1 00:00:04,140 --> 00:00:07,233 [Celia] I'd just like to acknowledge my collaborators. 2 00:00:08,190 --> 00:00:11,280 I especially wanna acknowledge Sarah Nelson, 3 00:00:11,280 --> 00:00:13,440 who is at the Appalachian Mountain Club, 4 00:00:13,440 --> 00:00:15,570 and really, the person who started 5 00:00:15,570 --> 00:00:20,280 this entire Dragonfly Mercury Project 6 00:00:20,280 --> 00:00:22,620 many years ago in Maine, 7 00:00:22,620 --> 00:00:24,300 when she was at the University of Maine. 8 00:00:24,300 --> 00:00:27,480 And I acknowledge my collaborators here, 9 00:00:27,480 --> 00:00:30,480 Christine Gardiner, my lab manager, and Vivian Taylor, 10 00:00:30,480 --> 00:00:33,960 who's in Earth Sciences here, who is also a collaborator. 11 00:00:33,960 --> 00:00:35,403 So, next slide please. 12 00:00:38,820 --> 00:00:40,380 So before we get into 13 00:00:40,380 --> 00:00:42,360 the community science side of all of this, 14 00:00:42,360 --> 00:00:44,520 I just wanna kind of justify 15 00:00:44,520 --> 00:00:46,260 why so many of us spend 16 00:00:46,260 --> 00:00:48,390 a lot of our time studying mercury. 17 00:00:48,390 --> 00:00:50,730 And just in case you don't know, 18 00:00:50,730 --> 00:00:53,850 it is ranked third on the US ATSDR 19 00:00:53,850 --> 00:00:56,790 priority list of contaminants in the US. 20 00:00:56,790 --> 00:00:59,070 It's a toxin that actually affects humans 21 00:00:59,070 --> 00:01:00,960 and wildlife at low levels, 22 00:01:00,960 --> 00:01:03,900 not just at acute exposures. 23 00:01:03,900 --> 00:01:05,160 Pregnant women, children, 24 00:01:05,160 --> 00:01:09,090 and seafood consumers are most at risk, 25 00:01:09,090 --> 00:01:10,260 because really, 26 00:01:10,260 --> 00:01:14,220 our exposure is mostly through consumption of fish; 27 00:01:14,220 --> 00:01:18,810 and 80% of the fish consumption advisories in the US, 28 00:01:18,810 --> 00:01:22,620 which cover many different kinds of contaminants, 29 00:01:22,620 --> 00:01:24,750 80% are for mercury. 30 00:01:24,750 --> 00:01:25,800 And to the right, 31 00:01:25,800 --> 00:01:29,850 you can see the "Alice in Wonderland" image 32 00:01:29,850 --> 00:01:34,110 because that was the exposure of the Mad Hatters 33 00:01:34,110 --> 00:01:36,750 were actually causing them to look mad 34 00:01:36,750 --> 00:01:40,020 from neurotoxicity from mercury, 35 00:01:40,020 --> 00:01:42,990 and the reason that we worry about mercury in fish 36 00:01:42,990 --> 00:01:44,398 is because it bio magnifies 37 00:01:44,398 --> 00:01:48,030 in that lower cartoon, you can see. 38 00:01:48,030 --> 00:01:51,780 It bio magnifies from mercury in water, 39 00:01:51,780 --> 00:01:53,550 which is almost undetectable, 40 00:01:53,550 --> 00:01:56,610 to very high levels in predatory fish. 41 00:01:56,610 --> 00:01:57,633 Next slide please. 42 00:02:00,870 --> 00:02:03,720 So in addition to effects on humans, 43 00:02:03,720 --> 00:02:06,720 we also know that there are exposures, 44 00:02:06,720 --> 00:02:10,020 important exposures and effects of wildlife, 45 00:02:10,020 --> 00:02:12,600 particularly obligate piscivores. 46 00:02:12,600 --> 00:02:17,600 And our very beloved common loon 47 00:02:17,615 --> 00:02:19,620 has been studied extensively 48 00:02:19,620 --> 00:02:21,960 by my colleague Dave Evers and his group, 49 00:02:21,960 --> 00:02:25,440 and they have found that even in the common loon, 50 00:02:25,440 --> 00:02:30,440 there are been detected aberrant incubation behaviors, 51 00:02:30,660 --> 00:02:34,557 lethargy, changes in wing asymmetry, 52 00:02:35,910 --> 00:02:38,700 and body burdens that are related 53 00:02:38,700 --> 00:02:43,380 to reduced numbers of fledged chicks. 