- Welcome everyone to the next talk
in our wildlife TREK.
Next, we have Caitlin Drasher who is now a PhD student.
She will be sharing her work as a student with the
Rubenstein School of Environment and Natural Resources.
within the university of Vermont.
The presentation is titled
Where will wildlife cross the road
using electrical circuit analysis
to map wildlife movement
and inform transportation management in Vermont.
- [Caitlin] Hi, my name is Caitlin Drasher
and I'm a graduate student at the University of Vermont.
Today I'll be discussing
a recent conductivity research project
that was completed by multiple partners in Vermont.
We created models and maps
of wildlife movement across the state
using electrical circuit theory
and use these models to inform
the management of transportation infrastructure,
to improve landscape connectivity
for terrestrial mammal species.
First, some quick acknowledgements.
Our research was funded by
the Vermont Agency of Transportation
and as a collaboration between
Glenn Gingras and Chris Slesar at Vtrans.
Paul Marangelo and Ann Ingerson
with The Nature Conservancy in Vermont.
Jens Hilke with the Vermont Fish and Wildlife Department.
And my advisor, Dr. James Murdoch and I
at the University of Vermont.
We also have some additional partners, Dr. Kim Hall
at The Nature Conservancy
and Vincent Landau at Conservation Science Partners
who've been a huge help with this project.
All right, beginning with some regional context
on issues of landscape connectivity in the Northeast.
This map shows the Northern Appalachian Acadian region,
which covers 330,000 square kilometers
through the Northeastern US and Southeastern Canada.
This is a very ecologically rich region
with many habitat types,
critical for supporting wildlife populations
and the movement of wildlife species.
There've been multiple priority linkage areas
identified for wildlife in the region,
like the one shown here from
The Staying Connected Initiative.
And six of these linkage areas fall into parts of Vermont.
So this is a very important region
for maintaining and improving connectivity,
especially as the climate changes
and species begin to shift their ranges
in response to the associated habitat changes.
And some background on connectivity
and transportation issues in Vermont.
We are a very rural state, 78% forested,
but we are not immune to habitat fragmentation.
We have over 25,000 kilometers of road in Vermont
and the public travels an estimated
11.4 billion kilometers annually on our roads.
We also have over 88,000
state managed transportation structures.
So things like culverts, bridges, and underpasses.
Just about 6,000 of these structures are large enough
for some species to pass through
which we'll return to in a minute.
But roads presents some real concerns
for terrestrial wildlife populations.
They can lead to direct mortality for animals
through wildlife vehicle collisions.
And this of course also presents
real threats to humans as well,
since these collisions can be fatal
or cause severe injuries,
and they have a huge economic impact.
Collisions involving large mammals in the US
cost us $8.4 billion annually.
And then in addition to the direct mortality aspect,
roads can also lead to indirect mortality for wildlife.
Fragmentation of habitat prevent species
from accessing important resources.
It can lead to decreased dispersal
and less genetic exchange across the landscape,
which can impact the viability of populations over time.
Again, this is especially a concern as the climate changes
and species undergo rain shifts to follow the habitats
and resources that they depend on
and Vermont has many potential linkage areas
for species movements.
One way to make our road barriers more permeable
for wildlife movement
is through the use of transportation structures
like culverts, bridges, and underpasses.
Thankfully, all road networks have these structures.
Some are already helping wildlife cross the road,
and others have the potential to do this
with some modifications.
So we can do a lot with what we already have,
which is great.
But we do need to work on some of these structures
to make them more wildlife-friendly
and we need to prioritize costly structure improvements
to areas that will most benefit multiple species.
I mentioned that we have about 6,000 structures in Vermont
that are potentially large enough
for some species to cross through.
These are all of the state managed structures
that are greater than three feet in diameter.
So VTrans wanted a way to figure out
which of these structures are most important
for wildlife movement and connectivity.
And in fact, they wanted a way to rank these structures
by their conductivity value
for terrestrial wildlife species.
That way, when a maintenance
or a construction project comes up for a specific structure,
they can look at this list of rankings
and see whether they should prioritize
wildlife focused improvements at that location.
