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- All right, I want to welcome everyone

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to our webinar about the new
online tool that was developed

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called Tracking Shifts
in Disturbance Regimes.

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And Pia Ruisi-Besares will start us off.

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- Thanks.

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Hi, everyone, thank
you so much for coming.

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I am Pia, I'm the project manager

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for the Forest Ecosystem
Monitoring Cooperative

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and I'm really excited to tell you about

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the newest release of our webtool,

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Tracking Shifts in Disturbance Regimes.

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So I will introduce the project

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and the process that went into the work

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and then I'm actually gonna
split the talk with Jim Duncan,

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our director who's here,

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and he'll share with you
the analysis and the trends.

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And then at the very end,

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we'll walk through the webtool live,

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or I will walk the webtool

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just to sort of show you how it works.

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And hopefully we'll have
plenty of time for questions

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at the end as well.

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So to start at the very beginning

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in case you're not familiar with us,

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the Forest Ecosystem
Monitoring Cooperative

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is a collaborative organization,

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and we work with federal
agencies, state agencies,

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and the University of Vermont

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and we synthesize trends
in forest ecosystem health

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across the region.

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And so to us the region
includes New England

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and the state of New York.

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And in order to provide the services,

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the FEMC has a regional
committee of cooperative members

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from different disciplines
and different states

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who come together annually
and discuss relevant questions

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about forest ecosystems
that need to be addressed

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across administrative boundaries,

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and then the FEMC carries this out.

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And if you know us,

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you'll know that a lot of our projects

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are sort of web-based

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because we have a really
strong web development team

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for an ecological organization.

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So hopefully you're familiar
with some of our work.

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And so this past fiscal year,

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there were two projects that we worked on.

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One was the Climate Indicators Project

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that I gave a talk on
a couple of weeks ago,

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and you can see that webinar information

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on YouTube if you're interested.

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And then the project I'll
be talking about today

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is our Tracking Shifts in
Disturbance Regimes Project.

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So as many of you probably know,

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shifts and disturbance
patterns across the Northeast

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are of increasing concern

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because as climate change
continues to change,

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there'll be impacts to our forests.

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So this project came
from that recognized need

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to understand the shifts historically,

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to predict them to the future

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and then to use whatever
information comes from that

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to hopefully implement
adaptive management strategies

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in Northeastern forests

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to sort of mitigate some of those impacts.

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So in particular, this project focuses on,

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changes in the patterns of
frequency, severity and extent

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of disturbance events across the region

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and hopes to look at sort
of the cascading impacts

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of forest ecosystems and human communities

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as the project progresses over time.

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So the goal of the project is not really

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to reinvent the wheel on this.

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We know that there's

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a lot of disturbance
work out there already,

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and there have been disturbance projects

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that have analyzed individual outcomes

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and individual disturbance types,

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so what we're trying to focus on here

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is consolidating that
information into one place

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and sort of look at the
current state of disturbance

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in Northeastern forests

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and provide a place for users
to come and look at trends

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and access data that can be
used for further exploration.

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So to dive in a little bit
more so we're on the same page,

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I just wanted to define
what we're talking about

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when we say disturbance
and disturbance regimes.

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So for this project,
we're defining disturbance

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as a biotic or abiotic event
that causes changes to,

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or disrupts the function
of forest ecosystems

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and/or the services that they provide.

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And then when we're talking
about a disturbance regime,

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it's the pattern of a
given disturbance event

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and its impacts.

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And so that definition,

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I think, is used in other places as well,

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but that's how we have shaped
it for our project here.

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And it's important to
understand these patterns,

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as I was saying, because
the historical changes

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will show us possible
predictions for the future,

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which can then allow us to explore

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some of our resilience
strategies that forests need

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as they are assaulted with
more and more disturbances.

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And so one of the ways we can
do this is through monitoring,

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and monitoring allows us to see baselines

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and look back into the past

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and also to see how things
are changing into the future.

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So in order to sort of make
this project manageable,

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since there are so many possible types

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of disturbance and impacts,

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we had three major driving questions

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that sort of helped develop
the scope of the work.

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And so these questions are,

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what are the key drivers and
responses to disturbance?

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So with so many options, what
should we focus on right now

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to best reflect changes in the Northeast

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and that's manageable for us to look at

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and it has accessible data
for us to start to analyze?

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And then we also wanted to
make sure that we covered

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what the historical and
anticipated shifts and trends are

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and specifically how there're changes

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in extent, severity and
frequency of disturbance events,

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and I'll talk about that
a little bit more later on

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but those are sort of the three metrics

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that we were looking at as
we thought about change.

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And then finally, we wanted to make sure

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that we had a database that
aggregated this information

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so it could be explored

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and that these specific
drivers or disturbances

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could be looked at in a different way.

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And so those were the sort
of the three main goals

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that we kept in mind

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as we moved forward through the project.

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And so with that information
in mind, we had three inputs,

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sorry, outputs at the end of our project.

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One is to have a filterable database,

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and so this is to quickly
find historical data sets

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related to specific disturbance
drivers and responses

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so that you could easily
find that information.

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The second and probably the
most time intensive component

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was the trend analysis section.

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To see an overview of changes in regime

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by region and by state.

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So it's a variety of graphs, overlaid

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and you'll get to see
those, that if possible,

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we would look at extent,
severity and frequency

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depending on the dataset.

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And then finally the third
output was a visual mapping tool

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that helps to identify where
monitoring is occurring

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and where there are gaps.

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And this part is always
under constant development

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so we look forward to hearing about

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monitoring projects that
can be added to this.

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So I will just briefly give

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some more information about
the process of how we did this

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to give a little more background

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and then I will define some of our terms

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and then you can see the
analysis that we worked through.

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So I think a great place to start

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is to acknowledge our advisory committee.

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So I mentioned in the beginning

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that we have a large steering committee

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that helps identify our projects,

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excuse me, we also often
have smaller committees,

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they're involved in individual
projects that we work on

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that are a collaboration
of different experts

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from across the region

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that bring different things to the table,

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and so for this project we have
expertise in various fields

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including fire dynamics, forest ecology,

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pests and pathogens specialists

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and freshwater and geomorphological
dynamic specialists.

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So we are getting information

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from people outside of our organization

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and we're hoping that that makes us

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a more comprehensive tool
that it can be used by others

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who have more expertise
in these various fields.

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So we got this committee
together and they helped us

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to guide the project.

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So once we had our steering committee,

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topic decision from our larger committee,

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we then started our process
of developing the project

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over about two years.

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It started with the cooperative survey

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and an initial literature
review that we did as FEMC staff

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and then we had an initial meeting

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with our advisory committee members

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where we got together and
showed them what we had found.

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And in that group, we sort
of had a working meeting

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where we determined the
critical disturbance types

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that we're gonna look at

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and within that, we found
that they were actually

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a difference between disturbance types

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and they were drivers and responses

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and I'll talk about that
a little bit more later

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but that was all determined by
our advisory committee group.

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After we made that determination,

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we started collecting data sets,

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we designed an information portal

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and we met again with
our advisory committee

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to show them the data sets
that we were planning to use

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for our trend analysis,
to kind of get the okay

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and work through any of
the details with others.

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And from there we started
the analysis process

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and created a web portal.

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And finally, before we were done,

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we had a final review with
the advisory committee

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who we also have met with in
different individual meetings

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across the time of the project.

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But they reviewed our final
analysis and interpretation

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and then we finished
up our technical report

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and released our webtool, so
that's where we are today.

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So it's a long process with a
lot of help from other people.

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All right.

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So I wanted to just mention

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the difference between
drivers and responses

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and some of our metrics

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and show you what they are
before we look at them.

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As we work through the
various types of disturbances

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in the project,

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we realized that there
were areas of interest

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that could be categorized
into two types of disturbance

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as we're kind of calling it.

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Disturbance drivers and
disturbance responses.

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So we'll be spending most of the time

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looking at drivers in this project

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and that's what we do our analysis on

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but I just wanted to take a minute

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to clarify our definitions

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because they show up differently

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on the website and the tool.

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So in this project, we're
calling a disturbance driver,

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an agent that causes disturbance to occur.

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And in this project they're mostly abiotic

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and climate related and
these are the aspects

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that we have trend analysis available for,

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most of which allow us

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to look at extent severity and frequency.

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Our disturbance responses are
key systems within forests

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that change following forest disturbance.

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And these systems can
be used as indicators

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so they show occurrence and severity

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in the implications of
a disturbance event,

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but they're not the actual
driver of the event.

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And they're important because
studying their dynamics

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can help to understand the
impacts of disturbance regimes

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and how they might be changing.

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However, the trend analysis
are unavailable right now

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because they're a little bit muddier

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and harder to parse out
the cause and effect.

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So we have information about these

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and they are very important to understand,

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but we haven't looked at

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their historical trends at this time.

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So the big reveal, our
selected drivers and responses

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for the project are here

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and you can learn more about them

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on the website in particular,

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I won't have time to walk
through why we selected each one,

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but I can say that these
were sort of all drivers

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that are important to the region

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00:10:51,980 --> 00:10:54,020
and also had large enough data sets

263
00:10:54,020 --> 00:10:56,370
that we could spend time
with pulling out information

264
00:10:56,370 --> 00:10:57,257
over the years.

265
00:10:57,257 --> 00:10:59,770
And so we have extreme weather,

266
00:10:59,770 --> 00:11:02,400
which includes flooding and high winds.

267
00:11:02,400 --> 00:11:03,860
We have our pest category,

268
00:11:03,860 --> 00:11:06,370
which we divided into advancing invasives,

269
00:11:06,370 --> 00:11:09,030
established invasives and native pests.

270
00:11:09,030 --> 00:11:11,400
We also have fire and we have droughts.

271
00:11:11,400 --> 00:11:14,200
And again, we recognize that this is not

272
00:11:14,200 --> 00:11:16,520
inclusive of every type
of important driver.

273
00:11:16,520 --> 00:11:19,590
These are just the ones we
sort of had time to dive into

274
00:11:19,590 --> 00:11:22,010
for the first version of this project.

275
00:11:22,010 --> 00:11:23,410
And then our responses

276
00:11:23,410 --> 00:11:25,770
that we were able to
aggregate information for

277
00:11:25,770 --> 00:11:28,740
were stream macroinvertebrates,

278
00:11:28,740 --> 00:11:31,330
invasive plants and cold water fisheries.

279
00:11:31,330 --> 00:11:34,010
So these are three systems

280
00:11:34,010 --> 00:11:37,490
or communities that are
impacted very clearly

281
00:11:37,490 --> 00:11:38,360
by disturbance events.

282
00:11:38,360 --> 00:11:39,920
There's a lot of research

283
00:11:39,920 --> 00:11:43,270
on these systems being
indications of disturbance.

284
00:11:43,270 --> 00:11:46,210
And so we've compiled information
about those on the site

285
00:11:46,210 --> 00:11:48,210
and given a little bit more information.

286
00:11:49,940 --> 00:11:52,320
And then finally, before Jim jumps in

287
00:11:52,320 --> 00:11:54,320
with the analysis of our drivers,

288
00:11:54,320 --> 00:11:56,570
I just wanted to revisit
some quick vocabulary

289
00:11:56,570 --> 00:11:59,340
from the beginning to sort
of frame the analysis.

290
00:11:59,340 --> 00:12:00,760
So as I mentioned earlier,

291
00:12:00,760 --> 00:12:04,070
we really focused on extent,
severity and frequency

292
00:12:04,070 --> 00:12:06,120
as our metrics of change,

293
00:12:06,120 --> 00:12:08,920
and that's what our trends
will be divided into.

