GoToMeeting Auto Voice >> This conference will now be recorded.

Heather Tabisola >> Hope everyone is having a good day--trying to.

Welcome to the EcoFOCI seminar.

This is our 2020 fall season.

I am Heather Tabisola and I co-run this seminar with Jens Nielsen, and if he wants to jump on video, he can. I don't know if everybody knows him.

This seminar is part of NOAA's EcoFoci biannual seminar series that's focused on the ecosystems of the North Pacific Ocean, Bering Sea, and US Arctic to improve understanding of ecosystem dynamics and applications of that understanding to the management of living marine resources.

Since October 21st, 1986, this seminar has provided an opportunity for research scientists and practitioners to meet, present, develop their ideas, and provoke conversations on subjects pertaining to fisheries oceanography, or regional issues in Alaska's marine ecosystems, including the US Arctic.

You can visit our EcoFOCI webpage for more information at www.ecofoci.noaa.gov.

And we truly thank you for joining us today.

Feel like it's fall.

Everybody has Zoom fatigue at this point, but we are really excited for this seminar lineup and especially for today, for our three speakers.

You can find our lineup via the one NOAA Seminar Series and also on the NOAA PMEL calendar of events.

We are here every Wednesday at 10 AM Pacific time through December 16th, except for two occasions, next week being one of them.

Please double check that your microphones are muted, that you were not using video, and during the talk, please put all of your questions into the chat.

Jens will be monitoring that.

And we will go through our three speakers first.

They will each have 10 minutes.

At the end, we will address the question and answers, and Jens and I will both be able to pull the questions from the chat, so we will be looking at that.

In there, it might be a good idea, just to say who the speaker is at the time just so we know exactly when we go back through, as well, just to double-check that we've hit all the questions that you've asked.

Today, we do have a special lightening round format.

This is the second time that we've tried this.

And we are featuring two postdoctoral scholars and a PhD candidate.

So, we have Dr. Jiaxu Zhang, Dr. Hongjie Wang, and Esther Kennedy.

So, our first speaker today is Jiaxu.

She is a postdoc scholar of physical oceanography through NOAA's Cooperative Institute at the University of Washington, recently renamed the Cooperative Institute for Climate, Ocean and Ecosystem Studies.

She joined our team in July and her current work work focuses specifically on Arctic freshwater content and its distribution, the Beaufort Gyre Dynamics and Arctic-Atlantic Arctic-Pacific interactions.

Jiaxu received her PhD from the University of Wisconsin Madison, and worked at the Department of Energy Los Alamos National Laboratory before coming to Seattle.

She has ocean modeling expertise, and extensive model diagnosis experience on regional, as well as global processes.

And so with that, Jiaxu, I'm going to turn it over to you, and today she's sharing her work on Labrador Sea freshening linked to the Beaufort Gyre freshwater release.

Hi Jiaxu! OK, let me sign off, and then you are good to go.

Jiaxu Zhang >> Ok, thank you, thank you.

So can you guys hear me? And uh...

Heather Tabisola >> Yes! Loud and clear.

Jiaxu Zhang >> Cool. Cool.

Hi, everyone.

This is Jiaxu and I'm going to turn to my next slide.

So this is my title page.

So I'd like to thank the organizers for giving me this chance to present our recent work

on Labrador Sea freshening linked to Beaufort Gyre freshwater release.

I want to thank my collaborators Wilbert Weijer, Mike Steele, Wei Cheng, Tarun Verma, and Milena Veneziani.

So this is a collaboration between Los Alamos National Lab, UW CICOES, NOAA PMEL, and UW APL.

So Beaufort Gyre is the largest freshwater reservoir in the Arctic Ocean, which is shown here, enclosed by this blue box.

So, observations shows that, starting from 2003, there is an unprecedented increase of its fresh water content.

And by the end of 2017, its freshwater content is already 40% above its longtime climatology.

So this is mostly because of a persistent anticyclonic wind, so, which is strengthening the gyre and as well as more available, freshwater coming from sea ice melt, runoff, and Pacific water inflow.

So if this high amount of fresh water is released in future, the excess freshwater will be transported to the subpolar North Atlantic and freshen its upper ocean salinity.

This means a lot to the Atlantic Meridional Overturning Circulation, the AMOC, because this is the region where the dense water forms.

So, existing studies have focused on the sources of the Beaufort Gyre freshwater.

But, not much its fate after it leaves the Beaufort Gyre.

