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What I want to do is give you a snapshot of some of the kinds
of data that are coming out now on monitoring effectiveness
for restoration projects, and also give you an idea of what some
of the concerns are in terms of things on the horizon
that we're going to have to contend with at a variety
of levels, both, I think, in terms of what's working
and what's not, but also legal issues.
So, there's lots of projects going on now.
Lots of stream restoration projects,
lots of wetland restoration projects.
In terms of ways that they have been monitored, historically,
they've been done by, for example, tracking miles
of riparian zones replanted.
In many instances, particularly streams,
it has been visual assessment,
sometimes just photographic pre and post.
And then more recently physical measurements, often
which are only one time measurements.
So what I want to do is talk briefly about three things.
Most of my time I'll spend on the first one
and that is what kind of data are we getting now in terms
of monitoring effectiveness and what kinds
of approaches are being used.
Then I'm going to move into this issue of what are the concerns
on the horizon and it turns out that one
of the biggest concerns is getting at
distinguishing structural changes in an ecosystem
from functional changes.
And then the last is, I'm going to talk just briefly
about what Lisa [Wainger] and I are doing in terms of trying
to put together the current knowledge that's in the peer-reviewed
literature, or literature that's fairly well
validated, that perhaps could lead
to some specific recommendations on what we should be monitoring.
And that project is not completed yet.
So you'll just hear a little bit
about on how we are approaching that.
Now in terms of rigorous studies,
what I mean by that specifically is
that they have several characteristics;
one is that they're quantitative,
two is that they have either a control site that's being looked
at comparing the restoration site to, or there's pre
and post restoration data.
In an ideal world you have both, you have pre data and post data
on the restored site as well as either a degraded, sort
of negative control site that hasn't been altered or one
that is considered a desirable state, a least-disturbed site,
maybe a forested site, those are few and far between now.
Here's an example of some good quantitative data, this is work
that Scott Stranko and myself
and others have been putting together,
looking throughout Maryland at biological attributes
in streams, urban streams, that have been restored,
those are the dark triangles versus the open ones,
and how they compare, this is an ordination plot.
So they're clustering differently in those streams
in terms of their biological components, biodiversity
and so forth, from streams that are degraded and also
from streams that are restored.
So that would be sort of the first level.
But it's clearly showing you
that the restored streams aren't clustering
with the reference sites.
Here's some work from Sonja Jaehnig in Germany
who looked at 26 restoration projects,
pre and post restoration.
If the dots are below the line it means
that the site actually was performing more poorly
after the restoration.
If it's above the line that means things looked better.
Along this x-axis is how the managers
of the projects ranked the projects.
So if they are at this [right] end, they were ranked largely successful.
Then she did assessments on-site at the projects
and the colors indicate the outcome of that.
If it's red and yellow it means actual field assessments
of the health of the system were poor or bad.
So what you can see is there is a disparity between sort
of subjective rankings of the site, how they're doing
and what the actual outcomes are.
And there's a pretty even spread in terms of some projects seem
to be causing more harm than good, although,
because these aren't dated in terms on how long they've been
in the ground, we have to be careful
with making a statement like that.
It's normal for some disturbance
to occur immediately post project.
Here's another example of a quantitative approach to figure
out what's working and what's not.
This is a synthesis project where I looked at data
in the published literature and I found 78 independent stream
and river restoration projects primarily in the U.S.,
Europe and Australia, and of those, these are ones
where there was statistical analysis, either pre and post,
or restored versus some control site.
Out of 78, only two had significant increases
in native biodiversity.
The most common metric for stream restoration--
I'm obviously emphasizing that more because it's my area--
is biodiversity; historically that's been what people have
looked at so there's more data on that.
These are just examples of a couple of the studies
where you see this is number of taxa is really no
different from the disturbed
versus the restored and the reference.
That one is in Sweden, this is in Indiana,
you see the lines aren't any different over time
between restored and reference sites.
Now, the best scenario is when we have quantitative data
that is done over a long period of time.
I'm going to give you an example,
this is primarily Solange Filoso's work, one
of my colleagues
at CBL (Chesapeake Biological Lab). Unfortunately we don't have pre-data
but we are preparing to do a new set of studies where we're going
to have pre and post over time.
