1 00:00:01,050 --> 00:00:03,800 GoToMeeting Auto Voice >> This conference will now be recorded. 2 00:00:03,800 --> 00:00:09,950 Heather Tabisola >> All right, well, good morning everyone. 3 00:00:09,950 --> 00:00:16,859 Keely, you have the official distinction of officially maxing out the first ever EcoFOCI 4 00:00:16,859 --> 00:00:25,349 seminar series with 151 people on the line, so not to make you nervous or anything today. 5 00:00:25,349 --> 00:00:29,329 So we'll definitely be recording this because we've run out of space, and both Adi and I 6 00:00:29,329 --> 00:00:33,300 are getting a lot of pop-ups for folks to join. 7 00:00:33,300 --> 00:00:34,300 Everyone's been really good about this. 8 00:00:34,300 --> 00:00:38,940 Just a reminder, please do not use your video cam, and make sure your mic is muted during 9 00:00:38,940 --> 00:00:40,329 this time. 10 00:00:40,329 --> 00:00:44,600 So good morning, everybody, and welcome to the 2020 Spring EcoFOCI seminar series. 11 00:00:44,600 --> 00:00:46,850 My name is Heather Tabisola. 12 00:00:46,850 --> 00:00:49,519 I'm the co-lead of the seminar with Jens Nielsen. 13 00:00:49,519 --> 00:00:54,829 And this seminar is part of NOAA's EcoFOCI biannual series, focused on the ecosystems 14 00:00:54,829 --> 00:00:59,179 of the North Pacific Ocean, Bering Sea, and US Arctic to improve the understanding of 15 00:00:59,179 --> 00:01:03,999 ecosystem dynamics and application of that understanding to the management of living 16 00:01:03,999 --> 00:01:06,450 marine resources. 17 00:01:06,450 --> 00:01:12,930 The first EcoFOCI seminar was held in October of 1986, so we've been doing this for awhile, 18 00:01:12,930 --> 00:01:16,570 and if you'd like more information on that, you can visit the EcoFOCI webpage. 19 00:01:16,570 --> 00:01:24,150 As of right now, we have Keely today, and then we have one more 20 00:01:24,150 --> 00:01:26,580 seminar following in the series. 21 00:01:26,580 --> 00:01:29,200 And we will continue to run these virtually. 22 00:01:29,200 --> 00:01:33,710 Our speaker lineup can be found via the One NOAA Science seminar series and also the NOAA 23 00:01:33,710 --> 00:01:35,670 PMEL calendar of events. 24 00:01:35,670 --> 00:01:39,820 So again, just a reminder, just double-check those microphones are muted, that you're muted 25 00:01:39,820 --> 00:01:43,820 on the phone, that your video is off. 26 00:01:43,820 --> 00:01:49,380 And then, during the chat, please feel free to type your questions in at any time. 27 00:01:49,380 --> 00:01:53,550 Both Jens and I will be monitoring the chat and we'll work with Keely at the end of the 28 00:01:53,550 --> 00:01:55,290 talk to answer those questions. 29 00:01:55,290 --> 00:02:02,119 So today, one of our newest members of the EcoFOCI AFSC team is joining us, and that's 30 00:02:02,119 --> 00:02:03,790 Kelia Axler. 31 00:02:03,790 --> 00:02:07,980 She'll be talking about her previous work on fine-scale distributions, predator-prey 32 00:02:07,980 --> 00:02:13,340 dynamics and survival of fish larvae in a dynamic coastal river-dominated ecosystem. 33 00:02:13,340 --> 00:02:15,670 Keely joined us in December. 34 00:02:15,670 --> 00:02:20,150 She obtained her BS from the University of Minnesota, and just recently her Master's 35 00:02:20,150 --> 00:02:22,090 from Oregon State University. 36 00:02:22,090 --> 00:02:26,060 She's worked, not only in the Gulf of Mexico, but California, current ecosystem, and now 37 00:02:26,060 --> 00:02:27,810 most recently the Chukchi Sea. 38 00:02:27,810 --> 00:02:33,380 She is part of the EcoFOCI ichthyoplankton team , working to link ichthyoplankton dynamics 39 00:02:33,380 --> 00:02:38,500 to physical and fisheries oceanography, to verify larval fishes from all of our Alaska 40 00:02:38,500 --> 00:02:41,940 ellomies and conduct field research with us, as well. 41 00:02:41,940 --> 00:02:43,650 So Keely, just welcome to the team. 42 00:02:43,650 --> 00:02:48,100 I know this is your first introduction to the group and we are so excited that you're 43 00:02:48,100 --> 00:02:51,410 going to be joining us today for a seminar, and we really look forward to hearing from 44 00:02:51,410 --> 00:02:52,410 you. 45 00:02:52,410 --> 00:02:54,450 And with that, I'm going to turn it over to you. 46 00:02:54,450 --> 00:02:56,370 Kelia Axler >> Great. 47 00:02:56,370 --> 00:02:57,370 Thank you, Heather. 48 00:02:57,370 --> 00:02:58,370 Can you hear me? 49 00:02:58,370 --> 00:03:01,459 Heather Tabisola >> Yes, you're good to go. 50 00:03:01,459 --> 00:03:03,100 Kelia Axler >> OK. 51 00:03:03,100 --> 00:03:04,100 Great. 52 00:03:04,100 --> 00:03:05,100 Alright. 53 00:03:05,100 --> 00:03:07,180 Well, thanks everyone for calling in today. 54 00:03:07,180 --> 00:03:12,490 So as Heather just said, I'm a newish fish biologist, at the EcoFOCI program at the Alaska 55 00:03:12,490 --> 00:03:13,819 Fisheries Science Center. 56 00:03:13,819 --> 00:03:17,451 And today, I'll be talking a little bit about some of the research I completed, my master's 57 00:03:17,451 --> 00:03:20,330 work at Oregon State University prior to coming here. 58 00:03:20,330 --> 00:03:24,400 And then I'll move on to a couple of the new projects I'm starting for Alaska Fisheries Science 59 00:03:24,400 --> 00:03:28,250 Center. 60 00:03:28,250 --> 00:03:32,620 The overarching theme of all of my past and present research has been to study how different 61 00:03:32,620 --> 00:03:37,650 physical processes and oceanographic conditions affect the early life stages of marine fishes. 62 00:03:37,650 --> 00:03:42,069 This is an important area to study because the survival of the planktonic stages is widely 63 00:03:42,069 --> 00:03:45,770 considered to be a bottleneck in recruitment success in the period when fishes are highly 64 00:03:45,770 --> 00:03:48,160 sensitive to changes in their environment. 65 00:03:48,160 --> 00:03:52,640 For example, during the Pelagic Larval phase, most marine fish experienced extremely high 66 00:03:52,640 --> 00:03:57,900 rates of mortality, with far reaching consequences for adult population dynamics. 67 00:03:57,900 --> 00:04:02,590 So failure to find food and avoid predation and attain favorable transport can lead to 68 00:04:02,590 --> 00:04:06,370 high mortality, which can translate to low year class strength. 69 00:04:06,370 --> 00:04:10,450 So there's a tight link between survival of the larval stages, and the surrounding oceanographic 70 00:04:10,450 --> 00:04:14,580 conditions that structure their spatial distributions and trophic interactions. 71 00:04:14,580 --> 00:04:21,309 So in the high latitudes of Alaska's large marine ecosystems, we're already seeing record 72 00:04:21,309 --> 00:04:24,439 sea surface temperatures, and unprecedented sea ice loss. 73 00:04:24,439 --> 00:04:28,569 These ecosystems are experiencing climate impacts at much faster rates than other places. 74 00:04:28,569 --> 00:04:32,919 And is therefore really critical to study the larval stages of fishes to be able to 75 00:04:32,919 --> 00:04:37,000 forecast how fisheries production will respond to rapidly changing ecosystem conditions. 76 00:04:37,000 --> 00:04:40,969 However, the impacts of climate change are not showing up elsewhere in the world nearly 77 00:04:40,969 --> 00:04:42,220 as rapidly as the Arctic. 78 00:04:42,220 --> 00:04:47,099 So for example, climate change projections for the mid-latitudes, like the Gulf of Mexico, 79 00:04:47,099 --> 00:04:50,240 are a little more variable and a little less certain as of now. 80 00:04:50,240 --> 00:04:54,309 But what impact that is already affecting Gulf of Mexico ecosystems, livelihoods, and 81 00:04:54,309 --> 00:04:58,930 fisheries is the increasing frequency of heavy rainfall storms, which is leading to record 82 00:04:58,930 --> 00:05:04,360 river flooding in the Midwest, and as a result, increased freshwater discharge into the Gulf. 83 00:05:04,360 --> 00:05:07,440 So, this is a really big deal. 84 00:05:07,440 --> 00:05:11,330 Because as annual precipitation in the Midwest increases, all that rain and snow melt makes 85 00:05:11,330 --> 00:05:14,729 its way down to the productive Gulf of Mexico ecosystem. 86 00:05:14,729 --> 00:05:18,740 The Mississippi River watershed as massive as shown here, and it entirely drains into 87 00:05:18,740 --> 00:05:22,659 the Northern Gulf the results of which have been devastating for Gulf Coast communities 88 00:05:22,659 --> 00:05:24,919 and ecosystems. 89 00:05:24,919 --> 00:05:30,800 So, for example, the Bonnet Carré spillway is one of the river diversion structures in 90 00:05:30,800 --> 00:05:34,710 the Mississippi River that is used to divert very high flows into the Northern Gulf in 91 00:05:34,710 --> 00:05:37,229 an attempt to protect life and property in New Orleans. 92 00:05:37,229 --> 00:05:42,370 It has only been open a little over a dozen times in its nearly 90 year history, but five 93 00:05:42,370 --> 00:05:44,379 of those times have been in the past decade. 94 00:05:44,379 --> 00:05:48,370 And this year, 2020, as they just re-opened it last week, will be its third consecutive 95 00:05:48,370 --> 00:05:51,580 year being open, which is unprecedented. 