We had eight terrestrial mammal species that we focused on,
bear, moose, deer, coyote,
bobcat, raccoon, red fox, and skunk.
These species were chosen for a few reasons.
They have cultural ecological
and economic importance in Vermont.
The larger body mammals like bear, moose and deer
are especially iconic in our state.
And they're also some of the more wide ranging species
that regularly encounter roadways,
and they're especially dangerous for motorists.
So for these species, the goal of the project
was to assess the conductivity value
of transportation structures in Vermont.
And we developed a terrestrial passage screening tool
to rank structures according to conductivity value
for all species combined.
To do this, we modeled the movements
of those eight species at two spatial scales
using an electrical circuit theory approach.
We also compile data on structure attributes,
human development influence,
and nearby protected lands to include in our rankings.
And finally, we ranked the structures
according to these different metrics
for all species combined using a decision making framework.
So let's walk through each step of this approach,
starting with the conductivity models.
As I mentioned, we used electrical circuit theory
to model wildlife movement.
This method treats the movement of animals,
just like the flow of electricity through a circuit.
The landscape serves as the circuit
and it's made up of different resistances,
which channels the flow of electricity or wildlife
through less resistant paths in the landscape.
In Vermont, this circuit is made up of things like forest,
agriculture, roadways, human development, et cetera.
And each land cover type has its own resistance
associated with the movement of different species.
This is because each species
has different movement behaviors.
For example, the resistance is in the circuit for a deer,
look a bit different than the resistances for a raccoon.
And we used a tool called Omniscape
to model these species movements,
which was developed by folks at the Nature Conservancy.
We modeled the movements of our species individually
using Omniscape at two spatial scales.
First we modeled the broader landscape level movements
of each species throughout Vermont.
An example of that is shown here on the left.
And next we modeled find scale movements
around each individual transportation structure
using high resolution land cover data.
An example of that is shown on the right.
So we have two scales, the landscape scale,
and the structure scale.
I'll walk through a visualization of the modeling process
for both spatial scales.
There are two inputs that we need for Omniscape.
The first input is called the source strength input.
This tells us where the electricity
or wildlife are coming from in the landscape.
The second input is the landscape resistance input,
which represents the resistances in our circuit.
This layer contains land cover variables
that are scored according to their relative resistance
to the movement of the wildlife species.
So Omniscape stacks that resistance map
on top of the source strength map.
The source strength map injects the species electricity
up into that resistance map
and species then travel throughout the landscape
most frequently in areas
where there is lower resistances for them.
Areas of increased predicted wildlife movement
have a higher electrical current density in the output
shown in yellow in the maps on the right.
Digging into those inputs a little bit more
starting with the source-strength layer.
We used existing wildlife occurrence
or occupancy data for this input
to tell us where in the landscape
our species electricity is coming from.
These data are from Pearman-Gillman et al,
and resulted from an extensive expert opinion survey
across the Northeastern US.
The occupancy maps tell us the probability of occurrence
of a given species in each pixel of the landscape.
In Omniscape this determines
where the electricity is coming from in the landscape,
but also how much electricity
is coming out of those locations.
The electricity output is proportional
to the occupancy probability in the pixel.
For example, a pixel with a 90% probability
of deer occurrence would admit more electricity
than a pixel with only 20% probability of occurrence.
Next, we have the landscape resistance layer.
This layer tells us
how the electricity moves around the landscape
based on the composition and the resistance
of different land cover types to movement of each species.
Resistance layers can be created in multiple ways,
but due to a lack of empirical wildlife movement data
for all of these species in Vermont,
we decided to use expert elicitation
to get at these values for each of the eight species.
We reached out to 10 regional wildlife experts
and use the following approach to collect resistance data.
We began with an online expert opinion survey.
Experts scored the resistances of each land cover type
to the movement of the species they have expertise in
on a one-to-one hundred scale
with 100 representing the highest resistance
to the movement of their species.
Since we're creating models at two spatial scales,
experts first scored land cover variables
in the 30 meter resolution and NLCD dataset
for our broader landscape scale models.
And then variables in the half meter Vermont
high resolution land cover data set
for use in our structure scale models.
