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This is Ecomaths, a brilliant way of looking at | 0:00:02 | 0:00:04 | |
fascinating, real-life situations | 0:00:04 | 0:00:06 | |
to understand how maths can be used to help create a sustainable future. | 0:00:06 | 0:00:10 | |
In the first film we explore renewable energy using algebra. | 0:00:10 | 0:00:14 | |
Then we look at food production comparing lamb and snails | 0:00:14 | 0:00:19 | |
using area, fractions and ratios. | 0:00:19 | 0:00:21 | |
And finally, in a trial of a natural pesticide, | 0:00:21 | 0:00:24 | |
we calculate volumes and concentrations using standard form. | 0:00:24 | 0:00:28 | |
VIOLIN MUSIC PLAYS | 0:00:30 | 0:00:32 | |
Hiya, I'm Stef. | 0:00:43 | 0:00:44 | |
Now, if you want to keep warm and cook food you need fuel, | 0:00:44 | 0:00:48 | |
and the oldest fuel known to humans is this stuff - wood. | 0:00:48 | 0:00:52 | |
You might think that all wood is pretty much the same, | 0:01:05 | 0:01:08 | |
but what's amazing is that different wood | 0:01:08 | 0:01:10 | |
contains different amounts of energy, sometimes very different. | 0:01:10 | 0:01:14 | |
But why does it matter? If we want to get warmer, | 0:01:14 | 0:01:16 | |
why don't we just stick another log on the fire? | 0:01:16 | 0:01:18 | |
Well, when we burn any fuel we come across global warming issues | 0:01:18 | 0:01:22 | |
that affect the entire planet, so it's crucial to understand | 0:01:22 | 0:01:27 | |
how much energy is in our fuel | 0:01:27 | 0:01:29 | |
so that we can make the best possible use of it, | 0:01:29 | 0:01:31 | |
and that's where Ecomaths comes in. | 0:01:31 | 0:01:33 | |
It's a brilliant way of using maths | 0:01:33 | 0:01:35 | |
to help make the world a better place. | 0:01:35 | 0:01:38 | |
'And if you want to know about wood, ask a woodsman. | 0:01:38 | 0:01:41 | |
'This is Martin Charlton.' | 0:01:41 | 0:01:43 | |
-Cup of tea. -Hey, top man! -There you go. -So, Martin, | 0:01:43 | 0:01:47 | |
how come there is energy in wood? | 0:01:47 | 0:01:50 | |
It's carbon. | 0:01:50 | 0:01:52 | |
The trees take the carbon dioxide with the sunlight, | 0:01:52 | 0:01:55 | |
turn it into carbon and oxygen and so it's a carbon fuel. | 0:01:55 | 0:02:00 | |
So does all wood have the same amount of energy in it? | 0:02:00 | 0:02:03 | |
Yes, it can. It all depends on the amount of moisture | 0:02:03 | 0:02:06 | |
you've got in there and the density of the wood, | 0:02:06 | 0:02:09 | |
but it is the moisture that's the critical thing. | 0:02:09 | 0:02:12 | |
In an oak tree, for example, you will have 350 litres of water. | 0:02:12 | 0:02:17 | |
In one of these pine trees there will be anywhere between 15 | 0:02:17 | 0:02:21 | |
and 20 litres of water at any one moment in time. | 0:02:21 | 0:02:25 | |
So before you can burn it you need to get the water out. | 0:02:25 | 0:02:29 | |
-So I have here a very damp piece of wood. -Yup. | 0:02:29 | 0:02:33 | |
I mean, you can literally see the dampness in it, | 0:02:33 | 0:02:35 | |
and so, if I put that on the fire, what happens? | 0:02:35 | 0:02:38 | |
It will only smoulder, it won't burn, | 0:02:38 | 0:02:41 | |
because the energy in the fire, the heat in the fire, | 0:02:41 | 0:02:44 | |
is going to dry the wood out first, | 0:02:44 | 0:02:45 | |
it will drive the water off as steam, before it can actually burn the wood. | 0:02:45 | 0:02:48 | |
Let's try to understand how much energy is released | 0:02:48 | 0:02:52 | |
when we burn different types of wood, | 0:02:52 | 0:02:55 | |
and here's where a bit of algebra comes in handy. | 0:02:55 | 0:02:57 | |
So, Y. Y is the amount of energy that's contained in the wood | 0:02:57 | 0:03:02 | |
that can be released when we burn it. | 0:03:02 | 0:03:05 | |
X is the mass of the wood, the amount of it that we've got. | 0:03:05 | 0:03:09 | |
But it all depends on the different amounts of moisture in it. | 0:03:13 | 0:03:18 | |
It's a simple equation. When you double the amount of wood, | 0:03:19 | 0:03:23 | |
or biomass, X, you get twice as much energy, Y, out. | 0:03:23 | 0:03:27 | |
The tree - we'll select the tree for various reasons, | 0:03:28 | 0:03:31 | |
whether it's not suitable for fencing or timber, | 0:03:31 | 0:03:34 | |
can be used for biomass. | 0:03:34 | 0:03:36 | |
We will fell it, we will section it up into the proper lengths | 0:03:36 | 0:03:39 | |
