Our next speaker is Dr Meredith Steele, who's assistant
professor of CSES, who has a masters in soil
science from the University of Maryland in 2007 and a
PhD in urban biogeochemistry, from texas A and M
in 2011. Her research is to understand
developed landscapes and the ecosystem services they provide to society
focusing on the water and soil components of the socio
ecological system. She is particularly interested in why and
how development changes, land and water at broad scales
and the resulting environmental consequences. Thank you and thank
you everybody for showing up today into the organizers for
inviting me to speak here. And the last speaker
was really a great uh set up for my especially
the last question about, you know, look at
this relationship between landscapes and people. Um and that's
what I'm going to talk about today. A little
broad intro, Most of what I'm going to talk
about and share with you is part of a larger
project on the ecological homogenization of urban America. It's
funded by the macro systems Biology program. Uh What
I'm going to talk about is mostly found in two
papers that just came out this winter. And if
you're interested in this broader question of ecological homogenization,
we have a couple papers out now from the larger
group and many more to come. So stay tuned
. Uh This is a large interdisciplinary group working on
this question and I'd like to recognize a couple of
people out of here. The first being Jim Heffernan
from Duke University who is an amazing thinker and the
other half of my brain on this hydrographic question that
I'm going to share with you. And also Peter
Graffman, who fearlessly leads a group of 15 p
. i. s. from like four different disciplines
and does an amazing job. So I mentioned that
this is coming out of macro systems and what we
have here really is an emerging discipline. So we
think of macro systems ecology and what I mean,
my macro systems is we would like to understand ecological
patterns and processes at continental scales. So college is
kind of looked around and said, hey, you
know, we know an awful lot about local scale
processes because we study a stream reach, we study
a couple of ponds, um and we actually know
a fair amount about what might be going on at
the global scale. It's this middle scale that we
seem to lack some information on. How does it
inform local processes? How do these processes emerge from
local? Uh and how does it inform global processes
? So this is really where I'm finding myself at
the crossroads of, I work specifically on developed landscapes
and urban nakata, which I'll share with you and
on water resources, specifically hydro graffiti. Um The
aware of water. So I'm going to use the
term hydro scape Um many times in the next 15
minutes and I'm going to define it for you.
I didn't make it up unfortunately, but I'm trying
to popularize it. Um it's the collection of water
features on a landscape, all the streams and the
rivers and channels and the lakes and ponds, the
collective surface water features. Um And just this afternoon
I happened to find out that there is a movie
coming out, not quite about what I did.
Um but has really so the new york times in
this article on a documentary coming out called Watermark.
I don't know if any of you have heard of
it yet. I can't recommend it because I haven't
seen it, but I'm going to because they're talking
about this relationship between people and water and what how
water has shaped people and how people have shaped water
. Um Most of you if you think say okay
, how do we shaped water? You'll think dams
and they show some lovely pictures of dams and terraced
landscapes with these water. I haven't seen it yet
, but I have a feeling of the right email
to the producers and say we have shaped so much
more water than what these, what you've shown.
But I'll let you know. So we have this
hydro scape of all these little features and I'd like
to show you just what we've done to some places
in the country. This is Boynton beach florida,
Minneapolis Minnesota and phoenix Arizona. We covered quite a
precipitation gradient here and I find the Minnesota picture just
a little ironic because the land of 1000 lakes needed
just a couple more. Um and this is a
global phenomenon that we see these kinds of lakes built
lake structures in Buenos Aires in Dubai in Australia,
a really wide area that these beautiful um structures have
come about. And if you think about it,
this is probably not the largest impact we are having
on the hydro escape, it's not what we are
building, it's what we're draining. So I'd like
to illustrate this for you with my favorite time series
from a magical place, southwest Houston in 1943 this
was an enormously wet landscape. All these little features
that you can see on here, some of them
are shining in the sun holding this water water is
transported across the system and it's in north. So
all these little features We fast forward 50 years and
this landscape has been developed for primarily residential housing and
all of those water features are gone all of them
. And but yet we have in the middle here
, we've added a few more that look nothing like
what was there and probably don't function the same way
. Houston has big problems with flooding. Houston has
big problems with water quality and you have to wonder
how much of that is due is because we have
completely rearranged the service water physical structure in the landscape
. So, so I noticed that some of those
pictures came from very dry places and some from very
wet. And what were the question was, do
these become more similar when we develop them? One
is the shots is from Miami one is Phoenix and
if I swap them, you probably wouldn't know which
one was, which dry places are becoming wetter,
what places are becoming much drier and a process called
convergence. And so this has been the big question
for the last couple of years for me, does
urbanization cause hydro scapes to converge as the characteristics become
more similar. So to test this uh implemented of
uh study of 100 cities across the United States.
