WEBVTT
Kind: captions
Language:  en

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[background conversations]

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[Music]

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[inaudible conversations]

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Good evening.
- [multiple responses]

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- And welcome to the latest
installment in the U.S. Geological

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Survey public lecture series.
I’m Helen Gibbons from the

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Pacific Coastal and Marine
Science Center in Santa Cruz.

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And I have the pleasure of working
with tonight’s speaker, Curt Storlazzi.

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Before I introduce Curt,
I would like to urge you all

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to come back for next
month’s lecture on May 31st.

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The title of that is
Yes, Humans Really Are

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Causing Earthquakes –
How Energy Industry Practices

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Are Causing Earthquakes
in America’s Heartland.

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As a reminder, you can
pick up a flier on the back table.

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And now to tonight’s lecture about
the role of U.S. coral reefs in

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coastal protection, presented by
research geologist Curt Storlazzi.

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Curt is currently the chief scientist
of the USGS Coral Reef Project.

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He leads a research team of scientists
who examine the geologic and

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oceanographic processes
that affect the sustainability

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of U.S. coral reefs and reef line coasts.
Curt has authored more than

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130 scientific papers, reports,
and book chapters on these topics.

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Curt received his bachelor
of science degree from the

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University of Delaware in 1996
and his Ph.D. from the

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University of California
at Santa Cruz in 2000.

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He has been a research
geologist with the USGS

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Coastal and Marine Geology
Program since 2003,

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working across the Pacific,
Atlantic, Arctic, and Indian Oceans.

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Curt is on the steering committee
for the U.S. Coral Reef Task Force,

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and he regularly contributes
scientific reviews for the

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U.S. Global Change Research Program,
the National Park Service,

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the U.S. Fish and Wildlife Service’s
Landscape Change Cooperatives,

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the USGS Climate Science Centers,
and NOAA’s National Marine

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Sanctuary Program.
The USGS is pleased to

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bring you Curt’s presentation on the
role of coral reefs in protecting coasts.

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Please join me in
welcoming Curt Storlazzi.

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[Applause]

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- Thanks, Helen.

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Well, seeing we’re going to be talking
about a lot of places across the U.S.,

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I first would like to say hafa adai,
talofa, aloha, hola, and good evening.

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Thank you for joining us.

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So today’s presentation –
or, this evening’s presentation

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is going to be about the role of
coral reefs in coastal protection.

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One of the things we’ve done
at the USGS in the hazards mission area

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that the Coastal and Marine
Geology Program I work under,

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is we’re really good at describing
kind of hazards and catastrophic events

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and a lot of times changes to
coastal environments –

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erosion and storm impacts
and degradation of environments

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such as marshes
and coral reefs.

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About a decade – a little more than a
decade ago, our director of the USGS

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kind of challenged many of us to – okay,
let’s talk about some solutions here.

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And it really reframed the
way a lot of us approach things.

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And at least for coral reefs,
this is hopefully a way that we can

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better think about coral reefs and protect
and preserve them as we’re required to

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under U.S. Executive Order 13089,
the U.S. Coral Reef Protection Act.

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So I’m Curt Storlazzi with the
Coastal and Marine Geology Program.

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This work is done in conjunction with
Mike Beck at The Nature Conservancy,

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Borja, Erik, and James Shope at the
University of California at Santa Cruz.

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As with most things we do,
it takes a team to do these things,

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and it’s a real honor to
work with these folks.

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So where are U.S. coral reefs?
Well, the U.S. has about –

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over 22,000 square
kilometers of coral reefs.

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And as you can see from the pie chart,
about 70% of them are in the Pacific.

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In total, the U.S. – U.S. coral reefs
have been estimated by a NOAA

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technical report in 2013 to generate
just a hair over $2 billion annually.

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Now, that’s primarily due to tourism,
fisheries, and ecosystem integrity.

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So why should we
care about coral reefs?

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Well, most importantly,
they’re really the rainforests of the sea.

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If anything, they exceed that.
They have a higher species diversity

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than the rainforests, although they
only cover less than half a percent of the

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ocean’s seafloor – which remember,
the oceans are 70% of the Earth.

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They’re home to, however,
more than 25% of all marine species.

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They’re a primary source of
protein for most island nations.

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They’re also –
importantly, they’re the

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nursery habitat for many larger
oceanic commercial species.

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And obviously, for any of you that
go to these places, obviously tourism

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is a major source of income for
a lot of these small island nations.

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So recently, we’ve done some work
on corals and coastal protection.

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Here’s a plot.
Across the X axis here is incident

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or incoming wave energy plot
versus wave energy dissipated.

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And what this shows
is that reefs reduce

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about 97% of the
incoming wave energy.

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So they actually act like kind of natural
breakwaters, protecting coastlines.

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More recently,
the U.S. Department of Defense –

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we have wrapped up a project –
actually, we wrapped up the

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project yesterday [chuckles]
for the U.S. Department of Defense

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looking at the roles of coral reefs on
wave-driven flooding of coastlines.

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And so here on the X axis, we’re talking
about reef hydrodynamic roughness.

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So no roughness
is a smooth reef.

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High hydrodynamic
roughness has a lot of live coral.

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So think about – like, they stick up
and it’s – like, causes a lot of friction.

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And what we see is, if we start over
here on the right side with high, good,

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healthy coral reefs, they dissipate a lot of
wave energy and cause lower flooding.

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But if those coral
reefs get degraded,

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it results in much higher
wave-driven flooding.

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So corals protect coastlines,
however, if they get degraded,

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they become less effective.
You get more coastal flooding.

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However, I think most of you
have seen in the newspapers

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that coral reefs are at risk.
And more than 10% of the world’s

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reefs has already been lost,
and another 60% are threatened

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by anthropogenic activities –
mostly land-based sources of pollution.

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Now, I hate to tell you,
but more like 90% are by global impacts,

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such as temperature-induced
bleaching and ocean acidification.

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And this has been
well-documented, again,

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in the news, scientific
articles, and elsewhere.

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Now, I’m going to make a statement
here that in the U.S., I’d say we

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struggle to protect and preserve our
coral reefs along populated coasts.

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And when I say “populated coasts,”
I mean, like, there’s the

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northwestern Hawaiian islands –
over 1,000 kilometers of coral reefs.

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We really can make those places
protected because no one’s there.

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However, they don’t provide
those services to the people

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who live on the islands.
And so, in the U.S., we average –

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along populated coastlines, less than
1% of the coral reefs are protected.

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Now, to put that in context,
Haiti has 20%.

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And I’d argue that that’s mostly due
to economic and geographic reasons.

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And what I mean by that is, first,
the geographic – like, yeah, let’s go

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make that marine protected area –
protect those coral reefs away from here

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that are, you know,
not in my backyard kind of thing.

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But also for economic
and geographic reasons.

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So say I’ve got a coral reef right here,
but I want to build – and I’m not

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knocking anyone in the construction
industry or anything – but say I want to

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build whatever structure that
may impact those coral reefs.

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Well, I’d argue that, well,
you know the fisheries?

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Well, most of the fish are –
live over on that reef.

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And, well, the high diversity
is over on that reef.

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And all the tourist boats
go on that one over there.

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So we – if we damage my
reef right here, no problem.

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We’re going to be okay.

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And, in return, you know, we’re going
to employ 200 people to build this

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for two years and then 50 people
to maintain it for the next 30 years.

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Yeah, just totally making numbers
up here, but – and so that’s why –

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and then we – then we argue, well,
but there’s ecosystem integrity and –

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well, but you said the
tourists don’t go here.

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And so, you know, it’s –
it usually gets balanced out.

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You know, you’re going
to do a cost-benefit.

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Well, there’s a lot of benefit and,
well, what’s the cost?

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So it seems like it’s lost for that way.
So if their innate beauty, tourism,

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fisheries, and species diversity are
not a compelling enough argument

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for protection and restoration
of coral reefs, what is?

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Well, again, going back to the
one thing we in the hazards mission area

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look at a lot is natural catastrophes.
Now, this is a plot of natural catastrophe

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overall losses in green,
insured losses in blue.

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These are adjusted dollars.
So it’s not just that, oh, well,

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you know, the dollar has gone up.
But these are adjusted losses.

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And so you see it
starting to rapidly grow,

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both the number and the
cost of these catastrophes.

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Why is this? More people.
We build more stuff. It gets damaged.

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Not anything new here. But it is
growing, and it’s growing faster.

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So when we think about coral reef areas,
well, here shows nice – these coral reefs

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causing these waves to break offshore
here off Honolulu and Waikiki,

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protecting a couple billion dollars’
worth of infrastructure.

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Here in Miami, Florida, there’s some
expensive property right there too.

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Hagatna, Guam –
that’s the capital of Guam.

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Key West.

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Pago Pago is the
capital of American Samoa.

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And so, in all these places,
the protection of the shoreline

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is dynamically tied to the health and
quality of those offshore coral reefs.

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Now, not only is it a concern for,
you know, those of us here, but the

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Department of Defense also has some
pretty expensive gear out there too.

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And, you know, the Department of
Defense has over $100 billion worth of

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infrastructure in low-lying places like this
that, again, are protected by coral reefs.