for collecting it in the woods, and then we'll stack it | 0:03:39 | 0:03:43 | |
in the woods so it starts to lose moisture, and when it gets down | 0:03:43 | 0:03:47 | |
to around about 40% moisture then we'll come along with a big machine | 0:03:47 | 0:03:51 | |
and extract it to the roadside or to the place that will chip it. | 0:03:51 | 0:03:56 | |
Look at this! | 0:04:12 | 0:04:13 | |
All of that huge amount of wood from the forest has been turned | 0:04:13 | 0:04:17 | |
into a vast mountain of sawdust. Julian, hi, there. | 0:04:17 | 0:04:22 | |
-Hello, Stefan. -What's happened, why does it now look like this? | 0:04:22 | 0:04:26 | |
It looks like this because what we've done is we have chipped it | 0:04:26 | 0:04:29 | |
into wood chip and it's important that it's not sawdust. | 0:04:29 | 0:04:33 | |
It's all to do with how our boilers work. | 0:04:33 | 0:04:35 | |
And what we're trying to do is turn it into something that flows, | 0:04:35 | 0:04:38 | |
and can be moved in a consistent way | 0:04:38 | 0:04:41 | |
to get a consistent amount of energy from it. | 0:04:41 | 0:04:43 | |
What you're doing is you're increasing the surface area | 0:04:43 | 0:04:45 | |
of the chip in order for the air to get at it | 0:04:45 | 0:04:48 | |
and therefore for it to be able to burn effectively. | 0:04:48 | 0:04:51 | |
How do you work out the moisture level of the wood? | 0:04:51 | 0:04:55 | |
We can, in the field, use moisture meters, | 0:04:55 | 0:04:57 | |
which are sort of electronic gadgets really, | 0:04:57 | 0:05:00 | |
but here at the yard in the farm, | 0:05:00 | 0:05:02 | |
we can use something as simple as a domestic microwave. | 0:05:02 | 0:05:06 | |
I don't recommend people do it at home, but you take a certain amount. | 0:05:07 | 0:05:11 | |
Let's say 100 grams. You put it in the microwave, | 0:05:11 | 0:05:13 | |
heat it up, for a period, take it out, reweigh it. | 0:05:13 | 0:05:17 | |
Heat it up again, take it out, reweigh it. | 0:05:17 | 0:05:20 | |
Once the weight no longer changes, you've got a final weight, | 0:05:20 | 0:05:23 | |
and you subtract that weight | 0:05:23 | 0:05:24 | |
from your original weight and you have your percentage in effect. | 0:05:24 | 0:05:29 | |
The final weight of 73 grams | 0:05:29 | 0:05:31 | |
is subtracted from the initial weight of 100 grams, | 0:05:31 | 0:05:35 | |
to give the moisture content. In this case, 27%. | 0:05:35 | 0:05:39 | |
The energy Y is proportional to the mass X of the wood fuel. | 0:05:39 | 0:05:43 | |
The gradient function M depends on the moisture. | 0:05:43 | 0:05:46 | |
The lower the moisture, the steeper the gradient | 0:05:46 | 0:05:48 | |
and the more energy you can get from the wood. | 0:05:48 | 0:05:51 | |
So in terms of getting energy out of this stuff, | 0:05:52 | 0:05:55 | |
what are the other aspects of the equation? | 0:05:55 | 0:05:57 | |
Clearly you've got to cut the wood down, | 0:05:57 | 0:05:59 | |
so there's energy in terms of the chainsaws used, | 0:05:59 | 0:06:01 | |
there's energy in terms of the vehicles that are used | 0:06:01 | 0:06:04 | |
to actually get it out of the woods, | 0:06:04 | 0:06:06 | |
to transport it from the woodlands to our yards. | 0:06:06 | 0:06:09 | |
And clearly also in the chipper, | 0:06:09 | 0:06:11 | |
and then being transported from here, | 0:06:11 | 0:06:13 | |
being loaded then transported from here to the customer site. | 0:06:13 | 0:06:16 | |
-Is that a big part of it? -Indeed. | 0:06:16 | 0:06:18 | |
We try to deliver within a 15-mile radius, | 0:06:18 | 0:06:21 | |
maximum of 30-mile radius, and that gives you | 0:06:21 | 0:06:23 | |
a sense of the distance it travels. | 0:06:23 | 0:06:25 | |
Compare that to oil, which has often come halfway round the world | 0:06:25 | 0:06:29 | |
from Saudi Arabia or somewhere like that, and this is a local product | 0:06:29 | 0:06:33 | |
produced by local people, it's a local energy resource. | 0:06:33 | 0:06:37 | |
And this is where the fire is. | 0:06:37 | 0:06:40 | |
Wow, that's terrifyingly hot. | 0:06:45 | 0:06:47 | |
And it's amazing to finally see all of the energy that was stored | 0:06:47 | 0:06:51 | |
in the forest finally being released. | 0:06:51 | 0:06:53 | |
But this massive biomass boiler doesn't heat some factory. | 0:07:01 | 0:07:06 | |