96 00:05:51,580 --> 00:05:55,840 In 2019, the diversions flushed trillions of gallons of nutrient-loaded freshwater into 97 00:05:55,840 --> 00:05:59,860 the saltwater Gulf of Mexico, reducing the Gulf salinity to dangerously low levels for 98 00:05:59,860 --> 00:06:05,279 sea creatures, and decimating nearshore populations of fish, shrimp, oysters, and crab. 99 00:06:05,279 --> 00:06:09,070 Federal fisheries disasters were declared in Mississippi, Alabama, and Louisiana in 100 00:06:09,070 --> 00:06:13,719 the summer last year, as a result of all this freshwater influx, and NOAA models forecasts 101 00:06:13,719 --> 00:06:17,099 another year of widespread river flooding in 2020. 102 00:06:17,099 --> 00:06:22,479 So, with the realization that these heavy rainfall events are increasing as a result 103 00:06:22,479 --> 00:06:26,740 of climate change, there is renewed interest in how high freshwater discharge events affect 104 00:06:26,740 --> 00:06:30,839 the early life stages of marine fishes, and how that translates to fisheries production 105 00:06:30,839 --> 00:06:32,360 in the nearshore. 106 00:06:32,360 --> 00:06:36,259 This satellite backscatter map shows the major sources of freshwater input into the Northern 107 00:06:36,259 --> 00:06:41,289 Gulf, most notably the Mississippi River to the west and Mobile Bay in the north. 108 00:06:41,289 --> 00:06:45,060 Both of these produce large nutrient-rich river plumes as shown here, that extend far 109 00:06:45,060 --> 00:06:48,719 offshore into the Gulf. 110 00:06:48,719 --> 00:06:53,589 So how does increased freshwater discharge affect the larval stages of marine fishes? 111 00:06:53,589 --> 00:06:59,009 As river discharges into the coastal ocean, they emit a low salinity plume that emanates 112 00:06:59,009 --> 00:07:00,009 offshore. 113 00:07:00,009 --> 00:07:04,149 As plume waters discharge offshore, convergence with the surrounding coastal waters, as shown 114 00:07:04,149 --> 00:07:08,470 here, forms distinct frontal boundaries, both horizontally and vertically. 115 00:07:08,470 --> 00:07:12,020 These frontal regions are marked by sharp physical gradients and have been shown to 116 00:07:12,020 --> 00:07:15,469 greatly influence larval fish and zooplankton spatial distributions. 117 00:07:15,469 --> 00:07:20,369 Therefore, not only do they impact the physical coastal environment, but they also affect 118 00:07:20,369 --> 00:07:25,089 the biological coastal environment. 119 00:07:25,089 --> 00:07:28,830 So previous studies have shown that larval fishes and zooplankton concentrate in plume 120 00:07:28,830 --> 00:07:33,740 frontal zones in higher abundances than surrounding coastal waters through a combination of convergent 121 00:07:33,740 --> 00:07:38,050 physical processes and increased biological productivity. 122 00:07:38,050 --> 00:07:41,389 Aggregated prey resources and plume monitors can have several important implications for 123 00:07:41,389 --> 00:07:45,750 larval fish population dynamics as feeding success is, a major determinant of larval 124 00:07:45,750 --> 00:07:49,990 fish survival and aggregated prey resources should lead to increase foraging in plume 125 00:07:49,990 --> 00:07:50,990 waters. 126 00:07:50,990 --> 00:07:55,000 However, while plumes may concentrate prey resources and enhance feeding, the degree 127 00:07:55,000 --> 00:07:59,240 to which this translates to heightened survival remains under question as the shallow frontal 128 00:07:59,240 --> 00:08:02,930 features that aggregate larval fishes and their prey, also concentrate known larval 129 00:08:02,930 --> 00:08:07,539 fish predators, such as gelatinous zooplankton whose buoyant bodies have a tendency to aggregate 130 00:08:07,539 --> 00:08:11,960 along plume frontal zones. 131 00:08:11,960 --> 00:08:17,289 So the objectives of this study were to analyze the influence of high-discharge river plumes 132 00:08:17,289 --> 00:08:22,999 on larval fish distributions and predator-prey dynamics over fine spatial and temporal scales 133 00:08:22,999 --> 00:08:26,689 and also to examine the impacts of plume encounter on larval fish growth and condition. 134 00:08:26,689 --> 00:08:35,169 I also want to note that this study was done as part of my Master's research at Oregon 135 00:08:35,169 --> 00:08:40,599 State, and was part of a larger multi-institution consortium project that included many different 136 00:08:40,599 --> 00:08:44,680 collaborators at Oregon State University, the University of Southern Mississippi, the 137 00:08:44,680 --> 00:08:49,800 University of South Alabama, and others without whom this research would not have been possible. 138 00:08:49,800 --> 00:08:54,890 Also, funding for this work was provided by the Gulf of Mexico Research Initiative. 139 00:08:54,890 --> 00:09:03,339 So our study region was Mobile Bay, a large brackish water estuary sourced from Alabama 140 00:09:03,339 --> 00:09:08,500 and Tombigbee River systems that contributes large nutrient-rich plumes tens of kilometers 141 00:09:08,500 --> 00:09:11,210 onto the shallow Alabama Continental shelf. 142 00:09:11,210 --> 00:09:15,210 It's a model two layer system where you have a fresher turbid surface layer, overlying 143 00:09:15,210 --> 00:09:21,150 a saltier, marine Layer, with distinct differences in physical parameters between layers. 144 00:09:21,150 --> 00:09:24,839 It's a dominant year-round influence in the region, and an important spawning and nursery 145 00:09:24,839 --> 00:09:29,180 habitat for many fishes making it a really useful system to study how high-discharge 146 00:09:29,180 --> 00:09:33,180 river plumes influence the spatial distributions and trophic interactions at the base of the 147 00:09:33,180 --> 00:09:35,580 marine food web. 148 00:09:35,580 --> 00:09:41,139 However, river plumes are highly dynamic and ephemeral features, which make them very difficult 149 00:09:41,139 --> 00:09:42,990 to study. 150 00:09:42,990 --> 00:09:47,120 Variations of river discharge, wind mixing, and tides and currents can alter the pattern 151 00:09:47,120 --> 00:09:51,440 of horizontal and vertical freshwater dispersal over very short timescales. 152 00:09:51,440 --> 00:09:55,120 This figure shows the rapid changes in surface salinity around the mouth of the Columbia 153 00:09:55,120 --> 00:09:58,279 River plume in Oregon through one title cycle. 154 00:09:58,279 --> 00:10:02,130 So you can see how it can be really difficult to study how these highly dynamic features 155 00:10:02,130 --> 00:10:09,930 effect larval fishes at sufficiently fine scales to resolve the underlying mechanisms. 156 00:10:09,930 --> 00:10:14,379 So to overcome this challenge, we used a variety of oceanographic equipment as part of a large-scale 157 00:10:14,379 --> 00:10:18,879 collaborative field effort from April 8th through 11th in 2016. 158 00:10:18,879 --> 00:10:23,410 So to track the plumes location and movement, we used both satellite imagery and plume tracking 159 00:10:23,410 --> 00:10:24,660 drifters. 160 00:10:24,660 --> 00:10:28,680 And to characterize the different plume physical properties, we towed a Chameleon microstructure 161 00:10:28,680 --> 00:10:34,430 profiler, did multiple CTD casts, and used shipboard ADCP to gather data such as turbulence, 162 00:10:34,430 --> 00:10:37,569 currents, salinity, temperature, depth, etc. 163 00:10:37,569 --> 00:10:42,339 And finally, to sample larval fish and zooplankton distributions, we towed an in situ plankton 164 00:10:42,339 --> 00:10:48,560 imager and did multiple net tows with a multinet system. 165 00:10:48,560 --> 00:10:55,089 So, to examine the spatial patterns of larval fish and zooplankton around the Mobile Bay 166 00:10:55,089 --> 00:10:58,050 plume, we used the plankton imaging system called ISIIS. 167 00:10:58,050 --> 00:11:01,940 While it's an unfortunate name, it's a really neat technology. 168 00:11:01,940 --> 00:11:06,069 This high resolution, towed plankton imager collects real-time shadow graph images of 169 00:11:06,069 --> 00:11:10,930 larval fish and zooplankton while simultaneously sampling the in situ physical data such as 170 00:11:10,930 --> 00:11:15,720 location, depth, salinity, temperature, dissolved oxygen in fluorescence in the water column. 171 00:11:15,720 --> 00:11:20,600 Further, because it samples in a tight, undulating fashion from surface to bottom, it allows 172 00:11:20,600 --> 00:11:25,770 fine-scale horizontal and vertical spatial analyses across oceanographic features. 173 00:11:25,770 --> 00:11:29,100 Additionally, it samples very large volumes of water. 174 00:11:29,100 --> 00:11:34,339 For example, we towed for six consecutive hours per transect, enabling characterization 175 00:11:34,339 --> 00:11:39,560 of distributions and habitat use of taxa at much finer scales than traditional net samplers. 176 00:11:39,560 --> 00:11:43,550 It's also a really useful tool for quantifying gelatinous zooplankton that often break apart 177 00:11:43,550 --> 00:11:44,550 in net tows. 178 00:11:44,550 --> 00:11:49,120 However, it collects around two terabytes of data per sampling transect which after 179 00:11:49,120 --> 00:11:52,589 multiple transects results in a pretty big data problem. 180 00:11:52,589 --> 00:11:58,480 To accommodate this, we use an automated computer algorithm to classify the different taxa. 181 00:11:58,480 --> 00:12:04,589 So image classification was done using an automated pipeline as shown here, which is 182 00:12:04,589 --> 00:12:08,870 created in collaboration with OSU Center for Genome Research and Biocomputing. 