00:00:09.843 --> 00:00:12.470
If any living species
is to inherit the Earth,

00:00:12.470 --> 00:00:15.473
it will not be man.

00:00:18.268 --> 00:00:20.645
Long before the time that
hydrogen bombs and pollution

00:00:20.645 --> 00:00:23.648
have put an end to us, we will face
competition for the Earth itself

00:00:23.690 --> 00:00:26.693
from a life form we arrogantly ignore.

00:00:28.236 --> 00:00:29.738
We will be overrun,

00:00:29.738 --> 00:00:33.992
Deposed and succeeded by an army
that was here long before us

00:00:33.992 --> 00:00:37.829
and is ultimately better
equipped to survive than we.

00:00:37.829 --> 00:00:41.041
battalions of mindless soldiers
entering the contest with capabilities

00:00:41.082 --> 00:00:44.085
beyond our imagination.

00:00:45.462 --> 00:00:48.173
I tell you, gentlemen,
science has agreed

00:00:48.173 --> 00:00:51.217
that unless something is done,
and done quickly,

00:00:51.217 --> 00:00:55.680
Man as the dominant species of life
on Earth will be extinct within a year.

00:00:56.723 --> 00:00:59.726
Yes, I'm talking about insects.

00:00:59.893 --> 00:01:02.520
And if you at this moment
dare to think this is lunacy,

00:01:03.646 --> 00:01:06.232
I invite you to remain in your seat,

00:01:06.232 --> 00:01:09.235
draw your own conclusion,

00:01:09.486 --> 00:01:12.489
and learn the inevitable
destiny of ignorance.

00:01:15.700 --> 00:01:18.703
We may be witnesses to a
biblical prophecy come true.

00:01:18.995 --> 00:01:21.915
And the beasts shall reign
over the Earth.

00:01:21.915 --> 00:01:22.665
Attention!

00:01:22.666 --> 00:01:25.469
You have 60 seconds to
clear the street.

00:01:25.472 --> 00:01:27.672
We are bringing through a
swarm of killer bees.

00:01:34.803 --> 00:01:36.554
Insects are far and away

00:01:36.554 --> 00:01:40.600
our greatest rivals in the struggle
for survival and mastery of the Earth.

00:01:41.101 --> 00:01:44.854
We must fight our insect enemies
with every weapon

00:01:44.854 --> 00:01:47.857
our imagination and science can devise.

00:02:49.171 --> 00:02:52.297
These are, I must admit they're
one of my favorite veg to grow

00:02:52.297 --> 00:02:53.965
'cause they're so easy.

00:02:53.965 --> 00:02:56.968
You basically just harvest them.

00:02:57.844 --> 00:03:00.680
Are you supposed to chop the
flowers off to get more tubers?

00:03:00.680 --> 00:03:01.514
But I never do.

00:03:01.514 --> 00:03:04.058
I just leave them to flower
and it doesn't seem to make any...

00:03:04.058 --> 00:03:07.187
Well, we get plenty of tubers
as you can see, so.

00:03:08.563 --> 00:03:10.064
Seems like a bit of a waste of time.

00:03:10.064 --> 00:03:12.525
Cheating the bees of the flowers.

00:03:12.525 --> 00:03:15.128
Oh, bugger.

00:03:20.533 --> 00:03:23.411
There is just something
really satisfying

00:03:23.411 --> 00:03:26.414
about growing your own food.

00:03:27.582 --> 00:03:30.585
My dad was a really keen
vegetable gardener,

00:03:31.544 --> 00:03:34.505
so maybe I got it partly from him.

00:03:35.298 --> 00:03:39.594
They gave me a little corner of my garden
when I was 6 or 7 years old, I guess.

00:03:40.345 --> 00:03:42.764
I'm actually made a
bumble bee nesting home.

00:03:42.764 --> 00:03:46.184
Never got any bumble bees going into it,

00:03:46.184 --> 00:03:48.787
but that was the hope.

00:03:49.229 --> 00:03:53.441
But also, growing flowers to attract
bees and so on is kind of fun.

00:03:53.441 --> 00:03:57.779
You know, quite rewarding
when are growing some little seedlings

00:03:57.779 --> 00:03:59.030
and seeing them grow up,

00:03:59.030 --> 00:04:01.157
and then you see bees buzzing around.

00:04:01.157 --> 00:04:03.451
Oh, there's a tree bumble bee.
Really pretty.

00:04:03.451 --> 00:04:07.163
Sorry, just getting distracted by
all these queen bees buzzing about.

00:04:07.413 --> 00:04:09.999
I have the dubious claim to fame of

00:04:09.999 --> 00:04:13.753
being the first person to catch a
tree bumble bee in the UK.

00:04:20.885 --> 00:04:23.263
You just watch a bee flying about.

00:04:23.263 --> 00:04:26.266
She often goes up to a flower
but doesn't land on it.

00:04:26.432 --> 00:04:29.936
She gets really close with her
antennae out and at the last second

00:04:30.311 --> 00:04:33.773
veers away, and she might do that
two or three times before she actually

00:04:34.482 --> 00:04:36.985
lands on the flower and puts her
tongue inside and drinks the nectar.

00:04:36.985 --> 00:04:39.112
And I just thought,
what's wrong with the flowers

00:04:39.112 --> 00:04:42.115
she's not landing on.

00:04:45.451 --> 00:04:50.832
Bascially, they're sniffing the flowers
for the whiff of a previous bee visitor.

00:04:50.832 --> 00:04:54.085
So every time a bee touches a flower,
they accidentally leave

00:04:54.085 --> 00:04:57.422
a little smear of hydrocarbons
on the petals.

00:04:57.839 --> 00:05:01.175
It's a queue, so any bee that then
comes along shortly afterwards,

00:05:01.259 --> 00:05:04.268
if they smell that a bee's recently
visited that flower,

00:05:04.270 --> 00:05:05.346
they know that there won't
be any nectar

00:05:05.346 --> 00:05:07.015
because the earlier bee
will have taken it,

00:05:07.015 --> 00:05:10.018
so there's no point in wasting their time
landing and putting their tongue inside.

00:05:10.268 --> 00:05:11.769
So they just give the flower
a quick sniff,

00:05:11.769 --> 00:05:14.105
and if they can't smell a bee
they land and feed.

00:05:14.105 --> 00:05:16.232
If they can, they go on
and try and find another one.

00:05:17.652 --> 00:05:21.654
Nobody knew they did that
until we worked it out, so.

00:05:21.654 --> 00:05:24.657
But by the time I'd finished with that...

00:05:24.782 --> 00:05:27.702
Well, there's another solitary bee
just landed on the lid and it's a female

00:05:27.702 --> 00:05:31.664
with pollen all over her legs,
and that's some kind of mining bee.

00:05:31.664 --> 00:05:34.375
But I couldn't without getting a
closer look tell you which one.

00:05:34.375 --> 00:05:35.999
Oh, oh, hang on, sorry.

00:05:36.001 --> 00:05:38.588
There's a black bee
buzzing around in here.

00:05:39.297 --> 00:05:40.340
It's called the...

00:05:40.340 --> 00:05:44.997
It's, that's a female of a thing called
the hairy footed flower bee,

00:05:44.999 --> 00:05:46.095
which is a great name.

00:05:46.095 --> 00:05:50.716
Because the males have
really hairy feet and...

00:05:50.999 --> 00:05:56.899
I've always kind of been slightly
obsessed by bugs.

00:05:57.398 --> 00:06:00.068
E.O. Wilson,
the American entomologist,

00:06:00.068 --> 00:06:03.488
he said everyone has a bug phase
but he just never grew out of his.

00:06:03.488 --> 00:06:05.114
And I guess I'm the same.

00:06:05.114 --> 00:06:07.075
I was just born that way,
I don't know.

00:06:07.075 --> 00:06:11.371
You know, some people are interested
in being a train driver or an astronaut.

00:06:11.371 --> 00:06:13.331
I just wanted to chase
around after bugs, really.

00:06:53.413 --> 00:06:58.399
I started as a nine-year-old.

00:06:58.793 --> 00:07:02.753
I got the idea very quickly from
reading National Geographic,

00:07:02.755 --> 00:07:06.050
and visiting the zoo and
then the Smithsonian,

00:07:06.092 --> 00:07:09.637
that it would be a wonderful life
to be a naturalist.

00:07:10.388 --> 00:07:14.434
And I had my stepmother
make a butterfly net,

00:07:15.184 --> 00:07:19.689
and I started collecting,
identifying and

00:07:20.565 --> 00:07:24.309
enthusiastically learning everything
I could about butterflies.

00:07:28.899 --> 00:07:34.287
In fact I was then already an
enthusiast for studying biodiversity,

00:07:34.287 --> 00:07:38.458
the variety of of living forms,
especially insects.

00:07:49.093 --> 00:07:53.055
Every species is a source of marvels

00:07:53.848 --> 00:07:56.051
and evolution.

00:07:58.394 --> 00:08:02.815
So I have a special concern
and affection

00:08:03.399 --> 00:08:06.402
for the little creatures
that run the Earth.

00:08:13.451 --> 00:08:16.746
They and their enormous millions,

00:08:17.497 --> 00:08:21.459
millions of millions,
are supporting the quality

00:08:21.459 --> 00:08:25.379
of the natural environment
that we all enjoy most.

00:08:28.075 --> 00:08:32.178
I just feel they need looking after.

00:08:41.938 --> 00:08:45.566
♪ God bless the grass
that grows through the cracks ♪

00:08:45.942 --> 00:08:49.153
♪ They try to pave 'em over
and try to push 'em back ♪

00:08:49.487 --> 00:08:53.282
♪ But the grass knows just
what it's supposed to do ♪

00:08:53.533 --> 00:08:56.410
♪ It pushes and heaves and
the grass comes through ♪

00:08:56.410 --> 00:08:58.120
♪ And God bless the grass ♪

00:08:58.120 --> 00:08:59.747
That's an approximation of the lyrics.

00:08:59.747 --> 00:09:02.750
It's not exact.

00:09:22.478 --> 00:09:25.523
I began the project back
in the early '70s.

00:09:26.232 --> 00:09:28.067
Beautiful trees.

00:09:28.067 --> 00:09:31.696
I had the project in the back of
my mind and what I needed

00:09:32.238 --> 00:09:36.075
was to be in one place
for at least five years

00:09:36.993 --> 00:09:41.122
to generate a sufficient amount of
data to do what I wanted to do.

00:09:43.708 --> 00:09:46.419
Okay, these are button bushes here,

00:09:46.419 --> 00:09:49.422
but button bushes are really good
nectar source.

00:09:51.841 --> 00:09:52.967
I wanted to know

00:09:52.967 --> 00:09:56.345
what are the factors in the environment

00:09:56.596 --> 00:10:00.099
that impact the timing of
butterfly life cycles?

00:10:01.559 --> 00:10:03.978
That's a female looking to lay eggs.

00:10:03.978 --> 00:10:07.189
They live a very long time
because they're toxic to predators,

00:10:07.189 --> 00:10:10.192
so the adults can live
four to six weeks.

00:10:11.319 --> 00:10:13.070
So there I was,

00:10:13.070 --> 00:10:16.032
I was set up to do a five year project,

00:10:16.699 --> 00:10:20.745
and now it's 46 years and still going.

00:10:21.996 --> 00:10:24.999
Ooh, Workman's admiral.

00:10:25.416 --> 00:10:27.619
Number 20.

00:10:42.141 --> 00:10:45.311
Many people don't really like
insects very much.

00:10:45.311 --> 00:10:48.439
They think they're annoying,
bitey, sting-y things.

00:10:52.026 --> 00:10:53.819
They tend to be harder to identify,

00:10:53.819 --> 00:10:57.573
which is also an obstacle to people
paying much attention to them.

00:10:57.573 --> 00:10:58.991
There's so many of them.

00:10:58.991 --> 00:11:03.037
There are almost certainly several
thousand species of insect just

00:11:03.037 --> 00:11:06.832
living in this garden here, and most
people can't identify most of them.

00:11:07.041 --> 00:11:08.376
I can't identify most of them

00:11:08.376 --> 00:11:12.004
and I'm a professional entomologist,
so I think that's one of the reasons

00:11:12.004 --> 00:11:14.548
why nobody's paying too much
attention to them.

00:11:18.052 --> 00:11:19.512
Life is all connected together,

00:11:19.512 --> 00:11:21.472
but insects make up the bulk of life,

00:11:21.472 --> 00:11:24.475
the bulk of species.

00:11:25.309 --> 00:11:28.312
Two thirds of the life that we
know of are insects,

00:11:28.646 --> 00:11:31.607
and almost all of the rest of life
on Earth depends on insects.

00:11:31.607 --> 00:11:34.402
one way or another.

00:11:34.402 --> 00:11:37.238
87% of the world's flowering plants

00:11:37.238 --> 00:11:40.950
need pollinating by some kind of
animal, and usually it's an insect.

00:11:40.950 --> 00:11:43.953
More often than not, it's a bee.

00:11:44.245 --> 00:11:45.871
But that's not all that insects do.

00:11:45.871 --> 00:11:49.458
They're food for most bird species,

00:11:49.834 --> 00:11:53.295
for frogs, lizards, bats.

00:11:53.879 --> 00:11:56.331
But then there's other stuff
that insects do as well, of course

00:11:56.333 --> 00:11:58.968
They're really important at
recycling nutrients,

00:11:59.135 --> 00:12:02.138
breaking down animal dung and
dead bodies and so on.

00:12:02.722 --> 00:12:04.640
The landscape would be
covered in cow pats

00:12:04.640 --> 00:12:08.352
if we didn't have flies and dung beetles
to come along and clear them away.

00:12:09.228 --> 00:12:12.065
They do so many different things
so they're kind of, if you like,

00:12:12.068 --> 00:12:13.967
the glue of life.

00:12:16.068 --> 00:12:18.612
These insects are performing
a myriad of functions,

00:12:18.612 --> 00:12:21.824
not just pollination
but also pest control,

00:12:21.824 --> 00:12:23.783
and they're moving seeds around,

00:12:23.783 --> 00:12:26.637
they're engineering
underneath the ground,

00:12:26.639 --> 00:12:29.623
the termites and the ants are
having a major effect.

00:12:29.623 --> 00:12:32.626
They're just doing so many
different things in the ecosystem.

00:12:35.047 --> 00:12:38.883
The estimate now is 3.4 million
species of insects.

00:12:38.924 --> 00:12:40.009
Every summer it happens,

00:12:40.009 --> 00:12:43.345
I collect a moth in my backyard
that is not described yet.

00:12:43.971 --> 00:12:45.890
That's just knowing what it is.

00:12:45.890 --> 00:12:46.724
What does it do?

00:12:46.724 --> 00:12:47.600
What does it eat?

00:12:47.600 --> 00:12:49.811
Out of the 12,000 moths
that we know about,

00:12:49.813 --> 00:12:53.564
we only know the host plants
for 7000 of them.

00:12:53.564 --> 00:12:56.567
That's not knowing very much about 'em.

00:12:57.443 --> 00:12:59.999
96% of our birds rear their
young on insects,

00:13:00.002 --> 00:13:01.822
and most of those insects
are caterpillars.

00:13:01.822 --> 00:13:05.493
Takes 6,000 to 9,000 caterpillars
to make one clutch of chickadees.

00:13:05.868 --> 00:13:06.999
So we're talking about lots and lots

00:13:07.001 --> 00:13:09.872
of caterpillars required to drive
just the bird food web.

00:13:09.914 --> 00:13:11.248
And that's just an example.

