All right, so today I'm going to be talking
about how effective dogs versus humans are
at being able to detect spotted lanternfly egg masses
not the adults but the actual egg masses.
And if I can advance this, there we go.
So there's a huge team that's been involved
in this work and I'd like to first acknowledge the co-PIs
on the project, Carrie Brown- Lima, and Ann Hajek, as well
as everyone else on this slide that's contributed either
with working with us as collaborators or in the field.
So, many thanks to the large team and funding
by the Cornell Atkinson Center for Sustainability.
For folks who don't know much about spotted lanternfly,
I'll give you a very brief background about them.
They're thought to have been introduced
from Asia on these stone slabs.
They lay their egg masses on smooth surfaces.
So you can see the picture
on the upper right are the actual egg masses.
These are the egg masses you can see
on that stone slab.
In 2014,
and they arrived in Pennsylvania.
And then despite a lot
of efforts that have been ongoing to try to
prevent the spread, they've rapidly spread.
I'll show a map in the next slide of that spread.
So they're plant hoppers
and they have these piercing, sucking mouth parts
and they feed on and damage agricultural species,
primarily grapes, apples, hops, peaches.
And one of the characteristics
of them is they excrete something called honey dew.
And once they excrete that honey dew, for example,
on the leaves, then there's a sooty mold that grows
on top of them, on top of the honey dew.
And that further damages both the crop itself
and the leaves.
In addition to the damage of the crops,
they also swarm in very large numbers
and can be quite the annoyance
if you're trying to do anything outside.
This is the distribution room.
This was actually October 26th
and they have spreads since October 26th.
I just checked the new map yesterday
which I didn't upload here
but there are actually new infestations,
especially this new one popped up right here.
So that's now considered an infestation rather
than just an occurrence.
So, the initial spotted lanternfly introduction
was right here in Berks County, Pennsylvania in 2014.
Now you can see they're
in York, Massachusetts, Michigan, Indiana, North Carolina.
So, rapidly spreading in Vermont.
You can see in the [Indistinct] area right there,
an individual detection.
No invasion as of this point.
And if we're thinking about managing invasive species,
particularly if we're thinking about just single individuals
or very small populations, we want to try to be
in this realm of eradication or maybe containing
the population.
In Pennsylvania and New Jersey now,
they're beyond the point
of trying to contain or eradicate.
This is where there is like asset protection mode.
But when we started this project in New York,
we're at this stage of not having infestations.
And so we were thinking about how do we prevent them
from coming into the state from Pennsylvania.
They're like knocking on our door
and we don't want them to come in.
That's what Vermont's situation is right now, right?
And so, we started to think about
these early detection, rapid response approaches
that might be suitable for use in New York
but it's challenging
because
the egg masses are very camouflaged
and they're very difficult to find.
So this tree right here has an egg mass on it.
Can anyone see it?
No, probably not.
I'm gonna zoom in,
now,
Can you see it there?
Still probably not is my guess.
There it is right there.
So they're extremely, extremely camouflaged,
very hard to find.
So even humans where you know
it is on a tree,
it's very easy to overlook them.
And so given the complexity with trying to find them,
what we did is we said,
"Well, can we use dogs to try to find the egg masses?"
Something that's very camouflage.
Dogs can use their olfactory senses,
we can train the dogs to smell the egg masses.
And especially
that honey dew
is something that they smell as well.
Can we train these dogs to be able to
to find the egg masses?
So our detection dog team here,
we used Dia and Fagan
and they were our trustee field workers
in addition to their handlers.
We surveyed 20 vineyards in New Jersey
and Pennsylvania and we surveyed them during the winter.
So that's the only time of the year when
the individuals, the species isn't moving, right?
So there are no adults in the environment at that time.
It's just these egg masses.
So we could think about the population being closed at
that period of time.
So, this was the original core in Harrisburg, Pennsylvania.
We're just east of that area.
And where we were in New York
and here's Cornell right up here.
And this is the the border where
the area of concern is.
For the survey methods, we surveyed 20 vineyards
and then the surrounding natural areas and by natural areas
usually this was like the forested area,
kind of the upland area that was adjacent to the vineyards.
We had 12 different transects
so that we're within the vineyard area.
And the average length of those was about 20 meters.
And then we had 20 transects that were
in these adjacent forests.
Those were about 26 meters in length.
We had subunits that we surveyed
and the subunits were kind of nested within these transects.
And so, here is for example, a transect
in the vineyard and you can see
the vines right here.
And this is a metal pole.
I don't know if it's a little bit dark
but there's metal poles that are usually between
these vines kind of holding them up.