183 00:12:08,870 --> 00:12:13,269 I'm not gonna go into great detail about it here, but to quickly explain this flowchart, 184 00:12:13,269 --> 00:12:17,399 you start with a raw image, like on the upper left, which is then segmented to individual 185 00:12:17,399 --> 00:12:18,399 organisms. 186 00:12:18,399 --> 00:12:22,709 A training library is created to train the computer to classify images by shape using 187 00:12:22,709 --> 00:12:26,120 a sparse convolutional neural network, which automates classification. 188 00:12:26,120 --> 00:12:31,110 There are also multiple error-checking steps along the pipeline, including a confusion 189 00:12:31,110 --> 00:12:33,420 matrix, which is used to quantify the error. 190 00:12:33,420 --> 00:12:40,529 The end result is that images are batched by organism group, type, and classification. 191 00:12:40,529 --> 00:12:46,269 So, in total after three, roughly six hour-long transects towing ISIIS throughout the outflow 192 00:12:46,269 --> 00:12:51,519 of the Mobile Bay plume, we ended up with around six terabytes of data and 693 million 193 00:12:51,519 --> 00:12:57,040 individual organisms identified by the automated classification pipeline, which comprise 89 194 00:12:57,040 --> 00:12:58,670 different groups of plankton. 195 00:12:58,670 --> 00:13:03,019 However, for ease of analysis and for the purposes of this study, only key taxa that 196 00:13:03,019 --> 00:13:07,639 were deemed to be ecologically important prey or predators of larval fishers were used in this study. 197 00:13:07,639 --> 00:13:12,579 And further, plankton were combined into higher taxonomic predator and prey categories. 198 00:13:12,579 --> 00:13:16,250 So the three different gelatinous predator categories that we focused on in this study 199 00:13:16,250 --> 00:13:19,580 were ctenophores, hydromedusae, and siphonophores. 200 00:13:19,580 --> 00:13:23,290 I also want to note that only species that are known to be larval fish predators within 201 00:13:23,290 --> 00:13:27,370 these predator groups, were included in our analyses. 202 00:13:27,370 --> 00:13:31,730 Calanoid copepods were chosen to represent the prey category because there are a rather 203 00:13:31,730 --> 00:13:34,629 ubiquitous prey for many marine fish larvae in this region. 204 00:13:34,629 --> 00:13:39,889 And this category actually comprised of acartia, centropages, paracalanidae, and other unidentified 205 00:13:39,889 --> 00:13:41,889 calanoid copepod species. 206 00:13:41,889 --> 00:13:47,110 But to confirm their use as a prey category, we conducted a small diet analysis on larval 207 00:13:47,110 --> 00:13:51,769 Striped anchovy and larval Sand seatrout which were the two most abundant larval fish species 208 00:13:51,769 --> 00:13:56,079 sampled during the study and confirmed that calanoid copepods were major prey items for 209 00:13:56,079 --> 00:13:57,149 both species. 210 00:13:57,149 --> 00:14:02,009 So, all of our fishes used in the analyses were manually verified by a human expert in 211 00:14:02,009 --> 00:14:07,009 order to assess the most common taxa which were engraulids, which are anchovies, cyanids, 212 00:14:07,009 --> 00:14:09,350 which are drums and gobies. 213 00:14:09,350 --> 00:14:14,830 And we found them in roughly similar proportions in the ISIIS imagery than the multiset system 214 00:14:14,830 --> 00:14:16,970 for this region. 215 00:14:16,970 --> 00:14:21,480 So, the in situ images shown on this slide were taken during the plume study, and show 216 00:14:21,480 --> 00:14:25,939 examples of different fish larvae, calanoid copepods, ctenophores, hydromedusae, and siphonophores, 217 00:14:25,939 --> 00:14:30,410 that we captured during the study period. 218 00:14:30,410 --> 00:14:36,689 So, now that I've gone over the methods, first I'm going to walk you through the different 219 00:14:36,689 --> 00:14:41,620 environmental settings that we sampled on April 8th through 11th, 2016. 220 00:14:41,620 --> 00:14:46,589 We told the ISIIS plankton imager, which is shown as the purple transect line on the map, 221 00:14:46,589 --> 00:14:49,740 and the Chameleon microstructure profiler, which is shown as the black transect lines 222 00:14:49,740 --> 00:14:54,840 on the map, across the Mobile Bay plume from west to east during a high river discharge 223 00:14:54,840 --> 00:14:55,840 event. 224 00:14:55,840 --> 00:15:00,550 For reference the Mobile Bay plume has a daily average discharge of 2200 cubic meters per 225 00:15:00,550 --> 00:15:01,550 second. 226 00:15:01,550 --> 00:15:06,749 In comparison, it was around 6000 cubic meters per second when we sampled in April 2016. 227 00:15:06,749 --> 00:15:12,389 Additionally, the three sample transect time periods, shown shaded in gray on the figure, 228 00:15:12,389 --> 00:15:16,170 differed from each other by degree of wind forcing, which strongly modified the plumes 229 00:15:16,170 --> 00:15:17,720 location and structure. 230 00:15:17,720 --> 00:15:21,610 For example, on April 9th, the first day of sampling, you can see that wind was light 231 00:15:21,610 --> 00:15:26,660 and variable, but it increased slightly before our second transect on April 9th through 10th, 232 00:15:26,660 --> 00:15:29,040 blowing around 5 to 10 knots from the south-southwest. 233 00:15:29,040 --> 00:15:34,600 And on April 10th through 11th, our third transect, the wind had switched to the southeast, 234 00:15:34,600 --> 00:15:39,399 and increased to 20 knots. 235 00:15:39,399 --> 00:15:43,579 So, the effects of wind stress are highly visible when you look at the degree of water 236 00:15:43,579 --> 00:15:45,019 column mixing in each transect. 237 00:15:45,019 --> 00:15:49,790 For example, the following panels show the three cross plume transects, with vertical 238 00:15:49,790 --> 00:15:53,899 profiles of salinity, to illustrate the contrasting plume and shelf layers and degree of wind 239 00:15:53,899 --> 00:15:55,000 mixing over time. 240 00:15:55,000 --> 00:16:00,279 So on the x-axis is distance along the transect, and the y-axis is depth to 20 meters. 241 00:16:00,279 --> 00:16:02,880 A reminder that this is a really shallow system. 242 00:16:02,880 --> 00:16:07,259 So warmer colors on the plots are higher values, while cooler colors are lower values. 243 00:16:07,259 --> 00:16:11,990 In the three panels, you can see that the Mobile Bay plume creates a two-layer system 244 00:16:11,990 --> 00:16:16,579 on the Alabama continental shelf where loweer salinity plume water is buoyant and at the 245 00:16:16,579 --> 00:16:19,850 surface overlaying the higher salinity continental shelf water. 246 00:16:19,850 --> 00:16:23,639 However, there are major differences between each of the three sample transects due to 247 00:16:23,639 --> 00:16:26,999 wind forcing modifying the location and mixing of the plume. 248 00:16:26,999 --> 00:16:32,670 So on April 9th, in panel A, you can see that we sampled a highly stratified water column 249 00:16:32,670 --> 00:16:35,520 with a really thin surface plume, shown in blue. 250 00:16:35,520 --> 00:16:38,959 This first transact with sampled during stable, low wind conditions. 251 00:16:38,959 --> 00:16:41,579 And you can see that there is little to no water column mixing. 252 00:16:41,579 --> 00:16:46,959 However, the following night of April 9th through 10th, shown in panel B, southwestward 253 00:16:46,959 --> 00:16:50,939 winds increased, causing some mixing of the water column, and slightly eroding stratification, 254 00:16:50,939 --> 00:16:53,689 while deepening the halo climb. 255 00:16:53,689 --> 00:16:58,050 The following night, on April 10th through 11th, shown in panel C, strong winds blew 256 00:16:58,050 --> 00:17:02,759 from the southeast switching, the system to downwelling and mixing the entire water column. 257 00:17:02,759 --> 00:17:06,920 I also want to highlight the other distinct differences between the plume and shelf water 258 00:17:06,920 --> 00:17:09,150 masses during the study period. 259 00:17:09,150 --> 00:17:14,810 For instance, fluorescence, which is shown in the second row of panels here, 260 00:17:14,810 --> 00:17:21,050 was distinctively higher in plume waters reflecting the high productivity of the nutrientirich 261 00:17:21,050 --> 00:17:23,650 river water flowing into the Gulf of Mexico. 262 00:17:23,650 --> 00:17:28,210 Additionally, turbulence, which is shown in the third row panels here, was on average, 263 00:17:28,210 --> 00:17:32,060 at least, an order of magnitude higher in the plume than shelf water masses throughout 264 00:17:32,060 --> 00:17:34,530 the duration of the study. 265 00:17:34,530 --> 00:17:38,210 Turbulence also increased threefold between transect one and transect three due to the 266 00:17:38,210 --> 00:17:41,440 strong wind-induced mixing of the plume and water column. 267 00:17:41,440 --> 00:17:45,530 So there are two things I want you to take away from this slide--in all three transects, 268 00:17:45,530 --> 00:17:49,100 plume waters were characterized by having lower salinity, and much higher turbulence 269 00:17:49,100 --> 00:17:51,990 in fluorescence than the underlying shelf waters. 270 00:17:51,990 --> 00:17:57,360 There is also this trend of increasing turbulence over time as when mixing increases. 