Very excited to have Jesse Turner join us today. Jesse is currently in transition between post doctoral position at the University of Connecticut and she's starting as an assistant professor at A Dominion University in January, so congratulations on getting that position. I excited to have you in the neighborhood as well. Or future collaborations. Jessie has BA in Earth and Osographic Sciences. She also has a master's in asenography from the University of Alaska Barbans, and she obtained her PhD in 2021 in PhD Marine Science from the Virginia Institute of Marine Science, Williams and Main. And so she's going to tell us about some really excellent work she's been doing in among the West Antarctic Peninsula. So Jesse. Take it away. All right, thanks, Carlos. And while I share my screen, I also want to add that I had the pleasure of sailing with Carlos in 2021 on the Palmer LTER cruise, and one of his students, Michael has been helping out our lab at the University of Connecticut ever since. So we have this great collaboration going, and I hope we can keep it up because it's been amazing. Uh Yes. I'm going to talk today about some phytoplankton observations we've been making from satellite and what we think might be driving those changes. As Carlos said, I'm wrapping up at Yukon and I'll be starting at Old Dominion, so that's where you can find me in the future. I'd like to acknowledge that this project started as a NASA interdisciplinary science grant to a bunch of folks, and I was hired on as a postdoc. And then I've got funding to continue it through an NSF postdoc. Over the past about a year and a half. So thanks to those folks. So this is out in Rine ecology progress series if you want more information. But we're going to talk about phenology. What I mean by phonology is the timing of recurring seasonal events. So if you're a nerd like me, in the springtime, you look out your window and you think, like, Oh, the Bradford pair is blooming. It's February 26. Wow, that's three days later than last year. What's going on? And so that's on land, but we're going to think about this in the marine environment, so the blooms of the plants of the sea. But it's the same concept. The interesting thing is that in polar regions, arctic and Antarctic, the spring bloom is predicted to start earlier as the climate warms. This is a model projection of the future in less than 100 years, minus the present. And blue means an earlier start of the spring phytoplankton bloom and red means a later start of the spring phytop bloom. Just about all the polar regions are blue, meaning the bloom is predicted to start earlier. If we look at the West Antarctic Peninsula, it's certainly blue. It's supposed to be earlier as things get warmer. That's what you hear on land, too. It's warmer. Things are blooming earlier. That's the narrative. Same with this paper. The start day is over here on the y axis, and if we look at the green squares, which are for the Southern ocean, the bloom is supposedly starting earlier over time. Now, I thought, well, what about the West Antarctic Peninsula? Is that happening here? We're going to talk about that here. Here we are rezooming in to our little region here. It's a great place to do research because we have this legacy of institute observations back to the 1990s. It's rapidly warming. Sea ice is declining. Glaciers are retreating on the continent, and my group is part of a collaboration with the LT ER group to bring the ocean optics and satellite remote sensing of phytoplankton in with the rest of the team. It's been a great collaboration with existing fieldwork to bring a little bit extra into the mix for these few years. More about West Antarctic Peninsula. I said it was quickly warming. Well, this is the temperature trend over about 50 years, and you can see the West Antarctic Peninsula, is this bright red, so it's rapidly warming, and that's leading to ocean temperature increases and changes in the glacial area over the same sets of years. We're losing glacial ice on land and we're warming in the waters as well, not just the air. I like to just show a picture of this place because many of you probably have been there on this call, but it really is a spectacular ecosystem. It's like nothing I had ever seen before in my life when I went down there. What strikes me is when you go to these penguin colonies and you look out, you think what you're looking at here is rock. But that's all birds. It's all birds, and just the magnitude of biomass that can be supported by this ecosystem is tremendous. You have all the whales, you have huge amounts of penguins, you have huge swarms of rill, and it's all supported by the base of the food chain, and that is phytoplankton. That's what I'm going to be talking about today. Just to keep it in perspective just how crazy this place is. Why would we want to add some satellite data? Well, we have this awesome data from the LTR program, a very rich time series. But it is only at point locations, so the triangles and the dots are generally where things get sampled, and it is generally in the month of January, right in the middle of the summer. We want to know about the rest of the year and we want to get the whole map, not just at point locations. Satellite data offers that advantage. Just looking at some images of the Southern ocean from satellite. This is near South Georgia Island. You can see a great big iceberg that was going on