00:13:16.170 --> 00:13:17.171
The insects

00:13:17.171 --> 00:13:20.716
and the plants that they
both pollinate and eat

00:13:21.050 --> 00:13:24.053
are the fabric of the planet.

00:13:28.808 --> 00:13:31.393
About one third of our food

00:13:31.393 --> 00:13:33.938
comes from pollination,

00:13:33.938 --> 00:13:36.941
almost exclusively from insects.

00:13:41.028 --> 00:13:44.657
There's a lot of complexity in
the behavior of these pollinators.

00:13:45.074 --> 00:13:47.827
They learn about each type of
flower that they visit.

00:13:47.827 --> 00:13:51.872
They are updating the information
that they're gathering all the time.

00:13:51.872 --> 00:13:53.624
They're learning from
their own experience,

00:13:53.624 --> 00:13:57.753
from the experience of others,
and integrating all that information

00:13:57.753 --> 00:14:00.756
despite the fact that in some cases
they only live a few weeks.

00:14:01.924 --> 00:14:04.343
It matters how they respond
to their environment

00:14:04.343 --> 00:14:06.554
and how they can deal
with that environment.

00:14:06.554 --> 00:14:08.848
And obviously,
if we change the environment,

00:14:08.848 --> 00:14:12.768
that's going to affect their
ability to thrive, to forage

00:14:12.768 --> 00:14:14.645
and to pollinate in those
kind of conditions,

00:14:16.648 --> 00:14:19.400
They're incredibly attuned to
information that we have no access to.

00:14:19.817 --> 00:14:21.694
So, they see flowers very differently.

00:14:21.694 --> 00:14:25.489
They start to see patterning
like nectar guides, which are heavily

00:14:25.489 --> 00:14:29.285
UV absorbing or UV reflecting,
so they're kind of big arrows to say,

00:14:29.493 --> 00:14:32.496
"Come here, land here, food in here."

00:14:36.794 --> 00:14:40.713
Everything inadvertently pollinates.
Bees don't set out to pollinate.

00:14:40.713 --> 00:14:43.757
They don't care what happens to
the plant, they're after the food.

00:14:43.757 --> 00:14:47.094
They're collecting the pollen,
or the nectar, or sometimes both.

00:14:47.177 --> 00:14:50.222
And in doing so,
in moving from flower to flower,

00:14:50.222 --> 00:14:54.268
they accidentally pollinate the flowers
as do butterflies, moths,

00:14:54.685 --> 00:14:58.522
hoverflies, wasps, beetles,
all sorts of other insects.

00:14:59.607 --> 00:15:02.985
These are more or less the only insects
that specialize in feeding on pollen

00:15:02.985 --> 00:15:07.281
and nectar right through their life,
so things like hoverflies and wasps

00:15:07.489 --> 00:15:10.492
will drink a bit of nectar
and maybe eat a bit of pollen,

00:15:10.618 --> 00:15:13.829
but they don't take it home to
feed to their offspring, whereas bees,

00:15:14.163 --> 00:15:17.166
from the day they hatch from their egg
to the day they die,

00:15:17.166 --> 00:15:18.959
all they eat is nectar and pollen.

00:15:18.959 --> 00:15:20.419
So they have to visit lots of flowers,

00:15:20.419 --> 00:15:22.296
and that's why they're kind of the

00:15:22.296 --> 00:15:26.175
most important pollinators
for most crops and for most flowers.

00:15:31.221 --> 00:15:34.808
Hardly any of these berries
are fit to eat yet.

00:15:35.559 --> 00:15:38.562
Here's a few that are kind of ripe,
but they look real dry.

00:15:41.941 --> 00:15:43.400
When we're in the woods,

00:15:43.400 --> 00:15:46.362
they'll be alot juicer if they're ripe.

00:15:52.785 --> 00:15:55.788
I had an individual childhood.

00:15:57.081 --> 00:15:59.500
My parents had a miserable marriage.

00:15:59.500 --> 00:16:01.460
They fought all the time.

00:16:01.460 --> 00:16:04.421
The atmosphere around
the house was terrible.

00:16:04.797 --> 00:16:08.592
So it was a matter of, as a kid,
getting the hell out of there.

00:16:09.885 --> 00:16:13.514
And I spent as much
time as I could alone

00:16:13.681 --> 00:16:16.684
walking in the woods.

00:16:18.060 --> 00:16:21.063
And I had many interests as a kid,

00:16:21.730 --> 00:16:24.733
but somehow I locked on
to butterflies.

00:16:25.067 --> 00:16:26.610
And here I am.

00:16:26.610 --> 00:16:31.073
I'm 72 years old and I'm still
doing the same stuff

00:16:31.073 --> 00:16:34.076
I did as a kid.

00:16:34.159 --> 00:16:36.412
This is a butterfly singles bar.

00:16:37.371 --> 00:16:38.789
Male swallowtails come

00:16:38.789 --> 00:16:42.626
to openings in the woods
to meet females.

00:16:42.626 --> 00:16:47.297
The females are genetically programed
to come to these places to get mated.

00:16:48.465 --> 00:16:52.011
Once the female has mated,
she leaves and she doesn't come back,

00:16:52.720 --> 00:16:56.640
but the male will come back day after day,
and some days he gets lucky

00:16:56.640 --> 00:16:59.643
and some days he doesn't.

00:17:12.239 --> 00:17:14.366
Butterflies are prominent

00:17:14.366 --> 00:17:17.369
in people's imaginations.

00:17:17.745 --> 00:17:19.371
Your heartbeat accelerates.

00:17:19.371 --> 00:17:22.332
You may break out in a sweat.

00:17:22.750 --> 00:17:25.419
And that seems to be
a general characteristic

00:17:25.419 --> 00:17:28.881
of enthusiasts about anything,
whether it's butterflies

00:17:28.964 --> 00:17:32.593
or whatever the hell it is,
it gives you a physiological rush.

00:17:33.093 --> 00:17:36.096
Ooh, Tiger swallowtail.

00:17:36.096 --> 00:17:39.099
Ooh, Workman's admiral.

00:17:39.099 --> 00:17:41.477
Eastern tailed-blue, comyntas.

00:17:41.477 --> 00:17:42.895
Ooh.

00:17:42.895 --> 00:17:44.438
Potius parnassian

00:17:44.438 --> 00:17:46.815
Ooh, West Virginia lady.

00:17:46.815 --> 00:17:48.400
Now it's interacting with a male.

00:17:48.400 --> 00:17:50.736
Now it's landing again,
now they're both down.

00:17:50.736 --> 00:17:51.999
Oh, two selfers.

00:17:52.001 --> 00:17:54.159
Another Pipeline swallowtail, see?

00:17:54.161 --> 00:17:55.899
Oh, there's a courtship.

00:17:56.241 --> 00:17:59.244
Ah, didn't work out. (chuckles)

00:18:00.204 --> 00:18:03.207
That was a Mourning cloak.

00:18:03.290 --> 00:18:06.251
How extraordinary!

00:18:06.710 --> 00:18:09.671
Make a note of that.

00:18:14.843 --> 00:18:16.804
So when Art started
visiting these sites

00:18:16.804 --> 00:18:20.682
in the early to mid '70s,
I think he was partly trying

00:18:20.682 --> 00:18:25.020
to get to know these butterfly communities
and to do some science at the same time.

00:18:25.437 --> 00:18:26.814
Oh, here's another Hairstreak.

00:18:26.814 --> 00:18:28.398
Who are you?

00:18:28.398 --> 00:18:31.401
Somehow there was a point where he had
been doing that and he just didn't stop.

00:18:32.569 --> 00:18:35.239
But he inadvertently created
one of the world's best

00:18:35.239 --> 00:18:38.242
long-term data sets of
insect populations.

00:18:46.542 --> 00:18:49.461
When you were actively
collecting the data,

00:18:49.461 --> 00:18:53.090
you're too close to the data
and you don't see what's happening.

00:18:53.090 --> 00:18:57.636
You have to step back
and look at the data objectively

00:18:57.636 --> 00:19:01.932
over a period of time
to see things actually happening.

00:19:01.932 --> 00:19:06.436
You're too busy in the here
and now to put it in context.

00:19:11.984 --> 00:19:16.280
So Art takes data on 3 x 5 cards
when he's in the field,

00:19:16.530 --> 00:19:21.899
and he records the number of individuals
of each species that's flying.

00:19:21.902 --> 00:19:23.537
By itself, that doesn't
mean a whole lot.

00:19:23.537 --> 00:19:26.582
But when you have these records
every couple of weeks

00:19:26.582 --> 00:19:30.377
for more than 40 years, it's
just an incredible picture of how

00:19:30.669 --> 00:19:33.672
a suite of insects has changed
over the years.

00:19:41.305 --> 00:19:45.100
We're doing a lot of research on
whether they are dying off and why.

00:19:45.559 --> 00:19:46.685
That's what we do.

00:19:50.230 --> 00:19:53.775
Well, they weren't put here
to help mankind,

00:19:54.651 --> 00:19:57.654
but they are pollinators.

00:19:58.405 --> 00:19:59.323
OK, we gotta go.

00:19:59.323 --> 00:20:00.616
It's hot.

00:20:41.615 --> 00:20:43.867
I was involved in publishing a study

00:20:43.867 --> 00:20:48.330
based on German data
on flying insect biomass.

00:20:48.455 --> 00:20:53.001
I was kind of brought in to help analyze
the data and polish up the English.

00:20:53.418 --> 00:20:58.757
And when I first saw the data,
I must admit I didn't quite believe it.

00:21:04.930 --> 00:21:09.559
So these entomologists have been putting
out malaise traps since the late 1980s.

00:21:09.559 --> 00:21:12.938
And the malaise trap,
it looks a bit like a tent and it catches

00:21:12.938 --> 00:21:15.941
any flying insect that bump into it.

00:21:16.817 --> 00:21:19.820
Perfecto.

00:21:25.367 --> 00:21:29.162
Many of us especially interested

00:21:29.162 --> 00:21:32.457
in methods of field work with insects.

00:21:34.543 --> 00:21:37.504
And one of these techniques

00:21:37.504 --> 00:21:42.175
are the malaise traps,
which we started to build

00:21:42.175 --> 00:21:47.472
our first malaise traps in 1982.

00:21:49.766 --> 00:21:53.353
We trapped with these because
we wanted to get information

00:21:53.353 --> 00:21:56.982
about the species composition
of a certain place.

00:22:35.395 --> 00:22:38.398
That's...

00:22:38.565 --> 00:22:41.568
collections...

00:22:42.194 --> 00:22:43.653
of insects.

00:22:43.653 --> 00:22:46.656
Here we have pollinators.

00:22:50.369 --> 00:22:53.372
Most pollinators are small.

00:22:59.002 --> 00:23:02.005
This is, ah, this is the old guys.

00:23:02.464 --> 00:23:05.467
A hundred or 80 years ago.

00:23:06.676 --> 00:23:10.979
The Entomological Society
is founded 1905.

00:23:12.997 --> 00:23:14.684
Over the complete period,

00:23:14.684 --> 00:23:18.939
they built a lot of
collections of insects

00:23:18.939 --> 00:23:25.278
and very important data about
insects mainly in the Rhineland.

00:23:29.001 --> 00:23:34.287
Many of us are doing systematic,
taxonomic work

00:23:34.704 --> 00:23:37.833
in describing new species for science.

00:23:38.875 --> 00:23:42.504
There are far more than
one million insects

00:23:42.504 --> 00:23:45.757
dry prepared in these collections,

00:23:45.757 --> 00:23:49.094
and much more millions of insects

00:23:49.511 --> 00:23:52.514
which are in fluids.

00:23:52.806 --> 00:23:58.435
It's the only possibility to study
biodiversity of insects

00:23:58.437 --> 00:24:03.358
if you build up collections,
and you need the original material

00:24:03.358 --> 00:24:07.904
to do any controls of that,
what has happened.

00:24:07.904 --> 00:24:11.324
And books are not enough

00:24:11.825 --> 00:24:14.828
to learn this, to work with this.

00:24:21.585 --> 00:24:24.444
Some of these specimens that
come in really terrible shape,

00:24:24.446 --> 00:24:27.090
we’ll completely do a wash, dry,

00:24:27.090 --> 00:24:31.344
fluff position on them,
get them looking buff again.

00:24:31.928 --> 00:24:34.806
Nothing worse than a bee with bad hair.

00:24:34.806 --> 00:24:36.850
It doesn't look bad,

00:24:36.850 --> 00:24:39.853
but it's noticeable,
and we want them to look really good.

00:24:39.936 --> 00:24:41.354
So, we do this to all our bees.

00:24:46.651 --> 00:24:47.861
About 50% of the reason

00:24:47.861 --> 00:24:50.864
I'm doing all these photographs is

00:24:51.198 --> 00:24:55.535
I love taking beautiful photographs
of bees, and a bee covered

00:24:55.535 --> 00:25:00.248
in dust and scale and
with matted hair is identifiable,

00:25:00.832 --> 00:25:03.835
but not beautiful.

00:25:10.550 --> 00:25:13.553
Let's get a shot just of the face.

00:25:16.056 --> 00:25:20.685
And then I'm going to move to the,

00:25:20.685 --> 00:25:24.898
just so that the back of the head
is just out of focus right there.

00:25:24.898 --> 00:25:27.734
And that'll be the start position.

00:25:27.734 --> 00:25:30.487
And then I'm going to
set the end position

00:25:30.487 --> 00:25:33.490
to the foreground is in focus,

00:25:33.865 --> 00:25:37.244
which includes the very tip
of the antenna

00:25:37.494 --> 00:25:40.288
which is now just out of focus.

00:25:40.288 --> 00:25:41.498
So I select that.

00:25:41.498 --> 00:25:44.459
Now we're ready to run.

00:25:44.459 --> 00:25:47.462
Beer cooler in place.

00:25:49.756 --> 00:25:52.759
Used cardboard box in place.

00:25:55.929 --> 00:25:58.839
And then we mash down this
button that starts it,

00:25:58.841 --> 00:26:01.434
and it’ll tell us it’s going
to take 43 shots.

00:26:03.603 --> 00:26:07.023
So each of these shots is
at a slightly different distance.

00:26:07.023 --> 00:26:10.402
And because we're working at a 3x lens,

00:26:10.694 --> 00:26:12.779
if I just took one picture,
it would be okay,

00:26:12.779 --> 00:26:14.864
but only a part of the picture
would be in focus.

00:26:14.864 --> 00:26:18.743
So now by taking multiple pictures,
it'll recombine

00:26:18.743 --> 00:26:22.664
everything into one photograph
that has everything in focus.

00:26:23.081 --> 00:26:25.292
How it does that, I have no idea.

00:26:25.292 --> 00:26:27.595
But it's great magic.

00:26:32.844 --> 00:26:37.262
Everyone relates to a being
through the eyes.

00:26:38.305 --> 00:26:39.472
So even though it's a bug

00:26:39.472 --> 00:26:45.186
that 500 million years ago separated
from our clan, you’re still relating to it

00:26:45.186 --> 00:26:48.189
by looking in its eyes
and making up stories.

00:27:04.331 --> 00:27:06.291
There's actually around the world

00:27:06.291 --> 00:27:09.252
20,000 bee species or more.

00:27:20.263 --> 00:27:24.643
There's very much that we
don't know about these bee species.

00:27:24.684 --> 00:27:27.646
We don't have much population data
on most of these species,

00:27:27.646 --> 00:27:31.066
so we don't really know how
rare they are, how abundant.

