Natural resources

WEBVTT
Kind: captions
Language: en

00:00:00.270 --> 00:00:02.970
- [Instructor] Humans are an
amazingly adaptable species.

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Not only can we survive almost anywhere,

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we also find ways to thrive

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even in the most
inhospitable environments.

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Our clever brains allow us
to look the world around us

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and figure out how to find food and water,

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build safe and comfortable shelters,

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and design useful tools.

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All of this is possible because
of the natural resources

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that surround us wherever we go.

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A natural resource is
anything found in nature

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that can be used by people.

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Natural resources can be renewable,

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meaning they can be replenished
over a human lifetime,

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or non-renewable,

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meaning they can take far
longer to be replaced.

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Both kinds of resources

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are unevenly distributed across Earth.

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This makes sense for
non-renewable resources, right?

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These resources are formed
by geologic processes,

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such as plate tectonics

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that take place in specific
locations on Earth.

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As a result, non-renewable
resources like soil,

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minerals, and fossil fuels

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are often concentrated in the places

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where they first formed.

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Let's take a look at one type
of non-renewable resource,

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metal ore.

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Metal ores are rocks that
contain valuable metals

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that people can extract,

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and they're often found
in large accumulations

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called deposits.

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For example, most copper ore

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is found in what are called
porphyry copper deposits.

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Porphyry just means that

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the rock that makes up these deposits

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contains a mix of large
and small crystals,

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like in this image here.

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Porphyry copper deposits
form in subduction zones

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along convergent tectonic
plate boundaries.

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Today, most subduction zones

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are found along Pacific coastlines,

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so you can expect to find

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a lot of porphyry copper
mines in these places.

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However, we also find
many of these ore deposits

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throughout Eurasia and Australia.

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Why? Turns out many of these places

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were subduction zones in the ancient past.

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The geologic processes that
form non-renewable resources

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are always happening,

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even if they occur over
thousands or millions of years.

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This means that non-renewable resources

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are not always found
where they first formed.

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Porphyry copper deposits follow
the same, slow life cycle

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as many other metal ores,

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forming in magma chambers below the crust,

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then uplifting towards the surface

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through tectonic activity.

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Once exposed to the elements,

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the deposits can experience
weathering and erosion,

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which allows them to gradually
recycle back into the earth,

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unless people find and mine them first.

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How can renewable natural resources

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be unevenly distributed
across Earth though?

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Doesn't everywhere have
things like sunlight and wind?

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Well, yes, but Earth's
tilt means that some places

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experience more direct sunlight

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throughout the year than others.

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And geography and other factors

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mean that some places
are windier than others.

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For example,

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take a look at this map of
average annual wind speeds

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across the contiguous United States.

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These purple, red, and orange places

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typically experience higher wind speeds,

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while these green and yellow places

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typically experience lower wind speeds.

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As a result, this central
part of the country here

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has a much higher capacity
for producing wind energy,

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so more people have invested in

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wind turbine technologies in these places.

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We can see that in this second map,

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which shows the distribution

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of wind power plants across the same area.

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Notice how most of the
country's wind power plants

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are concentrated around the places

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where people recorded
the highest wind speeds.

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The distribution of
certain natural resources

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can also be impacted by human activities.

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After all, we typically need to harvest

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and move natural resources to use them.

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Think about fossil
fuels, like coal and oil.

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Humans extract these raw
materials from Earth's crust

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using mining or drilling wells

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and then transport them all over the world

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to refine into usable products.

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Once fossil fuels are
removed from the ground,

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it can take millions of years
for Earth to replace them.

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So every time we use these
non-renewable resources,

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we have less available for future use.

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People can seek out new deposits,

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but they run the risk of
finding lower-quality materials

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or sites that are more challenging

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to extract resources from.

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Even renewable resources can
be affected by human actions.

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Take fresh water, for example.

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People may redistribute
fresh water on the surface

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by building dams across
rivers or other waterways.

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Dams store water for communities to use,

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and some even act as renewable
hydropower generators,

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converting the kinetic energy

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of running water into electricity.

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However, by changing the
natural flow of the water,

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dams can reduce the amount of water

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available to communities and
ecosystems further downstream.

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People may also redistribute freshwater

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by pumping it up from underground.

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Groundwater can consistently
provide freshwater

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in places where other sources are scarce,

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but if communities draw
that groundwater up

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faster than the water
cycle can replenish it,

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it can dry up.

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Naturally, unequal
distribution of resources

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already makes life
difficult for some places.

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And without careful management,

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human activities can make
these disparities even worse.

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However, if we work together
to avoid overexploiting

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the resources our planet
naturally provides,

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whether they can renew themselves or not,

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we can all continue to thrive
no matter where we live.


Student navigation

WEBVTT
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Language: en

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- Hi, I'm Stacy with Khan Academy.

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And today I'm going to
show you how students

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will navigate our new mastery view

00:00:07.470 --> 00:00:09.750
within the learning platform.

00:00:09.750 --> 00:00:11.850
Students will no longer need to navigate

00:00:11.850 --> 00:00:15.120
to a course homepage, or
to their learner homepage,

00:00:15.120 --> 00:00:18.750
in order to find the work that
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Navigation is now very easy to
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00:00:22.620 --> 00:00:26.193
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00:00:27.180 --> 00:00:29.610
When students are working
within Khan Academy

00:00:29.610 --> 00:00:32.460
their screen will look just like this one.

00:00:32.460 --> 00:00:35.940
This left side menu opens by default,

00:00:35.940 --> 00:00:39.210
but if students prefer a
focused content experience

00:00:39.210 --> 00:00:40.770
they can hide this menu

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Whenever students are ready
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00:00:47.670 --> 00:00:50.793
back up by once again,
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Notice that there is now a menu

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at the top of the left side
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The assignments in this menu
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regardless of whether or not
the student has completed them,

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so students are always
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that is due.

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Notice that in my list, my
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by due date.

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On the left navigation menu,
all experiences are listed

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in chronological order as students work

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This is especially helpful
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00:01:29.010 --> 00:01:31.320
for content to support exercises

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Notice that this exercise
is preceded by an article,

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and two instructional videos.

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That communicates to the
student that those videos,

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and that article inform the content

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with which they will be
practicing during this exercise.

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If students have been given an instruction

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by their teacher to focus
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which they can easily identify by looking

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to navigate to lessons
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If I click to the left, I'll
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and I can see the
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I'll move to future lessons where I'm also

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able to identify content that
I still need to complete.

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In this view, mastery levels are easy

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for students to identify by looking

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Students can use these bars
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as they work toward full mastery

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of each skill within the course.

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Notice that if a student is
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00:02:48.390 --> 00:02:51.900
and their course mastery goal
does not match the course

00:02:51.900 --> 00:02:54.960
with which their assignments
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00:02:54.960 --> 00:02:57.780
the students will see different titles.

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In this case, my course
mastery goal is set

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to get ready for eighth grade.

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So as I navigate that content, I'm looking

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at content from the Get Ready
for eighth grade course.

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My assignments that were given
by my teacher are being given

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from the full eighth
grade math class content.

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So if I'm choosing to work on
my self-paced learning journey

00:03:21.990 --> 00:03:26.190
through Course Mastery,
as I complete exercises

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I'm going to want to click
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This up next button is going to take me

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to the next exercise video, or article

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within this course mastery view.

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However, if I click on the blue button

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titled next assignment,
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to the next assignment that's
available from my teacher.

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We hope that you enjoy the
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00:03:51.690 --> 00:03:55.200
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as you continue to work
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Sewage treatment

WEBVTT
Kind: captions
Language: en

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- [Narrator] This is my cat, Rubiks.

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One of the many amazing
things about Rubiks is

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that he naturally works
to keep himself clean.

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His barbed tongue is really good

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at getting rid of the dust and dirt

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that he gets in his fur every day,

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but sometimes he needs a
little help getting clean.

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Healthy lakes and rivers
are kind of like cats.

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They naturally clean themselves.

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They have lots of spaces

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where contaminants from water can settle

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and to be filtered out by the soil

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and organisms like plants.

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The clean water produced by these systems

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is important for
irrigation, drinking water,

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and the ecosystem.

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But when humans add sewage

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and storm water pollution
into rivers too quickly

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natural ponds and streams can't keep up.

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The pollution can then build up

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and become a danger to
wildlife and people.

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To prevent this from happening

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many urban areas in developed countries

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use water management systems
to treat their water waste.

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Let's say I'm giving
Rubiks a bath one day,

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when I unplug the drain

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where will the water go?

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First, it will travel through
a long network of sewer pipes

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where it will be joined by water waste

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from homes and businesses

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and maybe some storm water

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from catch basins along roads.

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Eventually, it will reach
the water treatment plant

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where it'll go under
primary sewage treatment.

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Primary sewage treatment,

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which is also called
physical sewage treatment

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is where the treatment
plant physically takes out

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large objects from the water.

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This prevents the objects
from clocking up the pipes

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and pumps in future treatment steps.

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During primary treatment,

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the water goes through a series of screens

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with progressively smaller
and smaller openings.

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The screens sift out objects
like sticks, rocks, rags,

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plastic bottles, and Rubik's hair.

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Even though the screens take
out many of the larger objects

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there's still a lot of grit
in the water afterwards.

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Grit is made up of small loose
particles of sand, gravel,

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coffee grounds, food waste,

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and other pieces of material.

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To get rid of the grit,

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the treatment plant pumps the water

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through long narrow tanks

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that slow down the flow enough

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that the grit has time
to settle to the bottom.

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All that thick soft mud

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that gathers at the
bottom of the grit tank

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is called sludge,

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and it's collected and treated.

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The water then moves on to secondary

00:02:07.290 --> 00:02:09.420
or biological treatment.

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During this stage, the
wastewater is aerated

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or mixed with air

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to create perfect conditions

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to help increase the
population of aerobic bacteria.

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Aerobic bacteria are important

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because they quickly
feed on and break down

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the organic waste in the water.

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Sometimes bacteria loaded
sludge called activated sludge

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is also added to help
grow even more bacteria.

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When the bacteria have plenty of oxygen

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they metabolize the organic
material into carbon dioxide

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and yes, more sludge.

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The sludge, again, settles
to the bottom of the tank

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and is collected for treatment.

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I like to think of secondary treatment

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as kind of like being a good caretaker

00:02:45.030 --> 00:02:47.100
to millions of microbial pets

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when we provide our microscopic
pets with oxygen and food

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then they help us out by
doing the cleaning work.

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That's why secondary treatment

00:02:54.000 --> 00:02:55.980
is also called biological treatment

00:02:55.980 --> 00:02:58.230
because it uses living organisms.

00:02:58.230 --> 00:02:59.640
Like primary treatment,

00:02:59.640 --> 00:03:02.250
secondary treatment
generates lots of sludge.

00:03:02.250 --> 00:03:04.050
Some of the sludge may be recycled

00:03:04.050 --> 00:03:06.690
and added to water entering
secondary treatment.

00:03:06.690 --> 00:03:08.100
This increases the population

00:03:08.100 --> 00:03:10.080
of aerobic bacteria in the wastewater

00:03:10.080 --> 00:03:12.900
so the bacteria remove
the organic waste faster.

00:03:12.900 --> 00:03:15.390
The sludge collected from
primary and secondary treatment

00:03:15.390 --> 00:03:18.120
can be dried and buried
as a waste product,

00:03:18.120 --> 00:03:19.710
or dehydrated and heated

00:03:19.710 --> 00:03:22.620
to make a soil like
material called biosolids

00:03:22.620 --> 00:03:24.600
that can be used in agriculture.

00:03:24.600 --> 00:03:25.860
By the time the primary

00:03:25.860 --> 00:03:28.140
and secondary treatment
steps are completed

00:03:28.140 --> 00:03:31.170
about 85% of the organic
pollution has been removed

00:03:31.170 --> 00:03:32.370
from the wastewater,

00:03:32.370 --> 00:03:34.650
but there are still some
disease causing bacteria

00:03:34.650 --> 00:03:36.960
and viruses that are present in the water.

00:03:36.960 --> 00:03:39.060
So most treatment plants add another step

00:03:39.060 --> 00:03:41.220
to secondary treatment, disinfection.

