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Our next speaker is Dr Meredith Steele, who's assistant

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professor of CSES, who has a masters in soil

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science from the University of Maryland in 2007 and a

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PhD in urban biogeochemistry, from texas A and M

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in 2011. Her research is to understand

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developed landscapes and the ecosystem services they provide to society

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focusing on the water and soil components of the socio

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ecological system. She is particularly interested in why and

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how development changes, land and water at broad scales

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and the resulting environmental consequences. Thank you and thank

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you everybody for showing up today into the organizers for

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inviting me to speak here. And the last speaker

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was really a great uh set up for my especially

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the last question about, you know, look at

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this relationship between landscapes and people. Um and that's

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what I'm going to talk about today. A little

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broad intro, Most of what I'm going to talk

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about and share with you is part of a larger

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project on the ecological homogenization of urban America. It's

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funded by the macro systems Biology program. Uh What

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I'm going to talk about is mostly found in two

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papers that just came out this winter. And if

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you're interested in this broader question of ecological homogenization,

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we have a couple papers out now from the larger

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group and many more to come. So stay tuned

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. Uh This is a large interdisciplinary group working on

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this question and I'd like to recognize a couple of

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people out of here. The first being Jim Heffernan

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from Duke University who is an amazing thinker and the

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other half of my brain on this hydrographic question that

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I'm going to share with you. And also Peter

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Graffman, who fearlessly leads a group of 15 p

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. i. s. from like four different disciplines

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and does an amazing job. So I mentioned that

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this is coming out of macro systems and what we

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have here really is an emerging discipline. So we

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think of macro systems ecology and what I mean,

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my macro systems is we would like to understand ecological

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patterns and processes at continental scales. So college is

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kind of looked around and said, hey, you

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know, we know an awful lot about local scale

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processes because we study a stream reach, we study

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a couple of ponds, um and we actually know

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a fair amount about what might be going on at

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the global scale. It's this middle scale that we

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seem to lack some information on. How does it

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inform local processes? How do these processes emerge from

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local? Uh and how does it inform global processes

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? So this is really where I'm finding myself at

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the crossroads of, I work specifically on developed landscapes

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and urban nakata, which I'll share with you and

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on water resources, specifically hydro graffiti. Um The

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aware of water. So I'm going to use the

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term hydro scape Um many times in the next 15

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minutes and I'm going to define it for you.

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I didn't make it up unfortunately, but I'm trying

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to popularize it. Um it's the collection of water

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features on a landscape, all the streams and the

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rivers and channels and the lakes and ponds, the

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collective surface water features. Um And just this afternoon

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I happened to find out that there is a movie

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coming out, not quite about what I did.

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Um but has really so the new york times in

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this article on a documentary coming out called Watermark.

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I don't know if any of you have heard of

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it yet. I can't recommend it because I haven't

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seen it, but I'm going to because they're talking

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about this relationship between people and water and what how

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water has shaped people and how people have shaped water

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. Um Most of you if you think say okay

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, how do we shaped water? You'll think dams

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and they show some lovely pictures of dams and terraced

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landscapes with these water. I haven't seen it yet

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, but I have a feeling of the right email

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to the producers and say we have shaped so much

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more water than what these, what you've shown.

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But I'll let you know. So we have this

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hydro scape of all these little features and I'd like

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to show you just what we've done to some places

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in the country. This is Boynton beach florida,

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Minneapolis Minnesota and phoenix Arizona. We covered quite a

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precipitation gradient here and I find the Minnesota picture just

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a little ironic because the land of 1000 lakes needed

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just a couple more. Um and this is a

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global phenomenon that we see these kinds of lakes built

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lake structures in Buenos Aires in Dubai in Australia,

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a really wide area that these beautiful um structures have

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come about. And if you think about it,

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this is probably not the largest impact we are having

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on the hydro escape, it's not what we are

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building, it's what we're draining. So I'd like

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to illustrate this for you with my favorite time series

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from a magical place, southwest Houston in 1943 this

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was an enormously wet landscape. All these little features

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that you can see on here, some of them

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are shining in the sun holding this water water is

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transported across the system and it's in north. So

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all these little features We fast forward 50 years and

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this landscape has been developed for primarily residential housing and

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all of those water features are gone all of them

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. And but yet we have in the middle here

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, we've added a few more that look nothing like

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what was there and probably don't function the same way

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. Houston has big problems with flooding. Houston has

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big problems with water quality and you have to wonder

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how much of that is due is because we have

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completely rearranged the service water physical structure in the landscape

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. So, so I noticed that some of those

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pictures came from very dry places and some from very

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wet. And what were the question was, do

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these become more similar when we develop them? One

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is the shots is from Miami one is Phoenix and

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if I swap them, you probably wouldn't know which

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one was, which dry places are becoming wetter,

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what places are becoming much drier and a process called

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convergence. And so this has been the big question

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for the last couple of years for me, does

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urbanization cause hydro scapes to converge as the characteristics become

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more similar. So to test this uh implemented of

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uh study of 100 cities across the United States.