271 00:17:57,360 --> 00:18:03,790 So next, I want to highlight a couple of findings from the drifter data. 272 00:18:03,790 --> 00:18:09,670 The following map shows the red tracklines of six surface configured drifters that were 273 00:18:09,670 --> 00:18:15,330 all released from the mouth of Mobile Bay on April 9th at around 1500 in order to track 274 00:18:15,330 --> 00:18:18,040 the plumes movements over the following couple of days. 275 00:18:18,040 --> 00:18:21,820 There are a couple of interesting patterns here I want to point out. 276 00:18:21,820 --> 00:18:26,650 For one, in low wind conditions on April 9th, the four drifters released from the eastern 277 00:18:26,650 --> 00:18:32,210 and central side of the bay showed the plume discharging offshore where it was advected 278 00:18:32,210 --> 00:18:34,120 eastward by shelf currents. 279 00:18:34,120 --> 00:18:38,320 In contrast, drifters released from the west side of the bay, as you can see on the map, 280 00:18:38,320 --> 00:18:42,510 are retained for nearly seven hours, in the localized region, shown as the yellow shaded 281 00:18:42,510 --> 00:18:43,530 oval on the map. 282 00:18:43,530 --> 00:18:48,890 This is likely due to the strong physical convergence created by the outflowing plume, 283 00:18:48,890 --> 00:18:51,990 converging with the longshore currents and ambient shelf waters. 284 00:18:51,990 --> 00:18:56,350 Therefore, there appears to be mechanisms for physical retention of water masses, and 285 00:18:56,350 --> 00:19:00,510 entrained plankton on the west side of Mobile Bay on April 9th. 286 00:19:00,510 --> 00:19:04,330 This is important to note for later when we look at organism distributions. 287 00:19:04,330 --> 00:19:08,600 However, I also want to note that on the afternoon of April 10th, the winds shifted direction 288 00:19:08,600 --> 00:19:12,150 and began blowing strongly from the southeast at 20 knots. 289 00:19:12,150 --> 00:19:16,770 This advected the surface waters inshore against the Alabama coastline, as evidenced by the 290 00:19:16,770 --> 00:19:21,120 complete reversal and direction of the eastern drifters, which are shown as the dashed red 291 00:19:21,120 --> 00:19:23,060 lines on the map. 292 00:19:23,060 --> 00:19:27,600 These data highlight multiple dispersal pathways for larval fish and zooplankton in this region 293 00:19:27,600 --> 00:19:31,930 via offshore advection with the discharging plume, but also inshore advection due to the 294 00:19:31,930 --> 00:19:39,760 strong winds, reversing surface waters and pushing them inshore. 295 00:19:39,760 --> 00:19:43,940 So to see how larval fish has responded to all this physical forcing, we plotted fine 296 00:19:43,940 --> 00:19:49,050 scale concentrations of one meter vertically band larval fishes across the three plume 297 00:19:49,050 --> 00:19:50,050 transects. 298 00:19:50,050 --> 00:19:54,240 So here I am showing the same salinity depth profiles from earlier, but overlaid with in 299 00:19:54,240 --> 00:19:58,710 situ concentrations of fish larvae, within the one meter vertical bands, which are shown 300 00:19:58,710 --> 00:20:02,490 as the black circles, and are scaled by concentration. 301 00:20:02,490 --> 00:20:06,350 In the low wind, highly stratified conditions on April 9h, we found a dense aggregation 302 00:20:06,350 --> 00:20:10,580 of fish larvae accumulating near the outflow of the Mobile Bay plume at the western end 303 00:20:10,580 --> 00:20:11,680 of the transect. 304 00:20:11,680 --> 00:20:15,850 This is roughly the same spatial temporal location as the convergent region revealed 305 00:20:15,850 --> 00:20:19,200 by the plume tracking drifters I showed on the previous slide. 306 00:20:19,200 --> 00:20:23,680 However, as winds increase and there was slight mixing of the water column on April 9th through 307 00:20:23,680 --> 00:20:27,510 10th, the aggregation began to dissipate and fish larvae became more dispersed throughout 308 00:20:27,510 --> 00:20:28,510 the transect. 309 00:20:28,510 --> 00:20:33,370 And as strong southeast winds mixed the entire water column the following night, fish larvae 310 00:20:33,370 --> 00:20:37,180 were observed to become even more dispersed and much less abundant overall, likely due 311 00:20:37,180 --> 00:20:43,590 to plume-driven horizontal advection, as well as vertical mixing for wind forcing. 312 00:20:43,590 --> 00:20:50,280 So we also looked at the fine-scale calanoid copepod distributions, which served as the 313 00:20:50,280 --> 00:20:53,490 larval fish prey group across the three transects. 314 00:20:53,490 --> 00:20:58,270 In highly stratified plume conditions, copepods are rather ubiquitously distributed throughout 315 00:20:58,270 --> 00:21:00,740 the transect and very abundant. 316 00:21:00,740 --> 00:21:05,370 As wind stress and mixing increased, copepods became far less abundant. 317 00:21:05,370 --> 00:21:09,830 Siphonophores which represented one of the predator categories for fish larvae, show 318 00:21:09,830 --> 00:21:14,190 a similar distribution of fish larvae, as they were also densely aggregated on the western 319 00:21:14,190 --> 00:21:20,910 transect and appear to become similarly disburse and less abundant over time with mixing and 320 00:21:20,910 --> 00:21:21,910 advection. 321 00:21:21,910 --> 00:21:25,970 Both hydromedusae and ctenophores showed similar distributional patterns as the ones described 322 00:21:25,970 --> 00:21:30,980 here and are therefore not shown. 323 00:21:30,980 --> 00:21:35,280 So Spearman correlation heat maps were used to summarize the more general spatial patterns 324 00:21:35,280 --> 00:21:39,550 among different taxa as well as among the different environmental variables over time. 325 00:21:39,550 --> 00:21:43,970 So, the darker the color of each box, the stronger the correlation is between the two 326 00:21:43,970 --> 00:21:50,260 groups, and blue boxes represent significant positive correlations, while red boxes represent 327 00:21:50,260 --> 00:21:53,630 significant negative correlations and white boxes represent no correlation between the 328 00:21:53,630 --> 00:21:54,630 two groups. 329 00:21:54,630 --> 00:21:58,590 So, I don't have time to go over these in great detail but to examine predator-prey 330 00:21:58,590 --> 00:22:02,450 relationships across environmental conditions, I want to point out the columns highlighted 331 00:22:02,450 --> 00:22:08,020 in orange in each transect that show that in the first transect on April 9th, on the 332 00:22:08,020 --> 00:22:13,580 left side of the slide, fish larvae were positively spatially correlated with both their prey 333 00:22:13,580 --> 00:22:18,780 and predators, likely due to plume conditions that facilitate biological aggregation such 334 00:22:18,780 --> 00:22:22,520 as the inherently high productivity of plume water, but also the strong physical 335 00:22:22,520 --> 00:22:27,010 convergence near the mouth of Mobile Bay that appeared to accumulate and retain plankton. 336 00:22:27,010 --> 00:22:32,510 As mixing of water masses and turbulence increase in the water column in the second transect, 337 00:22:32,510 --> 00:22:36,610 fish became slightly less spatially correlated with their gelatinous predators. 338 00:22:36,610 --> 00:22:40,850 And as wind strength and further in the third transect, the water column was subjected to 339 00:22:40,850 --> 00:22:45,250 mixing and highly turbulent conditions, and fish larvae were not significantly spatially 340 00:22:45,250 --> 00:22:48,150 correlated with either their zooplankton prey or predators. 341 00:22:48,150 --> 00:22:52,840 So we observed the distinctive trend that, as physical forcing of the system increased, 342 00:22:52,840 --> 00:22:55,690 the spatial relationships between organisms fell apart. 343 00:22:55,690 --> 00:23:00,510 These patterns suggest that high discharge plumes modified by wind mixing, appear to 344 00:23:00,510 --> 00:23:04,870 affect the spatial distributions of larval fishes over very short timescales, which could 345 00:23:04,870 --> 00:23:11,030 result in alternate trophic interactions. 346 00:23:11,030 --> 00:23:21,140 Ok, so to determine the impacts of encounter with these dynamic plume processes on larval 347 00:23:21,140 --> 00:23:26,480 fish survival, we also towed a multi-net system over the same study period to capture fish 348 00:23:26,480 --> 00:23:31,800 larvae from turbulent, low salinity, plume water masses, and then we also towed nets 349 00:23:31,800 --> 00:23:35,430 to compare fish larvae from ambient shelfwater masses for comparison. 350 00:23:35,430 --> 00:23:40,290 So the locations and environmental conditions that each net tow sampled are shown in the 351 00:23:40,290 --> 00:23:46,160 physical profiles here. 352 00:23:46,160 --> 00:23:50,270 So we then examined the two most abundant species captured in the net tows, which were 353 00:23:50,270 --> 00:23:54,960 larval Striped anchovies shown on the left, and larval Sandy seatrout shown on the right. 354 00:23:54,960 --> 00:23:59,660 I've also included pictures of their adult stages so you have a better idea what they 355 00:23:59,660 --> 00:24:01,170 look like. 356 00:24:01,170 --> 00:24:04,880 So both of these are common species that are spawned in the nearshore regions of the Northern 357 00:24:04,880 --> 00:24:09,131 Gulf of Mexico, from March to April, and some larvae enter estuarine systems, which provide 358 00:24:09,131 --> 00:24:12,670 critical nursery habitat for the larval in juvenile stages. 