PubTalk 04/2019 - California's Ecosystems

PubTalk 04/2019 - California's Ecosystems

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This. Video, is, a one-hour presentation, of. The USGS, evening. Public lecture series titled. The, story of California's, changing, ecosystems. As observed. From space, the. Presentation. Is being hosted in the USGS, Menlo. Park facility. The. Host welcomes, the audience and, it introduces. The speaker Kristin. Byrd who, is a USGS physical. Scientist, this. Christian is giving her presentation. She is continually. Pointing, to you and referring. To slides presented on the screen the. Slides are a mixture of charts and graphs and photos, at. The end of the presentation. There, was a question-and-answer, session. With members, of the audience. Good. Evening, can, you hear me, great. My, name is Susan Benjamin I'm. One of the. More, that, better okay, you tell me I'm. Not good with these I'm not gonna be a rock singer anytime, oh I'm. One of the managers here. With USGS on the campus and, I'm delighted to welcome you all to the public lecture tonight, and, also, to, tell. You that we have another one of these plans in a little. Over a month to. Come back on May 30th. Susan. Hecker will be talking about new mapping of the Rogers Creek fault it's longer and more complex, than we thought that. Sounds like a great talk um, a, little, housekeeping, in. The event of an emergency a very, loud, noise, will. Come from the ceiling and I, hope that all of you will go carefully. And quietly out, the back door and and down the stairs and we. Will hope that won't happen but but she won't we want to stay in the building at the desk. So. It's my pleasure tonight, to introduce you. To dr. Kristin Byrd she's. A research physical, scientist, at the Western Geographic, Science Center here in Menlo Park with. Expertise, in Applied landscape, ecology, and remote sensing she leads, landscape, studies of natural, and working lands focusing, on wetlands, rangelands. Climate. And land use change in California's. Central Valley and in estuaries throughout, the country she. Received her PhD in, environmental science, policy and management, from UC Berkeley her. Master's in ecology. And systematics. From San Francisco, State University and, her. BS in environmental science, from Cornell University, Kristin. Uses remote sensing, of wetland vegetation to. Quantify habitat, quality for. Ecological forecasting, and, wetland, carbon, stocks for greenhouse, gas inventories. She's. Developed, scenarios, of land-use climate, and hydrologic, change to assess potential. Impacts, to ecosystem, services, in the, California, rangelands, and to, identify opportunities for, rangeland, conservation. Increased. Carbon sequestration, and drought resilience, she. Prioritizes the. Use of open data and open. Source, software to. Help aid tool, development, for decision-makers and her, projects always include outreach to land managers to support conservation, and. Restoration, planning. Her. Talk today is titled the. Story of California's changin ecosystems, as observed. From space. Thanks. Everyone for being here today. Yeah. Today I'd like to talk about California and, ecosystems. And diversity we have here in the state as you, know California, is a really diverse state, is actually a biodiversity. Hotspot. Which. Is um which means that it has high biodiversity but, it's also threatened, by a lot of human activity, and, 2025. Biodiversity. Hotspots, in the world, and. The reason for the diversity is a topographic, diversity that we have in the state and this, map here shows the, various eco regions that we have throughout the state and you're probably familiar with many, of them including the Coast Range the. Cascades. The. Central Valley in the middle the, Basin and Range to the east and then, the Sierra Nevada mountains. So. We have a lot of diversity we've experienced. Quite a bit of change over the past 100, 200, years with. The most populous, state in the country and back in 1900. There, were only 2 2 million people here and, by 1950, there were 10 million people and now we have about 39, million people in the state and. In. Addition to population, growth our. Climate has also been changing, just based on the historical, record we've, seen air temperatures, increasing, over time. In. The, years, 2014-15. Seating, and 17 were actually the warmest on record. And. Our. State is becoming more dry and precipitation, is more unpredictable, so.