So across we wanted to hit this with a big
hammer cover a wide range of precipitation and climate and
topography and size of cities. So I wish I
had a pointer. But this little mark here is
us, this is the Blacksburg Christiansburg roanoke. And
so it's an interesting question. Do little cities are
, are small place? What did I? Oh
, oh no, not roanoke, you're right,
Radford, there was an hour there, So little
cities are they also subject to this converging process.
So I took a slightly unconventional approach and took the
2006 National Land cover data and census block groups.
Census block groups are spatial delineations of cities that are
kind of social constructs, and they are nicely already
oriented to the way the city is laid out.
And using these two by asking what is the majority
land cover in the census block? Were able to
get a slightly coarser view of the landscape. Now
this is probably a few times you'll see someone in
a remote sensing G. I. S. Say
we needed to get coarser. Um And that's sometimes
this is what we had to do because our other
option was for a million water bodies. Try to
uh learn something about what the buffer of a water
body was. That was kind of the other options
uh for the data, we use the National Hydrographic
Data. And if you're familiar with this data set
at all, you'll realize there is some spatial variability
in the quality of the data. And this is
where I put a plea out to this group that
um at these large scales we could we could use
some better data and because we have some really question
interesting questions to ask. Um but we've done the
best we can with what we have for the time
being. So evidence of convergence, evidence that these
landscapes are coming together and becoming more similar. A
decrease in variance on this graph. See these are
a measure of surface water area, water body density
and channel density. The X. Axis. All
the way on your left is undeveloped. The variance
of the undeveloped landscapes in these uh M. S
. A. S. And the variance as you
can see all the boxes as the intensity of urbanization
increases, we have a decreasing variance across cities and
this is true, particularly for water percent water area
and also for channel density. So we also want
to look at the direction of change across this compared
to the undeveloped landscapes. And to do this,
we looked at the X axis is the undeveloped landscapes
in the region and the Y axis is the water
body coverage. And if you'll notice a pattern in
these, that the undeveloped when it's drier, things
tend to increase in the city. That has added
, well, it has more water than those undeveloped
regions at the other end of that access in each
of those graphs that when it's very, very wet
, we've had a large decrease in water. Um
And you'll note the log scale on this, uh
that far right point is Miami. And compared to
its surrounding on developed land, it went from having
80 water coverage to about six or seven in between
, which is a very significant drop. We see
a similar pattern for water body density and we also
see a similar pattern for channel density. So for
a lot of landscapes were losing features and for other
landscapes were adding them. So what we've used here
is kind of a space for time substitution. And
we'd really like to get this question of time.
Um How fast are these changing and what exactly are
some of the causal mechanisms? So we can hypothesize
a little bit because we've seen these in these pictures
that these are physical alterations. We have built these
water features and we have taken some away. And
also the second important one is choice of location um
that we are selecting out regions to develop that meet
certain needs, which makes sense. And is the
of efficient thing to do. But this is what's
giving some of these urban care ecosystem properties a certain
characteristics because we are selecting them. And this is
an important question for us coming up. So we've
been talking about cities, what about agriculture? Cities
are fabulous and I love them and but they only
cover about 3% of the earth's surface. Um give
or take the estimate. Um Agriculture on the other
hand, it covers an enormous area of the U
. S. And globally is covering agricultural development and
in agriculture, we have similar processes going on.
We have in some places we add water. We
have the concept of ubiquitous farm pond and in some
places we drain water. We have no real measure
of how many farm ponds have we added. We
don't know. And draining water futures right now is
a big issue. This is a just the headline
of a PNS paper that came out last year about
the transition and agricultural land cover in the upper midwest
. And the authors here did an excellent job of
of trying to ask to calculate how much agricultural land
is being put into production in response to ethanol.