Next we average the expert values for each species
and assign those averages to land cover variables
in each dataset.
We use these first drafts of the resistance inputs
to run preliminary Omniscape models
for the landscape and structure scales for each species.
We then had one-on-one follow-up meetings with each expert
to present these first drafts of the Omniscape maps
and get feedback on whether they thought them to be accurate
for their species in Vermont.
Experts were then given one opportunity
to rescore variables if they felt the maps could be improved
to better represent the movement of their species.
Final resistance layers were then created
with these updated average values from the experts.
All right, so when we combine those source strength
and resistance inputs,
here are what the final Omniscape maps look like
for each species individually at the landscape scale,
with all species combined on the right.
To summarize these landscape scale results,
we calculated the average amount
of electrical current density
in a one kilometer radius of each transportation structure
from each of the individual species maps.
Then we added those species specific averages together
to combine results into a single all species result.
Then we also ran those high resolution
structure-scale models.
For these, we ran Omniscape in a 100 meter radius
of each structure, and again,
took the average electrical current density
for each species, summing the averages together
for an all species result at each structure.
We ran these models on the
BlueMoon cluster of the supercomputer at UVM,
since they were a bit more computationally intensive.
These high resolution models really capture
some fine scale habitats that species will move through
that are not captured at the 30 meter resolution
from the landscape scale.
For example, bobcat's will often travel
along narrow hedgerows and agricultural areas.
And we were able to visualize
potential movement along hedgerows
by using this fine scale land cover data.
All right, so that was a lot of information
about our connectivity models,
but I also want to quickly mention a few other metrics
included in our rankings.
We completed additional analysis to help rank structures,
and these were really spearheaded by folks
at The Nature Conservancy in Vermont.
They compile data on attributes important for wildlife
like structure length and bankfull width ratio.
They also calculated the influence of human development
surrounding structures,
buffering 50 meters around each building footprint
to account for human activity
around more than just the building footprints themselves.
And finally, we calculated
the amount of protected lands around structures.
This is of interest since these lands
will likely not experience human development through time.
So structures that are surrounded
by large blocks of protected lands
will be especially valuable
for wildlife conductivity into the future.
All of these data then feed into
our terrestrial passage screening tool.
The tool is user-friendly, it's built in Microsoft Excel
and it's formatted as a linear programming
decision-making framework.
This spreadsheet takes in the raw data from each analysis,
normalizes the data so that it's all on the same scale
and then uses the normalized results
to rank structures in three different ways
to inform management actions.
The first wildlife movement priority rank
is the most important one for considering wildlife movement.
It includes the results
from the connectivity analysis at both scales,
as well as the human development influence metric.
This rank tells us whether a structure
is a priority for wildlife movement.
If a structure scores well here,
it could be a good candidate for wildlife improvements
because wildlife are predicted
to move in the vicinity of it.
But we also included two additional ranks.
This second structure characteristics rank
evaluates the condition of the structure for wildlife
based on the length and bankfull width with ratio
of the structure.
If the structure scores poorly here,
it likely needs some updates
to make it more wildlife friendly.
And then this third protected lands rank
assesses the amount and location of protected lands
around each structure.
Structures with large blocks of protected land
on both sides of the roadway
would receive the best score here.
And these locations would be especially beneficial
for wildlife movement through time.
These three rankings ultimately provide information
on wildlife movements, structure condition,
and nearby protected lands
that will help transportation managers make decisions
about the placement of wildlife improvements.
And here are the top 100 structure locations
just for that first wildlife movement priority rank.
These are some of the places where wildlife
are most likely to encounter a structure
based on their movement patterns.
This map also does not include any adjustments
to weights or constraints,
which we included options for in the tool spreadsheet,
in case managers want to rank a subset of structures
or emphasize certain analyses with weights.
So this is just a basic ranking of structures
without any adjustments.
Our project partners also collected wildlife camera data
through multiple phases of the project
at 52 structure locations beginning in 2015,
and they recorded species detections at these locations.
Circuit based conductivity models
are challenging to validate and it's rarely done,
but we use the species detections from structures
where we had cameras to check our connectivity scores
at these locations.