00:03:41.220 --> 00:03:42.300
Some treatment plants

00:03:42.300 --> 00:03:44.310
may use ultraviolet light treatment

00:03:44.310 --> 00:03:45.960
to prevent disease carrying bacteria

00:03:45.960 --> 00:03:47.490
from being able to multiply

00:03:47.490 --> 00:03:49.350
or treatment may use chlorine

00:03:49.350 --> 00:03:50.820
or ozone treatment processes

00:03:50.820 --> 00:03:53.220
to kill bacteria and viruses.

00:03:53.220 --> 00:03:55.440
Chlorination will kill more than 99%

00:03:55.440 --> 00:03:57.210
of the harmful bacteria.

00:03:57.210 --> 00:04:00.000
In some places, the wastewater
treatment plant directly

00:04:00.000 --> 00:04:02.910
releases cleaned water into
drinking water sources,

00:04:02.910 --> 00:04:04.620
agricultural water sources,

00:04:04.620 --> 00:04:06.660
or recreational water bodies.

00:04:06.660 --> 00:04:07.560
In these cases,

00:04:07.560 --> 00:04:10.050
the water may go through yet
another treatment process

00:04:10.050 --> 00:04:13.800
called tertiary treatment
or advanced treatment.

00:04:13.800 --> 00:04:15.540
Tertiary treatment looks different

00:04:15.540 --> 00:04:17.520
at different water treatment plants.

00:04:17.520 --> 00:04:19.770
Sometimes it uses a more targeted approach

00:04:19.770 --> 00:04:22.440
to the removal of specific
wastewater components.

00:04:22.440 --> 00:04:25.410
Some examples include
additional biological treatments

00:04:25.410 --> 00:04:28.050
capable of removing
nitrogen and phosphorus

00:04:28.050 --> 00:04:30.450
or physical chemical separation techniques

00:04:30.450 --> 00:04:34.470
such as filtration, carbon
absorption, distillation,

00:04:34.470 --> 00:04:38.160
and reverse osmosis for
removing a variety of chemicals.

00:04:38.160 --> 00:04:39.750
Despite being effective,

00:04:39.750 --> 00:04:43.590
these techniques are
expensive and not widely used.

00:04:43.590 --> 00:04:45.690
After treatment, the newly cleaned water

00:04:45.690 --> 00:04:47.250
will go out into the world,

00:04:47.250 --> 00:04:49.650
perhaps to an ocean or to a river

00:04:49.650 --> 00:04:52.293
or maybe even into Rubik's next bath.


Evidence of evolution: embryology

WEBVTT
Kind: captions
Language: en

00:00:00.360 --> 00:00:02.760
- Do you ever wish that you had a tail?

00:00:02.760 --> 00:00:04.470
You could swing your way to school,

00:00:04.470 --> 00:00:06.390
bake pies more efficiently,

00:00:06.390 --> 00:00:09.570
and carry an umbrella while
keeping your hands free.

00:00:09.570 --> 00:00:12.420
The funny thing is, you
did have a tail once,

00:00:12.420 --> 00:00:13.890
before you were born.

00:00:13.890 --> 00:00:16.290
Back then, you were an embryo.

00:00:16.290 --> 00:00:19.050
An embryo is an organism that
is in the earliest stages

00:00:19.050 --> 00:00:22.320
of development before
it is born or hatched.

00:00:22.320 --> 00:00:24.630
Early on in the growth of a human embryo,

00:00:24.630 --> 00:00:27.090
the embryo has a tail-like structure.

00:00:27.090 --> 00:00:29.730
As time goes on, the embryo grows,

00:00:29.730 --> 00:00:32.820
and eventually the cells that
made up that tail structure

00:00:32.820 --> 00:00:35.310
shift and form the tailbone,

00:00:35.310 --> 00:00:37.530
which makes up the bottom of the spine.

00:00:37.530 --> 00:00:40.050
By the time the embryo is eight weeks old,

00:00:40.050 --> 00:00:42.450
the tail is not visible at all.

00:00:42.450 --> 00:00:46.170
Humans are not the only species
to have tails as embryos.

00:00:46.170 --> 00:00:47.100
We share this trait

00:00:47.100 --> 00:00:49.380
with the embryos of
many other vertebrates,

00:00:49.380 --> 00:00:51.240
which are animals with a backbone,

00:00:51.240 --> 00:00:55.110
such as monkeys, mice,
turtles, and chickens.

00:00:55.110 --> 00:00:57.300
Scientists call features
such as embryo tails

00:00:57.300 --> 00:00:58.770
homologous features.

00:00:58.770 --> 00:01:01.050
Structurally similar
anatomical features that

00:01:01.050 --> 00:01:03.660
two species share that
indicate that the species

00:01:03.660 --> 00:01:05.220
share a common ancestor.

00:01:05.220 --> 00:01:07.650
Identifying homologous
features can help scientists

00:01:07.650 --> 00:01:10.380
figure out how different species
are related to each other

00:01:10.380 --> 00:01:12.090
and how they evolved.

00:01:12.090 --> 00:01:14.460
Studying embryos is a
helpful way for scientists

00:01:14.460 --> 00:01:16.740
to find similarities between species.

00:01:16.740 --> 00:01:18.570
Similarities that might not be visible

00:01:18.570 --> 00:01:21.330
once the animals are born and grow up.

00:01:21.330 --> 00:01:23.550
In general, embryos of
related species have

00:01:23.550 --> 00:01:25.170
more obvious homologous features

00:01:25.170 --> 00:01:27.330
at earlier stages of development,

00:01:27.330 --> 00:01:30.510
before the embryos anatomy
becomes highly specialized.

00:01:30.510 --> 00:01:32.940
During the stages of
an embryos development,

00:01:32.940 --> 00:01:35.910
the embryo goes through a
lot of physical changes.

00:01:35.910 --> 00:01:37.710
The embryo of an elephant
starts out weighing

00:01:37.710 --> 00:01:40.080
less than a gram and it eventually grows

00:01:40.080 --> 00:01:43.050
to its birth weight of
about 100 kilograms.

00:01:43.050 --> 00:01:45.180
Let's take a closer look
at the kinds of changes

00:01:45.180 --> 00:01:47.820
the elephant embryo goes
through as it develops.

00:01:47.820 --> 00:01:51.480
As an embryo grows, its
physical structures change.

00:01:51.480 --> 00:01:53.220
Some structures become visible,

00:01:53.220 --> 00:01:55.050
and others disappear.

00:01:55.050 --> 00:01:57.750
For example, towards the
beginning of development,

00:01:57.750 --> 00:01:59.760
an elephant embryo has structures called

00:01:59.760 --> 00:02:03.540
pharyngeal arches, or
gill arches, on its neck.

00:02:03.540 --> 00:02:07.560
As the embryo grows, the
pharyngeal arches change structure

00:02:07.560 --> 00:02:10.200
and help form the ears
and jaws of the elephant.

00:02:10.200 --> 00:02:12.300
And it turns out, all vertebrate embryos

00:02:12.300 --> 00:02:14.730
have pharyngeal arches
early in their development.

00:02:14.730 --> 00:02:18.180
In fish, these arches
develop into gill structures.

00:02:18.180 --> 00:02:21.090
In humans and other mammals,
these arches develop into

00:02:21.090 --> 00:02:24.450
ear and jaw structures, just
like they did in the elephant.

00:02:24.450 --> 00:02:27.090
Pharyngeal arches are homologous features,

00:02:27.090 --> 00:02:29.220
even though we can only
see this homologous feature

00:02:29.220 --> 00:02:31.230
early on in embryo development.

00:02:31.230 --> 00:02:33.450
Pharyngeal arches provide
evidence to scientists

00:02:33.450 --> 00:02:35.703
that all vertebrates
share a common ancestor.

00:02:36.540 --> 00:02:38.550
More distantly related
species tend to share

00:02:38.550 --> 00:02:41.340
fewer homologous features
during both embryo development

00:02:41.340 --> 00:02:42.210
and after birth.

00:02:42.210 --> 00:02:44.550
More closely related
species tend to share more

00:02:44.550 --> 00:02:46.740
homologous features during
both embryo development

00:02:46.740 --> 00:02:47.790
and after birth.

00:02:47.790 --> 00:02:51.150
So even though you don't have
a tail, as far as I know,

00:02:51.150 --> 00:02:53.580
studying homologous features in embryos,

00:02:53.580 --> 00:02:55.620
shows scientists that
humans are related to

00:02:55.620 --> 00:02:58.893
many tail-using creatures
because of evolution.


Evolution

WEBVTT
Kind: captions
Language: en

00:00:00.720 --> 00:00:02.280
- [Speaker] How many different species

00:00:02.280 --> 00:00:04.410
or kinds of birds are there?

00:00:04.410 --> 00:00:05.700
Take a guess.

00:00:05.700 --> 00:00:08.790
100, 1,000, more?

00:00:08.790 --> 00:00:10.830
Well, biologists have estimated

00:00:10.830 --> 00:00:14.460
that there are at least 10,000
different species of birds

00:00:14.460 --> 00:00:17.250
all around the world,
and some biologists think

00:00:17.250 --> 00:00:21.630
that there are even more, up
to 18,000 different species.

00:00:21.630 --> 00:00:24.000
Birds are incredibly diverse.

00:00:24.000 --> 00:00:27.060
Think about the differences
between an eagle, a parrot,

00:00:27.060 --> 00:00:30.090
a hummingbird, a duck, and a penguin.

00:00:30.090 --> 00:00:33.180
Some of them are small and some are big,

00:00:33.180 --> 00:00:34.470
and take a look at the differences

00:00:34.470 --> 00:00:37.470
in their beaks or bills
and their feathers.

00:00:37.470 --> 00:00:40.050
And not all of these
birds can fly, either.

00:00:40.050 --> 00:00:43.293
Penguins use their wings like
flippers to swim underwater.

00:00:44.550 --> 00:00:48.210
Collectively, these 10,000
plus different species of birds

00:00:48.210 --> 00:00:50.100
are a product of evolution,

00:00:50.100 --> 00:00:52.230
which is the change in heritable traits

00:00:52.230 --> 00:00:56.193
that occurs in a group of
organisms over many generations.

00:00:57.810 --> 00:01:01.230
But what are these
heritable traits exactly?

00:01:01.230 --> 00:01:03.570
Heritable traits are those that are passed

00:01:03.570 --> 00:01:05.940
from parents to offspring via genes,

00:01:05.940 --> 00:01:07.320
and they include things like

00:01:07.320 --> 00:01:09.150
the colorful patterns and plumage

00:01:09.150 --> 00:01:12.540
or the webbing or toes
and claws of bird feet.

00:01:12.540 --> 00:01:15.570
And even though offspring
inherit traits from their parents

00:01:15.570 --> 00:01:17.880
and look pretty similar to them,

00:01:17.880 --> 00:01:20.010
over many, many generations,

00:01:20.010 --> 00:01:22.473
these heritable traits can change.

00:01:23.400 --> 00:01:26.460
Evolution is made possible
by genetic variation

00:01:26.460 --> 00:01:29.670
or differences in genes
within a population.

00:01:29.670 --> 00:01:32.010
Genes are passed from parents to offspring

00:01:32.010 --> 00:01:35.490
and they affect how an organism
develops, how it functions,

00:01:35.490 --> 00:01:37.410
and even how it looks.

00:01:37.410 --> 00:01:40.650
Genes can come in
different forms or alleles,

00:01:40.650 --> 00:01:43.380
which can lead to different
versions of a trait.

00:01:43.380 --> 00:01:46.980
For example, in city pigeons,
also called rock doves,

00:01:46.980 --> 00:01:48.930
which you might see flying around,

00:01:48.930 --> 00:01:51.240
different alleles cause
different eye colors

00:01:51.240 --> 00:01:54.090
such as orange, black, and white.

00:01:54.090 --> 00:01:57.000
Genetic variation causes
organisms within a population

00:01:57.000 --> 00:01:58.560
to have a range of traits

00:01:58.560 --> 00:02:01.620
like differences in plumage or eye color.

00:02:01.620 --> 00:02:05.160
Genetic variation can come
from lots of different sources,

00:02:05.160 --> 00:02:08.250
one of which is through
sexual reproduction.