54 00:02:43,380 --> 00:02:46,110 So we know that there are, 55 00:02:46,110 --> 00:02:47,910 from our research in general, 56 00:02:47,910 --> 00:02:51,150 that there are detrimental effects 57 00:02:51,150 --> 00:02:53,550 on populations of wildlife. 58 00:02:53,550 --> 00:02:55,173 Next slide please. 59 00:02:56,730 --> 00:02:58,050 So for those of you who don't 60 00:02:58,050 --> 00:03:00,750 spend all your time thinking about the mercury cycle, 61 00:03:00,750 --> 00:03:04,110 I just wanted to give you all a little background 62 00:03:04,110 --> 00:03:07,980 on where it comes from and where it goes, and what it is. 63 00:03:07,980 --> 00:03:10,050 So when we talk about mercury, 64 00:03:10,050 --> 00:03:13,830 we're generally talking about two main forms: 65 00:03:13,830 --> 00:03:16,560 inorganic mercury and organic mercury. 66 00:03:16,560 --> 00:03:20,070 And in organic mercury, we call methyl mercury, 67 00:03:20,070 --> 00:03:23,730 is the toxic and most bioavailable form of mercury, 68 00:03:23,730 --> 00:03:26,790 but it is not the form that is 69 00:03:26,790 --> 00:03:29,490 emitted and transported in the environment. 70 00:03:29,490 --> 00:03:30,652 In the environment, 71 00:03:30,652 --> 00:03:35,652 the two forms of inorganic mercury are elemental. 72 00:03:36,180 --> 00:03:38,130 And since I can't really point to things, 73 00:03:38,130 --> 00:03:41,160 you can look up in the sky, there's an HG0, 74 00:03:41,160 --> 00:03:45,330 the atmospheric form is mostly HG0, elemental mercury. 75 00:03:45,330 --> 00:03:46,770 And then if you look down 76 00:03:46,770 --> 00:03:50,993 toward where the lake is and the stream, 77 00:03:50,993 --> 00:03:54,510 we have HG2 plus, which is oxidized mercury. 78 00:03:54,510 --> 00:03:57,150 And that's the dominant form in water. 79 00:03:57,150 --> 00:03:59,460 It isn't until that oxidized mercury 80 00:03:59,460 --> 00:04:02,730 gets into the water and into areas 81 00:04:02,730 --> 00:04:04,770 that are relatively anoxic, 82 00:04:04,770 --> 00:04:06,990 that that inorganic mercury, 83 00:04:06,990 --> 00:04:09,450 the HG2+ gets methylated 84 00:04:09,450 --> 00:04:11,820 and turned into methyl mercury. 85 00:04:11,820 --> 00:04:14,040 And if you look at the graph on the bottom, 86 00:04:14,040 --> 00:04:16,980 or at least the bioaccumulation factors, 87 00:04:16,980 --> 00:04:21,570 you can see that from one x in water 88 00:04:21,570 --> 00:04:25,620 it goes to 10,000 x in phytoplankton. 89 00:04:25,620 --> 00:04:28,290 So that's a big step of bioaccumulation, 90 00:04:28,290 --> 00:04:29,730 from water to phytoplankton. 91 00:04:29,730 --> 00:04:33,780 And then it just keeps on going up beyond that, 92 00:04:33,780 --> 00:04:37,785 so that the amount that in the far right, in loons, 93 00:04:37,785 --> 00:04:42,785 is 10 million times the concentration that was in water 94 00:04:42,870 --> 00:04:46,500 because of bioaccumulation and bio magnification. 95 00:04:46,500 --> 00:04:47,553 Next slide please. 96 00:04:49,920 --> 00:04:54,270 So dragonflies are what we are using 97 00:04:54,270 --> 00:04:58,470 as a bio indicator of mercury exposure 98 00:04:58,470 --> 00:05:00,780 in our community science. 99 00:05:00,780 --> 00:05:03,360 And this is because dragonflies 100 00:05:03,360 --> 00:05:07,530 occupy a diverse range of freshwater habitats. 