294
00:12:08,920 --> 00:12:11,280
And so just to make sure
we're all on the same page,

295
00:12:11,280 --> 00:12:12,550
extent is thinking about

296
00:12:12,550 --> 00:12:16,150
is the amount of area affected changing?

297
00:12:16,150 --> 00:12:18,589
Are disturbance regimes
happening in more places?

298
00:12:18,589 --> 00:12:19,590
Basically.

299
00:12:19,590 --> 00:12:22,270
The severity, so, is
severity of the impact

300
00:12:22,270 --> 00:12:23,970
of disturbance changing?

301
00:12:23,970 --> 00:12:25,530
Are disturbance lasting longer?

302
00:12:25,530 --> 00:12:27,340
Are they happening with more intensity?

303
00:12:27,340 --> 00:12:28,940
That would sort of all be encompassed

304
00:12:28,940 --> 00:12:30,570
in the severity category

305
00:12:30,570 --> 00:12:32,137
and then finally frequency,

306
00:12:32,137 --> 00:12:34,230
are disturbance events
happening more often?

307
00:12:34,230 --> 00:12:38,310
So have occurrences increased,
decreased, stayed the same?

308
00:12:38,310 --> 00:12:41,350
Those are sort of the main
metrics that we're using

309
00:12:41,350 --> 00:12:42,720
that Jim will show us more.

310
00:12:42,720 --> 00:12:45,663
So I'm gonna stop sharing
and let Jim take over.

311
00:12:53,360 --> 00:12:55,450
- Thanks Pia and as I pull this up here,

312
00:12:55,450 --> 00:12:57,823
let's make sure we're looking good there.

313
00:13:02,330 --> 00:13:04,390
Can you see my presentation screen?

314
00:13:04,390 --> 00:13:05,510
Yes, great.

315
00:13:05,510 --> 00:13:07,520
So, thank you for setting that up

316
00:13:07,520 --> 00:13:11,817
and my goal here is to walk
through some of the drivers

317
00:13:12,780 --> 00:13:14,700
and kind of give a high-level overview

318
00:13:14,700 --> 00:13:16,180
of what we've found in terms of trends

319
00:13:16,180 --> 00:13:18,410
and then where there are
some interesting pieces,

320
00:13:18,410 --> 00:13:21,010
we'll kind of dive into
those a little bit more.

321
00:13:21,010 --> 00:13:22,680
So we're gonna kind of
cover a lot of ground

322
00:13:22,680 --> 00:13:23,910
and a lot of depth,

323
00:13:23,910 --> 00:13:25,640
but just to wait to try and show

324
00:13:25,640 --> 00:13:29,160
what you can use this tool
for in terms of summary

325
00:13:29,160 --> 00:13:32,480
and thinking about these
different disturbance drivers

326
00:13:32,480 --> 00:13:36,760
and how we kind of came to some
findings from this project.

327
00:13:36,760 --> 00:13:39,100
So first we'll talk about high winds.

328
00:13:39,100 --> 00:13:39,933
High wind is defined

329
00:13:39,933 --> 00:13:42,040
as anything greater than 55 miles an hour

330
00:13:42,040 --> 00:13:43,750
based on established scales.

331
00:13:43,750 --> 00:13:47,530
We use some five second fastest
wind speed data from NOAA,

332
00:13:47,530 --> 00:13:51,040
which covers from 2001 to 2020,

333
00:13:51,040 --> 00:13:56,040
and gives us over 73
stations with 1800 events.

334
00:13:56,630 --> 00:14:00,960
And these are stations that
have consistent reporting

335
00:14:00,960 --> 00:14:01,870
across the time,

336
00:14:01,870 --> 00:14:04,700
so we can do that kind of
temporal trend analysis.

337
00:14:04,700 --> 00:14:06,270
So looking at our key questions

338
00:14:06,270 --> 00:14:10,910
around frequency, extent and severity,

339
00:14:10,910 --> 00:14:12,910
we can ask, are high winds
becoming more frequent?

340
00:14:12,910 --> 00:14:15,370
Based on this analysis, no, they're not.

341
00:14:15,370 --> 00:14:17,900
Are they happening in more places,

342
00:14:17,900 --> 00:14:20,600
letting up more stations
across the region?

343
00:14:20,600 --> 00:14:23,610
Yes, we are seeing regionally
that there are increases

344
00:14:23,610 --> 00:14:25,740
in high wind events,
which can topple trees

345
00:14:25,740 --> 00:14:27,856
or cause significant damage to forests

346
00:14:27,856 --> 00:14:31,023
in both the regional sense
and in the states shown.

347
00:14:32,180 --> 00:14:33,500
Are they getting more severe?

348
00:14:33,500 --> 00:14:36,700
Are we having more higher wind events,

349
00:14:36,700 --> 00:14:39,140
the maximum wind speed going up?

350
00:14:39,140 --> 00:14:42,490
No, they're getting less severe over time.

351
00:14:42,490 --> 00:14:45,660
And we see that pretty
consistently across the board.

352
00:14:45,660 --> 00:14:48,720
So the first one becoming more frequent,

353
00:14:48,720 --> 00:14:51,720
we just don't have a
statistical significance

354
00:14:51,720 --> 00:14:55,530
in more often occurrence of high winds,

355
00:14:55,530 --> 00:14:58,140
but these other two I'll
dive into a little bit more.

356
00:14:58,140 --> 00:15:00,720
So looking at high wind events happening

357
00:15:00,720 --> 00:15:03,850
in more than one place,
more places over time,

358
00:15:03,850 --> 00:15:06,010
the number of stations that
are reporting what event

359
00:15:06,010 --> 00:15:09,150
is going up statistically
over the last 20 years.

360
00:15:09,150 --> 00:15:11,630
So we do see this pattern
and this pattern holds

361
00:15:11,630 --> 00:15:14,793
in Connecticut, Massachusetts,
New York and Rhode Island.

362
00:15:16,320 --> 00:15:18,590
Are high wind events getting more severe?

363
00:15:18,590 --> 00:15:20,070
For this we looked at both

364
00:15:20,070 --> 00:15:23,750
the maximum wind speed
on average per year,

365
00:15:23,750 --> 00:15:27,240
as well as the number of
events in the 95th percentile

366
00:15:27,240 --> 00:15:29,610
for the entire year.

367
00:15:29,610 --> 00:15:33,200
So looking at that first
one, average max wind speed,

368
00:15:33,200 --> 00:15:36,920
there's definitely a
statistically significant decrease

369
00:15:36,920 --> 00:15:39,820
in that metric over time.

370
00:15:39,820 --> 00:15:43,350
The number of events
in the 95th percentile,

371
00:15:43,350 --> 00:15:44,183
it's a bit skewed

372
00:15:44,183 --> 00:15:46,720
because of the presence of
Hurricane Katrina in the record.

373
00:15:46,720 --> 00:15:48,950
So we do see a drop,

374
00:15:48,950 --> 00:15:53,120
but the signal is perhaps slightly driven

375
00:15:53,120 --> 00:15:54,400
by that large event.

376
00:15:54,400 --> 00:15:57,680
So no high wind events are
not getting more severe

377
00:15:57,680 --> 00:15:59,410
based on these metrics,

378
00:15:59,410 --> 00:16:00,570
and we are seeing this hole

379
00:16:00,570 --> 00:16:02,060
pretty much across the entire region

380
00:16:02,060 --> 00:16:03,560
with the exception of Vermont.

381
00:16:06,370 --> 00:16:07,783
Switching over to flooding,

382
00:16:09,010 --> 00:16:12,010
we define flooding as gauge
levels above flood stage,

383
00:16:12,010 --> 00:16:14,360
which is defined by USGS and NOAA.

384
00:16:14,360 --> 00:16:17,350
And we combined these two data sets

385
00:16:17,350 --> 00:16:20,100
to pull out records from gauges

386
00:16:20,100 --> 00:16:24,460
that have instantaneous stream levels

387
00:16:24,460 --> 00:16:29,040
and the a flood event database from NOAA.

388
00:16:29,040 --> 00:16:31,380
So it allows us to correlate

389
00:16:31,380 --> 00:16:32,970
the heights of those stream gauges

390
00:16:32,970 --> 00:16:35,320
with the flood events that are recorded.

391
00:16:35,320 --> 00:16:37,410
And then we can look at
if those flood events

392
00:16:37,410 --> 00:16:38,550
are getting more severe.

393
00:16:38,550 --> 00:16:40,590
There are, if you look into the tool,

394
00:16:40,590 --> 00:16:42,030
there's a real detailed breakdown

395
00:16:42,030 --> 00:16:44,960
by different severities of flood category.

396
00:16:44,960 --> 00:16:48,550
But here today, I'll just
talk about general patterns.

397
00:16:48,550 --> 00:16:49,700
Combining these data sets,

398
00:16:49,700 --> 00:16:54,400
we get 12 years of data at 179 stations

399
00:16:54,400 --> 00:16:55,653
with consistent records.

400
00:16:56,630 --> 00:16:58,840
So looking at the trends,

401
00:16:58,840 --> 00:16:59,673
across the board,

402
00:16:59,673 --> 00:17:03,430
we do not have any significant
trends at the regional scale,

403
00:17:03,430 --> 00:17:04,720
nor really at the state of scale.

404
00:17:04,720 --> 00:17:06,380
There's a couple of pieces,

405
00:17:06,380 --> 00:17:08,240
but it's really not a clear picture

406
00:17:08,240 --> 00:17:09,540
of increasing or decreasing

407
00:17:09,540 --> 00:17:13,100
in frequency, extent or severity

408
00:17:13,100 --> 00:17:15,950
for flooding based on these
categories for this data set.

409
00:17:17,094 --> 00:17:20,910
And that's not to say there
aren't localized patterns

410
00:17:20,910 --> 00:17:22,200
that will be missed

411
00:17:22,200 --> 00:17:24,390
in this kind of regional
and state level analysis,

412
00:17:24,390 --> 00:17:25,910
but given our charts

413
00:17:25,910 --> 00:17:27,070
to kinda look across the region

414
00:17:27,070 --> 00:17:28,420
and see if we see these shifts,

415
00:17:28,420 --> 00:17:30,020
we're not seeing it in flooding.

416
00:17:31,730 --> 00:17:33,810
Moving on to fire.

417
00:17:33,810 --> 00:17:38,810
This is somewhat of a less
common topic in the Northeast

418
00:17:39,590 --> 00:17:40,730
in terms of forest disturbance,

419
00:17:40,730 --> 00:17:43,490
especially when we look at
the national conversation

420
00:17:43,490 --> 00:17:45,530
around fire and our forests,

421
00:17:45,530 --> 00:17:47,680
but we did wanna examine this one

422
00:17:47,680 --> 00:17:49,870
'cause it's increasing interest,

423
00:17:49,870 --> 00:17:52,960
especially as climate change
starts to shift patterns

424
00:17:52,960 --> 00:17:54,800
of a suitable species

425
00:17:54,800 --> 00:17:57,810
and disturbance machines
across our landscape.

426
00:17:57,810 --> 00:18:01,240
So we looked at a research grade database

427
00:18:01,240 --> 00:18:03,970
called the Fire Program Analysis
by our current database,

428
00:18:03,970 --> 00:18:06,730
which as a way of integrating fire reports

429
00:18:06,730 --> 00:18:08,570
from across the region.

430
00:18:08,570 --> 00:18:11,600
And we looked at any fire
with a reported acreage

431
00:18:11,600 --> 00:18:15,900
between 1992 and 2018, which
is the extent of this data set.

