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- [Narrator] All right well,
we will start with Josh Blouin.

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He is with the Vermont Cooperative Fish

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and Wildlife Research Unit

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through the Rubenstein
School of Environment

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and Natural Resources at
the University of Vermont.

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And he will be presenting today about

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Moose Habitat Selection
and Fitness Consequences

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during two critical winter
tick life stages in Vermont.

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- [Joshua] Good afternoon,
my name is Joshua Blouin,

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I'm a masters student at
the University of Vermont,

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and today I'll be discussing
the second chapter

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of my masters thesis,

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Moose Habitat Selection and

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Fitness Consequences During
Two Critical Winter Tick

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Life Stages in Vermont.

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So due to time constraints

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I just wanna very quickly
give some background.

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Moose populations have
been declining in Vermont

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and a study was initiated in
2017 that ran through 2019

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to examine mortality
and productivity rates

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here in the State.

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So 126 moose were fixed
with GPS radio callers

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in wildlife management units E1 and E2

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in Northeastern, Vermont.

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This study and Jacob
Dubbo from the University

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of Vermont Thesis Work found
that heavy infestations

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of winter ticks is really a driving force

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of mortality for our population

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especially in the Northeast
corner of the State.

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And when I say heavy
infestations, I'm talking greater

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than 60,000 winter ticks on a single calf

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just under a year old.

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So this is a really gruesome hard way

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for these individuals
to ultimately perish.

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So what is the relationship
between winter ticks and moose?

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So I just wanna quickly go
through this life cycle.

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So we'll start when the
tick larvae are climbing

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onto vegetation and seeking
a host, preferably a moose.

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Once on the moose, these
winter techs go through

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two life stages, nymph
and adult on the moose

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taking blood meals and
molting between each stage.

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During the late winter
early spring period,

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these female ticks take their
most significant blood meal

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in preparation to drop-off the moose.

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So after they've engorged with blood,

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these female ticks drop from the moose

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into preferably leaf litter,

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where they then lay their
eggs and the cycle continues.

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I think it's really
important at this stage

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to point out these important
winter tick life stages.

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And again that is the peak questing period

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and the peak drop-off periods.

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So that fall questing period is that

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we defined as a 50 day period

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where these winter
ticks are really seeking

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that host or that moose and
the spring drop-off period

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when those female winter ticks are taking

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their largest blood meal,
which typically drives

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those calves under a
year old to mortality.

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So what do we know about
moose habitat selection

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during these two really critical
winter tick life periods?

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Well one important study
here in new England examined

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third-order or within home
range habitat selection

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during the questing and drop-off periods.

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And I'll talk here in just
a second about what I mean

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by third-order habitat selection,

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but the key findings from
Christine Healey's paper in 2018

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found that, moose were
selecting the same habitats

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during both the questing and
the spring drop-off periods,

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which was really promoting this
winter tick and moose cycle

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as winter ticks tend
to be fairly immobile.

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So where they drop-off is
typically where they're picked up.

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So I wanna transition quickly
into describing what I mean

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by first, second and
third-order habitat selection.

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So in 1980, Johnson described
this hierarchal manner

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of habitat selection.

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And it's important to note
these different scales

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as analysis and
interpretation of selection

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may change depending on
which scale you're examining.

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So first-order habitat
selection is interested

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and is more core scale examination

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of where a species tends to be found.

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What is their geographic range?

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While second-order habitat
selection is referring to

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the selection of a home range

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within that geographical range.

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So where are animals?

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Where do they tend to spend the most time

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within their geographical range?

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While third-order habitat
selection is more interested

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in this fine scale examination
of habitat components

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within an individual's home range.

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So this is what Christine
Healey was examining for

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during these two time periods.

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So what were moose using
within their home range?

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And this is also what I
used in the first chapter

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of my thesis when I was
examining utilization

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distributions for individual moose.

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And so we have a better
understanding of what mortality

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and reproductive rates
look like from this study,

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as well as the suitability of habitats

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from my first chapter,

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and this third-order selection

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during these important
winter took life stages

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outlined by Healey in 2018.

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But an analysis of habitat selection

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at these more core scales

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first and second-order habitat selection

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and how selection decisions

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may ultimately affect the fitness of moose

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could provide really important insights

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for their management
as they're in decline.

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So the objectives of this
chapter were to investigate

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that first-order habitat
selection of adult female moose

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during those two important
winter tick life stages

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using multi-season occupancy framework.

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And the second objective was to evaluate

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fitness consequences of habitat selection

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during the fall questing period for cows

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who had calves that survived

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versus cows who had calves that perished

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due to heavy winter tick infestations.