Approximately every meter is where
these vines or poles are.
So we considered those as sub-units.
And then also in the forest transect, we had these transects
and we were able to divide 'em
up into these one meter segments.
We repeated the survey two times with humans
and we repeated the survey two times with dogs.
So every transect we measured,
the same transect we measured twice
with both humans and dogs.
And then we gave the humans
and the dogs an unlimited search time.
And something important is that all
of the sites that we went
to had a known visible infestation.
We knew that there were going
to be egg masses there.
We didn't tell the dogs or the handlers where they are.
We didn't tell the humans where the are,
we just knew that that vineyard
had some kind of egg masses on it.
And the reason that we did that is
because we're trying to compare the difference
between humans and dogs.
So we needed to go to sites
that had something to be able to detect.
So, this isn't a very early detection scenario
per se
because we knew it had some kind of infestation.
For those of you who don't know about occupancy modeling,
I'll give you a little overview of that
because that's the method that we use to analyze these data.
The occupancy modeling accounts
for imperfect detection of organisms and surveys
and the picture or the figure at the bottom,
I'm going to go through
what I mean by that.
Basically, it uses presence data.
We'll denote that as a one
and non detection data and we'll denote that as a zero.
And we go out and we survey an area,
we're gonna go out and we're going
to survey for spotted lanternflies.
We go out and either one of two things happens.
We either see the species,
we see the spotted lanternfly or we don't.
So these are our field observations right here.
If we go out and we see the spotted lanternfly,
there's only one kind of biological reason why
we could have seen that spotted lanternfly
because it was actually there, right?
But if we go out
and we survey the area and we don't see the species,
one of two things might be going on.
The biological reality might be
well, it's actually not there.
But a second possibility is
the spotted lanternfly
is actually there, but we just didn't see it.
So, this issue right here is where the problem comes
in because this is our imperfect detection.
So as humans or as dogs,
we don't always see the biological reality.
So that is what we'll call field observation error
or this imperfect detection.
And these occupancy models allow us to account
for this imperfect detection
and we can estimate two parameters.
We can estimate the probability of occupancy,
the probability that a site has that species
and then the probability
of detection given that species is there,
what's our probability of being able to detect it?
And that's what we did
in the comparison of the humans versus the dogs.
So we used this multi-scale occupancy model
and the two scales are the transect level
and then the subunit level within that transect.
The transects,
we can think about those as being related
to the probability of invasion from a source.
So, if you're in the vineyard,
it's most likely to be invaded
from the forest site because
the spotted lanternfly is associated
with true species like tree of heaven that are likely coming
from the surrounding natural areas.
And then the subunits within that transect,
each individual vine or pole or one meter segment
within the forest can be thought to be related
to the intensity of infestation.
So how many of those one meter segments within
that transect
have the spotted lanternfly egg masses?
And then we could estimate the detection probability
of the subunits and compare humans versus dogs.
So here are the occupancy results.
First off, at the transect level,
so this is an individual transect in the vineyard
or an individual transect within the forest area.
The occupancy of egg masses was very high in both of them.
Within the vineyards, 0.94 and then within the forest, 0.85.
So most of the transects that we were surveying
had egg masses on them.
However, if we go down to the subunit level,
this is within those one meter segments,
the vineyard had an occupancy
at the subunit level of 0.47 and the forest at 0.13.
And so despite very high occupancy at
both the vineyards and the forest at the transect level,
the forest had much lower,
we could think of it as infestation level
within the individual one meter transects.
And this is showing the subunit occupancy
on the right, we have the occupancy probability
on the Y axis and then we're comparing vines,
the metal poles within the vineyard.
So those are kind of combined
into what we're calling the vineyard
and then the forested sites.
So two things that you'll see, one is
that the higher infestation sites had a higher probability
of occupancy.
And then the second thing
is that the metal poles had a higher probability
of occupancy than did the vines.
And so I mentioned that the spotted lanternfly likes to
lay their egg masses on smooth surfaces
and the metal poles are smooth relative to the rough vines.
So they,
kind of have a say a "preference"
for these vines or for the poles over the vines.
We can also look at the distance
from forest.
So, we have the vineyard transects that were laid out.
We surveyed these transects
but we could measure the distance
from that transect to that upland forest
and look at the probability of occupancy
as a function of how far away it is from the forest.
And our prediction would be
that the occupancy should be higher the closer you are
to the forests because that's
where the adults would be coming
from out of the forest because
of that association with with tree of heaven for example.
And that's exactly what we saw.
This is the occupancy probability
and distance to forest on the x axis.
