1 00:00:02,640 --> 00:00:04,410 Thanks, everybody, for being here. 2 00:00:04,410 --> 00:00:06,390 I was worried with Tony Yamato, the rockstar, 3 00:00:06,390 --> 00:00:07,470 giving a talk across the hall 4 00:00:07,470 --> 00:00:09,840 I was gonna get nobody, so maybe that room's full. 5 00:00:09,840 --> 00:00:11,158 So thank you for coming. 6 00:00:11,158 --> 00:00:13,761 (audience laughs and chatters) 7 00:00:13,761 --> 00:00:16,620 So I'll start just by thanking all this list of co-authors 8 00:00:16,620 --> 00:00:18,930 and organizations that supported this work, 9 00:00:18,930 --> 00:00:21,930 and especially Schoodic Institute at Acadia National Park, 10 00:00:21,930 --> 00:00:24,363 which is the organization that I'm from. 11 00:00:25,860 --> 00:00:27,450 And so I'll get started by introducing you 12 00:00:27,450 --> 00:00:29,100 to my favorite plant. 13 00:00:29,100 --> 00:00:31,500 This plant's called Three-toothed Cinquefoil, 14 00:00:31,500 --> 00:00:32,760 and it's my favorite plant 15 00:00:32,760 --> 00:00:36,240 because it's a really good example of the types 16 00:00:36,240 --> 00:00:39,150 of management challenges that practitioners 17 00:00:39,150 --> 00:00:42,300 and managers are facing all around the world. 18 00:00:42,300 --> 00:00:44,520 And so at Acadia National Park, we're actively trying 19 00:00:44,520 --> 00:00:45,660 to restore this plant 20 00:00:45,660 --> 00:00:47,970 and other plants on the summit of Cadillac Mountain 21 00:00:47,970 --> 00:00:50,850 and other mountains in the park. 22 00:00:50,850 --> 00:00:53,520 And it's doing really well in those restorations now. 23 00:00:53,520 --> 00:00:55,380 In fact, it's the plant that's probably doing the best 24 00:00:55,380 --> 00:00:59,043 in those restorations now, but it has a really bleak future. 25 00:00:59,970 --> 00:01:03,210 So models predict that it could lose 98% 26 00:01:03,210 --> 00:01:04,920 of its distribution in Maine by the end 27 00:01:04,920 --> 00:01:07,500 of the century due primarily 28 00:01:07,500 --> 00:01:10,170 to increased maximum summer temperatures. 29 00:01:10,170 --> 00:01:13,170 And so we're left trying to figure out at Acadia, 30 00:01:13,170 --> 00:01:14,490 how can we ensure that the money 31 00:01:14,490 --> 00:01:17,520 that we're investing in this restoration of this plant today 32 00:01:17,520 --> 00:01:20,340 will continue to provide benefits in the future 33 00:01:20,340 --> 00:01:21,450 as climates change 34 00:01:21,450 --> 00:01:24,474 and locations become unsuitable for this species. 35 00:01:24,474 --> 00:01:27,840 And as I said, that's a challenge that practitioners 36 00:01:27,840 --> 00:01:29,940 and natural resource managers are facing 37 00:01:29,940 --> 00:01:31,371 all around the world. 38 00:01:31,371 --> 00:01:33,870 And practitioners aren't without options. 39 00:01:33,870 --> 00:01:35,040 That's the good thing, right? 40 00:01:35,040 --> 00:01:37,860 There's dozens of options that have been proposed out there 41 00:01:37,860 --> 00:01:39,993 and all the different literature. 42 00:01:40,950 --> 00:01:44,640 And in fact, a review that was published in 2019 suggests 43 00:01:44,640 --> 00:01:46,710 that there's 23 different categories, 44 00:01:46,710 --> 00:01:48,000 so not 23 different options, 45 00:01:48,000 --> 00:01:51,450 but 23 different categories of climate adaptation options 46 00:01:51,450 --> 00:01:54,000 that have been proposed out there in the literature. 47 00:01:54,000 --> 00:01:57,690 But the problem is, almost none of those have been tested. 48 00:01:57,690 --> 00:02:02,160 And so that same review by Susan Prober showed 49 00:02:02,160 --> 00:02:04,650 that 84% of those strategies 50 00:02:04,650 --> 00:02:07,350 that have been proposed in the literature have no empirical 51 00:02:07,350 --> 00:02:09,750 or on-the-ground support to, you know, 52 00:02:09,750 --> 00:02:12,000 support their use in the field. 53 00:02:12,000 --> 00:02:14,880 And a review that came out just I think like last month, 54 00:02:14,880 --> 00:02:16,410 that, you know, supports that idea. 55 00:02:16,410 --> 00:02:17,790 And so, you know, this isn't something 56 00:02:17,790 --> 00:02:19,830 that was just back in 2019. 57 00:02:19,830 --> 00:02:21,270 It's still here now. 58 00:02:21,270 --> 00:02:23,790 Most climate change adaptation strategies 59 00:02:23,790 --> 00:02:25,740 haven't been tested. 60 00:02:25,740 --> 00:02:28,500 And so I'll give you a few take homes from this talk. 61 00:02:28,500 --> 00:02:29,790 This is the first one. 62 00:02:29,790 --> 00:02:31,680 We need more on-the-ground tests 63 00:02:31,680 --> 00:02:33,720 of our climate change adaptation strategies, 64 00:02:33,720 --> 00:02:35,910 because many of these things 65 00:02:35,910 --> 00:02:37,200 that are being proposed out there 66 00:02:37,200 --> 00:02:39,870 in the literature, they're novel, 67 00:02:39,870 --> 00:02:42,600 and so we don't necessarily know if they'll have 68 00:02:42,600 --> 00:02:44,490 the intended impact on ecosystems. 