00:01Today, I'm going to talk about geodesign applications in ecology...
00:04...using Yellowstone as a template for characterizing resilient and healthy ecosystems.
00:10I'm an ecologist with a background in systems approaches.
00:13Seventeen years ago, I cofounded a nonprofit based in Montana called Yellowstone Ecological Research Center...
00:19...where I served as senior research scientist, VP, and program manager.
00:27The greater Yellowstone ecosystem, about 20 million acres in extent, is a mosaic of public and private lands.
00:34In the center, you can see the park itself. It's about 60 by 60 miles in extent, a postage stamp, really, on the face of the earth.
00:42In Yellowstone, we have an ecosystem whose structures - protected undeveloped landscapes...
00:48...components - that is, species - and processes, for example, migration, predation, and hydrological regimes...
00:55...are among the most intact remaining in the temperate world.
00:59The "ferocious wild" of my title refers to the fact that all 18 species of terrestrial carnivores are originally endemic to the park...
01:07...or still present, one of the few places in the lower 48 where you can still see a wolf, a mountain lion, a grizzly bear roaming freely.
01:17Given this happy conjunction of ecological integrity and legal protection, Yellowstone offers itself as a benchmark...
01:24...or standard of reference, for the healthy, well normal ecosystem.
01:29Using Yellowstone as a model, the idea is to build a library, a set of reference standards, for healthy, functional ecosystems.
01:38The larger idea is to develop methodology and workflows for establishing reference values to characterize healthy ecosystems in general.
01:48Over the last six years, I've worked on a joint NASA/US Fish and Wildlife Service project...
01:53...developing tools, workflows, and imagery to build holistic ecosystem models.
01:58If any of you are interested in the more technical aspects of this project, find me later...
02:03...but for now, in a general sense, when I use the term benchmark ecosystem, what I'm getting at is this...
02:12...a systems approach to reference standards.
02:18Of course, all this begs the question, "What constitutes health?"
02:23Take a look at the two people in the image. Are they healthy?
02:27How would we know? What are the markers that we use?
02:30Then take a look at the setting - a lake, looks alpine, water looks clear, air looks clean, landscape appears undeveloped.
02:39That's often a kind of shorthand for ecosystem health.
02:42There are a lot of implicit assumptions we make based on outward appearances, but we know intellectually...
02:48...that appearances provide insufficient information about vulnerability, about resilience, about long-term health prospects.
02:56The look is not the metric; the look can't be the metric of health when we deal with ecosystems.
03:02We're left without adequate metrics. So what do we do?
03:13It strikes me that the most reasonable way that we can all approach ecosystem issues is to borrow from public health paradigms...
03:20...where it's established practice to operationally define health by both function and range of values.
03:28Think of your blood panel when you go to the doctor. How do you know you're sick?
03:32You've deviated measurably and directionally from a standard of published, validated, well normal conditions.
03:38These aren't political; these are reference standards.
03:42There's a library of ranges of values for almost all aspects of individual and population health.
03:49Think of infant mortality rates, influenza infection rates, your white blood cell count, your serum cholesterol.
03:56We're all quite comfortable with this system of metrics. Why not apply the same principles to ecosystem health metrics?
04:04We sort of do through the Clean Air and Clean Water acts, but that's as far as we've gotten.
04:10My work is about creating and supporting the library of well normal values for intact ecosystems.
04:20This approach moves the arguments about health and resilience into the empirical, data-driven domain.
04:26We remove the frame of contentious philosophy and move ahead with rationality informed by long-term vision of systems persistence.
04:35Ecology's historically been confused about its ability to deliver a clear outcomes-driven message.
04:42Let's contrast this with the thought system as it exists in the practice of medicine.
04:46In medicine, a code of bioethics informs all activities, whether you're a basic scientist, a bench researcher, a clinician, a family physician.
04:56All practitioners share an outcomes-driven, common code.
05:01In ecology, we experience a continuous recalibration of what we accept as minimal ecological integrity...
05:08...when we don't have reference standards or a guiding code of bioethics to go back to.
05:13But we can do better.
05:16Here's a workflow for the ecological benchmarking effort I've been working on...
05:21...supported in part by a NASA ecological forecasting grant...
05:24...to integrate remotely sensed data, organismic data, and geophysical data.
05:29We use geodesign principles throughout in workflows and thought process...
05:33...and in framing applications and approaches to complex ecological data integration.
05:39The fundamental workflow in all cases is as shown.
05:42So we begin with species and/or habitat data. These are available either present day or retrospective.
05:49We add in, from the huge armamentarium of available climate inputs, both retrospective and prospective.
05:58Yellowstone's one of the most intensively imaged areas globally, both because it's of interest ecologically and also because it serves...
06:07...as an analog for remote theaters of interest - highly dissected mountainous terrain, low population densities, low road densities.
06:17So lidar, small-footprint lidar, hyperspectral, radar, aerial photography - you name it - and there's a number of group shoots as well.
06:31These first three inputs are then fed into existing, already validated, well-proven ecological model structures...
06:37...and from those, we can take out support for management and decisions.
06:45This work focuses on animal populations because animals are aggregators of ecosystem condition information.
06:52The better the habitat quality, the more the animal community organization will be stable, functional, and persistent.
06:59Our modeling approaches make use of this information aggregation.
07:02We focus on animal densities as a highly efficient shorthand for ecological integrity.
07:08The converse is, of course, also true.
07:10Absence of animal populations shows us that a piece of the system is missing or out of the range of sustainable values.
07:24I'm going to quickly show you some work from a systems model in Yellowstone.
07:28What you're looking at on the left are the building blocks of a holistic ecological model, spatially specific data arrayed in layer stacks.
07:35Think of these as maps of attributes of interest.
