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- [Emma] So welcome everyone

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to the Long-Term Monitoring
Contributor talks.

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The first presenter will
be Soren Donisvitch,

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who's a master's student at
the University of Vermont,

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and he will be presenting on

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"The applications and utility
of a unified Continuous Forest

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Inventory Network in the
Northeastern United States.

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- Thank you so much.

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So my name is Soren Donisvitch.

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I received my bachelor's
from the University of Maine

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in Forestry and Survey
Engineering Technology.

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I'm currently a master's student,

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graduate student at the
University of Vermont

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under Tony D'Amato.

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And today I'm gonna talk about

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the Northeastern Forest Inventory Network,

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also known as NEFIN.

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So, as a brief overview, we're gonna just

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overview of like the order
of operations of this talk,

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we're gonna go over the
overview and background of NEFIN

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over the infrastructure and blueprints

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of the actual database itself,

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and then Utility and
Potential research aspects

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of this dataset.

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So what is NEFIN?

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Merely NEFIN is a web-based

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forest inventory data acquisition tool

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that allows your browsing,
and access to CFI information.

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CFI being a Continuous Forest Inventory,

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so the same plot monitored
over long periods of time.

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So what does this system accomplish?

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There's a wealth of data that's
out there in the Northeast

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about forest inventory data.

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And a lot of it is sparsed and separate.

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So this is aggregating a lot
of those resources together.

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We're trying to accomplish

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is a systematic inventory program

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of metadata and methodological changes.

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So over time, those programs
that are joined together

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may have certain changes,

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so switching from imperial to metric

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as it's over long periods of time

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and repetitive measurement.

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So this program matches and changes those,

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and then allows for kind of temporarily

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variable and much more robust dataset.

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The unified and comprehensive
CFI database in of itself

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so it's truly unified so
fields are unified species,

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et cetera, so this joint is
fully and entirely united.

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And then also we gonna do
some kind of peer review

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in technical publications
related to the database itself

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how it was developed and what
the relative implications

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of using these datasets are.

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So for some background,
this follows a lot of work

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from the FGMC in the Continuous
Forest Inventory program

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comparison tool, in which the
team primarily took a bunch

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of these different CFI
programs, and compare them

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and looked at the methodology, and to see

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if certain fields were able
to be calculated or generated.

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So species composition,
(indistinct) distribution,

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things like this.

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So this methodology comparison, the NEFIN

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in itself takes it a step further, instead

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of just evaluating, is truly
joining those datasets together

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and providing a product in
which users can download

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and query out certain kinds
of data from a joint dataset.

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So the current CFI
Program Land-base itself,

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you can see in the map on the right,

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we have currently 12 programs
that have incorporated

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into the initial effort.

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So this effort is not fully joined

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in a database currently,
as of yet, we're still

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creating the hierarchical
database structure itself, but all

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of the methodology has been
gone through and matched

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up and fields joined to a point that we're

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at the point where we're
starting to build that

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database infrastructure right now.

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As you can see

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there are some holes throughout
the Northeastern forest,

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but we're hopefully gonna
be able to fill those

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in, there's a wealth of
data that's out there.

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We've targeted 16 more potential datasets

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that we want to incorporate, yeah.

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So this is the project team.

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So Jen Pontius is the
primary PI, Jim Duncan,

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Clarke Cooper, Ali Kosiba,
Tony D'Amato, Emma Tait,

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Aaron Weiskittel and myself.

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So some goals for this
project and of itself is,

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we wanna increase the accessibility

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of the CFI data itself, creating
a truly unified dataset.

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So those fields are truly
joined, makes it easier

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for users to actually use.

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Is truly simplified, sort of point

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that many fields that are
usable in forest maturation

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can be easily queried out.

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It's an efficient use of methods,

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so that over time, the database
can be somewhat resilient

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and maintain some kind of
structure going into the future.

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We also use some demonstrating utility

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of these data resources
as primary research

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within, to keep researchers
within this project.

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Increase the connections
between people who have access

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to these datasets, is really
important for this project.

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Just to give some background

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of like what NEFIN actually does,

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and why it's a really
useful tool to actually use,

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is it primarily it's a time-saver,

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so most people as a research, you come

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with a question, and CFI programs

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and data can be really
useful as it deals with time,

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and they're really useful statistically

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and looking at certain questions,

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so you're looking through
primary like publications,

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you're calling people you know,

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to see if you can actually find the data.

