1 00:00:03,620 --> 00:00:05,880 - So without further ado, this is Mike Hallworth. 2 00:00:05,880 --> 00:00:09,020 He's a data scientist with Vermont Center for Ecostudies. 3 00:00:09,020 --> 00:00:12,170 And this is his talk, Living on the edge in a warming world: 4 00:00:12,170 --> 00:00:14,700 distributions and thermal refugia of forest insects 5 00:00:14,700 --> 00:00:17,150 across the northeastern United States. 6 00:00:17,150 --> 00:00:19,200 So I'll turn it over to you, Mike. 7 00:00:19,200 --> 00:00:21,000 - Great, good afternoon, everybody. 8 00:00:21,000 --> 00:00:22,710 Thank you for having me here. 9 00:00:22,710 --> 00:00:25,360 I'm excited to talk about some preliminary results 10 00:00:25,360 --> 00:00:28,030 with you today and how climate change may impact insects 11 00:00:28,030 --> 00:00:29,930 across the broader New England region. 12 00:00:31,330 --> 00:00:34,790 All right, so insects are the world's most species-rich 13 00:00:34,790 --> 00:00:38,200 and abundant group of macroscopic organisms on the planet. 14 00:00:38,200 --> 00:00:40,210 And community science data 15 00:00:41,220 --> 00:00:44,560 across the broader New England region confirm that. 16 00:00:44,560 --> 00:00:46,470 So this pie chart that you're looking at 17 00:00:46,470 --> 00:00:48,293 on the left-hand side here just shows 18 00:00:48,293 --> 00:00:51,870 that insects are by far and away the most speciose group 19 00:00:51,870 --> 00:00:54,130 that we've identified as community scientists, 20 00:00:54,130 --> 00:00:56,830 over 1,600 insect species. 21 00:00:56,830 --> 00:00:58,730 The problem is that they're experiencing 22 00:00:58,730 --> 00:01:00,720 precipitous declines. 23 00:01:00,720 --> 00:01:04,410 A recent study a couple of years ago 24 00:01:04,410 --> 00:01:09,240 showed that insect biomass has been declining 25 00:01:09,240 --> 00:01:11,670 in protected areas in Germany. 26 00:01:11,670 --> 00:01:15,260 And so here is flying insect biomass from malaise traps 27 00:01:15,260 --> 00:01:17,470 through time on the x-axis. 28 00:01:17,470 --> 00:01:20,280 And the rate of global declines is still uncertain. 29 00:01:20,280 --> 00:01:23,050 And there's some dispute about that, 30 00:01:23,050 --> 00:01:26,143 but scientists agree that insects are in decline globally. 31 00:01:27,160 --> 00:01:30,313 And we're seeing this decline in the Northeast as well. 32 00:01:31,160 --> 00:01:32,600 We're seeing beetle declines. 33 00:01:32,600 --> 00:01:36,680 One example came recently from a Wellesley undergrad, 34 00:01:36,680 --> 00:01:39,240 published a pretty high-impact paper 35 00:01:40,100 --> 00:01:44,420 where they replicated some window trap surveys for beetles 36 00:01:44,420 --> 00:01:47,530 at Hubbard Brook Experimental Forest in New Hampshire, 37 00:01:47,530 --> 00:01:50,330 where they did some window trap surveys in the '70s, 38 00:01:50,330 --> 00:01:55,330 and then they replicated the surveys in 2015 to 2017. 39 00:01:55,560 --> 00:01:58,050 What you're looking at on the y-axis here 40 00:01:58,050 --> 00:02:01,250 is the mean captures per two day period 41 00:02:01,250 --> 00:02:03,220 and time on the x-axis. 42 00:02:03,220 --> 00:02:06,700 And the gray bars show the results from the '70s, 43 00:02:06,700 --> 00:02:10,390 and the black bars show the more recent results. 44 00:02:10,390 --> 00:02:14,200 And there's a drastic decline in the number of beetles 45 00:02:14,200 --> 00:02:16,963 that were captured in a two day period. 46 00:02:18,430 --> 00:02:20,500 They found that the number of beetles that they caught 47 00:02:20,500 --> 00:02:24,710 during that time period was strongly correlated 48 00:02:24,710 --> 00:02:28,010 with the median snow depth during the preceding winter. 