Population regulation

WEBVTT
Kind: captions
Language: en

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- [Voiceover] What I
want to do in this video,

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is think a little bit more about

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how populations can be regulated.

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And broadly speaking, we can think of

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the regulation of populations
it two different categories.

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There's the regulation
dependent on density,

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so density, density dependent
regulation, density dependent.

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And then, there's the type of regulation

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that isn't dependent on density,

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so we could call that density
independent regulation.

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Independent, independent regulation.

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So first let's think about
density dependent regulation.

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Let me draw a little chart
here, to help us visualize that.

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So let's say that that
axis is the population.

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I'll say P for population.

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And let's say this axis is time.

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So, T for time.

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In previous videos we
talked about a population,

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and I like to use the example of rabbits,

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how it could grow exponentially.

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So if it's just growing a
certain percent every month,

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that population will grow exponentially,

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but we can't expect that that
will just happen forever,

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if rabbits just kept
growing exponentially,

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it wouldn't take long for them to

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cover the surface of the earth,

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and and then fill the universe,

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if in some way they weren't
limited by anything.

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But we know that they
are limited by things.

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And so the environment
only has a certain amount

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of carrying capacity, and
we'll think a little bit

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about this carrying capacity in a second,

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and what's determining
the carrying capacity.

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And so as the density of the
rabbits in a certain area

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get higher and higher
and higher, well then

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the density dependent,
use a different color,

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the density dependent
factors start to play,

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the density dependent limiting factors.

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And what could be some of these

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density dependent limiting factors that

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keep the population from going

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dramatically above the carrying capacity?

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Well the most obvious one could be

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competition for resources, competition,

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competition, for, resources.

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And the one that might

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come to mind most clearly
is food resources.

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So this is actually a picture
of Australia in the mid 1800s.

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And they had a bunny population problem.

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The rabbits were first introduced

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in order to have a little bit of hunting,

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but then they reproduced like rabbits.

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And it was estimated that at some point

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you had over a billion rabbits

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that had populated the
country, and that was,

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you might say, how cute,
but it was a huge problem.

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(stammering) The were
eating all of the farmable,

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they were eating crops.

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They were eating the grass that

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other types of livestock would graze on.

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So it was a huge infestation of rabbits.

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And so you can imagine one
competition for resources

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is just the grass itself.

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In this picture you can
see the land is barren.

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Maybe this happened because the rabbits

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ate all of the vegetation here.

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So, competition for resources,
one type of resource

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could be food, another type
of resource could be water,

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there might only be so much water

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to support organisms of a certain kind.

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You know here, we often
talk about animals,

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but it could be plants,
or it could be bacteria,

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it could be all sorts of organisms
that we're talking about.

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And if we're talking about plants,

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we could think about light.

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You could say, well what limits
having an infinite number

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of plants in a certain area?

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Well, water will limit,
the nutrients in the soil

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will limit, but also access to light.

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You've seen pictures of a
dense canopy in a rain forest,

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and the plants are trying to seek out

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whatever gap in the canopy they can find,

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so that they can get some
access to that light.

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Now there's other examples,

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and this wouldn't apply
as much to, say, plants,

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but the idea of shelter.

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This might apply to humans, or to other

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types of animals that maybe
need shelter in order to hide,

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or a place to reproduce, or whatever else.

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So at some point, if the
population density gets too high

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in a certain region, then these things

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are going to limit how dense
the population can get,

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or frankly just what the
population actually is,

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and so that would lead, once again

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we talked about this in a previous video,

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to this logistic curve right
over here, where we just,

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we don't, we just start
approaching the carrying capacity,

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and it is possible that you could even

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go above the carrying capacity
and then you're at kinda

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this very unstable situation,
and then something happens

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and you go below it, then you go above it,

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and then below it, and
then something like that.

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But what are other
density dependent factors

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that we could think about?

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Well, another thing is,
if you were a predator,

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when, say, the rabbits become this dense,

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it's much easier to
start to pick them off,

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it's much easier to get your lunch.

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And so, predatory factors,

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or we could say predation, predation.

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Once a population gets large
enough and dense enough,

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it might be the predators who can say,

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hey, we can start, it's way
easier for us to get our lunch.

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Now the other thing, it might
be a little less obvious,

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but when you have a
high density population,

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and there's examples of this
in medieval times in Europe,

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and even in modern times
today with human populations,

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but this happens with all organisms,

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is that when you become
a dense population,

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there's more interaction.

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There's more contact, there's more

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sharing of resources like water, and so

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disease and parasites becomes an issue.

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So let me write this down,
disease, disease, and parasites

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can spread much easier, and

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they're much more likely to
start limiting the population.

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The thing that always comes
to my mind is the plague

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in medieval times, where
it was very easy to spread

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from one human to the next, or

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frankly from rats to
humans, and whatever else.

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Now the other thing, and this is maybe

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somewhat related to everything else

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we've talked about, is waste accumulation.

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So let me write this right over here.

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Waste.

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If you have a really
high density population,

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and the waste is just everywhere,
it could poison the water,

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it might poison sources of food,

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it might help the spread
of disease and parasites.

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And once again, all of
these things help define

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what the carrying capacity,

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how dense can a population
get in a certain region.

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Now you might say, well maybe they don't

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have to stay in a region, maybe they can

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go and explore other
places, and that's possible,

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and that's been the story for

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many different types of species.

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Lemmings are famous for, when
their population gets dense

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in a certain area, groups of them

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start just running to start
exploring other areas.

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Sometimes running in directions

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that are not that good for them.

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So all of these are
density dependent factors.

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And a lot of these, as
we just talked about,

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you could think of them as biotic factors.

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They're related to other
living things around.

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The density independent
factors tend to be a-biotic.

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They tend to be not
related to living things.

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So the most common
density independent factor

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is natural disasters.

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So, natural, natural disaster.

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We have a picture here of a forest fire.

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The deer population here
might not be in any way

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close to their carrying
capacity, but despite that,

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the forest fire maybe might
kill off a lot of the deer.

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Other natural disasters,
you could have a flood,

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you could have a tsunami, you could have

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a meteorite coming from outer space.

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That happened to the dinosaurs.

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To just knock out huge populations.

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And so, density independent factors,

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you could have the
population growing and it's,

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and at just some random point it just,

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there's some density independent factor,

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there's a forest fire, there's
a flood, or something else.

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And then maybe the
population grows from there,

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and eventually gets closer
to its carrying capacity,

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who knows, but the density
independent factors, once again,

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it's not related to where
we are on this curve.

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It could happen at any
time, and to some degree

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they feel a little bit more random.

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Now, with all of this talk
about carrying capacity

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and the different density
dependent factors,

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you might be thinking well,
what about human beings?

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We are for sure a species, and so

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the same ideas apply to us.

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And so is there a
natural carrying capacity

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for the environments that we are in?

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And there's a famous philosopher
scientist Thomas Malthus,

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and I have a whole video on him, but

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he hypothesized that humanity
had a very serious problem.

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Because our populations
were growing exponentially,

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so this is population, this is time,

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and so he said, look, there's just

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a natural carrying
capacity for human beings.

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And as human beings just
kept growing exponentially,

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We would hit that carrying capacity,

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and the term for that carrying capacity,

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in the case of human beings,
that Thomas Malthus set up,

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and there's a whole video on
this, is the Malthusian limit.

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And he hypothesized
that once you crossed it

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or approached it, there
would be all sorts of crises,

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that once you're at
this carrying capacity,

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there might not be enough food, and then

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there might be a famine,
or we go across it

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and then disease spreads a lot more.

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And so he was just applying these

00:09:28.856 --> 00:09:32.234
ideas of density dependent
factors to human populations

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and said hey, this is not going
to be pleasant for humanity.

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Now what's been interesting,
is that humanity

00:09:38.806 --> 00:09:42.479
has found ways repeatedly, of pushing up

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the carrying capacity for us as a species.

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We've been able to do it,
frankly through technology.

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Frankly finding ways to grow food

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in denser and denser ways,
ways to stave off disease,

00:09:55.770 --> 00:09:59.937
ways to get rid of waste
and sewage and all of that,

00:10:01.538 --> 00:10:04.444
so it's an interesting
philosophical question to say,

00:10:04.444 --> 00:10:06.270
is there ever gonna be a point where

00:10:06.270 --> 00:10:09.119
human being just hits this Malthusian,

00:10:09.119 --> 00:10:12.451
where human society hits
this Malthusian limit,

00:10:12.451 --> 00:10:14.604
or are we always going
to be able to fend it off

00:10:14.604 --> 00:10:18.369
by just better and better
technology, or maybe even

00:10:18.369 --> 00:10:20.657
just regulation of the population itself,

00:10:20.657 --> 00:10:23.321
so that we don't, you know,
where we just have whatever,

00:10:23.321 --> 00:10:26.528
birth control, or family
planning, or whatever it might be,

00:10:26.528 --> 00:10:30.695
so that we are less likely
to hit some eventual limit.


Official SAT Practice on Khan Academy

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Exponential and logistic growth in populations

WEBVTT
Kind: captions
Language: en

00:00:00.421 --> 00:00:02.101
- [Voiceover] Let's say
that we're starting with a

00:00:02.101 --> 00:00:05.840
population of 1,000
rabbits, and we know that

00:00:05.840 --> 00:00:10.461
this population is
growing at 10% per month.

00:00:10.461 --> 00:00:14.443
What I wanna do is explore
how that population will grow,

00:00:14.443 --> 00:00:17.343
if it's growing 10% per month.

00:00:17.343 --> 00:00:19.299
So let's set up a little bit of a,

00:00:19.299 --> 00:00:23.429
let's set up a little
table here, a little table.

00:00:23.429 --> 00:00:26.819
And on this left column,
let's just say this is

00:00:26.819 --> 00:00:30.009
the number of months that have gone by,

00:00:30.009 --> 00:00:34.000
and on the right column, let's
say this is the population.

00:00:34.000 --> 00:00:37.136
So we know from the
information given to us,

00:00:37.136 --> 00:00:41.996
that at zero months, we're
starting off with 1,000 rabbits.

00:00:41.996 --> 00:00:45.096
Now let's think about what's
gonna happen after one month.