So, mostly, we don't know whether the water will follow the channels in the Canadian Archipelago, and then go through Davis Strait, and then go to Labrador Sea, or, they will follow the Transpolar Drift and then go through Fram Strait and then all the way to the east of Greenland.

Uh, also existing studies have focused on the overall pan Arctic freshwater budget.

But not specifically on the role of the Beaufort Gyre region apart from the rest of the Arctic Ocean.

So the objective of this study is to explore the fate of the Beaufort Gyre freshwater after it is released and to quantify its downstream impact on the subpolar North Atlantic salinity.

The tool we use is an ocean sea ice hindcast simulation from 1948 to 2009.

So we use a DOE model. It's a global model configured at 0.3 degree resolution, and we implemented some new tracer features, which I will show you the next slide.

So, we implemented a couple new tracers, one is dye tracer, which have been used before.

So, it is used to track volume transport.

So, as shown on the left here, so, basically this is stable for dye region.

So it is initialized as one in this region from the surface to the referenced salinity depth, which is about 400 meter and it's set to be zero outside.

So, when the simulation starts, it will be reset to one at each time step within the region, but outside will be, it will be advected and diffused, just as a regular passages.

So, here, we have an animation, I'm not sure how well you can see the animation.

But basically, the idea is that, you can see the tracer goes through all the channels, in the CAA here and then go all the way to Labrador Sea here.

And that actually finally, got drawn to the subpolar Gyre, and then some also goes through here the Fram Strait.

Another tracer we implemented is a salt tracer. So, it is essentially the same as the dye tracer except that it is initialized as the local salinity.

And what it is, it is reset.

It is reset to the local salinity too instead of 1.

So, this tracer is used to diagnose the freshwater transport from the Beaufort Gyre.

So, our research has three major findings.

The first is regarding the transport route. So we find that,

so by releasing tracer during two different periods, one is we call it a fast release period of the Beaufort Gyre water.

And the second is a fast accumulation period of the Beaufort Gyre water.

So, by doing this two experiments, we find the transport through Davis Strait so, first through the Canadian Archipelago, all the channels, and then down to Davis Strait, overall it's higher than transport through Fram Strait.

So, we conclude that this is the main route for the water to exit the Arctic Ocean into the North Atlantic Ocean.

And, secondly, if you focus on the Davis Strait itself, and you compare these two curves, you find that the water, the amount of water released during a release case, actually doubled the size of that during the fast accumulation case.

We further do a decomposition of the of the water. So, basically for each of the channel.
So, the Nares Strait and Lancaster Sound are the main two channels in the Canadian Archipelago and both of them feed into the Davis Strait, and this is the Fram.

So, we decompose the total transport into Beaufort Gyre source and non-Beaufort Gyre source.

So, we find that the increased Davis Strait freshwater transport is mostly, is dominated by water from the Beaufort Gyre region, as compared to other regions of the Arctic.

The second finding is about Labrador Sea freshening.

The two figures on the left show the upper 200 meter of freshening induced by Beaufort Gyre freshwater.

So, the darker color means stronger freshening, so you can see that during the fast release case compared with the fast accumulation case, so you can see there's a very strong freshening in the western Baffin Bay and also the western Labrador Sea.

But you can also see that the freshening is mostly on the shelf.

It's, it's it's upper, above 2000 meters.

And if you look at the figure on the right, which is a difference between these two map, clear, clearly it shows a difference.

And we also do a diagnosis find that a truss anomalous freshwater flux of about 25 million per job will induce a freshening on the western shelves by 0.2 psu.

The last finding is we compared our result with two recent results regarding the Greenland meltwater.

So we want to put our work in capacity with how, how, how much they compare with each other.

And we find, in terms of freshwater flux anomaly and freshwater amount, and the amount of freshening they induced the Beaufort Gyre water and Greenland meltwater are of comparable magnitude.

So, this is my last slide.

So, the objective of the research is to explore the fate of the Beaufort Gyre freshwater after it is released, and to quantify its downstream impact on the subpolar North Atlantic salinity.

And we have three major findings.

The first one is about its transport route.
They find it's mostly through the Canadian Archipelago and then the Davis Strait, instead of Fram.

And a second it's about how much freshening it induces.

So we find that, although the western shelves of the Labrador Sea is about 0.2, and if you zoom into the Labrador Current, it is 0.4 psu.

And finally, we compare it with Greenland meltwater estimation and they are of comparable magnitudes.

