WEBVTT
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Everyone to our National Marine Sanctuaries
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Webinar Series.
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We're so pleased to have you all joining us today
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for our special presentation on Seagrass Wasting syndrome.
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So I wanted to kick off by letting you all know
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that as attendees, you'll be joining us in listen only mode.
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If you have any questions,
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you can type them into the GoToWebinar question box,
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and we'll get to those either through a typed response
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or during our Q&A section.
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If you have any audio or visual trouble,
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please go ahead and also type that into the question box
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and we will do our best to try to help you
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navigate some of those AV issues.
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So with that, let's go ahead and get started.
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Today, myself and Brian Chansky will be hosts.
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I'm Claire Fackler. I go by she/her pronouns.
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I'm the National Education Liaison of the NOAA Office
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of National Marine Sanctuaries,
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and I'm joined by Brian,
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who is a virtual student federal service e-intern
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who's a undergraduate at the University of Delaware.
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So we welcome all of you.
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As usual, we'd like to do just a few intro slides
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to kind of set the stage
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of where this science and research is taking place.
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So this you're looking at
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is the National Marine Sanctuary System.
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You can think of it like the National Park System,
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but these are basically underwater parks.
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So each of these white dots on the map represent
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one of our national marine sanctuaries
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or special ocean or Great Lakes treasures.
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We have some triangles in the South Pacific
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and the northwestern Hawaiian islands
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that are also underwater parks.
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They're just called marine national monuments.
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So different terminology, but basically the same thing.
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And then we've got these yellow boxes.
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That's really exciting
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because during President Biden's
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America the Beautiful initiative which aligns
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with the global 30 by 30 is an effort to expand public lands
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and public waters by 30% by the year 2030.
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So a big time of expansion globally
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as well as in the United States in the sanctuary system.
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So all said, right now,
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NOAA manages about 620,000 square miles
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of ocean and Great Lakes treasures
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that we're protecting now and for the future.
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And these treasures are set aside
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for a wide variety of reasons, often by Congress,
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but through a stakeholder-driven process.
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In some cases, our marine sanctuaries
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and marine national monuments are set aside
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because of the incredible biodiversity.
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In other cases, it's because of the shipwrecks
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or cultural or maritime heritage.
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But all in all, these sites help provide shelter
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for threatened and endangered marine life,
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like this Hawaiian Green Sea turtle.
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So Congress actually mandates NOAA
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and the Office of National Marine Sanctuaries
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to conduct education and outreach.
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We're mandated to do research and monitoring,
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and all of this with the intent of protecting the resource,
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so protecting the habitat, the ecosystem.
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And I've already mentioned national parks.
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So you know that those land-based parks
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that are in the National Park system are special areas.
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So these are the special ocean and Great Lakes places.
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And just like a national park,
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we want you to get into it and explore and enjoy
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and fall in love with these special ocean areas
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and Great Lakes places.
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So there's so many different activities that you can do
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in your special sanctuaries and monuments.
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You can kayak.
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In some cases, you can fish, you can snorkel,
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scuba dive, surf,
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get on a boat, view marine life.
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Oftentimes, when people get to interact
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with these special ocean treasures,
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they get so inspired
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that they actually become volunteers for us.
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So with that, I will let Brian introduce our presenter
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who's going to be zooming in
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to our Greater Farallones National Marine sanctuary
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talking about seagrass.
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Thank you, Claire.
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All right, Serina Moheed is a second year PhD student
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at the University of California, Davis
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studying seagrass wasting disease
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in Northern California estuaries.
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As a NOAA, Nancy Foster scholar, she partners
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with the Greater Farallones National Marine Sanctuary
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to identify seagrass populations vulnerable to the disease
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and thinks about how to encourage resilience in these areas.
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Serina, take it away.
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And Serena while...
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Oh good. I was gonna say we wanna see you and there you are.
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So we're gonna pop off, Brian,
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and we'll let Serina take the center stage here.
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All right, perfect. Let's see.
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Sorry, just getting everything set up.
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Looks great.
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Oh, looks good? Okay, awesome.
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So you can see my screen okay, then?
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Yes, we can.
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All right, perfect. All right.
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Hello, everyone.
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Thank you, Brian and Claire, for the wonderful introduction,
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and thank you all for joining me today.
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So I'm gonna be talking about how plants get sick too,
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and monitoring seagrass wasting disease
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in a changing climate.
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So I first just want to run through a little bit more
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of an introduction.
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So again, hello, I'm Serina.
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I'm a second year PhD student
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at the University of California, Davis,
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and I study seagrass wasting disease.
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I'm also honored to be
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a Dr. Nancy Foster scholar and partner
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with the Greater Farallones National Marine Sanctuary
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to help protect our seagrass beds.
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And I'm super excited to talk with you today
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about marine diseases.
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So just to go through a brief outline
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of what we're gonna be talking about today,
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I'm gonna introduce you guys to what our marine disease is,
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what causes them,
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how can these be displayed in different organisms.
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And then kind of zooming into my study species.
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So what are seagrasses and why are they important?
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And then also then talking about seagrass wasting disease.
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So what is it and how do I study it
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and how am I using it for my PhD?
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So in the last couple of years,
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you might have seen some headlines
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that look a bit like this.
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And so marine diseases are caused by pathogens in the ocean
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that infect marine organisms,
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and it's actually much more common than you might think.
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And so they can affect coral reefs, starfish, oysters,
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and even larger marine mammals like sea otters.
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And so disease outbreaks can occur suddenly
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and without warning and infect many individuals
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in a short amount of time.
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And because there's often more than one cause
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for why a disease outbreak occurs,
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scientists are still kind of unraveling
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the who, what, where, when, and why
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around a lot of these diseases.
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And marine diseases can take on many forms
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and have different visual symptoms,
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much like terrestrial diseases.
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So some organisms can show lesions or tissue loss
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such as with stony coral tissue disease
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and sea star wasting disease,
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which you might've heard of.
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And this is actually where sea star limbs
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will detach from their body.
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But there also might be more kind of internal symptoms
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such as muscle loss with oysters herpesvirus,
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and brain inflammation with sea otter toxoplasmosis.
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So you can see that there's a range of symptoms
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that can occur with marine diseases.
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And so it's really important that we know what these are
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and what to look out for.
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And to help us tease apart why disease outbreaks occur,
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disease ecology uses a conceptual diagram
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called the disease triangle,
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and that's really meant to show the three main players
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necessary for any infectious disease to spread.
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And this also applies to terrestrial diseases.
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So we can use COVID as an example
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that we are all familiar with.
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So at the start of the COVID pandemic, we had our pathogen,
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the coronavirus.
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We also had hosts that were susceptible to this pathogen.
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And then we had an environment where people
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were interacting with each other
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to spread the pathogen around.
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And all these together created a disease pandemic.
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And to protect, especially vulnerable populations,
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scientists and doctors were recommending
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that people socially distance to try to stop the spread
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between hosts in a time where no one was resistant
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to this disease.
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And then at the same time,
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the pathogen itself was also evolving,
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but some of these new strains couldn't infect as many people
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because as a population,
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we had developed immunity through either vaccination
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or naturally recovering from the disease.
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But if your pathogen is in the water,
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how do you implement social distancing
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when your organism can't move
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and it's constantly exposed to this infectious environment?
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How do you figure out if the pathogen is evolving
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and whether host populations are resistant to it?
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So these are the kinds of questions
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that marine disease ecologists encounter
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when faced with an epidemic.
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And similarly, the same types of questions
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that I'm thinking about with my research on seagrasses.
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So just to start us off,
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I want to ask a little bit of poll question.
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So I wanna know how many of you guys know
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what seagrasses are?
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All right, everyone,
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the poll question has been launched,
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so go ahead and put in your response.
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And we are clicking up the votes here.
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This is a good way to assess the knowledge of our audience.
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All right, we're inching to 80% of you voting,
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so voting's important.
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Couple more seconds.
(Serina chuckles)
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All right, go ahead and share our results.
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So 95% of our audience know what seagrass is.
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We've got a very knowledgeable audience here with us.
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(Serina chuckles)
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All right. That's amazing.
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Okay, are you guys still seeing my screen
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or do I need to share it again?
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No, we are. You're back on.
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Oh, perfect. Okay.
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So that's really awesome.
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I was not expecting that,
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but it also makes me so happy that so many of you know
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what seagrasses are.
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So some of this might be reviewed for you guys,
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but hopefully you do end up learning something
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from this presentation.
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So a little bit of background on the folks
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that are not as familiar with seagrasses.
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So seagrasses are marine flowering plants
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that grow in salty and brackish waters.
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So this is water usually found in estuaries
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where salt water is mixing with fresh water,
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and they usually grow pretty shallow,
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so around one to three meters deep.
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But of course they have been found a lot deeper
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and there are plenty of deeper seagrass beds.
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And there was a recent assessment that concluded
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if you gather all the seagrass in the world,
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it will cover an area of about 160,000 kilometers squared,
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which to put that in context is about the size
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of the state of Georgia.
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However, seagrass is mapped very poorly.
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And so some people estimate that the current number
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actually might be three times this size,
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which would be about the size of France.
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And so the picture in the middle is a diagram showing you
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what seagrass plant would look like.
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And so like tree glasses, they have blades and leaves.
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And unlike seaweeds,
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they have this kind of root and rhizome system
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that connects them to other plants underneath the ground.
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And they reproduce asexually by producing clones.
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So you can think that if you're trying to propagate a plant,
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you take a cutting and then that'll grow
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into a whole new plant by itself.
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And then they also produce sexually via pollination
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and producing seeds.
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00:13:43.470 --> 00:13:46.110
So the flower in that diagram actually looks
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00:13:46.110 --> 00:13:49.770
a lot more like the picture to the far right there.
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00:13:49.770 --> 00:13:53.520
So that is a flowering blade of seagrass.
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00:13:53.520 --> 00:13:56.760
And those oblong shapes are actually fertilized seeds
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00:13:56.760 --> 00:14:01.590
that are ready to drop off and grow new seagrass plants.
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00:14:01.590 --> 00:14:03.030
And so in this way,
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seagrasses can form kind of dense patches
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that will eventually grow to entire meadows
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that can sometimes be miles or kilometers long.
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And so where are seagrasses found?
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So they are found globally and are probably more common
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than you might imagine.
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And so this world map is showing
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where seagrasses are present.