101 00:05:07,530 --> 00:05:11,460 They have site fidelity, so that when you find a dragonfly, 102 00:05:11,460 --> 00:05:14,160 and I'm talking about the larvae, 103 00:05:14,160 --> 00:05:17,550 they really represent where you find them. 104 00:05:17,550 --> 00:05:22,320 And so, most of you are probably familiar 105 00:05:22,320 --> 00:05:25,980 with the adults that we see around, 106 00:05:25,980 --> 00:05:28,650 especially in our region, 107 00:05:28,650 --> 00:05:32,790 we see them all over around aquatic habitats. 108 00:05:32,790 --> 00:05:34,410 But as you see on the left, 109 00:05:34,410 --> 00:05:36,240 the lifecycle of the dragonfly, 110 00:05:36,240 --> 00:05:41,240 those adults actually lay eggs on or in water bodies 111 00:05:41,340 --> 00:05:45,003 and then those eggs hatch into larvae, 112 00:05:46,433 --> 00:05:48,660 which is like number three to four, 113 00:05:48,660 --> 00:05:52,200 which can spend about two to three years 114 00:05:52,200 --> 00:05:56,850 in that environment, in that stage of life. 115 00:05:56,850 --> 00:06:00,030 And then later they then molt 116 00:06:00,030 --> 00:06:05,030 and the adults emerge from that larval stage. 117 00:06:05,550 --> 00:06:07,440 So what we are studying, 118 00:06:07,440 --> 00:06:09,090 are using as bio indicators, 119 00:06:09,090 --> 00:06:11,820 are dragonflies in their larval phase. 120 00:06:11,820 --> 00:06:13,590 And you can see on the right, 121 00:06:13,590 --> 00:06:14,910 in the bottom right corner, 122 00:06:14,910 --> 00:06:16,350 you can see these are ones that have been 123 00:06:16,350 --> 00:06:18,660 collected out of some of the habitats 124 00:06:18,660 --> 00:06:21,660 from which our community scientists 125 00:06:21,660 --> 00:06:25,470 have been collecting and measuring 126 00:06:25,470 --> 00:06:27,360 and identifying the species, 127 00:06:27,360 --> 00:06:28,920 or at least the families. 128 00:06:28,920 --> 00:06:32,100 Next slide please. 129 00:06:32,100 --> 00:06:34,530 So all around the country, 130 00:06:34,530 --> 00:06:36,360 this is being done and I'll talk about 131 00:06:36,360 --> 00:06:38,610 the national program in a moment. 132 00:06:38,610 --> 00:06:41,490 But what we see, as you might imagine, 133 00:06:41,490 --> 00:06:43,260 you might ask, well you know, 134 00:06:43,260 --> 00:06:46,800 are there the same species all around the country? 135 00:06:46,800 --> 00:06:47,790 And of course not. 136 00:06:47,790 --> 00:06:51,640 And in fact, there are seven different families 137 00:06:53,070 --> 00:06:56,040 that we pretty much identify; 138 00:06:56,040 --> 00:06:59,910 but really, four of them are what have been 139 00:06:59,910 --> 00:07:04,320 focused on in the Dragonfly Mercury project. 140 00:07:04,320 --> 00:07:06,120 So you can see on the left, 141 00:07:06,120 --> 00:07:08,880 there are all of these regressions 142 00:07:08,880 --> 00:07:11,400 that show the relationship between 143 00:07:11,400 --> 00:07:15,900 what we are calling the Aeschnid Total Mercury, 144 00:07:15,900 --> 00:07:18,120 which is on the Y axis, 145 00:07:18,120 --> 00:07:20,460 and then whatever other family 146 00:07:20,460 --> 00:07:22,110 that is shown in the four panels, 147 00:07:22,110 --> 00:07:24,180 the dragonfly larvae, total mercury. 148 00:07:24,180 --> 00:07:27,990 And what you can see from that is that Aeschnids, 149 00:07:27,990 --> 00:07:29,613 which is one of the families, 150 00:07:31,097 --> 00:07:32,610 the Aeschnids concentrations 151 00:07:32,610 --> 00:07:36,810 are very correlated with the ones 152 00:07:36,810 --> 00:07:41,130 that are in these other families of dragonflies. 