WEBVTT Kind: captions Language: en 00:00:08.179 --> 00:00:11.730 Ashley Fortune: �Good afternoon or good morning from the U.S. Fish and Wildlife Service's 00:00:11.730 --> 00:00:15.219 National Conservation Training Center in Shepherdstown, West Virginia. 00:00:15.219 --> 00:00:21.570 My name is Ashley Fortune, and I would like to welcome you to today's broadcast of the 00:00:21.570 --> 00:00:25.169 NCCWSC's Climate Change Science and Management Webinar Series. 00:00:25.169 --> 00:00:30.320 This series is held in partnership with the U.S. Geological Survey's National Climate 00:00:30.320 --> 00:00:32.840 Change and Wildlife Science Center. 00:00:32.840 --> 00:00:38.100 Today's webinar will focus on the impacts of melting glaciers on nutrient supply in 00:00:38.100 --> 00:00:42.829 coastal ecosystems of the northern Gulf of Alaska. 00:00:42.829 --> 00:00:46.370 Our speaker today is Dr. John Crusius. 00:00:46.370 --> 00:00:52.880 John received a BA in Chemistry from Carleton College and a PhD in Geochemistry from Columbia 00:00:52.880 --> 00:00:57.510 University and the LamontDoherty Earth Observatory. 00:00:57.510 --> 00:01:02.719 John did postdoctoral work at the University of British Columbia in Vancouver and worked 00:01:02.719 --> 00:01:07.530 for a while as a research scientist at the International Atomic Energy Agency Marine 00:01:07.530 --> 00:01:09.860 Environment Lab in Monaco. 00:01:09.860 --> 00:01:17.950 From 2003 to 2011, John was a research scientist in Woods Hole at the USGS Coastal and Marine 00:01:17.950 --> 00:01:19.320 Geology Center. 00:01:19.320 --> 00:01:26.060 Since 2011, John has remained a USGS research scientist with the Coastal and Marine Geology 00:01:26.060 --> 00:01:30.340 Program, but he is based in Seattle at the University of Washington, where he has an 00:01:30.340 --> 00:01:34.310 affiliate faculty position in the School of Oceanography. 00:01:34.310 --> 00:01:36.970 John is married and has one son in high school. 00:01:36.970 --> 00:01:38.900 John, that's quite the experience. 00:01:38.900 --> 00:01:42.070 Everyone, please welcome John, and you may begin. 00:01:42.070 --> 00:01:43.070 Thank you. 00:01:43.070 --> 00:01:49.320 John Crusius: �Thanks a lot, Ashley, and thanks for your help setting up. 00:01:49.320 --> 00:01:54.170 Good afternoon, everyone, or good morning, depending on which time zone you're in. 00:01:54.170 --> 00:02:00.200 Today, I'd like to speak on "Impacts of Melting Glaciers on Nutrient Supply and Coastal Ecosystems 00:02:00.200 --> 00:02:03.310 of the Northern Gulf of Alaska." 00:02:03.310 --> 00:02:07.830 I want to acknowledge a lot of collaborators who did a lot of this work. 00:02:07.830 --> 00:02:09.709 I'm going to give a broad overview. 00:02:09.709 --> 00:02:13.110 I've listed a lot of people here. 00:02:13.110 --> 00:02:16.309 I don't have time to acknowledge them all individually. 00:02:16.309 --> 00:02:21.680 In particular, I want to acknowledge funding from the USGS National Climate Change and 00:02:21.680 --> 00:02:27.309 Wildlife Science Center, from the Coastal Marine Geology Program, and from the Mendenhall 00:02:27.309 --> 00:02:29.310 Postdoctoral Fellowship Program. 00:02:29.310 --> 00:02:38.090 I'm going to speak briefly on some NASAfunded work of ours that is relevant to the overall 00:02:38.090 --> 00:02:40.129 project. 00:02:40.129 --> 00:02:42.040 Here's an outline of what I want to present today. 00:02:42.040 --> 00:02:47.939 This is a challenging talk because this is a large, multiinvestigator study, and I'm 00:02:47.939 --> 00:02:54.599 trying to summarize what a lot of people did in 45 minutes. 00:02:54.599 --> 00:02:59.769 Pretty much every slide I present could be expanded into a 45 minute talk, so I'm going 00:02:59.769 --> 00:03:02.879 to try to cover a lot of ground. 00:03:02.879 --> 00:03:08.379 I'm also going to try to keep it accessible to a fairly general audience while maintaining 00:03:08.379 --> 00:03:12.579 the scientific integrity, so please bear with me. 00:03:12.579 --> 00:03:15.569 I'll try to keep you with me as I go. 00:03:15.569 --> 00:03:22.150 Just to give you an outline, I'm going to speak briefly on the evidence for glacier 00:03:22.150 --> 00:03:26.930 mass loss, from the northern Gulf of Alaska in particular. 00:03:26.930 --> 00:03:34.419 I'm going to examine the marine food web foundations, including nutrients nitrate and iron, which 00:03:34.419 --> 00:03:36.840 limit phytoplankton growth. 00:03:36.840 --> 00:03:43.189 I hope I will convince you that glaciers are a source of iron, which is a nutrient that 00:03:43.189 --> 00:03:49.909 limits phytoplankton growth and that rivers and sediment resuspension and dust are all 00:03:49.909 --> 00:03:52.540 important sources of the micronutrient iron. 00:03:52.540 --> 00:03:58.400 I'm going to discuss some seasonal variability in the nutrient sources and allude to the 00:03:58.400 --> 00:04:04.129 fact that there's hyperactivity in the spring along the continental shelf transect that 00:04:04.129 --> 00:04:08.359 we studied in response to this high nutrient supply. 00:04:08.359 --> 00:04:12.500 By late summer, nitrate is the limiting nutrient. 00:04:12.500 --> 00:04:18.520 Zooplankton and fish abundance tend to be high in the river plume that we studied, the 00:04:18.520 --> 00:04:21.030 Copper River plume, for reasons of predator evasion. 00:04:21.030 --> 00:04:26.250 Then I'm going to end with some model simulations of Copper River discharge into the Gulf of 00:04:26.250 --> 00:04:33.229 Alaska, including some simulations of two times present discharge and discuss some impacts 00:04:33.229 --> 00:04:38.800 of that. 00:04:38.800 --> 00:04:47.169 Here are some results from a recent paper from the journal "Nature" showing evidence 00:04:47.169 --> 00:04:52.780 for glacier mass loss worldwide, although I'm focusing strictly on the northern Gulf 00:04:52.780 --> 00:04:55.610 of Alaska area glaciers. 00:04:55.610 --> 00:04:59.810 Here's a map of North America that you'll all recognize, and here's Alaska. 00:04:59.810 --> 00:05:05.340 You see this southern Alaska region at the northern end of what we refer to as the Gulf 00:05:05.340 --> 00:05:12.240 of Alaska, this being the Gulf of Alaska right where the number 12 is. 00:05:12.240 --> 00:05:18.930 This area is lined by many mountain glaciers, and there's a paper, this paper that I mentioned 00:05:18.930 --> 00:05:25.361 in "Nature," which documented mass loss of these glaciers over the time period 2003 to 00:05:25.361 --> 00:05:32.340 2011 using the GRACE Satellite. 00:05:32.340 --> 00:05:38.939 What you see here from 2003 to 2011 is mass increasing in the winter, decreasing in the 00:05:38.939 --> 00:05:44.509 summer and that cycle repeating over and over again, but there's a general downward trend 00:05:44.509 --> 00:05:48.930 that's pretty much indisputable over that time frame. 00:05:48.930 --> 00:05:54.170 There have been a lot of high profile papers on this general topic in recent years, and 00:05:54.170 --> 00:05:56.039 I could have picked any number of them. 00:05:56.039 --> 00:06:01.860 I picked this one mainly because it's quite recent, it was in the journal "Nature," and 00:06:01.860 --> 00:06:08.480 it actually shows data from this southern Alaska region. 00:06:08.480 --> 00:06:14.030 Some work that is relevant that was done by one of our USGS team members, I'm presenting 00:06:14.030 --> 00:06:15.030 here. 00:06:15.030 --> 00:06:20.830 This is work done on the Bering Glacier from 2002 to 2012. 00:06:20.830 --> 00:06:27.150 Our project really included fieldwork only from 2010 and 2011, so this represents a whole 00:06:27.150 --> 00:06:32.409 lot of extra effort by the lead author, Ed Josberger. 00:06:32.409 --> 00:06:38.219 This is work from the Bering Glacier at the northern end of the Gulf of Alaska. 00:06:38.219 --> 00:06:43.270 It's just a little bit east of the Copper River, for those of you who know where that 00:06:43.270 --> 00:06:45.889 is, and I'll show you that in a minute. 00:06:45.889 --> 00:06:48.479 This is a little bit different from the last paper I alluded to. 00:06:48.479 --> 00:06:56.930 This is documenting summer melt as a function of time from 2002 to 2012, and it teases apart 00:06:56.930 --> 00:07:04.819 the contributions to that melt of ice melt, snow melt, and precipitation. 00:07:04.819 --> 00:07:12.319 What's striking, to me anyway, is that there's surprisingly little variability during this 00:07:12.319 --> 00:07:21.379 10year time frame, fairly steady melt of 40 plus or minus 3 cubic kilometers per year. 00:07:21.379 --> 00:07:27.240 A little bit of up and down as time goes on but not a really noticeable temporal trend 00:07:27.240 --> 00:07:32.029 showing an increase over time. 00:07:32.029 --> 00:07:39.539 This line with the diamonds connecting it shows melting degree days, a measure of the 00:07:39.539 --> 00:07:41.689 warmth, essentially, during the summer melt period. 00:07:41.689 --> 00:07:46.800 Sure enough, during warmer periods, as you might expect, there's more melt and less melt 00:07:46.800 --> 00:07:52.150 during colder days, but there is not an overall trend. 00:07:52.150 --> 00:07:56.449 I want to emphasize that this is not really in conflict with the previous slide because 00:07:56.449 --> 00:07:58.120 this is only showing the summer melt. 00:07:58.120 --> 00:08:04.419 This is not looking at the annual mass balance, but interestingly, over this 10year time period, 00:08:04.419 --> 00:08:06.949 there's not an increase in melt over time. 00:08:06.949 --> 00:08:15.930 I'm going to come back to this analysis of what might happen in the future a little bit 00:08:15.930 --> 00:08:16.930 later. 