in 2020. In these blooms, you can see some beautiful phytoplankton blooms from space. What else do you see in this image Clouds? It's a little bit of a challenging part of the world to do remote sensing because there are just so many clouds when you're looking at ocean color, and then not only clouds but sea ice. You need the sea ice to have retreated and you need cloud free images. It can be challenging, but it's worth it to get more spatial and temporal coverage. Just to put that in perspective. So challenges of antarctic satellite data you have four ocean color specifically. You have the sea ice, you have the clouds. You have this really high solar zenith angle. The sun is very low over the horizon and that's a long distance through Earth's atmosphere, so it's like a long path length for that light to hit the water for us to be able to see it from satellite. So we have to keep that in mind, too. That's a little different than working in the tropics, let's say, where you have a better solar angle. But the opportunities are just so great to expand the spatial coverage and expand the seasonal cycle. We can get spring and fall from satellite even in the Antarctic. When you have polar night as soon as you have enough light, you can get data. Our question was, based on this satellite data, how is the timing of phytoplankton blooms in the West Santarctic Peninsula changing over time? We thought, surely, the blooms must be starting earlier and reaching their peak chlorophyll concentration earlier because that's what everyone's saying. This is the narrative. Spoiler alert. No, this is not what we found. We found that the blooms are starting later and reaching their peak chlorophyll later over time. Near Shore, when we're looking in the nearshore environment and this is from Palmer Station. This first bloom of the season, the spring bloom that I'm talking about is mostly diatoms. There are usually these big fat, juicy, delicious chain forming diatoms like lascia sirra really great high quality food. This is what's blooming in the spring bloom happening. This is what it looks like spatially. September is spring, and then we start to get more data as the sea ice retreats in October, you can see the bloom starts offshore. And we're getting more into spring and it's starting to bloom off of the shelf break into November. As we get into December, so more summer, the bloom is moving onshore and close to the coast and then very much blooming in Marguerite Bay down in the south here. Now we're in peak summer, January. We have this like shelf and coastal bloom, and it keeps going. It's high chlorophyll all the way into March and even April when we start to lose data because of the day length. That's the typical seasonal trajectory of the spatial extent of the bloom. Another way to look at that is this is the average of each month over the long term. October conditions, general, November conditions, et cetera. You see the same thing as in the animation I just played where the bloom starts offshore and we're blooming off of the shelf break and then moves onshore and into the coast and you get these very large high biomass blooms down in the Margaret Bay, the southern area. I persists, iclopal persists all the way through into fall. I looked at this in terms of different regions. I didn't consider the whole thing one big box. I separated it out by what regions experience seasonal sea ice. This box is number one, I consider that the offshore open ocean. It doesn't experience seasonal sea ice. But then this other pie slice here is the marginal one, which does experience seasonal sea ice, but it's off the shelf break. Then the shelf I split into three regions by latitude. I'll talk about those different areas here. Left is pathometry, and the right plot is the average start date of the spring bloom. It starts offshore, moves onshore, and then the latest start dates are in the South here, what we saw before, just in different visualization. What do I mean by the marginal ice one? Well, it's the area that experiences seasonal sea ice. And it's the highest seasonal variability in sea ice cover. So it's kind of the most variable conditions in terms of, are you covered up or are you not by ice? The Antarctic like the whole continent scale, the marginal ice one is about 32% of the total sea ice cover. And the majority of the sea ice cover for West Antarctic Peninsula is a marginal ice zone environment. So it's mostly seasonal. It doesn't all go away. I mean, I mostly all goes away and comes back. It's very seasonal in the West Antarctic Peninsula. What did I use? I used satellite chlorophyll from a Gap filled product because I wanted daily data to be able to say exactly which day was the start of the bloom each year. It's a Gap filled product CMMS globe color is the name of it, I always verify that my products are as accurate as I want them to be. I compared it to the not Gap field where there was no interpolation happening and it was quite a good match, so I found this to be trustworthy. And what I mean by a g, it's a global algorithm. So it's based on how phytoplankton absorb relatively more blue light than green light, that's your global lophal algorithm is generally that. It's known to be not the best for the West Antarctic Peninsula. This is kind of an ongoing mystery of why it's a little bit off. But satellites tend to underestimate inslophal by about a factor of two. This could be