69 00:02:44,490 --> 00:02:47,853 So we need more tests of these adaptation strategies. 70 00:02:49,110 --> 00:02:51,780 But testing climate change adaptation strategies comes 71 00:02:51,780 --> 00:02:52,800 with a trade-off, right? 72 00:02:52,800 --> 00:02:56,040 On the one hand, if we wanna stop the worst impacts 73 00:02:56,040 --> 00:02:57,300 of climate change, then we need 74 00:02:57,300 --> 00:02:59,280 to be getting these things on the ground yesterday, 75 00:02:59,280 --> 00:03:01,230 if not now, right? 76 00:03:01,230 --> 00:03:04,080 But on the other hand, if we wanna test these things, 77 00:03:04,080 --> 00:03:05,640 those tests take time, right? 78 00:03:05,640 --> 00:03:06,720 Ecology is slow. 79 00:03:06,720 --> 00:03:07,770 Things happen slowly. 80 00:03:07,770 --> 00:03:09,750 And so these things could take decades. 81 00:03:09,750 --> 00:03:12,150 And so, how do we overcome this trade-off 82 00:03:12,150 --> 00:03:13,620 between the urgency to adapt 83 00:03:13,620 --> 00:03:15,630 and the time it it takes to learn? 84 00:03:15,630 --> 00:03:17,640 Well, a lot of people that are familiar 85 00:03:17,640 --> 00:03:20,850 with adaptive management will think that's how we do this. 86 00:03:20,850 --> 00:03:22,950 We do this with adaptive management, 87 00:03:22,950 --> 00:03:24,960 and in the context of climate change, 88 00:03:24,960 --> 00:03:28,461 you know, this is how we often think of adaptive management. 89 00:03:28,461 --> 00:03:30,330 We implement a single strategy, 90 00:03:30,330 --> 00:03:32,760 we monitor that strategy over time, 91 00:03:32,760 --> 00:03:35,910 and then we evaluate if that strategy worked or not. 92 00:03:35,910 --> 00:03:37,440 If it doesn't work, then we just go back 93 00:03:37,440 --> 00:03:38,880 to the drawing board. 94 00:03:38,880 --> 00:03:42,390 And although this is useful in some circumstances, 95 00:03:42,390 --> 00:03:45,570 I'd suggest that it's often too slow, right? 96 00:03:45,570 --> 00:03:48,240 And so, as I said, you know, implementing a strategy, 97 00:03:48,240 --> 00:03:50,070 we could be decades before we get here 98 00:03:50,070 --> 00:03:51,390 to find out if that works. 99 00:03:51,390 --> 00:03:52,290 And then if it doesn't work, 100 00:03:52,290 --> 00:03:54,540 we're back to the drawing board, right? 101 00:03:54,540 --> 00:03:57,030 And then the other problem with this approach, right, 102 00:03:57,030 --> 00:04:00,330 is that we're not comparing this strategy 103 00:04:00,330 --> 00:04:01,770 to any other strategy. 104 00:04:01,770 --> 00:04:03,750 So we don't know if this is the best strategy 105 00:04:03,750 --> 00:04:04,620 that we implemented here. 106 00:04:04,620 --> 00:04:05,880 We don't even know if this is better 107 00:04:05,880 --> 00:04:07,410 than what we were doing before, right? 108 00:04:07,410 --> 00:04:11,460 We just know where it works or doesn't work at the end. 109 00:04:11,460 --> 00:04:13,440 And so because of this, we think we need kind 110 00:04:13,440 --> 00:04:15,060 of a better way to be testing 111 00:04:15,060 --> 00:04:17,210 our climate adaptation strategies. 112 00:04:17,210 --> 00:04:20,220 So what we're proposing is that rather than just implement 113 00:04:20,220 --> 00:04:23,460 a single strategy at this first phase, 114 00:04:23,460 --> 00:04:24,420 we should be implementing 115 00:04:24,420 --> 00:04:27,360 multiple strategies simultaneously. 116 00:04:27,360 --> 00:04:30,090 And we think that this will help us compare strategies 117 00:04:30,090 --> 00:04:34,110 including, you know, non-climate-adapted controls. 118 00:04:34,110 --> 00:04:36,300 And hopefully at the end of this process, 119 00:04:36,300 --> 00:04:38,640 we're in a much better spot from learning, right? 120 00:04:38,640 --> 00:04:42,060 We might know a better direction to go in the future. 121 00:04:42,060 --> 00:04:44,287 And then the key thing I wanna point out is that, 122 00:04:44,287 --> 00:04:47,460 you know, we shouldn't just do this willy-nilly, right? 123 00:04:47,460 --> 00:04:49,890 We should use a rigorous experimental design to do this. 124 00:04:49,890 --> 00:04:52,110 So when possible, it's not always possible, 125 00:04:52,110 --> 00:04:54,960 but when possible, we should use replication, 126 00:04:54,960 --> 00:04:57,720 randomization, and controls. 