- [Announcer] This conference will now be recorded.

- [Heather Tabisola] All right, let's get started. Good morning, everybody and welcome to another EcoFOCI Seminar Series. I am Heather Tabisola and I'm joined with Jens Nielsen and together we co-lead the seminar series. So this seminar is part of NOAA's EcoFOCI bi-annual seminar series focused on the ecosystems of the North Pacific Ocean, Bering Sea and U.S. Arctic to improve understanding of ecosystem dynamics and applications of that understanding for the management of living marine resources. Since 1986, the seminar has provided an opportunity for research scientists and practitioners to meet, dissent and provoke conversation on subjects pertaining to fisheries, oceanography or regional issues in Alaska's marine ecosystems. You can visit the EcoFOCI webpage for more information at www.ecofoci.noaa.gov. And again, we really thank all of you for continuing to join us. I know it's a virtual seminar. It's probably getting longer and taxing on everyone but we really, really do appreciate you being here supporting our speakers and just coming together. You can find our lineup on the OneNOAA Seminar Series and also on the NOAA/PMEL calendar of events. Join us here at 10:00 AM on Wednesdays through the end of this month. And if you missed a seminar, you can catch up on our YouTube page, PMEL's website. It does take a few weeks to get these posted but just give us a shout out and we'll let you know when they are updated. Please, everyone double check your microphones that they are muted and that you do not have on video. And during the talk, please feel free to type your questions into the chat, and both Jens and I will make sure to address those at the end of the talk. So today we are welcoming Dr. Mariela Brooks. She's a research chemist at the Alaska Fisheries Science Center in Juneau, Alaska. Today, she's going to be talking about upper ocean carbon-cycle dynamics and more specifically, experience looking at the Hawaii Ocean Time-series and Bermuda Atlantic Time-series Stations. Mariela works in RECA, so the Recruitment Energetics and Coastal Assessment program, focusing on stable isotope analysis and examining biogeochemical drivers of marine fisheries and trophic ecology, as well as exploring new analysis techniques and method development. Prior to joining AFSE, she had her doctoral research focused on Open Ocean Time-series measurements for both HOT and BATS using inorganic carbon chemistry and stable carbon isotopes to better understand upper ocean carbon-cycle dynamics. She received for her bachelor's of science in physics from Portland State University and studied marine chemistry at Scripps, where she received both her master's in earth sciences and PhD in oceanography. And with that, I'm really excited to hand it over to you Mariela.