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So to get at first-order habitat selection

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by adult female moose,

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we imposed a grid of roughly 1700 patches

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across our study area.

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Each one square kilometer in size.

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We then filtered our GPS
radio caller by two periods

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so that tick questing and
the tick drop-off period

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for all female moose
captured during the study,

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and this resulted in over 12,000
GPS locations of 74 moose.

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So the next step was to
identify habitat variables

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of potential importance
to moose occupancy.

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So we used LiDAR Habitat Structure,

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so this really fine scale examination

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of the height
classifications of vegetation

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as well as these NLCD
habitat composition variable.

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So what is the forest type of these areas?

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And so we can map these
across our study area.

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Here's an example of
some of our composition

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and structure variables as well as terrain

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such as elevation and slope
mapped across our study area.

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So as you might imagine,
incorporating both this structure

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and this composition habitat variables

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into a model can be rather complex

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and often these
relationships are correlated.

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And so we created a
principal component analysis

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or a PCA to account for their complexity

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and some often correlated relationships

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between habitat structure

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and composition variables.

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So each principal component is explaining

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or was explaining a different
combination of the variables

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which were ultimately
driven by these loadings.

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When I say loadings, the
figure on the right here

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is showing with arrows

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how certain habitat
variables are ultimately

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affecting our principal component.

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And I think the big
picture here is to focus on

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on the right, you know,

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we have all of these structure
and composition variables

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that are pulling these
principal components

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in different ways, but
we ultimately end up with

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the map on the left

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that is four primary principle components

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that describes all 11 of
those habitat variables.

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So now that we have gritted our landscape,

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created our patches or our sites

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and identified our
important habitat variables,

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we are now interested in mapping
the distribution of moose

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across patches on the landscape.

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So we create an encounter history

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for each of those important
winter tick life stages.

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And you can see here from
on the figure on the right

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if you can imagine that
gridded landscape again

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the green patches are identifying
patches on the landscape

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that were occupied by moose
during that time period

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or the white patches were areas
where moose were undetected,

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and this encounter histories
are showing changes

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in occupancy patterns through
time and across space.

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And so these multi-season occupancy models

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really allow us to examine
those changes through time.

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And there are four key parameters

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to a multi-season occupancy model,

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but for simplicity and time constraints,

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we'll really focus on these three.

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So the initial probability
that moose occupy a patch,

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is based on those habitats structure

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and composition variables.

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So psi is looking at, in that first year

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in early 2017 that dropout period,

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what is really driving
that initial probability

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that moose will be there and in a patch.

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Next colonization and
extinction parameters,

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they're really focusing
on what is driving changes

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in occupancy over time and through space.

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And so for example in the
drop-off tick period in 2017,

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the patches within this
red rectangle are moose

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there was undetected, no
moose were detected there

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but in the following time period,

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that questing period in 2017,

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some of these patches
were occupied by moose.

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So what is driving those
colonization rates?

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And same for extinction,

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so patches that were colonized
in 2018 drop-off period

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but then in the following
questing period of 2018

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moose were not there.

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So what is driving these changes?

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So we used our presence
to evaluate these changes

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in occupancy patterns, across
the patches and through time.

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So we created a model set of 24 models

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each representing an
alternative hypothesis

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explaining these changes in occupancy.

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I don't have time to go into the model set

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but just know that there
was one clear top model

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that was examining the
probabilities of extinction

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and colonization as a function
of the habitat structure

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and composition variables.

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So this brings us to the key
results for objective one.

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So we mapped the probabilities
of both the colonization

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and the extinction
rates for our top model.

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So the areas of darker
red in our study area

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are showing higher probabilities

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of either extinction or colonization,

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while the white patches are showing areas

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of lower probabilities.

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So there are a couple of key
takeaways from this figure.

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Number one in the upper right-hand figure

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we notice that during
the fall questing period

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the probability of extinction is very low

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for most patches in our study area.

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And this likely means that moose
are moving around much more

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during this time,

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which makes sense given what we know

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about moose behavior
during the mating season.

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Given that, let's focus on the time period

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when moose are dropping
ticks on the landscape.

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So the two figures on the left.

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So patches where the probability

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of extinction was low
and colonization was high

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during the spring drop-off period,

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is really showing these areas with the

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highest probability of moose occupancy.

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And these are really characterized

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by higher proportions
of young or shrub forage

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mixed forest at those greater elevations.

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I think it's also really important
at this point to remember

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that where winter ticks drop-off moose,

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is likely where they will
quest the following fall.