127 00:04:57,720 --> 00:05:00,180 And so, the second take home message from this talk 128 00:05:00,180 --> 00:05:03,330 is that I think if we can, you know, we can't always, 129 00:05:03,330 --> 00:05:06,840 but if we can implement multiple adaptation strategies 130 00:05:06,840 --> 00:05:10,350 simultaneously, that should significantly increase our rate 131 00:05:10,350 --> 00:05:13,560 of learning about which of these strategies work 132 00:05:13,560 --> 00:05:14,710 and where do they work. 133 00:05:16,140 --> 00:05:19,830 And so I'll give you a few examples of how we're doing this 134 00:05:19,830 --> 00:05:22,158 at Acadia National Park, mostly to show you that, 135 00:05:22,158 --> 00:05:24,090 you know, this is possible to do. 136 00:05:24,090 --> 00:05:25,200 And so I already introduced you 137 00:05:25,200 --> 00:05:27,390 to my favorite plant, Three-toothed Cinquefoil. 138 00:05:27,390 --> 00:05:29,910 I told you it's doing really well in our restorations today, 139 00:05:29,910 --> 00:05:31,890 and it has this really bleak future. 140 00:05:31,890 --> 00:05:33,390 And so we're trying to figure out, you know, 141 00:05:33,390 --> 00:05:35,495 how do we adapt to climate change? 142 00:05:35,495 --> 00:05:37,410 And there's really two strategies 143 00:05:37,410 --> 00:05:39,180 that are commonly proposed in the literature 144 00:05:39,180 --> 00:05:42,030 for adapting populations to climate change. 145 00:05:42,030 --> 00:05:44,040 One is to increase genetic diversity, 146 00:05:44,040 --> 00:05:46,350 and we can do that by collecting individuals 147 00:05:46,350 --> 00:05:49,260 from different locations, planting those individuals 148 00:05:49,260 --> 00:05:51,750 of cinquefoil at our restoration site. 149 00:05:51,750 --> 00:05:54,660 And then a more specific case of this is, you know, 150 00:05:54,660 --> 00:05:57,780 adding pre-adapted genotypes, or assisted gene flow, 151 00:05:57,780 --> 00:06:00,210 where we collect individuals specifically 152 00:06:00,210 --> 00:06:02,460 from warmer locations and we plant those 153 00:06:02,460 --> 00:06:04,380 at our restoration sites. 154 00:06:04,380 --> 00:06:06,330 And so these strategies are being implemented 155 00:06:06,330 --> 00:06:07,710 around the world already, 156 00:06:07,710 --> 00:06:10,650 but like most adaptation strategies, there's not a lot 157 00:06:10,650 --> 00:06:15,090 of evidence out there to support that they work effectively. 158 00:06:15,090 --> 00:06:19,050 And so in 2021, I set out to kind of test this, 159 00:06:19,050 --> 00:06:21,300 both of these strategies, increasing diversity 160 00:06:21,300 --> 00:06:23,970 and adding pre-adapted individuals. 161 00:06:23,970 --> 00:06:27,630 We collected cinquefoil individuals from 31 locations 162 00:06:27,630 --> 00:06:30,930 throughout New England, ranging from down here near Boston 163 00:06:30,930 --> 00:06:32,910 to up here in Central Maine, 164 00:06:32,910 --> 00:06:35,610 and we brought all those plants to Acadia National Park, 165 00:06:35,610 --> 00:06:38,460 and we planted them in an experimental restoration site. 166 00:06:38,460 --> 00:06:40,710 So this site looks identical 167 00:06:40,710 --> 00:06:43,230 to our other restoration sites on the summit. 168 00:06:43,230 --> 00:06:45,060 The only difference is we've partitioned it 169 00:06:45,060 --> 00:06:48,210 into these 15 different units, 170 00:06:48,210 --> 00:06:50,610 and then we randomly assigned a treatment 171 00:06:50,610 --> 00:06:51,990 to each one of those units. 172 00:06:51,990 --> 00:06:53,910 And so we have a management treatment 173 00:06:53,910 --> 00:06:56,490 that's kind of a non-climate-adapted control 174 00:06:56,490 --> 00:06:58,770 where we plant just local genotypes. 175 00:06:58,770 --> 00:07:00,600 That's what we do in our restorations now. 176 00:07:00,600 --> 00:07:03,210 So that's comparing what we do now. 177 00:07:03,210 --> 00:07:04,140 And we have these treatments 178 00:07:04,140 --> 00:07:05,790 where we increase genetic diversity 179 00:07:05,790 --> 00:07:07,140 and we have treatments where we added 180 00:07:07,140 --> 00:07:11,070 warm adapted genotypes, and then we've got replicates 181 00:07:11,070 --> 00:07:12,840 of each one of those treatments, 182 00:07:12,840 --> 00:07:14,670 and those are independent replicates 183 00:07:14,670 --> 00:07:16,650 using different source collections. 184 00:07:16,650 --> 00:07:20,730 So we've got this replication randomization and control. 185 00:07:20,730 --> 00:07:22,860 And there's two things I really wanna point out 186 00:07:22,860 --> 00:07:24,750 about this experiment. 187 00:07:24,750 --> 00:07:26,460 And the first is that, you know, 188 00:07:26,460 --> 00:07:27,960 this is not a big experiment. 189 00:07:27,960 --> 00:07:29,100 You know, it's the size 190 00:07:29,100 --> 00:07:30,480 of this space right here in this room. 191 00:07:30,480 --> 00:07:34,680 And I present this for that reason, right? 