00:27:32.986 --> 00:27:37.072
We have limited data even to describe
where they exist in the world,

00:27:37.072 --> 00:27:39.575
their ranges.

00:27:42.994 --> 00:27:45.705
Many of them are solitary, not social,

00:27:45.705 --> 00:27:48.609
which is something that
really surprises most people

00:27:48.610 --> 00:27:49.999
because we think of the honey bee,

00:27:50.001 --> 00:27:52.087
it's our iconic social bee.

00:27:52.089 --> 00:27:57.550
But the majority of all bee species
are actually nesting underground,

00:27:57.926 --> 00:28:01.388
and even a larger percentage
are solitary species.

00:28:23.118 --> 00:28:26.121
I like to call them
the keystone species.

00:28:26.413 --> 00:28:31.710
If you remove them you've
taken away a major co-evolutionary,

00:28:32.377 --> 00:28:36.047
I call it a contract, that's developed
over time between flowering plants

00:28:36.589 --> 00:28:39.592
and bees.

00:28:40.300 --> 00:28:44.764
Trees, shrubs, flowers,
vegetables, et cetera,

00:28:44.806 --> 00:28:47.767
depend upon bees.

00:28:48.852 --> 00:28:51.938
And so it is one of the most
important things out there

00:28:52.188 --> 00:28:55.567
to maintain our lifestyle
as we know it.

00:28:56.526 --> 00:29:00.071
We need bees.

00:29:33.313 --> 00:29:36.732
This is the largest bumble bee that
we know of, Bombus dahlbomii.

00:29:36.815 --> 00:29:39.360
I'm going to take the
glass off so you can...

00:29:41.237 --> 00:29:44.032
And you can see what a
magnificent animal it is.

00:29:44.032 --> 00:29:47.035
Its common name,
I think, was the flying mouse.

00:29:48.077 --> 00:29:52.248
This is now practically gone
from its range

00:29:52.499 --> 00:29:54.834
in Patagonia.

00:29:54.834 --> 00:29:58.421
But the fact that it's gone
is, is, it's just,

00:29:58.463 --> 00:30:01.466
you know, an unnecessary tragedy.

00:30:02.258 --> 00:30:06.012
As I've studied bees over
the last 35 years,

00:30:07.514 --> 00:30:09.349
the less I can generalize.

00:30:09.349 --> 00:30:11.476
Yes, of course you can make
some generalizations.

00:30:11.476 --> 00:30:15.939
But every species has its unique
behavior, its unique personality.

00:30:16.898 --> 00:30:19.984
And so I have a close connection
to the bees that I study.

00:30:20.276 --> 00:30:22.111
I really love the bees.

00:30:25.198 --> 00:30:26.590
10 years ago, 20 years ago,

00:30:26.591 --> 00:30:29.744
I never would have admitted that,
especially as a female biologist.

00:30:29.744 --> 00:30:32.997
You have to be very careful
not to be too emotional.

00:30:34.249 --> 00:30:35.917
Emotional attachment

00:30:35.917 --> 00:30:39.379
to one's organism is thought
to be less than scientific,

00:30:39.754 --> 00:30:42.465
but now we have the freedom to both

00:30:42.465 --> 00:30:45.426
say that and also feel it.

00:30:45.426 --> 00:30:48.012
There's a close connection to them,

00:30:48.012 --> 00:30:51.015
and when you see them declining

00:30:51.224 --> 00:30:54.027
it's frustrating.

00:31:10.660 --> 00:31:13.737
So here we are at Twin Creeks,
the natural history collection

00:31:13.740 --> 00:31:15.999
at the Great Smoky Mountains
National Park.

00:31:16.207 --> 00:31:19.043
The collection is comprised
of over 64,000

00:31:19.043 --> 00:31:23.506
catalog specimens, which represents
over 90,000 individual specimens.

00:31:23.590 --> 00:31:24.883
And it's estimated that we have

00:31:24.883 --> 00:31:28.094
about a quarter of a million specimens,
including our backlog.

00:31:28.469 --> 00:31:32.515
Collections like this are really important
because each individual specimen

00:31:32.515 --> 00:31:36.811
is a physical record of that species
at a specific time

00:31:36.811 --> 00:31:39.514
and a specific place.

00:31:47.572 --> 00:31:49.824
These are our specimens
of Bombus affinis,

00:31:49.824 --> 00:31:51.701
which is the rusty patched bumble bee.

00:31:51.701 --> 00:31:55.246
It's a notable species because
it's the only and first

00:31:55.413 --> 00:31:58.499
bumble bee on the endangered
species list, and the first bee

00:31:58.499 --> 00:32:01.669
listed on the continental United States
endangered species list.

00:32:03.556 --> 00:32:06.883
Bombas affinis was considered common
in the park for years and years.

00:32:06.883 --> 00:32:10.845
We have specimens from the park
from 1939 is the earliest,

00:32:10.845 --> 00:32:14.307
and they haven't been seen in the
park since the early 2000s.

00:32:17.393 --> 00:32:20.813
It was over a wide part of
the eastern United States from

00:32:20.813 --> 00:32:24.984
about North Carolina, up into southern
Canada, out into the Midwest.

00:32:24.984 --> 00:32:29.530
It was a very common species there in
fields and, you know, edges of forests.

00:32:29.781 --> 00:32:33.618
It was just another bumble bee
of the fields that was pretty common

00:32:33.618 --> 00:32:36.221
over much of that range.

00:32:38.581 --> 00:32:43.086
Between 2014 and 2017,

00:32:43.169 --> 00:32:46.589
I've collected, captured and identified

00:32:46.589 --> 00:32:50.593
25,000 bumble bees to get
one rusty patch.

00:32:50.760 --> 00:32:54.055
So, that's how rare it is
in these collections.

00:32:56.724 --> 00:32:59.352
Now, we don't know what
happened to affinis.

00:32:59.352 --> 00:33:03.856
It clearly lost an enormous
amount of its range in the east.

00:33:04.190 --> 00:33:05.817
It simply is gone there.

00:33:18.413 --> 00:33:20.873
We are in Sierra Valley

00:33:20.873 --> 00:33:24.585
on the east slope of the Sierra,
at about 5000 feet.

00:33:25.086 --> 00:33:26.963
This is one of my permanent sites.

00:33:26.963 --> 00:33:30.258
And we monitor the entire butterfly
fauna at roughly

00:33:30.258 --> 00:33:33.261
two week intervals
throughout the butterfly season.

00:33:34.429 --> 00:33:36.180
Oh, here's somebody here.

00:33:36.180 --> 00:33:39.183
Cabbage white.

00:33:40.768 --> 00:33:43.479
Boy, there ain't much.

00:33:43.479 --> 00:33:47.900
There are two species in the alpine
zone above treeline on Castle Peak

00:33:48.443 --> 00:33:51.446
that we haven't seen since 2015.

00:33:52.030 --> 00:33:54.282
Oh, this is very poor.

00:33:54.282 --> 00:33:57.285
We're seeing about a tenth of
what I would hope for here.

00:34:00.204 --> 00:34:03.207
Snowy copper at my foot.

00:34:04.250 --> 00:34:05.585
At low elevation,

00:34:05.585 --> 00:34:10.506
we had a long-term decline
in the fauna.

00:34:10.548 --> 00:34:14.969
We lost some species altogether,
from our sites and regionally.

00:34:15.803 --> 00:34:18.389
Nothing flying at all in the grassland.

00:34:18.389 --> 00:34:21.392
No butterflies so far.

00:34:21.476 --> 00:34:25.646
The decline was slow until 1999,

00:34:26.773 --> 00:34:29.776
and then it became precipitous,

00:34:30.026 --> 00:34:32.904
verging on catastrophic.

00:34:32.904 --> 00:34:35.907
There have been no monarch
seen here this year,

00:34:36.449 --> 00:34:39.577
and there's no sign of any monarch
breeding on these plants.

00:34:40.119 --> 00:34:43.122
We don't know where they are.

00:35:00.056 --> 00:35:01.766
I was always interested in

00:35:01.766 --> 00:35:06.979
looking for insects and other animals
when I was outside in the fields

00:35:06.979 --> 00:35:09.857
or when I was outside
in the woods, for example.

00:35:09.857 --> 00:35:12.443
And there was so much to explore,

00:35:12.443 --> 00:35:16.155
and I just saw so many different species
and I was not able to name them.

00:35:16.155 --> 00:35:19.408
And so I just thought,
I have to know what I just saw,

00:35:19.450 --> 00:35:21.119
I found there.

00:35:21.119 --> 00:35:24.205
So the Entomological Society
concentrates and focus on

00:35:24.205 --> 00:35:27.917
nature reserves here in
North Rhine-Westphalia mainly.

00:35:29.001 --> 00:35:32.797
So if we just take a closer
look on one sample of this

00:35:32.797 --> 00:35:35.842
malaise trap we see different
insect orders inside.

00:35:35.842 --> 00:35:39.470
And these are bees and wasps
and beetles, for example,

00:35:39.470 --> 00:35:41.973
but we also have butterflies inside.

00:35:41.973 --> 00:35:43.975
So, we have really a larger number

00:35:43.975 --> 00:35:46.978
of different insects orders
which are able to fly.

00:35:47.270 --> 00:35:50.523
And they are combined on
one of these biomass sample.

00:35:52.191 --> 00:35:54.318
So I just checked it now,

00:35:54.318 --> 00:35:58.072
and we have more than
30 species in this sample.

00:35:58.531 --> 00:36:03.327
And then there are several specimens
which are really hard to identify,

00:36:03.327 --> 00:36:06.330
and therefore I just have to
preserve them dry

00:36:06.581 --> 00:36:09.584
to identify those species.

00:36:25.933 --> 00:36:28.936
And you'll see this is 2014.

00:36:29.020 --> 00:36:32.023
It's a quite newer one.

00:36:34.942 --> 00:36:40.281
And every bottle is
one or two weeks of

00:36:40.281 --> 00:36:43.826
trap in the field on this place.

00:36:44.327 --> 00:36:49.207
And every box is one trap on one place.

00:36:49.999 --> 00:36:53.002
We have a complete material of

00:36:53.502 --> 00:36:56.547
many hundreds of investigations,

00:36:56.547 --> 00:36:59.842
in thousands of boxes.

00:37:01.219 --> 00:37:05.848
And in the old times
we had also these kind of bottles,

00:37:06.891 --> 00:37:10.061
which represent also only two weeks.

00:37:11.896 --> 00:37:14.899
We don't have a place with this,

00:37:15.983 --> 00:37:18.986
with these numbers today.

00:37:27.787 --> 00:37:31.666
There's a real lack of data
on how insects are doing.

00:37:31.958 --> 00:37:35.002
One of the things that I and
anyone else who studies insects is

00:37:35.002 --> 00:37:38.339
painfully aware of is that we don't have
long-term data on what's happening.

00:37:39.757 --> 00:37:41.841
So when someone came along and said,

00:37:41.843 --> 00:37:43.970
"Hey, we've got this data set
on insect numbers

00:37:44.262 --> 00:37:47.181
for the last 26 years from sites
all across Germany,"

00:37:47.181 --> 00:37:49.558
I thought, wow, you know,

00:37:49.558 --> 00:37:50.643
this is going to be fascinating.

00:37:50.643 --> 00:37:53.346
I've got to see it.

00:37:55.606 --> 00:37:57.441
The data I was looking at
were the weights.

00:37:57.441 --> 00:38:00.027
It's the daily weight
of insects caught.

00:38:00.027 --> 00:38:04.657
They haven't got 'round to counting
the insects yet, let alone identifying the

00:38:04.657 --> 00:38:08.244
tens or hundreds of millions of insects
that they probably have in these pots.

00:38:08.661 --> 00:38:11.664
But they have weighed them because
that's a pretty quick and easy thing to do.

00:38:16.512 --> 00:38:21.909
We had malaise traps with
a total of more than

00:38:21.911 --> 00:38:29.001
16,900 days in the field, in total.

00:38:29.432 --> 00:38:35.766
We had more than 1,500 data points

00:38:35.769 --> 00:38:37.201
of biomass weighting.

00:38:38.699 --> 00:38:43.612
So this is, in total, a big data set.

00:38:49.493 --> 00:38:54.457
It's not very easy to find the point

00:38:55.374 --> 00:38:59.587
when you said this is the year
we thought there is

00:38:59.628 --> 00:39:02.631
something very wrong.

00:39:16.437 --> 00:39:20.191
They sent me this data set
of daily catches of insects.

00:39:20.399 --> 00:39:24.236
And it shows this very simple, clear

00:39:24.779 --> 00:39:28.616
and massive decline that basically
the weight of insects caught per day

00:39:28.616 --> 00:39:32.119
has dropped by 76% in 26 years

00:39:32.119 --> 00:39:36.957
between 1989 and 2014,
which is staggering.

00:39:36.957 --> 00:39:40.961
And I kind of did a triple take and
looked through it really carefully.

00:39:40.961 --> 00:39:43.506
But it's actually
a pretty simple data set.

00:39:43.506 --> 00:39:46.342
There's no clever analysis needed
to see what's happening.

00:39:46.342 --> 00:39:49.970
It seems to be real that basically
our insects are disappearing.

00:39:51.972 --> 00:39:56.060
We think what we see is a slowly moving

00:39:56.268 --> 00:40:00.981
decline of common species,

00:40:01.273 --> 00:40:04.110
and the density

00:40:05.319 --> 00:40:08.322
within a habitat.

00:40:08.781 --> 00:40:12.868
These are drawers with bumble bees

00:40:13.411 --> 00:40:16.914
more than 60, 70 years.

00:40:17.581 --> 00:40:20.668
And many of these species are now

00:40:21.127 --> 00:40:24.130
extinct in this area.

00:40:25.381 --> 00:40:29.635
More than 50% of bumble bee species

00:40:30.928 --> 00:40:34.974
around Krefeld are not longer present.

00:40:38.894 --> 00:40:40.396
I've known insects were declining.

00:40:40.396 --> 00:40:43.107
We've got good evidence from bees,

00:40:43.107 --> 00:40:46.610
although we don't have a kind of
systematic bee population monitoring

00:40:46.610 --> 00:40:49.822
scheme in place for
anywhere in the world.

00:40:50.156 --> 00:40:53.284
We do know that bees are declining
because some have gone extinct

00:40:53.284 --> 00:40:56.287
and some have disappeared
from large parts of their range.

00:40:56.662 --> 00:40:59.623
We have much better data for butterflies,
and we know that butterflies

00:40:59.623 --> 00:41:01.083
are declining.

00:41:01.083 --> 00:41:04.128
But I was still surprised

00:41:04.128 --> 00:41:08.924
by the scale of this disappearance
of all insects in Germany.

00:41:08.924 --> 00:41:12.052
We've got clear evidence
that they're being wiped out.

00:41:12.928 --> 00:41:15.055
And what's even more alarming is

00:41:15.055 --> 00:41:18.058
there's no sign of that disappearance

00:41:18.225 --> 00:41:21.020
decreasing, abating towards
the end of the data set.

00:41:21.020 --> 00:41:23.898
It's basically a straight
line down to oblivion.

00:41:23.898 --> 00:41:26.901
And that is really disturbing.

00:41:27.568 --> 00:41:30.696
This will have consequences.

00:41:31.280 --> 00:41:34.283
You cannot have a decline

00:41:34.408 --> 00:41:39.121
in these dimensions
without consequences.

00:41:53.844 --> 00:41:56.847
Now, let me see what we've got here.

00:41:58.933 --> 00:42:00.684
Looks like it's turning out pretty low.

00:42:00.684 --> 00:42:03.687
I haven't seen an insect yet.