So, we have two important implications.

The first one is, this freshwater will have potential impact on the AMOC, but I cannot go into too much details now, but I would encourage, whoever is interested in this, can read our paper once it gets out.

But I do want to talk about the second application.

So, if we look at the figure on the left, which shows the time series of Beaufort Gyre liquid freshwater content from 1948 to present day basically.

So you can see that, so this is the fast release period.

And then, this is the fast accumulation period.

So, the anomaly studied currently in this, in our in our study, actually, is only half the size of the present day accumulation.

So you can imagine that if in the future, this high amount of freshwater gets released, its impact on the Labrador Sea can be really significant and easily exceeding similar fluxes from Greenland meltwater.

So I'll stop here.

Heather Tabisola >> Thank you, Jiaxu.

All right.

We will save questions for the next, for the end and Hongjie, you are next, and I'm just finding you on the list.

This is always the fun part.

Ok, Hongjie, you should be see the presenter request.

And when you're ready to share your screen and your camera.

Hongjie Wang >> Can you see my slide now?

Heather Tabisola >> I do see your slide.

Hongjie Wang >> Ok.

Heather Tabisola >> Ok, all right, let me introduce you really quick while you've got that going.

Hongjie Wang, who is joining us now, is a postdoc scholar, as well through CICOES and also joined us this summer at PMEL.

She's conducting research that focuses on the Arctic and Alaska marine carbon cycling, including new technology development and ocean acidification monitoring.

Hongjie comes to us after studying biochemistry in China, Texas, and Delaware, where she has developed some special expertise in working with large synthesis datasets and unique data products, which makes her a real asset to our ITAE and NSOAR teams.

She comes to PMEL after moving her whole family of four, including the pets, across the country during the middle of the pandemic this summer, and has already found a local fishing hole.

So, with that, Hongjie, I will turn it over to you and she is sharing her work on Summer pCO2 dynamics based on autonomous surface vehicles in the eastern Bering Sea and Chukchi Sea.

Hongjie Wang >> Thank you, Heather, for the introduction.

Um, so, so, we know that, the carbon dioxide concentration in the atmosphere that increased at a rate about a two micro atmosphere per year.

And in fact, about one third of all human-produced CO2 has to be absorbed by the ocean.

So in the following decades and a century, the rate of ocean carbon uptake largely determines the percentage of emission that will remain in the atmosphere.

So, so far, the CO2 flux in the open ocean is relatively well understood.

However, when it came to the highland good area, the uncertainty of CO2 flux remains very high.

For example as showed by this figure, the CO2 flux read in variancy rented former less than one millimole per meter square per day to over 20 units.

So, for your reference, the green bar here shows the average CO2 flux read in the open ocean.

And the high flux and salinity in the very same Chuckchi Sea is that was mainly caused by the specificity of the in situ data, so better knowledge of the original field uptick is urgently needed to understand the current state and future evolution of carbon cycle and that the global climate change.

So far, our knowledge is highly relied on the field data collection by research vessel and autonomous mooring platforms.

But boss matter have limited the spatial or temporal coverage, especially Arctic Ocean, because the to be a logistical challenge.

So in 2017, Saildrone, unmanned separate vehicle in partnership with NOAA PMEL completed its first autonomous crossing of the Barents Sea to measure CO2 concentration, update ocean.

So by figure, the new technologies provide us a very rich context to interpret the surface CO2 dynamics.

So now I want to share with you the CO2 flux that we now collected by Saildrone from 2017 to 2019.

So, this map, so the tracks are the Saildrone courses, this three consecutive years.

So in brief, two Saildrone each year, starting from Dutch Harbor, that's all the way through the Barents Sea, up the Barents Sea, the Barents Sea, up the Barents Sea, to the north sea interface study area and then come back.

So the slide here shows the location of M2 mooring side.

These two diamonds, so the location of atmospheric baseline stations, station, Barrow and a station Alert in Canada.

So since this, Saildrone sail too was a new technology that has not be necessarily standardized across a community yet, so it's very important to cross-check precision by comparing it with other standard measurements.

So we first compare that the Saildrone air CO2, which showed by the black triangle here with two already mentioned atmosphere station. Station Barrow and station Alert.

And also, M2 station.

And so, then, we find that, that mean difference between Saildrone CO2 and the two atmosphere stations was only 0.05  microatmosphere.

And differences between Saildrone and M2, which shown by the green triangle here, it's only -2.2 microatmosphere.