something to do with the phytoplankton themselves, that pigment wise, they're a little different from the rest of the world. It's cold. You've got to be big, bad and ugly to survive. They have maybe some different pigment characteristics, some different proteins, and there's there's no major rivers going into this area. It's not like the Arctic where you have rivers dumping sediments and dissolved materials. It's really different. And so there's not a lot of dissolved organic matter or detritus or sediments to make the water look greener. It's only phytoplankton, and there are these cold tolerant phytoplankton. This is kind of ongoing work in our lab that we're looking at, why this is. But I made sure I'm corrected for it. So I just corrected for it with this known algorithm that tends to work better here. So know that it's on the order of magnitude of insitu observations, everything I'm showing. When did I look at? I split it into two decades and you might say, well, why are your decades 11 years? That isn't a decade? Well, I did a change point analysis to make sure that decades were appropriate for this. The change point was around the year 2012 for most of these sub regions, most of these polygon boxes I used. For three out of five regions, it was the year 2011, 2012. That's why I split it at that year. How did I say what is the start date of the bloom? That can actually be controversial. How do you define when does the bloom begin? I tried a lot of different ways. I tried about five different metrics for this. The most representative way, it's called threshold method where you take the long term median chlorophil plus 5%, which is this red line at the bottom here. When chlorophyll crosses that and stays above it for at least five days, I called that the start of the bloom, the peak date is pretty straightforward. It's just whenever chloroph hit its maximum for that year. These are the start dates for the different decades. Left, you have the past start dates, middle panel, you have more recent start dates, and the right panel, you have the difference, where red is a later start date. And you can see it just even in the left two where you can see that more of the shelf has a later start date, and then the difference really shows that the red area is most of the shelf and even off the shelf break is experiencing a later start date of the spring phytoplankton bloom, and upwards of 20 days in a lot of places. We're talking about two, three weeks, even a month in some places later start date. It's the same story but lagged in time with the peak date. The peak date is usually about a month after the start date, but it is also getting later over time. Again, upwards of a month later off the shelf break here. Everything in the phyto point thonology is shifting later. If you look at it by region, this is another way to look at it is the blue line is the past. The pink line is more recent, and I'll do it by each region here. For the offshore environment, they're not terribly different over time. But as soon as you get into the marginal ice zone, you see these lines separating in the spring to where the more recent years have a much later start date crossing this dotted line and throughout. Same with the Northern shelf has a little bit later of a start date. The mid shelf has quite a lot of a start date, and so does the Southern shelf. Almost all of these areas, at least the four areas that experience seasonal sea ice, the blooms are starting later. If we take statistically, the three regions where this was statistically significant were the marginal one, the Northern shelf in the mid shelf, and it was ten to 19 days later on average, so around a week and a half to 2.5 weeks later over time. One more way to look at this is if you look at the months over time, so how is the month of October changing in its chlorophyll concentration over time, where blue is less chlorophal over time and red is more chlorophyll over time. The spring, like the month of October is showing us decreasing chlorophyll over time. But the fall, which I think this is really interesting in April, for example, is showing us increasing chlorophyll over time. Just because the blooms are starting later, doesn't mean the overall biomass is decreasing. It's we're making up for that with the fall increase in chlorophyll. Everything is just happening later, including in the fall. Over time, if you looked at the whole time series of chlorophyll, is chlorophyll decreasing over time? No, it's not. There's actually no significant trend at all in the actual biomass. It's just the timing of it is shifting later, both the start of the bloom and then I don't want to say the end of the bloom because chlorophyll stays high all the way through into the fall most of the time. It was hard for me to put a bloom duration metric or anything like that. I just chose not to. But if we look at the chlorophal concentration in fall, it is increasing, which is how I would say that things are shifting later into the fall. Looking at that, and we're thinking, Okay, so they're getting later, unlike the predictions. Why? Why is everything getting later? For this, we turned to the environmental data. We looked at Par, we looked at temperature, we looked at wind speed. We thought maybe it's getting cloudier, maybe it's getting warmer or colder and that's changing things or maybe it's getting windier. Another just teaser is that Par and temperature