In, The past 10, years seven, of them have been below average rainfall, compared. To the historical average. In. Addition, we have, experiencing. Creasing levels and feet of sea level. Rise. Since. 1900, sea levels and the San Francisco barrier have increased, by 7 inches. So, on top of that we you, know we see a lot of these changes and a lot of that takes, place along in, terms of our land use and how we use the land in California as well um, since the 1970s. We've seen an increase in development of 38%. It, seems like a lot but you have to remember that, you. Might have developed land our cities and our in our communities, across, the state will only represent, about 4% of the whole land area of the state, but. At the same time we've seen a great, loss of our grass landowners shrubland, ecosystems as. Well as our forests, due to development, and agriculture, and, things. Like forest, harvesting. But. At the same time we've actually put. A lot of investment into conservation, and starting. In the 1930s the state started. To really emphasize. Conservation. Of state lands where we caught a lot of the state parks formed. And if. You look at these maps going, from 1970. To the future you can see an. Increase in conservation lands throughout the state in. The matching image we've started to see a lot more investment. In federal, conservation, lands so if you look especially in. The east eastern, areas of the state you'll see larger. Green, areas, representing, more conservation, lands, coming into the state. So. You know it's very dynamic State we have a lot of changes. Happening. And. Luckily, we have many different kinds of satellites, in the sky that we can use to observe these changes, and. And track them over time this. Map this figure here is showing a, whole series of. Satellites. That. Are NASA. Earth science missions. Many, of them are existing. And some. Of them are planned for the future. But. Both these satellites, do they can measure many different kinds of features but this is where they're tracking the. Reflected. And emitted radiation. From the land service, at different wavelengths along the electromagnetic, spectrum. From. Some visible, wavelengths, I will be out to radio, to. Be, able to detect different. Features and the, changes, on the planet. So. Just to give you an example of some of the things that we can see from satellite images. You. Probably remember the camp fire back in the fall this is an image taken from the motifs, instrument, on the Terra satellite showing. The extent of the smoke, from the camp fire and. Because. Images, are collected. Over, repeat. Intervals, we can see change quite easily so this is a snowpack, in California, in 2011, which was a relatively right here and, then this is 2014, that was one of our extreme drought, years you can see the dramatic change, in snow and. Then, we can use tools like radar to look at things. Like subsidence. In the, San Joaquin Valley the. Sinking. Of our land, this. Area here shows subsidence. In the San Joaquin Valley, where. You have to break the bright yellow and.

Then. Here this may seem familiar to you this is the South Bay salt ponds just come near near to us where. We've, had a lot of restoration take place and looking at repeat images we can see the increase in the tidal marshes here, this being pre restoration. And then out here we. Have post, restoration. New Marsh is being formed. So. As you, saw from that first side. There's a lot of different types of satellites, available, to track, these changes, one. Of the satellites, that I've been working with most for my work is the Landsat, satellite. Series, so, this is a series, of satellites that have been in operation since 1972. It's. A joint USGS. National. Initiative. And it's the longest continuously. Acquired space-based. Moderate, resolution data, archive, and what's, great about it is it collects an image, at. The same place on the ground every two weeks, it covers the globe every, two weeks. It, has a resolution of about 30, meters by 30 meters for a pixel, so you, can really detect a lot of different things and. It's. Free and it, can be easily, downloaded, and the USGS. Processes. It for you so you can bring it right into your analysis. Pretty. Easily. So. The, Landsat. Satellite actually has two different sensors, on it one, is the operational, land imager and, it's tracking it's tracking reflected. Light from the visible to the near-infrared wavelengths and. Then. It has another, sensor, called the thermal infrared sensor with. Some, recording. Emitted thermal infrared radiation. Which come in use from mapping land surface, temperature or, soil and moisture for, an example. Most. The time I've been working, with the first. Sensor, the operational, land imager which. Is collecting. Information. At seven different. Sections. Of the electromagnetic, spectrum from, the visible. To the near-infrared so, it basically is taking seven different pictures, it's, seven, different spots along the spectrum. Your. Pictures taken from the UM from. The blue part of the spectrum all the way out to the short red shirt, wave infrared region of the spectrum. And. It's. Really interesting. We can take these seven different images and combine them in different ways to get a false color image to, be able to see certain features that we might not be able to see with the naked eye so here's a picture, of. Crater. Lake national park and the red is actually showing a lot of vegetation and in a false color image. So. I'm. Kind of tell you a little bit more about how how we work with this data, so. Different, features can reflect light in, different ways across the spectrum, and that causes, them to have a unique signature so. Something. Like like. Like. Plants. Might reflect a little bit of light and the green because we we see them as green but, then reflect a lot of light in the near-infrared. Spectrum, and and. Then they might and then as you go through the spectrum is you know different levels. Of reflectance. And then something like um clay. Or Kaylee Knight will have a really high reflectance in, the, visible part so. This is sort of their their their spectral. Signature, but there are Landsat, can see. The. Parts of the spectrum within these certain bands is aware the red the, red Peaks. Are and, so. We're getting information within, these certain, sections, and, we. Can analyze that data in a certain way to tell us something about the, features, that we're seeing like for example for plants we, can check the data and learn a lot of things about what kind of plans they are how, they're growing are they healthy are they stressed how large they are like.