It heats this place. It's a school, | 0:07:06 | 0:07:08 | |
and I'm going to find some experts who can tell me all about it. | 0:07:08 | 0:07:11 | |
-Hi, Eco-Team, how are you doing? -ALL: Hi! | 0:07:14 | 0:07:18 | |
Tell me about this biomass boiler, it's just so cool. | 0:07:18 | 0:07:20 | |
How much wood chip does it use every hour? | 0:07:20 | 0:07:23 | |
Well, to work it out we took the measurements of each container. | 0:07:23 | 0:07:27 | |
This container is six days' worth of wood chip to heat the school. | 0:07:27 | 0:07:31 | |
The students use the measurements to calculate | 0:07:31 | 0:07:33 | |
how much they need per hour, | 0:07:33 | 0:07:34 | |
so they can compare it with other fuels. | 0:07:34 | 0:07:36 | |
That's 2 metres 35. | 0:07:36 | 0:07:39 | |
So the amount of wood chips that go through that to heat | 0:07:40 | 0:07:43 | |
the whole school for one hour is 0.247 cubic metres? | 0:07:43 | 0:07:48 | |
-Yeah. -OK, well, that's fantastic, | 0:07:48 | 0:07:50 | |
so now we know how much wood chip the boiler uses. | 0:07:50 | 0:07:53 | |
The big question is, really, how does that compare to other fuels? | 0:07:53 | 0:07:57 | |
So, Natalie, you know about this, don't you? | 0:07:57 | 0:08:00 | |
Well, with the oil it's 3.4 times more energy | 0:08:00 | 0:08:03 | |
for every kilogram than biomass. | 0:08:03 | 0:08:06 | |
-Wow, that's a big difference, isn't it? -Yes. -So oil, | 0:08:06 | 0:08:10 | |
-3.4 times more energy. Per kilo that is, isn't it? -Yeah. | 0:08:10 | 0:08:16 | |
So it's a big difference, isn't it? So this, this is heating oil. | 0:08:18 | 0:08:21 | |
That gives you 3.4 times more energy per kilo. | 0:08:21 | 0:08:26 | |
-Mm-hmm. -That's a big difference. OK. | 0:08:26 | 0:08:28 | |
But what I want to know is how does it compare? | 0:08:28 | 0:08:30 | |
So let's get some gas on here. | 0:08:30 | 0:08:32 | |
How does wood chip compare to gas? | 0:08:33 | 0:08:36 | |
Gas, you get three times more energy per kilogram. | 0:08:36 | 0:08:41 | |
OK, so a little bit different | 0:08:41 | 0:08:42 | |
but still a big difference compared to it, isn't it? | 0:08:42 | 0:08:45 | |
Three times more energy per kilo. | 0:08:45 | 0:08:50 | |
So there's a huge difference in the energy per kilo, | 0:08:50 | 0:08:53 | |
but what about the cost, is there any difference? | 0:08:53 | 0:08:56 | |
Um, biomass is about 10% more expensive than gas. | 0:08:56 | 0:09:00 | |
-Oh, wow. So there is a significant difference, isn't there? -Mm-hmm. | 0:09:00 | 0:09:04 | |
So this is really interesting. There's a huge amount less energy | 0:09:07 | 0:09:10 | |
per kilo, and it's more expensive, so why would you go for wood chip? | 0:09:10 | 0:09:15 | |
Because it's not burning any fossil fuels. | 0:09:15 | 0:09:17 | |
Whereas trees can be regrown, we can't get the fossil fuels back | 0:09:17 | 0:09:21 | |
and in 30 years they might run out. | 0:09:21 | 0:09:23 | |
-Yeah. -So overall it's better for the environment. | 0:09:23 | 0:09:25 | |
Biomass should stay at quite a steady price | 0:09:25 | 0:09:28 | |
whereas things like oil should increase more | 0:09:28 | 0:09:31 | |
because there's less of them. | 0:09:31 | 0:09:34 | |
It's amazing to use maths to unravel the secret behind wood | 0:09:35 | 0:09:39 | |
as a biomass fuel, and I wondered if this could be inspiring for you. | 0:09:39 | 0:09:44 | |
Maybe you could change the way that your school uses energy using maths. | 0:09:44 | 0:09:47 | |
VIOLIN MUSIC PLAYS | 0:09:54 | 0:09:56 | |
Hiya, I'm Stef and this is glorious Dorset farmland, | 0:10:08 | 0:10:13 | |
which produces some of the finest food in the world. | 0:10:13 | 0:10:17 | |
The trouble is food production | 0:10:20 | 0:10:22 | |
uses a vast amount of energy, water and land. | 0:10:22 | 0:10:27 | |
And with the world population increasing so fast, | 0:10:27 | 0:10:31 | |
land is becoming a huge issue. | 0:10:31 | 0:10:33 | |
But the earth isn't growing in size, so we need to use land | 0:10:37 | 0:10:40 | |
in the best way possible to feed as many people as we can. | 0:10:40 | 0:10:44 | |
Now, I'm going to tackle this problem using maths, | 0:10:44 | 0:10:47 | |
but this isn't any old maths - this is Ecomaths. | 0:10:47 | 0:10:51 | |
ICE CRUNCHES | 0:10:52 | 0:10:53 | |
The best thing to start with is protein, cos it's essential | 0:10:55 | 0:10:57 | |
