us.

14:35

It was in a

14:37

place called Ambrellie, the Ambrellie

14:39

National Park. And we went there

14:42

to visit some Masai

14:44

tribesmen who are very much at the

14:46

sharp end of climate

14:48

change. And that was them saying hello. That was

14:50

them saying hello. Yeah. They were singing

14:52

as we got out of the car. It was just

14:54

the most wonderful uplifting,

14:58

moving welcome to anywhere

15:00

that I think any of us have ever

15:01

had. It was absolutely wonderful. And

15:04

you said they were telling us about their experience

15:06

of climate change. You could see

15:08

that it was not a very healthy

15:10

landscape. It was definitely not a healthy

15:12

landscape and they kept in

15:14

insisting to us that the landscape

15:16

we could see was not what they were used

15:18

to. They're used to sort of

15:20

green grass. They're pastoralist. They

15:22

graze cattle. And

15:24

that's the complete opposite of what

15:26

we experienced Here's a short clip

15:28

of of me noticing the vast

15:30

amounts of no grass.

15:32

So Esther, where we're sat?

15:35

There's about three centimeters of

15:38

just like dust

15:40

under our

15:40

feet. And That's all

15:43

I can see in every direction.

15:45

Is this normal?

15:47

Not tomorrow. Not

15:50

tomorrow at all. That was one

15:52

end of what we did, which was going to visit

15:54

people experiencing climate change.

15:57

And one of the places we visited

15:59

which didn't make it into our program, but has

16:01

stayed with me is Iqpak, which

16:04

is a climate prediction and

16:06

application center on the edge of

16:08

Kenya's cap on

16:08

Nairobi. Shining new building,

16:11

quite difficult to find. We did get

16:12

lost several times, I think, trying to

16:15

find it.

16:15

But clearly built as a reaction to

16:18

the emerging climate crisis. Yeah.

16:20

And you got really excited about

16:22

this particular and their situations room.

16:24

Because it was like something out of a

16:25

movie. It was like a control

16:28

center for a moon landing or

16:30

something like that.

16:31

I

16:31

mean, just of just the phrase disaster

16:33

operations room, situations

16:36

room, and And

16:37

very armageddon. It is. And I wanted

16:39

to know what the situations were.

16:41

So didn't understand what was on any of

16:43

the screens, but there were lots

16:45

of maps of the East Coast of Africa.

16:48

And Viola, ATN0 an

16:50

earth observation

16:50

expert, was at hand to explain what

16:53

sort of potential disasters they were

16:55

looking for. So mostly climate

16:57

related situations. So

16:59

we are looking at drop. We are looking

17:01

at flats. We are looking at

17:03

pests and

17:03

diseases. We are also looking at agricultural

17:06

conditions as

17:06

well. And in front of us, is

17:09

this Bank of TV screens

17:11

huge huge

17:13

screens? And there's a map of East Africa in

17:15

the center with all of these sort of little

17:17

arrows. What's that? And so what you

17:19

see on this screens are what

17:21

we're calling the life situation screens.

17:24

And the idea behind them is

17:26

that at any one point, we want to

17:28

have a very clear picture of what is happening where

17:30

in terms of disasters and hazards

17:32

as well. So what you see on

17:34

the first screen is what we're

17:36

calling the East Africa hazards

17:38

watch. And this is Allie warning systems,

17:41

and it provides near real time

17:43

information on different hazards.

17:45

Okay. So say there is

17:47

currently this very heavy

17:49

rainfall cloud over

17:51

Somalia. What do you do with that

17:53

information? So we disseminate the

17:55

information through

17:57

various ways. One is a mailing list, but the other

17:59

one is through communication channels

18:01

like WhatsApp or social media as

18:03

well. So we have us

18:05

WhatsApp that is specifically

18:07

for focal points from the disaster

18:09

risk management institutions within

18:11

the countries. We get the information, we share

18:13

it with them. They're able to downscale

18:16

this information to national level.