49 00:02:28,010 --> 00:02:30,650 So there's some climate component there potentially 50 00:02:30,650 --> 00:02:33,590 of the decline in beetle captures. 51 00:02:33,590 --> 00:02:37,650 But it wasn't just beetle captures that was reduced. 52 00:02:37,650 --> 00:02:41,450 It turns out that the species richness was also reduced, 53 00:02:41,450 --> 00:02:44,793 so the actual species that they captured in those surveys. 54 00:02:46,020 --> 00:02:50,320 This is the original species accumulation curve 55 00:02:50,320 --> 00:02:53,860 from the '70s where you have species taxa on the y-axis 56 00:02:53,860 --> 00:02:56,870 and the number of samples on the x-axis. 57 00:02:56,870 --> 00:02:58,760 And there's a drastic reduction 58 00:02:58,760 --> 00:03:00,930 in the number of species that they captured 59 00:03:00,930 --> 00:03:03,133 when comparing the two survey periods. 60 00:03:04,210 --> 00:03:05,210 So that leaves the question, 61 00:03:05,210 --> 00:03:07,210 like what factors are contributing 62 00:03:07,210 --> 00:03:09,610 to some of these observed declines? 63 00:03:09,610 --> 00:03:11,380 Ad David Wagner and colleagues 64 00:03:11,380 --> 00:03:13,640 published a paper recently this year 65 00:03:13,640 --> 00:03:16,200 in "Proceedings of the National Academy of Sciences". 66 00:03:16,200 --> 00:03:18,540 And they suggested that insect declines 67 00:03:18,540 --> 00:03:20,993 are caused by the death of a thousand cuts. 68 00:03:22,180 --> 00:03:26,750 And many of these cuts are related to climate change, 69 00:03:26,750 --> 00:03:28,700 whether it's species disruption, 70 00:03:28,700 --> 00:03:30,963 so changing species interactions, 71 00:03:32,310 --> 00:03:34,800 more intense and larger wildfires, 72 00:03:34,800 --> 00:03:38,040 storm intensity that caused increased flooding, 73 00:03:38,040 --> 00:03:40,180 warmer temperatures, which could alternate 74 00:03:40,180 --> 00:03:42,790 their life stages, and droughts. 75 00:03:42,790 --> 00:03:44,940 And all of those types of stressors 76 00:03:44,940 --> 00:03:47,420 are compounding what's happening below. 77 00:03:47,420 --> 00:03:50,230 So like deforestation, insecticides, 78 00:03:50,230 --> 00:03:53,760 introduced species, urbanization and so on. 79 00:03:53,760 --> 00:03:57,020 And so climate change is a real issue. 80 00:03:57,020 --> 00:04:02,020 So how might climate change impact insect populations? 81 00:04:02,920 --> 00:04:07,250 Well, it could reduce habitat suitability for some species, 82 00:04:07,250 --> 00:04:10,130 change habitat suitability for others. 83 00:04:10,130 --> 00:04:12,750 It could alter range limits and change range limits. 84 00:04:12,750 --> 00:04:15,660 So we see that some species are moving northward 85 00:04:15,660 --> 00:04:18,870 and some are moving potentially southward. 86 00:04:18,870 --> 00:04:21,590 It could alter the timing of life cycle events. 87 00:04:21,590 --> 00:04:22,660 So like think of 88 00:04:23,980 --> 00:04:26,880 when caterpillars form cocoons 89 00:04:26,880 --> 00:04:29,513 or when dragonflies enclose. 90 00:04:30,560 --> 00:04:33,733 And why does this all matter? 91 00:04:35,090 --> 00:04:38,090 Well, insects are hugely important, 92 00:04:38,090 --> 00:04:41,030 especially for forested ecosystems. 93 00:04:41,030 --> 00:04:44,010 They perform many, many ecosystem services. 94 00:04:44,010 --> 00:04:47,310 For example, they're culturally important, 95 00:04:47,310 --> 00:04:49,580 and they provide great aesthetics 96 00:04:49,580 --> 00:04:53,200 like this black swallowtail caterpillar. 