Eyes on Earth Episode 56 - Modeling the Past to Plan for the Future

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Detailed Description

Mapping land cover in the United States in the present isn’t a simple job, but satellites like Landsat make it possible. Mapping conditions in the pre-satellite era, which the LANDFIRE program does through its Biophysical Settings (BpS) GIS data products, is a far trickier proposition. BpS essentially offer a spatially-explicit map of pre-Colonial land cover in the U.S., alongside models that help scientists understand how landscapes re-grow and recover after disturbances. On this episode of Eyes on Earth, we learn how LANDFIRE went about creating its BpS datasets and the value they hold for land managers and fire scientists.

Details

Episode Number: 56

Date Taken:

Length: 00:17:36

Location Taken: Sioux Falls, SD, US

Credits

 

Guest, Kori Blankenship, Fire Ecologist and Spatial Analyst, The Nature Conservancy

Host, John Hult (Contractor for USGS EROS Center)

Transcript

JOHN HULT: Hello everyone, and welcome to another episode of Eyes on Earth. Weíre a podcast that focuses on our ever-changing planet, and on the people here at EROS and across the globe who use remote sensing to monitor and study the health of Earth. Iím your host, John Hult. Satellite data and ground surveys can give us a pretty good idea of what kinds of plant life exists across the United States right now. Thatís what LANDFIRE does through several of its GIS mapping products. But what if you wanted to know what kinds of plant life existed before the satellite era? Well, thatís a trickier question, and itís one that LANDFIRE has spent well over a decade working to answer. Through a product called Biophysical Settings, or BPS. BPS defines vegetation conditions prior to European settlement at Landsat satellite scale, all across the United States. Determining those settings wasnít easy though. It required input from more than 800 experts and multiple rounds of scientific review. Researchers with a LANDFIRE partner called the Nature Conservancy recently released a paper that explains how that work was performed, and how those baseline conditions help land managers and the scientific community understand the landscape, prioritize restoration projects, plan for fire response and much, much more. Here with us to talk about this topic is lead author Kori Blankenship. A fire ecologist with the Nature Conservancy. Kori, welcome to Eyes on Earth!
KORI BLANKENSHIP:
Thank you. Itís great to be here.
HULT:
Well, itís great to have you. Weíre always happy to have someone from the Nature Conservancy on the show. One of the partners of LANDFIRE. Partners with Earth Resources Observation and Science Center. Letís start off our talk about Biophysical Settings. Let me just ask you what does that mean in general? What does Biophysical Settings mean in the context of the LANDFIRE program? What are we talking about here?
BLANKENSHIP:
Well, you gave a great definition, I think, when you started. Itís essentially historical vegetation. Itís a fancy name for what we think was on the landscape prior to colonization. So thatís the idea of Biophysical Setting. LANDFIRE takes the concept and does two things with it. First, we create a map. So, we have spatial representation of where all these historical vegetation types existed. Then the second part, the piece that we wrote about in our paper, is that we model those historical vegetation types or ecosystems. So, we have a quantitative representation that describes the growth and change dynamics of those ecosystems over time.
HULT:
So you have the map itself, and then you have sort of an explanation.
BLANKENSHIP:
Right. So, you can see on the map where these things are located. And then you can learn more about it in the model. You know, how do these things function? How did they behave? How did they grow over time? What were the drivers of change?
HULT:
I see. So, they were all the factors that influenced the way the vegetation changed or grew up. If you want to use that sort of clunky analogy.
BLANKENSHIP:
Yeah. Actually, itís not so clunky. When we talk about human populations, you can think about how a child develops over time. You have young children. They grow up to be teenagers. Then adults. Then you have elderly. Well, vegetation changes in those same predictable ways. A forest might start with young seedlings and saplings. The trees will grow taller over time. Eventually you will have mature, what you might think of as adult tree on the landscape. And then finally, those older stages are those old growth forests. The models essentially quantify how long it takes to go through those stages. And then the second component, again going back to the population dynamics analogy Ö with a population you look at things like birth rates, migration, disease. All those drivers of change in a human population. Well, itís the same thing in an ecosystem. With ecosystems we look at drivers of change like hurricanes, fires, insects, and disease. So again, itís that growth and change over time in ecosystems just like you would look at with human populations.
HULT:
It sounds like it took a heck of a lot of work to pull these together. Tell us about the process. How did you find the answers to these questions? It sounds like there were a lot of collaborators and meetings and determinations, ut obviously none of you could go back in time in a DeLorean or something and take a look. How did you figure this out?
BLANKENSHIP:
Well, I wish we could have done that. But instead what we did is we asked experts around the country to help us. This project started in the early 2000s with a prototype. One of the things we learned right off the bat was that there really arenít enough data to build these ecosystem models. Weíre lacking information about how ecosystems function essentially, which is why we need models, right? So, we took a combination of experts as well as all the scientific data we could find. Combine those into the models and thatís how we created the set of models that we have today. Initially when we started this effort, we did kind of a road show. In about a year we went around the country and held twelve of thirteen large meetings where we invited experts to bring their knowledge to help us build these models. And then from that point over the last about fifteen years, weíve gone back and revisited the models and brought in more experts to help us, and new literature to improve the models over time. At this point weíve had about 800 people contribute to the development and refinement of this model set. We have over nine hundred models representing all the ecosystems across the United States.
HULT:
Wow. Thatís a lot of information and a lot of people. Now, forgive me if Iím getting too deep into the weeds here, but who are these people? Do you put a piece of paper up in the student union or something with a phone number on it and say do you know about the trees in 1483 or something? How do you find these folks and what are the areas of expertise? Where are you pulling this knowledge from?