359 00:24:12,670 --> 00:24:17,480 During their larval stages, major prey items for both species include calanoid copepods. 360 00:24:17,480 --> 00:24:22,090 To examine the effects of plume encounter on fish larvae, we compared growth and morphometric 361 00:24:22,090 --> 00:24:25,760 condition between larvae captured from these low band plume waters, which will be shown 362 00:24:25,760 --> 00:24:30,530 in green, in the subsequent slides, and high salinity shelfwaters, which were shown in 363 00:24:30,530 --> 00:24:32,550 blue from now on. 364 00:24:32,550 --> 00:24:40,610 So, to look at growth of fish larvae, we conducted otolith microstructure analysis for both species. 365 00:24:40,610 --> 00:24:45,250 Sagittal otolith, of each species were dissected, and read it a thousand times magnification 366 00:24:45,250 --> 00:24:47,440 using image processing software. 367 00:24:47,440 --> 00:24:51,530 Two metrics were used to analyze growth patterns in each water mass: Mean daily growth, which 368 00:24:51,530 --> 00:24:56,460 is shown us the purple line on the otolith, was calculated by averaging increment width 369 00:24:56,460 --> 00:24:59,400 over each day of life of all individuals. 370 00:24:59,400 --> 00:25:03,040 Mean recent growth, which is shown as the red line, was calculated by averaging growth 371 00:25:03,040 --> 00:25:07,460 of each individual over the last three full days of life prior to capture. 372 00:25:07,460 --> 00:25:11,410 Recent growth was used because exact timing of larval entrainment in each plume water 373 00:25:11,410 --> 00:25:12,580 mass is unknown. 374 00:25:12,580 --> 00:25:16,780 But this allows us to infer how the different environmental conditions the larvae were experiencing 375 00:25:16,780 --> 00:25:20,350 around the time of capture, affected their growth rate. 376 00:25:20,350 --> 00:25:27,150 So we use linear mixed effects models to test whether mean daily growth differed between 377 00:25:27,150 --> 00:25:30,890 plume and shelf-captured fish larvae for each of the two species. 378 00:25:30,890 --> 00:25:35,130 The model parameters for each species included fixed effects of age, the water mass they 379 00:25:35,130 --> 00:25:40,420 were captured from, either plume or shelf, and an age by water mass interaction term. 380 00:25:40,420 --> 00:25:44,320 To account for repeated measures of daily growth of individual fish, the full model 381 00:25:44,320 --> 00:25:48,220 included both the random intercept term of fish identity, and the random slip term of 382 00:25:48,220 --> 00:25:50,360 age for each individual. 383 00:25:50,360 --> 00:25:54,870 First order auto regressive correlation terms were also included in all models as a random 384 00:25:54,870 --> 00:25:59,140 effect, to account for the inherent auto correlation between measuring sequential order increments. 385 00:25:59,140 --> 00:26:03,480 Model selection was performed using a backward stepwise approach, because it successfully 386 00:26:03,480 --> 00:26:05,210 removed random and fixed effects. 387 00:26:05,210 --> 00:26:08,580 And the final model was selected using AIC, and is shown here. 388 00:26:08,580 --> 00:26:13,360 So for the results, we found that daily growth varied significantly with age and water mass 389 00:26:13,360 --> 00:26:15,230 occupied by larvae. 390 00:26:15,230 --> 00:26:20,290 For both species, these linear mixed effects models indicated that daily growth was initially 391 00:26:20,290 --> 00:26:24,450 slightly higher for plume larvae, which are shown in green, than shelf larvae, which are 392 00:26:24,450 --> 00:26:25,660 shown in blue. 393 00:26:25,660 --> 00:26:30,720 And this was in the early life, but then it reversed around day 20 to 25 for larval anchovy 394 00:26:30,720 --> 00:26:35,500 and around day 5 to 6 for larval seatrout and began increasing more rapidly with age 395 00:26:35,500 --> 00:26:37,660 and shelf larvae than plume larvae. 396 00:26:37,660 --> 00:26:41,880 So these diverging growth trajectories may be indicative of early encounter with plume 397 00:26:41,880 --> 00:26:48,150 water masses for seatrout larvae and later encounter in life for anchovy larvae. 398 00:26:48,150 --> 00:26:54,760 However, because the exact timing of larval entrainment within a plume could not be determined, 399 00:26:54,760 --> 00:26:58,280 we also examined recent growth during the last three complete days of life prior to 400 00:26:58,280 --> 00:27:03,020 capture for all larvae, to minimize the potential effects of differential spatial and environmental 401 00:27:03,020 --> 00:27:05,350 conditions on early larval growth. 402 00:27:05,350 --> 00:27:09,730 Interestingly, we found that mean recent growth over the last three days of life was significantly 403 00:27:09,730 --> 00:27:14,900 slower and plume larvae, shown in green, and shelf larvae, shown in blue for both species. 404 00:27:14,900 --> 00:27:19,330 In general, fast growing fish larvae are of higher condition, accumulating more lipids, 405 00:27:19,330 --> 00:27:22,890 and reaching the minimum condition needed for metamorphosis sooner than their slower 406 00:27:22,890 --> 00:27:24,170 growing counterparts. 407 00:27:24,170 --> 00:27:29,590 Thus, the slower growing larvae, in plume waters, were likely more susceptible to predation. 408 00:27:29,590 --> 00:27:33,980 By reducing growth and lengthening the duration of the small invulnerable larval stage, encounter 409 00:27:33,980 --> 00:27:43,420 with dynamic plume waters likely confers a survival disadvantage to fish larvae. 410 00:27:43,420 --> 00:27:47,920 So we also compared condition of plume and shelf larvae, by measuring 5 to 6 linear body 411 00:27:47,920 --> 00:27:53,260 dimensions, such as head depth, dorsal depth, etc. that have been shown to vary with larval 412 00:27:53,260 --> 00:27:55,020 feeding success. 413 00:27:55,020 --> 00:27:59,020 The body morphometrics were then regressed against length to compare condition of larvae 414 00:27:59,020 --> 00:28:01,310 collected from plume and shelf waters. 415 00:28:01,310 --> 00:28:05,560 Though fish larvae everywhere were skinnier-at-length, they were likely not feeding as well, suggesting 416 00:28:05,560 --> 00:28:06,990 they were in poorer condition. 417 00:28:06,990 --> 00:28:10,580 If fish larvae were fatter-at-length, they were likely feeding better, and therefore 418 00:28:10,580 --> 00:28:12,740 were in higher condition. 419 00:28:12,740 --> 00:28:19,490 So, non-metric, multidimensional scaling, revealed differences in body morphometrics 420 00:28:19,490 --> 00:28:20,960 between water masses. 421 00:28:20,960 --> 00:28:24,850 As you can see here, for both species of fish, Axis 1 explained most of the variation in 422 00:28:24,850 --> 00:28:29,120 body shape and was positively correlated with all body dimensions and therefore served as 423 00:28:29,120 --> 00:28:31,710 a suitable proxy for larval body condition. 424 00:28:31,710 --> 00:28:35,310 This means of a fish ordinates on the right side of the Axis and is fatter-at-length and 425 00:28:35,310 --> 00:28:36,770 in higher condition overall. 426 00:28:36,770 --> 00:28:41,620 When we ran the ordination, we found that plume-captured larvae, shown as the green 427 00:28:41,620 --> 00:28:45,410 triangles, generally clustering on the left side of the axis, indicating they were in 428 00:28:45,410 --> 00:28:50,480 poorer condition, or skinnier-at-length, while shelf-captured larvae, shown as the blue circles, 429 00:28:50,480 --> 00:28:53,640 generally clustered on the right side of the axis, indicating they were in higher morphometric 430 00:28:53,640 --> 00:28:56,080 condition. 431 00:28:56,080 --> 00:29:00,380 So not only were plumed-captured larvae generally growing slower, they were also skinnier-at-length 432 00:29:00,380 --> 00:29:07,900 on their shelf-caught specifics. 433 00:29:07,900 --> 00:29:12,540 So why were plume-captured larvae growing more slowly and in poorer condition? 434 00:29:12,540 --> 00:29:14,700 We have a couple of hypotheses. 435 00:29:14,700 --> 00:29:18,710 It could possibly be due to the physiological stress of entrainment within a low salinity 436 00:29:18,710 --> 00:29:20,260 water mass. 437 00:29:20,260 --> 00:29:25,110 However, experimental studies have shown that both anchovy and seatrout to be highly euryhaline 438 00:29:25,110 --> 00:29:29,500 and eurythermal and generally tolerant to the fluctuating conditions inherent of the 439 00:29:29,500 --> 00:29:33,180 coastal systems and estuaries they inhabit as larvae. 440 00:29:33,180 --> 00:29:38,400 So given this, it is likely that other physical and biological factors are more directly associated 441 00:29:38,400 --> 00:29:39,710 with reduced growth and condition. 442 00:29:39,710 --> 00:29:44,400 For example, perhaps there were less prey and feeding opportunities for fish larvae 443 00:29:44,400 --> 00:29:46,100 in plume water masses. 444 00:29:46,100 --> 00:29:51,860 However, when we actually compared calanoid copepod biomass in plume versus shelfwater 445 00:29:51,860 --> 00:29:56,210 masses, we found that there was actually higher concentrations of prey available in the plume 446 00:29:56,210 --> 00:30:03,000 water masses across all three transects of our study. 