The design for this was we were interested in asking
if stream restoration, if the effectiveness
in reducing the downstream transport of sediments
and nutrients differed between headwater channels and ones
at the tidal boundaries.
So the restoration projects were at different sites
within the watershed.
Now, what we did with this is a rigorous budget for nitrogen
and for sediments, where we measured inputs going
into the stream reach that was restored,
compared to what is coming
out at the bottom of the restored reach.
So in the tidal boundaries stream this is literally
emptying into tidal waters.
This was done for three years.
We have sampling throughout the year, every two weeks, and,
then, during storm events, very, very frequently.
And that's the kind of thing you have to do if you really want
to know if a project is resulting in a net reduction
in the movement of sediments and nutrients.
If you skip seasons you don't know if there's a massive efflux
of material out during that single season.
If you don't get storm events,
obviously you're missing a big part of the picture.
What has made this really tricky and has stimulated the next set
of projects is, if there's a steep slope at all, particularly
in these upper channels, you get significant inputs of water
and nutrients, potentially, from the groundwater and then
from little lateral surface flows along the restored reach.
You have to account for that and that's very hard
to do, it's hard to measure.
It's easier to measure groundwater inputs,
because we can use a conservative tracer,
than it is to measure the surface lateral inputs.
Here's some results from some
of the streams we have been looking at;
this is just coming out.
So these are the upland streams, these are the lowlands streams;
these are all coastal plain streams in Anne Arundel County.
What you see is this is a net export, so this is taken
over a three-year period.
This is the low flow conditions.
I'm not going to show you the storm flows
but I could show you that.
What you see is that during low flows we have very little
evidence of any retention in the streams that are in the uplands.
These numbers are actually below zero indicating,
suggesting they're actually exporting more.
In fact these are not statistically significant
from zero.
For the lowland streams right
at the tidal boundary we actually have evidence that some
of these are retaining nutrients.
This is just the nutrient data,
we also have sediment data we're working up right now.
The variability here and here was too high
and these are negative controls, so these are degraded controls.
Just an example that this kind of rigorous work,
I'm just giving you one slide out of a huge study,
this gives you another example of the kinds
of the interesting things that can come out of work like this.
We found that the form
of the nitrogen leaving the restored sites was often very
different than the form coming in.
So, for example, in this case, when you look at what's coming
into the restored reach at Howard's Branch,
we have a lot particulate nitrogen.
When you look at what's going out,
there's been a huge reduction in particulate nitrogen.
Some of the streams we looked at, you get a lot
of inorganic nitrogen coming in, in the form of nitrate,
and a lot of organic nitrogen going out.
What this tells you is a couple of things, one,
if you don't measure all the species or
at least total particulate and total dissolved,
you really don't know what's going on in the system
and if it's retaining significant amounts of nitrogen.
Okay, what's coming on the horizon, so now
I'm sort of to the second part and that is that we know a lot
of projects could have been implemented we're wondering,
are they really working.
And by working I mean,
if we look at the actual functionality,
so the last study I showed you was, it was literally looking
at nitrogen reduction and sediment reduction.
Here's an example from a wetland study and now these are coming out,
there's one for Florida, there's three or four
that have evaluated the ecological outcomes
of created wetlands, most of them done
through mitigation projects.
This one looked at to what extent did the projects
that were done in the state of California comply
with the mitigation requirements,
and compliance was actually very high.
But when they went out, when Rich Ambrose and colleagues went
out to the sites and actually did measurements in the field,
what you see is that most of the projects,
about 80% were suboptimal to poor ecological conditions.
What I'm trying to emphasize here is this is sort
of a look-see kind of approach.
At best it would look at structural measures;
like is there some water present there part of the year?
This is where they're actually saying, is it doing the kinds
of things it is supposed to be doing.
The idea is that there is a difference
between measuring structural attributes
of the system versus functioning.
Functional attributes
for monitoring really refers directly to things
that are rates, that are measured over time.
So, it integrates what happening seasonally
and annually, so they're dynamic.
We have had a long history, and it's not unique to the [Chesapeake] Bay,
it's all over the world.
Europe right now, they have a new freshwater framework
directive, they are struggling with the same thing.
We have had a history of measuring things at point
in times; what was the temperature that day?