97 00:04:53,200 --> 00:04:56,650 They provide critical ecosystem function 98 00:04:56,650 --> 00:04:59,640 like pollination and seed dispersal, 99 00:04:59,640 --> 00:05:02,280 but they're also bioindicators of ecosystem health 100 00:05:02,280 --> 00:05:03,863 and for water quality. 101 00:05:04,720 --> 00:05:09,100 They perform pest control and they help aerate soil. 102 00:05:09,100 --> 00:05:10,543 And there are so many more. 103 00:05:12,120 --> 00:05:17,030 They're also a hugely important component of food webs, 104 00:05:17,030 --> 00:05:19,820 especially for vertebrates. 105 00:05:19,820 --> 00:05:22,300 So just one example, the chickadees 106 00:05:22,300 --> 00:05:25,270 that presumably are breeding in your backyard, 107 00:05:25,270 --> 00:05:28,790 to successfully raise a brood, they have to forage 108 00:05:28,790 --> 00:05:31,860 and bring caterpillars, a lot of them every day, 109 00:05:31,860 --> 00:05:36,410 between 350 and 570 caterpillars per day 110 00:05:36,410 --> 00:05:38,300 to successfully raise a bird. 111 00:05:38,300 --> 00:05:41,423 So they're hugely important to our food webs. 112 00:05:43,780 --> 00:05:47,380 And since they occur ubiquitously in our food webs 113 00:05:47,380 --> 00:05:49,460 and they serve as bioindicators, 114 00:05:49,460 --> 00:05:51,540 it's imperative that we understand 115 00:05:51,540 --> 00:05:54,870 how their populations and species richness 116 00:05:54,870 --> 00:05:57,510 responds to climate change. 117 00:05:57,510 --> 00:06:00,930 And so today we set out, 118 00:06:00,930 --> 00:06:01,970 I'm gonna tell you a little bit 119 00:06:01,970 --> 00:06:04,310 about what we are working on, 120 00:06:04,310 --> 00:06:07,380 and we set out to develop the species distribution models 121 00:06:07,380 --> 00:06:11,040 to better understand where species are within the landscape 122 00:06:11,040 --> 00:06:13,320 and how their distributions may be changing 123 00:06:13,320 --> 00:06:15,220 given climate projections. 124 00:06:15,220 --> 00:06:18,300 And we need these detailed maps to understand 125 00:06:18,300 --> 00:06:21,030 both the current risks and the future risks 126 00:06:21,030 --> 00:06:24,690 that these species may encounter. 127 00:06:24,690 --> 00:06:29,550 And these distribution maps help fill critical data gaps, 128 00:06:29,550 --> 00:06:33,270 as identified in a lot of the state wildlife action plans 129 00:06:33,270 --> 00:06:34,830 across the northeast. 130 00:06:34,830 --> 00:06:37,510 And this data will help allow stakeholders 131 00:06:37,510 --> 00:06:39,360 to make really informed decisions 132 00:06:39,360 --> 00:06:42,430 about where to place management 133 00:06:42,430 --> 00:06:44,680 or take management action in the future, 134 00:06:44,680 --> 00:06:45,973 given climate change. 135 00:06:48,020 --> 00:06:51,670 So I'm gonna talk briefly about the methods. 136 00:06:51,670 --> 00:06:54,130 We used community science observations 137 00:06:54,130 --> 00:06:55,300 submitted to GBIF, 138 00:06:55,300 --> 00:06:58,570 or the Global Biodiversity Information Facility 139 00:06:58,570 --> 00:07:02,390 through iNaturalist and eButterfly and other sources. 140 00:07:02,390 --> 00:07:05,970 So we took the presence data for species, 141 00:07:05,970 --> 00:07:07,220 and all the insects 142 00:07:07,220 --> 00:07:11,010 with more than five independent research grade observations. 143 00:07:11,010 --> 00:07:12,350 That means that someone else said, 144 00:07:12,350 --> 00:07:14,360 oh, yes, that is a black swallowtail. 145 00:07:14,360 --> 00:07:16,260 So more than one person, 146 00:07:16,260 --> 00:07:18,283 there's confirmed by many people. 