- [Emma] So welcome everyone
to the Long-Term Monitoring Contributor talks.
The first presenter will be Soren Donisvitch,
who's a master's student at the University of Vermont,
and he will be presenting on
"The applications and utility of a unified Continuous Forest
Inventory Network in the Northeastern United States.
- Thank you so much.
So my name is Soren Donisvitch.
I received my bachelor's from the University of Maine
in Forestry and Survey Engineering Technology.
I'm currently a master's student,
graduate student at the University of Vermont
under Tony D'Amato.
And today I'm gonna talk about
the Northeastern Forest Inventory Network,
also known as NEFIN.
So, as a brief overview, we're gonna just
overview of like the order of operations of this talk,
we're gonna go over the overview and background of NEFIN
over the infrastructure and blueprints
of the actual database itself,
and then Utility and Potential research aspects
of this dataset.
So what is NEFIN?
Merely NEFIN is a web-based
forest inventory data acquisition tool
that allows your browsing, and access to CFI information.
CFI being a Continuous Forest Inventory,
so the same plot monitored over long periods of time.
So what does this system accomplish?
There's a wealth of data that's out there in the Northeast
about forest inventory data.
And a lot of it is sparsed and separate.
So this is aggregating a lot of those resources together.
We're trying to accomplish
is a systematic inventory program
of metadata and methodological changes.
So over time, those programs that are joined together
may have certain changes,
so switching from imperial to metric
as it's over long periods of time
and repetitive measurement.
So this program matches and changes those,
and then allows for kind of temporarily
variable and much more robust dataset.
The unified and comprehensive CFI database in of itself
so it's truly unified so fields are unified species,
et cetera, so this joint is fully and entirely united.
And then also we gonna do some kind of peer review
in technical publications related to the database itself
how it was developed and what the relative implications
of using these datasets are.
So for some background, this follows a lot of work
from the FGMC in the Continuous Forest Inventory program
comparison tool, in which the team primarily took a bunch
of these different CFI programs, and compare them
and looked at the methodology, and to see
if certain fields were able to be calculated or generated.
So species composition, (indistinct) distribution,
things like this.
So this methodology comparison, the NEFIN
in itself takes it a step further, instead
of just evaluating, is truly joining those datasets together
and providing a product in which users can download
and query out certain kinds of data from a joint dataset.
So the current CFI Program Land-base itself,
you can see in the map on the right,
we have currently 12 programs that have incorporated
into the initial effort.
So this effort is not fully joined
in a database currently, as of yet, we're still
creating the hierarchical database structure itself, but all
of the methodology has been gone through and matched
up and fields joined to a point that we're
at the point where we're starting to build that
database infrastructure right now.
As you can see
there are some holes throughout the Northeastern forest,
but we're hopefully gonna be able to fill those
in, there's a wealth of data that's out there.
We've targeted 16 more potential datasets
that we want to incorporate, yeah.
So this is the project team.
So Jen Pontius is the primary PI, Jim Duncan,
Clarke Cooper, Ali Kosiba, Tony D'Amato, Emma Tait,
Aaron Weiskittel and myself.
So some goals for this project and of itself is,
we wanna increase the accessibility
of the CFI data itself, creating a truly unified dataset.
So those fields are truly joined, makes it easier
for users to actually use.
Is truly simplified, sort of point
that many fields that are usable in forest maturation
can be easily queried out.
It's an efficient use of methods,
so that over time, the database can be somewhat resilient
and maintain some kind of structure going into the future.
We also use some demonstrating utility
of these data resources as primary research
within, to keep researchers within this project.
Increase the connections between people who have access
to these datasets, is really important for this project.
Just to give some background
of like what NEFIN actually does,
and why it's a really useful tool to actually use,
is it primarily it's a time-saver,
so most people as a research, you come
with a question, and CFI programs
and data can be really useful as it deals with time,
and they're really useful statistically
and looking at certain questions,
so you're looking through primary like publications,
you're calling people you know,
to see if you can actually find the data.