For Example one thing we'll do is we'll develop develop, a vegetation, index a, real common one is called a normalized, difference vegetation index, so. Ratio of reflected, light in the near-infrared and, red regions, and it, can tell us how healthy a plant is if as a high-value it's, a really healthy green large, biomass, large growth if, it's stressed it'll have a lower value. So. Because. Of this remote sensing data is collected that we, repeat, intervals, that have we have a long historical record, you. Can you see for, a lot of different kinds of analyses, so we. Can use it for you know Matt just mapping features creating maps but also quantifying. How much of something is on the ground. We. Can do historical, change detection to see how much things have changed in the past, we. Can even use it in models to model, environmental. Change and then, eventually. Forecast. Change, into the future and predict, what may happen. So. When. We're talking about some of these applications as I go through the talk. So, I I have actually been working a lot in in, wetlands. In California. Since. Early. 2000s, worked in different Whelan's across the state and so. My. Talk is going to focus on a couple of different examples of using very about sensing in different, wetlands and, how they've been changing, I've. Mostly been working, in in marshes. And so marshes, are really, characteristic. Of having. Herbaceous. Vegetation. That. Grows above the water surface, and the, bay Service's, gobei here we have marshes, that are different based on their salinity levels so we have tidal marshes either saline, or, brackish. Or fresh. We. Can have non tidal, freshwater marshes, and. Then as you go further east into the Central Valley we have marshes. As well but a lot of them are really highly managed. They've. Been a really important, part of California's, landscape, over the over. Its history but. They've experienced, quite a bit of change over the past 200 years. So. Here's a map, of the. Central Valley before. 1900. And kind of around present day and, you can see that you, know, before. The. Nineteen hundreds the. Central. Valley actually had extensive, bail-ins, all it running all the way through it from north to south. As. Long as a lot of grasslands, but as you know the Central Valley has been very transformed. And we. Have lost about 90 percent of those wetlands. There's. A group called the San Francisco estuary Institute. They've done a some really amazing, work on historical, ecology, and they've pulled together many data sets and photos and maps to, recreate what San Francisco Bay looked like 200 years ago and the, green here the map represents. Tidal. Marsh so you can see back. Before. A, lot of European. Development, we had extensive. Marshes, of all around the bay north bay this. Is Sassoon marsh and then in the South Bay where we are now and.

That's Been converted quite. A bit where, we have a lot of our culture in the North Bay now a. Lot of development, kind of an essential Bay and then where. We are now a lot, that Marsh got converted to the salt, times you've. Probably seen. San. Francisco instituted. A similar project, for the Delta this is going further east this San Francisco San Joaquin Delta and this area really experienced. Dramatic change, after. The gold rush the. People. Form, levees around marshes, to drain them and convert them to agriculture. And so. As a result we have lost 98%. Of our marshes. In this area. So. Despite, despite, the losses we've seen in Whelan's they still remain. Highly, valuable, ecosystem. For. This day as well as the people that live there and they. Have a lot of benefits, and these benefits are what we would call ecosystem. Services, so just, to name a few they're. Really beneficial as a nursery for a juvenile, Wildlife, they. Serve a purpose of helping, with flood control. And. Also, filtering. Stormwater. They. Can help reduce the impacts of storms, serving. As a buffer. Really. Important for recreation, and tourism. Really, important, sinks of cart for carbon, can. Be a source of employment, and jobs and also, can help reduce the impacts of sea level rise. So. Just focusing on one of those benefits. Carbon. Storage. Coastal. Wetlands especially, coastal tidal marshes, have, a really high capacity. To store a lot of carbon in their soils, and in their vegetation and they. Can store carbon it very, fast rates call it carbon sequestration they. Can actually store carbon faster. Than forests can two. To four times faster on a per area basis. So. Because of their high, capacity, to store carbon. They've. Kind of gotten the name of coastal wetland blue carbon, and people. Have been very, interested in in tracking their capacity, to do this as. A way of in. One, way of. Looking at us is to the incentivize, well in restoration because, this would be a benefit that would they would get out of it. So. Because of this coastal. Wetland blue carbon and how important, it is it's it's now included. In our, national, greenhouse gas inventory, that the EPA does every year that. Gets reported to the UN and so this inventory tracks, all of our emissions that we have in the country from all of our different industrial sectors as, well as our renewable, so our removals, are the how, we are taking, carbon out of the atmosphere and, sequestering, sequestering. It into the land base so what well ins play a role in that. So. So. That's now part of the the. Inventory, and. The way, that they're able to, include. This. Bird. Conduct. This interval for, coastal wetlands is to looking at changes. In carbon stocks from one year to the next because that change with one year the next would and would indicate, a removal, or of carbon. From the atmosphere and, into the land and. Typically. They'll track changes and carbon stocks across, five different pools, here like above-ground biomass dead, wood litter soil, organic matter and. And. I've been working on a project recently, really. Focusing, on tracking the above-ground biomass the biomass is sort of the volume of the vegetation how large it is how much it weighs, how much is growing and then. The carbon that's stored within that vegetation. So. As part of that project I was able to use the Landsat satellites, to, be able to map the biomass, of all the tidal marshes in, the San Francisco Bay and understand. The conversion, of the, weight of the biomass, to carbon, content, come up with a map of tidal. Marsh above-ground. Carbon, stocks. And. So as. You, might know the San, Francisco Bay is more saline, closer, to the Golden Gate it becomes more fresh as you go east and that really influences, biomass, and Cardoso you get higher carbon, carbon.