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So going back to that question, you
know, what’s a compelling argument?

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And I’d say
dollars and lives.

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One of our [chuckles] – one of our
people on our executive leadership team

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said to me a couple years ago –
he’s, like, the only thing

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that matters in Congress
is dollars and lives.

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And so, okay, well,
let’s try to see if we can

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quantify the coral reefs
in terms of dollars and lives.

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So my colleague Mike Beck
and [inaudible] Lange did a project

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for the World Bank Group basically
trying to value coastal protection

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services for mangroves and reefs.
And they did this at a global scale.

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Every 10 kilometers around
the world – incredible project.

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And so what they did is,
they measured – they estimated

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or modeled waves offshore,
how they got closer to shore,

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and how they came over habitats,
either over reefs and mangroves.

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And then they estimated the flooding.
So here would be a hypothetical

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flooding line with the habitat.
And then, if you remove that habitat,

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that flooding line is
going to be further inland.

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And then what you do
is you quantify the damages

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between these two,
and that’s the value of that habitat.

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Now, to do this at a global scale,
and to do this with, you know,

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data from disparate countries,
you kind of have to go to

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the lowest
common denominator.

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That’s what you’re stuck
with to do it consistently.

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And so they used kind of some
1980s type of technology and models.

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Because that’s all they could
do with this kind of scale.

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But they did it, and they showed,
you know, coral reefs protect,

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you know, over 200 million
people around the globe.

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And hundreds of millions of dollars,
potentially, of damage.

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So, well, when you get someone
like myself involved, you look –

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sadly, you make things
a lot more complicated.

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And so we basically developed –
here in the U.S., where we’ve got

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a lot more information, a lot more data,
and because – like, we did this project

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on coastal flooding for Department
of Defense, we have a lot more

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complicated tools that give us
a lot more resolution and precision.

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And so we could do it
at a much higher level.

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But it’s a heck of
a lot more complicated.

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And so I apologize, but I’m Italian,
and so I’m going to show you

00:14:28.850 --> 00:14:32.040
how we make sausage.
[laughter]

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So just to explain where we’re
doing this, we’re doing this

00:14:36.180 --> 00:14:39.880
for all U.S. coral
reef line shorelines.

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So that’s the Commonwealth of
the Northern Marianas in Guam.

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Let’s see. Commonwealth
of the Northern Marianas

00:14:46.580 --> 00:14:49.830
is the blue one
right over Helen’s head.

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Guam’s the one on the other side
of the Hawaiian flag over there.

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American Samoa,
which is not flagged over there.

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Hawaii’s the one that
looks like the British flag.

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Then we have Florida, the U.S.
Virgin Islands, and Puerto Rico.

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These all seem like pretty
small areas, right? Little islands.

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Well, if you actually total it up,
it’s over 3,000 kilometers of shoreline.

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Anyone know how long
the U.S. part of the West Coast is?

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2,000.
So it’s actually 50% longer –

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more shoreline than the
U.S. West Coast. That’s a lot.

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And if you actually totaled up
the exclusive economic area,

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the – you know, if you take 200
nautical miles off there of mineral rights,

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water rights, fishery rights,
it’s actually more than the

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U.S. East Coast and
Gulf Coast combined.

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Okay, so sausage. But this is
the cool thing to nerds like me.

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So the first thing we wanted to do is we
wanted to get the wave climate off here.

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And so my colleague Borja Reguero
did a wave hindcast using atmospheric

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models to model waves all around
the globe every hour for 61 years.

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That’s a lot. It was basically his
Ph.D. thesis, but he’s a smart kid.

00:16:07.240 --> 00:16:13.080
And so he did that.
However, we can’t run 61 years

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of hourly data, which is half –
basically half a million data points –

00:16:17.480 --> 00:16:21.640
at all shore – all those reef line
shorelines around the world.

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It’s just way too much.
So a wonderfully brilliant lady,

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Paula Camus, at the
University of Cantabria in Spain,

00:16:30.220 --> 00:16:32.980
developed this technique
where we can pick kind of –

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if there’s a scatter of data, we pick
points in that that best represent it.

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So we can take that half-million data
points and turn it into 500 conditions.

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Which is a lot easier to run. [chuckles]
You know, orders of magnitude less.

00:16:46.580 --> 00:16:51.350
So then what we do is we run those
500 conditions through this model called

00:16:51.350 --> 00:16:54.920
SWAN, or Simulating WAves in the
Nearshore – really standard wave model.

00:16:54.920 --> 00:16:57.060
So this is showing
wave heights –

00:16:57.060 --> 00:17:00.470
so high wave heights in red,
low wave heights in blue.

00:17:00.470 --> 00:17:04.010
This is the tip of the Florida Keys.
So you have big ocean waves.

00:17:04.010 --> 00:17:06.699
As they start to propagate
across the reefs, they start to

00:17:06.699 --> 00:17:09.390
decrease in wave energy,
and so you’ve got much lower

00:17:09.390 --> 00:17:13.520
wave energy close to shore.
So that’s our step here.

00:17:13.520 --> 00:17:17.610
And then what we do is
we bring it – we extract that data

00:17:17.610 --> 00:17:22.100
at these transects every
100 meters along the shoreline.

00:17:23.540 --> 00:17:27.640
So every 100 meters along
3,000 kilometers of shoreline.

00:17:27.640 --> 00:17:29.500
That’s a lot. [laughs]

00:17:29.500 --> 00:17:33.080
Just doing these SWAN models,
we ran 37 SWAN models,

00:17:33.080 --> 00:17:36.200
and that was 98 days
of processor time.

00:17:36.200 --> 00:17:40.240
Thank gosh for numerical
modeling clusters. [chuckles]

00:17:41.160 --> 00:17:45.780
And thank gosh we didn’t do this in the
wintertime when the power goes off.

00:17:45.780 --> 00:17:49.430
So then we set it up
on these cross-shore transects.

00:17:49.430 --> 00:17:55.240
And so – oh, so real quick – at the end
of those cross-shore transects, what we –

00:17:55.240 --> 00:18:00.070
we take Melissa’s mathematical
computations, we regenerate from

00:18:00.070 --> 00:18:07.370
these 500 conditions that 500,000
hourly data points for 61 years.

00:18:07.370 --> 00:18:10.980
And then we use that in a model
to determine return periods.

00:18:10.980 --> 00:18:15.200
So most of the engineers, they want to
know, what’s the five-year wave height,

00:18:15.200 --> 00:18:18.400
the 10-year wave height,
the 100-year wave height.

00:18:19.140 --> 00:18:21.820
I don’t know why – many of you
in here are probably engineers

00:18:21.820 --> 00:18:23.660
and can explain all that –
why you want that,

00:18:23.660 --> 00:18:27.040
but that gives us those
kind of return interval storms.

00:18:27.040 --> 00:18:32.520
And so then, what it allows us to do is
to pick – in our case, we were running

00:18:32.520 --> 00:18:38.740
the 10-, 50-, 100-, and 500-year storms.
But we can pick it off – basically,

00:18:38.740 --> 00:18:42.900
we model a distribution through
the data – some cool math stuff.

00:18:43.820 --> 00:18:46.560
And so, again, that gets us
to our return interval storms.

00:18:46.560 --> 00:18:49.770
And now it’s to model
the effects of the reef.

00:18:49.770 --> 00:18:54.480
So the NOAA Center for Coastal
and Ocean Science undertook,

00:18:54.480 --> 00:19:02.240
in the 2000s, an effort to map all U.S.
coral reefs at a scale of about an acre.

00:19:02.240 --> 00:19:05.430
And so they mapped them –
you see ranges here –

00:19:05.430 --> 00:19:12.970
zero to 10%, 10 to 50% coral cover,
50 to 90% coral cover, or 90 to 100%.

00:19:12.970 --> 00:19:17.540
So this is Lahaina, Maui –
here’s the Lahaina Harbor.

00:19:17.540 --> 00:19:23.610
So this was the original capital of Hawaii
when it was run primarily by whalers.

00:19:23.610 --> 00:19:25.980
And so you see there’s
a distribution of reefs –

00:19:25.980 --> 00:19:29.860
sometimes extend further offshore,
sometimes have higher coral coverage,

00:19:29.860 --> 00:19:34.610
sometimes have lower coral coverage.
And sometimes there’s less of them.

00:19:34.610 --> 00:19:36.940
And so you see, again,
here is our transect

00:19:36.940 --> 00:19:39.940
spaced every 100 meters
along the shoreline.

00:19:39.940 --> 00:19:44.900
So now we have coral coverage
along our cross-reef transects.

00:19:45.490 --> 00:19:48.680
So now I’m showing you an example
of one of these cross-reef transects.

00:19:48.680 --> 00:19:52.150
So this is from some distance offshore.
This is sea level.

00:19:52.150 --> 00:19:54.610
So here’s the shoreline.

00:19:54.610 --> 00:19:58.940
This line is actually –
downtown Lahaina sits right in here.

00:19:58.940 --> 00:20:03.260
And so it goes offshore,
and here’s some reef in red.

00:20:03.260 --> 00:20:07.920
There’s some more coral cover here
and here. Little bit here and here.

