1 00:00:06,750 --> 00:00:08,788 - Welcome everyone to the next talk 2 00:00:08,788 --> 00:00:10,623 in our wildlife TREK. 3 00:00:12,380 --> 00:00:17,380 Next, we have Caitlin Drasher who is now a PhD student. 4 00:00:17,990 --> 00:00:20,420 She will be sharing her work as a student with the 5 00:00:20,420 --> 00:00:23,400 Rubenstein School of Environment and Natural Resources. 6 00:00:23,400 --> 00:00:25,103 within the university of Vermont. 7 00:00:26,080 --> 00:00:27,670 The presentation is titled 8 00:00:27,670 --> 00:00:29,820 Where will wildlife cross the road 9 00:00:29,820 --> 00:00:32,070 using electrical circuit analysis 10 00:00:32,070 --> 00:00:33,760 to map wildlife movement 11 00:00:33,760 --> 00:00:37,253 and inform transportation management in Vermont. 12 00:00:38,850 --> 00:00:39,980 - [Caitlin] Hi, my name is Caitlin Drasher 13 00:00:39,980 --> 00:00:43,000 and I'm a graduate student at the University of Vermont. 14 00:00:43,000 --> 00:00:43,980 Today I'll be discussing 15 00:00:43,980 --> 00:00:45,980 a recent conductivity research project 16 00:00:45,980 --> 00:00:48,520 that was completed by multiple partners in Vermont. 17 00:00:48,520 --> 00:00:50,000 We created models and maps 18 00:00:50,000 --> 00:00:51,670 of wildlife movement across the state 19 00:00:51,670 --> 00:00:53,660 using electrical circuit theory 20 00:00:53,660 --> 00:00:55,100 and use these models to inform 21 00:00:55,100 --> 00:00:57,230 the management of transportation infrastructure, 22 00:00:57,230 --> 00:00:59,020 to improve landscape connectivity 23 00:00:59,020 --> 00:01:00,823 for terrestrial mammal species. 24 00:01:02,140 --> 00:01:03,760 First, some quick acknowledgements. 25 00:01:03,760 --> 00:01:04,920 Our research was funded by 26 00:01:04,920 --> 00:01:06,860 the Vermont Agency of Transportation 27 00:01:06,860 --> 00:01:08,240 and as a collaboration between 28 00:01:08,240 --> 00:01:10,670 Glenn Gingras and Chris Slesar at Vtrans. 29 00:01:10,670 --> 00:01:12,170 Paul Marangelo and Ann Ingerson 30 00:01:12,170 --> 00:01:13,293 with The Nature Conservancy in Vermont. 31 00:01:13,293 --> 00:01:16,690 Jens Hilke with the Vermont Fish and Wildlife Department. 32 00:01:16,690 --> 00:01:18,710 And my advisor, Dr. James Murdoch and I 33 00:01:18,710 --> 00:01:20,320 at the University of Vermont. 34 00:01:20,320 --> 00:01:22,770 We also have some additional partners, Dr. Kim Hall 35 00:01:22,770 --> 00:01:24,000 at The Nature Conservancy 36 00:01:24,000 --> 00:01:26,380 and Vincent Landau at Conservation Science Partners 37 00:01:26,380 --> 00:01:28,480 who've been a huge help with this project. 38 00:01:29,535 --> 00:01:31,763 All right, beginning with some regional context 39 00:01:31,763 --> 00:01:34,930 on issues of landscape connectivity in the Northeast. 40 00:01:34,930 --> 00:01:37,710 This map shows the Northern Appalachian Acadian region, 41 00:01:37,710 --> 00:01:40,440 which covers 330,000 square kilometers 42 00:01:40,440 --> 00:01:43,290 through the Northeastern US and Southeastern Canada. 43 00:01:43,290 --> 00:01:45,270 This is a very ecologically rich region 44 00:01:45,270 --> 00:01:46,520 with many habitat types, 45 00:01:46,520 --> 00:01:49,000 critical for supporting wildlife populations 46 00:01:49,000 --> 00:01:51,280 and the movement of wildlife species. 47 00:01:51,280 --> 00:01:53,640 There've been multiple priority linkage areas 48 00:01:53,640 --> 00:01:55,300 identified for wildlife in the region, 49 00:01:55,300 --> 00:01:56,470 like the one shown here from 50 00:01:56,470 --> 00:01:57,920 The Staying Connected Initiative. 51 00:01:57,920 --> 00:02:01,510 And six of these linkage areas fall into parts of Vermont. 52 00:02:01,510 --> 00:02:03,420 So this is a very important region 53 00:02:03,420 --> 00:02:05,680 for maintaining and improving connectivity, 54 00:02:05,680 --> 00:02:07,340 especially as the climate changes 55 00:02:07,340 --> 00:02:09,380 and species begin to shift their ranges 56 00:02:09,380 --> 00:02:12,113 in response to the associated habitat changes. 57 00:02:13,730 --> 00:02:15,280 And some background on connectivity 58 00:02:15,280 --> 00:02:17,340 and transportation issues in Vermont. 59 00:02:17,340 --> 00:02:20,640 We are a very rural state, 78% forested, 60 00:02:20,640 --> 00:02:23,540 but we are not immune to habitat fragmentation. 61 00:02:23,540 --> 00:02:26,610 We have over 25,000 kilometers of road in Vermont 62 00:02:26,610 --> 00:02:28,310 and the public travels an estimated 63 00:02:28,310 --> 00:02:32,010 11.4 billion kilometers annually on our roads. 64 00:02:32,010 --> 00:02:33,910 We also have over 88,000 65 00:02:33,910 --> 00:02:35,980 state managed transportation structures. 66 00:02:35,980 --> 00:02:38,970 So things like culverts, bridges, and underpasses. 