So, and this difference is less than 1% of the residual value.

And then we also compare that the Saildrone result, will show by the green here, and with the Healy and we measurement, shown by the light green in the background, and the difference between them is 4 microatmosphere.

So, by cross-checking the jumps too with other well-established measurement, we can from that the Saildrone are capable of a robust collection of airfield show and see what a CO2 in this harsh environment.

This figure summarize all the searches third pCO2, these three years, startup pCO2 is the uh, the difference between seawater CO2 and atmosphere CO2.

So, the majority of the Saildrone had acts as a CO2 sink because the CO2 was inactive.

But there were few exceptions, one farm near the Yukon River plume, and the other area, it's the north of the cap spread in region number three.

By the way, in order to better understand the spatial distribution of surface to we divide the entire study area into four rigid so by this rectangles.

So, I want to show you one example to show you one piece of Saildrone data.

So, the screen here shows the DBO site was collected in 2017. In the middle of the DBO transaction three, very high abnormally high surface temperature was measured.

Initially, people thought this weather may be mistakenly measured, however, the Saildrone data detailed come from that, this high field to the middle of the transect was actually caused by a strong upwelling event because station also find that very high field near this station.

In order to understand the very build-up of third pCO2, we then decompose the third pCO2 into 2 components, temperature dominate, and a non-temperature dominant process.

And we found that, warming, actually, the warming from winter to summer, contribute the increase of delta pCO2 by 50 to 100 microatmosphere.

It's the primary productivity, all the biological activity that maintain such a strong field to sink, in the study area.

And the elevated respiration is, it's raising costs the source near the Yukon River and not all cap off our list.

And next we plan to get it so to flux rate in the entire Pacific Arctic region.

And we have student made of that.

So we would need to admit that it's a very challenging to as shepherded the CO2 flux in this dynamic area.

So instead of simply multiply that every so to flux, and then the total area.

So we propose first to gather the water mass distribution in the studied area based on the historical data.

And so I'd show by these different colors the main fall water max in the studied area.

Then we get the average CO2 flux in each water mass based on Saildrone data in each subregion, then we add them together.

And so what's showed by the bar plot?
 
So you can see how dynamic this studied area for example, the total flux in the Alaska coastal water rinse allowed but just the different subregions.

And so, all these flaps were calculated based on one thing only.

And then we add them together and we put them in the with the little ritual value.

And so, shortly our value will fall into the range of little ritual value. OK, but we understand that I send out this is still very high with me resulted from the sea ice mounting and ocean circulation changing that also ways, you know, when do you actually change and the west developing the story are clearly more accurate and precise economist observation.

I need in the future to restrain the variability and the bed and send the future so to think a change in the studied area.

So I will stop here. Welcome to ask any question in the Q and A time.

Thank you.

Heather Tabisola >> Thank you, Hongjie. It's so fun to see work on the Saildrones.

The science coming out of it after working on the projects.

Esther, I am going to swap over to you and as you get ready for presenting, I will introduce you.

And everyone, don't forget, if you do have questions, Libby, I do see yours, please put them in the chat.

And then also, just note who the question is for so that we can follow up with that, with each speaker correctly.

So we will do a Q&A following Esther's talk.

So our third speaker today is Esther Kennedy. She's a PhD student at UC Davis, working on Ocean Climate Lab that is led by Dr. Tessa Hill.

Esther has a long history of working in Alaska.

After moving to Sitka in 2014, for an AmeriCorps fellowship, she spent five years supporting the Sitka Tribe as their staff environmental scientist where she developed the protocols now used for the SEATOR, a use ocean acidification community sampling program.

Using funding from NSF summer graduate fellowship, Esther approached, Alaska's Fishery Science Center and the Pacific Marine Environmental Lab about continuing her ocean acidification work in Alaska and spent this summer working with Dr. Jessica Cross, Elizabeth Siddon, and Darren Pilcher on ocean acidification forecasting.

So, with that, I will turn it over to Esther, who will be sharing her work on developing ocean acidification indices for Bering Sea fisheries.

Esther Kennedy >> Thank you so much, Heather.

And just to make sure everything is showing up, right?

Heather Tabisola >> Yes, we can see the screen, and I can hear you, and if you want to go on video, you can.
 
Esther Kennedy >> Um, I'm gonna leave my video off for now, but I promise I will turn it on later.

So thank you again.