00:20:07.920 --> 00:20:12.440
So the top line is
showing it with the reef.

00:20:12.440 --> 00:20:16.110
And then what we do is, based –
my colleague Kim Yates and

00:20:16.110 --> 00:20:21.300
our colleagues in the St. Petersburg
office in Florida have shown that,

00:20:21.300 --> 00:20:27.640
because of pollution, because of
thermally induced bleaching,

00:20:27.650 --> 00:20:30.910
that a lot of reefs
around the globe have decreased.

00:20:30.910 --> 00:20:33.560
The corals have died,
and the reefs have degraded.

00:20:33.560 --> 00:20:35.640
Now, they showed
great variability.

00:20:35.640 --> 00:20:40.420
Some places it’s 6 or 7 feet.
Some places it’s 3 feet.

00:20:40.420 --> 00:20:44.840
Because we don’t have that data all
around – mapped all around the U.S.,

00:20:44.850 --> 00:20:50.640
what we did is we assumed – we just
removed in the model a half-meter –

00:20:50.640 --> 00:20:53.030
about a foot and a half
of the reef and took all those

00:20:53.030 --> 00:20:55.820
live corals and
removed them.

00:20:55.820 --> 00:21:02.020
And so what you’re seeing here is –
the gray is kind of that reef minus the

00:21:02.020 --> 00:21:07.110
coral versus the red’s with the coral.
So now we can run the model

00:21:07.110 --> 00:21:12.059
over the profile with the
reef and without the reef.

00:21:12.059 --> 00:21:15.120
And what that does is,
we used a model call XBeach

00:21:15.120 --> 00:21:21.390
that the U.S. Army Corps of Engineers
and Deltares in the Netherlands

00:21:21.390 --> 00:21:24.360
and the University of Miami
developed to look at storm –

00:21:24.360 --> 00:21:27.590
like, hurricane-induced
flooding and erosion

00:21:27.590 --> 00:21:31.980
along the U.S. sandy shorelines
of the eastern Gulf Coast.

00:21:31.980 --> 00:21:33.660
Works great there.

00:21:33.670 --> 00:21:37.090
However, if you think about
the sandy shores of the East Coast,

00:21:37.090 --> 00:21:42.190
they’re relatively linear.
They’re relatively gently sloping.

00:21:42.190 --> 00:21:46.190
Coral reefs are pretty
much anything but that.

00:21:46.190 --> 00:21:48.710
And so the model didn’t
work for this environment.

00:21:48.710 --> 00:21:53.880
However, working with my colleague
Ap van Dongeren and Ellen Quataert,

00:21:53.880 --> 00:21:59.260
Deltares, during this big DoD project
we just finished up, it let us do enough

00:21:59.270 --> 00:22:03.880
experiments to heavily modify the
model to be able to work for coral reefs.

00:22:03.880 --> 00:22:08.280
And so what we’re showing here is,
this is now the flood level, right at

00:22:08.280 --> 00:22:11.550
this shoreline here. So what you’re
seeing is, red is with the reef.

00:22:11.550 --> 00:22:15.460
So the water levels are about a
half-meter above normal and kind of

00:22:15.460 --> 00:22:19.940
hit the shoreline here with the reef.
Now, when we remove this reef,

00:22:19.940 --> 00:22:24.580
now the flood levels are even
higher and extend further inland.

00:22:25.640 --> 00:22:29.380
So we can model the
effects of the reef.

00:22:31.060 --> 00:22:34.820
And so remember, these are done
every 100 meters along the shoreline.

00:22:34.830 --> 00:22:41.180
So that was a hair over 30,000 models.
And that took us over 1,000 days of

00:22:41.180 --> 00:22:46.020
processor time. Again, thank gosh
for numerical modeling clusters.

00:22:46.860 --> 00:22:50.600
Okay, so now we
can make flood maps.

00:22:50.600 --> 00:22:53.210
So here we’re showing –
this is Key West.

00:22:53.210 --> 00:22:54.770
This is for a
1-in-10-year storm.

00:22:54.770 --> 00:22:57.140
So remember, we’re talking
different return interval storms.

00:22:57.140 --> 00:23:01.150
So this is the – kind of the average
storm you’d see once every 10 years.

00:23:01.150 --> 00:23:04.640
And so the blue dots
are the points where

00:23:04.640 --> 00:23:07.130
those transects
intersect the shoreline.

00:23:07.130 --> 00:23:13.040
This greeny-yellow-ish – sorry – limon –
I don’t know what you’d call that color.

00:23:13.040 --> 00:23:17.080
But this is the flood extent.
And you see it floods inland.

00:23:17.740 --> 00:23:24.200
And that’s with the reef. Now, red is
without the reef, which is further inland.

00:23:24.210 --> 00:23:28.970
And so basically, everything in this
little red zone is the area protected

00:23:28.970 --> 00:23:32.780
by the coral reefs. And hopefully
you can see the resolution of this.

00:23:32.780 --> 00:23:35.760
We’ll zoom in on some places
elsewhere where – we’re doing this

00:23:35.760 --> 00:23:40.780
at every 10 square meters.
So at the scale of your house.

00:23:42.020 --> 00:23:45.940
Along 3,000 kilometers of shoreline.
[chuckles]

00:23:45.940 --> 00:23:50.000
So here shows a 1-in-10-year storm.
Here shows a 1-in-100-year storm.

00:23:50.000 --> 00:23:53.400
So the flood lines are –
bigger storm, bigger waves,

00:23:53.400 --> 00:23:55.559
flooding much
further inland.

00:23:55.559 --> 00:24:00.700
And so, again, you can see the red – the
area between the yellowish whatever and

00:24:00.700 --> 00:24:08.020
the red – the red areas are the areas – the
areas effectively protected by coral reefs.

00:24:08.020 --> 00:24:11.750
One thing you should note here
is that the relative amount –

00:24:11.750 --> 00:24:16.520
while there’s greater flooding here,
the relative amount is actually –

00:24:16.520 --> 00:24:20.440
protected by the reefs is less.
I’ll show that here again.

00:24:21.520 --> 00:24:26.300
So now that we have what we call –
these are flood masks, or this is a mask,

00:24:26.300 --> 00:24:30.560
or a coverage, of the floodwaters.
Now what we can do is start to say,

00:24:30.560 --> 00:24:35.080
well, what’s in those areas?
So the U.S. Census Bureau,

00:24:35.080 --> 00:24:38.380
every 10 years,
conducts the U.S. census.

00:24:38.380 --> 00:24:41.120
They put it in a
database called TIGER.

00:24:41.120 --> 00:24:44.330
And so you have everything
about how many people are there,

00:24:44.330 --> 00:24:46.100
how many people live
in a given household,

00:24:46.100 --> 00:24:50.170
their – you know, whether it’s poverty,
different levels of income,

00:24:50.170 --> 00:24:55.860
their age, sex, education. So you can
parse that out and say, okay, where’s –

00:24:55.860 --> 00:25:00.500
how many elderly people are in a
location? How many young people are –

00:25:00.510 --> 00:25:05.470
education, how many low-income,
minorities – all the information.

00:25:05.470 --> 00:25:10.840
And so our colleague Nate Wood,
who’s in Western Geographic here,

00:25:10.840 --> 00:25:14.980
has developed some really cool tools
that lets you basically dig into

00:25:14.980 --> 00:25:21.559
these incredibly difficult,
confusing databases and assimilate that

00:25:21.560 --> 00:25:25.320
so that we can match our flood
masks and that information.

00:25:26.800 --> 00:25:32.200
So for example,
here is now south Maui.

00:25:32.200 --> 00:25:35.440
Hopefully you can see here – because
I made them a little bit translucent –

00:25:35.440 --> 00:25:39.280
now you’re looking at individual
buildings in those flood masks.

00:25:39.860 --> 00:25:43.660
So pretty high resolution.
Kind of like Google Earth, right?

00:25:43.660 --> 00:25:45.890
What’s the first thing everyone
does in Google Earth?

00:25:45.890 --> 00:25:47.950
Goes and looks
for their house, right?

00:25:47.950 --> 00:25:49.760
So now you can
go look for your house

00:25:49.760 --> 00:25:52.970
and see if it’s protected
by coral reefs or not.

00:25:52.970 --> 00:25:58.350
But so, in this area – the red area, again,
is the area protected by coral reefs.

00:25:58.350 --> 00:26:01.230
And so what we can do is
match that up with census data and say,

00:26:01.230 --> 00:26:07.590
how many people are in those areas?
Are they children? Are they elderly?

00:26:07.590 --> 00:26:09.770
Are they low-income?
Are they high-income?

00:26:09.770 --> 00:26:12.290
Are they minorities?
Are they this, that?

00:26:12.290 --> 00:26:14.440
All that information is in there.
So we can quantify.

00:26:14.440 --> 00:26:17.120
And that’s really good because
we understand the impact.

00:26:17.120 --> 00:26:23.490
Is it disproportionately hitting a certain
age group, a certain income group?

00:26:23.490 --> 00:26:28.200
And we can understand those.
Again, that’s more of an ecological

00:26:28.200 --> 00:26:31.840
kind of thing – or, anthropologic.
But we can do those things.