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00:14:23.820 --> 00:14:26.400
And so the darker colors are representing
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places with highest seagrass abundance.
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00:14:30.360 --> 00:14:33.450
And you can see that essentially all the continents
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except for Antarctica have seagrass as present
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in some capacity on their coasts.
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00:14:38.460 --> 00:14:40.620
And the darker colors here also correspond
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00:14:40.620 --> 00:14:45.020
with areas where there are multiple species
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00:14:45.020 --> 00:14:46.473
of seagrasses present.
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00:14:47.340 --> 00:14:49.620
And so seagrasses can kinda be thought of
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as the grasslands of the sea.
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00:14:51.780 --> 00:14:53.520
They might not be that important,
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but they do harbor an incredible amount of biodiversity.
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00:14:57.030 --> 00:15:00.930
And I did have some videos queued up to share with you guys,
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but unfortunately technology was not on our side today.
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And so instead, I am just gonna tell you that
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you can have a range of organisms in seagrass beds
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00:15:11.730 --> 00:15:14.070
from really tiny to really large.
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00:15:14.070 --> 00:15:15.810
And so you can get surfperch
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00:15:15.810 --> 00:15:17.340
that are eating the tiny invertebrates
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00:15:17.340 --> 00:15:19.620
that live along the seagrass.
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00:15:19.620 --> 00:15:22.080
You could have ducks that actually feed
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00:15:22.080 --> 00:15:24.000
on the seagrass itself.
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00:15:24.000 --> 00:15:26.760
And you can also have larger organisms
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00:15:26.760 --> 00:15:29.643
such as leopard sharks and harbor seals.
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00:15:31.560 --> 00:15:35.280
And so there's a number of organisms
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00:15:35.280 --> 00:15:37.770
that actually use the seagrass habitat
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00:15:37.770 --> 00:15:41.133
or use the seagrass as habitat and then also for food.
308
00:15:43.110 --> 00:15:45.980
So that brings us to why are seagrasses important.
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00:15:45.980 --> 00:15:47.130
So we just kind of covered
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that they can be a foundational ecosystem
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00:15:50.070 --> 00:15:54.180
that's home to many different species, both large and small.
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00:15:54.180 --> 00:15:57.510
And given that meadows are often found in shallower water,
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they can actually decrease wave energy
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00:15:59.700 --> 00:16:01.893
and protect coastlines from storms.
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00:16:03.480 --> 00:16:06.060
They can also store carbon from the atmosphere
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00:16:06.060 --> 00:16:07.080
into their sediment.
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00:16:07.080 --> 00:16:08.820
And so we actually refer to these systems
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00:16:08.820 --> 00:16:10.950
as blue carbon systems,
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00:16:10.950 --> 00:16:13.260
and possibly more importantly,
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00:16:13.260 --> 00:16:15.120
they produce the oxygen that we breathe.
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00:16:15.120 --> 00:16:18.630
And so it's estimated that one square meter of seagrass
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00:16:18.630 --> 00:16:21.933
can actually produce up to 10 liters of oxygen a day.
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00:16:23.820 --> 00:16:27.240
And many fish species and invertebrate species
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00:16:27.240 --> 00:16:29.670
use seagrass meadows as nursery habitats
325
00:16:29.670 --> 00:16:31.050
to raise their young.
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00:16:31.050 --> 00:16:35.010
So seagrasses are really important as a driver
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00:16:35.010 --> 00:16:37.863
for the next generation of organisms as well.
328
00:16:41.310 --> 00:16:43.770
So unfortunately, like many marine organisms,
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00:16:43.770 --> 00:16:47.403
seagrasses are under threat due to a number of reasons.
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00:16:48.300 --> 00:16:50.460
First one is rising ocean temperatures
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00:16:50.460 --> 00:16:52.230
can cause stress for the seagrass,
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00:16:52.230 --> 00:16:53.730
which is bad for their health.
333
00:16:54.720 --> 00:16:56.610
There's also human made pollution.
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00:16:56.610 --> 00:16:59.130
And so agricultural runoff into these areas
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00:16:59.130 --> 00:17:02.250
can cause algal blooms that decreases the light
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00:17:02.250 --> 00:17:05.163
that's available to get down to the seagrass plants.
337
00:17:07.170 --> 00:17:12.170
Also, maritime activities can cause the physical removal
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00:17:12.540 --> 00:17:13.890
of seagrass plants as well.
339
00:17:13.890 --> 00:17:17.790
So a big one is when boats are going through seagrass beds,
340
00:17:17.790 --> 00:17:19.770
their propellers can catch on the plants
341
00:17:19.770 --> 00:17:21.780
and actually rip them up from the roots
342
00:17:21.780 --> 00:17:23.610
and cause these scars that you're seeing
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00:17:23.610 --> 00:17:25.680
in this bottom picture here.
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00:17:25.680 --> 00:17:28.200
And also dredging is another activity
345
00:17:28.200 --> 00:17:30.333
that's physically removing these plants.
346
00:17:32.160 --> 00:17:34.710
And then there's also disease,
347
00:17:34.710 --> 00:17:37.263
which I will get into in the next slide.
348
00:17:39.960 --> 00:17:42.480
So I'm really interested in studying seagrasses
349
00:17:42.480 --> 00:17:47.220
as a system that is affected by a seagrass wasting disease.
350
00:17:47.220 --> 00:17:49.080
And so we can go back to our disease triangle
351
00:17:49.080 --> 00:17:50.250
we were talking about earlier
352
00:17:50.250 --> 00:17:52.590
and just try to fill in the different points
353
00:17:52.590 --> 00:17:56.100
with the key players in this particular system.
354
00:17:56.100 --> 00:17:57.540
And so we have our environment,
355
00:17:57.540 --> 00:18:00.030
so it's a waterborne pathogen.
356
00:18:00.030 --> 00:18:01.920
The seagrasses live in water,
357
00:18:01.920 --> 00:18:04.240
and we know that the pathogen itself
358
00:18:05.610 --> 00:18:06.870
is also transmitted
359
00:18:06.870 --> 00:18:09.723
with blade-to-blade contact between plants.
360
00:18:11.070 --> 00:18:14.793
We have our hosts, the temperate seagrass, Zostera marina,
361
00:18:16.380 --> 00:18:18.000
and then we also have our pathogen,
362
00:18:18.000 --> 00:18:22.354
the slime mold protist, Labyrinthula zosterae.
363
00:18:22.354 --> 00:18:24.904
And so like other diseases that we've talked about,
364
00:18:26.070 --> 00:18:29.310
there are visual symptoms of this disease as well.
365
00:18:29.310 --> 00:18:32.430
And so you can see on the picture to the left,
366
00:18:32.430 --> 00:18:36.300
the pathogen actually causes these dark necrotic lesions
367
00:18:36.300 --> 00:18:38.880
on an otherwise green seagrass tissue.
368
00:18:38.880 --> 00:18:42.640
And the pathogen destroys the cell walls of the plant
369
00:18:43.680 --> 00:18:45.927
and gets rid of the chloroplast.
370
00:18:45.927 --> 00:18:48.270
And so it makes it unable for the plant
371
00:18:48.270 --> 00:18:51.630
to conduct efficient photosynthesis.
372
00:18:51.630 --> 00:18:54.210
And over time these lesions can grow
373
00:18:54.210 --> 00:18:56.643
and the plant can eventually die from this.
374
00:18:58.080 --> 00:19:01.050
And so I'm really interested in asking questions
375
00:19:01.050 --> 00:19:03.450
about the pathogen in this disease triangle.
376
00:19:03.450 --> 00:19:07.620
So when I'm looking at my different sites,
377
00:19:07.620 --> 00:19:11.520
how many strains of the pathogen are out there?
378
00:19:11.520 --> 00:19:14.130
Are there areas in the estuary with little disease
379
00:19:14.130 --> 00:19:16.320
versus areas with a lot of disease?
380
00:19:16.320 --> 00:19:19.860
And does this disease intensity vary seasonally?
381
00:19:19.860 --> 00:19:22.290
And so I really want to bring all these questions
382
00:19:22.290 --> 00:19:25.020
back to how can I protect vulnerable populations
383
00:19:25.020 --> 00:19:27.033
of seagrass from this disease?
384
00:19:29.516 --> 00:19:30.780
So to give you a bit more context
385
00:19:30.780 --> 00:19:33.120
of where I'm conducting this research,
386
00:19:33.120 --> 00:19:36.390
I work in two Northern California estuaries,
387
00:19:36.390 --> 00:19:38.220
Bodega Bay and Tomales Bay.
388
00:19:38.220 --> 00:19:40.860
So these are about an hour and a half north
389
00:19:40.860 --> 00:19:42.840
of San Francisco.
390
00:19:42.840 --> 00:19:46.590
And we have years in environmental data at these sites,
391
00:19:46.590 --> 00:19:48.450
and we know that they have seagrass beds
392
00:19:48.450 --> 00:19:53.160
that have been persistent despite changing ocean conditions
393
00:19:53.160 --> 00:19:54.783
in the last decade.
394
00:19:55.860 --> 00:19:59.160
And the interesting thing about Tomales Bay in particular
395
00:19:59.160 --> 00:20:01.620
is that it actually develops a temperature gradient
396
00:20:01.620 --> 00:20:02.453
during the summer.
397
00:20:02.453 --> 00:20:03.780
So these different colors
398
00:20:03.780 --> 00:20:06.303
are showing you different sea surface temperature.
399
00:20:08.010 --> 00:20:11.100
And you can see that that purple blue color
400
00:20:11.100 --> 00:20:12.780
near the map of the estuary,
401
00:20:12.780 --> 00:20:15.150
where it gets input from the ocean,
402
00:20:15.150 --> 00:20:16.890
is a much cooler temperature
403
00:20:16.890 --> 00:20:21.693
than near the head of the estuary in that red orange area.
404
00:20:22.920 --> 00:20:27.300
And so we actually have sites that we keep going back to
405
00:20:27.300 --> 00:20:29.580
to monitor at these yellow stars
406
00:20:29.580 --> 00:20:32.130
that are across this temperature gradient.
407
00:20:32.130 --> 00:20:35.520
And so that really gives us a natural lab to work from
408
00:20:35.520 --> 00:20:38.613
as we try to see what the disease is doing over time.
409
00:20:40.770 --> 00:20:42.930
So how do we actually go about doing this?
410
00:20:42.930 --> 00:20:47.190
So the sites we go to are intertidal seagrass meadows.