447 00:30:03,000 --> 00:30:06,860 Therefore we think it is most plausible that plume physical properties are disrupting larval 448 00:30:06,860 --> 00:30:08,140 feeding success. 449 00:30:08,140 --> 00:30:12,220 Our study showed very high levels of turbulence within the plumes as compared with the underlying 450 00:30:12,220 --> 00:30:13,470 shelfwaters. 451 00:30:13,470 --> 00:30:16,560 Experimental studies have shown that very high turbulence decreases larval fish prey 452 00:30:16,560 --> 00:30:18,530 capture success. 453 00:30:18,530 --> 00:30:23,000 One research group showed that at 10 to the negative 2 turbulence dissipation rates, herring 454 00:30:23,000 --> 00:30:27,570 and cod larvae experienced significant declines of captured successive prey. 455 00:30:27,570 --> 00:30:31,990 In comparison, our turbulence dissipation rates within plume waters exceeded these experimental 456 00:30:31,990 --> 00:30:33,790 values by a few orders of magnitude. 457 00:30:33,790 --> 00:30:38,310 Therefore, it is possible that the high turbulence within plume water may be inhibiting prey 458 00:30:38,310 --> 00:30:43,160 contact and decreasing the ability of larval fish to capture prey which would quickly manifest 459 00:30:43,160 --> 00:30:50,180 as slower recent growth and poorer morphometric condition for these larvae. 460 00:30:50,180 --> 00:30:54,540 Another hypothesis we have is that although prey are available, fish larvae may be unable 461 00:30:54,540 --> 00:30:56,820 to detect them within the plume waters. 462 00:30:56,820 --> 00:31:03,530 Side-by-side raw ISIIS images from the plume and nearby coastal shelfwaters show how dark 463 00:31:03,530 --> 00:31:07,810 and full of particulates Mobile Bay plume is at the scale of an individual fish larvae. 464 00:31:07,810 --> 00:31:13,630 This makes sense when you think of how nutrient-rich plume water is higher in both phytoplankton 465 00:31:13,630 --> 00:31:15,570 and sediments. 466 00:31:15,570 --> 00:31:19,480 Because fish larvae are visual predators, high turbidity and plumes could be inhibiting 467 00:31:19,480 --> 00:31:23,400 their ability to visually detect their prey and may be contributing to the lower growth 468 00:31:23,400 --> 00:31:26,110 and condition patterns we observed in this study. 469 00:31:26,110 --> 00:31:33,390 So to summarize, larval fish and river-dominated coastal ecosystems experienced highly variable 470 00:31:33,390 --> 00:31:35,210 physical and trophic environments. 471 00:31:35,210 --> 00:31:39,280 The aggregation and retention of planktonic prey and a stratified water column near the 472 00:31:39,280 --> 00:31:44,091 Mobile Bay plume suggests that under stable conditions with minimal wind forcing, distribution 473 00:31:44,091 --> 00:31:48,890 near coastal river plume could facilitate enhanced prey contact and thus increase survival 474 00:31:48,890 --> 00:31:49,930 of fish larvae. 475 00:31:49,930 --> 00:31:54,600 However, our documentation of the spatial separation of fish larvae from their prey, 476 00:31:54,600 --> 00:31:58,870 with increasing wind stress and turbulence, indicates this relationship can really quickly 477 00:31:58,870 --> 00:31:59,870 change. 478 00:31:59,870 --> 00:32:03,120 Additionally, entrainment within plume water masses appeared to result in larvae growing 479 00:32:03,120 --> 00:32:07,230 more slowly, and being skinnier-at-length than their shelf-caught specifics, suggesting 480 00:32:07,230 --> 00:32:11,230 there are measurable consequences for encounter with high discharge river plumes, especially 481 00:32:11,230 --> 00:32:12,840 under high wind stress. 482 00:32:12,840 --> 00:32:17,270 Therefore, our results suggest that the environmental conditions inherent of a freshwater influence 483 00:32:17,270 --> 00:32:22,501 coastal regions can indeed enhance larval fish survival via bottom-up processes, but 484 00:32:22,501 --> 00:32:26,610 at physical forcing the system begins to dominate the biological interactions the habitat can 485 00:32:26,610 --> 00:32:31,930 quickly become unfavorable for larval fishes. 486 00:32:31,930 --> 00:32:35,760 So future climate projections for the Northern Gulf of Mexico are variable and uncertain 487 00:32:35,760 --> 00:32:40,360 as of now, but general global patterns predict increases in weather extremes such as heavy 488 00:32:40,360 --> 00:32:44,130 precipitation storms, high river discharge events, and increasing wind speeds. 489 00:32:44,130 --> 00:32:50,370 The increase in frequency magnitude and duration of freshwater delivered to coastal ecosystems 490 00:32:50,370 --> 00:32:54,320 could prolong conditions that can negatively impact larval fish survival. 491 00:32:54,320 --> 00:32:59,580 So while increased nutrient-rich river discharge would immediately enhance coastal primary 492 00:32:59,580 --> 00:33:04,690 productivity, highly turbid plume water could impair the ability of fish larvae to forage 493 00:33:04,690 --> 00:33:10,030 successfully, despite the higher zooplankton biomass accompanying enhanced coastal productivity. 494 00:33:10,030 --> 00:33:15,240 Further, increased river discharge and widespread turbulent frontal zones may inhibit prey capture 495 00:33:15,240 --> 00:33:17,680 abilities of entrained fish larvae. 496 00:33:17,680 --> 00:33:22,180 Ultimately, results of the present study build on our understanding of how increased freshwater 497 00:33:22,180 --> 00:33:27,210 discharge and coastal ecosystems worldwide can influence nearshore fish communities at 498 00:33:27,210 --> 00:33:30,920 scales relevant to the vulnerable larval stages. 499 00:33:30,920 --> 00:33:34,400 All right. 500 00:33:34,400 --> 00:33:38,610 So now I'm going to change gears a bit, and give a quick overview on a couple of the research 501 00:33:38,610 --> 00:33:43,490 projects I'm involved with for the EcoFOCI group of the Alaska Fisheries Science Center, 502 00:33:43,490 --> 00:33:47,430 where I'll be studying how different climate mediated physical processes affect the early 503 00:33:47,430 --> 00:33:49,520 life stages of Alaskan and Arctic fishes. 504 00:33:49,520 --> 00:33:55,260 So, really, I'm asking similar research questions as before, but in a different and much colder 505 00:33:55,260 --> 00:33:58,950 system. 506 00:33:58,950 --> 00:34:03,100 So one major concern and research priority for Alaska Fisheres Science Center is understanding 507 00:34:03,100 --> 00:34:08,110 how species distributions may shift in response to increasing sea surface temperatures since 508 00:34:08,110 --> 00:34:12,011 there is the potential for the northward expansion of more southerly distributed species as a 509 00:34:12,011 --> 00:34:16,230 consequence of Arctic warming. 510 00:34:16,230 --> 00:34:19,710 So some new data I'm beginning to work with is looking at the distributional changes of 511 00:34:19,710 --> 00:34:23,589 different larval fish assemblages in the US Arctic from 2010 through 2019. 512 00:34:23,589 --> 00:34:28,540 A collaborator on this project, Esther Goldstein from Alaska Fisheres Science Center Age and 513 00:34:28,540 --> 00:34:33,159 Growth Group, ran a non-metric multidimensional scaling analysis to ordinate larval fish catches 514 00:34:33,159 --> 00:34:37,230 per unit effort, by warm, cold, and mixed water assemblages. 515 00:34:37,230 --> 00:34:41,810 You can see that the warmer water assemblages, shown in red on the left, was comprised of 516 00:34:41,810 --> 00:34:46,750 taxa like Yellowfin Sole, while the colder water assemblages, shown in blue on the right, 517 00:34:46,750 --> 00:34:50,990 was comprised of species like Arctic Cod, and that species such as Saffron Cod, and 518 00:34:50,990 --> 00:34:53,610 Pollock made up the middle, mixed assemblage. 519 00:34:53,610 --> 00:34:57,590 The color was based on Axis 1 scores and only larvae that made up greater than 2% of the 520 00:34:57,590 --> 00:35:02,110 data were used in this analysis. 521 00:35:02,110 --> 00:35:05,530 So the distributions of the different larval fish assemblages were then plotted for each 522 00:35:05,530 --> 00:35:06,530 year. 523 00:35:06,530 --> 00:35:10,810 You can see that in years where there is low summer sea ice, and more warm Alaskan coastal 524 00:35:10,810 --> 00:35:16,830 water present, like 2010 and 2011, also 2017, 2018 and 2019, that there are more warmer 525 00:35:16,830 --> 00:35:21,560 and mixed waters species, like Yellowfin Sole and Saffron Cod, shown as the red and teal 526 00:35:21,560 --> 00:35:24,290 circles dominating the assemblage. 527 00:35:24,290 --> 00:35:28,470 So there's this potential trend in warmer water larval fish assemblages, distributed 528 00:35:28,470 --> 00:35:33,180 further north into habitats historically primarily occupied by cold water assemblages such as 529 00:35:33,180 --> 00:35:34,290 Arctic Cod. 530 00:35:34,290 --> 00:35:41,640 So we plan to build off of this analysis to assess changes in these assemblages in relation 531 00:35:41,640 --> 00:35:45,800 to two different environmental drivers, like temperature, ice cover, and then different 532 00:35:45,800 --> 00:35:47,330 water masses. 