00:00:45.096 --> 00:00:47.767
Well, our population's gonna grow by 10%,

00:00:47.767 --> 00:00:50.376
so we can take our population
at the beginning of the month,

00:00:50.376 --> 00:00:52.376
and growing by 10%,
that's the same thing as

00:00:52.376 --> 00:00:55.505
multiplying by one point one.

00:00:55.505 --> 00:00:56.996
You have your original population,

00:00:56.996 --> 00:01:01.136
and then you grow it by 10%,
one plus 10% is one point one.

00:01:01.136 --> 00:01:03.336
So we can multiply it by one point one,

00:01:03.336 --> 00:01:04.509
and that math we can do in our head,

00:01:04.509 --> 00:01:07.435
it is 11 hundred, or 1,100,

00:01:07.435 --> 00:01:11.602
but let's just write this
as 1,000 times one point,

00:01:14.708 --> 00:01:17.729
not one point five, times one point one.

00:01:17.729 --> 00:01:20.597
Now let's think about what
happens as we go to month two.

00:01:20.597 --> 00:01:22.257
What's gonna have is
gonna be the population

00:01:22.257 --> 00:01:25.166
that we started at the
beginning of the month

00:01:25.166 --> 00:01:27.409
times one point one again,

00:01:27.409 --> 00:01:28.979
so it's gonna be the population

00:01:28.979 --> 00:01:32.116
at the beginning of the
month, which was that,

00:01:32.116 --> 00:01:33.339
which we have right over there,

00:01:33.339 --> 00:01:36.287
but then we're gonna multiply
by one point one again,

00:01:36.287 --> 00:01:40.729
or we can just say this
is one point one squared.

00:01:40.729 --> 00:01:42.677
I think you see a pattern emerging.

00:01:42.677 --> 00:01:44.659
After another month, the
population's gonna be

00:01:44.659 --> 00:01:48.409
1,000 times one point
one to the third power,

00:01:49.880 --> 00:01:52.562
we're just gonna multiply
by one point one again.

00:01:52.562 --> 00:01:56.092
And so if you were to go
n months into the future,

00:01:56.092 --> 00:01:57.920
well you can see what's going to be.

00:01:57.920 --> 00:02:01.753
It's gonna be 1,000
times, or being multiplied

00:02:02.782 --> 00:02:05.354
by one point one n times,

00:02:05.354 --> 00:02:09.187
or 1,000 times one point
one to the nth power.

00:02:10.383 --> 00:02:12.482
And so we can set up an expression here,

00:02:12.482 --> 00:02:13.965
we can say look the population,

00:02:13.965 --> 00:02:17.126
let's say that the population is P.

00:02:17.126 --> 00:02:21.293
The population as a function
of n, as a function of n,

00:02:23.866 --> 00:02:27.654
is gonna be equal to
our initial population,

00:02:27.654 --> 00:02:31.237
our initial population,
times one point one

00:02:32.333 --> 00:02:33.750
to the nth power.

00:02:34.855 --> 00:02:36.785
And you might say, "Okay this makes sense,

00:02:36.785 --> 00:02:38.767
"it doesn't look like we're
getting crazy numbers",

00:02:38.767 --> 00:02:40.697
but just for kicks, let's just think about

00:02:40.697 --> 00:02:42.418
what's gonna happen in 10 years.

00:02:42.418 --> 00:02:45.185
So 10 years would be 120 months.

00:02:45.185 --> 00:02:49.516
So the population at the end
of 120 months is gonna be

00:02:49.516 --> 00:02:53.266
1,000 times one point
one to the 120th power,

00:02:56.728 --> 00:03:00.809
and so let's, let me get a
calculator out to do that.

00:03:00.809 --> 00:03:02.758
I can not calculate one point one

00:03:02.758 --> 00:03:04.829
to the 120th power in my head.

00:03:04.829 --> 00:03:08.996
One point one to the 120th
power is equal to that,

00:03:12.208 --> 00:03:16.499
times our original
population, so times 1,000,

00:03:16.499 --> 00:03:20.332
one two three, is going
to be equal to roughly

00:03:21.910 --> 00:03:25.493
93 million rabbits,
let me write that down.

00:03:26.351 --> 00:03:29.119
So we started with 1,000,
and we're gonna have

00:03:29.119 --> 00:03:32.869
approximately 93 million
rabbits, 93 million,

00:03:35.952 --> 00:03:38.103
million rabbits.

00:03:38.103 --> 00:03:41.882
And so we grew by a factor
of 93,000 over 10 years,

00:03:41.882 --> 00:03:43.333
so over another 10 years,

00:03:43.333 --> 00:03:46.424
we're gonna grow by 93,000 times this.

00:03:46.424 --> 00:03:50.583
And so you quickly realize
10% per month is quite fast,

00:03:50.583 --> 00:03:52.702
and this might seem extremely fast,

00:03:52.702 --> 00:03:57.083
but it's actually not outlandish
for a population of rabbits

00:03:57.083 --> 00:04:01.250
that are not limited by
space or predators or food,

00:04:02.384 --> 00:04:04.535
and if you were to plot
something like this out,

00:04:04.535 --> 00:04:06.725
if you were to plot the rabbit population

00:04:06.725 --> 00:04:08.474
with respect to time,

00:04:08.474 --> 00:04:11.698
you would see a graph that
looks, let me draw it.

00:04:11.698 --> 00:04:15.448
So this axis it is time,
let's say in months,

00:04:16.998 --> 00:04:20.867
and this axis you have your population,

00:04:20.867 --> 00:04:22.950
you have your population.

00:04:24.211 --> 00:04:27.819
This type of function,
or this type of equation,

00:04:27.819 --> 00:04:31.088
let me see population I, population,

00:04:31.088 --> 00:04:32.898
this is an exponential function,

00:04:32.898 --> 00:04:35.127
and so your population
as a function of time

00:04:35.127 --> 00:04:37.377
is gonna look like this,
it's gonna have this kinda

00:04:37.377 --> 00:04:40.565
hockey stick j shape right over here.

00:04:40.565 --> 00:04:42.836
And if you let these rabbits
reproduce long enough,

00:04:42.836 --> 00:04:44.823
they would frankly take over the planet,

00:04:44.823 --> 00:04:47.894
if they had enough food and
they had enough space to do it.

00:04:47.894 --> 00:04:50.693
But if you notice I keep
saying if they have enough food

00:04:50.693 --> 00:04:52.696
and if they have enough space.

00:04:52.696 --> 00:04:55.124
The reality in the world
is that there is not

00:04:55.124 --> 00:04:56.905
infinite food and infinite space,

00:04:56.905 --> 00:05:00.123
and it isn't the case that
there are no predators,

00:05:00.123 --> 00:05:03.000
or competition for resources.

00:05:03.000 --> 00:05:05.753
And so there is actually a
maximum carrying capacity

00:05:05.753 --> 00:05:08.670
for certain part of the environment

00:05:09.745 --> 00:05:12.134
for a certain type of species.

00:05:12.134 --> 00:05:13.896
And so what's more likely to happen,

00:05:13.896 --> 00:05:17.775
what we described right over
here, is exponential growth,

00:05:17.775 --> 00:05:21.942
exponential growth, and why is
it called exponential growth?

00:05:23.134 --> 00:05:26.884
Well you notice, we are
growing by the input,

00:05:28.284 --> 00:05:32.367
which is time, is being
thrown into our exponent.

00:05:33.325 --> 00:05:35.946
And so that is exponential
growth, but obviously

00:05:35.946 --> 00:05:38.186
you can't have an
infinite number of rabbits

00:05:38.186 --> 00:05:40.157
or you can't just grow forever.

00:05:40.157 --> 00:05:45.008
There is going to be some
natural maximum carrying capacity

00:05:45.008 --> 00:05:47.507
that the environment can actually sustain.

00:05:47.507 --> 00:05:49.705
And so the actual growth
that you would see,

00:05:49.705 --> 00:05:53.246
when the population is well
below that carrying capacity,

00:05:53.246 --> 00:05:56.829
is reasonable to model it
with exponential growth,

00:05:56.829 --> 00:05:59.860
but as it get closer and closer
to that carrying capacity,

00:05:59.860 --> 00:06:02.739
it is going to asymptote up towards it,

00:06:02.739 --> 00:06:05.998
so it's gonna get up towards
it, but not cross it,

00:06:05.998 --> 00:06:07.090
and that's just a model.

00:06:07.090 --> 00:06:10.217
There are other situations
where maybe it goes up to it,

00:06:10.217 --> 00:06:12.889
and it crosses it, and
then it cycles around it,

00:06:12.889 --> 00:06:15.218
so these are all different
ways of thinking about it,

00:06:15.218 --> 00:06:17.583
but the general idea is you
wouldn't expect something

00:06:17.583 --> 00:06:20.972
to just grow unfettered forever.

00:06:20.972 --> 00:06:24.094
Now this blue curve,
which people often use

00:06:24.094 --> 00:06:26.253
to model population,
especially when they're

00:06:26.253 --> 00:06:29.263
thinking about the
population once they approach

00:06:29.263 --> 00:06:31.693
the environment's carrying capacity.

00:06:31.693 --> 00:06:36.532
This is, this kinda s shaped
curve, that is considered,

00:06:36.532 --> 00:06:38.664
that's called logistic growth,

00:06:38.664 --> 00:06:40.904
and there is a logistic
function that describes this,

00:06:40.904 --> 00:06:43.091
but you don't have to know it in the scope

00:06:43.091 --> 00:06:45.851
of a kinda introductory biology.

00:06:45.851 --> 00:06:48.738
There's a logistic, logistic growth,

00:06:48.738 --> 00:06:50.988
and it's described by
the logistic function.

00:06:50.988 --> 00:06:53.936
If you're curious about
it, we do have videos

00:06:53.936 --> 00:06:56.386
on Khan Academy about logistic growth

00:06:56.386 --> 00:06:58.126
and also about exponential growth,

00:06:58.126 --> 00:07:00.668
and we go into a lot more detail on that.

00:07:00.668 --> 00:07:03.638
But the general idea
here is when populations

00:07:03.638 --> 00:07:07.106
are not limited by their
environment, by food,

00:07:07.106 --> 00:07:11.273
by resources, by space, they
tend to grow exponentially,

00:07:12.217 --> 00:07:14.165
but then once they get close,

00:07:14.165 --> 00:07:16.583
that exponential growth
no longer models it well,

00:07:16.583 --> 00:07:19.874
once they start to really
saturate their environment,

00:07:19.874 --> 00:07:21.935
or they start to get
close to that ceiling,

00:07:21.935 --> 00:07:24.785
and overall the logistic,
or logistic function,

00:07:24.785 --> 00:07:28.045
or logistic growth, is a better model

00:07:28.045 --> 00:07:31.128
for what is actually going to happen.