432
00:18:15,900 --> 00:18:20,530
And that leads to over 125,000 fires

433
00:18:20,530 --> 00:18:23,170
that we had data to analyze.

434
00:18:23,170 --> 00:18:25,160
So pretty robust data source

435
00:18:25,160 --> 00:18:27,370
that said there is a lot
of data from New York

436
00:18:27,370 --> 00:18:31,010
as you can see in the map,

437
00:18:31,010 --> 00:18:34,090
there's a concentration of fire reporting

438
00:18:34,090 --> 00:18:38,977
in areas that have a longer
history of fire occurrence

439
00:18:38,977 --> 00:18:40,173
and fire management.

440
00:18:42,210 --> 00:18:44,320
So are fires becoming more frequent?

441
00:18:44,320 --> 00:18:45,763
Are we having more per year?

442
00:18:46,600 --> 00:18:49,220
Yes, we do see that
occurrences are going up

443
00:18:49,220 --> 00:18:53,510
in this data set both
regionally and in some states.

444
00:18:53,510 --> 00:18:56,580
Are they burning more overall area?

445
00:18:56,580 --> 00:18:58,920
And this is an interesting one, no,

446
00:18:58,920 --> 00:19:03,910
but we are seeing a decrease
in the average size of fires.

447
00:19:03,910 --> 00:19:05,630
So they're not burning more area,

448
00:19:05,630 --> 00:19:08,630
but maybe each individual fire
is taking a little less area.

449
00:19:09,810 --> 00:19:11,370
And are they burning more area at once?

450
00:19:11,370 --> 00:19:14,810
Is our fire size going up?

451
00:19:14,810 --> 00:19:15,730
No. And when I say no,

452
00:19:15,730 --> 00:19:18,940
we just don't see any significant change

453
00:19:20,540 --> 00:19:21,730
at the regional level,

454
00:19:21,730 --> 00:19:25,723
at the state level, we do
see some interesting results.

455
00:19:27,710 --> 00:19:31,163
So, are fires becoming more frequent?

456
00:19:32,900 --> 00:19:35,690
We use the metric of the
number of fires reported.

457
00:19:35,690 --> 00:19:38,610
You can see that over time,
this is trending upwards,

458
00:19:38,610 --> 00:19:40,510
at least in the record that we have.

459
00:19:40,510 --> 00:19:44,560
And this a statistically
significant increase holds

460
00:19:44,560 --> 00:19:47,220
both regionally and in Connecticut,
Massachusetts, New York,

461
00:19:47,220 --> 00:19:49,270
and in somewhat interestingly in Vermont.

462
00:19:52,000 --> 00:19:55,560
Are fires burning more overall area?

463
00:19:55,560 --> 00:19:57,630
I'll start out by saying
that general question,

464
00:19:57,630 --> 00:19:59,210
no, it's unclear.

465
00:19:59,210 --> 00:20:01,290
We don't see a trend

466
00:20:01,290 --> 00:20:05,970
in the size of individual fires over time,

467
00:20:05,970 --> 00:20:09,530
but we do see this a
statistically significant decrease

468
00:20:09,530 --> 00:20:13,310
in average fire size,

469
00:20:13,310 --> 00:20:15,230
whether this is a real signal

470
00:20:15,230 --> 00:20:16,960
or a result of more smaller fires

471
00:20:16,960 --> 00:20:20,080
being reported into the
database as an open question.

472
00:20:20,080 --> 00:20:22,010
But this decrease in average area

473
00:20:22,010 --> 00:20:23,920
does hold across these states,

474
00:20:23,920 --> 00:20:26,020
Connecticut, Maine, New York, and Vermont.

475
00:20:29,490 --> 00:20:33,450
Looking next at drought, we
used the US drought monitor,

476
00:20:33,450 --> 00:20:35,730
and probably many of you are familiar

477
00:20:35,730 --> 00:20:38,520
with the drought monitor
in some way or another.

478
00:20:38,520 --> 00:20:39,790
It is a great resource

479
00:20:39,790 --> 00:20:42,930
for monitoring ongoing drought
conditions across the state.

480
00:20:42,930 --> 00:20:44,730
And drought can have numerous ways

481
00:20:44,730 --> 00:20:46,640
of impacting forest ecosystems

482
00:20:46,640 --> 00:20:51,640
from stressing trees to lowering flows,

483
00:20:51,960 --> 00:20:54,091
to limiting groundwater recharged.

484
00:20:54,091 --> 00:20:57,290
So the ways that this
can affect the ecosystem

485
00:20:57,290 --> 00:20:58,123
are pretty broad,

486
00:20:58,123 --> 00:21:00,650
but it's certainly an
important consideration.

487
00:21:00,650 --> 00:21:04,410
The drought monitor
provides drought conditions

488
00:21:04,410 --> 00:21:06,560
in a number of drought status levels.

489
00:21:06,560 --> 00:21:09,740
And we looked at each of those in the tool

490
00:21:09,740 --> 00:21:10,683
and in the report.

491
00:21:11,840 --> 00:21:15,170
And since it's a spatially
contiguous data set

492
00:21:15,170 --> 00:21:17,900
that's updated on a regular
basis throughout the year,

493
00:21:17,900 --> 00:21:21,300
we're kind of working with
a continuous data source

494
00:21:21,300 --> 00:21:23,133
between 2000 and 2020.

495
00:21:25,130 --> 00:21:28,050
For the purposes of this
webinar is looking broadly at,

496
00:21:28,050 --> 00:21:33,050
do we see any trends in overall
drought through the record.

497
00:21:33,880 --> 00:21:35,740
Are droughts becoming more frequent?

498
00:21:35,740 --> 00:21:37,380
There's no sign of that.

499
00:21:37,380 --> 00:21:40,730
But when we looked at
some of the categories

500
00:21:40,730 --> 00:21:44,140
specifically at abnormally dry conditions,

501
00:21:44,140 --> 00:21:46,400
we're seeing Connecticut,
Massachusetts, and Vermont

502
00:21:46,400 --> 00:21:48,300
showing a slight increase in the length

503
00:21:48,300 --> 00:21:50,420
of those dry conditions.

504
00:21:50,420 --> 00:21:52,513
Are droughts affecting more area

505
00:21:52,513 --> 00:21:56,210
and becoming more widespread
across the region? No.

506
00:21:56,210 --> 00:21:57,670
No, we don't see a signal in that

507
00:21:57,670 --> 00:22:00,490
in any of the categories or overall.

508
00:22:00,490 --> 00:22:01,820
And are they're becoming more severe?

509
00:22:01,820 --> 00:22:04,970
In other words, are droughts
going from abnormally dry

510
00:22:04,970 --> 00:22:07,090
and moderate drought into the severe

511
00:22:07,090 --> 00:22:09,580
and extreme drought categories.

512
00:22:09,580 --> 00:22:11,498
And again, from the state of set,

513
00:22:11,498 --> 00:22:14,440
we don't see statistical
evidence that that's happening.

514
00:22:14,440 --> 00:22:15,810
I did wanna show,

515
00:22:15,810 --> 00:22:19,010
this is a little bit of a
complicated chart to interpret,

516
00:22:19,010 --> 00:22:21,910
but essentially it just shows
the total number of weeks

517
00:22:21,910 --> 00:22:24,650
and abnormally dry
conditions for Massachusetts,

518
00:22:24,650 --> 00:22:27,410
Vermont and Connecticut over the record.

519
00:22:27,410 --> 00:22:31,400
And there is an overall increase

520
00:22:31,400 --> 00:22:34,070
in these states reporting places

521
00:22:34,070 --> 00:22:35,780
that are in these conditions.

522
00:22:35,780 --> 00:22:38,760
So the trend lines are
statistically significant.

523
00:22:38,760 --> 00:22:42,600
So potentially we're having more time

524
00:22:42,600 --> 00:22:45,330
spent in drought conditions
in these three states,

525
00:22:45,330 --> 00:22:48,580
but this is a fairly limited category

526
00:22:48,580 --> 00:22:50,950
and there are other ways
of thinking about it

527
00:22:50,950 --> 00:22:52,590
that might be worth exploring,

528
00:22:52,590 --> 00:22:56,363
but generally the patterns
and droughts are not clear.

529
00:22:59,290 --> 00:23:00,270
The next category,

530
00:23:00,270 --> 00:23:02,230
I'm gonna talk about a
little bit differently

531
00:23:02,230 --> 00:23:06,000
because of the way that these
disturbance drivers operate

532
00:23:06,000 --> 00:23:08,520
and the nature of the data source.

533
00:23:08,520 --> 00:23:11,260
So looking at pests and pathogens,

534
00:23:11,260 --> 00:23:16,260
these are insects diseases
that affect tree canopies

535
00:23:16,730 --> 00:23:19,190
and eventually tree health.

536
00:23:19,190 --> 00:23:23,830
We looked at a data source,
which is the aerial detection,

537
00:23:23,830 --> 00:23:25,260
insect disease surveys.

538
00:23:25,260 --> 00:23:27,970
They're primarily flown
by state forestry agencies

539
00:23:27,970 --> 00:23:30,370
and US forest service
FEMC has done some work

540
00:23:30,370 --> 00:23:34,150
to pull together historical
data for this purpose.

541
00:23:34,150 --> 00:23:36,760
And we looked at damage,

542
00:23:36,760 --> 00:23:38,960
both the total area defoliated or killed

543
00:23:38,960 --> 00:23:41,990
and then also the share
of damage that's mortality

544
00:23:41,990 --> 00:23:44,840
or killing of the trees from an agent.

545
00:23:44,840 --> 00:23:49,840
And we have a data set that
nominally spans 1918 to 2020.

546
00:23:52,000 --> 00:23:54,970
There's some disparities in coverage

547
00:23:54,970 --> 00:23:57,360
for states in the earlier
part of the record.

548
00:23:57,360 --> 00:24:00,550
We know we have pretty consistent coverage

549
00:24:00,550 --> 00:24:03,750
across states from 1997 onward,

550
00:24:03,750 --> 00:24:06,210
but we did look at the entire
record for this project

551
00:24:06,210 --> 00:24:10,313
of over 130,000 polygons of
mapped damage on the landscape.

552
00:24:11,910 --> 00:24:14,860
But lumping all these together
wouldn't totally make sense,

553
00:24:14,860 --> 00:24:18,250
so we looked at three types of pests,

554
00:24:18,250 --> 00:24:20,600
those that are native and endemic pests,

555
00:24:20,600 --> 00:24:22,770
such as forest tent caterpillar,

556
00:24:22,770 --> 00:24:25,390
they've been here and been
established in these systems.

557
00:24:25,390 --> 00:24:29,100
The systems has evolved with
these pests as part of them.

558
00:24:29,100 --> 00:24:31,099
We looked at established invasives

559
00:24:31,099 --> 00:24:32,200
or invasives that have been here

560
00:24:32,200 --> 00:24:33,620
and introduced for a long time.

561
00:24:33,620 --> 00:24:36,670
And so taking on a role in that ecosystem

562
00:24:36,670 --> 00:24:37,740
with a longer record,

563
00:24:37,740 --> 00:24:39,730
and then we also looked
at advancing invasives

564
00:24:39,730 --> 00:24:41,440
are those that are introduced,

565
00:24:41,440 --> 00:24:43,140
by maybe moving into the region

566
00:24:44,060 --> 00:24:47,163
or throughout the region in a progression.