So I will be sharing the results of my summer internship, which was focused on developing ocean acidification indices for Bering Sea Red King crab.

And I do want to acknowledge my mentors and lab mates for this summer project, as well as the myriad other people who really helped me with this project.

Most especially Jim Thorson, um, as well, and thank you to the NSF for providing funding for this.

So as Hongjie mentioned, ocean acidification, as we also all know is the result of carbon dioxide dissolving into the ocean.
It's got a wide array of direct and indirect effects. It is expected to impact essentially every trophic level and on all ocean basins.

It is happening now and there many ways to measure it.

But for this talk, I will use aragonite saturation as I will focus on our aragonite saturation states.

Ocean acidification is of particular importance to you at the Bering Sea.

The Bering Sea hosts some of the largest, most valuable fisheries in the US.

It's critical to the food and economic security of Alaska and to the nation.

And to manage fisheries in the face of ocean acidification, we need to develop OA-specific indicators of fishery health.

One other reason to focus on the Bering Sea for this project is that there's a newly available OA hindcast model data, um, developed by Darren Pilcher and others, which offers really high spatial and temporal resolution throughout the region.

This new model output allowed us to ask my first research question, which was, "What are the spatial and temporal patterns of OA in the Bering Sea?"

But we also wanted to drill into a specific fishery.

And we chose to focus on Red King crab, in particular, because they are one of the highest value fisheries in the region and crab are expected to have negative impacts from OA.

So lab experiments have already shown that larval survival declines under under acidified conditions.

And other models have suggested up to a 50% decline in fishery yields and profits over the next 20 years.

This figure on the right from Seung et al., kind of highlights this.

The black line is showing or the, sorry, the blue line is showing you the expected yields and profits with no ocean OA effects.

And the other two lines are showing you the expected declines with OA affects.

And in both cases, you are expecting a significant population decline because of OA.

Making this more difficult, though, those ocean acidification effects might be masked by temperature impacts on the population.

Large temperature swings in the region are common, that can really overwhelm other oceanographic variables.

And in particular, as you can see, again on the graph on the right, when ocean acidification impacts are non-linear, which is also expected, they kind of track with no OA effects for quite some time.

So, it would be easy to imagine that we could lose the signal in the noise until things are a little bit too late, which brought us to our second research question given the spatial details of the OA hindcast we had, we chose to explore what are the spatial impacts of OA on adult Red King crab distributions?

To get at the first question, to explore some of those spatial patterns of OA., I used empiric orthogonal functions which defined spatial and temporal modes of variability.

Below, you can see the outcome of a temperature EOF, and on the left, you're seeing an entire index that trends from positive to negative.

This reflects the overall shift in the region from warm to cold.

And on the right, you see a map of the expected spatial pattern during a cold, during a cold period, when the the index is especially negative, as in 2012.

Sorry.

And so looking at additional oceanographic variables with all my other EOFs, it was very clear the temperature effects really dominated, as I alluded to before.

So the shift from warm to cool in 2007 was apparent in every single oceanographic variable that we looked at.

Multivariate indices were also completely indistinguishable from temperature indices alone.

That all said, here you can see two maps, the same temperature map and aragonite saturation and what I like to point out is that temperature and aragonite saturation covary on the Bering Sea shelf.

And in particular, those effects are concentrated in Bristol Bay, which is in the red square.

I also do want to point out that while those patterns are similar on the shelf, they are not identical even within Bristol Bay.

So given those spatial patterns, we sought to link those to Red King crab distributions to address that second research question.

And for this, I used VAST models, which are Vector Autoregressive Spatio-Temporal models.

And these define modes of variability and fisheries data that are analogous to the outputs of the EOFs that I was just showing.

We were experimenting, we experimented with a variety of environmental covariates and modeling methods.

And all of our model outputs had very high they had a high uncertainty, which you can kind of see in these residuals on the left, the vibrant confetti pattern is an indication of sort of high residuals, but the models also had really good agreement with the area-swept survey models that the annual Red King crab tech reports publish.

And essentially, were very much in line in terms of uncertainty with those same area-swept models.

So what did we actually see?

We did see a very significant shift in distribution with Red King crab.

So with these heat maps of crab density, you can see that from 2003 to 2006 crab were disbursed throughout the central Bristol Bay shelf.

But by the end of the time period, they're really closely concentrated along the Alaska Peninsula.

They've essentially abandoned the central shelf area.

This pattern was apparent regardless of the covariates we included.