Apoptosis

WEBVTT
Kind: captions
Language: en

00:00:00.166 --> 00:00:01.208
- [Voiceover] Hello, Emily.

00:00:01.208 --> 00:00:02.087
- [Voiceover] Hello, David.

00:00:02.087 --> 00:00:05.455
- [Voiceover] So we're here
today to talk about apoptosis.

00:00:05.455 --> 00:00:06.851
I was gonna ask you
some questions about it,

00:00:06.851 --> 00:00:10.995
you were going to explain
what it even is to me.

00:00:10.995 --> 00:00:12.421
- [Voiceover] Absolutely.
- [Voiceover] Okay.

00:00:12.421 --> 00:00:13.600
- [Voiceover] Let's talk apoptosis.

00:00:13.600 --> 00:00:16.294
- [Voiceover] So this word, apoptosis.

00:00:16.294 --> 00:00:18.956
I did a little bit of etymology research.

00:00:18.956 --> 00:00:20.158
I broke the word apart,

00:00:20.158 --> 00:00:24.016
'cause it comes from Greek
particles that I identified.

00:00:24.016 --> 00:00:28.250
So we have, here's the limit
of what I know right now.

00:00:28.250 --> 00:00:30.586
So it comes from these two pieces,

00:00:30.586 --> 00:00:33.304
the "apo" meaning "away,"

00:00:33.304 --> 00:00:37.088
and "ptosis," which
means, like, a falling.

00:00:37.088 --> 00:00:38.435
So it's really this kind of,

00:00:38.435 --> 00:00:40.732
it means, like, to be falling away.

00:00:40.732 --> 00:00:44.319
And my understanding is that
this programmed cell death,

00:00:44.319 --> 00:00:45.152
'cause that's what it is,

00:00:45.152 --> 00:00:45.985
that's what you've written,

00:00:45.985 --> 00:00:50.497
is kind of analogous to leaves
falling away from a tree,

00:00:50.497 --> 00:00:52.837
that it's something
that's supposed to happen,

00:00:52.837 --> 00:00:56.019
and the cells just die
in this prescribed way

00:00:56.019 --> 00:00:56.988
when they're supposed to.

00:00:56.988 --> 00:00:58.436
This isn't random.

00:00:58.436 --> 00:01:01.679
This is something that the cell embarks on

00:01:01.679 --> 00:01:03.879
for a particular purpose.

00:01:03.879 --> 00:01:05.620
- [Voiceover] Yeah, I
think that's a really,

00:01:05.620 --> 00:01:06.688
a good way of putting it,

00:01:06.688 --> 00:01:09.453
and I think that is why
it was named apoptosis

00:01:09.453 --> 00:01:12.283
by some of the first folks who studied it,

00:01:12.283 --> 00:01:13.622
is that they really wanted to underscore

00:01:13.622 --> 00:01:15.736
that this is a form of cell death

00:01:15.736 --> 00:01:17.243
that is a normal, healthy part

00:01:17.243 --> 00:01:19.822
of an organism's development,

00:01:19.822 --> 00:01:21.575
its maintenance of its body,

00:01:21.575 --> 00:01:23.709
even its prevention of things

00:01:23.709 --> 00:01:26.014
like viral infection or cancer.

00:01:26.014 --> 00:01:29.377
So it's very much a
normal and healthy thing

00:01:29.377 --> 00:01:32.015
that your body is
actually doing right now.

00:01:32.015 --> 00:01:33.364
- [Voiceover] So, right now?

00:01:33.364 --> 00:01:34.420
- [Voiceover] Right now.
- [Voiceover] Oh man.

00:01:34.420 --> 00:01:35.253
(laughing)

00:01:35.253 --> 00:01:39.333
So, okay, so what are the
ways in which a cell can die?

00:01:39.333 --> 00:01:41.966
What are, I mean, 'cause
we have this diagram here.

00:01:41.966 --> 00:01:44.032
Here's a normal, healthy cell.

00:01:44.032 --> 00:01:45.352
And then here we've got this,

00:01:45.352 --> 00:01:48.067
what looks like the aftermath
of some kind of explosion.

00:01:48.067 --> 00:01:49.626
What is this?

00:01:49.626 --> 00:01:51.057
- [Voiceover] So that's sort of showing

00:01:51.057 --> 00:01:54.623
two very broad categories
of ways that a cell can die,

00:01:54.623 --> 00:01:56.642
and the simplest way to label them

00:01:56.642 --> 00:01:58.438
would be messy and tidy.

00:01:58.438 --> 00:02:00.005
- [Voiceover] Okay.
- [Voiceover] But more,

00:02:00.005 --> 00:02:02.348
more formally, the bursting looking cell

00:02:02.348 --> 00:02:04.639
is undergoing necrosis,

00:02:04.639 --> 00:02:06.849
which is a form of cell death

00:02:06.849 --> 00:02:11.147
where the cell basically
swells up and explodes,

00:02:11.147 --> 00:02:12.683
and it releases its contents,

00:02:12.683 --> 00:02:14.261
which is not very good

00:02:14.261 --> 00:02:16.716
because those can damage
other cells in the area,

00:02:16.716 --> 00:02:19.369
they can attract cells
of the immune system

00:02:19.369 --> 00:02:21.320
that will cause inflammation.

00:02:21.320 --> 00:02:22.652
And then on the flip side,

00:02:22.652 --> 00:02:26.030
you have the tidy approach, apoptosis,

00:02:26.030 --> 00:02:28.985
and here you actually see
the cell shrinking down

00:02:28.985 --> 00:02:32.149
and kind of breaking up its DNA,

00:02:32.149 --> 00:02:33.082
breaking up its nucleus--

00:02:33.082 --> 00:02:35.084
- [Voiceover] And that's these
little orange things in here

00:02:35.084 --> 00:02:36.652
are the chromosomes being cut apart--

00:02:36.652 --> 00:02:37.878
- [Voiceover] Yes, so those are, like,

00:02:37.878 --> 00:02:39.594
really little fragments of chromosome.

00:02:39.594 --> 00:02:40.608
They'd actually be much littler

00:02:40.608 --> 00:02:42.899
even than what I've drawn there.

00:02:42.899 --> 00:02:43.979
But what the cell's gonna do

00:02:43.979 --> 00:02:46.195
is it's just kind of going to come apart

00:02:46.195 --> 00:02:50.898
into little fragments encircling
different cell components.

00:02:50.898 --> 00:02:53.384
So you can sort of see
those starting to bud off.

00:02:53.384 --> 00:02:56.155
And then cells from the immune system,

00:02:56.155 --> 00:02:59.061
whose job is basically
to gobble up debris,

00:02:59.061 --> 00:03:00.947
they're gonna come and eat
those little fragments,

00:03:00.947 --> 00:03:02.523
and it's gonna be like
nothing ever happened.

00:03:02.523 --> 00:03:03.589
- [Voiceover] So this is
kind of the difference

00:03:03.589 --> 00:03:07.779
between disposing of your
garbage in trash bags

00:03:07.779 --> 00:03:08.792
and disposing of your garbage

00:03:08.792 --> 00:03:12.349
by just dumping it out the
window of your apartment.

00:03:12.349 --> 00:03:14.111
- [Voiceover] Yes, I think that's true,

00:03:14.111 --> 00:03:16.583
but maybe even taking it a step further.

00:03:16.583 --> 00:03:19.040
If you dispose of your
garbage in trash bags,

00:03:19.040 --> 00:03:22.120
or by apoptosis, you can actually reuse

00:03:22.120 --> 00:03:23.417
what was in the garbage.

00:03:23.417 --> 00:03:24.250
- [Voiceover] Interesting.

00:03:24.250 --> 00:03:27.611
- [Voiceover] So other cells
can use those components

00:03:27.611 --> 00:03:29.034
for their own purposes,

00:03:29.034 --> 00:03:30.491
and they won't suffer any damage

00:03:30.491 --> 00:03:34.491
from having nasty stuff
floating around outside.

00:03:35.328 --> 00:03:37.220
- [Voiceover] So what
are the circumstances

00:03:37.220 --> 00:03:39.659
under which apoptosis happens?

00:03:39.659 --> 00:03:42.166
Like, how common is this,

00:03:42.166 --> 00:03:44.416
and how common is necrosis?

00:03:47.096 --> 00:03:49.187
- [Voiceover] So necrosis
is usually something

00:03:49.187 --> 00:03:51.565
that your body does not want to happen.

00:03:51.565 --> 00:03:53.569
That's gonna happen when a cell

00:03:53.569 --> 00:03:56.421
is perhaps exposed to a chemical toxin,

00:03:56.421 --> 00:04:00.171
when a cell is actually
mechanically damaged.

00:04:01.045 --> 00:04:03.608
So those are circumstances where a cell

00:04:03.608 --> 00:04:05.541
has basically received an insult

00:04:05.541 --> 00:04:08.609
that has caused it to die in
a not very controlled way.

00:04:08.609 --> 00:04:10.059
- [Voiceover] Okay.

00:04:10.059 --> 00:04:12.500
- [Voiceover] And apoptosis
is kind of something

00:04:12.500 --> 00:04:16.517
that would be going on
basically from the time

00:04:16.517 --> 00:04:20.684
a human being or another
vertebrate is a tiny embryo

00:04:21.792 --> 00:04:23.538
throughout its life.

00:04:23.538 --> 00:04:26.246
So when you're developing,

00:04:26.246 --> 00:04:27.849
when you're developing your hands,

00:04:27.849 --> 00:04:29.603
your hand actually kind of starts out

00:04:29.603 --> 00:04:31.252
as this chunk of tissue

00:04:31.252 --> 00:04:33.075
that's kind of like a paddle.
- [Voiceover] Okay.

00:04:33.075 --> 00:04:34.358
- [Voiceover] And it's actually apoptosis

00:04:34.358 --> 00:04:37.653
that is gonna whittle your
fingers out of that block.