were not really drivers of this, but wind speed certainly was. And so the seasonal cycles of PR, and we just looked in the offshore environment because looking at Par, which is think of it as incoming sunlight, photosynthetically active radiation. To get that from satellite, it's a plain parallel algorithm, so it doesn't work great when there's sea ice. So we just looked at it in the offshore environment. But in general, in the West Antarctic area, it's not really changing in its seasonal cycles. So I didn't really find that it was getting cloudier between decades per se. Se surface temperature, I didn't find any significant changes. One could argue, that maybe in some of these places, it's actually getting cooler at the surface in the summer, right? But the seasonal timing of when the cooling or warming, it warms every spring regardless, and the seasonal timing of that is not changing, but the peak summer temperature may be cooling in some of these regions, but we didn't think that would be driving the changes we're seeing in spring. So kind of ruled that out for now. But wind is intensifying wind speed. So the westerly winds, they're still westerly in the next decade, averaged over the whole decade, but they're intensified in the more recent decade, and that's associated with a positive Southern annular mode or Sam. And breaking it down by months, each one of these bars is a different month of the year, and the decreasing trends are blue bars and the increasing trends are red bars. The highest increasing wind speeds were happening in the spring months, which corresponds to what we saw. The spring wind mixing is probably inhibiting the blooming of the phytoplankton and making the blooms start later. M cartoon of this is that, let's say in the past, you have some representative lower wind speed than now. You have a fairly shallow mix layer depth as soon as you start to get towards summer that's above the critical depths and then allows the phytoplankton to bloom. Yeah. Then closer to the present, this more recent decade, we have much higher wind speeds in spring, and that is mixing the mix layer depth deeper than the critical depth, which doesn't allow for the phytoplankton to bloom. They have to essentially wait until later into the summer when enough stratification happens for them to bloom at the surface, so they're not light limited. For any people that are thinking, well, this has happened in other polar regions, for you Arctic people out there. There was something that was a lot like this that was found in the Baring sea, as you're between Alaska and Russia here. They found that in years without sea ice after mid March, so we're back to the Northern Hemisphere seasons, the spring bloom was delayed until solar heating could stratify the water column. In the same idea is that when you have more open water and the wind can mix things down, you are delaying the start of the phytoplankton bloom. We were partially satisfied by this. We said, Okay, it's most likely the wind speed. What else could we do to really dig into this to really get some more answers about why this is happening? For that, we're using a one dimensional model called the KI model. It stands for KPP Eco ice. This is by Ben Sands. If you're really into this and you like to run one D models, it's on GitHub. Just look up his name, KI and you can do it yourself. Again, KPP ecosystem ice and it's atmospheric forcing is the reanalysis product R five. It's C ice concentration in the model is forced to satellite observations, and it's initialized with temperature salinity profiles from mooring observations each summer. That's nice. The KPP is a mixing scheme from a Scott Dony model. The ecosystem model is BEC, if you're familiar with that. It has small phytoplankton, a small phytoplankton and diatom. To phytoplankton classes, a single grazer. It has nutrients, it has carbon chemistry and it has photo adaptation, which is important down in the high latitude southern notion. It has a fully coupled ice model, which is different than I've never used a one D model that has a fully ice system in it is fun, which is Siesta, which been also developed when he was working with Kevin rigo that's your details for you modeling people that might be interested. I consider these 1.5 year model runs. I becomes unstable after that because it's a nice simple accessible model. 1.5 years is great. It starts in January because that's when the mooring observations, that's when we have mooring observations is from the summer and goes for the following year and a half and I consider this first summer fall to be model spin up because I'm looking at the phytoplankton, right. Then you have your winter season, the sea ice forms, the sea ice retreats, and then I look at the following spring and summer to see what happens. I did these runs for three separate years because that way we capture the inter annual variability of the system. You have a couple of years with low ice conditions, and then one year 2011 with longer duration and higher concentration of sea ice. It's located at a great spot that I was just talking with Carlos about this same spot, about 300 100 station halfway across the Continental shelf off of Adelaide Island and right in the middle of the LTER sampling grid. We love this spot, great, very representative of the system. For each of these three years, I ran a windy experiment. I did a control run, which is what