The probability presence was relatively high
across all camera locations
for both ungulate and carnivore groups.
And this made sense based on the relatively
high landscape scale and structure scale conductivity scores
across these camera locations.
So what will these structure rankings actually lead to?
There are many different things that we can do
to make structures more appealing and usable for wildlife.
For example, if Vtrans might decide to change
the substrate of the structure.
This image here shows a bridge location
that has some large boulders as that movement surface.
And while this is great for this groundhog
who actually lived in this location
amongst all of these rocks,
it's not so great for deer,
which sometimes choose to walk through rivers
instead of over boulders.
So to improve a structure for deer,
we can fill this in with other materials
so that there is a more even surface to walk on.
On the other hand,
if there is a lot of water going through a structure,
bobcat sometimes opt to use shelves
that allow them to pass without walking through the water.
So this is something that could be added
to structures as well.
Those are just a couple of examples
of what can be done with these rankings.
And again, the ultimate goal is to prioritize investments
in these improvements,
to the locations that are actually seeing wildlife movements
that there'll be used and have the greatest benefit
for landscape connectivity.
All right, that's all I have.
Thank you for listening.
I'm happy to take any questions
or you can feel free to email me
with any questions that you might have later.
Thank you.
- Wonderful.
Thank you, Caitlin.
Some great stuff there.
- I'm happy to take any questions.
- There's one in the chat right now from Jeffrey Ward.
Did resistance include locating food?
I would think animals might not continue
in a general direction if no food was found.
- Yeah, that's a really great question.
So one of the inputs in our models that occupancy input
that tells us the probability of occurrence
of a given species is more,
that's more what considers the day-to-day habits of animals
in terms of the areas that they're occupying.
So those models more considered the food aspect
and the land cover types
that provide food for those different species.
movement behaviors can sometimes differ
than their normal occupancy behaviors.
So our movement maps,
they're kind of starting from those locations
where they have food,
and then we asked our experts
to score those resistance values,
according to the movement behavior of the species
that they have expertise in.
So they would have been considering things like, you know,
how their species typically moves across the landscape
and whether or not it's a food driven movement
like for bears, it definitely is a lot of times
compared to other species,
they all have different movement behavior.
Hopefully that kind of answers that question.
- We have another one.
As structures are improved,
does that reduce their resistance value
and does that get remodeled?
- Another great question.
Yeah.
So in our tool spreadsheet,
we do have another column
where the transportation managers will make a note
of whether or not that structure got worked on
and improved for wildlife,
so it won't repeatedly be considered in the rankings.
So yeah, it doesn't get remodeled unfortunately.
Some of these models
are really computationally intensive to run,
especially those fine scale high resolution land
cover structure scale models.
I think those took about four days to run per species
on the supercomputer.
So those won't be getting remodeled anytime soon.
But managers are making a note of
when they work on structures.
- All right.
And just real quickly.
Are these maps available for download
and are there analysis for small species
such as amphibians and reptiles?
- Great, yeah.
I'm gonna try to find our Vtrans project page.
I should've had that link ready.
I'll put that in the chat.
But we just published our final report,
which is on the
Vermont Agency of Transportation's research page.
So I'll try to find a link for that,
and that map is in that final report.
And other species like amphibians and reptiles.
Yeah.
I'm more of a mammal person in terms of my expertise,
but those are,
you could definitely model some of those species.
I think those models would look a lot different
just based on how far they can move in the landscape
and the areas that they're occupying.
So for this project,
the focus was more the larger bodied species
that pose a big danger to motorists
that are traveling great distances
and most frequently encountering roads.
But I think that would be a great next step
looking at some of those other species.
- And then any considerations for restricting
specific animal movement.
- I'm not sure if I'm interpreting this question correctly,
but there was another component in the model
that I left out because of time.
But for each species,
the movements of the electricity
from any source location in the landscape
is constrained by the average
home range size of each species.
So the electricity can't just come out of one location
and travel all the way across the state necessarily
unless that species has a huge home range size.
So the movements in the models
are a little bit constricted or restricted.
But I'm not sure if I was interpreting
your question correctly, Jim.
- All right.
Well, thank you, Caitlin.
- Thank you.