153 00:07:41,130 --> 00:07:44,853 And so by having that very linear relationship, 154 00:07:46,170 --> 00:07:47,909 those of us who are actually 155 00:07:47,909 --> 00:07:49,860 looking at national patterns, 156 00:07:49,860 --> 00:07:53,551 are able to convert the concentrations 157 00:07:53,551 --> 00:07:56,460 that are found in these other families 158 00:07:56,460 --> 00:07:58,950 into an Aeschnid equivalent. 159 00:07:58,950 --> 00:08:00,963 And you can see on the bottom graph, 160 00:08:02,076 --> 00:08:06,540 the Aeschnids actually are the highest in concentrations, 161 00:08:06,540 --> 00:08:10,170 compared to the other families of dragonflies. 162 00:08:10,170 --> 00:08:12,450 But it's this Aeschnid equivalent 163 00:08:12,450 --> 00:08:15,930 that allows us to then compare across sites, 164 00:08:15,930 --> 00:08:18,930 using the data that has been generated 165 00:08:18,930 --> 00:08:21,720 in some of the sites where they collected 166 00:08:21,720 --> 00:08:25,920 each Aeschnids and at least one of the other families. 167 00:08:25,920 --> 00:08:28,140 And you can see some of them on the right, 168 00:08:28,140 --> 00:08:29,100 that's what they look like 169 00:08:29,100 --> 00:08:30,684 when they're in their larval phase. 170 00:08:30,684 --> 00:08:32,073 Next slide please. 171 00:08:34,260 --> 00:08:35,850 So, I'm first gonna just talk 172 00:08:35,850 --> 00:08:37,890 about the Dragonfly Mercury project, 173 00:08:37,890 --> 00:08:40,800 which is one a project, 174 00:08:40,800 --> 00:08:42,902 it's a citizen science framework 175 00:08:42,902 --> 00:08:45,314 for monitoring mercury pollution in the US. 176 00:08:45,314 --> 00:08:50,314 And it's really conducted by the National Park Service, 177 00:08:51,180 --> 00:08:53,340 so we have collaborators there, 178 00:08:53,340 --> 00:08:57,840 and very much organized in terms of the data 179 00:08:57,840 --> 00:09:00,150 and receiving the samples and everything, 180 00:09:00,150 --> 00:09:02,580 by the US Geological Survey. 181 00:09:02,580 --> 00:09:04,953 So, next slide please? 182 00:09:07,080 --> 00:09:09,316 So this map just shows you 183 00:09:09,316 --> 00:09:13,167 the National Dragonfly Mercury Project, 184 00:09:13,167 --> 00:09:18,150 which has been going from 2009 to 2019. 185 00:09:18,150 --> 00:09:20,490 And you can see all of the circles 186 00:09:20,490 --> 00:09:23,400 are national parks all around the country, 187 00:09:23,400 --> 00:09:26,850 in which dragonflies have been collected 188 00:09:26,850 --> 00:09:29,044 by community scientists 189 00:09:29,044 --> 00:09:32,010 who are basically visiting those parks. 190 00:09:32,010 --> 00:09:36,720 And then they go out with trained park service rangers 191 00:09:36,720 --> 00:09:39,990 and they collect and learn about this project 192 00:09:39,990 --> 00:09:42,660 and they help to collect the samples. 193 00:09:42,660 --> 00:09:44,730 There's also a number of samples 194 00:09:44,730 --> 00:09:48,693 that are coming from non-National Parks service sites, 195 00:09:49,740 --> 00:09:51,630 but what you can also see from this 196 00:09:51,630 --> 00:09:56,070 is the coloration is an indication 197 00:09:56,070 --> 00:09:58,650 of Mercury deposition in the US. 198 00:09:58,650 --> 00:10:00,330 And what that shows is, 199 00:10:00,330 --> 00:10:03,600 the more yellow-red color shows 200 00:10:03,600 --> 00:10:05,940 higher deposition of mercury in the US 201 00:10:05,940 --> 00:10:09,180 and the blue-green is lower deposition. 