67 00:02:38,970 --> 00:02:41,610 Just about 6,000 of these structures are large enough 68 00:02:41,610 --> 00:02:43,230 for some species to pass through 69 00:02:43,230 --> 00:02:45,600 which we'll return to in a minute. 70 00:02:45,600 --> 00:02:47,650 But roads presents some real concerns 71 00:02:47,650 --> 00:02:49,940 for terrestrial wildlife populations. 72 00:02:49,940 --> 00:02:52,260 They can lead to direct mortality for animals 73 00:02:52,260 --> 00:02:53,840 through wildlife vehicle collisions. 74 00:02:53,840 --> 00:02:55,310 And this of course also presents 75 00:02:55,310 --> 00:02:57,070 real threats to humans as well, 76 00:02:57,070 --> 00:02:58,510 since these collisions can be fatal 77 00:02:58,510 --> 00:03:00,310 or cause severe injuries, 78 00:03:00,310 --> 00:03:02,810 and they have a huge economic impact. 79 00:03:02,810 --> 00:03:05,010 Collisions involving large mammals in the US 80 00:03:05,010 --> 00:03:08,510 cost us $8.4 billion annually. 81 00:03:08,510 --> 00:03:11,060 And then in addition to the direct mortality aspect, 82 00:03:11,060 --> 00:03:14,430 roads can also lead to indirect mortality for wildlife. 83 00:03:14,430 --> 00:03:16,660 Fragmentation of habitat prevent species 84 00:03:16,660 --> 00:03:18,990 from accessing important resources. 85 00:03:18,990 --> 00:03:20,790 It can lead to decreased dispersal 86 00:03:20,790 --> 00:03:22,930 and less genetic exchange across the landscape, 87 00:03:22,930 --> 00:03:26,360 which can impact the viability of populations over time. 88 00:03:26,360 --> 00:03:29,300 Again, this is especially a concern as the climate changes 89 00:03:29,300 --> 00:03:32,160 and species undergo rain shifts to follow the habitats 90 00:03:32,160 --> 00:03:33,890 and resources that they depend on 91 00:03:33,890 --> 00:03:36,210 and Vermont has many potential linkage areas 92 00:03:36,210 --> 00:03:37,573 for species movements. 93 00:03:39,500 --> 00:03:42,110 One way to make our road barriers more permeable 94 00:03:42,110 --> 00:03:43,150 for wildlife movement 95 00:03:43,150 --> 00:03:45,060 is through the use of transportation structures 96 00:03:45,060 --> 00:03:47,540 like culverts, bridges, and underpasses. 97 00:03:47,540 --> 00:03:50,360 Thankfully, all road networks have these structures. 98 00:03:50,360 --> 00:03:52,930 Some are already helping wildlife cross the road, 99 00:03:52,930 --> 00:03:54,580 and others have the potential to do this 100 00:03:54,580 --> 00:03:56,320 with some modifications. 101 00:03:56,320 --> 00:03:58,470 So we can do a lot with what we already have, 102 00:03:58,470 --> 00:03:59,370 which is great. 103 00:03:59,370 --> 00:04:01,540 But we do need to work on some of these structures 104 00:04:01,540 --> 00:04:03,510 to make them more wildlife-friendly 105 00:04:03,510 --> 00:04:06,500 and we need to prioritize costly structure improvements 106 00:04:06,500 --> 00:04:10,070 to areas that will most benefit multiple species. 107 00:04:10,070 --> 00:04:12,840 I mentioned that we have about 6,000 structures in Vermont 108 00:04:12,840 --> 00:04:14,130 that are potentially large enough 109 00:04:14,130 --> 00:04:16,300 for some species to cross through. 110 00:04:16,300 --> 00:04:18,350 These are all of the state managed structures 111 00:04:18,350 --> 00:04:21,150 that are greater than three feet in diameter. 112 00:04:21,150 --> 00:04:23,220 So VTrans wanted a way to figure out 113 00:04:23,220 --> 00:04:25,170 which of these structures are most important 114 00:04:25,170 --> 00:04:27,110 for wildlife movement and connectivity. 115 00:04:27,110 --> 00:04:29,860 And in fact, they wanted a way to rank these structures 116 00:04:29,860 --> 00:04:31,510 by their conductivity value 117 00:04:31,510 --> 00:04:33,910 for terrestrial wildlife species. 118 00:04:33,910 --> 00:04:35,190 That way, when a maintenance 119 00:04:35,190 --> 00:04:38,180 or a construction project comes up for a specific structure, 120 00:04:38,180 --> 00:04:39,840 they can look at this list of rankings 121 00:04:39,840 --> 00:04:41,650 and see whether they should prioritize 122 00:04:41,650 --> 00:04:44,283 wildlife focused improvements at that location. 123 00:04:46,030 --> 00:04:49,280 We had eight terrestrial mammal species that we focused on, 124 00:04:49,280 --> 00:04:51,510 bear, moose, deer, coyote, 125 00:04:51,510 --> 00:04:54,660 bobcat, raccoon, red fox, and skunk. 126 00:04:54,660 --> 00:04:57,020 These species were chosen for a few reasons. 127 00:04:57,020 --> 00:04:58,840 They have cultural ecological 128 00:04:58,840 --> 00:05:00,840 and economic importance in Vermont. 129 00:05:00,840 --> 00:05:03,310 The larger body mammals like bear, moose and deer 130 00:05:03,310 --> 00:05:05,140 are especially iconic in our state. 131 00:05:05,140 --> 00:05:07,660 And they're also some of the more wide ranging species 132 00:05:07,660 --> 00:05:09,840 that regularly encounter roadways, 133 00:05:09,840 --> 00:05:12,190 and they're especially dangerous for motorists. 