192 00:07:34,680 --> 00:07:37,740 We don't have to do a multimillion-dollar huge experiment 193 00:07:37,740 --> 00:07:38,670 to test these things. 194 00:07:38,670 --> 00:07:40,620 We can do it on a small scale, 195 00:07:40,620 --> 00:07:42,960 especially with this types of treatments. 196 00:07:42,960 --> 00:07:45,360 And then I'll just note that this is actually part 197 00:07:45,360 --> 00:07:46,470 of a much bigger study 198 00:07:46,470 --> 00:07:49,440 where we have common gardens across an elevational gradient 199 00:07:49,440 --> 00:07:51,300 so we can understand how these treatments 200 00:07:51,300 --> 00:07:53,010 respond in different temperatures. 201 00:07:53,010 --> 00:07:55,113 So that increases our ability to learn. 202 00:07:57,055 --> 00:07:59,400 And so there's the second example I wanna talk about 203 00:07:59,400 --> 00:08:01,680 is happening in two of the biggest wetlands 204 00:08:01,680 --> 00:08:03,180 in Acadia National Park, 205 00:08:03,180 --> 00:08:06,210 which are Great Meadow and Bass Harbor Marsh. 206 00:08:06,210 --> 00:08:09,150 And both of these sites are plagued by the same problem, 207 00:08:09,150 --> 00:08:12,000 which is this invasive shrub, glossy buckthorn. 208 00:08:12,000 --> 00:08:14,820 So the National Park Service spends a lot 209 00:08:14,820 --> 00:08:16,680 of time every year trying 210 00:08:16,680 --> 00:08:19,530 to remove glossy buckthorn from sites, 211 00:08:19,530 --> 00:08:22,020 but unfortunately, it commonly reinvades sites 212 00:08:22,020 --> 00:08:23,460 after just a couple of years. 213 00:08:23,460 --> 00:08:28,020 So for example, this is a picture of a site that was managed 214 00:08:28,020 --> 00:08:31,440 two years prior to when I took this picture, 215 00:08:31,440 --> 00:08:33,810 and almost every single green leaf in this picture 216 00:08:33,810 --> 00:08:35,580 is a glossy buckthorn seedling. 217 00:08:35,580 --> 00:08:38,880 So it comes back and it comes back with a vengeance. 218 00:08:38,880 --> 00:08:41,910 And the park keeps up with this problem now by going 219 00:08:41,910 --> 00:08:44,430 to these sites every three to five years 220 00:08:44,430 --> 00:08:47,340 and does management at the sites. 221 00:08:47,340 --> 00:08:48,810 But we're worried that climate change 222 00:08:48,810 --> 00:08:52,170 is gonna make this problem kind of unable to be managed. 223 00:08:52,170 --> 00:08:54,450 And there's a few reasons for that. 224 00:08:54,450 --> 00:08:56,490 There's a couple reasons why 225 00:08:56,490 --> 00:08:58,110 wetlands could be getting a little drier, 226 00:08:58,110 --> 00:09:00,837 which could favor glossy buckthorn in some spots. 227 00:09:00,837 --> 00:09:02,880 And then also we're worried that glossy buckthorn 228 00:09:02,880 --> 00:09:04,620 might be better able to take advantage 229 00:09:04,620 --> 00:09:06,030 of this longer growing season 230 00:09:06,030 --> 00:09:08,670 that we're already seeing at the park. 231 00:09:08,670 --> 00:09:09,990 And so to try to figure out 232 00:09:09,990 --> 00:09:12,360 how we can better do this management 233 00:09:12,360 --> 00:09:13,770 and hopefully be able 234 00:09:13,770 --> 00:09:16,920 to keep a handle on glossy buckthorn under climate change, 235 00:09:16,920 --> 00:09:20,760 we worked with the park to develop two different strategies 236 00:09:20,760 --> 00:09:22,440 in combination with their kind 237 00:09:22,440 --> 00:09:24,330 of removal only practice like they do now. 238 00:09:24,330 --> 00:09:25,920 So this is what they do now. 239 00:09:25,920 --> 00:09:27,810 This is a control. 240 00:09:27,810 --> 00:09:30,270 We also are now removing glossy buckthorn 241 00:09:30,270 --> 00:09:32,460 and then also planting graminoids. 242 00:09:32,460 --> 00:09:34,950 And the hope here is that those graminoids grow 243 00:09:34,950 --> 00:09:37,470 really quickly and then spread out over the site 244 00:09:37,470 --> 00:09:40,140 and out-compete glossy buckthorn seedlings. 245 00:09:40,140 --> 00:09:42,060 And then we're also removing glossy buckthorn 246 00:09:42,060 --> 00:09:43,890 and planting shrubs. 247 00:09:43,890 --> 00:09:46,230 And although those shrubs grow as quickly, 248 00:09:46,230 --> 00:09:48,173 hopefully they'll shade out glossy buckthorn 249 00:09:48,173 --> 00:09:51,660 after a while in some of these sites. 250 00:09:51,660 --> 00:09:54,060 And so we took these three treatments 251 00:09:54,060 --> 00:09:56,280 and we set up 15 different plots 252 00:09:56,280 --> 00:09:59,970 and both of these two marshes in Acadia National Park, 253 00:09:59,970 --> 00:10:01,860 and the plots look something like this. 254 00:10:01,860 --> 00:10:05,430 And so we first set up a deer fence. 