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(elegant piano music)
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Downloaded from
YTS.MX
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- In a lot of ways you can think
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of cities as one of the
largest unplanned experiments
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Official YIFY movies site:
YTS.MX
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of all time.
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(elegant piano music)
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- There can be really small differences
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that have very large
biological significance.
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(elegant piano music)
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- Cities are places, we call
them extreme habitats really.
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They are places where there
is a lot of opportunity.
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And at the same time,
there's also challenges.
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- [Narrator] As our city
spread, how will nature respond?
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Will plants and animals dwindle,
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or will they adapt to urban life?
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And what kind of new encounters
will we see in the city?
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In the historic French town of Albi,
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biologist Frederic Santoul
keeps an eye on his catfish.
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In 1983, fishermen released
these Eastern European fish
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into the Riverton.
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Today, they're at the top
of the river's food chain.
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(Frederic speaking in foreign language)
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- [Voiceover] This is
a fascinating species
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because we know so little about them.
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There are many myths that people believe,
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even that they eat dogs.
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There are many stories.
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- [Narrator] The biologist is interested
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in the behavior of the large fish
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that circle the reservoir's basins.
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(mysterious music)
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(Frederic speaking in foreign language)
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- [Voiceover] We work with
fishermen to tag the fish.
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They contacted us after
observing very strange behavior
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in the fish here in Albi.
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- [Narrator] The man-made landscape
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of the city fosters new
encounters of species.
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(Frederic speaking in foreign language)
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- [Voiceover] The pigeons have
never had to face predators
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from the water.
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Instead, they scan the
sky for birds of prey.
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- [Narrator] The pigeons
approach the water
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to bathe and drink.
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Sometimes a bird misses the
narrow strip of safe ground
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and touches down in open water.
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(Frederic speaking in foreign language)
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- [Voiceover] The catfish
don't really see the pigeons,
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but once they sense the birds' movements
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in the water with their
bobbles, then they strike.
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- [Narrator] This new hunting behavior
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of the catfish was
observed by the biologists
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for the first time in 2010.
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(whimsical music)
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For some catfish here,
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pigeons now account for
up to 40% of their prey.
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- There's suddenly this
ecological interaction
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which allows for evolution to start
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to improve the bird-catching
ability of the catfish
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and also to improve the
escape ability of the pigeons.
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So you can expect that all
these new interactions are
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also causing new evolutionary dynamic.
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- [Narrator] Dutch evolutionary biologist
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Menno Schilthuizen
researches the adaptation
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of wildlife to the city.
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Darwin's theory, he
believes, has gone urban.
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- Urban evolution is evolutionary change.
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So really genetic change in wild animals
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and plants in cities.
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It's all about understanding
how species will be able
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to survive in this very
human-dominated context.
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- [Narrator] Cities are homosapiens'
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most extreme intervention in nature.
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With concrete and steel,
we create new landscapes
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and alter the face of the earth.
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Already, most people live in cities,
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rather than in the countryside.
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How does this influence evolution?
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The development of new species?
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What selection pressures
does the city create?
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A summit evening in the
Dutch capital of Amsterdam,
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in the Vondelpark in
the center of the city,
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Biologist Menno Schilthuizen
uses a light trap
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to catch insects.
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He's leading a citizen science project
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to explore urban nature.
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- For insects and for some smaller plants,
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the diversity today in
cities seems to be higher
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than in intensively
managed agricultural areas.
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Today, agricultural land
is so intensively managed
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and every last bit of
production is squeezed out
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of every square meter of surface area
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that there's no space for nature
anymore in the countryside.
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And at the same time, cities get more,
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they get greener, people
pay more attention to nature
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and to urban nature.
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So it's actually becoming
a very rich environment
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with a higher biodiversity
than outside of the city.
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(uneasy music)
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- [Narrator] But overall, we're
rapidly losing biodiversity,
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both within and outside our cities.
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For insects, the declines
are particularly severe.
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In the Swiss Alps near Zurich,
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Scientist Florian Altermatt
has set up his light traps.
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Ever since humans began
to light up the night,
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billions of nocturnal insects
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have been dying off every year.
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(Florian speaking in foreign language)
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- [Voiceover] For such a
species it's problematic
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if it's attracted by light
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because then it cannot use
the few short days it has
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as a moth to lay eggs.
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- [Narrator] Light pollution is one
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of the major threats to moths.
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Scientists are now even speaking
of an insect apocalypse.
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(Florian speaking in foreign language)
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- [Voiceover] I think the
declines we're now seeing
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are already quite worrying.
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Studies show a 60 to
80% decline in biomass,
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sometimes even in nature reserves.
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These are incredibly large numbers.
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In my childhood, I used to
observe moths like these.
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I would set up this trap
next to my parents' house
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and attract moths, actually,
in quite large numbers.
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I don't think I'd find many today.
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- [Narrator] But might insects be capable
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of adapting to life in the
perpetual light of our cities?
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That's what Florian
Altermatt wanted to find out.
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His test subject, the spindle ermine moth,
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whose caterpillars develop
on the European spindle tree.
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(bird singing)
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(Florian speaking in foreign language)
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- [Voiceover] Actually,
it was a coincidence.
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While I was working on my PhD thesis,
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every day I walked through a park
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which had those Europeans spindle bushes.
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And I noticed that there
were these caterpillars,
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these moths which must
have lived there for years
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in a city park with
permanent light pollution.
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And then I thought I could
just collect them, raise them,
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and test how much the adult
moths are attracted by light.
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- [Narrator] With his experiments in 2006,
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Altermatt pioneered research
into urban evolution.
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He released the moths in a darkened room.
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The next morning, he
counted how many had flown
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into the light trap.
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(Florian speaking in foreign language)
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- [Voiceover] The results
showed a difference.
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About 20% fewer urban
moths flew into the trap.
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I was very surprised.
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It was widely known that
moths attracted by light,
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some more than others,
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but these differences
have always been observed
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between different species.
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Seeing variations within a single species,
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that we'd never seen before.
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- [Narrator] The experiment
clearly demonstrated
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a hereditary adaptation
to life in the city,
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direct proof of urban evolution.
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For Dutch biologist Menno Schilthuizen,
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the findings confirm a larger picture.
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In Amsterdam, he and his group
of citizen scientists debate
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whether we might soon observe even more
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and greater adaptations of
animals and plants to this city.
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- We see that evolutionary
processes are starting
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which will eventually
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or could eventually produce new species
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that are specialized
on living in the city.
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- [Narrator] For Menno
Schilthuizen, it's not if, but when.
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- Every organism that lives
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in the city will show
this urban evolution.
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These rapid changes in their behavior,
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in their physiology, in their appearances
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to optimize their life
in an urban environment.
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- [Narrator] But what elements
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of urban landscapes
prompt wildlife to adapt?
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Evolutionary biologist Jason Munshi-South
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is an expert on animals found
in the parks of New York City.
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For years, he's been studying
how rodents adapt to the city.
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Along with human immigrants from Europe,
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rats also voyage to the New World.
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Today, they roam the
city in subway tunnels.
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Most native rodent species, however,
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don't dare try their luck crossing town.
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This distinction sparked
the scientist's interest.
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- I used to be a tropical biologist,
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but then I moved to New York City
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for my first academic job
after graduate school.
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And I decided I wanted
to do some local work
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that would be interesting to
the people of New York City
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and to my myself.
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And I found out that there
was these small mammals living
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in essentially islands
of forest in the city,
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and I thought, you know,
that's interesting.
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Nobody's really ever looked at these.
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Are they becoming genetically different
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from mice outside of the city?
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Are they adapting? And
that's how it all started.
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- [Narrator] Central Park opened in 1873.
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It still hosts animal species
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that lived here long
before the city was built.
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- Right now we're in the
middle of Central Park.
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We're gonna be traveling to
the north end of the park
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where there's a very nice
forest called the North Woods.
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And there we'll be
setting up traps hopefully
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to capture white-footed mice.
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One of the things that inspired me
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when I first started this work is
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if you look at a New York City subway map,
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you see the subway lines,
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but then there are these
large green shapes,
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rectangles, and ovals, and so
forth that are the parklands.
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And they put those on the map
so you know where they are,
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but you also see that they
are almost like a chain
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of islands that are scattered
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in this sea of concrete and
roads and buildings and,
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you know, 8.5 million people.
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So in a sense, if it's
a species like a mouse
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that can't leave the forest, cross,
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you know, neighborhoods
and buildings and roads
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and make it to the other patch,
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it is essentially the same biologically
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as if they were on an island
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in terms of them not being able to move
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and spread their genes
with the other patches.
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And these urban patches,
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once they become sufficiently isolated,
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operate like a mini Galapagos
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and may be driving the
evolution of many species
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that are, you know, stuck there now.
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- [Narrator] The evolutionary
biologist is investigating
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whether the white-footed
mice actually develop
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in distinct ways in each
of the various parks.
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- Yeah.
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So this would be a really nice
spot for white-footed mice.
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They like to move next to logs
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so they're not completely out in the open.
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They might actually even
be living inside this log
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where it's rotting or in
holes underneath the log.
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So this is pretty much the ideal spot.
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- [Voiceover] This forest is
encircled by the Big Apple.
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Have the mice already adapted
to this unique environment?
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What traits do they need to survive here?
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- No shortage of good trapping spots.
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Later I'll be going to
one of our more suburban,
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almost rural sites with the
larger, more intact forests,
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lesser urbanization,
and I'll be setting out,
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you know, an equal number of traps
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with the hope that we
catch mice there as well.
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- [Narrator] Jason
Munshi-South will search
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within the animal's genetic
codes for the markers of life
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in the big city.