Stocks Um as you go further, east and into the fresh fresher, waters. What's. Pretty neat though is we're able to quantify that within. This region of the. Just within the above-ground part of the vegetation we, have over 32,000. Mega grams of carbon, and if, you convert that to co2 equivalent, you actually get the. Equivalent of 25 thousand, cars annually. On, the road which, is pretty, neat so you can see that how the tidal. Marshes are offsetting, those kinds of emissions and. Just, to give you an idea of how we actually go about making. This map a lot of it they're not a work on the ground that goes into making the map we have had a lot of people that we've worked with over the years that have been collecting a lot of field data in. Toddler marshes around the bay on biomass. And so what they do is they go out in the field and they they collect a sample of biomass and they also take a GPS reading at the same time to be able to register it on the, ground and, then. They, match. Up that biomass, data, with the Landsat, reflectance, that was taken at the same location, to, create a data set, and. The Doudna set can be put into a, machine. Learning algorithm. We. Use, something called random forests in order, to make predictions, and then we can predict what the biomass and the carbon might be in places where we didn't have data and by doing that we can we can make a map. So. That's sort of in, a nutshell how we how, we go about doing that. So. Looking a little bit closer into San Francisco Bay specifically. In the sassoon Marsh east, of us we did a focus study on a specific. Wetland, called Rush ranch and. This. Is part. Of the San Francisco Bay s2 where research reserve it's a reference March it's one of them mature marshes. And sassoon marsh that haven't really been very impacted, by people over time and. What. We were really interested in is understanding how, marsh. Habitat might, change in the future with sea level rise, so. There's a lot of models available, to be able to, calculate. This, and forecast what might happen to the marshes, but, what we wanted to do was see if we could run that model with remote sensing data so, we can get a, regional, perspective of what the change might be as opposed to just in one specific location. So. What's really interesting, I think about tidal. Marshes especially, is that they have different habitats, within.

Them But, their habitat. Changes are really tightly tied to the small. Changes, in elevation within, the marsh so, inrush. Ranch even. Just an elevation, change of one-and-a-half meters you can go from a mud flat to, an upland you have a couple of different Marsh habitats, in between but are really different according to their to, their vegetation and. Marshes. Do you have the capacity to gain their elevation, as sea level rises in, a gradual, sort of background rate and they've been doing that for millennia, so, in a way that can keep up with sea level rise but if the rates of sea levels rise. Increases too much then marshes may or may not be able to keep, pace and they may end up drowning. As a result, and a couple of things that influences, are. What. The baseline elevation. Is of the marsh. The. Plant biomass how much is growing there and. Also the suspended, sediment, concentrations. And the water because the suspended, sediments are being deposited on the marsh and they're helping to to, build up that soil. So. For our project we again use Landsat. And we were able to map the suspended, sediment, concentrations. And the channels so it's pretty neat to see you sort of the greeting of the of the sediments, as, you move up through the channels and into Rush Ranch. We. Had a neat application that, we used as part of the project, it was a it. Was an app on the iPhone, that you can you can download called hydro color and you. Can actually measure. The, concentration, of the sediments, in the water by, taking a picture of it so we were able to use that as like a way to calibrate, and create, our Maps. And. Again because Lisa takes a picture like every two weeks we could get a time series across. The year of how that sediment changed, and get, an annual average which was basically what we needed for for, our model for our purposes. So. What we did is we wanted to work with a model, is called a marsh equilibrium. Model is it's. A very detailed process. Base model that can, forecast. How a marsh elevation, will change gradually with sea level rise and we, provided input data from our from our satellites, so we had input data on above-ground. Biomass as. Well as suspended, sediment concentrations. And. You said to look at what changes might occur in brush Ranch. And. The other benefit, of having the remote sensing data so we can run the model in places where we weren't even able to get to to go, collect data in the field we can just get the data from the remote sensing. So. Here's an example of some results, so basically, this. Is a sort, of present-day rush ranch this the marsh is a high high high. Marsh. Habitat has. A sort. Of a, typical. Vegetation. Of a lot of salt grass. And. There's a couple other marshes, in the system marsh that we tested as well and, after. About a hundred years with a projected. 1 meter sea level rise we saw that the habitat did change and as. There was a sort of a small sinking, relative, to the sea level the, vegetation, changed to a low marsh habitat so, it would be a lot of in this case a lot of bull. Rushes now. In two leaves and similar. Things occurred in the other marsh - and in some cases even might, get converted to mud flat. Another. Thing we can do with this kind of information is, um tie. It with, information. About. Specific. Species, and, habitat their habitat requirements so, a couple, of endangered, species in the marsh should. Change it's actually California, Ridgeway Rail in the salt marsh harvest mouse need. High. Tide refugia. To. Survive and the. Model can help us to track where that high tide refugee and the marsh goes, over. Time with sea level rise it actually moves landward. And. This is something that we've been. Very, learning more about is is that as sea levels rise marshes. Will eventually, start to migrate man, word, up. To higher elevations. And. Conservationists. Are paying attention to the realize that we need to set side the land adjacent to marshes, as. Open. Space though we can allow that migration, to occur and allow marshes, to still persist, over time. So. Moving, back back, back, to the Central Valley I showed this a few minutes ago but. You know the Central Valley's been really. Greatly transformed. By a VOC conversion. Of the wetlands and the grasslands, to to. Agriculture. This. Is a really great book the, fall and rise of wetlands of California's, Great Central Valley, talks. About how you. Know, we lost, a lot of our wetlands there over 90% are lost by. Converting them to to, farming. But. The same time this region as well as the Bailey region is a really important stopover, in the Pacific. Flyway for, millions of shorebirds and waterfowl, including. Ducks and geese. They. Come through in the wintertime to forage, and rest and. As part of their migration.