00:08:16.930 --> 00:08:26.860 This is a map, obviously, of North America, primarily, and here is the Gulf of Alaska 00:08:26.860 --> 00:08:27.860 area. 00:08:27.860 --> 00:08:30.430 Here is this coastal Gulf of Alaska area. 00:08:30.430 --> 00:08:36.029 What I want to point out simply is that this area, which is not that well known to most 00:08:36.029 --> 00:08:43.180 people living in the lower 48 states, despite being fairly far removed from large population 00:08:43.180 --> 00:08:49.330 centers, it's actually an area that receives a tremendous amount of river discharge. 00:08:49.330 --> 00:08:56.370 Just to give you a number, these coastal Gulf of Alaska rivers discharge about 870 cubic 00:08:56.370 --> 00:08:59.220 kilometers per year. 00:08:59.220 --> 00:09:03.720 Contrast that with the Mississippi River, a much better known river, which discharges 00:09:03.720 --> 00:09:12.210 530 cubic kilometers per year, and the Columbia and the Yukon, around 200 cubic kilometers 00:09:12.210 --> 00:09:13.210 per year. 00:09:13.210 --> 00:09:18.420 Despite the fact that these Gulf of Alaska rivers are relatively obscure to most people, 00:09:18.420 --> 00:09:22.019 they discharge a heck of a lot of water, and that's because there's a lot of precipitation 00:09:22.019 --> 00:09:23.660 in this region. 00:09:23.660 --> 00:09:29.120 That's the main reason, primarily there's a lot of precipitation and then much of that 00:09:29.120 --> 00:09:32.550 drains off into the Gulf of Alaska. 00:09:32.550 --> 00:09:38.000 Another reason this area is of interest, scientifically, is that the Gulf of Alaska, again that's this 00:09:38.000 --> 00:09:45.480 region to the south of Alaska, is referred to as an ironlimited ecosystem. 00:09:45.480 --> 00:09:51.940 That means that iron is a nutrient that limits the growth of phytoplankton, essentially the 00:09:51.940 --> 00:09:57.260 base of the marine food web because of its relative scarcity. 00:09:57.260 --> 00:10:03.430 What I'm showing here in this plot is a global map of nitrate concentrations. 00:10:03.430 --> 00:10:07.910 What you see is that the nitrate concentrations in this Gulf of Alaska region are fairly high. 00:10:07.910 --> 00:10:10.310 That's for a couple of reasons, really. 00:10:10.310 --> 00:10:15.670 It's partly because that's at the end of what's casually referred to as the Global Conveyor 00:10:15.670 --> 00:10:22.880 Belt, the meridional overturning circulation that leads to upwelling of deepwater in this 00:10:22.880 --> 00:10:24.550 north Pacific region. 00:10:24.550 --> 00:10:31.410 So, it's the end of the line in terms of oceanographic circulation, but, in addition, phytoplankton 00:10:31.410 --> 00:10:38.760 growth is ironlimited because of distance from iron sources in this region. 00:10:38.760 --> 00:10:44.790 That is another thing that makes it somewhat unusual relative to the rest of the ocean, 00:10:44.790 --> 00:10:49.089 where nitrate is more typically the limiting nutrient. 00:10:49.089 --> 00:10:53.350 We know that iron is a limiting nutrient, but we don't know very much about the processes 00:10:53.350 --> 00:10:57.529 that transport iron to the ironlimited regions of the Gulf of Alaska. 00:10:57.529 --> 00:11:01.550 Some of this work is going to shed some light on some of those processes. 00:11:01.550 --> 00:11:05.649 This is just a twodimensional schematic that doesn't really do justice to everything, and 00:11:05.649 --> 00:11:14.670 I just want to point out this does not show eddies, which are a phenomenon that can transport 00:11:14.670 --> 00:11:17.810 iron from the coast into the open ocean. 00:11:17.810 --> 00:11:24.009 I'm going to focus on riverine inputs, on dust inputs, on some iron inputs from this 00:11:24.009 --> 00:11:31.490 continental shelf region, and all of these end up being sources of iron that fuel high 00:11:31.490 --> 00:11:34.910 plankton productivity in this shelf region. 00:11:34.910 --> 00:11:41.250 Another thing that makes this part of the world interesting, this is again showing the 00:11:41.250 --> 00:11:48.490 southern Alaska region and the coastal area just south of that glacierdominated area I 00:11:48.490 --> 00:11:49.839 referred to. 00:11:49.839 --> 00:11:55.190 This is a plot of chlorophyll concentration, and you see this high chlorophyll concentration 00:11:55.190 --> 00:11:56.910 in this coastal area. 00:11:56.910 --> 00:12:04.709 Some work by Ware and Thomson in "Science" in 2005 showed a relationship between mean 00:12:04.709 --> 00:12:11.250 chlorophyll concentration and the mean resident fish yield, which they interpreted to mean 00:12:11.250 --> 00:12:15.630 this ecosystem was controlled from the bottom up, in other words, from the base of the food 00:12:15.630 --> 00:12:20.060 web up, and phytoplankton being the base of the food web. 00:12:20.060 --> 00:12:28.250 One of the questions we posed was whether this ecosystem of the Copper River plume region, 00:12:28.250 --> 00:12:35.279 and that, just for your reference, is right around here on this plot, is also controlled 00:12:35.279 --> 00:12:39.589 in similar bottomup ecosystem fashion. 00:12:39.589 --> 00:12:41.660 Why the Copper River? 00:12:41.660 --> 00:12:45.720 We're going to focus on the Copper River, which is one of these rivers that drains into 00:12:45.720 --> 00:12:46.720 the Gulf of Alaska. 00:12:46.720 --> 00:12:49.889 First of all, it's the site of important fisheries. 00:12:49.889 --> 00:12:55.389 It's the single largest freshwater source for the Gulf of Alaska. 00:12:55.389 --> 00:13:00.699 A significant portion of the Copper River watershed is glaciercovered, and that has 00:13:00.699 --> 00:13:05.160 implications for the nutrient cycling and nutrient inputs into the ocean. 00:13:05.160 --> 00:13:11.319 Also, prior to this work there were little or no iron data and few oceanographic observations 00:13:11.319 --> 00:13:12.319 from the vicinity. 00:13:12.319 --> 00:13:17.699 Finally, a more general justification is that river plumes, in other words, the plume of 00:13:17.699 --> 00:13:23.380 water that extends out into the ocean from the river, can serve as protection for various 00:13:23.380 --> 00:13:25.569 organisms from predators. 00:13:25.569 --> 00:13:33.149 This is a plot of Copper River discharge from the Million Dollar Bridge Station, not too 00:13:33.149 --> 00:13:36.050 far from where it discharges into the ocean. 00:13:36.050 --> 00:13:45.339 A bit of an unusual representation of time, but the main point to make here is that...I 00:13:45.339 --> 00:13:48.290 guess there are a couple of main points. 00:13:48.290 --> 00:13:53.680 First of all, discharge increases dramatically in this AprilMay time frame. 00:13:53.680 --> 00:14:00.680 Discharge reaches a peak in JulyAugust, and it's still fairly high in the fall in response 00:14:00.680 --> 00:14:02.259 to various floods. 00:14:02.259 --> 00:14:05.030 This pattern of discharge is typical. 00:14:05.030 --> 00:14:08.540 This is an average discharge from the Copper River. 00:14:08.540 --> 00:14:11.269 It's typical for this region. 00:14:11.269 --> 00:14:16.089 It's quite atypical for probably most of the rivers that most of you who are listening 00:14:16.089 --> 00:14:17.089 are familiar with. 00:14:17.089 --> 00:14:22.630 The reason the discharge peaks in the summer is not that that's when all the precipitation 00:14:22.630 --> 00:14:23.630 happens. 00:14:23.630 --> 00:14:27.550 It's because that's when all the snow and ice melt happens, so you get this massive 00:14:27.550 --> 00:14:31.610 discharge peak in July and August. 00:14:31.610 --> 00:14:36.250 In the winter, from roughly November to March or so, there's very little discharge. 00:14:36.250 --> 00:14:39.629 Again, there's plenty of precipitation. 00:14:39.629 --> 00:14:42.279 This is not evidence of lack of precipitation at that time. 00:14:42.279 --> 00:14:47.190 It's just that the precipitation is freezing and not going out the river. 00:14:47.190 --> 00:14:53.339 This timing is quite different from rivers that many of you might be familiar with, but 00:14:53.339 --> 00:14:58.350 it has implications for the timing of the nutrient inputs into the ocean in this part 00:14:58.350 --> 00:14:59.350 of the world. 00:14:59.350 --> 00:15:06.639 One of the first questions we posed was, "How will the flux and distribution of riverine 00:15:06.639 --> 00:15:13.310 iron delivered to the Gulf of Alaska change due to warming climates and retreating glaciers"? 00:15:13.310 --> 00:15:17.080 First of all, let's just get oriented here. 00:15:17.080 --> 00:15:24.839 We're going to show some data from a series of tributaries from the Copper River watershed. 00:15:24.839 --> 00:15:25.920 Here's Alaska. 00:15:25.920 --> 00:15:33.019 Here, outlined in orange, is the Copper River watershed, and I'm going to show data from 00:15:33.019 --> 00:15:34.690 the set of tributaries. 00:15:34.690 --> 00:15:41.660 This is work that was carried out virtually entirely by Andrew Schroth as part of his 00:15:41.660 --> 00:15:48.319 Mendenhall Postdoctoral Program when he was at Woods Hole. 00:15:48.319 --> 00:15:52.439 This is the Copper River watershed. 00:15:52.439 --> 00:15:57.160 I'm going to show data from a few different river types, but the two main points I want 00:15:57.160 --> 00:16:00.140 to make are that there are these glacierdominated rivers. 