Once you have the data, you have to download it
whether it's CSV, Microsoft access database,
you're then having to deal with downloading
in a format that you can actually manage.
Once you do that, then you really have to dig
into the methodology and those methodologies
like how those fields were actually kept, taken,
was it using imperial metric, variable radius,
fixed radius plot.
Once you do all that, then you can finally figure out
whether or not that dataset can actually
be used for your question.
You have to do this as much as possible.
It's fundamentally more data
you have, the better your research is really gonna be.
Then you have to go through the process of cleaning,
we've all probably know it,
it's like having to find those 6,000 foot tall trees,
or comparing species, species codes, changing them
to FPS compatible, any of those kinds of things.
At the end you really wanna have a nice
and relatively clean dataset.
And you're doing that for many as possible.
And only then once those fields join up,
you truly zip them together and create a unified dataset.
And then only then, you can actually look
at that data and then compare the actual question
and see if that dataset can actually be used to
answer the questions you have.
So this is the NEFIN process.
So the NEFIN takes into consideration,
does all this for you.
It's a huge time-saver and allows you to go from directly
to a question, to usable data you can actually use and see
if you can actually use those data to answer your questions.
There was some background kind of infrastructure.
In general I'm gonna speed
through this, is that the database uploader.
So all this data are uploaded,
the metadata system tracks those things that change
over time, so it allows for data processing to change,
so you need to note when that plot was removed in 1973
and then re-established in 2018
but has the same plot number.
All those kinds of minutia, and then the data uploader
which is where you upload that data.
The processor I'm gonna go into a little bit more.
And then primarily as a user,
what you're gonna have access to
and be really looking at, is the access portal.
So this is something that's gonna be able to visualize
and download those reports,
for specific kind of queries you want.
So, the blueprints and processor itself,
fundamentally what's really important here is
that, those datasets are fundamentally broken down
at the beginning, so that you have a Raw Archiving Script
so that original image of those datasets are
stored, can always be looked back to or
if you want to, you can look at the primary data where
the way it was came into NEFIN.
And then the Transcribed script,
so it's broken into something that we can further break
down, so then it's broken into two things which is
Standardized Attributes and Ancillary Attributes.
So the standardized attributes are those attributes from
forest maturation that people commonly use.
So diameter, tree, height, species, et cetera.
The ancillary data are more of those kind of
programmatically, unique fields,
so a fungal pathogen on a tree, stand age, Cul
things that are kind of more unique,
so we don't really wanna throw out.
We wanna make sure that people who have these data
can pull them out if they want to.
Fundamentally, the output,
that we really trying to target for is,
a web access portal that is intuitive and customizable.
So if I wanna find all of the sugar maple,
all the plots that contain sugar maple
within the Northeastern region, within the NEFIN network,
you can query that out.
In the output,
this kind of a dataset becomes extremely valuable
or you can see the value when you actually mesh this
with other, another datasets such as FIA.
So FIA in of itself is an amazing program, wealth of data
and very useful for research and forest managers.
But this is something that will hopefully
enhance those datasets.
If the data's out there,
we might as well use as much as we can.
So another thing is that we wanna make sure
that the outputs in those reports are compatible with FVS.
So those plots that contain sugar, maple,
you can help with those upload the, upload them
in a compatible way to FVS and run those very quickly.
So you're able to go
from questions to answers quite quickly.
So some utility for these datasets,
this kind of data is extremely useful.
The first thing that comes
to mind for me is geospatial aspects.
So tying geospatial and remote sensing products
to the ground, taking that data and actually tying it
to real data, tying it to ground, I should say.
And really kind of, can be really valuable use
of this kind of a data source, as it spans for decades.
Forest monitoring and research,
so this is kind of, like this kind
of dataset is really kind of, pick your question
and run with it because there's so much you can do.
So the long-term evaluation of regional species composition,
is you're able to evaluate time,
and really see general patterns emerge, regeneration
in growth dynamics, temporary isolated
continuous assessment of forest productivity,
growth and yield, carbon storage and sequestration.
When you're dealing to ask big questions,
you have to have big data.