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Once you have the data,
you have to download it

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whether it's CSV,
Microsoft access database,

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you're then having to
deal with downloading

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in a format that you can actually manage.

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Once you do that, then
you really have to dig

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into the methodology
and those methodologies

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like how those fields
were actually kept, taken,

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was it using imperial
metric, variable radius,

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fixed radius plot.

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Once you do all that, then
you can finally figure out

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whether or not that dataset can actually

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be used for your question.

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You have to do this as much as possible.

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It's fundamentally more data

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you have, the better your
research is really gonna be.

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Then you have to go through
the process of cleaning,

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we've all probably know it,

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it's like having to find
those 6,000 foot tall trees,

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or comparing species,
species codes, changing them

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to FPS compatible, any
of those kinds of things.

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At the end you really wanna have a nice

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and relatively clean dataset.

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And you're doing that
for many as possible.

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And only then once those fields join up,

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you truly zip them together
and create a unified dataset.

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And then only then, you can actually look

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at that data and then
compare the actual question

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and see if that dataset
can actually be used to

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answer the questions you have.

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So this is the NEFIN process.

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So the NEFIN takes into consideration,

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does all this for you.

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It's a huge time-saver and
allows you to go from directly

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to a question, to usable data
you can actually use and see

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if you can actually use those
data to answer your questions.

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There was some background
kind of infrastructure.

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In general I'm gonna speed

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through this, is that
the database uploader.

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So all this data are uploaded,

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the metadata system tracks
those things that change

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over time, so it allows for
data processing to change,

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so you need to note when
that plot was removed in 1973

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and then re-established in 2018

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but has the same plot number.

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All those kinds of minutia,
and then the data uploader

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which is where you upload that data.

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The processor I'm gonna
go into a little bit more.

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And then primarily as a user,

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what you're gonna have access to

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and be really looking
at, is the access portal.

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So this is something that's
gonna be able to visualize

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and download those reports,

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for specific kind of queries you want.

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So, the blueprints and processor itself,

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fundamentally what's
really important here is

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that, those datasets are
fundamentally broken down

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at the beginning, so that you
have a Raw Archiving Script

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so that original image
of those datasets are

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stored, can always be looked back to or

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if you want to, you can look
at the primary data where

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the way it was came into NEFIN.

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And then the Transcribed script,

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so it's broken into something
that we can further break

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down, so then it's broken
into two things which is

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Standardized Attributes
and Ancillary Attributes.

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So the standardized attributes
are those attributes from

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forest maturation that
people commonly use.

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So diameter, tree, height,
species, et cetera.

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The ancillary data are
more of those kind of

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programmatically, unique fields,

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so a fungal pathogen on
a tree, stand age, Cul

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things that are kind of more unique,

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so we don't really wanna throw out.

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We wanna make sure that
people who have these data

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can pull them out if they want to.

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Fundamentally, the output,

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that we really trying to target for is,

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a web access portal that is
intuitive and customizable.

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So if I wanna find all of the sugar maple,

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all the plots that contain sugar maple

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within the Northeastern region,
within the NEFIN network,

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you can query that out.

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In the output,

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this kind of a dataset
becomes extremely valuable

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or you can see the value
when you actually mesh this

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with other, another datasets such as FIA.

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So FIA in of itself is an
amazing program, wealth of data

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and very useful for research
and forest managers.

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But this is something that will hopefully

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enhance those datasets.

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If the data's out there,

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we might as well use as much as we can.

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So another thing is
that we wanna make sure

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that the outputs in those
reports are compatible with FVS.

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So those plots that contain sugar, maple,

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you can help with those
upload the, upload them

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in a compatible way to FVS
and run those very quickly.

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So you're able to go

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from questions to answers quite quickly.

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So some utility for these datasets,

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this kind of data is extremely useful.

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The first thing that comes

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to mind for me is geospatial aspects.

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So tying geospatial and
remote sensing products

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to the ground, taking that
data and actually tying it

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to real data, tying it
to ground, I should say.

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And really kind of, can
be really valuable use

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of this kind of a data source,
as it spans for decades.

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Forest monitoring and research,

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so this is kind of, like this kind

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of dataset is really kind
of, pick your question

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and run with it because
there's so much you can do.

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So the long-term evaluation of
regional species composition,

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is you're able to evaluate time,

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and really see general
patterns emerge, regeneration

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in growth dynamics, temporary isolated

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continuous assessment
of forest productivity,

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growth and yield, carbon
storage and sequestration.

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When you're dealing to ask big questions,

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you have to have big data.