00:42:05.523 --> 00:42:08.067
Should have been able
to do better than that.

00:42:08.067 --> 00:42:11.028
Let me try over along another...

00:42:16.492 --> 00:42:18.443
We know right now

00:42:18.445 --> 00:42:22.164
that we're in the middle of
what has been called,

00:42:22.164 --> 00:42:26.252
I think, appropriately,
the insect apocalypse.

00:42:28.963 --> 00:42:32.508
These species are disappearing
around the world.

00:42:33.676 --> 00:42:36.470
We've made a big effort

00:42:36.470 --> 00:42:40.307
globally to stop the
extinction process.

00:42:41.225 --> 00:42:44.228
How much have we succeeded?

00:42:45.145 --> 00:42:47.848
Not very well.

00:42:51.652 --> 00:42:54.947
Now, I should have something.

00:43:01.999 --> 00:43:04.840
A small beetle of unknown family.

00:43:08.711 --> 00:43:09.718
Nothing.

00:43:10.087 --> 00:43:12.031
Nothing.

00:43:13.340 --> 00:43:14.925
Nothing.

00:43:21.640 --> 00:43:23.142
Two summers ago,

00:43:23.142 --> 00:43:28.480
I set out to count the number of
insects that hit the front windshield

00:43:28.647 --> 00:43:32.234
while taking a ride to a summer home
in New Hampshire.

00:43:33.027 --> 00:43:36.572
A nice sunny May day,
perfect for insects.

00:43:39.700 --> 00:43:41.684
On a ride like that, normally,

00:43:41.686 --> 00:43:45.922
you would have to get
out of the car occasionally

00:43:45.924 --> 00:43:48.667
to clean off the masses of insects

00:43:48.876 --> 00:43:51.879
that hits the windshield
and accumulates there.

00:43:55.758 --> 00:43:58.761
So we took this ride
in perfect weather,

00:43:59.428 --> 00:44:02.389
and the number of insects

00:44:02.473 --> 00:44:04.975
that hit the windshield--

00:44:04.975 --> 00:44:05.999
the number of them,

00:44:06.001 --> 00:44:11.999
not per ten minute but the
number for the entire trip--

00:44:12.001 --> 00:44:13.999
was one.

00:44:15.027 --> 00:44:17.279
And then not a single insect

00:44:17.279 --> 00:44:21.492
struck the windsheild in the entire
ride up to New Hampshire

00:44:21.784 --> 00:44:23.869
on a perfect day.

00:46:22.780 --> 00:46:25.783
Biologists talk about an
extinction debt,

00:46:27.034 --> 00:46:30.454
that essentially in the
20th century we lost

00:46:30.871 --> 00:46:33.874
most of our wildlife-rich habitats.

00:46:42.090 --> 00:46:43.342
The species that survive

00:46:43.342 --> 00:46:46.386
are mostly surviving in little habitat
islands in nature reserves.

00:46:46.762 --> 00:46:49.640
And probably those populations
aren't really viable in the long term.

00:46:49.640 --> 00:46:50.849
They're going to become inbred,

00:46:50.849 --> 00:46:54.478
they might just go extinct by chance
events, bad weather or whatever,

00:46:54.478 --> 00:46:55.999
in one year.

00:46:56.730 --> 00:46:58.106
So we could be seeing

00:46:58.106 --> 00:47:01.777
species disappearing as a result
of habitats that were lost

00:47:02.069 --> 00:47:05.697
20, 50 years ago
because of this extinction debt.

00:47:05.781 --> 00:47:09.884
Essentially they're non-viable populations
slowly blinking out one by one.

00:47:15.374 --> 00:47:16.458
The German study was done

00:47:16.458 --> 00:47:19.461
on nature reserves

00:47:20.504 --> 00:47:23.507
which are all surrounded by farmland.

00:47:25.008 --> 00:47:28.220
And it seems that those nature reserves
aren't able to support

00:47:28.220 --> 00:47:31.723
the insect life that they used to have
when the study started.

00:47:31.765 --> 00:47:34.768
It's just slowly and
steadily disappearing.

00:47:42.699 --> 00:47:47.364
We know that we have made
big chunks of the world

00:47:47.614 --> 00:47:50.701
essentially hostile to insects
and other life.

00:47:51.952 --> 00:47:55.247
Farmland doesn't provide
anything for most insects,

00:47:55.247 --> 00:47:58.417
so they're living in the scraps,
the little tiny bits of habitat

00:47:58.417 --> 00:48:01.420
that we didn't destroy
in the 20th century.

00:48:07.134 --> 00:48:09.136
It's certainly, in Europe,

00:48:09.136 --> 00:48:11.930
the predominant land use is
food production.

00:48:11.930 --> 00:48:13.640
Most people don't question it.

00:48:13.640 --> 00:48:17.811
We just go through the countryside
on a train or driving along the motorway

00:48:17.811 --> 00:48:21.398
and these huge fields on both sides
look bright green.

00:48:21.565 --> 00:48:23.358
A lot of people who live
in cities think that

00:48:23.358 --> 00:48:25.819
that's full of wildlife,
but actually it's not.

00:48:25.819 --> 00:48:27.863
There's precious little wildlife in it.

00:48:28.906 --> 00:48:30.198
On top of that, we know

00:48:30.198 --> 00:48:33.994
wildlife that particularly lives in
farmland is disappearing faster

00:48:34.119 --> 00:48:37.331
than wildlife, for example,
associated with woodland or whatever.

00:48:38.999 --> 00:48:42.502
It's pretty clear that the way
we farm is the biggest driver

00:48:42.586 --> 00:48:45.589
of loss of wildlife generally,
not just insects.

00:48:55.015 --> 00:48:57.992
Along in the 1930s, 1940s, 1950s,

00:48:57.994 --> 00:49:01.188
as crop sizes got really large

00:49:01.438 --> 00:49:04.441
and we started planting monocultures

00:49:04.524 --> 00:49:07.736
and as we started to
use insecticides on them,

00:49:07.736 --> 00:49:10.739
people started to see a
pollinator deficit.

00:49:10.739 --> 00:49:13.742
Everything before then
was just pollinated.

00:49:15.577 --> 00:49:16.662
And so honey bees

00:49:16.662 --> 00:49:20.332
started to be used as a mechanism

00:49:20.499 --> 00:49:24.103
to pollinate large-scale agriculture,

00:49:24.199 --> 00:49:28.048
and commercial beekeeping was born.

00:49:34.096 --> 00:49:37.557
Many people perhaps don't realize
that when they eat an apple

00:49:37.557 --> 00:49:42.562
or they eat an almond, that it's
because somebody brought bees,

00:49:42.562 --> 00:49:47.526
often on the back of a truck, honey bees,
and deposited these boxes on the field.

00:49:53.323 --> 00:49:55.450
In order to get the pollination
that we need,

00:49:55.450 --> 00:49:58.453
we have to bring the
bees to the fields.

00:50:18.974 --> 00:50:21.775
During February and
early March of every year,

00:50:21.977 --> 00:50:24.438
we've got the almonds here in
the Central Valley, California.

00:50:24.771 --> 00:50:28.358
And it's the largest managed honey bee
pollination event in the world.

00:50:28.525 --> 00:50:31.945
Requires nearly two million
beehives to pollinate

00:50:31.945 --> 00:50:34.948
the more than one million acres of
almonds that are in the valley.

00:50:35.907 --> 00:50:39.202
We get bees from practically every
state in the Union to pollinate almonds.

00:50:39.202 --> 00:50:45.167
Well, we have to, because it requires
at least 90% of the available managed

00:50:45.167 --> 00:50:48.378
commercial honey bees in the
entire USA to pollinate

00:50:48.378 --> 00:50:51.381
the almonds in this valley.

00:50:55.302 --> 00:50:58.013
We move our bees about six
times a year on average.

00:50:58.013 --> 00:50:59.306
Many beekeepers have been going

00:50:59.306 --> 00:51:02.392
interstate for decades and
basically need to follow the flowers.

00:51:02.392 --> 00:51:04.352
Whether you're planting a crop
or trying to make honey,

00:51:04.352 --> 00:51:05.645
you're trying to follow the flowers.

00:51:10.945 --> 00:51:14.905
Humans and bees have this
interesting relationship.

00:51:14.905 --> 00:51:17.908
Some people can't live without
their bee colonies.

00:51:19.550 --> 00:51:23.914
How humans have a relationship
with dogs or cats,

00:51:24.081 --> 00:51:26.458
they have that same thing
with their bees.

00:51:26.458 --> 00:51:30.629
It sounds odd because they're
not really a pet, you know?

00:51:30.629 --> 00:51:32.756
You can't really pet them. (chuckles)

00:51:32.756 --> 00:51:35.759
I do, but it's that same kind of love

00:51:35.842 --> 00:51:38.887
and that same kind of
reciprocal relationship.

00:51:38.887 --> 00:51:41.890
They get something from the bee colony.

00:51:43.433 --> 00:51:46.436
Honey bees go to people's heart.

00:51:46.436 --> 00:51:52.067
It's a little disturbing that many
people think bees equal honey bees,

00:51:52.400 --> 00:51:56.530
but people need to enter
a door somewhere.

00:52:02.202 --> 00:52:05.205
Honey bees are not native
to North America.

00:52:05.497 --> 00:52:10.669
Our first record of honey bees in North
America is from 1622, but honey bees

00:52:10.669 --> 00:52:15.173
were not brought to the United States
to use as a mechanism for pollination.

00:52:15.173 --> 00:52:17.425
They were brought here for
honey production.

00:52:20.011 --> 00:52:23.223
Prior to 2006, I always made

00:52:23.223 --> 00:52:26.518
more money producing honey
than I did pollinating crops.

00:52:27.561 --> 00:52:30.147
But since 2006, there's been many years

00:52:30.147 --> 00:52:33.984
when we've made more on pollination
than we've made on honey production.

00:52:34.568 --> 00:52:38.999
The USA used to routinely produce
well over 200 million pounds

00:52:39.002 --> 00:52:42.284
of honey annually,
but since the year 2000

00:52:42.367 --> 00:52:45.370
we have not produced a
200 million pound crop.

00:52:46.163 --> 00:52:49.249
There's been a change in the landscape,
not only through development

00:52:49.249 --> 00:52:51.899
and urbanization but
change in the Midwest,

00:52:52.001 --> 00:52:56.001
which is great honey country,
from prairie to corn and soybeans,

00:52:56.214 --> 00:52:59.551
which are not great honey crops
or not honey crops at all.

00:53:00.594 --> 00:53:03.597
Okay, okay.

00:53:06.016 --> 00:53:07.417
And you too?

00:53:07.919 --> 00:53:09.893
The bee health issues
we've been dealing with

00:53:09.895 --> 00:53:12.522
for the last 14, 15 years,

00:53:12.522 --> 00:53:15.025
it takes strong colonies
to produce a honey crop.

00:53:15.025 --> 00:53:19.362
So, our bee health issues are also
one reason that we're not producing

00:53:19.362 --> 00:53:21.364
as much honey as we did prior to 2000.

00:53:22.574 --> 00:53:25.660
A really good place to start is
with these dead beehives right here,

00:53:25.660 --> 00:53:29.748
because these had bees in them last
year but they died out in the fall,

00:53:30.081 --> 00:53:33.084
and it's something that we
deal with every year.

00:53:33.752 --> 00:53:37.464
Back in the '70s, we would be
able to go through the winter

00:53:37.464 --> 00:53:41.009
with maybe losing 5% or so
of the colonies.

00:53:41.009 --> 00:53:45.001
And over the years that
increased to 10%, and then 15,

00:53:45.003 --> 00:53:48.850
and our first major industry losses
where we did not have enough

00:53:48.850 --> 00:53:52.229
good bees to pollinate the almonds
in California was in 2004.

00:53:52.354 --> 00:53:53.355
That's two years before

00:53:53.355 --> 00:53:56.483
colony collapse disorder
became a popular phrase in the media.

00:53:58.777 --> 00:54:01.780
And we're still dealing with that.

00:54:02.155 --> 00:54:05.633
In the 1980s, something
called the Varroa mite

00:54:05.635 --> 00:54:08.578
was introduced into hives,
which started causing problems.

00:54:09.287 --> 00:54:15.377
And then in 2006 we started to
see a real something change.

00:54:17.003 --> 00:54:21.007
All of the bees that could fly in a hive

00:54:21.549 --> 00:54:24.469
would abscond,
which means they would just leave

00:54:24.469 --> 00:54:27.806
and beekeepers would come up to
the hives and all that would be left

00:54:27.806 --> 00:54:30.499
was the queen and the dying brood,

00:54:30.501 --> 00:54:33.370
because nobody's feeding them anymore.

00:54:36.481 --> 00:54:39.401
It was unlike anything that had
ever been seen before.

00:54:39.401 --> 00:54:43.947
So we came up with this name of
colony collapse disorder because we

00:54:43.949 --> 00:54:47.826
didn't know what was underlying a
healthy colony to do the collapse.

00:54:48.285 --> 00:54:51.538
And that triggered this realization

00:54:51.538 --> 00:54:54.541
that pollinators were in deep trouble.

00:54:54.833 --> 00:54:57.836
Some bee colonies now just look not well.

00:54:58.169 --> 00:55:00.630
It's sad to see. It's hard to see.

00:55:00.630 --> 00:55:03.633
It's hard to keep bee colonies
alive anymore.

00:55:05.510 --> 00:55:08.179
It's about the health of the earth,
if you will.

00:55:08.179 --> 00:55:09.597
There's a lot of species

00:55:09.597 --> 00:55:12.934
that are down in their populations
in addition to honey bees.

00:55:13.310 --> 00:55:16.563
That's a great concern for all of us.

00:55:18.783 --> 00:55:21.899
There is evidence of honey bees
spreading disease

00:55:21.899 --> 00:55:23.277
to native bees in some places.

00:55:23.278 --> 00:55:27.532
There are also concerns
about competition for flowers.

00:55:27.866 --> 00:55:31.619
So if you put 10 or 20 honey bee
colonies into an area that's

00:55:31.619 --> 00:55:35.332
a whole lot of bees that are competing
for resources with the native bees.

00:55:36.207 --> 00:55:39.502
But there are definitely concerns
that if you do everything

00:55:39.502 --> 00:55:42.839
you could to maximize
how well honey bees are doing,

00:55:43.048 --> 00:55:45.999
you may end up enhancing
the competition

00:55:46.001 --> 00:55:48.999
that native bees experience.

00:55:50.138 --> 00:55:51.598
The problem is not just

00:55:51.598 --> 00:55:55.518
the management of agriculture,
but it's the management of weedy spaces

00:55:55.518 --> 00:56:00.815
and all of the sort of areas in between
that are really good for insects.

00:56:01.107 --> 00:56:05.028
The edges of agriculture used to have
a higher diversity of weeds in them

00:56:05.153 --> 00:56:09.032
before modern agricultural techniques
allowed us to sort of, you know,

00:56:09.074 --> 00:56:14.037
laser-level fields and efficiently
clean out the weeds in nearby areas.

00:56:14.579 --> 00:56:17.624
That was too bad, because now
we know those weedy spaces

00:56:17.624 --> 00:56:21.628
around agriculture are great reservoirs
for native pollinators,

00:56:21.628 --> 00:56:25.590
native insects, and the whole food chains
that can persist around agriculture.

00:56:26.758 --> 00:56:29.969
Boy, there's very little habitat

00:56:30.678 --> 00:56:34.015
in this part of the valley for
native pollinators.