And. What was really interesting is, that you know back end like so the early 1900's, the. Sacramento, Valley in the North especially got, converted, mainly to rice fields and almost all the wetlands were gone but. The ducks and the geese still came and, because. It didn't have any wetland habitats they ended up foraging, in the rice fields, and really. Having a large impact on on, the rice crop and really, upsetting the farmers, there, and. So because of that they, realized they had to restore the wetlands to divert. The ducks and the geese from their fields, back, to an area that where they wouldn't be impacting, them, as much so. Because of that in the 1930s, there was a real push. To create, a network of wildlife refuges, all across the Central Valley to restore. A while and, to have habitat, for these for, these birds so. Now, this is what the landscape looks like it's so it's a mostly, agricultural, land different, agricultural, crops. Are grown here. Rice. And corn are very common. Especially. In the north and then, we. Have you know, well. In sort of interspersed, the blue the blue here shows the wetlands. And. The wetlands are kind, of a mix of public wildlife. Refuges, and also private, lands there's a lot of duck clubs throughout. The valley that provide important, habitat for the migratory, birds. So. Again this is another close up of those sort. Of habitats, that the birds use in, the. In. The. In the Central Valley and. They're. Really highly managed so yeah, the croplands. The, croplands, and the wetlands are actually flooded up in the wintertime to provide. Aquatic. Habitat for the ducks and the geese when, they arrive, in. Their migratory path and we've. Been working with a group called Point blue conservation, science and have been tracking those flooding, up of, these wetlands, and croplands, using satellite, imagery Landsat, again and tracking. How that surface water habitat, is changing over time I. Might. Mention that the water that gets, used. To flood these wetlands and crop lands are all through, you. Know management, of our water resources and. Allocations. Of water to the refuges, and to the farms through the different state, and federal water projects that we have. So. I just, want to show this is a pretty cool animation, showing the change in our surface water across, the Central Valley this was done by my colleague Matt Ryder at Point blue conservation, science so you're gonna see this, is all managed this is all you, know done, by by, people and. That. In the summertime there's not a lot of water on the landscape, but as we move into the fall time they start to flood up the wetlands, and the crop lengths, and. You see a lot more area. Flooded, that's the blue and this is an interesting area to look at this is called the grasslands, ecological, area it's, down by low Spanos and so I want I'll talk a little bit more about that in a minute. So. I'm taking, the. Some information. About flooded, wetlands and crop lands and how important they are for for. Wildlife, we've. Been working with pointy blue on a large project. To. Take this remote sensing data and use it to forecast. Habitats. For, migratory, birds, and. And. The. Birds themselves and. Is. That to manage water use across the valley to support both the wildlife but also other beneficial, uses of the water like groundwater, recharge and. So we're doing both short term and long, term projections of, these habitats, and the species. Distributions. And they're helping to use it in a way to support. Coordinated. Conservation. For. Wildlife across the valley. So. To do our projections. And our forecasts, of habitats, we're using remote sensing data and. The. Same thing I just want to talk really briefly about a couple of different remote sensing datasets that we've been developing as part. Of as part of this project and, that, would be moist.