567
00:24:48,150 --> 00:24:51,270
So I'm not gonna go into
the same level of detail

568
00:24:51,270 --> 00:24:53,760
for each of these, but
instead just talk about

569
00:24:53,760 --> 00:24:57,130
some notable trends that
we see in those key,

570
00:24:57,130 --> 00:24:59,730
somewhat like indicator pests

571
00:24:59,730 --> 00:25:01,890
that have a significant
presence in the region.

572
00:25:01,890 --> 00:25:04,053
The first is a forest tent caterpillar.

573
00:25:05,210 --> 00:25:08,620
We do see a decreasing extent.

574
00:25:08,620 --> 00:25:10,330
However, I would suspect

575
00:25:10,330 --> 00:25:11,810
that this is largely driven by

576
00:25:11,810 --> 00:25:14,710
an early large event in New York,

577
00:25:14,710 --> 00:25:16,980
but overall, even in
the later time periods

578
00:25:16,980 --> 00:25:20,120
that a decreasing trend is as apparent.

579
00:25:20,120 --> 00:25:22,100
So we're not seeing as
much area defoliated

580
00:25:22,100 --> 00:25:25,593
by a forest tent caterpillar
as we were previously.

581
00:25:27,030 --> 00:25:29,150
Looking at spruce budworm,

582
00:25:29,150 --> 00:25:33,270
which is another endemic
pest in the region

583
00:25:33,270 --> 00:25:34,803
that has an outbreak cycle,

584
00:25:35,650 --> 00:25:38,000
it does operate on a fairly long cycle.

585
00:25:38,000 --> 00:25:41,710
And so seeing trends in
extent is challenging,

586
00:25:41,710 --> 00:25:42,900
but based on the data

587
00:25:42,900 --> 00:25:44,680
that is in the area of detection surveys,

588
00:25:44,680 --> 00:25:47,353
that overall area damage is going down.

589
00:25:49,930 --> 00:25:52,100
And I'll note that in
the native pest category,

590
00:25:52,100 --> 00:25:56,830
we really didn't see any reportable trends

591
00:25:56,830 --> 00:26:00,900
around severity or around frequency.

592
00:26:00,900 --> 00:26:04,640
And again, because these
are outbreak cycle pests,

593
00:26:04,640 --> 00:26:06,630
frequency has different meaning.

594
00:26:06,630 --> 00:26:08,952
There is some indication that the period

595
00:26:08,952 --> 00:26:10,253
between these might be lessening,

596
00:26:10,253 --> 00:26:11,870
but it's not a significant change

597
00:26:13,620 --> 00:26:15,540
looking at established invasives.

598
00:26:15,540 --> 00:26:17,300
So these are ones that
have been introduced

599
00:26:17,300 --> 00:26:19,683
and been around for awhile.

600
00:26:22,130 --> 00:26:24,010
The first step is lymantria dispar,

601
00:26:24,010 --> 00:26:25,830
formerly known as gypsy moth,

602
00:26:25,830 --> 00:26:30,010
it is showing an increasing
overall mortality

603
00:26:30,010 --> 00:26:32,660
and an increasing share of
damage that's mortality,

604
00:26:32,660 --> 00:26:36,740
and anyone who has followed
the trends in this pest

605
00:26:36,740 --> 00:26:37,573
for the last little bit,

606
00:26:37,573 --> 00:26:39,610
know about the struggles
in Southern New England,

607
00:26:39,610 --> 00:26:42,160
combining lymantria dispar

608
00:26:42,160 --> 00:26:45,990
and drought conditions
and multi-year outbreaks

609
00:26:45,990 --> 00:26:49,710
and the increase that
we've seen in the Northern

610
00:26:49,710 --> 00:26:52,430
half of the region in
the last couple of years.

611
00:26:52,430 --> 00:26:56,210
So, a statistically significant
increase in mortality,

612
00:26:56,210 --> 00:26:58,260
both in New Hampshire and Massachusetts,

613
00:26:58,260 --> 00:26:59,823
as well as the regional scale.

614
00:27:03,960 --> 00:27:08,470
Another pest that has
been here for a long time

615
00:27:08,470 --> 00:27:12,970
and is of particular concern
in Maine is the browntail moth.

616
00:27:12,970 --> 00:27:16,825
And we are seeing an increase
in the overall extent

617
00:27:16,825 --> 00:27:21,825
of that pest damage to trees
in Maine to the record.

618
00:27:22,647 --> 00:27:24,330
And you can see is quite
a significant increase

619
00:27:24,330 --> 00:27:25,973
in the last few years.

620
00:27:29,960 --> 00:27:32,690
Turning to advancing invasives.

621
00:27:32,690 --> 00:27:37,690
We don't have enough data
on these to report trends.

622
00:27:38,050 --> 00:27:39,900
So we're really looking at
this more as a baseline.

623
00:27:39,900 --> 00:27:41,820
These are pests of concern

624
00:27:41,820 --> 00:27:46,820
that we know will be
important to understand

625
00:27:47,050 --> 00:27:48,760
their disturbance dynamics going forward,

626
00:27:48,760 --> 00:27:50,680
but we just don't have the information

627
00:27:50,680 --> 00:27:53,033
needed to analyze trends over time.

628
00:27:55,030 --> 00:27:56,590
So looking at emerald ash borer,

629
00:27:56,590 --> 00:27:59,740
this is a fairly new
introduction to our region.

630
00:27:59,740 --> 00:28:01,770
It's been in New York for awhile.

631
00:28:01,770 --> 00:28:04,450
Southern new England has dealt with it.

632
00:28:04,450 --> 00:28:05,900
It's moving it's way through Maine

633
00:28:05,900 --> 00:28:08,400
and New Hampshire and Vermont right now.

634
00:28:08,400 --> 00:28:12,570
So a significant increase in
observable damage from the air.

635
00:28:12,570 --> 00:28:14,050
And it's a reminder that this is,

636
00:28:14,050 --> 00:28:16,250
has to be visible from a plane.

637
00:28:16,250 --> 00:28:18,470
So we are seeing that
increase at uptake in acreage

638
00:28:18,470 --> 00:28:19,853
affected by EAB.

639
00:28:21,040 --> 00:28:24,100
Hemlock woolly adelgid has
a really strong control

640
00:28:24,100 --> 00:28:26,150
on its populations from
winter temperatures.

641
00:28:26,150 --> 00:28:29,050
So the cycles you see in acres damaged

642
00:28:29,050 --> 00:28:31,090
really kind of varies with the winter

643
00:28:31,090 --> 00:28:32,130
and southern pine beetle

644
00:28:32,130 --> 00:28:34,930
is limited almost exclusively to New York

645
00:28:34,930 --> 00:28:37,000
and just doesn't have much
of a presence in the region,

646
00:28:37,000 --> 00:28:39,470
but there is an initial record of damage,

647
00:28:39,470 --> 00:28:41,810
and as this pest moves in,

648
00:28:41,810 --> 00:28:44,640
this is something that can
be updated and examined.

649
00:28:44,640 --> 00:28:45,984
So overall,

650
00:28:45,984 --> 00:28:47,220
we just don't have enough
observations in the region

651
00:28:47,220 --> 00:28:48,600
to see trends of this data source,

652
00:28:48,600 --> 00:28:50,780
but it does provide a baseline

653
00:28:50,780 --> 00:28:53,200
for thinking about how we would monitor

654
00:28:53,200 --> 00:28:56,623
advancing invasives as they
move through the region.

655
00:28:58,170 --> 00:28:59,820
So I know I covered a lot,

656
00:28:59,820 --> 00:29:02,280
but that's a quick
overview of the snapshots,

657
00:29:02,280 --> 00:29:04,830
these trend information graphs,

658
00:29:04,830 --> 00:29:07,530
and the findings are available
in the technical report

659
00:29:07,530 --> 00:29:10,713
and website that Pia will dive into next.

660
00:29:15,910 --> 00:29:20,910
- Hi, I'm gonna shift
this over to the websites.

661
00:29:25,410 --> 00:29:26,470
And I just wanted to acknowledge

662
00:29:26,470 --> 00:29:29,370
that I saw questions in the
chat and we will get to those.

663
00:29:40,330 --> 00:29:42,903
So is everyone seeing this screen?

664
00:29:44,610 --> 00:29:46,800
Yes. Okay, thank you.

665
00:29:46,800 --> 00:29:48,660
So I would spend a little bit of time

666
00:29:48,660 --> 00:29:50,100
just walking through the tool

667
00:29:50,100 --> 00:29:52,830
and I very much encourage
you to look at it

668
00:29:52,830 --> 00:29:55,530
on your own afterward
if you have an interest,

669
00:29:55,530 --> 00:29:56,810
because it will be quick,

670
00:29:56,810 --> 00:29:58,550
but we're always available
to answer your questions.

671
00:29:58,550 --> 00:30:03,140
but this is the sort of pop-up
at the front of the website

672
00:30:03,140 --> 00:30:05,900
and I left it up because I
just really wanted to emphasize

673
00:30:05,900 --> 00:30:09,090
that this is sort of the
first version of this website.

674
00:30:09,090 --> 00:30:11,410
So it is complete for its first iteration,

675
00:30:11,410 --> 00:30:12,920
but we know that there are probably

676
00:30:12,920 --> 00:30:15,130
a lot of monitoring
efforts that we could add,

677
00:30:15,130 --> 00:30:17,650
or there might be comments
that folks have for feedback.

678
00:30:17,650 --> 00:30:19,750
So if you'd like to share that with us,

679
00:30:19,750 --> 00:30:20,610
we would love to hear,

680
00:30:20,610 --> 00:30:22,410
and you can do that right here

681
00:30:22,410 --> 00:30:23,950
through our contact information.

682
00:30:23,950 --> 00:30:27,740
You can share protocols, et cetera.

683
00:30:27,740 --> 00:30:29,760
And then we also have another tool

684
00:30:29,760 --> 00:30:32,500
that is related to this information

685
00:30:32,500 --> 00:30:34,320
called The Northeastern
Forest Health Atlas

686
00:30:34,320 --> 00:30:36,670
and you can learn more
about that here as well.

687
00:30:38,700 --> 00:30:39,940
So if you go to the website,

688
00:30:39,940 --> 00:30:42,090
there's sort of a couple of different ways

689
00:30:42,090 --> 00:30:43,550
to interact with it.

690
00:30:43,550 --> 00:30:45,980
And I'll start as if you're someone

691
00:30:45,980 --> 00:30:48,560
who hasn't decided what
you wanna learn about yet.

692
00:30:48,560 --> 00:30:50,240
So if you come to the page,

693
00:30:50,240 --> 00:30:52,670
you can kind of see a brief introduction

694
00:30:52,670 --> 00:30:56,570
about what's the purpose
and what's going on here.

695
00:30:56,570 --> 00:31:00,540
And you can see the disturbances
in their broader categories

696
00:31:00,540 --> 00:31:02,760
that we've selected and
also their responses.

697
00:31:02,760 --> 00:31:03,730
And from this page,

698
00:31:03,730 --> 00:31:07,690
you could explore any sub
categories that are related.

699
00:31:07,690 --> 00:31:09,840
So if you're interested
in extreme weather,

700
00:31:10,984 --> 00:31:12,060
you can click View,

701
00:31:12,060 --> 00:31:15,250
and you'll be taken to sort
of a shorter description

702
00:31:15,250 --> 00:31:20,250
of the categories that are
within this larger category,

703
00:31:20,700 --> 00:31:21,900
and at the moment,

704
00:31:21,900 --> 00:31:25,420
there's just the drivers
that we showed earlier.