202 00:10:09,180 --> 00:10:10,530 And you can see that, actually, 203 00:10:10,530 --> 00:10:12,640 the highest deposition is around 204 00:10:13,680 --> 00:10:17,010 the Midwest and the Gulf of Mexico, 205 00:10:17,010 --> 00:10:20,880 and also up in some of the mountainous areas 206 00:10:20,880 --> 00:10:23,309 in the Pacific Northwest. 207 00:10:23,309 --> 00:10:26,700 But, that said, we in the Northeast 208 00:10:26,700 --> 00:10:29,595 have also received a lot of mercury emissions 209 00:10:29,595 --> 00:10:33,093 and deposition from the Midwest. 210 00:10:34,734 --> 00:10:37,740 And also in the northeast, where we are, 211 00:10:37,740 --> 00:10:41,550 we have some of the more mercury sensitive habitats; 212 00:10:41,550 --> 00:10:43,230 in other words areas where 213 00:10:43,230 --> 00:10:45,720 Mercury gets methylated more readily 214 00:10:45,720 --> 00:10:49,860 and taken up by our ecosystems. 215 00:10:49,860 --> 00:10:51,003 Next slide please. 216 00:10:52,950 --> 00:10:56,070 So the national scale program 217 00:10:56,070 --> 00:10:59,580 has been written up kind of recently, in 2020, 218 00:10:59,580 --> 00:11:02,850 by Collin Eagles-Smith at the US Geological Survey 219 00:11:02,850 --> 00:11:05,340 and a whole bunch of our colleagues. 220 00:11:05,340 --> 00:11:10,340 And this study was quite a massive effort, 221 00:11:10,920 --> 00:11:12,990 to take all of the data 222 00:11:12,990 --> 00:11:17,990 from what was collected over that period of time, 223 00:11:18,660 --> 00:11:22,230 from 2009 actually to 2018 224 00:11:22,230 --> 00:11:24,870 at 457 unique locations, 225 00:11:24,870 --> 00:11:28,737 across a hundred national park service units. 226 00:11:28,737 --> 00:11:33,737 And it really involved more than 4,000 volunteers, 227 00:11:34,170 --> 00:11:36,180 which is pretty remarkable. 228 00:11:36,180 --> 00:11:38,280 And so I'm just gonna show you 229 00:11:38,280 --> 00:11:42,630 some of the findings from this study. 230 00:11:42,630 --> 00:11:44,370 Next slide please. 231 00:11:44,370 --> 00:11:45,900 [Moderator] I'm just gonna interrupt here, Celia, 232 00:11:45,900 --> 00:11:48,690 we're really mandated to stay on track time-wise, 233 00:11:48,690 --> 00:11:51,630 so we just have three minutes left. 234 00:11:51,630 --> 00:11:54,240 [Celia] Oh, because we started like, 235 00:11:54,240 --> 00:11:55,650 -[Moderator] Yeah. -[Celia] five minutes late, 236 00:11:55,650 --> 00:11:57,570 so I will have to, okay, 237 00:11:57,570 --> 00:12:00,903 well why don't I just skip these slides then? 238 00:12:01,917 --> 00:12:06,420 I would suggest you go to the Eagles-Smith paper 239 00:12:06,420 --> 00:12:08,340 in Environmental Science and Technology, 240 00:12:08,340 --> 00:12:10,395 or if you have any questions just let me know. 241 00:12:10,395 --> 00:12:15,395 And why don't we go straight on to the Dartmouth, 242 00:12:16,050 --> 00:12:17,733 so I think it's slide 13. 243 00:12:18,870 --> 00:12:19,703 Yeah. 244 00:12:20,610 --> 00:12:21,510 [Moderator] This one? 245 00:12:21,510 --> 00:12:23,700 [Celia] No, I'm gonna skip these 246 00:12:23,700 --> 00:12:25,713 because there's so little time. 247 00:12:27,150 --> 00:12:28,410 Yeah, go ahead. That one. 248 00:12:28,410 --> 00:12:32,399 Okay, so the Dartmouth Dragonfly Mercury Project 249 00:12:32,399 --> 00:12:37,399 ran from 2010 to just till last year. 250 00:12:38,250 --> 00:12:41,580 And we focused our efforts on taking this program, 251 00:12:41,580 --> 00:12:43,590 which was developed at the University of Maine, 252 00:12:43,590 --> 00:12:45,660 to New Hampshire and Vermont high schools. 