00:16:00.140 --> 00:16:04.250 Those of you who have seen glacierdominated rivers have probably seen this type of murky 00:16:04.250 --> 00:16:07.089 water before, this murky gray water. 00:16:07.089 --> 00:16:11.779 It's murky and gray because there's a lot of fine particulate matter in it that results 00:16:11.779 --> 00:16:15.120 from weathering from these glaciers. 00:16:15.120 --> 00:16:16.269 That's one river type. 00:16:16.269 --> 00:16:22.910 Whenever the river drains what we call a "glacierized river valley," this is typically what you 00:16:22.910 --> 00:16:25.380 see, very murky water. 00:16:25.380 --> 00:16:31.970 The other river type is this boreal lowland �blackwater� river type. 00:16:31.970 --> 00:16:41.870 This is a river that drains water that's much lower elevation, no glaciers, but very peaty. 00:16:41.870 --> 00:16:49.509 It's a region that's full of peatlands, wetlands, and, as a consequence, the water gets very 00:16:49.509 --> 00:16:55.220 brown because it has high concentrations of organic acids, high dissolved organic matter 00:16:55.220 --> 00:16:56.220 concentrations. 00:16:56.220 --> 00:17:03.149 This is actually a photo that shows these two river types mixing together when they 00:17:03.149 --> 00:17:08.939 flow into each other, just to show those two river types in one photo. 00:17:08.939 --> 00:17:15.420 I'm going to show how each of these manifests itself in terms of impacts on iron in just 00:17:15.420 --> 00:17:16.420 a minute. 00:17:16.420 --> 00:17:20.480 Here is a picture of the, again, the Copper River watershed. 00:17:20.480 --> 00:17:25.600 These dots represent different tributaries of the Copper River. 00:17:25.600 --> 00:17:31.390 Here's Andrew showing off his trace metal clean river sampling strategy. 00:17:31.390 --> 00:17:35.110 We always get a lot of laughs when we show this image of him in the truck. 00:17:35.110 --> 00:17:40.170 We need to get a different image for that, but that shows the trace metal clean river 00:17:40.170 --> 00:17:41.170 sampling. 00:17:41.170 --> 00:17:47.440 We're going to mention some different size fractions of iron. 00:17:47.440 --> 00:17:51.440 Particulate iron is larger than 0.45 micron. 00:17:51.440 --> 00:17:57.240 Colloidal iron is smaller than 0.45 micron but larger than 0.02 micron, and dissolved 00:17:57.240 --> 00:17:59.930 is less than 0.02 micron. 00:17:59.930 --> 00:18:04.550 This has implications for the fate of that iron as it goes into the ocean, which we'll 00:18:04.550 --> 00:18:06.870 get to in a minute. 00:18:06.870 --> 00:18:14.200 So these different tributary types have different characteristics, the glacierized tributaries...Let 00:18:14.200 --> 00:18:20.740 me back up, I'm plotting colloidal iron. 00:18:20.740 --> 00:18:26.050 You can think of it as small particles, concentration of small particles of iron versus dissolved 00:18:26.050 --> 00:18:27.050 iron. 00:18:27.050 --> 00:18:35.150 This is stuff that passes through a very fine filter and it's truly in solution, truly dissolved. 00:18:35.150 --> 00:18:39.930 These two different river types have very different iron types. 00:18:39.930 --> 00:18:47.260 There's the largely particulate iron that's common in these glacierized watersheds and 00:18:47.260 --> 00:18:52.610 a largely dissolved iron in these wetland dominated rivers. 00:18:52.610 --> 00:18:57.450 You can see that in a different way when you plot colloidal iron versus colloidal silica. 00:18:57.450 --> 00:19:05.340 Essentially, the glacierdominated rivers have both fine particulate iron and fine particulate 00:19:05.340 --> 00:19:08.470 silica because it's essentially ground-up rock. 00:19:08.470 --> 00:19:12.790 There's ground-up rock that is giving it that milky gray color. 00:19:12.790 --> 00:19:20.170 That's a source of iron, that's also a source of dissolved silica, versus the boreal forested 00:19:20.170 --> 00:19:27.680 rivers which show much lower dissolved silica concentration and, typically, smaller concentrations 00:19:27.680 --> 00:19:30.590 of iron as well. 00:19:30.590 --> 00:19:37.521 Andrew did some time series river sampling that I don't have time to show, but I just 00:19:37.521 --> 00:19:40.760 want to acknowledge that that work is a big part of this project as well. 00:19:40.760 --> 00:19:45.090 I'm going to jump ahead to some work that Andrew and I did at the mouth of the Copper 00:19:45.090 --> 00:19:46.090 River. 00:19:46.090 --> 00:19:51.970 Here is a satellite image of the Copper River and you see this muddy river plume extending 00:19:51.970 --> 00:19:54.420 into the ocean. 00:19:54.420 --> 00:19:59.490 On the right is actually a close up of that taken with a camera. 00:19:59.490 --> 00:20:07.900 On the left is this muddy river plume, freshwater, on the right is seawater, and this front occurs 00:20:07.900 --> 00:20:13.750 over a space of centimeters really, it's really dramatic. 00:20:13.750 --> 00:20:19.010 What is known from the iron literature is that dissolved iron tends to be removed in 00:20:19.010 --> 00:20:20.130 estuaries. 00:20:20.130 --> 00:20:26.070 Now, the estuary of the Copper River is quite different from what most of you might be familiar 00:20:26.070 --> 00:20:29.230 with when you think of an estuary. 00:20:29.230 --> 00:20:34.930 The Copper River is more this abrupt front from fresh to salt rather than a gradual mixing 00:20:34.930 --> 00:20:36.170 of the two. 00:20:36.170 --> 00:20:42.660 We did our best to try to sample across this front and I'm going to focus first on this 00:20:42.660 --> 00:20:49.170 plot on the lower right where I'm plotting dissolved iron versus salinity. 00:20:49.170 --> 00:20:52.210 The dissolved iron concentrations that have low salinity are quite high. 00:20:52.210 --> 00:20:55.090 That's because of this fresh water input into the ocean. 00:20:55.090 --> 00:21:00.350 At high salinity they're low, because that iron is getting diluted with iron poor sea 00:21:00.350 --> 00:21:02.280 water. 00:21:02.280 --> 00:21:13.550 If you had mixing of freshwater with sea water with no iron removal, the data points would 00:21:13.550 --> 00:21:18.690 fall on a line, looking something like this for my pretty much a straight line. 00:21:18.690 --> 00:21:24.410 Instead what you see is this pronounced curve where the iron concentration has dropped dramatically 00:21:24.410 --> 00:21:30.230 as you go into the salt water and then they stay fairly low. 00:21:30.230 --> 00:21:35.510 That shape is characteristic of dissolved iron removal. 00:21:35.510 --> 00:21:42.040 What happens is the organic iron complex readily flocculates and is removed. 00:21:42.040 --> 00:21:50.870 What that means is iron from these lowland, wetland dominated rivers is largely removed 00:21:50.870 --> 00:21:52.110 when it hits the ocean. 00:21:52.110 --> 00:21:58.650 By contrast, this total dissolvable iron is a measure of the particulate iron. 00:21:58.650 --> 00:22:06.970 This iron concentration, also quite high, shows different characteristics, it's largely 00:22:06.970 --> 00:22:13.200 a linear behavior between freshwater and saline water. 00:22:13.200 --> 00:22:17.190 What that means is a lot of the particulate iron in other words, a lot of the particulate 00:22:17.190 --> 00:22:22.140 iron is coming out from the glacier, this muddy, gray stuff is actually getting mixed 00:22:22.140 --> 00:22:23.830 out into the ocean without a lot of removal. 00:22:23.830 --> 00:22:30.050 So that has some big implications, the fact that that fine particulate stuff largely persists 00:22:30.050 --> 00:22:31.580 in the ocean. 00:22:31.580 --> 00:22:40.090 That's a very quick summary of the terrestrial sampling, I'm going to show you a summary 00:22:40.090 --> 00:22:44.680 of the marine sampling that we did on this transect from the Copper River mouth. 00:22:44.680 --> 00:22:46.260 Here is the Copper River. 00:22:46.260 --> 00:22:50.570 Again, here is Alaska, here's the mouth of the Copper River. 00:22:50.570 --> 00:22:56.550 This is the continental shelf break, our transect extended from the mouth of the Copper River 00:22:56.550 --> 00:22:59.740 out beyond the continental shelf break. 00:22:59.740 --> 00:23:04.960 We sampled on this ship, the RB Montague, based out of Cordova, Alaska. 00:23:04.960 --> 00:23:08.790 I'm just going to quickly show you some trace metal clean sampling equipment. 00:23:08.790 --> 00:23:20.010 We used this Teflon vein that was put in the water, it houses Teflon line tubing. 00:23:20.010 --> 00:23:24.080 This thing here is submerged below the water. 00:23:24.080 --> 00:23:29.620 There's a pump on the ship that runs all the time and sucks up water from this intake through 00:23:29.620 --> 00:23:34.350 the tubing, up through here, it comes into this lab. 00:23:34.350 --> 00:23:39.551 Here's an inside shot of the lab and you see this tubing coming to the lab. 00:23:39.551 --> 00:23:41.620 This is Andrew Schroth's sampling. 00:23:41.620 --> 00:23:49.550 Essentially, while the ship is moving, we can sample trace metal clean water just by 00:23:49.550 --> 00:23:50.920 turning a tap. 00:23:50.920 --> 00:23:52.550 It's pretty cool. 00:23:52.550 --> 00:23:58.390 The time from sample intake to sample collection is about one minute. 00:23:58.390 --> 00:24:00.250 It's quite a quick process. 00:24:00.250 --> 00:24:04.670 I'm going to show you some data from that sample collection system, which is necessary, 00:24:04.670 --> 00:24:09.320 that I should point out, to collect uncontaminated samples for iron. 00:24:09.320 --> 00:24:15.790 One thing about iron is it's easy to contaminate when you're sampling from a big, rusty ship, 00:24:15.790 --> 00:24:18.290 because their concentrations are pretty low in the ocean typically. 