705
00:31:25,420 --> 00:31:28,870
But the hope is that there'll
be more to add in the future.

706
00:31:28,870 --> 00:31:32,113
So this intermediate page will be helpful.

707
00:31:35,180 --> 00:31:37,240
I will go back to the
homepage really quickly, too,

708
00:31:37,240 --> 00:31:41,800
just to show you that you
can look through all of these

709
00:31:41,800 --> 00:31:44,430
and find the same sort of information.

710
00:31:44,430 --> 00:31:47,223
And you can also toggle up
here to go back and forth.

711
00:31:48,130 --> 00:31:51,570
The same information is
located here in a driver,

712
00:31:51,570 --> 00:31:53,110
in the response section.

713
00:31:53,110 --> 00:31:54,830
So if you've already visited the page

714
00:31:54,830 --> 00:31:56,210
and you know what you wanna look at,

715
00:31:56,210 --> 00:31:58,380
you can get to the same information here.

716
00:31:58,380 --> 00:32:01,923
These are all of the drivers,
and these are our responses.

717
00:32:02,910 --> 00:32:06,753
I'm gonna take us now into
one of the, we'll do floods.

718
00:32:07,700 --> 00:32:08,910
So on the flood page,

719
00:32:08,910 --> 00:32:11,860
you'll see more of the
trend analysis information

720
00:32:11,860 --> 00:32:13,220
that Jim walked through,

721
00:32:13,220 --> 00:32:15,930
but you have a lot more
ability to click and select

722
00:32:15,930 --> 00:32:17,980
different types of information.

723
00:32:17,980 --> 00:32:21,560
So all of them sort of start
with the whole region selected,

724
00:32:21,560 --> 00:32:23,390
which is what we talked about earlier,

725
00:32:23,390 --> 00:32:26,400
but you can also see
individual state information

726
00:32:26,400 --> 00:32:27,317
that will pop up here

727
00:32:27,317 --> 00:32:31,080
and you can remove regional
information as well.

728
00:32:31,080 --> 00:32:35,280
And if you toggle over
the different trends,

729
00:32:35,280 --> 00:32:37,310
I'm sorry, the different
trend lines on the graphs,

730
00:32:37,310 --> 00:32:39,783
you can see more detailed
information as well,

731
00:32:41,070 --> 00:32:42,060
and on the side here,

732
00:32:42,060 --> 00:32:44,880
you can also download
any of this information

733
00:32:44,880 --> 00:32:46,180
that you're interested in.

734
00:32:47,920 --> 00:32:48,950
For a quick overview,

735
00:32:48,950 --> 00:32:52,070
you have your disturbance
trend summary analysis here,

736
00:32:52,070 --> 00:32:53,653
and your highlights as well.

737
00:32:54,850 --> 00:32:56,890
And then as you scroll down,

738
00:32:56,890 --> 00:32:58,400
you can see additional resources.

739
00:32:58,400 --> 00:33:00,600
And I'm sorry, I should
have shown you that.

740
00:33:02,900 --> 00:33:06,290
There are several tabs
for each of these charts,

741
00:33:06,290 --> 00:33:07,940
because it was easier to look at

742
00:33:07,940 --> 00:33:10,060
the different metrics individually.

743
00:33:10,060 --> 00:33:12,100
So this is frequency.

744
00:33:12,100 --> 00:33:13,390
If there are all of them,

745
00:33:13,390 --> 00:33:16,693
you can look at extent
separately and severity as well.

746
00:33:20,000 --> 00:33:22,180
If possible, there's also
location information.

747
00:33:22,180 --> 00:33:25,220
I think that there are
for all of these data sets

748
00:33:25,220 --> 00:33:26,640
that we are sharing now,

749
00:33:26,640 --> 00:33:29,670
and this is the actual stations
where the data was recorded.

750
00:33:29,670 --> 00:33:31,670
So you can see that information as well.

751
00:33:36,370 --> 00:33:39,530
So these additional resources
are monitoring efforts

752
00:33:39,530 --> 00:33:40,480
that are related,

753
00:33:40,480 --> 00:33:42,610
but were not included
in the trend analysis.

754
00:33:42,610 --> 00:33:44,600
I think that's important to understand.

755
00:33:44,600 --> 00:33:46,320
So the trend analysis

756
00:33:46,320 --> 00:33:48,790
use just the data sets
that Jim highlighted.

757
00:33:48,790 --> 00:33:49,920
And that is because,

758
00:33:49,920 --> 00:33:52,790
although this other
information is interesting,

759
00:33:52,790 --> 00:33:54,300
it might not have had enough breadth,

760
00:33:54,300 --> 00:33:58,110
that might not have went,
had enough historical data,

761
00:33:58,110 --> 00:34:01,240
or it may have only been in
one small plot over time.

762
00:34:01,240 --> 00:34:04,140
So that information is
here and you can look at it

763
00:34:04,140 --> 00:34:05,640
if you'd like to,

764
00:34:05,640 --> 00:34:10,460
it just isn't currently
added to the analysis.

765
00:34:10,460 --> 00:34:11,760
And what you can see is that

766
00:34:11,760 --> 00:34:13,570
if there are any related data products,

767
00:34:13,570 --> 00:34:15,330
you can also grab them here.

768
00:34:15,330 --> 00:34:17,700
And I'm gonna show you
this in a different way

769
00:34:17,700 --> 00:34:18,623
in just a minute.

770
00:34:21,160 --> 00:34:24,593
So I'm gonna take us back to the homepage.

771
00:34:25,540 --> 00:34:27,863
If you've moved, oh, here we go.

772
00:34:30,340 --> 00:34:31,630
Another way you can use the tool,

773
00:34:31,630 --> 00:34:34,830
as if you've already decided
what you wanna look at

774
00:34:34,830 --> 00:34:36,190
in terms of,

775
00:34:36,190 --> 00:34:37,360
if you wanna look at a regional,

776
00:34:37,360 --> 00:34:39,050
from a regional perspective, I'm sorry,

777
00:34:39,050 --> 00:34:41,190
you can go to our
monitoring resources pages,

778
00:34:41,190 --> 00:34:42,960
and this shows that the
same type of information

779
00:34:42,960 --> 00:34:45,800
about where the monitoring
efforts are located

780
00:34:45,800 --> 00:34:47,293
and the studies that are related,

781
00:34:47,293 --> 00:34:48,460
it's the same information

782
00:34:48,460 --> 00:34:51,140
that's in that additional
resources section.

783
00:34:51,140 --> 00:34:52,890
So you can click here on View,

784
00:34:52,890 --> 00:34:55,550
or you could also go to the
monitoring and resources tab,

785
00:34:55,550 --> 00:34:57,220
which will take you here.

786
00:34:57,220 --> 00:34:59,680
So as you can see, it's a
similar type of information,

787
00:34:59,680 --> 00:35:01,430
you have this tabular view

788
00:35:01,430 --> 00:35:02,910
where you can see the data programs

789
00:35:02,910 --> 00:35:04,350
at the monitoring efforts,

790
00:35:04,350 --> 00:35:07,290
you can filter by the state, the subtype

791
00:35:07,290 --> 00:35:09,920
so those are our drivers
again, or our responses

792
00:35:09,920 --> 00:35:12,520
and you can look at the
years and the data products.

793
00:35:13,790 --> 00:35:16,430
You can also see this in a map version.

794
00:35:16,430 --> 00:35:19,100
So all of the different monitoring efforts

795
00:35:19,100 --> 00:35:20,090
are here on the map

796
00:35:20,090 --> 00:35:22,630
and right now they aren't
filtered in any way

797
00:35:22,630 --> 00:35:24,270
so everything is present,

798
00:35:24,270 --> 00:35:27,400
but you can filter here
and various dropdown menus

799
00:35:27,400 --> 00:35:29,150
right now they're all highlighted,

800
00:35:29,150 --> 00:35:32,710
but you could select
various different options,

801
00:35:32,710 --> 00:35:34,470
depending on what you're looking for.

802
00:35:34,470 --> 00:35:37,083
You can categorized by the years.

803
00:35:38,220 --> 00:35:40,920
And you can also search for the name of,

804
00:35:40,920 --> 00:35:42,180
by keyword up here in the top

805
00:35:42,180 --> 00:35:43,480
if you know a specific study,

806
00:35:43,480 --> 00:35:46,060
or if you have an area of interest

807
00:35:46,060 --> 00:35:48,813
that you think might show up
like a region, for example.

808
00:35:52,120 --> 00:35:54,430
You click into the
states and you wanna see

809
00:35:54,430 --> 00:35:57,670
sort of all of the different
categories within that state.

810
00:35:57,670 --> 00:35:59,960
If you haven't filtered anything,
this is what you will see.

811
00:35:59,960 --> 00:36:02,990
If you filtered for just
pests and pathogens and fire,

812
00:36:02,990 --> 00:36:04,147
that's all we'll come up with.

813
00:36:04,147 --> 00:36:07,147
But these are all the studies
divided into those categories,

814
00:36:08,970 --> 00:36:10,250
and you can click in further

815
00:36:10,250 --> 00:36:12,600
and see the names of each
study that's related.

816
00:36:14,640 --> 00:36:15,640
If you decide you wanna look

817
00:36:15,640 --> 00:36:16,960
at one of these studies in particular,

818
00:36:16,960 --> 00:36:20,980
you can click and you get the
separate pop-up video, modal,

819
00:36:20,980 --> 00:36:22,290
sorry,

820
00:36:22,290 --> 00:36:23,300
a separate pop-up modal

821
00:36:23,300 --> 00:36:26,120
that will then show you
any more specific location

822
00:36:26,120 --> 00:36:28,952
information about where the
monitoring effort is happening.

823
00:36:28,952 --> 00:36:30,970
This one doesn't have that.

824
00:36:30,970 --> 00:36:34,410
And a lot of them at this time
haven't been parsed out yet,

825
00:36:34,410 --> 00:36:36,490
but sometimes they will
have plot locations

826
00:36:36,490 --> 00:36:39,220
and if that's available, it will be here.

827
00:36:39,220 --> 00:36:41,380
You can also learn more about the study.

828
00:36:41,380 --> 00:36:43,760
You can get linked to the study itself,

829
00:36:43,760 --> 00:36:46,180
and then if there's any
associated datasets,

830
00:36:46,180 --> 00:36:47,860
you can find them here

831
00:36:47,860 --> 00:36:50,360
and you can be taken in a separate page

832
00:36:50,360 --> 00:36:52,040
to that information as well.

833
00:36:52,040 --> 00:36:53,120
So these studies, as I said,

834
00:36:53,120 --> 00:36:54,620
they're not included
in the trend analysis,

835
00:36:54,620 --> 00:36:56,640
but they still have very
important information

836
00:36:56,640 --> 00:36:59,690
and we hope that if it's
all aggregated in one place,

837
00:36:59,690 --> 00:37:01,230
that people can find that information

838
00:37:01,230 --> 00:37:02,870
and they can do their own trend analysis

839
00:37:02,870 --> 00:37:04,410
or build on a project

840
00:37:04,410 --> 00:37:07,103
and that's sort of the
goal of this section.

841
00:37:10,130 --> 00:37:11,330
The last thing I wanted to show,

842
00:37:11,330 --> 00:37:12,960
I know I'm running out of time

843
00:37:12,960 --> 00:37:14,020
and I know there are questions,

844
00:37:14,020 --> 00:37:16,894
but I wanted to show our
responses a little bit

845
00:37:16,894 --> 00:37:19,870
because I haven't spent very
much time talking about that.