And the closer you are to the forest,
the higher the probability of occupancy.
As you get away from the forest,
within those transects, there was a lower probability
that there was going to be egg masses there.
So this has implications for where you might think
about searching for egg masses within vineyards.
If you look at this, somewhere around 75 meters
or closer, would be really good places to search
since those have the highest occupancy probabilities.
This is consistent with a study
in Pennsylvania where they were looking at egg masses
and they found that 44% of them were
within 15 meters of the edge of the vineyard.
So again, there's strong association with the forest.
Now I'm switching to the detection results.
This is the difference between the humans and the dogs.
And if you look
at the figure on the right,
this is detection probability on the Y axis.
We have the humans searching the vineyards
and the dogs serving the vineyards,
humans searching the forest
and then dogs surveying the forest.
And what you can see here is that within the vineyards,
humans had a higher detection probability
than did the dogs.
They had 1.8% higher detection probabilities
than did the dogs.
Now humans use visual search.
The picture that I showed you on the tree was hard to see.
But when you're in a vineyard and you're up close to
a vine, a grapevine that is only this high,
it's really easy to see all of the egg masses
that are there.
However, when you go out into the forest,
we can see that the dogs are much better.
The dogs had a much higher detection probability
and did 3.4 times better than did the humans.
And the reason why is
because dogs can use their olfactory sensors
and we as humans are pretty useless in that context.
It's really hard brushy vegetation,
we don't know where to search, we can't see anything.
Yeah, it's just like stems
and leaves and it's like kind of impossible.
We can also think about the search efficiency.
So we had detections,
how well we're doing at detecting them
but if you think about how much time it took,
this turns into an issue of costs.
So, the dogs actually ended up searching
for a longer period of time than humans.
And in the vineyards, the humans had more detections
and the time that it took didn't overcome the dogs.
And so the human, the number of detections
per hour was 31 detections per hour for humans,
24 detections per hour for dogs.
So humans were better in terms of their efficiency.
In the forest, dogs were still slightly better
despite the longer time that it took them
to search these areas.
So it took dogs 7.6 detections
or they did 7.6 detections
per hour and humans had 6.7 detections per hour.
However, I'll note that
I think that the number of detections
and not the efficiency is probably more important when
we're thinking about early detection situations where
it's really important to be able to detect those
individuals.
So probably the cost of the search time
is worth it relative to the the gain.
And then infestation level, this is really not surprising.
The higher infestation sites had higher detection
probability, so there's just more egg masses that are
available to be detected.
Finally, what does this mean in practice,
if you're going out there and doing some searches.
One, I would recommend that you search vineyards
that are closer to the forest,
within about 75 meters.
Second one is searching larger trees near the edges,
especially at the higher elevations because the adults
will be coming down from those higher elevation tree sites,
searching the metal poles and the vineyards is a good idea.
And then using dogs to search the vineyards
in these early detections situations is still
a good approach.
We were, again, we were surveying in what would be
considered a moderate to high level infestation sites.
And then the dogs were particularly good
in the forested sites where humans kind
of fell apart
because our visual search is impeded in those forest sites.
So thank dogs have a great utility in these forested sites.
Thanks to all the vineyard owners
for access to their land.
And then finally, I will take any questions.
(students clap)
[Moderator] Somebody in the chat does have a question.
She asked, did the handlers ever report,
Did the handlers ever report
that the dogs alert for lanternfly when not working?
And if it gets widespread and established with the dogs
then would the dogs always be working?
Yeah. So this issue of the dogs,
so I can probably for folks
that don't know how the dogs work, I go over them
but basically you're training the dogs to detect something
and the dogs are motivated by like any normal dog,
they're motivated by the attention,
they're motivated by some kind of reward.
So every time that they find an egg mass,
you have to reward them
and you throw them a ball and you know, like a
think about a yellow lab or something,
they're just like, "Oh yeah."
and then they go get the ball.
They wanna keep working because you know
their handler just rewarded them.
So, this issue about the number
of detections is particularly important
because if they are everywhere,
you're gonna have to keep rewarding them
and rewarding them and rewarding them.
So we did have to reward them.
The dogs are basically pulled when the search
is done.
So, in terms of,
are they still finding them when they're not working?
There's a signal basically
that the handler handler will use to tell the dog,
like, "Okay, now it's work time."
So there isn't necessarily that issue.
[Moderator] You have one more minute
if you want to take this last question.
[Student] Will you be publishing
this somewhere accessible?
Yep, we're writing it up right now.
And so I'd say we'll send it out to a journal probably
in the next two months, something like that.
[Moderator] Thank you.
(students clap)