00:02:08.250 --> 00:02:10.710
This type of reproduction causes offspring

00:02:10.710 --> 00:02:14.010
to have different sets of
traits compared to their parents

00:02:14.010 --> 00:02:15.900
because they receive genetic material

00:02:15.900 --> 00:02:17.910
from both of their parents.

00:02:17.910 --> 00:02:19.470
In other words, the offspring

00:02:19.470 --> 00:02:23.010
aren't an exact genetic
copy of either parent.

00:02:23.010 --> 00:02:25.020
In this example of rock doves,

00:02:25.020 --> 00:02:28.590
parents carry different alleles
that affect their plumage,

00:02:28.590 --> 00:02:31.620
and, in turn, their offspring can inherit

00:02:31.620 --> 00:02:32.970
different sets of traits

00:02:32.970 --> 00:02:36.450
and may look quite different
from their parents.

00:02:36.450 --> 00:02:38.700
Now, let's take a look
at that dove example

00:02:38.700 --> 00:02:40.200
with the plumage differences

00:02:40.200 --> 00:02:42.570
and think about it at the population level

00:02:42.570 --> 00:02:44.760
with lots of doves.

00:02:44.760 --> 00:02:46.980
You could imagine that
those plumage traits

00:02:46.980 --> 00:02:49.770
can change over many, many generations

00:02:49.770 --> 00:02:53.250
of parents and offspring
in a large population.

00:02:53.250 --> 00:02:54.900
You might see new traits appear

00:02:54.900 --> 00:02:58.500
like different colors or
different patterns and feathers,

00:02:58.500 --> 00:03:01.230
or existing traits like dark colors

00:03:01.230 --> 00:03:03.960
may become more or less common.

00:03:03.960 --> 00:03:05.850
When this type of change occurs

00:03:05.850 --> 00:03:08.910
or any change in heritable traits,

00:03:08.910 --> 00:03:11.493
that group of organisms has evolved.

00:03:12.750 --> 00:03:16.260
Over many generations,
small differences in traits

00:03:16.260 --> 00:03:20.340
between generations can
add up, and over time,

00:03:20.340 --> 00:03:23.310
over thousands to millions of years,

00:03:23.310 --> 00:03:27.210
evolution can give rise
to new types of organisms.

00:03:27.210 --> 00:03:29.640
For example, over many generations,

00:03:29.640 --> 00:03:33.060
one population can evolve
into two different species,

00:03:33.060 --> 00:03:35.610
like the rock dove and the hill pigeon.

00:03:35.610 --> 00:03:37.410
Even though these two types of birds

00:03:37.410 --> 00:03:39.600
look pretty similar to one another,

00:03:39.600 --> 00:03:41.100
they are a distinct species

00:03:41.100 --> 00:03:44.340
that have been changing along
independent evolutionary paths

00:03:44.340 --> 00:03:46.383
for about a million years.

00:03:47.610 --> 00:03:51.600
Over the billions of years
that life has existed on Earth,

00:03:51.600 --> 00:03:54.420
evolution has given rise
to the amazing diversity

00:03:54.420 --> 00:03:56.790
of organisms on our planet.

00:03:56.790 --> 00:04:00.780
We have over 10,000 species
of birds alive today,

00:04:00.780 --> 00:04:02.430
and there are even more

00:04:02.430 --> 00:04:05.760
bird ancestors species that once existed.

00:04:05.760 --> 00:04:08.730
Ancestors that were literally dinosaurs,

00:04:08.730 --> 00:04:11.283
but, that's a topic for another video.


Human impacts on the environment

WEBVTT
Kind: captions
Language: en

00:00:00.270 --> 00:00:01.770
- [Narrator] Everything
we do has an impact

00:00:01.770 --> 00:00:03.300
on the world around us.

00:00:03.300 --> 00:00:06.120
That can be a good thing, or a bad one.

00:00:06.120 --> 00:00:09.240
For most of us, that impact
can seem pretty small.

00:00:09.240 --> 00:00:11.070
If you throw an empty can on the ground

00:00:11.070 --> 00:00:12.840
instead of in the recycling bin,

00:00:12.840 --> 00:00:15.120
your local park will
still be pretty clean.

00:00:15.120 --> 00:00:16.980
Those actions can add up though.

00:00:16.980 --> 00:00:18.360
What if everyone you know decides

00:00:18.360 --> 00:00:20.940
to start throwing their
trash on the ground too?

00:00:20.940 --> 00:00:22.530
Or a nearby factory decides

00:00:22.530 --> 00:00:24.810
to dump all of their trash there?

00:00:24.810 --> 00:00:28.020
As the human population of
Earth grows, we tend to consume

00:00:28.020 --> 00:00:31.650
and throw away more and
more natural resources.

00:00:31.650 --> 00:00:34.290
This trash bile is a simple
example of pollution,

00:00:34.290 --> 00:00:36.540
which can also refer to toxic particles

00:00:36.540 --> 00:00:38.460
in our air or waterways.

00:00:38.460 --> 00:00:39.960
Human activities are also contributing

00:00:39.960 --> 00:00:41.550
to more complex problems,

00:00:41.550 --> 00:00:43.980
like overfishing or deforestation,

00:00:43.980 --> 00:00:45.780
which can drive wildlife to extinction

00:00:45.780 --> 00:00:47.370
and disrupt the natural processes

00:00:47.370 --> 00:00:49.710
that keep our planet running smoothly.

00:00:49.710 --> 00:00:51.240
Let's take a look at a real place

00:00:51.240 --> 00:00:54.360
that's facing some of these
complex environmental problems.

00:00:54.360 --> 00:00:56.370
This is Lake Urmia in Iran,

00:00:56.370 --> 00:00:58.170
once the largest lake in the Middle East

00:00:58.170 --> 00:01:00.840
and the sixth largest
saltwater lake on Earth.

00:01:00.840 --> 00:01:02.520
The lake was a popular destination

00:01:02.520 --> 00:01:05.460
for people who wanted to visit
its uniquely salty shores,

00:01:05.460 --> 00:01:06.990
as well as for migratory birds,

00:01:06.990 --> 00:01:08.430
like flamingos and pelicans,

00:01:08.430 --> 00:01:10.770
who had stopped to rest
during their long journeys.

00:01:10.770 --> 00:01:14.070
This satellite image of
Lake Urmia is from 1984.

00:01:14.070 --> 00:01:17.400
Now, compare it to another
image taken in 2018.

00:01:17.400 --> 00:01:20.520
In just a few decades, the
lake has shrunk dramatically.

00:01:20.520 --> 00:01:21.810
What happened?

00:01:21.810 --> 00:01:23.370
Well, around the 1980s,

00:01:23.370 --> 00:01:25.830
Iran needed to create new
jobs and sources of food

00:01:25.830 --> 00:01:27.570
for its growing population.

00:01:27.570 --> 00:01:29.790
More people began moving near Lake Urmia,

00:01:29.790 --> 00:01:31.800
converting large portions of the landscape

00:01:31.800 --> 00:01:33.450
into agricultural fields.

00:01:33.450 --> 00:01:35.280
They tried growing profitable new crops

00:01:35.280 --> 00:01:37.710
like apples, watermelon, and sugar beets,

00:01:37.710 --> 00:01:40.110
but many of these plants
require a lot more water

00:01:40.110 --> 00:01:42.240
than the dry climate could provide.

00:01:42.240 --> 00:01:44.550
So people built dams
across many of the rivers

00:01:44.550 --> 00:01:45.720
that float into the region

00:01:45.720 --> 00:01:47.970
so they could more easily
transport fresh water

00:01:47.970 --> 00:01:49.800
to their fields and communities.

00:01:49.800 --> 00:01:51.870
Iran has always experienced droughts,

00:01:51.870 --> 00:01:53.760
but with people using up so much water,

00:01:53.760 --> 00:01:56.670
the impact of these
droughts became much worse.

00:01:56.670 --> 00:01:58.530
Lake Urmia began to shrink.

00:01:58.530 --> 00:02:01.410
The remaining water became so
salty that many aquatic fish

00:02:01.410 --> 00:02:03.420
and other small critters couldn't survive,

00:02:03.420 --> 00:02:04.530
leaving migratory birds

00:02:04.530 --> 00:02:06.660
and other wildlife
without a source of food.

00:02:06.660 --> 00:02:08.820
Sandstorms blew salt from the dry lake bed

00:02:08.820 --> 00:02:10.230
over agricultural fields,

00:02:10.230 --> 00:02:11.670
making it even harder for people

00:02:11.670 --> 00:02:13.560
to grow food during droughts.

00:02:13.560 --> 00:02:15.210
Farmers were forced to move away,

00:02:15.210 --> 00:02:17.580
and many others from the
tourist towns followed

00:02:17.580 --> 00:02:19.710
since few wanted to visit a vanishing lake

00:02:19.710 --> 00:02:22.470
where people could get sick
from breathing the salty air.

00:02:22.470 --> 00:02:25.380
At one point, lake Imia lost nearly 90%

00:02:25.380 --> 00:02:26.640
of its historical volume,

00:02:26.640 --> 00:02:28.740
and many of its once thriving communities

00:02:28.740 --> 00:02:30.360
turned into ghost towns.

00:02:30.360 --> 00:02:32.730
There's no question that human activities,

00:02:32.730 --> 00:02:34.620
from unsustainable farming practices

00:02:34.620 --> 00:02:36.030
to diverting water flow,

00:02:36.030 --> 00:02:38.790
cause this environmental catastrophe.

00:02:38.790 --> 00:02:41.130
Human activities aren't
always negative though.

00:02:41.130 --> 00:02:43.230
We can work together
to design technologies

00:02:43.230 --> 00:02:46.170
that monitor and minimize
our harmful impacts.

00:02:46.170 --> 00:02:48.450
Since environmental problems
are often so complex,

00:02:48.450 --> 00:02:50.160
we need to consider a
lot of different things

00:02:50.160 --> 00:02:52.200
to create sustainable solutions.

00:02:52.200 --> 00:02:53.790
What does scientific research tell us

00:02:53.790 --> 00:02:55.920
about this place and how it's changing?

00:02:55.920 --> 00:02:57.120
What are the needs, desires,

00:02:57.120 --> 00:02:59.520
and values of the people
affected by this problem,

00:02:59.520 --> 00:03:02.160
both as individuals and as a society?

00:03:02.160 --> 00:03:03.420
Are there any constraints

00:03:03.420 --> 00:03:06.810
or challenges that could
prevent us from taking action?

00:03:06.810 --> 00:03:08.880
Despite economic and
political constraints,

00:03:08.880 --> 00:03:11.700
many Iranians support
efforts to save Lake Urmia,

00:03:11.700 --> 00:03:13.950
which has encouraged leaders
to provide more funding

00:03:13.950 --> 00:03:16.110
and other restoration resources.

00:03:16.110 --> 00:03:18.150
Key parts of the ecosystem
are now protected

00:03:18.150 --> 00:03:20.190
by reserves or national parks.

00:03:20.190 --> 00:03:22.380
Researchers have introduced
new farming practices

00:03:22.380 --> 00:03:23.213
to the region,

00:03:23.213 --> 00:03:25.440
such as planting less
thirsty pomegranate trees

00:03:25.440 --> 00:03:28.410
or watering crops at night
to prevent evaporation.

00:03:28.410 --> 00:03:30.150
This has allowed farmers to save water

00:03:30.150 --> 00:03:32.220
while still producing enough food.

00:03:32.220 --> 00:03:34.650
Finally, engineers have been
building new technologies

00:03:34.650 --> 00:03:37.680
that transfer water from
surrounding areas into the lake.

00:03:37.680 --> 00:03:39.180
Even with all of these changes,

00:03:39.180 --> 00:03:41.040
the problems plaguing Lake Urmia

00:03:41.040 --> 00:03:42.870
aren't completely fixed yet.

00:03:42.870 --> 00:03:44.760
Wildlife habitats still
need to be restored

00:03:44.760 --> 00:03:46.440
so aquatic species can survive

00:03:46.440 --> 00:03:49.530
and migratory birds can fuel
up for their long journeys.

00:03:49.530 --> 00:03:52.200
Water levels are still too
low to attract many tourists.

00:03:52.200 --> 00:03:53.760
And salt from the exposed lake bed

00:03:53.760 --> 00:03:54.990
can still harm people's health

00:03:54.990 --> 00:03:56.940
when kicked up during sandstorms.