846
00:37:19,870 --> 00:37:21,560
I'll take us to stream macroinvertebrates.

847
00:37:21,560 --> 00:37:23,490
There's three individual pages

848
00:37:23,490 --> 00:37:25,330
for the disturbance responses.

849
00:37:25,330 --> 00:37:27,420
And as I said, there's
no analysis for these

850
00:37:27,420 --> 00:37:31,900
because the data sets
aren't quite as clear,

851
00:37:31,900 --> 00:37:33,690
but there is information about these.

852
00:37:33,690 --> 00:37:36,780
You can find additional
resources that hopefully

853
00:37:36,780 --> 00:37:39,940
as people have recommendations
to this will grow.

854
00:37:39,940 --> 00:37:41,380
These are not monitoring efforts,

855
00:37:41,380 --> 00:37:43,780
these are just resources about
stream macroinvertebrates

856
00:37:43,780 --> 00:37:45,660
or places where you can participate

857
00:37:45,660 --> 00:37:47,293
in citizen science, et cetera,

858
00:37:48,360 --> 00:37:52,010
but then you have a direct
already pre-filtered view

859
00:37:52,010 --> 00:37:54,750
of monitoring efforts
related to this response.

860
00:37:54,750 --> 00:37:55,890
So it works the same way.

861
00:37:55,890 --> 00:37:58,810
You can click in here and
see those pop up menus

862
00:37:58,810 --> 00:38:00,570
and learn more about studies.

863
00:38:00,570 --> 00:38:02,580
Oh, I clicked on the highlighted study.

864
00:38:02,580 --> 00:38:04,050
So that's great, it takes you,

865
00:38:04,050 --> 00:38:04,883
it rotates every month

866
00:38:04,883 --> 00:38:08,720
and you can see a different
highlighted report,

867
00:38:08,720 --> 00:38:12,280
but that information is also
reflected here in this table.

868
00:38:12,280 --> 00:38:13,620
And so you can sort through this table

869
00:38:13,620 --> 00:38:16,280
and find information
about macro invertebrates

870
00:38:16,280 --> 00:38:18,230
and different studies that are ongoing.

871
00:38:23,730 --> 00:38:25,460
I think that's all I'm gonna show today.

872
00:38:25,460 --> 00:38:27,890
I do wanna take a minute to
look at pests and pathogens,

873
00:38:27,890 --> 00:38:29,690
'cause it's a little bit different.

874
00:38:29,690 --> 00:38:31,693
So if you go into pests or pathogens,

875
00:38:32,630 --> 00:38:34,610
you can see that there's these
three different sections.

876
00:38:34,610 --> 00:38:39,610
And within the pests and
pathogens disturbance driver page,

877
00:38:40,900 --> 00:38:42,740
there are some slightly
different graphics.

878
00:38:42,740 --> 00:38:44,560
So of course the analysis were done

879
00:38:44,560 --> 00:38:46,890
in a way that is
appropriate with the data,

880
00:38:46,890 --> 00:38:51,190
but there are multiple different pests

881
00:38:51,190 --> 00:38:53,130
within each of these categories.

882
00:38:53,130 --> 00:38:54,580
So you have southern pine beetle,

883
00:38:54,580 --> 00:38:56,650
to look at hemlock woolly adelgid,

884
00:38:56,650 --> 00:38:59,750
you have to click the next
link and emerald ash borer.

885
00:38:59,750 --> 00:39:01,620
And there are separate
charts for all of these.

886
00:39:01,620 --> 00:39:03,890
And again, you can look at the region,

887
00:39:03,890 --> 00:39:05,000
you can look at the states

888
00:39:05,000 --> 00:39:06,047
and you'll see with pests and pathogens,

889
00:39:06,047 --> 00:39:08,020
and we don't have frequency

890
00:39:08,020 --> 00:39:11,070
because that was something
that particular metric

891
00:39:11,070 --> 00:39:12,940
didn't correlate with
the type of information

892
00:39:12,940 --> 00:39:15,443
or it didn't work with the
type of information we had.

893
00:39:16,380 --> 00:39:17,710
There's a lot to show here,

894
00:39:17,710 --> 00:39:20,980
so I'm actually gonna pause
and ask if Emma or Jim

895
00:39:20,980 --> 00:39:22,620
had anything they would
like me to highlight

896
00:39:22,620 --> 00:39:23,483
while I'm here.

897
00:39:24,720 --> 00:39:25,570
- Specifically,

898
00:39:25,570 --> 00:39:27,950
there was a question about
where Southern pine beetle

899
00:39:27,950 --> 00:39:29,780
is occurring in the region right now,

900
00:39:29,780 --> 00:39:31,340
if you would be able to click back to that

901
00:39:31,340 --> 00:39:32,500
and showed location tab,

902
00:39:32,500 --> 00:39:35,310
I think that's a nice way
to quickly get a picture

903
00:39:35,310 --> 00:39:38,580
of the location and the number of times

904
00:39:38,580 --> 00:39:41,060
that that has been observed.

905
00:39:41,060 --> 00:39:43,130
So yes, it aspires to be
confined to long island,

906
00:39:43,130 --> 00:39:47,200
there have been detections
in more Northern counties,

907
00:39:47,200 --> 00:39:50,920
but it's a largely a
pitch pine barren impact

908
00:39:50,920 --> 00:39:53,650
because of the role of
fire and fire suppression

909
00:39:53,650 --> 00:39:55,840
allowing the SPB to flourish.

910
00:39:55,840 --> 00:39:58,140
So I just wanted to show
that you can get this data

911
00:39:58,140 --> 00:40:00,766
through this location view,

912
00:40:00,766 --> 00:40:04,130
and this is available for
most of the maps as well.

913
00:40:04,130 --> 00:40:07,020
So that's available and like Pia you said,

914
00:40:07,020 --> 00:40:08,840
there's the Northeastern
Forest Health Atlas,

915
00:40:08,840 --> 00:40:12,593
which also has this data viewable there.

916
00:40:14,300 --> 00:40:15,250
- Great. Thank you.

917
00:40:18,120 --> 00:40:22,170
So I'm just scrolling in,
I will move us out of here,

918
00:40:22,170 --> 00:40:25,020
but I did wanna show that
any additional information

919
00:40:25,020 --> 00:40:26,530
that you would like to
see about these projects

920
00:40:26,530 --> 00:40:28,820
are found in our about tabs.

921
00:40:28,820 --> 00:40:29,653
And this is a place

922
00:40:29,653 --> 00:40:32,080
where you can read our
technical report as well.

923
00:40:32,080 --> 00:40:33,290
So if you really wanna know

924
00:40:33,290 --> 00:40:35,880
about the sort of minutia of the analysis,

925
00:40:35,880 --> 00:40:38,760
or if you want to find more
of our reference material

926
00:40:38,760 --> 00:40:39,940
it's in here.

927
00:40:39,940 --> 00:40:42,863
So please take a look
at our technical report,

928
00:40:44,707 --> 00:40:45,907
it was quite the effort.

929
00:40:47,245 --> 00:40:48,078
Okay.

930
00:41:02,810 --> 00:41:04,243
- Are we ready to start?

931
00:41:05,940 --> 00:41:07,670
- Sorry, I'm trying to get back to the,

932
00:41:07,670 --> 00:41:09,190
I have like two more slides.
- Oh, okay.

933
00:41:09,190 --> 00:41:10,170
- And they are ready

934
00:41:10,170 --> 00:41:12,420
so let me just get back
to that screen share.

935
00:41:40,470 --> 00:41:42,570
Okay. Are you seeing that?

936
00:41:42,570 --> 00:41:43,460
Great. Thank you.

937
00:41:43,460 --> 00:41:44,550
Sorry for the pause.

938
00:41:44,550 --> 00:41:49,120
So thank you for bearing
with me through that webtool.

939
00:41:49,120 --> 00:41:50,040
I know it's really fast.

940
00:41:50,040 --> 00:41:51,550
I'd love to spend more time looking at it

941
00:41:51,550 --> 00:41:53,010
and there's lots to see.

942
00:41:53,010 --> 00:41:55,190
So please do contact any of us

943
00:41:55,190 --> 00:41:56,800
if you'd like to hear or
ask questions at the end

944
00:41:56,800 --> 00:41:58,520
would be a great time to talk about it,

945
00:41:58,520 --> 00:42:00,470
but I just wanted to
recap our final outputs

946
00:42:00,470 --> 00:42:01,303
for the project,

947
00:42:01,303 --> 00:42:03,320
just to sort of remind
everyone what we've done here.

948
00:42:03,320 --> 00:42:04,520
So there's the technical report

949
00:42:04,520 --> 00:42:05,530
that I just showed you also

950
00:42:05,530 --> 00:42:08,138
that has a more detailed
analysis of methodologies

951
00:42:08,138 --> 00:42:11,170
and any next steps and recommendations

952
00:42:11,170 --> 00:42:12,800
can be found in there.

953
00:42:12,800 --> 00:42:14,900
We have the webtool,

954
00:42:14,900 --> 00:42:17,580
which has the regime trend
analysis for the seven drivers,

955
00:42:17,580 --> 00:42:19,860
and then also the additional
monitoring resources

956
00:42:19,860 --> 00:42:21,240
that we walked through.

957
00:42:21,240 --> 00:42:23,620
And then there are the
response pages as well,

958
00:42:23,620 --> 00:42:25,820
which are more informational at this time.

959
00:42:25,820 --> 00:42:29,400
And we hope that this
project will be built on.

960
00:42:29,400 --> 00:42:33,180
And so we have some next steps
that we've identified here.

961
00:42:35,370 --> 00:42:36,870
Oops, yeah.

962
00:42:36,870 --> 00:42:39,310
So currently the web
portal only allows users

963
00:42:39,310 --> 00:42:43,160
to see the data and the trend
visualizations at one time,

964
00:42:43,160 --> 00:42:45,380
so just one disturbance at a time.

965
00:42:45,380 --> 00:42:48,090
In the future, we're
hoping that we can focus on

966
00:42:48,090 --> 00:42:50,360
providing a customizable chart component

967
00:42:50,360 --> 00:42:53,710
that would allow viewers
to visualize the data

968
00:42:53,710 --> 00:42:55,320
with multiple disturbances at once.

969
00:42:55,320 --> 00:42:57,920
And this would provide a
more complex illustration

970
00:42:57,920 --> 00:42:59,950
of disturbance in the
region and also allow users

971
00:42:59,950 --> 00:43:02,630
to investigate the relationship
between disturbance trends.

972
00:43:02,630 --> 00:43:04,220
And we've heard that this is an interest

973
00:43:04,220 --> 00:43:07,513
so we are also excited about
the potential for that.

974
00:43:08,870 --> 00:43:11,210
The web portal trend analysis
for each of the drivers

975
00:43:11,210 --> 00:43:15,183
and some of the preliminary
interpretation shows that,

976
00:43:16,410 --> 00:43:19,930
sorry, excuse me, shows the
implication of the trends.

977
00:43:19,930 --> 00:43:22,300
However, the analysis
would be really enriched

978
00:43:22,300 --> 00:43:24,010
if we included expert interpretation.

979
00:43:24,010 --> 00:43:24,970
So what we're hoping

980
00:43:24,970 --> 00:43:27,600
is that folks will wanna
look at some of the data

981
00:43:27,600 --> 00:43:28,760
and provide some more inputs

982
00:43:28,760 --> 00:43:31,130
that we can make some
management recommendations

983
00:43:31,130 --> 00:43:32,453
based on what we've found.