- [Mariela Brooks] Wonderful, I'll just go ahead and get started, if my presentation will advance. Let's see, there we go. Okay, so thank you so much for that introduction. And as she mentioned, I recently started my position with NOAA but today I'm going to be talking about my doctoral research and that work was supported in large part by the Schmidt Family Foundation, the National Science Foundation and the National Center for Atmospheric Research. And that was all conducted with support from the Scripps Institution of Oceanography as well. And so today I'm gonna be focusing on inorganic carbon chemistry in the upper ocean, out in the open ocean, looking at changes in stable isotopes and dissolved inorganic carbon concentrations over the past three decades. So to get started thinking about the carbon cycle and how this interacts with the ocean, one of the important things to consider is what happens to carbon dioxide when it enters the surface ocean. And so this is important because in addition to sort of overall natural carbon uptake in the ocean, there's also an additional anthropogenic signal in which the ocean takes up about a quarter of the anthropogenic carbon emissions that we are putting into the atmosphere. And so when carbon dioxide enters the ocean it undergoes a series of equilibrium reactions. And one of these sort of important components is thinking about dissolved inorganic carbon, which is the pool of carbon dioxide, bicarbonate and carbonate ions. And essentially in this process of air-sea gas exchange and carbon uptake, the ocean removes carbon dioxide that otherwise might've contributed to warming in the atmosphere which is a positive thing for long-term climate change. But in addition to that, this increase of carbon dioxide in the ocean also leads to a reduction in pH or ocean acidification impacts. And so understanding how that may be changing over time and also overall what the different aspects of both natural and anthropogenic impacts of this approach and carbon cycle is important to understand. And so to do this, we look at dissolved inorganic carbon, as well as stable carbon isotopes of dissolved inorganic carbon. And so we measure both of these parameters to sort of better understand the carbon cycle. And using the combination of dissolved inorganic carbon as well as the stable carbon isotopes or delta C-13, we can understand sort of a combination of factors. And the benefit of using the stable carbon isotopes is that it's much less sensitive to sea surface temperature changes and this leads to quite a few different things but that includes difference in equilibration timescales. And so dissolved inorganic carbon equilibrates with the surface ocean over the timescale of about one year whereas delta C-13 takes about 10 years. And so that leads to different uptake signals and pathways. And then in addition to air-sea gas exchange, each of these variables also is impacted by a suite of different physical processes including horizontal advection, vertical diffusion, and mixing with layers beneath the surface mixed layer as well as biological impacts and due to photosynthesis or respiration of different biological sources in the surface mixed layer. In addition to being less sensitive to sea surface temperature, the delta C-13 value actually carries an atmospheric signal from anthropogenic emissions. And so as we continue to emit carbon dioxide into the atmosphere through the combustion of fossil fuels, this is actually impacting that signal of delta C-13 in the atmosphere, and so this depletes or decreases the isotopic values in the atmosphere and we can see those decreases reflected in the surface ocean as well. And so this helps us to kind of understand certain aspects of the anthropogenic signal. And again, there's a biological forcing on both the inorganic carbon and delta C-13 values in different ways. And so during photosynthesis you have uptake of carbon dioxide but there's also an impact on the stable carbon isotopes because there's a preferential use of lighter isotopes. And so you end up with a difference in isotopic signature both in the organic matter as well as in the dissolved inorganic carbon that remains in the surface mixed layer. And so looking at a combination of all of these factors, we can sort of understand better what's happening in this surface mixed layer. And so one of the sort of main pieces that we look to understand is sort of, what are the dominant drivers of carbon cycle variability and how can we understand how these may change over time? And so to do this part, the work that I've done is to take advantage of the long-term time-series stations located in the oligotrophic gyres in the North Atlantic and the North Pacific. And so, and the North Atlantic, we have Station S and the Bermuda Atlantic Time-series Station. And these are two stations located off the coast of Bermuda, and these have been in place since the early 80s for Station S and the late 80s for BATS. And then the HOT station ALOHA in the North Pacific Subtropical Gyre has also been in place since the late 80s. And so these stations are both located in the subtropical gyres. However, there are many physical differences in the oceanographic parameters and also there's a significant differences in terms of overall circulation patterns and biological forcing in these regions, and so it's very interesting to be able to compare between these two. And so the three core measurements that was part of the work that I did at Scripps was measuring the dissolved inorganic carbon concentrations as well as the stable isotopes in delta C-13 for dissolved inorganic carbon. And we also made alkalinity measurements, although today, I won't be talking about that as much. And this was primarily used in this case to just give us confidence that there was no additional consideration that needed to be made for significant shifts in alkalinity. And so the time-series here show the measurements of dissolved inorganic carbon at each of the stations. So we have the HOT station ALOHA on the left and the Bermuda stations on the right. A few things to note. So the top panel is dissolved inorganic carbon that has been solidity normalized, and this is done to remove potential impacts on the concentration values due to precipitation or evaporation solely. And in addition to that, these are all surface measurements taken from somewhere between five and 10 meters. And the Bermuda data set was combined because they were found to be essentially... They're very closely located and they're consistent between the two. And so we have the Bermuda Atlantic Time-series Station as well, the station has combined into one