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00:13:29,960 --> 00:13:32,377
(soft music)
254
00:13:34,900 --> 00:13:36,280
- I think what's been most interesting
255
00:13:36,280 --> 00:13:39,240
to me is thinking about how the things
256
00:13:39,240 --> 00:13:41,180
that we are all doing in our daily lives,
257
00:13:41,180 --> 00:13:42,890
where we put our garbage,
258
00:13:42,890 --> 00:13:46,470
what we're choosing to eat
and what we generate as waste,
259
00:13:46,470 --> 00:13:48,250
where we choose to live,
260
00:13:48,250 --> 00:13:50,100
how we choose to go to work
261
00:13:50,100 --> 00:13:52,210
or out to a restaurant or something,
262
00:13:52,210 --> 00:13:53,580
all of these things we are doing
263
00:13:53,580 --> 00:13:55,830
are now influencing other species
264
00:13:55,830 --> 00:13:58,230
in a way that we're just
starting to understand.
265
00:14:02,440 --> 00:14:04,270
- [Narrator] Though it's not only animals
266
00:14:04,270 --> 00:14:07,420
that adapt to human intervention
in the natural world.
267
00:14:07,420 --> 00:14:08,553
So do plants.
268
00:14:09,560 --> 00:14:12,680
In Southern France, the
yellow-flowered Crepis sancta
269
00:14:12,680 --> 00:14:15,720
is being studied by Biologist
Pierre-Olivier Cheptou.
270
00:14:16,663 --> 00:14:19,000
- [Voiceover] Crepis sancta
is a very common species
271
00:14:19,000 --> 00:14:20,540
in the Mediterranean region,
272
00:14:20,540 --> 00:14:24,600
a kind of Mediterranean
dandelion from the same family.
273
00:14:24,600 --> 00:14:26,910
And its essential advantage as a model is
274
00:14:26,910 --> 00:14:29,160
that it produces two types of seeds,
275
00:14:29,160 --> 00:14:30,893
large ones and small ones.
276
00:14:32,900 --> 00:14:34,850
- [Narrator] The small wildflower produces
277
00:14:34,850 --> 00:14:38,900
both lighter seeds with
parachutes allowing them to glide
278
00:14:38,900 --> 00:14:42,784
and heavier seeds that
simply fall to the ground.
279
00:14:42,784 --> 00:14:43,710
(Pierre speaking in foreign language)
280
00:14:43,710 --> 00:14:46,010
- [Voiceover] I'm interested
in the process of adaptation
281
00:14:46,010 --> 00:14:47,550
to an urban environment.
282
00:14:47,550 --> 00:14:49,330
And in particular, what happens
283
00:14:49,330 --> 00:14:52,110
when a species first arrives a city.
284
00:14:52,110 --> 00:14:55,640
It has recently colonized
certain areas of Montpellier.
285
00:14:55,640 --> 00:14:59,220
And in my comparison between
rural and urban populations,
286
00:14:59,220 --> 00:15:02,043
I focus on the traits related to seeds.
287
00:15:04,240 --> 00:15:06,620
- [Narrator] The idea of
studying the adaptation
288
00:15:06,620 --> 00:15:08,960
of the modest plant of the city came
289
00:15:08,960 --> 00:15:11,470
to Cheptou to almost by chance.
290
00:15:11,470 --> 00:15:13,190
When he came back from abroad,
291
00:15:13,190 --> 00:15:15,930
he noticed the inconspicuousness
flowers growing
292
00:15:15,930 --> 00:15:17,219
in the city.
293
00:15:17,219 --> 00:15:18,190
(Pierre speaking in foreign language)
294
00:15:18,190 --> 00:15:19,240
- [Voiceover] I had left Montreal
295
00:15:19,240 --> 00:15:20,830
in the middle of a blizzard.
296
00:15:20,830 --> 00:15:22,648
I got the plane to Paris.
297
00:15:22,648 --> 00:15:25,260
And when I took the bus
to Downtown Montpellier,
298
00:15:25,260 --> 00:15:28,140
it was sunny with a pristine blue sky.
299
00:15:28,140 --> 00:15:30,950
And then I noticed there
were Crepis sancta flowers
300
00:15:30,950 --> 00:15:33,900
everywhere in those tiny urban patches.
301
00:15:33,900 --> 00:15:36,070
It was then the intuition hit me.
302
00:15:36,070 --> 00:15:39,210
I knew there was something
to discover here,
303
00:15:39,210 --> 00:15:40,513
something to uncover.
304
00:15:41,780 --> 00:15:45,330
- Was the plant already
adapting to the city?
305
00:15:45,330 --> 00:15:48,393
Which aspects of the city
would drive that change?
306
00:15:49,394 --> 00:15:50,580
(Pierre speaking in foreign language)
307
00:15:50,580 --> 00:15:52,360
- [Voiceover] The predominant
mineral in cities,
308
00:15:52,360 --> 00:15:55,740
especially in European
cities, is concrete.
309
00:15:55,740 --> 00:15:59,760
Concrete exerts a powerful
fragmenting force on plants,
310
00:15:59,760 --> 00:16:03,600
driving them to ever-shrinking
refuges in these habitats.
311
00:16:03,600 --> 00:16:05,640
- [Narrator] Sometimes
the city's constraints
312
00:16:05,640 --> 00:16:08,720
on a plant's habitat can be extreme.
313
00:16:08,720 --> 00:16:10,873
How will evolution respond?
314
00:16:14,545 --> 00:16:15,580
(Pierre speaking in foreign language)
315
00:16:15,580 --> 00:16:16,413
- [Voiceover] I'm looking at
316
00:16:16,413 --> 00:16:18,800
how urban fragmentation will modify
317
00:16:18,800 --> 00:16:21,490
the dispersal traits of this species.
318
00:16:21,490 --> 00:16:23,570
I expect plants that produce more
319
00:16:23,570 --> 00:16:26,010
of the larger seeds
will be more successful
320
00:16:26,010 --> 00:16:28,200
at reproduction in urban areas
321
00:16:28,200 --> 00:16:30,100
than they would be in the countryside.
322
00:16:31,390 --> 00:16:33,470
- [Narrator] The heavier
seeds face less risk
323
00:16:33,470 --> 00:16:36,000
of being swept onto the asphalt.
324
00:16:36,000 --> 00:16:39,340
And indeed, the biologist
discovered that far more plants
325
00:16:39,340 --> 00:16:41,650
in the city produced the heavier seeds
326
00:16:41,650 --> 00:16:44,020
and are thus better able to survive.
327
00:16:44,020 --> 00:16:46,420
A difference of 15%.
328
00:16:46,420 --> 00:16:50,143
But what most stands out is
the speed of this adaptation.
329
00:16:51,455 --> 00:16:53,070
(Pierre speaking in foreign language)
330
00:16:53,070 --> 00:16:55,180
- [Voiceover] The evolution
we have seen has taken
331
00:16:55,180 --> 00:16:57,320
about 15 years.
332
00:16:57,320 --> 00:16:59,620
This is extremely brief.
333
00:16:59,620 --> 00:17:01,360
It was the first demonstration
334
00:17:01,360 --> 00:17:04,880
of such a rapid evolution
of seed traits for plants.
335
00:17:04,880 --> 00:17:08,100
And that's due to this
highly fragmented composition
336
00:17:08,100 --> 00:17:09,353
of the urban environment.
337
00:17:12,860 --> 00:17:14,450
- [Narrator] Genetic changes occurring
338
00:17:14,450 --> 00:17:18,010
at such a rate have long
been considered unlikely,
339
00:17:18,010 --> 00:17:20,073
even impossible by science.
340
00:17:23,540 --> 00:17:26,920
- I think Darwin would have
been amazed by the fastness
341
00:17:26,920 --> 00:17:28,610
by which these changes take place.
342
00:17:28,610 --> 00:17:31,520
He was sort of underestimating the power
343
00:17:31,520 --> 00:17:33,610
of natural selection himself.
344
00:17:33,610 --> 00:17:36,420
He said that you could never see any
345
00:17:36,420 --> 00:17:38,450
of these changes in progress.
346
00:17:38,450 --> 00:17:39,860
You cannot actually observe them,
347
00:17:39,860 --> 00:17:42,760
you can only deduce them from the fossils,
348
00:17:42,760 --> 00:17:44,490
from the patterns that you see in nature.
349
00:17:44,490 --> 00:17:46,970
You said evolution is too slow
350
00:17:46,970 --> 00:17:49,280
to see it happening in real time.
351
00:17:49,280 --> 00:17:51,840
And the fact that now
today, especially in cities,
352
00:17:51,840 --> 00:17:53,860
we see these changes taking place
353
00:17:53,860 --> 00:17:57,310
under our eyes in the streets
where we live right around us,
354
00:17:57,310 --> 00:17:59,710
I think Darwin would have
been thrilled by that.
355
00:18:02,240 --> 00:18:06,800
- In Los Angeles, the UCLA
campus also nurtures species
356
00:18:06,800 --> 00:18:10,240
that have migrated from
surrounding areas to the city.
357
00:18:10,240 --> 00:18:13,530
Evolutionary biologist Pamela Yeh studies
358
00:18:13,530 --> 00:18:15,093
the dark-eyed junco.
359
00:18:17,470 --> 00:18:19,460
The mountain bird has only been settled
360
00:18:19,460 --> 00:18:22,163
in California cities for a few decades.
361
00:18:23,240 --> 00:18:24,930
Pamela Yeh began her research
362
00:18:24,930 --> 00:18:27,823
in San Diego more than 20 years ago.
363
00:18:28,770 --> 00:18:33,190
Today, she's investigating
how the once shy bird manages
364
00:18:33,190 --> 00:18:35,690
to survive in bustling Los Angeles.
365
00:18:40,710 --> 00:18:42,970
- So this is a junko nest.
366
00:18:42,970 --> 00:18:44,550
Typically in the mountains they make all
367
00:18:44,550 --> 00:18:46,430
of their nests on the ground,
368
00:18:46,430 --> 00:18:49,500
but up here, we have a good
percentage of our nests
369
00:18:49,500 --> 00:18:51,910
that are up in the middle of, you know,
370
00:18:51,910 --> 00:18:54,570
branches of trees or up on the buildings,
371
00:18:54,570 --> 00:18:56,560
higher up off the ground.