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So across we wanted to hit this with a big

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hammer cover a wide range of precipitation and climate and

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topography and size of cities. So I wish I

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had a pointer. But this little mark here is

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us, this is the Blacksburg Christiansburg roanoke. And

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so it's an interesting question. Do little cities are

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, are small place? What did I? Oh

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, oh no, not roanoke, you're right,

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Radford, there was an hour there, So little

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cities are they also subject to this converging process.

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So I took a slightly unconventional approach and took the

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2006 National Land cover data and census block groups.

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Census block groups are spatial delineations of cities that are

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kind of social constructs, and they are nicely already

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oriented to the way the city is laid out.

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And using these two by asking what is the majority

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land cover in the census block? Were able to

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get a slightly coarser view of the landscape. Now

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this is probably a few times you'll see someone in

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a remote sensing G. I. S. Say

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we needed to get coarser. Um And that's sometimes

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this is what we had to do because our other

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option was for a million water bodies. Try to

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uh learn something about what the buffer of a water

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body was. That was kind of the other options

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uh for the data, we use the National Hydrographic

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Data. And if you're familiar with this data set

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at all, you'll realize there is some spatial variability

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in the quality of the data. And this is

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where I put a plea out to this group that

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um at these large scales we could we could use

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some better data and because we have some really question

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interesting questions to ask. Um but we've done the

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best we can with what we have for the time

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being. So evidence of convergence, evidence that these

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landscapes are coming together and becoming more similar. A

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decrease in variance on this graph. See these are

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a measure of surface water area, water body density

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and channel density. The X. Axis. All

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the way on your left is undeveloped. The variance

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of the undeveloped landscapes in these uh M. S

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. A. S. And the variance as you

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can see all the boxes as the intensity of urbanization

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increases, we have a decreasing variance across cities and

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this is true, particularly for water percent water area

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and also for channel density. So we also want

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to look at the direction of change across this compared

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to the undeveloped landscapes. And to do this,

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we looked at the X axis is the undeveloped landscapes

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in the region and the Y axis is the water

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body coverage. And if you'll notice a pattern in

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these, that the undeveloped when it's drier, things

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tend to increase in the city. That has added

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, well, it has more water than those undeveloped

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regions at the other end of that access in each

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of those graphs that when it's very, very wet

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, we've had a large decrease in water. Um

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And you'll note the log scale on this, uh

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that far right point is Miami. And compared to

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its surrounding on developed land, it went from having

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80 water coverage to about six or seven in between

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, which is a very significant drop. We see

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a similar pattern for water body density and we also

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see a similar pattern for channel density. So for

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a lot of landscapes were losing features and for other

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landscapes were adding them. So what we've used here

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is kind of a space for time substitution. And

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we'd really like to get this question of time.

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Um How fast are these changing and what exactly are

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some of the causal mechanisms? So we can hypothesize

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a little bit because we've seen these in these pictures

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that these are physical alterations. We have built these

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water features and we have taken some away. And

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also the second important one is choice of location um

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that we are selecting out regions to develop that meet

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certain needs, which makes sense. And is the

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of efficient thing to do. But this is what's

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giving some of these urban care ecosystem properties a certain

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characteristics because we are selecting them. And this is

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an important question for us coming up. So we've

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been talking about cities, what about agriculture? Cities

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are fabulous and I love them and but they only

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cover about 3% of the earth's surface. Um give

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or take the estimate. Um Agriculture on the other

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hand, it covers an enormous area of the U

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. S. And globally is covering agricultural development and

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in agriculture, we have similar processes going on.

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We have in some places we add water. We

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have the concept of ubiquitous farm pond and in some

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places we drain water. We have no real measure

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of how many farm ponds have we added. We

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don't know. And draining water futures right now is

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a big issue. This is a just the headline

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of a PNS paper that came out last year about

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the transition and agricultural land cover in the upper midwest

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. And the authors here did an excellent job of

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of trying to ask to calculate how much agricultural land

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is being put into production in response to ethanol.

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So we're driving this and they allude to this threat

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to wetlands. So we know that in this landscape

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, that when farmers tend to, they need the

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arable land so they get rid of the wetlands and

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this is not really what we want to be happening

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. And just the other last week, they put

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in a program to try to uh pay farmers not

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to drain these. So we don't really know though

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about what, what is the agricultural hydro escape,

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How did it get there and what, what causal

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mechanisms uh caused it to give it the characteristics that

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it does. So we took um that same study

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that I talked about and use the other side of

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that information, the undeveloped and agricultural land cover from

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these. And to try to get a preliminary look

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at what agricultural hydro scapes look like. Um because

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of the structure of the spatial structure here, we

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weren't able to do it as a categorical, but

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we ended up with a gradient of 0-79 agricultural land

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cover in these different units from 100 places across the

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United States. And what we observed is that agricultural