00:26:31.840 --> 00:26:34.480
Right now,
we’re just counting bodies.

00:26:35.380 --> 00:26:38.700
Now, the Department of
Homeland Security and FEMA

00:26:38.710 --> 00:26:42.400
have a database called Hazus.
And what this does is it has

00:26:42.400 --> 00:26:46.480
all the information about
what those buildings are.

00:26:46.480 --> 00:26:48.880
You know, are they essential facilities?
Are they power plants?

00:26:48.880 --> 00:26:51.990
Are they water treatment plants?
Are they roads?

00:26:51.990 --> 00:26:54.200
Utilities like power?

00:26:54.200 --> 00:26:59.260
High-potential loss facilities,
hospitals – building-specific data.

00:26:59.260 --> 00:27:00.630
And some of the
building-specific data

00:27:00.630 --> 00:27:04.250
is what they have – is what
we call depth-damage curves.

00:27:04.250 --> 00:27:07.430
So this would be, like,
zero depth and some high depth

00:27:07.430 --> 00:27:08.830
and zero damage
and high damage.

00:27:08.830 --> 00:27:12.220
So basically, with no flooding,
nothing gets damaged.

00:27:12.220 --> 00:27:15.470
But say – like, say this line here,
maybe this is a wooden house

00:27:15.470 --> 00:27:19.809
where water gets up to a certain point,
and it tears the whole thing down.

00:27:19.809 --> 00:27:21.400
Maybe this is like
a concrete structure

00:27:21.400 --> 00:27:25.450
where the water gets higher and higher,
and it slowly damages it more.

00:27:25.450 --> 00:27:28.840
So we have all this information,
so it’s not just assuming,

00:27:28.840 --> 00:27:31.840
a building gets wet, it’s damaged.
It’s really, how much it has to get

00:27:31.840 --> 00:27:36.590
wet for that to fail, and that’s based on
the different building properties.

00:27:36.590 --> 00:27:43.020
So great data set, and we can use our
flood masks and the depths in those.

00:27:43.020 --> 00:27:45.880
So, again, here’s our same area.
Our red’s showing our

00:27:45.880 --> 00:27:47.871
area protected by corals.
And we can all the sudden

00:27:47.880 --> 00:27:51.140
go in and say, okay, what’s the
value of those buildings?

00:27:51.140 --> 00:27:54.400
So, you know, in these –
you know, red, we’re talking,

00:27:54.410 --> 00:27:58.530
you know, millions of dollars
of homes and less are here.

00:27:58.530 --> 00:28:00.400
We can also say how
many of those are commercial,

00:28:00.400 --> 00:28:02.840
how many of those industrial,
how many of those are religious,

00:28:02.840 --> 00:28:09.380
how much are those government,
agricultural – my gosh, there’s, like –

00:28:09.380 --> 00:28:11.960
you’d be – it’d blow
your mind how much

00:28:11.970 --> 00:28:13.610
information there is out there.
[laughs]

00:28:13.610 --> 00:28:16.280
But in this case,
we’re just totaling the value.

00:28:16.900 --> 00:28:21.480
And, again, why these numbers
may be small – some of these may be –

00:28:21.480 --> 00:28:25.570
some of these may be partially damaged,
or not damaged at all, because in some

00:28:25.570 --> 00:28:29.881
places, the flood depths are so low.
So, like, if you were to look at some of

00:28:29.881 --> 00:28:33.110
these averages, you’re, like, oh,
well, it’s only 100,000 per building.

00:28:33.110 --> 00:28:35.510
Gosh, this is a place with
really expensive property.

00:28:35.510 --> 00:28:40.300
Well, that just means the property is
not completely destroyed, in some cases.

00:28:41.740 --> 00:28:45.270
So the thing is, is we know,
well, you know, when your

00:28:45.270 --> 00:28:48.420
business is demolished,
it’s kind of hard to work.

00:28:49.100 --> 00:28:54.080
And when your house is demolished, it’s
often hard to stay there and go to work.

00:28:54.080 --> 00:28:56.730
So one of the things we want to
say is kind of a follow-on step

00:28:56.730 --> 00:29:01.850
from this is to look at the
impact for the – basically, the impact

00:29:01.850 --> 00:29:07.670
of the GDP – people’s ability to work.
So it’s kind of that next follow-on step.

00:29:07.670 --> 00:29:10.320
And so one of the calculations
we can make is the number of people

00:29:10.320 --> 00:29:15.130
flooded times the average
GDP per person per year.

00:29:15.130 --> 00:29:20.980
Now, this is a older number because
the census was only done in 2010.

00:29:20.980 --> 00:29:24.780
Hazus was done in 2010.
So we’re using a 2010 GDP number.

00:29:24.780 --> 00:29:32.700
I think the GDP now is 54,600. But we
have to be consistent in our data.

00:29:32.700 --> 00:29:36.400
Then we did the number of
commercial and industrial buildings,

00:29:36.400 --> 00:29:39.350
saying that each one
of those is a business.

00:29:39.350 --> 00:29:41.890
And the average – if you
go to the Department of Labor,

00:29:41.890 --> 00:29:44.520
there’s average
15 employees per business.

00:29:44.520 --> 00:29:49.679
So we just take –
multiply 48,400 times 15 employees.

00:29:49.679 --> 00:29:55.310
That gives us just a hair under
3/4 million dollars per business per year.

00:29:55.310 --> 00:30:01.120
So that we can then go back in here and 
say, okay, well, this is 27 businesses,

00:30:01.120 --> 00:30:07.800
and these are 180 people, and thus
compute an economic disruption.

00:30:10.100 --> 00:30:15.000
So quantifying the benefits.
Basically, we have these kind of plots.

00:30:15.010 --> 00:30:18.500
So along the bottom, it’s showing you
examples – different return periods.

00:30:18.500 --> 00:30:22.040
So a 10-year storm, 100-year storm,
which is much bigger,

00:30:22.040 --> 00:30:26.380
and then a 500-year storm,
which is, like, my gosh, horrible.

00:30:26.380 --> 00:30:29.300
And what we’re showing you here is –
in this example, we’re just showing

00:30:29.300 --> 00:30:34.200
a theoretical population.
And so right now, we have a current –

00:30:34.200 --> 00:30:40.340
or, the existing conditions with our reefs.
And then the red is with reef loss.

00:30:40.340 --> 00:30:44.580
So in all of these cases, the difference
between these two is about 500 people.

00:30:44.580 --> 00:30:49.980
So it’s about, you know,
1,400 to 1,900 in this case.

00:30:49.980 --> 00:30:56.520
So obviously, the – both of them go
up with bigger and bigger storms.

00:30:56.520 --> 00:31:00.990
However, on this side,
we’re showing the percentage change.

00:31:00.990 --> 00:31:07.160
And so that 500 people, for roughly –
or, 400 people for roughly –

00:31:07.160 --> 00:31:12.960
out of 2,000, is actually about,
you know, a little over 30% change

00:31:12.960 --> 00:31:16.390
between this line and this line. However,
these lines are much higher, right?

00:31:16.390 --> 00:31:20.120
So now we’re at 500 –
or, 400 out of 3,500.

00:31:20.120 --> 00:31:23.480
So that’s, you know,
only about 18%.

00:31:23.480 --> 00:31:27.830
And so, even though there’s about
the same amount of people protected

00:31:27.830 --> 00:31:31.340
because this line’s lower here,
it’s a larger proportion.

00:31:31.340 --> 00:31:35.720
So what this actually shows is that
the effectiveness of reefs in hazard

00:31:35.720 --> 00:31:41.680
risk reduction is greater in actually
more frequent, smaller storms.

00:31:42.460 --> 00:31:44.800
Now, why that’s good is,
you don’t have to say, oh, gosh,

00:31:44.800 --> 00:31:49.600
well, it’s only effective in that 500-year
storm, and gosh, we’ll never see that.

00:31:49.610 --> 00:31:53.820
But this is saying the decadal storm,
you’re getting more effective.

00:31:53.820 --> 00:31:57.120
And how long is the average
mortgage on a house?

00:31:57.120 --> 00:31:59.840
You’re going to see a couple
of those kind of storms.

00:31:59.850 --> 00:32:02.570
So it’s not just, oh, this is something
we don’t have to worry about.

00:32:02.570 --> 00:32:04.960
Hey, they’re really effective
at useful time scales –

00:32:04.960 --> 00:32:08.300
on the time scales that
we make financial decisions.

00:32:09.100 --> 00:32:10.680
So now I’m going to
show you some actual –

00:32:10.680 --> 00:32:14.860
some data and some of our calculations.
So both these plots are showing –

00:32:14.860 --> 00:32:19.440
pardon me – [coughs] – the number
of buildings for a bunch of storms.

00:32:19.440 --> 00:32:24.010
So, again, the 10-year, the 50-year,
the 100-year, and the 500-year storms.

00:32:24.010 --> 00:32:29.270
The red is with reefs.
The blue is without reefs.

00:32:29.270 --> 00:32:31.880
So it’s – basically,
when we remove the reefs,

00:32:31.880 --> 00:32:34.860
more buildings are getting –
would get damaged.