So regionally this kind of a united data source allows
for regional questions to be asked
in a more, in just a better way.
And more, the modeling applications are really
exciting as well.
Both in creating certain types of models
whether it be a productivity model,
or species migration model.
In enhancement of current models,
adding data is always really good for testing
and evaluating current models and creating new ones.
So this is my first semester as a master's student,
so a lot of my research is still petitive,
but I'm really excited to be able to use
the NEFIN data itself.
And so I'm quite interested
in trying to leverage these datasets,
in the best way possible across the region,
so something that came to me was the forest tension zones.
So tension zone being geographic area
that marks a change from one type of vegetation to another.
The hardwoods transitioning to softwoods.
Northern hardwoods into broadleaf deciduous.
These kind of transitions zones
they're really interesting in forest dynamics.
So, we're talking about mortality, ingrowth, regeneration,
species composition, there's any number
of things that I really wanna look
within these kind of tensions zones,
as well as primarily incorporating a comparative tool.
So not a comparative tool, but a comparison
between the NEFIN data and the FIA data.
So the enhanced set where it's FIA
plus NEFIN versus just FIA, it kind of gives kind
of some statistical evaluation
of these datasets, with these questions.
I'm pretty sure I'm kind of probably running close
to time here, but I really I'm here trying to
champion the NEFIN project itself.
If you or anyone you know has access to data
you believe would be worthwhile
for this project to incorporate,
we're really open to that idea,
we wanna try to get as much data
as possible into this kind of this dataset,
so we can leverage it, and make it open to the public.
So if you have any questions,
or wanna contact me about those data
you might have access to, please contact me,
my email is right below,
and I believe it's time for questions.
- There's a question, in the chat,
from Jen Pontius asking what type of QA, QC goes
into evaluating which datasets to incorporate?
- I trying to find that, and by QA, QC,
what do you have any?
- [Jennifer] Yeah, I guess, Soren,
I'm just looking for a little more detail on how we know
whether or not it's worth bringing somebody's inventory data
into the database, what if it's a citizen science data, what
if it's a high school class that's collected,
data from behind their school?
Just curious if, how much thought has been
put into that yet?
- Yeah. so I was not really a part of
that initial effort, from what I understand, a big part
about this is that it's Continuous Forest Inventory,
so an inventory that's repetitive,
so you take a plot in a forest and
you measure that same point over and over.
That's fundamentally like a really necessary thing
for this to be incorporated because it has to be a CFI.
From my understanding, other aspects, citizens,
citizen science data is always extremely valuable,
but I would not be the first person to really say
whether or not those data can truly be incorporated.
- And we have a question from Charles Cogbill,
the tension zone diagram was for pre settlement period.
Are you interested in seeing
if this will change with modern data?
- Yes, yes I am,
so that Harvard paper, that was extremely influential
in me being a traditionally trained
surveyor looking at witness trees that was based
on witness trees, which is amazing, really wonderful work.
It's just that kind of work is really amazing
and so I am interested to see
whether or not how that's changed,
how that shifted, with modern data,
with after pre-settlement, leveraging those kind of data
sources, are really interesting, that is, that
I just love that paper,
I could talk about that forever, but yes, no
I am definitely interested to see how over time
the general trends and forest composition,
how, I'm really interested in leveraging these kind
of data over long periods of time.
So yes, I would be interested
in looking at how modern data has influenced
or can be compared to pre-settlement forests.
- And Jerry Carlson asks,
are you considering private land security
from remote sensing data of land use?
- Yes, so that was, I think one
of the biggest barriers to entry
for the private corporations or entities,
they go out and they wanna make sure that their data is
and the plot integrity is also extremely important.
So location much like FIA is I don't think is
going to be really a widely available for plot location,
but that's something that's kind of,
above where I am in this project, but no security
for landowners is being taken to consideration
especially private landowners, and all of these datasets
before incorporated, go through a process
where we're talking with the people who own
that data, who have control of that data
and so that we're not sharing anything that they
don't feel to be beyond what they want.