372
00:18:56,560 --> 00:18:58,640
- [Narrator] Darwin himself was fascinated
373
00:18:58,640 --> 00:19:00,350
by the evolution of birds,
374
00:19:00,350 --> 00:19:04,100
but until now, biologists
couldn't observe their adaptation
375
00:19:04,100 --> 00:19:06,370
to new habitats in real time.
376
00:19:06,370 --> 00:19:09,220
- They have this very famous
study on Darwin's finches
377
00:19:09,220 --> 00:19:10,280
in the Galapagos,
378
00:19:10,280 --> 00:19:13,770
and they can show really
large biological differences
379
00:19:13,770 --> 00:19:14,790
in terms of like mortality,
380
00:19:14,790 --> 00:19:16,270
like who's surviving and who's dying,
381
00:19:16,270 --> 00:19:19,180
by like a millimeter
or less of a beak depth
382
00:19:19,180 --> 00:19:21,900
or a beak length or beak width, right?
383
00:19:21,900 --> 00:19:25,340
And so I think there can
be really small differences
384
00:19:25,340 --> 00:19:29,760
that have very large
biological significance.
385
00:19:29,760 --> 00:19:32,090
- [Narrator] To track such subtle changes.
386
00:19:32,090 --> 00:19:33,760
Pamela Yeh and her team led
387
00:19:33,760 --> 00:19:37,290
by PhD candidate Ellie Diamant first have
388
00:19:37,290 --> 00:19:39,310
to catch the birds.
389
00:19:39,310 --> 00:19:43,563
- So the nest is just over here.
390
00:19:45,940 --> 00:19:47,410
Can you see it in the grate?
391
00:19:47,410 --> 00:19:49,920
There are five chicks
up there, nine days old,
392
00:19:49,920 --> 00:19:53,193
and the parents are going
back and feeding them.
393
00:19:54,120 --> 00:19:56,840
- [Narrator] Might recorded
birdsong jolt the bird
394
00:19:56,840 --> 00:19:58,450
into rash action?
395
00:19:58,450 --> 00:20:00,030
- So we're gonna play a playback,
396
00:20:00,030 --> 00:20:01,660
like a territorial junko song.
397
00:20:01,660 --> 00:20:04,940
And it's going to go
to that speaker there.
398
00:20:04,940 --> 00:20:06,400
And hopefully the male
399
00:20:06,400 --> 00:20:08,270
who seems like he's feeding
his chicks right now
400
00:20:08,270 --> 00:20:10,490
is gonna fly over, try to check it out,
401
00:20:10,490 --> 00:20:12,040
maybe go for the speaker,
402
00:20:12,040 --> 00:20:14,920
and hopefully get caught
in this net or in this net.
403
00:20:14,920 --> 00:20:15,753
We'll see.
404
00:20:15,753 --> 00:20:16,586
Okay.
405
00:20:19,435 --> 00:20:22,610
(junko chirping)
406
00:20:22,610 --> 00:20:24,920
- [Narrator] The call of a rival bird.
407
00:20:24,920 --> 00:20:27,633
The male, intent on driving
it off, rushes over.
408
00:20:29,680 --> 00:20:31,670
- [Ellie] Oh, there is a junco in the net.
409
00:20:31,670 --> 00:20:33,463
Guys, that was easy.
410
00:20:34,730 --> 00:20:37,290
- [Narrator] The team
tags and measures the bird
411
00:20:37,290 --> 00:20:39,620
and collects DNA samples.
412
00:20:39,620 --> 00:20:42,100
Back in San Diego in 2003,
413
00:20:42,100 --> 00:20:44,120
Professor Yeh had discovered a change
414
00:20:44,120 --> 00:20:48,000
in the appearance of the
city junco's tail feathers.
415
00:20:48,000 --> 00:20:49,450
Now her team wants to see
416
00:20:49,450 --> 00:20:51,763
if something similar is going on here.
417
00:20:53,280 --> 00:20:55,340
- [Ellie] Spreading his tail
so you can see the white
418
00:20:55,340 --> 00:20:56,363
on his tail there.
419
00:20:58,740 --> 00:21:00,990
- One of the main
differences that we found is
420
00:21:00,990 --> 00:21:04,150
that urban juncos had much
less white in the tail feather
421
00:21:04,150 --> 00:21:06,530
than the populations
in the local mountains,
422
00:21:06,530 --> 00:21:07,810
which had a lot of white.
423
00:21:07,810 --> 00:21:09,630
And what we wanted to know was then, well,
424
00:21:09,630 --> 00:21:12,260
why is it there's this huge difference
425
00:21:12,260 --> 00:21:13,680
that we're finding between the mountains
426
00:21:13,680 --> 00:21:14,903
and the city juncos?
427
00:21:16,050 --> 00:21:17,900
What's the reason for that?
428
00:21:17,900 --> 00:21:20,780
- [Narrator] Evidence suggests
the white tail feathers serve
429
00:21:20,780 --> 00:21:23,930
an important signaling
function in competition
430
00:21:23,930 --> 00:21:26,053
and partner selection by the birds.
431
00:21:28,307 --> 00:21:29,640
- Cool. Success.
432
00:21:29,640 --> 00:21:30,473
All right.
433
00:21:31,430 --> 00:21:34,130
- [Narrator] What new demands
does life between motorways
434
00:21:34,130 --> 00:21:36,420
and buildings make on birds
435
00:21:36,420 --> 00:21:39,793
to change their mating and
territorial preferences?
436
00:21:42,210 --> 00:21:44,550
The case of a species adapting its color
437
00:21:44,550 --> 00:21:47,410
to man-made environments
was first observed
438
00:21:47,410 --> 00:21:50,920
by natural scientists
during industrialization,
439
00:21:50,920 --> 00:21:53,720
even before Darwin put forward his theory
440
00:21:53,720 --> 00:21:55,483
on the origin of species.
441
00:21:58,350 --> 00:22:01,770
- The peppered moth is a species of moth
442
00:22:01,770 --> 00:22:03,920
that comes in two forms,
443
00:22:03,920 --> 00:22:06,450
a light-colored form with light wings
444
00:22:06,450 --> 00:22:08,190
and one with dark wings.
445
00:22:08,190 --> 00:22:11,000
And the dark-winged form
was only first found
446
00:22:11,000 --> 00:22:13,700
in England in the Industrial Revolution.
447
00:22:13,700 --> 00:22:15,800
In the middle of the 19th century,
448
00:22:15,800 --> 00:22:18,510
it began to appear and suddenly
it started to become more
449
00:22:18,510 --> 00:22:21,840
and more common over a
relatively short period of time
450
00:22:21,840 --> 00:22:24,540
in areas where there was
a lot of air pollution.
451
00:22:24,540 --> 00:22:26,270
- [Narrator] The smoke
from the chimneys coated
452
00:22:26,270 --> 00:22:29,300
the white birch bark with dark soot.
453
00:22:29,300 --> 00:22:32,930
The white moths thus
became easy prey for birds.
454
00:22:32,930 --> 00:22:36,770
The new darker moths
enjoyed superior camouflage.
455
00:22:36,770 --> 00:22:38,720
- People didn't really
understand what was going on.
456
00:22:38,720 --> 00:22:42,350
They thought that the
female moths maybe saw
457
00:22:42,350 --> 00:22:44,200
that the environment was getting darker
458
00:22:44,200 --> 00:22:46,580
and somehow that became
imprinted on their offspring.
459
00:22:46,580 --> 00:22:48,010
I mean, that's the way people thought
460
00:22:48,010 --> 00:22:51,490
about genetics and heredity in those days.
461
00:22:51,490 --> 00:22:54,150
- [Narrator] The conclusive
evidence connecting the spread
462
00:22:54,150 --> 00:22:59,150
of the dark moths to coal soot
was only found in the 1980s.
463
00:22:59,210 --> 00:23:01,210
The air was getting cleaner again,
464
00:23:01,210 --> 00:23:03,893
and the white moths returned.
465
00:23:05,740 --> 00:23:07,870
- Evolution can proceed fast
466
00:23:07,870 --> 00:23:10,980
if the environment
changes very dramatically,
467
00:23:10,980 --> 00:23:13,350
which means that a lot
of individuals will die
468
00:23:13,350 --> 00:23:14,500
and a few will survive,
469
00:23:14,500 --> 00:23:16,960
the ones that have some
genetic characteristic
470
00:23:16,960 --> 00:23:18,440
that makes them survive better.
471
00:23:18,440 --> 00:23:21,090
And they will then produce
the next generation.
472
00:23:21,090 --> 00:23:24,080
And they may also have some adaptations
473
00:23:24,080 --> 00:23:27,470
which then spread so that
evolution can proceed faster.
474
00:23:27,470 --> 00:23:29,100
- [Narrator] The color change was a simple
475
00:23:29,100 --> 00:23:31,010
but effective adaptation.
476
00:23:31,010 --> 00:23:33,893
It only required a
mutation of a single gene.
477
00:23:34,820 --> 00:23:38,060
But what if man-made pollutants
substantially distort
478
00:23:38,060 --> 00:23:40,223
the biochemistry of organisms?
479
00:23:41,070 --> 00:23:44,740
In the 1970s, the water at
New Bedford Harbor near Boston
480
00:23:44,740 --> 00:23:46,973
was severely polluted with PCBs.
481
00:23:48,080 --> 00:23:51,510
The US Environmental
Protection Agency, EPA,
482
00:23:51,510 --> 00:23:54,603
wanted to know just how bad
the pollution really was.
483
00:23:55,770 --> 00:23:59,700
- The original focus was
on what must be wrong
484
00:23:59,700 --> 00:24:02,270
with all the fish that live in that harbor
485
00:24:02,270 --> 00:24:04,910
because of the toxic chemicals.
486
00:24:04,910 --> 00:24:06,910
Instead, we came here looking trying
487
00:24:06,910 --> 00:24:10,570
to understand what must
be right about those fish
488
00:24:10,570 --> 00:24:11,963
that could survive here.