00:03:56.940 --> 00:03:58.530
People are worried that transferring water

00:03:58.530 --> 00:04:00.210
into Lake Urmia from nearby regions

00:04:00.210 --> 00:04:03.120
may cause even more
widespread water shortages.

00:04:03.120 --> 00:04:05.070
Their needs and concerns
need to be addressed

00:04:05.070 --> 00:04:07.950
for decisions to work
properly in the long term.

00:04:07.950 --> 00:04:09.360
While there's still plenty left to do,

00:04:09.360 --> 00:04:11.730
these efforts, combined
with a few good rain years,

00:04:11.730 --> 00:04:13.260
have allowed Lake Urmia to return

00:04:13.260 --> 00:04:15.630
to about half of its historical size.

00:04:15.630 --> 00:04:18.270
Check out this Google
Earth image from 2022.

00:04:18.270 --> 00:04:19.860
It's not back to the way it was,

00:04:19.860 --> 00:04:21.900
but it's looking a bit better.

00:04:21.900 --> 00:04:23.910
Lake Urmia isn't the only lake on Earth

00:04:23.910 --> 00:04:26.010
that's under threat from human activities.

00:04:26.010 --> 00:04:28.380
For example, the Great Salt
Lake in the United States

00:04:28.380 --> 00:04:31.140
is also shrinking for
very similar reasons.

00:04:31.140 --> 00:04:33.180
Shared challenges can
provide opportunities

00:04:33.180 --> 00:04:34.890
for people to share solutions.

00:04:34.890 --> 00:04:36.540
People can learn from
what others are doing

00:04:36.540 --> 00:04:40.020
to fix similar problems or
even brainstorm new ideas.

00:04:40.020 --> 00:04:41.700
For example, researchers from Iran

00:04:41.700 --> 00:04:43.650
and the United States have
started working together

00:04:43.650 --> 00:04:45.180
to compare conservation activities

00:04:45.180 --> 00:04:46.590
on both of their salt lakes

00:04:46.590 --> 00:04:48.810
even though they're half a world apart.

00:04:48.810 --> 00:04:51.000
While human action often
has a negative impact

00:04:51.000 --> 00:04:51.833
on the planet,

00:04:51.833 --> 00:04:54.360
we have the power to
spark positive change too.

00:04:54.360 --> 00:04:56.580
If you feel like your
actions alone are too small

00:04:56.580 --> 00:04:58.350
to make a difference
against a big problem,

00:04:58.350 --> 00:04:59.640
whether it's a shrinking lake

00:04:59.640 --> 00:05:02.160
or a giant pile of garbage
in your neighborhood,

00:05:02.160 --> 00:05:04.440
there's usually a few
other concerned citizens

00:05:04.440 --> 00:05:06.640
that would be happy to
help find a solution.


Environmental change and adaptation in Galápagos finches

WEBVTT
Kind: captions
Language: en

00:00:00.000 --> 00:00:02.970
- This here is a picture
of the ground finch

00:00:02.970 --> 00:00:04.480
of the Galapagos Islands.

00:00:04.480 --> 00:00:06.339
And one of its primary sources of food

00:00:06.339 --> 00:00:09.950
is seeds that it finds on the ground.

00:00:09.950 --> 00:00:12.170
And if we go back to 1976,

00:00:12.170 --> 00:00:15.140
we can look at the
distribution of beak depths.

00:00:15.140 --> 00:00:16.370
And these beak depths,

00:00:16.370 --> 00:00:18.667
I would assume these are
given in millimeters.

00:00:18.667 --> 00:00:21.350
Finches are quite small birds.

00:00:21.350 --> 00:00:23.105
And you can see in 1976,

00:00:23.105 --> 00:00:25.160
you have a large number of finches

00:00:25.160 --> 00:00:27.400
that had a beak depth of 8.8 millimeters,

00:00:27.400 --> 00:00:29.900
but it was a distribution around that.

00:00:29.900 --> 00:00:31.510
Now, after this data was collected,

00:00:31.510 --> 00:00:35.350
it turns out there was a drought
and there were fewer seeds.

00:00:35.350 --> 00:00:36.680
So the smaller seeds,

00:00:36.680 --> 00:00:39.199
which were easy to eat
for all of these finches,

00:00:39.199 --> 00:00:40.860
would have been consumed quickly.

00:00:40.860 --> 00:00:43.910
And all that would have been
left were the larger seeds,

00:00:43.910 --> 00:00:46.010
the ones that you need a larger beak

00:00:46.010 --> 00:00:48.990
in order to crack and
get at the good stuff.

00:00:48.990 --> 00:00:50.780
So what do you think would have happened

00:00:50.780 --> 00:00:53.170
to the distribution of beak depths

00:00:53.170 --> 00:00:56.050
over the course of the next two years?

00:00:56.050 --> 00:00:58.690
Well, you might guess that the birds,

00:00:58.690 --> 00:01:01.330
the finches that have larger beak depths,

00:01:01.330 --> 00:01:04.020
are more likely to survive
because they're more likely

00:01:04.020 --> 00:01:06.140
to be able to crack the larger seeds.

00:01:06.140 --> 00:01:08.182
And the finches that are
more likely to survive

00:01:08.182 --> 00:01:10.670
are also more likely to reproduce,

00:01:10.670 --> 00:01:13.440
and pass their large beak
trait to their offspring.

00:01:13.440 --> 00:01:16.393
And that is indeed what
scientists observed.

00:01:16.393 --> 00:01:20.160
As we go from 1976 to 1978,

00:01:20.160 --> 00:01:24.090
the distribution has shifted a
pretty good bit to the right.

00:01:24.090 --> 00:01:28.800
Now the most common beak depth is 9.8.

00:01:28.800 --> 00:01:32.750
So this is an example of an
environmental change, a drought,

00:01:32.750 --> 00:01:34.900
changing the food supply,

00:01:34.900 --> 00:01:37.620
because now there's fewer
small seeds available,

00:01:37.620 --> 00:01:40.380
that changed a distribution in beak depths

00:01:40.380 --> 00:01:42.320
over just two years.

00:01:42.320 --> 00:01:45.530
Now, environmental changes
don't always cause adaptation.

00:01:45.530 --> 00:01:46.460
If it's too severe,

00:01:46.460 --> 00:01:48.851
if the drought was so strong
that there were no seeds,

00:01:48.851 --> 00:01:50.570
you could have extinction.

00:01:50.570 --> 00:01:52.980
So the species disappears altogether.

00:01:52.980 --> 00:01:55.780
But here we have an example
that in just two years,

00:01:55.780 --> 00:01:59.320
a species was actually able
to adapt a pretty good bit.

00:01:59.320 --> 00:02:01.570
Now, no individual member of the species

00:02:01.570 --> 00:02:04.159
knew to somehow grew their beak.

00:02:04.159 --> 00:02:08.310
But as we saw, you always have
a variation of beak depths.

00:02:08.310 --> 00:02:09.331
And year after year,

00:02:09.331 --> 00:02:11.960
the birds with the bigger beak depth,

00:02:11.960 --> 00:02:14.870
were more likely to survive and reproduce.

00:02:14.870 --> 00:02:16.510
So the species as a whole

00:02:16.510 --> 00:02:19.653
adapted to the new
environmental conditions.


Natural selection in peppered moths

WEBVTT
Kind: captions
Language: en

00:00:00.320 --> 00:00:01.440
- [Narrator] You might be familiar with

00:00:01.440 --> 00:00:04.940
the idea of evolution, that
species change over time.

00:00:04.940 --> 00:00:08.210
And you can see that if you
look at old bones, old fossils,

00:00:08.210 --> 00:00:10.920
how they change through the fossil record.

00:00:10.920 --> 00:00:12.170
But the obvious question is,

00:00:12.170 --> 00:00:14.730
how do these species actually do that?

00:00:14.730 --> 00:00:16.420
What is the mechanism?

00:00:16.420 --> 00:00:20.540
Well, one of the major
mechanisms is natural selection.

00:00:20.540 --> 00:00:23.030
So natural selection is all based on

00:00:23.030 --> 00:00:24.950
at any given point in time,

00:00:24.950 --> 00:00:27.070
there is variation in a species.

00:00:27.070 --> 00:00:28.690
There are different traits that are

00:00:28.690 --> 00:00:31.120
expressed in different ways.

00:00:31.120 --> 00:00:34.480
And many times, a lot of
those variations are fine,

00:00:34.480 --> 00:00:36.980
but then you can have
environmental factors

00:00:36.980 --> 00:00:40.290
which make some of those traits
more favorable than others.

00:00:40.290 --> 00:00:42.490
And if those traits are more favorable

00:00:42.490 --> 00:00:46.120
to be able to survive,
to be able to get food,

00:00:46.120 --> 00:00:47.880
or to be able to reproduce,

00:00:47.880 --> 00:00:50.500
well then the genes that
code for those traits

00:00:50.500 --> 00:00:54.600
are more likely to be passed
on generation after generation.

00:00:54.600 --> 00:00:57.000
And to make this very tangible,

00:00:57.000 --> 00:00:59.890
I will give you the example
of the peppered moth,

00:00:59.890 --> 00:01:02.070
which is probably the most common example

00:01:02.070 --> 00:01:05.140
when people show evidence
of natural selection.

00:01:05.140 --> 00:01:08.270
If you were to go to
the mid 1800s in London,

00:01:08.270 --> 00:01:12.680
most of the peppered moths
were the white peppered moths.

00:01:12.680 --> 00:01:14.670
There were very few black peppered moths,

00:01:14.670 --> 00:01:15.880
but there was variation.

00:01:15.880 --> 00:01:17.020
There would be some lighter ones,

00:01:17.020 --> 00:01:20.050
there would be some darker
ones, and in-between.

00:01:20.050 --> 00:01:21.820
Now what's interesting is between

00:01:21.820 --> 00:01:25.110
the mid 1800s and the late 1800s,

00:01:25.110 --> 00:01:27.670
you have the industrial
revolution in London

00:01:27.670 --> 00:01:29.320
really hitting full gear.

00:01:29.320 --> 00:01:31.720
And so there was a lot
of pollution in the air.

00:01:31.720 --> 00:01:34.590
And so a lot of the surfaces
that the moths might rest on

00:01:34.590 --> 00:01:36.840
like trees, or the wall of a building,

00:01:36.840 --> 00:01:40.430
became darker and darker.

00:01:40.430 --> 00:01:44.470
So as where these moths could
rest became darker and darker,

00:01:44.470 --> 00:01:46.370
what do you think might have happened?

00:01:47.400 --> 00:01:49.130
Well, some of you might guess.

00:01:49.130 --> 00:01:51.280
In this different environment now,

00:01:51.280 --> 00:01:53.460
as the environment has gradually changed,

00:01:53.460 --> 00:01:56.980
all of a sudden having the
traits that make you darker

00:01:56.980 --> 00:01:58.810
will be more favorable than they were

00:01:58.810 --> 00:02:01.530
even 30 or 40 or 50 years ago.

00:02:01.530 --> 00:02:04.590
And the white trait,
which might've been okay

00:02:04.590 --> 00:02:06.740
in the mid 1800s, now all of a sudden

00:02:06.740 --> 00:02:09.970
makes these moths very obvious to see.

00:02:09.970 --> 00:02:12.760
So if there was a bird
that was looking for lunch,

00:02:12.760 --> 00:02:14.890
it'd be very easy to
pick off the white moths

00:02:14.890 --> 00:02:16.340
versus the black moths.

00:02:16.340 --> 00:02:20.290
And what we saw is actually by the 1900s,

00:02:20.290 --> 00:02:22.330
most of the peppered moths in London

00:02:22.330 --> 00:02:24.460
were now darker in color.

00:02:24.460 --> 00:02:28.130
And so what you had happening
generation after generation

00:02:28.130 --> 00:02:31.040
is variation in the moth color.

00:02:31.040 --> 00:02:33.880
But as the background
environment became darker,

00:02:33.880 --> 00:02:35.330
the ones that were white colored

00:02:35.330 --> 00:02:37.730
were easier to pick off by predators.

00:02:37.730 --> 00:02:39.580
And if they're picked off by a predator,

00:02:39.580 --> 00:02:41.050
they're definitely not reproducing

00:02:41.050 --> 00:02:42.590
and passing on their genes.