And indeed, it was essentially identical, regardless of covariates included.

But we did find a very strong correlation with that temperature index that I showed before.

This is not a surprise to many of you.

The, the tight relationship between temperature and crab behavior is, is well-known and has been they're just sort of discovered by and worked on, by many scientists, on this call.

But what we were hoping for was some separable relationship between a multivariate index or an or on, 0A-specific index, um, and crab and unfortunately, we did not find them.

But with the temperature indices, we saw correlation of 0.86 and that correlation actually increases to 0.91 when the crab index, which has shown here in the white bars, when that is lagged by one year.

And that just reflects that sort of slowness of moving a large population of not particularly fast walking animals from one place to another.

So as they actively move to seek out better habitat, there is a bit of a delay associated with that.

So in conclusion, as I mentioned, we really did not we did not find separable OA impacts on Red King crab distributions.

But this is both what we expected.

It's very con-it's consistent with the Seung and and others models.

And it's also important.

It shows some resilience in the system.

It would be incredibly bad news if we were able to see OA impacts already more than a decade ago.

And it also shows that Red King crab behavior, and again, this is this is not news, per se, but it confirms that Red King crab, Red King crab behavior will help them avoid ocean acidification impacts for a time.

As they moved to avoid colder water, they will also avoid the most corrosive water.

For future work, though, you really want to incorporate that more detailed environmental information into the models and, um, in a more precise way.

So as I mentioned, there are spatial differences between aragonite saturation and temperature.

And I was not able to incorporate those differences very precisely into the models.

But with a little bit, um, more detail there, you could probably better isolate OA impacts.

We also want to include larval and juvenile life stages.

Those are both life stages that are more vulnerable to OA than adult Red King crab are.

And finally, there's quite a bit more hindcast model output available already.

So, it's currently available all the way through 2019, and that is expected to be extended further into the past in the near future.

Thank you very much for your time, and I guess we'll now go to questions.

Heather Tabisola >> Thank you so much, Esther.

Thank you to Jiaxu and Hongjie as well.

And Esther, if you could stop sharing your screen.

And I will ask Jiaxu to join me on video.

And actually, why don't we just go...

Yeah.

And then, Esther, if you... Yeah, great.

We'll just put everybody up here.

And I will join in for the fun. Jens, if you want to keep monitoring chat.

Thank you guys so much.

I always do the round of applause from here, for everybody who can't hear it.

So, thank you, thank you.

All right. So, Jiaxu, we're gonna start with you with questions.

And, Libby, thank you for all of your questions in the chat, so I'm just gonna work my way through here.

So from Libby Logerwell, she works at the AFSC side of EcoFOCI.

Jiaxu, she asks, "How was the simulation model tuned or validated with observations?
Are you confident the simulation accurately represents the transport and flow?"

Jiaxu Zhang >> Well, that's a really good question.

So, this work, so, let's see.

So, actually, this, model is, is, is a new model.

So, we started with a pub two and size five, which is like an ocean and sea ice component of the CSM model.

And then we developed a new resolution, which is 0.3 degree resolution.

And then we validate tested everything and we do have like a report validated the whole thing.

So if we zoom into the Arctic, we did look at the temperature salinity distributions, and then we did compare the transport at each of the main Arctic-Atlantic gateways, to make sure that they are they fit the observations.

So I have to say no models are good in terms of transport because it's very hard, especially the freshwater transport.

It's really hard to get it correct.

On the other side, the observation is not complete.

So, so far, we don't have like a very reliable, continuous observation in terms of volume of transport and a freshwater transport in each of the gate.

So, most of them, there says, no.

Most of them, they just, you know, there, sit there for a year, but we rarely have, like, a long-term, like a full observations record.

So, it's really hard for the model.

I mean, we don't know where we can find, a good, good observation to compare with.

So, that's really hard to. But I have to say this model is, is that we did our best, and they are over largely consistent with the observation.

Oh, Heather, we can't hear you.

Heather Tabisola >> I was being kind, I wanted to mute while you're on, and then I forget. So, thank you, Jiaxu.

Libby, I hope that answers your question.

If not, Jens, why don't you message me if there's a follow-up as I read and I'm gonna jump to Hongjie for a question also from Libby.

"Could you please explain again how you determined the role of respiration in the pCO2 observations?"

And Hongjie, we also, you're on...

Yep!

Hongjie Wang >> Sure, thanks for asking.