00:24:18.290 --> 00:24:23.110 This is some of the motivation for this marine work. 00:24:23.110 --> 00:24:25.030 This is an image of chlorophyll. 00:24:25.030 --> 00:24:30.270 Here is Prince William Sound, to orient you, here is the Copper River. 00:24:30.270 --> 00:24:31.270 Red is high chlorophyll. 00:24:31.270 --> 00:24:35.530 This is from May of 2009, which is actually a year before our sampling started. 00:24:35.530 --> 00:24:39.701 But the main point here is there are these high plumes of chlorophyll in this coastal 00:24:39.701 --> 00:24:45.530 region that respond, we think, to high concentrations of nutrients. 00:24:45.530 --> 00:24:50.900 Our sampling was designed to examine some of those nutrient sources and try to understand 00:24:50.900 --> 00:24:58.050 what's causing this phytoplankton biomass and, I should say, high productivity as well. 00:24:58.050 --> 00:25:04.150 One thing that the oceanographers in the crowd will already know, but I'll mention it to 00:25:04.150 --> 00:25:09.620 those people who don't, who aren't oceanographers, this process of upwelling is a process by 00:25:09.620 --> 00:25:20.250 which deep water from the ocean is driven to the surface where the nutrients contained 00:25:20.250 --> 00:25:25.170 therein can be used by surface dwelling organisms like phytoplankton. 00:25:25.170 --> 00:25:31.780 The northern Gulf of Alaska, which I will refer to, periodically, as the GoA, is a downwelling 00:25:31.780 --> 00:25:32.780 area. 00:25:32.780 --> 00:25:36.680 In other words, it's predominantly downwelling. 00:25:36.680 --> 00:25:40.090 The water from the depth is not being raised to the surface. 00:25:40.090 --> 00:25:41.980 There's actually water from the surface going down. 00:25:41.980 --> 00:25:49.030 This is a NOAA daily upwelling index which is a function of wind largely. 00:25:49.030 --> 00:25:52.920 But the point here is that there's downwelling, so we go into this process by which deep water 00:25:52.920 --> 00:25:56.750 gets raised to the surface, except on fairly rare occasion. 00:25:56.750 --> 00:26:01.460 What's interesting is despite the fact that this area is a downwelling area, you still 00:26:01.460 --> 00:26:07.390 get high concentrations of nutrients sufficient to drive high productivity in this coastal 00:26:07.390 --> 00:26:08.390 area. 00:26:08.390 --> 00:26:12.850 Those processes are not that well understood and that was part of the motivation for this 00:26:12.850 --> 00:26:15.160 work. 00:26:15.160 --> 00:26:23.210 Here are some basic oceanographic observations from this coastal Gulf of Alaska area. 00:26:23.210 --> 00:26:28.370 This is just salinity in the top 40 meters of water. 00:26:28.370 --> 00:26:30.750 A lot of information on this slide. 00:26:30.750 --> 00:26:34.510 This is collected using this device called the mini bat by Rob Campbell of the Prince 00:26:34.510 --> 00:26:38.380 William Sound Science Center as part of our coastal cruises. 00:26:38.380 --> 00:26:45.470 This thing flies through the water going up and down to depths of up to 30 or 40 meters. 00:26:45.470 --> 00:26:57.070 It can essentially map out a 2D map of parameters that can be measured, in this case, salinity. 00:26:57.070 --> 00:26:58.860 Salinity of zero is freshwater. 00:26:58.860 --> 00:27:03.420 Salinity of 35 is truly sea water. 00:27:03.420 --> 00:27:06.930 There's a series of time slices here. 00:27:06.930 --> 00:27:12.640 What I want to point out is that in March the salinity is pretty boring, it's all fairly 00:27:12.640 --> 00:27:15.870 uniform at salinity of about 32 or so. 00:27:15.870 --> 00:27:17.640 That's because the water comes well mixed. 00:27:17.640 --> 00:27:21.860 You've got deep winter storms, there's not really any significant river discharge at 00:27:21.860 --> 00:27:23.510 that time of year. 00:27:23.510 --> 00:27:30.670 But starting in May you begin to see this yellow and blue region at the very surface. 00:27:30.670 --> 00:27:38.270 It's a very thin layer, only a few meters deep and extending some tens of kilometers 00:27:38.270 --> 00:27:39.770 off shore. 00:27:39.770 --> 00:27:47.770 But that is the river plume manifesting itself as freshwater discharge. 00:27:47.770 --> 00:27:51.450 Remember, there's not much river discharge in the winter, hence you don't see it in the 00:27:51.450 --> 00:27:52.450 winter. 00:27:52.450 --> 00:27:55.460 But starting in May and June you start to see this freshwater plume. 00:27:55.460 --> 00:27:59.350 That has big implications for all sorts of things. 00:27:59.350 --> 00:28:00.350 OK. 00:28:00.350 --> 00:28:03.250 One of those things is iron. 00:28:03.250 --> 00:28:08.420 In April, which is early in the season, again, the water column is well mixed. 00:28:08.420 --> 00:28:16.760 You get these deep storms and deep storms lead to churning up of the bottom of sediments. 00:28:16.760 --> 00:28:21.920 That's visible in this satellite image from up above where you can actually see this murky 00:28:21.920 --> 00:28:27.060 gray iron rich water in this whole coastal region. 00:28:27.060 --> 00:28:32.000 This blue line represents the 500 meter contour getting into deep water. 00:28:32.000 --> 00:28:37.640 But up until that point pretty much everything is this murky gray and that shows up in our 00:28:37.640 --> 00:28:38.650 iron data. 00:28:38.650 --> 00:28:43.620 This is what we refer to as dissolvable iron. 00:28:43.620 --> 00:28:49.380 It's the iron that dissolves from an unfiltered sample at pH 2. 00:28:49.380 --> 00:28:53.440 I think of it as a measure of the particle concentration of the water. 00:28:53.440 --> 00:28:56.000 Essentially, it crosses the entire continental shelf region. 00:28:56.000 --> 00:29:00.680 There are very high concentrations of particulate iron and then it drops off beyond that. 00:29:00.680 --> 00:29:06.010 This continental shelf break shown with this arrow is a real break point. 00:29:06.010 --> 00:29:11.730 It's a real point beyond which the things really change and you see that the iron concentrations 00:29:11.730 --> 00:29:15.240 drop off dramatically beyond that. 00:29:15.240 --> 00:29:20.890 Green is a measure of the dissolved iron, that which goes through a filter. 00:29:20.890 --> 00:29:22.470 That's more what the phytoplankton actually use. 00:29:22.470 --> 00:29:28.540 But you see that also drops off once you get beyond that continental shelf break. 00:29:28.540 --> 00:29:35.020 In response to all that iron, the nitrate gets consumed. 00:29:35.020 --> 00:29:41.210 These are actual depth profiles of nitrate from the same time frame. 00:29:41.210 --> 00:29:43.670 In green I'm showing nitrate in April. 00:29:43.670 --> 00:29:48.510 Nitrate concentrations are pretty boring in April, they're pretty uniform, consistent 00:29:48.510 --> 00:29:51.380 with that initial slide that I showed you. 00:29:51.380 --> 00:29:56.830 The nitrate profiles are roughly 18 micromolars, which is a high concentration. 00:29:56.830 --> 00:30:01.100 But by July that nitrate is largely gone in the surface water. 00:30:01.100 --> 00:30:09.490 So high nitrate in spring, by the summertime that nitrate is gone, that's because there's 00:30:09.490 --> 00:30:16.140 abundant iron and the iron is sufficient to allow complete draw down of this nitrate. 00:30:16.140 --> 00:30:20.970 Now, I want to draw your attention to a couple things, which I'm going to help make sense 00:30:20.970 --> 00:30:22.550 of something in a minute. 00:30:22.550 --> 00:30:27.300 Note that the nitrate concentration is depleted in the surface waters in these more offshore 00:30:27.300 --> 00:30:33.580 stations, but there are still plenty of nitrates below a depth of a few tens of meters in this 00:30:33.580 --> 00:30:34.630 July timeframe. 00:30:34.630 --> 00:30:39.000 That's going to help make some sense of something in a minute. 00:30:39.000 --> 00:30:46.300 Here is a plot of chlorophyll as a function of both time and distance. 00:30:46.300 --> 00:30:54.700 This is distance from the coast, from 0 to 25 kilometers, over time, from March through 00:30:54.700 --> 00:30:56.160 August. 00:30:56.160 --> 00:31:01.460 The thing to remember is that blue is low chlorophyll. 00:31:01.460 --> 00:31:02.880 Red is high chlorophyll. 00:31:02.880 --> 00:31:06.520 Chlorophyll is an indication of phytoplankton concentration, again, phytoplankton being 00:31:06.520 --> 00:31:09.250 the base of the marine food chain. 00:31:09.250 --> 00:31:14.460 In blue, early in the season in March, it's quite boring. 00:31:14.460 --> 00:31:15.460 There's essentially no chlorophyll. 00:31:15.460 --> 00:31:17.270 There's no fresh water discharge. 00:31:17.270 --> 00:31:21.060 There's very little light, at least not enough light to initiate a bloom. 00:31:21.060 --> 00:31:28.900 Starting in May, remember we got that river discharge, you get riverine input that is 00:31:28.900 --> 00:31:39.360 causing a freshwater lens at the surface in response to the freshwater input as well as 00:31:39.360 --> 00:31:42.030 the increased light levels at that time of year. 00:31:42.030 --> 00:31:45.650 You see this chlorophyll layer, this high chlorophyll layer. 00:31:45.650 --> 00:31:51.980 In other words, the phytoplankton are responding to the nutrients and the light in the surface 00:31:51.980 --> 00:31:53.810 water. 