BLANKENSHIP:
We looked to people that would have the ecological knowledge necessary to build these models. A lot of these people came from academia. We had a lot of experts from the Nature Conservancy. We drew heavily from the land management agencies in this country, so places like the Forest Service or Bureau of Land Management. Those are the people with the expertise. They are out on the ground. They have a lot of experience with how these ecosystems function, even if itís not in published literature. Thereís a lot of knowledge in how ecosystems behave and change over time. So, those are the people we invited.
HULT:
I want to talk about a science term: state and transition modeling. First of all, can you explain what that is? Is that kind of what you were doing where you were working backwards?
BLANKENSHIP:
Yes. So, when I say Biophysical Settings model or ecosystem model technically what I am talking about is this thing called a state and transition model. What that does is it breaks down an ecosystem into its component parts. Those are the development stages. The young forest, the adult forest, the old growth forest. Those become the states and then the transitions are the things that drive change over time. And the models are quantitative. So, each development stage has an age range associated with it. And thereís a probability for each transition. Like fire or hurricane. And so you can run the model out over time to get a sense of what the landscape may have looked like historically. And how often these disturbances occurred.
HULT:
Ok, ok. So, basically you are trying to figure out where it is and how it got there. And the transition is how it got there, and the state is where it is. And you can map that either backwards or forwards as I understand it. You guys went backwards.
BLANKENSHIP:
Thatís right.
HULT:
And LANDFIRE goes forwards as well, when they are modeling out changes to vegetation. Given the approach which you had for this, it seems like you could have gone further or maybe not quite as far. Why a pre-European condition baseline for Biophysical Settings? Why not go back further or not quite as far?
BLANKENSHIP:
Thereís nothing magical about the pre-colonization time period that we chose. But there were a couple reasons that we chose it. One, was that itís an ecologically relevant time period. If you go too far back, youíre getting into different climates that arenít relevant to management today. The second reason is that we had practical considerations. Even looking at pre-colonization, data are limited. We chose this time period because we felt like it was still ecologically relevant and there was still some science to guide us on what the conditions looked like.
HULT:
Right. So, there was actually some data that was collected that you could look at. That was a big factor.
BLANKENSHIP:
Thatís right. So, a couple of the sources that we used were things like fire histories. Fire histories actually look at the growth rings of trees. Each year a tree records an annual ring. Some trees will record a fire when it passes through, as a scar in that ring. And so, you can see how old trees are, how fast theyíre growing and how often fires occurred. So, thatís one source of data.
HULT:
The actual trees. The trees themselves.
BLANKENSHIP:
Exactly. That is a great source of data in those forest types that record fires. So thatís things like a ponderosa pine forest. Of course, that leaves out non-forest areas. But we have some other sources of data. One of those sources is general land office surveys. Back when this country was expanding westward, the government set out to survey all the land, and they did that in a rectangular grid pattern. So there was this regular grid, and you had surveyors going across the landscape, and they would take notes as they went. So, you have notes at regular intervals about what vegetation existed. And they would even note things like if a fire had passed through. And so we get clues to what the landscape looked like from those kind of data as well. Theyíre not perfect, but we take all these sources together and thatís how we develop this picture and these models of how the ecosystems functioned.
HULT:
So itís sort of a variety of different sources. Some, as you say, from the landscape, but also this grid system that was sort of mapped out, has been useful to give you some clues as to which way you are going.
BLANKENSHIP:
Thatís right. We take any information that we can. Whether it is fire history, old survey data, expert knowledge based on vegetation monitoring. All those things together give us information about how these ecosystems function.
HULT:
When we talk about BPS, are we talking about ideal conditions? Or is it just prior conditions? Is there a distinction, and does that distinction matter?
BLANKENSHIP:
Well, let me offer a different term for you. Rather than ideal, I think weíre talking about useful conditions. These are conditions that ecosystems evolved with and to which they are adapted. The reason thatís useful is because it helps us to understand the conditions, we see on the landscape today. It also gives us insight as to how these ecosystems behaved and how they might change in the future. Let me give you an example. I live in Bend, Oregon. Just a couple miles from the great Deschutes National Forest. The first vegetation type that you encounter is Ponderosa Pine Forest. Our models, the BPS models as well as other data sources, tell us that these forests were dominated by large, old, widely spaced trees in the past. That doesnít mean that you wouldnít have areas with younger maybe denser trees, but most of the landscape would have been these large, open, old growth conditions. We know from our Biophysical Settings models ,plus the last one hundred years of fire suppression, what happens when fire is removed from the landscape. You get a denser and younger forest. Especially as weíre looking towards a drier more fire prone future, the models can tell us what type of forests can handle that future. And again, itís those big, open stands of large, widely spaced trees. So, itís that understanding that helps the forest service manage the forests around here. Theyíre doing a lot of thinning and burning. And the idea is that they are making that forest more resilient to a future where we expect more fire. At the same time, thereís actually a lot of benefit for people, because there is decreasing risk of high severity fire in the community of Bend.
HULT:
I think that maybe some people will see pre-European conditions and think, ìWell, is that what all land managers are trying to get back to? Is that what you are trying to say?î And no, itís not really like that, is it? It is just understanding whatís on the landscape and whatís happened to it, and whatís going to happen to it. And seeing if thatís going to be relevant to the conditions on the ground today.
BLANKENSHIP:
Thatís right. Itís about informing land management. And so, getting back to that example of population dynamics for human communities, what youíre looking at when you are trying to understand human population dynamics is, you are trying to understand what your population looks like and plan for the needs of society over time. Land managers try to do the same thing. And they use ecosystem models to help them do that. In some cases, restoration is a goal. And you can use the Biophysical Settings models as a target for what restoration might look like to quantify your goal, as well as to give you insight into the types of management actions that will help you restore an ecosystem. The second example, and this is what LANDFIRE does with the Biophysical Settings models, is the models provide a baseline for measuring change over time. That can be used for things like prioritization, things like where do we want to allocate fuels money to reduce things like fire risk? Where do we want to invest conservation dollars in places that have relatively good vegetation condition?
HULT:
It almost sounds as though youíre saying there isnít enough money and there arenít enough resources to do everything we want to do. How could that be?
BLANKENSHIP:
Yep. Thatís exactly right. There was a study out in California. And they asked the question, ìCan we thin our way out of this problem with high severity wildfire?î Because we know, if we thin the forest, we reduce the intensity of fires. And the answer was no. When you take into consideration all the constraints that are placed on federal lands. For example, you canít log in wilderness. And you canít thin too far from a road. You canít thin too close to riparian areas. When you take into consideration all of those constraints, we canít thin our way out of the problem.