984
00:43:33,760 --> 00:43:36,270
And then we we're hoping that,

985
00:43:36,270 --> 00:43:37,543
oops, I'm sorry,

986
00:43:38,500 --> 00:43:39,620
that future research

987
00:43:39,620 --> 00:43:43,160
will inform how to connect
drivers and responses.

988
00:43:43,160 --> 00:43:44,990
So right now they're not connected,

989
00:43:44,990 --> 00:43:46,590
but there's a lot of evidence already

990
00:43:46,590 --> 00:43:49,140
that show that there
are kind of correlations

991
00:43:49,140 --> 00:43:50,520
between the types of information.

992
00:43:50,520 --> 00:43:52,510
So we're hoping that
that will be eliminated.

993
00:43:52,510 --> 00:43:53,343
And then finally,

994
00:43:53,343 --> 00:43:56,780
we hope that there will be more
information added from folks

995
00:43:56,780 --> 00:43:59,270
so that it can fill in
any gaps that we have

996
00:43:59,270 --> 00:44:01,620
in our monitoring and be
able to share information

997
00:44:01,620 --> 00:44:02,573
across the region.

998
00:44:04,750 --> 00:44:05,660
So thank you so much.

999
00:44:05,660 --> 00:44:07,610
I just wanna acknowledge
our committee members

1000
00:44:07,610 --> 00:44:10,220
who helped with our project
as well as our funding sources

1001
00:44:10,220 --> 00:44:13,200
and also our staff, particularly Emma Tait

1002
00:44:13,200 --> 00:44:14,370
who's here as well,

1003
00:44:14,370 --> 00:44:17,760
who did a lot of our trend
analysis and Jen Pontius.

1004
00:44:17,760 --> 00:44:19,440
So thank you all so much for coming

1005
00:44:19,440 --> 00:44:23,100
and we can take questions
now, if you have any.

1006
00:44:23,100 --> 00:44:24,683
I'm gonna stop screen sharing.

1007
00:44:35,700 --> 00:44:37,180
- Great. Thank you both.

1008
00:44:37,180 --> 00:44:39,920
And I was just gonna start,

1009
00:44:39,920 --> 00:44:42,140
we could ask some of the questions

1010
00:44:42,140 --> 00:44:46,640
that were put into the chat
earlier on in the conversation

1011
00:44:46,640 --> 00:44:48,593
just so that we don't lose those.

1012
00:44:49,800 --> 00:44:52,280
One question about fire is,

1013
00:44:52,280 --> 00:44:55,250
are there more fires present
in the Adirondack region,

1014
00:44:55,250 --> 00:44:56,833
Catskills or Western New York?

1015
00:44:59,580 --> 00:45:02,350
- So I was looking at the fire occurrence,

1016
00:45:02,350 --> 00:45:06,130
just the number of fires
reported in those regions,

1017
00:45:06,130 --> 00:45:08,810
it's definitely the lower Hudson valley

1018
00:45:08,810 --> 00:45:10,060
and the Catskills region,

1019
00:45:10,060 --> 00:45:12,230
as well as some pockets
of Western New York

1020
00:45:12,230 --> 00:45:15,663
that report more fires over
the course of the dataset.

1021
00:45:18,640 --> 00:45:20,740
But we didn't do a sub state.

1022
00:45:20,740 --> 00:45:22,500
We didn't look at different
regions within the state

1023
00:45:22,500 --> 00:45:25,810
in terms of trends or differences.

1024
00:45:25,810 --> 00:45:29,157
So that's just an observation
based on the existing data.

1025
00:45:29,157 --> 00:45:31,390
And if you were to click
on the location tab

1026
00:45:31,390 --> 00:45:33,220
in the fire section on the website,

1027
00:45:33,220 --> 00:45:36,903
you can see the graphic that
I showed during the slide.

1028
00:45:43,180 --> 00:45:44,150
- And then there was a question also

1029
00:45:44,150 --> 00:45:46,243
about harmful algal blooms.

1030
00:45:47,770 --> 00:45:51,253
And if that is something that could be,

1031
00:45:54,110 --> 00:45:55,940
included in measuring or collecting data

1032
00:45:55,940 --> 00:45:58,050
about blooms and water quality

1033
00:45:58,050 --> 00:46:02,003
and how that might impact
native and non-native species.

1034
00:46:06,990 --> 00:46:08,520
- I can take a stab at that Pia,

1035
00:46:08,520 --> 00:46:09,610
feel free to correct me if I'm wrong,

1036
00:46:09,610 --> 00:46:13,640
but, in general we didn't
look at harmful algal blooms

1037
00:46:13,640 --> 00:46:16,350
because they're somewhat
outside the systems

1038
00:46:16,350 --> 00:46:17,660
that we were trying to look at,

1039
00:46:17,660 --> 00:46:19,690
specifically forested systems.

1040
00:46:19,690 --> 00:46:22,520
Harmful algal blooms may be resulting from

1041
00:46:22,520 --> 00:46:24,850
disturbance and Upland watersheds,

1042
00:46:24,850 --> 00:46:28,200
but would be more of a response.

1043
00:46:28,200 --> 00:46:31,513
So, it was kind of outside
of the scope of this project.

1044
00:46:39,140 --> 00:46:41,210
- Does anyone else have
any other questions

1045
00:46:41,210 --> 00:46:44,760
or are there anything
else that you want us

1046
00:46:44,760 --> 00:46:49,760
to look at more closely
on the website itself

1047
00:46:49,970 --> 00:46:53,913
or anything that anyone would like to see?

1048
00:46:54,930 --> 00:46:56,820
Now is your chance to,

1049
00:46:56,820 --> 00:46:59,570
we'd like to open this up
for questions and discussion.

1050
00:47:19,853 --> 00:47:22,350
- I wanted to respond to one
question that Ronan posted

1051
00:47:22,350 --> 00:47:26,710
in the chat that we kind
of touched on in the chat

1052
00:47:26,710 --> 00:47:28,330
about southern pine beetle in particular,

1053
00:47:28,330 --> 00:47:30,766
some questions to that that
have been answered there,

1054
00:47:30,766 --> 00:47:33,080
but there was one that you asked around

1055
00:47:33,080 --> 00:47:34,110
is that also location

1056
00:47:34,110 --> 00:47:36,040
where there's abundance
of invasive species

1057
00:47:36,040 --> 00:47:37,260
from warmer temperatures.

1058
00:47:37,260 --> 00:47:40,230
And I think that's a
good thing to think about

1059
00:47:40,230 --> 00:47:44,240
when we have looked at our
region as a monitoring hole,

1060
00:47:44,240 --> 00:47:46,040
we look to the southern region

1061
00:47:46,040 --> 00:47:50,250
for where we can kind of learn from.

1062
00:47:50,250 --> 00:47:53,180
They're often the first to receive pests

1063
00:47:53,180 --> 00:47:55,850
from a warming climate
as they moved northward

1064
00:47:55,850 --> 00:47:57,740
for more suitable habitat into our region.

1065
00:47:57,740 --> 00:48:00,320
And certainly something
like hemlock woolly adelgid,

1066
00:48:00,320 --> 00:48:03,750
which has this winter control
is something that we'll see

1067
00:48:03,750 --> 00:48:08,630
becoming more prevalent and
region wide as a winters warm,

1068
00:48:08,630 --> 00:48:10,337
and we don't get those
killing temperatures.

1069
00:48:10,337 --> 00:48:12,510
And so I think thinking about Connecticut

1070
00:48:12,510 --> 00:48:15,250
and southern New York as
kind of the Harbinger's

1071
00:48:15,250 --> 00:48:17,980
of what the rest of New England
and New York might face,

1072
00:48:17,980 --> 00:48:20,630
is certainly something that
we should keep an eye on.

1073
00:48:29,800 --> 00:48:31,970
And then I'll answer your
other question, Ronan, about,

1074
00:48:31,970 --> 00:48:33,830
are southern pine beetles
bursts for New York

1075
00:48:33,830 --> 00:48:37,330
than say, Emerald Ash borer
or spotted lanternfly?

1076
00:48:37,330 --> 00:48:39,110
It really is a value question.

1077
00:48:39,110 --> 00:48:42,183
I think a spotted lantern
fly receives a lot of,

1078
00:48:43,420 --> 00:48:44,270
has a lot of concern

1079
00:48:44,270 --> 00:48:47,220
because it also is a
agricultural fruit tree pest.

1080
00:48:47,220 --> 00:48:50,630
And so the economic damage potential

1081
00:48:50,630 --> 00:48:55,020
from that pest on fruit
trees and vineyards

1082
00:48:55,020 --> 00:48:57,223
is gonna be a significant concern.

1083
00:48:58,230 --> 00:49:02,140
Emerald ash borer is very
effective at killing trees

1084
00:49:02,140 --> 00:49:04,090
and there are ash trees spread throughout

1085
00:49:04,090 --> 00:49:06,710
the Northern forest and in New York.

1086
00:49:06,710 --> 00:49:09,690
So that's gonna be a concern
for a different reason.

1087
00:49:09,690 --> 00:49:11,210
Also, we have a lot of street trees

1088
00:49:11,210 --> 00:49:12,640
or used to have a lot of street trees

1089
00:49:12,640 --> 00:49:15,200
that are now being removed
by emerald ash borer

1090
00:49:15,200 --> 00:49:17,410
or by municipalities.

1091
00:49:17,410 --> 00:49:18,590
Looking at Southern pine beetle,

1092
00:49:18,590 --> 00:49:20,870
it tends to be somewhat confined

1093
00:49:20,870 --> 00:49:23,240
to the southern New York area right now

1094
00:49:23,240 --> 00:49:24,960
because of where there are pitch pine

1095
00:49:24,960 --> 00:49:26,390
and fire adapted ecosystem.

1096
00:49:26,390 --> 00:49:28,550
So it depends on the system

1097
00:49:28,550 --> 00:49:30,250
and kind of what value you're speaking of

1098
00:49:30,250 --> 00:49:31,900
when thinking about what's worse.

1099
00:49:37,470 --> 00:49:41,057
- I see, there's another few
questions that have come in.

1100
00:49:41,057 --> 00:49:44,300
"Do you know of any long-term
data on deer herbivory

1101
00:49:44,300 --> 00:49:46,257
as a driver of forest disturbance?"

1102
00:49:49,370 --> 00:49:50,890
- I'll take that one

1103
00:49:50,890 --> 00:49:52,430
because I've been thinking about it a lot.

1104
00:49:52,430 --> 00:49:55,430
So our next upcoming regional project

1105
00:49:55,430 --> 00:49:57,485
is about ungulate browse

1106
00:49:57,485 --> 00:49:59,990
and impact assessment of browse herbivory,

1107
00:49:59,990 --> 00:50:03,420
so we are starting to look
through that information.

1108
00:50:03,420 --> 00:50:05,270
There was the region portal,

1109
00:50:05,270 --> 00:50:08,640
which was also created
several years ago with FEMC

1110
00:50:08,640 --> 00:50:09,630
and I can put that in the chat

1111
00:50:09,630 --> 00:50:12,510
where we started to look
at some of those studies

1112
00:50:12,510 --> 00:50:14,160
and aggregate them.

1113
00:50:14,160 --> 00:50:15,420
So there's some information there,

1114
00:50:15,420 --> 00:50:17,290
but we're hoping to have
a lot more information

1115
00:50:17,290 --> 00:50:18,820
about that by the end of the year.

1116
00:50:18,820 --> 00:50:21,150
So, yes, I think it's very important,

1117
00:50:21,150 --> 00:50:22,800
but we haven't included that yet.