most closely resembles observations, and then I did a windy run. But I didn't just generally increase wind speed. I increased it episodically. When wind speed was high, I made it higher or made the windy times windier, if you will. This is what happened. Our control run, we have some mixer depth deepens in winter, shallows in summer. O sea ice forms and then retreats. The bloom start date for this example for the control run was December 6, just for context. That's our control run. Then when I made it windier, It's maybe too extreme of an example, but it significantly deepened the mix there depth. It changed the C i slightly, although the duration is the same because it's forced to observations. But what was interesting to me was this delayed the bloom start date by about a month. It didn't start until 7 January. That's some further evidence that wind is a very reasonable driver of a later bloom start date. I varied by year. This first year, the bloom start date was delayed by 18 days. The second year I ran was delayed by 32 days, a whole month. But this high sea ice year, it was only delayed by one day. The same story with the peak date, the maximum chlorophyll, peak of the bloom. That was delayed 15 days and three days, but was not delayed at all, zero days in the year where we had the most sea ice. The low ice years had the most delay in the phytoplankton bloom timing, probably because when you have more open water, the windier windy times, the increased episodic winds have more chance to mix that water column when you have less sea ice and more open water. Since I have time, I thought I'd throw in some more a little bit more information of what I'm working on next, which is submitted to GRL. We're thinking about, what are the implications for carbon? We know these things are happening with chlorophyll. What are the implications for carbon? When you're thinking about C two, inorganic carbon, how much CO two does the Southern ocean take up? People will give you different answers, and it depends on your method and we don't even know the sin of the Southern ocean, whether it's a net sink or a net source of CO two, and you'll get different answers from airborne observations from models and from profiling floats. It's up for debate. So we're working toward regionally, whether we can answer that question. We took some ship track CO two data from the past 20 years and looked at similar regions to what I just showed, a little different because there's not a lot of vessels going through the marginal zone and offshore over here. It's mostly the drake passage and the shelf. We had to focus on where we had good ship track data for the CO two observations. For chlorophyll, we're also using a multi sensor product, similar to what I showed before, but this is not GAT filled. The CO two data is monthly. Monthly, we don't need to fill in gaps to use monthly chlorophyll. Monthly is fine. We're using a slightly different, very similar product. What we see is and I'm still looking at the seasonal cycle, so summer is in the middle, and chlorophyll is on the top panel, and Delta PCO two is on the bottom panel. Delta PCO two indicates whether there's uptake, which is a negative or outgassing, which is a positive value. And in the Drake passage, you have, sort of a spring bloom and then kind of Peters out. It's not a very high chlorophyll concentration, and Delta PCO two doesn't show that much seasonal variability. But as you get onto the shelf, this is just striking because these things are so tightly coupled to where when the chlorophyll increases, the Delta PC two gets more negative indicating CO two uptake, and they're very tightly coupled. And I was kind of shocked by just how high the correlation coefficients were. When you think of CO two and the global ocean, folks like to focus on the physical mechanisms, the solubility, when the water is cold, you get more CO two uptake and the mixing and the physics. And that's all happening here, but the biology is playing a tremendous role in the West Antarctic Peninsula. The phytoplankton blooms are really contributing to whether the CO two, Delta PCO two is an uptake or an outgassing throughout the season and net over the year. The implications of this are if you have a year, that maybe you have a year that's a really low phytoplankton year. That could make this whole thing shift up into the outgassing portion of Delta PCO two. You could change the sign of the carbon flux if you have a no bloom or low bloom year, or vice versa, if you have a really high biomass year, very productive, that could increase your carbon uptake. It's really more dramatic than I had anticipated. If you take all those points I just showed and just plot them against one another. You get a pretty tight relationship and it doesn't really vary by decade. It's just both decades over time. You're seeing as soon as you get over a clopal concentration of about one, you have a net CO two uptake, which is really interesting to think about. That's ongoing work I'm working on. I wanted to throw that in here as a little bit of a bonus. Yes. Before I finish up, I want to say that I'm actively recruiting students for fall 2025 and Fall 2026 when I start at ODU. If you are finishing up a master's and you know you want to keep going with grad school, or if you are an undergrad or know of an undergrad that really wants to go to grad school and is interested in polar work, or I also