134 00:05:13,550 --> 00:05:15,640 So for these species, the goal of the project 135 00:05:15,640 --> 00:05:17,430 was to assess the conductivity value 136 00:05:17,430 --> 00:05:19,250 of transportation structures in Vermont. 137 00:05:19,250 --> 00:05:22,640 And we developed a terrestrial passage screening tool 138 00:05:22,640 --> 00:05:25,070 to rank structures according to conductivity value 139 00:05:25,070 --> 00:05:27,400 for all species combined. 140 00:05:27,400 --> 00:05:28,980 To do this, we modeled the movements 141 00:05:28,980 --> 00:05:31,290 of those eight species at two spatial scales 142 00:05:31,290 --> 00:05:34,460 using an electrical circuit theory approach. 143 00:05:34,460 --> 00:05:37,010 We also compile data on structure attributes, 144 00:05:37,010 --> 00:05:38,640 human development influence, 145 00:05:38,640 --> 00:05:42,230 and nearby protected lands to include in our rankings. 146 00:05:42,230 --> 00:05:44,210 And finally, we ranked the structures 147 00:05:44,210 --> 00:05:45,215 according to these different metrics 148 00:05:45,215 --> 00:05:49,090 for all species combined using a decision making framework. 149 00:05:49,090 --> 00:05:51,100 So let's walk through each step of this approach, 150 00:05:51,100 --> 00:05:53,000 starting with the conductivity models. 151 00:05:54,710 --> 00:05:57,030 As I mentioned, we used electrical circuit theory 152 00:05:57,030 --> 00:05:59,030 to model wildlife movement. 153 00:05:59,030 --> 00:06:00,790 This method treats the movement of animals, 154 00:06:00,790 --> 00:06:03,510 just like the flow of electricity through a circuit. 155 00:06:03,510 --> 00:06:05,720 The landscape serves as the circuit 156 00:06:05,720 --> 00:06:07,530 and it's made up of different resistances, 157 00:06:07,530 --> 00:06:10,680 which channels the flow of electricity or wildlife 158 00:06:10,680 --> 00:06:13,410 through less resistant paths in the landscape. 159 00:06:13,410 --> 00:06:16,060 In Vermont, this circuit is made up of things like forest, 160 00:06:16,060 --> 00:06:19,320 agriculture, roadways, human development, et cetera. 161 00:06:19,320 --> 00:06:21,800 And each land cover type has its own resistance 162 00:06:21,800 --> 00:06:24,720 associated with the movement of different species. 163 00:06:24,720 --> 00:06:26,120 This is because each species 164 00:06:26,120 --> 00:06:27,990 has different movement behaviors. 165 00:06:27,990 --> 00:06:30,810 For example, the resistance is in the circuit for a deer, 166 00:06:30,810 --> 00:06:34,040 look a bit different than the resistances for a raccoon. 167 00:06:34,040 --> 00:06:35,740 And we used a tool called Omniscape 168 00:06:35,740 --> 00:06:37,250 to model these species movements, 169 00:06:37,250 --> 00:06:40,000 which was developed by folks at the Nature Conservancy. 170 00:06:41,320 --> 00:06:43,610 We modeled the movements of our species individually 171 00:06:43,610 --> 00:06:46,590 using Omniscape at two spatial scales. 172 00:06:46,590 --> 00:06:49,080 First we modeled the broader landscape level movements 173 00:06:49,080 --> 00:06:50,990 of each species throughout Vermont. 174 00:06:50,990 --> 00:06:53,440 An example of that is shown here on the left. 175 00:06:53,440 --> 00:06:55,260 And next we modeled find scale movements 176 00:06:55,260 --> 00:06:57,560 around each individual transportation structure 177 00:06:57,560 --> 00:06:59,830 using high resolution land cover data. 178 00:06:59,830 --> 00:07:01,950 An example of that is shown on the right. 179 00:07:01,950 --> 00:07:03,729 So we have two scales, the landscape scale, 180 00:07:03,729 --> 00:07:05,203 and the structure scale. 181 00:07:06,320 --> 00:07:08,810 I'll walk through a visualization of the modeling process 182 00:07:08,810 --> 00:07:10,530 for both spatial scales. 183 00:07:10,530 --> 00:07:13,730 There are two inputs that we need for Omniscape. 184 00:07:13,730 --> 00:07:16,640 The first input is called the source strength input. 185 00:07:16,640 --> 00:07:18,370 This tells us where the electricity 186 00:07:18,370 --> 00:07:20,693 or wildlife are coming from in the landscape. 187 00:07:21,570 --> 00:07:24,290 The second input is the landscape resistance input, 188 00:07:24,290 --> 00:07:27,090 which represents the resistances in our circuit. 189 00:07:27,090 --> 00:07:28,723 This layer contains land cover variables 190 00:07:28,723 --> 00:07:31,500 that are scored according to their relative resistance 191 00:07:31,500 --> 00:07:34,340 to the movement of the wildlife species. 