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So this brings us to our next objective.

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Are there important
patterns or relationships

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between the habitats adult
female moose are selecting

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during that period when
they're picking ticks up

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and the fate of their offspring.

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So to determine these
patterns of habitat selection

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and the fate of their offspring,

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we radio collar moose in January,

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we would follow these adult females

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throughout the winter into early may

260
00:13:23,540 --> 00:13:26,210
when they typically gave birth to a calf,

261
00:13:26,210 --> 00:13:28,900
we'd follow that calf
through the summertime,

262
00:13:28,900 --> 00:13:30,410
come the following January

263
00:13:30,410 --> 00:13:34,520
we asked the capture crew
to really target these cows

264
00:13:34,520 --> 00:13:36,150
that we knew had calves.

265
00:13:36,150 --> 00:13:38,340
So we had observed them all summer.

266
00:13:38,340 --> 00:13:43,340
And they were able to go out
and capture 10 cow calf pairs.

267
00:13:43,960 --> 00:13:47,390
And what this allowed
for was this inference

268
00:13:47,390 --> 00:13:49,980
of where was that cow calf pair

269
00:13:49,980 --> 00:13:53,240
during the fall time period
when they were picking up ticks.

270
00:13:53,240 --> 00:13:56,360
And now that we've collared
that calf in January

271
00:13:56,360 --> 00:13:57,840
we know their ultimate fate,

272
00:13:57,840 --> 00:14:01,490
so some died due to heavy
winter tick infestations

273
00:14:01,490 --> 00:14:02,630
and some lived,

274
00:14:02,630 --> 00:14:04,853
and thankfully it was split in half.

275
00:14:06,530 --> 00:14:09,110
So from this two resource
selection functions

276
00:14:09,110 --> 00:14:11,310
were estimated one for adult females

277
00:14:11,310 --> 00:14:14,010
whose calves survived age one,

278
00:14:14,010 --> 00:14:17,130
and one for adult females
whose calves perished

279
00:14:17,130 --> 00:14:19,140
prior to age one.

280
00:14:19,140 --> 00:14:21,460
So due to time, I just
wanna quickly breeze

281
00:14:21,460 --> 00:14:24,420
through these methods for objective two.

282
00:14:24,420 --> 00:14:26,360
So we greeted the landscape

283
00:14:26,360 --> 00:14:28,300
but this time at a much finer scale,

284
00:14:28,300 --> 00:14:30,880
so 200 meters squared patches.

285
00:14:30,880 --> 00:14:34,150
Also similar to objective
one we performed this PSA

286
00:14:34,150 --> 00:14:36,510
to really account for complexities

287
00:14:36,510 --> 00:14:39,873
and correlation between
our habitat variable.

288
00:14:41,960 --> 00:14:44,300
So for each resource selection function,

289
00:14:44,300 --> 00:14:48,340
we estimated used or unused patches

290
00:14:48,340 --> 00:14:49,970
as a function of the different

291
00:14:49,970 --> 00:14:53,290
principle components describing
our habitat variables.

292
00:14:53,290 --> 00:14:57,500
So for each individual, we used
all of the patches they used

293
00:14:57,500 --> 00:15:00,620
and a thousand randomly
selected unused patches.

294
00:15:00,620 --> 00:15:03,050
We then repeated this 10,000 times

295
00:15:03,050 --> 00:15:05,160
to end up with a resource
selection function

296
00:15:05,160 --> 00:15:07,000
for each individual.

297
00:15:07,000 --> 00:15:09,750
So these were then aggregated
across the individuals

298
00:15:09,750 --> 00:15:12,040
who had calves that lived versus those

299
00:15:12,040 --> 00:15:13,413
who had calves that died.

300
00:15:14,570 --> 00:15:17,650
So this brings us to our key
results for objective two.

301
00:15:17,650 --> 00:15:20,440
So if we look at this
figure here on the X-axis

302
00:15:20,440 --> 00:15:24,150
our principle components
describing our habitat variables

303
00:15:24,150 --> 00:15:26,300
and on the Y-axis are our estimates.

304
00:15:26,300 --> 00:15:29,000
And so we can see from this box plot

305
00:15:29,000 --> 00:15:32,360
that if a cow has a calf that died,

306
00:15:32,360 --> 00:15:34,250
so fate equals zero,

307
00:15:34,250 --> 00:15:39,250
those clear bars versus the
cows with calves that survived

308
00:15:39,490 --> 00:15:41,440
there are clear differences in how

309
00:15:41,440 --> 00:15:43,220
they are selecting habitats

310
00:15:43,220 --> 00:15:45,070
when they're picking up winter ticks.