00:56:34.015 --> 00:56:37.018
I'm not going to say there's zero,
but I'll say there's very, very few.

00:56:37.310 --> 00:56:40.939
This orchard here is a little over
100 acres, and it certainly wouldn't

00:56:40.939 --> 00:56:43.483
be enough native pollinators to make
a difference here if there were any.

00:56:43.483 --> 00:56:46.286
And I'm not aware that there are any.

00:56:49.239 --> 00:56:52.242
We used to grow crops in patches,

00:56:52.367 --> 00:56:55.078
where you would have a whole variety

00:56:55.078 --> 00:56:58.039
of different crops across
the landscape.

00:56:58.248 --> 00:57:01.084
Most crop pests are specific to a crop,

00:57:01.084 --> 00:57:05.088
so it's much harder for them
to build up big populations

00:57:05.088 --> 00:57:08.091
if you have a patchwork
across the landscape.

00:57:10.343 --> 00:57:11.928
But in the '30s, '40s, and '50s,

00:57:11.928 --> 00:57:16.808
we went to thousands,
tens of thousands of acres of one crop.

00:57:17.308 --> 00:57:21.187
That really sets up a system
where all of a sudden,

00:57:21.396 --> 00:57:25.275
"Oh, I can produce more,
but I have to have these inputs.

00:57:25.567 --> 00:57:28.194
I have to have inputs of fertilizer.

00:57:28.194 --> 00:57:32.031
I have to often
have inputs of insecticides,"

00:57:32.365 --> 00:57:35.743
because the larger the area,
the more monoculture it is,

00:57:35.743 --> 00:57:38.413
the more likely you are
to have these pests.

00:57:41.958 --> 00:57:44.544
You know, I think there was
kind of a bifurcation point

00:57:44.544 --> 00:57:47.547
where we could have taken
a different pathway.

00:57:47.630 --> 00:57:50.300
But around the 1940s
we had World War II,

00:57:50.300 --> 00:57:54.345
and people were producing
a lot of chemicals

00:57:54.596 --> 00:57:57.299
for chemical warfare.

00:57:58.057 --> 00:58:01.227
And when the war ended,
what were those factories going to do?

00:58:01.269 --> 00:58:04.272
What were people going to do
with all of those chemicals?

00:58:04.939 --> 00:58:07.942
So we turned to a war
on insects instead.

00:58:09.611 --> 00:58:12.489
It begins with the war-born
development of DDT.

00:58:12.489 --> 00:58:14.491
This diabolical weapon
of modern science

00:58:14.491 --> 00:58:17.702
saved millions of humans,
but killed billions of insects.

00:58:18.119 --> 00:58:20.830
It came from laboratories
where top scientists from

00:58:20.830 --> 00:58:24.209
famous universities and from industrial
and government organizations

00:58:24.626 --> 00:58:27.629
collaborated to develop something
new and different.

00:58:28.171 --> 00:58:30.173
They perfected Pestroy,

00:58:30.173 --> 00:58:33.218
the most effective weapon
man has ever wielded against insects.

00:58:34.135 --> 00:58:36.954
But the really short kill feature
of this insect killer

00:58:36.954 --> 00:58:39.599
isn't simply that it contains DDT.

00:58:39.849 --> 00:58:43.520
It's the way that it make sure
that bugs get the DDT that's in it.

00:58:43.811 --> 00:58:46.814
And once applied,
it keeps right on killing them.

00:58:48.233 --> 00:58:51.069
On fruit and vegetable stands.

00:58:51.069 --> 00:58:53.001
In cupboards,
the happy hunting grounds

00:58:53.003 --> 00:58:55.031
for all types of insects.

00:58:55.031 --> 00:58:59.160
Another constant threat to insects' life,
liberty and the pursuit of happiness.

00:59:00.078 --> 00:59:02.497
It's a handful of concentrated death

00:59:02.497 --> 00:59:05.625
and it's perfect for ridding Fido
of those unwelcome houseguests.

00:59:06.501 --> 00:59:08.920
Of all our weapons, insecticides

00:59:08.920 --> 00:59:12.590
are the most adaptable and effective
for achieving quick results.

00:59:13.007 --> 00:59:15.802
Vast areas can be treated
in a short time,

00:59:15.802 --> 00:59:19.806
an outstanding advantage
in our warfare against the insects.

00:59:20.598 --> 00:59:26.799
We may never eradicate a single
species of insect from this earth,

00:59:26.801 --> 00:59:30.441
but we will hold the upper hand.

00:59:32.277 --> 00:59:35.572
We started off with the organic chlorides,
which everyone thought were great--

00:59:35.572 --> 00:59:38.899
crop yields went up,
they killed all the insect pests--

00:59:39.001 --> 00:59:42.367
until the 1960s, when
Rachel Carson pointed out

00:59:42.370 --> 00:59:44.831
that they're actually doing terrible
harm to the environment

00:59:44.831 --> 00:59:47.375
because they were very persistent
and they bioaccumulated,

00:59:47.375 --> 00:59:50.420
and they were wiping out
raptors and umpteen other organisms.

00:59:50.878 --> 00:59:52.422
And so they were eventually banned.

00:59:56.467 --> 00:59:58.011
In the meantime

00:59:58.011 --> 01:00:02.390
we used a lot of organophosphates,
and not perhaps entirely surprisingly,

01:00:02.390 --> 01:00:07.228
eventually it became clear that they were
harmful to people when used in farming.

01:00:07.979 --> 01:00:11.065
So mostly we've banned
the organophosphates now.

01:00:12.442 --> 01:00:15.445
In the meantime, the pesticide
companies are registering

01:00:15.820 --> 01:00:18.823
new pesticides,
so on we go round and round.

01:00:35.092 --> 01:00:39.135
This alfafa field right here,
I mean, this is likely to be sprayed

01:00:39.135 --> 01:00:42.221
for alfalfa weevil at some point
before we have to leave here.

01:00:43.014 --> 01:00:46.934
We don't really like to be around that,
but we will be around because, I mean,

01:00:47.018 --> 01:00:50.021
every hayfield gets
sprayed at some point.

01:00:50.980 --> 01:00:53.107
As far as the almonds themselves go,

01:00:53.107 --> 01:00:56.486
there's fungicides
that are applied during bloom,

01:00:56.944 --> 01:01:01.991
and that's when the bees are most likely
to pick up something that's contaminated.

01:01:11.959 --> 01:01:14.086
We're seeing farmers applying

01:01:14.088 --> 01:01:17.090
more pesticides more often
than they used to,

01:01:17.382 --> 01:01:21.177
and this kind of modern intensive
farming system and some particular

01:01:21.177 --> 01:01:24.681
types of insecticide
seem pretty good candidates

01:01:24.681 --> 01:01:28.726
to be playing a role
in driving these insect declines.

01:01:30.478 --> 01:01:32.397
And these things are really poisonous,

01:01:32.397 --> 01:01:36.818
so one teaspoon is enough to kill one
and a quarter billion honey bees.

01:01:37.568 --> 01:01:41.406
Most honey bees in the world
are being routinely exposed

01:01:41.489 --> 01:01:44.575
to a neurotoxin designed
to kill insects.

01:01:46.953 --> 01:01:50.456
So all of these insecticides,
they do collateral damage.

01:01:50.456 --> 01:01:53.459
They kill the beneficial insects
that you would have

01:01:53.751 --> 01:01:56.754
hoped might have been
predating the pests.

01:01:56.838 --> 01:02:00.591
And in killing the predatory insects,
it then means the farmer becomes

01:02:00.591 --> 01:02:03.678
more reliant on pesticides
because he's wiped out

01:02:03.678 --> 01:02:06.973
all the natural enemies that could have
been helping him to control the pests.

01:02:07.598 --> 01:02:11.602
And then the only tool left to control
the pest is more and more pesticides,

01:02:13.354 --> 01:02:14.272
It makes it very hard.

01:02:14.272 --> 01:02:18.192
If they just stop,
then they will have big pest problems

01:02:18.443 --> 01:02:23.001
because the environment has been
depleted of all of its natural enemies.

01:02:43.885 --> 01:02:47.096
♪ My, what a quaint
little neighborhood ♪

01:02:47.180 --> 01:02:51.476
♪ But some tiny fiends
are up to no good ♪

01:02:51.476 --> 01:02:55.188
♪ Lucky for you,
we've concocted a plan ♪

01:02:55.521 --> 01:02:59.484
♪ Best to not mess
with the Orkin man ♪

01:03:03.362 --> 01:03:07.241
♪ Outbreak of bees or centipedes ♪

01:03:07.283 --> 01:03:10.244
♪ What are you to do? ♪

01:03:10.244 --> 01:03:14.457
♪ Well these pests will not mess
with the Orkin man ♪

01:03:14.832 --> 01:03:17.835
♪ That's a promise ♪

01:03:17.919 --> 01:03:22.006
♪ We’ll see through ♪

01:03:29.806 --> 01:03:32.932
The power of insecticides
you can go buy

01:03:32.934 --> 01:03:35.937
at Home Depot these days is stunning.

01:03:40.191 --> 01:03:43.909
You can buy things that could
kill all of the insects

01:03:43.912 --> 01:03:46.009
not only in your yard
but in your block or more

01:03:46.011 --> 01:03:48.441
very efficiently.

01:03:51.077 --> 01:03:52.787
Homeowners use twice as many pesticides

01:03:52.787 --> 01:03:56.541
as agriculture does,
and almost all of it is needless.

01:03:57.083 --> 01:04:01.139
You do not need to hire Chemlawn,
who sprays by the calendar,

01:04:01.142 --> 01:04:02.232
for no reason.

01:04:03.099 --> 01:04:04.674
So that you have a perfect lawn.

01:04:04.674 --> 01:04:06.592
That's not a good reason
to kill the world.

01:04:12.890 --> 01:04:16.002
We've got an area of lawn
the size of New England now.

01:04:16.003 --> 01:04:18.354
It's over 45.6 million acres.

01:04:22.441 --> 01:04:28.072
We tend to take a landscape and
we craft it more and more in our favor.

01:04:28.364 --> 01:04:32.743
And if we're not thinking about nature,
we're crafting it so that it moves

01:04:32.743 --> 01:04:36.664
more and more into a sterile,
non-nature based,

01:04:36.664 --> 01:04:39.667
non-supportive of the rest of
the environment landscape.

01:04:46.465 --> 01:04:49.468
Ecosystems can be pushed
to breaking points.

01:04:51.304 --> 01:04:54.307
They can look pretty good
in the short term

01:04:54.599 --> 01:04:57.602
but eventually they break,

01:04:57.852 --> 01:05:00.813
and they really change profoundly.

01:05:00.813 --> 01:05:04.609
And they can change so profoundly
that they can't find their way back

01:05:04.984 --> 01:05:07.987
to where they started from.

01:05:13.826 --> 01:05:14.911
I think one of the key things

01:05:14.911 --> 01:05:17.914
about the mass extinctions of the past,

01:05:18.247 --> 01:05:19.916
each one was a perfect storm.

01:05:21.459 --> 01:05:23.001
The really big mass extinctions,

01:05:23.003 --> 01:05:26.001
the Big Five that
paleontologists refer to,

01:05:26.003 --> 01:05:28.883
are each so big because
many things went wrong,

01:05:29.926 --> 01:05:32.929
and that it's not so much
the particular driver

01:05:33.387 --> 01:05:36.974
that causes those gigantic losses,
but that drivers piled up.

01:05:37.433 --> 01:05:41.703
Of course, what's going on with humans
today is we're another perfect storm.

01:06:02.670 --> 01:06:07.880
As insect biomass begins to decline,
that sends up some real red flags,

01:06:08.089 --> 01:06:12.259
because that insect population
has been such a fundamental part

01:06:12.259 --> 01:06:15.930
of the food chain in those habitats
for so many millions of years

01:06:16.263 --> 01:06:17.999
that the loss of them really
raises questions

01:06:18.002 --> 01:06:20.643
about how ecosystems will
continue to thrive.

01:06:21.686 --> 01:06:25.940
And those species are important to us,
sometimes in a way we don't know yet.

01:06:26.649 --> 01:06:28.999
And to me, that's one of the
most worrisome things

01:06:29.002 --> 01:06:31.770
about how extinction is
proceeding now.

01:06:31.770 --> 01:06:35.491
We're losing species whose role
we don't fully understand.

01:06:54.268 --> 01:06:59.890
We are a deadly weight on the
rest of life on this planet.

01:07:01.058 --> 01:07:04.061
We need to proceed with care.

01:07:09.650 --> 01:07:12.528
It's kind of sad that
future generations

01:07:12.528 --> 01:07:15.948
will simply not know
that they're living

01:07:15.948 --> 01:07:20.119
in this sad, impoverished world,
because they never knew any different.

01:07:20.578 --> 01:07:23.074
It sounds like I'm being melodramatic,

01:07:23.077 --> 01:07:24.874
but this is a kind of
ecological Armageddon.

01:07:24.874 --> 01:07:28.085
We're looking at the collapse
of life on Earth as we know it.

01:07:35.968 --> 01:07:38.999
All this was predicted by
E.O. Wilson back in 1987,

01:07:38.002 --> 01:07:40.848
He said, "Insects are the little things
that run the world."

01:07:41.380 --> 01:07:42.183
So you get rid of them,

01:07:42.183 --> 01:07:45.186
the world doesn't run,
and that includes humans.

01:07:45.269 --> 01:07:48.230
So insect decline is not
a trivial problem.

01:07:49.106 --> 01:07:52.401
What drives me crazy,
it's presented as if it's inevitable.

01:07:53.319 --> 01:07:54.320
It is not inevitable.

01:07:54.320 --> 01:07:57.323
We know what all the causes are
and we can reverse all the causes.

01:07:57.323 --> 01:07:58.741
We just have to make it a priority.

01:08:01.501 --> 01:08:05.456
There is no single solution
to what's going on now.

01:08:06.207 --> 01:08:11.212
I think the real answer is the solution
is a wide variety of responses

01:08:11.337 --> 01:08:15.633
and not a single silver bullet,
but it’s a panoply of solutions

01:08:15.800 --> 01:08:18.803
that are done at a whole range
of scales, from your backyard

01:08:18.928 --> 01:08:21.931
to the atmosphere of the planet.

01:08:22.139 --> 01:08:23.974
- Hey, Bill.

01:08:23.974 --> 01:08:26.977
I'm here to get my stuff.

01:08:27.386 --> 01:08:28.405
- OK, great, we're ready.

01:08:28.411 --> 01:08:31.025
Now these are fragrant sumac.

01:08:33.109 --> 01:08:36.112
So you have the, the smaller bayberry,

01:08:37.029 --> 01:08:40.324
I'm the owner of Native Plant Nursery
here in Fairfield, Connecticut.

01:08:41.117 --> 01:08:44.036
We are a small nursery that focuses on

01:08:44.036 --> 01:08:47.039
growing and selling plants
native to the northeast.

01:08:47.289 --> 01:08:50.292
And we use native plants
on our projects

01:08:50.751 --> 01:08:53.754
almost entirely and on a regular basis.

01:08:53.754 --> 01:08:56.632
I don't know really any other
nurseries that would carry these.

01:08:56.632 --> 01:08:57.999
- This is why we're here!

01:08:58.002 --> 01:08:59.200
- That's right.

01:08:59.593 --> 01:09:02.847
There's a number of different reasons
why it's great to use native plants.

01:09:03.055 --> 01:09:06.058
One of the big things was the
research done by Doug Tallamy.

01:09:06.433 --> 01:09:10.521
What his research found was
how many insects and bird life

01:09:10.521 --> 01:09:13.607
that the native plants support
compared to non-native plants.