00:31:53.810 --> 00:32:01.720 By May 28th, note that the phytoplankton are largely...The concentrations are much lower 00:32:01.720 --> 00:32:06.000 in this nearshore region on May 28th. 00:32:06.000 --> 00:32:12.840 But, by the middle of May, the phytoplankton in this midshore region, at a distance about 00:32:12.840 --> 00:32:18.830 10 to 20 kilometers or so, they've moved deeper in the water column. 00:32:18.830 --> 00:32:20.180 They're about 20 meters. 00:32:20.180 --> 00:32:26.890 Remember, the nitrate was largely consumed by this time, so what the phytoplankton are 00:32:26.890 --> 00:32:31.830 doing, they're actually moving down in the water column in response to the presence of 00:32:31.830 --> 00:32:35.890 the essential nutrient, nitrate, down there. 00:32:35.890 --> 00:32:43.600 By June, July, August, the phytoplankton concentrations across this whole transect are noticeably 00:32:43.600 --> 00:32:44.880 lower. 00:32:44.880 --> 00:32:51.500 Again, these are data by Rob Campbell from the Prince William Sound Science Center and 00:32:51.500 --> 00:32:55.980 collected as part of our joint cruises in this region. 00:32:55.980 --> 00:33:01.850 I want to acknowledge as well the extensive work by Laurel McFadden, who was a Master's 00:33:01.850 --> 00:33:05.340 student of Rob Campbell at the University of Alaska, Anchorage. 00:33:05.340 --> 00:33:10.440 She did some extensive work on the distribution and ecology of zooplankton and juvenile pelagic 00:33:10.440 --> 00:33:13.080 fishes in the Copper River plume. 00:33:13.080 --> 00:33:20.340 I don't have time to give this work justice, so I'm just going to acknowledge her extensive 00:33:20.340 --> 00:33:24.820 work and move on from there. 00:33:24.820 --> 00:33:31.310 I'm going to jump back very quickly to iron. 00:33:31.310 --> 00:33:37.360 Now remember, the freshwater discharge maxes out in July and August in the Copper River. 00:33:37.360 --> 00:33:45.260 This is this transect from shore, from the mouth of the Copper River offshore again. 00:33:45.260 --> 00:33:48.510 What you see is this low salinity water. 00:33:48.510 --> 00:33:54.960 I'm plotting both iron and salinity on the same plot as a function of distance from shore 00:33:54.960 --> 00:33:56.210 in July. 00:33:56.210 --> 00:34:02.070 You see this low salinity water with extremely high concentrations of iron. 00:34:02.070 --> 00:34:10.020 That's this particulate iron coming in from this massive river discharge that's happening. 00:34:10.020 --> 00:34:18.190 In fact, if you look closely at this plot, you see that iron and salinity, they covary 00:34:18.190 --> 00:34:19.540 at this time of year. 00:34:19.540 --> 00:34:22.669 Whenever the salinity is low, the iron is high. 00:34:22.669 --> 00:34:25.879 Whenever the salinity is high, the iron is low. 00:34:25.879 --> 00:34:31.619 What that's telling us is that the iron at this time of year is coming from this glacial 00:34:31.619 --> 00:34:37.069 melt water, and it's a pretty dramatic effect. 00:34:37.069 --> 00:34:44.139 Just a quick mention of interesting phenomena of nitrate. 00:34:44.139 --> 00:34:49.000 Remember nitrate is the limiting nutrient for phytoplankton in much of this transect. 00:34:49.000 --> 00:34:56.500 At this low salinity time of year when the river discharge is at its maximum, we see 00:34:56.500 --> 00:35:03.260 these low salinity surface waters and these nearshore stations offshore the Copper River. 00:35:03.260 --> 00:35:08.210 We also see a slight enrichment in nitrate in those surface waters. 00:35:08.210 --> 00:35:14.859 Remember this is a time of year when, by and large, the oceanderived nitrate is consumed, 00:35:14.859 --> 00:35:20.960 but what we see is that there's nitrate enrichment in this river plume water. 00:35:20.960 --> 00:35:26.450 It's suggestive, although not entirely convincing, that the river is becoming a source of nitrate 00:35:26.450 --> 00:35:27.920 at that time of year. 00:35:27.920 --> 00:35:31.640 There are a couple of possible explanations for that. 00:35:31.640 --> 00:35:37.009 One of which is that there could be nitrogenfixing plants that are invading the landscape that 00:35:37.009 --> 00:35:39.710 are causing this nitrate delivery. 00:35:39.710 --> 00:35:44.079 There are some other possibilities as well. 00:35:44.079 --> 00:35:49.220 Very briefly, I'm going to quickly mention another mechanism by which iron gets into 00:35:49.220 --> 00:35:52.380 the Gulf of Alaska and gets transported a long distance. 00:35:52.380 --> 00:35:56.440 Again, this is the Copper River region. 00:35:56.440 --> 00:36:01.210 What we're looking at in this instance is a satellite image of dust. 00:36:01.210 --> 00:36:08.410 This gray plume that you see...Here's the scale for reference, 0 to 100 kilometers or 00:36:08.410 --> 00:36:09.410 so. 00:36:09.410 --> 00:36:15.119 This gray plume is actually atmospherically transported dust that originates in the Copper 00:36:15.119 --> 00:36:19.529 River but also at some other sites along the coastline. 00:36:19.529 --> 00:36:27.359 This image was created using the MODIS sensor on satellites. 00:36:27.359 --> 00:36:35.130 It's a snapshot in time from November 6, 2006. 00:36:35.130 --> 00:36:41.000 I just want to highlight the location of Middleton Island because, in response to this observation 00:36:41.000 --> 00:36:46.349 that there are these dust events blowing iron and glacierderived dust out into the ocean, 00:36:46.349 --> 00:36:51.559 we set up a measurement station out on Middleton Island. 00:36:51.559 --> 00:36:53.010 Why dust in the autumn? 00:36:53.010 --> 00:36:55.240 The river levels are low, as I mentioned earlier. 00:36:55.240 --> 00:36:57.450 There's little or no snow. 00:36:57.450 --> 00:37:02.710 There are these abundant exposed sediments. 00:37:02.710 --> 00:37:09.549 They're essentially leftover glacial flour from the weathering that the glacier has achieved 00:37:09.549 --> 00:37:10.549 all summer long. 00:37:10.549 --> 00:37:12.780 This is fine sediment just sitting there. 00:37:12.780 --> 00:37:19.720 What happens is you get strong winds blowing out of these mountains that resuspend a lot 00:37:19.720 --> 00:37:25.359 of this material and transport it far offshore. 00:37:25.359 --> 00:37:27.069 I alluded to Middleton Island. 00:37:27.069 --> 00:37:29.880 Here's a satellite image from November 2011. 00:37:29.880 --> 00:37:35.410 It's not nearly as dramatic an event as the other event I showed you. 00:37:35.410 --> 00:37:42.160 Nonetheless, we have aerosol measurements from this time interval, and, in fact, you 00:37:42.160 --> 00:37:50.279 see dust being transported and being captured by our sampling system out on Middleton Island 00:37:50.279 --> 00:37:54.339 at exactly the same time that you see this dust in the air. 00:37:54.339 --> 00:37:59.450 This actually was a fairly modest event by the scale of other events that we've seen 00:37:59.450 --> 00:38:00.450 in the past. 00:38:00.450 --> 00:38:04.970 This past year, the fall of 2012, we had a much more dramatic event. 00:38:04.970 --> 00:38:09.900 I don't have the chemistry data to share with you, but we have the samples, and there's 00:38:09.900 --> 00:38:11.950 a lot of dust on those samples. 00:38:11.950 --> 00:38:14.569 This is just showing you the sampling equipment. 00:38:14.569 --> 00:38:16.799 Here's an aerial view of Middleton Island. 00:38:16.799 --> 00:38:19.740 This is our aerosol sampler system. 00:38:19.740 --> 00:38:25.460 I'm going to move forward just because I want to get to the end here. 00:38:25.460 --> 00:38:29.380 That's a very, very, very quick overview of some of the sampling. 00:38:29.380 --> 00:38:37.940 Now I want to give you a sense of some of the modeling that's been done by a group based 00:38:37.940 --> 00:38:41.660 at the University of Maine. 00:38:41.660 --> 00:38:48.019 I'm going to show you work for which Yuan Wang is the first author. 00:38:48.019 --> 00:38:54.490 He was a graduate student of Fei Chai and Huijie Xue at the University of Maine, and 00:38:54.490 --> 00:39:07.049 they took an existing Gulf of Alaska physical model and added Copper River discharge to 00:39:07.049 --> 00:39:08.049 that model. 00:39:08.049 --> 00:39:10.640 What I'm going to show you is the results of that work. 00:39:10.640 --> 00:39:12.660 Again, here's Alaska. 00:39:12.660 --> 00:39:15.480 Here's the Copper River watershed. 00:39:15.480 --> 00:39:18.210 Here's a brief model description. 00:39:18.210 --> 00:39:22.950 This is what's referred to as a ROMS model. 00:39:22.950 --> 00:39:26.510 ROMS is short for Regional Ocean Modeling System. 00:39:26.510 --> 00:39:33.080 It's what's referred to as a threelevel nested model. 00:39:33.080 --> 00:39:41.970 In other words, there are different regions of the ocean that get sampled at higher and 00:39:41.970 --> 00:39:43.790 higher resolution within the model. 00:39:43.790 --> 00:39:50.619 There's this coarser resolution region up here, smaller region at finer resolution, 00:39:50.619 --> 00:39:59.380 and finest resolution at this Copper River mouth region. 00:39:59.380 --> 00:40:04.079 There's horizontal resolution of 3.6 kilometers and 40 vertical layers. 00:40:04.079 --> 00:40:08.779 I'm going to show you results from 2010 and 2011, our sampling period. 00:40:08.779 --> 00:40:16.359 Essentially what these guys have done is created a modeling tool that can be used to simulate 00:40:16.359 --> 00:40:22.799 the entire Gulf of Alaska and, in particular, simulate how it's influenced by discharge 00:40:22.799 --> 00:40:23.809 from the Copper River. 00:40:23.809 --> 00:40:32.880 They used realistic model forcing, including North American Mesoscale Model meteorology. 