533 00:35:47,330 --> 00:35:52,140 But the primary goal of this project is to examine community-wide distributional shifts 534 00:35:52,140 --> 00:35:54,370 of Arctic-level fish taxa over time. 535 00:35:54,370 --> 00:35:59,260 So, is there a northward expansion of boreal species and how will this change the ecological 536 00:35:59,260 --> 00:36:02,530 interactions experienced by Arctic larval fishes? 537 00:36:02,530 --> 00:36:06,240 So this will likely involve comparing centers of distributions of common Arctic species 538 00:36:06,240 --> 00:36:10,390 from year to year, and possibly some predictive modeling to look at projections of future 539 00:36:10,390 --> 00:36:15,240 scenarios with increased temperature and sea ice loss. 540 00:36:15,240 --> 00:36:21,930 So, another project I'm beginning to work on focuses on Arctic Cod, which are one of 541 00:36:21,930 --> 00:36:27,090 the most abundant fish in the Arctic Ocean and a key prey resource for upper trophic-level 542 00:36:27,090 --> 00:36:28,210 organisms. 543 00:36:28,210 --> 00:36:35,060 Arctic Cod are tightly linked to the sea ice habitat, with young Arctic Cod feeding under 544 00:36:35,060 --> 00:36:38,250 the ice on small zooplankton that feed on the ice algae. 545 00:36:38,250 --> 00:36:42,960 Therefore, they are especially vulnerable to warming and loss of sea ice, which is a 546 00:36:42,960 --> 00:36:47,040 real problem, as we're seeing sea ice retreat earlier and earlier in the spring with overall 547 00:36:47,040 --> 00:36:49,330 less spatial coverage throughout the year. 548 00:36:49,330 --> 00:36:54,590 However, the impacts of recent severe shifts in sea ice extent and phenology on larval 549 00:36:54,590 --> 00:36:58,790 Arctic Cod survival is challenging to predict due to the lack of early life history data 550 00:36:58,790 --> 00:37:02,550 on this species. 551 00:37:02,550 --> 00:37:07,020 So this project stems from the Arctic Integrated Ecosystem Research Program field efforts, 552 00:37:07,020 --> 00:37:11,530 which sample larval fishes in the North Bering and Chukchi sea region using bongo nets in 553 00:37:11,530 --> 00:37:14,830 June and August and September of 2017 and 2018. 554 00:37:14,830 --> 00:37:19,820 So, when the lab opens up again, hopefully not too far in the future, my collaborator, 555 00:37:19,820 --> 00:37:24,240 Ali Deary and I, plan to conduct a seasonal and interannual comparison of the diet composition 556 00:37:24,240 --> 00:37:28,860 and prey selectivity of Arctic Cod larvae to examine trophic relationships in relation 557 00:37:28,860 --> 00:37:32,740 to sea ice loss and other climate mediated physical processes. 558 00:37:32,740 --> 00:37:36,680 Another collaborator on this project, Esther Goldstein, is also working on otolith analyses 559 00:37:36,680 --> 00:37:40,740 of some of these fish, which will enable us to back calculate hatch dates and hopefully 560 00:37:40,740 --> 00:37:45,320 relate growth to feeding success of Arctic Cod early life stages. 561 00:37:45,320 --> 00:37:52,050 So, ultimately, documenting changes in the distributions, trophic relationships, and 562 00:37:52,050 --> 00:37:57,130 survival of the early life stages of marine fishes in response to the environment, regardless 563 00:37:57,130 --> 00:38:01,170 of the system, is critical to predicting how future climate scenarios will affect fisheries 564 00:38:01,170 --> 00:38:02,170 production worldwide. 565 00:38:02,170 --> 00:38:06,400 So, that's all I have for the summary of my past and future research. 566 00:38:06,400 --> 00:38:09,920 And so with that, I will take any questions, if you have any. 567 00:38:09,920 --> 00:38:14,490 Heather Tabisola >> Keely, thank you so much. 568 00:38:14,490 --> 00:38:19,750 I will clap for everybody, just imagine a very big room, or 150 people clapping for 569 00:38:19,750 --> 00:38:20,750 you. 570 00:38:20,750 --> 00:38:21,750 Um... 571 00:38:21,750 --> 00:38:22,750 So... 572 00:38:22,750 --> 00:38:23,750 I know weird. 573 00:38:23,750 --> 00:38:29,470 Ok, so with that, I have not seen any questions yet go into the chat. 574 00:38:29,470 --> 00:38:35,120 So please, for those who are still on the line, please type your questions into the 575 00:38:35,120 --> 00:38:40,470 chat feature so that Jens and I can address those with Keely. 576 00:38:40,470 --> 00:38:43,790 And again, Keely, thank you so much for doing this. 577 00:38:43,790 --> 00:38:45,540 Kelia Axler >> Yeah, of course. 578 00:38:45,540 --> 00:38:49,080 Heather Tabisola >> Introduction to get to know the work that 579 00:38:49,080 --> 00:38:53,390 you've done and that you're going to be doing here with EcoFOCI. 580 00:38:53,390 --> 00:38:57,960 I'm just monitoring... 581 00:38:57,960 --> 00:38:59,480 Really? 582 00:38:59,480 --> 00:39:04,060 No questions, yet? 583 00:39:04,060 --> 00:39:09,990 You might scapegoat out of this one. 584 00:39:09,990 --> 00:39:15,150 Kelia Axler >> Well, if people do have questions they want to send later, and I put my e-mail 585 00:39:15,150 --> 00:39:16,990 at the bottom of the slide, so. 586 00:39:16,990 --> 00:39:18,450 Heather Tabisola >> Alright, we got this. 587 00:39:18,450 --> 00:39:19,450 Ok. 588 00:39:19,450 --> 00:39:22,110 Colleen, a teacher who actually used to work with the FOCI... 589 00:39:22,110 --> 00:39:25,670 See, now everybody's typing questions now, I won't even... 590 00:39:25,670 --> 00:39:32,640 Ok, so Colleen asks: Were there more gelatinous zooplankton associated with the higher turbidity 591 00:39:32,640 --> 00:39:37,960 waters in the Gulf of Mexico because they are non-visual predators and potential competitors 592 00:39:37,960 --> 00:39:38,960 with fish larvae? 593 00:39:38,960 --> 00:39:44,230 Kelia Axler >> Yes, that is something that we definitely think is happening. 594 00:39:44,230 --> 00:39:51,090 Generally, lots of studies have shown that gelatinous zooplankton are frequently found 595 00:39:51,090 --> 00:39:56,529 aggregating within plume waters but then also at the frontal edges of the plume waters and 596 00:39:56,529 --> 00:39:58,040 those convergent regions. 597 00:39:58,040 --> 00:40:03,961 And so that's why we use gelatinous zooplankton as the larval fish predator group to focus 598 00:40:03,961 --> 00:40:10,990 on because we know that they are very abundant in these water masses and that they aren't 599 00:40:10,990 --> 00:40:16,050 affected by turbidity, because they are not visual predators. 600 00:40:16,050 --> 00:40:19,230 They're tactile predators, so they are just feeling around. 601 00:40:19,230 --> 00:40:21,230 Yeah, so great question. 602 00:40:21,230 --> 00:40:23,740 Heather Tabisola >> Thank you, Colleen. 603 00:40:23,740 --> 00:40:30,920 Stephanie Donor, sorry, Stephanie if I mispronounced your last name, has asked: Have you compared 604 00:40:30,920 --> 00:40:36,970 your field results for Mobile Bay to modeled flow during typical and extreme outflows? 605 00:40:36,970 --> 00:40:41,500 Kelia Axler >> That's a good question. 606 00:40:41,500 --> 00:40:49,080 So like I said, the typical river discharge from Mobile Bay is 2200 cubic meters per second. 607 00:40:49,080 --> 00:40:51,690 And it can mean extreme outflows. 608 00:40:51,690 --> 00:40:55,200 I think they've recorded around 12,000 cubic meters per second. 609 00:40:55,200 --> 00:41:00,610 We only sampled during a high discharge event, which was 6000 cubic meters per second. 610 00:41:00,610 --> 00:41:08,780 So this is like, what we sample in was higher discharge, but not extremely high discharge. 611 00:41:08,780 --> 00:41:17,760 And so, it's, the level of discharge is pretty typical for this system in spring, when there's 612 00:41:17,760 --> 00:41:18,810 a lot of rain. 613 00:41:18,810 --> 00:41:26,000 And we're happy with that, with our sampling of that, because it is, they are conditions 614 00:41:26,000 --> 00:41:28,360 that occur throughout the year. 615 00:41:28,360 --> 00:41:33,119 So, it wasn't on the extreme end, but it also wasn't on the low end. 616 00:41:33,119 --> 00:41:42,050 Heather Tabisola >> Ok, Dave Kimmel has asked: Most of your work in the Gulf of Mexico occurred 617 00:41:42,050 --> 00:41:44,820 in the spring prior to hypoxia setting up. 618 00:41:44,820 --> 00:41:47,760 Oops, of course I just scrolled past it. 619 00:41:47,760 --> 00:41:52,180 But could you comment and how hypoxia might impact your findings? 620 00:41:52,180 --> 00:41:54,600 Kelia Axler >> Yes. 621 00:41:54,600 --> 00:41:55,600 Hypoxia? 622 00:41:55,600 --> 00:42:01,210 So, yeah, as as more nutrient-rich river discharge comes into the region and the water temperatures 623 00:42:01,210 --> 00:42:04,040 warm, and there's stratification, hypoxia can set in. 624 00:42:04,040 --> 00:42:05,740 And it would be really... 625 00:42:05,740 --> 00:42:10,340 So, we actually did do summer sampling during hypoxic regions. 626 00:42:10,340 --> 00:42:18,390 And I'll actually point you to Adam Greer has a paper out that discusses some of those 627 00:42:18,390 --> 00:42:22,840 hypoxia findings where he did look at larval fish and zooplankton distributions throughout 628 00:42:22,840 --> 00:42:25,110 hypoxic regions. 629 00:42:25,110 --> 00:42:30,650 And I believe he found that there was some that there was some potential and behavioral 630 00:42:30,650 --> 00:42:36,930 avoidance of these hypoxic regions by larval fish, but not so much of gelatinous zooplankton, 631 00:42:36,930 --> 00:42:41,880 which again seemed to be pretty highly tolerant of a lot of different conditions including 632 00:42:41,880 --> 00:42:44,060 low oxygen. 