192 00:07:34,340 --> 00:07:36,610 So Omniscape stacks that resistance map 193 00:07:36,610 --> 00:07:38,630 on top of the source strength map. 194 00:07:38,630 --> 00:07:41,340 The source strength map injects the species electricity 195 00:07:41,340 --> 00:07:42,960 up into that resistance map 196 00:07:42,960 --> 00:07:45,300 and species then travel throughout the landscape 197 00:07:45,300 --> 00:07:46,690 most frequently in areas 198 00:07:46,690 --> 00:07:49,280 where there is lower resistances for them. 199 00:07:49,280 --> 00:07:51,720 Areas of increased predicted wildlife movement 200 00:07:51,720 --> 00:07:54,780 have a higher electrical current density in the output 201 00:07:54,780 --> 00:07:56,830 shown in yellow in the maps on the right. 202 00:07:58,440 --> 00:08:00,120 Digging into those inputs a little bit more 203 00:08:00,120 --> 00:08:02,160 starting with the source-strength layer. 204 00:08:02,160 --> 00:08:03,749 We used existing wildlife occurrence 205 00:08:03,749 --> 00:08:06,050 or occupancy data for this input 206 00:08:06,050 --> 00:08:07,570 to tell us where in the landscape 207 00:08:07,570 --> 00:08:10,100 our species electricity is coming from. 208 00:08:10,100 --> 00:08:12,140 These data are from Pearman-Gillman et al, 209 00:08:12,140 --> 00:08:14,331 and resulted from an extensive expert opinion survey 210 00:08:14,331 --> 00:08:16,900 across the Northeastern US. 211 00:08:16,900 --> 00:08:19,690 The occupancy maps tell us the probability of occurrence 212 00:08:19,690 --> 00:08:22,950 of a given species in each pixel of the landscape. 213 00:08:22,950 --> 00:08:24,370 In Omniscape this determines 214 00:08:24,370 --> 00:08:26,940 where the electricity is coming from in the landscape, 215 00:08:26,940 --> 00:08:28,560 but also how much electricity 216 00:08:28,560 --> 00:08:30,840 is coming out of those locations. 217 00:08:30,840 --> 00:08:32,485 The electricity output is proportional 218 00:08:32,485 --> 00:08:35,510 to the occupancy probability in the pixel. 219 00:08:35,510 --> 00:08:38,350 For example, a pixel with a 90% probability 220 00:08:38,350 --> 00:08:41,170 of deer occurrence would admit more electricity 221 00:08:41,170 --> 00:08:44,403 than a pixel with only 20% probability of occurrence. 222 00:08:45,930 --> 00:08:48,350 Next, we have the landscape resistance layer. 223 00:08:48,350 --> 00:08:49,260 This layer tells us 224 00:08:49,260 --> 00:08:51,680 how the electricity moves around the landscape 225 00:08:51,680 --> 00:08:53,660 based on the composition and the resistance 226 00:08:53,660 --> 00:08:56,910 of different land cover types to movement of each species. 227 00:08:56,910 --> 00:08:59,300 Resistance layers can be created in multiple ways, 228 00:08:59,300 --> 00:09:01,970 but due to a lack of empirical wildlife movement data 229 00:09:01,970 --> 00:09:03,800 for all of these species in Vermont, 230 00:09:03,800 --> 00:09:05,870 we decided to use expert elicitation 231 00:09:05,870 --> 00:09:08,890 to get at these values for each of the eight species. 232 00:09:08,890 --> 00:09:11,200 We reached out to 10 regional wildlife experts 233 00:09:11,200 --> 00:09:14,100 and use the following approach to collect resistance data. 234 00:09:14,950 --> 00:09:17,600 We began with an online expert opinion survey. 235 00:09:17,600 --> 00:09:20,420 Experts scored the resistances of each land cover type 236 00:09:20,420 --> 00:09:22,850 to the movement of the species they have expertise in 237 00:09:22,850 --> 00:09:24,730 on a one-to-one hundred scale 238 00:09:24,730 --> 00:09:26,970 with 100 representing the highest resistance 239 00:09:26,970 --> 00:09:29,000 to the movement of their species. 240 00:09:29,000 --> 00:09:31,670 Since we're creating models at two spatial scales, 241 00:09:31,670 --> 00:09:34,150 experts first scored land cover variables 242 00:09:34,150 --> 00:09:36,840 in the 30 meter resolution and NLCD dataset 243 00:09:36,840 --> 00:09:39,780 for our broader landscape scale models. 244 00:09:39,780 --> 00:09:41,950 And then variables in the half meter Vermont 245 00:09:41,950 --> 00:09:43,660 high resolution land cover data set 246 00:09:43,660 --> 00:09:45,583 for use in our structure scale models. 247 00:09:46,630 --> 00:09:49,640 Next we average the expert values for each species 248 00:09:49,640 --> 00:09:52,120 and assign those averages to land cover variables 249 00:09:52,120 --> 00:09:53,610 in each dataset. 250 00:09:53,610 --> 00:09:56,280 We use these first drafts of the resistance inputs 251 00:09:56,280 --> 00:09:58,220 to run preliminary Omniscape models 252 00:09:58,220 --> 00:10:01,403 for the landscape and structure scales for each species. 253 00:10:02,430 --> 00:10:05,560 We then had one-on-one follow-up meetings with each expert 254 00:10:05,560 --> 00:10:08,140 to present these first drafts of the Omniscape maps 255 00:10:08,140 --> 00:10:10,598 and get feedback on whether they thought them to be accurate 256 00:10:10,598 --> 00:10:12,710 for their species in Vermont. 