147 00:07:19,710 --> 00:07:22,120 And we know that there's sampling bias 148 00:07:22,120 --> 00:07:24,490 in where people submit their observations, 149 00:07:24,490 --> 00:07:27,090 that like, you know, they tend to submit 150 00:07:27,090 --> 00:07:29,670 where they live and near roads. 151 00:07:29,670 --> 00:07:34,670 So we accounted for that sampling bias in the location data. 152 00:07:34,680 --> 00:07:37,440 And then we associated those occurrence records 153 00:07:37,440 --> 00:07:39,600 with bioclimatic data, 154 00:07:39,600 --> 00:07:42,110 so things like mean annual temperature, 155 00:07:42,110 --> 00:07:45,540 precipitation, for example. 156 00:07:45,540 --> 00:07:50,260 And we used that relationship between the current data, 157 00:07:50,260 --> 00:07:52,860 the occurrence data and the climate data 158 00:07:52,860 --> 00:07:57,040 to make predictions about how the occurrence will change 159 00:07:57,040 --> 00:07:58,880 given climate change. 160 00:07:58,880 --> 00:08:02,230 And that allowed us to make both current distribution maps, 161 00:08:02,230 --> 00:08:04,330 like shown here on the top, 162 00:08:04,330 --> 00:08:07,460 at one by one kilometer resolution. 163 00:08:07,460 --> 00:08:09,300 And then we also are able to feed, 164 00:08:09,300 --> 00:08:12,200 okay, well, how will the climate change 165 00:08:12,200 --> 00:08:14,470 given some ensemble models, 166 00:08:14,470 --> 00:08:16,380 and what is the projected relationship 167 00:08:16,380 --> 00:08:19,010 or the distribution of the species moving forward? 168 00:08:19,010 --> 00:08:21,270 So given the climate projection, 169 00:08:21,270 --> 00:08:24,170 the current relationship between climate, 170 00:08:24,170 --> 00:08:25,840 we can get a distribution map. 171 00:08:25,840 --> 00:08:28,980 And if those relationships stay similar, 172 00:08:28,980 --> 00:08:31,270 then this is the projected distribution 173 00:08:31,270 --> 00:08:34,260 for that species in the future. 174 00:08:34,260 --> 00:08:37,310 So I'm gonna dive right into some results here. 175 00:08:37,310 --> 00:08:40,410 Where are forest insects across the northeast? 176 00:08:40,410 --> 00:08:42,030 So what you're looking at is 177 00:08:42,030 --> 00:08:45,610 the estimated species richness on the left here. 178 00:08:45,610 --> 00:08:48,210 This is the current range where they are. 179 00:08:48,210 --> 00:08:51,310 And on the right is where they're projected to be 180 00:08:51,310 --> 00:08:54,630 given the most likely climate emission scenario, 181 00:08:54,630 --> 00:08:58,760 which is RCP 7.0 in the year 182 00:08:58,760 --> 00:09:03,760 where the climate that encompasses 2071 to 2100. 183 00:09:03,920 --> 00:09:07,170 You can see the range in species richness here 184 00:09:07,170 --> 00:09:09,563 between the current and the future. 185 00:09:10,830 --> 00:09:14,130 So this is great first picture of where things are, 186 00:09:14,130 --> 00:09:15,600 but I was kind of really interested 187 00:09:15,600 --> 00:09:18,750 in where things will be changing. 188 00:09:18,750 --> 00:09:20,840 And so what you're looking at in this slide 189 00:09:20,840 --> 00:09:22,450 is this is the previous map 190 00:09:22,450 --> 00:09:24,720 on the previous slide for reference. 191 00:09:24,720 --> 00:09:26,770 This histogram here on the lower left 192 00:09:26,770 --> 00:09:30,280 shows the change in species richness on the x-axis 193 00:09:30,280 --> 00:09:34,540 and the frequency of cells on the y-axis. 194 00:09:34,540 --> 00:09:39,540 So there are some places where we're losing 200-ish species, 195 00:09:39,890 --> 00:09:41,350 and there are lots of places 196 00:09:41,350 --> 00:09:44,820 where we're gaining lots of species, upwards of 800. 