1118
00:50:29,785 --> 00:50:30,618
- And then another question,

1119
00:50:30,618 --> 00:50:33,610
"Is it possible to see the
different disturbances all

1120
00:50:35,500 --> 00:50:36,937
on the same location map?"

1121
00:50:39,890 --> 00:50:40,723
- No.

1122
00:50:41,740 --> 00:50:42,630
Not currently.

1123
00:50:42,630 --> 00:50:45,360
So as I was sort of summing
up in the next steps,

1124
00:50:45,360 --> 00:50:46,820
which got a little distracting,

1125
00:50:46,820 --> 00:50:50,120
'cause all of my screens
started getting really wonky,

1126
00:50:50,120 --> 00:50:51,850
but right now you can't see them.

1127
00:50:51,850 --> 00:50:53,190
And it's a little bit challenging

1128
00:50:53,190 --> 00:50:56,540
because the data sets are very different.

1129
00:50:56,540 --> 00:50:57,910
And so to be able to put them together,

1130
00:50:57,910 --> 00:51:00,250
we'd have to really work with the data

1131
00:51:00,250 --> 00:51:02,150
and try to get it all established.

1132
00:51:02,150 --> 00:51:03,690
And we wanted to do that originally,

1133
00:51:03,690 --> 00:51:05,310
but we had some roadblocks,

1134
00:51:05,310 --> 00:51:07,680
but I think that that
could be very interesting.

1135
00:51:07,680 --> 00:51:10,770
And so the solution that
we're moving towards

1136
00:51:10,770 --> 00:51:13,520
is to have at least all of
the charts put together,

1137
00:51:13,520 --> 00:51:14,720
all the disturbance trends,

1138
00:51:14,720 --> 00:51:16,410
even if you can't see the locations

1139
00:51:16,410 --> 00:51:17,753
of all of the information.

1140
00:51:20,070 --> 00:51:21,840
Jim, do you wanna clarify
anything that I just said

1141
00:51:21,840 --> 00:51:23,300
or does that sound right?

1142
00:51:23,300 --> 00:51:24,133
- No, that's all right.

1143
00:51:24,133 --> 00:51:25,970
I think the only addition I would say

1144
00:51:25,970 --> 00:51:28,150
is that the Forest Health Atlas

1145
00:51:28,150 --> 00:51:30,530
does allow you to see
when those disturbances

1146
00:51:30,530 --> 00:51:35,190
have caused tree mortality or damage.

1147
00:51:35,190 --> 00:51:39,090
So you can look at wind
damage and flooding damage

1148
00:51:39,090 --> 00:51:41,880
and drought damage if it shows
up in those aerial surveys.

1149
00:51:41,880 --> 00:51:43,210
And I think as you know, Katie,

1150
00:51:43,210 --> 00:51:46,360
those are not ubiquitous,

1151
00:51:46,360 --> 00:51:48,640
like a reliable source
for all types of damage.

1152
00:51:48,640 --> 00:51:50,620
But if there's been a
significant wind event

1153
00:51:50,620 --> 00:51:52,200
that caused blow down or damage,

1154
00:51:52,200 --> 00:51:54,310
it'll show up in that aerial
detection survey data,

1155
00:51:54,310 --> 00:51:56,190
and that's not the Forest Health Atlas,

1156
00:51:56,190 --> 00:51:58,400
but what we can't do right now is say,

1157
00:51:58,400 --> 00:52:00,670
show me all the wind stations that lit up

1158
00:52:00,670 --> 00:52:01,650
in the last 10 years

1159
00:52:01,650 --> 00:52:04,286
across the landscape
with high wind events.

1160
00:52:04,286 --> 00:52:06,870
That's not currently doable.

1161
00:52:06,870 --> 00:52:08,645
It doesn't mean it couldn't be done,

1162
00:52:08,645 --> 00:52:11,390
it's just not them with this current tool.

1163
00:52:11,390 --> 00:52:12,740
And I'll drop the Forest Health Atlas

1164
00:52:12,740 --> 00:52:15,633
link in the chat too if folks
aren't familiar with that.

1165
00:52:23,240 --> 00:52:25,320
- Elissa, I think you're muted.

1166
00:52:25,320 --> 00:52:26,450
- Oops.

1167
00:52:26,450 --> 00:52:29,030
I was just saying that I just
dropped in the region tool

1168
00:52:29,030 --> 00:52:34,030
that Pia mentioned as well for
the deer and ungulate browse

1169
00:52:34,380 --> 00:52:36,473
that there's some information in there.

1170
00:52:38,630 --> 00:52:41,937
And then let's see another question,

1171
00:52:41,937 --> 00:52:44,320
"Will a high-level overview be available

1172
00:52:44,320 --> 00:52:47,543
on the website or updated
as data becomes available?

1173
00:52:53,350 --> 00:52:54,930
- I think I have a follow-up question.

1174
00:52:54,930 --> 00:52:59,863
Do you mean beyond the
regional trend analysis or.

1175
00:53:01,880 --> 00:53:03,973
- [Logan] Yeah, this is a Logan.

1176
00:53:03,973 --> 00:53:06,380
I appreciated Jim's kind of overview

1177
00:53:06,380 --> 00:53:08,500
in how succinctly you was put together

1178
00:53:08,500 --> 00:53:10,740
and I was just wondering
if I can find that anywhere

1179
00:53:10,740 --> 00:53:12,483
on the website kind of upfront.

1180
00:53:15,760 --> 00:53:16,950
- I think right now the information

1181
00:53:16,950 --> 00:53:18,930
is mostly in the technical report

1182
00:53:18,930 --> 00:53:21,283
and on the charts on the site,

1183
00:53:22,146 --> 00:53:24,196
is there somewhere else that I'm missing?

1184
00:53:25,373 --> 00:53:27,330
No.
- No, not in that format,

1185
00:53:27,330 --> 00:53:29,610
but we certainly could,

1186
00:53:29,610 --> 00:53:32,940
if that is a useful way of
representing this information

1187
00:53:32,940 --> 00:53:34,950
for someone like you in your work

1188
00:53:34,950 --> 00:53:36,690
or in understanding or looking at these,

1189
00:53:36,690 --> 00:53:39,680
I think we certainly could
provide that those images

1190
00:53:39,680 --> 00:53:41,900
and then link back to the underlying data

1191
00:53:41,900 --> 00:53:43,300
if you want it to go deeper.

1192
00:53:45,870 --> 00:53:50,400
- Yeah. I guess I'd also
add that we have been asked

1193
00:53:50,400 --> 00:53:52,530
to talk about some of these,

1194
00:53:52,530 --> 00:53:55,870
of our tools with specific
state partnership groups.

1195
00:53:55,870 --> 00:53:57,120
And I'm excited about that

1196
00:53:57,120 --> 00:53:58,640
because it gives us a little bit more time

1197
00:53:58,640 --> 00:54:01,370
to look at state specific
data and drill down

1198
00:54:01,370 --> 00:54:03,300
into that and present that information.

1199
00:54:03,300 --> 00:54:05,070
We couldn't really cover
that in this webinar,

1200
00:54:05,070 --> 00:54:07,890
but if there is ever an
interest to hear specifically

1201
00:54:07,890 --> 00:54:10,370
about state data, we can
look at that more closely too

1202
00:54:10,370 --> 00:54:12,483
and in shorter, more directed meetings.

1203
00:54:14,620 --> 00:54:15,720
- And Pia, would it be all right

1204
00:54:15,720 --> 00:54:18,400
if I added one more comment
on Logan's question.

1205
00:54:18,400 --> 00:54:19,233
- Yeah.

1206
00:54:19,233 --> 00:54:21,980
- You asked about when it's updated,

1207
00:54:21,980 --> 00:54:25,430
and I think that's an important
question for this tool.

1208
00:54:25,430 --> 00:54:28,950
We, I think we as a staff
and some of our partners

1209
00:54:28,950 --> 00:54:30,170
certainly see value in this

1210
00:54:30,170 --> 00:54:33,930
as an ongoing resource for the region.

1211
00:54:33,930 --> 00:54:37,340
We're very much in the phase
of seeing if that's true.

1212
00:54:37,340 --> 00:54:41,480
So if this is something that
you do want to see updated,

1213
00:54:41,480 --> 00:54:43,240
letting us know would be helpful

1214
00:54:43,240 --> 00:54:47,510
because as we talk with
our governing committees

1215
00:54:47,510 --> 00:54:48,580
and our partners,

1216
00:54:48,580 --> 00:54:50,840
and they're kind of directing
the work for the future,

1217
00:54:50,840 --> 00:54:53,440
knowing if this is something
we should update would be good.

1218
00:54:53,440 --> 00:54:57,600
These data sets that we used
are regularly updated sources

1219
00:54:57,600 --> 00:55:00,350
with a long, like a, a bit
of institutional support.

1220
00:55:00,350 --> 00:55:03,640
So that one of the reasons
we chose those data sets

1221
00:55:03,640 --> 00:55:06,230
is so that we can have
that ability to monitor it

1222
00:55:06,230 --> 00:55:09,130
on an ongoing basis and look for change.

1223
00:55:09,130 --> 00:55:10,920
There's certainly time that is needed,

1224
00:55:10,920 --> 00:55:13,260
but it's a lot less to keep it updated

1225
00:55:13,260 --> 00:55:14,200
than it was to build it.

1226
00:55:14,200 --> 00:55:16,550
So if this is a value, do let us know

1227
00:55:16,550 --> 00:55:18,300
so we can take that back to our committees

1228
00:55:18,300 --> 00:55:20,683
and prioritize that for future work.

1229
00:55:25,640 --> 00:55:26,473
- Great. Thank you.

1230
00:55:26,473 --> 00:55:29,280
I think that we're coming up on time here.

1231
00:55:29,280 --> 00:55:32,700
And so I wanna thank everyone
for joining us today.

1232
00:55:32,700 --> 00:55:36,930
I do have a quick survey
that I just put in the chat,

1233
00:55:36,930 --> 00:55:38,690
if you wouldn't mind completing that,

1234
00:55:38,690 --> 00:55:40,573
it'll take you a minute.

1235
00:55:42,590 --> 00:55:45,800
And I also wanted to share,

1236
00:55:45,800 --> 00:55:48,383
I think something that
Pia mentioned earlier was,

1237
00:55:49,340 --> 00:55:54,150
a recording from our
climate indicators webinar,

1238
00:55:54,150 --> 00:55:58,360
and that can be found on
the UVM streaming website

1239
00:55:58,360 --> 00:56:00,740
and we will be making a recording

1240
00:56:00,740 --> 00:56:02,800
of this webinar available as well.

1241
00:56:02,800 --> 00:56:05,403
So you can come back and watch again.

1242
00:56:09,484 --> 00:56:10,317
All right.

1243
00:56:10,317 --> 00:56:11,150
- Well thank you, Elissa.
- Thank you.

1244
00:56:11,150 --> 00:56:12,323
- Thanks everybody.

1245
00:56:12,323 --> 00:56:13,735
- Thank you.
- Thanks everyone.

1246
00:56:13,735 --> 00:56:14,800
- And then please feel free to contact me

1247
00:56:14,800 --> 00:56:18,090
if you have any questions or
if you wanna share any data.

1248
00:56:18,090 --> 00:56:19,830
Someone contacted me after my last webinar

1249
00:56:19,830 --> 00:56:23,740
I was really excited, so please reach out.

1250
00:56:23,740 --> 00:56:24,573
Thanks.