411
00:20:47.190 --> 00:20:49.320
So that means that during low tide
412
00:20:49.320 --> 00:20:51.870
they are generally uncovered by water,
413
00:20:51.870 --> 00:20:53.670
much more easily accessible
414
00:20:53.670 --> 00:20:57.783
and easier to count the seagrass as well.
415
00:20:58.680 --> 00:21:01.470
However, the seagrass at our sites also grows in mud flats,
416
00:21:01.470 --> 00:21:04.170
which means that you get a very decent workout
417
00:21:04.170 --> 00:21:05.790
tromping through the mud,
418
00:21:05.790 --> 00:21:09.120
and some sites are easier to get to than others.
419
00:21:09.120 --> 00:21:12.907
We're actually thinking about making a T-shirt being like,
420
00:21:12.907 --> 00:21:15.720
"Oh, you survived (chuckles) the mud,"
421
00:21:15.720 --> 00:21:17.793
because it can get quite messy.
422
00:21:19.920 --> 00:21:22.440
So sometimes, you know, even our scientific tools
423
00:21:22.440 --> 00:21:23.730
can become our crutch
424
00:21:23.730 --> 00:21:25.350
when we are trying to get out of the mud,
425
00:21:25.350 --> 00:21:27.900
as you can see from these two pictures here
426
00:21:27.900 --> 00:21:30.363
of me at one of our bodega sites.
427
00:21:33.660 --> 00:21:35.490
And so I'm gonna describe the field like we do
428
00:21:35.490 --> 00:21:38.730
to determine current disease levels out in the field,
429
00:21:38.730 --> 00:21:42.390
and then talk about some of the lab work I'm pairing it with
430
00:21:42.390 --> 00:21:46.410
to learn more about what pathogen is present out there.
431
00:21:46.410 --> 00:21:49.410
So here's a picture of me holding all the gear I use
432
00:21:49.410 --> 00:21:51.180
for my disease surveys.
433
00:21:51.180 --> 00:21:53.220
So we have our transect tapes,
434
00:21:53.220 --> 00:21:55.470
which are essentially giant tape measures we use
435
00:21:55.470 --> 00:21:58.200
to make sure that we're collecting along a straight line
436
00:21:58.200 --> 00:21:59.403
of a certain length.
437
00:22:00.540 --> 00:22:01.800
I'm holding some poles
438
00:22:01.800 --> 00:22:04.500
to anchor those transects into the mud.
439
00:22:04.500 --> 00:22:07.170
Datasheets, of course, to write down our observations
440
00:22:07.170 --> 00:22:08.523
and our measurements.
441
00:22:10.380 --> 00:22:15.060
A quadrat, which is essentially just a square of PVC pipes
442
00:22:15.060 --> 00:22:16.800
that is a standard area.
443
00:22:16.800 --> 00:22:19.170
And so I use that to look at how much seagrass
444
00:22:19.170 --> 00:22:20.673
is out there at my sites.
445
00:22:22.080 --> 00:22:25.650
Collection baggies to bring back samples to the lab.
446
00:22:25.650 --> 00:22:27.990
A GPS to make sure I know where I'm going
447
00:22:27.990 --> 00:22:30.873
and I'm going to the same place every time.
448
00:22:32.143 --> 00:22:33.720
And waders, which despite being
449
00:22:33.720 --> 00:22:35.970
an obvious fashion statement,
450
00:22:35.970 --> 00:22:38.190
are also just these insulated overalls
451
00:22:38.190 --> 00:22:43.050
that help me keep my clothes dry and not muddy,
452
00:22:43.050 --> 00:22:46.773
and then also help me tromp through the mud a bit better.
453
00:22:50.010 --> 00:22:53.700
And so I conduct seasonal sampling at the same six sites,
454
00:22:53.700 --> 00:22:56.223
so three in Bodega Bay, three in Tomales Bay,
455
00:22:57.600 --> 00:23:00.030
to get a sense of how disease is changing
456
00:23:00.030 --> 00:23:01.650
over the span of a year.
457
00:23:01.650 --> 00:23:03.540
So on the picture to the left,
458
00:23:03.540 --> 00:23:08.100
you can see me rolling out that transect on a seagrass bed
459
00:23:08.100 --> 00:23:10.080
at one of our bodega sites.
460
00:23:10.080 --> 00:23:13.050
And the picture to the right is an example of what I observe
461
00:23:13.050 --> 00:23:15.270
when I'm looking at the abundance of seagrass
462
00:23:15.270 --> 00:23:16.650
along my transect.
463
00:23:16.650 --> 00:23:19.560
And so I would actually count all the seagrass chutes
464
00:23:19.560 --> 00:23:21.420
that are within that white square
465
00:23:21.420 --> 00:23:24.300
and then estimate how much of that square is seagrass
466
00:23:24.300 --> 00:23:25.140
versus bare mud.
467
00:23:25.140 --> 00:23:29.970
So I would estimate that this is about maybe 20% seagrass.
468
00:23:29.970 --> 00:23:31.320
And I just wanna emphasize
469
00:23:31.320 --> 00:23:33.090
this is really giving us a snapshot
470
00:23:33.090 --> 00:23:34.980
of the current disease load
471
00:23:34.980 --> 00:23:37.230
in seagrass abundance at that time.
472
00:23:37.230 --> 00:23:39.030
But given enough time points,
473
00:23:39.030 --> 00:23:41.580
we would hopefully be able to paint a more clear picture
474
00:23:41.580 --> 00:23:43.980
of what's happening throughout the year as well.
475
00:23:48.630 --> 00:23:50.280
And so just to give you a sense
476
00:23:50.280 --> 00:23:53.010
of kinda what we're collecting and how we're using it,
477
00:23:53.010 --> 00:23:56.790
we take blades from the seagrass plants,
478
00:23:56.790 --> 00:24:00.150
bring them back to lab, wash them off, measure them,
479
00:24:00.150 --> 00:24:02.460
and then we scan them on sheet transparencies
480
00:24:02.460 --> 00:24:04.590
to document how severe the disease is.
481
00:24:04.590 --> 00:24:08.220
So these two pictures are an example
482
00:24:08.220 --> 00:24:11.310
of those sheet transparencies,
483
00:24:11.310 --> 00:24:13.380
and they're actually from the same time point,
484
00:24:13.380 --> 00:24:14.880
but two different sites.
485
00:24:14.880 --> 00:24:17.310
So you can see the picture on the left.
486
00:24:17.310 --> 00:24:18.660
The seagrass seems really healthy.
487
00:24:18.660 --> 00:24:20.310
It's a vibrant green color.
488
00:24:20.310 --> 00:24:22.920
There are not many lesions on there.
489
00:24:22.920 --> 00:24:25.470
If they are, they're like really small.
490
00:24:25.470 --> 00:24:27.450
However, at the site on the right,
491
00:24:27.450 --> 00:24:30.840
there's these like darker patches of lesions
492
00:24:30.840 --> 00:24:34.380
and it's much more obvious that these are disease plants.
493
00:24:34.380 --> 00:24:36.240
And so this kinda just goes to show
494
00:24:36.240 --> 00:24:39.720
that even at the same point in time,
495
00:24:39.720 --> 00:24:42.180
there are different disease dynamics that are happening
496
00:24:42.180 --> 00:24:44.160
at these different sites.
497
00:24:44.160 --> 00:24:47.070
And we've seen from past disease surveys
498
00:24:47.070 --> 00:24:50.340
that there can also be a lot of variation within sites
499
00:24:50.340 --> 00:24:52.920
in terms of where disease is peaking
500
00:24:52.920 --> 00:24:55.440
during the year, across years.
501
00:24:55.440 --> 00:24:58.740
So the peak of disease might not stay the same
502
00:24:58.740 --> 00:25:01.230
and being necessarily predictable.
503
00:25:01.230 --> 00:25:03.573
And then to analyze this data,
504
00:25:04.560 --> 00:25:06.780
we have collaborators up in Friday Harbor
505
00:25:06.780 --> 00:25:08.550
that utilize an AI technology
506
00:25:08.550 --> 00:25:11.400
to measure the surface area of lesion tissue
507
00:25:11.400 --> 00:25:13.920
versus the surface area of healthy tissue on a blade.
508
00:25:13.920 --> 00:25:16.890
And that can give us a metric of disease severity
509
00:25:16.890 --> 00:25:21.003
that we can then quantify and do statistical tests on.
510
00:25:22.680 --> 00:25:24.600
And so amazing, we have data.
511
00:25:24.600 --> 00:25:27.630
Well, now what? What does this actually tell us?
512
00:25:27.630 --> 00:25:29.700
So it can actually inform us
513
00:25:29.700 --> 00:25:34.563
on what seagrass populations are most vulnerable to disease.
514
00:25:35.400 --> 00:25:36.233
And so you might be asking
515
00:25:36.233 --> 00:25:38.400
what makes a population vulnerable?
516
00:25:38.400 --> 00:25:40.440
And so I know I've definitely experienced this,
517
00:25:40.440 --> 00:25:41.640
and probably some of you too,
518
00:25:41.640 --> 00:25:44.580
where you've had a really crazy week, really hectic,
519
00:25:44.580 --> 00:25:47.700
just running around everywhere, feeling a little rundown,
520
00:25:47.700 --> 00:25:50.760
and it might be easier for you to catch a cold.
521
00:25:50.760 --> 00:25:52.920
And so the same thing actually happens with seagrasses
522
00:25:52.920 --> 00:25:55.710
where if seagrasses are under stress
523
00:25:55.710 --> 00:25:57.870
from either warming temperatures or pollution,
524
00:25:57.870 --> 00:26:01.020
then they're much more susceptible to diseases.
525
00:26:01.020 --> 00:26:01.890
On the flip side,
526
00:26:01.890 --> 00:26:04.080
there also might be populations of seagrasses
527
00:26:04.080 --> 00:26:06.270
that have low levels of disease
528
00:26:06.270 --> 00:26:08.670
and have experienced that for a very long time.
529
00:26:08.670 --> 00:26:10.560
So they've kinda become a little more built up
530
00:26:10.560 --> 00:26:13.170
and resistant to that disease,
531
00:26:13.170 --> 00:26:16.470
and it means that those seagrass beds are more resilient.
532
00:26:16.470 --> 00:26:19.020
So it's really important to identify those as well.