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high scapes are complex and driving these hydro scapes are

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amount of precipitation that area receives the slope of the

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land and intensity of agriculture. So I'm gonna give

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you a case study from this one example and like

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I said, this is preliminary data and we're hoping

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that it's uh it's exciting enough to move forward to

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um So what you're looking at is just some simple

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regression relationships between the precipitation divided by the slope of

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the land. So as precipitation increases in land gets

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flatter. What this is saying is if there's no

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agricultural development that those blue uh marks are less than

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10 agricultural land cover in this area, that we

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have an increasing amount of yeah, area covered by

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wetlands. And that's pretty logical. And but the

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red regression or lack thereof is saying is that When

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we have greater than 60 agricultural land cover, this

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is the likely area of wetlands that we will have

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. Um And like I said, this is a

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preliminary look at this. But what it is really

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relating is that different places along the landscape as we

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think about our our spatial heterogeneity with precipitation gradients and

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topography, that the difference between what's going to be

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agricultural land and the natural condition is going to be

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highly variable and so tired. Okay, we can

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look at this at a fairly large level because we

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have precipitation data and we have topography data or slopes

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for the entire US. And using that, the

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data from the blue regression there. What you're looking

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at is uh, a map of what this saying

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, the, what percentage of wetlands would be across

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the United States if there were no land cover development

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. And like I said, this is preliminary and

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we'd like to take a a much more detailed approach

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to this because the other thing we can do with

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it is say, okay, if we use a

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simple multiple regression that with agricultural development, this is

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what we will see in this area. Um,

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this is done with a one square kilometer resolution.

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The likely if we do nothing, the likely hydro

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scape is going to look like with this amount of

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agricultural intensity. So we're pretty excited about this because

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if we know what happened, we might be able

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to a little with a little bit more dexterity forecast

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these changes. So that's really where we're left with

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that. Moving forward, I've shown you some hydro

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escaped patterns and characteristics of urban agriculture and what we'd

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like to do is look at these drivers and mechanisms

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will change. You know, what are the time

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scales? And one of the things that we looked

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at in the data was where there were errors.

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It might be a matter of time that especially in

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cities and in agriculture, what how fast these uh

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like small ponds and features appear and disappear on the

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landscape you much faster than what we anticipated. And

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also hind cast like I just show you what should

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be here and how is that different from what may

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be here and what if we have more development?

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What is the likely characteristics of that hydro escape?

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And also the another big question is of course,

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what are the ecosystem consequences? Hydro escapes play an

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important scaling role in watersheds and play an important role

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in water quality, quantity, bio geochemical cycles and

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habitat. Currently I can't tell you if some of

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these really altered landscapes if they function differently. But

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that is a question that I would like to be

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able to answer in the future. So those are

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hydra scapes and I hope that I have been impressed

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upon you the uh you'll go forth and use this

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term. Um and see the movie. So thank

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you very much. We have lots of we do

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. I chip. Mhm. Yeah. When you

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start off, you showed us like a natural Houston

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, probably natural landscape but some of the others it

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seems to me they were changes to things that were

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already changed. Like the farm ponds were results of

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. Yes. So you're talking about changes of things

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that were changed. So how does that? We

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looked at both of those? Um So in the

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estimate of what used for undeveloped it's we call it

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nominally undeveloped because that's what is categorized under land cover

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. But really it's a it's a look at the

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patterns related to what is there isn't converging relative to

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how it exists because there are very few places where

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that alter that surrounding landscaped isn't altered. So it

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is. And we looked at both of those things

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including like we took out some of the dams and

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so does it still is converging still happen relative if

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we take the dams out of the undeveloped with.

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So it's we had a couple of different measures of

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how it's and the same pattern emerged in every one

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of them. But you're right. It's I wish

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I could if I had 1000 years of imagery um

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It would be very handy right now when you use

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the N. H. D. It's available in

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different scales which may not be available everywhere. So

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how did you compensate for them? Common denominator believe

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that. 30. Yeah evenly. Yeah. So

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you have to look at what might have, things

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might change if you went to the high resolution.

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Uh Not currently. Yeah. Um I apologize for

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coming to lecture a little later. It addresses the

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beginning. But how did you know about doing your

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analysis and how did you huge? Mhm. Uh

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No just the one year. And because it The

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thing with the NH. D. Is that it

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was created by each state individually across the years.

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But the final date was about 2006. So we

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said okay this is the this is the best we

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can do. And so we used one date and

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we didn't see a whole lot of uh for the

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amount of effort it would take to go back and

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use the different NLCS to look at the change we

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didn't see really addressing the question with some efficiency.

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Um But yeah what what I ended up doing was

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to use the N. L. City into aggregate

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to a coarser view of the city by using census

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blocks to to ask what's the majority of the certain

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urban land cover type within a census block. Um

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And then look at it for all of those sorts

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of those census blocks. What's the density of water

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? Does that answer your question? Okay well thank

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you. Yeah.