So we're driving this and they allude to this threat
to wetlands. So we know that in this landscape
, that when farmers tend to, they need the
arable land so they get rid of the wetlands and
this is not really what we want to be happening
. And just the other last week, they put
in a program to try to uh pay farmers not
to drain these. So we don't really know though
about what, what is the agricultural hydro escape,
How did it get there and what, what causal
mechanisms uh caused it to give it the characteristics that
it does. So we took um that same study
that I talked about and use the other side of
that information, the undeveloped and agricultural land cover from
these. And to try to get a preliminary look
at what agricultural hydro scapes look like. Um because
of the structure of the spatial structure here, we
weren't able to do it as a categorical, but
we ended up with a gradient of 0-79 agricultural land
cover in these different units from 100 places across the
United States. And what we observed is that agricultural
high scapes are complex and driving these hydro scapes are
amount of precipitation that area receives the slope of the
land and intensity of agriculture. So I'm gonna give
you a case study from this one example and like
I said, this is preliminary data and we're hoping
that it's uh it's exciting enough to move forward to
um So what you're looking at is just some simple
regression relationships between the precipitation divided by the slope of
the land. So as precipitation increases in land gets
flatter. What this is saying is if there's no
agricultural development that those blue uh marks are less than
10 agricultural land cover in this area, that we
have an increasing amount of yeah, area covered by
wetlands. And that's pretty logical. And but the
red regression or lack thereof is saying is that When
we have greater than 60 agricultural land cover, this
is the likely area of wetlands that we will have
. Um And like I said, this is a
preliminary look at this. But what it is really
relating is that different places along the landscape as we
think about our our spatial heterogeneity with precipitation gradients and
topography, that the difference between what's going to be
agricultural land and the natural condition is going to be
highly variable and so tired. Okay, we can
look at this at a fairly large level because we
have precipitation data and we have topography data or slopes
for the entire US. And using that, the
data from the blue regression there. What you're looking
at is uh, a map of what this saying
, the, what percentage of wetlands would be across
the United States if there were no land cover development
. And like I said, this is preliminary and
we'd like to take a a much more detailed approach
to this because the other thing we can do with
it is say, okay, if we use a
simple multiple regression that with agricultural development, this is
what we will see in this area. Um,
this is done with a one square kilometer resolution.
The likely if we do nothing, the likely hydro
scape is going to look like with this amount of
agricultural intensity. So we're pretty excited about this because
if we know what happened, we might be able
to a little with a little bit more dexterity forecast
these changes. So that's really where we're left with
that. Moving forward, I've shown you some hydro
escaped patterns and characteristics of urban agriculture and what we'd
like to do is look at these drivers and mechanisms
will change. You know, what are the time
scales? And one of the things that we looked
at in the data was where there were errors.
It might be a matter of time that especially in
cities and in agriculture, what how fast these uh
like small ponds and features appear and disappear on the
landscape you much faster than what we anticipated. And
also hind cast like I just show you what should
be here and how is that different from what may
be here and what if we have more development?
What is the likely characteristics of that hydro escape?
And also the another big question is of course,
what are the ecosystem consequences? Hydro escapes play an
important scaling role in watersheds and play an important role
in water quality, quantity, bio geochemical cycles and
habitat. Currently I can't tell you if some of
these really altered landscapes if they function differently. But
that is a question that I would like to be
able to answer in the future. So those are
hydra scapes and I hope that I have been impressed
upon you the uh you'll go forth and use this
term. Um and see the movie. So thank
you very much. We have lots of we do
. I chip. Mhm. Yeah. When you
start off, you showed us like a natural Houston
, probably natural landscape but some of the others it
seems to me they were changes to things that were
already changed. Like the farm ponds were results of
. Yes. So you're talking about changes of things
that were changed. So how does that? We
looked at both of those? Um So in the
estimate of what used for undeveloped it's we call it
nominally undeveloped because that's what is categorized under land cover
. But really it's a it's a look at the
patterns related to what is there isn't converging relative to
how it exists because there are very few places where
that alter that surrounding landscaped isn't altered. So it
is. And we looked at both of those things
including like we took out some of the dams and
so does it still is converging still happen relative if
we take the dams out of the undeveloped with.
So it's we had a couple of different measures of
how it's and the same pattern emerged in every one
of them. But you're right. It's I wish
I could if I had 1000 years of imagery um
It would be very handy right now when you use
the N. H. D. It's available in
different scales which may not be available everywhere. So
how did you compensate for them? Common denominator believe
that. 30. Yeah evenly. Yeah. So
you have to look at what might have, things
might change if you went to the high resolution.
Uh Not currently. Yeah. Um I apologize for
coming to lecture a little later. It addresses the
beginning. But how did you know about doing your
analysis and how did you huge? Mhm. Uh
No just the one year. And because it The
thing with the NH. D. Is that it
was created by each state individually across the years.
But the final date was about 2006. So we
said okay this is the this is the best we
can do. And so we used one date and
we didn't see a whole lot of uh for the
amount of effort it would take to go back and
use the different NLCS to look at the change we
didn't see really addressing the question with some efficiency.
Um But yeah what what I ended up doing was
to use the N. L. City into aggregate
to a coarser view of the city by using census
blocks to to ask what's the majority of the certain
urban land cover type within a census block. Um
And then look at it for all of those sorts
of those census blocks. What's the density of water
? Does that answer your question? Okay well thank
you. Yeah.