253 00:12:45,660 --> 00:12:47,790 And so we collaborated with teachers, 254 00:12:47,790 --> 00:12:51,270 we took students out where they field sampled, 255 00:12:51,270 --> 00:12:53,370 the samples came to us, 256 00:12:53,370 --> 00:12:57,870 and we then also in the last two years, 257 00:12:57,870 --> 00:13:00,090 got funding from FEMC 258 00:13:00,090 --> 00:13:03,030 to expand this particular project out 259 00:13:03,030 --> 00:13:06,990 to some of the national forests. 260 00:13:06,990 --> 00:13:08,163 So, next slide. 261 00:13:11,190 --> 00:13:13,803 So you can see that this is where, 262 00:13:14,812 --> 00:13:15,930 in the last couple years, 263 00:13:15,930 --> 00:13:20,220 our sites were inclusive of schools and national forests, 264 00:13:20,220 --> 00:13:21,510 Green Mountain National Forest, 265 00:13:21,510 --> 00:13:26,070 as well as the White Mountain National Forest. 266 00:13:26,070 --> 00:13:30,810 And we included our schools in that, so keep going. 267 00:13:30,810 --> 00:13:31,643 Next slide. 268 00:13:33,900 --> 00:13:37,170 All of these samples from schools and from national forests 269 00:13:37,170 --> 00:13:39,300 come back to my lab here 270 00:13:39,300 --> 00:13:42,778 and they are re-identified for a taxonomy check. 271 00:13:42,778 --> 00:13:47,190 We run Mercury on a direct mercury analyzer 272 00:13:47,190 --> 00:13:48,810 and we do an inter calibration 273 00:13:48,810 --> 00:13:50,490 with the US Geological survey, 274 00:13:50,490 --> 00:13:53,670 so that the data can go into the national database. 275 00:13:53,670 --> 00:13:54,503 Next slide. 276 00:13:55,350 --> 00:13:57,190 And so this is just 277 00:13:58,380 --> 00:14:00,900 a figure showing some of the data, 278 00:14:00,900 --> 00:14:02,250 and I guess I don't have time 279 00:14:02,250 --> 00:14:03,540 to talk to you much about it, 280 00:14:03,540 --> 00:14:05,580 but we have, on the right side, 281 00:14:05,580 --> 00:14:09,690 data that came in from the National Forests 282 00:14:09,690 --> 00:14:11,220 and National Historical Parks, 283 00:14:11,220 --> 00:14:13,470 there is one site in the Green Mountain National Forest 284 00:14:13,470 --> 00:14:14,790 that's kind of high. 285 00:14:14,790 --> 00:14:16,920 And all the ones that have asterisks 286 00:14:16,920 --> 00:14:21,920 were collected by volunteers with our students 287 00:14:22,800 --> 00:14:25,080 and other volunteers. 288 00:14:25,080 --> 00:14:25,953 Next slide. 289 00:14:28,710 --> 00:14:32,070 Then we had a culminating symposium, 290 00:14:32,070 --> 00:14:34,080 with students coming to Dartmouth, 291 00:14:34,080 --> 00:14:38,190 and I think that was a really kind of seminal event 292 00:14:38,190 --> 00:14:39,330 for many of the students 293 00:14:39,330 --> 00:14:41,250 and they brought all their families. 294 00:14:41,250 --> 00:14:42,083 Next slide. 295 00:14:43,620 --> 00:14:47,344 So the last two examples of this 296 00:14:47,344 --> 00:14:51,090 are one that's in the Merrimack Watershed, 297 00:14:51,090 --> 00:14:53,040 which is run by Sarah Nelson, 298 00:14:53,040 --> 00:14:56,010 who is now at the Appalachian Mountain Club. 299 00:14:56,010 --> 00:14:59,216 And it is run with so many partners, 300 00:14:59,216 --> 00:15:01,350 as you can see on the left there. 