Soils Seed plant distributions. Their. Coverage, and their, yield or their. CDL their production. So. You might wonder what more, soil seed plants, are. So. Again these these managed wetlands, are flooded, in, the wintertime and then they're drained in the spring, intentionally. To grow a certain kind of plant these may also seed plants that are high in nutritional, quality. And they serve an important food resource, for the migratory, birds that are coming through. They're. Actually not native plants, but because of their high nutritional, value they're really prized as, you. Know a food resource for, the waterfowl, but. Across, the higher-value there really isn't a lot of information about how much is really ground but people really do need to know that information to, understand, how, many met, populations, of waterfowl that can support across the entire valley. So. What we did is mapped, all the managed wetlands in the Central Valley using. Again Landsat, satellite, data and we. Focused on mapping on, two main types of moist soil seed plants, the swamp Timothy, and the, water grass. And. We created. Maps across, a whole time series of ten years. And. Again I just want to emphasize it's, really interesting that the growth of these plants, are it's almost like it's like a source kind of a farming, where the. Managers. You know Dre draining, the land and then they they, plant seeds and they manage it and really, try to boost. Up their yields as much as possible so that it can provide the best quality habitat for, the Wildlife. So. In order to make their Maps we had it like I mentioned with with. The blue carbon stuff we had to go out in the field and collect a lot of data to build our models and in. 2007, teen I had a field team. Mostly. Austin. Lorenz and James Anderson who spend. The entire summer crossing the valley from. Northern, Sacramento Valley down, to the bottom of San Joaquin Valley collecting. Field data on plant, locations, and. There. Are biomass and their distributions. And. We. Were able to use this to build our models and just had to give them food because working out in the middle of July, and August in the Central Valley really, high. Temperatures, 113. Sometimes, we really had to be careful and manage your manage, your days well. So. Just to give you a little bit of information that about how they were able to do our mapping we. Use something called phenology. Meant, metrics, in order to tell these different species apart in. Our Maps and so phenology is, sort. Of the study of the pattern. Of growth over the course of the year of different. Things and. Our. Play offs had very different phonology. Patterns which, we could, use to tell them apart so the, water grass this is a map as is a figure showing, days. Of year from spring, to fall and, then this is sort of their growth. Their growth pattern, or their level, of greenness, that we see from the satellite and so in, water brass it starts off kind of slow and they get a peak greenness kind of around mid July. And. Then turn. Brown by about late August. Where. Swamp Timothy becomes really green and like, say early May and then, it becomes Browns really quickly like around. June. Or July so this is the kind of information that we can use to create, our maps and, and.

Do The so we end up with a pretty highly accurate map with the accuracies, of over, 8% which the remote sensing relatives actually, pretty. Good. And. Then, specifically. For swamp ginseng we were able to create a model of its productivity, and a seed yield and, we did that just using some linear. Regression, models and taking. Those vegetation, indices that we can pull from Landsat. In, order, to create, a model of the. Productivity, and then with those predictions then predict. Productivity. In different parts of the, region. And then create a map. So. Just to talk a little bit about what. We found I want to focus in on that graph on ecological area. Again in, Los Gatos in. San Joaquin Valley it, grows a lot of swamp Timothy it's actually a really important, wetland area in the Central Valley it. Encompasses about, a hundred and eighty thousand, acres. Of wetlands, and that. Makes that the largest block, of contiguous, wetland, habitat, remaining, in California. Even. More so than San Francisco Bay. So. Here's an example vegetation. Map that we were able to produce and, the bright, green area shows all the swamp Timothy, the, purple is emergent. Vegetation like. A, lot of bullrushes, cattails. And that sort of thing not a lot of water grass here. And. Then this map shows how, productive. That swamp Timothy is for. 2017. The. Lighter areas, are showing more highly productive areas. There's. A close-up of o of a wetland where. There's a higher production kind, of on the edges of the wetland pond on, the inside. So. Because we're able to do it a time-series analysis, and get maps going, back to 2007, which, encompassed. That really critical, drought period, of 2013. To 2016, we. Could understand, how water. Availability. Affected. Our capacity. To grow. This this type of vegetation that. Is used for supporting, our waterfowl and. What. We found was on those critical drought years. Which was the vertical lines here like like. 2014-2015. We. Had a lot more swamp Timothy growing in the valley as opposed to water, grass the, reason for that as swamp Timothy does not require summer. Irrigation. Water. Grass does and the managers. Of these wildlife refuges just were not receiving the water allocations, from the water, projects, that they typically, were and so they had to change their management practices. And, influence. What they were able to grow. Then. As you can imagine with less water they had less productivity, so they weren't able to produce as, high of a seen yield as as. In, the wetter years so. We, really want to look into this a little bit more to understand, how that affects, the, capacity, for the valley to support waterfowl, populations. During, these these, periods of drought. So. Going back and working with point bloom what, they were able to do was take these. These. Maps. We made of surface water and our meditation. And, it can put it into a model to, predict. The species distributions, of a number of different bird. Species here's showing examples of four, different duck species. And. They're sort of patterns of where, they're most likely to be found across the valley so. We have. Pintail. Green-winged. Teal, Shoveler. And mallard as an example. And. What. You might see here is the mallard is kind, of a generalist, it can be found all, over the place now kind of all distributed, across the valley, where. The pin, tail and the green winged teal are actually much more dependent. On those flood and habitats so have much smaller, ranges. And distributions. And. If. You look kind of a little bit further into the model you can understand. Why. That is. Certain, certain, variables. Are much, more important, in describing what some species are found versus, others and. Again. Things like. The. Pin tail and the green-winged teal were very, dependent. Upon, the, availability, of flooded wetlands, well, the, Mallards. Were not they could be found in many other different kinds of habitats and maybe you've observed that because mallards are actually pretty. Commonly, found throughout, our communities. So. Looking into the future what kind of satellite might we expect to see in the next ten. Years or so right. Now NASA. Is working on a new. Type, of satellite called a hyper hyper, spectral satellite, called, the surface biology, and geology designated. Observable, and, instead. Of having seven, bands or nine bands that might have like a hundred more, so it's taking, a snap shots at many other wavelengths. Along by the electromagnetic spectrum and so you have that much more detailed, information coming, in you can get a lot more information about the, features on the on the earth you can get information about biodiversity.