00:04:37.653 --> 00:04:41.203
- [Voiceover] So I've
got this hand, right,

00:04:41.203 --> 00:04:43.449
I've got this kind of, like, webby hand,

00:04:43.449 --> 00:04:46.606
and you're telling me
that as the hand develops,

00:04:46.606 --> 00:04:50.152
the tissue gets reabsorbed
into the other cells

00:04:50.152 --> 00:04:52.753
that were gonna make
up the rest of my hand?

00:04:52.753 --> 00:04:54.094
- [Voiceover] Yeah, so the cells,

00:04:54.094 --> 00:04:56.374
they'll first die by apoptosis,

00:04:56.374 --> 00:04:59.449
and then basically the
blebs will get scavenged up.

00:04:59.449 --> 00:05:00.578
- [Voiceover] I'm sorry, the what?

00:05:00.578 --> 00:05:02.087
- [Voiceover] I guess I never
named them, but the little--

00:05:02.087 --> 00:05:03.238
- [Voiceover] These are called blebs?

00:05:03.238 --> 00:05:04.227
- [Voiceover] The little protrusions,

00:05:04.227 --> 00:05:05.770
that's a very technical term.

00:05:05.770 --> 00:05:07.020
That's a bleb.
- [Voiceover] Bleb.

00:05:07.020 --> 00:05:08.895
I love that. (giggles)

00:05:08.895 --> 00:05:09.970
- [Voiceover] You'll
see it in scientific--

00:05:09.970 --> 00:05:11.792
- [Voiceover] That's a
science word, is bleb?

00:05:11.792 --> 00:05:12.625
- [Voiceover] Totally scientific.

00:05:12.625 --> 00:05:13.557
- [Voiceover] I love that, all right.

00:05:13.557 --> 00:05:14.548
- [Voiceover] It's blebs.
- [Voiceover] Okay.

00:05:14.548 --> 00:05:15.563
- [Voiceover] You can also see them

00:05:15.563 --> 00:05:17.892
in the picture up at right.

00:05:17.892 --> 00:05:20.485
- [Voiceover] So what is this image here?

00:05:20.485 --> 00:05:21.783
- [Voiceover] So those
are, that's basically

00:05:21.783 --> 00:05:24.908
just the same thing that
the line diagram is showing,

00:05:24.908 --> 00:05:27.159
healthy cells, which is the left panel,

00:05:27.159 --> 00:05:29.853
and then blebby cells
undergoing apoptosis,

00:05:29.853 --> 00:05:31.373
which is the right panel.

00:05:31.373 --> 00:05:34.017
- [Voiceover] So they're having
all of their cell components

00:05:34.017 --> 00:05:36.806
repackaged into garbage bags to be,

00:05:36.806 --> 00:05:38.502
or, if we want, recycling bags,

00:05:38.502 --> 00:05:40.341
that'd be sent off to other cells

00:05:40.341 --> 00:05:42.944
where their components
can be reused as stuff?

00:05:42.944 --> 00:05:45.323
- [Voiceover] Exactly.
- [Voiceover] Okay.

00:05:45.323 --> 00:05:48.240
Now what's this tadpole beast here?

00:05:49.822 --> 00:05:50.979
What is this about?

00:05:50.979 --> 00:05:52.100
- [Voiceover] So that's
kind of the same thing

00:05:52.100 --> 00:05:54.082
that we were talking about with the hand,

00:05:54.082 --> 00:05:57.167
but another place where you see apoptosis

00:05:57.167 --> 00:05:59.394
happening in development is when you have

00:05:59.394 --> 00:06:02.477
a tadpole metamorphosing into a frog.

00:06:03.611 --> 00:06:05.644
So tadpoles, this is actually kind of

00:06:05.644 --> 00:06:07.379
part of the way they're already,

00:06:07.379 --> 00:06:09.345
the tadpoles have a very long tail,

00:06:09.345 --> 00:06:13.118
and frogs generally don't have
much of a tail to speak of,

00:06:13.118 --> 00:06:15.190
and the way that the frog loses its tail

00:06:15.190 --> 00:06:17.064
is through apoptosis.

00:06:17.064 --> 00:06:20.429
And again, it's said to resorb the tail,

00:06:20.429 --> 00:06:22.867
so that it can make use of
the cellular components.

00:06:22.867 --> 00:06:24.576
- [Voiceover] Cool.

00:06:24.576 --> 00:06:28.543
So a tail just sort of shoots
up and becomes hindquarters?

00:06:28.543 --> 00:06:31.476
- [Voiceover] Yeah, I don't
actually know exactly,

00:06:31.476 --> 00:06:32.705
you know, if it starts from the end

00:06:32.705 --> 00:06:34.256
and eats its way inward,

00:06:34.256 --> 00:06:37.775
but somehow it gets
removed developmentally.

00:06:37.775 --> 00:06:39.866
- [Voiceover] Aw man, that's really cool.

00:06:39.866 --> 00:06:41.231
So it's not, it's not, it's not

00:06:41.231 --> 00:06:43.794
really like leaves falling off a tree.

00:06:43.794 --> 00:06:47.369
It's not like this is a
three-toed skink or something.

00:06:47.369 --> 00:06:50.224
If you grabbed a metamorphosing
tadpole by the tail,

00:06:50.224 --> 00:06:51.910
it would just break off.

00:06:51.910 --> 00:06:54.802
It's really more that it
gradually gets subsumed

00:06:54.802 --> 00:06:58.247
into the tissue of the growing frog.

00:06:58.247 --> 00:07:00.177
- [Voiceover] I mean,
at the cellular level,

00:07:00.177 --> 00:07:01.410
I guess the cells do,

00:07:01.410 --> 00:07:03.245
they pull away from their neighbors,

00:07:03.245 --> 00:07:05.446
so in that sense it's a falling off.

00:07:05.446 --> 00:07:07.005
But it's not necessarily a falling off

00:07:07.005 --> 00:07:09.847
that you see at the
level of a whole organ.

00:07:09.847 --> 00:07:12.817
It would be more a falling
off of an individual cell.

00:07:12.817 --> 00:07:14.001
- [Voiceover] So so far
we've given examples

00:07:14.001 --> 00:07:18.168
of apoptosis that are happening
within developing creatures,

00:07:19.177 --> 00:07:22.045
but you're saying that within, like,

00:07:22.045 --> 00:07:25.465
right now, apoptosis is
happening in my body.

00:07:25.465 --> 00:07:26.311
- [Voiceover] That's a fact.

00:07:26.311 --> 00:07:27.300
- [Voiceover] So does that mean,

00:07:27.300 --> 00:07:29.193
is that just to keep the number of cells

00:07:29.193 --> 00:07:31.184
in my body constant?

00:07:31.184 --> 00:07:32.159
- [Voiceover] That's a big part

00:07:32.159 --> 00:07:34.847
of the role that apoptosis plays,

00:07:34.847 --> 00:07:37.247
like your blood system in particular

00:07:37.247 --> 00:07:39.445
is continually producing new cells,

00:07:39.445 --> 00:07:43.596
and if you produce cells but
you never got rid of cells,

00:07:43.596 --> 00:07:46.222
you would eventually end
up with too many cells,

00:07:46.222 --> 00:07:48.879
and too many cells in
general is not a great thing

00:07:48.879 --> 00:07:50.130
to have in the human body.

00:07:50.130 --> 00:07:52.091
That's the kind of thing
that you might get in cancer,

00:07:52.091 --> 00:07:53.141
if you're having--
- [Voiceover] Okay.

00:07:53.141 --> 00:07:55.988
- [Voiceover] Cells accumulating too much.

00:07:55.988 --> 00:07:58.293
So part of it is just
keeping a healthy balance,

00:07:58.293 --> 00:08:00.738
but since we also just brought up cancer,

00:08:00.738 --> 00:08:03.081
that's actually another wonderful favor

00:08:03.081 --> 00:08:05.566
that all of our cells are doing for us,

00:08:05.566 --> 00:08:08.152
is if they suffer DNA damage,

00:08:08.152 --> 00:08:12.024
which could predispose
them to become cancerous,

00:08:12.024 --> 00:08:13.191
first they'll try to fix it,

00:08:13.191 --> 00:08:14.875
but if they can't fix it,

00:08:14.875 --> 00:08:17.611
they will actually, under
normal circumstances,

00:08:17.611 --> 00:08:20.716
undergo apoptosis, so there's no chance

00:08:20.716 --> 00:08:24.456
of them passing that damage
on and becoming cancerous.

00:08:24.456 --> 00:08:26.731
And that's actually a really
important protective role

00:08:26.731 --> 00:08:29.877
that apoptosis plays in an adult human,

00:08:29.877 --> 00:08:33.071
or in a human at any stage of their life.

00:08:33.071 --> 00:08:36.654
So it's kind of like
a big red button that,

00:08:38.363 --> 00:08:40.160
you know, it's like a
self-destruct button.

00:08:40.160 --> 00:08:43.370
If a cell comes to appreciate

00:08:43.370 --> 00:08:46.284
that it is developing cancerous symptoms,

00:08:46.284 --> 00:08:48.073
then it just hits the button

00:08:48.073 --> 00:08:51.347
and begins this cascade of enzymes

00:08:51.347 --> 00:08:54.627
that cause it to undergo apoptosis?

00:08:54.627 --> 00:08:55.494
- [Voiceover] Yeah, I mean, I think that's

00:08:55.494 --> 00:08:59.407
the general way to think of it for sure.

00:08:59.407 --> 00:09:01.432
So there are actually
kind of different ways

00:09:01.432 --> 00:09:03.227
that cells that are progressing

00:09:03.227 --> 00:09:05.380
towards cancer might be stopped,

00:09:05.380 --> 00:09:08.548
and some of those involve
internal mechanisms,

00:09:08.548 --> 00:09:10.968
so the cell doing its own surveillance

00:09:10.968 --> 00:09:14.460
and observing, wow, gee,
my DNA does not look good,

00:09:14.460 --> 00:09:15.324
and I can't fix it.

00:09:15.324 --> 00:09:16.649
- [Voiceover] Okay.
- [Voiceover] But also,

00:09:16.649 --> 00:09:20.758
you could have a cell
that might be observable

00:09:20.758 --> 00:09:23.046
from the outside by another cell

00:09:23.046 --> 00:09:24.743
as a potential cancer cell--

00:09:24.743 --> 00:09:26.489
- [Voiceover] So like an immune cell

00:09:26.489 --> 00:09:30.014
could come by and like, stick
a protein on the outside

00:09:30.014 --> 00:09:32.908
that also triggers the same thing?