00:40:32.880 --> 00:40:40.269 They use river discharge from the USGS office in Anchorage, including realtime freshwater 00:40:40.269 --> 00:40:45.869 observations and nutrient concentrations, specifically nitrate concentrations based 00:40:45.869 --> 00:40:47.980 on the river sampling that we did. 00:40:47.980 --> 00:40:50.509 They used three model cases. 00:40:50.509 --> 00:40:52.809 I'm going to show you two of those. 00:40:52.809 --> 00:40:59.130 I'm going to show you their model results with typical river discharge and also double 00:40:59.130 --> 00:41:00.369 discharge. 00:41:00.369 --> 00:41:09.140 The double discharge is an example of what would happen in an extreme case of warming 00:41:09.140 --> 00:41:12.730 where the discharge coming out of the Copper River is greatly increased. 00:41:12.730 --> 00:41:22.930 That is a substantial increase, but they did that largely to demonstrate what such a substantial 00:41:22.930 --> 00:41:24.520 increase would cause. 00:41:24.520 --> 00:41:28.930 When you use smaller perturbations, the changes are not quite so obvious. 00:41:28.930 --> 00:41:33.579 I should say right up front, this is definitely their work. 00:41:33.579 --> 00:41:41.369 I am not a modeler, and so I'm doing my best to describe what I can of their model. 00:41:41.369 --> 00:41:49.460 I might have had them present this, but the two lead scientists from this modeling effort 00:41:49.460 --> 00:41:54.190 are both in China right now, so we made a decision that I would present it for them, 00:41:54.190 --> 00:41:55.190 and I'll do my best. 00:41:55.190 --> 00:41:57.990 This is the model topography. 00:41:57.990 --> 00:42:01.519 Again, this is the Copper River. 00:42:01.519 --> 00:42:09.869 What you see, this blocky land, that is what really gets simulated in the model. 00:42:09.869 --> 00:42:10.869 This is Prince William Sound. 00:42:10.869 --> 00:42:12.460 This is the Copper River. 00:42:12.460 --> 00:42:15.730 These are our sampling stations over here, just off the Copper River. 00:42:15.730 --> 00:42:21.210 I'm going to show you also data from this mooring in the coastal region off Seward, 00:42:21.210 --> 00:42:22.779 this GAK1 location. 00:42:22.779 --> 00:42:32.119 GAK, is short for Gulf of Alaska, 1, just to orient you here. 00:42:32.119 --> 00:42:36.630 For those of you who are not oceanographers, it's well known and has been known for quite 00:42:36.630 --> 00:42:43.050 a long time there's a pattern of circulation that's well documented for the Gulf of Alaska. 00:42:43.050 --> 00:42:48.701 You have these coastal currents that come along the coastline from the south, and they 00:42:48.701 --> 00:42:53.930 bend along this northern Gulf of Alaska area to the west, and then they turn back south 00:42:53.930 --> 00:42:55.309 again. 00:42:55.309 --> 00:42:56.920 That's well known. 00:42:56.920 --> 00:43:00.190 You're going to see that show up in the model simulation in just a minute. 00:43:00.190 --> 00:43:04.890 Right now, I'm walking you through some still slides, and I'm going to do a model simulation 00:43:04.890 --> 00:43:09.499 at the very end just in case there are any hangups, so we won't be delayed by that hangup 00:43:09.499 --> 00:43:10.519 in the model. 00:43:10.519 --> 00:43:18.330 These are comparisons of the model results with this GAK1 mooring, this coastal site. 00:43:18.330 --> 00:43:25.640 The blue data are actual observations, actual measurements of salinity at 20 meters. 00:43:25.640 --> 00:43:27.749 The red is a model. 00:43:27.749 --> 00:43:29.059 It's not a perfect match. 00:43:29.059 --> 00:43:37.700 You'll see that in the winter, typically the model salinity is a little bit low, and the 00:43:37.700 --> 00:43:40.940 timing of these changes is not spot on. 00:43:40.940 --> 00:43:47.930 But in general, it captures the overall flavor of this variability in salinity in response 00:43:47.930 --> 00:43:50.720 to oceanographic processes. 00:43:50.720 --> 00:43:53.960 The model does a pretty good job although obviously not perfect. 00:43:53.960 --> 00:43:58.799 This is a simulation of temperature. 00:43:58.799 --> 00:44:08.549 The model does a pretty good job of simulating temperature. 00:44:08.549 --> 00:44:15.359 Temperatures are a little bit cooler in the model much of the time, but they're pretty 00:44:15.359 --> 00:44:16.359 close. 00:44:16.359 --> 00:44:24.160 What I'm going to show you is the results of a tracer experiment where they initiated 00:44:24.160 --> 00:44:26.759 this modelonly tracer. 00:44:26.759 --> 00:44:30.740 There's essentially discharge happening from the Copper River and coming out of the Copper 00:44:30.740 --> 00:44:31.740 River. 00:44:31.740 --> 00:44:36.030 This is just to show where this water from the Copper River goes and what happens to 00:44:36.030 --> 00:44:38.829 it and what the impacts are of some of that water. 00:44:38.829 --> 00:44:41.150 This is not really salinity. 00:44:41.150 --> 00:44:45.539 You can think of it as freshwater, but it's not really. 00:44:45.539 --> 00:44:48.930 It's something that you can do in a model that's a lot harder to do in the real world. 00:44:48.930 --> 00:44:54.950 They essentially created this fake parameter that they could trace, essentially just to 00:44:54.950 --> 00:44:57.829 show where the Copper River discharge goes. 00:44:57.829 --> 00:45:02.470 That was the whole point of it. 00:45:02.470 --> 00:45:09.250 Just to give some background, this two times discharge is not completely arbitrary. 00:45:09.250 --> 00:45:11.269 It's quite a big perturbation. 00:45:11.269 --> 00:45:19.290 Ed Josberger's work from the Bering Glacier suggests that if we had substantial warming 00:45:19.290 --> 00:45:28.650 to the tune of about four or five degrees, you would get double the melt discharge, double 00:45:28.650 --> 00:45:35.829 the summer discharge from the Bering Glacier, just to give you a rough idea. 00:45:35.829 --> 00:45:39.799 Again, I'm going to show you still shots, which are not as instructive as the video, 00:45:39.799 --> 00:45:45.710 but I'm going to do it just because there's potential that the video's going to have problems. 00:45:45.710 --> 00:45:54.250 In a nutshell, these are simulations from July 10th, from both 2010 and 2011. 00:45:54.250 --> 00:46:00.130 This upper left panel is just the normal discharge with the normal river discharge. 00:46:00.130 --> 00:46:04.519 You see this Copper River plume extending out into the ocean. 00:46:04.519 --> 00:46:11.339 With two times the river discharge, you see a much larger area impacted by that Copper 00:46:11.339 --> 00:46:12.450 River plume. 00:46:12.450 --> 00:46:18.430 2011, it's a little bit different because the conditions were a little bit different, 00:46:18.430 --> 00:46:21.250 but the contrast is the same pretty much. 00:46:21.250 --> 00:46:30.789 The region affected by this discharge being doubled is quite a bit larger than in the 00:46:30.789 --> 00:46:32.900 normal river discharge example. 00:46:32.900 --> 00:46:40.450 Just to give a sense of where this water's going in terms of a mass balance, if you have 00:46:40.450 --> 00:46:48.650 a hundred units of water coming out of the Copper River, a lot of it is going to be transported, 00:46:48.650 --> 00:46:51.829 as I mentioned before, to the west. 00:46:51.829 --> 00:46:54.840 Some of it's going to go into Prince William Sound. 00:46:54.840 --> 00:46:56.749 Some of it's going to come back out of Prince William Sound. 00:46:56.749 --> 00:47:04.270 Almost none of it is going to travel to the east because the prevailing currents are towards 00:47:04.270 --> 00:47:06.339 the west. 00:47:06.339 --> 00:47:10.940 What I want to draw your attention to at the moment is this contrast in what is transported 00:47:10.940 --> 00:47:13.650 offshore. 00:47:13.650 --> 00:47:17.339 The red line is the normal river discharge transport. 00:47:17.339 --> 00:47:23.430 It's only 3.8 percent of the total, but contrast that with the two times river discharge. 00:47:23.430 --> 00:47:29.609 If you double the river discharge, you have a 300 percent increase in offshore transport. 00:47:29.609 --> 00:47:38.920 In other words, it's three times as much transport offshore of this riverinfluenced water. 00:47:38.920 --> 00:47:47.369 That's one important difference of this double discharge scenario on the physical circulation. 00:47:47.369 --> 00:47:55.800 As a part outreach and part science effort, Rob Campbell conducted an experiment in collaboration 00:47:55.800 --> 00:47:57.779 with the native village of Eyak. 00:47:57.779 --> 00:48:00.930 This is a native group in Cordova, Alaska. 00:48:00.930 --> 00:48:02.910 Again, this is Prince William Sound. 00:48:02.910 --> 00:48:04.490 This is the Copper River. 00:48:04.490 --> 00:48:06.140 They released these drifters. 00:48:06.140 --> 00:48:10.220 These are devices that essentially float with the water. 00:48:10.220 --> 00:48:16.119 They did it three times in 2011, in March, May, and July. 00:48:16.119 --> 00:48:21.960 These devices have GPS on them, so they can be tracked and see where they go over time 00:48:21.960 --> 00:48:23.480 and see where they end up. 00:48:23.480 --> 00:48:31.430 What you see is, at all times, these drifters were transported along the coast and to the 00:48:31.430 --> 00:48:38.549 west as the theory would predict and as the model would predict. 00:48:38.549 --> 00:48:40.410 Some of them went into Prince William Sound. 