489
00:24:14,970 --> 00:24:17,920
So they've become a
natural experiment for us
490
00:24:17,920 --> 00:24:22,140
to study how animals can adapt
491
00:24:22,140 --> 00:24:25,670
to toxic human-made pollutants.
492
00:24:25,670 --> 00:24:28,560
Terrific. Just what we're looking for.
493
00:24:28,560 --> 00:24:31,160
Let's get 'em into a net,
bring 'em back to the lab.
494
00:24:33,140 --> 00:24:35,514
- [Narrator] Diane Nacci heads the EPA lab
495
00:24:35,514 --> 00:24:37,698
in Narragansett Rhode Island.
496
00:24:37,698 --> 00:24:40,615
(mysterious music)
497
00:24:45,310 --> 00:24:46,950
In the breeding facility,
498
00:24:46,950 --> 00:24:50,300
the scientists want to
unravel the mechanism
499
00:24:50,300 --> 00:24:54,150
that allows this population
of a killifish species
500
00:24:54,150 --> 00:24:58,363
to survive in the PCB-polluted
water of New Bedford Harbor.
501
00:25:02,370 --> 00:25:04,970
- [Diane] So let's see if
they left any eggs for us.
502
00:25:06,510 --> 00:25:08,400
- [Narrator] They plan to compare eggs
503
00:25:08,400 --> 00:25:10,540
from the New Bedford Harbor fish
504
00:25:10,540 --> 00:25:14,173
with those of a fish
population from a cleaner site.
505
00:25:17,750 --> 00:25:19,370
- Let's start a test and see what
506
00:25:19,370 --> 00:25:22,103
they do when we expose 'em to chemicals.
507
00:25:23,660 --> 00:25:26,160
- This killifish species occurs all
508
00:25:26,160 --> 00:25:29,390
along the North American Atlantic coast.
509
00:25:29,390 --> 00:25:32,070
- The killifish has been a favorite
510
00:25:32,070 --> 00:25:35,090
of biology literally for centuries.
511
00:25:35,090 --> 00:25:38,390
That they are quite common,
they are non-migratory,
512
00:25:38,390 --> 00:25:41,110
so they reflect their local environment,
513
00:25:41,110 --> 00:25:43,890
and each population is unique in
514
00:25:43,890 --> 00:25:45,980
that it is genetically different.
515
00:25:45,980 --> 00:25:48,340
It is adapted to its local environment.
516
00:25:48,340 --> 00:25:51,423
So it gives us opportunity
for lots of studies.
517
00:25:53,090 --> 00:25:55,730
- [Narrator] The researchers
need to observe the development
518
00:25:55,730 --> 00:26:00,730
of the fish embryos in the
egg in order to understand
519
00:26:01,350 --> 00:26:05,510
at which stages the
environmental toxin disrupts
520
00:26:05,510 --> 00:26:09,800
the animal's biochemistry or not.
521
00:26:09,800 --> 00:26:13,080
- So we'll look at the rate at
which the embryo is developed
522
00:26:13,080 --> 00:26:17,130
and certain features that we
know that PCBs fees can disturb
523
00:26:17,130 --> 00:26:20,060
like a proper development of the heart,
524
00:26:20,060 --> 00:26:23,400
evidence of proper development
of the circulatory system,
525
00:26:23,400 --> 00:26:25,213
and proper body size.
526
00:26:28,230 --> 00:26:30,210
- [Narrator] Why are
these particular fish able
527
00:26:30,210 --> 00:26:33,473
to resist deadly environmental toxins?
528
00:26:35,980 --> 00:26:38,570
- It's important to
understand which species can
529
00:26:38,570 --> 00:26:41,290
and which cannot adapt
because we want to forecast.
530
00:26:41,290 --> 00:26:44,410
We want to predict what the
environment will look like
531
00:26:44,410 --> 00:26:47,200
in the future, whether
the ecosystem surfaces
532
00:26:47,200 --> 00:26:49,980
that we rely on today like pollination,
533
00:26:49,980 --> 00:26:52,930
clean water, et cetera,
can still be relied on.
534
00:26:52,930 --> 00:26:55,610
And for that, we're
going to need adaptation
535
00:26:55,610 --> 00:26:57,770
of all kinds of animals and plants
536
00:26:57,770 --> 00:27:00,043
to this new world that we are creating.
537
00:27:01,230 --> 00:27:04,950
- [Narrator] In California,
some city juncos have less white
538
00:27:04,950 --> 00:27:08,180
in their tail feathers
than their mountain peers.
539
00:27:08,180 --> 00:27:11,540
Which selection pressures
are driving this evolution?
540
00:27:11,540 --> 00:27:14,283
What is the function of this pigmentation?
541
00:27:17,980 --> 00:27:19,300
- And one of the main purposes appears
542
00:27:19,300 --> 00:27:21,920
to be in dominance interactions
543
00:27:21,920 --> 00:27:24,610
between individuals where
typically the more white
544
00:27:24,610 --> 00:27:26,220
that you have, the more dominant
545
00:27:26,220 --> 00:27:27,970
and the more aggressive you are,
546
00:27:27,970 --> 00:27:30,270
and your successful at
winning competitions.
547
00:27:30,270 --> 00:27:31,890
If you're fighting with another one,
548
00:27:31,890 --> 00:27:34,303
often the one that has more white wins.
549
00:27:35,830 --> 00:27:37,990
- So we're gonna do some
aggression playbacks
550
00:27:37,990 --> 00:27:39,200
around Dickson Court.
551
00:27:39,200 --> 00:27:40,530
- All right. Good luck today.
552
00:27:40,530 --> 00:27:41,363
- All right.
- Okay. Yeah.
553
00:27:41,363 --> 00:27:42,448
Thank you so much today, Pam.
554
00:27:42,448 --> 00:27:43,281
- Okay. See you soon.
- We'll keep you up-to-date.
555
00:27:43,281 --> 00:27:44,870
- Okay. Bye-bye.
556
00:27:44,870 --> 00:27:46,720
- [Narrator] To learn
more about the adaptation
557
00:27:46,720 --> 00:27:48,340
of the birds to the city,
558
00:27:48,340 --> 00:27:51,180
PhD student Ellie Diamant aims
559
00:27:51,180 --> 00:27:54,450
to scientifically measure
their aggression levels here
560
00:27:54,450 --> 00:27:55,670
in Los Angeles.
561
00:27:55,670 --> 00:27:58,400
- So we're essentially setting up an arena
562
00:27:58,400 --> 00:27:59,510
to watch the bird.
563
00:27:59,510 --> 00:28:01,570
While they're in the car, it's fine.
564
00:28:01,570 --> 00:28:04,223
This is a Boris the fake junko,
565
00:28:05,210 --> 00:28:09,120
and it's the visual stimulus for the bird.
566
00:28:09,120 --> 00:28:10,380
He's just gonna sit here
567
00:28:11,230 --> 00:28:14,400
and there's gonna be a
song playing from there,
568
00:28:14,400 --> 00:28:17,680
and the bird is going to think
that this is a real junco
569
00:28:17,680 --> 00:28:20,190
and it's gonna hear the
song that it's singing,
570
00:28:20,190 --> 00:28:21,990
and then hopefully come and think
571
00:28:21,990 --> 00:28:24,690
that there is an intruding
bird on the territory.
572
00:28:24,690 --> 00:28:27,090
And we'll see how it reacts to that bird.
573
00:28:27,090 --> 00:28:29,680
- [Narrator] Juncos are territorial birds.
574
00:28:29,680 --> 00:28:32,940
from a male's response to a
stranger in his territory,
575
00:28:32,940 --> 00:28:35,293
the researchers can
gauge his aggressiveness.
576
00:28:36,210 --> 00:28:37,110
- Ready?
577
00:28:37,110 --> 00:28:38,359
- [Researcher] Yeah. All right.
578
00:28:38,359 --> 00:28:39,372
Starting now.
579
00:28:39,372 --> 00:28:40,205
- [Ellie] Okay.
580
00:28:40,205 --> 00:28:42,955
(junco chirping)
581
00:28:47,408 --> 00:28:48,991
I think I hear him.
582
00:28:49,907 --> 00:28:50,740
Oh.
- Oh.
583
00:28:50,740 --> 00:28:52,373
- He's there. Yeah, that's him.
584
00:28:53,440 --> 00:28:54,671
He's in the tree.
585
00:28:54,671 --> 00:28:55,660
- This angle you can.
586
00:28:55,660 --> 00:28:56,910
- Yeah, let me try. He's still singing.
587
00:28:56,910 --> 00:28:58,163
- [Researcher] He turned around.
588
00:28:59,220 --> 00:29:00,053
- Where is he? Oh.
589
00:29:00,053 --> 00:29:01,193
- [Researcher] He's down. Oh.
590
00:29:01,193 --> 00:29:02,383
- He's entering.
- He's entered.
591
00:29:04,400 --> 00:29:05,420
- [Narrator] Shortly before the end
592
00:29:05,420 --> 00:29:07,630
of the 15-minute trial period,
593
00:29:07,630 --> 00:29:10,303
the male stalks the intruder closely.
594
00:29:12,610 --> 00:29:14,210
- He's hiding behind some grass.
595
00:29:18,750 --> 00:29:20,050
Is he gonna knock it over?
596
00:29:22,440 --> 00:29:24,130
- [Narrator] The researchers
stop the playback
597
00:29:24,130 --> 00:29:25,960
to end the experiment.
598
00:29:25,960 --> 00:29:29,163
The male displayed some
aggression, but not a great deal.
599
00:29:31,010 --> 00:29:32,450
Why do the city birds seem
600
00:29:32,450 --> 00:29:34,633
to lose their drive for competition?
601
00:29:36,390 --> 00:29:38,090
- What we think is happening is
602
00:29:38,090 --> 00:29:41,870
that there's selection towards
for less aggressive birds
603
00:29:41,870 --> 00:29:44,670
who are better mates, the better parents,
604
00:29:44,670 --> 00:29:46,390
because you can likely
increase your fitness
605
00:29:46,390 --> 00:29:50,120
so much more by taking care of
the chicks that you do have,
606
00:29:50,120 --> 00:29:52,620
rather than looking for
extra pair copulation
607
00:29:52,620 --> 00:29:55,000
and extra pair fertilizations.