long record. And in addition to that, on the lower panels we can see the delta C-13 values over the course of the records for both the HOT station, as well as BATS. And initially just looking at these time-series, there's a few things to point out one of which that it's possible to see sort of these long-term records or long-term trends in the records as well as seasonal cycle and inter-annual variability that are super imposed on these. And another thing to point out is that the isotope records during the time that I spent at Scripps were able to be extended through the end of 2017 and so we now have approximately between 20 to 30 years at each of these stations. And so one of the first things that we wanted to consider was looking at these long-term trends in both the DIC and delta C-13. So looking at the long-term trends here, this is the same data set that I was showing before. Again, Hawaii is on the left, Bermuda is on the right, and this is the salinity normalized DIC values shown here in teal. And for these values have had the mean seasonal cycle has been removed. And so we used a set of 12, six and four-month harmonics to remove the seasonal cycle and leaving the longterm trends with the inter-annual variability is also evident in these still. And so one thing that we can note here is that these long-term trends are just, are shown here. That are the strong reflection of the anthropogenic carbon trends in the atmosphere. And so the overall trends match very much what we would expect if the seawater was fully equilibrated with the atmosphere. And so we can see that the trends that we observe in the atmosphere are very much shown in the surface water. And if we also look at these stable isotopes here, again this has had the mean seasonal cycle removed. And so on the left hand side of the y-axis in purple we can see the seawater values for delta C-13. And then the right side of the y-axis is the atmospheric values for delta C-13, and the overall signature for the isotopes are different. However, it's important to know that the scale for each of these is the same. So what we're seeing here is a very similar trend in both the DIC values and delta C-13 values relative to the atmospheric trends. And so if we take this a step further and decompose the time-series, and here we're gonna focus on looking at the inter-annual variability at Bermuda. So again, this is the same time-series with the mean seasonal cycle removed but we've also gone ahead and removed the long-term trends. And so this, we use the residual anomalies of inter-annual variability that we see at this station. And here again, the top panel shows the variability in dissolved inorganic carbon. The second panel is showing variability in delta C-13 or the stable carbon isotopes. And the bottom two panels show the mixed layer depth or MLD, and then the sea surface temperature values. And so one of the... Looking at sort of the relationships between some of these oceanographic measurements in these regions and the variability that we see in each of these parameters, we looked to see what correlation we might be able to see. And so at this in the North Atlantic at these stations, we see some correlation between the delta C-13 and DIC values as well as between delta C-13 and sea surface temperatures. And there's also some correlation between the dissolved inorganic carbon and sea surface temperatures, as well as with the mixed layer depth. And so the combination of these correlations suggest that there's strong vertical mixing driving variability on these timescales because of the relationship between the sea surface temperature variability as well as the mixed layer depth. And this has a lot to do with as you get colder temperatures and a very deep mixed layer depth that reached below the surface mixed layer, you're bringing up a lot of DIC rich water from below the mixed layer, and this would also be very depleted in delta C-13 due to remineralization of organic matter below the mixed layer. And in addition to that, especially for the DIC sensitivity to sea surface temperature as you're getting cooler temperatures you would be able to get a much larger amount of DIC uptake in that region or carbon dioxide uptake in that region. In addition to that, we also see some strong correlation with the North Atlantic Oscillation. And I'll talk about that a little bit later but it's important to know that sort of this supports this idea of vertical mixing sort of driving these parameters. And this agrees with some earlier studies by various groups in the North Atlantic near at these stations. And so if we then look at the similar relationships of trying to understand variability on inter-annual timescales at these stations, we can look at the variability at the Hawaii Ocean Time-series. And again so this is showing you the dissolved inorganic carbon, delta C-13, mixed layer depth, and sea surface temperature, residual anomalies with the seasonal cycle removed, with the long-term trends removed. And what we see is a slightly different story here. And so we don't see correlations that are quite as strong in that. And for example, for the stable carbon isotopes, we're not actually seeing any correlation with the other oceanographic variables in this region. We do see some correlation between dissolved inorganic carbon and sea surface temperature which is not overly surprising again, due to the sensitivity that carbon uptake has to sea surface temperature. And we also see some relationship with the mixed layer depth. But overall, the lack of coordination between the delta C-13 value or a correlation between the delta C-13 values and these variables helps to indicate that vertical mixing is likely not actually the dominant driver on these inter-annual timescales or at least there's some other aspect to be considered in these regions. That being said, over the course of these terms, sea records, they do seem to be some infrequent or short-term vertical mixing events. And so one good example of this is in 2012. You can see in the sort of highlighted section there that there was a negative anomaly in sea surface temperature and a deepening of the mixed layer depth that was showing some of the deeper mixed layer depths that we see in this region. And that had a corresponding increase in dissolved inorganic carbon and decrease in delta C-13. And this is sort of the relationship that we would expect given, again, the equilibration or sensitivity of uptake with dissolved inorganic carbon in relation to sea surface temperature and also that vertical gradient that you would see in DIC and delta C-13. So an increase in DIC and a decrease in delta C-13 as a result