197 00:09:44,820 --> 00:09:46,610 I should say, gaining, I said. 198 00:09:46,610 --> 00:09:48,440 I should say moving; species are moving. 199 00:09:48,440 --> 00:09:50,970 Because I limited the taxa 200 00:09:50,970 --> 00:09:52,910 to what is currently in New England 201 00:09:53,833 --> 00:09:57,090 and not what is potentially moving into New England. 202 00:09:57,090 --> 00:09:59,790 And this is where it's happening in space. 203 00:09:59,790 --> 00:10:01,430 The red indicates areas 204 00:10:01,430 --> 00:10:05,182 where species richness will be lower in 2100. 205 00:10:05,182 --> 00:10:08,620 And the warmer colors means that more species 206 00:10:08,620 --> 00:10:11,710 are potentially leaving that spot. 207 00:10:11,710 --> 00:10:15,700 And the cooler colors and blue indicate areas 208 00:10:15,700 --> 00:10:18,373 where there's species richness increase. 209 00:10:19,700 --> 00:10:22,250 On this histogram on top shows 210 00:10:22,250 --> 00:10:25,270 how that change is distributed in longitude. 211 00:10:25,270 --> 00:10:28,420 So this is on the west and this is east. 212 00:10:28,420 --> 00:10:29,910 And then this on the right, 213 00:10:29,910 --> 00:10:31,100 this histogram on the right shows 214 00:10:31,100 --> 00:10:33,570 how it will change with latitude. 215 00:10:33,570 --> 00:10:35,710 So this is south and north. 216 00:10:35,710 --> 00:10:38,880 So you can see where the projected changes 217 00:10:38,880 --> 00:10:40,930 may occur with latitude. 218 00:10:40,930 --> 00:10:42,500 So this is all taxa. 219 00:10:42,500 --> 00:10:46,650 So what I'm gonna do now is talk about some insect groups. 220 00:10:46,650 --> 00:10:50,190 So how will climate impact the major insect orders? 221 00:10:50,190 --> 00:10:52,920 And I just picked these major insect orders 222 00:10:52,920 --> 00:10:54,340 because I thought they were interesting, 223 00:10:54,340 --> 00:10:56,543 but we did 20 insect orders. 224 00:10:57,840 --> 00:11:00,570 So on the maps, you'll see more of these maps 225 00:11:00,570 --> 00:11:01,403 in a little while, 226 00:11:01,403 --> 00:11:05,450 but the current species richness is on the left, 227 00:11:05,450 --> 00:11:09,250 and the species richness for those orders 228 00:11:09,250 --> 00:11:13,283 is on the right in 2071 to 2100. 229 00:11:14,390 --> 00:11:15,250 Now I was interested 230 00:11:15,250 --> 00:11:18,830 in how to kind of numerically or quantitatively measure 231 00:11:18,830 --> 00:11:21,020 how things will change in the future. 232 00:11:21,020 --> 00:11:23,590 And so this is like 233 00:11:23,590 --> 00:11:27,870 a climate velocity analog to species richness. 234 00:11:27,870 --> 00:11:29,940 And so what you're looking at here is 235 00:11:29,940 --> 00:11:32,660 this is the current richness, 236 00:11:32,660 --> 00:11:35,610 and then this is the projected richness in the future. 237 00:11:35,610 --> 00:11:38,770 And so what this velocity is measuring 238 00:11:38,770 --> 00:11:39,980 is the rate of change 239 00:11:39,980 --> 00:11:43,380 between the current species richness value 240 00:11:43,380 --> 00:11:47,770 and where the closest analog pixel will be in the future. 241 00:11:47,770 --> 00:11:51,440 So how far does this cell 242 00:11:51,440 --> 00:11:53,110 need to move per year 243 00:11:53,110 --> 00:11:55,033 to represent this cell in the future? 244 00:11:56,130 --> 00:11:57,360 That's the rate of change. 