18:18

So for example, the information

18:20

that we disseminated over such

18:23

Sudan. The Sudan, we're able to now

18:25

create a bulletin and then also

18:27

transmit this information through the

18:29

radio stations and the TV stations

18:31

as

18:31

well. Yeah. And it turns out it's not

18:33

just weather that they're able to detect as

18:35

well because there was one map, which

18:37

it looked like it had a really big

18:40

rain cloud on it just heading over towards

18:42

Kenya, but it turned out to be a

18:44

swarm of desert locusts. And

18:46

that swarm took everybody by surprise

18:48

when it arrived following some extreme

18:51

weather in spring twenty

18:53

nineteen.

18:53

So mid-twenty nineteen, that's

18:56

when the outlook has inflation started.

18:58

And what we see is that there was

19:01

a stream of

19:03

extreme climate events. So

19:05

just to start way back in May twenty

19:07

eighteen, you had cyclone cigar.

19:10

And then shortly after cyclone

19:12

Makena and then shortly after

19:15

cyclone Luvan. And what this

19:17

means is that you ended up experiencing

19:19

very heavy rainfall over the desert

19:22

areas, which then caused abundant

19:24

vegetation as well. And all these

19:26

factors bringing together make for very

19:28

suitable driving conditions

19:30

for desert lockers. So

19:32

the rains mean more

19:36

vegetation, more vegetation means,

19:38

more food for locusts. is that,

19:40

but also for desert locusts to lay

19:42

eggs, I believe they require about twenty

19:45

millimeters of water

19:47

on the soil surface. So you have

19:49

heavy rainfall, then you have this

19:52

paddles forming, and then you

19:54

have dessert locusts being

19:56

able to breed. Much more

19:58

quickly. So you know that after the rain

20:00

come the locust? Yes.

20:02

So what you're seeing is

20:04

the intensity and the frequency of

20:06

extreme climate events has increased

20:09

and the projections also show that this

20:11

is going to increase in

20:13

the

20:13

future. So one of

20:15

the grim consequences of climate

20:17

change is that you do get heavier rainfall.

20:19

And when you get heavier rainfall on

20:23

baked grounds. It just sits

20:25

there like it's on pottery, and

20:27

that's what you need for these locust to

20:29

lay their

20:29

eggs, and that's why Kenya had

20:32

the worst locus plague in seventy years.

20:34

Yeah. And it also brought home what

20:36

a global issue

20:38

the effects of climate change

20:41

are because These locusts are

20:43

hatching thousands and miles away in Yemen.

20:45

This is not just a Kenyan

20:47

problem. The locusts had

20:49

come from elsewhere to

20:51

invade Kenya and it gave a

20:53

really good sense of

20:55

how all of these different nations

20:57

need to start to work together to

20:59

try and mitigate the effects

21:01

of climate change if nothing else.

21:03

Global weather systems, global

21:05

pest migration, Glacial

21:08

required. Exactly. Whether

21:10

those global solutions exist or not,

21:12

that's an entirely different

21:14

matter.

21:14

I I going to do more on climate change.

21:16

I don't can't imagine why

21:18

you think that. But, yes, I think

21:21

it's in entirely possible. There will be

21:23

questions in the inbox about it. So yeah.

21:25

Thank you, Ben. And moving from the

21:28

drought stricken landscape of to

21:30

another area also affected by climate change, but

21:32

this time a little bit colder.

21:35

One of the most extraordinary

21:37

trips I had the privilege of doing

21:39

this year for CrowdScience a

21:42

trip to Greenland and that was with

21:44

me and my producer, Sam

21:46

Baker, Who joins me now? Hello, Sam? Hello.

21:49

Greenland. What did you think? Greenland

21:51

blew my mind, actually.

21:54

I think, well, the ice sheet in particular.

21:56

Greenland itself reminded me of

21:58

other small fishing communities I've been

22:00

to

22:00

before, but I don't

22:03

know. The ice sheet was like a

22:05

landscape I've never seen before. And

22:07

we were there to get onto that

22:09

ice sheet. We were following this very

22:12

charismatic scientist called Professor Jason

22:14

Box. And he

22:16

was there with his team trying

22:18

to measure physically not with models remotely, actually

22:21

getting out onto that ice sheet to

22:23

try and work out among other things

22:25

how fast it was

22:25

melting. Right? Yeah. And how much

22:28

was already baked in?