of mixing from below the mixed layer. And in addition to that we can also see an interesting subsequent relationship with the North Pacific warm anomaly that occurred over 2013 to 2015, which as many of you are probably familiar, developed in the Gulf of Alaska, and it subsequently propagated down the West coast of the United States and made its way down to the subtropical gyre region near Hawaii as well. And we can actually see this reflected in the time series where after that vertical mixing event, there was a subsequent rapid increase in sea surface temperature shallowing of mixed layer depth and off-gassing of DIC and subsequent return to sort of the different values for delta C-13. And so one of the... Again in trying to understand sort of these drivers of variability one of the next steps that we were able to do was to work with the National Center for Atmospheric Research Community Earth System model, so we worked with the CD-CESM2. And here I'm showing values of both DIC and delta C-13 and the North Pacific and the North Atlantic from a pre-industrial hindcast simulation. These are showing just a climatological mean from 1960 to 2009, over a sort of this 10 to 20 meter depth in the surface ocean. And so this allowed us to sort of look at placing these time-series station in the broader context of the gyre regions. And so under trying to understand, in addition to what the driving mechanisms are for variability also, how does that relate to different spatial scales and what possible connections might we have to these different climate modes of variability in the region? And so, again, thinking about sort of what might be driving these patterns of variability that we see on different temporal and spatial scales, this figure shows a property-property plot looking at dissolved inorganic carbon and delta C-13 on the y-axis. And so this shows the relationship between DIC and delta C-13. The solid lines and data points in black are the observations. And so the solid lines show the observed seasonal cycle and then the data points that are the field circles show the observed inter-annual variability. And then the model results are shown in teal. And so again, the solid line shows the seasonal cycle, the data points show the inter-annual variability, and then the dashed line there shows the relationship with the vertical profile in the model from 1-200 meters. And so something that is important to note is that the relationship between DIC and delta C-13 seems to be relatively well captured by the model, which is confidence inducing in terms of being able to infer further relationships between these. And in addition to that, it seems like both on the seasonal as well as the inter-annual timescales, the relationship between delta C-13 and DIC is very consistent with what we see in the vertical profile. And so again, this lands credence to this idea that vertical mixing really dominates variability in the North Atlantic at the time-series station at BATS. And in addition to that, there's this relationship with the North Atlantic oscillation to consider. And so this is a schematic from a Grubel et al, 2002 paper looking at how these different modes of the North Atlantic Oscillation might impact seasonality and overall upper carbon-cycle dynamics in this region. And so during the positive North Atlantic Oscillation, we have positive SST anomalies or warmer water, and so shallower mixed layer depths, less mixing. And this lends itself to a smaller seasonal cycle and just overall a negative anomaly in DIC. And also a reduction in that community production and mixing down below and a reduction in air-sea gas exchange. Conversely, if you look at the period of negative North Atlantic Oscillation, this leads primarily to sort of this negative anomaly and sea surface temperature, much cooler waters, it tends to be much stormier. And so you have a lot more mixing going on in the surface mixed layer both in terms of air-sea gas exchange, but also in terms of development of very, very deep winter mixed layer depth that entrain DIC rich and depleted delta C-13 values from below the mixed layer depth. And it's also been shown that there's enhanced net community production during this time. And so there's a lot going on that leads to a much larger seasonal cycle and a stronger variability during that time. And so again, thinking about sort of placing these time-series stations in the context of the broader gyre is because it's wonderful to learn about what's happening at these time-series stations but it's also important to understand the value of potentially being able to extrapolate estimates across to the broader gyre scale dynamics. And so one of the things that we did in terms of looking at the overall model results is looking at in the North Atlantic, and correlating that with the variability that we observe across the rest of the North Pacific, and so, or sorry, the North Atlantic. And so what this shows is there's generally a significant positive correlation within the subtropical gyre near BATS. And so this is not surprising that you have stronger correlation that then radiates out in a gradient from the station. But it also shows that there's actually some good agreement in the variability that we see at BATS. And so it lends confidence to being able to expand estimates to the broader gyre regions of the observations in this area. And then we also looked at correlations between the North Atlantic Oscillation in this region and the DIC and delta C-13 variability. And this shows that across the gyre it does seem the DIC and delta C-13 to different extents seem to have correlation and variability with the North Atlantic Oscillation as well. So it seems like the overall dynamic in this region is both fairly well-represented by the station, but also impacted across the majority of the gyre by this climate mode of variability. And so doing a similar analysis at HOT suggests, again a more complicated story in this area. And so looking at the relationship between DIC and delta C-13 at this location, we can see that the inter-annual variability, which again is shown in these filled circles, observations are in black, modeled results are in teal, are nearly orthogonal to the vertical gradient in this region. And the seasonal cycle seems to be lying somewhere between this vertical gradient and the inter-annual variability forcing. And so it suggests that there's more likely to be biologically driven with some weak vertical mixing on seasonal timescales and some advection as well. But thinking about what's actually driving the variability again and thinking about what's happening on this inter-annual timescale. 