245 00:11:57,360 --> 00:11:59,820 So it's in kilometers per year. 246 00:11:59,820 --> 00:12:03,327 The direction of change measures which direction 247 00:12:03,327 --> 00:12:07,900 this particular cell will need to move with respect to north 248 00:12:07,900 --> 00:12:10,830 to represent this cell in the future. 249 00:12:10,830 --> 00:12:12,120 So there are two metrics here, 250 00:12:12,120 --> 00:12:15,073 velocity which is a rate, and direction. 251 00:12:17,080 --> 00:12:19,900 You'll see a few of these histograms coming forward. 252 00:12:19,900 --> 00:12:21,640 So I just wanna describe them a little bit. 253 00:12:21,640 --> 00:12:26,470 On the x-axis is the rate of change in kilometers per year. 254 00:12:26,470 --> 00:12:27,970 So this value here, 255 00:12:27,970 --> 00:12:31,280 there's a few values of six kilometers per year, 256 00:12:31,280 --> 00:12:34,740 and a lot of values that are close to zero, 257 00:12:34,740 --> 00:12:38,053 whereas that pixel does not have to move through time. 258 00:12:39,080 --> 00:12:41,300 The rose plot up on the upper right 259 00:12:41,300 --> 00:12:42,920 shows the direction of change 260 00:12:42,920 --> 00:12:47,650 where north is zero, east, south, and west. 261 00:12:47,650 --> 00:12:49,610 And so in this particular example, 262 00:12:49,610 --> 00:12:53,260 almost all the pixels were moving northward 263 00:12:53,260 --> 00:12:55,503 to match their species analog in the future. 264 00:12:56,990 --> 00:12:58,880 So diving into these results, 265 00:12:58,880 --> 00:13:01,090 how will climate impact the major insect orders? 266 00:13:01,090 --> 00:13:03,460 What you're looking at here is Lepidoptera. 267 00:13:03,460 --> 00:13:05,680 And so this is the histogram on the left 268 00:13:05,680 --> 00:13:09,060 of climate or the velocity kilometers per year, 269 00:13:09,060 --> 00:13:10,350 and the rose plot, 270 00:13:10,350 --> 00:13:15,050 so which direction do they have to go to meet that analog? 271 00:13:15,050 --> 00:13:19,420 Most of the species are moving northward, pixels, sorry. 272 00:13:19,420 --> 00:13:21,360 Some pixels are moving towards the east 273 00:13:21,360 --> 00:13:22,980 and some are moving towards the west, 274 00:13:22,980 --> 00:13:25,280 but the majority are moving north. 275 00:13:25,280 --> 00:13:30,120 And the mean velocity was about 1.5 kilometers per year 276 00:13:30,120 --> 00:13:33,360 between the current distribution 277 00:13:33,360 --> 00:13:36,633 and the distribution in 2100, let's say. 278 00:13:39,040 --> 00:13:41,280 So for Coleoptera, for beetles, 279 00:13:41,280 --> 00:13:44,500 the mean is 1.48 kilometers per year, 280 00:13:44,500 --> 00:13:46,760 so about the same as Lepidoptera, 281 00:13:46,760 --> 00:13:49,383 but almost all of those pixels and moving due north. 282 00:13:50,790 --> 00:13:53,680 For Diptera, we see a similar pattern. 283 00:13:53,680 --> 00:13:57,970 The mean is about 1.6 kilometers per year. 284 00:13:57,970 --> 00:14:00,360 So Diptera are the flies. 285 00:14:00,360 --> 00:14:03,610 And most of those pixels need to move north 286 00:14:03,610 --> 00:14:06,750 to reach that species richness analog in the future. 287 00:14:08,290 --> 00:14:11,580 Hymenoptera, bees, ants, et cetera, 288 00:14:11,580 --> 00:14:16,140 their mean is about 1.5 kilometers per year. 289 00:14:16,140 --> 00:14:18,040 That's how far the pixel would need to move 290 00:14:18,040 --> 00:14:20,360 to reach a species analog in the future. 291 00:14:20,360 --> 00:14:23,093 And almost all of those pixels need to move north. 292 00:14:24,650 --> 00:14:26,220 Hemiptera, so the true bugs, 293 00:14:26,220 --> 00:14:30,653 things like cicadas, aphids, plant hoppers and the like, 294 00:14:31,500 --> 00:14:33,763 their mean is about 1.45. 