What's the nutrient level? Doing this seasonally,
you might as well not get any data to be honest with you,
if all you are going to do is go out
and get seasonal measurements of a nutrient and you want to know
if it is retaining nutrients.
You actually have to do it over time and you have
to get measurements that tell you if the process is working.
Now I want to put a caveat in here, you don't have to do this
for every project, I'm not saying that, I know we don't have
enough money, what we need are smart designs,
where we select restoration projects either of a type design
or in different settings,
do a lot of thorough evaluation on those
and don't bother monitoring all the other ones.
So, I'm actually fairly critical
of the way the 2010 monitoring data has been distributed
with small pies, so every project has to be monitored.
Most of them aren't going to be monitored in a way that is going
to provide us a lot of learning kind of information.
What concerns are on horizon?
One of the things that Lisa and I have really been focused
on is that we think, until we have more information, there
needs to be much better attention paid
to targeting and site selection.
We talk a lot about targeting,
we want to in practice, targeting is typically not done.
And, yet, this is from something that Lisa has worked on,
but the idea here is simply that if you look
at restoring a system where it's completely degraded
to being completely healthy, and you think of this as the amount
of work you've done which removed some stress
on the system, that it's not a linear relationship.
That you may not see much change in this system
and the functionality until you reach a certain point
and then eventually it will level off.
She's just trying to make the point that if you consider
where you are on this curve,
you can have a bigger *** for your buck.
So, delta 10, in terms of your effort on the project,
is going to have a much bigger impact here
in the functionality the system than it is here.
This would suggest maybe putting your money
into super-degraded sites, may or may not be good,
you have to think about the setting.
Okay. And, then, to just get towards the end.
In terms of what we're doing
with the NFWF (National Fish and Wildlife Foundation) Project, we know --
I read a book about a year ago called "We Can't Wait On God".
We can't wait on all the science to be done.
We know that.
We have to come up with ideas about what to do.
And, so, we have spent a year or more going
through the literature in detail and trying to ask,
what is the evidence there to support certain types of metrics
for use in monitoring.
And, so, we've done this now for non-tidal wetlands,
tidal wetlands, streams; we've got somebody that is working
out at Virginia Tech on the agricultural BMP (Best Management Practice) end
and also somebody working, Allen Davis on the stormwater end.
And it's been a very extensive process
where we have identified structural metrics and ask,
are there scientific studies to show
that those structural metrics people are using actually
represent functionality.
And then we've been looking at whether or not
in what settings quantitative metrics are appropriate to use
or you can use qualitative metrics.
And just to give you a sense of some of the early findings
or conclusions we've been reaching from some
of our analyses is that it's pretty clear
that restoring isolated structural components doesn't
generate the desired functions.
It's easier to understand this in streams
because we've had two decades of work that has been focused
on restoring channel shape and structural attributes
and that has largely not lead to functional increases.
Instantaneous measurements
of dynamic processes are typically un-informing.
Going out in one day and measuring discharge,
or four times a year, it just doesn't really tell you
that much.
I know it's hard to give up monitoring, but it's true,
if you don't do enough of it it's really not worth anything.
Same thing if you have a highly spatially variable system
and you are only looking at one area.
So we've seen studies who have made conclusions
about nitrogen reduction benefits
in a stream restoration project,
but have only measured de-nitrification rates
in one bank in that stream.
It is so variable, you really have to do this
over much broader spatial areas.
It turns out that bio-assessment approaches often times are not
particularly useful.
And the reason is, they will tell you,
so if you have the right bugs in a stream
or you have the right plants in a wetland,
it may tell you something about whether
you are at the point you want to be or not,
but you're usually not, and it doesn't tell you anything
about why you're not there.
There are other methods that you can put your money
into that will tell you more than knowing
that you have a depauperate biological community.
That's not a popular message
that we've distributed but it's really true.
And, the last one, I think,
is that species are not necessarily a demonstration
of what's going on at the population level.
And, the example I like to use here is marine protected areas,
we are seeing a lot of studies that say,
we have more fish here, we have more fish here.
Well it may simply be an aggregation effect.
Until you have information on productivity of that fishery,
you really don't know if that MPA (marine protected area) is having the kind
of benefit that you want.
Oh, and then there's the last one,
just that metrics can provide both positive
and negative outcomes early on in the project,
which I already mentioned earlier.
Okay.