- [Jens] Mariela?

- [Mariela] ...Axis.

- [Jens] Sorry, Mariela. We'll have to do a short pause there 'cause I think people lost your slides.

- [Mariela] Oh oh!

- [Heather] We lost your video first and I really didn't wanna stop you 'cause you're on a roll.

- [Mariela] No worries! Let me see if I can find you.

- [Heather] It just stopped on this lovely North Atlantic BATS. And then I'm assuming that what you're talking about was supposed to be popping up on the bottom of the slide, but it didn't.

- [Mariela] Let's see.

- [Heather] That's funny, maybe if we stop presenting to you for a second and we... That will kick in here. So let me... I'm just gonna try something... Mariela, don't freak out.

- [Mariela] No worries.

- [Heather] Oh, that was not the right thing to do. Okay, hold on, I'm gonna pause all of that, this is... Jens, I kicked her out by accident.

- [Announcer] This conference will now be recorded.

- [Heather] Oh my goodness, everybody, I'm so sorry. I just kicked Mariela out by accident.

- [Jens] We should bring her back.

- [Heather] I don't know, I mean, there she is! Okay, hi!

- Welcome.

- [Heather] Okay, now I'm gonna make you a presenter again.

- [Mariela] Wonderful. It looks like my camera's working again, which is-

- [Heather] Yeah.

- Convincing .

- [Heather] Yeah, you're a presenter, it should be good. I did not mean to kick you out, but I'm hoping it worked.

- [Mariela] No worries.

- [Heather] Okay, are you...I don't see the slides. I see you.

- [Mariela] Did you send me the offer to share my slides? 'Cause I'm not seeing that.

- [Heather] Oh, no, it says you are the presenter.

- [Mariela] Oh, there we go.

- [Heather] Okay good.

- [Mariela] Success?

- [Heather] Yeah, success, thank you. I'm so sorry.

- [Mariela] No problem . Is this where I was when you last saw me perhaps?

- [Heather] We saw that... Yes, I don't think, I never saw the bottom two images-

- Great.

- [Heather] But yeah.

- [Mariela] Okay, but you can see them now?

- [Heather] Yes.