255 00:10:05,430 --> 00:10:07,290 As we heard this morning, deer are a problem 256 00:10:07,290 --> 00:10:08,670 and they'll eat our native plants. 257 00:10:08,670 --> 00:10:11,400 And so we set up these deer fences, 258 00:10:11,400 --> 00:10:13,590 we then removed all the glossy buckthorn 259 00:10:13,590 --> 00:10:17,760 within the fence, and then we set up these four subplots 260 00:10:17,760 --> 00:10:18,960 within the plot. 261 00:10:18,960 --> 00:10:20,610 And they just represent our treatments. 262 00:10:20,610 --> 00:10:23,850 So we have the typical control, the removal only plot, 263 00:10:23,850 --> 00:10:26,340 we planted shrubs, we planted grasses, 264 00:10:26,340 --> 00:10:27,480 and then we've got this plot 265 00:10:27,480 --> 00:10:29,460 where our technicians love this. 266 00:10:29,460 --> 00:10:31,590 You dig a hole like you're gonna plant a shrub 267 00:10:31,590 --> 00:10:34,209 and you fill in the hole and don't actually plant a shrub. 268 00:10:34,209 --> 00:10:35,195 (audience laughing) 269 00:10:35,195 --> 00:10:37,350 And the reason for that is we're worried 270 00:10:37,350 --> 00:10:38,723 that the soil disturbance 271 00:10:38,723 --> 00:10:41,970 that you get from doing these native plantings 272 00:10:41,970 --> 00:10:44,370 could actually make the glossy buckthorn problem worse. 273 00:10:44,370 --> 00:10:47,297 And so we're testing that as well. 274 00:10:47,297 --> 00:10:48,990 And so this is a good example 275 00:10:48,990 --> 00:10:51,540 of kind of how we can do this on a regional scale. 276 00:10:51,540 --> 00:10:54,090 You know, this is across the park in two different wetlands 277 00:10:54,090 --> 00:10:56,580 and we get a little bit more robust difference then 278 00:10:56,580 --> 00:11:00,480 about which strategies are working and which ones aren't. 279 00:11:00,480 --> 00:11:04,200 And so hopefully these two examples give you an idea 280 00:11:04,200 --> 00:11:05,280 that this is possible. 281 00:11:05,280 --> 00:11:08,100 We can do this both at local, regional, 282 00:11:08,100 --> 00:11:09,813 and even bigger scales, 283 00:11:10,680 --> 00:11:13,320 and it should hopefully result in rapid learning. 284 00:11:13,320 --> 00:11:16,410 But there's other benefits to taking this approach. 285 00:11:16,410 --> 00:11:18,690 And this is the third take home message I want 286 00:11:18,690 --> 00:11:22,050 from this talk is that there's secondary benefits 287 00:11:22,050 --> 00:11:25,337 to taking this kind of experimental approach to management. 288 00:11:25,337 --> 00:11:27,360 And one of those is resilience 289 00:11:27,360 --> 00:11:28,950 through the portfolio effect. 290 00:11:28,950 --> 00:11:32,820 So let's say we just did what we would normally do, 291 00:11:32,820 --> 00:11:33,960 we just pick one approach, 292 00:11:33,960 --> 00:11:36,030 we implemented that on the landscape, 293 00:11:36,030 --> 00:11:37,890 and then we get a really heavy rain event 294 00:11:37,890 --> 00:11:40,710 like we're getting a lot now at Acadia National Park 295 00:11:40,710 --> 00:11:43,860 and the wetland floods and all those shrubs die. 296 00:11:43,860 --> 00:11:47,400 Then our entire restoration has failed at that site. 297 00:11:47,400 --> 00:11:49,830 But if we implement two strategies 298 00:11:49,830 --> 00:11:52,710 and we also plant graminoids, which are more resilient 299 00:11:52,710 --> 00:11:55,980 to flooding, and we get a big flood, then at least only half 300 00:11:55,980 --> 00:11:57,930 of our restorations fail, right? 301 00:11:57,930 --> 00:12:00,570 So we're hedging our bets against the uncertainties 302 00:12:00,570 --> 00:12:02,877 of climate by kind of doing multiple things. 303 00:12:02,877 --> 00:12:04,893 And so that's one of the advantages. 304 00:12:05,820 --> 00:12:07,320 The second advantage I wanna point out 305 00:12:07,320 --> 00:12:09,480 is that I really think these experiments, 306 00:12:09,480 --> 00:12:12,450 especially in a beautiful place like Acadia National Park, 307 00:12:12,450 --> 00:12:15,300 are great science and management communication tools. 308 00:12:15,300 --> 00:12:19,050 So for example, I had the opportunity a few years back 309 00:12:19,050 --> 00:12:22,650 to take a US Congressional delegation 310 00:12:22,650 --> 00:12:25,230 around Acadia, talk about climate change, 311 00:12:25,230 --> 00:12:28,950 talk about climate change adaptation, and you know, we went 312 00:12:28,950 --> 00:12:31,740 to all the most beautiful places in the park, 313 00:12:31,740 --> 00:12:34,920 but US Representative Mike Quigley decided to tweet 314 00:12:34,920 --> 00:12:37,830 to his 52,000 constituents 315 00:12:37,830 --> 00:12:40,080 about our experimental restoration plot 316 00:12:40,080 --> 00:12:41,790 on the summit of Cadillac Mountain, right? 