608
00:29:55,000 --> 00:29:56,970
- [Narrator] With the
longest summers in the city
609
00:29:56,970 --> 00:29:59,830
and abundant food from watered greens,
610
00:29:59,830 --> 00:30:02,230
the birds can maintain more nests per year
611
00:30:02,230 --> 00:30:04,090
than in the mountains.
612
00:30:04,090 --> 00:30:05,980
Competition for additional mates
613
00:30:05,980 --> 00:30:08,833
and territories no
longer seems worthwhile.
614
00:30:13,490 --> 00:30:15,010
- There's a lot of reasons why these birds
615
00:30:15,010 --> 00:30:17,640
shouldn't be successful in urban areas,
616
00:30:17,640 --> 00:30:18,730
and yet they are.
617
00:30:18,730 --> 00:30:20,140
So I think understanding why they
618
00:30:20,140 --> 00:30:22,280
are and understanding the mechanisms,
619
00:30:22,280 --> 00:30:25,100
the processes underlying
that can tell us something
620
00:30:25,100 --> 00:30:27,240
about how do we encourage other species
621
00:30:27,240 --> 00:30:28,920
to also be successful.
622
00:30:28,920 --> 00:30:32,910
(elegant piano music)
623
00:30:32,910 --> 00:30:33,990
- [Narrator] What are the factors
624
00:30:33,990 --> 00:30:37,483
that allow individual
species to adapt to the city?
625
00:30:38,560 --> 00:30:42,393
Are parallel developments taking
place in cities worldwide?
626
00:30:43,930 --> 00:30:46,710
At the University of Toronto Mississauga,
627
00:30:46,710 --> 00:30:50,963
evolutionary biologist Marc
Johnson pursues these questions.
628
00:30:52,790 --> 00:30:54,580
- In a lot of ways you can think of cities
629
00:30:54,580 --> 00:30:59,580
as one of the largest unplanned
experiments of all time.
630
00:31:00,330 --> 00:31:02,320
The problem is, is
there's very few organisms
631
00:31:02,320 --> 00:31:04,270
where you could study adaptation
632
00:31:04,270 --> 00:31:07,610
to urban environments on a global scale.
633
00:31:07,610 --> 00:31:10,840
And white clover is one of
those very few organisms
634
00:31:10,840 --> 00:31:11,927
where you can actually do that.
635
00:31:11,927 --> 00:31:15,370
And so now this then becomes the model
636
00:31:15,370 --> 00:31:19,000
to understand whether
organisms in general can adapt
637
00:31:19,000 --> 00:31:21,850
to the convergent
environmental change associated
638
00:31:21,850 --> 00:31:24,390
with cities throughout the world.
639
00:31:24,390 --> 00:31:26,280
- [Narrator] Researchers across the globe
640
00:31:26,280 --> 00:31:28,460
are working together in this study.
641
00:31:28,460 --> 00:31:30,970
Evolutionary biologist Stephan Greiner
642
00:31:30,970 --> 00:31:34,850
and his team are collecting
white clover in Berlin.
643
00:31:34,850 --> 00:31:38,460
In cities, the plant
faces a different habitat.
644
00:31:38,460 --> 00:31:39,840
Temperatures are higher than
645
00:31:39,840 --> 00:31:41,763
in the suburbs and the countryside.
646
00:31:43,880 --> 00:31:45,668
(Stephan speaking in foreign language)
647
00:31:45,668 --> 00:31:46,880
- [Voiceover] What you can expect is that
648
00:31:46,880 --> 00:31:49,350
as humans create new
environmental conditions,
649
00:31:49,350 --> 00:31:50,650
life will adapt.
650
00:31:50,650 --> 00:31:52,750
And to be able to show
that on a global scale,
651
00:31:52,750 --> 00:31:54,880
that's a real scientific benefit.
652
00:31:54,880 --> 00:31:56,020
It has to be done.
653
00:31:56,020 --> 00:31:58,920
That's why we're dedicating
our free time to this project.
654
00:32:01,670 --> 00:32:03,740
- [Narrator] As they
proceed from the countryside
655
00:32:03,740 --> 00:32:05,360
to the city center of Berlin,
656
00:32:05,360 --> 00:32:10,360
Greiner and his team collect
specimens at 30 locations.
657
00:32:10,400 --> 00:32:13,130
That means the data will
be broad enough to compare
658
00:32:13,130 --> 00:32:15,303
with that from other global cities.
659
00:32:16,240 --> 00:32:18,290
In the shadow of the Television Tower,
660
00:32:18,290 --> 00:32:20,283
they find their final samples.
661
00:32:23,177 --> 00:32:25,143
- [Voiceover] That's it. All done.
662
00:32:27,880 --> 00:32:30,560
- In all, we have 168 cities right now,
663
00:32:30,560 --> 00:32:33,510
and over 250 collaborators all working
664
00:32:33,510 --> 00:32:35,070
on the same project together.
665
00:32:35,070 --> 00:32:39,550
There's never been a collaborative project
666
00:32:39,550 --> 00:32:42,910
on evolutionary biology of this scale.
667
00:32:42,910 --> 00:32:45,320
And so this is the largest
collaborative project
668
00:32:45,320 --> 00:32:47,630
in evolutionary biology ever.
669
00:32:47,630 --> 00:32:50,290
- [Narrator] So is clover
developing in the same way
670
00:32:50,290 --> 00:32:54,120
all over the world into a
kind of global city clover?
671
00:32:54,120 --> 00:32:55,970
From the vast set of data,
672
00:32:55,970 --> 00:32:58,033
the researchers hope to find an answer.
673
00:33:00,690 --> 00:33:04,400
In the grounds of a research
institute north of New York,
674
00:33:04,400 --> 00:33:07,140
geneticist Jason Munshi-South wants
675
00:33:07,140 --> 00:33:11,350
to catch white-footed
mice to compare their DNA
676
00:33:11,350 --> 00:33:13,380
with that of those in the city,
677
00:33:13,380 --> 00:33:14,311
but it's not easy.
- Go to the labs.
678
00:33:14,311 --> 00:33:15,500
- [Researcher] It's good.
679
00:33:15,500 --> 00:33:16,333
- Okay.
680
00:33:21,560 --> 00:33:23,080
So this is a trap that was open
681
00:33:23,080 --> 00:33:24,930
that didn't catch anything obviously.
682
00:33:27,970 --> 00:33:29,230
Wow, that's a toad.
683
00:33:29,230 --> 00:33:30,480
I thought it was a mouse.
684
00:33:31,370 --> 00:33:35,813
Nice day for other wildlife, I guess.
685
00:33:38,880 --> 00:33:39,800
We were really surprised
686
00:33:39,800 --> 00:33:42,260
that almost every park was
different from every other park.
687
00:33:42,260 --> 00:33:44,030
It's almost to the point
where you can take a mouse
688
00:33:44,030 --> 00:33:46,120
from one park, give it to our lab,
689
00:33:46,120 --> 00:33:48,860
and we could just look at a
small segment of its genome
690
00:33:48,860 --> 00:33:50,560
and tell you where it came from.
691
00:33:50,560 --> 00:33:52,700
That's how much they had
changed just randomly
692
00:33:52,700 --> 00:33:54,780
over time from being isolated.
693
00:33:54,780 --> 00:33:57,270
And that's when we started
our current studies looking
694
00:33:57,270 --> 00:33:59,315
at over 20,000 genes to see what genes
695
00:33:59,315 --> 00:34:02,020
and potentially what functions change
696
00:34:02,020 --> 00:34:04,366
when they adapt to living
in inside of New York City.
697
00:34:04,366 --> 00:34:07,616
(rich thrumming music)
698
00:34:08,941 --> 00:34:09,837
Oh, there's one.
699
00:34:10,702 --> 00:34:12,702
The first white-footed mouse of the day.
700
00:34:14,250 --> 00:34:15,230
- [Narrator] For the new study,
701
00:34:15,230 --> 00:34:18,670
Jason Munshi-South and his
team have already caught more
702
00:34:18,670 --> 00:34:22,873
than 100 mice and analyzed
their genetic compositions.
703
00:34:24,880 --> 00:34:28,380
They try to take their
samples as gently as possible
704
00:34:28,380 --> 00:34:30,083
so they don't hurt the animals.
705
00:34:34,469 --> 00:34:36,210
- And we take a genetic sample.
706
00:34:36,210 --> 00:34:39,170
In this case, we will be
using this small tool.
707
00:34:39,170 --> 00:34:42,750
It's like a paper punch, but for tissue.
708
00:34:42,750 --> 00:34:46,280
And we store that for a genetic analysis.
709
00:34:46,280 --> 00:34:47,550
And we want to be able to tie
710
00:34:47,550 --> 00:34:49,210
that tissue sample to a location
711
00:34:49,210 --> 00:34:50,670
because that's important for understanding
712
00:34:50,670 --> 00:34:51,780
how they vary when they're
713
00:34:51,780 --> 00:34:53,933
in a more urban or a
less urban population.
714
00:34:57,070 --> 00:34:59,650
So now they're pretty immobile.
715
00:34:59,650 --> 00:35:00,583
This is a male.
716
00:35:02,310 --> 00:35:03,503
It's a young male.
717
00:35:04,750 --> 00:35:06,140
All right, why don't we take the ear punch
718
00:35:06,140 --> 00:35:07,177
and we'll start on the other one.
719
00:35:07,177 --> 00:35:10,190
(rich thrumming music)
720
00:35:10,190 --> 00:35:11,500
- [Narrator] Hair isn't suitable
721
00:35:11,500 --> 00:35:13,945
for comprehensive genetic analysis.