257 00:10:12,710 --> 00:10:14,630 Experts were then given one opportunity 258 00:10:14,630 --> 00:10:17,530 to rescore variables if they felt the maps could be improved 259 00:10:17,530 --> 00:10:20,150 to better represent the movement of their species. 260 00:10:20,150 --> 00:10:22,110 Final resistance layers were then created 261 00:10:22,110 --> 00:10:24,973 with these updated average values from the experts. 262 00:10:26,570 --> 00:10:28,920 All right, so when we combine those source strength 263 00:10:28,920 --> 00:10:30,220 and resistance inputs, 264 00:10:30,220 --> 00:10:32,550 here are what the final Omniscape maps look like 265 00:10:32,550 --> 00:10:35,520 for each species individually at the landscape scale, 266 00:10:35,520 --> 00:10:37,970 with all species combined on the right. 267 00:10:37,970 --> 00:10:40,000 To summarize these landscape scale results, 268 00:10:40,000 --> 00:10:41,590 we calculated the average amount 269 00:10:41,590 --> 00:10:43,080 of electrical current density 270 00:10:43,080 --> 00:10:46,200 in a one kilometer radius of each transportation structure 271 00:10:46,200 --> 00:10:48,810 from each of the individual species maps. 272 00:10:48,810 --> 00:10:51,580 Then we added those species specific averages together 273 00:10:51,580 --> 00:10:54,503 to combine results into a single all species result. 274 00:10:56,500 --> 00:10:58,570 Then we also ran those high resolution 275 00:10:58,570 --> 00:11:00,150 structure-scale models. 276 00:11:00,150 --> 00:11:02,900 For these, we ran Omniscape in a 100 meter radius 277 00:11:02,900 --> 00:11:04,620 of each structure, and again, 278 00:11:04,620 --> 00:11:06,700 took the average electrical current density 279 00:11:06,700 --> 00:11:09,280 for each species, summing the averages together 280 00:11:09,280 --> 00:11:12,110 for an all species result at each structure. 281 00:11:12,110 --> 00:11:13,260 We ran these models on the 282 00:11:13,260 --> 00:11:15,550 BlueMoon cluster of the supercomputer at UVM, 283 00:11:15,550 --> 00:11:18,620 since they were a bit more computationally intensive. 284 00:11:18,620 --> 00:11:20,630 These high resolution models really capture 285 00:11:20,630 --> 00:11:23,320 some fine scale habitats that species will move through 286 00:11:23,320 --> 00:11:25,690 that are not captured at the 30 meter resolution 287 00:11:25,690 --> 00:11:27,340 from the landscape scale. 288 00:11:27,340 --> 00:11:29,540 For example, bobcat's will often travel 289 00:11:29,540 --> 00:11:32,370 along narrow hedgerows and agricultural areas. 290 00:11:32,370 --> 00:11:33,930 And we were able to visualize 291 00:11:33,930 --> 00:11:35,610 potential movement along hedgerows 292 00:11:35,610 --> 00:11:37,963 by using this fine scale land cover data. 293 00:11:39,810 --> 00:11:41,410 All right, so that was a lot of information 294 00:11:41,410 --> 00:11:42,630 about our connectivity models, 295 00:11:42,630 --> 00:11:45,140 but I also want to quickly mention a few other metrics 296 00:11:45,140 --> 00:11:47,090 included in our rankings. 297 00:11:47,090 --> 00:11:49,990 We completed additional analysis to help rank structures, 298 00:11:49,990 --> 00:11:51,740 and these were really spearheaded by folks 299 00:11:51,740 --> 00:11:53,840 at The Nature Conservancy in Vermont. 300 00:11:53,840 --> 00:11:56,590 They compile data on attributes important for wildlife 301 00:11:56,590 --> 00:11:59,630 like structure length and bankfull width ratio. 302 00:11:59,630 --> 00:12:02,270 They also calculated the influence of human development 303 00:12:02,270 --> 00:12:03,430 surrounding structures, 304 00:12:03,430 --> 00:12:05,940 buffering 50 meters around each building footprint 305 00:12:05,940 --> 00:12:07,370 to account for human activity 306 00:12:07,370 --> 00:12:10,740 around more than just the building footprints themselves. 307 00:12:10,740 --> 00:12:12,160 And finally, we calculated 308 00:12:12,160 --> 00:12:15,180 the amount of protected lands around structures. 309 00:12:15,180 --> 00:12:16,660 This is of interest since these lands 310 00:12:16,660 --> 00:12:19,620 will likely not experience human development through time. 311 00:12:19,620 --> 00:12:21,150 So structures that are surrounded 312 00:12:21,150 --> 00:12:22,870 by large blocks of protected lands 313 00:12:22,870 --> 00:12:24,090 will be especially valuable 314 00:12:24,090 --> 00:12:26,190 for wildlife conductivity into the future. 315 00:12:27,850 --> 00:12:29,470 All of these data then feed into 316 00:12:29,470 --> 00:12:31,930 our terrestrial passage screening tool. 317 00:12:31,930 --> 00:12:35,010 The tool is user-friendly, it's built in Microsoft Excel 318 00:12:35,010 --> 00:12:36,920 and it's formatted as a linear programming 319 00:12:36,920 --> 00:12:38,630 decision-making framework. 