317 00:12:41,790 --> 00:12:44,520 And talking about the mission now as adaptation 318 00:12:44,520 --> 00:12:47,400 and resilience, not just restoration, right? 319 00:12:47,400 --> 00:12:49,740 That's a huge reach that I wouldn't get on my own. 320 00:12:49,740 --> 00:12:52,860 And I think there's just something about having these plots 321 00:12:52,860 --> 00:12:54,420 in beautiful natural places 322 00:12:54,420 --> 00:12:56,370 that's really compelling to people. 323 00:12:56,370 --> 00:12:57,203 So they make these 324 00:12:57,203 --> 00:12:59,883 great science management communication tools. 325 00:13:01,290 --> 00:13:03,990 But you know, I wanna close by kind of acknowledging, right, 326 00:13:03,990 --> 00:13:06,000 that we're not the first people to suggest 327 00:13:06,000 --> 00:13:07,980 we should be doing experimental management, right? 328 00:13:07,980 --> 00:13:10,050 People have been talking about this for years, 329 00:13:10,050 --> 00:13:12,330 and of course it's not really happening on the landscape 330 00:13:12,330 --> 00:13:14,640 as much as we would like to see. 331 00:13:14,640 --> 00:13:18,060 And so we probably need some systemic changes if we want 332 00:13:18,060 --> 00:13:19,803 to see this happen more widely. 333 00:13:21,240 --> 00:13:22,920 And so I think the good thing is a lot 334 00:13:22,920 --> 00:13:24,660 of these changes are already happening. 335 00:13:24,660 --> 00:13:26,820 So the first change I wanna suggest 336 00:13:26,820 --> 00:13:29,880 is that we need more models of effective coproduction 337 00:13:29,880 --> 00:13:32,670 where scientists and managers work together every step 338 00:13:32,670 --> 00:13:35,370 of the way, right, to design these experiments. 339 00:13:35,370 --> 00:13:39,210 And Schoodic Institute where I work is a perfect example of, 340 00:13:39,210 --> 00:13:41,970 you know, we're an institute whose mission is to work 341 00:13:41,970 --> 00:13:45,300 with, be a science partner to the National Park Service. 342 00:13:45,300 --> 00:13:47,880 So we need more of this kind of work to ensure 343 00:13:47,880 --> 00:13:50,040 that we're using rigorous science 344 00:13:50,040 --> 00:13:53,043 to address relevant management challenges. 345 00:13:54,240 --> 00:13:56,430 We of course need different funding models, right? 346 00:13:56,430 --> 00:13:57,780 And so not always, 347 00:13:57,780 --> 00:13:59,910 but often managers don't wanna fund science, 348 00:13:59,910 --> 00:14:02,130 and scientists, scientific organizations 349 00:14:02,130 --> 00:14:03,750 don't wanna fund management. 350 00:14:03,750 --> 00:14:05,340 But that's changing too, right? 351 00:14:05,340 --> 00:14:08,730 Last year NSF put out this call for partnerships 352 00:14:08,730 --> 00:14:11,790 to advance conservation science and practice. 353 00:14:11,790 --> 00:14:14,580 And people are now taking even more novel routes, right? 354 00:14:14,580 --> 00:14:17,760 So adaptation research in the Southwest is now funded 355 00:14:17,760 --> 00:14:19,080 by this congressional bill. 356 00:14:19,080 --> 00:14:20,700 So we're going right to the source, 357 00:14:20,700 --> 00:14:22,980 right, to get money for these things. 358 00:14:22,980 --> 00:14:25,770 So these things are changing. 359 00:14:25,770 --> 00:14:28,740 And then last, we need to change our values. 360 00:14:28,740 --> 00:14:30,840 And so obviously, not always, 361 00:14:30,840 --> 00:14:34,200 but often the public values accountability, 362 00:14:34,200 --> 00:14:36,510 scientists value learning, and funders 363 00:14:36,510 --> 00:14:38,820 and practitioners value effectiveness. 364 00:14:38,820 --> 00:14:40,140 But again, this is changing. 365 00:14:40,140 --> 00:14:43,080 And so I was in a meeting the other day with folks, 366 00:14:43,080 --> 00:14:45,450 with a lot of different folks and the superintendent 367 00:14:45,450 --> 00:14:47,280 of Acadia National Park was there 368 00:14:47,280 --> 00:14:50,070 and he was talking about how we need science 369 00:14:50,070 --> 00:14:52,020 and learning to manage in a changing world. 370 00:14:52,020 --> 00:14:55,413 And that was really refreshing to hear him talk like that. 371 00:14:57,000 --> 00:15:00,330 So just to reiterate my take home messages 372 00:15:00,330 --> 00:15:02,930 are we need more tests of these kinds of strategies. 373 00:15:03,780 --> 00:15:06,450 Implementing multiple strategies simultaneously might be 374 00:15:06,450 --> 00:15:08,250 a quicker way for us to learn. 375 00:15:08,250 --> 00:15:09,900 Experimental adaptation has a lot 376 00:15:09,900 --> 00:15:12,270 of potential secondary benefits, 377 00:15:12,270 --> 00:15:14,700 but we need some systemic changes if we wanna see 378 00:15:14,700 --> 00:15:18,240 wider application of these types of approaches. 