- [Mariela] Okay, wonderful. Okay, well, so hopefully what I was saying makes a little more sense now. So again, these bottom two panels are the correlation with the North Atlantic Oscillation. And this is just showing sort of fairly coherent patterns of variability between the North Atlantic Oscillation and the gyre region variability for DIC and delta C-13. Which is again, sort of supporting this idea of the location of BATS being fairly representative of the overall gyre. Okay, so hopefully you are continuing to see these transitions, but so moving over to the Hawaii location, this is what I was moving on to talk about, which shows a difference in the relationship between DIC and delta C-13. And so this shows this inter-annual variability that is very different, again, from what we were seeing before in the North Atlantic. And so this shows the relationship between DIC and delta C-13 which is nearly orthogonal to the vertical gradient in this region. And then the seasonal cycle is also on a slightly different slope, which suggests sort of more of a direction from biologically driven variability and then some potential weak vertical mixing and advection on the seasonal timescales. And so to try to pull apart what's occurring on these inter-annual timescales, we took this a step further and one of the things that we did, so again, the property-property plot of DIC and delta C-13 at HOT. So the black field data points show the inter-annual variability at HOT. And then these multicolored open circles are the variability of varying grid cells along a transect. And so this particular figure shows a North-South transect that intersects with HOT in the region. And it does not seem like there's a very much of a relationship between these two. And then if we look at the East-West transect at HOT, it seems like there's at least variability occurring along a similar slope. And so this is suggesting more of a driver of variability from a source of lateral horizontal advection or potential circulation shifts in the gyre on these inter-annual timescales. And so there've been earlier studies from sort of this complication in understanding inter-annual variability in this region. And it has been suggested that sort of horizontal advection and potentially shifts in the circulation could play a role. And so this definitely supports that idea from what we see in the model results as well. But again, how does this actually relate to the broader spatial scale? So understanding something beyond just the time-series station itself. And so this these maps show the North Pacific concentration values of dissolved inorganic carbon and sea surface temperature. And so this really shows the sensitivity to sea surface temperature the dissolved inorganic carbon has. And it also shows the gradient of DIC in the region which is actually quite a significant relative to what we see in delta C-13. And so delta C-13 has a much weaker overall gradient in the different values that we see across the North Pacific. And it also, the patterns that we see in those concentrations are clearly not strongly tied to the sea surface temperature values that we see in the upper right. And so, in addition to all of this, this is a gyre region. And so it's important to consider the circulation patterns and what the... And so this shows on the bottom right the mean velocity field in the surface layer there. And I don't think I have the units there, but those velocity values are in centimeters per second. And so this potentially could explain some of the variability if we think about shifts in the water origin and where exactly that overall mean velocity field is hitting the time-series station just North of the Hawaiian Islands there. And so looking, thinking about sort of those concentration maps and thinking about the circulation patterns in the region, we also looked at the correlation similarly to how we looked in the North Atlantic between the dissolved inorganic carbon and delta C-13 variability at HOT and correlating that with the variability that we see across these gyre regions. And so this shows correlation within the subtropical gyre for DIC that occurs in a bi-modal pattern. So you have this positive correlation in and around the time-series station and the negative correlation sort of to the North Northwest of that location in this very region. Whereas we have some significant positive correlation close to Hawaii for a delta C-13, but this is occurring primarily along sort of the circulation path, the flowing from the Northeast down sort of and to the West and slightly South region. And so if we try to understand this bi-modal pattern that we're seeing in the DIC values, one of the pieces that we looked at in this region was the Pacific Decadal Oscillation. So we correlated the Pacific Decadal Oscillation with dissolved inorganic carbon and delta C-13 across the North Pacific basin. And so the correlation there also shows this bi-modal pattern, which is not overly surprising, again, due to the sensitivity to sea surface temperature changes especially for dissolved inorganic carbon. And so you can see that HOT is sort of located right in the mix of this bi-modal pattern in the subtropical gyre there in the North Pacific. And so thinking about how the variability in the North Pacific is linked to climate indices, we looked at the Pacific Decadal Oscillation, we looked at El Nino and earlier studies with shorter time-series records, we're not able to find strong correlations at the HOT station with dissolved inorganic carbon or a delta C-13 or even with some of the other variables that we looked at with these climate indices. But with the longer record, we were able to show some relationship with DIC, sea surface temperature and mixed layer