00:09:32.908 --> 00:09:35.102
- [Voiceover] Yeah, yeah, I don't,

00:09:35.102 --> 00:09:36.068
you know, I don't know exactly

00:09:36.068 --> 00:09:38.338
what the mechanism of
communication there is,

00:09:38.338 --> 00:09:41.023
but it would be an interaction
between the two cells

00:09:41.023 --> 00:09:42.687
where one of them would
tell the other, you know,

00:09:42.687 --> 00:09:45.072
okay, I see there's
something wrong with you.

00:09:45.072 --> 00:09:47.264
You know, time to wrap this up.

00:09:47.264 --> 00:09:48.097
- [Voiceover] Cool.

00:09:48.097 --> 00:09:50.369
So apoptosis can happen
in a couple of ways,

00:09:50.369 --> 00:09:52.233
but in pretty much all cases,

00:09:52.233 --> 00:09:56.307
it is a normal, healthy
part of the cell lifecycle.

00:09:56.307 --> 00:09:58.474
Do all cells die this way?

00:09:59.812 --> 00:10:00.790
- [Voiceover] I mean, there are cells

00:10:00.790 --> 00:10:03.040
that will undergo necrosis,

00:10:04.558 --> 00:10:08.069
so certainly in that sense
not every cell in your body

00:10:08.069 --> 00:10:10.486
is going to die by apoptosis.

00:10:11.353 --> 00:10:13.295
I would imagine that there are also

00:10:13.295 --> 00:10:15.535
other ways of recycling used cells

00:10:15.535 --> 00:10:19.035
that are not exactly considered apoptosis.

00:10:20.602 --> 00:10:24.416
Like skin cells, some of them will undergo

00:10:24.416 --> 00:10:25.665
kind of a similar process,

00:10:25.665 --> 00:10:28.201
but it's not technically apoptosis,

00:10:28.201 --> 00:10:30.578
even though it is a
regulated form of cell death.

00:10:30.578 --> 00:10:32.120
- [Voiceover] Okay.

00:10:32.120 --> 00:10:33.321
- [Voiceover] So I don't
think that I would go as far

00:10:33.321 --> 00:10:35.168
as to say that all of your cells

00:10:35.168 --> 00:10:37.489
were eventually gonna die this way.

00:10:37.489 --> 00:10:40.721
But it's sort of a very
common maintenance way

00:10:40.721 --> 00:10:43.435
for cells to die and be replaced.

00:10:43.435 --> 00:10:44.839
- [Voiceover] Cool.

00:10:44.839 --> 00:10:45.748
Thanks, Emily.

00:10:45.748 --> 00:10:46.997
- [Voiceover] Thanks, David.


Organism life history and fecundity

WEBVTT
Kind: captions
Language: en

00:00:00.000 --> 00:00:01.338
- [Voiceover] What we're
gonna talk about in this video

00:00:01.338 --> 00:00:04.976
is what I consider one of
the most fascinating subjects

00:00:04.976 --> 00:00:07.306
in biology and that's the variation we see

00:00:07.306 --> 00:00:10.352
from species to species in life histories

00:00:10.352 --> 00:00:12.983
and lifespans and the
rate of reproduction.

00:00:12.983 --> 00:00:16.066
For example, we have three
different species here.

00:00:16.066 --> 00:00:18.568
On the left we have an African elephant,

00:00:18.568 --> 00:00:19.993
and African elephant you might know,

00:00:19.993 --> 00:00:22.939
can live a long time,
especially out in the wild.

00:00:22.939 --> 00:00:26.526
It can live many decades,
even 40, 50, 60 years.

00:00:26.526 --> 00:00:29.612
And their life history
actually parallels human,

00:00:29.612 --> 00:00:32.255
at least modern human, life
history in a lot of ways.

00:00:32.255 --> 00:00:34.303
The first 10 years of their life,

00:00:34.303 --> 00:00:36.856
they are very dependent on their parents.

00:00:36.856 --> 00:00:39.905
After that, they kind of enter into a bit

00:00:39.905 --> 00:00:43.505
of an adolescence very
similar to how humans do

00:00:43.505 --> 00:00:44.338
where in theory, they could reproduce

00:00:44.338 --> 00:00:45.171
but they don't tend to

00:00:45.171 --> 00:00:46.004
and they are still somewhat dependent.

00:00:49.311 --> 00:00:51.876
And then they move into a phase

00:00:51.876 --> 00:00:53.473
when they do reproduce.

00:00:53.473 --> 00:00:54.306
And they will reproduce on the order of

00:00:54.306 --> 00:00:55.139
once every two to four years.

00:01:01.873 --> 00:01:04.769
A female African elephant will reproduce.

00:01:04.769 --> 00:01:08.084
Their gestation periods,
the amount of time the baby

00:01:08.084 --> 00:01:11.688
elephant will be in the mother's
womb is on the order of,

00:01:11.688 --> 00:01:13.744
it's actually longer than, for humans.

00:01:13.744 --> 00:01:15.747
Humans you probably know is nine months,

00:01:15.747 --> 00:01:17.232
for an African elephant it is 22 months.

00:01:17.232 --> 00:01:19.054
And so because of that,

00:01:19.054 --> 00:01:22.305
they can reproduce about
once every 2 to 4 years.

00:01:22.305 --> 00:01:24.340
Now, another example, and these are --

00:01:24.340 --> 00:01:27.558
actually elephants and
rabbits might not look

00:01:27.558 --> 00:01:29.584
closely related to you,
but they are actually

00:01:29.584 --> 00:01:32.173
pretty closely related if you think about

00:01:32.173 --> 00:01:33.467
the entire tree of life.

00:01:33.467 --> 00:01:36.236
They are both mammals
and actually everything

00:01:36.236 --> 00:01:38.419
we're considering here are animals.

00:01:38.419 --> 00:01:40.509
We're going to consider
African elephants, rabbits

00:01:40.509 --> 00:01:42.400
and we're going to consider salmon.

00:01:42.400 --> 00:01:45.100
But what I'm talking about
about applies to all life.

00:01:45.100 --> 00:01:47.718
It applies to bacteria,
it applies to trees,

00:01:47.718 --> 00:01:51.457
there's a huge variation
in their fecundity,

00:01:51.457 --> 00:01:53.719
the rate at which they reproduce.

00:01:53.719 --> 00:01:55.653
Let me write that word down.

00:01:55.653 --> 00:01:56.486
Fecundity.

00:01:57.754 --> 00:02:01.340
Fecundity, the rate at
which they reproduce,

00:02:01.340 --> 00:02:03.738
and also variation in
their actual lifespan,

00:02:03.738 --> 00:02:05.404
whether we're talking about a tree

00:02:05.404 --> 00:02:08.844
or a bacteria, or a fish, or a mammal.

00:02:08.844 --> 00:02:10.826
Just going from one mammal to another

00:02:10.826 --> 00:02:13.704
let's go to a rabbit, and
depending on which type

00:02:13.704 --> 00:02:17.214
of rabbit you're talking
about, but a rabbit could,

00:02:17.214 --> 00:02:20.874
lifespan is in the single-digit years.

00:02:20.874 --> 00:02:22.872
But unlike an elephant, an elephant,

00:02:22.872 --> 00:02:26.346
the first 10, 15, 20
years of their life, they

00:02:26.346 --> 00:02:28.785
aren't in that reproductive
phase of their life.

00:02:28.785 --> 00:02:31.792
A rabbit enters into
that reproductive phase

00:02:31.792 --> 00:02:33.740
of their life within several months,

00:02:33.740 --> 00:02:36.448
within four, five months of birth.

00:02:36.448 --> 00:02:39.246
And so, once they enter
into that reproductive phase

00:02:39.246 --> 00:02:42.206
and I'm showing the reproductive
phase in magenta here,

00:02:42.206 --> 00:02:44.558
they can reproduce a lot.

00:02:44.558 --> 00:02:46.784
They have high fecundity,
they have very high

00:02:46.784 --> 00:02:48.939
reproductive rate.

00:02:48.939 --> 00:02:51.405
Every time a female rabbit has a litter,

00:02:51.405 --> 00:02:54.905
it can have many, many baby rabbits in it.

00:02:58.827 --> 00:03:02.994
The numbers I found were one
to 14, one to 14 rabbits.

00:03:04.423 --> 00:03:07.128
And not only can they
have one to 14 rabbits

00:03:07.128 --> 00:03:10.243
every time they have a
litter, but they can have

00:03:10.243 --> 00:03:14.442
they can do this, on the
order of once a month.

00:03:14.442 --> 00:03:16.275
So every, every month.

00:03:18.904 --> 00:03:21.143
So even though the lifespan
of the female rabbit

00:03:21.143 --> 00:03:23.639
depending on which type of
rabbit you're talking about,

00:03:23.639 --> 00:03:27.056
it might be three, four, five, six years,

00:03:28.643 --> 00:03:31.176
depending on the type of
rabbit you're talking about.

00:03:31.176 --> 00:03:33.340
You can imagine, if they're
producing let's say,

00:03:33.340 --> 00:03:37.243
10 rabbits every month per
year, they could produce

00:03:37.243 --> 00:03:41.535
120 rabbits, or, if they can
produce 10 rabbits per month

00:03:41.535 --> 00:03:43.752
12 months a year, that's
120 rabbits a year

00:03:43.752 --> 00:03:45.335
over several years.

00:03:47.748 --> 00:03:50.031
And then you can imagine those rabbits,

00:03:50.031 --> 00:03:53.001
very quickly, the female
ones, if you assume roughly

00:03:53.001 --> 00:03:55.123
half of them are female, that half

00:03:55.123 --> 00:03:57.034
can very quickly get into
that reproductive phase

00:03:57.034 --> 00:03:58.903
and start reproducing at a similar rate.

00:03:58.903 --> 00:04:00.763
So, on an individual level

00:04:00.763 --> 00:04:02.800
a female rabbit has high fecundity,

00:04:02.800 --> 00:04:06.503
and on a population level,
that group of rabbits

00:04:06.503 --> 00:04:10.029
will also have very, very high fecundity.

00:04:10.029 --> 00:04:11.773
And then we can look at another example.