00:32:34.860 --> 00:32:37.380
I’m showing you three
sets of numbers here.

00:32:37.380 --> 00:32:41.980
AED is the annual expected damage,
or the expected value of losses

00:32:41.980 --> 00:32:48.720
per year with the reef, would be,
in this example, 169 buildings per –

00:32:48.720 --> 00:32:56.320
or, 169 buildings per year. The annual –
the AED without reefs is 731.

00:32:57.380 --> 00:33:01.100
And then, if we do the annual
expected benefit, or the expected

00:33:01.100 --> 00:33:07.490
value of avoided losses per year,
it’s 500 – basically, 562 buildings

00:33:07.490 --> 00:33:12.060
per year that coral reefs
protect on the island of Maui.

00:33:12.680 --> 00:33:17.080
Here on Guam, where there’s
less development at the coastline –

00:33:17.090 --> 00:33:21.970
it’s mostly up on the high
limestone plateau – lower numbers.

00:33:21.970 --> 00:33:26.260
Same kind of trends.
Increases with increasing storms.

00:33:26.260 --> 00:33:28.220
Without reefs is higher.

00:33:28.220 --> 00:33:33.740
But our annual expected
benefit is now just 19 buildings.

00:33:34.910 --> 00:33:38.100
We go to looking at
the resulting damages.

00:33:38.100 --> 00:33:41.050
So remember, the damage is a
function of – not only is it flooded,

00:33:41.050 --> 00:33:44.920
but how deep it’s flooded and
what the – what kind of building it is.

00:33:44.920 --> 00:33:55.760
We see that the annual expected benefit
is about $63 million per year for Maui.

00:33:55.760 --> 00:34:01.400
And Guam, with the fewer buildings,
is only $4.3 million per year.

00:34:01.400 --> 00:34:04.720
But that’s per year.
So you think, over the lifespan of

00:34:04.720 --> 00:34:10.980
an average building or a mortgage,
that’s – and then, if we do the

00:34:10.980 --> 00:34:13.700
number of people, again,
we have the same numbers.

00:34:13.700 --> 00:34:16.740
With reef, without reef,
and the annual expected benefit.

00:34:16.740 --> 00:34:25.219
It’s about – in Maui, it’s 1,845 people
per year. It’s a pretty big, high number.

00:34:25.219 --> 00:34:29.230
And then the – Guam, again
with fewer people by the coastline,

00:34:29.230 --> 00:34:33.880
it’s only about – just a hair
over 63 people per year.

00:34:34.600 --> 00:34:38.780
Okay, so let’s pull all that together.
So if we look at the damage in

00:34:38.789 --> 00:34:43.799
millions and the number of people
for Guam, we have basically

00:34:43.799 --> 00:34:51.450
$63 million a year in damage and 1,845.
Well, if we take that 1,845 people times

00:34:51.450 --> 00:34:58.320
that annual contribution of GDP
per year, that’s 89 million per year.

00:34:59.690 --> 00:35:03.660
We add that to the property damage,
that totals about $152 million

00:35:03.660 --> 00:35:08.080
in total avoided damages
and economic disruption per year.

00:35:08.980 --> 00:35:12.499
It’s a good number.
And to put that number in context,

00:35:12.499 --> 00:35:19.240
the value of – for all the eight islands
in the state of Hawaii for recreation,

00:35:19.240 --> 00:35:24.559
tourism, and fisheries for all of them
combined is 426 million a year.

00:35:24.559 --> 00:35:28.799
So that 152 – just the damage
risk reduction – hazard risk reduction

00:35:28.799 --> 00:35:32.210
is a third of that.
For one island.

00:35:32.210 --> 00:35:36.290
And remember, Oahu has got
90% of the people and

00:35:36.290 --> 00:35:40.970
probably 90% of the infrastructure.
So basically, we’re going to more than

00:35:40.970 --> 00:35:45.240
double the value of coral reefs
if we include coastal protection.

00:35:48.020 --> 00:35:51.819
And so let’s think about some of the
other things we can do with these tools.

00:35:51.819 --> 00:35:55.509
So we’re modeling
flooding along the coast.

00:35:55.509 --> 00:35:58.240
And so I’m just showing you
our same kind of return period.

00:35:58.240 --> 00:36:02.359
I’m showing you current reefs, future
reefs, and whichever our metric is here.

00:36:02.360 --> 00:36:06.120
But say – let’s talk about
coral reef degradation.

00:36:06.120 --> 00:36:11.470
Like, climate change,
land use practices, sea level rise.

00:36:11.470 --> 00:36:14.499
Well, that’s going to
push that number up.

00:36:14.499 --> 00:36:19.609
And now, again, we can – so if we
degrade the reef more at sea level,

00:36:19.609 --> 00:36:22.700
and that flooding is further inland,
we can, again, use these same

00:36:22.700 --> 00:36:28.040
data sets to quantify the dollars
and lives to say, what’s that value.

00:36:29.940 --> 00:36:34.880
The other thing that’s really neat is
we can do the reverse of that,

00:36:34.880 --> 00:36:41.800
is we can say, here’s the degraded reef.
If we increase the health of it,

00:36:41.800 --> 00:36:45.440
that flood is going to be less –
the flooding is going to be

00:36:45.440 --> 00:36:50.460
less far inland, and now we can –
we can count up, between the –

00:36:50.460 --> 00:36:53.240
before restoration
and the post-restoration.

00:36:53.240 --> 00:36:57.020
And that’s the benefit
of that restoration.

00:36:57.020 --> 00:36:59.820
And this is
becoming really exciting.

00:36:59.820 --> 00:37:02.440
And, again, so that would
drag those values down.

00:37:02.440 --> 00:37:07.780
And so now that area between the two
is the benefit of that restoration.

00:37:08.940 --> 00:37:13.200
So the question is, is how does the U.S.
decide to fund post-disaster restoration?

00:37:13.200 --> 00:37:17.769
Anyone? Because I had
zero clue about this myself.

00:37:17.769 --> 00:37:24.660
Okay. So it’s FEMA’s BCA Toolkit,
or benefit-cost analysis.

00:37:25.460 --> 00:37:27.320
Good way to
do a thing, right?

00:37:27.320 --> 00:37:30.200
You know, value –
balance the benefit and cost.

00:37:30.200 --> 00:37:35.479
And so it’s – in this case, you could
do the risk reduction versus the cost.

00:37:35.479 --> 00:37:39.059
And the cost in this case would be –
coral reef restoration is about

00:37:39.060 --> 00:37:43.840
half a million dollars to $3 million
per kilometer of shoreline.

00:37:43.840 --> 00:37:45.780
Sounds like a lot
of money, right?

00:37:45.780 --> 00:37:49.580
Does anyone know what a cost
of offshore breakwaters are?

00:37:50.320 --> 00:37:52.760
Well, it’s an order of
magnitude higher than that.

00:37:52.760 --> 00:37:54.960
I’ll just – sorry,
I’ll save you the suspense.

00:37:54.960 --> 00:37:58.940
But, yes, it’s an order of
magnitude higher than that.

00:38:00.960 --> 00:38:05.460
So what you really want is a
benefit-cost analysis greater than 1.

00:38:05.460 --> 00:38:09.660
Really good projects are,
like, 5-to-1 or 10-to-1.

00:38:09.670 --> 00:38:12.380
But you need to be able to
quantify both sides of that.

00:38:12.380 --> 00:38:15.740
Well, we already know
the cost of restoration.

00:38:15.740 --> 00:38:18.760
Well, now we can
do risk reduction.

00:38:18.779 --> 00:38:22.890
However, the U.S. Office of
Management and Budget’s

00:38:22.890 --> 00:38:27.170
Circular A-94 and the U.S. Stafford Act
says this has to be done at a

00:38:27.170 --> 00:38:32.460
spatial resolution and economically
rigorous manner – certain degrees.

00:38:33.320 --> 00:38:37.680
Well, we’re sure doing it
at spatial resolution.

00:38:38.540 --> 00:38:43.880
And, well, FEMA just determined
we meet those needs.

00:38:45.100 --> 00:38:51.440
So this model framework we’ve
developed is rigorous enough financially,

00:38:51.440 --> 00:38:57.170
rigorous – or, spatially fine
enough to really meet those needs.

00:38:57.170 --> 00:39:03.319
And so, what that says is, you know,
all these tools that they use to fund

00:39:03.319 --> 00:39:06.829
gray infrastructure –
seawalls, breakwaters, and stuff –

00:39:06.829 --> 00:39:10.300
we can use it fund
green infrastructure.

00:39:10.300 --> 00:39:12.420
And like I said in
the previous slide,

00:39:12.420 --> 00:39:18.240
green infrastructure is an order
of magnitude less costly.

00:39:18.240 --> 00:39:22.020
And provides those other
things like tourism, fisheries.

00:39:24.340 --> 00:39:28.780
And so Lloyd’s of London –
folks have probably heard of them –

00:39:28.789 --> 00:39:35.119
big insurance people – they actually
put together a document kind of saying,

00:39:35.120 --> 00:39:39.560
okay, well, what are the different things?
And you can do pre-disaster funding.