Species. Composition. Biochemistry. The nutrient, content of vegetation, much. More information about plant stress and canopy. Water content. Even. Even, mapping minerals. So. We're working with this kind of data and a new project that's just getting started, and this is a taking. Place really. Close to here in our neighborhood and the South Bay salt ponds region. So, you. Might know that we. Have a very large restoration. Project. Ongoing, in the South Face area. Here, 15,000. Acres which is a largest huddle well and restoration, project, in, the western US and, you. Hear a lot about the tidal marshes being restored but you might not know about the mud flaps the importance, of those habitats, the. Mudfest. That. Grow on. A present, just on the outskirts of the marshes. Really. Important again for foraging. For Shore bird habitat, and they. Have something, on them called biofilm. Which, is a sort, of a photosynthetic, gray. Substance, and, it's the kind of a mix of. Microbial. Bacteria, and. Diatoms, and protozoa, but. They're really important, in the diet, of shorebirds, so we're going to be using hyperspectral, data to. Be able to, quantify, the Spyro film and understand, this nutritional, equality to. See. How important, the mudflats are for the for, the shorebirds, so, that's a new project and hopefully. We'll have something to report on that and they in, the year or so. So. Just to end I really want to acknowledge all. Of my co-authors. And, collaborators. A lot, of these this work was done in partnership, with many people here the USGS, and in, other organizations. In. The bay and also. Want to acknowledge my, funding. Both. Through USGS, and NASA, and. That. I'll take some questions. Yeah. Recently. I've been reading or and hearing, that there's, a effort. To roll back. Some. Of the regulations. Governing. Wetlands. Particularly. The temporary, or vernal, ones here and. How. Does that affect this, or does it and, is. It, a major concern, if they do roll it back, I'm. Sorry, you're saying for them the, San Francisco Bay wetlands. I'm. Talking about the San Francisco Bay restoration or. Yeah. I'm not as familiar with some of those regulations on, sort. Of the seasonal, sort. Of you know ephemeral, wetlands, but around. Services obey because they're. Connected. To the navigable bodies of water I. Think they're still protected. Under the Clean, Water Act I so. I feel, I feel that there's just a lot of you probably seen you know many bonds being passed in San Francisco Bay to support. Wetland restoration I think there's a lot of momentum so. So, you mentioned. With. With. Rising. Sea water. How. We. Need to preserve, land. Beyond. Existing. Marshes. Are. There any maps showing. What. The estimated, land. Distance. Is - that needs to be preserved, -, so, that marshes can keep recreating yeah. Chum, is a little bit on the topography, about a upland. Land area so if it's a really really. Sort. Of flat, open. Space and would provide an opportunity for. Marshes. To migrate, further in because, just. Very small changes in elevation that, allow them to increase if it's a really steep. Upland. Area then they would kind of get stuck we wouldn't trap they wouldn't be able to do much but I haven't, actually seen they're, there maybe when they're you. Know a bay area wide map of those, areas I think it's I'm. Sure people are working on it but I haven't seen a final product oh. There. Are so many wastewater. Treatment plants, around the bay and they they. Discharge. How, does that affect, or are they trying to work that into. The. The map, here I don't know oh yeah, I am I haven't. I haven't really worked with that much, here, is at. All but I do know that like, in. Sacramento. They're upgrading their wastewater treatment plan that's gonna be changing, the kinds of or reducing, amount of nutrient inputs into. The Delta at least and so there's a lot of studies to see how that might change the ecosystem I don't know what the results are gonna be. Just. Curious about whether there, are also other, dimensions. You can look at in the inner light perhaps, the polarization, or, yeah. Yeah. So with radar polarization. Is actually a really important, tool so different there's different kinds, of ways. Of. Different. Kind of returns of polarized. Returns and that can be used to detect different kinds of features, so. Like. A vertical horizontal polarization. Would, be useful for looking at attracting.