HULT:
Do the Biophysical Settings evolve as LANDFIRE evolves? If so, how does it evolve? Do the figures change? Do the settings change? What does the future hold there?
BLANKENSHIP:
Well, theoretically on the types of time scales that we are interested in, in terms of management Biophysical Settings shouldnít change, because the sites arenít changing. But we know that our maps and our models are not perfect, and that is why we have invested over the last 15 years plus in updating and refining these models. A really great example is, when we started back in the early 2000s, we created a model of Appalachian Pine Oak Forest. At that time, we didnít have any or had very few fire history studies in the Appalachians. So at that time we estimated the fire frequency to be about a hundred years. Well, in the intervening decade or more, thereís been a lot of fire history work in that area. When we went back and revise this model recently, we changed the fire frequency to every 13 years. So we went from a hundred years to 13 years based on this new science and new information. Weíre still trying to represent that pre-Colonization vegetation, but our understanding does change over time.
HULT:
Where would people find this stuff? Is this all available in map format somewhere?
BLANKENSHIP:
Yeah. Like all LANDFIRE products, the Biophysical Settings models are online at LANDFIRE.gov and all the data are open and free to download.
HULT:
And you can actually map it out too. Thereís like a semi-intuitive mapping tool, right?
BLANKENSHIP:
Right. So, you can get the map of historical vegetation or Biophysical Settings, as well as the models. All online.
HULT:
Weíve been talking with Kori Blankenship of the Nature Conservancy about Biophysical Settings, vegetation dynamics and how LANDFIRE helps us to understand and manage our landís resources. Kori, thank you for joining us.
BLANKENSHIP:
Thank you so much.
HULT:
Thank you, listeners for joining us as well. Be sure to drop in for the next episode of Eyes on Earth. You can find us on our website at usgs.gov/eros or you can find our shows on Apple podcasts or Google podcasts. This podcast is a property of the US Geological Survey/Department of the Interior.