00:39:40.300 --> 00:39:45.560
You know, things like the Corps of
Engineers, FEMA pre-disaster mitigation

00:39:45.569 --> 00:39:51.499
grants, post-disaster funding – these
flood mitigation assistance programs.

00:39:51.500 --> 00:39:57.680
Something that’s happening right now in
the Caribbean following the hurricanes.

00:39:57.680 --> 00:40:03.840
And they also break out, like, who pays
versus, you know, who benefits from this.

00:40:03.840 --> 00:40:09.460
Well, again, so now, these are all funds
that theoretically can be tapped into.

00:40:10.760 --> 00:40:13.520
And we do two –
how do you restore a reef?

00:40:13.539 --> 00:40:15.559
Well, there’s two things.
One, you can do structural.

00:40:15.559 --> 00:40:19.869
These are basically concrete balls
called reef balls that can be

00:40:19.869 --> 00:40:23.039
dumped out on the seafloor
to increase the water depth.

00:40:23.040 --> 00:40:29.540
And then new corals land – recruit
to them and grow through time.

00:40:30.500 --> 00:40:34.240
And they’ve got all these nice holes
in them, so fish like to hide in them,

00:40:34.250 --> 00:40:38.249
and they’re really good.
But they cost something, right?

00:40:38.249 --> 00:40:44.079
The other thing is NOAA’s
Coral Reef Restoration Center.

00:40:44.079 --> 00:40:48.479
And a lot of governments in the Caribbean
and the Pacific and the Indian Ocean –

00:40:48.479 --> 00:40:52.180
foreign governments actually
have their own coral nurseries.

00:40:52.180 --> 00:40:56.869
So you can not only put the structural
feature out, and we can model that

00:40:56.869 --> 00:41:00.130
structural feature by the
decrease in water depth.

00:41:00.130 --> 00:41:05.069
But we can also measure the
increased roughness of those corals.

00:41:05.069 --> 00:41:09.739
So we can quantify the hazard risk
reduction and the resulting cost in

00:41:09.739 --> 00:41:13.799
dollars and – or, savings in dollars
and lives of both the structural

00:41:13.799 --> 00:41:17.559
restoration and the
biological restoration.

00:41:17.559 --> 00:41:22.170
And then do those benefit-cost
analysis for both of those.

00:41:22.170 --> 00:41:31.960
This is all great in theory, but sadly, the –
Hurricane Irma and Maria tore through

00:41:31.960 --> 00:41:36.469
the Caribbean causing billions
and billions of dollars in damage.

00:41:36.469 --> 00:41:41.020
Well, we had already set the
model up for these areas for, you know,

00:41:41.020 --> 00:41:49.780
the coral reefs, the – reduced the
annual damage and the people flooded.

00:41:49.780 --> 00:41:52.569
And, again, so we could flip this
model around, and so we could

00:41:52.569 --> 00:41:57.040
take the – well, in this case,
it would be the existing reef,

00:41:57.040 --> 00:42:00.660
put the restored reef on top of it,
and have that reduced.

00:42:00.660 --> 00:42:07.140
So to basically guide, where can they
do restoration to reduce coastal hazards?

00:42:08.520 --> 00:42:13.800
And we now have a proposal in to
do this with Puerto Rico and the

00:42:13.800 --> 00:42:23.380
U.S. Virgin Islands to basically guide
restoration to reduce coastal hazards.

00:42:24.660 --> 00:42:28.740
So we can improve the health
of the ecosystem, increase fisheries,

00:42:28.740 --> 00:42:34.579
increase tourism,
and do it to reduce coastal hazards,

00:42:34.580 --> 00:42:37.820
and in an
economically beneficial way.

00:42:38.580 --> 00:42:41.640
So where can this lead us?
Now, this is exciting stuff,

00:42:41.640 --> 00:42:44.019
and you people are all
probably an order of magnitude

00:42:44.019 --> 00:42:47.740
more financially savvy than I am.
But Mike Beck and

00:42:47.740 --> 00:42:51.940
The Nature Conservancy is really
trying to say, what’s the next step in this,

00:42:51.940 --> 00:42:55.380
is remember, we talked about how
there’s these mechanisms to fund it.

00:42:55.380 --> 00:42:58.240
Well, the first one’s insurance.

00:42:58.240 --> 00:43:03.780
And what one can do is fund restoration
of damaged reefs using insurance.

00:43:03.789 --> 00:43:05.950
You could set the
rates to promote protection.

00:43:05.950 --> 00:43:10.260
And this is something that The Nature
Conservancy is working with Swiss Re.

00:43:10.260 --> 00:43:14.380
Now, if you don’t know Swiss Re,
Swiss Re is – they’re the insurers

00:43:14.380 --> 00:43:18.730
of the insurance agencies. So they’re
in the billions to trillions of dollars.

00:43:18.730 --> 00:43:23.960
Like, and so when you
start to get those folks on board,

00:43:23.960 --> 00:43:29.099
all the little State Farms and
stuff like that kind of will follow.

00:43:29.099 --> 00:43:33.069
The other is – another example
is resilience infrastructure bonds.

00:43:33.069 --> 00:43:37.359
And so they can support
pre-reef restoration based on

00:43:37.359 --> 00:43:41.339
this projected hazard risk
reduction benefits.

00:43:41.339 --> 00:43:45.430
They can also pay for defense through
the reduced cost of insurance bonds.

00:43:45.430 --> 00:43:48.760
And this is something
they’re doing with Munich Re.

00:43:48.760 --> 00:43:53.020
Now, I believe Munich Re
is so big that they insure Mexico.

00:43:53.020 --> 00:43:56.260
Caribbean coast.
So, again, large-scale.

00:43:58.220 --> 00:44:02.300
So really what they’re doing – and this,
again, is The Nature Conservancy

00:44:02.300 --> 00:44:07.799
and Munich Re and Swiss Re,
is really a resilience insurance solution

00:44:07.799 --> 00:44:11.490
that overcomes the tradeoffs between
risk reduction and risk transfer.

00:44:11.490 --> 00:44:16.200
So you have this upfront reef
restoration investment that reduces risk.

00:44:16.200 --> 00:44:18.490
This risk-mitigating
impact reduces premiums,

00:44:18.490 --> 00:44:23.580
and that’s an incentive that’s created
for restoration and risk transfer.

00:44:26.440 --> 00:44:31.320
So here shows current coastal funding
for conservation and infrastructure.

00:44:31.320 --> 00:44:34.260
Over the first
15 years of the century.

00:44:34.260 --> 00:44:38.020
So this is dollars spent.
That’s billions.

00:44:38.020 --> 00:44:40.600
And you see what
goes into biodiversity aid,

00:44:40.609 --> 00:44:44.650
like coral reef restoration
and things like that.

00:44:44.650 --> 00:44:46.630
You go over to
the other side of here.

00:44:46.630 --> 00:44:50.360
Insured losses is over a
quarter of a trillion dollars.

00:44:51.280 --> 00:44:55.940
So using these mechanisms with –
well, the re-insurance industries,

00:44:55.940 --> 00:44:57.890
the insurance industries,
infrastructure bonds,

00:44:57.890 --> 00:45:01.319
what we’re looking to do is
see if somehow we could get

00:45:01.319 --> 00:45:04.759
a little of that money coming
out of the insured losses,

00:45:04.760 --> 00:45:10.540
put it into biodiversity aid to
reduce that overall large damage.

00:45:13.360 --> 00:45:15.900
So the implications – well, again,
there’s private incentives,

00:45:15.900 --> 00:45:18.340
such as insurance
and resilience bonds.

00:45:18.340 --> 00:45:21.180
Public incentives are these
pre-disaster green bonds and

00:45:21.190 --> 00:45:24.869
special purpose tax districts,
post-disaster FEMA restoration funds.

00:45:24.869 --> 00:45:29.239
But the big thing is this prioritization
of natural infrastructure and policy.

00:45:29.240 --> 00:45:33.800
FEMA’s starting to buy in on this.
Hopefully next we can get the Corps.

00:45:33.800 --> 00:45:37.280
Because we’re doing it
to save dollars and lives.

00:45:38.910 --> 00:45:42.060
So in summary, coral reefs
are our first line of defense.

00:45:42.069 --> 00:45:44.650
We can accurately and
rigorously account for

00:45:44.650 --> 00:45:48.059
the defenses the reefs provide.
We can generate value-based

00:45:48.059 --> 00:45:51.731
information to guide restoration
and increase – efforts to increase

00:45:51.731 --> 00:45:53.920
the resilience of coastal
communities and ecosystems

00:45:53.920 --> 00:45:58.710
at management-relevant scales.
And that’s really important.

00:45:58.710 --> 00:46:03.559
And so, you know, the push now – not
by us at the USGS, but our colleagues,

00:46:03.560 --> 00:46:08.600
to get the nature included
in these industry risk models.

00:46:08.600 --> 00:46:12.520
Because people are going to make the
right decision when the industry –

00:46:12.529 --> 00:46:16.910
insurance industry says, we’re not
going to insure that, not going to build it.

00:46:16.910 --> 00:46:20.280
And that’s where I think we’ll
start to get to really smart growth.