07:38On the left side of the image, we begin with a USGS quad orienting you to the region of interest.
07:44Below that, there's a small mammal biomass layer; basically, how many grams of small mammal per square meter.
07:50Think of small mammals as the krill of the terrestrial landscape, critically essential for the food web.
07:57Below that, a remotely sensed derived vegetation layer...
08:00...and elevation is, as you all know, critically important for prediction of response to changes in climatic regimes.
08:10Moving across the image, there's a little box called Data Integration.
08:15For those of you who live in the GIS world, that box can also be called Blood, Sweat, Tears, and Teeth Gnashing, right?
08:23A lot happens in there, so that's about 90 percent of the work in assembling these models occurs in that component.
08:31And then we move across to the right-hand side of the model, which is the layer stack array. And let's see.
08:42So we can see the same data layers connected by a punch-through, that purple rod, moving through all the data layers.
08:47The intersection of this punch-through with each of the data layers yields a value from the point of intersection...
08:53...and these are subsequently fed into tabular arrays, spreadsheets, for the follow-through into the modeling component of the workflow.
09:03Obviously, these purple punch-throughs are arrayed across a landscape...
09:07...and they can be developed according to different sampling regimes randomly or different sampling intensities.
09:13So the appeal of this layer stack and then punch-through approach is threefold.
09:18It's absolutely simple; it's scalable up or down on several levels; and lastly...
09:23...it's amenable to scenario building or what-if models, as we'll see in a moment.
09:28So let's just take a look at the right-hand side of this image in an expanded view.
09:34Same punch-through, here shown in red so it's a little bit more visible for you guys.
09:38On the layer stack of the data are fed - the data intersection values are fed into a tiny fragment of a table...
09:46...that you can see up there as a representative grab, and then again, these go into the models.
09:52So you all remember the concept of the well normal ranges of values for healthy ecosystem that we began with.
10:00This table can be immediately mined for high and low values across the region of interest, so we have a bankable range of values...
10:07...for each of the attribute layers, as well as a wealth of relational information and distributional information.
10:14For scenario building, data layers for anticipated futures, such as proposed developments like new roads, can be input...
10:21...and the resulting forecast models can be compared to existing models.
10:25We hold all inputs constant, save one, rerun the model.
10:28So this is a really controlled, rigorous, and transparent way of forecasting.
10:33The bottom layer in the layer stack is the model output itself.
10:37In this case, it's a probability surface for an antelope habitat model, and you'll see it again in the next image.
10:42If there's any modelers out there, it's a resource selection probability function map.
10:48And so here we see the modeled output.
10:51On the colored image at the top right represents about 15 hundred square miles of Yellowstone's northern range.
10:57You can see the USGS quad that orients you to this piece of landscape...
11:01...peeking out from underneath the same-scale color ramp modeled surface.
11:05Red line running through the center is a road.
11:08And as far as the color-ramped image itself, this image answers a question - Where's it great to be an antelope?...
11:14...with brown representing prime habitat and blue representing less used or less desirable habitat.
11:23So the color ramp surface here is arrived at by using equations that relate all environmental layers to each other...
11:30...then we fit the best model from the arsenal of current published ecological model structures.
11:35The table to the left side of the image depicts that part of the quantitative model results.
11:39I figured since this is a black hole of postlunch slump, we can leave that part out, right?
11:46So let's take a quick look at the lower right corner of this color-ramped image, where I've thrown in a yellow box, and we'll run a scenario.
11:54Here we see that grab of our original model surface.
11:57I have run a road through there in tan; it's evident and circled in yellow so you can see it.
12:03It's clear that that road runs through what we remember is prime antelope habitat in dark brown.
12:09So remember, for this process we hold all model inputs constant, save the one, and then we rerun the model.
12:16And we can see in the bottom image this rerun output.
12:19The total coverage of brown pixels by visual inspection is decreased...
12:24...and the road effect is also more pronounced at the convergence of the two roads.
12:29So here we have a quantifiable, transparent, and defensible forecast model.
12:39Remember that animals are information aggregators. They tell us directly about ecosystem quality.
12:46So we build models around animals, and their continued population presence is the most efficient way to understand ecosystem integrity.
12:55Animals provide the fundamental controls on the systems they inhabit.
12:59Our dominant cultural narrative portrays animals as decorations on the landscape...
13:05...but recent research shows us how integral they are to knitting together the fabric of the systems we rely on.
13:14Yellowstone is the planet's first national park, protected in perpetuity. Not just 250 years; perpetuity.
13:23That's a bold concept Roosevelt came up with.
13:26Her legacy has inspired the creation of parks and protected areas throughout the world.
13:31With all the components and processes still in place, she and the data that she embodies...
13:37...can be used as a standard of reference for system health - the world's first benchmark ecosystem.
13:47In conclusion, I agree with Bran Ferren's assertion that the stories we tell about the world we live in matter greatly.
13:54I believe in the power of narrative models and of visual and graphic imagery.
14:00These have the power to shift how we humans relate to the world.
14:04I think we can begin to write a story that's large enough to encompass a bioethical set of arguments.
14:11The story I'd like to write is a story of a data ark, A-R-K, in which to place our knowledge of the healthiest of what remains...
14:21...so that when we design our way forward, we still maintain the blueprints of the elements...
14:28...that we have not yet become wise enough to understand, let alone replicate.
14:35So I hope you take away three ideas.
14:37First, without a standard of reference, our conservation efforts will necessarily be incomplete.
14:43Let's benchmark our conservation efforts using state-of-the-art data.
14:47Second, animals are brilliant aggregators of information about ecosystem conditions.
14:52We can use their presence to inform us on how we're doing in supporting earth's systems.
14:59And lastly, a complex effort like this needs a superstructure, a powerful yet transparent architecture...
15:07...and geodesign can serve that function.