00:48:40.410 --> 00:48:42.579 Some of them came back out. 00:48:42.579 --> 00:48:49.430 The drifter experiment, while limited in scope with only three drifters, essentially confirms 00:48:49.430 --> 00:48:51.980 the predictions of the model. 00:48:51.980 --> 00:48:53.980 It's a nice validation. 00:48:53.980 --> 00:48:59.609 I mentioned it's part outreach, part science experiment, but it's a neat confirmation of 00:48:59.609 --> 00:49:03.509 what we think we know about circulation in the area. 00:49:03.509 --> 00:49:07.329 I'm just going to conclude, and then I'm going to come back and show that video. 00:49:07.329 --> 00:49:12.849 Just to conclude, I hope I convinced you that glaciers are losing mass in the Gulf of Alaska 00:49:12.849 --> 00:49:16.509 region, as in other regions worldwide. 00:49:16.509 --> 00:49:20.650 Glacier melt is a source of iron to the coastal Gulf of Alaska region. 00:49:20.650 --> 00:49:28.460 There's summertime river discharge, when much of the fine particulate mass in that river 00:49:28.460 --> 00:49:32.289 actually gets out of the ocean and escapes the estuary. 00:49:32.289 --> 00:49:36.619 Hence that glacierdriven discharge is important. 00:49:36.619 --> 00:49:42.030 In the wintertime, there's sediment resuspension from the continental shelf region. 00:49:42.030 --> 00:49:44.849 That still is this fine particulate matter from the glacier. 00:49:44.849 --> 00:49:49.670 It's just that it's settled out into the sediments, but it gets resuspended every year in the 00:49:49.670 --> 00:49:51.309 winter. 00:49:51.309 --> 00:49:57.239 In the autumn, there's dust derived from these winds that race down those mountain valleys 00:49:57.239 --> 00:50:02.529 and transport this fine sediment out from these river valleys hundreds of kilometers 00:50:02.529 --> 00:50:04.010 out into the ocean. 00:50:04.010 --> 00:50:10.950 I want to paint a picture of very seasonally variable sources of iron to this coastal Gulf 00:50:10.950 --> 00:50:14.130 of Alaska region. 00:50:14.130 --> 00:50:19.450 In the winter, there's deep, deep mixing as you get strong storms and limited river discharge. 00:50:19.450 --> 00:50:25.339 That leads to the water column being very well mixed and churned up and leads to high 00:50:25.339 --> 00:50:31.239 concentrations of iron and nitrate in surface waters, which together fuel high spring phytoplankton 00:50:31.239 --> 00:50:34.040 biomass on the shelf. 00:50:34.040 --> 00:50:37.650 Nitrate is actually the limiting nutrient on our shelf transect. 00:50:37.650 --> 00:50:45.059 I didn't actually show you, but Laurel's work suggests that zooplankton and fish she sampled 00:50:45.059 --> 00:50:49.359 tend to be more abundant within the river plume than outside the river plume. 00:50:49.359 --> 00:50:59.069 That's in response to evasion of predators in these turbid river waters. 00:50:59.069 --> 00:51:04.329 I want to emphasize that melting of glaciers is perturbing these nutrient cycles in ways 00:51:04.329 --> 00:51:09.550 that we do not fully understand, although there is a suggestion that the rivers are 00:51:09.550 --> 00:51:12.770 now becoming a summertime source of nitrate. 00:51:12.770 --> 00:51:19.059 In the winter, the ocean is that source of nitrate, but that nitrate gets used up by 00:51:19.059 --> 00:51:24.569 massive phytoplankton blooms in the spring and by the summertime, these glacierdominated 00:51:24.569 --> 00:51:32.130 rivers are becoming a source of nitrate, with a few different possibilities for sources. 00:51:32.130 --> 00:51:36.799 Impacts of the increased river discharge in response to the increased melt include...There's 00:51:36.799 --> 00:51:41.660 a larger area of Copper River plume. 00:51:41.660 --> 00:51:46.059 There's increased offshore transport of this river water, which includes particulate iron 00:51:46.059 --> 00:51:51.089 and other species as well. 00:51:51.089 --> 00:51:53.869 There's most likely increased stratification. 00:51:53.869 --> 00:51:58.569 In other words, that freshwater layer is less dense. 00:51:58.569 --> 00:52:03.890 It resides in its surface, and it reduces vertical mixing. 00:52:03.890 --> 00:52:08.989 The deep water can't mix up to the surface, and that probably translates to reduced nitrate 00:52:08.989 --> 00:52:10.880 flux to the surface. 00:52:10.880 --> 00:52:19.420 Some ecosystem responses in response to such a perturbation of increased Copper River discharge...These 00:52:19.420 --> 00:52:24.650 are fairly speculative, and I have to take ownership for this part. 00:52:24.650 --> 00:52:28.650 This is my speculation. 00:52:28.650 --> 00:52:33.880 These ecosystem responses might include increased productivity beyond the shelf in response 00:52:33.880 --> 00:52:39.750 to that increased offshore transport of iron and reduced productivity over the shelf in 00:52:39.750 --> 00:52:44.010 response to that increased stratification that limits nitrate flux to the surface. 00:52:44.010 --> 00:52:54.079 I just want to mention that impacts on eddies are beyond the scope of this project. 00:52:54.079 --> 00:52:56.490 I'm going to try to show a video quickly. 00:52:56.490 --> 00:52:59.289 Should I make this full screen? 00:52:59.289 --> 00:53:00.289 Ashley: �Yes. 00:53:00.289 --> 00:53:03.369 John: �What I'm going to show you is a video. 00:53:03.369 --> 00:53:07.890 This is a simulation of that discharge from the Copper River to give you a sense of the 00:53:07.890 --> 00:53:08.890 power of this. 00:53:08.890 --> 00:53:10.560 This is actually a really nice tool. 00:53:10.560 --> 00:53:18.829 Again, the people from the Gulf of Maine added the Copper River discharge to this Gulf of 00:53:18.829 --> 00:53:23.849 Alaska model, and with that, we can now understand impacts of Copper River discharge on this 00:53:23.849 --> 00:53:26.470 entire northern Gulf of Alaska region. 00:53:26.470 --> 00:53:33.180 Just to orient you, this is discharge from the Copper River, a tracer, if you will. 00:53:33.180 --> 00:53:36.660 It's just Copper River water, not really salinity. 00:53:36.660 --> 00:53:39.440 I want to point out the date at the top. 00:53:39.440 --> 00:53:40.589 It's May 1st, 2010. 00:53:40.589 --> 00:53:47.059 You'll see the date click along, and you'll see this river water discharge come out through 00:53:47.059 --> 00:53:49.359 this Copper River mouth in just a second. 00:53:49.359 --> 00:53:51.019 Bear with me. 00:53:51.019 --> 00:53:55.519 Now you see the dates moving along. 00:53:55.519 --> 00:54:03.289 You see increased discharge in response to increased melt in the summer and this phenomenon 00:54:03.289 --> 00:54:06.769 of this water being transported along shore. 00:54:06.769 --> 00:54:10.450 Now it's July. 00:54:10.450 --> 00:54:16.759 We're getting close to the period of peak discharge, and you'll begin to see this Copper 00:54:16.759 --> 00:54:19.220 River water going into Prince William Sound. 00:54:19.220 --> 00:54:21.130 There you go. 00:54:21.130 --> 00:54:25.269 Some of it makes its way into Prince William Sound, and it's harder to see it coming out 00:54:25.269 --> 00:54:26.769 again. 00:54:26.769 --> 00:54:33.480 Now the discharge is diminishing as summer winds down. 00:54:33.480 --> 00:54:43.150 It just gives you a feeling for the power of this modeling approach. 00:54:43.150 --> 00:54:46.089 Now we're into the autumn when there's much less discharge. 00:54:46.089 --> 00:54:50.569 I think I can stop it there. 00:54:50.569 --> 00:54:53.930 I'd be happy to take any questions. 00:54:53.930 --> 00:54:54.930 Phew. 00:54:54.930 --> 00:54:55.930 Got through it. 00:54:55.930 --> 00:54:57.769 Ashley: �[laughs] Thanks John. 00:54:57.769 --> 00:55:07.162 If you guys would like to ask a question...We do have one question from Gwenn, and it says, 00:55:07.162 --> 00:55:13.150 "How bioavailable is the particulate iron from the glacier melt waters"? 00:55:13.150 --> 00:55:15.920 John: �That's a good question. 00:55:15.920 --> 00:55:22.950 I perhaps should have gone into that, but I had to gloss over a lot of details. 00:55:22.950 --> 00:55:25.319 It's a very good question. 00:55:25.319 --> 00:55:34.400 Most of that is not bioavailable, but the thing to keep in mind is that it's a massive, 00:55:34.400 --> 00:55:35.400 massive quantity. 00:55:35.400 --> 00:55:43.329 It just takes a small amount of dissolution of that massive quantity of particulate iron 00:55:43.329 --> 00:55:53.210 to translate to a lot of iron in parts of the dissolved phase. 00:55:53.210 --> 00:56:01.029 This is a complicated thing to quantify, and there are various ways of doing it. 00:56:01.029 --> 00:56:09.829 Numbers that people throw out there as ballpark estimates of how much of that is available 00:56:09.829 --> 00:56:15.660 would be something in the range of maybe 2 to 20 percent. 00:56:15.660 --> 00:56:21.279 The literature on this is pretty confusing because there are estimates that range from 00:56:21.279 --> 00:56:26.400 well under 2 to well over 20 percent. 00:56:26.400 --> 00:56:31.569 In a nutshell, if you have a small amount of particulate matter in a large amount of 00:56:31.569 --> 00:56:37.950 water, you tend to dissolve a higher proportion of that particulate matter. 00:56:37.950 --> 00:56:40.720 Anyway, that's a quick answer to that. 00:56:40.720 --> 00:56:43.369 Does that answer your question? 00:56:43.369 --> 00:56:48.089 Ashley: �Gwenn says, "Yes, thank you." 00:56:48.089 --> 00:56:49.660 John: �OK. 00:56:49.660 --> 00:56:56.809 Ashley: �I know that we're running a little bit late, but if there are any last minute 00:56:56.809 --> 00:57:01.140 questions...We do have one from Benjamin, and it says, "At the beginning of your presentation, 00:57:01.140 --> 00:57:07.810 I think that you said that the GoA was not a nitrogenlimited system but, on the conclusion 00:57:07.810 --> 00:57:15.020 slide, that you said there was a transect that was nitrogenlimited. 