00:46:21.520 --> 00:46:24.599
So we’re trying to link
coral reef ecosystem health

00:46:24.599 --> 00:46:28.789
to coastal hazard risk reduction.
And that’s to reduce risk,

00:46:28.789 --> 00:46:33.260
increase coastal resilience, and better
direct reef restoration efforts.

00:46:33.260 --> 00:46:35.400
That’s all.
Thank you very much, folks.

00:46:35.400 --> 00:46:39.940
[Applause]

00:46:39.940 --> 00:46:43.020
- Thank you, Curt.
So now it’s time for questions.

00:46:43.020 --> 00:46:47.799
And, as usual, we’ll ask you to go to the
two microphones that are already set up.

00:46:47.800 --> 00:46:51.340
Or, if you’d like,
I can bring you this handheld mic.

00:46:53.080 --> 00:47:00.060
- So is there any breeding of higher-
temperature-resilient coral being done?

00:47:01.040 --> 00:47:04.920
- Yes, there is.
I cannot remember – it wasn’t

00:47:04.920 --> 00:47:07.280
the government that funded it,
and I don’t want to say it’s, like,

00:47:07.280 --> 00:47:11.760
Elon Musk or – it was –
it was a private group that funded it.

00:47:11.769 --> 00:47:15.229
And it’s what they
call the Coral XPRIZE.

00:47:15.229 --> 00:47:17.569
And what they’re doing is,
they’re doing – they’re basically

00:47:17.569 --> 00:47:21.059
going out and trying to find
corals that live in really extreme

00:47:21.059 --> 00:47:24.750
high-temperature environments –
places on the island of Ofu

00:47:24.750 --> 00:47:30.359
of American Samoa go up to,
like, 35 degrees C every day.

00:47:30.359 --> 00:47:34.609
Places in the Arabian Gulf.
And saying, gosh, these ones

00:47:34.609 --> 00:47:40.150
are predisposed to be able to
handle those high temperatures,

00:47:40.150 --> 00:47:42.660
and trying to breed those.
Now, obviously, when you

00:47:42.660 --> 00:47:45.999
start breeding select groups,
you decrease biologic diversity.

00:47:45.999 --> 00:47:49.369
You may – potentially susceptibility
to disease and things like that.

00:47:49.369 --> 00:47:52.039
But they’re doing that.
They’re doing it – and I can’t remember

00:47:52.039 --> 00:47:55.630
where in Australia, but they’re
doing it at the University of Hawaii’s

00:47:55.630 --> 00:48:00.400
Hawaiian Institute of Marine Biology
on Coconut Island off Oahu.

00:48:00.400 --> 00:48:05.720
So that’s Ruth Gates and others are
basically trying to breed super corals.

00:48:08.380 --> 00:48:09.460
Yes?

00:48:11.320 --> 00:48:17.040
- You were talking about
the restoration of reefs.

00:48:17.040 --> 00:48:20.840
- Mm-hmm.
- Is there a point of no return,

00:48:20.840 --> 00:48:26.299
where a reef – collection of
reefs can no longer be restored?

00:48:26.300 --> 00:48:32.259
And, as a follow-up to that, are we at
that stage for the Great Barrier Reef?

00:48:33.100 --> 00:48:36.700
- Okay, so the first question,
can reefs hit a point of no return? Yes.

00:48:36.710 --> 00:48:42.069
We’ve seen certain places in Hawaii
where there was really poor agricultural

00:48:42.069 --> 00:48:45.670
practices – primarily sugar and
pineapple – where so much sediment

00:48:45.670 --> 00:48:51.500
ran off the islands for a hundred
years that the reefs died,

00:48:51.500 --> 00:48:56.920
and they created so much sand
that there was no more hard ground.

00:48:56.920 --> 00:49:02.580
Corals need to settle on hard ground
to grow. They can’t land on sand.

00:49:02.589 --> 00:49:05.219
And so what we call it is a phase shift.
Like, it’s shifted to sand,

00:49:05.219 --> 00:49:09.779
and it’s not going to be reef again.
So that can happen.

00:49:09.780 --> 00:49:12.920
Has the Great Barrier Reef
hit that point?

00:49:14.720 --> 00:49:20.120
[chuckles] There’s a lot of biologists
and ecologists that would argue that.

00:49:20.700 --> 00:49:26.520
I’m a geologist, and I’ve looked –
I’ve had colleagues and others that

00:49:26.520 --> 00:49:32.620
look at history and say corals have been
around for a quarter of a billion years.

00:49:33.280 --> 00:49:35.320
They’ve gone through
some pretty bad things.

00:49:35.320 --> 00:49:38.420
They’re going through
bad things at a lot higher rate.

00:49:38.420 --> 00:49:40.779
But there’s going to
be some refugia in some places

00:49:40.779 --> 00:49:43.190
where they’re going to
make it through.

00:49:43.190 --> 00:49:48.240
Are the reefs going to look like they
look like today? Probably not.

00:49:49.100 --> 00:49:53.760
And we’re going to lose a lot of those
ecosystem services along the way.

00:49:53.769 --> 00:49:59.130
But do I think corals, as a – oh, gosh,
I don’t know if it’s a – it’s not a species.

00:49:59.130 --> 00:50:02.319
It’s a genera or somewhere in
that phylum kingdom thing.

00:50:02.320 --> 00:50:04.960
I’m sorry. I’m a geologist.
[laughter]

00:50:04.960 --> 00:50:08.920
You know, we’re not – they’re not
going to go extinct. Some species may.

00:50:08.920 --> 00:50:15.360
I will say this, is one of the big problems
with restoration historically is they’ve –

00:50:15.360 --> 00:50:19.420
in those coral reef nurseries, they’ve
found really fast-growing corals.

00:50:19.430 --> 00:50:22.099
Because, man, it makes you feel good
when something grows fast, right?

00:50:22.100 --> 00:50:23.800
Like, in your greenhouse?

00:50:23.800 --> 00:50:28.170
However, the corals that grow
really fast, they pour everything

00:50:28.170 --> 00:50:33.820
into growing fast, and they’re really,
really not robust and resilient.

00:50:34.100 --> 00:50:36.580
And, I mean, not really, but –
like, these are the kind of things,

00:50:36.581 --> 00:50:39.969
you sneeze on them, and they die.
And what they’ve really done is looking

00:50:39.969 --> 00:50:43.589
to shift the corals – and this has only
happened in the past couple years.

00:50:43.589 --> 00:50:46.829
Because, we’re, like – I hate to say,
some of the geologists came and

00:50:46.829 --> 00:50:49.789
would be, like, that species is –
you know, you look through

00:50:49.789 --> 00:50:53.170
the geologic record and, like,
anytime there’s a slight change

00:50:53.170 --> 00:50:56.349
in the climate, man, those things go.
They go. They go.

00:50:56.349 --> 00:50:59.019
And sadly, some of the main
coral species that the U.S.

00:50:59.019 --> 00:51:03.059
has put on the threatened and
endangered species list are those corals.

00:51:03.059 --> 00:51:07.440
Acropora. Acropora is this general –
they look beautiful. They’re out there.

00:51:07.440 --> 00:51:10.759
I mean, the geologic record,
something happens, they’re gone.

00:51:10.759 --> 00:51:13.450
They’re gone. They’re gone.
And they want to breed those because,

00:51:13.450 --> 00:51:15.549
you know, they make you feel good,
and they’re a threatened

00:51:15.549 --> 00:51:18.509
and endangered species.
However, they’re not really robust.

00:51:18.509 --> 00:51:21.950
The slower-growing
ones are the hardy ones.

00:51:21.950 --> 00:51:24.039
And so, at least in
a lot of these nurseries,

00:51:24.040 --> 00:51:27.700
they are moving towards
those more robust species.

00:51:28.680 --> 00:51:32.779
And, I mean, obviously, you want –
you want a diverse group to

00:51:32.779 --> 00:51:37.249
keep biodiversity up, but they’re
realizing that, gosh, you know.

00:51:37.249 --> 00:51:39.829
The other problem is, in a lot of places –
like, hey, when there’s a vessel

00:51:39.829 --> 00:51:45.640
grounding or a hurricane –
like, Irma came by and destroyed

00:51:45.640 --> 00:51:51.109
acres and acres of reefs in the Keys.
Okay, you can put corals back there.

00:51:51.109 --> 00:51:57.109
But in a lot of these areas where it’s
wastewater discharge that’s killed

00:51:57.109 --> 00:52:00.472
the reefs, or land-based pollution
that’s killed the reefs, are you going to

00:52:00.472 --> 00:52:03.339
take a new canary and put it back in
the same coal mine that killed the

00:52:03.339 --> 00:52:07.769
last canary? And sadly, that’s
what’s happened in a lot of cases.

00:52:07.769 --> 00:52:11.809
And so, they’re trying to be a little
smarter about, okay, well, you know,

00:52:11.809 --> 00:52:15.309
a vessel grounding site’s a
great place to replant corals.

00:52:15.309 --> 00:52:19.229
But in a lot of these places, they’re being
stressed by other factors, and us putting

00:52:19.229 --> 00:52:23.359
coral replants, or transplants, in there
is just going to have them die.

00:52:23.359 --> 00:52:26.529
So we need to better
manage those things.