311
00:15:46,450 --> 00:15:50,150
And so this brings us
to the major key result

312
00:15:50,150 --> 00:15:53,930
which is females with calves that died

313
00:15:53,930 --> 00:15:56,610
were selecting habitats
with higher proportions

314
00:15:56,610 --> 00:15:59,660
of young, mixed forest
at higher elevations.

315
00:15:59,660 --> 00:16:01,860
And if you remember from objective one,

316
00:16:01,860 --> 00:16:06,200
these were areas where the
probability of occupancy

317
00:16:06,200 --> 00:16:07,600
during the time period

318
00:16:07,600 --> 00:16:09,530
when they're dropping ticks was highest.

319
00:16:09,530 --> 00:16:12,850
So where the highest occupancy of moose

320
00:16:12,850 --> 00:16:14,800
where they're dropping their ticks,

321
00:16:14,800 --> 00:16:17,890
cows that were spending the
most time in those areas

322
00:16:17,890 --> 00:16:22,270
where their offspring were perishing

323
00:16:22,270 --> 00:16:25,350
from heavy winter tick infestations.

324
00:16:25,350 --> 00:16:28,770
While the individuals
with calves that survived

325
00:16:28,770 --> 00:16:31,000
were selecting habitats with

326
00:16:31,000 --> 00:16:33,460
adequate young deciduous forest,

327
00:16:33,460 --> 00:16:37,890
but also habitats with higher
proportions of mature canopy,

328
00:16:37,890 --> 00:16:41,250
evergreen forest, and
wetlands at lower elevations.

329
00:16:41,250 --> 00:16:44,750
So their second order
habitat selection patterns

330
00:16:44,750 --> 00:16:49,420
were deviating from the
majority of the moose

331
00:16:49,420 --> 00:16:51,253
in their occupancy analysis.

332
00:16:52,730 --> 00:16:54,620
So these are really exciting results

333
00:16:54,620 --> 00:16:56,880
in that they show fitness consequences

334
00:16:56,880 --> 00:17:00,470
of habitat selection
decisions made by female moose

335
00:17:00,470 --> 00:17:03,110
during that time when
they're picking up ticks.

336
00:17:03,110 --> 00:17:07,350
In our analysis of first and
second order habitat selection

337
00:17:07,350 --> 00:17:10,030
in combination with Healey's 2018

338
00:17:10,030 --> 00:17:12,150
third-order habitat selection,

339
00:17:12,150 --> 00:17:14,450
really gives this detailed examination

340
00:17:14,450 --> 00:17:17,540
of moose habitat selection patterns

341
00:17:17,540 --> 00:17:20,780
and how those selection
decisions may ultimately relate

342
00:17:20,780 --> 00:17:23,060
to winter tick infestations.

343
00:17:23,060 --> 00:17:24,840
So in terms of management,

344
00:17:24,840 --> 00:17:28,230
our model coefficients and mapped results

345
00:17:28,230 --> 00:17:31,060
really help to define
these potential hotspots

346
00:17:31,060 --> 00:17:34,370
for both moose and for winter ticks.

347
00:17:34,370 --> 00:17:36,850
And so Timber Management, for instance,

348
00:17:36,850 --> 00:17:41,810
may benefit from this
knowledge of potential hotspots

349
00:17:41,810 --> 00:17:45,400
by encouraging habitats
that benefit both moose

350
00:17:45,400 --> 00:17:47,920
but limit winter tick loads.

351
00:17:47,920 --> 00:17:50,510
So potentially encouraging uneven age

352
00:17:50,510 --> 00:17:52,343
selective cuts for example.

353
00:17:53,560 --> 00:17:54,910
In terms of winter ticks,

354
00:17:54,910 --> 00:17:58,900
little is known about the
ecology, abundance and management

355
00:17:58,900 --> 00:18:01,310
of these winter ticks in
their natural settings.

356
00:18:01,310 --> 00:18:05,830
So management and research
may benefit from these

357
00:18:05,830 --> 00:18:08,260
the knowledge of these potential hotspots

358
00:18:08,260 --> 00:18:11,620
and really focus future
research that can ultimately

359
00:18:11,620 --> 00:18:13,610
help break the negative impacts

360
00:18:13,610 --> 00:18:16,373
of this winter tick moose cycle.