00:02:42.590 --> 00:02:44.390
And then the ones that
were able to survive

00:02:44.390 --> 00:02:48.070
and pass on their genes
were the darker moths.

00:02:48.070 --> 00:02:51.100
Now it's been interesting
over the last 50 or so years

00:02:51.100 --> 00:02:53.950
as environmental regulations
have gone into effect,

00:02:53.950 --> 00:02:57.460
and the air has started to
clean up in places like London,

00:02:57.460 --> 00:03:00.640
you're seeing a return of
the white peppered moth.

00:03:00.640 --> 00:03:02.270
Because once again, the surfaces

00:03:02.270 --> 00:03:04.110
are no longer covered with soot,

00:03:04.110 --> 00:03:07.160
and so the variants that
are lighter in color

00:03:07.160 --> 00:03:09.800
now have a decent chance
of not being spotted.

00:03:09.800 --> 00:03:11.540
And if anything, now the darker ones

00:03:11.540 --> 00:03:14.450
might have a better
chance of being spotted

00:03:14.450 --> 00:03:16.303
in this cleaner environment.


Evidence of evolution: anatomy

WEBVTT
Kind: captions
Language: en

00:00:00.690 --> 00:00:03.090
- [Instructor] About
3.5 billion years ago,

00:00:03.090 --> 00:00:05.670
single-celled organisms
were the only life forms

00:00:05.670 --> 00:00:07.140
that existed on Earth.

00:00:07.140 --> 00:00:09.990
These organisms passed
on their genetic material

00:00:09.990 --> 00:00:12.750
with slight changes to their descendants.

00:00:12.750 --> 00:00:14.910
And over long periods of time,

00:00:14.910 --> 00:00:18.510
these genetic changes
resulted in new species.

00:00:18.510 --> 00:00:20.760
And eventually, the vast diversity

00:00:20.760 --> 00:00:22.590
of modern organisms evolves.

00:00:22.590 --> 00:00:25.290
Some organisms share a
more recent common ancestor

00:00:25.290 --> 00:00:26.370
than others do.

00:00:26.370 --> 00:00:27.720
Scientists have found evidence

00:00:27.720 --> 00:00:30.420
that we humans are more
closely related to chimpanzees

00:00:30.420 --> 00:00:31.770
than we are to rabbits.

00:00:31.770 --> 00:00:33.720
And we're more closely related to rabbits

00:00:33.720 --> 00:00:35.040
than we are to sharks.

00:00:35.040 --> 00:00:37.050
And you might be wondering
how can scientists

00:00:37.050 --> 00:00:39.060
determine how closely
two species are related

00:00:39.060 --> 00:00:40.110
to each other.

00:00:40.110 --> 00:00:41.077
Asking a shark,

00:00:41.077 --> 00:00:43.740
"Hey, do you think we
shared a common ancestor

00:00:43.740 --> 00:00:46.320
440 million years ago?" doesn't help,

00:00:46.320 --> 00:00:47.850
because even if they spoke English,

00:00:47.850 --> 00:00:50.100
they probably wouldn't
know the answer either.

00:00:50.100 --> 00:00:52.530
Scientists analyze the
similarities and differences

00:00:52.530 --> 00:00:54.540
between species to help figure out

00:00:54.540 --> 00:00:57.210
how they might be related
in evolutionary history.

00:00:57.210 --> 00:00:59.460
And they found significant
evidence for evolution

00:00:59.460 --> 00:01:01.320
by using a variety of methods,

00:01:01.320 --> 00:01:03.360
including examining the fossil record,

00:01:03.360 --> 00:01:05.640
analyzing the DNA of different organisms

00:01:05.640 --> 00:01:07.860
and comparing the development of embryos,

00:01:07.860 --> 00:01:10.860
which are what organisms are
called before they're born.

00:01:10.860 --> 00:01:13.200
However, you don't need
a microscope or a fossil

00:01:13.200 --> 00:01:14.700
to find evidence for evolution.

00:01:14.700 --> 00:01:16.441
You can find it by
looking at the anatomical

00:01:16.441 --> 00:01:19.590
or physical features of
organisms alive today.

00:01:19.590 --> 00:01:22.410
One way that scientists use
information from the present day

00:01:22.410 --> 00:01:25.140
to make sense of past
evolutionary relationships

00:01:25.140 --> 00:01:28.050
is by searching for clues
called homologous features.

00:01:28.050 --> 00:01:29.970
When two species share
a structurally similar

00:01:29.970 --> 00:01:31.500
anatomical feature that they inherited

00:01:31.500 --> 00:01:32.820
from a common ancestor,

00:01:32.820 --> 00:01:35.220
we say that the feature is homologous.

00:01:35.220 --> 00:01:36.540
The word homologous begins

00:01:36.540 --> 00:01:38.700
with a Latin prefix, meaning the same.

00:01:38.700 --> 00:01:39.930
And this makes sense,

00:01:39.930 --> 00:01:42.570
because when two species
have homologous features,

00:01:42.570 --> 00:01:44.850
it means they share the same ancestor.

00:01:44.850 --> 00:01:47.490
Have you ever looked at
an x-ray of a human's arm?

00:01:47.490 --> 00:01:49.260
If you have, you might
have noticed that we have

00:01:49.260 --> 00:01:54.260
humerus, ulna, radius,
carpals and metacarpal bones.

00:01:54.660 --> 00:01:56.910
If you looked at the
skeleton of a bird's wing,

00:01:56.910 --> 00:01:57.960
you could see that birds have

00:01:57.960 --> 00:01:59.910
a similar bone structure to ours.

00:01:59.910 --> 00:02:02.010
In fact, this similar
bone structure appears

00:02:02.010 --> 00:02:04.020
in the forearms of many other animals,

00:02:04.020 --> 00:02:08.460
including dogs, cats,
whales, elephants, and bats.

00:02:08.460 --> 00:02:11.310
These animals can use these
features in different ways

00:02:11.310 --> 00:02:14.940
to fly, to run, to swim or to wave hello.

00:02:14.940 --> 00:02:17.130
But despite these differences in function,

00:02:17.130 --> 00:02:18.930
the similarities of the bone structure

00:02:18.930 --> 00:02:21.270
indicate that these species
inherited these features

00:02:21.270 --> 00:02:22.620
from a common ancestor.

00:02:22.620 --> 00:02:25.320
This means that the bone
structure is a homologous feature.

00:02:25.320 --> 00:02:27.540
Compared to species with few similarities,

00:02:27.540 --> 00:02:29.790
two species that share
many homologous features

00:02:29.790 --> 00:02:31.500
are likely to be more closely related,

00:02:31.500 --> 00:02:32.940
which means that they're likely to share

00:02:32.940 --> 00:02:34.650
a more recent common ancestor.

00:02:34.650 --> 00:02:36.900
Species with fewer homologous features

00:02:36.900 --> 00:02:38.790
are likely to be less closely related,

00:02:38.790 --> 00:02:40.110
which means that they are likely to share

00:02:40.110 --> 00:02:42.120
a more distant common ancestor.

00:02:42.120 --> 00:02:43.620
For example, the wing of this bird

00:02:43.620 --> 00:02:44.900
has more structural similarities

00:02:44.900 --> 00:02:46.110
to the leg of this lizard

00:02:46.110 --> 00:02:47.490
than to the wing of this bat.

00:02:47.490 --> 00:02:49.800
This indicates that the
bird is more closely related

00:02:49.800 --> 00:02:51.690
to the lizard than it is to the bat,

00:02:51.690 --> 00:02:53.280
which means that the bird and the lizard

00:02:53.280 --> 00:02:55.020
share a more recent common ancestor

00:02:55.020 --> 00:02:56.670
than the bird and the bat do.

00:02:56.670 --> 00:02:58.350
When scientists believe
they have found species

00:02:58.350 --> 00:02:59.790
with homologous features,

00:02:59.790 --> 00:03:01.560
they can use other
methods to find out more

00:03:01.560 --> 00:03:03.540
about how the species evolved over time.

00:03:03.540 --> 00:03:06.600
They can compare the anatomical
features of modern organisms

00:03:06.600 --> 00:03:07.920
to those found in fossils

00:03:07.920 --> 00:03:09.630
to see how much they have in common.

00:03:09.630 --> 00:03:11.640
Sometimes, scientists find features

00:03:11.640 --> 00:03:13.740
that seem to be homologous
at first glance,

00:03:13.740 --> 00:03:16.110
but the features actually
evolved independently

00:03:16.110 --> 00:03:18.420
along different species' lineages.

00:03:18.420 --> 00:03:21.120
These features are called
analogous features.

00:03:21.120 --> 00:03:22.470
For example, let's take a look

00:03:22.470 --> 00:03:24.510
at the wings of two flying creatures:

00:03:24.510 --> 00:03:26.250
a bird and a butterfly.

00:03:26.250 --> 00:03:27.990
In order to figure out whether the wings

00:03:27.990 --> 00:03:29.340
are homologous features,

00:03:29.340 --> 00:03:31.800
we need to examine the physical
structure of the wings.

00:03:31.800 --> 00:03:34.080
The bird's wing is made up of hollow bones

00:03:34.080 --> 00:03:36.480
while the butterfly's wing
is made up of membranes

00:03:36.480 --> 00:03:38.485
made out of a protein called chitin.

00:03:38.485 --> 00:03:41.010
So even though birds and
butterflies can both fly,

00:03:41.010 --> 00:03:43.230
their wings have very
different structures.

00:03:43.230 --> 00:03:45.660
This means that bird
wings and butterfly wings

00:03:45.660 --> 00:03:47.400
are analogous features.

00:03:47.400 --> 00:03:48.540
This indicates to scientists

00:03:48.540 --> 00:03:50.199
that birds and insects did
not inherit that feature

00:03:50.199 --> 00:03:51.870
from a common ancestor.

00:03:51.870 --> 00:03:54.210
Instead, the ability to fly using wings

00:03:54.210 --> 00:03:56.887
evolved independently in each lineage.

00:03:56.887 --> 00:03:59.670
Comparing the anatomical
features of organisms

00:03:59.670 --> 00:04:01.770
has given scientists
a better understanding

00:04:01.770 --> 00:04:04.710
of how life on Earth has
evolved from common ancestors.

00:04:04.710 --> 00:04:06.780
So next time you meet a friendly shark,

00:04:06.780 --> 00:04:09.680
perhaps the two of you can
bond over your shared ancestry.


Fossils

WEBVTT
Kind: captions
Language: en

00:00:00.210 --> 00:00:01.500
- [Narrator] When I was 12 years old,

00:00:01.500 --> 00:00:04.050
I went on vacation to
Alaska with my family.

00:00:04.050 --> 00:00:05.250
While walking down one of

00:00:05.250 --> 00:00:07.059
the cold stone covered beaches,

00:00:07.059 --> 00:00:09.420
I spotted a large pile of rocks

00:00:09.420 --> 00:00:10.530
that seemed to have slid

00:00:10.530 --> 00:00:11.940
off the side of one of the hills

00:00:11.940 --> 00:00:13.470
that connected to the shore.

00:00:13.470 --> 00:00:14.940
These rocks caught my eye

00:00:14.940 --> 00:00:17.100
due to their peculiar outer rust color

00:00:17.100 --> 00:00:18.900
that contrasted with the rest

00:00:18.900 --> 00:00:20.426
of the rocks on the beach.

00:00:20.426 --> 00:00:23.100
As I began curiously looking through them,

00:00:23.100 --> 00:00:24.900
I accidentally knocked a few over.

00:00:24.900 --> 00:00:26.940
Splitting some in the process.

00:00:26.940 --> 00:00:28.470
But to my surprise,

00:00:28.470 --> 00:00:30.150
one of the rocks that split in half

00:00:30.150 --> 00:00:32.220
had a secret hidden within it.

00:00:32.220 --> 00:00:35.258
Inside with the imprint
of a tiny pine cone

00:00:35.258 --> 00:00:37.740
and nearby was rock covered

00:00:37.740 --> 00:00:39.540
in the imprints of leaves.

00:00:39.540 --> 00:00:42.180
I was so excited because that day

00:00:42.180 --> 00:00:44.760
I'd found real plant fossils,

00:00:44.760 --> 00:00:46.650
but what exactly are fossils

00:00:46.650 --> 00:00:48.450
and what can they tell us?