320 00:12:38,630 --> 00:12:41,800 This spreadsheet takes in the raw data from each analysis, 321 00:12:41,800 --> 00:12:44,870 normalizes the data so that it's all on the same scale 322 00:12:44,870 --> 00:12:46,780 and then uses the normalized results 323 00:12:46,780 --> 00:12:48,810 to rank structures in three different ways 324 00:12:48,810 --> 00:12:51,280 to inform management actions. 325 00:12:51,280 --> 00:12:53,410 The first wildlife movement priority rank 326 00:12:53,410 --> 00:12:56,630 is the most important one for considering wildlife movement. 327 00:12:56,630 --> 00:12:57,600 It includes the results 328 00:12:57,600 --> 00:12:59,940 from the connectivity analysis at both scales, 329 00:12:59,940 --> 00:13:03,000 as well as the human development influence metric. 330 00:13:03,000 --> 00:13:04,640 This rank tells us whether a structure 331 00:13:04,640 --> 00:13:06,910 is a priority for wildlife movement. 332 00:13:06,910 --> 00:13:08,450 If a structure scores well here, 333 00:13:08,450 --> 00:13:10,860 it could be a good candidate for wildlife improvements 334 00:13:10,860 --> 00:13:12,240 because wildlife are predicted 335 00:13:12,240 --> 00:13:14,003 to move in the vicinity of it. 336 00:13:15,000 --> 00:13:17,610 But we also included two additional ranks. 337 00:13:17,610 --> 00:13:19,740 This second structure characteristics rank 338 00:13:19,740 --> 00:13:22,240 evaluates the condition of the structure for wildlife 339 00:13:22,240 --> 00:13:24,270 based on the length and bankfull width with ratio 340 00:13:24,270 --> 00:13:25,670 of the structure. 341 00:13:25,670 --> 00:13:27,360 If the structure scores poorly here, 342 00:13:27,360 --> 00:13:28,960 it likely needs some updates 343 00:13:28,960 --> 00:13:31,610 to make it more wildlife friendly. 344 00:13:31,610 --> 00:13:33,610 And then this third protected lands rank 345 00:13:33,610 --> 00:13:36,070 assesses the amount and location of protected lands 346 00:13:36,070 --> 00:13:37,660 around each structure. 347 00:13:37,660 --> 00:13:39,790 Structures with large blocks of protected land 348 00:13:39,790 --> 00:13:41,220 on both sides of the roadway 349 00:13:41,220 --> 00:13:43,010 would receive the best score here. 350 00:13:43,010 --> 00:13:44,912 And these locations would be especially beneficial 351 00:13:44,912 --> 00:13:46,963 for wildlife movement through time. 352 00:13:47,800 --> 00:13:50,300 These three rankings ultimately provide information 353 00:13:50,300 --> 00:13:52,540 on wildlife movements, structure condition, 354 00:13:52,540 --> 00:13:53,890 and nearby protected lands 355 00:13:53,890 --> 00:13:56,620 that will help transportation managers make decisions 356 00:13:56,620 --> 00:13:58,993 about the placement of wildlife improvements. 357 00:14:00,630 --> 00:14:03,090 And here are the top 100 structure locations 358 00:14:03,090 --> 00:14:06,040 just for that first wildlife movement priority rank. 359 00:14:06,040 --> 00:14:07,600 These are some of the places where wildlife 360 00:14:07,600 --> 00:14:09,460 are most likely to encounter a structure 361 00:14:09,460 --> 00:14:11,340 based on their movement patterns. 362 00:14:11,340 --> 00:14:13,640 This map also does not include any adjustments 363 00:14:13,640 --> 00:14:14,900 to weights or constraints, 364 00:14:14,900 --> 00:14:17,710 which we included options for in the tool spreadsheet, 365 00:14:17,710 --> 00:14:20,150 in case managers want to rank a subset of structures 366 00:14:20,150 --> 00:14:22,710 or emphasize certain analyses with weights. 367 00:14:22,710 --> 00:14:24,830 So this is just a basic ranking of structures 368 00:14:24,830 --> 00:14:26,193 without any adjustments. 369 00:14:28,070 --> 00:14:30,770 Our project partners also collected wildlife camera data 370 00:14:30,770 --> 00:14:32,760 through multiple phases of the project 371 00:14:32,760 --> 00:14:36,130 at 52 structure locations beginning in 2015, 372 00:14:36,130 --> 00:14:39,580 and they recorded species detections at these locations. 373 00:14:39,580 --> 00:14:41,180 Circuit based conductivity models 374 00:14:41,180 --> 00:14:43,900 are challenging to validate and it's rarely done, 375 00:14:43,900 --> 00:14:46,360 but we use the species detections from structures 376 00:14:46,360 --> 00:14:48,990 where we had cameras to check our connectivity scores 377 00:14:48,990 --> 00:14:50,520 at these locations. 378 00:14:50,520 --> 00:14:52,900 The probability presence was relatively high 379 00:14:52,900 --> 00:14:54,430 across all camera locations 380 00:14:54,430 --> 00:14:56,350 for both ungulate and carnivore groups. 381 00:14:56,350 --> 00:14:58,280 And this made sense based on the relatively 382 00:14:58,280 --> 00:15:01,190 high landscape scale and structure scale conductivity scores 383 00:15:01,190 --> 00:15:02,963 across these camera locations. 384 00:15:04,650 --> 00:15:07,730 So what will these structure rankings actually lead to? 385 00:15:07,730 --> 00:15:09,410 There are many different things that we can do 386 00:15:09,410 --> 00:15:13,050 to make structures more appealing and usable for wildlife. 