722
00:35:13,945 --> 00:35:16,862
(thoughtful music)
723
00:35:23,040 --> 00:35:25,960
After collecting the samples
and some measurements,
724
00:35:25,960 --> 00:35:27,963
the scientists release the mice.
725
00:35:29,890 --> 00:35:33,580
Genetic analysis can reveal
the evolutionary trajectories
726
00:35:33,580 --> 00:35:34,960
of the mice.
727
00:35:34,960 --> 00:35:37,020
They point to a variety of physical
728
00:35:37,020 --> 00:35:40,500
and behavioral changes
spreading among the animals,
729
00:35:40,500 --> 00:35:43,260
each of them unique to the challenges
730
00:35:43,260 --> 00:35:45,417
of each city park environment.
731
00:35:45,417 --> 00:35:48,334
(thoughtful music)
732
00:35:54,780 --> 00:35:58,623
- So we're starting to fill
in our gradient really nicely.
733
00:36:00,220 --> 00:36:02,430
So here are the mice we have
today from the Calder Center,
734
00:36:02,430 --> 00:36:03,460
and you can see it's right
735
00:36:03,460 --> 00:36:06,780
in between highly urbanized New York City.
736
00:36:06,780 --> 00:36:09,760
And then all these sites we
have up here and went out here.
737
00:36:09,760 --> 00:36:10,670
So Central Park seems
738
00:36:10,670 --> 00:36:12,780
to be our most distinct population
739
00:36:12,780 --> 00:36:13,730
to date.
- We tested it.
740
00:36:13,730 --> 00:36:14,768
- It makes sense. Yeah.
741
00:36:14,768 --> 00:36:15,980
- Yeah.
742
00:36:15,980 --> 00:36:19,030
- Most urban, probably the most isolated.
743
00:36:19,030 --> 00:36:20,570
So if you took a mouse from Central Park,
744
00:36:20,570 --> 00:36:22,537
some of its genes will be
different from a mouse outside
745
00:36:22,537 --> 00:36:24,450
in the countryside in
a big park somewhere.
746
00:36:24,450 --> 00:36:25,870
Right, so for this one in particular-
747
00:36:25,870 --> 00:36:27,750
- [Narrator] The food
supply in Central Park,
748
00:36:27,750 --> 00:36:29,986
much of it human food waste,
749
00:36:29,986 --> 00:36:32,160
might've triggered a genetic response.
750
00:36:32,160 --> 00:36:34,350
- Other places in the
city near Central Park.
751
00:36:34,350 --> 00:36:35,183
And then once you get,
752
00:36:35,183 --> 00:36:37,880
so what we've learned so
far is that one set of genes
753
00:36:37,880 --> 00:36:41,490
that are changing in the city
have to do with metabolism.
754
00:36:41,490 --> 00:36:43,650
So these white-footed
mice are eating things,
755
00:36:43,650 --> 00:36:46,520
then they have to digest them
and assimilate the nutrients.
756
00:36:46,520 --> 00:36:48,590
And we know it's evolution
because a heritable change
757
00:36:48,590 --> 00:36:50,700
in DNA sequence is evolution.
758
00:36:50,700 --> 00:36:52,030
- [Narrator] Central Park mice seem
759
00:36:52,030 --> 00:36:54,210
to have genetically
altered their metabolism
760
00:36:54,210 --> 00:36:56,770
to better digest fast food.
761
00:36:56,770 --> 00:36:59,170
- It raises several like broader questions
762
00:36:59,170 --> 00:37:02,110
about what we are doing as a species.
763
00:37:02,110 --> 00:37:05,600
As we modify the Earth's
habitat for our needs,
764
00:37:05,600 --> 00:37:08,550
how are we changing the
future of other species?
765
00:37:08,550 --> 00:37:09,640
Not only are we affecting them,
766
00:37:09,640 --> 00:37:12,390
but we're changing what they
will become in the future.
767
00:37:16,988 --> 00:37:19,160
- [Narrator] And Narragansett, Diane Nacci
768
00:37:19,160 --> 00:37:21,010
and her team are investigating
769
00:37:21,010 --> 00:37:23,780
how the different fish embryos exposed
770
00:37:23,780 --> 00:37:27,220
to the toxic PCBs have developed.
771
00:37:27,220 --> 00:37:28,387
- So, come in.
772
00:37:30,400 --> 00:37:31,820
Hi, how's it going?
- Hi.
773
00:37:31,820 --> 00:37:32,653
Really well.
774
00:37:34,300 --> 00:37:38,000
So this is the study that's
comparing Scorton Creek
775
00:37:38,000 --> 00:37:42,110
and New Bedford Harbor exposed to PCB 126.
776
00:37:42,110 --> 00:37:47,110
So this one is the group
that was treated with PCBs,
777
00:37:48,290 --> 00:37:51,730
also from the clean site, Scorton Creek.
778
00:37:51,730 --> 00:37:52,817
And as you can see,
779
00:37:52,817 --> 00:37:55,870
the PCBs have had a pretty dramatic effect
780
00:37:55,870 --> 00:37:57,810
on the development,
which is what we expect
781
00:37:57,810 --> 00:37:59,970
with these very toxic chemicals.
782
00:37:59,970 --> 00:38:00,803
- Yeah.
783
00:38:00,803 --> 00:38:02,730
And in my experience, when I see this,
784
00:38:02,730 --> 00:38:07,480
this constellation of anomalies,
it's absolutely lethal.
785
00:38:07,480 --> 00:38:10,840
There's no way that an
animal would even hatch,
786
00:38:10,840 --> 00:38:13,200
nevermind survive, after hatching
787
00:38:13,200 --> 00:38:14,890
if the heart is not functional
788
00:38:14,890 --> 00:38:17,830
and the blood is
essentially not circulating
789
00:38:17,830 --> 00:38:18,810
around the body.
790
00:38:18,810 --> 00:38:22,360
So let's take a look at
that biochemical endpoint
791
00:38:22,360 --> 00:38:27,360
to see if they are also responsive
at the biochemical level.
792
00:38:27,800 --> 00:38:30,140
- [Narrator] Using a
special contrast agent,
793
00:38:30,140 --> 00:38:32,860
the scientists can trace enzyme activity
794
00:38:32,860 --> 00:38:34,233
in the unhatched fish.
795
00:38:37,220 --> 00:38:41,580
- So you can see that the
substrate is fluorescing
796
00:38:41,580 --> 00:38:44,760
in the bladder, showing that
this enzyme system is working
797
00:38:44,760 --> 00:38:48,070
and we're getting the expected
metabolites in the bladder.
798
00:38:48,070 --> 00:38:51,100
- [Diane] That's a very
dramatic demonstration
799
00:38:51,100 --> 00:38:54,020
of enzyme activity in a living organism.
800
00:38:54,020 --> 00:38:55,510
- Mm-hmm.
801
00:38:55,510 --> 00:38:57,240
- [Narrator] The active enzymes reveal
802
00:38:57,240 --> 00:39:00,290
how the organism tries
to break down the toxin,
803
00:39:00,290 --> 00:39:02,123
but parishes in the process.
804
00:39:03,290 --> 00:39:05,840
Then the team observes how
the offspring of the fish
805
00:39:05,840 --> 00:39:08,033
from New Bedford Harbor have developed.
806
00:39:09,980 --> 00:39:13,850
- Okay, so these are fish
from New Bedford Harbor
807
00:39:13,850 --> 00:39:16,380
that were exposed to the same level of PCB
808
00:39:16,380 --> 00:39:18,300
that we were just looking at.
809
00:39:18,300 --> 00:39:20,580
As you can see with this embryo,
810
00:39:20,580 --> 00:39:22,040
it doesn't seem to have any effect.
811
00:39:22,040 --> 00:39:25,280
The heart is still beating
normally and healthy
812
00:39:25,280 --> 00:39:27,440
and it's developed really well.
813
00:39:27,440 --> 00:39:30,780
- That looks like an embryo
that's about ready to hatch.
814
00:39:30,780 --> 00:39:33,730
- [Researcher] Some of them
actually already hatched.
815
00:39:33,730 --> 00:39:35,440
- [Narrator] These fish should be dead,
816
00:39:35,440 --> 00:39:39,120
poisoned by one of the most
lethal environmental toxins.
817
00:39:39,120 --> 00:39:41,683
But life, it seems, has found a way.
818
00:39:43,000 --> 00:39:46,140
- One thing we know about
this class of chemicals is
819
00:39:46,140 --> 00:39:49,053
that in all vertebrates, including people,
820
00:39:49,940 --> 00:39:52,803
it turns on a certain enzyme pathway.
821
00:39:53,650 --> 00:39:56,990
So a normally responsive person,
822
00:39:56,990 --> 00:39:59,310
or in this case, of fish,
823
00:39:59,310 --> 00:40:02,610
should have that enzyme system turned on
824
00:40:02,610 --> 00:40:04,793
if they were exposed to PCBs.
825
00:40:05,920 --> 00:40:07,970
- [Narrator] The
contrast-enhanced image shows
826
00:40:07,970 --> 00:40:10,270
how the enzymes that normally respond
827
00:40:10,270 --> 00:40:12,803
to the toxin remain silent.
828
00:40:14,860 --> 00:40:16,560
- So in this case,
829
00:40:16,560 --> 00:40:19,490
I see very little that's glowing brightly.
830
00:40:19,490 --> 00:40:23,050
It is a dramatic visual
difference that suggests
831
00:40:23,050 --> 00:40:27,973
that that enzyme system is
broken in the New Bedford fish.
832
00:40:29,220 --> 00:40:31,240
- [Narrator] The killifish
from New Bedford Harbor
833
00:40:31,240 --> 00:40:33,370
have changed their metabolism.
834
00:40:33,370 --> 00:40:36,330
The poison can no longer harm them.
835
00:40:36,330 --> 00:40:38,197
But which genetic modifications lead
836
00:40:38,197 --> 00:40:40,773
to the fish's toxin resistance?
837
00:40:42,090 --> 00:40:43,910
That's what geneticist Mark Hahn
838
00:40:43,910 --> 00:40:46,463
of Woods Hole Institute wants to find out.