to our diet, and we get most of our protein from meat. | 0:10:57 | 0:11:02 | |
But there are other ways to produce protein. | 0:11:02 | 0:11:04 | |
Ways that might chill your soul. | 0:11:04 | 0:11:08 | |
Welcome to the weird and wonderful world of the gastropod. | 0:11:08 | 0:11:12 | |
Meet Sidney. | 0:11:16 | 0:11:18 | |
'I'm here to find out whether gastropods, or snails to you and me, | 0:11:19 | 0:11:23 | |
'could be the future of the burger and save the planet along the way.' | 0:11:23 | 0:11:28 | |
Easy, now! | 0:11:28 | 0:11:31 | |
Let's go to meet the man who uses clever Ecomaths to produce | 0:11:31 | 0:11:35 | |
a large amount of snails on a very small amount of land. | 0:11:35 | 0:11:38 | |
These are the breeding snails. | 0:11:38 | 0:11:40 | |
They are enormous! They're terrifying! | 0:11:40 | 0:11:43 | |
The bigger the snail that we use for breeding, | 0:11:43 | 0:11:47 | |
the bigger the egg we get from it. | 0:11:47 | 0:11:49 | |
Snails lay eggs? | 0:11:49 | 0:11:51 | |
-Yep! About 100 eggs in a batch. -Wow. | 0:11:51 | 0:11:58 | |
And with our system we ask them to lay eggs every five weeks. | 0:11:58 | 0:12:05 | |
Now, these have actually hatched and they're small baby snails | 0:12:05 | 0:12:09 | |
and they are absolutely tiny. | 0:12:09 | 0:12:11 | |
These are so sweet, | 0:12:11 | 0:12:12 | |
-you can see they've got those little tiny antennae! -Yeah. | 0:12:12 | 0:12:16 | |
-OK, so that's the first stage of being a baby snail. -Yeah. | 0:12:16 | 0:12:20 | |
-So can we have a look at the fatties? -Yeah, sure. | 0:12:20 | 0:12:23 | |
-So I've got the feed here. -Yeah. | 0:12:23 | 0:12:25 | |
-That's all they need? -That, for one day, yeah. | 0:12:25 | 0:12:28 | |
That's enough... That's 100 snails? That is tiny, | 0:12:28 | 0:12:31 | |
when you think about the amount of food you feed to livestock, | 0:12:31 | 0:12:33 | |
I think it's an amazing use of resources. | 0:12:33 | 0:12:38 | |
-This is a batch which is now ready for the market. -Wow! | 0:12:39 | 0:12:43 | |
How many snails do you produce every week to send off to the restaurants? | 0:12:43 | 0:12:48 | |
Around about 6,000 each week. | 0:12:48 | 0:12:50 | |
6,000 snails? That's a huge amount, isn't it? | 0:12:50 | 0:12:53 | |
Not really, if you think it's only... | 0:12:53 | 0:12:55 | |
The average amount of snails in a dish on a menu is six. | 0:12:55 | 0:13:00 | |
That's only 1,000 dishes. | 0:13:00 | 0:13:02 | |
Mmm, it's not bad. And how much does each snail weigh? | 0:13:02 | 0:13:06 | |
They weigh between 12 and 15 grams. | 0:13:06 | 0:13:09 | |
The big question is how much land do you use | 0:13:09 | 0:13:12 | |
to produce these 6,000 snails? | 0:13:12 | 0:13:15 | |
The boxes take up around about 400 square feet, | 0:13:15 | 0:13:19 | |
which is about 37 square metres. | 0:13:19 | 0:13:22 | |
So snails are a very efficient use of space? | 0:13:22 | 0:13:25 | |
-I'd say very efficient, yeah. -Cos they just stack up higher and higher | 0:13:25 | 0:13:29 | |
rather than spreading out over big fields. | 0:13:29 | 0:13:32 | |
Well, if you take seven boxes stacked high, | 0:13:32 | 0:13:35 | |
you've got 700 snails there. | 0:13:35 | 0:13:37 | |
And then if you go up to 10, that's 1,000 in each stack. | 0:13:37 | 0:13:40 | |
But there's one last thing I need. | 0:13:40 | 0:13:42 | |
How much protein is there in your snails? | 0:13:42 | 0:13:45 | |
There's no fat at all, and there's about 90% protein. | 0:13:45 | 0:13:50 | |
90% protein, brilliant. That's all I need to know, | 0:13:50 | 0:13:53 | |
-I've got all of my facts and figures. -Good. | 0:13:53 | 0:13:56 | |
-There's your blanched snails ready to cook. -Fantastic. | 0:13:56 | 0:13:58 | |
And there's the live ones. Take care. | 0:13:58 | 0:14:01 | |
-Ha-ha! You're a star. -Thanks a lot. -Thank you very much. -Take care. | 0:14:01 | 0:14:05 | |
So how does that compare with figures of land use | 0:14:05 | 0:14:07 | |
to produce more traditional lamb or beef? | 0:14:07 | 0:14:10 | |
I know some young people who know all about the Ecomaths | 0:14:13 | 0:14:16 | |
behind lamb production. | 0:14:16 | 0:14:17 | |
This working farm is part of Oathall Community College | 0:14:20 | 0:14:23 | |
and today they're weighing the lambs. | 0:14:23 | 0:14:25 | |
17. | 0:14:25 | 0:14:27 | |
It's 43 kilograms. | 0:14:33 | 0:14:35 | |