387 00:15:13,050 --> 00:15:15,170 For example, if Vtrans might decide to change 388 00:15:15,170 --> 00:15:17,050 the substrate of the structure. 389 00:15:17,050 --> 00:15:18,960 This image here shows a bridge location 390 00:15:18,960 --> 00:15:21,860 that has some large boulders as that movement surface. 391 00:15:21,860 --> 00:15:23,710 And while this is great for this groundhog 392 00:15:23,710 --> 00:15:25,060 who actually lived in this location 393 00:15:25,060 --> 00:15:26,640 amongst all of these rocks, 394 00:15:26,640 --> 00:15:28,430 it's not so great for deer, 395 00:15:28,430 --> 00:15:30,260 which sometimes choose to walk through rivers 396 00:15:30,260 --> 00:15:31,930 instead of over boulders. 397 00:15:31,930 --> 00:15:33,560 So to improve a structure for deer, 398 00:15:33,560 --> 00:15:35,540 we can fill this in with other materials 399 00:15:35,540 --> 00:15:38,530 so that there is a more even surface to walk on. 400 00:15:38,530 --> 00:15:39,363 On the other hand, 401 00:15:39,363 --> 00:15:41,660 if there is a lot of water going through a structure, 402 00:15:41,660 --> 00:15:44,130 bobcat sometimes opt to use shelves 403 00:15:44,130 --> 00:15:47,010 that allow them to pass without walking through the water. 404 00:15:47,010 --> 00:15:48,490 So this is something that could be added 405 00:15:48,490 --> 00:15:50,300 to structures as well. 406 00:15:50,300 --> 00:15:51,740 Those are just a couple of examples 407 00:15:51,740 --> 00:15:53,330 of what can be done with these rankings. 408 00:15:53,330 --> 00:15:56,360 And again, the ultimate goal is to prioritize investments 409 00:15:56,360 --> 00:15:57,610 in these improvements, 410 00:15:57,610 --> 00:16:00,530 to the locations that are actually seeing wildlife movements 411 00:16:00,530 --> 00:16:02,720 that there'll be used and have the greatest benefit 412 00:16:02,720 --> 00:16:04,143 for landscape connectivity. 413 00:16:05,524 --> 00:16:06,970 All right, that's all I have. 414 00:16:06,970 --> 00:16:07,930 Thank you for listening. 415 00:16:07,930 --> 00:16:09,360 I'm happy to take any questions 416 00:16:09,360 --> 00:16:10,690 or you can feel free to email me 417 00:16:10,690 --> 00:16:12,490 with any questions that you might have later. 418 00:16:12,490 --> 00:16:13,323 Thank you. 419 00:16:15,120 --> 00:16:15,953 - Wonderful. 420 00:16:15,953 --> 00:16:16,786 Thank you, Caitlin. 421 00:16:16,786 --> 00:16:18,113 Some great stuff there. 422 00:16:19,181 --> 00:16:20,793 - I'm happy to take any questions. 423 00:16:22,610 --> 00:16:25,600 - There's one in the chat right now from Jeffrey Ward. 424 00:16:25,600 --> 00:16:28,500 Did resistance include locating food? 425 00:16:28,500 --> 00:16:30,430 I would think animals might not continue 426 00:16:30,430 --> 00:16:33,133 in a general direction if no food was found. 427 00:16:34,010 --> 00:16:36,540 - Yeah, that's a really great question. 428 00:16:36,540 --> 00:16:40,160 So one of the inputs in our models that occupancy input 429 00:16:41,140 --> 00:16:43,060 that tells us the probability of occurrence 430 00:16:43,060 --> 00:16:45,200 of a given species is more, 431 00:16:45,200 --> 00:16:50,050 that's more what considers the day-to-day habits of animals 432 00:16:50,050 --> 00:16:51,970 in terms of the areas that they're occupying. 433 00:16:51,970 --> 00:16:55,462 So those models more considered the food aspect 434 00:16:55,462 --> 00:16:56,950 and the land cover types 435 00:16:56,950 --> 00:16:59,310 that provide food for those different species. 436 00:16:59,310 --> 00:17:01,740 movement behaviors can sometimes differ 437 00:17:01,740 --> 00:17:04,690 than their normal occupancy behaviors. 438 00:17:04,690 --> 00:17:05,910 So our movement maps, 439 00:17:05,910 --> 00:17:07,620 they're kind of starting from those locations 440 00:17:07,620 --> 00:17:08,900 where they have food, 441 00:17:08,900 --> 00:17:11,334 and then we asked our experts 442 00:17:11,334 --> 00:17:13,390 to score those resistance values, 443 00:17:13,390 --> 00:17:15,870 according to the movement behavior of the species 444 00:17:15,870 --> 00:17:16,990 that they have expertise in. 445 00:17:16,990 --> 00:17:21,150 So they would have been considering things like, you know, 446 00:17:21,150 --> 00:17:23,480 how their species typically moves across the landscape 447 00:17:23,480 --> 00:17:25,270 and whether or not it's a food driven movement 448 00:17:25,270 --> 00:17:28,430 like for bears, it definitely is a lot of times 449 00:17:28,430 --> 00:17:29,410 compared to other species, 450 00:17:29,410 --> 00:17:31,440 they all have different movement behavior. 451 00:17:31,440 --> 00:17:33,690 Hopefully that kind of answers that question. 