00:04:11.773 --> 00:04:14.109
And this is the example of salmon

00:04:14.109 --> 00:04:16.293
and there are many types of salmon

00:04:16.293 --> 00:04:18.624
but the general way that salmon,

00:04:18.624 --> 00:04:22.782
the general life cycle
that salmon go through

00:04:22.782 --> 00:04:26.668
is they are born then
and they are usually born

00:04:26.668 --> 00:04:29.684
up some stream and usually some water

00:04:29.684 --> 00:04:32.605
where there isn't a strong current,

00:04:32.605 --> 00:04:35.417
and then once the baby salmon are born,

00:04:35.417 --> 00:04:38.346
and they can be born in groups of hundreds

00:04:38.346 --> 00:04:41.460
or thousands, they make
their way down that river

00:04:41.460 --> 00:04:44.137
down that stream, into the
ocean and then they have

00:04:44.137 --> 00:04:46.618
many years of a growth phase in the ocean

00:04:46.618 --> 00:04:48.478
where they get larger and larger.

00:04:48.478 --> 00:04:50.339
They're not reproducing then

00:04:50.339 --> 00:04:52.812
and then when they are ready to reproduce

00:04:52.812 --> 00:04:56.628
they fight their way
back up the same stream

00:04:56.628 --> 00:04:58.657
that they were born in or the same river

00:04:58.657 --> 00:05:01.070
that they were born in,
they fight their way

00:05:01.070 --> 00:05:04.414
back up to it they reproduce, and this is

00:05:04.414 --> 00:05:06.241
both the males and females.

00:05:06.241 --> 00:05:08.985
The males fertilize the
females produce the eggs,

00:05:08.985 --> 00:05:12.857
the males fertilize the
eggs and then they die.

00:05:12.857 --> 00:05:15.845
So they have one reproductive event.

00:05:15.845 --> 00:05:17.921
So you have one reproductive then death

00:05:17.921 --> 00:05:21.195
and then they kill, they just die.

00:05:21.195 --> 00:05:22.685
People still understanding,

00:05:22.685 --> 00:05:24.834
why exactly does this happen?

00:05:24.834 --> 00:05:28.584
So one reproductive
event, reproductive event

00:05:32.662 --> 00:05:34.162
and then they die.

00:05:35.312 --> 00:05:37.853
And there's actually a
technical term for species

00:05:37.853 --> 00:05:39.074
that do this.

00:05:39.074 --> 00:05:41.719
Salmon isn't the only one
where they have that one,

00:05:41.719 --> 00:05:43.739
where they go out with
you can kind of view it as

00:05:43.739 --> 00:05:46.264
a big bang, where they have
that one reproductive event

00:05:46.264 --> 00:05:49.367
where they might have hundreds
or even thousands of eggs,

00:05:49.367 --> 00:05:50.768
but then they die.

00:05:50.768 --> 00:05:52.843
This is called semel parity.

00:05:52.843 --> 00:05:54.881
Let me write this down.

00:05:54.881 --> 00:05:57.464
So this is called semel parity.

00:05:59.956 --> 00:06:02.712
Semel comes from the Latin for once.

00:06:02.712 --> 00:06:06.186
Parity comes from the
Latin for to beget so,

00:06:06.186 --> 00:06:07.914
to beget once.

00:06:07.914 --> 00:06:10.195
You're reproducing once,
and then in the case of

00:06:10.195 --> 00:06:12.240
salmon, you are are dying.

00:06:12.240 --> 00:06:14.109
And you might say okay,
if that's semel parity

00:06:14.109 --> 00:06:16.355
what would we call an elephant or rabbits,

00:06:16.355 --> 00:06:18.484
for sure, and an elephant as well.

00:06:18.484 --> 00:06:20.377
They can have multiple
reproductive events.

00:06:20.377 --> 00:06:23.210
Well, that is called itero parity.

00:06:25.079 --> 00:06:26.829
Itero, itero parity.

00:06:27.984 --> 00:06:30.465
You might've heard the word iterate

00:06:30.465 --> 00:06:33.076
that means to repeat something

00:06:33.076 --> 00:06:34.952
or to do something over and over again.

00:06:34.952 --> 00:06:37.429
Itero is the root for, it means repeat.

00:06:37.429 --> 00:06:40.468
So, itero parity, beget repeatedly.

00:06:40.468 --> 00:06:43.253
And so that's what animals
like elephants and,

00:06:43.253 --> 00:06:47.134
for sure, rabbits are actually doing.

00:06:47.134 --> 00:06:49.028
And what's fascinating about all of this

00:06:49.028 --> 00:06:51.410
and it is a question that I have wondered

00:06:51.410 --> 00:06:54.457
many, since I first
realized when I was young

00:06:54.457 --> 00:06:57.445
was, wow, why is there
so much variation here?

00:06:57.445 --> 00:07:01.028
Is, why has nature
selected for or why have

00:07:02.075 --> 00:07:05.279
these species found niches
in which they can operate

00:07:05.279 --> 00:07:07.883
in which it makes sense,
where natural selection

00:07:07.883 --> 00:07:11.569
has selected for these
very different lifespans,

00:07:11.569 --> 00:07:14.524
these very different reproduction rates

00:07:14.524 --> 00:07:16.661
this variation in fecundity,

00:07:16.661 --> 00:07:19.320
this, you know sometimes itero parity,

00:07:19.320 --> 00:07:20.825
sometimes a semel parity.

00:07:20.825 --> 00:07:23.135
And it is a bit of, it's not a mystery,

00:07:23.135 --> 00:07:25.172
people are studying this and they have

00:07:25.172 --> 00:07:27.517
good hypothesis, but
we don't know for sure,

00:07:27.517 --> 00:07:30.193
especially from species to species.

00:07:30.193 --> 00:07:31.994
And a framework you could use

00:07:31.994 --> 00:07:33.411
to think about it

00:07:35.851 --> 00:07:37.663
is a species,

00:07:37.663 --> 00:07:40.580
they're trying to optimize survival

00:07:41.732 --> 00:07:43.527
and not even of the individual,

00:07:43.527 --> 00:07:45.898
they're trying to optimize survival of

00:07:45.898 --> 00:07:48.190
really their genetic information.

00:07:48.190 --> 00:07:50.273
It's not like the species or the genes are

00:07:50.273 --> 00:07:52.127
actively trying to do
it, but natural selection

00:07:52.127 --> 00:07:53.907
is doing that for them.

00:07:53.907 --> 00:07:57.382
So let's call this box natural selection.

00:07:57.382 --> 00:07:58.882
Natural selection,

00:07:59.940 --> 00:08:01.868
and so, and what you have

00:08:01.868 --> 00:08:04.601
coming out of this is the fittest,

00:08:04.601 --> 00:08:05.768
fittest genes.

00:08:06.802 --> 00:08:08.544
And when we talk about fittest

00:08:08.544 --> 00:08:09.982
genes, were not talking about

00:08:09.982 --> 00:08:11.449
somehow that some are better

00:08:11.449 --> 00:08:13.717
than others, we're just
saying for that environment,

00:08:13.717 --> 00:08:18.301
the ones that seem, the
genes that produce the traits

00:08:18.301 --> 00:08:21.640
that are most suitable to survival

00:08:21.640 --> 00:08:23.812
and most suitable towards reproduction

00:08:23.812 --> 00:08:25.415
and then the inputs that are

00:08:25.415 --> 00:08:27.426
going into this natural selection box

00:08:27.426 --> 00:08:31.040
are things like availability of energy,

00:08:31.040 --> 00:08:33.532
of food, of what I called free energy.

00:08:33.532 --> 00:08:36.263
Availability, because it's
not just obviously plants

00:08:36.263 --> 00:08:39.313
can get that free energy from the sun.

00:08:39.313 --> 00:08:42.396
Availability, availability of energy,

00:08:45.094 --> 00:08:47.123
we can talk about the

00:08:47.123 --> 00:08:48.956
predatory environment,

00:08:50.073 --> 00:08:52.823
predatory, predatory environment.

00:08:54.641 --> 00:08:57.558
We can talk about disease, disease.

00:08:59.048 --> 00:09:02.815
Every moment that an organism is alive

00:09:02.815 --> 00:09:05.320
it has to worry about these things.

00:09:05.320 --> 00:09:07.543
It has to worry about finding food

00:09:07.543 --> 00:09:08.995
or competing for food.

00:09:08.995 --> 00:09:10.768
It has to worry about predators,

00:09:10.768 --> 00:09:12.537
it has to worry about disease.

00:09:12.537 --> 00:09:14.250
And once again the individual organism

00:09:14.250 --> 00:09:15.083
is not sitting there, it's not necessary

00:09:15.083 --> 00:09:16.963
that these salmon are like,

00:09:16.963 --> 00:09:18.674
"Oh, I hope I don't catch a disease,"

00:09:18.674 --> 00:09:22.198
or they might not even be
stressed about the bears

00:09:22.198 --> 00:09:24.807
that might try to grab
them as they go upstream

00:09:24.807 --> 00:09:27.629
but these are the factors
that play into how

00:09:27.629 --> 00:09:30.379
or what gets selected for I guess

00:09:33.054 --> 00:09:35.998
is that the best way to phrase it.

00:09:35.998 --> 00:09:38.799
And in terms from a species point of view

00:09:38.799 --> 00:09:41.301
the various styles will
these are things like

00:09:41.301 --> 00:09:46.121
reproduction, like what is
the species decide to do

00:09:46.121 --> 00:09:48.365
given these constraints?

00:09:48.365 --> 00:09:52.132
And so the various styles are fecundity,

00:09:52.132 --> 00:09:53.684
actually, let me write this,

00:09:53.684 --> 00:09:55.843
rate of reproduction, age of reproduction

00:09:55.843 --> 00:09:59.343
and these are related, age of reproduction

00:10:00.190 --> 00:10:03.414
things like lifespan and
these are all related

00:10:03.414 --> 00:10:04.858
in some way.

00:10:04.858 --> 00:10:07.608
Lifespan, growth, growth, health.

00:10:10.491 --> 00:10:13.158
And a species and an organism is

00:10:14.720 --> 00:10:16.798
making trade-offs all the time.