00:52:26.529 --> 00:52:28.390
The nice thing –
oh, I shouldn’t say the nice thing,

00:52:28.390 --> 00:52:32.969
but the thing about land-based sources
of pollution, these can be solved

00:52:32.969 --> 00:52:38.959
locally at a jurisdiction level,
at a state level, at a territory level.

00:52:38.959 --> 00:52:42.259
And we can hopefully reduce
those stressors to hopefully

00:52:42.259 --> 00:52:46.709
make those corals a little more resilient.
Because the global stressors are the ones

00:52:46.709 --> 00:52:53.869
that we can’t stop in Hawaii, in USVI,
in Puerto Rico – the increased

00:52:53.869 --> 00:52:58.049
temperatures that can cause bleaching,
and the increased ocean acidification.

00:52:58.049 --> 00:53:00.269
But at least, if we can
reduce land-based pollution,

00:53:00.269 --> 00:53:02.920
we can remove
that one stressor.

00:53:06.040 --> 00:53:10.000
- Oh, sorry. He’s leaving. Yes, ma’am?
- Yeah.

00:53:16.619 --> 00:53:20.009
I have a couple of questions.
One is, like, you did all these

00:53:20.009 --> 00:53:25.420
calculations. Did you test
against the real data?

00:53:25.420 --> 00:53:29.319
- Oh, yes. Because I always say,
I can make a model that shows

00:53:29.320 --> 00:53:33.920
purple elephants fly. But that’s
one of the things we’re good at.

00:53:33.920 --> 00:53:36.420
And we’re – I mean, I shouldn’t –
I wouldn’t say we’re forced to,

00:53:36.430 --> 00:53:40.799
but that’s one thing we do is
we have to prove our models work.

00:53:40.799 --> 00:53:44.500
And so we’ve run these –
the flooding models in certain locations

00:53:44.500 --> 00:53:47.180
to see that they’re doing accurate – 
because if you can’t model the

00:53:47.180 --> 00:53:51.400
present and do it right with data,
to do any projections, I mean,

00:53:51.400 --> 00:53:53.840
then you’re out of your mind.
Sadly, it happens.

00:53:53.849 --> 00:53:57.779
I will say here at the USGS, though,
we have to go – undergo peer review.

00:53:57.779 --> 00:54:01.679
So we have our colleagues look at it,
and they’ll call horse doody …

00:54:01.680 --> 00:54:04.680
- Yeah, the reason I’m asking
is that you didn’t show it.

00:54:04.680 --> 00:54:11.700
You showed the predictions, but not
how did it test against the real data.

00:54:11.709 --> 00:54:14.690
And I was looking for it.
- Okay. Well, I’ve got – trust me,

00:54:14.690 --> 00:54:16.630
I’ve got a bazillion [inaudible] …
- No, I’m not saying –

00:54:16.630 --> 00:54:17.919
I’m not questioning.
I’m just saying …

00:54:17.919 --> 00:54:19.969
- I just didn’t think that was
going to be the most exciting thing

00:54:19.969 --> 00:54:21.150
to show you folks.
- Oh, okay.

00:54:21.150 --> 00:54:24.029
- There’s a lot more even –
I mean, that was enough sausage,

00:54:24.029 --> 00:54:25.960
I thought, for most people.
[laughter]

00:54:25.960 --> 00:54:28.460
And I was kind of trying to
limit what I was showing you.

00:54:28.460 --> 00:54:30.489
But, yes, it has been calibrated
and validated.

00:54:30.489 --> 00:54:33.099
And it’s actually been peer-reviewed
and published, this methodology.

00:54:33.100 --> 00:54:37.140
- And the – another question
I have is the restoration.

00:54:37.140 --> 00:54:40.839
- Mm-hmm.
- Do you – are you assuming that

00:54:40.839 --> 00:54:45.729
all the coral reefs have been damaged?
Or it’s just specific areas

00:54:45.729 --> 00:54:51.359
which may require restorations?
And then, also, as you mentioned,

00:54:51.359 --> 00:54:56.920
there were these local policies and
practices versus the global practices,

00:54:56.920 --> 00:55:02.400
which are impacting the coral reefs.
- I’m not going to remember the –

00:55:02.400 --> 00:55:05.209
that’s a real long discussion.
Can I go to the one at a time?

00:55:05.209 --> 00:55:07.500
You were asking about the coral reef?
I apologize.

00:55:07.500 --> 00:55:10.859
I have a short attention span.
I’ll get lost there.

00:55:10.859 --> 00:55:15.650
So the first was asking about restoration.
Well, what we know is, already,

00:55:15.650 --> 00:55:21.349
in some places, that there are – I mean,
this is zero to 10% live coral coverage.

00:55:21.349 --> 00:55:24.549
So, as of right now,
maybe we could restore these

00:55:24.549 --> 00:55:28.309
and bring them up to
40% live coral cover.

00:55:28.309 --> 00:55:33.600
However, when you’re asking in other
places, like in Florida, Puerto Rico,

00:55:33.600 --> 00:55:38.480
USVI, NOAA’s Coral Reef
Conservation Program went out

00:55:38.489 --> 00:55:46.369
and did 300, 400-some site visits and
noted the degree of coral damage.

00:55:46.369 --> 00:55:49.529
So that we know – and they’ve
recorded that, so we know that,

00:55:49.529 --> 00:55:55.460
okay, there was 30% live coral,
and now it’s down to 5%.

00:55:55.460 --> 00:55:59.449
So we have data on that to say –
so then, what we can do is say, okay,

00:55:59.449 --> 00:56:05.060
we’re going to take – say this is a map –
this is a map after the damage.

00:56:05.060 --> 00:56:08.880
Okay, this is all now
5% live coral coverage.

00:56:08.880 --> 00:56:12.869
Let’s make it 50% live coral
cover and run the model on it.

00:56:12.869 --> 00:56:14.540
So that’s how
we’re doing that part.

00:56:14.540 --> 00:56:15.940
Sorry, please, now you
can ask your question.

00:56:15.940 --> 00:56:20.339
- No, so my next question was that,
how you’re going to reduce

00:56:20.339 --> 00:56:26.039
the local practices to –
so when the restoration is done,

00:56:26.039 --> 00:56:29.859
that the restoration stays
there and not degrade again?

00:56:29.859 --> 00:56:33.569
- Well, again, some of the places
it’s been – right now, the only place

00:56:33.569 --> 00:56:37.759
we’re doing restoration – we’re trying
to model to guide restoration is in those

00:56:37.760 --> 00:56:44.460
areas impacted by hurricane damage.
So those were, in some – most cases,

00:56:44.460 --> 00:56:48.799
relatively healthy reefs not
impacting by land-based pollution.

00:56:48.799 --> 00:56:53.059
Some of those are, though.
And that’s a very important question is,

00:56:53.059 --> 00:56:58.019
okay, well, this is a degraded –
this was a storm-impacted reef,

00:56:58.019 --> 00:57:03.089
but it was already degraded.
So – well, first off, the USGS,

00:57:03.089 --> 00:57:06.319
let me stress, does no policy.
We provide science to make other

00:57:06.319 --> 00:57:10.490
people make decisions –
or, make better-informed decisions.

00:57:10.490 --> 00:57:15.019
So them knowing that, hey,
that water quality is already violating

00:57:15.019 --> 00:57:18.609
the Clean Water Act or something,
that’s something that EPA or

00:57:18.609 --> 00:57:21.309
someone else needs to step in and say.
So we can’t guarantee it.

00:57:21.309 --> 00:57:24.289
We don’t do the restoration.
We don’t make the decisions

00:57:24.289 --> 00:57:27.599
to do the restoration.
We provide the science so that they

00:57:27.599 --> 00:57:30.839
can make a better-informed decision.
But they’re going to be –

00:57:30.839 --> 00:57:34.849
have that knowledge of, okay, this area
is not impacted by land-based pollution.

00:57:34.849 --> 00:57:38.440
Got trashed by a hurricane.
If we restore it, here’s our benefits.

00:57:38.440 --> 00:57:41.700
We can say, hey, we can restore this one,
and this would be your benefits.

00:57:41.700 --> 00:57:45.089
But [chuckles] you might have
less successful restoration,

00:57:45.089 --> 00:57:48.509
or at least the biological
or ecological restoration.

00:57:48.509 --> 00:57:53.660
We still put those big reef balls out
and help reduce the wave energy, but –

00:57:53.660 --> 00:57:57.719
so there’s a lot of information, and all
of that information comes from us,

00:57:57.719 --> 00:58:03.730
and there’s a lot of local management
decisions that need to be made.

00:58:03.730 --> 00:58:08.360
- Thank you.
- Yeah. No worries. My pleasure.

00:58:10.600 --> 00:58:17.880
[Silence]

00:58:18.700 --> 00:58:21.500
- Okay. Well, maybe that’s it.
- Thank you very much

00:58:21.500 --> 00:58:23.320
for coming folks.
We really appreciate it.

00:58:23.320 --> 00:58:28.780
[Applause]

00:58:31.200 --> 00:58:37.420
[background conversations]

00:58:37.420 --> 00:58:43.440
[Silence]