depth correlating with the Pacific Decadal Oscillation and El Nino 3.4 index at these locations. Consistent with that earlier results, delta C-13 in this region also does not seem to correlate with the other oceanographic variables there. And so it's likely that there's something else that's sort of tying itself to delta C-13 most likely related to the signal of net community productivity in the region as opposed to these other physical values. And also suggests, again, this idea of water mass shifts leading to or being the driving mechanism for variability in this region. In addition to all of that, though, it's important to consider the fact that the location of HOT is.... So the maps on the right here are showing the sea surface temperature correlation with the Pacific Decadal Oscillation and also with El Nino. And you can see certainly this bi-modal pattern in the region, and also that the location of HOT seems to sit more or less right on this sort of transition center between those nodes. And while the station itself, understandably is stationary in this part, the... Where though that exact node exists is not stationary. And so it's possible that the coherent patterns of variability are having an added complexity of sometimes being driven by one side over the other of what the dominant mode of climate variability is in that region. And so just to sort of summarize these findings. So we looked at the long-term trends and noted that the DIC and delta C-13 seem to follow these atmospheric trends. We showed that the variability seems to have a strong relationship with the vertical mixing in the North Atlantic, as well as a strong relationship with the North Atlantic Oscillation. It's a little more complicated in the North Pacific in a much larger gyre and a much broader region, and so it seems that variability at HOT is likely influenced by horizontal advection and potentially water mass shifts or bi-modal patterns of variability in the North Pacific. And there's also regional differences in the correlation extent where BATS variability seems to correlate over the significant portion of the gyre but HOT variability seems to correlate more closely with the circulation pattern near the station and also in this bi-modal pattern that I've been harping on. And so in addition to being able to sort of think about the time-series in and of themselves, the combination of dissolved inorganic carbon and delta C-13 values are actually really valuable for being used for other studies including it's possible to look at either anthropogenic carbon uptake estimates in the ocean with these or looking at net community productivity estimates using this unique values of delta C-13, they can also be used for model validation studies. So often if you're just looking at dissolved inorganic carbon you may get some seasonality to look along the lines of what you might expect, but that's possible to over-correct physics for. And so if you don't also get the delta C-13 values right that it essentially allows you to understand how well you're also modeling the net community productivity or biological component in the model. And it's also possible to look at these time-series stations in a combination with coral isotope records to understand sort of what's occurring in the water surrounding different reef locations. And so that sort of wraps up what I wanted to talk about in terms of my dissertation research. And so just a couple more slides to talk about, after or before coming to NOAA, I did a short term postdoc project looking at the impacts of freshwater discharge from glacial and non-glacial watersheds on the marine carbon cycle in near-shore ecosystems in Alaska. And so I got to transition some of this thinking to coastal southeast Alaska which has been a fun experience. And this work was done with a combination of inorganic carbon parameters from ferry measurements that Wiley Evans at the Hakai Institute has been making a combination of riverine chemistry from both the USGS and University of Alaska Southeast. Again, in this southeast coastal region and combining that with some modeled watershed hydrography from Dave Hill and Jordan Beamer looking at these freshwater impacts on carbon uptake and ocean acidification and maintenance. And so lastly, just to sort of transition into my current role here at AFSC, like Heather mentioned, I'm in the Recruitment, Energetics and Coastal Assessment Lab. I work in the chemistry lab here in Juneau. And so some of the initial efforts that I've been doing here with RECA include focusing on stable isotope measurements and trophic analysis, primarily looking at fish and zooplankton looking at increasing the sample throughput efficiency and method development for both bulk isotopes as well as compound specific isotopes. I'm also excited to be able to expand collaborations and support of ecosystem based fisheries management and also hope to be able to contribute to stock assessment and ecosystem models and general ecosystem monitoring in the region. I also recently put together a summary of the instrumentation and analytical capabilities of our chemistry lab. And so that's currently available on the AFSC intranet. So if you have access you can find it on there, but if not feel... And you're interested in learning more about that or reaching out to us about anything, feel free to reach out to me, I'd be happy to share that. And lastly, I've been able to also contribute by participating in fieldwork efforts, for example, most recently looking at some herring acoustic surveys in Southeast Alaska, which has been wonderful. And with that, I wanna thank you for your attention and for sticking with us through some technical difficulties. And I'd be happy to answer any questions if you have any.