00:00:48.450 --> 00:00:51.180
Fossils are preserved
evidence of organisms

00:00:51.180 --> 00:00:53.400
that lived in the distant past.

00:00:53.400 --> 00:00:55.590
They can be made up of
many different things

00:00:55.590 --> 00:00:58.680
like bones, shells, plants,

00:00:58.680 --> 00:01:00.570
or even markings like footprints

00:01:00.570 --> 00:01:03.330
that tell us about an
organism's behaviors.

00:01:03.330 --> 00:01:04.620
These preserved remains

00:01:04.620 --> 00:01:06.330
are mostly made possible

00:01:06.330 --> 00:01:07.980
by specific kind of rock

00:01:07.980 --> 00:01:09.960
known as sedimentary rock.

00:01:09.960 --> 00:01:11.610
Sedimentary rock is formed

00:01:11.610 --> 00:01:14.130
from compressed layers of sediment,

00:01:14.130 --> 00:01:16.680
which is a mixture of rocks, minerals,

00:01:16.680 --> 00:01:18.210
and organic matter.

00:01:18.210 --> 00:01:20.700
Sediment is the result of erosion,

00:01:20.700 --> 00:01:22.759
which is when bits of rock or soil

00:01:22.759 --> 00:01:26.190
break down and get
deposited somewhere else.

00:01:26.190 --> 00:01:28.470
Sediment is deposited in layers,

00:01:28.470 --> 00:01:30.060
one on top of the other.

00:01:30.060 --> 00:01:31.470
over millions of years,

00:01:31.470 --> 00:01:33.420
these layers become compressed,

00:01:33.420 --> 00:01:34.920
eventually solidifying

00:01:34.920 --> 00:01:36.960
and forming sedimentary rock.

00:01:36.960 --> 00:01:38.100
But how do the fossils

00:01:38.100 --> 00:01:40.380
even get inside of these rocks?

00:01:40.380 --> 00:01:43.320
Well, let's look back
at the fossil I found.

00:01:43.320 --> 00:01:44.640
If I had to guess,

00:01:44.640 --> 00:01:45.818
a long time ago,

00:01:45.818 --> 00:01:47.549
some leaves and a pine cone

00:01:47.549 --> 00:01:49.350
must have fallen to the ground

00:01:49.350 --> 00:01:51.390
and gotten covered in sediment.

00:01:51.390 --> 00:01:53.730
As more sediment layered on top of them,

00:01:53.730 --> 00:01:55.320
the plants pressed an imprint

00:01:55.320 --> 00:01:56.970
of their shape and patterns

00:01:56.970 --> 00:01:58.530
into the sediment.

00:01:58.530 --> 00:02:01.380
Over time, the sediment
compressed into rock

00:02:01.380 --> 00:02:03.270
and the original plant decayed,

00:02:03.270 --> 00:02:06.030
but its imprint stayed inside the rock.

00:02:06.030 --> 00:02:08.190
Then finally, my fossil sat

00:02:08.190 --> 00:02:11.220
until I literally stumbled upon it.

00:02:11.220 --> 00:02:13.650
So now that we know what fossils are,

00:02:13.650 --> 00:02:15.360
what can they tell us?

00:02:15.360 --> 00:02:16.800
As I mentioned before,

00:02:16.800 --> 00:02:18.870
fossils are like little time machines

00:02:18.870 --> 00:02:20.669
that can show us what types of organisms

00:02:20.669 --> 00:02:22.097
where alive millions

00:02:22.097 --> 00:02:24.780
or even billions of years ago.

00:02:24.780 --> 00:02:26.250
And they can show us how life

00:02:26.250 --> 00:02:28.740
on Earth has changed over time.

00:02:28.740 --> 00:02:31.230
But in order to unlock these secrets,

00:02:31.230 --> 00:02:32.550
scientists have to estimate

00:02:32.550 --> 00:02:34.710
the ages of the fossils they find.

00:02:34.710 --> 00:02:37.170
This can be done in two main ways.

00:02:37.170 --> 00:02:38.850
Either by looking at which layers

00:02:38.850 --> 00:02:40.110
of the sedimentary rock

00:02:40.110 --> 00:02:41.730
the fossils are found in

00:02:41.730 --> 00:02:43.530
or by using a process known

00:02:43.530 --> 00:02:45.390
as radiometric dating.

00:02:45.390 --> 00:02:47.910
Let's talk about layer analysis first.

00:02:47.910 --> 00:02:49.740
As you know, sedimentary rocks

00:02:49.740 --> 00:02:51.180
are formed in layers

00:02:51.180 --> 00:02:52.410
with each new layer

00:02:52.410 --> 00:02:54.359
forming on top of an old layer.

00:02:54.359 --> 00:02:56.160
This means that the layers

00:02:56.160 --> 00:02:57.526
that are closer to the surface

00:02:57.526 --> 00:02:59.217
tend to be newer than the layers

00:02:59.217 --> 00:03:01.260
that are deeper in the ground.

00:03:01.260 --> 00:03:02.820
This means that a fossil

00:03:02.820 --> 00:03:04.079
found in a deeper layer

00:03:04.079 --> 00:03:06.360
of undisturbed sedimentary rock

00:03:06.360 --> 00:03:07.800
will be older than the ones

00:03:07.800 --> 00:03:09.210
found closer to the top.

00:03:09.210 --> 00:03:10.620
By looking through these layers,

00:03:10.620 --> 00:03:11.610
we're able to not only

00:03:11.610 --> 00:03:14.700
tell how old a particular fossil may be,

00:03:14.700 --> 00:03:17.460
but we can also look into
the patterns of fossils

00:03:17.460 --> 00:03:18.990
over multiple layers

00:03:18.990 --> 00:03:20.220
to see how life on Earth

00:03:20.220 --> 00:03:22.080
has changed over time.

00:03:22.080 --> 00:03:24.780
The second way scientists
estimate a fossil's age

00:03:24.780 --> 00:03:26.010
is through a process known

00:03:26.010 --> 00:03:27.990
as radiometric dating.

00:03:27.990 --> 00:03:29.490
Radiometric dating tells us

00:03:29.490 --> 00:03:30.870
how old a fossil is

00:03:30.870 --> 00:03:32.700
by studying its chemical properties.

00:03:32.700 --> 00:03:35.021
Specifically, radiometric dating

00:03:35.021 --> 00:03:36.218
looks at the decay,

00:03:36.218 --> 00:03:37.942
or the loss of particles,

00:03:37.942 --> 00:03:41.520
from certain radioactive
atoms in the fossils.

00:03:41.520 --> 00:03:44.370
Scientists know how
fast this decay happens.

00:03:44.370 --> 00:03:46.500
So by measuring the amount of decay

00:03:46.500 --> 00:03:47.610
that has occurred,

00:03:47.610 --> 00:03:50.370
scientists can estimate
the age of the fossil.

00:03:50.370 --> 00:03:53.460
Once scientists know
how old the fossil is,

00:03:53.460 --> 00:03:56.160
it can then be added to
Earth's Fossil Record.

00:03:56.160 --> 00:03:57.480
Earth's Fossil Record

00:03:57.480 --> 00:04:00.240
consists of all the fossils found on Earth

00:04:00.240 --> 00:04:02.100
along with their relative ages.

00:04:02.100 --> 00:04:03.330
And it provides us

00:04:03.330 --> 00:04:04.642
with the big picture view

00:04:04.642 --> 00:04:06.810
of the history of life on Earth.

00:04:06.810 --> 00:04:07.710
And with that,

00:04:07.710 --> 00:04:10.459
you now know how fossils
are formed and dated.

00:04:10.459 --> 00:04:11.790
Let's go back through

00:04:11.790 --> 00:04:13.500
the layers of this lesson

00:04:13.500 --> 00:04:15.570
and go over what we've learned today.

00:04:15.570 --> 00:04:17.061
Fossils are preserved evidence

00:04:17.061 --> 00:04:19.523
of organisms that lived long ago.

00:04:19.523 --> 00:04:22.560
This evidence of life
is most commonly found

00:04:22.560 --> 00:04:24.810
in layers of sedimentary rock.

00:04:24.810 --> 00:04:26.880
Now, depending on how deep they are

00:04:26.880 --> 00:04:29.010
in the layers of sedimentary rock

00:04:29.010 --> 00:04:31.350
or their results from radiometric dating,

00:04:31.350 --> 00:04:33.310
fossils can be given an estimated age

00:04:33.310 --> 00:04:36.090
and be placed on Earth's fossil record.

00:04:36.090 --> 00:04:38.212
Now, when it comes to the fossil I found,

00:04:38.212 --> 00:04:40.410
it wasn't a major discovery

00:04:40.410 --> 00:04:42.870
like the discoveries of the Ichthyosaur,

00:04:42.870 --> 00:04:44.700
Plesiosaur fossils found

00:04:44.700 --> 00:04:47.310
by paleontologist Mary Anning,

00:04:47.310 --> 00:04:48.510
but it made me realize

00:04:48.510 --> 00:04:50.700
that discovering fossils
is not carried out

00:04:50.700 --> 00:04:53.070
strictly by professional scientists.

00:04:53.070 --> 00:04:56.170
You and I can both find fossils too.

00:04:56.170 --> 00:04:59.760
All we need is a keen eye, some patience,

00:04:59.760 --> 00:05:01.310
and maybe a little bit of luck.


Worked examples: Punnett squares

WEBVTT
Kind: captions
Language: en

00:00:01.663 --> 00:00:03.230
- We're told that in a
population of pea plants,

00:00:03.230 --> 00:00:07.740
some plants have round seeds
and others have wrinkled seeds.

00:00:07.740 --> 00:00:10.640
The gene for seed shape in this population

00:00:10.640 --> 00:00:12.720
has two possible alleles.

00:00:12.720 --> 00:00:16.800
Remember, alleles are
just versions of the gene.

00:00:16.800 --> 00:00:20.300
One allele or one version
is for round seeds,

00:00:20.300 --> 00:00:22.000
which we're denoting capital R,

00:00:22.000 --> 00:00:24.730
and the other allele is for wrinkled seeds

00:00:24.730 --> 00:00:26.610
which we're denoting lowercase R.

00:00:26.610 --> 00:00:29.290
And they're telling us
that the round seed allele,

00:00:29.290 --> 00:00:32.090
the capital R, is dominant.

00:00:32.090 --> 00:00:34.300
For a cross between two pea plants

00:00:34.300 --> 00:00:38.460
that are heterozygous
for the seed shape gene,

00:00:38.460 --> 00:00:41.010
determine the expected ratio of offspring

00:00:41.010 --> 00:00:45.720
with round seeds to offspring
with wrinkled seeds.

00:00:45.720 --> 00:00:48.300
All right, like always, pause this video

00:00:48.300 --> 00:00:49.670
and see if you can have a go at this

00:00:49.670 --> 00:00:52.623
by yourself before we do this together.

00:00:54.010 --> 00:00:54.930
All right.

00:00:54.930 --> 00:00:57.680
Now let's think about the genotype

00:00:57.680 --> 00:01:01.790
for the two pea plants
that are heterozygous.

00:01:01.790 --> 00:01:05.920
Heterozygous means they
have two different versions

00:01:05.920 --> 00:01:08.380
of the gene, or two different alleles.

00:01:08.380 --> 00:01:10.440
So these are going to be two pea plants

00:01:10.440 --> 00:01:13.890
that are capital R, lowercase R.

00:01:13.890 --> 00:01:15.750
They have one of each.

00:01:15.750 --> 00:01:18.480
And to see what happens
in a cross between them,

00:01:18.480 --> 00:01:21.160
I will draw a Punnett square.

00:01:21.160 --> 00:01:24.940
So just like this, and I will explain

00:01:24.940 --> 00:01:27.913
what I am doing in a second here.

00:01:28.790 --> 00:01:30.850
So I'll draw it like this.

00:01:30.850 --> 00:01:31.860
So what you need to think about

00:01:31.860 --> 00:01:33.850
is you have your two parents,

00:01:33.850 --> 00:01:38.560
and so each parent is
capital R, lowercase R.