301 00:15:01,350 --> 00:15:03,360 And we work with students, 302 00:15:03,360 --> 00:15:06,090 as well as park service, 303 00:15:06,090 --> 00:15:07,710 National Historic sites. 304 00:15:07,710 --> 00:15:09,596 And next slide. 305 00:15:09,596 --> 00:15:11,400 In this particular program, 306 00:15:11,400 --> 00:15:13,020 we're really able to reach 307 00:15:13,020 --> 00:15:14,550 a different kind of community, 308 00:15:14,550 --> 00:15:17,160 from what we were able to work with 309 00:15:17,160 --> 00:15:18,600 up in New Hampshire and Vermont. 310 00:15:18,600 --> 00:15:21,120 It's Lowell and Lawrence, Massachusetts, 311 00:15:21,120 --> 00:15:23,490 our environmental justice communities, 312 00:15:23,490 --> 00:15:25,380 and so we have a much more 313 00:15:25,380 --> 00:15:28,680 diverse population of students 314 00:15:28,680 --> 00:15:30,450 as well as community members 315 00:15:30,450 --> 00:15:34,560 who are involved in this particular project. 316 00:15:34,560 --> 00:15:37,020 And then, I think next slide? 317 00:15:37,020 --> 00:15:40,560 And then the last slide about the projects, 318 00:15:40,560 --> 00:15:44,790 is we've also just expanded in 23 to 24, 319 00:15:44,790 --> 00:15:47,040 up into the Lake Champlain watershed 320 00:15:47,040 --> 00:15:48,060 and we have been working 321 00:15:48,060 --> 00:15:51,600 with the Lake Champlain Watershed Alliance. 322 00:15:51,600 --> 00:15:56,160 And so that is taking this project 323 00:15:56,160 --> 00:15:59,940 to a new region of our region. 324 00:15:59,940 --> 00:16:03,660 And lastly, I must acknowledge, 325 00:16:03,660 --> 00:16:06,690 especially our collaborators, 326 00:16:06,690 --> 00:16:08,610 but also the funding sources 327 00:16:08,610 --> 00:16:12,330 which have been funding different parts 328 00:16:12,330 --> 00:16:15,690 of this overall regional program; 329 00:16:15,690 --> 00:16:18,780 including NIH and Wellborn Foundation, 330 00:16:18,780 --> 00:16:20,550 FEMC as I mentioned earlier, 331 00:16:20,550 --> 00:16:22,560 the US EPA, Parker Foundation, 332 00:16:22,560 --> 00:16:24,000 Lake Champlain Basin Program 333 00:16:24,000 --> 00:16:25,890 and Lake Champlain Sea Grant. 334 00:16:25,890 --> 00:16:28,413 So, I think I used up my time. 335 00:16:30,900 --> 00:16:32,700 And probably have no time for questions, 336 00:16:32,700 --> 00:16:36,123 but feel free to put them in a chat and I can respond. 337 00:16:36,990 --> 00:16:38,580 [Moderator] Yeah, we do have time for one question. 338 00:16:38,580 --> 00:16:39,420 People can leave too, 339 00:16:39,420 --> 00:16:41,913 but we can take one question if anybody has any. 340 00:16:42,810 --> 00:16:44,160 [Audience Member] How reliable do you find 341 00:16:44,160 --> 00:16:45,993 the data that students collect? 342 00:16:46,915 --> 00:16:48,900 [Celia] It's very reliable. 343 00:16:48,900 --> 00:16:53,900 We teach them clean hands, dirty hands technique. 344 00:16:54,270 --> 00:16:58,440 And because dragonflies have so much mercury in them, 345 00:16:58,440 --> 00:16:59,730 not so much, I should say, 346 00:16:59,730 --> 00:17:02,130 it's not like we're trying to sample water, 347 00:17:02,130 --> 00:17:03,630 which has very low levels; 348 00:17:03,630 --> 00:17:06,780 it's not so much of a contamination issue. 349 00:17:06,780 --> 00:17:09,630 And they wear gloves just like we do, 350 00:17:09,630 --> 00:17:12,993 and so the data are very robust. 351 00:17:14,157 --> 00:17:15,323 [Audience Member] Great, thank you.