work in Chesapeake Bay locally, Coastal or Polar work, please contact me and we'll be in touch. I'd like to thank all my collaborators on this work, and thank you for your time. Thanks, Jessie. This look great. Okay. We have a question from Matt Oliver. Yeah, I meant to put the clapping hands up, but I met Raise hand. But hey, so that was really great, Jessie. Enjoy your talk as usual. Hey, so I guess I'll ask the first question if that's okay, Carlos. Okay. So I'm totally on board with what you're saying about the increase in wind. We had a student here. Actually, Carlos was on his committee and we looked at we weren't looking at coastal regions. We were looking at the Southern Ocean in general, and we saw that higher current speeds, which are mostly Eckman driven in the Southern Ocean, certainly reduce chlorophil concentrations. And so we were using not wind but current velocities from the Oscar product as a proxy for mixing. And so our argument was that it doesn't matter if you have iron, you still have these crazy light limitation effects that are happening in the Southern ocean. And so I totally believe what you're talking about here with increased wind. My question for you is when you go back and look at your one D results. If you can go back to that. Yeah. And this is always a debate that we have in the biological oceanography class, which is when you're going to decide the bloom is going to start and how that relates to mixed layer, right? So I think, Like, Mike Brenfeld, would say, actually, your bloom is starting in October. Right. And the mixed layer depth is still going down. And so the control here is not wind, it's the release of grazing pressure due to dilution, right? And that was kind of history in the North Atlantic. And I kind of wonder what you would then, you have a bloom date there that's ten to the zero, so that's one. Like, can you talk about that a little bit that clearly starts when the mix layer shallows? And so it seems like that a lot of the interpretation around phonology is going to be dependent on when you think this event starts. And it feels like that that is still an ongoing conversation even when we talk about the North Atlantic, right? So, could you comment on that? Sure. Yeah, that's a great point. And I do want to throw in that I tried this with the grazer turned off and I got the same result. That's processing. But that could be something happening in the model as well. But what you're saying is very important. And I want to go back to actually this figure, it bear with me? Here. My dotted line here is this threshold method I used. But if I used another one, like a more barren feld friendly like one of his metrics, I can't remember what they're called because I did this a couple of years ago, but uses more of the rate of change and things that lowers this point, and it makes it an earlier bloom start date, like you said. It's what I consider this to be the threshold method is phytoplankton accumulation. When the accumulation is greater than the lost term, you can define that when the lost term reaches a minimum or something and that will make it earlier. But I'm limited by my method in this case. So if I had blighters or floats or cruise data from the whole spring season, I could do a better job of defining the start of the bloom, but I only have the surface. So I have to go by when the satellite surface that little surface layer of the ocean, when the chlorophyll increases there. And for that, the threshold method was the most appropriate. But if you had down into depth, I think you could define an earlier start date as far as what method you're using to define that. Maybe maybe we would have different results. But if you just look at these figures for a while, It's still even if you look earlier in the season, let's say you do call the bloom start date, October. October in recent years in the mid shelf is still lower chloropil than in the past years. So I think we maybe get similar results, but that is a really important point for people to think about. I think you're right. I think you would get a change in phonology, but I think the explanation for the change might change. Whether or not it is physically forced, which is kind of my default setting or whether or not there's this weird grazer right? You know, release of grazing pressure, that that's kind of more on the like modifying the lost terms. Right than modifying the modifying the growth terms. Yeah, it's a good point. And we don't have that I know of because the cruise goes out and measures Zoplnkton every January. We don't have very good grazing data for the spring. Well, yeah. I don't know if we have very good respiration data in general. Yeah. Right. So I feel like that's always kind of been this well, always. That feels like the sticking point. In fact, I think, wasn't Q Duclos on the call, and he wrote a nice review on that. Yeah. Yeah, you know, back in annual reviews. Yeah, anyway, I totally believe the mechanism and I'm tickled to see that the stuff that we saw offshore is also a big deal onshore. I think that makes sense to me being down there. So on congrats congrats on your new position, too. Thanks. A here. Actually, I have a question for you, Jesse. Sure. First of all, tremendous job. Great to see the way work done at Pomerlt to ER is just exploding and quality and interest and you're part of that. My question is maybe a great question for a satellite