We return to the classroom to look at the maths. | 0:14:40 | 0:14:44 | |
We calculated the mean of their growth weight, of their growth. | 0:14:44 | 0:14:47 | |
-Is that in kilograms? -Yeah, that's in kilograms. | 0:14:47 | 0:14:50 | |
And their breed, so Suffolk, Pedigree Suffolk, Texel, just a few. | 0:14:50 | 0:14:55 | |
So can you choose certain animals because they're fast-growing | 0:14:55 | 0:14:58 | |
and other ones for taste? | 0:14:58 | 0:14:59 | |
Why would you choose a different breed, why do you think? | 0:14:59 | 0:15:02 | |
It all kind of depends on how well they grow | 0:15:02 | 0:15:06 | |
and what breed will produce the best meat. You want it to taste nice | 0:15:06 | 0:15:10 | |
but you also want to make money out of it and make a profit. | 0:15:10 | 0:15:13 | |
-So, Sam and Freya, can I squeeze in here? -Yes. | 0:15:15 | 0:15:17 | |
Tell me what you've been up to here. | 0:15:17 | 0:15:20 | |
Well, we've been working out the amount of land used by lambs. | 0:15:20 | 0:15:26 | |
So literally the amount of space you require to produce | 0:15:26 | 0:15:29 | |
-a kilo of lamb? -Yes. | 0:15:29 | 0:15:30 | |
We produce about two lambs each week. | 0:15:30 | 0:15:33 | |
Each lamb, the bit that we use is about 22.5 kilograms. | 0:15:33 | 0:15:38 | |
Ten lambs needs 4,048 square metres. | 0:15:38 | 0:15:42 | |
As the farm produces two lambs each week, | 0:15:42 | 0:15:45 | |
we have to divide that by five. | 0:15:45 | 0:15:47 | |
We then take the 809 and divide it | 0:15:49 | 0:15:52 | |
by the amount of protein produced, and that gives us 25.7. | 0:15:52 | 0:15:58 | |
That is brilliant, because you've used maths to come up with | 0:15:58 | 0:16:01 | |
something really useful. We now know it takes 25.7 square metres of land | 0:16:01 | 0:16:06 | |
to produce one kilo of lamb protein. | 0:16:06 | 0:16:10 | |
That's pretty good, but I've got a challenge for you. | 0:16:10 | 0:16:14 | |
Can you use the same maths to work out something about this fella here? | 0:16:14 | 0:16:18 | |
This is Sidney the snail. Can you work out for me | 0:16:19 | 0:16:22 | |
how much land you need to produce a kilo of snail protein? OK. | 0:16:22 | 0:16:27 | |
-That sound like a good challenge? -Yeah. -Freya, put your hand out. | 0:16:27 | 0:16:30 | |
Get to work! | 0:16:30 | 0:16:32 | |
I left them with the data I collected at the snail farm | 0:16:35 | 0:16:37 | |
in Dorset, and a few friends I brought with me. | 0:16:37 | 0:16:41 | |
While these guys are finding out how much protein there is | 0:16:42 | 0:16:45 | |
in these fellas, I thought it might be a good idea to cook them some. | 0:16:45 | 0:16:49 | |
And this is how you go about it. First of all, get about 100 snails, | 0:16:49 | 0:16:53 | |
and boil them up in lots and lots of water, | 0:16:53 | 0:16:56 | |
then chuck them in a pan with lots and lots of garlicky butter, | 0:16:56 | 0:17:00 | |
and that way, frankly, anything should taste good. | 0:17:00 | 0:17:03 | |
To make it fair in the lamb v snail comparison, they took 12 grams | 0:17:03 | 0:17:06 | |
as the average weight per snail without the shell, | 0:17:06 | 0:17:09 | |
just as they took 50% to be the useable meat per lamb. | 0:17:09 | 0:17:13 | |
They also adjusted for the different protein content for the dry meat - | 0:17:13 | 0:17:17 | |
70% for lamb and 90% for snail. | 0:17:17 | 0:17:20 | |
Their final figures for land use for kilogram per week | 0:17:20 | 0:17:23 | |
were really surprising. | 0:17:23 | 0:17:25 | |
0.57. | 0:17:25 | 0:17:27 | |
So that's 0.57 square metres to produce a kilo of snail protein, | 0:17:27 | 0:17:32 | |
compared to 25.7 square metres for a kilo of lamb protein. | 0:17:32 | 0:17:36 | |
So now that we understand the amount of land needed for snails and | 0:17:36 | 0:17:39 | |
the amount needed for lamb, how do you relate the two figures together? | 0:17:39 | 0:17:44 | |
We took the two numbers and we came up with a ratio of 1 to 45. | 0:17:44 | 0:17:49 | |
Brilliant. So you need 45 times the amount of land to produce | 0:17:49 | 0:17:53 | |
a kilo of protein from lamb than you do from snail. | 0:17:53 | 0:17:56 | |
So this is a little bit of snails on toast. | 0:17:58 | 0:18:02 | |
So, first time for a gastropod? | 0:18:03 | 0:18:05 | |
-Mmmm. -Mm. -They're not bad, are they? | 0:18:07 | 0:18:10 | |