00:57:15.020 --> 00:57:22.460 Did I see that right, and, if so, why the difference?" 00:57:22.460 --> 00:57:27.109 John: �Perhaps I glossed over that too quickly. 00:57:27.109 --> 00:57:33.869 The broader Gulf of Alaska is ironlimited, but the coastal region tends to be nitratelimited. 00:57:33.869 --> 00:57:40.539 It depends on the time of year and where exactly you're talking about. 00:57:40.539 --> 00:57:48.630 Early in the growing season, it's not limited at all because there's abundant nitrate and 00:57:48.630 --> 00:57:52.569 abundant iron. 00:57:52.569 --> 00:57:55.390 One or the other tends to the limiting nutrient. 00:57:55.390 --> 00:58:04.470 By the time midsummer rolls along, in the coastal region, what I tried to emphasize 00:58:04.470 --> 00:58:10.979 is that nitrate tends to be fully consumed, and so nitrate tends to be limiting in that 00:58:10.979 --> 00:58:12.410 coastal area. 00:58:12.410 --> 00:58:14.869 Iron is more limiting farther offshore. 00:58:14.869 --> 00:58:18.570 That's not always the case. 00:58:18.570 --> 00:58:23.509 There are some coastal areas where they're ironlimited, but, at least from our data, 00:58:23.509 --> 00:58:31.050 it would appear that nitrate is actually the limiting nutrient in the summer, in the nearshore 00:58:31.050 --> 00:58:32.170 region. 00:58:32.170 --> 00:58:36.450 Somewhere out beyond the continental shelf break is where iron limitation kicks in. 00:58:36.450 --> 00:58:39.400 Ashley: �Thank you. 00:58:39.400 --> 00:58:45.569 We have a question from Tom, and it says, "What is the relationship between the Copper 00:58:45.569 --> 00:58:50.549 River outflow nutrients and the downwellingupwelling nutrient input"? 00:58:50.549 --> 00:58:53.000 John: �Good question. 00:58:53.000 --> 00:58:55.460 Again, something I really glossed over. 00:58:55.460 --> 00:59:04.690 I have to preface this by saying that the people who could best answer that question 00:59:04.690 --> 00:59:11.550 would be the modelers, and that's not me. 00:59:11.550 --> 00:59:22.010 The Copper River discharge into the ocean induces a process by which, at least it can 00:59:22.010 --> 00:59:30.490 induce a process by which you get upward mixing of nutrients from below in an estuarine circulation 00:59:30.490 --> 00:59:37.500 where you get outflow at the surface of this freshwater, and that induces entrainment of 00:59:37.500 --> 00:59:43.920 water below that that causes a return flow and an upwelling. 00:59:43.920 --> 00:59:52.089 The presence of the river itself can induce this upward, sort of an upwelling in the vicinity 00:59:52.089 --> 00:59:53.549 of the river plume. 00:59:53.549 --> 00:59:58.180 That's one reason that river plumes can be fairly productive, because you have all this 00:59:58.180 --> 01:00:01.880 mixing going on of deeper water being raised to the surface. 01:00:01.880 --> 01:00:07.710 That's a process that's somewhat independent of this downwellingupwelling phenomenon. 01:00:07.710 --> 01:00:19.180 The upwelling index that I showed, which tended to show primarily downwelling, that's more 01:00:19.180 --> 01:00:25.569 relevant to regions outside of the influence of the river, where the prevailing winds are 01:00:25.569 --> 01:00:29.920 largely what drive that. 01:00:29.920 --> 01:00:39.400 The winds are such that you tend to get downwelling, except in fairly rare occasions, in that part 01:00:39.400 --> 01:00:40.400 of the world. 01:00:40.400 --> 01:00:43.869 I'm not sure if I answered your question, but that's one attempt. 01:00:43.869 --> 01:00:56.619 Ashley: �Tom, if you just want to chat "yes" or "no," that would be great. 01:00:56.619 --> 01:01:00.869 He said, "Yes, it does. 01:01:00.869 --> 01:01:02.570 Thank you." 01:01:02.570 --> 01:01:04.270 John: �OK. 01:01:04.270 --> 01:01:10.579 Ashley: �We have one more question from Patricia, and it says, "Have you looked at 01:01:10.579 --> 01:01:16.130 how productivity varies with PDO or other climate variation? 01:01:16.130 --> 01:01:21.080 Put another way, do the local factors you discussed dominate productivity shifts, or 01:01:21.080 --> 01:01:26.989 do other factors like PDO dominate productivity at certain times or phases?" 01:01:26.989 --> 01:01:30.920 John: �Very good question. 01:01:30.920 --> 01:01:39.650 Let's see, it's hard for me to give a short answer to that question. 01:01:39.650 --> 01:01:45.109 Different people define productivity in different ways. 01:01:45.109 --> 01:01:52.670 Often people use the satellite image of Chlorophyll to say something about productivity. 01:01:52.670 --> 01:01:56.799 Chlorophyll was pretty much the only thing I showed in this presentation but that really 01:01:56.799 --> 01:02:05.859 is a measure of phytoplankton biomass whereas productivity is a rate that isn't really measured 01:02:05.859 --> 01:02:09.690 by that Chlorophyll concentration. 01:02:09.690 --> 01:02:16.329 To get at productivity requires, well, there's a whole bunch of different methods that people 01:02:16.329 --> 01:02:19.390 use. 01:02:19.390 --> 01:02:24.249 The classical way is to incubate samples in a bottle, radiocarbon labeling. 01:02:24.249 --> 01:02:30.089 Paul Clay, here at the University of Washington, is one of the people who has come up with 01:02:30.089 --> 01:02:40.640 a very elegant way, using dissolved gas measurements to get at this rate of carbon uptake or option 01:02:40.640 --> 01:02:41.640 production. 01:02:41.640 --> 01:02:46.219 In a nutshell, you get different answers depending on how you measure it. 01:02:46.219 --> 01:02:53.349 The bottle method I mentioned is an instantaneous snapshot plus there is sometimes bottle effects. 01:02:53.349 --> 01:02:55.650 I'm not trying to waffle. 01:02:55.650 --> 01:03:04.219 I'm trying just to say, there really aren't sufficient observations with enough different 01:03:04.219 --> 01:03:06.670 techniques to answer that question. 01:03:06.670 --> 01:03:18.289 Because you get variation, the different methods disagree by many times, by two to eight times 01:03:18.289 --> 01:03:19.289 when you intercompare them. 01:03:19.289 --> 01:03:24.380 There really needs to be more intercomparison of these various methods of inferring biological 01:03:24.380 --> 01:03:25.380 productivity. 01:03:25.380 --> 01:03:28.049 There hasn�t been a lot of that. 01:03:28.049 --> 01:03:39.660 Until there is a rigorous intercomparison, I don't feel like I can answer that question. 01:03:39.660 --> 01:03:49.200 No doubt broad scale oceanographic processes, such as the PDO, which by the way, stands 01:03:49.200 --> 01:03:53.660 for Pacific Decadal Oscillation, for those who don't know that term. 01:03:53.660 --> 01:04:01.230 They are going to have a big influence on biological processes in the broad Gulf of 01:04:01.230 --> 01:04:03.069 Alaska. 01:04:03.069 --> 01:04:09.789 Our work was focused more on the coastal region off shore of the Copper River, which is heavily 01:04:09.789 --> 01:04:11.779 influenced by the processes in the Gulf of Alaska. 01:04:11.779 --> 01:04:17.460 It is its own beast in a way too, because of the tremendous amount of fresh water discharge 01:04:17.460 --> 01:04:23.559 coming out there which influences nutrients and stratification. 01:04:23.559 --> 01:04:33.430 Ashley: �All right, I'm just scanning for any additional questions. 01:04:33.430 --> 01:04:38.640 Patricia said, "Thank you very much." 01:04:38.640 --> 01:04:48.479 We do have another one from Kay and it says, "How might ocean acidification affect the 01:04:48.479 --> 01:04:53.420 iron concentration in the model, if at all? 01:04:53.420 --> 01:04:54.599 (Fe)." 01:04:54.599 --> 01:05:00.499 John: �Another very good question. 01:05:00.499 --> 01:05:07.690 The first primary thing I have to say is that I don't think we know, and not because of 01:05:07.690 --> 01:05:08.979 insufficient observations. 01:05:08.979 --> 01:05:18.259 Your first instinct is that ocean acidification would lead to greater iron concentrations. 01:05:18.259 --> 01:05:22.269 The solubility of iron is a function of pH. 01:05:22.269 --> 01:05:27.650 Now, ocean acidification is a pretty small perturbation of pH. 01:05:27.650 --> 01:05:33.559 But, when the ocean gets more acidic, there's going to tend to be a little more solubility 01:05:33.559 --> 01:05:34.559 of iron. 01:05:34.559 --> 01:05:40.789 If anything, acidification, in and of itself, is probably going to cause slight increase 01:05:40.789 --> 01:05:44.089 in iron concentration. 01:05:44.089 --> 01:05:50.420 Having said that, it's probably likely that ocean acidification is going to have so many 01:05:50.420 --> 01:06:02.130 other impacts, that that pH effect, by itself, is going - well and this is my own gut feeling 01:06:02.130 --> 01:06:08.400 - it's going to be dominated by other things that are also going to effect the iron concentration. 01:06:08.400 --> 01:06:14.420 Just pH alone is going to affect the iron solubility and iron concentration. 01:06:14.420 --> 01:06:19.299 Ashley: �Thank you John. 01:06:19.299 --> 01:06:26.619 I'm not seeing any more questions. 01:06:26.619 --> 01:06:30.269 Kay says, "Thank you very much, John." 01:06:30.269 --> 01:06:38.450 All right, I'd like to thank John for an excellent presentation and that was very informative. 01:06:38.450 --> 01:06:38.959 Transcription by CastingWords p.