person, but I wonder if you can say anything about changing phytoplankton community composition that might be going along in concert with these other changes. Yes, thank you for asking that because that's actually what I'm working on right now. I wonder if I have a slide on it. I don't have a slide on it. But yes, we're looking at that now and partly because we now have this new satellite that can help us look at phytoplankton community composition. I of course want to map it throughout the whole season. So I need the satellite. Yeah, There's basically your big players are your cryptophytes, and your diatoms, what Oscar's group seems to have found is that when you have high phytopton biomass, when you have a big bloom year, you have a lot of diatoms and when you have low phytoplyton biomass, you have less diatoms, but you still have this background mixed flagulates, and you still maybe have some cryptophytes. The timing offshore anyway, we just don't have the data yet until we can map it from this pace satellite to show us the exact seasonal succession and whether the seasonal succession is changing. As far as I know, the going thought is that the first offshore bloom way off the shelf break that is sometimes phocysts rather than diatoms, and then the diatoms are happening on the shelf and closer to shore. We're really looking forward to mapping that. I'm actually looking at the calendar like, Okay, We're getting into summer down there, spring summer. When can I start to look at the pace data and see what's happening because it was launched in April. That was just the very end of the austral season down there. Skyler Nard, trying to think of her work with Phytoplankton community. At Palmer Station, she saw throughout several years that even if the timing of when the when the bloom started changed, you still had that first bloom of the year was diatoms. In the middle of the summer, you had more cryptophytes. Then in the fall, you had diatoms, but they were smaller size diatoms in the fall? That pattern persisted even if it shifted in timing, if that makes sense. Her data is the best so far that we have on that. But looking forward to looking at some more. All right. James, you have a question for Jessie? Yeah. Really interesting work. Because I don't know this at all. I'm going to ask sort of a clarifying question and maybe a background question. I thought when you were looking at the difference in wind speeds, it was differences on the order of 0.6%. So it was less than 1%. Does that match what you put into the one D model? And can you get the scale of Changes that you see from the scale of wind speed changes that you've observed. And the related questions, I assume that the grazers are coming in from outside of each grid cell. So what are we missing from the one D model? Could that Do you expect that to be part of what explains this or do you think that basically the wind is 100% of the explanation? Yeah. Yeah, those are great questions. Thank you. The wind speed. What I showed was the long term trend and it was a small change. It was generally a small change in wind speed. What I didn't put in is because I found it hard with one D is the change in direction. And so if you have slightly higher wind speeds, but they're all from the same direction and they're pushing away ice and you have all this open water, that's going to probably make more of a difference to the mixed layer depth. Um, so I didn't have that factored in. And I tried a lot of different increases, as far as how much I was increasing the wind speed when I did my modeling. And you're right, no, with a very, very small increase in wind speed, you didn't see very much of the delay in the start gate of the phytoplankton bloom. But it was always applied episodically. And so the way I think of that is that most of the time, if the wind speed doesn't increase over my threshold, The wind speed didn't increase in my windy run. If you take the long term average, that probably isn't that much of an increase in wind speed on the long term. But those episodic events are significantly increased. I don't know if that answers that question. That food factor into the graphs I showed on how wind speed is changing over time. Those are long term averages. Those aren't encapsulating those episodic events. That's one way to think of why those seem relatively small. And your other question was about the grazing in the model. I'm wondering, are there nutrients that are coming in from outside? What's determining these you know, when these blooms happen other than just mixin layers. It's pretty simplified. I mean, that's the downfall of the one D model is we're missing a lot of the horizontal infection. And I don't have the details in front of me to answer your question in a detailed way, but I do think we're probably missing some things without those horizontal infection terms. There are some in there as far as the physics, like the KPP physics part of the model has invection, but I don't know that the biogeochemistry does. Yeah, that's a good point. Worth thinking about. Thanks. Thanks. Thanks. Both, do you have a question for Jesse? Yeah. Thank you, door Turner for the rat tut. I'm glad to see those strat relations between the tub uptake and the biology. As a tub person myself, do you happen to know if there's any similar relationship in the arctic region Beta also mentioned there's the same photoplanton bloom in the arctic