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Going to talk about my

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master's thesis work which

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was carbon
sequestration potential

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falling riparian
restoration.

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And I worked within

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the Oregon State
University system.

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And this work was
funded partially

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BY clean water services
and Oregon State.

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So for this project,

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we had a couple of

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goals that we
wanted to fulfill

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and that was to
provide baseline data

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before and after
restoration on

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the soil carbon
percentages and

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the carbon stocks and

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also the fungal
communities.

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And this is an order
to demonstrate

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restorations impact on
carbon sequestration.

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So to do that,

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we add three objectives.

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The first was to quantify

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carbon percentage
and determine

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whether it changed
over time.

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And with this, we kind of

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trading time for space.

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So instead of monitoring

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one site for 14 years,

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let's say we had
multiple sites at

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different a sense
restoration.

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And when I say Asians
restoration me to

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just time after
Restoration occurred.

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And secondly, we wanted

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to measure soil
and physical soil,

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physical and
chemical properties

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such as soil composition.

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But the percentage of
plant coverage and

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nutrient content to
really see if there

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are any kind of
interactions or

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correlations that we could

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look at with those things.

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And the nutrients
we really

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focused on where nitrogen,

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potassium, and phosphorus,
that classic NPK.

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We also looked at soil pH

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and we had to look at

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bulk density in order

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to quantify carbon stocks.

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So all these
things were really

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important in
reaching our goals.

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Lastly, we look to

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identify microarrays
or guilds.

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And when I say guilds,
it's just like

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the functional
group that act as

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mycorrhiza that form

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those symbiotic
relationships

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between the fungi
and the plants.

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And we were looking for
correlations between

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carbon and these
specific fungi.

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So to do this,

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and winter of 2020,

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we went out to

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multiple clean water
service work areas

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or rest restored areas.

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We had four different
year periods

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where we at year 0,

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meaning no
restoration at how

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to occur now is
essentially our control.

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We had Year 2,

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which was two years
since restoration,

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year for four years since

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restoration and here 14.

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And we took for
soil cores,

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three of which
were used for

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the soil chemical
analysis,

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and one that was used
for the DNA analysis.

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And once the
course were taken,

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they were brought
back to the lab

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to air dry and process.

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And since this was during
the heart of COVID?

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Well, somewhat

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We couldn't I
couldn't personally

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work up the soil samples

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because I wasn't really
allowed in any labs.

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So I had to submit them to

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OSU central
Analytical Lab and

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the Center for Genomics
and buyout computing.

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And to quickly go
over the analysis,

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this is kind of
an example of

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the mean carbon
percentage that we

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found in our study sites.

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So this was with area

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two or a year 0
as control here,

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the carbon percentage
on the left-hand side

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and the year since
restoration on the bottom.

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And the black represents

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the overall additive
carbon percentage

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found in these samples.

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And then the blue
is the blue,

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the green and
the orange are

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the different
depth ranges.

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So blue is like the
first top layer,

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the 0 to ten
centimeters grain,

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10 to 20 centimeters,

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and then the
deepest soil layer,

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the 20 to 30 centimeters.

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And what we kind of,

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and this is just somewhat

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the raw data
just averaged.

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And we see this
initial bump and

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carbon percentage
that seems a

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plateau somewhat
over time.

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And we use linear
mean models

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to really try
to understand

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whether we actually,

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this bump we see and
this increase was

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really happening
and what was

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the extent of
that increase?

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And then for the fungal

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community proportions,

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we did odds ratios
of fungal presence.

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So what are the
odds that we'll see

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more fungal species
after restoration?

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And this graphic,
even though it's

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not representing micro
arousal fungal guilds,

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it really kind of
represents what we saw

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across all the
different gills

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I tried to look at.

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And we have the
odds ratio on

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the left-hand side and

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the different
year comparisons

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compared to year 0.

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On the bottom,
the brown dot

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is equating to

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the mean odd ratio
more or less.

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And then we have these
really big error bars.

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And the red dotted line

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means there's
no difference.

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So if our error bars
are intercepting that,

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then we didn't
actually observe

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a statistically
relevant difference in

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the number of species

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observed during
that time period.

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So.

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Pretty apparent
that we really

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only saw a difference

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in number of
fungal species

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from year 0 to year 2.

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So I really tried to

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condense down my results,

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discussion and
the conclusion.

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And for the
soil chemistry,

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which is
particularly focused

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on carbon sequestration,

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we would expect to see

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the percentage of
carbon to nearly

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double after 14 years
of post restoration,

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the toilets and
River watershed.

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And to kind of

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quantify this in the
carbon stock terms.

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And this is also
to understand if

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we kept everything
else at an average.

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So if we had 3.5% average

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across all three of

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those different
soil measurements

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that we took.

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And it doubled to 7%.

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And also the bulk
density stayed the same.

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The overall
summation would be,

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we sequestered
363 mega tons

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of carbon per
hectare acre.

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So we can conclude

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that riparian
restoration efforts,

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how many added benefits,

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which include increase
soil carbon percentage

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and stocks over time.

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But we would probably
want to prove that

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by surveying a single
area over time.

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And then our results for

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the fungal communities is

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that we estimate the
proportion of all fungi,

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fungal and my
parietal species

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to increase by 1.3515

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times respectively in year

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two when compare to Davis

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tool and Davis tools,

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the project area that
represents year 0.

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And we really didn't
see a difference,

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like I said in that slide

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with all the fungal
species over time.

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But this doesn't
really match

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the literature
that I read about.

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And when we look at
micro rivals species,

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they tend to hold
onto a lot of carbon

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because they create these

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really long that works.

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So I think that leads
into our limitations.

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And there is a really
high amount of

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unaccounted for
variability

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in the fungal models.

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We weren't able to
split the deaths and

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different fungal
communities live

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it even different
depth layers,

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as small as ten
centimeters.

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So I think that could
have helped clear up

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maybe this Week number
of species proportion.

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We also could have looked

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at it a different way of

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analyzing the data instead

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of just number of species.

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It could have been more of

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a community approach
because yeah,

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we had to use
presence or absence.

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And this was kind
of the last thing I

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was able to do
with my thesis.

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So I think overall,

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our next steps would be to

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resample and
sequence maybe the

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whole microbial
community and

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not just fine dry because

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community composition
could really lead

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to increased carbon
sequestration.

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And the second thing

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that I was alluding
to earlier,

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which would be
to sample a site

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at an established
plot over time.

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Because with all these
inferences that we're

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making in this study,
It's all correlative.

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And otherwise we could
do causal inference,

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which would be
more powerful.

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And we're gonna
get to questions.

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But I also want to shop

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this picture because
this is what I THE

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picture of one of the
days I laughed at like

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05:00 AM to go

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sample and it was
just gorgeous.

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This is Oak Ridge,
Oregon actually.

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And that's DOP this flag

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right across the
street from my house.

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So thank you.