533
00:26:20.310 --> 00:26:22.770
And so the second part of my experiment
534
00:26:22.770 --> 00:26:24.660
is actually delving into the idea
535
00:26:24.660 --> 00:26:26.670
that the pathogen is gonna vary at these sites.
536
00:26:26.670 --> 00:26:28.890
So knowing that disease outbreaks
537
00:26:28.890 --> 00:26:30.510
are going to keep recurring,
538
00:26:30.510 --> 00:26:33.300
how can we manage them better when they do?
539
00:26:33.300 --> 00:26:35.070
And so while we can't vaccinate
540
00:26:35.070 --> 00:26:37.170
every single seagrass plant out there,
541
00:26:37.170 --> 00:26:39.360
there is a distinct lack of information
542
00:26:39.360 --> 00:26:40.980
about the pathogen's ability
543
00:26:40.980 --> 00:26:43.680
to infect different populations.
544
00:26:43.680 --> 00:26:46.440
And so I'm trying to fill this gap in with my lab work,
545
00:26:46.440 --> 00:26:47.823
which I'll talk about next.
546
00:26:51.210 --> 00:26:53.520
All right, so in order to learn more about
547
00:26:53.520 --> 00:26:56.910
if there are differences in the pathogen at my site,
548
00:26:56.910 --> 00:26:58.260
I'm gonna try to culture them
549
00:26:58.260 --> 00:27:00.660
in a controlled environment in lab.
550
00:27:00.660 --> 00:27:03.210
And I like to liken this to taking care of a houseplant.
551
00:27:03.210 --> 00:27:04.230
Like, in many ways,
552
00:27:04.230 --> 00:27:06.660
you know, like a houseplant needs resources
553
00:27:06.660 --> 00:27:09.150
like soil, water, sunlight,
554
00:27:09.150 --> 00:27:12.360
and sometimes even temperature is really important.
555
00:27:12.360 --> 00:27:14.130
And we do a very similar thing,
556
00:27:14.130 --> 00:27:15.810
trying to grow this pathogen in lab.
557
00:27:15.810 --> 00:27:19.680
So we have Petri dishes with seawater serum agar
558
00:27:19.680 --> 00:27:21.240
which contains all the nutrients
559
00:27:21.240 --> 00:27:22.893
the pathogen needs to thrive.
560
00:27:23.730 --> 00:27:27.030
We place lesioned eelgrass tissue on the Petri dish.
561
00:27:27.030 --> 00:27:29.590
And so those darker patches are areas
562
00:27:31.140 --> 00:27:32.700
where the pathogen is active.
563
00:27:32.700 --> 00:27:35.490
And so we're hoping it'll come out of the seagrass tissue
564
00:27:35.490 --> 00:27:38.370
and grow onto this nice agar we set up.
565
00:27:38.370 --> 00:27:41.220
And, you know, after maybe about a week,
566
00:27:41.220 --> 00:27:43.050
we might get something like this.
567
00:27:43.050 --> 00:27:44.730
And so those yellow arrows
568
00:27:44.730 --> 00:27:48.780
are pointing to that kind of like white fuzzy clumps
569
00:27:48.780 --> 00:27:50.940
that you're seeing on the agar dish.
570
00:27:50.940 --> 00:27:54.030
And those are actually areas of very dense pathogen.
571
00:27:54.030 --> 00:27:55.920
So that's exactly what we want.
572
00:27:55.920 --> 00:27:58.170
However, we do wanna make sure, when we're doing this,
573
00:27:58.170 --> 00:28:01.770
that we are only isolating the pathogen that we want.
574
00:28:01.770 --> 00:28:04.620
And so we're gonna take a little square of that agar
575
00:28:04.620 --> 00:28:06.900
and put it onto a plate of new media
576
00:28:06.900 --> 00:28:08.820
and then watch that grow out.
577
00:28:08.820 --> 00:28:13.020
And so the cells that originally started
578
00:28:13.020 --> 00:28:14.430
on that little square of agar
579
00:28:14.430 --> 00:28:17.220
are growing out onto this new media very happily.
580
00:28:17.220 --> 00:28:19.500
And so it's reaching the point
581
00:28:19.500 --> 00:28:21.570
where the culture is kinda that red border
582
00:28:21.570 --> 00:28:22.773
that I've drawn there.
583
00:28:24.180 --> 00:28:26.880
And so this is definitely a learning process.
584
00:28:26.880 --> 00:28:30.870
You can get contamination on a lot of your plates
585
00:28:30.870 --> 00:28:35.790
or yourselves could use up all the media and then die.
586
00:28:35.790 --> 00:28:37.590
And so you really need to be consistent
587
00:28:37.590 --> 00:28:40.380
about checking on the cultures.
588
00:28:40.380 --> 00:28:44.220
And in that way, I think it is very similar
589
00:28:44.220 --> 00:28:45.513
to growing a houseplant.
590
00:28:48.840 --> 00:28:51.240
And so the end goal for my research
591
00:28:51.240 --> 00:28:54.390
is to be able to create a disease risk map
592
00:28:54.390 --> 00:28:56.190
of the estuaries that I work in,
593
00:28:56.190 --> 00:28:58.830
similar to this temperature map of Tomales Bay
594
00:28:58.830 --> 00:29:00.300
shown to the right.
595
00:29:00.300 --> 00:29:01.530
And so with my field work,
596
00:29:01.530 --> 00:29:05.550
I'm looking at how disease intensity
597
00:29:05.550 --> 00:29:09.150
throughout the year varies and what that looks like.
598
00:29:09.150 --> 00:29:11.310
And then with lab work, I'm delving
599
00:29:11.310 --> 00:29:14.430
into the different strains of the pathogen in the area.
600
00:29:14.430 --> 00:29:16.140
And so with these two IDs together,
601
00:29:16.140 --> 00:29:17.400
I'm hoping to combine them
602
00:29:17.400 --> 00:29:20.400
and be able to kind of predict disease hotspots
603
00:29:20.400 --> 00:29:23.550
that are occurring in the estuary.
604
00:29:23.550 --> 00:29:24.870
And then perhaps one question
605
00:29:24.870 --> 00:29:26.550
I might be able to answer from that is,
606
00:29:26.550 --> 00:29:28.320
do these disease levels reflect
607
00:29:28.320 --> 00:29:31.070
kind of the temperature patterns that we also see here?
608
00:29:32.580 --> 00:29:34.920
And through my work
609
00:29:34.920 --> 00:29:37.320
with the Greater Farallones National Marine Sanctuary,
610
00:29:37.320 --> 00:29:40.710
I am also hoping that my work will be useful to managers.
611
00:29:40.710 --> 00:29:42.930
So when managers are deciding,
612
00:29:42.930 --> 00:29:45.780
you know, what areas they wanna take donor plants from
613
00:29:45.780 --> 00:29:50.223
for seagrass restoration projects,
614
00:29:51.120 --> 00:29:52.620
this might be something that they look at
615
00:29:52.620 --> 00:29:55.740
to make sure that they're not taking plants from a site
616
00:29:55.740 --> 00:29:59.790
that has an extremely infectious pathogen around,
617
00:29:59.790 --> 00:30:01.860
as moving those to different parts of the estuary
618
00:30:01.860 --> 00:30:02.910
would be problematic.
619
00:30:03.960 --> 00:30:07.240
And so my work will also
620
00:30:08.100 --> 00:30:10.290
hopefully give us some predictive power
621
00:30:10.290 --> 00:30:13.260
in terms of what areas in the estuary
622
00:30:13.260 --> 00:30:16.560
are gonna be prone to disease now or in the future.
623
00:30:16.560 --> 00:30:20.430
And so identifying both resilient populations
624
00:30:20.430 --> 00:30:25.430
and also vulnerable populations that might be prioritized
625
00:30:26.190 --> 00:30:28.540
when we're thinking about conservation efforts.
626
00:30:30.930 --> 00:30:32.760
And so I just wanna go over this
627
00:30:32.760 --> 00:30:36.390
because I get this question a lot from either managers
628
00:30:36.390 --> 00:30:38.880
or people I run into at my field site.
629
00:30:38.880 --> 00:30:41.300
So obviously kinda the first thought is,
630
00:30:41.300 --> 00:30:42.960
if this disease is so dangerous,
631
00:30:42.960 --> 00:30:44.583
like are we looking for a cure?
632
00:30:45.810 --> 00:30:48.810
And I will say it's a very complicated question.
633
00:30:48.810 --> 00:30:52.950
With marine diseases, everything, you know, is so fluid,
634
00:30:52.950 --> 00:30:54.900
the pathogen is waterborne,
635
00:30:54.900 --> 00:30:59.430
and so it's really hard to put in large scale interventions
636
00:30:59.430 --> 00:31:00.900
without negatively harming
637
00:31:00.900 --> 00:31:03.840
some other organism in the environment.
638
00:31:03.840 --> 00:31:07.230
And with a continuous rise in ocean temperature,
639
00:31:07.230 --> 00:31:10.170
we know that disease outbreaks are increasing
640
00:31:10.170 --> 00:31:13.296
in both occurrence and severity.
641
00:31:13.296 --> 00:31:15.210
But this is not a doom and gloom story.
642
00:31:15.210 --> 00:31:17.190
That doesn't mean that there's nothing we can do
643
00:31:17.190 --> 00:31:19.743
to help these issues.
644
00:31:21.000 --> 00:31:23.250
There's actually some really exciting avenues of research
645
00:31:23.250 --> 00:31:25.860
with microbial communities in seagrasses
646
00:31:25.860 --> 00:31:27.750
and how they might be able to help bolster
647
00:31:27.750 --> 00:31:30.630
the ability of seagrasses to fight off infection.
648
00:31:30.630 --> 00:31:34.260
So this is similar to how you might drink probiotics
649
00:31:34.260 --> 00:31:37.170
to accumulate good bacteria in your body
650
00:31:37.170 --> 00:31:39.690
and help you feel more energized.
651
00:31:39.690 --> 00:31:42.930
And we can also focus on decreasing
652
00:31:42.930 --> 00:31:44.680
other stressors in the environment
653
00:31:45.540 --> 00:31:49.740
such as pollution or boating practices
654
00:31:49.740 --> 00:31:51.450
that are gonna tear up the seagrasses.
655
00:31:51.450 --> 00:31:56.250
So making it as ideal environment
656
00:31:56.250 --> 00:31:57.813
for seagrasses as possible.
657
00:31:59.220 --> 00:32:01.200
And there's also some really awesome
658
00:32:01.200 --> 00:32:03.750
successful restoration stories of seagrasses.