So, like, basically, we, firstly, we, we know that the pCO2 has some prediction with temperature.

So, we normalize all the observe the CO2 and you mean temperature, then, this is the temperature control of the process.

The difference between the temperature control path and observed the delta pCO2, is B the biological process.

And we attributed all the non-thermal part, plus biological process to control the part.
So, that's the way we do that.

Heather Tabisola >> Sorry, I'm copying over questions.

Thank you, Hongjie.

Hope that answered your question, as well.

All right.

Let's see, sorry, just monitoring and copying over questions so I don't miss anybody.

So Esther, I have a few questions for you.

So I will try not to give them all to you back to back in hopes that other questions for Jiaxu and Hongjie also come in.

So, Esther, first question, again from Libby.

She's a rockstar.

"Temperature and aragonite saturation covary. Is there a chemical / physical mechanism linking the two?"

Esther Kennedy >> Yes.

Um, and so most most notably, carbon dioxide is more soluble in, in water, at cooler temperatures.

So the colder it is, the higher your dissolved carbon dioxide will be, which will conversely sort of bring down your PH and all of these will work to drive the carbonate system away from to a lower saturation states, essentially.

So that is one reason also, that Alaska waters are kind of naturally more acidic or corrosive than the rest of the US, because in large part, they are much colder.

And so they have baseline, much higher pCO2 in them.

[Heather on mute]

Heather Tabisola >> Katie Russell, is wondering Esther, "Can you repeat what your second research question was?"

Esther Kennedy >> We were, oh, sorry, we were looking to see whether there were spatial impacts on Red King crab distributions as a result of ocean acidification parameters.

Heather Tabisola >> Katie, hope that helps answer that question.

All right, and more questions for you, Esther.

This was also from Libby, I believe.

"What would be the mechanism linking the distribution of OA and the distribution of our case, sea?"

Esther Kennedy >> Um, that's a great question.

Essentially, it would be in terms of seeking out better habitat, um, and so, or not surviving in, um, in unviable habitat.

And so, because there is so much variability in ocean acidification in, like, say, aragonite
saturation or PH concentrations along the shelf and across the Bering Sea.

There's a lot to be said for, there's a lot of sort of OA-specific habitat variation in the region, and so, it is worth then seeing whether or not that habitat variation actually results in crab moving.

Um, and that in particular, is going to have impacts if there are OA-specific impacts on where crab move, that's going to have both direct impacts on cost to the fishery, and sort of how the fishery works, but also, probably has significant impacts on population genetics or connectivity, the success of a breeding and sort of a bunch of biological things that I
know would be important, but I definitely should probably stop talking about, at this point.

Heather Tabisola >> Ok. Fair enough.

Let's see, OK. And then Esther, we also had a question from Ned Cokelet.

He works with us at the PMEL EcoFOCI side. And he asks, "Do the RKC actually move? Or do they just die out in an area? If they move, how do they know where to go?"

Esther Kennedy >> I think that's a great question.

I do think there is probably some dying happening.

But I also think there's some moving happening. In particular, from my own work I could not necessarily differentiate between the two.

But looking back at the um at the Crab Tech reports from the last 40 years you really don't see a tight, you don't really see a correlation or a tight correlation between temperature and projected population.

Um, but you do see a really tight correlation between temperature and where the crab are actually found or more specifically less between absolute temperature and more with, is it a cold year, crab are in this area, is it a warm year, crab have expanded.

And so I do think there's some, some movement happening there.

And I'm, sorry, there was a second piece to that question that I just lost.

Heather Tabisola >> "If they move, how do they know where to go?"

Esther Kennedy >> Um, yeah, I mean, I don't...

I would say, they're just chasing warmer water or, like less chasing warmer water and more avoiding the coldest water.

Um, I certainly can't speculate on sort of, crab internal mechanisms for, for knowing that, but I would say, if you're on a shelf and it's very cold, it's fairly intuitive to say, move towards the edges of that shelf and in particular towards the shore, so into shallower water that is also going to be warmer.

Heather Tabisola >> Thank you.

You just get all the questions, Esther. I'm sorry, Jiaxu and Hongjie.

All right, one more question, Esther.

"Can Red King crabs actually sense undersaturation as a prompt to movement?"

Esther Kennedy >> I don't know.

And I, I would say I I think there's there's no reason to expect that at any particular threshold, Red King crab would suddenly decide this saturation state is too low, I need to move.