295 00:14:35,190 --> 00:14:38,500 And almost all the cells would need to move 296 00:14:38,500 --> 00:14:39,740 in a northward direction 297 00:14:39,740 --> 00:14:43,780 to meet their species richness analog in the future. 298 00:14:43,780 --> 00:14:47,460 So one thing to take home from this part of the talk 299 00:14:47,460 --> 00:14:52,200 is that all the cell, most of the cells and all the orders 300 00:14:53,493 --> 00:14:54,943 would need to move northward. 301 00:14:56,930 --> 00:14:59,640 Almost all of them, so four of these five groups 302 00:14:59,640 --> 00:15:01,800 are moving almost exclusively north 303 00:15:01,800 --> 00:15:04,150 with the caveat of Lepidoptera. 304 00:15:04,150 --> 00:15:05,670 And that's likely because there are 305 00:15:05,670 --> 00:15:09,050 many, many more species in the Lepidoptera. 306 00:15:09,050 --> 00:15:11,180 There are thousands of species in leps, 307 00:15:11,180 --> 00:15:15,240 so they could be responding slightly differently 308 00:15:15,240 --> 00:15:18,080 than some of the other insect orders here. 309 00:15:18,080 --> 00:15:21,170 So how does velocity differ by forest type? 310 00:15:21,170 --> 00:15:22,640 So I'm gonna skip through here. 311 00:15:22,640 --> 00:15:27,410 The take home here is hat all forests at the top here, 312 00:15:27,410 --> 00:15:30,010 and deciduous forest seems to be moving, 313 00:15:30,010 --> 00:15:32,130 has the fastest climate velocity. 314 00:15:32,130 --> 00:15:33,220 And that pattern holds 315 00:15:33,220 --> 00:15:37,717 for most of all the five orders. 316 00:15:38,890 --> 00:15:40,380 So I wanna get to this slide 317 00:15:40,380 --> 00:15:43,400 where insect velocity is really high across New England. 318 00:15:43,400 --> 00:15:44,920 So where is that happening? 319 00:15:44,920 --> 00:15:48,070 The cool colors represent slower velocity areas. 320 00:15:48,070 --> 00:15:51,060 The high colors or the warm colors 321 00:15:51,060 --> 00:15:53,680 shown here in red. 322 00:15:53,680 --> 00:15:57,890 And I should note that the insect velocity is way higher 323 00:15:57,890 --> 00:16:01,850 than a lot of the other taxa in Western Hemisphere. 324 00:16:01,850 --> 00:16:02,850 Birds are about 0.6. 325 00:16:04,110 --> 00:16:08,240 And here are the 20 insect orders that we looked at. 326 00:16:08,240 --> 00:16:10,010 They're an order of magnitude higher 327 00:16:10,010 --> 00:16:13,700 than birds, amphibians and mammals. 328 00:16:13,700 --> 00:16:15,350 And why might that be? 329 00:16:15,350 --> 00:16:18,680 It's likely because the insects are closely tied to climate. 330 00:16:18,680 --> 00:16:21,010 So they're following the climate velocity faster, 331 00:16:21,010 --> 00:16:24,120 so their development, phenology, their migrations. 332 00:16:24,120 --> 00:16:26,870 And because their life histories are faster, 333 00:16:26,870 --> 00:16:28,822 they may be able to respond faster 334 00:16:28,822 --> 00:16:30,973 to how climate is changing. 335 00:16:32,190 --> 00:16:33,890 How can we use these data? 336 00:16:33,890 --> 00:16:37,850 Well, this is the climate velocity and the protected areas 337 00:16:37,850 --> 00:16:40,300 overlapped on that map. 338 00:16:40,300 --> 00:16:42,680 And you can see there are lots of areas 339 00:16:42,680 --> 00:16:44,380 with slower velocity, 340 00:16:44,380 --> 00:16:46,920 so these cooler colors that are not protected. 341 00:16:46,920 --> 00:16:50,010 And I should note that that's the species richness. 