Do you think that there's something important | 0:18:10 | 0:18:13 | |
about foods like this that take a lot less land to produce? | 0:18:13 | 0:18:17 | |
Although lamb does take up more land, | 0:18:17 | 0:18:19 | |
it's usually land that's unable for humans to use, | 0:18:19 | 0:18:23 | |
like they're grown on hills. | 0:18:23 | 0:18:26 | |
I think they are a lot better... way to preserve land, | 0:18:26 | 0:18:33 | |
but, to be honest, I'd still rather eat lamb! | 0:18:33 | 0:18:36 | |
STEFAN LAUGHS | 0:18:36 | 0:18:38 | |
Now, snails might not be your cup of tea but when you use maths | 0:18:39 | 0:18:44 | |
to take a close look at different types of food | 0:18:44 | 0:18:46 | |
and look at the energy and land and water | 0:18:46 | 0:18:48 | |
that goes into the production, you can make some choices | 0:18:48 | 0:18:51 | |
that could really change the world. | 0:18:51 | 0:18:54 | |
Everywhere you look, the planet is teeming with life. | 0:19:13 | 0:19:17 | |
It's called biodiversity and it's simply | 0:19:17 | 0:19:19 | |
the huge variety of living things that make up the natural world. | 0:19:19 | 0:19:24 | |
But that variety is getting less and less. | 0:19:28 | 0:19:30 | |
Who knows what that will mean for the good old human being. | 0:19:30 | 0:19:34 | |
Time is running out but there are solutions, | 0:19:35 | 0:19:38 | |
and we need maths to find them - | 0:19:38 | 0:19:40 | |
but not just any old maths. This is what I call Ecomaths. | 0:19:40 | 0:19:44 | |
But you don't have to go to the ends of the earth to find living things | 0:19:46 | 0:19:49 | |
that are under threat, and one of the main culprits | 0:19:49 | 0:19:52 | |
is this - insecticide. | 0:19:52 | 0:19:55 | |
It's used by farmers and gardeners across the world to kill pests. | 0:19:55 | 0:20:00 | |
So, what's the problem? | 0:20:00 | 0:20:03 | |
That's the problem - harmful to the environment. | 0:20:03 | 0:20:06 | |
So, what's going on? | 0:20:06 | 0:20:08 | |
I'm here at Swansea University to find out. | 0:20:08 | 0:20:11 | |
So, Tariq, explain to me about pesticides. | 0:20:11 | 0:20:15 | |
OK, Stef. Pesticides are chemicals which control organisms | 0:20:15 | 0:20:20 | |
which are undesirable organisms. They could be weeds... | 0:20:20 | 0:20:23 | |
Most of us think of pesticides as controlling insects | 0:20:23 | 0:20:27 | |
which are pests to crops, but they could also be diseases of crops. | 0:20:27 | 0:20:31 | |
So what are you doing here? | 0:20:31 | 0:20:32 | |
We're trying to develop alternatives to conventional chemical pesticides. | 0:20:32 | 0:20:36 | |
We're trying to exploit natural organisms which occur in the soil | 0:20:36 | 0:20:41 | |
and in our environment, so we're trying to develop these organisms | 0:20:41 | 0:20:45 | |
as alternatives to the chemical pesticides. | 0:20:45 | 0:20:49 | |
'This is where they keep all the pests. Let's take a look.' | 0:20:49 | 0:20:53 | |
Here, for example, we have weevils. There's a whole range of weevils. | 0:20:53 | 0:20:57 | |
These can actually devastate a whole range of forest trees. | 0:20:57 | 0:21:01 | |
They have powerful mouth parts and they chew away and remove bark, | 0:21:01 | 0:21:05 | |
particularly young saplings. It can be starved and stunted | 0:21:05 | 0:21:08 | |
and it can actually topple over, and basically, it's killed. | 0:21:08 | 0:21:11 | |
At the university, they're developing naturally occurring fungi | 0:21:11 | 0:21:15 | |
that have evolved to attack and kill specific bugs. | 0:21:15 | 0:21:18 | |
One such fungus, called Metarhizium, | 0:21:18 | 0:21:21 | |
is proving to be a potent biological alternative to harmful chemicals. | 0:21:21 | 0:21:26 | |
So you're developing alternatives to pesticides. | 0:21:26 | 0:21:29 | |
How do you go about proving whether they work or not? | 0:21:29 | 0:21:33 | |
You have to compare our fungus - this is the agent we're developing - | 0:21:33 | 0:21:37 | |
with the chemical pesticide. | 0:21:37 | 0:21:39 | |
It has to show that it's just as good in killing the pest. | 0:21:39 | 0:21:43 | |
One of the most important things is mathematics, | 0:21:43 | 0:21:46 | |
because you have to prove to a lot of people | 0:21:46 | 0:21:49 | |
that this thing is working. | 0:21:49 | 0:21:51 | |
So, Minshad, what are you preparing here? | 0:21:52 | 0:21:55 | |
This is the fungus, and I'm going to prepare a test. | 0:21:55 | 0:21:58 | |