And the reason I say that is because crab, like many other organisms, have a lot of control over their calcification, and even at really high saturation states, they are internally increasing the saturation state to many times ambient levels.

So the difference to a crab between, say, an aragonite  saturation state of 1.2 and 0.8 eight is maybe a little bit arbitrary.

But the lower the saturation state is, the more energy they have to expand to calcify.

So it would say, as a crab, what you're probably going to notice more is that you need more food, but they're not necessarily reacting to a specific aragonite saturation state.
It's more that, the lower that goes, the more their metabolism needs to compensate.

And so, so, essentially, no, I don't think that they are specifically reacting to like a threshold aragonite saturation state, but I do think you would see impacts on a gradient as that aragonite saturation state decreases.

Heather Tabisola >> Thank you.

Let's see, I do have one other question for Hongjie this time.

"What might be, um, what might the increasing impacts of ice melt be on the Arctic CO2 sink."

Hongjie Wang >> So, that's a very good question.

That's also one good question I want to answer.

So based on the Saildrone data, in the meltwater area the CO2 tend to be in a neutral state, it's like just very close to the atmosphere CO2 level.

Um, and they're, so like, there are a lot of process maintain this neutral state, for example, a little bit of warming can increase the CO2 and may, I guess so to even showed it to make this area into a CO2 source.

So, when they're mostly ice melting, this this area may turn into a source because the warming impact.

At the same time, when sea ice melting and the primary productivity may decrease because the new gene mutation and can reduce the biological activity, can make the CO2 sink, even a weak CO2 sink, this shows that process can make this area become a multi source.

But it's another parallel study we also find that the, the thinner sea ice may get melt in other locations, making this, like the the last that you see, the same to actually increase a little bit and, and the way it needs external water mass get into this area.

External water mass carry some biological product dispersion product, and the release of CO2
in this sea ice melt area.

So make this area even to be most able to solve a lot of prototyping in this area.

So, and depending on situation, depending on the sampling time, for example, in the early bloom season, or in the fall season.

So, it's complicated, and we are still developing the story.

Thank you for asking.

Heather Tabisola >> Spoken like the true scientist, it's always complicated, and there's more to the story. All the time.

But I love that, right, because there's always more to study and research.

Um, all right, we are like four minutes out from 11 o'clock.

We've been here for an hour.

I'm gonna ask one more time to our audience, any more questions?

And I'll give folks a minute, if they do, but I just want to also say thank you to all three of you.

I know lightning format is a little bit different, especially when on Zoom, but I love it.

It was so great to hear from all three of you and all the work that you've been doing.

Actually following up on Saildrone and other work that I've done, and Jiaxu following you along on this story, and I'm so excited for your publication. Hope that that gets featured within the lab as well so.

All right. Any parting thoughts from any of you that you would like to share?

Esther Kennedy >> Thank you for having us.

Hongjie Wang >> Yeah. Thank you for having me.

Heather Tabisola >> You're welcome. You're welcome.

Jiaxu Zhange >> Yeah. Thank you. It was good.

Heather Tabisola >> Oh, Matt.

Matt just asked me--he joined late, and "How do we access recordings?"

So, yes, so, most of our seminars this year, or this season are being recorded and once we make them accessible, with like subtitles and everything, we'll get them up on the PMEL Youtube page.

And I will try to remember to remind folks.

I will try to remind folks when those actually go up and where exactly to find them, but it is on the PMEL, Pacific Marine Environmental Lab YouTube's page.

And you can see previous seminars there. It starts with the seminar title it doesn't necessarily EcoFOCI seminars, it's just under seminars.

And then, next week, I believe, it's on, is it next week, Monday, I think, is our talk, and not on Wednesday? Thank you, Jiaxu. And it's with Jesse Lamb.

And yeah.

Anything else?

Oh, great.

Adi, thank you so much.

Adi put the link for the PMEL seminars that are recorded.

She put that link in the chat.

So Matt, you can double-check that.

It usually takes a couple a week or two for us to get it up, just based on time to review and do that.

Yeah, thank you, everybody for coming.

It's good to see the three of you here, Jens, and then seeing everybody else's names virtually, it's always nice to sort of connect now that we're seven months into being at home.

See everybody next week.

I hope you take some time for yourselves and do whatever you need to do to get through the rest of the week.

So, all right, everybody.

Thank you.

Thank you.

Bye.

Thank you.

Bye, Heather.

Bye. Thank you, Hongjie.