Wetlands For example, and. Then specular. Versus, perhaps. More, scattered. Diffused. Lighted, it's something they can do also or. Yeah. Um in terms of the different surfaces and that. For. Example the surface, of water he's. More of a specular, oh yeah, well, actually in terms of that that becomes, actually more of a problem than I've been evaluate, but they try to take images of the water at certain times of danger to remove that glint and that and to be able to actually. Detect the features, in the water they really want to get at like like, say chlorophyll, or suspended, sediment. So. It looked like you had in. The future coming up the Landsat, nine I think yeah, and it'll that'll. Give you about higher resolution, I. Think. They're working on it. Are. You implying that Landsat, 8 is already dead. Thank. You. And then one. Of your slides it looked like I work at NASA and, when this life looked like you had one of our year twos are. You doing imaging from. Yeah. Back, in in. The Russian ranch project we did use some well we actually use Everest, air to try. It out for for biomass mapping and we had some prism data I don't know if that was fun with the r2 or not but, yeah. We used that we had another model of the suspended-sediment based on the prison gave that to you okay yeah cuz we have like er tears down an Armstrong, I thought maybe you might use them for higher resolution. Yeah. This. Is obviously. An enormous amount of data and. We. Don't collect, data just for the sake of data, so. I, would ask what in the last, ten, years or, whatever have been real-world, policy. Changes, as, a, result of this what what are the biggest. Wins. In, a. Successful. Change of policy, that you've seen as a result of the data collection effort. It's. A good question I think that's something that you SJS we are constantly, striving, towards, is to make, research. Relevant. And I think, a couple of examples that I have here, is with. The coastal well in blue carbon maps we're able to, improve. Our ability to do. Greenhouse gas accounting, or coastal wetlands on the national, level so that gets recorded directly into, our national, greenhouse gas accounting, and what gets reported to the UN you know it's a small amount it's small increase but I think that increasing. Our ability to quantify these things on any level is oh. That's. Better, accounting, but where's the, policy. Change. Differently. As a result of better accounting. I'm. Not seeing here is how, this culminates, in, difference. In policy yes yeah. So in terms of them I think on the ground policy. Coastal. Well and blue carbon accounting is being. Used to incentivize. Restoration. Because there are some new. Voluntary. Carbon markets, that are available so that people can actually get paid to do well in a restoration, as a result of improved accounting, and so if, they can get paid into the rest room that's more incentive, and so hopefully, more restoration, occurs and becomes more feasible then, we have all the improved benefits that. We get out of wetlands, for people, and wildlife and. Then the other example is to work we've been doing in the Central Valley it's.

An It's a new project we're really been working with a lot of managers across the valley to talk about applications. There's a lot of interest but it looks like a. Couple, of different things on, a valley, wide scale we can use it to run bioenergetics. Models and understand. What kind of populations, of waterfowl can be supported, across. The valley and how that might train change in a drought year which, might incentivize, managers. To. Hopefully. You know find. Ways to increase yield so they can support wildlife and then, also on sort of a smaller, refuge, basis, on a wetland scale basis, understanding. The variability and productivity across time and seeing which balance maybe, not, performing. As well as others because, they you, know a lot a lot of our. Refuges, don't. Have large, amounts of staff and it's very difficult to monitor. And track things on a very detailed level and so, the remote sensing data can help them to do that and then to be able to focus, their efforts on like do I need to, you. Know restore this particular wetland, here to increase my to, my yield so kind of that targeted, assistance, with management, is kind of what we're aiming for. Anything. Else oh. And. One more I think. First. Of all I want to continue I want to commend you for an excellent presentation thank, you very much this. Is a little to the side but I'm curious I was. In the satellite, missile business my career and, I'm curious is what contractors, making, this new satellite for you and is it the same one that made the previous ones oh I. Don't think that that is been worked out yet I think they're just trying to the room the very beginning stages to talking about the new hyperspectral, they're, really working, on figuring out the requirements. And there's a lot of working groups right now to figure out you know what, do we need when do we need how much you, know repeat intervals, or resolutions. That, kind of thing so any. Particular contractor, working with you on developing, the criteria, oh I don't know I wouldn't be involved with that so thank. You. Anything. Else okay. Well thanks very much.

2019-05-04 02:36

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