633 00:42:44,060 --> 00:42:49,650 So again, the data are there to be analyzed someday in the future, perhaps. 634 00:42:49,650 --> 00:42:58,270 But I think that there would be some spatial avoidance of hypoxic zones by organisms that 635 00:42:58,270 --> 00:43:01,820 are more sensitive to lower oxygen conditions. 636 00:43:01,820 --> 00:43:03,690 Heather Tabisola >> Thanks, Keely. 637 00:43:03,690 --> 00:43:04,690 OK. 638 00:43:04,690 --> 00:43:05,690 Let's see. 639 00:43:05,690 --> 00:43:06,690 Valerie... 640 00:43:06,690 --> 00:43:13,520 Well, I should first say Natasha Hardy, who was on, she just had a comment, mainly, she 641 00:43:13,520 --> 00:43:17,520 said, this was awesome. 642 00:43:17,520 --> 00:43:18,900 And I agree, Natasha. 643 00:43:18,900 --> 00:43:19,900 Let's see. 644 00:43:19,900 --> 00:43:23,770 Ok, and Valerie Brady, the ice, that sounds pretty awesome. 645 00:43:23,770 --> 00:43:28,180 Could a device work...could such a device work in the Great Lakes? 646 00:43:28,180 --> 00:43:31,040 Kelia Axler >> Hi, Val. 647 00:43:31,040 --> 00:43:32,050 That's a good question. 648 00:43:32,050 --> 00:43:39,250 I think it would, but I also think that you would have to have a lot of large hard drives 649 00:43:39,250 --> 00:43:45,450 because there is a lot less plankton in the Great Lakes and so that would be a lot of 650 00:43:45,450 --> 00:43:53,130 video footage that you would have to tow for very long time to be able to collect, 651 00:43:53,130 --> 00:43:54,770 you know, substantial data. 652 00:43:54,770 --> 00:43:57,160 But I do think that the Great Lakes are very oligotrophic. 653 00:43:57,160 --> 00:43:58,160 I spent. 654 00:43:58,160 --> 00:43:59,160 well... 655 00:43:59,160 --> 00:44:00,860 Lake Superior, I'm thinking of, in particular. 656 00:44:00,860 --> 00:44:05,940 And so it would, the images would be pretty high quality because the visibility is a lot 657 00:44:05,940 --> 00:44:07,720 better in the in Lake Superior. 658 00:44:07,720 --> 00:44:11,290 Lake Michigan would be a different story, Lake Erie, but yeah. 659 00:44:11,290 --> 00:44:13,920 That, I think it's possible. 660 00:44:13,920 --> 00:44:18,050 Heather Tabisola >> And then Jerry Wiersma said... 661 00:44:18,050 --> 00:44:19,370 It's a long question. 662 00:44:19,370 --> 00:44:21,030 So, bear with me, OK. 663 00:44:21,030 --> 00:44:24,410 I think it's multiple questions here so I'm just gonna ask it. 664 00:44:24,410 --> 00:44:30,690 How do you measure the difference between shelf and plume fish larvae? 665 00:44:30,690 --> 00:44:35,930 In other words, how do you distinguish the larvae affected by plumes and living away 666 00:44:35,930 --> 00:44:37,290 from the plume? 667 00:44:37,290 --> 00:44:38,670 Was not really clear in the method. 668 00:44:38,670 --> 00:44:42,230 Hope my question is not too confusing. 669 00:44:42,230 --> 00:44:46,920 And then also, do you have a recommendation to reduce the plumes into the river? 670 00:44:46,920 --> 00:44:52,320 And will the reduction be likely to increase the survival rate of fish larvae? 671 00:44:52,320 --> 00:44:54,740 Kelia Axler >> For the first question. 672 00:44:54,740 --> 00:45:01,620 So we sampled, we towed nets within clean water masses, which you can visually see because 673 00:45:01,620 --> 00:45:06,030 of the turbidity difference from the surface, the water is like greener, browner. 674 00:45:06,030 --> 00:45:10,320 But we also had a CTD mounted on our net systems. 675 00:45:10,320 --> 00:45:15,520 And so while we were towing the nets, we knew exactly where, like, that we were in a low 676 00:45:15,520 --> 00:45:18,670 salinity water mass. 677 00:45:18,670 --> 00:45:22,880 And the shelf stations that we, the shelf station that we sampled, we knew was a high 678 00:45:22,880 --> 00:45:30,270 salinity water mass outside of the plume because we had a CTD again, and we're tracking the 679 00:45:30,270 --> 00:45:31,270 salinity. 680 00:45:31,270 --> 00:45:33,700 So we knew that these fish, the fish larvae that we collected, 681 00:45:33,700 --> 00:45:38,580 so at the time of capture, these fish larvae were either entrained within a plume or in 682 00:45:38,580 --> 00:45:40,320 surrounding shelf waters. 683 00:45:40,320 --> 00:45:48,610 For your second question as to how to reduce the amount of river discharge, there's not 684 00:45:48,610 --> 00:45:55,150 really a great way because obviously with increasingly heavy precipitation storms, there's 685 00:45:55,150 --> 00:45:58,540 in the Midwest, there's just more water that's coming down 686 00:45:58,540 --> 00:46:00,810 into the Gulf of Mexico. 687 00:46:00,810 --> 00:46:06,150 And again, you know, freshwater influence in coastal regions has generally been shown 688 00:46:06,150 --> 00:46:11,240 to increase coastal productivity and potentially provide a better feeding environment for fish 689 00:46:11,240 --> 00:46:12,290 larvae. 690 00:46:12,290 --> 00:46:22,390 But if there's so much that the...the phytoplankton blooms are enormous, and reducing turbidity 691 00:46:22,390 --> 00:46:25,660 but then also, I didn't talk about this, but they can cause... 692 00:46:25,660 --> 00:46:31,590 Sorry, harmful algal blooms, which can also kill marine organisms and cause stress on 693 00:46:31,590 --> 00:46:32,600 local fisheries. 694 00:46:32,600 --> 00:46:34,230 That's also a really big issue. 695 00:46:34,230 --> 00:46:36,650 So unfortunately, there's no, there's no easy fix there. 696 00:46:36,650 --> 00:46:39,410 Heather Tabisola >> Ok, let's see. 697 00:46:39,410 --> 00:46:41,070 Thank you, Keely. 698 00:46:41,070 --> 00:46:47,090 Oh, and Jerry just followed, yes, the turbidity and nutrient outwash is more of a problem 699 00:46:47,090 --> 00:46:48,340 than the salinity draw. 700 00:46:48,340 --> 00:46:52,290 Just a comment by him or them as well. 701 00:46:52,290 --> 00:46:59,960 Terence Wang also added, let's see, the fish larvae predators may be more tactile feeders. 702 00:46:59,960 --> 00:47:05,510 Are they still negatively impacted by the turbid waters because their prey are less 703 00:47:05,510 --> 00:47:07,670 concentrated and well fed? 704 00:47:07,670 --> 00:47:11,890 Kelia Axler >> Hmm, that's a good question. 705 00:47:11,890 --> 00:47:22,010 Um, I guess I would think that they would, their prey might be more concentrated within 706 00:47:22,010 --> 00:47:27,280 these plume water masses, as we saw like, for example, calanoid copepods were in higher 707 00:47:27,280 --> 00:47:31,060 abundances within the plume waters than the surrounding waters. 708 00:47:31,060 --> 00:47:37,040 And again, that's probably because of physical convergence, retaining and accumulating plankton 709 00:47:37,040 --> 00:47:43,000 in that region, but then also the higher primary productivity, which can increase the general 710 00:47:43,000 --> 00:47:44,000 zooplankton biomass. 711 00:47:44,000 --> 00:47:48,119 So, I actually think that the feeding there's more prey for gelatinous zooplankton within 712 00:47:48,119 --> 00:47:49,930 plumes. 713 00:47:49,930 --> 00:47:57,460 But again, them being tactile predators, they probably aren't affected by turbidity as much 714 00:47:57,460 --> 00:48:00,380 as visual predators like larval fishes are. 715 00:48:00,380 --> 00:48:05,109 Heather Tabisola >> Thank you, Keely. 716 00:48:05,109 --> 00:48:09,150 Um, alright, that is the last of the questions I have right now. 717 00:48:09,150 --> 00:48:12,110 So this is the last call for questions. 718 00:48:12,110 --> 00:48:18,240 And while I give that a minute, just to remember that we do have one more EcoFOCI seminar for 719 00:48:18,240 --> 00:48:21,350 this series, and that is next week. 720 00:48:21,350 --> 00:48:24,550 The seminar is listed on the One NOAA Science Seminar series. 721 00:48:24,550 --> 00:48:29,730 And then again, you can also find details through the NOAA Pacific Marine Environmental 722 00:48:29,730 --> 00:48:31,450 Lab calendar of events listed there. 723 00:48:31,450 --> 00:48:39,000 And of course, if you guys have, if anybody has follow-up questions, please message myself 724 00:48:39,000 --> 00:48:40,000 or Jens. 725 00:48:40,000 --> 00:48:41,660 We are listed as the point of contacts. 726 00:48:41,660 --> 00:48:45,120 And then also, we did record this seminar today. 727 00:48:45,120 --> 00:48:48,670 So there's a lot of folks who couldn't join in, so we'll be sending this out and making 728 00:48:48,670 --> 00:48:51,080 it available for a period of time. 729 00:48:51,080 --> 00:48:55,460 So if you know anybody who will be looking for that as well, please just have them message 730 00:48:55,460 --> 00:48:59,410 both Jens and I. Keely, there's no more questions. 731 00:48:59,410 --> 00:49:04,890 Oh, I think with that, just one last thank you so much for joining us today. 732 00:49:04,890 --> 00:49:07,600 And I think we will conclude the seminar. 733 00:49:07,600 --> 00:49:08,600 Kelia Axler >> Great. 734 00:49:08,600 --> 00:49:09,650 Thank you for having me. 735 00:49:09,650 --> 00:49:12,210 Heather Tabisola >> All right, all right, everybody. 736 00:49:12,210 --> 00:49:14,780 Have a wonderful rest of your day. 737 00:49:14,780 --> 00:49:17,630 And stay healthy, and sane out there, OK? 738 00:49:17,630 --> 00:49:18,960 And we'll see you all back here next week.