659
00:32:03.750 --> 00:32:07.950
So here in California, down in Southern California,
660
00:32:07.950 --> 00:32:12.000
Morro Bay in 2017,
661
00:32:12.000 --> 00:32:14.580
they had once thriving eelgrass beds
662
00:32:14.580 --> 00:32:18.120
that was actually cut down to about 13 acres,
663
00:32:18.120 --> 00:32:20.850
and then through active restoration efforts
664
00:32:20.850 --> 00:32:23.280
and then also just the eelgrass bed itself
665
00:32:23.280 --> 00:32:28.280
just naturally recovering, they got up to 500 acres in 2021.
666
00:32:28.410 --> 00:32:30.030
And so it's really efforts like this
667
00:32:30.030 --> 00:32:33.270
that showcase how resilient this ecosystem is
668
00:32:33.270 --> 00:32:36.453
and how our efforts do matter and can make a difference.
669
00:32:39.660 --> 00:32:42.600
And so I just wanna wrap up some key takeaways
670
00:32:42.600 --> 00:32:45.423
that I hope you got out of this presentation.
671
00:32:46.440 --> 00:32:50.250
One, that seagrasses are cornerstones for coastal ecosystems
672
00:32:50.250 --> 00:32:53.520
and protect our coastlines and are important to our society
673
00:32:53.520 --> 00:32:55.473
even if we don't really think so.
674
00:32:57.750 --> 00:33:00.120
Two, that by identifying vulnerable
675
00:33:00.120 --> 00:33:03.030
and resilient populations, we can be better prepared
676
00:33:03.030 --> 00:33:05.583
for future seagrass wasting disease outbreaks.
677
00:33:07.110 --> 00:33:10.110
And three, that although marine diseases are common,
678
00:33:10.110 --> 00:33:12.330
they can be managed by decreasing
679
00:33:12.330 --> 00:33:14.193
other stressors in the area.
680
00:33:17.670 --> 00:33:21.360
And so I put together some resources
681
00:33:21.360 --> 00:33:22.680
if you're interested in learning more
682
00:33:22.680 --> 00:33:24.930
about the background of seagrasses,
683
00:33:24.930 --> 00:33:27.450
and then also some educational resources.
684
00:33:27.450 --> 00:33:28.380
So there's some awesome,
685
00:33:28.380 --> 00:33:30.810
like, free teaching tools out there about seagrasses,
686
00:33:30.810 --> 00:33:33.720
this is only, like, a small snapshot of them,
687
00:33:33.720 --> 00:33:35.760
but I have put these in a little handout
688
00:33:35.760 --> 00:33:37.893
that that QR code will take you to.
689
00:33:39.450 --> 00:33:42.090
And so I wanted to just say
690
00:33:42.090 --> 00:33:44.040
thank you so much for joining me today,
691
00:33:45.040 --> 00:33:46.800
and please feel free to email me
692
00:33:46.800 --> 00:33:48.200
with any questions you have.
693
00:33:51.480 --> 00:33:55.320
Oh, thank you so much, Serina, for your great presentation
694
00:33:55.320 --> 00:33:57.870
and we appreciate it.
695
00:33:57.870 --> 00:34:01.380
So Brian and I will look through these questions here.
696
00:34:01.380 --> 00:34:04.350
A few have already come in, but for the rest of you,
697
00:34:04.350 --> 00:34:06.930
go ahead and start thinking about your questions,
698
00:34:06.930 --> 00:34:09.750
getting them typed into the question box.
699
00:34:09.750 --> 00:34:14.670
But to kick it off, when you were talking about
700
00:34:14.670 --> 00:34:18.240
the different salinity and temperature in the two bays,
701
00:34:18.240 --> 00:34:20.250
someone's asking about does Tomales Bay
702
00:34:20.250 --> 00:34:23.310
also have a salinity gradient,
703
00:34:23.310 --> 00:34:28.110
and how do the salinities compare between the two bays?
704
00:34:28.110 --> 00:34:30.600
Mm, yeah, that's a great question.
705
00:34:30.600 --> 00:34:34.260
So I think that, (chuckles)
706
00:34:34.260 --> 00:34:38.370
yeah, so there is a salinity gradient in Tamales Bay,
707
00:34:38.370 --> 00:34:41.010
but it's for such a short period of time
708
00:34:41.010 --> 00:34:43.290
and it's so unpredictable
709
00:34:43.290 --> 00:34:46.027
that I think it's much harder to kind of say that,
710
00:34:46.027 --> 00:34:47.610
"Oh, this is a constant trend,"
711
00:34:47.610 --> 00:34:49.650
or, "This is something that we can correlate
712
00:34:49.650 --> 00:34:51.570
with our disease metrics."
713
00:34:51.570 --> 00:34:54.120
So Tomales Bay does have
714
00:34:54.120 --> 00:34:55.860
a couple of different freshwater inputs
715
00:34:55.860 --> 00:34:58.860
from different creeks, and one of our sites is actually
716
00:34:58.860 --> 00:35:00.840
by one of those freshwater inputs.
717
00:35:00.840 --> 00:35:02.820
And so it's really during the winter time
718
00:35:02.820 --> 00:35:05.820
when you get snowmelt coming down or the rainy,
719
00:35:05.820 --> 00:35:07.920
or, yeah, I guess in this case, more the rainy season.
720
00:35:07.920 --> 00:35:09.060
Sorry, I'm from the East Coast,
721
00:35:09.060 --> 00:35:11.643
so winter and snow are kinda synonymous.
722
00:35:13.140 --> 00:35:16.470
And, yeah, so it's really only during maybe,
723
00:35:16.470 --> 00:35:18.390
you know, a couple days or a week
724
00:35:18.390 --> 00:35:20.220
during kinda those rainy winter seasons
725
00:35:20.220 --> 00:35:22.440
that you might actually get a really big influx
726
00:35:22.440 --> 00:35:24.600
of fresh water into the system.
727
00:35:24.600 --> 00:35:28.260
So in that case, there is kind of a very,
728
00:35:28.260 --> 00:35:32.010
I would say, measurable and significant change in salinity,
729
00:35:32.010 --> 00:35:35.340
but because of the current system in the bay,
730
00:35:35.340 --> 00:35:37.020
that, like, water residence
731
00:35:37.020 --> 00:35:39.670
is not necessarily gonna stick there for a long time.
732
00:35:40.590 --> 00:35:43.230
And, yeah, so I think that,
733
00:35:43.230 --> 00:35:45.120
you know, it is definitely possible
734
00:35:45.120 --> 00:35:47.280
that a salinity can have an effect in this case,
735
00:35:47.280 --> 00:35:49.080
but it's not necessarily a system
736
00:35:49.080 --> 00:35:53.550
where it's a big factor right now.
737
00:35:53.550 --> 00:35:54.900
Well, and that kind of a follow-up question,
738
00:35:54.900 --> 00:35:56.610
someone was asking like that,
739
00:35:56.610 --> 00:35:59.910
so salinity doesn't really necessarily play a role
740
00:35:59.910 --> 00:36:03.030
in explaining the wasting disease incidents then.
741
00:36:03.030 --> 00:36:05.580
This was kind of a follow-up question.
742
00:36:05.580 --> 00:36:08.700
So I will say that there have been studies
743
00:36:08.700 --> 00:36:13.700
that have looked at in low salinity environments,
744
00:36:13.710 --> 00:36:16.950
so in environments with a lot of freshwater input,
745
00:36:16.950 --> 00:36:20.790
the pathogen is shown to, you know, not do as well.
746
00:36:20.790 --> 00:36:24.060
And so I will say that there definitely could be an effect,
747
00:36:24.060 --> 00:36:26.340
but I think that for this system in particular,
748
00:36:26.340 --> 00:36:29.040
in Tomales Bay in particular,
749
00:36:29.040 --> 00:36:31.800
it would be much harder to kinda pin down those effects
750
00:36:31.800 --> 00:36:34.350
in terms of it would be a big enough difference in salinity
751
00:36:34.350 --> 00:36:36.210
for a long enough period of time
752
00:36:36.210 --> 00:36:39.153
to actually help us explain these disease variations.
753
00:36:43.170 --> 00:36:45.093
Brian, are you joinin' us?
754
00:36:48.270 --> 00:36:49.950
It's possible we lost him.
755
00:36:49.950 --> 00:36:52.740
We've had some wonky things with our, oh, there he is.
756
00:36:52.740 --> 00:36:53.573
Yay.
All right, Brian,
757
00:36:53.573 --> 00:36:56.777
I'll let you take a question here to send to Serina.
758
00:37:01.900 --> 00:37:03.540
There was a question in the chat
759
00:37:03.540 --> 00:37:07.290
that was about how this kind of disease
760
00:37:07.290 --> 00:37:09.780
compares with seagrass beds on the East Coast
761
00:37:09.780 --> 00:37:12.243
and how it relates to manatees as well.
762
00:37:13.260 --> 00:37:14.550
Yeah, that's a great question.
763
00:37:14.550 --> 00:37:16.650
So I'm sure you guys remember,
764
00:37:16.650 --> 00:37:18.420
you know, seagrasses are found globally,
765
00:37:18.420 --> 00:37:20.790
so of course we might not have manatees out here,
766
00:37:20.790 --> 00:37:23.370
but that's definitely true in, I believe, Florida.
767
00:37:23.370 --> 00:37:26.730
And I feel like it's actually really cool
768
00:37:26.730 --> 00:37:28.590
to kind of have this global network
769
00:37:28.590 --> 00:37:31.170
of seagrass ecologists working in different places.
770
00:37:31.170 --> 00:37:33.360
And so there is a big group out in,
771
00:37:33.360 --> 00:37:35.430
I believe, Chesapeake Bay out at VIMS
772
00:37:35.430 --> 00:37:37.650
that are, you know, just one of the groups
773
00:37:37.650 --> 00:37:39.903
looking at seagrasses out on the East Coast.
774
00:37:40.800 --> 00:37:43.500
And so they do have wasting disease out there.
775
00:37:43.500 --> 00:37:46.200
I would say there's very few places where wasting disease
776
00:37:46.200 --> 00:37:47.613
is actually not present.
777
00:37:48.450 --> 00:37:52.170
But in terms of whether it's, like, actually necessarily,
778
00:37:52.170 --> 00:37:55.560
like, harming the eelgrass to the extent
779
00:37:55.560 --> 00:38:00.560
where it's in danger of wiping out an entire meadow
780
00:38:00.840 --> 00:38:02.610
is not necessarily true.