379 00:15:18,240 --> 00:15:19,680 And I'll just close and leave this up. 380 00:15:19,680 --> 00:15:22,380 This is a paper that talks about this a lot more 381 00:15:22,380 --> 00:15:25,920 in a lot more detail and it just came out last week. 382 00:15:25,920 --> 00:15:28,140 So if you're interested, please check it out, 383 00:15:28,140 --> 00:15:29,590 and I'll take some questions. 384 00:15:36,930 --> 00:15:37,890 Yeah. 385 00:15:37,890 --> 00:15:39,750 [Participant] Thanks so much for your great work. 386 00:15:39,750 --> 00:15:41,700 So I have two questions about... 387 00:15:41,700 --> 00:15:43,320 Maybe just to try to combine 'em. 388 00:15:43,320 --> 00:15:44,700 One of them is the view 389 00:15:44,700 --> 00:15:47,160 about the glossy buckhorn, Frangula alnus. 390 00:15:47,160 --> 00:15:49,440 I imagine (audio cuts out) working 391 00:15:49,440 --> 00:15:51,750 with Rhamnus cathartica, similar, 392 00:15:51,750 --> 00:15:54,240 I don't know if you've heard of Mike Bald of Got Weeds, 393 00:15:54,240 --> 00:15:58,560 but he has a strategy that it's quite effective. 394 00:15:58,560 --> 00:16:00,540 We've used it on several restoration sites 395 00:16:00,540 --> 00:16:02,370 where you cut once and bound tight 396 00:16:02,370 --> 00:16:05,040 and then strip back two times in two seasons. 397 00:16:05,040 --> 00:16:06,780 You get a 90% death rate. 398 00:16:06,780 --> 00:16:08,790 So I was just wondering if they had applied that 399 00:16:08,790 --> 00:16:10,788 to that site that became green. 400 00:16:10,788 --> 00:16:12,120 It's a really good question. 401 00:16:12,120 --> 00:16:13,500 We're starting an experiment. 402 00:16:13,500 --> 00:16:16,380 We just got outta the field last week to find places 403 00:16:16,380 --> 00:16:18,030 to test that exact strategy. 404 00:16:18,030 --> 00:16:21,330 And so, how often do you have to go back and strip the trees 405 00:16:21,330 --> 00:16:23,970 after you've cut them once to kill them? 406 00:16:23,970 --> 00:16:25,980 And yeah, as you said, it's been done with common buckthorn, 407 00:16:25,980 --> 00:16:27,600 but not necessarily with, at least 408 00:16:27,600 --> 00:16:29,040 that I'm not aware of with glossy buckthorn. 409 00:16:29,040 --> 00:16:32,247 And so, yeah, we're about to test that. 410 00:16:32,247 --> 00:16:35,430 And so right now the Park Service uses pesticides. 411 00:16:35,430 --> 00:16:37,350 They do cutting, but they also use pesticides. 412 00:16:37,350 --> 00:16:39,330 They'd like to use a lot less pesticides. 413 00:16:39,330 --> 00:16:41,190 So if we can kind of find a method like that 414 00:16:41,190 --> 00:16:42,840 that works, we'd love to. 415 00:16:42,840 --> 00:16:44,430 So yeah, it just depends. 416 00:16:44,430 --> 00:16:45,780 If you have to go back every month 417 00:16:45,780 --> 00:16:47,820 and strip it, then it's probably too much work 418 00:16:47,820 --> 00:16:48,653 for the Park Service, yeah. 419 00:16:48,653 --> 00:16:51,030 [Participant] And the other part was that nice portfolio 420 00:16:51,030 --> 00:16:53,983 you've had with, you know, the grasses and then the shrubs. 421 00:16:53,983 --> 00:16:56,400 I think, you know, a neat third would be like 422 00:16:56,400 --> 00:16:57,840 the polyculture model. 423 00:16:57,840 --> 00:16:59,700 Yeah, agreed. Yeah. Yeah. 424 00:16:59,700 --> 00:17:01,200 And we thought about all sorts of stuff. 425 00:17:01,200 --> 00:17:02,940 You know, seeding is really where we wanna go. 426 00:17:02,940 --> 00:17:04,470 It's quicker, you don't have to dig the holes 427 00:17:04,470 --> 00:17:06,468 and all that stuff, but we just, you know. 428 00:17:06,468 --> 00:17:08,070 The hard part with these experiments 429 00:17:08,070 --> 00:17:10,260 is there's a lot of potential things 430 00:17:10,260 --> 00:17:13,320 to test and that's the bane of an experiment. 431 00:17:13,320 --> 00:17:14,153 You can't do that. 432 00:17:14,153 --> 00:17:15,217 And so, yeah, that's why we did. 433 00:17:15,217 --> 00:17:16,770 But yeah, good thought. 434 00:17:16,770 --> 00:17:17,763 Yeah. Thank you. 435 00:17:20,430 --> 00:17:23,400 I think we have a question online. 436 00:17:23,400 --> 00:17:24,450 [Presenter] Yeah, there. 437 00:17:24,450 --> 00:17:28,110 I think Brandon is trying 438 00:17:28,110 --> 00:17:30,690 to ask a question, although he's not, oh, here it is. 439 00:17:30,690 --> 00:17:32,100 Thank you, Chris. 440 00:17:32,100 --> 00:17:34,470 You alluded earlier that there are currently a ton 441 00:17:34,470 --> 00:17:38,130 of potential strategies in your work you've found. 442 00:17:38,130 --> 00:17:41,430 Have you found any that actually confound one another 443 00:17:41,430 --> 00:17:43,710 that practitioners should be aware of 444 00:17:43,710 --> 00:17:44,730 in their implementation 445 00:17:44,730 --> 00:17:47,490 to assure each interval strategy is the most effective? 