839
00:40:47,510 --> 00:40:49,880
Could this be a key to understanding
840
00:40:49,880 --> 00:40:53,620
how nature might resist
human interference?
841
00:40:53,620 --> 00:40:57,243
In the laboratory, he uses
the CRISPR-Cas method.
842
00:40:58,150 --> 00:40:59,650
- It's an incredibly powerful way
843
00:40:59,650 --> 00:41:03,870
to modify the genetics of an
experimental fish like this,
844
00:41:03,870 --> 00:41:07,060
to ask questions about the
roles of certain genes,
845
00:41:07,060 --> 00:41:09,980
and, in fact, the roles
of even single amino acids
846
00:41:09,980 --> 00:41:11,445
in the protein can be investigated
847
00:41:11,445 --> 00:41:13,780
with this CRISPR-Cas method.
848
00:41:13,780 --> 00:41:15,240
- [Narrator] To test their assumptions
849
00:41:15,240 --> 00:41:17,310
about the resistant killifish,
850
00:41:17,310 --> 00:41:21,270
Mark Hahn and his team
experiment with zebrafish.
851
00:41:21,270 --> 00:41:23,360
- I want to find out
exactly what are the changes
852
00:41:23,360 --> 00:41:26,150
in those genes, and to
be able to actually zero
853
00:41:26,150 --> 00:41:28,870
in on the specific molecular changes
854
00:41:28,870 --> 00:41:30,970
that are responsible for the resistance,
855
00:41:30,970 --> 00:41:33,790
and to be able to recreate
that in the laboratory
856
00:41:33,790 --> 00:41:37,413
to actually prove that that's
the mechanism of resistance.
857
00:41:38,310 --> 00:41:40,890
- [Narrator] They're inserting
portions of DNA taken
858
00:41:40,890 --> 00:41:45,033
from the resistant killifish
into embryos of zebrafish.
859
00:41:49,040 --> 00:41:49,873
- Hey, Mark.
- Hey, Neil.
860
00:41:49,873 --> 00:41:51,090
- How are you?
861
00:41:51,090 --> 00:41:51,923
- Good.
862
00:41:52,800 --> 00:41:53,800
- [Mark] Which ones are these?
863
00:41:53,800 --> 00:41:57,490
- [Neil] I'm injecting AIP exon two.
864
00:41:57,490 --> 00:41:58,930
- [Narrator] If the zebrafish growing
865
00:41:58,930 --> 00:42:01,860
from these eggs exhibit
the same resistance,
866
00:42:01,860 --> 00:42:05,030
they will have found
the responsible genes.
867
00:42:05,030 --> 00:42:07,650
- Here we are interested
to study a function
868
00:42:07,650 --> 00:42:10,160
of a gene known as AIP.
869
00:42:10,160 --> 00:42:11,780
So we are trying to delete this gene
870
00:42:11,780 --> 00:42:12,637
in this particular species
871
00:42:12,637 --> 00:42:15,800
and then try to study what's
the function of this gene
872
00:42:15,800 --> 00:42:19,840
and however that will alter
the resistance to PCBs.
873
00:42:22,640 --> 00:42:24,490
- [Narrator] With these experiments,
874
00:42:24,490 --> 00:42:29,060
science is venturing deep into
the source code of creation.
875
00:42:29,060 --> 00:42:31,980
The scientists believe
this research could yield
876
00:42:31,980 --> 00:42:34,740
the secret of life's ability to adapt
877
00:42:34,740 --> 00:42:37,760
to the most extreme conditions.
878
00:42:37,760 --> 00:42:40,850
And this knowledge could
also help other creatures
879
00:42:40,850 --> 00:42:44,503
to adapt and survive in
a rapidly changing world.
880
00:42:49,980 --> 00:42:52,620
- I think we will understand the extent
881
00:42:52,620 --> 00:42:55,360
to which we can extrapolate our knowledge
882
00:42:55,360 --> 00:42:58,240
from the killifish system out beyond
883
00:42:58,240 --> 00:43:01,290
to other fish and even other vertebrates.
884
00:43:01,290 --> 00:43:05,940
So a broader understanding of
the toxicology of pollutants
885
00:43:05,940 --> 00:43:09,400
and how that will impact
the natural world.
886
00:43:09,400 --> 00:43:11,070
How we can understand what will be
887
00:43:11,070 --> 00:43:12,618
the most vulnerable species.
888
00:43:12,618 --> 00:43:15,535
(mysterious music)
889
00:43:18,081 --> 00:43:20,790
- [Narrator] At the Max
Planck Institute in Potsdam,
890
00:43:20,790 --> 00:43:24,510
the research team processes
the clover samples from Berlin.
891
00:43:24,510 --> 00:43:27,420
Their goal, to find cyanide.
892
00:43:27,420 --> 00:43:29,337
Clover plants that produce cyanide
893
00:43:29,337 --> 00:43:31,920
are better protected against predators,
894
00:43:31,920 --> 00:43:34,990
but are less able to tolerate cold.
895
00:43:34,990 --> 00:43:37,000
It's warmer in city centers,
896
00:43:37,000 --> 00:43:39,693
so this clover might be more common there.
897
00:43:41,114 --> 00:43:42,270
(Stephan speaking in foreign language)
898
00:43:42,270 --> 00:43:44,160
- [Voiceover] This is a qualitative test.
899
00:43:44,160 --> 00:43:46,880
We use it to indirectly
detect a specific gene
900
00:43:46,880 --> 00:43:48,303
that generates this cyanide.
901
00:43:53,210 --> 00:43:55,340
- [Voiceover] So these are both rural?
902
00:43:55,340 --> 00:43:57,333
- [Voiceover] Yeah,
they're both still rural.
903
00:44:00,207 --> 00:44:02,590
- [Narrator] Greiner and
his team send their results
904
00:44:02,590 --> 00:44:05,600
and other clover specimens to Marc Johnson
905
00:44:05,600 --> 00:44:07,053
in his Toronto lab.
906
00:44:10,840 --> 00:44:12,680
- [Marc] Hey gang, how's it going?
907
00:44:12,680 --> 00:44:13,800
- Good.
908
00:44:13,800 --> 00:44:14,836
- Bita, how did that
extraction go yesterday?
909
00:44:14,836 --> 00:44:15,930
- It was good. Yeah.
- Yeah.
910
00:44:15,930 --> 00:44:20,753
So remind me, this is
Berlin and Buenos Aires.
911
00:44:21,870 --> 00:44:23,590
- [Narrator] The team prepares the clover
912
00:44:23,590 --> 00:44:25,360
for gene sequencing,
913
00:44:25,360 --> 00:44:27,590
but the cyanide values taken by the team
914
00:44:27,590 --> 00:44:29,430
in Germany should show
915
00:44:29,430 --> 00:44:32,880
whether the clover has adapted
an urban existence already.
916
00:44:32,880 --> 00:44:36,790
- Okay, Bita. Did we get
the data from Berlin?
917
00:44:36,790 --> 00:44:37,623
- [Bita] Yes, we did.
918
00:44:37,623 --> 00:44:39,470
And this screen here it is.
919
00:44:39,470 --> 00:44:40,998
So I think it's really good.
- Great.
920
00:44:40,998 --> 00:44:41,831
Okay.
921
00:44:41,831 --> 00:44:43,500
James, have you had a chance to look
922
00:44:43,500 --> 00:44:45,350
at the data from Berlin
923
00:44:45,350 --> 00:44:47,450
so we can understand how
the environment's changing
924
00:44:47,450 --> 00:44:50,160
from Downtown Berlin through the suburbs
925
00:44:50,160 --> 00:44:51,516
and into the rural areas?
926
00:44:51,516 --> 00:44:52,349
You got it.
927
00:44:52,349 --> 00:44:53,853
- All right. So let's take a look at.
928
00:44:55,160 --> 00:44:56,670
So Berlin is one of the cities
929
00:44:56,670 --> 00:45:01,030
where we see white clover
adapting to urban rural gradients.
930
00:45:01,030 --> 00:45:01,863
- [James] Yeah.
931
00:45:01,863 --> 00:45:02,696
- [Marc] Nice.
932
00:45:02,696 --> 00:45:04,620
And so now we're at about 33% of cities
933
00:45:04,620 --> 00:45:06,690
where white clover adapts?
934
00:45:06,690 --> 00:45:08,106
- Maybe 33.29.
935
00:45:08,106 --> 00:45:09,952
(Marc laughs)
936
00:45:09,952 --> 00:45:10,960
But yeah.
- Fair enough.
937
00:45:10,960 --> 00:45:11,793
- [James] It's about 33%.
938
00:45:11,793 --> 00:45:12,650
- Okay.
939
00:45:12,650 --> 00:45:13,930
So then next I think what we're gonna have
940
00:45:13,930 --> 00:45:15,940
to do is figure out what are the drivers,
941
00:45:15,940 --> 00:45:17,840
the environmental drivers
of this adaptation.
942
00:45:17,840 --> 00:45:19,620
So that's really cool.
943
00:45:19,620 --> 00:45:22,450
- [Narrator] In Berlin, plants
from downtown a more likely
944
00:45:22,450 --> 00:45:26,040
to produce cyanide, as
is the case in a third
945
00:45:26,040 --> 00:45:28,560
of the city surveyed so far.
946
00:45:28,560 --> 00:45:31,113
An indication of parallel evolution?
947
00:45:35,640 --> 00:45:39,200
- Some of the preliminary
insights are fascinating.
948
00:45:39,200 --> 00:45:40,800
So it really looks like,
949
00:45:40,800 --> 00:45:43,550
regardless of where you are in the world,
950
00:45:43,550 --> 00:45:47,300
whether you're in Europe,
North America, Japan,
951
00:45:47,300 --> 00:45:50,210
China, Australia, New Zealand,
952
00:45:50,210 --> 00:45:54,160
we see the ability for
this humble white clover
953
00:45:54,160 --> 00:45:56,073
to adapt to these cities.