01:09:13.607 --> 01:09:17.862
And when I learned of his research,
that really even increased

01:09:17.862 --> 01:09:20.865
my desire to use native plants,
work with native plants.

01:09:21.157 --> 01:09:22.174
Well, here's...

01:09:22.992 --> 01:09:24.201
This is a spotted cucumber beetle.

01:09:24.201 --> 01:09:27.538
I spent ten years trying to figure out
how they chose their mate.

01:09:28.956 --> 01:09:30.199
We did figure it out, but.

01:09:30.909 --> 01:09:32.479
This is called the Lepidoptera Trail.

01:09:32.960 --> 01:09:35.379
It's open to the public
for people to walk around

01:09:35.379 --> 01:09:39.091
and look at the relationship
between various host plants

01:09:39.091 --> 01:09:42.595
and the insects that use them,
particularly moths and butterflies.

01:09:42.720 --> 01:09:44.555
So that's really what this
was all about,

01:09:44.555 --> 01:09:46.616
and the idea was to show
that you can do it in an

01:09:46.618 --> 01:09:48.899
aesthetically pleasing way,
but also to show

01:09:48.899 --> 01:09:50.769
what these plants are doing.

01:09:50.769 --> 01:09:51.854
This is mountain mint,

01:09:51.854 --> 01:09:55.691
and it doesn't look like a fancy flower
but the native bees really love it.

01:09:56.233 --> 01:09:59.199
You can see a lot of native bees
and little potter wasps

01:09:59.201 --> 01:10:03.899
and all kinds of very tiny insects,
little scoliid wasps.

01:10:04.001 --> 01:10:05.570
What is this, New York ironweed?

01:10:05.576 --> 01:10:07.244
All these are native plants in here.

01:10:07.244 --> 01:10:09.413
Oh that's, that's actually
a honey bee colony.

01:10:09.413 --> 01:10:10.416
No wonder they’re so active.

01:10:12.401 --> 01:10:14.645
There are well-known causes
of insect decline,

01:10:14.647 --> 01:10:16.999
but one that isn't
talked about a whole lot

01:10:17.002 --> 01:10:20.090
is this broad-scale transformation

01:10:20.466 --> 01:10:23.886
of replacing native plant communities
that support insects

01:10:24.094 --> 01:10:27.097
with plant communities
from other continents that don't.

01:10:33.020 --> 01:10:36.901
Most of our insects, about 90%,
are what we call host plant specialists.

01:10:36.903 --> 01:10:38.921
They can only eat the plants
they have co-evolved with.

01:10:40.069 --> 01:10:43.999
So in New England, we know of
11 species of native bees

01:10:44.001 --> 01:10:45.658
that will only develop on goldenrod.

01:10:45.658 --> 01:10:48.661
If you don't have goldenrod you've
lost that 11 species right there.

01:10:48.827 --> 01:10:51.205
If you don't have willow,
you've lost nine more species.

01:10:51.205 --> 01:10:54.416
If you don't have asters, native asters,
you've lost eight more species.

01:10:54.625 --> 01:10:57.628
That's how this specialization
builds up.

01:10:59.088 --> 01:11:01.999
You can put a plant like
butterfly bush,

01:11:02.002 --> 01:11:03.550
which is from Asia, in your yard.

01:11:03.592 --> 01:11:06.804
It makes lots of nectar
and generalist bees go to that.

01:11:07.346 --> 01:11:08.141
It's supplying nectar

01:11:08.143 --> 01:11:11.642
for a few species of generalist bees,
and it's not making any new bees.

01:11:13.018 --> 01:11:15.562
Let's use monarch butterfly
as an example.

01:11:15.562 --> 01:11:18.357
It's a typical host plant specialist.

01:11:18.357 --> 01:11:22.319
It eats milkweeds, but it only eats
milkweeds because over the eons

01:11:22.319 --> 01:11:25.281
it has adapted to that one
genus of plant.

01:11:25.899 --> 01:11:28.784
Monarch's a great example,
but it's one species.

01:11:30.119 --> 01:11:34.001
There's about 12,000 described species
of moths and butterflies in the country,

01:11:34.003 --> 01:11:36.750
and about 14,000 if you add the
ones that aren't described.

01:11:36.917 --> 01:11:39.920
90% of those are
host plant specialists.

01:11:49.346 --> 01:11:50.472
Traditionally, what would happen?

01:11:50.472 --> 01:11:52.224
A subdivision would be built,

01:11:52.224 --> 01:11:55.227
and maybe they take over a farm
or a forest and they clear it

01:11:55.436 --> 01:11:58.439
and they end up
just putting lawn everywhere.

01:11:58.439 --> 01:12:00.774
But we start to look at your
property differently

01:12:00.774 --> 01:12:04.737
and find that you limit the lawn
to the actual minimum that you need,

01:12:04.737 --> 01:12:08.158
and then look for areas where you
can fill in around the edges,

01:12:08.158 --> 01:12:09.450
around the house.

01:12:09.450 --> 01:12:11.910
And those are perfect places
to put in these native plants.

01:12:11.910 --> 01:12:16.040
You have the best of both worlds where
you can use your property, enjoy it,

01:12:16.040 --> 01:12:19.126
but you can also help the local
environment and wildlife.

01:12:20.669 --> 01:12:22.298
So...

01:12:24.298 --> 01:12:27.301
This is 2013.

01:12:28.510 --> 01:12:30.063
When...

01:12:30.763 --> 01:12:32.639
we came in '12.

01:12:32.639 --> 01:12:34.387
And then in 2013,

01:12:34.390 --> 01:12:37.999
I became interested in doing
a real garden.

01:12:38.604 --> 01:12:41.565
And this is the other side.

01:12:41.565 --> 01:12:43.650
Originally I thought

01:12:43.650 --> 01:12:46.612
I would have both turf grass

01:12:46.779 --> 01:12:49.782
and then large planting areas.

01:12:50.032 --> 01:12:55.001
Later I decided to just remove
all of the turf grass

01:12:56.497 --> 01:12:59.500
and make the whole thing a garden.

01:13:13.514 --> 01:13:15.432
This is a nice plant.

01:13:15.432 --> 01:13:17.309
Blue flax.

01:13:17.309 --> 01:13:20.270
It's also native to the
Willamette Valley.

01:13:20.646 --> 01:13:23.482
Pollinators really like chives.

01:13:23.482 --> 01:13:24.441
That's interesting.

01:13:24.441 --> 01:13:27.044
That was just a fly.

01:13:27.569 --> 01:13:30.531
That's Cusick’s checkermallow.

01:13:30.739 --> 01:13:34.410
And that plant is actuall
threatened in the wild

01:13:34.410 --> 01:13:37.371
due to loss of habitat.

01:13:39.331 --> 01:13:43.710
Of the native shrubs
in the Willamette Valley,

01:13:43.710 --> 01:13:47.631
I have probably more than
half of them.

01:13:49.258 --> 01:13:52.469
The shrubs also have a
nice bloom cycle.

01:13:52.469 --> 01:13:55.764
Some of them come early, some come in

01:13:55.806 --> 01:13:59.768
late May and June,
and others bloom all summer really.

01:14:03.772 --> 01:14:05.444
It's kind of a little goal of mine

01:14:04.446 --> 01:14:09.999
to try to attract as many species
as I can, and I suppose,

01:14:10.154 --> 01:14:14.032
in a nano way,
it's my little contribution

01:14:14.700 --> 01:14:18.162
to the preservation of invertebrates.

01:14:20.789 --> 01:14:23.333
So I just plant what they like,

01:14:23.333 --> 01:14:26.336
and they come.

01:14:28.672 --> 01:14:31.475
Here's...oh.

01:14:31.884 --> 01:14:34.887
They're starting to come out now.

01:14:34.928 --> 01:14:37.973
You know, what I really love
is just observing.

01:14:39.016 --> 01:14:42.227
I just love watching these creatures.

01:14:45.522 --> 01:14:48.525
So this is a 50 by 100 lot.

01:14:49.526 --> 01:14:54.129
I'm able to use almost all of it
for gardening.

01:15:09.046 --> 01:15:12.591
The development has come
since we moved in.

01:15:17.638 --> 01:15:22.165
We're in the Overlook neighborhood
of North Portland.

01:15:22.726 --> 01:15:25.103
It's a transportation corridor.

01:15:25.103 --> 01:15:29.191
The city is keen to increase
population density.

01:15:29.775 --> 01:15:33.237
And so that's why we're
getting a lot of

01:15:33.237 --> 01:15:36.040
large apartment buildings.

01:15:41.286 --> 01:15:43.372
As properties are developed,

01:15:44.414 --> 01:15:48.249
I'm worried that they're losing
some of their urban habitat.

01:15:49.586 --> 01:15:53.632
Urban gardens turn out
to be very important

01:15:53.924 --> 01:15:56.927
in invertebrate preservation.

01:15:58.887 --> 01:16:01.890
We may be preserving them.

01:16:24.997 --> 01:16:25.831
- Hi there.

01:16:25.831 --> 01:16:28.041
I'm a researcher from over at
University of Michigan,

01:16:28.041 --> 01:16:31.753
and we've studied
bee populations here in the city.

01:16:31.962 --> 01:16:34.799
So we're just kind of showing
some people what we did

01:16:34.802 --> 01:16:36.675
and where we might have done it.

01:16:37.676 --> 01:16:38.676
- Wait, say that again?

01:16:38.676 --> 01:16:40.095
You caught me off guard.

01:16:40.095 --> 01:16:42.222
I got lost somewhere.

01:16:42.222 --> 01:16:45.999
- So, I'm a researcher from the
University of Michigan,

01:16:46.001 --> 01:16:47.477
and what me and my colleagues study

01:16:47.811 --> 01:16:51.440
is how wild bees, how they deal
with urban spaces.

01:16:51.440 --> 01:16:55.944
Actually, the wild bees that I
study with my labmates,

01:16:56.987 --> 01:16:58.447
a lot of them won't even sting people.

01:17:00.449 --> 01:17:02.576
That was fast, wasn't it?

01:17:02.576 --> 01:17:05.037
- Okay, I do a little honey,

01:17:05.037 --> 01:17:08.040
and so every now and then
I might run into somethin' like that.

01:17:09.207 --> 01:17:12.994
Those that are hiving there, you know,

01:17:12.996 --> 01:17:15.589
and got they hives and everything,

01:17:15.589 --> 01:17:17.341
it don't take much to get 'em angry.

01:17:17.341 --> 01:17:20.336
- Yeah, if you're right next to their hive.

01:17:20.338 --> 01:17:21.178
- You know, but like around the city,

01:17:21.178 --> 01:17:21.970
- Yeah.

01:17:21.970 --> 01:17:23.999
- you can come around
in here and maybe...

01:17:24.001 --> 01:17:26.797
Like, see over in the weeds or
bushes or something like that?

01:17:26.799 --> 01:17:27.726
- Yeah, that’s where we found a few.

01:17:27.726 --> 01:17:30.564
- If you run across something in there.

01:17:30.627 --> 01:17:32.627
Or, a vacant building.

01:17:32.689 --> 01:17:36.025
- It is the kind of place maybe
some wild bees could live,

01:17:36.027 --> 01:17:37.099
from the little cracks and
crevices and stuff.

01:17:37.101 --> 01:17:37.999
- Oh, definitely.

01:17:38.001 --> 01:17:40.001
Wild bears could live in that thing.

01:17:51.500 --> 01:17:53.835
I see nesting potential
for ground-nesting species.

01:17:53.835 --> 01:17:55.899
That's the landscape Detroit
is known for,

01:17:55.901 --> 01:17:58.757
that kind of mix of revitalizing
and vacant land.

01:17:58.757 --> 01:18:01.009
And that vacant land
is the available ground

01:18:01.009 --> 01:18:02.999
that the ground-nesting bees
need to use

01:18:03.001 --> 01:18:05.800
to actually find a place to nest.

01:18:08.894 --> 01:18:12.688
A lot of the bees we found in
Detroit are all cavity nesters.

01:18:13.021 --> 01:18:17.609
That means they can nest in small
openings in buildings, in masonry even.

01:18:18.193 --> 01:18:20.596
So yeah, there's a lot of
potential here.

01:18:39.131 --> 01:18:43.001
As Keep Growing Detroit interns,

01:18:43.003 --> 01:18:47.670
some of the most intelligent,
well rounded,

01:18:47.673 --> 01:18:50.517
well-versed individuals
here in the city of Detroit,

01:18:50.642 --> 01:18:53.854
I would like your answers
to be as clear

01:18:54.187 --> 01:18:57.607
and substantial as you are in value,

01:18:58.001 --> 01:19:00.110
which is super valuable.

01:19:01.194 --> 01:19:04.197
Climate change.

01:19:04.489 --> 01:19:05.489
Poverty.

01:19:05.489 --> 01:19:06.280
- Terrorism.

01:19:06.283 --> 01:19:08.410
- The upcoming election.

01:19:08.410 --> 01:19:09.410
- Politics.

01:19:09.850 --> 01:19:11.201
- Gun violence.
- Gun violence.

01:19:12.289 --> 01:19:15.875
- Now, can we name five
beautiful things,

01:19:15.877 --> 01:19:17.919
or treasures, or values?

01:19:18.879 --> 01:19:21.582
Babies...the sun...

01:19:21.585 --> 01:19:22.585
- Bees?

01:19:22.587 --> 01:19:24.009
- Pollinators.

01:19:24.009 --> 01:19:26.178
Bees, someone said bees.

01:19:26.178 --> 01:19:29.999
This group will do poverty,
and sun and earth.

01:19:30.999 --> 01:19:32.999
Bees and gun violence.

01:19:33.239 --> 01:19:35.239
And learning and climate change.

01:19:35.479 --> 01:19:37.230
It's not about putting 'em together.

01:19:37.230 --> 01:19:40.525
This is about using two things
in the same song.

01:19:41.359 --> 01:19:43.069
- Alright, so what do you want
the song to be about?

01:19:45.238 --> 01:19:47.264
- You guys want it to be about

01:19:47.270 --> 01:19:49.367
farmin' in the hood?

01:19:49.409 --> 01:19:50.509
- Okay.

01:19:50.511 --> 01:19:53.455
- I guess, you got bees
and you got gun violence,

01:19:53.455 --> 01:19:55.332
and they're both naturally
happenin' in the hood.

01:19:55.332 --> 01:19:57.083
- That's...

01:19:57.083 --> 01:19:58.001
- Well, yeah.

01:19:58.001 --> 01:20:00.921
Both those things are in
the same place.

01:20:00.921 --> 01:20:01.880
- The hood.

01:20:01.880 --> 01:20:02.798
- The hood. (laughs)

01:20:04.766 --> 01:20:06.468
- Bees flyin' like bullets...

01:20:07.803 --> 01:20:08.970
That feels nice right there.

01:20:08.970 --> 01:20:10.388
I don't even know where
that was goin'.

01:20:10.388 --> 01:20:13.391
- I was just thinkin' of that one.

01:20:13.691 --> 01:20:17.354
- Automatic...droppin' from the sky...

01:20:18.396 --> 01:20:21.399
Pollinatin’ left and right...

01:20:23.193 --> 01:20:26.363
Against the pesticides, Ohhhh!

01:20:31.368 --> 01:20:33.829
I was hired by
Michigan State University

01:20:33.831 --> 01:20:36.001
to open a site that they named

01:20:36.003 --> 01:20:38.360
Michigan State
University-Detroit Partnership

01:20:38.360 --> 01:20:39.960
for Food, Learning and Innovation.