781
00:38:02.610 --> 00:38:05.100
I think even in our California estuaries,
782
00:38:05.100 --> 00:38:06.810
you know, we're monitoring the seagrass,
783
00:38:06.810 --> 00:38:09.360
but the seagrass does come back year after year.
784
00:38:09.360 --> 00:38:12.810
And so, again, kinda pointing towards the resilience
785
00:38:12.810 --> 00:38:15.330
of these ecosystems.
786
00:38:15.330 --> 00:38:18.450
And so I think I would have to actually look at some data
787
00:38:18.450 --> 00:38:19.920
to see, you know, comparatively
788
00:38:19.920 --> 00:38:22.830
like what the disease levels are on the different coasts.
789
00:38:22.830 --> 00:38:23.910
But I think it's also,
790
00:38:23.910 --> 00:38:26.430
there are so many different environmental factors,
791
00:38:26.430 --> 00:38:28.440
you know, Atlantic versus Pacific Coast
792
00:38:28.440 --> 00:38:32.220
and different temperature regimes, like, down in Florida.
793
00:38:32.220 --> 00:38:36.030
And so I think that there's a lot of different factors
794
00:38:36.030 --> 00:38:37.410
that you're gonna have to take into account there
795
00:38:37.410 --> 00:38:40.323
when you're trying to compare across regions especially.
796
00:38:42.720 --> 00:38:44.070
Great.
797
00:38:44.070 --> 00:38:48.570
Someone's suggesting, and you can maybe clarify this,
798
00:38:48.570 --> 00:38:51.210
the seagrass, the Z. marina,
799
00:38:51.210 --> 00:38:54.903
is that an introduced exotic species on the West Coast?
800
00:38:56.040 --> 00:39:00.030
Yeah, so I think, I wanna say all the seagrass,
801
00:39:00.030 --> 00:39:03.060
although I definitely need to brush up on this,
802
00:39:03.060 --> 00:39:06.210
was originated in kinda the Japan area
803
00:39:06.210 --> 00:39:08.910
and then kind of migrated all over the world.
804
00:39:08.910 --> 00:39:12.827
So I believe, you know, it's not necessarily native,
805
00:39:14.700 --> 00:39:17.250
I guess I would say, but there are kind of,
806
00:39:17.250 --> 00:39:20.130
I would say, more invasive species than others.
807
00:39:20.130 --> 00:39:21.630
I know Zostera japonica,
808
00:39:21.630 --> 00:39:24.450
which is found a little bit further up the West Coast,
809
00:39:24.450 --> 00:39:26.910
kind of in the Oregon, Washington region
810
00:39:26.910 --> 00:39:28.740
I think it's a lot more common,
811
00:39:28.740 --> 00:39:30.270
I would say that is kind of viewed
812
00:39:30.270 --> 00:39:32.853
as a more invasive seagrass, if you will.
813
00:39:34.170 --> 00:39:36.033
And yeah, I think, again,
814
00:39:37.498 --> 00:39:39.498
I don't have the best knowledge on this,
815
00:39:41.460 --> 00:39:43.593
but that's the best I could explain it.
816
00:39:45.120 --> 00:39:46.650
Oh yeah, we might be asking questions
817
00:39:46.650 --> 00:39:49.563
that are outside your purview, so just let us know.
818
00:39:56.820 --> 00:39:59.640
All right, there's one here.
819
00:39:59.640 --> 00:40:02.640
Like, do you have any data on the amount of carbon
820
00:40:02.640 --> 00:40:05.400
that is stored by all of the seagrasses?
821
00:40:05.400 --> 00:40:08.100
I know we talked about blue carbon ecosystems,
822
00:40:08.100 --> 00:40:11.400
but is that something at your fingertips?
823
00:40:11.400 --> 00:40:15.540
That is not something I know off the top of my head.
824
00:40:15.540 --> 00:40:17.100
I would definitely encourage you guys
825
00:40:17.100 --> 00:40:22.100
to, you know, like Google any resources or papers
826
00:40:24.090 --> 00:40:26.160
'cause I'm sure, you know, that number
827
00:40:26.160 --> 00:40:27.060
is definitely out there.
828
00:40:27.060 --> 00:40:28.890
And I definitely don't wanna tell you a wrong number,
829
00:40:28.890 --> 00:40:32.640
but it's significant enough that people are,
830
00:40:32.640 --> 00:40:34.983
you know, noting it as a blue carbon system.
831
00:40:41.130 --> 00:40:43.620
Go ahead, Brian, if you found another good question here.
832
00:40:43.620 --> 00:40:47.010
There's quite a few, so we're kinda going through it.
833
00:40:47.010 --> 00:40:49.363
Yeah, I'm trying to keep up with all of them.
834
00:40:50.670 --> 00:40:51.633
Let's see.
835
00:40:52.830 --> 00:40:55.800
How long and frequently are you doing your field monitoring
836
00:40:55.800 --> 00:40:59.100
to help make your maps and temperature predictions?
837
00:40:59.100 --> 00:41:01.170
Yeah, so it's a little tricky
838
00:41:01.170 --> 00:41:02.820
because we do intertidal field work.
839
00:41:02.820 --> 00:41:07.820
So, like, relying on the tides gets a little challenging,
840
00:41:07.890 --> 00:41:10.590
especially in the kinda fall/winter area.
841
00:41:10.590 --> 00:41:13.740
So the tides are either super late at night
842
00:41:13.740 --> 00:41:15.480
or super early in the morning.
843
00:41:15.480 --> 00:41:16.920
And then often tides,
844
00:41:16.920 --> 00:41:18.720
they're like not necessarily good tides,
845
00:41:18.720 --> 00:41:21.990
so the water's still pretty deep even at low tide,
846
00:41:21.990 --> 00:41:24.270
that it might make it really difficult for us to go out.
847
00:41:24.270 --> 00:41:29.270
And so I completed almost one year of sampling,
848
00:41:30.630 --> 00:41:35.630
and so I did kind of a seasonal time point in the fall
849
00:41:35.700 --> 00:41:37.650
and a seasonal time point in the winter.
850
00:41:37.650 --> 00:41:41.280
And then from, I guess, February onward
851
00:41:41.280 --> 00:41:43.260
until probably August or September,
852
00:41:43.260 --> 00:41:45.450
I'll be doing monthly sampling time points.
853
00:41:45.450 --> 00:41:48.750
And so we're really hoping to be able to capture
854
00:41:48.750 --> 00:41:51.690
the start of when disease is really starting to ramp up
855
00:41:51.690 --> 00:41:55.260
in these seagrass beds, which might be around
856
00:41:55.260 --> 00:41:56.940
kind of like the spring-ish time point
857
00:41:56.940 --> 00:41:59.730
'cause then we do see a lot of disease lesions
858
00:41:59.730 --> 00:42:01.650
by the time you get to June, July, August.
859
00:42:01.650 --> 00:42:03.840
So we're hoping to be able to cover
860
00:42:03.840 --> 00:42:05.310
kind of like a breadth of area
861
00:42:05.310 --> 00:42:07.230
and then we'll see if that's necessary
862
00:42:07.230 --> 00:42:11.523
to continue this temporally for the next couple of years.
863
00:42:12.900 --> 00:42:15.690
Yeah, so with your analyzing your field data
864
00:42:15.690 --> 00:42:19.530
to determine hotspots, like I'm not sure if I caught this,
865
00:42:19.530 --> 00:42:22.113
can you do that through modeling as well?
866
00:42:23.490 --> 00:42:26.490
Yeah. Yes, exactly.
867
00:42:26.490 --> 00:42:30.360
So there's actually a postdoc in my lab
868
00:42:30.360 --> 00:42:33.480
who is starting to do a project also
869
00:42:33.480 --> 00:42:35.070
on seagrass wasting disease,
870
00:42:35.070 --> 00:42:38.380
and she's developing a model that will be able to
871
00:42:39.240 --> 00:42:41.970
essentially have an output that's very similar to this.
872
00:42:41.970 --> 00:42:44.790
So we are looking at, so for a model,
873
00:42:44.790 --> 00:42:46.530
it would probably need to be some type of,
874
00:42:46.530 --> 00:42:50.160
you know a transmission rate between healthy and infected,
875
00:42:50.160 --> 00:42:54.930
you know a recovery rate from if a plant is infected,
876
00:42:54.930 --> 00:42:57.390
can it recover and like what percentage of plants
877
00:42:57.390 --> 00:43:01.380
are gonna recover, what dosage of,
878
00:43:01.380 --> 00:43:05.100
you know, how many Labyrinthula zosterae cells are necessary
879
00:43:05.100 --> 00:43:06.480
to actually start an infection.
880
00:43:06.480 --> 00:43:09.480
And so there's a lot of smaller, I think, pilot experiments
881
00:43:09.480 --> 00:43:10.830
that need to be done before that
882
00:43:10.830 --> 00:43:12.930
to get information that you then put into a model,
883
00:43:12.930 --> 00:43:15.060
but that is kinda the idea
884
00:43:15.060 --> 00:43:18.810
of, like, using some type of model and technology like that
885
00:43:18.810 --> 00:43:20.410
to be able to create these maps.
886
00:43:26.490 --> 00:43:27.323
There's a couple of questions
887
00:43:27.323 --> 00:43:30.180
that I think kind of connect to each other
888
00:43:30.180 --> 00:43:33.180
regarding kinda genetic sequencing
889
00:43:33.180 --> 00:43:35.610
to determine if there is sort of a resilience.
890
00:43:35.610 --> 00:43:37.500
And then a second question,
891
00:43:37.500 --> 00:43:40.410
if there's the potential for the seagrasses
892
00:43:40.410 --> 00:43:42.360
to build some sort of immunity as well.
893
00:43:43.650 --> 00:43:48.650
Yeah, so it was genetic testing to determine,
894
00:43:48.720 --> 00:43:49.620
what was it again?
895
00:43:52.693 --> 00:43:53.700
A resilience.
896
00:43:53.700 --> 00:43:55.173
Resilience, okay, yes.