342 00:16:50,010 --> 00:16:51,400 It doesn't necessarily mean 343 00:16:51,400 --> 00:16:54,380 that the community under those cells will be the same. 344 00:16:54,380 --> 00:16:55,870 And so that's the next step. 345 00:16:55,870 --> 00:16:58,440 So where in the landscape will we see 346 00:16:58,440 --> 00:17:01,710 novel communities in the future that we don't see now? 347 00:17:01,710 --> 00:17:03,730 That's the next step that we're gonna take. 348 00:17:03,730 --> 00:17:06,918 And I just wanna, I'd be remiss if I didn't thank 349 00:17:06,918 --> 00:17:10,280 everyone that's submitting observations 350 00:17:10,280 --> 00:17:12,730 to iNaturalist or eButterfly. 351 00:17:12,730 --> 00:17:15,580 This work is only possible because that data are there 352 00:17:15,580 --> 00:17:16,470 and to play with. 353 00:17:16,470 --> 00:17:19,120 So thank you for being curious. 354 00:17:19,120 --> 00:17:20,800 And I just want to say thank you 355 00:17:20,800 --> 00:17:24,650 to all the funders and my collaborators 356 00:17:24,650 --> 00:17:29,340 and coauthors on this that have been helping this process. 357 00:17:29,340 --> 00:17:31,300 So I apologize for going over. 358 00:17:31,300 --> 00:17:32,333 Thank you very much. 359 00:17:34,510 --> 00:17:35,343 - [Tim] Tim Howard here. 360 00:17:35,343 --> 00:17:36,380 This is just a quick question. 361 00:17:36,380 --> 00:17:37,409 Can you hear me? 362 00:17:37,409 --> 00:17:38,242 - Yes. 363 00:17:38,242 --> 00:17:40,510 - [Tim] Yeah. So that's fascinating stuff 364 00:17:40,510 --> 00:17:41,560 and very interesting. 365 00:17:42,860 --> 00:17:45,210 So the velocity was richness to richness. 366 00:17:45,210 --> 00:17:47,280 So if a cell stayed 367 00:17:47,280 --> 00:17:49,390 from a richness of three to a richness of three 368 00:17:49,390 --> 00:17:54,130 but changed the species, that would be a velocity of zero. 369 00:17:54,130 --> 00:17:55,793 Am I my understanding that correct? 370 00:17:56,680 --> 00:17:58,700 And that's why you said, got to look at species next. 371 00:17:58,700 --> 00:17:59,780 Is that what's going on? 372 00:17:59,780 --> 00:18:03,130 - Yeah, so looking at like novel communities in the future 373 00:18:03,130 --> 00:18:03,963 is the next step. 374 00:18:03,963 --> 00:18:07,660 So will we see new communities popping up elsewhere 375 00:18:08,990 --> 00:18:10,260 that we don't see today? 376 00:18:10,260 --> 00:18:12,890 And that will have to involve, you know, 377 00:18:12,890 --> 00:18:15,440 modeling species that could be coming into New England 378 00:18:15,440 --> 00:18:16,690 that aren't currently in New England. 379 00:18:16,690 --> 00:18:20,430 So yes, this is a species richness velocity. 380 00:18:20,430 --> 00:18:22,100 - [Tim] Thank you. 381 00:18:22,100 --> 00:18:23,710 - [Moderator] We had one quick question in the chat, 382 00:18:23,710 --> 00:18:26,100 which is "What was behind the decision 383 00:18:26,100 --> 00:18:27,980 to focus on temperature refugia 384 00:18:27,980 --> 00:18:31,245 versus hydrologic or other gradient refugia?" 385 00:18:31,245 --> 00:18:33,610 - That's a great question. 386 00:18:33,610 --> 00:18:38,320 And the simple answer is that in my former life, 387 00:18:38,320 --> 00:18:40,730 I was at the Climate Research Science Center 388 00:18:40,730 --> 00:18:42,240 and we focused a lot on climate. 389 00:18:42,240 --> 00:18:45,490 And so hydrology changes would be a great thing 390 00:18:45,490 --> 00:18:48,350 to look at, but, you know, I'm very familiar 391 00:18:48,350 --> 00:18:50,610 with how temperature will change. 392 00:18:50,610 --> 00:18:52,660 But adding those type of components will give us 393 00:18:52,660 --> 00:18:56,180 great things to do in the future, 394 00:18:56,180 --> 00:18:58,533 and it would likely be very interesting as well.