It's called an LC50, Lethal Concentration, | 0:21:58 | 0:22:01 | |
to kill 50% of the insects. | 0:22:01 | 0:22:03 | |
'Minshad is doing a vital test | 0:22:03 | 0:22:04 | |
'to see how effective the fungus is at killing pests. | 0:22:04 | 0:22:08 | |
'These aren't actually the target pests. | 0:22:08 | 0:22:10 | |
'They're little larvae called Galleria. | 0:22:10 | 0:22:12 | |
'They're usually chosen to make sure it's a fair test.' | 0:22:12 | 0:22:16 | |
-Can I pick this up? -Yeah. They are quite friendly, | 0:22:16 | 0:22:19 | |
-and this is used as a model host, worldwide. -Quite friendly! | 0:22:19 | 0:22:22 | |
First Minshad takes the fungus, here in this Petri dish, | 0:22:23 | 0:22:27 | |
and makes up a concentrated solution. | 0:22:27 | 0:22:30 | |
'The preparation has to be done in sterile conditions.' | 0:22:30 | 0:22:33 | |
He needs to know how many spores there are per millilitre. | 0:22:34 | 0:22:38 | |
Believe it or not, he counts them. | 0:22:38 | 0:22:41 | |
He takes a tiny drop and looks down the microscope. | 0:22:41 | 0:22:44 | |
He counts the spores in the larger square. | 0:22:47 | 0:22:50 | |
Then another square. | 0:22:51 | 0:22:53 | |
He does this five times and takes an average, in this case 40. | 0:22:55 | 0:23:00 | |
As there are 25 squares, this means that there are 25 times 40 spores - | 0:23:00 | 0:23:05 | |
or 1,000 - in the sample. | 0:23:05 | 0:23:08 | |
'Since he knows the volume of the sample, | 0:23:08 | 0:23:10 | |
'he can calculate the concentration. | 0:23:10 | 0:23:12 | |
'It's 10 to the 8 spores per millimetre.' | 0:23:12 | 0:23:15 | |
So the final concentration will be | 0:23:15 | 0:23:17 | |
one times ten to the power of eight conidia per millilitre. | 0:23:17 | 0:23:20 | |
So, from this I'm going to make a dilution. | 0:23:22 | 0:23:25 | |
Now he prepares what's called a serial dilution. | 0:23:25 | 0:23:28 | |
He takes one millilitre of the concentrated solution | 0:23:28 | 0:23:32 | |
and adds it to nine millilitres of the wetting agent | 0:23:32 | 0:23:35 | |
in the second tube. | 0:23:35 | 0:23:36 | |
This makes the second tube ten times less concentrated. | 0:23:39 | 0:23:44 | |
Minshad repeats the process from one tube to the next. | 0:23:45 | 0:23:49 | |
You can see from the labels on the tubes | 0:23:51 | 0:23:53 | |
that the serial dilution gives you lower and lower concentrations, | 0:23:53 | 0:23:57 | |
each ten times less. | 0:23:57 | 0:23:59 | |
The last tube is the control with no spores. | 0:23:59 | 0:24:02 | |
In the LC50 test, they want to know which of these concentrations | 0:24:02 | 0:24:06 | |
will kill 50% of the bugs. | 0:24:06 | 0:24:08 | |
The fungus works by piercing the outer casing and infecting the bug. | 0:24:11 | 0:24:17 | |
The fungus grows and develops spores, | 0:24:17 | 0:24:19 | |
so that it can spread to other bugs. | 0:24:19 | 0:24:22 | |
Because the fungus is naturally occurring, | 0:24:22 | 0:24:24 | |
birds and other creatures that feed on these bugs are unharmed, | 0:24:24 | 0:24:28 | |
even if they do fancy a nibble at something distinctly unappetising. | 0:24:28 | 0:24:33 | |
And here are the bugs in the LC50 test. | 0:24:35 | 0:24:38 | |
It's day eight, so let's see what's happened. | 0:24:38 | 0:24:42 | |
This looks pretty gruesome. | 0:24:42 | 0:24:44 | |
What's going on here? | 0:24:44 | 0:24:46 | |
This is the LC50 test, where I'm testing the different concentration. | 0:24:46 | 0:24:51 | |
He counts how many have died and fills in the table for day eight. | 0:24:51 | 0:24:57 | |
The LC50 test results are that between ten to the six | 0:24:57 | 0:25:01 | |
and ten to the seven spores are needed to kill 50% of the bugs. | 0:25:01 | 0:25:06 | |
A computer program allows Minshad to calculate the exact concentration. | 0:25:06 | 0:25:11 | |
Now, it takes 2.3 million spores to kill half of the insects - | 0:25:13 | 0:25:18 | |
that's a vast amount of spores. | 0:25:18 | 0:25:20 | |
Well, it just looks a vast amount of spores, | 0:25:20 | 0:25:23 | |
but in natural conditions you can find the same number anywhere. | 0:25:23 | 0:25:28 | |
So where are we going? | 0:25:28 | 0:25:30 | |
'But where do you collect the fungi? Deepest Africa? | 0:25:30 | 0:25:33 | |
'The Amazon rainforest? No. | 0:25:33 | 0:25:36 | |