- [Heather] Awesome, thank you so much, Mariela. It's so nice to hear. I always do a round of applause, that's weird, but... Thank you everybody for joining us today. Please put your questions in the chat. Cool, thanks, Jordan. All right, sorry, I'm just reading it first. Okay, so Jordan Watson. "A recent Nature paper, Sala et al, 2021, suggested that bottom trawling is a major source of sequestered carbon from marine sediments that is potentially mobilized or remineralized and released to the atmosphere. How do you think aspects of MLD seasonality, et cetera, may affect this sort of hypothesis?"

- [Mariela] Oh, that's a great question. I actually saw that paper. I was just talking about it with somebody yesterday. And it's a really interesting question. It's also a really interesting question to think about the impacts of fishing efforts and bottom trawls on carbon dynamics in the ocean beyond just sort of emissions from driving a boat around out on the ocean. And I think that it would depend on the region but certainly if you have a region that has very deep winter mixed layer depths. And so again, thinking like the North Atlantic, or even the mixed layer depth in stormy or sort of subarctic or arctic regions, depending on where those bottom trawls are occurring and at what depths, I think that certainly that would. So if you're mixing up carbon that otherwise would have been in long-term storage into the water column and then you have very stormy events that are able to reach low enough, then that would certainly have an impact. But again, it would depend on what your overall mixed layer depths are and at what depths these bottom trawls are occurring.

- [Heather] Thanks for the question, Jordan. Jiaxu, "Great talk! Thanks Mariela. First question is that, what is the explanation of the general decreasing trend of d 13-C for both sites?"

- [Mariela] That is a great question. And I'm so sorry that I did not do a better job of explaining that. So the deceasing trend of delta C-13 is very much tied to what we're seeing in the atmosphere. So the long-term trends of increasing DIC and decreasing delta C-13 are very much tied to what's happening in the atmosphere. And so as we're increasing carbon dioxide in the atmosphere, we are also subsequently decreasing the delta C-13 values, just because the material that we're we're burning, primarily combustion of fossil fuels, have a lower delta C-13 value. And so over time, we've been able to observe the change in isotopes in the atmosphere. And as this atmosphere, anthropogenic carbon gets taken up into the ocean, you can see that change impacted or that impact in the surface ocean values as well.

- [Heather] Okay, and Jiaxu's second question was, "You showed CESM results. Are these from the isotope enabled output?"

- [Mariela] Yes, so the... Let me see if I can go back. Um... Okay, I don't know if I have the scalability. Yeah, so the short answer is yes. The CESM values that I showed are from a... Let me see if I can share. Are from a model that includes sort of the... Here we are. That includes biogeochemistry that has full carbon chemistry, including the stable carbon isotopes. So it includes delta C-13 as well in that model output.

- [Heather] Awesome. Jiaxu, I hope that--does that answer your question? Do you have any other followups? Any other questions from folks? It is.. She says, "Cool, thanks."

- [Mariela] Perfect.

- [Heather] Okay, so it is 10:57, and obviously we had... If folks have a lot of questions, we can go a little bit over, no problem, because I kicked Mariela out of her own presentation. Any other questions? What do you kind of most looking forward to working on in your new position at RECA?

- [Mariela] That's a great question. So, one thing that I'm really excited about is having a sort of focal topic that has a face. So, being able to work with studies that work with samples from organisms in the ocean as opposed to invisible gases in the ocean, is kind of a fun new flavor for me. And also being able to think about sort of fisheries management but also the impacts of broader oceanographic and climate ecosystem drivers as well. So being able to kind of pull all these things together and apply them to a new realm of research is really exciting for me.

- [Heather] Awesome. Do you think you're gonna tackle the FOCI moorings at all? Just some other studying?

- [Mariela] We'll see, I guess. So, yeah, being relatively new, I think some of those details are still being worked out in terms of exact regional focus, but yeah, I'm hoping to be able to look at a lot of different datasets.

- [Heather] Awesome. Any other questions from folks that are here? No, nothing. Okay, so reminder to folks, we are here again next week. It's the last of the seminar series. So just March for the spring season. Talks will go up in a couple of weeks following the last. So probably sometime in April or May, they'll be posted online. And Mariela, it's really awesome to have you speak today and welcome to the group in the extended FOCI family. I'm sure we'll be seeing a lot of you. So Jiaxu has a quick follow-up question. She was... Let's see, what did she say? Okay, "Quick follow up is that I was involved with the Isotope CESM Development. And that was mostly divined for paleoclimate simulation. So I'm really glad to see it has some modern applications too."

- [Mariela] Oh, wonderful, that's awesome! Thank you.

- [Heather] Cool, all right. Thank you, Mariela. And until next time, we'll see you back here next week. So thank you so much.

- [Mariela] All right, thank you.