00:10:16.798 --> 00:10:19.657
You know, the salmon goes
through that huge phase

00:10:19.657 --> 00:10:22.127
where it's deciding to
apply most of its energy

00:10:22.127 --> 00:10:24.650
towards growth and survival,
and then all of a sudden

00:10:24.650 --> 00:10:28.186
it kicks into another
gear, where it actually

00:10:28.186 --> 00:10:30.465
uses a lot of energy that was stored up

00:10:30.465 --> 00:10:33.488
to go upstream and goes
into a reproductive phase

00:10:33.488 --> 00:10:35.579
and then and then it dies.

00:10:35.579 --> 00:10:39.149
And natural selection
has, this has happened

00:10:39.149 --> 00:10:42.820
arguably because that somehow helps

00:10:42.820 --> 00:10:45.843
the salmon's DNA to spread more.

00:10:45.843 --> 00:10:48.702
Maybe somehow it adds
nutrients to the water

00:10:48.702 --> 00:10:51.232
or you know, they put all
that energy to go upstream

00:10:51.232 --> 00:10:53.956
so that their offspring
will have an easier time

00:10:53.956 --> 00:10:55.778
going downstream.

00:10:55.778 --> 00:10:57.772
But there's also other trade-offs.

00:10:57.772 --> 00:10:59.501
You could have things that lay,

00:10:59.501 --> 00:11:01.813
a salmon might, a female salmon might

00:11:01.813 --> 00:11:04.117
lay thousands of eggs
but very few of those

00:11:04.117 --> 00:11:08.016
actually make it, make it
through the full cycle.

00:11:08.016 --> 00:11:09.456
The estimates that I've seen is that

00:11:09.456 --> 00:11:11.852
out of those thousands
of eggs that get laid

00:11:11.852 --> 00:11:14.973
only about three make it back.

00:11:14.973 --> 00:11:17.642
This was the example I
saw for sockeye salmon,

00:11:17.642 --> 00:11:19.676
on average only three of them make it back

00:11:19.676 --> 00:11:21.274
for the next year.

00:11:21.274 --> 00:11:23.878
So you have a huge amount
of, I guess you could say,

00:11:23.878 --> 00:11:26.950
attrition, while in the
case of an elephant,

00:11:26.950 --> 00:11:29.869
they invest more per offspring

00:11:29.869 --> 00:11:32.289
and you have a much higher probability

00:11:32.289 --> 00:11:34.676
that each of those offspring will survive.

00:11:34.676 --> 00:11:37.062
So there's all sorts of
interesting trade-offs

00:11:37.062 --> 00:11:39.566
to think about when you
think about life history,

00:11:39.566 --> 00:11:43.267
lifecycle, lifespan and
things like fecundity

00:11:43.267 --> 00:11:45.600
and how organisms reproduce.


Ecology introduction

WEBVTT
Kind: captions
Language: en

00:00:00.853 --> 00:00:02.311
- [Voiceover] We're now
going to start looking at

00:00:02.311 --> 00:00:05.941
ecology, which is just the
study of how life interacts

00:00:05.941 --> 00:00:08.274
with other life or how
living things interact

00:00:08.274 --> 00:00:11.540
with each other and their environment.

00:00:11.540 --> 00:00:13.427
And you you could think of it well how

00:00:13.427 --> 00:00:15.477
is life interacting with living beings?

00:00:15.477 --> 00:00:18.265
So that's the technical term often given

00:00:18.265 --> 00:00:20.133
as biotic factors,

00:00:20.133 --> 00:00:23.966
biotic factors, you have
the word bio in there

00:00:24.813 --> 00:00:26.546
signaling life,

00:00:26.546 --> 00:00:29.629
or non-living things, abiotic factor.

00:00:30.467 --> 00:00:32.967
A is the prefix often for not,

00:00:34.241 --> 00:00:36.324
so abiotic is not living,

00:00:37.354 --> 00:00:40.122
not living factors, and those
are just the technical terms,

00:00:40.122 --> 00:00:43.518
but if you even think about
yourself as you watch this video

00:00:43.518 --> 00:00:47.433
you are in an environment,
you are interacting with it.

00:00:47.433 --> 00:00:50.178
There are many abiotic
factors around you that you

00:00:50.178 --> 00:00:53.261
might notice, the air
that you are breathing,

00:00:53.261 --> 00:00:56.909
the temperature, your access to water,

00:00:56.909 --> 00:00:59.112
but there's also biotic factors.

00:00:59.112 --> 00:01:01.024
Even if you think you're in a room alone,

00:01:01.024 --> 00:01:03.521
you're not fully, you're
not completely alone.

00:01:03.521 --> 00:01:05.794
There is bacteria around you that

00:01:05.794 --> 00:01:07.145
you might not see.

00:01:07.145 --> 00:01:08.539
There might be other forms of life,

00:01:08.539 --> 00:01:09.890
you might have a plant in the room.

00:01:09.890 --> 00:01:13.017
Those are the biotic factors
that you are interacting with.

00:01:13.017 --> 00:01:14.683
That plant in that room
might be producing oxygen

00:01:14.683 --> 00:01:16.415
that you are then breathing,

00:01:16.415 --> 00:01:18.395
or you're producing carbon
dioxide which that plant

00:01:18.395 --> 00:01:20.308
is able to fix and grow.

00:01:20.308 --> 00:01:22.783
And it might be interacting
with abiotic factors

00:01:22.783 --> 00:01:25.663
like sunlight to in
order to that it uses in

00:01:25.663 --> 00:01:27.621
photosynthesis in order to fix the carbon.

00:01:27.621 --> 00:01:29.444
We study all of that in
some depth in biology,

00:01:29.444 --> 00:01:33.718
and really ecology is a
bit of a synthesis of a lot

00:01:33.718 --> 00:01:36.598
of what we learn, if
anything, all of what we learn

00:01:36.598 --> 00:01:39.906
in biology because it's taking life,

00:01:39.906 --> 00:01:43.259
it's studying life at another level

00:01:43.259 --> 00:01:45.689
where it's not just the
individual organism anymore,

00:01:45.689 --> 00:01:49.425
and it's not even just the
population or the community,

00:01:49.425 --> 00:01:53.092
but we're talking about
an even bigger system that

00:01:53.092 --> 00:01:55.974
is incredibly complex and that's why it's

00:01:55.974 --> 00:01:57.525
a really interesting thing to study.

00:01:57.525 --> 00:02:00.833
Now all of these images here
are things that folks would

00:02:00.833 --> 00:02:03.690
associate with an ecosystem.

00:02:03.690 --> 00:02:05.490
Over here you have a coral reef,

00:02:05.490 --> 00:02:07.966
and some of the life is obvious,

00:02:07.966 --> 00:02:10.868
you see the coral, you see the fish here,

00:02:10.868 --> 00:02:13.839
but there's also life
that you're not seeing.

00:02:13.839 --> 00:02:16.403
There's going to be bacteria in this water

00:02:16.403 --> 00:02:18.316
that's not visible at
least in the picture.

00:02:18.316 --> 00:02:21.196
And the abiotic factors are going to

00:02:21.196 --> 00:02:22.884
be things like the water temperature,

00:02:22.884 --> 00:02:24.707
or frankly, just even
the existence of water,

00:02:24.707 --> 00:02:27.205
or the salt content of the water,

00:02:27.205 --> 00:02:29.567
or other minerals that are in the water.

00:02:29.567 --> 00:02:30.894
In these pictures over here,

00:02:30.894 --> 00:02:33.010
you don't necessarily see the animal life,

00:02:33.010 --> 00:02:35.811
but there is for sure
going to be if you were

00:02:35.811 --> 00:02:38.689
to dig into this grass or
look through those bushes

00:02:38.689 --> 00:02:39.991
you will find animal life,

00:02:39.991 --> 00:02:42.421
you will find insects, you
will find other animals.

00:02:42.421 --> 00:02:44.198
The trees are life,

00:02:44.198 --> 00:02:46.320
so that's going to be
part of the ecosystem.

00:02:46.320 --> 00:02:48.631
If we're studying ecology we think about

00:02:48.631 --> 00:02:52.051
well how do these trees
interact with the water,

00:02:52.051 --> 00:02:53.784
how do they interact
with the other species?

00:02:53.784 --> 00:02:54.999
How do they provide shelter for them?

00:02:54.999 --> 00:02:56.082
Or food?

00:02:56.082 --> 00:02:58.151
Or how are they dependent
on the other life

00:02:58.151 --> 00:02:59.342
in some way to grow?

00:02:59.342 --> 00:03:01.479
Same thing for in this case the mushrooms.

00:03:01.479 --> 00:03:05.845
How does the fungus living
on this tree branch,

00:03:05.845 --> 00:03:10.278
or in conjunction with the
moss and whatever else?

00:03:10.278 --> 00:03:12.843
All of this is the study of ecology,

00:03:12.843 --> 00:03:15.115
the study of ecosystems.

00:03:15.115 --> 00:03:17.163
Now when folks are talking about ecology

00:03:17.163 --> 00:03:19.300
they like to talk about different scales.

00:03:19.300 --> 00:03:24.071
And so let's now think
about the different scales

00:03:24.071 --> 00:03:27.468
within an ecosystem, or
even beyond an ecosystem.

00:03:27.468 --> 00:03:31.879
So I have some pictures that
if you watch a wildlife show

00:03:31.879 --> 00:03:34.395
you typically see some images like this,

00:03:34.395 --> 00:03:37.276
and so since we at least
are familiar with it,

00:03:37.276 --> 00:03:39.615
at least on TV hopefully we
get to visit this at some

00:03:39.615 --> 00:03:42.337
point in our life, let's just
think about the different

00:03:42.337 --> 00:03:45.398
characters here on the
different ecological scales.

00:03:45.398 --> 00:03:49.148
So at the most basic
scale is the individual.

00:03:50.348 --> 00:03:51.968
So let me write this down,

00:03:51.968 --> 00:03:54.781
you have the individual.

00:03:54.781 --> 00:03:57.212
So if we were talking
about these elephants,

00:03:57.212 --> 00:04:01.082
the individual would be
one individual elephant

00:04:01.082 --> 00:04:02.634
right over there.

00:04:02.634 --> 00:04:05.717
Now the next scale is the population,

00:04:08.576 --> 00:04:11.109
the next scale is the population,

00:04:11.109 --> 00:04:13.995
and if we were to stick with
our African savanna theme

00:04:13.995 --> 00:04:16.581
right over here, the population,
you have an individual

00:04:16.581 --> 00:04:19.889
elephant, the population
would be the members

00:04:19.889 --> 00:04:22.994
of that same species
that live in that area.