361
00:18:17,560 --> 00:18:19,800
So with that, I will
end my talk here today,

362
00:18:19,800 --> 00:18:21,540
thank you so much for listening,

363
00:18:21,540 --> 00:18:23,110
I just wanna give a real quick shout out

364
00:18:23,110 --> 00:18:25,630
to some of the organizations
that made this study possible

365
00:18:25,630 --> 00:18:28,250
such as the Silvio Conte Wildlife Refuge,

366
00:18:28,250 --> 00:18:29,710
and all the kind staff there

367
00:18:29,710 --> 00:18:32,580
particularly Refuge Manager, Steve Agius,

368
00:18:32,580 --> 00:18:34,710
also to VELCO for their continued support

369
00:18:34,710 --> 00:18:36,570
throughout the project.

370
00:18:36,570 --> 00:18:39,160
A handful of people to thank,
particularly my advisors

371
00:18:39,160 --> 00:18:41,410
Jen Murdoch, and Terry Donovan,

372
00:18:41,410 --> 00:18:45,010
and folks from the State
such as Cedric Alexander,

373
00:18:45,010 --> 00:18:47,940
Scott Darling, Mark Scott, and Tony Smith.

374
00:18:47,940 --> 00:18:49,220
So thank you for tuning in

375
00:18:49,220 --> 00:18:52,170
and I'll be happy to answer
any questions folks might have.

376
00:18:56,020 --> 00:18:57,765
- [Jason] This is Jason Helf.

377
00:18:57,765 --> 00:18:58,598
Can you hear me
- [Joshua] Oh hey Jason

378
00:18:58,598 --> 00:18:59,733
yep I can hear you.

379
00:18:59,733 --> 00:19:01,990
- [Jason] It's really
interesting that it looks

380
00:19:01,990 --> 00:19:04,630
like the high elevation habitats may pose

381
00:19:04,630 --> 00:19:06,330
to be maybe a little bit riskier

382
00:19:06,330 --> 00:19:08,720
for tick acquisition for these moose,

383
00:19:08,720 --> 00:19:12,400
so I'm thinking with
respect to climate change,

384
00:19:12,400 --> 00:19:14,400
is that potentially a good thing?

385
00:19:14,400 --> 00:19:17,280
Does that suggest that these
lower elevation habitats

386
00:19:17,280 --> 00:19:22,200
may provide viable areas for
moose longer than we think

387
00:19:22,200 --> 00:19:23,350
moving into the future?

388
00:19:25,020 --> 00:19:26,630
- [Joshua] Yeah, I think
that's a really good question

389
00:19:26,630 --> 00:19:28,053
and a good point,

390
00:19:29,050 --> 00:19:30,370
because I think it's important

391
00:19:30,370 --> 00:19:32,670
when we're thinking about the relationship

392
00:19:32,670 --> 00:19:35,310
between winter ticks and mooses,

393
00:19:35,310 --> 00:19:38,667
how weather may ultimately
affect winter ticks.

394
00:19:38,667 --> 00:19:42,170
And we know from some research at UVM

395
00:19:42,170 --> 00:19:45,910
with Sheryl Sullivan's
work and others elsewhere

396
00:19:45,910 --> 00:19:49,760
in New England in kind
of a laboratory setting,

397
00:19:49,760 --> 00:19:52,860
that weather and cold can
really impact these winter ticks

398
00:19:52,860 --> 00:19:56,110
and so, yeah, maybe these
higher elevation habitats

399
00:19:56,110 --> 00:19:59,940
may prove to be detrimental
for winter ticks

400
00:19:59,940 --> 00:20:01,160
as the weather changes.

401
00:20:01,160 --> 00:20:05,593
It's hard to know but I
think the big takeaway is,

402
00:20:06,690 --> 00:20:09,800
this is pointing towards
kind of supporting the theory

403
00:20:09,800 --> 00:20:13,560
of higher moose densities
are kind of driving

404
00:20:13,560 --> 00:20:15,160
this parasite load.

405
00:20:15,160 --> 00:20:18,460
And so those cows or
calves that are kind of

406
00:20:18,460 --> 00:20:20,570
selecting the perimeter,

407
00:20:20,570 --> 00:20:24,330
the periphery habitats that may be

408
00:20:24,330 --> 00:20:27,070
seen as potentially suboptimal

409
00:20:27,070 --> 00:20:28,840
in terms of forage and things,

410
00:20:28,840 --> 00:20:32,790
may ultimately be really
beneficial for their fitness.

411
00:20:32,790 --> 00:20:36,760
And so, yeah, it's an
interesting dynamic there but

412
00:20:36,760 --> 00:20:39,570
it's a good question about
future weather patterns

413
00:20:39,570 --> 00:20:43,163
and how that might affect
that the tick levels as well.