00:01:38.560 --> 00:01:41.130
Now that means that let's say parent one

00:01:41.130 --> 00:01:45.380
can contribute the
capital R to the offspring

00:01:45.380 --> 00:01:48.330
or it could contribute
the lowercase R allele

00:01:48.330 --> 00:01:50.570
to the offspring, and the
same thing could happen

00:01:50.570 --> 00:01:51.660
for the other parent.

00:01:51.660 --> 00:01:53.630
It could contribute the capital R

00:01:53.630 --> 00:01:56.110
or it could contribute the lowercase R.

00:01:56.110 --> 00:01:58.150
So what are all of the equally likely

00:01:58.150 --> 00:02:00.630
possibilities for the offspring?

00:02:00.630 --> 00:02:03.150
Well, the offspring might get a capital,

00:02:03.150 --> 00:02:06.900
the dominant allele,
the round seed allele,

00:02:06.900 --> 00:02:09.610
from both parents, capital R, capital R.

00:02:09.610 --> 00:02:12.130
All I'm doing is I'm taking
whatever letter's in the column

00:02:12.130 --> 00:02:13.810
and whatever's in the row.

00:02:13.810 --> 00:02:17.490
It could get a capital R from this parent

00:02:17.490 --> 00:02:20.250
and a lowercase R from that parent.

00:02:20.250 --> 00:02:22.900
It could get a lower
case R from this parent

00:02:22.900 --> 00:02:25.470
and a capital R from that parent,

00:02:25.470 --> 00:02:27.030
or in this situation, it's getting

00:02:27.030 --> 00:02:29.890
a lowercase R from either one.

00:02:29.890 --> 00:02:33.500
So these are the four
equally likely genotypes.

00:02:33.500 --> 00:02:35.800
Now they're not asking us about genotypes.

00:02:35.800 --> 00:02:39.070
They're saying determine the
expected ratio of offspring

00:02:39.070 --> 00:02:43.690
with round seeds to offspring
with wrinkled seeds.

00:02:43.690 --> 00:02:46.460
So what does the genotype
have to look like

00:02:46.460 --> 00:02:49.150
in order to have round seeds?

00:02:49.150 --> 00:02:51.900
Remember the round seed
allele is dominant.

00:02:51.900 --> 00:02:53.640
Well, this would be a
situation where you could be

00:02:53.640 --> 00:02:56.310
capital R capital R, but it's dominant.

00:02:56.310 --> 00:02:58.720
So you could also be capital R lowercase R

00:02:58.720 --> 00:03:01.170
and still have round seeds.

00:03:01.170 --> 00:03:02.500
The only way that you're going to have

00:03:02.500 --> 00:03:05.260
wrinkled seeds right over here

00:03:05.260 --> 00:03:10.260
is if you are homozygous for
the wrinkled seed allele.

00:03:10.430 --> 00:03:13.410
So this is the only
wrinkled seed scenario.

00:03:13.410 --> 00:03:15.330
So if you look here, you look and see

00:03:15.330 --> 00:03:18.430
out of the four equally likely scenarios,

00:03:18.430 --> 00:03:22.620
three of them end up with
a phenotype of round seeds

00:03:22.620 --> 00:03:25.640
and only one of them
ends up with a phenotype.

00:03:25.640 --> 00:03:28.160
Remember, phenotype is
what's being expressed.

00:03:28.160 --> 00:03:30.970
Only one of these four
equally likely scenarios

00:03:30.970 --> 00:03:33.260
has a phenotype of wrinkled seeds.

00:03:33.260 --> 00:03:36.130
So the expected ratio is going to be,

00:03:36.130 --> 00:03:38.710
you're gonna expect to see three offspring

00:03:38.710 --> 00:03:41.540
with round seeds for every
one with wrinkled seeds

00:03:41.540 --> 00:03:46.423
or you would expect a three to one ratio.

00:03:47.840 --> 00:03:50.550
Now I have another part of this question

00:03:50.550 --> 00:03:53.960
that is asking us, what
about a cross between

00:03:53.960 --> 00:03:57.480
a pea plant that is
homozygous for wrinkled seeds

00:03:57.480 --> 00:03:59.400
and one that is heterozygous?

00:03:59.400 --> 00:04:00.880
Pause the video again and see if you can

00:04:00.880 --> 00:04:01.980
have a go at this one.

00:04:03.560 --> 00:04:05.850
All right, so the first
thing that I like to do

00:04:05.850 --> 00:04:08.480
is just think about, what
are going to be the genotypes

00:04:08.480 --> 00:04:10.630
for each of these parents?

00:04:10.630 --> 00:04:15.300
So if we're talking about
homozygous for wrinkled seeds,

00:04:15.300 --> 00:04:17.690
remember the wrinkled seed
allele, we're denoting

00:04:17.690 --> 00:04:19.070
with a lowercase R.

00:04:19.070 --> 00:04:20.500
So that's going have a genotype

00:04:20.500 --> 00:04:22.660
of lowercase R, lowercase R,

00:04:22.660 --> 00:04:26.351
and then they say one
that is heterozygous.

00:04:26.351 --> 00:04:28.100
Well, we already saw that before.

00:04:28.100 --> 00:04:31.340
That's going to be capital
R and lowercase R. so

00:04:31.340 --> 00:04:36.340
let's draw a Punnett square
again, to be able to do this.

00:04:36.410 --> 00:04:41.410
So I'll do it like this,
like that, like that

00:04:42.420 --> 00:04:47.320
and then make sure I have
two columns and two rows,

00:04:47.320 --> 00:04:51.190
and let's put the
homozygous parent up here.

00:04:51.190 --> 00:04:53.910
They could either contribute a lowercase R

00:04:54.770 --> 00:04:56.771
or they could contribute a lowercase R.

00:04:56.771 --> 00:04:58.601
They're gonna contribute one of these two,

00:04:58.601 --> 00:05:01.675
and then let's think about
the heterozygous parent.

00:05:01.675 --> 00:05:04.641
Well, they can contribute a capital R,

00:05:04.641 --> 00:05:07.870
the dominant allele, or they
can contribute a lowercase R.

00:05:07.870 --> 00:05:10.240
So let's think about the
equally likely scenarios here,

00:05:10.240 --> 00:05:11.800
at least for genotype.

00:05:11.800 --> 00:05:14.060
Well, these are all scenarios

00:05:14.060 --> 00:05:17.300
in which we get a capital R
from this parent over here,

00:05:17.300 --> 00:05:19.500
the heterozygous parent,
I guess I could say.

00:05:19.500 --> 00:05:23.130
So let me write capital R, capital R.

00:05:23.130 --> 00:05:24.810
And in both of these scenarios,

00:05:24.810 --> 00:05:29.560
we're getting the lowercase
R from the homozygous parent.

00:05:29.560 --> 00:05:34.030
And both of these situations
are we are getting

00:05:34.030 --> 00:05:38.730
the wrinkled seed allele
from both parents.

00:05:38.730 --> 00:05:43.130
You're getting the lowercase R
from the heterozygous parent,

00:05:43.130 --> 00:05:46.690
and in either scenario,
you're getting a lowercase R

00:05:46.690 --> 00:05:48.810
from the homozygous parent.

00:05:48.810 --> 00:05:51.950
So let me write that right over here.

00:05:51.950 --> 00:05:54.680
So, which of these genotypes would have

00:05:54.680 --> 00:05:58.610
a phenotype of round seeds?

00:05:58.610 --> 00:06:03.050
Well, round seeds are
going to be scenarios

00:06:03.050 --> 00:06:07.070
where you have at least one
of the round seed alleles.

00:06:07.070 --> 00:06:10.210
So these are all going to be
round seeds, right over here.

00:06:10.210 --> 00:06:11.500
They're going to have a phenotype,

00:06:11.500 --> 00:06:13.860
I should say, of round seeds

00:06:13.860 --> 00:06:16.240
because remember, the
round allele is dominant.

00:06:16.240 --> 00:06:18.010
Even though you have one of each,

00:06:18.010 --> 00:06:20.280
the dominant allele is
what you're actually

00:06:20.280 --> 00:06:22.690
going to see in the phenotype here.

00:06:22.690 --> 00:06:25.280
And then we see these two

00:06:25.280 --> 00:06:30.280
are going to be wrinkled, wrinkled.

00:06:30.360 --> 00:06:33.910
So what's the ratio of round
to wrinkled going to be?

00:06:33.910 --> 00:06:35.190
Well, it's going be one to one.

00:06:35.190 --> 00:06:37.360
For every two round, you're
going to have two wrinkled,

00:06:37.360 --> 00:06:41.530
or for every one round, you're
going to have one wrinkled.

00:06:41.530 --> 00:06:43.780
Two to two is the same thing as one to one

00:06:43.780 --> 00:06:46.723
when we're talking about
ratios, and we're done.


Genetics vocabulary

WEBVTT
Kind: captions
Language: en

00:00:00.570 --> 00:00:01.403
- [Instructor] We know that

00:00:01.403 --> 00:00:03.680
any sexually reproducing organism

00:00:03.680 --> 00:00:06.940
is getting DNA from both its male parent

00:00:06.940 --> 00:00:09.124
and its female parent

00:00:09.124 --> 00:00:11.510
and that's true also for human beings.

00:00:11.510 --> 00:00:14.710
You might know we have
23 pairs of chromosomes

00:00:14.710 --> 00:00:16.380
but let's zoom in on one of those pairs.

00:00:16.380 --> 00:00:18.930
So let's say this is one of
the chromosomes in a pair

00:00:18.930 --> 00:00:22.240
and let's say that this is the
other chromosome in the pair.

00:00:22.240 --> 00:00:23.810
So one came from one parent.

00:00:23.810 --> 00:00:25.980
The other came from the other parent.

00:00:25.980 --> 00:00:30.380
Chromosomes are nothing more
than bunched up strands of DNA

00:00:30.380 --> 00:00:32.670
plus other things that help package it.

00:00:32.670 --> 00:00:34.340
So let's unravel a little bit

00:00:34.340 --> 00:00:36.760
to understand how these relate to genes.

00:00:36.760 --> 00:00:37.593
And then, we'll dive

00:00:37.593 --> 00:00:40.730
into a little bit more
terminology around genetics.

00:00:40.730 --> 00:00:44.680
So you have this big, long strand of DNA

00:00:44.680 --> 00:00:47.990
and segments of this
code for different genes.

00:00:47.990 --> 00:00:50.080
Maybe this part right over here

00:00:50.080 --> 00:00:52.539
is related to how tall you become.

00:00:52.539 --> 00:00:54.570
So let's say that part right over there,

00:00:54.570 --> 00:00:56.650
that might be related to hair color.

00:00:56.650 --> 00:00:57.840
And in other videos,

00:00:57.840 --> 00:01:00.020
we talk about how these genes

00:01:00.020 --> 00:01:03.460
can essentially be translated eventually

00:01:03.460 --> 00:01:05.410
into proteins which are expressed in forms

00:01:05.410 --> 00:01:07.440
like height or hair color or eye color,

00:01:07.440 --> 00:01:10.196
or many, many, many, many other ways.

00:01:10.196 --> 00:01:12.720
But each of these chromosomes

00:01:12.720 --> 00:01:14.870
actually code, generally speaking,

00:01:14.870 --> 00:01:16.310
for the same genes.

00:01:16.310 --> 00:01:19.600
So if this one has a region
that codes for that gene,

00:01:19.600 --> 00:01:21.910
this one will as well

00:01:21.910 --> 00:01:24.156
and this one will also.

00:01:24.156 --> 00:01:27.070
The other chromosome in the
pair will also have a region

00:01:27.070 --> 00:01:28.763
that codes for this other gene.

00:01:29.630 --> 00:01:31.230
Now, as you can imagine,

00:01:31.230 --> 00:01:33.520
the genes that get
translated into the proteins

00:01:33.520 --> 00:01:35.820
that eventually are show
up in your hair color,

00:01:35.820 --> 00:01:38.820
they can come in different versions.

00:01:38.820 --> 00:01:42.620
So what we call the
different versions of a gene

00:01:42.620 --> 00:01:44.193
is an allele.