00:04:22.994 --> 00:04:25.717
So in this case the population would be,

00:04:25.717 --> 00:04:28.034
would at least include
these elephants that we see

00:04:28.034 --> 00:04:30.127
in this picture, there might
be a couple of elephants

00:04:30.127 --> 00:04:32.062
that are off the picture,

00:04:32.062 --> 00:04:33.683
and I should say in
particular these are going to

00:04:33.683 --> 00:04:35.032
be the African elephants.

00:04:35.032 --> 00:04:36.519
So it's the members of the same species

00:04:36.519 --> 00:04:39.490
that are living in the same place.

00:04:39.490 --> 00:04:42.097
And it's up for the classifier,

00:04:42.097 --> 00:04:43.178
or the scientist,

00:04:43.178 --> 00:04:44.370
whoever is studying it to define

00:04:44.370 --> 00:04:46.823
what do we mean by
living in the same place?

00:04:46.823 --> 00:04:49.005
We might define it as the people,

00:04:49.005 --> 00:04:51.436
you know, the people
(laughs), the elephants

00:04:51.436 --> 00:04:55.261
that live within a few
miles of this watering hole.

00:04:55.261 --> 00:04:57.871
You might define it as
the elephants that live

00:04:57.871 --> 00:05:00.213
within a broader area,
it could be you know,

00:05:00.213 --> 00:05:02.956
that live in East Africa, or South Africa,

00:05:02.956 --> 00:05:04.329
whatever it might be.

00:05:04.329 --> 00:05:06.264
And so defining the population is

00:05:06.264 --> 00:05:08.739
all the members of a species
that live in an area,

00:05:08.739 --> 00:05:12.249
but that area is up for definition.

00:05:12.249 --> 00:05:15.064
Now the next level up is the community,

00:05:15.064 --> 00:05:16.481
is the community.

00:05:18.100 --> 00:05:21.520
And that is all the living things that

00:05:21.520 --> 00:05:24.873
might live in that area
however we define the area.

00:05:24.873 --> 00:05:28.068
So for example, if this
lion and this giraffe

00:05:28.068 --> 00:05:31.600
lives in the area that we
used to define the population

00:05:31.600 --> 00:05:35.121
they would be members of the community.

00:05:35.121 --> 00:05:36.806
Let me circle that,

00:05:36.806 --> 00:05:39.464
so they would be members of the community.

00:05:39.464 --> 00:05:41.600
And it wouldn't even
just be the big animals

00:05:41.600 --> 00:05:43.984
that you see here, it
would include all the life

00:05:43.984 --> 00:05:46.010
that is in that area.

00:05:46.010 --> 00:05:49.835
So it would include the
vegetation that is in the area,

00:05:49.835 --> 00:05:52.625
it would include the bacteria,
it would include the fungus,

00:05:52.625 --> 00:05:54.492
it would include any animals that

00:05:54.492 --> 00:05:57.440
are living inside of this
water that you would see there.

00:05:57.440 --> 00:06:01.468
Now if you go even one more
level of kind of inclusion,

00:06:01.468 --> 00:06:03.801
then we go to the ecosystem.

00:06:04.979 --> 00:06:07.138
So then we go, I'll go down here,

00:06:07.138 --> 00:06:08.892
then you go to an ecosystem.

00:06:08.892 --> 00:06:11.502
And what an ecosystem is,

00:06:11.502 --> 00:06:13.752
it's all of the living
things in that community,

00:06:13.752 --> 00:06:16.115
so all of the living things in an area,

00:06:16.115 --> 00:06:18.590
and then you're also adding
the non-living things,

00:06:18.590 --> 00:06:20.593
the abiotic factors.

00:06:20.593 --> 00:06:22.164
So you're including the rock,

00:06:22.164 --> 00:06:25.022
and the air, and the
weather, and the clouds,

00:06:25.022 --> 00:06:28.555
and the water itself that is
part of that watering hole.

00:06:28.555 --> 00:06:30.557
And a lot of times you
might think that the

00:06:30.557 --> 00:06:34.247
abiotic factors well they for sure affect,

00:06:34.247 --> 00:06:37.580
they for sure affect the biotic factors.

00:06:38.928 --> 00:06:40.795
If you don't have water,
or if the temperature

00:06:40.795 --> 00:06:43.405
is too cold or too hot
it might be hard for a

00:06:43.405 --> 00:06:46.308
certain type of life to thrive,

00:06:46.308 --> 00:06:47.658
but it goes both ways.

00:06:47.658 --> 00:06:50.741
The biotic factors affect
the abiotic factors.

00:06:50.741 --> 00:06:54.521
We have oxygen in our
environment due to life on Earth.

00:06:54.521 --> 00:06:57.491
They might also affect the various,

00:06:57.491 --> 00:07:01.706
the chemical composition of
certain parts of the abiotic

00:07:01.706 --> 00:07:05.967
factors, say the water, or
the soil, or whatever else.

00:07:05.967 --> 00:07:08.993
And if you want to get a
level above an ecosystem,

00:07:08.993 --> 00:07:12.908
then sometimes you'll hear
people talk about a biosphere.

00:07:12.908 --> 00:07:16.241
Biosphere, which is, you can think of it

00:07:17.543 --> 00:07:20.603
as a meta-ecosystem, or
oftentimes in my head

00:07:20.603 --> 00:07:24.518
I view it as a fully, it
contains all of the ecosystems

00:07:24.518 --> 00:07:26.701
that are in some way
connected to each other.

00:07:26.701 --> 00:07:30.444
So a fully enclosed,
fully contained ecosystem.

00:07:30.444 --> 00:07:31.816
And biospheres are actually,

00:07:31.816 --> 00:07:35.484
well I guess the most
famous biosphere (laughs)

00:07:35.484 --> 00:07:38.432
or the one that we're
typically referring to

00:07:38.432 --> 00:07:40.682
is we could refer to the
whole Earth as a biosphere.

00:07:40.682 --> 00:07:42.148
It has multiple ecosystems,

00:07:42.148 --> 00:07:44.283
and once again,
ecosystems, it depends what

00:07:44.283 --> 00:07:46.060
the researcher wants to
define as an ecosystem.

00:07:46.060 --> 00:07:48.400
They could define it as you know,

00:07:48.400 --> 00:07:52.180
just something around a certain
river in a certain area,

00:07:52.180 --> 00:07:54.475
just like that, or they might define the

00:07:54.475 --> 00:07:56.321
ecosystem as a broader region.

00:07:56.321 --> 00:07:58.615
But all of the ecosystems in the world

00:07:58.615 --> 00:08:01.902
are part of the biosphere that we know as

00:08:01.902 --> 00:08:03.735
that is part of Earth.

00:08:04.714 --> 00:08:07.301
And it's self-contained
because we don't think

00:08:07.301 --> 00:08:08.786
that there are that many influences

00:08:08.786 --> 00:08:10.136
from outside of the earth.

00:08:10.136 --> 00:08:12.882
Although, even there, we
have to give some credit to

00:08:12.882 --> 00:08:16.369
the Sun that is providing
abiotic factors for sure.

00:08:16.369 --> 00:08:18.147
We wouldn't have life
on Earth as we know it

00:08:18.147 --> 00:08:19.521
without the Sun.

00:08:19.521 --> 00:08:21.213
And there's also things like the Moon

00:08:21.213 --> 00:08:22.355
the gravitational effect,

00:08:22.355 --> 00:08:24.245
you could consider that an abiotic factor,

00:08:24.245 --> 00:08:26.517
without the tides we would
not have life as we know it.

00:08:26.517 --> 00:08:27.912
But one thing that's really fun,

00:08:27.912 --> 00:08:30.434
and as many of you all know
I enjoy science fiction,

00:08:30.434 --> 00:08:32.593
is to think about well
what kind of biospheres

00:08:32.593 --> 00:08:35.158
could you have if you think
about beyond the Earth?

00:08:35.158 --> 00:08:36.511
And this is a depiction here,

00:08:36.511 --> 00:08:38.556
this is actually from NASA's website.

00:08:38.556 --> 00:08:42.316
How humans could create
biospheres outside of a planet,

00:08:42.316 --> 00:08:44.023
and it's this interesting thing where

00:08:44.023 --> 00:08:46.836
you know that's quote,
unquote land up here.

00:08:46.836 --> 00:08:49.155
Artificially created, and
then you would rotate it

00:08:49.155 --> 00:08:52.911
so that there's the perception of gravity.

00:08:52.911 --> 00:08:55.206
But anyway, the study of ecosystems,

00:08:55.206 --> 00:08:58.312
the study of biospheres, the
study of ecology in general

00:08:58.312 --> 00:09:00.405
is incredibly, incredibly fascinating

00:09:00.405 --> 00:09:02.744
because when you have
all of this complexity,

00:09:02.744 --> 00:09:05.692
each living thing is incredibly complex.

00:09:05.692 --> 00:09:06.862
In fact if you want,

00:09:06.862 --> 00:09:09.158
you could even sometimes
consider part of a living thing

00:09:09.158 --> 00:09:11.115
as an ecosystem in and of itself.

00:09:11.115 --> 00:09:12.803
If you were to look even on
the surface of your hand,

00:09:12.803 --> 00:09:14.717
you have bacteria living
there that's dependent

00:09:14.717 --> 00:09:16.470
on you in some way, and
you might actually benefit

00:09:16.470 --> 00:09:18.293
from the bacteria, or actually get hurt

00:09:18.293 --> 00:09:20.408
from the bacteria in some way.

00:09:20.408 --> 00:09:21.938
So there's all sorts of different scales,

00:09:21.938 --> 00:09:24.661
but once you start factoring
everything in together

00:09:24.661 --> 00:09:26.529
it becomes these incredibly
beautiful, complex,

00:09:26.529 --> 00:09:28.728
often balanced, sometimes
imbalanced systems

00:09:28.728 --> 00:09:32.095
that have emergent
properties that start to,

00:09:32.095 --> 00:09:34.428
that start to have behaviors

00:09:37.251 --> 00:09:39.504
and I want to use that word very loosely

00:09:39.504 --> 00:09:42.195
that are somehow described,

00:09:42.195 --> 00:09:43.631
or I guess you could say properties

00:09:43.631 --> 00:09:47.631
that somehow describe
the ecosystem as a whole.