954
00:45:57,110 --> 00:45:59,020
- [Narrator] In the warmth of the city,
955
00:45:59,020 --> 00:46:02,943
cyanide-producing clover stands
a better chance of survival.
956
00:46:06,080 --> 00:46:08,280
But to survive in the city,
957
00:46:08,280 --> 00:46:11,930
all organisms must adapt
to higher temperatures.
958
00:46:11,930 --> 00:46:14,567
What scientists call "heat islands."
959
00:46:18,810 --> 00:46:22,640
- In cities, humans and
their machinery creates
960
00:46:22,640 --> 00:46:25,930
a lot of heat, and we
have a bubble of hot air
961
00:46:25,930 --> 00:46:26,950
in large cities.
962
00:46:26,950 --> 00:46:29,870
A city of more than a
million people can be seven,
963
00:46:29,870 --> 00:46:31,273
eight degrees Celsius hotter
964
00:46:32,200 --> 00:46:34,530
in the center of the city
than outside of the city.
965
00:46:34,530 --> 00:46:37,430
- [Narrator] This, Menno
Schilthuizen believes,
966
00:46:37,430 --> 00:46:41,333
also influences the evolution
of the white-lipped snail.
967
00:46:42,220 --> 00:46:44,760
Their shells come in many shades
968
00:46:44,760 --> 00:46:47,030
from brown to pale yellow.
969
00:46:47,030 --> 00:46:49,323
A single gene determines the color.
970
00:46:50,320 --> 00:46:53,220
- So they basically carry
their genes on their back.
971
00:46:53,220 --> 00:46:57,280
The shell color determines
the internal temperature
972
00:46:57,280 --> 00:46:59,740
of the snail to some extent.
973
00:46:59,740 --> 00:47:04,030
The difference in temperature
inside can be two degrees
974
00:47:04,030 --> 00:47:05,370
under the same conditions.
975
00:47:05,370 --> 00:47:07,390
And that could be just the difference
976
00:47:07,390 --> 00:47:08,450
between life or death.
977
00:47:08,450 --> 00:47:09,740
On a hot summer day,
978
00:47:09,740 --> 00:47:12,950
you know it was 40 degrees
in Amsterdam a few weeks ago,
979
00:47:12,950 --> 00:47:16,420
it could be that some of
these yellow snails survived,
980
00:47:16,420 --> 00:47:19,560
but many of the brown ones
died because they got too hot,
981
00:47:19,560 --> 00:47:21,860
they overheated, and they died.
982
00:47:21,860 --> 00:47:25,071
- [Narrator] But will statistics
confirm this hypothesis?
983
00:47:25,071 --> 00:47:30,071
- Snails are evolving
towards more yellow shelling.
984
00:47:30,350 --> 00:47:34,590
So the plan is now to just
add some data to the dataset.
985
00:47:34,590 --> 00:47:36,053
So let's go.
986
00:47:37,260 --> 00:47:39,210
- [Narrator] In order
to collect and evaluate
987
00:47:39,210 --> 00:47:42,300
as many snails as possible
throughout Europe,
988
00:47:42,300 --> 00:47:45,473
Menno Schilthuizen is
helped by volunteers.
989
00:47:47,360 --> 00:47:49,160
- You know, you don't have
to go to the Galapagos
990
00:47:49,160 --> 00:47:51,850
to study evolution or
become a paleontologist.
991
00:47:51,850 --> 00:47:53,860
It's happening everywhere all the time.
992
00:47:53,860 --> 00:47:57,963
It's a continuous, very
normal biological process.
993
00:47:59,030 --> 00:48:01,180
- [Narrator] This time
the volunteers find only
994
00:48:01,180 --> 00:48:03,060
a few life snails,
995
00:48:03,060 --> 00:48:06,730
but empty snail shells
can also provide data.
996
00:48:06,730 --> 00:48:08,980
The snail shells are photographed
997
00:48:08,980 --> 00:48:11,340
and added to the database with an app
998
00:48:11,340 --> 00:48:13,943
that anyone can install
on their mobile phone.
999
00:48:17,800 --> 00:48:19,960
- If we're looking at the adaptations
1000
00:48:19,960 --> 00:48:23,650
of urban animals and plants
to the urban heat islands,
1001
00:48:23,650 --> 00:48:25,300
which, of course, is happening,
1002
00:48:25,300 --> 00:48:27,790
has been happening more rapidly
than global climate change,
1003
00:48:27,790 --> 00:48:31,470
we can probably predict what's
going to happen globally
1004
00:48:31,470 --> 00:48:33,123
in response to climate change.
1005
00:48:34,027 --> 00:48:36,490
- [Narrator] With
temperatures rising globally,
1006
00:48:36,490 --> 00:48:38,220
our cities become a window
1007
00:48:38,220 --> 00:48:41,103
into nature's future transformations.
1008
00:48:42,360 --> 00:48:45,670
Every October in Mexico's Sierra Nevada,
1009
00:48:45,670 --> 00:48:49,470
monarch butterflies
gather in their millions.
1010
00:48:49,470 --> 00:48:52,980
They traverse the whole of
the North American continent
1011
00:48:52,980 --> 00:48:54,763
to spend winter down south.
1012
00:48:56,570 --> 00:48:58,010
But our growing cities make
1013
00:48:58,010 --> 00:48:59,993
their journey ever more perilous.
1014
00:49:01,190 --> 00:49:04,413
- Monarch butterflies are
these really great insects.
1015
00:49:05,320 --> 00:49:08,190
Unfortunately, right
now they're in decline.
1016
00:49:08,190 --> 00:49:09,930
In the United States,
1017
00:49:09,930 --> 00:49:14,050
they've experienced 80%
population declines.
1018
00:49:14,050 --> 00:49:14,883
There we go.
1019
00:49:14,883 --> 00:49:17,940
- In this industrial area of Toronto,
1020
00:49:17,940 --> 00:49:21,863
monarch butterflies take a
rest stop before flying on.
1021
00:49:23,020 --> 00:49:26,523
They also take the opportunity
to mate and reproduce.
1022
00:49:26,523 --> 00:49:30,600
- Ooh, it's a really big caterpillar.
1023
00:49:30,600 --> 00:49:34,090
This is the baby monarch.
1024
00:49:34,090 --> 00:49:36,600
This one's probably a day or two away
1025
00:49:36,600 --> 00:49:39,230
from going into its chrysalis
1026
00:49:39,230 --> 00:49:42,530
and then becoming a monarch butterfly.
1027
00:49:42,530 --> 00:49:44,650
- [Narrator] While other
species have the ability
1028
00:49:44,650 --> 00:49:47,360
to switch to other food sources,
1029
00:49:47,360 --> 00:49:50,993
monarch butterflies remained
dependent on a single plant.
1030
00:49:53,320 --> 00:49:54,670
- [Man] I got one.
1031
00:49:54,670 --> 00:49:58,183
- Let's check it out. You found a monarch.
1032
00:50:00,290 --> 00:50:03,620
- [Narrator] The butterflies
lay their eggs on the milkweed.
1033
00:50:03,620 --> 00:50:07,230
Their caterpillars feed
exclusively on this plant.
1034
00:50:07,230 --> 00:50:08,830
And in many cities,
1035
00:50:08,830 --> 00:50:12,453
the land on which milkweed
can grow is disappearing.
1036
00:50:15,340 --> 00:50:18,460
- Unfortunately, a lot of
the cities are providing
1037
00:50:18,460 --> 00:50:21,000
these barriers that just
don't have the resources
1038
00:50:21,000 --> 00:50:22,250
that they need.
1039
00:50:22,250 --> 00:50:24,840
And so it would basically be
1040
00:50:24,840 --> 00:50:26,700
if you're driving along the road
1041
00:50:26,700 --> 00:50:29,110
and you have any fuel stations
1042
00:50:29,110 --> 00:50:31,863
and you run out of gas, you're stuck,
1043
00:50:32,710 --> 00:50:35,860
then that's what's happening
with these butterflies.
1044
00:50:35,860 --> 00:50:38,520
- [Narrator] Not all species can adapt.
1045
00:50:38,520 --> 00:50:41,020
As our cities continue to expand,
1046
00:50:41,020 --> 00:50:43,683
accommodating wildlife might be crucial.
1047
00:50:44,640 --> 00:50:48,750
How we shape our cities in
the future may prove decisive
1048
00:50:48,750 --> 00:50:51,700
for the course of life on earth.
1049
00:50:51,700 --> 00:50:54,950
- Biodiversity helps us
with the food that we eat.
1050
00:50:54,950 --> 00:50:57,280
It helps us with the air that we breathe.
1051
00:50:57,280 --> 00:51:00,920
So if we continue along
the path that we have,
1052
00:51:00,920 --> 00:51:04,830
many different populations,
including human populations,
1053
00:51:04,830 --> 00:51:06,283
will start to crash.
1054
00:51:07,510 --> 00:51:11,950
- Urban evolution can help
us design green cities
1055
00:51:11,950 --> 00:51:13,623
in a Darwinian way.
1056
00:51:15,080 --> 00:51:19,240
- As humans become more urban,
we have the potential to,
1057
00:51:19,240 --> 00:51:20,960
you know, allow some
species to live in the city
1058
00:51:20,960 --> 00:51:22,130
and adapt to our cities,
1059
00:51:22,130 --> 00:51:25,760
but then put less pressure
on the other habitats,
1060
00:51:25,760 --> 00:51:26,620
which would allow, you know,
1061
00:51:26,620 --> 00:51:28,680
the species that can't survive in the city
1062
00:51:28,680 --> 00:51:29,873
to continue to thrive.
1063
00:51:31,860 --> 00:51:34,880
- We're going to see more
and more the realization
1064
00:51:34,880 --> 00:51:37,500
that we are part of nature,
1065
00:51:37,500 --> 00:51:41,098
and that is actually probably
going to help us survive.
1066
00:51:41,098 --> 00:51:43,765
(elegant music)
79735
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