00:01:45.070 --> 00:01:49.016
So for example, from this parent,

00:01:49.016 --> 00:01:51.751
you might have gotten the allele here

00:01:51.751 --> 00:01:54.140
that would describe,

00:01:54.140 --> 00:01:57.060
let's say, blonde hair,

00:01:57.060 --> 00:01:59.480
I'll denote that with lowercase b,

00:01:59.480 --> 00:02:01.550
while from this parent,

00:02:01.550 --> 00:02:03.300
you might have gotten the allele

00:02:03.300 --> 00:02:06.970
that's associated with say, brown hair.

00:02:06.970 --> 00:02:10.440
So they're both associated
or they're both coding

00:02:10.440 --> 00:02:12.190
for the same type of protein

00:02:12.190 --> 00:02:13.990
that might play a role in hair color

00:02:13.990 --> 00:02:15.620
but they're different versions of it.

00:02:15.620 --> 00:02:17.260
So you could view an allele

00:02:17.260 --> 00:02:21.728
as versions or a version,

00:02:21.728 --> 00:02:26.433
I'll say, alleles are versions of a gene.

00:02:27.490 --> 00:02:30.640
Now, if you know which versions you have,

00:02:30.640 --> 00:02:33.240
then you're able to say,
"I know my or I know

00:02:33.240 --> 00:02:35.680
the organism's genotype."

00:02:35.680 --> 00:02:38.850
So in this situation, we know
we have the capital B allele

00:02:38.850 --> 00:02:40.560
which is for the brown hair

00:02:40.560 --> 00:02:42.380
and we have the lowercase b allele

00:02:42.380 --> 00:02:43.600
which is for the blonde hair,

00:02:43.600 --> 00:02:46.291
and so the genotype in this situation,

00:02:46.291 --> 00:02:49.928
where you actually know
what alleles you have,

00:02:49.928 --> 00:02:53.630
you would say that that
is, you have a capital B

00:02:53.630 --> 00:02:54.810
from one parent

00:02:54.810 --> 00:02:56.990
and you have the lowercase b

00:02:56.990 --> 00:02:58.810
from another parent.

00:02:58.810 --> 00:03:00.300
Now the thing you might be asking is,

00:03:00.300 --> 00:03:02.860
but what does this organism look like?

00:03:02.860 --> 00:03:05.770
How does this genotype
actually get expressed?

00:03:05.770 --> 00:03:07.780
And if you're asking that question

00:03:07.780 --> 00:03:10.650
where you're asking a
question of phenotype.

00:03:10.650 --> 00:03:13.672
Phenotype is what is expressed

00:03:13.672 --> 00:03:17.730
and this is usually
observable in some way.

00:03:17.730 --> 00:03:19.730
So the phenotype in this situation

00:03:19.730 --> 00:03:22.953
might be, and it's seldom
this simple in genetics,

00:03:22.953 --> 00:03:24.610
but we're gonna make it simple

00:03:24.610 --> 00:03:26.280
in this scenario,

00:03:26.280 --> 00:03:29.629
that if you have a brown
allele and blonde allele,

00:03:29.629 --> 00:03:32.970
that maybe the brown allele is dominant

00:03:32.970 --> 00:03:35.883
which is that if you have
even one brown allele,

00:03:35.883 --> 00:03:38.490
at the end of the day,
you're going to see brown.

00:03:38.490 --> 00:03:40.450
So I'll just write that
down for this scenario

00:03:40.450 --> 00:03:42.330
although that's not actually
going to be the case.

00:03:42.330 --> 00:03:45.110
Genetics gets a lot more
complicated than that

00:03:45.110 --> 00:03:47.033
but certain genes, certain alleles,

00:03:48.000 --> 00:03:51.652
they are that simply
dominant or recessive.

00:03:51.652 --> 00:03:54.630
Now you can imagine there's
many different genotypes

00:03:54.630 --> 00:03:56.090
based on what I just described

00:03:56.090 --> 00:03:58.330
that could result in this phenotype.

00:03:58.330 --> 00:04:01.690
You could have this genotype
that we just showed.

00:04:01.690 --> 00:04:05.357
You could get a brown
allele from both parents.

00:04:05.357 --> 00:04:08.330
Either of these genotypes
would express themselves

00:04:08.330 --> 00:04:11.880
as the phenotype brown, if we assume,

00:04:11.880 --> 00:04:13.220
and that is a big if,

00:04:13.220 --> 00:04:17.810
if we assume that this is the
dominant version of the gene

00:04:17.810 --> 00:04:19.780
or the dominant allele.

00:04:19.780 --> 00:04:21.900
If that is, then in either case,

00:04:21.900 --> 00:04:24.505
it will express itself as
the phenotype of brown.

00:04:24.505 --> 00:04:27.840
The only way you would get
blonde hair in this scenario

00:04:27.840 --> 00:04:31.780
is if you had two of the recessive gene

00:04:31.780 --> 00:04:33.210
or the recessive version of the gene

00:04:33.210 --> 00:04:35.250
or the recessive allele.

00:04:35.250 --> 00:04:40.250
This would lead to a blonde phenotype

00:04:40.500 --> 00:04:41.600
right over here.

00:04:41.600 --> 00:04:43.110
We've talked about dominant alleles.

00:04:43.110 --> 00:04:45.540
We've talked about recessive alleles

00:04:45.540 --> 00:04:47.940
and another piece of terminology

00:04:47.940 --> 00:04:50.360
that you will hear when
you talk about genetics

00:04:50.360 --> 00:04:54.590
are notions of homozygous, homozygous

00:04:55.610 --> 00:04:59.927
and/or versus heterozygous genotypes.

00:05:01.050 --> 00:05:01.990
And when people are talking

00:05:01.990 --> 00:05:03.840
about homozygous or heterozygous,

00:05:03.840 --> 00:05:05.699
they're talking about the genotype.

00:05:05.699 --> 00:05:10.170
Homozygous, you might know the
prefix homo refers to same.

00:05:10.170 --> 00:05:11.590
So this is a situation

00:05:11.590 --> 00:05:16.123
where both the alleles are
the same, same alleles,

00:05:17.430 --> 00:05:20.229
and heterozygous is a
situation where hetero,

00:05:20.229 --> 00:05:25.229
that's referring to
different, different alleles.

00:05:25.801 --> 00:05:29.140
So what would we call this
scenario right over here?

00:05:29.140 --> 00:05:32.985
We would call this a heterozygous
genotype for this gene.

00:05:32.985 --> 00:05:36.340
This would be homozygous dominant.

00:05:36.340 --> 00:05:38.860
We have two of the same dominant allele

00:05:38.860 --> 00:05:42.710
and this would be homozygous recessive.

00:05:42.710 --> 00:05:43.830
I'll leave you there.

00:05:43.830 --> 00:05:47.153
You're now armed to talk
a lot about genetics.


Mutations

WEBVTT
Kind: captions
Language: en

00:00:01.020 --> 00:00:01.853
- [Instructor] In this video,

00:00:01.853 --> 00:00:04.050
we're gonna talk a little
bit about mutations,

00:00:04.050 --> 00:00:05.580
and I wanna apologize ahead of time.

00:00:05.580 --> 00:00:07.020
My voice is a little strange today.

00:00:07.020 --> 00:00:08.970
I rode more roller coasters

00:00:08.970 --> 00:00:10.470
than I thought I would yesterday,

00:00:10.470 --> 00:00:12.960
and I screamed a little bit.

00:00:12.960 --> 00:00:14.100
But anyway, (chuckles)

00:00:14.100 --> 00:00:16.080
what we see right over here

00:00:16.080 --> 00:00:20.850
is what's often known as the
central dogma of biology.

00:00:20.850 --> 00:00:25.440
It explains how we go from
information in our DNA,

00:00:25.440 --> 00:00:28.740
which is really sequences of nucleotides,

00:00:28.740 --> 00:00:33.510
genes are segments of our DNA
that code for specific things.

00:00:33.510 --> 00:00:35.460
So we see these nucleotides,

00:00:35.460 --> 00:00:38.940
which we denote with A, C, Gs, and Ts.

00:00:38.940 --> 00:00:42.330
And every three of them,
that's known as a codon,

00:00:42.330 --> 00:00:43.980
and for every three of them,

00:00:43.980 --> 00:00:46.740
it's associated with an amino acid.

00:00:46.740 --> 00:00:49.830
And in other future parts
of your biology education,

00:00:49.830 --> 00:00:50.850
you'll go into more depth

00:00:50.850 --> 00:00:53.760
on the molecular
structures of amino acids.

00:00:53.760 --> 00:00:54.840
But what you need to know now

00:00:54.840 --> 00:00:58.230
is the amino acids are
essentially strung together.

00:00:58.230 --> 00:01:00.510
And then they create proteins.

00:01:00.510 --> 00:01:05.400
And proteins have all sorts
of functions in your body.

00:01:05.400 --> 00:01:07.800
To a large degree, they make you, you.

00:01:07.800 --> 00:01:10.230
They construct what you are.

00:01:10.230 --> 00:01:12.030
So this is a simplified version

00:01:12.030 --> 00:01:17.030
of how we go from DNA,
to you, to some degree.

00:01:17.250 --> 00:01:19.110
Now, mutations, as you might know,

00:01:19.110 --> 00:01:20.430
even when you watch some movies,

00:01:20.430 --> 00:01:22.110
these are changes in DNA.

00:01:22.110 --> 00:01:23.970
You might have seen superheroes

00:01:23.970 --> 00:01:26.520
be exposed to radiation
or some type of chemical,

00:01:26.520 --> 00:01:27.690
and then they get mutations,

00:01:27.690 --> 00:01:29.760
and then all of a sudden they have powers.

00:01:29.760 --> 00:01:31.650
Well, we don't know
about too many mutations

00:01:31.650 --> 00:01:35.580
that create the ability to
fly or to stick to walls.

00:01:35.580 --> 00:01:40.050
But mutations are a way that
we get new genetic information

00:01:40.050 --> 00:01:42.420
in the gene pool.

00:01:42.420 --> 00:01:43.253
Now you might be saying,

00:01:43.253 --> 00:01:44.970
wait, I already know
about sexual reproduction.

00:01:44.970 --> 00:01:47.490
Sexual reproduction creates variation.

00:01:47.490 --> 00:01:48.630
And that's true.

00:01:48.630 --> 00:01:51.120
Sexual reproduction creates variation

00:01:51.120 --> 00:01:53.250
but it really just
shuffles around the genes

00:01:53.250 --> 00:01:55.110
and the chromosomes they're on

00:01:55.110 --> 00:01:57.870
that exist already inside of a gene pool.

00:01:57.870 --> 00:02:02.250
Mutations are actually
changes in the genes.

00:02:02.250 --> 00:02:04.350
Now, where do these mutations come from?

00:02:04.350 --> 00:02:08.910
Well, there are sometimes
errors when DNA is copied,

00:02:08.910 --> 00:02:11.790
but can also happen from
environmental influences,

00:02:11.790 --> 00:02:14.850
like radiation or other things.

00:02:14.850 --> 00:02:15.750
Now, as you can imagine,

00:02:15.750 --> 00:02:18.300
many times, if you were
to just all of a sudden

00:02:18.300 --> 00:02:20.010
eliminate some nucleotides,

00:02:20.010 --> 00:02:22.740
or if you were to change
them into something else,

00:02:22.740 --> 00:02:23.880
that might be harmful.

00:02:23.880 --> 00:02:26.790
All of a sudden it might
code for an amino acid here

00:02:26.790 --> 00:02:31.110
that does not allow this
protein to function properly.

00:02:31.110 --> 00:02:33.300
Sometimes, it can be beneficial.

00:02:33.300 --> 00:02:36.660
And that's how we can get new
versions of genes, alleles,

00:02:36.660 --> 00:02:38.430
or new genes altogether.

00:02:38.430 --> 00:02:40.230
All of a sudden this became that,

00:02:40.230 --> 00:02:43.080
this becomes a different amino acid,

00:02:43.080 --> 00:02:46.410
maybe this protein functions better.

00:02:46.410 --> 00:02:47.670
And then as you can imagine,

00:02:47.670 --> 00:02:50.010
sometimes, it doesn't matter at all.

00:02:50.010 --> 00:02:51.750
Maybe the different amino acid here

00:02:51.750 --> 00:02:54.660
really doesn't change the
structure of this protein.

00:02:54.660 --> 00:02:57.930
And in some cases, you can
even change a nucleotide

00:02:57.930 --> 00:03:00.753
and it still codes for
the same amino acid.