'This parkland is part of the university campus, | 0:25:36 | 0:25:39 | |
'and lurking in the soil could be a new fungus strain.' | 0:25:39 | 0:25:43 | |
This is an untreated area, | 0:25:43 | 0:25:46 | |
and we're hoping to find a bio-control agent. | 0:25:46 | 0:25:50 | |
So we're looking to find some fungi? | 0:25:50 | 0:25:52 | |
Yes, we're looking to find fungi. | 0:25:52 | 0:25:54 | |
'Earthworms are a sign of the rich biodiversity of untreated soil. | 0:25:54 | 0:25:59 | |
'That's why Minshad chooses this location | 0:25:59 | 0:26:01 | |
'to search for promising new fungi | 0:26:01 | 0:26:03 | |
'for the development of biological pesticides.' | 0:26:03 | 0:26:06 | |
It's only because of the huge biodiversity of the planet | 0:26:06 | 0:26:09 | |
that we can find something as amazing as a fungus | 0:26:09 | 0:26:12 | |
that can help us combat pests. | 0:26:12 | 0:26:14 | |
But you have to do the maths to prove that it works. | 0:26:14 | 0:26:17 | |
I'm off somewhere else where they're keeping an eye on the environment. | 0:26:17 | 0:26:21 | |
Birds are often the earliest indication | 0:26:23 | 0:26:25 | |
of changes to our environment and their impact on biodiversity. | 0:26:25 | 0:26:29 | |
These students at Dorothy Stringer High School in Brighton | 0:26:29 | 0:26:32 | |
are carrying out a bird walk and counting the species | 0:26:32 | 0:26:35 | |
in the school grounds. | 0:26:35 | 0:26:37 | |
Can you guys count how many gulls there are | 0:26:37 | 0:26:40 | |
on the top of the main block over there? | 0:26:40 | 0:26:43 | |
ALL: One, two, three, four, five. | 0:26:43 | 0:26:47 | |
-Brilliant. Make a note. -Are you going to mark them on your sheets? | 0:26:47 | 0:26:50 | |
STUDENTS CHATTER | 0:26:50 | 0:26:53 | |
Right, we're now coming to the woodland environment, | 0:26:55 | 0:26:58 | |
so now I want you to... | 0:26:58 | 0:26:59 | |
You've got your lists - look up in the trees | 0:26:59 | 0:27:02 | |
and we'll try to see how many we can identify. | 0:27:02 | 0:27:04 | |
Most important is that you count the number of each species that you see. | 0:27:04 | 0:27:08 | |
Each winter for four years, the students have been recording | 0:27:08 | 0:27:11 | |
the birds, and building a valuable database, | 0:27:11 | 0:27:14 | |
that contributes to a nationwide survey. | 0:27:14 | 0:27:17 | |
What have you discovered over the years? | 0:27:17 | 0:27:19 | |
We've got some data here from the main birds | 0:27:19 | 0:27:23 | |
that actually are in this area. | 0:27:23 | 0:27:25 | |
Are there any big changes that you've seen? | 0:27:25 | 0:27:28 | |
The blackbird - it's gone from, in 2009, seven, | 0:27:28 | 0:27:32 | |
to 0.5. | 0:27:32 | 0:27:34 | |
-That's quite surprising. -Yeah, that's quite a big change. | 0:27:34 | 0:27:37 | |
There's always a constant with the black-headed gulls | 0:27:37 | 0:27:40 | |
and the heron gulls. They've always been a big species here, | 0:27:40 | 0:27:46 | |
but the jackdaws have kind of gone down, but the problem is, | 0:27:46 | 0:27:49 | |
as the recording isn't always at the same time of year... | 0:27:49 | 0:27:53 | |
-And that'll have a big effect on the numbers. -Yeah. | 0:27:53 | 0:27:56 | |
And this is averaged over quite a few different visits to the woods, | 0:27:56 | 0:27:59 | |
-isn't it? -Yes. -Yes. | 0:27:59 | 0:28:00 | |
Over the course of the whole of the year. | 0:28:00 | 0:28:02 | |
I think every class... | 0:28:02 | 0:28:04 | |
-Pretty much every person would have gone through. -Yes. | 0:28:04 | 0:28:07 | |
-A lot of people. -There's quite a lot of data, then, being averaged out | 0:28:07 | 0:28:11 | |
-and condensed. -It should be pretty reliable if it's that many. | 0:28:11 | 0:28:14 | |
'They're not just collecting data - they're also | 0:28:14 | 0:28:17 | |
'investing in future biodiversity by planting trees | 0:28:17 | 0:28:19 | |
'to attract butterflies.' | 0:28:19 | 0:28:21 | |
-So what are we going to do here? -We'll plant some saplings. -Yeah. | 0:28:21 | 0:28:25 | |
-So, you've got to make a T shape. -Yep. | 0:28:25 | 0:28:27 | |
-The bottom bit of the T. -Yep. -And then make that the top bit of the T. | 0:28:27 | 0:28:32 | |
'Come springtime, they'll be back, | 0:28:34 | 0:28:37 | |
'analysing the results of their efforts using Ecomaths.' | 0:28:37 | 0:28:41 | |
Subtitles by Red Bee Media Ltd | 0:28:51 | 0:28:54 |