452 00:17:34,836 --> 00:17:35,840 - We have another one. 453 00:17:35,840 --> 00:17:37,350 As structures are improved, 454 00:17:37,350 --> 00:17:39,020 does that reduce their resistance value 455 00:17:39,020 --> 00:17:41,150 and does that get remodeled? 456 00:17:41,150 --> 00:17:43,102 - Another great question. 457 00:17:43,102 --> 00:17:43,935 Yeah. 458 00:17:43,935 --> 00:17:46,360 So in our tool spreadsheet, 459 00:17:46,360 --> 00:17:48,140 we do have another column 460 00:17:48,140 --> 00:17:50,390 where the transportation managers will make a note 461 00:17:50,390 --> 00:17:51,975 of whether or not that structure got worked on 462 00:17:51,975 --> 00:17:53,430 and improved for wildlife, 463 00:17:53,430 --> 00:17:57,110 so it won't repeatedly be considered in the rankings. 464 00:17:57,110 --> 00:18:00,830 So yeah, it doesn't get remodeled unfortunately. 465 00:18:00,830 --> 00:18:01,663 Some of these models 466 00:18:01,663 --> 00:18:03,510 are really computationally intensive to run, 467 00:18:03,510 --> 00:18:07,330 especially those fine scale high resolution land 468 00:18:07,330 --> 00:18:09,470 cover structure scale models. 469 00:18:09,470 --> 00:18:11,840 I think those took about four days to run per species 470 00:18:11,840 --> 00:18:12,710 on the supercomputer. 471 00:18:12,710 --> 00:18:15,562 So those won't be getting remodeled anytime soon. 472 00:18:15,562 --> 00:18:17,610 But managers are making a note of 473 00:18:17,610 --> 00:18:19,083 when they work on structures. 474 00:18:20,150 --> 00:18:20,983 - All right. 475 00:18:20,983 --> 00:18:24,173 And just real quickly. 476 00:18:25,490 --> 00:18:28,910 Are these maps available for download 477 00:18:28,910 --> 00:18:31,119 and are there analysis for small species 478 00:18:31,119 --> 00:18:33,792 such as amphibians and reptiles? 479 00:18:33,792 --> 00:18:35,720 - Great, yeah. 480 00:18:35,720 --> 00:18:38,380 I'm gonna try to find our Vtrans project page. 481 00:18:38,380 --> 00:18:39,460 I should've had that link ready. 482 00:18:39,460 --> 00:18:40,710 I'll put that in the chat. 483 00:18:40,710 --> 00:18:42,950 But we just published our final report, 484 00:18:42,950 --> 00:18:44,080 which is on the 485 00:18:44,080 --> 00:18:47,020 Vermont Agency of Transportation's research page. 486 00:18:47,020 --> 00:18:48,330 So I'll try to find a link for that, 487 00:18:48,330 --> 00:18:50,223 and that map is in that final report. 488 00:18:51,546 --> 00:18:54,850 And other species like amphibians and reptiles. 489 00:18:54,850 --> 00:18:55,683 Yeah. 490 00:18:55,683 --> 00:18:58,380 I'm more of a mammal person in terms of my expertise, 491 00:18:58,380 --> 00:18:59,830 but those are, 492 00:18:59,830 --> 00:19:02,220 you could definitely model some of those species. 493 00:19:02,220 --> 00:19:04,490 I think those models would look a lot different 494 00:19:04,490 --> 00:19:07,320 just based on how far they can move in the landscape 495 00:19:07,320 --> 00:19:08,990 and the areas that they're occupying. 496 00:19:08,990 --> 00:19:11,770 So for this project, 497 00:19:11,770 --> 00:19:13,930 the focus was more the larger bodied species 498 00:19:13,930 --> 00:19:16,320 that pose a big danger to motorists 499 00:19:16,320 --> 00:19:18,230 that are traveling great distances 500 00:19:18,230 --> 00:19:19,810 and most frequently encountering roads. 501 00:19:19,810 --> 00:19:22,290 But I think that would be a great next step 502 00:19:22,290 --> 00:19:24,240 looking at some of those other species. 503 00:19:25,258 --> 00:19:27,600 - And then any considerations for restricting 504 00:19:27,600 --> 00:19:29,223 specific animal movement. 505 00:19:32,320 --> 00:19:34,480 - I'm not sure if I'm interpreting this question correctly, 506 00:19:34,480 --> 00:19:37,340 but there was another component in the model 507 00:19:37,340 --> 00:19:39,330 that I left out because of time. 508 00:19:39,330 --> 00:19:41,580 But for each species, 509 00:19:41,580 --> 00:19:43,140 the movements of the electricity 510 00:19:43,140 --> 00:19:45,580 from any source location in the landscape 511 00:19:45,580 --> 00:19:47,350 is constrained by the average 512 00:19:47,350 --> 00:19:49,520 home range size of each species. 513 00:19:49,520 --> 00:19:52,470 So the electricity can't just come out of one location 514 00:19:52,470 --> 00:19:54,760 and travel all the way across the state necessarily 515 00:19:54,760 --> 00:19:57,810 unless that species has a huge home range size. 516 00:19:57,810 --> 00:19:59,520 So the movements in the models 517 00:19:59,520 --> 00:20:02,610 are a little bit constricted or restricted. 518 00:20:02,610 --> 00:20:03,930 But I'm not sure if I was interpreting 519 00:20:03,930 --> 00:20:05,623 your question correctly, Jim. 520 00:20:07,517 --> 00:20:08,350 - All right. 521 00:20:08,350 --> 00:20:09,973 Well, thank you, Caitlin. 522 00:20:09,973 --> 00:20:10,973 - Thank you.