897
00:43:56.190 --> 00:44:00.780
Yeah, so I think that I was kind of thinking more,
898
00:44:00.780 --> 00:44:02.160
so there is definitely
899
00:44:02.160 --> 00:44:04.263
a lot of seagrass genetics work going on,
900
00:44:05.190 --> 00:44:08.493
and especially in terms of there are,
901
00:44:10.350 --> 00:44:12.300
yeah, kind of like different genotypes,
902
00:44:12.300 --> 00:44:14.820
and I know there's actually another lab at UC Davis
903
00:44:14.820 --> 00:44:16.500
who's kinda focusing on that
904
00:44:16.500 --> 00:44:19.710
and have looked at seagrass disease metrics as well
905
00:44:19.710 --> 00:44:21.450
in their experiments.
906
00:44:21.450 --> 00:44:23.730
I think for me, I was thinking again,
907
00:44:23.730 --> 00:44:27.330
kind of more about the different pathogen strains
908
00:44:27.330 --> 00:44:28.320
that might be out there.
909
00:44:28.320 --> 00:44:30.840
And so I would sequence those samples
910
00:44:30.840 --> 00:44:32.760
in terms of trying to figure out
911
00:44:32.760 --> 00:44:35.580
are there genetic differences between my pathogen strains?
912
00:44:35.580 --> 00:44:39.180
If so, does that point towards certain factors
913
00:44:39.180 --> 00:44:44.180
that might affect how virulent the pathogen is,
914
00:44:44.610 --> 00:44:47.340
how much it's able to infect a plant.
915
00:44:47.340 --> 00:44:51.420
So I guess I'm kinda going less on the host side of things
916
00:44:51.420 --> 00:44:53.400
because I feel like there are a lot of people doing that
917
00:44:53.400 --> 00:44:55.770
and kinda more on the pathogen side of things
918
00:44:55.770 --> 00:44:57.873
that are a bit more unknown.
919
00:44:58.980 --> 00:45:01.470
And so I think that both those factors
920
00:45:01.470 --> 00:45:04.740
can kinda tell us about resilience
921
00:45:04.740 --> 00:45:07.173
as kinda like a community or population.
922
00:45:08.670 --> 00:45:12.603
And did I forget one other part of your question?
923
00:45:16.320 --> 00:45:17.520
Yeah, I think we forgot too.
924
00:45:17.520 --> 00:45:20.331
What was it, Brian? (laughs)
925
00:45:20.331 --> 00:45:22.302
The immunity and-
Oh, immunity.
926
00:45:22.302 --> 00:45:23.998
Yeah.
Yes.
927
00:45:23.998 --> 00:45:25.388
Immunity against the pathogen, yeah.
928
00:45:25.388 --> 00:45:26.221
Right, yeah.
929
00:45:26.221 --> 00:45:29.520
So unlike humans, seagrasses do not have
930
00:45:29.520 --> 00:45:30.750
an adaptive immune system.
931
00:45:30.750 --> 00:45:33.217
So they really only have kinda this like innate response to,
932
00:45:33.217 --> 00:45:36.521
"Something's wrong, let's, like, try to fix this."
933
00:45:36.521 --> 00:45:39.840
And so there has been some work done on phenology.
934
00:45:39.840 --> 00:45:41.070
And so these are compounds
935
00:45:41.070 --> 00:45:42.630
that the seagrass is gonna produce
936
00:45:42.630 --> 00:45:45.483
to try to protect itself from any type of threat.
937
00:45:46.650 --> 00:45:48.870
Like, these are mostly chemical compounds.
938
00:45:48.870 --> 00:45:52.323
And so I think that over time,
939
00:45:53.310 --> 00:45:55.440
through different generations,
940
00:45:55.440 --> 00:45:59.610
there might be some indication that seagrasses,
941
00:45:59.610 --> 00:46:02.103
you know, might be able to,
942
00:46:03.270 --> 00:46:05.670
for instance, if your parents, like, had the disease,
943
00:46:05.670 --> 00:46:09.030
like it is possible that maybe that somehow passes down
944
00:46:09.030 --> 00:46:10.023
to the offspring.
945
00:46:11.160 --> 00:46:13.740
And then also kind of within the seagrass plant's life,
946
00:46:13.740 --> 00:46:15.420
like if it's been infected before,
947
00:46:15.420 --> 00:46:18.600
like what's the possibility that it is more,
948
00:46:18.600 --> 00:46:20.190
you know, resistant to that infection?
949
00:46:20.190 --> 00:46:23.400
And I think, like, there's a lot of kinda like hypotheses
950
00:46:23.400 --> 00:46:24.780
that this might happen,
951
00:46:24.780 --> 00:46:28.257
and hopefully some of my work will be able to get at this,
952
00:46:28.257 --> 00:46:30.420
but I do think that's kinda like a burning question
953
00:46:30.420 --> 00:46:31.570
a little bit right now.
954
00:46:34.170 --> 00:46:37.350
This is one specific to your lab work.
955
00:46:37.350 --> 00:46:39.630
So at what temperature, or temperatures,
956
00:46:39.630 --> 00:46:43.230
are you incubating your pathogen isolates in the lab,
957
00:46:43.230 --> 00:46:45.810
and is there a temperature optimum
958
00:46:45.810 --> 00:46:49.800
for these microbes for rapid multiplication?
959
00:46:49.800 --> 00:46:52.680
Mm, yeah, that's a great question.
960
00:46:52.680 --> 00:46:54.630
So I'm actually a little bit lucky
961
00:46:54.630 --> 00:46:58.080
that I kinda stumbled upon the seagrass system in that one,
962
00:46:58.080 --> 00:47:00.900
the pathogen is culturable in lab, which is great,
963
00:47:00.900 --> 00:47:03.000
and that you can just leave the plates
964
00:47:03.000 --> 00:47:06.690
out at room temperature and they seem to grow just fine.
965
00:47:06.690 --> 00:47:08.520
And so I did experiment a little bit
966
00:47:08.520 --> 00:47:12.510
with like raising the temperature
967
00:47:12.510 --> 00:47:16.590
maybe to like 20 degrees Celsius or something like that,
968
00:47:16.590 --> 00:47:18.363
or a little bit higher, like 21,
969
00:47:19.230 --> 00:47:21.930
and it didn't really seem to make that much of a difference.
970
00:47:21.930 --> 00:47:24.210
This is also an area of kinda like
971
00:47:24.210 --> 00:47:26.100
active investigation in my lab
972
00:47:26.100 --> 00:47:27.720
that probably in the next, like, couple weeks
973
00:47:27.720 --> 00:47:30.020
or couple months, like I'm definitely gonna be
974
00:47:30.990 --> 00:47:32.880
getting a lot more into this
975
00:47:32.880 --> 00:47:35.160
in terms of what is the optimum temperature.
976
00:47:35.160 --> 00:47:38.880
And the postdoc in my lab who's working on models
977
00:47:38.880 --> 00:47:40.890
is also working on thermal performance curves
978
00:47:40.890 --> 00:47:42.930
of Labyrinthula zosterae.
979
00:47:42.930 --> 00:47:45.960
So she's also gonna be, you know, looking,
980
00:47:45.960 --> 00:47:47.490
especially at this question of
981
00:47:47.490 --> 00:47:49.470
what is the optimum temperature
982
00:47:49.470 --> 00:47:51.270
that this pathogen can go really well at
983
00:47:51.270 --> 00:47:53.970
and how does that compare to environmental conditions?
984
00:47:58.800 --> 00:48:00.900
There's a few questions as well
985
00:48:00.900 --> 00:48:05.900
about what was the native species before the Z. marina
986
00:48:05.940 --> 00:48:09.630
and then how kind of the ecosystems that they support
987
00:48:09.630 --> 00:48:12.120
and the roles that the two different species have
988
00:48:12.120 --> 00:48:13.670
kind of compared to each other.
989
00:48:14.520 --> 00:48:18.570
So yeah, I feel like as these questions are rolling in
990
00:48:18.570 --> 00:48:19.920
about kinda like native species,
991
00:48:19.920 --> 00:48:23.040
I'm like, "Oh, this is something I should learn more about."
992
00:48:23.040 --> 00:48:25.710
So my sense is that, like, the,
993
00:48:25.710 --> 00:48:28.830
I guess like transmigration of seagrasses from Japan
994
00:48:28.830 --> 00:48:30.660
happened a very long time ago.
995
00:48:30.660 --> 00:48:32.458
So in terms of like nativity,
996
00:48:32.458 --> 00:48:34.860
like what is the time frame that we're thinking about
997
00:48:34.860 --> 00:48:37.050
might be a good question to ponder.
998
00:48:37.050 --> 00:48:41.790
And so I know that, like, seagrasses have been in the area
999
00:48:41.790 --> 00:48:44.913
for, I would say, a pretty substantial amount of time,
1000
00:48:45.870 --> 00:48:49.560
and I don't necessarily, I believe that Zostera marina
1001
00:48:49.560 --> 00:48:54.150
is the majority species that we have here at least
1002
00:48:54.150 --> 00:48:56.163
and has been for a very long time.
1003
00:48:58.340 --> 00:48:59.760
Like, you know, Indigenous tribes
1004
00:48:59.760 --> 00:49:04.233
have been using seagrasses for decades, centuries,
1005
00:49:06.859 --> 00:49:09.390
you know, as a weaving material for baskets
1006
00:49:09.390 --> 00:49:13.320
or as housing material to, like, patch roofs.
1007
00:49:13.320 --> 00:49:15.810
So I would say that it's been here
1008
00:49:15.810 --> 00:49:16.800
a long enough amount of time
1009
00:49:16.800 --> 00:49:19.500
that it has kind of integrated itself into the community
1010
00:49:19.500 --> 00:49:21.000
and how the community uses it.
1011
00:49:21.960 --> 00:49:24.420
And as far as I know, Zostera marina,
1012
00:49:24.420 --> 00:49:27.120
that has been the species that's been present
1013
00:49:27.120 --> 00:49:27.953
for the longest.
1014
00:49:27.953 --> 00:49:32.640
But, again, this is pushing the edges of my knowledge
1015
00:49:32.640 --> 00:49:33.543
a little bit here.
1016
00:49:35.310 --> 00:49:36.960
And this is kind of an interesting question.
1017
00:49:36.960 --> 00:49:39.970
Like, are there other things that can cause
1018
00:49:41.460 --> 00:49:44.070
something that looks similar to the disease lesions,
1019
00:49:44.070 --> 00:49:46.020
like feeding by snails?
1020
00:49:46.020 --> 00:49:49.290
And if so, like, how can you tell the difference?