446 00:17:47,490 --> 00:17:48,323 Hm. 447 00:17:49,890 --> 00:17:51,810 Yeah, maybe I don't understand the question. 448 00:17:51,810 --> 00:17:54,150 It's tough when they're online, but I think... 449 00:17:54,150 --> 00:17:55,410 [Presenter] He said, have you found any 450 00:17:55,410 --> 00:17:57,990 that actually confound one another? 451 00:17:57,990 --> 00:17:59,820 Yeah, I mean, that's why we have 452 00:17:59,820 --> 00:18:01,350 in that summit restoration plot, 453 00:18:01,350 --> 00:18:03,300 we have this increasing genetic diversity 454 00:18:03,300 --> 00:18:05,760 and adding pre-adapted individuals, 455 00:18:05,760 --> 00:18:07,740 those are both increasing genetic diversity, right? 456 00:18:07,740 --> 00:18:10,740 We're always bringing individuals from different locations. 457 00:18:10,740 --> 00:18:12,750 And the reason we have those two treatments 458 00:18:12,750 --> 00:18:15,960 is 'cause we just added pre-adapted individuals. 459 00:18:15,960 --> 00:18:19,230 We wouldn't know if it's that we're getting individuals 460 00:18:19,230 --> 00:18:20,580 from warmer sites 461 00:18:20,580 --> 00:18:22,530 or is it that we're increasing genetic diversity? 462 00:18:22,530 --> 00:18:26,790 What's the mechanism allowing that strategy to work? 463 00:18:26,790 --> 00:18:28,920 So that's kind of why we are testing them both. 464 00:18:28,920 --> 00:18:33,240 And that might sound esoteric, but it's a lot of work to try 465 00:18:33,240 --> 00:18:35,877 to find these warm adapted populations, right? 466 00:18:35,877 --> 00:18:37,227 And so if we don't have to do that 467 00:18:37,227 --> 00:18:40,380 and we can just go get individuals from other places, 468 00:18:40,380 --> 00:18:42,930 then that's a much simpler strategy. 469 00:18:42,930 --> 00:18:44,430 So it's not really that esoteric. 470 00:18:44,430 --> 00:18:48,150 So that is kind of a confounding strategy. 471 00:18:48,150 --> 00:18:49,519 And just so you all know, 472 00:18:49,519 --> 00:18:51,660 and at least right now preliminary data 473 00:18:51,660 --> 00:18:53,130 from that experiment suggests neither 474 00:18:53,130 --> 00:18:55,290 of those strategies is working. 475 00:18:55,290 --> 00:18:56,123 [Presenter] I think you were wondering 476 00:18:56,123 --> 00:18:57,300 if whether he's saying, 477 00:18:57,300 --> 00:18:59,550 could one strategy cancel the other one out? 478 00:18:59,550 --> 00:19:00,383 Have you found any? 479 00:19:00,383 --> 00:19:01,620 Maybe you're implementing multiple- 480 00:19:01,620 --> 00:19:02,910 I see, I see. 481 00:19:02,910 --> 00:19:04,200 [Presenter] Are there any that you found 482 00:19:04,200 --> 00:19:05,400 that could cancel each other out 483 00:19:05,400 --> 00:19:06,900 that you don't really wanna be implementing 484 00:19:06,900 --> 00:19:07,733 at the same time? 485 00:19:07,733 --> 00:19:08,566 I see, yeah. 486 00:19:08,566 --> 00:19:09,960 That is a good... 487 00:19:09,960 --> 00:19:12,810 I can't think of a particular example off my head, 488 00:19:12,810 --> 00:19:14,924 but yeah, that would be important. 489 00:19:14,924 --> 00:19:17,550 And I think in the paper we talk about different ways 490 00:19:17,550 --> 00:19:19,500 to kind of implement these experiments. 491 00:19:19,500 --> 00:19:20,850 One way to get around that is, you know, 492 00:19:20,850 --> 00:19:23,250 you could do different things at different sites. 493 00:19:23,250 --> 00:19:25,590 You just need a lot more sites if you're gonna do that 494 00:19:25,590 --> 00:19:27,270 to be able to weed out kind of the noise. 495 00:19:27,270 --> 00:19:29,730 But yeah, so that'd be a way to get around this kind 496 00:19:29,730 --> 00:19:32,493 of confounding two strategies in a safe place. 497 00:19:35,010 --> 00:19:35,843 Yeah. 498 00:19:35,843 --> 00:19:37,680 [Participant] Are you aware of any research 499 00:19:37,680 --> 00:19:42,540 on biocontrol strategies for either buckthorn species? 500 00:19:42,540 --> 00:19:43,373 I'm not. 501 00:19:43,373 --> 00:19:44,280 Yeah. I don't know. 502 00:19:44,280 --> 00:19:46,770 Just, do you guys know colleagues in the back? 503 00:19:46,770 --> 00:19:47,603 No. 504 00:19:47,603 --> 00:19:50,550 Yeah, I'm not aware of any biocontrol strategies for them. 505 00:19:50,550 --> 00:19:52,170 Yeah. 506 00:19:52,170 --> 00:19:53,405 Are you? 507 00:19:53,405 --> 00:19:55,339 (audience laughs) 508 00:19:55,339 --> 00:19:58,006 (garbled audio) 509 00:19:59,705 --> 00:20:01,090 [Participant] Years of evolution, maybe. 510 00:20:01,090 --> 00:20:03,743 Nah. (laughs) 511 00:20:03,743 --> 00:20:06,326 So with all of that, thank you.