01:20:39.960 --> 01:20:44.422
I think they were trying to set a
world record for length of site title.

01:20:44.923 --> 01:20:48.385
And my job is to turn it into
an urban agriculture,

01:20:48.385 --> 01:20:51.388
urban forestry research
and demonstration site.

01:20:51.638 --> 01:20:55.058
So here at this site we have
a cover crop experiment.

01:20:55.058 --> 01:20:58.061
We're doing soil management,
soil restoration.

01:20:58.061 --> 01:21:01.314
We're creating healthy soils
that you can produce vegetables in,

01:21:01.314 --> 01:21:06.987
and then I trust that I benefit
from all of those things as well.

01:21:08.154 --> 01:21:11.157
So, it's a lot of trust in the system.

01:21:16.790 --> 01:21:21.501
Detroit for me, as a predominantly
Black city, was really appealing.

01:21:21.501 --> 01:21:25.839
But then also Detroit as the city
that has been through

01:21:25.839 --> 01:21:29.926
so much economic strife, racism, etc.,

01:21:30.302 --> 01:21:35.432
it's a really great place
to be connected to innovation.

01:21:35.891 --> 01:21:39.436
The people who come to Detroit
and live in Detroit and work in Detroit

01:21:39.853 --> 01:21:41.021
are people who are doing work

01:21:41.021 --> 01:21:44.024
that is relevant and, like, the work
that people should be doing.

01:21:44.816 --> 01:21:47.777
Grow food, share food,

01:21:47.777 --> 01:21:50.780
localize economic systems,
educational system.

01:21:50.780 --> 01:21:54.075
There's just that whole historical,
like, work ethic of Detroit.

01:21:54.534 --> 01:21:57.495
And it's super meaningful
and refreshing to be, like,

01:21:57.495 --> 01:22:00.098
a part of that.

01:22:06.504 --> 01:22:09.507
There was a building here,
the Lafayette Building,

01:22:09.674 --> 01:22:15.221
which was abandoned for decades,
and it was torn down in 2011.

01:22:16.014 --> 01:22:19.851
And it's really for people
to come in and envision

01:22:20.268 --> 01:22:22.938
what they can do on a vacant lot.

01:22:22.938 --> 01:22:26.999
So one of our missions
is to help Detroit

01:22:27.001 --> 01:22:28.899
one lot at a time, you know,

01:22:28.901 --> 01:22:31.404
one vacant lot at a time, because
there's so much vacant land here.

01:22:32.155 --> 01:22:33.615
We get a lot of bees here.

01:22:33.615 --> 01:22:37.243
There's been more honey bees here
than were last year.

01:22:37.243 --> 01:22:39.537
That's the only thing
I can compare it to.

01:22:39.537 --> 01:22:43.083
We also just get a lot of wild bees.

01:22:46.002 --> 01:22:49.212
When we sampled for bumble bees here,

01:22:49.214 --> 01:22:50.215
along with a bunch of other bees,

01:22:50.215 --> 01:22:54.552
we found that this site had literally
only one less than our most

01:22:55.011 --> 01:22:57.973
quote unquote "natural site" in our
nature reserve in a prairie.

01:22:58.765 --> 01:23:00.725
Something like this is going to
attract bees for certain,

01:23:00.725 --> 01:23:04.938
but what we found kind of along
the urban gradient from very natural

01:23:04.938 --> 01:23:08.566
to very urban, coming into Detroit
was a decrease of bumble bees

01:23:08.566 --> 01:23:10.443
and then a little bit of an uptick
toward the end.

01:23:10.443 --> 01:23:11.820
And that was all in Detroit.

01:23:11.820 --> 01:23:15.615
And the average number of bees in Detroit
was much higher than the trendline

01:23:15.615 --> 01:23:17.033
should have suggested.

01:23:17.033 --> 01:23:20.662
So it's going to take more studying to
be 100?rtain why that's happening.

01:23:20.662 --> 01:23:25.000
But everything that seems
to kind of make sense as to why Detroit

01:23:25.000 --> 01:23:29.295
would be helpful for bees was at least
mirrored in the data that we had.

01:23:45.520 --> 01:23:49.999
There had been a number of studies
at the time we started

01:23:50.001 --> 01:23:51.526
that hinted that city spaces

01:23:51.526 --> 01:23:55.989
were surprisingly habitable spaces
for a lot of wild bees,

01:23:56.573 --> 01:23:59.409
even in comparison to more rural sites,
because rural sites

01:23:59.409 --> 01:24:01.661
might be surrounded
by industrial agriculture.

01:24:01.661 --> 01:24:06.374
In Detroit, you have the most urban space,
but it also has a bunch of vacant land,

01:24:06.916 --> 01:24:08.999
a bunch of places that's
not being mowed,

01:24:09.001 --> 01:24:12.088
not being sprayed with pesticides,
not being sprayed with herbicides.

01:24:12.088 --> 01:24:13.798
So you're not killing the
insects directly,

01:24:13.798 --> 01:24:15.258
you're not killing their
flowers directly

01:24:15.258 --> 01:24:18.261
that they want to get food from.

01:24:22.898 --> 01:24:23.898
Hey, hey.

01:24:25.001 --> 01:24:26.001
- Saturday!

01:24:26.003 --> 01:24:27.003
- Yeah, right.

01:24:27.005 --> 01:24:28.772
Sometimes it doesn't feel like it.

01:24:28.772 --> 01:24:29.981
Forget what day it is all the time.

01:24:29.981 --> 01:24:32.150
- Weather's been holding out.

01:24:32.150 --> 01:24:35.653
- Naim was a big part of us
finding places to do our work.

01:24:36.905 --> 01:24:38.890
- The research Paul was involved in

01:24:38.890 --> 01:24:42.285
kind of indicated
two basic takeaways for me.

01:24:42.494 --> 01:24:45.538
One is Detroit as a city

01:24:45.538 --> 01:24:49.999
that's considered kind of
disinvested or in urban decline

01:24:50.001 --> 01:24:55.340
has a disproportionate amount of
space where humans are absent.

01:24:56.174 --> 01:24:58.510
And from the vacant land,

01:24:58.510 --> 01:25:01.001
the unoccupied land, the fallow land,

01:25:01.003 --> 01:25:04.349
has come abundance
from an ecological perspective.

01:25:04.349 --> 01:25:08.603
So insects and all types of species
are actually thriving

01:25:08.895 --> 01:25:11.648
where humans are leaving.

01:25:11.648 --> 01:25:13.817
But at the same time,

01:25:13.817 --> 01:25:17.028
urban agriculture has also taken off
and demonstrated

01:25:17.028 --> 01:25:21.366
that humans can play a very active role
in creating reservoirs,

01:25:21.741 --> 01:25:25.245
food spaces, habitat and spaces
that are just very supportive

01:25:25.245 --> 01:25:28.248
of biodiversity and
species conservation.

01:25:28.665 --> 01:25:30.041
- Thank you, Naim.  Appreciate it.

01:25:30.041 --> 01:25:32.460
Everything good? All right.

01:25:32.460 --> 01:25:33.753
Peace.  Peace.

01:25:33.753 --> 01:25:36.256
Well, so we started in 2006.

01:25:36.256 --> 01:25:39.467
And frankly, when we started in 2006,

01:25:39.467 --> 01:25:42.470
the main organizations doing
urban ag in Detroit,

01:25:42.470 --> 01:25:45.933
or doing what we now call
"food justice work",

01:25:45.933 --> 01:25:47.433
were white-led nonprofits.

01:25:47.433 --> 01:25:50.271
And while I'm not against
white-led nonprofits,

01:25:50.271 --> 01:25:54.399
in a city that's 80-some percent
African-American,

01:25:54.399 --> 01:25:57.008
to have all the people leading the
food work be white people

01:25:57.009 --> 01:25:58.820
was highly problematic for us.

01:25:58.820 --> 01:26:03.575
And so initially one of the things
we wanted to do was create a vehicle

01:26:03.575 --> 01:26:06.787
for Detroit's African-American
community to participate

01:26:06.787 --> 01:26:11.541
in the food movement in a robust way
and contribute to the public discourse

01:26:12.041 --> 01:26:14.752
around urban ag and
food system reform.

01:26:14.752 --> 01:26:16.296
And so it's very difficult now

01:26:16.296 --> 01:26:19.340
to have a discussion about food
system work or urban ag in Detroit

01:26:19.632 --> 01:26:22.635
without a discussion
on racial justice and equity.

01:26:23.303 --> 01:26:27.140
We now have a seven acre farm
where we we’re providing a vehicle

01:26:27.140 --> 01:26:31.227
for people to learn about
urban agriculture and to learn

01:26:31.227 --> 01:26:34.522
about the process of working together,
which is equally as important.

01:26:35.023 --> 01:26:39.110
Trying to be more reconnected with
the cycles of nature was definitely part

01:26:39.110 --> 01:26:43.198
of our thinking from the very beginning
and part of how we approach agriculture.

01:26:43.364 --> 01:26:46.451
We're trying to shift how we see
our relationship to the Earth

01:26:46.451 --> 01:26:49.120
and to the creatures that
co-inhabit the Earth with us.

01:26:49.120 --> 01:26:52.040
A lot of times, human beings,
we walk around and stick our chest out

01:26:52.040 --> 01:26:54.083
and say, "I'm human!",
but we're totally dependent

01:26:54.083 --> 01:26:57.128
on these little insects,
so we need to dial it back a notch

01:26:57.503 --> 01:26:59.505
and realize we're part of
the matrix of life

01:26:59.505 --> 01:27:02.759
and that we're totally in an
interdependent situation

01:27:03.092 --> 01:27:05.929
with the other plants and animals
that we co-inhabit the planet with.

01:27:09.641 --> 01:27:12.999
Detroit is both a blessing and
a curse happening here,

01:27:13.001 --> 01:27:14.896
the tremendous amount of
vacant land and blight.

01:27:15.230 --> 01:27:18.024
But on another level it provides
the opportunity for us to do

01:27:18.024 --> 01:27:21.027
urban ag on a scale that can't be done
anywhere else in the United States.

01:27:23.529 --> 01:27:25.281
I want living things to be able

01:27:25.281 --> 01:27:28.284
to live their whole life cycle,
like, on this site.

01:27:28.660 --> 01:27:33.539
Reintroducing native plants and doing
everything I know to be beneficial

01:27:33.539 --> 01:27:36.542
to pollinators, insects, soil health,

01:27:36.668 --> 01:27:39.671
climate change, all that stuff,

01:27:40.088 --> 01:27:43.091
the best life I could possibly
imagine for myself.

01:27:43.800 --> 01:27:45.051
- I'm gonna look at that
bumble bee quick, pardon me.

01:27:54.435 --> 01:27:56.999
This is either fervidus
or pensylvanicus,

01:27:57.002 --> 01:27:58.996
both of which are rare.

01:27:58.999 --> 01:28:00.524
So, it's the same thing we saw
the queen of earlier.

01:28:00.524 --> 01:28:01.818
This is great.

01:28:01.818 --> 01:28:02.944
But yeah, you have multiple species.

01:28:03.999 --> 01:28:04.999
- Woo-hoo!

01:28:09.099 --> 01:28:11.494
We wanna get to the other side

01:28:11.828 --> 01:28:16.958
of disinvestment, blight,
globalization, segregation.

01:28:16.958 --> 01:28:19.999
We wanna to see, like,
what a beautiful community

01:28:19.999 --> 01:28:21.999
that our hearts tell us can exist.

01:28:22.004 --> 01:28:24.716
where you know your neighbors
and you know who grew your food.

01:28:25.133 --> 01:28:29.999
But I'm really trying to live my life
to make the world a better place.

01:28:37.353 --> 01:28:39.022
Ah yes, I was right.

01:28:39.022 --> 01:28:40.902
I had a reason for going right here,

01:28:40.905 --> 01:28:41.905
and there it is.

01:28:41.932 --> 01:28:44.235
They're perennial white buckwheat.

01:28:44.777 --> 01:28:48.530
It's a very important butterfly
resource which is disappearing

01:28:48.533 --> 01:28:50.992
because it's habitats are being developed

01:28:52.243 --> 01:28:55.001
as residential neighborhoods
in Folsom,

01:28:55.250 --> 01:28:57.250
as industrial parks, as malls,

01:28:57.498 --> 01:28:58.541
all kinds of things.

01:28:58.541 --> 01:29:00.710
So, it's becoming quite scarce.

01:29:00.710 --> 01:29:05.613
Oh, there's absolutely nobody here
at this tall buckwheat.

01:29:06.924 --> 01:29:08.418
Horrible.

01:29:08.718 --> 01:29:11.221
Where is everybody?

01:29:28.446 --> 01:29:31.324
Land use changes appear to be

01:29:31.324 --> 01:29:35.203
the biggest factor in butterfly
declines at low elevation here.

01:29:36.120 --> 01:29:39.123
And when you do the math,

01:29:39.332 --> 01:29:43.795
you find that habitat loss
and pesticides contribute

01:29:43.795 --> 01:29:49.299
about equally to the probable
causation of the butterfly declines.

01:29:49.550 --> 01:29:53.096
Climate was not likely to be
responsible for that.

01:29:56.150 --> 01:30:00.103
What appeared to be the major
factor was habitat loss

01:30:00.728 --> 01:30:03.356
or habitat conversion,

01:30:03.356 --> 01:30:06.818
or lack of continuity of habitats.

01:30:06.859 --> 01:30:09.001
Connectivity.

01:30:10.905 --> 01:30:13.699
Almost all organisms exist

01:30:13.699 --> 01:30:18.204
in suites of interconnected populations
that ecologists call metapopulations.

01:30:19.872 --> 01:30:21.416
They're semi-independent,

01:30:21.416 --> 01:30:24.794
so you have population fluctuations
over here and over here

01:30:24.836 --> 01:30:27.239
with occasional movement between them.

01:30:27.880 --> 01:30:29.841
That occasional movement
is really important

01:30:29.841 --> 01:30:31.300
because the occasional movement

01:30:31.300 --> 01:30:34.929
will rescue this population when it's
going through a natural downturn.

01:30:35.388 --> 01:30:39.559
And so even if you maintain this area
in this area, if organisms can't move

01:30:39.559 --> 01:30:43.855
as easily between them,
you will see eventual decline.

01:30:46.441 --> 01:30:49.360
When the habitat gets fragmented,

01:30:49.360 --> 01:30:52.363
the resources you need are over there.

01:30:52.697 --> 01:30:57.416
And you're a gravid female looking
for resources, and you're over here,

01:30:57.420 --> 01:31:00.705
and between where you are
and where the plants are

01:31:01.414 --> 01:31:05.426
you've got all this butterfly
unfriendly habitat.

01:31:05.426 --> 01:31:06.999
And your odds of getting through that

01:31:07.002 --> 01:31:10.756
and finding what you need
to find are very low.

01:31:10.756 --> 01:31:12.967
So the idea is to

01:31:12.967 --> 01:31:15.470
make their trip easier.

01:31:17.972 --> 01:31:19.808
- Pull that through.

01:31:20.308 --> 01:31:24.145
- We are working with a local
conservation group nonprofit

01:31:24.520 --> 01:31:28.483
that is focused on conserving
pollinators and helping pollinators.

01:31:28.816 --> 01:31:30.885
- I think we could get
two more, though.

01:31:30.985 --> 01:31:32.570
I think I have enough money
to get two more.

01:31:32.570 --> 01:31:33.870
If you have two more,
do you have two more?

01:31:33.870 --> 01:31:34.847
- Yeah.