1021
00:49:49.290 --> 00:49:50.550
Yeah, that's a great question.
1022
00:49:50.550 --> 00:49:54.330
Actually I realized I, like, didn't really get into this.
1023
00:49:54.330 --> 00:49:56.040
But while we're doing our disease surveys,
1024
00:49:56.040 --> 00:50:00.240
we are also documenting grazing scars on the eelgrass.
1025
00:50:00.240 --> 00:50:03.000
So sometimes you'll have little chomps sticking out of it,
1026
00:50:03.000 --> 00:50:04.770
and you're like, "Okay, that's obviously
1027
00:50:04.770 --> 00:50:06.240
like an invertebrate feeding on it,"
1028
00:50:06.240 --> 00:50:09.150
or snails in particular will actually scrape away
1029
00:50:09.150 --> 00:50:09.990
the eelgrass tissue.
1030
00:50:09.990 --> 00:50:11.520
So it's actually a little bit translucent
1031
00:50:11.520 --> 00:50:13.830
when you hold it up to the light.
1032
00:50:13.830 --> 00:50:15.990
And so there are definitely indications
1033
00:50:15.990 --> 00:50:19.740
that, you know, like grazing that can happen.
1034
00:50:19.740 --> 00:50:23.340
And there is also bleaching. So seagrass can bleach.
1035
00:50:23.340 --> 00:50:25.650
I think it's maybe less common at our sites.
1036
00:50:25.650 --> 00:50:27.900
I know it's probably more common.
1037
00:50:27.900 --> 00:50:31.440
I've seen it a lot up in the Friday Harbor area
1038
00:50:31.440 --> 00:50:33.990
where the seagrass will actually just turn
1039
00:50:33.990 --> 00:50:36.603
kind of like a translucent light brownish.
1040
00:50:37.440 --> 00:50:39.030
And that's really just because,
1041
00:50:39.030 --> 00:50:41.310
you know, in intertidal environments,
1042
00:50:41.310 --> 00:50:43.260
you're gonna be exposed to the air, to the sun
1043
00:50:43.260 --> 00:50:45.630
for, you know, a couple hours a day.
1044
00:50:45.630 --> 00:50:47.010
And if the sun's really intense,
1045
00:50:47.010 --> 00:50:49.080
then you might end up bleaching.
1046
00:50:49.080 --> 00:50:51.600
So it is, especially I think now
1047
00:50:51.600 --> 00:50:54.780
when a disease hasn't quite ramped up yet,
1048
00:50:54.780 --> 00:50:57.660
there's been a lot of judgment calls we've had to make on,
1049
00:50:57.660 --> 00:51:01.560
is this a lesion or is this, you know, like something else?
1050
00:51:01.560 --> 00:51:03.060
And there's definitely the possibility
1051
00:51:03.060 --> 00:51:05.760
that, you know, there are other pathogens out there
1052
00:51:05.760 --> 00:51:07.620
that are infecting seagrasses
1053
00:51:07.620 --> 00:51:11.730
and might cause similar, like, visual symptoms.
1054
00:51:11.730 --> 00:51:16.350
But yeah, so definitely, definitely true
1055
00:51:16.350 --> 00:51:18.963
that there are other things out there as well.
1056
00:51:21.270 --> 00:51:23.220
All right, Brian, let's get one last question in
1057
00:51:23.220 --> 00:51:25.110
and then we'll do our wrap up slides
1058
00:51:25.110 --> 00:51:26.820
and then Serina's off the hook.
1059
00:51:26.820 --> 00:51:29.700
Lots of great questions coming through.
1060
00:51:29.700 --> 00:51:31.650
Yeah, let's see.
1061
00:51:31.650 --> 00:51:34.410
Do you see any seasonality of outbreaks
1062
00:51:34.410 --> 00:51:36.993
or increase in diseased plants?
1063
00:51:38.310 --> 00:51:40.380
Yes, so we definitely do.
1064
00:51:40.380 --> 00:51:43.620
So temperature is, I would say,
1065
00:51:43.620 --> 00:51:46.680
you know, one of the most obvious driving factors
1066
00:51:46.680 --> 00:51:47.880
in seagrass wasting disease.
1067
00:51:47.880 --> 00:51:50.400
So we definitely see kinda the prime time for disease
1068
00:51:50.400 --> 00:51:51.780
is gonna be that summer period.
1069
00:51:51.780 --> 00:51:54.360
So probably like June to August
1070
00:51:54.360 --> 00:51:56.970
is when you see a ton of disease lesions out there.
1071
00:51:56.970 --> 00:51:58.410
They're very big lesions.
1072
00:51:58.410 --> 00:52:00.513
They're, like, very obviously lesions.
1073
00:52:01.410 --> 00:52:03.720
And so there have been a lot of studies
1074
00:52:03.720 --> 00:52:05.700
kind of identifying that,
1075
00:52:05.700 --> 00:52:07.230
you know, rising ocean temperatures,
1076
00:52:07.230 --> 00:52:08.550
it puts a lot of stress on the plant.
1077
00:52:08.550 --> 00:52:11.760
And then it, you know, possibly also in general
1078
00:52:11.760 --> 00:52:13.530
has been increasing disease outbreaks,
1079
00:52:13.530 --> 00:52:15.120
not just for seagrass wasting disease,
1080
00:52:15.120 --> 00:52:17.340
but for other diseases as well.
1081
00:52:17.340 --> 00:52:20.580
And so, however, I think it's like,
1082
00:52:20.580 --> 00:52:23.580
you know, not quite a closed door answer
1083
00:52:23.580 --> 00:52:26.520
in terms of it's not just rising temperatures
1084
00:52:26.520 --> 00:52:29.070
that are affecting whether an outbreak happens or not.
1085
00:52:29.070 --> 00:52:31.980
There's probably, you know, a myriad of different factors
1086
00:52:31.980 --> 00:52:35.970
that are involved, and so it's kinda hard
1087
00:52:35.970 --> 00:52:37.417
to, like, parse through, you know, like,
1088
00:52:37.417 --> 00:52:39.810
"This is the cause," or like, "This is the reason,"
1089
00:52:39.810 --> 00:52:42.723
but we definitely do see a lot more disease in the summer.
1090
00:52:45.900 --> 00:52:46.733
Excellent.
1091
00:52:46.733 --> 00:52:49.800
Well, thank you so much for your great presentation.
1092
00:52:49.800 --> 00:52:52.710
There's been lots of kudos,
1093
00:52:52.710 --> 00:52:56.460
let me get back here to my slides, coming through.
1094
00:52:56.460 --> 00:52:58.500
So we appreciate your time, Serina.
1095
00:52:58.500 --> 00:53:02.160
It's lovely to have one of our Dr. Nancy Foster scholars
1096
00:53:02.160 --> 00:53:05.337
who's a PhD candidate presenting your research
1097
00:53:05.337 --> 00:53:09.600
and what you're finding about seagrass wasting syndrome.
1098
00:53:09.600 --> 00:53:13.170
So I wanted to just wrap up with a few slides here.
1099
00:53:13.170 --> 00:53:14.820
Don't worry about the long URL.
1100
00:53:14.820 --> 00:53:16.650
We're a typical government, everything's long,
1101
00:53:16.650 --> 00:53:18.600
the names of things and URLs,
1102
00:53:18.600 --> 00:53:20.970
but I just popped it into the chat box.
1103
00:53:20.970 --> 00:53:23.460
So an archive of today's presentation
1104
00:53:23.460 --> 00:53:27.540
will be available online within about a week
1105
00:53:27.540 --> 00:53:30.990
for you to share with colleagues or of course,
1106
00:53:30.990 --> 00:53:33.060
for those that didn't make the live presentation,
1107
00:53:33.060 --> 00:53:35.013
they'll be able to see the recording.
1108
00:53:36.240 --> 00:53:40.350
All attendees will also receive a Certificate of Attendance
1109
00:53:40.350 --> 00:53:44.220
for one contact hour of professional development.
1110
00:53:44.220 --> 00:53:46.440
So for those that are watching the recording,
1111
00:53:46.440 --> 00:53:48.180
this is where you can send an email
1112
00:53:48.180 --> 00:53:52.230
to sanctuary.education@noaa.gov
1113
00:53:52.230 --> 00:53:54.900
to ask for your Certificate of Attendance.
1114
00:53:54.900 --> 00:53:56.700
But the rest of you that are attending live,
1115
00:53:56.700 --> 00:53:58.653
this will be emailed to you tomorrow.
1116
00:53:59.730 --> 00:54:02.400
We have a great presentation coming up
1117
00:54:02.400 --> 00:54:05.970
by Dr. Julia Parrish, What's Washed In:
1118
00:54:05.970 --> 00:54:09.660
Seabirds, Marine Debris, and Citizen Science.
1119
00:54:09.660 --> 00:54:12.870
So that's gonna be occurring April 23rd.
1120
00:54:12.870 --> 00:54:15.933
You can go to our webpage to sign up.
1121
00:54:16.830 --> 00:54:18.870
And as always,
1122
00:54:18.870 --> 00:54:22.530
we've been doing this webinar series since 2016
1123
00:54:22.530 --> 00:54:25.320
and we greatly value your feedback.
1124
00:54:25.320 --> 00:54:29.130
So there's a four or five question evaluation
1125
00:54:29.130 --> 00:54:32.490
that wraps up when you close out of GoToWebinar.
1126
00:54:32.490 --> 00:54:35.550
If you wouldn't mind taking literally one
1127
00:54:35.550 --> 00:54:38.100
to one and a half minutes to complete that evaluation,
1128
00:54:38.100 --> 00:54:40.110
we would greatly appreciate it.
1129
00:54:40.110 --> 00:54:42.630
If you're a formal and informal educator,
1130
00:54:42.630 --> 00:54:46.290
there's a longer STEM multimedia distance learning
1131
00:54:46.290 --> 00:54:49.830
evaluation that I'll send in a follow-up email.
1132
00:54:49.830 --> 00:54:53.070
So with that, again, we thank you so much
1133
00:54:53.070 --> 00:54:55.950
for your attendance today.
1134
00:54:55.950 --> 00:54:58.800
We thank Serina for your great presentation,
1135
00:54:58.800 --> 00:55:02.220
Brian for joining me as webinar co-host.
1136
00:55:02.220 --> 00:55:05.880
And with that, it'll conclude today's live presentation.
1137
00:55:05.880 --> 00:55:07.713
Thank you so much. Take care.