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So regionally this kind of
a united data source allows

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for regional questions to be asked

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in a more, in just a better way.

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And more, the modeling
applications are really

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exciting as well.

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Both in creating certain types of models

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whether it be a productivity model,

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or species migration model.

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In enhancement of current models,

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adding data is always
really good for testing

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and evaluating current
models and creating new ones.

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So this is my first semester
as a master's student,

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so a lot of my research is still petitive,

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but I'm really excited to be able to use

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the NEFIN data itself.

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And so I'm quite interested

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in trying to leverage these datasets,

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in the best way possible
across the region,

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so something that came to me
was the forest tension zones.

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So tension zone being geographic area

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that marks a change from one
type of vegetation to another.

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The hardwoods transitioning to softwoods.

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Northern hardwoods into
broadleaf deciduous.

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These kind of transitions zones

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they're really interesting
in forest dynamics.

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So, we're talking about
mortality, ingrowth, regeneration,

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species composition, there's any number

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of things that I really wanna look

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within these kind of tensions zones,

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as well as primarily
incorporating a comparative tool.

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So not a comparative
tool, but a comparison

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between the NEFIN data and the FIA data.

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So the enhanced set where it's FIA

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plus NEFIN versus just
FIA, it kind of gives kind

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of some statistical evaluation

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of these datasets, with these questions.

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I'm pretty sure I'm kind
of probably running close

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to time here, but I
really I'm here trying to

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champion the NEFIN project itself.

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If you or anyone you
know has access to data

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you believe would be worthwhile

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for this project to incorporate,

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we're really open to that idea,

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we wanna try to get as much data

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as possible into this
kind of this dataset,

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so we can leverage it, and
make it open to the public.

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So if you have any questions,

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or wanna contact me about those data

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you might have access
to, please contact me,

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my email is right below,

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and I believe it's time for questions.

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- There's a question, in the chat,

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from Jen Pontius asking
what type of QA, QC goes

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into evaluating which
datasets to incorporate?

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- I trying to find that, and by QA, QC,

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what do you have any?

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- [Jennifer] Yeah, I guess, Soren,

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I'm just looking for a little
more detail on how we know

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whether or not it's worth
bringing somebody's inventory data

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into the database, what if it's
a citizen science data, what

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if it's a high school
class that's collected,

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data from behind their school?

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Just curious if, how much thought has been

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put into that yet?

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- Yeah. so I was not really a part of

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that initial effort, from
what I understand, a big part

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about this is that it's
Continuous Forest Inventory,

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so an inventory that's repetitive,

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so you take a plot in a forest and

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you measure that same point over and over.

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That's fundamentally like
a really necessary thing

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for this to be incorporated
because it has to be a CFI.

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From my understanding,
other aspects, citizens,

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citizen science data is
always extremely valuable,

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but I would not be the
first person to really say

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whether or not those data
can truly be incorporated.

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- And we have a question
from Charles Cogbill,

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the tension zone diagram was
for pre settlement period.

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Are you interested in seeing

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if this will change with modern data?

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- Yes, yes I am,

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so that Harvard paper, that
was extremely influential

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in me being a traditionally trained

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surveyor looking at witness
trees that was based

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on witness trees, which is
amazing, really wonderful work.

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It's just that kind of
work is really amazing

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and so I am interested to see

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whether or not how that's changed,

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how that shifted, with modern data,

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with after pre-settlement,
leveraging those kind of data

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sources, are really
interesting, that is, that

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I just love that paper,

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I could talk about that
forever, but yes, no

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I am definitely interested
to see how over time

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the general trends and forest composition,

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how, I'm really interested
in leveraging these kind

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of data over long periods of time.

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So yes, I would be interested

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in looking at how modern
data has influenced

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or can be compared to
pre-settlement forests.

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- And Jerry Carlson asks,

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are you considering private land security

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from remote sensing data of land use?

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- Yes, so that was, I think one

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of the biggest barriers to entry

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for the private corporations or entities,

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they go out and they wanna
make sure that their data is

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and the plot integrity is
also extremely important.

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So location much like
FIA is I don't think is

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going to be really a widely
available for plot location,

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but that's something that's kind of,

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above where I am in this
project, but no security

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for landowners is being
taken to consideration

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especially private landowners,
and all of these datasets

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before incorporated, go through a process

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where we're talking
with the people who own

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that data, who have control of that data

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and so that we're not
sharing anything that they

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don't feel to be beyond what they want.