01:31:34.847 --> 01:31:37.999
So they have what they call
a pollinator pathway,

01:31:38.001 --> 01:31:41.901
and they are working with all
different property owners

01:31:41.903 --> 01:31:44.899
to find ways to introduce
more native plants

01:31:45.002 --> 01:31:47.101
into the landscape to help pollinators.

01:31:49.879 --> 01:31:51.005
My name's Louise Washer.

01:31:51.005 --> 01:31:53.132
I'm the president of the Norwalk River
Watershed Association.

01:31:53.132 --> 01:31:56.928
I want to thank you so much for
coming out and volunteering today.

01:31:56.928 --> 01:32:01.349
One of the things we do is restore
habitat and open space.

01:32:01.599 --> 01:32:05.186
And so one of our projects is the
pollinator pathway started in Wilton,

01:32:05.186 --> 01:32:07.939
and right now we are launching Norwalk.

01:32:09.315 --> 01:32:10.199
You know what?

01:32:10.201 --> 01:32:12.585
If you're taking on these big guys,
you might need a pickax.

01:32:12.985 --> 01:32:15.388
There's more of those
if people are looking for 'em.

01:32:16.906 --> 01:32:18.407
So, we're doing that here today.

01:32:18.407 --> 01:32:21.099
And from here, hopefully we're going
to connect up and down

01:32:21.102 --> 01:32:23.001
the Norwalk River Valley Trail

01:32:23.003 --> 01:32:27.291
to plant pollinator-friendly plants along
the trail as the new sections go in.

01:32:27.416 --> 01:32:29.999
So, the idea is to create a greenway.

01:32:30.101 --> 01:32:33.565
It's habitat for bees,
butterflies, birds.

01:32:33.730 --> 01:32:36.899
Connecting our parks and open spaces
by having people do this

01:32:36.903 --> 01:32:38.219
in their yards, as well.

01:32:38.219 --> 01:32:41.514
Between the open spaces,
people are planting native plants

01:32:41.639 --> 01:32:44.642
and not using pesticides.

01:32:47.442 --> 01:32:51.148
Part of what we're going in addition
to planting is taking out

01:32:51.148 --> 01:32:53.001
some of the invasive plants
that are here,

01:32:53.003 --> 01:32:55.101
because they crowd out the natives.

01:32:58.698 --> 01:33:01.033
What is supposed to be growing here,

01:33:01.033 --> 01:33:04.537
and what insects come
when you let those things grow?

01:33:04.787 --> 01:33:06.131
I didn't know what a native bee was.

01:33:06.133 --> 01:33:07.831
Like, now I'm (gasps).

01:33:07.836 --> 01:33:09.041
You know, "There's a sweat bee!"

01:33:09.041 --> 01:33:12.044
So it's been a, like, really
life-changing thing for me.

01:33:16.007 --> 01:33:18.792
Our plan is to continue to
talk to people

01:33:18.795 --> 01:33:22.430
who are living on this pathway
between those open spaces

01:33:22.430 --> 01:33:27.184
and get them to see that their
backyards and front yards are habitat

01:33:27.184 --> 01:33:30.938
and are on this trail that we're creating
that's connecting the open spaces,

01:33:30.938 --> 01:33:33.941
and empower people to do
something in their own yard.

01:33:47.670 --> 01:33:51.709
Just down the street there's two women
who have a garden just like this.

01:33:52.585 --> 01:33:53.585
Hi.

01:33:53.588 --> 01:33:54.588
- How ya doin'?

01:33:54.591 --> 01:33:55.591
- Good.

01:33:56.505 --> 01:33:59.508
These are my fellow travelers.

01:34:00.259 --> 01:34:04.180
And as you can see,
the pollinators like it.

01:34:06.349 --> 01:34:09.310
Gets their seal of approval.

01:34:14.357 --> 01:34:18.194
I suspect there's some back and forth

01:34:18.361 --> 01:34:21.947
for the pollinators going back and
forth between our two gardens.

01:34:24.200 --> 01:34:27.161
If I could, if I had the money,

01:34:27.244 --> 01:34:31.932
I would make my neighbor an
offer he couldn't refuse

01:34:31.934 --> 01:34:35.628
and just turn the whole thing
into a garden.

01:34:36.796 --> 01:34:40.800
Unfortunately, the zoning
won't permit that.

01:34:41.717 --> 01:34:43.761
I would have to build something here

01:34:43.761 --> 01:34:47.181
that's a multi-unit structure,

01:34:48.474 --> 01:34:50.601
because...

01:34:50.601 --> 01:34:52.561
that's...

01:34:52.561 --> 01:34:55.164
city policy.

01:35:19.171 --> 01:35:21.340
It's amazing how much
food you produce.

01:35:21.340 --> 01:35:23.999
And you don't need to use any
pesticides or any chemicals at all

01:35:24.001 --> 01:35:26.429
to grow food like this,
it's really easy.

01:35:26.429 --> 01:35:27.722
Don't get any big pest problems

01:35:27.722 --> 01:35:29.974
'cause you haven't got huge
monocultures of crops.

01:35:29.974 --> 01:35:31.851
You've just got little patches
of different crops.

01:35:31.851 --> 01:35:35.479
So it's really hard to, you know,
lots of natural enemies of pests.

01:35:35.896 --> 01:35:39.999
I think part of the answer is getting
millions more people growing food

01:35:40.001 --> 01:35:41.501
in a small scale.

01:35:48.367 --> 01:35:51.370
These are solitary bee hotels.

01:35:53.706 --> 01:35:57.042
Each female bee adopts one of these
holes and she starts at the bottom.

01:35:57.418 --> 01:35:59.399
She puts a little pile of
yellow pollen,

01:35:59.401 --> 01:36:00.401
lays an egg on it,

01:36:00.403 --> 01:36:03.033
and then seals it up with a mud wall.

01:36:03.133 --> 01:36:04.999
They're kind of brown pupae
in there at the moment,

01:36:05.001 --> 01:36:07.261
which should be hatching any day.

01:36:08.055 --> 01:36:11.390
Yeah, mining bees,
very sweet little things.

01:36:12.183 --> 01:36:14.852
It's really easy to make your
garden bee friendly.

01:36:14.852 --> 01:36:18.814
Yeah, I spend a lot of my life
trying to persuade people to plant

01:36:19.106 --> 01:36:22.568
wildflowers and bee-friendly flowers
and stick up a bee hotel

01:36:22.568 --> 01:36:24.612
and not spray insecticides around.

01:36:24.612 --> 01:36:26.489
And that's all you have to do, really.

01:36:26.489 --> 01:36:29.366
And you don't need to have a garden
that looks a mess.

01:36:29.366 --> 01:36:31.452
Like, mine's a bit of a mess in places,

01:36:31.452 --> 01:36:34.747
but that's just because I'm too lazy
to keep it all under control.

01:36:34.914 --> 01:36:39.668
Imagine if every garden was full of
wildflowers and bees, and suchlike.

01:36:40.669 --> 01:36:42.755
Adds up to a lot of land.

01:36:42.755 --> 01:36:46.050
You know, in Britain the area of
gardens is more than a million acres.

01:36:46.050 --> 01:36:49.428
So, that's more than all of our
nature reserves put together.

01:36:49.678 --> 01:36:53.182
If we could make them all bee friendly
it would really help.

01:36:53.182 --> 01:36:55.999
Might not be enough to turn
them around completely,

01:36:56.002 --> 01:36:58.564
but it'd be a step in
the right direction.

01:37:02.149 --> 01:37:03.692
So, there's one of these mason bees.

01:37:03.692 --> 01:37:06.695
First one I've seen this year,
actually, so that a male

01:37:07.947 --> 01:37:10.950
just kind of checking out
the nests there.

01:37:11.075 --> 01:37:13.369
The males hang around.

01:37:13.369 --> 01:37:14.372
So these are...

01:37:14.377 --> 01:37:16.977
If we stop using pesticides tomorrow,

01:37:17.081 --> 01:37:20.084
actually I think it would be
a pretty wonderful thing.

01:37:21.585 --> 01:37:23.712
Organic farming produces

01:37:23.712 --> 01:37:27.424
on average about 80% of the
yield of conventional farming.

01:37:27.424 --> 01:37:30.886
So, that would mean a drop in food
production in the short term.

01:37:31.387 --> 01:37:33.514
Some people say that
that would be a disaster

01:37:33.514 --> 01:37:35.307
because we then have to rip up
a whole load more

01:37:35.307 --> 01:37:38.936
natural habitats and start farming
them to make up for the deficit.

01:37:39.436 --> 01:37:43.315
I would disagree, I think there are
different ways you could tackle it.

01:37:43.858 --> 01:37:47.528
And with a bit of investment in research
I think the yields from those kinds of

01:37:47.528 --> 01:37:50.190
farming could be just as high as
they are from conventional farming,

01:37:50.192 --> 01:37:51.192
maybe higher.

01:37:51.448 --> 01:37:54.410
What a cool world it would be
if suddenly there were no pesticides

01:37:54.410 --> 01:37:55.369
to worry about at all.

01:39:41.350 --> 01:39:43.060
Ecologists and natural scientists,

01:39:43.060 --> 01:39:45.479
we build models and we
accumulate evidence for them.

01:39:45.479 --> 01:39:49.108
And right now the best model we have for
what's happening in natural ecosystems

01:39:49.316 --> 01:39:50.693
is a suite of stressors

01:39:50.693 --> 01:39:54.697
that are happening in concert,
pushing on natural populations.

01:39:54.905 --> 01:39:58.242
That is the model we have that explains
what is going on.

01:39:58.242 --> 01:40:00.035
That's different than proving
any one factor.

01:40:00.035 --> 01:40:04.331
We don't need to do that in order to
act and make things better.

01:40:06.291 --> 01:40:08.836
- What makes you want to get into
butterflies and stuff?

01:40:08.836 --> 01:40:12.419
- Oh, I've been doing it my
entire career, 50 years.

01:40:12.423 --> 01:40:14.299
- What have you found out
about butterflies?

01:40:14.999 --> 01:40:16.427
- A hell of a lot,
more than I can tell you.

01:40:16.468 --> 01:40:17.468
- Like what?

01:40:17.470 --> 01:40:18.846
- Oh, we've learned what they eat.

01:40:18.846 --> 01:40:20.305
We leanred where they migrate.

01:40:20.305 --> 01:40:21.974
We learned about their genetics.

01:40:23.142 --> 01:40:24.309
All kinds of things.

01:40:24.309 --> 01:40:26.979
- But everything, in some kinda way,

01:40:26.979 --> 01:40:30.482
I believe that butterflies in some
kind of way can help mankind.

01:40:30.816 --> 01:40:34.778
Well, aesthetically they can,
'cause people like to look at them.

01:40:34.778 --> 01:40:35.778
- Not look at them.

01:40:35.829 --> 01:40:37.406
For us.

01:40:37.406 --> 01:40:38.365
In some kind of way.

01:40:38.365 --> 01:40:40.784
- Okay, that's a spiritual belief.

01:40:40.784 --> 01:40:42.777
I don't deal in religion,
I deal in science.

01:40:42.777 --> 01:40:43.777
- Me either.

01:40:46.165 --> 01:40:48.584
He’s way over there.

01:40:48.584 --> 01:40:49.918
Religion separates people.

01:40:50.318 --> 01:40:51.754
And we need something
better than that.

01:40:51.754 --> 01:40:53.255
We need something that's gonna
pull us together.

01:40:53.255 --> 01:40:54.350
- I quite agree.

01:40:56.050 --> 01:40:56.857
- But anyway.

01:40:56.859 --> 01:40:58.052
Like Butterflies.

01:40:58.452 --> 01:40:59.845
Butterflies will pull us together.

01:40:59.845 --> 01:41:01.680
- I hope so.

01:41:01.680 --> 01:41:03.640
Okay we gotta go, have a good one.

01:41:03.640 --> 01:41:04.683
- Okay.

01:41:04.683 --> 01:41:07.086
He's a little sufferin', though.

01:41:07.686 --> 01:41:08.686
He is.

01:41:08.999 --> 01:41:11.231
When he got his eye on the prize,

01:41:12.357 --> 01:41:14.943
there is no other way that, you know.

01:41:14.943 --> 01:41:17.536
It's like you can't teach a
old dog new tricks.

01:41:18.113 --> 01:41:20.107
- Oh, there are two of them.

01:41:20.616 --> 01:41:23.019
Now they're fighting.

01:41:24.703 --> 01:41:27.199
Male-on-male territorial dispute.

01:41:33.128 --> 01:41:35.273
(imitates cow mooing)

01:41:36.001 --> 01:41:37.301
Okay.

01:41:39.401 --> 01:41:43.597
One thing is clear from studying
the fossil record of extinction.

01:41:43.889 --> 01:41:46.892
We're not at one of the
Big Five extinctions yet.

01:41:47.476 --> 01:41:50.479
We're setting up the world
for big extinction

01:41:51.313 --> 01:41:54.316
if we don't mitigate what
we're doing now.

01:41:56.401 --> 01:41:59.404
And so the question is,
what's going to happen next?

01:41:59.655 --> 01:42:01.782
And that's really hard to predict.

01:42:01.782 --> 01:42:04.785
Part of that depends on
what we do next.

01:42:16.463 --> 01:42:20.092
♪ Yeah, we're gonna to take
that flower nectar to go ♪

01:42:20.092 --> 01:42:23.478
♪ It's gonna become honey
for your soul ♪

01:42:23.422 --> 01:42:27.099
♪ We’re gonna take that
flower nectar to go ♪

01:42:27.099 --> 01:42:30.853
♪ It's gonna become honey
for your soul ♪

01:42:37.818 --> 01:42:39.611
♪ We gotta pollinate the plants ♪

01:42:39.611 --> 01:42:41.598
♪ Black and yellow pants ♪

01:42:41.600 --> 01:42:42.698
♪ Fuzzy and we’re small ♪

01:42:42.698 --> 01:42:45.576
♪ and we do the wiggle dance ♪

01:42:45.576 --> 01:42:48.579
♪ Hop into a flower,
take a pollen shower ♪

01:42:48.871 --> 01:42:52.666
- That's all we got so far.
(all laughing)

01:42:57.838 --> 01:42:59.047
- As you find your voice,

01:42:59.047 --> 01:43:02.050
know that you always have a way
of expressing yourself.

01:43:02.259 --> 01:43:04.999
You can build tools,
you can build houses,

01:43:05.002 --> 01:43:06.771
you can write a new constitution.

01:43:06.773 --> 01:43:10.100
Like, there's no limit to
your creative ability.

01:43:10.267 --> 01:43:14.271
So today was just, like,
a little microcosm,

01:43:14.479 --> 01:43:17.316
if you will, of, like, all the things

01:43:17.316 --> 01:43:20.027
that you're truly capable of.

01:43:20.027 --> 01:43:22.237
Okay, catch you later.

01:43:22.237 --> 01:43:23.237
- Thank you!

01:43:23.239 --> 01:43:24.239
- Ciao.

01:43:25.273 --> 01:43:29.211
I'm personally very optimistic

01:43:29.411 --> 01:43:32.414
that we can solve
the mass extinction problem

01:43:32.956 --> 01:43:36.002
because we know what it is,

01:43:36.461 --> 01:43:40.881
we're measuring its magnitude
with increasing precision,

01:43:41.757 --> 01:43:44.884
and these solutions that have
been suggested,

01:43:44.884 --> 01:43:47.584
they are doable.

01:43:48.972 --> 01:43:51.767
All we have to do is
give the bugs a chance.