region. That's a great question. The short answer is I don't know about the Arctic. There's someone from the North Atlantic Ocean that does this work. I'm not really a carbon person that's a little out of my wheelhouse, but our project, our greater collaboration project has been working on this. I just decided to be the leader on that little set of things. It's a little out of my wheelhouse. But the North Atlantic person I was talking about said she was finding similar things where the windier years were showing a different pattern. But she didn't have a lot of figures, so I don't have a good example for you, but I'm not sure. That's worth looking into. T hanks for that. Thanks, well. So I have a question related to this kind of migration of the bloom kind of onshore and the timing. I guess, you know, and this goes back to, I think, both Matt and James's questions about what is driving these changes. On one, I think, clear difference between these two regions is that the near shore region is probably much more heavily impacted by melting from land. And so the controls on the timing and kind of the drivers of the evolution of the mixed layer are different. And because it's in nearshore is probably less driven by sea ice and more driven by melting from the continent, that also means that, W D model wouldn't capture that because it's not included. So do you have any thoughts about that or how we can make progress maybe? Let's see if I can show So yes, you're right, and a lot of my most significant results or most substantial results were at the shelf and the shelf break. And if you look at the coast, it's quite patchy in some places where even the bloom start dates were a little bit earlier. So taken as an average, the start dates are getting later. But in these specific little regions and, you know, very little smaller areas, it's not as straightforward, and I think that's because of what you're saying. So that's one thing I ran into. See this shows it a little bit too, like, up in this northern area, it's not necessarily getting later, and it's not as clear a story along the coast as it is in the shelf break marginal one area. So I think that's part of it. And then as far as modeling it, That's one thing on my list of things to try with this one D model is it's built on the shelf, mid shelf. But if I could initialize it with conditions that were more representative of a coastal station that has a glacial meltwater input and show that strong stratification at the surface, that might be a good way to try that. That's on my list, things to try with that. A good point. Thanks, Jesse. Do you have any other questions for Jesse at this point? Well, thanks, Essie. That was great. That was super fun. And yeah, thank you for your time today, and thanks everyone else for coming to the seminar. And I guess we'll see you next week. Thanks.
Jessie Turner - SMSP Fall Seminar Series 2024
From Taylor Link October 25, 2024
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"Changing Phenology of West Antarctic Peninsula Phytoplankton and Environmental Drivers"
Zoom Recording ID: 99179954296 UUID: H7oq/yfSRNO5XGNV3eXBSA== Meeting Time: 2024-10-25 03:51:12pmGMT
Jessie Turner
Postdoctoral Research Associate
University of Connecticut
October 25, 2024, 12:00 PM
ZOOM ONLY
Hosted by Carlos Moffat
Abstract: Shifts in phenology, the timing of annually occurring biological events, are being altered in the global ocean with climate change. The timing and magnitude of phytoplankton blooms in the marginal ice zone are critical drivers of carbon uptake and food quality for higher trophic levels. We examined phenological changes in the phytoplankton accumulation season in a polar region using long-term patterns in satellite-derived chlorophyll-a concentration. A merged multi-sensor cloud-filled remote sensing dataset was analyzed to determine shifts in the phenology of the phytoplankton growing season from 1997-2021 for the West Antarctic Peninsula, a rapidly warming ocean region. In spring, the phytoplankton accumulation season is beginning later in the season over time, initiating up to three weeks later in recent years compared to the late 1990s. In fall, the marginal ice zone is experiencing elevated surface chlorophyll concentrations during recent years compared to the past. Correspondingly, the seasonality of the air-sea CO2 flux has also shifted, showing evidence of a longer-lasting CO2 sink extending later into the fall. Possible mechanisms for spring shifts include increased wind speed and decreased ice-associated early season water column stability. Possible mechanisms for fall shifts include later sea ice advance and nutrient availability during the extended ice-free season. Mechanisms were tested with coupled physical-biogeochemical modeling experiments, using an ice-ocean-ecosystem model and an advanced data-assimilative ocean biogeochemistry model. Experiments included scenarios with varying mixed layer depths and wind conditions, including higher wind speeds during episodic windy storm events. Modeling experiments suggest that increased wind speed is one likely mechanism for the observed changes in the spring season. Observed shifts in phytoplankton phenology will have important implications for carbon cycling and food web dynamics.
Zoom Recording ID: 99179954296 UUID: H7oq/yfSRNO5XGNV3eXBSA== Meeting Time: 2024-10-25 03:51:12pmGMT
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