22:30

You know, how much has

22:32

our contribution to greenhouse

22:34

gases

22:35

how much does that mean that Greenland is going

22:37

to melt for sure? Like, kind of

22:39

the physics of that, if you will. So we

22:42

made a whole episode of that. But

22:45

the bit that did not go in

22:47

was this was

22:49

us talking to Jay as they

22:51

were preparing all of their kit at

22:53

the hotel where we were all staying

22:55

in this tiny little

22:57

village, and they were preparing all of their

22:59

kit, getting it ready to go into

23:01

the helicopter so that they could not

23:03

waste any time when they were out on the ice

23:05

because it was all very weather dependent. Right?

23:08

Yeah. And I was worried we weren't gonna actually get out there. I

23:10

mean, we only had was it a week

23:12

in total? And there are

23:14

definitely times when they don't

23:16

make it out there because weather is so bad every

23:18

day. So I I felt very lucky that we

23:20

did get to see it. So

23:22

this sum is from the first evening

23:24

as Professor Box and team are prepping their

23:26

kits. Mhmm. And I ask

23:27

him whether scientists ever use any of

23:30

Greenland's ice and drinks

23:32

and he says there's a particular type

23:34

we need to find. And

23:36

we we call that party ice.

23:39

it

23:42

the best party ice you can find floating

23:44

out in the water. Mhmm. It's also called

23:46

black ice because it's clear.

23:48

So you bring that that back and

23:50

you put some of that in your glass

23:53

and because the ice fabric has

23:55

larger crystals and it

23:57

has, like, preference orientation of the

24:00

ice crystal matrix, you

24:02

get a much more

24:04

aesthetic ice than the

24:07

refrigerator ice. Refrigerator

24:09

ice freezes too quickly. This stuff,

24:12

you know, develops over thousands of

24:14

years. So in your whiskey glass you

24:16

have this like forty

24:18

thousand year old ice

24:20

cube and it's floating in a

24:22

way way, the shape

24:25

is self similar

24:27

with icebergs, the fractal geometry

24:30

of nature. So shape of an

24:32

iceberg in your whiskey glass is

24:34

the same as it is out in

24:36

the

24:36

sea. And you can

24:40

behold that as you're enjoying your fine

24:42

drink. So

24:45

I think it's fair to say

24:48

that That set

24:50

us on a bit of a quest. Aside

24:52

from making two episodes of CrowdScience,

24:54

which we did do,

24:57

we, Sam, both, got a little

24:59

bit intrigued by

25:01

trying to find party ice.

25:03

Right? I mean, who didn't want

25:05

the ultimate cocktail ice in

25:07

that drink. Yeah. You know, it's a

25:09

it's a fleeting experience. You can only have

25:11

while you're there, I suppose. We took

25:13

a trip out into the fjords and we

25:15

got the boat owner Lars,

25:17

very nice chap to

25:19

fish some ice out.

25:21

So we were looking for black

25:22

ice, but what he came out with didn't

25:25

look like the forty thousand year old

25:27

stuff. Right? Yeah. You could see

25:28

quite a few more bubbles in it.

25:31

And you could even hear them.

25:33

This is us in our

25:36

hotel room. With

25:39

five thousand year old

25:41

ice, and I just happened to I

25:44

always travel with miniatures

25:46

of of liquor. We

25:47

came prepared. We came prepared. Right. Yeah.

25:49

They said bring any supplies with you

25:51

so so we did. And

25:53

this is us. Attempting some mix

25:56

ecology in our in our

25:58

hotel room. That's

26:04

tiny bits of the

26:07

atmosphere from Earth from five

26:09

thousand years ago. Releasing

26:13

themselves. And it when you

26:15

put it in the liquids, it

26:17

you could hear it.

26:19

Yeah. Kinda reminded me of

26:21

rice krispies, like that snack snap

26:23

crackle pop, like, get those

26:26

little crackily sounds coming out

26:28

of it, that air

26:29

releasing, which was very cool to

26:31

listen to. I suggested to Jason

26:33

that this was more than just

26:35

a fun thing for researchers

26:38

to to do in their

26:40

spare evenings when they're in

26:41

Greenland. He could potentially make

26:44

a bit of money off this. One

26:46

of the great things about coring,

26:48

if you can date a certain

26:50

layer, if you get chronology in

26:52

the ice

26:53

is, okay, this is the year of

26:57

Christ. This is the year of Elvis. So

26:59

you can drink

27:00

a whiskey or you can take water from

27:02

a certain period of time. This is Julius

27:04

Caesar. This is this period

27:06

of time. And and

27:08

you market that you could actually sell

27:11

ice and water from

27:13

a specific

27:13

date. And

27:14

I think

27:15

there's a market for this there's

27:17

a really good side hustle because this isn't

27:20

cheap science, is it? So No.

27:22

That could subsidize.

27:24

Absolutely. Fund all that expensive

27:27

research with a new

27:29

business venture, if you will. One of the things

27:31

I didn't realize until I got to Greenland

27:33

was just how many different

27:35

kinds of ice there seemed to

27:36

be? Yeah. I mean,

27:39

when we were boating

27:41

through that fjord, we saw all these

27:43

crazy icebergs like big white ones

27:45

that looked almost kind of snowy and

27:47

then these kind of

27:49

deep turquoise blue jewel like

27:52

ones. So those are coming from

27:54

different parts of the

27:56

glaciers, which we could see. Right? We could

27:58

see kind of the edge of that glacier

28:01

as if someone had just like chopped

28:03

it off, which essentially it was calving

28:05

off into the

28:08

fjord. But what yeah. What I

28:10

learned recently is that So the

28:12

top, you have this crust, the

28:14

fern, it's called. So this

28:16

is the ice that comes down each

28:18

winter or snow, and it kind of turns

28:20

into this crusty ice that we

28:22

were walking on on the ice

28:24

sheet, and that's got a lot of air in

28:26

it. And then each year that gets

28:28

pressed down, So the

28:30

newer ice towards the top still has quite

28:32

a bit of air in it. But

28:34

as it gets pressed further

28:36

and further down, more of

28:38

that air gets squished

28:40

out. So the stuff at the bottom

28:42

is this deeper color

28:45

with with less

28:47

air bubbles, and that's how they can date

28:49

these different sections of it, and

28:52

have a better sense of, you

28:54

know, how much C02 there

28:56

was two thousand than years ago

28:58

or whatever they're looking

28:58

at. This is how they date CA2

29:01

levels going back like

29:03

a million years.

29:04

Right? Yeah. I think they

29:07

have gone back eight hundred thousand years

29:09

so far, but they're working right now

29:11

in Antarctica on getting

29:13

back to three million years

29:14

ago, which is mind boggling. But So trip

29:17

to the other pole of the earth.

29:19

Maybe we can

29:21

get Maybe we can get a crowd

29:23

science going where where we get to go to

29:25

the Antarctic. Haven't done that

29:27

yet?

29:27

Yep. Go through the oldest ice core.

29:30

I

29:30

mean, if you will, Sam. Yes.

29:31

Absolutely. I mean, we've already got

29:34

our our cold weather gear, so we're good to go. I'd say.

29:36

Well, that's us out of time. Do

29:38

keep your questions coming listeners and thanks

29:40

to the team for sharing stories of

29:43

bullying parents party ice, locust

29:45

plague, and terrible pirates.

29:47

Right. CrowdScience since

29:50

you're still here, I'm gonna get

29:52

you all to coordinate on

29:54

reading the credits, please. You've

29:56

been listening to crowd science from the

29:59

BBC World Service. The

30:00

stories you heard were by Me, Flooringboard, and Me,

30:03

Ben Motley. And Me,

30:04

Sam Baker. This whole show runs

30:06

on listener questions. So if you

30:09

have anything. You want us to turn into a custom

30:11

science documentary for you. Do drop us

30:13

a line. The email address is

30:16

crowd science at BBC

30:18

dot c o dot u

30:19

k. Thanks for listening.

30:22

Bye.

30:26

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30:34

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30:39

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30:41

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30:44

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30:44

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